bluuebunny/crossref_metadata_2025 huggingface dataset:
Prospective cold metal working and analysis of deformation susceptibility of CuMg alloys with high magnesium content
Authors: Strzępek Paweł , Zasadzińska Małgorzata
Published: March 2024

Metal alloys designated for cold metal working exhibit much higher strength properties than pure materials due to solid-solution hardening. However, with the increase of mechanical properties its plasticity and workability decreases. Constant development and demand in this area has led to research on many copper alloys, such as copper alloys with high content of magnesium which were never tested before. The limitations regarding cold metal working of CuMg alloys is the main objective of this paper. Here we show that the tested materials exhibit much higher mechanical properties than currently used as electric conductors and carrying-conducting equipment materials such as pure copper, aluminum, M63 brass or CuNiSi alloy. The results were obtained using Hollomon relation, Considére criterion, Gubkin method and hardness measurements. It lead to assessing the prospective cold metal working of CuMg alloys with 2 wt% of magnesium up to 4 wt% of magnesium. The test range included upsetting with 10–50% of cold deformation. It provided the results on evolution of mechanical properties and deformability of tested alloys. Additional information was provided based on the alloys subjected to 50% of strain. The results have proven that as the amount of magnesium increased so did the assessed values, however, it was also linked with increasing friction coefficient. Measured hardness was 2 times higher and calculated Ultimate Tensile Strength (UTS) was even 2.5 times higher in reference to pure copper in the as-cast state. However, with magnesium content at 3.6 wt% or higher, the elevated amount of α + β phase causes brittleness making it impossible to subject these materials to cold metal working processes. We anticipate our assay to be a starting point for more sophisticated models and experimental research concerning cold metal working processes of CuMg alloys of high-strength, which may lead to developing novel and promising set of alloys.
Unveiling potential drug targets for hyperparathyroidism through genetic insights via Mendelian randomization and colocalization analyses
Authors: Chen Bohong , Wang Lihui , Pu Shengyu , Guo Li , Chai Na , Sun Xinyue , Tang Xiaojiang , Ren Yu , He Jianjun , Hao Na
Published: March 2024

Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the management of hyperparathyroidism, radical options to halt underlying disease progression remain lacking. Identifying putative genetic drivers and exploring novel drug targets that can impede HPT progression remain critical unmet needs. A Mendelian randomization (MR) analysis was performed to uncover putative therapeutic targets implicated in hyperparathyroidism pathology. Cis-expression quantitative trait loci (cis-eQTL) data serving as genetic instrumental variables were obtained from the eQTLGen Consortium and Genotype-Tissue Expression (GTEx) portal. Hyperparathyroidism summary statistics for single nucleotide polymorphism (SNP) associations were sourced from the FinnGen study (5590 cases; 361,988 controls). Colocalization analysis was performed to determine the probability of shared causal variants underlying SNP-hyperparathyroidism and SNP-eQTL links. Five drug targets (CMKLR1, FSTL1, IGSF11, PIK3C3 and SLC40A1) showed significant causation with hyperparathyroidism in both eQTLGen and GTEx cohorts by MR analysis. Specifically, phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) and solute carrier family 40 member 1 (SLC40A1) showed strong evidence of colocalization with HPT. Multivariable MR and Phenome-Wide Association Study analyses indicated these two targets were not associated with other traits. Additionally, drug prediction analysis implies the potential of these two targets for future clinical applications. This study identifies PIK3C3 and SLC40A1 as potential genetically proxied druggable genes and promising therapeutic targets for hyperparathyroidism. Targeting PIK3C3 and SLC40A1 may offer effective novel pharmacotherapies for impeding hyperparathyroidism progression and reducing disease risk. These findings provide preliminary genetic insight into underlying drivers amenable to therapeutic manipulation, though further investigation is imperative to validate translational potential from preclinical models through clinical applications.
Temperature, pressure, and duration impacts on the optimal stiffening of carbonates aged in diammonium phosphate solution
Authors: Desouky Mahmoud , Aljawad Murtada Saleh , Abduljamiu Amao , Solling Theis , Al-Shehri Dhafer , AlTammar Murtadha J. , Alruwaili Khalid M.
Published: March 2024

Diammonium phosphate (DAP) has been proven effective in improving the stiffness of weak or acid-damaged carbonates, thereby preserving hydraulic fracture conductivity. The reaction between DAP and calcite in chalk formations primarily produces hydroxyapatite (HAP), which is stiffer than calcite. However, the optimal reaction outcomes vary greatly with factors such as DAP concentration and reaction conditions. This study investigated the DAP-calcite reaction duration, pressure, and temperature effects on the stiffness magnitude of soft Austin chalk. Also, the catalyst effect and depth of HAP formation were examined. The study involved the assessment of stiffness non-destructively (impulse hammering), mineralogy (XRD, SEM), and elemental composition (XRF). The study tested 15 different DAP-chalk reaction variations, where the pressure, temperature, aging time and catalyst addition were modified in each case. The samples' elastic stiffness distributions were then collected and compared to the pre-reaction ones. The results showed that the elastic stiffness increased in all treated samples, with an 181% maximum increase achieved after 72 h at 6.9 MPa and 75 °C. However, the pressure effect was minor compared to the temperature. The SEM images revealed different HAP morphology corresponding to different treatment conditions. Although the treated samples showed an increased intensity of phosphorus throughout the entire sample, the near-surface zone (4–6 mm) was the most affected, as inferred from the XRF elemental analysis. The study's findings can help optimize hydraulic fracturing operations in weak carbonate reservoirs, improving production rates and overall well performance.
Investigating the potential roles of intra-colonial genetic variability in Pocillopora corals using genomics
Authors: Oury Nicolas , Magalon Hélène
Published: March 2024

