Miracle-dz/UniFAR-FTUs huggingface dataset:
Blast TBI Models, Neuropathology, and Implications for Seizure Risk

Traumatic brain injury (TBI) due to explosive blast exposure is a leading combat casualty. It is also implicated as a key contributor to war related mental health diseases. A clinically important consequence of all types of TBI is a high risk for development of seizures and epilepsy. Seizures have been reported in patients who have suffered blast injuries in the Global War on Terror but the exact prevalence is unknown. The occurrence of seizures supports the contention that explosive blast leads to both cellular and structural brain pathology. Unfortunately, the exact mechanism by which explosions cause brain injury is unclear, which complicates development of meaningful therapies and mitigation strategies. To help improve understanding, detailed neuropathological analysis is needed. For this, histopathological techniques are extremely valuable and indispensable. In the following we will review the pathological results, including those from immunohistochemical and special staining approaches, from recent preclinical explosive blast studies.
Correspondence validation method for GUI operations and scenarios by operation history analysis

Interactions between users and software are usually described as scenarios so that it is easy to reflect users' viewpoints in software development. In many cases, scenarios are written in a natural language so that users can communicate with software developers smoothly. However, it is difficult to validate correspondences between the flows of operations written in scenarios and those in software. We assume that the flows of software can be expressed by the flows of Graphical User Interface (GUI) operations. In this paper, we propose a method for validating the correspondences between the flows of operations in scenarios and those of actual GUIs. This validation can be performed by analyzing the historic data of GUI operations heuristically. The label names on widgets are extracted from the histories, terms corresponding to label names on widgets are extracted from scenarios, and then the orders of appearance of label names and f terms are validated.
Short-Term Traffic Prediction Based on Dynamic Tensor Completion

Short-term traffic prediction plays a critical role in many important applications of intelligent transportation systems such as traffic congestion control and smart routing, and numerous methods have been proposed to address this issue in the literature. However, most, if not all, of them suffer from the inability to fully use the rich information in traffic data. In this paper, we present a novel short-term traffic flow prediction approach based on dynamic tensor completion (DTC), in which the traffic data are represented as a dynamic tensor pattern, which is able capture more information of traffic flow than traditional methods, namely, temporal variabilities, spatial characteristics, and multimode periodicity. A DTC algorithm is designed to use the multimode information to forecast traffic flow with a low-rank constraint. The proposed method is evaluated on real-world data sets and compared with other state-of-the-art methods, and the efficacy of the proposed approach is validated on the experiments of traffic flow prediction, particularly when dealing with incomplete traffic data.
The Micro-Bubble Distribution in the Wake of a Cavitating Circular Cylinder

Bubble nuclei populations in the wake of a circular cylinder under cavitating and noncavitating conditions were measured using a Phase Doppler Anemometry (PDA) system. In addition, the mean velocity defect and the turbulent fluctuations were monitored in order to try to understand the nuclei population dynamics within the flow. At the Reynolds numbers of these experiments (20000->33000) the laminar near-wake is fairly steady and under very limited cavitation conditions nuclei accumulate in this wake so that the population there is several orders of magnitude larger than in the upstream flow. Further downstream the population declines again as nuclei are entrained into the wake. However at fifteen diameters downstream the population is still much larger than in the upstream flow.
Absorptive capacity in child welfare: measurement challenges and item development

ABSTRACT Promoting successful implementation of evidence-based practices within child welfare agencies necessitates accurately measuring absorptive capacity (i.e., the ability to acquire, assimilate, transform, and exploit knowledge) through valid and reliable assessment. However, a measurement tool does not exist for child welfare agencies. As such, this exploratory study identified existing measures and items relevant to absorptive capacity in child welfare. The study resulted in 12 identified measures, comprising 98 applicable items. This research is a first step toward creating a measure for use in child welfare settings that will guide practice and administration decisions through valid measurement.
Push-Push: A Drag-like Operation Overlapped with a Page Transition Operation on Touch Interfaces

A page transition operation on touch interfaces is a common and frequent subtask when one conducts a drag-like operation such as selecting text and dragging an icon. Traditional page transition gestures such as scrolling and flicking gestures, however, cannot be conducted while conducting the drag-like operation since they have a confliction. We proposed Push-Push that is a new drag-like operation not in conflict with page transition operations. Thus, page transition operations could be conducted while performing Push-Push. To design Push-Push, we utilized the hover and pressed states as additional input states of touch interfaces. The results from two experiments showed that Push-Push has an advantage on increasing performance and qualitative opinions of users while reducing the subjective overload.
CloneCloud: Boosting Mobile Device Applications Through Cloud Clone Execution

