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Cost efficiency of commercial banks in Ethiopia: Does financial technology matter?

This study aims to assess the effects of financial technology on the cost efficiency of commercial banks in Ethiopia. Secondary panel data were collected from the audited annual reports of seventeen commercial banks for twelve fiscal years between 2011 and 2022. The cost efficiency of banks was investigated via a stochastic frontier approach. The findings indicate that commercial banks operating in Ethiopia are efficient in cost management, with an 83% efficiency rate on average. In addition to financial technology, the effects of bank size, interest spread rate, management quality, foreign exchange rate, capitalization and bank ownership are significant for cost efficiency. Notably, financial technology plays a remarkable role in the cost efficiency of commercial banks in Ethiopia. The study results show the presence of a positive association between financial innovation platforms and the cost efficiency of commercial banks. Banking services delivered via card banking, mobile banking, and internet banking improve the cost efficiency of commercial banks in Ethiopia. As a strategic resource, financial innovation in banking operations enhances the cost efficiency of banks by reducing noneconomic costs and the time needed to deliver banking services. To improve their cost efficiency, commercial banks in Ethiopia are encouraged to use financial innovation platforms to deliver financial services and update the current cost management strategy intended to reduce operating costs incurred to generate and collect loans and advances and interest expenses paid to maintain deposits and other interest-bearing liabilities.

Forecasting the use of chiropractic services within the Veterans Health Administration

Objective To model future use of chiropractic services and predict clinical resource needs within the Veterans Health Administration (VA) over the next 5 years. Methods A serial cross-sectional analysis of chiropractic use data from VA’s Corporate Data Warehouse for fiscal years (FY) 2017 through 2022 (10/1/2016-9/30/2022). We calculated the proportion of VA chiropractic users–via care provided on-station and/or purchased from Community Care Network (CCN) providers–compared to overall VA healthcare users for each FY. We calculated the historical year-over-year compound annual growth rate (CAGR), which was used to predict use in FY2023 through 2027 (10/1/2022-9/30/2027). Results VA’s chiropractic use rate increased from 1.4% in FY2017 to 3.5% in FY2022, at which point 2.0% of VA users received only CCN chiropractic care, 1.3% only on-station, and 0.2% both. During the 6-year observation period, the CAGRs were overall 17.9%, CCN only 23.8%, on-station only 12.4%, and both 27.7%. Using those rates to extrapolate, by the end of FY2027 overall use will be 8.9%, with 5.9% only CCN, 2.3% only on-station, and 0.6% both. Conclusion Overall use of VA chiropractic services is projected to more than double from FY 2022 to FY2027. These findings underscore the need for proactive resource planning to address the expected increased use of both CCN and on-station care.

Capacity-building interventions for health extension workers in Ethiopia: A scoping review

Introduction Capacity-building interventions for health extension workers (HEWs) are key to providing quality health services to the community. Since Ethiopia’s Health Extension Program was established, several types of capacity-building interventions have been developed to build HEW competencies. However, no comprehensive study has mapped the types of capacity-building interventions being used or the competencies targeted. Objective To (1) identify and characterize evidence on capacity-building interventions for Ethiopian HEWs, including the competencies measured; (2) clarify evidence gaps in this area; and (3) explore how successful the interventions have been to inform the design of health extension programs and further research. Methods We used keywords (health extension workers, capacity building, competencies) and related terminologies to search PubMed, Scopus, and Embase for published studies on capacity-building interventions for Ethiopian HEWs, and Google Scholar for unpublished studies and reports. Our search was limited to studies and reports published in English from 2003 to present. We used the JBI scoping review methodology to conduct this scoping review in a stepwise approach and a categorization approach to synthesize the evidence. Results Our search strategy identified 20 articles, all published except for one program report. The most common capacity-building intervention designed for HEWs was training, followed by supportive supervision, performance review and clinical mentoring meetings, and equipment supply; the most salient competency domains investigated were knowledge and skills. The interventions significantly improved immediate outcomes (knowledge, skills, attitude change among HEWs) and intermediate outcomes, such as increased service utilization and health-seeking behavior among community members. Only one study assessed whether capacity-building interventions improved inter- and intra-personal domains of capacity/competency. Conclusions Capacity-building interventions for Ethiopian HEWs were found to be effective, but they mainly focused on improving technical competencies, such as knowledge and skills. Little attention has been paid to other competency domains, including motivation, leadership, and communication. Thus, future research could focus on a comprehensive set of capacity-building initiatives that addresses motivation, job satisfaction, communication, commitment, and resource allocation.

