Miracle-dz/UniFAR-FTUs huggingface dataset:
Ranking and combining multiple predictors without labeled data

Significance A key challenge in a broad range of decision-making and classification problems is how to rank and combine the possibly conflicting suggestions of several advisers of unknown reliability. We provide mathematical insights of striking conceptual simplicity that explain mutual relationships between independent advisers. These insights enable the design of efficient, robust, and reliable methods to rank the advisers’ performances and construct improved predictions in the absence of ground truth. Furthermore, these methods are robust to the presence of small subgroups of malicious advisers (cartels) attempting to veer the combined decisions to their interest. In a broad range of classification and decision-making problems, one is given the advice or predictions of several classifiers, of unknown reliability, over multiple questions or queries. This scenario is different from the standard supervised setting, where each classifier’s accuracy can be assessed using available labeled data, and raises two questions: Given only the predictions of several classifiers over a large set of unlabeled test data, is it possible to (i) reliably rank them and (ii) construct a metaclassifier more accurate than most classifiers in the ensemble? Here we present a spectral approach to address these questions. First, assuming conditional independence between classifiers, we show that the off-diagonal entries of their covariance matrix correspond to a rank-one matrix. Moreover, the classifiers can be ranked using the leading eigenvector of this covariance matrix, because its entries are proportional to their balanced accuracies. Second, via a linear approximation to the maximum likelihood estimator, we derive the Spectral Meta-Learner (SML), an unsupervised ensemble classifier whose weights are equal to these eigenvector entries. On both simulated and real data, SML typically achieves a higher accuracy than most classifiers in the ensemble and can provide a better starting point than majority voting for estimating the maximum likelihood solution. Furthermore, SML is robust to the presence of small malicious groups of classifiers designed to veer the ensemble prediction away from the (unknown) ground truth.
Journal of Reproduction and Development

Heat stress (HS) negatively affects reproduction in cattle; however, its effect on endocrine function in bovine endometrial cells remains unclear. In this study, we examined the effects of HS on the production of prostaglandin (PG) E2 and PGF2α in the cultured bovine endometrial epithelial and stromal cells separately. To evaluate the effect of HS on endocrine function, the cells were cultured at 38.5°C (control) or 40.5°C (HS). After treatment, PGE2 and PGF2α levels were measured via enzyme immunoassay (EIA) and mRNA expressions of enzymes involved in PG synthesis were examined via quantitative reverse transcription polymerase chain reaction (RT-PCR). HS did not influence the production of PGE2 or PGF2α in the epithelial cells; however, HS significantly enhanced the production of both PGE2 and PGF2α in the stromal cells (P < 0.05). In addition, HS significantly increased phospholipase A2 (PLA2), cyclooxygenase 2 (COX2), prostaglandin F synthase (PGFS), prostaglandin E synthase (PGES), and carbonyl reductase 1 (CBR1) mRNA expression in the stromal cells (P < 0.05). The overall results suggest that HS induces mRNA expression of enzymes involved in PG synthesis, resulting in the upregulation of PGE2 and PGF2α production in the stromal cells, but not in the epithelial cells. The HS-induced increase of PGE2 and PGF2α secretion in bovine endometrial stromal cells may disrupt the normal estrous cycle and cause infertility in cows during summer.
Extracellular Signal-Regulated Kinase Regulates RhoA Activation and Tumor Cell Plasticity by Inhibiting Guanine Exchange Factor H1 Activity

ABSTRACT In certain Ras mutant cell lines, the inhibition of extracellular signal-regulated kinase (ERK) signaling increases RhoA activity and inhibits cell motility, which was attributed to a decrease in Fra-1 levels. Here we report a Fra-1-independent augmentation of RhoA signaling during short-term inhibition of ERK signaling. Using mass spectrometry-based proteomics, we identified guanine exchange factor H1 (GEF-H1) as mediating this effect. ERK binds to the Rho exchange factor GEF-H1 and phosphorylates it on S959, causing inhibition of GEF-H1 activity and a consequent decrease in RhoA activity. Knockdown experiments and expression of a nonphosphorylatable S959A GEF-H1 mutant showed that this site is crucial in regulating cell motility and invasiveness. Thus, we identified GEF-H1 as a critical ERK effector that regulates motility, cell morphology, and invasiveness.
Brief Screening Tools for Long-Term Sickness Absence Due to Mental Disorders in Public Servants

