bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data
Authors: Fezzi Carlo , Fanghella Valeria 
Published: August 2020

AbstractIn response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses’ shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy. Unlike official statistics, which are published with a delay of a few months, our approach permits almost real-time monitoring of the economic impact of the containment policies and the financial stimuli introduced to address the crisis. We illustrate our methodology using daily data for the Italian day-ahead power market. We estimate that the 3 weeks of most severe lockdown reduced the corresponding Italian Gross Domestic Product (GDP) by roughly 30%. Such negative impacts are now progressively declining but, at the end of June 2020, GDP is still about 8.5% lower than it would have been without the outbreak.
Impacts of the COVID-19 Pandemic on the Global Agricultural Markets
Authors: Elleby Christian , Domínguez Ignacio Pérez , Adenauer Marcel , Genovese Giampiero 
Published: August 2020

AbstractThis paper analyses the impacts on global agricultural markets of the demand shock caused by the COVID-19 pandemic and the first wave of lockdown measures imposed by the governments in the first semester of 2020 to contain it. Specifically, we perform a scenario-based analysis on the IMF economic growth forecasts for 2020 and 2021 using a global multi-commodity agricultural market model. According to our results, the sharp decline in economic growth causes a decrease in international meat prices by 7–18% in 2020 and dairy products by 4–7% compared to a business as usual situation. Following the slowdown of the economy, biofuel prices fall strongly in 2020, followed by their main feedstocks, maize and oilseeds. Although the income losses and local supply chain disruptions associated with the pandemic undoubtedly has led to an increase in food insecurity in many developing countries, global food consumption is largely unaffected due to the inelastic demand of most agricultural commodities and the short duration of the shock. From an environmental viewpoint, the COVID-19 impacts point to a modest reduction of direct greenhouse gases from agriculture of about 1% or 50 million tonnes of carbon dioxide equivalents in 2020 and 2021.
COVID-19, Systemic Crisis, and Possible Implications for the Wild Meat Trade in Sub-Saharan Africa
Authors: McNamara James , Robinson Elizabeth J. Z. , Abernethy Katharine , Midoko Iponga Donald , Sackey Hannah N. K. , Wright Juliet H. , Milner-Gulland EJ 
Published: August 2020

AbstractWild animals play an integral and complex role in the economies and ecologies of many countries across the globe, including those of West and Central Africa, the focus of this policy perspective. The trade in wild meat, and its role in diets, have been brought into focus as a consequence of discussions over the origins of COVID-19. As a result, there have been calls for the closure of China’s “wet markets”; greater scrutiny of the wildlife trade in general; and a spotlight has been placed on the potential risks posed by growing human populations and shrinking natural habitats for animal to human transmission of zoonotic diseases. However, to date there has been little attention given to what the consequences of the COVID-19 economic shock may be for the wildlife trade; the people who rely on it for their livelihoods; and the wildlife that is exploited. In this policy perspective, we argue that the links between the COVID-19 pandemic, rural livelihoods and wildlife are likely to be more complex, more nuanced, and more far-reaching, than is represented in the literature to date. We develop a causal model that tracks the likely implications for the wild meat trade of the systemic crisis triggered by COVID-19. We focus on the resulting economic shockwave, as manifested in the collapse in global demand for commodities such as oil, and international tourism services, and what this may mean for local African economies and livelihoods. We trace the shockwave through to the consequences for the use of, and demand for, wild meats as households respond to these changes. We suggest that understanding and predicting the complex dynamics of wild meat use requires increased collaboration between environmental and resource economics and the ecological and conservation sciences.
General Relativity, Mental Causation, and Energy Conservation
Authors: Pitts J. Brian 
Published: August 2020

AbstractThe conservation of energy and momentum have been viewed as undermining Cartesian mental causation since the 1690s. Modern discussions of the topic tend to use mid-nineteenth century physics, neglecting both locality and Noether’s theorem and its converse. The relevance of General Relativity (GR) has rarely been considered. But a few authors have proposed that the non-localizability of gravitational energy and consequent lack of physically meaningful local conservation laws answers the conservation objection to mental causation: conservation already fails in GR, so there is nothing for minds to violate. This paper is motivated by two ideas. First, one might take seriously the fact that GR formally has an infinity of rigid symmetries of the action and hence, by Noether’s first theorem, an infinity of conserved energies-momenta (thus answering Schrödinger’s 1918 false-negative objection). Second, Sean Carroll has asked (rhetorically) how one should modify the Dirac–Maxwell–Einstein equations to describe mental causation. This paper uses the generalized Bianchi identities to show that General Relativity tends to exclude, not facilitate, such Cartesian mental causation. In the simplest case, Cartesian mental influence must be spatio-temporally constant, and hence 0. The difficulty may diminish for more complicated models. Its persuasiveness is also affected by larger world-view considerations. The new general relativistic objection provides some support for realism about gravitational energy-momentum in GR (taking pseudotensor laws seriously). Such realism also might help to answer an objection to theories of causation involving conserved quantities, because energies-momenta would be conserved even in GR.
Beyond ‘Safeguarding’ and ‘Empowerment’ in Hong Kong: Towards a Relational Model for Supporting Women Who Have Left their Abusive Partners
Authors: Kong Sui-Ting 
Published: August 2020

