bluuebunny/crossref_metadata_2025_split huggingface dataset:
An accumulation rate curve estimator for total species
Authors: Shestopaloff Konstantin 
Published: February 2025

Abstract
In this paper we present a total species estimator based on modelling the rate of change of a species accumulation curve (SAC). The proposed approach calculates an accumulation rate curve (ARC) for new species conditional on observed data and extrapolates it using parametric functions with varying rates of decay. The curve fits are integrated to obtain estimates for undetected species and a weighted estimate is calculated by optimizing a loss function subject to a set of restrictions. Confidence intervals are evaluated using a parametric bootstrap of aggregate counts, with the underlying count covariances estimated from a regularized mixture distribution fit to observed count data. A data smoothing technique and adjusting for bias are also discussed. The method is tested using a simulation study and applied to two example datasets. The results indicate that the proposed method is robust in a majority of cases and outperforms existing methods in bias and mean squared error. Performance is especially improved when the proportion of unobserved species is high. Confidence interval coverage is noticeably better compared to existing methods and conservative interval widths are maintained. The smoothing technique is also shown to be effective in reducing mean squared error under certain conditions.
Fast, Verified Computation for HOL ITPs
Authors: Abrahamsson Oskar , Myreen Magnus O. , Norrish Michael , Kanabar Hrutvik , Pohjola Johannes Åman 
Published: February 2025

Abstract
We add an efficient function for computation to the kernels of higher-order logic interactive theorem provers. First, we develop and prove sound our approach for Candle. Candle is a port of HOL Light which has been proved sound with respect to the inference rules of its higher-order logic; we extend its implementation and soundness proof. Second, we replicate our now-verified implementation for HOL4 with only minor changes, and build additional automation for ease of use. The automation exists outside of the HOL4 kernel, and requires no additional trust. We exercise our new computation function and associated automation on the evaluation of the CakeML compiler backend within HOL4’s logic, demonstrating an order of magnitude speedup. This is an extended version of our previous conference paper [2], which described implementation and soundness proofs for Candle. Our HOL4 implementation and automation are new, as are the CakeML benchmarks.
What Determines Cartel Duration? Global Evidence Using Quantile Regression Analysis
Authors: Polemis Michael L. 
Published: February 2025

Abstract
The longevity of cartels has been a highly contested topic among economists and policymakers, with numerous researchers arguing that cartels are inherently unstable, and their endurance is usually short-lived. Understanding the main factors that influence cartel duration is essential from a managerial point of view let alone the competition policy perspective. The present paper employs quantile regression techniques thus allowing for a more thorough and precise depiction of the data in terms of estimations compared to the traditional OLS analysis. The empirical findings support that the number of cartelists imposes an asymmetric effect, reducing (increasing) the lifespan of collusion only in the short (long)-lived cartels. Operating internationally and having a third-party facilitator both lengthen cartels, but the magnitudes of these effects decline monotonically over the range of the distribution. Relative to price-fixing, bid-rigging lengthens cartels in the bottom 20% of the distribution but has no significant effect elsewhere. Finally, the institutional effect such as the prevalence of leniency programs appears to have no significant effect on cartel duration, except at the very bottom of the distribution where the effect is small in magnitude. The results survive robustness checks addressing endogeneity and reverse causality.
Local inequality and crime: New evidence from South Africa
Authors: Büttner Nicolas 
Published: February 2025

Abstract
This paper investigates the relationship between socio-economic inequalities of various dimensions and crime at the local level in South Africa. It uses a novel panel dataset of police precincts that combines crime records from the South African Police Service with socio-economic data from two population censuses and household surveys. The identification exploits variation of inequality and crime across time and space, controlling for socio-economic and demographic characteristics of police precincts, province-specific time trends, police cluster-fixed effects, and spatial correlations. I find robust evidence for a significant, positive, and linear relationship between income inequality within precincts and local rates of violent crime, and an inverted u-shaped relationship with property crime. Education and housing inequality and racial heterogeneity are also positively correlated with crime. While inter-racial inequality contributes more to property crime, intra-racial inequality contributes more to violent crime. Richer precincts display higher property crime rates as compared to their poorer neighbors.
Enriching the Existing Knowledge About Co-creation: Identifying Dimensions of Co-creation Using Explicit Theory in Various Research Fields
Authors: Messiha Katrina , Altenburg Teatske M. , Giné-Garriga Maria , Chastin Sebastien , Chinapaw Mai J. M. 
Published: February 2025

