Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling behavioral thermoregulation in a climate change sentinel

Abstract When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature‐sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north‐facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.
Hyperaccreting Black Holes and Gamma-Ray Bursts

A variety of current models of gamma-ray bursts (GRBs) suggest a common engine: a black hole of several solar masses accreting matter from a disk at a rate of 0.01 to 10 M☉ s-1. Using a numerical model for relativistic disk accretion, we have studied steady state accretion at these high rates. Outside about 108 cm, the disk is advection dominated; energy released by dissipation is carried in by the optically thick gas, and the disk does not cool. Inside this radius, for accretion rates greater than about 0.01 M☉ s-1 a global state of balanced power comes to exist between neutrino losses, chiefly pair capture on nucleons, and dissipation. As a result of these losses, the temperature is reduced, the density is raised, and the disk scale height is reduced compared to the advective solution. The sudden onset of neutrino losses (due to the high temperature dependence) and photodisintegration leads to an abrupt thinning of the disk that may provide a favorable geometry for jet production. The inner disk remains optically thin to neutrinos for accretion rates of up to about 1 M☉ s-1. The energy emitted in neutrinos is less, and in the case of low accretion rates, very much less, than the maximum efficiency factor for black hole accretion (0.057 for no rotation; 0.42 for extreme Kerr rotation) times the accretion rate, Ṁc2. Neutrino temperatures at the last stable orbit range from 2 MeV (no rotation, slow accretion) to 13 MeV (Kerr geometry, rapid accretion), and the density ranges from 109 to 1012 g cm-3. The efficiency for producing a pair fireball along the rotational axis by neutrino annihilation is calculated and found to be highly variable and very sensitive to the accretion rate. For some of the higher accretion rates studied, it can be several percent or more; for accretion rates less than 0.05 M☉ s-1, it is essentially zero. The efficiency of the Blandford-Znajek mechanism in extracting rotational energy from the black hole is also estimated. In light of these results, the viability of various gamma-ray burst models is discussed, and the sensitivity of the results to disk viscosity, black hole rotation rate, and black hole mass is explored. A diverse range of GRB energies seems unavoidable, and neutrino annihilation in hyperaccreting black hole systems can explain bursts of up to 1052 ergs. Larger energies can be inferred for beaming systems.
Examining Self-Care Among Individuals Employed in Social Work Capacities

Increasingly, the social work profession recognizes the need for more attention to self-care. Concomitantly, this growing awareness and ethical commitment is fostering a burgeoning self-care movement. However, despite recognition about the importance of self-care, there is a paucity of research that explicitly examines self-care practices among social workers. This cross-sectional study examined the self-care practices of individuals employed in social work capacities (n=1,011) in one southeastern state in the United States. Findings suggest that participants in the sample engaged in personal and professional self-care practices only moderately. Further, data suggest significant group differences in the practice of self-care, by relationship status, educational attainment, health status, and current financial situation, respectively. Overall, results indicate self-care as a potential area of improvement for participants in this study, in general, and perhaps for individuals employed in social work contexts, more generally.
Influence of Oleic Acid on Rumen Fermentation and Fatty Acid Formation In Vitro

A series of batch cultures were conducted to investigate the effects of oleic acid (OA) on in vitro ruminal dry matter degradability (IVDMD), gas production, methane (CH4) and hydrogen (H2) production, and proportion of fatty acids. Rumen fluid was collected from fistulated goats, diluted with incubation buffer, and then incubated with 500 mg Leymus chinensis meal supplemented with different amounts of OA (0, 20, 40, and 60 mg for the CON, OA20, OA40 and OA60 groups, respectively). Incubation was carried out anaerobically at 39°C for 48 h, and the samples were taken at 12, 24 and 48 h and subjected to laboratory analysis. Supplementation of OA decreased IVDMD, the cumulative gas production, theoretical maximum of gas production and CH4 production, but increased H2 production. However, no effect was observed on any parameters of rumen fermentation (pH, ammonia, production of acetate, propionate and butyrate and total volatile fatty acid production). The concentrations of some beneficial fatty acids, such as cis monounsaturated fatty acids and conjugated linoleic acid (CLA) were higher (P < 0.05) from OA groups than those from the control group at 12 h incubation. In summary, these results suggest that the OA supplementation in diet can reduce methane production and increase the amount of some beneficial fatty acids in vitro.
SEVA: A Salient Event Detection Framework from Video Shots Using Support Vector Data Description

