Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of Genetic Algorithm and Support Vector Machine for Daily Flow Forecasting

This paper applied a genetic algorithm (GA) to optimize the parameters of support vector machine (SVM) for daily flow forecasting of Chickasaw creek located in Mobile County. To investigate the impact of variable enabling/disabling of flow, rainfall and evaporation on model prediction accuracy, four model structures with different input vectors were developed and the performance of them was evaluated in terms of the mean square error and the coefficient of determination. The results show that the third model structure consisting of the past 3 days' flow, the past rainfall and evaporation as the inputs is superior to other model structures in performance. Compared with the back-propagation network (BPN), experimental results show that the prediction accuracy of the proposed SVM model is better than the former and can be used for forecasting the daily flow in engineering management.
Empirical Analysis of Motor Vehicle Theft in Israel, 1990-97

Trends in motor vehicle theft in Israel over the past decade are distinctly different from those found in other Western countries. This study used formal crime data to gain understanding of the offence and the offenders involved in it. The data were analysed by logistic regression models, the final condition of the stolen motor vehicle serving as the dependent variable classifying the theft and the offender. The findings showed an increase in the frequency of the offence due, among other things, to increasing professionalism. Such findings are compatible with reports of the media, police and a public committee claiming that motor vehicle theft forms part of a highly developed organized industry in which the stolen cars are transferred to the newly established Palestinian Authority for dismantling into car parts and resale in Israel.
Tunable enhancement of second-harmonic generation in dual graphene optical gratings

Employing geometry dependent plasmon resonances of graphene gratings, we design a graphene bi-layer optical grating, which can achieve several orders of magnitude enhancement of the second-harmonic generation (SHG) intensity. More importantly, this dual grating can act as an ultrafast optical switch as the SHG intensity can be readily controlled via gate voltage tuning.
Ubiquitous robotics in physical human action recognition: A comparison between dynamic ANNs and GP

Two different classifier representations based on dynamic artificial neural networks (ANNs) and genetic programming (GP) are being compared on a human action recognition task by an ubiquitous mobile robot. The classification methodologies used, process time series generated by an indoor ubiquitous 3D tracker which generates spatial points based on 23 reflectable markers attached on a human body. This investigation focuses mainly on class discrimination of normal and aggressive action recognition performed by an architecture which implements an interconnection between an ubiquitous 3D sensory tracker system and a mobile robot to perceive, process, and classify physical human actions. The 3D tracker and the robot are used as a perception-to-action architecture to process physical activities generated by human subjects. Both classifiers process the activity time series to eventually generate surveillance assessment reports by generating evaluation statistics indicating the classification accuracy of the actions recognized.
Web-scale table census and classification

We report on a census of the types of HTML tables on the Web according to a fine-grained classification taxonomy describing the semantics that they express. For each relational table type, we describe open challenges for extracting from them semantic triples, i.e., knowledge. We also present TabEx, a supervised framework for web-scale HTML table classification and apply it to the task of classifying HTML tables into our taxonomy. We show empirical evidence, through a large-scale experimental analysis over a crawl of the Web, that classification accuracy significantly outperforms several baselines. We present a detailed feature analysis and outline the most salient features for each table type.
VisualCNA: a GUI for interactive constraint network analysis and protein engineering for improving thermostability

UNLABELLED Constraint network analysis (CNA) is a graph theory-based rigidity analysis approach for linking a biomolecule's structure, flexibility, (thermo)stability and function. Results from CNA are highly information-rich and require intuitive, synchronized and interactive visualization for a comprehensive analysis. We developed VisualCNA, an easy-to-use PyMOL plug-in that allows setup of CNA runs and analysis of CNA results linking plots with molecular graphics representations. From a practical viewpoint, the most striking feature of VisualCNA is that it facilitates interactive protein engineering aimed at improving thermostability. AVAILABILITY AND IMPLEMENTATION VisualCNA and its dependencies (CNA and FIRST software) are available free of charge under GPL and academic licenses, respectively. VisualCNA and CNA are available at http://cpclab.uni-duesseldorf.de/software; FIRST is available at http://flexweb.asu. edu.
Enhanced Milieu Teaching

This study examined the effects of training 4 parents to use enhanced milieu teaching with their preschool children with developmental delays. A multiple baseline design across 3 intervention strategies was used to assess the parents' acquisition of the strategies. A multiple-probe design across 2 families, replicated across 2 additional families, was used to assess the effects of the parents' implementation of the strategies on their children's communication skills. The parents learned to use the strategies in the clinic and generalized them to the home. Positive effects were observed on children's spontaneous communication and target use, and on parent and child affect. Evidence of positive effects on child language development was also observed. Parent satisfaction with the intervention was high.
Self-rated health as a predictor of disability pension and death — A prospective study of middle-aged men

