Miracle-dz/UniFAR-FTUs huggingface dataset:
Lipoteichoic acid from Staphylococcus aureus reduces renal ischemia/reperfusion injury.

BACKGROUND The aim of this study was to investigate whether in vivo administration of a low, sub-lethal dose of lipoteichoic acid (LTA), a bacterial wall-fragment derived from the Gram-positive bacterium Staphylococcus aureus, protects the kidney against the renal dysfunction and injury caused by ischemia/reperfusion (I/R). METHODS Male Wistar rats were administered LTA from S. aureus (1 mg/kg, IP). After 24 hours, rats were subjected to bilateral renal ischemia (45 min) followed by reperfusion (6 h). Serum and urinary markers were measured for the assessment of renal function, tubular and reperfusion-injury. Renal sections were used for histological grading of renal injury and for immunohistochemical localization of P-selectin, inducible nitric oxide synthase (iNOS) and nitrotyrosine (indicative of peroxynitrite formation). Kidney myeloperoxidase (MPO) activity and malondialdehyde (MDA) levels were measured for assessment of polymorphonuclear (PMN) cell infiltration and lipid peroxidation, respectively. Nitric oxide (NO) production was determined by measurement of plasma nitrite/nitrate levels. RESULTS LTA pretreatment significantly reduced renal dysfunction, tubular and reperfusion-injury caused by I/R of the kidney as well as histological evidence of renal injury. LTA also reduced the expression of P-selectin and kidney MPO activity associated with renal I/R. MDA levels were significantly reduced by LTA pretreatment suggesting a reduction in the lipid peroxidation and formation of reactive oxygen species (ROS). LTA pretreatment also markedly reduced both the expression of iNOS and the formation of nitrotyrosine associated with renal I/R. Although LTA significantly reduced plasma nitrite/nitrate levels associated with I/R, nitrite/nitrate levels remained at levels significantly higher than that measured from the plasma obtained from Sham-operated animals. CONCLUSIONS These data suggest, to our knowledge for the first time, that LTA pretreatment for 24 hours significantly reduces renal I/R injury. We propose that the mechanism of the protective effect involves reduction of the production of NO, ROS and peroxynitrite subsequent to reduced P-selectin and iNOS expression and PMN recruitment. However, although LTA pretreatment resulted in a reduction of iNOS expression and NO production, we hypothesize that the remaining significant levels of NO contribute to the beneficial actions provided by LTA.
On Conceptual Indexing for Data Summarization

A summary is a comprehensive description that grasps the essence of a subject. A text, a collection of text doc- uments, a query answer can be summarized by simple means such as an automatically generated list of the most frequent words or "advanced" by a meaningful textual description of the subject. In between these two extremes are summaries by means of selected concepts exploiting background knowledge providing selected key concepts. We address in this paper an approach where conceptual summaries are provided through a conceptualization as given by an ontology. The idea is to re- strict a background ontology to the set of concepts that appears in the text to be summarized and thereby provide a structure, a so-called instantiated ontology, that is specific to the domain of the text and can be used to condense to a summary not only quantitatively but also conceptually covers the subject of the text.
Robustness and Separation in Multidimensional Screening

A principal wishes to screen an agent along several dimensions of private information simultaneously. The agent has quasilinear preferences that are additively separable across the various components. We consider a robust version of the principal's problem, in which she knows the marginal distribution of each component of the agent's type, but does not know the joint distribution. Any mechanism is evaluated by its worst‐case expected profit, over all joint distributions consistent with the known marginals. We show that the optimum for the principal is simply to screen along each component separately. This result does not require any assumptions (such as single crossing) on the structure of preferences within each component. The proof technique involves a generalization of the concept of virtual values to arbitrary screening problems. Sample applications include monopoly pricing and a stylized dynamic taxation model.
Short Segment versus Long Segment Pedicle Screws Fixation in Management of Thoracolumbar Burst Fractures: Meta-Analysis