BACKGROUND: Mental disorders are often a cause of long-term sickness absence (LTSA). Kessler 6 (K6) and the Brief Job Stress Questionnaire (BJSQ) are short mental health assessment questionnaires and widely used for assessing mental health in the workplace. OBJECTIVE: The purpose of this study is to evaluate the screening performance of these tools for the prediction of LTSA due to mental disorders (LTSA-MD). METHODS: K6 and BJSQ were administered to 19,321 public servants, of whom 131 took LTSA-MD during the study period. A receiver operating characteristic curve was drawn to estimate the area under the curve (AUC), sensitivity, and specificity with optimal cut-off points for K6 and four BJSQ subscales (Job Stressors; Stress Responses; Social Support; and Job Stressors + Social Support). RESULTS: K6 showed the highest AUC, and K6 and the Stress Responses subscale of the BJSQ showed higher AUC and sensitivity than other BJSQ subscales. CONCLUSIONS: The psychological distress experienced at the time, i.e. K6 and the Stress Responses, was the best predictors of LTSA-MD. Using these instant effective tools will enable us to identify high-risk workers, employ suitable interventions to improve mental health at an early stage, and reduce the incidence of LTSA-MD.
Well-posedness of boundary control systems

Continuity of the input/output map for boundary control systems is shown through the system transfer function. Our approach transforms the question of continuity of the input/output map of a boundary control system into boundedness of the solution to a related elliptic problem. This is shown for a class of boundary control systems with Neumann control or Robin boundary control.
Topology, tinkering and evolution of the human transcription factor network

Patterns of protein interactions are organized around complex heterogeneous networks. Their architecture has been suggested to be of relevance in understanding the interactome and its functional organization, which pervades cellular robustness. Transcription factors are particularly relevant in this context, given their central role in gene regulation. Here we present the first topological study of the human protein–protein interacting transcription factor network built using the TRANSFAC database. We show that the network exhibits scale‐free and small‐world properties with a hierarchical and modular structure, which is built around a small number of key proteins. Most of these proteins are associated with proliferative diseases and are typically not linked to each other, thus reducing the propagation of failures through compartmentalization. Network modularity is consistent with common structural and functional features and the features are generated by two distinct evolutionary strategies: amplification and shuffling of interacting domains through tinkering and acquisition of specific interacting regions. The function of the regulatory complexes may have played an active role in choosing one of them.
Test-Based Cloud Service Certification of Opportunistic Providers

Through automatically checking whether cloud services satisfy customers' requirements, cloud service certification promises cloud providers competitive advantages, e.g. by attracting new customers. However, certification can increase costs of cloud providers, creating incentives for fraudulent providers to save costs by only pretending to satisfy customers' requirements. Opportunistic providers are fraudulent providers who will only cheat if they are not caught. In this paper, we propose an approach to support cloud service certification of opportunistic providers. To that end, we introduce a method to model the behavior of opportunistic providers and propose a framework supporting test-based certification which builds on randomized testing and is non-invasive. We show how our framework reduces the willingness of opportunistic providers to cheat, and present experimental results of tests supporting the certification of requirements related to resource availability, resource provisioning, and quality of service.
Ensemble of Deep Models for Event Recognition

In this article, we address the problem of recognizing an event from a single related picture. Given the large number of event classes and the limited information contained in a single shot, the problem is known to be particularly hard. To achieve a reliable detection, we propose a combination of multiple classifiers, and we compare three alternative strategies to fuse the results of each classifier, namely: (i) induced order weighted averaging operators, (ii) genetic algorithms, and (iii) particle swarm optimization. Each method is aimed at determining the optimal weights to be assigned to the decision scores yielded by different deep models, according to the relevant optimization strategy. Experimental tests have been performed on three event recognition datasets, evaluating the performance of various deep models, both alone and selectively combined. Experimental results demonstrate that the proposed approach outperforms traditional multiple classifier solutions based on uniform weighting, and outperforms recent state-of-the-art approaches.
It's Not Where Your Data Is, It's How It Got There

Modern flash devices, which perform updates 'out of place', require different optimization strategies than hard disks. The focus for flash devices is on optimizing data movement, rather than optimizing data placement. An understanding of the processes that cause data movement within a flash drive is crucial for analyzing and managing it. While sequentiality on hard drives is easy to visualize, as is done by various defragmentation tools, data movement on flash is inherently dynamic. With the lack of suitable visualization tools, researchers and developers must rely on aggregated statistics and histograms from which the actual movement is derived. The complexity of this task increases with the complexity of state-of-the-art FTL production and research optimizations. Adding visualization to existing research and analysis tools will greatly improve our understanding of modern, complex flash-based systems. We developed SSD Player, a graphical tool for visualizing the various processes that cause data movement on SSDs. We use SSD Player to demonstrate how visualization can help us shed light on the complex phenomena that cause data movement and expose new opportunities for optimization.
Paleoclimate support for a persistent dry island effect in the Colombian Andes during the last 4700 years

