Molecular dynamics (MD) simulations present a sophisticated nano-scale computational approach that can play a critical role in material design for next generation batteries. One critical piece of information needed for MD simulations is the non-bonded potential parameters, which can be obtained through quantum mechanics (QM) calculations or experimental methods. However, experimental data is not available for exploratory and novel materials to derive the potential parameters. Also, the QM approach needs significant computational power and is too time consuming for large systems. On the other hand, current Artificial Intelligence techniques are faster, but they cannot be generalized across molecules and properties. As a result, there is a significant barrier to discovering and exploring new materials. Overcoming this barrier, in this work, we propose a Machine Learning (ML) based technique that can learn inter-atomic potential parameters for various particle-particle interactions employing QM calculations. This ML model can be used as an alternative for QM calculations for predicting non-bonded interactions in a computationally efficient manner. Using these parameters as input to MD simulations, we can predict a diverse range of properties, enabling researchers to design new and novel materials suitable for various applications in the absence of experimental data. We employ our ML-based technique to learn the Buckingham potential, a non-bonded interatomic potential. Subsequently, we utilize these predicted values to compute the densities of four distinct molecules, achieving an accuracy exceeding 93%. This serves as a strong demonstration of the efficacy of our proposed approach.

We report a detailed investigation of vibrational modes, structure, and dynamics of glutathione (GSH) solutions using ultrasonic relaxation spectroscopy, FT-IR vibrational spectroscopy and electronic absorption measurements. The experimental data were analyzed in view of density functional theory (DFT) and molecular docking calculations. Three distinct Debye-type relaxation processes are resolved in the acoustic spectra, which are assigned to conformational changes between GSH conformers, self-association of GSH, and protonation processes. The standard volume changes for each process were estimated both experimentally and theoretically revealing a close resemblance among them. The higher the effect of the relaxation process in the structure, the greater the induced volume changes. From the temperature dependence of specific acoustic parameters, the thermodynamic characteristics of each process were determined. The experimental FT-IR spectra were compared with the corresponding theoretically predicted vibrational spectra revealing that the GSH dimers and extended conformers dominate the structure of GSH solutions in the high concentration region. The absorption spectra in the ultraviolet region confirmed the gradual aggregation mechanism that takes place in the aqueous GSH solutions. The results of the present study were discussed and analyzed in the framework of the current phenomenological status of the field.

The development of the ovarian antral follicle is a complex, highly regulated process. Oocytes orchestrate and coordinate the development of mammalian ovarian follicles, and the rate of follicular development is governed by a developmental program intrinsic to the oocyte. Characterizing oocyte signatures during this dynamic process is critical for understanding oocyte maturation and follicular development. Although the transcriptional signature of sheep oocytes matured in vitro and preovulatory oocytes have been previously described, the transcriptional changes of oocytes in antral follicles have not. Here, we used single-cell transcriptomics (SmartSeq2) to characterize sheep oocytes from small, medium, and large antral follicles. We characterized the transcriptomic landscape of sheep oocytes during antral follicle development, identifying unique features in the transcriptional atlas, stage-specific molecular signatures, oocyte-secreted factors, and transcription factor networks. Notably, we identified specific gene and signaling pathways in each antral follicle stage that may reflect oocyte quality and in vitro maturation competency. Additionally, we discovered key biological processes that drive the transition from small to large antral follicles, revealing hub genes involved in follicle recruitment and selection. Thus, our work provides a comprehensive characterization of the single-oocyte transcriptome, filling a gap in the mapping of the molecular landscape of sheep oogenesis. We also provide key insights into the transcriptional regulation of the critical stages of antral follicular development, which is essential for understanding how the oocyte orchestrates follicular development.

Worldwide, hypoxia-related conditions, including cancer, COVID-19, and neuro-degenerative diseases, often lead to multi-organ failure and significant mortality. Oxygen, crucial for cellular function, becomes scarce as levels drop below 10 mmHg (<2% O2), triggering mitochondrial dysregulation and activating hypoxia-induced factors (HiFs). Herein, Oxygen nanoBubbles (OnB), an emerging versatile oxygen de-livery platform, implies to offer a novel approach to address hypoxia-related pathologies. This review explores OnB oxygen delivery strategies and systems, including diffusion, ultrasound, photodynamic, and pH-responsive nanobubbles. It delves into the nanoscale mechanisms of OnB, elucidating their role in mitochondrial metabolism (TFAM, PGC1alpha), hypoxic responses (HiF-1alpha), and their interplay in chronic pathologies including cancer and neurodegenerative disorders, amongst others. By understanding these dynamics and underlying mechanisms, this article aims to contribute to our accruing knowledge of OnB and the developing potential in ameliorating hypoxia- and metabolic stress-related conditions and fostering innovative therapies.

In Pakistan, bats are one of the dominant mammals that play an important role in the ecosystem in terms of pollination, seed dispersal, and control of pest insects. Bats have also played an im-portant role in the emergence and transmission of zoonotic pathogens; however, most current studies focus on viral pathogens, not potential bacterial pathogens. This study was designed to estimate the prevalence and antibiotic profiling of Staphylococcus (S.) aureus in oral and rectal samples from bats captured in northern Pakistan and to determine the factors associated with in-fection. Two hundred individual bats of five species: Pipistrellus javanicus (n = 17), Pipistrellus pipistrellus (n = 10), Rhinopoma microphyllum (n = 48), Rousettus leschenaultii (n = 124), and Scotophilus kuhlii (n = 1) were captured for non-lethal collection of oral and rectal samples to iso-late S. aureus. Bats were sampled from three sites: a natural cave, a man-made castle, and an an-imal shed, in Khyber Pakhtunkhwa and Punjab provinces. Oral (n = 200) and rectal (n = 200) swabs were collected from each individual bat using sterile cotton swabs specifically for use in bacteriological studies. Each isolate of bacteria was identified by using phenotypic tests and con-firmed as S. aureus based on PCR assay. Out of a cumulative four hundred samples, 80 swabs were positive for S. aureus including 47 rectal and 33 oral swabs. Prevalence of S. aureus infection varied significantly among species, with Rousettus leschenaultii exhibiting the highest prevalence (n = 77; 37.90%). In addition to bat species, prevalence varied significantly among habitats but not between sex, age class, or reproductive status. This study confirmed the occurrence of S. aureus in oral and rectal microbiota of bats in Pakistan. Importantly, S. aureus isolates showed resistance to tetracycline, gentamicin, and erythromycin and carried resistant genes such as TetK, TetM, Erma, and aacA-D. In this regard, efforts should be taken to educate the local communities on how to minimize exposure to an antibiotic-resistant bacterial pathogen through contact with bats while simultaneously increasing the awareness of protecting bats as a vital component of our ecosystem.

The emergence of multidrug-resistant pathogens such as Listeria monocytogenes and Shiga toxin-producing Escherichia coli (STEC) poses public health challenges, and this has led to a continuous search for effective novel antimicrobial agents. This study aimed to isolate marine actinomycetes from South Africa, evaluate their in vitro antimicrobial activity against Listeria and STEC, and characterize their mechanisms of action. Marine actinoymcetes were isolated and identified by 16S rRNA sequencing. Gas chromatography-mass spectrometry (GC-MS) was used to identify the chemical constituents of bioactive actinomycetes secondary metabolites. Antibacterial activity of the secondary metabolites was assessed by the broth microdilution method and their mode of actions were predicted using computational docking. While five strains showed antibacterial activity during primary screening, only Nocardiopsis dassonvillei strain SOD(B)ST2SA2 exhibited activity during secondary screening for antibacterial activity. GC-MS identified five major bioactive compounds: 1-octadecene, diethyl phthalate, pentadecanoic acid, 6-octadecenoic acid, and tri-fluoroacetoxy hexadecane. SOD(B)ST2SA2`s extract demonstrated the minimum inhibitory con-centration and minimum bactericidal concentration ranging from 0.78–25 mg/ml and 3.13 to > 25 mg/ml, respectively. Diethyl phthalate displayed the lowest bacterial protein binding energies (kcal/mol): −7.2, dihydrofolate reductase; −6.0, DNA gyrase B, and −5.8, D-alanine:D-alanine lig-ase. Thus, marine N. dassonvillei SOD(B)ST2SA2 is a potentially good source of antibacterial compounds that can be used to control STEC and Listeria monocytogenes.

BMAP-27 peptide known to exert cytotoxic effects against cancer cells by membrane integrity disruption. In the current investigation, we aimed to study the role of the BMAP-27 peptide in reducing colon cancer cell proliferation and inducing apoptosis. This study utilized both primary and metastatic colon cancer cell lines (SW480 and SW620). Proliferation was measured using CCK-8, and cellular damage was analyzed by lactate dehydrogenase assay. The study assessed apoptosis, cell cycle, and proliferation by measuring the expression of CASPASE3, BAX, BCL-2, TP53, CDK-6, PCNA, Wnt11, AXIN1, and CTNNB1. Additionally, in-silico studies were conducted to determine the binding affinities of BMAP-27 with APC and β-catenin proteins. BMAP-27 peptide reduced colon cancer cell proliferation, upregulated CASPASE3, BAX, TP53, AXIN1 expression, and downregulated BCL-2, CDK-6, PCNA, WNT11, CTNNB1 in both colon cancer cell lines, however, demonstrated higher activity in primary than metastatic colon cancer cells. The molecular dynamic simulation revealed substantial binding affinity of the peptide to adenomatous polyposis coli and β-catenin proteins.BMAP-27 peptide effectively inhibited the proliferation and enhanced apoptosis in the primary than in metastatic colon cancer cells. In-silico findings suggest that BMAP-27 exhibits a strong binding affinity with APC and β-catenin, highlighting its potential role as an anti-colon cancer agent.

Hoechst 33342 (H33342) is a fluorescent probe that is commonly used to stain DNA of living cells. To do so, it needs to interact with and permeate through cell membranes. The pH of biological media may vary quite significantly and this influences H33342 ionization state, and may change its rate of permeation through biomembranes. In this work, we address the effect of pH in the association of H33342 with lipid bilayers using a combined experimental and computational approach. The partition of H33342 to 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid membranes was experimentally quantified using fluorescence spectroscopy and isothermal titration calorimetry (ITC) measurements. Quantum chemical calculations were performed to select the most stable isomer of H33342 for the overall charges 0, +1, and +2, expected to predominate across the 5 &lt; pH &lt; 10 range. The interaction of these isomers with POPC bilayers was then studied by both unrestrained and umbrella sampling molecular dynamics simulations. While probe insertion occurs for all ionization states, with similar overall equilibrium location, orientation was found to depend on the probe charge, with the neutral form lying mostly parallel and the doubly charged displaying a significant tilt relative to the membrane plane. Both experimental results and computational free energy profiles indicate that the partition coefficient of H33342 displays a small variation over a wide pH range, not exceeding one order of magnitude. The enthalpy of interaction is negative and is larger at lower pH values. This suggests efficient hydrogen bonding between the probe and the lipid, namely for the protonated +2 form. The relatively high lipophilicity obtained for the charged species contrasts with the decrease in their general hydrophobicity as estimated from water and octanol partition. This highlights the distinction between lipophilicity and hydrophobicity, and the importance of considering association with lipid bilayers when predicting the affinity for biomembranes.

The adsorption of proteins on polymer is widely used in biosensors. Here, molecular dynamics (MD) simulation was used to study the immobilization of angiotensin converting enzyme II (ACE2) with six initial orientations proposed on polystyrene (PS) at the ambient conditions of pH (4.5, 6, 7, 8, 9.5) and NaCl (0.01, 0.05, 0.1, 0.15, 0.2, 0.25 M). ACE2 immobilization under favorable ambient conditions was characterized by minimum distance (short), settlement time (fast), interaction energy (substantial) and protein configuration (stable). ACE2 orientations proposed in 0.15M NaCl were respectively preferable to (90, 0, 0), (0, 0, 0) and (0, 270, 0), (180, 0, 0) and (0, 90, 0), (90, 0, 0) at pH 4.5, 6, 7, 9.5. ACE2 immobilization was further evaluated at pH 7 by optimizing NaCl concentration. Its proposed orientations of (i) (0, 270, 0), (ii) (0, 0, 0) and (90, 0, 0), and (iii) (0, 90, 0) and (90, 0, 0) were preferable in 0.05, 0.1 and 0.2 M NaCl, respectively. The great significance of cubic-orientation settlement mode provides tangible improvement for the microfabrication of biochips for rapid diagnosis of severe acute respiratory syndrome coronavirus II (SARS-CoV-2).

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

Due to species barriers and poor adaptability to new host environments, few pathogens cause global pandemics. But, SARS-CoV-2 is one exception with its high transmissivity and delayed onset of symptoms. Fortunately, the world was able to tap on the technologies especially the maturing RT-qPCR designed to combat SARS to launch an initial offensive on SARS-CoV-2. These initial efforts may have bought time for scientists to develop more refined diagnostic tests that specifically target SARS-CoV-2. This article describes the effort put forth by the biotech industry and academia in Singapore to develop diagnostic tests that aid the early detection of positive cases, and thereby help contain the virus. Direct tests such as RT-qPCR and antigen rapid test profile the virus nucleic acid and surface proteins, respectively. But, of equal importance in case detection and treatment is serological tests that measure the relative abundance of IgM and IgG which is indicative of infection phase and quality of immune response in positive cases. Other tests such as isothermal amplification, CRISPR-based diagnostics and breath tests are also in development or at initial field deployment, and would undoubtedly provide valuable use experience useful for the development of molecular assays to detect and combat the next pathogen of global concern.

