Miracle-dz/UniFAR-FTUs huggingface dataset:
Sperm Chromatin Immaturity Observed in Short Abstinence Ejaculates Affects DNA Integrity and Longevity In Vitro

Background The influence of ejaculatory abstinence (EA) on semen parameters and subsequent reproductive outcome is still debatable; hence understanding the impact of EA on sperm structural and functional integrity may provide a valuable information on predicting successful clinical outcome. Objective To understand the influence of EA on sperm chromatin maturity, integrity, longevity and global methylation status. Methods This experimental prospective study included 76 ejaculates from 19 healthy volunteers who provided ejaculates after observing 1, 3, 5 and 7 days of abstinence. Sperm chromatin maturity, DNA integrity and global methylation status were assessed in the neat ejaculate. Sperm motility, DNA integrity and longevity were assessed in the processed fraction of the fresh and frozen-thawed ejaculates to determine their association with the length of EA. Results Spermatozoa from 1 day ejaculatory abstinence (EA-1) displayed significantly higher level of sperm chromatin immaturity in comparison to EA-3 (P < 0.05) and EA-5 (P < 0.01) whereas; the number of 5-methyl cytosine immunostained spermatozoa did not vary significantly across groups. On the other hand, in vitro incubation of processed ejaculate from EA-1 resulted in approximately 20 and 40 fold increase in the DNA fragmented spermatozoa at the end of 6 and 24h respectively (P < 0.01–0.001). Conclusion Use of short-term EA for therapeutic fertilization would be a clinically valuable strategy to improve the DNA quality. However, use of such spermatozoa after prolonged incubation in vitro should be avoided as it can carry a substantial risk of transmitting DNA fragmentation to the oocytes.
Iranian Women’s Experiences of Health Information Seeking Barriers: A Qualitative Study in Kerman

Background: Women as active health information seekers play a key role in determining lifestyle and possible implementation of preventive measures, thereby improving the health of individuals, families and society. Although studies indicate that equipping people with adequate health information leads to optimal health outcomes, sometimes the complexity of human behavior and presence of barriers and limitations expose them to challenges. Objectives: This study was designed to explore women's experiences of health information seeking barriers. Patients and Methods: In this qualitative content analysis study, data collection was conducted regarding inclusion criteria, through purposive sampling and semi-structured interviews with 17 women and using documentation and field notes until data saturation. Qualitative data analysis was performed constantly and simultaneously with data collection. Results: Five central themes were emerged to explain women's experiences of barriers to health information seeking as inadequate support from health care system, shame and embarrassment, costs, wrong ideas and beliefs and inadequate health literacy. Conclusions: It seems the accurate and evidence-based review of the current health system is crucial to support the health informative requirements in a community-based approach, respecting the community cultural-religious beliefs and client participation in health care and according to local resources.
Wide input voltage range compensation in DC/DC resonant architectures for on-board traction power supplies

Several methods to reduce the effect of wide input voltage variation in soft-switched DC/DC converters for high-power and high-voltage traction applications are presented in this paper. To enhance high conversion efficiency together with high reliability and cost reduction, the document addresses the use of a power architecture whose front-end is a three-level half-bridge converter non standard NPC configuration. Thanks to a structured control methodology based on the possibility to use either a two-level or a three-level modulation strategy according to the input voltage level, it is possible to optimize the converter performance over the whole input voltage range. First, the soft-switching implementation of the converter which allows ZVS operation in the entire load range by using the magnetizing inductance of the transformer is discussed. Then, the operation of the converter at both two-level and three-level operation is addressed. Concluding, experimental results obtained in the specified input voltage range are presented to confirm the validity of the theoretical analysis.
Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks

This paper proposes an effective autonomous task allocation method that can achieve efficient cooperative work by divisional cooperation in multi-agent contexts. Computer and network technology has enabled agents/robots to behave autonomously and to be used in a variety of applications such as cleaning and security patrolling. However, to cover large environments, cooperation and collaboration among several agents are mandatory for efficiency and for the required task quality. However, how agents cooperate is a challenging issue because actual environments are usually complicated and because their own (very uncommon) characteristics. Thus, we first define the continuous cooperative patrolling problem, in which agents split up and move around the environments with the required frequencies that are defined for every location. Then, we extend the previous cooperation method to prompt autonomous and effective division of labor by introducing the negotiation for task (re) allocations. We experimentally show that agents with our method enable effective division and fair allocation by identifying their own responsible locations in a bottom-up manner and that they could achieve considerably improved results compared with those of the previous method. We also investigated the structure of the resulting regime for cooperation and analyzed why our method could achieve the effective task allocation.
A security architecture for microprocessors

