Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating Automated Student Modeling in a Java MOOC

With the advent of ubiquitous web, programming is no longer a sole prerogative of computer science schools. Scripting languages are taught to wider audiences and programming has become a flag post of any technology related program. As more and more students are exposed to coding, it is no longer a trade of the select few. As a result, students who would not opt for a coding class a decade ago are in a position of having to learn a rather difficult subject. The problem of assisting students in learning programming has been explored in several intelligent tutoring systems. The key component of such systems is a student model that keeps track of student progress. In turn, the foundation of a student model is a domain model – a vocabulary of skills (or concepts) that structures the representation of student knowledge. Building domain models for programming is known as a complicated task. In this paper we explore automated approaches for extracting domain models for learning programming languages and modeling student knowledge in the process of solving programming exercises. We evaluate the validity of this approach using large volume of student code submission data from a MOOC on introductory Java programming.
Quantization for soft-output demodulators in bit-interleaved coded modulation systems

We study quantization of log-likelihood ratios (LLR) in bit-interleaved coded modulation (BICM) systems in terms of an equivalent discrete channel. We propose to design the quantizer such that the quantizer outputs become equiprobable. We investigate semi-analytically and numerically the ergodic and outage capacity over single- and multiple-antenna channels for different quantizers. Finally, we show bit error rate simulations for BICM systems with LLR quantization using a rate 1/2 low-density parity-check code.
Space-time observation of an electron gas in SiO2.

We report the first space-time observation of the ultrafast excitation and relaxation of an electron gas pumped into the conduction band of a wide band-gap insulator by an intense subpicosecond laser pulse. The experiment is based on a new phase-sensitive technique which allows a resolution of 120 fs in time and 5 \ensuremath{\mu}m in space. In crystalline and amorphous Si${\mathrm{O}}_{2}$, no evidence of gas expansion has been observed and a mean trapping time of 150 fs for the photogenerated carriers is measured.
Mobile Social Media Mining Challenges Overview : A Case Study of WeChat

Data mining is likely to be considered a much valuable tool especially when applied to social media. Social media mining is the process of representing, analyzing and extracting useful patterns from data in social media, resulting from social interactions. Since its release in 2011 WeChat quickly became the most fast-growing networking mobile app in China. People of similar interests and backgrounds meet and cooperate using this social network, enabling them to share information flexibly and globally. Today just like Facebook and Twitter, WeChat contains millions of unprocessed raw data. The mined information from this mobile social media can considerably impact business strategy of any business enterprise. However, for the general public, mining WeChat unlike Facebook and Twitter remains a very complex task. This paper identifies and analyzes some challenges engineers and researchers may face if they want to mine this rich user-generated contains from WeChat database.
Starting up the Multilingual Central Repository

This paper describes the initial design of the Multilingual Central Repository. The first version of the MCR integrates into the same EuroWordNet framework, five local wordnets (including three versions of the English WordNet from Princeton), the EuroWordNet Top Ontology, MultiWordNet Domains, and hundreds of thousand of new semantic relations and properties automatically acquired from corpora. In fact, the resulting MCR is going to constitute the largest and richest multilingual lexical-knowledge ever build.
Theoretical Evaluation of Moisture Protection Using Coatings

Abstract : A theoretical approach is used to determine important attributes for moisture protection of polymer-matrix composite structures provided by polymeric coatings. Developed solutions are used to evaluate a range of coating materials and thicknesses for thin and thick substrates. The diffusion constants and the saturation levels for the coating material were obtained from the range of available coating materials. The results include typical diffusion patterns for coating materials, saturation of the coating layer, development of moisture through time, and effects of the material properties for the various substrate thicknesses. Moisture diffusion behavior at the substrate-coating interface is also presented. For relatively thick coating layers, the results show that the diffusion constant and the saturation level of the coating must both be low to significantly affect the diffusion process. The study also shows differences in the behavior of the substrate-coating interface.
Vaccinia Virus–Encoded Ribonucleotide Reductase Subunits Are Differentially Required for Replication and Pathogenesis

