Miracle-dz/UniFAR-FTUs huggingface dataset:
Shoreline Dynamics and Evaluation of Cultural Heritage Sites on the Shores of Large Reservoirs: Kuibyshev Reservoir, Russian Federation

Over the last decades, the number of artificial reservoirs around the world has considerably increased. This leads to the formation of new shorelines, which are highly dynamic regarding erosion and deposition processes. The present work aims to assess the direct human action along the largest reservoir in Europe—Kuibyshev (Russian Federation) and to analyse threatened cultural heritage sites from the coastal area, with the help of historical maps, UAV (unmanned aerial vehicle), and topographic surveys. This approach is a necessity, due to the oscillating water level, local change of climate, and to the continuous increasing of natural hazards (in this case coastal erosion) all over the world. Many studies are approaching coastal areas of the seas and oceans, yet there are fewer studies regarding the inland coastal areas of large artificial reservoirs. Out of the total number of 1289 cultural heritage sites around the Kuibyshev reservoir, only 90 sites are not affected by the dam building; the rest had completely disappeared under the reservoir’s water. The scenario of increasing and decreasing water level within the reservoir has shown the fact that there must be water oscillations greater than ±1 m in order to affect the cultural heritage sites. The results show that the coastal area is highly dynamic and that the complete destruction of the last remaining Palaeolithic site (Beganchik) from the shoreline of Kuibyshev reservoir is imminent, and immediate mitigation measures must be undertaken.
What is “usable” knowledge? Perceived barriers for integrating new knowledge into management of an iconic Canadian fishery

Understanding the perspectives of knowledge users and the demands of their decision-making environment would benefit researchers looking to enhance the utility of the knowledge they generate. Using the Fraser River Pacific salmon fishery as a case study, we investigate the views of 49 government employees and stakeholders regarding the barriers to incorporating new knowledge into fisheries management. Our study uses analysis of qualitative data structured by a knowledge–action framework, which revealed that 90% of respondents perceived the contextual dimension (e.g., institutional structures and norms) as a barrier for incorporating new knowledge, followed by barriers related to the characteristics of knowledge actors (52% of respondents), characteristics of the knowledge (27%), time and timing (27%), knowledge transfer strategies (17%), and relational dimension (8%). The identified barriers have indirect–direct relationship with knowledge producers and appear hierarchical in nature. We note that informal relationships can enable conditions whereby knowledge users can access new knowledge, and knowledge producers can gain insights on users’ needs. We discuss lessons learned from the case, which we believe can be applied more beyond fisheries.
Evaluation of the anti-inflammatory and analgesic activities of Vitex doniana leaves

The anti-inflammatory and analgesic activities of extract of leaves of Vitex donianaSweet (Verbenaceae) were investigated as well as the mechanisms of action. The extract significantly (P<0.05) inhibited the formation of paw edema induced by agar in rats and increased reaction latency to thermal pain in mice in a dose-dependent manner. The extract caused a significant (P<0.05) dose-dependent ulceration of the rat gastric mucosa and concentration-dependent inhibition of hypotonicity-induced haemolysis of red blood cells. Also, the extract significantly (P<0.05) inhibited the activities of phospholipase A2 and prostaglandin synthase in a concentration-related manner. These suggest that the leaves possess anti-inflammatory and analgesic activities mediated through sequential inhibition of the enzymes responsible for prostaglandin synthesis from arachidonic acid. Phytochemical analysis of the extract revealed the presence of glycosides, tannins, alkaloids, flavonoids and saponins. Acute toxicity studies established an oral LD50 greater than 3 000 mg/kg. Key words: Vitex doniana, anti-inflammatory, analgesic, ulcerogenic activity.
Disruptions in One-Warehouse Multiple-Retailer Systems

We study two-echelon distribution systems (also known as one-warehouse, multiple-retailer (OWMR) systems) subject to supply disruptions. We propose algorithms to find the optimal or near-optimal stocking levels of all the locations in the system by assuming periodic review base-stock policies, deterministic demands at the retailers and non-overlapping disruptions at the supply processes of the warehouse and the retailer. This is the first paper to consider OWMR systems with all locations keeping inventory and all locations subject to supply disruptions. We show how supply disruptions at different parts of the network affect inventory decisions and we quantify the effects of ignoring the disruptions at different parts of the supply chain. Our results suggest that companies should work on reducing the duration of supply disruptions instead of trying to prevent them. In addition, if they choose to do nothing to prevent the consequences of some of the disruptions, these should not be the ones happening close to the customers.
Preschoolers' Self-Regulation, Skill Differentials, and Early Educational Outcomes