Intra-colonial genetic variability (IGV), the presence of more than one genotype in a single colony, has been increasingly studied in scleractinians, revealing its high prevalence. Several studies hypothesised that IGV brings benefits, but few have investigated its roles from a genetic perspective. Here, using genomic data (SNPs), we investigated these potential benefits in populations of the coral Pocillopora acuta from Reunion Island (southwestern Indian Ocean). As the detection of IGV depends on sequencing and bioinformatics errors, we first explored the impact of the bioinformatics pipeline on its detection. Then, SNPs and genes variable within colonies were characterised. While most of the tested bioinformatics parameters did not significantly impact the detection of IGV, filtering on genotype depth of coverage strongly improved its detection by reducing genotyping errors. Mosaicism and chimerism, the two processes leading to IGV (the first through somatic mutations, the second through fusion of distinct organisms), were found in 7% and 12% of the colonies, respectively. Both processes led to several intra-colonial allelic differences, but most were non-coding or silent. However, 7% of the differences were non-silent and found in genes involved in a high diversity of biological processes, some of which were directly linked to responses to environmental stresses. IGV, therefore, appears as a source of genetic diversity and genetic plasticity, increasing the adaptive potential of colonies. Such benefits undoubtedly play an important role in the maintenance and the evolution of scleractinian populations and appear crucial for the future of coral reefs in the context of ongoing global changes.
AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling
Authors: Kim Changgyun , Park Jae-Hyeon , Lee Ji-Yong
Published: March 2024

This study develops a solution to sports match-fixing using various machine-learning models to detect match-fixing anomalies, based on betting odds. We use five models to distinguish between normal and abnormal matches: logistic regression (LR), random forest (RF), support vector machine (SVM), the k-nearest neighbor (KNN) classification, and the ensemble model—a model optimized from the previous four. The models classify normal and abnormal matches by learning their patterns using sports betting odds data. The database was developed based on the world football league match betting data of 12 betting companies, which offered a vast collection of data on players, teams, game schedules, and league rankings for football matches. We develop an abnormal match detection model based on the data analysis results of each model, using the match result dividend data. We then use data from real-time matches and apply the five models to construct a system capable of detecting match-fixing in real time. The RF, KNN, and ensemble models recorded a high accuracy, over 92%, whereas the LR and SVM models were approximately 80% accurate. In comparison, previous studies have used a single model to examine football match betting odds data, with an accuracy of 70–80%.
The roles of autophagy, ferroptosis and pyroptosis in the anti-ovarian cancer mechanism of harmine and their crosstalk
Authors: Zhu Jun , Zhu Hong , Zhu Qing , Xu Shi Lei , Xiao Lu , Zhang Ming Yue , Gao Jun
Published: March 2024

This study aimed to investigate the role of autophagy, ferroptosis, and pyroptosis in the antitumour mechanism of harmine (Har) and its crosstalk in ovarian cancer. By transmission electron microscopy, we found that compared with those in the control group, the cytoplasm of human ovarian cancer cells (SKOV3) treated with Har showed increased numbers of autophagic vesicles, decreased intracellular mitochondrial volume, increased bilayer membrane density, and decreased cristae. Western blot, immunofluorescence, and monodasylcadaverine (MDC) staining all suggested that Har promoted autophagy in SKOV3 cells. LY294002 and siFOXO3 rescued the inhibition of the PI3K/AKT/mTOR/FOXO3 signalling pathway and the promotion of autophagy by Har. Additionally, the levels of ferroptosis- and pyroptosis-related proteins and the levels of Fe2+ , glutathione (GSH), malondialdehyde (MDA), and superoxide dismutase (SOD) suggested that Har promoted ferroptosis and pyroptosis in SKOV3 cells. Interestingly, pretreatment with chloroquine (CQ), erastin, rapamycin (Rap), or ferrostatin-1 (Fer-1) increased or reversed the ferroptosis and pyroptosis promoted by Har, respectively. In vivo, the volume of tumours in the Har group was decreased, and immunohistochemistry revealed decreased levels of Ki-67 and GPX4 and increased levels of ATG5 and NARL3. In conclusion, Har exerts its anti-ovarian cancer effect not only by promoting autophagy by regulating the PI3K/AKT/mTOR/FOXO3 signalling pathway but also by promoting ferroptosis and pyroptosis. Additionally, there is complex crosstalk between autophagy, ferroptosis, and pyroptosis in ovarian cancer.
De novo antioxidant peptide design via machine learning and DFT studies
Authors: Hesamzadeh Parsa , Seif Abdolvahab , Mahmoudzadeh Kazem , Ganjali Koli Mokhtar , Mostafazadeh Amrollah , Nayeri Kosar , Mirjafary Zohreh , Saeidian Hamid
Published: March 2024

