Miracle-dz/UniFAR-FTUs huggingface dataset:
A fast background estimation method for vehicle surveillance

This paper presents a fast background estimation method for vehicle surveillance based on multi-resolution analysis (MRA) and block updating strategy. Firstly, an approximate expression of original image is achieved by (MRA) and the feature difference is calculated along adjacent frames to divide the foreground and background; Secondly, the isolated pixels are removed by morphologic operation; and then each block of the original image is classified to foreground or background according to the relationship of the multi-resolution analysis; finally, the background is updated block by block based on the hypotheses that moving object is not fixed in a certain place. The proposed method realizes the estimation and updating of background by block and the application of MRA can improve the computation efficiency. Experimental results show the validity and the blur effect of the conventional methods is avoided.
Brain imaging and its implications for studying centrally targeted treatments in irritable bowel syndrome: a primer for gastroenterologists

Research into brain-gut interactions, and the use of brain imaging, as potential investigative tools for functional gastrointestinal disorders, such as irritable bowel syndrome, is a promising new area. Studies are beginning to identify the structure and function of regions of the brain and their relationships to pain perception, stress, and other psychosocial variables. These imaging modalities may also have diagnostic potential, and perhaps even therapeutic applications, particularly with regard to understanding the benefit of centrally targeted modalities such as antidepressants and psychological treatments.
Case study on applying augmented reality for process supervision in industrial use cases

Augmented Reality (AR) applications gain more and more relevance in various industrial applications, e. g. for product presentations, education, engineering, etc. In the industrial domain, especially in process supervision applications, a number of standards and guidelines have been established to ensure that the design of user interfaces meets the safety requirements of plants or factories. Hence, we seek an evaluation if these guidelines can be applied to AR applications. In this paper, we present the first preliminary results of a case study on the application of those standards to a visual AR application for in-field inspection and servicing scenarios.
- Kernels Must And Can Be

For a general acceptance,-kernels must be fast and not burden applications. For fulllling these conditions, cache architectures require-kernels to be small. The L4-kernel shows that smallness can be achieved. 1. -kernels must be small This is not obvious. Most rst-generation-kernels were large; typically they need 300 Kbyte of code and 140 system calls. Some of their architects argued that`' in this context meansìower level' and not`small size'. Demanding smallness radically diiers from this approach. It could (and in fact it does) change-kernel technology dramatically. Why should-kernels be as small as possible? (We avoid the term \minimal" because of its mathematical implications.) The reasons are performance, exibility and perhaps correctness. 1.1. \A non-small-kernel is not fast. " The most relevant performance costs of a-kernel result from its cache consumption. If a frequently invoked kernel operation accesses a substantial part of the primary cache (\\oods the cache"), the user is punished twice. First, the kernel operation itself is degraded by cache misses, since it must displace user code and data. Second, the user program has to pay for additional cache misses, since it must re-establish its cache working set. From Chen's 1993] measurements for a Mach benchmark on a DS 5000/200, we can calculate that on average 20% of the system cache misses are caused by user-kernel competition. We expect a substantially higher number for more up-to-date hardware and faster (but non-small) kernels. 1 On modern processors, the mentioned cache misses might consume up to 5 ((ve! ) times as many cycles as the kernel code required for execution in the ideal case. What happens if the kernel working set is reduced, say from 75% to 15% of the cache size? The small kernel needs only 1/5 of the instructions. Since-kernel operations usually execute very few loops, we can expect a corresponding 4 to 5 times speed improvement. There is a good chance that competition between user working-set and kernel working-set is substantially reduced. Ideally, frequently invoking a-kernel operation does neither cost kernel-level nor subsequent user-level cache misses. A somehow strange eeect occurs if the-kernel working set is substantially larger than the cache: enlarging the cache does not really improve the-kernel's performance ; in the worst case, it might even degrade it since the cache-reestablishing costs increase. For a rough understanding of these eeects, we look at a rather naive model: the cache is highly associative and the application always lls it completely between successive-kernel …
Wortassoziation und Schizophrenie − Eine empirische Studie

Since Bleuler's (1911) work on dementia praecox, numerous studies on associative disturbances in schizophrenics have been published. Methodological flaws and difficulties in interpreting the disturbances consistently have brought about a certain dilemma: they are unanimously considered a basic disorder in schizophrenia, but the problem of their reliable evaluation has remained unanswered. 43 schizophrenics, 15 affective psychotics, and 46 normals were investigated in order to compare different forms of the word association test (WAT). The schizophrenics gave less common responses than the normals in the free association task. However, the two groups differed more widely in their performance when asked to respond "individually", "commonly", or using a multiple-choice associative test. The affective psychotics were similar in their response behaviour, partly to the schizophrenics (free and common response conditions; multiple-choice test), partly to the normals (individual response condition). The relationship of the WAT to personality characteristics (Eysenck's psychoticism), the influence of psychopathology and the course of the disease, the patients' well-being and self-report of speech and thought disorders are discussed.
A simple quasi-orthogonal space-time scheme for use in asynchronous virtual antenna array enabled cooperative networks