Abstract
Despite increasing popularity of co-creation approaches across various types of co-creation (e.g., value co-creation) and research fields, systematic and effective theory-building of co-creation research is generally lacking. We explored co-creation literature underpinned by explicit theory, taking a hybrid approach by combining a narrative literature review of studies in various research fields and a systematic literature review of studies in the field of public health. Subsequently, we identified common dimensions applied to the co-creation process across various types of co-creation and research fields, in performing an inductive thematic analysis. Across the total 27 articles included as part of the narrative and systematic review, we identified 5 dimensions related to the co-creation process applied across 9 research fields: (1) Multi-stakeholder collaborative action; (2) Process of co-learning towards innovation; (3) Contextual knowledge production; (4) Generating meaning; and, (5) Open, trustful and inclusive dialogue. The findings offer renewed insight into the common dimensions of the co-creation process, with underpinning explicit theories across various types of co-creation and research fields. A clear and consistent definition of co-creation was often lacking, especially in the field of public health. We strongly emphasise the need for research to adopt a multi-dimensional approach to the co-creation process—as well as to work towards developing a common language around co-creation, which involves operationalising these identified five dimensions.
The syntax of Philippine-type alignment: Insights from case-marking
Authors: Chen Victoria 
Published: February 2025

Abstract
Despite the apparent hallmarks of syntactic ergativity found in Philippine-type Austronesian languages, a closer look at the distribution of three basic case markers reveals that their ergative characteristics are only illusory. Support for an accusative view firstly comes from the presence of the putative oblique case on ECM subjects, derived objects, and objects inside restructuring infinitives—a distribution that undermines the antipassive view of Philippine-type Actor Voice, indicating instead that the alleged antipassive features accusative object and does not alternate transitivity based on voice. Further evidence comes from the locality-constrained distribution of the putative inherent ergative case, which shows hallmarks of structural nominative and suggests that the extraction restriction imposed on these languages is distinct from the ban on ergative extraction. Finally, the nonlocal distribution of the so-called absolutive case reveals that it is a marker independent of case, in line with recent Ā-topic approaches to this marker. These observations motivate the view that ‘Philippine-type alignment’ reflects a nominative-accusative case system obscured by prominent topic-marking that overrides morphological case. This conclusion lends new support to the accusative view of Philippine-type languages and yields two implications: (i) highly constrained Ā-extraction asymmetry may be independent of syntactic ergativity, and (ii) discourse-configurational languages such as Philippine-type Austronesian languages may exhibit superficial traits of syntactic ergativity where topic-marking is imprecisely treated as part of their case system.
In season estimation of economic optimum nitrogen rate with remote sensing multispectral indices and historical telematics field-operation data
Authors: Abdipourchenarestansofla Morteza , Piepho Hans-Peter 
Published: February 2025

