Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive highlighting for digital UML class diagrams: a new feature

Improving the usability of software modeling tools is a quest that has led to the growth of a large set of publications covering a wide variety of usability aspects. In the case of reading and navigating within diagrams in modeling tools, existing solutions often ask designers to take time to manually manage the annotations or the layering of elements themselves to improve comfort. To free users from this manual constraint and still facilitate their work, another approach is to augment modeling tools with features capable of autonomously assisting navigation. In this paper, we focus on this approach through the proposal of an automatic highlighting feature for UML class diagrams. After describing its design, we investigate the effect of highlighting on reading and navigating within diagrams using a prototype implemented in the mxGraph environment. To measure the impact of this assistance feature, we conducted a quantitative experiment by presenting 5 types of questions on 4 types of diagrams to 54 participants. The results show that our highlighting feature significantly reduces the response time on simple direct relationship questions, but also reduces the number of errors on navigation questions. Using our highlighting feature also allows users to perceive the task significantly more positively and less demanding. However, one simple highlighting mechanism is not enough to assist complex diagram browsing questions.
Electrical transport properties of focused ion beam lithography Au contacts on PbTiO3 nanorods

PbTiO3 nanorods with tetragonal phase were synthesized by hydrothermal method and heat treatment, and temperature-dependent electrical transport properties of individual PbTiO3 nanorod were investigated. The results show that the conductivities of PbTiO3 nanorods are gradually enhanced with temperature increasing from 77.4 to 295[Formula: see text]K, and exhibit the typical nonlinear I–V characteristics. The barrier height between Au electrode and nanorod is reduced from 0.137 to 0.088[Formula: see text]eV with increasing bias from 0.2 to 1[Formula: see text]V. The corresponding values of thermal activation energies are 0.172 and 0.06[Formula: see text]eV below the conduction band for 180–295 and 77.4–180[Formula: see text]K, respectively. This semiconductor-like behavior may result from the larger number of surface defects or localized states in the amorphorized PbTiO3.
A Performance Comparison Of Clustering Algorithms In Ad Hocnetworks

An ad hoc network is comprised of wireless mobile nodes without the need of wired network infrastructure. Due to the limited transmission range of nodes, the exchange of data between them may not be possible using direct communication. Partitioning the network into clusters and electing a clusterhead for each cluster to assist with the resource allocation and data packet transmissions among its members and neighboring clusterheads is one of the most common ways of providing support for the existing ad hoc routing protocols. This thesis presents the performance comparison of four ad hoc network clustering protocols: Dynamic Mobile Adaptive Clustering (DMAC), Highest-Degree and Lowest-ID algorithms, and Weighted Clustering Algorithm (WCA). Yet Another Extensible Simulation (YAES) was used as the simulator to carry out the simulations.
Lighting up supervised learning in user review-based code localization: dataset and benchmark

As User Reviews (URs) of mobile Apps are proven to provide valuable feedback for maintaining and evolving applications, how to make full use of URs more efficiently in the release cycle of mobile Apps has become a widely concerned and researched topic in the Software Engineering (SE) community. In order to speed up the completion of coding work related to URs to shorten the release cycle as much as possible, the task of User Review-based code localization is proposed and studied in depth. However, due to the lack of large-scale ground truth dataset (i.e., truly related pairs), existing methods are all unsupervised learning-based. In order to light up supervised learning approaches, which are driven by large labeled datasets, for Review2Code, and to compare their performances with unsupervised learning-based methods, we first introduce a large-scale human-labeled ground truth dataset, including the annotation process and statistical analysis. Then, a benchmark consisting of two SOTA unsupervised learning-based and four supervised learning-based Review2Code methods is constructed based on this dataset. We believe that this paper can provide a basis for in-depth exploration of the supervised learning-based Review2Code solutions.
CodeMatcher: a tool for large-scale code search based on query semantics matching

Due to the emergence of large-scale codebases, such as GitHub and Gitee, searching and reusing existing code can help developers substantially improve software development productivity. Over the years, many code search tools have been developed. Early tools leveraged the information retrieval (IR) technique to perform an efficient code search for a frequently changed large-scale codebase. However, the search accuracy was low due to the semantic mismatch between query and code. In the recent years, many tools leveraged Deep Learning (DL) technique to address this issue. But the DL-based tools are slow and the search accuracy is unstable. In this paper, we presented an IR-based tool CodeMatcher, which inherits the advantages of the DL-based tool in query semantics matching. Generally, CodeMatcher builds indexing for a large-scale codebase at first to accelerate the search response time. For a given search query, it addresses irrelevant and noisy words in the query, then retrieves candidate code from the indexed codebase via iterative fuzzy search, and finally reranks the candidates based on two designed measures of semantic matching between query and candidates. We implemented CodeMatcher as a search engine website. To verify the effectiveness of our tool, we evaluated CodeMatcher on 41k+ open-source Java repositories. Experimental results showed that CodeMatcher can achieve an industrial-level response time (0.3s) with a common server with an Intel-i7 CPU. On the search accuracy, CodeMatcher significantly outperforms three state-of-the-art tools (DeepCS, UNIF, and CodeHow) and two online search engines (GitHub search and Google search).
Cryogenic Multilayer Insulation Theory and An Analysis of Seams Under a Variety of Assumptions

