bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys
Authors: Yang Biaobiao , Vassilev-Galindo Valentin , Llorca Javier 
Published: January 2024

AbstractTwin nucleation in textured Mg alloys was studied by means of electron back-scattered diffraction in samples deformed in tension along different orientations in more than 3000 grains. In addition, 28 relevant parameters, categorized in four different groups (loading condition, grain shape, apparent Schmid factors, and grain boundary features) were also recorded for each grain. This information was used to train supervised machine learning classification models to analyze the influence of the microstructural features on the nucleation of extension twins in Mg alloys. It was found twin nucleation is favored in larger grains and in grains with high twinning Schmid factors, but also that twins may form in the grains with very low or even negative Schmid factors for twinning if they have at least one smaller neighboring grain and another one (or the same) that is more rigid. Moreover, twinning of small grains with high twinning Schmid factors is favored if they have low basal slip Schmid factors and have at least one neighboring grain with a high basal slip Schmid factor that will deform easily. These results reveal the role of many-body relationships, such as differences in stiffness and size between a given grain and its neighbors, to assess extension twin nucleation in grains unfavorably oriented for twinning.
Construction of chitosan-supported nickel cobaltite composite for efficient electrochemical capacitor and water-splitting applications
Authors: Medany Shymaa S. , Nafady Ayman , Soomro Razium Ali , Hefnawy Mahmoud A. 
Published: January 2024

AbstractThe construction of highly efficient electrode material is of considerable interest, particularly for high capacitance and water-splitting applications. Herein, we present the preparation of a NiCo2O4-Chitosan (NC@Chit) nanocomposite using a simple hydrothermal technique designed for applications in high capacitance and water-splitting. The structure/composition of the NC@Chit composite was characterized using different analytical methods, containing electron microscope (SEM and TEM), and powder X-ray diffraction (XRD). When configured as an anode material, the NC@Chit displayed a high capacitance of 234 and 345 F g−1 (@1Ag−1 for GC/NC and NC@Chit, respectively) in an alkaline electrolyte. The direct use of the catalyst in electrocatalytic water-splitting i.e., HER and OER achieved an overpotential of 240 mV and 310 mV at a current density of 10 mA cm−2, respectively. The obtained Tafel slopes for OER and HER were 62 and 71 mV dec−1, respectively whereas the stability and durability of the fabricated electrodes were assessed through prolonged chronoamperometry measurement at constant for 10 h. The electrochemical water splitting was studied for modified nickel cobaltite surface using an impedance tool, and the charge transfer resistances were utilized to estimate the electrode activity.
Insights into the DHQ-BN: mechanical, electronic, and optical properties
Authors: Lopes Lima K. A. , Lopes Mendonça F. L. , Giozza W. F. , de Sousa Junior R. T. , Ribeiro Junior L. A. 
Published: January 2024

AbstractComputational materials research is vital in improving our understanding of various class of materials and their properties, contributing valuable information that helps predict innovative structures and complement empirical investigations. In this context, DHQ-graphene recently emerged as a stable two-dimensional carbon allotrope composed of decagonal, hexagonal, and quadrilateral carbon rings. Here, we employ density functional theory calculations to investigate the mechanical, electronic, and optical features of its boron nitride counterpart (DHQ-BN). Our findings reveal an insulating band gap of 5.11 eV at the HSE06 level and good structural stability supported by phonon calculations and ab initio molecular dynamics simulations. Moreover, DHQ-BN exhibits strong ultraviolet (UV) activity, suggesting its potential as a highly efficient UV light absorber. Its mechanical properties, including Young’s modulus (230 GPa) and Poisson’s ratio (0.7), provide insight into its mechanical resilience and structural stability.
Emerald eco-synthesis: harnessing oleander for green silver nanoparticle production and advancing photocatalytic MB degradation with TiO2&CuO nanocomposite
Authors: Shawky Amira M. , Elshypany Rania , El Sharkawy Heba M. , Mubarak Mahmoud F. , Selim Hanaa 
Published: January 2024

