Miracle-dz/UniFAR-FTUs huggingface dataset:
Why pay for nothing? An experiment on a conditional subsidy scheme in a threshold public good game.

The voluntary provision of public goods can be enhanced by subsidies paid to contributors. However, in the case of threshold public goods, subsidies can be wasted if the public good is not ultimately produced. We therefore test the performance of a conditional subsidy paid to each contributor only if the public good threshold is attained by the group, in comparison to the classic subsidy paid to contributors even if the public good is not produced. This system offers the obvious advantage of sparing public money when the public good is not produced but there is the risk that such incentive discourages contributions. Our experimental results show that subsidy schemes improve the provision of threshold public goods and are welfare-improving compared to a no-subsidy situation. Furthermore, the collective conditionality improves the efficiency of the subsidy mechanism and in some cases improves its effectiveness, despite identical game-theoretic predictions. Applying this conclusion to environmental issues, these results suggest that, in the case of threshold pollution, subsidy schemes encouraging polluters to abate could be improved by introducing a collective conditionality.
Severe IgE‐mediated anaphylaxis following consumption of fried frog legs: definition of α‐parvalbumin as the allergen in cause

Background: IgE‐mediated allergic reactions to bullfrog and edible frog have been reported. The implicated allergens have not been defined so far. The frog material and the patient's serum from a case of severe food‐induced anaphylaxis were used to define the implicated allergen at the protein and DNA level.
Frequency Regulation Contribution Through Variable-Speed Wind Energy Conversion Systems

This paper presents a new method to enhance the participation of variable-speed wind energy conversion systems (WECS) in existing frequency regulation mechanisms. The proposed approach, based on a modified inertial control scheme, takes advantage of the fast response capability associated with electronically-controlled WECS, allowing the kinetic energy stored by rotational masses to be partly and transiently released in order to provide earlier frequency support. An additional improvement is achieved by communicating the WECS response to conventional generators so that these can eventually take care of the full load imbalance. Several simulations using a two-area test system are performed to demonstrate the benefits of the proposed scheme.
Culture, Communication, and the Information Problem in Contingent Valuation Surveys: A Case Study of a Wildlife Enhancement Scheme

Contingent valuation (CV) is a technique for providing estimates of the monetary value of public goods which have no market. The authors consider whether the information provided for the hypothetical market enables respondents to express their ‘true’ preference for the ‘good’, or whether their willingness to pay is dependent on the quantity and quality of information provided in the survey. They argue that a cultural perspective in which the CV transaction is viewed as a communicative ‘dialogue-at-a-distance’ between researchers and respondents through the medium of the CV text provides more insight into the encoding and decoding of the ‘good’—in this case an agri-environment policy to enhance nature conservation on an internationally significant wetland in South East England. They argue that, within its own scientific parameters, CV surveys are unable to capture fully all the aspects of the ‘good’ to be valued. The problem is more acute when the ‘good’ represents the uncertain outcomes (in terms of landscape and biodiversity) of a policy. Without a complete specification, which may well be an impossibility for environmental ‘goods’, respondents are able to bring their own readings to their interpretation of the scenario. This means that CV researchers cannot know precisely what ‘good’ respondents were attempting to ‘value’. The authors follow the production of the CV scenario for the valuation of the Pevensey Levels Wildlife Enhancement Scheme; conduct a critical discourse analysis to demonstrate how the linguistic and visual representations inevitably fulfil rhetorical functions; and then present the deliberations of respondents to the CV survey who participated in in-depth discussion groups after completion of the survey.
Reluctance of internists and medical nurses to perform mouth-to-mouth resuscitation.

BACKGROUND Physicians and nurses constitute a major part of citizen cardiopulmonary resuscitation responders and serve as educators and resource personnel concerning cardiopulmonary resuscitation. We decided to determine if fear of infectious disease has dampened physician and nurse response to perform mouth-to-mouth resuscitation (MMR). METHODS Four hundred thirty-three internists and one hundred fifty-two medical nurses responded to presentations of mock cardiac arrest scenarios. RESULTS Forty-five percent of the physicians and 80% of the nurses would refuse to do MMR on a stranger. Between 18% and 25% of nurses and attending internists would not do MMR on a child. Being born in the United States or white racial background decreased the reluctance of the respondents to perform MMR. Only 15% of the respondents would do MMR on a stranger in a gay neighborhood. All respondents that would not do MMR stated that their reason involved fear of contracting communicable diseases, especially acquired immunodeficiency syndrome. CONCLUSIONS Internists and medical nurses are highly reluctant to perform MMR. We recommend that the teaching of MMR should emphasize performance on children and family members where willingness to perform MMR is high. We urge public education along with widespread availability of effective barrier masks to resuscitate MMR itself.
Fast Solution Techniques for Energy Management in Smart Homes

