bluuebunny/crossref_metadata_2025 huggingface dataset:
Willingness-to-pay for CO2 offsets: A large-scale field study on revealed preferences in the aviation
Authors: Schlöder Francisco , Berger Sebastian , Kilchenmann Andreas , Lenz Oliver
Published: May 2021

Studies assessing people’s willingness-to-pay for carbon offsets are overwhelmingly grounded in hypothetical stated-preference approaches. Here, we report on a large-scale observational field study involving a final sample of 63,520 bookings made with a European airline, allowing us to gauge willingness-to-pay for offsets in a revealed-preference approach. Our pre-registered study shows that the median willingness-to-pay to voluntarily offset a ton of CO2 from flight-related emissions is zero, with the mean willingness-to-pay being around 1 EUR. Neither prices of the offset nor airfares are predictive of offsetting behavior in a highly powered sample. Climate vulnerability of the destination has no significant impact on the compensation decision either. On the other hand, higher ancillary spending is associated with an increased likelihood to compensate, even though the effect size is low due to the general unwillingness to internalize flight-related emissions. Additionally, we find the choice of a vegetarian meal to be of similar predictive power (significant, but low in effect size given an overall low proportion of passengers choosing a vegetarian meal). Our results inform existing research on stated preferences as well as mitigation efforts relying on voluntary climate action.
Why we need a gradient approach to word order
Authors: Levshina Natalia , Namboodiripad Savithry , Allassonnière-Tang Marc , Kramer Mathew Alex , Talamo Luigi , Verkerk Annemarie , Wilmoth Sasha , Rodriguez Gabriela Garrido , Gupton Timothy , Kidd Evan , Liu Zoey , Naccarato Chiara , Nordlinger Rachel , Panova Anastasia , Stoynova Natalia
Published: May 2021

This paper argues for a gradient approach to word order, which treats word order preferences, both within and across languages, as a continuous variable. Word order variability should be regarded as a basic assumption, rather than as something exceptional. Although this approach follows naturally from the emergentist usage-based view of language, we argue that it can be beneficial for all frameworks and linguistic domains, including language acquisition, processing, typology, language contact, language evolution and change, variationist linguistics and formal approaches. Gradient approaches have been very fruitful in some domains, such as language processing, but their potential is not fully realized yet. This may be due to practical reasons. We discuss the most pressing methodological challenges in corpus-based and experimental research of word order and propose some solutions and best practices.
Comparing Political Polarization in Political and Cultural Preferences
Authors: Fischer Sean
Published: May 2021

The popular press has given substantial attention to the notion that Democrats and Republicans hold diverging cultural and lifestyle preferences that manifest in the TV shows they watch, the music they listen to, and the clothes they buy. The academic research in this area is split, though, with some suggesting that such divisions exist and others arguing that they ultimately fail to materialize in real-world behavior. In this study, I use network methods to evaluate whether such partisan cultural polarization exists at the individual-level. I do so by constructing networks of shared cultural preferences and networks of shared political beliefs based on closed-ended survey responses. For each network, I calculate the assortativity (correlation) between linked respondents' partisan identity, ideology, age, gender, race, and education level. I show that the assortativity for the political identity measures is low across the cultural-preference networks compared to the political-belief networks. These results suggest that cultural preferences are not associated with partisan or ideological identities.
The Power of Conformity in Citizens’ Blame: Evidence from a Survey Experiment
Authors: Sievert Martin , Vogel Dominik , Reinders Tim , Ahmed Waqar
Published: May 2021

The authors examine whether conformity towards prevailing public opinions and pre-existing blame influences citizens’ attribution of blame for public service failure, by using a between-group experimental design with five groups. Two groups received information cues mentioning different public opinions. Two additional groups received information on pre-existing blame or the absence of such blame. One control group did not receive any information. The empirical analysis reveals that public opinion in favor of blame leads to increased blame attribution, while a contrary public opinion decreases citizens’ blame. Likewise, the expected increase in citizens’ blame resulting from pre-existing blame is supported. However, the absence of blame has no effect. Overall, the experiment supports the impact of conformity on citizens' blame. In addition, the literature on citizens’ blame is extended by utilizing a citizen-centered perspective and taking social psychological theory into account.
Innovations and human capital of Belarus
Authors: Bogdan Nina
Published: May 2021

The article discusses the modern directions of innovation policy related to the digitalization of the economy and the tasks of developing human capital. Problems of measuring the effectiveness of the use of human potential and the challenges of using human capital in Belarus in the context of creating a digital economy are identified. The necessity of application a “human-centered” concept of social development has been substantiated.
Problems of education in the post-industrial era
Authors: Artamonov Vladimir , Artamonova Elena
Published: May 2021

Considering the problems of education in the post-industrial era, the authors present the key concepts and make an attempt to describe the post-industrial reality as a volatile and complex system. Тhe authors discuss new approaches in technical and corporate education. A model of the development of «post-industrial education» is proposed, which helps to understand the main trends and challenges that await the education system in the future. The problems of «post-visual reality» and distance education are discussed, technical and organizational methods of its implementation are considered. In accordance with the concept of «life-long learning», conclusions are drawn about the changing roles of students and teachers.
Przedmowa
Authors: Zgryzek Kazimierz
Published: May 2021

