Journal of Biosensors and Bioelectronics Research
Journal of Biosensors and Bioelectronics Research is an open access peer-reviewed journal from the publishers of Scientific Research and Community (SRC) which publishes articles in the form of written, Video and Power-Point Presentations from the arena of Biosensors and Bioelectronics. The journal focuses to build up accessing the complete content of articles freely from online for reader’s perusal. Article acceptance will be in the form of Research, Review, Case Reports, Analysis, Magazines, Editorials, Opinion, Communications, Mini-Review, Short Communications, Picturized, Book Review, Video Type and Power Point Presentations (PPTs). You can submit articles through Online: https://srcpublishers.com/biosensors-and-bioelectronics-re/user/register or can send through an E-mail with attachment for editor.jbbr@onlinescientificresearch.info 0.35 Impact Factor 84.5% Citations 90% Acceptance
An Improved Amperometric Acetylcholine Biosensor by Integrating Enzyme Nanoparticles with Graphene Oxide Nanoparticles
An improved amperometric acetylcholine (ACh) biosensor was developed by co-immobilizing enzyme nanoparticles (ENPs) i.e. acetylcholine esterase (AChENPs) and choline oxidase (ChONPs) onto graphene oxide nanoparticles (GrONPs) electrodeposited onto pencil graphite electrode (PGE). The GrONPs were prepared from graphite rod and characterized by cyclic voltammetry (CV) transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), UV and visible spectroscopy. ENPs/GrONPs/PGE was studied by scanning electron microscopy (SEM) and FTIR at different stages of its construction. The biosensor showed optimum current response at an applied potential of 0.5V within 2s at pH 7.0 and 30˚C in acetylcholine concentration range, 0.001μM to 1000μM, with a detection limit (LOD) of 0.001 μM. The analytical recovery of added acetylcholine in serum, as measured by this bio sensor was 98%. Within and between batch coefficient of variations were 0.04% and 0.06%, respectively. A good correlation (R2 = 0.989) was found between sera ACh level measured by standard enzymic colorimetric method and the present biosensor. The biosensor measured ACh level in sera of apparently healthy persons and patients suffering from Alzheimer’s. The working electrode lost 25% of its initial activity, over 240 days, when stored dry at 4˚C.
Copyright (c) 2026 Journal of Biosensors and Bioelectronics Research
How Biosensors are Transforming Chronic Disease Management?
With the rising prevalence of chronic conditions like diabetes, it has become increasingly important to track the blood glucose levels of patients. This has resulted in increased adoption of various blood tracking devices among healthcare professionals, medical facilities, and patients. Among these devices, biosensors have gained traction due to the numerous benefits they offer in order to alleviate symptoms of diseases like diabetes and blood-related conditions such as blood pressure.
Copyright (c) 2025 Journal of Biosensors and Bioelectronics Research
Immobilization of Bilirubin Oxidase Nanoparticles onto Gold Electrode for Amperometric Detection of Serum Bilirubin
‘Bilirubin oxidase nanoparticles’ (BOxNPs) were prepared from commercial bilirubin oxidase by using the ‘desolvation method’. An amperometric bilirubin biosensor was developed by immobilizing BOxNPs onto an Au electrode. The morphology in terms of size and shape of BOxNPs aggregates was studied by “transmission electron microscopy (TEM)”, “dynamic light scattering (DLS)” and “Scanning electron microscopy (SEM)” which were utilized to characterize BOxNPs/Au electrode. BOxNPs/Au electrode demonstrated an optimum response time (1s), pH (8.5), and temperature (35°C) when polarized at a potential (+0.3 V). The lowest ‘detection limit’ (0.01 µM) was calculated by selecting a concentration range from 0.01 to 1000 µM for bilirubin. BOxNPs/Au electrode was employed to detect total serum bilirubin in healthy people and people suffering from jaundice. When the electrode was stored at a low temperature in sodium phosphate buffer (0.1 M, pH 7.0), it retained 50% of its original activity with storage stability of 150 days.
