bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiology of gastroenteropancreatic neuroendocrine neoplasms: a review and protocol presentation for bridging tumor registry data with the Italian association for neuroendocrine tumors (Itanet) national database
Authors: Panzuto Francesco , Partelli Stefano , Campana Davide , de Braud Filippo , Spada Francesca , Cives Mauro , Tafuto Salvatore , Bertuzzi Alexia , Gelsomino Fabio , Bergamo Francesca , Marcucci Stefano , Mastrangelo Laura , Massironi Sara , Appetecchia Marialuisa , Filice Angelina , Badalamenti Giuseppe , Bartolomei Mirco , Amoroso Vito , Landoni Luca , Rodriquenz Maria Grazia , Valente Monica , Colao Annamaria , Isidori Andrea , Fanciulli Giuseppe , Bollina Roberto , Ciola Michele , Butturini Giovanni , Marconcini Riccardo , Arvat Emanuela , Cinieri Saverio , Berardi Rossana , Baldari Sergio , Riccardi Ferdinando , Spoto Chiara , Giuffrida Dario , Gattuso Domenico , Ferone Diego , Rinzivillo Maria , Bertani Emilio , Versari Annibale , Zerbi Alessandro , Lamberti Giuseppe , Lauricella Eleonora , Pusceddu Sara , Fazio Nicola , Dell’Unto Elisabetta , Marini Marco , Falconi Massimo 
Published: January 2024

Abstract
Neuroendocrine neoplasms (NENs) are rare tumors with diverse clinical behaviors. Large databases like the Surveillance, Epidemiology, and End Results (SEER) program and national NEN registries have provided significant epidemiological knowledge, but they have limitations given the recent advancements in NEN diagnostics and treatments. For instance, newer imaging techniques and therapies have revolutionized NEN management, rendering older data less representative. Additionally, crucial parameters, like the Ki67 index, are missing from many databases. Acknowledging these gaps, the Italian Association for Neuroendocrine Tumors (Itanet) initiated a national multicenter prospective database in 2019, aiming to gather data on newly-diagnosed gastroenteropancreatic neuroendocrine (GEP) NENs. This observational study, coordinated by Itanet, includes patients from 37 Italian centers. The database, which is rigorously maintained and updated, focuses on diverse parameters including age, diagnostic techniques, tumor stage, treatments, and survival metrics. As of October 2023, data from 1,600 patients have been recorded, with an anticipation of reaching 3600 by the end of 2025. This study aims at understanding the epidemiology, clinical attributes, and treatment strategies for GEP-NENs in Italy, and to introduce the Itanet database project. Once comprehensive follow-up data will be acquired, the goal will be to discern predictors of treatment outcomes and disease prognosis. The Itanet database will offer an unparalleled, updated perspective on GEP-NENs, addressing the limitations of older databases and aiding in optimizing patient care.

Study registration
This protocol was registered in clinicaltriasl.gov (NCT04282083).
Cerebellar Asymmetry of Motivational Direction: Anger-Dependent Effects of Cerebellar Transcranial Direct Current Stimulation on Aggression in Healthy Volunteers
Authors: Kruithof Eline S. , Klaus Jana , Schutter Dennis J. L. G. 
Published: January 2024