Foreword
Przyznanie się do winy jako warunek zakończenia sprawy w konsensualnym modelu procesu sądowego
Authors: Pustuła Marta
Published: May 2021

The aim of the following article is to consider the possibility of accepting the admission of guilt by the defendant as the primary condition for conclusion of the court proceedings in all consensual modes of trial as delineated by the Code of Criminal Procedure. The article contests the validity of the criterion of the seriousness of the act, which has been established by the legislator for the purposes of distinguishing a separate consensual model of court proceedings. At the same time, the article aims to consider whether it would be more reasonable to broaden the possibility of plea bargaining to include all cases, regardless of the seriousness of the act, if the defendant pleads guilty. Moreover, the author considers the prerequisites for sentencing without court proceedings, provided for under Article 335 § 1 of the Code of Criminal Procedure, including the assessment of the defendant’s own account in the context of all evidence collected in the investigation.
Jawność zewnętrzna postępowania przygotowawczego na tle art. 12 ustawy Prawo o prokuraturze
Authors: Wiącek Iwona
Published: May 2021

The aim of the following article is to discuss the issues of the power of the prosecutor to reveal information pertaining to ongoing preparatory proceedings in the light of the new regulations determined by Article 12 of the Act of January 28, 2016, the Law on the Prosecutor’s Office. The aforementioned regulation constitutes an important exception to the general rule of confidentiality of preparatory proceedings, which heavily informs the scope of the analysis. Moreover, the author discusses the relationship between Article 12 of the Law on the Prosecutor’s Office and earlier regulations regarding the revealing of information regarding preparatory proceedings included in the following acts: press law, law on access to public information, personal data protection act, supplemented with relevant regulations of the Criminal Code and Code of Criminal Procedure. In addition, the author discusses the consequences of the analyzed regulation for the interest of the criminal justice system, the interest of the public, as well as the interest of the parties in the proceedings, which has allowed her to assess the justification for that regulation and the necessity of implementing it in Polish legal system.
Ustrojowe gwarancje praw zatrzymanego jako wzorce sądowej kontroli zatrzymania w polskim procesie karnym
Authors: Kępa Patryk
Published: May 2021

The purpose of the article is to draw attention to the fact that the Polish legal system features system-related guarantees of the rights of the detainee which are regulated in a multi-centric system of law, consisting of a set of constitutional norms and legal international norms, which create the models of judicial control of detention in a Polish criminal lawsuit. The article puts forward a thesis that the Polish system features the socalled dispersed control of constitutionality, which is erroneously considered a synonym of the concept of the so-called direct application of the constitution. The questions under discussion are analysed by means of a formal-dogmatic method. The article also discusses the possibility of the participation of assistant judges in the exercise of judicial control of detention, with reference to the recent modification of the system-based position of assistant judges.
Głos w dyskusji o zaniechaniu ścigania jako sposobie reakcji na przestępstwo w prawnie dopuszczalnym procesie karnym
Authors: Basa Michał Wojciech
Published: May 2021

The subject of considerations is an attempt to describe and assess the institution of cessation of prosecution, resulting from reaching an agreement, as reaction to crime. The effective consensus-driven approach ought to be aimed at combining court instruments and values with the axiological basis of agreement-based litigation (namely, principle of restorative justice), and also with legal measures which allow to mete out a due penal reaction or, frequently, the cessation of prosecution. In case of proceedings regarding misdemeanours, where there is a possibility of eliminating the consequences of the crime solely by compensatory actions within victim-perpetrator relation, the state ought to waive the execution of ius puniendi. What should constitute the limit of waiving the right to punish is a combination of circumstances such as: negligible degree of social harm, reaching a plea agreement that includes the manner of compensation, along with executing thereof. Then, the sufficient reaction to crime is redressing damage or compensation for the harm suffered and the prosecutor’s decision to cease prosecution. The stage of judicial proceeding does not have to and should not be merely a forum for reaching and executing court agreements. The described variant of cessation of the prosecution combines instrumental values, such as the promptness and cost-effectiveness of proceedings with non-instrumental ones, such as due process and implementation of restorative justice. Through only partial waiver of the trial subject implementation, cessation of the proceedings may constitute a compromise between legalistic values and those of judicial opportunism.
LIFE LESSONS AND MORALS OF A TEACHER (ABOUT PROFESSOR VIKTOR CHERNAVSKY)
Authors: Abdulhabirov М.
Published: May 2021

The article contains not only a brief description of the biological founders of osteosynthesis (surgery of the osteoarticular system) in the Soviet Union, but also moral lessons that were not preached, but guided by their own investigation, Professor Viktor Alekseevich Chernavsky.
FUNCTIONAL CHARACTERISTICS OF AUXILIARY SUBSTANCES IN THE TECHNOLOGY OF MEDICINAL SHAMPOOS
Authors: Bejan P. , Ladatko D. , Kafarov V. , Alekseev K.
Published: May 2021

Diseases of the skin of the scalp are an important medical and social problem associated with their wide prevalence and significant impact on the quality of human life. They account for up to 4 % of the total number of skin diseases.

