Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Driven Season Characteristic Enhancement of Natural Image

We present a system of creating new scenes in different seasons from an input image captured in a particular season by stylizing it according to similar images in our library which includes a vast number of different season scenes and objects. Firstly, we transfer the color appearance of the input scene in accordance with the color style of other seasons scenes by using color transfer approach. Secondly, user scribbles are used to guide the detection of repeated elements in the input image and geometric information of these detected elements are obtained. Then context-sensitive objects of specified class that match most of the required properties are retrieved from our library and edited according to the geometric information of the specified elements in the scene, such as inserting new objects into the scene or replacing objects by new ones. After that, a repeated-elements-based modification duplication scheme is proposed and implemented to semi-automatically propagate the user-specified objects modification. Finally, blending is applied to the inserted objects to achieve consistency with the target scene in illumination. The main contribution of this work is that we present a complete system to create new scenes of different seasons.
Metabolic syndrome and insulin resistance in obese adolescents

Objective: To verify the prevalence of metabolic syndrome and insulin resistance in obese adolescents and its relationship with different body composition indicators. Methods: A cross-sectional study comprising 79 adolescents aged ten to 18 years old. The assessed body composition indicators were: body mass index (BMI), body fat percentage, abdominal circumference, and subcutaneous fat. The metabolic syndrome was diagnosed according to the criteria proposed by Cook et al. The insulin resistance was determined by the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) index for values above 3.16. The analysis of ROC curves was used to assess the BMI and the abdominal circumference, aiming to identify the subjects with metabolic syndrome and insulin resistance. The cutoff point corresponded to the percentage above the reference value used to diagnose obesity. Results: The metabolic syndrome was diagnosed in 45.5% of the patients and insulin resistance, in 29.1%. Insulin resistance showed association with HDL-cholesterol (p=0.032) and with metabolic syndrome (p=0.006). All body composition indicators were correlated with insulin resistance (p<0.01). In relation to the cutoff point evaluation, the values of 23.5 and 36.3% above the BMI reference point allowed the identification of insulin resistance and metabolic syndrome. The best cutoff point for abdominal circumference to identify insulin resistance was 40%. Conclusions: All body composition indicators, HDL-cholesterol and metabolic syndrome showed correlation with insulin resistance. The BMI was the most effective anthropometric indicator to identify insulin resistance.
Origin of complex quantum amplitudes and Feynman's rules

Complex numbers are an intrinsic part of the mathematical formalism of quantum theory and are perhaps its most characteristic feature. In this article, we show that the complex nature of the quantum formalism can be derived directly from the assumption that a pair of real numbers is associated with each sequence of measurement outcomes, with the probability of this sequence being a real-valued function of this number pair. By making use of elementary symmetry conditions, and without assuming that these real number pairs have any other algebraic structure, we show that these pairs must be manipulated according to the rules of complex arithmetic. We demonstrate that these complex numbers combine according to Feynman's sum and product rules, with the modulus-squared yielding the probability of a sequence of outcomes.
A tool for reliability and availability prediction

As the number of embedded systems in everyday usage has been increasing at an enormous rate recently, the demand for reliable and readily available systems is continuously growing. Problems in reliability and availability are typically detected after system implementation, when fault correction and modifications are difficult and expensive to implement. This is why a new method has been developed for predicting reliability and availability already from architectural models. However, to be beneficial in system development, the prediction method should enable quick, easy and repeatable quality analysis. Therefore, the different procedures and features of the method require tool support. Our contribution is the tool that supports reliability and availability prediction at the architectural level. The tool enables a representation of these two quality attributes in the architecture, and assists in analyzing system reliability and availability using architectural models. The tool has been tested and validated by using it for reliability and availability prediction in a case example.
A New Type of Contact Shape Meter and Its Industry Application

A contact shape meter with new structure, called MPIBPST(Multi-Roll-Piece Inner Bore Piezomagnetic Sensor Type) shape meter, for cold-rolled steel strip is developed, and it is applied to 1050II HC mill. Optimization design on the structure of shape meter roll is carried out and shape signal is compensated properly from several perspectives, for example, shape meter roll deflection, strip temperature and amplitude-frequency characteristic, etc. The application result shows that the MPIBPST shape meter has the advantages of rational structure, stronger anti-interference ability, signal stability and credibility, high-precision and a long service life.
Detecting Compromised Email Accounts from the Perspective of Graph Topology

