Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditions for Technology Acceptance - Broadening the Scope of Determinants of ICT Appropriation

Regarding the ICT industry, we have a fast evolving sector being under pressure due to a growing number of failing innovations. Companies are forced to be the first on the market and for that reason thorough insights in user preferences are indispensable. New technological innovations often fail because too much attention is given to (technical) product-related features without taking into account the most important parameters of user acceptance. In this paper we highlight some theoretical considerations on this matter. First of all, we propose an approach in which more traditional and often scattered vision(s) on adoption determinants are broadened into an integrated framework. The approach should provide a stronger base for better targeting of (new) users of technologies. Second, we elaborate on this by rethinking these determinants with regard to the later adopters. Later adopters (or even non-users) are often ignored in technology acceptance research. However, especially for policy purposes, the understanding of why people do not adopt or do not use ICT is strongly relevant in the light of the development of the information society. Both approaches – focusing towards early as well as late adopters – are illustrated by case studies starting from a common framework. “Consumer research has shown that knowledge about the user tends to be limited . It is quite self-evident that both social and commercial policies will benefit from accurate insight into the different parameters determining the success (acceptance and use) of these technologies according to a user’s point of view. ” (Burgelman, 2000: 236)
Evaluation of the PATHFAST Chemiluminescent Enzyme Immunoassay for Measuring Progesterone in Whole Blood and Serum of Mares

Evaluation of a new chemiluminescent enzyme immunoassay, the PATHFAST assay system (PATHFAST), for measurement of circulating progesterone in mares was performed. Five mares at the mid-luteal stage were administrated a single i.m. injection of prostaglandin F2α analog (PGF2α; cloprostenol 250 μg/ml), and then blood samples were collected from the jugular vein at 0, 15, 30 and 45 min, at one-hour intervals until 24 and at 48 hr via a catheter in the jugular vein. To monitor the physiological changes in circulating progesterone in mares after induced luteolysis, concentrations of progesterone in whole blood and serum samples were measured by PATHFAST. In addition, concentrations of progesterone in serum samples measured by PATHFAST were compared with those measured by radioimmunoassay (RIA) and enzyme immunoassay (EIA). Using PATHFAST, the serum concentrations of progesterone in mares correlated highly with those of whole blood samples (r=0.9672, n=88). The serum concentrations of progesterone as measured by PATHFAST correlated well with RIA (r=0.9654, n=88) and EIA (r=0.9323, n=112). An abrupt decline in circulating progesterone in whole blood samples was observed within 2 hr (50%), followed by a gradual decline until 48 hr later. The results for progesterone in whole blood samples correlated highly with those in serum samples, and the declining pattern paralleled that of the serum samples. These results demonstrated that PATHFAST is useful in the equine clinic as an accurate diagnostic tool for rapid assay of progesterone within 26 min, using unextracted whole blood.
RUC-Tencent at ImageCLEF 2015: Concept Detection, Localization and Sentence Generation

In this paper we summarize our experiments in the Image- CLEF 2015 Scalable Concept Image Annotation challenge. The RUC- Tencent team participated in all subtasks: concept detection and local- ization, and image sentence generation. For concept detection, we ex- periments with automated approaches to gather high-quality training examples from the Web, in particular, visual disambiguation by Hierar- chical Semantic Embedding. Per concept, an ensemble of linear SVMs is trained by Negative Bootstrap, with CNN features as image represen- tation. Concept localization is achieved by classifying object proposals generated by Selective Search. For the sentence generation task, we adopt Google's LSTM-RNN model, train it on the MSCOCO dataset, and ne- tune it on the ImageCLEF 2015 development dataset. We further develop a sentence re-ranking strategy based on the concept detection informa- tion from the rst task. Overall, our system is ranked the 3rd for concept detection and localization, and is the best for image sentence generation in both clean and noisy tracks.
High Performance Non-uniform FFT on Modern X86-based Multi-core Systems

