Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Shared Molecular Signatures Indicate the Susceptibility of Endometriosis to Multiple Sclerosis

Women with endometriosis (EMS) appear to be at a higher risk of developing other autoimmune diseases predominantly multiple sclerosis (MS). Though EMS and MS are evidently diverse in their phenotype, they are linked by a common autoimmune condition or immunodeficiency which could play a role in the expansion of endometriosis and possibly increase the risk of developing MS in women with EMS. However, the common molecular links connecting EMS with MS are still unclear. We conducted a meta-analysis of microarray experiments focused on EMS and MS with their respective controls. The GEO2R web application discovered a total of 711 and 1516 genes that are differentially expressed across the experimental conditions in EMS and MS, respectively with 129 shared DEGs between them. The functional enrichment analysis of DEGs predicts the shared gene expression signatures as well as the overlapping biological processes likely to infer the co-occurrence of EMS with MS. Network based meta-analysis unveiled six interaction networks/crosstalks through overlapping edges between commonly dysregulated pathways of EMS and MS. The PTPN1, ERBB3, and CDH1 were observed to be the highly ranked hub genes connected with disease-related genes of both EMS and MS. Androgen receptor (AR) and nuclear factor-kB p65 (RelA) were observed to be the most enriched transcription factor in the upstream of shared down-regulated and up-regulated genes, respectively. The two disease sample sets compared through crosstalk interactions between shared pathways revealed commonly up- and down-regulated expressions of 10 immunomodulatory proteins as probable linkers between EMS and MS. This study pinpoints the number of shared genes, pathways, protein kinases, and upstream regulators that may help in the development of biomarkers for diagnosis of MS and endometriosis at the same time through improved understanding of shared molecular signatures and crosstalk.
Between-Class Learning for Image Classification

In this paper, we propose a novel learning method for image classification called Between-Class learning (BC learning)1. We generate between-class images by mixing two images belonging to different classes with a random ratio. We then input the mixed image to the model and train the model to output the mixing ratio. BC learning has the ability to impose constraints on the shape of the feature distributions, and thus the generalization ability is improved. BC learning is originally a method developed for sounds, which can be digitally mixed. Mixing two image data does not appear to make sense; however, we argue that because convolutional neural networks have an aspect of treating input data as waveforms, what works on sounds must also work on images. First, we propose a simple mixing method using internal divisions, which surprisingly proves to significantly improve performance. Second, we propose a mixing method that treats the images as waveforms, which leads to a further improvement in performance. As a result, we achieved 19.4% and 2.26% top-1 errors on ImageNet-1K and CIFAR-10, respectively.2
Immune Clearance of Attenuated Rabies Virus Results in Neuronal Survival with Altered Gene Expression

Rabies virus (RABV) is a highly neurotropic pathogen that typically leads to mortality of infected animals and humans. The precise etiology of rabies neuropathogenesis is unknown, though it is hypothesized to be due either to neuronal death or dysfunction. Analysis of human brains post-mortem reveals surprisingly little tissue damage and neuropathology considering the dramatic clinical symptomology, supporting the neuronal dysfunction model. However, whether or not neurons survive infection and clearance and, provided they do, whether they are functionally restored to their pre-infection phenotype has not been determined in vivo for RABV, or any neurotropic virus. This is due, in part, to the absence of a permanent “mark” on once-infected cells that allow their identification long after viral clearance. Our approach to study the survival and integrity of RABV-infected neurons was to infect Cre reporter mice with recombinant RABV expressing Cre-recombinase (RABV-Cre) to switch neurons constitutively expressing tdTomato (red) to expression of a Cre-inducible EGFP (green), permanently marking neurons that had been infected in vivo. We used fluorescence microscopy and quantitative real-time PCR to measure the survival of neurons after viral clearance; we found that the vast majority of RABV-infected neurons survive both infection and immunological clearance. We were able to isolate these previously infected neurons by flow cytometry and assay their gene expression profiles compared to uninfected cells. We observed transcriptional changes in these “cured” neurons, predictive of decreased neurite growth and dysregulated microtubule dynamics. This suggests that viral clearance, though allowing for survival of neurons, may not restore them to their pre-infection functionality. Our data provide a proof-of-principle foundation to re-evaluate the etiology of human central nervous system diseases of unknown etiology: viruses may trigger permanent neuronal damage that can persist or progress in the absence of sustained viral antigen.
Concomitant Loss of the Glyoxalase System and Glycolysis Makes the Uncultured Pathogen “Candidatus Liberibacter asiaticus” an Energy Scavenger

