Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Hierarchical Clustering Algorithm for Software Architecture Recovery

Recovering software architecture from a software system is a good manner to understand and maintain it, and has great significance for legacy systems whose problem is a lack of information for maintenance and evolution. Recently, many clustering algorithm have been employed for software architecture recovery. To increase the recovering accuracy and enhance the effectivity, an improved hierarchical clustering algorithm is proposed in this paper. On the basis of ScaLable Information BOttleneck (LIMBO) algorithm, our methodology is achieved by introducing more static and dynamic information as the features of a software system and moreover different weights are assigned to different features. With the help of labels generated during clustering, evaluation is achieved. Finally, some experiments are conducted, and the experimental results depict our proposed algorithm improves the accuracy and efficiency of software architecture recovery to some extend.
Cotinine halts the advance of Alzheimer's disease-like pathology and associated depressive-like behavior in Tg6799 mice

Alzheimer's disease (AD) is associated with cognitive and non-cognitive symptoms for which there are currently no effective therapies. We have previously reported that cotinine, a natural product obtained from tobacco leaves, prevented memory loss and diminished amyloid-β (Aβ) plaque pathology in transgenic 6799 mice (Tg6799 mice) when treated prior to the development of the pathology. We have also shown that cotinine reduces depressive-like behavior in normal and chronically stressed C57BL/6 mice. Here, we extend our previous studies by investigating the effects of cotinine on the progression of AD-like pathology, depressive-like behavior, and the mechanisms underlying its beneficial effects in Tg6799 mice when left untreated until after a more advanced stage of the disease's development. The results show that vehicle-treated Tg6799 mice displayed an accentuated loss of working memory and an abundant Aβ plaque pathology that were accompanied by higher levels of depressive-like behavior as compared to control littermates. By contrast, prolonged daily cotinine treatment to Tg6799 mice, withheld until after a mid-level progression of AD-like pathology, reduced Aβ levels/plaques and depressive-like behavior. Moreover, this treatment paradigm dramatically improved working memory as compared to control littermates. The beneficial effects of cotinine were accompanied by an increase in the expression of the active form of protein kinase B and the postsynaptic density protein 95 in the hippocampi and frontal cortices of Tg6799 mice. This suggests that cotinine halts the progression of AD-like pathology while reducing depressive-like behavior by stimulating signaling pathways supporting synaptic plasticity in Tg6799 mice. The potential use of cotinine to treat cognitive and non-cognitive symptoms of AD is discussed.
SUSY-breaking Soft Terms in a MSSM Magnetized D7-brane Model

We compute the SUSY-breaking soft terms in a magnetized D7-brane model with MSSM-like spectrum, under the general assumption of non-vanishing auxiliary fields of the dilaton and Kahler moduli. As a particular scenario we discuss SUSY breaking triggered by ISD or IASD 3-form fluxes.
Dense and Sparse Matrix Operations on the Cell Processor

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. Therefore, the high performance computing community is examining alternative architectures that address the limitations of modern superscalar designs. In this work, we examine STI's forthcoming Cell processor: a novel, low-power architecture that combines a PowerPC core with eight independent SIMD processing units coupled with a software-controlled memory to offer high FLOP/s/Watt. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop an analytic framework to predict Cell performance on dense and sparse matrix operations, using a variety of algorithmic approaches. Results demonstrate Cell's potential to deliver more than an order of magnitude better GFLOP/s per watt performance, when compared with the Intel Itanium2 and Cray X1 processors.
Cluster encoding for modelling temporal variation in video

Classical Bag-of-Words methods represent videos by modeling the variation of local visual descriptors throughout the video. In this approach they mix variation in time and space indiscriminately while these dimensions are fundamentally different. Therefore, in this paper we present a novel method for video representation which explicitly captures temporal variation over time. We do this by first creating frame-based features using standard Bag-of-Words techniques. To model the variation in time over these frame-based features, we introduce Hard and Soft Cluster Encoding, novel techniques to model variation inspired by the Fisher Kernel [1] and VLAD [2]. Results on the Rochester ADL [3] and Blip10k [4] datasets show that our method yields improvements of respectively 6.6% and 7.4% over our baselines. On Blip10k we outperform the state-of-the-art by 3.6% when using only visual features.
Interaction with the Unfolded Protein Response Reveals a Role for Stargazin in Biosynthetic AMPA Receptor Transport

