Miracle-dz/UniFAR-FTUs huggingface dataset:
The Change of junior middle school students' Life Satisfaction and the Prospective Effect of Resilience: A two year Longitudinal Study

Longitudinal data(N=249) on grade one junior middle school students' life satisfaction and resilience were collected at 4 time points in two years by using the Students' Life Satisfaction Scale(SLSS)and the Resilience Scale for Chinese Adolescents.The present study employed Hierarchical Linear Model to analyze the changing trends of junior middle school students' life satisfaction and explore the longitudinal effects of gender,school regional difference and resilience on life satisfaction.Results show that 1) Junior middle school students' life satisfaction had dropped significantly from the Second Semester of grade 1 to the Second Semester of grade 3;2) The influences of gender,school regional difference on junior middle school students' life satisfaction change were not significant;3) The affect control and family support of resilience had a significantly positive effect on junior middle school students' life satisfaction change,but goal planning,positive thinking and help-seeking of resilience had no significant effect.4) The individual power of resilience showed a larger direct effect and little moderating effect on junior middle school students' life satisfaction change,and the supportive power of resilience showed a larger moderating effect.
A scalable distributed algorithm for shape transformation in multi-robot systems

Distributed reconfiguration is an important problem in multi-robot systems such as mobile sensor nets and metamorphic robot systems. In this work, we present a scalable distributed reconfiguration algorithm, hierarchical median decomposition, to achieve arbitrary target configurations. Our algorithm is built on top of a novel distributed median consensus estimator. The algorithms presented are fully distributed and do not require global communication. We show results from simulations in an open source multi-robot simulator.
A robust understanding model for spoken dialogues

This paper presents a robust model for language understanding in spoken dialogue systems, in which the understanding problem is formulated as a three-stage process. In the first stage, semantic concepts included in the utterance are identified through a bottom-up chart parser to build a concept graph. Then, in the second stage, communicative goal of each candidate path searched from the concept graph is determined by a classifier based on latent semantic analysis. Finally, information of discourse history is introduced to guide the search in all hypotheses for the best result. Experiments with a test set composed of spontaneous utterances show that this model outperforms a rule-based model by 8.1% and 21.5% in goal and concept understanding respectively, which proves its advantage to robust spontaneous language understanding.
Task mapping and communication routing model for minimizing power consumption in multi-cores

In this paper we introduce a novel MILP formulation for the problem of mapping tasks and routing communications on multi-core systems with power minimization objective. The cores have several power consumption modes. Dynamic and static power consumptions are modeled independently and the dynamic power consumption depends on core load rate. Three types of communication routing are examined: single-path, multi-path and fractional multi-path. Initially a mathematical model is introduced and afterwards a linearized mixed-integer program formulation is proposed. We conclude the paper by presenting computational results on task graph instances obtained from StreamIt applications.
Compression of fully-connected layer in neural network by Kronecker product

In this paper we propose and study a technique to reduce the number of parameters in fully-connected layers of neural networks using Kronecker product, at a mild cost of the prediction quality. The technique proceeds by replacing fully-connected layers with so-called Kronecker fully-connected layers, where the weight matrices of the fully-connected layers are approximated by linear combinations of multiple Kronecker products of smaller matrices. Just as the Kronecker product is a generalization of the outer product from vectors to matrices, our method is a generalization of the low rank approximation method for fully-connected layers. We also use combinations of different shapes of Kronecker product to increase modelling capacity. Experiments on SVHN, scene text recognition and ImageNet dataset demonstrate that we can achieve 10x reduction of number of parameters with less than 1% drop in accuracy, showing the effectiveness and efficiency of our method.
Configuring Random Graph Models with Fixed Degree Sequences

Random graph null models have found widespread application in diverse research communities analyzing network datasets, including social, information, and economic networks, as well as food webs, protein-protein interactions, and neuronal networks. The most popular family of random graph null models, called configuration models, are defined as uniform distributions over a space of graphs with a fixed degree sequence. Commonly, properties of an empirical network are compared to properties of an ensemble of graphs from a configuration model in order to quantify whether empirical network properties are meaningful or whether they are instead a common consequence of the particular degree sequence. In this work we study the subtle but important decisions underlying the specification of a configuration model, and investigate the role these choices play in graph sampling procedures and a suite of applications. We place particular emphasis on the importance of specifying the appropriate graph labeling (stub-labeled or vertex-labeled) under which to consider a null model, a choice that closely connects the study of random graphs to the study of random contingency tables. We show that the choice of graph labeling is inconsequential for studies of simple graphs, but can have a significant impact on analyses of multigraphs or graphs with self-loops. The importance of these choices is demonstrated through a series of three vignettes, analyzing network datasets under many different configuration models and observing substantial differences in study conclusions under different models. We argue that in each case, only one of the possible configuration models is appropriate. While our work focuses on undirected static networks, it aims to guide the study of directed networks, dynamic networks, and all other network contexts that are suitably studied through the lens of random graph null models.
The Grid Portal Development Kit

