bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational Insights into Mechanism and Kinetics of Organic Reactions: Multiscale Modeling of SN2 and Claisen Rearrangements
Authors: Dehabadi Maryam Haji , Saidi Hamid , Zafari Faezeh , Irani Mehdi 
Published: May 2024

Abstract

This study explores the application of quantum mechanical (QM) and multiscale computational methods in elucidating the reaction mechanisms and kinetics of SN2 reactions and the Claisen rearrangement. The aim is to assess the accuracy and efficacy of these methods in predicting experimental outcomes for these organic reactions. By employing various variants of QM/MM, QM1/QM2, and QM1/QM2/MM methodologies, we investigated the mechanisms and kinetics parameters involving methyl iodide with NH2OH and NH2O− for SN2 reactions, as well as the Claisen rearrangement of 8-(vinyloxy)dec-9-enoate. Our results emphasize the importance of explicitly considering solvent effects in the calculations for accurate reproduction of transition state geometry and energetics, particularly evident in SN2 reactions. Multiscale methods, notably QM/MM and QM1/QM2, demonstrated promising performance in predicting activation energies, with some variants showing close agreement with experimental values. Additionally, the study highlights the significant influence of the MM active region size on the accuracy of calculated activation energies. For the Claisen rearrangement, both QM-only and multiscale methods successfully reproduced the proposed reaction mechanism, although discrepancies were observed in the calculated activation free energies. This study underscores the critical role of method selection and setup parameters in computational chemistry studies, with implications for future research aimed at refining computational models to improve predictive capabilities in organic reaction studies. Additionally, a Python code for setting up multiscale calculations with ORCA is introduced, available on GitHub at https://github.com/iranimehdi/pdbtoORCA.
Trends and influencing factors of complementary feeding practices in Niger: An analysis of national surveys from 2000 - 2018
Authors: Shakya Evaniya , Ngoutane Raphia Moluh , Sodjinou Roger , Kaligirwa Christine , Dain Anne-Sophie Le , Garg Aashima , Zagre Noel , Kodish Stephen R. , Na Muzi 
Published: May 2024

Abstract

Background
To examine the trends and influencing factors of complementary feeding (CF) practices among Nigerien children aged 6–23 months between 2000–2018.
Methods
Using the 2000 Multiple Indicator Cluster Survey (MICS), 2006 Demographic and Health Survey (DHS), 2012 DHS, and 2018 Standardized Monitoring and Assessment of Relief and Transitions (SMART) survey, we estimated the trends of four WHO-UNICEF CF indicators: timely introduction of complementary foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD). The analysis included youngest singleton infants and children aged 6–23 months living with their mothers. We identified risk factors associated with meeting the WHO-UNICEF CF indicators using modified Poisson regression models using DHS 2012.
Results
The proportion of infants and children meeting INTRO (53.7–81.8%), MMF (53.6–78.2%), MDD (9.7–24.1%), and MAD (5.8–13.0%) increased between 2012–2018. In 2012, older children and mothers who listened to the radio had a higher prevalence of meeting MMF, MDD, and MAD. Children of employed mothers had a higher prevalence of meeting INTRO, MDD, and MAD. Child vitamin A supplementation, child iron supplementation, and mothers watching TV were associated with MMF, MDD, and MAD respectively. Poorer wealth quintiles were associated with lower prevalence of meeting MDD and MAD.
Conclusions
The modifiable risk factors of suboptimal CF include child micronutrient supplementation, maternal employment, and household wealth. As CF practices remain inadequate in Niger, emphasis should be given to multisectoral strategies that target these modifiable risk factors.
Acid concentration, low and high valent sulfate anion, and solvent effects on polaronic transitions and conductivity of new poly (ortho-methoxyaniline) nanocomposites
Authors: Modarresi-Alam Ali Reza , Shariati Ilnaz , Khamooshi Ferydoon 
Published: May 2024

