Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring User-generated Data Visualization in the Accommodation Sector

An important part of our information-gathering behavior has always been to find out what other people think. People now actively use information technologies to seek out and understand the opinions of others. This is due to the availability and popularity of opinion-rich resources such as online review sites and blogs. The accommodation sector is one of those where the guest opinion dictates its future. This sector needs to adapt and update the services they offer to their guests in order to stay competitive. In this paper we outline the potential use of tree-oriented visual techniques to map 1500 online reviews collected from 50 small and medium hotels (SMH). Our goal is to deliver visually the results of these reviews as straightforward and intuitively as possible to the accommodation managers, enabling them use it to support their decision making.
ATTACKING THE ARTICULATION PROBLEM IN TEACHER EDUCATION

A continuing challenge for preservice teacher education is the articulation between initial training and subsequent practice. This study investigated the effect of a fully elaborated training model on the transfer of complex teaching strategies into the practice of first year graduates. A cohort of 30 graduates was followed through their first year of full-time teaching to determine the frequency and appropriateness of their use of two complex teaching strategies, Concept Attainment and Inductive Thinking (Joyce and Weil, 1996). Although only some 10% of inservice teachers transfer new learning into their active teaching repertoires without workplace support for their new behaviours (Joyce and Showers, 1995), the first year teachers in this cohort achieved transfer rates of 40% and 27% respectively for each of the strategies. Students attributed their success in transferring complex teaching models into their beginning repertoires to the intensive training program completed at university. Discussion of results includes analysis of program design as well as planned program changes to facilitate yet higher rates of transfer of key teaching skills.
Real-time detection of PRT 1-mediated ubiquitination via fluo-1 rescently labeled substrate probes 2 3

1 Independent Junior Research Group on Protein Recognition and Degradation, Leibniz Institute of Plant Biochemistry 8 (IPB), Weinberg 3, D-06120 Halle (Saale), Germany 9 2 ScienceCampus Halle – Plant-based Bioeconomy, Betty-Heimann-Str. 3, D-06120 Halle (Saale), Germany 10 3 Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry (IPB), Weinberg 3, D-06120 Halle (Saale), 11 Germany 12 4 present address: Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, 11 Arany Janos, Cluj-Napoca, 13 Romania 14 5 present address: Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, D-37077 Göttingen, Germany 15 16 17 * Correspondence should be addressed to N.D. (nico.dissmeyer@ipb-halle.de). 18 19 20 21 RUNNING TITLE 22 Live assays with fluorescent N-end rule substrates 23
Secrecy-Based Energy-Efficient Data Offloading via Dual Connectivity Over Unlicensed Spectrums

Offloading cellular mobile users' (MUs') data traffic to small-cell networks is a cost-effective approach to relieve congestion in macrocell cellular networks. However, as many small-cell networks operate in the unlicensed bands, the data offloading might suffer from a security issue, i.e., some eavesdropper could overhear the offloaded data over unlicensed spectrums. This motivates us to investigate a secrecy-based energy-efficient uplink data offloading scheme. Specifically, we consider the recent paradigm of traffic offloading via dual connectivity, which enables an MU to simultaneously deliver traffic to a macro base station (mBS) over the licensed channel and a small-cell access point (sAP) over the unlicensed channel. We formulate an MU's joint optimization of traffic scheduling and power allocation problem, with the objective of minimizing the total power consumption while meeting both the MU's traffic demand and secrecy requirement. Despite the non-convex nature of the joint optimization problem, we propose an efficient algorithm to compute the optimal offloading solution. By evaluating the impact of the MU's secrecy requirement and the eavesdropper's channel condition, we quantify the conditions under which the optimal offloading solution corresponds to the full-offloading and zero-offloading, respectively. Numerical results validate the optimal performance of our proposed algorithm, and show that the optimal offloading can significantly reduce the total power consumption compared with some fixed offloading schemes. Based on the optimal offloading solution for each MU, we further analyze the scenario of multiple MUs and sAPs, and investigate how to optimally exploit the sAPs' total offloading capacity to serve the MUs while accounting for the MUs' corresponding power consumptions for offloading data. To this end, we formulate a total network-benefit maximization problem that accounts for the reward for serving the MUs successfully, the mBS's bandwidth usage, and the MUs' power consumptions. Numerical results show that the optimal solution can improve the total network benefit compared with some heuristic sAP-selection scheme.
The quantitative study of shape and pattern perception.