Antioxidant peptides (AOPs) are highly valued in food and pharmaceutical industries due to their significant role in human function. This study introduces a novel approach to identifying robust AOPs using a deep generative model based on sequence representation. Through filtration with a deep-learning classification model and subsequent clustering via the Butina cluster algorithm, twelve peptides (GP1–GP12) with potential antioxidant capacity were predicted. Density functional theory (DFT) calculations guided the selection of six peptides for synthesis and biological experiments. Molecular orbital representations revealed that the HOMO for these peptides is primarily localized on the indole segment, underscoring its pivotal role in antioxidant activity. All six synthesized peptides exhibited antioxidant activity in the DPPH assay, while the hydroxyl radical test showed suboptimal results. A hemolysis assay confirmed the non-hemolytic nature of the generated peptides. Additionally, an in silico investigation explored the potential inhibitory interaction between the peptides and the Keap1 protein. Analysis revealed that ligands GP3, GP4, and GP12 induced significant structural changes in proteins, affecting their stability and flexibility. These findings highlight the capability of machine learning approaches in generating novel antioxidant peptides.
Feasibility of assessing non-invasive intracranial compliance using FSI simulation-based and MR elastography-based brain stiffness
Authors: Gholampour Seifollah
Published: March 2024

Intracranial compliance (ICC) refers to the change in intracranial volume per unit change in intracranial pressure (ICP). Magnetic resonance elastography (MRE) quantifies brain stiffness by measuring the shear modulus. Our objective is to investigate the relationship between ICC and brain stiffness through fluid–structure interaction (FSI) simulation, and to explore the feasibility of using MRE to assess ICC based on brain stiffness. This is invaluable due to the clinical importance of ICC, as well as the fast and non-invasive nature of the MRE procedure. We employed FSI simulation in hydrocephalus patients with aqueductal stenosis to non-invasively calculate ICP which is the basis of the calculation of ICC and FSI-based brain stiffness. The FSI simulated parameters used have been validated with experimental data. Our results showed that there is no relationship between FSI simulated-based brain stiffness and ICC in hydrocephalus patients. However, MRE-based brain stiffness may be sensitive to changes in intracranial fluid dynamic parameters such as cerebral perfusion pressure (CPP), cerebral blood flow (CBF), and ICP, as well as to mechano-vascular changes in the brain, which are determining parameters in ICC assessment. Although optimism has been found regarding the assessment of ICC using MRE-based brain stiffness, especially for acute-onset brain disorders, further studies are necessary to clarify their direct relationship.
A novel MPPT technology based on dung beetle optimization algorithm for PV systems under complex partial shade conditions
Authors: Mai Chunliang , Zhang Lixin , Chao Xuewei , Hu Xue , Wei Xiaozhao , Li Jing
Published: March 2024

Solar power is a renewable energy source, and its efficient development and utilization are important for achieving global carbon neutrality. However, partial shading conditions cause the output of PV systems to exhibit nonlinear and multipeak characteristics, resulting in a loss of output power. In this paper, we propose a novel Maximum Power Point Tracking (MPPT) technique for PV systems based on the Dung Beetle Optimization Algorithm (DBO) to maximize the output power of PV systems under various weather conditions. We performed a performance comparison analysis of the DBO technique with existing renowned MPPT techniques such as Squirrel Search Algorithm, Cuckoo search Optimization, Horse Herd Optimization Algorithm, Particle Swarm Optimization, Adaptive Factorized Particle Swarm Algorithm and Gray Wolf Optimization Hybrid Nelder-mead. The experimental validation is carried out on the HIL + RCP physical platform, which fully demonstrates the advantages of the DBO technique in terms of tracking speed and accuracy. The results show that the proposed DBO achieves 99.99% global maximum power point (GMPP) tracking efficiency, as well as a maximum improvement of 80% in convergence rate stabilization rate, and a maximum improvement of 8% in average power. A faster, more efficient and robust GMPP tracking performance is a significant contribution of the DBO controller.
Understanding the consumer-citizen gap in Chinese public attitudes toward farm animal welfare
Authors: Jiang Bing , Cui Lihang , Deng Xiaoshang , Chen Hongbo , Tang Wenjie
Published: March 2024