ABSTRACT Methylglyoxal (MG) is a cytotoxic, nonenzymatic by-product of glycolysis that readily glycates proteins and DNA, resulting in carbonyl stress. Glyoxalase I and II (GloA and GloB) sequentially convert MG into d-lactic acid using glutathione (GSH) as a cofactor. The glyoxalase system is essential for the mitigation of MG-induced carbonyl stress, preventing subsequent cell death, and recycling GSH for maintenance of cellular redox poise. All pathogenic liberibacters identified to date are uncultured, including “Candidatus Liberibacter asiaticus,” a psyllid endosymbiont and causal agent of the severely damaging citrus disease “huanglongbing. ” In silico analysis revealed the absence of gloA in “Ca. Liberibacter asiaticus” and all other pathogenic liberibacters. Both gloA and gloB are present in Liberibacter crescens, the only liberibacter that has been cultured. L. crescens GloA was functional in a heterologous host. Marker interruption of gloA in L. crescens appeared to be lethal. Key glycolytic enzymes were either missing or significantly downregulated in “Ca. Liberibacter asiaticus” compared to (cultured) L. crescens. Marker interruption of sut, a sucrose transporter gene in L. crescens, decreased its ability to take up exogenously supplied sucrose in culture. “Ca. Liberibacter asiaticus” lacks a homologous sugar transporter but has a functional ATP/ADP translocase, enabling it to thrive both in psyllids and in the sugar-rich citrus phloem by (i) avoiding sucrose uptake, (ii) avoiding MG generation via glycolysis, and (iii) directly importing ATP from the host cell. MG detoxification enzymes appear to be predictive of “Candidatus” status for many uncultured pathogenic and environmental bacteria. IMPORTANCE Discovered more than 100 years ago, the glyoxalase system is thought to be present across all domains of life and fundamental to cellular growth and viability. The glyoxalase system protects against carbonyl stress caused by methylglyoxal (MG), a highly reactive, mutagenic and cytotoxic compound that is nonenzymatically formed as a by-product of glycolysis. The uncultured alphaproteobacterium “Ca. Liberibacter asiaticus” is a well-adapted endosymbiont of the Asian citrus psyllid, which transmits the severely damaging citrus disease “huanglongbing. ” “Ca. Liberibacter asiaticus” lacks a functional glyoxalase pathway. We report here that the bacterium is able to thrive both in psyllids and in the sugar-rich citrus phloem by (i) avoiding sucrose uptake, (ii) avoiding (significant) MG generation via glycolysis, and (iii) directly importing ATP from the host cell. We hypothesize that failure to culture “Ca. Liberibacter asiaticus” is at least partly due to its dependence on host cells for both ATP and MG detoxification.
Some mathematical challenges in materials science

