Miracle-dz/UniFAR-FTUs huggingface dataset:
Recursion , Lambda Abstractions and Genetic Programming

Module creation and reuse are essential for Genetic Programming (GP) to be effective with larger and more complex problems. This paper presents a particular kind of program structure to serve these purposes: modules are represented as λ abstractions and their reuse is achieved through an implicit recursion. A type system is used to preserve this structure. The structure of λ abstraction and implicit recursion also provides structure abstraction in the program. Since the GP paradigm evolves program structure and contents simultaneously, structure abstraction can reduce the search effort for good program structure. Most evolutionary effort is then focused on the search for correct program contents rather than the structure. Experiments on the Even-N-Parity problem show that, with the structure of λ abstractions and implicit recursion, GP is able to find a general solution which works for any value of N very efficiently .
IFAO-Simo: A spatial-simulation based facility network optimization framework

This paper describes an innovative framework, iFAO-Simo, which integrates optimization, simulation and GIS (geographic information system) techniques to handle complex spatial facility network optimization problems ever challenged from retailing, banking and logistics nowadays. At the top level of iFAO-Simo, an optimization engine serves to generate and test candidate solutions iteratively by use of optimization algorithms such as Tabu Search and Genetic Algorithms. For each scenario given by the candidate solutions, a discrete event simulation engine is triggered to simulate customer and facility behaviors based on a GIS platform to characterize and visualize the spatial, dynamic and indeterministic environments. As the result, the target measures can be easily calculated to evaluate the solution and feedback to the optimization engine. This paper studies a real case of banking branch network optimization problem, and the results show that iFAO-Simo provides a useful way to handle complex spatial optimization problems.
Microbeam methodologies as powerful tools in manganese hyperaccumulation research: present status and future directions

Microbeam studies over the past decade have garnered unique insight into manganese (Mn) homeostasis in plant species that hyperaccumulate this essential mineral micronutrient. Electron- and/or proton-probe methodologies employed to examine tissue elemental distributions have proven highly effective in illuminating excess foliar Mn disposal strategies, some apparently unique to Mn hyperaccumulating plants. When applied to samples prepared with minimal artefacts, these are powerful tools for extracting true ‘snapshot’ data of living systems. For a range of reasons, Mn hyperaccumulation is particularly suited to in vivo interrogation by this approach. Whilst microbeam investigation of metallophytes is well documented, certain methods originally intended for non-biological samples are now widely applied in biology. This review examines current knowledge about Mn hyperaccumulators with reference to microbeam methodologies, and discusses implications for future research into metal transporters.
Defect Collection and Reporting System for Git based Open Source Software

This paper describes Defect Collection and Reporting System which is an automated tool that aids in generating various reports to provide useful information regarding the defects which were present in a given version of a Git Version Control System based Open Source Software and were fixed in the subsequent version. The generated reports contain information such as the total number of defects, class wise and the corresponding values of different OO metrics for each class in the source code. Such kind of defect data can be readily used for defect prediction hypothesis pertaining to Git based Open Source Software. Some potential fields of application could be analysis and validation of the effect of a given metric suite on fault proneness; to predict fault proneness models for Defect Prediction, etc. In addition to the core functionalities and overall functioning of the above stated tool, this paper also gives an overview of some of the functionalities which might be useful for the end user, namely- cloning of Git Repositories, and self-logging data of the tool.
Link Scheduling for Minimum Delay in Spatial Re-Use TDMA

Time division multiple access (TDMA) based medium access control (MAC) protocols provide QoS with guaranteed access to wireless channel. However, in multihop wireless networks, these protocols may introduce delay when packets are forwarded from an inbound link to an outbound link on a node. Delay occurs if the outbound link is scheduled to transmit before the inbound link. The total round trip delay can be quite large since it accumulates at every hop in the path. This paper presents a method that finds schedules with minimum round trip scheduling delay. We show that the scheduling delay can be interpreted as a cost collected over a cycle on the conflict graph. We use this observation to formulate a min-max program for the delay across a set of multiple paths. The min-max delay program is NP-complete since the transmission order of links is a vector of binary integer variables. We design heuristics to select appropriate transmission orders. Once the transmission orders are known, a modified Bellman-Ford algorithm is used to find the schedules. The simulation results confirm that the proposed algorithm can find effective min-max delay schedules.
Adolescents’ social background and non-standard writing in online communication

