Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel image based positioning technique using mobile eye tracker for a museum visit

Eye tracking can be an easy way for identifying users' focus of attention and interests. This promise triggered large and continues research and technology development efforts with remarkable results. In this paper we aim at developing a novel technique for location awareness, interest detection and focus of attention using computer vision techniques and mobile eye-tracking technology. Our focus will be on museum visit and optimizing the positioning procedure by exploiting the visit style to choose the appropriate algorithm.
Approximate Bisimulation Equivalence and Variable Refinement

In this paper, we consider an operator for refinement of variables to b e used in the design of hybrid system. Variables on a given level of abstraction are replaced by more complicated processes on a lower level just like the function are called in the program. Then we established the equivalence, bisimulation equivalence and approximate bisimulation equivalence which are by polynomial flow event structures. These equivalence, bisimulation equivalence a nd approximate bisimulation equivalence are based on the common forms of their zeros. The example show that the equivalence, bisimulation equivalence and approximate bisimulation equivalence are preserved or not under the variables refinement, if the equivalence is not preserved precisely, then we can use the approximate methods to make them approximate equivalence. Lastly we show that our refineme nt has some nice properties.
Use of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for Improving the Accuracy of the Risk Classification of Type 1 Diabetes

OBJECTIVE We studied the utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of type 1 diabetes (T1D) risk classification in TrialNet Natural History Study (TNNHS) participants. RESEARCH DESIGN AND METHODS The cumulative incidence of T1D was compared between normoglycemic individuals with DPTRS values >7.00 and dysglycemic individuals in the TNNHS (n = 991). It was also compared between individuals with DPTRS values <7.00 or >7.00 among those with dysglycemia and those with multiple autoantibodies in the TNNHS. DPTRS values >7.00 were compared with dysglycemia for characterizing risk in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 670) and TNNHS participants. The reliability of DPTRS values >7.00 was compared with dysglycemia in the TNNHS. RESULTS The cumulative incidence of T1D for normoglycemic TNNHS participants with DPTRS values >7.00 was comparable to those with dysglycemia. Among those with dysglycemia, the cumulative incidence was much higher (P < 0.001) for those with DPTRS values >7.00 than for those with values <7.00 (3-year risks: 0.16 for <7.00 and 0.46 for >7.00). Dysglycemic individuals in DPT-1 were at much higher risk for T1D than those with dysglycemia in the TNNHS (P < 0.001); there was no significant difference in risk between the studies among those with DPTRS values >7.00. The proportion in the TNNHS reverting from dysglycemia to normoglycemia at the next visit was higher than the proportion reverting from DPTRS values >7.00 to values <7.00 (36 vs. 23%). CONCLUSIONS DPTRS thresholds can improve T1D risk classification accuracy by identifying high-risk normoglycemic and low-risk dysglycemic individuals. The 7.00 DPTRS threshold characterizes risk more consistently between populations and has greater reliability than dysglycemia.
Brain dynamics of decision-making in the generalized trust game: Evidence from ERPs and EEG time-frequency analysis

