bluuebunny/crossref_metadata_2025_split huggingface dataset:
Causal association between mTOR-dependent circulating protein levels and autism spectrum disorder: a Mendelian randomization study
Authors: Fu Jingfen , Dong Meiyuan , Chen Lingling , Du Chunhui , Yu Ze , Wang Hongqiang 
Published: April 2024

Abstract

Background
Overactivation of the mTOR signaling pathway is a critical mechanism in the pathogenesis of autism spectrum disorder (ASD). However, the causal relationships between key molecules downstream of the mTOR signaling pathway and ASD remains unclear. This study aimed to explore the causal associations between seven mTOR-dependent circulating protein levels and ASD.
Methods
Instrumental variables (IVs) used as proxies for mTOR-dependent circulating protein levels were derived from the proteomics-GWAS INTERVAL study (3,301 participants) and a serum protein GWAS study in an Icelandic population (5,368 participants). Two ASD summary datasets were obtained from a meta-analysis study of ASD GWAS datasets (22,196 cases and 32,504 controls) and the FinnGen Consortium (646 cases and 301,879 controls), respectively. We applied two-sample Mendelian randomization (MR) to assess whether there is a causal association between seven mTOR-dependent circulating protein levels and ASD. Furthermore, validation analyses of positive exposures in the discovery cohort were performed to confirm the reliability of the findings.
Results
In this two-sample MR study, plasma PKCα level was found to be causally related to ASD in both the discovery cohort (IVW: OR = 1.15, 95% CI = 1.05–1.25, p = 0.002) and the validation cohort (IVW: OR = 1.14, 95% CI = 1.02–1.27, p = 0.017).
Conclusions
There was a causal association between the plasma level of PKCα and ASD, suggesting PKCα as a potential biomarker for the prevention, monitoring and treatment of ASD. However, whether PKCα can play a role in the clinical management of ASD remains to be demonstrated in future research.
A Feasibility-Preserved Quantum Approximate Solver for the Capacitated Vehicle Routing Problem
Authors: Xie Ningyi , Lee Xinwei , Cai Dongsheng , Saito Yoshiyuki , Asai Nobuyoshi , Lau Hoong Chuin 
Published: April 2024

Abstract

The Capacitated Vehicle Routing Problem (CVRP) is an NP-optimization problem (NPO) that arises in various fields including transportation and logistics. The CVRP extends from the Vehicle Routing Problem (VRP), aiming to determine the most efficient plan for a fleet of vehicles to deliver goods to a set of customers, subject to the limited carrying capacity of each vehicle. As the number of possible solutions skyrockets when the number of customers increases, finding the optimal solution remains a significant challenge. Recently, the Quantum Approximate Optimization Algorithm (QAOA), a quantum-classical hybrid algorithm, has exhibited enhanced performance in certain combinatorial optimization problems compared to classical heuristics. However, its ability diminishes notably in solving constrained optimization problems including the CVRP. This limitation primarily arises from the typical approach of encoding the given problems as penalty-inclusive binary optimization problems. In this case, the QAOA faces challenges in sampling solutions satisfying all constraints. Addressing this, our work presents a new binary encoding for the CVRP, with an alternative objective function of minimizing the shortest path that bypasses the vehicle capacity constraint of the CVRP. The search space is further restricted by the constraint-preserving mixing operation. We examine and discuss the effectiveness of the proposed encoding under the framework of the variant of the QAOA, Quantum Alternating Operator Ansatz (AOA), through its application to several illustrative examples. Compared to the typical QAOA approach, the proposed method not only preserves the feasibility but also achieves a significant enhancement in the probability of measuring optimal solutions.
Causal relationship between immune cells and posttraumatic stress disorder: a bulk two-sample Mendelian randomization study
Authors: Zhou Kai qi , Deng Zhou wei , Tan Yu lun 
Published: April 2024

Abstract
Background: There is increasing evidence that the immune system is associated with posttraumatic stress disorder (PTSD). However, the causal relationship between immune cells and PTSD and the possible related types of immune cells are still unclear.
Aim: To determine the causal relationship between immune cells and PTSD. Two-sample Mendelian randomization (MR) analysis was then performed.
Materials and Methods: The exposure and outcome data used in this study were obtained from a GWAS (https://gwas.mrcieu.ac.uk/). Two-sample MR analysis was performed to assess the causal relationships between 731 types of immune cell features and PTSD. We used 731 types of immune cells for exposure and PTSD as the outcome. Our MR analysis uses a variety of methods to ensure the robustness of the experiment. For each immune cell that may be related to PTSD, we adopted a sufficient number of methods to ensure the accuracy and effectiveness of the results.
Results: Our study identified potential causal relationships between various immune cells and PTSD. We identified 10 types of immune cells that are potentially causally linked to PTSD. CD33-related cells are the most prominently related immune cells.
Conclusions: Our study determined the causal relationship between a variety of immune cells and PTSD via MR, which can provide help for future clinical practice.
Effect of reductant on property and CO 2 sequestration for belite cement from phosphogypsum
Authors: Li Kaiwen , Liu Changrong , Ma Xiaoling , Tan Hongbin , Taha Yassine , Dong Faqin , Yang Feihua 
Published: April 2024

