bluuebunny/crossref_metadata_2025_split huggingface dataset:
Payload Prediction for Quadro Drone using Temporal Deep Machine Learning Models
Authors: Zitar Raed Abu , Kashkash Mariam , Seghrouchni Amal El Fallah , Barbaresco Frederic 
Published: March 2024

Abstract
In this paper, four different deep-learning and temporal machine-learning techniques are used to predict the payload of the DJI Matrice 100 quadcopter drone based on its tracking data. Tracking variables for real-life experimentations are provided as open source for payloads of 0.0, 250, 500, and 750 grams. The drone is a Quado drone DJI matrice 100. The Machine Learning techniques are RNN, LSTM, TCN, and GRU. The values of the tracks’ kinematics come from several different flights for the different loads. The tracks’ kinematics and flight parameters are used in training the four models. The temporal nature of the data values triggers the need for machine learning methods that use history/memory as part of inputs. This application is a real and relevant test to evaluate the capabilities of the 4 famous types of deep temporal machine learning models. The original data has more than 1400 records for every flight with more than 22 variable values. More than 270 flights were conducted with the 4 payloads. The models were tuned and initialized with the optimum parameters found. Several simulations were implemented for training, testing, and validation. Cross-validation for the models was implemented The RMSE and MAE errors were used to evaluate the loss and the accuracies. The TCN model with the optimum parameters showed the best performance compared to other techniques. The RNN (many-to-one) showed the lowest performance. The results emphasize the superiority of the modern TCN methods over other temporal deep techniques for this kind of problem.
Prednisolone Versus Colchicine for Acute Gout in Primary Care: statistical analysis plan for the pragmatic, multicenter, randomized, and double-blinded COPAGO non-inferiority trial
Authors: Richter Adrian , Truthmann Julia , Hummers Eva , Pereira Julia Freyer Martins , Gágyor Ildikó , Schuster Franziska , Witte Amelie , Böhm Susanne , Greser Alexandra , Kamin Petra , Stracke Sylvia , Dörr Marcus , Bülow Robin , Engeli Stefan , Chenot Jean François , Ittermann Till 
Published: March 2024

Abstract
Background: To date, colchicine and prednisolone are two effective therapies for the treatment of acute gout, but have never been compared directly in a randomized clinical trial. In addition, in previous trials of treating acute gout patients with concomitant comorbidities were often excluded due to contraindications to naproxen.
Study design: This pragmatic, prospective, double-blind, double-dummy, parallel-group, randomized, non-inferiority trial compares prednisolone with colchicine in terms of non-inferiority in patients with acute gout. Patients presenting to their general practitioner with acute gout can be included if the gout attack has occurred within the last 2 days. A total of 60 practices in the vicinity of three university medical centers (Greifswald, Göttingen and Würzburg) participate in the study. The intervention group receives 30 mg prednisolone for 5 days while the group of standard care receives low-dose colchicine (day 1: 1.5 mg; day 2-5: 1 mg). The first dose of treatment is provided at day 0 when patients present to the general practitioner due to an acute gout attack. From day 0 to day 6, patients will be asked to complete a study diary on daily basis regarding pain quantification. For safety reasons potential side effects and the course of systolic blood pressure are also assessed.
Statistical analysis plan: N=314 patients have to be recruited to compensate for 10% of dropout and to allow for showing non-inferiority of prednisolone compared to colchicine with a power of 90%. We use permuted block randomization with block sizes of 2, 4, and 6 to avoid imbalanced treatment arms in this multi-center study; patients are randomized in a 1:1 ratio. The absolute level of pain on day 3 (in the last 24 hours) is the primary outcome and measured on a numerical rating scale (NRS: 0-10). Using a multiple linear regression model adjusted for age, sex, and pain at baseline, prednisolone is considered non-inferior if the effect estimate including the confidence intervals is lower than a margin of 1 unit on the NRS. Average response to treatment, joint swelling and tenderness, physical function of the joint, and patients’ global assessment of treatment success are secondary outcomes.
Discussion: The trial will provide evidence from a direct comparison of colchicine and prednisolone regarding their efficacy of pain reduction in acute gout patients of primary care and to indicate possible safety signals.
Trial registration: ClinicalTrials.gov Identifier: NCT05698680 first posted on January 26, 2023 (retrospectively registered).
Variations in the alveolar bone morphology in maxillary molar area: a retrospective CBCT study
Authors: Han Bing , Liang Wei , Chen Si , Tang Yao , Zhang Yunfan , Lu Wenhsuan , Wu Weiqiang , Sun Qiannan , Zhang Yuning , Liu Xiaomo 
Published: March 2024