In a large corpus (2.9 million tokens) of chat conversations, we studied the impact of Flemish adolescents’ social background on non-standard writing. We found significant correlations between different aspects of social class (level of education, home language and profession of the parents) and all examined deviations from formal written standard Dutch. Clustering several social variables might not only lead to a better operationalization of the complex phenomenon of social class, it certainly allows for discriminating social groups with distinct linguistic practices: lower class teenagers used each of the non-standard features much more often and in some cases in a different way than their upper class peers. Possible explanations concern discrepancies in terms of both linguistic proficiency and linguistic attitudes. Our findings emphasize the importance of including social background as an independent variable in variationist studies on youngsters’ computer-mediated communication.
RDBMS for service repository and composition

Relational Database for its huge success in data management has been used here as a scalable repository for storing webservices in UDDI framework. The operator `join' has been used to derive service composition by matching inputs of a service to outputs of another. Adopting three modes of composability for a desired service, the possibility of having different kinds of compositions is demonstrated in form of a Composition Search Tree.
A novel intrusion detection approaches based on data mining

Data mining has been gaining popularity in the knowledge discovery field, particularity with the increasing availability of digital documents in various languages from all around the world. Several data mining methods which applied in intrusion detection systems are introduced. And an agent-based network intrusion detection system using data mining approaches is presented. The proposed system is constructed by a number of agents, which are totally different in both training and detecting processes. The model can easily be adaptive and scalable with the adaptive learning ability of agents.
Testing the AgreementMaker System in the Anatomy Task of OAEI 2012

The AgreementMaker system was the leading system in the anatomy task of the Ontology Alignment Evaluation Initiative (OAEI) competition in 2011. While AgreementMaker did not compete in OAEI 2012, here we report on its performance in the 2012 anatomy task, using the same configurations of AgreementMaker submitted to OAEI 2011. Additionally, we also test AgreementMaker using an updated version of the UBERON ontology as a mediating ontology, and otherwise identical configurations. AgreementMaker achieved an F-measure of 91.8% with the 2011 configurations, and an F-measure of 92.2% with the updated UBERON ontology. Thus, AgreementMaker would have been the second best system had it competed in the anatomy task of OAEI 2012, and only 0.1% below the F-measure of the best system.
The Impact of an Associative Strategy (the PROFO Program) on Small and Medium Enterprises in Chile

The main objective of this article is to determine if associative strategies followed in Chile have had any impact on the enhancement of productive performance of Chilean SMEs firms. In order to do that, the estimate of the impact is approached using the benchmark given by Social Experiment but within the context of a `non-experimental' evaluation design. We conclude that these kinds of policies have been effective in increasing the productivity of the participating firms, and have also been efficient since they have achieved high social profits.
Unifying Logic and Probability : Recent Developments

Logic and probability theory are two of the most important branches of mathematics and each has played a significant role in artificial intelligence (AI) research. Beginning with Leibniz, scholars have attempted to unify logic and probability. For “classical” AI, based largely on first-order logic, the purpose of such a unification is to handle uncertainty and facilitate learning from real data; for “modern” AI, based largely on probability theory, the purpose is to acquire formal languages with sufficient expressive power to handle complex domains and incorporate prior knowledge. This paper reports on recent efforts in these directions, focusing in particular on open-universe probability models that allow for uncertainty about the existence and identity of objects. Such models encompass a wide range of applications and may lead to qualitative advances in core areas of AI.
Sublethal gamma-radiation induces differentiation of CD4-/CD8- into CD4+/CD8+ thymocytes without T cell receptor beta rearrangement in recombinase activation gene 2-/- mice

DNA recombination of the immunoglobulin (Ig) or T cell receptor (TCR) gene loci is an essential step in the production of lymphocytes bearing antigen-specific receptors. Mice that lack the ability to rearrange their Ig and TCR gene loci are devoid of mature B and T cells. Complete rearrangement and expression of the TCR-beta chain has been suggested to allow immature thymocytes to switch from the CD4-/CD8- to the CD4+/CD8+ stage of thymic development. Thus, thymocytes from severe combined immune deficient (SCID) mice or mice deficient in recombinase activation genes (RAG), which do not undergo proper DNA rearrangement, are arrested at the early CD4-/CD8- stage of development. B cell precursors in SCID or RAG mice do not progress from the B220+/sIgM- /heat stable antigen (HSA)+/CD43+ to the B220+/sIgM-/HSA+/CD43- stage. In an attempt to reconstitute RAG-2-/- mice with bone marrow- or fetal liver-derived progenitor cells, we subjected these mice to sublethal doses of gamma-radiation. It is surprising that in the absence of donor cells, irradiated RAG-2-/- mice revealed a dramatic change in their lymphoid phenotype. 14 d after irradiation, the majority of thymocytes had advanced to the CD4+/CD8+ stage of T cell development and a small number of bone marrow precursors had progressed to the CD43-, HSAhi stage of B cell development. Analysis of the resulting CD4+/CD8+ thymocytes revealed no surface expression of the TCR/CD3 complex and no V-D-J rearrangement of the TCR-beta gene locus. Our findings provide evidence for a novel pathway that allows the transition of thymocytes from the CD4-/CD8- to the CD4+/CD8+ stage and that does not appear to require TCR-beta chain rearrangement.
Nurses' Coping Mechanisms in a Mental Health Establishment

