bluuebunny/crossref_metadata_2025 huggingface dataset:
Heat Transfer and Entropy Generation in a Lithium-Ion Battery Pack Against Battery Spacing and Discharge Rate
Authors: Acharya Swastik , Khan Rustam , Agarwal Praveen Kumar
Published: June 2023

Three-dimensional continuity, momentum, and energy equations have been solved in a battery pack of a unit module with 3 × 3 × 3 and 4 × 4 × 4 Li-ion cells to obtain the flow field and temperature distribution around the batteries. The battery spacing to hydraulic diameter ratio in x, y, and z directions have been varied in a wide range from 0.04458 to 0.08172, 0.00833 to 0.07133, and 0.007496 to 0.08052 for 4 × 4 × 4 cells, and 0.06 to 0.11, 0.0111 to 0.09649, 0.01 to 0.11 for 3 × 3 × 3 to obtain the optimum configuration for maximum heat transfer and minimum entropy generation. Air is pumped through the battery pack as a transport medium for heat transfer with Reynolds number (Re) varying in the laminar range from 400 to 2000. The results are plotted in terms of the average surface Nu over the battery surface and average volumetric temperature of the battery and air. It is found that the temperature of the battery pack remains almost constant against Sx. However, a significant rise in battery temperature is observed when we increase Sy. The scenario becomes different when spacing is varied in the z-direction. An optimum spacing for the minimum temperature of the battery pack is obtained at Sz/Dh = 0.03. The temperature variation trend is almost identical in 3 × 3 × 3 and 4 × 4 × 4 cells; however, the absolute temperature inside the pack is lower in 3 × 3 × 3 cells. In each case, the maximum temperature is seen on the batteries located at the top and bottom corners of the outlet. Among all the cases, the maximum temperature of 355 K has been found in 4 × 4 × 4 cells with a 3.6C discharge rate at Sy/Dh of 0.07133. Different discharging rates (1C, 2C, 3.6C, and 4C) have been considered to generate different amounts of heat inside the battery. However, it is numerically and theoretically proved that Nu and the nondimensional volumetric average temperature inside the pack are independent of the heat generation rate inside the battery pack.
Steady State Heat Conduction in Exchanger Tubes by Using the Meshfree Boundary Integral Equation Method: Conduction Shape Factor and Degenerate Scale
Authors: Lee Jia-Wei , Yang Hung-Wen , Chen Jeng-Tzong
Published: June 2023

Regarding the steady-state heat conduction problem in exchanger tubes, the meshfree boundary integral equation method is employed to determine the conduction shape factor in this paper. Different from the conventional boundary element method, the present method is free of mesh generation. After using the parametric function to represent the boundary contour and adopting the Gaussian quadrature, only collocating points on the boundary is required to obtain the linear algebraic equations. By introducing the local exact solution, the singular integral in the sense of the Cauchy principal value can be novelly determined. In addition, the boundary layer effect due to the nearly singular integral in the boundary integral equation can be dealt with. Two cases of different boundary conditions are considered. One is the isothermal condition on both the inner and outer surfaces. The other is the isothermal condition on the inner surface and the convection condition on the outer surface. Besides, numerical instability is found and the nonuniqueness solution due to the degenerate scale is examined by calculating the conduction shape factor and the temperature on the outer surface.
Transverse momentum broadening of medium-induced cascades in expanding media
Authors: Adhya Souvik Priyam , Kutak Krzysztof , Płaczek Wiesław , Rohrmoser Martin , Tywoniuk Konrad
Published: June 2023

In this work, we explore the features of gluonic cascades in static and Bjorken expanding media by numerically solving the full BDIM evolution equations in longitudinal momentum fraction x and transverse momentum $${{\varvec{k}}}$$

k

using the Monte Carlo event generator . Confirming the scaling of the energy spectra at low-x, discovered in earlier works, we use this insight to compare the amount of broadening in static and expanding media. We compare angular distributions for the in-cone radiation for different medium profiles with the effective scaling laws and conclude that the out-of-cone energy loss proceeds via the radiative break-up of hard fragments, followed by an angular broadening of soft fragments. While the dilution of the medium due to expansion significantly affects the broadening of the leading fragments, we provide evidence that in the low-x regime, which is responsible for most of the gluon multiplicity in the cascade, the angular distributions are very similar when comparing different medium profiles at an equivalent, effective in-medium path length. This is mainly due to the fact that in this regime, the broadening is dominated by multiple splittings. Finally, we discuss the impact of our results on the phenomenological description of the out-of-cone radiation and jet quenching.
A Review on: Ageing Parameters and Monitoring Methods for Lithium-Ion Batteries Used in Electric Vehicle
Authors: Palwe Roopali Bhaskar , Khairnar Dilip , Deshmukh Rutuja , Nagargoje Shivaji G.
Published: June 2023

