bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metareflexivität: Von der Veränderungs- zur Vernunftorganisation
Authors: Meisinger Norman 
Published: May 2023

ZusammenfassungLängst überlassen Unternehmen ihre Modernisierung nicht mehr dem Zufall. Verankert in der Organisationsarchitektur sollen Lernroutinen (hier konzipiert als institutionalisierte Reflexivität) die Veränderungs- und damit Überlebensfähigkeit, vor allem von größeren Unternehmen in dynamischen Settings, langfristig sichern. Diese reflexiven Qualitäten zum Zwecke der Verstetigung ertragreichen Wirtschaftens bedürfen nun selbst einer Transformation, um fortan (auch) Lernprozesse vernünftigen Wirtschaftens zu stimulieren. Eine systematische Transformation zur unternehmerischen Inwertsetzung von Natur und Mensch wird in diesem Beitrag als Metareflexivität in die Debatte eingeführt. Denn wenn ertragreiches und vernünftiges Wirtschaften in einer kontradiktorischen Beziehung zueinander stehen, dürfen auch Spannungen in ihren Modernisierungsroutinen vermutet werden, die sich erst auf übergeordneter Ebene angemessen verarbeiten lassen.
Increased prevalence of nodular thyroid disease in patients with Klinefelter syndrome
Authors: di Fraia Rosa , Esposito Daniela , Selvaggio Lucia Digitale , Allosso Francesca , Alfano Roberto , Rotondi Mario , Balercia Giancarlo , Accardo Giacomo , Pasquali Daniela 
Published: May 2023

Abstract
Purpose
Thyroid dysfunction in patients with Klinefelter syndrome (KS) remains an unresolved issue. Although low free thyroxine (FT4) levels within the normal range and normal thyroid stimulating hormone (TSH) levels have been reported, there is currently no data on nodular thyroid disease in this population. This study aims to evaluate the results of thyroid ultrasound (US) examinations in KS patients compared with healthy controls.

Methods
A cohort of 122 KS and 85 age-matched healthy male controls underwent thyroid US screening and thyroid hormone analysis. According to US risk-stratification systems, nodules ≥1 cm were examined by fine needle aspiration (FNA).

Results
Thyroid US detected nodular thyroid disease in 31% of KS compared to 13% of controls. No statistical differences in the maximum diameter of the largest nodules and in moderate and highly suspicious nodules were found between patients and the control group. Six KS patients and two controls with nodules underwent FNA and were confirmed as cytologically benign. In line with published data, FT4 levels were found significantly near the lower limit of the normal range compared to controls, with no differences in TSH values between the two groups. Hashimoto’s thyroiditis was diagnosed in 9% of patients with KS.

Conclusions
We observed a significantly higher prevalence of nodular thyroid disease in KS compared to the control group. The increase in nodular thyroid disease is likely linked to low levels of FT4, inappropriate TSH secretion, and/or genetic instability.
Pentoxifylline changes the balance of immune cell population in breast tumor-infiltrating lymphocytes
Authors: Kazemi Mohammad Hossein , Shokrollahi Barough Mahdieh , Momeni-Varposhti Zahra , Ghanavatinejad Alireza , Zarehzadeh Mehrabadi Ali , Sadeghi Behnam , Falak Reza 
Published: May 2023

