The refractive index of solids guages their transparency to incident light, while the energy gap determines the threshold for light absorption. This paper provides a mathematical formulation for the relationship between refractive index and energy gap. It is also established that this formulation aided in the unification of the Moss, Ravindra, and Herve-Vandamme relationships.

Electrospinning is a simple versatile method to generate nanofibres. Remarkable progress has been made in the development of electrospinning process. The production of nanofibers is affected by many parameters, which influence the final material properties. Electrospun fibers have a wide range of applications such as energy storage and biomedical scaffolds. Polyacrylonitrile (PAN) has been widely used in the production of carbon nanofibers. PAN has received increasing interest in recent years, due to its excellent characteristics, such as spinnability, biocompatibility, and commercial viability, opening new applications in the biotechnological field. This paper provides an overview of the electrospinning process, its main parameters, and operation modes that affect nanofibers fabrication. A review of their biological applications is proposed. A focus is made on PAN fibers formation, functionalization, and application as scaffolds to allow cell growth. Overall, nanofibre scaffolds, made of stabilized PAN, appear as a powerful tool in medical applications needing controlled cell culture.

Purpose: The purpose of this study was to evaluate the dosimetric impact of multiple channels compared to a single channel in high dose rate (HDR) vaginal cuff brachytherapy (VCBT). Methods and materials: Sample plans of HDR VCBT from both single and multiple channel cylinders at 2.5, 3.0 and 3.5 cm in diameter were created and analyzed. The doses were prescribed either at the 0.5 cm depth with 5.5 Gy for 4 fractions or at the cylinder surface with 8.8 Gy for 4 frac¬tions, in various treatment lengths ranging from 3 to 8 cm. A 0.5 cm ring target volume called PTV_Eval was contoured for each plan and served as the target volume for dosimetric evaluation. Mean doses and the doses covering 90% (D90), 10% (D10), and 5% (D5) of PTV_Eval were calculated and compared. The same treatment lengths, same prescription regimens, same target volume contouring and same plan evaluation methods were repeated for the similar size single channel and multiple channel cylinders. Results: The mean doses of both regimens with the multi-channel cases (6.3 to 7.1 Gy) were comparable to single channel ones (6.4 and 7.5 Gy). The ranges of D90, D10 and D5 were from 3.654 to 5.04 Gy, 8.44 to 10.08 Gy and 8.84 to 10.86 Gy in the multi-channel cases, but from 5.36 to 5.76 Gy, 7.40 to 9.97 Gy and 8.16 to 11.93 Gy in the single channel cases, respectively. Conclusion: The single channel and multiple-channel cylinder deliver a similar mean dose, but with marked heterogeneity in D90, D5 and D10 for the same prescription dose and target volume. Multi-channel cylinders adequately cover the target volume, but given the heterogeneity, increased treatment time and cost are best suited for asymmetric target volumes.

Unlike aerial or terrestrial navigation, the Global Navigation satellite system (GNSS) is not available underwater. This is a big challenge for underwater navigation. The inertial navigation system (INS) aided by the single-beacon acoustic positioning system (APS) provides one solution, but the long-range case is limited by low SNR conditions. Inspired by passive synthetic aperture detection, we proposed a new tightly coupled navigation algorithm based on spatial synthesis and one-way-travel-time (OWTT) range measurement. We design two estimators: the DOA/Range estimator using the model-based method and the tightly coupled INS/APS navigation estimator. Based on the improved UKF, all information is combined. Simulation is carried out in MATLAB. Compared with range-only tightly coupled INS/APS navigation, synthetic long baseline (SLBL) algorithm and Doppler velocity logger (DVL) aided centralized extended Kalman filter (CEKF) based single beacon INS/OWTT navigation, the proposed method's performance is proven. The main contributions of this work are: 1. Propose a new architecture of underwater integrated navigation; 2. Apply the passive acoustic detecting method in the navigation to improve accuracy. 3. Apply the tightly coupled method to improve availability.

In this paper, four types of open service signals of BDS-3 satellite (B1I, B1C, B2a, and B3I) and B2I signals broadcasted by BDS-2 satellites were used in the time frequency transfer and positioning experiments with signal coexisting in BDS system, and the single frequency PPP (precise point positioning) method was used. Modified GRoup And PHase Ionospheric Correction (GRAPHIC) method was proposed and verified by the experiment. The results show that 18 selected stations can achieve decimeter-level positioning results with single frequency. Compared with the general observation method, the proposed modified GRAPHIC method improves the stability and precision of positioning and timing significantly, and the positioning accuracy of 5 frequency signals is increased 40.4%, 32.2%, 80.3%, 12.4%, and 10.3%, respectively. The frequency stability can reach the same accuracy as that of dual-frequency with BDS in the current state.

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder characterized by unexplained left ventricular hypertrophy, with or without left ventricular outflow tract (LVOT) obstruction. Single nuclei RNA-sequencing (snRNA-seq) of both obstructive and nonobstructive HCM patient samples have revealed alterations in communication between various cell types but a direct and integrated comparison between the two HCM phenotypes has not been reported. We performed a bioinformatic analysis of HCM snRNA-seq datasets from obstructive and nonobstructive patient samples to identify differentially expressed genes and distinctive patterns of intercellular communication. Differential gene expression analysis revealed 37 differentially expressed genes, predominantly in cardiomyocytes but also in other cell types, relevant to aging, muscle contraction, cell motility and the extracellular matrix. Intercellular communication was generally reduced in HCM, affecting the extracellular matrix, growth factor binding, integrin binding, PDGF binding and SMAD binding, but with increases in adenylate cyclase binding, calcium channel inhibitor activity, and serine-threonine kinase activity in nonobstructive HCM. Increases in neuron to leukocyte and dendritic cell communication, in fibroblast to leukocyte and dendritic cell communication and in endothelial cell communication to other cell types, largely through changes in expression of integrin-b1 and its cognate ligands, were also noted. These findings indicate both common and distinct physiological mechanisms affecting the pathogenesis of obstructive and nonobstructive HCM and provide opportunities for personalized management of different HCM phenotypes.

Tuberculosis (TB) remains a global healthcare crisis with an estimated 10 million new cases and 1.4 million deaths per year TB is caused by infection with the major human pathogen Mycobacte-rium tuberculosis, which is difficult to rapidly diagnose and treat. There is an urgent need for new methods of diagnosis, sufficient in vitro models which capably mimic all physiological condi-tions of the infection, and high-throughput drug screening platforms. Microfluidic-based tech-niques provide single-cell analysis which reduces experimental time, the cost of reagents, and have been extremely useful for gaining insight into monitoring microorganisms. This review out-lines the field of microfluidics and discusses the use of this novel technique so far in M. tuberculo-sis diagnostics, research methods, and drug discovery platforms. The practices of microfluidics have promising future applications for diagnosing and treating TB.

The City of Meycauayan is considered as one of the most polluted cities in the developing world on the account of industrial discharges of toxic materials to the environment. This work investigated the sources of the heavy metal pollution by analyzing soil and sediment samples for heavy metals (Cr, Hg, Ni, and Pb) together with selected environmental indicators (TN, TOM, and TP) located along the Meycauayan River. Hierarchical cluster analysis (HCA), principal components analysis (PCA), and Pearson correlation analysis (CA) were used to identify the sources of the metals. Results showed delineated locations of severe levels of heavy metal pollution downstream because of the concentration of industrial activities. Cr contributed more than any other heavy metals analyzed due to proliferation of tanneries discharging untreated wastewaters to the river. Significant inputs of Pb and Hg from Pb-acid battery recycling and gold smelting industries were also found. Risk assessments indicated severe levels of heavy metal pollution where industrial activities are concentrated. The mean Cr, Pb, Ni, and Hg in the sampling locations have mean incidences of toxicity of 91.7 %, 53.6 %, 27.7 %, and 70.0 %, respectively. Our study showed a serious need to address heavy metal pollution in Meycauayan.

Deep convolutional neural network (CNN) has shown their great advantages in the single image deraining task. However, most existing CNN-based single image deraining methods still suffer from residual rain streaks and details lost. In this paper, we propose a deep neural network including the Multi-scale feature extraction module and the channel attention module, which are embed in the feature extraction sub-network and the rain removal sub-network respectively. In the feature extraction sub-network, the Multi-scale feature extraction module is constructed by a Multi-layer Laplacian pyramid, and is then integrated multi-scale feature maps by a feature fusion module. In the rain removal sub-network, the channel attention module, which assigns different weights to the different channels, is introduced for preserving image details. Experimental results on visually and quantitatively comparison demonstrate that the proposed method performs favorably against other state-of-the-art approaches

Nanoparticles of platinum-group metals (PGM) on carbon supports are widely used as catalysts for a number of chemical and electrochemical conversions on laboratory and industrial scale. The newly emerging field of single atom catalysis focuses on the ultimate level of metal dispersion, i.e. atomically dispersed metal species anchored on the substrate surface. However, the presence of single atoms in traditional nanoparticle-based catalysts remains largely overlooked. In this work we use aberration-corrected scanning transmission electron microscope to investigate four commercially available nanoparticle-based PGM/C catalysts (PGM = Ru, Rh, Pd, Pt). We show that in addition to nanoparticles, single atoms are also present on the surface of carbon substrates. These observations raise questions about the role that single atoms play in conventional nanoparticle PGM/C catalysts. We critically discuss the observations with regard to the quickly developing field of single atom catalysis.

Single valued neutrosophic set has king power to express uncertainty characterized by indeterminacy, inconsistency and incompleteness. Most of the existing single valued neutrosophic cross entropy bears an asymmetrical behavior and produce an undefined phenomenon in some situations. In order to deal with these disadvantages, we propose a new cross entropy measure under single valued neutrosophic set (SVNS) environment namely SN- cross entropy and prove its basic properties. Also we define weighted SN-cross entropy measure and investigate its basic properties. We develop a new multi attribute group decision making (MAGDM) strategy for ranking of the alternatives based on the proposed weighted SN-cross entropy measure between each alternative and the ideal alternative. Finally, a numerical example of MAGDM problem of investment potential is solved to show the validity and efficiency of proposed decision making strategy. We also present comparative anslysis of the obtained result with the results obtained form the existing solution strategies in the solution.

A gold(I) complex with a triphenylphosphine and a monodentate N,N-dimethyldithiocarbamate ligand was synthesized and characterized by Raman spectroscopy and single crystal X-ray diffraction. DFT calculations (Gaussian 09, PBE1PBE/Lanl2dz) were undertaken for a single complex in the gas-phase. The DFT-optimized structure is in good agreement with the crystal structure and the DFT-calculated Raman spectrum also is in excellent agreement with the experimental spectrum. Assignments of the Raman peaks are based on these DFT calculations. Frontier molecular orbitals were calculated and their nature is discussed.

Wheat dwarf virus (WDV) causes an important vector transmitted virus disease, which leads to significant yield losses in barley production. Due to the fact, that at the moment no plant protection products are approved to combat the vector Psammotettix alienus and this disease cannot be controlled by chemical means, therefore the use of WDV resistant or tolerant genotypes is the most efficient method to control and reduce negative effects of WDV on barley growth and production. In this study, a set of 480 barley genotypes were screened to identify genotypic differences in response to WDV and five traits were assessed under infected and non-infected conditions. In total, 32 genotypes showed resistance or tolerance against WDV. Subsequently, the phenotypic data of 191 out of 480 genotypes combined with 34,408 single nucleotide polymorphisms (SNPs) in a genome wide association study to identify quantitative trait loci (QTLs) and markers linked to resistance/tolerance to WDV, using Tassel, GAPIT, and FARM CPU. In total, 1, 3, 2, 2 and 1 significantly associated markers on chromosomes 3H, 4H, 5H and 7H identified by all three methods for ELISA-60, relative performance of total grain weight, plant height, number of ears per plant and thousand grain weight, respectively.

