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Each substation is critically essential to the overall operation of the electrical power system. Potential dangers include thermal stress, noise, slip, trip, fall hazards, animal waste, and nonionizing radiation. These are the causes of joint failures of cables and overhead lines, failure of one or more phases of circuit breakers, and melting of fuses or conductors in one or more phases. These kinds of failures bring about a decline in the substation's level of dependability. On the consumer side, power cannot be received adequately because there are losses in the transmission line. To accomplish the objective of enhancing the voltage profile, the DG must be optimized. The substation's transient analysis utilizing a variety of factors, a study of faults and transients that occur in the substation and their effects using ETAP, and an optimization of a range of parameters using artificial intelligence techniques are all used for this goal. This paper offers the complete simulation of a 500kv substation. The simulation uses advanced software Electrical Transient Analyzer Program (ETAP) with detailed load flow analysis and short circuit study of the 500 kV substation system using ETAP software. From the ETAP-generated load flow details and the short circuit details, which are studied by varying loads or other parameters, these whole simulations are carried out multiple times using real-time data from the past eighteen months. A simulation data set contains data on both standard and different faulty conditions. In the 1st step, the normal and faulty conditions are classified. In the 2nd step, the reasons for fault occurrence include line-to-line, line-to-ground, and double line-to-ground using the Artificial Intelligence technique. In both steps, Catboost performs well, followed by Support Vector Machine and Logistic Regression. In the first step, Catboost classifies normal and faulty conditions with an accuracy of 98%, SVM is 96%, and Logistic regression is 93%. Again, in the 2nd step to identify different faulty conditions, the accuracies of Catboost SVM and Logistic Regression are 97%, 95%, and 92%, respectively. [ABSTRACT FROM AUTHOR]

The present study employs the improved F-expansion and modified exp (- Z (ς)) -expansion function methodologies to generate an enormous amount of novel wave solutions for the (2 + 1) -dimensional extended shallow water wave equation. This equation has widespread applications in many scientific and engineering domains, such as oceanography, hydraulic engineering, flood risk assessment, coastal engineering, tsunami modeling, environmental monitoring, and research on climate change. The improved F-expansion technique yields traveling wave solutions in the trigonometric and hyperbolic trigonometric formats while modified exp (- Z (ς)) -expansion function generates these solutions in the rational and linear forms in addition to trigonometric and hyperbolic trigonometric forms. In this regard, a wide range of solutions, which incorporate the kink pattern, Z-pattern, singular bell pattern or singular bright, anti-kink pattern, singular anti-bell pattern or singular dark, singular periodic pattern, singular pattern, singular complexiton pattern and plane pattern solitary wave solutions are generated via these two techniques. The physical significance of the solitons and singular solitons solutions that originated using these two analytical approaches are also discussed in this work. This work also discusses the stability analysis of the model. Applying the earlier described approach, provide a number of graphical representations, such as surface, 2D, and contour graphics, that illustrate the computational and fluctuating characteristics of the produced solutions. [ABSTRACT FROM AUTHOR]

In this article, we are going to discuss about how alternant codes over Eisenstein integers are crucial in today’s technologies especially in encoding data and correction of those data. Based on the parity check matrices of alternant codes, the codes are constructed with symbols from finite commutative local rings with unity of Eisenstein integers modulo n. Particularly, the factorization of x n - 1 is over the unit-ring of an appropriate extension of the finite local commutative ring of Eisenstein integers. These codes are built similarly to the BCH codes over the finite integer rings and provide a solid background for the process of encoding the data. This work further proved the applicability of the said algorithm for the purpose of error correction in the discussed alternant codes in order to improve transference effectiveness. Through analyzing the mathematical concepts behind as well as practical applications of alternant codes over Eisenstein integers the possibility of changing today’s technological setting is disclosed. The paper demonstrates that the purpose of the codes is to enhance data integrity and security and underlines that this is why they should be useful for modern communication systems and much more. [ABSTRACT FROM AUTHOR]

In applied research, fractional calculus plays an important role for comprehending a wide range of intricate physical phenomena. One of the Klein-Gordon model's peculiar case yields the Phi-four equation. Additionally, throughout the past few decades it has been utilized to explain the kink and anti-kink solitary waveform contacts that occur in biological systems and in the field of nuclear mechanics. In this current work, the key objective is to analyze the consequences of fractional variables on the soliton wave dynamic behavior in a nonlinear time-fractional Phi-four equation. Using the formulation of the conformable fractional derivative it illustrates some of the recovered solutions and analyze their dynamic behavior. The analytical solutions are drawn by using the extended direct algebraic and the Bernoulli Sub-ODE scheme. Various types of soliton solutions are proficiently expressed. Adjusting the specific values of fractional parameters allows to produce the periodic, kink, bell shape, anti-bell shape and W-shaped solitons. The impact of the conformable derivative on the precise solutions of the fractional Phi-four equation is demonstrated with a series of 2D, 3D and contour graphical representations. [ABSTRACT FROM AUTHOR]