Therapy of diseases of the scalp is determined by the type of disease. A number of diseases involve the use of local drugs. One of the dosage forms intended for topical use are medicinal shampoos.
Le « budget vert » de l’État français : Quelle genèse et quel contenu pour quels horizon et effets ?
Authors: Degron Robin , Stroeymeyt Louis
Published: May 2021

Impulsée par l’OCDE, l’initiative en faveur d’un « budget vert » telle qu’elle est mise en oeuvre en France se caractérise par un effort de transparence en matière d’externalités environnementales des recettes et dépenses du budget de l’État. Pour limitée que sa portée soit, l’exercice s’inscrit dans un contexte de crise sanitaire et environnementale singulier associé à des plans de relance importants. À l’échelle nationale, le plan français appellerait des outils de projection budgétaire à moyen-long terme et devrait pousser à un renfort de l’unité des acteurs publics, en particulier l’État et les collectivités territoriales. Force est cependant de constater qu’il manque une nouvelle loi de programmation des finances publiques qui soit en phase avec les ambitions d’une relance qui se veut durable. L’actualité des crises renoue finalement avec les difficultés structurelles de notre droit financier. Ses lignes de faille historiques en termes de rapport au temps long et de fragmentation de l’action publique jouent de concert au moment de définir et de mettre en oeuvre une stratégie de transition écologique.
La elección del presidente en las democracias presidenciales y semipresidenciales: Guía Introductoria 21 para la Elaboración Constitucional
Authors: Abebe Adem , Bulmer Elliot
Published: May 2021

Los diferentes volúmenes de las Guías Introductorias para la Elaboración Constitucional pretenden contribuir a los procesos nacionales de elaboración o reforma constitucional ayudando a los ciudadanos, partidos políticos, organizaciones de la sociedad civil, funcionarios públicos y miembros de asambleas constituyentes a tomar decisiones constitucionales informadas. Además proporcionan orientación al personal de las organizaciones intergubernamentales y a otros agentes externos en su intento de apoyar de manera informada y relevante al contexto a los decisores políticos locales. Las Guías se han concebido como introducción para lectores no especializados y como recordatorio útil para lectores con conocimientos previos o experiencia en elaboración constitucional. Las Guías, organizadas temáticamente en torno a las decisiones prácticas que deben tomar los contribuyentes a la elaboración constitucional, tienen como objetivo explicar cuestiones constitucionales complejas de manera rápida y sencilla.
Valores de densidad en la escala de grises de materiales restauradores mediante tomografía computarizada de haz cónico. Estudio piloto.
Authors: Ruiz-Imbert Ana Cecilia
Published: May 2021

Objetivo de estudio: Determinar el valor de densidad en la escala de grises (VDEG) de tres materiales de obturación coronaria, mediante Tomografía Computarizada de Haz Cónico (TCHC). Materiales y métodos: Se seleccionaron seis cabezas de cerdo y a cada una se le realizó una restauración coronaria en la pieza 72, utilizando uno de los siguientes materiales: amalgama, resina o Cention N®, obteniendo dos muestras para cada material. Se adquirieron dos tomografías de cada espécimen, una de campo de visión pequeño (4x4cm) y otra de campo de visión grande (8x8cm), con parámetros de exposición fijos (90kV, 5mAs), para una muestra total de 12 tomografías. Se registraron los VDEG de los materiales para calcular el promedio de cada material. Resultados y conclusiones: Se observó que el VDEG promedio fue de 27 929.85 para amalgama, 5.798,54 para resina y 5.885,47 para Cention N®. A pesar de que se observa una variación en los VDEG de cada material al cambiar el tamaño de campo, dicha diferencia no es estadísticamente significativa.
Prevalencia de lesiones cervicales no cariosas en el Ecuador. Una revisión de la literatura
Authors: Molina Alvarado María Alejandra
Published: May 2021

Las lesiones cervicales no cariosas se caracterizan por la pérdida de estructura dentaria a nivel del límite amelocementário, sin una etiología bacteriana. Los estudios demuestran que existe un amplio rango de prevalencia de estas lesiones que pueden llegar hasta el 85%, siendo significativa también en el Ecuador. El objetivo de este estudio consiste en analizar los trabajos de investigación existentes en Ecuador sobre prevalencia de lesiones cervicales no cariosas (LCNC), establecer sus resultados, analizarlos e identificar las piezas dentales más afectadas. Se realizo la búsqueda en repositorios universitarios y bases de datos como Pub Med y Elsevier para seleccionar un total de 15 publicaciones relevantes en idioma inglés y español desde el año 2010 utilizando palabras clave estratégicas.
Impact of Supra-segmental Features on Reading Comprehension in First and Second Language: A Comparative Study of Iranian EFL learners
Authors: Mirfatemi Fatemeh , Sadeghi Amir , P Niyazi Mitra
Published: May 2021

