Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Website Aesthetics on Approach Intention

Designing purchasing environment that produce specific emotional effects in the buyer might enhance purchase probability. However, studies on effect of website aesthetics on emotion and behavior intention seem to be limited. Therefore, the purpose of this study is to investigate the effect of visual aesthetics on approach/avoidance intention and the mediating role of emotional responses. Overall, 116 subjects participated in the experiment. A repeated measure design with three levels of website aesthetics which are classical, expressive, and low aesthetics was employed to investigate the emotional response and approach/avoidance intention. The results show that aesthetics of website affects emotional responses and that the emotions affect approach/avoidance intention. The design factors, which induce higher pleasure or arousal, will produce higher approach intention.
Therapeutic plasmapheresis and red blood cell exchange in a sickle cell trait patient with rhabdomyolysis

We report a case of a 16‐year‐old African‐American male with sickle cell trait and a past medical history significant for asthma that was transferred to our hospital for management of respiratory failure. On the fourth day of hospitalization, the patient was found to have increased creatine kinase (CK) levels and urine myoglobin levels consistent with rhabdomyolysis. No clear etiology was identified. Aggressive standard hydration and urine alkalization were applied without response. On the sixth day of hospitalization, the patient underwent a 1–1.5 plasma volume therapeutic plasma exchange (TPE) resulting in a transient reduction of serum CK and myoglobin by 50%, which became elevated once again within 4 h. Since his clinical presentation resembles exertional rhabdomyolysis documented in patients with sickle cell trait, RBC exchange was performed. The patient tolerated the procedure without complications. In addition to his improved overall condition, the patient's post‐exchange CK and serum myoglobin levels dropped dramatically without rebound. To our knowledge, this case represents the first reported case of TPE followed by RBC exchange in a SCT patient with rhabdomyolysis. J. Clin. Apheresis 2012. © 2012 Wiley Periodicals, Inc.
Optimal Heterophily and Communication Effectiveness: Some Empirical Findings

A fundamental principle of human communication is that source-receiver similarity promotes communication effectiveness. But do perceived source-receiver dissimilarities have instrumental value in enhancing the effectiveness of communication? This study demonstrates the application of a method for gauging the relationship between heterophily or source-receiver dissimilarity and communication effectiveness and for identifying relevant dimensions of homophily/heterophily in achieving effective communication. One hundred ninety-two Ss viewed three slides of widely-differing college males, to whom three pre-scaled neutral statements were randomly attributed. Measures were obtained of Ss ratings of themselves and these “sources” along twenty-one personal attributes, as well as their agreement (or disagreement) with the attributed statements. Perceived source-receiver distances varied across the three sources, as did the agreement measure of communication effectiveness. The moderately-distant source achieved the highest agreement, lending support to Everett M. Rogers'notion that optimal heterophily produces communication effectiveness. The pattern and directions of the perceived dimensions of interpersonal differences gave further understanding of the relative communication effectiveness of communication sources.
The DROPS package for numerical simulations of incompressible flows using parallel adaptive multigrid techniques

In this paper we present an overview of a software package called DROPS, which has recently been developed at the IGPM (Institut für Geometrie und Praktische Mathematik) at the Aachen University of Technology. This development is still continuing and our aim is to build an efficient software tool for the numerical simulation of incompressible flows. In the field of incompressible CFD already quite a few packages exist. The state of the art, however, is such that for complicated three-dimensional fluid dynamics (e. g. turbulent flows, multiphase reacting flows, flows with free boundaries) a black-box solver is not yet available. The DROPS package is developed in an interdisciplinary project (SFB 540 “Model-based Experimental Analysis of Kinetic Phenomena in Fluid Multi-phase Reactive Systems”, cf. [36]) where complicated flow phenomena are investigated. The modeling of several complex physical phenomena in this project (e. g., mass transfer between liquid drops and a surrounding fluid or the fluid dynamics and heat transport in a laminar falling film) requires a flexible efficient and robust CFD package. Our aim is to provide such a tool. From the scientific computing point of view it is of interest to develop a CFD code in which several modern numerical techniques which have recently been introduced in the literature are implemented. Examples of such techniques are error estimation methods for Navier-Stokes equations ([18, 33]), fast and robust iterative solvers for discretized Navier-Stokes equations with large Reynolds numbers ([15, 16]) and level set methods for two-phase flows ([37, 44]). In this paper we describe the main components of the DROPS package and show results of a few first applications. At the end of the paper an outlook concerning the further development of the code in the near future is given.
A Pattern Approach to Dealing with NFRs in Ubiquitous Systems

