Miracle-dz/UniFAR-FTUs huggingface dataset:
Software.zhishi.schema: A Software Programming Taxonomy Derived from Stackoverflow

In this paper, we are the first to construct a software programming taxonomy from Stackoverflow. More precisely, we propose a machine learning based method with novel features to capture the hierarchical semantic structure of tags in Stackoverflow. A graph pruning algorithm is applied to eliminate the conflicts by constructing a Directed Acyclic Graph (DAG). As a result, our dataset, named Software.zhishi. schema, contains 38,205 concepts together with 36,249 subsumption relations. In order to further test the usability of our published data, we adopt a similarity computing task of words from software programming which is one of the most fundamental tasks in the software repository mining area. The results show that our dataset can outperform other knowledge bases due to its high coverage with finergrained domain concepts.
Differences in Clinical Presentation Between Depressed Outpatients Wanting versus Not Wanting Treatment for Comorbid Social Anxiety Disorder

Patients with comorbid major depressive disorder (MDD) and social anxiety disorder (SAD) demonstrate greater severity of symptoms and functional impairment compared with patients with either disorder alone. However, no known studies have examined what differentiates patients who do and do not want treatment for comorbid SAD in addition to MDD. The aim of the current study was to examine clinical characteristics (e.g., variables related to depression and social anxiety severity) of patients who did versus did not desire treatment for comorbid SAD. Results showed that patients who desired treatment for comorbid SAD reported a greater number of social fears and poorer work and current social functioning compared with patients who did not desire treatment for SAD. Work functioning and number of social fears remained significant after controlling for depression and overall illness severity. Results suggest that future treatments adapted for comorbid MDD and SAD perhaps should target work functioning and a broad range of social fears.
Multimerization of the Receptor Activator of Nuclear Factor-κB Ligand (RANKL) Isoforms and Regulation of Osteoclastogenesis*

The receptor activator of nuclear factor-κB ligand (RANKL), a member of the tumor necrosis factor family, is a transmembrane protein, which is known as an essential initiation factor of osteoclastogenesis. Previously, we identified three RANKL isoforms. RANKL1 was identical to the originally reported RANKL. RANKL2 had a shorter intracellular domain. RANKL3 did not have the intracellular or transmembrane domains and was suggested to act as a soluble form protein. Here, we show that RANKL forms homo- or heteromultimers. NIH3T3 cells transfected with RANKL1 or RANKL2 form mononuclear tartrate-resistant acid phosphatase-positive preosteoclasts in an in vitro osteoclastogenesis assay system. Coexpression of RANKL1 and RANKL2 induces multinucleated osteoclasts. RANKL3 has no effect on the formation of preosteoclasts or osteoclasts but significantly inhibits fusion of preosteoclasts when coexpressed with RANKL1 and RANKL2. These findings imply the presence of multiple multimeric structures of RANKL, which may regulate bone metabolism.
Effect of failure/success feedback and the moderating influence of personality on reward motivation

While motivation to pursue goals is often assumed to be a trait-like characteristic, it is influenced by a variety of situational factors. In particular, recent experiences of success or failure, as well as cognitive responses to these outcomes, may shape subsequent willingness to expend effort for future rewards. To date, however, these effects have not been explicitly tested. In the present study, 131 healthy individuals received either failure or success feedback on a cognitive task. They were then instructed to either ruminate or distract themselves from their emotions. Finally, they completed the Effort Expenditure for Rewards Task, a laboratory measure of reward motivation. Results indicate that participants who received failure feedback relied more strongly on the reward magnitude when choosing whether to exert greater effort to obtain larger rewards, though this effect only held under conditions of significant uncertainty about whether the effort would be rewarded. Further, participants with high levels of trait inhibition were less responsive to reward value and probability when choosing whether to expend greater effort, results that echo past studies of effort-based decision-making in psychological disorders.
Adaptive sharpening of multimodal distributions

In this work we derive a novel framework rendering measured distributions into approximated distributions of their mean. This is achieved by exploiting constraints imposed by the Gauss-Markov theorem from estimation theory, being valid for mono-modal Gaussian distributions. It formulates the relation between the variance of measured samples and the so-called standard error, being the standard deviation of their mean. However, multi-modal distributions are present in numerous image processing scenarios, e.g. local gray value or color distributions at object edges, or orientation or displacement distributions at occlusion boundaries in motion estimation or stereo. Our method not only aims at estimating the modes of these distributions together with their standard error, but at describing the whole multi-modal distribution. We utilize the method of channel representation, a kind of soft histogram also known as population codes, to represent distributions in a non-parametric, generic fashion. Here we apply the proposed scheme to general mono- and multimodal Gaussian distributions to illustrate its effectiveness and compliance with the Gauss-Markov theorem.
Highly Concurrent Stream Synchronization in Many-core Embedded Systems

