Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Motion Trajectory Analysis for Dual Human Interaction Using Video Sequences

Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.). Keywords—Motion detection, motion tracking, trajectory analysis, video surveillance.
Dissecting UbuntuOne: Autopsy of a Global-scale Personal Cloud Back-end

Personal Cloud services, such as Dropbox or Box, have been widely adopted by users. Unfortunately, very little is known about the internal operation and general characteristics of Personal Clouds since they are proprietary services. In this paper, we focus on understanding the nature of Personal Clouds by presenting the internal structure and a measurement study of UbuntuOne (U1). We first detail the U$1$ architecture, core components involved in the U1 metadata service hosted in the datacenter of Canonical, as well as the interactions of U$1$ with Amazon S3 to outsource data storage. To our knowledge, this is the first research work to describe the internals of a large-scale Personal Cloud. Second, by means of tracing the U$1$ servers, we provide an extensive analysis of its back-end activity for one month. Our analysis includes the study of the storage workload, the user behavior and the performance of the U1 metadata store. Moreover, based on our analysis, we suggest improvements to U1 that can also benefit similar Personal Cloud systems. Finally, we contribute our dataset to the community, which is the first to contain the back-end activity of a large-scale Personal Cloud. We believe that our dataset provides unique opportunities for extending research in the field.
BPS and non BPS 7D Black Attractors in M-Theory on K3

We study the BPS and non BPS black attractors in 7D N=2 supergravity embedded in 11D M-theory compactified on K3. Combining Kahler and complex moduli in terms of SO(3) representations, we build the Dalbeault like (DL) basis for the second cohomology of K3 and set up the fundamental relations of the special "hyperKahler" geometry of the underlying moduli space of the 7D theory. We study the attractor eqs of the 7D black branes by using the method of the criticality of the effective potential and also by using the extension of the so called 4D new attractor approach to 7D N=2 supergravity. A comment, regarding a 6D/7D correspondence, along the line of Ceresole-Ferrara-Marrani used for 4D/5D, ref.arXiv:0707.0964, is made.
Chimera: hybrid program analysis for determinism

Chimera uses a new hybrid program analysis to provide deterministic replay for commodity multiprocessor systems. Chimera leverages the insight that it is easy to provide deterministic multiprocessor replay for data-race-free programs (one can just record non-deterministic inputs and the order of synchronization operations), so if we can somehow transform an arbitrary program to be data-race-free, then we can provide deterministic replay cheaply for that program. To perform this transformation, Chimera uses a sound static data-race detector to find all potential data-races. It then instruments pairs of potentially racing instructions with a weak-lock, which provides sufficient guarantees to allow deterministic replay but does not guarantee mutual exclusion. Unsurprisingly, a large fraction of data-races found by the static tool are false data-races, and instrumenting them each of them with a weak-lock results in prohibitively high overhead. Chimera drastically reduces this cost from 53x to 1.39x by increasing the granularity of weak-locks without significantly compromising on parallelism. This is achieved by employing a combination of profiling and symbolic analysis techniques that target the sources of imprecision in the static data-race detector. We find that performance overhead for deterministic recording is 2.4% on average for Apache and desktop applications and about 86% for scientific applications.
Conservation Planning for Coral Reefs Accounting for Climate Warming Disturbances

Incorporating warming disturbances into the design of marine protected areas (MPAs) is fundamental to developing appropriate conservation actions that confer coral reef resilience. We propose an MPA design approach that includes spatially- and temporally-varying sea-surface temperature (SST) data, integrating both observed (1985–2009) and projected (2010–2099) time-series. We derived indices of acute (time under reduced ecosystem function following short-term events) and chronic thermal stress (rate of warming) and combined them to delineate thermal-stress regimes. Coral reefs located on the Brazilian coast were used as a case study because they are considered a conservation priority in the southwestern Atlantic Ocean. We show that all coral reef areas in Brazil have experienced and are projected to continue to experience chronic warming, while acute events are expected to increase in frequency and intensity. We formulated quantitative conservation objectives for regimes of thermal stress. Based on these objectives, we then evaluated if/how they are achieved in existing Brazilian MPAs and identified priority areas where additional protection would reinforce resilience. Our results show that, although the current system of MPAs incorporates locations within some of our thermal-stress regimes, historical and future thermal refugia along the central coast are completely unprotected. Our approach is applicable to other marine ecosystems and adds to previous marine planning for climate change in two ways: (i) by demonstrating how to spatially configure MPAs that meet conservation objectives for warming disturbance using spatially- and temporally-explicit data; and (ii) by strategically allocating different forms of spatial management (MPA types) intended to mitigate warming impacts and also enhance future resistance to climate warming.
Pyrococcus furiosus flagella: biochemical and transcriptional analyses identify the newly detected flaB0 gene to encode the major flagellin