AbstractThe tertiary composite of TiO2/CuO @ Ag (TCA) were synthesized by the solid state method using different ratios of TiO2/CuO NCs and Ag NPs. The structural, morphological, and optical properties of nanocomposites were analyzed by scanning electron microscope, Transmission electron microscope, X-ray diffraction, Fourier transform infrared spectra, UV–Vis diffuse reflectance spectra (UV–Vis/DRS) and photoluminescence spectrophotometry. The results showed enhanced activity of TCA hybrid nano crystals in oxidizing MB in water under visible light irradiation compared to pure TiO2. The photocatalytic performance TCA samples increased with suitable Ag content. The results show that the photo degradation efficiency of the TiO2 compound improved from 13 to 85% in the presence of TiO2–CuO and to 98.87% in the presence of Ag containing TiO2–CuO, which is 7.6 times higher than that of TiO2. Optical characterization results show enhanced nanocomposite absorption in the visible region with long lifetimes between e/h+ at optimal TiO2–CuO/Ag (TCA2) ratio. Reusable experiments indicated that the prepared TCA NC photo catalysts were stable during MB photo degradation and had practical applications for environmental remediation.
Efficient pneumonia detection using Vision Transformers on chest X-rays
Authors: Singh Sukhendra , Kumar Manoj , Kumar Abhay , Verma Birendra Kumar , Abhishek Kumar , Selvarajan Shitharth 
Published: January 2024

AbstractPneumonia is a widespread and acute respiratory infection that impacts people of all ages. Early detection and treatment of pneumonia are essential for avoiding complications and enhancing clinical results. We can reduce mortality, improve healthcare efficiency, and contribute to the global battle against a disease that has plagued humanity for centuries by devising and deploying effective detection methods. Detecting pneumonia is not only a medical necessity but also a humanitarian imperative and a technological frontier. Chest X-rays are a frequently used imaging modality for diagnosing pneumonia. This paper examines in detail a cutting-edge method for detecting pneumonia implemented on the Vision Transformer (ViT) architecture on a public dataset of chest X-rays available on Kaggle. To acquire global context and spatial relationships from chest X-ray images, the proposed framework deploys the ViT model, which integrates self-attention mechanisms and transformer architecture. According to our experimentation with the proposed Vision Transformer-based framework, it achieves a higher accuracy of 97.61%, sensitivity of 95%, and specificity of 98% in detecting pneumonia from chest X-rays. The ViT model is preferable for capturing global context, comprehending spatial relationships, and processing images that have different resolutions. The framework establishes its efficacy as a robust pneumonia detection solution by surpassing convolutional neural network (CNN) based architectures.
GMean—a semi-supervised GRU and K-mean model for predicting the TF binding site
Authors: Chuah Chai Wen , He Wanxian , Huang De-Shuang 
Published: January 2024

AbstractThe transcription factor binding site is a deoxyribonucleic acid sequence that binds to transcription factors. Transcription factors are proteins that regulate the transcription gene. Abnormal turnover of transcription factors can lead to uncontrolled cell growth. Therefore, discovering the relationships between transcription factors and deoxyribonucleic acid sequences is an important component of bioinformatics research. Numerous deep learning and machine learning language models have been developed to accomplish these tasks. Our goal in this work is to propose a GMean model for predicting unlabelled deoxyribonucleic acid sequences. The GMean model is a hybrid model with a combination of gated recurrent unit and K-mean clustering. The GMean model is developed in three phases. The labelled and unlabelled data are processed based on k-mers and tokenization. The labelled data is used for training. The unlabelled data are used for testing and prediction. The experimental data consists of deoxyribonucleic acid experimental of GM12878, K562 and HepG2. The experimental results show that GMean is feasible and effective in predicting deoxyribonucleic acid sequences, as the highest accuracy is 91.85% in predicting K562 and HepG2. This is followed by the prediction of the sequence between GM12878 and K562 with an accuracy of 89.13%. The lowest accuracy is the prediction of the sequence between HepG2 and GM12828, which is 88.80%.
Efficacy and safety of intravitreal faricimab for neovascular age-related macular degeneration: a systematic review and meta-analysis
Authors: Yen Wei-Ting , Wu Chen-Shu , Yang Chang-Hao , Chen Yi-Hao , Lee Cho-Hao , Hsu Cherng-Ru 
Published: January 2024