Design and Development of Foot Massage Assistive Device
The operation of the Foot Massage Stick involves three essential elements: sequence, direction, and force. Among these, force is particularly difficult to describe and master. To provide users with a visual means of understanding the force being applied, however a product lacking such functionality on the market, this study decided to develop a pressure-sensing massage stick. This study applied a systematic design approach to develop the foot massage stick. This approach included setting design goals, mechanical design, appearance design, and functional verification. Ultimately, this product was developed. The key features of this design are as follows: 1) Performance meets the accuracy standards of commercially available instruments. 2) The applied force and duration are displayed in real time during the operation. 3) After the operation is completed, data such as the maximum applied force, average, standard deviation, and application time are displayed. 4) By visualizing the applied force, learning is facilitated, helping to ensure that the required operation is achieved. The results and procedures of this study can provide a reference for the development and design of assistive device products.
Evidence of Field Torsion through a Hall’s Sensor with Dynamic Magnetic Dilaton
Torsion is an observable and invariant, which in geometry is a second curvature. In field theory, the torsion is the better evidence of the birth of gravity, the interaction between electromagnetic fields and gravitational fields or matter presence from microscopic level and its different effects until our days with the gravitational waves that are echoes detected from big bang in astronomical observatories. Through electronics is designed an analogue of torsion measurement, considering the electronic signals detected by a Hall sensor gauge to detect the magnetic field of a dilation (gauge particle of magnetic nature). This moves along a spiral trajectory with certain constant torsion as well as variable torsion, where curvature energy can be obtained through electromagnetic fields. However, in the case of the torsion, is required a trajectory whose torsion is detectable and measured by fine instruments. A consideration important raised of some investigations using Hall sensors gauged to different ranges of magnetic field is the obtaining of the torsion as energy spectra whose energy density is a spectral torsion determined through the energy curvature developed in the spinor-twistor framework, used to evidence the torsion in sources and holes in the space-time, for example.
Synapse Calcium Image Analysis (SCIA): A Groundbreaking Toolkit for Real-Time Analysis of Synaptic Calcium Signals
With the continuous advancement of fluorescence microscopy technology and improved fluorescent indicators, we can now record neuronal calcium activity with unprecedented resolution and signal- to-noise ratio. By using calcium sensors to monitor and track calcium signals, we can observe changes in pixel intensity over time within regions of interest, thereby capturing neuronal calcium activity, including synaptic calcium activity. Custom tools were initially developed within individual labs for neuronal image analysis and shared across the research community. In the past, data analysis using opensource toolboxes like CaImAn and SIMA, previous image processing toolkits often subtract a universal background signal during image procession, which is inaccurate for delicate synapse calcium signals, neglecting the background heterogeneity of synapse. Additionally, those toolboxes require a certain level of programming proficiency, which could hinder some researchers lacking programming experience. We have proposed and designed a more streamlined and user-friendly synapse calcium imaging analysis toolbox to overcome these challenges. Synapse Calcium Image Analysis (SCIA) employs various signal extraction methods. It incorporates local background processing techniques, including detection, comparison, and subtraction, enabling rapid and precise identification of active calcium signal regions in neurons. Meanwhile, the toolbox provides a user- friendly GUI, allowing users to quickly and easily obtain accurately matched signal regions. As a result, it provides users with a simple yet efficient synapse calcium imaging analysis tool, saving them time and effort.
Detection of Phenolic Compounds by Laccase Biosensors: A Review
Laccase [EC 1.10.3.2] is the most extensively studied copper-containing oxido-reductase enzyme that can be isolated from bacteria, fungi and plants. Laccase catalyses the oxidation reaction i.e. electron-transfer from phenolic compounds in the presence of molecular oxygen without requiring a cofactor. It had high potential for oxidation of phenols and benzenediols. Several traditional methods were followed for detection of phenolic compounds like spectrophotometry and chromatography but these are in-efficient, expensive and required trained personal to operate. These limitations were overcome by laccase-based biosensors, which are simple, sensitive, highly specific, rapid and cost-effective. This review article describes various types of immobilization of laccase onto transducer in laccase biosensors, their mechanism of action, selectivity, sensitivity and applications in different fields.
Protein Complex Heterogeneity in the Nerve System
A neuron has a unique axonal mRNA translocation and axonal translation. Thus, the neuron may have a different gene and protein expression regulation mechanism. However, we found that neuronal mRNA abundance is inverse-related to the CDS length of mRNA, which is consistent with other cell types. Meanwhile, the RNA and protein abundance have a low correlation, as revealed using paired mRNA-seq and proteomic data. Furthermore, our findings revealed the presence of extensive protein heterogeneity within main protein complexes. We utilized multiple single-cell mass spectrometry datasets to assess the protein heterogeneity within nuclear pore complexes and ribosomes. This study revealed a notable discrepancy between the proportion of protein complex subunits and their mature Stoichiometry under STED microscopy and CRYO-EM, suggesting heterogeneity of the protein complex.
