bluuebunny/crossref_metadata_2025_split huggingface dataset:
LKC-Net: Large kernel convolution object detection network
Authors: Wang Weina , Li Shuangyong , Shao Jiapeng , Jumahong Huxidan 
Published: March 2023

Abstract
Deep learning-based object detection methods have achieved great performance improvement. However, since small kernel convolution has been widely used, the semantic feature is difficult to obtain due to the small receptive fields, and the key information cannot be highlighted, resulting in a series of problems such as wrong detection, missing detection, and repeated detection. To overcome these problems, we propose a large kernel convolution object detection network based on feature capture enhancement and vast receptive field attention, called LKC-Net. Firstly, a feature capture enhancement block based on large kernel convolution is proposed to improve the semantic feature capturing ability, and depth convolution is used to reduce the number of parameters. Then, the vast receptive filed attention mechanism is constructed to enhance channel direction information extraction ability, and it is more compatible with the proposed backbone than other existing attention mechanisms. Finally, the loss function is improved by introducing the SIoU, which can overcome the angle mismatch problem between the ground truth and prediction box. Experiments are conducted on Pascal VOC and MS COCO datasets for demonstrating the performance of LKC-Net.
Brain Computer Interface training for patients with severe upper limb paresis after stroke - A randomized controlled pilot trial
Authors: Brunner Iris , Lundquist Camilla Biering , Pedersen Asger Roer , Spaich Erika , Dosen Strahinja , Savic Andrej 
Published: March 2023

Abstract
Background
Restorative Brain-Computer Interfaces (BCI) combined with visual feedback and functional electrical stimulation may provide sorely needed treatment alternatives for patients with severely impaired upper limb (UL) function after stroke.
Objectives
This study aimed to examine if BCI-based training is more effective in improving UL motor function than conventional therapy in the subacute phase after stroke and if patients with preserved cortical-spinal tract (CST) integrity benefit more from BCI training.
Methods
Forty patients with severe UL paresis (< 13 on Action Research Arm Test (ARAT) were randomized to either a 12-session BCI training as part of their rehabilitation or conventional UL rehabilitation. BCI sessions were conducted 3–4 times weekly for 3–4 weeks. At baseline, Transcranial Magnetic Stimulation (TMS) was performed to examine CST integrity. Main endpoint was the ARAT at 3 months post-stroke. A binominal logistic regression was conducted to examine the effect of treatment group and CST integrity on achieving meaningful improvement. In the BCI group, EEG data were analyzed to investigate if there were changes in Event-related desynchronization (ERD) and lateralization.
Results
Data from 35 patients (15 in the BCI group and 20 in the control group) were analyzed at 3-month follow-up. Few patients (10/35) improved above the minimally clinically important difference of 6 points on ARAT, 5/15 in the BCI group, 5/20 in control. An independent-samples Mann-Whitney U test revealed no differences between the two groups, p = 0.382. In the logistic regression only CST integrity was a significant predictor for improving UL motor function, p = 0.007.
Conclusion
Though more patients in the BCI group improved relative to the group size, the difference between the groups was not significant. In the present study, preserved CTS integrity was much more vital for UL improvement than which type of intervention the patients received. Larger studies including only patients with some preserved CST integrity should be attempted.
Obesity-and lipid-related indices as a predictor of hypertension in Mid-aged and Elderly Chinese: A Cross-sectional Study
Authors: Gui Jiaofeng , Li Yuqing , Liu Haiyang , Guo Lei-lei , Li Jinlong , Lei Yunxiao , Li Xiaoping , Sun Lu , Yang Liu , Yuan Ting , Wang Congzhi , Zhang Dongmei , Li Jing , Liu Mingming , Hua Ying , Zhang Lin 
Published: March 2023