Risky behavior in virtual reality: The roles of personality, environment, and physiology

Virtual reality (VR) provides a unique opportunity to simulate various environments, enabling the observation of human behavior in a manner that closely resembles real-world scenarios. This study aimed to explore the effects of anticipating reward or punishment, personality traits, and physiological arousal on risky decision-making within a VR context. A custom VR game was developed to simulate real-life experiences. The sample comprised 52 students (63.46% female) from the University of Novi Sad, Serbia. The study assessed four parameters within the VR environment: elapsed game time, number of steps taken, average score, and decision-making time. Three physiological signals, heart rate, skin conductance, and respiratory rate, were recorded. Results indicated that personality traits, specifically Fight (β = -0.33, p = 0.024) and Freeze (β = 0.431, p = 0.009), were significantly related to behavior in the VR environment (R = 0.572, R2_adj = 0.227, RMSE = 23.12, F(6, 40) = 3.25, p = 0.011). However, these effects were not significant after negative feedback. Emotional arousal, measured by respiratory rate amplitude (β = 0.276, p = 0.045), showed a more pronounced role after feedback (β = 0.337, p = 0.028). These findings indicate that personality traits primarily influence behavior in a VR environment prior to the actual threat, whereas environmental characteristics become more important afterwards. The results offer valuable insights for experimental and personality psychologists by revealing how risk-taking is influenced by situational, emotional, and personality factors. Additionally, they provide guidance for VR designers in creating more ecologically valid environments, highlighting VR’s potential as a tool for psychological research, while also underscoring the critical importance of selecting objective VR measures to accurately capture the complexities of human behavior in immersive environments.

Increased resting heart rate indicates high-workload hearts with augmented aortic hydraulic power in hypertensive pigs

Clarifying the inceptive pathophysiology of hypertensive heart disease helps to impede the disease progression. Through coarctation of the infrarenal abdominal aorta (AA), we induced hypertension in minipigs and evaluated physiological reactions and morpho-functional changes of the heart. Moderate aortic coarctation was achieved with approximately 30 mmHg systolic pressure gradient in minipigs. Hypertension was assessed by pressure increment of the carotid artery. Perioperative heart rate (HR) was recorded. We measured aortic flow rate and pressure proximal to coarctation to calculate hydraulic power, an indicator for cardiac workload, and resistance. The hearts harvested at sacrifice were examined for myocardial hypertrophy, fibrosis, and dysfunction. The parameters capable of indicating high-workload heart and their prediction effectiveness were determined by cluster and receiver operating characteristic (ROC) analyses. Prolonged AA coarctation for 8–12 weeks induced hypertension in a portion of minipigs. The cluster of minipigs exhibiting increased aortic hydraulic power displayed hypertension and mean HR elevation without changing arterial resistance. Notably, the blood pressure and HR were measured under full anesthesia, equivalent to resting status. Myocardial hypertrophy was not detected at the tissue, cellular or molecular levels. Expression of biomarkers for cellular stress and heart failure didn’t increase except for heat shock protein 40. ROC analysis showed that aortic hydraulic power, resting HR, and mean blood pressure, but not arterial resistance, can serve as the indicators for high-workload hearts. These results suggested that resting HR increase in hypertensive pigs indicates hearts with high workload. Heart failure may develop without appropriate treatment.