Desalination of Hyper-Concentrated Brines via Microwave Irradiation Mechanism: Case Studies. A Simultaneous Integration of ThermalDesalination, Steam Turbines and Brine Mining into a Desalination Plant Design
A new and novel approach to thermal desalination is being developed. This application involves microwave irradiation of custom-made reactors that can generate instantaneous temperatures of over 1000 ºC and cause instant evaporation of seawater. The benefits are severalfold: in addition to purified water, suitable for human consumption, a large amount of energy can be generated via steam turbines that can be fitted into the desalination module. This approach also makes brine mining of rare metals possible, as large amounts of brine are generated and stored for further processing. The energy consumption is just a fraction of the conventional thermal desalination process. This approach can be transferred into portable desalination devices that can be easily deployed in emergency and distress situations.
Metal-ligand Coordination Induced Rapid Li+ Transport Kinetics through Bidirectional Anchoring Strategy
The unstable interfacial contact and slow Li+ transport at the side of cathode have been two major challenges for practical application of garnet-based solid-state batteries (SSBs). In this work, a strategy of metal-ligand coordination induced rapid Li+ transport kinetics through bidirectional anchoring is proposed to address aforementioned issues by decorating the cathode with Li6.4La3Zr1.4Ta0.6O12 (LLZTO) nanoparticles and stabilizing the interface with succinonitrile-based interlayer (SL). The strong metal- ligand coordination of the -CN in SL with the LLZTO solid-state electrolytes and the LiCoO2 (LCO)@LLZTO composite cathode enables an intimate contact at the atomic scale, constructing bidirectional channels of fast Li+ transport at the interface. Additionally, LLZTO nanoparticles within the composite cathode establish three- dimensional (3D) channels of fast Li+ transport. The synergistic effect of the bidirectional channels of fast Li+ transport at the interface and 3D channels of Li+ transport at internal cathode achieves rapid Li+ transport kinetics at the cathode side. As a result, a high-capacity retention of 80.6% after 700 cycles at 0.1 C is achieved for the LCO@LLZTO(SL)|LLZTO|Li batteries (3.0-4.2 V, 3 mg·cm-2). It also exhibits excellent cycling performance even at high voltages of 3.0-4.4 V. This work offers a new possibility for fabricating ultra-stable SSBs.
Advances in Lactose Biosensors and Sensors: A Mini Review
Quantitative determination of lactose in different dairy products is required to access their nutritional value and diagnosis of various diseases such as lactose intolerance, diarrhoea, nausea, abdominal bloating, vomiting and flatulence. Among the various methods available for lactose, bio-sensing, methods based on immobilized β-galactosidase and glucose oxidase are better, as these are more simple, sensitive, specific and rapid. The present mini review describes various bio-sensing and sensing methods for determination of lactose. The lactose biosensors work ideally in the pH range, 5.0 to 7.0, temperature 30-350 C, response time 4-30s and linear concentration range 1µM to 100 mM, with LOD ranging from 1 µM to 4 mM. The lactose biosensors had storage stability between 10-20 days at 40 C.The miniaturization of lactose biosensors is expected to make them portable and commercial individuals. Non enzymatic lactose sensors offer advantages over enzymatic biosensors byovercoming enzyme stability, simpler fabrication and providing higher sensitivity, broader working range(1fM to 3.47 mM) and lower detection limit 200aM to 26µM.However, non enzymatic biosensors are not specific like enzymatic biosensors.
