Miracle-dz/UniFAR-FTUs huggingface dataset:
The efficiency of using everyday technological devices by older adults: the role of cognitive functions

ABSTRACT Older adults experience more problems than younger people when using everyday technological devices such as personal computers, automatic teller machines and microwave ovens. Such problems may have serious consequences for the autonomy of older adults since the ability to use technology is becoming essential in everyday life. One potential cause of these difficulties is age-related decline of cognitive functions. To test the role of cognitive abilities in performing technological tasks, we designed the Technological Transfer Test (TTT). This new and ecologically valid test comprises eight technological tasks that are common in modern life (operating a CD player, a telephone, an ATM, a train-ticket vending machine, a microwave-oven, an alarm clock, a smart card charging device and a telephone voice menu). The TTT and a comprehensive battery of cognitive tests were administered to 236 healthy adults aged 64–75 years on two separate occasions. The results demonstrated that the performance time for five of the eight tasks was predicted by cognitive abilities. The exact cognitive functions affecting technological performance varied by the technological task. Among several measures and components of cognition, the speed of information processing and cognitive flexibility had the greatest predictive power. The results imply that age-related cognitive decline has a profound effect on the interaction between older adults and technological appliances.
Studying Relational Chains from Narrative Material

Étudier les chaînes relationnelles à partir d’un matériau narratif : Les chaînes relationnelles sont une approche mal connue des réseaux sociaux, dont on classe habituellement les méthodes d’analyse selon la dichotomie réseaux personnels / réseaux complets. Plutôt que de cartographier les réseaux de façon statique, l’étude des chaînes relationnelles reconstitue les mobilisations concrètes de relations sociales dans des processus d’accès à des ressources ou de mise en relation de personnes. La méthode que nous présentons permet de reconstruire ces chaînes à partir d’un matériau narratif constitué sur la base d’entretiens croisés. Cette méthode est particulièrement adaptée à la saisie des phénomènes d’encastrement des activités économiques dans les réseaux sociaux. Nous la présentons dans cet article à partir de deux enquêtes, l’une sur les relations science-industrie et l’autre sur les créations d’entreprises. Relational chains are a poorly understood approach to social networks, whose methods of analysis are usually classified according to the personal networks / complete networks dichotomy. Rather than mapping out networks statically, the study of relational chains reconstructs the concrete mobilisations of social relations in processes for accessing resources or networking with people. The method we present reconstructs chains from a narrative material established on the basis of crossed interviews. This method is especially well suited to capturing phenomena of embeddedness of economic activities in social networks. We introduce it in this article based on two surveys, one on science-industry relations and the other on enterprise creation.
Years of Higher Order Programming Languages

Fifty years ago one of the greatest breakthroughs in computer programming and in the history of computers happened – the appearance of FORTRAN, the first higher-order programming language. From that time until now hundreds of programming languages were invented, different programming paradigms were defined, all with the main goal to make computer programming easier and closer to as many people as possible. Many battles were fought among scientists as well as among developers around concepts of programming, programming languages and paradigms. It can be said that programming paradigms and programming languages were very often a trigger for many changes and improvements in computer science as well as in computer industry. Definitely, computer programming is one of the cornerstones of computer science. Today there are many tools that give a help in the process of programming, but there is still a programming tasks that can be solved only manually. Therefore, programming is still one of the most creative parts of interaction with computers. Programmers should chose programming language in accordance to task they have to solve, but very often, they chose it in accordance to their personal preferences, their beliefs and many other subjective reasons. Nevertheless, the market of programming languages can be merciless to languages as history was merciless to some people, even whole nations. Programming languages and developers get born, live and die leaving more or less tracks and successors, and not always the best survives. The history of programming languages is closely connected to the history of computers and computer science itself. Every single thing from one of them has its reflexions onto the other. This paper gives a short overview of last fifty years of computer programming and computer programming languages, but also gives many ideas that influenced other aspects of computer science. Particularly, programming paradigms are described, their intentions and goals, as well as the most of the significant languages of all paradigms.
Fluent-based animation: exploiting the relation between goals and scenarios for requirements validation