We have described previously that the flagella of the Euryarchaeon Pyrococcus furiosus are multifunctional cell appendages used for swimming, adhesion to surfaces and formation of cell-cell connections. Here, we characterize these organelles with respect to their biochemistry and transcription. Flagella were purified by shearing from cells followed by CsCl-gradient centrifugation and were found to consist mainly of a ca. 30 kDa glycoprotein. Polymerization studies of denatured flagella resulted in an ATP-independent formation of flagella-like filaments. The N-terminal sequence of the main flagellin was determined by Edman degradation, but none of the genes in the complete genome code for a protein with that N-terminus. Therefore, we resequenced the respective region of the genome, thereby discovering that the published genome sequence is not correct. A total of 771 bp are missing in the data base, resulting in the correction of the previously unusual N-terminal sequence of flagellin FlaB1 and in the identification of a third flagellin. To keep in line with the earlier nomenclature we call this flaB0. Very interestingly, the previously not identified flaB0 codes for the major flagellin. Transcriptional analyses of the revised flagellar operon identified various different cotranscripts encoding only a single protein in case of FlaB0 and FlaJ or up to five proteins (FlaB0-FlaD). Analysing the RNA of cells from different growth phases, we found that the length and number of detected cotranscript increased over time suggesting that the flagellar operon is transcribed mostly in late exponential and stationary growth phase.
Students’ Trust Formation and Credibility Judgements in Online Health Information – A Review Article

Health information is a frequent subject for online information seeking. Research on the phenomenon has to a certain extent included students. This review, based on an analysis of 61 articles, shows the current state of the art of research on students’ trust in online health information. The review covers methodological approaches and findings of previous previous empirical studies: research design; trustworthy health information sources; credibility assessment; and factors impacting on trust formation. The analysis of research designs reveals that the survey method was most frequent, but small qualitative studies were also occurring. More than half of the studies were administered in the USA, while only a smaller part concerned ‘non-Western’ countries. Female subjects were more frequent than male. The concept of trust was not always explicitly defined in the studies. The students' actual propensity to use internet was generally taken as an expression of trust. The antecedents of trust identified in the studies can be summarized as the perceived quality of the information, the perceived credibility of the source or source provider, the users’ general inclination to trust, the actual use of information, and the perceived intelligibility of the information. The findings show that Internet was among the main sources for health information, but parents or other family members, friends, schools, health professionals were also frequent sources of health information, and students were not immediately accepting online information as trustworthy. The students’ trust and credibility judgments were influenced by social and demographic, cultural, psychological, knowledge and skills-related, and source, system and content-related factors. Governmental and organizational websites were reported as the most trustful sources, although some issues regarding website features and presentation of content were reported as barriers. Easy access were of importance for using a particular resource, but there seemed to be a learning effect impacting on seeking behaviour and trust formation.
Convergence and stability properties of minimal polynomial and reduced rank extrapolation algorithms

The minimal polynomial and reduced rank extrapolation algorithms are two acceleration of convergence methods far sequences of vectors. In a recent survey these methods were tested and compared with the scalar, vector, and topological epsilon algorithms, and were observed to be more efficient than the latter. It was also observed that the two methods have similar convergence properties. The purpose of the present work is to analyze the convergence and stability properties of these methods, and to show that they are bona fide acceleration methods when applied to a class of vector sequences that includes those sequences obtained from systems of linear equations by using matrix iterative methods.
Colon-Derived Liver Metastasis, Colorectal Carcinoma, and Hepatocellular Carcinoma Can Be Discriminated by the Ca2+-Binding Proteins S100A6 and S100A11