SAM ist eine Sicherheitsarchitektur, die aus einer Prozessorerweiterung und einem entsprechend angepassten Betriebssystem besteht. Die Prozessorerweiterung besteht primar aus einer fur den Programmierer transparenten Sicherheitsschicht, die automatisch die Integritat aller geladenen Daten pruft und samtliche Daten, die den Prozessor verlassen, verschlusseln kann. Damit ist es selbst bei einem direkten Zugriff auf den Hauptspeicher nicht moglich, ungeschutzte Daten zu lesen oder zu manipulieren. Entschlusselte Daten sind dabei nur innerhalb des Prozessors verfugbar und werden dort durch die Architektur vor unerlaubtem Zugriff geschutzt. Dieser Schutz schliest auch Schutz vor privilegierten Benutzern wie Administratoren mit erweiterten Rechten ein. Weiterhin stellt SAM sicher, dass ein Programm nur auf bestimmten Prozessoren entschlusselt werden kann und somit nur auf diesen ausfuhrbar ist. Die Integritatssicherung wird uber kryptographische Hashes erreicht. Diese ermoglichen eine Uberprufung der Daten und dienen damit der Erkennung von Manipulationen. Jede vom Prozessor erkannte Manipulation fuhrt zu einem sofortigen Programmabbruch. Somit ist sichergestellt, dass nur unmodifizierte Programme ausgefuhrt werden konnen und Manipulationen die Datensicherheit beeintrachtigen konnen. Der Prozessor muss verschlusselte, gesicherte und ungesicherte (und damit auch unverschlusselte) Speicherbereiche unterscheiden konnen. Bei SAM wird der Speicher dazu in einen gesicherten, einen verschlusselten und einen ungesicherten Bereich aufgeteilt. Instruktionen, die in einem gesicherten Bereich liegen, konnen auf auf den gesamten Speicher zugreifen und verschlusselte Daten werden transparent entschlusselt. Ungesicherte Instruktionen konnen ebenfalls auf den gesamten Speicher zugreifen, allerdings bleiben verschlusselte Bereiche verschlusselt und konnen somit nicht analysiert werden. Das Betriebssystem basiert auf einem fur SAM geringfugig angepassten Linux-Kernel. Die Anderungen sind bestehen hauptsachlich aus der Anpassung hardwarenaher Funktionen des Prozessmanagements und des Multitaskings an die Sicherheitsfunktionen des Prozessors. Die Prozessorerweiterung ist als optionale Erweiterung entwickelt worden, damit normale und ungesicherte Programme parallel zu verschlusselten Programmen ausgefuhrt werden konnen. Damit konnen die mit SAM gesicherten Prozessoren ebenfalls fur nicht sicherheitskritische Aufgaben verwendet werden um deren Auslastung zu erhohen. Die Umwandlung bestehender Programme in fur SAM gesicherte Programme ist einfach, und erfordert nur minimale Anderungen am Programmcode.
Towards a Software Component Quality Model

Component based software development is becoming more generalized, representing a considerable market for the software industry. The perspective of reduced development costs and shorter life cycles acts as a motivation for this expansion. However, several technical issues remain unsolved before software component’s industry reaches the maturity exhibited by other component industries. Problems such as the component selection by their integrators, the component catalogs formalization and the uncertain quality of third-party developed components, bring new challenges to the software engineering community. In this sense, this paper presents a brief survey on software component certification area, analyzing its lacks and further directions. Through this study, we propose a component quality model, describing consistent and well-defined characteristics for the components evaluation.
Bilingual children’s story comprehension across language boundaries: does retelling improve comprehension?

ABSTRACT The main objective of this study was to investigate 9–10-year-old children’s comprehension processes during listening to and free recall of a story. A cross-linguistic design comprised texts in L1 German and recall in L2 English and vice versa. Corresponding mono-linguistic control conditions in either L1 or L2 allowed to examine the extent to which higher-level comprehension processes led to the same performance of story recall, construction of a coherent text representation and inference making across language boundaries. The findings revealed that comprehension predominantly occurred during the input phase. Better comprehension resulted when L1 input was provided as opposed to L2 input. Retelling the story in L1 added less to comprehension when the input was in L2. The findings supported the prediction derived from the capacity hypothesis that bilingual children’s comprehension benefits from resources set free by more automatic processing during listening to a story in L1. A comparable automaticity effect was not observed during retelling in L1. L1-dominant bilinguals’ comprehension reacted sensitively to bilingual language conditions in contrast to balanced bilinguals’ performance.
Tackling the PAN’09 External Plagiarism Detection Corpus with a Desktop Plaigiarism Detector

