State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

Transaction-based energy (TE) management and control has become an increasingly relevant topic, attracting considerable attention from industry and the research community alike. As a result, new techniques are emerging for its development and actualization. This paper presents a comprehensive review of TE involving peer-to-peer (P2P) energy trading and also covering the concept, enabling technologies, frameworks, active research efforts and the prospects of TE. The formulation of a common approach for TE management modelling is challenging given the diversity of circumstances of prosumers in terms of capacity, profiles and objectives. This has resulted in divergent opinions in the literature. The idea of this paper is therefore to explore these viewpoints and provide some perspectives on this burgeoning topic on P2P TE systems. This study identified that most of the techniques in the literature exclusively formulate energy trade problems as a game, an optimization problem or a variational inequality problem. It was also observed that none of the existing works has considered a unified messaging framework. This is a potential area for further investigation

Value of Travel Time Reliability: A review of current evidence

Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by users in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the users. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.variability, reliability, travel time, scheduling.

Research and Regions. a KWIC Indexed Bibliography

Computerized techniques applied to economics to produce bibliography of related materia

Deceleration: Revealed Preference in Society and Win-Win-Strategy for Sustainable Management

Until recently "deceleration" has been little recognized as a technical term or as an idea, but now it seems to be getting more attention. Despite time is a decisive factor for the productivity and competitive advantages of companies continual acceleration may well be counter-productive and lead to an "acceleration paradox" – more of it not always is better. Three levels of the emergence and spread of the acceleration phenomenon can be distinguished: the macroeconomic, the microeconomic, and the motivational and behavioural level, all of them bearing, however, the danger of an "acceleration trap". Despite possible damages of acceleration deceleration processes usually seem only to be accepted if they are win-win strategies, i.e., if they have a positive impact on ecological and human targets and foster company interests at the same time. The study provides three case studies where win-win situations are realized. Going one step further, however, one can also find a preference for deceleration of agents if deceleration and economic goals are conflicting. How can the agents' willingness to pay for deceleration in such trade-off situations be measured? We do a first step in his direction with three experiments which were conducted at the Technical University of Dresden. In the first experimental setting the subjects are confronted with a trade-off between gaining a possibly higher financial reward by solving mental exercises more quickly and decelerating by taking refreshment brakes during the exercises at the expense of a potentially lower reward. In the second and the third settings subjects are virtually offered an accelerated and a decelerated alternative (more stress for higher income; more stress for faster technical progress of personal computers). The empirical evidence of all three experiments are fully consistent with the expectation that deceleration has a positive value to the subjects. --Acceleration,deceleration,acceleration trap,win-win strategy,individual willingness to pay

Why is the Doha development agenda failing? And what can be done?: A computable general equilibrium-game theoretical approach

"We herein use a world Computable General Equilibrium (CGE) model to simulate 143 potential trade reforms and seek solutions to the issues hampering progress in the Doha Development Agenda (DDA). Inside the domain defined by all these possible outcomes, we apply the axiomatic theory of bargaining and select the Nash solution of cooperative games. The solutions vary according to the objective functions adopted by the trade negotiators. When real income is the objective and services are excluded, or when optimizing terms of trade is the objective, the Nash solution is the status quo. Trade liberalization is feasible only when the negotiators focus on national exports or Gross Domestic Product (GDP). Our assessment of some possible solutions reveals that excluding members having a GDP below a certain threshold improves the bargaining process, regardless of the governments' objective. Formation of coalition, such as the G20, constitutes an option for its members to block outcomes imposed by rich members. We also find that side payments may be a solution, but represent a very high share of the global income gain." from authors' abstractTrade negotiations, Computable general equilibrium (CGE) modeling, Nash solution, Side payments, Cooperative games, Globalization, Markets, Doha Development Agenda,

Role of telemedicine in the management of oral anticoagulation in atrial fibrillation: a practical clinical approach