AbstractThis project explores the post-separation needs of Chinese women in Hong Kong who have left their abusive partners and how they might be addressed The project aims to provide insights for improving the local domestic violence service, whose main focus is on crisis intervention. Cooperative Grounded Inquiry (CGI) was developed as a novel participatory action research methodology (PAR) for fostering collaboration between social work practitioner-researchers and women service users. Its purpose is to generate useful knowledge and provide support for abused women and their children. The project involved 7 Hong Kong Chinese women as participant-researchers. The inquiry group met at least once a week for 6 months to explore the post-separation needs of the women and their children, and to implement and evaluate the practices/services developed through this project together in a participatory manner. Women participants identified the problems of doing either ‘victim’ or ‘survivor’ that respectively underpin the ‘safeguarding’ and the ‘empowerment’ models; and they developed practices for ‘doing being oneself’ beyond the victim-survivor dichotomy. This paper presents the changing self-narratives of women participants over the research project, from victimhood to survivorhood and from survivorhood to survivor-becoming. These narratives demonstrate the importance of safeguarding women’s space for undertaking symbolic action and of empowering them through using volcabulary that can help them describe themselves/their experiences differently from mainstream discourses. Women’s narratives highlight the existing ‘planetary difference’ between the safeguarding model, which treats women as helpless and vulnerable and in need of external support, and the empowerment model which treats them as powerful, resilient and with resources and solutions to problems. The study transcends the victim-survivor dichotomy and service models by proposing an alternative relational model that emphasises power sharing in making sense of abusive experiences and finding one’s own voice in a supportive community.
Addressing storage time restrictions in the S-graph scheduling framework
Authors: Hegyháti Máté , Holczinger Tibor , Ősz Olivér 
Published: August 2020

AbstractStorage planning and utilization are among the most important considerations of practical batch process scheduling. Modeling the available storage options appropriately can be crucial in order to find practically applicable solutions with the best objective value. In general, there are two main limitations on storage: capacity and time. This paper focuses on the latter and investigates different techniques to tackle limited storage time within the S-graph framework. The S-graph framework is a collection of combinatorial algorithms and a directed graph based model that has been introduced three decades ago and has been under development ever since. In this work, several options for addressing storage time limitations within the framework were implemented and tested for efficiency. The empirical results over a huge number of tests have unequivocally favored one of the approaches, which will be applied in later developments.
The impact of entrepreneurship on economic, social and environmental welfare and its determinants: a systematic review
Authors: Neumann Thomas 
Published: August 2020

AbstractThis paper presents a systematic review of (a) the impact of entrepreneurship on economic, social and environmental welfare and (b) the factors determining this impact. Research over the past 25 years shows that entrepreneurship is one cause of macroeconomic development, but that the relationship between entrepreneurship and welfare is very complex. The literature emphasizes that the generally positive impact of entrepreneurship depends on a variety of associated determinants which affect the degree of this impact. This paper seeks to contribute to the literature in three ways. First, it updates and extends existing literature reviews with the recently emerged research stream on developing countries, and incorporates studies analysing not only the impact of entrepreneurship on economic growth and welfare but also on social and environmental welfare. Second, it identifies and structures the current knowledge on the determinants of this impact. And third, it provides a roadmap for future research which targets the shortcomings of the existing empirical literature on this topic. The review of 102 publications reveals that the literature generally lacks research which (a) goes beyond the common measures of economic welfare, (b) examines the long-term impact of entrepreneurship and (c) focuses on emerging and developing countries. Regarding the determinants of the impact of entrepreneurship, the results highlight the need for empirical research which addresses both already investigated determinants which require more attention (e.g. survival, internationalisation, qualifications) and those which are currently only suspected of shaping the impact of entrepreneurship (e.g. firm performance, the entrepreneur’s socio-cultural background and motivations).
Pseudo-total antimony content in topsoils of the Berlin Metropolitan Area
Authors: Thestorf Kolja , Makki Mohsen 
Published: August 2020

Abstract
Purpose
Sb is a metalloid that naturally occurs in traces in the Northern German Lowland Area, only. Its frequent and still growing demand for industrial purposes and its release during coal combustion and by vehicular emissions lead to an enrichment of Sb in topsoils. Numerous analyses on heavy metals have been conducted in the urban environment so far, but although Sb can be ecologically harmful and potentially carcinogenic, only few studies on Sb in soils were carried out.