Abstract
Objective
Middle-aged and elderly people in China probably suffer from hypertension. There is a close relationship between obesity-and lipid-related index and hypertension, which is recognized by recent studies. However, these studies have not systematically compared the relationship between the two. We aim to find the most effective obesity-and lipid-related index for predicting hypertension.
Method
A total of 9488 middle-aged and elderly people in China participated in this study. In this study, the subjects were divided into male and female groups by the definition of the 2018 Chinese Guidelines for Prevention and Treatment of Hypertension. Searching for the best predictors among 13 obesity-and lipid-related indicators through binary logistic regression analyses and receiver operator curve (ROC). These 13 indicators are body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR)
Results
After adjusting bias, all 13 indexes are risk factors for hypertension. In ROC curve analysis, thirteen obesity-and lipid-related factors can predict the occurrence of hypertension. Among them, CVAI has the best prediction effect (male: AUC = 0.660, female: AUC = 0.699). AUC for WHtR was equal to that for BRI and TyG -WHtR in identifying hypertension in male. Similarly, AUC of TyG-BMI and BMI were the same. In females, AUC for WHtR and BRI were the same when predicting hypertension. AUC of ABSI was much lower than other test indexes.
Conclusion
In predicting hypertension, thirteen obesity-and lipid-related factors are effective. In addition, in males and females, CVAI is the best indicator to indicate hypertension. TyG-WHtR, WHtR, and BRI performed well in predicting metabolic syndrome in both males and females. ABSI has a poor ability to predict hypertension.
A Perspective on The Synergistic Potential of Artificial Intelligence and Product-Based Learning Strategies in Biobased Materials Education
Authors: Marquez Ronald , Barrios Nelson , Vera Ramon , Mendez Maria E. , Tolosa Laura , Zambrano Franklin , Li Yali 
Published: March 2023

Abstract
The integration of product-based learning strategies in Materials in Chemical Engineering education is crucial for students to gain the skills and competencies required to thrive in the emerging circular bioeconomy. Traditional materials engineering education has often relied on a transmission teaching approach, in which students are expected to passively receive information from instructors. However, this approach has shown to be inadequate under the current circumstances, in which information is readily available and innovative tools such as artificial intelligence and virtual reality environments are becoming widespread (e.g., metaverse). Instead, we consider that a critical goal of education should be to develop aptitudes and abilities that enable students to generate solutions and products that address societal demands. In this work, we propose innovative strategies, such as product-based learning methods and GPT (Generative Pre-trained Transformer) artificial intelligence text generation models, to modify the focus of a Materials in Chemical Engineering course from unsustainable materials to sustainable ones, aiming to address the critical challenges of our society. This approach aims to achieve two objectives: first to enable students to actively engage with raw materials and solve real-world challenges, and second, to foster creativity and entrepreneurship skills by providing them with the necessary tools to conduct brainstorming sessions and develop procedures following scientific methods. The incorporation of circular bioeconomy concepts, such as renewable resources, waste reduction, and resource efficiency into the curriculum provides a framework for students to understand the environmental, social, and economic implications in chemical engineering. It also allows them to make informed decisions within the circular bioeconomy framework, benefiting society by promoting the development and adoption of sustainable technologies and practices.
Solving inverse problems with sparse noisy data, operator splitting and physics-constraints machine learning
Authors: Li Chun , Deng Lijun 
Published: March 2023

Abstract
Using measurable data as a starting point, inverse problems can be used to estimate model parameters. In science and engineering, several problems can be viewed as inverse problems. Partial differential equations (PDEs) or variational problems are also used to characterize similar issues. Typically, an energy function is used to address a variational problem. Because curvature-driven regularities have been shown to require a lot of prior understanding of physics concepts, they have received a lot of attention. Unfortunately, curvature-driven regularities correlate with the higher-order Euler-Lagrangian equations and frequently have nonsmooth and nonconvex features, making numerical solutions a difficult challenge in a variety of applications. Thus, we introduce a method based on physics-constrained deep learning based on automatic differentiation (AD) to manage inverse problems from noisy data. Additionally, to address this challenge, we combine standard variational approaches with deep learning-based algorithms. The operator split technique can successfully break nonconvex variational models into multiple simple subproblems to solve. Each subproblem corresponds to an Euler-Lagrangian PDE, which is effectively solved using deep neural networks via the AD process.
Neutron biological effectiveness in inducing DNA damage: a full mapping as a function of incident neutron energy and depth in a human-sized phantom
Authors: Mentana Alice , Quaresima Virgilio , Kundrát Pavel , Guardamagna Isabella , Lonati Leonardo , Iaria Ombretta , Fino Luca Di , Romoli Giulia , Amantini Giorgia Santi , Narici Livio , Baiocco Giorgio 
Published: March 2023

