Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulee: Detecting CUDA Synchronization Bugs via Memory-Access Modeling

While CUDA has become a mainstream parallel computing platform and programming model for general-purpose GPU computing, how to effectively and efficiently detect CUDA synchronization bugs remains a challenging open problem. In this paper, we propose the first lightweight CUDA synchronization bug detection framework, namely Simulee, to model CUDA program execution by interpreting the corresponding LLVM bytecode and collecting the memory-access information for automatically detecting general CUDA synchronization bugs. To evaluate the effectiveness and efficiency of Simulee, we construct a benchmark with 7 popular CUDA-related projects from GitHub, upon which we conduct an extensive set of experiments. The experimental results suggest that Simulee can detect 21 out of the 24 manually identified bugs in our preliminary study and also 24 previously unknown bugs among all projects, 10 of which have already been confirmed by the developers. Furthermore, Simulee significantly outperforms state-of-the-art approaches for CUDA synchronization bug detection.
Attitude determination for three-vehicle heterogeneous formations

Attitude determination in formations of vehicles plays a critical role in many missions. This thesis proposes a representative heterogeneous formation with three vehicles, in which the line-of-sight vector measurements are constrained to be between a chief vehicle and the other two. Moreover, every vehicle has access to an inertial measurement, possibly distinct for each vehicle. The deterministic solution for the different attitude matrices of the problem is developed employing a multistage method. Firstly, the relation between the chief and each of the other vehicles is considered, which gives, in general, two solutions. Nonetheless, there are degenerate cases that have infinite solutions and specific configurations that give a unique solution. Secondly, the inertial attitude of the chief is found from each of the candidates from the first stage. This stage has, in general, a unique solution for each candidate or infinite solutions in the degenerate cases. Afterwards, a comparison leads to the selection of the correct candidate and all the other attitude matrices are, finally, computed from the ones already determined. In general, there is a unique solution for all the attitude matrices, both relative and inertial. Besides the degenerate cases that have infinite solutions, there are special cases where the correct solution cannot be distinguished from two final candidates. This situation is fully characterized. The proposed solution is simulated using a convenient sensor noise model and the results are coherent with state-of-the-art approaches to similar problems.
Influence of surface characteristics on biofouling formed on polymers exposed to coastal sea waters of India

Biofouling on six different (silicone rubber, polydimethylsiloxane, polypropylene, high density polyethylene, polyvinylchloride, and polycarbonate) substrata with varying surface energy (18–40 mN/m) and surface roughness (Ra 45–175 m) was studied in the Eastern coastal waters of India over a short period of time (3 days). The results showed that the substrata surface energy (SE) followed by the surface roughness (Ra) had profound effect on attachment of fouling organisms. After one day of immersion, viable count of bacteria in the biofilm was positively correlated with surface energy (r = 0.69, p < 0.05) and not with surface roughness (r = −0.02) of the substratum. Whereas, Pseudomonas count was inversely correlated with surface energy (r = −0.66, p < 0.05) and surface roughness (r = −0.52, p < 0.05). The attachment of macrofouler and the surface characteristics were also well correlated with SE 0.48 and with roughness 0.62, p < 0.05. A positive correlation was observed amongst the various biofouling constituents such as bacteria, ATP, carbohydrates and organic matter on almost all the substrata. However after the first day, the surface characteristics of the substratum became less important and the conditioning film that was formed on the substrata appeared to directly influence further fouling on the surfaces, as evidenced by poor correlation between surface energy and macrofouler attachment (r = −0.11). The observation of high numbers of Hydroides elegans on PVC could be solely due to the influence of surface roughness (r = 0.62). Though there is no marked difference in the ‘primary film’, and the composition of the biofilm, the amount of attached macrofouler is minimal on silicone rubber and polydimethylsiloxane on subsequent days of immersion, which reveals the foul release quality of these substrata probably due to their flexible nature. © 2011 Elsevier B.V. All rights reserved.
Technical Parameters Affecting the Production of Soursop (Annona muricata) Juice

Soursop (Annona muricata) is one of the exotic fruits prized for its very pleasant,sub-acid, aromatic and juicy flesh juice. It softens very rapidly during ripening and becomes mushy and difficult to consume fresh. Freshly expressed juice, is highly susceptible to spoilage, in fact more so than whole fruit. In the present study, various technical parameters influencing to production of soursop (Annona muricata) juice were clearly investigated such as ratio of pulp: water, sugar addition during the blending process; pasteurization, storage condition to stability of soursop juice. Optimal results showed that ratio of pulp: water (1.0: 2.0 w/v); 9% of sugar addition; 95C, 30 seconds in pasteurization; 28C within 6 weeks of preservation could maintain stability of soursop juice.
The 2008 presidential elections in Zambia: incumbency, political contestation and failure of political opposition