AbstractIt has recently been theorized that the frontal asymmetry of approach- and avoidance-related motivation is mirrored in the posterolateral cerebellum. Accordingly, left-to-right dominant cerebellar activity is associated with avoidance-related motivation, whereas right-to-left dominant cerebellar activity is associated with approach-related motivation. The aim of this study was to examine the cerebellar asymmetry of motivational direction in approach-related behavior in the context of aggression. In this randomized double-blind sham-controlled crossover study, thirty healthy right-handed adult volunteers received 2 mA active or sham left cathodal-right anodal transcranial direct current stimulation (tDCS) to the cerebellum on two separate occasions while engaging in the Point Subtraction Aggression Paradigm (PSAP) task to measure aggressive behavior. Self-reported state anger was assessed before, halfway and immediately after the task, and heart rate and heart rate variability (HRV) were measured during the task. No main effects of tDCS on aggressive behavior, heart rate and HRV were found. Higher state anger before and during the PSAP task was associated with increased aggressive behavior in the active compared to sham tDCS condition. Aggressive behavior was positively correlated with heart rate during active tDCS, while an inverse association was observed during sham tDCS. Results provide support for the cerebellar asymmetry of motivational direction in approach-related behavior and illustrate the importance of affective state-dependency in tDCS-related effects.
Transient Decrease in Sperm Motility after Plateletpheresis
Authors: von Ostau Nicola E. , Martynov Aleksandr , Schreiber Janina , Wiesehöfer Marc , Hadaschik Boris A. , Temme Christian , Stang Andreas , Dankert Jaroslaw T. , Wiesehöfer Caroline , Wennemuth Gunther 
Published: January 2024

AbstractAlthough people are constantly exposed to phthalates little is known about the extent to which PAEs affect sperm. Most studies do not address changes at the single-cell level. Our study concentrated on the examination of donors who were assumed to have been exposed to high levels of phthalate under plateletpheresis. We used Computer-Assisted-Sperm-Analysis to study the association between the most potent phthalate, di-2-ethylhexyl phthalate, and a decrease in sperm motility. In an exploratory in vivo study, we investigated whether plateletpheresis of donors led to an increase in the concentration of active metabolites of DEHP in seminal plasma and whether this had an effect on sperm motility. PAE metabolites and sperm motility parameters of ejaculate donors were analyzed at a single-cell level before and after plateletpheresis. We found an increase in PAE metabolite concentration in the seminal plasma, associated with a decrease in flagellar beat frequency after plateletpheresis. Follow-up analysis showed that this was a transient effect of plateletpheresis in terms of a PAE concentration increase in seminal plasma and a decrease in sperm motility. This study shows that plateletpheresis results in high levels of phthalate exposure and that these are associated with a transient and reversible decrease in sperm motility.
Two-Step Parameter Estimation for Read Feature Models
Authors: Erhard Florian 
Published: January 2024

AbstractOver the last two decades, the field of molecular biology has witnessed a revolution due to the development of next generation sequencing (NGS) technologies. NGS enables researchers to routinely generate huge amounts of data that can be used to pursue a large variety of questions in diverse biological systems. The development of these techniques has propelled the emergence of a sub-discipline within computational biology that is concerned with developing methods and statistical models to derive quantitative information from the complex and often indirect data that are generated by NGS. Often, NGS analysis results in particular patterns per biological entity that can be exploited to estimate quantitative parameters of biological interest. Here, I define read feature models (RFMs) as a general framework for such data. RFMs entail global, genome-wide parameters as well as parameters per biological entity, suggesting a two-step procedure for parameter estimation. I describe the analysis of metabolic RNA labeling data as an example of an RFM and analyze and discuss the merits and shortcomings of the two-step estimation.
Impact of differential torsional rotor cant on the flight characteristics of a passenger-grade quadrotor
Authors: Atci Kagan , Jusko Tim , Štrbac Alexander , Guner Feyyaz 
Published: January 2024

AbstractAt the Institute of Flight Systems at DLR, studies have been performed to understand the flight characteristics of novel eVTOL configurations. As part of these studies, previously conducted handling qualities assessments on a two-passenger generic quadrotor configuration had revealed major deficiencies about its yaw axis. Based on this result, the quadrotor model has been modified by differential torsional canting to improve its yaw characteristics. This paper analyzes the resulting impacts of such modification on the flight performance, dynamic stability and handling qualities. A piloted simulator test campaign was conducted to assess predicted and assigned handling qualities levels in compliance with the quantitative and qualitative performance standards of ADS-33E. The results show an improvement in midterm yaw response at the expense of increase in total required power. The pilot ratings and comments confirm the improvement on the yaw response upon the flown MTEs.
Decade Milestone Advancement of Defect-Engineered g-C3N4 for Solar Catalytic Applications
Authors: Hou Shaoqi , Gao Xiaochun , Lv Xingyue , Zhao Yilin , Yin Xitao , Liu Ying , Fang Juan , Yu Xingxing , Ma Xiaoguang , Ma Tianyi , Su Dawei 
Published: January 2024