AbstractImmunotherapy utilizing tumor-infiltrating lymphocytes (TILs) is a promising approach for cancer treatment. Pentoxifylline (PTXF), a xanthine derivative, exhibits antitumor properties. This study aimed to investigate the impact of PTXF on the phenotype and function of TILs and splenocytes in a triple-negative breast cancer (TNBC) mouse model. TNBC was subcutaneously induced in BALB/c mice, followed by nine intraperitoneal injections of 100 mg/kg PTXF. TILs were then isolated by enzymatic digestion of tumors and cocultured with 4T1 cells. The proportion of regulatory T cells (Tregs) and cytotoxic T cells in TILs and splenocytes was assessed using flow cytometry. Transforming growth factor (TGF)-β and interferon (IFN)-γ production in TILs and splenocytes cultures was measured by ELISA. Relative expression of t-bet, foxp3, gata-3, and ror-γt in TILs and splenocytes was evaluated using real-time PCR. Tumor growth in PTXF-treated mice was significantly lower than that in the controls (P < 0.01). The frequency of regulatory and cytotoxic TILs in PTXF-treated mice was approximately half (P < 0.01) and twice (P < 0.05) that of the control group, respectively. The level of TGF-β and IFN-γ in the supernatant of PTXF-treated TILs was decreased and increased, respectively (P < 0.05). The relative expression of t-bet and foxp3 in the PTXF-treated mice compared to controls was increased and decreased, respectively (P < 0.05). Changes in the immune cell balance were less significant in the spleen compared to the TILs. PTXF treatment could limit the tumor growth and modify the regulatory-to-cytotoxic TILs ratio, as well as cytokine balance of TILs, in favor of antitumor responses.
Model-Based Cybersecurity Analysis
Authors: Jiang Yuning , Jeusfeld Manfred A. , Ding Jianguo , Sandahl Elin 
Published: May 2023

AbstractCritical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid.
Paradoxical tensions in exploiting data to implement circular economy in the textile industry
Authors: Luoma Päivi , Penttinen Esko , Tapio Petri , Toppinen Anne 
Published: May 2023

AbstractIncreasing utilization of data, enabled by digitalization, constitutes a major driver toward circular economy but is not without potential paradoxical tensions. A two-round disaggregative Delphi study and analysis of the qualitative material generated in it explored these tensions. They were found to cohere around three themes: consumer concurrence, business transparency, and technology relevance. The first theme is connected with consumers’ behavior and their perceptions as to data’s value, the transparency one involves alignment of business interests and practices with data-driven developments, and the third pertains to the actual environmental impact of digital technologies used to initiate data-driven circular economy. Business decision-making should address both the positive and the negative effects, in both the short and long term. Insight as to these tensions supports discovering how businesses can successfully utilize data in their efforts promoting circular economy within the complex reality of dynamically changing business environments.
Pyrolysis of biosolids with waste cardboard: effect of operating parameters, feedstock size and blending ratio
Authors: Zuhara S. , Pradhan S. , McKay G. 
Published: May 2023

AbstractGlobal waste is a rising problem that requires attention. Pyrolysis is a process that converts waste into valuable products like biochar, bio-oil, and gas by heating feeds above 300 °C. Pyrolysis studies mostly concentrate on fuel production and characterization, while biochar studies lack parametric analysis, especially for co-pyrolysis. Little attention is given to the effects of blending ratio and particle size on biochar yield. This research focuses on the pyrolysis of biosolids obtained from gas-to-liquid wastewater treatment, waste cardboard, and co-pyrolysis of blended samples. Pyrolysis was performed using a muffled furnace at temperatures ranging from 350–850 °C , heating rates of 3–10 °C /min, and residence times of 30–180 min to examine biochar yield and properties. Particle sizes and blending ratios were also studied. Proximate and ultimate analyses, metal composition, surface area, and surface charge studies were conducted on biochar samples utilizing analytical instruments. Biosolids had the highest yield followed by mixed samples and cardboard for all conditions, with temperature and blending ratio having the greatest impact on yield. Regarding surface area, the maximum was found to be at 650 °C revealing 10.34, 170.4, and 124.8 m2/g for biosolids, cardboard, and mixed samples, respectively. A significant effect with change in blending ratio and a minimal effect by varying particle size was observed on the biochar yield. For future applications, temperatures below 550 °C can be considered in terms of biochar yield, ash, and metal contents; as heating rate and residence time showed minimal effects on yield, lower points are preferred to conserve energy during pyrolysis. Overall, mixing waste improved quality and yield, making it environmentally beneficial for applications.
Graphical abstract
In-vitro antiplatelet effect of melatonin in healthy individuals and patients with type 2 diabetes mellitus
Authors: Böhm A. , Lauko V. , Dostalova K. , Balanova I. , Varga I. , Bezak B. , Jajcay N. , Moravcik R. , Lazurova L. , Slezak P. , Mojto V. , Kollarova M. , Petrikova K. , Danova K. , Zeman M. 
Published: May 2023

