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1. Net Energy Positive: Waste-to-Energy bio-technology that converts organic contamination to renewable natural gas. 2. Fast, convenient & compact installation: Turnkey installations built with arrays of powerful 100L modules. 3. Solution to Climate Change: Mitigation of CO2 and Methane emissions. 4. Futureproof against new regulations: Reactor outputs clean water that can be discharged or recycled.
Future Tech | Green Energy & Environment/Life ApplicationWe propose a technology to reduce the specific on-resistance (Ron,sp) of 1.7 kV voltage rating VDMOSFET on 4H-SiC, including channel area process optimization, channel and source self-alignment, recessed source contact, etc. The technology improves the Baliga’s figure-of-merit (BFOM), which is superior to existing products and published literature with the same voltage rating, and has the advantage of continuously reducing the cell pitch.
Future Tech | Electronics & Optoelectronics/Green Energy & EnvironmentIn this project, power-efficient architectures for the PAM-4 transmitter and receiver are developed in 28nm CMOS. It demonstrates a 112Gb/s PAM-4 end-to-end link under 10dB channel loss with 2.5pJ/b power efficiency. The XSR transceiver can be utilized as a chiplet and applied into heterogeneous integration for next-generation advanced package applications.
Future Tech | Materials & Chemical Engineering & Nanotech/Electronics & OptoelectronicsElectrocardiography (ECG) is a fundamental method not only commonly used in the hospital for clinical requirements but also widely adopted in home and personal healthcare systems to obtain the electrical activity of the heart. An arrhythmia monitoring system (product name: YuGuard) is proposed and used in a clinical trial. The proposed system has three parts. The first is a high-resolution, low-power analog front-end circuit for implementing bio-signal sensing circuits. The features of the circuits are low complexity, high resolution, and low power consumption. The second part is a digital signal processor with a decimation filter and a universal asynchronous receiver/transmitter package generator. The last part is used to realize a software interface on the smartphone for ECG signal recording, display, and classification. A wavelet-based classification method is also proposed to classify the rhythm. The chip used in the system is fabricated through the TSMC 0.18 μm standard CMOS process. The classification algorithm is verified with data from the MIT/BIH Arrhythmia Database. The accuracy of beat detection and arrhythmia classification is 99.4% and 95.83%, respectively. Patients in Tainan Hospital are enrolled in a human study to verify the performance of the proposed arrhythmia monitoring system. Results show that the system can acquire and classify ECG signals.
Future Tech | Biotechnology & Medical careIn the microgrid, the regional load can be supported by the regional small scale generator or renewable sources, which can be treated as a small inde pendent control power system composed of distributed renewable sourc e, conventional small scale generator, energy storage system (ESS), superv isory system, and regional loads. The microgrid is connected to the main p ower grid with static switch. Normally, the microgrid is connected to the main power grid and controlled for supporting the stability of the power grid. When the main power grid is abnormal, the microgrid is disconnecte d from the main power grid by the static switch. Then the regional loads a re powered by the regional sources and ESS. The 30 kVA grid-forming (GFM) inverter for energy storage system is prop osed in this research, which integrating the supervisory system and power inverter. The supervisory system commend the power inverter for automa tic frequency control (AFC), photovoltaic (PV) output smoothing, or load c ompensation for contract capacity, etc. As the power inverter is connected with the grid, the real or reactive power is provided to or received from th e grid by the commend of the supervisory system. When the grid is off, th e power inverter can support the regional load by forming a stand-alone v oltage source. The 3-phase 3-level neutral-point clamped, NPC, inverter is adopted in this research. With the multilevel structure, lower output harm onic distortion and voltage stress reduced to only half of the input dc-link voltage for lower switching losses are obtained. The wide-bandgap power switch, SiC, is adopted for the superior characteristics to the conventional Si-based power switch. Then, the switching frequency is increased for high er power density and also power conversion efficiency.
