Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Subchronic Inhalation Toxicity of Dimethyl Disulfide in Rats

This study was carried out to investigate the potential subchronic inhalation toxicity of dimethyl disulfide (DMDS) via whole-body exposure in F344 rats. Groups of 10 rats of each sex were exposed to DMDS vapor by whole-body exposure at concentrations of 0, 5, 25, or 125 ppm for 6 h/day, 5 days/wk for 13 wk. All the rats were sacrificed at the end of treatment period. During the test period, clinical signs, mortality, body weights, food consumption, ophthalmoscopy, urinalysis, hematology, serum biochemistry, gross findings, organ weights, and histopathology were examined. At 25 ppm, a decrease in the body weight gain, food intake, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and blood urea nitrogen (BUN) was observed in the males, but not in the females. However, at 125 ppm, a decrease in the body weight gain, food intake, and thymus weight and an increase in the weights of adrenal glands were observed in both genders. Serum biochemical investigations revealed a decrease in the AST, ALT, BUN, creatine phosphokinase (CPK), and triglyceride levels and an increase in the glucose level. In contrast, no treatment-related effects were observed in the 5 ppm group. The toxic potency of DMDS was slightly higher in males than that in females. In these experimental conditions, the target organ was not determined in rats. The no-observed-adverse-effect concentration (NOAEC) was found to be 5 ppm, 6 h/day for male rats and 25 ppm, 6 h/day for female rats.
Efficient Parallel Implementation of State Estimation Algorithms on Multicore Platforms

For many applications in signal processing and control it is crucial that estimates of the state vector in a dynamic system can be obtained in real time. This poses the problem of producing algorithms that are fast enough to enable online execution. In this article, it is investigated how two of the most popular and powerful state estimation algorithms, the Kalman filter and the particle filter, can be efficiently implemented in parallel on a multicore architecture. The proposed parallel implementations are analyzed in terms of hardware requirements, such as memory bandwidth and available cache memory, to provide the desired speedup. The algorithms are exemplified by and evaluated in an adaptive filtering and a bearings-only tracking application. In the cases when original algorithms have been modified for parallelization, the accuracy of the estimates obtained is evaluated in comparison with that of the sequential algorithm. It is found that linear speedup, in the number of cores used, can indeed be achieved without loss of accuracy, for both state estimation algorithms.
Relationship of Physical Fitness Measures vs. Occupational Physical Ability in Campus Law Enforcement Officers

Abstract Beck, AQ, Clasey, JL, Yates, JW, Koebke, NC, Palmer, TG, and Abel, MG. Relationship of physical fitness measures vs. occupational physical ability in campus law enforcement officers. J Strength Cond Res 29(8): 2340–2350, 2015—Law enforcement officers (LEOs) on university campuses are required to perform a variety of physical occupational tasks. Identifying which physical fitness characteristics are associated with these occupational tasks will assist in the development of appropriate exercise programs and physical fitness assessments. Therefore, the purpose of this study was to identify physical fitness and demographic characteristics that were correlated with occupational tasks commonly performed by campus LEOs. The occupational assessment was conducted using an Officer Physical Ability Test (OPAT), which simulated a foot chase of a suspect. Sixteen male LEOs (age: 33.1 ± 8.7 years; body mass: 87.2 ± 11.2 kg; height: 179.0 ± 7.9 cm) performed the OPAT. A battery of physical fitness tests were used to assess aerobic capacity, muscular endurance, strength, power, flexibility, agility, and body composition. Bivariate correlations were performed to identify significant (p ⩽ 0.05) correlations between physical fitness characteristics and OPAT time. The officers' age was significantly correlated to the majority of OPAT tasks, physical fitness, and anthropometric assessments. Therefore, partial correlations were used to control for the confounding effects of age. After controlling for the officers' age, the overall OPAT time was significantly correlated with agility (r = 0.57) and aerobic endurance (r = −0.65). Furthermore, push-up, curl-up, body mass, waist circumference, and abdominal circumference were significantly correlated to individual OPAT tasks. In conclusion, exercise programs and fitness assessments should be used for campus LEOs that address a variety of physical fitness characteristics associated with occupational performance. In addition, exercise programs should focus on body composition management and fitness for older LEOs.
Evidence for Hand-Size Constancy

The hand is a reliable and ecologically useful perceptual ruler that can be used to scale the sizes of close, manipulatable objects in the world in a manner similar to the way in which eye height is used to scale the heights of objects on the ground plane. Certain objects are perceived proportionally to the size of the hand, and as a result, changes in the relationship between the sizes of objects in the world and the size of the hand are attributed to changes in object size rather than hand size. To illustrate this notion, we provide evidence from several experiments showing that people perceive their dominant hand as less magnified than other body parts or objects when these items are subjected to the same degree of magnification. These findings suggest that the hand is perceived as having a more constant size and, consequently, can serve as a reliable metric with which to measure objects of commensurate size.
Who Are Informed? The Evidence from Institutional Trades

