bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Potential of Untargeted SWATH Mass Spectrometry-Based Metabolomics to Differentiate Closely Related Exposures in Observational Studies
Authors: Klont Frank , Sosnowski Piotr , Kremer Daan , Knobbe Tim J. , Bonner Ron , Blokzijl Hans , Weersma Rinse K. , Bakker Stephan J. L. , Investigators TransplantLines , Hak Eelko , Touw Daan J. , Hopfgartner Gérard
Published: October 2022

Mass spectrometry (MS) is increasingly used in clinical studies to obtain molecular evidence of chemical exposures, such as tobacco smoke, alcohol, and drugs. This evidence can help verify clinical data retrieved through anamnesis or questionnaires and may provide insights into unreported exposures, for example those classified as the same despite small but possibly relevant chemical differences or due to contaminants in reported exposure compounds. Here, we aimed to explore the potential of untargeted SWATH metabolomics to differentiate such closely related exposures. This data-independent acquisition MS-based profiling technique was applied to urine samples of 316 liver and 570 kidney transplant recipients from the TransplantLines Biobank and Cohort Study (NCT03272841), where we focused on the immunosuppressive drug mycophenolate, which is either supplied as a morpholino-ester prodrug or as an enteric-coated product, the illicit drug cocaine, which is usually supplied as an adulterated product, and the proton pump inhibitors omeprazole and esomeprazole. Based on these examples, we found that untargeted SWATH metabolomics has considerable potential to identify different (unreported) exposure or co-exposure metabolites and may determine variations in their abundances. We also found that these signals alone may sometimes be unable to distinguish closely related exposures, and enhancement of differentiation, for example by integration with pharmacogenomics data, is needed.
Hopomics: Humulus lupulus Brewing Cultivars Classification Based on LC-MS Profiling and Nested Feature Selection
Authors: Ikhalaynen Yuriy Andreevich , Plyushchenko Ivan Victorovich , Rodin Igor Alexandrovich
Published: October 2022

Omics approaches in plant analysis find many different applications, from classification to new bioactive compounds discovery. Metabolomics seems to be one of the most informative ways of describing plants’ phenotypes, since commonly used methods such as liquid chromatography–mass spectrometry (LC-MS) and nuclear magnetic resonance spectroscopy (NMR) could provide a huge amount of information about samples. However, due to high efficiency, many disadvantages arise with the complexity of the experimental design. In the present work, we demonstrate an untargeted metabolomics pipeline with the example of a Humulus lupulus classification task. LC-MS profiling of brewing cultivars samples was carried out as a starting point. Hierarchical cluster analysis (HCA)-based classification in combination with nested feature selection was provided for sample discrimination and marker compounds discovery. Obtained metabolome-based classification showed an expected difference compared to genetic-based classification data. Nine compounds were found to have the biggest classification power during nested feature selection. Using database search and molecular network construction, five of them were identified as known hops bitter compounds.
Multi-Omics, an Integrated Approach to Identify Novel Blood Biomarkers of Alzheimer’s Disease
Authors: François Maxime , Karpe Avinash V. , Liu Jian-Wei , Beale David J. , Hor Maryam , Hecker Jane , Faunt Jeff , Maddison John , Johns Sally , Doecke James D. , Rose Stephen , Leifert Wayne R.
Published: October 2022

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal (CN) and dementia patients diagnosed with MCI or AD, to identify specific cellular pathways and new biomarkers altered with the progression of the disease. We analysed 80 plasma samples from individuals with MCI or AD, as well as age- and gender-matched CN individuals, by utilising mass spectrometry methods and data analyses that included combined pathway analysis and model predictions. Several proteins clearly identified AD from the MCI and CN groups and included plasma actins, mannan-binding lectin serine protease 1, serum amyloid A2, fibronectin and extracellular matrix protein 1 and Keratin 9. The integrated pathway analysis showed various metabolic pathways were affected in AD, such as the arginine, alanine, aspartate, glutamate and pyruvate metabolism pathways. Therefore, our multi-omics approach identified novel plasma biomarkers for the MCI and AD groups, identified changes in metabolic processes, and may form the basis of a biomarker panel for stratifying dementia participants in future clinical trials.
Serum Bile Acid Profiling and Mixed Model Analysis Reveal Biomarkers Associated with Pruritus Reduction in Maralixibat-Treated Patients with BSEP Deficiency
Authors: Zhao Xueheng , Zhang Wujuan , Vig Pamela , Kostrub Cory , Setchell Kenneth D. R.
Published: October 2022

