In this article, an efficient die bonding technology based on silver sintering due to induction heating is presented. By using this technology, the heat for the sintering reaction is locally limited to the bonding area and the heating of the entire power module is avoided. Furthermore, the sintering reaction is promoted due to current flow between the silver particles and the sintering time is drastically reduced. Next to the experimental trials presented in this paper, FE-simulation methods were applied in order to develop a suitable induction coil geometry for the bonding of a diode to a direct bonded copper (DBC) substrate. Additional heating and sintering tests verified the reliability of the simulation model as well as the technological approach. Diodes were successfully bonded during the experiments and were analyzed by means of scanning electron microscopy (SEM) and function tests in order to qualify the inductive bonding technology. The results presented in this paper demonstrate, that induction heating has high potential for cost effective production in the field of die-attach and can drastically increase the output in power electronics production.

The extracellular matrix (ECM) is earning an increasingly relevant role in many disease states and the process of aging. Analyzing these disease states is possible with GWAS and PheWAS methodology, and through our analysis, we aimed to explore the relationships between polymorphisms in the compendium of ECM genes (i.e., matrisome genes) in various disease states. A significant contribution on the part of the ECM polymorphisms is evident in many varying types of diseases, particularly those in the core matrisome genes. Our results confirm previous links to connective tissue disorders, but also unearth new and underexplored relationships with neurological, psychiatric, and age-related disease states. Upon analysis of drug indications for gene-disease relationships, we identified numerous targets that may be repurposed for age-related pathology. The identification of ECM polymorphisms and their contribution to disease plays an integral role in future therapeutic developments, drug repurposing, precision medicine, and personalized care.

Objective: Determine the feasibility of utilizing longitudinal electronic dental record (EDR) data to track change over time in patient periodontal disease (PD) and to generate three patient cohorts: 1) patients whose disease did not change over time, 2) patients whose PD progressed, and 3) patients whose disease improved over time using informatics approaches. Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between January 1, 2009, and December 31, 2014, at the Indiana University School of Dentistry (IUSD) clinics. We developed and tested three automated computer applications to: 1) diagnose periodontitis cases from periodontal charting, 2) retrieve clinician-documented diagnoses from clinical notes, and 3) track disease change over time. We also evaluated the density of longi-tudinal EDR data for the following follow-up times: 1) none, 2) up to 5 years, 3) >5 and <=10 years, and 4) >10 and <=15 years Results: Thirty-four percent (n=9,954) of the study cohort had up to five years of follow-up visits with an average of 2.78 visits with periodontal charting information. An average of three patient visits per year that contained periodontal charts (63,552) were utilized to obtain a diagnosis, which is considered excellent. For clinician-documented diagnoses from clinical notes, 42% of patients (n=5,562) had at least two PD diagnoses to determine their disease change. In this cohort with cli-nician-documented diagnoses, 72% percent of patients (n=3,919) did not have a disease status change between their first and last visits, 669 (13%) patients' disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We found excellent longitudinal data when diagnoses generated from periodontal charting were considered (three visits per pa-tient). This information can be now utilized for studying the clinical course of periodontitis.

People with diabetic foot frequently exhibit poor gait and balance. However, there is no review to inform digital biomarkers of poor gait and balance related to diabetic foot, measurable by wearables outside traditional gait laboratories. Such information could assist in designing remote patient monitoring platform to track changes in gait and balance dysfunction among people with diabetic foot for timely referral and intervention. Accordingly, we conducted a web-based review using PubMed. Our search was limited to human subjects and English-written papers published in peer-reviewed journals. We identified 20 papers in this review. We found preliminary evidence of digital biomarkers of gait and balance dysfunction in people with diabetic foot, measured by wearables, such as slow gait speed, large gait variability, unstable gait initiation, and large body sway. However, due to heterogeneities in included papers in terms of study design, movement tasks, and small sample size, more studies are recommended to confirm this preliminary evidence. Additionally, based on our review, we recommend establishing appropriate strategies to successfully implement wearable-based assessment into clinical practice for diabetic foot care.