Ribonucleotide reductases (RRs) are evolutionarily-conserved enzymes that catalyze the rate-limiting step during dNTP synthesis in mammals. RR consists of both large (R1) and small (R2) subunits, which are both required for catalysis by the R12R22 heterotetrameric complex. Poxviruses also encode RR proteins, but while the Orthopoxviruses infecting humans [e.g. vaccinia (VACV), variola, cowpox, and monkeypox viruses] encode both R1 and R2 subunits, the vast majority of Chordopoxviruses encode only R2 subunits. Using plaque morphology, growth curve, and mouse model studies, we investigated the requirement of VACV R1 (I4) and R2 (F4) subunits for replication and pathogenesis using a panel of mutant viruses in which one or more viral RR genes had been inactivated. Surprisingly, VACV F4, but not I4, was required for efficient replication in culture and virulence in mice. The growth defects of VACV strains lacking F4 could be complemented by genes encoding other Chordopoxvirus R2 subunits, suggesting conservation of function between poxvirus R2 proteins. Expression of F4 proteins encoding a point mutation predicted to inactivate RR activity but still allow for interaction with R1 subunits, caused a dominant negative phenotype in growth experiments in the presence or absence of I4. Co-immunoprecipitation studies showed that F4 (as well as other Chordopoxvirus R2 subunits) form hybrid complexes with cellular R1 subunits. Mutant F4 proteins that are unable to interact with host R1 subunits failed to rescue the replication defect of strains lacking F4, suggesting that F4-host R1 complex formation is critical for VACV replication. Our results suggest that poxvirus R2 subunits form functional complexes with host R1 subunits to provide sufficient dNTPs for viral replication. Our results also suggest that R2-deficient poxviruses may be selective oncolytic agents and our bioinformatic analyses provide insights into how poxvirus nucleotide metabolism proteins may have influenced the base composition of these pathogens.
Acylated and unacylated ghrelin inhibit doxorubicin‐induced apoptosis in skeletal muscle

Doxorubicin, a potent chemotherapeutic drug, has been demonstrated previously as an inducer of apoptosis in muscle cells. Extensive induction of apoptosis may cause excessive loss of muscle cells and subsequent functional decline in skeletal muscle. This study examined the effects of acylated ghrelin, a potential agent for treating cancer cachexia, on inhibiting apoptotic signalling in doxorubicin‐treated skeletal muscle. Unacylated ghrelin, a form of ghrelin that does not bind to GHSR‐1a, is also employed in this study to examine the GHSR‐1a signalling dependency of the effects of ghrelin.
Fragmental Frequency Analysis Method to Estimate Electrical Cell Parameters From Bioimpedance Study

This paper introduces an alternate approach utilizing the fragmental frequency analysis method for analyzing bioimpedance data to estimate electrical cell parameters. Impedance of cervical cancer cells (HeLa) in phosphate buffer saline media is measured using an electric cell-substrate impedance sensing (ECIS) device and impedance analyzer. The measured impedance data were visualized by modeling an equivalent electrical circuit of the system considering the dominancy of individual parameters of the ECIS system and analyzed in different frequency zones. The present approach eliminates the convergence inaccuracy in fitting the experimental impedance data with fitting software arising due to invalid initial conditions, and a large number of data points. This method provides high-frequency characterization, modeling of ECIS system, knowledge of effect of ECIS model parameters with frequency, and an alternate way to calculate model parameters.
Locator/ID Separation Protocol Delegated Database Tree (LISP-DDT) Referral Internet Groper (RIG)

A simple tool called the Locator/ID Separation Protocol Delegated Database Tree (LISP-DDT) Referral Internet Groper (RIG), also referred to in this document as "rig", can be used to query the LISP- DDT hierarchy. This document describes how the "rig" tool works.
Prediction of Skin Sensitization with a Particle Swarm Optimized Support Vector Machine

