Miracle-dz/UniFAR-FTUs huggingface dataset:
Do institutional networks affect winery survival?

PurposeThe present study aims to provide new evidence regarding the factors that determine the survival of firms in the Spanish wine industry and to improve the understanding of sector dynamics.Design/methodology/approachThe empirical analysis, conducted over a representative sample of wineries in the DOC Rioja wine industry, is based on non-parametric (Kaplan–Meier graph) and semi-parametric survival models (Cox proportional hazard model). FindingsThe empirical model finds that wineries with a higher number of networks with institutions enjoy better survival prospects. This study also shows that a winery’s previous performance affects the winery’s survival probability; therefore, successful wineries in the past encounter a smaller hazard of exit. Although spending on R&D and exporting are factors likely to improve wineries' efficiency and competitiveness, these factors did not contribute significantly to the survival of DOC Rioja wineries.Originality/valueThis paper makes a significant contribution to the understanding of the determinants of wineries' survival and has important policy implications. In order to raise the probability of survival, policy makers should promote the networks that link wineries and institutions. Moreover, this study is based on survival analysis which, although frequently used in medical and behavioural sciences, has rarely been applied to wine economics. Finally, it uses a unique data set obtained from primary data collection, which previous studies have not analysed in relation to the probability of winery survival.
Functionnal and Technological Properties of Five Strawberry (Arbutus Unedo L.) Fruit as Bioactive Ingredients in Functional Foods

ABSTRACT The objective of this study was to identify, quantify, and elucidate the polyphenols, flavonoids, and anthocyanins, and their antioxidant activities (via 13 2,2-diphenyl-1-picrylhydrazyl) (DPPH) radical and 2,2ʹ-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical cation scavenging abilities and bleaching β-carotene tested in vitro in the whole fruit, fruit skin of strawberry tree fruits of 5 genotypes and to find out the most valuable fruit for disease preventing diets. Total phenols, total flavonoids, total anthocyanins, antioxidant activity (DPPH, ABTS and β-carotene bleaching assay), pH, titrable acidity, soluble solids, and organic acids were investigated in five strawberry tree genotypes belonging to several areas in Morocco. Qualitative and quantitative analyses of individual phenolic compounds by high-performance liquid chromatography (HPLC) were also carried out. Significant differences (p˂0.05) were observed across the five genotypes in total phenols (25.37–39.06 mg GAE/g DW), total flavonoids (3.30–7.07 mg RE/g DW), total anthocyanins (0.15–0.64 mg cya-3-glu/100 g DW), pH (2.44–3.92), titrable acidity (0.65–1.01 g malic acid/100 g fw), and soluble solids (14.83–18.53%). The antioxidant activity was evaluated by three assays. The values were 3.33–21.08, 2.25–19.58, and 1.08–13 mg AAE/g DW for DPPH scavenging test, ABTS, and β-carotene bleaching, respectively. Gallocatechol and catechin were the most abundant phenolic compounds. Principal component analysis showed that the ﬁrst three components formed 90.25% of the total inertia. Chlorogenic acid, ellagic acid derivative I, ellagic acid, rutin, and cyanidin-3,5-diglucoside were the most involved variables in the total variance explained.
Translating RNA Splicing Analysis into Diagnosis and Therapy

A large proportion of rare disease patients remain undiagnosed and the vast majority of such conditions remain untreatable whether diagnosed or not. RNA splicing analysis is able to increase the diagnostic rate in rare disease by identifying cryptic splicing mutations and can help in interpreting the pathogenicity of genomic variants. Whilst targeted RT-PCR analysis remains a highly sensitive tool for assessing the splicing effects of known variants, RNA-seq can provide a more comprehensive transcriptome-wide analysis of splicing. Appropriate care should be taken in RNA-seq experimental design since sample quality, processing, choice of library preparation and sequencing parameters all introduce variability. Many bioinformatic tools exist to aid both in the prediction of splicing effects from DNA sequence and in the handling of RNA-seq data for splicing analysis. Once identified, splicing abnormalities may be amenable to correction using antisense oligonucleotide compounds by masking cryptic splice sites or blocking key splice regulatory elements, or by use of alternative corrective technologies such as trans-splicing. A growing number of such drugs have started to enter clinical use, most notably nusinersen for the treatment of spinal muscular atrophy. By bringing together the fields of RNA diagnostics and antisense therapeutics, it is becoming feasible to envisage the development of a truly personalised medicine pipeline. This has already been shown to be possible in the case of milasen, an n=1 bespoke antisense drug, and the growth and convergence of these technologies means that similar therapeutic opportunities should arise in the near future.
Can feedback, correct, and incorrect worked examples improve numerical magnitude estimation precision?

