Miracle-dz/UniFAR-FTUs huggingface dataset:
Organisational commitment of accountants in Australia and South Africa

This paper examines the independent variables of perceived environmental uncertainty (PEU) and the cultural beliefs of collectivism/individualism between two countries, Australia and South Africa. These countries were chosen because Australia is a stable democracy and South Africa an emerging democracy which is undergoing significant political, social and economic transformation. The purpose of this paper is to determine whether accountants’ commitment to an organization is associated with perceived environmental uncertainty, collectivism and nationality. The results of this study suggest that individuals’ organisational commitment is associated with nationality (South African and Australian) and that relationship is associated with their cultural beliefs (collectivism/individualism) and an environmental variable, perceived environmental uncertainty. This research is regarded as important in that multi-national organizations operating in different political and social environments may choose to use different means to ensure the maximum organisational commitment from their employees, in particular, those who are professional accountants.
Plumbagin suppresses epithelial to mesenchymal transition and stemness via inhibiting Nrf2-mediated signaling pathway in human tongue squamous cell carcinoma cells

Tongue squamous cell carcinoma (TSCC) is the most common malignancy in oral and maxillofacial tumors with highly metastatic characteristics. Plumbagin (5-hydroxy-2-methyl-1, 4-naphthoquinone; PLB), a natural naphthoquinone derived from the roots of Plumbaginaceae plants, exhibits various bioactivities, including anticancer effects. However, the potential molecular targets and underlying mechanisms of PLB in the treatment of TSCC remain elusive. This study employed stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomic approach to investigate the molecular interactome of PLB in human TSCC cell line SCC25 and elucidate the molecular mechanisms. The proteomic data indicated that PLB inhibited cell proliferation, activated death receptor-mediated apoptotic pathway, remodeled epithelial adherens junctions pathway, and manipulated nuclear factor erythroid 2-related factor 2 (Nrf2)-mediated oxidative stress response signaling pathway in SCC25 cells with the involvement of a number of key functional proteins. Furthermore, we verified these protein targets using Western blotting assay. The verification results showed that PLB markedly induced cell cycle arrest at G2/M phase and extrinsic apoptosis, and inhibited epithelial to mesenchymal transition (EMT) and stemness in SCC25 cells. Of note, N-acetyl-l-cysteine (NAC) and l-glutathione (GSH) abolished the effects of PLB on cell cycle arrest, apoptosis induction, EMT inhibition, and stemness attenuation in SCC25 cells. Importantly, PLB suppressed the translocation of Nrf2 from cytosol to nucleus, resulting in an inhibition in the expression of downstream targets. Taken together, these results suggest that PLB may act as a promising anticancer compound via inhibiting Nrf2-mediated oxidative stress signaling pathway in SCC25 cells. This study provides a clue to fully identify the molecular targets and decipher the underlying mechanisms of PLB in the treatment of TSCC.
Hyperpolarization-activated ion channels as targets for nitric oxide signalling in deep cerebellar nuclei

Most biological effects of nitric oxide (NO) in the brain are mediated by guanylyl cyclase‐coupled NO receptors, whose activation results in increased intracellular cGMP levels. Apart from protein kinase activation little is known about subsequent cGMP signal transduction. In optic nerve axons, hyperpolarization‐activated cyclic nucleotide‐modulated cation (HCN) channels, which bind cGMP or cAMP directly, were recently suggested to be a target. The aim here was to test this possibility more directly. Neurones of the rat deep cerebellar nuclei were selected for this purpose, their suitability being attested by immunocytochemistry showing that the principal neurones expressed guanylyl cyclase protein and that NO synthase‐containing fibres were abundant in the neuropil. Using whole‐cell voltage‐clamp recording, HCN channels in the neurones were activated in response to isoprenaline and exogenous cAMP but only occasionally did they respond to NO, although exogenous cGMP was routinely effective. With the less invasive sharp microelectrode recording technique, however, exogenous NO modulated the channels reproducibly, as measured by the size of the HCN channel‐mediated voltage sag following hyperpolarization. Moreover, NO also blunted the subsequent rebound depolarizing potentials, consistent with it increasing the hyperpolarization‐activated current. Optimizing the whole‐cell solution to improve the functioning of NO‐activated guanylyl cyclase failed to restore NO sensitivity. Minimizing cellular dialysis by using the perforated‐patch technique, however, was successful. The results provide evidence that HCN channels are potential downstream mediators of NO signalling in deep cerebellar nuclei neurones and suggest that the more general importance of this transduction pathway may have been overlooked previously because of unsuitable recording methods.
A Graph Transformation based Approach for Runtime Constrained Evolution of Service-Oriented Architectures