Posterior pedicle screw fixation has become a popular method for treating thoracolumbar burst fractures. However, it remains unclear whether additional fixation of more segments could improve clinical and radiological outcomes. This meta-analysis was performed to evaluate the effectiveness of fixation levels with pedicle screw fixation for thoracolumbar burst fractures. MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, Springer, and Google Scholar were searched for relevant randomized and quasirandomized controlled trials that compared the clinical and radiological efficacy of short versus long segment for thoracolumbar burst fractures managed by posterior pedicle screw fixation. Risk of bias in included studies was assessed using the Cochrane Risk of Bias tool. Based on predefined inclusion criteria, Nine eligible trials with a total of 365 patients were included in this meta-analysis. Results were expressed as risk difference for dichotomous outcomes and standard mean difference for continuous outcomes with 95% confidence interval. Baseline characteristics were similar between the short and long segment fixation groups. No significant difference was identified between the two groups regarding radiological outcome, functional outcome, neurologic improvement, and implant failure rate. The results of this meta-analysis suggested that extension of fixation was not necessary when thoracolumbar burst fracture was treated by posterior pedicle screw fixation. More randomized controlled trials with high quality are still needed in the future.
The AMD Opteron Northbridge Architecture

To increase performance while operating within a fixed power budget, the AMD opteron processor integrates multiple times86-64 cores with a router and memory controller. AMD's experience with building a wide variety of system topologies using Opteron's hypertransport-based processor interface has provided useful lessons that expose the challenges to be addressed when designing future system interconnect, memory hierarchy, and I/O to scale with both the number of cores and sockets in future times86-64 CMP architectures.
Displacement of the Endotracheal Tube Caused by Change of Head Position in Pediatric Anesthesia: Evaluation by Fiberoptic Bronchoscopy

Displacement of the endotracheal tube (ETT) caused by flexion and extension of the neck and the placement of a tongue depressor was investigated in 10 small children between the ages of 16 and 19 mo by means of a fiberoptic bronchoscope.The ETT tip moved a mean distance of 0.9 cm toward the carina with flexion and 1.7 cm toward the vocal cords with extension of the neck. After the placement of a tongue depressor, the ETT tip, which had once moved toward the vocal cords with neck extension, was displaced a mean distance of 1.2 cm toward the carina. Our results demonstrate that endobronchial intubation and accidental extubation could occur after significant changes of the head position and careless placement of a tongue depressor in small children. (Anesth Analg 1996;82:251-3)
Ambiguity and Unknown Term Translation in CLIR

In this paper we present a report on our participation in the CLEF Chinese-English ad hoc bilingual track, and we discuss a disambiguation strategy which employs a modified co-occurrence model to determine the most appropriate translation for a given query. This strategy is used alongside a pattern-based translation extraction method which addresses the ‘unknown term’ translation problem. Experimental results demonstrate that a combination of these two techniques substantially improves retrieval effectiveness when compared to various baseline systems that employ basic co-occurrence measures or make no provision for out-of-vocabulary terms.
Context-Aware Computing: Opportunities and Open Issues

