New Outlooks on Reshaping and Revitalizing Post-Conflict Regions: Strategies, Principles and Models of Reconstruction

Within societies recently recovering from war, people operating at the community or national levels are pressed to deal with reconciliation, development, reintegration and security. Changes and advancements are already at our front door in political philosophy, technology, communications, infrastructure, and shifts in attitudes and behavior of people. All of this will affect regions and communities, and basically alter the requisites for future planning and roles of professionals. Planning in the new millennium is needed to assist people and communities to manage change by all the techniques and skills that it possesses. In progressive crisis situations there is a need for progressive methods and new approaches, especially if the systems in use are not producing necessary results and changes. The situation where the primary objective is the rebuilding of livelihoods and rebuilding a community in a traumatized setting, a holistic way of looking at the ''big picture'' is a condicio sine qua non for any sustainable development effort. The paper draws attention to situations, which require interdisciplinary approaches and the collaboration of different professional actors. In order to structure the complex question of post-conflict reconstruction in a more systematic way, a conceptual interdisciplinary model called Sustainable Communities in Post-Conflict Environments (SCOPE) could be developed for rebuilding communities. This presentation looks at how such a model, applied to places like Bosnia and Herzegovina and Kosovo, can effectively conceptualize and design policies, programs and projects that efficiently address the above-mentioned issues, giving at the same time a new strategic and innovative approach.

Customer Segmentation and Business Sales Forecasting using Machine Learning for Business Development

This study explores the application of machine learning techniques for business development, focusing on sales prediction and customer segmentation, using a Walmart dataset. Performance metrics include Mean Absolute Error (MAE) and R2 scores. Our hybrid approach combines the BIRCH algorithm with time-lagged machine learning (TL-ML). The results reveal that customer segmentation significantly improves model performance across all metrics. Among the techniques tested, models incorporating customer segmentation (CS-RFR and CS-TL-ML) outperform standard Random Forest Regressor models. Specifically, CS-TL-ML shows a slight advantage in terms of both lower MAE and higher R2 scores, confirming its efficacy for sales prediction and customer segmentation tasks

UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection

Deep Ensemble Convolutional Neural Networks has become a methodology of choice for analyzing medical images with a diagnostic performance comparable to a physician, including the diagnosis of Diabetic Retinopathy. However, commonly used techniques are deterministic and are therefore unable to provide any estimate of predictive uncertainty. Quantifying model uncertainty is crucial for reducing the risk of misdiagnosis. A reliable architecture should be well-calibrated to avoid over-confident predictions. To address this, we propose a UATTA-ENS: Uncertainty-Aware Test-Time Augmented Ensemble Technique for 5 Class PIRC Diabetic Retinopathy Classification to produce reliable and well-calibrated predictions.Comment: To Appear at Medical Imaging meets NeurIPS Workshop 202

Rhizospheric bacteria: the key to sustainable heavy metal detoxification strategies

The increasing rate of industrialization, anthropogenic, and geological activities have expedited the release of heavy metals (HMs) at higher concentration in environment. HM contamination resulting due to its persistent nature, injudicious use poses a potential threat by causing metal toxicities in humans and animals as well as severe damage to aquatic organisms. Bioremediation is an emerging and reliable solution for mitigation of these contaminants using rhizospheric microorganisms in an environmentally safe manner. The strategies are based on exploiting microbial metabolism and various approaches developed by plant growth promoting bacteria (PGPB) to minimize the toxicity concentration of HM at optimum levels for the environmental clean-up. Rhizospheric bacteria are employed for significant growth of plants in soil contaminated with HM. Exploitation of bacteria possessing plant-beneficial traits as well as metal detoxifying property is an economical and promising approach for bioremediation of HM. Microbial cells exhibit different mechanisms of HM resistance such as active transport, extra cellular barrier, extracellular and intracellular sequestration, and reduction of HM. Tolerance of HM in microorganisms may be chromosomal or plasmid originated. Proteins such as MerT and MerA of mer operon and czcCBA, ArsR, ArsA, ArsD, ArsB, and ArsC genes are responsible for metal detoxification in bacterial cell. This review gives insights about the potential of rhizospheric bacteria in HM removal from various polluted areas. In addition, it also gives deep insights about different mechanism of action expressed by microorganisms for HM detoxification. The dual-purpose use of biological agent as plant growth enhancement and remediation of HM contaminated site is the most significant future prospect of this article

