bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of machine learning and process‐based model outputs via ensemble Kalman filter enhanced space–time modelling of soil organic carbon in a highly human impacted area
Authors: Xie Enze , Chen Jian , Peng Yuxuan , Yan Guojing , Zhao Yongcun 
Published: November 2024

AbstractAccurate prediction of soil organic carbon stock (SOCS) dynamics in areas with intensive human activities is crucial for developing sustainable soil management practices and climate change mitigation strategies. This study investigated the spatiotemporal dynamics of SOCS by collecting a total of 1219 topsoil samples in southern Jiangsu Province of China in 1980, 2000 and 2015, and compared the performance of three predictive models: random forest (RF), RothC, and a hybrid model of RF‐RothCEnKF. The hybrid model integrated outputs from the process‐based RothC model and the data‐driven RF model using the Ensemble Kalman Filter (EnKF) for sequential model state updates. Results showed that the three models presented similar spatial patterns of SOCS from 1980 to 2015, with relatively higher SOCS mainly distributed in the areas surrounding Taihu Lake. The mean SOCS change rates estimated by the RF‐RothCEnKF model represented an overall net increase of 0.04 t C ha−1 yr.−1 during that period. The RF‐RothCEnKF model exhibited high prediction accuracy, with an R2 of .52, a mean absolute error (MAE) of 7.38 t C ha−1, and a root mean square error (RMSE) of 9.13 t C ha−1 in 2015. This highlighted the RF‐RothCEnKF's ability to enhance performance when the individual RF model (R2 = .47, MAE = 7.66 t C ha−1, and RMSE = 9.42 t C ha−1) and the RothC (R2 = .13, MAE = 8.77 t C ha−1, and RMSE = 10.87 t C ha−1) fell short. Our findings may not only provide a framework for integrating process‐based and machine learning models to enhance the accuracy and adaptability of SOCS modelling in areas affected by intensive human activities, but also offer some guidance for developing sustainable agricultural practices and carbon management strategies in complex environmental settings.
Combined Molecular Mismatch Approaches to Predict Immunological Events Within the First Year After Renal Transplantation
Authors: Jäger Cäcilia , Niemann Matthias , Hönger Gideon , Wehmeier Caroline , Hopfer Helmut , Menter Thomas , Amico Patrizia , Dickenmann Michael , Schaub Stefan 
Published: November 2024

ABSTRACTSeveral molecular mismatch assessment approaches exist, but data on their combined use are limited. In this study, we aimed to define distinct risk groups for rejection based on the combination of three molecular mismatch assessment approaches (i.e., eplet mismatch count, the number of highly immunogenic eplets and PIRCHE‐II score) in 439 consecutive immunological standard risk transplantations. For each molecular mismatch assessment approach, ROC analyses were used to define cut‐offs for prediction of (sub) clinical rejection according to Banff 2019 classification within the first year post‐transplant as a reference. If all three scores were below the cut‐off, the patient was assigned to the low‐risk group (19% of patients); if all three scores were above the cut‐off, the patient was assigned to the high‐risk group (21% of patients). The one‐year incidence of (sub) clinical rejection was 12% in the low‐risk group and 33% in the high‐risk group (p = 0.003). Internal validation of the assigned risk groups for prediction of other outcomes revealed a high consistency: clinical rejection (6% vs. 24%; p = 0.004), ATG‐treated rejection (1% vs. 16%; p < 0.001) and development of de novo HLA‐DSA at 5 years post‐transplant (6% vs. 25%; p = 0.003). The molecular mismatch risk group was an independent predictor for (sub) clinical rejection (high‐risk vs. low‐risk: hazard ratio 3.11 [95%‐CI 1.50–6.45]; p = 0.002). We conclude that combining molecular mismatch approaches allows us to distinguish low‐ and high‐risk groups among standard renal allograft recipients. Independent validation in other patient populations and different ethnicities is required.
A Novel HLA Class I Allele, HLA‐C*12:424, Identified Using Next‐Generation Sequencing
Authors: Glover Jonathon , Hagerty Melanie , Pimpinella Eric , Carozza Carly , Berka Noureddine 
Published: November 2024

ABSTRACTDiscovery of a novel HLA class I allele, HLA‐C*12:424, identified using two NGS methods.
A Novel HLA‐DPA1*02 Variant, HLA‐DPA1*02:141, Identified in a Bone Marrow Donor Candidate From Brazil
Authors: Stelet Vinícius N. , Lemos Gabriela , Romero Matilde , Binato Renata , Abdelhay Eliana 
Published: November 2024