Mobile applications are becoming increasingly ubiquitous and provide ever richer functionality on mobile devices. At the same time, such devices often enjoy strong connectivity with more powerful machines ranging from laptops and desktops to commercial clouds. This paper presents the design and implementation of CloneCloud, a system that automatically transforms mobile applications to benefit from the cloud. The system is a flexible application partitioner and execution runtime that enables unmodified mobile applications running in an application-level virtual machine to seamlessly off-load part of their execution from mobile devices onto device clones operating in a computational cloud. CloneCloud uses a combination of static analysis and dynamic profiling to optimally and automatically partition an application so that it migrates, executes in the cloud, and re-integrates computation in a fine-grained manner that makes efficient use of resources. Our evaluation shows that CloneCloud can achieve up to 21.2x speedup of smartphone applications we tested and it allows different partitioning for different inputs and networks.
Specifying Secure Transport Channels

Security architectures often make use of secure transport protocols to protect network messages: the transport protocols provide secure channels between hosts. In this paper we present a hierarchy of specifications for secure channels. We give trace specifications capturing a number of different confidentiality and authentication properties that secure channels might satisfy, and compare their strengths. We use the various modes of TLS as a running example, and we give examples of single-message protocols that we believe satisfy the channel specifications.
USE OF POINT SYMMETRY BASED DISTANCE FOR GENE EXPRESSION DATA CLUSTERING

Introduction of microarray technology helps to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Clustering techniques have been widely used for analyzing such microarray data, typical properties of which are its inherent uncertainty, noise and imprecision. In this paper we have developed some unsupervised approaches for clustering of tissue samples. In recent years some symmetry based clustering techniques have been developed. These clustering algorithms try to optimize total symmetry within a given partitioning. We have used these point symmetry based clustering techniques as the underlying unsupervised approach for gene expression data clustering. Here for grouping of different genes point symmetry based distance is used. The performance of the symmetry based clustering method is compared with that of several other clustering algorithms for some publicly available benchmark gene expression datasets. Biological significance tests have been conducted to analyze the biological relevance of the clustering solutions.
Control of single phase grid connected transformerless PV inverter system

Normal 0 false false false TR ZH-CN X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Normal Tablo"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-ansi-language:TR;} Bu calisma, cok verimli ve guvenli evirici konseptli transformatorsuz eviricili sebeke baglantili fotovoltaik maksimum guc noktasi takip sisteminin kontrolunun benzetim performansini sunmaktadir. Guc ve gerilimin degisimini temel alan durt ve gozlemle teknigi, fotovoltaik birim sisteminden maksimum guc elde etmek icin kullanilmaktadir. DA-DA yukselten cevirici bu teknik ile cevirici anahtarina ait PWM sinyalinin doluluk orani degistirilerek uygulanmaktadir. Tek fazli cok verimli ve guvenli evirici konseptli transformatorsuz evirici, sebekeye guc akisini saglamaktadir. Evirici kontrolu, sebeke gerilimi ve akimi ve ayrica DA-DA yukselten cevirici cikis gerilim degerlerine dayanmaktadir. Sistem performansi, PV modul ve DA-DA yukselten cevirici cikis gerilim ve akimlari, sebeke akimi ve gerilimi, kacak akim, aktif ve reaktif gucler ve guc verim karakteristigi yonunden degerlendirilmektedir. Onerilen sistemde benzetim sonuclari HERIC evirici icin maksimum verimini %97.96, Avrupali verimini %96.84 ve Kaliforniyali verimini %97.60 olarak 20 kHz anahtarlama frekansinda gostermektedir.
Sentiment classification via integrating multiple feature presentations

In the bag of words framework, documents are often converted into vectors according to predefined features together with weighting mechanisms. Since each feature presentation has its character, it is difficult to determine which one should be chosen for a specific domain, especially for the users who are not familiar with the domain. This paper explores the integration of various feature presentations to improve the classification accuracy. A general two phases framework is proposed. In the first phase, we train multiple base classifiers with various vector spaces and use these classifiers to predict the class of testing samples respectively. In the second phase, the previous predicted results are integrated into the ultimate class via stacking with SVM. The experimental results demonstrate the effectiveness of our method.
Why God has left the Netherlands: Explanations for the decline of institutional Christianity in the Netherlands between 1966 and 2015

Why has the Netherlands witnessed such a strong process of secularization? This article examines this process very extensively. Based on modernization theory, it follows several social cultural developments in Dutch society over the last 50 years and distinguishes between effects on the individual level as well as on the level of society. We are able to do so because of rich data availability, derived from micro‐level longitudinal surveys (God in the Netherlands, Social and Cultural Developments in the Netherlands) enriched with macro‐level statistics (Statistics Netherlands). With this integrated approach, we provide explanatory insights into the transition of the Netherlands from a predominant Christian nation to a predominant secular nation. Our analysis clearly shows that macro‐level educational expansion has affected this process of secularization in the Netherlands, supplemented with the increase in social security, as a so‐called cohort effect. Moreover, the long‐term effect of Christian socialization is waning; Dutch people who were raised in a religious way increasingly lapse later in their life.
Solving the Probabilistic Traveling Salesperson Problem with Profits ( pTSPP ) with a Noise-aware Evolutionary Multiobjective Optimization Algorithm

