bluuebunny/crossref_metadata_2025_split huggingface dataset:
A finite-deformation anisotropic non-associative viscoplasticity/damage coupled thermodynamic model for ductile fracture of thick adhesive composite joint
Authors: Pengfei Liu , Chen H.Y. , Sun J. , Xia. S.F. 
Published: September 2024

Abstract

This paper develops a finite-deformation anisotropic non-associative (visco)plasticity/ damage coupled model for thick adhesive composite joints within the framework of irreversible thermodynamics. First, a four-order damage tensor that is composed of a two-order damage tensor is introduced into the elastic constitutive model, the Drucker-Prager’s type yielding function and plastic potential function by considering the variable hydrostatic pressure and non-associative plasticity. The spectral decomposition of the second-order damage tensor is performed to derive the fourth-order damage tensor. Second, a damage potential function is also introduced to describe the coupled relationship between plastic deformation and damage evolution. Since the two-order damage tensor is related to the elastic strain tensor, plastic anisotropy and damage-induced anisotropy after plastic deformation interact. Third, both isotropic hardening and kinematic hardening are considered, represented by the back stress and the hardening stress as well as their conjugate relationships with the corresponding internal variables. They are derived by the Helmholtz free energy, and their evolved relationships are derived by the plastic potential function according to the Kuhn-Tucker loading-unloading consistency conditions for the rate-independent plasticity/damage coupled model. Fourth, an extended version of the Perzyna’s type model by introducing an over-stress function is developed to derive the consistency plasticity factor for the viscoplasticity/damage coupled model, regardless of the Kuhn-Tucker plastic loading-unloading consistency conditions. It is shown that the rate-independent plasticity model is just a particular case of the viscoplasticity model as viscous parameters tend to be zero. Fifth, all the thermodynamic forces and internal variables as well as the tangent modulus for the two models above are updated under the corotated configuration for finite deformation in the consistent integration procedure by implicit FEA. In order to simplify numerical computation, the stress and strain at time n + 1 are first updated using the frozen damage tensor and back stress tensor at time n, and then the latter two tensors are updated individually at time n + 1. Finally, the developed model and numerical algorithm by FEA are used to predict the stress, strain, and damage features of the dog-bone MMA ductile adhesive specimens under tensile loads and the thick MMA adhesive joint specimens under shear loads. It should be emphasized that numerical convergence and parameter identification in FEA should be addressed properly in order to lead to accurate and robust predictions of mechanical responses of structures.
Photocatalyst Design Principles for Photocatalytic Hydrogen Production and Benzyl Alcohol Oxidation with CdS Nanosheets
Authors: Kim Ryun Na , Kim Jihun , Kim Gui-Min , Lee Doh C. , Kim Whi Dong 
Published: September 2024

Abstract

To produce hydrogen using photocatalysts while maintaining environmentally friendly characteristics, research has focused on using benzyl alcohol (BzOH) as a hole scavenger to convert it into the valuable compound benzaldehyde. However, due to the relatively slow oxidation rate of BzOH compared to conventional hole scavengers, tailored photocatalyst designs are necessary. In this study, we prepared CdS nanosheets (NSs) and introduced Na2SO4-Na2SO3 and BzOH as hole scavengers to adjust the oxidation half-reaction rate (OHR) during the photocatalytic reaction. Various co-catalysts were introduced to examine how changes in the reduction half-reaction (RHR) and OHR rates influence hydrogen production. The results reveal that the selection of co-catalyst and hole scavenger significantly influences the rate-determining step (RDS) in the photocatalytic reaction. For bare CdS NSs, the slow RHR results in the RDS being the RHR, leading to similar hydrogen production rate regardless of the scavenger type. However, with Pt as a co-catalyst, the RDS shifts to the OHR due to the accelerated RHR, inducing hydrogen production rate highly sensitive to the type of scavenger. Consequently, hydrogen production is significantly reduced when using BzOH, which has a slower oxidation rate. These findings suggest that achieving high hydrogen yields is fundamentally challenging with BzOH due to its slow oxidation rate, even with the introduction of excellent co-catalysts. Therefore, it is imperative to develop photocatalyst materials with lower valence band level for high oxidation power.
Kernel ridge regression improving based on golden eagle optimization algorithm for multi-class classification
Authors: Mahmood Shaimaa Waleed , Algamal Zakariya Yahya 
Published: September 2024

