Miracle-dz/UniFAR-FTUs huggingface dataset:
Riverine landscapes: Challenges and future trends in research and management

River systems are among the world's most threatened ecosystems, facing multiple and often interlinked pressures across different spatial and temporal scales (Best, 2019; Tockner, Pusch, Borchardt, & Lorang, 2010; Vörösmarty et al., 2010). With increasing population growth, industrialization, and the intensification of land use during the last century, both the variety of demands and the intensity of uses have increased, while ecological integrity, functioning, and biodiversity of riverine landscapes have declined (Ferreira, Globevnik, & Schinegger, 2019). The subordination of multiple ecosystem services provided by pristine river-floodplain systems to a few dominant anthropic uses has reduced the multifunctionality of these ecosystems severely (Parsons et al., 2017). Today, river managers face the challenge of considering a variety of social, economic, and ecological demands simultaneously and objectively, where policy and human attitudes and perceptions may hamper the acceptance of management measures (Dunham et al., 2018; Jähnig et al., 2011). Thus, future management and restoration need to recognize river landscapes as socio-ecological entities, which provide ecosystem services for humans based on their ecological integrity. The 6th Biennial Symposium of the International Society for River Science (ISRS) was hosted by the Institute of Hydrobiology and Aquatic Ecosystem Management at the University of Natural Resources and Life Sciences, Vienna (BOKU), Austria, from September 8–13, 2019. According to the conference theme “Riverine landscapes as coupled socio-ecological systems,” the symposium emphasized integrative research on the sustainable use, management, and protection of aquatic ecosystems. Particular attention was given to the complex interactions between society and the ecological functioning of highly modified riverine landscapes. This special issue of River Research and Applications includes 16 articles from this meeting, which address various challenges and solutions relating to the management and restoration of river-floodplain systems in the face of changing environmental and climatic conditions and increasing complexity of ecological and socio-economic demands. The articles span a wide range of topics, from the hydro-morphological development of river systems to the consideration of social aspects and complex abiotic–biotic interactions in river management, thus highlighting the need for process-based, dynamic, and integrated approaches in river management. 2 | THEMES OF THIS SPECIAL ISSUE
An Automated Segment Selection Algorithm Based on the Assessment of Surface Wave Characteristic in Ambient Noise Recordings

Passive surface wave methods have been widely used to reconstruct velocity structures on different scales. The methods are becoming increasingly popular in urban areas because of the urgent needs of urban development. Unlike years of recordings on continental scales, the duration of recordings in urban areas usually lasts only for hours, even minutes. Thanks to huge amounts of cultural noise, especially from traffic, passive surface wave methods have proved their efficiency in urban areas, even with relatively short-time recordings. However, data needs to be processed more carefully for obtaining valuable information with limited recordings. Based on the characteristic of surface waves in − domain, we propose a formula to assess the intensity of surface waves in a linear array, thereby forming an automated data selection algorithm by selecting those segments with energetic surface waves. Results of a real-world example demonstrated the procedures of the proposed algorithm, and its effectiveness and reliability are therefore validated.
Automated adaptive TFSF method for solving time domain Maxwell's equations

The total field–scattered field (TFSF) formulation is quite popular for solving Maxwell's equations in finite difference time domain (FDTD) and finite volume time domain (FVTD) methods. Here a fixed TFSF interface around the scattering body is employed to separate the total field (TF) cells and scattered field (SF) cells. This interface is selected based on experience as it is assigned prior to the solution, and, therefore, the solution accuracy may not be optimal. In the present work, a novel automated adaptive total field–scattered field (ATFSF) method is proposed for accurately computing the electromagnetic scattering by complex‐shaped metal objects excited by an external plane wave. In the proposed method, an algorithm is devised to dynamically identify the TF cells and the SF cells, to be solved using TF and SF methods, respectively, using intensity of electromagnetic (EM) wave. The algorithm is tested in a 2‐D spectral volume time domain (SVTD) framework for solving electromagnetic scattering, and the predicted surface current/radar cross section is compared against the SF, TF, and the conventional TFSF methods. It is seen that the present method improves the solution accuracy significantly.
Collaborative filtering based on multiple attribute decision making

ABSTRACT To address the sparsity problem, a novel collaborative filtering approach based on multiple attribute decision making (MADM-CF) is proposed. In MADM-CF, users in collaborative filtering are treated as decision alternatives, items are treated as attributes. The weight of each item is determined, and the preference similarities between the active user and other users are computed. The preference similarity means that how the users’ preferences are similar on positive ratings and negative ratings. According to the preference similarities, the candidate neighbourhood of the active user is determined. A method to compute overall assessment value is designed, the overall assessment value of each user in the candidate neighbourhood is computed, and users with the smallest overall assessment values are selected as the active user’s nearest neighbours. Finally, the most frequent item recommendation method (MFIR) is used to provide top-N recommendations to the active user. Experimental results based on MovieLens and Netflix datasets show that the proposed approach is superior to existing alternatives.
Battery energy storage systems (bess) state of the art

