Miracle-dz/UniFAR-FTUs huggingface dataset:
The Factors Affecting Perceived Playability of Hardcore and Casual Players in Online Role-Playing Games

Purpose-A new design concept, playability, has emerged and been advocated as a decisive factor for players' gameplay experiences. The present study intends to identify what playability factors might affect players' gaming experiences, particularly from the perspective of individual motivation. Design/methodolgy/approach-According to the game heuristics and playability design guidelines, the present study developed and managed a wide-scale survey to investigate the determinants of playability, reflecting hardcore and casual players' RPG gaming experiences. Finding-The survey results revealed that the Gameplay dimension is primary decisive factor leading players to value the playability of an online role-playing game, following by Game Interface and then Game Mechanics. From the hardcore players' point of view, Gameplay is definitely more important than Game Interface, while Game Interface is equally important to Game Mechanics. From the casual players' point of view, Gameplay is positioned at the same critical level as Game Interface while Game Interface has a stronger impact than Game Mechanics. Research limitations/implications-The results of the present study can merely provide information of which design factors of playability might be deemed important by players from the perspective of individual motivation. In addition, although the emotion issue is highly related to the psychological dimension of the player's gaming experience, it wasn't included in this investigation due to the limitation of the survey method, and the match between issues of emotion and playability has yet to be specified. Practical implications and originality/value-From the survey results of the present study, it provides a useful design reference for game developers. What players consider to be a good game largely lies more on the hedonistic level than on the ergonomic level. In other words, usability design in online role-playing game environments comes second to the emotional elements.
Discriminating real from fake smile using convolution neural network

In our society, sometime we hide our genuine feeling and emotion and purposely express different emotion in front of our surrounding folks. But as it's not actually a natural emotion, hence, it is more or less, predictable by others. Human vision system has enormous capability to recognizing genuine and fake smile of an individual. Discriminating genuine and fake smile is very thought-provoking task and even though very smaller amount of research has been carried out in this topic. In this paper, we are exploring a method to distinguish real from fake smile with high precision by using convolution neural networks (CNN). System has been train with FERC-2013 dataset having seven types of emotions namely happy, sad, disgust, angry, fearful, surprised and neutral. Emotions percentages of real and fake face are recorded by the emotion detection system. Based on recorded score, we investigate the effect of various percentages of emotions presented on both faces and then we are going to classify the smile on the face is real or fake.
Serum concentration of dehydroepiandrosterone sulfate and testosterone in women with severe atopic eczema/dermatitis syndrome.

BACKGROUND Although a growing body of evidence indicates that androgens modulate immune response and certain alterations in sex hormone metabolism and balance are thought to predispose an individual to immune-mediated diseases, few studies have investigated the role of androgens in atopic eczema/dermatitis syndrome (AEDS). OBJECTIVE We evaluated serum concentration of dehydroepiandrosterone sulfate (DHEA-S) and total testosterone in women with severe AEDS to characterize the hormonal milieu of such patients. METHODS Serum concentrations of DHEA-S and total testosterone in 13 female patients with severe AEDS were compared with concentrations in weight- and age-matched healthy controls. Measurement was by electrical chemiluminescence immunoassay. RESULTS There were no significant differences in serum concentrations of DHEA-S or testosterone between the 2 groups. We found no correlation between serum concentrations of DHEA-S and total immunoglobulin E. CONCLUSION This small study suggests there may be no abnormalities in peripheral blood concentrations of DHEAS-S and total testosterone in women with severe AEDS.
Phase Separations in Mixtures of a Nanoparticle and a Liquid Crystal

Liquid crystal suspensions including variousmicroand nano-colloidal particles have recently been received great attention for many practical applications such as nanosensors and devices, etc. When large colloidal particles of micronscale are dispersed in a uniform nematic liquid crystal phase, the colloidal particles disturb a long-range orientational order of the nematic phase. For a strong anchoring between the colloidal surface and a liquid crystal, different defect structures such as hedgehogs or Saturn rings can appear around a single colloidal particle, due to strong director deformations. (Fukuda, 2009; Skarabot et.al., 2008; Stark, 2001) Experiments have also shown two-dimensional crystalline structures of colloidal particles. (Loudet et. al., 2004; Musevic et. al., 2006; Nazarenko et. al., 2001; Pouling et.al., 1997; Yada et. al., 2004; Zapotocky et.al., 1999) On the other hand, under a weak surface anchoring between the colloidal surface and a liquid crystal, the coupling to the orientational elasticity of the liquid crystals tends to expel the colloidal particles and the suspension shows a phase separation into an almost pure nematic phase coexisting with a colloidal rich phase. (Anderson et.al., 2001; Pouling et. al., 1994) Such phase separations induced by a nematic ordering have also been discussed in flexible polymers dispersed in a nematic liquid crystal. (Chiu & Kyu, 1999; Das & Ray, 2005; Dubaut et.al., 1980; Matsuyama & Kato, 1996; Shen & Kyu, 1995)
Deep Convolution Neural Network Application in Lung Nodule Detection on CT Images