Peyronie's disease (PD) is a benign condition caused by plaque formation on the tunica albuginea of the penis. It is associated with penile pain, curvature, and shortening, and contributes to erectile dysfunction, which worsens patient quality of life. In recent years, understanding of the detailed mechanisms and risk factors involved in development of PD has been increasing. In this review, the pathological mechanisms and several closely related signaling pathways, including TGF-β, WNT/β-catenin, Hedgehog, YAP/TAZ, MAPK, ROCK, and PI3K/AKT, are described. Findings regarding cross-talk among these pathways are then discussed to elucidate the complicated cascade behind tunica albuginea fibrosis. Finally, various risk factors including genetic involved in the development of PD are presented and their association with the disease summarized. The purpose of this review is to provide better understanding regarding involvement of risk factors in the molecular mechanisms associated with PD pathogenesis, as well as provide insight into disease prevention and novel therapeutic interventions.

Topological indices are invariant numerical fields of a graph that give facts about the structure of graphs and are found to be very helpful in predicting the physical properties of aluminophosphates. The characteristics of the aluminophosphates are similar to those of zeolites. Two examples of current applications are natural gas dehydration and humidity sensor. New frameworks are being synthesised by researchers in chemistry and materials science. There are many layers and holes in these substances. In this study, Vertex version of distance-based topological indices, the entropy of topological indices and their numerical analysis are explained.

Among bryophytes, the Plagiochila genus represents a large group of leafy liverworts, with over 500 species. Plagiochilins A-to-X are sesquiterpenoids isolated from Plagiochila species. The lead compound plagiochilin A (Plg-A), endowed with anticancer and anti-parasitic properties, has been characterized as a potent mitosis inhibitor, acting selectively at the late stage of cytokinesis termed abscission. The compound perturbs the dynamic of microtubules, blocking cell cycle progression and triggering the death of malignant cells. Based on the compound mechanism of action and the analogy with other natural products bearing a dihydro-pyrone moiety, we postulated that Plg-A could bind to the pironetin site of α-tubulin. A molecular docking analysis has been performed to compare binding of all 24 plagiochilins to α-tubulin and to establish structure-binding relationships. The identification of Plg-E and Plg-G as the best binders in the series pointed out to the importance of the C13-OH or C=O group for α-tubulin recognition. This observation led to the testing of the natural product ester plagiochilin A-15-yl n-octanoate and the corresponding alcohol (Plg-OH), both identified as robust α-tubulin binders. The study provides a rational to explain potentially the mechanism of action of Plg-A and to guide the design of new derivatives.

In the course of SARS-CoV-2 infection, the 3CL or nsp5 protease plays a pivotal role as the most important viral protease required for the maturation of viral proteins during host infection. Herein, we simulated for 500 ns 3CLproWT, 3CLproH41A, , 3CLproBeta, and 3CLproOmicron, in complex with the substrates nsp 4|5 and nsp 5|6. Our results show that mutations in the 3CLpro present in the SARS-CoV-2 variant of concerns (VOCs) did not lead to significant conformational changes or changes in substrate binding affinities. However, significantly high cleavage rates for the boundary between nsp4 and nsp5 were obtained for 3CLproBeta and 3CLproOmicron and may play a key role in the viral replication and virus fitness gain. Our molecular dynamics data suggest that the cleavage rate of nsp4|5 may be related to the increased amount of viral load observed for these VOCs, releasing more nsp4 than other non-structural proteins. Based on our hydrogen bonding analyses, we also discovered that Gly143 and Glu166 are key residues in substrate recognition, suggesting that these residues may be incorporated as pharmacophoric centers for Beta and Omicron variants in drug design. Our results suggest that Gly143 and Glu166 are essential residues to interact with Gln6 of the different substrates and, therefore, are potential broad-spectrum pharmacophoric centers of SARS-CoV-2 3CLpro.

Inositol poly- and pyrophosphates (InsPs and PP-InsPs) are central eukaryotic messengers. These very highly phosphorylated molecules can exist in two distinct conformations, a canonical one with five phosphoryl groups in equatorial positions, and a “flipped” axial conformation. Using 13C-labeled InsPs / PP-InsPs, the behavior of these molecules was investigated by 2D-NMR under solution conditions reminiscent of a cytosolic environment. Remarkably, the most highly phosphorylated messenger InsP8 readily adopts both conformations at physiological conditions. Environmental factors - such as pH, metal cation composition, and temperature - strongly influence the conformational equilibrium. Thermodynamic data revealed that the transition of InsP8 from the equatorial to the axial conformation is, in fact, an exothermic process. The speciation of InsPs and PP-InsPs also affects their interaction with protein binding partners; addition of Mg2+ decreased the binding constant Kd of InsP8 to an SPX protein domain. The results illustrate that PP-InsP speciation reacts very sensitively to solution conditions, suggesting it might act as an environment-dependent molecular switch.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have triggered a recent pandemic of respiratory disease and affected almost every country all over the world. A large amount of natural bioactive compounds is under clinical investigation for various diseas-es. Especially, marine natural compounds are gaining more attention in the new drug develop-ment process. The present study has aimed to identify potential marine-derived inhibitors against the target proteins of COVID-19 using a computational approach. Currently, 16 marine clinical-level compounds were selected for computational screening against the four SARS-CoV-2 main proteases. Computational screening resulted from the best drug candidates for each target based on the binding affinity scores and amino acid interactions. Among these, five marine-derived compounds namely Chrysophaentin A (-6.6 kcal/mol), Geodisterol sulfates (-6.6 kcal/mol), Hymenidin (-6.4 kcal/mol), Plinabulin (-6.4 kcal/mol) and Tetrodotoxin (-6.3 kcal/mol) expressed the minimized binding energy and molecular interactions such as covalent and hydrophobic interactions to the SARS CoV-2 Main Protease. Using Molecular dynamic stud-ies, the Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (ROG), and Hydrogen bonds (H-Bonds) values were calculated for SARS-CoV-2 Main Protease with Hymenidin docked complex. Additionally, in silico Druglikeness and pharmaco-kinetic property assessments of the compounds demonstrated favorable druggability. These re-sults suggested that marine natural compounds are capable of fighting SARS-CoV-2. Further, in vitro and in vivo studies need to be carried out to confirm their inhibitory potential.

The factors influencing hepatitis E virus (HEV) circulation remain largely unexplored. We investigated HEV seroprevalence in humans and the prevalence of infection in farm pigs and rabbits in different regions of the Russian Federation, as well as the genetic diversity and population dynamics of HEV. Anti-HEV IgG antibody detection rates in the general population increase significantly with age, from 1.5% in children and adolescents under 20 years old to 4.8% in adults aged between 20 and 59 years old, to 16.7% in people aged 60 years and older. HEV seroprevalence varies between regions, with the highest rate observed in Belgorod Region (16.4% compared with the national average of 4.6%), which also has the country’s highest pig population. When compared with the archival data, both increases and declines in HEV seroprevalence have been observed within the last 10 years, depending on the study region. Virus shedding has been detected in 19 out of the 21 pig farms surveyed. On one farm, circulation of the same viral strain for five years was documented. All human and animal strains belonged to the HEV-3 genotype, with its clade 2 sequences being predominant in pigs. Sequences from patients, pigs, and sewage from pig farms clustered together, suggesting a zoonotic infection in humans and possible environmental contamination. The HEV-3 population size predicted using SkyGrid reconstruction demonstrated exponential growth in the 1970s–1990s, with a subsequent decline followed by a short rise around the year 2010, the pattern being similar to the dynamics of the pig population in the country. The HEV-3 reproduction number (Re) predicted using Birth-Death Skyline analysis has fluctuated around 1 over the past 20 years in Russia, but is 10 times higher in Belgorod Region. In conclusion, HEV-3 circulation varies both geographically and temporally, even within a single country. The possible factors contributing to this variability are largely related to the circulation of the virus among farm pigs.

Non-invasive radionuclide molecular visualization of human epidermal growth factor receptor type 2 (HER2) can provide stratifcation of patients for HER2-targeting therapy. This method can also enable monitoring of the response to such therapies and thereby the treatment will be more personalized and efficient. Phase I clinical evaluation of two scaffold protein-based imaging probes, [99mTc]Tc-(HE)3-G3 and [99mTc]Tc-ADAPT6, demonstrated that their injections are safe, well-tolerated and cause low level of absorbed and equivalent doses. The goal of this preclinical study was to select the best probe for patients’ stratification and for response monitoring. Biodis-tribution of both tracers was compared in mice bearing SKOV-3 xenografts with high HER2 ex-pression and MDA-MB-468 xenografts with very low expression. Changes in accumulation of both probes in SKOV-3 tumors 24 h after injection of trastuzumab were evaluated. Both [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3 permitted high contrast imaging of HER2-expressing tumors and clear discrimination between tumors with high and low HER2 expression. However, [99mTc]Tc-ADAPT6 has better preconditions for higher sensitivity and specificity of stratification. On the other hand, [99mTc]Tc-(HE)3-G3 is capable to sense the decrease of HER2 expression on re-sponse to trastuzumab therapy only 24 h after injection of loading dose. This indicates that this tracer would be better for monitoring early response to such treatment. Results of this study should be considered in planning of further clinical development of HER2 imaging probes.

Background: While mankind is still dealing with the COVID-19 pandemic, on May 7, 2022, a case of monkeypox virus (MPXV) has been reported to the WHO. Monkeypox is a viral zoonotic disease with characteristics comparable to those seen in smallpox cases in the past. It has been a public health threat, particularly in Africa, but recently have been circulating the world, consequently, may become a global public health threat in a very short period. Thus, the current work was planned and then constructed a multi-epitope vaccine that can evoke an immunological response against MPXV utilizing cell surface-binding protein as a target in order to develop a novel vaccine that is both safe and almost free of side effects. Results: The proposed vaccine composed of 304 amino acids and was shown to be antigenic in Vaxijen server (0. 5311) and nonallergenic in AllerTop server. The 3D structure of the designed vaccine is predicted, refined and validated by various in silico tools to assess the stability of the vaccine. Moreover, solubility of the vaccine construct was found greater than the average solubility provided by protein-Sol server indicating the solubility of the vaccine construct. Moreover, the most promising epitopes bound to MHC I and MHC II alleles were found having good binding affinities with low energies ranging between ₋7.0 - ₋8.1kcal/mol. Conclusion: We conclude from our research that the cell surface-binding protein is one of the primary proteins involved in MPXV pathogenesis. The most promising epitopes were selected using a rigorous procedure and used for vaccine design. As a result, our study will aid in the development of appropriate therapeutics and prompt the development of future vaccines against MPXV, which could serve as an important milestone in the production of an antiviral vaccine against MPXV.

Turbulence is a fluid dynamic problem refractory to mathematical treatment. Examining a theoretical model of liquid water flowing in a cylinder at different Raleigh numbers, we propose a novel approach to elucidate the first stages of turbulent flows. The weakly bonded molecular assemblies of liquid water form a fluctuating branched polymer in which every micro-cluster displays different density. Against the common view of liquid water as an incompressible and continuous fluid, we suggest that the occurrence of transient local aggregates could be able to generate the vortices and eddies that are the hallmarks of turbulence. We quantify the local changes in velocity, diameter and density required to engender “obstacles” to the average flow. Then, we show how these microstructures, equipped with different Raleigh numbers and characterized by high percolation index, could generate boundary layers that contribute to micro-vortices production. We conclude that the genesis of turbulence cannot be assessed in terms of collective phenomena, rather is sustained, among many other factors, by the underrated microscopic inhomogeneities of fluids like liquid water.

In previous studies regarding the osseointegration of zirconia (ZrO2) implants, a lack of consistency was observed in the surface topographies of the ZrO2 and Ti samples because of the difficult processability of ZrO2 surfaces. To resolve this problem, we used the molecular precursor method (wet process), which is a surface-modifying technique that can easily change the surface chemistry without changing the surface topography. A roughened Ti surface was prepared using sandblasting (large-grit) and acid treatment. We were able to create ZrO2-coated Ti implants with the same topography as that of roughened Ti substrates using the molecular precursor method, which solution contained a Zr complex. The uniform presence of tetragonal Zr was confirmed, and the apparent zeta potential of the surface of the ZrO2-coated Ti implant was higher than that of Ti. In animal experiments, ZrO2-coated Ti implants showed an equivalent or higher bone-to-implant contact ratio compared to that of the non-coated implants inserted into the femur bone defects of the rats. ZrO2 with the same surface topography as that of roughened Ti exhibits a promotion of osteogenesis equivalent to or better than that of Ti in the early stages of bone formation.

Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can provide predictions, reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.