Abstract
Purpose
The incidence of acute myocardial infarctions (AMI) shows circadian variation typically peaking during morning hours with a decline at night. However, this variation does not occur in patients with diabetes mellitus (DM). The night’s decline of AMI may be partially explained by melatonin-related platelet inhibition. Whether this effect is absent in diabetic patients is unknown. The aim was to study the effect of melatonin on in-vitro platelet aggregation in healthy individuals and patients with type 2 DM.

Methods
Platelet aggregation was measured in blood samples from healthy individuals (n = 15) and type 2 DM patients (n = 15) using multiple electrode aggregometry. Adenosine diphosphate (ADP), arachidonic acid (ASPI) and thrombin (TRAP) were used as agonists. Aggregability for each subject was tested after adding melatonin in two concentrations.

Results
In healthy individuals, melatonin inhibited platelet aggregation in both higher (10–5 M) and lower concentrations (10–9 M) induced by ADP, ASPI, and TRAP (p < 0.001, p = 0.002, p = 0.029, respectively). In DM patients, melatonin did not affect platelet aggregation in both concentrations induced by ADP, ASPI, and TRAP. Melatonin decreased platelet aggregation induced by ADP, ASPI, and TRAP significantly more in healthy individuals compared to patients with DM. (p = 0.005, p = 0.045 and p = 0.048, respectively).

Conclusion
Platelet aggregation was inhibited by melatonin in healthy individuals. In-vitro antiplatelet effect of melatonin in type 2 DM patients is significantly attenuated.
Numerical Analysis of Vibration Attenuation and Bandgaps in Radially Periodic Plates
Authors: Manconi E. , Hvatov A. , Sorokin S. V. 
Published: May 2023

Abstract
Objective
Periodic configuration of mechanical and civil structures has shown great potential for noise and vibration reduction. However, the use of Cartesian coordinates in studying periodicity effects in elastic structures overlooks the benefits of radially periodic configurations when dealing with wave propagation in large flexible plates disturbed by a small source area. This paper presents an easy-to-use numerical approach to predicting bandgap characteristics in polar coordinates.

Methodology
To demonstrate the vibration-attenuation effect, we consider a circular radially periodic plate model. We use an adapted Wave Finite-Element method in numerical experiments to demonstrate the existence of the attenuation effect. To verify the numerical results, we apply an adapted Floquet theory to polar coordinates.

Results and Conclusions
Our findings indicate that theoretical and numerical results are in excellent agreement considering a new parameter that introduces the distance from the origin. The adapted Wave Finite-Element approach and Floquet theory presented here demonstrate their potential to model more complex structures in polar coordinates.
Standardizing fairness-evaluation procedures: interdisciplinary insights on machine learning algorithms in creditworthiness assessments for small personal loans
Authors: Genovesi Sergio , Mönig Julia Maria , Schmitz Anna , Poretschkin Maximilian , Akila Maram , Kahdan Manoj , Kleiner Romina , Krieger Lena , Zimmermann Alexander 
Published: May 2023

