bluuebunny/crossref_metadata_2025_split huggingface dataset:
ESG Disclosure and Idiosyncratic Risk in Initial Public Offerings
Authors: Reber Beat , Gold Agnes , Gold Stefan 
Published: June 2021

AbstractAlthough legitimacy theory provides strong arguments that environmental, social and governance (ESG) disclosure and performance can help mitigate firm-specific (idiosyncratic) risks, this relationship has been repeatedly challenged by conceptual arguments, such as ‘transparency fallacy’ or ‘impression management’, and mixed empirical evidence. Therefore, we investigate this relationship in the revelatory case of initial public offerings (IPOs), which represent the first sale of common stock to the wider public. IPOs are characterised by strong information asymmetry between firm insiders and society, while at the same time suffering from uncertainty in firm legitimacy, culminating in amplified financial risks for both issuers and investors in aftermarket trading. Using data from the United States, we demonstrate that (1) voluntary ESG disclosure reduces idiosyncratic volatility and downside tail risk and (2) higher ESG ratings have lower associated firm-specific volatility and downside tail risk during the first year of trading in the aftermarket. We provide theoretical arguments for the relationships observed, suggesting that companies striving for ESG performance and communicating their efforts signal their compliance with sustainability-related norms, thus acquiring and upholding a societal license to operate. ESG performance and disclosure help companies build their reputation capital with investors after going public. We also report that ESG disclosure is a more consistent proxy for ex-ante uncertainty as an indicator of aftermarket risk, thereby replacing some of the more conventional measures, such as firm age, offered in the existing literature.
Regenerative medicine: characterization of human bone matrix gelatin (BMG) and folded platelet-rich fibrin (F-PRF) membranes alone and in combination (sticky bone)
Authors: Csönge Lajos , Bozsik Ágnes , Tóth-Bagi Zoltán , Gyuris Róbert , Kónya János 
Published: June 2021

AbstractDuring the last two decades autologous platelet and leukocyte rich products (PRP; PRF), opened new perspectives in regenerative medicine. In particular regenerative dentistry played a pioneer role in the application of these products in bone regenerative cases. Many aspects of cytokines, such as, growth factor release, blood cell content and its characterization were reported, but some practical questions are still unanswered in the preparation of PRF membranes and sticky bones. A new folding technique was introduced that created a good quality, pliable, and strong F-PRF membrane with a dense fibrin network and more homogenous blood cell distribution. F-PRF produced a very promising sticky bone combined with human freeze-dried cortical bone matrix gelatin (BMG). There hasn’t been much focus on the quality and character of the applied bone and the optimal membrane/bone particle ratio has not been reported. A 0.125 g BMG/ml plasma (1 g/8 ml) seems like the ideal combination with maximal BMG adhesion capacity of the membrane. Particle distribution of BMG showed that 3/4 of the particles ranged between 300–1000 µ, the remnant 1/4 was smaller than 300 µ. The whole F-PRF membrane and its parts were compared with conventional A-PRF membrane concerning their resistance against proteolytic digestion. The F-PRF was superior to A-PRF, which dissolved within 4–5 days, while F-PRF was destroyed only after 11 days, so this provides a better chance for local bone morphogenesis. The F-PRF pieces had similar resistance to the whole intact one, so they can be ideal for surgical procedures without risk of fast disintegration.
Youth Psychopathology in Daily Life: Systematically Reviewed Characteristics and Potentials of Ecological Momentary Assessment Applications
Authors: Thunnissen Marjolein R. , aan het Rot Marije , van den Hoofdakker Barbara J. , Nauta Maaike H. 
Published: June 2021