This article presents a review of the battery energy storage method or BESS for its acronym in English (Battery Energy Storage System), considering that the era of high capacity storage batteries is approaching and why historically the storage of energy did not appear in the planning or operation of electrical systems. However, this solution is currently setting a global trend for having high levels of efficiency and why it is also being driven by the need to modernize the network in order to increase the use of renewable energies.
A Robust Share-of-Choice Model

In this paper, we propose an approach to take into account, in a robust way, part-worth uncertainty in a share-of-choice (SOC) model. More precisely, we extend the method proposed by Wang and Curry by endogenously including competition. Indeed in their approach, competition is described exogenously and the model cannot take into account part-worth uncertainty for the competition’s products. Our extension permits us to take into account all effects of part-worth uncertainty, even those relative to the competition, and therefore improve substantially Wang and Curry’s approach.
Government-nonprofit funding relationships in human services: Differences in cost-reimbursement and fixed-cost agreements

Funding agreements are the legal foundation for government-nonprofit funding relations and specify the terms and expectations for both parties. Yet little attention focuses on the funding agreements themselves, which vary in structure, form, compensation arrangements, and amount of risk each party bears in the funding relationship. Using data on human service nonprofits in the U.S., we examine whether the type of funding agreement—cost-reimbursement versus fixed-cost—influence the reliability of government funding during the Great Recession and the level of engagement by nonprofit providers. We find those who bear the burden of the risk at the outset have less reliable funding during recessionary times and nonprofit providers with a flat amount agreement are less engaged with government funders. Findings have implications for public and nonprofit managers to carefully consider risks and relationships to implement effective funding agreements.
Optimal PID Controller based on Convex Optimisation and Particle Swarm Techniques

This paper discusses the design and implementation of multiple optimisation algorithms for tuning a PID controller. A metaheuristic algorithm known as particle swarm optimisation (PSO) is used together with convex optimisation techniques, and the validity of the proposed algorithm is examined by comparing its performance with the performance of the classic PSO-PID and the well-known Ziegler–Nichols PID (ZN-PID). To obtain useful comparisons, a non-linear system, the air levitation system (AL), was utilised, controlled using a PID with three tuning strategies: the modified particle swarm technique (M-PSO-PID), the classic particle swarm (C-PSO-PID), and the Ziegler-Nichols method. The performance of the controllers was monitored through a cost function, the Integral Absolute Error (IAE). A disturbance was also imposed on the AL system to test the performance and the robustness of the algorithm under different conditions. The proposed algorithm is designed to determine and set the parameters for the M-PSO-PID controller utilising stabilising regions Kp, Ki, and Kd which form a convex problem. The PSO technique is then used to search for the optimal values inside the convex area. The simulation results for the control system show that the M-PSO-PID offered good closed-loop performance with advantages over other algorithms with regard to the system settling time and rise time. The results thus indicate the supremacy of the proposed algorithm.
Plugging and Its Stability Evaluation for the Ore Pass in the Nonempty Condition Based on Controllable Grouting of Cement-Sodium Silicate Grout

Aimed at the problem to plug the main ore pass with the large collapse at Xingshan Iron Mine, the viscosity-time test and the heap perfusion test of cement-silicate grout in a loose rock mass are carried out. The relationship between the vertical diffusion distance of cement-silicate grout and setting time of grout is studied, and research results are applied to the design of plugging engineering of the main ore pass in -330 m. Based on the numerical simulation of the plugging structure and the long-term stress monitoring of the cable sensors, the stability of the plugging structure itself and the control for the movement of shafts nearby are comprehensively evaluated. The test results show that for a specific loose rock mass, the vertical diffusion distance of cement-silicate grout in the loose rock mass is a power function of grout setting time. Based on the design concept to plug the main ore pass with the large collapse using artificially constructed “bite-bonded arch,” the plugging design and construction procedures are proposed. A numerical model and long-term monitoring of cable stress show that the plugging structure is stable and has an obvious effect on the control movement of abutment shafts.
Interactive Sequential Basket Recommendation by Learning Basket Couplings and Positive/Negative Feedback