Self-sustenance of India in oil and coal has consistently turned down, so electric vehicles are the future need of the society and environment. The heart of an electric vehicle is a battery; its degradation and safety are prime important issues to avoid accidents. Therefore, setting such a mechanism that improves the performance of a battery is a requirement of the society. The main objective of this article was to compare various aging parameters of a battery used in the electric vehicle, in terms of their effects, monitoring methods, and benefits for battery aging. It also aimed to illustrate the information out of touch that can be used for future research. This helps to maintain the clean environment by reducing pollution and economical benefit to the society.
Design and Analysis of Low-Power Bulk-Driven Operational Transconductance Amplifier: A Self-Cascode Partial Positive Feedback Approach
Authors: Sharma Kulbhushan , Sharma Aveksha , Pandey Rahul , Madan Jaya
Published: June 2023

Achieving high-gain and low-noise operation of bulk-driven (BD) operational transconductance amplifier (OTA) with low-power consumption is a challenging task owing to inherent low transconductance and high noise in BD MOSFET. In this paper, we report a self-cascode partial positive feedback (SCPPF) approach-based BD OTA and have fairly compared the results with regular single MOS partial positive feedback (PPF) approach-based BD OTA. In comparison to regular BD PPF OTA, the proposed BD SCPPF OTA yields an improved gain of 68.71 dB, gain-bandwidth of 39.4 kHz, power consumption of 630 nW, output impedance of 0.4 MΩ and common mode rejection ratio of 134.4 dB for same input referred noise of 1.11 μV/√ Hz at frequency of 10 Hz and supply voltage of ±0.5 V. The area consumed by BD SCPPF OTA is 0.0523 mm2. The proposed BD SCPPF OTA can be possibly used to improve the performance of biomedical analog front-end sensing and signal processing systems.
Interactive Visualization of Deep Neural Networks for Feature Positioning and Biomedical Monitoring in Physical Education
Authors: Wang Xiang-Ling , Wang Xiang-Ying
Published: June 2023

Visualization is primarily utilized as a training method to enhance athletic movement quality, increase concentration power, and minimize competition stress on the player while building firm confidence. Physical literacy (PL) provides a valuable lens for analyzing physical activity (PA) movement in more significant social and affective learning processes. This paper presents an Interactive Visualization positioning in physical education (IVPPE) to deal with the signal fluctuations and positioning techniques in visualizing Deep Neural Network (DNN). To ensure the success of their game, athletes are always looking for new ways to improve their health and performance. Using sensors to keep tabs on training and recovery has become more popular among athletes. Currently, sports teams are using sensors to track both the players’ internal and external workloads. It illustrates the multilayer localizer (MLL) based on transfer learning to improve the positioning accuracy and physical literacy positioning model (PLPM) as a health determinant. A variety of data augmentation techniques are used to combat signal fluctuations. As a result, the combined effects of motivation-promoting physical activity-based visualization improve the accuracy ratio to 96.7%, prediction ratio to 96.2%, efficiency ratio to 96.8%, and reduce the error rate to 18.7%, stress level (52.8%) compared to other conventional models and have a positive impact on the localizer and positioning, making a difference in physical activity (PA) levels.
Fuzzy Influenced Process to Generate Comparable to Parallel Corpora
Authors: Banik Debajyoty , Ekbal Asif , Satapathy Suresh Chandra
Published: June 2023

Data-driven supervised approaches rely on the parallel corpus. Due to lack of data and resources availability, it has become more difficult to achieve accurate outputs. In addition, the efficiency of the machine translation system depends on the quality of the used corpora. Hindi still lacks good quality parallel corpora and needs more resources for accurate machine translation. Comparable corpora are easily available compared to parallel corpora, but they cannot be used directly in machine translation. In our present research, we propose an algorithm to mine these comparable corpora from the web, and generate the parallel corpora automatically. Machine translation systems, system combination approach, and IR-based technique join their hands together to choose the set of sentence pairs. Then the sentence pairs having the best score are chosen to prepare the final parallel corpora.

The primary modules of this architecture are fuzzy logic-based evaluation metric, information retrieval module, statistical machine translation system, Google neural machine translation system, Microsoft machine translation system, and system combination module for machine translation. For case study, we prepare the Hindi-English parallel corpora of (30825 + 51235) = 82060 sentence pairs. Evaluation results show that the F-Score measurement varies from 95.73 to 96.98 for various data sets. The source code and prepared dataset (comparable and parallel corpus) can be found at https://github.com/debajyoty/Comparable-partallel-Algo2.git.
A Survey of Accelerating Parallel Sparse Linear Algebra
Authors: Xiao Guoqing , Yin Chuanghui , Zhou Tao , Li Xueqi , Chen Yuedan , Li Kenli
Published: June 2023

Sparse linear algebra includes the fundamental and important operations in various large-scale scientific computing and real-world applications. There exists performance bottleneck for sparse linear algebra since it mainly contains the memory-bound computations with low arithmetic intensity. How to improve its performance has increasingly become a focus of research efforts. Using parallel computing techniques to accelerate sparse linear algebra is currently the most popular method, while facing various challenges, e.g., large-scale data brings difficulties in storage, and the sparsity of data leads to irregular memory accesses and parallel load imbalance. Therefore, this article provides a comprehensive overview on acceleration of sparse linear algebra operations using parallel computing platforms, where we focus on four main classifications: sparse matrix-vector multiplication (SpMV), sparse matrix-sparse vector multiplication (SpMSpV), sparse general matrix-matrix multiplication (SpGEMM), and sparse tensor algebra. The takeaways from this article include the following: understanding the challenges of accelerating linear sparse algebra on various hardware platforms; understanding how structured data sparsity can improve storage efficiency; understanding how to optimize parallel load balance; understanding how to improve the efficiency of memory accesses; understanding how do the adaptive frameworks automatically select the optimal algorithms; and understanding recent design trends for acceleration of parallel sparse linear algebra.
Causal Feature Selection in the Presence of Sample Selection Bias
Authors: Yang Shuai , Guo Xianjie , Yu Kui , Huang Xiaoling , Jiang Tingting , He Jin , Gu Lichuan
Published: June 2023

