Computational Devices Research Articles

THE VISUAL LOAD DUE TO MAN-MACHINE WORK (COMPUTER, DIGITAL DEVICES)

Prolonged use of computers and digital devices can lead to various physical and mental health problems. This study sought to assess computer and digital device ergonomics (CDDE) of designers, photographers, IT professionals, accountants and suppliers in several Bulgarian firms and to determine the visual (VS) and musculoskeletal (MS) symptoms reported by the respondents. In the study, a survey was made, through a survey, using a Google Form. 42 participants were surveyed, within two weeks, in 3 age groups: up to 30 years, from 30 to 40 years and over 40 years. A significant proportion of employees reported various symptoms of VS and MS. The most affected parts of the body are identified: neck, arm/shoulder/wrist and waist. Special attention is paid to eye strain, and the symptomatology is most often related to visual symptoms, such as eye fatigue, eye pain, sensitivity to light, and others. The research covers significant issues related to health care and the importance of ergonomics in practice.

Peningkatan Pemahaman Teknologi Internet Sehat Bagi Siswa Sekolah Dasar

Community Service (PKM) is one form of the Tridharma of Higher Education. This PKM is proposed to carry out socialization and educational activities at Madrasah Ibtidaiyah Budi Mulya in West Pademangan, North Jakarta City. This activity is proposed to educate elementary school students about healthy internet use. This activity is carried out by observing that internet use in the student environment is very difficult to inhibit or limit. In today's modern era, internet use can not only be done via computer devices, but can also be accessed via smart devices or smartphones. So it is increasingly difficult to control children's use of the internet. However, many internet users are not aware of the dangers of negative impacts from the internet. Therefore, it is necessary to increase vigilance and awareness of the dangers of the negative impacts of the internet which are unconsciously carried out by internet users, especially students in elementary schools. Based on these problems, the idea of socializing and educating healthy internet use for elementary school students could be one of disseminating knowledge and training regarding healthy internet use for education and for students.

Reconfigurable spintronic logic gate utilizing precessional magnetization switching

In traditional von Neumann computing architecture, the efficiency of the system is often hindered by the data transmission bottleneck between the processor and memory. A prevalent approach to mitigate this limitation is the use of non-volatile memory for in-memory computing, with spin–orbit torque (SOT) magnetic random-access memory (MRAM) being a leading area of research. In this study, we numerically demonstrate that a precise combination of damping-like and field-like spin–orbit torques can facilitate precessional magnetization switching. This mechanism enables the binary memristivity of magnetic tunnel junctions (MTJs) through the modulation of the amplitude and width of input current pulses. Building on this foundation, we have developed a scheme for a reconfigurable spintronic logic gate capable of directly implementing Boolean functions such as AND, OR, and XOR. This work is anticipated to leverage the sub-nanosecond dynamics of SOT-MRAM cells, potentially catalyzing further experimental developments in spintronic devices for in-memory computing.

A Novel Feature Selection Approach-Based Sampling Theory on Grapevine Images Using Convolutional Neural Networks

AbstractFeature selection, reducing number of input variables to develop classification model, is an important process to reduce computational and modeling complexity and affects the performance of image process. In this paper, we have proposed new statistical approaches for feature selection based on sample selection. We have applied our new approaches to grapevine leaves data that possess properties of shape, thickness, featheriness, and slickness that are investigated in images. To analyze such kind of data by using image process, thousands of features are created and selection of features plays important role to predict the outcome properly. In our numerical study, convolutional neural networks have been used as feature extractors and then obtained features from the last average pooling layer to detect the type of grapevine leaves from images. These features have been reduced by using our suggested four statistical methods: simple random sampling, ranked set sampling, extreme ranked set sampling, moving extreme ranked set sampling. Then, selected features have been classified with artificial neural network and we obtained the best accuracy of 97.33% with our proposed approaches. Based on our empirical analysis, it has been determined that the proposed approach exhibits efficacy in the classification of grapevine leaf types. Furthermore, it possesses the potential for integration into various computational devices.