The pre-eminent importance of formal or relational factors in perception has been abundantly demonstrated during some forty years of gestalt psychology. It seems extraordinary, therefore, that so little progress has been made (and, indeed, that so little effort has been expended) toward the systematizing and quantifying of such factors. Our most precise knowledge of perception is in those areas which have yielded to psychophysical analysis (e.g., the perception of size, color, and pitch), but there is virtually no psychophysics of shape or pattern. Several difficulties may be pointed out at once: (a) Shape is a multidimensional variable, though it is often carelessly referred to as a "dimension," along with brightness, hue, area, and the like, (b) The number of dimensions necessary to describe a shape is not fixed or constant, but increases with the complexity of the shape, (c) Even if we know how many dimensions are necessary in a given case, the choice of particular descriptive terms (i.e., of referenceaxes in the multidimensional space with which we are dealing) remains a problem; presumably some such terms have more psychological meaningfulness than others.
The pH-Responsive Regulon of HP0244 (FlgS), the Cytoplasmic Histidine Kinase of Helicobacter pylori

ABSTRACT Helicobacter pylori colonizes the acidic gastric environment, in contrast to all other neutralophiles, whose acid resistance and tolerance responses allow only gastric transit. This acid adaptation is dependent on regulation of gene expression in response to pH changes in the periplasm and cytoplasm. The cytoplasmic histidine kinase, HP0244, which until now was thought only to regulate flagellar gene expression via its cognate response regulator, HP0703, was found to generate a response to declining medium pH. Although not required for survival at pH 4.5, HP0244 is required for survival at pH 2.5 with 10 mM urea after 30 min. Transcriptional profiling of a HP0244 deletion mutant grown at pH 7.4 confirmed the contribution of HP0244 to σ54 activation via HP0703 to coordinate flagellar biosynthesis by a pH-independent regulon that includes 14 flagellar genes. Microarray analysis of cells grown at pH 4.5 without urea revealed an additional 22 genes, including 4 acid acclimation genes (ureA, ureB, ureI, and amiE) that are positively regulated by HP0244. Additionally, 86 differentially expressed genes, including 3 acid acclimation genes (ureF, rocF [arginase], and ansB [asparaginase]), were found in cells grown at pH 2.5 with 30 mM urea. Hence, HP0244 has, in addition to the pH-independent flagellar regulon, a pH-dependent regulon, which allows adaptation to a wider range of environmental acid conditions. An acid survival study using an HP0703 mutant and an electrophoretic mobility shift assay with in vitro-phosphorylated HP0703 showed that HP0703 does not contribute to acid survival and does not bind to the promoter regions of several genes in the HP0244 pH-dependent regulon, suggesting that there is a pathway outside the HP0703 regulon which transduces the acid-responsive signal sensed by HP0244.
Intrahost Diversity of Feline Coronavirus: A Consensus between the Circulating Virulent/Avirulent Strains and the Internal Mutation Hypotheses?

