Physical Limitations Research Articles

Enhancing a-IGZO Thin-Film Transistors Performance Via Multi-Parameter Machine Learning

Driven by miniaturization in accordance with Moore's Law, memory devices like DRAM and NAND have achieved significant performance improvements. However, this relentless scaling has encountered fundamental physical limitations, hindering further miniaturization of traditional silicon (Si)-based transistors and restricting further performance gains. To confront this challenge, research is actively exploring new materials and architectures. Among these promising candidates, the Indium Gallium Zinc Oxide (IGZO) channel transistor has emerged as particularly attractive due to its advantages in low leakage current. Despite the advantages of IGZO for low-power consumption, achieving high field-effect mobility, crucial for fast operation speeds in memory devices, remains a significant challenge.To overcome this limitation, a novel machine learning (ML)-based approach is proposed for fabricating high-performance, ultra-thin IGZO thin-film transistors (TFTs) using sputtering process for the channel. This method optimizes the sputtering process, resulting in IGZO TFTs with outstanding multiple electrical properties simultaneously. The fabricated TFTs exhibit a high field-effect mobility of 33.2 cm²/V·s, a near-zero threshold voltage of -0.05 V, and a channel with a sub-10nm thickness. The performance of the fabricated TFTs is comparable to that of transistors produced by Atomic Layer Deposition (ALD), a technique renowned for its ability to create ultra-thin films with high quality. This achievement implies the potential of sputtering process to overcome the throughput challenges of ALD. Leveraging machine learning's strengths, the proposed method guides the optimization of the sputtering process, eliminating the need for traditional labor-intensive and trial-and-error methods. This approach has the potential to significantly accelerate the development of next-generation memory devices with unprecedented efficiency and speed.

Regioselective Electrocatalytic Deuteration Reactions in PEM Reactor

Although organic chemistry has brought significant benefits to humanity by providing a wide range of chemicals, conventional production methods often generate a significant amount of chemical waste. As the need for sustainability increases, there is a growing demand for organic reactions that utilize fewer chemical reagents, resulting in reduced waste generation. In this context, electrochemical synthetic methods have garnered great attention in recent decades. Unlike general redox reactions in organic synthesis, which require stoichiometric amounts of oxidants and reductants, electrochemical oxidation and reduction utilize electricity as a substitute for these chemicals, leading to a reduction in chemical usage and waste production.In industrial-scale synthesis, the characteristics of electro-organic synthesis, particularly its applicability in waste reduction, become increasingly important. However, scaling up electrochemical reactions presents a hurdle, as the reaction occurs on the surface of the electrodes, necessitating larger electrode surface areas. According to the square-cube law, as the reaction scale increases, the ratio of the electrode's surface area to the reaction volume decreases proportionally. This implies a physical limitation to scaling up electro-organic reactions.To circumvent this limitation and enable scalable and sustainable synthesis, flow reactors offer a viable solution. Flow synthesis offers numerous benefits over conventional batch reactions and proves advantageous for scaling up. Flow reactors allow for the successive insertion of reactants into the reactor and subsequent passage outside, eliminating the need to enlarge the reactor to increase the reaction scale.Herein, we report a flow electrosynthesis using a proton-exchange membrane (PEM) reactor. With the PEM reactor, water serves as the proton source for the hydrogenation and semi-hydrogenation of unsaturated compounds, as well as bis-deuterated alkenes via the semi-hydrogenation of alkynes using heavy water as a deuterium source. Additionally, we found that reductive deuteration reactions could be applicable to the dehalogenation of (hetero)aryl halides, thereby producing mono-deuterated compounds.