COVID-19; Direct oral anticoagulant; TelemedicineCOVID-19; Anticoagulante oral directo; TelemedicinaCOVID-19; Anticoagulant oral directe; TelemedicinaCompared with face-to-face consultations, telemedicine has many advantages, including more efficient use of healthcare resources, partial relief of the burden of care, reduced exposure to COVID-19, treatment adjustment, organization of more efficient healthcare circuits and patient empowerment. Ensuring optimal anticoagulation in atrial fibrillation patients is mandatory if we want to reduce the thromboembolic risk. Of note, telemedicine is an excellent option for the long-term management of atrial fibrillation patients. Moreover, direct oral anticoagulants may provide an added value in telemedicine (versus vitamin K antagonists), as it is not necessary to monitor anticoagulant effect or make continuous dosage adjustments. In this multidisciplinary consensus document, the role of telemedicine in anticoagulation of this population is discussed and practical recommendations are provided.V Barrios has received consultancy/lecture fees from Bayer, BMS/Pfizer, Boehringer Ingelheim and Daiichi Sankyo. S Cinza-Sanjurjo has received honoraria for presentations from Bayer, Boehringer-Ingelheim, Daiichi Sankyo and Pfizer-BMS; advisory board fees from Bayer, Boehringer-Ingelheim, Daiichi Sankyo and Pfizer-BMS; and funding for studies from Bayer. J García-Alegría reports consulting fees and/or lectures honoraria from Bayer, Boehringer Ingelheim, Bristol-Myers Squibb and Daiichi Sankyo. R Freixa-Pamias has received honoraria for presentations from Bayer, Boehringer-Ingelheim, Daiichi Sankyo and Pfizer-BMS. F Llordachs-Marques. No potential conflicts of interest were declared by the author. CA Molina reports consulting fees and/or honoraria from Novo Nordisk, Bayer, Pfizer, BMS, Daiichi Sankyo and Boehringer Ingelheim. A Santamaría has received honoraria per conferences from Octapharma, Novo Nordisk, Bayer, Pfizer, BMS, Sobi, Shire, Sanofi, LEO Pharma, Rovi, Daiichi Sankyo, Werfen and Ferrer. D Vivas reports no potential conflicts of interest were declared by the author. C Suárez has received speaker and/or advisory fees from Bayer, Pfizer/BMS, Daiichi Sankyo. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed

Machine Learning for Smart and Energy-Efficient Buildings

Energy consumption in buildings, both residential and commercial, accounts for approximately 40% of all energy usage in the U.S., and similar numbers are being reported from countries around the world. This significant amount of energy is used to maintain a comfortable, secure, and productive environment for the occupants. So, it is crucial that the energy consumption in buildings must be optimized, all the while maintaining satisfactory levels of occupant comfort, health, and safety. Recently, Machine Learning has been proven to be an invaluable tool in deriving important insights from data and optimizing various systems. In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient. For the convenience of readers, we provide a brief introduction of several machine learning paradigms and the components and functioning of each smart building system we cover. Finally, we discuss challenges faced while implementing machine learning algorithms in smart buildings and provide future avenues for research at the intersection of smart buildings and machine learning

Authenticity in Language Learning: A Study of Language Materials in Public High Schools

Instructional materials are paramount in effecting language instruction. However, there are contextual issues related to the use and selection of these materials. This study focused on authentic language instructional materials in public secondary schools in the Philippines. This study employed a mixed-methods research approach. This study concludes that internet-based authentic language instructional materials are inadequate in language instruction, showing limitations on the capacity of the school and the language teachers to provide adequate internet-based materials; there are concerns about using authentic language instructional materials that hinder learners' authentic response and comprehension to authentic language instructional materials, and there were measures to overcome the concerns which could develop authentic language instructional materials into the ideal learning materials. It is recommended that language teachers select resources according to the learners' unique requirements, proficiency levels, cultural contexts, and educational contexts. The participation of learners in the selection process and activity design is crucial to ensure the materials are engaging and culturally pertinent. To effectively address the challenges associated with using these resources, a collaborative approach is recommended, involving teachers, students, and other stakeholders in implementing the suggested solutions