Abstract

The aim of this research is to the identification of the changes in anion- and solvent-dependent polaronic transitions and the ratio of acid to monomer during the polymerization of new poly(ortho-methoxyaniline)nanosilica-supported sulfuric acid emeraldine salt1/salt2(POMA-NSSSA-ES1/ES2) nanocomposites. The synthesis is done by doping poly(ortho-methoxyaniline)-emeraldine base(POMA-EB) in the presence of nanosilica-supported sulfuric acid(NSSSA) under solid-state conditions. The structure, size, and morphology of all samples were identified using spectroscopy methods. Effect of acid concentration(0.5, 1.5, and 2.0) and low- and high-valent sulfate anion(H2SO4/HSO4- Vs. HSO4-/SO42-) on polaronic transitions of poly(ortho-methoxyaniline) nanocomposites in different solvents(NMP, MCR, DMSO and MeOH) and conductivity were studied and changes in polaron mutations under changing conditions were analyzed. Changes in polaron mutations under changing conditions were analyzed. Increasing the acid concentration compared to the monomer increases the absorption number in the UV-Vis study along with the red shift and bathochromic effect in low acid concentration and hyperchromic effect in high acid concentration for polaronic transition. The anion effect proved that by increasing the negative charge of the anion (SO42-) due to the limiting potential of the polaron and bipolaron structures, it prevents the creation of delocalized polaron structure with no change in a decrease and limitation of the POMA-NSSSA-ES2 nanocomposite conductivity. Results showed that the average size of nanocomposite particle obtained by this method was a range of 40-50 nm the morphology of nanocomposites was spherical (nanospheres) and POMA-NSSSA nanocomposites are completely in a doped state and the emeraldine salt from of POMA. During this research, for the first time, the polaronic orbital energy level was determined.
The Merrifield-Simmons Index of Two Classes of Silicate Molecular Graphs
Authors: Zhang Hailiang , Liu Lu 
Published: May 2024

Abstract

Graph theory is of great use in modeling chemistry structures. In chemistry and physics, the silicate are the largest, the most interesting and the most completed class of minerals, and are the component of the common rock-forming minerals. The tetrahedron SiO4 is fundamental unit of silicates. The corner vertices are oxygen atoms and the center atom is the silicon atom. In this paper, we compute the Merrifield-Simmons index of two classes of silicate molecular graphs. We also show that these two classed molecular have the same independence entropy. The difference of matching entropy and the independence entropy is (log 2)/3.
Promising acerola (Malpighia emarginata Sessé &amp; Moc. ex DC.) genotypes with high fruit quality for different purposes
Authors: Silva Raquel de Souza , Souza Flávio de França , Vilvert João Claudio , Ribeiro Tiffany da Silva , Costa Cristina dos Santos Ribeiro , de Freitas Sérgio Tonetto 
Published: May 2024

Abstract

Acerola is a tropical superfruit known for its rich vitamin C content. Due to the considerable genotypic variability in fruit quality traits, an effective multitrait selection is essential for an acerola breeding program aimed to identify promising genotypes for distinct purposes. In this study, fruits from 95 acerola genotypes were evaluated at two maturity stages across three growing seasons. The genotypes were selected for vitamin C extraction (green unripe fruits) and fresh consumption (red ripe fruits), using four selection indices. The variability ranges for quality traits were as follows: fruit mass of 4.19–5.60 g (green fruit) and 4.13–5.90 g (red fruit), vitamin C of 1492.0–2995.8 mg/100 g (green fruit) and 1247.2–2873.6 mg/100 g (red fruit); soluble solids and titratable acidity of 4.70–13.07% and 0.60–1.60%, both in red fruit. Desirable gains for all traits were achieved by the multitrait indices. Twelve genotypes (Flor Branca, IARP 01, ALHA 03, ACO 10, Junko, Natália, LAG 04, Lígia, Luisa, LAG 05, Costa Rica and BV 01) stood out for vitamin C extraction at the green stage, as well as eleven genotypes (Manoela, IARP 01, Okinawa, LAG 04, Costa Rica, Clone 71/2, ACO 05, ACO 14, LAG 01, BRS Rubra and MAR 10) excelled for fresh consumption at the red stage. Costa Rica, IARP 01 and LAG 04 were selected as dual-purpose genotypes, intended for both fresh consumption and vitamin C extraction.
A Stable Meshfree Method for Simulations of Munition Penetration into Earth
Authors: Atif Mohammed Mujtaba , Chi Sheng-Wei , Li Xuejun , Tian Jianfei 
Published: May 2024