Materials and methods
Due to the formation of anthropogenic soils by men, especially in the course of industrialization and after World War II, more than 50% of the Berlin soils consist of anthropogenic material like redeposited natural material, debris, waste, or ashes. This composition of soils of the Berlin Metropolitan Area can function as a model for other metropolitan regions of Central Europe. In the urban and peri-urban area of Berlin, analysis of more than 900 topsoil samples has been performed measuring the content of 12 heavy metals and metalloids (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, and Zn). As a reference for the natural environment, soil profiles of typical parent rock material have been investigated taking also the regional (0.3 mg/kg), the local background value (0.61 mg/kg), and the baseline value (0.07 mg/kg) for Sb into account.

Results
By doing so, we could show the spatial distributional pattern of Sb in the Berlin Metropolitan Area and statistically evaluate our results in dependency of land-use, parent material, and soil parameters such as organic carbon content and pH. Thereby, we could prove an average enrichment two to six times over the regional background value. Median Sb content is very low in forest topsoils (0.54 mg/kg) and reaches its maximum in roadside soils (1.75 mg/kg). Technogenic materials, vehicular emissions, industrial processes, and (former) land-use are the predominant factors for Sb enrichment and distribution in the study area. Some single samples show an enrichment of up to 600% of the regional background value for topsoils.

Conclusion
Our study revealed that the Sb content in the Berlin Metropolitan Area is elevated compared to natural environments. Furthermore, we could demonstrate that Sb is a previously neglected key pollutant, specific to metropolitan areas. Due to the high environmental relevance, further Sb data from selected investigated spaces in other metropolises and specific land-use types are needed to assess the potential environmental risk of Sb in metropolitan areas.
Effect of the Process Gas and Scan Speed on the Properties and Productivity of Thin 316L Structures Produced by Laser-Powder Bed Fusion
Authors: Pauzon C. , Leicht A. , Klement U. , Forêt P. , Hryha E. 
Published: August 2020

Abstract
The development of the laser powder bed fusion (L-PBF) process to increase its robustness and productivity is challenged by ambitious design optimizations, such as thin wall structures. In this study, in addition to the effect of commonly used gases as Ar and N2, increased laser scanning speed and new process gases, such as helium, were successfully implemented. This implementation allowed to build 316L stainless steel components with thin walls of 1 mm thickness with an enhanced build rate of 37 pct. The sample size effect and the surface roughness were held responsible for the reduction in strength (YS > 430 MPa) and elongation (E
AB > 30 pct) for the 1 mm samples studied. Similar strength was achieved for all process gases. The increased scanning speed was accompanied by a more random texture, smaller cell size, and grain size factor along the building direction when compared to the material built with the standard laser parameters. Stronger preferential orientation 〈101〉 along the building direction was observed for material built with standard parameters. Finally, the use of helium as a process gas was successful and resulted in reduced cell size. This finding is promising for the future development of high strength 316L stainless steel built with high build rates.
DeepMapi: a Fully Automatic Registration Method for Mesoscopic Optical Brain Images Using Convolutional Neural Networks
Authors: Ni Hong , Feng Zhao , Guan Yue , Jia Xueyan , Chen Wu , Jiang Tao , Zhong Qiuyuan , Yuan Jing , Ren Miao , Li Xiangning , Gong Hui , Luo Qingming , Li Anan 
Published: August 2020

AbstractThe extreme complexity of mammalian brains requires a comprehensive deconstruction of neuroanatomical structures. Scientists normally use a brain stereotactic atlas to determine the locations of neurons and neuronal circuits. However, different brain images are normally not naturally aligned even when they are imaged with the same setup, let alone under the differing resolutions and dataset sizes used in mesoscopic imaging. As a result, it is difficult to achieve high-throughput automatic registration without manual intervention. Here, we propose a deep learning-based registration method called DeepMapi to predict a deformation field used to register mesoscopic optical images to an atlas. We use a self-feedback strategy to address the problem of imbalanced training sets (sampling at a fixed step size in nonuniform brains of structures and deformations) and use a dual-hierarchical network to capture the large and small deformations. By comparing DeepMapi with other registration methods, we demonstrate its superiority over a set of ground truth images, including both optical and MRI images. DeepMapi achieves fully automatic registration of mesoscopic micro-optical images, even macroscopic MRI datasets, in minutes, with an accuracy comparable to those of manual annotations by anatomists.
Dimensionality of narcissism: a Bifactorial model of the Narcissistic Personality Inventory using single-stimulus response formats
Authors: Engyel Márton , Urbán Róbert , Bandi Szabolcs , Nagy László 
Published: August 2020