Cloud-edge-end-based aircraft assembly production quality monitoring system framework and applications

In recent years, the increasing complexity of quality control in aircraft assembly has necessitated the development of innovative and integrated solutions. This paper introduces a novel framework based on cloud-edge-end architecture to enhance quality monitoring systems in aircraft assembly production. The framework consists of five parts: cloud, edge, end, network, and the trained model. By leveraging the advantages of cloud computing, edge computing, and terminal devices, this framework aims to provide a comprehensive, real-time, and efficient quality monitoring solution. Key technologies within the cloud-edge-end framework are proposed, including data collection, storage, and transmission, deep learning methods based on Channel Attention Convolutional Neural Network (CACNN), and feedback mechanisms from the cloud layer to the lower layers. These innovations enable effective information sharing and utilization at various stages of the aircraft assembly process, providing operational managers with timely and accurate insights into assembly quality. A prototype system application has been implemented at an aircraft assembly site, facilitating process data monitoring and assembly status analysis. Experimental validation of the proposed CACNN algorithm has demonstrated its capability to monitor hole diameters online. Various case studies confirm the framework's effectiveness, showcasing substantial improvements in monitoring accuracy and operational efficiency.

CYBER CRIME CYBERSTALKING THROUGH THE CYBER LAW FORENSIC SCIENCE AND CRIMINAL INVESTIGATION

As it is well known, the usage of the internet and mobile phones has entirely turned this world into a virtual one. In this virtual setting, Pandemic 2020 offers a fresh viewpoint on human existence. IT now serves as a crucial organ for survival. Not only has information technology expanded the sphere of development, but it has also turned into an axis for global development. People may quickly and easily access a variety of information in the virtual world. However, everything has two sides, just like a coin, and the development of information technology has sped up the growth of cybercrime everywhere. Cyber stalking is the act of following someone using a computer or other device connected to one, which can instil terror in the victim. A relatively modern form of cybercrime is cyber stalking. The study focuses about the meaning, nature, typology and history of cyber stalking.. This thesis compares the law relating to cyber stalking in India with different foreign countries. This thesis also discussed about the reported cases of cyber stalking from 2017-2020 as per the data of NCRB. Reason and effect of cyber staling has also been discussed in this study. Scholar suggests that there is the need of amendment of current laws specifically for the gender neutral laws and law which add the issues of international jurisdiction. Study also suggest that self-awareness is also needed for safeguard ourselves from such crimes. Digital technology is encompassing in all walks of life, all over the world and has brought the real meaning of globalization. At the one end cyber system provides opportunities to communicate and at the other end some individuals or community exploit its power for criminal purposes. Criminals exploit the Internet and other network communications which are international in scope. Situation is alarming; Cybercrime is an upcoming and is talk of the town in every field of the society/system. Theoretically and practically this is a new subject for researchers and is growing exponentially. Lot of work has been done and endless has to be go because the invention or up gradation of new technology leads to the technical crime i.e. the digital or we can say the cybercrime or e-crime. This is because every day a new technique is being developed for doing the cybercrime and many times, we are not having the proper investigating method/model/technique to tackle that newly cybercrime. Cybercrime is a criminal activity in which computers or computer networks are used as a tool, a target, or a place of criminal activity and includes everything from electronic cracking to denial of service attacks. It is also used to include traditional crimes in which computers or networks are used to enable the illicit activity.

A Health-Related Quality of Life Measure for Patients Who Undergo Minimally Invasive Glaucoma Surgery

PurposeTo develop a standardized patient-reported outcome measure to assess the impact of glaucoma and treatment, including minimally invasive glaucoma surgery (MIGS), on health-related quality of life (HRQOL). DesignObservational study before and after concomitant cataract and FDA-approved implantable MIGS device surgery to provide information on the measure's performance in assessing HRQOL. Methods SettingSurvey administration was done by electronic patient-reported outcomes (ePRO) application to patients at multiple sites on a computer, iPad, or similar device. Patient PopulationOne hundred eighty-four adults completed a baseline survey, 124 completed a survey 3 months after surgery, and 106 completed the 1-month test-retest reliability survey. The age range was 37-89, and the average age was 72. Most of the respondents were female (57%), non-Hispanic White (81%), and had a college degree (56%). Main Outcome MeasuresThe Glaucoma Outcomes Survey (GOS) includes 42 questions assessing functional limitations (27 items), vision-related symptoms (7 items), psychosocial issues (7 items) and satisfaction with microinvasive glaucoma surgery (1 item). The three multiple-item scales were scored on a 0-100 range, with a higher score indicating worse health. ResultsInternal consistency reliability estimates ranged from 0.75 (vision-related symptoms) to 0.93 (functional limitations) and one-month test-retest intraclass correlations ranged from 0.65 (PROMIS global mental health) to 0.92 (functional limitations). Product-moment correlations among the GOS scales ranged from 0.56 to 0.60. Improvement in visual acuity in the study eye from baseline to the 3-month follow-up was significantly related to improvements in GOS functional limitations (r =0.18, p =0.0485), vision-related symptoms (r = 0.19, p = 0.0386), and psychosocial concerns (r = 0.18, p =0.0503). The highest proportion of responders to treatment was seen for the GOS functional limitations scale (48%), followed by GOS psychosocial issues (21%) and GOS vision-related symptoms (17%). ConclusionsThis study provides initial support for using the GOS instrument in ophthalmic procedures such as MIGS. Further evaluation of the GOS in other samples, including different patient subgroups and clinical settings, will be valuable. The instrument may be useful for evaluations of other treatments for glaucoma.

