Miracle-dz/UniFAR-FTUs huggingface dataset:
China as Dairy Importer: Rising Milk Prices and Production Costs

China’s emergence as a major importer of dairy products corresponds to rapid increases in its domestic milk prices. Allocating growth in China’s milk prices from 2006 to 2014 to production cost categories shows that feed concentrates and fodder account for about half of the price increases. While labor productivity grew rapidly, there was only moderate growth in milk per cow and no improvement in milk output per unit of feed. Scarcity of feed resources, particularly forage, is likely to constrain growth of China’s milk production and maintain the country’s demand for dairy imports.
Is it Useful to Support Users with Lexical Resources? A User Study.

Current search engines are used for retrieving relevant documents from the huge amount of data available and have become an essential tool for the majority of Web users. Standard search engines do not consider semantic information that can help in recognizing the relevance of a document with respect to the meaning of a query. In this paper, we present our system architecture and a first user study, where we show that the use of semantics can help users in finding relevant information, filtering it ad facilitating quicker access to data.
Stochasticity in foraging theory: risk and information

This thesis considers the importance of adding stochasticity to models of optimal foraging behaviour. The problem is divided into two elements, risk and information, which are treated separately. Part One: Risk. The theoretical and empirical results concerning animal preferences in risky situations are reviewed. Animals are known to show both risk-averse and risk-prone preferences over food reward. It is shown, theoretically, that a simple optimality model mimimizing the probability of death due to starvation accounts for at least some of the observed patterns of preference. The model is generalized to consider preference from arbitrary combinations of mean and variance. Three limitations of the model are treated in detail, that is the importance of starvation by "ruin", mind-changing about risk preferences, and energetic carry-over are discussed. The implications and limitations of these models are outlined. Part Two: Information. The theoretical literature is reviewed, and the problem of information is divided into three elements. A simple model of environmental tracking is studied. The model suggests that there is a trade-off between sensitivity to change and the costs of sampling. The model is tested using great tits (Parus major) foraging in an aviary. The trend in sampling was as predicted, but the birds were less sensitive to change than predicted. The problem of patch sampling is critically discussed. The value of sampling is defined, and this definition is used to compare the assumptions of previous models. Three such problems are treated: the importance of variance in the mixing distribution of patch sub-types; the importance of alternative and unambiguous patch types; and the importance of patch depression. It is concluded that previous models have often over-valued sampling. A simple and natural model of partial patch recognition is considered, and is shown to have empirical support. Implications and limitations of these models of information are discussed.
No positive correlation between species and genetic diversity in European alpine grasslands dominated by Carex curvula

The distributional range of alpine plants experienced dramatic changes during the Quaternary ice ages. These changes offer many opportunities for studying the impact of habitat contraction and fragmentation on both species and genetic diversity. Here, we examined the amplified fragment length polymorphism‐based genetic diversity in the sedge Carex curvula All. in relation to the species diversity of siliceous European alpine grasslands in which the sedge is dominant. We found no relationship or even a negative relationship between genetic and species diversity indices. Local species richness was associated with the regional pool size of siliceous alpine species, which was itself dependent on the extant area of suitable habitats for these species. Genetic diversity of C. curvula was primarily shaped by the presumed location of glacial refugia and the routes of post‐glacial colonization. We conclude that the two levels of diversity are not positively correlated because genotypes and species do not respond similarly to the spatial dynamics of suitable habitats induced by Quaternary temperature changes.
Na+/K+-ATPase α subunits as new targets in anticancer therapy

Background: The sodium pump (Na+/K+-ATPase) could be a target for the development of anticancer drugs as it serves as a signal transducer, it is a player in cell adhesion and its aberrant expression and activity are implicated in the development and progression of different cancers. Cardiotonic steroids (CS) are the natural ligands and inhibitors of the sodium pump and this supports the possibility of their development as anticancer agents targeting overexpressed Na+/K+-ATPase α subunits. Objectives: To highlight and further develop the concept of using Na+/K+-ATPase α1 and α3 subunits as targets in anticancer therapy and to address the question of the actual usefulness of further developing CS as anticancer agents. Conclusions: Targeting overexpressed Na+/K+-ATPase α subunits using novel CS might open a new era in anticancer therapy and bring the concept of personalized medicine from aspiration to reality. Clinical data are now needed to further support this proposal. Furthermore, future medicinal chemistry should optimize new anticancer CS to target Na+/K+-ATPase α subunits with the aim of rendering them more potent and less toxic.
Yeast Cell Wall and Cell Surface

