Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute rapamycin nephrotoxicity in native kidneys of patients with chronic glomerulopathies.

BACKGROUND Based on its success as a transplant immunosuppressor, there is intense interest in using rapamycin in the treatment of progressive glomerulopathies involving native kidneys. However, we call attention to the potential toxicity associated with the use of rapamycin in this setting. METHODS We conducted a study to examine the efficacy and safety of rapamycin in patients with progressive chronic renal failure. Eleven patients with either focal segmental glomerulosclerosis, immunoglobulin A nephropathy, membranous nephropathy or membrano-proliferative glomerulonephritis and progressive renal failure (defined as an increase in >25% of baseline serum creatinine over the last year or loss of glomerular filtration rate > or =5 ml/min/year as determined by the Cockcroft-Gault formula), proteinuria > or =1.0 g/24 h and with a creatinine clearance of > or 20 ml/min/1.73 m(2) were entered into a 12 month study. Patients were treated with rapamycin, starting at 5 mg/day, orally, aiming for target blood levels of 7-10 ng/dl. All patients were on treatment with an angiotensin-converting enzyme inhibitor and/or an angiotensin receptor blocker, aiming to control blood pressure < or =145/90 mmHg. RESULTS Six patients developed acute renal failure, defined as an increase in serum creatinine > or =0.5 mg/dl (baseline: 3.2+/-0.9 mg/dl; peak: 5.6+/-1.6 mg/dl; P<0.01, paired t-test). In four patients, discontinuation of the drug resulted in improvement of renal function close to baseline levels. One patient required haemodialysis and had no subsequent recovery of renal function. In another patient, renal function recovered after discontinuation of the drug and then rapamycin was resumed at a lower dose when creatinine returned to baseline. This resulted in a second acute increase in serum creatinine that failed to return to baseline when the medication was discontinued. Four other patients had the following adverse events: skin rash, severe hypertriglyceridaemia, diarrhoea and hyperkalaemia. In none of the subjects were rapamycin levels >15 ng/dl. CONCLUSIONS Rapamycin can cause nephrotoxicity in some patients with chronic glomerulopathies. Whether the toxicity is solely related to rapamycin, due to the combination of proteinuria and rapamycin, or other unknown factor use is presently undetermined.
Learning the unified kernel machines for classification

Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel Machines (UKM) from both labeled and unlabeled data. Our proposed framework integrates supervised learning, semi-supervised kernel learning, and active learning in a unified solution. In the suggested framework, we particularly focus our attention on designing a new semi-supervised kernel learning method, i.e., Spectral Kernel Learning (SKL), which is built on the principles of kernel target alignment and unsupervised kernel design. Our algorithm is related to an equivalent quadratic programming problem that can be efficiently solved. Empirical results have shown that our method is more effective and robust to learn the semi-supervised kernels than traditional approaches. Based on the framework, we present a specific paradigm of unified kernel machines with respect to Kernel Logistic Regresions (KLR), i.e., Unified Kernel Logistic Regression (UKLR). We evaluate our proposed UKLR classification scheme in comparison with traditional solutions. The promising results show that our proposed UKLR paradigm is more effective than the traditional classification approaches.
The Effect of Common-Mode Voltage Elimination on the Iron Loss in Machine Core Laminations of Multilevel Drives

This paper studies the effect of common-mode voltage elimination (CMVE) on the iron loss of electrical machine core laminations under multilevel converter supply. Three identical magnetic ring cores are excited by either a three-level converter or a five-level voltage source converter to study the behavior of CMVE on a three-phase system. Both multilevel converters are controlled by using a space vector pulsewidth modulation as it is one of the most often used techniques for CMVE. These experimental results are confirmed numerically with a dynamic iron loss model. In addition, the effect of CMVE, at different switching frequencies, on the core loss of a synchronous machine is numerically studied. The results presented in this paper show that the core loss is considerably increased when the CMVE is implemented. However, this iron loss increase in the five-level drive systems is lower compared with the three-level ones. Therefore, it is important that the designers of drive systems take such effects into consideration.
Approaching Textual Entailment with LFG and FrameNet Frames

