Metal 3D Printing - Current State and Future Potential
You may have heard the term 'metal 3D printing' being thrown around in recent years. Since its inception, the concept has proven its worth in the development of both prototypes and industrial end-use parts and is slowly making its way into regulated industries such as aerospace, medical, and defense. The reality is that metal 3D printing is a very broad concept. There is no single additive manufacturing technology that metal 3D printing boils down to, rather a collection of sub-technologies that - you guessed it - print with metals. There are now a whole host of companies that base their entire business models on metal 3D printing, whether it be through manufacturing 3D printers, developing novel 3D printing alloys, or providing metal 3D printing services. Powder bed fusion Without a doubt, the most popular and widely adopted metal 3D printing process is powder bed fusion. PBF makes use of either a laser beam or an electron beam to melt metal powder in a powder bed, fusing consecutive layers on top of each other to build 3D parts. With companies such as EOS, Farsoon, and SLM Solutions pouring so many resources into R&D, PBF is one of the more advanced 3D printing technologies out there and has its uses in just about every industry that benefits from metal components. Earlier this year, Ford Motor Company and EOS collaborated to combat alloy wheel theft through the development of unique 3D printed locking wheel nuts. which can not be loosened with standard tools. For context, locking wheel nuts are used to secure the wheels of a vehicle, which can be unscrewed with the key supplied with them. Third-party removal tools for these nuts have become more accessible as a result of cars being bought and sold without passing down the original components. Unfortunately, alloy wheels have become a target for thieves as they can use these tools to loosen and remove a car’s wheels, which are sometimes valued at around $2600. By designing the nut and key in a personalized manner using 3D printing, Ford aimed to provide a system that can not be removed using standard equipment. The nut and key are designed as one piece, then 3D printed using acid and corrosion-resistant stainless steel on an EOS M 290 metal DMLS 3D printer. Elsewhere, in the aviation sector, aerospace supplier Premium AEROTEC, together with GE Additive, very recently announced that it had reached a new productivity milestone in the series production of titanium parts via PBF. Just last year, the partners were able to qualify multi-laser titanium builds on a GE Additive Concept Laser M2 system, and have since been working on increasing the machine’s throughput. The flagship system features two lasers and a build volume measuring 250 x 250 x 350mm, as well as a 3D optic with variable spot diameter. The current generation of the machine, series 5, was designed with regulated industries in mind and claims to deliver the accuracy, repeatability, and safety necessary to produce such parts. These parts include fuel nozzles, engine casing components, and a whole host of other functional prototypes. Directed energy deposition One of the other major metal 3D printing technologies is directed energy deposition. DED, although not as popular as PBF, is capable of producing highly dense parts at previously unseen throughputs, with some machines being able to print several kg of metal every hour. The process involves depositing powder or metal at the tip of a nozzle, where it intersects with either a laser, electron beam, or plasma arc that melts and fuses it to the plate below. DED is very commonly used to repair parts and add to already existing components. As such, it’s used heavily in MRO applications in the aerospace industry. Optomec, a leader in DED 3D printing systems, recently received a $1M contract from the U.S. Air Force to deliver a high-volume DED machine to be used for the refurbishment of titanium turbine engine components. The U.S.-based company was tasked with manufacturing the machine, which is set to feature a range of state-of-the-art capabilities, including an automation system for batch processing, an oxygen-free controlled atmosphere, and an adaptive vision system. The machine will be installed at Tinker Air Force Base in Oklahoma City. The automated additive repair system designed by Optomec will be able to process tens of thousands of repairs each year, initially focusing on tip refurbishment for the U.S. Air Force’s turbine blades. The company will also assist the Air Force in developing optimal process parameters for a range of target repairs - a prime application of the technology. Metal 3D printing: from novelty to common-place Metal 3D printing is here and it's here to stay. A couple of decades ago, the technology may very have been a gimmicky novelty, but it has since found its uses in advanced industries such as aerospace and automotive. The ability to produce high strength parts with excellent thermal and chemical properties is a very powerful tool, all wrapped up in the design freedom wrapper offered by 3D printing. While the technology is currently limited in its throughput, its effectiveness in functional prototyping is near-unmatched. The next ten years will undoubtedly yield a plethora of technological advancements that will put it on a more level playing field with conventional manufacturing.
With ongoing technological advancements in metal and polymer 3D printing systems, regulated industries have seen an increase in additive manufacturing adoption rates. One such sector is aviation, where a few major players take the lion’s share of the market. Companies like GE, Boeing, and Airbus have all had their fair share of run-ins with 3D printing, but what kinds of components are actually being fabricated? The Federal Aviation Administration When it comes to flight-critical components or components where performance is crucial if the aircraft is to operate reliably, they must receive FAA certification before they are allowed to be installed. One of the first 3D printed components to receive the certification was the LEAP fuel nozzle, which is featured in GE's GE9X jet engine. The famed engine now contains over 300 individual 3D printed parts, including temperature sensors and fuel mixers, and larger parts, like heat exchangers, separators, and foot-long low-pressure turbine blades - all serving to save weight (and fuel) via geometric optimization. The engine recently completed its first test flight on a Boeing 777x airliner, which is the world’s largest twin-engine jetliner and passenger plane. Two previous attempts at getting the 777X airborne were made, however, the tests were postponed due to high winds. In January of 2020, however, the airplane took off from Paine Field in Everett, WA. Honeywell Aerospace, the aerospace division of conglomerate Honeywell, also recently received an FAA certification for one such 3D printed component. The part in question – a #4/5 bearing housing – is a key structural component of the ATF3-6 turbofan engine found in the Dassault Falcon 20G maritime patrol aircraft. The part is already in production and has been installed in an operational Falcon unit, with dozens more expected to be printed by the end of the year. Over in academia, Auburn University’s National Center for Additive Manufacturing Excellence (NCAME) recently received a $3M grant from the FAA, which it will use to commence a two-year research project to improve air travel. Specifically, the NCAME engineers will delve deeper into metal 3D printing and its materials to fine-tune the parameters required to print end-use components for commercial aircraft. Under the hood, the Auburn project is ultimately intended to solve a core issue in additive manufacturing, which is variability in performance. Variability results in identical parts 3D printed on different machines having discrepancies in their mechanical properties. According to the NCAME, there is also a lack of understanding when it comes to the microstructures of 3D printed metal parts, and their subsequent effects on fatigue and fracture resistance. This makes it very difficult to define specifications and standards in the industry – especially with tightly controlled parts for sectors such as aviation. 3D printing polymers for aviation While metal components certainly dominate the aviation industry, 3D printed or otherwise, there are of course polymer parts making their way into the sector too. Boeing very recently qualified 3D printer OEM Stratasys' Antero 800NA thermoplastic filament for flight parts. As such, the PEKK-based polymer can now be used to 3D print end-use components aboard Boeing's planes. Antero 800NA is a high-performance PEKK-based polymer designed specifically for Stratasys’s industrial-grade FDM 3D printers, such as the F900 and the Fortus 450mc. It is also available as a material option for customers who opt to use the company’s on-demand manufacturing service, Stratasys Direct Manufacturing. The other filament in the Antero family is 840CN03, a close relative with electrostatic dissipation qualities. With a tensile strength of 93MPa and an elongation at break of 6%, 800NA aims to combine the excellent mechanical and low outgassing properties of PEKK with the design freedom of FDM 3D printing. The high strength, heat and chemical resistance, toughness, and wear resistance of the filament make it an excellent jack-of-all-trades alternative to metals such as aluminum for aerospace applications. Elsewhere, researchers from the University of Sheffield’s Advanced Manufacturing Research Centre (AMRC) have previously used 3D printing to aid in a large-scale manufacturing project for Airbus. The AMRC engineers were commissioned to work on a high-precision drilling operation involving carbon fiber, aluminum, and titanium aerospace parts. With aerospace-grade tolerance requirements, it was crucial that cross-contamination did not occur between any holes produced during the project. The team realized that they needed drilling caps to cover up the holes, but couldn’t opt for traditional machining or injection molding as this would cause weeks of delays. With only 10 days left to produce 500 caps, the engineers turned to Formlabs’ 3D printing technology and cut the lead time down by weeks to just two days, meaning the project remained on schedule and within budget. The next steps for aviation Much like medical and the wider aerospace industry, the aviation sector will always have stringent quality requirements. Seeing as 3D printing is in its relative infancy, this is the major hurdle that still needs to be jumped. While the field as a whole is rapidly warming up to additive manufacturing technology, there still needs to be a heavy push towards the development of standards and widespread practices before 3D printing can begin to transition from novelty to the norm.