To evaluate the most controversial issue concerning current feline coronavirus (FCoV) virology, the coexisting hypotheses of the intrahost and interhost origins of feline infectious peritonitis virus (FIPV) in regard to the pathogenesis of feline infectious peritonitis (FIP), this study aimed to assess the molecular diversity of the membrane gene FCoVs in 190 samples from 10 cats with signs of FIP and in 5 faecal samples from cats without signs of FIP. All samples from the non-FIP cats and 25.26% of the samples from the FIP cats were positive for the FCoV membrane (M) gene. Mutations in this gene consisted of SNP changes randomly scattered among the sequences; few mutations resulted in amino acid changes. No geographic pattern was observed. Of the cats without FIP that harboured FECoV, the amino acid sequence identities for the M gene were 100% among cats (Cats 1–3) from the same cattery, and the overall sequence identity for the M gene was ≥91%. In one cat, two different lineages of FCoV, one enteric and one systemic, were found that segregated apart in the M gene tree. In conclusion, the in vivo mutation transition hypothesis and the circulating high virulent-low virulent FCoV hypothesis have been found to be plausible according to the results obtained from sequencing the M gene.
Methods for Qualitative Spatial Reasoning

The theoretical properties of qualitative spatial reasoning in the RCC-8 framework have been analyzed extensively. However, no empirical investigation has been made yet. Our experiments show that the adaption of the algorithms used for qualitative temporal reasoning can solve large RCC-8 instances, even if they are in the phase transition region { provided that one uses the maximal tractable subsets of RCC-8 that have been identi ed by us. In particular, we demonstrate that the orthogonal combination of heuristic methods is successful in solving almost all apparently hard instances in the phase transition region up to a certain size in reasonable time.
Research Directions in Handheld AR

Handheld mobile devices are an exciting new platform for Augmented Reality (AR). Mobile phones and PDAs have the potential to provide AR experiences to hundreds of millions of consumers. However, before widespread use can occur there are some obstacles that must be overcome. In particular, developers must consider the hardware and software capabilities of mobile devices and how these can be used to provide an effective AR experience. They must also develop AR interaction metaphors suitable for handheld AR. In this paper we review current and previous research in the field, provide design guidelines and outline future research directions.
Reasoning about Interactions between Variables

Thinking about interactions between variables is a necessary condition for accurate scientific thinking. The purpose of this study was to investigate difficulties in thinking about interactions between variables and to suggest remedial educational means. A conceptual analysis distinguishes between valid interaction inferences, invalid interaction inferences, and limited inferences which can be seen as a partial or a primitive interaction inference. Empirical findings show that expert thinkers demonstrate thinking about interactions at both an operational and a metastrategic level. Some lay-adults however, although able to draw many limited inferences, encounter substantial difficulties in drawing valid interaction inferences while engaged in an investigation of a scientific sort. Four types of difficulties were identified in this study: lack of a “double set of controlled comparisons” strategy that is necessary for valid inferences about interacting variables; lack of the conceptual framework for interacting factors; diversion of attention to other features; and difficulty in maintaining the necessary control of other variables. The implications of the findings to science curriculum are discussed.
Antidepressant-Like Effect of the Norepinephrine-Dopamine Reuptake Inhibitor Bupropion in a Mouse Model of Huntington's Disease with Dopaminergic Dysfunction.

BACKGROUND The pre-motor stages of Huntington's disease (HD) are commonly associated with psychiatric manifestations including depression. Recent clinical data indicate that dopaminergic dysfunction is common in both symptomatic and pre-manifest HD gene carriers. There is also increasing evidence implicating catecholamine dysfunction in the pathophysiology of depression. OBJECTIVE In this study, we aimed to functionally investigate the dopaminergic system in the R6/1 mouse model of HD prior to onset of motor symptoms. METHODS We assessed the effects of acute administration of bupropion (a dopamine-norepinephrine reuptake inhibitor) on spontaneous locomotor activity and depression-like behaviour (using the forced-swim test). RESULTS Here we show that the bupropion-induced increased locomotor activity found in wild-type animals was no longer observed in HD mice. We also found that acute administration with bupropion rescued depressive-like behaviours in HD animals, possibly through dopamine D2/D3 receptor mechanisms. CONCLUSION Our present data are the first in vivo evidence of an impaired dopamine D1 receptor-dependent function in pre-motor symptomatic R6/1 HD mice. Moreover, our findings suggest clinical potential for bupropion to alleviate depressive symptoms in HD.
Left ventricular dyssynchrony in patients with left bundle branch block and patients after myocardial infarction: integration of mechanics and viability by cardiac magnetic resonance.