Computational science portals are emerging as useful and necessary interfaces for performing operations on the Grid. The Grid Portal Development Kit (GPDK) facilitates the development of Grid portals and provides several key reusable components for accessing various Grid services. A Grid portal provides a customizable interface allowing scientists to perform a variety of Grid operations including remote program submission, file staging, and querying of information services from a single, secure gateway.
A BnB Mobile Game Online Based on J2ME and J2EE

Through the example of Bubble and Bubble (BnB) mobile game, the whole development process of mobile game based on J2ME and J2EE is showed. First, Game API in the Mobile Information Device Profile-MIDP-2.0 is used to build the game engine. Through the optimization and compatibility design of process, middleware framework is selected. Second, the game classes and components design is introduced in detail. Third, the server performance for detonation on the client, the communications time between the clients with the server and the procedure performance of the server have been tested. Various techniques, such as object pool, multi-threaded, socket connection, sprite, Maps etc., are applied in BnB's development. Experiment demonstrates its performance and proves this case is meaningful and useful for other online mobile game development. Some propositions for further research is also suggested.
Structural information based malicious app similarity calculation and clustering

Depending on expansion of supply of smartphone, development of mobile application is more active using various mobile platform. As a result of malicious applications, but also targeting the mobile it is rapidly increasing. In this paper, method of Android malware similarity and clustering. First, there is a need for a process for extracting the control flow graph in an Android application. By extract the control flow graph, we form structural information of methods in Android application called '4-tuple'. After we create the structural information extracted from the control flow graph it is necessary to compare the matching process. Matching process we propose has two steps, 'initial matching' and 'second matching'. Initial matching step is the process of matching the '4-tuple' information but not exactly same with each other only a single in Android application. Second matching step is process of matching in the same way as the initial matching target method that calling its method and method that is invoked. Finally, it measure the ratio of the total number of method in Android application and matched method after initial matching and second matching. Finally, it measure the ratio of the total number of method in Android application and matched method after initial matching and second matching. We proceeds clustering using the above process. Based on previous studies, we used the DBSCAN algorithm for clustering. It was 65.8% average using the structural information of the result of the clustering.
A Metalloproteinase Secreted by Streptococcus pneumoniae Removes Membrane Mucin MUC16 from the Epithelial Glycocalyx Barrier

The majority of bacterial infections occur across wet-surfaced mucosal epithelia, including those that cover the eye, respiratory tract, gastrointestinal tract and genitourinary tract. The apical surface of all these mucosal epithelia is covered by a heavily glycosylated glycocalyx, a major component of which are membrane-associated mucins (MAMs). MAMs form a barrier that serves as one of the first lines of defense against invading bacteria. While opportunistic bacteria rely on pre-existing defects or wounds to gain entry to epithelia, non opportunistic bacteria, especially the epidemic disease-causing ones, gain access to epithelial cells without evidence of predisposing injury. The molecular mechanisms employed by these non opportunistic pathogens to breach the MAM barrier remain unknown. To test the hypothesis that disease-causing non opportunistic bacteria gain access to the epithelium by removal of MAMs, corneal, conjunctival, and tracheobronchial epithelial cells, cultured to differentiate to express the MAMs, MUCs 1, 4, and 16, were exposed to a non encapsulated, non typeable strain of Streptococcus pneumoniae (SP168), which causes epidemic conjunctivitis. The ability of strain SP168 to induce MAM ectodomain release from epithelia was compared to that of other strains of S. pneumoniae, as well as the opportunistic pathogen Staphylococcus aureus. The experiments reported herein demonstrate that the epidemic disease-causing S. pneumoniae species secretes a metalloproteinase, ZmpC, which selectively induces ectodomain shedding of the MAM MUC16. Furthermore, ZmpC-induced removal of MUC16 from the epithelium leads to loss of the glycocalyx barrier function and enhanced internalization of the bacterium. These data suggest that removal of MAMs by bacterial enzymes may be an important virulence mechanism employed by disease-causing non opportunistic bacteria to gain access to epithelial cells to cause infection.
Characteristic X-Ray Variability of TeV Blazars: Probing the Link between the Jet and the Central Engine

