bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence, risk factors, and severity of erectile dysfunction following renal transplantation
Authors: Miron Adelina , Nistor Ionuț , Moroșanu Corneliu , Sirițeanu Lucian , Pricop Catalin , Puia Dragos , Covic Adrian 
Published: December 2024

Abstract
Background
Sexual dysfunction is common among dialysis and transplant patients. Our study evaluated the prevalence, risk factors, and severity of erectile dysfunction (ED) post-transplant in a single center.

Methods
We conducted a single-centre, observational, non-interventional study of adult male renal graft recipients. Sociodemographic and clinical data were collected, and erectile function was assessed with the International Index of Erectile Function (IIEF) questionnaire.

Results
179 patients transplanted between 1995 and 2021 were enrolled (170 answered the questionnaire). Mild, moderate, and severe ED was noted in 33.5%, 20.6% and 10.6% of cases, respectively. ED prevalence increased with age (42.6% of patients < 40, 47.4% of patients aged 40–60, 78.9% of patients > 60). The total mean IIEF score was 16.32 ± 6.93 (erectile function 19.22 ± 7.9, orgasmic function 6.8 ± 2.9, sexual desire 6.43 ± 2.1, intercourse satisfaction 8.96 ± 3.7, overall satisfaction 6.78 ± 2.6). Age, alcohol consumption, type, time on dialysis pre-transplant, and donor type were significantly associated with erectile dysfunction (p < 0.05). Most patients (93.5%) were treated for comorbidities in addition to immunosuppression. Severe ED was significantly more common among patients taking alpha blockers and non-steroidal anti-inflammatory drugs.

Conclusions
Self-reported erectile dysfunction post renal transplantation seems influenced by age, alcohol intake, dialysis history, donor type and certain drugs, but not by comorbidities (hypertension, diabetes, heart disease).
Studying economic complexity with agent-based models: advances, challenges and future perspectives
Authors: Chudziak Szymon 
Published: December 2024

AbstractAgent-based computational economics has considerable achievements. However, it has gone too quickly into a direction similar to the one of models based on solely analytical—as opposed to algorithmic—dynamic systems of difference equations. An increasingly large focus has been put on matching moments of real-world time series of data, a set of stylised facts, or on estimation. Reasons why this is not desirable are discussed. Firstly, both estimation and inference from models will be biased, unless they represent the real data-generating processes. Secondly, surrendering the attempt to incorporate realistic microfoundations is not only against the original ACE agenda, but also is subject to a form of Lucas critique. Thirdly, characteristics of complex systems, especially differences between feedback loops and emergent phenomena that characterise systems of various levels of complexity, undermine the justification of building structurally simplistic models. That is, an attempt at reducing the interaction of many different sectors, populated with agents using various decision rules will yield information loss, i.e., some phenomena by definition are possible to emerge only in systems of higher levels of complexity. A different research agenda is proposed, with the aim of systematically analysing and uncovering the mechanisms, feedback loops and impact channels of complex multi-sectoral economic and financial systems.
Machine learning-aided selection of CPT-based transformation models using field monitoring data from a specific project
Authors: Tian Hua-Ming , Wang Yu , Shi Chao 
Published: December 2024

AbstractTransformation models have been widely used in geotechnical engineering to relate data from lab or field tests (e.g., cone penetration tests, CPT) to design parameters required in geotechnical analysis and design. Proper selection of transformation models is crucial but challenging for accurate prediction of geotechnical responses (e.g., reclamation-induced settlement) in practice. This study proposes a general machine learning framework that accommodates a wide variety of existing CPT-based transformation models and uses field monitoring data (e.g., settlement data observed from a specific project) to select suitable transformation models for improving prediction of spatiotemporally varying reclamation-induced settlement. The proposed approach takes advantage of sparse dictionary learning (SDL) and achieves prediction of settlement by a linear weighted sum of dictionary atoms that are constructed using outputs from finite element models (FEM) of reclamation-induced consolidation. Input parameters of the FEM models are determined using existing transformation models in literature. A transformation model database that relates multiple soil consolidation parameters with CPT data is also compiled for consolidation analysis and dictionary construction in SDL. The proposed approach is illustrated using a real reclamation project in Hong Kong. Results show that the proposed approach provides an effective and transparent vehicle to leverage existing abundant transformation models, identify appropriate transformation models using field monitoring data, and improve prediction of spatiotemporally varying reclamation-induced settlement, with greatly reduced prediction uncertainty. The transformation model selection and settlement prediction are also improved continuously as more field monitoring data are obtained.
Dynamiken des Klimakonflikts: Eskalation, Gegeneskalation und De-Eskalation seit Fridays for Future und der Letzten Generation
Authors: August Vincent 
Published: December 2024