Almost all existing causal feature selection methods are proposed without considering the problem of sample selection bias. However, in practice, as data-gathering process cannot be fully controlled, sample selection bias often occurs, leading to spurious correlations between features and the class variable, which seriously deteriorates the performance of those existing methods. In this article, we study the problem of causal feature selection under sample selection bias and propose a novel Progressive Causal Feature Selection (PCFS) algorithm which has three phases. First, PCFS learns the sample weights to balance the treated group and control group distributions corresponding to each feature for removing spurious correlations. Second, based on the sample weights, PCFS uses a weighted cross-entropy model to estimate the causal effect of each feature and removes some irrelevant features from the confounder set. Third, PCFS progressively repeats the first two phases to remove more irrelevant features and finally obtains a causal feature set. Using synthetic and real-world datasets, the experiments have validated the effectiveness of PCFS, in comparison with several state-of-the-art classical and causal feature selection methods.
Privacy Scoring over OSNs: Shared Data Granularity as a Latent Dimension
Authors: Kilic Yasir , Inan Ali
Published: June 2023

Privacy scoring aims at measuring the privacy violation risk of a user over an online social network (OSN) based on attribute values shared in the user’s OSN profile page and the user’s position in the network. Existing studies on privacy scoring rely on possibly biased or emotional survey data. In this study, we work with real-world data collected from the professional LinkedIn OSN and show that probabilistic scoring models derived from the item response theory fit real-world data better than naive approaches. We also introduce the granularity of the data an OSN user shares on her profile as a latent dimension of the OSN privacy scoring problem. Incorporating data granularity into our model, we build the most comprehensive solution to the OSN privacy scoring problem. Extensive experimental evaluation of various scoring models indicates the effectiveness of the proposed solution.
Approximating Inverse Cumulative Distribution Functions to Produce Approximate Random Variables
Authors: Giles Michael , Sheridan-Methven Oliver
Published: June 2023

For random variables produced through the inverse transform method, approximate random variables are introduced, which are produced using approximations to a distribution’s inverse cumulative distribution function. These approximations are designed to be computationally inexpensive and much cheaper than library functions, which are exact to within machine precision and, thus, highly suitable for use in Monte Carlo simulations. The approximation errors they introduce can then be eliminated through use of the multilevel Monte Carlo method. Two approximations are presented for the Gaussian distribution: a piecewise constant on equally spaced intervals and a piecewise linear using geometrically decaying intervals. The errors of the approximations are bounded and the convergence demonstrated, and the computational savings are measured for C and C++ implementations. Implementations tailored for Intel and Arm hardware are inspected alongside hardware agnostic implementations built using OpenMP. The savings are incorporated into a nested multilevel Monte Carlo framework with the Euler-Maruyama scheme to exploit the speedups without losing accuracy, offering speed ups by a factor of 5–7. These ideas are empirically extended to the Milstein scheme and the non-central χ
2
distribution for the Cox-Ingersoll-Ross process, offering speedups of a factor of 250 or more.
Global Risk Assessment of the Occurrence of Bovine Lumpy Skin Disease: Based on an Ecological Niche Model
Authors: An Qi , Li Yue-peng , Sun Zhuo , Gao Xiang , Wang Hong-bin
Published: June 2023

Lumpy skin disease (LSD) is a highly contagious disease in bovine animals. An outbreak of LSD can cause devastating economic losses to the cattle industry. To investigate the distribution characteristics of historical LSD epidemics, LSD was divided into four phases for directional distribution analysis based on trends in epidemic prevalence. Ecological niche models were developed for LSD as well as for two vectors (Stomoxys calcitrans and Aedes aegypti), and global predictive maps were generated for the probability of LSD occurrence and the potential distribution of the two LSD vectors. The models had good predictive performance (the AUC values were 0.894 for the LSD model, 0.911 for the S. calcitrans model, and 0.950 for the A. aegypti model). The LSD combined vector prediction map was generated by combining the distribution maps of Stomoxys calcitrans and Aedes aegyptiwith fuzzy overlay tool in ArcGIS. The LSD combined vector prediction map was combined with the LSD prediction map to generate the LSD vector transmission risk map. The eastern and northwestern regions of North America, the eastern and northern regions of South America, the central and southern regions of Africa, the southern region of Europe, the northwestern and southeastern regions of Asia, and the eastern region of Australia were predicted to provide suitable environmental conditions for the occurrence of LSD. Cattle density, buffalo density, and bio2 (mean diurnal range) were identified as key variables for the occurrence of LSD. The findings of this study can be useful to policymakers in developing and implementing preventive measures of LSD for the health of cattle and the cattle industry.
Longitudinal Association between Periodontitis and the Risk of Hypertension
Authors: Aremu John B. , Pérez Cynthia M. , Joshipura Kaumudi J.
Published: June 2023