Service Oriented Architecture(SOA) is a new form of distributed software architecture. SOA promotes loose coupling, services distribution, dynamicity and agility. Services involved in an SOAare remote and autonomous services, the SOA designer can not control them and unpredictable behavior can occur. This makes the SO different from other architectures for its special architecture elements and its dynamic and evolving structure. How to model this specific architecture and support service-oriented development is unimportant research field in service-oriented software engineering community. This paper proposed a graph transformation based approach to model SOA and its evolution at runtime. Graph grammar is used tore present the architectural style, type and structural constraints are introduced to improve the robustness and adaptability when reconfiguring the architectures at runtime.
Design Trade-offs of a 6 T FinFET SRAM Cell in the Presence of Variations

As the impact of process variations become increasingly significant in ultra deep submicron technologies, FinFETs are becoming increasingly popular a contender for replacement of bulk FETs due to favorable device characteristics. This paper explores the impacts of random and systematic process variations on SRAM cell stability and timing. The largest contributors to these robustness and timing metrics are identified. Design tradeoffs are explored in optimizing the SRAM cell for increased stability and timing.
Simulation of FOC Vector Control of Induction Motor Based on LabVIEW

Based on the theory of vector control of the induction motor, a new method for modeling and simulation of induction motor field orientation based on LabVIEW is proposed. This paper discusses the calculation of the flux position, the realization of the SVPWM, the equivalent transformation. The reasonability and validity are verified by the simulation and experimentation. This method offers a new thinking for designing and debugging actual motors. Keywords-LabVIEW; vector control; field orientation; SVPWM ; simulation
Chinese question classification in community question answering

Community Question Answering (CQA) has become a popular and effective mean for seeking information on the Web. It is now possible and effective to post a question asked in natural language on a popular community Question Answering (QA) portal, and to rely on other users to provide answers. These online collaborative services are attracting users and questions at an explosive rate, while how to correctly categorize a given question is the first problem that a community QA system must dispose. Question classification plays a crucial important role in the community QA System because categorizing a given question correctly is beneficial to obtain accurate answers quickly. In this paper, we present a classifier based on the Support Vector Machine (SVM) machine learning algorithm, and develop a variety of lexical and semantic features for this task. Our experimental results, obtained from a large scale evaluation over thousands of real questions, show the feasibility and effectiveness of our approach.
A Forgery Video Detection Algorithm for Resolution Promotion Manipulations Using Frequency Spectrum Analysis

Resolution is one of the important factors for video visual quality. With the development of the video editing software, one video sequence can be easily enlarged and inserted into another video sequence to generate a forgery video. The detection of video resolution modifications has become an important issue for digital video authentication. In this paper, we propose a passive detection algorithm based on the zero-crossings of the high-frequency component of the key frames in frequency domain. Firstly, the key frames of video are extracted before the second-order differential is executed. Then, the zero crossings of differential are calculated to generate a one-dimensional binary sequence. Finally, the frequency analysis is applied to expose the original resolution of the video for detection. Based on this method, we also develop a forgery detection method for sequence inserting. The experimental results demonstrate that the proposed method can accurately estimate the video original resolution, as well as detect the forgery traces of synthetic videos with maliciously inserted irrelevant video sequences.
Abdominoplasty Improves Quality of Life, Psychological Distress, and Eating Disorder Symptoms: A Prospective Study