Human societies are unique in terms of large-scale social cooperation and trust between unrelated people (generalized trust). As an important social signaling mechanism, generalized trust reduces transaction costs, facilitates cooperative behavior, and promotes human society’s prosperity. The question of why and when people trust each other has important implications for human social interaction and economic decision-making. Previous fMRI research utilizing the Trust Game has revealed brain regions involved in the decision to trust, including medial prefrontal cortex, caudate nucleus, amygdala, insula and dorsolateral prefrontal cortex. However, the extant research has failed to clearly reveal neurophysiological mechanisms of the investor’s decision-making in the Trust Game. To investigate the time course and neural oscillation courses of trust decision-making, we recorded the electroencephalographic (EEG) data of 21 healthy human participants while they played the role of trustor in the one-shot Trust Game; in this game, participants made decisions to trust or distrust the counterpart. In addition to behavioral data analysis and event-related potential (ERP) analysis, we also conducted spectral analysis to examine the neural oscillations underlying the trust game responses. Behavioral results indicated that participants made trusting decisions more than chance. Electrophysiological results suggested that distrusting choices induced a more negative N2 and a less positive P3 than did trusting choices. Spectral analysis results showed that the beta-band (18~28 Hz, 250~350 ms) power for distrusting choices was significantly larger than trusting choices; this may suggest greater inhibitory control exerted to distrust. Moreover, trusting choice after a negative outcome elicited a significant higher beta-band (15~20 Hz, 150~300 ms) power than did trusting choice after a positive outcome, while the beta-band power for distrusting choice after a negative outcome was similar compared to distrusting choice after a positive outcome. Our study provided some new insights into the psychophysiological processes underlying human’s decisions to trust strangers. Specifically, when making a decision to trust or distrust the counterpart, the distrusting choice induced a larger N2 than did the trusting choice, which may reflect greater cognitive control to inhibit trusting behavior. On the other hand, a more positive going P3 for the trusting choice than the distrusting choice may suggest that increased attention and motivation are associated with the trusting behavior. Moreover, the increased beta power across frontal areas for distrusting choices might reflect frontal inhibitory processes. These findings highlight the ingrained norm of cooperation and trust in modern societies, and provide preliminary spatio-temporal and spectral results understanding human’s decision-making in the one-shot Trust Game.
Improving Min-cut Placement for VLSI Using Analytical Techniques

Over the past few decades, several powerful placement algorithms have been used successfully in performing VLSI placement. With the increasing complexity of the VLSI chips, there is no clear dominant placement paradigm today. This work attempts to explore hybrid algorithms for large-scale VLSI placement. Our work aims to evaluate existing placement algorithms, estimate the ease of their reuse, and identify their sensitivities and limitations. We study particular aspects of large-scale placement and particular types of netlists on which cause commonly known placement algorithms produce strikingly sub-optimal layouts. Our work points out that significant room for improvement remains in terms of robustness of placement algorithms. Indications are that combining multiple placement algorithms is a worthwhile approach to improve performance on multiple types of netlists. In practice, it is important to have a robust and efficient linearsystem solver for VLSI analytical placement. To this end, we describe the design of a parallel variant for linear systems derived from VLSI analytical placement problems.
A WEIGHTED GENERALIZED LEAST – SQUARES SUPPORT VECTOR MACHINE

Among Neural Network methods, the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they automatically derive the “optimal” network structure, in respect to generalization error for a given problem. In practice it means, that a lot of decisions that had to be made during the design of a traditional NN (e.g. the number of neurons, the length and type of the learning cycle etc.) are eliminated, but the price to pay is SVM high computational complexity. The Least–Squares Support Vector Machine (LS–SVM) is especially important, because it is computationally more effective than the standard SVM methods. In the LS–SVM case training means solving a set of linear equations instead of the long and computationally hard quadratic programming problem that standard SVM involves [1]. While the least–squares version incorporates all training data in the network to produce the result, the traditional SVM selects some of them (the support vectors) that are important in the regression. This sparseness of traditional SVM can also be reached with LS-SVM by applying a pruning method [2], but this requires the entire large problem to be solved at least once. The LS–SVM method should also be able to handle outliers, resulting, e.g. from non–Gaussian noise, therefore another modification of the method, called weighted LS–SVM, is introduced to reduce the effects of this type of noise. The proposed Generalized LS–SVM [5] modifies the formulation of the LS–SVM, which can provide a pruned result. This approach is extended with weighting, which enables us to accomplish both goals.
Rhythmic Bursting in the Cortico-Subthalamo-Pallidal Network during Spontaneous Genetically Determined Spike and Wave Discharges