Ubiquitous Computing has become increasingly important, thanks to its attractive aims to provide invisible computing everywhere and anytime. Dealing with Non-Functional Requirements (NFRs), such as usability or privacy, during requirements engineering for Ubiquitous Computing, however, is oftentimes a difficult task, given the unique features of this paradigm (e.g. context-awareness or technological unobtrusiveness). In this paper, we present an approach in which pieces of knowledge about recurring situations in ubiquitous systems are identified and clearly captured as patterns. The approach is illustrated through an example of an e-Learning ubiquitous system.
Effects of nitric oxide synthase inhibitors on murine infection with Mycobacterium tuberculosis

We have recently demonstrated that the macrophage L-arginine-dependent cytotoxic pathway effectively kills the virulent Erdman strain of Mycobacterium tuberculosis in vitro via the generation of toxic reactive nitrogen intermediates by the enzyme nitric oxide synthase. This report demonstrates that two distinct inhibitors of nitric oxide synthase (aminoguanidine and NG-monomethyl-L-arginine) render similar deleterious effects on tuberculous infection in mice, as assessed by mortality, bacterial burden, and pathological tissue damage, thus confirming the importance of reactive nitrogen intermediates in resistance against M. tuberculosis.
Data Storage Security and Privacy in Cloud Computing: A Comprehensive Survey

Cloud Computing is a form of distributed computing wherein resources and application platforms are distributed over the Internet through on demand and pay on utilization basis. Data Storage is main feature that cloud data centres are provided to the companies/organizations to preserve huge data. But still few organizations are not ready to use cloud technology due to lack of security. This paper describes the different techniques along with few security challenges, advantages and also disadvantages. It also provides the analysis of data security issues and privacy protection affairs related to cloud computing by preventing data access from unauthorized users, managing sensitive data, providing accuracy and consistency of data stored .
Optical reflectance spectroscopy for detection of human prostate cancer

We present the method and application of optical reflectance spectroscopy to differentiate prostate cancer from normal tissue using a needle like, bifurcated, fiber-optic probe. An analytical expression to model light reflectance recently published by Zonios et. al. was used to derive optical properties of tissue. A total of 23 cases of human prostate specimens were investigated to analyze statistical differences between the respective cancerous tissues versus normal tissues. The results demonstrate that the derived hemodynamic parameters and optical properties can serve as good bio-markers to differentiate tumor tissue from normal tissue in human prostate.
Systematic Identification and Molecular Characteristics of Long Noncoding RNAs in Pig Tissues

Long noncoding RNAs (lncRNAs) are non-protein-coding RNAs that are involved in a variety of biological processes. The pig is an important farm animal and an ideal biomedical model. In this study, we performed a genome-wide scan for lncRNAs in multiple tissue types from pigs. A total of 118 million paired-end 90 nt clean reads were obtained via strand-specific RNA sequencing, 80.4% of which were aligned to the pig reference genome. We developed a stringent bioinformatics pipeline to identify 2,139 high-quality multiexonic lncRNAs. The characteristic analysis revealed that the novel lncRNAs showed relatively shorter transcript length, fewer exons, and lower expression levels in comparison with protein-coding genes (PCGs). The guanine-cytosine (GC) content of the protein-coding exons and introns was significantly higher than that of the lncRNAs. Moreover, the single nucleotide polymorphism (SNP) density of lncRNAs was significantly higher than that of PCGs. Conservation analysis revealed that most lncRNAs were evolutionarily conserved among pigs, humans, and mice, such as CUFF.253988. 1, which shares homology with human long noncoding RNA MALAT1. The findings of our study significantly increase the number of known lncRNAs in pigs.
[Establishment and evaluation of animal model for studying the effect of traumatic brain injury on bone fracture healing].

OBJECTIVE To establish a stable animal model for studying the effect of traumatic brain injury on bone fracture healing. METHODS Eighty adult male Sprague-Dawley rats were randomly divided into fracture combined brain injury group (A) and simple fracture group (B). Animals of the two groups were killed 6 hours, 1 week, 2 weeks, 1 month and 2 months after trauma, respectively. Their brain histopathology changes were observed and neurological severity scores (NSS, 0 through 25 from no injury to severe injury) determined to measure the brain injury after head trauma, and fracture-healing was assessed by measuring callus volume and X ray examination at the scheduled time points after trauma. The callus volumes were compared between the groups using independent-samples t test 1 week, 2 weeks, 1 month and 2 months after trauma respectively. A value of P<0.05 was considered statistically significant. RESULTS Ninety percent of the rats of group A presented with hemiplegia and the mortality rate was 10% (4/40) . The survived rats developed decorticated flexion deformity of the forelimbs, with behavioral depression, and lost some reflexes and muscle tone. The NSS were 10.83±1.94, 9.33±0.82, 8.17±1.17, 7.83±0.75 and 8.07±0.82 with 6 hours, 1 week, 2 weeks, 1 month and 2 months after trauma, respectively. It showed that the animals received moderate head injury, which tended to be stable from 2 weeks after trauma. Brain pathology showed that blood brain barrier was destroyed, and neurons were degenerative and necrotic at and around the trauma sites. The callus volumes(unit: mm(3)) of the two groups 1 week, 2 weeks, 1 month and 2 months after trauma were 60.03±28.05 and 32.80±11.04, 78.54±15.16 and 51.36±23.02, 93.01±10.65 and 72.38±20.38, 115.26±40.00 and 60.30±13.34, respectively. The callus volumes of the two groups 2 weeks, 1 month and 2 months after trauma were statistically and significantly different (P values were 0.036, 0.006 and 0.01 respectively), and there was no difference 1 week after trauma (P=0.065). CONCLUSION This model is capable of producing accurately quantified brain injury. The animal model is credible, stable and reproducible, so it is an effective platform for studying the effect of traumatic brain injury on fracture.
Dealing with the complexity deluge: VREs in the arts and humanities