Individuals of the general public can perform both consumer and citizen roles in farm animal welfare, and attitudes toward farm animal welfare may differ between these roles. However, scant research is available regarding this distinction, especially in developing countries such as China. The present study aimed to explore consumer-citizen gaps in Chinese public attitudes toward farm animal welfare across three dimensions and across demographic characteristics. A 36-item scale was designed, and completed by 5284 Chinese participants in a large-scale cross-sectional survey. Consumer-citizen gaps in attitudes toward farm animal welfare across three dimensions and demographic characteristics were analyzed using the Wilcoxon signed-rank test, and effects of demographic characteristics on attitudes were further explored by linear regression analysis. A significant consumer-citizen gap was found in overall attitudes, although the consumer role was only slightly more positive than the citizen role. The consumer-citizen gap is driven by differences in both cognitive attitudes and behavioral attitudes. The gap is most pronounced in cognitive attitudes, where the consumer role is significantly more positive, and smaller in behavioral attitudes, where the citizen role is significantly more positive. The consumer-citizen gap varies significantly among different demographic groups, including gender, age, education, monthly household income, area of residence, and occupation. Additionally, education, monthly household income, and area of residence have significant effects on attitudes in the dual role, whereas gender only affect consumer-role attitudes significantly. The findings provide evidence that consumer-citizen gaps in Chinese public attitudes toward farm animal welfare exist, and this distinction is mainly determined by demographic characteristics.
Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes
Authors: Hawks Z. W. , Beck E. D. , Jung L. , Fonseca L. M. , Sliwinski M. J. , Weinstock R. S. , Grinspoon E. , Xu I. , Strong R. W. , Singh S. , Van Dongen H. P. A. , Frumkin M. R. , Bulger J. , Cleveland M. J. , Janess K. , Kudva Y. C. , Pratley R. , Rickels M. R. , Rizvi S. R. , Chaytor N. S. , Germine L. T.
Published: March 2024

Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations.
Rainfall variability increased with warming in northern Queensland, Australia, over the past 280 years
Authors: Dyez Kelsey A. , Cole Julia E. , Lough Janice M.
Published: March 2024

Floods and droughts are hydrological extremes that impact ecosystems, agriculture, and human well-being. These extremes are expected to intensify in a warmer world, although many regions lack the observations needed to place current trends in the context of long-term variability. Here we present a new multi-century record of tropical rainfall based on a multi-proxy approach from northern Great Barrier Reef coral. The robust calibration with instrumental rainfall allows us to quantitatively estimate summer rainfall in northern Queensland back to 1746 CE. We find that as global climate warmed, wet-season rainfall in this region has increased by ~10% since 1750 and the standard deviation (21-yr 1-σ) of wet-season rainfall more than doubled, as rainy years became much wetter, while dry years remained dry. Reconstructed rainfall correlates with El Niño indices and the link to Pacific temperature variability has strengthened as climate warmed, consistent with expected intensification of La Niña-related rainfall.
AAV9:PKP2 improves heart function and survival in a Pkp2-deficient mouse model of arrhythmogenic right ventricular cardiomyopathy
Authors: Wu Iris , Zeng Aliya , Greer-Short Amara , Aycinena J. Alex , Tefera Anley E. , Shenwai Reva , Farshidfar Farshad , Van Pell Melissa , Xu Emma , Reid Chris , Rodriguez Neshel , Lim Beatriz , Chung Tae Won , Woods Joseph , Scott Aquilla , Jones Samantha , Dee-Hoskins Cristina , Gutierrez Carolina G. , Madariaga Jessie , Robinson Kevin , Hatter Yolanda , Butler Renee , Steltzer Stephanie , Ho Jaclyn , Priest James R. , Song Xiaomei , Jing Frank , Green Kristina , Ivey Kathryn N. , Hoey Timothy , Yang Jin , Yang Zhihong Jane
Published: March 2024

Background

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial cardiac disease associated with ventricular arrhythmias and an increased risk of sudden cardiac death. Currently, there are no approved treatments that address the underlying genetic cause of this disease, representing a significant unmet need. Mutations in Plakophilin-2 (PKP2), encoding a desmosomal protein, account for approximately 40% of ARVC cases and result in reduced gene expression.

Methods

Our goal is to examine the feasibility and the efficacy of adeno-associated virus 9 (AAV9)-mediated restoration of PKP2 expression in a cardiac specific knock-out mouse model of Pkp2.

Results

We show that a single dose of AAV9:PKP2 gene delivery prevents disease development before the onset of cardiomyopathy and attenuates disease progression after overt cardiomyopathy. Restoration of PKP2 expression leads to a significant extension of lifespan by restoring cellular structures of desmosomes and gap junctions, preventing or halting decline in left ventricular ejection fraction, preventing or reversing dilation of the right ventricle, ameliorating ventricular arrhythmia event frequency and severity, and preventing adverse fibrotic remodeling. RNA sequencing analyses show that restoration of PKP2 expression leads to highly coordinated and durable correction of PKP2-associated transcriptional networks beyond desmosomes, revealing a broad spectrum of biological perturbances behind ARVC disease etiology.

Conclusions

We identify fundamental mechanisms of PKP2-associated ARVC beyond disruption of desmosome function. The observed PKP2 dose-function relationship indicates that cardiac-selective AAV9:PKP2 gene therapy may be a promising therapeutic approach to treat ARVC patients with PKP2 mutations.
Dual-functional porphyrinic zirconium-based metal–organic framework for the fluorescent sensing of histidine enantiomers and Hg2+
Authors: Qin Shili , Meng Fanshu , Jin Fenglong , Xu Xidi , Zhao Ming , Chu Hongtao , Gao Lidi , Liu Shuren
Published: March 2024

l-Cys/PCN-222 as a novel and dual-functional fluorescent sensor was developed. It not only showed a higher chiral fluorescent recognition of l-histidine but also performed as a visual sensor for Hg2+ in actual surface water.
Accessing the usefulness of atomic adsorption configurations in predicting the adsorption properties of molecules with machine learning
Authors: Malone Walter , von der Heyde Johnathan , Kara Abdelkader
Published: March 2024

