Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of IT in Sustainable Competitive Advantage of Global Retailing Companies

The emphases of the study on IT competition value in enterprises have begun to transform from strategic information system, which is the carrier of achieving competitive advantage, to IT capability construction. The core of this transformation is how to obtain sustainable competitive advantage. This paper illustrates this by analyzing two leading retailing companies in the world, Wal-Mart and Japan 7-11. It puts forward the analysis framework of IT capability and mechanism of acquiring sustainable competitive advantage of company. The study points out, from the resource based theory, that the enterprise enjoys sustainable competitive advantage only if its resources and skills are valuable, rare, irreplaceable and difficult to imitate. Furthermore, the paper finds the importance of IT in sustainable competitive advantage of Wal-Mart and Japan 7-11. The key is the construction of logistic, governance capability, operation and corporate innovation, which are related to not only the technology, but also information technology. The experience of Wal-Mart and Japan 7-11 in IT capability construction has significant implication for other developing retailing companies.
Neural Networking using Multiple Web Page Noise Removing Method

The internet web pages having lot of rising amount of content accessible, a useful method for users to determine the positive message from the needless information is immediately essential. A Cleanout web page for web data mining becomes important for civilizing presentation of information recovery and information removal. So, we study to remove different noise model in different web pages in its place of removing important message from web pages to receive major content message. In this research work, we propose concept to decide multiple noise model and remove noise data model from web pages of any web sites. The different web pages are first constructing DOM Tree. Our approach is based on finding noise in current web page and also web noise similarity by using basic Case-Based Reasoning (CBR) approach. We also apply a back transmission neural network algorithm to categorize the stored various noise model by corresponding noise data in current web page. We have implemented of our approach on many commercial web sites and news web sites to checking the presentation and development of our concept. This research paper show on the experimental result leads to more perfect and success of the approach.
Complex I Is the Major Site of Mitochondrial Superoxide Production by Paraquat*

Paraquat (1,1′-dimethyl-4,4′-bipyridinium dichloride) is widely used as a redox cycler to stimulate superoxide production in organisms, cells, and mitochondria. This superoxide production causes extensive mitochondrial oxidative damage, however, there is considerable uncertainty over the mitochondrial sites of paraquat reduction and superoxide formation. Here we show that in yeast and mammalian mitochondria, superoxide production by paraquat occurs in the mitochondrial matrix, as inferred from manganese superoxide dismutase-sensitive mitochondrial DNA damage, as well as from superoxide assays in isolated mitochondria, which were unaffected by exogenous superoxide dismutase. This paraquat-induced superoxide production in the mitochondrial matrix required a membrane potential that was essential for paraquat uptake into mitochondria. This uptake was of the paraquat dication, not the radical monocation, and was carrier-mediated. Experiments with disrupted mitochondria showed that once in the matrix paraquat was principally reduced by complex I (mammals) or by NADPH dehydrogenases (yeast) to form the paraquat radical cation that then reacted with oxygen to form superoxide. Together this membrane potential-dependent uptake across the mitochondrial inner membrane and the subsequent rapid reduction to the paraquat radical cation explain the toxicity of paraquat to mitochondria.
Title The effect of rainfall on the incidence of cholera in Bangladesh . Author ( s )

Background: The incidence of cholera in Bangladesh shows clear seasonality, suggesting that weather factors could play a role in its epidemiology. We estimated the effects of rainfall on the incidence of cholera in Dhaka, Bangladesh. Methods: We examined time-series patterns of the weekly number of hospital visits due to cholera in relation to weekly rainfall from 1996 to 2002. We used Poisson regression models, adjusted for seasonal variation, between-year variation, public holidays and temperature. The role of river level on the rainfall-cholera relationship was also examined by incorporating river-level terms into the models. Results: The weekly number of cholera cases increased by 14% (95 % confidence interval = 10.1% 18.9%) for each 10-millimeter increase above the threshold of 45 millimeters for the average rainfall, over lags 0−8 weeks. Conversely, the number of cholera cases increased by 24% (10.7% 38.6%) for a 10-millimeter decrease below the same threshold of average rainfall, over lags 0−16 weeks. River level partly explained the association between high rainfall and the number of cholera cases. Conclusions: The number of cholera cases increased with both high and low rainfall in the weeks preceding hospital visits. These results suggest that factors associated with river level are on the causal pathway between high rainfall and incidence of cholera.
Multimodal Emotion Recognition Integrating Affective Speech with Facial Expression

