Miracle-dz/UniFAR-FTUs huggingface dataset:
Crowd motion analysis for group detection

Understanding crowd dynamics is an interesting problem in computer vision owing to its various applications. We propose a dynamical system to model the dynamics of collective motion of the crowd. The model learns the spatio-temporal interaction pattern of the crowd from the track data captured over a time period. The model is trained under a least square formulation with spatial and temporal constraints. The spatial constraint allows the model to consider only the neighbors of a particular agent and the temporal constraint enforces temporal smoothness in the model. We also propose an effective group detection algorithm that utilizes the eigenvectors of the interaction matrix of the model. The group detection is cast as a spectral clustering problem. Extensive experimentation demonstrates a superlative performance of our group detection algorithm over state-of-the-art methods.
New Place and Route Algorithms for Wire Length Improvement With Concern to Critical Paths

3D Circuits are one of the most promising technologies for reducing wire lengths [1] and improving circuit power [2] and timing [3] for future high performance designs. On a 3D VLSI Circuit, tiers of active area are stacked, providing higher integration density, shrinking the distances between the cells and reducing wire lengths as a consequence. In order to take full benefit of the technology, new algorithms on the CAD field must be provided to handle 3D arrangement of circuit elements while considering new issues caused by the 3D integration. Today, the research in this field is still on the early years. Consider the 3D placement problem, for instance. The richness and variety of techniques that led to significant advances on 2D circuit placement over the decades will be able to deliver similar maturity to the 3D placement field. This thesis targets the wire length improvement of VLSI circuit considering critical elements of a circuit. It considers the problem from two different perspectives: placement and routing. On placement, it explores methods to perform placement of 3D circuits considering issues related to vertical interconnects (3D-Vias). A very significant volume of new methods and contributions are presented in the text and fully validated in a tool called Z-Place (section II). On routing, a new flexible algorithm called AMAZE is proposed (section III), combining existing and new methods that are very effective to produce short wire length and low delay to critical elements.
N-Acyl Homoserine Lactone-Mediated Quorum Sensing with Special Reference to Use of Quorum Quenching Bacteria in Membrane Biofouling Control

Membrane biofouling remains a severe problem to be addressed in wastewater treatment systems affecting reactor performance and economy. The finding that many wastewater bacteria rely on N-acyl homoserine lactone-mediated quorum sensing to synchronize their activities essential for biofilm formations; the quenching bacterial quorum sensing suggests a promising approach for control of membrane biofouling. A variety of quorum quenching compounds of both synthetic and natural origin have been identified and found effective in inhibition of membrane biofouling with much less environmental impact than traditional antimicrobials. Work over the past few years has demonstrated that enzymatic quorum quenching mechanisms are widely conserved in several prokaryotic organisms and can be utilized as a potent tool for inhibition of membrane biofouling. Such naturally occurring bacterial quorum quenching mechanisms also play important roles in microbe-microbe interactions and have been used to develop sustainable nonantibiotic antifouling strategies. Advances in membrane fabrication and bacteria entrapment techniques have allowed the implication of such quorum quenching bacteria for better design of membrane bioreactor with improved antibiofouling efficacies. In view of this, the present paper is designed to review and discuss the recent developments in control of membrane biofouling with special emphasis on quorum quenching bacteria that are applied in membrane bioreactors.
A Nucleotide Binding Motif in Hepatitis C Virus (HCV) NS4B Mediates HCV RNA Replication

ABSTRACT Hepatitis C virus (HCV) is a major cause of viral hepatitis. There is no effective therapy for most patients. We have identified a nucleotide binding motif (NBM) in one of the virus's nonstructural proteins, NS4B. This structural motif binds and hydrolyzes GTP and is conserved across HCV isolates. Genetically disrupting the NBM impairs GTP binding and hydrolysis and dramatically inhibits HCV RNA replication. These results have exciting implications for the HCV life cycle and novel antiviral strategies.
Neuronal Coding of pacemaker neurons - A random dynamical systems approach