During drilling operations, abnormal pore pressures pose significant risks including blowouts, wellbore collapse, and pipe sticking, emphasizing the need for accurate pore pressure estimation in geoscience exploration and drilling projects. However, current prediction methods, whether mathematical or statistical, have limitations. Manual mathematical approaches are prone to human error, while statistical methods excel in inferring variable relationships but fall short in predictive accuracy. In response, artificial intelligence (AI), particularly deep learning (DL), offers promising solutions. This study proposes an innovative framework leveraging AI and DL for efficient pore pressure prediction solely from 3D seismic data. The framework includes end-to-end strategies, from preprocessing seismic data to predicting pressure zones. Data sourced from the Roosevelt, Utah field comprising 375 traces is employed, labelled using Eaton's pore pressure calculation and Gardner's bulk density approximation. A DL model based on a simple deep neural network is integrated into the framework, incorporating techniques like training set resampling and hyperparameter optimization to enhance performance. Comparative analysis with state-of-the-art machine learning models validates the superiority of the proposed DL model. Results demonstrate its state-of-the-art performance, achieving 95.5% accuracy, 96.6% precision, 94.2% recall, and an F1-score of 95.3% in predicting pressure zones. This research showcases the potential of AI and DL in revolutionizing pore pressure prediction, offering advanced and cost-effective solutions to mitigate drilling-related risks in the oil and gas industry. [ABSTRACT FROM AUTHOR]

In this work, we use the ansatz transformation functions to investigate different analytical rational solutions by symbolic computation. For the (2+1)-dimensional Calogero-Bogoyavlenskii Schiff (CBS) model, we derive a variety of rational solutions, such as homoclinic breather solutions (HBs), M-shaped rational solutions (MSRs), periodic cross-rationals (PCRs), multi-wave solutions (MWs), and kink cross-rational solutions (KCRs). Their dynamic is shown in figures by selecting appropriate values for the pertinent parameters. The Calogero-Bogoyavlenskii-Schiff model describes the interface of Riemann waves in two spatial dimensions. The Riemann wave can be used to explain a wide range of physical phenomena, including internal ocean waves, tsunamis, tidal waves, and magneto-sound waves in plasmas.In addition, two different types of interactions between kink waves and M-shaped rational solutions are studied. The proposed model plays a crucial role in elucidating the internal structure of tangible composite phenomena in several fields such as nonlinear optics, wave behaviors in deep seas, plasma physics, and two-dimensional discrete electrical lattices. In order to verify the physical properties of the established solitons, we use constant parameter values to create 3D, 2D, and contour profiles of the solutions. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis is an inflammatory disease of the joints and their cartilage that causes rigidity and damage to the bone at their joint levels. This review discusses rheumatoid arthritis, its etiology, pathology, parthenogenesis, signs and symptoms as well as complications, diagnosis, treatment and therapy. Some patents are also discussed that contain the development of different techniques that have made a significant improvement in RA and other associated diseases. Treatment methods include the use of interleukins, tumor necrotic factor-alpha, sialoprotein and several other factors. Varieties of biomarkers are also incorporated in the diagnosis of RA. Our main focus centers on newer trends in dealing with RA. Currently, glucocorticoids (GCs) and nonsteroidal anti-inflammatory drugs (NSAIDs), for reducing pain and inflammation, are primarily used in the treatment of rheumatoid arthritis, while disease-modifying antirheumatic drugs (DMARDs) are the primary medication in the initial stages to prevent specific immune responses. NSAIDs and GCs only provide relief for pain, inflammation and joint stiffness in RA, while DMARDs are the main therapy. Biological therapies include chimeric anti-CD20 monoclonal-antibody, rituximab, inhibitors of tumor-necrosis factor-α (TNF-α) like etanercept, infliximab, adalimumab, a recombinant inhibitor of interleukin-1, anakinra, costimulation blocker and abatacept. Experimental biological therapies include TNF-α inhibitors, JAK inhibitors, anti-interleukin-6-receptor monoclonal-antibodies (mABs), and antibodies against vital molecules involved in the survival and development of functional B-cells. These newer treatment options have improved the treatment, leading to successfully remitting their symptoms in early diagnosis. This article reviews the literature in order to study the therapeutic options for RA therapy, covering the existing gold standards. [ABSTRACT FROM AUTHOR]

This paper applies the extended direct algebraic method (EDAM) for the first time to obtain the soliton solutions of the fractional Sasa–Satsuma equation (FSSE) with the descriptions of two fractional derivatives. To evaluate the optical soliton and some other solutions of the FSSE, the presented research applies the fractional beta and conformable derivatives. As a useful result of this research, several types of solitons have been identified, such as the single soliton, M-shaped, W-shaped, combined dark-bright, smooth dark, sharp dark, dark-bright, anti-bell shaped, and periodic. Among the nonlinear optics fields expanding at the fastest rate are optical solitons. A fundamental equation in the theory of optical fibers and telecommunications is the fractional Sasa–Satsuma equation. The transmission of femtosecond pulses in optical fibers as well as the interaction and propagation of ultrashort pulses in the sub-picosecond or femtosecond region are influenced by this equation. Additionally, the physical properties of the completed solutions are illustrated via contour, 3D, and 2D graphs. The EDAM is a practical and effective technique that offers a variety of avenues for future investigation. The fresh versions of the findings presented here have not been published in the full body of literature before. [ABSTRACT FROM AUTHOR]