AbstractOver the past decade, graphitic carbon nitride (g-C3N4) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C3N4 is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultra-active coordinated environment (M–Nx, M–C2N2, M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra (fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C3N4 “customization”, motivating more profound thinking and flourishing research outputs on g-C3N4-based photocatalysis.
Emissions from the Construction Sector in the United Kingdom
Authors: Desouza Carl , Marsh Daniel , Beevers Sean , Molden Nick , Green David 
Published: January 2024

AbstractThe UK national atmospheric emissions inventory estimates of construction industry emissions use a top-down approach, based on fuel consumption and employment. It estimates that the sector is the 2nd largest emitter of PM2.5 (14%) and 4th largest emitter of NOX (7%). In this study, we have adopted a bottom-up approach to assess emissions of NOX from the sector and show that emissions are 39% higher than the existing estimates. By developing a novel fleet turnover model to predict the population and emission standard of construction machinery up to 2025, we demonstrate a significant shift in the quantity and types of machines used. The overall uncertainty of the model was calculated to be 55%. Applying the estimated uncertainties to the model, in 2018, the non-road mobile machinery fleet in the UK emitted 36.6 ± 10.0 kilo-tonnes of NOX, whilst the NAEI estimated 33.2 kilo-tonnes for the same sector. For the subsequent years 2019 and 2020, the NAEI estimate was within the model’s uncertainty prediction—28.0 kilo-tonnes compared with 32.7 ± 8.9 kilo-tonnes for 2019 and 23.2 kilo-tonnes compared with 29.5 ± 8.1 kilo-tonnes for 2020. Overall, the size of the non-road mobile machinery fleet in the UK is predicted to reduce by 4% in 2025 compared to 2018. Furthermore, the introduction of Stages IV and V emission regulations for new machines will lead to a 58% reduction in fleet NOX emissions over the same period. These emission regulations are targeted at the larger, more polluting machines, with smaller machines not required to meet tighter emissions standards under Stage V. As a result, mini-excavators are the most common machines and consequently become the dominant source of NOX emissions from the fleet, contributing 55% in 2025. Therefore, tighter emissions regulations, or the uptake of battery power in the form of electrification, for these small machines would yield significant emissions reductions.
Graphical Abstract
Anthony V. Bouza and the Founding of Evidence-Based Policing
Authors: Sherman Lawrence W. 
Published: January 2024

AbstractAnthony V. Bouza (1928–2023) was a founding father of evidence-based policing. The first police chief to authorize a randomized controlled trial (RCTs) of arrest, he turned the Minneapolis Police Department (MPD) into a “crime lab’’ for what works in policing. In his 9 years as Chief, he sponsored the first RCTs done anywhere on such key topics as hot spot patrols, problem-oriented policing, neighborhood watch, and arrests for misdemeanor domestic assault. He also sponsored the first digital analysis of repeat call addresses, which found that 5% of the street addresses produced 64% of the calls for service (New York Times, Minneapolis study places origins of 911 calls, 1987). Taken together, these research projects formed a critical mass of knowledge for describing evidence-based policing as a framework for police reform (Sherman, Evidence-Based Policing, 1998).
FDrisk: development of a validated risk assessment tool for Fabry disease utilizing electronic health record data
Authors: Lobel Caryn J. , Laney Dawn A. , Yang Jingjing , Jacob David , Rickheim Amy , Ogg Carol Z. , Clynes Diana , Dronen Jessica 
Published: January 2024

