Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward power-aware computing with dynamic voltage scaling for heterogeneous platforms

Energy conservation is a dynamic topic of research in high performance computing and cluster computing. Power-aware computing for heterogeneous world-wide Grid is a new track of research. In this work, we study and evaluate the impact of the heterogeneity of the nodes of a computing platform on the energy consumption. We propose to take advantage of this heterogeneity in order to save energy with no significant loss of performance by using dynamic voltage scaling (DVS) in a distributed eigensolver. We show that using DVS only during the slack-time does not penalize the performances but it does not provide significant energy savings. If DVS is applied to all the execution, we get important global and local energy savings (respectively up to 9% and 20%) without a significant rise of the wall-clock times.
Managing Requirements Inconsistency with Development Goal Monitors

Managing the development of software requirements can be a complex and difficult task. The environment is often chaotic. As analysts and customers leave the project, they are replaced by others who drive development in new directions. As a result, inconsistencies arise. Newer requirements introduce inconsistencies with older requirements. The introduction of such requirements inconsistencies may violate stated goals of development. In this article, techniques are presented that manage requirements document inconsistency by managing inconsistencies that arise between requirement development goals and requirements development enactment. A specialized development model, called a requirements dialog meta-model, is presented. This meta-model defines a conceptual framework for dialog goal definition, monitoring, and in the case of goal failure, dialog goal reestablishment. The requirements dialog meta-model is supported in an automated multiuser World Wide Web environment, called DEALSCRIBE. An exploratory case study of its use is reported. This research supports the conclusions that: an automated tool that supports the dialog meta-model can automate the monitoring and reestablishment of formal development goals; development goal monitoring can be used to determine statements of a development dialog that fail to satisfy development goals; and development goal monitoring can be used to manage inconsistencies in a developing requirements document. The application of DEALSCRIBE demonstrates that a dialog meta-model can enable a powerful environment for managing development and document inconsistencies.
Fuzzy Reliability Model for Component-Based Software Systems

Component-based software engineering has been projected off-late as an appropriate paradigm for embedded systems development. However this becomes feasible only if the dependability attributes, such as reliability, of embedded systems can be properly estimated and guaranteed using appropriate models. Another recent trend is the prevalence of architectural modelling of software systems due to the advantages such as composability reasoning and analysis of system behaviour as well as the flexibility and reusability of models. However, a major issue is that there exist uncertainty in the reliability parameters associated with the traditional testing-based approaches for particular architectural entities (e.g. components and/or connectors). In this context, we propose a new approach for the reliability estimation of component-based software systems, which steps on an architectural model of the system using Generalized Nets. This notation is a generalization of Petri nets and is an all-purpose formal modelling technique for the description of parallel phenomena. For the reliability description, we apply possibility theory, which has the potential to solve the uncertainty aspect. This is based on fuzzy sets and describes reliability properties of software components in systems architecture with fuzzy measures.
Detecting overlapping use cases

To deal with the complexity of large information systems, the divide-and-conquer policy is usually adopted to capture requirements from a large number of stakeholders: obtain requirements from different stakeholders, respectively, and then put them together to form a full requirement specification. One of the problems induced by the policy is overlapping requirements. A use case driven approach could not avoid overlapping requirements either: it produces overlapping use cases, which are even more harmful, because a use case describes not only inputs and outputs as traditional requirements do, but also the scenarios. Each of the overlapping use cases provides a message sequence to implement the common subgoal. Overlapping use cases not only decrease the maintainability of the requirement specification, but also result in a complicated, confusing and expensive system. To be worse, it is difficult to detect overlapping use cases with existing methods for requirement management. To find out overlapping use cases, a detection approach using sequence diagrams and statecharts is proposed. Evaluation results suggest that practical requirement models do contain overlapping use cases, and the proposed approach is effective in detecting them.
Insights in global public spending

Governments around the globe are opening up public spending data in order to promote transparency and citizen awareness. However, data openness by itself is not enough to guarantee that the data is consumed efficiently and in meaningful ways. In this work public spending data from seven governments, both local and national, with total value almost 1,5 trillion euro, are processed, cleansed and converted to Linked Open Data, following best practices. Namely, the cases of Greece, the UK, the US federal government, Australia, the city of Chicago and the states of Alaska and Massachusetts are considered. Furthermore, the resulting Linked Data are interlinked with external resources and made accessible on a public SPARQL endpoint. A web portal application with several functionalities is deployed in order to make the data mashups understandable and easily consumable.
Software Security and Randomization through Program Partitioning and Circuit Variation