In recent years, emotion recognition has attracted extensive interest in signal processing, artificial intelligence and pattern recognition due to its potential applications to human-computer-interaction (HCI). Most previously published works in the field of emotion recognition devote to performing emotion recognition by using either affective speech or facial expression. However, Affective speech and facial expression are mainly two important ways of human emotion expression, as they are the most natural and efficient manners for human beings to communicate their emotions and intentions. In this paper, we aim to develop a multimodal emotion recognition system integrating affective speech with facial expression and investigate the performance of multimodal emotion recognition at the feature-level and at the decision-level. After extracting acoustic features and facial features related to human emotion expression, the popular support vector machines (SVM) classifier is employed to perform emotion classification. Experimental results on the benchmarking eNTERFACE’05 emotional database indicate that the given approach of multimodal emotion recognition integrating affective speech with facial expression obtains obviously superior performance to the single emotion recognition approach, i.e., speech emotion recognition or facial expression recognition. The best performance obtained by using the product rule at the decision-level fusion is up to 67.44%. Key-Words: Mutimodal emotion recognition, affective speech, facial expression, support vector machines, speech emotion recognition, facial expression recognition
COPING WITH THE COFFEE CRISIS IN CENTRAL AMERICA : THE ROLE OF THE NICARAGUAN SOCIAL SAFETY NET PROGRAM

The international and local Nicaraguan media have widely reported on the “coffee crisis” in Latin America and there is substantial evidence that there has been a downturn and that this has been more severe in the coffee growing regions. Using household panel data from a randomized community-based intervention carried out in both coffee and non-coffee growing areas, I examine the role of a conditional cash transfer program, the Red de Protección Social (RPS) during this downturn. While not designed as a traditional safety net program in the sense of reacting or adjusting to crises or shocks, RPS has performed like one, with larger estimated program effects for those who were more affected by the downturn. For example, it protected households against declines in per capita expenditures and, while not significantly depressing labor supply relative to before the program, muted additional labor effort for beneficiaries in coffee growing areas, relative to their counterparts without the program. The evidence is more mixed, however, as to whether RPS enabled households to reallocate their resources in a fashion consistent with the historical downward trends in coffee prices. Beneficiaries who participated in the coffee industry as laborers were more likely to have exited the coffee industry, whereas those who participated as producers were less likely to have exited. The findings are consistent with the existence of credit constraints inhibiting such transitions in the absence of the program. Overall, then, RPS appears to be playing an important part in the “risk” coping strategies of households, a conclusion also supported by a separate analysis of individual household-level idiosyncratic shocks. This research builds on the evaluation of the Red de Protección Social by the International Food Policy Research Institute. I thank the Red de Protección Social team, for their continued support. Natàlia Caldés, Dave Coady, Andy Mason, Nancy McCarthy, Pedro Olinto, Laura Rawlings, Ferdinando Regalía, and Renos Vakis provided many helpful comments, as have seminar participants at NEUDC and the World Bank. I gratefully acknowledge funding for this research from the Inter-American Development Bank, through the Norwegian Fund for Social Innovation, and from the World Bank.
Natural Plant Sugar Sources of Anopheles Mosquitoes Strongly Impact Malaria Transmission Potential

An improved knowledge of mosquito life history could strengthen malaria vector control efforts that primarily focus on killing mosquitoes indoors using insecticide treated nets and indoor residual spraying. Natural sugar sources, usually floral nectars of plants, are a primary energy resource for adult mosquitoes but their role in regulating the dynamics of mosquito populations is unclear. To determine how the sugar availability impacts Anopheles sergentii populations, mark-release-recapture studies were conducted in two oases in Israel with either absence or presence of the local primary sugar source, flowering Acacia raddiana trees. Compared with population estimates from the sugar-rich oasis, An. sergentii in the sugar-poor oasis showed smaller population size (37,494 vs. 85,595), lower survival rates (0.72 vs. 0.93), and prolonged gonotrophic cycles (3.33 vs. 2.36 days). The estimated number of females older than the extrinsic incubation period of malaria (10 days) in the sugar rich site was 4 times greater than in the sugar poor site. Sugar feeding detected in mosquito guts in the sugar-rich site was significantly higher (73%) than in the sugar-poor site (48%). In contrast, plant tissue feeding (poor quality sugar source) in the sugar-rich habitat was much less (0.3%) than in the sugar-poor site (30%). More important, the estimated vectorial capacity, a standard measure of malaria transmission potential, was more than 250-fold higher in the sugar-rich oasis than that in the sugar-poor site. Our results convincingly show that the availability of sugar sources in the local environment is a major determinant regulating the dynamics of mosquito populations and their vector potential, suggesting that control interventions targeting sugar-feeding mosquitoes pose a promising tactic for combating transmission of malaria parasites and other pathogens.
The Evolving Definition of "Sedentary"

Studies that did not directly measure sedentary behavior often have been used to draw conclusions about the health effects of sedentariness. Future claims about the effects of sedentary, light, and moderate-to-vigorous activities on health outcomes should be supported by data from studies in which all levels of physical activity are differentiated clearly and measured independently.
Passively safe Receding Horizon Control for satellite proximity operations