Progressive familial intrahepatic cholestasis (PFIC) is a debilitating disease manifest by severe cholestasis, intractable pruritus and growth delay that ultimately leads to liver failure or transplantation. Maralixibat (MRX) was recently approved for the treatment of cholestatic pruritus in patients with Alagille syndrome. The aim of this study was to determine whether specific changes in the composition of the serum bile acid metabolome could predict pruritus response to treatment. Serum BAs (sBA) and 7α-hydroxy-4-cholesten-3-one (7α-C4), a surrogate marker of BA synthesis, were monitored by ultrahigh-performance liquid chromatography coupled with tandem mass spectrometry over 72 weeks in PFIC patients with mild to moderate non-truncating bile salt export pump (BSEP) mutations (n = 19) treated with MRX. The weekly itch reported outcome observer (ItchRO[Obs]) score measured pruritus severity. Linear mixed models (LMM) were applied to explore the effects of individual sBA profiles and their relationship to pruritus response. Changes in the composition of sBA correlated with pruritus improvement. Notably, the trajectory of serum total and individual BA species and 7α-C4 were significantly associated with ItchRO[Obs] score (p < 0.05). These results reveal that beyond simple total sBA concentrations, specific changes to the BA metabolome are associated with pruritus reduction in patients with BSEP deficiency, thus providing further insight into causal relationship of bile acids and pruritus.
Metabolic Disorders in Menopause
Authors: Jeong Hye Gyeong , Park Hyuntae
Published: October 2022

Menopause is an aging process and an important time equivalent to one-third of a woman’s lifetime. Menopause significantly increases the risk of cardiometabolic diseases, such as obesity, type 2 diabetes, cardiovascular diseases, non-alcoholic liver disease (NAFLD)/metabolic associated fatty liver disease (MFFLD), and metabolic syndrome (MetS). Women experience a variety of symptoms in the perimenopausal period, and these symptoms are distressing for most women. Many factors worsen a woman’s menopausal experience, and controlling these factors may be a strategy to improve postmenopausal women’s health. This review aimed to confirm the association between menopause and metabolic diseases (especially MetS), including pathophysiology, definition, prevalence, diagnosis, management, and prevention.
Microstructure Transformation in Laser Additive Manufactured NiTi Alloy with Quasi-In-Situ Compression
Authors: Yang Xiao , Wang Shuo , Pan Hengpei , Zhang Congyi , Chen Jieming , Zhang Xinyao , Gao Lingqing
Published: October 2022

For NiTi alloys, different additive manufacturing processes may have different compressive recovery capabilities. In particular, there are relatively few studies on the compressive recovery ability of NiTi alloys by the laser-directed energy deposition (LDED) process. In this paper, the compression recovery properties of NiTi alloys with the LDED process were investigated quasi-in-situ by means of transmission electron microscopy, an electron backscatter diffractometer, and focused ion beam–fixed-point sample preparation. The results showed that the material can be completely recovered under 4% deformation and the B19’ martensite phase content and dislocation density are basically unchanged. However, the recovery rate was only 90% and the unrecoverable strain was 0.86% at 8% deformation. Meanwhile, the B19’ martensite phase content and dislocation density of the material increased. Furthermore, with the increase in deformation, the relative dislocation pinning effect of the Ti2Ni precipitated phase in the alloy was enhanced, which reduced the compressive strain recovery to a certain extent.
Simulation Study of FEUDT Structure Optimization and Sensitive Film Loading of SAW Devices
Authors: Bin Shen , Yang Haiyang , Jiang Leiming , Liu Xinlei
Published: October 2022

In order to further improve the degree of frequency response of the surface acoustic wave (SAW) sensor for gas detection, the structure of the forked-finger transducer was analyzed, and its optimal structural parameters were simulated and designed. The simulation model of the unidirectional fork-finger transducer is established by using COMSOL finite element software. The thickness of the piezoelectric substrate, the electrode structure and material, and the thickness of the coating film are optimized and simulated. The results show that: the optimal thickness of the piezoelectric substrate is 3λ. The optimal thickness ratio and the lay-up ratio of the forked-finger electrode are 0.02 and 0.5, respectively. The Al electrode is more suitable as the a forked-finger electrode material compared to Cu, Au and Pt materials. Under the same conditions, the metal oxide-sensitive film (ZnO and TiO2) has a higher frequency response than the polymer-sensitive film (polyisobutylene and polystyrene), and the best sensitive film thickness range is 0.5~1 μm.
A Review of Fault Diagnosis Methods for Rotating Machinery Using Infrared Thermography
Authors: Wang Rongcai , Zhan Xianbiao , Bai Huajun , Dong Enzhi , Cheng Zhonghua , Jia Xisheng
Published: October 2022

At present, rotating machinery is widely used in all walks of life and has become the key equipment in many production processes. It is of great significance to strengthen the condition monitoring of rotating machinery, timely diagnose and eliminate faults to ensure the safe and efficient operation of rotating machinery and improve the economic benefits of enterprises. When the state of a rotating machine deteriorates, the thermal energy that is much more than its normal operation will be generated due to the increase in the friction between the components or other factors. Therefore, using the infrared thermal camera to collect the infrared thermal images of rotating machinery and judge the health status of rotating machinery by observing the temperature distribution in the thermal images is often more rapid and effective than other technologies. Nevertheless, after decades of development, the research achievements of infrared thermography (IRT) and its application in various industrial fields are numerous and complex, and there is a lack of systematic sorting and summary of the achievements in this field. Accordingly, this paper summarizes the development and application of IRT as a non-contact and non-invasive tool for equipment condition monitoring and fault diagnosis, and introduces the basic theory of IRT, image processing technology and fault diagnosis methods of rotating machinery in detail. Finally, the review is summarized and some future potential topics are proposed, which will make the subject easier for beginners and non-experts to understand.
The Effect of Fin Shape on the Heat Transfer and the Solution Time of a Microchannel Evaporator in a CO2 Air Conditioning System—A Numerical Investigation
Authors: Nguyen Tronghieu , Dang Thanhtrung
Published: October 2022