Abstract

Objectives: This study quantitatively analyzed the anatomic structure of the alveolar bone in the maxillary molar region at three potential locations for Temporary Anchorage Device (TAD) placement. Additionally, the study compared the variability in this region across different age groups, sagittal skeletal patterns, vertical facial types, and sexes.
Materials and Methods: In this retrospective cone-beam computed tomography study, the buccal alveolar bone was analyzed in the posterior molar area of 200 patients, the measurement items include buccal alveolar bone height, alveolar bone thickness, interradicular distance, and maxillary retromolar space.
Results: Buccal alveolar height was greatest in the U56 region. The interradicular space was largest in the U56 region and increased from the alveolar crest to the sinus floor. Buccal alveolar bone thickness was highest in the U67 region and generally increased from the alveolar crest to the sinus floor. The maxillary retromolar space gradually increased from the alveolar crest to the root apex.
Conclusions: TADs are safest when placed in the buccal area between the maxillary second premolar and the first molar, particularly at the 9 mm plane. The U67 region is the optimal safe zone for TAD placement for maxillary dentition distalization. TADs placement in adolescents can be challenging. Maxillary third molar extraction can be considered for maxillary dentition distalization.
Impact of Rare Non-coding Variants on Human Diseases through Alternative Polyadenylation Outliers
Authors: Li Lei , Zou Xudong , Zhao Zhaozhao , Chen Yu , Xiong Kewei , Wang Zeyang , Chen Shuxin , Chen Hui , Wei Gong-Hong , Xu Shuhua , Li Wei , Ni Ting 
Published: March 2024

Abstract

Although rare non-coding variants (RVs) play crucial roles in human complex traits and diseases, understanding their functional mechanisms and identifying those most closely associated with diseases continue to be major challenges. Here, we constructed the first comprehensive atlas of alternative polyadenylation (APA) outliers (aOutliers) from 15,201 samples across 49 human tissues. Strikingly, these aOutliers exhibit unique characteristics markedly distinct from those of outliers based on transcriptional abundance or splicing. This is evidenced by a pronounced enrichment of RVs specifically within aOutliers. Mechanistically, aOutlier RVs frequently alter poly(A) signals and splicing sites, and experimental perturbation of these RVs indeed triggers APA events. Furthermore, we developed a Bayesian-based APA RV prediction model, which successfully pinpointed a specific set of RVs with significantly large effect sizes on complex traits or diseases. A particularly intriguing discovery was the observed convergence effect on APA between rare and common cancer variants, exemplified by the combinatorial regulation of APA in the DDX18 gene. Together, this study introduces a novel APA-enhanced framework for individual genome annotation and underscores the importance of APA in uncovering previously unrecognized functional non-coding RVs linked to human complex traits and diseases.
Construing the resilience to osmotic stress using endophytic fungus in maize (Zea mays L.)
Authors: B Roopashree , S Rajendra Prasad , Kumar M K Prasanna 
Published: March 2024