Background It is unknown, on the proteomic level, whether the protein patterns of tumors change during metastasis or whether markers are present that allow metastases to be allocated to a specific tumor entity. The latter is of clinical interest if the primary tumor is not known. Methodology/Principal Findings In this study, tissue from colon-derived liver metastases (n = 17) were classified, laser-microdissected, and analysed by ProteinChip arrays (SELDI). The resulting spectra were compared with data for primary colorectal (CRC) and hepatocellular carcinomas (HCC) from our former studies. Of 49 signals differentially expressed in primary HCC, primary CRC, and liver metastases, two were identified by immunodepletion as S100A6 and S100A11. Both proteins were precisely localized immunohistochemically in cells. S100A6 and S100A11 can discriminate significantly between the two primary tumor entities, CRC and HCC, whereas S100A6 allows the discrimination of metastases and HCC. Conclusions Both identified proteins can be used to discriminate different tumor entities. Specific markers or proteomic patterns for the metastases of different primary cancers will allow us to determine the biological characteristics of metastasis in general. It is unknown how the protein patterns of tumors change during metastasis or whether markers are present that allow metastases to be allocated to a specific tumor entity. The latter is of clinical interest if the primary tumor is not known.
Scheduling stream programs with improving arithmetic unit usage on NoC-based VLIW multi-core architectures

Stream programming model has received a lot of interest due to its naturally-exposed task, data and pipeline parallelism. Many researches concentrated on scheduling stream programs on multi-core systems. However, few of them consider the arithmetic unit utilization, which is a vital factor to determine the performance of multi-core systems. This paper focuses on scheduling stream programs on NoC-based VLIW multi-core architectures, aiming at improving the performance through increasing the arithmetic unit utilization. Three phases are proposed for the scheme. First, the stream program is replicated into multiple threads for providing enough parallel kernels. Second, parallel kernels are grouped and operators of each kernel group are scheduled together for high arithmetic unit utilization. Third, a hierarchical integer linear programming (ILP)-based methodology is proposed to map kernel groups onto each core for optimizing the maximum workload. A set of benchmarks are exploited for evaluation. Experimental results show that, compared with two other existing scheduling schemes, our proposed scheme can significantly improve the performance of the multi-core processor.
State self-esteem ratings in women with bulimia nervosa and bulimia nervosa in remission.

OBJECTIVE Bulimia nervosa (BN) is associated with low self-esteem. This study was designed to assess whether low self-esteem persists in nondepressed individuals who have recovered from BN (BN-R). METHOD Study groups included BN (n = 22), BN-R (n = 20), and healthy controls (n = 42). Participants were medication-free, and none met criteria for current major depression. Assessment instruments included the State Self-Esteem Scale (SSES), a self-rating scale designed to measure state-related changes in self-esteem. RESULTS Consistent with previous reports, SSES scores for BN were lower than for controls (p < .001). For BN-R, SSES scores were higher than for BN (p < .001), but lower than for controls (p < .025). For BN-R, scores on the SSES Appearance subscale were inversely correlated with ratings of dietary restraint (p < .005). CONCLUSION This study provides new evidence for persistent low self-esteem following recovery from BN. Follow-up studies are needed to assess whether low self-esteem contributes to recurrent dieting and risk for relapse.
Leukotriene B4 Enhances NOD2-Dependent Innate Response against Influenza Virus Infection

Leukotriene B4 (LTB4), a central mediator of inflammation, is well known for its chemoattractant properties on effectors cells of the immune system. LTB4 also has the ability to control microbial infection by improving host innate defenses through the release of antimicrobial peptides and modulation of intracellular Toll-like receptors (TLRs) expression in response to agonist challenge. In this report, we provide evidences that LTB4 acts on nucleotide-binging oligomerization domain 2 (NOD2) pathway to enhance immune response against influenza A infection. Infected mice receiving LTB4 show improved survival, lung architecture and reduced lung viral loads as compared to placebo-treated animals. NOD2 and its downstream adaptor protein IPS–1 have been found to be essential for LTB4-mediated effects against IAV infection, as absence of NOD2 or IPS–1 diminished its capacity to control viral infection. Treatment of IAV-infected mice with LTB4 induces an increased activation of IPS-1-IRF3 axis leading to an enhanced production of IFNβ in lungs of infected mice. LTB4 also has the ability to act on the RICK-NF-κB axis since administration of LTB4 to mice challenged with MDP markedly increases the secretion of IL–6 and TNFα in lungs of mice. TAK1 appears to be essential to the action of LTB4 on NOD2 pathway since pretreatment of MEFs with TAK1 inhibitor prior stimulation with IAV or MDP strongly abrogated the potentiating effects of LTB4 on both IFNβ and cytokine secretion. Together, our results demonstrate that LTB4, through its ability to activate TAK1, potentiates both IPS–1 and RICK axis of the NOD2 pathway to improve host innate responses.
A low power lookup technique for multi-hashing network applications

