bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative Analysis of Single and Multiagent Large Language Model Architectures for Domain-Specific Tasks in Well Construction
Authors: Sabbagh V. B. , Lima C. B. C. , Xexéo G. 
Published: October 2024

Summary
This paper explores the application of large language models (LLMs) in the oil and gas (O&G) sector, specifically within well construction and maintenance tasks. The study evaluates the performances of a single agent and a multiagent LLM-based architecture in processing different tasks, offering a comparative perspective on their accuracy and the cost implications of their implementation. The results indicate that multiagent systems offer improved performance in question and answer (Q&A) tasks, with a truthfulness measure 28% higher than single-agent systems but at a higher financial cost. Specifically, the multiagent architecture incurs costs that are, on average, 3.7 times higher than those of the single-agent setup due to the increased number of tokens processed. Conversely, single-agent systems excel in Text-to-SQL (structured query language) tasks, particularly when using the Generative Pre-Trained Transformer 4 (GPT-4), achieving a 15% higher score compared to multiagent configurations, suggesting that simpler architectures can sometimes outpace complexity. The novelty of this work lies in its original examination of the specific challenges presented by the complex, technical, unstructured data inherent in well construction operations, contributing to strategic planning for adopting generative artificial intelligence (AI) (Gen-AI) applications and providing a basis for optimizing solutions against economic and technological parameters.
Weld pool boundary detection based on U-Net algorithm and weld seam tracking in plasma arc welding
Authors: Lu Jidong , Yamane Satoshi , Wang Weixi , Li Ning , Wang Siqi , Xia Yuxiong 
Published: October 2024

Abstract

Plasma arc welding (PAW)can achieve high-quality welding joints in high-strength manufacturing fields such as aviation and automotive and improve production efficiency. The plasma keyhole arc welding(K-PAW) can be used for butt welding in thick plates since the plasma arc is more concentrated than Metal Active Gas (MAG) welding. The weld pool can effectively reflect the welding melt state. To make robot automatic welding, it is important to observe the weld pool in real-time. The K-PAW will be stable to ensure the welding quality if the weld line can be taught accurately. However, the electrodes of the plasma welding torch cannot be observed from the outside. Teaching the weld line to torch in real-time from human sight will be difficult. In this study, the Complementary Metal-Oxide-Semiconductor (CMOS) camera fixed on the welding torch with an interference filter was utilized to observe the weld pool. Estimate the weld line position in real-time by image processing techniques based on deep learning. The control of seam tracking was performed to avoid misalignment using the weld line position. Specifically, the authors employed the U-Net autoencoder, a deep learning technology to create a training model and then used the training model to detect the boundary area from the weld pool image observed by a camera in the welding process. The model demonstrates sufficient prediction which the accuracy reached 99.5% for the training data and 96.5% on the test data recognition. Moreover, the authors discussed a control method that utilized weld line position estimated from the boundary area to verify the effectiveness of this prediction model from 3mm within the deviation of 1 mm in controlling process. It is important to improve the quality of KAW welding in this study. Combining vision sensing technologies and deep learning methods will provide new technologies to enable greater welding precision and improve welding quality. It could also accelerate the development of welding technology in the intelligent manufacturing field.
Tumor innervation in cervical cancer: More is worse
Authors: Chen Guoqiang , Ji Qingqing , He Ruihua , Chen Yunxia , Pan Zhouyuan , Zhou Yuqing , Wei Zhihong , Sun Hao , Zheng Zhen , Feng Lixia 
Published: October 2024

Abstract

Background: The nervous system plays a significant role in tumor growth and metastasis. However, the low frequencies of perineural invasion reported in previous studies on human cervical cancer — ranging from 7.0% to 35.1% of cases — may overlook the active role that nerves play in cervical cancer progression. Neurosecretory factors can promote tumor migration and invasion, even in cases classified as “PNI-negative”. Therefore, this study aims to clarify whether tumor innervation influences tumor progression and patient outcomes.
Methods: We evaluated the gene signatures of human myelinating Schwann cells using the IPAS scoring system to predict the degree of tumor innervation in 304 cervical cancer patients from the TCGA database. Subsequently, we constructed a myelin-associated risk prognostic signature by LASSO regression analysis. Finally, we obtained a risk score by a quantitative formula and divided all samples into high- and low- risk score groups.
Results: Our results indicated that tumor innervation in cervical cancer was associated with poor patient survival. Higher levels of innervation correlated with an impaired immune response and reduced expression of immune checkpoints, including PD-1. The prognostic model demonstrated excellent consistency between predictions and actual survival outcomes.
Conclusions: Tumor innervation plays a crucial role in the regulation of prognosis in cervical cancer, and the identified risk prognostic signatures offer a valuable tool for risk stratification and prognostic prediction in clinical practice.
A urine patch model for evaluating tactical management strategies for reducing nitrogen leaching loss from pasture- based dairy farms
Authors: Adams Christopher , Kok Jacobus , Beukes Pierre C. , Amer Peter 
Published: October 2024