Abstract

In a wake of shifting climatic scenarios, plants are frequently forced to undergo a spectrum of abiotic and biotic stresses at various stages of growth, many of which have a detrimental effect on production and survival. Naturally, microbial consortia partner up to boost plant growth and constitute a diversified ecosystem against abiotic stresses. Despite this, little is known pertaining to the interplay between endophytic microbes which release phytohormones and stimulate plant development in stressed environments. In a lab study, we demonstrated that an endophyte isolated from the Kargil region of India, a Fusarium equiseti strain K23-FE, colonizes the maize hybrid MAH 14 − 5, promoting its growth and conferring PEG-induced osmotic stress tolerance. To unravel the molecular mechanism, maize seedlings inoculated with endophyte were subjected to comparative transcriptomic analysis. In response to osmotic stress, genes associated with metabolic, photosynthesis, secondary metabolites, and terpene biosynthesis pathways were highly upregulated in endophyte enriched maize seedlings. Further, in a greenhouse experiment, maize plants inoculated with fungal endophyte showed higher relative leaf water content, chlorophyll content, and antioxidant enzyme activity such as polyphenol oxidase (PPO) and catalase (CAT) under 50% field capacity conditions. Non-enzymatic molecules like proline were higher and malondialdehyde content was reduced in colonized plants. This study set as proof of concept to demonstrate that endophytes adapted to adverse environments can efficiently tweak non-host plant responses to abiotic stresses such as water deficit stress via physiological and molecular pathways, offering a huge opportunity for their deployment in sustainable agriculture.
Construction of a postoperative delirium nursing care plan for patients with Stanford type A aortic dissection：A Delphi study
Authors: Li Xueping , Li Ruru , Lin Ailin , Chen Chaohong , Wang Hongxia , Zhang Huai , Wu Yuanbo , Yin Zhiqin 
Published: March 2024

Abstract
Aim
To develop a plan for care of postoperative delirium in patients with Stanford type A aortic dissection in the ward, and to provide reference for the prevention and care of postoperative delirium in such patients.
Background
Postoperative delirium is one of the common and serious postoperative complications in patients with type A aortic dissection. It can significantly affect surgical efficacy and postoperative recovery. However, there is currently lack of effective postoperative management programs.
Design:
This study adopted evidence-based nursing research and the Delphi expert consensus method. Methods: Through literature research, group discussions, and evidence-based nursing research, a plan for postoperative delirium care for patients with type A aortic dissection in the ward was formulated. The retrieval time is from establishment of the database to May 2022. The plan was modified through two rounds of Delphi expert consultation to form the final draft.
Results
After two rounds of Delphi expert consultation, the expert authority coefficient, concentration degree and degree of coordination of expert opinions, all showed good results. The content of the plan includes 5 primary components (delirium judgment, delirium risk stratification and related assessment, general management, management of patients with delirium, family caregiver support), 18 secondary components, and 47 tertiary components.
Conclusion
This protocol has good accuracy and operability, and provides a reliable basis for the management of postoperative delirium in patients with type A aortic dissection in the general wards.
Implications for Nursing Management:
This study can provide a reference for clinical nurses to implement in the management of postoperative delirium and provide a theoretical basis for perpetual improvement of postoperative nursing quality in cardiac surgery.
An Iterative Calculation Method for Internal Forces of Straight-wall Arch Tunnel Lining Considering the Effect of Elastic Resistance
Authors: Huang Rongbin , Gu Shuancheng 
Published: March 2024

Abstract
Accurate analysis of the stress characteristics of straight-wall arch tunnel lining is a prerequisite for the design of support structures and stability analysis. In this paper, an elliptical curve is employed as the fitting curve for the top of the straight-wall arch, upon which a mechanical analysis model is established. An iterative method is proposed to determine the distribution pattern and scope of elastic resistance, revealing the stress characteristics of the straight-wall arch tunnel lining under the combined action of external loads and elastic resistance. To simplify the iterative process, an iterative transfer coefficient K is introduced, enabling accurate and rapid calculations of the internal forces of the lining. The superiority and practicality of the proposed method are verified through example calculations and comparative analysis.
China's traditional rural communities rely on technology diffusion to achieve transformation and development
Authors: Zhu Qiankun , Qiao Jiajun , DHEKRA Ben Amara , Isaac Sarfo 
Published: March 2024

Abstract

Rural revitalization is currently a focus of development in China, with rural communities industrialization being an important means of promoting economic development in agricultural areas. The key to promote the transformation of rural communities is the introduction and dissemination of production technology. The study taked Xuchang Village, a rural community, as the case study area. This study conducted in-depth interviews with local government personnel and industry authorities, and conducted a questionnaire survey among 36 folk music instrument shop owners and 151 shop employees. The study aimed to analyze the technological diffusion process, characteristics, and mechanism of transforming ordinary communities into specialized communities. The study showed that: the technology diffusion exhibited a top-down, center-periphery structure, with an irreversible transmission direction and small-scale group diffusion. Notably, there were significant differences in technology diffusion corridors during different periods. In the initial stage, business ties were the main corridors for technology diffusion. In the middle stage, blood ties were the main corridors of technology diffusion. In the late stage, geographical ties were the main corridors of technology diffusion. Such experiences have great reference value for promoting economic development in rural areas in China and other developing countries.
Transcriptome-wide identification of N6-methyladenosine modifications for aortic dissection
Authors: Chai Tianci , Ma Likang , Li Jiakang , Xie Rumei , Tang Lele , He Jian , Qiu Zhihuang , Chen Liangwan 
Published: March 2024