ZusammenfassungDer Konflikt um die politische Reaktion auf den Klimawandel ist trotz weiterer Krisen präsent geblieben. Da sich das Konfliktgeschehen weiterentwickelt, bedarf die Forschung ständiger Aktualisierungen. Zugleich fokussiert sie sich zurzeit stark auf die Bewegungsseite, oft auf einzelne Protestgruppen. In diesem Artikel wird demgegenüber eine konflikttheoretische Perspektive vorgeschlagen, die die Analyse kategorial ausweitet. Dadurch werden drei maßgebliche Beiträge geleistet: Erstens wird die Entwicklungsdynamik des Konflikts im Zeitverlauf über mehrere Gruppen hinweg rekonstruiert und auf Mechanismen der Eskalation und De-Eskalation zurückgeführt (Organisation und Exhaustion von Solidarität, Allianzen, Ressourcen). Zweitens zeigt der Beitrag eine konflikttheoretisch erwartbare Gegeneskalation auf, die für den Konfliktverlauf entscheidend ist. Vor dem Hintergrund von (Gegen‑)Eskalation und De-Eskalation werden drittens Verhältnis und Strategiewechsel von Gruppierungen wie Fridays for Future und Letzter Generation diskutiert. Insgesamt plädiert der explorative Beitrag für eine breitere Analyse der Konfliktkonstellationen und -dynamiken, exploriert die Entwicklung von 2018 bis zum Jahreswechsel 2023/2024 anhand einer umfänglichen Dokumentensammlung und zeigt neue Forschungsrichtungen auf. Die Konflikttheorie bietet dabei einen Rahmen, der mehrere Ebenen einbezieht und zudem die Forschung zu Protesten und climate obstruction ins Gespräch bringen kann.
Editorial: Topical Collection “Ethical and Societal Implications of AgeTech”
Authors: Rubeis Giovanni , Sixsmith Andrew 
Published: December 2024

AbstractAgeTech refers to a growing sector that is advancing the use of technologies, such as information and communication technologies (ICTs), mobile technologies, robotics, wearables and smart home systems to enhance the lives of older adults. Although AgeTech can be seen as an opportunity for empowering older people and enhance their overall quality of life, crucial ethical issues have to be addressed. The articles in this topical collection focus on these and other ethical questions, particularly in respect to key emerging technologies of AI and robotics. The overall aim is to explore the multifaceted ethical landscape of emerging AgeTech and to provide frameworks and strategies for ethically-appropriate technologies that support the health, well-being, and quality of life of older adults.
Technological Remedies for Social Problems: Defining and Demarcating Techno-Fixes and Techno-Solutionism
Authors: Sætra Henrik Skaug , Selinger Evan 
Published: December 2024

AbstractCan technology resolve social problems by reducing them to engineering challenges? In the 1960s, Alvin Weinberg answered yes, popularizing the term “techno-fix” in the process. The concept was immediately criticized and over time evolved into a disparaging term—a synonym for unrealistic technological proposals and their advocates. As the debate progressed, skepticism grew to include condemnation of a related term: “techno-solutionism.” Despite extensive criticism, both “techno-fix” and “techno-solutionism” remain ill-defined concepts. In this article, we provide more precise definitions and clearly distinguish between techno-fixes and techno-solutionism through conceptual engineering. By refining these concepts, we aim to advance the discussion and lay the groundwork for more productive analyses of the role of technology in solving social problems.
Autopsy characteristics of deaths due to pulmonary thromboembolism in northern and western denmark: a 10-year retrospective study
Authors: Christensen Martin Roest , Larsen Annesofie Bjerrum , Boel Lene Warner Thorup 
Published: December 2024