Pulmonary cancer is the leading cause of cancer-related death worldwide, and early stage of pulmonary cancer detection using low-dose computed tomography (CT) could prevent millions of patients being killed every year. However, reading millions of those CT scans is an enormous burden for radiologists. Therefore, an immediate need is to read, detect and evaluation CT scans automatically and fast. In the paper, we propose a new implementation method which is an improved to SSD network that is suitable for lung-nodule detection and a 3D Deep Convolution Neural Network that is suitable for false positive reduction. A 3D network performs better than a 2D network as it also captures the vertical information of nodules. Also, leaky ReLUs are used to replace the ReLUs in all activation layers. Furthermore, we don’t apply any extra fully connected layers to speed-up the train process and also obtained good result. The team interpolated the original images and crop out a cube where centered as the given coordinations of all candidates, and apply the common data augmentation methods to balance the positive and negative samples. Finally result is evaluated by a free receive operating characteristic (FROC), and we reach the average sensitivity of 0.881 at 7 different false positive rates.
Behavioural Aspects of Postgraduate Students in Using Electronic Information Resources at the Library Eastern University, Sri Lanka

The introduction of computer technology in university libraries has made possible the use of information resources via the Internet or Intranet. Since the poor usage of digital resources by students as well as the staff of universities has strained these innovative efforts towards the next information era, there was a need to carry out research to examine the behavior in utilizing electronic information resources in higher educational institutions. The main objective of this study is to examine the behavioral intention to utilize electronic information resources by postgraduate students at the Eastern University, Sri Lanka (EUSL), applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The study was tested with a conceptual model using 208 postgraduate students. The study revealed that the facilitating-conditions and effort expectancy are highly significant to students’ behavioral intention to use electronic information resources at the library. Students’ computer experience moderated the relationship between facilitating-conditions and intention to use. The intention-to-use behavior highly impacts on students’ usage of electronic information resources. The developed model will assist other researchers to understand the students’ behavioural intention and influencing factors in respect to introducing new innovative technologies in libraries and it could be used by other higher education institutions to make decisions related to the investment in the modern library systems. Hence, this study recommends further researches to be covered in all the Sri Lankan Universities in order to generalize the results and findings.
CAPILLARY GROWTH FROM REVERSED RAT AORTIC SEGMENTS CULTURED IN COLLAGEN GEL

The process of angiogenesis from aortic segments turned inside out and embedded in collagen gel was studied. Two to three days after inoculation, fibroblastic cells migrated from both ends of the segments. Later, capillary sprouts also appeared from both ends of the segments but not from the outer surface, even though there was a covering of endothelial cells. If the outer surface was injured, capillaries sometimes appeared at the damaged site. This may suggest that endothelial cells have more affinity for basement membrane than collagen gel and that they migrate only from an injured site. Immuno‐histochemical staining demonstrated factor VHI‐related antigen in the capillary structures but not in the fibroblastic cells. Electron microscopically, capillary lumina were lined with several endothelial cells, and fibroblastic cells had the characteristics of smooth muscle cells. Since these fibroblastic cells have been known to appear under angiogenetic conditions in vivo, they may play an important role in angiogenesis, and the present culture technique may be a useful model for studying this process. ACTA PATHOL JPN 38: 1503∼1512, 1988.
Regulation of the SOS response analyzed by RecA protein amplification

A split UV light dose procedure was used in Escherichia coli to induce an SOS function, RecA protein amplification, which was measured by an immunoradiometric assay. The SOS system was partially induced after the first UV irradiation, and the inducing effects of subsequent identical UV doses were quantified. Variations in the inducing effects of successive UV doses were related to modulations of the SOS signal level during SOS induction. A reduction in the level of SOS signal was found after 20 min in the wild-type strain, hypothesized to result from negative control of repair functions. A few DNA repair mutants were tested by the same procedure; the uvrA, recF, and umuC genes were involved in SOS induction control, but we found differences in their respective kinetics of expression. On the contrary, in a recB mutant, only a slight effect was obtained on this control.
On Nearby-Fit Spatial Keyword Queries

Geo-textual data is ubiquitous nowadays, where each object has a location and is associated with some keywords. Many types of queries based on geo-textual data, termed as spatial keyword queries, have been proposed, and are to find optimal object(s) in terms of both its (their) location(s) and keywords. In this paper, we propose a new type of query called nearby-fit spatial keyword query (NSKQ), where an optimal object is defined based not only on the location and the keywords of the object itself, but also on those of the objects nearby. For example, in an application of finding a hotel, not only the location of a hotel but also the objects near the hotel (e.g., shopping malls, restaurants, and bus stops nearby) might need to be taken into consideration. The query is proved to be NP-hard, and in order to perform the query efficiently, we developed two approximate algorithms with small constant approximation factors equal to 1.155 and 1.79. We conducted extensive experiments based on both real and synthetic datasets, which verified our algorithms.
Domain rotations between open, closed and bullet-shaped forms of the thermosome, an archaeal chaperonin.