Abstract

Gypsum can be decomposed at low-temperature by adding reductant, which is beneficial to obtain cement. The effects of different reductant on the phases of belite cement raw meals were studied by calcining at 1300℃ for 2h and using phosphogypsum as raw materials. Diffraction peaks of calcium sulfate were not observed in the samples when 10 wt% activated carbon was added and the molar ratio of CaS to CaSO4 was 3, respectively. The Sulfur trioxide contents of in the clinkers were 0.80 and 0.64 wt%, respectively.
The effect of carbonation curing on the cement properties was also studied. Carbonation curing can promote cement hydration and increase strength at 20 ℃, 75 % relative humidity and 20% CO2 concentration. As the carbonation curing age increased, the compressive strengths of the samples gradually enhanced. When 10 wt% carbon was employed as the reducing agent, compressive strengths of the samples were 15.5, 15.6, and 15.6 MPa after carbonation curing at 3, 7 and 28 d, respectively. When CaS was employed as the reducing agent, the compressive strengths of the samples were 19.8, 27.2, and 34.1 MPa after carbonation curing for 3, 7 and 28 d, respectively. The carbon dioxide sequestration contents of the samples prepared with a 10 wt% carbon and CaS reductant, were 11.6% and 9.2% after carbonation curing for 28 d, respectively. These findings demonstrate the potential to use phosphogypsum with various reductants to enhance the quality of belite cement and at the same time consume more CO2 in the atmosphere during curing process.
Moisture content prediction of municipal sludge drying process based on genetic algorithm optimized BP neural network
Authors: Zhang Kaiqiang , Wang Ningfung 
Published: April 2024

Abstract

Municipal sludge drying process of internal moisture detection difficulties, and in order to predict the change rule of the internal moisture in the hot-air drying process of municipal sludge, the moisture change of municipal sludge under different drying conditions was monitored through experiments. The moisture prediction model of municipal sludge drying process was established by optimizing the BP neural network using mathematical model, back-propagation (BP) neural network and genetic algorithm (GA), and the performance analysis of the model was carried out. In addition, a sensitivity analysis of the GA-BP model was performed. The results showed that the temperature had the most significant effect on the drying process of municipal sludge, reducing the thickness of the mud layer could improve the drying rate of sludge, and the moisture reduction rate of municipal sludge showed a fast and then a slow trend during the whole drying process. Through the performance analysis, the coefficient of determination of the test set of GA-BP model is 0.9999, and the root mean square error is only 0.0039, which means that the GA-BP model has a better prediction effect and can predict the dynamic change of moisture in the drying process of municipal sludge more accurately. The sensitivity analysis shows that the drying time and drying temperature have the greatest influence on moisture ratio(MR), and the results of the study can provide a theoretical basis for the optimization of the sludge drying process and procedure, and provide a powerful reference for guiding the resource utilization of sludge.
Comparison of Displacement Estimation Techniques for Background Oriented Schlieren of High-speed Compressible Turbulent Flows
Authors: Zhou Tanbo , Gaskins Jonathan , Poggie Jonathan , Bane Sally 
Published: April 2024

Abstract

Background oriented schlieren (BOS) is a non-intrusive optical method for measuring density gradients in a fluid flow based on changes of local refractive index.The density gradients can be obtained by observing the displacement betweentwo images of a background pattern, with and without the presence of the flow.Existing methods to estimate displacements include block matching and optical flow. Image registration in computer vision seeks reasonable transformationsbetween two images such that one matches the other and has been under-utilizedin determining the displacement for BOS image processing. Deformable imageregistration (DIR) methods allow non-global transformations and are proposedas displacement estimation methods for processing BOS images. Numerical raytracing simulations are performed to generate synthetic BOS images of variousflows. The estimated density gradient results of block matching, optical flow,and DIR methods are compared to the ground truth (the path-averaged densitygradient of the schlieren object used in ray tracing) to assess and compare theirperformances. The performances of these methods are also validated on experimental BOS images to determine the displacement estimation method that ismost suitable for high-speed, turbulent flows.
Limits of outpatient palliative oncological care: A cost analysis of nutritional interventions.
Authors: Molnarova Veronika , Maresova Petra , Rezny Lukas , Bezrouk Ales , Milka Dalibor , Priester Iva , Ticha Alena , Novosadova Martina , Filip Stanislav 
Published: April 2024