While the level of political contestation in Zambia has increased since 2001, the quality of elections remains poor and alternation in power has not occurred. The legacy of using incumbency to win elections, tolerance of undemocratic procedures, exclusivist politics and opposition’s failure to unite and capture nation-wide support have combined to retain the MMD in every election, albeit with narrow majorities. The paper examines political opposition’s performance in the 2008 presidential elections and explains their failure to win. The paper traces enduring legacies from the authoritarian period and how they have shaped Zambian electoral experience. The nature and character of the party system, especially the opposition is analysed against the background of undemocratic and exclusivist politics. By using the 2008 election results the paper concludes that the main opposition Patriotic Front’s (PF) poor electoral performance was tampered by narrow ethno-regional mobilization, disunity within the opposition, and low voter turnout. It is also argued that incumbency, national sympathy in the wake of Mwanawasa’s death rather than good performance were responsible for MMD’s fifth straight win in 17 years.
Crowdsourcing Based Business Model Innovation and Consumer Engagement

The development of ICT caused changes in business approaches and models as well as various new phenomena such as crowdsourcing, gamification, big data, and internet of things. The present paper provides analysis of crowdsourcing and how it contributes to business model innovation as well as consumer engagement. Based on the analysis consumer engagement dimensions are defined and application opportunities of crowdsourcing in business model context are determined. These constructs are integrated and empirically tested in Lithuanian market defining what is a level of consumer engagement in crowdsourced activities used for business model innovation
Electric Power System for ISTnanosat-1

This paper describes the design process for Electric Power System (EPS) of a Nanosatellite. The EPS aims to make the collection of solar energy in space environment and perform the correct storage in internal battery. The energy collected is converted into regulated power supplies 3.3 V, 5 V and 12 V for use across the Nanosatellite. The EPS must meet space and performance requirements of Cubesat architecture, using DC / DC converters to perform the power supply regulation in high yield, making the performance recording and correcting the
Study of Quantum Motivated Evolutionary Algorithms

—This paper introduces a compact study of another class of metaheuristics, drawing their motivation from both: organic advancement and unitary development of quantum framework. In the initial segment of the paper, general ideas driving quantum-roused developmental calculations have been exhibited. In the second section, a best in class of this field has been talked about and a writing audit has been directed.
Using proteomics to understand how parasites adapt to the host environment

Trypanosoma brucei is an extracellular parasite that is the causative agent of Human African Trypanosomiasis (HAT) and which is transmitted by tsetse flies. Within the mammalian host, T. brucei was recently found to accumulate in the adipose tissue. T. brucei’s adipose tissue forms were shown to be transcriptionally distinct from the bloodstream forms, suggesting a functional adaptation of the parasite to the adipose tissue. In light of this discovery, this project’s main goal was to identify the most significant differences at the protein level between these two parasite forms. To achieve this goal, the optimal parasite isolation protocol and the most suited tool to perform label-free protein quantification data analysis were first defined. MaxQuant is a free software that provides an end-to-end solution to proteomics data processing, with high accuracy and reliability of the results. Thus, this software was chosen to perform proteomics raw data analysis. The comparison of the proteome data of parasites residing in the bloodstream and in the adipose tissue showed that, similarly to what we had observed at the RNA level, T. brucei functionally adapts to the tissue environment, by rewiring the gene expression of several genes. Overall, during this thesis, we established a proteomics data analysis workflow in our Lab and we showed significant differences in the proteome of T. brucei in the adipose tissue and in the bloodstream.
NEUROLOGY2016788349 854..858

The cathedral ceiling located in the entrance hall of the Montreal Neurological Institute, planned by its founder Wilder Penfield, has intrigued visitors since it was erected in 1934. Central to its charm is a cryptic comment by the ancient physician Galen of Pergamum, which refutes a dire Hippocratic aphorism about prognosis in brain injury. Galen’s optimism, shared by Penfield, is curious from a fellow ancient. In this article, we use primary sources in Ancient Greek as well as secondary sources to not only examine the origins of Galen’s epistemology but also, using a methodology in classics scholarship known as reception studies, illustrate how an awareness of this ancient debate can illuminate contemporary clinical contexts. While Galen based his prognostications on direct clinical observations like the Hippocratics, he also engaged in experimental and anatomic work in both animals and humans, which informed his views on neurologic states and outcomes. Penfield’s memorialization of Galen is representative of the evolution of the neurosciences and the ongoing importance of evidence-based prognostication in severe brain injury. Neurology®
Second-order shape optimization of a steel bridge

