bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blueberry plants support a distinctive microbiome as a function of plant genetics and tissue
Authors: Giese Matteo , Stefani Erika , Larger Simone , Pindo Massimo , Farneti Brian , Ajelli Matteo , Cattani Monica , Delgado-Baquerizo Manuel , Giongo Lara , Coleine Claudia , Donati Claudio 
Published: December 2024

Abstract

Background
Fruits, such as blueberries, are critical for food production and ecosystem sustainability as they are largely consumed by humans and animals worldwide. The microbial communities (bacteria, archaea, and fungi) within and on the surface of these fruits play a key role in regulating food quality, alongside supporting crucial aspects of plant physiology and development. However, the specific factors shaping the microbiomes of blueberry fruits, as well as their relationship with other above-ground parts of the plant such as leaves and their stability over different years, remain poorly understood.
Results
We conducted a field experiment to characterize the taxonomic composition of fungal and bacterial communities colonizing the leaves and the surface and pulp of fruits on a collection of 10 different cultivars of blueberry over two consecutive years. We found that, independently from the sampling time, pulp of the fruit, surface and leaves harbors specific and distinct microbiomes. The major factor determining the structure of the microbiome of blueberry fruits and leaves was plant genetics, followed by tissue. We further identified the core microbiome for each plant tissue and demonstrated that core taxa account for the dominant fraction of the microbiota of each plant.
Conclusions
We showed that blueberries have a distinct microbiome associated with plant cultivar, and that this microbiome is consistent with time. We identified a tissue-specific core microbiome, with some genera shared among different tissues, and others consistently present only in specific tissues. As trade and production of blueberries is expanding globally, our results provide a foundation for advancing the development of targeted microbiome management strategies, with potential applications in enhancing plant health and productivity.
Temporal and spatial distribution, variability, and trend of hydroclimate in the Dabus River Basin Upper Blue Nile, Ethiopia
Authors: Tola Mekuria Tefera , Bekitie Kassahun Ture , Zeleke Tadesse Terefe , Anose Fikru Abiko 
Published: December 2024

Abstract

Background
High-resolution local scale climate research approach is very effective in examining the existing climate change and predicting its risk. Thus, this study investigated the hydroclimate distribution, variation, trend, and abrupt change points, and considered more than the climate normal time range (1981 to 2020) to determine the climate change of the Dabus River Basin. The study employed different statistical, parametric, and nonparametric modified trend tests, and exact changing point detecting models.
Results
The result found the basin received 57.7% of the annual rainfall in June, July, and August. The standard anomaly index (SAI) value indicates 1999 and 2000 were the wettest years whereas 1982,1983,1984,1986 and 2015 were the driest years in the area. The basin experienced very fluctuating rainfall for the last four decades. Peaks of Precipitation Concentration Index (PCI) were observed in the years 1987,1991, 2002,2003,2006, and 2011 which indicates the strong irregular distribution of rainfall. The annual mean rainfall and maximum temperature (Tmax) increased significantly (p < 0.05), whereas the annual mean minimum temperature (Tmin), river flow, and river runoff decreased. In Dabus the abrupt increasing change point of annual rainfall was observed in 1996 whereas Tmax in 1993 and 1997. The abrupt decreasing change point of Tmin, river flow, and river runoff was observed in 1987, 1998, and 1999, respectively.
Conclusions
The study found the climate change in the basin due to the significant increase in temperature with fluctuating rainfall distribution as well as reduction of river flow and runoff. This climate change could upset agriculture, electric power production, and water demand in the basin.
Dynamic Simulation and Experimental Verification of Foldable Thin-film Using ANCF
Authors: HUANG Zhuoran , CHENG Wei , Deng Zhiming 
Published: December 2024