The effects of radiofrequency exposure on male fertility: A systematic review of human observational studies with dose–response meta-analysis

BackgroundThe World Health Organization (WHO) is bringing together evidence on radiofrequency electromagnetic field (RF-EMF) exposure in relation to health outcomes, previously identified as priorities for research and evaluation by experts in the field, to inform exposure guidelines. A suite of systematic reviews have been undertaken by a network of topic experts and methodologists to collect, assess and synthesise data relevant to these guidelines. Following the WHO handbook for guideline development and the COSTER conduct guidelines, we systematically reviewed the evidence on the potential effects of RF-EMF exposure on male fertility in human observational studies. MethodsWe conducted a broad and sensitive search for potentially relevant records within the following bibliographic databases: MEDLINE; Embase; Web of Science and EMF Portal. We also conducted searches of grey literature through relevant databases including OpenGrey, and organisational websites and consulted RF-EMF experts. We hand searched reference lists of included study records and for citations of these studies. We included quantitative human observational studies on the effect of RF-EMF exposure in adult male participants on infertility: sperm concentration; sperm morphology; sperm total motility; sperm progressive motility; total sperm count; and time to pregnancy. Titles and abstracts followed by full texts were screened in blinded duplicate against pre-set eligibility criteria with consensus input from a third reviewer as required. Data extraction from included studies was completed by two reviewers, as was risk of bias assessment using the Office of Health Assessment and Translation (OHAT) tool. We conducted a dose–response meta-analysis as possible and appropriate. Certainty of the evidence was assessed by two reviewers using the OHAT GRADE tool with input from a third reviewer as required. ResultsWe identified nine studies in this review; seven were general public studies (with the general public as the population of interest) and two were occupational studies (with specific workers/workforces as the population of interest).General public studies.Duration of phone use: The evidence is very uncertain surrounding the effects of RF-EMF on sperm concentration (10/6 mL) (MD (mean difference) per hour of daily phone use 1.6 106/mL, 95 % CI −1.7 to 4.9; 3 studies), sperm morphology (MD 0.15 percentage points of deviation of normal forms per hour, 95 % CI −0.21 to 0.51; 3 studies), sperm progressive motility (MD −0.46 percentage points per hour, 95 % CI −1.04 to 0.13; 2 studies) and total sperm count (MD per hour −0.44 106/ejaculate, 95 % CI −2.59 to 1.7; 2 studies) due to very low-certainty evidence. Four additional studies reported on the effect of mobile phone use on sperm motility but were unsuitable for pooling; only one of these studies identified a statistically significant effect. All four studies were at risk of exposure characterisation and selection bias; two of confounding, selective reporting and attrition bias; three of outcome assessment bias and one used an inappropriate statistical method.Position of phone: There may be no or little effect of carrying a mobile phone in the front pocket on sperm concentration, total count, morphology, progressive motility or on time to pregnancy.Of three studies reporting on the effect of mobile phone location on sperm total motility and, or, total motile count, one showed a statistically significant effect. All three studies were at risk of exposure characterisation and selection bias; two of confounding, selective reporting and attrition bias; three of outcome assessment bias and one used inappropriate statistical method.RF-EMF Source: One study indicates there may be little or no effect of computer or other electric device use on sperm concentration, total motility or total count. This study is at probably high risk of exposure characterisation bias and outcome assessment bias.Occupational studies.With only two studies of occupational exposure to RF-EMF and heterogeneity in the population and exposure source (technicians exposed to microwaves or seamen exposed to radar equipment), it was not plausible to statistically pool findings. One study was at probably or definitely high risk of bias across all domains, the other across domains for exposure characterisation bias, outcome assessment bias and confounding. DiscussionThe majority of evidence identified was assessing localised RF-EMF exposure from mobile phone use on male fertility with few studies assessing the impact of phone position. Overall, the evidence identified is very uncertain about the effect of RF-EMF exposure from mobile phones on sperm outcomes. One study assessed the impact of other RF-EMF sources on male fertility amongst the general public and two studies assessed the impact of RF-EMF exposure in occupational cohorts from different sources (radar or microwave) on male fertility.Further prospective studies conducted with greater rigour (in particular, improved accuracy of exposure measurement and appropriate statistical method use) would build the existing evidence base and are required to have greater certainty in any potential effects of RF-EMF on male reproductive outcomes. Prospero Registration: CRD42021265401 (SR3A)