We have studied the rapid X-ray variability of three extragalactic TeV γ-ray sources: Mrk 421, Mrk 501, and PKS 2155-304. Analyzing the X-ray light curves obtained from ASCA and/or Rossi X-Ray Timing Explorer observations between 1993 and 1998, we have investigated the variability in the time domain from 103 to 108 s. For all three sources, both the power spectrum density (PSD) and the structure function (SF) show a rollover with a timescale of the order of 1 day or longer, which may be interpreted as the typical timescale of successive flare events. Although the exact shape of turnover is not well constrained and the low-frequency (long timescale) behavior is still unclear, the high-frequency (short timescale) behavior is clearly resolved. We found that, on timescales shorter than 1 day, there is only small power in the variability, as indicated by a steep power spectrum density of f-2~-3. This is very different from other types of mass-accreting black hole systems, for which the short-timescale variability is well characterized by a fractal, flickering-noise PSD (f-1~-2). The steep PSD index and the characteristic timescale of flares imply that the X-ray-emitting site in the jet is of limited spatial extent: D ≥ 1017 cm distant from the base of the jet, which corresponds to ≥102 Schwarzschild radii for 107-10 M☉ black hole systems.
Towards Practical Query Answering for Horn-SHIQ

Query answering has become a prominent reasoning task in Description Logics. This is witnessed not only by the high number of publications on the topic in the last decade, but also by the increasing number of query answering engines. A number of systems provide full conjunctive query (CQ) answering capabilities, including [1, 23, 25, 4, 11]. A common feature of these approaches is that they rely on existing technologies for relational or deductive databases. They focus on lightweight DLs like DL-Lite and EL, and they use query rewriting to reduce the problem of answering a query over a DL ontology to a database query evaluation problem. For more expressive DLs that are not tractable in combined complexity, however, CQs (with the complete first-order semantics) are not yet supported by current reasoning engines. A range of algorithms has been designed, but they serve for theoretical purposes such as showing complexity bounds and are not amenable to practical implementation. The only exception is the rewriting algorithm implemented in the REQUIEM system, which covers ELHI [23], an expressive extension of EL for which standard reasoning is EXPTIME-hard. In this paper, we contribute to the development of practical query answering systems beyond DL-Lite and EL. We consider Horn-SHIQ, the Horn fragment of the popular DL SHIQ that underlies OWL DL. It combines all the expressive features of DL-Lite and EL, and simultaneously extends them with transitive roles, qualified number restrictions and some universal quantification. Standard reasoning tasks in Horn-SHIQ are already EXPTIME-hard in combined complexity but, due to the absence of disjunction, they are polynomial in data complexity. Since in Horn-SHIQ models are significantly more complex than in DL-Lite and (most dialects of) EL, extending existing query rewriting techniques is not straightforward. The main contribution of this paper is a query answering method for Horn-SHIQ that appears to be promising for practicable systems, as confirmed by the experimental evaluation of a prototype implementation. – The core of the method is a novel query rewriting technique which transforms an input query q into a union Q of CQs (a UCQ) such that the answers of q over an ontology O = 〈T ,A〉 with TBox T and ABox A coincide with the answers over A
A Comparative Approach to Hand Force Estimation using Artificial Neural Networks

In many applications that include direct human involvement such as control of prosthetic arms, athletic training, and studying muscle physiology, hand force is needed for control, modeling and monitoring purposes. The use of inexpensive and easily portable active electromyography (EMG) electrodes and position sensors would be advantageous in these applications compared to the use of force sensors which are often very expensive and require bulky frames. Among non-model-based estimation methods, Multilayer Perceptron Artificial Neural Networks (MLPANN) has widely been used to estimate muscle force or joint torque from different anatomical features in humans or animals. This paper investigates the use of Radial Basis Function (RBF) ANN and MLPANN for force estimation and experimentally compares the performance of the two methodologies for the same human anatomy, ie, hand force estimation, under an ensemble of operational conditions. In this unified study, the EMG signal readings from upper-arm muscles involved in elbow joint movement and elbow angular position and velocity are utilized as inputs to the ANNs. In addition, the use of the elbow angular acceleration signal as an input for the ANNs is also investigated.
Insect Control Using Chitinolytic Soil Actinomycetes as Biocontrol Agents

Several actinomycetes species were isolated from United Arab Emirates soil using conventional microbiological techniques. Out of thirty-eight isolates, only three were selected according to their high production of the chitinase enzyme. The three isolates were identified to the species level using cultural, physiological, biochemical and chemotaxonomical characteristic. Isolates 1, 7 and 40 were identified as Actinoplanes philippinensis, Actinoplanes missouriensis and Streptomyces clavuligerus, respectively. Chitinolytic activities of the three isolates were tested against Drosophila melanogaster development as percentage of successful pupal formation. The three actinomycetes were individually applied against D. melanogaster, and then in combinations of two and all three actinomycetes isolates were used to study synergistic and antagonistic effects between them. The application of either A. philippinensis or A. missouriensis gave a good effect, shown as lowest pupal formation percentages, being 39.43 and 31.75%, respectively. At the same time, S. clavuligerus gave the least effect, being 55.71% compared to control treatment. In the combination of two isolates experiment, S. clavuligerus, which gave the least activity when applied individually, was synergized by the presence of A. philippinensis (27.35%) and A. missouriensis (33.24%). Meanwhile, the combination of A. philippinensis and A. missouriensis, gave an indication of antagonism (51.06%) shown as high percentage of successful pupal formation. The combination of all of three isolates experiment showed no antagonism (37.47 ± 2.48%).
Carbon dioxide variability and air‐sea fluxes in the northern Adriatic Sea