Scenarios and goals are effective and popular techniques for requirements definition. Validation is essential in order to ensure that they represent what stakeholders actually want. Rather than validating scenarios and goals separately, possibly driving the elaboration of one through the validation of the other, This work focuses on exploiting the relation between goals and scenarios. The aim is to provide effective graphical animations as a means of validating both. Goals are objectives that a system is to meet. They are elaborated into a structure that decomposes declarative goals into goals that can be formulated in terms of events that can be controlled or monitored by the system. Scenarios are operational examples of system usage. The relation between scenarios and goals is established by means of fluents that describe how events of the operational description change the state of the basic propositions from which goals are expressed. Graphical animations are specified in terms of fluents and driven by a behaviour model synthesised from the operational scenarios.
Factors Influencing Efavirenz and Nevirapine Plasma Concentration: Effect of Ethnicity, Weight and Co-Medication

Background The aim of this study was to examine factors influencing plasma concentration of efavirenz and nevirapine. Methods Data from the Liverpool Therapeutic Drug Monitoring (TDM) registry were linked with the UK Collaborative HIV Cohort (CHIC) Study. For each patient, the first measurement of efavirenz (600 or 800 mg/day) or nevirapine (400 mg/day) plasma concentration was included. Linear regression was used to evaluate the association of dose, gender, age, weight, ethnicity and concomitant antiretroviral drugs or rifampicin with log-transformed drug concentration, adjusted for time since last intake. Results Data from 339 patients on efavirenz (34% black, 17% rifampicin) and 179 on nevirapine (27% black, 6% rifampicin) were included. Multivariable models revealed the following predictors for efavirenz concentration: black ethnicity (59% higher; P<0.001), weight (10% lower per additional 10 kg; P=0.002), 800 mg/day (52% higher; P=0.027), rifampicin (35% lower; P=0.039), and zidovudine (25% lower; P=0.010). Notably, without adjustment for other factors, patients on rifampicin had 48% higher efavirenz concentration, as these patients were mostly black and on 800 mg/day. For nevirapine the predictors were black ethnicity (39% higher; P=0.002), rifampicin (40% lower; P=0.002), protease inhibitor (28% higher; P=0.008) and tenofovir (22% higher; P=0.024). Conclusions We observed clear associations between ethnicity and concentrations of nevirapine and efavirenz. Our analyses confirm that concomitant rifampicin substantially decreases concentration of both efavirenz and nevirapine; however, for efavirenz this effect was more than counterbalanced by the effect of ethnicity and increased efavirenz dose. There was also an additional impact of weight, which should be considered when determining optimal dosage. Other associations from our analysis (between tenofovir or protease inhibitor and nevirapine, and zidovudine and efavirenz), require confirmation in formal pharmacokinetic studies.
Batch steganography in the real world

We examine the universal pooled steganalyzer of in two respects. First, we confirm that the method is applicable to a number of different steganographic embedding methods. Second, we consider the converse problem of how to spread payload between multiple covers, by testing different payload allocation strategies against the universal steganalyzer. We focus on practical options which can be implemented without new software or expert knowledge, and we test on real-world data. Concentration of payload into the minimal number of covers is consistently the least detectable option. We present additional investigations which explain this phenomenon, uncovering a nonlinear relationship between embedding distortion and payload. We conjecture that this is an unavoidable consequence of blind steganalysis. This is significant for both batch steganography and pooled steganalysis.
Effect of Low-Frequency rTMS on Electromagnetic Tomography (LORETA) and Regional Brain Metabolism (PET) in Schizophrenia Patients with Auditory Hallucinations

Background: Auditory hallucinations are characteristic symptoms of schizophrenia with high clinical importance. It was repeatedly reported that low frequency (≤1Hz) repetitive transcranial magnetic stimulation (rTMS) diminishes treatment-resistant auditory hallucinations. A neuroimaging study elucidating the effect of rTMS in auditory hallucinations has yet to be published. Objective: To evaluate the distribution of neuronal electrical activity and the brain metabolism changes after low-frequency rTMS in patients with auditory hallucinations. Methods: Low-frequency rTMS (0.9 Hz, 100% of motor threshold, 20 min) applied to the left temporoparietal cortex was used for 10 days in the treatment of medication-resistant auditory hallucinations in schizophrenia (n = 12). The effect of rTMS on the low-resolution brain electromagnetic tomography (LORETA) and brain metabolism (18FDG PET) was measured before and after 2 weeks of treatment. Results: We found a significant improvement in the total and positive symptoms (PANSS), and on the hallucination scales (HCS, AHRS). The rTMS decreased the brain metabolism in the left superior temporal gyrus and in interconnected regions, and effected increases in the contralateral cortex and in the frontal lobes. We detected a decrease in current densities (LORETA) for the beta-1 and beta-3 bands in the left temporal lobe whereas an increase was found for beta-2 band contralaterally. Conclusion: Our findings implicate that the effect is connected with decreased metabolism in the cortex underlying the rTMS site, while facilitation of metabolism is propagated by transcallosal and intrahemispheric connections. The LORETA indicates that the neuroplastic changes affect the functional laterality and provide the substrate for a metabolic effect.
International Conference on Mobile Web Information Systems ( MobiWIS ) Empirical Comparisons of Attack and Protection Algorithms for Online Social Networks