In this paper, we employ some ansatz transformations to investigate various nonlinear waves for a well-known model, the generalized reaction Duffing model, including lump soliton, rogue waves, breather waves, Ma-breather, and Kuznetsov-Ma-breather. The standard Duffing equation is expanded upon in the generalized Duffing model, which adds more terms to take into consideration for more complex behaviors. The generalized reaction Duffing model is useful in many domains, such as electrical engineering, biomechanics, climate research, seismic research, chaos theory, and many more, due to its rich behavior and nonlinear dynamic. Lump soliton is a robust, confined, self-reinforcing wave solution to non linear partial differential equations. Breather waves are periodic, specific solutions in nonlinear wave systems that preserve their amplitude and structure. Rogue waves, which pose a hazard to marine safety, are unexpectedly strong and sharp ocean surface waves that diverge greatly from the surrounding wave pattern. They frequently appear in solitary and apparently random situations. The solutions are graphically displayed using contour, 3D, and 2D graphs. [ABSTRACT FROM AUTHOR]

Maize cultivation is under the growing threat of charcoal rot (Macrophomina phaseolina). Chemical control of diseases imparts serious health hazards to humans and the ecosystem. Biochar as an alternative disease management approach has been under consideration of the researchers for some time now. The biochar utilized in this study was derived from maize stalks and cobs. Crystallographic structure, inorganic minerals content and size of maize biochar were analyzed by powder X-ray diffractometer, while scanning electron microscopy revealed rough, irregular, tubular structure of the biochar surface. EDX spectra revealed that the maize biochar composition was dominated by 'C' followed by 'O'. The current study was designed to determine the synergistic effect of maize biochar (MB), and biocontrol agent (BCA) Trichoderma viride as soil amendments on the suppression of M. phaseolina. In vitro bioassays were conducted to check the efficiency of antagonistic effect of Trichoderma spp., in combination with maize biochar. On the basis of maximum mycelial growth inhibition T. viride was selected for a glasshouse experiment. Maize plants were grown in pots containing a mixture of soil with MB at application at the rate of 3 and 6% (v/v) separately, associated with or without T. viride. Treatments amended with 3% MB inoculated with M. phaseolina significantly reduced the percentage disease severity index by 40%. While in the presence of T. viride, 3% MB showed maximum disease suppression and a minimum percentage severity index i.e. 60 and 20%, respectively. Highest nitrogen contents were 18.4 g kg−1 observed in treatment 6% MB, while highest phosphorus and potassium contents were 3.11 and 15.2 g kg−1, respectively in the treatment with 3% MB. Conclusively, the effect of variable concentrations of maize biochar and T. viride as soil amendment was evident on the development of charcoal rot, growth and physiology of maize plants. According to the available literature, our report is the first on the implementation of biochar in synergism with T. viride to suppress the charcoal rot in maize. [ABSTRACT FROM AUTHOR]

In this research, we use several ansatz transformations to study analytical solutions of different nonlinear waves (such as lump soliton, periodic waves, multi-waves, lump one kink, and lump two kink) for a well-known model, the Landau–Ginzburg–Higgs model. The Landau–Ginzburg–Higgs (LGH) model combines concepts from particle physics and condensed matter physics to describe phase transitions and symmetry-breaking processes. It integrates the particle physics concepts of the Higgs mechanism, the Landau theory of phase transitions, and the Ginzburg-Landau theory of superconductivity. A lump soliton is a confined wave phenomenon that travels through a medium without changing form or amplitude. These solitons are produced in a variety of nonlinear systems, including optical fibers and some kinds of fluid dynamics equations, where they are essential for transferring energy and information. Periodic waves are defined by consistent, recurring oscillation patterns in both space and time. These waves are essential to many technology applications and natural phenomena, such as electromagnetic radiation and ocean waves. A confined wave disturbance with a single sudden shift in amplitude is referred to as a soliton with one kink, or single-kink soliton. A soliton with two kinks is a solution for a solitary wave that has two localized areas where the wave profile bends or alters abruptly. The solutions are graphically displayed using contour, 3D, and 2D graphs. [ABSTRACT FROM AUTHOR]

