Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating physically based sound models in a multimodal rendering architecture

This paper presents a multimodal rendering architecture that integrates physically based sound models with haptic and visual rendering. The proposed sound modeling approach is compared to other existing techniques. An example of implementation of the architecture is presented, that realizes bimodal (auditory and haptic) rendering of contact stiffness. It is shown that the proposed rendering scheme allows tight synchronization of the two modalities, as well as a high degree of interactivity and responsiveness of the sound models to gestures and actions of a user. Finally, an experiment on the relative contributions of haptic and auditory information to bimodal judgments of contact stiffness is presented. Experimental results support the effectiveness of auditory feedback in modulating haptic perception of stiffness. Copyright © 2006 John Wiley & Sons, Ltd.
A bcl-2 transgene expressed in hepatocytes protects mice from fulminant liver destruction but not from rapid death induced by anti-Fas antibody injection

Stimulation of the Fas (APO-1, CD95) receptor, which is present on a variety of cells, usually triggers a process of programmed cell death. Systemic injection of anti-Fas antibody into mice leads to fulminant liver destruction resulting from massive hepatocyte apoptosis, and to rapid death. Hepatocytes bear Fas but do not express Bcl-2, a protein that plays, in a number of conditions, a protective role against apoptosis. We have generated mice whose liver expresses Bcl-2 as the result of bcl-2 transgene placed under the control of the hepatocyte- specific alpha1-anti-trypsin gene promoter, but is otherwise not distinguishable from that of normal mice. These mice display a marked to almost total resistance to liver damage induced by anti-Fas antibody injection. This protective effect of Bcl-2 occurs in the absence of significant variations, in the stimulated livers, in the level of expression of other proteins also involved in resistance or sensitivity to apoptosis, namely Bcl-x, Bax, Bad, Bak, and p53. Mice with protected livers, however, die almost as rapidly as normal mice, which indicates that acute lethality results from stimulation of Fas receptors present on other target organs or cells.
Measurement and analysis of long-range dependent behavior of Internet packet delay

We analyze 12 traces of round-trip Internet packet delay. We find that these traces, when viewed as time series data, often exhibit Hurst parameter (H) estimates greater than 0.5, indicating long-range dependence. Several traces, however, are not well-modeled with a constant H. We discuss in detail our analytical methods and the robustness of empirical estimators of H under conditions of non-negligible packet loss. Our results indicate that Internet delay is bursty across multiple time scales, which implies that end-user duality of service in the Internet is likely to be impacted by long periods of very large and/or highly variable delays.
Bidding Behavior in Asymmetric Auctions: An Experimental Study

We review an asymmetric auction experiment. Based on Plum (1992) private valuations of the two bidders are independently drawn from distinct but commonly known distributions, one of which stochastically dominating the other. We test the qualitative properties of that model of asymmetric auctions, in particular whether the weak bidder behaves more aggressively than the strong and then test bidders' preference for first- vs. second-price auctions.
On an Efficient CAD Implementation of the Distance Term in Pelgrom's Mismatch Model

In 1989, Pelgrom et al. published a mismatch model for MOS transistors, where the variation of parameter mismatch between two identical transistors is given by two independent terms: a size-dependent term and a distance-dependent term. Some CAD tools based on a nonphysical interpretation of Pelgrom's distance term result in excessive computationally expensive algorithms, which become nonviable even for circuits with a reduced number of transistors. Furthermore, some researchers are reporting new variations on the original nonphysically interpreted algorithms, which may render false results. The purpose of this paper is to clarify the physical interpretation of the distance term of Pelgrom and indicate how to model it efficiently in prospective CAD tools.
Age Discrimination Laws and Labor Market Efficiency

In Lazear's model of long‐term incentive contracts, age discrimina‐tion laws barring age‐ based involuntary terminations preclude such contracts, reducing efficiency. Alternatively, such laws may serve as precommitment devices for these contracts, without pre‐venting firms from offering strong financial incentives to induce retirement at specific ages. In this case, age discrimination laws may encourage Lazear contracts, hence increasing efficiency. We assess evidence on these alternative interpretations using variation in state and federal age discrimination laws. The evidence indicates that age discrimination laws steepen age‐earnings profiles for co‐horts entering the labor market, suggesting that these laws encour‐age the use of Lazear contracts.
Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data

Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications.
Correlation between Complicated Diverticulitis and Visceral Fat

