Miracle-dz/UniFAR-FTUs huggingface dataset:
Registering panoramic range data and omnidirectional color image based on edge histograms

In this paper we propose a robust method to register a panoramic range data obtained by a panoramic laser range finder and an omnidirectional image acquired by a stereo omnidirectional system (SOS), by matching the horizontal and vertical edge histograms of the two images. The proposed method first estimates the relative horizontal rotation angle by matching the vertical edge histograms. Next, for each horizontal direction, we generate horizontal edge histograms for both SceneModeler and SOS, using the perspective images with a FOV of 90/spl deg/ centered at the direction concerned. Then we match the horizontal edge histogram in each direction and use the matching results to estimate the relative pose between the sensors. Experimental results show the effectiveness and robustness of the proposed method.
A Distributed base station On/Off Control Mechanism for energy efficiency of small cell networks

This paper considers the power consumption problem in a macro-cell system with a number of small cells and proposes a Distributed base station On/Off Control Mechanism (D-OCM) for reducing the power consumption of the network. Using D-OCM, an inactive small base station (SBS) can be activated by either an active SBS or the macro base station (MBS), while an active SBS can be deactivated by the active SBS itself, both in a distributed manner. To support D-OCM, each base station needs to maintain three tables to store relevant network status information on its neighbor base stations. Both the MBS and an SBS build the tables using the network status information collected from the users within their coverage. Each base station, either the MBS or an SBS, makes a decision to activate an SBS in a sleep state or to deactivate an SBS in a working state based on the traffic load within its coverage. Simulation shows that the proposed D-OCM mechanism can significantly reduce the power consumption of the network as compared a traditional control mechanism.
All-Oral 12-Week Treatment With Daclatasvir Plus Sofosbuvir in Patients With Hepatitis C Virus Genotype 3 Infection: ALLY-3 Phase III Study

Treatment options for patients with hepatitis C virus (HCV) genotype 3 infection are limited, with the currently approved all‐oral regimens requiring 24‐week treatment and the addition of ribavirin (RBV). This phase III study (ALLY‐3; ClinicalTrials.gov: NCT02032901) evaluated the 12‐week regimen of daclatasvir (DCV; pangenotypic nonstructural protein [NS]5A inhibitor) plus sofosbuvir (SOF; pangenotypic NS5B inhibitor) in patients infected with genotype 3. Patients were either treatment naïve (n = 101) or treatment experienced (n = 51) and received DCV 60 mg plus SOF 400 mg once‐daily for 12 weeks. Coprimary endpoints were the proportions of treatment‐naïve and treatment‐experienced patients achieving a sustained virological response (SVR) at post‐treatment week 12 (SVR12). SVR12 rates were 90% (91 of 101) and 86% (44 of 51) in treatment‐naïve and treatment‐experienced patients, respectively; no virological breakthrough was observed, and ≥99% of patients had a virological response (VR) at the end of treatment. SVR12 rates were higher in patients without cirrhosis (96%; 105 of 109) than in those with cirrhosis (63%; 20 of 32). Five of seven patients who previously failed treatment with an SOF‐containing regimen and 2 of 2 who previously failed treatment with an alisporivir‐containing regimen achieved SVR12. Baseline characteristics, including gender, age, HCV‐RNA levels, and interleukin‐28B genotype, did not impact virological outcome. DCV plus SOF was well tolerated; there were no adverse events (AEs) leading to discontinuation and only 1 serious AE on‐treatment, which was unrelated to study medications. The few treatment‐emergent grade 3/4 laboratory abnormalities that were observed were transient. Conclusion: A 12‐week regimen of DCV plus SOF achieved SVR12 in 96% of patients with genotype 3 infection without cirrhosis and was well tolerated. Additional evaluation to optimize efficacy in genotype 3–infected patients with cirrhosis is underway. (Hepatology 2015;61:1127–1135)
A Review of Power Harvesting from Vibration using Piezoelectric Materials

The process of acquiring the energy surrounding a system and converting it into usable electrical energy is termed power harvesting. In the last few years, there has been a surge of research in the area of power harvesting. This increase in research has been brought on by the modern advances in wireless technology and low-power electronics such as microelectromechanical systems. The advances have allowed numerous doors to open for power harvesting systems in practical real-world applications. The use of piezoelectric materials to capitalize on the ambient vibrations surrounding a system is one method that has seen a dramatic rise in use for power harvesting. Piezoelectric materials have a crystalline structure that provides them with the ability to transform mechanical strain energy into electrical charge and, vice versa, to convert an applied electrical potential into mechanical strain. This property provides these materials with the ability to absorb mechanical energy from their surroundings, usually ambient vibration, and transform it into electrical energy that can be used to power other devices. While piezoelectric materials are the major method of harvesting energy, other methods do exist; for example, one of the conventional methods is the use of electromagnetic devices. In this paper we discuss the research that has been performed in the area of power harvesting, and the future goals that must be achieved for power harvesting systems to find their way into everyday use.
Coffee drinking and cutaneous melanoma risk in the NIH-AARP diet and health study.