ABSTRACTIdentification of the novel HLA‐DPA1*02:141 allele that differs from HLA‐DPA1*02:02:02:01 at one position in exon 4.
Validation of pathogen reduced plasmas from maxi‐pools combined with fast thawing
Authors: Auvinen Marja‐Kaisa , Knutson Folke , Löf Helena 
Published: November 2024

AbstractObjectivesFast thawing for emergency situations and reduction of plasma wastage.BackgroundEvaluation of plasma units, pooled and pathogen reduced (PR) in “maxi‐pools” with amotosalen and UVA light, and fast thawing.Methods/MaterialsPer replicate, 10 WB‐derived leukocyte depleted plasma units were frozen within 24 h at ≤ −25°C and stored for 7 days. After thawing, a maxi‐pool was constituted from the 10 units. After splitting into 4 sub‐pools of 650 mL, the sub‐pools were PR treated then split into 3 units resulting in 12 PR plasma units at 200 mL. Hundred and twenty PR plasma units were produced in total. The units were frozen at ≤ −25°C for 1 week, then thawed either in a fast plasma thawer for 5 min or in other control devices (17 to 23 min). FVIII:C, Fibrinogen, albumin, IgG, protein S and VWF were measured in plasma units, maxi‐pools and plasmas after PR treatment and thawing.ResultsThere was a statistically significant (p < 0.001) but still clinically acceptable (over the recommended levels of ≥0.5 IU/mL and ≥2 g/L) reduction of FVIII:C and Fibrinogen after PR with 69% and 87% recovery, respectively. Other proteins were not significantly affected by the processes.ConclusionPooling 10 plasma units before the PR treatment standardises volume and protein content of plasma units. Besides the economic value of generating 12 products for transfusion, this procedure combined with a thawing time of about 5 min is of value in emergency situations and may reduce plasma wastage.
Tomato MADS‐RIN regulates GAME5 expression to promote non‐bitter glycoalkaloid biosynthesis in fruit
Authors: Xie Yinhuan , Xu Yaping , Jia Huimin , Wang Ke , Chen Siyu , Ma Ting , Deng Yuanwei , Lang Zhaobo , Niu Qingfeng 
Published: November 2024

SUMMARYA well‐known defense‐associated steroidal glycoalkaloid (SGA) metabolic shift eliminates the bitterness and toxicity of ripe tomato fruits. This study was conducted to clarify the effects of MADS‐RIN (RIN) and its cofactors on SGA metabolism in tomato fruits. Using a CRISPR/Cas9‐based gene‐editing system, we mutated RIN and two cofactor genes (FUL1 and FUL2). The observed changes to fruit color and size in the mutants reflected the overlapping and distinct effects of RIN, FUL1, and FUL2 on fruit ripening. According to a UPLC‐MS/MS analysis, the RIN and cofactor mutants had decreased levels of the relatively non‐toxic metabolite esculeoside A, but they accumulated toxic SGA pathway intermediates, suggesting RIN and its cofactors are directly involved in esculeoside A biosynthesis. Transcriptome and qPCR analyses detected the downregulated expression of GAME5, which encodes a key enzyme mediating esculeoside A biosynthesis. ChIP‐seq and ChIP‐qPCR analyses confirmed GAME5 is targeted by RIN. RIN was observed to activate GAME5 transcription by binding to two non‐canonical CArG‐boxes in the GAME5 promoter. Additionally, RIN promotes SGA metabolism independently of ethylene. Collectively, these findings enhance our understanding of the molecular mechanism governing tomato fruit ripening and SGA biosynthesis. Furthermore, they may be useful for improving tomato fruit quality and safety.
Splitting apheresis platelets as a contingency measure for inventory shortages
Authors: Rai Herleen , Forsythe Kyle , Smith Nyle , Smetana Heather , Neally Melissa A. , Marshall Christi , Francischetti Ivo M. B. , Ness Paul M. , Bloch Evan M. , Tobian Aaron A. R. , Crowe Elizabeth P. 
Published: November 2024