The theory of thermal radiation as applied to cryogenic surfaces is explored and validation cases are solved in Thermal Desktop. Some results are compared to previously published research. Additionally, new results are published regarding cracks in both spherical and cylindrical cryogenic insulations with a cold boundary of 90 K to 220 K for ten layer blankets under a variety of assumptions and scenarios. It was found that enabling directional emission–as well as specular, mirrorlike reflections–have little impact on the results.
Influence of lignin-based adhesives upon the properties of particleboards made from rape straws.

The present paper investigates the physical and mechanical properties of the particleboard made from rape straws and lignin-based adhesives as bonding agents. Three receipts of lignin-based adhesives were prepared by hydroxyl methylation reaction. For the first one, lignin was treated by hydroxyl methylation with NaOH, formaldehyde was added for the second one and oxidation with H2O2 was applied for the third receipt. In the last variant, untreated lignin was used for particleboard manufacturing. Target density of the panels was of 600kg/m. Boards were hot pressed at a temperature of 180oC, pressure of 2.5N/mm and pressing time of 1min/mm. Physical (density, water absorption, and thickness swelling) and mechanical (modulus of elasticity, bending strength and internal bond strength) properties of the particleboards obtained in the laboratory conditions were tested, and the recorded values were compared to the limits imposed by SR EN 312: 2004 technical specifications. Particleboard made with lignin treated by hydroxyl methylation with NaOH as adhesive met the requirements of SR EN 312: 2004 for P1 panels. A good performance of internal bond property was recorded for the boards where lignin was treated by oxidation with H2O2. Pure lignin proved to have a poor adhesion to the rape straw particles. Unfortunately, the resistance to water for all panels was too low. Water absorption and thickness swelling recorded high values for all variants.
Safe and Interactive Autonomy: Control, Learning, and Verification

Author(s): Sadigh, Dorsa | Advisor(s): Seshia, Sanjit; Sastry, Shankar | Abstract: The goal of my research is to enable safe and reliable integration of human-robot systems in our society by providing a unified framework for modeling and design of these systems. Today's society is rapidly advancing towards autonomous systems that interact and collaborate with humans, e.g., semiautonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. The safety-critical nature of these systems require us to provide provably correct guarantees about their performance. In this dissertation, we develop a formalism for the design of algorithms and mathematical models that enable correct-by-construction control and verification of human-robot systems.We focus on two natural instances of this agenda. In the first part, we study interaction-aware control, where we use algorithmic HRI to be mindful of the effects of autonomous systems on humans' actions, and further leverage these effects for better safety, efficiency, coordination, and estimation. We further use active learning techniques to update and better learn human models, and study the accuracy and robustness of these models. In the second part, we address the problem of providing correctness guarantees, while taking into account the uncertainty arising from the environment or human models. Through this effort, we introduce Probabilistic Signal Temporal Logic (PrSTL), an expressive specification language that allows representing Bayesian graphical models as part of its predicates. Further, we provide a solution for synthesizing controllers that satisfy temporal logic specifications in probabilistic and reactive settings, and discuss a diagnosis and repair algorithm for systematic transfer of control to the human in unrealizable settings.While the algorithms and techniques introduced can be applied to many human-robot systems, in this dissertation, we will mainly focus on the implications of my work for semiautonomous driving.
Single-crystal gradient plasticity with an accumulated plastic slip: Theory and applications

In experiments on metallic microwires, size effects occur as a result of the interaction of dislocations with, e.g., grain boundaries. In continuum theories this behavior can be approximated using gradient plasticity. A numerically efficient geometrically linear gradient plasticity theory is developed considering the grain boundaries and implemented with finite elements. Simulations are performed for several metals in comparison to experiments and discrete dislocation dynamics simulations.
First Principle Study of the Physical Properties of Platinum (Pt) Decorated Graphene and NH2 Doped Pt-decorated Graphene; Effect on Hydrogen Storage