AbstractBecause pulmonary thromboembolism (PTE) has an inherent high risk of sudden and unexpected death, this condition is a classic entity in forensic casework. The purpose of this study was to elucidate the characteristics surrounding deaths from PTE. We conducted a retrospective study from 2010 to 2019 at the Department of Forensic Medicine in Aarhus, Denmark. We recorded demographic characteristics, risk factors, comorbidities, and autopsy findings, including BMI. Furthermore, we contextualized the role of forensic autopsy in terms of determining the correct cause of death (COD).Among the 3,572 autopsies, 58 had PTE as the main COD (1.6%), whereas only 0.3% of the deaths in the Danish COD registry were attributed to PTE in the same period. The decedents had a mean age of 52 years (range 19–87), and although the majority had preexisting comorbidities, approximately one-third died suddenly and unexpectedly. Additionally, more than half (35/58) of the decedents died in an out-of-hospital setting, and only a few of these (6/35) reported symptoms prior to death, underscoring the insidiousness of the condition. We identified a mean BMI of 32.7 among the decedents, with more than half of them (30/58) having a BMI ≥ 30.In conclusion, obesity is a major risk factor for fatal PTE. The blurred clinical presentation of PTE underscores the importance of an autopsy to determine the correct COD, and with an increased autopsy rate, the true prevalence may well be higher.
Who thinks the media is hostile?! An examination of individual differences predicting the hostile media effect concerning news media coverage of individuals with a migratory background in Germany
Authors: Sindermann Cornelia 
Published: December 2024

Abstract
The present study explores individual differences related to the perception of the media coverage of immigrants as biased. Building on previous research, relations with the extremity in preexisting attitudes toward immigrants and in affective ratings of non-immigrants versus immigrants are examined. Additionally, the present study extends previous work by investigating dogmatism and intellectual humility, including their potential moderating roles on the relations of extremity in attitudes and affective ratings with perceived media bias. A sample of N = 212 (59% men) individuals from the general German population completed self-reports on their preexisting attitudes and affective ratings, as well as dogmatism and intellectual humility online. Moreover, participants rated their perception of news media coverage of immigrants as biased against their views. Results indicate that particularly more extreme negative attitudes toward immigrants and affective ratings favoring non-immigrants relative to immigrants are positively associated with perceiving the media coverage of immigrants as biased. No robust relations of dogmatism, intellectual humility, or their interactions with the extremity scores with perceived media bias were found. These findings underline the importance of negative extremity in (out) group-related attitudes and affect in perceiving the media coverage as biased. New approaches investigating media perceptions from a group-related perspective are discussed.
Data-Driven Framework for the Techno-Economic Assessment of Sustainable Aviation Fuel from Pyrolysis
Authors: Okolie Jude A. , Moradi Keon , Rogachuk Brooke E. , Narra Bala Nagaraju , Ogbaga Chukwuma C. , Okoye Patrick U. , Adeleke Adekunle A. 
Published: December 2024

AbstractThe aviation sector plays a vital role in global transportation, economic growth, and social integration. However, its rapid expansion has led to increased emissions. Sustainable aviation fuel (SAF) provides a promising solution by offering a clean-burning, renewable alternative to conventional jet fuel. SAF can be produced through various processes and feedstocks, significantly reducing the aviation industry’s environmental footprint. Fast pyrolysis (FP) presents a cost-effective and scalable approach for SAF production due to its low-cost feedstocks, rapid reaction times, and simpler technology. However, estimating the economic viability of FP for SAF production is complex and labor-intensive, requiring detailed process models and numerous assumptions. Furthermore, determining the relationship between feedstock properties and the minimum selling price (MSP) of the fuel can be challenging. To address these challenges, this study developed a data-driven framework for the preliminary estimation of SAF's MSP from FP. Synthetic data was generated using Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE), and hyperparameter optimization was performed using Grid Search to enhance model accuracy and predictions. Five surrogate models were evaluated: linear regression, gradient boost regression (GBR), random forest (RF), extreme boost regression (XGBoost), and elastic net. Among these, GBR and RF showed the most promise, based on metrics such as R2, RMSE, and MAE for both original and synthetic datasets. Specifically, GBR achieved a Train R2 of 0.9999 and a Test R2 of 0.9277, while RF recorded Train and Test R2 scores of 0.9789 and 0.9255, respectively. The use of data from the VAE further improved model accuracy. Additionally, a publicly accessible graphical user interface was developed, enabling researchers to estimate the MSP of SAF based on biomass properties, plant capacity, and location.
Gut Microbiota Dysbiosis Facilitates Susceptibility to Bloodstream Infection
Authors: Lin Xiaomin , Lin Chun , Li Xin , Yao Fen , Guo Xiaoling , Wang Meimei , Zeng Mi , Yuan Yumeng , Xie Qingdong , Huang Xudong , Jiao Xiaoyang 
Published: December 2024

