Application of Supply Chain Tools In Power Plant- A Case of Rayalaseema Thermal Power Plant

Inventories are considered to be one of the important weapons of supply chain to improve the efficiency of any manufacturing unit. Continuous availability of inventories are the prime requirement for uninterrupted working .To effectively manage inventory levels, it is essential to consider the appropriate reorder points as well as the optimized ordering quantity. The proposed system uses the Genetic algorithm to find the optimized ordering quantity at proper reorder point , by considering the power plant live data as a practical case study. The proposed approach is implemented in Matlab  platform version 7.10 Key words. Inventories, supply chain, Genetic algorithm, Reorder point, ordering quantity, manufacturing unit, power plant, raw materials

C3a Enhances Nerve Growth Factor-Induced NFAT Activation and Chemokine Production in a Human Mast Cell Line, HMC-1

Activation of cell surface G protein-coupled receptors leads to transphosphorylation and activation of a number of receptor tyrosine kinases. Human mast cells express G protein-coupled receptors for the complement component C3a (C3aR) and high affinity nerve growth factor (NGF) receptor tyrosine kinase, TrkA. To determine whether C3a cross-regulates TrkA signaling and biological responses, we used a human mast cell-line, HMC-1, that natively expresses both receptors. We found that NGF caused tyrosine phosphorylation of TrkA, resulting in a sustained Ca2+ mobilization, NFAT activation, extracellular-signal regulated kinase (ERK) phosphorylation, and chemokine, macrophage inflammatory protein-1β (MIP-1β) production. In contrast, C3a induced a transient Ca2+ mobilization and ERK phosphorylation but failed to stimulate TrkA phosphorylation, NFAT activation, or MIP-1β production. Surprisingly, C3a significantly enhanced NGF-induced NFAT activation, ERK phosphorylation, and MIP-1β production. Pertussis toxin, a Gi/o inhibitor, selectively blocked priming by C3a but had no effect on NGF-induced responses. Mitogen-activated protein/ERK kinase inhibitor U0126 caused ∼30% inhibition of NGF-induced MIP-1β production but had no effect on priming by C3a. However, cyclosporin A, an inhibitor of calcineurin-mediated NFAT activation, caused substantial inhibition of NGF-induced MIP-1β production both in the absence and presence of C3a. These data demonstrate that NGF caused tyrosine phosphorylation of TrkA to induce chemokine production in HMC-1 cells via a pathway that mainly depends on sustained Ca2+ mobilization and NFAT activation. Furthermore, C3a enhances NGF-induced transcription factor activation and chemokine production via a G protein-mediated pathway that does not involve TrkA phosphorylation

COVID-19 Pandemic and Its Effects on Youth Mental Health in Bangladesh

COVID-19 is a worldwide pandemic that is caused by severe acute respiratory syndrome coronavirus (SAR-CoV-2). For the effect of this pandemic, the people of Bangladesh are suffering from unprecedented challenges of all ages. Coronavirus pandemic has hit the young mental health badly. The main purpose of this research was to investigate the mental health condition among young people during the COVID-19 pandemic in Bangladesh. In this study, a qualitative research method was used where twenty case studies were carried out to evaluate critical situations as well as the determinants of psychological health problems that young adults are facing. Result demonstrates that like other ages, young people are bound to stay at home during lockdown that causes a profound effect on their mental health. Due to COVID-19 young people are going through a variety of critical situations including financial hardship, conflict with family members, quarantine-related crisis, increasing pressure for marriage, extreme addiction to the virtual world, and addiction to different video games that threaten their psychological health, for example increasing suicidal tendency, loneliness, anxiety, depression, psychological trauma, low self-confidence anger, etc. Researchers have suggested some potential recommendations to reduce the psychological pressure of young people during pandemics

A technical perspective on integrating artificial intelligence to solid-state welding

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes with an accuracy range of 85 – 99%, while Response Surface Methodology such as Optimization Strategy can achieve up to 95 percent confidence levels in improving bonding strength and optimizing process parameters. Using ANNs for FSW gives an average percentage error of about 95%, but using metaheuristics refined it at an incrementally improved accuracy rate of about 2%. In UW, ANN, Hybrid ANN, and ML models predict output parameters with accuracy levels ranging from 85 to 96%. Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. ANN’s high accuracy of nearly 95% compared to other techniques like FL and ML in predicting welding parameters. HM exhibits superior precision, showcasing their potential to enhance weld quality, minimize trial welds, and reduce costs and time. Various emerging hybrid methods offer better prediction accuracy

The Isoelectric Region of Proteins: A Systematic Analysis

Background: Binding of proteins in ion exchange chromatography is dominated by electrostatic interactions and can be tuned by adjusting pH and ionic strength of the solvent. Therefore, the isoelectric region (IER), the pH region of almost zero charge near the pI, has been used to predict the binding properties of proteins. Principal findings: Usually the IER is small and binding and elution is carried out at pH values near to the pI. However, some proteins with an extended IER have been shown to bind and elute far away from its pI. To analyze factors that mediate the size of the IER and to identify proteins with an extended IER, two protein families consisting of more than 7000 proteins were systematically investigated. Most proteins were found to have a small IER and thus are expected to bind or elute near to their pI, while only a small fraction of less than 2 % had a large IER. Conclusions: Only four factors, the number of histidines, the pI, the number of titratable amino acids and the ratio of acidic to basic residues, are sufficient to reliably classify proteins by their IER based on their sequence only, and thus to predict their binding and elution behaviour in ion exchange chromatography