Using the relation between institutional trades and sequential public information, this paper provides a systematic way to identify institutional trades that are informative about future equity returns. By studying actively managed U.S. institutions from 1994 to 2010, I show that institutional trades initiated by managers responding proactively to upcoming informational signals strongly predict future stock returns. A hedging portfolio based on these trades generates an average risk-adjusted abnormal return of approximately 3% per quarter. The predictability is more pronounced for stocks with higher information asymmetry, such as those of firms with high volatility and young age. I also find that the most informed institutional traders are likely to have short-term investment horizon, large block holdings, high industry portfolio concentrations, as well as reside in financial centers. My results indicate that the informedness of certain institutional investor groups is substantially reduced after Regulation FD.
Board Composition and Open-End Mutual Fund Performance

The mutual fund industry has grown rapidly during the past decade. In the U.S., each mutual fund that is registered with the Securities and Exchange Commission (SEC) is required to be overseen by a board of directors or board of trustees. They oversee the fund’s compliance program, negotiate the fees paid for the advisors and supervise the fund performance. They manage the funds on behalf of the shareholders and is a bridge between shareholders and fund managers. So what composes a good mutual fund board? Besides fund managers’ day-to-day running, could the composition and structure of the board impact fund performance? Using a large sample of open-end mutual funds, and three corresponding manually-collected databases of board of directors for 2009, 2011 and 2013, we examine whether the average board composition and diversity characteristics have an explanatory power of fund performance. We find that none of these tested characteristics is a consistently significant determinant of relative cross-sectional performance.
Integrated analysis of high‐resolution DNA methylation profiles, gene expression, germline genotypes and clinical end points in breast cancer patients

Breast cancer is a heterogeneous disease for which alterations in DNA methylation patterns have been shown to be of biological and clinical importance. Here we report on the integrated analysis of molecular alterations including the methylation status of 27 gene promoters analyzed by highly quantitative pyrosequencing, and the association to gene expression, germline genotype and clinical parameters including survival. Breast cancer specific deregulation of DNA methylation (both hyper‐ and hypomethylation) was found in twenty genes including ACVR1, OGG1, IL8 and TFF1. The methylation level in the promoter regions was significantly negatively correlated to gene expression for twelve genes (such as MST1R, ST6GAL1 and TFF1) indicating that a gain of aberrant methylation (hypermethylation) inhibits gene expression. Multiple associations between molecular and clinical parameters were identified, and multivariate statistical analysis demonstrated that methylation was more strongly associated to clinical parameters than gene expression for the investigated genes. The methylation level of BCAP31 and OGG1 showed significant association to survival, and these associations were validated in a larger patient cohort (The Cancer Genome Atlas). Our study provides evidence for the promise of DNA methylation alterations for clinical applications.
Depth Exam From attention to object proposals

The problem of finding locations where people look at first in images, known as saliency detection, spans decades of research from multiple disciplines including psychology, neuroscience, and computer vision. Because of the complexity of the problem it can hardly be considered as solved. Here, we give an overview of the methods for saliency detection starting from early biologically-plausible methods from neuroscience and ending with supervised methods using machine-learning techniques in computer vision. We divide saliency detection methods into three main categories: psychologically-inspired, segmentation-based, and data-driven. We review representative works in each category. Also, we discuss challenges such as evaluation criteria, repeatability and robustness of the methods, and list a number of possible directions for future work.
To What Extent Can Central Banks Influence Exchange Rates with Foreign Exchange Interventions? The Case of Poland

The significant depreciation of the Polish zloty in the second half of 2011, difficult to explain by fundamentals, was accompanied by a large increase in exchange rate volatility. The foreign exchange interventions carried out by the National Bank of Poland at that time were aimed at reducing the volatility of the Polish currency and the risk of its disorderly depreciation. In this regard, the two event studies presented in this paper argue that the central bank’s policy was effective. On the date of the intervention, the zloty typically appreciated against the euro while the implied volatility of the currency tended to decline.Full publication: Market Volatility and Foreign Exchange Intervention in EMEs: What Has Changed?
Postpartum use of long-acting reversible contraception in a military treatment facility.