Uveal melanoma (UM) is characterized by relatively few, highly incident molecular alterations and their association with metastatic risk is deeply understood. Nevertheless, this knowledge has so far not led to innovate therapies for the successful treatment of UM metastases or for adjuvant therapy, leaving survival after diagnosis of metastatic UM almost unaltered in decades. The driver mutations of UM, mainly in the G-protein genes GNAQ and GNA11, activate the MAP-kinase pathway as well as the YAP/TAZ pathway. At present, there are no drugs that target the latter and this likely explains the failure of MEK-inhibitors. Immune checkpoint blockers, despite the game changing effect in cutaneous melanoma (CM) show only marginal effects in UM probably because of the low mutational burden of 0.5 per megabase and the unavailability of antibodies targeting the main immune checkpoint active in UM. The highly pro-tumorigenic microenvironment of UM also contributes to therapy resistance. However, T-cell redirection by a soluble T cell receptor that is fused to an anti-CD3 single-chain variable fragment, local, liver specific therapy, new immune checkpoint blockers and YAP/TAZ specific drugs give new hope to repeat the success of innovative therapy obtained for CM.

Agaricus bisporus is belonging to family agaricaceae, which is widely acceptable and mostly cultivated among the all mushrooms. It has great nutritional values and it is rich in proteins, vitamins, carbohydrates, fibers, minerals and amino acids. It is effective in antimicrobial, anticancer, antidiabetic, antihypercholesterolemic, antihypertensive, hepatoprotective and antioxidant activities. As it is effective in anticancer property, we check the effects of chemical constituents of Agaricus Bisporus on DNA damaging protein which results its activity PARP inhibiting or vise-versa. We choose the molecular docking technique to check the effects of different chemical constituents of Agaricus Bisporus on DNA damaging protein. For that different PARP inhibitory drugs taken as the standard. We perform the molecular docking of the chemical constituents of Agaricus Bisporus, using 4UND protein with the help of PyRx software and BIOVIA Discovery studio software. Along with that PARP inhibitor drugs also run against the same protein. The results of molecular docking shows the some of the constituents of Agaricus Bisporus has better binding affinity than the standard taken PARP inhibitor drugs. The ergosterol shows the better binding affinity than the niraparib and rucaparib on the same proteins. On other hands the naringenin, quercetin, anthocyanin, folate and myricetin shows the better results than the rucaparib. That means the ergosterol shows the better results as PARP inhibitor than the niraparib and rucaparib.

Abstract: In 2016, we conducted an entomological survey in a railway transect between Banfora and Ouagadougou, Burkina Faso. The aim was to evaluate the risk factors for arbovirus epidemics, including vector infection status, in areas representative of the country. Aedes aegypti mosquitoes were collected at larval stage from four study sites and reared until adult stage and kept in RNAlater for detection of arbovirus RNA. In the laboratory, the mosquito specimens were screened for dengue virus (DENV) and chikungunya virus (CHIKV) using one step real-time qRT-PCR. We detected one DENV-2 positive pool from Ouagadougou, giving a minimum infec-tion rate (MIR) of 16.67, and 6 CHIKV positive pools, giving a MIR of 66.67 from Ouagadougou, but also in Banfora and Boromo. The qRT-PCR is a useful tool for the surveillance of arboviruses of public health importance in Burkina Faso and may be incorporated into disease surveillance and control programs in Burkina Faso.

We present a critical analysis of the mechanism of reversible hydrogen evolution reaction based on thermodynamics of hydrogen processes considering atomic and ionic species as intermediates. Clear distinction between molecular hydrogen evolution/oxidation (H$_2$ER and H$_2$OR) and atomic hydrogen evolution/oxidation (HER and HOR) reactions is made. It is suggested that the main reaction describing reversible H$_2$ER and H$_2$OR in acidic and basic solutions is: $\ce{H3O^+} + 2e^- \xrightleftharpoons{\mathrm{({H}_{2}^{+}})_{ad}} \ce{H2} + \ce{OH^-}$, which proceeds via the formation of hydrogen molecular ion as intermediate and its potential is $E^{0}$ = 0.414~V (at the standard Hydrogen electrode SHE scale). We analyse experimentally reported data with models which provide \emph{quantitative} match (R.J.Kriek et al., Electrochem. Sci. Adv. e2100041 (2021)). The experimentally observed slope of $\lg(Current)$ vs. $Potential$ equal to $\approx 30$~mV/dec corroborates the presented model of H$_2$ER/H$_2$ER based on \ce{H2$^+$} as intermediate.

The [3+2] cycloaddition (32CA) reactions of strongly nucleophilic norbornadiene (NBD) with simplest diazoalkane (DAA) and three DAAs of increased electrophilicity have been studied within the Molecular Electron Density Theory (MEDT) at the MPWB1K/6-311G(d,p) computational level. These pmr-type 32CA reactions follow an asynchronous one-step mechanism with activation enthalpies ranging from 17.7 to 27.9 kcal·mol-1 in acetonitrile. The high exergonic character of these reactions makes them irreversible. The presence of electron-withdrawing (EW) substituents in the DAA increases the activation enthalpies, in complete agreement with the experimental slowing-down of the reactions, but contrary to the Conceptual DFT prediction. Despite the nucleophilic and electrophilic character of the reagents, the global electron density transfer at the TSs indicates rather non-polar 32CA reactions. The present MEDT study allows establishing that the depopulation of the NNC core in this series of DAAs with the increase of the EW character of the substituents present at the carbon center is responsible for the experimentally found deceleration.

Molecular mechanisms for N2 fixation (solar NH3) and CO2 conversion to C2+ products in enzymatic conversion (Nitrogenase), electrocatalysis, metal-complexes and plasma-catalysis are analysed and compared. It is evidenced that differently from what present in thermal and plasma-catalysis, the electrocatalysis path requires not only the direct coordination and hydrogenation of undissociated N2 molecule, but to realize a series of features present in the Nitrogenase mechanism. There is the need of i) a multi-electron and -proton simultaneous transfer, not as sequential steps, ii) forming bridging metal hydride species, iii) generate intermediates stabilized by bridging multiple metal atoms, iv) have the capability of the same sites to be effective both in N2 fixation and in COx reduction to C2+ products. Only iron oxide/hydroxide stabilized at defective sites of nanocarbons was found to have these features. This comparison of the molecular mechanisms in solar NH3 production and relations with CO2 reduction is proposed to be a source of inspiration to develop the next generation electrocatalysts to address the challenging transition to a future sustainable energy and chemistry beyond fossil fuels.

Zinc finger proteins (ZFP) play important roles in cellular processes. The DNA binding region of ZFP consists of 3 zinc finger DNA binding domains connected by amino acid linkers, the sequence TGQKP connects ZF1 and ZF2, and TGEKP connects ZF2 with ZF3. Linkers act to tune the zinc finger protein in the right position to bind its DNA target, the type of amino acid residues and length of linkers reflect on ZF1-ZF2-ZF3 interactions and contribute to the search and recognition process of ZF protein to its DNA target. Linker mutations and the affinity of the resulting mutants to specific and nonspecific DNA targets were studied by MD simulations and MM_GB(PB)SA. The affinity of mutants to DNA varied with type and position of amino acid residue. Mutation of K in TGQKP resulted in loss in affinity due to the loss of positive K interaction with phosphates, mutation of G showed loss in affinity to DNA, WT protein and all linker mutants showed loss in affinity to a nonspecific DNA target, this finding confirms previous reports which interpreted this loss in affinity as due to ZF1 having an anchoring role, and ZF3 playing an explorer role in the binding mechanism. The change in ZFP-DNA affinity with linker mutations is discussed in view of protein structure and role of linker residues in binding.

The world faces two seemingly unrelated challenges—a shortfall in the STEM workforce and increasing antibiotic resistance among bacterial pathogens. We address these two challenges with Tiny Earth, an undergraduate research course that excites students about science and creates a pipeline for antibiotic discovery.

The outbreak of COVID-19, the disease caused by SARS-CoV-2, continues to affect millions of people around the world. The absence of a globally distributed effective treatment makes the exploration of new mechanisms of action a key step to address this situation. Stabilization of non-native Protein-Protein Interactions (PPIs) of the nucleocapsid protein of MERS-CoV has been reported as a valid strategy to inhibit viral replication. In this study, the applicability of this unexplored mechanism of action against SARS-CoV-2 is analyzed. During our research, we were able to find three inducible interfaces of SARS-CoV-2 N protein NTD, compare them to the previously reported MERS-CoV stabilized dimers, and identify those residues that are responsible for their formation. A drug discovery protocol implemented consisting of docking, molecular dynamics and MM-GBSA enabled us to find several compounds that might be able to exploit this mechanism of action. In addition, a common catechin skeleton was found among many of these molecules, which might be useful for further drug design. We consider that our findings could motivate future research in the fields of drug discovery and design towards the exploitation of this previously unexplored mechanism of action against COVID-19.

Evaporation studies of water using classical molecular dynamics simulations are largely limited due to its high computational expense. We aim at addressing the computational issues by developing a coarse grain model for evaporation of water on solid surfaces by combining four water molecules into a single bead. Most commonly used mono atomic pair potentials like Lennard Jones, Morse, Mie and three body potential like Stillinger-Weber are optimized using a combination of Genetic algorithm and Nelder-Mead algorithm. Among them, Stillinger-Weber based model shows excellent agreement of density and Enthalpy of vaporization with experimental results for a wide range of temperatures. Further, the new water model is used to simulate contact angle of water and thin film evaporation from surfaces with different wettabilities.

Metabolic enzymes are often targeted for drug development programs of metabolic diseases such as diabetes and its complications. Many secondary metabolites isolated from natural products have shown therapeutic action against these enzymes. However, some commercially available synthetic drugs have shown unfriendly impacts with various side effects. Thus, this research has focused on a comprehensive study of secondary metabolites showing better inhibitory activities towards metabolic enzymes such as α-amylase, α-glucosidase, aldose reductase, and lipase. Further receptor-based virtual screening was performed against the various secondary metabolites database designed in-silico. Using Gold combined with subsequent post-docking analyses, the score was obtained as methyl xestospongic ester (Gold score 65.83), 2,″4″-O-diacetylquercitrin (Gold score 65.15), kaempferol-3-O-neohesperidoside (Gold score 53.37) and isosalvianolic acid C methyl ester (Gold score 53.44) for lipase, aldol reductase, α-amylase, and α-glucosidase, respectively. Besides, vitexin and isovitexin for α-amylase; N-trans-Caffeoyl-tyramin for α-glucosidase; purpurolide F and schaftoside for lipase; acteoside and orientin for aldose reductase could be potential drugs for respective enzymes based on in-silico analyses, supported by experimental IC₅₀ values reported. They could bind to the competitive sites of the various targets of metabolic enzymes, and finally, toxicity analysis using ProTox-II was also performed.

Never in mitosis gene A-related kinase 2 (NEK2) a member of serine-threonine kinase protein mainly involved in the cell cycle process. Clinical studies revealed NEK2 overexpression in various tumour types, also NEK2 was reported for their association with genetic abnormalities like mitotic machinery deregulation and chromosomal instability. Besides NEK2 plays a key role in maintaining the transformed phenotype of cancer cells and chemo-resistance of several tumour types. Thus, NEK2 transcriptional profile is important for diagnosis, treatment, and prognosis stages of cancer studies. Screening of novel NEK2 inhibitor would be beneficial in developing the specific lead molecules. Our studies involved NEK2 transcriptional profile search, screening of druggable cavities in NEK2, Drug likeliness of mangrove derived naphthoquinone derivatives avicennoneA , avicennoneB , avicennoneC , avicennoneD , avicenoneE , avicennone F , and avicennone G , avicequinone A, stenocarpoquinone B , avicequinone C , avicenol A , avicenol C,brugine, apigenin, chrysin and molecular docking studies to assess MNC compounds binding efficacy towards NEK2. Mangrove derived compounds conferred the intermolecular hydrogen bond, Pi-alkyl,pi-cation interactions with NEK2 kinase domain region residues Tyr 19, Lys 37, Arg 164, Lys174. Nearly 200 kinase proteins contained this promising Cys 22 residue as its positioned in the catalytic site like NEK family proteins. Avicenna A, Avicennone G, Chrysin and Brugine formed the irreversible covalent binding with NEK2 through Cys 22, thus they can be considered as potential kinase inhibitors with the limited off-target response. But these MNC compounds need to be tested further in invitro and invivo studies to propose as potent NEK2 inhibitors.