Absence seizures are characterized by impairment of consciousness associated with bilaterally synchronous spike-and-wave discharges (SWDs) in the electroencephalogram (EEG), which reflect paroxysmal oscillations in thalamocortical networks. Although recent studies suggest that the subthalamic nucleus (STN) provides an endogenous control system that influences the occurrence of absence seizures, the mechanisms of propagation of cortical epileptic discharges in the STN have never been explored. The present study provides the first description of the electrophysiological activity in the cortico-subthalamo-pallidal network during absence seizures in the genetic absence epilepsy rats from Strasbourg, a well established model of absence epilepsy. In corticosubthalamic neurons, the SWDs were associated with repetitive suprathreshold depolarizations correlated with EEG spikes. These cortical paroxysms were reflected in the STN by synchronized, rhythmic, high-frequency bursts of action potentials. Intracellular recordings revealed that the intraburst pattern in STN neurons was sculpted by an early depolarizing synaptic potential, followed by a short hyperpolarization and a rebound of excitation. The rhythmic hyperpolarizations in STN neurons during SWDs likely originate from a subpopulation of pallidal neurons exhibiting rhythmic bursting temporally correlated with the EEG spikes. The repetitive discharges in STN neurons accompanying absence seizures might convey powerful excitation to basal ganglia output nuclei and, consequently, may participate in the control of thalamocortical SWDs.
Initial Stability of Subtrochanteric Oblique Osteotomy in Uncemented Total Hip Arthroplasty: A Preliminary Finite Element Study

Background Subtrochanteric oblique osteotomy (SOO) has been widely used to reconstruct highly dislocated hips in uncemented total hip arthroplasty. The occurrence of complications can be attributed to the instability of the osteotomy region. The aim of this study was to evaluate the initial stability of SOO in uncemented total hip arthroplasty. Material/Methods A 3-dimensional finite element femur-stem model was created, and a virtual SOO was performed at 4 oblique angles: 30°, 45°, 60°, and 90°. The von Mises stress distribution in the femur-stem complex and the displacement under different oblique angles were evaluated in the SOO models, in comparison with that of the intact model. Results The study demonstrated that the distal fragment of the femur bore more stresses than the proximal fragment, and the maximum stress was concentrated in the femoral neck and the cortical bone, which contacted with the distal end of the stem. SOO increased the stress of both the femur and the stem, and fractures may occur in the stress concentration sites. Additionally, comparing the displacement at different oblique angles, the lateral region was larger than that of the medial region on the subtrochanteric osteotomy plane. The minimum micromotion on the osteotomy plane was obtained when the oblique angle was 45°. Conclusions The fit and fill of the distal fragment of the femur and the stem is essential for the stability of the subtrochanteric osteotomy region. The optimal oblique angle for SOO appears to be 45°.
Ku-Band Radar Altimeter Surface Wind Speed Algorithm

A surface wind speed retrieval algorithm from Ku-band radar altimeter backscatter coefficients is presented. It was derived using two-months of ENVISAT altimeter backscatter data collocated with ECMWF model and in situ wind speeds and was extensively verified for ENVISAT, ERS-2, and Jason-1/2 against model and in situ wind data. The algorithm performs better than the two-parameter (backscatter and significant wave height, SWH) algorithms of Jason-1/2. The success of the current algorithm raises a question regarding the usefulness of SWH alone as a second parameter for retrievals. It is argued that SWH alone is not the proper choice to represent the sea-state conditions.
Effective management of hypertension with dihydropyridine calcium channel blocker-based combination therapy in patients at high cardiovascular risk

The increasing prevalence of hypertension, owing to modern lifestyles and the increasing elderly population, is contributing to the global burden of cardiovascular (CV) disease. Although effective antihypertensive therapies are available, blood pressure (BP) is generally poorly controlled. In addition, the full benefits of antihypertensive therapy can only be realised when target BP is achieved. International guidelines and clinical trial evidence support the use of combination therapy to manage hypertension. In high‐risk patients, such as those with coronary artery disease, diabetes and renal dysfunction, BP targets are lower and there is a need for intensive management with combination therapy to control BP and provide additional CV risk reduction benefits.
Finding, Assessing, and Integrating Statistical Sources for Data Mining