Abstract

Mesh-free methods, such as the Reproducing Kernel Particle Method, have been proven advantageous in modeling excessive deformation problems involving material separation, fracture, impact, etc. However, the domain integration in the RKPM remains challenging due to instability and sub-optimal convergence for high strain rate events. Although some novel developments alleviate the above issue, they are either computationally expensive or require evaluating the contour integral, which is not straightforward to obtain in contact and material separation problems using meshfree discretization. This work develops a simple and stable integration method based on the extension of modified Simpson’s rule. The method is free from conforming subdomains and can straightforwardly be applied to the meshfree formulation with updated configuration. To model penetration into the earth, a standard viscous boundary is introduced to address the issue of reflecting waves from the truncated computational domain for the ground target. proposed semi-Lagrangian RK framework to mimic the earth domain. The numerical results are validated with experimental data for various geo-materials and experimental setups.
Optimizing Machine Learning for Daily Rainfall Prediction in Bogor City, Indonesia: A Two-Stage Statistical Downscaling Approach
Authors: Arassah Fradha Intan , Sadik Kusman , Sartono Bagus , Sofan Parwati 
Published: May 2024

Abstract

Statistics for machine learning come as a significant tool for studying data. General Circulation Model (GCM) are the most sophisticated model for predicting climate and weather. This study deployed a two stage of machine learning model for statistical downscaling approach to predict daily rainfall in Bogor, Indonesia. This study compared three different domains of GCM and compare two different approaches to handling missing data. First, we made two datasets based on approaches to handling missing value. Then, Support Vector Classification model was applied to classify rainy and non-rainy days. Finally, we developed a model of rainy-day data using Recurrent Neural Networks (RNN) method to estimate daily rainfall. The results show that using random forest imputation for handling missing value can increase the accuracy and lower the RMSE of the model. The best domain from GCM data is 5 km from local station climatology. SVC model with radial basis kernel is the best model for classify rainy and non-rainy data with 0.985 (98.5%) accuracy and RNN model have RMSE at 16.19. Accurately estimating the increase or decrease in extreme rainfall is crucial to provide effective recommendations in disaster mitigation efforts.
Non-isothermal kinetic analysis of UHMWPE sheet
Authors: Jagriti Jagriti , Khattar Nidhi , Kainth Shagun , Sharma Piyush , Diwan P. K. 
Published: May 2024

Abstract

Thermal decomposition behavior of ultra high molecular weight polyethylene (UHMWPE) is studied through thermogravimetric analysis technique. Thermograms are recorded at four different heating rates (2.5, 5, 10, 15 and 20 ℃/min) in nitrogen environment. These thermograms revealed that the thermal decomposition of UHMWPE occurred in three different stages. Among these stages, second stage of decomposition is highly complex. Therefore, deconvoluted into two peaks by using bi-Gaussian asymmetric function. Kinetic triplets related to these peaks are determined by adopting two iso-conversional kinetic models (Starink (SR) and Friedman (FR)). The reaction mechanism is also identified by using integral master plot method. Finally, thermodynamic parameters viz. change in entropy (∆S), change in enthalpy (∆H) and change in Gibbs free energy (∆G) are estimated at considered heating rates.
Therapeutic efficacy of bovine serum albumin-gold nanocluster against antibiotic-resistant bacterial susceptibility
Authors: Samivel Ramachandran , Almubrad Turki , A.Khan Adnan , Masmali Ali , ALANAZI SAUD , Akhtar Saeed 
Published: May 2024

Abstract

Biofilm formation is one of the most vital risk factors for antimicrobial resistance in bacteria. In the present study we investigated the effect of bovine serum albumin-gold nanoclusters (BSA-GNCs) against antibiotic-resistant bacterial susceptibility. BSA-GNCs was synthesized by adding HAuCl4 and BSA as a capping agent. BSA-GNCs were characterized by UV-Visible spectrophotometer, FTIR, Zeta sizer, SEM-EDX and TEM analysis. Antibacterial activity from antibiotic-resistant bacterial strains Klebsiella pneumoniae, Streptococcus aureus, and non-resistant bacterial strains Pseudomonas aeruginosa and Enterococcus faecalis were assessed using the disc diffusion method. The pellets of the control and BSA-GNCs treated bacteria were procured for transmission electron microscopy. The ultrastructural images of the bacteria were captured using a bottom mounted 15-megapixel Quemesa camera with iTEM software. A peak at λmax = 550nm from UV-Visible spectrophotometer spectrum was confirmed the formation of gold nanoclusters. FTIR peaks were found at 598.33, 1102.79, 1261.21, 1637.84, 2923.54 & 3430.76cm− 1, and average hydrodynamic particle size distribution peaks were 22.72nm. BSA-GNCs were homogenous as well as cluster nature. BSA-GNC (20µL/disc) treatment inhibited the growth zone of the bacteria (KP 13.17 ± 1.32, SA 16.67 ± 1.46, PA 23.17 ± 1.82 and EF 25.67 ± 1.93 mm) at 24 hours. The BSA-GNCs treated bacteria accommodating shrunken, stranded and degenerated cytoplasm. The degeneration of the bacteria was more severe in antibiotic susceptible bacteria than antibiotic resistant bacteria. BSA-GNCs attenuate the transport of essential elements to the bacteria leading to the degeneration of the cytoplasm followed by the disintegration of the plasma membrane, cell walls and extinguishing the bacteria.
A Robust Lightweight Compound Emotion Recognition Approach Using Depthwise Separable CNN
Authors: Ullah Sana , Xie Yuanlun , Ou Jie , Wang Zhaokun , Tian Wenhong 
Published: May 2024