The structure and organization of the yeast cell wall and the nature of the cell surface have been investigated in terms of the composition of the wall; the structures of the wall components; the immunochemistry of the cell surface and binding of dyes, lectins, or specific antibodies; the degradative action of enzymes; and the visual evidence from scanning and thin-section electron microscopy. Most or all of these methods have been applied to the cells during vegetative growth, sporulation, and mating, and the analyses have been furthered by the availability in recent years of a variety of cell-wall mutants. A general conclusion from all of these studies is that yeast cell walls show less apparent organization than bacterial walls but that the yeast wall is as metabolically active and the cell surface as antigenically polymorphic as those of Gram-positive bacteria. To keep this review manageable, it will be limited in most instances to Saccharomyces cerevisiae , with only occasional reference to other yeasts. The aim is to treat the subject topics briefly and to direct the reader to several recent reviews in which leading references to the original literature can be found. VEGETATIVE CELL WALL Composition and Structure Three components, glucan, mannoprotein (previously called mannan), and chitin, make up over 90% of the cell wall, whereas only small and variable amounts of lipid have been reported (Phaff 1971). When grown on hexadecane, however, the cell wall of Candida tropicalis increases in covalently linked fatty acid (Kappeli et al. 1978). Thus, cell-wall composition.
Alignement multimodal de ressources éducatives et scientifiques

Cet article présente certaines questions de recherche liées au projet COC O 1 . L’ambition de ce projet est de valoriser les ressources éducatives et académiques en exploitant au mieux les différents médias disponibles (vidéos de cours ou de présentations d’articles, manuels éducatifs, articles scientifiques, présentations, etc). Dans un premier temps, nous décrirons le problème d’utilisation jointe de ressources multimédias éducatives ou scientifiques pour ensuite introduire l’état de l’art dans les domaines concernés. Cela nous permettra de présenter quelques questions de recherche sur lesquelles porteront des études ultérieures. Enfin nous finirons en introduisant trois prototypes développés pour analyser ces questions.
Machine Learning for Cyberattack Detection Machine Learning for Cyberattack Detection

Machine learning has become rapidly utilized in cybersecurity, rising from almost non-existent to currently over half of cybersecurity techniques utilized commercially. Machine learning is advancing at a rapid rate, and the application of new learning techniques to cybersecurity have not been investigate yet. Current technology trends have led to an abundance of household items containing microprocessors all connected within a private network. Thus, network intrusion detection is essential for keeping these networks secure. However, network intrusion detection can be extremely taxing on battery operated devices. The presented work presents a cyberattack detection system based on a multilayer perceptron neural network algorithm. To show that this system can operate at low power, the algorithm was executed on two commercially available minicomputer systems including the Raspberry PI 3 and the Asus Tinkerboard. An analysis of accuracy, power, energy, and timing was performed to study the tradeoffs necessary when executing these algorithms at low power. Our results show that these low power implementations are feasible, and a scan rate of more than 226,000 packets per second can be achieved from a system that requires approximately 5W to operate with greater than 99% accuracy.
Towards Understanding ASR Error Correction for Medical Conversations

Domain Adaptation for Automatic Speech Recognition (ASR) error correction via machine translation is a useful technique for improving out-of-domain outputs of pre-trained ASR systems to obtain optimal results for specific in-domain tasks. We use this technique on our dataset of Doctor-Patient conversations using two off-the-shelf ASR systems: Google ASR (commercial) and the ASPIRE model (open-source). We train a Sequence-to-Sequence Machine Translation model and evaluate it on seven specific UMLS Semantic types, including Pharmacological Substance, Sign or Symptom, and Diagnostic Procedure to name a few. Lastly, we breakdown, analyze and discuss the 7% overall improvement in word error rate in view of each Semantic type.
EXPLORING TRIPLE BOTTOM LINE WITH GROUNDED THEORY

This paper describes how grounded theory was used to explore triple bottom line (TBL) in a global organization from a marketing perspective. TBL is a sustainability-related concept that focuses on the economic, social, and environmental aspects simultaneously. Sustainability-related constructs have been gaining momentum in recent scholarship from various research fields. The case study in which this paper is based on was designed to gain a deeper understanding of why an organization would emphasize the elements of TBL through an investigation of the interactions among TBL, strategic positioning, and image differentiation. The qualitative research was conducted using grounded theory, which was justified by the exploratory purpose of the study in understanding an emerging phenomenon [TBL]. The purpose of this paper is to illustrate the usage of grounded theory in developing theoretical propositions. This paper provides an overview of grounded theory, a description of how the research was conducted, and a discussion on the results, limitations, and recommendations for future research.
Understorey competition affects tree growth and fate of fertilizer-applied 15N in a Coastal British Columbia plantation forest: 6-year results