Development of Vertical Structured TFT Using Interfacial Oxidation

As advancements in display technology persist, ongoing research endeavors into Thin-Film Transistors (TFTs) to move forwards display evolution endure. Among the various semiconductors in TFT technologies, oxide TFTs have garnered considerable attention due to their manifold advantages, including heightened electron mobility in comparison to a-Si, superior transmittance, and suitability for medium to large-scale applications.Recent developments in display engineering suggest that Augmented Reality (AR), Virtual Reality (VR), and flexible displays are the vanguards of next-generation displays. These rapidly expanding applications desire several specifications for TFTs, such as minimalized occupied area, high resolution, low-power operation, etc. Given the challenges associated with fulfilling these mentioned requirements using conventional TFT technologies is difficult due to the facing physical limitations. Therefore, a novel enhancement methodology becomes necessary. In response to this necessity, there has been a rapidly growing interest in Vertical TFTs (VTFTs), which represent a structural refinement of next-generation TFTs in recent years.VTFT was propounded by Professor Y. Uchida of Japan in 1984 utilizing a-Si [1]. In the V-TFT structure, the source and drain electrodes are vertically separated by an insulator spacer. The annel lies between them, attached to the spacer's sidewall, directing carrier flow vertically. Therefore, VTFTs can easily achieve short channel lengths under 1µm, larger aspect ratios W/L, and higher packaging density, greatly reducing the occupied area over conventional TFTs. Nevertheless, the development of previously proposed VTFTs facing into unresolved challenges, including process complexity attributable to the requisite spacers and interlayer dielectrics (ILDs), as well as reduced yields due to the process complexity.M. Chandra Sekhar et al., have postulated a methodology [2] employing the oxide layer formed at the interface as a leading layer during the deposition of metal and oxide, subsequently evaluating its reliability. This oxide film is termed Interfacial Oxidation.As illustrated in Figure 1, our study introduces a novel VTFT processing methodology assured to improve process complexity and low yield rates, which represent inherent challenges in conventional VTFT fabrication.Tantalum (Ta), characterized by low Gibbs's free energy, is harnessed as the gate electrode, while Indium Tin Oxide (ITO) serves as the source and drain electrodes. Concurrently, an interfacial oxide film occurs through the heat treatment-induced interfacial oxidation reaction between ITO and Ta, serving as an insulating film. This innovative VTFT processing protocol offers the following advantages: 1) Substituting the gate electrode prevents the necessity for conventional spacers and prevents the deposition of an interlayer insulating film, thereby simplifying the fabrication process considerably. 2) The insulating layer conforms to the contour of the gate electrode, obviating the deposition process for the insulating layer. This prevents defects that may emerge during additional insulating layer processing, mitigating electrode damage and averting diminished yields. 3) As a result, VTFT configuration offers an exceedingly short channel in the nm range, corresponding to the gate thickness, thereby producing a low power consumption—an outstanding advantage for driving applications.Consequently, this research holds the potential to substantially contribute to the advancement of low-power electronic devices and the realization of next-generation display applications, encompassing form factor innovations, automotive integration, and AR/VR implementation, while simultaneously addressing the challenges posed by vertical TFT technology. Figure 1

Oxidation effects on the optical and electrical properties of MoS2 under controlled baking temperatures

As silicon-based semiconductor technology scales down to the nanoscale, it encounters significant physical limitations, including reduced electron mobility, short-channel effects, and increased heat generation, which hinder device performance and reliability. Two-dimensional (2D) semiconductors, such as molybdenum disulfide (MoS2), offer great potential with superior electrical properties at the nanoscale, but the issue of excessive heat generation in highly integrated circuits persists. Therefore, it is essential to investigate the thermal durability of MoS2 under various heating conditions and its impact on physical properties and device performance. In this study, we systematically investigated the oxidation behavior and related physical property variations of CVD-grown MoS2 monolayers by baking them at different temperatures. It was clearly revealed that high-temperature baking induces p-doping and structural deformation, significantly altering optical and electrical properties. Despite the degradation in device performance, reduced interfacial Coulomb scattering was observed, suggesting potential for improved device stability. This study underscores the importance of understanding thermal stability to accelerate the development of 2D semiconductors for next-generation electronic devices.