Abstract

Kernel Ridge Regression is a supervised machine-learning approach that merges concepts from ridge regression and the kernel trick. It is especially beneficial for addressing regression problems characterized by a nonlinear relationship between the input and output variables. Kernel Ridge Regression (KRR) involves utilizing the kernel trick to implement ridge regression. The approach can acquire knowledge of a non-linear function in a space with more dimensions while taking advantage of ridge regression's regularization. However, the hyper-parameter settings that define the kernel type influence KRR's effectiveness. Significant processing costs, memory expenses, and low accuracy burden the current approaches for collecting these hyper parameter values. This study introduces a substantial enhancement to the golden eagle optimization method. The enhancement entails implementing elite opposite-based learning (EOBL) to increase population diversity in the search space. We do this to choose the optimal hyper parameters effectively. We used ten publicly available multi-class datasets to verify and authenticate the effectiveness of the suggested enhancement to Kernel Ridge Regression. Based on several assessment criteria, the results clearly showed that the suggested enhancement outperforms all other basic procedure techniques in terms of categorization efficacy.
Developing a Novel Aging Assessment Model to uncover heterogeneity in Organ Aging and Facilitates Screening of Aging-related Drugs
Authors: Xu Yingqi , Li Maohao , Hu Congxue , Luo Yawen , Gao Xing , Li Xinyu , Li Xia , Zhang Yunpeng 
Published: September 2024

Abstract

Background: The decline in organ function due to aging significantly impacts the health and quality of life of the elderly. Assessing and delaying aging has become a major societal concern. Previous studies have largely focused on differences between young and old, often overlooking the complexity and gradual nature of aging.
Methods: We annotated the aging trajectories of 16 organs to reveal functional specificity and identify organ-specific aging trend genes. Through inter-organ correlation analysis, we identified a set of global aging trend genes and constructed a multi-organ aging assessment (2A) model, which was validated using gene expression and pharmacogenomic data from mice and humans. Additionally, we used a random walk algorithm and GSEA enrichment analysis to screen for drugs that could improve multi-organ aging.
Results: The 2A model, constructed using aging trend genes, effectively evaluates the aging status in human and mouse tissues and predicts the clearance of senescent cells. The model scores exhibit a strong correlation with actual age, highlighting its robustness and reliability. Functional annotation indicated that the lungs and kidneys are particularly sensitive to aging, with immune function and cell death playing key roles. Notably, single-cell data confirmed that plasma cell accumulation and naive-like cell reduction showed linear changes during organ aging. The aging trend genes of each organ are significantly enriched with aging-related functions, allowing for precise assessment of the aging process and identification of specific aging milestones for each organ. In addition, drug screening pinpointed Fostamatinib, Ranolazine, and Metformin as influential in multi-organ aging. Enrichment analysis further elucidated their impact on critical aging-related pathways, including longevity regulation and circadian rhythm.
Conclusion: This study elucidated functional changes during organ aging and developed the 2A model as a robust method for monitoring aging. Additionally, our research provides a foundation for anti-aging drug screening and establishes a scientific framework for intervening in organ aging.
Structure of Molecular Nitrogen Nanoclusters Containing Stabilized Nitrogen Atoms
Authors: Wetzel Cameron , Lee David , Khmelenko Vladimir 
Published: September 2024

Abstract

Impurity-helium condensates (IHCs) formed by injecting the discharge products of gaseous mixtures of helium atoms and nitrogen molecules into bulk superfluid \(^{4}\) He at temperature 1.5 K, were studied by X-band electron spin resonance (ESR). IHCs consists of collections of N \(_2\) nanoclusters which form aerogel-like structure inside bulk HeII. It was found that N$_2$ nanoclusters have a two shell structure, an outer shell which contains high concentration of stabilized N atoms and an interior shell with lower concentrations of N atoms. In this paper we have studied the dependence of the shell structure of the N$_2$ nanoclusters which compose the IHCs by varying the ratio of nitrogen to helium in the prepared gas mixture from 0.06% to 1%. The highest local concentration of N atoms in nanoclusters (1.2 \(\cdot\) 10 \(^{21}\) cm \(^{-3}\) ) was observed in the sample prepared from the gas mixture containing the lowest nitrogen admixture (0.06%). Additionally, the evolution of nanocluster structure was studied as the samples were drained of liquid helium (T \(\le\) 3.5 K) and warmed beyond the point of explosive recombination (3.5 K $\le$ T $\le$ 6.5 K).
Health risks associated with trace elements and macrominerals in cultivars grown on Yamuna floodplain using various soil amendments: a correlation analysis
Authors: Sharma Pooja , Mahongnao Sophayo , Nanda Sarita 
Published: September 2024