Numerical simulations on the fin shape of a microchannel evaporator in a CO2 air conditioning system were performed at the inlet evaporative temperature of 10 °C and the vapor quality of 0.61. Two types of fin shapes were dealt with: the straight fins and V-fins. The numerical results were verified by the experimental data. For the system under consideration and for the same heat transfer area and the heat transfer coefficient for the air side in the microchannel evaporator, the effect of the fin shape on the heat transfer was not different; however, the solution time and the physical memory for the straight fins were 1.3 and 1.45 times compared with the V-fins, respectively. Therefore, the V-fin shape should be used for numerical simulation to compare it with the straight fin shape. In this study, the evaporation of the refrigerant in the microchannel evaporator took place in four passes. The normal heat flux from the air through the fins and tubes was almost reached at 1550 W/m2 at the evaporative temperature of 10 °C. The results obtained from the experimental data were in good agreement with those obtained from the numerical results, with a deviation of less than 10%.
A Digital Microfluidic RT-qPCR Platform for Multiple Detections of Respiratory Pathogens
Authors: Huang Huitao , Huang Kaisong , Sun Yun , Luo Dasheng , Wang Min , Chen Tianlan , Li Mingzhong , Duan Junwei , Huang Liqun , Dong Cheng
Published: October 2022

The coronavirus disease 2019 pandemic has spread worldwide and caused more than six million deaths globally. Therefore, a timely and accurate diagnosis method is of pivotal importance for controlling the dissemination and expansions. Nucleic acid detection by the reverse transcription-polymerase chain reaction (RT-PCR) method generally requires centralized diagnosis laboratories and skilled operators, significantly restricting its use in rural areas and field settings. The digital microfluidic (DMF) technique provides a better option for simultaneous detections of multiple pathogens with fewer specimens and easy operation. In this study, we developed a novel digital microfluidic RT-qPCR platform for multiple detections of respiratory pathogens. This method can simultaneously detect eleven respiratory pathogens, namely, mycoplasma pneumoniae (MP), chlamydophila pneumoniae (CP), streptococcus pneumoniae (SP), human respiratory syncytial virus A (RSVA), human adenovirus (ADV), human coronavirus (HKU1), human coronavirus 229E (HCoV-229E), human metapneumovirus (HMPV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (FLUA) and influenza B virus (FLUB). The diagnostic performance was evaluated using positive plasmids samples and clinical specimens compared with off-chip individual RT-PCR testing. The results showed that the limit of detections was around 12 to 150 copies per test. The true positive rate, true negative rate, positive predictive value, negative predictive value, and accuracy of DMF on-chip method were 93.33%, 100%, 100%, 99.56%, and 99.85%, respectively, as validated by the off-chip RT-qPCR counterpart. Collectively, this study reported a cost-effective, high sensitivity and specificity on-chip DMF RT-qPCR system for detecting multiple respiratory pathogens, which will greatly contribute to timely and effective clinical management of respiratory infections in medical resource-limited settings.
Development of Finite Element Models of PP, PETG, PVC and SAN Polymers for Thermal Imprint Prediction of High-Aspect-Ratio Microfluidics
Authors: Ciganas Justas , Griskevicius Paulius , Palevicius Arvydas , Urbaite Sigita , Janusas Giedrius
Published: October 2022

Polymeric microstructures and microchannels are widely used in biomedical devices, optics, microfluidics and fiber optics. The quality, the shape, the spacing and the curvature of microstructure gratings are influenced by different mechanisms and fabrication techniques used. This paper demonstrates a cost-effective way for patterning high-aspect-ratio thermoplastic microstructures using thermal imprint technology and finite element modeling. Polymeric materials polypropylene (PP), polyethylene terephthalate glycol (PETG), polyvinyl chloride (PVC) and styrene-acrylonitrile (SAN) were chosen for the experimental investigations. A finite element model was constructed to define the most suitable parameters (time, heating temperature, pressure, etc.) for the formation of microstructures using the thermal imprint procedure. To confirm the relevance of the finite element model, different types of PP, PETG, PVC and SAN microstructures were fabricated using theoretically defined parameters. Experimental investigations of imprinted microstructures’ morphological and optical properties were performed using scanning electron microscopy, atomic force microscopy and a diffractometer. Obtained results confirmed the relevance of the created finite element model which was applied in the formation of high-aspect-ratio microstructures. Application of this model in thermal imprint would not only reduce the fabrication time, but also would highly increase the surface quality and optical properties of the formed structures.
A Siamese Vision Transformer for Bearings Fault Diagnosis
Authors: He Qiuchen , Li Shaobo , Bai Qiang , Zhang Ansi , Yang Jing , Shen Mingming
Published: October 2022