AbstractWe conducted a systematic review and meta-analysis to evaluate the visual, anatomical, and safety outcomes of the intravitreal faricimab, a novel vascular endothelial growth factor (VEGF)/angiopoietin-2 (Ang-2) bispecific agent, in neovascular age-related macular degeneration (nAMD) patients. The follow-up times in the included studies ranged from a minimum of 36 weeks to a maximum of 52 weeks. EMBASE, Ovid-Medline, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Scopus, the WHO ICTRP, ClinicalTrial.gov, the EU Clinical Trials Register, and Chinese Clinical Trial Registry (ChiCTR) were searched (The last literature search was performed on August 17, 2023) for randomized controlled trials (RCTs) comparing faricimab with control groups for neovascular age-related macular degeneration (nAMD). The risk of bias for eligible RCTs was independently assessed using the Cochrane Risk of Bias Tool by two authors (W.-T.Y. and C.-S.W.). The meta-analysis was conducted using Review Manager 5.4 software. The mean best corrected visual acuity (BCVA), central subfield thickness (CST), total choroidal neovascularization (CNV) area, and total lesion leakage were analyzed as continuous variables and the outcome measurements were reported as the weighted mean difference (WMD) with a 95% confidence interval (CI). The ocular adverse events and ocular serious adverse events were analyzed as dichotomous variables and the outcome measurements were analyzed as the odds ratios (ORs) with a 95% CI. Random-effects model was used in our study for all outcome synthesizing due to different clinical characteristics. Four RCTs with 1,486 patients were eligible for quantitative analysis. There was no statistically significant difference between intravitreal faricimab and anti-VEGF in BCVA [weighted mean difference (WMD) = 0.47; 95% CI: (− 0.17, 1.11)]. The intravitreal faricimab group showed numerically lower CST [WMD =  − 5.96; 95% CI = (− 7.11, − 4.82)], total CNV area [WMD =  − 0.49; 95% CI = (− 0.68, − 0.30)], and total lesion leakage [WMD =  − 0.88; 95% CI = (− 1.08, − 0.69)] after intravitreal therapy compared with the intravitreal anti-VEGF group. There were no statistically significant differences between intravitreal faricimab and anti-VEGF in ocular adverse events (AEs) [pooled odds ratio (OR) = 1.10; 95% CI = (0.81, 1.49)] and serious adverse events (SAEs) [pooled OR = 0.84; 95% CI = (0.37, 1.90)]. The intravitreal bispecific anti-VEGF/angiopoietin 2 (Ang2) antibody faricimab with a extended injection interval was non-inferior to first-line anti-VEGF agents in BCVA. It was safe and had better anatomical recovery. Large, well-designed RCTs are needed to explore the potential benefit of extended faricimab for nAMD. This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42022327450).
Physics and semantic informed multi-sensor calibration via optimization theory and self-supervised learning
Authors: Hayoun Shmuel Y. , Halachmi Meir , Serebro Doron , Twizer Kfir , Medezinski Elinor , Korkidi Liron , Cohen Moshik , Orr Itai 
Published: January 2024

AbstractWidespread adaptation of autonomous, robotic systems relies greatly on safe and reliable operation, which in many cases is derived from the ability to maintain accurate and robust perception capabilities. Environmental and operational conditions as well as improper maintenance can produce calibration errors inhibiting sensor fusion and, consequently, degrading the perception performance and overall system usability. Traditionally, sensor calibration is performed in a controlled environment with one or more known targets. Such a procedure can only be carried out in between operations and is done manually; a tedious task if it must be conducted on a regular basis. This creates an acute need for online targetless methods, capable of yielding a set of geometric transformations based on perceived environmental features. However, the often-required redundancy in sensing modalities poses further challenges, as the features captured by each sensor and their distinctiveness may vary. We present a holistic approach to performing joint calibration of a camera–lidar–radar trio in a representative autonomous driving application. Leveraging prior knowledge and physical properties of these sensing modalities together with semantic information, we propose two targetless calibration methods within a cost minimization framework: the first via direct online optimization, and the second through self-supervised learning (SSL).
Establishment of a synchronized tyrosinase transport system revealed a role of Tyrp1 in efficient melanogenesis by promoting tyrosinase targeting to melanosomes
Authors: Nakamura Hikari , Fukuda Mitsunori 
Published: January 2024