The main objective of this study is to provide a comprehensive and inclusive review of current research on sustainable entrepreneurship (SE). One of the aims of this study is to navigate the understanding of SE practices by investigating the prospects and trends in research on sustainable entrepreneurship. It seeks to present an efficient portrayal of the latest research on sustainable entrepreneurship, serving as a valuable reference for scholars, practitioners, and policymakers. By applying the PRISMA approach, this study is based on a systematic literature review (SLR), and a substantial pool of 363 Scopus results and 291 WOS results was obtained using the keyword "sustainable entrepreneurship," yielding a total of 654 articles that may be deemed possibly relevant. After the methodological screening, 234 mainly chosen studies using databases, including Scopus and WOS. This SLR utilizes thorough descriptive, Network, and thematic analysis, research tendencies, and methodological approaches. The findings of this study discussed the possible research gaps and future trends, suggesting the significant need for a stable framework for SE concepts. Empirical and exploratory studies are linked with social, economic, and technological scope, specifically sustainability, and are related to artificial intelligence (AI) studies. It contributes to laying the groundwork for future investigations into the critical connection between entrepreneurship and sustainability. Furthermore, given the continuously changing landscape of sustainable business, certain conclusions may be outdated. [ABSTRACT FROM AUTHOR]

In this article, the modified extended Fan sub-equation approach as an analytical tool to investigate the optical soliton solutions of the paraxial wave dynamical model with Kerr media. Indistinguishable and non-diffractive spatially scattered waves transmitting in the optical Kerr medium are explained by optical solitary waves. The solitons, single and mixed non-degenerate Jacobi elliptic function type solutions of the time-dependent dimensionless paraxial wave equation are assembled using the modified extended Fan sub-equation approach. The aforementioned approach offers new, comprehensive solutions that are relatively easy to implement, in contrast to earlier continuous strategies. This technique uses a traveling wave transformation to convert a non-linear partial differential equation into an ODE. The developed wave solutions have substantial significance in the fields of science and engineering. Visual illustrations of various soliton layouts can be achieved by supplying suitable values for the parameters via this technique. The computer software Mathematica 13.2 is used to illustrate several modulus, real, and imaginary solutions visually in the form of contour, 2D, and 3D visualizations that help understand the concrete importance of the paraxial wave dynamical model. The results are fascinating and can potentially be helpful in investigating the stochastic aspects of many nonlinear physical theories that arise in optical studies and a number of other scientific fields. [ABSTRACT FROM AUTHOR]

Nonlinear partial differential equations (NLPDEs) are used in a wide range of natural and applied sciences phenomena. A fascinating and rapidly developing scientific field is the study of soliton solutions to nonlinear evolution equations (NLEEs). In this research, different types of soliton solutions for the strain wave model (SWM) are derived by using the F-expansion method (FEM) and the Bernoulli Sub-ODE method (BSODE) scheme. This equation plays an important role in engineering and mathematical physics. The acquired solutions in this work include compactons, bell-shaped soliton, dark, bright, kink soliton and periodic solutions. These precise solutions help researchers to understand the physical phenomena of this wave equation. [ABSTRACT FROM AUTHOR]

The aim of our study is to develop a simple, delicate, precise and economical protocol for the qualitative and quantitative determination of Chlorpheniramine using spectrophotometer. Our validation is distinctive and provides a precise picture of a very weak chromophore of chlorpheniramine (CPN) that had not been accurately detected before by traditional techniques. The blue color which formed by mixing pheniramine and Cobalt- thiocyanate solution was extracted with chloroform. CPN presented a linearity range of 25 – 125 μg at 628 nm. Limit of quantification (15 μg/mL) and limit of detection (08 μg/mL) of cobalt-chloride were analyzed. The resulting data was statistically significant. Because of the appropriate reproducibility and reliability of this proposed analysis, it can be used to screen CPN in pharmaceutical preparations. It is also validated through the International Council of Harmonization for accuracy, linearity, precision, LOD and LOQ. Various dosage forms of pheniramine were evaluated and have shown that they did not exceed their relative standard deviation by 1%. Their percentage purity was within 99.62 – 103.34%. The suspected sample was treated with 2 – 3 drops of cyanocobalamine after which violet coloration appeared. The percentage relative standard deviation of accuracy and precision was acquired as 1.57 and 1.15, respectively, exactly following the authentication criteria for newly established methods. Because of the profound potential of these developed methods, including precise, fast, flawless and inexpensive, it can easily be adopted in laboratories for the routine analysis of Chlorpheniramine. [ABSTRACT FROM AUTHOR]

