Miracle-dz/UniFAR-FTUs huggingface dataset:
A study of the effect of domestic violence on maternal-neonatal attachment in prim gravida women referred to hospitals affiliated to Shiraz University of Medical Sciences

Introduction: Domestic violence during pregnancy is a threat that may affect the relationship of mothers and babies. This study aimed to determine the effect of domestic violence severity on neonatal-maternal attachment. Materials and Methods: This is an analytic-descriptive study carried out on 150 pregnant women aged between 18 to 35 years by purposive sampling. Research tools included the violence questionnaire and Avant’s checklist. Spearman correlation test was used for data analysis. Results: No significant difference was reported between maternal-neonatal attachment and total score of violence (p=0.742). However, the correlation between violence and maternal-neonatal attachment was statistically significant in some subtitles. Analysis of Variance (ANOVA) showed a statistically significant correlation between maternal-neonatal attachment and social violence (p=0.006). Therefore, based on ttest, no significant difference was reported between maternal anxiety levels and total score of violence (p=0.094). Conclusion: No significant difference was reported between the maternal-neonatal attachment and mother’s anxiety with total score of violence.
Choix du type de contrat et performance : le cas des marchés publics de défense

Le choix systematique de la Delegation Generale pour l’Armement en faveur des contrats a prix fixe alors que les transactions sont complexes et incertaines est-il pertinent ? La performance de deux marches dont l’objet est identique mais pour lesquels les choix du type de contrat ont ete differents, l’un ayant ete gouverne par un contrat a remboursement de couts et l’autre par un contrat a prix fixe, est comparee et expliquee. A travers cette etude de cas, nous montrons que le differentiel de performance peut etre explique a la fois par les concepts avances par la theorie de l’agence et par la theorie des couts de transaction, en insistant sur leur caractere complementaire en vue de rendre pleinement compte de nos observations factuelles, ce qui presente des implications en matiere de choix contractuels.
Item Context Effects in IS Survey Research

This paper discusses correlational and directional item context effects as two method biases that can threaten the validity of survey data. Two empirical studies are used to establish their presence in IS research. In addition, item separation with partial randomization is shown to be a viable way for researchers to control for correlational item context effects associated with inflated Cronbach’s alphas.
An Extensible Web Mining Framework for Real Knowledge

With the emergence of Web 2.0 applications that bestow rich user experience and convenience without time and geographical restrictions, web usage logs became a goldmine to researchers across the globe. User behavior analysis in different domains based on web logs has its utility for enterprises to have strategic decision making. Business growth of enterprises depends on customer-centric approaches that need to know the knowledge of customer behavior to succeed. The rationale behind this is that customers have alternatives and there is intense competition. Therefore business community needs business intelligence to have expert decisions besides focusing customer relationship management. Many researchers contributed towards this end. However, the need for a comprehensive framework that caters to the needs of businesses to ascertain real needs of web users. This paper presents a framework named eXtensible Web Usage Mining Framework (XWUMF) for discovering actionable knowledge from web log data. The framework employs a hybrid approach that exploits fuzzy clustering methods and methods for user behavior analysis. Moreover the framework is extensible as it can accommodate new algorithms for fuzzy clustering and user behavior analysis. We proposed an algorithm known as Sequential Web Usage Miner (SWUM) for efficient mining of web usage patterns from different datasets. We built a prototype application to validate our framework. Our empirical results revealed that the framework helps in discovering actionable knowledge. KeywordsKnowledge discovery; Web usage mining, Fuzzy clustering, Business intelligence.
An Efficient Classification Approach for Examine Health Records of Cause of Death

Now a day’s examining the health of each person in the every country is an integral part of healthcare. After examining the health of each person we can identify type of risk to be occurred. The analysis of risk based unlabelled data can be done by using classification approach in the data mining. Particularly we are take unlabelled data contains information related to participants in the health examination whose health condition is vary from great health to very ill. In this study we formulated the task of risk prediction as a multiclass classification problem using the Cause of Death (COD) information as labels, regarding the health-related death as the “highest risk”. The goal of risk prediction is to effectively classify 1) whether a health examination participant is at risk, and if yes, 2) predict what the key associated disease category is. In other words, a good risk prediction model should be able to exclude low-risk situations and clearly identify the high-risk situations that are related to some specific diseases. In the examination of health we are identifying different states of health without ground truth. So that by predicting risk of each participant by using classification approaches in the data mining. In this paper we proposed Mixed Probability Binary Rule Based Classification Algorithm is used to predict health risk of participate person. By implementing this algorithm we can get efficient classification result and also give better performance.
A Decision and Control System Mimicking a Skilled Grower's Thinking Process for Dynamic Optimization of the Storage Environment