Development of a novel self-healing Zn(II)-metallohydrogel with wide bandgap semiconducting properties for non-volatile memory device application

A rapid and effective strategy has been devised for the swift development of a Zn(II)-ion-based supramolecular metallohydrogel, termed Zn@PEH, using pentaethylenehexamine as a low molecular weight gelator. This process occurs in an aqueous medium at room temperature and atmospheric pressure. The mechanical strength of the synthesized Zn@PEH metallohydrogel has been assessed through rheological analysis, considering angular frequency and oscillator stress dependencies. Notably, the Zn@PEH metallohydrogel exhibits exceptional self-healing abilities and can bear substantial loads, which have been characterized through thixotropic analysis. Additionally, this metallohydrogel displays injectable properties. The structural arrangement resembling pebbles within the hierarchical network of the supramolecular Zn@PEH metallohydrogel has been explored using FESEM and TEM measurements. EDX elemental mapping has confirmed the primary chemical constituents of the metallohydrogel. The formation mechanism of the metallohydrogel has been analyzed via FT-IR spectroscopy. Furthermore, zinc(II) metallohydrogel (Zn@PEH)-based Schottky diode structure has been fabricated in a lateral metal–semiconductor-metal configuration and it’s charge transport behavior has also been studied. Notably, the zinc(II) metallohydrogel-based resistive random access memory (RRAM) device (Zn@PEH) demonstrates bipolar resistive switching behavior at room temperature. This RRAM device showcases remarkable switching endurance over 1000 consecutive cycles and a high ON/OFF ratio of approximately 270. Further, 2 × 2 crossbar array of the RRAM devices were designed to demonstrate OR and NOT logic circuit operations, which can be extended for performing higher order computing operations. These structures hold promise for applications in non-volatile memory design, neuromorphic and in-memory computing, flexible electronics, and optoelectronic devices due to their straightforward fabrication process, robust resistive switching behavior, and overall system stability.

Programmable Computational RNA Droplets Assembled via Kissing-Loop Interaction.

DNA droplets, artificial liquid-like condensates of well-engineered DNA sequences, allow the critical aspects of phase-separated biological condensates to be harnessed programmably, such as molecular sensing and phase-state regulation. In contrast, their RNA-based counterparts remain less explored despite more diverse molecular structures and functions ranging from DNA-like to protein-like features. Here, we design and demonstrate computational RNA droplets capable of two-input AND logic operations. We use a multibranched RNA nanostructure as a building block comprising multiple single-stranded RNAs. Its branches engaged in RNA-specific kissing-loop (KL) interaction enables the self-assembly into a network-like microstructure. Upon two inputs of target miRNAs, the nanostructure is programmed to break up into lower-valency structures that are interconnected in a chain-like manner. We optimize KL sequences adapted from viral sequences by numerically and experimentally studying the base-wise adjustability of the interaction strength. Only upon receiving cognate microRNAs, RNA droplets selectively show a drastic phase-state change from liquid to dispersed states due to dismantling of the network-like microstructure. This demonstration strongly suggests that the multistranded motif design offers a flexible means to bottom-up programming of condensate phase behavior. Unlike submicroscopic RNA-based logic operators, the macroscopic phase change provides a naked-eye-distinguishable readout of molecular sensing. Our computational RNA droplets can be applied to in situ programmable assembly of computational biomolecular devices and artificial cells from transcriptionally derived RNA within biological/artificial cells.