In this paper we present a novel full-rate and full-diversity quasi-orthogonal space-time block coding scheme for use in asynchronous cooperative relay networks. A variant of orthogonal frequency division multiplexing (OFDM) is implemented at the source node to mitigate the effects of random delays at the relay nodes, which operate in a simple amplify-and-forward mode. Utilizing a feedback channel, a simple phase rotation is applied at the relay nodes to extract full order diversity. A simple feedback quantization approach which reduces the overhead in the feedback channel for practical systems is also proposed. Average bit error rate simulations confirm the utility of the schemes.
Assessing Sustainable Behavior and its Correlates: A Measure of Pro-Ecological, Frugal, Altruistic and Equitable Actions

Measures of sustainable behavior (SB) usually include the self-report of activities aimed at the conservation of the natural environment. The sustainability notion explicitly incorporates both the satisfaction of human needs and the need of conserving the natural environment. Yet, the assessment of sustainable behaviors rarely considers the protection of the social environment as situation to investigate. In this paper, we propose the use of an instrument assessing SB, which includes the report of pro-ecological and frugal actions in addition to altruistic and equitable behaviors. The responses provided by 807 Mexican undergraduates to a questionnaire investigating those four instances of SB were processed within a structural equation model. Emotional (indignation due to environmental destruction, affinity towards diversity, happiness) and rational (intention to act) factors assumedly linked to sustainable behavior were also investigated. Significant interrelations among pro-ecological, frugal, altruistic and equitable behaviors resulted, suggesting the presence of a higher-order-factor that we identified as SB. This factor, in turn, significantly correlated with the rest of the investigated pro-environmental factors.
Carbon Price Dynamics – Evidence from Phase II of the European Emission Trading Scheme

In this paper we empirically investigate potential determinants of allowance (EUA) price dynamics in the European Union Emission Trading Scheme (EU ETS) during Phase II. In contrast to previous papers, we analyze a significantly longer time series, place particular emphasis on the importance of price variable selection, and include an extensive data of renewable energy feed-in in Europe. We show (i) that results are extremely sensitive to choosing different price series of potential determinants, such as coal and gas prices, (ii) that EUA price dynamics are only marginally influenced by renewable energy provision in Europe, and iii) that EUA prices currently do not reflect marginal abatement costs across Europe. We conclude that the expectation of a more mature allowance market in Phase II cannot be confirmed.
Improving TCP/IP over geostationary satellite links

We focus in this paper on the undesirable phenomenon of early buffer overflow during slow start (SS) when TCP operates in large bandwidth-delay product networks such as those including geostationary satellite links. This phenomenon, already identified by Altman, Bolot, Nain, Elouadghiri, Erramdani, Brown and Collange (1995) and by Lakshman and Madhow (see IEEE/ACM Transactions on Networking, 1997) is caused by the bursty type of TCP traffic during SS. It results in an underestimation of the available bandwidth and a degradation in TCP throughput. Given the high cost and the scarcity of satellite links, it is of importance to find solutions to this problem. We propose two simple modifications to TCP algorithms and illustrate their effectiveness via mathematical analysis and simulations. First, we reduce the SS threshold in order to get in congestion avoidance before buffer overflow. Second, we space the transmission of packets during SS.
Cardioprotection by Ecto-5′-Nucleotidase (CD73) and A2B Adenosine Receptors

Background— Ecto-5′-nucleotidase (CD73)–dependent adenosine generation has been implicated in tissue protection during acute injury. Once generated, adenosine can activate cell-surface adenosine receptors (A1AR, A2AAR, A2BAR, A3AR). In the present study, we define the contribution of adenosine to cardioprotection by ischemic preconditioning. Methods and Results— On the basis of observations of CD73 induction by ischemic preconditioning, we found that inhibition or targeted gene deletion of cd73 abolished infarct size-limiting effects. Moreover, 5′-nucleotidase treatment reconstituted cd73−/− mice and attenuated infarct sizes in wild-type mice. Transcriptional profiling of adenosine receptors suggested a contribution of A2BAR because it was selectively induced by ischemic preconditioning. Specifically, in situ ischemic preconditioning conferred cardioprotection in A1AR−/−, A2AAR−/−, or A3AR−/− mice but not in A2BAR−/− mice or in wild-type mice after inhibition of the A2BAR. Moreover, A2BAR agonist treatment significantly reduced infarct sizes after ischemia. Conclusions— Taken together, pharmacological and genetic evidence demonstrate the importance of CD73-dependent adenosine generation and signaling through A2BAR for cardioprotection by ischemic preconditioning and suggests 5′-nucleotidase or A2BAR agonists as therapy for myocardial ischemia.
Adaptive Partitioning for Very Large RDF Data