AbstractBackgroundSplitting apheresis platelet (PLT) units increase available inventory during shortages. The impact of prolonged storage in gas‐impermeable aliquot bags on PLT quality in vitro and transfusion outcomes in patients remains uncertain.Study Design and MethodsWe assessed in vitro PLT quality and thromboelastography (TEG) in PLTs stored for 8 or 24 h in aliquot bags compared with baseline (T0). Retrospective assessment of response (PLT increment and corrected count increment (CCI)) was conducted among adults (≥18 years) transfused with split platelet units from January 2021 to June 2022.ResultsNo differences were observed in PLT and white blood cell (WBC) counts, mean platelet volume, or TEG parameters during storage, except for an increase in TEG R time (mean ± SD) at 24 h (6.1 ± 0.5 min) compared to T0 (4.4 ± 0.8 min), p = 0.0031 one‐way ANOVA. Eighty‐one patients were transfused 119 split units with a median [IQR] PLT yield of 2.1 × 1011[1.9 × 1011 to 2.3 × 1011] and storage duration of 1.6[0.7–9.1] h. The overall median PLT count increment was 6.0 × 103/uL and CCI was 5.0 × 103, correlating negatively with split unit storage duration (Spearman rho = −0.218, p = 0.017). Compared with split transfusions of pathogen‐reduced (PR) PLTs, non‐PR splits were associated with higher median platelet count increments (7.0 × 103/μL vs. 4.0 × 103/μL, p = 0.0263 Mann–Whitney U) and higher CCIs (6.5 × 103 vs. 3.9 × 103, p = 0.0116 Mann–Whitney U) despite no differences in PLT yields (2.1 × 1011/μL vs. 2.1 × 1011/μL).DiscussionStoring PLTs in aliquot bags for 8 or 24 h does not adversely affect their quality in vitro. Splitting apheresis PLTs are feasible for adult transfusions during shortages. It may be advisable to prioritize non‐PR PLTs for splitting given improved patient responses.
Laboratory detection of donors implicated in transfusion‐transmitted malaria
Authors: Galel Susan A. 
Published: November 2024

AbstractBackgroundTransfusion‐transmitted malaria (TTM) is rare in non‐endemic areas (non‐EAs) but can potentially be fatal. This review analyzes the laboratory results of donors causing TTM in non‐EAs, to assess the detectability of their Plasmodium infection by molecular or antibody tests.Study Design and MethodsTTM cases in the United States, Canada, and Europe since 2010 were identified through a literature review. Authors and laboratories were contacted for missing details about sample types and laboratory methods. Results of Plasmodium polymerase chain reaction (PCR) and antibody tests were summarized.ResultsTwelve cases of TTM and one bone marrow transplant transmission were identified. Of the 13 source donors, 12 were tested by PCR, 10 were positive on at least one sample; the 2 negative donors were tested only on retained segments of blood refrigerated for several weeks. All donors were PCR positive on a fresh sample except one who was positive on a retained but not a fresh sample. These PCRs targeted Plasmodium DNA with sensitivities in the range of 1000–10,000 parasites/mL. Antibody EIA was positive in only three of seven donors tested.DiscussionThis review found that antibody EIAs failed to detect four of the seven TTM donors tested. DNA‐based PCRs were able to detect Plasmodium infection in all donors tested except for two tested only on samples likely to have deteriorated from prolonged storage. Recently developed ribosomal RNA‐based molecular donor screening assays are approximately 1000 fold more sensitive than these DNA‐based PCRs, holding promise as a potential method to further reduce TTM.
Hermitian metrics with vanishing second Chern Ricci curvature
Authors: Broder Kyle , Pulemotov Artem 
Published: November 2024

AbstractWe describe a rigidity phenomenon exhibited by the second Chern Ricci curvature of a Hermitian metric on a compact complex manifold. This yields a characterisation of second Chern Ricci‐flat Hermitian metrics on several types of manifolds as well as a range of non‐existence results for such metrics.
Analysis of Variable Renewable Energy and Reserve Margins
Authors: Licata Anthony , Kokkinos Angelos , Michell Frank 
Published: November 2024

Abstract
The variability and intermittency of the output from wind and solar generating facilities does not allow for consistent predictions of power generation that electric grid operators can use to ensure reliable and resilient electric service to meet the system demand. Dispatchability is commonly considered as the extent to which the resource (i.e., demand or supply resource) can be relied on to “follow a target” in relation to its load or generation. Variable renewable energy (VRE) or intermittent renewable energy sources (IRES) are renewable energy sources that are not dispatchable due to their fluctuating and intermittent nature, such as wind power and solar power, as opposed to dispatchable renewable energy sources such as hydroelectric, or fossil and nuclear baseloaded plants.
Flow Accelerated Corrosion Failures in Nominally Low-Risk HRSG Tube Locations
Authors: Fabricius A. , Malloy J. , Taylor M. , Vestdam Kasper D. , Rusaas Jan 
Published: November 2024