Hippocampal subfield volume alterations and associations with severity measures in long COVID and ME/CFS: A 7T MRI study

Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) patients share similar symptoms including post-exertional malaise, neurocognitive impairment, and memory loss. The neurocognitive impairment in both conditions might be linked to alterations in the hippocampal subfields. Therefore, this study compared alterations in hippocampal subfields of 17 long COVID, 29 ME/CFS patients, and 15 healthy controls (HC). Structural MRI data was acquired with sub-millimeter isotropic resolution on a 7 Telsa MRI scanner and hippocampal subfield volumes were then estimated for each participant using FreeSurfer software. Our study found significantly larger volumes in the left hippocampal subfields of both long COVID and ME/CFS patients compared to HC. These included the left subiculum head (long COVID; p = 0.01, ME/CFS; p = 0.002,), presubiculum head (long COVID; p = 0.004, ME/CFS; p = 0.005), molecular layer hippocampus head (long COVID; p = 0.014, ME/CFS; p = 0.011), and whole hippocampal head (long COVID; p = 0.01, ME/CFS; p = 0.01). Notably, hippocampal subfield volumes were similar between long COVID and ME/CFS patients. Additionally, we found significant associations between hippocampal subfield volumes and severity measures of ‘Pain’, ‘Duration of illness’, ‘Severity of fatigue’, ‘Impaired concentration’, ‘Unrefreshing sleep’, and ‘Physical function’ in both conditions. These findings suggest that hippocampal alterations may contribute to the neurocognitive impairment experienced by long COVID and ME/CFS patients. Furthermore, our study highlights similarities between these two conditions.

Development and effectiveness analysis of a safety management model for SMEs integrating lean management innovation with SQCDP framework

This study organically integrates the safety, quality, cost, delivery, and people (SQCDP) management mode and lean management to create the SQCDP + lean safety management (SLSM) mode, which addresses certain problems faced by China’s small- and medium-sized enterprises (SMEs), such as imperfect safety management systems, poor regulatory implementation, challenging problem correction, and perfunctory management. It then explains the benefits proposed mode for SMEs and the establishment of a novel mode that aligns with the current safety production and operation management of SMEs. The application of the SLSM mode to a private machinery manufacturing company in Wenzhou resulted in the effective shouldering of safety responsibilities by the company, a year-on-year decrease in accident rates, and a significant increase in production efficiency, thereby providing corporate managers with guidance and suggestions for making improvements.

Equalization of basic public services enabled by digitization: A study of mechanism and heterogeneity

Digitalization has penetrated into every aspect of life. However, research on the mechanisms through which digitalization affects the equalization of basic public services, as well as the heterogeneity of its impact on different fields of these services, is still insufficient. Based on the panel data of 30 provincial-level administrative regions in China from 2013 to 2023, this paper studies the mechanism and heterogeneity of the impact of digital development on the equalization of basic public services. The research finds that the improvement of the digital development level can significantly promote the equalization process of basic public services, and this finding remains robust after a series of endogeneity and robustness tests. The discussions on regional heterogeneity and spatial complexity show that digitalization makes a greater contribution to the equalization of basic public services in the central and western regions and the northeast than in the east. However, achieving equalization of basic public services across regions through digitalization is challenging. The development of digitalization and the equalization of basic public services are limited by territorial cohesion in geographical space. Underdeveloped regions have poor access to digitalization for achieving equalization of basic public services. This leads to a ‘digital divide’ between developed and underdeveloped regions. It also results in a ‘low-lying area’ phenomenon in basic public services. Additionally, the promoting effect of digitalization on the equalization of different areas of basic public services varies significantly. The effect is strongest for basic living services. It is moderate for environmental protection services and education services. The effect on medical services is not significant.

Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement

Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs. To help bridge this gap and enable hundreds of stakeholders to collect more affordable soil data by leveraging a centralized open resource, the Soil Spectroscopy for Global Good initiative has created the Open Soil Spectral Library (OSSL). In this paper, we describe the procedures for collecting and harmonizing several SSLs that are incorporated into the OSSL, followed by exploratory analysis and predictive modeling. The results of 10-fold cross-validation with refitting show that, in general, mid-infrared (MIR)-based models are significantly more accurate than visible and near-infrared (VisNIR) or near-infrared (NIR) models. From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). Although many soil properties are well predicted, total sulfur, extractable sodium, and electrical conductivity performed poorly in all spectral regions, with some other extractable nutrients and physical soil properties also performing poorly in one or two spectral regions (VisNIR or NIR). Hence, the use of predictive models based solely on spectral variations has limitations. This study also presents and discusses several other open resources that were developed from the OSSL, aspects of opening data, current limitations, and future development. With this genuinely open science project, we hope that OSSL becomes a driver of the soil spectroscopy community to accelerate the pace of scientific discovery and innovation.

