bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced trends in spectral greening and climate anomalies across Europe
Authors: Kempf Michael 
Published: January 2023

AbstractEurope witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend—most likely as a response to rising atmospheric CO2 concentrations and global warming. But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948–2021) to recent vegetation index data (Normalized Difference Vegetation Index (NDVI), 2001–2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events.
Vacuum polarization on three-dimensional anti-de Sitter space-time with Robin boundary conditions
Authors: Namasivayam Sivakumar , Winstanley Elizabeth 
Published: January 2023

AbstractWe study a quantum scalar field, with general mass and coupling to the scalar curvature, propagating on three-dimensional global anti-de Sitter space-time. We determine the vacuum and thermal expectation values of the square of the field, also known as the vacuum polarisation (VP). We consider values of the scalar field mass and coupling for which there is a choice of boundary conditions giving well-posed classical dynamics. We apply Dirichlet, Neumann and Robin (mixed) boundary conditions to the field at the space-time boundary. We find finite values of the VP when the parameter governing the Robin boundary conditions is below a certain critical value. For all couplings, the vacuum expectation values of the VP with either Neumann or Dirichlet boundary conditions are constant and respect the maximal symmetry of the background space-time. However, this is not the case for Robin boundary conditions, when both the vacuum and thermal expectation values depend on the space-time location. At the space-time boundary, we find that both the vacuum and thermal expectation values of the VP with Robin boundary conditions converge to the result when Neumann boundary conditions are applied, except in the case of Dirichlet boundary conditions.
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
Authors: Mökander Jakob , Sheth Margi , Watson David S. , Floridi Luciano 
Published: January 2023

AbstractOrganisations that design and deploy artificial intelligence (AI) systems increasingly commit themselves to high-level, ethical principles. However, there still exists a gap between principles and practices in AI ethics. One major obstacle organisations face when attempting to operationalise AI Ethics is the lack of a well-defined material scope. Put differently, the question to which systems and processes AI ethics principles ought to apply remains unanswered. Of course, there exists no universally accepted definition of AI, and different systems pose different ethical challenges. Nevertheless, pragmatic problem-solving demands that things should be sorted so that their grouping will promote successful actions for some specific end. In this article, we review and compare previous attempts to classify AI systems for the purpose of implementing AI governance in practice. We find that attempts to classify AI systems proposed in previous literature use one of three mental models: the Switch, i.e., a binary approach according to which systems either are or are not considered AI systems depending on their characteristics; the Ladder, i.e., a risk-based approach that classifies systems according to the ethical risks they pose; and the Matrix, i.e., a multi-dimensional classification of systems that take various aspects into account, such as context, input data, and decision-model. Each of these models for classifying AI systems comes with its own set of strengths and weaknesses. By conceptualising different ways of classifying AI systems into simple mental models, we hope to provide organisations that design, deploy, or regulate AI systems with the vocabulary needed to demarcate the material scope of their AI governance frameworks.
Optical quantum random number generators: a comparative study
Authors: Guillan-Lorenzo Omar , Troncoso-Costas Marcos , Alvarez-Outarelo David , Diaz-Otero Francisco Javier , Garcia-Escartin Juan Carlos 
Published: January 2023

AbstractQuantum random number generators give the opportunity to, in theory, obtain completely unpredictable numbers only perturbed by the noise in the measurement. The obtained data can be digitalized and processed so that it gives as a result a uniform sequence of binary random numbers without any relation with the classical noise in the system. In this work we analyze the performance of optical QRNGs with three different arrangements: a homodyne detector measuring vacuum fluctuations, a homodyne detector measuring amplified spontaneous emission from an EDFA and a spontaneous emission phase noise-based generator. The raw data from the experiments is processed using a Toeplitz extractor, giving as a result sequences of binary numbers capable of passing the NIST Statistical Test Suite.
Plural harm: plural problems
Authors: Carlson Erik , Johansson Jens , Risberg Olle 
Published: January 2023

AbstractThe counterfactual comparative account of harm faces problems in cases that involve overdetermination and preemption. An influential strategy for dealing with these problems, drawing on a suggestion made by Derek Parfit, is to appeal to plural harm—several events together harming someone. We argue that the most well-known version of this strategy, due to Neil Feit, as well as Magnus Jedenheim Edling’s more recent version, is fatally flawed. We also present some general reasons for doubting that the overdetermination and preemption problems for the counterfactual comparative account can be satisfactorily solved by appealing to plural harm.
After successful fundraising: how overfunding and category spanning affect the release and audience-perceived quality of crowdfunded products
Authors: Weber Clarissa E. , Steigenberger Norbert , Wilhelm Hendrik 
Published: January 2023

