bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term health effects of a third-generation waste-to-energy plant: the experience of Turin (Italy)
Authors: Gandini Martina , Farina Elena , Bena Antonella , Ivaldi Cristiana , Crosetto Laura 
Published: January 2025

Abstract
The long-term study on adverse health effects of the third-generation waste-to-energy (WTE) plant located in Turin, Italy, is part of a broader health surveillance system. We considered 369 236 subjects living in areas with different levels of emission fallout, as well as a control group, from 1 January 2014, until the end of the follow-up period. Hospital admissions for cardiac diseases (ICD-IX: 390–429), ischaemic heart diseases (ICD IX: 410–414), chronic heart failure (ICD IX: 428.0, 428.2, 428.9), cerebrovascular diseases (ICD IX: 430–438), acute respiratory diseases (ICD IX: 460–466, 480–487), and COPD (ICD IX: 490–492, 494, 496) were evaluated for the population considered. Cox models were used, considering individual characteristics and overall environmental exposure. We also considered all births (n = 8296) of women residing in the area at the time of delivery during the study period. Log-binomial models were run separately for each outcome (sex ratio, multiple births, preterm births, on term low birthweight and small for gestational age births), adjusting for exposure to other pollution sources and maternal characteristics. Miscarriages were evaluated using hospital admissions registries. No relationship was found for the outcomes considered in the wider area, neither with hospital admissions nor with adverse reproductive outcomes. There is an association with chronic heart failure and ischaemic heart diseases in the maximum exposure area, but the small number of events suggests caution in interpreting this result. This study confirm results of other health surveillance lines, showing no evident harmful effects of the WTE plant.
Identification and segmentation of branch whorls and sawlogs in standing timber using terrestrial laser scanning and deep learning
Authors: Pehkonen Mika , Vastaranta Mikko , Holopainen Markus , Hyyppä Juha , Kukko Antero , Pyörälä Jiri 
Published: January 2025

Abstract
Gaining insight into the wood quality of standing timber could facilitate more precise utilization of wood material, thereby promoting a more sustainable use of forest resources. In this study, we utilized convolutional neural network–based object detectors to segment individual branch whorls and sawlog sections from images derived from terrestrial laser scanning (TLS) point clouds. TLS was employed to capture the point clouds of 479 Norway spruce sample trees (Picea abies (L.) H. Karst.) from 14 stands in southeastern Finland. Subsequently, the trees were harvested and the sawlogs measured with X-ray at an industrial sawmill. The convolutional neural network–based branch whorl detector was trained with 2D images of the stem sections of trees in the TLS point clouds from which the branch whorls were manually annotated. The sawlog section detector was trained with 2D TLS images of whole trees in which sawlogs were automatically annotated, using the sawmill measurements. Comparing the detections of the whorl detector with those of the X-ray measurements yielded a root-mean-squared error of 7.73 (64.41%) for the whorl count. Additionally, we conducted further comparison of the detections against a dataset in which the whorls were manually measured from the TLS images, resulting in a root-mean-squared error of 3.99 (20.60%). The detections made by the sawlog detector in the TLS images of whole trees were utilized to calculate the predicted log length and volume, which were then compared with the sawmill measurements of the reference logs. In this comparison, the root-mean-squared error of log length was 0.73 m (15.18%), and that of volume was 0.10 m3 (36.62%). The results indicate that the whorl detector can be utilized for extracting branching features of standing timber that can serve as predictors of the internal wood quality. However, directly depicting the internal knot structure with external branch whorl detections poses a challenge. Additionally, while the sawlog detector demonstrated moderate performance in sawlog segmentation, the accuracies of the predicted log length and volume were relatively weak. Nevertheless, we anticipate that deep learning–based approaches can enhance the autonomous characterization of standing timber, e.g. when laser scanners in harvesters become more commonplace.
Legitimating non-state actor engagement in global climate governance
Authors: Yang Hai , Walker Hayley 
Published: January 2025