Embedded many-core architectures are expected to serve as significant components in the infrastructure of upcoming technologies like networks for the Internet of Things (IoT), facing real-time and stream processing challenges. In this work we explore the applicability of ScaleGate, a synchronization object from the massive data stream processing domain, on many-core embedded systems. We propose a new implementation of ScaleGate on the Epiphany architecture, a scalable embedded many-core co-processor, and study communication patterns that appear in the context of a baseband signal processing application. Our experimental evaluation shows significant improvements over standard barrier-based approaches, due to the asynchrony exploited by the use of ScaleGate.
Multiactive objects and their applications

In order to tackle the development of concurrent and distributed systems, the active object programming model provides a high-level abstraction to program concurrent behaviours. There exists already a variety of active object frameworks targeted at a large range of application domains: modelling, verification, efficient execution. However, among these frameworks, very few consider a multi-threaded execution of active objects. Introducing controlled parallelism within active objects enables overcoming some of their limitations. In this paper, we present a complete framework around the multi-active object programming model. We present it through ProActive, the Java library that offers multi-active objects, and through MultiASP, the programming language that allows the formalisation of our developments. We then show how to compile an active object language with cooperative multi-threading into multi-active objects. This paper also presents different use cases and the development support to illustrate the practical usability of our language. Formalisation of our work provides the programmer with guarantees on the behaviour of the multi-active object programming model and of the compiler.
Cloning and analysis of the nuclear gene for YmL33, a protein of the large subunit of the mitochondrial ribosome in Saccharomyces cerevisiae

The N-terminal amino acid sequence of a large subunit protein, termed YmL33, of the mitochondrial ribosome of the yeast Saccharomyces cerevisiae was determined. The data were obtained to synthesize two kinds of oligonucleotide primers, which were used in the polymerase chain reaction to amplify and clone the nuclear gene for this protein. By nucleotide sequencing, the cloned gene, MRP-L33, was found to encode a basic protein of 11 kDa with 98 amino acid residues. The protein encoded by this gene appears to have no leader sequence at its N terminus. The N-terminal two-thirds of the deduced amino acid sequence showed a significant degree of sequence similarity to ribosomal protein L30 of Escherichia coli and Bacillus stearothermophilus. In addition, the C-terminal one-third showed sequence similarity, though to a lesser extent, to a yeast cytoplasmic ribosomal protein termed L16. By hybridization with the yeast chromosomes and their restriction enzyme fragments, the MRP-L33 gene was concluded to exist on chromosome XIII as a single-copy gene. Disruption of the gene by insertion of a HIS3-containing fragment showed that MRP-L33 was essential for mitochondrial function. The transcriptional level of MRP-L33 in strains with different mitochondrial genetic backgrounds was analyzed in the presence of glucose, galactose, or glycerol.
A Review on Internet of Things ( IoT ) in Healthcare

Internet of Things (IoT) rises as a powerful domain where embedded devices and sensors can connect and exchange information over the Internet. The importance of IoT devices and data can be critical, so security constraints are required to keep IoT data safe from intruders; authentication is one of basic and important means to confirm data privacy and security. The nature of IoT devices as a resource contains devices required a special authentication schema that does not consume high computing and energy resources. In this paper, a review for IoT healthcare usage and a novel authentication mechanism for IoT networks have been proposed. The architecture of reliable and secure healthcare architecture has been proposed. ECC algorithm over the CoAP protocol has been used. The proposed authentication approach provides an efficient authentication mechanism with high security.
Inflammation and Renal Function after a Four-Year Follow-Up in Subjects with Unimpaired Glomerular Filtration Rate: Results from the Observational, Population-Based CARLA Cohort

Background There is evidence that chronic inflammation is associated with the progression/development of chronic renal failure; however, relations in subjects with preserved renal function remain insufficiently understood. Objective To examine the association of inflammation with the development of renal failure in a cohort of the elderly general population. Methods After excluding subjects with reduced estimated glomerular filtration rate (eGFR<60 mL/min/1.73 m2) and missing data, the cohort incorporated 785 men and 659 women (aged 45–83 years). Follow-up was performed four years after baseline. Covariate adjusted linear and logistic regression models were used to assess the association of plasma/serum concentrations of soluble tumour necrosis factor receptor 1 (sTNF-R1), C-reactive protein (CRP), and interleukin 6 (IL-6) with change in eGFR/creatinine. The areas under the curve (AUCs) from receiver operating characteristics (ROCs) were estimated. Results In adjusted models sTNF-R1 was distinctively associated with a decline in eGFR in men (0.6 mL/min/1.73 m2 per 100 pg/mL sTNF-R1; 95% CI: 0.4–0.8), but not in women. A similar association could not be found for CRP or IL-6. Estimates of sTNF-R1 in the cross-sectional analyses were similar between sexes, while CRP and IL-6 were not relevantly associated with eGFR/creatinine. Conclusion In the elderly male general population with preserved renal function sTNF-R1 predicts the development of renal failure.
Use of DPOSS data to study globular cluster halos: an application to M 92