Introduction: Coronaviruses are zoonotic viruses that include human epidemic pathogens such as the Middle East Respiratory Syndrome virus (MERS-CoV), and the Severe Acute Respiratory Syndrome virus (SARS-CoV), among others (e.g., COVID-19, the recently emerging coronavirus disease). The role of animals as potential reservoirs for such pathogens remains an unanswered question. No systematic reviews have been published on this topic to date. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess MERS-CoV and SARS-CoV infection in animals and its diagnosis by serological and molecular tests. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 6,493articles were retrieved (1960-2019). After screening by abstract/title, 50 articles were selected for full-text assessment. Of them, 42 were finally included for qualitative and quantitative analyses. From a total of 34 studies (n=20,896 animals), the pool prevalence by RT-PCR for MERS-CoV was 7.2% (95%CI 5.6-8.7%), with 97.3% occurring in camels, in which pool prevalence was 10.3% (95%CI 8.3-12.3). Qatar was the country with the highest MERS-CoV RT-PCR pool prevalence, 32.6% (95%CI 4.8-60.4%). From 5 studies and 2,618 animals, for SARS-CoV, the RT-PCR pool prevalence was 2.3% (95%CI 1.3-3.3). Of those, 38.35% were reported on bats, in which the pool prevalence was 14.1% (95%CI0.0-44.6%). Discussion: A considerable proportion of infected animals tested positive, particularly by nucleic acid amplification tests (NAAT). This essential condition highlights the relevance of individual animals as reservoirs of MERS-CoV and SARS-CoV. In this meta-analysis, camels and bats were found to be positive by RT-PCR in over 10% of the cases for both; thus, suggesting their relevance in the maintenance of wild zoonotic transmission.

Bitter gourd is an important vegetable of the family Cucurbitaceae, cultivated mainly in humid and subtropical Asia. Bitter gourd is vegetable with immense health benefits due to the presence of medicinal compounds such as charatin, vicine, and polypeptide-p, which play an essential role in lessening the blood glucose levels. Moreover, bitter gourd fruits are particularly rich in vitamin C, minerals, and carotenes. Here, an effort has been made to critically evaluate the extent of achievements during the enhancement and enactment of bitter gourd breeding programs with the use of latest technologies. Broadening of the genetic base of cultivated bitter groud varieties as a result of enrichment of the existing resources by using the wild species in the breeding programs. Practical seed production technological know-how along with the use of the MS system (male sterility)/chemical-induced sterility procedure is nonetheless vital to cope up with the market demands. Superior yielding bitter gourd hybrids combining early maturity and resistance to biotic and abiotic stresses are regularly needed to cope up with the challenge of bitter gourd production.

Around the World, the number of compound databases of natural products in the public domain is rising. This is in line with the increasing synergistic combination of natural product research and chemoinformatics. Towards this global endeavor, countries in Latin America are assembling, curating, and analyzing the contents and diversity of natural products available in their geographical regions. In this manuscript we collect and analyze the efforts that countries in Latin America have made so far to build natural product databases. We further encourage the scientific community in particular in Latin America, to continue their efforts to building quality natural product databases and, whenever possible, to make them publicly accessible. It is proposed that all compound collections could be assembled into a unified resource called LANaPD: Latin America Natural Products Database. Opportunities and challenges to build, distribute, and maintain LANaPD are also discussed

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the world health organization declared it pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. In this urgency situation, development of SARS-CoV-2 based vaccines is immediately required. Immunoinformatic and molecular modelling are generally used time-efficient methods to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines is proved to be a promising immunization strategy against viruses and pathogens, which induce more comprehensive protective immunity. The current study demonstrated a comprehensive in-silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in-silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in E. Coli. Despite this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can present to be a better prophylactic solution against COVID-19.

Malignant gliomas are heterogeneous neoplasms. Glioma stem-like cells (GSCs) are undifferentiated and self-renewing cells that develop and maintain these tumors. These cells are the main population that resist current therapies. Genomic and epigenomic analyses has identified various molecular subtypes. Bone morphogenetic protein 4 (BMP4) reduces the number of GSCs through differentiation and induction of apoptosis, thus increasing therapeutic sensitivity. However, the short half-life of BMP4 impedes its clinical application. We have previously reviewed BMP4 signaling in central nervous system development and glioma tumorigenesis and its’ potential as a treatment target in human gliomas. Recent advances in understanding both adult and pediatric malignant gliomas highlight critical roles of BMP4 signaling pathways in the regulation of tumor biology, and indicate its’ potential as a therapeutic molecule. Furthermore, significant progress has been made on synthesizing BMP4 biocompatible delivery materials, which can bind to and markedly extend BMP4 half-life. Here, we review current research associated with BMP4 in brain tumors, especially in pediatric malignant gliomas. We also summarize BMP4 delivery strategies, with a focus on biocompatible BMP4 binding peptide amphiphile nanostructures as promising novel delivery platforms for treatment of these devastating tumors.

I demonstrate that the ionization energy (IE) and the electron affinity (EA) of organic molecular crystals can be predicted from first-principles. Here, I describe the induced electronic polarization and the electrostatic effects upon crystalline IE and EA. I also demonstrate that the electronic polarization mainly originates from the screened coulomb interaction inside the crystalline bulk phase, and that the electrostatic contribution to IE and EA crucially depends on the orientation of the molecule at the surface. The former is well described by the GW approximation, while the latter is reasonably estimated by the difference in frontier orbital energy between the gas phase and the surface at the level of a generalized gradient approximation to the density functional theory. The present methodology enables to demonstrate the impact of the electrostatic effect upon the energy level of the injected charge at a multi-monolayer surface of an organic semiconductor thin film.

Excitotoxicity related to the dysfunction of the N-methyl-d-aspartate receptor (NMDAR) has been indicated to play an integral role in the pathophysiology of multiple disease states, including neurodegenerative disorders such as Parkinson’s disease. There is a notable gap in the market for novel NMDAR antagonists, however current methods to analyze potential antagonists rely on indirect measurements of calcium flux and hazardous radioligand binding assays. Recently, a fluorescent NMDAR ligand, N-adamantan-1-yl-dimethylamino-1-naphthalenesulfonic acid, known as AM-DAN was developed by our group. Additional studies on this ligand is necessary to evaluate its potential as a biological tool in NMDAR research. Therefore, this study was aimed at conducting structural analyses, fluorescence experiments, high-accuracy NMDAR molecular modelling and NMDAR phencyclidine (PCP) site competition binding studies using AM-DAN. Results revealed that AM-DAN has appropriate structural properties, significant fluorescent ability in various solvents and is able to bind selectively and compete for the PCP-binding site of the NMDAR. Therefore, AM-DAN holds promise as a novel fluorescent ligand to measure the affinity of prospective drugs binding at the NMDAR PCP-site and may circumvent the use of radioligands.

Molecular dynamics(MD) simulations are carried out to characterize the mechanicalproperties and failure behavior of van der Waals heterostructures composed ofgraphene and hexagonal boron nitride(hBN) single layer sheets. The graphene–hBNand hBN–graphene–hBN heterostructures simulations are carried out under tensileand shear deformation. Accordingly, stress versus strain curves of each systemare plotted and various properties of heterostructures, namely elastic modulusand shear modulus as well as failure stress and failure strain, are evaluatedand compared with one another as well as with the pristine graphene and hBNsheets. Subsequently, the failure mechanism/characterization of each sheet in theheterostructures is described. Alternatively, the elastic and shear modulus of eachheterostructure are computed by means of rule of mixture(ROM) which are in goodagreement with results that are obtained from MD simulations.

The tsscds method, recently developed in our group, discovers chemical reaction mechanisms with minimal human intervention. It employs accelerated molecular dynamics, spectral graph theory, statistical rate theory and stochastic simulations to uncover chemical reaction paths and to solve the kinetics at the experimental conditions. In the present review, its application to solve mechanistic/kinetics problems in different research areas will be presented. Examples will be given of reactions involved in photodissociation dynamics, mass spectrometry, combustion chemistry and organometallic catalysis. Some planned improvements will also be described.

Binderless zeolite macrostructures in the form of ZK-4 microspheres were prepared using anion exchange resin beads as shape directing macrotemplates. The particles were synthesized under hydrothermal conditions at different temperatures and treatment times. The influence of the different synthesis parameters was investigated by X-ray diffraction, scanning electron microscopy, fluorescence X, nitrogen adsorption measurements and ²⁹Si solid NMR. Fully crystalline spheres similar in size and shape to the original resin beads were obtained by a hydrothermal treatment at the highest temperatures (150 - 180 °C) for a short treatment time of 24 h. The synthesized microspheres showed to be promising in the molecular decontamination of Volatile Organic Compounds (VOCs).

This work examines atomic and molecular signatures in laser-induced plasma in standard ambient temperature and pressure environments, including background contributions to the spectra that depend on the laser pulse-width. Investigations include solids, gases, and nano-particles. Abel inversions of measured line-of-sight data reveal insight into the radial plasma distribution. For nominal 6 nanosecond laser pulses and for pulse-energies in the range of 100 to 800 milli-Joules, expansion dynamics and turbulence due to shock phenomena are elucidated to address local equilibrium details that are frequently assumed in spatially averaged emission spectroscopy. Chemical equilibrium computations reveal temperature dependence of selected plasma species. Specific interests include atomic hydrogen (H) and cyanide (CN). The atomic H spectra, collected following optical breakdown in ultra-high-pure hydrogen and 9:1 mixtures of ultra-pure hydrogen and nitrogen gases, indicate spherical shell structures and isentropic expansion of the plasma kernel over and above the usual shockwave. The recombination radiation of CN emanates within the first 100 nanoseconds for laser-induced breakdown in a 1:1 CO₂:N₂ gas mixture when using nanosecond laser pulses to create the micro-plasma. The micro-plasma is generated using 1064 nm, 150 mJ, 6 ns Q-switched Nd:YAG laser radiation. Measurements of the optical emission spectra utilize a 0.64 m Czerny-Turner type spectrometer and an intensified charge-coupled device.

Structural DNA nanotechnology provides an excellent foundation for diverse nanoscale shapes that can be used in various bioapplications and materials research. From all existing DNA assembly techniques, DNA origami has proven to be the most robust one for creating custom nanoshapes. Since its invention in 2006, building from the bottom up using DNA has drastically advanced, and therefore, more and more complex DNA-based systems have become accessible. So far, vast majority of the demonstrated DNA origami frameworks are static by nature, but interestingly, there also exist dynamic DNA origami devices that are increasingly coming into view. In this review, we discuss DNA origami nanostructures that perform controlled translational or rotational movement triggered by predefined DNA strands, various molecular interactions and/or other external stimuli such as light, pH, temperature and electromagnetic fields. The rapid evolution of such dynamic DNA origami tools will undoubtedly have a significant impact on molecular scale precision measurements, targeted drug delivery and diagnostics, but they can also play a role in development of optical/plasmonic sensors, nanophotonic devices and nanorobotics for numerous different tasks.

We performed for the first time to our knowledge fully ab initio molecular dynamics simulations of additive tribochemistry in boundary lubrication conditions. We consider an organophosphourus additive that has been experimentally shown to reduce friction in steel-on-steel sliding contacts thanks to the tribologically-induced formation of an iron phosphide tribofilm. The simulations allow us to observe in real time the molecular dissociation at the sliding iron interface under pressure and to understand the mechanism of iron phosphide formation. We discuss the role played by the mechanical stress by comparing the activation times for molecular dissociation observed in the tribological simulations at different applied loads with that expected on the basis of the dissociation barrier.

Effect of abrasive shape on the three-body abrasion behaviors of monocrystalline silicon was investigated by Molecular dynamics modelling. The axial ratio of abrasive particle was varied from 1.00, i.e., a complete sphere, to 0.40 to mimic abrasive shape. The particle’s movement turns toward sliding from rolling when the axial ratio becomes less than a critical value 0.46. In the abrasion process, the friction force and normal force showed an approximately sinusoid-like fluctuation for the rolling ellipsoidal particles, while the front cutting of particle caused that friction force increased and became larger than normal force for sliding particles. The phase transformation process was tracked under different particle’ movement patterns. The Si-II and Bct5 phase producing in loading process can partially transform to Si-III/Si-XII phase and backtrack to original crystal silicon under pressure release, which also occurred in the abrasion process. The secondary phase transformation showed difference for particles’ rolling and sliding movements after three-body abrasion. The rolling of particle induced the periodical and inhomogeneous deformation of substrates, while the sliding benefited producing high-quality surface in CMP process. This study aiming to construct more precise model to understand the wear mechanism benefits evaluating the MEMS wear and CMP process of crystal materials.

The mesoporous heteroatom molecular sieve MCM-41 bulk crystals with the crystalline phase were synthesized via a one-step hydrothermal method using an ionic complex as template. The ionic complex template was formed by interaction between cetyltrimethylammonium ions and metal complex ion [M (EDTA)]2- (M=Co or Ni ). The materials were characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, N2 adsorption–desorption isotherms, and X-ray absorption fine structure spectroscopy. The results showed that the materials possess a highly ordered mesoporous structure with the crystalline phase and possess high uniform ordered arrangement channels. The structure is in the vertical cross directions with a crystalline size of about 12 µm and high specific surface areas. The metal atoms were incorporated into the zeolite frameworks in the form of octahedral coordinate and have a uniform distribution in the materials. The amount of metal complexes formed by metal ion and EDTA is an essential factor for the formation of the vertical cross structure. Comparing to Si-MCM-41, the samples exhibited better conversion, higher selectivity for cumene cracking.