Role of Communication in Adaptive Mechanisms of Micro and Small Entrepreneurship for Disabled in Indonesia

People with disabilities face multiple challenges in entrepreneurship, including physical limitations, accessibility to resources, and social stigma that often hinders their business development. This study aims to explore the challenges and adaptive strategies faced by people with disabilities in entrepreneurship and identify critical factors that can support their business success. Focusing on the use of communication technology and financial support, this research examines how adaptive training and inclusive policies can influence the success of disabled entrepreneurs. The research methodology involves a literature review and data analysis from various sources to understand communication, adaptive mechanisms, micro and small entrepreneurship, and people with disabilities. Relevant data surrounding these variables were collected, summarized, and analyzed. This study underscores the pivotal role of communication in the adaptive mechanisms of micro and small enterprises operated by individuals with disabilities. Through an extensive literature review, it has been demonstrated that effective communication is essential for disabled entrepreneurs to establish robust social networks, engage with customers, and secure vital resources to address various business challenges.

(Invited) Impact of CMOS Miniaturization on Digital and RF Applications and Its Future

Semiconductors, especially CMOS LSIs (Complementary Metal-Oxide-Semiconductor Large-Scale Integrated Circuits), are fundamental to our contemporary highly intelligent society, exemplified by technologies like artificial intelligence (AI). The exceptional performance and functionality of current CMOS LSIs are largely attributed to the ongoing miniaturization of their core components: MOSFETs (Metal-Oxide-Semiconductor Field-Effect Transistors). Since the inception of MOS LSI production in the early 1970s, MOSFETs have undergone regular size reductions every 2 to 3 years. The minimum linewidth, which was 10 μm in 1970, has now shrunk to nearly one-thousandth of that size, approaching 10 nm. Each phase of MOSFET miniaturization has encountered formidable technological challenges, overcome through innovative solutions.However, we stand at a critical juncture. The relentless drive toward smaller MOSFETs is now approaching physical limits. The future trajectory of CMOS LSIs will veer away from further miniaturization and instead focus on channel stacking—a strategy to sustain progress. In this presentation, I delve into the history of CMOS LSI miniaturization, explore its impact on digital information processing and RF communication applications, and gaze into the post-miniaturization era, anticipating both opportunities and challenges.

Diagnostic performance of dual-energy computed tomography in detecting anterior cruciate ligament injuries: a systematic review and meta-analysis.

Anterior cruciate ligament (ACL) injuries are common and lead to significant physical limitations. While MRI is the diagnostic gold standard, its use is restricted in acute trauma cases due to contraindications and longer imaging times. Dual-energy computed tomography (DECT) has emerged as a potential alternative. This meta-analysis evaluates the diagnostic accuracy of DECT for ACL injuries. Following PRISMA guidelines, a comprehensive literature search was conducted using PubMed, Web of Science, Scopus, and Embase for studies published up to June 2024. Studies that provided diagnostic accuracy data for DECT in ACL ruptures were included. Metrics of diagnostic accuracy were aggregated using a bivariate random effects model. The meta-analysis, which included five studies with a total of 191 patients, found that DECT had a pooled sensitivity of 88.1% (95% CI, 78.0-93.9%) and a specificity of 82.0% (95% CI, 62.0-92.7%) for diagnosing ACL ruptures, with an AUC of 0.92 (95% CI, 0.72-0.96). For complete ruptures, sensitivity was 83.2% (95% CI, 68.2-92.0%), and specificity was 94.9% (95% CI, 92.2-96.7%), with an AUC of 0.96 (95% CI, 0.81-0.98). In acute/subacute settings, sensitivity was 89.4% (95% CI, 76.8-95.6%), and specificity was 82.1% (95% CI, 56.2-94.2%), with an AUC of 0.93 (95% CI, 0.71-0.97). Our findings suggest that DECT is a valuable diagnostic tool for ACL injuries, particularly as an adjunct or alternative when MRI is unavailable or contraindicated, enabling timely and accurate diagnosis.

Presenting and Evaluating a Smartwatch-Based Intervention for Smoking Relapse (StopWatch): Feasibility and Acceptability Study.