Abstract

With the innovation in computer vision, facial expression recognition (FER) is a dynamic research domain considering extensive practical applications in various domains together with health, education, safety, law enforcement, Banking, marketing, and many more. The researchers have conducted tremendous research work on basic facial expressions recognition, but less on compound emotions recognition, which have complex features due to the combination of basic emotions. Different deep learning models have been used for compound emotions recognition; however, these deep learning models are computationally expensive due to large parameters and training time. To overcome this problem, we have proposed a robust lightweight approach using depthwise separable convolution (DSC), and residual connections. The proposed model outperformed the state-of-the-art (SOTA) models with an achieved accuracy of 70.4% on the RAFDB dataset, and 67.2% on the CFEE dataset. The proposed model improved the accuracy performance of compound emotion recognition by 1.9% on the RAFDB dataset, and 9.8% on the CFEE dataset from the SOTA models. The proposed approach reduced model parameters, and memory consumption compared with the deep learning model of standard convolution.
Prevention of TB in nonhuman primates by a stress-response deficient mutant of Mycobacterium tuberculosis via induction of classical T cell immunity
Authors: Kaushal Deepak , Singh Dhiraj , Ahmed Mushtaq , Akter Sadia , Bucsan Allison , Mishra Abhishek , Shivanna Vinay , Golden Nadia , Didier Peter , Dick Edward , Doyle-Meyers Lara , Hall-Ursone Shannan , Roy Chad , Arora Garima , Jagannath Chinnaswamy , Mehra Smriti , Khader Shabaana 
Published: May 2024

Abstract

The need for novel vaccination strategies to control tuberculosis (TB) is underscored by the limited and variable efficacy of the currently licensed vaccine, Bacillar Calmette-Guerin (BCG). SigH is critical for Mycobacterium tuberculosis (Mtb) to mitigate oxidative stress, and in its absence Mtb is unable to scavenge host oxidative/nitrosative bursts. The MtbDsigH (DsigH) isogenic mutant induced signatures of the innate immune response in macrophages, and protected rhesus macaques from a lethal Mtb challenge. To understand the immune mechanisms of protection via mucosal vaccination with DsigH, we employed the resistant cynomolgus macaques; and our new results show that DsigH vaccination significantly protected against lethal Mtb challenge in this species. DsigH­-vaccinated macaques are devoid of granulomas and instead generate inducible bronchus associated lymphoid structures, and robust antigen-specific CD4+ and CD8+ T cell responses, driven by a hyper-immune, trained immunity-like phenotype in host macrophages with enhanced antigen presentation. Correlates of protection in DsigH­-vaccinated macaques include gene signatures of T cell activation, IFNG production, including IFN-responsive, activated T cells, concomitant with IFNG production, and suppression of IDO+ IFN-responsive macrophage recruitment. Thus, ΔsigH is a promising lead candidate for further development as an antitubercular vaccine.
Application of stochastic simulation-estimation approach to the optimization of Pharmacokinetic studies design in the context of paediatric extrapolation: A step toward better decision making for drug sponsors and regulators
Authors: Djokoto Happy Phanio , Ernst Lana , Dogné Jean-Michel , Musuamba Flora T. 
Published: May 2024