The transmembrane protein stargazin enhances levels of functional AMPA receptors at the neuronal plasma membrane and at synapses. To clarify the mechanism for this effect, we studied trafficking of the AMPA receptor subunit glutamate receptor 1 (GluR1) in transfected COS7 cells. GluR1 expressed poorly on the surface of these cells and was primarily retained in the endoplasmic reticulum (ER). Stargazin expression strongly increased the surface fraction of GluR1. This effect was not reduced by a dominant-negative dynamin mutant, suggesting that stargazin does not inhibit AMPA receptor endocytosis. Interestingly, upregulation of ER chaperones as part of the unfolded protein response (UPR) both mimicked and occluded the effect of stargazin, suggesting a role for stargazin in ER processing of AMPA receptors. Consistent with this idea, we detected UPR induction in cerebellar granule cells lacking stargazin. Finally, residual AMPA receptor currents in stargazin-deficient neurons were suppressed by inhibition of the UPR. These findings uncover a role for stargazin in AMPA receptor trafficking through the early compartments of the biosynthetic pathway. Furthermore, they provide evidence for modulation of AMPA receptor trafficking by the UPR.
Method for variable quantization in JPEG for improved perceptual quality

One of the main limitations of the ubiquitous JPEG standard is the fact that visible artifacts can often appear in the decompressed image at moderate to high compression ratios. This is especially true for parts of the image containing graphics, text, or some other such synthesized component. Artifacts are also common in smooth regions and in image blocks containing a single dominant edge. One approach to deal with this problem is to change the 'coarseness' of quantization as a function of image characteristics in the block being compressed. The latest extension of the JPEG standard, called JPEG Part-3, provides the necessary syntax for supporting this process by means of scale factors that can be used to uniformly vary the quantization step sizes on a block by block basis. However, the standard does not recommend any specific technique or algorithm for determining scale factors. This paper proposes a simple algorithm for computing scale factors for the quantization tables used in the JPEG compression standard. The algorithm classifies each image block according to its activity and type which index into look-up tables that provide the scale factor to be used for the block. The look-up tables are designed experimentally to yield perceptually lossless compression for the target device under consideration.
Visual perception and working memory in schizotypal personality disorder.

OBJECTIVE Patients affected by schizophrenia show deficits in both visual perception and working memory. The authors tested early-stage vision and working memory in subjects with schizotypal personality disorder, which has been biologically associated with schizophrenia. METHOD Eleven subjects who met DSM-III-R criteria for schizotypal personality disorder and 12 normal comparison subjects were evaluated. Performance thresholds were obtained for tests of visual discrimination and working memory. Both form and trajectory processing were evaluated for each task. RESULTS Subjects with schizotypal personality disorder showed intact discrimination of form and trajectory but were impaired on working memory tasks. CONCLUSIONS These data suggest that subjects with schizotypal personality disorder, unlike patients affected by schizophrenia, have relatively intact visual perception. Subjects with schizotypal personality disorder do show specific deficits on tasks of comparable difficulty when working memory demands are imposed. Schizotypal personality disorder may be associated with a more specific visual processing deficit than schizophrenia, possibly reflecting disruption of frontal lobe systems subserving visual working memory operations.
A Novel Security Algorithm for Universal Mobile Telecommunication System