Abstract
Our study examines how international organizations seek to legitimate non-state actor engagement to elite audiences, using the secretariat of the United Nations Framework Convention on Climate Change (UNFCCC) as an illustrative case. We employ the prism of legitimation, a process whereby international organizations justify their institutional designs, decision-making procedures and policy outcomes with a view to enhancing legitimacy. We unpack legitimation along two vectors: normative and operational. Normative legitimation seeks to justify a particular norm, while operational legitimation explains how the organization meets a norm—or why it fails to do so. The latter constitutes a blind spot in existing literature. Based on a qualitative analysis of official documents and interviews with UNFCCC secretariat officials, we present two findings. First, the secretariat has sought to justify the need for non-state actor engagement by accentuating its significance for procedural and performance legitimacy. Second, in response to contestation over its engagement practices, the secretariat advances operational claims. It has underscored multiple constraints to its agency, the tension between ever-rising audience demands and a finite supply of engagement opportunities, and a unique organizational environment. Our analysis highlights the need to recognize the complex operational realities international organizations face when making normative demands or gauging the appropriateness of global governance.
The US factor in Chinese perceptions of militarized artificial intelligence
Authors: Zeng Jinghan 
Published: January 2025

Abstract
Leading military forces around the world have expressed enormous interest in artificial intelligence (AI) due to its military potential. This policy paper examines Chinese perceptions of the military use of AI by studying Chinese-language scholarly materials. A key finding is that, while the Chinese strategic community has explored the military use of AI across various countries, the United States plays a central and unique role in shaping Chinese perceptions of militarized AI. The US serves as a global near-competitor, providing a benchmark for China to measure its own development and competitiveness. In addition, the US acts as a role model for the Chinese military to emulate in terms of its ideas, policies and practices. Consequently, American success in AI has become a primary source of anxiety among the Chinese strategic community, prompting self-reflection and accelerating the development of ambitious Chinese AI plans. Contrary to the popular narrative in Washington that China has already surpassed the US in the global AI race, Chinese discussions reveal considerable admiration for American AI leadership, with a focus on catching up rather than overtaking the US. This paper suggests that both the US and China need to play their parts in mitigating the risks of a global AI race.
Winnie Mice: A Chronic and Progressive Model of Ulcerative Colitis
Authors: Chieppa Marcello , De Santis Stefania , Verna Giulio 
Published: January 2025

Abstract
Recent trends show a continuous worldwide rise in the incidence of ulcerative colitis (UC), leading to increased interest in its etiology and pathogenesis, which is currently unknown. To gain a better mechanistic understanding of this disease, many mouse models have been developed over the last several years, with variations of dextran sodium sulfate administration representing the most widely employed. The Winnie mouse strain was created through elicited random mutations in Muc2, resulting in a progressive, chronic intestinal inflammation localized to the colon that worsens over time. Moreover, Winnie mice display immunologic and microbiota features that are similar to those that can be found in UC patients. Phenotypically, the presence, albeit rare, of rectal prolapse and other complications impacting quality of life can be observed in Winnie mice, as well as extraintestinal manifestations that are often associated with UC. While Winnie mice are currently less studied compared to other more established models of colitis, much has been discovered in the initial years of its use as a UC-like model. In summary, the use of Winnie mice adds to the growing armamentarium that is required to develop precision-based medicine for its future application in treating complex multifactorial diseases, such as UC.
Research on time series analysis of data products in electric power marketing management information platform based on recurrent neural networks
Authors: Wang Leilei , Zhu Pingfei , Liu Junyan , Wang Yukun , Bai Ling , Zhu Xinpo 
Published: January 2025