In deaths and diseases attributed to tobacco smoke cardiovascular events exceed cancer and respiratory diseases. Second hand smoke (SHS) promotes the development of arteriosclerosis and can also trigger acute changes of endothelial function and of blood coagulability. Indoor smoking bans reduced coronary syndrome and myocardial infarction 10-20% within one year and were followed by sustainable decreases of stroke and diabetes. With a smoke-free hospitality industry people recognized tobacco smoke as an air pollutant, smoking in public was denormalized and social acceptance of smoking in front of children and pregnant women decreased also in homes and in cars. Combined effects with ambient air pollution are proven for active smoking and suspected for SHS. Contamination with third hand smoke (THS, “cold smoke”) persists for months in homes and cars, creating secondary pollutants that in some cases are more toxic (e.g., tobacco-specific nitrosamines). Remnants found in air, dust, and on surfaces (carpets, wallpapers, upholstery, soft toys) were associated with their metabolites in saliva and urine of children and with elevated levels of nicotine on hands and cotinine in urine of nonsmokers residing in homes previously occupied by smokers. In animal experiments effects of THS were found on thrombogenesis, insulin resistance through oxidative stress, on the developing immune system, lipid metabolism and alterations in liver, lung, skin and behavior. Much less is known about health effects for bystanders from the aerosols exhaled during “vaping” of e-cigarettes, but nicotine and other toxins from e-cigarettes are certainly a hazard, which should be prevented by the use of dermal and oral nicotine products, which are safer for nicotine replacement and without risk for bystanders.

This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section, the basic taxonomy of attribute identification is adopted in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The basis of theoretical considerations is Dezert-Smarandache theory (DSmT) of inference. The paper presents and practically uses for combining identification information from different ESM sensors and radars six information fusion rules proposed by DSmT - the Proportional Conflict Redistribution rules (PCR1, PCR2, PCR3, PCR4, PCR5 and PCR6). In the paper, rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. It was proposed that each signal vector sent by the ESM sensor contained an extension specifying a randomized identification declaration (hypothesis) - basic belief assignment (BBA). The paper also presents a model for determining the basic belief assignment for a combined primary and secondary radar. Results of the PCR rules of sensor information combining for different scenarios of radio-electronic situation (deterministic and Monte Carlo) are presented in the final part of the paper. They confirm the legitimacy of the use of Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.

This study evaluated the effectiveness of an electronic system for managing drug-sensitive pulmonary tuberculosis patients in the Kyrgyz Republic. This was a cohort study using programmatic data. The study included patients registered on the paper-based system in 2019 and the electronic system between June 2021 and May 2022. Data was taken from 302 individuals from the electronic system for completeness and concordance in comparison with the paper-based system. The study showed that for most variables the completeness and concordance was 85.3%-93.0% and was lowest for non-mandatory fields such as medication side effects (26.8% vs 13.6%). No significant difference was observed in time taken from symptom onset to diagnosis and treatment initiation between the two systems. However, the electronic system had a significantly higher percentage of patients who initiated treatment on the same day of diagnosis (80.3% vs. 57.1%). The proportion with successful outcomes was similar in both groups, but the electronic system had a significantly lower proportion of patients with outcomes that were not evaluated or recorded (4.8% vs. 14.3%, p &lt; 0.001). The study highlights the potential advantages of implementing an electronic TB register system for improving records. We advocate for similar studies in other regions in Kyrgyz Republic.

The purpose of water treatment through ultraviolet (UV) radiation is to interrupt the development and multiplication of microorganisms by preventing their growth and reproduction.Ultraviolet treatment has become a very affordable solution to produce clean water of optimal quality in regions where access to drinking water is essential. The experimental water treatment unit is powered by a photovoltaic (PV) source. It incorporates a discharge lamp used to generate ultraviolet radiation, which is harnessed to address bacteriological issues related to water quality. This lamp is continuously powered by a photovoltaic (PV) source through an inverter and an electronic ballast. The water treatment system also includes a motor pump designed to draw contaminated water from the input reservoir, a flow control valve to adjust flow rates as needed, and a filter aimed at enhancing the quality of the contaminated water. The water circulates between the input reservoir (contaminated water) and the output reservoir (treated water) through the UV lamp. The relationship between the intensity of the UV lamp and the water flow rate can ensure an adequate water quality.