Supra-segmental features refer to various forms of intonation and how words and sentences are uttered. Such features challenge meaning and comprehension, too. Despite the importance of these features and their reported association with phonological awareness and linguistic comprehension, their effects on reading comprehension have not been explored. The current work investigated the impact of a remedial program on Persian and English reading comprehension of a group of English language learners (N=30 divided into experimental and control groups). The measurements tested the components of reading comprehension based on the Simple View of Reading (SVR). Additionally, supra-segmental features were assessed by Profiling Elements of Prosody (i.e., supra-segmentals) in Speech-communication (PEPS) in both languages. As a result, English and Persian elision and also Persian listening were affected by teaching supra-segmental features. Assessing the transfer of linguistic skills revealed that Persian listening and knowledge of supra-segmentals, in particular, recognizing short syllables and awareness of stress position in a sentence, contribute to English reading comprehension. It indicates that reading and listening comprehension are affected by similar cognitive processes that may lay in the knowledge of supra-segmentals. The findings also suggest that simpler systems of supra-segmentals are more likely to transfer. Pertinent pedagogical implications were presented, as well.
Processamentos internos criados a partir da inteligência artificial
Authors: Nedel Nathalie Kuczura , Corrêa Maryana Zubiaurre
Published: May 2021

A inteligência artificial (IA) participa ativamente do mundo humano pois simula a capacidade de pensamento semelhantemente com o do ser humano, podendo, inclusive, criar invenções. Diante disso, cumpre questionar quem seria o titular da patente referente à invenção desenvolvida por sistemas dotados de inteligência artificial quando não há interferência humana direta? Para responder tal problemática, utiliza-se o método de abordagem dedutivo e como métodos de procedimento empregam-se o estruturalista e histórico. Assim, ao final, verificou-se que, analisando a Lei de Propriedade Intelectual atual, o ideal seria uma reformulação que abarcasse a temática. Porém, para não deixar referido direito descoberto, o melhor caminho até que tal ocorra, é, adotar o entendimento do Instituto Nacional de Propriedade Industrial, no sentido de conceder a titularidade das invenções geradas por sistemas dotados de IA a quem criou o sistema.
Patterns of the rheumatic disease course in the setting of a new coronavirus infection
Authors:   S.M. Kirov Military Medical Academy, Saint-Petersburg, Russian Federation, Vakhlevskiy V.V. , Tyrenko V.V. ,   S.M. Kirov Military Medical Academy, Saint-Petersburg, Russian Federation, Svintsitskaya I.S. ,   S.M. Kirov Military Medical Academy, Saint-Petersburg, Russian Federation, Kryukov E.V. ,   S.M. Kirov Military Medical Academy, Saint-Petersburg, Russian Federation
Published: May 2021

The article describes the main pathophysiological mechanisms underlying the potential use of antirheumatic therapy in the new COVID-19 in patients with rheumatic diseases. Also, it summarizes current data on the risk and outcome of COVID-19 in patients with systemic autoimmune diseases. To date, there are no large randomized studies on the use of antirheumatic drugs in patients with rheumatic diseases in the setting of COVID-19. Besides, there is no convincing evidence that any disease-modifying antirheumatic drug (conventional synthetic, biological, or targeted synthetic) can prevent the development of a severe COVID-19 course. At the same time, the importance of concomitant pathology (hypertension, obesity, cardiovascular diseases, diabetes mellitus) and risk factors (smoking) in the development of a severe COVID-19 course in patients with rheumatic diseases is shown. The article presents possible options for initiating and continuing treatment with antirheumatic drugs in patients with rheumatic diseases, depending on the stage of the infectious disease process. KEYWORDS: COVID-19, rheumatic diseases, disease-modifying antirheumatic drug, interleukin, tumor necrosis factor, glucocorticosteroids. FOR CITATION: Vakhlevskiy V.V., Tyrenko V.V., Svintsitskaya I.S., Kryukov E.V. Patterns of the rheumatic disease course in the setting of a new coronavirus infection. Russian Medical Inquiry. 2021;5(2):84–88. DOI: 10.32364/2587-6821-2021-5-2-84-88.
Extending Labelling Semantics to Weighted Argumentation Frameworks
Authors: Taticchi Carlo , Bistarelli Stefano
Published: May 2021

Argumentation Theory provides tools for both modelling and reasoning with controversial information and is a methodology that is often used as a way to give explanations to results provided using machine learning techniques. In this context, labelling-based semantics for Abstract Argumentation Frameworks (AFs) allow for establishing the acceptability of sets of arguments, dividing them into three partitions: acceptable, rejected and undecidable (instead of classical Dung two sets IN and OUT partitions). This kind of semantics have been studied only for classical AFs, whilst the more powerful weighted and preference-based framework has been not studied yet. In this paper, we define a novel labelling semantics for Weighted Argumentation Frameworks, extending and generalising the crisp one.
Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation
Authors: Bonetta Giovanni , Cancelliere Rossella , Liu Ding , Vozila Paul
Published: May 2021