Abstract
Overfunding of crowdfunded product-development projects would seem to be a welcome outcome for entrepreneurs, yet initial theory and evidence suggest that overfunding can have both positive and negative consequences. To overcome these contradictory predictions, we develop theory linking research on slack resources, audience expectations, and product category spanning to hypothesize boundary conditions for whether and when overfunding has a positive or negative effect on the product-development outcomes of product release and audience-perceived product quality. Post-crowdfunding data on video-game development projects show that entrepreneurs with high-category-spanning products benefit substantially less from overfunding than entrepreneurs with low-category-spanning products. Our study provides novel insights into the relation between overfunding and product release as well as audience-perceived product quality. It also contributes to our emerging understanding of the role of categories in the context of crowdfunding. We discuss implications for theory and practice.
Higher education policies and interdisciplinarity in Germany
Authors: Leišytė Liudvika , Rose Anna-Lena , Sterk-Zeeman Nadine 
Published: January 2023

Abstract
Universities have increasingly been subjected to policy- and industry demands to produce multi- and interdisciplinary knowledge. This paper explores the extent to which different higher education policy instruments are used to promote interdisciplinarity in teaching and research at universities in the German higher education system comparing them across different federal states. Based on a manifest content analysis of higher education laws and performance agreements with universities in the 16 German states, we were able to distinguish between three types of states: Those a) with a general use of policy instruments aimed at all universities in a state, whereas considerable differences could be observed with regard to the degree of coercion (enabling versus prescriptive provisions) and scope (teaching or research), b) a directed use of policy instrument, targeting specific universities, and c) a hybrid use of policy instruments using both general and directed elements. This paper provides a novel mapping of the promotion of interdisciplinarity in German higher education policies through a variety of policy instruments and hereby contributes to the extant literature on interdisciplinarity in higher education.
Corruption as state -corporate crime: the example of the health sector in Greece
Authors: Stamouli Eirini , Gasparinatou Margarita , Kouroutzas Christos 
Published: January 2023

AbstractThe study analyses the relations and processes underpinning grand corruption in the health sector in Greece. Viewed from a systemic-structural perspective, corruption is examined as a phenomenon emerging from the interactions and interconnections between the organized structures of venture capital and the state apparatus. Applying an integrated theoretical model of state-corporate crime and drawing on extensive empirical qualitative research, this paper traces the processes of normalization and institutionalization of corruption within the context of social networks and organizations. It is argued that corruption is not a deviant response to a normal system but a normal response to a system fostering illicit practice in accordance with capitalist ethos, profiteering, and the distribution of economic resources. In this wide political economy context, existing power relations and structures within the health sector are being reproduced.
Influence of Extraction and Pretreatment Conditions on the Yield, Solubility, and Quality of Rice Bran Oil Extracted with CO2-Expanded Hexane
Authors: Mathias Mathayo Gervas , Okajima Idzumi , Ito Kaichi , Aoki Yusuke , Kong Chang Yi , Sako Takeshi 
Published: January 2023

Abstract
Efficient, low-cost methods are required to produce impurity-free bio-oils with minimal nutrient depletion. This study investigated the effect of extraction and pretreatment conditions on the quality of rice bran oil extracted with CO2-expanded hexane. The extraction conditions considered were temperature (20–30 °C), CO2 mole fraction (0.76–0.94), and pressure (4.2–7.0 MPa). The effectiveness of rice bran hot air drying at 80–100 °C for 0.5, 1, 3, and 5 h for lipase inactivation was also studied. The rice bran oil yield and the content of free fatty acids did not depend significantly on the extraction temperature or pressure. The oil solubility increased significantly (p < 0.05) with every 5 °C increment while decreasing significantly at pressures below 5.0 MPa. The optimum extraction conditions for phosphorus-free rice bran oil (phosphorus concentrations of 9.8, 9.1, and 6.2 ppm) were CO2 mole fraction of 0.82 at 5.1 MPa and 20 °C, CO2 mole fraction of 0.87 at 5.0 MPa and 25 °C, and CO2 mole fraction of 0.92 at 5.1 MPa and 30 °C, respectively. The most effective pretreatment conditions for rice bran before storage for 10 weeks were 100 °C for 1 h. In addition, the phosphorus concentration of rice bran oil extracted with CO2-expanded hexane at a CO2 mole fraction of 0.88, 5.1 MPa, and 25 °C was ≤ 7.00 ppm, regardless of the pretreatment conditions. Therefore, CO2-expanded hexane extraction can be potentially used to produce impurity-free rice bran oil from both treated and untreated rice bran without refining.
Relationship between early nutrition and deep gray matter and lateral ventricular volumes of preterm infants at term-equivalent age
Authors: Toppe Felicia , Rasche Tobias , Weiss Christel , Schock Alexandra , Felderhoff-Müser Ursula , Müller Hanna 
Published: January 2023

Abstract
Background
The survival of preterm infants has improved over the last decade, but impaired brain development leading to poor neurological outcomes is still a major comorbidity associated with prematurity. The aim of this study was to evaluate the effect of nutrition on neurodevelopment in preterm infants and identify markers for improved outcomes.