Abstract
The power marketing management information platform can promote the energy industry's decision-making ability for power marketing business and improve demand-side management. Due to the large number of power marketing users and heterogeneous data, traditional time series analysis methods are difficult to flexibly deal with this scenario, and deep learning methods based on feedforward neural networks have weak modeling capabilities for the time dimension of data, making it difficult to effectively use these data to support decision-making. To this end, this study proposes a new time series analysis model for the power marketing management information platform, which uses a recurrent neural network (RNN) enhanced by an attention mechanism. By integrating the long-term time dependency modeling capability of RNN and the adaptive extraction capability of the attention mechanism, the model can efficiently represent time series data. Experimental evaluation shows that our method greatly outperforms traditional models and achieves higher prediction accuracy on several key performance indicators.
Exhaust waste heat recovery system using thermoelectric generator: a prospective of novel simulation technique toward low-carbon technology
Authors: Kubenova Marzhan , Kuterbekov Kairat , Bekmyrza Kenzhebatyr , Kabyshev Asset , Kabdrakhimova Gaukhar , Atamurotov Farruh , Ibrahim Wubshet 
Published: January 2025

Abstract
This study numerically optimizes energy harnessing in vehicle engines using three heat exchanger fin designs: wall to wall, pyramid, and hexagonal. Two thermoelectric generator (TEG) array configurations are compared for electrical power generation. Results show the wall-to-wall fin provides the highest heat transfer, producing 161 W of power from 13 590.53 W of heat. Both TEG configurations generate similar output, with the series offering slightly higher voltage. The flow direction has minimal impact, but increasing the number of heat exchangers boosts efficiency. The total system output reaches 27 763.60 W with a four-parallel exchanger setup and an efficiency of 1.72.
Is Systemic Dissemination of BCG Following Neonatal Vaccination Required for Protection Against Mycobacterium tuberculosis?
Authors: Kollmann Tobias R , Amenyogbe Nelly , Schaltz-Buchholzer Frederik , Bæk Ole , Campbell James , Lynn David J , Campbell Anita J , Aaby Peter , Stabell Benn Christine , Netea Mihai G , Divangahi Maziar 
Published: January 2025

Abstract
Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) and is a leading cause of death. BCG is the only licensed TB vaccine. Preclinical studies have shown that in adults, intravenous administration of BCG improves protection against TB. We hypothesize that intradermal administration of BCG to the human newborn leads to low-grade BCG bacteremia and that this systemic dissemination improves protection against Mtb infection. This hypothesis is based on supporting observations including animal and human studies. It is a testable hypothesis and offers to deliver immediately actionable insight to advance the global efforts against TB.
Primary schools’ readiness for SARS-CoV-2 preventive measures in Maputo City, Mozambique: a cross-sectional study
Authors: Bauhofer Adilson Fernando Loforte , Pololo Ramígio , Chissaque Assucênio , Campos Fernanda , Ussivane Édio , António Luciana , Iahaia Fátima , Miranda Emerson , Gatambire Aline , Gonçalves Luzia , de Deus Nilsa , Inlamea Osvaldo 
Published: January 2025

Abstract

Background
To reduce the spread and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), schools implemented a series of non-pharmacological interventions such as handwashing stations and cleaning protocols. A baseline assessment of the available interventions and readiness scores for SARS-CoV-2 prevention was conducted in primary schools in Maputo City, Mozambique.

Methods
A cross-sectional study was conducted between August and October 2023. Data were collected using a semi-structured questionnaire that assessed the availability of preventive measures. Readiness scores were calculated, based on the relative frequency of available preventive measures against SARS-CoV-2, recommended by the government. Schools with readiness scores of 100% were considered ready.

Results
Of the enrolled schools, 60.6% (66/109) were from the public sector. The median readiness score for preventive measures against SARS-CoV-2 implemented in schools was 70%. Water was the most frequent available measure, with 98.2% (107/109). Ash/soap for handwashing (47.7% [52/109]) and functioning thermometers (31.2% [34/109]) were the least available measures. Private schools showed significantly higher readiness scores compared with public schools (p&lt;0.001).