Objective: Self-rated health (SRH) is increasingly attracting attention as a predictor of morbidity and mortality while its relation to impaired function has been given less momentum. The aim of this study was to assess the relation between SRH and the risk of being awarded a disability pension and premature death. Methods : Five birth-year cohorts of middle-aged men were invited to a screening programme and were followed for approximately 11 years. Of the 718 (12%) men with a disability pension granted during follow-up, 46% had perceived their health as perfect on inclusion. The corresponding figure for the remaining 5,082 men was 77%. Results: The crude relative risk (RR) of disability pension for men with SRH less than perfect was 3.7 (3.2-4.2). After adjustment for premorbidity/medication, the RR declined to 3.3 (2.8-3.8). The crude RR of death associated with SRH less than perfect was 1.6 (1.3-2.0), unchanged after adjustment. Conclusion: The results showed that SRH is a strong and independent predictor of disability and, to a lesser degree, of mortality.
Empathy Examined From Perspectives of Neuroscience and Artistic Imagination

This response to Ian E. Wickramasekera II’s article, Mysteries of Hypnosis and the Self Are Revealed by the Psychology and Neuroscience of Empathy, is addressed from a joint perspective on consciousness comprising two related orientations: neuroscience and artistic imagination. We find that the central importance of empathy to empathic involvement theory (Wickramasekera II, 2015) reflects the pivotal nature of empathy in the brain and in the relational exchange implicit in the psychotherapeutic process, particularly when using art in therapy. We offer a preliminary unpacking of the roles related to key psychological processes, such as imagination, that are implicated in clinical uses of verbal and visual empathic resonance.
Reasons for Exercise Inventory koulukyselyssä : mittarin reliabiliteetti- ja rakennevaliditeettitarkastelua

All material supplied via JYX is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Reasons for Exercise Inventory koulukyselyssä : mittarin reliabiliteettija rakennevaliditeettitarkastelua Ojala, Kristiina; Vuori, Mika; Välimaa, Raili; Tynjälä, Jorma; Kannas, Lasse
The Impact of Phenotypic Switching on Glioblastoma Growth and Invasion

The brain tumour glioblastoma is characterised by diffuse and infiltrative growth into surrounding brain tissue. At the macroscopic level, the progression speed of a glioblastoma tumour is determined by two key factors: the cell proliferation rate and the cell migration speed. At the microscopic level, however, proliferation and migration appear to be mutually exclusive phenotypes, as indicated by recent in vivo imaging data. Here, we develop a mathematical model to analyse how the phenotypic switching between proliferative and migratory states of individual cells affects the macroscopic growth of the tumour. For this, we propose an individual-based stochastic model in which glioblastoma cells are either in a proliferative state, where they are stationary and divide, or in motile state in which they are subject to random motion. From the model we derive a continuum approximation in the form of two coupled reaction-diffusion equations, which exhibit travelling wave solutions whose speed of invasion depends on the model parameters. We propose a simple analytical method to predict progression rate from the cell-specific parameters and demonstrate that optimal glioblastoma growth depends on a non-trivial trade-off between the phenotypic switching rates. By linking cellular properties to an in vivo outcome, the model should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.
Extraction of Semantic Clusters for Terminological Information Retrieval from MRDs

This paper describes a semantic clustering method for data extracted from machine readable dictionaries (MRDs) in order to build a terminological information retrieval system that finds terms from descriptions of concepts. We first examine approaches based on ontologies and statistics, before introducing our analogy-based approach that lets us extract semantic clusters by aligning definitions from two dictionaries. Evaluation of the final set of clusters for a small set of definitions demonstrates the utility of our approach.
Research on the Relationship of Surface Temperature and Urban Heat Island Using the Thermal Infrared Remote Sensing Image