Methods
Totally 67 premature infants with a gestational age of 24–34 weeks and a birth weight of 450–2085 g were included. Clinical parameters and documented diet were collected from medical records. The nutritional analysis comprised the protein, fat, carbohydrate, and energy intake during different time spans. Brain development was assessed by determining deep gray matter (DGM; basal ganglia and thalamus) and lateral ventricular (LV) volumes as measured on cerebral magnetic resonance imaging scans obtained at term-equivalent age (TEA), and potential associations between nutrition and brain volumetrics were detected by regression analysis.

Results
We observed a negative correlation between mean daily protein intake in the third postnatal week and MRI-measured DGM volume at TEA (P = 0.007). In contrast, head circumference at a corrected age of 35 weeks gestation (P < 0.001) and mean daily fat intake in the fourth postnatal week (P = 0.004) were positively correlated with DGM volume. Moreover, mean daily carbohydrate intake in the first postnatal week (P = 0.010) and intraventricular hemorrhage (P = 0.003) were revealed as independent predictors of LV volume.

Conclusion
The study emphasizes the importance of nutrition for brain development following preterm birth.
On the potentials of quantum computing – An interview with Heike Riel from IBM Research
Authors: Alt Rainer 
Published: January 2023

AbstractIn this interview, Dr. Heike Riel, a leading scientist and Fellow at IBM Research, reports on the current state of research in the field of quantum computing. Building on the distinction of gateable quantum computers and quantum annealers, the interview sheds light on how research has evolved on gateable quantum computers, which are the path developed by IBM. These gateable quantum computers are described with their current status as well as the improvements and challenges regarding speed, scale, and quality. All three parameters are important for increasing the performance of these universal quantum computers and for leveraging their potentials compared to classical computers. In particular, complex mathematical problems being present in numerous applications in science and business may be solved. Among the examples mentioned are optimization problems that tend to scale exponentially with the number of parameters, for example, in material and natural sciences or simulation problems in the financial industry and in manufacturing. The interview concludes with a critical assessment of possible risks and expectations for the future.
Distances Between Immersed Graphs: Metric Properties
Authors: Buchin Maike , Chambers Erin , Fang Pan , Fasy Brittany Terese , Gasparovic Ellen , Munch Elizabeth , Wenk Carola 
Published: January 2023

AbstractGraphs in metric spaces appear in a wide range of data sets, and there is a large body of work focused on comparing, matching, or analyzing collections of graphs in different ambient spaces. In this survey, we provide an overview of a diverse collection of distance measures that can be defined on the set of finite graphs immersed (and in some cases, embedded) in a metric space. For each of the distance measures, we recall their definitions and investigate which of the properties of a metric they satisfy. Furthermore we compare the distance measures based on these properties and discuss their computational complexity.
The CTCN-LightGBM Joint Model for Industrial Balanced Loading Prediction
Authors: Chen Zihua , Wang Chuanli , Jin Huawei , Li Jingzhao , Zhang Shunxiang , Ouyang Qichun 
Published: January 2023

AbstractBalanced industrial loading mainly relies on accurate multi-adjustment values, including the truck speed and chute flow. However, the existing models are weak in real-time loading prediction because the single-objective regression may ignore the correlation of multi-adjustment parameters. To solve the problem, we propose a joint model that fuses the composited-residual-block temporal convolutional network and the light gradient boosting machine (i.e., called CTCN-LightGBM). First, the instance selection deviations and abnormal supplement methods are used for data preprocessing and normalization. Second, we propose a side-road dimensionality reduction convolutional branch in the composited-residual-block temporal convolutional network to extract collaborative features effectively. Third, the feature re-enlargement method reconstructs extracted features with the original features to improve extraction accuracy. Fourth, the reconstructed feature matrix is utilized as the input of the light gradient boosting machine to predict multi-adjustment values parallelly. Finally, we compare the CTCN-LightGBM with other related models, and the experimental results show that our model can obtain superior effects for multi-adjustment value prediction.
Adaptation and validation of a protein intake screening tool for a UK adult population
Authors: Tuttiett Esme R. , Ioannou Elysa , Wijnhoven Hanneke A.H. , Corfe Bernard M. , Williams Elizabeth A. 
Published: January 2023