OBJECTIVE To determine the rate at which long-acting reversible contraception (LARC) is desired immediately postpartum and utilized within 12 weeks of delivery at our institution. METHODS This prospective cohort study analyzed 400 consecutive postpartum patients between January 2009 and March 2009. We followed contraceptive desire prior to discharge and actual contraception utilized within 12 weeks postpartum. Patient demographics and LARC utilization was analyzed to determine characteristics predictive of use. RESULTS There was complete follow-up information on 329 (82.3%) of the studied women. Thirty-three percent (132/400) desired LARC immediately postpartum, and overall LARC utilization at 12 weeks was 31% (100/329). Demographic characteristics predictive of LARC desire and utilization included age <25 years (adjusted RR=1.53, 95% CI 1.17-1.92) and African-American ethnicity (adjusted RR=1.39, 95% CI 1.03-1.78). CONCLUSION In our institution, LARC is highly desired and utilized within 12 weeks postpartum with African-American ethnicity and age <25 years predictive of use.
Why Do Some Firms Make Seemingly Inferior Decisions?

Empirical studies on corporate decisions often employ the treatment model, the Heckman selectivity model, or the matched sample method and find that one choice (treatment) is strictly better than the other. These results lead to a puzzle - why do some firms select the inferior choices? In this paper, I show that methodological issues drive such findings because these methods rule out the possibility that firms with heterogeneous characteristics can make different optimal decisions. The objects of this paper are to discuss how such an optimal decision making process is fundamentally incompatible with the assumptions required by the above methods and to caution the applications of those methods in studying corporate decisions.
Targeting the Folate Receptor (FR): Imaging and Cytotoxicity of ReI Conjugates in FR‐Overexpressing Cancer Cells

The synthesis, characterization, in vitro imaging, and cytotoxic properties of a new folate conjugate of rhenium(I) are reported. The conjugate [FA‐PEG‐BQAV‐Re(CO)3]+ (γ‐4) was screened against an adriamycin‐ and cisplatin‐resistant human ovarian cancer cell line (A2780/AD) that overexpresses the folate receptor (FR). Compound γ‐4 was internalized by a folate‐receptor‐mediated endocytotic pathway, which results in internal accumulation of γ‐4. This was contrasted with a FR‐negative Chinese hamster ovary cell line in which no internalization of γ‐4 was observed. γ‐4 was found to be cytotoxic with IC50 values of 189 and 78 μM at 6 and 24 h, respectively, toward the FR‐positive cell line. This is in contrast to the IC50 value of 502 μM at 6 h and 84 μM at 24 h for cisplatin in the same cell line, with a significantly greater toxicity at the earlier time point. The cytotoxicity of γ‐4 as explained by interactions that occur between the rhenium(I) complex moiety and DNA is described.
Obtaining Formal Knowledge from Informal Text Analysis

Populating formal knowledge-bases from natural-language text is a long-standing objective in computer science. Recent advancements in both ontology research and information extraction research are making this objective increasingly obtainable. However, there are still serious obstacles to performing automated reasoning over the contents of text documents. This paper focuses on one of those obstacles: differences between the formal ontologies used by reasoning systems and the informal ontologies used by extraction systems. We describe a framework for automating translation from extracted information to formal knowledge, and we describe a complex, implemented system that uses this framework. We also describe results from this system applied to a moderately large (approximately 75 MB) text corpus.
A Giant GTPase, Very Large Inducible GTPase-1, Is Inducible by IFNs 1

The complex, partially overlapping, cellular responses to IFN type I (IFN-α and -β) and IFN type II (IFN-γ) involve several hundred genes that can be largely classified in terms of specific cellular programs functional in innate and adaptive immunity. Among these programs are previously unconsidered mechanisms of cell-autonomous resistance against various pathogens mediated by dedicated, largely novel families of GTPases. We report here the identification and characterization of a new GTPase family that contributes to the cellular response to both type I and type II IFNs. We name this family the very large inducible GTPases (VLIGs). The prototype VLIG, VLIG-1, is a strongly IFN-inducible, soluble, cytosolic and nuclear protein of 280 kDa. The open reading frame of VLIG-1 is encoded on a single very large exon, and outside the canonical GTP-binding motifs, sequence and structural prediction suggest a unique family without significant relationship to other known protein families. Within the GTPase superfamily the VLIG family is more closely related to IFN-inducible GTPases mediating cell-autonomous resistance than to other GTPase families. In addition, we provide evidence that VLIG-1 is polymorphic in mice of different genetic backgrounds and is a member of a small gene family on mouse chromosome 7 with a conserved homologue located on human chromosome 11.
Morphine Reward Promotes Cue-Sensitive Learning: Implication of Dorsal Striatal CREB Activity

