Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Coverage in a K-Covered and Connected Sensor Network Using Genetic Algorithms

Sensing coverage of a sensor network characterizes how well an area is monitored or tracked by sensors. Connectivity is an important requirement that shows how nodes in a sensor network can effectively communicate. Some hotspot areas in the network are more important than other areas and need to be covered by more sensors. We are interested in an initial deployment strategy that maximizes the coverage area of wireless sensor network while preserving connectivity between nodes provided that all given hotspot regions are covered by at least k sensors. We propose a genetic algorithm based solution to find an optimal sensor node distribution. Experimental results are presented to evaluate our algorithm.
Who Wins the Peace? Elites, Citizens, and the Decision for War

We build a model of bargaining and war over public and private goods to explore how domestic institutions and international issues interact to influence the probability of war and the distribution of benefits in peace. We show that half-measures toward democracy such as expanding the size of the elite or taxing the elite as a form of executive control can increase the potential for conflict, while full liberalization reduces the potential for conflict. When international bargains are peaceful, relative democracies deliver more public goods to citizens while the private goods obtained by non-democracies may contribute to greater levels of
Effective Spoken Natural Language Dialog Requires Variable Initiative Behavior: An Empirical Study

The usefulness of spoken natural language dialog for human-computer interaction is unquestioned. A spoken natural language interface provides a flexible means of communication while enabling human users to keep their hands and eyes busy on the task at hand. In this paper we claim that spoken natural language dialog is even more useful if the participating system permits variable initiative behavior. This is behavior where the task initiative can vary from strongly computer controlled to strongly user controlled or somewhere in between. Such behavior allows a system to effectively communicate with both task novices and experts as well as users with intermediate levels of expertise. In support of this claim, we present experimental results from a study of an implemented system that can operate at differing levels of initiative while engaging in spoken natural language dialog with users in order to provide assistance in repairing an electronic circuit. The results are based on eight users who participated in a total of 141 dialogs speaking 2840 utterances.
A Comparison of a Computer-Based and a Lecture-Based Computer Literacy Course: A Turkish Case

Computer-based instructional applications are considered an effective alternative to traditional teaching methods and today in numerous educational and training settings, interactive computer programs are used to teach young students and adults computer literacy skills. The purpose of this study is to compare the attitudes and motivations of students who attended a computer-based in-class computer literacy course with the attitudes and motivations of those who participated in a classical lecture-based computer literacy course. The results show that there is no significant difference between computer-based instruction group students’ and lecture-based instruction group students’ total attitudes scores. However, a significant instructional mode effect on students’ motivation was detected.
A high-precision forum crawler based on vertical crawling

In this paper, we present a special crawler for Internet forums. Different from General Crawler and Focused Crawler, it can get structured information directly get the most valuable web resources by utilizing the least system resources, filter the useless information to the maximum extent and finally supply users with high-precision information. This crawler adopts template-based processing method which is to use regular expressions to extract structured information. The URL queue is initialized by URLs set in seeds file and valuable URLs are extracted from web pages and added into the queue during the crawling process. Once the time of one post is beyond the specified time span or the web information is unchanged, the crawler can skip it in time to avoid wasting system's resources. Experimental results demonstrate that our crawler can collect real-time forum information more efficiently and precisely than other crawlers.
Phosphatidylinositol 3-Kinase-Associated Protein (PI3KAP)/XB130 Crosslinks Actin Filaments through Its Actin Binding and Multimerization Properties In Vitro and Enhances Endocytosis in HEK293 Cells

Actin-crosslinking proteins control actin filament networks and bundles and contribute to various cellular functions including regulation of cell migration, cell morphology, and endocytosis. Phosphatidylinositol 3-kinase-associated protein (PI3KAP)/XB130 has been reported to be localized to actin filaments (F-actin) and required for cell migration in thyroid carcinoma cells. Here, we show a role for PI3KAP/XB130 as an actin-crosslinking protein. First, we found that the carboxyl terminal region of PI3KAP/XB130 containing amino acid residues 830–840 was required and sufficient for localization to F-actin in NIH3T3 cells, and this region is directly bound to F-actin in vitro. Moreover, actin-crosslinking assay revealed that recombinant PI3KAP/XB130 crosslinked F-actin. In general, actin-crosslinking proteins often multimerize to assemble multiple actin-binding sites. We then investigated whether PI3KAP/XB130 could form a multimer. Blue native-PAGE analysis showed that recombinant PI3KAP/XB130 was detected at 250–1200 kDa although the molecular mass was approximately 125 kDa, suggesting that PI3KAP/XB130 formed multimers. Furthermore, we found that the amino terminal 40 amino acids were required for this multimerization by co-immunoprecipitation assay in HEK293T cells. Deletion mutants of PI3KAP/XB130 lacking the actin-binding region or the multimerizing region did not crosslink actin filaments, indicating that actin binding and multimerization of PI3KAP/XB130 were necessary to crosslink F-actin. Finally, we examined roles of PI3KAP/XB130 on endocytosis, an actin-related biological process. Overexpression of PI3KAP/XB130 enhanced dextran uptake in HEK 293 cells. However, most of the cells transfected with the deletion mutant lacking the actin-binding region incorporated dextran to a similar extent as control cells. Taken together, these results demonstrate that PI3KAP/XB130 crosslinks F-actin through both its actin-binding region and multimerizing region and plays an important role in endocytosis.
Modeling and Control of Water Purification Systems