We study the effect of adding atomic adsorption configurations into the training and validation dataset for a neural network's predictions of the adsorption energies of small molecules on single metal and bimetallic, single crystal surfaces.
High-throughput DNA synthesis for data storage
Authors: Yu Meng , Tang Xiaohui , Li Zhenhua , Wang Weidong , Wang Shaopeng , Li Min , Yu Qiuliyang , Xie Sijia , Zuo Xiaolei , Chen Chang
Published: March 2024

Using DNA molecules for digital data storage: the writing and reading of the data are realized by high throughput DNA synthesis and sequencing technologies, where high density array-based chips play an important role.
Synthesis of metallic high-entropy alloy nanoparticles
Authors: Sun Xiuyun , Sun Yugang
Published: March 2024

This article reviews the methods for synthesizing high-entropy alloy nanoparticles, which fall into five categories based on their commonality.
Low temperature CO oxidation over Rh supported on N-doped carbon
Authors: Whitcomb Colby A. , Shrestha Anukriti , Paolucci Christopher , Davis Robert J.
Published: March 2024

Computational screening of transition metal ions in nitrogen-doped carbon (N–C) as catalysts for CO oxidation at low T revealed Rh to be a potential candidate, which was confirmed experimentally by synthesizing Rh–N–C and testing it in CO oxidation.
Cordyceps sinensis accelerates stem cell recruitment to human skeletal muscle after exercise
Authors: Dewi Luthfia , Liao Yu-Chieh , Jean Wei-Horng , Huang Kuo-Chin , Huang Chih-Yang , Chen Liang-Kung , Nicholls Andrew , Lai Li-Fan , Kuo Chia-Hua
Published: March 2024

Cordyceps sinensis is a parasitic fungus known to induce immune response. Cordyceps accelerates recruitment of CD34+/Pax7+ cells to exercised muscle which results in faster recovery from post-exercise muscle damage.
In vitro study of the blood–brain barrier transport of bioactives from Mediterranean foods
Authors: Gallardo-Fernandez Marta , Garcia Ana Rita , Hornedo-Ortega Ruth , Troncoso Ana M. , Garcia-Parrilla M. Carmen , Brito M. Alexandra
Published: March 2024

Bioactives from Mediterranean diet (MD), hydroxytyrosol (HT), tyrosol (TYRS), serotonin (SER) and protocatechuic acid (PCA) cross the blood-brain barrier (BBB) and do not impair its integrity.
Palladium-catalyzed conversion of phenols into tetrahydroacridines
Authors: Yu Jianjin , Zhan Renqin , Li Chao-Jun , Zeng Huiying
Published: March 2024

A drug and medicinal skeleton, tetrahydroacridines (including tacrine), were synthesized from phenolic lignin monomers and 2-aminoarylketones via palladium catalysis.
Synthesis of 1,2,3-triazole-piperazin-benzo[b][1,4]thiazine 1,1-dioxides: antibacterial, hemolytic and in silico TLR4 protein inhibitory activities
Authors: Ramu Nagavelli , Krishna Thupurani Murali , Kapavarapu Ravikumar , Narsimha Sirassu
Published: March 2024

Novel 1,2,3-triazoles (6a–6j & 8a–8g) were synthesized and evaluated for their antibacterial activity against S. aureus. The more potent compounds were further evaluated for their in silico TLR4 inhibitory activity.
Design, synthesis and biological evaluation of indole-2-carboxylic acid derivatives as novel HIV-1 integrase strand transfer inhibitors
Authors: Zhang Rong-Hong , Chen Guo-Qi , Wang Weilin , Wang Yu-Chan , Zhang Wen-Li , Chen Ting , Xiong Qian-Qian , Zhao Yong-Long , Liao Shang-Gao , Li Yong-Jun , Yan Guo-Yi , Zhou Meng
Published: March 2024

Integrase plays an important role in the life cycle of HIV-1, and indole-2-carboxylic acid derivative 17a can effectively inhibit the strand transfer of integrase.
Machine learning guided tuning charge distribution by composition in MOFs for oxygen evolution reaction
Authors: Yu Licheng , Zhang Wenwen , Nie Zhihao , Duan Jingjing , Chen Sheng
Published: March 2024

We utilize machine learning (ML) to accelerate the synthesis of MOFs, starting by building a library of over 900 MOFs with different metal salts, solvent ratios and reaction tine, and then utilizing zeta potentials as target variables for ML training.
Shell thickness-induced thermal dependence: highly sensitive core–shell CdSe/ZnS/POSS-based temperature probes
Authors: Sun Jiannan , Yan Ke , Pan Aizhao , Zhang Pan , Chen Xuehang , Shi Xinyi , Shi Chengyu
Published: March 2024

Fluorescence nanothermometry based on quantum dots is a current research hotspot for novel non-contact temperature monitoring, and is of vital significance for the modulation and design of the sensing properties of sensors.
Study on lattice dynamics and thermal conductivity of fluorite AF2 (A = Ca, Sr, Ba) based on first principles calculations
Authors: Liu Peipei , Zhao Yinchang , Wang Xichang , Ni Jun , Dai Zhenhong
Published: March 2024