Future Tech | Green Energy & EnvironmentThis technology is divided into three parts: making the sample into a need le shape with a focused ion beam, collecting atomic-level projection imag es of the sample at various angles with a spherical aberration-corrected el ectron microscope, and iteratively optimizing the three-dimensional tomo graphic reconstruction with Fourier transform. In this way, the three-dime nsional atomic structure can be obtained in a FinFET sample with a resolut ion of 1.8 angstroms. First, the target is to prepare the test piece into a needle-shaped sample w ith a diameter of less than 50 nanometers. When preparing, we first positi on the sample and use high-voltage ion beam current to roughly cut it int o a needle shape with a diameter of about 5 microns. Then, the ion beam current is reduced to 300 pA, and the cutting is carried out using a ring m ask. Finally, the voltage of the ion beam is reduced to 5 kV, and the current is reduced to below 100 pA so that the damage caused by the ion beam is minimized, reaching a needle with a diameter of 50 nanometers. Then, use a scanning transmission electron microscope (STEM) with a sph erical aberration corrector and an annular dark field detector (ADF) to coll ect atomic projections of the needle-shaped sample at all angles. STEM-A DF images are dark field images, also known as Z-contrast images, and do not have the problem of contrast reversal caused by changing the focus. T herefore, the SiGe thin film, high dielectric constant thin film, ferroelectric layer, and metal gate are promising for observation. Finally, 3D images were obtained using optimized tomographic reconstru ction techniques. Since the experimental data are on the polar grid points, and the reconstruction is on the Cartesian grid points, using all the experi mental data to perform global interpolation in the Fourier space and then performing inverse Fourier transform will obtain the 3D reconstruction wi th a better resolution.
Future Tech | Electronics & OptoelectronicsPneumoperitoneum refers to the presence of free air in the abdominal cav ity. Accompanied with the clinical presentation of acute abdominal pain, p neumoperitoneum found on imaging is highly suggestive of a perforated viscus. Urgent surgical evaluation and intervention is required to reduce p atient morbidity and mortality as delayed treatment can lead to septic sho ck and multi-organ failure, eventually resulting in death. Computed tomography (CT) is the best imaging modality in identifying p neumoperitoneum. At present, response time to patients with pneumoper itoneum is heavily dependent on the vigilance of attending clinicians and turnaround reporting times of radiologists. This is however easily confoun ded by congested emergency departments with long lists of imaging due for reporting in addition to physician fatigue, amongst other factors. We therefore embarked on the development of an artificial intelligence (A I) algorithm via deep-learning to assist clinicians in the preliminary interpr etation of CT abdominal imaging. Upon completion of CT scans, the imag es are automatically uploaded into our AI algorithm for the screening of a bnormal free gas in the abdominal cavity. The process takes 5 minutes, an d those with positive findings are immediately alerted to the on-site radiol ogists and/or physicians for further confirmation. Our deep learning-powered novel algorithm and system thus assist with t he rapid identification of pneumoperitoneum on abdominal CT imaging, with the ultimate aim of hastening the subsequent surgical evaluation and intervention required by these patients for better clinical outcomes.
Future Tech | Biotechnology & Medical careOur technology is based on an integrated self-powered wearable module for effective care of chronic wounds. Among them, the functional compon ents include (1) nanogenerators, which can directly convert energy such a s body movements and body heat into electricity, and the output can be c ontrolled between 1 and 30 volts, which is suitable for stimulating chronic wounds and promoting their healing; another feature is: pulse output, pulse duration and frequency can be controlled, suitable for different chronic wounds. (2) Smart dressing for infection prevention, containing bismuth t elluride nanoplates as thermoelectric catalysts, can produce low-concentr ation hydrogen peroxide of only uM when the difference between the env ironment and body temperature is only 5 degrees, without harming norm al cells and tissue, it helps the wound to avoid infection. (3) Wound monit oring APP. different wounds (like infected wound) and normal skin will hav e different resistance values, especially during the healing process of chro nic wounds, the resistance value will gradually increase, approaching nor mal skin, so that we can establish different calibration curves of the woun d can be used to know the healing status at any times without tearing the dressing, destroying the new tissue, and exposing the wound to the risk of infection; the signal transmission is through the Bluetooth system, which means that we can know remotely the degree of wound healing from time to time. In the future, it can further target more complex types of wounds suc h as venous ulcers, ischemic wounds or keloids, which not only provides p atients with a new type of personalized wound care, but also provides a n ew direction for the development of wearable medical devices.