The aim of this study was to examine the relationship of complications related to diverticulitis and visceral obesity. The study was based on a retrospective case note review conducted at the Hanyang University Hospital. Patients were diagnosed with diverticulitis based on clinical symptoms and abdominal computed tomography (CT) findings and divided into two groups: those admitted with complicated diverticulitis and those with a simple diverticulitis episode. We compared the body mass index (BMI) and degree of visceral obesity, measured by abdominal CT. The study included 140 patients, 87 (62.1%) were simple diverticulitis and 53 (37.9%) were complicated diverticulitis. In the complicated diverticulitis group, 9 (6.4%) cases were recurrent, 29 (20.7%) were perforation or abscess patients, and 28 (20%) were patients with systemic inflammatory response syndrome (SIRS). Of the SIRS patients, 13 were involved in other complication groups. When comparing in the two groups, the complicated diverticulitis group had a significantly higher visceral fat area (128.57 cm2 vs 102.80 cm2, P = 0.032) and a higher ratio of visceral fat area/subcutaneous fat area (0.997 vs 0.799, P = 0.014). Visceral obesity is significantly associated with complications of diverticulitis.
Refining Ovarian Cancer Test accuracy Scores (ROCkeTS): protocol for a prospective longitudinal test accuracy study to validate new risk scores in women with symptoms of suspected ovarian cancer

Introduction Ovarian cancer (OC) is associated with non-specific symptoms such as bloating, making accurate diagnosis challenging: only 1 in 3 women with OC presents through primary care referral. National Institute for Health and Care Excellence guidelines recommends sequential testing with CA125 and routine ultrasound in primary care. However, these diagnostic tests have limited sensitivity or specificity. Improving accurate triage in women with vague symptoms is likely to improve mortality by streamlining referral and care pathways. The Refining Ovarian Cancer Test Accuracy Scores (ROCkeTS; HTA 13/13/01) project will derive and validate new tests/risk prediction models that estimate the probability of having OC in women with symptoms. This protocol refers to the prospective study only (phase III). Methods and analysis ROCkeTS comprises four parallel phases. The full ROCkeTS protocol can be found at http://www.birmingham. ac.uk/ROCKETS. Phase III is a prospective test accuracy study. The study will recruit 2450 patients from 15 UK sites. Recruited patients complete symptom and anxiety questionnaires, donate a serum sample and undergo ultrasound scored as per International Ovarian Tumour Analysis (IOTA) criteria. Recruitment is at rapid access clinics, emergency departments and elective clinics. Models to be evaluated include those based on ultrasound derived by the IOTA group and novel models derived from analysis of existing data sets. Estimates of sensitivity, specificity, c-statistic (area under receiver operating curve), positive predictive value and negative predictive value of diagnostic tests are evaluated and a calibration plot for models will be presented. ROCkeTS has received ethical approval from the NHS West Midlands REC (14/WM/1241) and is registered on the controlled trials website (ISRCTN17160843) and the National Institute of Health Research Cancer and Reproductive Health portfolios.
Polynomial Solvability of Variants of the Trust-Region Subproblem

We consider an optimization problem of the form [EQUATION] where P ⊆ Rn is a polyhedron defined by m inequalities and Q is general and the μh e Rn and the rh quantities are given. In the case |S| = 1, |K| = 0 and m = 0 one obtains the classical trust-region subproblem; a strongly NP-hard problem which has been the focus of much interest because of applications to combinatorial optimization and nonlinear programming. We prove that for each fixed pair |S| and |K| our problem can be solved in polynomial time provided that either (1) |K| > 0 and the number of faces of P that intersect [EQUATION] is polynomially bounded, or (2) |K| = 0 and m is bounded.
laGP: Large-Scale Spatial Modeling via Local Approximate Gaussian Processes in R

Gaussian process (GP) regression models make for powerful predictors in out of sample exercises, but cubic runtimes for dense matrix decompositions severely limit the size of data - training and testing - on which they can be deployed. That means that in computer experiment, spatial/geo-physical, and machine learning contexts, GPs no longer enjoy privileged status as data sets continue to balloon in size. We discuss an implementation of local approximate Gaussian process models, in the laGP package for R, that offers a particular sparse-matrix remedy uniquely positioned to leverage modern parallel computing architectures. The laGP approach can be seen as an update on the spatial statistical method of local kriging neighborhoods. We briefly review the method, and provide extensive illustrations of the features in the package through worked-code examples. The appendix covers custom building options for symmetric multi-processor and graphical processing units, and built-in wrapper routines that automate distribution over a simple network of workstations.
A Multivariate Study of Internet Use and the Digital Divide

Objective This article explores the use of Internet, including social networks, e‐government services, and e‐commerce, from the perspective of the digital divide. First, it aims to find out what factors explain the digital divide. Second, the article aims to identify the groups that are digitally excluded. Method The article is based on survey data (N = 2,304) collected in Spain, which are analyzed using multiple regression, principal component analysis, and cluster analysis. Results Two dimensions are identified: the first is the comprehensive use of Internet and the second is the nature of this use, differentiating between a professional use and a recreational and social use of Internet. The article verifies that factors explaining the digital divide are age, education level, and income. Conclusions The article identifies digitally excluded segments, and the efforts and actions for digital training to eradicate the digital divide should be directed at these groups. The most serious problem is encountered in homeworkers who are mainly woman. NEETs (not in education, employment, or training) are frequent users of Internet, but they only use it for entertainment and to certain extent they are digitally excluded.
Does a property‐specific environmental health risk create a “neighborhood” housing price stigma? Arsenic in private well water