While email plays a growingly important role on the Internet, we are faced with more severe challenges brought by compromised email accounts, especially for the administrators of institutional email service providers. Inspired by the previous experience on spam filtering and compromised accounts detection, we propose several criteria, like Success Outdegree Proportion, Reverse Pagerank, Recipient Clustering Coefficient and Legitimate Recipient Proportion, for compromised email accounts detection from the perspective of graph topology in this paper. Specifically, several widely used social network analysis metrics are used and adapted according to the characteristics of mail log analysis. We evaluate our methods on a dataset constructed by mining the one month (30 days) mail log from an university with 118,617 local users and 11,460,399 mail log entries. The experimental results demonstrate that our methods achieve very positive performance, and we also prove that these methods can be efficiently applied on even larger datasets.
Special Issue: Practicing Collaboration Social and Information Relations in Networks of Small and Medium-Sized Firms

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Enhancing classroom management through parental involvement by using social networking apps

The purpose of this study is to explore the classroom management effectiveness enhancement by using social networking apps through electronic devices such as smartphones, tablet computers, and personal computers, as well as the role of parental involvement. Quantitative research was conducted, and the Structural Equation Modelling (SEM) statistical technique applied. From 15 different Changhua County primary schools in Taiwan, 411 teachers were chosen using stratified random sampling in proportion to the size and location of schools. Each teacher was invited to fill out a questionnaire. A total of 403 (98.05%) questionnaires were returned, with 382 (92.94%) considered valid. In order to confirm the statistical results, a focused group interview was also conducted. The effects of the behaviour intention of using Line, parental involvement, and classroom management effectiveness were all found to be positively associated with one another. Moreover, the mediating role of parents in the relationship between the behaviour intention of using Line and classroom management effectiveness enhancement was also supported and confirmed. Keywords: behaviour intention; classroom management effectiveness; parental involvement; social networking apps; Taiwan’s primary schools
The Intersectin 2 Adaptor Links Wiskott Aldrich Syndrome Protein (WASp)-mediated Actin Polymerization to T Cell Antigen Receptor Endocytosis

Induction of T cell antigen receptor (TCR) endocytosis has a significant impact on TCR signaling and T cell behavior, but the molecular interactions coordinating internalization of the activated TCR are poorly understood. Previously we have shown that TCR endocytosis is regulated by the Wiskott Aldrich Syndrome protein (WASp), a cytosolic effector which, upon interaction with the cdc42 Rho GTPase, couples TCR engagement to Arp 2/3 complex-mediated actin polymerization. Here we report that WASp associates in T cells with intersectin 2, an endocytic adaptor containing multiple domains including a Dbl homology (DH) domain with the potential to activate Rho GTPases. Intersectin 2 association with WASp increases after TCR engagement, and its overexpression in Cos-7 cells induces WASp translocation to endocytic vesicles within which intersectin 2 colocalizes with both WASp and cdc42. Intersectin 2, but not a DH domain-deleted (ΔDH) form of intersectin 2, and stimulation via the TCR also trigger the activation of cdc42. Induction of TCR internalization is also augmented by intersectin 2 and severely impaired by latrunculin B treatment. Thus, intersection 2 appears to function cooperatively with WASp and cdc42 to link the clathrin endocytic machinery to WASp-mediated actin polymerization and ultimately to occupancy-induced TCR endocytosis.
Fully automated liver segmentation for low- and high- contrast CT volumes based on probabilistic atlases

Automated liver segmentation is problematic due to variations in liver shape / size and because the liver has a similar density distribution to surrounding structures. We propose a method that: 1) utilizes iteratively constructed probabilistic liver and rib cage atlases, 2) conducts the Gaussian distribution analysis to avoid incorrectly classifying the irrelevant surrounding tissues as ‘liver region’ in the conventional probabilistic atlas based method, and maps the intensity range of the input candidate liver region onto the liver atlas, 3) retrieves the ‘missing parts’ of the liver by deformable registration. Our approach is automated and able to segment the liver from high-contrast and low-contrast CT volumes. Forty clinical CT studies were used for atlas construction and validation. Our method outperformed two other probabilistic atlas-based liver segmentation methods.
Applying usability testing to improving Scrum methodology in develop assistant information system

The need for software development methods that have faster and flexible development process has emerged nowadays. Agile software development method is a method that promises shorter time-to-market and higher flexibility to accommodate changes of requirements. One framework that relies on agile software development method is Scrum. It has iterative, focus on teamwork, and collaboration development process. Scrum also has several challenges, such as long users' feedback loops, lack of users' involvement in testing, and lack of software quality. In this paper, we aimed to address those challenges by applying usability testing. It is expected that by applying usability testing to Scrum could improve the Scrum in addressing the challenges. There is also a software that built using Scrum to proof the concept.
Dietary magnesium and copper affect survival time and neuroinflammation in chronic wasting disease

