Manufacturing Strategy: An Analysis of the Saudi Manufacturing Private Sector

This study is motivated by the desire to develop an understanding of the manufacturing strategy concept within the Saudi business environment. More specifically the objectives of the study are to detect the existing type of manufacturing strategies in Saudi plants in the last two years (i.e., 1987 and 1988) as well as in the next two years (i.e., 1990 and 1991); to use SWOT analysis to find out strengths and weaknesses within the plants surveyed as well as opportunities and threats in the environment; and finally to test six hypotheses of the model of manufacturing strategy. The model consists of eight factors: organisational environment, corporate and business strategies, manufacturing task statement, manufacturing task, the role of the production manager, structural category of decisions, infrastructural category of decisions, and finally organisational performance

Chemical Properties from Graph Neural Network-Predicted Electron Densities

According to density functional theory, any chemical property can be inferred from the electron density, making it the most informative attribute of an atomic structure. In this work, we demonstrate the use of established physical methods to obtain important chemical properties from model-predicted electron densities. We introduce graph neural network architectural choices that provide physically relevant and useful electron density predictions. Despite not training to predict atomic charges, the model is able to predict atomic charges with an order of magnitude lower error than a sum of atomic charge densities. Similarly, the model predicts dipole moments with half the error of the sum of atomic charge densities method. We demonstrate that larger data sets lead to more useful predictions in these tasks. These results pave the way for an alternative path in atomistic machine learning, where data-driven approaches and existing physical methods are used in tandem to obtain a variety of chemical properties in an explainable and self-consistent manner

AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials

Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is the need to accurately compute the adsorption energy for an adsorbate and a catalyst surface of interest. Traditionally, the identification of low energy adsorbate-surface configurations relies on heuristic methods and researcher intuition. As the desire to perform high-throughput screening increases, it becomes challenging to use heuristics and intuition alone. In this paper, we demonstrate machine learning potentials can be leveraged to identify low energy adsorbate-surface configurations more accurately and efficiently. Our algorithm provides a spectrum of trade-offs between accuracy and efficiency, with one balanced option finding the lowest energy configuration 87.36% of the time, while achieving a 2000x speedup in computation. To standardize benchmarking, we introduce the Open Catalyst Dense dataset containing nearly 1,000 diverse surfaces and 100,000 unique configurations.Comment: 26 pages, 7 figures. Submitted to npj Computational Material

Review of Inverse Laplace Transform Algorithms for Laplace-Space Numerical Approaches

A boundary element method (BEM) simulation is used to compare the efficiency of numerical inverse Laplace transform strategies, considering general requirements of Laplace-space numerical approaches. The two-dimensional BEM solution is used to solve the Laplace-transformed diffusion equation, producing a time-domain solution after a numerical Laplace transform inversion. Motivated by the needs of numerical methods posed in Laplace-transformed space, we compare five inverse Laplace transform algorithms and discuss implementation techniques to minimize the number of Laplace-space function evaluations. We investigate the ability to calculate a sequence of time domain values using the fewest Laplace-space model evaluations. We find Fourier-series based inversion algorithms work for common time behaviors, are the most robust with respect to free parameters, and allow for straightforward image function evaluation re-use across at least a log cycle of time

Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review

BACKGROUND: Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. METHODOLOGY/FINDINGS: Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. CONCLUSIONS: This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future

Micronutrient fortification of food and its impact on woman and child health: A systematic review

Background: Vitamins and minerals are essential for growth and metabolism. The World Health Organization estimates that more than 2 billion people are deficient in key vitamins and minerals. Groups most vulnerable to these micronutrient deficiencies are pregnant and lactating women and young children, given their increased demands. Food fortification is one of the strategies that has been used safely and effectively to prevent vitamin and mineral deficiencies.Methods: A comprehensive search was done to identify all available evidence for the impact of fortification interventions. Studies were included if food was fortified with a single, dual or multiple micronutrients and impact of fortification was analyzed on the health outcomes and relevant biochemical indicators of women and children. We performed a meta-analysis of outcomes using Review Manager Software version 5.1.Results: Our systematic review identified 201 studies that we reviewed for outcomes of relevance. Fortification for children showed significant impacts on increasing serum micronutrient concentrations. Hematologic markers also improved, including hemoglobin concentrations, which showed a significant rise when food was fortified with vitamin A, iron and multiple micronutrients. Fortification with zinc had no significant adverse impact on hemoglobin levels. Multiple micronutrient fortification showed non-significant impacts on height for age, weight for age and weight for height Z-scores, although they showed positive trends. The results for fortification in women showed that calcium and vitamin D fortification had significant impacts in the post-menopausal age group. Iron fortification led to a significant increase in serum ferritin and hemoglobin levels in women of reproductive age and pregnant women. Folate fortification significantly reduced the incidence of congenital abnormalities like neural tube defects without increasing the incidence of twinning. The number of studies pooled for zinc and multiple micronutrients for women were few, though the evidence suggested benefit. There was a dearth of evidence for the impact of fortification strategies on morbidity and mortality outcomes in women and children.Conclusion: Fortification is potentially an effective strategy but evidence from the developing world is scarce. Programs need to assess the direct impact of fortification on morbidity and mortality

Rare case of spot diagnosis of nephrotic syndrome in a Saudi male

A 26- year- old Saudi male school teacher presented with clinical features of nephrotic syndrome. Physical examination revealed loss of subcutaneous fat over the face and upper arms (partial lipodystrophy) and drusen in both eyes. The serum level of complement C3 was low, with normal C4. Renal biopsy revealed features consistent with membranoproliferative glomerulo- nephritis (MPGN) type II [Dense Deposit Disease (DDD)]. He was treated with prednisolone and mycophenolate mofetil with partial remission. He also received lipitor and lisinopril. The occurrence of partial lipo- dystrophy and drusen in a patient with nephrotic syndrome provides a rare clinical opportunity of making a bedside diagnosis of type II MPGN even before kidney biopsy

An Integrated Management Approach for Red Palm Weevil Rhynchophorus Ferrugineus Oliv. a Key Pest of Date Palm in the Middle East

The date palm, Phoenix doctylifera L., is the most important fruit crop in the Middle East, cultivated since prehistoric times. Since mid-eighties the dreaded pest of palms viz. the red palm weevil. Rhynchophorus ferrugineus Oliv. has been reported to cause serious damage to date palm in certain pockets of the Gulf region. The pest subsequently spread to most of the date growing centers in the region and attained a key pest status. The unique agroclimatic conditions prevailing in the Middle East and the nature of the crop, coupled with transportation of planting material have helped in the rapid development and spread of the pest in a short period of about a decade Feeding of the soft tissues by this concealed borer often leads to the death of the palm. if timely curative measures are not adopted. However, taking up curative measures in the early stage of attack is often not possible as detection in infestation in the early stage is difficult. Moreover, the presence of neglected date gardens, beheaded palms, retention of unwanted off shoots etc. make the problem intricate. To tackle this problem from various angles and successfully combat the pest, the following Integrated Pest Management (IPM) programme is suggested. The major components of the IPM strategy are surveillance, trapping the weevil using pheromones lures, detection of infestation by examining palms. Eliminating hidden breeding sites, clearing abandoned gardens, maintaining crop and field sanitation, preventive chemical treatments, curative chemical control implementing quarantine measures and training and education