The behaviour of neurons under the influence of periodic external input has been modelled very successfully by circle maps. The aim of this note is to extend certain aspects of this analysis to a much more general class of forcing processes. We apply results on the fibred rotation number of randomly forced circle maps to show the uniqueness of the asymptotic firing frequency of ergodically forced pacemaker neurons. The details of the analysis are carried out for the forced leaky integrate-and-fire model, but the results should also remain valid for a large class of further models.
Non-Instrumental Movement Inhibition (NIMI) Differentially Suppresses Head and Thigh Movements during Screenic Engagement: Dependence on Interaction

Background: Estimating engagement levels from postural micromovements has been summarized by some researchers as: increased proximity to the screen is a marker for engagement, while increased postural movement is a signal for disengagement or negative affect. However, these findings are inconclusive: the movement hypothesis challenges other findings of dyadic interaction in humans, and experiments on the positional hypothesis diverge from it. Hypotheses: (1) Under controlled conditions, adding a relevant visual stimulus to an auditory stimulus will preferentially result in Non-Instrumental Movement Inhibition (NIMI) of the head. (2) When instrumental movements are eliminated and computer-interaction rate is held constant, for two identically-structured stimuli, cognitive engagement (i.e., interest) will result in measurable NIMI of the body generally. Methods: Twenty-seven healthy participants were seated in front of a computer monitor and speakers. Discrete 3-min stimuli were presented with interactions mediated via a handheld trackball without any keyboard, to minimize instrumental movements of the participant's body. Music videos and audio-only music were used to test hypothesis (1). Time-sensitive, highly interactive stimuli were used to test hypothesis (2). Subjective responses were assessed via visual analog scales. The computer users' movements were quantified using video motion tracking from the lateral aspect. Repeated measures ANOVAs with Tukey post hoc comparisons were performed. Results: For two equivalently-engaging music videos, eliminating the visual content elicited significantly increased non-instrumental movements of the head (while also decreasing subjective engagement); a highly engaging user-selected piece of favorite music led to further increased non-instrumental movement. For two comparable reading tasks, the more engaging reading significantly inhibited (42%) movement of the head and thigh; however, when a highly engaging video game was compared to the boring reading, even though the reading task and the game had similar levels of interaction (trackball clicks), only thigh movement was significantly inhibited, not head movement. Conclusions: NIMI can be elicited by adding a relevant visual accompaniment to an audio-only stimulus or by making a stimulus cognitively engaging. However, these results presume that all other factors are held constant, because total movement rates can be affected by cognitive engagement, instrumental movements, visual requirements, and the time-sensitivity of the stimulus.
Climate Change and Marx in the 21st Century, Part I

ABSTRACT This paper comes in two parts. Part I begins with an examination of the relationship between Marx’s characterization of the centrality of commodity production to capitalism as a system, its destructive results on Nature, and the global scale of the climate crisis confronting the 21st century. It then moves on to critically examine three models of political economy (Hayekism, Keynesianism and State Socialism). Part II takes the argument forward by critically examining a fourth model, Green Keynesianism, currently being manufactured in response to the crisis of climate change, in order to show the inability of all four models to resolve the existential threat posed to humanity in the 21st century and beyond. We then proceed to posit, as a thought experiment, a fifth model of political economy, Green Socialism, as something now needed in the 21st century and discuss the important building blocks of the future evolution of a coherent system. The paper concludes with a brief mention of both the ends and means that need deliberation if Green Socialism is to be realized.
Body sets and lines: A reliable representation of images

This paper proposes a novel definition of color lines and sets, based on the dichromatic model for lambertian objects. The ends of the body vectors are robustly detected, from the clearest to the darkest through to a multi-level 2D histogram analysis. Finally, instead of classically defining the topographic map along one sole luminance direction, our body lines are designed along each body vector. Compared to existing topographic maps, our method is more compact while better preserving the color quality. Furthermore, it is faster to compute than.
A Survey of Security and Privacy Research in Online Social Networks

This survey highlights the major issues concerning privacy and security in online social networks (OSNs). Firstly, we discuss research that aims to protect user data from the various attack vantage points including other users, advertisers, third party application developers, and the online social network provider itself. Next we cover social network inference of user attributes, locating hubs, and link prediction. Because online social networks are so saturated with sensitive information, network inference plays a major privacy role. As a response to the issues brought forth by client-server architectures, distributed social networks are discussed. We then cover the challenges that providers face in maintaining the proper operation of an online social network including minimizing spam messages, and reducing the number of sybil accounts. Finally, we present research in anonymizing social network data. This area is of particular interest in order to continue research in this field both in academia and in industry.
Construction of a method for predicting the number of enterobacteria in milk using artifical neural networks