Genome editing (GE) has revolutionized biological research through its ability to precisely edit the complete set of genes or genetic material present in a cell of living organisms, including humans, plants, animals, and microbes. In recent years, various GE tools have been explored to edit both simple and complex genomes. It can be used either to add desirable or remove undesirable alleles simultaneously in a single event. In less than a few years, the gene-editing technology Clustered Regularly Interspaced Short Palindromic Repeats commonly known as known CRISPR has revolutionized modern biology's face and generated excitement for new and improved gene therapies. It is dramatically more manageable, cheaper, and more versatile than previous technologies and enables scientists to alter genomes practically at will. It's not perfect, but it has already been used to correct genetic diseases in humans and animals. The problem with this approach is that it only works for certain types of DNA. For example, if you had a disease called "Leber's Hereditary Optic Neuropathy" and your eyesight was starting to go, you could theoretically use CRISPR to correct the defective gene that causes it, but you'd still get the other problems caused by the mutation you got first (in this case, bad vision). This is one of the limitations. With other diseases, the situation is slightly better, but not much. Editing out diseases is possible, but it's still in the very early testing stages. The other big limitation of CRISPR is that it's hard to ensure a precise cut. This means if multiple possible genes could be cut, many of the edited cells may have the wrong change, which leads to messed up cells and tissues. Usually, when referring to CRISPR, it means Crispr/Cas9 - a riboprotein complex composed of a short strand of RNA and an efficient DNA-cutting enzyme. It has high efficiency, accuracy, and ease of use. Newly emerging CRISPR/Cas systems like spCas9-NG, base editing, xCas9, Cpf1, Cas13, and Cas14 are now being used for GE. So, the question facing researchers using these technologies is: “what is going to happen when the scientist makes the change? Sure, he will get the expected change but what else, unexpected, is going to happen?” Scientists are looking at ways to answer this tricky question and are experimenting with Artificial Intelligence. Microsoft has built a machine learning tool to help in CRISPR/Cas9 design and has developed two predictive modeling approaches, Azimuth and Elevation, to tackle the problems of on-target and off-target activity prediction. Using an in-depth learning approach, the tool can discover the correlation between the editing applied to the genome and the consequences at a global scale, basically linking the genotype with the phenotype. In the future, this may provide a crucial tool to fix problems appearing at the phenotype level by tweaking with the genome (it will also show that some issues do not have a solution with this approach, since fixing something -like changing the number of fingers in a hand- will ruin something else). Many startups are making their presence felt in the arena of genome engineering. Inscripta launched the world’s first benchtop platform for digital genome engineering. They have an enzyme engineering program that allows their customers to create their own customized gene-editing applications. Inscripta has also created a family of CRISPR enzymes (MADzymes), which have innovative features, said to increase the speed and efficiency of precision genome editing. Inari Agriculture is building the world's first ‘Seed Foundry’ through which they are reintroducing nature's genetic diversity and working to address some of today's significant challenges, including climate change. They’re focusing on using CRISPR to manage specific gene expressions in plants. They are also developing customized seeds that significantly reduce the land, water, and other natural resources required to produce food and feed. These CRISPR-edited seeds are planting a sustainable future for the agricultural industry. Synthego, the genome engineering company, is designing new foundational technology for standardized precision and control of CRISPR-based gene editing inside cells. They have come up with a CRISPR Design Tool, which uses several built-in algorithms to identify guide sequences targeting a gene, and simplifies gRNA design using light. They’re also developing a Gene knockout kit v2 that’s designed to guarantee a gene knockout, saving scientists from trial and error cycles in their CRISPR experiments. CRISPRomics is an industrialized discovery engine of KSQ Therapeutics that utilizes a suite of proprietary CRISPR/Cas9 tools to generate disease-specific insights for every human gene with improved precision and at an unprecedented scale. They have evolved this engine into multiple distinct platforms to identify and genetically validate optimal novel targets for drug discovery. CRISPRomics has broad utility across numerous therapeutic areas, and the company is currently deploying this approach in oncology, immuno-oncology, autoimmune disease, and select rare diseases. eGenesis are leaders in gene editing and genome engineering and are uniquely positioned to address the organ crisis with their multiplexed gene-editing platform. They use rapid and automated DNA sequencing to perform microbial fingerprinting and have been awarded the first US Patent for their fast DNA sequencing platform to control hospital-acquired infections. eGenesis has partnered with Quihan Bio (China) in using CRISPR to create the most extensively genetically engineered pigs, whose tissues have all the features necessary for being transplanted into humans. Verve Therapeutics, a biotech company pioneering gene-editing medicines to treat cardiovascular disease, is developing one-time gene editing medicines to safely and precisely turn off a gene in the liver to permanently lower LDL cholesterol or triglyceride levels and thereby treat adults with coronary heart disease, the leading cause of death worldwide. They target base editing to knock out PCSK9 or ANGPTL3 in the liver and substantially reduce blood levels of LDL cholesterol or triglycerides. Coronary heart disease occurs when cholesterol-laden plaque builds up in the heart's arteries, which can restrict blood flow and lead to a heart attack. Tango Therapeutics is leveraging the principle of synthetic lethality to develop medicines that take direct aim at specific tumors. Using an approach that starts and ends with patients, they’re expanding the reach of genetically targeted therapies. They have built a target discovery platform that uses CRISPR to find vulnerabilities in specific cancers. Tango Therapeutics collaborated with Gilead Sciences in 2018 to discover, develop, and commercialize a pipeline of innovative targeted immuno-oncology therapies. Beyond CRISPR A mini-me: The components of CRISPR–Cas9 system - Cas9 and a strand of RNA- are too large to stuff into the virus's genome, most commonly used in gene therapy to shuttle foreign genetic material into human cells. A solution comes in the form of a mini-Cas9, which was plucked from the bacterium Staphylococcus aureus. It’s small enough to squeeze into the virus used in one of the gene therapies currently on the market. Two groups used the mini-me Cas9 in mice to correct the gene responsible for Duchenne muscular dystrophy. Expanded reach: Cas9 will not cut everywhere it’s directed to. A specific DNA sequence must be nearby for that to happen. This demand is easily met in many genomes but can be a painful limitation for some experiments. It has been surpassed by one such enzyme, called Cpf1, smaller than Cas9, it has different sequence requirements and is highly specific. Another enzyme, called C2c2, targets RNA rather than DNA - a feature that holds the potential for studying RNA and combating viruses with RNA genomes. True editors: Many labs use CRISPR–Cas9 only to delete sections in a gene, thereby abolishing its function. Those who want to swap one sequence with another face a more difficult task. When Cas9 cuts DNA, the cell often makes mistakes as it stitches together the broken ends. This creates the deletions that many researchers desire. But researchers who want to rewrite a DNA sequence rely on a different repair pathway that can insert a new sequence — a process that occurs at a much lower frequency than the error-prone stitching. Researchers announced that they had disabled Cas9 and tethered to it an enzyme that converts one DNA letter to another. The disabled Cas9 still targeted the sequence dictated by its guide RNA but could not cut: instead, the attached enzyme switched the DNA letters, ultimately yielding a T where once there was a C. Pursuing Argonautes: Researchers claimed that they could use a protein called NgAgo to slice DNA at a predetermined site without needing a guide RNA or a specific neighboring genome sequence. Instead, the protein — which is made by a bacterium — is programmed using a short DNA sequence that corresponds to the target area. What’s next? Genome-editing technology applies for the good of humankind and the planet. The genome-editing wish list includes better methods for multiplexing-editing more than one gene at a time. Given its popularity and availability, CRISPR dominates genome-editing predictions. CRISPR-based systems will continue to improve incrementally. CRISPR is already very powerful, and so many people are working on it and other genome-editing systems that they'll inevitably continue to improve. The full realization of the potential of CRISPR/Cas9 approaches will require addressing many challenges. It is somewhat clunky, unreliable, and a bit dangerous too. It can't bind to just any place in the genome. It sometimes cuts in the wrong places, and it has no off-switch. Cas9 is large, so its gene is challenging to deliver to cells via vectors such as adeno-associated viruses commonly used in gene therapy. Also, scientists worry about off-target effects. This remains the most significant obstacle for CRISPR/Cas9 use regarding gene cargo delivery systems, and an all-purpose delivery method has yet to emerge. Instead, multiple ways are seen for delivering CRISPR to cells. Every technique has both advantages and disadvantages, and some can be quite specific or ill-suited to certain types of delivery.