Abstract

Animal urine and urine patch characteristics are import drivers of nitrogen leaching in pasture-based dairy systems and their manipulation offers opportunities to mitigate these losses. We developed a model, based on previous work, to investigate the effect of applying tactical management strategies to reduce nitrogen leaching from urination events during different times of the year. Our model predicted that reducing pasture height or increasing the volume per urination event to increase the spread of individual urine patches may not reduce nitrogen leaching at paddock scale, most likely due to the opposing effect of increasing the proportion of overlapping urine patches. In contrast, decreasing dietary nitrogen intake by 30% or increasing total daily urination volume by 40% reduced nitrogen leaching by 16% and 4%, respectively. Furthermore, decreasing nitrogen intake by 30% during targeted times of the year (January to May) still reduced the nitrogen leaching loss by a considerable amount relative to applying this strategy for the whole year (10% versus 16%, respectively). Our modelling indicates that management strategies can be applied tactically during key times of the year to reduce the nitrogen leaching risk. This is important for dairy producers who can add substantial reductions to N leaching from their farm systems, while reducing the management effort and costs by focussing on two key urine characteristics and only during a limited time of the farm season.
Exploring the Impact of Dosiomics Features on DQA Results in TomoDirect based Radiotherapy
Authors: Kim Jinseon , Mun Chi-Woong , Choi Byung-Ock , Kim Jina , Kang Young-nam 
Published: October 2024

Abstract

This study investigates the correlation between dosiomics features and Delivery Quality Assurance (DQA) results in TomoDirect radiotherapy treatments, aiming to enhance DQA accuracy and efficiency. Dosiomics features, such as shape characteristics, statistical properties, and texture metrics (e.g., GLCM, GLSZM), were extracted from RT Dose DICOM files of patients treated with TomoDirect on the Radixact X9 system. Regions of interest (ROI), such as the planning target volume (PTV), were used to isolate dose values for feature extraction. The DQA results were classified using gamma analysis (3%/3mm criteria), and statistical methods like correlation, group comparison, and regression analysis were applied to assess the relationship between these features and DQA outcomes. The analysis identified several key predictors of DQA success. Shape features, including surface area and object size, along with texture features like GLCM autocorrelation and GLDM high gray-level emphasis, showed significant correlations with DQA pass rates. The multivariate regression model explained 79.7% of the variance in DQA outcomes, emphasizing the potential of dosiomics features to predict DQA results. Additionally, features related to dose uniformity and complexity, such as firstorder_10th Percentile and GLCM contrast, significantly impacted gamma pass rates. This study demonstrates that dosiomics can enhance the predictability of DQA outcomes in TomoDirect treatments. The identified features can support the development of predictive models to streamline DQA processes, improve treatment accuracy, and reduce manual verification efforts. Future research should explore integrating additional parameters and expanding these methods to other radiotherapy techniques and machines for broader applicability.
The regioselectivity in the gold-catalyzed cycloisomerization of alcohols: A full DFT study on carbene versus non-carbene mechanisms
Authors: Tavakol Hossein , Wei Yin , Shi Min 
Published: October 2024

Abstract

The mechanistic study of in the gold-catalyzed cycloisomerization of alcohols or amine tethered-vinylidenecyclopropanes has been performed using high-level DFT calculations to find the reasons of the observed selectivity of the products. Two possible pathways were observed, which in the first product, during the cyclization process, the vinylidenecyclopropane moiety converts to methylidenecyclopropane-containing product (P1) via an ionic (non-carbene) intermediate and in the second product, converts to cyclobutene-containing product (P2) via a carbene intermediates. In all six examined derivatives (containing different alkyl group at C1 allenic carbon) P2 was the major product by both thermodynamic (the more stability of P1 than P2) and kinetic (the smaller barrier for producing P2 versus P1) criteria in both gas phase and solvent (THF, using PCM model) media. However, in the derivatives with low-strain allenic group (R), I1 (which leads to P1) is more stable than I3 intermediates (which leads to P2) by 0.6–4.2 kcal/mol in the gas phase and 1.0-3.1 kcal/mol in the solvent and the derivatives with high-strain allenic group, I3 is more stable than I1 by 2.1–2.5 kcal/mol in the gas phase and 3.5–4.2 kcal/mol in the solvent. Therefore, both gas phase and solvent data show that because of the different hinderance between alkyl group and gold cation complex, the selectivity of the reaction is yielded by the favorability of I1 or I3 intermediates. Interestingly, another evidence was provided by atomic charges in the reactants using NBO calculations. These calculations showed that when the atomic charge of C1 allenic carbon was higher than C3, the gold cation prefers to produce I1, leading to P1, and when the atomic charge of C3 allenic carbon was higher than C1, the gold cation prefers to produce I2, leading to P2.
Prerequisites for creating programmable structures based on stimuli-sensitive hydrophilic polymers
Authors: Suleimenov Ibragim , Kabdushev Sherniyaz , Yermukhambetova Bayana , Irmukhametova Galiya , Bakirov Akhat , Mun Grigoriy 
Published: October 2024