Distributed RDF systems partition data across multiple computer nodes (workers). Some systems perform cheap hash partitioning, which may result in expensive query evaluation, while others apply heuristics aiming at minimizing inter-node communication during query evaluation. This requires an expensive data preprocessing phase, leading to high startup costs for very large RDF knowledge bases. Apriori knowledge of the query workload has also been used to create partitions, which however are static and do not adapt to workload changes; hence, inter-node communication cannot be consistently avoided for queries that are not favored by the initial data partitioning. In this paper, we propose AdHash, a distributed RDF system, which addresses the shortcomings of previous work. First, AdHash applies lightweight partitioning on the initial data, that distributes triples by hashing on their subjects; this renders its startup overhead low. At the same time, the locality-aware query optimizer of AdHash takes full advantage of the partitioning to (i)support the fully parallel processing of join patterns on subjects and (ii) minimize data communication for general queries by applying hash distribution of intermediate results instead of broadcasting, wherever possible. Second, AdHash monitors the data access patterns and dynamically redistributes and replicates the instances of the most frequent ones among workers. As a result, the communication cost for future queries is drastically reduced or even eliminated. To control replication, AdHash implements an eviction policy for the redistributed patterns. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds.
Thermodynamic stability of small hairpin RNAs highly influences the loading process of different mammalian Argonautes

MicroRNAs and siRNAs interact with target sequences in mRNAs, inducing cleavage- and non-cleavage–based gene repression through the RNA-induced silencing complex (RISC) that consists of one of four mammalian Argonaute proteins, Ago1–Ago4. The process of how Dicer substrate small hairpin RNAs (shRNAs) are loaded into different mammalian Agos in vivo is not well established. Here we report that shRNAs are loaded into mammalian Agos in two stepwise processes, physical association and activation, with the latter being the rate-limiting step with noncleaving RISC. We establish that, although RNA duplexes processed from shRNAs bind to Agos in cells with similar affinity, the degree by which the complexes are activated (coupled with the removal of the passenger strand) correlates with the thermodynamic instability of RNA duplexes being loaded rather than the structure of the RNA, as was previously demonstrated in Drosophila. Interestingly, Ago loading of siRNAs is less sensitive to thermostability than that of their shRNA equivalents. These results may have important implications for the future design of RNAi-based therapeutics.
ROBUST FINGERPRINT IDENTIFICATION BASED ON HYBRID PATTERN RECOGNITION METHODS

For personal identification, fingerprint identification has been much more widely used than other automatic biometric identification methods. For reliable feature extraction we analyze the direction of ridges, and the structural characteristics, such as the ridge line width and interval, are automatically estimated based on the ridge line following algorithm. To eliminate false features outside the region of interest (ROI), we generate adaptive matching boundaries. The concept of fuzzy sets is applied to the extracted features and the quantitative feature values are defined. In the feature matching stage, we introduce a weighted matching score using quantitative feature values to guarantee reliable matching results. Furthermore, a two-step estimation of transformation parameters is employed to reduce the computational complexity. The experimental results show that our system can achieve a fast personal identification with a good performance.
Spatio-temporal decoupling of stomatal and mesophyll conductance induced by vein cutting in leaves of Helianthus annuus

Reduction of hydraulic conductance to the canopy has been shown to result in stomatal responses to limit transpiration. To test for similar responses to perturbations of the hydraulic network in leaves, we simultaneously measured leaf gas exchange with spatially explicit chlorophyll-a fluorescence and leaf temperature to examine the effects of cutting a primary leaf vein in Helianthus annuus. We repeated the leaf treatment at each of three different vapor pressure deficits and monitored the short-term dynamics of gas exchange following the treatment. Immediately after treatment, photosynthesis and stomatal conductance (gs) showed a transient “wrong way” response in which photosynthesis declined despite increased gs. Comparisons of fluorescence and temperature across the leaf showed that both photosynthesis and gs were transiently patchy across the measured leaf area, but that the patchiness of the two processes did not correspond in space or time. This suggests that photosynthesis and gs respond to vein cutting-induced cavitation via different mechanisms. Because the stomatal response varied by vapor pressure difference condition but photosynthesis did not, it is likely that gs, but not photosynthesis, responded to a hydraulic signal. In contrast, we hypothesize that photosynthesis declined due to a wound-induced electrical signal that has recently been shown to transiently decrease mesophyll conductance to CO2. The interaction of epidermal hydraulics and the electrical signal across the leaf likely created a patchy pattern of chlorophyll fluorescence and leaf temperature that cannot be explained through the action of a single signal.
Oxytocin Selectively Improves Empathic Accuracy