The molecular basis of Down syndrome (DS) predisposition to leukemia is not fully understood but involves various factors such as chromosomal abnormalities, oncogenic mutations, epigenetic alterations, and changes in selection dynamics. Myeloid leukemia associated with DS (ML-DS) is preceded by a preleukemic phase called transient abnormal myelopoiesis driven by GATA1 gene mutations and progresses to ML-DS through additional mutations in cohesin genes, CTCF, RAS, or JAK/STAT pathway genes. DS-related ALL (ALL-DS) differs from non-DS ALL in terms of cytogenetic subgroups and genetic driver events and aberrant expression of CRLF2, JAK2 mutations, and RAS pathway activating mutations are frequent in ALL-DS. Recent advancements in single-cell multi-omics technologies have provided unprecedented insights into the cellular and molecular heterogeneity of DS-associated hematologic neoplasms. Single-cell RNA sequencing and digital spatial profiling enable the identification of rare cell subpopulations, characterization of clonal evolution dynamics, and exploration of the tumor microenvironment's role. These approaches may help identify new druggable targets and tailor therapeutic interventions based on distinct molecular profiles, ultimately improving patient outcomes with the potential to guide personalized medicine approaches and the development of targeted therapies.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

We have shown that lipid-associated loci discovered by genome-wide association studies (GWAS) have pleiotropic effects on lipid metabolism, carotid intima-media thickness (CIMT), and CAD risk. Here, we investigated the impact of lipid-associated GWAS loci on the efficacy of rosuvastatin therapy in terms of changes in plasma lipid levels and CIMT. The study comprised 116 CAD patients with hypercholesterolemia. CIMT, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were measured at baseline and after 6 and 12 months of follow-up, respectively. Genotyping of fifteen lipid-associated GWAS loci was performed by the MassArray-4 System. Linear regression analysis adjusted for sex, age, body mass index, and rosuvastatin dose was used to estimate the phenotypic effects of polymorphisms, and P-values were calculated through adaptive permutation tests. Over one-year therapy, a decrease in CIMT was linked to rs1689800, rs4846914, rs12328675, rs55730499, rs9987289, rs11220463, rs16942887, and rs881844 polymorphisms (Pperm<0.05). TC change was associated with rs55730499, rs11220463, and rs6065906; LDL-C change was linked to the rs55730499, rs1689800, and rs16942887 polymorphisms; and TG change was linked to polymorphisms rs838880 and rs1883025 (Pperm<0.05). In conclusion, the polymorphisms rs1689800, rs55730499, rs11220463, and rs16942887 were found to be predictive markers for multiple antiatherogenic effects of rosuvastatin in CAD patients.

Pasmo (Septoria linicola) is a fungal disease causing major losses in seed yield and quality, and stem fibre quality in flax. Pasmo resistance (PR) is quantitative and has low heritability. To improve PR breeding efficiency, the accuracy of genomic prediction (GP) was evaluated using a diverse worldwide core collection of 370 accessions. Four marker sets, including three defined by 500, 134, and 67 previously identified quantitative trait loci (QTL) and one of 52,347 PR-correlated genome-wide single nucleotide polymorphisms, were used to build ridge regression best linear unbiased prediction (RR-BLUP) models using pasmo severity (PS) data collected from field experiments performed during five consecutive years. With five-fold random cross-validation, GP accuracy as high as 0.92 was obtained from the models using the 500 QTL when the average PS was used as the training dataset. GP accuracy increased with training population size, reaching values >0.9 with training population size greater than 185. Linear regression of the observed PS with the number of positive-effect QTL in accessions provided an alternative GP approach with an accuracy of 0.86. The results demonstrate the GP models based on marker information from all identified QTL and the 5-year PS average is highly effective for PR prediction.

Titanium-based metal-matrix composites manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing high reinforcement content remains challenging. This study reports an improved manufacturing process for Ti-TiC enabling high reinforcement content and significant fracture strain concurrently: mechanical blending, followed by laser powder bed fusion and a single heat treatment. As-built microstructure shows both un-melted TiC particles and sub-stoichiometric TiC dendrites resulting from a partial dissolution of TiC particles. The heat treatment is shown to fully convert TiC dendrites into equiaxed TiC grains. Reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. Ti-TiC tensile samples reached fracture strains of up to 1.7%, Young’s moduli of up to 149 GPa and ultimate tensile strengths of up to 827 MPa. Lower TiC initial powder size distributions displayed the best mechanical performance.

Due to the nonlinear stiffness and fractional-order damping characteristics of some real suspension systems, coupled with the presence of viscoelastic materials, fractional-order nonlinear suspension system modeling has become a focus of research in recent years. In this study, an electric oil and gas actuator based on fractional-order PID position feedback control is proposed, through which the damping coefficient of the suspension system is adjusted to realize the active control of the suspension. A fractional order PID algorithm is used to control the motor's rotational angle to realize the damping adjustment of the suspension system. In this process, the road roughness is collected by the sensors as the criterion of damping adjustment, and the particle swarm algorithm is utilized to find the optimal objective function under different road surface slopes, to obtain the optimal cornering value. According to the mathematical and physical model of the suspension system, the simulation model and the corresponding test platform of this type of suspension system are built. The simulation and experimental results show that the simulation results of the fractional-order nonlinear suspension model are closer to the actual experimental values than those of the traditional linear suspension model, and the accuracy of each performance index is improved by more than 18.5%. The designed active suspension system optimizes the body acceleration, suspension dynamic deflection, and tire dynamic load to 89.8%, 56.7%, and 73.4% of the passive suspension, respectively. Notably, the designed fractional order PID control circuit for the motor shows better control results compared to the conventional PID control circuit. This study provides an effective theoretical and empirical basis for the control and optimization of fractional-order nonlinear suspension systems.

With the engineering system becoming more and more complex, the uncertainty factors have a more and more profound influence on the reliability and security of the engineering system. In recent years, Reliability-Based Design Optimization (RBDO) has been studied extensively in complex engineering system design. The research on reliability optimization design considering stochastic uncertainty has been comprehensive and widely used. However, the reliability optimization design considering mixed uncertainty has the disadvantages of large computation and imprecise convergence. This study proposes an RBDO method based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to overcome this challenge. In the method, PSO is used to solve the most probable point, while SA has excellent global optimization capability to acquire the global optimal solution. Finally, three examples are given to illustrate the advantages of the proposed method.

This article presents the development of an innovative Maximum Power Point Tracking (MPPT) strategy, utilizing a Particle Swarm Optimization (PSO) algorithm to improve the effectiveness of PV systems and expedite convergence. The new MPPT method incorporated a unique Swarm Self-Reinforcement Mechanism (SSRM) within the PSO algorithm, targeting quick convergence and excellent tracking accuracy. This approach enables the PSO to eliminate the fitness function that has the lowest value and subsequently reinforce it in the next iteration, revolving around the global maximum power point (GMPP). By applying this novel PSO-based method, the MPPT performance of PV systems was significantly improved, facilitating the algorithm to proficiently navigate through the solution space and quickly locate the GMPP, even in rapidly changing environmental conditions. The outcomes derived from this novel approach were contrasted with other algorithmic optimization methods, validating its superior convergence speed and tracking accuracy. Different swarm sizes were examined using SSRM, and the optimal swarm size for the system employing MPPT was identified to achieve the lowest convergence time (CT). The results showcased the impressive performance capabilities of this novel strategy, resulting in a time con-traction of up to 28% compared to the conventional PSO technique, where the optimal swarm size was found to be 5. This achievement marks a significant milestone in the evolution of PSO-based MPPT techniques, and paves the way for future advancements in this exciting field.

In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian Coherent Structures (LCS) in large-scale Direct Numerical Simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient, constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains requiring efficient search algorithms in large structured domains. While this manuscript focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication.

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity to the users in a coverage free zone. The main contributions of this work include two approaches to position the UAVs and to assign user equipment (UE) to each UAV, such that the sum-rate and the coverage probability of the network is maximized. An approach can be selected depending on the prevailing scenario. The first approach uses clustering algorithm to determine the 2D positioning of the UAV and a matching algorithm is used for UE assignment by considering the characteristics of the air-to-ground propagation channels as well as the impact of co-channel interference from ABSs. Then it uses exhaustive search on different altitudes to find the optimal altitude. In the second approach, 2D positioning and UE assignment are done similarly to the first approach. However, the sub-optimal altitude is estimated using particle swarm optimization (PSO). The first approach is suitable for a system which has computational resource constraints or lower probability of line of sight (LoS) links. In contrast, the second approach is suitable for data rate greedy systems or a higher probability of LoS links.

We explore the possibility to nd the usual quantum theories, within the formulation of a classic theory of mechanics in C⁴. Specically, by releasing the end-point of the integral of the action derived in C⁴, we derive the dynamic path length of the geodesic equation in C⁴. In the at case, the derived Hamilton-Jacobi equations, were identied as the usual Klein-Gordon equation, where the complex functional action S(z_i), is identied as the usual complex scalar field φ. Afterwards, we study the energy-momentum 4-d complex vector, in order to re-establish the usual covariant derivative of gauge theories.

The properties of the charged dark matters are discussed in terms of the new three-dimensional quantized space model. Because of the graviton evaporations, the very small Coulomb’s constant (k(dd)) of 10^-48 k and large gravitation constant (G_N(dd)) of 10⁶ G_N for the charged dark matters at the present time are expected. The tentative values of G and k are used for the explanation purpose. Therefore, F_c(mm) > F_g(dd) > F_g(mm) > F_g(dm) > F_c(dd) > F_c(dm) = 0 for the proton-like particle. Also, the gravitation constant has been changed with increasing of the time because of the graviton evaporation. In the present work, the B1, B2 and B3 bastons with the condition of k(mm) = k >> k(dd) > k(dm) = 0 are explained as the good candidates of the dark matters. Also, the particle creation, dark matters and dark energy could be deeply associated with the changing gravitation constants (G). It is expected that the changing process of the gravitation constant between the matters from G_N(mm) ≈ 10³⁶ G_N to G_N(mm) = G_N happened mostly near the inflation period. Therefore, during most of the universe evolution the gravitation constant could be taken as G_N(mm) = G_N. And the effective charges and effective rest masses of the particles are defined in terms of the fixed Coulomb’s constant (k) and fixed gravitation constant (G_N). Then, the effective charge of the B1 dark matter with EC = −2/3 e is (EC)_eff = −2/3·10⁻²⁴ e.

Biochar is a carbon-rich material that recently received attention due to its increasing agronomical potential. The agricultural utilization of biochar relates to its potential to act in the soil as a soil conditioner, nevertheless, the complex information on the direct dependence of biochar physical properties (texture, particle size) and corresponding leaching and availability of organic molecules (e.g. the polycyclic and heterocyclic organic compounds) and inorganic mineral salts (based on micro– and macroelements) are still not consistent. These aspects were addressed in our study. A multi-elemental analysis (ICP-OES) was used to access the information on the aqueous-extractable and total contents of inorganic macro- and macroelements in used commercial biochar samples (purchased from Sonnenerde GmbH, Novoterrra Sonnenerde GmbH, Biouhel.cz, s.r.o.). Potassium (K) was identified as the major macroelement, responsible for alkaline pH and the conductivity of biochar extract. Our results indicate an indirect relation between the size fraction of biochar and the content of extractable K, sodium (Na), and calcium (Ca) and a direct relation with the contents of phosphorus (P) and magnesium (Mg). As the total determined amounts of inorganic elements were significantly higher compared to aqueous-extractable amounts, we believe it could indicate the potential for repeated release to the surrounding soil. These findings were also confirmed by the analysis of biochar samples obtained after the cultivation (duration of 2 years) in selected representative soil samples from the Czech Republic (Cambisol, Fluvisol, Regosol, Chernozem). Moreover, gas chromatography (GC) coupled with mass spectroscopy (MS) was further used to reveal the concentrations of available polycyclic aromatic and heterocyclic compounds in biochar samples. The detected concentration of these types of organic compounds were far below the certified limits. We believe our in-depth analysis could provide the necessary insight into the description of biochar mineral content, its connection to biochar texture, corresponding physicochemical properties and potential availability to leach nutrients to the soil. These findings could help in further assessment of the potential applications of biochar in modern agriculture as a soil conditioner.