Abstract

This study addresses the contamination challenges in the agricultural sector of the Yamuna Floodplain, a vital region for supplying vegetables to the National Capital Region (NCR). The research involved cultivating spinach, green amaranth, and red amaranth over two consecutive seasons, with various waste compost amendments applied to the soil, while groundwater was used for irrigation. The quality of these organically grown vegetables was assessed by analyzing macro-minerals and trace elements using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results indicated that the mean concentrations (mg/100g) of phosphorus, sulfur, manganese, and potassium were significantly enhanced in compost-amended crops, leading to improvements in their respective percentages of Recommended Dietary Allowance (RDA) and Estimated Average Requirement (EAR) compared to those grown with chemical fertilizers. Health risk assessments revealed that both the hazard quotient (HQ) and the health index (sum of Target Hazard Quotients, THQ) were below 1, indicating minimal non-carcinogenic risk. Furthermore, compost amendments were found to significantly reduce the non-carcinogenic risks associated with manganese, iron, copper, zinc, and selenium, compared to conventional chemical fertilizers. Notably, trace elements such as zinc and molybdenum exhibited a significant negative correlation with macro-minerals like magnesium and calcium in compost-amended crops. Based on these findings, we recommend the use of urban organic compost in cultivating vegetables on the Yamuna Floodplain, combined with groundwater irrigation, as a sustainable approach to producing high-quality crops with minimal health risks for human consumption.
An Efficient Prediction of Sustainable Concrete Properties of Hybrid Steel Fiber-Reinforced Self-Compacting Concrete Using the Novel JO-mSigmoid-ANN Model
Authors: B Ramkumar K , R Kannan Rajkumar P , J Baskara Sundararaj , M Jegan 
Published: September 2024

Abstract

Sustainable and renewable energy has gained global prominence because of the alarming depletion of natural resources and rise in greenhouse gas (GHG) emissions. With the increasing utilisation of supplementary cementitious materials (SCMs) in concrete, it has become necessary to accurately predict the properties of concrete. In the construction field, the development of artificial intelligence-based prediction models has received remarkable attention. As a result, developing a model to predict the properties of SCC with regards to sustainability concerns is essential to save time, cost and energy. However, models for the prediction of fresh properties of concrete is scarce. To carry out this assessment in an automated manner, this research work proposes a novel jellyfish optimiser-based modified sigmoid-activated artificial neural network (JO-mSigmoid-ANN) model for the prediction through the regression analysis of the flow and mechanical properties of the 60 and 80 MPa SCC, in which 0.5% and 0.75% of hybrid steel fibres (hooked steel and micro steel) were added. The ANN results were compared with the experimental results obtained in this research as well as the results available in the existing literature. The proposed model effectively predicts the flow and mechanical properties of SCC blended with hybrid steel fibres in comparison with the experimental data set with R2 values of 0.9679 and 0.9931. Similarly, the R2 value obtained for four existing data sets are 0.9868, 0.9164, 0.9338 and 0.74619, respectively.
Research of quality during drilling of CFRP with ultrasonic-assisted machining
Authors: Gong Yuxuan , Zhu Baiwei , Zhuang Bailiang , Liu Erliang 
Published: September 2024

