Miracle-dz/UniFAR-FTUs huggingface dataset:
Burden and predictors of Staphylococcus aureus and S. pseudintermedius infections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

Background Staphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between various Staphylococcus infections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa. Methods Records of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections. Results Twenty-seven percent of the samples tested positive for Staphylococcus spp. The species of Staphylococcus identified were S. pseudintermedius (19.0%), S. aureus (3.8%), S. epidermidis (0.7%) and S. felis (0.1%). The remaining 2.87% consisted of unspeciated Staphylococcus. Distribution of the species by age of dog showed that S. pseudintermedius was the most common (25.6%) in dogs aged 2–4 years while S. aureus was most frequent (6.3%) in dogs aged 5–6 years. S. pseudintermedius (34.1%) and S. aureus (35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection with Staphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive for S. pseudintermedius compared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive for S. aureus than those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive for S. pseudintermedius than those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive for S. pseudintermedius compared to those <2 years of age. The risk of infection with S. pseudintermedius or S. aureus was significantly higher in ear canal and skin specimens compared to other specimens. Conclusions The findings suggest that S. pseudintermedius and S. aureus were the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with both Staphylococcus species investigated. Significant increasing temporal trend was observed for S. pseudintermedius but not S. aureus. This information is useful for guiding clinical decisions as well as future research.
Integrated tandem traveling-wave electroabsorption modulators for >100 Gbit/s OTDM applications

Integrated tandem traveling-wave electroabsorption modulators are demonstrated as high-speed optical short pulse generators and demultiplexers for >100 Gbit/s optical time-division-multiplexed systems. The tandem significantly increases the extinction ratio and further compresses the optical pulses in comparison to a single modulator. An extinction ratio of /spl sim/50 dB is achieved while optical pulses of 4-6 ps width at 30-40 GHz are generated.
Learning the Popularity of Items for Mobile Tourist Guides

A context-aware recommender system incorporates the knowledge of different contextual factors such as time or weather information to improve item suggestions made to a user. This requires the system to have a large knowledge base for inferring contextual information and enabling accurate and timely recommendations. We present a versatile approach for a context-aware recommender system in the tourism domain by crawling publicly available information from a variety of sources and learning the contextual popularity of points of interest based on a generalized check-in model. We have deployed a test instance of our system for the greater area of Munich and the German state of Bavaria. Analyzing the results from the offline learning has led to interesting insights including when and in which weather conditions certain items are popular.
The effects of backpack loads and spinal stabilization exercises on the dynamic foot pressure of elementary school children with idiopathic scoliosis

[Purpose] The purpose of this study was to measure and observe the changes in dynamic plantar pressures when school children carried specific bag loads, and to determine whether improved physical balance after an eight-week spinal stabilization exercise program can influences plantar pressures. [Subjects] The subjects were 10 school students with Cobb angles of 10° or greater. [Methods] Gait View Pro 1.0 (Alfoots, Korea) was were based on to measure the pressure of the participants’ feet. Spinal stabilization exercises used TOGU Multi-roll Functional (TOGU, Germany) training. Dynamic plantar pressures were measured with bag loads of 0% no bag and 15% of subjects’ body weight. The independent t test was performed to analyze changes in plantar pressures. [Results] The plantar pressure measurements of bag load of 0% of subjects’ body weight before and after the spinal stabilization exercise program were not significantly different, but those of two foot areas with a 15% load were statistically significant (mt5, 67.32±24.25 and 51.77±25.52 kPa; lat heel, 126.00±20.46 and 102.08±23.87 kPa). [Conclusion] After performance of the spinal stabilization exercises subjects’ overall plantar pressures were reduced, which may suggest that physical balance improved.
A Comparison of Elman and Radial Basis Function (RBF) Neural Networks in Optimization of Fuzzy outputs for Epilepsy Risk Levels Classification from EEG Signals

In this paper; we investigate the optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals using two categories (Recurrent &Non Recurrent) of neural networks. The fuzzy techniques are applied as a first level classifier to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Elman neural network (with error Back propagation training) & Radial Basis Function (RBF) neural network are identified as post classifiers on the classified data to obtain the optimized risk level that characterizes the patient's epilepsy risk level. The Performance Index (PI) and Quality Value (QV) are calculated for the above methods. A group of ten patients with known epilepsy findings are used in this study. High PI such as 97.87 %, and 98.92% was obtained at QV's of 23.31, and 23.98 in Elman and RBF neural network optimization when compared to the value of 40% and 6.25 through fuzzy techniques respectively. We find that the RBF (Non Recurrent) neural network out performs Elman Network in optimizing the epilepsy risk levels.
An Anytime Algorithm for Finding the ?-Core in Nontransferable Utility Coalitional Games

