bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on influencing factors and optimization of carbon fiber wear resistance test
Authors: Li Wusheng , Meng Xiangshu , Qiao Rui 
Published: December 2023

Abstract
In order to accurately distinguish the wear resistance level of different carbon fibers including high strength fibers and high modulus fibers, and ensure minimal fluctuations in testing results, orthogonal tests are designed based on the testing method of carbon fiber wear resistance from the standard Q/ZHFC 4403-2014, and the influencing factors of wear resistance test is determined, and the corresponding test parameters were optimized by the error sum of squares. The results show that within a certain factor level, the traction tension, friction load, friction rod angle and the number of friction rods have a highly significant impact on the test results of fuzz mass, the traction speed has an impact on the test results, and the density of sponge sheet has no impact. When the traction tension is 25N, the friction load is 350g, the traction speed is 30m/min, and the sponge density is 2.28×10−2g/cm3, the angle of friction rod is 120°, the coefficient of variation of the fuzz mass test results is 2.9%~5.0%, which means the testing method with optimized parameters can accurately and quantitatively distinguish the wear resistance level of different brand carbon fibers.
FAIR AI models in high energy physics
Authors: Duarte Javier , Li Haoyang , Roy Avik , Zhu Ruike , Huerta E A , Diaz Daniel , Harris Philip , Kansal Raghav , Katz Daniel S , Kavoori Ishaan H , Kindratenko Volodymyr V , Mokhtar Farouk , Neubauer Mark S , Eon Park Sang , Quinnan Melissa , Rusack Roger , Zhao Zhizhen 
Published: December 2023

Abstract
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.
Small proteins in Gram-positive bacteria
Authors: Brantl Sabine , Ul Haq Inam 
Published: December 2023

Abstract
Small proteins comprising less than 100 amino acids have been often ignored in bacterial genome annotations. About 10 years ago, focused efforts started to investigate whole peptidomes, which resulted in the discovery of a multitude of small proteins, but only a number of them have been characterized in detail. Generally, small proteins can be either membrane or cytosolic proteins. The latter interact with larger proteins, RNA or even metal ions. Here, we summarize our current knowledge on small proteins from Gram-positive bacteria with a special emphasis on the model organism Bacillus subtilis. Our examples include membrane-bound toxins of type I toxin–antitoxin systems, proteins that block the assembly of higher order structures, regulate sporulation or modulate the RNA degradosome. We do not consider antimicrobial peptides. Furthermore, we present methods for the identification and investigation of small proteins.
Assessing the potential of synthetic and ex situ airborne laser scanning and ground plot data to train forest biomass models
Authors: Schäfer Jannika , Winiwarter Lukas , Weiser Hannah , Novotný Jan , Höfle Bernhard , Schmidtlein Sebastian , Henniger Hans , Krok Grzegorz , Stereńczak Krzysztof , Fassnacht Fabian Ewald 
Published: December 2023

Abstract
Airborne laser scanning data are increasingly used to predict forest biomass over large areas. Biomass information cannot be derived directly from airborne laser scanning data; therefore, field measurements of forest plots are required to build regression models. We tested whether simulated laser scanning data of virtual forest plots could be used to train biomass models and thereby reduce the amount of field measurements required. We compared the performance of models that were trained with (i) simulated data only, (ii) a combination of simulated and real data, (iii) real data collected from different study sites, and (iv) real data collected from the same study site the model was applied to. We additionally investigated whether using a subset of the simulated data instead of using all simulated data improved model performance. The best matching subset of the simulated data was sampled by selecting the simulated forest plot with the highest correlation of the return height distribution profile for each real forest plot. For comparison, a randomly selected subset was evaluated. Models were tested on four forest sites located in Poland, the Czech Republic, and Canada. Model performance was assessed by root mean squared error (RMSE), squared Pearson correlation coefficient (r$^{2}$), and mean error (ME) of observed and predicted biomass. We found that models trained solely with simulated data did not achieve the accuracy of models trained with real data (RMSE increase of 52–122 %, r$^{2}$ decrease of 4–18 %). However, model performance improved when only a subset of the simulated data was used (RMSE increase of 21–118 %, r$^{2}$ decrease of 5–14 % compared to the real data model), albeit differences in model performance when using the best matching subset compared to using a randomly selected subset were small. Using simulated data for model training always resulted in a strong underprediction of biomass. Extending sparse real training datasets with simulated data decreased RMSE and increased r$^{2}$, as long as no more than 12–346 real training samples were available, depending on the study site. For three of the four study sites, models trained with real data collected from other sites outperformed models trained with simulated data and RMSE and r$^{2}$ were similar to models trained with data from the respective sites. Our results indicate that simulated data cannot yet replace real data but they can be helpful in some sites to extend training datasets when only a limited amount of real data is available.
A method for identifying and segmenting branches of Scots pine (Pinus sylvestris L.) trees using terrestrial laser scanning
Authors: Yrttimaa Tuomas , Kankare Ville , Luoma Ville , Junttila Samuli , Saarinen Ninni , Calders Kim , Holopainen Markus , Hyyppä Juha , Vastaranta Mikko 
Published: December 2023