AbstractIn the current European debate on the regulation of Artificial Intelligence there is a consensus that Artificial Intelligence (AI) systems should be fair. However, the multitude of existing indicators allowing an AI system to be labeled as “(un)fair” and the lack of standardized, application field specific criteria to choose among the various fairness-evaluation methods makes it difficult for potential auditors to arrive at a final, consistent judgment. Focusing on a concrete use case in the application field of finance, the main goal of this paper is to define standardizable minimal ethical requirements for AI fairness-evaluation. For the applied case of creditworthiness assessment for small personal loans, we highlighted specific distributive and procedural fairness issues inherent either to the computing process or to the system’s use in a real-world scenario: (1) the unjustified unequal distribution of predictive outcome; (2) the perpetuation of existing bias and discrimination practices; (3) the lack of transparency concerning the processed data and of an explanation of the algorithmic outcome for credit applicants. We addressed these issues proposing minimal ethical requirements for this specific application field: (1) regularly checking algorithmic outcome through the conditional demographic parity metric; (2) excluding from the group of processed parameters those that could lead to discriminatory outcome; (3) guaranteeing transparency about the processed data, in addition to counterfactual explainability of algorithmic decisions. Defining these minimal ethical requirements represents the main contribution of this paper and a starting point toward standards specifically addressing fairness issues in AI systems for creditworthiness assessments aiming at preventing unfair algorithmic outcomes, in addition to unfair practices related to the use of these systems. As a final result, we indicate the next steps that can be taken to begin the standardization of the three use case-specific fairness requirements we propose.
Analyzing the impact of COVID-19 on the electricity demand in Austin, TX using an ensemble-model based counterfactual and 400,000 smart meters
Authors: Dai Ting-Yu , Radhakrishnan Praveen , Nweye Kingsley , Estrada Robert , Niyogi Dev , Nagy Zoltan 
Published: May 2023

AbstractThe COVID-19 pandemic caused lifestyle changes and has led to the new electricity demand patterns in the presence of non-pharmaceutical interventions such as work-from-home policy and lockdown. Quantifying the effect on electricity demand is critical for future electricity market planning yet challenging in the context of limited smart metered buildings, which leads to limited understanding of the temporal and spatial variations in building energy use. This study uses a large scale private smart meter electricity demand data from the City of Austin, combined with publicly available environmental data, and develops an ensemble regression model for long term daily electricity demand prediction. Using 15-min resolution data from over 400,000 smart meters from 2018 to 2020 aggregated by building type and zip code, our proposed model precisely formalizes the counterfactual universe in the without COVID-19 scenario. The model is used to understand building electricity demand changes during the pandemic and to identify relationships between such changes and socioeconomic patterns. Results indicate the increase in residential usage , demonstrating the spatial redistribution of energy consumption during the work-from-home period. Our experiments demonstrate the effectiveness of our proposed framework by assessing multiple socioeconomic impacts with the comparison between the counterfactual universe and observations.
Nutritional Risk Assessment and Countermeasures for Stroke Patients Based on Deep Learning and Multimodal MRI Images
Authors: Jiang Yiming , Sun Jian , Ren Xinchen , Wang Huikai 
Published: May 2023

AbstractThe main objective of this study is to evaluate the nutritional risk of stroke patients through deep learning and multimodal MRI images, and provide appropriate nutrition for patients in a timely manner to improve their recovery speed. The method of this article mainly solves the problem of incomplete understanding of patient nutritional risk through a deep learning (DL) and multimodal MRI image-based nutritional risk assessment (RA) model, and accurately provides corresponding countermeasures. The evaluation model based on DL and multimodal MRI images shows that 27 people in Group A are at nutritional risk, accounting for 90%. 26 people in Group B are at nutritional risk, accounting for 86.6%. Both groups of patients urgently need corresponding strategies to reduce risk. Therefore, this article also tested two sets of nutritional support methods, and the results showed that the nutritional support methods in Group B were more effective. The nutritional indicators are not only normal, but the infection rate and mortality rate of patients have also decreased. The results demonstrate that deep learning and multimodal MRI images can promote the recovery process of patients.
Earnings differentials between H-2A and unauthorized citrus harvesters in Florida
Authors: Simnitt Skyler Mark , Onel Gulcan 
Published: May 2023

