Water Poverty and its Impact on Income Poverty and Health Status in Sudan: The Case of Gezira State (1993-2013)

Water resource development can address poverty, improve well-being, and enhance people\u27s opportunities in different fields of life. Even though water resources are available in Sudan, some parts of the country still continue to face significant water provision challenges. This research is aimed at measuring water poverty in Gezira State, Sudan over the period of 1993-2013 using the methodology of Sullivan et al. (2003). The research employed data collected from the Central Bureau of Statistics, Khartoum, Sudan. Both descriptive and empirical approaches are used to analyze the data. The average incidence of the water poverty index (WPI) over the period under consideration is estimated at 41.8 %, which is quite high given the fact that Gezira State is endowed with huge water resources and capacities. Environmental problems are found to be the main contributor to water poverty in the state. The results also assert that water poverty significantly increases income poverty. In this case, a 1% increase in water poverty is found to increase income poverty by 2.3%. It is worth noting that agriculture is the dominant economic activity in Gezira State because water is of paramount importance for production, grazing, and agro-industries. Furthermore, the results reveal that water poverty significantly reduces life expectancy at birth. The elasticity of life expectancy at birth with respect to changes in the WPI is estimated at -0.11. The study recommends the adoption of better water use in various fields of development besides solving the water supply problems, particularly in rural areas of the state, solving the environmental challenges that face water resources, enhancing institutional capacities for the water sector, improving the level of water management by the adoption of effective water regularity systems, and encouraging water awareness programs through the different types of media. Investing in water and sanitation is highly recommended to generate rapid returns

On w-copure projective modules

Let $R$ be a commutative ring. An $R$-module $M$ is said to be $w$-split if Ext$_{R}^1(M,N)$ is a GV-torsion $R$-module for all $R$-modules $N$. It is known that every projective module is $w$-split, but the converse is not true in general. In this paper, we study the w-split dimension of a flat module. To do so, we introduce and study the so-called $w$-copure (resp., strongly $w$-copure) projective modules which is in some way a generalization of the notion of copure (resp., strongly copure) projective modules. An $R$-module $M$ is said to be $w$-copure projective (resp., strongly $w$-copure projective) if Ext$_{R}^1(M,N)$ (resp., Ext$_{R}^n(M,N)$) is a GV-torsion $R$-module for all flat $R$-modules $N$ and any $n\geq1$.Comment: 13 page

Blockage Prediction for Mobile UE in RIS-assisted Wireless Networks: A Deep Learning Approach

Due to significant blockage conditions in wireless networks, transmitted signals may considerably degrade before reaching the receiver. The reliability of the transmitted signals, therefore, may be critically problematic due to blockages between the communicating nodes. Thanks to the ability of Reconfigurable Intelligent Surfaces (RISs) to reflect the incident signals with different reflection angles, this may counter the blockage effect by optimally reflecting the transmit signals to receiving nodes, hence, improving the wireless network's performance. With this motivation, this paper formulates a RIS-aided wireless communication problem from a base station (BS) to a mobile user equipment (UE). The BS is equipped with an RGB camera. We use the RGB camera at the BS and the RIS panel to improve the system's performance while considering signal propagating through multiple paths and the Doppler spread for the mobile UE. First, the RGB camera is used to detect the presence of the UE with no blockage. When unsuccessful, the RIS-assisted gain takes over and is then used to detect if the UE is either "present but blocked" or "absent". The problem is determined as a ternary classification problem with the goal of maximizing the probability of UE communication blockage detection. We find the optimal solution for the probability of predicting the blockage status for a given RGB image and RIS-assisted data rate using a deep neural learning model. We employ the residual network 18-layer neural network model to find this optimal probability of blockage prediction. Extensive simulation results reveal that our proposed RIS panel-assisted model enhances the accuracy of maximization of the blockage prediction probability problem by over 38\% compared to the baseline scheme

On τq\tau_q-weak global dimensions of commuative rings

In this paper, the $\tau_q$-weak global dimension $\tau_q$-\cwd$(R)$ of a commutative ring $R$ is introduced. Rings with $\tau_q$-weak global dimension equal to $0$ are studied in terms of homologies, direct products, polynomial extensions and amalgamations. Besides, we investigate the $\tau_q$-weak global dimensions of polynomial rings.Comment: arXiv admin note: text overlap with arXiv:2111.03417, arXiv:2302.0456

Comparison between laser hemorrhoidoplasty procedure and conventional open surgical hemorrhoidectomy

Background: Hemorrhoids are a very common anorectal condition defined as the symptomatic enlargement and distal displacement of the normal anal cushions.Objective: The present study aimed to compare between laser hemorrhoidoplasty and conventional open surgical hemorrhoidectomy in treatment of the hemorrhoidal diseases.Patients and methods: This study included 30 patients with symptomatizing hemorrhoidal diseases. They were divided into two groups: 15 patients underwent open method (MMH) and 15 patients underwent laser method (LHP). They were admitted to General Surgery Department, Faculty of Medicine, Zagazig University Hospitals with symptomatic hemorrhoidal diseases. Full history, clinical examination and pre- and post-operative assessment were performed.Results: The mean age was distributed as 36.03 ± 7.32 in the MMH group and 35.73 ± 8.39 years in the LHP group with no significant difference between both groups. The mean operative time was distributed as 29.53 ± 4.05 and 14.60 ± 3.13 minutes for MMH and LHP groups respectively. The mean hospital stay for MMH group was 36.25 ± 6.58 hours and 7.85 ± 2.11 hours for LHP, MMH group significantly associated with longer hospital stay. MMH group was significantly associated with more bleeding at 1st and 2nd week but no bleeding founded after 2nd week at both groups.Conclusion: laser hemorrhoidoplasty (LHP) technique for the management of hemorrhoids was, with shorter operative time, less postoperative pain, shorter hospital stay, and less postoperative complications than open surgical hemorrhoidectomy

Role of Matrix Metalloproteinase-9 in Neonatal Hypoxic-Ischemic Encephalopathy

BACKGROUND: Neonatal encephalopathy is a heterogeneous syndrome characterised by signs of central nervous system dysfunction in the newborn. Matrix metalloproteinase-9(MMP-9) increases the blood-brain barrier permeability, and their inhibitors can reduce its damage. MMP-9 has been implicated specifically in cerebral ischemia. AIM: To measure serum MMP-9 in neonatal hypoxic-ischemic encephalopathy and evaluate its correlation to the severity of early prediction and treatment. METHODS: its case-control study. The serum concentration of MMP-9 was determined by ELISA in 100 hypoxic neonates and 50 healthy neonates of matched age and sex who served as controls. RESULTS: In our present study the serum MMP-9 level was significantly higher at p = 0.0001 in hypoxic-ischemic full-term newborns (176.7 ± 68.7 ng/ml)as compared to control newborn (69.4 ± 34.85 ng/ml)and it was significantly higher at p = 0.0075 in hypoxic-ischemic preterm newborn (171.2 ± 132.9 ng/ml) when compared to control newborn (72.54 ± 36.74 ng/ml),also MMP-9 was significantly higher at Sarnat stage III at p = 0.0001. CONCLUSION: Serum MMP-9 level was significantly higher in hypoxic-ischemic newborns, and significantly increased with severity, so we suggest that serum MMP-9 level is important for predicting neurological sequel and severity in neonatal encephalopathy. &nbsp

Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18–49, 50–69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population