AI in Psychiatry - Detecting Mental Illness Using AI
Advancement in artificial intelligence has designed smart algorithms that support clinicians with early detection and diagnostics of various types of mental health issues. These algorithms can analyze data much faster than humans, suggest possible treatments, monitor a patient's progress, and alert human professionals to any concerns. Neuroscientists and clinicians around the world are using machine learning to identify mental health biomarkers, develop treatment plans, and predict crises. Machine learning algorithms could help determine key behavioral biomarkers to aid mental health professionals in deciding if a patient is at risk of developing a particular mental health disorder. Additionally, the algorithms may also assist in tracking the effectiveness of a treatment plan. Machine learning algorithms can also take in a combination of self-provided data and passive data from smartphones/social media to determine whether an episode of mental disorder is imminent for a patient. There are key indicators as to whether an episode is imminent. These crises can be predicted accurately if we can detect a pattern of stress, isolation, or exposure to triggers. Startups such as Clarigent Health, based in the US, develop a platform based on AI and machine learning (ML) to detect mental health conditions early-on. The platform acts as a clinical decision support tool providing medical staff with insights into suicide ideation and other mental health issues. Similarly, 7Cups offers on-demand coaching & real-time support service with licensed mental health counselors & coaches. The counselors & coaches help individuals in their personal and professional development by introducing them to meditation and breathwork techniques. Consultations are available around the clock on an anonymous basis, thanks to the service's mobile nature. To assist people with depression and bipolar disorders, a German startup Moodpath offers mood tracking services, and guides affected individuals toward recovery faster. As a mental health companion, Moodpath asks questions daily to evaluate a person's wellbeing and screen them for symptoms of depression. The app also periodically generates an electronic document with monitoring results that can be used for consultation with a healthcare professional. It also provides educational videos and psychological exercises to strengthen mental health. Meditopia, a Turkish startup, develops a meditation app to reduce stress, sleep well and find calm for body and mind. The app offers personalized meditation sessions, bedtime stories with various topics to choose from, and music to relax. People suffering from anxiety, depression, and bipolar disorders need continuous monitoring and support tools to help them manage their own emotions and track changes in emotional habits or patterns daily. A USA-based company, Sentio Solutions, builds Feel, an emotion-sensing wristband together with an app that provides real-time monitoring and personalized interventions for individuals with anxiety or depression. Sentio's solution for Augmented Mental Health uses a combination of evidence-based behavioral techniques (Cognitive Behavioral Therapy, Mindfulness, Positive Psychology) and the company's proprietary emotion recognition technology. The human voice can be an indicator of health as well. Spoken communication encodes a wealth of information. Recent research and technology intersected to enable our voice to be one of the most useful biomarkers of health. The use of vocal (voice or speech) and visual (video or image of facial or body behaviors) expression data has gained attention in diagnosing mental health disorders. Besides, thermal images that track persons' breathing patterns were fed to a deep model to estimate the psychological stress level. UK based- BioBeats is enabling individuals to take preventative action against mental Illness. Using wearable sensors coupled with an app and a machine learning system in the cloud to detect, prevent, and treat mental disorders. It aims to allow users to understand how their body and mind respond to stress and how it affects them in their work and personal life. For instance, sentences that don't follow a logical pattern can be an acute symptom in schizophrenia. Shifts in tone or pace can hint at mania or depression, and memory loss can sign both cognitive and mental health problems. AI system can assess the speech samples, compare them to previous models by the same patient and the broader population, and then rate the patient's mental state. Help in Psychiatry Compared to a human psychiatrist or psychologist, the most advantageous features of smart algorithms could be their anonymity and accessibility. For example, many smartphone-based applications have been developed in recent years that can proactively check on patients, be ready to listen and chat anytime, anywhere, and recommend activities that improve the users' wellbeing. Moreover, these applications are usually more affordable than the therapy itself. Thus, also those people could get some help who could otherwise not get any counseling at all. Seattle-based Lyssn uses AI and machine learning to transcribe therapist-patient conversations into text and analyzes the interactions to determine if providers are using evidence-based, best practices in their treatment. The startup announced a new telehealth platform that uses Lyssn's secure video-conferencing system to provide remote mental healthcare. The service works like personal assistants such as Alexa, Siri, and Cortana, listening to conversations and making sense of them. Woebot, a little algorithmic assistant, aims to improve mood. It promises to connect with the user meaningfully, to show bits and pieces of empathy while giving you a chance to talk about your troubles to a virtual robot and have some counseling in return. Pacifica has come up as a tool to boost users' moods through cognitive behavioral therapy. Tools and activities include meditation, relaxation, mood, and health tracking tools. Likewise, Thriveport is a system of applications that helps users alleviate symptoms of mental illness. It also bases the guided activities on cognitive behavioral therapy's achievements to identify and change negative thought patterns over time. The AI-based 'emotionally intelligent' chatbot, Wysa, combines cognitive behavioral therapy techniques, dialectic behavioral therapy with guided meditation, breathing, and yoga. It was developed in collaboration with researchers from Columbia and Cambridge universities and aimed to help users manage their emotions and thoughts. AskAri, an AI Chatbot developed by Albert "Skip" Rizzo at the University of Southern California, teaches students self-care skills and offers mental health support and information to help them engage in campus life. From here, where do we go? The integration of AI has opened up opportunities to provide mental health support that is impossible with traditional in-person therapy. As with physical health, AI will likely overtake humans' accuracy of mental health diagnosis relatively quickly. While there is great promise for using AI to help the current mental health crisis, there are still obstacles to overcome. There are significant privacy concerns and challenges in terms of making people comfortable and willing to accept various levels of being monitored in their day-to-day lives. Besides, there is no regulation for these applications, so it is advised that any app be used in conjunction with a mental health professional. As AI tools are created, there must be protocols to make them safe and effective and are built and trained with a diverse data set, so they aren't biased. We don't see machine learning algorithms and AI bots replacing therapists anytime soon, but they could make them far more effective and increase their reach multi-fold. Most importantly, for millions of people who feel alone and don't have a support system of friends and therapists around them, artificial intelligence may well build resilience, provide support, and save lives.