Abstract We investigated whether three interventions – studying incorrect worked examples, studying correct worked examples, or receiving feedback – improved children’s 0–1,000 (Experiment 1) and adults’ 1 thousand–1 billion (Experiment 2) number-line estimation precision relative to a no intervention control group. At pretest, participants estimated numbers on number lines (without feedback or examples) and judged their confidence in each estimate. They were then assigned to an intervention group, completed intervention trials, and then estimated numbers and judged their confidence at posttest. Children’s and adults’ confidence judgments did not increase from pretest to posttest. However, consistent with prior research, feedback improved children’s and adults’ estimation precision from pretest-to-posttest. Importantly, studying correct worked examples also improved precision, but studying incorrect worked examples did not. Although not all children benefited from training, those who did were able to transfer their knowledge to a number-categorization task. Adults in the feedback group were also able to transfer their learning. These outcomes highlight benefits of studying worked examples for improving children’s and adults’ estimation precision, but to obtain benefits, corrective feedback must be included.
An Improved Data Fusion Method for Water Quality Sensors

This paper proposes an improved data fusion method for water quality sensors. First, a deep learning network model is formed by stacking automatic encoder and sparse automatic encoder, so as to realize feature mining and sparse representation of sample data. Second, after large-scale sample training, the network model may fit complex nonlinear functions, and has certain generalization ability for low-quality sample data. As a result, the accuracy of prediction and classification can be improved. The experimental results demonstrate that the proposed method can obtain higher classification accuracy.
Cambodian Teacher Educators’ Attitudes towards the Use of Information and Communication Technologies (ICT) in Education: Trends and Patterns

The effective use of Information and Communication Technologies (ICT) can improve educational quality, especially develop the 21 st century skills. Whether teachers use ICT in their teaching or not depends on their attitudes towards the use of ICT. The purposes of the study were to investigate the trends and patterns of Cambodian basic education teacher educators’ attitudes towards the use of ICT. The total sample of 135 teacher educators from both Phnom Penh Teacher Education College and Battambang Teacher Education College were purposively selected to participate in the survey. The findings indicated that teacher educators had a positive attitude towards the use of ICT. They had very high intention towards the use of ICT compared to their emotion and belief. There were significant differences across gender, computer experience, and ICT training while their age did not. To enhance teacher educators’ attitudes, the Ministry of Education, Youth, and Sport (MoEYS) of Cambodia should consider the provision of sufficient ICT training so as to equip them with more computer experience before being able to use it in their teaching and learning process.
Diversity and Communities of Fungal Endophytes from Four Pinus Species in Korea

Fungal endophytes are ubiquitous in nature. They are known as potential sources of natural products, and possible agents for biocontrol attributing to their ability to produce a repertoire of bioactive compounds. In this study, we isolated fungal endophytes from three different tissues (needle, stem and root) of four Pinus species (Pinus densiflora, Pinus koraiensis, Pnus rigida, and Pinus thunbergii) across 18 sampling sites in Korea. A total number of 5872 culturable fungal endophytes were isolated using standard culturing techniques. Molecular identification based on the sequence analyses of the internal transcribed spacer (ITS) or 28S ribosomal DNA revealed a total of 234 different fungal species. The isolated fungal endophytes belonged to Ascomycota (91.06%), Basidiomycota (5.95%) and Mucoromycota (2.97%), with 144 operational taxonomic units (OTUs) and 88 different genera. In all sampling sites, the highest species richness (S) was observed in site 1T (51 OTUs) while the lowest was observed in site 4T (27 OTUs). In terms of diversity, as measured by Shannon diversity index (H’), the sampling site 2D (H′ = 3.216) showed the highest while the lowest H’ was observed in site 2K (H’ = 2.232). Species richness (S) in three different tissues revealed that root and needle tissues are highly colonized with fungal endophytes compared to stem tissue. No significant difference was observed in the diversity of endophytes in three different tissues. Among the four Pinus species, P. thunbergii exhibited the highest species richness and diversity of fungal endophytes. Our findings also revealed that the environmental factors have no significant impact in shaping the composition of the fungal endophytes. Furthermore, FUNGuild analysis revealed three major classifications of fungal endophytes based on trophic modes namely saprotrophs, symbiotrophs, and pathotrophs in four Pinus species, with high proportions of saprotrophs and pathothrops.
Coordinating Entrainment Phenomena: Robot Conversation Strategy for Object Recognition