Despite the benefits of smoking cessation, maintaining abstinence during a quit attempt is difficult, and most attempts result in relapse. Innovative, evidence-based methods of preventing relapse are needed. We present a smartwatch-based relapse prevention system that uses passive detection of smoking to trigger just-in-time smoking cessation support. This study aims to evaluate the feasibility of hosting just-in-time smoking cessation support on a smartwatch and the acceptability of the "StopWatch" intervention on this platform. The person-based approach for intervention development was used to design the StopWatch smoking relapse prevention intervention. Intervention delivery was triggered by an algorithm identifying hand movements characteristic of smoking from the smartwatch's motion sensors, and the system-generated intervention messages (co-designed by smokers) were delivered on the smartwatch screen. A total of 18 smokers tested the intervention over a 2-week period, and at the end of this period, they provided qualitative feedback on the acceptability of both the intervention and the smartwatch platform. Participants reported that the smartwatch intervention increased their awareness of smoking and motivated them to quit. System-generated intervention messages were generally felt to be relevant and timely. There were some challenges with battery life that had implications for intervention adherence, and the bulkiness of the device and the notification style reduced some participants' acceptability of the smartwatch platform. Our findings indicate our smoking relapse prevention intervention and the use of a smartwatch as a platform to host a just-in-time behavior change intervention are both feasible and acceptable to most (12/18, 66%) participants as a relapse prevention intervention, but we identify some concerns around the physical limitations of the smartwatch device. In particular, the bulkiness of the device and the battery capacity present risks to adherence to the intervention and the potential for missed detections. We recommend that a longer-term efficacy trial be carried out as the next step.

Liquid Hopfield model: Retrieval and localization in multicomponent liquid mixtures

Biological mixtures, such as the cellular cytoplasm, are composed of a large number of different components. From this heterogeneity, ordered mesoscopic structures emerge, such as liquid phases with controlled composition. The competition of these structures for the same components raises several questions: what types of interactions allow the retrieval of multiple ordered mesoscopic structures, and what are the physical limitations for the retrieval of said structures. In this work, we develop an analytically tractable model for multicomponent liquids capable of retrieving states with target compositions. We name this model the liquid Hopfield model in reference to corresponding work in the theory of associative neural networks. In this model, we show that nonlinear repulsive interactions are a general requirement for retrieval of target structures. We demonstrate that this is because liquid mixtures at low temperatures tend to transition to phases with few components, a phenomenon that we term localization. Taken together, our results reveal a trade-off between retrieval and localization phenomena in liquid mixtures, and pave the way for other connections between the phenomenologies of neural computation and liquid mixtures.

Usability of an automated medication dispensation device and adherence dashboard: A study protocol.

Non-adherence to prescribed medication regimens can lead to suboptimal control of chronic health conditions and increased hospitalizations. Older adults may find it particularly challenging to self-manage medications due to physical and cognitive limitations, resulting in medication non-adherence. While automated medication dispensing technologies may offer a solution for medication self-management among older adults, these technologies must demonstrate usability before effectiveness can be investigated and products made available for widespread use. This study will aim to measure usability, workload, and unassisted task completion rates of an automated medication dispenser and medication adherence dashboard on the Medipense portal with older adults and their clinicians, respectively. This study is designed as a convergent parallel mixed-methods observational study with older adults and their clinicians. Usability will be examined with the use of the System Usability Scale (SUS) while NASA Load Index (NASA-TLX) will be utilized to assess the workload of both the device and the adherence monitoring platform. Cognitive walkthrough will be utilized prior to usability testing to identify series of steps required to use the automated dispenser and adherence dashboard. The study will assess the unassisted task completion rates to successfully operate the device. Semi-structured interviews with both types of participants will provide qualitative data with which to comprehensively gauge the automated dispenser user experience. The results of this study will allow us to examine usability of both the automated medication dispensing system and the adherence monitoring dashboard from older adult and health-care provider perspectives. The results of this study will highlight and address the challenges with usability that older adults and health-care providers may face with this device and dashboard. The results of this study will be used to optimize the usability of both the automated medication dispenser and the adherence dashboard. In clinical practice, usability of technology is important to establish prior to full-scale implementation. Products that are not user friendly, add to workload, impact workflow, or are difficult to navigate by both clinicians and population in general may not be adopted. Usability permits an evaluation of the products, to identify problems that must be addressed prior to implementation and to ensure products are useful in clinical practice.