The power of 3D printing has been felt far and wide in a vast number of sectors in recent years. The field of prosthetics, or limb extensions/replacements, is no exception to this. A traditionally manufactured prosthetic can cost upwards of several thousand dollars and must be highly customized to fit a unique user. There is also the issue of growth, as prosthetics designed for children will be outgrown in a number of months, racking up further costs. The design freedom granted by additive manufacturing has been known to come in very handy for applications such as this, as the technology is not limited by the geometric constraints of a production line and conventional manufacturing methods. Design iterations can be made on the fly, and pivoting mid-product lifecycle doesn’t set the project back all that far. Virtually anyone with a dream and a 3D printer (and some CAD software) can produce their own prosthetics, with basic assemblies costing less than around $100. Of course, for a long-lasting and reliable piece of kit, costs may end up significantly more than this but even higher-end products will benefit from material and time savings. In fact, the concept of 3D printed prosthetics, although niche, makes up large parts of business models for certain specialist companies, and is the topic of extensive research - we'll have a look at a few of these cases shortly. 3D printed prosthetics in the industry Just last year, UNYQ, a San Francisco-based company specializing in 3D printed medical wearables, announced the launch of the UNYQ Socket, the company's very own 3D printed prosthetic leg socket. The UNYQ Socket is one of the various products that the company has since added to its Prosthetics Wear line, intending to eventually provide a complete, 'aesthetically unified' prosthetic leg product by the end of 2021. For context, a prosthetic leg socket is the section of a prosthesis that attaches to the residual limb. The UNYQ Socket has been implemented with various features designed to provide benefits for both the amputee and the clinician that are not present in traditional prosthetic leg sockets. Using 3D printing, the socket is designed to be lightweight, replacing the metal material often found in a traditional prosthetic leg, whilst also improving on the style of existing options. Furthermore, the 3D printed prosthetic leg socket has also been integrated with sensors to record the user's activity, such as the number of steps and potential calories burned, allowing users to keep track of their fitness and exercise. Elsewhere, New Zealand-based medical startup myReflection has previously announced the development of personalized breast prostheses for cancer patients post-mastectomy, using 3D scanning and 3D printed molds. The prostheses are made from a 3D torso scan and are designed with an inner core and an ISO-certified outer silicone, meaning they’re fully compliant with stringent medical regulations. Since similar traditional prostheses don't last all that long, users are often hit with concern when deterioration sets in, as they'll have to pay for the next one out of pocket. The material used by myReflection is reportedly very stable, elastic, and tear-resistant, so it can last around for years and is designed to be loseable and ultimately replaceable. Pediatric prosthetics The world of pediatrics, or child care, is where 3D printed prosthetics really shine. Researchers from the University of Lincoln, UK, have previously developed a prototype for a 3D printed, sensor-operated prosthetic arm designed for children under two-years-old. Dubbed the Soft-Grasp Infant Myoelectric Prosthetic Arm (SIMPA), the prosthetic was created using 3D scanning, additive manufacturing, and an armband-based Surface Electromyography (sEMG) system. What makes the SIMPA special is that it is a myoelectric prosthetic, a type of prosthetic controlled by electrical signals in the muscles, and commonly given to adults but not children due to the difficulty and expenses of down-scaling. This is due to the rate at which a child grows, which calls for the constant replacement of such a device. To add to this, in cases where young children with upper limb amputation have prosthetic devices, the child is prone to develop their own methods of grasping objects which can limit their motor neural skills. The manufacturing technique even has its uses in warzones. Syria Relief, a UK-based charity working in Syria, has previously appealed for the UK’s Department for International Development (DFID) to provide funding for 3D printed prosthetics for children affected by conflict. It is estimated that over 30,000 people have lost limbs in the Syrian conflict, and the average number of people per month receiving a prosthetic limb is 60. For children alone, a traditionally manufactured electronic arm costs an eye-watering £1000 and can take weeks to produce. Syria Relief believes that a one-off investment in 3D printers can help alleviate pressure off doctors, and meet the needs of prosthetic users in the country. The future of 3D printed prosthetics As amazing as the technology is, 3D printing materials generally cannot yet replace the durability and reliability of conventional prostheses. This is changing, however, with technological advancements in both metals and polymers for additive manufacturing. Besides this, there is of course the cost-effectiveness and significant lead time reductions offered by 3D printing, so it’s safe to say additive manufacturing has a bright future in the field. What's really needed, much like with most of the technology's applications, is funding and trust in the process. Organizations like Syria Relief have realized this, and are now attempting to lead the push with government appeals. With time and a little bit of luck, we could very well see 3D printed prosthetics take off and change lives daily.
Blockchain and Transparency in the Food Supply Chain
Bitcoin has been around for a while now, and so have its proponents. Blockchain the underlying technology of cryptocurrencies like bitcoin is poised to revolutionize the finance industry and has the potential to transform the world economy. And of the potential new avenues for blockchain, perhaps none is more promising than the food supply chain. Where traditional paper tracking and manual inspection systems can be open to fraud and inaccuracy, blockchain technology provides a permanent record of transactions. This allows companies to automate information-gathering at all aspects of production, recording things like product age, price, quality, certification, and location, which can help prevent counterfeit products. Blockchain technology can also potentially improve access to funding as the improved coordination and transparency that come with product traceability translates into more efficient regulatory processes, making it easier for lenders to identify worthy recipient firms. An immutable ledger can potentially store transactions that would otherwise be difficult to cross-reference, allowing firms to connect a retailer sourcing a product, and a bank providing the money for that product order. In traditional enterprise resource planning (ERP) systems conflicts in the supply chain would be costly and time-consuming to find. But Walmart was able to use blockchain solutions to shrink the time to receive tracking info, a task that previously took a week, down to 2 seconds. This can make things like food recalls much faster and cheaper. Walmart China collaborated with VeChainThor Blockchain to create the Walmart China Blockchain Traceability Platform. In the USA the company has implemented IBM’s blockchain for food traceability solution. Walmart recently put out a press release on this issue, with Frank Yiannas, Vice President of Food Safety saying that its customers "deserve a more transparent supply chain. We felt the one-step-up and one-step-back model of food traceability was outdated for the 21st century. This is a smart, technology-supported move that will greatly benefit our customers and transform the food system, benefitting all stakeholders.” Oracle, a leader in ERP systems, identifies three key elements to maintaining a healthy food supply chain: transparency, traceability, and trust. Because of the lack of interoperability among ERP systems along the supply chain, information is frequently unverified or withheld. Transparency is the food system is gaining importance for a lot of customers globally. The traditional systems required that any indication of abnormal temperatures led to the destruction of the whole shipment, while other abnormalities would frequently go unchecked. By using temperature sensors on each pallet or even each case, firms can remove specific items rather than entire shipments, leading to a more focused and effective recall. Startups Working in This Space We have already mentioned how big companies like Walmart are taking advantage of this technology to offer greater consistency and transparency to their customers. Albertsons is another example: they used blockchain technology to do a traceback on bulk romaine lettuce back in 2019. Major tech companies like IBM and Oracle are also offering blockchain solutions: Nestle and Carrefour partnered with IBM for their GUIGOZ Bio 2 and 3 infant milk range, and IBM is also working with Ecuadorian milk processor El Ordeño, Cermaq salmon, and the Organo Corporation to provide transparency and streamline the quality control process for their products. Nestle is also collaborating with blockchain platform OpenSc, and Carrefour uses IBM’s Food Trust platform to track food products, offering information to consumers. While it’s clear that large companies can leverage their market position and influence to guide decision making, there are also smaller companies that are utilizing the power of blockchain in new areas: • Supply chain startup Provenance has had some success in tracking ethical tuna sourcing in Indonesia. • Tech startup Monegraph uses blockchain technology to enable ownership and usage of video clips and brand-sponsored content, and sharing of revenue among creators, publishers, and distributors. • B2B trade startup Skuchain targets the global trade and finance market with supply chain finance products. • UK-based app Breedr launched in 2019 and seeks to increase certainty and productivity in livestock production. Future Success? Analysts across the world opine that the current food sourcing and production systems are unsustainable and the need for innovation is bigger than ever. Consumers are seeking information about how the source of their food, how it is produced, and assurance that it is safe. These changes in customer preference are resulting in increased adoption of digital technologies such as blockchain, artificial intelligence, and near field communication by food companies across the globe – a trend which is going to further explode in the near future. What kind of limitations might affect the adoption of blockchain technology in the food supply? For one thing. Typical blockchain technology, like Bitcoin, is based on open records with anonymous users. This is exactly the opposite of what a supply chain needs, as they must monitor their users and protect the privacy of the firms involved. Blockchain also requires a consensus protocol, which is usually achieved by having participants verify each transaction. This means that the Bitcoin network can handle less than 400,000 transactions a day. In industries that handle potentially billions of transactions, this is simply unfeasible. It’s also not clear right now who would profit or lose money from these changes, and most firms are unwilling to take the steps necessary if they don’t see everyone around them doing it. However, with companies like Walmart getting involved, who get to dictate what the firms that sell to them can do, it may not be long before these changes are either widely adopted by big-name brands or legally required through legislation.