We investigated middle- and late-Holocene hydroclimate patterns in the Colombian Andes using indicators of watershed erosion (lithic abundance), precipitation intensity (% silt), lake-level variability (organic carbon and nitrogen, % sand, and diatoms), and fire frequency (fossil charcoal) from a ~4700-year-long sediment archive from Laguna de Ubaque, a small sub-alpine lake on the eastern flank of the eastern Colombian Andes. Our results indicate reduced precipitation, low lake levels, and increased fire occurrence at Ubaque between 4700 and 3500 cal. yr BP (hereafter BP). Precipitation and lake levels increased abruptly while fire occurrence decreased between 3500 and 2100 BP, with the exception of a 300-year dry phase between 2800 and 2500 BP. Although wetter than the 4700–3500 BP interval, precipitation decreased, lake levels fell, and fire occurrence increased after 2100 BP, but with high-frequency variability. Comparison of the Ubaque results with other Colombian paleoclimate records (e.g. Lakes Fúquene and La Cocha) supports an antiphase pattern of precipitation between the high/interior Andes and frontal slope sites. This spatial pattern of variability is consistent with modern responses to the changes in terrestrial atmospheric convection associated with the so-called ‘dry island’ effect. Further comparison with paleoclimate records from Venezuela suggests that the millennial trend toward increasing frontal slope precipitation is consistent with orbitally induced increases in Andean atmospheric convection. Sub-orbital dry island–like hydroclimate variability suggests that other mechanisms that affect Northern Hemisphere convection may act to enhance or diminish this effect on centennial and shorter timescales.
Retention in Online Blogging: A Case Study of the Blogster Community

Community-based blogging platforms can be rich sources of information on a variety of specialized topics, from finance to parenting. The usefulness of such platforms depends heavily on user participation and contribution. However, one potential problem is lower retention: users' fail to contribute in the long run. This paper is an investigation of retention in the popular community blogging platform “Blogster. ” We use the points users earn for their activities as a proxy of retention and explore the attributes that are associated with their retention. We find that highly retained users are most central in the network and their blogger friends are mutually less connected. They get more views and comments to their posted blogs. We also examine the homophily of retention in the social network. Based on our empirical observations, we build a classifier that is able to detect top retained users with accuracy as high as 94%. Our work has theoretical implications for the social behavior literature of community bloggers and practical design implications for potential community blogging platform developers.
Modeling the MJO in a cloud‐resolving model with parameterized large‐scale dynamics: Vertical structure, radiation, and horizontal advection of dry air

Two Madden‐Julian Oscillation (MJO) events, observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign, are simulated in a limited‐area cloud‐resolving model using parameterized large‐scale dynamics. Three parameterizations of large‐scale dynamics—the conventional weak temperature gradient (WTG) approximation, vertical mode‐based spectral WTG (SWTG), and damped gravity wave coupling (DGW)—are employed. A number of changes to the implementation of the large‐scale parameterizations, as well as the model itself, are made and lead to improvements in the results. Simulations using all three methods, with imposed time‐dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large‐scale vertical motion profile, however. WTG produces the most top‐heavy profile, while DGW's is less so, and SWTG produces a profile between the two, and in better agreement with observations. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top‐heaviness of large‐scale vertical motion during the MJO active phases. Experiments in which a temporally constant radiative heating profile is used indicate that radiative feedbacks significantly amplify the MJO. Experiments in which interactive radiation is used produce agreement with observations that is much better than that achieved in previous work, though not as good as that with imposed time‐varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and radiative feedbacks to the dynamics of the MJO.
Frontotemporal dementia with amyotrophic lateral sclerosis: A clinical comparison of patients with and without repeat expansions in C9orf72