ABSTRACT Chronic wasting disease (CWD), the only known wildlife prion disease, affects deer, elk and moose. The disease is an ongoing and expanding problem in both wild and captive North American cervid populations and is difficult to control in part due to the extreme environmental persistence of prions, which can transmit disease years after initial contamination. The role of exogenous factors in CWD transmission and progression is largely unexplored. In an effort to understand the influence of environmental and dietary constituents on CWD, we collected and analyzed water and soil samples from CWD-negative and positive captive cervid facilities, as well as from wild CWD-endozootic areas. Our analysis revealed that, when compared with CWD-positive sites, CWD-negative sites had a significantly higher concentration of magnesium, and a higher magnesium/copper (Mg/Cu) ratio in the water than that from CWD-positive sites. When cevidized transgenic mice were fed a custom diet devoid of Mg and Cu and drinking water with varied Mg/Cu ratios, we found that higher Mg/Cu ratio resulted in significantly longer survival times after intracerebral CWD inoculation. We also detected reduced levels of inflammatory cytokine gene expression in mice fed a modified diet with a higher Mg/Cu ratio compared to those on a standard rodent diet. These findings indicate a role for dietary Mg and Cu in CWD pathogenesis through modulating inflammation in the brain.
Stabilization of discrete-time linear systems with saturating actuators using sliding modes: Application to a twin-rotor system

This paper investigates the stabilization problem for discrete-time linear controllable systems subject to actuator saturation. In the case of completely known plants, a control design technique based on a time varying sliding surface is proposed ensuring stabilization under the assumption of availability of all state measurements. Further, in the presence of matched disturbances with known constant bound, a discrete time sliding mode controller is proposed ensuring plant practical stabilization, and a conservative estimate of the attraction domain is given. Theoretical results have been validated by experimental data using a twin-rotor system.
Combining empirical and machine learning techniques to predict math expertise using pen signal features

Multimodal learning analytics aims to automatically analyze students' natural communication patterns based on speech, writing, and other modalities during learning activities. This research used the Math Data Corpus, which contains time-synchronized multimodal data from collaborating students as they jointly solved problems varying in difficulty. The aim was to investigate how reliably pen signal features, which were extracted as students wrote with digital pens and paper, could identify which student in a group was the dominant domain expert. An additional aim was to improve prediction of expertise based on joint bootstrapping of empirical science and machine learning techniques. To accomplish this, empirical analyses first identified which data partitioning and pen signal features were most reliably associated with expertise. Then alternative machine learning techniques compared classification accuracies based on all pen features, versus empirically selected ones. The best unguided classification accuracy was 70.8%, which improved to 83.3% with empirical guidance. These results demonstrate that handwriting signal features can predict domain expertise in math with high reliability. Hybrid methods also can outperform black-box machine learning in both accuracy and transparency.
3D mesh coding through region based segmentation

In this paper, we are interested in wavelet-based coding of 3D semi-regular meshes in order to ensure the progressiveness of the reconstruction. The contribution of this work relies on the adaptation procedure of the lifting scheme operators carried out at each resolution level. More precisely, we propose to firstly segment the original mesh into nonoverlapping regions. The involved predictors are then optimally computed for each region.
The Effects of Perioperative Pain Management Techniques on Food Consumption and Body Weight After Laparotomy in Rats

We examined the effects of two perioperative pain management techniques on recovery after laparotomy, as assessed by body weight (BW) and food consumption (FC). All rats received a preoperative intrathecal mixture of morphine plus bupivacaine combined with one of two treatments: (a) injection of slow-release morphine at the end of the surgery or (b) an antiinflammatory drug, interleukin-1 receptor antagonist (IL-1ra), combined with the preoperative mixture. Laparotomy significantly decreased FC and BW. Both analgesic treatments resulted in a faster recovery of FC and BW. This beneficial effect was more pronounced in the group receiving preoperative analgesics combined with IL-1ra.
Study on Similarity Search

- Content-Aware Search can be defined as a method for searching a word or a phrase in such a way that we are able to extract wanted data from the search engine, example Google. It explores issues that are related to searching, refining and filtering of feature-rich, text and non-text data types. Content Based Similarity search explains that for given a query object we need to find similar objects, that is, objects with similar features (not exact features). This paper basically focuses on the various types of algorithms available for searching. The search can include both text and non-text data. Content based search system can be of different kinds-Full Similarity Search and Partial Similarity Search. There are various algorithms that work efficiently for the searching mechanism. Most of the algorithms are based on the nearest neighbour problem.
A support vector machine approach to credit scoring