Forensic Investigation Capabilities of Microsoft Azure: A Comprehensive Analysis and Its Significance in Advancing Cloud Cyber Forensics

This article delves into Microsoft Azure’s cyber forensic capabilities, focusing on the unique challenges in cloud security incident investigation. Cloud services are growing in popularity, and Azure’s shared responsibility model, multi-tenant nature, and dynamically scalable resources offer unique advantages and complexities for digital forensics. These factors complicate forensic evidence collection, preservation, and analysis. Data collection, logging, and virtual machine analysis are covered, considering physical infrastructure restrictions and cloud data transience. It evaluates Azure-native and third-party forensic tools and recommends methods that ensure effective investigations while adhering to legal and regulatory standards. It also describes how AI and machine learning automate data analysis in forensic investigations, improving speed and accuracy. This integration advances cyber forensic methods and sets new standards for future innovations. Unified Audit Logs (UALs) in Azure are examined, focusing on how Azure Data Explorer and Kusto Query Language (KQL) can effectively parse and query large datasets and unstructured data to detect sophisticated cyber threats. The findings provide a framework for other organizations to improve forensic analysis, advancing cloud cyber forensics while bridging theoretical practices and practical applications, enhancing organizations’ ability to combat increasingly sophisticated cybercrime.

Navigating life with single-ventricle CHD: psychosocial needs across adulthood

Abstract Objective: The population of adults with single-ventricle congenital heart disease (CHD) is growing. This study explores their lived experiences through an adult developmental psychology framework. Methods: Individuals aged 18 and older with single-ventricle CHD participated in Experience Group sessions and 1:1 interviews. Sessions were transcribed and analysed thematically. Themes were categorized by developmental domains and age group. Results: Of the 29 participants, 18 (62%) were female, 10 (35%) were emerging (18–29 years), 13 (45%) were established (30–45 years), and 6 (21%) were midlife adults (46–60 years). Emerging adults expressed reluctance to initiate romantic relationships and fear of burdening partners, while established adults reported strong relationships with partners deeply involved in caregiving. Emerging adults struggled with finding fulfilling work that meets their health needs, whereas established and midlife adults faced unemployment or early retirement due to health limits. Family dynamics shifted, with established and midlife adults educating their children to become caregivers. Physical limitations and low self-rated health were consistent across life stages, and midlife adults did not worry about traditional chronic conditions. Mental health concerns, including anxiety and depression, persisted across all life stages, but resiliency and positive affect were also evident. Conclusion: Adults with single-ventricle CHD experience developmental milestones differently, indicating the need for early anticipatory guidance in these domains to achieve optimal outcomes in adulthood.

Obstacles to Instructional Leadership in Rural Areas

This study aims to examine the factors that hinder school principals in rural areas from fulfilling their instructional leadership roles. By identifying the challenges faced by school principals in the context of instructional leadership, it is anticipated that the research will fill a gap in literature and provide solutions for researchers. The study was conducted using a basic qualitative research design, which aims to gather in-depth information about the challenges and experiences faced by participants. The research included ten principals from public primary and secondary schools in rural areas of Turkey’s Western Black Sea Region as participants. Data was collected using interviews with open-ended questions and observation techniques. Based on the collected data, the factors that hinder instructional leadership in rural school principals were categorized under three main themes and five subcategories. The findings of the study reveal the primary factors limiting the active participation of rural school principals in instructional leadership: low income and educational levels, disengaged family background, physical limitations arising from school facilities, financial constraints, lack of human resources, and excessive workload. These findings provide significant evidence for understanding the reasons why school principals in rural areas are unable to fully perform their instructional leadership roles.