Integrating AI-Driven Neurofeedback with Brain-Computer Interfaces: A Paradigm for Effortless Learning and Workforce Transformation
The integration of advanced AI-driven neurofeedback systems with brain-computer interface (BCI) technology marks a transformative frontier in cognitive neuroscience and educational technology. Recent developments demonstrate the feasibility of interpreting cognitive signals-”reading thoughts” - to facilitate direct communication with digital interfaces, thus superseding traditional keyboard and mouse inputs [1]. Such advances not only hold promise for individuals with paraplegia or other disabilities that limit traditional computer interactions but also signify a profound shift in how knowledge and skills might be acquired implicitly and effortlessly. As Industry 4.0 rapidly progresses, characterized by automation, interconnected systems, and AI-driven innovation, the ability for workers and learners to swiftly acquire new competencies becomes critically important. BCI-driven learning platforms leveraging AI-based neurofeedback present the potential to significantly streamline training processes, ensuring individuals can maintain pace with technological advancements without engaging in exhaustive or explicit study
AI & XR Explorations to Support Social Interactions: Speculative Design for Ubiquitous Workplace Space by and for Neurodivergent Employees
This study explores the potential of interdisciplinary theories and advanced technologies, such as augmented realities and artificial intelligence, to address the socio-professional integration challenges faced by neurodivergent individuals, particularly those on the autism spectrum. It investigates the design of personalized, functional spaces that integrate interconnected living environments and intelligent systems tailored to support communication needs. Using speculative design methodology, the research adopts an experiential framework to examine alternative solutions, starting with a central hypothesis and testing it through debates with researchers, experts, neurodivergent individuals, and knowledge users. The premise is rooted in the recognition that neurodivergent individuals encounter significant barriers to social interaction and communication, limiting their integration into professional and social environments. This project envisions leveraging Internet of Things devices and immersive extended reality systems to create accessible, personalized spaces where individuals can reflect, feel secure, and engage in meaningful interactions. These spaces aim to foster confidence, well-being, and adaptability while addressing the limitations of existing tools. Hypotheses are informed by frameworks addressing autistic experiences and studies on self-narratives, proposing innovative applications of AI and immersive technologies. A diegetic device illustrates an augmented reality environment allowing users to practice social scenarios, engage in interest-based interactions, and participate freely, while preserving the emotional safety of a personalized setting. The research highlights the potential for such environments to transform social and workplace adaptation, fostering inclusion and employability amongeurodivergent individuals. Results and discussions delve into emerging ideas, providing a foundation for advancing adaptive strategies that meet the specific needs of this population. By bridging theoretical and technological innovations, this work seeks to open new possibilities for integrating neurodivergent individuals into society while enhancing their quality of life through tailored, intelligent, and interactive solutions.
XR and AI with Augmented Realities and Artificial Intelligence
An Enhanced Amperometric HER2 Immunosensor for Early Detection of Breast Cancer
Human epithelium receptor 2(HER2) is the most important breast cancer biomarker, whose increased level in blood is very important for detection of breast cancer at early stage We describe herein the enhancement of an HER2 antibody based amperometric immunosensor for detection of breast cancer, by graphene (Gr) sheets. The working electrode i.e. anti-HER2/Gr-sheets/PGE was characterized using cyclic voltammetry, scanning electron microscopy and electrochemical impedance spectra. The immunosensor had optimum activity at pH 7.0, 25°C, and antibody concentration of 18 µg/ml. It exhibited a linearity in the concentration range 1 fg/ml to 20 ng/ml, with a detection limit (LOD) of 0.85fg/ml. The immunosensor was employed to determine HER2 concentrations in sera of apparently healthy women and those women suffering from breast cancer at early stage. It was increased significantly(p
Risks Assessment of Petroleum Fires at Elevated Pressures and Temperatures aboard Oil Tankers Using Computer Model
This paper starts with briefs for effects of elevated pressures and temperatures on risks increase of petroleum fires including autoignition phenomenon. The paper then discuss some important parameters in combustion science such as burning velocities, which is a very important factor in risk assessment for any combustible material (fuels, oil products and chemicals) via using computer programs at different initial conditions to evaluate final temperatures of flames in the surroundings. Four different fuels are used in this work. The paper also explains other important issues such as, Flammability limits of such materials and flames instability. Those two parameters help to know and understand flames behaviors and their propagation in the surrounding environment. Flame instabilities are phenomenon, which not well understood in combustion due its complexity and the tremendous changes and fluctuations of physical and chemical states of burned species in flames. This situation makes fire more dangerous and harder to control. Finally, the paper ends with some conclusions
Self-Locking Domino Logic Pipelines: Application in RISC-V Architectures in FPGA
his paper presents the design and implementation of a self-locking domino logic pipeline controller for a RISC-V processor implemented on an FPGA. The emphasis is on asynchronous circuit design, which offers advantages such as enhanced resilience to supply voltage fluctuations, optimized power efficiency, and the elimination of clock-related issues such as skew and single-point failures. By leveraging the asynchronous Globally Asynchronous Locally Synchronous (GALS) systems and domino logic, the controller ensures hazard-free operation while maintaining race-free processing. The asynchronous approach, integrated into a 32- bit RISC-V processor, allows for flexible and energy-efficient operation, thereby demonstrating its potential for performance-critical applications. This paper high- lights the contrasts between the asynchronous design and the traditional synchronous multicycle processor, demonstrating the benefits of asynchronous systems in terms of power consumption and performance. A significant contribution of this design is the pipeline’s completion detection mechanism, which ensures that each processing stage locks until valid results are obtained, thereby markedly enhancing system stability. Furthermore, the paper investigates the parallelization of domino gates and introduces an asynchronous Arithmetic Logic Unit (ALU), which further optimizes performance through self-locking mechanisms. The power, performance, and area (PPA) analysis of the design demonstrates considerable improvements in throughput (up to 10%) and reduced latency per instruction in comparison to its synchronous counterpart, while maintaining moderate resource utilization on an FPGA. The results indicate that asynchronous domino logic pipelines may offer a promising approach for achieving energy-efficient and high-performance processors in future computing architectures.