Background. Only some studies provide sufficient data regarding the effects of nonpostbariatric (aesthetic) abdominoplasty on various aspects of quality of life. Nevertheless, when considering the effects on eating habits, publications are lacking. Therefore we decided to assess the effects of nonpostbariatric abdominoplasty on eating disorder symptoms, psychological distress, and quality of life. Materials and Methods. 64 consecutive women underwent nonpostbariatric abdominoplasty. Three outcome measures were completed: the Eating Disorder Inventory (EDI), Raitasalo's modification of the Beck Depression Inventory (RBDI), and the 15D general quality of life questionnaire. Results. The mean age at baseline was 42 years and the mean body mass index (BMI) 26.4. Fifty-three (83%) women completed all the outcome measures with a mean follow-up time of 5 months. A significant improvement from baseline to follow-up was noted in women's overall quality of life, body satisfaction, effectiveness, sexual functioning, and self-esteem. The women were significantly less depressive and had significantly less drive for thinness as well as bulimia, and their overall risk of developing an eating disorder also decreased significantly. Conclusions. Abdominoplasty results in significantly improved quality of life, body satisfaction, effectiveness, sexual functioning, self-esteem, and mental health. The risk of developing an eating disorder is decreased significantly. This trial is registered with Clinicaltrials.gov NCT02151799.
Polarity mediates asymmetric trafficking of the Gβ heterotrimeric G-protein subunit GPB-1 in C. elegans embryos

Asymmetric cell division is an evolutionarily conserved process that gives rise to daughter cells with different fates. In one-cell stage C. elegans embryos, this process is accompanied by asymmetric spindle positioning, which is regulated by anterior-posterior (A-P) polarity cues and driven by force generators located at the cell membrane. These force generators comprise two Gα proteins, the coiled-coil protein LIN-5 and the GoLoco protein GPR-1/2. The distribution of GPR-1/2 at the cell membrane is asymmetric during mitosis, with more protein present on the posterior side, an asymmetry that is thought to be crucial for asymmetric spindle positioning. The mechanisms by which the distribution of components such as GPR-1/2 is regulated in time and space are incompletely understood. Here, we report that the distribution of the Gβ subunit GPB-1, a negative regulator of force generators, varies across the cell cycle, with levels at the cell membrane being lowest during mitosis. Furthermore, we uncover that GPB-1 trafficks through the endosomal network in a dynamin- and RAB-5-dependent manner, which is most apparent during mitosis. We find that GPB-1 trafficking is more pronounced on the anterior side and that this asymmetry is regulated by A-P polarity cues. In addition, we demonstrate that GPB-1 depletion results in the loss of GPR-1/2 asymmetry during mitosis. Overall, our results lead us to propose that modulation of Gβ trafficking plays a crucial role during the asymmetric division of one-cell stage C. elegans embryos.
Eliminating frequency and space-time correlations in multiphoton states

Multiphoton states constructed from photon pairs generated in the process of spontaneous parametric downconversion possess frequency and space-time correlations that may carry undesired distinguishing information. It is shown that these correlations may be eliminated if certain conditions in the source configuration are satisfied. For the cases in which these conditions cannot be satisfied because of experimental constraints, it is shown that the correlations may be reduced through proper choices of crystal length and pump bandwidth. The advantage of such source engineering is that it yields much higher count rates, since no photon pairs are lost by predetection spectral filtering.
Common Gene Variants in the Tumor Necrosis Factor (TNF) and TNF Receptor Superfamilies and NF-kB Transcription Factors and Non-Hodgkin Lymphoma Risk