Abstract

Background: N6-methyladenosine (m6A) plays important roles in many biological processes such as gene expression control and may have functional roles in aortic dissection (AD). The aim of this study was to identify N6-methyladenosine (m6A) modification and the expressions of the m6A regulatory genes related to AD.
Methods: Aortic tissue samples were obtained from AD and controls and MeRIP-seq and RNA-seq experiments were performed to detect m6A methylation and mRNA expression profiles, respectively. The differentially RNA methylation peaks were validated by MeRIP-PCR in AD cases and controls.
Results: Compared with the control samples, 3,318 up methylated and 1,573 down methylated coding genes in AD were detected. These genes were mainly enriched in focal adhesion, ECM-receptor interaction and regulating the transcription such as splicing. Significant differentially methylated m6A sites in some well-known susceptibility genes for AD were identified, including FBN1, TGFB1, TGFBR1/2, LOXL3, COL3A1, SMAD3, VEGFA and MAPK1/3. A total of 651 differentially expressed genes, including 594 protein-coding genes (96 upregulated and 498 downregulated), and 57 lncRNAs (20 upregulated and37 downregulated) were identified. Integrated analysis of the data from MeRIP-seq and RNA-Seq identified 74 genes that changed significantly in both m6A level and mRNA abundance in AD cases compared with the controls. We observed the same m6A-level changes in 14 out of the 16 selected m6A methylated transcripts in the independent sample.
Conclusions: This study identified m6A changes in critical AD susceptibility genes. The identified m6A modification may play a role in critical AD-related pathways, thereby regulating the pathogenesis of AD.
Effect of Oral Health Motivational Interviewing on Prevention of Early Childhood Caries: a Randomized Controlled Study
Authors: besci tolga , BORAN Perran , AKBEYAZ Ecem , KARGUL Betül 
Published: March 2024

Abstract

Objectives: Early childhood caries (ECC) is one of the most common chronic diseases in childhood and is associated with poor growth and development. The aim of this study was to evaluate the effectiveness of motivational interviewing (MI) during well-child visits on children’s oral health status and practices.
Methods: This randomized controlled interventional study was conducted between April 2015 and June 2016. Mothers of infants aged between 6 and 12 months who attended their scheduled visits were eligible. Both groups received regular anticipatory guidance on oral health, and the intervention group received additional oral health education using MI augmented with an educational booklet and a reminder phone call. Study participants completed a questionnaire about oral health and nutritional habits 12 months post-intervention. Dental examinations were performed on children, and decayed, missing, and filled teeth (dmft) scores were calculated by a pediatric dentist.
Results: A total of 241 mother-infant dyads were randomly allocated to the intervention (n = 121) and control (n = 120) groups, and 171 (70.9%) completed the final assessments. The overall incidence of caries in primary teeth was 21%. Caries frequency and dmft scores were significantly lower in the intervention group compared to the control group (16.0% vs. 42.2% and 0.49 vs. 0.89, respectively [p<0,001]). Regular tooth brushing was significantly higher in the intervention group (51.2 vs. 5.6%, respectively [p<0,001]).
Conclusion: Oral health education delivered during well-child visits by MI was associated with better oral health. MI reduced parental risk-related behavior for ECC in the study population. Well-child visits provide an excellent opportunity for counseling parents concerning preventive strategies regarding ECC.
Comparing the Dental Knowledge of Large Language Models
Authors: Tussie Camila , Starosta Abraham 
Published: March 2024