This paper examines the impact of arsenic contamination of groundwater on sale prices of residential properties and bare land transactions in two Maine towns, Buxton and Hollis, that rely on private wells to supply their drinking water. Prompted by tests of well water by the state of Maine, media attention focused on the communities in 1993 and 1994 when 14% of private wells were found to have arsenic concentrations exceeding the U.S. Environmental Protection Agency standard of 0.05 mg/L. Households could mitigate the serious health risks associated with arsenic ingestion by purchasing bottled water or by installing a reverse osmosis home treatment system. Our results indicate that the initial arsenic finding in 1993 led to significant, but temporary, 2 year decreases in property prices. This is a much shorter effect on prices than has been observed for Superfund sites, where prices can be depressed for a decade. These results suggest that a property‐specific contamination incident that is treatable may not have a long‐lasting effect on sale prices, but further research is needed to confirm if the dissipation of the price effect was actually due to the installation of in‐home water treatment systems or due to the dissipation of perceived risk once the media coverage stopped.
Identifying Students’ Expectancy-Value Beliefs: A Latent Class Analysis Approach to Analyzing Middle School Students’ Science Self-Perceptions

This study extends current research by organizing information about students’ expectancy-value achievement motivation in a way that helps parents and teachers identify specific entry points to encourage and support students’ science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs and task values and links these science-self-perceptions to interest in science. Findings suggest that there is a positive relationship between students’ science self-perceptions and interest in science which is consistent with previous research (see for example, Author, 2014). The relationship between self-perceptions and interest in science was similar regardless of gender or ethnicity. Despite study limitations, self-perceptions should be considered valuable because teachers have influence on both learning activities and students’ sense of self as a science learner. These results underscore the importance of preparing teachers to foster student desire to learn more science in the future. In organizing the data using this particular methodology, information is provided in a potentially powerful way to target specific interventions or support.
A class of linearly constrained nonlinear optimization problems with corner point optimal solutions and applications in finance

We identify a class of linearly constrained nonlinear optimization problems with corner point optimal solutions. These include some special polynomial fractional optimization problems with an objective function equal to the product of some power functions of positive linear functionals subtracting the sum of some power functions of positive linear functionals, divided by the sum of some power functions of positive linear functionals. The powers are required to be all positive integers, and the aggregate power of the product is required to be no larger than the lowest power in both of the two sums. The result has applications to some optimization problems under uncertainty, particularly in finance.
Automatic Classification of Thangka Headdresses Based on Convolutional Depth Neural Networks

As a representative of Tibetan culture, people's headdresses in Thangka can be divided into hairpin, monk hat and crown. In order to meet users' demand for accurate retrieval of Thangka, the category information can be used to mark headdresses of Thangka, thereby increasing the accuracy. Existing headdress classifiers suffer from a common problem: image segmentation is required before classification. When segmentation is not satisfactory, the human interaction is also required. This paper presents a classification method for Thangka headdress based on convolutional deep neural networks, without segmentation and human interaction, ease of application. First, top features of headdresses are unsupervised learned by self-encoding; then enter labeled training samples to train a softmax classifier after the convolution and pooling operation process; and finally using the test sampled to test classifier's performance. Compared with other methods, experimental results show that this method can be a good automatic classifier of headdresses, and can be more readily applied to headdress labeling.
Drawing Lessons from the Boom of Temporary Jobs in Spain

We review some lessons from the Spanish experience of using temporary employment contracts for regular jobs since 1984. The focus is on the role of fixed-term contracts with low severance pay, which have substituted for reform of employment protection legislation for permanent contracts. We consider the main findings about this reform on the Spanish labour market in the light of the main theoretical implications derived from models dealing with dual labour markets, and address why the incidence of temporary work has remained highly persistent, around 33% of salaried employment, in the 1990s, despite several reforms aimed at reducing it.
Breathing manoeuvre-dependent changes in myocardial oxygenation in healthy humans.