The crystals, C11H4BrF5N2S, (I), 1-((4-bromothiophen-2-yl)methylene)-2-(perfluorophenyl)hydrazine and C12H6BrF5N2S, (II), 1-((4-bromo-5-methylthiophen-2-yl)methylene)-2-(perfluorophenyl)hydrazine are molecules with two rings and hydrazone part like a centre of the molecule. The compounds have been synthesized and characterized by elemental, spectroscopic (¹H-NMR) analysis. The crystal structures of the solid phase were determined by single crystal X-ray diffraction method. They crystallize in the monoclinic space group with Z = 4 and Z = 2 molecules per unit-cell. The compound (I) crystallizes as a racemate in the centrosymmetric space group and the compound (II) crystallizes as a non-racemate in the non-centrosymmetric space group. The “absolute configuration and conformation for bond values” were derived from the anomalous dispersion (ad) for (II). The crystal structures are revealed diverse non-covalent interactions such as intra- and interhydrogen bonding, π-ring···π-ring, C-H···π-ring and they were investigated. The expected stereochemistry of hydrazones atoms C7, N2 and N1 were confirmed for (I) and (II). The hole molecule of the (I), and (II) possesses “a boat conformation” like a 6-membered ring. The results of the single crystal studies are reproduced with the help of Hirshfeld surface study and Gaussian software.

In the present work, three different atmospheric plasma sprayed (APS) alumina coatings were fabricated using three fused and crushed alumina powders of different particle size fine, medium and coarse. The influence of the particle size on thermal properties and micro-structural features of the produced coating were investigated by thermal insulation test and detailed image analysis technique, respectively. The analyzed micro-structural features include the total porosity, pore size (fine, medium, and large) and cracks. All types of cracks were considered in calculations as voids and were evaluated according to their sizes as pores. All spray parameters except the particle size were fixed throughout the spraying process. The results revealed that the fine starting powder has produced the densest coating with the lowest total porosity and that the total porosity increases with an increasing particle size. This was expected as powders of smaller particle size will reach a higher in-flight temperature and velocity than powders of bigger particle sizes as long as the same spray parameters are applied. However, a detailed image analysis investigation on the three produced coatings showed that the fraction of fine pores and cracks versus the total porosity is substantially higher in coatings produced by using fine starting powders than those produced using medium and coarse powders. In this work, a connection between the thermal insulation and the porosity fraction, which includes fine pores and cracks, was revealed.

Base excision repair (BER) is a cellular process that removes damaged bases arising from exogenous and endogenous sources including reactive oxygen species, alkylation agents, and ionizing radiation. BER is mediated by the actions of multiple proteins that work in a highly concerted manner to resolve DNA damage efficiently to prevent toxic repair intermediates. During the initiation of BER, the damaged base is removed by one of 11 mammalian DNA glycosylases resulting in abasic sites. Many DNA glycosylases are product inhibited by binding to the abasic site more avidly than the damaged base. Traditionally apurinic/apyrimidinic endonuclease, APE1, was believed to help turnover the glycosylases to undergo multiple rounds of damaged base removal. However, in a series of papers from our laboratory we have demonstrated that UV-damaged DNA binding protein (UV-DDB) stimulates the glycosylase activities of human 8-oxoguanine glycosylase (OGG1), MUTY DNA glycosylase (MUTYH), alkyladenine glycosylase/N-methylpurine DNA glycosylase (AAG/MPG), and single-strand selective monofunctional glycosylase (SMUG1), between three-to-five-fold. Moreover, we have shown UV-DDB can assist chromatin decompaction facilitating access of OGG1 to 8-oxoguanine damage in telomeres. This review summarizes the biochemistry, single-molecule, and cell biology approaches that our group used to directly demonstrate the essential role of UV-DDB in BER.

Abstract Antibacterial activities can be improved using mixed ligands. Mixed ligands involved in this research are sodium sulfadiazine (Na-sfz) and dithiocarbamate (ai-dtc). One-pot synthesis was used to synthesize ligand of aniline dithiocarbamate (ai-dtc) and the corresponding coordination compounds of [VO(sfz)(ai-dtc)] and [Zn(sfz)(ai-dtc)]. Crystals of ai-dtc, which grew from the solution when refrigerated after five days, were diffracted with technique of single crystal x-ray crystallography to reveal the structure. Other characterization techniques involving physicochemical parameters, FT-IR, UV-Vis and NMR (1H NMR and 13C NMR) were carried out on ligands of ai-dtc, sfz and corresponding coordination compounds. Differences in results of FT-IR, UV-Vis and NMR between ligands and their respective metal ions confirmed the coordination. The in vitro antibacterial studies showed that the ligands (not the metal complexes) had modest activity against Gram negative bacteria: Staphylococcus aureus, whereas, the coordination compounds had modest activities against the Gram negative bacteria: Escherichia coli and Pseudomonas aeruginosa.

The proximal part of the colon offers opportunities to prolong the absorption window following oral administration of a drug. In this work, we used computer simulations to understand how the hydrodynamics in the proximal colon might affect the release from dosage forms designed to target the colon. For this purpose, we developed and compared three different models: a completely-filled colon, a partially-filled colon and a partially-filled colon with a gaseous phase present (gas-liquid model).The highest velocities of the liquid were found in the completely-filled model, which also shows the best mixing profile, defined by the distribution of tracking particles over time. No significant differences with regard to the mixing and velocity profiles were found between the partially-filled model and the gas-liquid model. The fastest transit time of an undissolved tablet was found in the completely-filled model. The velocities of the liquid in the gas-liquid model are slightly higher along the colon than in the partially-filled model. The filling level has an impact on the exsisting shear forces and shear rates, which are decisive factors in the development of new drugs and formulations.

The minimum ignition energy (MIE) has been extensively studied via experiments and simulations. However, our literature review reveals little quantitative consistency, with results varying for f=1.0 from 0.324 to 1.349 mJ, and for f=0.9 from 0.22 to 0.944 mJ. Therefore, there is a need to resolve these discrepancies. This RANS study aims to partially address this knowledge gap. Additionally, it presents other flame evolution parameters essential for robust combustion design. Using the reactingFOAM solver we predict the threshold energy required to ignite the fuel mixture. For this, the single step using the Arrhenius law is selected to model ignition in the flame kernel of stochiometric and lean CH₄/air mixtures, allowing it to develop into a self-sustained flame. The ignition power density, an energy quantity normalised with volume is incrementally varied keeping the kernel critical radius r_s constant 0.5 mm in the quiescent mixture of two equivalence ratios fs 0.9, and 1.0, for varied operating pressures 1, 5 and 10 bar at constant initial temperature 300 K. The minimum ignition energy is validated with twelve independent 1 bar data sets both numerical and experiments. Finally, a mathematical formulation of MIE is devised, a function of pressure and equivalence ratio shows a slightly curved relationship.

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a Specular-Light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the Multi-Scale Normalized Cross Correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

Japan has the world’s largest old population ratio, and aging is an urgent societal issue. As global trends seem to be following Japan’s social changes, there is an emphasis on municipalities becoming more age-friendly. Hence, we examine the age-friendliness of 135 Japanese municipalities, selecting 240 resident architectural designers and constructors to assess their municipalities, using the Age-Friendly Cities and Communities Questionnaire (AFCCQ). The findings indicate that Japan lacks “outdoor spaces and buildings.” Additionally, the evaluation of “housing,” “community support and health services,” and “transportation” in populated municipalities in the past five years is significantly higher than those in depopulated ones. Age-friendliness is significantly affected in the AFCCQ total score (hereafter, Score) based on “housing,” “social participation,” “community support and health services,” “transportation” and “financial situation” evaluations. High specificity (0.939) was found when the Score was treated as a marker of depopulation and, therefore, an age-friendly approach is a necessary condition to prevent depopulation. Furthermore, a lack of “communication and information” is observed in municipalities with a higher rate of single-person households aged 65 years and above. Therefore, resident architectural designers’ and constructors’ assessments, combined with the AFCCQ can be a powerful tool in evaluating the age-friendliness of municipalities.

Background and Objectives: Rheumatic diseases often exhibit a complex pattern of comorbidities, including the increased occurrence of emotional disorders like anxiety and depression, which are closely related to the presence of chronic pain. Therefore, a multimodal approach is necessary for treatment, targeting both the physical and psychological functioning. Due to the increased burden within the healthcare context that emerged during the post-pandemic period, the need to adjust the content and length of psychological interventions became ubiquitous. In this way, the main objective of this study was to investigate the efficiency of a single-session, process-based psychological intervention for patients with rheumatic conditions and emotional comorbidities in a naturalistic, in-patient setting. Materials and Methods: After the screening, a total of 31 participants (Mage = 58.9, SD = 12.03) completed the single session intervention. The therapeutic protocol relied on a process-based cognitive-behavioural therapy framework aiming to improve cognitive, emotional and behavioural functioning. Assessments were conducted prior to the intervention, post-intervention and one month following the hospitalization. Results: Immediately after the intervention, significant reductions in dysfunctional cognitive and emotional processes, along with the improvement of behavioural strategies were observed. At the one-month telephonic evaluation, participants reported decreased pain, state anxiety and state depression levels. Conclusions: The single-session, process-based approach represents a promising intervention in healthcare contexts, targeting important psychopathological mechanisms in patients with rheumatic conditions. Future studies could clarify the extent to which these outcomes persist over time and their specific associations with anxiety and depressive symptoms, by using more controlled and rigorous trial designs.

Human Ribonuclease (RNase) 6 is a monocyte and macrophage-derived protein with potent an-timicrobial activity toward uropathogenic bacteria. The RNASE6 gene is heterogeneous in hu-mans due to the presence of single nucleotide polymorphisms (SNPs). RNASE6 rs1045922 is the most common non-synonymous SNP, resulting in a G to A substitution that determines an ar-ginine (R) to glutamine (Q) transversion at position 66 in the protein sequence. By structural analysis we observed that R66Q substitution significantly reduces the positive electrostatic charge at the protein surface. Here, we generated both recombinant RNase 6 -R66 and -Q66 protein variants and determined their antimicrobial activity toward uropathogenic Escherichia coli (UPEC), the most common cause of UTI. We found that the R66 variant, encoded by the major SNP rs1045922 allele, exhibited superior bactericidal activity in comparison to the Q66 variant. The higher bactericidal activity of R66 variant correlated with an increase in the protein lipopolysac-charide binding and bacterial agglutination abilities, while retaining the same enzymatic effi-ciency. These findings encourage further work to evaluate RNASE6 SNP distribution and its impact in UTI susceptibility.

Adult stem cells (ASCs) can be cultured with difficulty from most tissues, often requiring chemical or transgenic modification to achieve adequate quantities. We show here that mouse primary fibroblasts grown in suspension change from the elongated and flattened morphology observed under standard adherent culture conditions generating rounded cells with large nuclei and scant cytoplasm expressing the mesenchymal stem cell (MSC) marker (Sca1; Ly6A) within 24hrs. Based on this initial observation, we describe here a suspension culture method that, irrespective of the lineage used, mouse fibroblast, primary human somatic cells (fibroblasts, hepatocytes and keratinocytes), is capable of generating a high yield of cells in spheroid form which display expression of ASCs surface markers, circumventing the anoikis which often occurs at this stage. Moreover, mouse fibroblasts-derived spheroids can be differentiated into adipogenic and osteogenic lineages. Analysis of single cell RNA sequence data identified 8 distinct cell clusters with one in particular comprising approximately 10% of the cells showing high levels of proliferative capacity expressing high levels of genes related to MSCs and self-renewal as well as extracellular matrix (ECM). We believe the rapid, high-yield generation of proliferative, multi-potent ASC-like cells by the process we term suspension-induced stem cell transition (SIST) could have significant implications for regenerative medicine.