Growth of planted seedlings in cutovers dominated by salal (Gaultheria shallon Pursh) is poor largely because of low N availability and understorey competition. In this paper, the response of tree growth and fertilizer recovery to understorey competition was studied. The trees were four years old when (15NH4)2SO4 (200 kg N/ha, 3.38004% enrichment) was applied in 1991 to single-tree plots, with either understorey removed from (treated) or left (control) in the plots. Half of the plots were either sampled after two (1992) or six (1996) growing seasons. Understorey competition continued to significantly reduce height and diameter growth between 1992 and 1996, except diameter growth for western redcedar (Thuja plicata Donn.). Nitrogen and 15N concentration in both tree and understorey components decreased from 1992 to 1996 and N concentration in 1-year-old foliage in 1996 (but not in 1992) was significantly lower in the control than in the treated plots, indicating that the site was low in N supply and the ef.
Beyond economic rationale: psychological dimension as a complement perspective to understand the strategic motivation of near-retirement CEOs

Are all CEOs driven by wealth maximization at the last stage of their career? Although extant literature based on economic rationale suggests that near-retirement CEOs are more likely to be risk averse and tend not to initiate a long-term risky strategy, we argue that at the top position and this life stage they are more likely than other individuals to be satisfied with their wealth and driven by psychological needs. It is therefore crucial to incorporate their psychological characteristics into the analysis of near-retirement CEOs’ motivation behind strategic decisions. This conceptual paper proposes three such psychological characteristics and suggests the direction and degree of their impacts on near-retirement CEOs’ strategic decision. It extends the present knowledge on CEO career horizon and decision making literature, and contributes to corporate governance practice.
On the role of effective and referring questions in GuessWhat?!

Task success is the standard metric used to evaluate referential visual dialogue systems. In this paper we propose two new metrics that evaluate how each question contributes to the goal. First, we measure how effective each question is by evaluating whether the question discards objects that are not the referent. Second, we define referring questions as those that univocally identify one object in the image. We report the new metrics for human dialogues and for state of the art publicly available models on GuessWhat? Regarding our first metric, we find that successful dialogues do not have a higher percentage of effective questions for most models. With respect to the second metric, humans make questions at the end of the dialogue that are referring, confirming their guess before guessing. Human dialogues that use this strategy have a higher task success but models do not seem to learn it.
Simple Compounded-Label Training for Fact Extraction and Verification

Automatic fact checking is an important task motivated by the need for detecting and preventing the spread of misinformation across the web. The recently released FEVER challenge provides a benchmark task that assesses systems’ capability for both the retrieval of required evidence and the identification of authentic claims. Previous approaches share a similar pipeline training paradigm that decomposes the task into three subtasks, with each component built and trained separately. Although achieving acceptable scores, these methods induce difficulty for practical application development due to unnecessary complexity and expensive computation. In this paper, we explore the potential of simplifying the system design and reducing training computation by proposing a joint training setup in which a single sequence matching model is trained with compounded labels that give supervision for both sentence selection and claim verification subtasks, eliminating the duplicate computation that occurs when models are designed and trained separately. Empirical results on FEVER indicate that our method: (1) outperforms the typical multi-task learning approach, and (2) gets comparable results to top performing systems with a much simpler training setup and less training computation (in terms of the amount of data consumed and the number of model parameters), facilitating future works on the automatic fact checking task and its practical usage.
Exploring HRM Practices to Retain Generation-Z in Information Technology Sector: A Systematic Literature Review

Deloitte consultancy firm has forecasted that the working world is expecting 75% of total world workforce could be generated from millennials and Generation-Z (Gen-Z) by 2025. Thus, a past researcher like Jacob Morgan has stated that Gen-Z individuals who were born after 1994 are quite different from the millennials who were born from 1975 to 1994. Therefore, a proper retention mechanism is needed in order to address the behaviours and expectations of the Gen-Z. The research question of how conventional Human Resources Management (HRM) practices should be amended as per the desires of the Gen-Z is very critical, therefore, the values or modifications should be added into the HRM practices such as power distribution, team constructing, job stress mitigation, performance management, and training and developments to increase the attractiveness for the Gen-Z people to work with satisfied manner. Besides, HRM practices would improve the productivity of the organization and increase the benefits to the employees and reduce employees’ intention to leave the organization. Adopting an explanatory sequential research design under the basis of pragmatic world-view research approach to further evaluate the conceptual framework illustrated could compose the suitability to the real-world implementation process of the outcome in this paper.
Seasonal and spatial variation of phytoplankton assemblages, biomass and cell size from spring to summer across the north-eastern New Zealand continental shelf