AIMS To quantify left ventricular (LV) dyssynchrony in patients with left bundle branch block (LBBB) and in patients after myocardial infarction (MI) applying an accelerated three-dimensional (3D) tagging cardiac magnetic resonance (CMR) technique, and to combine dyssynchrony information with viability data obtained by late gadolinium enhancement (LGE) CMR. METHODS AND RESULTS Thirty-two patients (59 +/- 11 years) after first MI (Pats(MI)), 10 patients (63 +/- 10 years) with LBBB (ejection fraction < 40%; Pats(LBBB<40)), 13 patients (63 +/- 11) with LBBB (ejection fraction >or= 40%; Pats(LBBB >or=40 )), and 15 healthy controls (53 +/- 10 years) underwent 3D tagging CMR and LGE imaging at 1.5 T. As a measure of mechanical LV dyssynchrony, the standard deviation of T(max) over the LV, the circumferential uniformity ratio estimate (CURE) index, and a segmental-based circumferential systolic dyssynchrony index (SDI) were calculated. All three parameters detected significantly increased circumferential dyssynchrony in patients compared with controls. The CURE and SDI showed a good correlation (r = 0.93, P < 0.0001) and detected most severe dyssynchrony in Pats(LBBB<40) (P < 0.001 vs. controls, P < 0.005 vs. Pats(MI)). Systolic dyssynchrony index additionally allowed integration of localized viability information to yield SDI(viable) which was highest in Pats(LBBB<40). CONCLUSION Dyssynchrony patterns in the LV can be quantified globally and regionally by 3D tagging CMR. Combination of viability and dyssynchrony information allows for a comprehensive dyssynchrony quantification in patients with LBBB or post-MI. Future studies are required to test the value of the method to predict responsiveness to resynchronization.
Thermodynamics of cercarial development and emergence in trematodes

SUMMARY Temperature is an important factor influencing the biology of ectothermic organisms and is intrinsically linked to climate change. Trematodes are potentially susceptible to temperature changes and in order to develop predictive frameworks of their responses to climate change large-scale analyses are needed. The present study, using the Q10 value, analyses experimental data from the scientific literature on the effects of temperature on cercarial development and emergence across a wide range of temperature in low (⩽35°) and mid-latitude (36–60°) species. Temperature appears to have no significant effect on the rate of development of cercariae within molluscan hosts. Data on cercarial emergence, corrected to incorporate the minimum emergence temperature threshold (METT) and acclimation status, was found to be largely unaffected by temperature over optimum ranges of ≈20 °C (15–25 °C) for mid-latitude species and ≈25 °C (20–30 °C) for low-latitude species. In addition, a decline in emergence rates was shown at higher temperatures. These results are contrary to a previous study on the meta-analysis of cercarial emergence. Some evidence of strain-specific differences and thermostability over a wide temperature range for both cercarial development and emergence was apparent. The significance of these results in furthering our understanding of cercarial biology under natural conditions is discussed.
Effects of head shape on EEGs and MEGs

Results are presented of computer modeling studies of the effects of head shape on electroencephalograms (EEGs) and magnetoencephalograms (MEGs) and on the localization of electrical sources in the brain using these measurements. The effects of general, nonspherical head shape are determined by comparisons of EEG and MEG maps from nonspherical head models with corresponding maps from a spherical head model. The effects on source localization accuracy are determined by calculating moving dipole inverse solutions in a spherical head model using EEGs and MEGs from the nonspherical models and comparing the solutions with those for known sources. It was found that nonspherical head shape can produce significant changes in the maps produced by some sources in the cortical region of the brain but produce localization errors of less than approximately 1 cm. No significant differences in the effects of such deviations on EEGs and MEGs were found. <<ETX>>
The Role of Family‐Centered Care in Research: Supporting the Social Communication of Children With Autism Spectrum Disorder