The Impact of AI and VR/AR Technologies on Yuan Blue-and-White Porcelain Art

Yuan blue-and-white porcelain, a treasure of Chinese ceramic art, is renowned worldwide for its unique artistic value and cultural significance. With the continuous advancement of artificial intelligence (AI) technology, the artistic innovation of Yuan blue-and-white porcelain is experiencing new opportunities. AI technology not only improves the efficiency and quality of creation but also breaks through traditional physical limitations, enabling the creation of more diverse and creative artworks. By integrating augmented reality (AR) and virtual reality (VR) technologies, AI provides new ways to display and interact with Yuan blue-and-white porcelain art. In non-physical artistic innovation, AI generates new designs through deep learning algorithms, breaking free from the constraints of traditional handmade processes and creating diverse works. Technologies like generative adversarial networks (GANs) can produce highly realistic Yuan blue-and-white designs, while convolutional neural networks (CNNs) can quickly generate design sketches, enhancing creative efficiency. AI can also optimize designs, improving the artistic quality and visual effects of the works.AR and VR technologies offer immersive experiences and interactivity for the audience. Through virtual exhibition spaces and AR applications, viewers can appreciate Yuan blue-and-white artworks as if they were physically present, enhancing interactivity and visual appeal. VR technology, through virtual exhibitions and other means, enhances the viewing experience and impact of the artworks. The application of AI technology in the non-physical artistic innovation of Yuan blue-and-white porcelain not only enhances creation efficiency and quality but also brings limitless possibilities to artistic creation. The combination of AR and VR technologies further enhances the visual appeal and interactivity of Yuan blue-and-white art. As technology continues to advance, AI will play an increasingly important role in the artistic innovation of Yuan blue-and-white porcelain, creating more splendid artworks.

Exploring the lived experiences of deep vein thrombosis patients in Lahore, Pakistan: a qualitative phenomenological study on healthcare challenges, resilience and social support

ObjectiveThis study aimed to explore and describe the lived psychological and emotional experiences of sufferers of deep vein thrombosis (DVT) and to narrate the effect of those experiences on their...

Network analysis of anxiety and depressive symptoms among patients with heart failure

BackgroundAnxiety and depressive symptoms are common among patients with heart failure (HF). Physical limitations, lifestyle changes, and uncertainties related to HF can result in the development or exacerbating of anxiety and depressive symptoms. However, the central and bridge symptoms of anxiety and depressive symptoms network among patients with HF remain unclear. Network analysis is a statistical method that can discover and visualize complex relationships between multiple variables. This study aimed to establish a network of anxiety and depressive symptoms and identify the central and bridge symptoms in this network among patients with HF.MethodsThis study employed a cross-sectional study design and convenience sampling to recruit patients with HF. This study followed the Helsinki Declaration and was approved by the Research Ethics Committee of Hospital. The Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire (PHQ-9) were administered to evaluate anxiety and depressive symptoms among patients with HF, respectively. Network analysis of anxiety and depressive symptoms was performed using R.ResultsIn the anxiety and depressive symptoms network, PHQ2 (feeling down, depressed, or hopeless), PHQ7 (inability to concentrate), and GAD4 (difficulty relaxing) were the most central symptoms. Anxiety and depressive symptoms were linked by PHQ2 (feeling down, depressed, or hopeless), GAD6 (becoming easily annoyed or impatient), GAD5 (unable to sit still because of anxiety), GAD7 (feeling afraid that something terrible is about to happen), and PHQ6 (feeling bad or like a failure, or disappointing oneself or family).ConclusionsThis study identified the central and bridge symptoms in a network of anxiety and depressive symptoms. Targeting these symptoms can contribute to interventions for patients with HF at risk of—or suffering from—anxiety and depressive symptoms, which can be effective in reducing the comorbidity of anxiety and depression.

Self-catalyzed growth of sub-25-nm-diameter InAs nanowire arrays on Si patterned substrate

The feature size of advanced Si-based chips is approaching its physical limit, and it is difficult to continue Moore's Law by simply pursuing the technical route of miniaturizing device size to increase the integrated density. III-V nanowire devices represented by InAs material have much higher mobility than Si based devices, but they have not been successfully applied to CMOS nanowire devices and have not shown excellent performance. The reason is that the hole mobility of III-V materials is much lower than their electron mobility. If the nanowire diameter becomes ultrafine, the quantum confinement effect becomes more prominent, the light hole band will reverse above the heavy hole band, and the hole mobility will be greatly increased. Aiming at the integrability of III-V high mobility CMOS devices on Si, how to prepare ultrafine InAs nanowire arrays on Si/SiO2 patterned substrates has been studied in this work. New method in this work has solved the problem that the nanohole will enlarge due to etching side wall of nanohole by HF process before growth. A technology and mechanism of ultrafine InAs nanowire arrays grown by this method was developed, and the smallest diameter of nanowire in array has reached only 25 nm.

