Miracle-dz/UniFAR-FTUs huggingface dataset:
Phosphate coated iron powder and method for the manufacture thereof

The present invention relates to a new low oxygen powder comprising particles of a base powder consisting essential of pure iron having an insulating oxygen-containing insulating barrier and a phosphorus-containing barrier. The amount of oxygen of the new powder is often up to 0.2% by weight than the oxygen content of the base powder, as measured by the ESCA method O: The ratio of P is from 30 to 1, preferably from 15 to 2, and most preferably from 10 to 3 . The present invention also provides an iron comprising the steps of for the powder drying method comprising treatment with a phosphoric acid solution in an organic solvent, and the obtained mixture to prepare a base powder consisting of mulwon-shape iron powder or a sponge-type iron powder relates to a process for preparing a base powder, a phosphoric acid solution by such a method is sprayed onto the base powder while being mixed.
Trading for Sustainable Development Goals: Trade Policy, Inequality and Poverty in Emerging Economies

The objective of the study is to identify the impact of trade policy on two significant goals of sustainable development namely poverty and income inequality in the emerging economies. Using trade openness and trade facilitation as a measure of trade policy the study examines their impact on Gini coefficient and average income of the poorest quintile as a proxy to income inequality and poverty headcount ratio and poverty gap at $1.90 per day (2011 PPP) as indicators of extreme poverty. It applies dynamic panel data model with panel datasets over the period of 1986-2013 for trade openness and 2005-2013 for trade facilitation on the emerging economies based on the availability of data. The findings of the study suggest that trade openness and trade facilitation as measures of trade policy significantly reduce the extreme poverty as measured by poverty headcount ratio and poverty gap at $1.90 a day and increase the average per capita income of the lowest 20% population of the emerging economics whereas the two measures of trade policy increase the income inequality in these economies.
COPING WITH NUMERICAL PROBLEMS IN IMPLEMENTATION OF 3D DELAUNAY TRIANGULATION

An electromagnetic-induction heater having electromagnets which are disposed on both sides of a strip and in face-to-face relationship with each other is disclosed. The electromagnetic-induction heater is arranged to heat by the use of electromagnetic induction the strip which is transferred in a predetermined direction. The electromagnets are respectively constituted by a plurality of magnetic-pole segments which are disposed in a split manner transverse to the direction of travel of the strip and which are capable of individually moving toward the strip, and common coils which surround the magnetic-pole segments. The electromagnetic-induction heater comprises a nonmagnetic-metal movable shielding plate which is disposed at each end portion of each magnet which is near the strip. The shielding plate is moved forward and backward parallel to and transversely relative to the length of the strip, thereby reducing a fringing field generated by each of the magnetic-pole segments.
A Feature Selection and Evaluation Scheme for Computer Virus Detection

Anti-virus systems traditionally use signatures to detect malicious executables, but signatures are over-fitted features that are of little use in machine learning. Other more heuristic methods seek to utilize more general features, with some degree of success. In this paper, we present a data mining approach that conducts an exhaustive feature search on a set of computer viruses and strives to obviate over-fitting. We also evaluate the predictive power of a classifier by taking into account dependence relationships that exist between viruses, and we show that our classifier yields high detection rates and can be expected to perform as well in real-world conditions.
Quasi-Monte Carlo Techniques and Rare Event Sampling ?

In the last decade considerable practical interest, e.g. in credit and insurance risk or telecommunication applications, as well as methodological challenges caused intensive research on estimation of rare event probabilities. This article aims to show that recently developed rare event estimators are especially well-suited for a quasiMonte Carlo framework by establishing limit relations for the so-called eectiv e dimension and proposing smoothing methods to overcome problems with cusps of the integrand.
Comparing Different Approaches in Large-Scale Seaweed Gene Discovery

Seaweeds are of economic and ecological importance, and for centuries have been used in food, phycocolloid, and pharmaceutical industries. With the advance development of computational biology and bioinformatics, the study of seaweeds is entering a new revolutionary phase. Molecular genetic study and gene discovery in seaweeds will greatly facilitate the process of deciphering the physiology, biochemistry and molecular biology of seaweeds, leading to genetic improvements by means of gene modification and genetic engineering. This article reviews the approaches, recent developments and future in molecular genetic study and gene discovery in seaweeds.
Rapid Prototyping of Extended Entity-Relationship Models

