Masader Plus: A New Interface for Exploring +500 Arabic NLP Datasets

Masader (Alyafeai et al., 2021) created a metadata structure to be used for cataloguing Arabic NLP datasets. However, developing an easy way to explore such a catalogue is a challenging task. In order to give the optimal experience for users and researchers exploring the catalogue, several design and user experience challenges must be resolved. Furthermore, user interactions with the website may provide an easy approach to improve the catalogue. In this paper, we introduce Masader Plus, a web interface for users to browse Masader. We demonstrate data exploration, filtration, and a simple API that allows users to examine datasets from the backend. Masader Plus can be explored using this link https://arbml.github.io/masader. A video recording explaining the interface can be found here https://www.youtube.com/watch?v=SEtdlSeqchk

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Enhancing Smart Irrigation Efficiency: A New WSN-Based Localization Method for Water Conservation

The shortage of water stands as a global challenge, prompting considerable focus on the management of water consumption and irrigation. The suggestion is to introduce a smart irrigation system based on wireless sensor networks (WSNs) aimed at minimizing water consumption while maintaining the quality of agricultural crops. In WSNs deployed in smart irrigation, accurately determining the locations of sensor nodes is crucial for efficient monitoring and control. However, in many cases, the exact positions of certain sensor nodes may be unknown. To address this challenge, this paper presents a new localization method for localizing unknown sensor nodes in WSN-based smart irrigation systems using estimated range measurements. The proposed method can accurately determine the positions of unknown nodes, even when they are located at a distance from anchors. It utilizes the Levenberg–Marquardt (LM) optimization algorithm to solve a nonlinear least-squares problem and minimize the error in estimating the unknown node locations. By leveraging the known positions of a subset of sensor nodes and the inexact distance measurements between pairs of nodes, the localization problem is transformed into a nonlinear optimization problem. To validate the effectiveness of the proposed method, extensive simulations and experiments were conducted. The results demonstrate that the proposed method achieves accurate localization of the unknown sensor nodes. Specifically, it achieves 19% and 58% improvement in estimation accuracy when compared to distance vector-hop (DV-Hop) and semidefinite relaxation-LM (SDR-LM) algorithms, respectively. Additionally, the method exhibits robustness against measurement noise and scalability for large-scale networks. Ultimately, integrating the proposed localization method into the smart irrigation system has the potential to achieve approximately 28% reduction in water consumption

Analytical Model for Enhancing the Adoptability of Continuous Descent Approach at Airports

Continuous Descent Approach (CDA) is the flight technique for aircraft to continuously descend from cruise altitude with an idle thrust setting and without level-offs, contrary to the staircase-like Step-down Descent Approach (SDA). Important for air transportation sustainability, using CDA reduces noise, fuel consumption, and pollution. Nevertheless, CDA has been limited to low traffic levels at airports, often at night, because it requires more separation distance between aircraft arrivals and, thus, could decrease throughput. Insufficient attention has been given to helping air traffic controllers decide when CDA may be used. In this paper, we calculate the probability that an aircraft arriving during a particular brief period of time (e.g., 15 min) will need to revert to SDA when the controller tentatively plans to permit CDA for all aircrafts arriving during that time period. If this probability is low enough, the controller may plan to permit CDA during that time period. We utilize an analytical approach and queueing theory framework that considers factors such traffic and weather conditions to estimate the probability. We also provide the number of aircrafts that can be accommodated within the airport’s stacking space using CDA. This number provides insight into whether a particular aircraft may use CDA

Analytical Model for Enhancing the Adoptability of Continuous Descent Approach at Airports

Continuous Descent Approach (CDA) is the flight technique for aircraft to continuously descend from cruise altitude with an idle thrust setting and without level-offs, contrary to the staircase-like Step-down Descent Approach (SDA). Important for air transportation sustainability, using CDA reduces noise, fuel consumption, and pollution. Nevertheless, CDA has been limited to low traffic levels at airports, often at night, because it requires more separation distance between aircraft arrivals and, thus, could decrease throughput. Insufficient attention has been given to helping air traffic controllers decide when CDA may be used. In this paper, we calculate the probability that an aircraft arriving during a particular brief period of time (e.g., 15 min) will need to revert to SDA when the controller tentatively plans to permit CDA for all aircrafts arriving during that time period. If this probability is low enough, the controller may plan to permit CDA during that time period. We utilize an analytical approach and queueing theory framework that considers factors such traffic and weather conditions to estimate the probability. We also provide the number of aircrafts that can be accommodated within the airport’s stacking space using CDA. This number provides insight into whether a particular aircraft may use CDA

Assessment of risk factors associated with multidrug-resistant organism infections among patients admitted in a tertiary hospital - a retrospective study