Recent on-orbit mission performance illustrates a pressing need to develop passively safe formation flight trajectories and controllers for multiple satellite proximity operations. A receding horizon control (RHC) approach is formulated that directly relates navigation uncertainty and process noise to non-convex quadratic constraints, which enforce passive safety in the presence of a large class of navigation or propulsion system failures. Several Keplerian simulations are executed to examine increased ¿v usage incurred by adding passive safety constraints, the corresponding reduction in collision probability, and resulting passively safe formation flight geometries. Results show that modest cross-track motion significantly reduces collision probability, and that once a passively safe relative orbit is achieved, steady-state ¿v usage rates are comparable to usage rates without passive safety constraints. Navigation uncertainty and process noise are found to be significant ¿v usage drivers for passively safe proximity operations. Onorbit autonomous RHC control with passive safety constraints applied to proximity operation missions enables trajectory generation and control that reduces collision probability to acceptable levels while minimizing ¿v usage.
Inverse Narrowing for the Inductive Inference of Functional Logic Programs ∗

We present a framework for the Induction of Functional Logic Programs (IFLP) from facts. This can be seen as an extension to the now consolidated field of Inductive Logic Programming (ILP). For that purpose we study the reversal of narrowing, the more usual operational mechanism for Functional Logic Programming. Also we fix the goal and heuristics in consilient programs rather than look for the shortest one as it is common in ILP. Initially, a simple nonincremental algorithm for the induction of functional programs is suggested for toy problems. Next, a more sophisticated incremental algorithm is presented to face more real problems. We discuss the advantages of IFLP in front of ILP, most of them inherited from the power of narrowing w.r. t. resolution. In the end, we comment the plausibility of extending the presented techniques to higher-order induction and its appropiateness for function invention, a topic which is difficult to incorporate homogeneously with the basic first-order inductive rules of inference in ILP.
Candidate Constructions of Fully Homomorphic Encryption on Finite Simple Groups without Ciphertext Noise

We propose constructions of fully homomorphic encryption completely different from the previous work, using special kinds of non-commutativenite groups. Unlike the existing schemes, our ciphertexts involve no \noise" terms, hence the inefficient \bootstrapping" procedures are not necessary. Ourrst scheme is based on improved results on embeddings of logic gates into (almost) simple groups (Ostrovsky and Skeith III, CRYPTO 2008). Our second scheme is based on properties of the commutator operator (analogous to those used in Barrington's theorem) and a new idea of input rerandomization for commutators, effective for some (almost) simple matrix groups. Our main idea is to conceal the concrete structures of the underlying groups by randomly applying some special transformations famous in com- binatorial group theory, called Tietze transformations , to a kind of symbolic representations of the groups. Ideally, the resulting group is expected to behave like a black-box group where only an abstract group structure is available; a detailed analysis of the true effect of random Tietze transformations on the security is a future research topic. We emphasize that such a use of Tietze transformations in cryptology has no similar attempts in the literature and would have rich potential for further applications to other areas in cryptology.
Indirect Adaptive Fuzzy Control of Unmanned Aerial Vehicle

Abstract The design and application of indirect adaptive fuzzy controller is developed and applied to Unmanned Aerial Vehicles (UAVs). The parameters of identified model are adapted on-line based on the error between the identified model and the actual output. The model process sensitivity factor and the error between the reference input and process output are used to adapt the controller parameters. The model process sensitivity is seen to improve the convergence in addition to improving the response of the UAV, when applied to the attitude control of a typical UAV. Simulation results show the superiority of the proposed controller in the attitude control of the UAV.
Conflicting goal constrained architecture of a heterogeneous mobile sensor network

Maintaining coverage and connectivity is a conventional research problem in a sensor network. However, it is still a challenging research field due to the power constraint and connection vulnerability of the battery powered sensing devices. However now a days a network comprises of different mobile devices of different ranges. Still now, there is no comprehensive optimal solution for providing coverage with desired connectivity in a mobile wireless sensor network. In our paper, we present an efficient coverage model for heterogeneous mobile sensing devices maintaining the required connectivity. We compute the optimal positioning of the mobile devices based on Linear Programming, maintaining the required connectivity. We validate our claim by experimental results.
The Vela Pulsar’s Proper Motion and Parallax Derived from VLBI Observations

The Vela pulsar is the brightest pulsar at radio wavelengths. It was the object that told us (via its glitching) that pulsars were solid rotating bodies not oscillating ones. Along with the Crab pulsar, is it the source of many of the models of pulsar behavior. Therefore it is of vital importance to know how far away it is and its origin. The proper motion and parallax for the Vela pulsar have been derived from 2.3 and 8.4 GHz very long baseline interferometry (VLBI) observations. The data span 6.8 years and consist of 11 epochs. We find a proper motion of μα cos δ = -49.68 ± 0.06, μδ = 29.9 ± 0.1 mas yr-1 and a parallax of 3.5 ± 0.2 mas, which is equivalent to a distance of 287 pc. When we subtract out the Galactic rotation and solar peculiar velocity, we find μ* = 45 ± 1.3 mas yr-1 with a position angle of 301° ± 1. °8 which implies that the proper motion has a small but significant offset from the X-ray nebula's symmetry axis.
J ul 2 00 7 Coevolution of agents and networks in an epidemiological model 1