Currently Single Board Computers (SBCs) are sufficiently powerful to run Real-Time Operating Systems (RTOSs) and applications with real-time attributes and requirements. SBCs serve as a foundation in Industrial Internet of Things (IIoT). The NXP Semiconductors produces a series of SBCs based on ARM-processors for a variety of industrial applications. The continuous increase in real-time data generated by IoT devices adds further research issues about the efficiency of such systems and applications. The purpose of this research was to investigate the timing performance of an NXP TWR-K70F120M device with μClinux OS on running concurrently tasks with real-time features and constraints. A custom-built multithreaded application with specific compute-intensive sorting and matrix operations was developed and applied to obtain measurements in specific timing metrics, including task’s execution time, threads waiting time, and response time, under different threads variations. The performance of this device was additionally benchmarked and validated against favorite platforms, a Raspberry Pi4 and BeagleBone AI SBCs. The experimental results showed that this device stands well both in terms of timing and efficiency metrics. Execution times were quite lower than the others, by approximately 56% in the case of two threads, and by 29% in the case of thirty-two threads configurations.

Achieving high-yield potential is always the ultimate objective of any breeding program. However, various abiotic stresses like salinity, drought, cold, flood, and heat hampered rice productivity tremendously. Salinity is one of the most important abiotic stresses that adversely affect rice grain yield. The present investigation was undertaken to dissect new genetic loci, which are responsible for salt tolerance at the early seedling stage in rice. A bi-parental mapping population (F2:3) was developed from the cross between BRRI dhan28/Akundi, where BRRI dhan28 (BR28) is a salt-sensitive irrigated (boro) rice mega variety and Akundi is a highly salinity tolerant Bangladeshi origin indica rice landrace that is utilized as a donor parent. We report stable QTLs for salt tolerance from a common donor (Akundi) irrespective of two different genetic backgrounds (BRRI dhan49/Akundi and BRRI dhan28/Akundi). A robust 1k-Rice Custom Amplicon (1k-RiCA) SNP marker genotyping platform was used to genotype this bi-parental population. After eliminating markers with high segregation distortion, 886 polymorphic SNPs built a genetic linkage map covering 1526.5 cM of whole rice genome with an average SNP density of 1.72 cM for the 12 genetic linkage groups. A total of 12 QTLs for nine different salt tolerance-related traits were identified using QGene and inclusive composite interval mapping of additive and dominant QTL (ICIM-ADD) under salt stress on seven different chromosomes. All of these 12 new QTLs found unique, as no other map from the previous study has reported these QTLs in the similar chromosomal location and found them different from extensively studied Saltol, SKC1, OsSalT and salT locus. Twenty-eight significant digenic/epistatic interactions identified between chromosomal regions linked to or unlinked to QTLs. Akundi acts like a new alternate donor source of salt tolerance except for other usually known donors like Nona Bokra, Pokkali, Capsule, and Hasawi used in salt tolerance genetic analysis and breeding programs worldwide, including Bangladesh. Integration of the seven novel and stable QTLs (qSES1, qSL1, qRL1, qSUR1, qSL8, qK8, qK1) reported in this investigation will expedite the cultivar development that is highly tolerant to salt stress.

Glioblastoma (GBM) is one of the most aggressive solid tumors, particularly due to the presence of cancer stem cells (CSCs). Today the characterization of this type of cells with an efficient, fast and low-cost method remains an issue. Hence, we have developed a microfluidic lab-on-a-chip based on dielectrophoresis (DEP) single cell electro-manipulation to measure the two crossover frequencies: f_x01 in low frequency range (below 500 kHz) and f_x02 in Ultra High Frequency range (UHF, above 50 MHz). First, in vitro conditions were investigated. U87-MG cell lines were cultured in different conditions in order to induce an undifferentiated phenotype. Then, ex vivo GBM cells from patients’ primary cell culture, were passed through the developed microfluidic system and characterized in order to reflect clinical conditions. This article demonstrates that the usual exploitation of low frequency range DEP does not allow the discrimination of the undifferentiated from the differentiated phenotypes of GBM cells. However, the presented study highlights the use of UHF-DEP as a relevant discriminant parameter. The proposed microfluidic lab-on-a-chip is able to follow the kinetic of U87-MG phenotype transformation in a CSC enrichment medium and their cancer stem cells phenotype acquirement.

Current dry powder formulations for inhalation deposit a large fraction of their emitted dose in the upper respiratory tract where they contribute to off-target adverse effects and variability in lung delivery. The purpose of current study is to design a new formulation concept that more effectively targets inhaled dry powders to the large and small airways. The formulations are based on adhesive mixtures of drug nanoparticles and nanoleucine carrier particles prepared by spray drying of a co-suspension of leucine and drug particles from a nonsolvent. The physicochemical and aerosol properties of the resulting formulations are presented. The formulations achieve 93% lung delivery in the Alberta Idealized Throat model that is independent of inspiratory flow rate and relative humidity. Largely eliminating URT deposition with a particle size larger than solution pMDIs is expected to improve delivery to the large and small airways, while minimizing alveolar deposition and particle exhalation.

The greenhouse gases and air pollution generated by extensive energy use have exacerbated climate change. An electric-bus (e-bus) transportation system favors reducing pollution and carbon emissions. This study analyzed the minimization of construction costs for an all battery-swapping public e-bus transportation system. A simulation was conducted according to existing timetables and routes. Daytime charging was incorporated during the hours of operation; the two parameters of the daytime charging scheme were the residual battery capacity and battery-charging energy during various intervals of daytime peak electricity hours. The parameters were optimized using three algorithms: particle swarm optimization (PSO), a genetic algorithm (GA), and a PSO–GA. This study observed the effects of optimization on cost changes (e.g., number of e-buses, on-board battery capacity, number of extra batteries, charging facilities, and energy consumption) and compared the plug-in and battery-swapping e-bus systems. The results revealed that daytime charging can reduce the construction costs of both systems. In contrast to the other two algorithms, the PSO–GA yielded the most favorable optimization results for the charging scheme. Finally, according to the cases investigated and the parameters of this study, the construction cost of the plug-in e-bus system was lower than that of the battery-swapping e-bus system.

The effect of elastic constants, cij, on the nature (easy or difficult) of a cleavage system in YBa2Cu3O7−δ is investigated, by employing a novel three-dimensional eigenfunction expansion technique, based in part on separation of the thickness-variable and partly a modified Frobenius type series expansion technique in conjunction with the Eshelby-Stroh formalism. Out of the available three complete sets of elastic constants, the first constitutes an estimate, while the second assumes tetragonal symmetry. This leaves only the experimental measurements by resonant ultrasound spectroscopy, despite reported values of c12 and to a lesser extent, c66, being excessively high. The present investigation considers six through-thickness crack systems weakening orthorhombic YBCO mon-crystalline plates. More important, the present approach predicts whether a crack would propagate in its original plane/direction or deflect to a different one. This fracture mechanics criterion is then employed for accurate determination of the full set of elastic constants of mono-crystalline YBCO. Finally, generally unavailable results, pertaining to the through-thickness variations of stress intensity factors and energy release rates for a crack corresponding to symmetric and skew-symmetric hyperbolic cosine loads that also satisfy the boundary conditions on the bounding surfaces of an orthorhombic monocrystalline plate bridge a longstanding gap in the field.

The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis and skin psoriasis, albeit only for subsets of individuals with each condition. This suggests intersecting "nodes" in inflammatory networks at a molecular and cellular level may drive and/or maintain IMIDs, being “shared” between traditionally distinct diagnoses without mapping neatly to a single clinical phenotype. In line with this proposition, integrative tumour tissue analyses in oncology have highlighted novel cell states acting across diverse cancers, with important implications for precision medicine. Drawing upon advances in the oncology field, this narrative review will first summarise learnings from the Human Cell Atlas in health as a platform for interrogating IMID tissues. It will then review cross-disease studies to date that inform this endeavour, before considering future directions in the field.

Weed competitive ability (WCA) is a desirable key trait for the improvement of grain yield under direct-seeded rice (DSR) and the aerobic rice ecosystem. The present study targeted screening of 167 introgression lines (ILs) of a Green Super Rice (GSR) IR2-6 population derived from a cross between Weed Tolerant Rice 1 (WTR1) as the recipient parent and Y134 as the donor parent developed at IRRI for weed competitiveness in screen house conditions (SHC). The ILs were phenotyped for WCA traits such as early seed germination (ESG) and early seedling vigor (ESV) in Petri dishes and pot experiment conditions. The results of phenotypic variance revealed ESG-related traits, especially first germination count (1st GC) that positively correlated with second germination count (2nd GC), germination percentage (GP), total dry weight (TDW), total fresh weight (TFW), and vigor index (VI-1), whereas, in ESV, all the traits were positively correlated with each other except for three traits: root dry weight (RDW), 1st GC, and GP-2. The ESG and ESV traits are vital for weed competitiveness. A 6K SNP array was used to study the genetic association for the WCA traits. Forty-four QTLs for WCA traits were mapped on all chromosomes (except on chromosomes 4 and 8) through single marker analysis (SMA). Out of 44 QTLs, 29 were associated with ESG traits and 15 with ESV traits, with LOD scores of 2.93 to 8.03 and 2.93 to 5.04 and explained phenotypic variance ranging from 7.85% to 19.9% and from 7.85% to 13.2%, respectively. However, 31 QTLs were contributed by a negative additive allele from Y134, whereas a positive additive allele was contributed by WTR1 in 13 QTLs. Among them, two QTL hotspot regions were mapped on chromosome 11 (24.7-27.9 Mb) and chromosome 12 (14.8-17.4 Mb). The majority of the QTLs related to WCA traits were grouped into two QTL hotspots: QTL hotspot-I (qAFW11.1, qFC11.1, qFC11.2, qSC11.1, qGP-111.1, qGP-111.2, qTFGS11.1, qVI-111.1, and qVI-111.2) and QTL hotspot-II (qFC12.1, qFC12.2, qSC12.1, qFC12.2, qGP-112.1, qGP-112.2, qTFGS12.1, qTFGS12.2, qVI-112.1, qIV12.2, qFC12.1, and qGC12.2), and a few of them were co-localized on chromosomes 11 and 12. Further, we fine-tuned in the genomic regions of QTL hotspots and identified a total of 13 putative candidate genes on chromosomes 11 and 12 collectively. The present study is the first report on the genetic basis of WCA-related traits and the co-localized QTLs, which could be highly valuable in future breeding programs aiming to improve WCA in rice.

The relaxation processes induced by an exposure of the Ar matrices doped with CH4 (0.1 – 10%) to an electron beam were studied with a focus on the dynamics of radiolysis products – H atoms, H2 molecules, CH radicals, and energy transfer processes. Three channels of energy transfer to dopant and radiolysis products were discussed: by free charge carriers, free excitons and photons from the “intrinsic source” provided by emission of the self-trapped excitons. Radiolysis products along with the total yield of desorbing particles were monitored in a correlated manner. Analysis of methane transformation reactions induced by free excitons showed that the CH radical can be considered as a marker of the CH3 species. The competition between exciton self-trapping and energy transfer to the dopant and radiolysis products has been demonstrated. A nonlinear concentration behavior of the H atoms in doped Ar matrices has been established. Real-time correlated monitoring of optical emissions (H atom and CH3 radicals), particle ejection, and temperature revealed a nonmonotonic behavior of optical yields with a strong luminescence flash after almost an hour of exposure, which correlated with explosive pulse of particle ejection and temperature. The connection of this phenomenon with the processes of energy transfer and radical-radical recombination is discussed.