Fault diagnosis methods based on deep learning have progressed greatly in recent years. However, the limited training data and complex work conditions still restrict the application of these intelligent methods. This paper proposes an intelligent bearing fault diagnosis method, i.e., Siamese Vision Transformer, suiting limited training data and complex work conditions. The Siamese Vision Transformer, combining Siamese network and Vision Transformer, is designed to efficiently extract the feature vectors of input samples in high-level space and complete the classification of the fault. In addition, a new loss function combining the Kullback-Liebler divergence both directions is proposed to improve the performance of the proposed model. Furthermore, a new training strategy termed random mask is designed to enhance input data diversity. A comparative test is conducted on the Case Western Reserve University bearing dataset and Paderborn dataset and our method achieves reasonably high accuracy with limited data and satisfactory generation capability for cross-domain tasks.
Rapid Microchip Electrophoretic Separation of Novel Transcriptomic Body Fluid Markers for Forensic Fluid Profiling
Authors: Layne Tiffany R. , Nouwairi Renna L. , Fleming Rachel , Blair Haley , Landers James P.
Published: October 2022

Initial screening of criminal evidence often involves serological testing of stains of unknown composition and/or origin discovered at a crime scene to determine the tissue of origin. This testing is presumptive but critical for contextualizing the scene. Here, we describe a microfluidic approach for body fluid profiling via fluorescent electrophoretic separation of a published mRNA panel that provides unparalleled specificity and sensitivity. This centrifugal microfluidic approach expedites and automates the electrophoresis process by allowing for simple, rotationally driven flow and polymer loading through a 5 cm separation channel; with each disc containing three identical domains, multi-sample analysis is possible with a single disc and multi-sample detection per disc. The centrifugal platform enables a series of sequential unit operations (metering, mixing, aliquoting, heating, storage) to execute automated electrophoretic separation. Results show on-disc fluorescent detection and sizing of amplicons to perform comparably with a commercial ‘gold standard’ benchtop instrument and permitted sensitive, empirical discrimination between five distinct body fluids in less than 10 min. Notably, our microfluidic platform represents a faster, simpler method for separation of a transcriptomic panel to be used for forensically relevant body fluid identification.
Fabrication and Manipulation of Non-Spherical Particles in Microfluidic Channels: A Review
Authors: Jiang Di , Liu Shaowei , Tang Wenlai
Published: October 2022

Non-spherical shape is a general appearance feature for bioparticles. Therefore, a mechanical mechanism study of non-spherical particle migration in a microfluidic chip is essential for more precise isolation of target particles. With the manipulation of non-spherical particles, refined disease detection or medical intervention for human beings will be achievable in the future. In this review, fabrication and manipulation of non-spherical particles are discussed. Firstly, various fabrication methods for non-spherical microparticle are introduced. Then, the active and passive manipulation techniques for non-spherical particles are briefly reviewed, including straight inertial microchannels, secondary flow inertial microchannels and deterministic lateral displacement microchannels with extremely high resolution. Finally, applications of viscoelastic flow are presented which obviously increase the precision of non-spherical particle separation. Although various techniques have been employed to improve the performance of non-spherical particle manipulation, the universal mechanism behind this has not been fully discussed. The aim of this review is to provide a reference for non-spherical particle manipulation study researchers in every detail and inspire thoughts for non-spherical particle focused device design.
A Dielectric Elastomer Actuator-Driven Vibro-Impact Crawling Robot
Authors: Wu Chuang , Yan Huan , Cai Anjiang , Cao Chongjing
Published: October 2022

Over the last decade, many bio-inspired crawling robots have been proposed by adopting the principle of two-anchor crawling or anisotropic friction-based vibrational crawling. However, these robots are complicated in structure and vulnerable to contamination, which seriously limits their practical application. Therefore, a novel vibro-impact crawling robot driven by a dielectric elastomer actuator (DEA) is proposed in this paper, which attempts to address the limitations of the existing crawling robots. The novelty of the proposed vibro-impact robot lies in the elimination of anchoring mechanisms or tilted bristles in conventional crawling robots, hence reducing the complexity of manufacturing and improving adaptability. A comprehensive experimental approach was adopted to characterize the performance of the robot. First, the dynamic response of the DEA-impact constraint system was characterized in experiments. Second, the performance of the robot was extensively studied and the fundamental mechanisms of the vibro-impact crawling locomotion were analyzed. In addition, effects of several key parameters on the robot’s velocity were investigated. It is demonstrated that our robot can realize bidirectional motion (both forward and backward) by simple tuning of the key control parameters. The robot demonstrates a maximum forward velocity of 21.4 mm/s (equivalent to 0.71 body-length/s), a backward velocity of 16.9 mm/s, and a load carrying capacity of 9.5 g (equivalent to its own weight). The outcomes of this paper can offer guidelines for high-performance crawling robot designs, and have potential applications in industrial pipeline inspections, capsule endoscopes, and disaster rescues.
Research on Continuous Error Compensation of a Sub-Arc-Second Macro/Micro Dual-Drive Rotary System
Authors: Yang Manzhi , Li Linyue , Zhang Chuanwei , Huang Yumei , Wu Hongzhang , Feng Bin
Published: October 2022