Skin sensitization is the most commonly reported occupational illness, causing much suffering to a wide range of people. Identification and labeling of environmental allergens is urgently required to protect people from skin sensitization. The guinea pig maximization test (GPMT) and murine local lymph node assay (LLNA) are the two most important in vivo models for identification of skin sensitizers. In order to reduce the number of animal tests, quantitative structure-activity relationships (QSARs) are strongly encouraged in the assessment of skin sensitization of chemicals. This paper has investigated the skin sensitization potential of 162 compounds with LLNA results and 92 compounds with GPMT results using a support vector machine. A particle swarm optimization algorithm was implemented for feature selection from a large number of molecular descriptors calculated by Dragon. For the LLNA data set, the classification accuracies are 95.37% and 88.89% for the training and the test sets, respectively. For the GPMT data set, the classification accuracies are 91.80% and 90.32% for the training and the test sets, respectively. The classification performances were greatly improved compared to those reported in the literature, indicating that the support vector machine optimized by particle swarm in this paper is competent for the identification of skin sensitizers.
Multi-Objective Optimal SVC Installation for Power System Loading Margin Improvement

Proper installation of flexible ac transmission systems (FACTS) in existing transmission networks can improve transmission system loading margin (LM) to a certain degree and reduce network expansion cost. In the paper, under each contingency with high risk index (RI) value, the modal analysis (MA) technique is used to determine which buses need static var compensator (SVC) installation, and with maximum LM and minimum SVC installation cost composed into the multi-objective function the optimal LM enhancement problem is formulated as a multi-objective optimization problem (MOP) and solved by using the fitness sharing multi-objective particle swarm optimization (MOPSO) algorithm for a Pareto front set. In the Pareto front set for each considered contingency, the solution with the biggest performance index value is determined for SVC installation. Finally, an SVC installation scheme derived from the union of the SVC installations for all considered contingencies is recommended for LM enhancement. The proposed method is validated on the IEEE 24-bus reliability test system (RTS) and a practical power system.
Aural-perceptual speaker identification: problems with noncontemporary samples

The degree to which speech and/or speech samples are noncontemporary is considered important to the speaker identification process. There are two dimensions to the problem; the first relates to the listener and, especially, to earwitness lineups. Here, the subject or witness is asked to make identifications at various times after having heard (but not having seen, of course) the speaker. It has been found that a person's memory for a voice decays over time. In the second case, it is the samples of the speaker's utterances which are temporally displaced. The prevailing opinion here has been that the use of non- contemporary speech samples poses just as difficult a challenge to the speaker identifi- cation process as does the decaying memory of a witness. Accordingly, research was carried out to test this possibility (Hollien and Schwartz, in press); it was found that the overall drop in correct identification over latencies from four weeks to six years was only about 15-25 per cent. It was not until the greatest of the time separations was studied (i.e., twenty years) that a substantial drop occurred (to 31 per cent). At this juncture, a number of questions arose; and three of them have been investigated. First, is listener gender important to the process; second, are the identification levels affected by the type of lis- teners employed and, finally, can external factors serve to differentially degrade listener performance? It was found that the first question could be answered in the negative and the second two in the affirmative. These findings should aid in clarifying some of the rela- tionship between sample latency and identification accuracy.
Robust Estimation of Light Directions and Albedo Map of an Object of Known Shape

This paper describes a method to determine the direction of a light source and the distribution of diffuse reflectance from two images under different lighting conditions. While most inverse-rendering methods require 3 or more images, we investigate the use of only two images. Using the relationships between albedo and light direction at 6 or more points, we firstly show that it is possible to simultaneously estimate both of these if the shape of the target object is given. Then we extend our method to handle a specular object and shadow effect by applying a robust estimation method. Thorough experimentation shows that our method is feasible and stable not only for well controlled indoor scenes, but also for an outdoor environment illuminated by sunlight.
Randomized trial of denosumab in patients receiving adjuvant aromatase inhibitors for nonmetastatic breast cancer.