The aim of study was to investigate epidemiology aspects of magnetic resonance imaging (MRI) during COVID-19 pandemic. The study comprised depersonalized residents of Tomsk and Tomsk Region (n = 1714). Invitations to take online survey were sent to 50,000 residents by target SMS with response rate of 1.2% (n = 727, Cohort 1). Cohort 2 comprised retrospective patients (n = 987) who underwent contrast-enhanced cardiac MRI (CMR) in 2019-2022. Referrals, clinical characteristics, diagnosis, gender, age, past COVID-19, MRI study protocols, and MRI data were analyzed. 29% of respondents in cohort 1 received MRI examination within past two years; 26% of respondents considered MRI the most informative imaging modality for detecting COVID-19 pneumonia; 12% of respondents reported MRI unavailable. Proportion of CMR among MRI studies increased during COVID-19 pandemic, and maximum incidence of cardiac diseases detected by MRI was in 2021. Incidence of myocardial fibrosis increased from ~67% in 2019 to ~84% in 2022. The rate of outpatient MRI studies significantly increased in 2020, but returned to pre-pandemic level in 2021. COVID-19 pandemic increased the need for MRI and CMR. Patients with history of COVID-19 had persistent and newly occurring symptoms of myocardial damage suggesting chronic cardiac involvement requiring continuous follow-up.

In this ‘New Normal' post-COVID-19 modern world, people's health is becoming increasingly important to track. An advanced technology that uses sensory instruments to track and record critical parameters and communicates with others is the need of the time. It's difficult to keep track of all of the medical parameters and post-operative data of people with non-communicable diseases like diabetes and heart disease on a continuous basis. The system discussed here to be designed for patients who are confined to their homes, particularly when going out and being exposed to the outer world is prohibited. This paper proposed a groundbreaking health management system based on the Internet of Things (IoT) for accessing patient medical parameters in both local and remote areas. When a person's wellbeing becomes urgent, this initiative seeks to send an emergency alert to family members or loved ones. A cloud server records data from the patient's temperature sensor and pulse sensor; the data is analyzed using support vector machine algorithms to identify irregular conditions, and an emergency message is sent to the rest of the family via a mobile application, as well as a warning message to the nearest hospital.

Generalized relativistic pseudopotentials (GRPP) of atomic cores implying the use of different potentials for atomic electronic shells with different principal quantum numbers give rise to accurate and reliable relativistic electronic structure models of atoms, molecules, clusters, and solids. These models readily incorporate the effects of Breit electron-electron interactions and one-loop quantum electrodynamics effects. Here we report the computational procedure for evaluating one-electron integrals of GRPP over contracted Gaussian functions. This procedure was implemented in a library of routines named LIBGRPP, which can be integrated into existing quantum chemistry software, thus enabling the application of various methods to solve the many-electron problem with GRPPs. Pilot applications to electronic transitions in the ThO and UO2 molecules using the new library and intermediate-Hamiltonian Fock space relativistic coupled cluster method are presented. The results clearly demonstrate that rather economical tiny-core GRPP models can exceed in accuracy relativistic all-electron models defined by Dirac-Coulomb and Dirac-Coulomb-Gaunt Hamiltonians.

For better export marketing strategies (EMS), companies mobilize their internal resources, which are managerial commitment, firm experience, and product uniqueness. However, Small businesses with constrained resources cannot be well explained with this view. So, more research on how small business come up with EMS have been called for. To explain how resource-restricted firms which rely heavely on entrepreneur, this study adopted the concept of dynamic managerial capabilities (DMCs) and resource versatility to better explain small business exports. We analyzed small businesses in Mongolia with qualitative research methods, including interviews with entrepreneurs and support organizations, site visits, and group discussions. We suggest international dynamic marketing capabilities (IDMCs), which are entrepreneurial orientation, networking capability, and versatile dynamic capability for small business. Theoretical and managerial implications are discussed.

1) Background: Capturing patients’ medical histories significantly influences clinical decisions. Errors in this process lead to clinical errors, increase costs and dissatisfaction among physicians and patients. Physicians in developing countries are overloaded with patients and cannot always follow the proper history-taking procedure. The challenges are acknowledged; however, a comprehensive understanding of the status and the remedies remained unexplored. 2) Objective: This paper aims to investigate the workload, history-taking challenges, and the willingness of the physicians to accept digital solutions. 3) Methods: A cross-sectional online survey was conducted on 104 physicians across Bangladesh, featuring 22 questions regarding their professional environment, workload, digitization status of health records, challenges in history-taking, and attitudes toward adopting digital solutions for managing patient histories; 4) Results: 92.67% of the physicians face workloads, 88.46% struggle in medical history-taking, and only 4.81% use digital medical records. About 70% struggle to complete the necessary history-taking steps, emphasizing the urgent need for solutions. An AI-based Smart Health Gantt Chart (SHGC) system has been introduced for their instant feedback. 93.27% of physicians expressed their willingness to use such a system. 5) Conclusions: The proposed SHGC has the potential to enhance healthcare efficiency in developing nations, benefit physicians, and improve patient-centered care.