We present a baseline system for modeling textual entailment that combines deep syntactic analysis with structured lexical meaning descriptions in the FrameNet paradigm. Textual entailment is approximated by degrees of structural and semantic overlap of text and hypothesis, which we measure in a match graph. The encoded measures of similarity are processed in a machine learning setting.1
Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here.
NMDA‐receptor‐mediated sensory responses of brain noradrenergic neurons are suppressed by in vivo concentrations of extracellular magnesium

Recent studies reveal at least three receptor subtypes for excitatory amino acid (EAA) neurotransmitters. Activation of one of these, the N‐methyl‐D‐aspartate (NMDA) receptor‐channel complex, has been strongly implicated in neuronal mechanisms of several important brain processes, including learning and memory. As NMDA receptors are highly sensitive to extracellular magnesium (Mg++), we tested whether in vivo concentrations of this ion are sufficient to suppress NMDA‐receptor‐mediated responses. We show that slow, local microinfusion of Mg++‐free artificial cerebrospinal fluid onto noradrenergic locus coeruleus (LC) neurons reveals an NMDA‐receptor‐mediated component of their response to a sensory stimulus. This is the first demonstration that the in vivo concentration of extracellular Mg++ ions suppresses synaptically mediated NMDA receptor activation. We also present evidence that unmasking this NMDA receptor activity induces prolonged enhancement of the EAA‐mediated sensory response of LC neurons.
Chinese medical herbs for chemotherapy side effects in colorectal cancer patients.

BACKGROUND Side effects, including nausea and vomiting, sore mouth , diarrhoea, hepatotoxicity, myelosuppression, and immunosuppression , are commonly encountered in patients with colorectal cancer who are treated with chemotherapy. A variety of Chinese herbal medicines have been used for managing these adverse effects. OBJECTIVES To assess the effect of herbal medicines plus chemotherapy, compared with chemotherapy alone, on the side effects of chemotherapy on the quality of life, and on adverse events in patients with colorectal cancer. SEARCH STRATEGY We searched the Cochrane Library, MEDLINE, EMBASE, CBM, and handsearched the relevant Chinese journals. SELECTION CRITERIA Randomised trials comparing either chemotherapy only or chemotherapy plus anti-emetics (tropisetron, sulpiride etc) with chemotherapy plus Chinese herbs. DATA COLLECTION AND ANALYSIS Trial quality was assessed independently by two reviewers. Data were extracted by one reviewer and checked by the second reviewer. Since the four included studies differed significantly in design, we could only perform limited meta-analyses. We have therefore presented the majority of the data in narrative form. MAIN RESULTS We included four relevant trials. All of them were of low quality. All of studies used a decoction containing Huangqi compounds as the intervention with chemotherapy. The intervention groups of three studies were compared to a chemotherapy alone control group, the fourth study compared the decoction of Huangqi compounds with two other Chinese herbal interventions. None of the studies reported on primary outcome using Common Toxicity Criteria (CTC). There was a significant reduction in the proportion of patients who experienced nausea & vomiting when decoctions of Huangqi compounds were given in addition to chemotherapy. There was also a decrease in the rate of leucopenia (WBC <3 x 10(9) per L). Huangqi compounds were also associated with increases in the proportions of T-lymphocyte subsets: CD3; CD4 and CD8. Huangqi decoctions had no significant effects on Immunoglobulins G, A or M. AUTHORS' CONCLUSIONS Despite the included studies being of low quality, the results suggest that decoctions of Huangqi compounds may stimulate immunocompetent cells and decrease side effects in patients treated with chemotherapy. Due to the methodological limitations of the studies, there is no robust demonstration of benefit. We found no evidence of harm arising from the use of Chinese herbs. We need high quality randomised controlled studies investigating the effects of decoctions of Chinese herbs, particularly Astragalus spp. (as in Huangqi), upon chemotherapy-related side effects.
A study on deep neural network acoustic model adaptation for robust far-field speech recognition