In this work, we investigated whether the Pseudo-Newtonian theory (PNP) is applicable to black hole solution in modified gravity. In this regard, as an example, a static spherically symmetric 4D AdS Schwarzschild Yang-Mills black hole in EinsteinGauss-Bonnet gravity is considered. Also, a brief discussion on the structure and horizons of this black hole spacetime is presented. We calculated angular momentum and energy in the framework of the general theory of relativity as well as in PNP theory. In both of these framework, a graphical comparison of angular momentum has been studied

This paper presents an Edge-based color image segmentation derived from the method of Particle Motion in a Vector Image Fields (PMVIF) that could previously be applied only to monochrome images. Instead of using an edge vector field derived from a gradient vector field and a normal compressive vector field derived from a Laplacian-gradient vector field, two novel orthogonal vector fields, directly computed from a color image, one parallel and another orthogonal to the edges, were used in the model to force a particle to move along the object edges. The normal compressive vector field is derived from the center-to-centroid vectors of local color distance images. Next, the edge vector field is derived by taking the normal compressive vector field, multiplied by differences of auxiliary image pixels to obtain a vector field analogous to a Hamiltonian gradient vector field. Using the PASCAL Visual Object Classes Challenge 2012 (VOC2012) and the Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500), the benchmark score of the proposed method is provided in comparison with those of the traditional PMVIF, Watershed, SLIC, K-means, Mean shift, and JSEG. The proposed method yields better RI, GCE, NVI, BDE, Dice coefficients, faster computation time, and noise resistance.

Real-time energy management of a converter-based microgrid is difficult to determine optimal operating points of a storage system in order to save costs and minimise energy waste. This complexity arises due to time-varying electricity prices, stochastic energy sources and power demand. Many countries have imposed real-time electricity pricing to efficiently control demand side management. This paper presents a particle swarm optimisation (PSO) for the application of real-time energy management to find optimal battery controls of a community microgrid. The modification of the PSO consists in altering the cost function to better model the battery charging/discharging operations. As optimal control is performed by formulating a cost function, it is suitably analysed and then a dynamic penalty function in order to obtain the best cost function is proposed. Several case studies with different scenarios are conducted to determine the effectiveness of the proposed cost function. The proposed cost function can reduce operational cost by 12% as compared to the original cost function over a time horizon of 96 hours. Simulation results reveal the suitability of applying the regularised PSO algorithm with the proposed cost function, which can be adjusted according to the need of the community, for real-time energy management.

The demand for polymer composites with improved mechanical and electrical properties is crucial for advanced aerospace, electronics, and energy storage applications. Single-walled carbon nanotubes (SWCNTs) and iron oxide (Fe₃O₄) nanoparticles are key fillers that enhance these properties, yet challenges like orientation, uniform dispersion, and agglomeration must be addressed to realize their full potential. This study focuses on developing SWCNTs/Fe₃O₄ epoxy composites by keeping the SWCNT concentration constant at 0.03 Vol.% and varying Fe₃O₄ concentrations at 0.1, 0.5, and 1 Vol.% with two different configurations: randomly orientated (R-) and magnetic field-assisted horizontally aligned (A-) SWCNTs/Fe3O4 epoxy composites and investigates the effects of filler concentration, dispersion, and magnetic alignment on the mechanical and electrical properties. The research reveals that both composite configurations achieve an optimal mechanical performance at 0.5 Vol.% Fe₃O₄, while A- SWCNTs/Fe3O4 epoxy composites outperformed at all concentrations. However, at 1 Vol.% Fe₃O₄, mechanical properties decline due to nanoparticle agglomeration, which disrupts stress distribution. In contrast, electrical conductivity peaks at 1 Vol.% Fe₃O₄, indicating that the higher density of Fe₃O₄ nanoparticles enhances the conductive network despite the mechanical losses. This study highlights the need for precise control over filler content and alignment to optimize mechanical strength and electrical conductivity in SWCNTs/Fe₃O₄ epoxy nanocomposites.

The aim of this pilot study was to investigate whether single nucleotide polymorphisms (SNP) in the gene encoding the catalytic subunit of glutamate cysteine ligase (GCLC) are associated with the risk and clinical features of psoriasis. A total of 944 unrelated individuals, including 474 patients with a diagnosis of psoriasis and 470 healthy controls, were recruited for the study. Six common SNPs in the GCLC gene were genotyped using the MassArray-4 system. Polymorphisms rs648595 (OR=0.56 95%CI 0.35-0.90, Pperm=0.017) and rs2397147 (OR=0.54 95%CI 0.30-0.98, Pperm=0.05) were associated with susceptibility to psoriasis in males. In the male group, diplotype rs2397147-C/C×rs17883901-G/G was associated with decreased risk of psoriasis (FDR-adjusted P=0.014), whereas diplotype rs6933870-G/G×rs17883901-G/G (FDR-adjusted P=0.045) showed association with increased disease risk in females. Joint effects of SNPs with tobacco smoking (rs648595 and rs17883901) and alcohol abuse (rs648595 and rs542914) on the risk of psoriasis were observed (Pperm≤0.05). Furthermore, we found multiple sex-independent associations between GCLC gene polymorphisms and various clinical features such as earlier disease onset, the psoriatic triad, and specific localizations of skin lesions. The present study is the first to show that polymorphisms of the GCLC gene are significantly associated with the risk of psoriasis and related to its clinical features.

Observations of ocean surface winds from Indian scatterometer SCATSAT-1 have been combined with background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium Range Weather Prediction (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. This is done by making use of concepts from the modern particle filter technique, which does not represent the model probability density function (PDF) following the Gaussian technique. The 6 hourly hybrid wind is generated for the entire year of 2018 and is validated using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform dataset (CCMP) and global buoy data from National Data Buoy Centre (NDBC). The results indicate potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and along swath biases. The study shows the generated hybrid winds have very high quality with respect to the already existing daily product available from ISRO.

A number of experiments suggest that the elementary particles are non-local entities. A dissipative self-organization, that treats particles as open systems may provide a better understanding of the underlying phenomena than conservative models. The proposed toy model is such an attempt. We found that self-gravitation (although accompanied by self-diffusion) may not only be compatible with the quantum phenomena but is perhaps the major reason for the existence of quantum fields. According to the proposed model, fields/particles (resemble those of the Standard Model) emerge from a dynamic self-organized medium (which we associate with vacuum dust) from competition between self-gravitation and self-diffusion. These forces produce turbulence in the form of vortices (which we call vacuum cells) that serve as the building blocks for fields and particles. Field/particle features and symmetries are based on their internal (intracellular) dynamics and vortex synchronization (intercellular dynamics). This model allows for rough estimations of relative field coupling strengths, the quantity of charges and flavors, the probabilities of quark transmutations, the dimensionality and the topologies of phase spaces, and other Standard Model parameters that came not from the theory but rather determined by experiment.

Single-confinement housing can pose welfare risks to domestic horses. This study investigated horses’ stress responses when confined to single stalls in different stable designs in a tropical savanna region to address a literature gap. In total, 23 horses were assigned to a stable with a central corridor and solid external walls (A) (N = 8), a stable with one side corridor and solid external walls (B) (N = 6) or a stable with a central corridor and no solid external walls (C) (N = 9). Air velocity, relative humidity, air temperature and noxious gases were measured inside the stables, and the heart rate and HRV of the horses were also determined. The relative humidity was lower in stable C than in stable A (p < 0.05), while the air temperature was higher in stable C than in stable B (p < 0.05) during the day. The airflow and ammonia levels were higher in stable C than in stables B and A (p < 0.01–0.0001). Overall, horses’ HRV in stable A was lower than in those in stables B and C (p < 0.05-0.01). Horses in stable A tended to experience more stress than those in other stables.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

It's a method to achieve energy savings in single-phase active power greater than that obtained with the "Fan Law" in electric machines applied to ventilation. Quantitative analysis methods were based on electrotechnical techniques, practiced with the corresponding laboratory equipment on the working materials (three prototypes of electric machines). The results obtained from experimentation on the test bench were recorded in tables that collect data of formulas, values, and physical units. The discussion provides a comprehensive comparative study, mainly between power (watts), active energy consumption (kWh), and rotational speed (revolutions per minute). The permanent magnet synchronous motor (PMSM) with the coupling of an RL circuit design does mechanical work at its maximum speed of 3000 (RPM) with only 6.3 (Watts), which is equivalent to 25.2% of the active power required by the single-phase induction asynchronous motor (or shaded pole motor), which required 25 (Watts) to rotate at 1690 (RPM). This translates to 75% lower active power with a 44% superiority in speed, resulting in a 75% savings in single-phase active energy (measured in kWh). The same occurs when comparing it to the universal AC motor (with brushes and wound rotor) to maintain a speed of 3000 (RPM); since it consumes 64.8 (Watts), which is 90.3% more single-phase active energy than that required to achieve the same rotational speed as the permanent magnet synchronous motor (PMSM). The study was conducted on all motors with the same impeller blade diameter and under identical air temperature and atmospheric pressure conditions.

Induction heating (IH) technology is widely recognized and utilized in residential applications due to its high efficiency and safe operating characteristics. Resonant inverter circuits are widely used in IH systems because of their high efficiency and ability to perform soft-switching. Among the various resonant inverters used in IH systems, the single-switch quasi-resonant (SSQR) inverter topology is typically preferred for low-cost and low-output-power applications. Despite its cost advantage, the SSQR topology has a relatively narrow soft-switching range, which can be unstable depending on the electrical parameters of the load and the resonant converter circuit. Accurately determining the capacitance value of the resonant capacitor and the inductance value of the induction coil, which are the key circuit elements of the SSQR induction cooker, is crucial for designing a reliable, efficient, and durable cooking system. In other words, there exists a critical relationship between the resonant converter circuit parameters, load characteristics, and safe operating conditions. Additionally, when considering closed-loop control methods used for power control and safety, selecting appropriate resonant circuit elements becomes vital in ensuring both reliable and efficient operation. This paper focuses on a novel and simplified design method for the SSQR inverter utilized in household appliances. The proposed method and its advantages in terms of the safe operating area of the switch are theoretically investigated and verified through simulations and prototype circuits.

The product is a centrifugal air extractor, whose objective is to extract the stale air of SARS-CoV-2 or Covid-19 (Coronavirus); designed for civil and commercial use, it works with a single-phase alternating current (AC) motor of 220 (V) and 50 (Hz), with high energy efficiency (EE). Developed under the Design Thinking methodology, by electromechanical simulation using NI Multisim 14.0 software, case design using Cfturbo 2020 R2.0 CAD software, and rapid 3D prototyping with the OverLord Pro printer; with a prototype of the conventional stator winding of a synchronous motor with a two-pole PMSM/IPM single-phase alternating current (AC) field winding and a 4000 (Gauss) ferromagnetic ceramic magnet rotor. Innovating online nº 15 of invention patent nº 381968 by Nikola Tesla, 5/1/1888.One of the objectives is to link the middle level or Technical Schools with the University system (and careers with a Technological profile) through Project B374 located in the Secretariat of Science and Technology (SCyT) of the National University of La Plata ( UNLP), whose title is: “Integrated Management of Design and Innovation. Contributions for a theoretical-conceptual and methodological review” by the Director: Mg. Federico del Giorgio Solfa. Just as links were sought with the Research and Development Laboratory of the Department of Industrial Design (LIDDI-FBA-UNLP) through its Director D.I. Pablo Ungaro and D.I. Ana Bocos. In 2021, the project participated in the INNOVAR National Contest of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCYT), Argentine Republic; in the "Covid-19 Projects" category, having been selected in the catalog of innovative products, won the 1st. "Covid-19 Projects" position of the National Agency for Research and Technological Development and local innovation (R+D+i) dependent on MINCYT.The results showed, according to the analysis of the test bench, that the PMSM/IPM type synchronous motor used in the centrifugal fan, with the innovation of the reactance-inductive control in series plus the capacitor in parallel, reduces the power by 67% (Watts) and active energy consumption (kWh), performing 56% more mechanical work (Joules) on the fluid air (with a 50% reduction in carbon footprint). Which leads us to the following conclusion: it is possible to develop centrifugal fans that save electricity (kWh) without the need to resort to (1) the "Fan Affinity Law", nor (2) the use of variable speed drives (VDF) or frequency (which are devices with complex and expensive electronics). Which would bring an enormous saving of the cost of electrical energy.