ANALYST RELUCTANCE IN CONVEYING NEGATIVE INFORMATION TO THE MARKET

This paper investigates one of the main sources of financial markets’ public information: financial analysts’ reports. We analyze reports on S&P 500 index through a multidisciplinary approach integrating behavioral finance with linguistic analysis to understand how financial phenomena reflect in or are deviated by language, i.e. whether financial and linguistic trends follow the same patterns, boosting each other, or diverge. In the latter, language could conceal financial events, mitigating analysts’ feelings and misleading investors. Therefore, we attempt to identify behavioral biases (mainly represented by cognitive dissonances) present in analysts’ reports. In doing so, we try to understand whether analysts try to hide perception of negative price-sensitive events or not, eventually anticipating and controlling the market “mood”. The study focuses on how analysts use linguistic strategies in order to minimize their risk of issuing wrong advice. Our preliminary results show reluctance to incorporate negative information in the reports. A slight asymmetry between the use of positive/negative keywords taken into account and the negative/positive trends of the index seems to emerge. In those weeks characterized by the index poor performances, the frequency of keywords with a negative meaning is lower. On the contrary, in the recovering weeks a higher use of keywords with a positive meaning does not clearly appear. A thorough investigation on the market moods, and the analysis of the text of the reports enable us to assess if and to what extent analysts have been willing to mitigate pessimism or emphasize confidence. Furthermore, we contribute to the existing literature also proposing a possible analysts’ value function based on the Prospect Theory [Kahneman and Tversky, 1979] where analysts try to maximize the value deriving from enhancing their reputation, taking into account the risks that may cause a reputational loss. This theoretical framework supports our preliminary findings and supports the idea that analysts are risk-averse when facing reputational gains and risk-seeking in case of potential reputational losses

Fuzzy decision making system and the dynamics of business games

Effective and efficient strategic decision making is the backbone for the success of a business organisation among its competitors in a particular industry. The results of these decision making processes determine whether the business will continue to survive or not. In this thesis, fuzzy logic (FL) concepts and game theory are being used to model strategic decision making processes in business organisations. We generally modelled competition by business organisations in industries as games where each business organization is a player. A player formulates his own decisions by making strategic moves based on uncertain information he has gained about the opponents. This information relates to prevailing market demand, cost of production, marketing, consolidation efforts and other business variables. This uncertain information is being modelled using the concept of fuzzy logic. In this thesis, simulation experiments were run and results obtained in six different settings. The first experiment addresses the payoff of the fuzzy player in a typical duopoly system. The second analyses payoff in an n-player game which was used to model a perfect market competition with many players. It is an extension of the two-player game of a duopoly market which we considered in the first experiment. The third experiment used and analysed real data of companies in a case study. Here, we chose the competition between Coca-cola and PepsiCo companies who are major players in the beverage industry. Data were extracted from their published financial statements to validate our experiment. In the fourth experiment, we modelled competition in business networks with uncertain information and varying level of connectivity. We varied the level of interconnections (connectivity) among business units in the business networks and investigated how missing links affect the payoffs of players on the networks. We used the fifth experiment to model business competition as games on boards with possible constraints or restrictions and varying level of connectivity on the boards. We also investigated this for games with uncertain information. We varied the level of interconnections (connectivity) among the nodes on the boards and investigated how these a ect the payoffs of players that played on the boards. We principally used these experiments to investigate how the level of availability of vital infrastructures (such as road networks) in a particular location or region affects profitability of businesses in that particular region. The sixth experiment contains simulations in which we introduced the fuzzy game approach to wage negotiation in managing employers and employees (unions) relationships. The scheme proposes how employers and employees (unions) can successfully manage the deadlocks that usually accompany wage negotiations. In all cases, fuzzy rules are constructed that symbolise various rules and strategic variables that firms take into consideration before taken decisions. The models also include learning procedures that enable the agents to optimize these fuzzy rules and their decision processes. This is the main contribution of the thesis: a set of fuzzy models that include learning, and can be used to improve decision making in business