It is now established that artificial neural networks (ANNs) provide better simulation and prediction of the number of microorganisms in raw materials and foodstuffs. In this case, ANNs could be used as informative, fast, and cost-effective means. According to the European requirements to food products, basic microbiological indicators are the total number of microorganisms and bacteria from the Enterobacteriaceae family, since they are most commonly associated with food-borne diseases and poisonings. The aim of this work was to devise a method for predicting the number of bacteria from the Enterobacteriaceae family in raw milk at its chilled storage and to estimate the predictive capability of ANN. Construction of the method included 4 stages. At the first stage, we examined the number of enterobacteria depending on the physical-chemical composition of raw milk, temperature and duration of storage in a refrigerator. At the second stage, we compiled a base of experimental data obtained from research models. At the next stage, we introduced the received database to ANN. And at the last stage we assessed effectiveness of the predicting technique. The constructed ANN consists of three layers: an input layer (5 parameters: milk storage temperature (4, 6, 8, and 10 °C), duration of milk storage (from 1 to 48 hours); the acidity of milk (17‒20 %), the fat content (3.2; 3.6; 4.0; 4.5 %) and protein content (2.9; 3.0; 3.3 %) in milk; hidden layers (with 30 neurons) and the output layer (the projected number of bacteria). In order to train and optimize the ANN, we used 1,200 experimental data, which revealed that the prediction had the highest rate of deviation of 2.497 % (or 370 bacterial cells per 1 ml). Thus, the devised predicting method could be used to predict the number of bacteria taking into consideration the complex of environmental variables in different food products. In addition, a given approach could be employed as artificial intelligence when assessing microbiological risks and for quick monitoring of food safety.
Uncertain attribute graph model of web social network and its application

Integrating characteristics' of uncertain graph and attribute graph, this paper presents" the uncertain attribute graph " concept on the basis of practical problem that relationship between individual and individual exists uncertainty and Individual and its relationship with attribute uncertainty in social network. And it descript its attribute. It respectively gives these concepts, edges uncertain attribute graph, vertices uncertain attribute graph, edges and vertices are uncertain attributes graph. It proves their property and their relationship with attribute graph, uncertain graph. It given uncertain attribute graph comprehensive model basis of considering the vertices and edges attributes may also exist uncertainty and it proves uncertain graph. Attribute graph are exceptions of uncertain attribute graph and uncertain attribute graph is their development research. At last the paper gives uncertain attribute sub-graph and its mining method. Analysis shows that, uncertain attribute graph can reflect the real structure of the Web social networking.
NavigaTor: Finding Faster Paths to Anonymity

The Tor network is currently by far the most popular system for providing anonymity on the Internet. Even though both latency and throughput have been significantly improved in recent years, Tor users still experience variable delays on connecting to servers. Such delays have been shown to be especially harmful for browsing the web and prevent altogether the use of protocols where a certain quality of service is indispensable. In this paper we propose and evaluate methods to measure and improve performance in the Tor network. To estimate the quality of circuits for future traffic, we use active Round-Trip-Time (RTT) measurements and a-priori information of the distribution of RTT values. In this way, slow circuits can be discarded before having negative impact on user experience. Using NavigaTor, our high performance measurement software which includes a custom Tor path generator, we are the first to conduct large-scale performance measurements on the live Tor network, building millions of circuits within days, without stressing the anonymity network. As part of our study, we conduct several experiments from PlanetLab on the live Tor network to analyze the trade-off between the quality of protection and the quality of service. We compare our Circuit-RTT method to the current state-of-the-art method Circuit Build Time (CBT) and the more recently proposed congestion-aware scheme, finding that the congestion-aware scheme in its original design achieves only minor improvements on the current Tor network and that Circuit-RTT improves latency and throughput more effectively than CBT.
Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia.