A 2011 Gartner report [3] describes context-aware computing as a game-changing opportunity for enterprises to improve both productivity and profits. Context-aware computing is about making applications and content more relevant to a user's context, e.g., when and where the user is, thereby improving user experience. For instance, a coupon delivered to a user at a wrong time or at a wrong location is considered a nuisance. On the contrary, receiving a timely, usable coupon before purchasing a merchandise is a treat. Context-aware computing is not a new concept, but the ongoing mobile revolution makes it both necessary and feasible. • Necessary because the mobile phone display is small and information must be delivered with much higher relevance and precision to meet user needs. • Feasible because small, light-weight mobile devices allow users to almost always carry them around, and much can be learned via a phone about its user's habits and states. Context-aware computing involves first acquiring context and then taking context-dependent actions. For instance, a phone can sense a user's location and turn off its GPS unit to conserve power when the user enters a building, or it can collect EKG signals of a user and trigger an alert if the user's heart beats irregularly. Similarly, a restaurant can send a coupon to a user when that user is queued up in front of a nearby restaurant. The useful context can be divided into three categories: information on the user (knowledge of habits, emotional state, biophysiological conditions), the user's environment (time, location, co-location of others, social interaction), and the user's tasks (transportation mode, engaged tasks, general goals) [4]. Context-aware computing can be applied to benefit applications in many areas including but not limited to information retrieval, facility management, productivity enhancement, in addition to the aforementioned three examples representing power management, health care, and commerce, respectively.
Can the higher risk of disability onset among older people who live alone be alleviated by strong social relations? A longitudinal study of non-disabled men and women.

PURPOSE to investigate if the increased risk of disability onset among older people who live alone could possibly be moderated by either high social participation or by being satisfied with the social relations. DESIGN AND METHODS logistic regression models were tested using two waves in a study population of 2,697 non-disabled older men and women from The Danish Longitudinal Study on Preventive Home Visits. RESULTS living alone and low social participation were significant risk factors for later male disability onset. Not being satisfied with the social relations was significantly associated with onset of disability for both genders. Among men who lived alone low social participation was a significant predictor of disability onset [odds ratio, OR = 2.30 (1.00-5.29)]; for cohabiting men social participation was not associated with disability onset, [adjusted OR = 0.91 (0.49-1.71)]. Similar results were present concerning satisfaction with the social relations among men. There was no significant interaction for women. CONCLUSIONS the study suggests that men who live alone can possibly alleviate their risk of disability onset by being socially active and by having access to satisfactory social relations. Women do not seem to benefit as much from cohabitation as men, although women who live alone and who are not satisfied with their social relations also constitute a significant risk category.
Vaccination with ant‐idiotype antibodies mimicking a renal cell carcinoma‐associated antigen induces tumor immunity

We have previously isolated and characterized 6 different internal image mouse monoclonal anti‐idiotype antibodies (Ab2) directed against the paratope of mouse monoclonal antibody G250 (MAbG250, Abl), which specifically reacts with human renal cell carcinoma (RCC). These Ab2s (NUH31,44,51, 71,82 and 91) demonstrated specificity for the combining site of AbI, and appeared to recognize 2 partly overlapping idiotopes on AbI. In this study, we further characterize the fine specificity of the Ab2, investigate whether the immunogenicity of Ab2 could be enhanced by conjugation to a carrier and investigate the anti‐tumor efficacy of Ab3 sera in mice challenged with RCC. Immunization of animals with Ab2 conjugated to keyhole limpet hemocyanin as carrier protein resulted in a 2‐fold increase in antigen‐specific anti‐anti‐idiotype antibodies (Ab3) as compared with immunization using Ab2 alone. Specific reactivity was observed with antigen‐positive cell lysates, and all Ab3 sera contained immunoglobulin resembling AbI (Abl), as shown by competitive AbI ‐antigen binding assays. Fine‐specificity studies of Ab3 sera revealed that the Ab2s can be divided into 4 mutually exclusive groups, showing that the 6 Ab2s recognize 4 slightly different idiotopes in the Abl binding pocket. Treatment of RCC‐challenged mice with Ab3 sera resulted in significant tumor growth inhibition and lower tumor take rates as compared with control groups. Ab3 sera obtained from NUH‐91‐immunized animals showed superior characteristics as compared to the other Ab3 sera: no tumors remained after 5 weeks of Ab3‐NUH91 treatment. Our findings indicate that the Ab2 elicit powerful anti‐tumor effects in immune‐competent animals.
A vertebrate RNA‐binding protein Fox‐1 regulates tissue‐specific splicing via the pentanucleotide GCAUG