AbstractPurposeFabry disease (FD) is a rare, X-linked, lysosomal storage disease characterized by great variability in clinical presentation and progressive multisystemic organ damage. Lack of awareness of FD and frequent misdiagnoses cause long diagnostic delays. To address the urgent need for earlier diagnosis, we created an online, risk-assessment scoring tool, the FDrisk, for predicting an individual’s risk for FD and prompting diagnostic testing and clinical evaluation.MethodsUtilizing electronic health records, data were collected retrospectively from randomly selected, deidentified patients with FD treated at the Emory Lysosomal Storage Disease Center. Deidentified, negative controls were randomly selected from the Fabry Disease Diagnostic Testing and Education project database, a program within the American Association of Kidney Patients Center for Patient Education and Research. Diagnosis of FD was documented by evidence of a pathogenic variant inGLAand/or an abnormal level of leukocyte α-Gal A. Thirty characteristic clinical features of FD were initially identified and subsequently curated into 16 clinical covariates used as predictors for the risk of FD. An overall prediction model and two sex-specific prediction models were built. Two-hundred and sixty samples (130 cases, 130 controls) were used to train the risk prediction models. One-hundred and ninety-seven independent samples (30 cases, 167 controls) were used for testing model performance. Prediction accuracy was evaluated using a threshold of 0.5 to determine a predicted case vs. control.ResultsThe overall risk prediction model demonstrated 80% sensitivity, 83.8% specificity, and positive predictive value of 47.1%. The male model demonstrated 75% sensitivity, 95.8% specificity, and positive predictive value of 75%. The female model demonstrated 83.3% sensitivity, 81.3% specificity, and positive predictive value of 45.5%. Patients with risk scores at or above 50% are categorized as “at risk” for FD and should be sent for diagnostic testing.ConclusionWe have developed a statistical risk prediction model, the FDrisk, a validated, clinician-friendly, online, risk-assessment scoring tool for predicting an individual’s risk for FD and prompting diagnostic testing and clinical evaluation. As an easily accessible, user-friendly scoring tool, we believe implementing the FDrisk will significantly decrease the time to diagnosis and allow earlier initiation of FD-specific therapy.
Supervised machine learning algorithms for predicting student dropout and academic success: a comparative study
Authors: Villar Alice , de Andrade Carolina Robledo Velini 
Published: January 2024

AbstractUtilizing a dataset sourced from a higher education institution, this study aims to assess the efficacy of diverse machine learning algorithms in predicting student dropout and academic success. Our focus was on algorithms capable of effectively handling imbalanced data. To tackle class imbalance, we employed the SMOTE resampling technique. We applied a range of algorithms, including Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), as well as boosting algorithms such as Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), and Light Gradient Boosting Machine (LB). To enhance the models' performance, we conducted hyperparameter tuning using Optuna. Additionally, we employed the Isolation Forest (IF) method to identify outliers or anomalies within the dataset. Notably, our findings indicate that boosting algorithms, particularly LightGBM and CatBoost with Optuna, outperformed traditional classification methods. Our study's generalizability to other contexts is constrained due to its reliance on a single dataset, with inherent limitations. Nevertheless, this research provides valuable insights into the effectiveness of various machine learning algorithms for predicting student dropout and academic success. By benchmarking these algorithms, our project offers guidance to both researchers and practitioners in their choice of suitable approaches for similar predictive tasks.
Introduction of AI-based sales forecasting: how to drive digital transformation in food and beverage outlets
Authors: Groene Nicole , Zakharov Sergii 
Published: January 2024

