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Innovative Technologies in Supply Chain Management for Bangladesh’s Readymade Garments Sector – A Comprehensive Review
Ready-Made Garments (RMG) sector is crucial to Bangladesh's economy, significantly contributing to GDP, employment, and exports. However, supply chain management (SCM) inefficiencies, such as poor demand forecasting, inventory management, logistics, and quality control, pose persistent challenges. This study investigates the potential of integrating advanced technologies like AI, IoT, blockchain, Big Data Analytics, and automation to improve SCM in the Bangladeshi RMG sector. Through a review of literature, industry reports, and case studies, the study assesses the benefits and challenges of technology adoption in the sector. Advanced technologies can enhance visibility, efficiency, quality control, decision-making, and sustainability in SCM. However, challenges such as high costs, data privacy, technical complexity, and resistance to change require strategic planning to overcome. Adopting these technologies can significantly improve the RMG sector's efficiency and global competitiveness, requiring collaboration between policymakers and industry leaders. This study provides a concise analysis of technology integration in Bangladeshi RMG SCM, offering balanced insights to guide future research and industry practices.
Helioseismic inference of the solar radiative opacity
A dynamic co-expression approach reveals Gins2 as a potential upstream modulator of HNSCC metastasis
Genetic coupling of enhancer activity and connectivity in gene expression control
Abstract Gene enhancers often form long-range contacts with promoters, but it remains unclear if the activity of enhancers and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. Here, we study the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 male individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detect 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associate with enhancer accessibility and activity. Capitalising on these shared effects, we devise a multi-modality Bayesian strategy, identifying 629 “trimodal QTLs” jointly associated with enhancer accessibility, eGene promoter contact, and gene expression. Causal mediation analysis and CRISPR interference reveal causal relationships between these three modalities. Many detected QTLs overlap disease susceptibility loci and influence the predicted binding of myeloid transcription factors, including SPI1, GABPB and STAT3. Additionally, a variant associated with PCK2 promoter contact directly disrupts a CTCF binding motif and impacts promoter insulation from downstream enhancers. Jointly, our findings suggest an inherent genetic coupling of enhancer activity and connectivity in gene expression control relevant to human disease and highlight the regulatory role of genetically determined chromatin boundaries.
Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis
Data-driven exploration of weak coordination microenvironment in solid-state electrolyte for safe and energy-dense batteries
Binocular stereo vision-based relative positioning algorithm for drone swarm
A compendium of Amplification-Related Gain Of Sensitivity genes in human cancer
Abstract While the effect of amplification-induced oncogene expression in cancer is known, the impact of copy-number gains on “bystander” genes is less understood. We create a comprehensive map of dosage compensation in cancer by integrating expression and copy number profiles from over 8000 tumors in The Cancer Genome Atlas and cell lines from the Cancer Cell Line Encyclopedia. Additionally, we analyze 17 cancer open reading frame screens to identify genes toxic to cancer cells when overexpressed. Combining these approaches, we propose a class of ‘Amplification-Related Gain Of Sensitivity’ (ARGOS) genes located in commonly amplified regions, yet expressed at lower levels than expected by their copy number, and toxic when overexpressed. We validate RBM14 as an ARGOS gene in lung and breast cancer cells, and suggest a toxicity mechanism involving altered DNA damage response and STING signaling. We additionally observe increased patient survival in a radiation-treated cancer cohort with RBM14 amplification.
Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
Splicing accuracy varies across human introns, tissues, age and disease
Abstract Alternative splicing impacts most multi-exonic human genes. Inaccuracies during this process may have an important role in ageing and disease. Here, we investigate splicing accuracy using RNA-sequencing data from >14k control samples and 40 human body sites, focusing on split reads partially mapping to known transcripts in annotation. We show that splicing inaccuracies occur at different rates across introns and tissues and are affected by the abundance of core components of the spliceosome assembly and its regulators. We find that age is positively correlated with a global decline in splicing fidelity, mostly affecting genes implicated in neurodegenerative diseases. We find support for the latter by observing a genome-wide increase in splicing inaccuracies in samples affected with Alzheimer’s disease as compared to neurologically normal individuals. In this work, we provide an in-depth characterisation of splicing accuracy, with implications for our understanding of the role of inaccuracies in ageing and neurodegenerative disorders.