Background A promoter polymorphism in the pro-inflammatory cytokine tumor necrosis factor (TNF) (TNF G-308A) is associated with increased non-Hodgkin lymphoma (NHL) risk. The protein product, TNF-α, activates the nuclear factor kappa beta (NF-κB) transcription factor, and is critical for inflammatory and apoptotic responses in cancer progression. We hypothesized that the TNF and NF-κB pathways are important for NHL and that gene variations across the pathways may alter NHL risk. Methodology/Principal Findings We genotyped 500 tag single nucleotide polymorphisms (SNPs) from 48 candidate gene regions (defined as 20 kb 5′, 10 kb 3′) in the TNF and TNF receptor superfamilies and the NF-κB and related transcription factors, in 1946 NHL cases and 1808 controls pooled from three independent population-based case-control studies. We obtaineded a gene region-level summary of association by computing the minimum p-value (“minP test”). We used logistic regression to compute odds ratios and 95% confidence intervals for NHL and four major NHL subtypes in relation to SNP genotypes and haplotypes. For NHL, the tail strength statistic supported an overall relationship between the TNF/NF-κB pathway and NHL (p = 0.02). We confirmed the association between TNF/LTA on chromosome 6p21.3 with NHL and found the LTA rs2844484 SNP most significantly and specifically associated with the major subtype, diffuse large B-cell lymphoma (DLBCL) (p-trend = 0.001). We also implicated for the first time, variants in NFKBIL1 on chromosome 6p21.3, associated with NHL. Other gene regions identified as statistically significantly associated with NHL included FAS, IRF4, TNFSF13B, TANK, TNFSF7 and TNFRSF13C. Accordingly, the single most significant SNPs associated with NHL were FAS rs4934436 (p-trend = 0.0024), IRF4 rs12211228 (p-trend = 0.0026), TNFSF13B rs2582869 (p-trend = 0.0055), TANK rs1921310 (p-trend = 0.0025), TNFSF7 rs16994592 (p-trend = 0.0024), and TNFRSF13C rs6002551 (p-trend = 0.0074). All associations were consistent in each study with no apparent specificity for NHL subtype. Conclusions/Significance Our results provide consistent evidence that variation in the TNF superfamily of genes and specifically within chromosome 6p21.3 impacts lymphomagenesis. Further characterization of these susceptibility loci and identification of functional variants are warranted.
Identifying the Demand and Supply Effects of Financial Crises on Bank Credit—Evidence from Taiwan

In the aftermath of the Asian financial crisis, Taiwan's bank credits slowed down dramatically while the economy experienced one of the worst recessions in recent history. Whether the slowdown was mainly caused by the demand or the supply effect is unclear. An innovative empirical approach is adopted that uses the short-side rule of bank loans' market transactions to help infer the relative shifts of the demand and supply. For the disaggregate data, a novel model is proposed that accommodates the short-side rule and yet requires only data from the borrowers or the lenders. We find that a large decline in supply is mainly responsible for the slowdown, and we identify the deposit drain and the increase in overdue loans as the main contributing factors. Results also indicate that smaller firms are disproportionately affected by the credit cutback, and that shrinkages in alternative financing sources might have indirectly contributed to the excess demand.
Modeling Multilevel Structures of Information Technology Acceptance: An Investigation of Group Level Effects on Individual Usage of Web-Based Systems

Despite the sizable and continually increasing amount of investment in information technology (IT), IT often falls short of realizing its expected benefits due to inadequate user acceptance. Understanding the key factors that facilitate user acceptance of IT is an issue that has considerable practical implications. While much research effort has been directed to investigating the effects of various variables operating at the individual level, little effort has been made to modeling and assessing the effects of group level variables on individual usage behavior. Our study addresses this issue by proposing a multilevel model composed of individual level variables and group level variables, integrating the Unified Theory of Acceptance and Use of Technology model with Resource-Based Theory. Research hypotheses derived from this integrative model will be empirically validated in a field study setting involving college students who use a Web-based system over a 12-week period. The proposed model will be tested using a hierarchical linear modeling approach, which is specifically designed to examine multilevel data structures. The findings are expected to provide important insights into the dynamic interplay between individual level variables and group level variables and their joint effects on individual acceptance of IT.
A 0.18 µm CMOS multi-Gb/s 10-PAM transmitter

