Evaluating Weight of Evidence in the Mystery of Balkan Endemic Nephropathy

Balkan endemic nephropathy (BEN) is a chronic, progressive wasting disease of the kidneys, endemic in certain rural regions of the Balkan nations Croatia, Serbia, Bulgaria, and Romania. It is irreversible and ultimately fatal. Though this disease was first described in the 1950s, its causes have been a mystery and a source of much academic and clinical contention. Possible etiologic agents that have been explored include exposure to metals and metalloids, viruses and bacteria, and the dietary toxins aristolochic acid (AA) and ochratoxin A (OTA). AA is a toxin produced by weeds of the genus Aristolochia, common in Balkan wheat fields. Aristolochia seeds may intermingle with harvested grains and thus inadvertently enter human diets. OTA is a mycotoxin (fungal toxin) common in many foods, including cereal grains. In this study, we analyzed the weight of evidence for each of the suspected causes of BEN using the Bradford Hill criteria (BHC): nine conditions that determine weight of evidence for a causal relationship between an agent and a disease. Each agent postulated to cause BEN was evaluated using the nine criteria, and for each criterion was given a rating based on the strength of the association between exposure to the substance and BEN. From the overall available scientific evidence for each of these suspected risk factors, AA is the agent with the greatest weight of evidence in causing BEN. We describe other methods for testing causality from epidemiological studies, which support this conclusion of AA causing BEN.     

Max Weinreich,assimilation and the social politics of Jewish nation-building

Through an analysis of the methodological and theoretical writings of Max Weinreich that were devoted to the inter-war Jewish youth research programme at the Jewish Scientific Institute (YIVO), this article discusses the ideological and political assumptions that lay behind this scientific project. Deconstructing the main research categories of the project, the author presents ways in which Weinreich and his associates constructed the Jewish nation and its place in the new inter-war political and social reality. This reality was seen in a complex manner, as a simultaneous chance for Jewish modernisation, upward mobility, productivisation, and as a response to the threat of modern state institutions that were introducing discriminatory policies, and, most importantly, assimilation. The last process was seen as the biggest danger, which could fragment and finally even dissolve the essentialist, secular and national model of Jewish community as envisioned by Max Weinreich and YIVO. The author shows how the essentialist vision of the nation omnipotent in inter-war Poland (among both Polish and Jewish communities) introduced unresolved tension between the need for social and cultural integration of the Jews, which was important for Weinreich and his circle, and the simultaneous aim of building a culturally and politically coherent Jewish nation. Further discussion shows how this kind of perception of social reality transformed a scientific research project into a kind of social intervention and nation-building programme, comparable to the ideologies of Jewish national secularist political parties. While presenting itself as a universal, national institution and addressing its call to all Jewish youth, YIVO promoted a particular political view of the Jewish nation and its tradition, history and religion. By engaging Jewish youth in a research programme devoted to its “personality,” one of the hidden aims of the project was to influence the political and social consciousness of Eastern Europe's Jewish youth.     

Amphibians in an urban environment: a case study from a central European city (Wrocław,Poland)

Urban Ecosystems - In 2016, we studied the occurrence of amphibians in 231 selected ponds in the city of Wroc?aw (Lower Silesia, Poland) and confirmed the occurrence of 10 species: Bombina...     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

“She Is Not Acting,She Is”

This essay examines the popular television show RuPaul's Drag Race to reveal the ways drag performance provides an ambivalent, contradictory space for wrestling with contentious issues surrounding cultural identity and authenticity in reality TV. Focusing on the show's controversial season three, the authors demonstrate how drag queens subvert and play with ideas of gender “realness” but find an impasse in open discussions of race. The racial minstrelsy of some contestants we observe created antagonisms between black/brown characters and their white/Asian counterparts, exposing a rift in ideas about racial play despite the general acceptance of flexibility in gender bending. Recognizing that reality TV exploits and uncovers these tensions, we demonstrate that while drag performance enacts a subversive mode of queer performance, it provides a contested site and complex semiotic space for dealing with sensitive matters of race/ethnicity, especially when certain forms of stereotyping are rewarded over others.     

Disruptions in tightly coupled supply chain networks: the case of the US offshore oil industry

Managers have paid increasing attention to the exposure of their supply chains to disruptions and seek ways to mitigate supply chain vulnerability. The interconnectedness of tightly coupled supply chain networks makes this a challenging task, because interconnectedness and tight coupling of nodes in the network lead to an amplification of the actual risk exposure. This phenomenon can be attributed to the propagation of losses through the network, which exhibits certain dynamics. In order to investigate this mechanism, we studied the complex supply chain network of the oil industry in the Gulf of Mexico. Our results provide an estimate of the economic impact of eventual random and hurricane-related disruptions and can be used as a decision support tool for risk management of supply disruptions in interconnected supply chain networks.     

Robust Inference for the Bivariate Bifurcating Autoregressive Model

Cell lineage data consist of observations on quantitative characteristics of the descendants of an initial cell, recorded as a tree so that the relationships between the cells may be determined. The bifurcating autoregressive model of Cowan & Staudte (1986) has been used previously to model univariate characteristics of cell linkage data. Here we extend this model to analyze bivariate cell data. Both maximum likelihood and robust estimators are derived for both balanced and unbalanced cell lineage trees and are applied to a real dataset to estimate the correlation between cell lifetime and final cell diameter.     

Autoregressive Model with Partial Forgetting within Rao-Blackwellized Particle Filter

The authors are concerned with Bayesian identification and prediction of a nonlinear discrete stochastic process. The fact that a nonlinear process can be approximated by a piecewise linear function advocates the use of adaptive linear models. They propose a linear regression model within Rao-Blackwellized particle filter. The parameters of the linear model are adaptively estimated using a finite mixture, where the weights of components are tuned with a particle filter. The mixture reflects a priori given hypotheses on different scenarios of (expected) parameters' evolution. The resulting hybrid filter locally optimizes the weights to achieve the best fit of a nonlinear signal with a single linear model.