Convolutional neural networks to classify human stress that occurs during in‐field sugarcane harvesting: A case study

AbstractAssessing human stress in agriculture proves to be a complex and time‐intensive endeavor within the field of ergonomics, particularly for the development of agricultural systems. This methodology involves the utilization of instrumentation and the establishment of a dedicated laboratory setup. The complexity arises from the need to capture and analyze various physiological and psychological indicators, such as heart rate (HR), muscle activity, and subjective feedback to comprehensively assess the impact of farm operations on subjects. The instrumentation typically includes wearable devices, sensors, and monitoring equipment to gather real‐time data of subject during the performance of farm operations. Deep learning (DL) models currently achieve human performance levels on real‐world face recognition tasks. In this study, we went beyond face recognition and experimented with the recognition of human stress based on facial features during the drudgery‐prone agricultural operation of sugarcane harvesting. This is the first research study for deploying artificial intelligence‐driven DL techniques to identify human stress in agriculture instead of monitoring several ergonomic characteristics. A total of 20 (10 each for male and female) subjects comprising 4300 augmented RGB images (215 per subject) were acquired during sugarcane harvesting seasons and then these images were deployed for training (80%) and validation (20%). Human stress and nonstress states were determined based on four ergonomic physiological parameters: heart rate (ΔHR), oxygen consumption rate (OCR), energy expenditure rate (EER), and acceptable workload (AWL). Stress was defined when ΔHR, OCR, EER, and AWL reached or exceeded certain standard threshold values. Four convolutional neural network‐based DL models (1) DarkNet53, (2) InceptionV3, (3) MobileNetV2 and (4) ResNet50 were selected due to their remarkable feature extraction abilities, simple and effective implementation to edge computation devices. In all four DL models, training performance results delivered training accuracy ranging from 73.8% to 99.1% at combinations of two mini‐batch sizes and four levels of epochs. The maximum training accuracies were 99.1%, 99.0%, 97.7%, and 95.4% at the combination of mini‐batch size 16 and 25 epochs for DarkNet53, InceptionV3, ResNet50, and MobileNetV2, respectively. Due to the best performance, DarkNet53 was tested further on an independent data set of 100 images and found 89.8%–93.3% confident to classify stressed images for female subjects while 92.2%–94.5% for male subjects, though it was trained on the integrated data set. The comparative classification of the developed model and ergonomic measurements for stress classification was carried out with a net accuracy of 88% where there were few instances of wrong classifications.

Alternative Virtual Lab-Based Practical Learning Model to Improve Scientific Attitude and Science Process Skills

A virtual laboratory is computer software that has the ability to perform mathematical modeling of computer devices presented in the form of simulations. Virtual laboratories are not a substitute for real laboratories, but are used to complement and improve the weaknesses of real laboratories. This research aims to determine the effect of virtual labs on science education students' scientific attitude abilities and science process skills in science courses. The design of this research is a repeated pre-experiment without a control class, with a one-group and pretest-posttest design. The sample in this study was 60 students of the science education study program at Makassar State University, Indonesia, used as experiment 1 group A (n = 30), experiment 2 group B (n = 30). Two groups (experiment 1 and experiment 2) were tested with a pretest and posttest. Each group uses a virtual lab-based practical model (PbVLab). Scientific attitudes and scientific skills were measured using multiple choice tests before and after treatment. The mixed method ANOVA statistical test was used to determine how effective the use of PbVLab was in improving scientific attitudes and science process skills. The results of testing research based on Within-Subjects Effects showed that there was no difference between the pretest-posttest scores for scientific attitudes and scientific skills (F = 0.00; p < 0.05) in each group. The results of the pairwise comparison showed a significance value of <0.05, and there was a significant increase in the pretest-posttest scores for scientific attitudes and science process skills in each group. The effect size results (partial eta squared) show that experimental group 1 experienced an increase in scientific attitudes by 52%; science process skills 53%, experimental group 2 scientific attitudes 54% and science process skills 56%. So, it can be concluded that experimental group 1 and experimental group 2 (PbVab model) provide the most effective contribution to improving scientific attitudes and science process skills.

Neuro-oncology anywhere: A decentralized approach to clinical trials in brain tumors and beyond.