In this article, the Bernoulli sub-ODE and generalized Kudryashov methods have been successfully used to look for travelling wave solutions for the coupled non-linear evolution equations including the coupled Higgs equation and the Maccari system. The aforementioned approaches provide more new broad solutions than the previous ones now in use and are straightforward to apply. In both techniques, a travelling wave transformation is employed to convert non-linear partial differential equations into an ordinary differential equation. The solitary wave solutions are also generated from the travelling wave solutions when the parameters are considered as unique values. Several soliton solutions are generated for various parameter combinations. Numerous innovative solutions have been created by using Bernoulli sub-ODE and generalized Kudryashov approaches, including the periodic wave, kink wave, bell shape, anti-bell shape, M-shape, V-shape, W-shape, Z-shape, bright, dark and singular soliton solutions. To demonstrate how the Bernoulli sub-ODE and generalized Kudryashov approaches can be used to uncover the analytical solutions of the coupled Higgs equation and the Maccari system, replicate many figures in computer software Mathematica 13.2 along with several 3D, 2D, and contour plots. The similarities, contrasts, advantages and disadvantages of the two analytical techniques are examined. It has been demonstrated that the travelling wave solutions generated by these two analytical techniques, each using a different basis equation, have unique characteristics. The outcomes show that the methods used may reliably identify wide-spectral stable travelling wave solutions to non-linear evolution equations that appear in a variety of scientific, technical, and engineering disciplines. [ABSTRACT FROM AUTHOR]

The impact of nitrogen (N) and boron (B) foliar applications on Solanum melongena growth, yield, and phytochemicals was studied. The impact of foliar applications using N levels (0, 0.25%, 0.5%, and 1%) and B levels (0, 0.1%, 0.25%, and 0.5%) following a randomized block design with three replications was studied. With the increase in N level, the yield characters increased. Foliar application of N shows the maximum height of plant (112.5 cm), number of leaves (186.0), leaf area (46.20), number of branches (7.67), number of blossom flowers/plant (21.25), number of fruits/plant (11.42), fruit length (10.97 cm), fruit width (7.39 cm), fruit volume (305.7), fruit weight (12.67 g), fruit yield (12.78), protein (10.9%), total carbohydrates (27.5%), and crude fiber (7.21%) while decreasing minimum days at 50% appearance of flowers (48.0). In the case of B application, the maximum height of the plant (112.0 cm), number of leaves (187.6), leaf area (47.82), number of branches (7.67), number of blossom flowers/plant (22.08), number of fruits/plant (11.33), fruit length (10.95 cm), fruit width (7.35 cm), fruit volume (298.0), fruit weight (206.1 g), fruit yield (12.13), protein (9.31%), carbohydrates (30.2%), TSS (4.20), crude fiber (7.34%), DPPH (4.68 mg/mL), Chl a (1.39), Chl b (0.53), TPC (60.78), DAO activity (81.43), and PAO activity (39.10) were observed, while decreasing minimum days at 50% appearance of flowers (48.33). Application of N at 0.5% and B at 0.25% increased the growth, yield parameters, and phytochemical contents of S. melongena. The impact of different nitrogen and boron foliar applications on eggplant growth, phytochemicals, and quality attributes is significantly improved. [ABSTRACT FROM AUTHOR]

Key message: TheDof22gene encoding a deoxyribonucleic acid binding with one finger in maize, which is associated with its drought tolerance. The identification of drought stress regulatory genes is essential for the genetic improvement of maize yield. Deoxyribonucleic acid binding with one finger (Dof), a plant-specific transcription factor family, is involved in signal transduction, morphogenesis, and environmental stress responses. In present study, by weighted correlation network analysis (WGCNA) and gene co-expression network analysis, 15 putative Dof genes were identified from maize that respond to drought and rewatering. A real-time fluorescence quantitative PCR showed that these 15 genes were strongly induced by drought and ABA treatment, and among them ZmDof22 was highly induced by drought and ABA treatment. Its expression level increased by nearly 200 times after drought stress and more than 50 times after ABA treatment. After the normal conditions were restored, the expression levels were nearly 100 times and 40 times of those before treatment, respectively. The Gal4-LexA/UAS system and transcriptional activation analysis indicate that ZmDof22 is a transcriptional activator regulating drought tolerance and recovery ability in maize. Further, overexpressed transgenic and mutant plants of ZmDof22 by CRISPR/Cas9, indicates that the ZmDof22, improves maize drought tolerance by promoting stomatal closure, reduces water loss, and enhances antioxidant enzyme activity by participating in the ABA pathways. Taken together, our findings laid a foundation for further functional studies of the ZmDof gene family and provided insights into the role of the ZmDof22 regulatory network in controlling drought tolerance and recovery ability of maize. [ABSTRACT FROM AUTHOR]

The dynamic behavior of the Vakhnenko-Parkes equation is examined in this manuscript. This is an important subject because of its implications for comprehending intricate mathematical models describing traveling wave phenomena and solitons. The construction of traveling wave solutions for the Vakhnenko-Parkes equation in closed form is the main issue addressed in the study. The modified auxiliary equation approach and the extended (G ′ G 2) -expansion method are used to address this because they are effective in producing precise solutions of a large class of nonlinear partial differential equations. A visual component to comprehending the behavior of the equation is added by employing 3D-surface graphs, 2D-line graphs, and contour plots to explore these solutions graphically. A variety of traveling wave behavior is observed from the obtained solutions. These results imply that the Vakhnenko-Parkes equation and its solutions are complex, offering important insights into the underlying dynamics. The proposed techniques are applied for the first time to study the considered model in this work. A comparison of the obtained results with the previous works is presented to confirm the significance and novelty of the reported results. [ABSTRACT FROM AUTHOR]

Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing odor evaluation methods are subjective, costly, and potentially harmful to the health of evaluators. In this study, we analyzed 139 automotive interior parts and 92 vehicles, establishing a cost-effective, data-driven method for odor evaluation. The contents of benzene, toluene, ethylbenzene, xylene, styrene, formaldehyde, acetaldehyde, acrolein, and total volatile organic compounds (TVOC) were detected by thermal desorption gas chromatography-mass spectrometry (TD-GC/MS) and high-performance liquid chromatography with an ultraviolet detector (HPLC–UV). Professional odor evaluators assessed the odors, identifying intensity levels from 2.0 to 4.5 in interior parts and 2.5 to 3.5 in whole vehicles. Leveraging this data, we applied four supervised learning algorithms to develop predictive models for the odor intensity of both interior parts and entire vehicles. During model training, we implemented early stopping techniques for the artificial neural network (ANN) and convolutional neural network-bidirectional long short-term memory (CNN-BiLSTM) models, while optimizing the support vector machine (SVM) and extreme gradient boosting (XGBoost) models using the GridSearch algorithm. The evaluation results reveal that the CNN-BiLSTM model performs the best, achieving an average accuracy of 89% for unknown samples within an odor intensity level of 0.5. The root mean square error (RMSE) is 0.24, and the mean absolute error (MAE) is 0.08. The model also underwent a sevenfold cross-validation, achieving an accuracy of 83.43%. Additionally, we employed SHapley Additive exPlanations (SHAP) for the interpretative analysis of the model, which confirmed the consistency of each VOC's odor contribution with human olfactory rules. By predicting odors based on VOCs through supervised learning, this study reduces the costs and enhances the efficiency and applicability of odor assessment across various vehicle interiors. [ABSTRACT FROM AUTHOR]

Fractional order nonlinear partial differential equations are useful for detailing many practical models in multidisciplinary fields. In theory and numerical studies, recognizing solitary wave solutions to these equations is therefore preferable. The nonlinear properties of the fractional Peyrard Bishop DNA (FPBDNA) model make it relevant to several areas in integrable systems and nonlinear dynamics. The mathematical properties of the model, such as integrability and soliton solutions, have been examined by mathematicians to comprehend the behavior of nonlinear systems. In this article, we demonstrate how our techniques might be applied in a real life scenario like FPBDNA model. The soliton solutions to this model are determined using two effective analytical techniques namely the bernoulli sub ODE method and the modified khater method. These solutions have been obtained by using β and M-truncated derivatives. It is assumed that the obtained results have never been found in previous literature. The discovered solitons are smooth dark and bright, compactons, bell-shape and cuspon, peakon, anti-peakon, dark singular, bright singular, dark periodic singular, and kink-type solitons. The physical description is given using 2D and 3D for a finer perception. [ABSTRACT FROM AUTHOR]

In this work, the (2+1)-dimensional Painlevé integrable Burgers equation is investigated. By applying a certain unified method, some analytical solutions, involving rational functions, trigonometric functions and hyperbolic functions, are achieved. In order to predict the wave dynamics, several three-dimensional and two-dimensional graphs and contour profiles are constructed. Bright, dark, periodic, kink, anti-kink, singular, singular periodic, bell-shaped waves are thus obtained. The dynamics of these solutions can be illustrated graphically by choosing appropriate values for the parameters involved. Due to the presence of arbitrary constants in these derived solutions, they can be used to explain a variety of qualitative traits present in wave phenomena. The approach is efficient to algebraic computation and it can be used to categorize a wide range of wave forms, as shown by the demonstrated soliton solutions. Travelling wave solutions are converted into solitary wave solutions when certain values are set for the parameters. Using the Wolfram program Mathematica, we sketch the figures for various values of the associated parameters in order to closely examine the obtained solitons. [ABSTRACT FROM AUTHOR]

DnaJ, or heat shock protein 40 (HSP40), is a conserved protein that functions as a molecular chaperone with a strong cytoprotective effect, participating in plant signal transduction, growth, development, and the response to heat stress and other adverse environmental conditions. Although functional characteristics of DnaJ/HSP40 have been described in several plant species, the underlying mechanisms are not completely understood. In this study, 99 putative maize (Zea mays L.) DnaJ genes (ZmDnaJ01–99) randomly distributed on 10 chromosomes were identified in the whole genome using bioinformatics approaches and classified into three groups according to protein structure. The conservation of the gene structure was closely related to the evolutionary tree. Collinearity analysis of DnaJ family genes among species revealed a close evolutionary relationship between maize and sorghum. Transposon analysis revealed helitrons inserted in 49 ZmDnaJs. Multiple stress-related cis-elements were found in the promoter regions of ZmDnaJ genes, suggesting a role in gene expression regulation in response to abiotic stress. The co-expression network screened 12 ZmDnaJ genes that could be induced by stress (drought, high temperature, and salt) and regulated by abscisic acid. ZmDnaJ96 overexpression increased antioxidant enzyme activity and reduced the damage caused by drought and high-temperature stress in Arabidopsis chloroplasts. Virus-induced silencing of ZmDnaJ96 reduced drought and heat tolerance in maize by reducing antioxidant enzyme activity. These results provide genetic resources for maize stress resistance molecular breeding, enhance knowledge of DnaJ gene function in maize, and offer a solid foundation for further in-depth study of the relationship between maize DnaJ/HSP40 members. [ABSTRACT FROM AUTHOR]