The user authentication process is an important task in mobile networks. With the development of new standard Universal Mobile Telecommunication System (UMTS), the security weaknesses of previous standards are removed. However one security weakness has been found by researchers in UMTS, which is the sending of user's International Mobile Subscriber Identity (IMSI) in plain text over the air interface during authentication process. In order to address this issue, a novel security algorithm named as Airam is presented in this research work. Airam algorithm uses hybrid cryptography technique to resolve the problem of sending user's IMSI is plain text over the air interface during authentication process. Simulation results show that the proposed Airam algorithm also provides adequate security against replay and imposition attacks.
Positive predictive value of the infant respiratory distress syndrome diagnosis in the Danish National Patient Registry

Background Infant respiratory distress syndrome (IRDS) is the most common respiratory disease in preterm infants, and is associated with considerable morbidity and mortality. Valid data on IRDS are important in clinical epidemiological research. Objectives The objective of this study was to estimate the positive predictive value (PPV) of the IRDS diagnosis registered in the population-based Danish National Patient Registry according to the International Classification of Diseases, 8th and 10th revisions. Methods Between January 1, 1977 and December 31, 2008, we randomly selected three patients per year, 96 in total, who were registered with an IRDS diagnosis in the Danish National Patient Registry and living in the northern part of Denmark. Data on the infants included information on the presence of predefined clinical symptoms. We defined IRDS as the presence of at least two of four clinical symptoms (tachypnea, retractions or nasal flaring, grunting, and central cyanosis), which had to be present for more than 30 minutes. Using medical record review as the reference standard, we computed the positive predictive value of the registered IRDS diagnosis including 95% confidence intervals (CIs). Results We located the medical record for 90 of the 96 patients (94%), and found an overall PPV of the IRDS diagnosis of 81% (95% CI 72%–88%). This did not vary substantially between primary and secondary diagnoses. The PPV was higher, at 89% (95% CI 80%–95%), for preterm infants born before 37 weeks of gestation. Conclusion The PPV of the IRDS diagnosis in the Danish National Patient Registry is reasonable when compared with symptoms described in the corresponding medical records. The Danish National Patient Registry is a useful data source for studies of IRDS, particularly if restricted to preterm infants. Nonetheless, the potential impact of misclassification of the IRDS diagnosis must be considered.
Beyond Integration: A Phenomenology of Faith-Informed Clinical Practice

The provision of clinical counseling within the context of a Christian worldview has profound meaning for those who seek education in Christian institutions. This phenomenology explored the essence of faith-informed clinical practice for experienced licensed professional counselors. The following six overarching themes emerged from interviews with 10 clinicians: Faith-Informed Clinical Practice Emerges from an Eternal Perspective, Distinct Aspirations of Faith-Informed Clinicians, The Clinician’s Inner World, Bi-directional Influences of Faith and Professional Development, Clinical Issues Specific to Faith-informed Practice, and Suggestions for Faith-Based Education. Recommendations include the replacement of integration studies with spiritual formation and a more holistic, practical, experiential, and spiritual approach to counselor training in faith-based institutions.
Fluorescence Characteristics and Lifetime Images of Photosensitizers of Talaporfin Sodium and Sodium Pheophorbide a in Normal and Cancer Cells

Fluorescence spectra and fluorescence lifetime images of talaporfin sodium and sodium-pheophorbide a, which can be regarded as photosensitizers for photodynamic therapy, were measured in normal and cancer cells. The reduction of the fluorescence intensity by photoirradiation was observed for both photosensitizers in both cells, but the quenching rate was much faster in cancer cells than in normal cells. These results are explained in terms of the excessive generation of reactive oxygen species via photoexcitation of these photosensitizers in cancer cells. The fluorescence lifetimes of both photosensitizers in cancer cells are different from those in normal cells, which originates from the different intracellular environments around the photosensitizers between normal and cancer cells.
Learning begins at birth: Improving access to early learning

Early learning is a complex process involving interactions between the child’s brain and experiences. The required early stimulation must be appropriate to the child’s developmental level, and is a central consideration in the design of early learning programmes. Formerly, early learning was closely associated with cognitive development. Today, it is recognised that self-regulation, perseverance, motivation and socio-emotional development all underpin children’s ability to learn. Ideally early learning should start at home, progressing to playgroups and more formal programmes for older children. Yet only 20% of South Africa’s poorest children under 5 years access a formal early learning programme. 1 While the National Development Plan 2
Use of provisional routes to speed-up change assimilation in InfiniBand networks