Abstract
Terrestrial laser scanning (TLS) has been adopted as a feasible technique to characterize tree stems while the characterization of trees’ branching architecture has remained less explored. In general, branching architecture refers to the spatial arrangement of branches and their characteristics that are important when exploring the eco-physiological functioning of trees or assessing tree biomass and wood quality. Our aim was to develop a point cloud processing method for identifying and segmenting individual branches from TLS point clouds. We applied a Cartesian-to-cylinder coordinate transformation and a simple morphological filtering for stem surface reconstruction and stem-branch separation. Then branch origins were identified as their intersections with the stem surface, and individual branches were segmented based on their connectivity with the branch origins. The method, implemented in MATLAB and openly available, was validated on a 0.4-ha mature and managed southern boreal forest stand. The branch identification performance was assessed based on visual interpretation of 364 randomly sampled stem sections from 100 Scots pine (Pinus sylvestris (L.)) trees that were inspected for branch identification accuracy. The results showed that the branches could only be identified up to the height where the stem could be reconstructed. For 90% of the trees, this threshold ranged between 59.3% and 81.2% relative tree heights. Branches located below this threshold were identified with a recall of 75%, a precision of 92%, and an F1-score of 0.82. Based on our study, it appears that in a managed Scots pine stand, most of the branches can be identified with the developed method for the most valuable stem part eligible for logwood. The findings obtained in this study promote the feasibility of using TLS in applications requiring detailed characterization of trees. The developed method can be further used in quantifying the characteristics of individual branches, which could be useful for biomass and wood quality assessment, for example.
Intellectual monopolies as a new pattern of innovation and technological regime
Authors: Rikap Cecilia 
Published: December 2023

Abstract
Building on Schumpeter Mark I and Mark II, I propose an additional pattern of innovation and technological regime called the intellectual monopoly (IM) to explain the co-habitation of large incumbent firms with high entry and exit rates and provide evidence for pharmaceuticals and information technologies. I associate the IM pattern and technological regime with corporate innovation systems and illustrate that patterns not only evolve after changes in technological regimes but also due to economic, political, and institutional transformations.
A glucagon-like peptide-1 receptor antagonist reduces the insulin response to a glycemic meal in ponies
Authors: de Laat Melody A , Fitzgerald Danielle M , Harris Patricia A , Bailey Simon R 
Published: December 2023

Abstract
High plasma concentrations of insulin can cause acute laminitis. Ponies and horses with insulin dysregulation (ID) exhibit marked hyperinsulinemia in response to dietary hydrolyzable carbohydrates. Glucagon-like peptide-1 (GLP-1), an incretin hormone released from the gastrointestinal tract, enhances insulin release, and is increased postprandially in ponies with ID. The aim of this study was to determine whether blocking the GLP-1 receptor reduces the insulin response to a high glycemic meal. Five adult ponies were adapted to a cereal meal and then given two feed challenges 24 h apart of a meal containing 3 g/kg BW micronized maize. Using a randomized cross-over design all ponies received both treatments, where one of the feeds was preceded by the IV administration of a GLP-1 receptor blocking peptide, Exendin-3 (9-39) amide (80 µg/kg), and the other feed by a sham treatment of peptide diluent only. Blood samples were taken before feeding and peptide administration, and then at 30-min intervals via a jugular catheter for 6 h for the measurement of insulin, glucose, and active GLP-1. The peptide and meal challenge caused no adverse effects, and the change in plasma glucose in response to the meal was not affected (P = 0.36) by treatment: peak concentration 9.24 ± 1.22 and 9.14 ± 1.08 mmol/L without and with the antagonist, respectively. Similarly, there was no effect (P = 0.35) on plasma active GLP-1 concentrations: peak concentration 14.3 ± 1.36 pM and 13.7 ± 1.97 pM without and with the antagonist, respectively. However, the antagonist caused a significant decrease in the area under the curve for insulin (P = 0.04), and weak evidence (P = 0.06) of a reduction in peak insulin concentration (456 ± 147 μIU/mL and 370 ± 146 μIU/mL without and with the antagonist, respectively). The lower overall insulin response to the maize meal after treatment with the antagonist demonstrates that blocking the GLP-1 receptor partially reduced insulin production in response to a high starch, high glycemic index, diet. Using a different methodological approach to published studies, this study also confirmed that GLP-1 does contribute to the excessive insulin production in ponies with ID.
A revised model of energy transactions and body composition in sheep
Authors: Oddy V Hutton , Dougherty James C H , Evered Mark , Clayton Edward H , Oltjen James W 
Published: December 2023