Nano-biochar: recent progress, challenges, and opportunities for sustainable environmental remediation

Biochar is a carbonaceous by-product of lignocellulosic biomass developed by various thermochemical processes. Biochar can be transformed into “nano-biochar” by size reduction to nano-meters level. Nano-biochar presents remarkable physico-chemical behavior in comparison to macro-biochar including; higher stability, unique nanostructure, higher catalytic ability, larger specific surface area, higher porosity, improved surface functionality, and surface active sites. Nano-biochar efficiently regulates the transport and absorption of vital micro-and macro-nutrients, in addition to toxic contaminants (heavy metals, pesticides, antibiotics). However an extensive understanding of the recent nano-biochar studies is essential for large scale implementations, including development, physico-chemical properties and targeted use. Nano-biochar toxicity on different organisms and its in-direct effect on humans is an important issue of concern and needs to be extensively evaluated for large scale applications. This review provides a detailed insight on nanobiochar research for (1) development methodologies, (2) compositions and properties, (3) characterization methods, (4) potentiality as emerging sorbent, photocatalyst, enzyme carrier for environmental application, and (5) environmental concerns

Total sulfane sulfur bioavailability reflects ethnic and gender disparities in cardiovascular disease

Hydrogen sulfide (H2S) has emerged as an important physiological and pathophysiological signaling molecule in the cardiovascular system influencing vascular tone, cytoprotective responses, redox reactions, vascular adap- tation, and mitochondrial respiration. However, bioavailable levels of H2S in its various biochemical metabolite forms during clinical cardiovascular disease remain poorly understood. We performed a case-controlled study to quantify and compare the bioavailability of various biochemical forms of H2S in patients with and without cardiovascular disease (CVD). In our study, we used the reverse-phase high performance liquid chromatography monobromobimane assay to analytically measure bioavailable pools of H2S. Single nucleotide polymorphisms (SNPs) were also identified using DNA Pyrosequencing. We found that plasma acid labile sulfide levels were significantly reduced in Caucasian females with CVD compared with those without the disease. Conversely, plasma bound sulfane sulfur levels were significantly reduced in Caucasian males with CVD compared with those without the disease. Surprisingly, gender differences of H2S bioavailability were not observed in African Americans, although H2S bioavailability was significantly lower overall in this ethnic group compared to Caucasians. We also performed SNP analysis of H2S synthesizing enzymes and found a significant increase in cystathionine gamma-lyase (CTH) 1364 G-T allele frequency in patients with CVD compared to controls. Lastly, plasma H2S bioavailability was found to be predictive for cardiovascular disease in Caucasian subjects as de- termined by receiver operator characteristic analysis. These findings reveal that plasma H2S bioavailability could be considered a biomarker for CVD in an ethnic and gender manner. Cystathionine gamma-lyase 1346 G-T SNP might also contribute to the risk of cardiovascular disease development

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Gingival augmentation procedure prior to fixed orthodontic treatment

Patients seek orthodontic treatment for correction of malocclusion and aesthetic improvement. A strong correlation between labially placed teeth and gingival recession has been found. If such cases are left untreated with or without orthodontic therapy, it may lead to an increase in the severity of the disease. A similar case of a 21-year-old male patient with gingival recession in the mandibular anterior region is reported. The patient was successfully treated using a free gingival graft technique. This technique not only improves the aesthetic aspect but also avoids future attachment loss and thus makes the patient more stable for further orthodontic treatment. The aim behind the treatment of gingival recession is not only to cover the exposed root surface, but also to improve aesthetics and reduce dentinal hypersensitivity. Different soft tissue-grafting procedures have been proposed for the treatment of gingival recession, of which free gingival graft is the most reliable one. The purpose of this case report is to illustrate the importance of root coverage prior to orthodontic treatment and to describe the planning for successful treatment which will improve the overall periodontal status of the patient