TPS1647 Background: The majority of patients with primary and secondary central nervous system (CNS) malignancy develop cognitive impairment, fatigue, and mood-related symptoms. Radiotherapy has been shown to contribute to symptom burden often limiting quality of life and functional status. The development of interventions mitigating neurocognitive toxicity requires an accurate assessment of function and symptom burden. Formal neuropsychological evaluation is resource and time intensive, and often challenging to incorporate in routine clinical practice. There is a critical need to accurately assess cognition without causing undue burden to cancer patients while evaluating the efficacy of interventions that can be scaled and implemented at a population level. Methods: To adequately assess the neurocognitive function and related symptoms in patients with CNS malignancy we have designed an open-label decentralized clinical trial that will randomize patients who received intracranial radiation for primary or metastatic brain tumors in a 1:1 allocation to a therapy targeting radiation-related toxicity (metformin shipped to patient home) plus health promotion with a wearable device vs. health promotion with a wearable device alone. Participants will be stratified based on tumor type (glioblastoma vs. other glioma vs. brain metastases vs. meningioma) and age (<70 vs. 70+ years). Participants will be provided a wearable device for monitoring health status. Participants will undergo serial remote cognitive assessments with the Mayo Test Development Through Rapid Iteration, Validation and Expansion platform (Mayo Test Drive). Remote reported symptom collection via patient surveys and remote neurologic examination by telehealth will also be incorporated. Cognitive assessments and symptom surveys will be designed for completion on a smartphone, tablet, or computer device. Health data will be collected from the wearable device, including the number of steps per day and sleep quality/duration. Participants receiving metformin will utilize device apps to report medication adherence and adverse events. Study-related laboratory assessments will be completed remotely and transmitted electronically. This decentralized clinical trial will provide real-world cognitive and quality-of-life data for patients with primary and metastatic brain tumors while providing preliminary data on the effectiveness of device-based health promotion with or without metformin for treating radiation-related cognitive decline. Results gained from this study will guide future trials in neuro-oncology and other fields. This study is expected to open in March 2024.

Exploring non-steady-state charge transport dynamics in information processing: insights from reservoir computing

Exploring nonlinear chemical dynamic systems for information processing has emerged as a frontier in chemical and computational research, seeking to replicate the brain’s neuromorphic and dynamic functionalities. In this study, we have extensively explored the information processing capabilities of a nonlinear chemical dynamic system through theoretical simulation by integrating a non-steady-state proton-coupled charge transport system into reservoir computing (RC) architecture. Our system demonstrated remarkable success in tasks such as waveform recognition, voice identification and chaos system prediction. More importantly, through a quantitative study, we revealed that the alignment between the signal processing frequency of the RC and the characteristic time of the dynamics of the nonlinear system plays a crucial role in this physical reservoir’s performance, directly influencing the efficiency in the task execution, the reservoir states and the memory capacity. The processing frequency range was further modulated by the characteristic time of the dynamic system, resulting in an implementation akin to a ‘chemically-tuned band-pass filter’ for selective frequency processing. Our study thus elucidates the fundamental requirements and dynamic underpinnings of the non-steady-state charge transport dynamic system for RC, laying a foundational groundwork for the application of dynamical molecular scale devices for in-materia neuromorphic computing.

Multiferroic neuromorphic computation devices

Neuromorphic computation is based on memristors, which function equivalently to neurons in brain structures. These memristors can be made more efficient and tailored to neuromorphic devices by using ferroelastic domain boundaries as fast diffusion paths for ionic conduction, such as of oxygen, sodium, or lithium. In this paper, we show that the local memristor generates a second, unexpected feature, namely, weak magnetic fields that emerge from moving ferroelastic needle domains and vortices. The vortices appear near ferroelastic “junctions” that are common when the external stimulus is a combination of electric fields and structural phase transitions. Many ferroelastic materials show such phase transitions near room temperatures so that device applications display a “multiferroic” scenario where the memristor is driven electrically and read magnetically. Our computer simulation study of an elastic spring model suggests magnetic fields in the order of 10−7 T, which opens the way for a fundamentally new way of running neuromorphic devices. The magnetism in such devices emerges entirely from intrinsic displacement currents and not from any intrinsic magnetism of the material.

Leak-resilient enzyme-free nucleic acid dynamical systems through shadow cancellation

DNA strand displacement (DSD) emerged as a prominent reaction motif for engineering nucleic acid-based computational devices with programmable behaviours. However, strand displacement circuits are susceptible to background noise, known as leaks, which disrupt their intended function. The ill effects of leaks are particularly severe in circuits with complex dynamics, as leaks in them amplify nonlinearly, resulting in rapid circuit degradation. Shadow cancellation is a dynamic leak-elimination strategy originally proposed to control the leak growth in such circuits. However, the kinetic restrictions of the method incur a significant design overhead, making it less accessible. In this work, we use domain-level DSD simulations to examine the method’s capabilities, the inner workings of its components and, most importantly, its robustness to the practical deviations in its design requirements. First, we show that the method could stabilize the dynamics of several catalytic and autocatalytic dynamical systems heavily affected by leaks. Then, through several probing experiments, we show that its design restrictions could be significantly relaxed without impacting the circuit function by simply adjusting the circuit parameters. Finally, we discuss several ideas to tackle the practical challenges in applying the method to arbitrary DSD circuits, paving the way for future experimental work.