We conducted theoretical investigation of the structural and electronic properties of Pt-functionalized graphene and NH-doped Pt-functionalized graphene, which are shown to be efficient materials for hydrogen storage. Nitrene radical dopant was an effective addition required for enhancing the Pt binding on the graphene sheet. We found that up to three H2 molecules could be adsorbed by Pt-functionalized graphene with an average binding energy in the range 3.049−1.731eV eV. The most crucial part of our work is measuring the effect of nitrene radical on Pt-functionalized graphene. Our calculations predicted that the addition of NH radicals on Pt-functionalized graphene enhance the binding of Pt on graphene, which helps also to avoid the desorption of Pt(H2)n (n=1-3) complexes from graphene sheet. Our results also predict Pt-functionalized NH-doped graphene is a potential hydrogen storage medium for on-board applications.
Characteristics of the droplet motion of a liquid antifreeze reagent

The object of investigation is the process of spraying of the anti-icing reagent. As an object of research, external forces are selected that affect on each drop of the reagent: counteraction forces, gravity forces, Coriolis force and centrifugal inertial forces, lifting force, frictional forces of the reagent on the surface of the working equipment: disk and blades. It is assumed that the liquid reactant is fed under pressure to the hydraulic nozzles installed in the disk casing, and then falls onto the distribution disk. The tasks solved within the framework of the article: the identification of external forces acting on each drop of the reagent from the moment of flow from the nozzle to the moment when it reaches the coating, the study of the effect of external forces on the characteristics of droplet motion, the mathematical description of the process of formation of the sputtering zone. To refine the droplet motion characteristics under the action of external forces using the already available mathematical description of the droplet motion along a distribution disk, a mathematical model of their motion in the air environment has been developed. The equation of motion of the drops of the reagent, the dependences of the droplet's flight range on the mode and parameters of the working equipment are obtained. Meteorological factors such as wind speed and direction, as well as air environment properties (dynamic and kinematic viscosity, depending on the temperature of the medium) are considered in the simulation. This model will provide an opportunity to the reasonably assignation of the parameters of the distribution equipment during their design and operation and will also serve as a base for mathematical and software systems for the continuous monitoring of the process of applying liquid reagents for road and airfield pavements. Its operation will allow to provide a high-quality treatment of coatings ensuring the preservation of their operational properties and to make a reagent savings.
Rescue of the increased susceptibility to Mild Chronic Oxidative Stress of iNeurons carrying the MAPT Chromosome 17q21.3 H1/H1 risk allele by FDA-approved compounds

The microtubule associated protein tau (MAPT) chromosome 17q21.31 locus lies within a region of high linkage disequilibrium (LD) conferring two extended haplotypes commonly referred to as H1 and H2. The major haplotype, H1 has been genetically associated with an increased risk for multiple neurodegenerative disorders, including Progressive Supranuclear Palsy (PSP), Corticobasal Degeneration (CBD), APOE ε4-negative Alzheimer’s disease (AD) and Parkinson’s disease (PD). The mechanism causing this increased risk is largely unknown. Here, we investigated the role of Mild Chronic Oxidative Stress (MCOS) in neurogenin 2 (NGN2) induced neurons (iNeurons) derived from iPS (induced pluripotent stem cells) from carriers of both haplotypes. We identified that iNeurons of the H1 homozygous haplotype showed an increased susceptibility to MCOS compared to homozygous H2 carriers, leading to cell death through ferroptosis. We performed a cellular screen in H1 iNeurons using a FDA-approved Drug Library and identified candidate molecules that rescued the increased susceptibility to MCOS and prevented ferroptosis in H1 iNeurons. Highlights Mild Chronic Oxidative Stress induces neurotoxicity via ferroptosis on iNGN2 neurons Axonal degeneration, disordered microtubules, blebs precede neurotoxicity MAPT-17q21.3 locus H1/H1, risk allele for NDD is more vulnerable to MCOS FDA-approved drugs reverse MCOS induced ferroptosis on H1/H1 risk allele
Tutorial and Survey Articles: An introduction to Petri Nets

This paper describes the fundamental concepts and characteristics of Petri nets (PNs) that make them a significant tool for modeling and analyzing asynchronous systems with concurrent and parallel activities and follows the extensions that improved the implementation capabilities of the original PNs. Their first and most relevant extension was time modeling, a vital aspect of system performances not considered in the original version. There are several possibilities for introducing time in PNs. Among them, a technique that associates time with places is presented in some detail. As PNs tend to become cumbersome and time consuming when large and complex systems are involved, a method for decomposing timed PNs of open queuing networks is reviewed here. Though initially developed as an information/computer-based technique, PNs were immediately adopted in a variety of application areas, such as manufacturing, design, planning and control. Viewed through a more recently developed programming perspective, the ordinary PNs became “high level” PNs suitable for defining different data types and for applying hierarchical approaches. It is expected that the robust theoretical basis of this tool coupled with its visual and flexibility features will continue to appeal to researchers and practitioners alike in a variety of domains and as a result will continue to evolve and expand.
Screening of Metabolism-Disrupting Chemicals on Pancreatic α-Cells Using In Vitro Methods