PURPOSE Adjuvant aromatase inhibitor therapy is well established in postmenopausal women with hormone receptor-positive breast cancer, but such therapy is complicated by accelerated bone loss and increased fracture risk. We investigated the ability of denosumab, a fully human monoclonal antibody against receptor activator of nuclear factor-kappaB ligand, to protect against aromatase inhibitor-induced bone loss. PATIENTS AND METHODS Eligible women with hormone receptor-positive nonmetastatic breast cancer treated with adjuvant aromatase inhibitor therapy were stratified by duration of aromatase inhibitor therapy (< or = 6 v > 6 months), received supplemental calcium and vitamin D, and were randomly assigned to receive placebo (n = 125) or subcutaneous denosumab 60 mg (n = 127) every 6 months. At enrollment, all patients were required to have evidence of low bone mass, excluding osteoporosis. The primary end point was percentage change from baseline at month 12 in lumbar spine bone mineral density (BMD). RESULTS At 12 and 24 months, lumbar spine BMD increased by 5.5% and 7.6%, respectively, in the denosumab group versus placebo (P < .0001 at both time points). Increases were observed as early as 1 month and were not influenced by duration of aromatase inhibitor therapy. Increases in BMD were also observed at the total hip, total body, femoral neck, and the predominantly cortical one-third radius. Bone turnover markers decreased with denosumab treatment. Overall incidence of treatment-emergent adverse events (AEs) was similar between treatment groups. CONCLUSION In women with nonmetastatic breast cancer and low bone mass who were receiving adjuvant aromatase inhibitor therapy, twice-yearly administration of denosumab led to significant increases in BMD over 24 months at trabecular and cortical bone, with overall AE rates similar to those of placebo.
Diffusion of Xenon and Nitrous Oxide into the Bowel during Mechanical Ileus

ONE well-known side effect of nitrous oxide is its diffusion into gas filled spaces, including the bowel. In dogs, Eger and Saidman found increased gas volumes in obstructed bowel after 4 h of 70-80% nitrous oxide anesthesia. In their study, it was speculated that the distension of the bowels and consecutive impairment of bowel perfusion could self-limit the effect of increased intraluminal pressure and thus prevent the rupture of bowels. 1 1 That assumption has never been tested. From a previous investigation xenon is known to diffuse into bowels to a lesser extent than nitrous oxide. Whether ileus is a contraindication for the administration of xenon could not be answered in this investigation. 2 These questions were investigated in the current study.
Offset Analysis and Design Optimization of a Dynamic Sense Amplifier for Resistive Memories

The input-referred offset of a dynamic latch-based sense amplifier for resistive memories is extensively analyzed. This circuit is modeled using both small and large signal analysis, in order to evaluate mismatch effects and to support design robustness to process variations. Effect of various design parameters on offset are studied and reported. It is shown that load capacitance has a profound effect on the sense amplifier offset. Design optimization is then proposed thanks to this analysis, resulting to an input-referred offset (simply called offset in the rest of the paper) down to about 200 Ohms for one sigma variation with 20fF applied load capacitance.
Essential Role of Cytoplasmic cdk5 and Prx2 in Multiple Ischemic Injury Models, In Vivo

Recent evidence suggests that abnormal activation of cyclin-dependent kinase 5 (cdk5) is a critical prodeath signal in stroke. However, the mechanism(s) by which cdk5 promotes death is unclear. Complicating the role of cdk5 are the observations that cdk5 can exist in multiple cellular regions and possess both prosurvival and prodeath characteristics. In particular, the critical role of cytoplasmic or nuclear cdk5 in neuronal jury, in vivo, is unclear. Therefore, we determined where cdk5 was activated in models of ischemia and how manipulation of cdk5 in differing compartments may affect neuronal death. Here, we show a critical function for cytoplasmic cdk5 in both focal and global models of stroke, in vivo. Cdk5 is activated in the cytoplasm and expression of DNcdk5 localized to the cytoplasm is protective. Importantly, we also demonstrate the antioxidant enzyme Prx2 (peroxiredoxin 2) as a critical cytoplasmic target of cdk5. In contrast, the role of cdk5 in the nucleus is context-dependent. Following focal ischemia, nuclear cdk5 is activated and functionally relevant while there is no evidence for such activation following global ischemia. Importantly, myocyte enhancer factor 2D (MEF2D), a previously described nuclear target of cdk5 in vitro, is also phosphorylated by cdk5 following focal ischemia. In addition, MEF2D expression in this paradigm ameliorates death. Together, our results address the critical issue of cdk5 activity compartmentalization, as well as define critical substrates for both cytoplasmic and nuclear cdk5 activity in adult models of stroke.
An Incentive Compatible Multi-Armed-Bandit Crowdsourcing Mechanism with Quality Assurance