The banking industry is undergoing a transition from traditional paper-based system to digital payments. The problem with this new system is that it's not foolproof and can be hacked easily. Banks are constantly looking for ways to prevent fraud and detect fraudulent activity on their systems. This is where artificial intelligence comes into play. One way they're doing this is by using machine learning techniques, which are computers that have been trained to recognize patterns or understand language. For example, if you give a machine learning algorithm a bunch of data sets of known photos and images, it can be used to recognize new images. This phenomenon is what allows AI to be powerful and beneficial to the industry. Machine learning algorithms are quickly becoming an indispensable tool for banks looking to prevent fraud and detect it if it occurs. The number of cases of digital banking fraud is expected to increase in the coming years and banks are looking to prevent as much of it as they can with AI. How Might AI Help Stop Digital Banking Fraud? Banks are always on the lookout for new ways to prevent fraud in their money transfer system. One way is by hiring more people to help screen questionable transfers. However, this can become expensive and time-consuming. The other way is to use AI to screen transfers. This can be done in a couple of ways: 1. Through the use of "Bayesian Belief Networks" that analyze a network of actors involved in a transaction and the variables that affect the likelihood of that actor committing fraud. 2. By using "Natural Language Processing" that analyze the words in a transaction and calculate the probability that the transaction is fraudulent. Backing up the first method is the use of "Bayesian Networks" that use Bayes' rule to determine the probability that a transaction is fraudulent. Backing up the second method is the use of "Markov Models" that analyze similar past fraud patterns to come up with a more accurate prediction of whether a transaction is fraudulent or not. The second method involves using "fuzzy logic" that analyzes variable meanings of words in a message and the probability that those words are being used randomly by a human rather than with intent. Another emerging method involves using "Neural Networks" which are made up of neurons that communicate with each other and recognize patterns in data. The more patterns that are recognized, the stronger the connection between the patterns and the higher accuracy of a prediction. DataVisor is a California based AI start-up that provides fraud detection solutions. It develops big data solutions that predict attack vectors among various users and accounts. It also provides security, analytics, and infrastructure solutions for predictive threat management. Teradata is another firm that uses AI to detect and prevent fraud. The company’s solution is used by U.S. Bank to predict threats and deeply personalize the banking experience for its customers. Other companies providing AI-based solutions for fraud detection and prevention include Polish company Nethone, Indian start-up ADVARISK, French-based Shift Technology, etc. Anti-fraud surveillance Anti-fraud surveillance focuses on looking for suspicious behavior that could indicate a potential fraud attack. One potential behavior is people making many transactions of small value. If you're sending small amounts of money to lots of people, then you may be attempting to send the money to someone using a "pen pal" method or a similar scheme. Another potential behavior is a large number of transactions from a single IP address. Whenever a person opens up a new account, the first thing they usually do is send a large amount of money to test the system. AI companies like "SentinelOne" are developing solutions to help prevent fraud. The company provides endpoint protection using AI and machine learning through its Autonomous Al Platform. Anomaly Detection Major banks have used anomaly detection to detect fraud! One great example is detecting if someone is trying to transfer money to an account that they're not authorized to access. Anomaly detection could range from malware and more traditional banking fraud methods to money laundering attempt through receiving and sending payments from suspicious entities. FeatureSpace is a UK based start-up that detects anomalies in real-time to spot new fraud attacks and suspicious money laundering activity using adaptive behavioral analytics and machine learning. Feedzai is another company providing anomaly detection solutions to banks through its Risk Management Platform. Phishing Scams Phishing Scams is another area where AI can help banking. This method focuses on stealing financial credentials through malicious emails, fake phone calls, etc. Scams are becoming more advanced and banks should stay ahead of the game and implement new solutions to prevent fraud. There are a few different types of phishing scams. One type is the "Impersonation" phishing scam. For this scam, scammers will pose as a bank representative and contact you via online message. They will ask you for your password or security questions to help you with a technical issue. One company that is helping in eliminating phishing using AI is Israeli startup Cyberfish, with their Anti-Phishing Solution. The solution combines computer vision and AI to stop phishing emails and websites in real-time. The program monitors and detects new and suspicious login attempts. Once it detects a potential login attempt, it will send you a link that you can use to determine if the login request is real or a phishing scam. Another company AimBrain is developing AI solutions to help prevent phishing. AimBrain's solution is a chatbot that you can add to your online banking platform. It brings proven ability to leverage Deep Neural Networks for fraud detection, to the table. At the same time, it gives you the ability to keep a human in the loop by simply logging into your account and providing human input. As scams and frauds become sophisticated, AI-based cybersecurity solutions will become an essential part of banking and will play a critical role in safeguarding the financial ecosystem. Another benefit of embracing AI and ML is that it will help banks reduce operations costs significantly and allow them to focus on the one thing that matters most – Customer Experience!
Growing Application of Artificial Intelligence in Retail industry
The retail industry is a good example of how artificial intelligence can be used to improve the efficiency and profitability of an existing business. The most obvious way to do this would be to automate the repetitive tasks that are currently done by humans, such as stocking shelves or checking out customers. Another possibility is to use AI to help with customer service. The first option is a bit more difficult to implement but can have a much bigger impact in the long term. It would reduce costs for the business as fewer employees are needed and should also increase profitability. The second option would be to use AI as a way to help employees provide better customer service. This might include using voice user assistants or chatbots to help customers with queries. By focusing on the needs of the customer, businesses can improve their conversion rates and decrease costs by not losing potential customers due to service delays. Inventory Management Using AI AI can also focus on inventory management. Currently, many businesses keep track of what they have in stock using a system that uses manual input. As you might expect, this can be a time-consuming process. AI might be able to manage inventory using a more advanced version of this algorithm: if you can define a set of criteria that can be used to determine whether an item has to be added to or removed from the inventory, then a computer program could check if the store has enough of an item without needing to contact the supplier. Conversely, AI can be used to improve the efficiency of the supply chain. One of the main causes of inefficiency in the supply chain is at the warehouse level. Many businesses do not have the most up to date information on what they have in stock and how much it is worth. Peak AI Ltd. is a company that is working on a solution to this problem. Using artificial intelligence, they are developing software that can scan product packages to determine their contents with 97% accuracy. This information could be used by businesses to better manage their inventory. For example, if the product package contains a bottle of wine, then the package can be scanned and the AI system can determine if the contents are more valuable as a wine bottle or an empty glass bottle. AI can help in increasing forecast and rebuying accuracy to drive profitability, avoid stock-outs, optimize inventory sell-through, and reduce wastage. Sales Forecasting and Customer Engagement Another area in that AI can make a difference in the retail business is the accuracy of forecasting sales. This can be done in a number of ways, the most obvious being to use AI to automatically generate sales forecasts. These forecasts could be used in a few different ways. The first would be to use them by themselves. New York based Saggie uses AI and Big Data to forecast sales. Another startup Neuralytics provides AI-powered sales software that adds external data such as weather, traffic, and sports into the sales forecast. AI-enabled chatbots can be used to interact with social media users to find out what they would like to see from your brand. Based on these requests, the chatbot can send you questions to ask your customers to better understand their needs and suggest products that customers may like. Aigo.ai is a startup that is working on this exact solution. Aigo uses a chatbot to interact with customers on Facebook Messenger and Instagram. It uses customer conversations as the basis for product recommendations. By collecting reviews, you can improve product recommendations for your customers. AI-enabled Sales Assistants The AI-enabled sales assistant is another use case for AI. The sales assistant could be tasked with answering customer questions and providing personalized assistance. These assistants could also be used for support and to increase your overall conversion rates. Pepper is a robot developed by SoftBank, which can be similarly used by businesses. Pepper can ask questions to customers and understand their needs. It can also browse products and answer questions about them. Pepper is currently used in around 140 of SoftBank's Japanese stores and has also been trailed in American stores. A small team of AI engineers from Amazon has also been experimenting with using Pepper to enhance the customer experience in Amazon stores. Peapod is an online grocery delivery service, which uses AI to ensure their orders are correct. The company uses AI to identify the items ordered and also uses machine learning to recommend items that can be ordered together. Peapod is part of an online retail trend that uses cutting edge technology to disrupt the industry. Conversica is a tech company that allows businesses to connect with their customers in a more personal way. Using AI and human experts, the company reviews customer messages and social media posts to determine the state of customer happiness. AI in Warehouse and Logistics As warehouses become more automated, they can also involve more use of AI. Imagine a warehouse with self-driving forklifts and a system that detects and routes around damaged unnecessary or dangerous items. Through the use of sensors and AI, items will no longer be piled on top of each other and packages will not be stacked too high. Companies such as Amazon are already using technologies like AI and Robotics to manage their logistics infrastructure. Traditionally, for a package to be delivered, it has to pass through several human hands. With AI-powered logistic platforms, a package can be routed automatically, based on factors such as expected delivery date, current traffic conditions, or even a package's temperature. Using machine learning, Amazon's technology can detect when items need to be picked, sorted, or packed and then assigns that job to a human or automaton. Future of AI in retail We are still in the early stages of AI being implemented into the world of retail. There are a few use cases in place and a few startups that are working on smaller-scale projects. The growth in AI and ML technologies will continue to boom in the coming years and you can be sure that we will start seeing this implement itself into the everyday world of online and offline retail.
