Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of Nanometric Bi 4 Ti 3 O 12 Powders : from Synthesis to Optical and Dielectric Properties

This paper aims to evaluate the synthesis and annealing parameters for production of nanometric Bi4Ti3O12 and its properties. The powders were obtained through the solution combustion route and the impacts of annealing temperature on the materials’ physicochemical features as well as their optical and electrical properties were investigated. Thus, the prepared powders were annealed at 600oC, 700oC and 800oC and then characterized by several techniques. The results demonstrated that the combustion method was effective for production of nanocrystalline powders with high levels of purity. A trend for particle and crystallite growth was observed as the calcination temperature increased. X-Ray, HRTEM and Raman spectroscopy confirmed the crystalline nature of the powders, whereas impedance spectroscopy demonstrated a reduction of electrical resistance according to the calcination temperature applied. Optical properties were not highly influenced by annealing. The temperature of 600oC was appropriate to produce crystalline particles with desirable low sizes for application.
UCR-VCG @ TRECVID 2018: Video to Text Retrieval

We participated in the video to text description: matching and ranking task in TRECVID 2018. The goal of this task is to return a ranked list of the most likely text descriptions that correspond to each video in the test set. We trained joint visual-semantic embedding models using image-text pairs from an image-captioning dataset and applied to the video-text retrieval task utilizing key frames of videos extracted by a sparse subset selection approach. Our retrieval system performed reasonably across all the testing sets. Our best system, which uses a late-fusion of similarity scores obtained from the key frames of a video, achieved mean inverted ranking score of 0.225 on the testing set C, and we ranked the 4th overall on this task.
Consideration of disturbances and deficiencies in the moisture safety design of tall timber facades

In order to create high quality and durable wooden buildings, a close look at moisture exposure is necessary. Too often, the moisture design process considers only the plain wall without disturbances or deficiencies. This paper points out the necessity to take details and human errors into account as well. Moreover, it gathers current knowledge about deficiencies in standards and literature and compiles it in a critical way. Simulations and experiments with intended deficiencies are presented and discussed.
Enhancing Recommendation Diversity by a Dual Recommendation Interface

e beyond-relevance objectives of recommender system are getting more and more aention in the eld. For example, a diversityenhanced interface has been shown positively associate with the user satisfaction. However, lile is known about how a diversityenhanced interface can help users to fulll the various real-world tasks. In this paper, we present a visual diversity-enhanced interface which presents recommendations in a two-dimensional scaer plot. Our goal was to design a recommender system interface to explore dierent relevance prospects of recommended items in parallel and stress their diversity. A within-subject user study with real-life tasks was conducted to compare our visual interface with a standard ranked list interface. Our user study results show that the visual interface signicantly reduced the exploration eorts for the explored tasks. Also, the users’ subjective evaluation shows signicant improvement on many user-centric metrics. We show the user did explore a diverse set of recommended items while improving the user satisfaction.
Relationship Between Working Memory and Study Support of Students at Higher Education Institution

At Japanese higher education institutions, there are many difficulties in receiving medical diagnosis, and students offer the support needs by themselves. So how to apply support need for students with developmental disorders is an issue. students with cognitive imbalance do not always have a high level of “Support Need” and often do not lead to utilize study support the purpose of this study is to examine the characteristics of students who need study support in relation to working memory. We divided 71 students into 2 or 3 groups by based on WMI score (High, Middle, Low) or whether they need study support (HNSG) or not (LNSG). For each of them, the results of relations between WMI score and “(a) Support Need Inventory for University Life (Sasaki, Takahashi, & Takeda, 2018)”, “ (b) AQ Japanese version”, “ (c) CAARS Japanese version” were described by descriptive statistics respectively. And compared between groups. Result; it was confirmed that the deviations of score related to “Digit Span” is relatively large. It seemed that LSNG might have had “Support Need” and "Autism Spectrum Disorder like characteristics", but their influence on daily life might have been small.
Rationality and bounded rationality: you can’t have one without the other

Abstract This article compares and contrasts the various perspectives on rationality and bounded rationality, and in doing so, advances two claims. The central one is that the definition of rationality depends on bounded rationality. This is reminiscent of debates in philosophy concerning the definition of concepts in terms of their opposites, which has led to efforts to destabilise dichotomies. In addition, as argued in this article, there is a related connection between the (bounded) rationality of economists and the agents they study.
Machine-Learning-Based Column Selection for Column Generation

