Miracle-dz/UniFAR-FTUs huggingface dataset:
STUDIES ON READING THE URBAN CENTRE VIA COGNITIVE MAPS: THE EXAMPLE OF ESKIŞEHIR, TURKEY

Cities are open spaces where people exist together, socialize and perform the actions of encountering and meeting others. Urbanites carry out their socio-cultural life through their activities in exterior space within the construct of the urban physical environment. Social structuring emerges in open public spaces, in which the relationship between the individual and society is reinforced by the physical environment. Nevertheless, today, the rapid growth of the uncontrolled urban development in a complex pattern increasingly renders it difficult for the urbanite to detect and easily scrutinize exterior spaces in the city. The environmental image acquired by the individual gives them the feeling of being emotionally secure when bearing this image in mind. The elevated qualities of legibility and wayfinding in the cities are of the most important “urban design principles”. Urban legibility means that an environment is discernable and is perceivable within continuity. The more rapid a city can create an image in mind, the more legible it becomes. In this study, the city of Eskişehir, which is located in the northwestern part of Turkey and has a history that dates back to Phrygian civilization, is scrutinized. Apart from being an industrial and commercial city, Eskişehir has been a university city since the 1950s. Currently, university students comprise 10% of the urban population. In this study, reading the city was carried out via the cognitive map of the university students who experience the city for a while.
Evolving Portrait Painter Programs using Genetic Programming to Explore Computer Creativity

Creative systems as opposed to standard evolutionary systems favor exploration over optimization, finding innovative or novel solutions over a preconceived notion of a specific optimal solution. The best creative evolutionary systems only provide tools, allowing the evolutionary process to discover novelty and innovation on its own. We experiment with computer creativity by employing and modifying techniques from evolutionary computation to create a related family of abstract portraits. A new type of Genetic Programming (GP) system is used called Cartesian GP, which uses typical GP Darwinian evolutionary techniques (crossover, mutation, and survival), but has several features that allow the GP system to favor creative solutions over optimized solutions including accommodating for genetic drift where different genotypes map to the same phenotype, visual mapping modules and a knowledge of a painterly color space. This work with its specific goal of evolving portrait painter programs to create a portrait 'sparked' by the famous portrait of Darwin, speaks to the evolutionary processes as well as creativity, as seen by the early results where the evolving programs use recurring, emergent and merged creative strategies to become good abstract portraitists.
A massively parallel implementation of the watershed based on cellular automata

The watershed transform is a very powerful segmentation tool which comes directly from the idea of watershed line in geohydrology. It has proved its efficiency in many computer vision application fields. This paper presents a new implementation of the watershed which is optimal according to computation time. The flooding algorithm is reminded. Then, a massively parallel cellular automaton is proposed to propagate data using this approach. We discuss the pros and cons of a hardware implementation and give an example of application. A comparison between the results obtained and theoretical limit cases is also presented.
A cognitively based approach to affect sensing from text

Studying the relationship between natural language and affective information as well as assessing the underpinned affective qualities of natural language are becoming crucial for improving human computer interaction. Different approaches have already been employed to "sense" affective information from text but none of those considered the cognitive structure of individual emotions and appraisal structure of those emotions adopted by emotion sensing programs. It has also been observed that previous attempts for textual affect sensing have categorized texts into a number of emotion groups, e.g. six so-called "basic" emotion proposed by Paul Ekman which we believe insufficient to classify textual emotions. Hence we propose a different approach to sense affective information from texts by applying the cognitive theory of emotions known as OCC model [1] which distinguishes several emotion types that can be identified by assessing valenced reactions to events, agents or objects described in the texts. In particular we want to create a formal model that can not only "understand" what emotions people wrap with their textual messages, but also can make automatic empathic response with respect to the emotional state detected in the text (e.g. in a chat system). We first briefly describe relevant works and then we explain our proposal with examples. Finally we conclude with future work plans.
System-level power-performance trade-offs in task scheduling for dynamically reconfigurable architectures