In this paper we propose SEVA (Salient Events for Video Analytics), a framework for accurate detection and localization of salient events from a given video shot. Our proposed method is based on statistical learning theory and models salient event detection as a one-class classification problem. Video frames are split into blocks for extracting both the spatial and temporal features. Given a video shots we first track the moving foreground blob. Features are extracted using only the foreground pixels to avoid influence of the background. Using Support Vector Data Description (SVDD) in kernel feature space for each block in a given video frame, the decision boundary for the normal activity class is modeled. For a test video sequence, feature vectors are computed from the video frames and the learnt model is utilized to classify each block as normal or salient. Finally, we have adapted a spatio-temporal smoothing approach to remove the false positives. We have reported both qualitative and quantitative results of our experiments on two real-world benchmarked video datasets. Performance of SEVA is compared with five recent works on video event detection to validate its effectiveness.
Inhibition of Hb Binding to GP1bα Abrogates Hb-Mediated Thrombus Formation on Immobilized VWF and Collagen under Physiological Shear Stress

Background Reports including our own describe that intravascular hemolysis increases the risk of thrombosis in hemolytic disorders. Our recent study shows that plasma Hb concentrations correlate directly with platelet activation in patients with paroxysmal nocturnal hemoglobinuria (PNH). The binding of Hb to glycoprotein1bα (GP1bα) increases platelet activation. A peptide AA1-50, designed from N-terminal amino acid sequence of GP1bα significantly inhibits the Hb binding to GP1bα as well as Hb-induced platelet activation. This study further examined if the Hb-mediated platelet activation plays any significant role in thrombus formation on subendothelium matrix under physiological flow shear stresses and the inhibition of Hb-platelet interaction can abrogate the above effects of Hb. Methods and Results Study performed thrombus formation assay in vitro by perfusing whole blood over immobilized VWF or collagen type I in presence of Hb under shear stresses simulating arterial or venous flow. The Hb concentrations ranging from 5 to 10 μM, commonly observed level in plasma of the hemolytic patients including PNH, dose-dependently increased thrombus formation on immobilized VWF under higher shear stress of 25 dyne/cm2, but not at 5 dyne/cm2. The above Hb concentrations also increased thrombus formation on immobilized collagen under both shear stresses of 5 and 25 dyne/cm2. The peptide AA1-50 abrogated invariably the above effects of Hb on thrombus formation. Conclusions and Significance This study therefore indicates that the Hb-induced platelet activation plays a crucial role in thrombus formation on immobilized VWF or collagen under physiological flow shear stresses. Thus suggesting a probable role of this mechanism in facilitating thrombosis under hemolytic conditions.
Chain-based pseudorandom tests for pre-silicon verification of CMP memory systems

The coherent shared-memory abstraction is expected to keep its crucial role in Chip Multiprocessors even on the scale of hundreds of cores. As a result, the growing hardware complexity to support such abstraction makes the design of the memory system proner to error. Therefore, it is crucial to check for errors in shared-memory behavior as early as possible in the design flow. Given a design representation of a memory subsystem, this paper addresses the pre-silicon verification of its expected behavior, which is captured by the axioms that specify the coherence and consistency requirements of a memory model. As opposed to typical pseudorandom generation of test programs, this paper proposes the exploitation of significant operation orderings from aggressive memory model specifications for inducing load/store sequences that are more effective in uncovering design errors. The effectiveness of the novel technique was evaluated, for 8, 16, and 32-core architectures, when synthesizing 1200 distinct test programs for verifying 8 derivative designs containing errors (9600 use cases per architecture). The synthesized tests explored 5 program sizes, 4 levels of sharing, 4 instruction mixes, and 15 random seeds. Our results show that, as compared to typical pseudorandom generation, the proposed technique is more effective in exposing design errors whose sharing-level distributions are flat. For such design errors, our technique was more effective by 30% on average.
GasP: a minimal FIFO control