Sequential recommendation, such as next-basket recommender systems (NBRS), which model users’ sequential behaviors and the relevant context/session, has recently attracted much attention from the research community. Existing session-based NBRS involve session representation and inter-basket relations but ignore their hybrid couplings with the intra-basket items, often producing irrelevant or similar items in the next basket. In addition, they do not predict next-baskets (more than one next basket recommended). Interactive recommendation further involves user feedback on the recommended basket. The existing work on next-item recommendation involves positive feedback on selected items but ignores negative feedback on unselected ones. Here, we introduce a new setting—interactive sequential basket recommendation, which iteratively predicts next baskets by learning the intra-/inter-basket couplings between items and both positive and negative user feedback on recommended baskets. A hierarchical attentive encoder-decoder model (HAEM) continuously recommends next baskets one after another during sequential interactions with users after analyzing the item relations both within a basket and between adjacent sequential baskets (i.e., intra-/inter-basket couplings) and incorporating the user selection and unselection (i.e., positive/negative) feedback on the recommended baskets to refine NBRS. HAEM comprises a basket encoder and a sequence decoder to model intra-/inter-basket couplings and a prediction decoder to sequentially predict next-baskets by interactive feedback-based refinement. Empirical analysis shows that HAEM significantly outperforms the state-of-the-art baselines for NBRS and session-based recommenders for accurate and novel recommendation. We also show the effect of continuously refining sequential basket recommendation by including unselection feedback during interactive recommendation.
Caracterización parcial del sector ganadero ecológico español y problemática actual

An on-line questionnaire was emailed to 1,055 organic farmers from November 2018 to February 2019 to gather information about issues and use of contentious inputs in organic production. A total of 116 responses were retained for the analysis. Characteristics of the participants (68 % men) and participating farms (67 % only had one species) were representatives of the Spanish organic livestock secCarmen L. Manuelian et al. ITEA-Inf. Tec. Econ. Agrar. (en prensa), Vol. xx: 1-25 1 * Autor para correspondencia: carmenloreto.manuelianfuste@unipd.it Cita del artículo: Manuelian CL, Albanell E, Such X, De Marchi M (en prensa). Caracterización parcial del sector ganadero ecológico español y problemática actual. ITEA-Información Técnica Económica Agraria. Vol. xx: 1-25 . https://doi.org/10.12706/itea.2020. 044 2 Carmen L. Manuelian et al. ITEA-Inf. Tec. Econ. Agrar. (en prensa), Vol. xx: 1-25
Ternary Sentiment Classification of Airline Passengers’ Twitter Text Based on BERT

Traditional word vector generation model cannot solve the polysemy problem of word representation in Twitter text, so, a method is presented here, firstly, by using Bidirectional Encoder Representations from Transformers (BERT), the semantic feature vector of the text can be obtained, and then, the feature vector is inputted into the Softmax classifier to implement the sentiment classification of Twitter text. The experimental datasets are source from passengers’ Twitter comments of USA six airlines, the sentiment classification model based on Embeddings from Language Model (ELMo) as the experimental control group. The experimental results indicate that the proposed model is advantage over the experimental control group by using F1-score as the evaluation index.
Educational Assistance Bot

An Internet bot performs automated tasks over the Internet. This software application is also known as a web robot or robot or simply bot, Typically, bots runs simple and structurally repetitive tasks, at a much higher rate than would be possible for a human alone. This effort is to help the users by providing all the basic student’s academic details like subjects, faculty names, books, notes and routine according to their need using bot. Users can also get other information like fees structure, library inventory list, calendar etc. Additional information like top educational sites, most trending educational videos etc will be regularly updated by the admin. This is an all-in-one application which can also be used to fetch and update information which is purely related to COVID-19.
The Prize of Governance. How the European Union Uses Symbolic Distinctions to Mobilize Society and Foster Competitiveness

Since its origins, the European Union (EU) has increasingly relied on prizes to highlight the values and principles channelling European integration. In the last two decades, such symbolic tools of governance have shifted away from the kind of distinctions granted by elites to elites and aiming to honour prominent figures offered as role models mainly in the field of identity, memory and cultural policies. In an increasingly market-oriented Europe, prizes are used as incentives and disciplining instruments to enhance self-compliance of economic and social actors with an ethos of competitiveness and innovation. They work as a magnifying glass of the evolution of the EU towards a government at distance through policy instruments. The focus is on four areas where prizes have multiplied since the 2000s: research and innovation, economic governance, territorial and environmental policies, and communication policies. The article draws on a qualitative analysis of a corpus of ninety-one prizes, institutional documentation, parliamentary debates and media controversies related to prizes.
The clinical characteristics and treatment approaches of COVID-19: a concise review

