Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Smoke Simulation with Adaptive Octree Refinement

Three dimensional fluid simulation becomes expensive on high resolution grids which can easily consume a large amount of physical memory. This paper proposes an octree-based algorithm for visual simulation of smoke on ordinary workstations. This method adaptively subdivides the whole simulation volume into multiple subregions using an octree. Each leaf node in the octree also holds a uniform subgrid which is the basic unit for simulation. Because of the octree partition, the physical memory of the workstation only needs to be large enough to hold a small number of subgrids with the majority of the subgrids stored on hard disks. A previous smoke simulation algorithm based on a semi-Lagrangian scheme has been adapted to this hybrid octree-based data structure. A pair of PullUp and PushDown procedures are designed to solve the Poisson equation for pressure at each octree node. A novel node subdivision and merging scheme is also proposed to dynamically adjust the octree during each iteration of the simulation so that regions containing more details are more likely to be subdivided to achieve better accuracy. The result is an algorithm that can solve smoke simulation on large grids using a limited amount of memory.
Personality and Academic Achievement in Three Educational Levels

This study was undertaken to examine the relationship between “personality fitness” and academic achievement. 175 subjects from three educational levels, university, vocational technical institute, and high school, were administered the Eysenck Personality Questionnaire, the Raven's Advanced Progressive Matrices, and an Information Questionnaire. The personality dimension of introversion had the highest correlation with academic performance for the university sample, especially for the students in the “hard sciences. ” Raven's intelligence score was the best predictor for the? vocational technical institute sample. Personality dimensions of neuroticism and psychoticism, as well as average number of study hours, added differently to the multiple regression equations for the various samples.
Attachment and Adult Romantic Relationships: An Interview with M. Carole Pistole

Dr. M. Carole Pistole is an associate professor in the Department of Educational Studies at Purdue University. She is regarded as a leading researcher in adult attachment theory. In addition to chapters and editorials, she has published more than 25 refereed journal articles. Dr. Pistole’s adult attachment theory work incorporates two complementary bonding systems: attachment and caregiving. The knowledge gained from Dr. Pistole’s testing of theory has increased confidence in the basic tenets of attachment theory and contributed to understanding how people can better conduct or, when necessary, end their central emotional relationships. Her work includes theory development, particularly with regard to counseling practice. She has incorporated theoretical and measurement developments into her work, as reflected in using the four-category model of attachment and a multi-item attachment measure that permits more sophisticated statistical analyses. For more information on attachment and Dr. Pistole’s research efforts, readers are encouraged to visit her Web site at http://www.edst. purdue.edu/pistole/. The following interview was conducted in August 2003 via conference call.
Ad-hoc networked UAVs as Aerial Mesh Network for disaster management application and remote sensing: An approach

Now a days Unmanned Aerial Vehicles (UAVs) is being used for wide range of application. For example, UAVs are utilized to surveillance disaster affected and resource constrained network area and create the wide range of communication network. In this paper we proposed an Ad-hoc networked UAVs for Aerial Sensor Network for disaster management application and remote sensing. We used Wireless Mesh Network to connect multiple set of UAVs with each and other to increase the coverage of the observable area. We present an approach that works on the basis of process-patterns, each describing the context-dependent behavior of UAVs according to the execution order of services for different situations. Furthermore, the logical communication path is optimized within the mesh network based on each node's areal position using a dynamic hierarchical communication structure. As, this method we used wireless mash network for connecting one with another and do not required any existing network system, so it can be easily used over resource constrained networks, which are normally associated with any disaster or hazardous scenario. And we can also surveillance the complete area with bird eye view.
Hybrid Switched-Inductor Converters for High Step-Up Conversion

In applications where the high voltage gain is required, such as photovoltaic grid-connected system, fuel-cell and high-intensity discharge lamps for automobile, high step-up dc-dc converters have been introduced to boost the low voltage to a high bus voltage. The voltage gain of traditional boost converter is limited, considering the issues such as the system efficiency and current ripple. This paper proposes a class of hybrid switched-inductor converters (H-SLCs) for high step-up voltage gain conversion. First, the topological derivation of H-SLCs is deduced by combining the passive and active switched-inductor unit; second, this paper illustrates the operation modes of the proposed asymmetrical and symmetrical converters; third, the performance of the proposed converters is analyzed in detail and compared with existing converters; finally, a prototype is established in the laboratory, and the experimental results are given to verify the correctness of the analysis.
Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints

This paper considers the use of energy harvesters, instead of conventional time-invariant energy sources, in wireless cooperative communication. For the purpose of exposition, we study the classic three-node Gaussian relay channel with decode-and-forward (DF) relaying, in which the source and relay nodes transmit with power drawn from energy-harvesting (EH) sources. Assuming a deterministic EH model under which the energy arrival time and the harvested amount are known prior to transmission, the throughput maximization problem over a finite horizon of N transmission blocks is investigated. In particular, two types of data traffic with different delay constraints are considered: delay-constrained (DC) traffic (for which only one-block decoding delay is allowed at the destination) and no-delay-constrained (NDC) traffic (for which arbitrary decoding delay up to N blocks is allowed). For the DC case, we show that the joint source and relay power allocation over time is necessary to achieve the maximum throughput, and propose an efficient algorithm to compute the optimal power profiles. For the NDC case, although the throughput maximization problem is non-convex, we prove the optimality of a separation principle for the source and relay power allocation problems, based upon which a two-stage power allocation algorithm is developed to obtain the optimal source and relay power profiles separately. Furthermore, we compare the DC and NDC cases, and obtain the sufficient and necessary conditions under which the NDC case performs strictly better than the DC case. It is shown that NDC transmission is able to exploit a new form of diversity arising from the independent source and relay energy availability over time in cooperative communication, termed "energy diversity", even with time-invariant channels.
From ‘Psychology in Literature’ to ‘Psychology is Literature’

Three categories, varying from lowest to highest levels of abstraction, of possible relationships between psychology and literature are critically examined. The first category represents the lowest level of abstraction and involves ‘psychology in literature’: literature as a source of psychological data; literature as a source of insights for psychology. The second involves literature as an independent variable; literature as a dependent variable; literature as understood through psychology. The third, at the highest level of abstraction, involves psychology as nomothetic and literature as idiographic; psychology as culture-free and literature as culture-bound; psychology as concerned with actual worlds and literature with possible worlds; and, finally, ‘psychology is literature’. Each option is viable at a particular level of abstraction, although ‘psychology is literature’ is particularly provocative, and also nurturing of cultural research.
Refractoriness in Sustained Visuo-Manual Control: Is the Refractory Duration Intrinsic or Does It Depend on External System Properties?

Researchers have previously adopted the double stimulus paradigm to study refractoriness in human neuromotor control. Currently, refractoriness, such as the Psychological Refractory Period (PRP) has only been quantified in discrete movement conditions. Whether refractoriness and the associated serial ballistic hypothesis generalises to sustained control tasks has remained open for more than sixty years. Recently, a method of analysis has been presented that quantifies refractoriness in sustained control tasks and discriminates intermittent (serial ballistic) from continuous control. Following our recent demonstration that continuous control of an unstable second order system (i.e. balancing a ‘virtual’ inverted pendulum through a joystick interface) is unnecessary, we ask whether refractoriness of substantial duration (∼200 ms) is evident in sustained visual-manual control of external systems. We ask whether the refractory duration (i) is physiologically intrinsic, (ii) depends upon system properties like the order (0, 1st, and 2nd) or stability, (iii) depends upon target jump direction (reversal, same direction). Thirteen participants used discrete movements (zero order system) as well as more sustained control activity (1st and 2nd order systems) to track unpredictable step-sequence targets. Results show a substantial refractory duration that depends upon system order (250, 350 and 550 ms for 0, 1st and 2nd order respectively, n = 13, p<0.05), but not stability. In sustained control refractoriness was only found when the target reverses direction. In the presence of time varying actuators, systems and constraints, we propose that central refractoriness is an appropriate control mechanism for accommodating online optimization delays within the neural circuitry including the more variable processing times of higher order (complex) input-output relations.
First investigation of universal speech attributes for speaker verification

The universal speech attributes to speaker verification (SV) is addressed in this paper. The manner and place of articulation form the universal attribute unit inventory, and deep neural network (DNN) is used as acoustic model. Two methods to generate the attribute units are proposed in this paper: one is that the manner and place of articulation are directly combined to generate more robust universal speech attribute units, and the other is that the different context-dependent speech arttribute units are merged to a new speech attribute unit set by means of automatic clustering in accordance with likelihood calculation. Evaluated on the core test from the 2008 NIST speaker verification evaluation (SRE), the novel generated attribute units based system can achieve a better performance than that of the phoneme based system. Furthermore, the attribute based system has demonstrated a good complementarity with the GMM-UBM/i-vector and phoneme based DNN/i-vector systems.
A new and fast index for the quantification of short range self-similarity in RR time series