AbstractTo study the role of intestinal flora in the development of bloodstream infections (BSIs). 42 patients and 19 healthy controls (HCs) were screened into the study and their intestinal flora was measured by 16S rRNA gene sequencing. The bacterial diversity was significantly lower in the BSI group compared with that in the HCs (P < 0.001), and beta diversity was significantly differentiated between the two groups (PERMANOVA, P = 0.001). The four keystone species [Roseburia, Faecalibacterium, Prevotella, and Enterococcus (LDA > 4)] differed significantly between the two groups. Dysbiosis of fecal microbial ecology is a common condition present in patients with BSI. The proliferation of certain pathogens or reduction of SCFA-producing bacteria would cause susceptibility to BSI.
Identity Experiences, Group Consciousness, and Collective Action Among Bisexual Individuals: An Investigation of Identity-Based Pathways That Facilitate and Constrain Collective Action Through Multiple Levels of Influence
Authors: Hung Fei Nga , Chan Randolph C. H. 
Published: December 2024

Abstract
Introduction
Social identity has been recognized as a central factor explaining participation in collective action. Previous studies have predominantly focused on collective action within sexual minority groups as a whole. However, there is a need to explore the specific experiences of bisexual individuals who face distinct challenges due to monosexism. Currently, limited research has been conducted to understand the underlying mechanism that connects bisexual identity experiences to engagement in collective action. The present study examined group consciousness at intrapersonal, interpersonal, and community levels as a mediating mechanism between various aspects of bisexual identity experiences and collective action among bisexual individuals.

Methods
A total of 162 individuals who identified as bisexual completed the questionnaire on bisexual identity experiences (i.e., illegitimacy of bisexuality, anticipated binegativity, internalized binegativity, and identity affirmation), group consciousness, and collective action.

Results
The results revealed that anticipated binegativity and internalized binegativity were associated with collective action through commitment to social justice, whereas anticipated binegativity and identity affirmation were related to collective action through community connectedness. Moreover, illegitimacy of bisexuality was linked to different identity experiences, which in turn contributed to participation in collective action through group consciousness.

Conclusions and Policy Implications
This study offers empirical evidence highlighting the significance of group consciousness as a fundamental process that mobilizes collective action within the bisexual community. These results have important implications for clinical, educational, and community practices aimed at fostering bisexual group consciousness and reducing stigma associated with bisexuality.
Positive Outcomes of Long-Term Relationship Satisfaction Trajectories in Stable Romantic Couples: A 10-Year Longitudinal Study
Authors: Roth Michelle , Landolt Selina A. , Nussbeck Fridtjof W. , Weitkamp Katharina , Bodenmann Guy 
Published: December 2024

AbstractGrowing evidence challenges the longstanding assumption of a universal decline in relationship satisfaction for all couples by demonstrating variability in the change. However, knowledge about how differential long-term trajectories of relationship satisfaction are associated with positive individual functioning is lacking. Using dyadic latent class growth analysis, we studied long-term trajectories of relationship satisfaction of N = 300 mixed-gender couples over 10 years and examined positive outcomes in latent subgroups. At the final assessment, partners reported on positive outcomes, specifically affect, mental health, and life satisfaction. Depending on their subgroup membership, couples systematically differed: Couples in the subgroup with high initial and relatively stable relationship satisfaction reported the most favorable outcomes—more positive affect, better mental health, and higher life satisfaction—as compared to subgroups with declining and/or lower relationship satisfaction. The findings show the importance of considering the variability in long-term relationship satisfaction trajectories and point to their relevance for positive functioning.
Meromorphic functions that share three limit values with their derivatives
Authors: Sauer Andreas 
Published: December 2024