Four challenges to mathematics research posed by the field of materials science are given, plus an additional challenge purely from the field of geometric measure theory. The problems all concern the effects of surface and grain boundary free energy: motion by weighted mean curvature and/or surface diffusion and/or other kinetics, proofs of minimality of soap bubble clusters and their anisotropic analogs, shapes of crystals in a gravitational or other field, incorporating data from simulations into mathematics, and understanding flat chains modulo ν. The figures are selected copies of transparencies presented at the lecture on which this paper is based. Materials science is both much older and much younger than mathematics. Ancient humans discovered various elemental metals, like gold and copper. At some point, they discovered that if you mix a little tin into copper, you get something quite different from either, namely bronze. There is a period of human history labeled the Bronze Age; I don’t think there is any labeled the Arithmetic Age. On the other hand, the term “materials science” only came into general use within the last 30 years or so, as the subjects of metallurgy, ceramics, and polymers were collected into one discipline. The Materials Research Society was founded in 1973, and the International Congress of Materials Research Societies in 1991. And along with the old problems of making better structural materials such as steel came new issues unimaginable a century ago. Some of these include the ability to see and manipulate individual atoms with an atomic force microscope, the study of carbon nanotubes, the fabrication of electronic chips, and the making of thin films for CD’s and other storage media. What are mathematicians doing in such a field? First of all, as Rodney Nichols said at the New York Academy of Sciences on June 5, 2000, “Much more than a few decades ago, there are mathematicians everywhere – and that is for the good. ” Secondly, there has been an effort by the National Science Foundation to encourage this interdisciplinary research. A search of the NSF database under the Division of Mathematical Sciences, performed in the year 2000, revealed 85 grants since January 1, 1997 with the words “materials science” in their abstracts. There have been several multi-million-dollar awards, co-sponsored by DARPA, for such cooperative efforts targeted at specific problems. Part of the result is that the collection of mathematicians working on problems from materials science has grown from isolated individuals prior to the mid-1980’s, to a small community, and now Received by the editors November 6, 2000, and, in revised form, February 21, 2002. 2000 Mathematics Subject Classification. Primary 74N20; Secondary 49Q20, 49Q15, 35R99,
Understanding Human Development: Dialogues With Lifespan Psychology

Foreword K. Warner Schaie. Acknowledgments. List of Contributors. 1. Why Read Another Book on Human Development? Understanding Human Development Takes a Meta-theory and Multiple Disciplines U.M. Staudinger, U. Lindenberger. I: The Overall Architecture of Lifespan Development. 2. On the Incomplete Architecture of Human Ontogeny: Selection, Optimization and Compensation as Foundation of Developments/Theory reprint P.B. Baltes. 3. Age Differences in Evolutionary Selection Benefits B. Thomas, L. Kirkwood. 4. Age Differences in Longevity in Cultural Efficiency: Secular Trends H. Maier, J.W. Vaupel. II: Basic Processes of Lifespan Development: Selective Optimization with Compensation (SOC). 5. The Process of Successful Aging: Selection, Optimization, and Compensation M.M. Baltes, L.L. Carstensen. 6. Intentionality and Time in Human Development and Aging: Compensation and Goal Adjustment in Changing Developmental Contexts J. Brandtstadter, K. Rothermund. 7. An Economic Perspective on Selection, Optimization, and Compensation (SOC) as Elements in the Conceptualization and Understanding of Lifespan Human Development Processes J.R. Behrman. III: A Lifespan View of Self and Personality. 8. Completing the Psychobiological Architecture of Human Personality Development: Temperament, Character, and Coherence C.R. Cloninger. 9. The Cumulative Continuity Model of Personality Development: Striking a Balance Between Continuity and Change in Personality Traits Across the Life Course B.W. Roberts, A. Caspi. 10. The Gain-Loss Dynamic in Lifespan Development:Implications for Change in Self and Personality During Old and Very Old Age J. Smith. IV: A Lifespan View of Intelligence and Cognition. 11. Enablement and Constraint H.M. Wellman. 12. Interrelations of Aging, Knowledge, and Cognitive Performance T.A. Salthouse. 13. Formal Models of Age Differences in Task-Complexity Effects R. Kliegl, et al. V: At the Frontiers of Lifespan Methodology. 14. Structuring and Measuring Change over the Lifespan J.R. Nesselroade, P. Ghisletta. 15. The Relationship Between the Structure of Interindividual and Intraindividual Variability: A Theoretical and Empirical Vindication of Developmental Systems Theory P.C. M. Molenaar, et al. 16. Combining Molecular and Quantitative Genetics: Decomposing the Architecture of Lifespan Development G.E. McClearn. VI: The Future of Lifespan Psychology: Comments from Related Fields and Neighboring Disciplines. 17. The Future of Lifespan Developmental Psychology: Perspectives from Control Theory J. Heckhausen. 18. Without Gender, Without Self G. Labouvie-Vief. 19. Contributions of Lifespan Psychology to the Future Elaboration of Developmental Systems Theory R.M. Lerner, et al. 20. The Adaptive Toolbox and Lifespan Development: Common Questions? G. Gigerenzer. 21. The Nature-Nurture Problem Revisited W. Singer. 22. Development in Adolescence Under the Restriction of Secondary School O. Koller, et al. 23. The Sociology of the Life Course and Lifespan Psychology: Diverging or Converging Pathways? K.U. Mayer. 24.
DIABETIC STUDIES The Review of Chapter I . 6 Novel Biomarkers in Type 1 Diabetes