A multi-Gb/s transmitter using multi-level pulse amplitude modulation (M-PAM) is presented. 10-PAM enables transmitter to decrease the symbol rate compared to binary signaling. The transmitter transmits data in current-mode instead of voltage mode, so that high switching speed of driver is achieved. Besides core blocks of the transmitter, Pseudo random bit sequence (PRBS) generator was designed for built-in self-test (BIST). The 10-PAM transmitter is designed in 0.18 µm CMOS process and achieves 3.2 Gb/s with 1.8 V supply voltage.
Sentiment classification using weakly supervised learning techniques

Due to the advanced technologies of Web 2.0, people are participating in and exchanging opinions through social media sites such as Web forums and Weblogs etc., Classification and Analysis of such opinions and sentiment information is potentially important for both service and product providers, users because this analysis is used for making valuable decisions. Sentiment is expressed differently in different domains. Applying a sentiment classifiers trained on source domain does not produce good performance on target domain because words that occur in the train domain might not appear in the test domain. We propose a hybrid model to detect sentiment and topics from text by using weakly supervised learning technique. First we create sentiment sensitive thesaurus using both labeled and unlabeled data from multiple domains. The created thesaurus is then used to classify sentiments from text. This model is highly portable to various domains. This is verified by experimental results from four different domains where the hybrid model even outperforms existing semi-supervised approaches.
Methods for Solving Non-Linear Tasks for Calculating Construction Structures

The present article contains a brief description of several methods for solving non-linear tasks used when calculating the strength, stability and oscillation of construction structures. The investigated structures are: beams, thin-wall reinforced shells, including shells with fractures in the middle of the surface. Calculations are carried out with consideration of physical and geometrical non-linearity using the variational Ritz's method. As the Ritz's method has certain drawbacks, the gradient method is proposed to make up for them. Calculation is presented for reinforced-concrete beams in the non-linear elastic variant with the use of diagram according to the Euro standard. The non-linear theory for structures calculations was developed as a purely theoretical science and it only obtained practical relevance when large-powered computers became available. Complexity of initial equations often prevents from achieving analytical solutions in the closed species, not even for the simplest tasks; therefore, obtaining usable results is closely related to the use of numerical methods; one of them is the method of finite elements (FEM). Non-linear tasks are also related to calculations of seismic influences, when, in order to decrease the buildings' oscillations amplitude, non-linear elastic links are installed.
Timing-aware power-optimal ordering of signals

A computationally efficient technique for reducing interconnect active power in VLSI systems is presented. Power reduction is accomplished by simultaneous wire spacing and net ordering, such that cross-capacitances between wires are optimally shared. The existence of a unique power-optimal wire order within a bundle is proven, and a method to construct this order is derived. The optimal order of wires depends only on the activity factors of the underlying signals; hence, it can be performed prior to spacing optimization. By using this order of wires, optimality of the combined solution is guaranteed (as compared with any other ordering and spacing of the wires). Timing-aware power optimization is enabled by simultaneously considering timing criticality weights and activity factors for the signals. The proposed algorithm has been applied to various interconnect layouts, including wire bundles from high-end microprocessor circuits in 65 nm technology. Interconnect power reduction of 17% on average has been observed in such bundles.
Estimation and Control of the False Discovery Rate of Bayesian Network Skeleton Identification

An important problem in learning Bayesian networks is assessing confidence on the learnt structure. Prior work in constraint-based algorithms focuses on estimating or controlling the False Discovery Rate (FDR) when identifying the skeleton (set of edges without regard of direction) of a network. We present a unified approach to estimation and control of the FDR of Bayesian network skeleton identification and experimentally evaluate the performance of a standard FDR estimator in both tasks over several benchmark networks and sample sizes. We demonstrate that conservative estimation and strong control of FDR are not achieved in some cases due to insufficient sample size and/or unfaithfulness. We show that a permutation-based and a parametric-bootstrapbased FDR estimator achieve more accurate FDR estimation and strong control than the standard estimator. Finally, we present a relaxed definition of false positive that leads to more conservative estimation and control of FDR in relatively small sample sizes.