The composition, biomass and cell size of phytoplankton taxonomic groups were determined in the Hauraki Gulf and adjacent shelf of north-eastern New Zealand. In early spring, on the inner shelf, over-winter mixing and upwelling supported a bloom dominated by large, chain forming diatoms in a moderately turbulent water column. The bloom declined in late spring because of nutrient limitation, and the assemblage evolved initially toward small diatoms, and eventually to co-occurrence of dinoflagellates, small nanoflagellates and picophjtoplankton in early and late summer. Mid- to outer-shelf biomass was much lower than inshore, and was dominated by small or motile taxa which were probably limited by grazing and light. In early summer, strong upwelling displaced inner shelf phytoplankton to beyond the shelf edge, whilst enriching the shelf with nutrients. However, shelf phytoplankton biomass increased only after the relaxation of upwelling. The Hauraki Gulf was strongly stratified from early spring through late summer. The flora were seasonally less variable than on the shelf, with a thecate dinoflagellate-dominated flora in early spring, replaced post-bloom by the co-occurrence of presumably low-nutrient-adapted autotrophic and/or heterotrophic dinoflagellates (most of which were non-thecate, and some toxic), nanoflagellates and picophytoplankton. The succession in floristics was consistent with a change from an autotrophic toward a heterotrophic ecosystem from spring to summer. Implications for secondary production, and vertical and lateral organic carbon export on the shelf, are discussed.
Characteristics of Multi-Layer Perceptron Switching between Learning and Non-Learning Neurons

—A glia has important functions for a higher brain functions. Among them, we notice that the glia inﬂuences the synaptic Long-Term Potentiation (LTP). The ﬁred glia increase a Ca 2+ concentration. The Ca 2+ generates a d-serine. The d-serine happens the synaptic LTP. In previous study, we proposed the Multi-Layer Perceptron (MLP) with switching learning and non-learning neurons. In this method, neurons in the hidden-layer are connected with glias and separated to some groups according to the connected glia. The glias are regularly ﬁred. The neurons are switched the learning and non-learning terms according to the glia ﬁring. We consider that switching between two terms is efﬁcient to the MLP performance. By the simulations, we conﬁrm that the change of the number of neurons is how to inﬂuence to the learning performance.
HOW SPORTING GOODS BRANDS SHOW THEIR SPORT BRAND AUTHENTICITY?

Brand strategy is one of the key factors for successful corporate management. The first step of strong brand building is setting up the brand core image, brand identity. Nowadays brand authenticity is studied as a core branding source by some marketing field researchers. This research focuses on the brand authenticity can make sporting goods brand succeed consistently. Sport authentic brands are loved by customers as their loyal sporting goods brand. Customers consume a sporting brand as an image of authentic high performing athletes. This research defined sport brand authenticity based on the former studies of social science. And this research showed the differences in brand communication between sport authentic brand and non-sport authentic brand through content analysis of sporting goods brand website. There were meaningful differences in their way of brand communication. Sport authentic brands tried to show images of sports activities and their high performing equipment in their website, and their communication sources are more concentrated on male, elite athlete with impassive and serious face.
Findings of the Fourth Workshop on Neural Generation and Translation

We describe the finding of the Fourth Workshop on Neural Generation and Translation, held in concert with the annual conference of the Association for Computational Linguistics (ACL 2020). First, we summarize the research trends of papers presented in the proceedings. Second, we describe the results of the three shared tasks 1) efficient neural machine translation (NMT) where participants were tasked with creating NMT systems that are both accurate and efficient, and 2) document-level generation and translation (DGT) where participants were tasked with developing systems that generate summaries from structured data, potentially with assistance from text in another language and 3) STAPLE task: creation of as many possible translations of a given input text. This last shared task was organised by Duolingo.
Dénomination d’image versus détection interne de phonème : deux méthodes pour étudier la planification de la production de parole (Picture naming versus internal phoneme monitoring: two methods for exploring speech production planning)[In French]

Cette étude est motivée initialement par une question méthodologique : la validité des mesures de temps de dénomination d’image, très utilisés pour explorer les processus de planification de production de parole. Le temps de dénomination est le temps écoulé entre affichage de l’image et début acoustique de la réponse verbale. Dans cet article, nous résumons la littérature sur les inconvénients de cette mesure. Nous présentons ensuite notre étude, qui compare directement temps de dénomination d’image et temps de détection interne de phonème initial. Les participants sont hispanophones. Les noms d’image sont contrastés en fréquence lexicale et phonème initial. Les temps de réponse pour les deux mesures sont assez proches. Cependant, ceux de détection de phonème sont relativement insensibles au type de phonème initial, contrairement aux temps de dénomination. Au delà de l’avantage méthodologique de la détection interne de phonème, nos données suggèrent que celle-ci opère sur des représentations relativement abstraites.
Radarly : écouter et analyser le web conversationnel en temps réel (Real time listening and analysis of the social web using Radarly)[In French]

De par le contexte conversationnel digital, l’outil Radarly a été conçu pour permettre de traiter de grands volumes de données hétérogènes en temps réel, de générer de nouveaux indicateurs et de les visualiser sur une interface cohérente et confortable afin d’en tirer des analyses et études pertinentes. Ce document expose les techniques et processus utilisés pour extraire et traiter toutes ces données.