In this paper, a sub-arc-second macro/micro dual-drive rotary system is designed, and the continuous compensation of the system error and its experimental research are completed. First, the macro-drive system is driven by a direct-drive motor, and the micro-drive system uses a piezoelectric ceramic to drive the micro-drive rotary mechanism; the system uses a micro-drive system to compensate the motion error of the macro-drive system, and uses circular grating to feedback the displacement of the macro/micro total output turntable to form a macro/micro dual-drive closed-loop control system. Second, based on the establishment of the system error model, the design of the system’s continuous error compensation scheme is completed. Finally, the positioning accuracy testing of the system, direct error compensation of the macro-drive, manual error compensation of the macro-drive, error compensation performance of the micro-drive part and macro/micro compensation of the system are carried out in the study. The results show that the repeated positioning error and the positioning error of the system are reduced by 78.8% and 95.2%, respectively, after macro/micro compensation. The correctness and effectiveness of the designed system design, error compensation and control method are verified through performance tests, and its positioning accuracy is verified to the sub-arc-second (0.1 arcsecond) level. The research in this paper has important reference value for the development of ultra-precision macro/micro dual-drive technology.
Towards an Innovative Sensor in Smart Capsule for Aerial Drones for Blood and Blood Component Delivery
Authors: Liu Rongrong , Pitruzzello Giorgio , Rosa Mafalda , Battisti Antonella , Cerri Chiara , Tortora Giuseppe
Published: October 2022

Aerial drone technology is currently being investigated worldwide for the delivery of blood components. Although it has been demonstrated to be safe, the delivered medical substances still need to be analyzed at the end of the flight mission to assess the level of haemolysis and pH prior to the use in a patient. This process can last up to 30 min and prevent the time saved using drone delivery. Our study aims to integrating an innovative sensor for the haemolysis and pH detection into the Smart Capsule, an already demonstrated technology capable of managing transfusion transport through drones. In the proposed scenario, the haemolysis is evaluated optically by a minilysis device using LED–photodetector combination. The preliminary validation has been demonstrated for both the thermal stability of the Smart Capsule and the haemolysis detection of the minilysis device prototype. Firstly, the onboard temperature test has shown that the delivery system is capable of maintaining proper temperature, even though the samples have been manipulated to reach a higher temperature before inserting into the Smart Capsule. Then, in the laboratory haemolysis test, the trend of linear regression between the outputs from the spectrophotometer and the minilysis prototype confirmed the concept design of the minilysis device.
A Glass–Ultra-Thin PDMS Film–Glass Microfluidic Device for Digital PCR Application Based on Flexible Mold Peel-Off Process
Authors: Xia Yanming , Chu Xianglong , Zhao Caiming , Wang Nanxin , Yu Juan , Jin Yufeng , Sun Lijun , Ma Shenglin
Published: October 2022

The microfluidic device (MFD) with a glass–PDMS–glass (G-P-G) structure is of interest for a wide range of applications. However, G-P-G MFD fabrication with an ultra-thin PDMS film (especially thickness less than 200 μm) is still a big challenge because the ultra-thin PDMS film is easily deformed, curled, and damaged during demolding and transferring. This study aimed to report a thickness-controllable and low-cost fabrication process of the G-P-G MFD with an ultra-thin PDMS film based on a flexible mold peel-off process. A patterned photoresist layer was deposited on a polyethylene terephthalate (PET) film to fabricate a flexible mold that could be demolded softly to achieve a rigid structure of the glass–PDMS film. The thickness of ultra-thin patterned PDMS could reach less than 50 μm without damage to the PDMS film. The MFD showcased the excellent property of water evaporation inhibition (water loss < 10%) during PCR thermal cycling because of the ultra-thin PDMS film. Its low-cost fabrication process and excellent water evaporation inhibition present extremely high prospects for digital PCR application.
Anticipative QoS Control: A Self-Reconfigurable On-Chip Communication
Authors: Tsai Wen-Chung , Lin Hsiao-En , Lan Ying-Cherng , Chen Sao-Jie
Published: October 2022

A self-reconfigurable Network-on-Chip (NoC) architecture that supports anticipative Quality of Service (QoS) control with penetrative switch ability is proposed to enhance the performance of bidirectional-channel NoC communication while supporting prioritized packet transmission services. The anticipative QoS control not only allows each communication channel to be dynamically self-configured to transmit flits in either direction for a better channel utilization of on-chip hardware resources, but also enhances the latency performance for QoS services. The proposed anticipative control is based on penetratingly observing channel direction requests of routers that is two hops away from the current one. The added ability enables a router to allocate high-priority packets to a dedicated virtual channel and then rapidly bypass it to the next destination router. The provided flexibility of packet switch promises better channel bandwidth utilization, lower packet delivery latency, and furthermore guarantees the high-priority packets being served with a better QoS. Accordingly, in this paper, an enhanced NoC architecture supporting the hybrid anticipative QoS, penetrative switch, and bidirectional-channel control, namely Anticipative QoS Bidirectional-channel NoC (AQ-BiNoC) is presented. Tested with cycle-accurate synthetic traffic patterns, significant performance enhancement has been observed when the proposed AQ-BiNoC architecture is compared against conventional NoC designs.
Vertical Graphene-Based Biosensor for Tumor Cell Dielectric Signature Evaluation
Authors: Tincu Bianca , Burinaru Tiberiu , Enciu Ana-Maria , Preda Petruta , Chiriac Eugen , Marculescu Catalin , Avram Marioara , Avram Andrei
Published: October 2022