the mathematical models of each process link consumption in water purification systems were established by means of the mechanism method, and the model for optimal coagulant dosage was given by setting the sum of those units as the objective function. To take into consideration large time delay and disturbance characteristics in the coagulation sedimentation process, a forward-feedback control method was proposed in this paper. Actual results showed that the algorithm introduced was well suited to overcoming disturbances, improving control effectiveness, stabilizing effluent turbidity, and that the optimal coagulant dosage model was satisfied. The result achieved optimal operation of the water purification system, along with operating cost savings.
Coding-residual-based motion vector recovery algorithm

Recently video communication has been massively adopted in internet transmission, and H.264/AVC is the major standard for the compressed video stream. To overcome channel errors resulted from the unstable connection quality of internet, many methods have been proposed for error concealment. Motion vector (MV) recovery is one of the most commonly used methods. We proposed a novel MV recovery method that utilizes the encoding residual information in the neighborhood of the lost MBs, to enhance the performance of MV extrapolation (MVE) and better conceal errors. In our proposed method, better MVs could be found after interpolation with inverse residual weighting. Experimental results show that compared to the state-of-the-art error concealment algorithm, our algorithm provides better performance subjectively and objectively.
SimSOTA: engineering and simulating feedback loops for self-adaptive systems

Engineering a decentralized system of autonomous service components and ensembles having multiple and interacting feedback loops is very challenging. While several works have expressed feedback loops as first-class entities, very little attention has been given to providing actual tool support. In this paper, we propose a novel approach to architect and engineer self-adaptive systems based on feedback loops. We also present the first implementation of SimSOTA, an Eclipse plug-in being developed to support the modeling, simulating and validating of self-adaptive systems based on our feedback loop-based approach. We validate our approach using a case study in cooperative electric vehicles.
CCR2 Gene Deletion and Pharmacologic Blockade Ameliorate a Severe Murine Experimental Autoimmune Neuritis Model of Guillain-Barré Syndrome

The molecular determinants and signaling pathways responsible for hematogenous leukocyte trafficking during peripheral neuroinflammation are incompletely elucidated. Chemokine ligand/receptor pair CCL2/CCR2 has been pathogenically implicated in the acute inflammatory demyelinating polyradiculoneuropathy variant of Guillain-Barré syndrome (GBS). We evaluated the role of CCR2 in peripheral neuroinflammation utilizing a severe murine experimental autoimmune neuritis (sm-EAN) model. Sm-EAN was induced in 8–12 week old female SJL CCR2 knockout (CCR2KO), heterozygote (CCR2HT) and wild type (CCR2WT) mice, and daily neuromuscular severity scores and weights recorded. In vitro and in vivo splenocyte proliferation and cytokine expression assays, and sciatic nerve Toll-like receptor (TLR) 2, TLR4 and CCL2 expression assays were performed to evaluate systemic and local innate immune activation at disease onset. Motor nerve electrophysiology and sciatic nerve histology were also performed to characterize the inflammatory neuropathy at expected peak severity. To further determine the functional relevance of CCR2 in sm-EAN, 20 mg/kg CCR2 antagonist, RS 102895 was administered daily for 5 days to a cohort of CCR2WT mice following sm-EAN disease onset, with efficacy compared to 400 mg/kg human intravenous immunoglobulin (IVIg). CCR2KO mice were relatively resistant to sm-EAN compared to CCR2WT and CCR2HT mice, associated with attenuated peripheral nerve demyelinating neuritis. Partial CCR2 gene deletion did not confer any protection against sm-EAN. CCR2KO mice demonstrated similar splenocyte activation or proliferation profiles, as well as TLR2, TLR4 and CCL2 expression to CCR2WT or CCR2HT mice, implying a direct role for CCR2 in sm-EAN pathogenesis. CCR2 signaling blockade resulted in rapid, near complete recovery from sm-EAN following disease onset. RS 102895 was significantly more efficacious than IVIg. CCR2 mediates pathogenic hematogenous monocyte trafficking into peripheral nerves, with consequential demyelination in sm-EAN. CCR2 is amenable to pharmacologic blockade, making it a plausible drug target for GBS.
An Investigation on Software Bug-Fix Prediction for Open Source Software Projects -- A Case Study on the Eclipse Project