Relationships of Brain Cholesterol and Cholesterol Biosynthetic Enzymes to Alzheimer’s Pathology and Dementia in the CFAS Population-Derived Neuropathology Cohort

Altered cholesterol metabolism is implicated in brain ageing and Alzheimer's disease. We examined whether key genes regulating cholesterol metabolism and levels of brain cholesterol are altered in dementia and Alzheimer's disease neuropathological change (ADNC). Temporal cortex (n = 99) was obtained from the Cognitive Function and Ageing Study. Expression of the cholesterol biosynthesis rate-limiting enzyme HMG-CoA reductase (HMGCR) and its regulator, SREBP2, were detected using immunohistochemistry. Expression of HMGCR, SREBP2, CYP46A1 and ABCA1 were quantified by qPCR in samples enriched for astrocyte and neuronal RNA following laser-capture microdissection. Total cortical cholesterol was measured using the Amplex Red assay. HMGCR and SREBP2 proteins were predominantly expressed in pyramidal neurones, and in glia. Neuronal HMGCR did not vary with ADNC, oxidative stress, neuroinflammation or dementia status. Expression of HMGCR neuronal mRNA decreased with ADNC (p = 0.022) and increased with neuronal DNA damage (p = 0.049), whilst SREBP2 increased with ADNC (p = 0.005). High or moderate tertiles for cholesterol levels were associated with increased dementia risk (OR 1.44, 1.58). APOE ε4 allele was not associated with cortical cholesterol levels. ADNC is associated with gene expression changes that may impair cholesterol biosynthesis in neurones but not astrocytes, whilst levels of cortical cholesterol show a weak relationship to dementia status

Analysis of the potential of cancer cell lines to release tissue factor-containing microvesicles: correlation with tissue factor and PAR2 expression

BackgroundDespite the association of cancer-derived circulating tissue factor (TF)-containing microvesicles and hypercoagulable state, correlations with the incidence of thrombosis remain unclear.MethodsIn this study the upregulation of TF release upon activation of various cancer cell lines, and the correlation with TF and PAR2 expression and/or activity was examined. Microvesicle release was induced by PAR2 activation in seventeen cell lines and released microvesicle density, microvesicle-associated TF activity, and phoshpatidylserine-mediated activity were measured. The time-course for TF release was monitored over 90 min in each cell line. In addition, TF mRNA expression, cellular TF protein and cell-surface TF activities were quantified. Moreover, the relative expression of PAR2 mRNA and cellular protein were analysed. Any correlations between the above parameters were examined by determining the Pearson’s correlation coefficients.ResultsTF release as microvesicles peaked between 30–60 min post-activation in the majority of cell lines tested. The magnitude of the maximal TF release positively correlated with TF mRNA (c = 0.717; p

Abundance of ACVR1B transcript is elevated during septic conditions: perspectives obtained from a hands-on reductionist investigation

Sepsis is a complex heterogeneous condition, and the current lack of effective risk and outcome predictors hinders the improvement of its management. Using a reductionist approach leveraging publicly available transcriptomic data, we describe a knowledge gap for the role of ACVR1B (activin A receptor type 1B) in sepsis. ACVR1B, a member of the transforming growth factor-beta (TGF-beta) superfamily, was selected based on the following: 1) induction upon in vitro exposure of neutrophils from healthy subjects with the serum of septic patients (GSE49755), and 2) absence or minimal overlap between ACVR1B, sepsis, inflammation, or neutrophil in published literature. Moreover, ACVR1B expression is upregulated in septic melioidosis, a widespread cause of fatal sepsis in the tropics. Key biological concepts extracted from a series of PubMed queries established indirect links between ACVR1B and "cancer", "TGF-beta superfamily", "cell proliferation", "inhibitors of activin", and "apoptosis". We confirmed our observations by measuring ACVR1B transcript abundance in buffy coat samples obtained from healthy individuals (n=3) exposed to septic plasma (n = 26 melioidosis sepsis cases)ex vivo. Based on our re-investigation of publicly available transcriptomic data and newly generated ex vivo data, we provide perspective on the role of ACVR1B during sepsis. Additional experiments for addressing this knowledge gap are discussed

Engaging Parents in Education for Discharge (\u3cem\u3ee\u3c/em\u3ePED): Evaluating the Reach, Adoption & Implementation of an Innovative Discharge Teaching Method

Purpose This paper describes the evaluation of the implementation of an innovative teaching method, the “Engaging Parents in Education for Discharge” (ePED) iPad application (app), at a pediatric hospital. Design and methods The Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework was used to guide the evaluation. Three of the five RE-AIM elements are addressed in this study: Reach, Adoption, and Implementation. Results The Reach of the ePED was 245 of 1015 (24.2%) patient discharges. The Adoption rate was 211 of 245 (86%) patients discharged in the five months\u27 study period. High levels of fidelity (89.3%) to Implementation of the ePED were attained: the Signs and Symptoms domain had the highest (93%) and Thinking Forward about Family Adjustment screen had the lowest fidelity (83.3%). Nurse themes explained implementation fidelity: “It takes longer”, and “Forgot to do it.” Conclusions The ePED app operationalized how to have an engaging structured discharge conversation with parents. While the Reach of the ePED app was low under the study conditions, the adoption rate was positive. Nurses were able to integrate a theory-driven practice change into their daily routine when using the ePED app. Implications for practice The rates of adoption and implementation fidelity support the feasibility of future hospital wide implementation to improve patient and family healthcare experience. Attention to training of new content and the interactive conversation approach will be needed to fully leverage the value of the ePED app. Future studies are needed to evaluate the maintenance of the ePED app