Abstract

Background
The purpose of palliative medicine is to achieve and maintain the best possible quality of life for patients and support their families, relatives, and friends. Therefore, we conducted a case-control observational retrospective study evaluating the economic burden of nutritional intervention during ambulatory palliative oncology care, aiming to implement the obtained data to the quality of healthcare.
Methods
A comparison of total expenses per patient was made between the three groups of patients, i.e., Group A – 256 patients with systematic nutritional intervention during 2020-22, Group B − 1393 patients treated during 2020-22, and Group C – 940 patients without systematic nutritional intervention during in 2017-19. The expense analysis was performed using mixed methods monitoring nutritional intervention, i.e. medical records, laboratory tests, and insurance bills from the palliative oncology clinic. The collected data included four categories (direct and indirect cost): nutritional supplements, other medical expenses, requested care, and other care. The qualitative costs and benefits analyses were done within the CBA method framework, i.e. online interviews of relevant stakeholders who were involved in the process of nutritional measures.
Results
The Mann–Whitney U-test showed significant (P < 0.001) differences between the tested groups, with the lowest median of total expenses in Group B (2,921 CZK) and the highest in Group A (16,692 CZK), demonstrating a significant reduction in total expenses. The same was observed in the comparison between Group C (4,923 CZK) and Group B (2,921 CZK) during 2020-22.
Conclusion
The present study proves that nutritional intervention, and the related modifications in palliative treatment, benefit the patients and reduce the overall costs of healthcare.
Visual and Semantic Guided Scene Text Retrieval
Authors: Luo Hailong , Ibrayim Mayire , Hamdulla Askar , Deng Qilin 
Published: April 2024

Abstract

In this paper, we introduce a novel end-to-end trainable network for the task of scene text retrieval. Diverging from the state-of-the-art methods that match the visual features of individual character images for retrieval, our network transforms the entire query text into a single query image. By integrating visual and language modules, our network extracts rich visual and semantic features from the query image, facilitating efficient similarity modeling and query matching. This hybrid embedding approach using visual-semantic features of query images shows excellent robustness in dealing with complex text styles and layouts. Experimental results on multiple benchmark datasets validate the superiority of our framework, especially in multilingual retrieval tasks, where our framework achieves a 20.15% increase in mAP score compared to the current state-of-the-art. This significant performance boost showcases the potent potential of our network in multilingual scene text retrieval tasks.
Micro-mechanical properties of the Song Dynasty stone tiles based on nanoindentation tests and homogenization approach
Authors: Wang Zhi-Liu , Hu Meng-Xin , Wang Yu-Long , Li Xin-Ming , Yin Song 
Published: April 2024

Abstract

The Song Dynasty stone tiles are one of the representatives of ancient Chinese building materials and reflect the technical level and the aesthetic concept of architecture in the Song Dynasty. Studying the mechanical properties of the Song Dynasty stone tiles is a great significance to design and develop restoration materials. The stone cultural relics are different from modern buildings, because of their particularity, cultural relics protection should preserve their original historical features as much as possible. It is a challenge to sample and perform traditional tests, which require numerous large specimens. The nanoindentation technique and the homogenization calculation method based on the Mori-Tanaka model were proposed to calculate the mechanical parameters of the Song Dynasty stone tiles. With the help of X-ray diffraction (XRD) and scanning electron microscope (SEM), the indentation morphology and mineral composition in indentation area were quantitatively analyzed. The mechanical properties, such as elastic modulus, hardness and fracture toughness of the Song Dynasty stone tiles in Henan, China, were investigated by nanoindentation test. The homogenization approach based on the Mori-Tanaka model was developed to upscale mechanical parameters from micro-scale to meso-scale, which were further compared with uniaxial compression results of non-standard samples. The results show that there is a positive linear correlation between elastic modulus, hardness and the fracture toughness under micro-scale. The average elastic modulus of red stone tiles and green stone tiles are 29.47GPa and 30.21GPa respectively. Compared with the parameter results obtained by upscaling, the deviation rates are 10.3% and 9.6%, respectively. The mechanical parameters of the Song Dynasty stone tiles obtained by nanoindentation test and homogenization approach is reliable.The proposed methods in this work provide the basis and reference for obtaining the mechanical strength index of the Song Dynasty stone tiles.
Evaluation of Physical and Mechanical Properties of Graphene Oxide Reinforced Epoxy/Kevlar Hybrid Composites
Authors: Hassin Md Shadman , Faruk Mohammad Omar , Ali Mir Iffat , Begum Shahida 
Published: April 2024