Estimating whole-body centre of mass sway during quiet standing with inertial measurement units

Our ability to balance upright provides a stable platform to perform daily activities. Balance deficits associated with various clinical conditions may affect activities of daily living, highlighting the importance of quantifying standing balance in ecological environments. Although typically performed in laboratory settings, the growing availability of low-cost inertial measurement units (IMUs) allows the assessment of balance in the real world. However, it is unclear how many IMUs are required to adequately estimate linear displacements of the centre of mass (CoM) at stance widths associated with daily activities. While wearing IMUs on their head, sternum, back, right thigh, right shank, and left shank, 16 participants stood quietly on a force platform in narrow, hip-width, and shoulder-width stances, each for three two-minute trials. Using a multi-segment biomechanical model, we estimated CoM displacements from all possible combinations of the IMUs. We then calculated the correlation between the IMU- and force platform- CoM estimates to determine the minimal number of IMUs needed to estimate CoM sway. Four IMUs were necessary to accurately estimate anteroposterior (AP) and mediolateral (ML) CoM displacements across stance widths. Using IMUs on the back, right thigh, and both shanks, we found strong correlations between the IMU CoM estimation and the force platform CoM estimation in narrow stance (AP: r = 0.92±0.04, RMSE = 2.39±2.08 mm; ML: r = 0.97±0.02, RMSE = 1.16±0.77 mm), hip-width stance (AP: r = 0.93±0.04, RMSE = 2.00±1.18 mm; ML: r = 0.92±0.06, RMSE = 0.92±0.70 mm), and shoulder-width stance (AP: r = 0.93±0.03, RMSE = 1.95±1.66 mm; ML: r = 0.86±0.13, RMSE = 1.39±1.46 mm). These results indicate that IMUs can be used to estimate CoM displacements during quiet standing and that four IMUs are necessary to do so. Using an algorithm based on a simple biomechanical model, researchers and clinicians can estimate whole-body CoM displacements accurately during unperturbed quiet standing. This approach can improve the ecological validity of standing balance research and opens the possibility for assessing/monitoring patients with standing balance deficits.

Food insecurity and early childhood development among children 24–59 months in Nigeria: A multilevel mixed effects modelling of the social determinants of health inequities

Food insecurity (FI) has been identified as a determinant of child development, yet evidence quantifying this association using the newly developed Early Childhood Development Index 2030 (ECDI2030) remains limited. Herein, we provide national estimates of early childhood development (ECD) risks using the ECDI2030 and examined to what extent FI was associated with ECD among children aged 24–59 months in Nigeria. This population based cross-sectional analyses used data from the UNICEF-supported 2021 Multiple Indicator Cluster Survey in Nigeria. The analytic sample comprised children aged 24–59 months (weighted N = 12,112). We measured early childhood development for each child using the ECDI2030, measured across three domains: learning, psychosocial well-being and health. Food insecurity was assessed using the Food Insecurity Experience Scale (FIES), categorized as none/mild, moderate and severe. We fitted mixed-effects multilevel logistic regression models, with random intercepts, to estimate the odds of association between FI status and ECD. A total of 11,494 children aged 24–59 months (mean ± SD age, 43.4 ± 9.9 months), including 5,797 boys (50.2%) and 5,697 girls (49.8%), were included in the study. Approximately 46.4% of children were developmentally off track and about 76% of children lived in food-insecure households. The intercept-only model indicated significant variation in ECD prevalence across communities (τ00 = 0.94, intraclass correlation = 0.22, p < 0.0001), suggesting nonignorable variability in ECD across communities. Adjusting for confounders, we observed no significant association between FI and ECD. However, increasing child’s age and disability status appeared as significant risk factors for higher odds of children being developmentally off track. These findings highlight that while FI alone may not explain ECD, a combination of individual and contextual factors plays a crucial role. Future interventions addressing ECD in Nigeria should consider these multidimensional influences to promote optimal child development.