The selective and rapid detection of tumor cells is of critical consequence for the theragnostic field of tumorigenesis; conventional methods, such as histopathological diagnostic methods, often require a long analysis time, excessive analytical costs, complex operations, qualified personnel and deliver many false-positive results. We are considering a new approach of an electrochemical biosensor based on graphene, which is evidenced to be a revolutionary nanomaterial enabling the specific and selective capture of tumor cells. In this paper, we report a biosensor fabricated by growing vertically aligned graphene nanosheets on the conductive surface of interdigitated electrodes which is functionalized with anti-EpCAM antibodies. The dielectric signature of the three types of tumor cells is determined by correlating the values from the Nyquist and Bode diagram: charge transfer resistance, electrical double layer capacity, Debye length, characteristic relaxation times of mobile charges, diffusion/adsorption coefficients, and variation in the electrical permittivity complex and of the phase shift with frequency. These characteristics are strongly dependent on the type of membrane molecules and the electromagnetic resonance frequency. We were able to use the fabricated sensor to differentiate between three types of tumor cell lines, HT-29, SW403 and MCF-7, by dielectric signature. The proposed evaluation method showed the permittivity at 1 MHz to be 3.63 nF for SW403 cells, 4.97 nF for HT 29 cells and 6.9 nF for MCF-7 cells.
Learning-Based Repetitive Control of a Bowden-Cable-Actuated Exoskeleton with Frictional Hysteresis
Authors: Shi Yunde , Guo Mingqiu , Hui Chang , Li Shilin , Ji Xiaoqiang , Yang Yuan , Luo Xiang , Xia Dan
Published: October 2022

Bowden-cable-actuated soft exoskeleton robots are known for their light weight and flexibility of power transmission during rehabilitation training or movement assistance for humans. However, friction-induced nonlinearity of the Bowden transmission cable and gearbox backlash pose great challenges forprecise tracking control of the exoskeleton robot. In this paper, we proposed the design of a learning-based repetitive controller which could compensate for the non-linearcable friction and gearbox backlash in an iterative manner. Unlike most of the previous control schemes, the presented controller does not require apriori knowledge or intensive modeling of the friction and backlash inside the exoskeleton transmission system. Instead, it uses the iterative learning control (ILC)to adaptively update the reference trajectory so that the output hysteresis caused by friction and backlashis minimized. In particular, a digital phase-lead compensator was designed and integrated with the ILC to address the issue of backlash delay and improve the stability and tracking performance. Experimental results showed an average of seven iterations for the convergence of learning and a 91.1% reduction in the RMS tracking error (~1.37 deg) compared with the conventional PD control. The proposed controller design offers promising options for the realization of lightweight, wearable exoskeletons with high tracking accuracies.
Recent Advances in MEMS-Based 3D Hemispherical Resonator Gyroscope (HRG)—A Sensor of Choice
Authors: Ranji Ahmad Rahbar , Damodaran Vijayakanthan , Li Kevin , Chen Zilang , Alirezaee Shahpour , Ahamed Mohammed Jalal
Published: October 2022

Macro-scale, hemispherical-shaped resonating gyroscopes are used in high-precision motion and navigation applications. In these gyroscopes, a 3D wine-glass, hemispherical-shaped resonating structure is used as the main sensing element. Motivated by the success of macroscale hemispherical shape gyroscopes, many microscale hemispherical-shaped resonators have been produced due to the rapid advancement in semiconductor-based microfabrication technologies. The dynamic performance of hemispherical resonators depends on the degree of symmetry, uniformity of thickness, and surface smoothness, which, in turn, depend on the type of materials and fabrication methods. The main aim of this review paper is to summarize the materials, characterization and fabrication methods reported in the literature for the fabrication of microscale hemispherical resonator gyroscopes (µHRGs). The theory behind the development of HRGs is described and advancements in the fabrication of microscale HRGs through various semiconductor-based fabrication techniques are outlined. The integration of electrodes with the hemispherical structure for electrical transduction using other materials and fabrication methods is also presented. A comparison of different materials and methods of fabrication from the point of view of device characteristics and dynamic performance is discussed. This review can help researchers in their future research and engineers to select the materials and methods for µHRG development.
Generation and Modulation of Controllable Multi-Focus Array Based on Phase Segmentation
Authors: Liu Zihan , Hou Jiaqing , Zhang Yu , Wen Tong , Fan Lianbin , Zhang Chen , Wang Kaige , Bai Jintao
Published: October 2022