Comparison of Short Fast Fourier Transform and Continuous Wavelet Transform in Study of Stride Interval
Neurodegenerative diseases (NDD) are a heterogeneous group of complex diseases characterized by neuronal loss and progressive degeneration of different areas of the nervous system. Gait analysis presents an early recognition system for NDD which is important to increase the patient’s awareness of their health conditions. However, it is very difficult to identify and formulate suitable digital biomarkers from the data collected from gait experiments such as stride interval and swing. The objective of this paper is to compare the result of Short - Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) on the collected stride interval of healthy young people and healthy old people. In this paper, STFT and CWT are performed on the collected stride interval and from the result of the STFT and CWT, further features are extracted like instantaneous RMS and maximum RMS value. STFT is performed on the collected stride interval from a window length of 64 to 512 while CWT is performed on the collected stride interval from the scale of 128 to 2048. The processing time of the STFT and CWT with varied window lengths and scales respectively are collected. Besides, the actual maximum time from the time - frequency plot derived from STFT and CWT is also collected. Both STFT and CWT show that the young group has a higher maximum RMS, an indication of higher stride interval than the old group and higher variance, an indication of higher gait complexity. The suitable window lengths for STFT in analyzing the stride interval are 64 and 128 while the scale for CWT should be set to the lowest scale. Overall, STFT with a window length of 64 and 128 is better in analyzing the stride interval due to low processing time at the expense of slightly less accurate time - frequency representation.
Mathematical Modeling and Enhancing the Carrying Capacity of National Parks in the United States
A rapid growth in the number of visitors has been observed for many national parks in the United States, examples include Yellowstone National Park, Yosemite National Park, Rocky Mountain National Park and Arches National Park. As a result, public transit and parking resources have been stretched closer and closer to their capacities in these parks. In response, some National Park Services (NPS) have started to implement crowd control measurements, such as the timed entry reservation systems, where visitors have to reserve their slots to visit the park during certain time periods of the year. However, such policy does not touch on the fundamental issue of the subject, that is, the carrying capacity of the park. In this paper, we demonstrate that there will be even greater growth in the number of visitors in the near future, which means that a capacity boost is inevitable. Fortunately, we also observe that if we can fix some key bottlenecks, then we can dramatically increase the capacity of the park without destroying more natural land.
Research on the Correlation between Quantum Entanglement and Thinking Consciousness
The development of quantum technology has profoundly influenced research on consciousness. By analyzing the interaction of various microscopic particles in the universe, the article proposed that all things exhibit interconnected non-locality in both time and space, and that the interrelated connections of everything in the universe are based on quantum entanglement. Through analysis of the cellular and nervous system functions of organisms, as well as the influence of quantum science theories on consciousness and combined with research results in related fields, this paper presents the following viewpoints: first, life bodies exhibit quantum entanglement phenomena. Second, biological electricity phenomena are closely tied to consciousness. Third, both life bodies and non-life bodies are conscious, but different entities exhibit varying degrees of strong and weak consciousness. The strong and weak thinking consciousness influences the fluctuation of quantum and the size of quantum entanglement degree. Quantum fluctuations affect the consciousness of both life bodies and non-life bodies, and the entanglement quantum influences the degree of inductance between each other. Finally, the combination of quantum entanglement technology and thinking consciousness can realize the interconnection between human beings and the universe. Consciousness may affect the results measured in quantum mechanics when people observe. However, the macroscopic world mainly adopts the laws of classical physics to solve problems in life. Under certain conditions, the law of quantum physics and the law of classical physics can affect people’s lives together. No matter what angle we view the material world, it is real, and the universe is not illusory.