3D printing of different fibres towards HA/PCL scaffolding induces macrophage polarization and promotes osteogenic differentiation of BMSCs

With the rise of bone tissue engineering (BET), 3D-printed HA/PCL scaffolds for bone defect repair have been extensively studied. However, little research has been conducted on the differences in osteogenic induction and regulation of macrophage (MPs) polarisation properties of HA/PCL scaffolds with different fibre orientations. Here, we applied 3D printing technology to prepare three sets of HA/PCL scaffolds with different fibre orientations (0–90, 0-90-135, and 0-90-45) to study the differences in physicochemical properties and to investigate the response effects of MPs and bone marrow mesenchymal stem cells (BMSCs) on scaffolds with different fibre orientations. The results showed that multi-angle staggered fibres affected the overall porosity and compressive strength of the scaffolds. Compared with the other two groups, the 0-90-45 scaffold induced osteogenic differentiation of BMSCs more significantly, while promoting the polarisation of MPs towards the M2 phenotype to form an osteogenic-friendly immune microenvironment. Unexpectedly, the 0-90-45 scaffold significantly upregulated the expression of angiogenic genes (PDGF, VEGF). Therefore, we conclude that the multi-angle interlaced fibres better mimic the physiological structure of cancellous bone, and that the excellent biomimetic properties reflect the best in vitro osteogenic, immunomodulatory and angiogenic effects. In conclusion, this study is a step forward in the exploration of BET scaffolds and provides a very promising bone filling material.

Inpatient service utilization amongst infants diagnosed with Respiratory Syncytial Virus infection (RSV) in the United States

Introduction Respiratory syncytial virus (RSV) is the leading cause of hospitalization among US infants. Characterizing service utilization during infant RSV hospitalizations may provide important information for prioritizing resources and interventions. Objective The objective of this study was to describe the procedures and services received by infants hospitalized during their first RSV episode in their first RSV season, in addition to what proportion of infants died during this hospitalization. Methods In this retrospective observational study, we analyzed three different administrative claims datasets to examine healthcare service utilization during RSV hospitalizations among infants. The study population included infants born between July 2016 and February 2020 who experienced an RSV episode during their first RSV season and had an associated inpatient hospitalization. We stratified infants into three comorbidity groups: healthy term, palivizumab-eligible, and other comorbidities. Outcomes included extracorporeal membrane oxygenation, supplemental oxygen use (in-hospital and post-discharge), mechanical ventilation (invasive and non-invasive), chest imaging, infant mortality, length of inpatient stay, intensive care unit (ICU) admission, and number of days in the ICU. Results Chest imaging was the most frequently administered procedure during RSV-associated hospitalizations, with approximately 34–38% of infants receiving it. Around one-quarter of infants were admitted to the ICU during their first RSV hospitalization. Median lengths of stay in the hospital were 3–4 days, extending to 4–6 days in the presence of ICU admission. Palivizumab-eligible infants had higher utilization of healthcare services and spent more time in the hospital or ICU compared to healthy infants or those with other comorbidities. Conclusions This study provides insights into the utilization of healthcare services during RSV hospitalizations among infants. Understanding service utilization patterns can aid in improved management and resource allocation for infants in the United States, ultimately contributing to better outcomes and reduced healthcare costs overall. However, likely under-ascertainment of ventilation and oxygen-related services in insurance claims remains an impediment to studying these outcomes.