Oxytocin is known to regulate prosocial behavior and social cognition in animals (Ross & Young, 2009), and recent studies suggest that oxytocin may have similar functions in humans. For example, oxytocin increases trust (Kosfeld, Heinrichs, Zak, Fischbacher, & Fehr, 2005) and accuracy in mental-state attribution (Domes, Heinrichs, Michel, Berger, & Herpertz, 2007; Guastella et al., 2009). These findings have generated excitement about oxytocin’s potential to ameliorate social deficits in such disorders as social phobia and autism (Bartz & Hollander, 2006; Guastella et al., 2009; Kosfeld et al., 2005). This excitement has not been confined to the scientific community: Dubbed the “hormone of love,” oxytocin is a common topic in the popular press. Is oxytocin truly a universal social panacea? Although some studies have shown that oxytocin improves social cognition and empathy (Domes et al., 2007; Guastella et al., 2009), others have not (Singer et al., 2008). Even studies demonstrating positive effects have ambiguities: Domes et al. (2007) found that oxytocin improved performance for difficult—but not easy—test items. These observations imply that rather than working universally, oxytocin may selectively facilitate social cognition given certain constraints. For example, by altering specific motivational or cognitive states, oxytocin might increase the salience of social cues, which in turn could improve social-cognitive performance for some individuals, but not others. The effects of oxytocin, then, should be most pronounced in individuals who—at baseline—are less socially proficient; this would be consistent with broader interactionist views emphasizing that individual differences in competencies interact with situational variables to determine behavior (Mischel & Shoda, 1995). To test whether normal variance in social proficiency moderates the effects of oxytocin on social-cognitive performance, we used a randomized, double-blind, placebo-controlled, crossover challenge in which participants received either intranasal oxytocin or a placebo and performed an empathicaccuracy task that naturalistically measures social-cognitive abilities (Zaki, Bolger, & Ochsner, 2008). We measured variance in baseline social competencies with the Autism Spectrum Quotient (AQ; Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), a self-report instrument that predicts social-cognitive performance (Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001). We hypothesized that drug condition and AQ score would interact to predict performance on the empathic-accuracy task, with oxytocin having the most pronounced effects for less socially proficient individuals (i.e., those with higher AQ scores).
A Survey on Various Optimization Techniques with Respect to Flexible Job Shop Scheduling

The purpose of this paper is to show the survey study done on the optimization algorithms for the Flexible Job Shop Scheduling Problem. There are many algorithms that have been used for finding the optimal solution of Flexible Job Shop Scheduling Problem. Here the Multi Objective aspects have been also taken into consideration. The FJS problem has already been proved an NP hard problem. Pareto optimality principal enriches the solution with the ease of finding the optimal solution.
Considering Feature Interactions in Product Lines: Towards the Automatic Derivation of Dependencies between Product Variants

Employing a software product line presents a systematic approach for the reuse of software assets. This is achieved by the explicit modeling of variability, i.e., the description of points of variation and variants within the development artifacts. To derive concrete products from the reusable assets, dependencies between variants have to be considered when binding the overall variability. Consequently, being aware of the dependencies between variants is essential, as otherwise incorrect products will result. However, determining such dependencies is far from trivial because in reasonably complex systems many such dependencies might have to be elicitated. Therefore, an approach for systematically and semi-automatically deriving variant dependencies from product line assets is introduced in this paper. Upon recognizing that many of the variants can be understood as features, this approach is realized by extending existing solutions for the automatic detection of feature interactions in single products.
2015 Ieee International Conference on Big Data (big Data) Smog Disaster Forecasting Using Social Web Data and Physical Sensor Data

—Smog disaster is a type of air pollution event that negatively affects people's life and health. Forecasting smog disasters may largely reduce potential loss that they may cause. However, it is a great challenge since smog disasters are often caused by many complex factors. With the availability of huge amounts of data from the social web and physical sensors, covering information of air quality, meteorology, social event, human mobility, people's opinion, etc., it becomes possible to utilize such big data to forecast smog disasters. Especially, we can investigate the effect of social activities in smog disaster forecasting with the help of social web, which is ignored in traditional studies. In this paper, we propose a big data approach named B-Smog for smog disaster forecasting. It mainly has two components: 1) features extraction from multiple data sources to model the factors that indicate the appearance or disappearance of a smog disaster like traffic condition, human mobility, weather condition and air pollution transportation; 2) learning and predicting with heterogeneous features in multiple views. For the second component, we propose a prediction model based on an ensemble learning framework and artificial neural networks (ANNs), which achieves high accuracy in this application and can also be applied to other similar problems. We present the effectiveness of B-Smog through two cases studies in Beijing and Shanghai, and evaluate the accuracy of the prediction model through comparing it with some baselines. Moreover, the empirical findings of our study can also support decision making in smog disaster management.