Ferret is a fast and effective tool for detecting similarities in a group of files. Applying it to the PAN'09 corpus required modifications to meet the require- ments of the competition, mainly to deal with the very large number of files, the large size of some of them, and to automate some of the decisions that would nor- mally be made by a human operator. Ferret was able to detect numerous files in the development corpus that contain substantial similarities not marked as plagiarism, but it also identified quite a lot of pairs where random similarities masked actual plagiarism. An improved metric is therefore indicated if the "plagiarised" or "not plagiarised" decision is to be automated.
Robust stability and stabilization of uncertain linear positive systems via Integral Linear Constraints: L1- and Linfinity-gains characterization

Copositive linear Lyapunov functions are used along with dissipativity theory for stability analysis and control of uncertain linear positive systems. Unlike usual results on linear systems, linear supply-rates are employed here for robustness and performance analysis using L1- and Linfinity-gains. Robust stability analysis is performed using Integral Linear Constraints (ILCs) for which several classes of uncertainties are discussed. The approach is then extended to robust stabilization and performance optimization. The obtained results are expressed in terms of robust linear programming problems that are equivalently turned into finite dimensional ones using Handelman's Theorem. Several examples are provided for illustration.
Fuzzy Set Approaches to Spatial Data Mining of Association Rules

This paper presents an approach to the discovery of association rules for fuzzy spatial data. Association rules provide information of value in assessing significant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types, directional or geometric relationships, etc. We have combined and extended techniques developed in both spatial and fuzzy data mining in order to deal with the uncertainty found in typical spatial data.
Novel Graph Cuts Method for Multi-Frame Super-Resolution

In this letter, we propose a new graph cuts multi-frame super resolution method. The method is carried out in 3 steps. First, we project each high-resolution pixel p onto the low-resolution images and select low-resolution pixels which fall within the zone of influence of p. Second, we weigh the contribution of the low-resolution pixels via a soft switching function and add them to construct a virtual low resolution pixel. The high resolution image is then recovered after minimizing a Maximum a posteriori Markov Random Field (MAP-MRF) energy function. This is done by approximating our energy function to make it graph representable and minimize it with a graph cuts α-expansion algorithm. Experimental results show that our approach outperforms state-of-the-art methods.
HOW MUCH BANK CAPITAL IS NEEDED TO MAINTAIN FINANCIAL STABILITY ?

This paper describes and implements for UK banks a simple top-down approach to analyzing capital adequacy. Under di erent assumptions, we calculate default probabilities and implicit deposit insurance values using credit risk models based on the behavior of the banks' equity-liability ratio. Furthermore, we investigate how probabilities of default and of nancial crisis (de ned as the simultaneous deterioration in several banks' nances) change as bank capital levels are adjusted. JEL Nos: G12, G21, G28.
Automatic Categorization of Fanatic Texts

This paper presents a task of automatic categorization of fanatic texts. The analyzed set of texts stems from an Arabic environment in Kuwait, where teachers and students were asked questions regarding various terrorist tendencies. The responses were classified by a domain expert into one of three classes with respect to degree of fanaticism of their content. The main task was to develop an automated tool, which is able to grasp the implicit expert’s knowledge and distinguish the documents according to their content, i.e., a classifier. The paper deals with the bag-ofwords representation of the documents. It applies learning algorithms that proved to work well in the field of text categorization (TFIDF classifier, multinomial probabilistic model) as well as the random forest classifier that is well-known to cope with domains described by a large number of features. The associated task was to discover any knowledge helping to understand the domain. For this reason, the final models were also analyzed and used to reveal inherent structure inside the set of documents (a sub-class structure) or to identify important words and their possible relations.
Analyzing the Transferability of Collective Inference Models Across Networks

Collective inference models have recently been used to significantly improve the predictive accuracy of node classifications in network domains. However, these methods have generally assumed a fully labeled network is available for learning. There has been relatively little work on transfer learning methods for collective classification, i.e., to exploit labeled data in one network domain to learn a collective classification model to apply in another network. While there has been some work on transfer learning for link prediction and node classification, the proposed methods focus on developing algorithms to adapt the models without a deep understanding of how the network structure impacts transferability. Here we make the key observation that collective classification models are generally composed of local model templates that are rolled out across a heterogeneous network to construct a larger model for inference. Thus, the transferability of a model could depend on similarity of the local model templates and/or the global structure of the data networks. In this work, we study the performance of basic relational models when learned on one network and transferred to another network to apply collective inference. We show, using both synthetic and real data experiments, that transferability of models depends on both the graph structure and local model parameters. Moreover, we show that a probability calibration process (that removes bias due to propagation errors in collective inference) improves transferability.
A specification schema for software connectors