As the knowledge discovery process has been widely applied in a variety of domains, there is a growing opportunity to use the Linked Open Data (LOD) cloud as a primary data source for knowledge discovery. The tasks of finding the relevant data from various sources and then using that data for the desired analysis are the key challenges. There is a striking increase on the availability of statistical data and indicators (e.g. social, economic) in the LOD, and the Cube ontology has become the de facto standard for their description according to a multi-dimensional model. In this paper we discuss a detailed scenario for using the LOD as a primary source of data for building analysis models in the Peacebuilding domain. Next, we present an approach to finding potentially relevant cube datasets in the LOD cloud, assessing their compatibility, and then integrating the compatible datasets to enable the application of data
Impact of long term Yoga practice on sleep quality and quality of life in the elderly

Background: Sleep disturbances and decline in the physical functionality are common conditions associated with aging. Pharmacological treatment of sleep disturbances can be associated with various adverse effects. Short term trials of Yoga on sleep have shown beneficial effects. Objectives: To evaluate the effect of long-term Yoga exercises on sleep quality and quality of life (QOL) in the elderly. Materials and Methods: This was a cross-sectional study in which data were collected from elderly people aged 60 years or more living in Nagpur city. We employed two types of survey questionnaires: Pittsburgh sleep quality index (PSQI) and QOL Leiden-Padua (LEIPAD) Questionnaire. A total of 65 elderly men and women who signed an informed consent and completed questionnaires were included in the study. Sleep quality score PSQI and QOL (LEIPAD Questionnaire) score of the study group were evaluated and compared with the control group using Mann-Whitney U test. Results: Total PSQI score in Yoga group was lower than that of the control group. Also various QOL scores of the Yoga groups were higher than the control group. Conclusion: Addition of regular Yoga exercises in the daily routine of elderly people can help to achieve good sleep quality as well as improve the QOL.
Thermal Evaluation and Optimization of Polycrystalline Solar Silicon Cell by Using Water as Surface Coolant.

The aim of this paper is to examine the increase in the efficiency of solar cell by decreasing its temperature using water as a coolant. The energy requirement of the world is rising day by day and it is difficult to supply energy using conventional sources since they are depleting quickly. Hence to meet the demand of ever increasing population nonconventional energy should be used. Solar energy is one of the sources of energy which can satisfy the world's demand if utilization is done properly. The main barrier in using solar energy as a source of energy is cost and efficiency of solar panels. Both these parameters are inversely related to each other. If Efficiency is more, fewer solar cells are required to generate the required amount of energy and will decrease the cost. Keywords—Efficiency, Non-conventional energy, solar energy, Water.
Leveraging the Construction of Semantic Web Applications Using the Model Driven Architecture

This paper describes an ongoing research work carried out at the Software Engineering Laboratory of the Computer Science Department at the Catholic University of Rio de Janeiro. This work tries to leverage the construction of Semantic Web applications through the use of OMG’s Model Driven Architecture (MDA). An annotation tool was developed to manage the knowledge of a group of researchers and now some tools to access the semantically annotated data need to be developed. For that purpose, the use of MDA seems quite applicable.
Temperature and Temperament: Evidence from a Billion Tweets