Metabolism-disrupting chemicals (MDCs) are endocrine disruptors with obesogenic and/or diabetogenic action. There is mounting evidence linking exposure to MDCs to increased susceptibility to diabetes. Despite the important role of glucagon in glucose homeostasis, there is little information on the effects of MDCs on α-cells. Furthermore, there are no methods to identify and test MDCs with the potential to alter α-cell viability and function. Here we used the mouse α-cell line αTC1-9 to evaluate the effects of MDCs on cell viability and glucagon secretion. We tested six chemicals at concentrations within human exposure (from 0.1 pM to 1 μM): bisphenol-A (BPA), tributyltin (TBT), perfluorooctanoic acid (PFOA), triphenylphosphate (TPP), triclosan (TCS), and dichlorodiphenyldichloroethylene (DDE). Using two different approaches, MTT assay and DNA-binding dyes, we observed that BPA and TBT decreased α-cell viability via a mechanism that depends on the activation of estrogen receptors and PPARγ, respectively. These two chemicals induced ROS production, but barely altered the expression of endoplasmic reticulum (ER) stress markers. Although PFOA, TPP, TCS, and DDE did not alter cell viability nor induced ROS generation or ER stress, all four compounds negatively affected glucagon secretion. Our findings suggest that αTC1-9 cells seem an appropriate model to test chemicals with metabolism-disrupting activity and that the improvement of the test methods proposed herein could be incorporated into protocols for the screening of diabetogenic MDCs.
Psychological and social indicators of suicide ideation and suicide attempts in Zuni adolescents

Suicide behavior is a significant problem for many American Indian populations, often more so than in the general population, but little tribal-specific data available. In this study, baseline data on the correlates of suicide ideation and the social and psychological differences between suicide attempters and nonattempters were collected on a sample of 84 Zuni adolescents. Results show significant correlations between a measure of suicide ideation and past suicide attempt behavior, drug use, depression, hopelessness, stress, psychological symptomatology, social support, liking for school, and interpersonal communication. Significant differences between the 30% of the students who reported having previously attempted suicide and the nonattempters were also found on these measures. Areas for education and prevention efforts are suggested. Language: en
A new Taylor tensile impact test for the identification of dynamic material behavior law

Strain rate has a significant influence on the material behavior subjected to dynamic loading, that is why a lot of work has been concentrated on accurate high strain rate experiments to identify the parameters of such dynamic constitutive laws. Taylor impact test, based on the use of gas gun, is well known because some ultra-high strain rates (around $10^{5}\;s^{-1}$) can be attained in this kind of test. An original tensile test, based on Taylor impact technique, has already been proposed in our laboratory (Laboratoire Genie de Production) for characterizing the behavior of materials subjected to high strain rate tensile loading, where a projectile is launched to impact a specially designed target and tensile deformation is mainly generated in the center zone of the target. In the present paper, a new design of this target is proposed in order to optimize the results.
Optimization of an Injection Locked Laser System for Cold Neutral Atom Traps

Many types of quantum systems are being explored for use in quantum computers. One type of quantum system that shows promise for quantum computing is trapped neutral atoms. They have long coherence times, since they have multiple stable ground states and have minimal coupling with other atoms and their environment, and they can be trapped in arrays, making them individually addressable. Once trapped, they can be initialized and operated on using laser pulses. This experiment utilizes a pinhole diffraction pattern, which can trap atoms in both bright and dark areas. To maximize trap strength, an injection-locked laser amplification system is used to provide a high-power, precisely tunable light source for the diffraction pattern. This amplification system depends on the coupling between a “seed” laser and a “receiving” laser. In previous analyses of the coupling between these two laser diodes, the effects on injection locking when varying temperature and current of both lasers have been shown to be highly nonlinear, and few general trends have been identified. In this project, in order to optimize and better characterize the system, automation of the data-taking and varying parameters was implemented. High efficiency lock zones of laser currents and temperatures were identified, and these locking zones will allow us to create strong atom traps for our experiment.
Feature Selection And Vectorization In Legal Case Documents Using Chi-Square Statistical Analysis And Naïve Bayes Approaches

Most machine learning techniques employed in the area of text classification require the features of the documents to be effectively selected owing to the large chunk of data encountered in the classification process and term weights built from document vectors for proper infusing into the respective classifier algorithms. Effective selection of the most important features from the raw documents is achieved by implementing more extensive pre-processing techniques and the features obtained were ranked using the chisquare statistical approach for the elimination of irrelevant features and proper selection of more relevant features in the entire corpus. The most relevant ranked features obtained are converted to word vectors which is based on the number of occurrences of words in the documents or categories concerned, using the probabilistic characteristics of Naïve Bayes as a vectorizer for machine learning classifiers. This hybrid vector space model was experimented on legal text categories and the study revealed better discovered features using the preprocessing and ranking technique, while better term weights from the documents was successfully built for machine learning classifiers used in the text classification process.