A comparison is made between the cost minimization of a truss with variable cross-sectional dimensions and fixed geometry (sizing) and the same problem with variable nodal coordinates (shape optimization). Both problems can be formulated as a mathematical program that comprises both structural analysis and design. When this integrated formulation is used, the number of variables in the mathematical program is usually large and an efficient algorithm is required. In this paper the shape optimization problem is solved by a second-order algorithm called NEWTOP that is based on the Lagrange-Newton method. The expressions that define the mathematical program are parsed and their first and second derivatives are symbolically determined and evaluated by the computer program. With the NEWTOP code, problems with more than 4 000 independent design variables and 20 000 constraints have already been successfully solved. The solution of a large variety of structural optimization problems has shown that this code is robust, efficient and very accurate. A simple shape optimization example and a bridge design problem are presented. The latter corresponds to a steel pedestrian bridge with eight spans and constant height. Sizing and shape optimization of one of the central spans are performed and compared.
Axiomatic Scene Estimation for Robotic Manipulation

The main challenge for robots performing complex manipulation tasks for human is that many aspects of the human’s world model are difficult or impossible for the robot to sense directly. We posit the critical missing component is the grounding of symbols that conceptually tie together lowlevel perception and high-level reasoning for extended goaldirected autonomy. Just as important, human users need to more intuitively specify goals for robots, as desired states of the world, through spatial arrangements, such as scene graphs now ubiquitous in modern 3D computer graphics. In this paper, we describe an approach to axiomatic state estimation, the Axiomatic Particle Filter (APF) to perform anchoring and manipulation in cluttered scenes containing objects in physical contact. We describe the problem of axiomatic state estimation as the perception of a robot’s environment axiomatically as a scene graph, where each object in the scene is a node and inter-object relations are edges. The Axiomatic Particle Filter is then presented as an implementation that estimates the pose and spatial relations of objects in a scene from 3D point clouds, assuming known object geometries. We present results from experiments of axiomatic particle filtering within a sequential manipulation for controlled scenes involving objects that are stacked and partially occluded.
From Spoon Feeding to Self-Feeding : Helping Learners Take Control of Their Own Learning

Recent research findings confirm that learning becomes more effective when learners are in control of their own learning and are aware of the learning process and of themselves as learners. Learner autonomy has thus become a prominent area of research in the last three decades. This paper, therefore, argues for an autonomy-based approach to teaching and learning in Oman as an alternative to the existing model which is largely characterized by spoon-feeding and missing voice of the learner. The paper proposes a framework for a gradual handover of some of the roles traditionally held by teachers to the students, emphasizing the role of the teacher in helping students „feed‟ themselves and minimize their over-reliance on the teacher.
Speech Coding and Audio Preprocessing for Mitigating and Detecting Audio Adversarial Examples on Automatic Speech Recognition

An adversarial attack is an exploitative process in which minute changes are made to a natural input, causing that input to be misclassiﬁed by a neural model. Due to recent trends in speech processing, this has become a noticeable issue in speech recognition models. In late 2017, an attack was shown to be quite effective against the Speech Commands classiﬁcation model. Limited-vocabulary classi-ﬁers, such as the Speech Commands model, are used quite frequently for managing automated attendants in traditional telephony and voice over IP (VoIP) contexts. As such, this research examines the effectiveness of VoIP speech coding in mitigating audio adversarial attacks when compared to more primitive forms of audio preprocessing and shows that an ensemble defense in tandem with speech coding is more robust than other forms of preprocessing defenses in mitigating adversarial examples. This research also proposes a new metric for evaluating preprocessing defenses against adversarial attacks. Additionally, this research explores using speech coding and various other forms of preprocessing for detecting adversarial examples.
Ketogenic Diet Combined with Moderate Aerobic Exercise Training Ameliorates White Adipose Tissue Mass, Serum Biomarkers, and Hepatic Lipid Metabolism in High-Fat Diet-Induced Obese Mice

Obesity is a serious public health issue worldwide. Growing evidence demonstrates the efficacy of the ketogenic diet (KD) for weight loss, but there may be some adverse side effects such as dyslipidemia and hepatic steatosis. Aerobic exercise is a widely recognized approach for improving these metabolic markers. Here we explored the combined impacts of KD and moderate aerobic exercise for an 8-week intervention on body weight and fat loss, serum biomarkers, and hepatic lipid metabolism in a mouse model of high-fat diet-induced obesity. Both KD and KD combined with exercise significantly reduced body weight and fat mass. No significant adverse effects of KD were observed in serum biomarkers or hepatic lipid storage, except for an increase in circulating triglyceride level. However, aerobic exercise lowered serum triglyceride levels, and further ameliorated serum parameters, and hepatic steatosis in KD-fed mice. Moreover, gene and protein expression analysis indicated that KD combined with exercise was associated with increased expression of lipolysis-related genes and protein levels, and reduced expression of lipogenic genes relative to KD without exercise. Overall, our findings for mice indicate that further work on humans might reveal that KD combined with moderate aerobic exercise could be a promising therapeutic strategy for obesity.
Flexible Security Policy Architecture for Trusted Operating Systems

