A New Distribution System Reconfiguration Approach Using Optimum Power Flow and Sensitivity Analysis for Loss Reduction

This paper presents a new approach for distribution system reconfiguration (DSR) based on optimum power flow (OPF) in which the branch statuses (open/close) are represented by continuous functions. In the proposed approach, all branches are initially considered closed, and from the OPF results, a heuristic technique is used to determine the next loop to be broken by opening one switch. Then the list of switches that are candidates to be opened is updated, and the above process is repeated until all loops are broken, making the distribution system radial. This paper includes results and comparisons on test systems utilized in three classical papers published in the technical literature, as well as in a previous paper by the authors. Results obtained on a real large-scale distribution system are also presented     

A Comparative Study of High-Field Diamagnetic Fluctuations in Deoxygenated YBa2Cu3O7-x and Polycrystalline (Bi–Pb)2Sr2Ca2Cu3O10

We studied three single crystals of YBa₂Cu₃O_7-x, (Y123) with superconducting transition temperature, T_c=62.5, 52, and 41 K, and a highly textured polycrystalline specimen of (Bi–Pb)₂Sr₂Ca₂Cu₃O₁₀ (Bi2223), with T_c=108K. Isofield magnetization data were obtained as a function of temperature, with the magnetic field applied parallel to the c axis of each sample. The reversible magnetization data for all samples exhibited a rounded transition as magnetization tended toward zero. The reversible data were interpreted in terms of two-dimensional diamagnetic lowest-Landau-level (LLL) fluctuation theory. The LLL scaling analysis yielded consistent values of the superconducting transition temperatures T_c(H) for the various samples. The resulting scaling data were fit well by the two-dimensional LLL expression for magnetization obtained by Tesanovic and colaborators, producing reasonable values of κ but the fitting parameter ∂H_c2/∂T produced values that were larger than the experimentally determined ones. We performed simultaneous scaling of Y123 data and Bi2223, obtaining a single collapsed curve. The single curve was obtained after multiplying the x and y axis of each scaling curve by appropriate sample-dependent scaling factors. An expression for the two-dimensional x-axis LLL scaling was extracted from theory, allowing comparison of theoretical values of the x-axis scaling factors with the experimental values. The comparison between the values of the x-axis produced a deviation of 40% which suggests that the hypothesis of universality of the two-dimensional LLL fluctuations is not supported by the studied samples. We also observe that Y123 magnetization data for temperatures above T_c obbey a universal scaling obtained for the diamagnetic fluctuation magnetization from a theory considering non-local field effects. The same scaling was not obbeyed by the corresponding magnetization calculated from the two-dimensional LLL theory.     

Ferroptosis Modulation: Potential Therapeutic Target for Glioblastoma Treatment

Glioblastoma multiforme is a lethal disease and represents the most common and severe type of glioma. Drug resistance and the evasion of cell death are the main characteristics of its malignancy, leading to a high percentage of disease recurrence and the patients’ low survival rate. Exploiting the modulation of cell death mechanisms could be an important strategy to prevent tumor development and reverse the high mortality and morbidity rates in glioblastoma patients. Ferroptosis is a recently described type of cell death, which is characterized by iron accumulation, high levels of polyunsaturated fatty acid (PUFA)-containing phospholipids, and deficiency in lipid peroxidation repair. Several studies have demonstrated that ferroptosis has a potential role in cancer treatment and could be a promising approach for glioblastoma patients. Thus, here, we present an overview of the mechanisms of the iron-dependent cell death and summarize the current findings of ferroptosis modulation on glioblastoma including its non-canonical pathway. Moreover, we focused on new ferroptosis-inducing compounds for glioma treatment, and we highlight the key ferroptosis-related genes to glioma prognosis, which could be further explored. Thereby, understanding how to trigger ferroptosis in glioblastoma may provide promising pharmacological targets and indicate new therapeutic approaches to increase the survival of glioblastoma patients.     

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.     

Acoustic seafloor sediment classification using self-organizingfeature maps

A self-organizing feature map (SOFM), a kind of artificial neural network (ANN) architecture, is used in this work for continental shelf seafloor sediment classification. Echo data are acquired using an echosounding system from three types of seafloor sediment areas. Excellent classification (~100%) for an ideal output neuron grid size of 15×1 is obtained for a moving average of 35 input snapshots     

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.     

Characterizing landscape changes in central Rondonia using Landsat TM imagery

An analysis of landscape changes in a region of pioneer settlements in central Rondonia, western Brazilian Amazon, was derived from Landsat TM data. Total deforested area increased from 206 x 103 ha in 1977, to 565 x 103 ha in 1985 and to 1210 x 103 ha, or 35.5% of the region, in 1995. Eighty-one per cent of the total 1995 deforestation had occurred in regions within 12.5km from areas of pioneer colonization deforested by 1977. Deforested area exceeded 79% in regions within 12.5km from the region's first road.