Abstract
A mechanistic, dynamic model was developed to calculate body composition in growing lambs by calculating heat production (HP) internally from energy transactions within the body. The model has a fat pool (f) and three protein pools: visceral (v), non-visceral (m), and wool (w). Heat production is calculated as the sum of fasting heat production (FHP), heat of product formation (HrE) and heat associated with feeding (HAF). Fasting heat production is represented as a function of visceral and non-visceral protein mass. Heat associated with feeding (HAF) calculated as ((1-km) x MEI, where km is partial efficiency of ME use for maintenance, and MEI = metabolizable energy intake) applies at all levels above and below maintenance. The value of km derived from data where lambs were fed above maintenance was 0.7. Protein change (dp/dt) is the sum of change in the m, v, and w pools, and change in fat is equal to net energy available for gain minus dp/dt. Heat associated with change in body composition (HrE) is calculated from change in protein and fat with estimated partial efficiencies of energy use of 0.4 and 0.7 for protein and fat respectively. The model allows for individuals to gain protein while losing fat, or vice versa.
When evaluated with independent data, the model performed better than the current Australian feeding standards (Freer et al., 2007) for predicting protein gain in the empty body but did not perform as well as well for gain of fat and fleece-free empty body weight. Models performed similarly for predicting clean wool growth. By explicit representation of the major energy using processes in the body, and through simplification of the way body composition is computed in growing animals, the model is more transparent than current feeding systems while achieving similar performance. An advantage of this approach is that the model has the potential for wider applicability across different growth trajectories and can explicitly account for the effects systematic changes on energy transactions, such as the effects of selective breeding, growth manipulation, or environmental changes.
Context Matters
Authors: Nuzban Yulia 
Published: December 2023

Abstract
In seven trials to date, the International Criminal Court (ICC) has relied on the expertise of historians, anthropologists and political scientists to provide historical and political context. Overview expert witnesses help the judges appreciate the evidence of charged crimes in a wider context of conflict and violence. In this article, I consider the fundamental purpose and factors militating in favour of engaging an overview expert. In addition, I first review and then reflect on the current use of overview expert evidence — as a subset of expert evidence — in ICC trials, to better understand its legal and practical utility in international crimes cases. I focus on four aspects: relevance in criminal proceedings, timing of engaging an expert, selection of experts and impact on the fairness of proceedings.
Principles-Focused Evaluation: A Promising Practice in the Evaluation of Continuing Professional Development
Authors: Parker Kathryn , Sud Abhimanyu 
Published: December 2023

Abstract:
Outcome-based evaluations still dominate in continuing professional development (CPD) despite the availability of evaluation approaches that address program processes and contexts. Our continued reliance on outcomes-based evaluation fails to respect the importance of complexity and the human element of program planning and implementation. Therefore, it is time that the field of CPD embrace complementary approaches to program evaluation that consider the complexity and maturity of programs and their contexts, while providing credible and relevant information to inform strategic decisions regarding the future of a program. Principles-focused evaluation provides a complement to traditional evaluation approaches through the articulation of a program's values that can be actioned. These “actionable values,” known as principles, become the focus of the evaluation for the purposes of program decision-making. This paper describes how one CPD program, designed as a response to growing opioid-related harms, adopted a principles-focused evaluation to inform ongoing iteration of the program. The process used to design the principles, how the principles are informing the transportability of the program, and implications for CPD evaluation are discussed.
Deep learning quantification reveals a fundamental prognostic role for ductular reaction in biliary atresia
Authors: Nyholm Iiris , Sjöblom Nelli , Pihlajoki Marjut , Hukkinen Maria , Lohi Jouko , Heikkilä Päivi , Mutka Aino , Jahnukainen Timo , Davenport Mark , Heikinheimo Markku , Arola Johanna , Pakarinen Mikko P. 
Published: December 2023

Background:
We aimed to quantify ductular reaction (DR) in biliary atresia using a neural network in relation to underlying pathophysiology and prognosis.

Methods:
Image-processing neural network model was applied to 259 cytokeratin-7–stained native liver biopsies of patients with biliary atresia and 43 controls. The model quantified total proportional DR (DR%) composed of portal biliary epithelium (BE%) and parenchymal intermediate hepatocytes (PIH%). The results were related to clinical data, Sirius Red–quantified liver fibrosis, serum biomarkers, and bile acids.