Abstract

It has been shown that the neural network properties of systems based on stimuli-sensitive hydrophilic polymers make it possible to raise the question of creating programmable structures based on such materials. It has been shown that the phenomenon of multidimensional hysteresis can occur in systems based on stimulus-sensitive polymers, the behaviour of which significantly depends on more than one thermodynamic variable. In this case, the dependence of the parameters characterising the system's state on the control thermodynamic variables is described by a complex folded surface on which areas corresponding to abrupt phase transitions can be identified. It is shown that the system's state in which multidimensional hysteresis is realised depends not only on the current values of thermodynamic variables but also on the path along which the representing point moves in the space of control parameters. On this basis, it has been proven that analogues of neural networks can be implemented in which information is recorded by submitting the same code sequences to all inputs of the first layer of the network. Physically, this corresponds to the fact that the programming of structures of the type under consideration is carried out using macroscopic influences expressed in the form of changes in thermodynamic variables according to a given law. Simple and illustrative model examples built based on standard stimuli-sensitive polymer systems are considered, proving the possibility of implementing neural networks of this type.
SCFI-ESeg: Enhancing Semantic Segmentation with Spatial and Content Feature Integration
Authors: Li Ning , Zhang Xudong , Li Bo , Yuan Baohua , Yang Gaochao 
Published: October 2024

Abstract

In recent years, with the development of deep learning technologies, significant progress has been made in the field of semantic segmentation. However, existing models still face challenges in utilizing spatial information and capturing multi-level and multi-scale information. To address this, this paper proposes a novel semantic segmentation model called SCFI-ESeg, built on the Segmenter framework. By integrating spatial information and content features, SCFI-ESeg significantly enhances segmentation accuracy. The SCFI-ESeg model introduces the Spatial Feature Enhancement Module (SFEM), Multi-Stage Attention Module (MStA), and Dense Continuous Atrous Spatial Pyramid Pooling (DCASPP), effectively improving the model's ability to express spatial and semantic information. The SFEM module leverages the encoder's query features to specifically enhance spatial information, thereby improving the model's perception of image details. The MStA module strengthens the interaction between high-level and low-level features through multi-stage feature fusion, effectively enhancing the integration of features at different levels. The DCASPP extracts features under varying receptive fields and merges them with pooling results, improving the network's understanding of multi-scale information. Experimental results demonstrate that SCFI-ESeg exhibits excellent performance on the public datasets ADE20K and Pascal Context, particularly in complex scenarios. Various experimental variants achieve an average improvement of 1.6\% over the baseline model on the ADE20K dataset, and a 2.5\% improvement when using the ViT-tiny configuration. Additionally, the model maintains a low computational cost and parameter count, showcasing its practicality.
3D printing individualized spacer prosthesis and acetabular implant for the treatment of Crowe type III developmental dysplasia of the hip
Authors: Chen Beibei , Liang Hairui , Yang Lei , Duan Siyu , Xu Rongda , Zhou Xueting , Cai Zhencun 
Published: October 2024