Land Surface Temperature (LST) estimation has been studied for several purposes, while the optimal method of estimating the LST has not been criticized yet. This research explores the optimum method in Land Surface Temperature (LST) estimation using LANDSAT-8 imagery data. Four different LST retrieval approaches, the Radiative Transfer Equation-based method (RTE), the Improved Mono-Window method (IMW), the Generalized Single-Channel method (GSC), and the Split-Window algorithm (SW), were calculated to present the LSTs over Buriram Town Municipality, Thailand. The calculated LSTs from these four methods were compared with the ground-based temperature data, taken on the same date and time of the employed LANDSAT-8 images. For this reason, the optimum method of the LST calculation was justified by considering the lowest normalized root means square error (NRMSE) values. As a result, the SW algorithm presents an optimum method in LST estimation. Regarding the SW, this algorithm requires not only the atmospheric profiles during satellite acquisition but also the retrieval of several coefficients. Besides, the LST retrieval method based on the SW algorithm is sensitive to water vapor content and coefficients. Although the SW algorithm is an optimum method explored in this study, it is emphasized that the adjustable values of coefficient response to the atmospheric state may be recommended. With these conditions, the SW algorithm can generate the land-surface temperature over the mixed land-use and land cover on the LANDSAT-8 images.

Recently, several research groups have reported on anomalous enhancement of the self-field critical currents, Ic(sf,T), at low temperatures in superconductor/Dirac-cone material/superconductor (S/DCM/S) junctions. Some papers attributed the enhancement to the low-energy Andreev bound states arising from winding of the electronic wave function around DCM. In this paper, Ic(sf,T) in S/DCM/S junctions have been analyzed by two approaches: modified Ambegaokar-Baratoff and ballistic Titov-Beenakker models. It is shown that the ballistic model is an inadequate tool to analyze experimental data from S/DCM/S junctions. The primary mechanism for limiting superconducting current in S/DCM/S junctions is different from the conventional view that the latter is the maximum value within the order parameter phase variation. Thus, there is a need to develop a new model for self-field critical currents in S/DCM/S systems.

Recently, Kayyalha et al. (Phys. Rev. Lett., 2019, 122, 047003) reported on anomalous enhancement of the self-field critical currents, I_c (sf,T), at low temperatures in Nb/BiSbTeSe₂-nanoribbon/Nb Josephson junctions. The enhancement was attributed to the low-energy Andreev bound states arising from winding of the electronic wave function around the circumference of the topological insulator BiSbTeSe₂ nanoribbon. In this paper, we show that identical enhancement in I_c(sf,T) and in the upper critical field, B_c2(T), at approximately same reduced temperatures, were reported by several research groups in atomically thin junctions based on a variety of Dirac-cone materials (DCM) earlier. Our analysis shows that in all these S/DCM/S systems the enhancement is due to a new superconducting band opening. Taking in account that several intrinsic superconductors also exhibit the effect of new superconducting band(s) opening when sample thickness becomes thinner than the out-of-plane coherence length, we strength our previous proposal that there is a new phenomenon of additional superconducting band(s) opening in atomically thin films.

The objective of the paper is to introduce new similarity measure for single valued neutrosophic sets based on logarithm function. We define logarithm similarity measure and their weighted similarity measure for single valued neutrosophic sets. Then we define hybrid logarithm similarity measure and weighted hybrid logarithm similarity measure for single valued neutrosophic sets. We prove the basic properties of the proposed measures. We then define an entropy function using logarithm function to determine unknown attribute weights. We develop a novel multi attribute group decision making strategy for single valued neutrosophic sets based on the weighted hybrid logarithm similarity measure. We address an illustrative example to demonstrate the effectiveness and aptness of the proposed strategies. We conduct a sensitivity analysis of the developed strategy. We also make a comparison between the obtained results from proposed strategies and different existing strategies in the literature.

Neutrosophic cubic set (NCS) is one of the important family members of neutrosophic hybrid sets. Neutrosophic cubic set has more strength than other family members of neutrosophic hybrid sets to express incomplete information due to the presence of interval valued neutrosophic set (IVNS) and single valued neutrosophic set (SVNS) in its structure. Cross entropy measure is one of the best way to calculate the divergence of any variable from the priori one variable. In this paper we first define a new cross entropy measure under NCSs environment which we call NC- cross entropy measure. We investigate the basic properties of NC-cross entropy. We also propose weighted NC-cross entropy and investigate its basic properties. We develop a novel multi attribute decision making (MADM) strategy based on weighted NC-cross entropy. To show the feasibility and applicability, we solve a MADM problem using the proposed strategy.

Inflammation involves the activation of innate immune cells and is believed to play an important role in the development and progression of both infectious and non-infectious diseases such as neurodegeneration, rheumatoid arthritis or cancer. Inflammation in the brain is marked by the upregulation of the translocator protein (TSPO) in microglia. Moreover, high TSPO levels are found, for example in macrophages during rheumatoid arthritis and in malignant tumor cells compared to its relatively low physiological expression. The same applies for cycloxygenase-2 (COX-2), which is constitutively expressed in the kidney, brain, thymus and gastrointestinal tract, but induced in microglia, macrophages and synoviocytes during inflammation. This puts TSPO and COX-2 in the spotlight as important targets for the diagnosis of inflammation. Imaging modalities, such as positron emission tomography and single-photon emission tomography, can be used to localize inflammatory processes and to track their progression over time. They could also enable to monitor the efficacy of therapy and predict its outcome. This review focuses on the current development of PET and SPECT tracers not only for the detection of neuroinflammation, but also for emerging diagnostic measures in infectious and other non-infectious diseases like rheumatic arthritis, cancer, cardiac inflammation and in lung diseases.

Foot-and-mouth disease virus (FMDV) causes the highly contagious foot-and-mouth disease, which is characterized by the appearance of vesicles in and around the mouth and feet of cloven-hoofed animals. BHK21 cells are the cell line of choice for the propagation of FMDV for vaccine production world-wide but vary in their susceptibility for different FMDV strains. Previous studies showed that the FMDV resistance of a certain BHK cell line can be overcome by using a closely related but permissive cell line for the pre-adaptation of the virus, but the adapted strains were found to harbor several capsid mutations. In this study, these adaptive mutations were introduced into the original Asia-1 Shamir isolate individually or in combination to create a panel of 17 Asia-1 mutants by reverse genetics and examine the effects of the mutations on receptor usage, viral growth, immunogenicity and stability. A single amino acid exchange from glutamic acid to lysine at position 202 in VP1 turned out to be of major importance for productive infection of the suspension cell line BHK-2P. In consequence, two traditionally passage-derived strains and two recombinant viruses with a minimum set of mutations were tested in vivo. While the passaged-derived viruses showed a reduced particle stability, the genetically modified viruses were more stable but did not confer a protective immune response against the original virus isolate.

Here we will explain the correlation between the Kerr-Newman diagram and the theory: RLC electrical modelling of a black hole and the early universe. We will develop a black hole model that describes and explains both theories. In the development of our analysis, we will emphasize the following conditions: M² > Q² + a², M² = Q² + a² and M² < Q² + a² and we will also analyse the condition in which the mass of a black hole reaches its critical mass M = Mc. We will demonstrate that the interpretation of the Kerr-Newman diagram is equivalent to the interpretation of the theory: RLC electrical modelling of a black hole and the early universe. Finally, we will generalize the proposed model for a black hole and propose a black hole model formed by negative particles, neutroniumd, which after reaching critical conditions of mass, pressure, volume, temperature, density, etc.; decays into a positively charged black hole, protoniu. Let us remember that both models are formed by charged particles of matter (they do not contain antimatter), but their vector configuration means that the net charges of both proposed black holes are zero.

One of the most widely available and extensively produced varieties of industrial hemp, which generates a substantial amount of consumer-increasing waste in the form of hemp cellulose. In this study, recycling with a compressed and high-speed method that combines crushing and alkali treatment effectively converts leftover hemp fiber into ultrafine powder. SEM (Scanning Electron Microscopy), AFM (Atomic Force Microscope), FTIR (Fourier-transform Infrared Spectroscopy), and XRD (X-ray Diffraction) examined the original morphology of hemp fiber treated with alkali, fiber heated to 200 ℃, and crushed powder. Particle size, crystallinity, fiber surface, and strength increased and decreased. It became apparent that fiber strength decreased and fiber roughness significantly increased after alkali treatment. Fiber increased significantly, and crystallinity decreased after crushing. It was simple and effective for converting the leftover hemp fiber into micron-sized powder. In about 3 to 5 minutes, approximately 1 kg of dry ultrafine powder with a particle size of 10.44 μm was produced. This production method will significantly enhance future industrial applications of waste hemp fiber.

This systematic literature review explores the burgeoning use of Artificial Intelligence (AI) in manufacturing systems, in line with the principles of Industry 4.0 and the growth of smart factories. In this landscape, AI is crucial in addressing the complexity and dynamism of contemporary manufacturing processes, including machine breakdowns, fluctuating orders and unpredictable job arrivals. This systematic literature review, conducted using the Scopus database and bibliometric tools, pursues two primary objectives. First, it identifies the prevailing trends in solving scheduling problems with AI and identifies the most commonly used AI techniques in the literature. Secondly, it analyses how authors have successfully employed AI to address production scheduling challenges in real-world industrial settings and assesses the benefits obtained by companies. The dynamic nature of manufacturing systems requires adaptive scheduling paradigms. AI, including Particle Swarm Optimization, Neural Networks, and Reinforcement Learning, is applied to optimize production processes, predict machine failures, and achieve substantial benefits. In real-world applications, these AI-driven solutions have led to reduced production costs, enhanced energy efficiency, and more efficient scheduling processes. AI is increasingly recognized as an essential tool in addressing the evolving challenges of modern manufacturing environments.

In this work, a generalized analogue to the Pauli spin matrices is presented and investigated. The proposed Hermitian spin matrices exhibit a general symmetry. The generalized spin projection operators are derived and the electrodynamics for hypothetical fermions are explored using the proposed spin matrices. The fermionic quantum Heisenberg model is constructed using the proposed spin matrices and comparative studies against simulation results using the Pauli spin matrices are conducted. Further analysis on key findings as well as discussions on extending the proposed spin matrix framework to describe hypothetical bosonic systems (spin-1) are provided.

Single particle analysis with cryogenic electron microscopy (cryo-EM) can determine high resolution structures of macromolecular assemblies. To reconstruct final three-dimension(3D) density map, a reliable initial model is essential and ab-initio reconstruction usually can avoid model bias. The grand challenge for ab-initio reconstruction is to alignment two-dimension(2D) low signal-to-noise ratio(SNR) of particle images with random and unknown parameters. Here we formulate a fast ab initio reconstruction method(named AlignFM) based on Fourier Mellin transform and particle-swarm intelligence optimization(PSO) algorithm. It enables simultaneous 2D alignment and 3D refinement, which can fast generate a reliable 3D map. After experiments on several real datasets. AlignFM shows high performance on fast ab initio reconstruction with a small amount of data.

The compilation summarizes results so far gathered in a project that investigates the atom with classical (Newtonian) physics. It posits that the atom’s wave-particle dual nature is real, objective and intrinsic; the wave gives rise to the cosmic vacuum field while the particle, of course, manifests condensed matter. Light’s π radians oscillation manifests, on molar scale, significant radial tension in the vacuum field, the effect, amongst others, causes molecular matter to precipitate out of the vacuum – so-called ‘molecular outflow’. Cosmic vacuum field radial tension relates to molecular mass, in other words, a mass-radius (M-R) relationship is uncovered. It is argued that using the M-R relation it is possible to perform a valid simulation of the cosmic physical reality. The three states of matter are meaningfully accounted for using the atom’s e-m radiation wavelength. It is explained that force, be it of any kind whatsoever, originates in the atomic waveform, i.e., the cosmic vacuum field.