We provide the first anytime algorithm for finding the e-core in a nontransferable utility coalitional game. For a given set of possible joint actions, our algorithm calculates e, the maximum utility any agent could gain by deviating from this set of actions. If e is too high, our algorithm searches for a subset of the joint actions which leads to a smaller e. Simulations show our algorithm is more efficient than an exhaustive search by up to 2 orders of magnitude.
Why Philosophers, Social Scientists, and Lawyers Think Differently about Property Rights

Property is a powerful concept. It features prominently in academic and public discourse. But it is also a source of ongoing confusion. While some of this disarray may be attributed to the success of “disintegrative�? normative agendas, much of it is the result of a methodological and conceptual disconnect both within and among different fields of study. Aimed at narrowing this gap, this Article analyzes the transformation of property from a moral and social concept into a legal construct. It seeks not to develop a historical or intellectual account of such an evolution, but to analyze the institutional and structural features of property once it is incorporated into the legal realm. The Article identifies the unique jurisprudential ingredients of a system of rules by which society allocates, governs, and enforces rights and duties among persons in relation to resources. It examines the work of decision-making institutions entrusted with the task of designing property norms over time. Clarifying the institutional and structural attributes of property does not require, however, adhering to a uniform body of substantive norms or to a single set of underlying values. Illuminating the construction of property allows rather for a better informed debate about the socially-desirable content of property rights.
DECENTRALIZED VARIATIONAL CLUSTERING ALGORITHM FOR TARGET TRACKING IN HYBRID SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION

In target tracking, Wireless Sensor Networks are used to track the target to find its mobility of the nodes in order to improve the performance of the network. In the existing system, target tracking is done with the help of static sensor nodes with few dynamic nodes. The terms like velocity and acceleration are considered for predicting the next position of the target. In order to predict the precise information of the target’s next position, in addition to the velocity and acceleration, parameters like direction and angle of direction of the target are also considered in the proposed system. The proposed method is described in two phases namely: Estimation and Prediction phase using interval theory. Further, the relocating of nodes employs the Ant Colony Optimization Algorithm. In the proposed system, static nodes ensures that coverages of the sensing area and dynamic nodes to assure the prediction of the target. Once the target next position is predicted that allowing the mobile sensor nodes to move nearer to the target. Using Particle Swarm Optimization, cluster formation takes place and the sensed information is being transmitted to the Base Station. The proposed system assures that, the minimum estimation time of the target with minimal error. Using Ns-2 simulator, the proposed system is simulated and the performance are compared with the existing system.
Development of Genomic Resources in the Species of Trifolium L. and Its Application in Forage Legume Breeding

Clovers (genus Trifolium) are a large and widespread genus of legumes. A number of clovers are of agricultural importance as forage crops in grassland agriculture, particularly temperate areas. White clover (Trifolium repens L.) is used in grazed pasture and red clover (T. pratense L.) is widely cut and conserved as a winter feed. For the diploid red clover, genetic and genomic tools and resources have developed rapidly over the last five years including genetic and physical maps, BAC (bacterial artificial chromosome) end sequence and transcriptome sequence information. This has paved the way for the use of genome wide selection and high throughput phenotyping in germplasm development. For the allotetraploid white clover progress has been slower although marker assisted selection is in use and relatively robust genetic maps and QTL (quantitative trait locus) information now exist. For both species the sequencing of the model legume Medicago truncatula gene space is an important development to aid genomic, biological and evolutionary studies. The first genetic maps of another species, subterranean clover (Trifolium subterraneum L.) have also been published and its comparative genomics with red clover and M. truncatula conducted. Next generation sequencing brings the potential to revolutionize clover genomics, but international consortia and effective use of germplasm, novel population structures and phenomics will be required to carry out effective translation into breeding. Another avenue for clover genomic and genetic improvement is interspecific hybridization. This approach has considerable potential with regard to crop improvement but also opens windows of opportunity for studies of biological and evolutionary processes.
Mono- and oligochromatic extreme-mass ratio inspirals