Fluorite materials have received particular attention in electron optics due to their favorable optical properties.
Understanding and fine tuning the propensity of ATP-driven liquid–liquid phase separation with oligolysine
Authors: Zhu Qiang , Wu Yongxian , Luo Ray
Published: March 2024

Liquid–liquid phase separation (LLPS) plays a pivotal role in the organization and functionality of living cells.
A diacetylene covalent organic framework through a one-step two-electron O2 reduction pathway for efficient photosynthesis of H2O2
Authors: Li Pengken , Zhao Hui , Ji Rong , Chi Wenwen , Sun Xinyu , Dong Yuming , Zhu Yongfa
Published: March 2024

A one-step two-electron oxygen reduction pathway is crucial for the stable and efficient photosynthesis of hydrogen peroxide.
Rare-metal-free high-performance water-activated paper battery: a disposable energy source for wearable sensing devices
Authors: Ishibashi Kosuke , Ono Shimpei , Kamei Jun , Ito Koju , Yabu Hiroshi
Published: March 2024

This paper reports the realization of a water-activated magnesium–air paper battery by using only low environmental impact materials and without use of heavy metals.
Modification of chitosan-coated magnetic material with glycidyltrimethylammonium chloride and its application as heterogeneous base catalyst for levulinic acid esterification
Authors: Mukhayani Feri , Kamiya Yuichi , Otomo Ryoichi , Kunarti Eko Sri , Nuryono Nuryono
Published: March 2024

A magnetically separable solid Lewis base catalyst composed of natural magnetic material, chitosan, and glycidyltrimethylammonium chloride was developed. The catalyst is effective for esterification of levulinic acid to produce ethyl levulinate.
Revealing the synergistic effect of Ni single atoms and adjacent 3d metal doped Ni nanoparticles in electrocatalytic CO2 reduction
Authors: Liu Yingjie , Wu Zhaohui , Bai Sha , Shen Tianyang , Li Qian , Liu Guihao , Sun Xiaoliang , Hu Yihang , Song Ziheng , Chu Jinfeng , Song Yu-Fei
Published: March 2024

Ni1+NPsCu@NCNT with the co-existance of NiCu nanoparticles trapped in N-CNTs and a Ni single atom with Ni–N4 coordination exhibited a FECO of 96.92% in CO2RR.
Stable dispersion of carbon nanotubes in a molten salt of KNO3–NaNO3–NaNO2–LiNO3–LiOH
Authors: Guo Dongyu , Li Yuying , Chen Tao , Li Hongyan , Han Liang , Jia Xilai
Published: March 2024

Chemical bonds and adsorption between Li+ and π electrons of CNTs contribute to dispersion of CNTs.
Size and temperature dependent shapes of copper nanocrystals using parallel tempering molecular dynamics
Authors: Zhang Huaizhong , Khan Mohd Ahmed , Yan Tianyu , Fichthorn Kristen A.
Published: March 2024

Parallel-tempering molecular dynamics simulations reveal the temperature- and size-dependent shapes of Cu nanocrystals.
A luminescent Ag8(DPPY)6(PhCC)6 cluster with a triangular superatomic Ag8 core
Authors: Peter Blessing D. , Pei Wei , Andrew Gaya N. , Zhou Si , Luo Zhixun
Published: March 2024

We have synthesized single crystals of a highly stable Ag8 nanocluster protected by six ligands of diphenyl-2-phosphinic pyridine (DPPY) plus six ligands of phenylacetylene (PhCC).
Photocatalytic degradation of drugs and dyes using a maching learning approach
Authors: Anandhi Ganesan , Iyapparaja M.
Published: March 2024

The waste management industry uses an increasing number of mathematical prediction models to accurately forecast the behavior of organic pollutants during catalytic degradation.
Sonification of molecular electronic energy density and its dynamics
Authors: Arasaki Yasuki , Takatsuka Kazuo
Published: March 2024

A method is proposed for sonification of the molecular electronic energy density.
Systematic surface bowing in 2D III-nitride monolayers
Authors: Hussain Imdad , Khan Adnan Ali , Ahmad Iftikhar , Ahmad Rashid , Ullah Saif
Published: March 2024

This work reports systematic surface bowing in the 2D structure of III-nitrides due to the C60 adsorption as we proceed from BN → AlN → GaN → InN.
Sequential proton coupled electron transfer events from a tetraruthenium polyoxometalate in photochemical water oxidation
Authors: Rossin Elena , Bonchio Marcella , Natali Mirco , Sartorel Andrea
Published: March 2024

The tetraruthenium polyoxometalate Ru4POM shows sequential oxidative proton coupled electron transfer (PCET) events in a [Ru(bpy)3]2+/S2O82− photochemical cycle for catalytic water oxidation, reaching quantum efficiency approaching 14%.
Changes in Speech Production Following Perceptual Training With Orofacial Somatosensory Inputs
Authors: Ashokumar Monica , Schwartz Jean-Luc , Ito Takayuki
Published: March 2024

Purpose:

Orofacial somatosensory inputs play an important role in speech motor control and speech learning. Since receiving specific auditory–somatosensory inputs during speech perceptual training alters speech perception, similar perceptual training could also alter speech production. We examined whether the production performance was changed by perceptual training with orofacial somatosensory inputs.