Abstract

Graphene is a miracle material with low density, excellent mechanical strength, electrical conductivity, molecular barrier properties and many other remarkable properties. Hence, recent research has been more focused on delving into various application areas of graphene. In this study, the effects of graphene oxide (GO) on the mechanical properties of composites based on epoxy resin and Kevlar fibers were investigated. The composites were fabricated by incorporating varying concentrations (1%, 3%, 5%, 10%, and 16%) of graphene oxide (GO) into an epoxy matrix. The matrix was reinforced by two different wt.% (12.5% and 25%) of Kevlar fibers (KF). The hybrid composites were manufactured by hand lay-up process in a silicon mold at room temperature. Mechanical characterizations such as flexural, impact and hardness test exhibited an enhancement of the mechanical properties of the composites. Moreover, the measured density showed a significant reduction in density with increasing wt.% of GO. As a result, it was possible to fabricate a composite with a significant increase of specific flexural strength and specific flexural modulus. A microstructural analysis of the composites was performed by Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Analysis (EDX). From the SEM images, it was revealed that the interphase bonding of the GO particles with Kevlar fibers and matrix was strong, thereby resulting in improved mechanical performance. It was observed that 5 wt.% GO incorporation along with 25wt.% KF showed improved flexural strength, hardness and impact strength than that of sample fabricated only with Kevlar.
Are Transformers more Suitable for Plant Disease Identification than Convolutional Neural Networks?
Authors: Zhou Changjian , Zhang Xin , Zhong Yujie 
Published: April 2024

Abstract

Recent studies suggest that the transformer-based architectures have made unprecedented achievements in various computer vision tasks, such as image classification, object detection, semantic segmentation, etc. However, as the de facto approach, convolutional neural networks (CNNs) have reigned for a decade in plant disease identification tasks. We cannot help but propose a scenario: are transformers more suitable for plant disease identification than CNNs? Conceivably, this work aims to further investigate and evaluate whether it is feasible to trivially switch to transformers in plant disease identification tasks. To address this issue, a series of experiments were curated into three training strategies and implemented on two representative plant disease image datasets. Experimental results indicated that the vanilla transformer methods performed unsatisfactorily when trained from scratch, and the two mainstream transfer learning-based approaches achieved better prediction performance but with little margin. It is encouraging that the self-supervision-based transformer methods outperform their CNN-based counterparts, which provides new insights for agricultural image processing. Importantly, this work revealed a model selection solution based on the experimental results and target datasets, and gained a better interpretation by visualizing the feature maps.
Stimulating the use of multigrain composite flours in instant multigrain semolina: A compositional and functional attributes
Authors: Vaduguru Viswanath , Puttananjaiah Mohankumari Honganoor 
Published: April 2024

Abstract
The study evaluated the proximate, functional properties, bioactive compound, and scavenging activity of multigrain semolina with and without acacia gum using composite flour (rice, ragi, cowpea, and black gram) formulations. The multigrain semolina is analyzed for its nutrient composition and biochemical properties. Bioactive components like total phenolic content, total flavonoid content, and antioxidant activity were also analyzed. In the case of semolina, S3-AG and S3 + AG reported highest protein content of 14.37 ± 0.44 and 14.32 ± 1.35%, respectively. S1-AG and S2 + AG show an increase in the protein. WAC of semolina was significantly higher than the values found for the control sample (wheat semolina, 103.86 ± 1.81). The main objective of this study is to replace wheat semolina with multigrain semolina as a rich source of protein to increase the nutritional quality and the functional properties of the product. Results also suggested that by blending cereals and pulse flour, it is possible to enhance the functional properties and bioactive components of the composite flours and semolina.
Exploring the Role of Governance Mechanisms in Promoting Sustainability Across Supply Chains
Authors: Reynolds Samantha 
Published: April 2024

Abstract
This qualitative research delves into the intricate relationship between governance mechanisms and sustainability practices within supply chains. Employing a qualitative approach, the study aims to elucidate the nuanced ways in which various governance mechanisms influence and promote sustainability initiatives across supply chains. Drawing upon interviews, case studies, and literature reviews, the research uncovers multifaceted insights into the role of governance mechanisms in fostering sustainable practices, thereby contributing to a deeper understanding of sustainable supply chain management. The findings reveal the significance of regulatory frameworks, industry standards, collaborative initiatives, contractual arrangements, buyer-supplier relationships, organizational culture, and leadership in shaping sustainability outcomes within supply chains. Regulatory frameworks and industry standards provide the foundation for ensuring compliance with environmental, social, and ethical requirements, while collaborative governance mechanisms foster transparency, accountability, and collective action across supply chain networks. Buyer-supplier relationships and organizational culture play critical roles in driving innovation, capacity-building, and continuous improvement in sustainability performance. Overall, the research underscores the interconnectedness of governance mechanisms across different levels of analysis and emphasizes the need for a holistic and integrated approach to sustainable supply chain management. By recognizing and leveraging these interdependencies, stakeholders can develop more effective strategies for advancing sustainability goals and creating shared value for stakeholders within and beyond the supply chain.