BACKGROUND Cutaneous melanoma is the fifth most common cancer in the United States. Modifiable risk factors, with the exception of exposure to ultraviolet radiation (UVR), are poorly understood. Coffee contains numerous bioactive compounds and may be associated inversely with melanoma. However, previous epidemiological evidence is limited. METHODS Coffee intake was assessed at baseline with a food frequency questionnaire in the National Institutes of Health-AARP prospective cohort study. Among 447 357 non-Hispanic whites who were cancer-free at baseline, 2904 incident cases of malignant melanoma were identified during 4 329 044 person-years of follow-up, with a median of 10.5 years of follow-up. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for coffee intake and subsequent melanoma risk with non-coffee drinkers as the reference group. Statistical tests were two-sided, and P values less than . 05 were interpreted as statistically significant. RESULTS The highest category of coffee intake was inversely associated with malignant melanoma (≥4 cups/day: HR = 0.80, 95% CI = 0.68 to 0.93, P trend = .01). This association was statistically significant for caffeinated (≥4 cups/day: HR = 0.75, 95% CI = 0.64 to 0.89, P trend = .01) but not for decaffeinated coffee (P trend = .55). CONCLUSIONS Higher coffee intake was associated with a modest decrease in risk of melanoma in this large US cohort study. Additional investigations of coffee intake and its constituents, particularly caffeine, with melanoma are warranted.
Pulse sequence based multi-acquisition MR intensity normalization

Intensity normalization is an important preprocessing step in magnetic resonance (MR) image analysis. In MR images (MRI), the observed intensities are primarily dependent on (1) intrinsic magnetic resonance properties of the tissues such as proton density (PD), longitudinal and transverse relaxation times (T1 and T2 respectively), and (2) the scanner imaging parameters like echo time (TE), repeat time (TR), and flip angle (α). We propose a method which utilizes three co-registered images with different contrast mechanisms (PD-weighted, T2-weighted and T1-weighted) to first estimate the imaging parameters and then estimate PD, T1, and T2 values. We then normalize the subject intensities to a reference by simply applying the pulse sequence equation of the reference image to the subject tissue parameters. Previous approaches to solve this problem have primarily focused on matching the intensity histograms of the subject image to a reference histogram by different methods. The fundamental drawback of these methods is their failure to respect the underlying imaging physics and tissue biology. Our method is validated on phantoms and we show improvement of normalization on real images of human brains.
The Parietal Cortex in Sensemaking: The Dissociation of Multiple Types of Spatial Information

According to the data-frame theory, sensemaking is a macrocognitive process in which people try to make sense of or explain their observations by processing a number of explanatory structures called frames until the observations and frames become congruent. During the sensemaking process, the parietal cortex has been implicated in various cognitive tasks for the functions related to spatial and temporal information processing, mathematical thinking, and spatial attention. In particular, the parietal cortex plays important roles by extracting multiple representations of magnitudes at the early stages of perceptual analysis. By a series of neural network simulations, we demonstrate that the dissociation of different types of spatial information can start early with a rather similar structure (i.e., sensitivity on a common metric), but accurate representations require specific goal-directed top-down controls due to the interference in selective attention. Our results suggest that the roles of the parietal cortex rely on the hierarchical organization of multiple spatial representations and their interactions. The dissociation and interference between different types of spatial information are essentially the result of the competition at different levels of abstraction.
Recent Applications of Economic Theory in Information Technology Research Recent Applications of Economic Theory in Information Technology Research

Academicians and practitioners are becoming increasingly interested in the economics of Information Technology (IT). In part, this interest stems from the increased role that IT now plays in the strategic thinking of most large organizations, and from the significant dollar costs expended by these organizations on IT. Naturally enough, researchers are turning to economics as a reference discipline in their attempt to answer questions concerning both the value added by IT and the true cost of providing IT resources. This increased interest in the economics of IT is manifested in the application of a number of aspects of economic theory in recent information systems research, leading to results that have appeared in a wide variety of publication outlets. This article reviews this work and provides a systematic categorization as a first step in establishing a common research tradition, and to serve as an introduction for researchers beginning work in this area. Six areas of economic theory are represented: information economics, production economics, economic models of organizational performance, industrial organization, institutional economics (agency theory and transaction cost theory), and macroeconomic studies of IT impact. For each of these areas, recent work is reviewed and suggestions for future research are provided.
Dietary lipotropes, hepatic microsomal mixed-function oxidase activities, and in vivo covalent binding of aflatoxin B1 in rats.