Abstract
Accurate estimation and spatial allocation of economic optimum nitrogen (N) rates (EONR) can support sustainable crop production systems by reducing chemical compounds to be applied to the ground while preserving the optimum yield and profitability Smart Farming (SF) techniques such as historical precision agriculture (PA) machinery data, satellite multispectral imagery, and on-machine nitrogen adjustment sensors can bring together state-of-the-art precision in determining EONR. The novelty of this study is in introducing an efficient optimization framework using SF technology to enable real-time and prescription based EONR application execution. An optimization strategy called response surface modelling (RSM) was implemented to support decision making by fusing multiple sources of information while keeping the underlying computation simple and interpretable. Here, a field of winter wheat with an area of 7 ha was used to prove the proposed concept of determining EONR for each location in the field using auxiliary variables called multispectral indices (MSIs) derived from Sentinel 2. Three different image acquisition dates before the actual N application were considered to find the best time combination of MSIs along with the best MSIs to model yield. The best MSIs were filtered out through three phases of feature selection using analysis of variance (ANOVA), Lasso regression, and model reduction of RSM. For the date 2020.03.25, 14 out of 21 MSIs exhibited a significant interaction with the N applied as determined through an on-machine N sensor. For dates 2020.03.30 and 2020.04.04, the numbers of significant indices were identified as 6 and 10, respectively. Some of the MSIs were no longer significant after five days of the growth period (5-day interval between Sentinel 2 revisits). The best model demonstrated an average prediction error of 14.5%. Utilizing the model’s coefficients, the EONR was computed to be between 43 kg/ha and 75 kg/ha for the target field. By incorporating MSIs into the fitted model for a given N range, it was demonstrated that the shape of the yield-N relation (RSM) varied due to field heterogeneity. The proposed analytical approach integrates farmer engagement by participatory annual post-mortem analysis. Using the determined RSM approach, retrospective assessment compares economically optimal N input, based on observed MSIs values to each location, with the actual applied rates.
Secret Two-Part Tariffs and Retailer Risk Aversion
Authors: Lømo Teis Lunde 
Published: February 2025

Abstract
This paper studies a manufacturer that offers secret two-part tariffs to multiple retailers that compete in prices. Prior work on this setting has shown that, in equilibrium, wholesale prices equal marginal cost and profits vanish as retailers become undifferentiated. I extend the prior work by introducing demand uncertainty and downstream risk aversion. I show that if merely a single retailer is risk averse, all wholesale prices will lie above marginal cost. Intuitively, the manufacturer provides insurance to the risk-averse retailer by reducing its fixed fee and increasing the wholesale price above cost. The positive upstream margin in turn induces the manufacturer to divert sales toward the risk-averse retailer, which it does by increasing wholesale prices for the risk-neutral retailers as well. Relatedly, downstream risk aversion can increase industry and upstream profits compared to risk neutrality if retailers are close substitutes.
A novel geo-independent and privacy-preserved traffic speed prediction framework based on deep learning for intelligent transportation systems
Authors: Akin Murat , Canbay Yavuz , Sagiroglu Seref 
Published: February 2025

Abstract
Intelligent transportation systems (ITS) involve collecting, storing, and delivering real-time traffic data to optimize efficiency, enhance transportation safety, and reduce energy consumption by integrating advanced electronics, information systems, and telecommunication technologies into roads, vehicles, and related infrastructure. These systems typically use some indicators such as speed, flow, and density to predict traffic information, which are measured by geographically fixed-position sensors located on the roads. Privacy leakage is a major problem since traffic information derived from users’ or vehicles’ mobility data contains sensitive information. Consequently, existing approaches are constrained by geographical dependencies, restrictions and privacy vulnerabilities. This study introduces a state-of-the-art, privacy-preserving, feature engineering-based, geo-independent traffic speed prediction framework to address these challenges for the first time. The framework, evaluated using performance metrics such as mean absolute error (MAE), mean absolute percentage error (MAPE), mean square error (MSE), and root-mean-square error (RMSE) on a real-world dataset, was implemented using long short-term memory, bidirectional long short-term memory, gated recurrent unit (GRU), linear regression, support vector regression, multilayer perceptron and random forest regression, and differential privacy with varying epsilon values. According to the results, GRU yielded the most favorable outcome with MAE of 7.7, MAPE of 28.5%, MSE of 132.7, and RMSE of 11.5 for Istanbul, MAE of 9.7, MAPE of 17.2%, MSE of 177.4, and RMSE of 13.2 for Eskisehir, and MAE of 3.1, MAPE of 5.4%, MSE of 12.4, and RMSE of 3.4 for Konya Roads with the epsilon value of 200, respectively. These findings highlight the framework’s potential to advance privacy-aware traffic management and urban mobility solutions, offering a transformative approach for ITS applications.
Daytime sleepiness estimated using the Karolinska Sleepiness Scale during mandibular advancement device therapy for snoring and sleep apnea: a secondary analysis of a randomized controlled trial
Authors: Marklund Marie , Carlberg Bo , Forsgren Lars , Rietz Helene , Olsson Tommy , Franklin Karl A 
Published: February 2025