The Non-Uniform Fast Fourier Transform (NUFFT) is a generalization of FFT to non-equidistant samples. It has many applications which vary from medical imaging to radio astronomy to the numerical solution of partial differential equations. Despite recent advances in speeding up NUFFT on various platforms, its practical applications are still limited, due to its high computational cost, which is significantly dominated by the convolution of a signal between a non-uniform and uniform grids. The computational cost of the NUFFT is particularly detrimental in cases which require fast reconstruction times, such as iterative 3D non-Cartesian MRI reconstruction. We propose novel and highly scalable parallel algorithm for performing NUFFT on x86-based multi-core CPUs. The high performance of our algorithm relies on good SIMD utilization and high parallel efficiency. On convolution, we demonstrate on average 90% SIMD efficiency using SSE, as well up to linear scalability using a quad-socket 40-core Intel(R) Xeon(R) E7-4870 Processors based system. As a result, on dual socket Intel(R) Xeon(R) X5670 based server, our NUFFT implementation is more than 4x faster compared to the best available NUFFT3D implementation, when run on the same hardware. On Intel(R) Xeon(R) E5-2670 processor based server, our NUFFT implementation is 1.5X faster than any published NUFFT implementation today. Such speed improvement opens new usages for NUFFT. For example, iterative multi channel reconstruction of a 240×240×240 image could execute in just over 3 minutes, which is on the same order as contemporary non-iterative (and thus less-accurate) 3D NUFFT-based MRI reconstructions.
High Diagnostic Yield of Tuberculosis From Screening Urine Samples From HIV-Infected Patients With Advanced Immunodeficiency Using The Xpert MTB/RIF Assay

Abstract:We determined the diagnostic yield of the Xpert MTB/RIF assay for tuberculosis (TB) when testing small volumes of urine from ambulatory HIV-infected patients before starting antiretroviral therapy in South Africa. Compared with a gold standard of sputum culture, the sensitivity of urine Xpert among those with CD4 cell counts of <50, 50–100, and >100 cells per microliter were 44.4%, 25.0%, and 2.7% (P = 0.001), respectively. Urine Xpert testing provides a means of rapid TB diagnosis in patients with advanced immunodeficiency and poor prognosis. These data are indicative of high rates of TB dissemination and renal involvement in this clinical population.
Dissecting the Neutralizing Antibody Specificities of Broadly Neutralizing Sera from Human Immunodeficiency Virus Type 1-Infected Donors

ABSTRACT Attempts to elicit broadly neutralizing antibody responses by human immunodeficiency virus type 1 (HIV-1) vaccine antigens have been met with limited success. To better understand the requirements for cross-neutralization of HIV-1, we have characterized the neutralizing antibody specificities present in the sera of three asymptomatic individuals exhibiting broad neutralization. Two individuals were infected with clade B viruses and the third with a clade A virus. The broadly neutralizing activity could be exclusively assigned to the protein A-reactive immunoglobulin G (IgG) fraction of all three donor sera. Neutralization inhibition assays performed with a panel of linear peptides corresponding to the third hypervariable (V3) loop of gp120 failed to inhibit serum neutralization of a panel of HIV-1 viruses. The sera also failed to neutralize chimeric simian immunodeficiency virus (SIV) and HIV-2 viruses displaying highly conserved gp41-neutralizing epitopes, suggesting that antibodies directed against these epitopes likely do not account for the broad neutralizing activity observed. Polyclonal IgG was fractionated on recombinant monomeric clade B gp120, and the neutralization capacities of the gp120-depleted samples were compared to that of the original polyclonal IgG. We found that the gp120-binding antibody population mediated neutralization of some isolates, but not all. Overall, the data suggest that broad neutralization results from more than one specificity in the sera but that the number of these specificities is likely small. The most likely epitope recognized by the monomeric gp120 binding neutralizing fraction is the CD4 binding site, although other epitopes, such as the glycan shield, cannot be excluded.
Strategic Implications of Competing For Consumers with Time Inconsistent Preferences ∗

I examine oligopolistic competition for time inconsistent consumers. The two cases of investment (health clubs) and leisure goods (credit cards) have different implications for strategy. For leisure goods the firms offer introductory rates at the fully rational consumer level, but consumers end up paying higher fixed rates later. In the limit, the markups go to zero. For investment goods there is a non-trivial cutoff of consumer naivete above which the market equilibrium is as if the consumers are rational. Below the cutoff the firms offer schedules such that consumers pay the membership fee, but do not attend.
Sellers’ Implicit Collusion in Directed Search Markets

Abstract This paper studies a competing-mechanism game for directed search markets in which multiple sellers simultaneously offer selling mechanisms to multiple buyers in order to compete for trading opportunities and profits. Buyers approach any particular seller via directed search, but there can be mis-coordination among buyers in the sense that they choose all the sellers offering the same mechanism with equal probability. A seller’s mechanism can be sufficiently general to make his trading price contingent on participating buyers’ messages, which may reflect changes in trading prices somewhere else. This allows sellers to sustain implicit collusion. This paper focuses on symmetric equilibria in which sellers offer the same mechanism that induces buyers’ ex-post truth telling on market information. It provides the characterization of all symmetric ex-post truth telling equilibrium allocations and comparative statics regarding the range of equilibrium prices and profits. In a large market, the probability that sellers can sell their products at collusive prices depends on the ratio of buyers to sellers.
201o International Conference on Computer and Communication Technologies in Agriculture Engineering Underwater Target Recognition Based on Wpt and Svm