Driven by the need to allocate capital in a profitable way and by the recently suggested Basel II regulations, financial institutions are being more and more obliged to build credit scoring models assessing the risk of default of their clients. Many techniques have been suggested to tackle this problem. Support Vector Machines (SVMs) is a promising new technique that has recently emanated from different domains such as applied statistics, neural networks and machine learning. In this paper, we experiment with least squares support vector machines (LS-SVMs), a recently modified version of SVMs, and report significantly better results when contrasted with the classical techniques.
Proton sensitivity of ASIC1 appeared with the rise of fishes by changes of residues in the region that follows TM1 in the ectodomain of the channel

The acid‐sensitive ion channel 1 (ASIC1) is a neuronal Na+ channel insensitive to changes in membrane potential but is gated by external protons. Proton sensitivity is believed to be essential for the role of ASIC1 in modulating synaptic transmission and nociception in the mammalian nervous system. To examine the structural determinants that confer proton sensitivity, we cloned and functionally characterized ASIC1 from different species of the chordate lineage: lamprey, shark, toadfish and chicken. We observed that ASIC1s from early vertebrates (lamprey and shark) were proton insensitive in spite of a high degree of amino acid conservation (66–67%) with their mammalian counterparts. Sequence analysis showed that proton‐sensitive ASIC1s could not be distinguished from proton‐insensitive channels by any signature in the protein sequence. Chimeras made with rat ASIC1 (rASIC1) and lamprey or shark indicated that most of the ectodomain of rASIC1 was required to confer proton sensitivity and the distinct kinetics of activation and desensitization of the rat channel. Proton‐sensitive chimeras contained the segment D78–E136, together with residues D351, Q358 and E359 of the rat sequence. However, none of the functional chimeras containing only part of the rat extracellular domain retained the kinetics of activation and desensitization of rASIC1, suggesting that residues distributed in several regions of the ectodomain contribute to allosteric changes underlying activation and desensitization. The results also demonstrate that gating by protons is not a feature common to all ASIC1 channels. Proton sensitivity arose recently in evolution, implying that agonists different from protons activate ASIC1 in lower vertebrates.
Coping Strategies to Improve the Quality of Life among Thai Students

Thai Students who are getting educated in Indonesia are experiencing various circumstances such as stress due to cultural differences. This makes the students have the appropriate coping strategies to adjust themself in the face of cultural differences that are stressful. This research is a research survey conducted by spreading detailed questionnaire on a sample size of 99 Thai students in town X, Indonesia. The results obtained are that 75.8% of students experience culture shock with the percentage of male students being larger than female students. It is also found that CS experienced affects learning achievement index students, other than that based on the duration the length of stay affect coping strategies are conducted where the students stayed not long ago had a strategy of coping with high facing the CS is experienced so high CS found in students who have already live longer in Indonesia. We also found that coping strategy that focuses on emotions can have significant effects against CS.
Self-Assembled Monolayers That Resist the Adsorption of Proteins and the Adhesion of Bacterial and Mammalian Cells

This paper examines the hypothesis that surfaces resistant to protein adsorption should also be resistant to the adhesion of bacteria (Staphylococcus aureus, Staphylococcus epidermidis) and the attachment and spreading of mammalian cells (bovine capillary endothelial (BCE) cells). The surfaces tested were those of self-assembled monolayers (SAMs) terminated with derivatives of tri(sarcosine) (Sarc), N-acetylpiperazine, permethylated sorbitol, hexamethylphosphoramide, phosphoryl choline, and an intramolecular zwitterion (−CH2N+(CH3)2CH2CH2CH2SO3-) (ZW); all are known to resist the adsorption of proteins. There seems to be little or no correlation between the adsorption of protein (fibrinogen and lysozyme) and the adhesion of cells. Surfaces terminated with derivatives of Sarc and N-acetylpiperazine resisted the adhesion of S. aureus and S. epidermidis as well as did surfaces terminated with tri(ethylene glycol). A surface that presented Sarc groups was the only one that resisted the adhesion of BCE cells a.
Robust parametric detection in non homogeneous clutter

In this paper we address the problem of robust adaptive parametric radar detection in non-homogeneous clutter. Interfering targets and clutter edges in secondary cells are regarded as outliers. Classical estimators of parametric models are not sufficiently robust in such situations. We consider stationary segments, where the clutter is modelled as an autoregressive process, we apply a robust filter and we estimate the autoregressive model to construct the parametric detector.