Objectives. Hypertension poses a major public health challenge due to its association with increased risk of heart disease, chronic kidney disease, and death. The objective of this study is to evaluate the longitudinal association between periodontitis and the risk of hypertension. Methods. Using a cohort study design, 540 participants free of diagnosed hypertension/prehypertension in the San Juan Overweight Adults Longitudinal Study and with complete 3-year follow-up data were included. Periodontitis was classified according to the 2012 Centers for Disease Control and Prevention/American Academy of Periodontology definition. Participants were considered to have developed hypertension if they reported physician-diagnosed hypertension over the follow-up period or had average systolic blood pressure (SBP) ≥140 mm Hg or diastolic blood pressure (DBP) ≥90 mm Hg at follow-up. Participants free of diagnosed hypertension or prehypertension and with normal BP at baseline (SBP < 120 mm Hg and DBP < 80 mm Hg) were considered to develop prehypertension if they had SBP between 120 and 139 mm Hg or DBP between 80 and 89 mm Hg at follow-up. An additional (secondary) outcome was defined as the development of prehypertension/hypertension over the follow-up period among participants who had normal BP at baseline. We used Poisson regression, adjusting for age, sex, smoking status, physical activity, alcohol intake, diabetes, waist circumference, and family history of hypertension. Results. One hundred and six (19.6%) participants developed hypertension, and 58 of the 221 with normal BP (26%) developed prehypertension/hypertension. There was no consistent association between periodontitis and the risk of developing hypertension. However, people with severe periodontitis had an increased incidence of prehypertension/hypertension (multivariate incidence rate ratios: 1.47; 95% confidence interval: 1.01, 2.17) than people without periodontitis after adjusting for confounders. Conclusion. There was no association between periodontitis and hypertension in this cohort study. However, severe periodontitis was associated with an increased risk of prehypertension/hypertension.
Study on Muck Pile Shape of Open-Pit Bench Blasting Based on PFC
Authors: Gao Wenle , Zhang Jianwei , Li Chenhao , Cheng Lin , Liu Penghui
Published: June 2023

To study the influence of different resistance lines and rows delay intervals on the shape of the muck pile and the throwing distance of open-pit bench blasting based on the open-pit bench blasting test, two-dimensional particle flow code (PFC2D) is used for numerical simulation. The experimental and simulation data were compared and analyzed, and the error value was acceptable. Meanwhile, different resistance lines and row delay intervals are used to conduct numerical simulation analysis. The results show that the height change of the muck pile is directly proportional to the resistance line, and the rock throwing distance is inversely proportional to the resistance line change. The best resistance line is 1.75 m in the actual working condition, according to the effect of the muck pile. By fitting the relationship between the resistance line and rock throwing distance and blasting muck pile’s height, it is found that the relationship is nonlinear. By simulating different row delays, the optimal row delay time difference in the bench blasting model is determined to be 25 ms under similar working conditions. It provides a guiding significance for the blasting parameter design under similar working conditions.
Research on Static/Dynamic Global Path Planning Based on Improved A

∗

Algorithm for Mobile Robots
Authors: Bao Huifang , Fang Jie , Wang Chaohai , Li Zebin , Zhang Jinsi , Wang Chuansheng
Published: June 2023

In view of the problems of A

∗

algorithm in path planning, such as collision risk, the path is not necessarily optimal, and there are numerous turning nodes. Therefore, this study proposes an improved A

∗

algorithm to improve the quality of the planned path. First, the 8-neighborhood children of the parent node are generated, and the security of the planned path is improved by further investigating the properties of the neighbors of these children one by one to reasonably set virtual obstacles. Second, the heuristic function of A

∗

algorithm is ameliorated to make it closer to the actual cost, so as to enhance the accuracy of the planned path; finally, the planned path is smoothed by using the cubic uniform B-spline curve to eliminate corner sharp points in the path. The simulation results show that the improved A

∗

algorithm can not only ensure the safety and smoothness of the planned path but also obtain the shortest planned path in the static environment with different obstacle rates. In addition, we combine the improved A

∗

algorithm with the dynamic window algorithm to enable mobile robots to realize real-time dynamic obstacle avoidance while ensuring the optimality of global path planning.
Can Baseline Characteristics Predict Successful Outcomes after Individual, Physiotherapist-Led Rehabilitation in Patients with Chronic Musculoskeletal Pain?
Authors: Bondesson Elisabeth , Jöud Anna , Rivano Fischer Marcelo , Trulsson Schouenborg Anna
Published: June 2023