AbstractTyrosinase (Tyr) is a key enzyme in the process of melanin synthesis that occurs exclusively within specialized organelles called melanosomes in melanocytes. Tyr is synthesized and post-translationally modified independently of the formation of melanosome precursors and then transported to immature melanosomes by a series of membrane trafficking events that includes endoplasmic reticulum (ER)-to-Golgi transport, post-Golgi trafficking, and endosomal transport. Although several important regulators of Tyr transport have been identified, their precise role in each Tyr transport event is not fully understood, because Tyr is present in several melanocyte organelles under steady-state conditions, thereby precluding the possibility of determining where Tyr is being transported at any given moment. In this study, we established a novel synchronized Tyr transport system in Tyr-knockout B16-F1 cells by using Tyr tagged with an artificial oligomerization domain FM4 (named Tyr-EGFP-FM4). Tyr-EGFP-FM4 was initially trapped at the ER under oligomerized conditions, but at 30 min after chemical dissociation into monomers, it was transported to the Golgi and at 9 h reached immature melanosomes. Melanin was then detected at 12 h after the ER exit of Tyr-EGFP-FM4. By using this synchronized Tyr transport system, we were able to demonstrate that Tyr-related protein 1 (Tyrp1), another melanogenic enzyme, is a positive regulator of efficient Tyr targeting to immature melanosomes. Thus, the synchronized Tyr transport system should serve as a useful tool for analyzing the molecular mechanism of each Tyr transport event in melanocytes as well as in the search for new drugs or cosmetics that artificially regulate Tyr transport.
Long term studying of uranium and radium-226 activity in drinking water in some regions of Ukraine and assessment of corresponding hypotetical irradiation doses
Authors: Buzynnyi Mykhailo , Mykhailova Liubov 
Published: January 2024

AbstractThe article summarizes the activity concentrations data of 226Ra and the sum of uranium isotopes (∑U) in samples of drinking underground water for different regions of Ukraine studied during 1998–2023 in the radiation monitoring laboratory of the State Institution "O.M. Marzieiev Institute of Public Health National Academy of Medical Sciences of Ukraine. Arithmetic mean and standard deviations, minimum and maximum values for 226Ra and ∑U activity concentrations are presented for the entire 1240 sample set and for each region separately. Collected data show that the established state permissible level for drinking water of 1.0 Bq/l is exceeded for 226Ra in 1.1% of the studied samples, and for ∑U—in 3.9% correspondingly. The detected high levels of 226Ra and ∑U activity concentrations correspond to certain regions belonging to the Ukrainian crystalline shield territory. A comparison of the current data with the data of previous studies held during of 1989–1991 indicates a significant difference: for the previous studies the average and standard deviations are much higher. We attribute this to the fact that the centralized sampling of previous studies was random, and it was related exclusively to communal water supply systems. At the same time, the current sample set covers a much larger number of regions, different water consumers; the data set includes the results of repeated studies for a large number of sources, in particular, sources with purified water. Hypothetical exposure doses caused by consumption of 226Ra and ∑U in water for the current sample set were estimated for different age groups for each sample studied, as is, without taking into account the pattern of water consumption. The corresponding dose exceeds the WHO recommended value of 0.1 mSv per year for children under the age of one year for 220 cases (17.7%). This dose limit excess for other age groups corresponds—for children: aged 12–17 years—13.1%, aged 1–2 years—7.4%, 7–12 years old—5.6%, 2–7 years old—3.9% and for adults—4.1%.
Using Spirulina platensis as a natural biocoagulant for polystyrene removal from aqueous medium: performance, optimization, and modeling
Authors: Eydi Gabrabad Mohaddeseh , Yari Mohammadreza , Bonyadi Ziaeddin 
Published: January 2024