A decision and control system mimicking a skilled grower's thinking process is proposed which was then applied to dynamic optimization of the relative humidity that minimizes both the water loss and the fungal development of fruits during storage. A skilled grower's thinking process consists mainly of two steps: (1) “learning”through experience and (2) “selection and decision”through simulation of a mental model developed in his brain by the learning. After a decision, (3) “action”in a loose and/or sophisticated manner is taken. The decision and control system proposed here consists of two decision systems (I and II) and a fuzzy on-off controller for ventilation. The optimal set points of the relative humidity are first determined using decision system I, and then the relative humidity is controlled based on these set points using a fuzzy on-off controller. In decision system I, neural networks identify the water loss and fungal development of the fruit as affected by the relative humidity (“learning”), and genetic algorithms search for the optimal set points of the relative humidity that minimize the water loss and fungal development of the fruit through simulation of the identified model (“selection and decision”) . The optimal set points obtained here involved a slightly low humidity during the first few days after storage and then higher humidity. The fuzzy on-off controller tuned optimally by decision system II showed good control of the relative humidity. This control technique is widely applicable to dynamic optimizations of complex agricultural systems.
Research on the design method of user interface for mobile Internet based on data mining

In order to improve the interactive and artisticof user interface of APP for mobile Internet, the design method based on data mining is proposed in this paper. This paper takes the interface design of smartphone mobile Internet application as the research object, adopts a collection of literature investigation, applies interdisciplinary research method, and combines practical case analysis to reconstruct interface design knowledge system, namely SUIG interface design knowledge system, with big-picture thinking of smartphone mobile Internet application from four aspects such as design strategy, user model and its task analysis, interaction of interface, and visual design. Besides, on this basis of the study, by taking the interface design process of smartphone mobile Internet application as the research content, the paper analyses the principle and method of the interface design of smartphone mobile Internet application, emphasizes the user-centred ideas figuring out the whole process of interface design of application would require around the user and task model implementation and development. The experiment result shows the proposed method can improve the overall performance for the design of user interface for mobile Internet.
TGING : graphic information processing for teaching

We present TGINF, a software application for graphic information processing designed in Visual Basic (taking Bertin's works as a reference) to introduce data processing in teaching. We will describe the software, the rationale behind it, how it works and an example of its actually being used on a matrix of Boolean data to show the possibilities and limits of TGINF.
Could Google Translate Shakespeare

Translation technology has made very rapid advances in recent years, and we now expect our devices to provide us with serviceable translations of many kinds of text, at the touch of a screen. Literary texts are still viewed as an exception to this trend, but is it only a matter of time before we can expect Google to come up with a decent translation of Shakespeare?
A Binarization Method for Extracting High Entropy String in Gait Biometric Cryptosystem

Inertial-sensors based gait has been considered as a promising approach for user authentication in mobile devices. However, securing enrolled template in such system remains a challenging task. Biometric Cryptosystems (BCS) provide elegant approaches for this matter. The primary task of adopting BCS is to extract from raw biometric data a discriminative, high entropy and stable binary string, which will be used as input of BCS. Unfortunately, the state-of-the-art researches does not notice the gait features' population distribution when extracting such string. Thus, the extracted binary string has low entropy, and degrades the overall system security. In this study, we address the aforementioned drawback to improve entropy of the extracted string, and also enhance the system security. Specifically, we design a binarization scheme, in which the distribution population of gait features are analyzed and utilized to allow the extracted binary string achieving maximal entropy. In addition, the binarization is also designed to provide strong variation toleration to produce highly stable binary string which enhances the system friendliness. We analyzed the proposed method using a gait dataset of 38 volunteers which were collected under nearly realistic conditions. The experiment results show that our proposed binarization method improves the extracted binary string's entropy 30%, and the system achieved competitive performance (i.e., 0.01% FAR, 9.5% FRR with 139-bit key).
Phase separation of a binary liquid mixture in porous media studied by nuclear magnetic resonance cryoporometry