Dynamic scheduling for System-on-Chip (SoC) platforms has become an important field of research due to the emerging range of applications with dynamic behavior (e.g. MPEG-4). Dynamically reconfigurable architectures are an interesting solution for this type of applications.However, dynamic scheduling for run-time reconfigurable architectures with power-performance trade-offs has not been addressed in previous research efforts. In this paper, we address this open issue using a system-level approach. Within our approach, we have used clock-gating and frequency-scaling strategies for power consumption minimization, jointly with our proposed architecture and scheduling algorithms.Device reconfiguration is a high-power consumption process. Thus reducing the number of device reconfigurations not only helps to reduce the reconfiguration overhead penalty (minimizing the application execution time), but also helps to reduce the system-level power consumption. Thus, dynamic task scheduling and reconfiguration context scheduling become a critical issue for power-performance trade-offs in embedded systems design.
A study of the relationship between antivirus regressions and label changes

AntiVirus (AV) products use multiple components to detect malware. A component which is found in virtually all AVs is the signature-based detection engine: this component assigns a particular signature label to a malware that the AV detects. In previous analysis [1-3], we observed cases of regressions in several different AVs: i.e. cases where on a particular date a given AV detects a given malware but on a later date the same AV fails to detect the same malware. We studied this aspect further by analyzing the only externally observable behaviors from these AVs, namely whether AV engines detect a malware and what labels they assign to the detected malware. In this paper we present the results of the analysis about the relationship between the changing of the labels with which AV vendors recognize malware and the AV regressions.
Stability analysis and trajectory design of a 2-D.O.F. bipedal walker

This paper studies a walking 2-DOF robot, which consists of a stance leg, swing leg and a hip mass. Due to the hybrid nature of the robot, a hybrid virtual holonomic constraint (hVHC) to be enforced is constructed. A sufficient condition to the stability of the constraint is proposed. For a desired gait trajectory, the paper presents a systematic procedure on designing a gait profile with per-defined period while enforcing the hVHC at the same time. In addition, necessary and sufficient conditions are proposed that regulates tracking error even at impact events.
A simple and efficient explicit parallelization of logic programs using low-level threading primitives

In this work, we present an automatic way to parallelize logic programs for finding all the answers to queries using a transformation to low level threading primitives. Although much work has been done in parallelization of logic programming more than a decade ago (e.g., Aurora, Muse, YapOR), the current state of parallelizing logic programs is still very poor. This work presents a way for parallelism of tabled logic programs in XSB Prolog under the well founded semantics. An important contribution of this work relies in merging answer-tables from multiple children threads without incurring copying or full-sharing and synchronization of data-structures. The implementation of the parent-children shared answer-tables surpasses in efficiency all the other data-structures currently implemented for completion of answers in parallelization using multi-threading. The transformation and its lower-level answer merging predicates were implemented as an extension to the XSB system.
Elder abuse within the family environment in the Azores Islands

ABSTRACT Objectives: to dimension abuse against vulnerable adults within the family and community environment in the Azores Islands, identify risk factors for abuse and describe the profile of an abused elder. Method: descriptive cross-sectional study. Random sampling. The instruments used were: clinical histories of the users, Mini-Mental State Examination, Index of Independence in Basic Activities of Daily Living, Family APGAR Scale, Elder Abuse Suspicion Index and Social Work Assessment Form. Descriptive statistical analysis was used for qualitative and quantitative variables and multiple logistic regression was used to identify factors associated with elder mistreatment. Results: abuse suspicion was identified in 24.5% of elderly participants. Psychological abuse was the most common type of abuse and sons were the main abusers. Conclusion: being a woman and belonging to a dysfunctional family is associated with an increased risk of becoming a victim of abuse; the high level of domestic violence against the elderly in the Azores Islands is in line with the rest of Portugal.
Actin disassembly by cofilin, coronin, and Aip1 occurs in bursts and is inhibited by barbed-end cappers

Turnover of actin filaments in cells requires rapid actin disassembly in a cytoplasmic environment that thermodynamically favors assembly because of high concentrations of polymerizable monomers. We here image the disassembly of single actin filaments by cofilin, coronin, and actin-interacting protein 1, a purified protein system that reconstitutes rapid, monomer-insensitive disassembly (Brieher, W.M., H.Y. Kueh, B.A. Ballif, and T.J. Mitchison. 2006. J. Cell Biol. 175:315–324). In this three-component system, filaments disassemble in abrupt bursts that initiate preferentially, but not exclusively, from both filament ends. Bursting disassembly generates unstable reaction intermediates with lowered affinity for CapZ at barbed ends. CapZ and cytochalasin D (CytoD), a barbed-end capping drug, strongly inhibit bursting disassembly. CytoD also inhibits actin disassembly in mammalian cells, whereas latrunculin B, a monomer sequestering drug, does not. We propose that bursts of disassembly arise from cooperative separation of the two filament strands near an end. The differential effects of drugs in cells argue for physiological relevance of this new disassembly pathway and potentially explain discordant results previously found with these drugs.
A multi-protocol framework for the development of collaborative virtual environments