The gravitational capture of a stellar-mass object by a supermassive black hole represents a unique probe of warped spacetime. The small object, typically a stellar-mass black hole, describes a very large number of cycles before crossing the event horizon. Because of the mass difference, we call these captures extreme-mass ratio inspirals (EMRIs). Their merger event rate at the Galactic Centre is negligible, but the amount of time spent in the early inspiral is not. Early EMRIs (E-EMRIs) spend hundreds of thousands of years in band during this phase. At very early stages, the peak of the frequency will not change during an observational time. At later stages, it will change a bit and finally the EMRI explores a wide range of them when it is close to merger. We distinguish between ``monocromatic'' E-EMRIs, which do not change their (peak) frequency, oligochromatic E-EMRIs, which explore a short range and polychromatic ones, the EMRIs which have been discussed so far in the literature. We derive the number of E-EMRIs at the Galactic Centre, and their signal-to-noise ratios (SNR) and perform a study of parameter extraction. We show that parameters such as the spin and the mass can be extracted with an error which can be as small as $10^{-11}$ and $10^{-5}\,M_{\odot}$. There are between hundreds and thousands of E-EMRIs in their monochromatic stage at the GC, and tens in their oligochromatic phase. The SNR ranges from a minimum of $10$ (larger likelihood) to a maximum of $10^6$ (smaller likelihood). Moreover, we derive the contribution signal corresponding to the incoherent sum of continuous with two representatives masses; $10\,M_{\odot}$ and $40\,M_{\odot}$ and show that their curves will cover a significant part of LISA's sensitivity curve. Depending on their level of circularisation, they might be detected as individual sources or form a foreground population.
Factores asociados a la satisfacción de vida de adultos mayores de 60 años en Lima-Perú

One hundred twenty two older adults were interviewed at Lima city with the porpoise of identify main factors associated to life satisfaction. For this, it was built a seven levels scale (resentment, satisfaction of life, older adult punishment, dependence by disability, social support, prosocial friendly identity, antisocial friendly identity). The results pointed out that socio demographic features of sample was similar to the national and international older adults population. By other hand, it was found that interviewed old people has a high life satisfaction; nevertheless they point out to have a high level of dissatisfaction en aspects such as body weakness, feelings of been given up by relatives and loneliness or been hopeless. In addition, it was found that resentment was the first factor associated to life satisfaction, follow by level of instruction, received social support, psychoactive substances consumption, family ill treating and friendly amount.
Properties and intracellular localization of calpain activator protein.

In this paper, we have further analyzed the properties of calpain activator (CA) in order to better define its physiological function. The activator shows a pH optimum approximately 7.8-8.0, independently of the nature of the buffer used. Although the maximal activity is observed with human acid-denatured globin, the effect of CA is detectable with other protein substrates, such as casein and insulin. A comparable activating effect is observed also with the synthetic substrate Succ-Leu-Tyr-AMC. The activatory effect has been evaluated in a reconstructed system, using plasma membrane Ca(2+)-ATPase as substrate. CA is localized in erythrocyte precursor cells on the inner surface of the plasma membrane in very high amount and its level profoundly decreases up to 10% of the original value when cells reach the terminal differentiated state.
Stress, monoamines, and cognitive flexibility

Stress has been implicated in psychiatric disorders that are characterized by impaired executive function, which is mediated by the prefrontal cortex (PFC). The stress-related neuropeptide, corticotropin-releasing factor (CRF) regulates monoamine systems that project to the PFC, including the locus coeruleus norepinephrine (LC-NE) system and the dorsal raphe-serotonin (DRN-5-HT) system. CRF actions on these systems may underlie cognitive symptoms of stress-related disorders. The age at which stress occurs can determine its impact, and adolescent stress has been linked to adult psychopathology. This dissertation explores the role of CRF in stress-induced modulation of the LC-NE and DRN-5-HT systems and the developmental time course of the impact of stress on PFC-dependent cognitive function using attentional setshifting tasks, microdialysis, and immunohistochemistry. CRF microinfusion into the LC and DRN produced dose-dependent effects on distinct cognitive functions. Low doses CRF in the LC facilitated set-shifting and increased c-fos expression in the PFC. In contrast, high doses of CRF in the LC facilitated reversal learning, suggesting that mild and severe stress affect different cognitive processes through LC-PFC projections. In the DRN, CRF facilitated set-shifting at a dosage that decreased 5-HT levels in the PFC. This effect switched to facilitation of reversal learning in a defeat-resistant subpopulation of rats exposed to social stress, underscoring the importance of stress history and coping strategy in determining the impact of stress. Finally, adolescent social stress produced an enduring impairment of cognitive flexibility that was seen in adulthood and occurred selectively in rats that resisted social defeat, further reinforcing the importance of coping style in the consequences of stress. Together these studies demonstrate how CRF modulation of monoamine systems can affect cognitive flexibility in ways that are adaptive for dealing with acute stress. They also show the importance of stress history, coping style, and age at which stress occurs as determinants of the impact of stress on cognition. This research may lead to the development of novel, individualized monoamine-targeted treatments for individuals suffering from stress-related cognitive impairments that may be related to the etiology of a diverse range of psychiatric disorders. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience First Advisor Rita J. Valentino
Weakly Supervised Multiclass Video Segmentation