Diabetes mellitus is the fifth deadliest disease in the developing countries. Even with all the research and new drugs available, combating diabetes is still challenging. There are successes in finding new cost effective drugs without side effects, even if not perfect. In our investigation we studied binding mechanism of secondary metabolite of T. chebula in silico. It was observed that three compounds out of 16 have a higher binding affinity for the target proteins. Ellagic acid showed highest binding affinity with alpha amylase, beta glucosidase and alpha glucosidase with lesser binding energies -4.5kcal/mol, -5.36kcal/mol and -4.48kcal/mol respectively. Arjungenin has lesser binding energy of 4.77 kcal/mol with glucokinase while luteoline has binding energy of -7.25kcal/mol for enzyme glycogen synthase kinase. These entire compounds interacted with non-covalent interaction. Petroleum ether extract showed the significant alpha amylase inhibitory activity i.e. 51.22% as compared to standard drug (65.99%).TLC analysis revealed the presence of total 9 compounds in different plant extracts one of them might be a lead compound which could be further exploited for the development of novel safer and potent antidiabetic drug.

The new coronavirus SARS-CoV-2 is the cause of the COVID-19 pandemic, which has created an incomparable global health problem. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. The review begins by elucidating the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Employing homology modeling, a tertiary structure model of PLpro is constructed, laying the groundwork for subsequent investigations. To expedite the search for potential therapeutic candidates, the study harnesses computational methodologies. Molecular docking techniques are employed to explore binding sites for antiviral drugs within the catalytic region of PLpro. This computational approach not only aids in drug development but also provides crucial preliminary data before experimental research commences. The stability of drug-PLpro complexes is assessed through comprehensive all-atom molecular dynamics (MD) simulations, affording dynamic insights into drug-PLpro interactions. By evaluating binding energy estimates from MD simulations, stable drug-PLpro complexes with potential antiviral properties are identified. However, it is emphasized that experimental validation is imperative to confirm these computational findings, necessitating in vitro and in vivo tests to assess safety and efficacy. This pivotal stage bridges the computational realm with real-world clinical applications. The review emphasizes the imperative need for enhancements in the existing PLpro-targeting drugs currently on the market. Their actions are insufficient for clinical use and necessitate thorough characterization and improvement. The Supervised Molecular Dynamics (SuMD) simulation technique reveals critical information about drug unbinding pathways, shedding light on opportunities for refinement. In addition to optimizing existing drugs, the investigation of sub-structurally similar molecules emerges as a promising avenue for drug development. In conclusion, the review underscores the pivotal role of targeting SARS-CoV-2 PLpro in the ongoing battle against COVID-19. By integrating molecular dynamics simulations, structural modeling, and computational insights, a robust foundation is established for identifying promising antiviral drug candidates. The continual need for improvement in existing drugs and the exploration of novel compounds remain paramount in the global effort to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, illustrating the interdisciplinary synergy crucial to this endeavor.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

Background Obesity is a major healthcare challenge worldwide. Recently, glucagon-like peptide-1 receptor agonists (GLP-1RAs) have emerged as a promising pharmacological option for managing type 2 diabetes mellitus (T2DM) and obesity in diabetic patients. Objective This systematic review aims to evaluate the efficacy and safety of GLP-1RAs in nondiabetic patients. Methods We systematically reviewed 2356 published articles from the past ten years (2013 to November 22, 2023). After rigorous screening, 11 articles were selected for an in-depth review. The analysis focused on the efficacy and safety of GLP-1RAs in nondiabetic patients, considering various baseline characteristics and subgroups. Results The review found that GLP-1RAs, including exenatide, liraglutide, semaglutide, and the dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist (GIP/GLP-1RA) tirzepatide, significantly promoted weight loss in obese/overweight nondiabetic patients. Additionally, these agents positively affected cardiovascular risk factors such as blood pressure, glycemic control, nephropathy, lipid levels, serum insulin levels, and C-reactive protein (CRP) profiles. However, GLP-1RAs, including tirzepatide, were associated with gastrointestinal adverse drug reactions such as nausea, diarrhea, vomiting, and constipation. These adverse events were typically transient, mild-to-moderate in severity, and subsided over time. Conclusion GLP-1RAs are effective and relatively safe for weight management and improving cardiovascular risk factors in nondiabetic patients, despite the occurrence of some gastrointestinal side effects. Further research is warranted to optimize the use of these agents in nondiabetic populations.

To address the issue of traditional static evaluation models being unable to comprehensively analyse the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and Entropy Weight Method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analysed ultra-supercritical coal-fired units, taking into account time weight. This allowed us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the dynamic comprehensive evaluation model, which uses an improved CRITIC and EWM, has significant advantages in improving evaluation accuracy, weight-balanced distribution, and generality. Provides more accurate, reasonable, and reliable evaluation results for practical decision making.

Climate change-induced temperature fluctuations pose a significant threat to crop production, particularly in the Southern Hemisphere. This study investigates the transcriptome and physiological responses of rapeseed to post-flowering temperature increases, providing valuable insights into the molecular mechanisms underlying rapeseed tolerance to heat stress. Two rapeseed genotypes, Lumen and Solar, were assessed under control and heat stress conditions in field experiments conducted in Valdivia, Chile. Results showed that seed yield and seed number were negatively affected by heat stress, with genotype-specific responses. Lumen exhibited a 9.3% average seed yield reduction, while Solar showed a 28.7% reduction. RNA-seq analysis of siliques and seeds revealed tissue-specific responses to heat stress, with siliques being more sensitive to temperature stress. Hierarchical clustering analysis identified distinct gene clusters reflecting different aspects of heat stress adaptation in siliques, with a role for protein folding in maintaining silique development and seed quality under high temperature conditions. In seeds, three distinct patterns of heat-responsive gene expression were observed, with genes involved in protein folding and response to heat showing genotype-specific expression. Gene coexpression network analysis revealed major modules for rapeseed yield and quality, as well as the trade-off between seed number and seed weight. Overall, this study contributes to understanding the molecular mechanisms underlying rapeseed tolerance to heat stress and can inform crop improvement strategies targeting yield optimization under changing environmental conditions.

This study investigated the effects of whole-body circuit training using a weighted vest on plasma resistin, cardiovascular disease risk factors, and cardiorespiratory fitness for normal-weight obese women. In this study, thirty- six normal-weight obese women were divided into three groups: Weighted Vest Circuit Training (WVCT) (n = 12), Body Weight Circuit Training (BWCT) (n = 12), and Control (CON) (n = 12). Whole-body circuit training was conducted three times a week for eight weeks to compare and analyze plasma resistin, cardiovascular disease risk factors, and cardiorespiratory fitness before and after training. Although there was no significant baseline difference between the groups regarding skeletal muscle mass, it significantly increased for the WVCT group after eight weeks. percent body fat significantly decreased for the WVCT and BWCT groups, and there was a significant difference when the percent body fat of these two groups were compared to that of the control group. Moreover, the WVCT and BWCT groups displayed a significant decrease in plasma resistin, showing a significant difference from the CON group. The WVCT and BWCT group showed a significant decrease in plasma IL-6, whereas the CON group showed a significant increase. VO2max significantly increased post-training compared to before in the BWCT group and the WVCT group, and the WVCT group showed differences between groups compared to the BWCT group and the CON group. None of the three groups displayed significant changes in plasma hs-CRP, yet there was a significant difference between the hs-CRPs of the WVCT and BWCT group and that of the CON group. In conclusion, whole-body circuit training using a weighted vest efficiently improves body composition, plasma resistin, and cardiopulmonary fitness, reducing cardiovascular disease risk factors in normal-weight obese women.

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets.

Long-chain omega-3 fatty acid status during pregnancy may influence newborn anthropometry and duration of gestation. Evidence from high-quality trials from LMICs is limited. We conducted a double-blind, randomized, placebo-controlled trial among 957 pregnant women (singleton gestation, 14-20 weeks’ gestation at enrollment) in India to test the effectiveness of 400 mg/d algal docosahexaenoic acid (DHA) compared to placebo provided from enrollment through delivery. Among 3379 women who were screened, 1171 were found eligible; 957 enrolled and were randomized. The intervention was two microencapsulated algal DHA (200 X 2= 400 mg/d) or two microencapsulated soy and corn oil placebo tablets to be consumed daily from enrollment (20 weeks) through delivery. The primary outcome was newborn anthropometry (birth weight, length, head circumference). Secondary outcomes were gestational age and 1 and 5 min Appearance, Pulse, Grimace, Activity, and Respiration (APGAR) score. The groups (DHA; n=478 and placebo; n=479) were well balanced at baseline. There were 902 live births. Compliance with the intervention was similar across groups (DHA: 88.5%; placebo: 87.1%). There were no significant differences between DHA and placebo group for birth weight (2750.6 ± 421.5 vs. 2768.2 ± 436.6 g, p=0.54), length (47.3 ± 2.0 vs. 47.5 ±2.0 cm, p=0.13) or head circumference (33.7 ± 1.4 vs 33.8 ± 1.4 cm, p=0.15). The mean gestational age at delivery was similar between groups (DHA: 38.8 ± 1.7 placebo: 38.8 ± 1.7 wk, p= 0.54) as were APGAR scores at 1 and 5 min. Supplementing mothers through pregnancy with 400mg/d DHA did not impact the offspring birthweight, length or head circumference.

Planktonic foraminiferal biomineralization intensity, reflected by their shell calcite mass, affects global carbonate deposition and is known to follow the climate cycles by being increased during glacial stages and decreased during interglacial ones. Here we measure the dissolution state and the mass of the shells of the planktonic foraminifera species Globigerina bulloides from a Tropical Eastern North Atlantic site over the last two glacial-interglacial climatic transitions and we report no major changes in plankton calcite production with the atmospheric pCO2 variations. We attribute this consistency in foraminifera calcification to the climatic and hydrological stability of the tropical regions. We however recorded increased shell masses midway through the penultimate deglaciation (Termination II). In order to elucidate the cause of the increased shell weights we performed δ18O, Mg/Ca and μCT measurements on the same shells from a number of samples surrounding this event. We find that shells of increased mass are internally contaminated by sediment infilling and that shell weights are responding to local hydrographic changes.

Single particle tracking is a powerful technique to investigate the motion of molecules or particles. Here we review methods for analyzing the reconstructed trajectories, step needed for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean square displacement (MSD), highlighting sometimes-neglected factors potentially affecting results accuracy. We then report methods that exploit distributions of parameters other than displacements, e.g. angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in MSD analysis. Hidden Markov Models are also used for this purpose, and these allow identifying different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field: trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on combined different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

The low coefficient of thermal expansion of Invar 36 represents a significant consideration in light of its potential effects, particularly in industrial applications where thermal stability is of paramount importance. In light of this, a three-step heat treatment was employed, to reduce the thermal expansion coefficient, and enhance the thermal dimensional stability. The ingots produced by vacuum induction melting were subjected to a warm rolling process at 900 °C, followed by a three-step heat treatment consisting of water quenching at 850 °C, tempering at 350 °C with a holding time of 1 hour, and aging at 100 °C for 24 hours. This process enabled the coefficient of thermal expansion to remain almost unchanged, exhibiting values between 0.5 and 0.6 x10-6/°C up to 150 °C. Following the heat treatment, the total elongation increased up to 40% as a natural consequence of the reduction of residual stresses, while a slight decrease in tensile strength was observed. The implementation of a three-step heat treatment process has facilitated an enhancement of the soft magnetic property, which has exhibited a decline in coercivity and an increase in saturation magnetization. As a consequence, three-step heat-treated invar 36 alloys are emerging as a potential candidate for utilization in the aerospace and precision electronics industries, given their satisfactory physical and mechanical characteristics.

Recent advancements highlight the utilization of vegetable oils as additives in polymeric materials, particularly for replacing conventional plasticizers. Buriti oil (BO), extracted from the Amazon's Mauritia flexuosa palm tree fruit, boasts an impressive profile of vitamins, minerals, proteins, carotenoids, and tocopherol. This study investigates the impact of incorporating buriti oil as a plasticizer in linear low-density polyethylene (LLDPE) matrices. The aim of this research was to evaluate how buriti oil, a bioactive compound, influences the thermal and rheological properties of LLDPE. Compositions of buriti oil\LLDPE were prepared via melt intercalation techniques, and the resulting materials were characterized through Thermogravimetric Analysis (TGA), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), mechanical property testing, and contact angle measurement. The addition of buriti oil was found to act as a processing aid and plasticizer, enhancing the fluidity of LLDPE polymer chains. TGA revealed distinct thermal stabilities for buriti oil/LLDPE under different degradation conditions Notably, buriti oil exhibited an initial weight loss temperature at 402°C, whereas LLDPE at 466.4°C. This indicated a minor reduction in the thermal stability of buriti oil/LLDPE compositions. The thermal stability, as observed through DSC displayed a nuanced response to the oil's incorporation, suggesting a complex interaction between the oil and polymer matrix. Detailed mechanical testing indicated a marked increase in tensile strength and elongation at break, especially at optimal concentrations of buriti oil. SEM analysis showcased a more uniform and less brittle microstructure, correlating with the enhanced mechanical properties. Contact angle measurements revealed a notable shift in surface hydrophobicity, indicating a change in the surface chemistry. This study demonstrates that buriti oil can positively influence the processability and thermal properties of LLDPE contributing to expand its potential applications as an effective plasticizer.