Abstract
Introduction: With the advancement of Artificial Intelligence, Large Language Models (LLMs) have emerged as technology that can generate human-like text across various domains. They hold vast potential in the dental field, able to be integrated into clinical dentistry, administrative, and for student and patient education. However, the successful integration of LLMs into dentistry is reliant on the dental knowledge of the models utilized, as inaccuracies can lead to significant risks in patient care and education.Aims We are the first to compare different LLMs on their dental knowledge through testing the accuracy of different model responses to Integrated National Board Dental Examination (INBDE) questions.Methods We include closed-source and open-source models and analyzed responses to both “Patient Box” style board questions and more traditional, textual based multiple-choice questions.Results For the entire INBDE question bank, GPT-4 had the highest dental knowledge with an accuracy of 75.88%, followed by Claude-2.1 with 66.38% and then with Mistral-Medium’s 54.77%. There was a statistically significant difference in performance across all models.Conclusion Our results highlight the high potential of LLM integration into the dental field, the importance of which LLM is chosen when developing new technologies, and the limitations that must be overcome before unsupervised clinical integration can be adopted.
Soft Ground Micro TBM Jack Speed and Torque Prediction using Machine Learning Models through Operator Data and Micro TBM-Log Data Synchronization
Authors: KILIC Kursat , Narihiro Owada , Ikeda Hajime , Adachi Tsuyoshi , Kawamura Youhei 
Published: March 2024

Abstract

Tunnel Boring Machines (TBMs) are pivotal in underground projects like subways, highways, and water supply tunnels. Predicting and monitoring jack speed and torque is crucial for optimizing TBM excavation efficiency. Conventionally, skilled operators manually adjust numerous tunnelling parameters to regulate the machine's progress. In contrast, machine learning (ML) algorithms offer a promising avenue where computers learn from operator actions to establish parameter relationships autonomously. This study introduces an innovative approach to enhancing operator monitoring and TBM data comprehension. A robust correlation between TBM operator behaviour and TBM logged data is established by leveraging an Optuna-assisted ML methodology—the research light on the intricate dynamics influencing TBM advance rate parameters. Operational data is collected from micro slurry tunnel boring machine (MSTBM) umbrella support excavations. The proposed framework harnesses Optuna, an advanced hyperparameter optimization platform, to dynamically refine jack speed and torque settings. Through meticulous analysis of the interplay between TBM operator decisions and real-time logged data, the AI model discerns patterns, empowering informed decision-making. Using Optuna, a range of models, including random forest (RF), K-nearest neighbours (kNN), decision tree (DT), and XGBoost are automatically compared and tuned. The best model's (RF) performance is evaluated through a correlation coefficient (R2) of 96%, mean squared error (MSE) of 119.7, and mean absolute error (MAE) of 4.42 for jack speed decision making while 83% of R2, MSE of 0.62, and MAE of 0.42 for the torque decision making. This intelligent model can assist the TBM operator in making decisions about TBM control.
Serum albumin level as predictor of infection in children with nephrotic syndrome age 2- 18years in northwest and East Amhara region, Ethiopia: a multi-center cross-sectional retrospective study
Authors: Mekonnen Birhanu , Alene Tilahun Dessie , Yimer Yalemwork Anteneh , Lakew Ayenew Molla , Genet Geta Bayu 
Published: March 2024

Abstract

Background
Infection is the most common complication of pediatric patients with nephrotic syndrome. The factors associated with infection in nephrotic syndrome are lacking in the setting where this research was done. This study aimed to identify the prevalence and associated factors among children with nephrotic syndrome aged 2 to 18 years.
Methods
A hospital based retrospective cross-sectional study was conducted. An Epi5 collector electronic data collector installed with a smartphone was used to collect the data. The collected data was exported to Stata version 15.1 for analysis. Descriptive findings like mean, standard deviation and percentage were reported. Logistic regression was used to identify the factors associated with infection.
Results
In this study, the prevalence of infection among nephrotic syndrome children is 39.8% (95%CI: 30.7, 49.7). The types of infection identified were pneumonia, urinary tract infection, diarrheal disease, cutaneous fungal infection, intestinal parasitic infection, and sepsis. Serum albumin level, hematuria, and residence were significantly associated with infection.
Conclusions
The presence of hematuria predicted the presence of infection in nephrotic syndrome in children. Increasing the level of serum albumin decreased the likelihood of infection in children with nephrotic syndrome. Further study is recommended to strengthen this finding.