Racial and Ethnic Disparities in Perceived Health Status Among Patients With Cardiovascular Disease.

Understanding health outcomes among people with cardiovascular disease (CVD) is crucial for improving treatment strategies and patient quality of life. This study investigated racial and ethnic disparities in perceived health status among non-Hispanic Black, Hispanic, and non-Hispanic White adults with CVD. The study had a retrospective cross-sectional design and used data from the Medical Expenditure Panel Survey spanning 8 calendar years (2014-2021). The study population consisted of adults diagnosed with various CVDs. We used ordinal logistic regression models adjusted for demographic and socioeconomic characteristics, CVD severity, comorbidities, and health care expenditures to assess racial and ethnic differences in perceived health status. Among the 11,715 (weighted frequency, 15,431,283) adults with CVD, we observed significant differences in perceived health status across racial and ethnic cohorts. The unadjusted analysis showed that non-Hispanic Black adults had significantly higher odds than non-Hispanic White adults of perceiving their health as poorer (odds ratio [OR]= 1.89; 95% CI, 1.74-2.07; P < .001), with a similar observation among Hispanic adults (OR = 2.05; 95% CI, 1.85-2.26; P < .001). Although female sex, higher education, and better income had protective effects on perceived health status independent of race, we found significant racial and ethnic differences in the effect of older age, physical and cognitive limitations, and health insurance status on perceived health status. This study revealed substantial racial disparities in perceived health status among adults with CVD, with notable differences in the effects of predictive factors. Addressing these disparities requires targeted interventions to improve health care access and enhance socioeconomic conditions tailored to the needs and experiences of racial and ethnic populations.

Mathematical Optimization of Electric Motor Designs

When designing and improving the performance of electric motors, mathematical optimization is very important. The main goals are usually to make the motors more efficient, lower their costs, and work within certain limits. The main topic of this study is how to improve electric motor designs using advanced optimization methods, such as multi-objective optimization. The study looks at how to use different types of computer algorithms together, like gradient-based methods, genetic algorithms, and particle swarm optimization, to solve difficult design problems. Some of these problems are reducing energy loss, making the best use of materials, and finding the right balance between different performance measures such as speed, power density, and temperature management. Building mathematical models of the motor's physical and functional features is the first step in this method. Then, optimization methods are applied to these models. Finite element analysis (FEA) is used to correctly model the motor's electric behavior. This makes sure that the optimization process considers physical limits and nonlinearities that happen in the real world. The study also looks into how different design factors, like the shape of the motor's core, the way the windings are set up, and the materials used, affect its total performance. The study also looks at the fact that motor design has more than one goal by using Pareto front analysis to find the best ways to balance different goals. This lets people come up with motor designs that are good for speed, efficiency, and cost-effectiveness. Case studies of the design of different kinds of electric motors, such as induction motors, permanent magnet synchronous motors (PMSMs), and brushless DC motors (BLDCs), show that the proposed optimization method works well. The results show that mathematical optimization has the ability to make the planning process a lot better. This could lead to motors that work better, cost less, and are better suited to certain uses. The study ends with a talk of how optimization methods could be used in the future to improve the design of electric motors, especially for new technologies like electric cars and green energy systems.

The Role of Technology in Inclusive Education: Challenges and Opportunities in Developing Countries

The objective of inclusive education is to guarantee that every individual, irrespective of physical, intellectual, social or emotional limitations, is provided with equal access to educational opportunities. The advent of technology has led to the emergence of new possibilities for the implementation of inclusive education, particularly in resource-constrained developing countries. However, the implementation of technology in inclusive education in developing countries is confronted with a multitude of challenges, encompassing deficiencies in infrastructure and constraints in educator training. This article seeks to examine the role of technology in inclusive education in developing countries and identify the challenges and opportunities that arise. The research employs a literature review methodology to collate data from pertinent studies and proffer policy recommendations to enhance the role of technology in inclusive education.