AbstractAdequate dietary protein intake is important in human subjects for maintaining muscle turnover, determining the protein content of tissues and thus the preservation of muscle mass and function as we age. A screening tool to assess if an older individual is likely to have a lower dietary protein intake (predicted probability of protein intake ≤1⋅0 g/kg per d), has been developed for a Netherlands dietary profile, but this has not been validated in a UK population. This study aimed to adapt and then validate the protein screening tool for use in a UK population. Amendment of the tool was undertaken using data from UK BioBank and the UK National Diet and Nutrition Survey to reflect protein sources in the UK diet. Validation of the amended version of the protein screener screening tool was conducted using protein intake derived from a food frequency questionnaire (FFQ) in a sample of UK adults (n= 184) (age range 18–91 years) as the reference standard. Using the FFQ, 40 % of respondents (n= 74) reported a protein intake of ≤1⋅0 g per kg body mass. The discriminative accuracy of the amended screener was tested using receiver operating characteristic (ROC) curves. The area under the curve for the ROC was 0⋅731 (95 % CI 0⋅657, 0⋅805), indicating that the amended screener may be a valid tool to screen for individuals consuming ≤1⋅0 g/kg adjusted BM/d in an adult UK population. This protein screener tool is a potential method to screen individuals with a likelihood of habitually consuming protein intakes of ≤1⋅0 g/kg per d. Further validation is needed using a more robust dietary intake methodology and for specific groups, such as older adults. The screener may be applicable across healthcare, clinical and research applications.
Analysis of a non-reversible Markov chain speedup by a single edge
Authors: Gerencsér Balázs 
Published: January 2023

AbstractWe present a Markov chain example where non-reversibility and an added edge jointly improve mixing time. When a random edge is added to a cycle of n vertices and a Markov chain with a drift is introduced, we get a mixing time of
$O(n^{3/2})$
with probability bounded away from 0. If only one of the two modifications were performed, the mixing time would stay
$\Omega(n^2)$
.
The scientific discourse circulated during a national-populist commemoration: Dannunzian Fiume and the ‘Italo-cosmopolitan’ field of history
Authors: Lamour Christian 
Published: January 2023

AbstractIn today's Europe, commemorations can be times at which to affirm international reconciliation, based notably on the knowledge produced by historians who are becoming progressively cosmopolitan. However, commemorations are also used by national-populist political parties for electoral purposes and can lead to tensions with neighbouring states. This was the case in Trieste in September 2019, when the city council executive (controlled by a right-wing national-populist coalition) decided to erect a statue of Gabriele D'Annunzio, 100 years after he had occupied the nearby city of Fiume (now Rijeka) in Croatia. This commemoration led to a series of debates among historians, especially in Italy. Based on a critical discourse analysis and an interdiscursive approach to narratives produced by historians for colleagues and for the broader society, the current research investigates the use of cosmopolitanism in the field of history when in parallel a commemoration is coordinated by national-populist forces in a public space.
Developmental trajectories of premorbid functioning predict cognitive remediation treatment response in first-episode schizophrenia
Authors: Kuo Susan S. , Ventura Joseph , Forsyth Jennifer K. , Subotnik Kenneth L. , Turner Luana R. , Nuechterlein Keith H. 
Published: January 2023

AbstractBackgroundCognitive development after schizophrenia onset can be shaped by interventions such as cognitive remediation, yet no study to date has investigated whether patterns of early behavioral development may predict later cognitive changes following intervention. We therefore investigated the extent to which premorbid adjustment trajectories predict cognitive remediation gains in schizophrenia.MethodsIn a total sample of 215 participants (170 first-episode schizophrenia participants and 45 controls), we classified premorbid functioning trajectories from childhood through late adolescence using the Cannon-Spoor Premorbid Adjustment Scale. For the 62 schizophrenia participants who underwent 6 months of computer-assisted, bottom-up cognitive remediation interventions, we identified MATRICS Consensus Cognitive Battery scores for which participants demonstrated mean changes after intervention, then evaluated whether developmental trajectories predicted these changes.ResultsGrowth mixture models supported three premorbid functioning trajectories: stable-good, deteriorating, and stable-poor adjustment. Schizophrenia participants demonstrated significant cognitive remediation gains in processing speed, verbal learning, and overall cognition. Notably, participants with stable-poor trajectories demonstrated significantly greater improvements in processing speed compared to participants with deteriorating trajectories.ConclusionsThis is the first study to our knowledge to characterize the associations between premorbid functioning trajectories and cognitive remediation gains after schizophrenia onset, indicating that 6 months of bottom-up cognitive remediation appears to be sufficient to yield a full standard deviation gain in processing speed for individuals with early, enduring functioning difficulties. Our findings highlight the connection between trajectories of premorbid and postmorbid functioning in schizophrenia and emphasize the utility of considering the lifespan developmental course in personalizing therapeutic interventions.