Future Tech | Biotechnology & Medical careThe surfactant protein D (SP-D) is produced by type II alveolar cells and se rves as an antimicrobial agent as well as to prevent inflammation. Our pre vious study examined single nucleotide polymorphisms in the SP-D gene i n Taiwanese COPD patients. We found that SP-D gene variants were relate d to COPD clinical manifestations, severity and prognosis. SP-D levels wer e significantly associated with COPD airflow obstruction. We found haplot ype G-G-C-C-A associated with lower COPD risk. COPD patients with hapl otype G-G-C-C-A had lower serum SP-D levels, higher rates of positive res ponse to bronchodilator treatment, more improvement of forced expirato ry volume in 1 s in yearly follow-up and better 3-year survival rate than C OPD patients with non G-G-C-C-A haplotype. It appears that SP-D haploty pe can be used as a prognostic factor in Chinese COPD patients. Our invention identifies SP-D gene variants that are predictive of COPD occurrence and prognosis, and has gained USA patent status. COPD, including chroni c bronchitis and emphysema, is Taiwan's seventh leading cause of death and America's third leading cause. Our innovation is that we are the first team in the world to apply fragment of recombinant human lung surfacta nt protein D (rfhSP-D) to treat ozone and cigarette-exposed mice model o f COPD. Exogenous rfhSP-D prevented the formation of oxidized low-den sity lipoprotein-induced foamy macrophage in vitro and reversed the airw ay inflammation and emphysematous changes caused by oxidative stress and CS exposure in vivo. SP-D upregulated the expression of genes involv ed in countering oxidative stress and lipid metabolism perturbations indu ced by CS and OxLDL in bone marrow-derived macrophages. We demonst rate that SP-D plays a crucial role in maintaining the lipid homeostasis of dysfunctional alveol
Future Tech | Biotechnology & Medical careAny defect in a solar cell will reduce the amount of electricity generated. Over time, these defects will result in hot spots. Currently, EL images are commonly utilized for defect detection during the production process of solar modules. However, manual visual inspection is primarily employed formodule defect assessment, leading to inconsistencies in standards and judgments.Our detection technology is based on the original and adaptable Yolo architecture. This technology incorporates innovative approaches like incremental learning and transfer learning to address the challenges associated with diverse flaw types and difficult data collection. Consequently, the accur acy of defect identification has been significantly enhanced, and it can now achieve real-time detection of dozens of defects with an impressive accuracy rate of 99.8%. Furthermore, our solar panel IR thermal defects technology employs a novel object detection method specifically designed for detecting thermal in IR videos. Our team's EL inspection software has been certified by KIWA in the Netherlands. In July 2020, "Msapiens Technology Co., Ltd." was established, and it secured investment from domestic venture capital firms. Presently, venture capital firms from the Netherlands and Germany are showing strong interest. Four Technical Advantages: (1) The largest number: it has more than 21 million EL images and has established the world's largest effective solar module EL image database. (2) The most accurate detection: impressive accuracy rate of 99.8%. Other industries typically achieve accuracy rates ranging from 75% to 95%. (3) The fastest detection rate: Our EL full-load detection speed reaches 18,000 pieces/hour. In comparison, other industries only manage 100 pieces/hour. (4) Highest market share: successfully obtained 8 customers of the world 's top ten solar module manufacture
Future Tech | Green Energy & Environment/Electronics & OptoelectronicsRecent advances in protecting node privacy on graph data and attacking graph neural networks (GNNs) gain much attention. An adversary can utili ze the powerful GNNs to infer users’ private labels in a social network. W e propose to adversarially defend against GNN-based privacy attacks, and present a graph perturbation algorithm, NetFense, to achieve the goal. Ne tFense can simultaneously keep perturbed graph data unnoticeable (i.e., n ot affect social connections), maintain the prediction confidence of target ed label classification (i.e., preserving data utility), and reduce the predicti on confidence of private label classification (i.e., protecting the privacy). E xperiments on 3 benchmark datasets exhibit that the perturbed graphs by NetFense can effectively maintain the performance on targeted label class ification, and significantly decrease the prediction confidence of private la bel classification. The tech is published in IEEE TKDE 2023, and collaborate d with banks E.Sun and SinoPac.
Future Tech | Information & Communications/Machinery & SystemBiological samples that are transparent and thin are difficult to observe wi th a normal bright field microscope. Phase contrast and fluorescence micr oscopes are commonly used, but they have limitations in terms of image c larity and sample viability. AI-assisted 3D label-free quantitative microsco py overcomes these limitations by providing high-quality images and qua ntitative cellular information without the need for fluorescence dyes. By u sing structured light illumination and reconstruction algorithms, this appr oach enables the visualization of organelle structures and offers valuable s tatistical data for studying cell activity and drug effects on cancer cells. In contrast to expensive and specialized equipment required for commerc ial phase contrast microscopy, our system is modular and integrates illumi nation control, image acquisition, and phase reconstruction using thin-fil m transistor (TFT) panels. It can be easily incorporated into existing invert ed microscopes, providing high-quality images without the need for costl y setups. Automation of the system, including light source control and im age capture/storage, saves time and allows for flexible adjustments of the light source position and incident angles. The AI algorithms enhance imag e acquisition efficiency, sample applicability, and image quality, making th e system suitable for capturing dynamic cellular information, particularly f or rapidly changing cell behaviors like division or fusion, and enabling lon g-term observations.