Method:

We focused on the French vowels /e/ and /ø/, contrasted in their articulation by horizontal gestures. Perceptual training consisted of a vowel identification task contrasting /e/ and /ø/. Along with training, for the first group of participants, somatosensory stimulation was applied as facial skin stretch in backward direction. We recorded the target vowels uttered by the participants before and after the perceptual training and compared their F1, F2, and F3 formants. We also tested a control group with no somatosensory stimulation and another somatosensory group with a different vowel continuum (/e/−/i/) for perceptual training.

Results:

Perceptual training with somatosensory stimulation induced changes in F2 and F3 in the produced vowel sounds. F2 decreased consistently in the two somatosensory groups. F3 increased following the /e/−/ø/ training and decreased following the /e/−/i/ training. F2 change was significantly correlated with the perceptual shift between the first and second half of the training phase in the somatosensory group with the /e/−/ø/ training, but not with the /e/−/i/ training. The control group displayed no effect on F2 and F3, and just a tendency of F1 increase.

Conclusion:

The results suggest that somatosensory inputs associated to speech sound inputs can play a role in speech training and learning in both production and perception.
Drag reduction capacity of multi‐scale and multi‐level riblet in turbulent flow
Authors: Chen Dengke , Li Wenhao , Zhao Yichen , Liu Jinhai , Cui Xianxian , Zhao Zehui , Liu Xiaolin , Chen Huawei
Published: March 2024

For high‐speed moving objects, drag reduction has been a prolonged major challenge. To address this problem, passive and negative strategies have been proposed in the preceding decades. The integration of creatures and nature has been continuously perfected during biological evolution. Unique structure characteristics, material properties, and special functions of marine organisms can provide inexhaustible inspirations to solve this intractable problem of drag reduction. Therefore, a simple and low‐cost laser ablation method was proposed. A multi‐scale and multi‐level riblet (MSLR) surface inspired by the denticles of the sharkskin was fabricated by controlling the density of the laser path and ablation times. The morphology and topographic features were characterised using an electron microscope and a scanning white‐light interfering profilometer. Then, the drag reduction capacity of the bionic riblet surface was measured in a circulating water tunnel. Finally, the mechanism of drag reduction was analysed by the computational fluid dynamics (CFD) method. The results show that the MSLR surface has a stable drag reduction capacity with an increase in Reynold (Re) number which was contributed by high‐low velocity stripes formed on the MSLR surface. This study can provide a reference for fabricating spatial riblets with efficient drag reduction at different values of Re and improving marine antifouling.
Improvement of ship target detection algorithm for YOLOv7‐tiny
Authors: Zhang Huixia , Yu Haishen , Tao Yadong , Zhu Wenliang , Zhang Kaige
Published: March 2024

In addressing the challenge of ships being prone to occlusion in multi‐target situations during ship target detection, leading to missed and false detections, this paper proposes an enhanced ship detection algorithm for YOLOv7‐tiny. The proposed method incorporates several key modifications. Firstly, it introduces the Convolutional Block Attention Module in the Backbone section of the original model, emphasizing position information while attending to channel features to enhance the network's ability to extract crucial information. Secondly, it replaces standard convolution with GSConv convolution in the Neck section, preserving detailed information and reducing computational load. Subsequently, the lightweight operator Content‐Aware ReAssembly of Features is employed to replace the original nearest‐neighbour interpolation, mitigating the loss of feature information during the up‐sampling process. Finally, the localization loss function, SIOU Loss, is utilized to calculate loss, expedite training convergence, and enhance detection accuracy. The research results indicate that the precision of the improved model is 91.2%, mAP@0.5 is 94.5%, and the F1‐score is 90.7%. These values are 3.7%, 5.5%, and 4.2% higher than those of the original YOLOv7‐tiny model, respectively. The improved model effectively enhances detection accuracy. Additionally, the improved model achieves an FPS of 145.4, meeting real‐time requirements.
Exploring the application of machine‐learning techniques in the next generation of long‐term hydropower‐thermal scheduling
Authors: Wang Jinghao , Yousefi Mojtaba , Rajasekharan Jayaprakash , Arghandeh Reza , Farahmand Hossein
Published: March 2024

This paper introduces a shape‐based inflow scenarios reduction framework applied in long‐term hydro‐thermal scheduling. This scheduling problem involves strategically managing the limited stored hydro energy in coordination with the electricity system. The scenario fan problem, selected as a long‐term hydro‐thermal scheduling approach, can effectively represent the individual hydropower plants and their short‐term flexibility within the long‐term scheduling process, making it well‐suited for capturing the disaggregated physical characteristics of hydro stations. However, the computational burden of scenario fan problem increases due to the complexity of the cascaded system and the large number of inflow scenarios. To tackle these challenges, a machine learning clustering method is developed for extracting shape‐based features to capture the energy and shape attributes of hydro inflows. A comparative analysis was conducted to evaluate the effectiveness of the proposed method, comparing it with four established clustering methods. This evaluation was carried out on a hydro‐thermal test case, utilizing both in‐sample and out‐of‐sample data analysis. The findings demonstrate that the proposed framework outperforms other methods in terms of computational time by 42.6% and optimal reservoir trajectories by 12.1% considering K‐means using Euclidean distance as the benchmark. Additionally, this study showcases the feasibility of performing long‐term hydro‐thermal scheduling at a granular level, with detailed topological information and a shorter time scale. This expanded approach opens up new possibilities for addressing the integration of renewable energy resources within the realm of long‐term hydro‐thermal scheduling.
Performance of high-order Godunov-type methods in simulations of astrophysical low Mach number flows
Authors: Leidi G. , Andrassy R. , Barsukow W. , Higl J. , Edelmann P. V. F. , Röpke F. K.
Published: March 2024