In the future, residential energy users will seize the full potential of demand response schemes by using an automated smart home energy management system (SHEMS) to schedule their distributed energy resources. The underlying optimisation problem facing a SHEMS is a sequential decision making problem under uncertainty because the states of the devices depend on the past state. There are two major challenges to optimisation in this domain; namely, handling uncertainty, and planning over suitably long decision horizons. In more detail, in order to generate high quality schedules, a SHEMS should consider the stochastic nature of the photovoltaic (PV) generation and energy consumption. In addition, the SHEMS should accommodate predictable inter-daily variations over several days. Ideally, the SHEMS should also be able to integrate into an existing smart meter or a similar device with low computational power. However, extending the decision horizon of existing solution techniques for sequential stochastic decision making problems is computationally difficult and moreover, these approaches are only computationally feasible with a limited number of storage devices and a daily decision horizon. Given this, the research investigates, proposes and develops fast solution techniques for implementing efficient SHEMSs. Specifically, three novel methods for overcoming these challenges: a two-stage lookahead stochastic optimisation framework; an approximate dynamic programming (ADP) approach with temporal difference learning; and a policy function approximation (PFA) algorithm using extreme learning machines (ELM) are presented. Throughout the thesis, the performance of these solution techniques are benchmarked against dynamic programming (DP) and stochastic mixed-integer linear programming (MILP) using a range of residential PV-storage (thermal and battery) systems. We use empirical data collected during the Smart Grid Smart City project in New South Wales, Australia, to estimate the parameters of a Markov chain model of PV output and electrical demand using an hierarchical approach, which first cluster empirical data and then learns probability density functions using kernel regression (Chapter 2). The two-stage lookahead method uses deterministic MILP to solve a longer decision horizon, while its end-of-day battery state of charge is used as a constraint for a daily DP approach (Chapter 4). Here DP is used for the daily horizon as it is shown to provide
The Economic Impact of Terrorist Incidents on the Italian Hospitality Industry

Acts of terror are intended to incite fear and intimidation, which makes tourism particularly susceptible to attacks. Because the hospitality industry serves as a useful barometer of the indirect impact of attacks, we examine the impact of terrorist incidents on lodging-use rates in Italy between 1995 and 1997. We make use of data on domestic as well as international terrorism at the city level to explore more localized implications of terrorist incidents. We find that lodgings used by foreign visitors are the most sensitive to terrorist attacks and that the incidents have the largest impact during the year of the attack.
A Study of Dynamic Market Strategies of Hedge Funds Using the Kalman Filter

The authors consider the dynamic market strategies of hedgefunds by using the Kalman filter. There are many studies onthe behavior of conditional alphas and betas of hedge funds,but the dynamics of these coefficients is studied within thetraditional regression framework: The resulting conditionalalphas and betas are hence for a great part arbitrary becausethey do not result from a dynamic optimization process. Inthis article, the authors try to correct this problem in partby writing transition equations for the alpha and the betawhose explanatory variables are market financial variables.The alphas of hedge fund indices appear quite difficult tocontrol, a result in line with the market efficiency hypoth-esis. Besides, the betas are much more controlable, their reac-tion to market variables being significant.
INSULATION OF INDIA FROM THE EAST ASIAN CRISIS: AN ANALYSIS

This paper investigates the effects of the East Asian crisis on the Indian economy and exchange rate movements. Despite the contagion effects that profoundly affected the other crisis-hit countries, the Indian economy and the rupee were found less affected. Reforms after the 1990–1991 crisis, control of capital flows, weak economic linkages with crisis-affected countries and stabilization policies that include intervention in the foreign exchange market and tightening of monetary policy are reasons for the insulation of the Indian economy from the crisis.
Linking Entities in Scientific Metadata

Linked entity data in metadata records builds a foundation for the Semantic Web. Even though metadata records contain rich entity data, there is no linking between associated entities such as persons, datasets, projects, publications, or organizations. We conducted a small experiment using the dataset collection from the Hubbard Brook Ecosystem Study (HBES), in which we converted the entities and their relationships into RDF triples and linked the URIs contained in RDF triples to the corresponding entities in the Ecological Metadata Language (EML) records. Through the transformation program written in XML Stylesheet Language (XSL), we turned a plain EML record display into an interlinked semantic web of ecological datasets. The experiment suggests a methodological feasibility in incorporating linked entity data into metadata records. The paper also argues for the need for change in the scientific as well as the general metadata paradigm.
Exploring the effect of meta-structural information on the global consistency of SLAM