AbstractThe H-2A temporary agricultural workers visa program is a federal program allowing agricultural employers to bring in foreign workers on a seasonal basis. The extent to which H-2A workers earn more compared to their domestic unauthorized counterparts is of interest for both producers and workers. Using novel data on citrus harvest workers in the state of Florida, we estimate hourly earnings differentials by legal status using Classical and Bayesian inference. Findings suggest that participation in the H-2A program is associated with 18–23% higher hourly earnings for migrant harvesters in Florida after controlling for observable demographic and work-related variables.
Agricultural credit association efficiencies over time and with mergers
Authors: He Yurou , Tauer Loren W. 
Published: May 2023

AbstractEfficiencies of Agricultural Credit Associations of the US Farm Credit System are measured quarterly from 2005 through 2020. A slacks-based measure based on the directional distance function is used with non-performing loans included as an undesirable output. This permitted efficiency scores to be measured by type of defined input or output. Generally, most Associations were highly efficient, but there was deterioration in mean efficiency over the years 2008–2018, a period of financial difficulties in the US agriculture. Efficiencies of Associations that merged or consolidated were tracked before and after these activities. Mergers and consolidations often led to increased efficiencies.
Mechanism for the subglacial formation of cryogenic brines
Authors: Neuhaus Sarah U. , Tulaczyk Slawek M. 
Published: May 2023

AbstractCryogenic brines are under-studied, despite the fact that they may contain information about past ice-sheet behavior. Cryogenic brines form through cryoconcentration of seawater, although the specific setting and mechanism of formation have been debated. Previous conceptual models of brine formation require seawater isolation from the ocean in a closed basin experiencing freezing. We propose instead that they may form in pore spaces of marine sediments subjected to repeat cycles of ice-sheet advance and retreat. During periods of basal freezing, cryoconcentration produces hypersaline brines which experience downward flow driven by unstable density stratification. Our advection-diffusion model of porewater chemistry evolution successfully recreates the porewater chemistry of two deep Antarctic cores containing cryogenic brines (AND-1B and AND-2A), suggesting that cryogenic brines can be formed through the repeated isolation and cryoconcentration of marine waters within subglacial sediment pore spaces of modern and past ice sheets.
The dark side of fear expression: Infant crying as a trigger for maladaptive parental responses
Authors: Parsons Christine E. , Skewes Joshua C. 
Published: May 2023

Abstract
While infant fearfulness, and its expression via crying, may have been adaptive in our evolutionary history, for modern parents, crying can be challenging to respond to. We discuss how and why prolonged crying can raise the risk for difficulties with adult care. Given that crying is the most-reported trigger for shaking, its potential to elicit maladaptive responses should not be overlooked.
Fearfulness: An important addition to the starter kit for distinctively human minds
Authors: Dwyer Dominic M. , Heyes Cecilia 
Published: May 2023

Abstract
Grossmann's impressive article indicates that – along with attentional biases, expansion of domain-general processes of learning and memory, and other temperamental tweaks – heightened fearfulness is part of the genetic starter kit for distinctively human minds. The learned matching account of emotional contagion explains how heightened fearfulness could have promoted the development of caring and cooperation in our species.
Narratives of crisis: From affective structures to adaptive functions
Authors: Pelletier Petra , McLaughlin Cécile , Boespflug Magali 
Published: May 2023

Abstract
This commentary focuses on affective structures and the main adaptive functions of shared narratives to fill the gaps of the Conviction Narrative Theory. The transmission of narratives among individuals in highly uncertain situations is irrevocably tainted by affects and anchored in collective memory. Narratives have important evolutionary functions for human beings under threat and act as the social glue that creates and strengthens social bonds among individuals.
Is Conviction Narrative Theory a theory of everything or nothing?
Authors: Newell Ben R. , Szollosi Aba 
Published: May 2023

Abstract
We connect Conviction Narrative Theory to an account that views people as intuitive scientists who can flexibly create, evaluate, and modify representations of decision problems. We argue that without understanding how the relevant complex narratives (or indeed any representation, simple to complex) are themselves constructed, we also cannot know when and why people would rely on them to make choices.