We exploited the large areal coverage offered by the DPOSS to analyze the outermost regions of the galactic globular cluster M 92. Two independent photometric reduction programs (SKICAT and DAOPHOT) were used to construct a color-magnitude diagram and a surface density profile for this cluster, based on J- and F-band DPOSS plates. A strong similarity has been found in the performance of the two programs in the low--crowded outermost cluster regions. After removing the background contribution, we obtained the cluster outer surface density profile down to a surface brightness magnitude of mu_V ~ 31 mag/sq.arcsec and matched it with the inner profile of Trager et al. 1995. The profile shapes match very well: since our data are uncalibrated, the shift in magnitude between the profiles has been also used to calibrate our profile. The analysis shows that the cluster has an extra tidal halo extending out to ~ 30 arcmin from the cluster center at a 3 sigma level over the background noise. This halo is revealed to be almost circular.
ON THE LIMITING PROBABILITY DISTRIBUTION OF A TRANSITION PROBABILITY TENSOR

In this paper we propose and develop an iterative method to calculate a limiting probability distribution vector of a transition probability tensor P arising from a higher-order Markov chain. In the model, the computation of such limiting probability distribution vector x can be formulated as a Z-eigenvalue problem Pxm−1 = x associated with the eigenvalue 1 of P where all the entries of x are required to be non-negative and its summation must be equal to one. This is an analog of the matrix case for a limiting probability vector of a transition probability matrix arising from the first order Markov chain. We show that if P is a transition probability tensor, then solutions of this Z-eigenvalue problem exist. When P is irreducible, all the entries of solutions are positive. With some suitable conditions of P, the limiting probability distribution vector is even unique. Under the same uniqueness assumption, the linear convergence of the iterative method can be established. Numerical examples are presented to illustrate the theoretical results of the proposed model and the iterative method.
Integrated model-driven design-space exploration for embedded systems

Embedded systems and their design trajectories are becoming increasingly complex, and there is a growing demand for performance, reliability, energy efficiency and low cost. To cope with these challenges, decision making early in the development trajectory needs to be supported by appropriate modeling and analysis. To achieve this support, we need to find the modeling abstractions that allow extensive design-space exploration, tune these modeling abstractions towards the users, and integrate support for different types of modeling and analysis.
4.5 A 2-phase resonant switched-capacitor converter delivering 4.3W at 0.6W/mm2 with 85% efficiency

In this work, we present a 2-phase ReSC converter that operates with supply voltages from 3.6 to 6V, providing compatibility for a range of applications including Li-Ion battery supplies. Figure 4.5. 2 shows the power train of the 2-phase ReSC converter. The architecture is similar to the 2:1 SC converters in [2-3], but uses inductance, L<sub>X</sub>, to resonate with the on-chip flying capacitor, C<sub>X</sub>. On-chip bypass capacitance, C<sub>bp</sub>, is used to filter the output voltage and complete the resonant loop in the energy transfer process. The timing of key signals in converter operation is shown in Fig. 4.5. 3. In normal operation at the fundamental resonant frequency, ω<sub>o</sub>=(L<sub>X</sub>C<sub>X</sub>)<sup>-1/2</sup>, resonant impedance Z<sub>X</sub> is configured in parallel with Vin-Vout in φ<sub>1</sub>; in φ<sub>2</sub>, Z<sub>X</sub> is configured in parallel with Vout. If there is a voltage difference between Vin-Vout and Vout-GND, voltage V<sub>X</sub> appears as a square wave at the resonant frequency. In φ<sub>1</sub>, a positive half wave current flows into Z<sub>X</sub>, drawing energy from Vin; in φ<sub>2</sub>, a negative half wave current flows out of Z<sub>X</sub>, supplying energy to the load. Similar to the SC topology, this process can be modeled as an effective resistance, REFF, the details of which are discussed in [6]. Operation at the fundamental mode provides the lowest achievable R<sub>EFF</sub>, which is approximately R<sub>ESR</sub>·π<sup>2</sup>/8 for the 2:1 configuration, near the minimum achievable R<sub>EFF</sub> for a comparable SC converter.
Prevalence and antimicrobial susceptibility patterns of Shigella species in Asmara, Eritrea, northeast Africa.