The commodity status of Field Programmable Gate Arrays (FPGAs) has allowed computationally intensive algorithms, such as cryptographic protocols, to take advantage of faster hardware speed while simultaneously leveraging the reconfigurability and lower cost of software. Numerous security applications have been transitioned into FPGA implementations allowing security applications to operate at real-time speeds, such as firewall and packet scanning on high speed networks. However, the utilization of FPGAs to directly secure software vulnerabilities is seemingly non-existent. Protecting program integrity and confidentiality is crucial as malicious attacks through injected code are becoming increasingly prevalent. This paper lays the foundation of continuing research in how to protect software by partitioning critical sections using reconfigurable hardware. This approach is similar to a traditional coprocessor approach to scheduling opcodes for execution on specialized hardware as opposed to running on the native processor. However, the partitioned program model enables the programmer the ability to split portions of an application to reconfigurable hardware at compile time. The fundamental underlying hypothesis is that synthesizing portions of programs onto hardware can mitigate potential software vulnerabilities. Further, this approach provides an avenue for randomization or diversity for software layout and circuit variation.
Regulation of p53 Stability and Apoptosis by a ROR Agonist

Activation of p53 function leading to cell-cycle arrest and/or apoptosis is a promising strategy for development of anti-cancer therapeutic agents. Here, we describe a novel mechanism for stabilization of p53 protein expression via activation of the orphan nuclear receptor, RORα. We demonstrate that treatment of cancer cells with a newly described synthetic ROR agonist, SR1078, leads to p53 stabilization and induction of apoptosis. These data suggest that synthetic ROR agonists may hold utility in the treatment of cancer.
Lifestyle Factors and Inflammation: Associations by Body Mass Index

Chronic inflammation, which is associated with obesity, may play a role in the etiology of several diseases. Thus, reducing inflammation may offer a disease-prevention strategy, particularly among the obese. Several modifiable factors have been associated with inflammation, including: dietary fiber intake, saturated fat intake, physical activity, smoking, alcohol, and use of certain supplements and medications (glucosamine, chondroitin, fish oil, vitamin E, statins and aspirin). To study whether these associations differ by body mass index (BMI), we used data on 9,895 adults included in the 1999–2004 cycles of the National Health and Nutrition Examination Survey (NHANES). Survey-weighted linear regression was used to evaluate the associations between modifiable factors and serum high-sensitivity C-reactive protein (hsCRP) concentrations across the following groups: underweight/normal weight (BMI<25 kg/m2), overweight (25-<30 kg/m2) and obese (30+ kg/m2). While several factors were significantly associated with decreased hsCRP among the normal weight or overweight groups (increased fiber intake, lower saturated fat intake, physical activity, not smoking, and use of chondroitin, fish oil and statins), only increasing dietary fiber intake and moderate alcohol consumption were associated with reduced hsCRP among the obese. Effect modification by BMI was statistically significant for the saturated fat-hsCRP and smoking-hsCRP associations. These results suggest that posited anti-inflammatory drugs and behaviors may be less strongly associated with inflammation among the obese than among lower weight persons.
Understanding the motivations: A qualitative analysis of israelis holding a bachelor's degree who pursue an MBA abroad

Motivations for study abroad have been studied mostly from a quantitative point of view. This study attempted to understand those motivations through qualitative methodology, by getting "into the heads" of international students using a multiple case study approach. Participants were 15 Israeli Hebrew-speaking graduates. Data sources included in-depth interviews with the students, a business professor, as well as official program documents. Findings show that while intrinsic motivations recur in the data, that are in essence the selling points of an MBA, stressing experience and gaining knowledge and skills, the dominant motivations are instrumental and at times even fantastic and extreme, although presented implicitly in the discourse. All these motivations reflect a mismatch between students’ perceptions of MBA education and the actual reality of getting a graduate business degree abroad, which has serious ramifications for students' learning experience and the way in which efforts and resources are prioritized.
Structured system threat modeling and mitigation analysis for industrial automation systems

Industrial control systems are an important part of critical infrastructures and their uninterrupted operation is important for many aspects of society. In recent years these systems have come under more scrutiny, as reports about attacks on them have become more frequent. There is therefore a need to better secure them, and the first step to achieve this is to identify the threat landscape for such systems. This is typically done by creating a threat model of a system, enumerating the potential threats, and then devising mitigation options based on the discovered threats. However, many of the available threat modeling methods and tools target very specific systems (e.g., software components), and do not lend themselves well to evaluating diverse systems or abstract reference architectures of systems. In this paper we present a methodology for system threat modeling that addresses this gap, by enabling the modeling of a diverse range of systems and reference architectures of systems. Furthermore, the methodology provides additional functionality, such as guiding the user in the completion of a threat model and automatically detecting unmitigated threats in a system. In addition, our methodology also takes mitigation into account by modeling the security components in a system. We have implemented the methodology in a web-based tool, and also evaluated the tool on a reference architecture of a complex automation system, validating both the approach and the tool.
Evolution models for dynamic networks