Abstract

The lightweight and foldable characteristics of foldable thin-film structures align with the development trend of large-scale and lightweight spacecraft. Consequently, they are frequently employed in spacecraft components, including large antennas, sunshades, etc.In order to analyse the nonlinear properties of space thin-film origami structures, the dynamics of the thin-film and the crease is described based on experiments and numerical model . Specifically, the kinematic of space thin-film origami structures is described based on the Absolute Nodal Coordinate Formulation (ANCF). The crease is modeled by pre-configuration elements. The locking problem of the fully parameterized element is improved by applying a selective reduced integration method.The parameters of the film creases are identified based on the tensile experiments + Particle swarm optimization (PSO).A vision-based single crease unfolding experiment is constructed to verify that the simulation of film configuration changes during unfolding is consistent with the experiment.Additionally,the unfolding driving force is obtained by a multiple-creases unfolding tensile experiment. The comparison between the simulation and the experiment validate the simulation capability of the model applied to the unfolding process of complex film structures.This paper presents a more precise and systematic methodology for simulating thin-film unfolding process, which can be employed to inform the design and analysis of spatial thin-film structures.
Enhanced Antenna Design through Hyper parameter Optimization of Diverse Machine Learning Models Using Bayesian Optimization
Authors: Huang Chung-Hao , Ali Amir , Hsu Chang-Chen , Tsao Han-Hsing 
Published: December 2024

Abstract

This work investigates the use of machine learning (ML) models for microstrip patch antenna design optimization with Bayesian optimization. Based on datasets produced by CST Microwave Studio 2023 simulations, key antenna parameters, including resonance frequency, bandwidth, and return loss, were first predicted using Support Vector Regressor (SVR), k-Nearest Neighbor (KNN), and Gradient Boosting Regressor (GBR) models. With slot distance, patch length, and patch width as target parameters, pre-processing was used to transform CST output into structured input-output pairs in order to get the dataset ready for machine learning training. Extending this first method, we assessed ten machine learning models, each optimized with Bayesian hyperparameter tuning: SVR, KNN, GBR, Random Forest, XGBoost, Decision Tree, Stochastic Gradient Descent, Artificial Neural Network, Gaussian Process Regressor, and Linear Regression. By fine-tuning parameters like max_depth, n_estimator, Bayesian optimization greatly improved complicated models, lowering Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) while raising R2 scores. After optimization, the Random Forest and XGBoost models produced the best predicted accuracy, according to comparative data. To further enable real-time model training, testing, and performance visualization, a unique graphical user interface (GUI) was created, offering a useful tool for interactive antenna optimization. This system provides a solid basis for data-driven improvements in advanced engineering applications by showcasing how ML models combined with Bayesian tuning can successfully handle challenging antenna design problems.
The effect of preoperative body weight loss on 5-year bariatric surgery outcomes
Authors: Flores Lilliam , Andreu Alba , Olbeyra Romina , Cañizares Silvia , Claro Maria , Rios Jose , Molero Judith , Jimenez Amanda , Vidal Josep 
Published: December 2024

Abstract

Objectives This study aimed to evaluate the effect of preoperative total body weight loss (TBWL) following a structured 6-month lifestyle change program (LCP) on operation time, hospital stay, surgical complications, obesity-associated pathology remission, and the achievement and maintenance of BWL at 12 and 60 months post-bariatric surgery (BS). Methods This retrospective, single-center study analyzed patients undergoing primary BS between 2013 and 2014. Outcomes were compared between patients participating in the LCP (LCP group) and those receiving standard preoperative education (Control group: CG). Data collected included anthropometric measurements, obesity-related pathologies, surgical complications, and weight-related outcomes.
Results Among 340 BS procedures performed, 165 patients met the inclusion criteria, with 59 in the LCP group and 106 in the CG. The mean age was 47 (±11.6) years in the LCP group and 45 (±11.1) years in the CG with no significant differences in baseline clinical characteristics. At surgery, the LCP group showed significant weight reduction (-5.9 kg vs. -0.72 kg in controls, p = 0.008) and their BMI was significantly lower (46.55 vs. 49.47 kg/m², p = 0.002). Postoperatively, weight-related outcomes [BWL, BMI and TBWL] were better in the LCP group at 1 and 5 years. Additionally, patients achieved a preoperative TBWL >5% demonstrated a significantly lower weight and BMI, along with a higher postoperative TBWL. Surgical complications were minimal, with no significant differences in 30-day complication rates. We did not observe a greater resolution of comorbidities in patients who participated in the LCP or those who achieved a preoperative TBWL > 5%.
Conclusions while current evidence suggests that preoperative BWL provides short-term benefits, our data suggest this may also be the case for TBWL in the long-term. Further research is needed to fully elucidate the role of preoperative BWL in comorbidity resolution in BS patients.
Effect of heating medium and pressure on the set recovery and physicochemical properties of surface- compressed Chinese fir
Authors: Li Jing , Huang Rongfeng , Zhang Shuangbao 
Published: December 2024