IMPORTANCE To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race. OBJECTIVE To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia. DESIGN, SETTING, AND PATIENTS We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge. MAIN OUTCOME MEASURES We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing. RESULTS From 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race. CONCLUSION AND RELEVANCE Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.
EXACT SOLUTIONS AND THE ATTRACTOR MECHANISM IN NON-BPS BLACK HOLES

We analyze the attractor mechanism for the D0-D4 black hole solution in the four-dimensional supergravity. Our analyses are based on new exact solutions, which show explicitly the attractor mechanism for the extremal non-BPS black holes. Our solutions take into account the moduli as general complex fields, while in almost all the non-BPS solutions obtained by previous authors, the moduli fields are restricted to be purely imaginary.
Aims of the Thesis Summary of the Findings

The aim of the present thesis was to investigate the importance of connectivity during sleep and its role in cognitive functioning during wakefulness. Sleep is a complex phenomenon, which arises from the interaction of multiple regions. A central tenet of this thesis was that, to understand sleep and its functions, it is not sufficient to assess the activity within one circumscribed neuronal population, but it is necessary to look at the interplay over numerous spatial and temporal scales. Connectivity occurs at multiple levels of descriptions, such as structural connectiv-ity, which describes the anatomical pathways between brain regions, functional connectivity, which quantifies the correlation in activity between distant neu-ronal populations, and effective connec-tivity, which indicates the directed influence of one region onto another. These multiple levels of description of the degree of connectivity, over different spatial and temporal scales, are interwo-ven with the research questions described in each chapter. How does structural con-nectivity, measured with diffusion tensor imaging (DTI), affect the expression profile and synchronization properties of slow waves and spindles? Does the propagation of slow waves depend on the coordination of central neuronal populations with widespread afferents over multiple regions of the cortex? How do the slow fluctuations, such as slow waves, often thought to be a marker of global activity, favor the emergence of synchronization at the local level, tagged by gamma activity in the electroencephalography (EEG)? Does learning a task that requires the coordinated contribution of multiple areas increase functional connectivity between those regions, not only during its performance, but during subsequent sleep as well? How does sleep deprivation affect the transmission of information over distant brain regions, measured by effective connectivity, and do changes in this transmission affect cognitive perfor-mance? What are the brain mechanisms involved in the perseverance and impaired cognitive switching that are often seen after sleep deprivation and suggest an impairment in fast and flexible reconfigura-tions of the neuronal network activity? Main Findings The patterns of structural and functional connectivity between brain regions determine the expression of characteristic features of the sleep EEG, in particular slow waves and spindles. The white-matter tracts that connect distant brain regions affect the expression profile of these features, as shown in Chapter 2. At the functional level, sleep arises from a delicate integration of global and local processing at widely different temporal and spatial scales. Slow waves combine aspects of global processing, shown in Chapter 3 to be …
Design And Fabrication Of Thin-Film Optical Filters For Mid-Infrared Spectroscopy Application

This paper reports the design, fabrication, and results of thin film Fabry-Perot interferometer (FPI) for mid-infrared spectroscopy application. The system is designed to be integrated in a small portable spectrometer for the measurement of molecular absorption or emission as well as substance that has an infrared signature. The filter is based on Fabry-Perot interferometer and the wavelength of interest is in the mid-infrared (5 to 15 micrometers). The layers were selected carefully to minimize the thickness required to meet the quarter-wave optical-thickness criteria for the interferometer.
Schulze et al . — Nitrogen Fixation by White Lupin 733

JOACHIM SCHULZE*, GLENA TEMPLE, STEPHEN J. TEMPLE, HEIDRUN BESCHOW and CARROLL P. VANCE Department of Crop Science, Plant Nutrition, Georg-August-University Göttingen, Carl-Sprengel-Weg 1, D-37075 Göttingen, Germany, Department of Soil, Water and Climate, University of Minnesota, 1991 Upper Buford Circle, St Paul, MN 55108-6026, USA, Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, St Paul, MN 55108-6026, USA, Viterbo University, Biology Department, 815 Ninth Street South, LaCrosse, WI 54601, USA, Forage Genetics International, N5292 South Gills Coulee Road, West Salem, WI 54669, USA, Institute of Soil Science and Plant Nutrition, Martin-Luther-University Halle-Wittenberg, Adam-Kuckhoff-Str. 17b, 06108 Halle/Saale, Germany and United States Department of Agriculture, Agricultural Research Service, Plant Science Research Unit, St Paul, MN 55108-6026, USA