Birth weight pattern and factors affecting birth weight in urban areas of South-Western Ethiopia

Abstract: A community-based cross-sectional study of birth-weight was carried out in 30 villages of Jimma Zone, to determine the pattern of birth weight, its relationship with ante-natal care, and the influencing factors in birth-weight. A total of 537 mother-newborn pairs were included in the study revealing an overall low birth weight rate of 10.6%. About 72% of the mothers were booked for ante-natal care during the current pregnancy, and 332 (86%) of the deliveries were attended by trained personnel, including trained traditional birth attendants. Mean birth-weight for both sexes was 3,202 grams; and there was no statistically significant difference between the sexes (P>0.05). Higher mean birth weight was observed for newborns whose mothers attended ante-natal clinic and whose births were attended by trained personnel than those mothers without ante-natal care and unattended by trained personnel (P<0.05). Low birth weight was associated with being single, poor, without ante-natal care and not attended by trained personnel during delivery. Efforts to increase the utilization of ante-natal care services is recommended to minimize the risk of low birth-weight as it will help the timely correction of factors predicting low birth weight. [Ethiop. J. Health Dev. 1998;12(1):33-37

Thermal Analysis of a New Sliding Smart Window Integrated with Vacuum Insulation, Photovoltaic, and Phase Change Material

A zero-energy building (ZEB) requires an innovative integration of technologies, in which windows play a paramount role in energy reduction, storage, and generation. This study contributes to four innovative designs of sliding smart windows. It integrates air-gap (AG), phase change material (PCM), photovoltaic (PV), and vacuum glazing (VG) technologies. These smart sliding windows are proposed to generate electricity along with achieving efficient thermal insulations and heat storage simultaneously. A two-dimensional multiphysics thermal model that couples the PCM melting and solidification model, PV model, natural convection in the cavity, and the surface-to-surface radiation model in the vacuum gap are developed for the first time. The model is validated with data in the literature. The transient simulations were carried out to investigate the thermo-electrical performance of a window with an area of 1 m by 1 m for the meteorological conditions of Kuwait city on the 10th of June 2018, where the window was oriented to south direction. The results showed that the total solar heat energy gain per unit window area is 2.6 kWh, 0.02 kWh, 0.22 kWh, 1.48 kWh, and 0.2 kWh for the double AG, AG + PV + PCM + VG, PV + PCM + VG, AG + PV + PCM, and the ventilated AG + PV + PCM + VG, respectively. The results elucidate the advantages of the integration of VG in this integrated sliding smart window. The daily generated PV electrical energy in these systems is around 1.3 kWh, 1.43 kWh, and 1.38 kWh for the base case with double AG, PV + PCM + VG, and the ventilated AG + PV + PCM + VG respectively per unit window area

Fourth-generation SM imprints in B -> K^*l^+l^- decays with polarized K^*

The implication of the fourth-generation quarks in the B -> K^*l^+l^- (l=mu,tau) decays, when K^* meson is longitudinally or transversely polarized, is presented. In this context, the dependence of the branching ratio with polarized K^* and the helicity fractions (f_{L,T}) of K^* meson are studied. It is observed that the polarized branching ratios as well as helicity fractions are sensitive to the NP parameters, especially when the final state leptons are tauons. Hence the measurements of these observables at LHC can serve as a good tool to investigate the indirect searches of new physics beyond the Standard Model.Comment: 13 pages, 10 figures, V2: some of the graphs are modified according to the new data from recent experiments. arXiv admin note: substantial text overlap with arXiv:1107.569

High Frequency of cagA and vacA s1a/m2 Genotype among Helicobacter pylori Infected Gastric Biopsies of Pakistani Children

The vacuolating cytotoxin VacA and cytotoxin associated gene product CagA, encoded by vacA and cagA are major virulence determinants associated with pathogenesis of Helicobacter pylori. The presence and prevalence of two major H. pylori virulence associated genes among gastric biopsies of Pakistani children were investigated in the current study. Fifty one gastric biopsy specimens of children were analysed for 16S rRNA, vacA and cagA genes using PCR. The results showed that 21 (41.2%) biopsies were positive for H. pylori as determined by 16S rRNA PCR. In the 21 H. pylori positive gastric biopsies, 19 (90.5%) showed vacA s1a, 1 (4.75%) was vacA s1b and 1 (4.75%) was vacA s2 whereas, 5 (23.8%) were vacA m1 and 16 (76.2%) were vacA m2. None of the H. pylori positive biopsies carried vacA s1c subtype. The cagA gene was found in 13 (61.9%) of H. pylori infected biopsies and different vacA combinations were found with or without cagA gene. H. pylori was detected with high frequency of cagA while vacA s1a and vacA m2 regions with vacA s1a/m2 genotype were predominant in H. pylori infected gastric biopsies of children