Are there skill differentials in young children's competence levels by their self-regulation abilities and do such early life differences mark the onset of increasing disparities in competence development? We add to previous research by investigating the relationship between preschoolers' self-regulation and their mathematical competence and its development early in primary school. We use data from the kindergarten cohort of the German National Educational Panel Study (NEPS) which provides observations of self-regulatory behavior as well as mathematical skills and allows controlling for a rich set of relevant background variables. Our results imply a positive association between children's self-regulation and their mathematical competence levels, even when holding general cognitive ability in kindergarten constant. Yet, self-regulation is not related to competence development over the first two years of primary school, meaning that the initial skill gap neither widens nor narrows substantially. Heterogeneity analyses indicate that self-regulation benefits children with low initial levels of mathematical competence at the transition from kindergarten to primary school. No growth gradient, however, is observable between grade 1 and grade 2.
Recent Trends in Stratospheric Chlorine From Very Short‐Lived Substances

Very short‐lived substances (VSLS), including dichloromethane (CH2Cl2), chloroform (CHCl3), perchloroethylene (C2Cl4), and 1,2‐dichloroethane (C2H4Cl2), are a stratospheric chlorine source and therefore contribute to ozone depletion. We quantify stratospheric chlorine trends from these VSLS (VSLCltot) using a chemical transport model and atmospheric measurements, including novel high‐altitude aircraft data from the NASA VIRGAS (2015) and POSIDON (2016) missions. We estimate VSLCltot increased from 69 (±14) parts per trillion (ppt) Cl in 2000 to 111 (±22) ppt Cl in 2017, with >80% delivered to the stratosphere through source gas injection, and the remainder from product gases. The modeled evolution of chlorine source gas injection agrees well with historical aircraft data, which corroborate reported surface CH2Cl2 increases since the mid‐2000s. The relative contribution of VSLS to total stratospheric chlorine increased from ~2% in 2000 to ~3.4% in 2017, reflecting both VSLS growth and decreases in long‐lived halocarbons. We derive a mean VSLCltot growth rate of 3.8 (±0.3) ppt Cl/year between 2004 and 2017, though year‐to‐year growth rates are variable and were small or negative in the period 2015–2017. Whether this is a transient effect, or longer‐term stabilization, requires monitoring. In the upper stratosphere, the modeled rate of HCl decline (2004–2017) is −5.2% per decade with VSLS included, in good agreement to ACE satellite data (−4.8% per decade), and 15% slower than a model simulation without VSLS. Thus, VSLS have offset a portion of stratospheric chlorine reductions since the mid‐2000s.
Oxidative Stress Upregulates the Transcription of Genes Involved in Thiamine Metabolism

Thiamine is a major vitamin that acts as a cofactor in energy metabolism in all organisms, as well as in lipid and amino acid metabolisms, and is associated with many diseases. It is known that glucose starvation decreases the intracellular thiamine pool while increasing oxidative stress tolerance. Earlier, in whole genome analysis, we detected major differences in the expression of genes related to thiamine pathway against oxidative stress in Schizosaccharomyces pombe. We investigated the effects of oxidative stress and glucose repression to thiamine pathway in S. pombe by comparing some genes encoding key enzymes of each related pathway at the transcription level. In the present study, we found that the expression of genes related to thiamine biosynthesis and transport (thi2, thi3, and pho1) increased in wild type and ird11 cells grown in thiamine-rich media under oxidative stress induced by H2O2. Based on our findings, we suggested that there might be an important effect of oxidative stress on thiamine biosynthesis and transport.
Desempeño del sistema de vigilancia colombiano durante la pandemia de COVID-19: evaluación rápida de los primeros 50 días

Resumen Introducción. La pandemia de COVID es un desafío para la vigilancia en salud pública y una oportunidad para evaluar sus fortalezas y debilidades en aras de mejorar la respuesta. Objetivo. Evaluar el desempeño del sistema de vigilancia en salud pública colombiano durante los primeros 50 días de la pandemia de COVID-19 en el país. Materiales y métodos. Se analizaron los datos publicados entre el 6 de marzo y el 24 de abril de 2020 por el Instituto Nacional de Salud y la Organización Mundial de Salud (OMS). Se consideraron en la evaluación: i) la calidad de los datos según la ley de Benford y ii) la oportunidad de la información, medida como la diferencia en fechas entre los datos generados en el Instituto Nacional de Salud y los recogidos en el informe situacional de la OMS. La variabilidad en el cumplimiento de la ley de Benford se evaluó con los valores de p en las pruebas de razón del logaritmo de la verosimilitud, ji al cuadrado o exacta de Moreno. Resultados. Hasta el 24 de abril hubo 4.881 casos de COVID-19 en Colombia. En la mayoría de los primeros 50 días se cumplió la ley de Benford, excepto en los primeros días de la epidemia. La diferencia entre los informes del Instituto Nacional de Salud y la OMS ha dependido, en gran medida, de la diferencia en los horarios de cierre de la información. Conclusión. En general, el sistema de vigilancia en salud pública colombiano cumplió con la ley de Benford, lo cual sugiere que hubo calidad en los datos. En futuros estudios que comparen el desempeño de los departamentos y distritos se podrá mejorar el diagnóstico de la vigilancia en salud pública del país.
Apprentissage de Représentation appliqué à la Recommandation pour la Littérature Scientifique