Even though deep neural network acoustic models provide an increased degree of robustness in automatic speech recognition, there is still a large performance drop in the task of far-field speech recognition in reverberant and noisy environments. In this study, we explore DNN adaptation techniques to achieve improved robustness to environmental mismatch for far-field speech recognition. In contrast to many recent studies investigating the role of feature processing in DNN-HMM systems, we focus on adaptation of a clean-trained DNN model to speech data captured by a distant-talking microphone in a target environment with substantial reverberation and noise. We show that significant performance gains can be obtained by discriminatively estimating a set of adaptation parameters to compensate the mismatch between a clean-trained model and a small set of noisy and reverberant adaptation data. Using various adaptation strategies, relative word error rate improvements of up to 16% could be obtained on the single-channel task of the recent Aspire challenge.
Enterprise System Implementation and Employee Job Performance: Understanding the Role of Advice Networks

The implementation of enterprise systems, such as enterprise resource planning (ERP) systems, alters business processes and associated workflows, and introduces new software applications that employees must use. Employees frequently find such technology-enabled organizational change to be a major challenge. Although many challenges related to such changes have been discussed in prior work, little research has focused on post-implementation job outcomes of employees affected by such change. We draw from social network theory-- specifically, advice networks--to understand a key post-implementation job outcome (i.e., job performance). We conducted a study among 87 employees, with data gathered before and after the implementation of an ERP system module in a business unit of a large organization. We found support for our hypotheses that workflow advice and software advice are associated with job performance. Further, as predicted, we found that the interactions of workflow and software get-advice, workflow and software give-advice, and software get- and give-advice were associated with job performance. This nuanced treatment of advice networks advances our understanding of post-implementation success of enterprise systems.
Validity Assessment of 5 Day Repeated Forced-Swim Stress to Model Human Depression in Young-Adult C57BL/6J and BALB/cJ Mice

Visual Abstract The development of animal models with construct, face, and predictive validity to accurately model human depression has been a major challenge. One proposed rodent model is the 5 d repeated forced swim stress (5d-RFSS) paradigm, which progressively increases floating during individual swim sessions. The onset and persistence of this floating behavior has been anthropomorphically characterized as a measure of depression. This interpretation has been under debate because a progressive increase in floating over time may reflect an adaptive learned behavioral response promoting survival, and not depression (Molendijk and de Kloet, 2015). To assess construct and face validity, we applied 5d-RFSS to C57BL/6J and BALB/cJ mice, two mouse strains commonly used in neuropsychiatric research, and measured a combination of emotional, homeostatic, and psychomotor symptoms indicative of a depressive-like state. We also compared the efficacy of 5d-RFSS and chronic social defeat stress (CSDS), a validated depression model, to induce a depressive-like state in C57BL/6J mice. In both strains, 5d-RFSS progressively increased floating behavior that persisted for at least 4 weeks. 5d-RFSS did not alter sucrose preference, body weight, appetite, locomotor activity, anxiety-like behavior, or immobility behavior during a tail-suspension test compared with nonstressed controls. In contrast, CSDS altered several of these parameters, suggesting a depressive-like state. Finally, predictive validity was assessed using voluntary wheel running (VWR), a known antidepressant intervention. Four weeks of VWR after 5d-RFSS normalized floating behavior toward nonstressed levels. These observations suggest that 5d-RFSS has no construct or face validity but might have predictive validity to model human depression.
Long hours in paid and domestic work and subsequent sickness absence: does control over daily working hours matter?

Objectives: To explore the associations of working hours (paid, domestic, commuting, and total) with sickness absence, and to examine whether these associations vary according to the level of employee control over daily working hours. Methods: Prospective cohort study among 25 703 full-time public sector employees in 10 towns in Finland. A survey of working hours and control over working hours was carried out in 2000–01. The survey responses were linked with register data on the number of self-certified (⩽3 days) and medically certified (>3 days) sickness absences until the end of 2003. Poisson regression analyses with generalised estimating equations were used to take into account the fact that the employees were nested within work units. Adjustments were made for work and family characteristics and health behaviour. The mean follow-up period was 28.1 (SD 8.1) months. Results: Long domestic and total working hours were associated with higher rates of medically certified sickness absences among both genders. In contrast, long paid working hours were associated with lower rates of subsequent self-certified sickness absences. Long commuting hours were related to increased rates of sickness absence of both types. Low control over daily working hours predicted medically certified sickness absences for both the women and men and self-certified absences for the men. In combinations, high control over working hours reduced the adverse associations of long domestic and total working hours with medically certified absences. Conclusions: Employee control over daily working hours may protect health and help workers successfully combine a full-time job with the demands of domestic work.
A proof of a generalization of Deligne’s conjecture