This paper studies an evolutionary algorithm to solve a new multiobjective optimization problem (MOP), the Probabilistic Traveling Salesperson Problem with Profits (pTSPP), which has noisy objective functions. As a variant of TSP, many real-world noisy MOPs can be reduced to pTSPP. The proposed algorithm leverages a novel noise-aware dominance operator, called the α-dominance operator. The operator statistically estimates the impacts of noise on objective functions and judges which solution candidates are superior/inferior to the others. Unlike existing noise-aware dominance operators, the α-dominance operator assumes no noise distributions. Thus, it is well applicable to various real-world noisy MOPs that follow unknown noise distributions. Experimental results show that the α-dominance operator effectively reveals the dominance relationships among solution candidates, aids to obtain quality solutions to pTSPP and outperforms existing noise-aware dominance operators.
A cluster of Pneumocystis infections among renal transplant recipients: molecular evidence of colonized patients as potential infectious sources of Pneumocystis jirovecii.

BACKGROUND Eighteen renal transplant recipients (RTRs) developed Pneumocystis jirovecii infections at the renal transplantation unit of Brest University Hospital (Brest, Brittany, France) from May 2008 through April 2010, whereas no cases of P. jirovecii infection had been diagnosed in this unit since 2002. This outbreak was investigated by identifying P. jirovecii types and analyzing patient encounters. METHODS The identification of P. jirovecii internal transcribed spacer (ITS) types was performed on P. jirovecii isolates from the 18 RTRs (12 patients with Pneumocystis pneumonia [PCP], 6 colonized patients), 22 unlinked control patients (18 patients with PCP, 4 colonized patients), and 69 patients (34 patients with PCP, 35 colonized patients) with contemporaneously diagnosed P. jirovecii infections in the Brest geographic area. A transmission map was drawn up. Its analysis was combined with the results of P. jirovecii typing. RESULTS P. jirovecii ITS type identification was successful in 14 of 18 RTRs, 15 of 22 control patients, and 48 of the 69 patients. Type Eg was the most frequent type in the 3 patient groups. However, its frequency was significantly higher in the first patient group than in the 2 other groups (P < .05 and P < .01, respectively). Fourteen encounters between RTRs who harbored an identical type were observed. Ten patients were considered as possible index patients, of whom 3 were colonized by the fungus, and 7 presented PCP. CONCLUSIONS The results provide to our knowledge the first data on the role of colonized patients as potential sources of P. jirovecii in a context of nosocomial acquisition of the fungus.
Automatic Detection and Intensity Estimation of Spontaneous Smiles

Both the occurrence and intensity of facial expression are critical to what the face reveals. While much progress has been made towards the automatic detection of expression occurrence, controversy exists about how best to estimate expression intensity. Broadly, one approach is to adapt classifiers trained on binary ground truth to estimate expression intensity. An alternative approach is to explicitly train classifiers for the estimation of expression intensity. We investigated this issue by comparing multiple methods for binary smile detection and smile intensity estimation using two large databases of spontaneous expressions. SIFT and Gabor were used for feature extraction; Laplacian Eigenmap and PCA were used for dimensionality reduction; and binary SVM margins, multiclass SVMs, and e-SVR models were used for prediction. Both multiclass SVMs and e-SVR classifiers explicitly trained on intensity ground truth outperformed binary SVM margins for smile intensity estimation. A surprising finding was that multiclass SVMs also outperformed binary SVM margins on binary smile detection. This suggests that training on intensity ground truth is worthwhile even for binary expression detection.
Monetary policy and the transition to rational expectations

Under the assumption of bounded rationality, economic agents learn from their past mistaken predictions by combining new and old information to form new beliefs. The purpose of this paper is to examine how the policy-maker, by affecting private agents' learning process, determines the speed at which the economy converges to the rational expectation equilibrium. I find that by reacting strongly to private agents' expected inflation, a central bank would increase the speed of convergence. I assess the relevance of the transition period from the learning to the rational expectations equilibrium when looking at a criterion for evaluating monetary policy decisions and suggest that a fast convergence is not always suitable
Methylated TRF2 associates with the nuclear matrix and serves as a potential biomarker for cellular senescence