Abstract

In this study, an ultrasonic tool holder was designed and improved based on traditional tool holder designs to process the difficult-to-machine materials, such as carbon fiber composite materials. The design incorporated a variable cross-section ultrasonic horn and a core-clamped piezoelectric transducer with dimensions calculated by MATLAB R2021b based on the equivalent circuit method. Focusing on the longitudinal vibration ultrasonic knife handle, ANSYS 2022R1 was used to conduct finite element modal and harmonic response simulations to determine the resonant frequency of the tool holder. After the assembling of the tool holder, the experimental testing was conducted to determine the resonant frequency, resistance, effective electromechanical coupling coefficient, etc. The experimental results are compared with the simulation outcomes to validate the accuracy of the design. The amplitude of the ultrasonic tool holder was measured using a Doppler laser vibrometer, revealing a resonant frequency of 20260 Hz and a front-end amplitude of 10 μm, which aligned with the simulations. the ultrasonic tool holder was then connected to the spindle interface of the machine tool and installed on the ultrasonic combined machine tool. Power and cutting force testing were performed on a carbon fiber reinforced polymer/plastic (CFRP) composite plate using a force measuring instrument. The experimental results show that the amplitude of the ultrasonic knife increases linearly with ultrasonic power, and the force on the composite plate gradually decreases at constant speeds and feeds. When the reference powers were set at 40%, 60%, and 80%, the axial force exerted by the ultrasonic tool holder during drilling was lower compared to concentional tool holders,yielding favorable machining results. Moreover, results demonstrate that the ultrasonic-assisted processing enhances the cutting efficiency and quality of CFRP composite materials.
Distinct management units for the Critically Endangered angelshark (Squatina squatina) revealed in the Canary Islands
Authors: Meyers Eva KM , Faure Nadia , Jimenez-Alvarado David , Barker Joanna , Toledo-Padilla Hector , Tuya Fernando , Pike Charlotte , Mead Lucy R , Sealey Michael J , Caro Maria Belen , Jacoby David MP , Olivares Felipe Ravina , Bañeras Tomas , Guerra-Marrero Airam , Espino-Ruano Ana , Castro Jose Juan , Bousquet Caroline , Giovos Ioannis , Rödder Dennis , Manel Stéphanie , Deter Julie , Feldheim Kevin A 
Published: September 2024

Abstract

The angelshark, Squatina squatina, is listed as Critically Endangered on the IUCN Red List of Threatened Species and remaining populations are highly fragmented throughout its historical distribution range. The Canary Islands archipelago in the North East Atlantic has been identified as a uniquely large stronghold for the species. In the present study, we compared the population genetic structure of S. squatina across different islands of the Canary Island archipelago using both microsatellite and single nucleotide polymorphism (SNP) markers. Both markers revealed significant differentiation of angelsharks between islands in the archipelago, with three main genetic units at: (1) Tenerife, (2) Gran Canaria and (3) a third one that included La Graciosa, Lanzarote and Fuerteventura. Our results imply a connectivity barrier between some adjacent islands, most likely driven by abyssal depths, and varying geological history and oceanographic patterns. Therefore, we suggest that in the Canary Islands, S. squatina populations should be managed locally, with conservation and research priorities designed and implemented specifically for each of the three genetic units.
Molecular Docking, Pharmacophore Mapping, and Virtual Screening of Novel Glucokinase Activators as Antidiabetic Agents
Authors: Mehra Anuradha , Mittal Amit , Thakur Divya 
Published: September 2024

Background:
A pivotal impetus has led to the development of numerous small molecules
to develop therapeutic strategies for type 2 diabetes. Novel heterocyclic derivatives are now available
with expansive pharmacological activity designed specifically to activate Glucokinase (GK) in
the body. This target is of particular significance in antidiabetic drug design since it is a newly validated
target. Individuals with type 2 diabetes are unable to maintain blood glucose homeostasis due
to impaired glucokinase function. The novel approach to managing type 2 diabetes relies on utilizing
heterocyclic derivatives to activate the GK enzyme, also known as a metabolic enzyme.

Objective:
In this research endeavor, the primary objective was to improve drug delivery while minimizing
adverse effects by using molecules that activate glucokinase.

Methods:
There are 53,000 compounds included in Maybridge's online repository, which has been
subjected to rigorous scrutiny. Eight two compounds that encompass the specific oxadiazole core
were selectively extracted from this extensive collection. ChemBioDraw Ultra was used for structural
drawing, and AutoDock Vina 1.5.6 was used to perform docking analysis. For the online prediction
of log P, the SwissADME algorithm was employed. A PKCSM software program was used
to predict toxicity for leading compounds.