Collaborative virtual environments (CVEs) are used for collaboration and interaction of possibly many participants that may be spread over large distances. Both commercial and freely available CVEs exist today. Currently, CVEs are used already in a variety of different fields: gaming, business, education, social communication, and cooperative development In this paper, a general framework is proposed for the development of a cooperative environment which is able to exploit a multi protocol network infrastructure. The framework offers support to concerns such as communication security and inter-protocol interoperability and let software engineers to focus on the specific business of the CVE under development. To show the framework effectiveness we consider, as a case of study, the design of a reusable software layer for the development of distributed card games built on top of it. This layer is, in turn, used for the implementation of a specific card game.
Barriers and Facilitators to Care for Transgender Patients Experiencing Low Socioeconomic Status and Homelessness

Purpose: Discrimination and disparity including increased rates of poverty, homelessness, and lack of access to healthcare, are well-documented in the transgender community. Despite high prevalence of low socioeconomic status (SES), limited health research focuses on this subset of the trans patient population. This study seeks to explore barriers and facilitators to care specific to low SES and homeless trans patients. Methods: Using a semistructured interview format, transgender patients (n=5) were asked about their experiences accessing care at an urban federally qualified health center. Using a directed content data analysis methodology, interview transcripts were coded using preidentified category labels and novel themes were also identified and coded. Results: Emerging barriers to care include lack of primary care and post-operative care, miscommunication within the care team, misinformation of Medicaid benefits, referrals to non-affirming healthcare environments, and lack of trans community building. Emerging facilitators include intentional patient panel assignment, a feeling of “moving forward” in transition, and access to health insurance and coverage for transition related care. Conclusion: These interviews elucidate the unique clinical experiences of homeless and low SES transgender patients and offer insight for systems-level process modifications that could improve patient experience of healthcare and care coordination.
An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their inputloutput data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data. In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a Zineurizution of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.
Conditional and Unconditional Categorical Regression Models with Missing Covariates

Summary. We consider methods for analyzing categorical regression models when some covariates (Z) are completely observed but other covariates (X) are missing for some subjects. When data on X are missing at random (i.e., when the probability that X is observed does not depend on the value of X itself), we present a likelihood approach for the observed data that allows the same nuisance parameters to be eliminated in a conditional analysis as when data are complete. An example of a matched casecontrol study is used to demonstrate our approach.
Real-time Average Recurrence Interval Rainfall Maps for the U.S

Describing floods in terms of an average recurrence internal (ARI) or “return period” (100-year) has been used for decades to convey the rareness of major flooding events. However, describing the intensity of heavy rainstorms in a similar manner has not been as routine, but provides an equally good perspective of extreme rainfall events. Although the ARI of rainfall does not necessarily equate to a flood of the same ARI, ARI maps of rainfall provide an excellent indicator of flooding potential. Plus, real-time ARI maps of rainfall provide forecasters and media outlets a critical alternative to stream gauge information during rain-induced flooding events, especially considering flooding can often destroy or cause stream gauges to malfunction. The concept of ARI rainfall mapping has been used in recent government documents pertaining to extreme rainstorms. However, this paper/presentation will introduce the concept of real-time ARI rainfall maps, a new tool for conveying the magnitude of heavy rainfall events to the public. This is especially important as society and infrastructure become increasingly more vulnerable and impacted by extreme rainfall events, making timely, accurate and informative rainfall information paramount to protecting property, saving lives and efficiently managing water. Expressing the rarity (or commonness) of rainfall in terms of an ARI provides an objective and useful perspective of the rainfall that most people understand, even for those not familiar with the rainfall in a particular area. Real-time ARI rainfall maps provide a new and powerful means for the media to communicate where the rainfall is most unusual and most apt to produce flooding. The rainfall-to-ARI conversion is based on official rainfall frequency data published by the National Atmospheric and Oceanic Administration (NOAA) together with high-resolution (1 km x 1 km) gauge-adjusted radar rainfall from Weather Decision Technologies, Inc. (WDT) and the National Weather Service (NWS). The rainfall-to-ARI process is highly computational given the millions of grid cells that comprise the contiguous U.S. domain, but software has been optimized in to operate in a highly reliable, fast and redundant data center. Depending on the extent of rainfall across the country, a contiguous U.S. ARI map is processed in 4-8 minutes on a multiple-processor Linux computer. Operational ARI maps/grids are available within 25 minutes of their valid time and converted into a number of common formats. Once ARI maps for discrete periods (e.g. last 24-hours) are created, maps of the maximum ARI over a given period of time (e.g. 72-hours) can easily be created. These so-called maximum ARI maps/grids have the unique ability of portraying the ARI of a storm event, regardless of when the heaviest rainfall occurred across an area. An overview of rainfall frequency estimates as well as 6and 24-hour ARI maps, including several case studies, animations and real-time examples will be presented.
Innate Fear-Induced Weight Regulation in the C57BL/6J Mouse