Abstract

Extrapolation-based approaches are widely used in the context of paediatric drug development. Most of the times, inference is made on the (favourable)[1] benefit/risk balance (BRB) based on the similarity pharmacokinetics (PK) exposures between adults and children. This PK-based extrapolation approach necessitates generation of PK data in children. Given the ethical and practical challenges inherent to conducting clinical trials in children, it is crucial to ensure that the collected data are relevant and informative. In the present work, we propose a stochastic simulation-estimation-based approach to ensure the optimality of the key study design factors (number of patients, number of samples and sampling times) for conduct of PK studies in the context of paediatric extrapolation. Using 3 case-studies including a monoclonal antibody administered subcutaneously and two small molecules with intravenous and oral administration routes, we illustrate how stochastic simulation estimation (SSE) can be used in the context of drug development, to meet regulatory requirements. The present research demonstrates how the design of a paediatric study can be optimized before data collection based on the available data from the adult drug development, that often precedes children’s. Our results show how, for each of the 3 case-drugs, using a simulation-based approach, paediatric PK study can be designed ensuring that model parameters precision and accuracy would be under 30% and 20% respectively. These results provide useful information for drug sponsors and regulators as far as extrapolation in smaller populations such as paediatric is concerned.
Prevalence and psychiatric correlates of loneliness in UK university students
Authors: Akram Umair , Drabble Jennifer , Irvine Kamila , Allen Sarah , Akram Asha , Stevenson Jodie , Gardani Maria 
Published: May 2024

Abstract

University students remain vulnerable to the experience of loneliness and comorbid psychiatric difficulties, as evidenced in countries worldwide. Despite this, few studies provide data concerning these factors amongst those studying at institutions in the UK. In the present study, we examined the prevalence of loneliness among UK university students whilst assessing the association between multiple psychiatric risk factors. Here, N=1408 students completed eight validated measures were used: Generalized Anxiety Disorder Scale; Patient Health Questionnaire; The Mood Disorder Questionnaire; The Sleep Condition Indicator; The Perceived Stress Scale; Suicidal Behaviours Questionnaire-Revised; The Prodromal Questionnaire 16; and the University of California Loneliness Scale. Moderate to severe levels of loneliness was reported by approximately two thirds of students (67.2%). Loneliness was significantly associated with each psychiatric symptom. After accounting for shared variance between symptoms, linear regression analyses determined loneliness to be significantly related to perceived stress, depression, psychotic like experiences and suicidal ideation. We demonstrate the exceedingly high prevalence of loneliness amongst large sample of UK university students, whilst highlighting the prominent role of depresion, psychotic experiences, perceived stress, and suicidal ideation. Whilst highlighting the primacy of tailored interventions for lonely students, future work should explore contextual factors faced by UK university students.
Antibiotic resistance profiles of sentinel bacteria isolated from aquaculture in Cambodia
Authors: Peng Chanthol , Moniroth Sopheavattey , Khy Panha , Chea Sopheaktra , Thanh Channmuny , Heng Oudam , Sarter Samira , Cheng Sokleaph , Caruso Domenico 
Published: May 2024

ABSTRACT

The misuse of antibiotics and the emergence of antimicrobial resistance (AMR) is a concern in the aquaculture industry because it contributes to global health risks and impacts the environment. This study analyzed the AMR of sentinel bacteria associated with striped catfish (Pangasisanodon hypophthalmus) and giant snakehead (Channa micropeltes), the two main fish species reared in the pond culture in Cambodia. Phenotypic and genotypic characterization of the recovered isolates from fish, water, and sediment samples revealed the presence of bacteria, such as 22 species belonging to families Aeromonadaceae, Enterobacteriaceae, and Pseudomonadaceae. Among 48 isolates, Aeromonas caviae (n = 2), Aeromonas hydrophila (n = 2), Aeromonas ichthiosmia (n = 1), Aeromonas salmonicida (n = 4) were detected. A. salmonicida and A. hydrophilla are known as fish pathogens that occur worldwide in both fresh and marine water aquaculture. Antibiotic susceptibility testing revealed antibiotic resistance patterns of 24 (50 %) isolates among 48 isolates with higher multiple antibiotic resistance index (&gt; 0.2). All the isolates of Enterobacteriaceae were susceptible to ciprofloxacin. Ciprofloxacin is a frontline antibiotic that is not recommended to use in aquaculture. Therefore, its use has to be strictly controlled. This study expands our knowledge of the AMR status in aquaculture farms which is very limited in Cambodia.