AbstractMicroplastics (MPs) are newly recognized contaminants that result from the breakdown of plastics released into aquatic environments. This study focuses on the elimination of polystyrene (PS) using S. platensis, a natural biocoagulant, from aqueous solutions. The research investigated several crucial variables, including the initial level of PS ranging from 100 to 900 mg L−1, pH levels from 4 to 10, the contact time of 20–40 min, and doses of S. platensis ranging from 50 to 250 mg L−1. The analysis of the data revealed that the quadratic model offered the best fit for the experimental results. In the present study, we utilized S. platensis as a novel natural biocoagulant to effectively eliminate PS from aqueous solutions. Process optimization was performed using a Box–Behnken design (BBD). The best-fitting model for the data was the quadratic model. The results displayed that the highest elimination of PS (81%) was occurred at a pH of 4, with a contact time of 30 min, a dose of S. platensis at 250 mg L−1, and a PS concentration of 500 mg L−1. These findings show that S. platensis has a significant effect on removing PS from the aquatic environment. Algae can serve as a convenient and eco-friendly method, replacing chemical coagulants, to effectively remove MPs from the aquatic environment.
A lncRNA Dleu2-encoded peptide relieves autoimmunity by facilitating Smad3-mediated Treg induction
Authors: Tang Sibei , Zhang Junxun , Lou Fangzhou , Zhou Hong , Cai Xiaojie , Wang Zhikai , Sun Libo , Sun Yang , Li Xiangxiao , Fan Li , Li Yan , Jin Xinping , Deng Siyu , Yin Qianqian , Bai Jing , Wang Hong , Wang Honglin 
Published: January 2024

AbstractMicropeptides encoded by short open reading frames (sORFs) within long noncoding RNAs (lncRNAs) are beginning to be discovered and characterized as regulators of biological and pathological processes. Here, we find that lncRNA Dleu2 encodes a 17-amino-acid micropeptide, which we name Dleu2-17aa, that is abundantly expressed in T cells. Dleu2-17aa promotes inducible regulatory T (iTreg) cell generation by interacting with SMAD Family Member 3 (Smad3) and enhancing its binding to the Foxp3 conserved non-coding DNA sequence 1 (CNS1) region. Importantly, the genetic deletion of Dleu2-17aa in mice by start codon mutation impairs iTreg generation and worsens experimental autoimmune encephalomyelitis (EAE). Conversely, the exogenous supplementation of Dleu2-17aa relieves EAE. Our findings demonstrate an indispensable role of Dleu2-17aa in maintaining immune homeostasis and suggest therapeutic applications for this peptide in treating autoimmune diseases.
Context‐aware relation enhancement and similarity reasoning for image‐text retrieval
Authors: Cui Zheng , Hu Yongli , Sun Yanfeng , Yin Baocai 
Published: January 2024

AbstractImage‐text retrieval is a fundamental yet challenging task, which aims to bridge a semantic gap between heterogeneous data to achieve precise measurements of semantic similarity. The technique of fine‐grained alignment between cross‐modal features plays a key role in various successful methods that have been proposed. Nevertheless, existing methods cannot effectively utilise intra‐modal information to enhance feature representation and lack powerful similarity reasoning to get a precise similarity score. Intending to tackle these issues, a context‐aware Relation Enhancement and Similarity Reasoning model, called RESR, is proposed, which conducts both intra‐modal relation enhancement and inter‐modal similarity reasoning while considering the global‐context information. For intra‐modal relation enhancement, a novel context‐aware graph convolutional network is introduced to enhance local feature representations by utilising relation and global‐context information. For inter‐modal similarity reasoning, local and global similarity features are exploited by the bidirectional alignment of image and text, and the similarity reasoning is implemented among multi‐granularity similarity features. Finally, refined local and global similarity features are adaptively fused to get a precise similarity score. The experimental results show that our effective model outperforms some state‐of‐the‐art approaches, achieving average improvements of 2.5% and 6.3% in R@sum on the Flickr30K and MS‐COCO dataset.
Intrusion detection and defence for CAN bus through frequency anomaly analysis and arbitration mechanism
Authors: Dong Qiang , Song Zenglu , Shao Haoshu 
Published: January 2024

AbstractAs automobile intelligence continues to develop, the electronic control units connected to the Controller Area Network (CAN) bus within vehicles face an increasing number of threats from potential attacks originating from the internet. To address this issue, an intrusion detection and defence method is proposed that is capable of detecting illegal messages through the use of frequency anomaly detection, and subsequently disrupting them through utilization of the CAN bus arbitration mechanism. This proposed method offers a simple implementation compared to traditional approaches, while being able to identify suspicious units and neutralize threats in real‐time. Experimental results demonstrate the effectiveness of this approach.