The Extended UTAUT Acceptance Model of Computer-Based Distance Training System Among Public Sector's Employees in Jordan

The utilization of advanced network technologies and modern computer applications in distance learning raises the importance of distance learning system in the delivery of learning materials and resources to remote trainees. This innovation offers the organizations and their employees an opportunity to solve the problems associated with traditional training methods. In this respect, the acceptance of computer based distance training system (CBDTS) is considered critical in determining the success of its implementation. However, the number of studies that have been conducted to examine the acceptance of distance training system by employees of public sector organizations in the Kingdom of Jordan is very limited. It is also questionable whether the information system acceptance models that have been previously developed can be used to examine the acceptance of CBDTS by public sector employees in Jordan. Questions are also raised to the idea that perhaps there may be other factors that play important roles in this context. The main objectives of this study therefore are to determine the factors that lead to the acceptance of public sector employees on computer-based distance training system and finally to propose a model of technology acceptance of computer-based distance training system by public sector employees. A total of 600 questionnaires were distributed through a survey to public sector employees in Jordan. The study received about 386 responses, which represents 64.3% returned rate. Structural equation model (SEM) was used with AMOS version 16.0 to analyze the data. The findings indicate that six core determinants, namely, performance expectancy, effort expectancy, system flexibility, system enjoyment, social influence, and facilitating conditions significantly influenced employee intention to use distance training system. Five core determinants; system interactivity, system enjoyment, computer anxiety, computer self efficacy, and facilitating conditions significantly determine effort expectancy while only four of them including system interactivity, system enjoyment, computer anxiety, and effort expectancy significantly determine performance expectancy. Consequently, based on these findings, the final research model known as computer-based distance training acceptance model (CBDTAM) is proposed to explain and predict public sector employee’s intention in using computer-based distance training system. A comprehensive understanding of this model will assist decision makers to identify the reasons for the acceptance or resistance of computer based distance training system among public sector employees in the future and finally to support them to enhance the system’s acceptance and usage

The Kalman Filter Performance for Dynamic Change in System Parameters

This paper studies the performance of the simple kalman filter for dynamic changes of the system variables. The kalman filter was used to detect the fundamental component of power system signal contained harmonics. First the performance of the kalman filter was examined for a sudden change in the amplitude of the fundamental component, then for a frequency variation. The noise covariance matrices were assumed to be unknown, the values of these matrices were changed to study the.DOI:http://dx.doi.org/10.11591/ijece.v3i6.385

Wind Power Generation Utilizing a Special Buildings Layout Design to Enhance the Wind Speed

There is a high growing interest for the use of wind power utilizing the building's layout design. The main objective of this work is to accelerate the wind speed before reaching the turbines by using spatial design of twin's buildings; this will generate more electric power. The variables which are affecting the wind speed directed to turbines are the angle between the twin buildings, the height and the length of buildings. The results have shown that the wind speed was accelerated in the intervening space between the buildings irrespective of the distance between the walls of adjacent buildings. Nine wind turbines were installed in three rows and three columns on the wall between the two buildings to generate the electricity. These turbines were located at the top of the wall to face higher wind speed because wind speed depends on height. Also the results showed that the wind speed was accelerated by about five times for the building layout design of the present study; while the generated power was about 125 times in comparison with the buildings do not have a spatial layout design (i.e. they do not enclose an angle between them). Finally the average power generated for the present work buildings dimensions with normal consumption of electricity will cover about 13% of the total normal consumption demand of the buildings (the power generated of the present work buildings layout design is about 0.23 GWh/year)

Impacts of hydroclimate change on climate-resilient agriculture at the river basin management