1H nuclear magnetic resonance cryoporometry has been applied to study the low-temperature phase separation of the two components in a binary liquid imbibed in porous glass. The mixture of hexane and nitrobenzene was quenched below both its upper critical temperature and the freezing point of the nitrobenzene. The size distribution of phase-separated liquid domains was observed through their melting point suppression that reveals small droplets of nitrobenzene surrounded by hexane within the pores. If the bottlenecks of the porous network allow, some of these droplets coalesce and thereby completely fill parts of the network.
APPLICATION OF USABILITY CONCEPTS IN WINE MARKETING: A MULTIDISCIPLINARY REVIEW

Various studies have shown that the wine consumption decline in young generation could be influenced by the perception of wine as intimidating and difficult to understand, and by the lack of adaptability of the product’s communication strategy and packaging design to their lifestyle. Information available on the packaging is often complex and confusing for novice wine consumers and sometimes even irrelevant in regards to the intrinsic characteristics of the product. Furthermore, wine is seen by young adult consumers as old fashion, formal and mostly not associated with their relaxed attitude and “on the move” lifestyle. The objective of this paper is to analyse the usability key principles and heuristic and their applicability in wine marketing as a mean to improve the perception and increase understanding of wine for the young and/or novice consumers. The paper aims to review the existing knowledge and findings about the concept of usability (with special emphasis on Usability Engineering and Human Computer Interaction (HCI)), in order to explore the aspects applicable in wine marketing. The usability concept proves useful in wine marketing to simplify the decision process, to make the meeting with the product less intimidating and more engaging, and to decrease the risk perception for the inexperienced wine consumers.
Improved PSO Approach for The Solution of Unit Commitment Problem

Unit commitment problem (UCP) is a large scale nonlinear hybrid integer programming problem and it involves determining on/off states of units and generations of units. This paper proposes an improved particle swarm optimization (IPSO) for the solution of UCP. In the proposed approach, the on/off states of units are limited into feasible schedules by providing a new method related to a time order at first. After that, the problem is transformed into a simple economic load dispatch problem. Then this dispatch problem is solved by an improved priority list technique instead of the classical equal lambdaiteration method. All the above improvements are embedding into the framework of PSO approach for UCP. It is seen from the numerical results that the presented algorithm surely possesses a high quality and a high convergence speed. Keywords-unit commitment problem; particle swarm optimization; time order; priority list
MULTILEVEL GENERALIZED STRUCTURED COMPONENT ANALYSIS

Generalized structured component analysis has been proposed as an alternative to partial least squares for path analysis with latent variables. In practice, observed and latent variables may often be hierarchically structured in that their individual-level scores are grouped within higher-level units. The observed and latent variable scores nested within the same higher-level group are likely to be more similar than those in different groups, thereby giving rise to the interdependence of the scores within the same group. Unless this interdependence is taken into account, obtained solutions are likely to be biased. In this paper, generalized structured component analysis is extended so as to account for the nested structures of both observed and latent variables. An alternating least-squares procedure is developed for parameter estimation. An empirical application concerning the measurements of customer-level customer satisfaction nested within different companies is presented to illustrate the usefulness of the proposed method.
Towards polarizing beam splitters for cold neutrons using superparamagnetic diffraction gratings

For holographic gratings recorded in superparamagnetic nanoparticle-polymer composites the diffraction efficiency should – next to grating spacing, nanoparticle concentration and grating thickness – depend on the strength of an external magnetic field and the incident neutron spin state. As a consequence, diffraction gratings should be tunable to act as mirrors for one spin state, while being essentially transparent for the other. Thus, polarizing beam splitters for cold neutrons become feasible.
A Model of International Asset Pricing with a Constraint on the Foreign Equity Ownership

This paper derives a closed-form valuation model in a two-country world in which the domestic investors are constrained to own at most a fraction, δ, of the number of shares outstanding of the foreign firms. When the “δ constraint” is binding, two different prices rule in the foreign securities market, reflecting the premium offered by the domestic investors over the price under no constraints and the discount demanded by the foreign investors. The premium is shown to be a multiple of the discount, the multiple being the ratio of the aggregate risk aversion of the domestic and foreign investors. Given the aggregate risk-aversion parameters, the equilibrium premium and discount are determined by the severity of the δ constraint and the “pure” foreign market risk.
Polymers for Cardiovascular Stent Coatings