We propose a new and very fast index (the frequency of sign changes of the mirrored differences or fscmd) with good correlation with the short range scaling exponent (αl) estimated among scales 4 to 16 of the DFA. fscmd computes the relative number of sign changes of the difference of the RR time series minus their corresponding reversed RR time series after a moving average detrending procedure is applied using a window of 30 samples. Linear regression results with simulated time series with Fractional Brownian Noise and with actual time series using the Fantasia (FT), Normal Sinus Rhythm RR time series (NSR) and Congestive Heart Failure RR interval (CHF) databases after artifact correction show good agreement between fscmd and αl. Finally, Mann-Whitney Rank Sum tests applied to αl and fscmd when comparing NSR and CHF databases show very significant differences (p&#60;0.001) between groups for both indices.
ESProNa: Constraint-Based Declarative Business Process Modeling

In this paper we describe how declarative process modeling together with ontologies can be used to build complex clinical process models. Our approach supports the definition of functional, behavioral, organizational, data and operational process perspectives, resulting in an expressive and flexible modeling language. We use constraints for representing inter-process dependencies and constraint propagation for finding which processes are executable in user selected or given scenarios. Knowledge about the organizational perspective of a clinical ontology can be represented and imported from RDF files for interfacing with other applications. We implemented our approach in ESProNa, a Log talk application running on SWI-Prolog extended with the CLP(FD) constraint library and the N3 parser Henry.
DEVELOPMENT, SELECTION AND VALIDATION OF A SET OF COGNITIVE AND LINGUISTIC ATTRIBUTES FOR THE SAT I VERBAL: ANALOGY SECTION1

The purpose of this study is to use the rule space procedure to develop a general set of cognitive and linguistic attributes that account for performance on the Analogy Section of the SAT I Verbal. The overall research strategy was to develop a set of cognitive and linguistic attributes on one form of the Analogy Section, the experimental form, and then to examine the generalizability of these by applying the same set of attributes to a different form of the test, the generalizability form. Results produced a set 13 cognitive and linguistic attributes, with 6 interaction attributes, that were able to classify 97% of test-takers into their latent knowledge states on the experimental form; the same set of attributes were able to classify 90% of test takers into their latent knowledge states on the generalizability form. The analysis provides a strong indication of the important determinants of success on the SAT Analogy task, and provides evidence that these are relatively stable across forms.
Inhibitory activity on bacterial motility and in vivo protective activity of human monoclonal antibodies against flagella of Pseudomonas aeruginosa

Three stable hybridoma cell lines, IN-2A8, IN-5D6, and ZI-3A8, that secrete human monoclonal antibodies (MAbs) specific for b-type flagella of Pseudomonas aeruginosa were established by fusing peripheral blood lymphocytes from healthy volunteers with murine myeloma P3X63-Ag8.653 cells. The immunoglobulin M MAbs reacted specifically with flagellin (Mr, 52,000) by Western blotting (immunoblotting) analysis and bound specifically to clinical isolates belonging to Homma serotypes A, B, H, I, and M at frequencies of 58, 50, 46, 30, and 35%, respectively, but did not bind to any serotype E or G isolates. Overall, the MAbs bound to 31% of the clinical isolates. MAb IN-2A8 strongly protected burned mice challenged with P. aeruginosa bearing b-type flagella from death following parenteral administration of 0.1 microgram per mouse. This MAb also inhibited P. aeruginosa colony spreading in soft agar at a concentration of more than 1 microgram/ml but only slightly enhanced opsonophagocytosis by human polymorphonuclear leukocytes. A line of evidence suggests that the potent in vivo activity of MAb IN-2A8 in the burned-mouse model is likely to be caused by its inhibition of bacterial motility after binding to flagella.
Functional Links between the Fusion Peptide-proximal Polar Segment and Membrane-proximal Region of Human Immunodeficiency Virus gp41 in Distinct Phases of Membrane Fusion*

The binding of CD4 and chemokine receptors to the gp120 attachment glycoprotein of human immunodeficiency virus triggers refolding of the associated gp41 fusion glycoprotein into a trimer of hairpins with a 6-helix bundle (6HB) core. These events lead to membrane fusion and viral entry. Here, we examined the functions of the fusion peptide-proximal polar segment and membrane-proximal Trp-rich region (MPR), which are exterior to the 6HB. Alanine substitution of Trp666, Trp672, Phe673, and Ile675 in the MPR reduced entry by up to 120-fold without affecting gp120-gp41 association or cell-cell fusion. The L537A polar segment mutation led to the loss of gp120 from the gp120-gp41 complex, reduced entry by ∼10-fold, but did not affect cell-cell fusion. Simultaneous Ala substitution of Leu537 with Trp666, Trp672, Phe673, or Ile675 abolished entry with 50–80% reductions in cell-cell fusion. gp120-gp41 complexes of fusion-defective double mutants were resistant to soluble CD4-induced shedding of gp120, suggesting that their ability to undergo receptor-induced conformational changes was compromised. Consistent with this idea, a representative mutation, L537A/W666A, led to an ∼80% reduction in lipophilic fluorescent dye transfer between gp120-gp41-expressing cells and receptor-expressing targets, indicating a block prior to the lipid-mixing phase. The L537A/W666A double mutation increased the chymotrypsin sensitivity of the polar segment in a trimer of hairpins model, comprising the 6HB core, the polar segment, and MPR linked N-terminally to maltose-binding protein. The data indicate that the polar segment and MPR of gp41 act synergistically in forming a fusion-competent gp120-gp41 complex and in stabilizing the membrane-interactive end of the trimer of hairpins.
Robustness and Security Hardening of COTS Software Libraries