Abstract
Research on Flow Accelerated Corrosion (FAC) tends to be focused on the influence of water chemistry or material choices on the overall risk of pipe and tube wall thinning. Indeed, choosing a higher chromium (low alloy) material, e.g., P/T 11 or 22, tends to reduce wear rates to acceptable levels over the lifetime of the boiler, regardless of water chemistry regime. Some horizontal gas path Heat Recovery Steam Generator (HRSG) designs use low alloy material in Low-Pressure Evaporator (LP Evaporator) upper tube bends as these are considered to be at higher risk due to the geometry factor. Plants originally designed with carbon steel bends and suffering from FAC failures have replaced them with low alloy materials. Sometimes this was done with a so-called semi-harp replacement, including new bends and tube stubs, and this has been a popular solution. Although this prevents FAC in the tube bend there are several instances where it appears to continue to develop in the upstream straight carbon steel tubes below the low alloy section. This has resulted in failures on several units. This paper presents results from investigations into “straight tube FAC” including comparisons between units, computational fluid dynamics (CFD) simulations, and failure analyses. The case studies are from plants in the EMEA region, and all failure areas are located in the straight part of the tube, in the carbon steel region, upstream of low alloy tube sections. A FAC risk assessment would not show any particular risk of failures in this area given the low geometry factors. The results of the phenomena are discussed and recommendations for managing semi harp replacements are given.
An Analysis of Different Techniques for Cooling Direct Drive Generators
Authors: Hayes Austin C. , Whiting Gregory L. 
Published: November 2024

Abstract
Direct drive generators have become advantageous for wind turbines, especially offshore wind, due to their increased reliability and efficiency. Any type of generator must be adequately cooled in order to meet operating conditions preventing the degradation of copper winding insulation and thermal deflections. The amount of cooling is related to the current density of the coils at maximum loading conditions. This condition is set by the cooling technique as a more effective cooling technique allows a greater stator current density while achieving the desired temperature. In this work, four different cooling techniques for a 10 MW direct drive generator were assessed for maximum current density allowable within a class F insulation rating. These techniques included natural convection, forced convection, direct liquid cooling, and two-phase cooling. Machine parameters were compared between cooling techniques and a large drop in generator size and mass found as the heat transfer coefficient increased. For the same power rating and efficiency, the volume of the two-phase cooled stator was reduced by 40% compared to forced air convection. Discussion on the practical employment of each cooling technique was explored and simulations of temperatures within the stator given for each cooling technique. The current density and cooling technique influence on generator efficiency is discussed as well as implications for high power density offshore wind turbine generators.
Hyper-Parameter Optimization of Deep Learning Models for Compressor Air Leak Prediction in a Gas Turbine
Authors: Nogueras-Rivera Diego I. , Mojica-Vazquez Lemuel , Bonilla-Alvarado Harry , Bryden Kenneth M. , Tucker David , Traverso-Avilés Luis M. , Aponte-Roa Diego A. 
Published: November 2024

Abstract
Gas turbine systems are widely used in the power industry because they provide continuous and reliable power to the electrical grid. One of the main concerns for implementing gas turbine systems is the maintenance costs. Therefore, predictive maintenance methods driven by Deep Learning (DL) models present an opportunity to extract important information and knowledge from the process data to minimize maintenance costs and reduce equipment failure rates. A previous study aimed to benchmark various state-of-the-art DL models for predicting compressor air leak with multivariate time-series data from a modified recuperated gas turbine system. However, the brute-force approach used to select the hyper-parameters of the DL models could be improved. This paper aims to address the hyper-parameter optimization process of the best performers for predicting the next future time-step: GRU-LSTM, Sequential CNN-LSTM, and BI-LSTM. In addition, a BI-GRU model was implemented and a common grid search algorithm was combined with proposed algorithms for automating the selection of hyper-parameter values to build the DL models. The datasets were provided from experiments conducted at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL) Hybrid Performance (Hyper) Facility. Results suggest better performance can be obtained from the already good performing bench-marked models; however, reproducing the best results for some models may take more training cycles. The BI-GRU model exhibited the most reproducible results across all tests.
Analyzing the Operating Parameters of a Compression Ignition Diesel Engine Using Artificial Neural Network
Authors: Kakati Jyotirmoy , More Shubham M. , Pal Sukhomay , Saha Ujjwal K. 
Published: November 2024