Background/Objectives: The burden of hospital-acquired infections (HAIs) is particularly sub-stantial in low- and middle-income countries (LMICs). However, a comprehensive understanding of their prevalence in these regions is lacking. This systematic review aimed to evaluate the prevalence of HAIs in LMICs. Methods: Major databases, including Scopus, PubMed, and Web of Science, were thoroughly searched for published studies between January 1, 2000, and July 15, 2024. The PRISMA guidelines were followed for a comprehensive and systematic approach. The pooled prevalence of HAIs was estimated using a random-effects model and a 95% confidence interval (CI). Results: The literature search identified 87 studies reporting HAI prevalence in LMICs. The overall prevalence of HAIs across LMICs was 22% (95% CI: 17-28), with notable regional variations. The South-East Asian Region (SEAR) presented the highest prevalence at 37% (95% CI: 13-62), followed by the African Region at 25% (95% CI: 16-33). The European Region (EUR) had the lowest preva-lence, at 14% (95% CI: 5-23). In terms of income level, low-income countries had the highest prevalence at 37% (95% CI: 23-52), followed by lower-middle income at 22% (15-30) and up-per-middle income at 13% (95% CI: 6-20). Surgical site infections (SSIs) had the highest prevalence among infection types at 27% (95% CI: 23-31), followed by pneumonia at 23% (95% CI: 18-28) and urinary tract infections (UTIs) at 22% (95% CI: 19-26). Gastrointestinal infections (GIs) were less prevalent at 6% (95% CI: 3-9). Conclusions: This systematic review underscores the high prevalence of HAIs in most LMICs, with variations based on region and income level, emphasizing the need to facilitate the development of targeted prevention and control strategies to mitigate the impact of this critical public health issue, especially in resource-limited settings.

Low-Code Development Platforms (LCDPs) empower users to create and deploy custom software with little to no programming. These platforms streamline development, offering benefits like faster time-to-market, reduced technical barriers, and broader participation in software creation, even for those without traditional coding skills. This study explores the application of LCDPs in Precision Agriculture (PA) through a systematic literature review (SLR). By analyzing the general characteristics and challenges of LCDPs, alongside insights from existing PA research, we assess their feasibility and potential impact in agricultural contexts. Our findings suggest that LCDPs can enable farmers and agricultural professionals to create tailored applications for real-time monitoring, data analysis, and automation, enhancing farming efficiency. However, challenges such as scalability, extensibility, data security, and integration with complex IoT systems must be addressed to fully realize the benefits of LCDPs in PA. This study contributes to the growing knowledge base in agricultural technology, offering valuable insights for researchers, practitioners, and policymakers looking to leverage LCDPs for sustainable and efficient farming practices.

Background Lower respiratory tract infections (LRTIs), particularly pneumonia, are a leading cause of morbidity and mortality among children worldwide, especially in low-resource settings. The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines currently recommend antibiotic treatment for all case of with pneumonia based on clinical signs along, which can lead to over-prescription of antibiotics and contribute to antimicrobial resistance (AMR). Point of care Lung Ultrasound (LUS) has emerged as a promising diagnostic tool in this context and has demonstrated potential in distinguishing between bacterial and viral pneumonia, thus enabling more targeted antibiotic use. This study aims to explore whether integrating LUS into the IMCI-based management of clinical pneumonia will better identify those who would benefit from antibiotic treatment, reducing antibiotic overuse without compromising health outcomes. Methods An open label randomized controlled trial will enrol 3500 children aged 60 days to 12 years presenting with IMCI-defined pneumonia. Participants will be enrolled in Senegal, Tanzania, and South Africa. Participants will be randomly assigned in a ratio of 1:1, stratified by site and age group (<5years, 5-12years) to either an intervention group, where LUS will guide antibiotic prescriptions utilising a predefined interpretation framework, or a control group receiving routine IMCI-based care. The co-primary outcomes of this study are the reduction in antibiotic use on the day of enrolment (Day 1) and rate of clinical failure by Day 8, using an acceptable clinical difference of 1.5x as a non-inferiority margin (delta of 2.5%). Secondary outcomes will include adverse drug reactions, cure rates, hospital admissions including in-patient duration, and cost-effectiveness. Data will be collected at baseline (Day 1), Day 8, and Day 29 post-enrolment. Discussion This study seeks to provide evidence on the clinical and public health benefits of using LUS to improve the diagnosis and management of paediatric pneumonia in low-resource settings. If this intervention proves effective it could contribute significantly toward reducing unnecessary antibiotic prescriptions, thereby addressing AMR. The potential for LUS to be integrated into routine clinical practice could revolutionize pneumonia management, especially in areas with limited access to advanced diagnostic tools. Trial Registration This trial will be registered on ClinicalTrials.gov and The South African National Clinical Trials Register (SANCTR) prior to participant enrolment.

In the 21st century, climate change and its consequences are getting more serious. The changes in temperature and precipitation alter the run-off conditions, subsequently influencing the channel processes of rivers. The study aims to analyse the hydrological changes of a small, sub-alpine river (Rába River, Central Europe) and the bank erosional processes since the 1950s. The bank erosion was determined based on topographical maps, aerial photographs, and RTK–GPS surveys. Short (2–3 days) floods were common between 1950–1980, and low stages occurred in 65–81% of a year. However, in the 21st century, extreme regimes developed, as record-high, flashy floods alter with long low stages (91–96% of a year). The bank erosion shows a cyclic temporal pattern, gradually increasing until it reaches a high value (4.1–4.9 m/y), followed by a limited erosional rate (2.2–2.8 m/y). However, the magnitude of the bank erosion is decreasing. It could be explained by (1) the lower transport capacity of the more common low stages and (2) the seasonal shift of the flood waves, appearing in the vegetational period when the riparian vegetation can more effectively protect the banks from erosion.

As the largest contributor of carbon emissions in China, the building sector currently relies mostly on enterprises’ own effort to report carbon emissions, which usually results in challenges related to information transparency and workload for regulatory bodies, who play an otherwise vital role in controlling the building sector’s carbon footprint. In this study, we established a novel regulatory model known as QCEPM (Quantitative Carbon Emission Prediction Model) by conducting multiple linear regression analysis using the quantities of concrete, rebar, and masonry structures as independent variables, and the embodied carbon emissions of a building as the dependent variable. We processed the data in the detailed quantity list of 20 multi-story frame-structure buildings and fed them to QCEPM for solution. Comparison of the QCEPM-calculated results against the time-consuming and error-prone manual calculation results suggested a mean absolute percentage error (MAPE) of 2.26%. Using this simplified model, regulatory bodies can efficiently supervise the embodied carbon emissions in multi-storey frame structures by setting up carbon quota for a project in its approval stage, allowing the construction enterprise to carry out dynamic control over the audited three most important building materials throughout a project’s planning and implementation phase.

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen enriched compressed natu-ral gas (HCNG). It is also injected into the natural gas pipeline network to realize the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load peak and trough period is adjusted, and large-scale consumption of renewa-ble energy and the reduction of carbon emissions are realized. First of all, a fine model of hydro-gen production and hydrogen use equipment is established to analyze the impact of adding hy-drogen mixing on the economy and low-carbon of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utiliza-tion rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment opera-tion cost, carbon emission cost, wind curtailment cost and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natu-ral gas was established. The model was linearized and solved by using MATLAB and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

To date, radiation adaptation response has been reported as a low-dose related phenomenon and has been associated with radiation hormesis. Well-known cancers are caused by non-radiation active reactants, in addition to radiation. A model of suppression for radiation-specific cancers was previously reported, but the model did not target radiation-nonspecific cancers. In this paper, we describe kinetic models of radiation-induced suppressors for general radiation non-specific cancers, estimating the dose that induces the maximum hormesis effect while satisfying the condition that the risk is approximately proportional to dose above 100 mSv. It was found that the radiation hormesis effect is maximal at about 20 mSv when the rate constant for generation is the same as the rate constant for decomposition. When the two rate constants are different, the dose at which the radiation hormesis effect is maximized depends on both rate constants, but the dose increases as the two rate constants approach each other, reaching a maximum of about 20 mSv. This conclusion may lead to the discovery of unknown cancer suppressors at low doses and the development of cancer suppression methods in the future.

This study leverages the relationships between the Great Plains low-level jet (GP-LLJ) and the circumglobal teleconnection (CGT) to enhance the 30-day rainfall forecast skill in the Northern Great Plains (NGP). The assessment of 30-day simulated precipitation using the Climate Forecast System (CFS) is contrasted with the North American Regional Reanalysis, searching for sources of precipitation predictability associated with extended wet and drought events. We analyze the 30-day sources of precipitation predictability using (1) the characterization of dominant statistical modes of variability of 900-mb winds associated with the GP-LLJ, (2) the large-scale atmospheric patterns based on 200-mb geopotential height (HGT), and (3) the use of GP-LLJ and CGT conditional probability distributions using a continuous correlation threshold approach to identify when and where the forecast of NGP precipitation occurs. Two factors contributing to the predictability of precipitation in the NGP are documented. We found that multi-scale geospatial interactions occur at the daily and sub-seasonal time windows. The CFS reforecast suggests that the ability to forecast sub-seasonal precipitation increases in response to the enhanced simulation of the GP-LLJ and CGT. Finally, the multi-dimensional analysis of covariance reveals that high-precipitation forecasting skill is associated with a better prognostic of GP-LLJ and CGT.

For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions at the expense of the main lobe resolutions. Therefore, the improved spatially variant apodization imaging method for forward-looking sonar is proposed to reduce the sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear post-processing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent beam sidelobe heightening from occurring prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately -40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

The improvement of agricultural low-carbon efficiency is an important path to promote the realization of the "double carbon" goal in the Yellow River Basin. In the context of rapid urbanization development, it is of great significance to explore whether the promotion of urbanization will affect the agricultural low-carbon efficiency. Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this paper uses super-DEA model, three-dimensional kernel density model and Markov chain model to measure and analyze the spatio-temporal evolution of agricultural low-carbon efficiency in the Yellow River Basin, on this basis, the panel Tobit model is used to analyze the relationship between urbanization and low-carbon efficiency in agriculture. The results show that: (1) The level of agricultural low-carbon efficiency in the Yellow River Basin is low and has not reached the effective state, showing a slow downward trend in general, among which, the agricultural low-carbon efficiency in the lower reaches is higher than that in the middle reaches, and the upper reaches is the lowest. (2) The agricultural low-carbon efficiency in the Yellow River Basin has a negative trend of transferring to the low level on the whole, and tends to maintain the original state level, and it is difficult to realize the leapfrog transfer between states. Agricultural low-carbon efficiency has obvious spatial spillover effect and "club convergence" phenomenon, high efficiency area has a positive driving effect on the neighborhood area, while low efficiency area has a negative impact on the neighborhood area. (3) The level of urbanization has a significant positive impact on the low-carbon efficiency of agriculture in the upper, middle and lower reaches of the Yellow River Basin, which plays an important role in promoting the green development of agriculture. Finally, based on the above research conclusions, relevant policy recommendations were put forward, in order to provide references for promoting the improvement of low-carbon agricultural efficiency and promoting high-quality agricultural development in the Yellow River Basin.

This study aimed to assess the prevalence and identify risk factors for schistosomiasis among school-aged children in low- and middle-income communities. A retrospective cross-sectional study was conducted, involving the examination of 24 034 children for Schistosoma haematobium ova. Data were analyzed using IBM Statistical Package for the Social Sciences (SPSS) version 27. Logistic regression was employed to determine the factors associated with schistosomiasis. The overall prevalence of schistosomiasis in the study population was 75%, with higher rates observed in rural-dominated areas, particularly Bushbuckridge (73%) and Nkomazi (51%). Age, a history of bilharzia, and the presence of blood in urine were significantly associated with schistosomiasis, while being a female child was found to be a protective factor. This study underscores the importance of implementing robust screening procedures and the necessity for health education to mitigate the high prevalence of schistosomiasis and prevent its further spread.

Rural areas, as a system, face multiple challenges. Among these are population decline and attendant economic and social maladies namely demographic issues considering a scarce population. Pull factors for immigrants to go to other countries are known, nevertheless, to comprehend factors for remaining in rural areas after arriving could support a strategic local policy, and for an informed practice. The purpose of the study is to explore motivations shaping immigrants’ intentions to stay in the Alentejo, a depopulated region in Portugal, using a qualitative approach. Research questions are: What motivates immigrants to remain living in depopulated regions in Portugal? Furthermore, what contributions can practitioners and immigrants give for local policy and practice? Eight practitioners and fifteen non-European Union immigrants living in this region were interviewed between 2020 and 2021. Empirical data were analysed, supported by MaxQDA software. Results point out that the intention to remain in rural areas arise from a progressive construction, it is a process that immigrants experience to become motivated to stay long-term. Factors influencing the process include four components: 1. instrumental and material motivations; 2. emotional and social motivations; 3. motivations based on quality of life; and 4. motivations based on political dimensions. Components are conditioned by the availability of : stable and suitable jobs, access to decent and affordable housing, as well as quality of education and health services for their children; additionally to socio-emotional satisfaction, as family reunification, migrants network, integration and real intercultural living in the host community, close relationships to practitioners from social services; and quality of life, such as lower rents, peaceful and secure living conditions, granted a better future for their children as in any another place in Europe, associated finally to the simplified policy enabling one to become a legal citizen. Conclusions highlight implications for policy and practice, suggesting more investment for rural regions to reverse depopulation reality.