With the growing resistance of pathogenic microbes to traditional drugs, biogenic silver nanoparticles (SNPs) have recently drawn attention as potent antimicrobial agents. In the present study, SNPs synthesized with the aid of orange (Citrus sinensis) peel were engineered by screening variables affecting their properties via Plackett–Burman design. Among the variables screened (temperature, pH, shaking speed, incubation time, peel extract concentration, AgNO3 concentration and extract/AgNO3 volume ratio), pH was the only variable with significant effect on SNPs synthesis. Therefore, SNPs properties could be enhanced to possess highly regular shape with zeta size of 11.44 nm and zeta potential of − 23.7 mV. SNPs purified, capped and stabilized by cloud point extraction technique were then checked for their antimicrobial activity against Bacillus cereus, Listeria innocua, Listeria monocytogenes, Staphylococcus aureus, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella typhimurium and Candida albicans. The maximum antimicrobial activity of SNPs was recorded against E. coli, L. monocytogenes and C. albicans with clear zone diameter of 33.2, 31.8 and 31.7 mm, respectively. Based on minimum inhibition concentration and minimum bactericidal concentration of SNPs (300 mg/l) as well as their effect on respiratory chain dehydrogenases, cellular sugar leakage, protein leakage and lipid peroxidation of microbial cells, E. coli was the most affected. Scanning electron microscopy, protein banding and DNA fragmentation proved obvious ultrastructural and molecular alterations of E. coli treated with SNPs. Thus, biogenic SNPs with enhanced properties can be synthesized with the aid of Citrus peel; and such engineered nanoparticles can be used as potent antimicrobial drug against E. coli. [ABSTRACT FROM AUTHOR]

Atmosphere pollution is a burning issue in Pakistan and therefore getting substantial attention at both the national and international levels. It is not only confined to the cities, but the small towns in Pakistan also suffer from this problem. However, very little information exists regarding public awareness and willingness to pay (WTP) for atmosphere pollution, particularly among the inhabitants of towns. This study aims to investigate the role of public awareness and WTP in the elimination of atmosphere pollution via a well-structured interview schedule. The interval regression model is used to analyze the data. The analysis shows that radio, television, and newspapers are the prime sources of information regarding atmosphere pollution in the study area. The attitude of the respondents concerning the severity of atmosphere pollution, only 46.0 percent declares pollution in towns as 'moderately severe.' Regarding the sources of pollution, 48 percent of the respondents attribute vehicular emissions besides industrial emissions to atmosphere pollution. The environment-friendly measures that respondents favored include the use of public transportation (37.7%) and solar equipment (27.7%) followed by the carbon tax and personal car sharing. There exists a significant difference between the WTP for self-protective measures before and after the dissemination of information. The analysis further demonstrates that the WTP to support the control and prevention of air pollution after the dissemination of information is significantly higher than before the dissemination of such information. However, respondents tend to pay more for self-protective measures than to support the control and prevention measures. Alternatively, this may indicate that inhabitants of the study area want the government to play a dominant role in controlling atmosphere pollution and preventive actions. Among the various socio-economic factors, the level of education and income significantly increase the WTP to eliminate atmosphere pollution. This study is important to better understand public awareness and WTP to prevent atmosphere pollution in Pakistan. It could also contribute to activating positive public participation to control atmosphere pollution and its management to move toward sustainable development. [ABSTRACT FROM AUTHOR]

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain’s base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system’s potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements. [ABSTRACT FROM AUTHOR]

This study brings a novel dimension to mentoring theory by exploring the relatively unexamined aspect of cross-gender infatuation between mentors and mentees. At the heart of the mentoring relationship, according to this study, lies personal identification, which is characterized by feelings of connectedness, belonging, and a strong desire to forge a relationship. To examine into this topic, the study employed phenomenological methods, conducting thorough interviews with a balanced group of 20 participants. This group included five male mentors, five male mentees, five female mentors, and five female mentees. The data gathered from these interviews were meticulously analyzed using first and second cycle coding techniques, and the findings are articulated through a process model. Drawing on psychoanalytic theory, the study posits that gender differences play a crucial role in the process of personal identification within mentoring relationships. It examines situations where infatuation, driven by sexual desires, arises in one or both parties involved. The study discusses how societal gender norms often compel individuals to suppress these intimate desires. This suppression and avoidance can lead to sexual repression, manifesting as disruptive behavior and hindering the development of personal identification. Consequently, this dynamic adversely affects the caregiving aspect of the mentor-mentee relationship. The findings of this study enrich mentoring theory by shedding light on the impact of gender roles in the identification process within mentorship relationships. It highlights the complex interplay of personal emotions and societal norms in mentoring dynamics, offering a deeper understanding of the factors that influence these relationships. [ABSTRACT FROM AUTHOR]