Accurate online estimation of the environment structure simultaneously with the robot pose is a key capability for autonomous robotic vehicles. Classical simultaneous localization and mapping (SLAM) algorithms make no assumptions about the configuration of the points in the environment, however, real world scenes have significant structure (ground planes, buildings, walls, ceilings, etc.) that can be exploited. In this paper, we introduce meta-structural information associated with geometric primitives into the estimation problem and analyze their effect on the global structural consistency of the resulting map. Although we only consider the effect of adding planar and orthogonality information for the estimation of 3D points in a Manhattan-like world, this framework can be extended to any type of geometric, kinematic, dynamic or even semantic information. We evaluate our approach on a city-like simulated environment. We highlight the advantages of the proposed solution over SLAM formulation considering no prior knowledge about the configuration of 3D points in the environment.
Managing HIV/AIDS: Yunnan's Government-driven, Multi-sector Partnership Model

This article seeks to unravel the management model used by China's Yunnan Province in its fight against HIV/AIDS. This government-driven, multi-sector partnership model has led to some capacity building and stabilization of HIV transmission among certain at-risk populations. The organizational strategies employed in this model might be useful for resource-poor countries in containing the spread of HIV/AIDS.
Mobile Learning for English Language Acquisition: Taxonomy, Challenges, and Recommendations

Mobile learning (m-learning) is increasingly becoming a popular global trend, especially among English language learners. However, despite the growing interest in mobile English language learning, there have been no reviews of research conducted on this subject. This paper represents the first attempt to provide a comprehensive analysis of the existing literature (2010–2015) to identify the taxonomy and distribution of research as well as to identify the advantages and challenges and provide some recommendations to facilitate the effective use of mobile English language learning and its applications. Following a review protocol, articles on mobile English language learning from six major databases (IEEE Xplore, ScienceDirect, Web of Science, ERIC, SpringerLink, and Wiley Online Library) were reviewed. Applying inclusion and exclusion criteria, 133 related articles were identified. The results show that the majority of studies were conducted on application m-learning technologies. Pure mobile applications were the most widely-used applications in the English m-learning context. Meanwhile, concerns regarding quality, usability, integration, financial costs, security and privacy, pedagogical practice, and safety were found to be the main challenges of mobile English language learning. Finally, some recommendations are provided for users, developers/providers, and researchers. The results of this paper can assist users, researchers, policymakers, and practitioners in the education sector to allocate the necessary resources and make plans to mitigate the challenges and facilitate the effective use of mobile English language learning in educational practices.
Changing the Paradigm

This article explores the feasibility of a trust-based organizational paradigm as a new model for public sector management. A conceptual model is developed from a literature review of more than 100 journal articles and books. The author proposes that participation in decision making, feedback from and to employees, and empowerment of employees lead to increased interpersonal trust (between supervisor and employee) in a public organization. The article further hypothesizes that these trust-building practices between supervisors and workers can lead to increased productivity and strengthened organizational commitment. The conceptual model is empirically tested using as a case study both structural equation modeling and data from a municipal government. The analysis demonstrates that the trust-based model is a viable paradigm for increasing interpersonal trust, organizational commitment, and productivity in the public sector.
Penalties and Rewards As Inducements To Cooperate

This paper considers self-stipulated penalties for defection and rewards for cooperation as inducements to cooperate in the prisoner's dilemma. The paper explicitly characterizes penalties and rewards that are necessary and suffcient to induce the players to cooperate. The characterization results imply a partion of prisoner's dilemma games into four classes according to whether both penalties and rewards can induce the players to cooperate; penalties but not rewards can induce the players to cooperate; rewards but not penalties can induce the players to cooperate; and neither penalties nor rewards can induce the players to cooperate. The paper also discusses implications of the results to "penalty clauses" in the law of contracts.
Multi-Source Social Feedback of Online News Feeds

The profusion of user generated content caused by the rise of social media platforms has enabled a surge in research relating to fields such as information retrieval, recommender systems, data mining and machine learning. However, the lack of comprehensive baseline data sets to allow a thorough evaluative comparison has become an important issue. In this paper we present a large data set of news items from well-known aggregators such as Google News and Yahoo! News, and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn. The data collected relates to a period of 8 months, between November 2015 and July 2016, accounting for about 100,000 news items on four different topics: economy, microsoft, obama and palestine. This data set is tailored for evaluative comparisons in predictive analytics tasks, although allowing for tasks in other research areas such as topic detection and tracking, sentiment analysis in short text, first story detection or news recommendation.
Noise-Aware Floorplanning for Fast Power Supply Network Design

As device size continues to shrink in the sub-micron regime, power supply noise is becoming a performance and reliability bottleneck in modern VLSI design. In this paper, we propose a new floorplanning methodology for fast power supply noise design convergence. By evaluating power supply noise at this early design stage, area-efficient floorplans with considering IR voltage drop and electromigration (EM) are generated. Compared to designs based on area-optimized floorplans, the proposed methodology achieves noise-satisfied designs with an average 52% less power routing resource.
Informality and Minimum Wages by Cohort in Colombia