Abstract
We present new developments for an ab-initio model of the neutron relative biological effectiveness (RBE) in inducing specific classes of DNA damage. RBE is evaluated as a function of the incident neutron energy and of the depth inside a human-sized phantom. The adopted mechanistic approach traces neutron RBE back to its origin, i.e. neutron physical interactions with biological tissues. To this aim, we combined the simulation of radiation transport through biological matter, performed with the Monte Carlo code PHITS, and the prediction of DNA damage using analytical formulas, which ground on a large database of biophysical radiation track structure simulations performed with the code PARTRAC. In particular, two classes of DNA damage were considered: sites and clusters of double strand breaks (DSBs), which are known to be correlated with cell fate following radiation exposure. Within a coherent modelling framework, this approach tackles the variation of neutron RBE in a wide energy range, from thermal neutrons to neutrons of hundreds of GeV, and reproduce effects related to depth in a human-size receptor, as well as to the receptor size. RBE predictions were successfully compared to the currently adopted radiation protection standards for neutron weighting factors. Our results also suggest that great care is needed when applying weighting factors as a function of incident neutron energy, not explicitly considering RBE variation in the target. Look-up RBE tables and an analytical representation of the maximal RBE vs. neutron energy are finally proposed, to facilitate the use of our results in radiation biology studies and radiation protection applications with neutron exposures.
On the evaluation of grinding wheel surface condition under different process parameters via in-machine monitoring
Authors: Muñoz Arkaitz , Barrenetxea David , Álvarez Jorge , Garcia Maria , Godino Leire 
Published: March 2023

Abstract
The role of the grinding wheel is significant in all grinding operations. Two main indicators related to the process behaviour are the ground workpiece surface roughness and the consumed amount of energy. Both of these factors are affected by grinding wheel topography condition. Thus, an in-deep analysis of the wheel surface condition will extend the understanding of both process behaviour and wheel performance. This condition can be described by the micro-wear mechanisms such as flattening of abrasive grits (wear flat) and adhesion of chips between grits and pores (wear by deposition or loading) in conjunction with the arrangement of abrasive grains. In this sense, in this work a tool for in-machine analysis of wheel surface features such as attritious wear, loading and the number of grains involved in the cutting action is developed. The device is then used in experimental tests in order to validate its ability to analyse the wheel-process behaviour. Researchers have deeply studied the influence of the wheel wear condition on the grinding process, but there is still a lack of knowledge on the effect that both grinding and dressing processes have on the wheel wear condition evolution. The developed tool is also employed for that purpose. Results obtained with the device are consistent with previous works and literature. Therefore, it can be used for a comprehensive understanding of process behaviour during grinding with different wheel-workpiece material combinations and different process conditions, as well as for the analysis and optimization of new abrasives and bonds performances.
The intelligence way of economical synthesis strategies of an N-alkylcarbazole
Authors: Jabha Mohamed , Mesky Mohammed El , Zgueni Hicham , Amri Nabil , Azdouz M’barek , Oubair Ahmad , Chebabe Driss , Azrour Mohamed , Mabrouk El Houssine 
Published: March 2023

Abstract
The alkaloid carbazole is one of the relevant structural motifs in drug discovery. Indeed, carbazoles have been largely investigated for their various biological properties. In this article, in order to ensure the possibility of carrying out this reaction at the level of the synthesis laboratory and to have access to a new active biomolecule, we present the theoretical study of the synthesis strategies of an N-alkylcarbazole using the DFT method at B3LYP, with the basis set 6-31G (d, p). In fact, this research has enabled us to establish a simple, economical and efficient synthesis strategy for this nitrogenous heterocyclic with an excellent yield, by N-alkylation between carbazole and propargyl bromide under different experimental conditions. We have developed an environmentally friendly compound, mild condition protocol and convenient procedure for the preparation of this polycyclic aromatic compound. The structure of the synthesized compound was determined by spectroscopic methods: 1H-NMR, 13C-NMR and MS data. The theoretical results corroborate with experiences. The study of the substitution effect on the optical properties of reagents and products shows that N-alkylation has an influence on the optical properties.
Heterogeneity governs 3D-cultures of clinically relevant microbial communities
Authors: Pacheco Daniela , Bertoglio Federico , Butnarasu Cosmin , Vargas Natalia Suarez , Guagliano Giuseppe , Ziccarelli Anna , Briatico‐Vangosa Francesco , Ruzzi Vincenzo , Buzzaccaro Stefano , Piazza Roberto , Uden Sebastião van , Crotti Elena , Visentin Sonja , Visai Livia , Petrini Paola 
Published: March 2023