Weanling male Sprague-Dawley rats were fed either a nutritionally complete synthetic diet (Diet 1) or a diet marginally deficient in choline and methionine, and lacking folacin (lipotrope deficient, Diet 2) to determine the role of hepatic mixed-function oxidase metabolism of aflatoxin B1 (AFB1) in the Diet 2-induced enhancement of AFB1 hepatocarcinogenesis previously reported. Hepatic microsomal mixed-function oxidase activities, as assayed by ethylmorphine N-demethylation, ethoxycoumarin O-dealkylation, cytochrome c reduction, AFB1 metabolism, and cytochrome P-450 content, were all depressed by Diet 2. Furthermore, the proportion of an i.p. dose of AFB (1 mg/kg) that became covalently bonded to DNA and RNA was similarly reduced when measured 6 hr after administration. The formation of AFB1-protein adducts was not influenced by dietary treatment. The depression of DNA and RNA adduct formation in the Diet 2 animals was probably related to the lower mixed-function oxidase activities and not to an alteration of glutathione levels, which remained unchanged by dietary treatment. These results suggest that the marginally lipotrope-deficient diet does not enhance tumor formation through an increased microsomal activation of AFB1. Alternative hypotheses without data are suggested.
15 Years of Protest and Media Technologies Scholarship: A Sociotechnical Timeline

This article investigates the relationship between the invention of new media technologies and scholarship concerning protest and political engagement. Building on an innovative approach that moves beyond a systematic literature review, this article contributes to our understanding of scholarship concerning digital communication technologies and how they may have been adopted and shaped protest movements and political engagement. Based on visualizations, we draw a sociotechnical timeline of protest and media technology scholarship within three dimensions: technological development, methods and techniques, and the social phenomena under investigation. The article concludes by identifying major trends in protest and media technologies scholarship over the past 15 years. The sociotechnical timeline enhances our understanding of academic discourse at the intersection of protest and media technologies by highlighting shortcomings and potential for future research.
Country Spreads and Emerging Countries: Who Drives Whom?

A number of studies have stressed the role of movements in US interest rates and country spreads in driving business cycles in emerging market economies. At the same time, country spreads have been found to respond to changes in both the US interest rate and domestic conditions in emerging markets. These intricate interrelationships leave open a number of fundamental questions: Do country spreads drive business cycles in emerging countries or vice versa, or both? Do US interest rates affect emerging countries directly or primarily through their effect on country spreads? This paper addresses these and other related questions using a methodology that combines empirical and theoretical elements. The main findings are: (1) US interest rate shocks explain about 20 percent of movements in aggregate activity in emerging market economies at business-cycle frequency. (2) Country spread shocks explain about 12 percent of business-cycle movements in emerging economies. (3) About 60 percent of movements in country spreads are explained by country-spread shocks. (4) In response to an increase in US interest rates, country spreads first fall and then display a large, delayed overshooting; (5) US-interest-rate shocks affect domestic variables mostly through their effects on country spreads. (6) The fact that country spreads respond to business conditions in emerging economies significantly exacerbates aggregate volatility in these countries. (7) The US-interest-rate shocks and country-spread shocks identified in this paper are plausible in the sense that they imply similar business cycles in the context of an empirical VAR model as they do in the context of a theoretical dynamic general equilibrium model of an emerging market economy.
On a Hybrid MPI-Pthread Approach for Simplicial Branch-and-Bound

We investigate models that efficiently map branch-and-bound algorithms on a distributed computer architecture using a case of multidimensional Lipschitz Global Optimization. A combination of MPI and Pthreads is studied: MPI for distributed computation (inter-node) and Pthreads for multicore computation (intra-node). That model adapts the algorithm to the characteristics of the architecture at hand with an increasing number of nodes. Dynamic load balancing is performed in intra-node space through dynamic generation of threads. Results show performance improvements compared to OpenMP and MPI versions used in previous work.
Inequalities for trace anomalies, length of the RG flow, distance between the fixed points and irreversibility

I discuss several issues about the irreversibility of the RG flow and the trace anomalies c, a and a'. First I argue that in quantum field theory: (i) the scheme-invariant area Δa' of the graph of the effective beta function between the fixed points defines the length of the RG flow; (ii) the minimum of Δa' in the space of flows connecting the same UV and IR fixed points defines the (oriented) distance between the fixed points and (iii) in even dimensions, the distance between the fixed points is equal to Δa = aUV − aIR. In even dimensions, these statements imply the inequalities 0 ≤ Δa ≤ Δa' and therefore the irreversibility of the RG flow. Another consequence is the inequality a ≤ c for free scalars and fermions (but not vectors), which can be checked explicitly. Secondly, I elaborate a more general axiomatic set-up where irreversibility is defined as the statement that there exist no pairs of non-trivial flows connecting interchanged UV and IR fixed points. The axioms, based on the notions of length of the flow, oriented distance between the fixed points and certain 'oriented-triangle inequalities', imply the irreversibility of the RG flow without a global a function. I conjecture that the RG flow is also irreversible in odd dimensions (without a global a function). In support of this, I check the axioms of irreversibility in a class of d = 3 theories where the RG flow is integrable at each order of the large N expansion.
Is there an inverted U-shape relationship between job demands and work engagement : the moderating role of social support