Underwater target recognition, which possesses a crucial theoretic and application value, is a very important topic in the world. The basic principles of wavelet packets transform (WPT) and support vector machine (SVM) are briefly introduced at first. Then the signals of ship radiated are pre-processed and filtered by WPT and the wavelet packets energy spectrum feature parameters are extracted from sub-frequency-bands after WPT. At last, the characteristic vector is established with normalization process and the signals are classified by SVM. The simulation experiment results demonstrate that, the ship radiated signals can be classified or recognized availably based on WPT and SVM. I. INTRODUCTION In the phase of underwater target automatic recognition, feature extraction from ship radiated noise is the key step. Because of complexity of ocean environment and particularity of acoustic communication channel, to find a good extraction method which both can be represented the target's essence and satisfied the demand of underwater detection, is the hotspot and topic in the domain! l. 21. Wavelet transform (W T) has nice location merits both in time and frequency, and can reflect the signal's essence of time and scales. The characteristic vector has facility and nicety after WT because equal to filter processing by each band[3]. Wavelet packets transform (W PT), a new orthogonal decomposing method has more elaborate than WP which recur to the thought of wavelet transform multi-resolution analysis (MRA). WPT rid the shortcoming of bad frequency distinguish in high frequency part of WT and has more stronger self-adjustment in depicting the signals essence. Many researches has been carried through and obtained many achievements, such as reference! 41 from power spectrum or energy density, and reference! 5 1 from least entropy rule. Statistical Learning Theory (SL T)l61, a recently developed new theory for pattern recognition(PR) and machine Learning(ML), is a small-sample statistics proposed by Vapnik [ 71, which deals mainly with the statistic principles when samples are limited, especially to describe the properties of learning procedure in such cases. It provides us a new framework for the small-sample learning problem, and also a novel powerful learning method called Support Vector Machine (SVM), which can solve small-sample learning problem better. Today SL T and SVM have been became the hotspot of ML in the world and have applied to face recognition, text
Personal _ Movie – A Geolocated Movie Recommendation System For Events

—Considering how hard it is to provide more assertive and personalized information, products and service for people/tourists who are searching for a service, such as: having lunch/dinner, searching what's hot about films in theaters right now in the " Olympic villa " , for instance. In order to fill this gap this paper describes a Recommendation System (RS) that applies contextual information and people' personality as recommender inputs in order to predict more personalized films for Cinemark's clients (Personal_Movie). In order to illustrate our discussion we present an experiment that uses a software for mobile that uses geo-location and people's personality to further improve the quality of the film recommendation. The experiment has shown promising results and its potential in the generation of more assertive recommendation. We believe the results might by asl applicable for other products and services requested in Brazilian mega events
Analysis of Product Purchase Patterns in a Co-Purchase Network

Real world social networks are often temporal in nature. They evolve with time as new nodes may appear, old nodes may cease to exist and the relationships between the entities may also change. In this paper, we have studied a publicly available dynamic network dataset, namely Amazon co-purchase network dataset. We have analyzed the network data to understand the significance of nodes with high in-degree and high out-degree. We subsequently analyze the evolution of communities in the network by observing the change of association among nodes and by observing communities to see how many members they could retain over time. We show some frequent item sets from the co-purchase market basket in terms of the item categories and subcategories. We finally select some central entities and group of such entities from the network to recommend how promoting some of the co-purchased items may increase the sales of the selected items.
Paying with Plastic: The Digital Revolution in Buying and Borrowing

Over the course of history there have been four major innovations in how people pay for things: metallic coins in ancient times, checks in the Middle Ages, paper money in modern times, and now payment cards. Since Diners Club issued its first charge cards in 1950, payment cards - credit, debit and charge cards - have revolutionized how and when we pay for goods and services. In 1998 US consumers had more than 720 million payment cards, which they could use to pay for goods and services at more than 4 million merchant locations in the United States and another 11 million in other countries. David Evans and Richard Schmalensee provide a nontechnical distillation of their years of research on the economic, technological and institutional forces that have shaped the payment card industry. They show how competition works in an industry that does not neatly fit any of the standard economic models. They describe how the entrepreneurs in this industry solved the chicken-and-egg problem: merchants will not take cards if few consumers use them, and consumers will not use cards if few merchants take them. They also describe how the payment card companies such as MasterCard and Visa have developed complex systems for coordinating transactions among their thousands of bank members and millions of cardholders and accepting merchants. Evans and Schmalensee also describe recent developments in the industry and consider its likely evolution.
Computation of emotions in man and machines