We study the spreading of an infection within an SIS epidemiological model on a network. Susceptible agents are given the opportunity of breaking their links with infected agents, and reconnecting those links with the rest of the population. Thus, the network coevolves with the population as the infection progresses. We show that a moderate reconnection frequency is enough to completely suppress the infection. A partial, rather weak isolation of infected agents suffices to eliminate the endemic state.
Mass Transport Phenomena in a MCFC Cathode

A molten carbonate fuel cell (MCFC) is an electro-chemical energy conversion technology that runs on natural gas and employs a molten salt electrolyte. In order to keep the electrolyte in this state, the cell must be kept at a temperature above 500 C, eliminating the need for precious metals as the catalyst. There has been only a limited amount of research on modelling the transport processes inside this device, mainly due to its restricted applicability for mobile applications. In this work, three one-dimensional models of a MCFC cathode are presented based on different types of diffusion and convection. Comparisons between models are performed so as to assess their validity. Regarding ion transport, it is shown that there exists a limiting case for ion migration across the cathode that depends on the conductivity for the liquid potential. Finally, an optimization of the diffusivity across the cathode is carried out in an attempt to increase the cell performance and its longevity.
Regularizing CNNs with Locally Constrained Decorrelations

Regularization is key for deep learning since it allows training more complex models while keeping lower levels of overfitting. However, the most prevalent regularizations do not leverage all the capacity of the models since they rely on reducing the effective number of parameters. Feature decorrelation is an alternative for using the full capacity of the models but the overfitting reduction margins are too narrow given the overhead it introduces. In this paper, we show that regularizing negatively correlated features is an obstacle for effective decorrelation and present OrthoReg, a novel regularization technique that locally enforces feature orthogonality. As a result, imposing locality constraints in feature decorrelation removes interferences between negatively correlated feature weights, allowing the regularizer to reach higher decorrelation bounds, and reducing the overfitting more effectively. In particular, we show that the models regularized with OrthoReg have higher accuracy bounds even when batch normalization and dropout are present. Moreover, since our regularization is directly performed on the weights, it is especially suitable for fully convolutional neural networks, where the weight space is constant compared to the feature map space. As a result, we are able to reduce the overfitting of state-of-the-art CNNs on CIFAR-10, CIFAR-100, and SVHN.
Language policy and political economy: English in a global context

one that rejects essentialism and is not closely associated with anglophone cultures. The emergent nature of cultural identities is also stressed once again. ELF research is seen to challenge the traditional notion of communicative competence, indicating the importance of ‘pragmatic and interactional competence demonstrated by successful intercultural communication’ (241). The critical and fluid attributes of ICA have important implications for English language teaching from a postnormative perspective. Baker’s book focuses more on theoretical knowledge and construction, and – although one chapter does deal with implications for language teaching – practitioners might find it difficult to fully implement his model if they do not view intercultural communication from a poststructuralist perspective. In any event, the book constitutes a successful attempt to address the issue of intercultural communication in an ELF paradigm, and it will be interesting to see if the model it presents can or will be applied in other settings.
MicroRNA-137 inhibits BMP7 to enhance the epithelial-mesenchymal transition of breast cancer cells

Bone morphogenetic protein-7 (BMP7) is known to antagonize transforming growth factor β 1 (TGFβ1)-mediated fibrosis through suppressing epithelial-mesenchymal transition (EMT). We recently reported that BMP7 also antagonizes the effects of TGFβ1 in breast cancer (BC) tumorigenesis-related EMT. Nevertheless, the control of BMP7 expression in BC remains ill-defined. Here, we detected significantly lower levels of BMP7 and significantly higher levels of microRNA-137 (miR-137) in the BC specimens, relative to paired adjacent non-tumor breast tissue. BMP7 and miR-137 levels were correlated inversely. Additionally, the high miR-137 levels in BC specimens were correlated with reduced patient survival. In vitro, overexpression of miR-137 significantly increased cell EMT and invasion, while depletion of miR-137 significantly decreased cell EMT and invasion in BC cells. The increases in BC cell invasiveness by miR-137 appeared to result from its suppression of BMP7, through direct binding of miR-137 to the 3'-UTR of BMP7 mRNA, thereby blocking its protein translation in BC cells. This study sheds light on miR-137 as a crucial factor that enhances BC cell EMT and invasiveness, and points to miR-137 as a promising innovative therapeutic target for BC treatment.