The GasP family of asynchronous circuits provides controls for simple pipelines, for branching and joining pipelines, for round-robin scatter and gather for data dependent scatter and gather and for join on demand through arbitration. The family is designed so that each stage operates at the speed of a three-inverter ring oscillator Test chips in 0.35 micron technology exhibit throughput in excess of 1.5 giga data items per second (GDI/s). Between GasP pipeline stages a single wire carries both request and acknowledge messages, also recording the FULL or EMPTY state of each pipeline stage. GasP control circuits rely on careful choice of transistor widths to equalize the delay in logic gates. Assurance of uniform gate delays permits use of self-resetting logic forms that have very low logical effort.
Modulation of Tamoxifen Cytotoxicity by Caffeic Acid Phenethyl Ester in MCF-7 Breast Cancer Cells

Although Tamoxifen (TAM) is one of the most widely used drugs in managing breast cancer, many women still relapse after long-term therapy. Caffeic acid phenethyl ester (CAPE) is a polyphenolic compound present in many medicinal plants and in propolis. The present study examined the effect of CAPE on TAM cytotoxicity in MCF-7 cells. MCF-7 cells were treated with different concentrations of TAM and/or CAPE for 48 h. This novel combination exerted synergistic cytotoxic effects against MCF-7 cells via induction of apoptotic machinery with activation of caspases and DNA fragmentation, along with downregulation of Bcl-2 and Beclin 1 expression levels. However, the mammalian microtubule-associated protein light chain LC 3-II level was unchanged. Vascular endothelial growth factor level was also decreased, whereas levels of glutathione and nitric oxide were increased. In conclusion, CAPE augmented TAM cytotoxicity via multiple mechanisms, providing a novel therapeutic approach for breast cancer treatment that can overcome resistance and lower toxicity. This effect provides a rationale for further investigation of this combination.
A Novel Approach Using Active Contour Model for Semi-Automatic Road Extraction from High Resolution Satellite Imagery

Road Extraction from satellite imagery is of fundamental importance in the context of spatial data capturing and updating for GIS applications. As fully automatic method for feature extraction is difficult due to the increasing complexity of objects. This paper proposes a semi-automatic road extraction methodology from high resolution satellite imagery using active contour model (Snakes). First the image is preprocessed using relaxed median filter. In the next step the user inputs initial seed points on the road to be extracted. Then the road segment is extracted using active contour model. The method is tested using high resolution satellite imagery and the results are presented in the paper.
Ghent University-IBCN participation in TAC-KBP 2014 slot filling and cold start tasks

This paper presents the system of the UGENT IBCN team for the TAC KBP 2014 slot filling and cold start (slot filling variant) tasks. This was the team’s first participation in both tasks. The slot filling system uses distant supervision to generate training data combined with a noise reduction step, and two different types of classifiers. We show that the noise reduction step significantly improves precision, and propose an application of word embeddings for slot filling.
MAKING AIRLINE SCHEDULES MORE ROBUST

Aircraft fleet can have a major effect on the efficiency and smooth running of an airline. Constructing good quality schedules is essential for an airline to operate in an effective and efficient way in order to accomplish high levels of consumer satisfaction and to maximise profits. The robustness of an airline schedule is an indicative measure of how good the schedule is because a robust plan allows the airline to cope with the unexpected disturbances which normally occur on a daily basis. This paper describes a method to measure the robustness of schedules for aircraft fleet scheduling within KLM airlines. The method is based on the ‘Aircraft on Ground (ACOG)’ measure, it employs statistical methods (although alternative methods were also considered) and it is shown to provide a good estimation of the robustness of a given schedule.
Web application security by SQL injection detection tools

SQL injection is a type of attack which the attacker adds Structured Query Language code to a web form input box to gain access or make changes to data. SQL injection vulnerability allows an attacker to flow commands directly to a web application's underlying database and destroy functionality or confidentiality. Researchers have proposed different tools to detect and prevent this vulnerability. In this paper we present all SQL injection attack types and also current tools which can detect or prevent these attacks. Finally we evaluate these tools.
Prevalence of Salmonella in intestinal mucosal samples from free-ranging Red-eared Sliders (Trachemys scripta elegans) in Illinois