This study proposes a robot conversation strategy involving speech and gestures to improve a robot’s indicated object recognition, i.e., the recognition of an object indicated by a human. Research conducted to improve the performance of indicated object recognition is divided into two main approaches: development and interactive. The development approach addresses the development of new devices or algorithms. Through human–robot interaction, the interactive approach improves the performance by decreasing the variability and the ambiguity of the references. Inspired by the findings of entrainment and entrainment inhibition, this study proposes a robot conversation strategy that utilizes the interactive approach. While entrainment is a phenomenon in which people unconsciously tend to mimic words and/or gestures of their interlocutor, entrainment inhibition is the opposite phenomenon in which people decrease the amount of information contained in their words and gestures when their interlocutor provides excess information. Based on these phenomena, we designed a robot conversation strategy that elicits clear references. We experimentally compared this strategy with the other interactive strategy in which a robot explicitly requests clarifications when a human refers to an object. We obtained the following findings: (1) The proposed strategy clarifies human references and improves indicated object recognition performance, and (2) the proposed strategy forms better impressions than the other interactive strategy that explicitly requests clarifications when people refer to objects.
A wideband microstrip triangle patch antenna with double dumbbell shaped Defective Ground Structure for 5G application

In the 5G cellular communication system requires an antenna that has a wide bandwidth and works at millimeter-wave frequencies. In this study, the addition of defective ground structure (DGS) to a microstrip triangle antenna was developed to improve bandwidth performance. Development is carried out through the addition of a double dumbbell-shaped at the DGS antenna structure that works at 28 GHz for 5G applications. The sample design is 4T4R microstrip antenna using Rogers RT5880 substrate material with a dielectric constant (ε_r) of 2.2, h = 0.787 mm. The sample antenna design has dimension 30.11 × 19.89 mm. This study uses a research and development approach through the calculation of DGS structure and design of multiple dumbbell-shaped on the ground layer. The simulation and measurement results show a significant increase in bandwidth performance compared to without using DGS. This study also shows the improvement in bandwidth performance and the gain of microstrip antenna with the addition of double dumbbell-shaped compared to the addition of single dumbbell-shaped in previous studies.
Robustness and Sensitivity Tuning of the Kalman Filter for Speech Enhancement

The inaccurate estimates of linear prediction coefficient (LPC) and noise variance introduce bias in Kalman filter (KF) gain and degrades speech enhancement performance. The existing methods proposed a tuning of the biased Kalman gain particularly in stationary noise condition. This paper introduces a tuning of the KF gain for speech enhancement in real-life noise conditions. First, we estimate noise from each noisy speech frame using a speech presence probability (SPP) method to compute the noise variance. Then construct a whitening filter (with its coefficients computed from the estimated noise) and employed to the noisy speech, yielding a pre-whitened speech, from where the speech LPC parameters are computed. Then construct KF with the estimated parameters, where the robustness metric offsets the bias in Kalman gain during speech absence to that of the sensitivity metric during speech presence to achieve better noise reduction. Where the noise variance and the speech model parameters are adopted as a speech activity detector. The reduced-biased Kalman gain enables the KF to minimize the noise effect significantly, yielding the enhanced speech. Objective and subjective scores on NOIZEUS corpus demonstrates that the enhanced speech produced by the proposed method exhibits higher quality and intelligibility than some benchmark methods.
Generation of Handwritten Numbers Using Generative Adversarial Networks

As a promising generative modeling method, Generative Adversarial Networks are a deep-learning-based generative model, in which two networks, namely the generative network and the discriminant network, contest with each other in a game during which the generator “learns” and get trained to be able to fool the discriminator of believing a specific image is (superficially) authentic. It is widely used to generate pictures based on existing data. Based on the MNIST data set, this paper studies and analyzes the application of Generative Adversarial Networks in the generation of handwritten digital images. In addition, by studying the Deep Convolutional Generative Adversarial Network and the Conditional Generation Adversarial Network model, we compared the connections and differences between these three models in training the MNIST dataset to generate handwritten digits algorithms, and gave an optimization method for generating handwritten digits.
Unpleasant Emotions in Linking Cognitive Appraisals and Academic Procrastination in Doing Thesis Article: A Perspective of Control-Value Theory

The objective the present study was to investigate the relationships among cognitive appraisals (selfefficacy, value, and causal attribution), unpleasant emotions (anxiety, anger, boredom, and hopeless), and academic procrastination (intention-behavior discrepancy, lack of promptness, and preferences in choosing activities) in college student while they were doing thesis. More specifically, the study investigated the mediating role of unpleasant emotions in linking cognitive appraisals and procrastination in doing thesis from the perspective of the expectancy-value theory. A total of 128 college students completed a self-reported survey for the study. The results of the study showed that unpleasant emotions influencing procrastination in doing thesis is anxiety, which was also influenced by cognitive appraisals, self-efficacy particularly. Based on the findings of the current research, it seemed that to increase perseverance and engagement in doing thesis could be done by increasing the efficacy of students so that it will reduce anxiety. Keywords—emotions, Linking Cognitive, Procrastination,
Omni-Directional Wideband Antenna Array with Solar Cells