Transformer-based models have demonstrated excellent capabilities of capturing patterns and structures in natural language generation and achieved state-of-the-art results in many tasks. In this paper we present a transformer-based model for multi-turn dialog response generation. Our solution is based on a hybrid approach which augments a transformer-based generative model with a novel retrieval mechanism, which leverages the memorized information in the training data via k-Nearest Neighbor search. Our system is evaluated on two datasets made by customer/assistant dialogs: the Taskmaster-1, released by Google and holding high quality, goal-oriented conversational data and a proprietary dataset collected from a real customer service call center. Both achieve better BLEU scores over strong baselines.
Domain-agnostic Document Representation Learning Using Latent Topics and Metadata
Authors: Raman Natraj , Nourbakhsh Armineh , Shah Sameena , Veloso Manuela
Published: May 2021

Fine-tuning a pre-trained neural language model with a task specific output layer is the de facto approach of late when dealing with document classification. This technique is inadequate when labeled examples are unavailable at training time and when the metadata artifacts in a document must be exploited. We address these challenges by generating document representations that capture both text and metadata in a task agnostic manner. Instead of traditional auto-regressive or auto-encoding based training, our novel self-supervised approach learns a soft-partition of the input space when generating text embeddings by employing a pre-learned topic model distribution as surrogate labels. Our solution also incorporates metadata explicitly rather than just augmenting them with text. The generated document embeddings exhibit compositional characteristics and are directly used by downstream classification tasks to create decision boundaries from a small number of labels, thereby eschewing complicated recognition methods. We demonstrate through extensive evaluation that our proposed cross-model fusion solution outperforms several competitive baselines on multiple domains.
System Z for Conditional Belief Bases with Positive and Negative Information
Authors: Sezgin Meliha , Kern-Isberner Gabriele
Published: May 2021

In non-monotonic reasoning, conditional belief bases mostly contain positive information in the form of standard conditionals. However, in practice we are often confronted with negative information, stating that a conditional does \emph{not} hold, i.e. we need a suitable approach for reasoning over belief bases $\Delta$ with positive and negative information. In this paper, we investigate the interaction of positive and negative information in a conditional belief base and establish a property for partitions of $\Delta$ that is equivalent to consistency. Based on this property, we develop a non-trivial extension of system Z for mixed conditional belief bases and provide an algorithm to compute this partition.
A Regularized Vector Autoregressive Hidden Semi-Markov model, with Application to Multivariate Financial Data
Authors: Xu Zekun , Liu Ye
Published: May 2021

Hidden Markov model (HMM) has been a popular choice for financial time series modeling due to its advantage in capturing dynamic regimes. However, HMM's implicit assumption that the state duration follows a geometric distribution is too strong to hold in practice. In this work, we propose a regularized vector autoregressive hidden semi-Markov model to analyze multivariate financial time series. One challenge in such a model setting is that the number of parameters is too large to be reliably estimated unless the time series is extremely long. To address this issue, an augmented EM algorithm is developed for parameter estimation by using regularized estimators for the state-dependent covariance matrices and autoregression matrices in the M-step. The performance of the proposed model is evaluated in a simulation experiment, and demonstrated with the New York Stock Exchange financial portfolio data.
Detecting the Presence of Named Entities in Bengali: Corpus and Experiments
Authors: Rashid Farzana , Hamid Fahmida
Published: May 2021

Named Entity Recognition (NER) belongs to the field of Information Extraction (IE) and Natural LanguageProcessing (NLP). NER aims to find and categorize named entities present in the textual data into recognizable classes. Named entities play vital roles in other related fields like question-answering, relationship extraction, and machine translation. Researchers have done a significant amount of work (e.g., dataset construction and analysis) in this direction for several languages like English, Spanish, Chinese, Russian, Arabic, to name a few. We do not find a comparable amount of work for several South-Asian languages like Bengali/Bangla. Hence, as part of the initial phase, we have constructed a qualitative dataset in Bengali.In this paper, we identify the presence of Named Entities (NEs) in the Bengali text (sentences), classify them in standardized categories, and test whether an automatic detection of NE is possible. We present a new corpus and experimental results. Our dataset, annotated by multiple humans, shows promising results (F-measures ranging from 0.72 to 0.84) in different setups (support vector machine (SVM) setups with simple language features and Long-Short Term Memory (LSTM) setup with various word embedding).
A General Framework for Domain-Specialization of Stance Detection
Authors: Mather Brodie , Dorr Bonnie J , Rambow Owen , Strzalkowski Tomek
Published: May 2021