The goal of this paper is to give a simple proof of Deligne's conjecture (proven by Fujiwara) and to generalize it to the situation appearing in our joint project with David Kazhdan on the global Langlands correspondence over function fields. Our proof holds in the realm of ordinary algebraic geometry and does not use rigid geometry.
Pacific Asia Conference on Information Systems ( PACIS ) 2015 Improving Information Security Training : An Intercultural Perspective

To ensure successful compliance with information security (InfoSec) policy and standards, organisations must harmonise their InfoSec training programmes with the national culture of the local workforce. A successful InfoSec policy must demonstrate the value of security, not just the requirement for security. We conducted a quantitative study of 177 professionals across 35 national cultures to investigate whether national culture influences InfoSec training and best practices using Hofstede’s six cultural dimensions. Our findings indicate that training programmes should more directly address the variances in perception of InfoSec across cultures. These training programmes should also reflect the significance of the organisation’s InfoSec policies in the context of the local employee, while maintaining unified corporate governance. By increasing training comprehension, organisations can reduce security incidents resulting from unintentional policy violations and, in turn, avoid costly remediation efforts.
The strengthening of metals by dispersed particles

A review is made of the yield strength attainable by dispersing particles in a metal matrix in order to hinder dislocation motion. The advantages and drawbacks of the various methods used to introduce the particles are considered. The greatest strengths are found in materials containing a large volume fraction of dispersed phase coupled with a high density of dislocations in the matrix. The greatest strengths should be achieved if the dispersed particles are very strong and are loaded to fracture. To load the particles they must be needle-shaped. Experiments on model systems of a metal containing wires to simulate the strong phase are described. These indicate some of the conditions necessary to obtain maximum strength and suggest how extreme brittleness can be avoided.
Neural Substrates of Sexual Desire in Individuals with Problematic Hypersexual Behavior

Studies on the characteristics of individuals with hypersexual disorder have been accumulating due to increasing concerns about problematic hypersexual behavior (PHB). Currently, relatively little is known about the underlying behavioral and neural mechanisms of sexual desire. Our study aimed to investigate the neural correlates of sexual desire with event-related functional magnetic resonance imaging (fMRI). Twenty-three individuals with PHB and 22 age-matched healthy controls were scanned while they passively viewed sexual and nonsexual stimuli. The subjects' levels of sexual desire were assessed in response to each sexual stimulus. Relative to controls, individuals with PHB experienced more frequent and enhanced sexual desire during exposure to sexual stimuli. Greater activation was observed in the caudate nucleus, inferior parietal lobe, dorsal anterior cingulate gyrus, thalamus, and dorsolateral prefrontal cortex in the PHB group than in the control group. In addition, the hemodynamic patterns in the activated areas differed between the groups. Consistent with the findings of brain imaging studies of substance and behavior addiction, individuals with the behavioral characteristics of PHB and enhanced desire exhibited altered activation in the prefrontal cortex and subcortical regions. In conclusion, our results will help to characterize the behaviors and associated neural mechanisms of individuals with PHB.
A Classification and Comparison Framework for Software Architecture Description Languages

Software architectures shift the focus of developers from lines-of-code to coarser-grained architectural elements and their overall interconnection structure. Architecture description languages (ADLs) have been proposed as modeling notations to support architecture-based development. There is, however, little consensus in the research community on what is an ADL, what aspects of an architecture should be modeled in an ADL, and which of several possible ADLs is best suited for a particular problem. Furthermore, the distinction is rarely made between ADLs on one hand and formal specification, module interconnection, simulation and programming languages on the other. This paper attempts to provide an answer to these questions. It motivates and presents a definition and a classification framework for ADLs. The utility of the definition is demonstrated by using it to differentiate ADLs from other modeling notations. The framework is used to classify and compare several existing ADLs, enabling us, in the process, to identify key properties of ADLs. The comparison highlights areas where existing ADLs provide extensive support and those in which they are deficient, suggesting a research agenda for the future.