Families and their children with special healthcare needs require effective interventions to address children's needs in the context of daily family interactions. This article offers a unique perspective to understanding the role of family-centered care. It extends beyond expected practice in service delivery to the role of families in the implementation of intervention research, specifically when collaborating with families of children with autism spectrum disorder. Two intervention studies are described involving children with autism spectrum disorder and their families and the application of principles of family-centered care. Elements of family-centered care demonstrated in the intervention research are summarized. Finally, specific challenges are described associated with conducting family-centered intervention research and suggestions are offered to clinical researchers to inform future research endeavors.
Recursive EM algorithm for finite mixture models with application to Internet traffic modeling

In the past decade, many quantities characterizing high-speed telecommunication network performance have been reported to have heavy-tailed distributions, namely, with tails decreasing hyperbolically rather than exponentially. Since mixture distributions can approximate many heavy-tailed distributions with high precision, the paper uses mixture distributions to model Internet traffic and applies the EM algorithm to fit the models. Making use of the fact that, at each iteration of the EM algorithm, the parameter increment has a positive projection on the gradient of the likelihood function, the paper proposes a recursive EM algorithm to fit the models, and the Bayesian information criterion is applied to select the best model. To illustrate the efficiency of the proposed algorithm, numerical results and experimental results on real traffic are provided.
Characterizing User Mobility from the View of 4G Cellular Network

The mobility models obtained from mobile data are expected to affect numbers of fields, including urban planning, road traffic engineering, human sociology, epidemiology of infectious diseases, or telecommunication networks. Current user mobility models are mainly extracted from Call Detail Records (CDR) data or WiFi traces. However, CDR data only captures user movements during telephone calls or short message service (SMS) and WiFi traces can not provide intuitive understanding to mobility behavior of cellular network users in large scale. In this paper, we take the first step to investigate if the characteristics of mobility derived from 4G cellular data network is different from the previous findings utilizing other data sources, especially the widely used, CDR based approach. Utilizing our Hadoop based mobile big data processing platform together with a systematic analysis framework of user mobility, we present a comprehensive characterization of the mobility models from the 6 Terabyte (TB) 4G data traffic. Through the comparison with CDR models and 3G models from the view of user occurrence patterns, user movement patterns and dominant locations of users, we find that the 4G data traffic can provide finer granularity of mobility and location information.
Learning Multifaceted Latent Activities from Heterogeneous Mobile Data

Inferring abstract contexts and activities from heterogeneous data is vital to context-aware ubiquitous applications but still remains one of the most challenging problems. Recent advances in Bayesian nonparametric machine learning, in particular the theory of topic models based on Hierarchical Dirichlet Process (HDP), has provided an elegant solution towards these challenges. However, limited existing methods have addressed the problem of inferring latent multifaceted activities and contexts from heterogeneous data sources such as those collected from mobile devices. In this paper, we extend the original HDP to model heterogeneous data using a richer structure of the base measure being a product-space. The proposed model, called product-space HDP (PS-HDP), naturally handles the heterogeneous data from multiple sources and identify the unknown number of latent structures in a principle way. Although this framework is generic, our current work primarily focuses on inferring (latent) threefold activities of who-when-where simultaneously, which corresponds to inducing activities from data collected for identity, location and time. We demonstrate our model on synthetic data as well as on a real-world dataset – the StudentLife dataset. We report results and provide analysis on the discovered activities and patterns to demonstrate the merit of the model. We also quantitatively evaluate the performance of PS-HDP model using standard metrics including F1-score, NMI, RI, purity, and compare them with well-known existing baseline methods.