Distributed sensor networks are becoming more and more widespread due to their substantial benefits to our daily lives. These sensors, in most cases, are distributed in nature and even may require mobility. This, in turn, implies omnidirectional collector units to collect the data from various sensors at arbitrary directions. This work summarizes the performance outcomes of various integrated wide-band antenna structures and solar power generation topologies to achieve equal gain in all directions. Purpose of the array in this instance is contrary to enhance the received signal levels in all directions. Low-cost solutions ranging from the planar helical printed circuit board (PCB) designs to vertical wire helical antennas were investigated. An optimum design structure for multiple ISM bands (868 MHz to 915 MHz) was proposed and characterized considering the cost, size, directional coverage and most significantly RF sensitivity and range of the overall design. The final water-resistant solarpowered wideband transceiver front-end has provided range improvement and omnidirectional radiation pattern. The system consists of a 190mm x 190mm low-cost FR4 substrate and a Wilkinson network to combine the power of 8 helical wire antennas sprinkled along with the solar cells. The self-contained, Sun-powered unit resulted in 4.5-dB sensitivity improvement in measurements.
Radioiodination of Quetiapine and Cyclobenzaprine as Brain Monitoring Agents: Comparative Study on SPECT Imaging

The aim of this study is to use new drugs capable of crossing the blood-brain barrier (BBB) to develop new radiopharmaceuticals for non-invasive brain imaging. Quetiapine (QTP) and cyclobenzaprine (CBP), as two 5-HT2A receptor antagonists, were successfully labeled with radioactive iodine (125I) using Chloramine-T (CAT) as an oxidizing agent via electrophilic substitution reactions. After studying the parameters affecting the labeling yield (substrate amount, CAT amount, pH of the reaction mix., reaction time and temperature), the highest radiochemical yields of125I-QTP and 125I-CBP were found to be 94.5 % ± 1.0 and 91.7 % ± 0.6, respectively, at pH 2. The biodistribution and the SPECT/CT image showed that the maximum uptake of radioiodinated-QTP by the mouse brain was 10.2% and 10.9% at 120 minutes post-injection, while the radioiodinated-CBP was 7.7% and 12.4% at 240 minutes post-injection. The results have shown that radioiodinated-QTP and radioiodinated-CBP are novel radiopharmaceuticals and may be used for brain imaging.
Pilot Study of a Play-based Intervention Enrichment Program Using Board Games, for Mothers and Children from a Culturally Challenged Immigrant Group

ABSTRACT Play is a central occupation of children, contributing to their development. Play opportunities depend on physical, social, and cultural environments. Family-focused programs need to be developed and adapted to diverse populations. This study endeavored to evaluate the effectiveness of a short-term intervention enrichment program for a group of mothers and children from a cultural immigrant group in Israel, which focused on playing board games together. Twelve mothers and 12 children participated in a play-based program. A demographic questionnaire and a set of adapted PAPI questionnaires were used to examine mothers’ levels of knowledge and self-efficacy relating to playing board games, as well as children’s participation before and after intervention. Qualitative information was also collected, as well as mothers’ satisfaction levels. A significant improvement (p < .006; ɳ 2 > .14) was found in some items relating to mothers’ knowledge, awareness, and self-efficacy resulting from play, and relating to children’s participation in play. Three months post intervention, a nonsignificant decrease was found in comparison to immediate post-intervention scores. The mothers reported a high level of satisfaction with the program. Short-term programs focusing on board game-playing among mothers and children from a cultural immigrant group may have the potential to strengthen parental knowledge, awareness, and self-efficacy relating to playing board games, and may improve their children’s participation in leisure play. Possible change mechanisms include occupational-based intervention, a family-centered approach, and environmental and cultural adaptations. The results suggest the need for developing culturally sensitive programs for diverse cultural groups. Future studies are needed among diverse populations, using additional assessments and control groups.
A Review on the Service Virtualisation and Its Structural Pillars

Continuous delivery is an industry software development approach that aims to reduce the delivery time of software and increase the quality assurance within a short development cycle. The fast delivery and improved quality require continuous testing of the developed software service. Testing services are complicated and costly and postponed to the end of development due to unavailability of the requisite services. Therefore, an empirical approach that has been utilised to overcome these challenges is to automate software testing by virtualising the requisite services’ behaviour for the system being tested. Service virtualisation involves analysing the behaviour of software services to uncover their external behaviour in order to generate a light-weight executable model of the requisite services. There are different research areas which can be used to create such a virtual model of services from network interactions or service execution logs, including message format extraction, inferring control model, data model and multi-service dependencies. This paper reviews the state-of-the-art of how these areas have been used in automating the service virtualisation to make available the required environment for testing software. This paper provides a review of the relevant research within these four fields by carrying out a structured study on about 80 research works. These studies were then categorised according to their functional context as, extracting the message format, control model, data model and multi-service dependencies that can be employed to automate the service virtualisation activity. Based on our knowledge, this is the first structural review paper in service virtualisation fields.