Perceptions and Aspirations of Undergraduate Computer Science Students Towards Generative AI: A Qualitative Inquiry
This article presents a comprehensive study conducted during the spring semester of 2024, aimed at exploring undergraduate computer science students’ perceptions, awareness, and understanding of generative artificial intelligence (GAI) tools within the context of their Artificial Intelligence (AI) courses. The research methodology employed qualitative techniques, including human-subject research and focus groups, to delve into students’ insights on the evolution of AI as delineated in the seminal textbook by Russell and Norvig. The study-initiated discussions on the historical development of AI, prompting students to reflect on the aspects that intrigued them the most, and to identify which historical concepts and methodologies, perhaps even those not directly covered in their curriculum, piqued their interest. Furthermore, the dialogue encompassed the learning methodologies highlighted in the textbook, seeking students’ feedback on the strategies that have been most effective for mastering complex AI theories and their practical applications. Interdisciplinary applications of AI were also discussed, encouraging students to contemplate AI’s role beyond the realm of computer science and its potential to foster innovative solutions across various fields. Finally, the conversation shifted towards students’ personal goals and aspirations in AI, urging them to consider how their perspectives have evolved in light of technological advancements, societal needs, and ethical considerations. The findings underscore a notable gap in students’ awareness of AI’s history and its current capabilities, indicating a need for educational strategies that not only deepen understanding but also foster a broader appreciation of AI’s potential. This study contributes valuable insights into enhancing AI education and encouraging interdisciplinary innovation among the next generation of computer scientists.
Advancing Sentiment Analysis Through Emotionally-Agnostic Text Mining in Large Language Models (LLMS)
The conventional methodology for sentiment analysis within large language models (LLMs) has predominantly drawn upon human emotional frameworks, incorporating physiological cues that are inherently absent in text-only communication. This research proposes a paradigm shift towards an emotionallyagnostic approach to sentiment analysis in LLMs, which concentrates on purely textual expressions of sentiment, circumventing the confounding effects of human physiological responses. The aim is to refine sentiment analysis algorithms to discern and generate emotionally congruent responses strictly from text-based cues. This study presents a comprehensive framework for an emotionally-agnostic sentiment analysis model that systematically excludes physiological indicators whilst maintaining the analytical depth required for accurate emotion detection. A novel suite of metrics tailored to this approach is developed, facilitating a nuanced interpretation of sentiment within text data, which is paramount for enhancing user interaction across a spectrum of text mining applications, including recommendation systems and interactive AI characters. The research undertakes a critical comparative analysis, juxtaposing the newly proposed model with traditional sentiment analysis techniques, to evaluate efficacy enhancements and to substantiate its application potential. Further, the investigation delves into the short-term memory capabilities of LLMs, exploring the implications for character AI roleplaying interfaces and their ability to recall and respond to user input within a text-driven emotional framework. Findings indicate that this emotionally-agnostic sentiment analysis approach not only simplifies the sentiment assessment process within LLMs but also opens avenues for a more precise and contextually appropriate emotional response generation. This abstracted model, devoid of human physiological constraints, represents a significant advancement in text mining, fostering improved interactions and contributing to the evolution of LLMs as adept analytical tools in various domains where emotional intelligence is crucial.
Order Analysis of a Vibration Signal of a Rotating Machine
Order analysis is a technique used in vibration analysis to identify the sources of vibration in rotating machinery. It helps to determine the frequencies at which various components within the machinery are experiencing vibration. The RPM profile serves as a key parameter in vibration analysis of rotating machinery, allowing for the examination of vibration amplitude changes as a function of rotational speed. By considering these characteristics, analysts can gain valuable insights into the behavior of rotating systems, identify potential faults, and make informed decisions regarding maintenance and repairs.
IOT, or the Internet of Things, is all about connecting physical devices, appliances, and objects to the internet. These devices have sensors, software, and connectivity that allow them to collect and exchange data. The goal is to make our everyday objects smarter and more interconnected.