Future Tech | Biotechnology & Medical careCardiovascular disease is one of the major health concerns in Taiwan and worldwide. The number of patients with cardiovascular disease has drama tically increased over the years, with coronary artery disease (CAD) being t he most significant condition. Traditional diagnostic methods for CAD are expensive and resource-intensive. However, this technology utilizes artific ial intelligence (AI)-enhanced electrocardiography (ECG) to improve the d etection of CAD thereby enabling more accurate detection of asymptomat ic coronary artery stenosis.This AI-based technology is a SaMD (software as medical device). Three p atents are applied: (1) Method for selecting feature of ECG; (2) Method for predicting blockage of coronary artery; (3) Method for diagnosing heart s tate based on ECG. Moreover, we expand the output format to PDF vector files, enhancing its commercial potential. Regarding signal processing, it includes wavelet transform, statistical indic ators, and personalized heartbeat intervals. Regarding feature engineerin g, it includes various time intervals, slopes, and height differences betwee n heartbeats to capture subtle abnormalities. Regarding model predictio n, it utilizes a combination of deep learning and machine learning method s, ensuring stability and accuracy. In terms of product application, both XML and PDF files are applicable as i nput. The interpretability of features aids clinicians in identifying abnorma l locations on ECG. Finally, the performance was validated in two hospitals. The results revealed that our AI technology has a superiorly better perfor mance. Traditional resting ECG achieves to 50%-60% accuracy, and exercis e ECG achieves to 70% accuracy. Remarkably, our AI algorithm achieves an 84%-90% accuracy of AUC. Currently, CAD cannot be easily detected in high-risk asymptomatic patie nts. Our AI algorithm can identify 80%-90% of asymptomatic patients wit h normal ECG but actually having stenosis, thus enhancing the accuracy fo r detecting
Future Tech | Biotechnology & Medical careThe average nocturnal blood pressure (BP) or BP dip is a highly sensitive i ndicator of cardiovascular disease risks. However, the nocturnal BP during sleep can not be easily obtained by current BP measurement devices with out disturbing the user’s daily life. As opposed to the point BP estimatio n by smart watch in the sitting position, our research team, composed of r esearchers from National Taiwan University Hospital, National Central University, and Mediatek, uses SENSIOTM smart watch to collect 24-hour pho toplethysmography (PPG) signals together with ambulatory BP monitorin g (ABPM) outputs of the patients for developing a diurnal and nocturnal B P estimation algorithm from wrist PPG in free-living scenario. The applicability of BP estimation during daily life condition is assessed th rough a signal quality indicator established by 3-axis accelerometer and P PG skewness. The correlation coefficient between our activity count (AC) a nd the activity evaluation from sports watch is 0.92 and thus correct judge ment of activity condition can be acquired. To construct a personal model based on multi-layer perceptron and convolutional neural network with fe w training data, the model agnostic meta learning (MAML) technique is a dopted. The stationary data from 535 subjects were employed as the train ing task while the 24-hour data from 14 subjects with age 55.2 23.2 years old were used as the testing task. The query set of testing task contains 6 r ecordings, 3 at daytime and 3 at nighttime. The support set of testing task consists of 5 recordings. The average root mean square error of the BP esti mation per subject is 7.65 mmHg. The mean and standard deviation of tot al SBP estimation error are 0.68 7.98mmHg. The long-term and pervasive monitoring of personal health thus can be achieved by the wearable devic e.
Future Tech | Information & Communications/Machinery & SystemThe development of green and sustainable energy is urgent. Inspired by t he water circulation system of trees, our team has developed an all-paper- based environmentally friendly moisture-powered battery (Figure 1). We have created this new type of “self-powered” energy generation device that utilizes hydrophilic paper-based materials, highly conductive two-di mensional materials with rich functional groups, and water-harvesting me tal-organic framework (MOF). The device can autonomously absorb moist ure from the environmentally humidity air and drive the movement of wat er molecules and ions through capillary action and evaporation, leading t o the electrokinetic effect. This enables the continuous production of ener gy with stable, high-efficiency, and long-lasting output voltage and curre nt. The membrane battery can spontaneously generate electricity by simply p utting it in ambient environment. The membrane battery is highly flexible, ensuring continuous power generation even under different bending and folding angles. Under ambient temperature and humidity (25±2 °C, RH 60 ±5 %), a single membrane weighing 0.05 gram achieves impressive perfor mance with high voltage (> 0.55 V), high current (53 μA), and ultra-long-la sting output (> 12 days). More importantly, the power density of up to 10 μW/cm2 can be achieved, much higher than all the similar state-of-the-art moisture electricity devices. To demonstrate the feasibility of practical app lications, we combined eight membranes in series to power electronics, lik e commercial calculator, LED, electronic watch. This innovative invention r epresents a new generation of sustainable energy and can be considered as a future cutting-edge technology. It will contribute to the “Taiwan Net Zero Carbon Emissions by 2050” pathway.