Three conformations of the thermosome, an archaeal group II chaperonin, have been determined by cryo-electron microscopy (EM). We describe an open form of the double-ring oligomer, a closed form and a bullet-shaped form with one ring open and the other closed. Domain movements have been deduced by docking atomic coordinates into the EM maps. The subunit apical domains, bearing the putative substrate binding sites, rotate about 30 degrees upwards and twist in the plane of the ring from the closed to the open conformation. The closed rings have their nucleotide binding pockets closed by the intermediate domains, but in the open rings, the pocket is accessible.
Integrating hidden Markov models based on Mixture-of-Templates and k-NN2 ensemble for activity recognition

This paper considers the activity recognition problem using inertial sensor data. It is a challenging temporal pattern recognition problem as the sensor data can be easily mixed with noise and also has large intra-class variation, resulting from different characteristic of people doing same activity, and interclass similarity among several similar activities. To handle these problems concentrating on the classification method, this paper proposes a novel ensemble scheme of hidden Markov models for activity recognition. To improve the performance of activity recognition, our method models the outputs of multiple hidden Markov models by using enhanced template-based classifier fusion method, in which multiple local templates are generated as Mixture-of-Templates, and k-NN2 ensemble method is proposed to elaborately recognize activities. To show the effectiveness of the proposed method, we carried out several experiments on UCI Human Activity Recognition dataset and compared our method with several alternative methods. As a result, our method outperforms other methods.
Apolipoproteins modulate the inflammatory response to lipopolysaccharide

An increasing body of evidence demonstrates a close interplay between lipoprotein metabolism and sepsis. Sepsis results in an increase of plasma triglycerides within VLDL as a consequence of an enhanced hepatic VLDL production and/or inhibited peripheral and hepatic VLDL clearance. In contrast, sepsis decreases plasma cholesterol within LDL and mainly HDL. The decrease in HDL is accompanied by a loss of mainly apoAI-containing particles, an almost total loss of apoCI, and an increase in apoE-containing HDL, as related to the effect of LPS on a wide range of apolipoproteins, plasma enzymes, lipid transfer factors, and receptors that are involved in HDL metabolism. Reciprocally, all lipoprotein classes have been shown to bind LPS and to attenuate the biological response to LPS in vitro and in rodents. Moreover, triglyceride-rich lipoproteins protect rodents against death from LPS and bacterial sepsis. Accumulating evidence indicates that apolipoproteins such as apoE and apoAI, and not the lipid moieties of the particles, may be responsible for these protective effects of lipoproteins. Therefore, to increase our understanding of the complex interaction between lipoprotein metabolism and sepsis, further studies that address the specific roles of apolipoproteins in sepsis are warranted.
Pan cancer patterns of allelic imbalance from chromosomal aberrations in 33 tumor types

Somatic copy number alterations (SCNAs), including deletions and duplications, serve as hallmarks of tumorigenesis. SCNAs may span entire chromosomes and typically result in deviations from an expected one-to-one ratio of alleles at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation (CBS) algorithm, providing segment mean copy number estimates from Affymetrix single-nucleotide polymorphism DNA microarray total (log R ratio) intensities, but not allele-specific (“B allele”) intensities that inform of AI. Here we seek to provide a TCGA-wide description of AI in tumor genomes, including AI induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH), using a powerful haplotype-based method applied to allele-specific intensities. We present AI summaries for all 33 tumor sites and propose an automated adjustment procedure to improve calibration of existing SCNA calls in TCGA for tumors with high levels of aneuploidy where baseline intensities were difficult to establish without annotation of AI. Overall, 94% of tumor samples exhibited AI. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p as well as mixed event types on 8p and 13q. The AI-based approach identified frequent cnLOH on 17p across multiple tumor sites, with additional site-specific cnLOH patterns. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.
Non-Markovian Infection Spread Dramatically Alters the Susceptible-Infected-Susceptible Epidemic Threshold in Networks