Copyright (c) 2024 Journal of Biosensors and Bioelectronics Research
Enhancing Workplace Neuro Health and Productivity: The Synergy of Wearable Technology with Biophilic and Oxygenation Strategies
In the contemporary workplace, where a staggering 62% of employees reported experiencing burnout in 2023 according to a Medium article, the integration of wearable technology with biophilic and oxygenation strategies emerges as a vital Neurohemal initiative. This approach is particularly relevant for supporting neurodivergent individuals, as well as those recovering from stroke and long-COVID, in the context of return-to-office mandates. The article underscores the significance of research on increased hydrostatic pressure in circulation, particularly its impact on spinal and spinal cord blood flow during water immersion. This insight lays the groundwork for innovations like non-wet water massage devices, which could significantly aid in neurological recovery, thereby facilitating smoother reintegration into the workplace. Moreover, the fusion of biometrics with medical technology in wearables is explored, with a focus on enhancing interoception and proprioception. This technological synergy is key in activating the parasympathetic nervous system (PSNS), inducing a relaxed state conducive to effective digestion and oxygenation, crucial in mitigating workplace stress. The concept of ‘Interoceptive in Water’ is examined for its potential to improve blood flow and overall bodily function. In addition, the article advocates for the introduction of oxygenation bars in office spaces. These bars would offer a dedicated environment for enhanced oxygen intake, vital for cognitive function and stress alleviation, benefitting neurodivergent individuals, stroke survivors, and long-COVID patients. Wearables capable of detecting and correcting low oxygen or circulation issues are highlighted as essential tools for fostering a more inclusive, productive, and healthier workplace, thereby contributing to the overarching goal of NeuroHealth in the professional sphere.
Parasympathetic Nervous System Activation
Designing Technical Systems in The Anthropocene: Manifesto fora New Paradigm
The RASSCAS Laboratory (Applied Research in Social Sciences to Design a Sustainable Anthropocene) is a human sciences laboratory based in a digital engineering school. The idea of this laboratory is to guide engineering students towards models of design and innovation that respond both to the ethical desires of this young generation and to the need for responsible innovation imposed by the context of access to development that is fair for mankind and sustainable for life and the planet. This article is first and foremost a profession of faith, that of researchers who have decided to commit themselves to the path of development that respects life. It is also a call to become aware of the need to modify traditional design models. It’s a call for a paradigm shift from anthropocentric models to one that gives equal place to human and non-human living beings.
Virtual Reality at Workplace for Autistic Employees: Preliminary Results of Physiological-Based Well-Being Experience
Emotional health problems in the workplace often hinder the integration and retention of autistic employees (AE), a challenge identified in many sectors. Recent literature highlights the consequences of these problems, such as burnout leading to reduced productivity and resignation. Previous research supports the effectiveness of virtual reality (VR) for training a variety of specific skills (e.g. riding a bus or plane travel), as well as more complex social skills, such as emotion recognition and functional communication. In addition, existing studies on using physiological self-monitoring in AE training offer a promising approach to promoting improved emotional health. The present paper reports on implementing a VR system that simulates workplace training and integration and enables real-time monitoring of three physiological signals, in five post-secondary autistic students. Using an Oculus Quest 2 and non-clinical grade sensors, the researchers delivered the VR intervention over three days to each participant. At the end of these interventions, the researchers measured the perceived satisfaction of these integrated systems, based on several technological criteria, on a 5-point scale. The integrated system received an overall rating of 4, suggesting its likelihood of acceptance and use. A preliminary analysis of a participant’s physiological responses to this VR intervention is also presented. This preliminary report suggests the efficacy of a VR workplace simulation and physiological self-monitoring in promoting emotional well-being and basic task training for post-secondary AE. The researchers’ observations and the proposal of a theoretical framework to enhance real-time emotional communication based on physiological markers for AE are also discussed.
Virtual Reality (VR) Workplace Simulation
Behavioral Biometrics for Continuous Authentication
Gaining control over the security of the information and personal data stored in the devices has been crucial in the current digital world. Passwords and PINs, which are the common identity check methods at the beginning of the using phase of the devices, are less powerful once the devices themselves are in use. Transitioning to the second type, continuous authentication based on behavioral biometrics, becomes a strong solution to improve security throughout the session. This paper aims to discuss continuous authentication and its usage in coupling the behavioral components across computing devices. These recommendations underscore the successes of some of the methods, like keystroke dynamics and mouse movements, in ascertaining users’ identities in real time. These are how the various platforms can work together and handle privacy-related issues. The future trends of studies focus on the necessity of improving the algorithms of biometric identification and increasing the adaptability of those algorithms to provide maximum protection in cyberspace.