Volatile organic compounds (VOCs) released from plants have been correlated with disease-status. Analysis of VOCs using GC-MS is time-consuming, laboratory-based, and requires specialist training. Electronic nose devices (E-nose) provide a portable alternative. Three different E-nose devices were compared to assess how accurately they could detect Mango Twig Tip Dieback and Panama disease in banana. The devices were initially trained on known volatiles, then pure cultures of Pantoea sp., Staphylococcus sp., and Fusarium odoratissimum, and finally, on infected and healthy mango leaves and field-collected, infected banana pseudo-stems. The experiments were repeated three times with six replicates for each host-pathogen pair. The variation between healthy and infected host materials was evaluated by principal component and linear discriminant analysis, cross-validation and chemometric data analysis. GC-MS analysis was conducted contemporaneously and identified an 80% similarity between healthy and infected plant material. The portable C 320 was 100% successful in discriminating known volatiles but had a low capability in differentiating healthy and infected plant substrates. The advanced devices (PEN 3 / MSEM 160) successfully detected healthy and diseased samples with a high variance. The results suggest that E-nose devices are more sensitive and accurate in detecting changes of VOCs between healthy and infected plants compared to headspace GC-MS.

: Considering that Einstein's relation between the diffusion coefficient and the drift mobility of the free randomly moving charge carriers in homogeneous materials including metals is always valid, it is shown that the effective electric force acting on free electrons in metal depends on the ratio between the kinetic free electron energy at the Fermi surface to the classical particle energy 3kT/2. The electrical resistivity of elemental metals dependence on very low temperatures has the quadratic term, which has been explained by electron-electron scattering. In this paper, it is shown that the quadratic term of the electrical resistivity at low temperatures is caused by scattering of the free RM electrons by electronic defects due to linear effective free electron scattering cross-section dependence on temperature, but not by electron-electron scattering.

A conventional electrical grid mostly depends on the electrical power generated from fossil fuels. However, the pollutants from fossil fuels are the key factors for adverse climate change. Most of the developed countries of the world have already recognized the fact that the energy mix requires to be diversified by incorporating renewable energy. This is especially relevant for many of the member countries of the Organization of Islamic Cooperation (OIC), consisting of 57 countries, whose abundance of fossil fuel reserve indicates that much of their electric power is still generated from fossil fuels. In order to integrate renewable energy sources into the hybrid energy mix, an existing conventional grid needs to undergo drastic changes. Alongside this, the population boom in the OIC member countries has caused higher demand for a steady supply of electricity that the conventional grids have long been struggling to cope with. With a view to solving this multifaceted problem, incorporation of the smart power management schemes is indispensable using a smart electrical grid, where information and communications technology is integrated into its major building blocks. This allows advanced applications of a grid, such as the formation of micro-grids, demand-side management, energy storage, high-tech power electronic converters, etc. As the smart grids are being adopted by many developed countries, it is high time for the OIC member countries to pay due attention to this development, if they have not already done so. This paper explains, with special focus on the OIC member countries, the various smart power management technologies, their operations and applications, and the benefits and challenges. Then it goes on to carry out the Strength-Weakness-Opportunity-Threat with Analytical-Heuristic-Procedure (SWOT-AHP) analysis to evaluate its feasibility of incorporation and the underlying strategies appropriate for its implementation. Furthermore, a Hybrid Multi-Criteria-Decision-Making (MCDM) analysis is performed to evaluate the sequence of the emphasis that should be given on each of the technologies from those available for the smart power management initiative. Finally, the study reinforces the stance by drawing parallels from the UN Sustainable Development Goals (SDG) and highlights the importance of the smart grid in line with the global vision of SDG. This paper aims at assisting the decision-makers in implementing smart power management schemes in the OIC member countries, in particular, and other countries of the world, in general.

Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems in which systematic architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope up with current Information and Communication Technologies (ICT). The distributed generation in smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review on architecture for smart grids. An in depth analysis of layered and agent based architectures is presented and compared under various domains.

A new framework in quantum chemistry has been proposed recently ("An approach to first principles electronic structure calculation by symbolic-numeric computation'' by A. Kikuchi). It is based on the modern technique of computational algebraic geometry, viz. the symbolic computation of polynomial systems. Although this framework belongs to molecular orbital theory, it fully adopts the symbolic method. The analytic integrals in the secular equations are approximated by the polynomials. The indeterminate variables of polynomials represent the wave-functions and other parameters for the optimization, such as atomic positions and contraction coefficients of atomic orbitals. Then the symbolic computation digests and decomposes the polynomials into a tame form of the set of equations, to which numerical computations are easily applied. The key technique is Grröbner basis theory, by which one can investigate the electronic structure by unraveling the entangled relations of the involved variables. In this article, at first, we demonstrate the featured result of this new theory. Next, we expound the mathematical basics concerning computational algebraic geometry, which are necessitated in our study. We will see how highly abstract ideas of polynomial algebra would be applied to the solution of the definite problems in quantum mechanics. We solve simple problems in "quantum chemistry in algebraic variety'' by means of algebraic approach. Finally, we review several topics related to polynomial computation, whereby we shall have an outlook for the future direction of the research.

This review article is focused on the analysis of the state of the art of sensors for guided 9 ultrasonic waves for the detection and localization of impacts, therefore of interest for the structural 10 health monitoring (SHM). The recent developments in sensor technologies are then reported and 11 discussed through the many references in recent scientific literature. The physical phenomena re-12 lated to impact event and the main physical quantities are then introduced to discuss their im-13 portance in the development of the hardware and software components for SHM systems. An im-14 portant aspect of the article is the description of the different ultrasonic sensor technologies cur-15 rently present in the literature and what advantages and disadvantages they could bring, in relation 16 to the various phenomena investigated. In this context, the analysis of the front-end electronics is 17 deepened, the type of data transmission both in terms of wired and wireless technology and in terms 18 of online and offline signal processing. The integration aspects of sensors for the creation of net-19 works with autonomous nodes with the possibility of powering through energy harvesting devices 20 and the embedded processing capacity is also studied. Finally, the emerging sector of processing 21 techniques using deep learning and artificial intelligence concludes the review by indicating the 22 potential for the detection and autonomous characterization of the impacts.

Increased screen time during the COVID-19 pandemic and the accelerated incorporation of technology into daily practices have directly contributed to the increased prevalence of eye disease. The human eye is not built for continual technological use and must adjust to exposure to digital screens. Overexposure to technology can result in eye strain and an increased risk of eye diseases such as myopia with complications later in life, including retinal tears, cataracts, and macular degeneration. As vision and ocular diseases become more prevalent, the study of eye diseases, including their causes and treatments, is especially relevant. There is a need to prevent ocular diseases before they become a burden to individuals, their families, and their communities by better understanding the pathophysiology of ocular diseases. Several ocular diseases are thought to be caused by imbalances in reactive oxygen species (ROS) and autophagy. ROS refers to a class of highly reactive oxygen-containing molecules that can undergo damaging reactions with other molecules in the cell. Autophagy is a cellular process of self-eating whereby damaged, harmful, or dead material in cells is broken down to maintain cellular homeostasis. This paper discusses the role of ROS and autophagy in the pathogenesis of computer vision syndrome (CVS), digital eye strain (DES), myopia, cataracts, glaucoma, diabetic retinopathy (DR), age-related macular degeneration (AMD), optic nerve crush injury (OCN), optic nerve gliomas, and retinoblastoma. Lifestyle changes such as limiting screen time, ensuring adequate exposure to evening sunlight, and using blue light protection measures or protective eyewear are important in the prevention of eye disease. Nutrition also contributes significantly to eye health. A balanced diet rich in vitamins and antioxidants may help to prevent ROS and autophagy imbalance-induced eye disease. Medical and surgical treatments become necessary when preventative measures fail. This paper also addresses how government measures to decrease the onset of eye disease, including targeted programs to increase access to fresh vegetables and fruits in food deserts, are a critical macro-level avenue to reduce eye disease prevalence in the US, which according to the National Eye Institute, costs $139 billion yearly.