AbstractThe Narcissistic Personality Inventory is a widely used measure of narcissism; however, several different conflicting factor structures have been proposed. The present study aimed to untangle those differences by offering a bifactor model of narcissism with an underlying general narcissism factor and several specific factors. Our objective was to estimate the variance explained by the general and the specific factors. Therefore, we applied a set of confirmatory factor analyses on three independent studies (N = 791; N = 319 and N = 237), and also tested the construct validity of these factors with other contemporary measures of grandiose and vulnerable narcissism, big five personality traits, explicit self-esteem, gender and well-being. Our results suggest that the bifactor model with three specific factors yielded acceptable fit to our data in all of the different single-stimulus response formats and languages used in our studies and modelling three specific factors offered more insight into the adaptive and maladaptive characteristics of narcissism. The general narcissism factor alone explains only about half of the common variance, highlighting the importance of the specific factors as well.
Building moisture diagnosis: Processing, assessing and representation of environmental data for root cause analysis of mould growth
Authors: Lopez-Arce Paula , Altamirano-Medina Hector , Berry James , Rovas Dimitrios , Sarce Fernando , Hodgson Steve 
Published: August 2020

AbstractThe occurrence of surface condensation and mould can lead to concerns of poor indoor air quality and adverse health implications of occupants. Remedial actions require identification of the root causes, but this can be challenging even for experts. The focus of the research is the development of a diagnostic tool that helps to streamline root cause analysis. The diagnostic method comprises a protocol with guidelines for installation of sensors, easy data collection, and a set of calculations to process environmental information. Environmental parameters collected and calculated from an environmental monitoring exercise of dwellings with and without mould, include physical properties associated with the indoor surface of external walls and surrounding air conditions. The methodology relies on linking specific surface and air environmental parameters together with critical thresholds proposed for the control and avoidance of surface condensation and mould growth in dwellings. These parameters were assessed and used to determine the likely causal factors of a moisture imbalanced environment leading to surface condensation and mould growth; poor thermal building envelope performance, an imbalanced heat-moisture regime, and/or insufficient ventilation. Examples from different scenarios are presented to show the process towards environmental data collection, post-processing to compute and assess pertinent parameters, and the display of environmental conditions in a clear and easy-to-interpret manner. The novel developed system is a time-saving method for processing and represents environmental data. It provides a straightforward building moisture index (BMI) and a systematic diagnostic procedure for environmental assessment and possible causes of mould growth. This helps to support neutral decision making, to identify rectification strategies and direct to more cost-efficient solutions to existing damp and mould problems in buildings.
A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment
Authors: Afflerbach Patrick , van Dun Christopher , Gimpel Henner , Parak Dominik , Seyfried Johannes 
Published: August 2020

AbstractResearch has shown that aggregation of independent expert judgments significantly improves the quality of forecasts as compared to individual expert forecasts. This “wisdom of crowds” (WOC) has sparked substantial interest. However, previous studies on strengths and weaknesses of aggregation algorithms have been restricted by limited empirical data and analytical complexity. Based on a comprehensive analysis of existing knowledge on WOC and aggregation algorithms, this paper describes the design and implementation of a static stochastic simulation model to emulate WOC scenarios with a wide range of parameters. The model has been thoroughly evaluated: the assumptions are validated against propositions derived from literature, and the model has a computational representation. The applicability of the model is demonstrated by investigating aggregation algorithm behavior on a detailed level, by assessing aggregation algorithm performance, and by exploring previously undiscovered suppositions on WOC. The simulation model helps expand the understanding of WOC, where previous research was restricted. Additionally, it gives directions for developing aggregation algorithms and contributes to a general understanding of the WOC phenomenon.
Surface characterization of steel/steel contact lubricated by PAO6 with novel black phosphorus nanocomposites
Authors: Luo Zhiheng , Yu Jingyuan , Xu Yufu , Xi He , Cheng Gang , Yao Lulu , Song Ruhong , Dearn Karl D. 
Published: August 2020

AbstractIn the present work, two types of novel nano additives, titanium sulfonate ligand/black phosphorus (TiL4/BP) and titanium dioxide/black phosphorus (TiO2/BP) nanocomposites, were prepared. The tribological behavior of the steel/steel friction pairs lubricated by polyalphaolefins type 6 (PAO6) containing the nanocomposites under boundary lubrication was studied. The worn surfaces were analyzed using modern surface techniques. The experimental results show that the rubbed surfaces became smooth and showed little wear with the addition of the nanocomposites. TiO2/BP nanocomposites can significantly improve the lubricity of BP nanosheets under high contact stress. The synergistic roles of the load-bearing abilities and rolling effect of TiO2 nanoparticles, the slip induced by the BP with its layered structure, and the establishment of a tribofilm on the sliding interface are the basis of the tribological mechanisms.