AbstractTraditionally, symptoms of youth psychopathology are assessed with questionnaires, clinical interviews, or laboratory observations. Ecological Momentary Assessment (EMA) could be a particularly valuable additional methodology, since EMA enables examining the daily lives of youths near real-time, considering fluctuations and specific contexts of symptoms. This systematic review aimed to review the characteristics of current EMA applications and to provide a synthesis of their potential in studying youth psychopathology. Following a systematic search in PsycInfo and Medline, we identified 50 studies in clinical samples. Most studies used EMA to examine fluctuations in symptoms, affect, and behavior, and the relation with contextual factors. EMA was also used to investigate interactions between parents and their children over time, and to monitor and predict treatment response. EMA appeared feasible in youth and could provide valuable insights that contribute to understanding youth psychopathology. Benefits, gaps, and suggestions for future research and clinical practice are discussed.
Security analysis of Subterranean 2.0
Authors: Song Ling , Tu Yi , Shi Danping , Hu Lei 
Published: June 2021

AbstractSubterranean 2.0 is a cipher suite that can be used for hashing, authenticated encryption, MAC computation, etc. It was designed by Daemen, Massolino, Mehrdad, and Rotella, and has been selected as a candidate in the second round of NIST’s lightweight cryptography standardization process. Subterranean 2.0 is a duplex-based construction and utilizes a single-round permutation in the duplex. It is the simplicity of the round function that makes it an attractive target of cryptanalysis. In this paper, we examine the single-round permutation in various phases of Subterranean 2.0 and specify three related attack scenarios that deserve further investigation: keystream biases in the keyed squeezing phase, state collisions in the keyed absorbing phase, and one-round differential analysis in the nonce-misuse setting. To facilitate cryptanalysis in the first two scenarios, we novelly propose a set of size-reduced toy versions of Subterranean 2.0: Subterranean-m. Then we make an observation for the first time on the resemblance between the non-linear layer in the round function of Subterranean 2.0 and SIMON’s round function. Inspired by the existing work on SIMON, we propose explicit formulas for computing the exact correlation of linear trails of Subterranean 2.0 and other ciphers utilizing similar non-linear operations. We then construct our models for searching trails to be used in the keystream bias evaluation and state collision attacks. Our results show that most instances of Subterranean-m are secure in the first two attack scenarios but there exist instances that are not. Further, we find a flaw in the designers’ reasoning of Subterranean 2.0’s linear bias but support the designers’ claim that there is no linear bias measurable from at most $$2^{96}$$

2
96

data blocks. Due to the time-consuming search, the security of Subterranean 2.0 against the state collision attack in keyed modes still remains an open question. Finally, we observe that one-round differentials allow to recover state bits in the nonce-misuse setting. By proposing nested one-round differentials, we obtain a sufficient number of state bits, leading to a practical state recovery with only 20 repetitions of the nonce and 88 blocks of data. It is noted that our work does not threaten the security of Subterranean 2.0.
A New Definition of “Artificial” for Two Artificial Sciences
Authors: Bianchini Francesco 
Published: June 2021

AbstractIn this article, I deal with a conceptual issue concerning the framework of two special sciences: artificial intelligence and synthetic biology, i.e. the distinction between the natural and the artificial (a long-lasting topic of history of scientific though since the ancient philosophy). My claim is that the standard definition of the “artificial” is no longer useful to describe some present-day artificial sciences, as the boundary between the natural and the artificial is not so sharp and clear-cut as it was in the past. Artificial intelligence and synthetic biology, two disciplines with new technologies, new experimental methods, and new theoretical frameworks, all need a new, more specific, and refined definition of (the) “artificial”, which is also related to the use of the synthetic method to build real world entities and in open-ended (real or virtual) environments. The necessity of a new definition of the artificial is due to the close relationship of AI and synthetic biology with biology itself. They both are engineering sciences that are moving closer and closer, at least apparently, towards (natural) biology, although from different and opposite directions. I show how the new concept of the artificial is, therefore, the result of a new view on biology from an engineering and synthetic point of view, where the boundary between the natural and the artificial is far more blurred. From this, I try to formulate a brand-new, more useful definition for future understanding, practical, and epistemological purposes of these two artificial sciences.
The impact of COVID-19 on households´ income in the EU
Authors: Almeida Vanda , Barrios Salvador , Christl Michael , De Poli Silvia , Tumino Alberto , van der Wielen Wouter 
Published: June 2021