In today's world of seamless interconnectivity, AI's ability to identify disease patterns through machine learning is empowering public health practitioners and policymakers with enormous potentials. This offers new hope in effectively preventing various diseases by recognizing early subtle signs of the disease and preventing it from progressing. Focused, context-specific preventive steps promote cost-savings on therapeutic care, expand access to health information and services, and enhance individual responsibility for their health and well-being to combat the rise of infectious disease epidemics. Many startups are providing services for the early diagnosis of many diseases. An example is Onward Health, which uses predictive analytics and machine learning to build a portfolio of diagnostic tools in classifiers and analytical tools. These tools help pathologists diagnose even the most subtle change, providing more in-depth, more accurate insights from available histopathological samples. Also, Onward Health is leveraging computer vision techniques and ML algorithms to offer tools in computational pathology and mammography. A foundational AI technology called transport-based morphometry (TBM) helps doctors identify diseases that are otherwise imperceptible to the human eye. Research shows that even before apparent signs of an illness can be seen on medical images, this technology predicts osteoarthritis conditions using machine learning to link these patterns to future osteoarthritis symptoms. There is substantial diagnostic potential for this technology as TBM can hasten disease detection, which is beneficial to many patients as they can take charge of their health early before troubling symptoms develop. There are many startups in this field. For example, diagnostic tests and blood work to test for cancer is done by Freenome using AI. By deploying AI at general screenings, Freenome aims to detect cancer in its earliest stages and subsequently develop new treatments. Harvard University's teaching hospital, Beth Israel Deaconess Medical Center, uses artificial intelligence to diagnose potentially deadly blood diseases at a very early stage. Doctors are using AI-enhanced microscopes to scan for harmful bacterias (like E. coli and staphylococcus) in blood samples faster than is possible using manual scanning with 95% accuracy. Another example is the Nevada-based startup Cyrcadia that has developed a breast patch to detect temperature changes in breast tissue, and the data is analyzed using machine learning algorithms. Pathway Genomics has developed a blood test kit called 'CencerIntercept Detect,' which collects blood samples from high-risk individuals who have never been diagnosed with cancer as part of a research study to determine if early detection is possible. Similarly, New Hampshire based Breast Health Solutions applies deep learning algorithms to 2D mammography, 3D mammography (digital breast tomosynthesis or DBT), and breast density assessment. It's ProFound AI technology became the first artificial intelligence solution for 3D mammography approved by the FDA. Transpara by ScreenPoint Medical trained on over a million mammograms helps radiologists analyze both 2D and 3D mammograms. The answer is already in use in 15 countries, including the USA, France, and Turkey. Electronic health records give a lot of useful information. Israel based Medial EarlySign is leveraging artificial intelligence to mine this EHR data to detect colorectal cancer risk much earlier. The University of Oxford has validated a study done in Israel on a population of 3 million individuals. They also have two products that identify prediabetes patients and those Type 2 patients who are at risk of developing chronic kidney disease within three years. India-based AADAR operates in the "Ayurveda-inspired" preventive healthcare space. It offers herb-based products to curb lifestyle ailments like protein deficiencies, blood sugar, indigestion, cholesterol, and obesity. Yet another startup is Prognos. It is a New York-based startup that works with the primary goal to eliminate various diseases by using artificial intelligence to predict disease and drive decisions earlier in healthcare. The Prognos Registry includes more than 15 billion medical records, and it analyzes clinical lab and diagnostics results to make predictions about an individual's risk for having asthma, lung cancer, and many rare diseases. Podimetrics is a care management company with the leading solution to help prevent diabetic foot ulcers. Likewise, Siren Care creates Neurofabrics; the first product is Siren Diabetic Socks, which allows people living with diabetes to avoid amputations. Russian based Brain Beat Ltd develops high-tech biomedical equipment that non-invasively monitors blood glucose levels. This helps keep the disease under control and improve the quality of life of patients with diabetes mellitus. Anticipating heart failure with machine learning Excess fluid in the lungs often presents a diagnostic dilemma as it dictates the doctor's course of action. Clinicians rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans. Recently, a new machine learning algorithm was developed by researchers at MIT that can look at an X-ray to quantify how severe the edema (fluid collection). The system determined the right level more than half of the time and correctly diagnosed the most severe cases 90 percent. Better edema diagnosis helps in the case of acute heart issues, but other conditions like sepsis and kidney failure. Take a selfie to detect heart disease A new study published in the European Heart Journal found that sending a photo selfie to the doctor could be a cheap and simple way of detecting heart disease using AI. This study is a first of its kind that uses a deep learning computer algorithm to detect coronary artery disease (CAD) by analyzing four photographs of a person's face. Although the algorithm needs to be further refined and evaluated in more comprehensive groups of individuals from various ethnic backgrounds, the researchers believe it has the potential to be used as a screening method that could detect possible heart disease in individuals in the general population or in high-risk groups that could be recommended for further clinical testing. Know the weather to prevent diseases There is a significant level of evidence that the weather can influence the emergence and transmission of disease. xtLytics, LLC has pre-built predictive deep learning AI algorithms and services that enable government organizations, pharmacy, insurance, and pharmaceutical companies in engaging patient and making a better decision using multiple datasets like weather-related parameters, socio-demographic parameters, geo-location parameters, treatment/medicine-utilization pattern or claims, and patient social interaction to predict the potential number of incident cases by postal code at least 15 days in advance. This model has shown promising results in predicting Vector-Borne Diseases (Dengue and Malaria), Airborne Disease (Influenza), Atopic Triad (Atopic Dermatitis-Allergic Rhinitis-Asthma/COPD), and certain types of precancerous skin conditions like actinic keratosis and skin cancers like Melanoma, which is positively correlated with temperatures and ultraviolet radiation (UVR). What's the Future? AI can predict the possible turn of events using particular segments, disease susceptibilities, and previous diseases. Along with the prevention of diseases with early diagnosis, it can also map potential victims in the wake of a disaster. For example, information about respiratory diseases in older adults can be analyzed and used to predict susceptibility to infections such as COVID-19. Similarly, military veterans who have been exposed to asbestos become incredibly susceptible to respiratory infections such as coronavirus. Such kind of information is vital in controlling COVID-19 from becoming fatal globally. Although these prospects look attractive, before we make a final decision about the applicability of AI in disease prevention, all stakeholders should insist on research that rigorously evaluates the accuracy of the predictive models and their effects on health outcomes when used in particular ways in real clinical settings. Benefits of incorporating AI in our routine healthcare system include increased efficiency in treating and diagnosing patients by giving physicians the ability to focus on diagnoses and procedures that require more remarkable skill and judgment, increased diagnostic accuracy, and improved treatment regimens. However, there are also several risks associated with integrating AI into medical devices used to diagnose and treat patients, such as potential liability for harm to patients in case the decision made by the algorithm is incorrect, unauthorized use of private health information, and chances for reduced physician and patient medical decision making. Despite all these arguments, the reality is that AI will continue to grow in the medical field and alter existing workflows, paradigms, and relationships.