RÉSUMÉ. La littérature scientiﬁque forme un large réseau d’information reliant des acteurs va-riés (laboratoires, entreprises, institutions, etc.). La vaste quantité de données générées par ce réseau constitue un graphe hétérogène attribué dynamique, dans lequel de nouvelles informations sont constamment produites et dont il est de plus en plus difﬁcile d’extraire du contenu d’intérêt. Dans cet article, je présente mes premiers travaux de thèse réalisés en partena-riat avec un acteur industriel. Celui-ci propose un outil de veille scientiﬁque abordant diffé-rentes problématiques, telles que la recommandation d’articles et la recherche d’experts. Tout d’abord, je détaille les données habituellement associées à la littérature scientiﬁque. Ensuite, j’aborde le problème de la recherche d’experts, son évaluation et propose une nouvelle méthode pour juger de la qualité d’un algorithme. Enﬁn, j’introduis un algorithme d’apprentissage de représentations abordant le problème du plongement des nœuds d’un graphe dans un espace de faible dimension, étendu pour intégrer l’information textuelle liée à ces nœuds. ABSTRACT. The scientiﬁc literature is a large information network linking various actors (laboratories, companies, institutions, etc.). The vast amount of data generated by this network constitutes a dynamic attributed heterogeneous network, in which new information is constantly produced and from which it is increasingly difﬁcult to extract content of interest. In this article, I present my ﬁrst thesis works in partnership with an industrial company. This later offers a scientiﬁc watch tool addressing various issues, such as the recommendation of articles and the search for experts. First, I detail the data usually associated with the scientiﬁc literature. Then I present the problem of expert ﬁnding, its evaluation and I suggest a new method to juge the quality of an algorithm. Finally, I introduce a representation learning algorithm for the problem of embedding the nodes of a graph in a vector space of small dimension, extended to integrate the textual information related to these nodes.
Exploration de l'apport de l'analyse des perceptions oculaires : étude préliminaire pour le bouclage de pertinence

RÉSUMÉ. Nos travaux visent à évaluer l’impact potentiel de l’utilisation des perceptions ocu-laires vis-à-vis du mécanisme de bouclage de pertinence d’un moteur de recherche d’information. Nous nous sommes intéressés aux situations écologiques où l’utilisateur évalue la per-tinence des résultats d’une requête via les snippets afﬁchées sur la page des résultats. Notre hypothèse est que la connaissance des termes lus par un utilisateur sur cette page de résultats peut être utilisée pour améliorer le mécanisme de bouclage de pertinence, sans intervention explicite de l’utilisateur. Pour cela, nous modélisons le comportement visuel de l’utilisateur lorsqu’il consulte les résultats d’une requête, pour extraire de cette modélisation des indica-teurs. Nous avons étudié le dernier mot ﬁxé et le mot le plus longtemps ﬁxé, dans la page de résultats et dans chaque snippet. Les résultats des expériences réalisées avec des utilisateurs indiquent que le mot le plus longtemps ﬁxé est souvent un mot pertinent pour compléter la re-quête. ABSTRACT. Our work aims to evaluate the potential impact of the use of ocular perceptions analysis in the relevance feedback mechanism of a retrieval engine. We focus on ecological situations where the user evaluates the relevance of the results of a query via the snippets displayed on the results page. Our hypothesis is that the knowledge of the terms read by a user on the result page can be used to improve the relevance feedack mechanism, without explicit intervention of the user. For this, we model the visual behavior of the user when reading the results of a query, to extract indicators. We explored the last ﬁxed word and the longest ﬁxed word, in the results page and in each snippet. The results of the user experiments indicate that the longest ﬁxation word is often a relevant word to complement the query.
A Novel Resistive Memory-based Process-in-memory Architecture for Efficient Logic and Add Operations

The coming era of big data revives the Processing-in-memory (PIM) architecture to relieve the memory wall problem that embarrasses the modern computing system. However, most existing PIM designs just put computing units closer to memory, rather than a complete integration of them due to their incompatibility in CMOS manufacturing. Fortunately, the emerging Resistive-RAM (ReRAM) offers new hope to this dilemma owing to its inherent memory and computing capability using the same device. In this article, we propose a ReRAM memory structure with efficient PIM capability of both logic and add operations. It first leverages non-linearity to suppress sneak current and thus sustains high memory density. Using a differential bit cell, it also enables efficient processing of arbitrary logic functions using the same memory cells with non-destructive operations. Then, a novel PIM adder is proposed, which customizes a sneak current path as the carry-chain for fast carry propagation and improves adder performance significantly. In the experiment, the proposed PIM demonstrates higher efficiency in both computing area and performance for logic and addition, which greatly increases the ReRAM PIM applicability for future computable architectures.
Recommendation Mechanism for Patent Trading Empowered by Heterogeneous Information Networks