Conclusions
Private compared with public schools had higher readiness scores for preventive measures against SARS-CoV-2 in Maputo City, Mozambique. These findings suggest a need for targeted interventions to improve readiness in public schools.
TLR7 responses in glomerular macrophages accelerate the progression of glomerulonephritis in NZBWF1 mice
Authors: Tanaka Reika , Murakami Yusuke , Ellis Dorothy , Seita Jun , Yinga Wu , Kakuta Shigeru , Kumano Keiki , Fukui Ryutaro , Miyake Kensuke 
Published: January 2025

Abstract
Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by the production of autoantibodies and damage to multiple organs. Glomerulonephritis, a manifestation involving glomerular deposition of immune complexes and complement components, significantly contributes to disease morbidity. Although the endosomal single-stranded RNA sensor TLR7 is known to drive glomerulonephritis by promoting autoantibody production in B cells, the contribution of macrophage TLR7 responses to glomerulonephritis remains poorly understood. Here, we have examined Tlr7‒/‒ NZBWF1 mice and found that TLR7-deficiency ameliorates lupus nephritis by abolishing autoantibody production against RNA-associated antigens, C3 deposition, and macrophage accumulation in glomeruli. Furthermore, TLR7 signaling increased CD31 expression on glomerular endothelial cells and Ly6Clow macrophages but not on T and B cells, suggesting that CD31 mediates TLR7-dependent migration of monocyte into glomeruli. Compared to their splenic counterparts, glomerular macrophages produced IL-1β in a TLR7-dependent manner. In addition, single cell RNA sequencing (scRNA-seq) of glomerular macrophages revealed that TLR7 signaling induced expression of lupus associated genes including those encoding Chitinase 3 like 1, ferritin heavy chain 1, IKKε, and complement factor B (CfB). Although serum CfB did not increase in NZBWF1 mice, TLR7-dependent CfB protein expression was detected in glomerular macrophages. In addition, TLR7 signaling promoted C3 cleavage and deposition predominantly on mesangial cells. These findings suggest that TLR7 responses in glomerular macrophages accelerates the progression of glomerulonephritis in NZBWF1 mice.
Therapeutic drug monitoring versus Bayesian AUC-based dosing for vancomycin in routine practice: a cost–benefit analysis
Authors: Claus Barbara O M , De Smedt Delphine , De Cock Pieter A 
Published: January 2025

Abstract

Background
AUC-based dosing with validated Bayesian software is recommended as a good approach to guide bedside vancomycin dosing.

Objectives
To compare treatment and vancomycin-associated acute kidney injury (AKI) costs between Bayesian AUC-based dosing and conventional therapeutic drug monitoring (TDM) using steady-state plasma concentrations of vancomycin administered as continuous infusion in hospitalized non-critically ill patients with severe Gram-positive infection.

Methods
A cost–benefit analysis presented as a return on investment (ROI) analysis from a hospital perspective was conducted using a decision tree model (TDM versus AUC-based dosing) to simulate treatment cost (personnel, serum sampling and drug cost), vancomycin-associated AKI risk and cost up to 14 days. ROI was calculated against AUC-based software cost. One-way and probabilistic sensitivity analyses (respectively OWSA and PSA) were performed to check for robustness.

Results
In base case, an overall cost per patient of €621.0 with TDM and €543.6 with AUC-based dosing resulted in a treatment saving of €77.4 per patient when applying AUC-based dosing. This saving against the software cost (€26.9/patient) generated an ROI per patient of €1.9 per invested € in software [€1.9 (95% CI 1.6–2.2) in PSA]. Enrolling 900 AUC-based dosed patients annually translated to a net saving of €45 469. Software break-even was reached after 313 patients. In OWSA, a higher AKI risk with TDM strongly contributed to a positive ROI.

Conclusions
AUC-based dosing appeared a cost-saving strategy compared with conventional TDM when applying base-case settings of vancomycin-associated AKI risk, treatment and AKI costs.
Genetic insights into the first detection of Paracoccus marginatus (Hemiptera: Pseudococcidae) in Australia
Authors: Yadav Sonu , Patel Shreya , Kithulgoda Sachinthi , Brown Haidee , Thistleton Brian 
Published: January 2025