Summary form only given. The InfiniBand architecture has been proposed as a technology both for communication between processing nodes and I/O devices, and for interprocessor communication. The InfiniBand specification defines a basic management infrastructure that is responsible for subnet configuration, activation, and fault tolerance. Each time a topology change is detected, management entities collect the current subnet topology. After that, new forwarding tables have to be computed and uploaded to routing devices. The time required to compute these tables is a critical issue, due to application traffic being negatively affected by the temporary lack of connectivity. We present a way to compute a valid set of subnet routes in a short period of time. These provisional routes can be immediately distributed to routing devices. After that, final routes can be later uploaded without affecting user traffic.
Performance of angle-and-range-based localization of wireless sensors

In wireless sensor networks, the accuracy of localization information deteriorates significantly after relaying multiple hops due to accumulation of errors. Techniques exist to enhance the localization information by employing redundant measurements available in networks with high connectivity or from a large number of reference nodes. However, it is challenging to obtain accurate localization information in deployment environments with: 1) unfavorable radio-propagation characteristics that degrade measurements, or 2) sparse topologies that limit the redundancy. One such example is underground tunnels. In this paper, we study the performance of localization techniques that are applicable to such sparse networks. Particularly we focus on the COBALT method, which is based on cliques of nodes in the network and uses angle of arrival and range estimates. For different techniques, we show the influence of the connectivity among sensor nodes on the accuracy. Our results show that the COBALT method outperforms other general-purpose localization techniques.
Combining name and context matching for semantic integration

Interoperability is a key issue for information system nowadays. The need for integration of different sources of data is needed when working in a distributed environment as well as when thinking of use data captured in the web. In both cases data may come with heterogeneities in many aspects, and thus the integration is mandatory to allow the correct use of data. A first step in this sence is integrate the schemas used to describe the data, which can be ontologies, conceptual schemas, XML-schemas, etc. In this paper we present the a methodoloy to integrate schemas considering string distance metrics for name matching and also an ontology approach for context matching in a semi-automatic way. The methodology is based on an algorithm which consider different approaches depending on the schemas to be integrated.
Ataluren treatment of patients with nonsense mutation dystrophinopathy

Introduction: Dystrophinopathy is a rare, severe muscle disorder, and nonsense mutations are found in 13% of cases. Ataluren was developed to enable ribosomal readthrough of premature stop codons in nonsense mutation (nm) genetic disorders. Methods: Randomized, double‐blind, placebo‐controlled study; males ≥5 years with nm‐dystrophinopathy received study drug orally 3 times daily, ataluren 10, 10, 20 mg/kg (N = 57); ataluren 20, 20, 40 mg/kg (N = 60); or placebo (N = 57) for 48 weeks. The primary endpoint was change in 6‐Minute Walk Distance (6MWD) at Week 48. Results: Ataluren was generally well tolerated. The primary endpoint favored ataluren 10, 10, 20 mg/kg versus placebo; the week 48 6MWD Δ = 31.3 meters, post hoc P = 0.056. Secondary endpoints (timed function tests) showed meaningful differences between ataluren 10, 10, 20 mg/kg, and placebo. Conclusions: As the first investigational new drug targeting the underlying cause of nm‐dystrophinopathy, ataluren offers promise as a treatment for this orphan genetic disorder with high unmet medical need. Muscle Nerve 50: 477–487, 2014
A Virtual Rhomb Grid-Based Movement-Assisted Sensor Deployment Algorithm in Wireless Sensor Networks