The desire of enabling computers to learn semantic concepts from large quantities of Internet videos has motivated increasing interests on semantic video understanding, while video segmentation is important yet challenging for understanding videos. The main difficulty of video segmentation arises from the burden of labeling training samples, making the problem largely unsolved. In this paper, we present a novel nearest neighbor-based label transfer scheme for weakly supervised video segmentation. Whereas previous weakly supervised video segmentation methods have been limited to the two-class case, our proposed scheme focuses on more challenging multiclass video segmentation, which finds a semantically meaningful label for every pixel in a video. Our scheme enjoys several favorable properties when compared with conventional methods. First, a weakly supervised hashing procedure is carried out to handle both metric and semantic similarity. Second, the proposed nearest neighbor-based label transfer algorithm effectively avoids overfitting caused by weakly supervised data. Third, a multi-video graph model is built to encourage smoothness between regions that are spatiotemporally adjacent and similar in appearance. We demonstrate the effectiveness of the proposed scheme by comparing it with several other state-of-the-art weakly supervised segmentation methods on one new Wild8 dataset and two other publicly available datasets.
Transitive Hashing Network for Heterogeneous Multimedia Retrieval

Hashing is widely applied to large-scale multimedia retrieval due to the storage and retrieval efficiency. Cross-modal hashing enables efficient retrieval of one modality from database relevant to a query of another modality. Existing work on cross-modal hashing assumes that heterogeneous relationship across modalities is available for learning to hash. This paper relaxes this strict assumption by only requiring heterogeneous relationship in some auxiliary dataset different from the query or database domain. We design a novel hybrid deep architecture, transitive hashing network (THN), to jointly learn cross-modal correlation from the auxiliary dataset, and align the data distributions of the auxiliary dataset with that of the query or database domain, which generates compact transitive hash codes for efficient cross-modal retrieval. Comprehensive empirical evidence validates that the proposed THN approach yields state of the art retrieval performance on standard multimedia benchmarks, i.e. NUS-WIDE and ImageNet-YahooQA.
Sociolinguistic approaches to language change : phonology.

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The Beetle and BeeDiff tutoring systems

We describe two tutorial dialogue systems that adapt techniques from task-oriented dialogue systems to tutorial dialogue. Both systems employ the same reusable deep natural language understanding and generation components to interpret students' written utterances and to automatically generate adaptive tutorial responses, with separate domain reasoners to provide the necessary knowledge about the correctness of student answers and hinting strategies. We focus on integrating the domain-independent language processing components with domain-specific reasoning and tutorial components in order to improve the dialogue interaction, and present a preliminary analysis of BeeDiff's evaluation. Index Terms: tutoring systems, dialogue, deep processing
Spadafore-Attention Deficit Hyperactivity Disorder Rating Scale: A New Instrument.

AUTHOR Spadafore, Gerald J.; Spadafore, Sharon J. TITLE Spadafore-Attention Deficit Hyperactivity Disorder Rating Scale: A New Instrument. PUB DATE 1997-04-04 NOTE 23p. ; Paper presented at the Annual Meeting of the National Association of School Psychologists (Anaheim, CA, April 2-5, 1997). PUB TYPE Speeches/Meeting Papers (150) Tests/Questionnaires (160) EDRS PRICE MF01/PC01 Plus Postage. DESCRIPTORS *Attention Deficit Disorders; *Clinical Diagnosis; Elementary Secondary Education; Evaluation Methods; Hyperactivity; Interpersonal Competence; Questionnaires; Rating Scales IDENTIFIERS Impulsiveness