This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such framework allows the time analysis of the relationship between the dynamic laws and the network characterizing features (degree distribution, clustering coefficient, controllability indexes, etc.) providing new insight on the network properties. The framework also allows to relate and generalize existing inference procedures for modelling real world time evolving complex systems.
Two special cases of the Rational Shuffle Conjecture

The Classical Shuffle Conjecture of Haglund et al. (2005) has a symmetric function side and a combinatorial side. The combinatorial side $q,t$-enumerates parking functions in the $n ×n$ lattice. The symmetric function side may be simply expressed as $∇ e_n$ , where $∇$ is the Macdonald eigen-operator introduced by Bergeron and Garsia (1999) and $e_n$ is the elementary symmetric function. The combinatorial side has been extended to parking functions in the $m ×n$ lattice for coprime $m,n$ by Hikita (2012). Recently, Gorsky and Negut have been able to extend the Shuffle Conjecture by combining their work (2012a, 2012b, 2013) (related to work of Schiffmann and Vasserot (2011, 2013)) with Hikita's combinatorial results. We prove this new conjecture for the cases $m=2$ and $n=2$ .
User Localization Using Wearable Electromagnetic Tracker and Orientation Sensor

This paper describes a localization method with wearable electromagnetic sensor and orientation sensor for wearable computer users. Many user localization methods have been investigated to realize location-based services in a wide environment. The localization methods usually employ a hybrid approach in which user's position is estimated by using positioning infrastructures and dead reckoning such as a pedometer. However, the installation cost of infrastructures increases when the area expands, and the error of the pedometer is frequently caused by failures in walking locomotion detection and the difference between ideal and estimated step lengths. If the relative distance is accurately estimated by dead reckoning approach, the installation cost of infrastructures can be reduced. This paper proposes a new localization method that improves the estimation accuracy of step length in dead reckoning approach. The proposed method measures user's orientation and geometrical relationship between user's heel and waist with an orientation sensor and an electromagnetic tracker attached to user's body. When both feet come into contact with the ground, user's position is updated by adding the estimated step length which means the relationship between user's heels and the position estimated in the previous step. The proposed localization method has been experimented using a prototype system to evaluate the accuracy of the proposed method.
A modified ant colony optimization algorithm for implementation on multi-core robots

The Ant Colony Optimization (ACO) algorithm is an evolutionary algorithm that bio-mimics the behavior of ants in finding the shortest path between an origin and a destination within a set of pre-determined constraints. The goal of this work is to create a small-scale application of the ACO using a swarm of small autonomous robots. We investigate the practical applicability of the algorithm in real-life situations by addressing the issues and challenges encountered in the transition from the modeling/simulation level to the real-life application of the algorithm. We also suggest some modifications that will make feasible the implementation of the algorithm on the robots limited computing systems. The results show that the suggested modified algorithm, when implemented on the robotic swarm, enables them to successfully identify the shortest path between two points. These results open the door to a wide variety of applications like search & rescue, path planning, and mass transportation.
RetriBlog: a framework for creating blog crawlers

Blogs are becoming an important social tool. By means of blogs, bloggers share their likes and dislikes, express their opinions, report news and form groups related to some subjects. Thus, the available information on the Blogsphere can certainly helps in the creation of interesting applications in various domains, such as e-learning, e-commerce, and e-government. However, due to the increasing number of blogs posted every day on the Web, and the dynamic nature of the Blogsphere, the tasks of collecting and extracting relevant information from blogs have become hard and time consuming. In this paper, we use techniques both from information retrieval and information extraction fields to deal with this problem. Since the blogs have many points of variability it is necessary to provide applications that can be easily adapted. We present the RetriBlog system, a framework for the development of blog crawlers dealing the variations in blogs. This paper presents the RetriBlog details and an evaluation of the proposed algorithms.
Association between the CYP11 family and six cancer types

Cytochromes P450 (CYPs) are a major source of variability in pharmacokinetics and drug response. CYPs utilize a variety of small and large molecules as substrates in enzymatic reactions. The CYP genes may be divided into two groups: Endogenous CYPs (CYP family 7–51) and xenobiotic CYPs (CYP family 1–4). The aim of the present study was to investigate whether endogenous CYPs exhibit similar gene expression and mutations in various cancer types. The gene expression profiles and somatic mutations exhibited in colon adenocarcinoma, kidney renal clear cell carcinoma, liver hepatocellular carcinoma, lung squamous cell carcinoma, prostate adenocarcinoma and uterine corpus endometrial carcinoma were analyzed using data obtained from The Cancer Genome Atlas. The expression of CYP11A1 was significantly downregulated in all six cancer types. In addition, CYP11B1 and CYP11B2 exhibited the highest number of mutations among endogenous CYPs in all samples. As the CYP11 family is important for steroid biosynthesis, and previous studies have demonstrated that steroid hormones are associated with certain cancers, these results indicate a common role of the CYP11 family in various cancer types.
Simultaneous information and power transfer in multiple antenna relay channels