The temperature of the earth's land surface plays a very import ant role in the land-air interactions. It is critical parameters in the research of global change. Therefore, the use of satellite remote sensing data for surface temperature retrieval has become an important task of the study. Regional surface temperature is an important parameter of thermal energy distribution in the region, to obtain which is the most convenient and effective method. Thermal infrared remote sensing is an important area, and from thermal infrared remote sensing image information extracting temperature is a prerequisite for applying thermal infrared remote sensing technology . Based on remote sensing image data reading, radiometric calibration, regional cropping pretreatment; Then Landsat band 6 inversion of surface brightness temperature, It introduces the effect of the urban heat island using Landsat remote sensing ,having obtained the changes of spatial distribution of surface temperature, and prospects for future development in this field.
A Robot With Personality: Interacting With a Group of Humans

robots are becoming more and more common in our lifes. The personality of a robot determines how the robot is perceived. Before only dyadic interactions were examined to improve the social robots, but robots are, depending on the spatial configuration, likely to interact with multiple humans at the same time. Therefore it is important to understand what the effects of group interactions are on the perception of the robot, so robots can be optimized for both types of interactions. In this study the effects of group interactions and robot personality on the perception of the robot are examined. 21 students watched one video in which a robot was performing a teacher task. The robots extraversion and the type of interaction (dyadic vs group) was manipulated in each video. The students then completed an online survey with several scales describing the robots personality traits. Statistical analysis showed that the type of interaction combined with the robot personality does have an effect on how the robot is perceived. Introvert robots are considered more intelligent in group interactions, while extravert robots are more intelligent in dyadic interactions. There is also a bit of evidence for the type of interactions affecting the fun and likeability of the robot. Both findings indicate that the type of interaction is affecting the way a robot is being perceived, therefore it is important to do further research on this subject in order to make the most sufficient social robots.
Exploring Alignment of Community College Students for Preparedness and Achievement of Basic Skills

This mixed-method study explored the alignment of expected student learning outcomes (SLOs) and expected student entrance skills, as stated within “course outlines of record” (CORs), for basic skills courses in one California community college district. Researchers evaluated consistencies and discrepancies in course alignment. There were some occasional redundancies and gaps in skills across some course sequences. Still, the overall data suggested that across the majority of course sequences, expected SLOs and entrance skills align well between sequential courses and with the culminating college-level courses. These patterns of alignment within the basic skills curricula at this community college represent a well-conceived and logical progression of learning for students, which supports the “scaffolding” concept used as a theoretical foundation of this study. When actual enrollment patterns for students were examined, the intentional alignment of courses was not necessarily honored by students’ enrollment behavior. This finding suggests that faculty planning of course sequencing is not fully supported by institutional practice. To ensure that faculty intended course sequencing is not disregarded, the researchers offer recommendations for the entire system of community colleges to consider, rather than individual institutions. As such, this study puts forward a five-step ALIGN-model for community colleges to follow in order to integrate the basic skills curriculum that supports student learning and success in college.
Soviet Education and Comparative Research-a German view

The forces of reform that have been unleashed in the Soviet Union over the last few years and have since been making themselves felt elsewhere in Eastern Europe have been observed with a mixture of fascination and hopeful anticipation by the world at large. Glasnost and perestroika have become everyday expressions in the political vocabulary of Western languages. The 'new political thinking' which is to assist in surmounting the crisis in the economic and political system does not even draw the line at tackling ideological dogma and political and historical taboos hitherto regarded as inviolable. Many of the old ideological patterns of thought no longer provide a reliable basis for a fundamental reform of society. New modes of thinking and orientation guide-lines are being sought as a result of the freer and less inhibited opportunities for taking stock of affairs in the world outside. Such interest is particularly directed towards the Western capitalist world, with regard not only to its lead in the field of technological development but also to the underlying conditions of the economic and socio-political system. This interest in finding strategic patterns and practical examples which can be applied to the reconstruction of the Soviet economy and to stimulating the necessary processes of social change is focussed mainly on Japan and the USA, though developments in Sweden, the Federal Republic of Germany (FRG) or England are being carefully studied to see if certain solutions can be transferred to the Soviet situation.
On the futility of thermal through-silicon-vias

Thermal integrity is one of the most important challenges faced by three-dimensional integrated circuits (3D ICs). Towards this, thermal through-silicon-vias (TTSVs) have been widely used to assist heat dissipation. The metal inside TTSVs can conduct heat more effectively than the silicon substrate, and the metal bumps underneath TTSVs can help heat penetrate through the inter-layer thermal interface material (TIM). However, the surrounding silicon dioxide blocks the heat flowing into them. This makes the effectiveness of TTSVs questionable. In this paper, we argue that some existing TTSV models fail to capture those effects. Experimental results based on finite element simulations verify and confirm that the temperature reduction is indeed brought by the metal bumps underneath the TTSVs rather than the TTSVs themselves. We demonstrate that it is sufficient to add bumps between tiers to reduce temperature without wasting silicon area.
Using Social Media and Mobile Technologies to Foster Engagement and Self-Organization in Participatory Urban Planning and Neighbourhood Governance