To enable purposeful design and implementation of automated concrete technologies, precise assessment and prediction of the complex material flow at various stages of the process chain are necessary. This paper investigates the intermediate stage of the extrusion and deposition processes in extrusion-based 3D-concrete-printing, using a numerical model based on the Particle Finite Element Method (PFEM). In PFEM, due to the Lagrangian description of motion, remeshing algorithms and the alpha shape method are used to track the free surface during large deformation scenarios. The Bingham constitutive model was used for describing the rheological behaviour of fresh concrete. This model is validated by comparing the numerically predicted layer geometries with those obtained from laboratory 3D printing experiments. Extensive parametric studies were then conducted using the numerical simulation, delineating the influence of process and material parameters on the layer geometries, the dynamic surface forces generated under the extrusion nozzle and the inter-layer interactions.

In the literature of Low-Energy Nuclear Reactions (LENR), particle tracks in photographic emulsions (and other materials) associated with certain electrical discharges have been reported. Some Russian and French researchers have considered these particles to be magnetic monopoles. These tracks correspond directly to tracks created with a simple uniform exposure to photons without an electrical discharge source. This simpler method of producing tracks supports a comprehensive exploration of particle track properties. Out of 750 exposures with this method, elliptical particle tracks were detected, 22 of which were compared to Bohr-Sommerfeld electron orbits. Ellipses fitted to the tracks were found to have quantized semi-major axis sizes with ratios of ≈n²/α² to corresponding Bohr-Sommerfeld hydrogen ellipses. This prompts inquiry relevant to magnetic monopoles due to the n²/α² force difference between magnetic charge and electric charge using the Schwinger quantization condition. A model using analogy with the electron indicates that the elliptical tracks could be created by a bound magnetically charged particle with mass m_m = 1.45 × 10^-3 eV/c², yet with superluminal velocities. Using a modified extended relativity model, m_m becomes the relativistic mass of a superluminal electron, with m₀ = 5.11 × 10^-3 eV/c², the fine structure constant becomes a mass ratio and charge quantization is the result of two states of the electron.

A study of Bianchi Type I cosmological model is undertaken in the framework of creation of particles. To accommodate the creation of new particles, the universe is regarded as an Open thermodynamical system. The energy conservation equation is modified with the incorporation of a creation pressure in the energy momentum tensor. Exact solutions of the field equations are obtained (i) for a particular choice of the particle creation function and (ii) by considering the deceleration parameter to be constant. In the first model the behavior of the solution at late times is investigated. The physical aspects of the model have also been discussed. In the case of the second model we have restricted our analysis to the power law behaviour for the average scale factor. This leads to a particular form for the particle creation function. The behavior of the solution is investigated and the physical aspects of the model have also been discussed for the matter dominated era.

The Particle-In-Cell (PIC) method has been developed in order to investigate microscopic phenomena, and with the advances of computing power, newly developed codes have been used for several fields such as astrophysical, magnetospheric, and solar plasmas. PIC applications have grown extensively with large computing powers available on supercomputers such as Pleiades and Blue Waters in the US. For astrophysical plasma research PIC methods have been utilized for several topics such as reconnection, pulsar dynamics, non-relativistic shocks, relativistic shocks, relativistic jets, etc. PIC simulations of relativistic jets have been reviewed with the emphasis on the physics involved in the simulations. This review summarizes PIC simulations, starting with the Weibel instability in slab models of jets, and then focuses on global jet evolution in helical magnetic field geometry. In particular we address kinetic Kelvin-Helmholtz instabilities and mushroom instabilities.

Scientific knowledge evolves in small steps, with occasional backsteps to correct inaccuracies, all occurring within a competitive environment. This perspective for the first time looks at the history of latency-related RNA (LR-RNA) that was later renamed latency-associated transcript (LAT). At the 1986 International Herpesvirus Workshop (IHW) meeting in Leeds, England, Daniel L Rock and Anthony B Nesburn first reported the discovery of human herpes virus 1 (HSV-1) latency-related (LR)-RNA that is antisense to ICP0. Less than a month after the IHW meeting a paper was submitted to Science magazine and 8 months later appeared in print thanking “D. Rock for suggesting RNA complementary to the ICP0 message may be present in latently infected cells”. This perspective is not a review of LAT literature but intends to clarify the timeline of LAT discovery and subsequent breakthroughs such as reactivation, apoptosis, CD8+ T cell exhaustion, and LAT expression in different cell types detected during latency. While many review articles have been written about LAT since 1987, the most comprehensive and balanced review about LAT was written by Dr. David Bloom’s group (1). In this overview, I will discuss our original collaboration with Dr. Dan Rock and subsequent work that our group performed, which is still ongoing. Finally, I will discuss the controversies associated with LAT from its inception to current times.

Implant-supported-screw-retained prostheses are really popular. Some of the most frequent complications have been mechanical complications. These include abutment screw loosening or even screw fracture. Using an intermediate abutment can offer several advantages. However, little literature has been found regarding how this affects the mechanical behavior of dental restorations. This study focuses on understanding the mechanical behavior of implant-supported restorations with a transepithelial component compared to those with a direct implant-supported restoration. It was carried out by using the Finite Element Method (FEM) and was experi-mentally validated. The results showed that in the case of transepithelial-supported restoration, the prosthetic screw mounted over the transepithelial component suffers higher stress than the one screwed directly to the implant. After applying a cyclic fatigue load, it is experimentally proven that, in the transepithelial-supported restorations, the fuse changes from being the screw that goes to the implant, to being the upper one. As a conclusion we can say that the use of an intermediate abutment in dental restoration not only provides better protection to the rest of the dental restoration but also allows easier repair in the event of a fracture. This can potentially lead to more efficient procedures and improved patient outcomes.

Here, using the theory of electrical-quantum modelling of the neutron and proton as a three-phase alternating current electrical generator, we will analyse the proton decay and the inverse neutron decay and determine the following subatomic particles, Dproton, Protoniu, Dneutron and Neutroniumd.

Germanium (Ge) is a system-forming material of IR photonics for the atmospheric transparency window of 8 – 14 µm. For optics of the 3 – 5 µm range, more widespread silicon (Si), which has phonon absorption bands in the long-wave region, is predominantly used. A technology for growing Ge single crystals has been developed, allowing the production of precision optical parts up to 500 mm in diameter. Ge is used primarily for the production of transparent optical parts for thermal imaging devices in the 8 – 14 µm range. In addition, germanium components are widely used in a large number of optical devices where such properties as mechanical strength, good thermal properties and climatic resistance are required. A very important area of application of germanium is nonlinear optics, primarily acousto-optics. The influence of doping impurities and temperature on the absorption of IR radiation in germanium is considered in detail. The properties of germanium photodetectors are reported, primarily on the effect of photon drag of holes. Optical properties in the THz range are considered. The features of optical properties for all five stable isotopes of germanium are studied. The isotopic shift of absorption bands in the IR region, caused by phonon phenomena, which was discovered by the authors for the first time, is considered.

Single-sided deafness (SSD) refers to a condition where there is severe to profound Sensorineural hearing loss in one ear, while the other ear has normal or near-normal hearing. SSD can significantly impact an individual's ability to localize sounds, understand speech in noisy environments, and maintain spatial awareness, often resulting in a reduced quality of life and increased social isolation. In children with unilateral deafness, it can impede spoken language development and potentially impact cognitive abilities. Historically, there was a misconception that the unaffected ear could adequately support speech development in early cases and provide acceptable hearing function in adults. Consequently, SSD was frequently undertreated. However, advances in technology and a deeper understanding of the psychological and developmental impact of SSD have led to a shift in management strategies. Various treatment options are available for addressing SSD, but ongoing debate surrounds the most effective approach. These options include cochlear implants (CI), contra-lateral-routing-of-signal (CROS) devices, and bone conduction devices (BCDs). The aim of this study is to review the scientific evidence on different treatment options for SSD and compare their impact on the quality of life of individuals with this condition.

We are going to demonstrate the origin of dark energy, using a Hardwire similarity, a test that is carried out in terrestrial seismic with vibroseis in the search for gas and oil. In the first instance, we are going to analyse the mathematical function of Dirac's delta and compare it with the detonation of an explosive that is carried out in the search for gas and oil. Let's understand that in both cases a frequency spectrum is produced. We will also explain the meaning of a non-causal, zero-phase system; a causal system, of minimum phase, in order to determine the mathematical behaviour that corresponds to the Big Bang. Next, following the line of seismic, we will analyse a Hardwire Similarity to demonstrate that a vibroseis source, which generates a sweep, produces, in addition to the ideal sweep of fundamental frequencies, spurious harmonic frequencies and additional noise. We will show that this additional energy generated by the spurious harmonic frequencies and additional noise adds to the energy of the fundamental frequency sweep in analogy as dark energy does.

The structure of existing activated models is inherently deficient in reflecting the major role of the membrane filtration. This study developed and proposed a novel model, MASM, for the membrane activated process. The effective filtration size imposed by the membrane module, entrapping larger size particles was adopted as the basis of the proposed model. The model defined a modified COD fractionation, accounting for the captured COD fractions as additional model components and utilizing related mass balance relationships. It was implemented for testing the fate of soluble hydrolysable COD and system performance of super-fast membrane activated sludge based on real data for the characterization and process kinetics of domestic sewage and denim processing effluents. Model evaluation was carried for parallel systems with gravity settling and membrane filtration operated at a sludge age range of 0.5-2.0 d. Results reflected significantly better performance of super-fast membrane activated sludge system for both wastewaters, underlining that it was crucially important to account for the captured COD fractions to provide an accurate evaluation of system behavior and effluent quality. This should also be identified as the major shortcoming of the ASM models for evaluating and predicting system performance of activated sludge configurations with membrane separation.

This paper examines some of the largely neglected areas of opportunity to utilize skeletal space structure systems in support of modular, industrialized, economical, sustainable and digital future of the construction industry. In this context, the feasibility of future use of skeletal space structures is studied for a few classes of engineering structures, namely, residential apartment buildings, and offshore platforms, along with their suitability for reconstruction, renovation, modernization and retrofit of damaged buildings and urban areas of cultural heritage significance. Finally, the particulars of lean project management of space structures are discussed with emphasis on engineering and economic factors, production management, environmental aspects, quality management, and reliability, maintainability and sustainability considerations. This article concludes that skeletal space structures can fulfil many of the essential construction requirements of modern societies, especially those facing environmental challenges, all while allowing for design flexibility and mass customization.

Autonomous unmanned aerial vehicles (UAVs) require highly reliable navigation information. Generally, navigation systems with the inertial navigation system (INS) and global navigation satellite system (GNSS) have been widely used. However, the GNSS is vulnerable to jamming and spoofing. The terrain referenced navigation (TRN) technique can be used to solve this problem. In this study, to obtain reliable navigation information even if a GNSS is not available or the degree of terrain roughness is not determined, we propose a federated filter based INS/GNSS/TRN integrated navigation system. we also introduce a TRN system that combines batch processing and an auxiliary particle filter to ensure stable flight of UAVs even in a long-term GNSS-denied environment. As an altimeter sensor for the TRN system, we use an interferometric radar altimeter (IRA) to obtain reliable navigation accuracy in high altitude flight. In addition, a parallel computing technique with general-purpose computing on graphics processing units (GPGPU) is applied to process a high resolution terrain database and a nonlinear filter in real time on board. Finally, we verify the performance of the proposed system through software-in-the-loop (SIL) tests and captive flight tests in a GNSS unavailable environment.

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5−20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

In this paper, a multi-patch weakly singular isogeometric boundary element method (WSIGABEM) for two-dimensional elastostatics is proposed. Since the method based on the weakly singular boundary integral equation, the quadrature techniques, dedicated for the weakly singular and regular integrals, are applied in the method. A new formula for the generation of collocation points is suggested to take the full advantage of the multi-patch technique. The generated collo-cation points are essentially inside the patches without any correction. If the boundary conditions are assumed to be continuous in every patch, no collocation point lies on the discontinuous boundaries, thus simplifying the implementation. The multi-patch WSIGABEM is verified by the simple examples with analytical solutions. The feature of the present multi-patch WSIGABEM is investigated by the comparison with the traditional IGABEM. Furthermore, the combination of the present multi-patch WSIGABEM and the particle swarm optimization algorithm results in a shape optimization method in two-dimensional elastostatics. By changing some specific control points and their weights, the shape optimizations of the fillet corner, the spanner and the arch bridge are verified to be effective.