AbstractThis analysis makes use of economic forecasts for 2020 issued by the European Commission in Autumn 2019 and Spring 2020, and of a counterfactual under a no-policy change assumption, to analyse the impact of the COVID-19 crisis on EU households´ income. Additionally, our analysis assesses the cushioning effect of discretionary fiscal policy measures taken by the EU Member States. We find that the COVID-19 pandemic is likely to affect significantly households’ disposable income in the EU, with lower income households being more severely hit. However, our results show that due to policy intervention, the impact of the crisis is expected to be similar to the one experienced during the 2008–2009 financial crisis. In detail, our results indicate that discretionary fiscal policy measures will play a significant cushioning role, reducing the size of the income loss (from −9.3% to −4.3% for the average equivalised disposable income), its regressivity and mitigating the poverty impact of the pandemic. We conclude that policy interventions are therefore instrumental in cushioning against the impact of the crisis on inequality and poverty.
Relationships Between Exposure to Different Gambling Advertising Types, Advertising Impact and Problem Gambling
Authors: Syvertsen André , Erevik Eilin K. , Hanss Daniel , Mentzoni Rune A. , Pallesen Ståle 
Published: June 2021

AbstractPeople with gambling problems report more exposure and impact from gambling advertising, although less is known regarding the role of specific advertising types. Data on gamblers (n = 5830, 48.5% women, mean age = 44.27) was collected from a general population cross-sectional survey in Norway (32.7% response rate). We examined if problem gambling was associated with perceived advertising impact (on gambling involvement, awareness, and knowledge) or exposure (via internet, TV, retail outlet, newspaper, and direct advertising). We also investigated if advertising exposure was associated with advertising impact. ANOVAs revealed that problem gambling was associated with increased perceived advertising impact on gambling involvement (ω2 = 0.09, p < .001) and awareness of gambling (ω2 = 0.04, p < .001). Reported exposure to direct advertising increased linearly with problem gambling level (ω2 = 0.04, p < .001), whereas we found small/no differences in exposure to other types of advertising. Multiple regressions revealed that among advertising types, internet advertising was the strongest predictor of perceived advertising impact on gambling involvement (β = 0.1, p < .001). TV advertising was the strongest predictor of advertising impact on knowledge of gambling forms and operators (β = 0.28, p < .001) and awareness of gambling (β = .05, p < .05). Future studies should elucidate how different subtypes of internet advertising impact gambling involvement. Clinicians should assess clients’ experiences with direct advertising and devise interventions for coping. Researchers should be aware that internet and direct advertising allow for more tailored content compared to other advertising types.
A Federated Learning Approach to Frequent Itemset Mining in Cyber-Physical Systems
Authors: Ahmed Usman , Srivastava Gautam , Lin Jerry Chun-Wei 
Published: June 2021

AbstractEffective vector representation has been proven useful for transaction classification and clustering tasks in Cyber-Physical Systems. Traditional methods use heuristic-based approaches and different pruning strategies to discover the required patterns efficiently. With the extensive and high dimensional availability of transactional data in cyber-physical systems, traditional methods that used frequent itemsets (FIs) as features suffer from dimensionality, sparsity, and privacy issues. In this paper, we first propose a federated learning-based embedding model for the transaction classification task. The model takes transaction data as a set of frequent item-sets. Afterward, the model can learn low dimensional continuous vectors by preserving the frequent item-sets contextual relationship. We perform an in-depth experimental analysis on the number of high dimensional transactional data to verify the developed models with attention-based mechanism and federated learning. From the results, it can be seen that the designed model can help and improve the decision boundary by reducing the global loss function while maintaining both security and privacy.
A Shape Optimization Problem on Planar Sets with Prescribed Topology
Authors: Briani Luca , Buttazzo Giuseppe , Prinari Francesca 
Published: June 2021