Spectral study of COVID-19 pandemic in Japan: The dependence of spectral gradient on the population size of the community

We have carried out spectral analysis of coronavirus disease 2019 (COVID-19) notifications in all 47 prefectures in Japan. The results confirm that the power spectral densities (PSDs) of the data from each prefecture show exponential characteristics, which are universally observed in the PSDs of time series generated by nonlinear dynamical systems, such as the susceptible/exposed/infectious/recovered (SEIR) epidemic model. The exponential gradient increases with the population size. For all prefectures, many spectral lines observed in each PSD can be fully assigned to a fundamental mode and its harmonics and subharmonics, or linear combinations of a few fundamental periods, suggesting that the COVID-19 data are substantially noise-free. For prefectures with large population sizes, PSD patterns obtained from segment time series behave in response to the introduction of public and workplace vaccination programs as predicted by theoretical studies based on the SEIR model. The meaning of the relationship between the exponential gradient and the population size is discussed.

Communication needs regarding heart failure trajectory and palliative care between patients and healthcare providers: A cross-sectional study

Introduction Heart failure (HF) is a chronic condition with an unpredictable trajectory, making effective communication between patients and healthcare providers crucial for optimizing outcomes. This study aims to investigate and compare the communication needs regarding HF trajectory and palliative care between patients and healthcare providers and to identify factors associated with the communication needs of patients with HF. Methods A cross-sectional study design was employed, involving 100 patients with HF and 35 healthcare providers. Data were collected using structured questionnaires assessing communication needs, health literacy, self-care behavior, and social support. Statistical analyses were performed, including Spearman’s rank correlation, Pearson’s correlation, and multiple regression analyses. Results Patients prioritized communication related to device-related questions, whereas healthcare providers focused more on aspects of HF in daily life. Both groups ranked end-of-life communication as the lowest priority. The communication needs of patients were positively correlated with health literacy (r = 0.27, p = .007), self-care behavior (r = 0.32, p = .001), and social support (r = 0.24, p = .016). Multiple regression analyses indicated that self-care behavior was a significant factor influencing the communication needs of patients (β = 0.27, p = .011). Conclusions Enhanced patient-centered communication strategies are required to address the communication priority gaps between patients and healthcare providers. Improving health literacy, supporting self-care behaviors, and leveraging social support are critical in meeting patients’ communication needs. Tailored communication training for healthcare providers can bridge this gap and improve overall HF management.

Rural Roads to cognitive Resilience (RRR): A prospective cohort study protocol

Background Ambient air pollution, detrimental built and social environments, social isolation (SI), low socioeconomic status (SES), and rural (versus urban) residence have been associated with cognitive decline and risk of Alzheimer’s disease and related dementias (ADRD). Research is needed to investigate the influence of ambient air pollution and built and social environments on SI and cognitive decline among rural, disadvantaged, ethnic minority communities. To address this gap, this cohort study will recruit an ethnoracially diverse, rural Florida sample in geographic proximity to seasonal agricultural burning. We will (1) examine contributions of smoke-related fine particulate matter (PM 2.5 ) exposures to SI and cognitive function; (2) determine effects of built and social environments on SI and cognitive function; and (3) contextualize SI and cognitive function among residents from different ethnoracial groups during burn and non-burn seasons. Methods We will recruit 1,087 community-dwelling, dementia-free, ≥45-year-olds from five communities in Florida’s Lake Okeechobee region. Over 36 months, participants will complete baseline visits to collect demographics, health history, and health measurements (e.g., blood pressure, body mass index) and 6-month follow-ups assessing cognitive function and social isolation at each visit. A subsample of 120 participants representative of each community will wear smartwatches to collect sensor data (e.g., heart rate) and daily routine and predefined activities (e.g., GPS-captured travel, frequent destinations) over two months. Ecological momentary assessments (EMA) (e.g., whether smoke has bothered participant in last 30 minutes) will occur over two months during agricultural burning and non-burning months. PurpleAir monitors (36 total) will be installed in each community to continuously monitor outdoor PM 2.5 levels. Discussion We expect to identify individual- and community-level factors that increase the risk for SI and cognitive decline in a vulnerable rural population.