Alternative splicing is one of the central mechanisms that regulate eukaryotic gene expression. Here we report a tissue‐specific RNA‐binding protein, Fox‐1, which regulates alternative splicing in vertebrates. Fox‐1 bound specifically to a pentanucleotide GCAUG in vitro. In zebrafish and mouse, fox‐1 is expressed in heart and skeletal muscles. As candidates for muscle‐specific targets of Fox‐1, we considered two genes, the human mitochondrial ATP synthase γ‐subunit gene (F1γ) and the rat α‐actinin gene, because their primary transcripts contain several copies of GCAUG. In transfection experiments, Fox‐1 induced muscle‐specific exon skipping of the F1γ gene via binding to GCAUG sequences upstream of the regulated exon. Fox‐1 also regulated mutually exclusive splicing of the α‐actinin gene, antagonizing the repressive effect of polypyrimidine tract‐binding protein (PTB). It has been reported that GCAUG is essential for the alternative splicing regulation of several genes including fibronectin. We found that Fox‐1 promoted inclusion of the fibronectin EIIIB exon. Thus, we conclude that Fox‐1 plays key roles in both positive and negative regulation of tissue‐specific splicing via GCAUG.
Complicated Dual Diagnosis: A Case for Physician Involvement in Addictions Treatment

Despite the high prevalence of substance use disorders, the prevention and treatment of such illnesses seem to receive little attention during physician training. This provides cause for concern, as physician involvement in addiction treatment has been relatively sparse. We present the case of a patient whose successful treatment likely relied upon her physicians' intensive training in each of the biological, psychological, and social aspects of her clinical presentation. The case illustrates the need for added emphasis on the assessment and treatment of addictive disorders during medical training, and for more active physician involvement in addictions treatment.
Cultural differences in American and Mexican mother-child pretend play

Toddler-age children's play with their mothers (n = 60) was videotaped in the U.S. and Mexico. Episodes were examined for pretend play, mutual involvement in social play, joint involvement in cooperative social pretend play, and maternal play behaviors. Contextual features were observed, recorded, and analyzed using an activity setting model. Mothers were interviewed about their value of children's play behavior
Weighted Flow and Spectral Resource to Enhance QoS for Multi-hop Cognitive Radio Networks

The flow with different service levels and path lengths requires different amount of spectral resource for data transmission. Different spectral bands possess different occupied rates to be available for secondary users (SUs). This work addresses the priority issues of both flow and spectral bands to achieve transmission delay fairness. The available bands are different link-by-link so that how to allocate these bands for the different services flows is a challenge issue. This work addresses the resource allocation based on priority constraints to achieve the delay bias of each packet within interference range equivalent for each cycle. To utilize spectral bands optimally, we ormulate the spectral bands allocation problem with interference and interrupt rate. The problem is solved by the proposed metric in a distributed fashion. We also proposed a heuristic algorithm to approximately solve it. The related standard algorithms are also included in the experiment to evaluate the proposed metric and heuristic.
3-D facial expression representation using statistical shape models