Different parallel neural circuits interact and may even compete to process and store information: whereas stimulus–response (S–R) learning critically depends on the dorsal striatum (DS), spatial memory relies on the hippocampus (HPC). Strikingly, despite its potential importance for our understanding of addictive behaviors, the impact of drug rewards on memory systems dynamics has not been extensively studied. Here, we assessed long-term effects of drug- vs food reinforcement on the subsequent use of S–R vs spatial learning strategies and their neural substrates. Mice were trained in a Y-maze cue-guided task, during which either food or morphine injections into the ventral tegmental area (VTA) were used as rewards. Although drug- and food-reinforced mice learned the Y-maze task equally well, drug-reinforced mice exhibited a preferential use of an S–R learning strategy when tested in a water-maze competition task designed to dissociate cue-based and spatial learning. This cognitive bias was associated with a persistent increase in the phosphorylated form of cAMP response element-binding protein phosphorylation (pCREB) within the DS, and a decrease of pCREB expression in the HPC. Pharmacological inhibition of striatal PKA pathway in drug-rewarded mice limited the morphine-induced increase in levels of pCREB in DS and restored a balanced use of spatial vs cue-based learning. Our findings suggest that drug (opiate) reward biases the engagement of separate memory systems toward a predominant use of the cue-dependent system via an increase in learning-related striatal pCREB activity. Persistent functional imbalance between striatal and hippocampal activity could contribute to the persistence of addictive behaviors, or counteract the efficiency of pharmacological or psychotherapeutic treatments.
Linked Statistical Shape Models for multi-modal segmentation of the prostate on MRI-CT for radiotherapy planning

We present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate delineations of a SOI’s boundary on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. We apply the LSSM in the context of multi-modal prostate segmentation for radiotherapy planning, where we segment the prostate on MRI and CT simultaneously. Prostate capsule segmentation is a critical step in prostate radiotherapy planning, where dose plans have to be formulated on CT. Since accurate delineations of the prostate boundary are very difficult to obtain on CT, pre-treatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to do compared to CT. Hence, our framework incorporates multi-modal registration of MRI and CT to map 2D boundary delineations of prostate (obtained from an expert radiation oncologist) on MR training images onto corresponding CT images. The delineations of the prostate capsule on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. We acquired 7 MRI-CT patient studies and used the leave-one-out strategy to train and evaluate our LSSM (fLSSM), built using expert ground truth delineations on MRI and MRI-CT fusion derived capsule delineations on CT. A unique attribute of our fLSSM is that it does not require expert delineations of the capsule on CT. In order to perform prostate MRI segmentation using the fLSSM, we employed a regionbased approach where we deformed the evolving prostate boundary to optimize a mutual information based cost criterion, which took into account region-based intensity statistics of the image being segmented. The final prostate segmentation was then transferred onto the CT image using the LSSM. We compared our fLSSM against another LSSM (xLSSM), where, unlike the fLSSM, expert delineations of the capsule on both MRI and CT were employed in the model building; xLSSM representing the idealized LSSM. We also compared our fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of capsule on CT only. Due to the intensity-driven nature of the segmentation algorithm, the ctSSM was not able segment the prostate. On MRI, the xLSSM and fLSSM yielded almost identical results. On CT, our results suggest that the fLSSM, while not dependent on highly accurate delineations of the capsule on CT, yields comparable results to an idealized LSSM scheme (xLSSM). Hence, the fLSSM provides an accurate alternative to SSMs that require careful SOI delineations that may be difficult or laborious to obtain, while providing concurrent segmentations of the capsule on multiple modalities.
Automatically Repairing Web Application Firewalls Based on Successful SQL Injection Attacks

Testing and fixing Web Application Firewalls (WAFs) are two relevant and complementary challenges for security analysts. Automated testing helps to cost-effectively detect vulnerabilities in a WAF by generating effective test cases, i.e., attacks. Once vulnerabilities have been identified, the WAF needs to be fixed by augmenting its rule set to filter attacks without blocking legitimate requests. However, existing research suggests that rule sets are very difficult to understand and too complex to be manually fixed. In this paper, we formalise the problem of fixing vulnerable WAFs as a combinatorial optimisation problem. To solve it, we propose an automated approach that combines machine learning with multi-objective genetic algorithms. Given a set of legitimate requests and bypassing SQL injection attacks, our approach automatically infers regular expressions that, when added to the WAF&#x2019;s rule set, prevent many attacks while letting legitimate requests go through. Our empirical evaluation based on both open-source and proprietary WAFs shows that the generated filter rules are effective at blocking previously identified and successful SQL injection attacks (recall between 54.6% and 98.3%), while triggering in most cases no or few false positives (false positive rate between 0% and 2%).
Min-Max Output Integral Sliding Mode Control for Multiplant Linear Uncertain Systems

In this paper we consider the problem of using the min-max optimal control based on the LQ-index for a set of systems where only output information is available. We consider that each system is affected by matched uncertainties, and we propose to use an output integral sliding mode (OISM) to compensate the matched uncertainties right after the beginning of the process. For the case when the number of inputs is less than the number of outputs, a hierarchical sliding mode observer is proposed that converges to the original state with any small arbitrarily precision after any arbitrarily time.