Methylation of N-terminal arginines of the shelterin component TRF2 is important for cellular proliferation. While TRF2 is found at telomeres, where it plays an essential role in maintaining telomere integrity, little is known about the cellular localization of methylated TRF2. Here we report that the majority of methylated TRF2 is resistant to extraction by high salt buffer and DNase I treatment, indicating that methylated TRF2 is tightly associated with the nuclear matrix. We show that methylated TRF2 drastically alters its nuclear staining as normal human primary fibroblast cells approach and enter replicative senescence. This altered nuclear staining, which is found to be overwhelmingly associated with misshapen nuclei and abnormal nuclear matrix folds, can be suppressed by hTERT and it is barely detectable in transformed and cancer cell lines. We find that dysfunctional telomeres and DNA damage, both of which are potent inducers of cellular senescence, promote the altered nuclear staining of methylated TRF2, which is dependent upon the ATM-mediated DNA damage response. Collectively, these results suggest that the altered nuclear staining of methylated TRF2 may represent ATM-mediated nuclear structural alteration associated with cellular senescence. Our data further imply that methylated TRF2 can serve as a potential biomarker for cellular senescence.
ERPs contributing to classification in the ”P300” BCI

Brain Computer Interfaces (BCI) provide a non-muscular communication channel for people with severe motor impairment. The most commonly used BCI for communication is the so called P300-Speller that received its name from the event-related potential (ERP) P300 which is elicited by the speller (oddball) paradigm. Several researchers reported that it is not only the P300 but also other ERPs that are classified with this type of BCI. This study thus, aims at contributing to the discussion by assessing the ERPs which contribute most to classification in a large sample size of N=51 participants. Our results indicate that almost 30% of all participants reached highest determination coefficients with the N200, not with the P300. Furthermore it is often a combination of both potentials that is picked up for classification. Therefore the ”P300”-BCI is truely a BCI that is controlled by various ERPs, especially the N200 and P300.
Budding Yeast Rif1 Controls Genome Integrity by Inhibiting rDNA Replication

The Rif1 protein is a negative regulator of DNA replication initiation in eukaryotes. Here we show that budding yeast Rif1 inhibits DNA replication initiation at the rDNA locus. Absence of Rif1, or disruption of its interaction with PP1/Glc7 phosphatase, leads to more intensive rDNA replication. The effect of Rif1-Glc7 on rDNA replication is similar to that of the Sir2 deacetylase, and the two would appear to act in the same pathway, since the rif1Δ sir2Δ double mutant shows no further increase in rDNA replication. Loss of Rif1-Glc7 activity is also accompanied by an increase in rDNA repeat instability that again is not additive with the effect of sir2Δ. We find, in addition, that the viability of rif1Δ cells is severely compromised in combination with disruption of the MRX or Ctf4-Mms22 complexes, both of which are implicated in stabilization of stalled replication forks. Significantly, we show that removal of the rDNA replication fork barrier (RFB) protein Fob1, alleviation of replisome pausing by deletion of the Tof1/Csm3 complex, or a large deletion of the rDNA repeat array all rescue this synthetic growth defect of rif1Δ cells lacking in addition either MRX or Ctf4-Mms22 activity. These data suggest that the repression of origin activation by Rif1-Glc7 is important to avoid the deleterious accumulation of stalled replication forks at the rDNA RFB, which become lethal when fork stability is compromised. Finally, we show that Rif1-Glc7, unlike Sir2, has an important effect on origin firing outside of the rDNA locus that serves to prevent activation of the DNA replication checkpoint. Our results thus provide insights into a mechanism of replication control within a large repetitive chromosomal domain and its importance for the maintenance of genome stability. These findings may have important implications for metazoans, where large blocks of repetitive sequences are much more common.
Natural zinc ribbon HNH endonucleases and engineered zinc finger nicking endonuclease

Many bacteriophage and prophage genomes encode an HNH endonuclease (HNHE) next to their cohesive end site and terminase genes. The HNH catalytic domain contains the conserved catalytic residues His-Asn-His and a zinc-binding site [CxxC]2. An additional zinc ribbon (ZR) domain with one to two zinc-binding sites ([CxxxxC], [CxxxxH], [CxxxC], [HxxxH], [CxxC] or [CxxH]) is frequently found at the N-terminus or C-terminus of the HNHE or a ZR domain protein (ZRP) located adjacent to the HNHE. We expressed and purified 10 such HNHEs and characterized their cleavage sites. These HNHEs are site-specific and strand-specific nicking endonucleases (NEase or nickase) with 3- to 7-bp specificities. A minimal HNH nicking domain of 76 amino acid residues was identified from Bacillus phage γ HNHE and subsequently fused to a zinc finger protein to generate a chimeric NEase with a new specificity (12–13 bp). The identification of a large pool of previously unknown natural NEases and engineered NEases provides more ‘tools’ for DNA manipulation and molecular diagnostics. The small modular HNH nicking domain can be used to generate rare NEases applicable to targeted genome editing. In addition, the engineered ZF nickase is useful for evaluation of off-target sites in vitro before performing cell-based gene modification.