Evaluating demand driven MRP: a case based simulated study

This study evaluates the assumption underpinning Material Requirements Planning (MRP), buffer management and DDMRP before analysing the case company and evaluating the potential benefits, utilizing simulated data from the existing ERP system. The purpose of this research is to evaluate DDMRP in the context of improving the performance of a printing ink manufacturing company. The main issues the company is facing using a traditional MRP system include poor due-date performance, stock levels not corresponding to the actual market needs and overall system instability leading to inefficiencies. The findings indicate the potential of DDMRP to improve system stability and product availability

Unconventional carrier-mediated ferromagnetism above room temperature in ion-implanted (Ga, Mn)P:C

Ion implantation of Mn ions into hole-doped GaP has been used to induce ferromagnetic behavior above room temperature for optimized Mn concentrations near 3 at.%. The magnetism is suppressed when the Mn dose is increased or decreased away from the 3 at.% value, or when n-type GaP substrates are used. At low temperatures the saturated moment is on the order of one Bohr magneton, and the spin wave stiffness inferred from the Bloch-law T^3/2 dependence of the magnetization provides an estimate Tc = 385K of the Curie temperature that exceeds the experimental value, Tc = 270K. The presence of ferromagnetic clusters and hysteresis to temperatures of at least 330K is attributed to disorder and proximity to a metal-insulating transition.Comment: 4 pages, 4 figures (RevTex4

Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data

Predicting wildfire spread is critical for land management and disaster preparedness. To this end, we present `Next Day Wildfire Spread,' a curated, large-scale, multivariate data set of historical wildfires aggregating nearly a decade of remote-sensing data across the United States. In contrast to existing fire data sets based on Earth observation satellites, our data set combines 2D fire data with multiple explanatory variables (e.g., topography, vegetation, weather, drought index, population density) aligned over 2D regions, providing a feature-rich data set for machine learning. To demonstrate the usefulness of this data set, we implement a neural network that takes advantage of the spatial information of this data to predict wildfire spread. We compare the performance of the neural network with other machine learning models: logistic regression and random forest. This data set can be used as a benchmark for developing wildfire propagation models based on remote sensing data for a lead time of one day.Comment: submitted to IEEE Transactions on Geoscience and Remote Sensin

A High-resolution Large-eddy Simulation Framework for Wildfire Predictions using TensorFlow

As the impact of wildfires has become increasingly more severe over the last decades, there is continued pressure for improvements in our ability to predict wildland fire behavior over a wide range of conditions. One approach towards this goal is through coupled fire/atmosphere modeling tools. While significant progress has been made on advancing their physical fidelity, existing modeling tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. By addressing this gap, this work presents a new wildfire simulation framework that enables landscape-scale wildfire simulations with physical representation of the combustion at affordable computational cost. This is achieved by developing a coupled fire/atmosphere model in the TensorFlow programming paradigm, which enables highly efficient and scalable computations on Tensor Processing Unit (TPU) hardware architecture. To validate this simulation framework and demonstrate its efficiency, simulations of the prescribed fire experiment FireFlux II (Clements et al., 2019) are performed. By considering a parametric study on the mesh resolution, we show that the global quantities such as volumetric heat release and fire-spread rate are insensitive to the horizontal mesh resolution within a range between 0.5 m and 2 m, which is sufficient for predicting fire intermittency and dynamic fire properties associated with fine-scale turbulent structures in the atmospheric boundary layer.Comment: 10 figures, 2 tables, 4559 word

Повышение надежности линейной части магистрального газопровода

Цель работы – повышение надежности линейной части магистрального газопровода путем проведение капитального ремонта участка газопровода 372 – 383 км. Задачи работы: обоснование необходимости проведения капитального ремонта участка газопровода; разработка технологии проведения капитального ремонта маги-стрального газопровода; провести расчеты толщены стенки трубы, проверка трубопро-вода на прочность, проверка трубопровода на пластические деформации.The aim of the work is to increase the reliability of the linear part of the main gas pipeline by overhauling the section of the 372 - 383 km gas pipeline. Work tasks: necessity substantiation for major overhaul of the gas pipeline section; technologies for capital repairs of the mainstream gas pipeline development; Calculate the pipes wall thickness, check the pipeline strength, check the pipeline for plastic deformation

Mediation effect of anxious attachment on relationship between childhood trauma and suicidal ideation sensitive to psychological pain levels

Introduction: Childhood trauma (CT), depression and psychological pain are known predictors of suicidal ideation. Recent literature additionally highlights the importance of the attachment system.Methods: We aimed to predict suicidal ideation through CT, attachment, and psychological and social pain by using mediation models aiming to predict suicidal ideation through CT (predictor) and attachment (mediator). In the same models, we introduced psychological or social pain as moderator of the relationship between attachment, CT, and suicidal ideation. We included 161 depressed patients and assessed depression, attachment, CT, suicidal ideation, psychological pain, and social pain.Results: We found I) a complete mediating effect of anxious attachment (a2b2 = 0.0035, CI95% = [0.0010; 0.0069]) on the relationship between CT on suicidal ideation, and II) a significant complete conditional mediating effect of anxious attachment and psychological pain (Index of moderated mediation VAS: 0.0014; CI95% = [0.0002; 0.0032]) but not social pain on the relationship between CT and suicidal ideation. Both models were controlled for history of suicidal attempt, depression severity, and sex.Conclusion: Our results suggest a developmental profile of suicidal ideation in mood disorder that is characterized by the presence of CT and insecure attachment, especially anxious attachment, that is sensitive to experiences of psychological pain. Nevertheless, we cannot conclude that avoidantly attached individuals do not present the same mechanism, as they may not disclose those ideas

Global and regional trends in particulate air pollution and attributable health burden over the past 50 years

Long-term exposure to ambient particulate matter (PM2.5, mass of particles with an aerodynamic dry diameter of < 2.5 μm) is a major risk factor to the global burden of disease. Previous studies have focussed on present day or future health burdens attributed to ambient PM2.5. Few studies have estimated changes in PM2.5 and attributable health burdens over the last few decades, a period where air quality has changed rapidly. Here we used the HadGEM3-UKCA coupled chemistry-climate model, integrated exposure-response relationships, demographic and background disease data to provide the first estimate of the changes in global and regional ambient PM2.5 concentrations and attributable health burdens over the period 1960 to 2009. Over this period, global mean population-weighted PM2.5 concentrations increased by 38%, dominated by increases in China and India. Global attributable deaths increased by 89% to 124% over the period 1960 to 2009, dominated by large increases in China and India. Population growth and ageing contributed mostly to the increases in attributable deaths in China and India, highlighting the importance of demographic trends. In contrast, decreasing PM2.5 concentrations and background disease dominated the reduction in attributable health burden in Europe and the United States. Our results shed light on how future projected trends in demographics and uncertainty in the exposure–response relationship may provide challenges for future air quality policy in Asia