A series of cases of pneumonia occurred in China in late 2019. For this type of coronavirus, the WHO formally identified the condition as a coronavirus disease 2019 (COVID-19). They announced that this disease is the recent main concern of health problems in the world. Transfer of this novel coronavirus (nCoV) from human to human exists predominantly among family members, who have close contact with each other. This review article is provided based on the recent findings of COVID-19, which were retrieved by searching PubMed, Google Scholar, Scopus, and Web of Science until December 2020. Here, we highlighted the coronaviruses types, COVID-19 symptoms, epidemiology of the disease, transmission ways, and nCoV related pneumonia pathogenesis and continue with characteristic features and treatment methods. While no approved treatments are available for this type of infection therapy but several drugs may have potential benefits. It seems that identifying the detailed characteristics of the novel coronavirus disease offers the foundation for further research into the production of effective anti-COVID-19 drugs and vaccines.
Fabrication optimization of polyethersulfone (PES)/polyvinylpyrrolidone (PVP) nanofiltration membranes using Box–Behnken response surface method

Herein response surface methodology (RSM) is employed to optimize the fabrication of polyethersulfone (PES) nanofiltration (NF) membranes via phase inversion. The Box–Behnken design matrix is applied to develop predictive regression models, minimize the number of experiments, and investigate the effects of parameters on the response. Four important parameters, including PES polymer concentration (18–22% w/w), PVP concentration (0–2% w/w), evaporation time (0–3 min) and coagulation bath temperature (0–50 °C), were chosen as independent variables and the optimization objectives were water flux and rejection. Consequently, 27 experiments were conducted to construct a quadratic model. The fabricated NF membranes were characterized via scanning electron microscopy (SEM) and water contact angle measurements. The performance of the fabricated membranes was evaluated using a bench scale cross-flow filtration unit. According to analysis of variance (ANOVA), all four independent parameters are statistically significant and the final model is reasonably accurate. Response surfaces and contours are plotted to represent the regression equations and their interpretation. Furthermore, the optimal experimental conditions for both water permeation flux and rejection were separately evaluated. The maximum permeation flux of 159.84 kg m−2 h−1 and rejection of 78.41% were achieved under the optimal fabrication parameters. Deviations between the predicted and actual responses of permeation flux and rejection were within 10% and 3%, respectively, which confirm the accuracy and validation of the model.
Actors and Authority in the International Tax Ecosystem

This chapter provides an interdisciplinary framework for understanding changes in the international tax ecosystem. The chapter describes three broad disciplinary approaches to taxation grouped according to assumptions of how actors operate and project authority. On this basis, the international tax ecosystem framework consists of four components, with associated actors and forms of authority: jurisdictions, political mandates, markets, and normative environments. The framework emphasizes a sensitivity to different kinds of actorhood, and how changes are driven by actors’ claims to different forms of authority. After outlining the history of the international tax ecosystem, the framework is applied to present the most important changes to the tax ecology in the last decade. We argue that the evolution in the ecosystem is characterized by persistent legal indeterminacy and political complexity. The scholarly concern, then, is being open to different forms of actorhood and authority while untangling evolution within the international tax ecosystem.
What Lies beneath Sustainable Education? Predicting and Tackling Gender Differences in STEM Academic Success

In many societies across the globe, females are still underrepresented in science, technology, engineering, and math (STEM fields), although they are reported to have higher grades in high school and college than males. The present study was guided by the assumption that the sustainability of higher education critically rests on the academic success of both male and female students under conditions of equitable educational options, practices, and contents. It first assessed the persistence of familiar patterns of gender bias (e.g., do competencies at enrollment, serving as academic precursors, and academic performance favor females? ) in college students of a society in transition from a gender-segregated workforce with marked gender inequalities to one whose aims at integrating into the global economy demand that women pursue once forbidden careers thought to be the exclusive domain of men. It then examined how simple indices of academic readiness, as well as preferences for fields fitting traditional gender roles, could predict attainment of key competencies and motivation to graduate (as measured by the average number of credits completed per year) in college. As expected, females had a higher high school GPA. Once in college, they were underrepresented in a major that fitted traditional gender roles (interior design) and over-represented in one that did not fit (business). Female students’ performance and motivation to graduate did not differ between the male-suited major of business and the female-suited major of interior design. Male students’ performance and motivation to graduate were higher in engineering than in business, albeit both majors were gender-role consistent. Although high school GPA and English proficiency scores predicted performance and motivation for all, preference for engineering over business also predicted males’ performance and motivation. These findings offered a more complex picture of patterns of gender bias, thereby inspiring the implementation of targeted educational interventions to improve females’ motivation for and enrollment in STEM fields, nowadays increasingly available to them, as well as to enhance males’ academic success in non-STEM fields such as business.