Abstract
A distinctive feature of the biological substrates hosting bacterial niches is their intrinsic heterogeneity, which should be retained in in vitro cultures to closely represent the complex microbial ecology. Here, we design and characterise 3D substrates providing bacteria with environments that possess structural heterogeneity and spontaneous microscopic dynamics. As a case study, we generate by diffusion-induced gelation a mucin-based hydrogel (CF-Mu3Gel) bioinspired on cystic fibrosis (CF) mucus, a microbial niche challenging current therapeutic strategies. We demonstrate that gradients in the properties of the CF-Mu3Gel impact the organisation and the antimicrobial tolerance in mono- and co-cultures of S. aureus and P. aeruginosa. This leads to typical microbial aggregates and generates anoxic regions mimicking CF clinical features that standard cultures are unable to emulate. Our findings shed new light on the understanding of how the substrate influences microbial behaviour, providing a new platform to develop novel effective and possibly personalised therapies.
New insight of chemical constituents in Persea americana fruit against obesity: A data-driven study
Authors: Oh Ki-Kwang , Yoon Sang-Jun , Lee Su-Been , Lee Sang Yoon , Gupta Haripriya , Ganesan Raja , Sharma Satya Priya , Won Sung-Min , Jeong Jin-Ju , Kim Dong Joon , Suk Ki-Tae 
Published: March 2023

Abstract
BACKGROUND
Persea americana fruit (PAF) is a favorable nutraceutical resource that comprises diverse unsaturated fatty acids. Unsaturated fatty acids are of significance in dietary supplementation, as they relieve metabolic disorders, including obesity (OB). Unquestionably, a plethora of natural plants contain fatty acids like those found in PAF. This study focused on the anti-OB efficacy of the non-fatty acids in PAF using a network pharmacology approach.
METHODS
The chemical constituents of PAF were retrieved from the NPASS database and literature sources. The OB-related targets obtained by DisGeNET and the overlapping targets from the SEA and STP databases were analyzed with a Venn diagram to discover the crucial targets in OB. The crucial targets were analyzed via PPI and PSTC networks, the constructed bubble chart and molecular docking studies. Finally, the toxicities of the key compounds were identified by ProTox-II.
RESULTS
A total of 41 chemical compounds in PAF were identified by NPASS and other reports. The 31 overlapping targets were selected from the 52 intersecting targets and OB-related targets (3028) and were considered to be key protein encoding genes in OB, with AKT1 being the most significant among them. On the bubble chart, the PPAR signaling pathway had the highest rich factor and its modulation was determined to be the key mechanism, suggesting that this pathway may have an agonistic function for the treatment of OB. Likewise, the PSTC network showed that AKT1 had the greatest degree value. The MDA results showed that AKT1-γ-tocopherol, PPARA-fucosterol, PPARD-stigmasterol, PPARG-fucosterol, NR1H3-campesterol, and ILK-α-tocopherol formed the most stable complexes. These five key compounds were nontoxic, and could be developed as new antagonists to alleviate OB.
CONCLUSION
In summary, alpha-tocopherol, gamma-tocopherol, fucosterol, stigmasterol, and campesterol might be key players in the activation of the PPAR signaling pathway.
Both Cytomegalovirus and Epstein-Barr virus infections affect quantities of circulating T- cells and combined they result in an aging-related T-cell phenotype at younger age
Authors: Hofstee Marloes Imke , Cevirgel Alper , de Zeeuw-Brouwer Mary-Lène , de Rond Lia , Klis Fiona van der , Buisman Anne-Marie 
Published: March 2023