Simultaneous wireless information and power transfer (SWIPT) is an emerging technology that has received significant attention recently. In a communication system with SWIPT capabilities, both of these tasks, information and power transfer is done over wireless medium simultaneously instead of making these separately. In addition to providing a reliable alternative to powering communication networks solely with batteries or with cables, SWIPT capabilities bring increased mobility and prolong network uptime. In this thesis, SWIPT in a multiple-antenna relay system with multiple users is studied. The relay is used for increasing communication range for the information receivers (IRs) as well as powering the energy harvesting receivers (ERs) that demand power. We focus on the design of the amplify-and-forward strategy at the relay (relay precoder) and the precoder at the base station. The minimum mean-square error (MMSE) is used as the performance criterion for information transfer. We consider two main scenarios: i) one-way relay system and ii) two-way relay system. For the one-way relay system, the relay amplify-and-forward strategy (relay precoder) to minimize the MMSE from the base station to the information user while satisfying energy harvesting constraints at the energy harvesting users is investigated. For the two-way relay system, minimizing the MMSE from the information users to the base station while satisfying the signal-to-interference-plus-noise-ratio (SINR) constraints at the information users and the energy harvesting constraints at the ERs is considered. Here the precoders at the base station and the relay are optimized jointly. These problem formulations lead to non-convex optimization problems. Due to limitations of the available approaches for solving these problems, a novel numerical approach is proposed. Using the proposed technique, the trade-offs between the MMSE and the energy harvesting constraints are found. The results show that it is important to design novel transmission techniques in order to deliver information and energy simultaneously more efficiently. The performance of the proposed designs is also compared with the performance of the some existing techniques in the literature that is developed for some special scenarios and it is observed that the proposed designs provide the same performance with these existing techniques in these special cases. The rate of the convergence of the proposed method is also investigated and it is found suitable for solving the mentioned problems.
Interleukin-13 receptor-targeted cancer therapy in an immunodeficient animal model of human head and neck cancer.

Although interleukin-13 receptors (IL-13R) are overexpressed on several head and neck cancer cell lines, a majority of cell lines express only low levels of IL-13R. We have found that the primary interleukin-13-binding protein IL-13Ralpha2 chain plays an important role in ligand binding and internalization. We showed that the gene transfer of IL-13Ralpha2 chain into various solid tumor cell lines that express few IL-13Rs can dramatically sensitize cells to the cytotoxic effect of a recombinant chimeric protein composed of interleukin-13 and a mutated form of Pseudomonas exotoxin A, IL13-PE38QQR. Based on the expression of IL-13R, we have classified five head and neck cancer cell lines into two groups: (a) IL-13Ralpha2 chain-positive cell lines (SCC-25 and KCCT873); and (b) IL-13Ralpha2 chain-negative cell lines (A253, YCUT891, and KCCT871). By plasmid-mediated stable gene transfer, we demonstrate that not only IL-13Ralpha2 chain-positive head and neck cancer cell lines but also IL-13Ralpha2 chain-negative cell lines can dramatically increase sensitivity to IL-13 toxin by 520-1000-fold compared with mock-transfected control cells after genetic alteration to express high levels of the IL-13Ralpha2 chain. In animal studies, i.p. or intratumoral administration of IL13-PE38QQR given daily or on alternate days for 3-5 days showed dramatic tumor response with complete remission in intratumorally injected tumors in both IL-13Ralpha2 chain-positive and -negative but transfected with IL-13Ralpha2 chain head and neck tumor implanted s.c. in nude mice. These results demonstrate that by using a combination approach of gene transfer and systemic or locoregional cytotoxin therapy, the IL-13R represents a new potent target for head and neck cancer therapy.
Gestalt-based action segmentation for robot task learning

In programming by demonstration (PbD) systems, the problem of task segmentation and task decomposition has not been addressed with satisfactory attention. In this article we propose a method relying on psychological gestalt theories originally developed for visual perception and apply it to the domain of action segmentation. We propose a computational model for gestalt-based segmentation called competitive layer model (CLM). The CLM relies on features mutually supporting or inhibiting each other to form segments by competition. We analyze how gestalt laws for actions can be learned from human demonstrations and how they can be beneficial to the CLM segmentation method. We validate our approach with two reported experiments on action sequences and present the results obtained from those experiments.