The aim of this study was to explore and to describe nurses’ coping mechanisms in a mental health establishment in the North West province of South Africa so as to improve the methods of how they manage stressful situations in their care for mental healthcare users. A qualitative-explorative-descriptive and contextual design was followed to deal with the researcher’s concern. The target population included all categories of nurses who are caring for mental healthcare users in a mental health establishment in the North West province. Participants were selected purposively based on a set of selection criteria. The size of the sample was determined by data saturation which was reached after interviewing 10 nurses. Information obtained was transcribed verbatim for data analysis. Trustworthiness was ensured through credibility, dependability, transferability and confirmability techniques. The findings of the study revealed four main themes, namely psychosocial support, coaching and mentoring, stakeholder support, and suggestions for improving nurses’ coping mechanisms. From the findings of the study, recommendations were made for the nursing practice, education and research.
Cognitive and Noncognitive Skills and the Selection and Sorting of Migrants

There is growing evidence that cognitive and noncognitive skills are strong predictors of the economic and social outcomes of individuals. In this paper, we analyze how they affect the migration decisions of individuals over their lifecycles. We use data that combine military enlistment and administrative records for the male population born in 1932 and 1933 in Norway. Records of interviews with a psychologist at age 20 allow us to construct an index of `sociability' and `adaptability' for each individual, as well as an index of cognitive ability, the intelligence quotient. We find that adaptability and cognitive ability have significant and positive impacts on the probability of an individual migrating out of his area, whether this involves rural-urban, long distance, or international migration. Adaptability has a particularly strong impact on migration for individuals with low cognitive skills, implying a strong positive selection of less educated migrants with respect to the (previously unobserved) adaptability skill. We also show that cognitive skills have a strong positive effect on sorting of migrants across destinations, whereas adaptability has no significant effect on sorting. This evidence suggests that adaptability reduces the psychological cost of migrating, whereas cognitive skills increase the monetary returns associated with migration.
A Program Evaluation of a Drug and Alcohol Family Treatment Program

The current study is a program evaluation at John Muir Behavioral Health, Center for Recovery. The research determined the effectiveness of the program at Center for Recovery that is offered to patients that struggle with substance use disorder and their families. The purpose of this study is to assess patients’ behavioral, cognitive and social/environmental factors as it relates to their commitment to sobriety and examine how the involvement of family members influences the patient’s recovery process. I utilized a mixed methodology of quantitative and qualitative interviews of patients and family members. The findings suggest depressive symptoms were negatively correlated with commitment to sobriety. The correlation between higher rates of treatment helpfulness predicted lower levels of depression scores. As hypothesized, individuals with increased levels of social support reported lower levels of depression on the pre-test and post-test. Lastly, the correlation between higher rates of treatment helpfulness predicted lower levels of depression scores for patients at CFR.
Diet and Aging

Nutrition has important long-term consequences for health that are not only limited to the individual but can be passed on to the next generation. It can contribute to the development and progression of chronic diseases thus effecting life span. Caloric restriction (CR) can extend the average and maximum life span and delay the onset of age-associated changes in many organisms. CR elicits coordinated and adaptive stress responses at the cellular and whole-organism level by modulating epigenetic mechanisms (e.g., DNA methylation, posttranslational histone modifications), signaling pathways that regulate cell growth and aging (e.g., TOR, AMPK, p53, and FOXO), and cell-to-cell signaling molecules (e.g., adiponectin). The overall effect of these adaptive stress responses is an increased resistance to subsequent stress, thus delaying age-related changes and promoting longevity. In human, CR could delay many diseases associated with aging including cancer, diabetes, atherosclerosis, cardiovascular disease, and neurodegenerative diseases. As an alternative to CR, several CR mimetics have been tested on animals and humans. At present, the most promising alternatives to the use of CR in humans seem to be exercise, alone or in combination with reduced calorie intake, and the use of plant-derived polyphenol resveratrol as a food supplement.
Squid: an extensible infrastructure for analyzing software product line implementations