Consider a requester who wishes to crowdsource a series of identical binary labeling tasks to a pool of workers so as to achieve an assured accuracy for each task, in a cost optimal way. The workers are heterogeneous with unknown but fixed qualities and their costs are private. The problem is to select for each task an optimal subset of workers so that the outcome obtained from the selected workers guarantees a target accuracy level. The problem is a challenging one even in a non strategic setting since the accuracy of aggregated label depends on unknown qualities. We develop a novel multi-armed bandit (MAB) mechanism for solving this problem. First, we propose a framework, Assured Accuracy Bandit (AAB), which leads to an MAB algorithm, Constrained Confidence Bound for a Non Strategic setting (CCB-NS). We derive an upper bound on the number of time steps the algorithm chooses a sub-optimal set that depends on the target accuracy level and true qualities. A more challenging situation arises when the requester not only has to learn the qualities of the workers but also elicit their true costs. We modify the CCB-NS algorithm to obtain an adaptive exploration separated algorithm which we call { \em Constrained Confidence Bound for a Strategic setting (CCB-S)}. CCB-S algorithm produces an ex-post monotone allocation rule and thus can be transformed into an ex-post incentive compatible and ex-post individually rational mechanism that learns the qualities of the workers and guarantees a given target accuracy level in a cost optimal way. We provide a lower bound on the number of times any algorithm should select a sub-optimal set and we see that the lower bound matches our upper bound upto a constant factor. We provide insights on the practical implementation of this framework through an illustrative example and we show the efficacy of our algorithms through simulations.
Refinement of Surface Mesh for Accurate Multi-View Reconstruction

In this paper we propose a pipeline for accurate 3D reconstruction from multiple images that deals with some of the possible sources of inaccuracy present in the input data. Namely, we address the problem of inaccurate camera calibration by including a method adjusting the camera parameters in a global structure-and-motion problem, which is solved with a depth map for representation that is suitable to large scenes. Secondly, we take the triangular mesh and calibration improved by the global method in the first phase to refine the surface both geometrically and radiometrically. Here we propose surface energy which combines photoconsistency with contour matching and minimize it with a gradient descent method. Our main contribution lies in effective computation of the gradient that naturally regularization and data terms by employing scale space approach. The results are demonstrated on standard high-resolution datasets and a complex outdoor scene.
APLICATION THE DEVELOPMENT OF BALIKPAPAN BAY INDONESIA BASED ON SUSTAINABLE TOURISM

The development of sustainable tourism has become an important issue for every country. Although it has been studied extensively, the study of bay tourism development which is in danger of damage is still limited. The purpose of this study is to (1) investigate the picture of tourism potential in Balikpapan Bay; (2) analyze the concept of sustainable tourism development in Balikpapan Bay; (3) examine the direction of sustainable tourism management policies in Balikpapan Bay as a leading tourist destination. The study method uses a mixed method approach. The results of the study revealed that the Balikpapan Bay area has the potential to be an ecotourism-based tourist area with the presence of marine ecosystems, coral reefs, mangrove forests, duyung (mermaid)/ dugong (dugong dugon), and the existence of 250,000 inhabitants of Balikpapan Bay, 80 percent of whom are fishermen. This concept can simultaneously be a solution in facing the threat of more severe environmental damage, increasing the economy of the local community and preserving the culture of the community. The direction of the development of Balikpapan Bay based on sustainable tourism is the Destination Management Organization (DMO).