Most studies on susceptible-infected-susceptible epidemics in networks implicitly assume Markovian behavior: the time to infect a direct neighbor is exponentially distributed. Much effort so far has been devoted to characterize and precisely compute the epidemic threshold in susceptible-infected-susceptible Markovian epidemics on networks. Here, we report the rather dramatic effect of a nonexponential infection time (while still assuming an exponential curing time) on the epidemic threshold by considering Weibullean infection times with the same mean, but different power exponent ? For three basic classes of graphs, the Erd? s-Renyi random graph, scale-free graphs and lattices, the average steady-state fraction of infected nodes is simulated from which the epidemic threshold is deduced. For all graph classes, the epidemic threshold significantly increases with the power exponents ? Hence, real epidemics that violate the exponential or Markovian assumption can behave seriously differently than anticipated based on Markov theory.
Automated Recognition of Retinopathy of Prematurity with Deep Neural Networks

Retinopathy of Prematurity (ROP) is a blinding disease, which primarily occurs on premature infants whose birth weights is less than 1250 grams or gestation is less than 31 weeks. ROP has become the leading cause of preventable childhood blindness throughout the world. Nowadays, more and more researchers start attempting to develop auto or semi-auto methods based on digital image analysis to diagnose ROP. However, factors like high measurement errors or redundant analysis phrases make traditional analysis methods difficult to assist diagnose ROP perfectly. In this paper, we develop an automated system to analyse premature infants’ retinal images using deep neural networks. We primarily try to solve two problems. (1) the existence of ROP, normal or ROP; (2) the severity of ROP, mild-ROP or severe-ROP. Deep neural networks take the advantages of strong representation ability and enable to nonlinear mapping, attain high accuracies and great generalization performances on retinal fundus image datasets.
Medication Errors Reported in a Pediatric Intensive Care Unit for Oncologic Patients

Background: Considering all sources of errors that may occur during healthcare, medication errors are the most common and also the most frequent cause of adverse events. Objective: The objective of the study was to describe the medication errors reported in a pediatric intensive care unit for oncologic patients. Methods: This is a descriptive and exploratory study. The errors were reported by the professionals involved in the medication system in a medication error report form developed for the study. Results: The sample consisted of 110 medication errors reported on 71 forms. The omission error was the most common error type reported (22.7%), followed by administration error (18.2%). No harm to patients was reported in 83.1% of the notifications. Conclusion: The analysis of the110 medication errors provides evidence of the context of their occurrence and the need to implement measures that can prevent or intercept these errors. Implications for Practice: In an institution without adverse events report and a formal system to patient safety analysis, the implementation of a local nonpunitive approach to medication errors notification represented an important tool to patient safety promotion.
Impacts of Observational Constraints Related to Sea Level on Estimates of Climate Sensitivity

Reduced complexity climate models are useful tools for quantifying decision‐relevant uncertainties, given their flexibility, computational efficiency, and suitability for large‐ensemble frameworks necessary for statistical estimation using resampling techniques (e.g., Markov chain Monte Carlo). Here we document a new version of the simple, open‐source, global climate model Hector, coupled with a 1‐D diffusive heat and energy balance model (Diffusion Ocean Energy balance CLIMate model) and a sea level change module (Building blocks for Relevant Ice and Climate Knowledge) that also represents contributions from thermal expansion, glaciers and ice caps, and polar ice sheets. We apply a Bayesian calibration approach to quantify model uncertainties surrounding 39 model parameters with prescribed radiative forcing, using observational information from global surface temperature, thermal expansion, and other contributors to sea level change. We find the addition of thermal expansion as an observational constraint sharpens inference for the upper tail of posterior equilibrium climate sensitivity estimates (the 97.5 percentile is tightened from 7.1 to 6.6 K), while other contributors to sea level change play a lesser role. The thermal expansion constraint also has implications for probabilistic projections of global surface temperature (the 97.5 percentile for RCP8.5 2100 temperature decreases 0.3 K). Due to the model's parameterization of thermal expansion as an uncertain function of global ocean heat, we note a trade‐off between two ways of incorporating thermal expansion information: Ocean heat data provide a somewhat sharper equilibrium climate sensitivity estimate while thermal expansion data allow for constrained sea level projections.
The Relationship Between ADHD Symptomology and Decision Making

Objective: To explore the relationship between the symptoms of ADHD, the extent to which college students seek to maximize their decisions, and the degree to which students feel regret for their decisions. Method: Undergraduate students (N = 275) completed four questionnaires measuring ADHD symptomology, internal restlessness, maximization tendencies, and regret. It was hypothesized that (a) participants who reported more behaviors associated with ADHD and internal restlessness would report more maximizing tendencies, (b) participants reporting greater ADHD symptoms and internal restlessness symptoms would be more likely to report feelings of regret, (c) men would report more symptoms of ADHD and internal restlessness than women, and (d) men would be more likely to report maximization tendencies than women. Results: Findings supported the hypotheses and interaction were found. Conclusions: Findings provided new information concerning relationships between ADHD symptomology, internal restlessness, maximization tendencies, and regret.