We present a generalized framework for domain-specialized stance detection, focusing on Covid-19 as a use case. We define a stance as a predicate-argument structure (combination of an action and its participants) in a simplified one-argument format, e.g., wear(a mask), coupled with a task-specific belief category representing the purpose (e.g., protection) of an argument (e.g., mask) in the context of its predicate (e.g., wear), as constrained by the domain (e.g., Covid-19). A belief category PROTECT captures a belief such as “masks provide protection,” whereas RESTRICT captures a belief such as “mask mandates limit freedom.” A stance combines a belief proposition, e.g., PROTECT(wear(a mask)), with a sentiment toward this proposition. From this, an overall positive attitude toward mask wearing is extracted. The notions purpose and function serve as natural constraints on the choice of belief categories during resource building which, in turn, constrains stance detection. We demonstrate that linguistic constraints (e.g., light verb processing) further refine the choice of predicate-argument pairings for belief and sentiment assignments, yielding significant increases in F1 score for stance detection over a strong baseline.
Technology Policy Recommendations Using Artificial Intelligence
Authors: Batarseh Feras A. , Anuga Ashita , Nguyen Minh , Perini Dominick , Svetovidov Andrei , Tolman Amanda , Wani Qasim
Published: May 2021

Conventionally, the approach to policy making includesweighing the costs and benefits (i.e., tradeoffs) of certainchoices to calculate expected outcomes. However, quantifyingchoices is not always straightforward without understandingmany factors such as time, causal effects, and associations- making it difficult to label policy as either afailure or a success. Accordingly, our work proposes utilizingArtificial Intelligence (AI) algorithms to assess the impactof policy (state-level science and technology policies asan example). Our approach allows for an efficient policygenerating process, providing policymakers with insightsbased on previous legislation and historical data for their respectivestates. Leveraging AI this way stimulates humanlikelearning which can yield better results with the subjectivebehavior of public policy. Our approach consists of collectingdatasets relevant to science and technology policies,utilizing AI to create methods for determining the best pathforward, testing the validity of the algorithms using AI assurance,and measuring attributions to determine whichcomponents contribute to the outcomes most effectively.Using AI provides context relevant to the impacts of certainpolicies, and an overall data-driven approach that mitigatesdepending solely on expert’s judgment, subjective experiences,or ad-hoc processes.
Learning Sub-Character level representation for Korean Named Entity Recognition
Authors: Kim Yejin , Kim Yekyung
Published: May 2021

Most of the previous studies on the Korean Named Entity Recognition (NER) topic focused on utilizing morphological-level information because the language is rich in character diversity. This paper illustrates an improved unigram-level Korean NER model with sub-character level representation, jamo, which can represent a unique linguistic structure of Korean and its syntactic properties and morphological variations. The experimental result shows that exploiting sub-character gives us a boost of + (avg) 2 F1, also, our proposed C-GRAM model outperformed about 3 F1 comparing with the baseline.
The Empirical Evaluation of Semantic Alignment Quality Metrics for Vehicle Domain Component Frameworks Interface Ontologies
Authors: De Sangita , Brada Premek , Mottok Juergen , Niklas Michael
Published: May 2021

Semantic alignment of application software components’ ontologies represents a great interest in vehicle application domains that manipulate heterogeneous overlapping knowledge application frameworks. In the past few years, with the growth in the novel vehicle service requirements such as autonomous driving, V2X (Vehicle-to-Vehicle communication) and many others, automotive application software component models are becoming increasingly collaborative with other qualified cross-enterprise industrial partners to accomplish these complex service requirements. The most daunting impediment to this cross-enterprise collaboration is semantic interoperability. For efficient services collaboration through cross-enterprise semantic interoperability between the vehicle application frameworks’ software components, aligning the interface ontologies of these components by identifying the depth of semantic alignment relationships between the concepts of the interface ontologies is the major focus of this paper. In contrast to several existing ontology structural metrics, this work defines, evaluates and validates ontology metrics to measure the depth of semantic alignment between the vehicle domain software component frameworks’ interface ontological models. To emphasize the substantial role of semantic alignment of software component frameworks’ interface ontologies in semantic interoperability, a typical vehicle domain case study involving vehicle applications is considered for demonstration.
Probabilistic reputation networks
Authors: Atkinson Timothy
Published: May 2021

A reputation system is proposed in the form of a Reputation Network based on the premise of availability of a model of the world as a Dynamic Bayesian Network where the network's posterior for one time slice is set as the prior probability in the next time slice. These networks are solutions with better overall properties than the original network reducing the complexity of using the results when the input data is random. Experiments are an extension of prior work detecting when P2P Group Owner (GO) negotiation unfairly makes one of the participants GO more often than the other. The decision process of who becomes GO can be modeled as a Bernoulli trial. Based on this model, we show that we can set the false positive rate, we can detect more nuanced cheating without extra nodes in the network to help us, and when the underlying distribution favors one element as GO, it will declare a positive and keep the positive set without needing a second interpretive layer. Furthermore, we demonstrate that the original properties of non-random data are maintained.
You can simply rely on communities for a robust characterization of stances
Authors: Furman Damián Ariel , Marro Santiago , Cardellino Cristian , Popa Diana Nicoleta , Alonso Alemany Laura
Published: May 2021