What is the welfare cost of environmental stress? The change in amenity values resulting from temperature increases may be a substantial unaccounted-for cost of climate change. Because there is no explicit market for climate, prior work has relied on cross-sectional variation or survey data to identify this cost. This paper presents an alternative method of estimating preferences over nonmarket goods which accounts for unobserved cross-sectional and temporal variation and allows for precise estimates of nonlinear effects. Specifically, I create a rich dataset on hedonic state: a geographically and temporally dense collection of updates from the social media platform Twitter, scored using a set of both humanand machine-trained sentiment analysis algorithms. Using this dataset, I find limited evidence of temperature effects on hedonic state in low temperatures and strong evidence of a sharp decline in hedonic state above 70◦F. This finding is robust across all measures of hedonic state and to a variety of specifications. ∗University of California, Berkeley. Energy Institute at Haas; 207 Giannini Hall, Berkeley, CA 947203310; Phone: (507) 581-1807; E-mail: pbaylis@berkeley.edu. I am grateful to Maximilian Auffhammer, Severin Borenstein, and Solomon Hsiang for their invaluable suggestions, and to Michael Anderson, Judson Boomhower, Josh Blonz, Marshall Burke, Fiona Burlig, Tamma Carleton, Richard Carson, Aluma Dembo, Meredith Fowlie, Walter Graf, Sylvan Herskowitz, Elizabeth Sadoulet, and to seminar participants at UC Berkeley, the AERE Annual Conference, the CU Environmental and Resource Economics Workshop, and the Heartland Workshop at Illinois. Errors are entirely my own. †The latest version of this paper is available at: http://are.berkeley.edu/candidate/patrick-baylis.
Expression Sensitivity Analysis of Human Disease Related Genes

Background. Genome-wide association studies (GWAS) have shown its revolutionary power in seeking the influenced loci on complex diseases genetically. Thousands of replicated loci for common traits are helpful in diseases risk assessment. However it is still difficult to elucidate the variations in these loci that directly cause susceptibility to diseases by disrupting the expression or function of a protein currently. Results. We evaluate the expression features of disease related genes and find that different diseases related genes show different expression perturbation sensitivities in various conditions. It is worth noting that the expression of some robust disease-genes doesn't show significant change in their corresponding diseases, these genes might be easily ignored in the expression profile analysis. Conclusion. Gene ontology enrichment analysis indicates that robust disease-genes execute essential function in comparison with sensitive disease-genes. The diseases associated with robust genes seem to be relatively lethal like cancer and aging. On the other hand, the diseases associated with sensitive genes are apparently nonlethal like psych and chemical dependency diseases.
A Theory for Photometric Self-Calibration of Multiple Overlapping Projectors and Cameras

A theory for photometric calibration of cameras and multiple projectors with overlapping displays is presented. The theory is predominantly based on the analysis of isointensity curves in projector input state space curves which define different projector input intensity combinations that result in the same camera-observed pixel intensities. Three methods, which have different speed and accuracy tradeoffs, are proposed for recovering the projector-to-screen and screento- camera intensity transfer functions. The methods do not require a specific parametric model for the shapes of these functions, nor impose any smoothness constraints. Additional methods are described for calibrating projector offsets and binary light sources, and also extending the perpixel analysis to other pixels in the display. The methods do not require the use of expensive equipment, and may be carried out with a low dynamic range camera with minimal controls.
Survey on Recommender systems

Social networks have become a great source of information, for that several applications have been proposed to extract information from social networks such as: recommender systems. The speed and scalability of such a recommender algorithm is as important as the actual logic behind the algorithm because such algorithms generally run over a "huge" graph and implementing these normally would probably take a lot of time for recommending items even for just one user. The basic idea of the algorithm is to recommend items to users connected via social network. In this paper various categories in which recommender systems are classified are discussed. Also various open sources, scalable, distributed and non distributed graph processing platforms are also discussed. The concept of recommender system with Giraph which is an open source distributed graph processing platform for highly reliable, scalable graph datasets is introduced in this paper.
Organization and development of brain stem auditory nuclei of the chicken: Dendritic gradients in nucleus laminaris

Nucleus laminaris (NL) is a third‐order auditory nucleus in the avian brain stem which received spatially‐segregated binaural inputs from the second‐order magnocellular nuclei. The organization of dendritic structure in NL was examined in Golgi‐impregnated brains from hatchling chickens. Quantitative analyses of dendritic size and number were made from camera lucida drawings of 135 neurons sampled from throughout the nucleus.