A Circular-Sectorial Phase Segmentation (CSPS) noniterative method for effectively generating and manipulating muti-focus array (MFA) was proposed in this work. The theoretical model of the CSPS was built up based on vectorial diffraction integral and the phase modulation factor was deduced with inverse fast Fourier transform. By segmenting the entrance pupil into specified regions, which were sequentially assigned with the values carried out by phase modulation factor, the methodology could generate flexible MFAs with desired position and morphology. Subsequently, the CSPS was investigated in parallelized fabrication with a laser direct writing system. The positioning accuracy was greater than 96% and the morphologic consistency of the parallelly fabricated results was greater than 92%.
Deep Learning for Clothing Style Recognition Using YOLOv5
Authors: Chang Yeong-Hwa , Zhang Ya-Ying
Published: October 2022

With the rapid development of artificial intelligence, much more attention has been paid to deep learning. However, as the complexity of learning algorithms increases, the needs of computation power of hardware facilities become more crucial. Instead of the focus being on computing devices like GPU computers, a lightweight learning algorithm could be the answer for this problem. Cross-domain applications of deep learning have attracted great interest amongst researchers in academia and industries. For beginners who do not have enough support with software and hardware, an open-source development environment is very helpful. In this paper, a relatively lightweight algorithm YOLOv5s is addressed, and the Google Colab is used for model training and testing. Based on the developed environment, many state-of-art learning algorithms can be studied for performance comparisons. To highlight the benefits of one-stage object detection algorithms, the recognition of clothing styles is investigated. The image samples are selected from datasets of fashion clothes and the web crawling of online stores. The image data are categorized into five groups: plaid; plain; block; horizontal; and vertical. Average precison, mean average precison, recall, F1-score, model size, and frame per second are the metrics used for performance validations. From the experimental outcomes, it shows that YOLOv5s is better than other learning algorithms in the recognition accuracy and detection speed.
Simulations and Experiments on the Vibrational Characteristics of Cylindrical Resonators with First Three Harmonic Errors
Authors: Liang Chen , Yang Kaiyong , Pan Yao , Tao Yunfeng , Li Jingyu , Jin Shilong , Luo Hui
Published: October 2022

A cylindrical resonator gyroscope is a kind of Coriolis gyroscope, which measures angular velocity or angle via processing of the standing wave. The symmetry of a cylindrical resonator is destroyed by different degrees of geometric nonuniformity and structural damage in the machining process. The uneven mass distribution caused by the asymmetry of the resonator can be expressed in the form of a Fourier series. The first three harmonics will reduce the anti-interference ability of the resonator to the external vibration, as well as increase the angular random walk and zero-bias drift of the gyroscope. In this paper, the frequency split of different modes caused by the first three harmonic errors and the displacement of the center of the cylindrical resonator bottom plate are obtained by simulation, and the relationship between them is explored. The experimental results on five fused silica cylindrical resonators are consistent with the simulation, confirming the linear relationship between the n = 1 frequency split and second harmonic error. A method for evaluating the first three harmonic errors of fused silica cylindrical resonators is provided.
Design and Implementation of a Prosthesis System Controlled by Electromyographic Signals Means, Characterized with Artificial Neural Networks
Authors: Tinoco-Varela David , Ferrer-Varela Jose Amado , Cruz-Morales Raúl Dalí , Padilla-García Erick Axel
Published: October 2022

Around the world many people loss a body member for many reasons, where advances of technology may be useful to help these people to improve the quality of their lives. Then, designing a technologically advanced prosthesis with natural movements is worthy for scientific, commercial, and social reasons. Thus, research of manufacturing, designing, and signal processing may lead up to a low-cost affordable prosthesis. This manuscript presents a low-cost design proposal for an electromyographic electronic system, which is characterized by a neural network based process. Moreover, a hand-type prosthesis is presented and controlled by using the processed electromyographic signals for a required particular use. For this purpose, the user performs several movements by using the healthy-hand to get some electromyographic signals. After that, the obtained signals are processed in a neural network based controller. Once an usable behavior is obtained, an exact replica of controlled motions are adapted for the other hand by using the designed prosthesis. The characterization process of bioelectrical signals was performed by training twenty characteristics obtained from the original raw signal in contrast with other papers in which seven characteristics have been tested on average. The proposed model reached a 95.2% computer test accuracy and 93% accuracy in a real environment experiment. The platform was tested via online and offline, where the best response was obtained in the online execution time.
Micromanufactured Tactile Samples for Characterization of Rough and Dry Tactile Perception
Authors: Yanagibashi Keiichiro , Miki Norihisa
Published: October 2022

The quantitative characterization of tactile perception, which is crucial in the design of tactile devices, requires the tested samples to have individually and precisely controlled properties associated with the senses. In this work, we microfabricated such tactile samples and then quantitatively characterized tactile perception with a focus on roughness and dryness. In the roughness perception experiments, the tactile samples had a stripe pattern with ridge and groove widths that were individually controlled. The experimental results revealed that the feeling of roughness was more dominated by the width of the groove than that of the ridge and that conventionally used roughness parameters such as Sa and Sq were not sufficient for predicting roughness perception. In the dryness perception experiments, the tactile samples had a micropattern formed by dry etching and an array of squares. The experimental results revealed that dry perception had different properties when the feature sizes were below and above 30 µm, which may have been due to the effect of adhesion on friction. The proposed tactile samples were suitable for the quantitative and precise characterization of tactile perception.
Hybrid Bipedal Locomotion Based on Reinforcement Learning and Heuristics
Authors: Wang Zhicheng , Wei Wandi , Xie Anhuan , Zhang Yifeng , Wu Jun , Zhu Qiuguo
Published: October 2022