AbstractFood and beverage (F&B) outlets such as restaurants, delis and fast-food joins are commonly owner-operated small businesses with limited access to modern forecasting technologies. Managers often rely on experience-based forecasting heuristics, which face challenges, as demand is dependent on external factors such as weather conditions, holidays, and regional events. Introducing practical AI-based sales forecasting techniques is a way to improve operational and financial planning and automate repetitive forecasting tasks. This case study proposes an approach to work with F&B owners in creating and introducing machine learning (ML)-based sales forecasting tailored to the unique local aspects of the business. It enhances demand forecasting in the F&B domain by identifying data types and sources that improve predictive models and bolster managerial trust. The case study uses over 5 years of hourly sales data from a fast-food franchise in Germany. It trains a predictive algorithm using historical sales, promotional activities, weather conditions, regional holidays and events, as well as macroeconomic indicators. The AI model surpasses heuristic forecasts, reducing the root mean squared error by 22% to 33% and the mean average error by 19% to 31%. Although the initial implementation demands managerial involvement in selecting predictors and real-world testing, this forecasting method offers practical benefits for F&B businesses, enhancing both their operations and environmental impact.
Food Security: The impact of migrants and remittances in Sri Lanka
Authors: Jayaweera R. , Verma R. 
Published: January 2024

AbstractThe objective of this paper is to show that migrants and the subsequent remittances influence household food consumption in different ways. This paper contributes to the literature by developing an analytical framework to analyse how migrants and remittances need to be looked at separately in the migration/food security nexus. The multivalued treatment effect is used to analyse the model using the Sri Lankan household income and expenditure data (2016/17). The findings of this study shed light on areas where the government and policymakers should focus on improving the impact of migration and remittances on food security in Sri Lanka. The study's findings show that migrants and remittances affect food expenditure, calorie consumption dietary diversity in two distinct ways. Both migrants and remittances positively impact food expenditure and calorie consumption. However, remittances promote less healthy food consumption, while migrants promote healthy food consumption. Migrants and remittances jointly affect households to purchase and consume calories from expensive food. Remittances positively affect food diversity in terms of both expenditure and calorie consumption. However, migrants positively affect only expenditure-based food diversity.
Reconsidering reappraisal: in emotionally intense contexts, people choose distraction or minimizing over reconstrual to regulate others’ emotions
Authors: Xu Vicky , Double Kit S. , MacCann Carolyn 
Published: January 2024

AbstractPrior research has established that people use reappraisal to regulate others’ emotions in higher-emotional intensities but use distraction in lower-emotional intensities. However, research has not compared different reappraisal subtypes, such as reconstrual versus minimizing. In three pre-registered studies, participants completed a novel advice-giving task where they selected regulation strategies (distraction, reconstrual, or minimizing) to help a ‘partner’ who was ostensibly experiencing stimuli of differing emotional intensities and types (the partner was, in fact, non-existent). In Experiment 1, participants selected reconstrual over distraction significantly more for low versus high intensity stimuli. In Experiment 2, participants showed no significant preference for minimizing over distraction on low versus high intensity stimuli. In Experiment 3, participants selected reconstrual over minimizing significantly more on low versus high intensity stimuli. Results indicate that previous findings regarding the effect of emotional intensity on ‘reappraisal’ preference are limited to reconstrual and may not generalize to other reappraisal subtypes (i.e., minimizing) which require lower cognitive costs and emotional engagement with the stimuli.
Geography is not destiny: A quantitative test of Diamond's axis of orientation hypothesis
Authors: Chira Angela M. , Gray Russell D. , Botero Carlos A. 
Published: January 2024

Abstract
Jared Diamond suggested that the unique East–West orientation of Eurasia facilitated the spread of cultural innovations and gave it substantial political, technological and military advantages over other continental regions. This controversial hypothesis assumes that innovations can spread more easily across similar habitats, and that environments tend to be more homogeneous at similar latitudes. The resulting prediction is that Eurasia is home to environmentally homogenous corridors that enable fast cultural transmission. Despite indirect evidence supporting Diamond's influential hypothesis, quantitative tests of its underlying assumptions are currently lacking. Here we address this critical gap by leveraging ecological, cultural and linguistic datasets at a global scale. Our analyses show that although societies that share similar ecologies are more likely to share cultural traits, the Eurasian continent is not significantly more ecologically homogeneous than other continental regions. Our findings highlight the perils of single factor explanations and remind us that even the most compelling ideas must be thoroughly tested to gain a solid understanding of the complex history of our species.