Column generation (CG) is widely used for solving large-scale optimization problems. This article presents a new approach based on a machine learning (ML) technique to accelerate CG. This approach, called column selection, applies a learned model to select a subset of the variables (columns) generated at each iteration of CG. The goal is to reduce the computing time spent reoptimizing the restricted master problem at each iteration by selecting the most promising columns. The effectiveness of the approach is demonstrated on two problems: the vehicle and crew scheduling problem and the vehicle routing problem with time windows. The ML model was able to generalize to instances of different sizes, yielding a gain in computing time of up to 30%.
EVALUATION OF DIFFERENT IMAGE SEGMENTATION METHODS WITH RESPECT TO COMPUTATIONAL SYSTEMS

Image segmentation is a fundamental step in the modern computational vision systems and its goal is to produce amore simple and meaningful representation of the image making it easier to analyze. Imagesegmentation is a subcategory of image processing ofdigital images and, basically, it divides a given image into two parts: the object(s) of interest and the background. Image segmentation is typically used to locate objects and boundaries in images and its applicability extends to other methods such as classification, feature extraction and pattern recognition. Most methods are based on histogram analysis, edge detection and region-growing. Currently, other approaches are presented such as segmentation by graph partition, using genetic algorithms and genetic programming. This paper presents a review of this area, starting with taxonomy of the methods followed by a discussion of the most relevant ones.
Extinction risk and conservation of marine bony shorefishes of the Greater Caribbean and Gulf of Mexico

1 International Union for Conservation of Nature Marine Biodiversity Unit, Department of Biological Sciences, Old Dominion University, Norfolk, Virginia, USA Smithsonian Tropical Research Institute, Balboa, Panama Department of Organismal and Environmental Biology, Christopher Newport University, Newport News, Virginia, USA School of Mathematics and Natural Sciences, Arizona State University, Glendale, Arizona, USA Program in Sustainability, Florida Institute of Technology, Melbourne, Florida, USA Correspondence Kent E. Carpenter, International Union for Conservation of Nature Marine Biodiversity Unit, Department of Biological Sciences, Old Dominion University, Norfolk, Virginia, USA. Email: kcarpent@odu.edu Funding information National Fish and Wildlife Foundation, Grant/ Award Number: 37733; Agence Française de Développement
Phytochemical Study and Evaluation of Antimicrobial , Antioxidant and Insecticidal Activity of Essential Oils and Polyphenols of Bitter Orange ( Citrus Aurantium L . )

In this study, we conducted a phytochemical screening followed by evaluation of the antimicrobial and antioxidant activity of essential oils and polyphenols of Citrus aurantium. In parallel, we evaluated the insecticide effect of polyphenolic extract of Citrus aurantium L. on the larvae of Galleria mellonela, for this, we evaluated the mortality rate, TL50 and DL50. The phytochemical screening has allowed us to highlight the presence of secondary metabolites in the leaves and bark of Citrus, like saponins, mucilage, and flavonoids with significant amounts. Observations on the antibacterial activity show that Staphylococcus aureus is the most sensitive strain, followed by Escherichia coli, the polar extracts proved devoid of any antifungal activity against Saccharomyces cerevisiae, and Aspergillus sp. Two phytopathogenic bacteria were treated with polyphenols of Citrus aurantium ; Pseudomonas savastanoi and Pectobacterium spedonicus. The test of antibacterial activity showed a growth inhibition of these two phyopathogènes bacteria. The evaluation of the antioxidant, revealed an important activity. Concerning the insecticidal effect of the polyphenols of the bitter orange leaves on the larvae of the wax moth Galleria mellonela, very significant results are achieved with 100% mortality recorded 24 hours after treatment at the high dose (30μl / ml). Keywords— Citrus aurantium L. , characterization, essential oil, polyphenols, activity. Oulebsir-Mohandkaci Hakima1 Laboratory of Valorization and Conservation of Biological Resources, Department of Biology, Faculty of Sciences, University M'hamed Bougara of Boumerdes, BP35000, Algeria Ait Kaki Sabrina2 Laboratory of Soft Technology, Valorization, Physicochemical of Biological Material and Biodiversity. University M’hamed Bougara of Boumerdes. 35000, Algeria. Behidj Nassima3 Laboratory of Soft Technology, Valorization, Physicochemical of Biological Material and Biodiversity. University M’hamed Bougara of Boumerdes. 35000, Algeria.
Does crop diversification reduce downside risk in maize yield enhancing investments? Evidence from Ethiopia using panel data