COTS components, like software libraries, can be used to reduce the development effort. Unfortunately, many COTS components have been developed without a focus on robust- ness and security. We propose a novel approach to harden software libraries to improve their robustness and security. Our approach is automated, general and extensible and consists of the following stages. First, we use a static analysis to prepare and guide the following fault injection. In the dynamic analysis stage, fault injection experiments execute the library functions with both usual and extreme input values. The experiments are used to derive and verify one protection hypothesis per function (for instance, function foo fails if argument 1 is a NULL pointer). In the hardening stage, a protection wrapper is generated from these hypothesis to reject unrobust input values of library functions. We evaluate our approach by hardening a library used by Apache (a web server).
Multiview Feature Analysis via Structured Sparsity and Shared Subspace Discovery

Since combining features from heterogeneous data sources can significantly boost classification performance in many applications, it has attracted much research attention over the past few years. Most of the existing multiview feature analysis approaches separately learn features in each view, ignoring knowledge shared by multiple views. Different views of features may have some intrinsic correlations that might be beneficial to feature learning. Therefore, it is assumed that multiviews share subspaces from which common knowledge can be discovered. In this letter, we propose a new multiview feature learning algorithm, aiming to exploit common features shared by different views. To achieve this goal, we propose a feature learning algorithm in a batch mode, by which the correlations among different views are taken into account. Multiple transformation matrices for different views are simultaneously learned in a joint framework. In this way, our algorithm can exploit potential correlations among views as supplementary information that further improves the performance result. Since the proposed objective function is nonsmooth and difficult to solve directly, we propose an iterative algorithm for effective optimization. Extensive experiments have been conducted on a number of real-world data sets. Experimental results demonstrate superior performance in terms of classification against all the compared approaches. Also, the convergence guarantee has been validated in the experiment.
Linking Research and Teaching to Benefit Student Learning

Linking research and teaching is a topic of international interest. The links may take many different forms and may be found in all types of higher education institution. The main aim of the paper is to explore the complexity and contested nature of the research-teaching nexus in different national and institutional contexts, with particular reference to geography. It is argued that the relationship depends on how the terms ‘research’ and ‘teaching and learning’ are conceptualized. It is suggested that undergraduate students are likely to gain most benefit from research in terms of depth of learning and understanding when they are involved actively, particularly through various forms of inquiry-based learning. The development of such research-based curricula provides challenges to staff across the sector, not least because they may lead to finding new ways for staff and students to work together.
Video gestures identification and recognition using Fourier descriptor and general fuzzy minmax neural network for subset of Indian sign language

Sign languages are natural languages that use to communicate with deaf and mute people. There exist different sign languages in the world. But we focused on Indian Sign Language which is on the way of standardization & very less work has been done on it so far. We have focused on Indian sign language history and progress in this domain and work carried out by various researchers in Indian Sign language recognition. Also we have proposed an approach that will convert the video of full sentence gesture of Indian sign language to text. It will initially identify individual words from the video & convert them on to text. Finally, the system will process those words to form a meaningful sentence in compliance with the simple grammar rules.
Self-rated attractiveness predicts preferences for opposite-sex faces, while self-rated sex-typicality predicts preferences for same-sex faces

Abstract Several studies have reported positive correlations between women's own attractiveness and their mate preferences. A recent study also reported a similar correlation between men's mate preferences and their own self-rated attractiveness. Surprisingly, however, relatively little is known about the relationship between measures of own condition and men's and women's attractiveness judgments of same-sex individuals. Here, we investigated how men's and women's self-rated attractiveness and selfrated sex-typicality predict their preferences for exaggerated sex-typical shape cues in both same-sex and opposite-sex faces. Our findings provide further support for models of condition-dependent mate preferences in both women and men; people who judged themselves as more attractive had stronger preferences for exaggerated sex-typical shape cues in opposite-sex faces. Additionally, we show a novel relationship between self-rated sex-typicality and perceptions of same-sex, but not opposite-sex, faces; people w.