This article aims to analyze the effect of minimum wage levels on the decision to join the informal job sector. We estimated a pseudo panel model of engagement in the informal sector using an IV-probit. Our results show that an increased wage gap—the relative difference between observed and minimum wage—has not only a disincentive effect on the probability of joining informality, but also leads to a substitution effect between younger and older cohorts. ***** Este articulo busca analizar el efecto de los niveles del salario minimo en la decision de unirse al sector del empleo informal. Estimamos un modelo pseudo panel de participacion en el sector informal usando un probit-IV. Nuestros resultados muestran que la creciente brecha salarial –la diferencia relativa entre el salario observado y el salario minimo– no solo tiene un efecto de desincentivo en la probabilidad de unirse a la informalidad, sino que ademas lleva a un efecto de sustitucion entre las cohortes mas jovenes y las de mayor edad.
description of changes in action potential firing elicited by stimuli in olfactory sensory neurons in situ

The discovery of the odorant receptor (OR) family by Buck and Axel in 1991 provided a quantum jump in our understanding of olfactory function. However, the study of the responsiveness of ORs to odor ligands was challenging due to the difficulties in deorphanizing the receptors. In this manuscript, we review recent findings of OR responsiveness that have come about through improved OR deorphanization methods, site-directed mutagenesis, structural modeling studies, and studies of OR responses in situ in olfactory sensory neurons. Although there has been a major leap in our understanding of receptor–ligand interactions and how these contribute to the input to the olfactory system, an improvement of our understanding of receptor structure and dynamics and interactions with intracellular and extracellular proteins is necessary.
Free Radical Scavenging Effect of Donepezil as the Possible Contribution to its Memory Enhancing Activity in Mice

Abstract Background: Donepezil (DP) is the major drug currently used for enhancing memory function in patients with Alzheimer’s disease (AD), an action ascribed to the elevation of central cholinergic neurotransmission. However, there are indications that DP may protect neurons against injury through the prevention of free radical-mediated neuroinflammation that has been implicated in the pathology of AD. Thus, this study was carried out to examine the effect of DP on memory impairment and on biomarkers of oxidative stress induced by scopolamine (SC) and lipopolysaccharide (LP) in mice. Methods: Mice were treated with DP (0.5–4 mg/kg, i. p.) 30 min prior to i. p. injection of SC or LP once daily for 7 days before assessing for memory function utilizing the Y-maze paradigm and levels of biomarkers of oxidative stress using standard biochemical procedures. Results: DP (0.5–2 mg/kg) significantly reversed the memory impairment produced by SC (1 mg/kg) or LP (250 µg/kg) in mice, indicating memory enhancing effect. The increased brain levels of malondialdehyde (MDA) evoked by SC (1 mg/kg) or LP (250 µg/kg), was significantly inhibited by DP (0.5–4 mg/kg), suggesting antioxidant property. Further, DP (0.5–4 mg/kg) significantly inhibited glutathione (GSH) depletion caused by SC (1 mg/kg) or LP (250 µg/kg) in mice brains, which suggest free radical scavenging property. Conclusion: These findings suggest that DP has antioxidant effect, which might be playing a significant role in its memory enhancing activity in mice. However, more detailed studies are necessary to confirm the relevance of this finding and its implications in clinical settings.
The role of the mutT gene of Escherichia coli in maintaining replication fidelity.

Spontaneous mutation levels are kept low in most organisms by a variety of error-reducing mechanisms, some of which ensure a high level of fidelity during DNA replication. The mutT gene of Escherichia coli is an important participant in avoiding such replication mistakes. An inactive mutT allele is a strong mutator with strict mutational specificity: only A.T-->C.G transversions are enhanced. The biological role of the MutT protein is thought to be the prevention of A.G mispairs during replication, specifically the mispair involving a template A and an oxidized form of guanine, 8-oxoguanine, which results when the oxidized form of dGTP, 8-oxodGTP, is available as a polymerase substrate. MutT is part of an elaborate defense system that protects against the mutagenic effects of oxidized guanine as a part of substrate dGTP and chromosomal DNA. The A.G mispairings prevented by MutT are not well-recognized and/or repaired by other fidelity mechanisms such as proofreading and mismatch repair, accounting in part for the high mutator activity of mutT. MutT is a nucleoside triphosphatase with a preference for the syn form of dGTP, hydrolyzing it to dGMP and pyrophosphate. 8-oxodGTP is hydrolyzed 10 times faster than dGTP, making it a likely biological substrate for MutT. MutT is assumed to hydrolyze 8-oxodGTP in the nucleotide pool before it can be misincorporated. While the broad role of MutT in error avoidance seems resolved, important details that are still unclear are pointed out in this review.