Sensor deployment, to a large extent, affects the performance and effectiveness of wireless sensor networks (WSN). For the conservation of energy, selecting only a subset of nodes is active and others are sleep. The problem is represented by the connected dominating set (CDS) of the graph, and the minimum connected dominating set (MCDS) is NP-hard for arbitrary graphs. The deployment is either deterministic or self-organizing. By analyzing of the relationship between both of the deployment, a virtual rhomb grid-based movement-assisted sensor deployment algorithm (VRGMSD) is proposed, which integrates both deterministic and self-organizing deployment in a unified framework. The VRGMSD algorithm (1) can form a MCDS; (2) ensures that there is no "holes" in the sensor field; (3) can select different k (the degree of coverage or connectivity) according to the demand on different applications. This flexibility allows the network to self-configure for a wide range of applications
ZigZag: A New Approach to Adaptive Online Learning

We develop a novel family of algorithms for the online learning setting with regret against any data sequence bounded by the empirical Rademacher complexity of that sequence. To develop a general theory of when this type of adaptive regret bound is achievable we establish a connection to the theory of decoupling inequalities for martingales in Banach spaces. When the hypothesis class is a set of linear functions bounded in some norm, such a regret bound is achievable if and only if the norm satisfies certain decoupling inequalities for martingales. Donald Burkholder's celebrated geometric characterization of decoupling inequalities (1984) states that such an inequality holds if and only if there exists a special function called a Burkholder function satisfying certain restricted concavity properties. Our online learning algorithms are efficient in terms of queries to this function. We realize our general theory by giving novel efficient algorithms for classes including lp norms, Schatten p-norms, group norms, and reproducing kernel Hilbert spaces. The empirical Rademacher complexity regret bound implies --- when used in the i.i. d. setting --- a data-dependent complexity bound for excess risk after online-to-batch conversion. To showcase the power of the empirical Rademacher complexity regret bound, we derive improved rates for a supervised learning generalization of the online learning with low rank experts task and for the online matrix prediction task. In addition to obtaining tight data-dependent regret bounds, our algorithms enjoy improved efficiency over previous techniques based on Rademacher complexity, automatically work in the infinite horizon setting, and are scale-free. To obtain such adaptive methods, we introduce novel machinery, and the resulting algorithms are not based on the standard tools of online convex optimization.
Combination Patterns of Major R Genes Determine the Level of Resistance to the M. oryzae in Rice (Oryza sativa L.)

Rice blast caused by Magnaporthe oryzae is the most devastating disease of rice and poses a serious threat to world food security. In this study, the distribution and effectiveness of 18 R genes in 277 accessions were investigated based on pathogenicity assays and molecular markers. The results showed that most of the accessions exhibited some degree of resistance (resistance frequency, RF >50%). Accordingly, most of the accessions were observed to harbor two or more R genes, and the number of R genes harbored in accessions was significantly positively correlated with RF. Some R genes were demonstrated to be specifically distributed in the genomes of rice sub-species, such as Pigm, Pi9, Pi5 and Pi1, which were only detected in indica-type accessions, and Pik and Piz, which were just harbored in japonica-type accessions. By analyzing the relationship between R genes and RF using a multiple stepwise regression model, the R genes Pid3, Pi5, Pi9, Pi54, Pigm and Pit were found to show the main effects against M. oryzae in indica-type accessions, while Pita, Pb1, Pik, Pizt and Pia were indicated to exhibit the main effects against M. oryzae in japonica-type accessions. Principal component analysis (PCA) and cluster analysis revealed that combination patterns of major R genes were the main factors determining the resistance of rice varieties to M. oryzae, such as ‘Pi9+Pi54’, ‘Pid3+Pigm’, ‘Pi5+Pid3+Pigm’, ‘Pi5+Pi54+Pid3+Pigm’, ‘Pi5+Pid3’ and ‘Pi5+Pit+Pid3’ in indica-type accessions and ‘Pik+Pib’, ‘Pik+Pita’, ‘Pik+Pb1’, ‘Pizt+Pia’ and ‘Pizt+Pita’ in japonica-type accessions, which were able to confer effective resistance against M. oryzae. The above results provide good theoretical support for the rational utilization of combinations of major R genes in developing rice cultivars with broad-spectrum resistance.