Online social networks, like Facebook, are popular social networking websites, on which hundreds of millions of users make friends and interact with people. There is a large amount of personal information in these networking websites and their security is rather concerned by both users and researchers, because valuable private information will bring great profit to some people or groups. In the real world, profits motivate people and groups to obtain the personal private data lawlessly and many attacks are launched on the social networks. Facing various attacks, distinct protective strategies are proposed by researches to reduce the negative effect of attacks. However, the practical performance of protections is unknown when they are battling with the real attacks. Moreover, we also understand little about how strong attacks would be when they are facing protections. Therefore, this paper proposes an Attack-Protect-Attack (APA) comparison scheme to explore the performance and bias of various attack algorithms and protective strategies for online social networks. By this way, the comparison results are valuable and meaningful for further protection of private information. We apply several attacking and protective approaches on a real-world dataset from Facebook, then evaluate them by the accuracy of attack algorithms. Following the comparison scheme, the experiments demonstrate that the performance of protective strategies is not satisfactory in the complex and practical case.
Cleavage of K-FGF produces a truncated molecule with increased biological activity and receptor binding affinity

The K-FGF/HST (FGF-4) growth factor is a member of the FGF family which is efficiently secreted and contains a single N-linked glycosylation signal. To study the role of glycosylation in the secretion of K-FGF, we mutated the human K-fgf cDNA to eliminate the glycosylation signal and the mutated cDNA was cloned into a mammalian expression vector. Studies of immunoprecipitation from the conditioned medium of cells expressing this plasmid revealed that the lack of glycosylation did not impair secretion, however the unglycosylated protein was immediately cleaved into two NH2-terminally truncated peptides of 13 and 15 kD, which appeared to be more biologically active than the wild-type protein. These two proteins also showed higher heparin binding affinity than that of wt K-FGF. We have expressed in bacteria the larger of these two proteins (K140), in which the NH2-terminal 36 amino acids present in the mature form of K-FGF have been deleted. Mitogenicity assays on several cell lines showed that purified recombinant K140 had approximately five times higher biological activity than wild-type recombinant K-FGF. Studies of receptor binding showed that K140 had higher affinity than wt K-FGF for two of the four members of FGF receptor's family, specifically for FGFR-1 (flg) and FGFR-2 (bek). K140 also had increased heparin binding ability, but this property does not appear to be responsible for the increased affinity for FGF receptors. Thus removal of the NH2-terminal 36 amino acids from the mature K-FGF produces growth factor molecules with an altered conformation, resulting in higher heparin affinity, and more efficient binding to FGF receptors. Although it is not clear whether cleavage of K-FGF to generate K140 occurs in vivo, this could represent a novel mechanism of modulation of growth factor activity.
Analogical Reasoning and Knowledge Generation in Organization Theory

This paper reviews and evaluates the cognitive status to which metaphors and analogies have been ascribed in the process of knowledge generation in organiza tion theory. Three perspectives are identified: metaphors as ways of thinking, metaphors as dispensable literary devices, and metaphors as potential ideological distortions. The main tenets of each one of them are reviewed and subsequently submitted to criticism. It is argued here that, despite their differing claims, the preceding perspectives converge on the assumption that there is a gap between metaphorical and scientific languages. The grounds for the existence of this gap are challenged in this paper, noting that the structure-mapping theory of analogy provides a methodology for developing metaphorical insights to yield scientific models and theories.
Transitioning to an athletic subjectivity: first-semester experiences at a corporate (sporting) university