Results:
Among all of the compounds, AD80 and AD27 displayed the highest affinity for GK receptors.
These compounds, by adhering to Lipinski’s Rule of Five, exhibited good absorption and
excretion profiles through the gastrointestinal (GI) tract. Lipinski’s Rule of Five refers to physicochemical
properties that favor good oral bioavailability, and these specifications are zero to five hydrogen
bond donors, zero to ten hydrogen bond acceptors, molecular weight below 500, and log P
no more than five. These criteria ensure that the compounds of the invention have acceptable solubility
and permeability, which are vital prerequisites when given orally, to be absorbed via the gastrointestinal
wall, metabolized, and found in the urine. Therefore, the chance of drug candidates exhibiting
favorable pharmacokinetic characteristics is increased, enhancing their chances of being
developed for oral administration. In comparison with standard drugs Dorzagliatin as a glucokinase
activator (GKA) and MRK (co-crystallized ligand), these compounds exhibit no skin sensitization,
AMES toxicity, or hepatotoxicity.

Conclusion:
The recently designed lead molecules exhibit an improved pharmacokinetic profile,
enhanced binding affinity, and minimal toxicity based on the computational study, potentially making
them suitable candidates for further optimization as glucokinase activators.
Pyrylium Compounds as Dual-transition pH Indicators and their Applications to Smartphone-assisted pH Determination
Authors: Şakacı Doğukan , Teknikel Efdal 
Published: September 2024

Introduction:
pH indicators have long been utilized for rapid pH determination, relying
on color changes to indicate pH values. However, visual color detection suffers from low sensitivity
due to the limitations of the human eye. In this study, we explored the use of pyrylium compounds as
pH indicators.

Method:
Three pyrylium compounds were synthesized, and their pH-dependent UV-Vis absorption
and color changes were investigated. UV-Vis absorption studies revealed distinct pH-dependent
changes, enabling the compounds to function as dual-transition pH indicators. The pKa values of
these indicators can be tuned by changing the substituent on the chromophore core.

Results:
Principal component analysis of the mixture of these three compounds demonstrated the
ability of the system to measure pH with high precision, making it suitable for real sample analysis.
Smartphone-assisted analysis was employed to exploit the potential of these indicators for widerange
(4.0-13.5) pH determination.

Conclusion:
The obtained results demonstrated for the first time that pyrylium compounds can be
used as dual-transition pH indicators. By modifying the substituents on this chromophore, indicators
operating in different pH ranges can be obtained and utilized in smartphone-assisted pH detection.
Impact of Upright Position during the First Stage of Labour on Maternal Outcomes: A Randomized Controlled Trial
Authors: Rani Kamlesh , Ravi Ramya Kundayi , Attri Vijeta , Kaur Harpreet , Pareek Bharat , Baby Priya 
Published: September 2024

Background:
Maternal position during delivery can affect the physiology of labour and
the mechanics of childbirth.

Objective:
The study aimed to evaluate the impact of an upright position during the first stage of
labour on maternal outcomes.

Methods:
This parallel group randomised control trial was conducted from April to June 2020
among 60 women (30 each in the experimental and control groups) admitted to the selected hospital
in Punjab, India. Women who entered the active stage of labour naturally with a single live foetus
in cephalic presentation, aged 18-45 years, and with normal body mass index were randomly
assigned either to the experimental or control group using a concealed envelope method. Women
in the experimental group were informed and encouraged to adopt the upright position, while
those in the control group received the standard routine care during the first stage of labour. The
effectiveness of upright positions during the first stage of labour was assessed in terms of duration
of the first, second, and third stages of labour, mode of delivery, and perineal lacerations. Outcome
assessors were blinded to the intervention. The differences in the groups were evaluated by
mean, median, frequency, percentage, Chi-square, and t-test.

Results:
The results of 60 women were analysed. Women in the experimental group experienced a
significant reduction in the incidence of instrumental delivery (p =0.005), perineal laceration (p
=0.001), and duration of the first stage (p =0.0001) and third stage (p =0.0001) of labour compared
to those in the control group. No harm was reported across the study groups.

Conclusion:
This study urges nurses and midwives to recommend the use of upright positions during
the first stage of labour to reduce the duration of labour and incidence of perineal laceration
among women.