Biomarkers are useful tools for research into type 1 diabetes (T1D) for a number of purposes, including elucidation of disease pathogenesis, risk prediction, and therapeutic monitoring. Susceptibility genes and islet autoantibodies are currently the most useful biomarkers for T1D risk prediction. However, these markers do not fully meet the needs of scientists and physicians for several reasons. First, improvement of the specificity and sensitivity is still desirable to achieve better positive predictive values. Second, autoantibodies appear relatively late in the disease process, thus limiting their value in early disease prediction. Third, the currently available biomarkers are not useful for assessing therapeutic outcomes because some are not involved in the disease process (autoantibodies) and others do not change during disease progression (susceptibility genes). Therefore, considerable effort has been devoted to the discovery of novel T1D biomarkers in the last three decades. The advent of high-throughput technologies for genetic, transcriptomic, and proteomic studies has allowed genome-wide examinations of genetic polymorphisms, global gene changes, and protein expression changes in T1D patients and prediabetic subjects. These large-scale studies resulted in the discovery of a large number of susceptibility genes and changes in gene and protein expression. While these studies have provided a number of novel biomarker candidates, their clinical benefits remain to be evaluated in prospective studies, and no new “star biomarker” has been identified until now. Previous studies suggest that significant improvements in study design and analytical methodologies have to be made to identify clinically relevant biomarkers. In this review, we discuss progress, opportunities, challenges, and future directions in the development of T1D biomarkers, mainly by focusing on the genetic, transcriptomic, and proteomic aspects.
Distributed modelling of shallow landslides triggered by intense rainfall

Abstract. Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use). For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997) that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy). In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.
Unknown Attacks Detection Using Feature Extraction from Anomaly-Based IDS Alerts

Intrusion Detection Systems (IDSs) play an important role detecting various kinds of attacks and defend our computer systems from them. There are basically two main types of detection techniques: signature-based and anomaly-based. A signature-based IDS cannot detect unknown attacks because a signature has not been written. To overcome this shortcoming, many researchers have been developing anomaly-based IDSs. Although they can detect unknown attacks, there is a problem that they just classify network traffic into normal or abnormal. Therefore, IDS operators have to manually inspect IDS alerts to classify them into known attacks or unknown attacks. Because there are a lot of alerts related to known attacks, it is difficult to extract only unknown attacks from them. In this paper, we present a method that automatically detects unknown attacks from an anomaly-based IDS alerts. We evaluate our method using Kyoto2006+ dataset.
Tomato Analyzer-color Test: A New Tool for Efficient Digital Phenotyping