Molecular epidemiology and phylogenetic insights of lumpy skin disease in cattle from diverse agro-ecological regions of Punjab, Pakistan

Lumpy skin disease (LSD) is an emerging, highly contagious transboundary disease of bovines caused by the Lumpy skin disease virus (LSDV), responsible for substantial economic losses to the dairy, meat, and leather industries in Pakistan as well as various countries around the world. Epidemiological information on LSD is scarce in Punjab, Pakistan. Therefore, a molecular epidemiological study was conducted in two agro-ecologically diverse districts (Bhakkar and Jhang) of Punjab, Pakistan. A total of 800 blood samples were randomly collected from the jugular vein of clinically suspected cattle with nodular lesions using a multistage cluster sampling technique. The sampling unit was indigenous, crossbred, and exotic breeds of cattle. Four hundred samples were collected from each district. Ten union councils (UC) were selected from each district, and two villages were selected from each union council. From each village, twenty cattle were selected for sample collection. The PCR-based overall prevalence of LSDV in clinically suspected cattle using the P32 gene was 36.25% (36.25%; 290/800). The multivariable logistic regression analysis indicated that animals who were not treated with acaricide (P = 0.014; OR = 1.459; C.I = 1.079–1.972), body condition score (emaciated animals; P = 0.019; OR = 1.573; CI = 1.076–2.301), and gender (female; (P = 0.016; OR = 1.435; CI = 1.072–1.969) were significantly at higher risk for LSDV infection in cattle. The phylogenetic insights revealed that our isolates were linked to Kenya, China, Russia, Egypt, India, Zimbabwe, Iraq, and Iran. It can be concluded that LSD is widely distributed in the study area, with evidence of genetic diversity. Further studies are required on genetic composition using variable genetic markers for effective control and eradication of LSDV in Pakistan.

Modulation pattern recognition method of wireless communication automatic system based on IABLN algorithm in intelligent system

The aim of this study is to address the limitations of convolutional networks in recognizing modulation patterns. These networks are unable to utilize temporal information effectively for feature extraction and modulation pattern recognition, resulting in inefficient modulation pattern recognition. To address this issue, a signal modulation recognition method based on a two-way interactive temporal attention network algorithm has been developed. A two-way interactive temporal network is designed on the basis of the long and short-term memory network with the objective of enhancing the contextual connection of the temporal network. The output of the temporal network is attentively weighted using the soft attention mechanism. The proposed algorithm exhibited enhanced overall, average, and maximum recognition rates at varying signal-to-noise ratios, with an increase of 10.34%, 8.33%, and 3.33%, respectively, in comparison to other algorithms within the Radio Machine Learning (RML) 2016.10b dataset. Furthermore, the modulated signal recognition accuracy was as high as 92.84%, with an average increase in the Kappa coefficient of 12.28%. The Kappa coefficient in the Communication Signal Processing Benchmark for Machine Learning (CSPB.ML2018) 2018 dataset was 0.62, representing an average increase of 10.32% over other algorithms. The results demonstrate that the proposed recognition method can enhance the network’s accuracy in recognizing modulated signals. Moreover, it has potential applications in modulation pattern recognition in automatic systems for wireless communications.

Critical behavioral traits foster peer engagement in Online Mental Health Communities

Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immediate interactions with peers, granting users a vital space for seeking mental health assistance. However, the largely unregulated nature of these platforms introduces intricate challenges for both users and society at large. This study explores the factors that drive peer engagement within counseling threads, aiming to enhance our understanding of this critical phenomenon. We introduce BeCOPE, a novel behavior encoded Peer counseling dataset comprising over 10, 118 posts and 58, 279 comments sourced from 21 mental health-specific subreddits. The dataset is annotated using three major fine-grained behavior labels: (a) intent, (b) criticism, and (c) readability, along with the emotion labels. Our analysis indicates the prominence of “self-criticism” as the most prevalent form of criticism expressed by help-seekers, accounting for a significant 43% of interactions. Intriguingly, we observe that individuals who explicitly express their need for help are 18.01% more likely to receive assistance compared to those who present “surveys” or engage in “rants.” Furthermore, we highlight the pivotal role of well-articulated problem descriptions, showing that superior readability effectively doubles the likelihood of receiving the sought-after support. Our study emphasizes the essential role of OMHCs in offering personalized guidance and unveils behavior-driven engagement patterns.

Daily briefing: The science behind the deadly Los Angeles firestorm