Regulation of body weight is an important strategy for small prey animals to avoid capture. Field and laboratory studies have shown that prey animals reduce body size when subjected to long-term predator stimuli. However, the causes of predator-induced weight regulation are highly variable and the underlying mechanisms remain unclear. Understanding this phenomenon is important for gaining a better understanding of how animals regulate body weight under ethologically relevant conditions and has implications for obesity. Here we expose inbred C57BL/6J mice to a fear-inducing odorant (2,4,5-trimethylthiazole; mT) to model predation-induced weight regulation. Eight week-old mice were put on a 45% high fat diet (HFD) or chow diet (5% fat) and exposed daily to mT, an equally aversive dose of butyric acid (BA), or a neutral control scent (almond). mT-exposed mice in both diet groups gained significantly less weight over a 6-week period than BA-exposed mice. This differential weight gain appears unlikely to be due to differences in food intake and activity level, or brown adipose thermogenesis between the mT and BA groups. However, following chronic mT exposure we find increases in ΔFosB protein, a marker for long-term neural plasticity, in the dorsomedial hypothalamus (DMH)—an area previously implicated in chronic stress and defensive responses, as well as weight regulation. This study establishes a simplified and robust laboratory model of predation-mediated weight regulation with inbred lab mice and fear-inducing odor, and suggests a likely, yet undetermined, metabolic adaptation as contributing to this response.
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines

In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands. More specifically, our approach leverages affective lexica and word embeddings in combination with convolutional neural networks to infer the sentiment of financial news headlines towards a target company. Such architecture was used and evaluated in the context of the SemEval 2017 challenge (task 5, subtask 2), in which it obtained the best performance.
Complementarity of MFCC, PLP and Gabor features in the presence of speech-intrinsic variabilities

In this study, the effect of speech-intrinsic variabilities such as speaking rate, effort and speaking style on automatic speech recognition (ASR) is investigated. We analyze the influence of such variabilities as well as extrinsic factors (i.e., additive noise) on the most common features in ASR (mel-frequency cepstral coefficients and perceptual linear prediction features) and spectro-temporal Gabor features. MFCCs performed best for clean speech, whereas Gabors were found to be the most robust feature in extrinsic variabilities. Intrinsic variations were found to have a strong impact on error rates. While performance with MFCCs and PLPs was degraded in much the same way, Gabor features exhibit a different sensivity towards these variabilities and are, e.g., well-suited to recognize speech with varying pitch. The results suggest that spectro-temporal and classic features carry complementary information, which could be exploited in feature-stream experiments. Index Terms: automatic speech recognition, speech-intrinsic variabilities, feature extraction, spectro-temporal features
Health and Illness Concepts Among Lower Income Nicaraguan Women

Concepts of health and illness are culturally defined; however, few researchers have reported on these concepts among Latina women. A purposive sample of 14 lower income Nicaraguan women living in a squatter settlement is the focus of this qualitative study. The authors used in-depth, tape-recorded interviews in Spanish to gather data on the women’s concepts of health and illness for adults and babies and of health maintenance activities. The authors analyzed the verbatim transcripts and analyzed them for themes. The women’s concepts of health and illness included four themes: activities, disposition, eating, and appearance. Health maintenance activities included hygiene and sanitation, medical intervention, nutrition, and the appearance of cleanliness. Nurses and other health care providers will find these themes instructive in developing and providing health services for similar Latina women.