Purpose – The aim of this paper is to review the concept of the virtual research environment (VRE) in the light of its development over the past five years, and assess its applicability to the arts and humanities disciplines.Design/methodology/approach – Evidence from a number of case studies exemplifying the VRE approach is reviewed, and the case of a VRE in archaeology, the Silchester Roman Town project, is discussed in detail. The interpretive implications of using computers as a means of dealing with artistic and humanistic data, are highlighted.Findings – There is a critical comparison to be drawn between VREs in the sciences and the humanities/arts. This is caused by the “fuzzy” nature of data and workflows in the latter, as compared with the more formal and definable research practice in the former. It is proposed that, to deal with this, the plan of any project which seeks to set up a VRE in the humanities should consider the research process under three headings: processes which the VRE seeks to .
Terrain contact modeling and classification for ATVs

We present a method for estimating the contact event between sensor-free active subtracks, named flippers, of an articulated tracked vehicle (ATV) and the terrain surface. The main idea is to consider both the moving base link and unexpected collisions dynamics as disturbances of the flipper dynamics. On this basis we extend the generalized momenta fault detection and isolation (FDI) method to compute the residual dynamics of the flippers, without resorting to additional sensory information. Under the hypothesis that the residual signal presents disturbance patterns that can be discriminated by those generated by unexpected collisions of the flippers with the ground, we apply a classification method to recover the contact event. The wavelet packet transform is used to decompose the signal and to generate a feature space for the residual, from the different subbands. Finally, sparse SVM, based on feature selection discriminates the contact signal.
Is a Newspaper's Companion Website a Competing Outlet Channel for the Print Version?

This paper uses Granger non{causality tests to analyze if channel competition exists between the companion websites of 93 German newspapers observed between I/1998 and II/2005. It provides econometric evidence for significant negative effects of companion website tra? c on the print circulation of national newspapers and for significantly positive effects on local newspapers, at least for the period since I/2002.
Protein tyrosine phosphatase PTPN21 acts as a negative regulator of ICAM-1 by dephosphorylating IKKβ in TNF-α-stimulated human keratinocytes

Intercellular adhesion molecule-1 (ICAM-1), which is induced by tumor necrosis factor (TNF)-α, contributes to the entry of immune cells into the site of inflammation in the skin. Here, we show that protein tyrosine phosphatase non-receptor type 21 (PTPN21) negatively regulates ICAM-1 expression in human keratinocytes. PTPN21 expression was transiently induced after stimulation with TNF-α. When overexpressed, PTPN21 inhibited the expression of ICAM-1 in HaCaT cells but PTPN21 C1108S, a phosphatase activity-inactive mutant, failed to inhibit ICAM-1 expression. Nuclear factor-κB (NF-κB), a key transcription factor of ICAM-1 gene expression, was inhibited by PTPN21, but not by PTPN21 C1108S. PTPN21 directly dephosphorylated phospho-inhibitor of κB (IκB)-kinase β (IKKβ) at Ser177/181. This dephosphorylation led to the stabilization of IκBα and inhibition of NF-κB activity. Taken together, our results suggest that PTPN21 could be a valuable molecular target for regulation of inflammation in the skin by dephosphorylating p-IKKβ and inhibiting NF-κB signaling.
Personality Is Reflected in the Brain's Intrinsic Functional Architecture

Personality describes persistent human behavioral responses to broad classes of environmental stimuli. Investigating how personality traits are reflected in the brain's functional architecture is challenging, in part due to the difficulty of designing appropriate task probes. Resting-state functional connectivity (RSFC) can detect intrinsic activation patterns without relying on any specific task. Here we use RSFC to investigate the neural correlates of the five-factor personality domains. Based on seed regions placed within two cognitive and affective ‘hubs’ in the brain—the anterior cingulate and precuneus—each domain of personality predicted RSFC with a unique pattern of brain regions. These patterns corresponded with functional subdivisions responsible for cognitive and affective processing such as motivation, empathy and future-oriented thinking. Neuroticism and Extraversion, the two most widely studied of the five constructs, predicted connectivity between seed regions and the dorsomedial prefrontal cortex and lateral paralimbic regions, respectively. These areas are associated with emotional regulation, self-evaluation and reward, consistent with the trait qualities. Personality traits were mostly associated with functional connections that were inconsistently present across participants. This suggests that although a fundamental, core functional architecture is preserved across individuals, variable connections outside of that core encompass the inter-individual differences in personality that motivate diverse responses.
Towards context-aware search by learning a very large variable length hidden markov model from search logs

Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approach to document re-ranking, query suggestion, and URL recommendation may improve users' search experience substantially. In this paper, we propose a general approach to context-aware search. To capture contexts of queries, we learn a variable length Hidden Markov Model (vlHMM) from search sessions extracted from log data. Although the mathematical model is intuitive, how to learn a large vlHMM with millions of states from hundreds of millions of search sessions poses a grand challenge. We develop a strategy for parameter initialization in vlHMM learning which can greatly reduce the number of parameters to be estimated in practice. We also devise a method for distributed vlHMM learning under the map-reduce model. We test our approach on a real data set consisting of 1.8 billion queries, 2.6 billion clicks, and 840 million search sessions, and evaluate the effectiveness of the vlHMM learned from the real data on three search applications: document re-ranking, query suggestion, and URL recommendation. The experimental results show that our approach is both effective and efficient.
Alcohol, Tobacco, and Prescription Drugs: The Relationship With Illicit Drugs in the Treatment of Substance Users

Alcohol, tobacco, prescription drug, and illicit drug use frequently co-occur. This paper reviews the extent of this co-occurrence in both general population samples and clinical samples, and its impact on treatment outcome. We argue that the research base for understanding comorbidity among tobacco, alcohol, prescription, and illicit drugs needs to be broadened. We specifically advocate for: (1) more epidemiological studies of relationships among alcohol, tobacco, and other illicit drug use; and (2) increased research on treatment options that address the problematic use of all of these drugs.
The multi-scale spatio-temporal redundancy information reduction based lift scheme in wireless sensor network

Spatio-temporal redundancy information in sensor network data is brought about thanks to stochastic deployment, dense sensing and dynamic topology. Moreover, typical sensor data are not only irregularly spaced but also temporal irregular, which is incompatible with standard wavelet algorithm. As for limited resource of wireless sensor network: power, computation, communication and etc, tradeoff of computation and communication is vital for budget for energy consumes and life prolongs. An efficient scheme of collaborative information and signal processing (CISP) is put forward for hierarchical data aggregation and spatio-temporal decorrelation based on in-cluster distributed second-generation wavelet lift-scheme. This ubiquitous local algorithm not only decrease sharply the communication cost when transmitting information to sink node with approximate information reserved, but also deals with the fundamental issue of spatio-temporal irregular samples.
A Multilevel Algorithm for Wavefront Reduction

A multilevel algorithm for reordering sparse symmetric matrices to reduce the wavefront and profile is described. The algorithm is a combinatorial algorithm that uses a maximal independent vertex set for coarsening the adjacency graph of the matrix and an enhanced version of the Sloan algorithm on the coarsest graph. On a range of examples arising from practical applications, the multilevel algorithm is shown to produce orderings that are better than those produced by the Sloan algorithm and are of comparable quality to those obtained using the hybrid Sloan algorithm. Advantages over the hybrid Sloan algorithm are that the multilevel approach requires no spectral information and less CPU time.
Loneliness and Divorce.

Loneliness was found to be associated with divorce. Women were more affected than men. The greatest feelings of loneliness were in social situations when women felt they had no one with whom to share responsibility; when women felt that finances were a limiting factor; and when women had certain tasks to perform and felt there was no one with whom to share the responsibility. Both men and women were lonely when they felt out of place at a particular time or event.
Disclosure-Free GPS Trace Search in Smartphone Networks

In this paper we present a powerful distributed framework for finding similar trajectories in a smart phone network, without disclosing the traces of participating users. Our framework, coined Smart Trace, exploits opportunistic and participatory sensing in order to quickly answer queries of the form: "Report the users that move more similar to Q, where Q is some query trace". Smart Trace, relies on an in-situ data storage model, where geo-location data is recorded locally on smart phones for both performance and data-disclosure reasons. Smart Trace then deploys an efficient top-K query processing algorithm that exploits distributed trajectory similarity measures, resilient to spatial and temporal noise, in order to derive the most relevant answers to Q quickly and efficiently. We assess our ideas with realistic and real workloads from Microsoft Research Asia and other sources. Our study reveals that Smart Trace computes the desired results with 74% less energy consumption and 13% faster than its centralized and decentralized counterparts. Our experimental results also confirm our analytical study.