Abstract

Pressurized heat treatment is an effective modification method for reducing the deformation recovery of compressed wood. In this study, the set-recovery behavior, physicochemical and mechanical properties were studied for Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) subjected to surface compression treatment followed by pressurized heat treatment. The surface compression of wood was conducted in an open hot press with compression ratio of 33%, followed by pressurized heat treatment at 180℃ with different heating medium (nitrogen, steam, and nitrogen-steam mixed gas) under varying pressures of 0.1 MPa, 0.3 MPa, and 0.5 MPa. The resulted showed that the compressed layer density, the modulus of rupture (MOR), and the modulus of elasticity (MOE) of surface-compressed wood increased by about 55.56%, 56.60% and 30.90%, respectively, compared with the uncompressed wood. At a higher heating medium pressures of 0.5 MPa with steam, the set-recovery of surface-compressed (SC) wood induced by immersion and boiling in water were reduced by 88.03% and 70.11%, respectively, compared to the SC wood without pressurized heat treatment. Under the same medium pressure, SC wood treated with steam exhibited reduced set recovery than that treated with nitrogen and a nitrogen-steam mixed gas. It should be noted that incorporating nitrogen as a heating medium during the steam heat treatment process can reduce educe surface discoloration and improve mechanical properties while permanently fixing more than 70% of the compressive deformation of wood.
Short-Term Load Forecasting for Smart Grid based on Bidirectional-LSTM Recurrent Neural Network
Authors: Zafar Saima , Hashmi Shahwaiz Ahmed , Ayub Rana Hamza , Farooq Hasan 
Published: December 2024

Abstract

The traditional power grid is evolving into a smart grid, integrating advanced two-way communication technologies and a greater proportion of renewable energy sources, resulting in a more dynamic and flexible network. Accurate load forecasting is crucial for effective operation, planning, and management of the smart grid. Short-term load forecasting (STLF) is particularly challenging due to the high variability and unpredictability in individual consumer behavior, which can impact forecasting accuracy and complicate daily operations and scheduling. Advanced deep learning techniques offer a promising solution to this problem by improving the accuracy of STLF. In this paper, we introduce an ensemble forecasting framework that combines the convolutional neural network (CNN) with a bidirectional long short-term memory (BiLSTM) recurrent neural network with dynamic weight adjustment (DWA). The CNN layers extract features from the data, the DWA layer multiplies the extracted features by their respective dynamic weights before passing them to the BiLSTM model which enhances the forecasting accuracy by capturing both past and future temporal dependencies. We evaluate this framework using a high-resolution real residential smart meter readings dataset and compare its performance against standalone and hybrid models. Our results demonstrate that the BiLSTM-based framework outperforms LSTM-based and traditional approaches in key metrics, including mean absolute percentage error (MAPE) with an improvement of MAPE by 1.99% against the benchmark CNN-LSTM model. This underscores our model's superior accuracy and reliability for STLF, marking a significant advancement over traditional methods. Our model effectively enhances forecasting accuracy in smart grid applications.
Serum Amino Acid Alterations in Hyperuricemia: Potential Targets for Renal Disease Prevention
Authors: Sheng Qinglin , Ma Yuqing , Geng Bingjie , Chen Jiahui , Cheng Junfei , liu Su , Li Rui , Li Xiangtong , Wang Jing , Lu Hongtao , Gao Fangyuan , Gao Fu 
Published: December 2024