We show that the structure of communities in social me- dia provides robust information for weakly supervised approaches to assign stances to tweets. Using as seed the SemEval 2016 Stance Detection Task annotated data, we retrieved a high number of topically related tweets. We then propagated information from the manually an- notated seed to the retrieved tweets and thus obtained a bigger training corpus. Classifiers trained with this bigger, weakly supervised dataset reach similar or better performance than those trained with the manually annotated seed. In addition, they are more robust with respect to common manual annotator errors or biases and they have arguably more coverage than smaller datasets. Weakly supervised approaches, most notably self- supervision, commonly suffer from error propagation. Interestingly, communities seem to provide a structure that constrains error propagation. In particular, weakly supervised classifiers that incorporate community struc- ture are more robust with respect to class imbalance. Additionally, this is a straightforward, transparent ap- proach, using standard tools and pipelines, cheaper and faster than methods like crowd sourcing for manual an- notations. Thus it facilitates adoption, interpretability and accountability.
InferNER: an attentive model leveraging the sentence-level information for Named Entity Recognition in Microblogs
Authors: Shahzad Moemmur , Amin Ayesha , Esteves Diego , Ngonga Ngomo Axel-Cyrille
Published: May 2021

We investigate the problem of named entity recognition in the user-generated text such as social media posts. This task is rendered particularly difficult by the restricted length and limited grammatical coherence of this data type. Current state-of-the-art approaches rely on external sources such as gazetteers to alleviate some of these restrictions. We present a neural model able to outperform state of the art on this task without recurring to gazetteers or similar external sources of information. Our approach relies on word-, character-, and sentence-level information for NER in short-text. Social media posts like tweets often have associated images that may provide auxiliary context relevant to understand these texts. Hence, we also incorporate visual information and introduce an attention component which computes attention weight probabilities over textual and text-relevant visual contexts separately. Our model outperforms the current state of the art on various NER datasets. On WNUT 2016 and 2017, our model achieved 53.48\% and 50.52\% F1 score, respectively. With Multimodal model, our system also outperforms the current SOTA with an F1 score of 74\% on the multimodal dataset. Our evaluation further suggests that our model also goes beyond the current state-of-the-art on newswire data, hence corroborating its suitability for various NER tasks.
Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon
Authors: Verdear Daniel , Visser Ubbo
Published: May 2021

Competitive Pokemon is a domain with rich semantics and complex relationships between its elements. Current research in the domain has focused on developing AI agents to select moves within a match, ignoring the problem of team building. We propose a team verification tool based on ontologies to model the complexities of the domain. A user can input their team into the tool, and the tool uses a description logic reasoner to classify Pokemon into their appropriate roles. The tool exports a visual representation of the team and a score evaluating its competitive viability. The classifications made by the TeamVerify tool have 87.7% precision and 86.0% recall in a multiclass, multilabel domain. We expect such a tool to reduce the learning curve for novice players who have not yet built intuitions on proper team structure.
Backtracking Restarts for Deep Reinforcement Learning
Authors: Marji Zaid Khalil , Licato John
Published: May 2021

Manipulating the starting states of a Markov Decision Process to accelerate the learning of a deep reinforcement learning agent is an idea that has been proposed in several ways in the literature. Examples include starting from random states to improve exploration, taking random walks from desired goal states, and using performance-based metrics for starting states selection policy. In this paper, we explore the idea of exploiting the RL agent's trajectories generated during training for use as starting states. The main intuition behind this proposal is to focus the training of the RL agent to overcome its current weaknesses by practicing overcoming failure states by resetting the environment to a state in its recent past. We shall call the idea of starting from a fixed (or variable) number of steps back from recent terminal or failure states `backtracking restarts'. Our empirical findings show that this modification yields tangible speedups in the learning process.
Thinking Fast and Slow: A CBR Perspective
Authors: Kaurav Srashti , Ganesan Devi , P Deepak , Chakraborti Sutanu
Published: May 2021

In a path-breaking work, Kahneman characterized human cognition as a result of two modes of operation, Fast Thinking and Slow Thinking. Fast thinking involves quick, intuitive decision making and slow thinking is deliberative conscious reasoning. In this paper, for the first time, we draw parallels between this dichotomous model of human cognition and decision making in Case-based Reasoning (CBR). We observe that fast thinking can be operationalized computationally as the fast decision making by a trained machine learning model, or a parsimonious CBR system that uses few attributes. On the other hand, a full-fledged CBR system may be seen as similar to the slow thinking process. We operationalize such computational models of fast and slow thinking and switching strategies, as Models 1 and 2. Further, we explore the adaptation process in CBR as a slow thinking manifestation, leading to Model 3. Through an extensive set of experiments on real-world datasets, we show that such realizations of fast and slow thinking are useful in practice, leading to improved accuracies in decision-making tasks.
Compressing Graph Data by Leveraging Domain Independent Knowledge
Authors: Velampalli Dr. Sirisha
Published: May 2021