The power of industrial additive manufacturing technology, or 3D printing, is felt in a wide variety of industries around the world. Included in this list is the oil and gas industry, despite some considering it a dying sector with the inevitable rise of renewables. End-use parts in oil and gas, by nature of the field, tend to require chemical and heat resistance, and this is something 3D printing can provide. There exists a multitude of 3D printing processes that excel at fabricating parts made of metals such as Inconel and titanium and even polymers such as PEEK which display similar qualities. But who exactly is operating in this landscape, and what are the benefits? Big names in fossil fuels According to financial reports, British multinational oil and gas company BP is said to invest approximately $400M a year on research and development and commercial pilots and trials of new technology. As one of the world’s seven largest oil and gas publicly traded companies, commonly known as “supermajors” it invests a further $200M annually in energy-based innovation through its in-house fund BP Ventures. Just last year, BP confirmed its use of 3D printing to manufacture chemical-contacting components for its petrochemicals business. The company previously began integrating additive manufacturing to produce parts within its chemicals division, including agitators used inside catalytic reactors. Through the use of additive manufacturing, BP is now aiming to create pipes and additional components for its offshore platforms. The company is also exploring other industry 4.0 technologies as well as 3D printing, such as drones for routine inspections of pipelines in Alaska and “crawlers” – robotic devices used to monitor corrosion in pipes and risers. Similarly, energy giant Royal Dutch Shell has previously announced a four-year pilot project at its Pulau Bukom refinery in Singapore to trial a ‘Digital Twin’ technology. The system, when fully implemented in 2024, is expected to boost productivity while improving reliability and safety. Shell's system will run alongside several other digitization technologies that the company has already implemented at the refinery, including 3D printing. Metal 3D printing for oil and gas China-headquartered Nanfang Additive Manufacturing Technology Co. has previously signed a contract with the state-owned petroleum company Tubular Goods Research Institute to explore the use of electron beam melting (EBM) for oil pipeline parts. EBM, which is a sub-technology within powder bed fusion, is known for its ability to produce high-density, high-strength, and generally high-performance metal parts at relatively low costs (making it particularly suited to the application). Another major advantage of the process is its capability to produce parts that lack residual stresses, which can be a problem when dealing with cylindrical geometries and large cross-sections. Prior to the contract, Nanfang had manufactured a prototype pressure vessel cylinder for a project with the country’s Nuclear Power Research Institute using a combination of metal 3D printing and CNC machining. Weighing in at 400kg, the prototype served as a precursor to the EBM project, which specifically involved the development of new EBM materials and their application to thick-walled, three-way pipe fittings. Elsewhere, in the U.S., California-based 3D printer manufacturer VELO3D recently announced plans to collaborate with Oklahoma-based precision machining company Duncan Machine Products. As a parts supplier for the oil and gas sector, Duncan will use VELO’s metal additive manufacturing technology to improve its part performances while also reducing lead times. The precision machining company has already received over 1500 orders to 3D print metal parts for downhole tools used in onshore and offshore oil exploration. Duncan has stated that it expects this number to increase up to tenfold in the next two years. VELO's flagship Sapphire 3D printer is currently being used as an alternative to the traditional method of investment casting, which requires a mold to be produced and doesn’t quite lend itself to the rapid design iteration that additive manufacturing is known to offer. Over in Florida, 3D printing service bureau Sintavia has previously signed a term sheet with metallurgy specialist Howco to advance the capabilities of 3D printing in oil and gas. Sintavia, which mainly deals with energy, aerospace, and maritime clients, utilizes metal 3D printers from major players such as EOS, GE’s Concept Laser, and SLM Solutions. Now, the partners are in the process of jointly delivering the economic and technical potential of the technology for their customers via a mutually beneficial agreement. The next steps for 3D printing in the energy sector Admittedly, the oil and gas industry was one of the slower adopters of AM, especially when compared to automotive and medical. The last couple of years have seen major names such as BP and Shell making headlines, however, so it is likely that others will follow suit as trust in the technology improves over time. Yes, rapid prototyping is of particular value to the industry, and AM can provide this like no other. As such, development cycles for critical parts can be shortened significantly, all while omitting production lines and clunky design iteration processes. The key challenge that remains, however, is reliability in relation to standards. End-use components in regulated industries are constantly under heavy scrutiny, and a single critical part fracture can result in catastrophic failure, major monetary setbacks, and even loss of life. This is the big hurdle in the way of AM - industry certification. With a sector-wide push, completing the transition from prototyping to end-use component production may just be possible, all while meeting stringent performance and safety requirements.