Low Emission Zone (LEZ) is an important mechanism to limit the negative environmental impact of traffic pollution in an urban area. Car traffic in the zone is strictly regulated to meet certain technical and environmental criteria. Such solutions of urban environment protection are gaining popularity, especially in European conurbations. Nowadays there are above 300 zones in Europe, mostly established in Italy and Germany. So far there are no LEZs in Eastern and Central European countries. However, the Warsaw authorities are just discussing launching of a LEZ in the city in 2024. According to the ongoing project, the zone is to be launched gradually, in five phases between 2024 and 2032, with the traffic criteria being tightened accordingly. The progressive emission reductions of the predominant pollutants in LEZ in consecutive phases were estimated on the basis of the Real Driving Emissions (RDE) test, carried out in 2020 by the ICCT. The gradually reduced emissions of NOx and PM were subsequently utilized as the input dataset for the regional CALPUFF model predictions, to calculate concentrations of these main traffic-induced pollutants within the LEZ area. The direct effect of the zone activation is reduction of air pollution in the urban center, which is mostly exposed to the pollution risk due to heavy traffic. Computer simulations reveal that implementation of the zone in the case of Warsaw will result in a quite significant reduction of NOx concentrations within the LEZ, such that its mean concentration in the zone becomes comparable to the rest of the conurbation. However, it will bring only a slight reduction of PM2.5 concentrations. This situation is due to the long-standing dominance of coal combustion in the Polish economy, which also applies to the urban municipal sector. As a consequence, particulate matter emissions of this sector are clearly predominant over the road traffic contribution. Balance can be achieved once the ongoing de-carbonization of the national economy has been completed.

Over a century ago, low-dose-rate (LDR) brachytherapy was introduced to treat prostate cancer (PCa). Since then, it has been widely applied worldwide, including in East Asia. LDR brachythera-py has been performed in 88 institutes in Japan. Beneficial clinical outcomes of LDR brachytherapy for intermediate-to-high-risk PCa have been demonstrated in large clinical trials. These clinical outcomes were achieved through advances in methods, such as urological precise needle puncture and seed placement, and the quantitative decision-making regarding radiological parameters by radiation oncologists. Combined use of LDR brachytherapy with other therapeutical modalities, such as external beam radiation and androgen deprivation therapy, for clinical risk classification of PCa has led to better anticancer treatment efficacy. In this study, we summarized basic LDR brachytherapy findings that should remain unchanged and be passed down in urology depart-ments. We also discussed the applications of LDR brachytherapy for PCa in various clinical settings, including focal and salvage therapies. In addition, we highlighted technologies associated with brachytherapy that are under development.

Transitioning to clean cooking fuels is not only part of achieving SDG7, but also makes a significant contribution to mitigating climate change by reducing carbon emissions. The paper contradicts the conventional wisdom that electricity is too expensive to cook with. The paper explores the energy required to cook dishes using different technologies and fuels by analysing data from Cooking Diaries and Controlled Cooking tests conducted under the MECS programme. Electric pressure cookers (EPCs) use least energy when compared with electric hotplates, and a detailed description of how the EPC works explains why this should be. The paper draws out distinctions between African and Asian dishes, notably the impact of energy intensive dishes prepared mostly in Africa. Standard efficiency based approaches to comparing the performance of stoves are not appropriate to modern electric cooking devices so an alternative approach based on specific energy consumptions is proposed e.g. charcoal stoves use 15 times as much energy as EPCs to cook African dishes. Energy ratios provide a basis for estimating carbon emission reductions associated with transitioning to modern cooking fuels. Historical costs show that the cost of cooking with an EPC can be only 20% of the cost of cooking with charcoal, which highlights the potential for modern, energy efficient electric cooking devices to defy the conventional wisdom of the energy ladder.

Oxidative stress (OS) is reported in several chronic diseases. Extra-cellular superoxide dismutase (ec-SOD) catalyzes the dismutation of superoxide anion with a protective role on endothelial cells. In chronic kidney diseases (CKD), OS and thyroid dysfunction (low T3 syndrome) are fre-quently present, but their relationship has not been investigated. This cohort study evaluated ec-SOD activity in CKD patients during haemodialysis, divided into: “acute hemodialytic pa-tients” (AH, 1-3 months of treatment) and “chronic hemodialytic patients” (CH, treated for a longer period). We also evaluated plasmatic total antioxidant capacity (TAC) and the relation-ships with thyroid hormones. Two basal samples (“basal 1”, 3 days after the last dialysis and “basal 2”, 2 days after the last dialysis) were collected. On the same day of basal 2, a sample was collected 5 and 10 min after the standard heparin dose and at the end of the procedure. The ec-SOD values were significantly higher in CH vs AH in all determinations. Moreover, they pre-sented lower TAC values. Dividing CH patients into two subgroups according to fT3 levels (nor-mal or low) we found significantly lower ec-SOD values in the group with low fT3 at basal, 5 and 10 min samples. Finally, a significant correlation was observed between fT3 and ec-SOD in the basal 1 samples. These data, confirming OS and low T3 syndrome in CKD, suggest that low fT3 concentrations can influence ec-SOD activity and therefore contribute to possible endothelial oxi-dative damage in such a situation.

A reduced ability to work with information contained in a text is usually registered in low-achieving students. One important internal factor influencing reading comprehension concerns the child’s executive functioning. The current study investigated whether the domain-specific intervention ExeFun-READ targeting language abilities related to reading comprehension and executive functioning in primary school children would be effective in improving their scholastic performance in their reading domain and executive functioning. ExeFun-READ is designed to address the relations between domain-specific versus thinking-skill-oriented (domain-general) instruction. A child’s active learning is focused on semantic, phonetic, morphological and syntactical comprehension of linguistic material. In total, 151 students attending grade four from seven elementary schools took part in the project. The study concerned a pretest-intervention-posttest experimental design with three conditions: the experimental condition, an active, and a passive control group. To assess the children’s level of EF, the Delis–Kaplan Executive Function System test battery was used; to assess children’s language ability in reading domain, the Cognitive Abilities Test (the verbal battery, Thorndike &amp; Hagan, 1986 [1]), was used. In the current study, the intervention led to improved language abilities related to reading comprehension, but in terms of executive functioning the improvement only extended to switching fluency. Regarding the effects of the ExeFun-READ intervention on children’s reading abilities, specified as language abilities related to reading comprehension, significant improvements were found in vocabulary, completion of sentences, and classification of terms in the group of children that received the ExeFun-READ intervention.

Methicillin-resistant Staphylococcus aureus (MRSA) constitutes a serious public health concern with a considerable impact on patients' health and substantial healthcare costs. In this study, patients, and healthcare workers (HCWs)from six public hospitals in Benin were screened for MRSA. Strains were identified as MRSA using conventional microbiological methods in Benin and confirmed using Matrix-Assisted Laser Desorption/Ionization Time of Flight (MALDI-TOF) mass spectrometry in Belgium. Whole genome sequencing (WGS) was used on confirmed MRSA isolates to characterize their genomic content and study their relatedness. In total,304 and 61 samples were collected from patients and HCWs, respectively. The mecA gene was detected in all isolates. The isolates were assigned to five sequence types (STs), with ST8 (55.6%, n=15), ST152 (18.52%, n=5), and ST121 (18.52%, n=5) being the most common. All isolates carried multiple virulence genes, including genes encoding the Panton-Valentine leukocidin toxin (48.15%, n=13) and the test gene (29.63%, n=8) associated with toxic shock syndrome. The presence of strains carrying numerous genomic features associated with antibiotic resistance and virulence in HCWs is a major public health concern. This study highlights the need to implement a multimodal strategy for reducing the risk of cross-transmission of MRSA in hospitals.

Climate change complies firms to introduce various measures to enhance both their competitiveness and sustainability, particularly energy efficiency measures (EEMs). Energy efficiency is particularly important in energy-intensive sectors such as the industrial sector. However, EEMs within the industrial firms are hindered by several internal barriers such as competing interests within firms, the lack of information regarding energy efficiency opportunities, and the low technical competence. In this regard, energy audit aims to improve energy efficiency in facilities and to tackle internal barriers to energy efficiency. We construct a model which aims to explore the importance of energy audit in implementing EEMs and reducing the intensity of internal barriers to energy efficiency. Our research model was empirically tested through survey data gathered from 193 industrial firms in Morocco. Results show that competing interests, the lack of information and the low technical competence hinder the adoption of EEMs within industrial firms. In addition, energy audits enhance EEMs, and mitigate the negative effect of the lack of information and the low technical competence on the adoption of EEMs. However, energy audits do not attenuate the negative effect of competing interests on EEMs. This study reinforces previous studies with additional confirmation regarding the importance of energy audits for tackling the lack of information, and the low technical competence within firms. Furthermore, our study extends prior research as we found that energy audits do not reduce the intensity of competing interests within firms regarding EMMs’ implementation.

Deep-Brain Stimulation (DBS) is a a highly effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric deceases, and has been consolidated as a first-line tool in the treatment of these conditionsin the last two decades. Closed Loop Deep-Brain Stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. In this context, this paper presents a Low-Noise Amplifier (LNA) and a Neurostimulator circuits fabricated in the low-power/low-voltage 65 nm CMOS process from the TSMC, which were designed targeting implantable applications. To achieve the best trade-off between input-referred noise and power consuption, metaheuristic algorithms were employed to determine and optimizes the dimentions of the LNA devices during the design phase. The measurement results showed that the LNA had a gain of 40.6 dB, a 3 dB bandwidth spanning over three decades from 10 Hz to 8.6 kHz, and a power consumption of 6.19 uW. Simulations results indicated an input-referred noise of 4.86 uVrms for the LNA. The circuit of the Neurostimulator is a programmable Howland Current-Pump, whose measurements showed its ability to generate currents with arbitrary shapes ranging from between 325 uA to +318 uA. The simulations showed a quiescent power consumption of 0.13 W with a zero neurostimulation current. The LNA and the Neurostimulator circuits are supplied with 1.2 V voltage and occupy a microdevice area of 145 um x 311 um and 88 um x 89 um, respectively, making them suitable for implantation in applications involving Closed Loop Deep-Brain Stimulation.

Low-cost particulate matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and their cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors but some models of sensors also report particle number concentrations (PNC) segregated into different PM size bins. In this study, 8 units of each Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors to different particle size distributions to quantify and better understand the low cost sensors performance across a range of relevant environmental ranges. The PNC reported by the sensors were analysed. This study showed that there is added value in directly using the PNC reported by the sensors instead of the mass concentrations, which could aid the efforts to calibrate these sensors to a known accuracy. It demonstrated that all sensors tested here could track the fine temporal variation of PNC, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it showed that particle size distribution and composition are more impactful on the sensors measurement than relative humidity.

A low-resource emotional speech synthesis system for empathetic speech synthesis based on modelling prosody features is presented here. Secondary emotions, identified to be needed for empathetic speech, are modelled and synthesised in this paper. As secondary emotions are subtle in nature, they are difficult to model compared to primary emotions. They are also less explored, and this is one of the few studies that model secondary emotions in speech. Current speech synthesis research uses large databases and deep learning techniques to develop emotion models. There are many secondary emotions, and hence, developing large databases for each of the secondary emotions is expensive. This research presents a proof-of-concept using hand-crafted feature extraction and modelling of these features using a low resource-intensive machine learning approach, thus creating synthetic speech with secondary emotions. Here, a quantitative model-based transformation is used to shape the emotional speech fundamental frequency contour. Speech rate and mean intensity are modelled via rule-based approaches. Using these models, an emotional text-to-speech synthesis system to synthesise five secondary emotions - anxious, apologetic, confident, enthusiastic and worried is developed. A perception test to evaluate the synthesised emotional speech is also conducted.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P&lt;0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

Introduction. Self-sampling has the potential to increase cervical cancer screening (CCS) among women living with HIV (WLWH) in low and middle-income countries (LMICs). However, our understanding of how HPV self-collection studies have been conducted in WLWH is limited. The purpose of this scoping review was to examine the extent to which the HPV self-sampling has been applied among WLWH in LMICs. Method: We conducted multiple searches in several databases for articles published between 2000 and January 2022. With the combination of keywords relating to HPV self-sampling, LMICs, and WLWH, we retrieved over 9,000 articles. We used pre-defined inclusion and exclusion criteria to select relevant studies for this review. Once a study met the inclusion criteria, we created a table to extract each study’s characteristics and classified them under common themes. We used a qualitative descriptive approach to summarize the scoping results. Results: A total of 12 articles were included in the final review. Overall, 3,178 women were enrolled in those studies and 2,105 (66%) of them were WLWH. The self-sampling participation rate was 92.6%. The findings of our study show that 43% of the WLWH in 8 of the studies reviewed tested positive for high-risk HPV (hr-HPV) genotypes, indicating 4 out of 10 WLWH in the studies are at risk of cervical cancer. The prevalence of the hr-HPV in WLWH was 18% higher than that of HIV-negative women. Most women in the study found the self-sampling experience acceptable, easy to use, convenient, and comfortable. Self-sampling performance in detecting hr HPV genotypes is comparable to clinician-performed sampling. However, limited access (i.e., affordability, availability, transportation), limited knowledge about self-screening, doubts about the credibility of self-sampling results, and stigma remain barriers to wide acceptance and implementation of self-sampling. In conclusion, the findings of this review highlight that (a) cervical cancer is a threat to every sexually active woman but for WLWH the threat increases, (b) self-sampling laboratory performance is similar to clinician performed sampling, (c) self-sampling is associated with an increase in cervical cancer screening uptake and (d) WLWH reported a positive experience with self-sampling. However, personal, environmental, and structural barriers challenge the application of self-sampling in LMICs, and these need to be addressed. Keywords: keyword 1; keyword 2; keyword 3 (List three to ten pertinent keywords specific to the article yet reasonably common within the subject discipline.)

Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM2.5 values in the PurpleAir database from Washington, Oregon, and California between January 1, 2017 and September 8, 2021. Daily outdoor PM2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

A right frontoparietal neoplastic lesion was found in a young-aged patient with analgesic refractory headache. Surgical resection was performed, and the pathologist analysis turned out a cellular ependymoma with signs of anaplasia. In the follow-up, a MRI showed a suspicious lesion, so a [18F]Fluorocholine PET/CT was performed. An increased uptake was described in the right parietal region on the margin of residual cystic lesion. The patient got a complete resection which was confirmed later by MR. In the pathology analysis, a focally congestive cerebral parenchyma with a central histiocytic reaction to foreign body area was described. Foreign body reaction in brain tissue is a very rare immune response that has not been well studied. Haemostatic material has been reported as a possible trigger of this response in other organs and could be detected by [18F]FDG PET/CT. Following the experience of the current case report, [18F]Fluorocholine PET/CT could also show a false positive related to foreign body reaction.

The instability of traveling pulses in nonlinear diffusion problems is inspected on the example of Gunn domains in semiconductors. Mathematically the problem is reduced to the calculation of the "energy" of the ground state in Schrödinger equation with a complicated potential. A general method to obtain the bottom-part spectrum of such equations based on the approximation of the potential by square wells is proposed and applied. Possible generalization of the approach to other types of nonlinear diffusion equations is discussed.

High-strength low-alloy steels (HSLAs) are widely used in the structural body components of many domestic motor vehicles owing to their better mechanical properties and greater resistance. The real production process of HSLA steelmaking can be regarded as a model that builds on the relationship between process parameters and product quality attributes. A surrogate modeling method is used, and the resulting production process model can be applied to predict the optimal manufacturing process parameters. We used different methods in this paper to build such a surrogate model, including linear regression, random forests, support vector regression, multilayer perception, and a simplified VGG model. We then applied three bio-inspired search algorithms, namely particle swarm optimization, the artificial bee colony algorithm, and the firefly algorithm, to search for the optimal controllable manufacturing process parameters. Through experiments on 9,000 test samples used for building the surrogate model, and 299 test samples for making the optimal process parameter selection, we found that the combination of a simplified VGG model and the firefly algorithm was the most successful at reaching a success rate of 100%—in other words, when the product quality attributes of all test samples satisfy the mechanical requirements of the end products.

In this paper we perform numerous numerical studies for the problem of low-rank matrix completion. We compare the Bayesian approaches and a recently introduced de-biased estimator which provides a useful way to build confidence intervals of interest. From a theoretical viewpoint, the de-biased estimator comes with a sharp minimax-optimal rate of estimation error whereas the Bayesian approach reaches this rate with an additional logarithmic factor. Our simulation studies show originally interesting results that the de-biased estimator is just as good as the Bayesian estimators. Moreover, Bayesian approaches are much more stable and can outperform the de-biased estimator in the case of small samples. However, we also find that the length of the confidence intervals revealed by the de-biased estimator for an entry is absolutely shorter than the length of the considered credible interval. These suggest further theoretical studies on the estimation error and the concentration for Bayesian methods as they are being quite limited up to present.

The log interpretation and evaluation of Chang 8 tight sandstone reservoir in Longdong West area, Ordos Basin, is facing great challenges due to the existence of low resistivity contrast oil pays. To better guide the exploration of oil resources in this area, the characteristics and control mechanism of low resistivity contrast oil pays were studied in this research. Firstly, according to the relative value of apparent resistivity increase rate of the target formation, the reservoir was divided into two types: low resistivity contrast oil pay (LRCP) and high resistivity oil pay (HRP). Then, the reservoir characteristics were studied by comparing and analyzing the experimental data, formation water data and logging data collected from the two reservoir types. On this basis, the control mechanism of LRCP was studied and summarized into reservoir micro factors and regional macro factors, respectively. It is found that the reservoir rock composition between LRCP and HRP is basically the same. Compared with HRP reservoir, the average porosity and permeability of LRCP reservoir are relatively better, but the pore structure is relatively poorer because of the high content of micro pores. When the filling pressure of crude oil is sufficient enough, the high oil saturation can be formed in LRCP reservoir. The high irreducible water saturation and high formation water salinity are the main micro factors reduced the reservoir resistivity. Besides, the difference of hydrocarbon expulsion capacity of source rock and the regional difference of formation water salinity are the macro factors influenced the distribution of LRCP and HRP from vertical and horizontal of the region. The formation of LRCP is controlled by the comprehensive influence of reservoir micro factors and regional macro factors. And the comprehensive consideration of the influence of micro factors and macro factors on LRCP is suggested during the log interpretation and evaluation.

We propose a novel transfer learning method for speech emotion recognition allowing us to obtain promising results when only few training data is available. With as low as 125 examples per emotion class, we were able to reach a higher accuracy than a strong baseline trained on 8 times more data. Our method leverages knowledge contained in pre-trained speech representations extracted from models trained on a more general self-supervised task which doesn’t require human annotations, such as the wav2vec model. We provide detailed insights on the benefits of our approach by varying the training data size, which can help labeling teams to work more efficiently. We compare performance with other popular methods on the IEMOCAP dataset, a well-benchmarked dataset among the Speech Emotion Recognition (SER) research community. Furthermore, we demonstrate that results can be greatly improved by combining acoustic and linguistic knowledge from transfer learning. We align acoustic pre-trained representations with semantic representations from the BERT model through an attention-based recurrent neural network. Performance improves significantly when combining both modalities and scales with the amount of data. When trained on the full IEMOCAP dataset, we reach a new state-of-the-art of 73.9% unweighted accuracy (UA).

Emerging pollutants as pharmaceuticals have been focusing international attention for few decades. Ciprofloxacin (CIP) is a common drug widely found in effluents from hospitals, industrial and different wastewater treatment plants, as well as rivers. In this work, the lab-scale 3D-BER system was established, and more than 90% of the antibiotic CIP removal from the Low C/N wastewater. Best results were obtained with current intensity, and different C/N ratio significantly improve the removal of CIP and nitrates, when the ideal conditions were; C/N = 1.5-3.5, pH =7.0-7.5, and I = 60 mA. The highest removal efficiency of CIP = 94.20 %, NO3--N= 95.53 % and total nitrogen (TN) = 84.27 %, respectively. In this novel system, the autotrophic-heterotrophic denitrifying bacteria played vital role for the removal of CIP and enhanced denitrification process. Thus, autotrophic denitrifying bacteria uses CO2 and H2 as carbon sources to reduce nitrates to N2. This system has the assortment and prosperous community revealed at the current intensity of 60 mA, and the analysis of bacterial community structure in effluent samples fluctuates under different condition of C/N ratios. According to the results of LC-MS/MS analysis, the intermediate products were proposed after efficient biodegradation of CIP. Microbial community on biodegrading was mostly found at phylum, and class level was dominantly responsible for the NO3--N and biodegradation of CIP. This work can provide some new insights towards the biodegradation of CIP and the efficient removal of nitrates from low C/N wastewater treatment by the novel 3D-BER system.

Abstract The COVID-19 pandemic is thought to began in Wuhan, China in December 2019. Mobility analysis identified East-Asia and Oceania countries to be highly-exposed to COVID-19 spread, consistent with the earliest spread occurring in these regions. However, here we show that while a strong positive correlation between case-numbers and exposure level could be seen early-on as expected, at later times the infection-level is found to be negatively correlated with exposure-level. Moreover, the infection level is positively correlated with the population size, which is puzzling since it has not reached the level necessary for population-size to affect infection-level through herd immunity. These issues are resolved if a low-virulence Corona-strain (LVS) began spreading earlier in China outside of Wuhan, and later globally, providing immunity from the later appearing high-virulence strain (HVS). Following its spread into Wuhan, cumulative mutations gave rise to the emergence of an HVS, known as SARS-CoV-2, starting the COVID-19 pandemic. We model the co-infection by an LVS and an HVS, and show that it can explain the evolution of the COVID-19 pandemic and the non-trivial dependence on the exposure level to China and the population-size in each country. We find that the LVS began its spread a few months before the onset of the HVS, and that its spread doubling-time is $\sim 1.59\pm 0.17$ times slower than the HVS. Although more slowly spreading, its earlier onset allowed the LVS to spread globally before the emergence of the HVS. In particular, in countries exposed earlier to the LVS and/or having smaller population-size, the LVS could achieve herd-immunity earlier, and quench the later-spread HVS at earlier stages. We find our two-parameter (the spread-rate and the initial onset time of the LVS) can accurately explain the current infection levels (R^2$\mathrm{=0.74}$; correlation p-value (p) of 5x10^-13$$). Furthermore, countries exposed early should have already achieved herd-immunity. We predict that in those countries cumulative infection levels could rise by no more than 2-3 times the current level through local-outbreaks, even in the absence of any containment measures. We suggest several tests and predictions to further verify the double-strain co-infection model and discuss the implications of identifying the LVS.

Uniform illumination is a key requirement in different research fields. However, this requirement is often difficult to achieve when high intensity is required at the same time. Recent advancements in LED lamps allow nowadays for compact and economical solutions. In this work we present a suitable solution for various laboratory purposes requiring stable, uniform and high intensity illumination. The system is composed of four identical high power white LED arrays of 30 mm diameter each, placed on a supporting and cooling structure having a minimum volume of 26 cm x 26 cm x 8 cm. A numerical model has been developed, based on a ray tracing software, in order to simulate the performances. These have then been experimentally validated with measurements of the power density map, carried out with a 1% uncertainty pyranometer. Data show that the built system is very stable over time and provides an illumination uniformity higher than 98%, on a surface of 50 mm radius, which reduces to 95% on a surface of 75 mm radius. The power density can be adjusted in the 390-1360 W m-2 range, not affecting uniformity.

In this paper, we draw on recent experiences from the Young Lives study to discuss some of the ethical and practical challenges facing longitudinal cohort studies in low- and middle-income countries in the time of coronavirus. We argue that COVID-19 has instigated an ‘ethics of disruption’ for social researchers across the world, and for longitudinal cohort studies like Young Lives, this requires navigating three core considerations: first, managing research relationships and reciprocity within an observational study design; second, maintaining methodological continuity and consistency across time; and third, balancing an immediate short-term response to COVID-19 against the longer-term perspective. We refer to the study’s plan to implement a new COVID-19 phone survey to illustrate how the team are navigating this altered ethical terrain.

Chronic kidney disease (CKD) affects >10% of the adult population. Each year approximately 120,000 Americans develop end-stage kideny disease and initiate dialysis, which is costly and associated with functional impairments, worse health-related quality of life, and high early-mortality rates exceeding 20% in the first year. Recent declarations by the World Kidney Day and the U.S. Government Executive Order seek to implement strategies that reduce the burden of kidney failure by slowing CKD progression and controlling uremia without dialysis. Pragmatic dietary interventions may have a role in improving CKD outcomes and preventing or delaying dialysis initiation. Evidence suggests that a patient-centered plant-dominant low-protein diet (PLADO) of 0.6-0.8 g/kg/day comprised of >50% plant-based sources, administered by dietitians trained in non-dialysis CKD care, can be promising. The scientific premise of the PLADO is based on the observations that high protein diets with high meat intake are not only associated with higher cardiovascular disease risk but also higher CKD incidence and faster CKD progression due to increased intraglomerular pressure and glomerular hyperfiltration. Meat intake increases production of nitrogenous end-products, worsens uremia, and may increase the risk of hyperkalemia, given constipation from the typical low fiber intake. Plant-dominant, fiber-rich, low-protein diet may lead to favorable alterations in the gut microbiome, which can modulate uremic toxin generation and slow CKD progression, along with reducing cardiovascular risk in CKD patients. PLADO is a heart-healthy, safe, flexible, and feasible diet that could be the centerpiece of a conservative and preservative CKD-management strategy that challenges the prevailing dialysis-centered paradigm.