AbstractWe consider shape optimization problems involving functionals depending on perimeter, torsional rigidity and Lebesgue measure. The scaling free cost functionals are of the form$$P(\Omega )T^q(\Omega )|\Omega |^{-2q-1/2}$$P(Ω)Tq(Ω)|Ω|-2q-1/2, and the class of admissible domains consists of two-dimensional open sets$$\Omega $$Ωsatisfying the topological constraints of having a prescribed numberkof bounded connected components of the complementary set. A relaxed procedure is needed to have a well-posed problem, and we show that when$$q<1/2$$q<1/2an optimal relaxed domain exists. When$$q>1/2$$q>1/2, the problem is ill-posed, and for$$q=1/2$$q=1/2, the explicit value of the infimum is provided in the cases$$k=0$$k=0and$$k=1$$k=1.
Adaptive Euler methods for stochastic systems with non-globally Lipschitz coefficients
Authors: Kelly Cónall , Lord Gabriel J. 
Published: June 2021

AbstractWe present strongly convergent explicit and semi-implicit adaptive numerical schemes for systems of semi-linear stochastic differential equations (SDEs) where both the drift and diffusion are not globally Lipschitz continuous. Numerical instability may arise either from the stiffness of the linear operator or from the perturbation of the nonlinear drift under discretization, or both. Typical applications arise from the space discretization of an SPDE, stochastic volatility models in finance, or certain ecological models. Under conditions that include montonicity, we prove that a timestepping strategy which adapts the stepsize based on the drift alone is sufficient to control growth and to obtain strong convergence with polynomial order. The order of strong convergence of our scheme is (1 − ε)/2, for ε ∈ (0,1), where ε becomes arbitrarily small as the number of finite moments available for solutions of the SDE increases. Numerically, we compare the adaptive semi-implicit method to a fully drift-implicit method and to three other explicit methods. Our numerical results show that overall the adaptive semi-implicit method is robust, efficient, and well suited as a general purpose solver.
A spatially explicit optimization model for the selection of sustainable transport technologies at regional bus companies
Authors: Chinese Damiana , Pinamonti Piero , Mauro Caterina 
Published: June 2021

AbstractBuses account for almost 60% of the total public transport services in Europe, and most of the vehicles are diesel fuelled. Regional transport administrators, under pressure by governments to introduce zero-emission buses, require analytical tools for identifying optimal solutions. In literature, few models combine location analysis, least cost planning, and emission assessment, taking into account multiple technologies which might achieve emission reduction goals. In this paper, an existing optimal location model for electric urban transport is adapted to match the needs of regional transport. The model, which aims to evaluate well-to-wheel carbon emissions as well as airborne emissions of NOx and PM10, is applied to a real case study of a regional bus transport service in North Eastern Italy. The optimization has identified electric buses with relatively small (60 kWh) batteries as the best compromise for reducing carbon equivalent emissions; however, under current economic conditions in Italy, the life cycle cost of such vehicles is still much higher than those of Euro VI diesel buses. In this context, our model helps in identifying ways to minimize infrastructure costs and to efficiently allocate expensive resources such as electric buses to the routes where the maximum environmental benefit can be achieved.
Entrepreneurial learning in online communities
Authors: Schou Peter Kalum , Bucher Eliane , Waldkirch Matthias 
Published: June 2021

Abstract
New digital technologies possess the potential to transform entrepreneurial processes, such as how entrepreneurs pursue opportunities and access funding and how they learn. How entrepreneurs learn may be transformed as digital technologies provide new spaces for learning, such as online communities. Online communities can gather thousands of participants and provide entrepreneurs with new opportunities for learning that are not limited by time, space, or social class. Yet, we know little about how entrepreneurs take advantage of the new digital opportunities of learning. To remedy this, we studied a large online community of entrepreneurs on Reddit (r/startups), where we qualitatively analyzed the top-voted 100 threads from 2018 to 2019 (10,277 comments in total). By drawing on coactive vicarious learning, a theory that describes how learning is socially constructed through discursive interactions, we outline how entrepreneurial learning is socially constructed through conversations, which are taking place in different micro-learning contexts. Through identifying distinct entrepreneurial learning conversations, we build new theory on entrepreneurial learning in online communities. Our theorizing contributes to (1) the growing research on how entrepreneurial learning is socially constructed in communities, (2) the current debate on knowledge creation in online communities, and (3) the knowledge on how coactive vicarious learning unfolds in communities.

