Machine Learning Methods for Attack Detection in the Smart Grid

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semi-supervised) are employed with decision and feature level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than the attack detection algorithms which employ state vector estimation methods in the proposed attack detection framework.Comment: 14 pages, 11 Figure

New Singular and Nonsingular Colliding Wave Solutions in Einstein - Maxwell - Scalar Theory

A technique is given to generate coupled scalar field solutions in colliding Einstein - Maxwell (EM) waves. By employing the Bell - Szekeres solution as seed and depending on the chosen scalar field it is possible to construct nonsingular solutions. If the original EM solution is already singular addition of scalar fields does not make the physics any better. In particular, scalar field solution that is transformable to spherical symmetry is plagued with singularities.Comment: 15 pages, To be published in GR

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Immigration represents a promising counter-narrative for Rust Belt cities in the 21st century. Increasingly, both immigrants and refugees are part of the comeback stories of Northeastern and Midwestern cities from Buffalo, to Dayton and Pittsburgh. This review explores recent research in urban geography and allied disciplines focusing on the international migration patterns, processes, and politics reshaping the urban geography of the American Rust Belt. Recent research sheds crucial light on how im/migrant lives are reshaping urban landscapes of Rust Belt cities, and conversely, how local immigration policies in these cities are rearranging the uneven geographies of immigrant receptivity across the U.S. Overall, this review highlights the limitations of the singular spatial imaginary of the Rust Belt advanced previously by many urbanists. Rather, this review illustrates the rich, complex, and tangled contemporary spatial nuances associated with international migration in this region. These spatial nuances are complicated by increasingly exclusionary immigration policy and rhetoric at the federal level since January of 2017

Inositols: From established knowledge to novel approaches

Myo-inositol (myo-Ins) and D-chiro-inositol (D-chiro-Ins) are natural compounds involved in many biological pathways. Since the discovery of their involvement in endocrine signal transduction, myo-Ins and D-chiro-Ins supplementation has contributed to clinical approaches in ameliorating many gynecological and endocrinological diseases. Currently both myo-Ins and D-chiro-Ins are well-tolerated, effective alternative candidates to the classical insulin sensitizers, and are useful treatments in preventing and treating metabolic and reproductive disorders such as polycystic ovary syndrome (PCOS), gestational diabetes mellitus (GDM), and male fertility disturbances, like sperm abnormalities. Moreover, besides metabolic activity, myo-Ins and D-chiro-Ins deeply influence steroidogenesis, regulating the pools of androgens and estrogens, likely in opposite ways. Given the complexity of inositol-related mechanisms of action, many of their beneficial effects are still under scrutiny. Therefore, continuing research aims to discover new emerging roles and mechanisms that can allow clinicians to tailor inositol therapy and to use it in other medical areas, hitherto unexplored. The present paper outlines the established evidence on inositols and updates on recent research, namely concerning D-chiro-Ins involvement into steroidogenesis. In particular, D-chiro-Ins mediates insulin-induced testosterone biosynthesis from ovarian thecal cells and directly affects synthesis of estrogens by modulating the expression of the aromatase enzyme. Ovaries, as well as other organs and tissues, are characterized by a specific ratio of myo-Ins to D-chiro-Ins, which ensures their healthy state and proper functionality. Altered inositol ratios may account for pathological conditions, causing an imbalance in sex hormones. Such situations usually occur in association with medical conditions, such as PCOS, or as a consequence of some pharmacological treatments. Based on the physiological role of inositols and the pathological implications of altered myo-Ins to D-chiro-Ins ratios, inositol therapy may be designed with two different aims: (1) restoring the inositol physiological ratio; (2) altering the ratio in a controlled way to achieve specific effects

When one size does not fit all: Reconsidering PCOS etiology, diagnosis, clinical subgroups, and subgroup-specific treatments

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder that affects a large proportion of women. Due to its heterogeneity, the best diagnostic strategy has been a matter of contention. Since 1990 scientific societies in the field of human reproduction have tried to define the pivotal criteria for the diagnosis of PCOS. The consensus Rotterdam diagnostic criteria included the presence of hyperandrogenism, oligo/anovulation, and polycystic ovarian morphology (PCOM), and have now been updated to evidence based diagnostic criteria in the 2018 and 2023 International Guideline diagnostic criteria endorsed by 39 societies internationally. Within the Rotterdam Criteria, at least two out of three of the above-mentioned features are required to be present to diagnose PCOS, resulting in four phenotypes being identified: phenotype A, characterized by the presence of all the features, phenotype B, exhibiting hyperandrogenism and oligo-anovulation, phenotype C, presenting as hyperandrogenism and PCOM and finally the phenotype D that is characterized by oligo-anovulation and PCOM, lacking the hyperandrogenic component. However, it is the hypothesis of the EGOI group that the Rotterdam phenotypes A, B, and C have a different underlying causality to phenotype D. Recent studies have highlighted the strong correlation between insulin resistance and hyperandrogenism, and the pivotal role of these factors in driving ovarian alterations, such as oligo-anovulation and follicular functional cyst formation. This new understanding of PCOS pathogenesis has led the authors to hypothesis that phenotypes A, B, and C are endocrine-metabolic syndromes with a metabolic clinical onset. Conversely, the absence of hyperandrogenism and metabolic disturbances in phenotype D suggests a different origin of this condition, and point towards novel pathophysiological mechanisms; however, these are still not fully understood. Further questions have been raised regarding the suitability of the “phenotypes” described by the Rotterdam Criteria by the publication by recent GWAS studies, which demonstrated that these phenotypes should be considered clinical subtypes as they are not reflected in the genetic picture. Hence, by capturing the heterogeneity of this complex disorder, current diagnostic criteria may benefit from a reassessment and the evaluation of additional parameters such as insulin resistance and endometrial thickness, with the purpose of not only improving their diagnostic accuracy but also of assigning an appropriate and personalized treatment. In this framework, the present overview aims to analyze the diagnostic criteria currently recognized by the scientific community and assess the suitability of their application in clinical practice in light of the newly emerging evidence

The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis

Membranous Nephropathy (MN) is a rare autoimmune cause of kidney failure. Here we report a genome-wide association study (GWAS) for primary MN in 3,782 cases and 9,038 controls of East Asian and European ancestries. We discover two previously unreported loci, NFKB1 (rs230540, OR = 1.25, P = 3.4 × 10-12) and IRF4 (rs9405192, OR = 1.29, P = 1.4 × 10-14), fine-map the PLA2R1 locus (rs17831251, OR = 2.25, P = 4.7 × 10-103) and report ancestry-specific effects of three classical HLA alleles: DRB1*1501 in East Asians (OR = 3.81, P = 2.0 × 10-49), DQA1*0501 in Europeans (OR = 2.88, P = 5.7 × 10-93), and DRB1*0301 in both ethnicities (OR = 3.50, P = 9.2 × 10-23 and OR = 3.39, P = 5.2 × 10-82, respectively). GWAS loci explain 32% of disease risk in East Asians and 25% in Europeans, and correctly re-classify 20-37% of the cases in validation cohorts that are antibody-negative by the serum anti-PLA2R ELISA diagnostic test. Our findings highlight an unusual genetic architecture of MN, with four loci and their interactions accounting for nearly one-third of the disease risk