The entity-relationship model is considered to be the standard for conceptual design of data in information systems and relational databases. Extended entity-relationship models provide extra concepts such as generalization, dependency and classification. In the context of objectoriented software development, such models are able to represent part of the functionality whereas more operational functionality is implemented in the object-oriented language. In the resulting object-oriented program, however, the original data model is often lost and the relationship and dependency constraints are not enforced. We propose an approach which consists of an active modeling phase and an interactive prototyping phase. The overall result is a model in which the elements have active links to fully operational implementation objects, which in turn are actively constrained by the model. We have developed a system that supports the manual steps in these two phases and fully implements the (semi-)automatic steps.
Photogrammetric Methodology for the Production of Geomorphologic Maps: Application to the Veleta Rock Glacier (Sierra Nevada, Granada, Spain)

In this paper we present a stereo feature-based method using SIFT (Scale-invariant feature transform) descriptors. We use automatic feature extractors, matching algorithms between images and techniques of robust estimation to produce a DTM (Digital Terrain Model) using convergent shots of a rock glacier.The geomorphologic structure observed in this study is the Veleta rock glacier (Sierra Nevada, Granada, Spain). This rock glacier is of high scientific interest because it is the southernmost active rock glacier in Europe and it has been analyzed every year since 2001. The research on the Veleta rock glacier is devoted to the study of its displacement and cartography through geodetic and photogrammetric techniques.
M-COPE: a multiple continuous query processing engine

A data stream management system (DSMS) should support an efficient evaluation scheme for long-running continuous queries over infinite data streams. This demonstration presents a scalable query processing engine, M-COPE (Multiple Continuous Query Processing Engine) developed to evaluate multiple continuous queries efficiently. A multiple query optimization scheme implemented in the system generates a single network of operations as an execution plan for registered queries in order to maximize the reuse of the intermediate results of common sub-expressions in the queries adaptively. In this paper, we describe the overall architecture of M-COPE along with its special features. Network traffic flow streams are used to demonstrate the main features of M-COPE.
Fast Rotation-Invariant DAISY Descriptor for Image Keypoint Matching

In this paper, we introduce an improved version of DAISY descriptor algorithm for fast and high-quality image key point matching. Since DAISY descriptor algorithm has many prominent advantages but lacks the ability of handling large in-plane rotation, we thus construct our Rotation-Invariant DAISY descriptor to effectively settle this shortcoming. We first extract key points of images by Harris corner detector, and then use histogram data of every key point to assign a local orientation for each. During the step of constructing descriptors, we rotate the coordinate axis of every key point to its local orientation, and obtain Rotation-Invariant DAISY descriptors. In order to accelerate matching task, we apply PCA to descriptors for dimension reduction. Our experiments demonstrate that the Fast Rotation-Invariant DAISY has better performance in various image distortions. The results also testify that this approach consumes less time when obtains similar results of SIFT descriptor algorithm, and it can be applied more densely in different kinds of images but SIFT cannot.
Phase diagrams of the two-dimensional Hubbard and t-J models by a variational Monte Carlo method.

We use a variational Monte Carlo technique to study the ground state of the two-dimensional Hubbard and t-J models on a square lattice. We use a trial wave function that allows a continuous description of the paramagnetic, antiferromagnetic, and superconducting phases, as well as the coexistence of these phases, with no a priori constraint on double occupancy. The phase diagram of both models is given for intermediate coupling (U=10t). We show that the apparent discrepancies between the two models, that appeared in previous variational Monte Carlo studies, are not present when this sufficiently good variational wave function is used. The two models are in good qualitative agreement. We find that except at half-filling a pure antiferromagnetic phase does not exist but is always in coexistence with a d-wave superconducting phase, and is followed by a pure d-wave superconducting phase at doping up to \ensuremath{\delta}\ensuremath{\sim}0.3. The staggered magnetization and the superconducting gap are measured, and a comparison with other analytical or numerical results is made.
Serelaxin in acute heart failure patients with preserved left ventricular ejection fraction: results from the RELAX-AHF trial

Aims Serelaxin is effective in relieving dyspnoea and improving multiple outcomes in acute heart failure (AHF). Many AHF patients have preserved ejection fraction (HFpEF). Given the lack of evidence-based therapies in this population, we evaluated the effects of serelaxin according to EF in RELAX-AHF trial. Methods and results RELAX-AHF randomized 1161 AHF patients to 48-h serelaxin (30 μg/kg/day) or placebo within 16 h from presentation. We compared the effects of serelaxin on efficacy endpoints, safety endpoints, and biomarkers of organ damage between preserved (≥50%) and reduced (<50%, HFrEF) EF. HFpEF was present in 26% of patients. Serelaxin induced a similar dyspnoea relief in HFpEF vs. HFrEF patients by visual analogue scale-area under the curve (VAS-AUC) through Day 5 [mean change, 461 (−195, 1117) vs. 397 (10, 783) mm h, P = 0.87], but had possibly different effects on the proportion of patients with moderately or markedly dyspnoea improvement by Likert scale at 6, 12, and 24 h [odds ratio for favourable response, 1.70 (0.98, 2.95) vs. 0.85 (0.62, 1.15), interaction P = 0.030]. No differences were encountered in the effect of serelaxin on short- or long-term outcome between HFpEF and HFrEF patients including cardiovascular death or hospitalization for heart/renal failure through Day 60, cardiovascular death through Day 180, and all-cause death through Day 180. Similar safety and changes in biomarkers (high-sensitivity troponin T, cystatin-C, and alanine/aspartate aminotransferases) were found in both groups. Conclusions In AHF patients with HFpEF compared with those with HFrEF, serelaxin was well tolerated and effective in relieving dyspnoea and had a similar effect on short- and long-term outcome, including survival improvement.
A Novel Approach to Predict the Learning Skills of Autistic Children using SVM and Decision Tree