Abstract This paper focuses on exploring the potential of Climate resilient agriculture CRA for river basin scale management Our analysis is based on long term historical and future climate and hydrological datasets within a GIS environment focusing on the Ajoy River basin in West Bengal Eastern India The standardized anomaly index SAI and slope of the linear regression SLR methods were employed to analyse the spatial pattern of the climate variables precipitation Tmax and Tmin and hydrological variables actual evapotranspiration AET runoff Q vapor pressure deficit VPD potential evapotranspiration PET and climate water deficit DEF using the TerraClimate dataset spanning from 1958 to 2020 Future climate trend analysis spanning 2021 to 2050 was conducted using the CMIP6 based GCMs MIROC6 and EC Earth3 dataset under shared socio economic pathway SSP2 4 5 SSP5 8 5 and historical For spatiotemporal water storage analysis we relied on Gravity Recovery and Climate Experiment GRACE from the Center for Space Research CSR and the Jet Propulsion Laboratory JPL data covering the period from 2002 to 2021 Validation was performed using regional groundwater level data employing various machine learning classification models Our findings revealed a negative precipitation trend approximately 0 04 mm year in the southern part whereas the northern part exhibited a positive trend approximately 0 10 mm yea

Risk Stratification of Penicillin Allergy Labeled Children: A Cross-Sectional Study from Jordan

Jomana W Alsulaiman,1 Khalid A Kheirallah,2 Ahmad Alrawashdeh,3 Tareq Saleh,4 Maha Obeidat,5 Yareen J Alawneh,2 Ziydoun Abu Sanad,5 Wajdi Amayreh,1 Rama J Alawneh2 1Department of Pediatrics, Faculty of Medicine, Yarmouk University, Irbid, Jordan; 2Department of Public Health and Family Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan; 3Department of Allied Medical Sciences, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid, Jordan; 4Department of Pharmacology and Public Health, Faculty of Medicine, The Hashemite University, Zarqa, Jordan; 5Department of Pediatrics, Princess Rahma Teaching Hospital, Irbid, JordanCorrespondence: Jomana W Alsulaiman, Associate Professor of Pediatrics, Department of Pediatrics, Faculty of Medicine, Yarmouk University, Irbid, 21163, Jordan, Tel + 962 07 9941 2277, Email [email protected]: Implementing allergy testing among children with a reported history of penicillin allergy could be challenging, particularly in developing countries with limited resources. This study screened and risk-stratified the likelihood of true penicillin allergy among children labeled with penicillin allergy in Jordan.Methods: A web-based survey, completed by parents, assessed history, type, and severity of penicillin allergic reactions, including age at diagnosis, symptoms, time to the reaction, reaction’s course and resolution, and received medical evaluation/testing. Low-risk allergic symptoms were defined as vomiting, diarrhea, headache, dizziness, itching, rash, cough, or runny nose without evidence of anaphylaxis or severe cutaneous reactions.Results: A total of 530 parents of “penicillin allergy”-labeled children completed the survey. Of these, 86.4% reported allergic reactions to penicillin and 13.6% reported avoidance of penicillin due to family history. Among the former, 52.2% were male, 67.3% were three years old or younger when the reported reaction was established, and 68.3% experienced exclusively low-risk symptoms. Overall, skin rash was the most reported symptom (86.0%). High-risk symptoms were reported in 31.5% of children. About two-thirds (64.0%) of children were reported to have experienced symptoms after the first exposure to penicillin. The most common indication for antibiotic use was a throat infection (63.8%). Asthma comorbidity was significantly higher among high-risk (24.8%) compared low-risk group (11.5%).Conclusion: In Jordan, many parent-reported penicillin allergic reactions seem to be clinically insignificant and unlikely to be verifiable, which can adversely affect patients’ care and antimicrobial stewardship. An appropriate clinical history/evaluation is a key step in identifying true immunoglobulin E-mediated allergic reactions and risk stratifying patients for either de-labeling those with obviously non‐immune–mediated reactions or identifying candidates for direct oral challenge test.Keywords: children, drug hypersensitivity, drug resistance, Jordan, penicillin resistanc

UCHL1-dependent control of hypoxia-inducible factor transcriptional activity during liver fibrosis