Abstract

Purpose
The effect of mandibular advancement device therapy on daytime sleepiness remains unclear. Here, we evaluate the effect of a mandibular advancement device on daytime sleepiness using the Karolinska Sleepiness Scale.

Methods
We randomized 88 snoring patients with an apnea-hypopnea index < 30 and daytime sleepiness to a mandibular advancement device or a sham device for four months. The Karolinska Sleepiness Scale, which measures grades of sleepiness from 1 (very alert) to 9 (very sleepy), was used for seven consecutive days, four times each day. The results were analyzed with quantile regression at quartiles controlling for baseline, age, body mass index (kg/m2), sex, apnea-hypopnea index, and full-time work.

Results
The Karolinska Sleepiness Scale score was lower with the mandibular advancement device than with the sham device at specific time intervals. The positive effect of mandibular advancement device therapy occurred at wake up and before lunch during the whole week and before lunch on weekdays at the middle quartile. The adjusted differences between the interventions favored mandibular advancement device therapy by almost one unit and normalized the Karolinska Sleepiness Scale scores at wake up and before lunch. In addition, there were positive effects of mandibular advancement device therapy before dinner at the highest quartile during the whole week, on weekdays, and on the weekend.

Conclusion
Mandibular advancement devices used for snoring and sleep apnea reduce daytime sleepiness, particularly at wake up and before lunch, but provide some benefit before dinner.
Electronic Melting of Silicon in Nanostructures using X-ray Forbidden Bragg Reflections
Authors: Robinson Ian , Yang David , Wu Longlong , Kim Hyunjung , Ha Sung Soo , Choi Sungwook , Song Changyong , Hwang Junha , Heo Seung-Phil , Park Jaeku , Eom Intae , Kim Sunam 
Published: February 2025

Abstract
We carried out a short beamtime at the Pohang Accelerator Laboratory x-ray Free Electron Laser to perform a pump-probe (PP) laser excitation diffraction experiment on the silicon (222) forbidden Bragg peak. To limit the x-ray penetration, we used a “device layer” silicon film wafer bonded to a silicon substrate. The sample, specially fabricated by MEMC Electronic Materials, had a Si(100) substrate bonded to a 170 nm Si(100) film rotated at 45° for crystallographic isolation. A second sample was reactive-ion-etched down to 52 nm thickness. In the silicon lattice, the covalent bonds are seen exclusively at the 222 reflection. Upon laser excitation, these electrons are expected to be excited to the valence band on femtosecond electronic time scales. The Si(222) reflection is therefore expected to be extinguished on this fast time scale, while the electron–phonon coupled acoustic response is determined by the lattice dynamics. The latter is determined by the speed of sound over the device thickness, which is in the mid-picosecond range.
The comparison of endotracheal intubation and laryngeal tube insertion with face-to-face method in in-vehicle traffic accidents
Authors: Arslan Merve , Ekşi Ali 
Published: February 2025