Abstract Repeat expansions in C9orf72 are a major cause of frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS). Not all FTD-ALS patients show expansions. The study examined whether there are clinical differences between FTD-ALS patients with and without expansions in C9orf72. We examined case notes from consecutive FTD-ALS patients, screened for C9orf72 expansions, and documented demographic, neurological, behavioural and cognitive characteristics. Sixty patients met the selection criteria, of whom 11 showed expanded repeats (C9-positive) and 49 did not (C9-negative). A strong male bias was present in the C9-negative group only. A family history of FTD or ALS was recorded in both groups, but was significantly more common in C9-positive cases. Psychotic and irrational behaviours, apathy, disinhibition and loss of empathy were significantly more common in C9-positive cases, with a trend towards more frequent bulbar signs. No differences were found in onset age, presentation (ALS or FTD first), or cognitive changes (language and executive impairments). In conclusion, FTD-ALS is not clinically uniform. Phenotypic differences exist between patients with and without C9orf72 expansions, suggesting that FTD-ALS may be underpinned by distinct neurobiological substrates. The presence of psychiatric symptoms in the context of FTD-ALS should alert clinicians to the possibility of C9orf72 expansions.
The Q-Theory Approach to Understanding the Accrual Anomaly

ABSTRACT Interpreting accruals as working capital investment, we hypothesize based on "q"-theory that firms optimally adjust their accruals in response to discount rate changes. A higher discount rate means less profitable investments and lower accruals, and a lower discount rate means more profitable investments and higher accruals. Our evidence supports this optimal investment hypothesis: (1) adding an investment factor into standard factor regressions substantially reduces the magnitude of the accrual anomaly, often to insignificant levels; (2) accruals covary negatively with discount rate estimates from the dividend discounting model, and for the most part, with estimates from the residual income model; (3) accruals with low accounting reliability covary more with capital investment than accruals with high accounting reliability; and (iv) expected returns to accruals-based trading strategies are time-varying, suggesting that the deterioration of the accrual effect in recent years might be temporary and likely to mean-revert in the near future. Copyright (c), University of Chicago on behalf of the Accounting Research Center, 2009.
PI-3K Inhibitors Preferentially Target CD15+ Cancer Stem Cell Population in SHH Driven Medulloblastoma

Sonic hedgehog (SHH) medulloblastoma (MB) subtype is driven by a proliferative CD15+ tumor propagating cell (TPC), also considered in the literature as a putative cancer stem cell (CSC). Despite considerable research, much of the biology of this TPC remains unknown. We report evidence that phosphatase and tensin homolog (PTEN) and phosphoinositide 3-kinase (PI-3K) play a crucial role in the propagation, survival and potential response to therapy in this CD15+ CSC/TPC-driven malignant disease. Using the ND2-SmoA1 transgenic mouse model for MB, mouse genetics and patient-derived xenografts (PDXs), we demonstrate that the CD15+TPCs are 1) obligately required for SmoA1Tg-driven tumorigenicity 2) regulated by PTEN and PI-3K signaling 3) selectively sensitive to the cytotoxic effects of pan PI-3K inhibitors in vitro and in vivo but resistant to chemotherapy 4) in the SmoA1Tg mouse model are genomically similar to the SHH human MB subgroup. The results provide the first evidence that PTEN plays a role in MB TPC signaling and biology and that PI-3K inhibitors target and suppress the survival and proliferation of cells within the mouse and human CD15+ cancer stem cell compartment. In contrast, CD15+ TPCs are resistant to cisplatinum, temozolomide and the SHH inhibitor, NVP-LDE-225, agents currently used in treatment of medulloblastoma. These studies validate the therapeutic efficacy of pan PI-3K inhibitors in the treatment of CD15+ TPC dependent medulloblastoma and suggest a sequential combination of PI-3K inhibitors and chemotherapy will have augmented efficacy in the treatment of this disease.
B cell depletion in autoimmune diabetes: insights from murine models

Introduction: The incidence of type 1 diabetes (T1D) is rising for reasons that largely elude us. New strategies aimed at halting the disease process are needed. One type of immune cell thought to contribute to T1D is the B lymphocyte. The first Phase II trial of B cell depletion in new onset T1D patients indicated that this slowed the destruction of insulin-producing pancreatic beta cells. The mechanistic basis of the beneficial effects remains unclear. Areas covered: Studies of B cell depletion and deficiency in animal models of T1D. How B cells can influence T cell-dependent autoimmune diabetes in animal models. The heterogeneity of B cell populations and current evidence for the potential contribution of specific B cell subsets to diabetes, with emphasis on marginal zone B cells and B1 B cells. Expert opinion: B cells can influence the T cell response to islet antigens and B cell depletion or genetic deficiency is associated with decreased insulitis in animal models. New evidence suggests that B1 cells may contribute to diabetes pathogenesis. A better understanding of the roles of individual B cell subsets in disease will permit fine-tuning of therapeutic strategies to modify these populations.