Software product line engineering is about producing a set of related products that share more commonalities than variabilities. This approach promotes benefits such as cost reduction, product quality, productivity and time to market, but it brings new challenges that must be considered during the evolution of the software product line. In this context, recent research has explored and proposed automated approaches based on code analysis and traceability techniques for change impact analysis. This paper presents Squid, an extensible infrastructure for analyzing software product line implementations. The approach uses information from variability modeling, variability mapping to code assets, and dependency relationships between code assets to perform analysis of SPL implementations. A Squid instantiation example is presented to illustrate the usage of the tool in practical scenarios.
Sensitisation and Evolution of Chromium-depleted Zones in Fe-Cr-Ni-C Systems

The development of chromium concentration profiles in austenitic stainless steels, due to the grain boundary precipitation of carbides has been modelled, taking account of multicomponent effects, both in the estimation of the state of equilibrium at the carbide/matrix interface and in diffusion. A comparison against published experimental data shows that the theory accounts for the development of the depleted zone as well as self-healing, unlike recent work where these effects are treated as separate phenomena. At the same time, the present model preserves local equilibrium at the precipitate-matrix interface and provides a natural explanation for the observation of delays in reaching the minimum chromium content.
Person name spotting by combining acoustic matching and LDA topic models

In this article, we are interested in spoken term detection task, with a particular focus on Person Name (PN) spotting in automatic speech recognition (ASR) system outputs. We propose a two-step method that combines an acoustic matching based on a Phoneme Confusion Network (PCN) with a semantic rescoring based on the Latent Dirichlet Allocation (LDA) models. The first module allows to find, in the PCN, potential PN candidates in speech segments, while the second is in charge of ranking the competing PN, according to a LDA topic model. The proposed LDA-based approach outperforms significantly the baseline system based on a search in the ASR phoneme lattice, obtaining a F-measure score of 77.04% on PN detection.
Denoising Bodies to Titles: Retrieving Similar Questions with Recurrent Convolutional Models

Question answering forums are rapidly growing in size with no automated ability to refer to and reuse existing answers. In this paper, we develop a methodology for finding semantically related questions. The task is difficult since 1) key pieces of information are often buried in extraneous detail in the question body and 2) available annotations are scarce and fragmented, driven by participants. We design a novel combination of recurrent and convolutional models (gated convolutions) to effectively map questions to their semantic representations. The models are pre-trained within an encoder-decoder framework (from body to title) on the basis of the entire raw corpus, and fine-tuned discriminatively from limited annotations. Our evaluation demonstrates that our model yields 10\% gain over a standard IR baseline, and 6\% over standard neural network architectures (including CNNs and LSTMs) trained analogously.
Human Herpesvirus 8 Interferon Regulatory Factor-Mediated BH3-Only Protein Inhibition via Bid BH3-B Mimicry

Viral replication efficiency is in large part governed by the ability of viruses to counteract pro-apoptotic signals induced by infection of host cells. For HHV-8, viral interferon regulatory factor-1 (vIRF-1) contributes to this process in part via inhibitory interactions with BH3-only protein (BOP) Bim, recently identified as an interaction partner of vIRF-1. Here we recognize that the Bim-binding domain (BBD) of vIRF-1 resembles a region (BH3-B) of Bid, another BOP, which interacts intramolecularly with the functional BH3 domain of Bid to inhibit it pro-apoptotic activity. Indeed, vIRF-1 was found to target Bid in addition to Bim and to interact, via its BBD region, with the BH3 domain of each. In functional assays, BBD could substitute for BH3-B in the context of Bid, to suppress Bid-induced apoptosis in a BH3-binding-dependent manner, and vIRF-1 was able to protect transfected cells from apoptosis induced by Bid. While vIRF-1 can mediate nuclear sequestration of Bim, this was not the case for Bid, and inhibition of Bid and Bim by vIRF-1 could occur independently of nuclear localization of the viral protein. Consistent with this finding, direct BBD-dependent inactivation by vIRF-1 of Bid-induced mitochondrial permeabilization was demonstrable in vitro and isolated BBD sequences were also active in this assay. In addition to Bim and Bid BH3 domains, BH3s of BOPs Bik, Bmf, Hrk, and Noxa also were found to bind BBD, while those of both pro- and anti-apoptotic multi-BH domain Bcl-2 proteins were not. Finally, the significance of Bid to virus replication was demonstrated via Bid-depletion in HHV-8 infected cells, which enhanced virus production. Together, our data demonstrate and characterize BH3 targeting and associated inhibition of BOP pro-apoptotic activity by vIRF-1 via Bid BH3-B mimicry, identifying a novel mechanism of viral evasion from host cell defenses.