Quantum computing arrives. Preceded by Mādhava of Sangamagrāma and other Hindu mathematicians, around 1,500 CE, and our previous work, we show at least 4 quantum properties that are indeed universal in some number systems; here we use them to enable quantum computing. Using the sets B={0,1}, B^n, N, Z, Q, and Q*, one has +4 quantum properties that one can trust, as archetypes of easy communication to friends and foes, to ignoranti or cognoscenti, and for quantum consciousness. Therefore, this work applies to computer calculations, apps in cell phones, algebra, atoms, mathematics, physics, and the human mind.

In a complex working environment, the fault signal of the gearbox is greatly affected by the outside world, and fault feature recognition is difficult, so the fault diagnosis accuracy is difficult to meet the expected requirements. To solve this problem, this paper proposes a gearbox fault diagnosis method based on an optimized stacked denoising auto encoder (SDAE) and kernel extreme learning machine (KELM). Firstly, the Particle Swarm Optimization algorithm in Adaptive Weight (SAPSO) was adopted to optimize the SDAE network structure, and the number of hidden layer nodes, learning rate, noise addition ratio and iteration times were adaptively obtained to make SDAE obtain the best network structure. Then, the best SDAE network structure was used to extract the deep feature information of weak faults in the original signal. Finally, the extracted fault features are fed into KELM for fault classification. Experimental results show that, compared with existing commonly used methods of fault diagnosis, the fault diagnosis model proposed in this paper can reduce the influence of noise in the original signal can better learn the deep-level features in the original signal and has higher diagnosis accuracy, faster diagnosis speed and good generalization in fault diagnosis.

We present a new vision on the double-slit experiment (DSE), that does not use any waves or the so-called wave-particle duality. It is based on particles, viewed as localized vibrations. Rather than being illogical, or mysterious, the approach reproduces logically the interference patterns observed externally, using the well-known ``amplification of stimulated emission'' (ASE). The conservation of particle number is not observed. Different particles can present ASE with in-phase or counter-phase behavior, making the patterns observed for electrons, other particles, even atoms. The Law of the Excluded Middle (LEM) is not broken illogically in two-states macroscopically, but broken naturally in three or more states, microscopically, using ASE. Any particle supporting ASE, in-phase or counter-phase, can enter a DSE, and provide an external interference pattern. Frequency plays a role, while amplitude is not considered. This work is important in quantum computing, possibly saving cost, time, and welcoming more participants.

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment and improvements of its most basic as well as some of the very recent state–of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

Viral infections can endanger public health by causing serious illness, leading to pandemics and burdening healthcare systems. Moreover, in the situation of a global spread, disruptions occur in every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has huge implications for saving people’s lives, preventing spread of the diseases, and minimizing social and economic damages. In the last decades, polymerase chain reaction (PCR) based techniques have been frequently used to detect viruses in the clinic. However, in a situation where rapid virus detection is the primary measure in preventing the spread, as in the case of ongoing COVID-19 pandemic, disadvantages of PCR, such as long processing times and requirement of sophisticated laboratory instruments, have been faced. Due to the urgent need for accurate techniques for virus detection, biosensor systems involved in many applications in biological detection are being developed for rapid, real-time, and high-throughput detection of viruses. Among various sensing platforms, optical devices are of great interest due to their advantages such as high sensitivity and direct readout. In the current review, usability of sensing techniques depending on optical phenomena, such as fluorescence-based sensors, surface plasmon resonance (SPR), surface enhanced Raman scattering (SERS), optical resonators and interferometry-based platforms, is discussed for virus diagnostics applications. Then, we focus on an interferometric biosensor developed by our group, single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

Neutrosophic cubic set is the hybridization of the concept of neutrosophic set and interval neutrosophic set. Neutrosophic cubic set has the capacity to express the hybrid information of both the interval neutrosophic set and the single valued neutrosophic set simultaneously. As newly defined, little research on the operations and applications of neutrosophic cubic sets appear in the current literature. In the present paper we propose the score, accuracy functions for neutrosophic cubic sets and prove their basic properties. We firstly develop TODIM method to solve multi attribute group decision making in neutrosophic cubic set environment, which we call NC-TODIM. Also, we solve a MAGDM problem using the proposed NC-TODIM method to show the applicability and effectiveness of the developed method. We also conduct sensitivity analysis to show the impact of ranking order of the alternatives for different values of attenuation factor of losses for multi-attribute group decision making problem.

The principle of the constancy of the velocity of light, which stated that the light velocity is invariant to the motion of the emitter, was well established and directly proven by experiments. Interestingly, the further assumption that the light velocity is independent of the motion of the observer was, arguably, never directly proven by any experiment for a century. This paper proposed the design of two experiments to directly test this assumption, which tried to address some perceived technical difficulty in such experiments. One is to directly measure the light speed as to moving sensors. The experiment setup is designed in such a way that the concerns of time synchronization and dilation can be avoided. Another experiment is to test the isotropy of the light speed to a moving particle in the electromagnetic accelerator by measuring the momentum to acceleration ratio. The experiment result, if positive, will provide direct and solid proof of the assumption. Otherwise, it may imply a need for further investigation. Since the light speed invariance to moving observers is a key assumption of some fundamental physical theory, either way, the experiments will have significant meanings.

Swimming pools are examples of water-intensive facilities, where solutions for reducing economic and environmental costs are increasingly frequently searched. One of the solutions is the recovery of water from wastewater, including from washings obtained through the process of rinsing filter bed. The study objective was the qualitative and quantitative assessment of post-coagulation sludges, the main pollutant found in the washings. During the analyses, assessment of the sedimentation capabilities of the sludges was performed (gravitationally), particle size distribution was assessed (particle size distribution analyzer) and assessment of phytotoxicity with the use of plant indicators in short-term tests was performed (Lemna minor, Lepidium sativum, Sinapis alba, Raphanus sativus). The samples were collected from two independent circulations, which differed in terms of capacity and type of coagulant used. The tested post-coagulation sludges were characterized by high content of total suspended solids: in samples from Circulation 1 from 251 to 128 mg/l, in Circulation 2 from 489 to 228 mg/l. However, the sedimentation processes enabled significant separation of sludges. The hydrolyzed coagulant contributed to the improvement of sedimentation capabilities of sludges. Despite the fact that in many samples low sludge concentrations favored stimulation of plant growth, the post-coagulation sludges can constitute a hazard to plant growth, particularly in the long-term perspective.

The mushroom industry generates large amounts of stems, a co-product with valuable sensory and health characteristics. This work aimed to study the influence of particle size (L — &gt;0.510 mm; LI — 0.510-0.315 mm; SI—0.315-0.180 mm; S — &lt;0.180 mm) and species in the characterization and antioxidant activity of flours from stems of Agaricus bisporus (ABSF) and Pleurotus ostreatus (POSF). ABSF was rich in protein (14 g/100 g), calcium (428.23-700.77 mg/100 g), and sorbitol (22.57-26.60 g/100 g), while POSF in β-glucans (36.62-40.34 g/100 g) and linoleic acid (20.57-39.86 g/100 g of lipid). Both species were flush in amino acids with umami flavor. The highest hydration properties and oil holding capacity were exhibited in the S size of both species. ABSF showed elevated values for emulsifying activity than POSF. ABSF-S recorded the heightened antioxidant capacity in vitro, in consonance with the total phenolic compounds (0.91 mg/g). However, this antioxidant assays in POSF presented a positive correlation with β-glucans content. According to these results, there could be several food applications for these co-products, such as emulsifier stabilizer, sweetener or fortifier in the development of functional food.

In recent years, computer-aided analysis techniques have emerged as valuable tools in assisting dermatologists by providing objective and efficient analysis of skin cancer images. This paper utilizes the combination of the Contourlet Transform (CT) and Local Binary Pattern (LBP) techniques for accurately recognizing borders, contrast changes, and shapes of skin cancer images. These results often contain many features, leading to high computational costs and potential over-fitting issues. Hence, we applied Particle Swarm Optimization (PSO) to select the most informative and discriminating features, reducing the dimensionality while retaining important information for accurate classification. After reducing the feature set with PSO, we applied these sets to Machine learning classification algorithms: Support Vector Machine (SVM), Random Forest (RF), and Neural Networks (NN). The results show that SVM has the lowest time complexity of 0.0458 seconds, followed by the Neural Network at 0.08730 seconds, and the Random Forest model has the highest time complexity of 0.1622 seconds. The SVM and Neural Network models are faster to train than the Random Forest model, making them more suitable for real-time or latency-sensitive applications. We also compared our proposed model with the state-of-the-art models and obtained the accuracy of 86.9%, which is the highest among the models.

Mental stress state recognition using electroencephalogram (EEG) signals for real-life applications needs a conventional wearable device. This requires an efficient number of EEG channels and an optimal feature set. The main objective of the study is to identify an optimal feature subset that can best discriminate mental stress states while enhancing the overall performance. Thus, multi-domain feature extraction methods were employed, namely, time domain, frequency domain, time-frequency domain, and network connectivity features, to form a large feature vector space. To avoid the computational complexity of high dimensional space, a hybrid feature selection (FS) method of minimum Redundancy Maximum Relevance with Particle Swarm Optimization and Support Vector Machine (mRMR-PSO-SVM) is proposed to remove noise, redundant, and irrelevant features and keep the optimal feature subset. The performance of the proposed method is evaluated and verified using four datasets, namely EDMSS, DEAP, SEED, and EDPMSC. To further consolidate, the effectiveness of the proposed method is compared with that of the state-of-the-art heuristic methods. The proposed model has significantly reduced the features vector space by an average of 70% in comparison to the state-of-the-art methods while significantly increasing overall detection performance.

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

A novel metaheuristic optimization method is proposed based on an earthquake that is a geology phenomenon. The novel Earthquake Algorithm (EA) proposed, adapts the principle of propagation of geology waves P and S through the earth material composed by random density to ensure the dynamic balance between exploration and exploitation, in order to reach the best solution to optimization complex problems by searching for the optimum into the search space. The performance and validation of the EA are compared against the Bat Algorithm (BA) and the Particle Swarm Optimization (PSO) by using 10 diverse benchmark functions. In addition, an experimental engineering application is implemented to evaluate the proposed algorithm. Early results show a feasibility of the proposed method with a clearly constancy and stability. It is important highlight the fact that the main purpose of this paper is to present a new line of research, which is opened from the novel EA.

Safe sample transport is of great importance for infectious diseases diagnostics. Various treatments and buffers are used to inactivate pathogens in diagnostic samples. At the same time, adequate sample preservation, particularly of nucleic acids, is essential to allow an accurate laboratory diagnosis. For viruses with single-stranded RNA genomes of positive polarity, such as foot-and-mouth disease virus (FMDV), however, naked full-length viral RNA can itself be infectious. In order to assess the risk of infection from inactivated FMDV samples, two animal experiments were performed. In the first trial, six cattle were injected with FMDV RNA (isolate A22/IRQ/24/64) into the tongue epithelium. All animals developed clinical disease within two days and FMDV was reisolated from serum and saliva samples. In the second trial, another group of six cattle was exposed to FMDV RNA by instilling it on the tongue and spraying it into the nose. The animals were observed for 10 days after exposure. All animals remained clinically unremarkable and virus isolation as well as FMDV genome detection in serum and saliva were negative. No transfection reagent was used for any of the animal inoculations. In conclusion, cattle can be infected by injection with naked FMDV RNA, but not by non-invasive exposure to the RNA. Inactivated FMDV samples that contain full-length viral RNA carry only a negligible risk of infecting animals.