-This research paper propose the security policy architecture for Trusted Operating Systems use of security performance flexibility model to balance performance and to keep high security for trusted operating systems. This model allows system administrators to skip or disable some unnecessary security checks in trusted operating systems through which they can effectively balance their performance needs without compromising the security of the system. Which operation is need to be skipped and which operation is not need to be skipped is very much subjective in nature, this will depend upon the user’s requirement and the particular application‘s requirement. The selection of these operations for a particular application is the part of software requirement elicitation process. This paper discusses the Design aspect of Security in Trusted Operating Systems.
Survey of Simple Neural Networks in Semantic Textual Similarity Analysis

—Learning the semantic resemblance between natural language sentences for computers is a difﬁcult task due to the inherent complexity of natural language. To combat this complexity in learning natural language semantics, a rise in the research of complex architectures for machine learning has become prevalent in the ﬁeld. It is necessary to establish a lower bound of performance that must be met in order for new complex architectures to be not only novel, but also worth while in terms of implementation. This paper focuses on the speciﬁc natural language processing task of determining semantic textual similarity (STS). To construct the lower bound that all complex models must surpass to be deemed practical, this research investigated the performance of relatively simpler models in the STS matching task using SemEval’s 2017 STS competition dataset.
On the Robustness of Deep Neural Networks

Deep Neural Networks (DNNs) have become the quasi-standard in many machine learning tasks since they obtain state-of-the-art results and outperform more traditional machine learning models for problems in vision, image and speech processing, and many other tasks. One reason that DNNs have proven very useful is that they are one of the few algorithms that can make principled use of huge databases for training. However, despite their brilliant recognition capabilities, little is known about how DNNs achieve their accuracies, and even less is known about their robustness and their limitations. After Szegedy et al. [19] showed that deep networks have some “intriguing” properties, several researchers started actively exploring the limitations, and showed how easily the networks could be attacked or fooled – demonstrating essential limits of the robustness of DNNs. This paper analyzes these two categories of attacks: adversarial images [19, 3], which are imperceptible perturbations to an input to turn it into another class, and fooling images [9], which look like none of the ∗This research is based upon work funded in part by NSF IIS-1320956 and in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA R&D Contract No. 2014-14071600012. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.
EDGES MEMO #124 ARIZONA STATE UNIVERSITY SCHOOL OF EARTH AND SPACE EXPLORATION

The errors are obtained through simulation. Measured values for the open, short, and match are simulated using the models provided by the Agilent Application Note 1287-11, and the standard definitions of the Agilent 85033E 3.5-mm calibration kit. The true reflection coefficients of the standards are simulated by making perturbations to the measured values, in magnitude and phase. This has the purpose of studying the scenario where the assumed model of one of the standards is incorrect.
Becoming and being academic women in Cambodia: Cultural and other understandings

Abstract Cambodia’s higher education is under development. This is the first study of the role of women teaching in a university in Cambodia. There has been many studies of academic women in western countries and these guided the 16 interviews in Khmer that were carried out by young female researchers, translated by them and then analysed with the assistance of NVivo. Becoming an academic for many Cambodian women meant support from their parents and others close to them. Receipt of an international scholarship may have been critical. Perhaps the most important issue for these academic women was the need to balance demands on their time. Teaching hours could be negotiated, potentially at least, but only where the student numbers warranted it. An affirmative action approach appears to have developed at one of the two universities. Areas for future research are identified.
Harnessing the Power of Cerenkov Luminescence Imaging for Gastro-enterology: Cerenkov Luminescence Endoscopy

: The Cerenkov luminescence imaging (CLI) has built a bridge between the nuclear and optical imaging, and opened a new direction of optical imaging in clinic translation. However, the wide applications of CLI are limited by the weak intensity and poor penetration capacity. By coupling highly sensitive charged coupled device camera with optical fiber bundle based endoscope, Cerenkov luminescence endoscopy (CLE) has recently been developed to overcome these limitations. Using the CLE, diseases deep buried in the body, such as the gastrointestinal (GI) tract cancer, can be identified by radiotracer, which can hardly be detected by CLI from the surface of the body. Here, we review recent progress on CLI and CLE, including the principle, imaging instrument, as well as applications. In addition, the intensity enhanced strategies for Cerenkov luminescence are presented, which may provide an ideal solution to the obstacle of CLE in the translation studies. In the end, we present possible future directions of the CLE technology.