Abstract
Cytomegalovirus (CMV) is known to alter circulating effector memory CD45RA+ (TemRA) or CD45RA- (TemRO) T-cell numbers, but whether Epstein-Barr virus (EBV) does the same or this is amplified during a CMV and EBV co-infection is unclear.
Immune cell numbers in blood of children and young, middle-aged, and senior adults (n = 336) were determined with flow cytometry, and additional multivariate linear regression, intra-group correlation, and cluster analyses were performed. CMV alone caused more immune cell variance for all age groups, and CMV+ EBV- senior adults had more late-differentiated CD4+ and CD8+ TemRA and TemRO T-cells. EBV alone resulted in a more equal immune cell composition for children and young adults, and CMV- EBV+ senior adults had more intermediate/late-differentiated CD4+ TemRA and TemRO T-cells. CMV and EBV together gave young and middle-aged adults with an elevated BMI and anti-CMV antibody levels a similar immune cell composition as senior adults, and CMV+ EBV+ middle-aged adults had more late-differentiated CD8+ TemRA, TemRO, and HLA-DR+ CD38- T-cells than CMV+ EBV- controls.
This study identified CMV- or EBV-induced changes in T-cell numbers and that some young and middle-aged adults were more negatively impacted by a CMV and EBV co-infection giving them an aging-related T-cell phenotype.
Enhancing photoresponse of GaAs-based photodetector by plasmon grating structures
Authors: Ma Zhengzhou , Tang Ping , Xue Jiancai , Zhou Jinyun 
Published: March 2023

Abstract
Nanostructured mental-semiconductor-mental photodetectors (MSM-PDs) can assist in future high-speed communication devices for achieving high responsivity characteristics. However, such devices suffer from low responsivity due to low absorption, and the large band gap limits its detection range. Herein, we propose a GaAs-based photodetector with enhanced photoresponse by plasmonic Au-GaAs grating structure. The design of a grating structure on the surface of n-GaAs can excite a plasmon mode to enhance the photoelectric performance of photodetectors. Consequently, under 795 nm incident light irradiation, the grating hybrid detector exhibits a nearly 4.2-fold increase in photocurrent compared to the bare GaAs device. The enhanced absorption can be up to 99% and a specific responsivity of 240 mA/W is realized. These results can thus provide a potential scheme to fabricate high-performance GaAs detector for numerous applications.
The Role of Free Vitamin D and Vitamin D Binding Protein in SARS-Cov-2 Infection in Children
Authors: Us Mahmut Caner , Lanpir Aslı Devrim , Kurtuluş Şükran Özdatlı , Yağcı Mesut , Akarsu Özlem , Şahin Kamil , Akkoç Gülşen 
Published: March 2023

Abstract
Purpose: Many studies have discussed the effects of serum vitamin D deficiency in SARS-CoV-2 patients. This study aimed to investigate the relationship between SARS-CoV-2 infection severity and free vitamin D (FVD) and bioavailable vitamin D (BAVD) levels in children.
Methods: A prospective case-control study design was used. Participants were divided into three groups based on the World Health Organization (WHO) COVID-19 Clinical Progression Scale. Serum 25-hydroxyvitamin D (25OH vitamin D; ng/mL), albumin (g/L), and vitamin D binding protein (ng/mL) levels were evaluated to investigate the relationship between disease severity and FVD and BAVD levels.
Results: In total, 82 participants were included in the study. Of those, 24.4 % were uninfected (n = 20), 50% had a mild case of SARSS-CoV-2 (n = 41), and 25.6% had a moderate case (n = 21). There was a statistically significant difference in FVD and BAVD levels between the groups (p = 0.026). Median FVD (p = 0.007, Cohen’s d = 0.84) and BAVD (p = 0.007, Cohen’s d = 0.86) levels were significantly higher in the mild group compared to the moderate group. FVD and BAVD metabolites were moderately positively correlated with lymphocyte counts (FVD: r = 0.437, p < 0.001; BAVD: r = 0.439, p < 0.001).
Conclusion: This is the first study to demonstrate a relationship between SARS-CoV-2 symptom severity and FVD and BAVD levels. The relationship between FVD and BAVD levels and lymphocyte counts could play an important role in symptom severity and should be evaluated in further studies.
The study was registered with Clinical Trials (NCT05598957, 10/06/2022).