Since the invention of the connectors that serve as one of the building blocks of software architecture, various researchers have described the characteristics of connectors that they have discovered in given software systems. These characteristics have frequently been revealed by employing a bottom-up approach to different disciplines of software engineering. As a consequence, numerous attributes of connectors have been introduced at a rather technical level, and the vocabulary regarding specific aspects of connectors is highly heterogeneous. This eclectic list of attributes is not an appropriate abstraction level for an architect when developing connectors for application software. Instead, it would be more helpful to have a framework that begins from a conceptual perspective and guides the software architect in identifying the attributes required for a specific connector. To this end, a hierarchical schema for specifying software connectors is proposed in this paper. In contrast to existing schemas in which either the attributes considered are few in number and ungrouped or the attribute specification and grouping was not the main focus of the research, this paper presents a homogenous specification schema at different levels of abstraction and is based on logical perspectives rather than technical features. The schema can support architects in various situations--such as connector selection and documentation--and can aid in implementing or generating concrete software connectors. The application of the schema will be demonstrated by specifying a software connector between Twitter and an application.
Parallel Instantiation in DLV

Answer Set Programming (ASP) is a purely-declarative logic programming language allowing for disjunction and nonmonotonic negation. The evaluation of ASP Programs is traditionally carried out in two steps. In the first step an input program P undergoes the so-called instantiation (or grounding) process, which produces a program P ′ semantically equivalent to P , but not containing any variable; in turn, P ′ is evaluated by using a backtracking search algorithm in the second step. This paper presents a new parallel version of the instantiator of DLV, featuring new load-balancing and granularity control heuristics, which is able to exploit the processing power offered by multi-core/multi-processor SMP machines.
Assessing the influence of neutral grounds on match outcomes

ABSTRACT The home advantage in various sports has been well documented. So far, we lack knowledge whether playing in neutral venues indeed removes many, if not all, theoretically assumed advantages of playing at home. Analysing over 3,500 senior men’s Gaelic football and hurling matches – field games with the highest participation rates in Ireland – between 2009 and 2018, we test the potential moderating influence of neutral venues. In hurling and Gaelic football, a considerable share of matches is played at neutral venues. We test the influence of neutral venues based on descriptive statistics, and multilevel logistic and multinomial regressions controlling for team strength, the importance of the match, the year, and the sport. With predicted probabilities ranging between 0.8 and 0.9, the favourite team is very likely to win home matches. The predicted probability drops below 0.6 for away matches. At neutral venues, the favourite team has a predicted probability of winning of 0.7. A Coarsened Exact Matching (CEM) approach also reveals very substantive and significant effects for the “treatment” of neutral venues. Overall, neutral venues appear to be an under-utilised option for creating fairer and less predictable competition, especially in single-game knock-out matches.
Requirements traceability in automated test generation

Automated test case and test driver generation from a formal model is becoming a more widely used practice in the smart card area. This innovative approach for validation testing makes it possible to ensure the functional coverage of the test suite and to automate the production of executable test scripts. This paper presents an approach to automatically produce the Traceability Matrix from requirements to test cases, as part of the test generation process. This approach is embedded in the LEIRIOS Test Generator (LTG) tool, and has been used for several real-life applications in the smart card industry. This paper introduces the approach to annotating the formal model and using it to generate the Traceability Matrix. It also discusses some lessons learnt from our experience using Model-Based Testing for smart card software validation.
Confirming a population of hot-dust dominated, star-forming, ultraluminous galaxies at high redshift

We identify eight z > 1 radio sources undetected at 850 μm but robustly detected at 70 μm, confirming that they represent ultraluminous infrared galaxies (ULIRGs) with hotter dust temperatures (〈T_d〉= 52 ± 10 K) than submillimetre galaxies (SMGs) at similar luminosities and redshifts. These galaxies share many properties with SMGs: ultraviolet spectra consistent with starbursts, high stellar masses and radio luminosities. We can attribute their radio emission to star formation since high-resolution Multi-Element Radio Linked Interferometer Network (MERLIN) radio maps show extended emission regions (with characteristic radii of 2–3 kpc), which are unlikely to be generated by active galactic nucleus (AGN) activity. These observations provide the first direct confirmation of hot, dusty ULIRGs which are missed by current submillimetre surveys. They have significant implications for future observations from the Herschel Space Observatory and Submillimetre Common-User Bolometer Array 2 (SCUBA2), which will select high-redshift luminous galaxies with less selection biases.
Constrained image segmentation from hierarchical boundaries

In this paper, we address the problem of constrained segmentation of natural images, in which a human user places one seed point inside each object of interest in the image and the task is to determine the object boundaries. For this purpose, we study the connection between seed-based and hierarchical segmentation. We consider an Ultrametric Contour Map (UCM), the representation of a hierarchy of segmentations as a real-valued boundary image. Starting from a set of seed points, we propose an algorithm for constructing Voronoi tessellations with respect to a distance defined by the UCM. As a result, the main contribution of the paper is a method that allows exploiting the information of any hierarchical scheme for constrained segmentation. Our algorithm is parameter-free, computationally efficient and robust. We prove the interest of the approach proposed by evaluating quantitatively the results with respect to ground-truth data.