Open source software projects (OSS) receive a large number of bug reports from various contributors and developers alike, where many planned to be fixed by OSS developers. Given the next release cycle information, OSS users can be more effective and flexible in planning and to fix the bugs that are not to be fixed in the next release. It is therefore vital for OSS users to learn which bugs the OSS developers will fix, unfortunately such information may not be readily available, nor there is a prediction framework exists to serve such an important purpose. In this study, we would like to answer the question "Will this bug be fixed by the next release? ", this is addressed by building a bug fixing prediction model based on the characteristics of a bug-related metric and by incorporating the progress of bug fixing measures such as status, period and developer metrics to provide aggregated information for the OSS users. The proposed model calculates the deviance of each variable to analyze the most important metrics, and it has been experimented using a case study with Eclipse platform. Result shows a bug fixing prediction model using both base metrics and state metrics provide significantly better performance in precision (139%) and recall (114\%) than the standard model using only base metrics.
Eurobot Vision System , an Integrated Approach : Results & Recommendations

For ISS application and for exploration, the European Space Agency studies, for ISS application and beyond, a robot that would provide EVA assistant capabilities. This robot, named Eurobot, is of a humanoid like structure with two arms and one leg mounted on a central torso and a head with stereo vision capabilities for scene overview. While developing the vision system, several challenges were encountered: The calibration of the vision system itself, as Eurobot operates both in air and also in water; The hand-eye calibration to relate the identified camera with the end-effector tip; The objects to recognize which are handrails with no sharp edges and texture; Sometimes the vision system could still not identify the handrail location, in this case an automatic recovery procedure was called-in, and the handrail or object pose to grapple was identified with the operator support. The updates of the Eurobot pose into its environment, using results of the vision system. Nevertheless good initial results obtained, vision based control remains a very challenging field. To mitigate risk, ESA has initiated parallel work on vision (VIMANCO). Different methodologies will be evaluated and their merits compared.
An improved fast implementation method for FFT pruning algorithm

For the application of increasing the FFT's spectrum resolution by zero padding, this paper proposes an improved fast implementation method for FFT pruning algorithm, in which only part spectral of the whole FFT's spectral need to be calculated. According to the structural characteristics of input data and output data, the proposed method in this paper utilizes the data copying and assistant matrix to decrease the computational complexity and enhance the implementary flexibility of the FFT pruning algorithm. The simulations show that: With the method proposed in this paper, there is no limitation to the length of the input and output data, the spectrum at any index can be easily obtained, and the computational consumption is effectively decreased.
Experimental Studies of Cognitively Based Air Traffic Control Complexity Metrics for Future Operational Concepts

New procedures and technologies of Air Traffic Control (ATC) under development in Next Generation Air Transportation System (NextGen) will change controllers' tasks, roles, and responsibilities. However, cognitive complexity will remain one of the limiting factors in future system's capacity and none of existing complexity metrics can be directly extended to evaluate cognitive complexity under future operational concepts. Therefore, complexity metrics, applicable to future operational concepts, need to be developed. This thesis developed the structure for a cognitively based complexity metric, Modified Aircraft Count (MAC). Cognitive complexity is decomposed based on individual aircraft complexity factors and sector specific factors. The complexity contribution of each aircraft is summed and adjusted by sector level complexity factors. Cognitive principles, such as controller strategies, may be incorporated in aircraft specific complexity factors and sector level complexity factors. To investigate complexity factors in Modified Aircraft Count, two simulations were developed to explore two proposed NextGen operational concepts, including Time-Based Control at a Metering Fix and Dynamic Route Structure Control. Two experiments were designed to evaluate controller performance and subjective workload under the simulated operational concepts. The Time-Based Control at a Metering Fix was found to have enhanced schedule conformance, reduced operational errors and lower perceived complexity. The Dynamic Route Structure Control introduced longer hand-off acceptance times, however, no other significant changes of controller performance and subjective workload were found.
Periodicity, directionality, and randomness: Wold features for perceptual pattern recognition

One of the fundamental challenges in pattern recognition is choosing a set of features appropriate to a class of problems. In applications such as image retrieval, if is important that features used by the system in pattern comparison provide good measures of "perceptual similarity". The authors present a new set of features and an image model based on the three mutually orthogonal components produced by the 2-D Wold decomposition of random fields. These components have visual properties which approximate the three most important perceptual dimensions of human texture perception. The method presented here is different from the existing Wold-based models in that it tolerates certain local inhomogeneities which arise in natural textures and reduces computation for comparison of patterns subjected to transformations such as rotation. An image retrieval algorithm based on the new texture model is presented. The effectiveness of the new Wold features for retrieving perceptually similar natural textures is demonstrated by comparing it to that of other well-known pattern recognition methods. The Wold model appears to offer a perceptually more satisfying measure of pattern similarity.
Predicting Recovery of Voluntary Upper Extremity Movement in Subacute Stroke Patients with Severe Upper Extremity Paresis