Abstract

Background
Observational studies have linked uric acid (UA) levels and kidney disease to amino acid homeostasis, but the causal relationship is unclear. This study aims to determine if elevated UA affects amino acid levels and whether amino acids mediate this relationship, focusing on the causal links between UA, circulating amino acids, and kidney disease. Methods: This study utilized Uox-KO mice as a hyperuricemia model, assessed renal injury through blood biochemistry and pathology, analyzed serum amino acid changes via targeted amino acidomics, and employed Mendelian randomization to investigate the causal links between uric acid, amino acids, and renal disease. Results: Hyperuricemic Uox-KO mice have significantly higher serum UA and renal impairment markers, with histopathological analysis showing extensive renal tissue damage. Changes in amino acid balance were found in the mice's serum, with key metabolites like alanine, isoleucine, leucine, aspartic acid, cysteine, glutamate, and glycine potentially influencing UA pathophysiology.Genetically predicted UA was positively correlated with chronic renal failure (CRF) and blood urea nitrogen(BUN) levels and negatively with serum cystatin C (eGFRcys) and serum creatinine (eGFRcrea). Alanine (Ala) mediated the effect of UA on elevated CRF and BUN risk, accounting for 4.5% of the UA-CRF relationship and 14.4% of the UA-BUN association. Conclusion: In hyperuricemic mice, serum amino acids undergo metabolic changes. Genetically predicted UA levels are positively linked to CRF and BUN, but negatively linked to eGFRcys and eGFRcrea. Ala mediates UA's effect on CRF and BUN risk, indicating Ala could be a target for preventing renal diseases caused by hyperuricemia.
Can Toll-like Receptor 4 Gene Polymorphi̇sm Play a Role in Pathogenesi̇s of Breast Cancer?
Authors: Arpacı Erkan , Celik Sevim Karakas 
Published: December 2024

Abstract

Introduction: Breast cancer is one of the most common cause of death from cancer in women worldwide. Dynamic interplay between tumors and the immune system is essential for tumor survival, growth, and metastasis. The immune system is known to play a major role in preventing tumor progression by recognizing tumor antigens, and dysregulation of immune system activity could contribute to tumorigenesis. Recent studies have shown that dysregulation of innate immunity receptors such as Toll-like receptors (TLRs) play an important role in the activation of natural and adaptive immunity in response to endogenous hazard signals from pathogens and damaged or dead cells. These receptors are expressed in the immune system cells and some epithelial cells. Recent studies have shown that these receptors are also exaggerated in malignant breast cancer cells. Many studies have shown that the TLR4 gene expression is increased in breast cancer cells, but also associated with metastasis. However, there is no study that could correlate TLR4 gene polymorphisms with breast cancer.
Materials and methods: We conducted a case study with 100 patients and 100 healthy subjects and planned to investigate whether there is a relationship between TLR4 gene polymorphisms [rs4986790 (Asp299Gly) ve rs4986791 (Thr399Ile)] and breast cancer. In this study, polymerase chain reaction (PCR) based restriction fragment length polymorphism (RFLP) method was used for gene polymorphisms.
Results: It was observed that there was relationship between breast cancer and TLR4 gene polymorphisms . Because TLR-4 plays an active role in the innate immune system, the loss of function of this protein may lead to a depressed immune response, thus promoting cancer development.
Research on 3D LiDAR Outdoor SLAM Algorithm Based on LiDAR/IMU Tight Coupling
Authors: Darong Zhu , Qi Wang , Fangbin Wang , Xue Gong 
Published: December 2024

Abstract

Aiming at the problems of easy loss of GPS positioning signals in outdoor environments and inaccurate map construction and position drift of traditional SLAM algorithms in outdoor scenes, this paper proposes a 3D LiDAR and inertial guidance tightly coupled SLAM algorithm. Firstly, IMU forward propagation is used to predict the current position, then backward propagation is used to compensate the motion distortion in the LiDAR data, and the point cloud alignment residuals are constructed based on the GICP algorithm, and then the Iterative Error State Kalman Filter (IESKF) algorithm is utilized to complete the fusion of the point cloud residuals and the a priori position obtained from the forward propagation of the Inertial Measurement Unit (IMU) to complete the state updating, and then the front-end fusion odometer is constructed. front-end fused odometry. Then, a sparse voxel nearest neighbor structure iVox-based method is used to select key frames and construct local maps to utilize the spatial information during frame-map matching, thus reducing the point cloud alignment time consuming. Then, the front-end odometry and loopback detection factor are used together to complete the global factor map optimization. Finally, the robustness and accuracy of this paper's algorithm are verified in campus field scenes and outdoor open-source dataset KITTI, and compared with the current mainstream algorithms FAST-LIO2 and LIO-SAM. The results show that the algorithm proposed in this paper has smaller cumulative error, higher localization accuracy, and better visualization with higher robustness in the campus scene.
Stichwort Threads
Authors: Matinyan Maria 
Published: December 2024