Background. No strong and consistent variables to predict outcome after pain rehabilitation have been reported in patients with chronic musculoskeletal pain. The aim of the present study was to clarify if baseline variables could predict successful outcome after a unique, individualized, physiotherapist-led rehabilitation of nine sessions. Methods. In 274 individuals with severe chronic musculoskeletal pain, the risk ratio (RR) and 95% confidence intervals (CIs) were estimated for potentially predictive baseline variables on successful outcomes of pain management, overall health, and pain rating. Results. Statistically significant results show that patients rating moderate or severe baseline pain were in both cases 14% less likely to improve pain management compared to patients rating mild baseline pain (RR = 0.86; 95% CI 0.77–0.97, RR = 0.86; 95% CI 0.74–1.00). Patients with the shortest pain duration were 1.61 times more likely to improve overall health (RR = 1.61; 95% CI 1.13–2.29) compared to patients reporting the longest pain duration (>5 years). Patients reporting anxiety/depression or severe pain were in both cases 1.48 times more likely to improve overall health compared to better baseline presentations (RR = 1.48; 95% CI 1.16–1.88, RR = 1.48; 95% CI 1.03–2.15). Patients with regional/generalized pain were 36% less likely to rate pain reduction (RR = 0.64; 95% CI 0.41–1.00) compared to patients rating localized baseline pain. Of 17 potentially predictive baseline variables, four reached statistical significance for at least one of the three outcomes; although none of them for all three outcomes. Conclusions. Of 17 potentially predictive baseline variables, mild pain ratings, short pain duration, and localized baseline pain were statistically significantly associated with improvements after individual, physiotherapist-led rehabilitation for patients with chronic musculoskeletal pain. This suggests that this type of rehabilitation probably should be offered early in the pain process. Reporting anxiety/depression or severe pain at the baseline did not hinder the improvements of overall health.
Energy-Efficient Compressed Sensing in Cognitive Radio Network for Telemedicine Services
Authors: Vivekanand Chettiyar Vani , Inbamalar T. M. , Nadar Kannan Pauliah , Kannagi V. , Arthi Devarani P.
Published: June 2023

Wireless body area networks (WBAN) are becoming a promising solution for health care applications. WBAN allows monitoring of patients continuously in their own comfort zone. These devices use the industrial, scientific, and medical band (ISM) for communication. This band is overcrowded due to the increasing number of wireless medical devices and other wireless devices occupying this band. This causes interference, which can be damaging and could result in a change in received power. However, WBAN also needs minimum and reliable energy communication for a longer lifetime and improved quality of service. This work addresses both problems and proposes solutions for the same. A cognitive radio controller is employed as a centralized controller with dynamic spectrum allocation properties to mitigate the interference. The sensing of the spectrum is based on compressed sensing with a nonreconstruction model to save energy. To quantify interference measurement, the interference mitigation factor is introduced. Further, to increase energy efficiency, the K-means algorithm is used to cluster WBANs. However, critical emergency data and normal data are categorized as priority data and normal data, respectively, by the proposed priority scheduling algorithm. The performance of this cognitive radio-based system for telemedicine applications is analyzed through simulations. The simulations are performed using MATLAB 2019.
Gender Disparity in Expression of Sarcopenia in Haemodialysis Recipients: Analysis from the FITNESS Cohort
Authors: Anderson Benjamin M. , Wilson Daisy V. , Qasim Muhammad , Correa Gonzalo , Evison Felicity , Gallier Suzy , Ferro Charles J. , Jackson Thomas A. , Sharif Adnan
Published: June 2023

Background. There has been little exploration of the interplay between sarcopenia and frailty in haemodialysis, particularly regarding gender difference. We aimed to (1) assess whether ultrasound-derived low muscle mass (LMM) and sarcopenia are more common in male or female haemodialysis recipients; (2) assess whether age influences any observed gender difference, and (3) explore the interplay between sarcopenia, frailty, and gender in haemodialysis recipients. Methods. This was an exploratory analysis of a subgroup of adult prevalent (≥3 months) haemodialysis with frailty phenotype (FP) scores. Bilateral anterior thigh thickness (BATT) was obtained according to an established ultrasound protocol. Associations with frailty were explored via both linear and logistic regressions for BATT, LMM, and sarcopenia with a priori covariables, stratified by gender. Results. In total of 223 studies, participants had ultrasound measurements. Males showed greater prevalence of LMM. On adjusted analyses, LMM was associated with lower hand grip strength in males (β = −4.17; 95% C.I. −7.57 to −0.77;

P
=
0.02

), but not females (β = −1.88; 95% C.I. −5.41 to 1.64;

P
=
0.29

). LMM was also associated with slower walking speed in both males (β = −0.115; 95% C.I. −0.258 to −0.013;

P
=
0.03

) and females (β = −0.152; 95% C.I. −0.300 to −0.005;

P
=
0.04

). Sarcopenia was associated with greater odds of frailty on adjusted models in males (OR = 9.86; 95% C.I. 1.8 to 54.0;

P
=
0.01

), but not females (OR = 5.16; 95% C.I. 0.22 to 124;

P
=
0.31

). Conclusions. The clinical expression and significance of sarcopenia differ substantially between males and females on haemodialysis. Further work is required to elucidate underlying mechanisms and guide tailored treatment.
Nonlocal Hybrid Integro-Differential Equations Involving Atangana–Baleanu Fractional Operators
Authors: Alshammari Saleh , Alshammari Mohammad , Abdo Mohammed S.
Published: June 2023