Hand Gesture Vocaliser using IoT

Abstract: This study suggests creating a hand gesture vocalizer system for people who are paralysed or deaf and cannot talk. By using the Internet of Things (IoT) technology, this system is able to recognise hand motions and convert them into voice, facilitating effective communication between users. A glove with sensors to identify hand movements and a microprocessor to process the data make up the system. After that, the data is sent wirelessly to a computer or mobile device, where a machine learning algorithm interprets the user's motions and turns them into audible speech. For those who are unable to communicate verbally, the suggested approach is anticipated to offer an efficient and natural means of doing so, enhancing their socialisation and quality of life. User testing will be used to assess the correctness and dependability of the system, and subsequent development efforts will concentrate on enhancing the system's portability and usability.

Design of Resonant Converter of Trans cutaneous Energy Transfer System to Power Artificial Heart

Wireless technologies have matured to recharge the batteries of consumer devices efficiently. The benefit of the technology is being used by mobile communication devices, personal computation devices, and wearable entertainment devices. The wireless energy transfer techniques employ the transfer of electrical energy between two-tesla coils in surface contact and not by electrical contact through the phenomenon of electromagnetic induction. Many international consortiums have made guidelines for designing and manufacturing these devices. However, for active implantable medical devices such as artificial hearts, a large amount of electrical energy usually in the range of 15W to 30W needs to be transferred across the skin at a depth of 10mm to 30mm. The design needs to be optimized for maximum power transfer with the highest possible efficiency. Any loss in power will be reflected as heat energy and cause burns and tissue death. A transcutaneous energy transfer system is such type of wireless energy transfer mechanism across the skin to power implanted life-saving devices. In this paper, the design of a resonant converter and its performance is investigated to wirelessly transfer electrical power up to a tissue thickness of about 25mm.

Switching mechanisms of two-dimensional transition metal dichalcogenides(2D TMDCs)-based memristive devices for neuromorphic computing

The recent surge in artificial intelligence has escalated the demand for computing performance and storage capability in information processing hardware. However, in traditional von Neumann architecture, the processing and memory units are connected by a bus with limited bandwidth, which leads to excessive time and power consumption in data transfer. To address this issue, the emerging neuromorphic architecture co-locates the memory and processing functionalities by mimicking the information processing akin to the human brain. The inefficiency of traditional technology in neuromorphic hardware has led to extensive interest in novel memristive devices. The two-dimensional (2D) transition metal dichalcogenides (TMDCs) exhibit appealing characteristics for memristive devices, including tunable bandgap, high mobility at atomic thickness, and the rich possibility of defect engineering. This review focuses on the switching mechanisms of memristive devices based on 2D TMDCs. Additionally, properties and performances of 2D TMDCs-based memristive devices are also summarized in this review with respect to different switching mechanisms.

Reconfigurable image processing metasurfaces with phase-change materials.

Optical metasurfaces have enabled analog computing and image processing within sub-wavelength footprints, and with reduced power consumption and faster speeds. While various image processing metasurfaces have been demonstrated, most of the considered devices are static and lack reconfigurability. Yet, the ability to dynamically reconfigure processing operations is key for metasurfaces to be used within practical computing systems. Here, we demonstrate a passive edge-detection metasurface operating in the near-infrared regime whose response can be drastically modified by temperature variations smaller than 10 °C around a CMOS-compatible temperature of 65 °C. Such reconfigurability is achieved by leveraging the insulator-to-metal phase transition of a thin layer of vanadium dioxide, which strongly alters the metasurface nonlocal response. Importantly, this reconfigurability is accompanied by performance metrics-such as numerical aperture, efficiency, isotropy, and polarization-independence - close to optimal, and it is combined with a simple geometry compatible with large-scale manufacturing. Our work paves the way to a new generation of ultra-compact, tunableand passive devices for all-optical computation, with potential applications in augmented reality, remote sensing and bio-medical imaging.