Measuring plant characteristics via image analysis has the potential to increase the objectivity of phenotypic evaluations, provides data amenable to quantitative analysis, and is compatible with databases that aim to combine phenotypic and genotypic data. We describe a new tool, which is implemented in the Tomato Analyzer (TA) software application, called Color Test (TACT). This tool allows for accurate quantification of color and color uniformity, and allows scanning devices to be calibrated using color standards. To test the accuracy and precision of TACT, we measured internal fruit color of tomato (Solanum lycopersicum L.) with a colorimeter and from scanned images. We show high correlations (r > 0.96) and linearity of L*, a*, and b* values obtained with TACT and the colorimeter. We estimatedgenotypic variancesassociated withcolorparameters and show thatthe proportion oftotal phenotypic variance attributed to genotype for color and color uniformity measured with TACT was significantly higher than estimates obtained from the colorimeter. Genotypic variance nearly doubled for all color and color uniformity traits when collecting data with TACT. This digital phenotyping technique can also be applied to the characterization of color in other fruit and vegetable crops. Digital phenotyping aims to accurately describe a trait based on analysis of electronic images. Computer-based analysis of objects from digital images has the potential to increase the objectivity of data collection while reducing subjective char- acterization that is typically prone to bias. There are a number of computer image acquisition and analysis techniques for color in foods such as apple (Malus ·domestica Borkh (Leemans
Statistical Tests of Rival Monetary Rules

University of Minnesota T HIS essay compares statistically the performance since 1900 of four rival monetary rules in the American economy. These rules are: 1. The "judgment" rule, according to which the monetary authority or authorities meet each situation as it arises to the best of its (their) own judgment(s). Discretion is subject to fixed rules only within very broad limits. In the American case, there is the further complication of a plural "monetary authority. " Responsibility in monetary matters is divided among the Federal Reserve system, the United States Treasury, fiftyone commercial banking systems, and various other lending and regulatory agencies, public and private. 2. The "inflexible" rule, according to which the money supply, somehow de-
Reform the power : an institutional analysis of power sector reforms in Pakistan

Pakistan’s electricity sector is underperforming. It is inadequate, inefficient and unreliable. There is capacity shortage, high transmission and distribution (T&D) losses, inefficient pricing structures, costly and ineffective subsidies, circular debts and an inefficient resource mix in generation. These problems cause many and hours long system blackouts during day and night in Pakistan, thus inflicting impasse on daily life. These problems already existed before the 1990s, the period that Pakistan reformed its power sector with the intention to solve these problems. But the problems weren’t solved by the institutional reforms. Therefore, we assumed in this study that the continuation of the poor functioning of Pakistan’s power sector is caused by poor and incomplete design of the institutional reform of the power sector and by the pace of implementation of the reforms. So, inspired by New Institutional Economics, this dissertation analyses the institutional causes of the problems to find an answer to the question why the institutional reforms of the Pakistan power sector did not result in the expected improvement of the organization and functioning of electricity supply in Pakistan. The study utilizes a mixture of quantitative and qualitative methods to answer the overarching and its connected research questions. The analysis is based on a theoretical framework crafted from the work of Douglass North and Oliver Williamson (Nobel Laureates in Economics). The study holds that institutional barriers remained important in restraining the electricity reforms reducing the severity of the pre-reform problems of the power sector of Pakistan. This has contributed to the continuation of the pre-reform problems until recently. This requires re- designing the power sector reforms in coherence with the institutional endowments of the country.
Exploring Topological Environments

This report reviews current research trends related to the problem of robotic exploration and mapping. In exploring and mapping an unknown environment, one fundamental problem is answering the question ‘have I been here before? ’ (This is also known as the ‘loop closing’ problem.) Answering this question involves disambiguating the current place of the robot against previously visited or known locations. Two fundamental approaches to solving the problem are reviewed. The first approach resorts to the use of an ‘oracle’ to help solve the disambiguation problem. Oracles are available with different disambiguating powers, and the relative strengths of different oracles are explored. The second approach exploits augmenting locations with metric information that describes the underlying environment. Open questions are discussed.