Facial expressions are visible signs of person's affective state, cognitive activity and personality. Automatic recognition of facial expressions is an important component for a wide spectrum of applications including human-computer interfaces, video conferencing, augmented reality and human activity monitoring to mention a few. Facial expression representation is an essential part in the automatic recognition of facial expressions. It is concerned with finding distinguishable features that can be utilised for representing different facial expressions without constraints of age, ethnicity or gender. This thesis reports on research and development in the facial expression representation. The author has proposed two novel methods for representing facial expressions. One is based on the shape space vector (SSV) of the statistical shape model (SSM); the other is based on the SSV of the B-spline statistical shape model (BSSM). The first proposed method uses the SSV of the SSM as a significant feature for representing facial expressions embedded in 3-D facial surfaces. In order to obtain the SSV, a novel model-based surface registration method is proposed that iteratively deforms and matches the model to an unseen new facial surface. Two major stages are included in this method, namely, model building and model fitting. In the model building stage, a SSM is built by using a training data set with estimated correspondences. In the model fitting stage, the built model is adapted to represent the shape of the new facial surface, which has not been included in the training data set. To build the model, the thin plate spline warping has been used so that all of the facial surfaces in the training data set are aligned into a common reference facial surface and the dense correspondences of points between these facial surfaces can be calculated. To fit the model to the new facial surface a modified iterative closest point (ICP) algorithm and least-squares projection on to the estimated shape space, constructed using the training data set, are applied. The second proposed method uses the SSV of the BSSM for facial expression representation. The mddel is built using B-spline control points instead of the surface points as in the SSM based method. In order to obtain the control points of B-spline, a novel method for the B-spline surface fitting has been proposed. The robustness and efficiency of both model-based facial expression representation methods are improved by introducing a multi-resolution scheme in the model fitting stage. The experimental results on simulated and real 3-D facial surfaces show that the proposed methods can effectively provide distinguishable features for facial expression analysis and recognition.
Accounting for the Distribution of Income in the U.S. National Accounts

The views expressed in this research, including those related to statistical, methodological, technical, or operational issues, are solely those of the authors and do not necessarily reflect the official positions or policies of the Census Bureau or the Bureau of Economic Analysis, or the views of other staff members. The authors accept responsibility for all errors. This paper is released to inform interested parties of ongoing research and to encourage discussion of work in progress.
Tracking concept drift in malware families

The previous efforts in the use of machine learning for malware detection have assumed that malware population is stationary i.e. probability distribution of the observed characteristics (features) of malware populations don't change over time. In this paper, we investigate this assumption for malware families as populations. Malware, by design, constantly evolves so as to defeat detection. Evolution in malware may lead to a nonstationary malware population. The problem of nonstationary populations has been called concept drift in machine learning. Tracking concept drift is critical to the successful application of ML based methods for malware detection. If the evolution causes the malware population to drift rapidly then frequent retraining of classifiers may be required to prevent degradation in performance. On the other hand, if the drift is found to be negligible, then ML based methods are robust for such populations for long periods of time. We propose two measures for tracking concept drift in malware families when feature sets are very large-relative temporal similarity and metafeatures. We illustrate the use of the proposed measures with a study on 3500+ samples from three families of x86 malware, spanning over 5 years. The results of the study show negligible drift in mnemonic 2-grams extracted from unpacked versions of the samples. The measures can likewise be applied to track drift in any number of malware families. Tracking drift in this manner also provides a novel method for feature type selection, i.e., use the feature type that drifts the least.
Enhancing MapReduce via Asynchronous Data Processing

The Map Reduce programming model simplifies large-scale data processing on commodity clusters by having users specify a map function that processes input key/value pairs to generate intermediate key/value pairs, and a reduce function that merges and converts intermediate key/value pairs into final results. Typical Map Reduce implementations such as Hadoop enforce barrier synchronization between the map and reduce phases, i.e., the reduce phase does not start until all map tasks are finished. In turn, this synchronization requirement can cause inefficient utilization of computing resources and can adversely impact performance. Thus, we present and evaluate two different approaches to cope with the synchronization drawback of existing Map Reduce implementations. The first approach, hierarchical reduction, starts a reduce task as soon as a predefined number of map tasks completes, it then aggregates the results of different reduce tasks following a tree structure. The second approach, incremental reduction, starts a predefined number of reduce tasks from the beginning and has each reduce task incrementally reduce records collected from map tasks. Together with our performance modeling, we evaluate different reducing approaches with two real applications on a 32-node cluster. The experimental results have shown that incremental reduction outperforms hierarchical reduction in general. Also, incremental reduction can speed-up the original Hadoop implementation by up to 35.33% for the word count application and 57.98% for the grep application. In addition, incremental reduction outperforms the original Hadoop in an emulated cloud environment with heterogeneous compute nodes.