Many network security applications require large virus signature sets to be maintained, retrieved, and compared against the network streams. Software applications frequently fail to identify so many signatures through comparisons at very high network speeds. Bloom filters are one of the main multi-hashing schemes utilized in hardware to support this level of security. Nevertheless Bloom filters consume significant power to store, retrieve and lookup virus signatures owing to many hash function computations required to index to the memory. We present a novel lookup technique and architecture to decrease the power consumption of multi-hashing schemes, predominantly Bloom filters, in hardware. The theoretical analysis has shown that power gain achieved through new lookup technique can go up to 90%. Simulation results with three different classes of the hash functions embedded into the Bloom filter have indicated that power consumption of the Bloom filters can be considerably decreased by employing the low power lookup technique
From hyperlinks to Semantic Web properties using Open Knowledge Extraction

Open information extraction approaches are useful but insufficient alone for populating the Web with machine read- able information as their results are not directly linkable to, and immediately reusable from, other Linked Data sources. This work proposes a novel paradigm, named Open Knowledge Extraction, and its implementation (Legalo) that performs unsuper- vised, open domain, and abstractive knowledge extraction from text for producing machine readable information. The imple- mented method is based on the hypothesis that hyperlinks (either created by humans or knowledge extraction tools) provide a pragmatic trace of semantic relations between two entities, and that such semantic relations, their subjects and objects, can be revealed by processing their linguistic traces (i.e. the sentences that embed the hyperlinks) and formalised as Semantic Web triples and ontology axioms. Experimental evaluations conducted on validated text extracted from Wikipedia pages, with the help of crowdsourcing, confirm this hypothesis showing high performances. A demo is available at http://wit.istc. cnr.it/stlab-tools/ legalo.
Research on camera calibration in track and field competition video

Camera self-calibration in video is an important technique of 3D reconstruction in augmented reality of sporting events. According the features of sports, our system has realized 3D reconstruction in the video of track and field competition by applied binocular stereo vision knowledge to the camera self-calibration algorithm. In this paper, SIFT is used for corner detection, RANSAC is for the fundamental matrix. Regard two adjacent images as the same scene taken by binocular cameras, we can obtained camera's internal and external parameters according to the geometrical relationship between the two images in the same scene. Experiments show this calibration system can gain better effect in some scene.
A novel self-organizing quantum evolutionary algorithm for multi-objective optimization

In this study, a self-organizing quantum evolutionary algorithm for multi-objective optimization (MSQEA) is proposed. Because of the quantum dynamic mechanism all the subpopulations may move concurrently in a force-field until all of them reach their equilibrium states. We estimate the performance of algorithm. The efficiency of the approach has been illustrated by applying to 0/1 Multi-objective knapsack problems. The results show that MSQEA can yield improvement in solution quality.
Identity construction in coaching: Schemas, information processing, and goal commitment.

Leadership coaching is a nearly $2 billion per year industry (International Coach Federation, 2012), and although many different theories and approaches to coaching exist, relatively little is known about the differential effectiveness of various coaching approaches. Grounded in theories germane to but that transcend coaching (e.g., social identity, information processing), this study explores the ways in which several factors influence a very proximal outcome of coaching—commitment to set goals. It was hypothesized that coaches can intentionally help their coachees attain a more helpful coaching schema; additionally, it was hypothesized that this schema influences information processing during the session, which in turn affects goal commitment. A laboratory study was conducted in which trained research associates conducted a 1-session coaching session with undergraduate students focused on improving conflict management skills. Key findings highlight the importance of the coaching schema for directing information processing and eliciting higher levels of goal commitment in coaching.
Quasi-cyclic LDPC codes from difference families

We consider in this paper regular and nearly regular quasi-cyclic low-density paritycheck (LDPC) codes, derived from families of difference sets. The codes have girth at least 6, and sparse parity-check matrices. They are designed to perform well when iteratively decoded with the sum-product decoding algorithm and to allow low complexity encoding.