AIMS CO₂ is an intrinsic vasodilator for cerebral and myocardial blood vessels. Myocardial vasodilation without a parallel increase of the oxygen demand leads to changes in myocardial oxygenation. Because apnoea and hyperventilation modify blood CO₂, we hypothesized that voluntary breathing manoeuvres induce changes in myocardial oxygenation that can be measured by oxygenation-sensitive cardiovascular magnetic resonance (CMR). METHODS AND RESULTS Fourteen healthy volunteers were studied. Eight performed free long breath-hold as well as a 1- and 2-min hyperventilation, whereas six aquatic athletes were studied during a 60-s breath-hold and a free long breath-hold. Signal intensity (SI) changes in T₂*-weighted, steady-state free precession, gradient echo images at 1.5 T were monitored during breathing manoeuvres and compared with changes in capillary blood gases. Breath-holds lasted for 35, 58 and 117 s, and hyperventilation for 60 and 120 s. As expected, capillary pCO₂ decreased significantly during hyperventilation. Capillary pO₂ decreased significantly during the 117-s breath-hold. The breath-holds led to a SI decrease (deoxygenation) in the left ventricular blood pool, while the SI of the myocardium increased by 8.2% (P = 0.04), consistent with an increase in myocardial oxygenation. In contrast, hyperventilation for 120 s, however, resulted in a significant 7.5% decrease in myocardial SI/oxygenation (P = 0.02). Change in capillary pCO₂ was the only independently correlated variable predicting myocardial oxygenation changes during breathing manoeuvres (r = 0.58, P < 0.01). CONCLUSION In healthy individuals, breathing manoeuvres lead to changes in myocardial oxygenation, which appear to be mediated by CO₂. These changes can be monitored in vivo by oxygenation-sensitive CMR and thus, may have value as a diagnostic tool.
Modeling, Design & Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Speed Control of Induction Motor

A novel design of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling some of the parameters, such as speed, torque, flux, voltage, current, etc. of the induction motor is presented in this paper. Induction motors are characterized by highly non-linear, complex and time-varying dynamics and inaccessibility of some of the states and outputs for measurements. Hence it can be considered as a challenging engineering problem in the industrial sector. Various advanced control techniques has been devised by various researchers across the world. Some of them are based on the fuzzy techniques. Fuzzy logic based controllers are considered as potential candidates for such an application. Fuzzy based controllers develop a control signal which yields on the firing of the rule base, which is written on the previous experiences & these rules are fired which is random in nature. As a result of which, the outcome of the controller is also random & optimal results may not be obtained. Selection of the proper rule base depending upon the situation can be achieved by the use of an ANFIS controller, which becomes an integrated method of approach for the control purposes & yields excellent results, which is the highlight of this paper. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. This integrated approach improves the system performance, cost-effectiveness, efficiency, dynamism, reliability of the designed controller. The simulation results presented in this paper show the effectiveness of the method developed & has got faster response time or settling times. Further, the method developed has got a wide number of advantages in the industrial sector & can be converted into a real time application using some interfacing cards.
Lack of Knowledge of HIV Status a Major Barrier to HIV Prevention, Care and Treatment Efforts in Kenya: Results from a Nationally Representative Study

Background We analyzed HIV testing rates, prevalence of undiagnosed HIV, and predictors of testing in the Kenya AIDS Indicator Survey (KAIS) 2007. Methods KAIS was a nationally representative sero-survey that included demographic and behavioral indicators and testing for HIV, HSV-2, syphilis, and CD4 cell counts in the population aged 15–64 years. We used gender-specific multivariable regression models to identify factors independently associated with HIV testing in sexually active persons. Results Of 19,840 eligible persons, 80% consented to interviews and blood specimen collection. National HIV prevalence was 7.1% (95% CI 6.5–7.7). Among ever sexually active persons, 27.4% (95% CI 25.6–29.2) of men and 44.2% (95% CI 42.5–46.0) of women reported previous HIV testing. Among HIV-infected persons, 83.6% (95% CI 76.2–91.0) were unaware of their HIV infection. Among sexually active women aged 15–49 years, 48.7% (95% CI 46.8–50.6) had their last HIV test during antenatal care (ANC). In multivariable analyses, the adjusted odds ratio (AOR) for ever HIV testing in women ≥35 versus 15–19 years was 0.2 (95% CI: 0.1–0.3; p<0.0001). Other independent associations with ever HIV testing included urban residence (AOR 1.6, 95% CI: 1.2–2.0; p = 0.0005, women only), highest wealth index versus the four lower quintiles combined (AOR 1.8, 95% CI: 1.3–2.5; p = 0.0006, men only), and an increasing testing trend with higher levels of education. Missed opportunities for testing were identified during general or pregnancy-specific contacts with health facilities; 89% of adults said they would participate in home-based HIV testing. Conclusions The vast majority of HIV-infected persons in Kenya are unaware of their HIV status, posing a major barrier to HIV prevention, care and treatment efforts. New approaches to HIV testing provision and education, including home-based testing, may increase coverage. Targeted interventions should involve sexually active men, sexually active women without access to ANC, and rural and disadvantaged populations.