This paper explores how eight women experience, and are incorporated into, the regulatory regimes and pedagogical practices of a corporate (sporting) university in their first semester of college. Using Foucault's conceptions of power, discipline and subjectivity, we situate women's participation on the soccer team within the context of a corporatized Division-I University. As sport has become increasingly corporatized, low-profile sports have begun to emulate high-profile sports. The corporate university and corporate sport model indicative of high-profile college programs, such as the one involved in this study, use (sporting) bodies as resources, rendering them detached and alienated from many college experiences. As evidenced in the data from this study, the pedagogies of highly structured schedules and authoritative-, peer- and self-disciplining mechanisms functioned to normalize the experiences of stress, tension, isolation, loneliness and little autonomy. Nevertheless, we also discuss a point of rupture, wherein two women, for different reasons, refused their athletic subjectivities at The University after their first semester by discontinuing their athletic participation. The contextualization of such experiences reveals the complex relations of power emerging from young adults’ immersion into an athletic system imbued with corporatist ideologies housed within a simulated aura of education and development. This paper aims not to provide definitive answers but rather, by exploring power relations, to open for discussion critical questions about college athletics and to advocate for a more humanist research agenda that considers athletic subjectivities.
A fast 25/6-approximation for the minimum unit disk cover problem

Given a point set P in 2D, the problem of finding the smallest set of unit disks that cover all of P is NP-hard. We present a simple algorithm for this problem with an approximation factor of 25/6 in the Euclidean norm and 2 in the max norm, by restricting the disk centers to lie on parallel lines. The run time and space of this algorithm is O(n log n) and O(n) respectively. This algorithm extends to any Lp norm and is asymptotically faster than known alternative approximation algorithms for the same approximation factor.
Preventing model of job stress, emotional exhaustion and deviant behaviors through management, leadership and ethical values

Aim: This research was conducted with the purpose of introducing a model for the prevention of job stress, emotional exhaustion and deviant behaviors through ethical values, leadership and management. Method: method of research was correlation (Covariance Matric) and the population was consisted of 7000 employees of the Iranian Metal Company Ltd. From this statistical population, 385 persons were selected to participate in the study using stratified sampling through employees' list of names. The following questionnaires were used to assess research variables: Job Stress Questionnaire (Kahn et al, 1964), Emotional Exhaustion Scale (Maslach & Jackson, 1981), Organizational Deviant Behaviors Questionnaire (Bennett & Robinson, 2000), Higher Management Support for Ethical Behaviors Scale (Viswesvaran et al, 1998), Moral Leadership Questionnaire (Rowold, 2008) and Corporate Ethical Values Questionnaire (Hunt et al, 1989). Data were analyzed using Pearson's correlation coefficient and structure equation modeling. Results: Results revealed that, in the revised final model of this research, top management support with corporate ethical values correlated significantly with moral based leadership, corporate ethical values with moral based leadership, moral based leadership with job stress, job stress, corporate ethical values and moral based leadership with emotional exhaustion, and emotional exhaustion, top management support for ethical behaviors, job stress and corporate ethical values correlated with deviant behaviors. Conclusions: It is argued that through a series of chain relationships, job stress and emotional exhaustion as well as deviant behaviors may be decreased through top management support for ethical behaviors, along with moral based leadership and involvement in ethical values.
Machine Learning Methods for High-Dimensional Imbalanced Biomedical Data

Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
In Pursuit of Delay-Related Brain Activity for Anticipatory Eye Movements

How the brain stores motion information and subsequently uses it to follow a moving target is largely unknown. This is mainly due to previous fMRI studies using paradigms in which the eye movements cannot be segregated from the storage of this motion information. To avoid this problem we used a novel paradigm designed in our lab in which we interlaced a delay (2, 4 or 6 seconds) between the 1st and 2nd presentation of a moving stimulus. Using this design we could examine brain activity during a delay period using fMRI and have subsequently found a number of brain areas that reveal sustained activity during predictive pursuit. These areas include, the V5 complex and superior parietal lobe. This study provides new evidence for the network involved in the storage of visual information to generate early motor responses in pursuit.
MARC: A Mobile Application Review Classifier

Mobile application stores enable end-users of software to directly express their needs and share their experience with mobile apps in the form of textual reviews. These reviews often contain important user feedback that can be leveraged by app developers to help them understand their end-user needs. However, such information are not readily available, and vetting individual reviews manually can be a tedious task. To alleviate this effort, we introduce MARC, a Mobile Application Review Classifier. MARC is a stand-alone automated solution that enables developers to extract and classify user reviews into fine-grained software maintenance requests, including bug reports and user requirements. MARC is equipped with a set of configuration features to enable practitioners and researchers to classify user reviews under different settings. A dataset of app reviews sampled from three apps are used to evaluate the performance of MARC. The results show that MARC achieves accuracy levels that can be adequate for practical and research applications