The present trends in education are moving toward further comprehensive educational experiences for children with autism spectrum disorder, totally different learning styles, and differentiated instructional practices to support all children to succeed. The very important goal of the paper is to predict and forecast the autism spectrum disorder children performance by applying data mining classification algorithms in Weka tool. The data mining tool is accepted as a decision making tool to facilitate higher resource utilization in terms of autism children performance. The classification algorithms may be specifically mentioned as J48 and Support Vector Machine. The results of the classification model deals with the accuracy level, error rate level, confusion matrices, efficiency of classifiers and additionally the execution time. Sequential Minimal optimization (SMO) algorithmic rule with Normalized Polykernel used in performing classifier SVM and the J48 algorithmic rule is employed in constructing decision trees. KeywordsDecision Tree, Support Vector Machine
Sex Differences in β-Adrenergic Responsiveness of Action Potentials and Intracellular Calcium Handling in Isolated Rabbit Hearts

Cardioprotection in females, as observed in the setting of heart failure, has been attributed to sex differences in intracellular calcium handling and its modulation by β-adrenergic signaling. However, further studies examining sex differences in β-adrenergic responsiveness have yielded inconsistent results and have mostly been limited to studies of contractility, ion channel function, or calcium handling alone. Given the close interaction of the action potential (AP) and intracellular calcium transient (CaT) through the process of excitation-contraction coupling, the need for studies exploring the relationship between agonist-induced AP and calcium handling changes in female and male hearts is evident. Thus, the aim of this study was to use optical mapping to examine sex differences in ventricular APs and CaTs measured simultaneously from Langendorff-perfused hearts isolated from naïve adult rabbits during β-adrenergic stimulation. The non-selective β-agonist isoproterenol (Iso) decreased AP duration (APD90), CaT duration (CaD80), and the decay constant of the CaT (τ) in a dose-dependent manner (1–316.2 nM), with a plateau at doses ≥31.6 nM. The Iso-induced changes in APD90 and τ (but not CaD80) were significantly smaller in female than male hearts. These sex differences were more significant at faster (5.5 Hz) than resting rates (3 Hz). Treatment with Iso led to the development of spontaneous calcium release (SCR) with a dose threshold of 31.6 nM. While SCR occurrence was similar in female (49%) and male (53%) hearts, the associated ectopic beats had a lower frequency of occurrence (16% versus 40%) and higher threshold (100 nM versus 31.6 nM) in female than male hearts (p<0.05). In conclusion, female hearts had a decreased capacity to respond to β-adrenergic stimulation, particularly under conditions of increased demand (i.e. faster pacing rates and “maximal” levels of Iso effects), however this reduced β-adrenergic responsiveness of female hearts was associated with reduced arrhythmic activity.
Multisensory innovation: Haptic input and its role in product design

For many companies, differentiating their offerings from competitors' value propositions is becoming increasingly challenging. In order to formulate convincing value propositions, a holistic approach is required that takes human perception and sensation into consideration. This article assesses the role of haptics in multisensory product design. It systematically reviews previous research, illustrates factors affecting haptic perception and sheds light on the processing of haptic input. This article serves to illustrate how haptic input activates processes that affect human perception of products and ultimately alters behavior and thus substantiates its role in multisensory innovation and product design.
Contribution of Natural Language Processing in Predicting Rehospitalization Risk

Greenwald et al. propose using free text in patient records to estimate hospital readmission risk. They use expert knowledge to identify 35 groups of phrases indicative of 30-day rehospitalization, and use 16 of these in logistic regression. We believe the use of natural language processing (NLP) for predicting rehospitalization is an interesting approach, and provide suggestions to improve the model.
Acquiring Cultural Perceptions during Study Abroad: The Influence of Youthful Associates