Abstract
Fossil fuels are the primary source of energy to global industrialization and rapid development and are consumed at an alarming rate. This creates a dire need to develop alternative techniques for analyzing the operating parameters of compression ignition (CI) diesel engines. The traditional approach of experimenting, simulating, and optimizing the CI engine operating parameters is complex, time-consuming, and costly. This has led the researchers to shift their focus to agile and computationally economic techniques like soft computing (SC) for predicting the optimum performance with a substantial accuracy. Artificial neural network (ANN), one of the SC techniques, has proven to be a viable alternative to traditional experimental and simulation methodologies. The present research work mainly focuses on the implementation of ANN for the prediction of performance, combustion and emission parameters of a single-cylinder, four-stroke, water-cooled, variable compression ratio CI engine powered by the conventional diesel fuel. The ANN models have been developed to predict the brake power, brake thermal efficiency, brake specific fuel consumption, ignition delay, combustion duration, carbon monoxide, carbon dioxide and oxides of nitrogen. These models have been trained by considering a small sized dataset acquired by experimenting on a single-cylinder CI diesel engine and using different training algorithms namely Levenberg-Marquardt, Scaled Conjugate Gradient and Broyden-Fletcher-Goldfarb-Shanno. All the ANN models considered are found to predict the operating parameters with a low root mean squared error (RMSE) and correlation coefficient (R) greater than 0.9, thereby implying a high resemblance between the experimental and the predicted values. The present study demonstrates the prediction capabilities of various ANN models using the small datasets.
ADMS Technology: the Challenges of Modeling to Operating Electrical Systems With Digital Twins
Authors: Ruiz Flores Luis Ivan 
Published: November 2024

Abstract
In this article, we present the evolution of “off-line analysis”, associated with a single-line diagram, and its analysis in steady state, and transient state, towards an “online analysis” of the electric system model, with an interface for Provide users the ability to analyze with “Real-time technology”. In addition, the benefit of implementing this Real-Time Technology capable of monitoring, operating, managing the electrical network and performing analysis of the electrical system will be shown. In addition, it will show the relationship ADMS has with construction engineering, and what is sought from the design of the “electric model” to achieve the integration of systems. The opportunity to have an integrated and unified electric model in which it can be performed: state estimation and load distribution; monitoring and control; predictive simulation of the type “What would happen if?” Forensic analysis; contingency analysis; historical data and analytical tools; automated operation based on SCADA – Supervisory Control and Data Acquisition, DMS – Demand Management System, EMS – Energy Management System, EMCS – Energy Monitoring and Control System, PMS – Power Management System, SCMS – Substation Control and Monitoring System; and maintenance management of the electrical system.
The “Real-time Technology” is reflected by having a true ADMS, advanced distribution management system. The purpose of the article is to guide specialists and operators of electrical distribution systems, as well as dispatchers, planning engineers, reliability analysts and managers, in the implementation of ADMS with the possibility of integrating legacy and third-party software: creating a - digital twin - allowing from modeling to operation.
More Questions About Excellencism, Perfectionism, and Attitudes Toward Cheating in Professional Baseball: A Look at Potential Mediators and Doping Attitudes
Authors: Gaudreau Patrick , Boileau Laurence , Schellenberg Benjamin J.I. 
Published: November 2024

The Model of Excellencism and Perfectionism has been proposed to differentiate the pursuit of high but realistic standards (excellencism) from the pursuit of perfectionistic standards. In a recent study, perfectionistic standards were positively linked to bottom-line mentality, moral disengagement, and tolerance toward electronic sign stealing (cheating) in professional baseball. In this follow-up study, we investigated the reactions of sports fans when the Houston Astros qualified for the 2021 World Series of Baseball 2 years after being found guilty of cheating. We found that fans of the Astros (n = 202) displayed a higher tolerance toward cheating than those of the Atlanta Braves (n = 265). Results of multiple regression (controlling for in-group vs. out-group status) showed higher tolerance toward cheating and doping in perfection strivers compared with excellence strivers. A winning-at-all-cost mentality and moral disengagement mediated the relationships between perfectionism and cheating attitudes.