Over several decades, production and inventory systems have been widely studied in different aspects, but only a few studies have considered the production disruption problem. In production systems, the production may be disrupted by priorly unknown disturbance and the entire manufacturing plan can be distorted. This research introduces a production-disruption model for a multi-product single-stage production-inventory system. First, a mathematical model for the multi-item production-inventory system is developed to maximize the total profit for a single-disruption recovery-time window. The main objective of the proposed model is to obtain the optimal manufacturing batch size for multi-item in the recovery time window so that the total profit is maximized. To maintain the matter of multi-product, budget and space constraints are used. A genetic algorithm and pattern search techniques are employed to solve this model and all randomly generated test results are compared. Some numerical examples and sensitivity analysis are given to explain the effectiveness and advantages of the proposed model. This proposed model offers a recovery plan for managers and decision-makers to make accurate and effective decisions in real time during the production disruption problems.
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http://dx.doi.org/10.1016/j.jmsy.2020.05.015 | DOI Listing |
J Cheminform
January 2025
Department of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, Republic of Korea.
The human ether-a-go-go-related gene (hERG) channel plays a critical role in the electrical activity of the heart, and its blockers can cause serious cardiotoxic effects. Thus, screening for hERG channel blockers is a crucial step in the drug development process. Many in silico models have been developed to predict hERG blockers, which can efficiently save time and resources.
View Article and Find Full Text PDFOrphanet J Rare Dis
January 2025
Laboratory of Neurogenetics and Molecular Medicine, Center for Genomic Sciences in Medicine, Institut de Recerca Sant Joan de Déu, Únicas SJD Center, Hospital Sant Joan de Déu, Barcelona, Spain.
Background: Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. In addition, for most RDs, few to no treatments are available and it is often difficult to find a specialized care team.
Objectives: The project "acERca las enfermedades raras" (in English: "bringing RDs closer") is an initiative primary designed to generate a consensus by a multidisciplinary group of experts to detect the strengths and weaknesses in the public healthcare system concerning the comprehensive care of persons living with a RD (PLWRD) in the region of Catalonia, Spain, where a Network of Clinical Expert Units (Xarxa d'Unitats de Expertesa Clínica or XUEC) was created and is being implemented since 2015.
BMC Psychiatry
January 2025
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
The current DSM-oriented diagnostic paradigm has introduced the issue of heterogeneity, as it fails to account for the identification of the neurological processes underlying mental illnesses, which affects the precision of treatment. The Research Domain Criteria (RDoC) framework serves as a recognized approach to addressing this heterogeneity, and several assessment and translation techniques have been proposed. Among these methods, transforming RDoC scores from electronic medical records (EMR) using Natural Language Processing (NLP) has emerged as a suitable technique, demonstrating clinical effectiveness.
View Article and Find Full Text PDFPsychon Bull Rev
January 2025
Boston University, Boston, USA.
Individuals with "agrammatic" receptive aphasia have long been known to rely on semantic plausibility rather than syntactic cues when interpreting sentences. In contrast to early interpretations of this pattern as indicative of a deficit in syntactic knowledge, a recent proposal views agrammatic comprehension as a case of "noisy-channel" language processing with an increased expectation of noise in the input relative to healthy adults. Here, we investigate the nature of the noise model in aphasia and whether it is adapted to the statistics of the environment.
View Article and Find Full Text PDFGeroscience
January 2025
Division of Endocrinology, Department of Medicine, Augusta University, Augusta, GA, USA.
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is frequently associated with musculoskeletal complications, including sarcopenia and osteoporosis, which substantially impair patient quality of life. Despite these clinical observations, the molecular mechanisms linking AD to bone loss remain insufficiently explored. In this study, we examined the femoral bone microarchitecture and transcriptomic profiles of APP/PS1 transgenic mouse models of AD to elucidate the disease's impact on bone pathology and identify potential gene candidates associated with bone deterioration.
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