In this study, we develop a theory for the nonlocal hybrid boundary value problem for the fractional integro-differential equations featuring Atangana–Baleanu derivatives. The corresponding hybrid fractional integral equation is presented. Then, we establish the existence results using Dhage’s hybrid fixed point theorem for a sum of three operators. We also offer additional exceptional cases and similar outcomes. In order to demonstrate and verify the results, we provide an example as an application.
Acquired Fanconi Syndrome from Tenofovir Treatment in a Patient with Hepatitis B
Authors: Jiang Shirley X. , Duncan John , Ko Hin Hin
Published: June 2023

Fanconi syndrome is a rare disease of generalized proximal tubule dysfunction which can be acquired secondary to certain medications, including tenofovir, a commonly used hepatitis B treatment. Signs and symptoms of ensuing renal wasting can be severe but vague, leading to potentially avoidable invasive investigations and delays in diagnosis. We present a case of a 62-year-old female with chronic hepatitis B on tenofovir treatment who was found to have subacute weakness, anorexia, and weight loss. She underwent extensive investigations including computed tomography (CT) imaging, bronchoscopy, upper and lower endoscopy, and psychiatric evaluation. Finally, persistent electrolyte derangements led to urine studies, which demonstrated acquired Fanconi syndrome secondary to tenofovir. After discontinuing tenofovir disoproxil fumarate and starting tenofovir alafenamide, her symptoms resolved and her renal function recovered. This case illustrates the importance of maintaining clinical suspicion for tenofovir-induced Fanconi syndrome, given the common use of tenofovir as first-line hepatitis B treatment and the availability of less nephrotoxic alternatives.
Poor Sleep Quality and Associated Factors among People Living with HIV/AIDS Attending ART Clinic at Tirunesh Beijing Hospital, Addis Ababa, Ethiopia
Authors: Tadesse Atsede , Badasso Kufa , Edmealem Afework
Published: June 2023

Background. Sleep is a universal need of all higher life forms, including humans. However, sleep problems are one of the most common problems raised by patients living with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). Poor sleep quality is one of the hidden and unrecognized factors contributing to poor medication adherence and functional inactivity among people living with human immunodeficiency virus/acquired immunodeficiency syndrome. Methods. A hospital-based cross-sectional study was conducted from April 15, 2022, to May 30, 2022, at an antiretroviral therapy (ART) clinic of Tirunesh Beijing Hospital. A systematic sampling technique was used to select study participants. A total of 413 people who are living with human immunodeficiency virus/acquired immunodeficiency syndrome were enrolled in the study. Data were collected through interviews when study participants finished their visit. Variables whose

P

value was less than 0.2 in bivariable logistic regression were entered into multivariable binary logistic regression to identify factors associated with poor sleep quality. Result. The level of poor sleep quality among people living with HIV/AIDS was 73.7%. People living with HIV/AIDS who had poor sleep hygiene were 2.5 times more likely to have poor sleep quality compared with those patients who had good sleep hygiene. Moreover, study participants who had anxiety were three times more likely to have poor sleep quality compared with those who did not have anxiety (AOR: 3.09; 95% CI = 1.61–5.89). Study participants who had chronic diseases in addition to HIV/AIDS were 3 times more likely to have poor sleep quality compared with those who do not have it (AOR: 2.99; 95% CI = 1.15–7.79). Additionally, people living with HIV/AIDS who were stigmatized due to their disease were 2.5 times more likely to have poor sleep quality compared with their counterparts (AOR = 2.49; 95% CI = 1.43–4.21). Conclusion. In this study, the magnitude of poor sleep quality among people living with HIV/AIDS was high. Being a farmer, being a merchant, having chronic diseases, having anxiety, having a CD4 count of 200–499 cells/mm3, being stigmatized, and having poor sleep hygiene were factors that had an association with poor sleep quality. Healthcare providers should screen people living with HIV/AIDS for anxiety and encourage them to practice good sleep hygiene during follow-up.
The Impact of Angle Lambda on Patient Satisfaction after Optiflex Trio Trifocal Intraocular Lens Implantation
Authors: Kaya Ünsal Sultan , Sunay Ertan
Published: June 2023