The importance of emotional expression as part of human communication has been understood since Aristotle, and the subject has been explored scientifically since Charles Darwin and others in the nineteenth century. Advances in computer technology now allow machines to recognize and express emotions, paving the way for improved human–computer and human–human communications. Recent advances in psychology have greatly improved our understanding of the role of affect in communication, perception, decision-making, attention and memory. At the same time, advances in technology mean that it is becoming possible for machines to sense, analyse and express emotions. We can now consider how these advances relate to each other and how they can be brought together to influence future research in perception, attention, learning, memory, communication, decision-making and other applications. The computation of emotions includes both recognition and synthesis, using channels such as facial expressions, non-verbal aspects of speech, posture, gestures, physiology, brain imaging and general behaviour. The combination of new results in psychology with new techniques of computation is leading to new technologies with applications in commerce, education, entertainment, security, therapy and everyday life. However, there are important issues of privacy and personal expression that must also be considered.
Causal Role of Motor Simulation in Turn-Taking Behavior

Overlap between sensory and motor representations has been documented for a range of human actions, from grasping (Rizzolatti et al., 1996b) to playing a musical instrument (Novembre and Keller, 2014). Such overlap suggests that individuals use motor simulation to predict the outcome of observed actions (Wolpert, 1997). Here we investigate motor simulation as a basis of human communication. Using a musical turn-taking task, we show that pianists call on motor representations of their partner's part to predict when to come in for their own turn. Pianists played alternating solos with a videoed partner, and double-pulse transcranial magnetic stimulation was applied around the turn-switch to temporarily disrupt processing in two cortical regions implicated previously in different forms of motor simulation: (1) the dorsal premotor cortex (dPMC), associated with automatic motor resonance during passive observation of hand actions, especially when the actions are familiar (Lahav et al., 2007); and (2) the supplementary motor area (SMA), involved in active motor imagery, especially when the actions are familiar (Baumann et al., 2007). Stimulation of the right dPMC decreased the temporal accuracy of pianists' (right-hand) entries relative to sham when the partner's (left-hand) part had been rehearsed previously. This effect did not occur for dPMC stimulation without rehearsal or for SMA stimulation. These findings support the role of the dPMC in predicting the time course of observed actions via resonance-based motor simulation during turn-taking. Because turn-taking spans multiple modes of human interaction, we suggest that simulation is a foundational mechanism underlying the temporal dynamics of joint action. SIGNIFICANCE STATEMENT Even during passive observation, seeing or hearing somebody execute an action from within our repertoire activates motor cortices of our brain. But what is the functional relevance of such “motor simulation”? By combining a musical duet task with a real-time repetitive transcranial magnetic stimulation protocol, we provide evidence indicating that the dorsal premotor cortex plays a causal role in accurate turn-taking coordination between a pianist and their observed interaction partner. Given that turn-taking behavior is a fundamental feature of human communication, we suggest that simulation is a foundational mechanism underlying the temporal dynamics of communicative joint action.
Intrusion Detection System based on Ant Colony System

Challenge of designing and building of the current Network Intrusion Detection System not only improves the ability for discriminating the improper internet behaviors, but also considers the plenty of computer resources which will be cost during the analysis of the network packets and behaviors. During the establishment of a fast intrusion detection system, the major purpose of the research is to intensify the data handling capacity when the network management system faces the mass network behavior. In the research, the modules stored in the network packets of the intrusion detection system are analyzed, and then the network flow data by applying the clustering algorithm based on the ant colony system is classified. Finally, a kind of algorithm which can remove repetitive computation is designed so that the flow can accelerated and the velocity can be distinguished. Experimental results show that the proposed fast clustering algorithm can significantly reduce the original computation time while sacrificing or promoting a very small accuracy, and then the computation speed of the intrusion detection system can be accelerated.
Firm size and growth opportunities: a survey

The qualifying aspect of the ongoing changes in firm growth processes seems to be the increased heterogeneity of size and a trend towards a broader fluctuation in average size. Exogenous factors (market size, demand trends, technological innovations, higher competition) determine a different impact on firms will to increase their own size, while endogenous variables play a greater role than in the past. The outcome is represented by a growth pattern that characterises some firms, but not all of them. Growth appear to be an asymmetric phenomenon, involving selectively but not casually a subgroup of firms. In the present paper it is hypothesized that growth stems from the asymmetric distribution of internalized resources (both material and immaterial), allowing some firms (regardless of the original size) to enter evolutionary paths that others don’t want or simply can’t enter.