High-order Godunov methods for gas dynamics have become a standard tool for simulating different classes of astrophysical flows. Their accuracy is mostly determined by the spatial interpolant used to reconstruct the pair of Riemann states at cell interfaces and by the Riemann solver that computes the interface fluxes. In most Godunov-type methods, these two steps can be treated independently, so that many different schemes can in principle be built from the same numerical framework. Because astrophysical simulations often test out the limits of what is feasible with the computational resources available, it is essential to find the scheme that produces the numerical solution with the desired accuracy at the lowest computational cost. However, establishing the best combination of numerical options in a Godunov-type method to be used for simulating a complex hydrodynamic problem is a nontrivial task. In fact, formally more accurate schemes do not always outperform simpler and more diffusive methods, especially if sharp gradients are present in the flow. For this work, we used our fully compressible Seven-League Hydro (SLH) code to test the accuracy of six reconstruction methods and three approximate Riemann solvers on two- and three-dimensional (2D and 3D) problems involving subsonic flows only. We considered Mach numbers in the range from 10−3 to 10−1, which are characteristic of many stellar and geophysical flows. In particular, we considered a well-posed, 2D, Kelvin–Helmholtz instability problem and a 3D turbulent convection zone that excites internal gravity waves in an overlying stable layer. Although the different combinations of numerical methods converge to the same solution with increasing grid resolution for most of the quantities analyzed here, we find that (i) there is a spread of almost four orders of magnitude in computational cost per fixed accuracy between the methods tested in this study, with the most performant method being a combination of a low-dissipation Riemann solver and a sextic reconstruction scheme; (ii) the low-dissipation solver always outperforms conventional Riemann solvers on a fixed grid when the reconstruction scheme is kept the same; (iii) in simulations of turbulent flows, increasing the order of spatial reconstruction reduces the characteristic dissipation length scale achieved on a given grid even if the overall scheme is only second order accurate; (iv) reconstruction methods based on slope-limiting techniques tend to generate artificial, high-frequency acoustic waves during the evolution of the flow; and (v) unlimited reconstruction methods introduce oscillations in the thermal stratification near the convective boundary, where the entropy gradient is steep.
Effect of strain rates on the forming properties of DP Steel at high-temperature
Authors: Lade Jayahari , Baloji Dharavath , Seshacharyulu K. , Govardhan D. , Butchiraju K. , Igorevich Rozhdestvenskiy Oleg
Published: March 2024

Dual Phase steel grade, with its remarkable combination of features including formability and resistance to high temperatures, has been a revolutionary alloy in modern industry. It is a useful material that may be applied to many different tasks. It presents us with the task of examining its characteristics in response to changes in critical parameters such as temperature and loading rate during stretching operations. Understanding the formability behavior of DP steel sheets, which have a thickness of 1 mm, at various increased temperatures and strain rates was the main goal of the investigation. We investigated and examined the tensile characteristics at 650 and 750 degrees Celsius in the first investigation. On the other hand, because of flow stresses in the material at higher temperatures, elongation has decreased in value as deformation rates have increased. In addition, we plotted the FLDs experimentally and examined the formation behavior while performing the Nakazima Test on specimens with a thickness of 1 mm. Furthermore, a limiting dome height (LDH) study was conducted on a laboratory scale. In terms of temperature, the LDH was shown to be higher at 750 and at 0.001/s
Review of surface roughness and material removing rate on abrasive flow machining process
Authors: Rao Peram Kondala , Janardhana G. Ranga
Published: March 2024

Every day, advancements in manufacturing technology research and innovation yield a highly finished surface with lower labour and machining costs. The conventional materials that were frequently employed in the chemical, automotive, and aerospace industries have been replaced by materials like ceramics, metal matrix composites, polymers, and super alloys. The AFM technology is capable of maintaining precision, reliability, and adaptability across adverse range of applications. Internal parts, through holes, intersecting holes, and freeform surfaces that are challenging to finish with other conventional finishing techniques can all be polished and deburred with AFM. The current study aims to determine the process variables that have a major impact on the change in surface roughness of the inner, outer, and side surfaces as well as the amount of material removal. These parameters include abrasive mesh size, abrasive concentration in media, and the number of passes. A review of published technical articles on the AFM process is attempted in this article, and the studies are divided into four categories: experimental setups, abrasive media, modelling and optimisation, and applications of the AFM process. The review article provides fresh directions for future investigation. Page layout