Background and Objective Prediction of voluntary upper extremity (UE) movement recovery is largely unknown in patients with little voluntary UE movement at admission. The present study aimed to investigate (1) the extent and variation of voluntary UE movement recovery, and (2) the best predictive model of the recovery of voluntary UE movement by clinical variables in patients with severe UE paresis. Design Prospective cohort study. Methods 140 (out of 590) stroke patients with severe UE paresis completed all assessments. Voluntary UE movement was assessed using the UE subscale of the Stroke Rehabilitation Assessment of Movement (STREAM-UE). Two outcome measures, STREAM-UE scores at discharge (DCSTREAM-UE) and changes between admission and discharge (ΔSTREAM-UE), were investigated to represent the final states and improvement of the recovery of voluntary UE movement. Stepwise regression analyses were used to investigate 19 clinical variables and to find the best predictive models of the two outcome measures. Results The participants showed wide variation in both DCSTREAM-UE and ΔSTREAM-UE. 3.6% of the participants almost fully recovered at discharge (DCSTREAM-UE > 15). A large improvement (ΔSTREAM-UE >= 10) occurred in 16.4% of the participants, while 32.9% of the participants did not have any improvement. The four predictors for the DCSTREAM-UE (R2 = 35.0%) were ‘baseline STREAM-UE score’, ‘hemorrhagic stroke’, ‘baseline National Institutes of Health Stroke Scale (NIHSS) score’, and ‘cortical lesion excluding primary motor cortex’. The three predictors for the ΔSTREAM-UE (R2 = 22.0%) were ‘hemorrhagic stroke’, ‘baseline NIHSS score’, and ‘cortical lesion excluding primary motor cortex’. Conclusions Recovery of voluntary UE movement varied widely in patients with severe UE paresis after stroke. The predictive power of clinical variables was poor. Both results indicate the complex nature of voluntary UE movement recovery in patients with severe UE paresis after stroke.
A 80~900MHz CMOS VCO with Tunable AAC Circuit

This paper presents an 80~900MHz LC VCO which is implemented in 0.25-mum CMOS technology. The oscillator adopts a multi-VCO structure and an off-chip LC tank. In addition, a charge-pump automatic amplitude control circuit (AAC) is used to ensure a reliable startup and stable working status without degrading the phase noise performance. And the AAC circuit can be tuned to achieve optimized phase noise performance for different frequency bands. Measurement results show that the phase noise achieves -85dBz/Hz at 10 kHz offset frequency
Schema versioning in τXSchema-based multitemporal XML repositories

τXSchema [7] is a framework (a language and a suite of tools) for the creation and validation of time-varying XML documents. A τXSchema schema is composed of a conventional XML Schema document annotated with physical and logical annotations. All components of a τXSchema schema (i.e., conventional schema, logical annotations, and physical annotations) can change over time to reflect changes in user requirements or in reference world of the database. Since many applications need to keep track of both data and schema evolution, schema versioning has been long advocated to be the best solution to do this. In this paper, we deal with schema versioning in the τXSchema framework. More precisely, we propose a set of schema change primitives for the maintenance of logical and physical annotations and define their operational semantics.
$k$ -Connectivity in Random Key Graphs With Unreliable Links

Random key graphs form a class of random intersection graphs that are naturally induced by the random key predistribution scheme of Eschenauer and Gligor for securing wireless sensor network (WSN) communications. Random key graphs have received much attention recently, owing in part to their wide applicability in various domains, including recommender systems, social networks, secure sensor networks, clustering and classification analysis, and cryptanalysis to name a few. In this paper, we study connectivity properties of random key graphs in the presence of unreliable links. Unreliability of graph links is captured by independent Bernoulli random variables, rendering them to be on or off independently from each other. The resulting model is an intersection of a random key graph and an Erdos-Renyi graph, and is expected to be useful in capturing various real-world networks; e.g., with secure WSN applications in mind, link unreliability can be attributed to harsh environmental conditions severely impairing transmissions. We present conditions on how to scale this model's parameters so that: 1) the minimum node degree in the graph is at least k and 2) the graph is k-connected, both with high probability as the number of nodes becomes large. The results are given in the form of zero-one laws with critical thresholds identified and shown to coincide for both graph properties. These findings improve the previous results by Rybarczyk on k-connectivity of random key graphs (with reliable links), as well as the zero-one laws by Yagan on one-connectivity of random key graphs with unreliable links.