Purpose - The purpose of this paper is to examine the possibility of an inverted U-shaped relationship between job demands and work engagement, and whether social support moderates this relationship. Design/methodology/approach – This study uses 307 technical and information technology (IT) managers who responded to an online survey. Multiple regressions are employed to examine linear and curvilinear relationship among variables. Findings – Overall, results support the applicability of the quadratic effect of job demands on employee engagement. However, only supervisor support, not colleague support, moderated the relationship between job demands and work engagement. Originality/value – The paper is the first to shed light on the quadratic effect of job demands on work engagement. The findings have noteworthy implications for managers to design optimal job demands that increase employee engagement.
INVESTIGATION OF POST PROCESSING TECHNIQUES TO REDUCE THE SURFACE ROUGHNESS OF FUSED DEPOSITION MODELED PARTS

Fused Deposition Modeling is most popular rapid prototyping process because of its faster, economical and clean technology, however it suffers from low surface finish quality. To improve its surface finish quality, various attempts had been made by several researchers by controlling various process parameters. The main objective of this research is to apply chemical treatment processes through Design of Experiments using different chemicals with variant conditions like different levels of concentration, time of exposure, temperatures and initial roughness, interaction effects of the process parameters have also been analyzed. ANOVA technique is used to find out the significant factors affecting the surface finish. Results show satisfactory improvement in surface finish of FDM parts (ABS) with simple inexpensive and harmless chemical treatment processes.
Linguistic and Prosodic Emotion Recognition

This paper compares the performance of linguistic and acoustic/ prosodic features for emotion recognition by evaluating them on two speech databases collected using deployed customer care IVR systems. In our anger recognition task, the target is to recognize emotional user states, using either acoustic properties of the speech signal, or a transcription of what was said. Robust processing of speech will require the examination both sources, and an understanding of how these sources behave on different corpora. We present dependencies of both approaches and outlines future improvements. Given the present database design, acoustic/ prosodic modeling clearly outperforms linguistic modeling.
An Algorithm Combining Graph-Reduction and Graph-Search for Workflow Graphs Verification

Since the structural conflicts in workflow processes can lead to malfunctioning of workflow management systems, the problem should be detected before workflow processes are put into execution. In this paper, we propose a combined graph-reduction and graph-search algorithm "CWRS" to verify workflow graphs. This algorithm reduces a cyclic workflow graph to an acyclic workflow graph, and then verifies this acyclic workflow graph by using Mahanti-Sinnakkrishnan algorithm. Computational complexity of this algorithm is 0(E), where E refers to number of edges in a workflow graph. In comparison with others, our algorithm can verify both cyclic and acyclic workflow graphs.
A Statistical Framework for Improving Genomic Annotations of Prokaryotic Essential Genes

Large-scale systematic analysis of gene essentiality is an important step closer toward unraveling the complex relationship between genotypes and phenotypes. Such analysis cannot be accomplished without unbiased and accurate annotations of essential genes. In current genomic databases, most of the essential gene annotations are derived from whole-genome transposon mutagenesis (TM), the most frequently used experimental approach for determining essential genes in microorganisms under defined conditions. However, there are substantial systematic biases associated with TM experiments. In this study, we developed a novel Poisson model–based statistical framework to simulate the TM insertion process and subsequently correct the experimental biases. We first quantitatively assessed the effects of major factors that potentially influence the accuracy of TM and subsequently incorporated relevant factors into the framework. Through iteratively optimizing parameters, we inferred the actual insertion events occurred and described each gene’s essentiality on probability measure. Evaluated by the definite mapping of essential gene profile in Escherichia coli, our model significantly improved the accuracy of original TM datasets, resulting in more accurate annotations of essential genes. Our method also showed encouraging results in improving subsaturation level TM datasets. To test our model’s broad applicability to other bacteria, we applied it to Pseudomonas aeruginosa PAO1 and Francisella tularensis novicida TM datasets. We validated our predictions by literature as well as allelic exchange experiments in PAO1. Our model was correct on six of the seven tested genes. Remarkably, among all three cases that our predictions contradicted the TM assignments, experimental validations supported our predictions. In summary, our method will be a promising tool in improving genomic annotations of essential genes and enabling large-scale explorations of gene essentiality. Our contribution is timely considering the rapidly increasing essential gene sets. A Webserver has been set up to provide convenient access to this tool. All results and source codes are available for download upon publication at http://research.cchmc. org/essentialgene/.