[1] High-frequency measurements of surface water partial pressure of CO2 (pCO2) in the Gulf of Trieste in the north Adriatic Sea, the most northern part of the Mediterranean, are presented. Sea surface pCO2 was measured at the coastal oceanographic buoy Vida (45° 32′ 55.68′′ N, 13° 33′ 1.89′′ E), using the Submersible Autonomous Moored Instrument for CO2 during four deployments from 2007 to 2008. The pCO2 measurements were combined with physical observations at Vida, Sea-viewing Wide Field-of-view Sensor chlorophyll-a, and daily river discharge to elucidate the biological and physical processes that control pCO2 on seasonal to interannual time scales. Sea surface pCO2 ranged from 260 to 340 μatm in spring 2007, 220 to 380 μatm in late summer/fall 2007, 200 to 500 μatm in spring/summer 2008, and 240 to 370 μatm in fall 2008. Mean CO2 fluxes (±standard deviation) from the atmosphere into the ocean during these seasons were −5.0 (±6.2), −12.1 (±14.2), −0.9 (±9.7), and −6.4 (±7.0) mmol m−2 d−1 resulting in a net sink of atmospheric CO2 of −2–3 mol m−2 yr−1. The seasonal and interannual variability in this semienclosed sea is dominated by heating and cooling based on strong correlations with sea surface temperature. These correlations break down during convective mixing in the fall, bora wind events, and brief periods of freshwater input.
Posterior Probability Object Tracking Method Using Momentum Based Level Set

This paper proposes a novel object tracking method that is robust to a cluttered background and a large motion. First, a posterior probability measure (PPM) is adopted to locate the object region. Then the momentum based level set is used to evolve the object contour in order to improve the tracking precision. To achieve rough object localization, the initial target position is predicted and evaluated by the Kalman filter and the PPM, respectively. In the contour evolution stage, the active contour is evolved on the basis of an object feature image. This method can acquire more accurate target template as well as target center. The comparison between our method and the kernel-based method demonstrates that our method can effectively cope with the deformation of object contour and the influence of the complex background when similar colors exist nearby. Experimental results show that our method has higher tracking precision.
Understanding and Promoting Self-Direction in Freshman and Master’s Students: A Qualitative Approach

This study investigates how the transition toward self-direction is experienced and facilitated in 2 semester-long courses in teacher education degree programs and the differences in such a transition for freshman and master’s students. The thematic analysis of the written self-assessments of 8 illustrative examples enabled the detection of (a) students’ initial upset in the face of demands for internal authority; (b) the support of the teacher and peers in managing that upset; and (c) the students’ shift toward more complex conceptions of learning and teaching, including evidence of increasing self-direction. These findings shed light on the potential of intentionally designed learning contexts for promoting students’ epistemological development. The similarities found between freshman and master’s students’ experiences when managing the demands of internal authority emphasize the underutilization of the most extended teaching practices in higher education.
RPI-BLENDER TAC-KBP2013 Knowledge Base Population System

This year the RPI-BLENDER team participated in the following four tasks: English Entity Linking, Regular Slot Filling, Temporal Slot Filling and Slot Filling Validation. The major improvement was made for Regular Slot Filling and Slot Filling validation. We developed a fresh system for both tasks. Our approach embraces detailed linguistic analysis and knowledge discovery, and advanced knowledge graph construction and truth-finding algorithms.
Finite State Machines With Input Multiplexing: A Performance Study

Finite state machines with input multiplexing (FSMIMs) have been proposed in previous works as a technique for efficient mapping FSMs into ROM memory. In this paper, we propose a new architecture for implementing FSMIMs, called FSMIM with state-based input selection, whose goal is to achieve a further reduction in memory usage. This paper also describes in detail the algorithms for generating FSMIMs used by the tool FSMIM-Gen, which has been developed and made available on the Internet for free public use. A comparative study in terms of speed and area between FSMIM approaches and other field programmable gate array-based techniques is presented. The results show that the FSMIM approaches obtain huge reductions in the look-up table (LUT) usage by using a small number of embedded memory blocks. In addition, speed improvements over conventional LUT-based implementations have been obtained in many cases.