Purpose. To evaluate the vision‐related quality of life (QOL), visual acuities, and refractive outcomes of patients with different angle lambda (λ) after a trifocal intraocular lens (IOL) implantation at Veni Vidi Eye Hospital, İstanbul, Turkey. Methods. This retrospective, nonrandomized, and noncomparative case series included patients who had phacoemulsification bilaterally with the implantation of a trifocal IOL (Optiflex Trio) and responded to a vision‐related QOL questionnaire measuring patient satisfaction. The patients were divided into two groups according to the angle λ with a cutoff value of 0.5 mm. Evaluations were conducted to examine the monocular visual acuities, spherical equivalents, corneal astigmatism measured 3 months after surgery, and outcomes of the QOL questionnaire in the two groups. Results. The study examined 130 eyes from 65 patients aged from 41 to 78 years old. There were no statistically significant differences between the two groups at 3 months after surgery in terms of uncorrected distance visual acuity (UDVA), monocular uncorrected intermediate visual acuity (UIVA), monocular uncorrected near visual acuity (UNVA), spherical equivalent, and corneal astigmatism (P > 0.05). Patients with a greater angle λ had significantly more difficulty going out to see movies, plays, or sporting events (P = 0.02), driving at night (P = 0.002), and driving in difficult conditions (P < 0.001) than patients with a lower angle λ. Conclusions. The Optiflex Trio showed good results in terms of visual acuity at all distances, positive refractive outcomes, and high patient satisfaction in daily life according to the QOL questionnaire. An angle λ greater than 0.5 mm may potentially cause dysphotopsia symptoms, especially during nighttime activities.
Leveraging Community Support Services to Support an Integrated Health and Social System Response to COVID-19: A Mixed Methods Study
Authors: Northwood Melissa , Kalles Elizabeth , Harrington Cathy , Hogeveen Sophie , Heckman George
Published: June 2023

The COVID-19 pandemic restricted access to health and social care for older adults. In response, a standardized, self-report instrument, the interRAI COVID-19 Vulnerability Screener (CVS), was developed. In collaboration with a community support service organization, this project aimed to evaluate a surveillance process to identify those at risk and triage them to health- or social-care services. A convergent, mixed methods design was used. Virtual focus groups were conducted with partner staff. The clinical, social, and functional characteristics of screened clients were analyzed descriptively. The mixed methods analysis generated implementation considerations. Participants successfully utilized the CVS to identify and support vulnerable clients who may have otherwise been overlooked. Most screened clients were not experiencing COVID-19 symptoms, yet had elevated mortality risk should they become infected, and were negatively impacted by social isolation. Findings support the use of the CVS by community support services during the pandemic or other disasters to identify those at risk due to frailty and social or economic vulnerability. Implementation requirements include a knowledgeable workforce, active facilitation, and incorporation of the CVS into existing workflows. Health- and social-care integration would be enhanced by the development of updated privacy policies and shared digital infrastructure.
Blind nonlinear unmixing using nonnegative matrix factorization based bi-objective autoencoder
Authors: Bhakthan Sreejam Muraleedhara , Loganathan Agilandeeswari , Bansal Aashish
Published: June 2023

Hyperspectral image processing is one of the trending techniques used in many fields such as remote sensing, medical, agriculture, food processing, and military. The unique discrimination of hyperspectral images can be used for object identification, classification, and prediction. One of the main challenges of these tasks is the mixed pixel problem. Hyperspectral unmixing is the process of identifying the endmembers and their abundance in pixels. In linear unmixing, the mixture of the endmembers is assumed to be linear homogenous patches. Even though these models are simple and faster in performance, most of the real-world images are not linear. A modified nonlinear mixture-based sparsity regularized bi-objective autoencoder model based on nonnegative matrix factorization (NMF-BOA) is proposed in this article. The performance analysis shows that our model gives competitive results compared to the state-of-the-art models.
Towards a new healthy food decision-making system
Authors: Outfarouin Ahmad , Laaffat Nourane
Published: June 2023

Latterly, food recommendation systems have received high attention due to their importance to healthy living. On the recommendation domain, most studies focus on recommendations that suggest healthy products for each user based on their profiles. These types of recommender systems offer additional functionality to persuade users to change their buying behavior profitably. However, these systems must highlight the health preferences of the users and their health problems must be adequately taken into account. In this work, healthy food products recommender systems (RS) are our interest study and more specifically using content-based filtering. We represented this content by the food product composition. Our goal was to provide a healthy recommendation to consumers or citizens around the world, especially at this time when disease abounds. Thus, we developed our new healthy recommendation system (HRS). In this paper, we present a new recommendation process for individuals in the area of healthy eating. Furthermore, we analyze the existing state of the art in recommender system techniques and implement an algorithm that responds to this new process with very satisfactory results from the beginning, to conclude we discuss the research challenges related to the development of this kind of HRS.
A literature review for measuring maintainability of code clone
Authors: Khaleel Shahbaa I. , Al-Khatouni Ghassan Khaleel
Published: June 2023

Software organizations face constant pressure due to stakeholder requirements and the increasing complexity of software systems. This complexity, combined with defects in code quality and failures, can pose risks to software systems. To ensure code is understood before maintenance, developers must spend over 60% of their time modifying and improving code quality, which is costly. This study examines the impact of code refactoring activities on software maintainability and quality by reviewing relevant research and explaining key terms. The research finds that refactoring activities can enhance specific quality characteristics, including maintainability, understandability, and testability. The study also identifies important factors that should be considered when developing refactoring tools. Refactoring enables code improvement without altering program behavior and can be applied multiple times to source code.
Network intrusion detection and classification using machine learning predictions fusion
Authors: Somashekar Harshitha , Boraiah Ramesh
Published: June 2023