Copyright (c) 2023 Journal of Biosensors and Bioelectronics Research
The Role of IoT in Enhancing HVAC Control Systems
This comprehensive research paper investigates the paradigm shift in Heating, Ventilation, and Air Conditioning (HVAC) control systems propelled by the transformative integration of the Internet of Things (IoT). In an era marked by the convergence of digital technologies, the infusion of IoT into HVAC systems heralds a new era of dynamic, interconnected control mechanisms. This study undertakes a thorough examination of the evolving landscape, shedding light on the profound advancements, discernible benefits, and nuanced challenges intrinsic to harnessing IoT for the augmentation of HVAC control systems. The journey begins by elucidating the fundamental shifts catalyzed by the assimilation of IoT in HVAC systems. The traditional boundaries of HVAC control are transcended as interconnected devices seamlessly communicate, fostering an environment where each component becomes an intelligent node in a networked ecosystem. Real-time data exchange becomes the bedrock, facilitating a level of monitoring and control hitherto unseen. The paper explores the intricacies of this interconnectedness, unveiling the potential for granular control and adaptability that IoT ushers into HVAC operations. A focal point of this research is the exploration of the tangible benefits that arise from this symbiosis of IoT and HVAC control. The paper meticulously examines how real-time monitoring empowers system operators with unprecedented insights into performance metrics, energy consumption patterns, and environmental conditions. Harnessing this wealth of data, IoT-equipped HVAC systems demonstrate an unparalleled capacity for adaptive control, responding dynamically to fluctuating demands and external variables. The consequential improvements in energy efficiency and resource utilization contribute not only to operational cost savings but also align with global sustainability objectives. However, in the pursuit of technological advancement, challenges inevitably emerge. This research critically evaluates the impediments and challenges inherent in the integration of IoT into HVAC control systems. Security concerns, data privacy issues, and the evolving landscape of technology standards are among the multifaceted challenges explored in depth. The paper endeavors to provide a nuanced understanding of these challenges, offering insights that can inform the development of robust and resilient IoT-enabled HVAC control systems.
Research on the Correlation Between Anemia and Chronic Malnutrition in School-Age Children in Rural Areas of the Toumodi Health District in Côte d’Ivoire
Introduction: Anemia and chronic malnutrition are widespread in sub-Saharan Africa and constitute public health problems. This study was carried out to assess the association between chronic malnutrition and anemia in rural school-age children. Method: This is a descriptive and analytical cross-sectional study carried out in the Toumodi health district in central Côte d’Ivoire. Study subjects were selected from children aged 6 to 15 years from rural school areas, according to inclusion and exclusion criteria, resulting in a sample of 588 pupils. The study was carried out in two stages: - The first step was to screen all consenting children for anemia using a Hemocue ®-System. - The second step was to collect anthropometric and biological data: the result of the presence of the malaria parasite in the blood by malaria test and the presence of helminths in the stools. Data entry and statistical analysis were carried out using Excel and SPSS version 12.0 software respectively. Results: Chronic malnutrition (weight-by-age) accounted for 22.4% of children, while the prevalence of anemia was 70.7%. The percentage of children with a positive malaria test was 57.5%. Helminths were observed in the stools of 52.8% of children. Anemia was correlated with chronic malnutrition and malaria. Moreover, chronically malnourished children were about twice (OR = 1.81) as likely to develop anemia as those who were not. Conclusion: This study revealed a strong association between chronic malnutrition and anemia.
Ensuring Security in Semiconductor Design through Verification
The ever-growing complexity of semiconductor designs, the demand for powerful and feature-rich electronics, presents a significant challenge in ensuring their correctness and security. Security verification has become a critical process in the semiconductor design lifecycle, aiming to identify and mitigate potential vulnerabilities that could be exploited. Given the increasing reliance on semiconductor devices for critical infrastructure and applications, the importance of robust security verification cannot be overstated. This paper explores few of the crucial role verification plays in guaranteeing security within semiconductor design. It examines various facets of this process, including analyzing potential security threats and vulnerabilities. This paper delves into the critical role of verification in ensuring semiconductor security. It also explores various verification techniques, discusses emerging trends, and outlines future directions in this crucial field.