ABSTRACT The emerging patent trading platforms help to ease information asymmetry and trust issues during transaction, but a proactive recommendation mechanism that intelligently helps patent buyers identify relevant patents is still absent in the literature. This study proposes a recommendation mechanism for patent trading empowered by heterogeneous information networks (HIN) that integrates various patent information such as patent trading, patent invention, patent citation, patent ontology, and patent contents. Further, the meta-path-based similarity measure (i.e., AvgSim) is employed to calculate relevance and identify the different motivations of potential buyers in buying patents. We conducted two experiments to examine the performance of a proposed mechanism. An offline experiment on Public PatentsView database and Patent Assignment database show that the HIN-empowered recommendation outperforms baseline methods. We also implemented the proposed mechanism on a real-world trading platform (www.InnoCity.com). The recommendation function achieves satisfying results by tracking users’ feedback, which further validates the usability of HIN-empowered recommendation in a patent trading context.
Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective decision making would be affected by the agents’ diversity in problem understanding and/or behavior in discussion, as well as by their social network structure. Simulation results indicated that groups with consistent problem understanding tended to produce higher utility values of ideas and displayed better decision convergence, but only if there was no group-level bias in collective problem understanding. Simulation results also indicated the importance of balance between selection-oriented (i.e., exploitative) and variation-oriented (i.e., explorative) behaviors in discussion to achieve quality final decisions. Expanding the group size and introducing nontrivial social network structure generally improved the quality of ideas at the cost of decision convergence. Simulations with different social network topologies revealed collective decision making on small-world networks with high local clustering tended to achieve highest decision quality more often than on random or scale-free networks. Implications of this evolutionary theory and simulation approach for future managerial research on collective, group, and multilevel decision making are discussed.
Economic Success of Physicians in the Online Consultation Market: A Signaling Theory Perspective

ABSTRACT E-consultation is considerably significant in today’s highly competitive environment in reducing medical costs, improving operational efficiency and effectiveness, enhancing the equity of medical resources, and meeting customers’ satisfaction. However, the prosperity of e-consultation depends on doctors’ consistent participation and continued contribution. In addition, receiving a monetary return may be deemed as one of the major factors for doctors to stay on e-consultation platforms and provide the needed online services. This study investigates how a physician can achieve economic success in the online consultation market from the perspective of signaling theory. A secondary data econometric analysis using transaction data obtained from an e-consultation Website (haodf.com) was conducted. The obtained results indicate that both seller signals (knowledge contribution) and market signals (reputation), which are observable from the Website, may positively affect physicians’ income. In fact, the two types of online signals are the substitutes for each other; in addition, the impacts of both seller signals (knowledge contribution) and market signals (reputation) obtained from the Website were negatively moderated (weakened) by the offline signals (status). This study contributes to the literature by making a clear distinction between the online and offline signals, as well as between the seller signals and market signals. This study also provides practical implications, indicating that knowledge contribution and reputation are two important factors for physicians to increase their online income.
How emergency managers engage Twitter users during disasters

Natural disasters are increasingly more frequent and intense, which makes it critical for emergency managers to engage social media users during crises. This study examined emergency official accounts' social media engagement at each disaster stage based on Fink's four-stage model of crisis and disaster: prodromal, acute, chronic and termination stages and linked topics and sentiments to engagement. ,Using text mining and sentiment analysis, 1,226 original tweets posted by 66 major emergency official Twitter accounts and more than 15,000 retweets elicited across the life cycle of Hurricane Irma were analyzed. ,Results identified the most engaging official accounts and tweets. Most tweets and the most engaging tweets were posted in the prodromal stage. Tweets related to certain topics were significantly more engaging than others. The most frequently tweeted topics by official accounts were less engaging than some seldom tweeted topics. Negative sentiment words increased the engagingness of the tweet. Sadness was the strongest predictor of tweet engagement. Tweets that contained fewer sadness words were more engaging. Fear was stronger in positively predicting tweet engagement than anger. Results also demonstrated that words for fear and anger were critical in engaging social media discussions in the prodromal stage. Words for sadness made the tweets less engaging in the chronic stage. ,This study provided detailed instructions on how to increase the engagingness of emergency management official accounts during disasters using computational methods. Findings have practical implications for both emergency managers and crisis researchers.