The primary objective of an intrusion detection system (IDS) is to monitor the network performance and to look into any indications of malformation over the network. While providing high-security network IDS played a vital role for the past couple of years. IDS will fail to identify all types of attacks, when it comes to anomaly detection, it is often connected with a high false alarm rate with accuracy and the detection rate is very average. Recently, IDS utilize machine learning methods, because of the way that machine learning algorithms demonstrated to have the capacity of learning and adjusting as well as permitting a proper reaction for real-time data. This work proposes a prediction-level fusion model for intrusion detection and classification using machine learning techniques. This work also proposes retraining of model for unknown attacks to increase the effectiveness of classification in IDS. The experiments are carried out on the network security layer knowledge discovery in database (NSL-KDD) dataset using the Konstanz information miner (KNIME) analytics platform. The experimental results showed a classification accuracy of 90.03% for a simple model to 96.31% for fusion and re-trained models. This result inspires the researchers to use machine learning techniques with a fusion model to build IDS.
Efficient automated car parking system based modified internet of spatial things in smart cities
Authors: Alsaedi Noor , Jalal Ali Sadeq Abdulhadi
Published: June 2023

The technological advances of smart cities have been progressively increasing to improve the quality of life to humans, especially in urban mobility. Parking appears to be a major issue, with residents needing to find a suitable parking space among many parking areas, resulting in time and fuel waste as well as environmental pollution. We propose in this paper a new automated system model that integrates reinforcement learning (RL), Q-learning, and image processing algorithms based on modified Internet of Spatial Things (IoST) architecture to optimize automated parking in smart cities. For demonstrating the efficiency of the proposed model, iFogSim simulation is used to reduce network usage and latency. Moreover, it deploys heterogeneous devices in multi layers and different scenarios. The experimental results show that the suggested system for automated car parking in fog-based placement-IoST network is feasible and effective. it minimizes latency and the total network usage compared to the cloud-based placement of the implemented system.
Bluetooth low energy for internet of things: review, challenges, and open issues
Authors: Al-Shareeda Mahmood A. , Saare Murtaja Ali , Manickam Selvakumar , Karuppayah Shankar
Published: June 2023

As a result of its ultra-low power consumption, simple development, sufficient network coverage, and rapid data transfer speed, Bluetooth low energy (BLE) has emerged as the standard communication standard for internet of things (IoT) nodes. Therefore, in this review paper introduces the concept of Bluetooth low energy for the internet of things (BLE-IoT) in terms of Bluetooth classic, Bluetooth version, applications for BLE-IoT, and new features of BLE-IoT. We then provide a taxonomy of literature reviews based on the parameter adjustment approach (e.g., advertiser side schemes, scanner side schemes, hybrid schemes) and collision avoidance approach (e.g., advertiser side schemes and scanner side schemes). Finally, we discuss research challenges and future opportunities for BLE-IoT.
Optimizing multimedia communication in internet of thing network for improving quality of service
Authors: Vijaykumar Sathya , Thyagaraj Shiva Prakash
Published: June 2023

The internet of things (IoT) has revolutionized the way we interact with technology, with the proliferation of interconnected devices leading to an increase in the volume of data transmitted over the network. One of the key applications of IoT is in multimedia communication, where real-time audio and video data is transmitted over the network. However, the diverse nature of applications and the sheer volume of data in IoT networks can lead to network congestion, latency, and variable quality of service (QoS) at the internet side, resulting in a degradation of the overall QoS for multimedia traffic. In this paper, we propose a cross-layer multimedia optimization solution for multi-point to point IoT networks that incorporates service differentiation and bandwidth reservation techniques to improve the QoS of multimedia traffic. We evaluate the performance of our proposed solution using simulations and compare it with existing solutions. Our results show that our proposed solution can significantly improve the QoS of multimedia traffic in IoT networks, even during periods of high network congestion or variable QoS at the internet side.
Optimal placement of the phasor measurement units using differential evolution algorithm
Authors: Zadehbbagheri Mahmoud , Abbasi Alireza , Sutikno Tole
Published: June 2023

The increasing consumption of the electric energy aimed at develop the transmission networks and the demand for higher reliability from the network; in this regard, wide-area measurement systems using phasor measurement units (PMUs) have revolved the trend of power network management. In this paper, the optimal allocation of PMUs in order to reach the perfect observability of the network; based on a differential evolution algorithm, is proposed and it is shown that, the deployment of constraints related to the zero-injection busses (ZIB) aimed to decrease the number of PMUs and their corresponding cost. By comparing the proposed method to the other methods, its simplicity and good performance are approved.
Evaluation of additional electricity losses in electric networks using a meter
Authors: Kakhramon Rakhimovich Allaev , Saleem Adeel , Ilkhombek Khosiljonovich Kholiddinov , Iqbal Atif , Abdinabi ugli Eraliev Khojiakbar
Published: June 2023

In this article, additional electricity losses are calculated using the voltage imbalance factor. There is also a method for predicting extra losses in the case of longitudinal and transverse asymmetry, as well as information on how to measure power quality indicators. It is suggested that home appliances be used to monitor a separate power system's power quality indicators. The findings of investigations on the condition of asymmetry conducted in operational low voltage electrical networks are presented, along with an illustration of how to calculate additional electricity losses in low-voltage networks. In this article for this purpose, the author developed a Malika device, which is fully capable to measure, store, analyze, and draw conclusions from the results of all electrical quality indicators.