Future Tech | Green Energy & Environment/Materials & Chemical Engineering & NanotechIrritable bowel syndrome (IBS) is a functional gastrointestinal disorder cha racterized by recurrent abdominal pain and changes in bowel habits. Alth ough IBS accounts for 20-40% of gastroenterology outpatients, there is n o satisfactory drug for the treatment of IBS abdominal pain and it is still a highly unmet need. We found the serotonin type 7 receptor (5-HT7R) is a new target for the treatment of IBS abdominal pain. After drug design and lead optimization, a safe and effective drug candidate DC105 was selectedfor preclinical studies, and an investigational new drug application is expe cted to be filed in 2024. This technique consists of three parts- 1. Discovery of novel mechanism and target: Colon biopsy specimens fro m IBS patients and healthy subjects were collected. Higher expression of 5 -HT7R was found in the specimens from IBS patient than that of healthy s ubjects. Human nerve cell line SH-SY5Y was used to confirm that adding i ntestinal tissue sterile supernatant, 5-HT, and neurotrophic factors can pr omote nerve fiber elongation, while pretreatment of DC105 or 5-HT7R ge ne silencing can reduce the length of nerve fibers. There is a positive feed back relationship between 5-HT and neurotrophic factors, which can caus e excessive growth of nerve fibers by 5-HT7R activation. Thus, 5-HT7R ant agonist is a promising treatment for IBS pain. 2. Establishment of a platform for evaluation of analgesic activity: The pos t-infection with water avoidance stress GW mice and the post-inflammatio n PT mice models were established. The visceral pain in mice and the drug activity to inhibit hyperalgesia were determined by measuring the visceral motor responses stimulated by colorectal distension. 3. Development of a first-in-class drug for IBS abdominal pain: DC105 is a highly specific 5-HT7R antagonist with suitable drug-like properties and s afety. After oral administration of DC-105, the visceral hypersensitivity wa s effectively reduced without affecting normal
Future Tech | Biotechnology & Medical careEstablish high-accuracy AI governance technology to produce a local path ogen-themed database. 1.Cooperate with the National Health Insurance (NHI) Administration to a pply natural language processing (NLP) technology to develop a set of me thods for managing pathogen data, which can automatically standardize t he data format, and combine the expertise of infectious disease physician s to make the standardized data meet the needs of professional fields. 2.Using NLP technology, the data uploaded from the hospital to the infor mation system of the NHI Administration, it will automatically collects the strain name, antibiotic name, antibiotic susceptibility and resistance value. The data collection process includes the following steps: (1)Data classification: Classify the uploaded data into two types: complete and incomplete; (2)Word tokenization: Use Regular Expression to separate the string of co mpleted data into individual words or symbols; (3)Extract key data: From the comparison results of the tokenized data, ext ract the strain name, antibiotic name, antibiotic susceptibility and resistan ce values; (4) Look for the law of data: look for the law of pathogen resistance data, e.g., [antibiotic name][abbreviation of antibiotic][antibiotic susceptibili ty][resistance value]; (5) Compiling data: according to the law of key data, compile data sequen tially; (6) Data integration: output the pattern data and the aggregated data in d ifferent Excel files. Results: 1.High accuracy: Develop AI models to rectify pathogen-themed database s. The correct rate of data compilation can reach 93.88%. 2.Save manpower-time: (1)Non-blood bacterial data: It only takes about 65 hours to collect 240,00 0 pieces of data using this technology. It would take about 1,000 working days to sort out these materials manually. (2)Blood bacteria data: It only takes about 25 hours to collect 60,000 piece s of data using this technology. It would take about 250 working days to s ort out these m
Future Tech | Information & Communications/Machinery & SystemThis technology applies high-voltage wide-bandgap components to the converters used in electric vehicle charging. Due to the high-voltage tolerance and rapid switching characteristics of these components, the technology enables fast charging capabilities for electric vehicles, while also improving system conversion efficiency and power density.
Future Tech | Materials & Chemical Engineering & Nanotech/Electronics & OptoelectronicsComing soon!