––Turtles can be carriers of bacteria of the genus Salmonella, and numerous studies have documented Salmonella shedding in both captive and free-living populations. Because turtles may shed Salmonella intermittently, however, data based on fecal samples may underestimate the true prevalence of the bacterium in turtles. We examined intestinal mucosal scrapings using molecular methods to identify Salmonella in free-ranging Red-eared Sliders (Trachemys scripta elegans) to determine carriage rates. Salmonella was detected in 11% (8/73) of turtles. Prevalence of infection did not vary among the nine ecologically varied ponds sampled. The prevalence of Salmonella infection in this study was higher than documented in a previous study that was conducted on conspecifics in the same area and during the same year but using fecal samples, suggesting that free-ranging Red-eared Sliders can harbor Salmonella but not shed the bacterium in feces.
A Comparison Study of Cluster Validity Indices Using a Nonhierarchical Clustering Algorithm

Cluster analysis is widely used in the initial stages of data analysis and data reduction. The K-means algorithm, a nonhierarchical clustering algorithm, has regained popularity among researchers in data mining and knowledge discovery, partly because of its low time complexity. The algorithm requires the number of clusters as an input parameter. When the parameter value is not known a priori, a researcher often has to use a cluster validity index to search for a suitable parameter value. In this study, we use computational experiments to examine the performance of cluster validity indices with the K-means algorithm. Our analysis parallels the study performed by Milligan and Cooper on cluster validity indices; we use hierarchical clustering algorithms and present observations and conclusions resulting from the simulation study
Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint

The reconstruction of artifact‐free images from radially encoded MRI acquisitions poses a difficult task for undersampled data sets, that is for a much lower number of spokes in k‐space than data samples per spoke. Here, we developed an iterative reconstruction method for undersampled radial MRI which (i) is based on a nonlinear optimization, (ii) allows for the incorporation of prior knowledge with use of penalty functions, and (iii) deals with data from multiple coils. The procedure arises as a two‐step mechanism which first estimates the coil profiles and then renders a final image that complies with the actual observations. Prior knowledge is introduced by penalizing edges in coil profiles and by a total variation constraint for the final image. The latter condition leads to an effective suppression of undersampling (streaking) artifacts and further adds a certain degree of denoising. Apart from simulations, experimental results for a radial spin‐echo MRI sequence are presented for phantoms and human brain in vivo at 2.9 T using 24, 48, and 96 spokes with 256 data samples. In comparison to conventional reconstructions (regridding) the proposed method yielded visually improved image quality in all cases. Magn Reson Med 57:1086–1098, 2007. © 2007 Wiley‐Liss, Inc.
Effect of decision rule on speaker recognition performance

Speaker recognition from speech signal is still an ongoing research in forensics and biometrics area. Speaker recognition is the process to enable machine to recognize speaker's identity from their speech. The applications of speaker recognition technologies include access control system, security control for confidential information, and telephone banking. As a subset of speaker recognition, speaker identification task needed in forensics is to decide how likely it is that two recordings are from the same person. In these circumstances, pattern classification engine for speaker identification should capable to manage and process huge speaker data sets in a short time limit. Meanwhile, current works for the production of speaker recognition are almost directed towards accuracy problems, not time processing problems. How to make a decision is a critical question to reduce the time consuming problem. In this paper, we propose a novel technique that applying decision tree method towards better decision making for speaker identification system. In our proposed modeling, we take the superiority of decision tree theory, which is simplicity computation to distinguish a group of speaker into smaller subgroup. We believe that smaller group of training data will decrease time processing in run times. To evaluate the performance of our method, we have done simulations based on well known pattern classification method, Vector Quantization. A comparison about time processing has made between proposed method and baseline Vector Quantization model. Comparative results show that our decision tree method always yielded better improvements in time processing. Thus, our method provides an alternative way for real time identification system which time is the important issue. In this paper, a new, robust and simplicity computation method of pattern classification technique for speaker identification system is proposed. Consequently, this research is intended to develop a fully optimize ways speaker identification approach from decision tree theory.
Team-Based Incentives in the NHS: An Economic Analysis, CMPO Working Paper 01/037

The NHS Plan welcomes the use of team rewards but does not specify how team based incentives are to be implemented or make clear what types of teams such incentives are to be given to. This paper looks for insights from economic theory on how to define teams and optimal incentive schemes within them. We give a brief description of the incentive mechanisms suggested in the NHS Plan and discuss the implications of the economic theory of team-incentives to the NHS. One implication is that the optimal compensation scheme depends on the type of team. Hence, the definition of teams in the NHS should precede the identification of the system of team rewards. We therefore examine which types of teams might be suitable for team rewards. We then consider issues in the use of financial incentives for such teams. JEL Classification: D23, J41