Abstract

Background
In patients with Crowe III developmental dysplasia of the hip (DDH), surgery presents challenges such as severe bone defects and inadequate acetabular cup coverage. This study compares the clinical efficacy of 3D-printed personalized spacer prostheses with conventional femoral head reshaping and structural bone grafting in total hip arthroplasty (THA) for patients with Crowe III DDH.
Methods
A retrospective analysis was conducted on 52 Crowe III patients. The 3D group (26 cases) used 3D printing technology combined with computer simulation to design personalized spacer prostheses. Preoperative models were printed to simulate the surgical procedure, and high-porosity porous structured spacer prostheses and acetabular cup layers were printed using titanium alloy powder. The non-3D group (26 cases) underwent traditional femoral head reshaping and structural bone grafting. The study compared the differences in lower limb length, the horizontal and vertical distances of the hip joint rotation center from the teardrop line, acetabular cup abduction angle, acetabular cup coverage, operation time, intraoperative blood loss, postoperative time to mobilization, time to hospital discharge, Harris hip scores during follow-up, and complications between the two groups.
Results
In the 3D group compared to the non-3D group, intraoperative blood loss (261.92 ± 14.70 vs. 313.85 ± 20.02 ml, P < 0.05), time to mobilization (1.27 ± 0.45 vs. 4.85 ± 1.05 days, P < 0.05), and time to discharge (2.77 ± 0.65 vs. 5.85 ± 0.92 days, P < 0.05) were significantly lower, as was the limb length discrepancy on the first postoperative day (0.25 ± 0.21 cm vs. 0.48 ± 0.28 cm, P < 0.05). The acetabular cup coverage rates on the first postoperative day and at 3 months postoperatively (1 ± 0.00 vs. 0.93 ± 0.07; 1 ± 0.00 vs. 0.83 ± 0.11, P < 0.05) were significantly higher in the 3D group. The Harris hip scores at 3, 6, and 12 months postoperatively were also higher in the 3D group than in the non-3D group, with statistically significant differences (P < 0.05).
Conclusion
The use of 3D-printed personalized spacer prostheses in THA offers an innovative treatment option for Crowe III DDH patients, providing personalized care, enhancing surgical precision, and improving treatment outcomes.
Using a Theory of Change to integrate digitalised lived experience stories into the Youth Friendship Bench, a psychological intervention for treating common mental disorders in young people in Zimbabwe
Authors: Kamvura Tiny Tinashe , Chrisikopoulou Marina , Shoniwa Leeroy Tafadzwa , Mboweni Sandra Ngonidzashe , Munetsi Mary Wadzanai , Dambi Jermaine , Barkoczi Istvan Daniel , Takaona Tapiwa Leslie , Jongwedzvuku Providence , Ponciano Karen , Motsi Kudzanai , Lunde Victoria , Zamchiya Lena , Westerheim Jimmy , Chibanda Dixon 
Published: October 2024

Abstract

Background
Advances in multimedia technologies' capabilities and accessibility have made it possible for stories to be digitally recorded, stored, and shared with a much wider audience. In mental health, digitalised lived experiences have been used to promote self-management and recovery during therapy, mental health awareness and literacy, and social relationships. In this paper, we describe the theory of change process we used to integrate The Human Aspect’s digitalised lived experiences (videos) into the Friendship Bench intervention.
Results
There was consensus from the stakeholders that digitalised lived experiences could be used as in-session and between-session resources for promoting the subjective psychological well-being of Friendship Bench clients. The stakeholders were of the same view that the digital videos be used as both an in-session and between-session intervention. Clients would be given the opportunity to choose the modality that works for them. It was agreed that the digitalised lived experiences stories could potentially be used to increase mental health awareness, improve mental health literacy, reduce mental health-related stigma and help facilitate recovery in Friendship Bench clients.
Conclusions
Theory of Change can be used to build consensus on how to integrate digitalised lived experiences into an existing evidence-based mental health intervention. There is now a need to evaluate the feasibility and acceptability of the integration as well as evaluate its effectiveness in reducing common mental disorders symptoms through an adequately powered study.
The decreased requirement for haem or iron results in artemisinin resistance in Plasmodium
Authors: Sun Jun , Guo Fujiang , Fang Chuantao , Liu Chuang , Si Wenwen , Chen Bo , Xu Wenyue , Li Jia , Du Xiling , Sun Jia 
Published: October 2024

Abstract

Artemisinin resistance is often associated with mutations in the Pfkelch13 gene (K13), which lead to decreased hemoglobin endocytosis and activation of artemisinin. However, certain non-K13 mutations linked to artemisinin resistance are also connected to hemoglobin endocytosis or degradation. This coincidence suggests that the development of artemisinin resistance is related to hemoglobin degradation. Here, we report that the stages most susceptible to artemisinin utilize the highest levels of haem and iron while also engaging in DNA replication. Notably, haem degradation releases iron, which facilitates DNA synthesis. Additionally, artemisinin can form adducts with haem and disrupt hemozoin aggregation, thereby interfering with haem and iron utilization. Furthermore, the addition of haem or iron (HI) weakened, rather than enhanced, the antimalarial effect of artemisinin, strongly suggesting that artemisinin kills malaria parasites by sequestering haem and impeding HI utilization rather than primarily by producing free redicals. We also observed that the K13 mutant strain, P. falciparum 3D7C580Y, exhibited downregulation of genes related to haem, iron, and DNA synthesis, indicating a decrease in HI utilization and reproduction compared with P. falciparum 3D7WT. Notably, prolonged iron supplementation decreased, rather than increased, its resistance to artemisinin, suggesting a restoration of sensitivity when high iron requirements of the K13 mutant strain are met. Taken together, decreased hemoglobin degradation reduces HI supply, leading to diminished HI utilization ability, ultimately resulting in insensitivity to HI deficiency caused by artemisinin, while the K13 mutation represents one of the mechanisms that decrease HI requirement and utilization.