This editorial explores the potential of social media and mobile technologies to foster citizen engagement and participation in urban planning. We argue that there is a lot of wishful thinking, but little empirically validated knowledge in this emerging field of study. We outline key developments and pay attention to larger societal and political trends. The aim of this special issue is: 1) To offer a critical state-of-the-art overview of empirical research; and 2) to explore whether social media and mobile technologies have measurable effects on citizens' engagement beyond traditional mobilization and participation tools. We find that wider engagement only ‘materializes’ if virtual connections also manifest themselves in real space through concrete actions, by using both online and offline engagement tools. Another requirement is that planners do not seek to marginalize dissenting voices in order to promote the interests of powerful developers.
Mineralocorticoid receptor overexpression in forebrain decreases anxiety-like behavior and alters the stress response in mice

Although numerous stress-related molecules have been implicated in vulnerability to psychiatric illness, especially major depression and anxiety disorders, the role of the brain mineralocorticoid receptor (MR) in stress, depression, and affective function is not well defined. MR is a steroid hormone receptor that detects circulating glucocorticoids with high affinity and has been primarily implicated in controlling their basal level and circadian rhythm. To specifically address the role of MR in hypothalamic-pituitary-adrenal axis activity and anxiety-related behaviors, we generated transgenic mice with increased levels of MR in the forebrain (MRov mice) by using the forebrain-specific calcium/calmodulin-dependent protein kinase II α promoter to direct expression of MR cDNA. A mild but chronic elevation in forebrain MR results in decreased anxiety-like behavior in both male and female transgenic mice. Female MRov mice also exhibit a moderate suppression of the corticosterone response to restraint stress. Increased forebrain MR expression alters the expression of two genes associated with stress and anxiety, leading to a decrease in the hippocampal glucocorticoid receptor (GR) and an increase in serotonin receptor 5HT-1a, consistent with the decreased anxiety phenotype. These data suggest that the functions of forebrain MR may overlap with GR in hypothalamic-pituitary-adrenal axis regulation, but they dissociate significantly from GR in the modulation of affective responses, with GR overexpression increasing anxiety-like behavior and MR overexpression dampening it. These findings point to the importance of the MR:GR ratio in the control of emotional reactivity.
An equivalence-preserving CPS translation via multi-language semantics

Language-based security relies on the assumption that all potential attacks follow the rules of the language in question. When programs are compiled into a different language, this is true only if the translation process preserves observational equivalence. To prove that a translation preserves equivalence, one must show that if two program fragments cannot be distinguished by any source context, then their translations cannot be distinguished by any target context. Informally, target contexts must be no more powerful than source contexts, i.e., for every target context there exists a source context that "behaves the same. " This seems to amount to being able to "back-translate" arbitrary target terms. However, that is simply not viable for practical compilers where the target language is lower-level and, thus, contains expressions that have no source equivalent. In this paper, we give a CPS translation from a less expressive source language (STLC) to a more expressive target language (System F) and prove that the translation preserves observational equivalence. The key to our equivalence-preserving compilation is the choice of the right type translation: a source type σ mandates a set of behaviors and we must ensure that its translation σ+ mandates semantically equivalent behaviors at the target level. Based on this type translation, we demonstrate how to prove that for every target term of type σ+, there exists an equivalent source term of type σ- even when sub-terms of the target term are not necessarily "back-translatable" themselves. A key novelty of our proof, resulting in a pleasant proof structure, is that it leverages a multi-language semantics where source and target terms may interoperate.
Generalized loop‐erased random walks and approximate reachability

In this paper we extend the loop‐erased random walk (LERW) to the directed hypergraph setting. We then generalize Wilson's algorithm for uniform sampling of spanning trees to directed hypergraphs. In several special cases, this algorithm perfectly samples spanning hypertrees in expected polynomial time. Our main application is to the reachability problem, also known as the directed all‐terminal network reliability problem. This classical problem is known to be # P‐complete, hence is most likely intractable (Ball and Provan, SIAM J Comput 12 (1983) 777–788). We show that in the case of bi‐directed graphs, a conjectured polynomial bound for the expected running time of the generalized Wilson algorithm implies a FPRAS for approximating reachability. Copyright © 2012 Wiley Periodicals, Inc. Random Struct. Alg. , 44, 201‐223, 2014