The interdependence of language and culture highlights the need to find methods for second language students to acquire cultural information and practices. This article reviews definitions of culture posited by anthropologists and language educators and discusses problems related to the recent paradigm shift from "small 'c' and big 'C'" as classifications for culture to the three 'P's of products, practices, and perspectives proposed by the Standards for Foreign Language Learning in the 21st Century (National Standards 2006). Drawing from Kramsch's (1993) postulate of real culture (C1) versus perceived culture (C1'), the current study solicited responses to a questionnaire regarding the practices of Spaniards from two age groups (young and mature) and American students involved in a study abroad program in Spain. Data analyses reveal that perceptions of American Students most closely align with those of Young Spaniards. Implications point to the need for intervention and instruction to provide students with a broader perspective of Spain's cultural practices.
Eye movement interactions in google cardboard using a low cost EOG setup

In this paper, we present a low cost way to track user's eye movements in a Google Cardboard Virtual Reality Headset. We use the Electrooculography (EOG) module from commercial disassembled smart glasses to augment a cardboard. We present a first signal level evaluation and concepts about VR interaction techniques using relative eye movements.
Feedback on health status and peer popularity influences social risk decision-making processes in adolescents and young adults

Abstract Cognitive and dual-processes models, involving cognitive and socio-emotional components, for adolescents’ risky behaviour have been proposed. This study tested their predictions by manipulating the presence or absence of feedback about gains and losses in health and peer popularity in a decision-making task with peers. Risky (e.g., taking or refusing a drug) and ambiguous decisions (e.g., eating hamburger or hotdog) were examined in 256 adolescents (aged 13–14; 15–16; 17–18) and young adults (aged 19–20). Participants made more risky choices and required less decision time when receiving feedback about the negative consequences on health and positive consequences on peer popularity. Decision times were comparatively larger for risky than for safe options in late adolescence and young adulthood. Results supported the dual-processes model showing that, though late cognitive changes were observed that could eventually lead to the selection of safe options, feedback gains in peer popularity outweighed unhealthy consequences leading to risky decisions.
MetaCyc: a multiorganism database of metabolic pathways and enzymes

MetaCyc is a database of metabolic pathways and enzymes located at . Its goal is to serve as a metabolic encyclopedia, containing a collection of non-redundant pathways central to small molecule metabolism, which have been reported in the experimental literature. Most of the pathways in MetaCyc occur in microorganisms and plants, although animal pathways are also represented. MetaCyc contains metabolic pathways, enzymatic reactions, enzymes, chemical compounds, genes and review-level comments. Enzyme information includes substrate specificity, kinetic properties, activators, inhibitors, cofactor requirements and links to sequence and structure databases. Data are curated from the primary literature by curators with expertise in biochemistry and molecular biology. MetaCyc serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. Querying, visualization and curation of the database is supported by SRI's Pathway Tools software. The PathoLogic component of Pathway Tools is used in conjunction with MetaCyc to predict the metabolic network of an organism from its annotated genome. SRI and the European Bioinformatics Institute employed this tool to create pathway/genome databases (PGDBs) for 165 organisms, available at the website. These PGDBs also include predicted operons and pathway hole fillers.
A comparison of the components of the multifocal and full-field ERGs

Abstract The multi-input technique of Sutter and Tran (1992) yields multiple focal ERGs. The purpose here was to compare the components of this multifocal ERG to the components of the standard, full-field ERG. To record multifocal ERGs, an array of 103 hexagons was displayed on a monitor. Full-field (Ganzfeld) ERGs were elicited by flashes presented upon steady background fields. The latencies of two prominent subcomponents of the full-field ERG were altered by varying the intensity of the incremental flash or the intensity of the background field. By showing that similar manipulations of the multi-input parameters produce similar changes in latency, we were able to relate the components of the multifocal ERG to the components of the full-field ERG. The biphasic responses of the multifocal ERG appear to be generated by the same cells generating the a-wave and positive peaks of the full-field cone ERG.
Time series forecasting with missing values

Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM). We employ the input patterns with the temporal information which is defined as local time index (LTI). Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.
Examining Relationships and Effects in Gifted Education Research

The aim of this Methodological Brief to structural equation modeling (SEM) is to help readers become more aware of its uses and how to understand research using it. SEM provides many benefits over traditional multiple regression, including the ability to model multiple outcomes simultaneously and to account for measurement error. This Brief provides a general overview of the purposes of SEM and reviews how SEM can estimate models with both observed variables as well as their underlying constructs and how the adequacy of models is assessed in SEM. Finally, this Brief introduces path diagrams and latent variable models with an illustration of how to understand diagrams and standardized estimates.