Polymers have found widespread applications in cardiology, in particular in coronary vascular intervention as stent platforms (scaffolds) and coating matrices for drug-eluting stents. Apart from permanent polymers, current research is focussing on biodegradable polymers. Since they degrade once their function is fulfilled, their use might contribute to the reduction of adverse events like in-stent restenosis, late stent-thrombosis, and hypersensitivity reactions. After reviewing current literature concerning polymers used for cardiovascular applications, this review deals with parameters of tissue and blood cell functions which should be considered to evaluate biocompatibility of stent polymers in order to enhance physiological appropriate properties. The properties of the substrate on which vascular cells are placed can have a large impact on cell morphology, differentiation, motility, and fate. Finally, methods to assess these parameters under physiological conditions will be summarized.
Hume's Naturalized Philosophy

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The peripartum period influenced the serum macromineral profile in mares

Abstract. Changes in metabolic requirements during pregnancy may produce nutritional imbalances predisposing mares to pathological conditions. Therefore, we aimed to examine changes in serum macrominerals during the peripartum period in mares. Fifteen pregnant mares (Group A) were monitored starting at the 263rd day of pregnancy until the 21st day after foaling. Seven non-pregnant and non-lactating mares were used as a control group (Group B). Group A was subjected to blood sampling within 24 ± 12 h after parturition (P) and then 7, 14 and 21 days after foaling (+1, +2, +3 weeks, respectively). Group B was subjected to regular sampling throughout the study to ensure that seasonal changes had no significant effect on studied parameters. Serum samples were analysed for serum electrolytes including sodium (Na+), potassium (K+), calcium (Ca+ + ), phosphorus (P+), chloride (Cl−) and magnesium (Mg+ + ). Two-way repeated measures of analysis of variance (ANOVA) was applied to evaluate significant effects of peripartum on electrolyte concentrations. Group A showed a decrease in Cl− concentrations (P = 0.011) after foaling and lower P+ concentrations (P = 0.015) compared to Group B throughout the study. The linear regression model showed an increase in Na+ concentrations (P = 0.002) and a gradual decrease in serum Ca+ + (P = 0.001) during pregnancy. Because the most significant changes in serum electrolytes occurred within 2 weeks before and 2 weeks after foaling, monitoring serum electrolyte concentrations would indicate whether the mare needs further mineral supplementation at this stage. The significant changes in a mare's macromineral profile that we observed over the peripartum provide enhanced knowledge about mineral interrelations and their modifications during specific physiological conditions such as late pregnancy and early postpartum.
Textures of Peritectic Crystals as Guides to Reactive Minerals in Magmatic Systems: New Insights from Melting Experiments

Peritectic crystals in igneous rocks may be derived from either the source or country rocks, or may have formed by reactive assimilation of source-inherited solids, primary magmatic minerals during self- or magma mixing, or country-rock xenoliths or xenocrysts. Identifying such peritectic crystals is important for constraining the components and textures of igneous rocks and the underlying processes of magmatic evolution. In this study we demonstrate that peritectic olivine formed in melting experiments crystallizes as clusters of euhedral to subhedral crystals. Olivine replacing orthopyroxene, amphibole, and phlogopite forms crystal clusters with distinct crystal to melt ratios, 2D surface area, grain boundary segmentation, and inclusion relations. In our experiments the textures of peritectic crystals are primarily controlled by the stability temperature and decomposition rate of reactive minerals. High-temperature minerals such as orthopyroxene slowly decompose to form high-density clusters of large crystals with long grain boundary segments. The SiO2-rich peritectic melt produced favours formation of melt inclusions. Low-temperature minerals such as amphibole and phlogopite rapidly decompose to form low-density clusters of small crystals with short grain boundary segments. The relatively SiO2-poor peritectic melt produced results in the formation of fewer melt inclusions. Host melt composition has a minor effect on the textures of peritectic olivine formed in the melting experiments of this study and previous contamination experiments, but affects the assemblages of the peritectic crystal clusters. Cluster density and 2D surface area of peritectic olivine tend to decrease, whereas grain boundary segment length increases with increasing experimental temperature and H2O content. Using textural criteria that distinguish olivine formed after different minerals in our melting experiments, we hypothesize that two olivine populations from a basaltic^andesitic lava flow of the Tatara^San Pedro volcanic complex, Chile, may be peritectic crystals formed after amphibole and orthopyroxene. Both amphibole and orthopyroxene are common in xenoliths preserved in some Tatara^San Pedro lava flows. One notable difference between the experimental and natural olivine crystals is that the natural olivine crystals have 2D surface areas and 2D grain boundary segments up to � 1000 and � 100 times larger, respectively, than those produced in our experiments. We propose that this size difference is primarily controlled by comparatively slow heating and decomposition of reactive crystals and textural coarsening of peritectic crystals during prolonged magma residence in the natural system.