Using a unique household level panel data collected from the major maize producing regions of Ethiopia, this study assesses the role of crop diversification in minimizing the downside risks associated with the use of improved seed and chemical fertilizer in maize production. Empirical results show that maize-legume intercropping and rotation increases the average maize yield and reduces downside risk as captured by the estimated yield distribution using Endogenous Switching Regression models and quintile moment approaches. Controlling for plot and household level characteristics that may induce selection bias in technology adoption, maximum yield was obtained on plots with maize-legume rotation or intercropping sequences. The contribution of crop diversification in reducing downside risk in maize yield was higher when diversification was applied to plots that received improved seed and chemical fertilizers. In addition to the technical support provided to smallholder farmers on the use of improved seed and chemical fertilizer in maize production, the existing agricultural extension program in Ethiopia may also need to give due emphasis to both spatial and temporal crop diversification practices to enhance crop productivity further and reduce the potential downside risk hampering smallholder farmers initiatives in investing in purchased agricultural inputs in maize production. Acknowledgement : The authors would like to acknowledge two projects financially supported the collection of panel data used in this study: Sustainable Intensification of Maize-Legume cropping systems for food security in Eastern and Southern Africa (SIMLESA) project funded by the Australian Center for International Agricultural Research (ACIAR) and Diffusion and Impact of Improved Varieties in Africa (DIIVA) project funded by Bill and Melinda Gates Foundation (BMGF) through Bioversity International which collaborated with the Standing Panel for Impact Analysis (SPIA) in the CGIAR and CIMMYT. Views in this paper are of the authors. The usual disclaimer also works here.
PISA 2015 Matematik Okuryazarlığını Etkileyen Faktörlerin Eğitsel Veri Madenciliği ile Çözümlenmesi

The aim of this study is to determine the factors affecting PISA 2015 Mathematics literacy by using data mining methods such as Multi-layer Perceptron Artificial Neural Networks and Random Forest. Cause and effect relation within the context of the study was tried to be discovered by means of data mining methods at the level of deep learning. In terms of Prediction Ability, the findings of the method whose performance was high were accepted as the factors determining the qualifications in Mathematics literacy in Turkey. In this study, the information, which was collected from a total of 4422 students, 215 (49%) of whom were boys and 2257 (51%) of whom were girls participating in PISA 2015 test, was used. The scores, which the students, having gone in for PISA 2015 test, got from mathematics test, and dependent variables and 25 variables, which were thought to have connection with dependent variables institutionally, were included in the analysis as predictors. As a result of analysis, it was witnessed that Random Forest (RF) method made prediction with smaller errors in terms of a number of performance indicators. The factors that random forest method found important after anxiety variable are Turkish success level of students, mother education level, motivation level, the belief in epistemology, interest level of teachers and class disciplinary environment, respectively. The statistical meaning, significance and impact levels of other variables were tackled together with their details in this study. It is expected that this study will set an example for data mining use in the process of educational studies and that the factors whose affects were found out about the students’ mathematics literacy will shed light on National Education system.
Global synthesis of the effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield across global regions is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control and pollination services in adjacent crops using a global dataset of 529 sites. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimize floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.
Comparison of gamma-densitometry tomography and electrical-impedance tomography for determining material distribution in liquid-solid flows

The spatial distribution of materials in multiphase flows is of importance to many industrial processes. For example, in indirect coal liquefaction, a reactive gas is bubbled through a catalyst-laden liquid (slurry), and a spatially nonuniform gas distribution can reduce process efficiency by inducing large-scale buoyancy-driven recirculating flows. Gamma-densitometry tomography (GDT) and electrical-impedance tomography (EIT) are techniques with the potential of providing spatially resolved information on material distribution in multiphase flows. GDT and EIT have both been applied to a liquid-solid flow for comparison purposes. The experiment consisted of a cylinder (19 cm diameter) filled with water, in which 80 {micro}m glass spheres were suspended by a mixer to achieve solid volume fractions of 0.01, 0.02, and 0.03. Both GDT and EIT revealed a relatively uniform distribution of solids in the measurement plane, and the average solid volume fractions from both techniques were in good agreement.
Emotional recognition of children with high-functioning autism spectrum disorder