AbstractLet f be a transcendental meromorphic function in the complex plane. We prove that if f and $$f'$$

f
′

share three finite limit values, then f and $$f'$$

f
′

share all limit values. If f is entire, two finite shared limit values with $$f'$$

f
′

give the same conclusion.
Neonatal diabetes due to KCNJ11 pathogenic variant and its associated late risks
Authors: Gaidamaviciene Gabija , Traberg Rasa , Mockeviciene Giedre , Aldakauskiene Ilona 
Published: December 2024

AbstractNeonatal diabetes, characterized by hyperglycemia within the first 6 months of life, is a rare disorder primarily caused by monogenic mutations, exhibiting diverse clinical manifestations. KCNJ11 and ABCC8 pathogenic variants account for most permanent neonatal diabetes cases. We report a case of a 2-day-old presenting with hyperglycemia and later diagnosed with a KCNJ11 pathogenic variant. The male newborn was born in the 35th week of pregnancy. Capillary glucose levels started to rise at the 36th hour of life. A continuous infusion of insulin was started at the 96th hour of life. The need for insulin remained constant. Genetic analysis confirmed a heterozygous pathogenic KCNJ11 gene variant NM_000525.4:c.175G > A p.(Val59Met) via Sanger sequencing (conducted at The Exeter Genomics Laboratory). This variant is associated with neonatal diabetes and a high likelihood of DEND (developmental delay, epilepsy, neonatal diabetes) syndrome. Glibenclamide therapy was started at the age of 57 days. Follow-up visits with the neurology and endocrinology teams showed good glycemic control with glibenclamide, a slight delay in motor development, and no epilepsy. Despite the rarity of genetic neonatal diabetes, it should be considered in infants with persistent hyperglycemia. In some cases, diabetes can be successfully managed with oral sulphonylurea agents, so rapid genetic testing and initiation of appropriate medication are extremely important because they significantly improve quality of life as well as general outcomes.
Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance
Authors: Elhoseny M. , Rao Deepak Dasaratha , Veerasamy Bala Dhandayuthapani , Alduaiji Noha , Shreyas J. , Shukla Piyush Kumar 
Published: December 2024

AbstractEnvironmental perception is one of the key technologies to realize autonomous vehicles. The fault diagnosis process involves identifying the fault that occurred or the cause of the out-of-control condition. Here, the major objective is to locate problems in detection by analysing previous data or sequential patterns of data that cause failure. This study evaluates the use of deep learning for improved sensor data fusion in fault identification and tolerance using the KITTI dataset. The input video from the dataset has been transformed to frames through median filtering. Next, feature extraction is applied to a preprocessed image, resulting in the fusion of sensor data. Data fusion is then carried out utilizing an enhanced RPN (region proposal network). The enhanced RPN also has a loss function (object detection loss, bounding box loss and target classification loss), an estimate of ROI and feature extraction network (FEN). Through the use of the COOT connected blue monkey optimization (CCBMO) model, the weight of the optimally enhanced RPN is established. Next, using global non-maximum suppression with both global and local confidence, fault identification and tolerance are carried out. From the analysis, it clearly shows that proposed method accomplished better results in terms of accuracy, precision and specificity of 97.78%, 93.76% and 93.43%, respectively, when compared with various conventional models with respect to diverse performance measures.
Newton–Cotes quadrature formula, 3/8 rule, and Boole’s rule integration of the Current minus the Short-Circuit Current, to obtain the Co-Content function and photovoltaic device parameters with more precision, in the case of constant percentage noise
Authors: Rangel-Kuoppa Victor-Tapio 
Published: December 2024

AbstractIn this article, the Newton–Cotes quadrature formula, the 3/8 rule, and the Boole’s rule integration techniques are used to integrate the Current minus the Short-Circuit Current, to obtain a more accurate Co-Content function, and from this one, deduce with more accuracy the photovoltaic device parameters, namely, the Shunt Resistance, the Series Resistance, the Ideality Factor, the Saturation Current, and the Light Current, compared with the usually used trapezoidal integration technique. Less than 5% error (in some cases 1% or smaller) can be obtained on the extracted photovoltaic device parameters, for 31 measured points per volt, or less, in case the percentage noise is <0.05%.