Abstract
Emergency airway management is a critical focus in prehospital emergency healthcare. The right technique and the right equipment may increase survival. The study aimed to compare endotracheal intubation and laryngeal tube insertion with the face-to-face method in difficult conditions such as in-vehicle traffic accidents in which the injured person is trapped inside the vehicle. The population of the study, which was carried out as experimental research, consisted of emergency health workers currently working in Bursa 112 Ambulance Services (n: 383). The study compared two different airway applications with face-to-face techniques using a simulator mannequin. Data were collected between February and May 2023 and the IBM Statistical Package for Social Sciences for Windows (SPSS 25) computer program was used for statistical data analysis. The suitability of the numerical variables for normal distribution was tested by the Shapiro–Wilk test. Since the variables did not conform to the normal distribution, they were given as median (Q1–Q3) values. Participants’ preparation, implementation, and total times for ETI and LT were compared using the Wilcoxon test. The duration of face-to-face ETI and LT times were compared regarding participants' personal characteristics, experience status, and the training they received with the Mann–Whitney U test and the Kruskal–Wallis test. Categorical variables are given as number and percentage values. p < 0.05 was considered significant. In face-to-face endotracheal intubation, 24.3% of the participants were successful in the first attempt, 30% in the second attempt, 27.1% in the third attempt, 18.6% failed in all three attempts, and 38.6% performed esophageal intubation. 87.1% of the participants were successful in face-to-face laryngeal tube insertion in the first and 12.9% in the second attempt. The duration of face-to-face laryngeal tube placement was found to be significantly shorter than the duration of endotracheal intubation (p < 0.05). In face-to-face airway conduct, the length of endotracheal intubation time and the high risk of esophageal intubation make the laryngeal tube more advantageous than endotracheal intubation. Furthermore, the high number of attempts required for successful face-to-face endotracheal intubation may pose additional risks by causing destabilization in trauma patients requiring cervical stabilization.
Blacksmith’s house, wooden knives: why do legacy firms succeed in promoting digital outcomes but struggle with the digital transformation of their existing business models?
Authors: Franco Matheus , Quadros Ruy , Clauß Thomas , Minatogawa Vinicius 
Published: February 2025

Abstract
Although research recognizes that legacy firms struggle with digital transformation, frequently abandoning initiatives, the underlying mechanisms remain a black box. To tackle this issue, we adopt an Attention-based view lens and follow a multiple case study design with five Brazilian legacy firms as a methodological approach. We draw evidence from longitudinal data spanning six years (2016–2021), triangulating archival data from the companies’ annual reports with their websites and formal and informal interviews. Our findings reveal the interplay between attention shortsightedness, resulting in temporal myopia, and the mechanisms that we call the ‘spinning the slots’ for DT and ‘trendy decision-making’ to explain the procedural inconsistency. Therefore, we contribute to DT literature in several ways. First, we expand the DT literature by uncovering strategy-making mechanisms underlying legacy firms’ struggle with DT. Second, we challenge the overall positive vision of DT as an enabler of more rational strategic decision-making. We discuss that ambiguity and attention conflicts can lead to silos of garbage can decision-making, where DT can be a result of chance rather than increased rational decisions.
Analysis of Machine Learning Algorithms for the Computer Simulation of Moisture Sorption Isotherms of Coffee Beans
Authors: Collazos-Escobar Gentil A. , Gutiérrez-Guzmán Nelson , Váquiro Henry A. , García-Pérez José V. , Cárcel Juan A. 
Published: February 2025

Abstract
Digital twin–based machine learning (ML) techniques can improve the control of the storage conditions of dried products, strengthening the classical water sorption isotherm–based approach by including additional process variables. In this study, water sorption isotherms of dried parchment and green coffee beans were experimentally determined at 25, 35, and 45 °C using the dynamic dew point (DDI) method. Experimental data (both coffee bean types and temperatures) were simultaneously modeled by means of three ML techniques, support vector machine (SVM), random forest (RF), and artificial neural networks (ANN), with 75% of data used for model training and 25% for validation. The hyperparameters were identified by minimizing the mean square error (MSE). The ML model’s accuracy was addressed by a multiway ANOVA on the mean relative error (MRE), the coefficient of determination (R
2), and the computation time (CT). The sorption isotherms were significantly (p-value < 0.05) affected by the type of coffee and the temperature. The SVM model provided the best fit (MRE < 1% and R
2 > 99%) in a reasonable CT (< 13 s). These results revealed the potential of ML models as a robust tool for the fast prediction of the equilibrium moisture content, including additional variables such as the type of coffee stage (dried parchment or green) and temperature; this paves the way for their industrial-level implementation to assist storage management.