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]

Human Body Posture Recognition Approaches: A Review

Human body posture recognition has become the focus of many researchers in recent years. Recognition of body posture is used in various applications, including surveillance, security, and health monitoring. However, these systems that determine the body’s posture through video clips, images, or data from sensors have many challenges when used in the real world. This paper provides an important review of how most essential ‎ hardware technologies are ‎used in posture recognition systems‎. These systems capture and collect datasets through ‎accelerometer sensors or computer vision. In addition, this paper presents a comparison ‎study with state-of-the-art in terms of accuracy. We also present the advantages and ‎limitations of each system and suggest promising future ideas that can increase the ‎efficiency of the existing posture recognition system. Finally, the most common datasets ‎applied in these systems are described in detail. It aims to be a resource to help choose one of the methods in recognizing the posture of the human body and the techniques that suit each method. It analyzes more than 80 papers between 2015 and 202

Comparison of mechanical properties of wheat and rice straw influenced by loading rates

This study investigates the comparison of mechanical properties of wheat and rice straw such as shear strength, specific shearing energy and cutting forces. The experiments were conducted at three loading rate of 15, 20 and 25 mm min-1 and three internode positions 70 (N1), 130 (N2) and 190 (N3) mm down from the ear. Results show that by increasing the loading rate, strength of wheat and rice straw changed from 8.12 to 22.94 and 6.06 to 14.33 MPa and specific shear energy was varied from 12.10 to 18.64 and 10.40 to 16.17 mJ mm-2, respectively. Moreover, the values of cutting forces of wheat and rice straw were within the ranges 13.23 to 19.50 and 9.40 to 16.70 N. Whereas the shear strength, specific shearing energy and cutting force were higher at higher loading rate at the third internode of both straw internode positions. The shear strength, specific shearing energy and cutting force of rice straw were significantly higher (p<0.05) than that of wheat straw. With respect to the findings of the present research study, it is concluded that with decreasing loading rate of cutting blade toward the first internode, more energy can be saved by harvesting and threshing machines.Keywords: Cutting force, rice straw, shear strength, specific shearing energy, wheat strawAfrican Journal of Biotechnology Vol. 12(10), pp. 1068-107

Arabic fake news detection for Covid-19 using deep learning and machine learning

When newspapers were the dominant form of conventional media, fake news was widespread. Due to the vast influence of such false news and the growing user reach of technical media sources (TV, Internet, social media, blogs). Humans have become more dependent on the news as they make daily decisions for ensuring the safety of their loved ones and themselves in the wake of COVID-19 becoming a pandemic which has impacted humans all over the world. Fake news, on the other hand, is on the verge of becoming a "second pandemic" or "infodemic," endangering the health of individuals all over the world. Previous research hasn't used fake news detection to coronavirus in Arabic due to the fact that fake news connected to coronavirus is such a recent occurrence. A total of 4 versions of the datasets used in this study have been produced (D0, D1, D2, and D3). To understand the effects of deep learning (DL) and machine learning (ML) techniques on any dataset, a total of 4 datasets were created. Also, the research analyzes them with regard to ML and DL to determine the efficacy of preprocessing (D1), raw dataset (D0), light stemming (D3), and root stemming (D2). Dataset version zero (D0) is finished when creating an excel file. From the first version (D0), three more versions (D2, D1, and D3) were created. This study examines the detection of fake news articles concerning COVID-19 on Facebook with the use of DL approaches, like the Bidirectional Long Short-Term Memory Networks (Bi-LSTM), Bidirectional Encoder Representations from Transformers (BERT) and AraBert of Arabic text and ML techniques Linear Support Vector Machines (SVM) and Random Forest (RF). On testing data-set (D0), BERT yields the greatest accuracy of 97.32