Die bisher am schnellsten wachsende App in der Geschichte, die gerne eine ernsthafte Konkurrenz für X wäre: Threads weckte in den ersten Tagen nach der Veröffentlichung das Interesse von Millionen von Menschen.
Threads ist eine mobile Anwendung von Mark Zuckerbergs Firma Meta. Die App ist textfokussiert und erlaubt Beiträge von bis zu 500 Zeichen. Threads ist eng mit der Schwesterplattform Instagram verknüpft und ermöglicht das Teilen von Fotos, Videos und Audioinhalten. Der Fokus liegt auf Textbeiträgen und der anschließenden Diskussion innerhalb der Community.
Die Plattform wurde am 5. Juli 2023 in den USA und weiteren 100 Ländern veröffentlicht und erreichte innerhalb von zwei Monaten 100 Millionen Nutzer*innen. In der EU war die App erst fünf Monate später verfügbar, nachdem die Datenschutzbestimmungen geklärt waren. Nach der Übernahme durch Elon Musk und der Umbenennung von Twitter zu X erhielt die Plattform starke Kritik und befand sich in einer Krise. Zuckerberg profitierte davon und veröffentlichte Threads genau zum richtigen Zeitpunkt, um unzufriedene Nutzer*innen von X für Threads zu gewinnen. Threads eignet sich gut für Nutzer*innen, denen auf Instagram der Fokus auf Gespräche und Austausch in Echtzeit, vor allem durch Text, gefehlt hat. Die App ermöglicht es, mit Freund*innen zu kommunizieren und den eigenen Status zu teilen. Threads ist außerdem eine gute Alternative für diejenigen, die sich in X nicht (mehr) wohl fühlen, aber etwas Ähnliches suchen. Außerdem ermöglicht Threads eine Kompatibilität mit anderen Plattformen und Instanzen wie dem datenschutzsensiblen Mastodon, was X bisher nicht zulässt.
Obwohl der Start vielversprechend war, ist derzeit noch unklar, ob Threads wirklich in der Lage ist X langfristig Konkurrenz zu machen. Es bleibt abzuwarten, wie sich die Plattform weiterentwickelt.
КОЛОНИАЛЬНАЯ СИСТЕМА В ОЦЕНКАХ АМЕРИКАНСКОЙ ПРЕССЫ БАЛАНС И ПЕРСПЕКТИВЫ В 1945 г.
Authors: С.О. Буранок 
Published: December 2024

Исследования колониальной проблематики в условиях Холодной войны невозможны без привлечения прессы участников данных процессов. Изучение прессы США даст возможность более глубоко и конкретно осветить американские представления о практических подходах в международных отношениях в условиях трансформации миропорядка после Второй мировой войны. Анализ прессы показал, что в течение 1945 г. в американском общественном дискурсе происходила смена приоритетных подходов: рузвельтовский план ликвидации колониальных империй постепенно заменялся планами сохранения и использования колониальных империй и их опыта для решения новых задач внешней политики США.
No research in the colonial system issues during the Cold War would be complete without studying the press of the participating parties. In order to give a detailed analysis of the international relationships in terms of the global transformations from the American point of view, the author draws relevant newspaper articles published after the World War II. The results have shown changes to priority schemes as viewed in American social discourse during 1945. Roosevelt’s plan for the dismantling of the colonial empires was gradually replaced with less radical plans, which presupposed using the colonial experience for foreign policy of the USA. Keywords: colonialism, public opinion, the US press, colonial empires, World War II