Abstract
Species spread in a new environment is often associated with founders’ effect, and reduced effective population size and genetic diversity. However, reduced genetic diversity does not necessarily translate to low establishment and spread potential. Paracoccus marginatus Williams and Granara de Willink is a polyphagous pest that has invaded 4 continents in around 34 years. It was first detected in the Northern Territory, Australia in July 2023. Following this, we collected 45 specimens from 20 suburbs across 3 regions. Using mitochondrial cytochrome oxidase I and nuclear ribosomal RNA genes (18S and 28S), we examined molecular diagnostics robustness, genetic diversity, haplotype network, and demographics (Tajima D) of the recently detected Australian population. We compared our samples with publicly available sequences deposited on GenBank. All 3 genes were suitable for molecular diagnosis with a 100% identity score. For all 3 genes, we found low nucleotide diversity, haplotype diversity, and negative Tajima D in the newly detected P. marginatus population, suggesting a recent single founder event by a few individuals. Comparing our study’s sequences with global sequences showed low haplotype diversity, nucleotide diversity, and Tajima’s D, suggesting that despite low genetic diversity at the 3 genes, P. marginatus has successfully invaded South America, Africa, Asia, and Oceania. Our study highlights the role of demographic and life history traits in the species’ invasion success. We provide a baseline dataset from the first detection of P. marginatus in Australia. Further analysis of the spread can provide insights into invasive species’ adaptation in a novel environment.
Rare malignant ovarian tumors: a review
Authors: Ishikawa Mitsuya 
Published: January 2025

Abstract
There are many histologic types of gynecologic malignancies. I reviewed three rare ovarian tumor types that have poor prognoses. Ovarian mesonephric-like adenocarcinoma (MLA) is a newly described histological type known for its aggressive behavior. It is thought to arise from mesonephric duct remnants of the female genital tract and is typically associated with endometriosis. Although MLA has some similarities to endometrioid carcinoma, they have different prognoses. Recurrence of MLA is common, even in early stage cases, and distant metastases, especially in the lungs, are often seen. MLA is characterized by positive immunohistochemical-staining for TTF-1, GATA3, PAX2, and CD10, and negative staining for estrogen and progesterone receptors. Data on treatment for MLA are scarce, and further studies are needed. Adult granulosa cell tumors, the most common type of malignant ovarian sex cord-stromal tumors, have an indolent growth pattern. Chemotherapy, hormone therapy, and radiotherapy have all shown some efficacy. However, debulking surgery remains the most important treatment because tumor disruption or remnants are risk factors for recurrence. Late recurrence is also characteristic of this tumor. Malignant transformations of mature teratoma are suspected when the patient is relatively old and the tumor is large. Squamous cell carcinoma is the most common somatic malignancy. Treatment must be tailored to the transformed histology. Chemotherapy and radiation have shown some efficacy; however, the prognosis is extremely poor in advanced cases. Because these three types of ovarian tumors are rare, research on possible treatments has been difficult, but recent significant advances in drug therapy are expected to lead to the development of effective treatments.
Evaluating treatment effect modifiers using data from randomized two-sequence, two-period crossover clinical trials: application to a diabetes study
Authors: Emoto Ryo , Igeta Masataka , Matsui Kota , Ishii Kiyoaki , Takamura Toshinari , Matsui Shigeyuki 
Published: January 2025

Abstract
Type 2 diabetes is known as a heterogeneous disease with diverse pathophysiology. The identification of treatment effect modifiers for personalized medicine, however, has been difficult in basic research due to complex biological mechanisms related to various genetic and nongenetic factors, and in clinical research due to confounding bias and limited sample sizes. In this paper, we focus on a two-sequence, two-period crossover (CO) clinical trial of type 2 diabetes with baseline markers as a new strategy for analyzing treatment effect modification that allows confounding elimination and efficiency enhancement by within-patient treatment comparison. We provide a framework for statistical analysis of treatment effect modification and develop methods for testing for treatment effect modification and estimating individualized predictors of treatment differences in the CO trial with limited sample size. Numerical assessments showed that the efficiency of the proposed CO analysis was substantially higher than the standard analysis based on parallel-group comparison in these analyses. Application to the diabetes trial showed that markers based on gene expression in peripheral blood cells before pharmacological treatment significantly modified the effect of the treatment on the response and that marker-based predictors produced two subgroups of patients for whom different treatments should be recommended.