In everyday life, people generally infer others’ feelings and behave accordingly based on these assessments. It is necessary to appropriately understand others’ emotions in order to maintain harmonious interpersonal relationships. Facial expressions are considered an obvious cue containing a wealth of information regarding human emotions. Therefore, it is essential that we are able to adequately recognize facial expressions as a way to infer others’ emotions. Autism spectrum disorder (ASD) is characterized by three major symptoms: impairments concerning social interactions, communication, and restricted or repetitive interests and behaviors (American Psychiatric Association, 2000). Golan & Baron-Cohen (2006) suggest that one factor associated with social dysfunction among individuals with ASD is a difficulty in understanding others’ emotions due in part to impairment in interpreting facial expressions. However, this deficit is not always observed: although some studies show evidence of an impairment or abnormality in emotion recognition in individuals with ASD (e.g., Celani, Battacchi, & Arcidiacono, 1999; Davies, Bishop, Manstead, & Tantam, 1994; Hobson, 1986; Lindner & Rosén, 2006), others show that individuals with ASD and typically developing (TD) groups have equal abilities (e.g., Baron-Cohen, Wheelwright, & Jolliffe, 1997; Capps, Yirmiya, & Sigman, 1992; Castelli, 2005; Homer & Rutherford, 2008). Several perspectives could explain this inconsistency. First, there could be differences in intellectual levels among individuals with ASD. The intended clinical participants in previous studies Emotional recognition of children with high-functioning autism spectrum disorder
Strategic change and adaptation in the context of dynamic capacity development

This study aims to understand the process of change and strategic adaptation of a family business focused on the management of health units, located in the northwest of Rio Grande do Sul, in the period between 2013 and 2018. It seeks to understand the critical periods existing in the organization's history and what dynamic capabilities prevail at those times. As for the methodological aspects, this is a unique case study, of descriptive nature and qualitative approach. The periods of strategic change were analyzed from the dimensions proposed by Pettigrew, Ferlie and Mckee (1992), context, content and process and through longitudinal and historical analysis through direct research procedures (Mintzberg, 1983). With the realization of the study, it was possible to characterize the organization's history in four strategic periods: Birth (2013-2014), Critical period (2015), Reflections and repositioning (2016) and Reorganization of organizational structure (2017-2018). The analyzes pointed out that the dynamic capacities that had an emphasis in each period were respectively: absorptive capacity, adaptive capacity, absorptive capacity and adaptive capacity. The organization has demonstrated, therefore, internal competences and receptivity to the demands of new services from the environment by the users of the services themselves. In each period it was able to reorganize its resources and competences and shows indications of search also of the development of the innovative capacity.
Observation of topological transition in highT c superconductor FeTe

Superconductors with topological surface or edge states have been intensively explored for the prospect of realizing Majorana bound states, which obey non-Abelian statistics and are crucial for topological quantum computation. The traditional routes for making topological insulator/superconductor and semiconductor/superconductor heterostructures suffer fabrication difficulties and can only work at low temperature. Here, we use angleresolved photoemission spectroscopy to directly observe the evolution of a topological transition of band structure nearby the Fermi level in two-dimensional high-Tc superconductor FeTe1-xSex/SrTiO3(001) monolayers, fully consistent with our theoretical calculations. Furthermore, evidence of edge states is revealed by scanning tunneling
Insecticidal potential of aqueous and solvent extracts of Cassia fistula, Cleome viscosa and Capparis decidua against Callosobruchus chinensis L. (Coleoptera: Bruchidae)

In the present investigation different bioassays were conducted to evaluate insecticidal potential of Cassia fistula, Cleome viscosa, Capparis decidua extracts against the pulse beetle Callosobruchus chinensis. Various solvent extracts such as acetone, chloroform, petroleum ether, methanol, hexane and water were prepared and used to expose the insects. These have shown very high insecticidal potential as LD50 obtained in each solvent extract was very low. In addition both solvent and aqueous extracts significantly repelled large no. of insects at a very low dose. When beetles were exposed with sub-lethal doses of above extracts it also significantly inhibited oviposition in C. chinensis as the % ODI (oviposition deterrence index) was obtained very high i.e. 56.31% to 85.51%. The study showed that solvent extracts of these plants showed 90-100% mortality that may be due to presence of toxic components in above plant species which can be used to control insects if isolated and used in pure form.