Locomotion control has long been vital to legged robots. Agile locomotion can be implemented through either model-based controller or reinforcement learning. It is proven that robust controllers can be obtained through model-based methods and learning-based policies have advantages in generalization. This paper proposed a hybrid framework of locomotion controller that combines deep reinforcement learning and simple heuristic policy and assigns them to different activation phases, which provides guidance for adaptive training without producing conflicts between heuristic knowledge and learned policies. The training in simulation follows a step-by-step stochastic curriculum to guarantee success. Domain randomization during training and assistive extra feedback loops on real robot are also adopted to smooth the transition to the real world. Comparison experiments are carried out on both simulated and real Wukong-IV humanoid robots, and the proposed hybrid approach matches the canonical end-to-end approaches with higher rate of success, faster converging speed, and 60% less tracking error in velocity tracking tasks.
The Molecular Characterization of Nosocomial Carbapenem-Resistant Klebsiella pneumoniae Co-Harboring blaNDM and blaOXA-48 in Jeddah
Authors: Alhazmi Wafaa , Al-Jabri Ahmed , Al-Zahrani Ibrahim
Published: October 2022

Carbapenem-resistant Klebsiella pneumoniae (CRKP)-associated infections have become a major concern and life-threatening worldwide. Understanding the epidemiology of CRKP using a reliable molecular technology can help to develop an effective infection control policies. In the western region of Saudi Arabia, there are no sufficient data on the prevalence of CRKP and its carbapenem-resistant determinants. Therefore, this study aimed to determine the molecular epidemiology of CRKP and identify the most common carbapenemase genes. In the current study, a total of 191 CRKP isolates were collected and obtained from clinical specimens of patients at King Fahad Armed Forces Hospital (KFAFH), Jeddah, Saudi Arabia. All isolates that were resistant or intermediately susceptible to either of the carbapenem antimicrobials (imipenem, meropenem, or ertapenem) were included. All CRKP showed resistance to ceftazidime, cefepime, and piperacillin/tazobactam, whereas low (14%) and moderate (37.7%) levels of resistance were reported against tigecycline and colistin, respectively. The most common carbapenemase genes identified were blaOXA-48 (n = 157 [82.2%]), followed by blaNDM in 27 (14%) isolates. The blaVIM and blaKPC were reported in only one isolate each and no blaIMP producers were detected among all tested isolates. The high prevalence of OXA-48 among K. pneumoniae isolates reported in the current study may reflect that OXA-48 has become an endemic in Saudi Arabian hospitals. The second major finding was that the identification of CRKP co-harbors both blaNDM and blaOXA-48, and such isolates can be threating for healthcare societies (patients and healthcare workers) due to their high level of resistance to carbapenems. These results suggest that the use of molecular diagnostic methods and proper surveillance programs are required to monitor and control the spread of all multidrug-resistant (MDR) bacteria, including CRKP. Therefore, further research is recommended to expand the study and further analyze the genotyping of the most common clones of CRKP in other hospitals in the western regions of Saudi Arabia.
Epidemiological and Clinical Characteristics of Non-Typhoidal Salmonella Bloodstream Infections in Central Israel: A Case-Control Study
Authors: Israel Yael , Muhsen Khitam , Rokney Assaf , Adler Amos
Published: October 2022

Non-typhoidal Salmonella (NTS) infection continues to be a significant cause of morbidity. In addition to gastroenteritis (GE), NTS may cause bloodstream infections (BSI). Our goals were to characterize the demographics, clinical characteristics and outcome of NTS-BSI in central Israel. The study was a retrospective, case-control study conducted at the Tel Aviv Sourasky Medical Center between 2001–2018. Cases with NTS-BSI were matched by age and compared with two control groups, hospitalized patients with NTS-GE and patients with E. coli BSI. The NTS-BSI group included 34 patients who were compared with 69 and 68 patients in the NTS-GE and E. coli BSI groups, respectively. In the NTS-BSI group, the median age was 59 years, with 20% of patients below 20 years of age. Diarrhea was less common in NTS-BSI patients compared with NTS-GE: 53% vs. 80% (p < 0.01). Compared with NTS-GE patients, NTS-BSI patients had a higher rate of recent antimicrobial use: 21% vs. 5.9%, p = 0.03, respectively. They also had a slightly higher Charlson Comorbidity Index score, and history of past malignancy and steroid use, but these differences were not statistically significant. Antimicrobial treatment was documented in 30/34 of the NTS-BSI patients vs. 55/69 of the NTS-GE patients (p < 0.001). NTS-BSI patients had higher rates of in-hospital death (23% vs. 4%, p < 0.01) and a longer length of stay (8 vs. 4 days, p < 0.001) compared with NTS-GE. There was no significant difference in the outcome compared with the E. coli BSI group. In conclusion, our study found relatively low rates of pediatric cases compared with previous studies in Israel. NTS-BSI patients had slightly higher rates of comorbidities compared with NTS-GE patients, and a similar prognosis to E. coli BSI patients.