BACKGROUND AND PURPOSE Diarrheal diseases are an important cause of morbidity and mortality in children in developing countries. Of the bacterial causes of dysentery, Shigella are the major enteropathogens with outbreak potential and common development of antimicrobial resistance. This study determined the prevalence and antimicrobial susceptibility patterns of different spp. of Shigella in Asmara, Eritrea. METHODS Diarrheic stool specimens of a total of 2,420 children were screened for Shigella organisms over a period of 3 years using standard methods. The Shigella isolates were tested for antimicrobial susceptibility pattern by the disk diffusion method. RESULTS Of the 84 Shigella isolates, 54 were Shigella flexneri and 20 were Shigella dysenteriae type 1. High rates of resistance were observed against ampicillin, chloramphenicol, and trimethoprim-sulfamethoxazole; 6% of the S. flexneri isolates were resistant to nalidixic acid. CONCLUSION The study emphasizes the need for continuous monitoring of the occurrence of Shigella organisms and their antimicrobial susceptibility pattern for the successful treatment and control of Shigella dysentery, and also for the development of public health policy for populations at risk for shigellosis.
Selflearning Codebook Speech Enhancement

A novel speech enhancement system is presented which exploits a codebook for noise estimation. In contrast to state-of-the-art noise estimators which usually rely on the assumption that the noise signal is only slightly timevarying, codebook approaches allow also non-stationary environments. The basic concept of the proposed codebook noise estimation is a superposition of a scaled speech and noise codebook entry. In order to be independent of a priori noise knowledge, the new estimator is able to learn new noise types online. Training vectors for codebook updates are identified using a speech activity detector (VAD) and a codebook mismatch measure. The VAD is realized as part of the codebook matching. A Wiener filter or any state-of-the-art weighting rule can be applied subsequently for speech enhancement. Experiments confirmed that the new system is able to learn new noise types and provides improved performance compared to state-of-the-art algorithms.
Search Engine-Crawler Symbiosis

Web crawlers have been used for nearly a decade as a search engine component to create and update large collections of documents. Typically the crawler and the rest of the search engine are not closely integrated. If the purpose of a search engine is to have as large a collection as possible to serve the general Web community, a close integration may not be necessary. However, if the search engine caters to a specific community with shared focused interests, it can take advantage of such an integration. In this paper we investigate a tightly coupled system in which the crawler and the search engine engage in a symbiotic relationship. The crawler feeds the search engine and the search engine in turn helps the crawler to better its performance. We show that the symbiosis can help the system learn about a community’s interests and serve such a community with better focus. The search engine-crawler symbiosis is a first step toward a more general model in which we envision truly distributed, collaborative search among Web peers.
An Immaterial, Dual-sided Display System with 3D Interaction

We present an interactive wall-sized immaterial display that introduces a number of interesting possibilities for advanced interface design. The immaterial nature of a thin sheet of fog allows users to penetrate and even walk through the screen, while its dual-sided nature allows for new possibilities in multi-user faceto- face collaboration and pseudo-3D visualization.
tDAR: A Cultural Heritage Archive for Twenty-First-Century Public Outreach, Research, and Resource Management

Hundreds of thousands of archaeological investigations in the United States conducted over the last several decades have documented a large portion of the recovered archaeological record in the United States. However, if we are to use this enormous corpus to achieve richer understandings of the past, it is essential that both CRM and academic archaeologists change how they manage their digital documents and data over the course of a project and how this information is preserved for future use. We explore the nature and scope of the problem and describe how it can be addressed. In particular, we argue that project workflows must ensure that the documents and data are fully documented and deposited in a publicly accessible, digital repository where they can be discovered, accessed, and reused to enable new insights and build cumulative knowledge.
Automatic ROI Selection in Structural Brain MRI Using SOM 3D Projection

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer's disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer's Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer's disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.
Power aware page allocation

One of the major challenges of post-PC computing is the need to reduce energy consumption, thereby extending the lifetime of the batteries that power these mobile devies. Memory is a particularly important target for efforts to improve energy efficiency. Memory technology is becoming available that offers power management features such as the ability to put individual chips in any one of several different power modes. In this paper we explore the interaction of page placement with static and dynamic hardware policies to exploit these emerging hardware features. In particular, we consider page allocation policies that can be employed by an informed operating system to complement the hardware power management strategies. We perform experiments using two complementary simulation environments: a trace-driven simulator with workload traces that are representative of mobile computing and an execution-driven simulator with a detailed processor/memory model and a more memory-intensive set of benchmarks (SPEC2000). Our results make a compelling case for a cooperative hardware/software approach for exploiting power-aware memory, with down to as little as 45% of the Energy Delay for the best static policy and 1% to 20% of the Energy Delay for a traditional full-power memory.