Results:
In total, 2 biliary atresia biopsies were obtained preoperatively, 116 at Kasai portoenterostomy (KPE) and 141 during post-KPE follow-up. DR% (8.3% vs. 5.9%, p=0.045) and PIH% (1.3% vs. 0.6%, p=0.004) were increased at KPE in patients remaining cholestatic postoperatively. After KPE, patients with subsequent liver transplantation or death showed an increase in DR% (7.9%–9.9%, p = 0.04) and PIH% (1.6%–2.4%, p = 0.009), whereas patients with native liver survival (NLS) showed decreasing BE% (5.5%–3.0%, p = 0.03) and persistently low PIH% (0.9% vs. 1.3%, p = 0.11). In Cox regression, high DR predicted inferior NLS both at KPE [DR% (HR = 1.05, p = 0.01), BE% (HR = 1.05, p = 0.03), and PIH% (HR = 1.13, p = 0.005)] and during follow-up [DR% (HR = 1.08, p<0.0001), BE% (HR = 1.58, p = 0.001), and PIH% (HR = 1.04, p = 0.008)]. DR% correlated with Sirius red–quantified liver fibrosis at KPE (R = 0.47, p<0.0001) and follow-up (R = 0.27, p = 0.004). A close association between DR% and serum bile acids was observed at follow-up (R = 0.61, p<0.001). Liver fibrosis was not prognostic for NLS at KPE (HR = 1.00, p = 0.96) or follow-up (HR = 1.01, p = 0.29).

Conclusions:
DR predicted NLS in different disease stages before transplantation while associating with serum bile acids after KPE.
Age-specific and sex-specific risks for HCC in African-born persons with chronic hepatitis B without cirrhosis
Authors: Kamal Habiba , Ingre Michael , Stål Per , Westman Gabriel , Bruce Daniel , Wedemeyer Heiner , Duberg Ann-Sofi , Aleman Soo 
Published: December 2023

Background:
The international recommendations of HCC surveillance for African-born persons with chronic hepatitis B (CHB) without cirrhosis are divergent, probably due to scarce data on incidence rate (IR) for HCC.

Methods:
We assembled a cohort with prospectively collected data of Swedish residents of African origin with diagnosed CHB without cirrhosis at baseline from 1990 to 2015. Data from nationwide registers were used to calculate the sex-specific IR and IR ratio (incidence rate ratios) in relation to age, comorbidities, and birth region, using a generalized linear model with a log-link function and Poisson distribution.

Results:
Among 3865 African-born persons with CHB without cirrhosis at baseline, 31 (0.8%; 77.4% men) developed HCC during a median of 11.1 years of follow-up, with poor survival after HCC diagnosis. The mean age at HCC diagnosis was 46.8 (SD±14.7; range 23–79) in men. HCC IR exceeded the recommended surveillance threshold of 0.2%/year at ages 54 and 59 years in men and women, respectively, and at ages 20–40 years if HCV or HDV co-infection was present. African-born men with CHB had an incidence rate ratios of 10.6 (95% CI 4.4–31.5) for HCC compared to matched African-born peers without CHB, and an incidence rate ratios of 35.3 (95% CI 16.0–88.7) compared to a matched general population.

Conclusions:
African-born men with CHB without cirrhosis reached an IR of 0.2%/year between 50 and 60 years, and at younger ages if HCV or HDV co-infection was present. Our findings need further confirmation, and new cost-effectiveness analyses specific for young populations are needed, to provide personalized and cost-effective HCC surveillance.
Design of dot-blot hybridization assay for simultaneous detection of Campylobacter jejuni and Campylobacter coli: a preliminary study
Authors: Bakhshi Bita , Shams Saeed , Rezaie Niloofar , Ameri Shah Reza Mahdieh 
Published: December 2023

Objectives:
Campylobacters are a major cause of gastroenteritis worldwide. These are fastidious in culture and false negative results are seen in many clinical laboratories. Among molecular methods, the dot-blot technique is widely used for a variety of purposes, especially diagnostics. So, the authors aimed to detect C. jejuni and C. coli simultaneously using a dot-blot assay.

Methods:
After evaluating the bioinformatics studies, a cadF-conserved fragment was selected for the design of primers and probe. DNAs from standard strains and a recombinant plasmid, prepared in this study, were used to assess the technique. The specificity of the method was also surveyed using DNAs from other enteric bacteria. The limit of detection was evaluated by recombinant plasmid and different concentrations of the designed probe.

Results:
A 95-bp fragment of cadF was selected, and in silico analysis studies showed that it is conserved between both species. Also, the non-specific annealing of the primers and probe with other bacteria was not seen theoretically. The technique with recombinant plasmid as well as DNAs of standard strains created black spots on the membrane, confirming that the probe was correctly synthesized. No non-specific reactions with other bacterial species were observed (specificity=100%). The limit of detection of the test was determined to be 50 µg/ml.

Conclusions:
This is the first study to simultaneously detect two important pathogens in the Campylobacter genus and was able to detect C. jejuni and C. coli with acceptable sensitivity and specificity.