Graphs are used to solve many problems in the real world.At the same time size of the graphs presents a complexscenario to analyze essential information that they contain.Graph compression is used to understand high level structureof the graph through improved visualization. In this work,we introduce CRADLE (CompRessing grAph data with Domainindependent knowLEdge), a novel method based onknowledge rule called netting, which reports the number ofexternal networks for each instance of the substructure. Byfinding such substructures with more number of external networkswe can judiciously improve the compression rate. Weempirically evaluate our approach using synthetic as well asreal-world datasets. We compare CRADLE with baseline approaches.Our proposed approach is comparable in compressionrate, search space, and runtimes to other well-knowngraph mining approaches.
An Experimental Study on the Optimization of Learners' Cognitive Load in Web-based Learning Environment
Authors: Cui Ning , Fang Yuan
Published: May 2021

With the global epidemic of COVID-19, online teaching and learning have been carried out on a large scale all over the world, and MOOC has been further developed and applied. Through experiments, this study verified the feasibility of advance organizer strategy, eliminating redundancy strategy and ARCS model design strategy. The results are as follows. (1) In the Web-based learning environment, for the more difficult materials, it is beneficial to reduce the internal cognitive load of learners to provide a certain advance organizer before the learners start formal learning; but for the easier materials, whether or not to provide advance organizer has no significant impact on the learning results of learners. (2) In the Web-based learning environment, it is better to provide advance organizer for the more difficult knowledge by implanting background music into the Web-based learning environment; it can obviously hinder the learners' learning, but it is not obvious when the e-learners learn relatively simple knowledge. (3) In the Web-based learning environment, ARCS model design can stimulate the learning motivation of e-learners and optimize the cognitive load of e-learners.
Capim Zuri (Panicum Maximum BRS) Na Região Do Município De Ariquemes/RO Brasil: Sob A Perspectiva Do Produtor
Authors: Camacho Sérgio Henrique da Silva , Preato Dânlei de Oliveira
Published: May 2021

O presente artigo elucida, a viabilidade de implantação do capim Zuri (Panicum Maximum BRS) em propriedades do município de Ariquemes/RO. Os argumentos expostos no decorrer da pesquisa, foram elaborados por meios de entrevistas de campo, semi e estruturada, web sites, artigos e teses. Buscou-se de modo comparativo analisar os avanços das pastagens no Brasil, no período de 1985 a 2019, afim de entender melhor tais evoluções no segmento pecuário brasileiro. De maneira geral serão expostos relatos dos produtores rurais que implantaram o BRS Zuri, em suas propriedades, trazendo uma interpretação sucinta e objetiva da viabilidade de sua implantação no município de Ariquemes/RO.
НАПРЯМИ ПІДВИЩЕННЯ КОНКУРЕНТОСПРОМОЖНОСТІ ПОСЛУГ ФАРМАЦЕВТИЧНОГО ПІДПРИЄМСТВА
Authors: Білоус Світлана , Яковенко Ангеліна
Published: May 2021

З кожним днем ми можемо спостерігати, як зростає кількість аптечних закладів у кожному місті, а відповідно і в країні в цілому. Поточна економічна ситуація призводить до посилення конкуренції на українському ринку фармацевтичних послуг і стимулює аптеки України більше уваги приділяти своїй конкурентоспроможності. Це може стосуватися як цінової політики закладу, так і рівня обслуговування у ньому. Найбільш перспективними напрямами підвищення конкурентоспроможності аптечного бізнесу є підвищення рівня сервісу та якості фармацевтичних послуг. У статті проаналізовано фармацевтичний ринок нашої країни та розглядаються ключові шляхи підвищення конкурентоспроможності послуг фармацевтичних компаній. Автори розробили низку рекомендацій щодо підвищення рівня конкурентоспроможності аптек. Рекомендації щодо його застосування дають автори.
ФОРМУВАННЯ МАРКЕТИНГОВОЇ СТРАТЕГІЇ УПРАВЛІННЯ КОНКУРЕНТНІСТЮ ПІДПРИЄМСТВ З ВИРОЩУВАННЮ КРУП’ЯНИХ КУЛЬТУР
Authors: Нісходовська Олена
Published: May 2021

Стаття присвячена актуальним питанням щодо формування маркетингової стратегії управління конкурентністю підприємств в галузі вирощування круп’яних культур. У статті визначено методичні підходи до формування конкурентної стратегії; здійснено групування загальнокорпоративних цілей підприємств по вирощуванню круп’яних культур; досліджено з визначенням переваг сутність конкурентоспроможності підприємства по вирощуванню круп’яних культур; обґрунтовано розроблену маркетингову стратегію підприємств по вирощуванню круп’яних культур; визначено необхідність розробки стадій формування конкурентної стратегії підприємств по вирощуванню круп’яних культур; окреслено основні стратегічними напрямами забезпечення конкурентоспроможності підприємств по вирощуванню круп’яних культур; встановлено, що за допомогою маркетингової стратегії можна сформувати універсальну пропозицію для всіх споживачів ринку.