Plain English Summary

When entrepreneurs go online to learn, new research shows how online communities provide entrepreneurs with diverse learning spaces for developing ideas, learning new skills, and coping with the uncertainties of being an entrepreneur. Entrepreneurs increasingly use social media for doing business, but can they also use it to learn about doing business? In this article, we investigate this question by studying an online community of entrepreneurs on Reddit called r/startups, in which entrepreneurs exchange experiences and help each other with questions and issues. We show that entrepreneurial learning is taking place in five forms of learning conversations, which are situated in four learning contexts that differ from each other, from a classroom with a student–teacher dynamic, a collab space where entrepreneurs collect ideas and develop new skills and knowledge, a club context in which they challenge each other, and a care context in which they can bring their fears and uncertainties. Our findings show how entrepreneurship practitioners can make use of online communities, encouraging teaching and policy to pay more attention to how entrepreneurs work digitally.
Astronomers of the inward: on the histories and case histories of Alexander Luria and Oliver Sacks
Authors: Proctor Hannah 
Published: June 2021

AbstractThis essay discusses the brief but extensive correspondence Soviet neuro-psychologist Alexander Luria exchanged with his younger American colleague Oliver Sacks between 1973 and 1977, the year Luria died. Sacks, whose case histories went on to become mainstream bestsellers, always expressed his indebtedness to Luria, whose warm and detailed approach to writing about his patients’ peculiar and sometimes distressing neurological conditions inspired Sacks. This essay explores this influence but also probes distinctions between the two scientists’ understandings of human consciousness tied to the very different social and political contexts in which they conducted their clinical research.
Learning teamwork through a computer game: for the sake of performance or collaborative learning?
Authors: Riivari Elina , Kivijärvi Marke , Lämsä Anna-Maija 
Published: June 2021

AbstractOur study examined using a computer-based learning game as a tool to facilitate teaching and learning teamwork skills. The game was applied to an undergraduate level human resource management course at a business school in Finland. We focused on students’ experiences and key learning outcomes of collaborative learning of teamwork skills through the game, and our analysis highlighted two key features of learning outcomes. First, the computer-based learning game promoted students’ self-reflection and evaluation of their individual team roles. Second, although the game taught students the importance of continuous information sharing in teamwork, their evaluation of team outcomes was performance driven; students predominantly took team efficiency as a sign of good teamwork. This case revealed the benefits and challenges of using computer-based learning games as a pedagogical tool. We identified what is required from lecturers and students for the game to be successful, and how team values other than performance could be learned through the game.
The role of MRI in cervical cancer > 2 cm (FIGO stage IB2-IIA1) conservatively treated with neoadjuvant chemotherapy followed by conization: a pilot study
Authors: Russo Luca , Gui Benedetta , Miccò Maura , Panico Camilla , De Vincenzo Rosa , Fanfani Francesco , Scambia Giovanni , Manfredi Riccardo 
Published: June 2021

Abstract
Introduction
MRI is very accurate in selecting young women with cervical cancer for fertility-sparing surgery (FSS), in particular radical hysterectomy (RH). In order to improve obstetrical outcomes, neoadjuvant chemotherapy (NACT) followed by cold knife conization (CKC) has been proposed as alternative technique.

Objective
To investigate the role of MRI in evaluation of response to treatment after neoadjuvant chemotherapy (NACT), followed by CKC, in patients with cervical cancer FIGO stage IB2-IIA1 with tumor size 2 – 4 cm, desiring to preserve their fertility.

Methods
13 young women (23–36 years old) with cervical cancer stage IB2-IIA1 desiring to preserve their fertility were included. Tumor diameter at baseline and after treatment was detected on 1.5 T MRI. Treatment response was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST 1.1) and then compared to histopathology result.

Results
MRI correctly assessed 11 out of 13 cases, according to RECIST 1.1, compared to histopathology. Among these 7 patients with partial response (PR), 2 cases of CR, 1 SD and 1 PD with persistence or enlargement of primary tumor.

Conclusion
Our pilot study supports the usefulness of MRI in assessment of treatment response after NACT, followed by CKC.

Trial registration number
ClinicalTrials.gov: NCT02323841