\ua9 2024 The Author(s)Liver fibrosis is the excessive accumulation of extracellular matrix proteins that occurs in most types of chronic liver disease. At the cellular level, liver fibrosis is associated with the activation of hepatic stellate cells (HSCs) which transdifferentiate into a myofibroblast-like phenotype that is contractile, proliferative and profibrogenic. HSC transdifferentiation induces genome-wide changes in gene expression that enable the cell to adopt its profibrogenic functions. We have previously identified that the deubiquitinase ubiquitin C-terminal hydrolase 1 (UCHL1) is highly induced following HSC activation; however, the cellular targets of its deubiquitinating activity are poorly defined. Here, we describe a role for UCHL1 in regulating the levels and activity of hypoxia-inducible factor 1 (HIF1), an oxygen-sensitive transcription factor, during HSC activation and liver fibrosis. HIF1 is elevated during HSC activation and promotes the expression of profibrotic mediator HIF target genes. Increased HIF1α expression correlated with induction of UCHL1 mRNA and protein with HSC activation. Genetic deletion or chemical inhibition of UCHL1 impaired HIF activity through reduction of HIF1α levels. Furthermore, our mechanistic studies have shown that UCHL1 elevates HIF activity through specific cleavage of degradative ubiquitin chains, elevates levels of pro-fibrotic gene expression and increases proliferation rates. As we also show that UCHL1 inhibition blunts fibrogenesis in a pre-clinical 3D human liver slice model of fibrosis, these results demonstrate how small molecule inhibitors of DUBs can exert therapeutic effects through modulation of HIF transcription factors in liver disease. Furthermore, inhibition of HIF activity using UCHL1 inhibitors may represent a therapeutic opportunity with other HIF-related pathologies

Development and Validation of a Comprehensive Model to Estimate Early Allograft Failure among Patients Requiring Early Liver Retransplant

Importance: Expansion of donor acceptance criteria for liver transplant increased the risk for early allograft failure (EAF), and although EAF prediction is pivotal to optimize transplant outcomes, there is no consensus on specific EAF indicators or timing to evaluate EAF. Recently, the Liver Graft Assessment Following Transplantation (L-GrAFT) algorithm, based on aspartate transaminase, bilirubin, platelet, and international normalized ratio kinetics, was developed from a single-center database gathered from 2002 to 2015. Objective: To develop and validate a simplified comprehensive model estimating at day 10 after liver transplant the EAF risk at day 90 (the Early Allograft Failure Simplified Estimation [EASE] score) and, secondarily, to identify early those patients with unsustainable EAF risk who are suitable for retransplant. Design, Setting, and Participants: This multicenter cohort study was designed to develop a score capturing a continuum from normal graft function to nonfunction after transplant. Both parenchymal and vascular factors, which provide an indication to list for retransplant, were included among the EAF determinants. The L-GrAFT kinetic approach was adopted and modified with fewer data entries and novel variables. The population included 1609 patients in Italy for the derivation set and 538 patients in the UK for the validation set; all were patients who underwent transplant in 2016 and 2017. Main Outcomes and Measures: Early allograft failure was defined as graft failure (codified by retransplant or death) for any reason within 90 days after transplant. Results: At day 90 after transplant, the incidence of EAF was 110 of 1609 patients (6.8%) in the derivation set and 41 of 538 patients (7.6%) in the external validation set. Median (interquartile range) ages were 57 (51-62) years in the derivation data set and 56 (49-62) years in the validation data set. The EASE score was developed through 17 entries derived from 8 variables, including the Model for End-stage Liver Disease score, blood transfusion, early thrombosis of hepatic vessels, and kinetic parameters of transaminases, platelet count, and bilirubin. Donor parameters (age, donation after cardiac death, and machine perfusion) were not associated with EAF risk. Results were adjusted for transplant center volume. In receiver operating characteristic curve analyses, the EASE score outperformed L-GrAFT, Model for Early Allograft Function, Early Allograft Dysfunction, Eurotransplant Donor Risk Index, donor age × Model for End-stage Liver Disease, and Donor Risk Index scores, estimating day 90 EAF in 87% (95% CI, 83%-91%) of cases in both the derivation data set and the internal validation data set. Patients could be stratified in 5 classes, with those in the highest class exhibiting unsustainable EAF risk. Conclusions and Relevance: This study found that the developed EASE score reliably estimated EAF risk. Knowledge of contributing factors may help clinicians to mitigate risk factors and guide them through the challenging clinical decision to allocate patients to early liver retransplant. The EASE score may be used in translational research across transplant centers

ER stress protein AGR2 precedes and is involved in the regulation of pancreatic cancer initiation

The work was supported by a grant A12008 from CR-UK (L. Dumartin, N.R. Lemoine and T. Crnogorac-Jurcevic)

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. Funding: Bill & Melinda Gates Foundation