Background: Bacterial resistance has become a global health concern. To treat suspected multidrug resistant organisms (MDROs), physicians first use broad-spectrum antibiotics; however, this increases the chance of developing antimicrobial resistance. Thus, defining the risk factors for MDROs could aid in the selection of the ideal initial antimicrobial therapy and improve clinical outcomes. Objective: This study aimed to identify the common risk factors for MDRO infection among patients admitted to King Fahad Hospital (KFH) and to analyze the comorbidity factors associated with MDRO infections. Methods: This retrospective, observational, case-control study included adult patients ≥ 18 years old admitted to KFH between 1st of January to 31st of March 2021, with positive microbial culture. Pediatric patients, outpatients, or patients with only positive fungal cultures were excluded. Data were obtained from the KFH laboratory MDRO documenting database. Results: Two hundred and seventy patients were included in this study: 136 in the study group and 134 in the control group. Among patients, 167 (61.9 %) were males and 184 (68.1%) were 18 to 65 years old. The use of drugs such as cotrimoxazole, amikacin, and imipenem (OR = 4.331, C. I. of OR:1.728, 10.855, p = 0.002) were significantly associated with MDRO infections, whereas cefazolin was associated with a lower risk of MDRO infections (OR = 0.080, C.I. of OR:0.018, 0.347, p < 0.001). The intensive care unit showed higher odds of significant association with MDRO infections than those of the surgical unit (odds ratio [OR] = 8.717, 95% C.I. of OR: 3.040, 24.998, p < 0.001). Patients who previously consumed acid-suppressive medications showed higher odds of developing MDRO infections (OR = 5.333, C.I. of OR: 2.395, 11.877, p < 0.001). Conclusion: The most significant comorbidities were diabetes, hypertension, antibiotic use prior to hospitalization and the use of cotrimoxazole, amikacin and imipenem among other antibtiotics was mostly associated with MRDO infections. This study revealed an increasing trend of MDRO infections and a positive correlation with the incidence of strokes and mortality, which highlights the importance of understanding the risk factors for MDRO infections

Collaborative Impact of Compost and Beneficial Rhizobacteria on Soil Properties, Physiological Attributes, and Productivity of Wheat Subjected to Deficit Irrigation in Salt Affected Soil

Plant growth and crop productivity under unfavorable environmental challenges require a unique strategy to scavenge the severely negative impacts of these challenges such as soil salinity and water stress. Compost and plant growth-promoting rhizobacteria (PGPR) have many beneficial impacts, particularly in plants exposed to different types of stress. Therefore, a field experiment during two successive seasons was conducted to investigate the impact of compost and PGPR either separately or in a combination on exchangeable sodium percentage (ESP), soil enzymes (urease and dehydrogenase), wheat physiology, antioxidant defense system, growth, and productivity under deficient irrigation and soil salinity conditions. Our findings showed that exposure of wheat plants to deficit irrigation in salt-affected soil inhibited wheat growth and development, and eventually reduced crop productivity. However, these injurious impacts were diminished after soil amendment using the combined application of compost and PGPR. This combined application enhanced soil urease and dehydrogenase, ion selectivity, chlorophylls, carotenoids, stomatal conductance, and the relative water content (RWC) whilst reducing ESP, proline content, which eventually increased the yield-related traits of wheat plants under deficient irrigation conditions. Moreover, the coupled application of compost and PGPR reduced the uptake of Na and resulted in an increment in superoxide dismutase (SOD), catalase (CAT), and peroxidase (POX) activities that lessened oxidative damage and improved the nutrient uptake (N, P, and K) of deficiently irrigated wheat plants under soil salinity. It was concluded that to protect wheat plants from environmental stressors, such as water stress and soil salinity, co-application of compost with PGPR was found to be effective

Predictors of Parental Recall of Newborn Hearing Screening Program in Saudi Arabia

Hearing impairment is a prevalent disabling condition among children; all newborns should undergo a universal newborn hearing screening (UNHS). Unfortunately, many newborns who fail the screening test are lost to follow-up. Our study aims to evaluate parents’ perceptions of UNHS and to identify predictors for newborn hearing screening recall in Saudi Arabia. A cross-sectional study involving Saudi parents with 0-to-18-year-old children born in Saudi Arabia was conducted. Descriptive statistics and binary logistic regression were used to describe the participants’ characteristics and to identify UNHS recall predictors. A total of 1533 parents were surveyed. Overall, 29.9% of them recalled a hearing screening at birth, while 22.2% reported no hearing screening, and 47.8% were unable to remember. Only (6.9%) participants reported a failed hearing screening, of which 75.9% recalled a follow-up recommendation. Females, parents aged 30–34 years, consanguineous parents, and parents of newborns who were treated with antibiotics were more likely to recall hearing screening compared to others. This study highlights inadequate awareness of UNHS among parents. Our findings support the need to improve the reporting system of UNHS results and implement educational programs to increase parents’ recall of hearing test results and ensure early follow-ups for neonates with failed test results