Technological integration of Artificial Intelligence (AI) and machine learning in the Prosthetic and Orthotic industry has become a boon for persons with disabilities. The concept of neural network has been used by the leading manufacturers of rehabilitation aids for simulating various anatomical and biomechanical functions of the lost parts of the human body. Moving from the lab to real-life is not only a scientific challenge but also an engineering challenge. AI and neural interfaces are fundamental but will need robust, efficient, and lightweight designs to succeed. Advances in prosthetics, especially brain-machine interface wearables, are coming up with innovations that enable us to measure and stimulate the electrical impulses from neurons. As a result, much smarter and more adaptive prostheses are approaching a reality in which replacement with artificial appendages offer near-normal function. Advancement in the field of AI and robotics has created a ray of hope for millions of persons with disabilities through physical rehab devices such as Bionic led, mind-controlled prosthesis, and exoskeletons. The basis of incorporating artificial intelligence in robotic prostheses is that the algorithm interprets nerve signals from the patient's muscles that will allow for the prosthesis to be controlled more precisely. The technique is based on a regenerative peripheral nerve interface. Surgeons use a small piece of muscle and wrap it around the amputated nerve to produce amplified signals. This is then applied to machine learning algorithms to turn the alerts into subtle prosthetics movements like picking up small things, making a fist, or pinching fingers together! A team of engineers at the University of Utah has designed a new approach to prosthetic limb movement that uses artificial intelligence to mimic the user's residual leg's motion, making the act of walking smoother and more intuitive. Rejoint has developed a solution for knee replacement based on the integration of 3D Additive Manufacturing, AI, and the Internet of Things, which enables the design of personalized implants and surgical simulation-based on unique patient anatomy. Kernel is an early-stage brain-machine interface company developing neuroprosthesis to mimic, repair, and improve cognition. Kernel's Neuroscience gives on-demand access to its brain recording technology. They are now finding a way to measure and stimulate many neurons' electrical impulses at once. The technology will be used clinically for diseases such as depression or Alzheimer's. Dreem based in San Francisco is a neurotechnology startup that has developed a sleep-monitoring, head-mounted wearable. The device uses EEG electrodes to monitor and analyze brain activity during sleep. It then uses "bone conduction technology" to modulate brain activity by emitting subtle sounds at precise moments that the company claims enhances the overall quality of deep sleep. Thync, again a San Francisco based startup, has developed a small, wearable "pod" that attaches to the back of the neck and uses neurostimulation to combat stress and promote better sleep. The product is targeted towards consumers who frequently suffer from anxiety and consequently struggle to sleep. BrainCo, a product of the Harvard Innovation Lab, specializes in brain-machine interface wearables. The company's main product line is the Focus series, which offers wearable headbands for education, fitness, and mind-controlled games. BrainCo has also expanded into prosthetics, working under the name BrainRobotics. The company is developing a robotic prosthetic hand that can be controlled by the user's mind. Flow Neuroscience uses brain stimulation to treat depression. The company has developed a headset that delivers transcranial direct current stimulation (tDCS) to the forehead, which, according to the company, reverses neural activity imbalances in the frontal lobe observed in people with depression. DEKA is a New Hampshire based company that builds a robotic arm prosthesis designed to restore body functionality for individuals with upper extremity amputations. After the replanted nerves are innervated on the chest muscles, the amputated or paralyzed patient will have to think about the arm and hand movements. The result is a contracted muscle that will move according to what the individual is thinking of. Exii is a Japanese startup that builds affordable, stylish, and highly functional electronic prosthetic arms. The sensors, strapped around a wearer's arm, detect muscle signals, and five artificial fingers, linked to a built-in motor, automatically change finger angles according to the degree of muscle expansion and contraction. Ekso Bionics is a leading developer of wearable exoskeletons that amplify human potential such as human mobility, strength, and endurance for military, civilian, and medical uses. It offers technologies that range from helping those with paralysis to stand up and walk. ReWalk Robotics is an innovative medical device company designing, developing, and commercializing exoskeletons allowing individuals who use wheelchairs to stand and walk. CYBERDYNE Inc. is a venture firm established to materialize the idea to utilize Robot Suit HAL for the benefits of humankind in medicine, caregiving, welfare, labor, and massive works, entertainment, and so on. AI and Robotics for future Prosthetics Research shows that every 30 seconds, there could be an amputee in some parts of the world. These numbers are likely to increase in the coming years owing to various factors such as aging populations, increased incidence of vascular diseases, gangrenes resulting from uncontrolled diabetes mellitus, and trauma that could lead to amputations. Without any doubt, there's a promise for amputees with advances in robotics, machine learning, and prosthetics. The developments will improve future artificial limbs and turn them into truly artificially intelligent limbs. AI-powered prostheses, with their abilities to be upgraded both on the hardware and software fronts, hold the potential to be superior to biological arms, and they could be used in the future even to augment the capacities of manual workers. Powered prostheses aim to mimic the missing biological limb with controllers that are finely tuned to replicate the nominal gait pattern of non-amputee individuals. But this control approach poses a problem with real-world ambulation, which includes tasks such as crossing over obstacles, where the prosthesis trajectory must be modified to provide adequate foot clearance and ensure timely foot placement. It is a formidable challenge to replicate lost anatomical structure and function. High costs of these devices are significant limitations as many persons with disabilities cannot afford it. Government bodies, manufacturing units, and funding agencies must come forward and invest in this field so that the highest quality and latest technology reach a larger population of disabled at an affordable cost.
Way back in 1890, William Coley, a young cancer surgeon, noticed that dozens of cancer patients had a regression of their disease while carrying a separate infection. This raised a significant question: While fighting against bacterial infection, can the human body simultaneously battle a tumor? Researchers found the answer when tumor shrinkage was noticed after injecting bacteria into nearly a thousand patients with varying degrees of success. This ability to modulate the body's immune response and behavior, by applying engineering principles to biology forms the basis of Synthetic Biology. This technology is ushering in a new era of cancer therapy and changing the landscape of healthcare. Genetic reprogramming of immune cells and safer immune-therapeutics are two main focus of synthetic biology in cancer therapy. Can bacteria cure cancer? Engineering of bacteria for immune-cancer therapy using synthetic biology is an upcoming trend. This involves various treatment aspects such as therapeutic, safety, and specificity features through genetic modification. Developments in genetic reprogramming include targeting bacteria to tumors, specific sensing and response to tumor microenvironments, remote induction methods, and controllable release of therapeutics. Synthetic biology capitalizes on bacteria's natural ability to colonize immunoprivileged, hypoxic core regions of tumors by escaping from leaky vasculature. A variety of strategies such as targeting, inducing gene expression, quorum-sensing, expressing and releasing cytotoxics, and intracellular gene delivery have been engineered to control these bacteria's behavior and produce anti-tumor effects. Cancer startups with a bold twist Synlogic is preparing to transform cancer management by introducing live, engineered bacteria as a cancer drug. Their lab results have shown that mice injected with engineered, live bacteria SYNB1891 could shrink cancer tumors. The treatment also appeared to provide mice with long-term protection in the form of immune memory. Promisingly, treatment of human cells with SYNB1891 led to a similar stimulation of the immune response as seen in mouse models, providing a positive indication for humans' success. Targeted vaccines and cancer immunotherapies using synthetically engineered bacteria are available at Prokarium. This microbial cancer immunotherapy uses Onconella™ strain, a particular bacterium developed by the company, acts by identifying the solid tumor, targeting it, and then colonizing it to exert its therapeutic effect. Ideaya Biosciences is an oncology-focused startup aiming to discover breakthrough synthetic lethality medicines for genetically defined patient populations and immuno-oncology therapies targeting immuno-metabolism and innate immunity. Poseida Therapeutics uses gene-editing techniques to develop treatments for multiple myeloma and prostate cancer, among other conditions. These work by harnessing the power of a patient's own immune system for the treatment of cancer. It is aimed to result in safer, more effective, accessible, and affordable remedies for patients in need. Tango Therapeutics uses technology like CRISPR to genetically edit immune cells such as T cells and infuse them back into the patients for cancer treatment. OncoOne develops drugs that target an oxidized version of an immune protein called macrophage migration inhibitory factor (oxMIF), which is only present in diseased tissue that can be used in cancer treatment. Sana Biotechnology designs cells to treat cancer, central nervous system diseases, heart disease, and genetic disorders. These specialized cells can function in a variety of ways, depending on the application. For instance, some might replace damaged or missing cells in the body, while others deliver molecular payloads of RNA, DNA, or proteins to reprogram existing cells. ArsenalBio is focused on integrating technologies such as CRISPR-based genome engineering, scaled and high throughput target identification, synthetic biology, and machine learning to advance a new paradigm to discover and develop in immune cell therapies. The potential applications of CRISPR are enormous. It's the closest stage to a cure for cancer. Using this technology, HIV infection in animal models and even human cell cultures has been cured by removing the viral genes that insert themselves into our DNA. Kite Pharma offers innovative cancer immunotherapy through re-engineered chimeric antigen receptor and t-cell receptor therapy, capable of boosting the patient's immune system's ability to recognize and kill tumors. ZIOPHARM Oncology employs novel cell engineering techniques and multigenic gene programs to develop next-generation patient- and donor-derived adoptive cellular therapies based on designer cytokines, such as genetically modified T cells and NK cells, to target hematologic malignancies and solid tumors as well as graft-versus-host-disease. These technologies are designed to improve safety and decrease the cost, time, and complexity of development associated with cell-based therapies. Better future with better therapy Cancer immunotherapy has come a long way. Treatment options are now available that use antibodies to target specific proteins of cancer. These antibodies come as drugs, vaccines, or immune cell infusions, and they work to enable the body's natural defenses to fight cancer naturally. Synbio in cancer therapy takes advantage of both biotechnology and the human body's unique immune capabilities. It gives the clinician the capacity to deliver wave after wave of immune response from a single treatment utilizing synbio. However, currently, there are challenges, such as genetic stability, that researchers must address to successfully implement this novel therapy in humans. The ultimate goal would be to deliver targeted genetic material in vivo and ex vivo gene therapies to redefine disease treatment.