Trichogramma chilonis (Ishii) is an important biocontrol agent that is widely used around the world to control numerous lepidopteran pests. The overuse of pesticides in agricultural systems causes lethal and sublethal effects on biocontrol agents. In ectothermic organisms, temperature influences the toxicity of insecticides. In the context of global warming, it is crucial to assess the effects of pesticides on beneficial arthropods under temperature stresses. The toxicity of bifenthrin, carbosulfan, chlorantraniliprole, dimethoate, fipronil, flubendiamide, imidacloprid, lambda-cyhalothrin and lufenuron was studied on T. chilonis at 18, 25 and 32 °C constant temperatures. The temperature coefficient was calculated as the ratio of higher LC50 values to lower LC50 values of an insecticide at different temperatures. The temperature coefficient of imidacloprid, bifenthrin and lambda-cyhalothrin was negative at 25 °C when compared to 18 °C and became positive at 32 °C, while dimethoate and lufenuron had an opposite trend. For carbosulfan and fipronil, the temperature coefficient was positive and for chlorantraniliprole and flubendiamide the coefficient was negative at all tested temperatures. Insecticides having a negative temperature coefficient become less toxic at higher temperatures; this might help reduce non-target insecticide risk to T. chilonis. The risk quotient (RQ) estimated as the ratio of field doses to the LC50 of beneficial organisms indicated that chlorantraniliprole at 25 °C and 32 °C and flubendiamide at 32 °C are harmless to T. chilonis and can be used a component of the integrated pest management (IPM) programs while the other tested insecticides should be avoided. This research can help develop successful pest management systems by reducing the adverse effects of insecticides on non-target species. [ABSTRACT FROM AUTHOR]

While the discussion on generative artificial intelligence, such as ChatGPT, is making waves in academia and the popular press, there is a need for more insight into the use of ChatGPT among students and the potential harmful or beneficial consequences associated with its usage. Using samples from two studies, the current research examined the causes and consequences of ChatGPT usage among university students. Study 1 developed and validated an eight-item scale to measure ChatGPT usage by conducting a survey among university students (N = 165). Study 2 used a three-wave time-lagged design to collect data from university students (N = 494) to further validate the scale and test the study's hypotheses. Study 2 also examined the effects of academic workload, academic time pressure, sensitivity to rewards, and sensitivity to quality on ChatGPT usage. Study 2 further examined the effects of ChatGPT usage on students' levels of procrastination, memory loss, and academic performance. Study 1 provided evidence for the validity and reliability of the ChatGPT usage scale. Furthermore, study 2 revealed that when students faced higher academic workload and time pressure, they were more likely to use ChatGPT. In contrast, students who were sensitive to rewards were less likely to use ChatGPT. Not surprisingly, use of ChatGPT was likely to develop tendencies for procrastination and memory loss and dampen the students' academic performance. Finally, academic workload, time pressure, and sensitivity to rewards had indirect effects on students' outcomes through ChatGPT usage. [ABSTRACT FROM AUTHOR]

The dynamical behaviour of the (4+1)-dimensional fractional Fokas equation is investigated in this paper. The modified auxiliary equation method and extended (G ′ G 2) -expansion method, two reliable and useful analytical approaches, are used to construct soliton solutions for the proposed model. We demonstrate some of the extracted solutions used the definition of the truncated M-derivative (TMD) to understand its dynamical behaviour. The hyperbolic, periodic, and trigonometric function solutions are used to derive the analytical solutions for the given model. As a result, dark, bright, and singular solitary wave solitons are obtained. We observe the fractional parameter impact of the above derivative on the physical phenomena. Each set of travelling wave solutions have a symmetrical mathematical form. Last but not least, we employ Mathematica to produce 2D and 3D figures of the analytical soliton solutions to emphasize the influence of TMD on the behaviour and symmetry of the solutions for the proposed problem. The physical importance of the solutions found for particular values of the combination of parameters during the representation of graphs as well as understanding of physical incidents. [ABSTRACT FROM AUTHOR]

In recent years, many subclasses of univalent functions, directly or not directly related to the exponential functions, have been introduced and studied. In this paper, we consider the class of S e ∗ for which z f ′ (z) / f (z) is subordinate to e z in the open unit disk. The classic concept of Hankel determinant is generalized by replacing the inverse logarithmic coefficient of functions belonging to certain subclasses of univalent functions. In particular, we obtain the best possible bounds for the second Hankel determinant of logarithmic coefficients of inverse starlike functions subordinated to exponential functions. This work may inspire to pay more attention to the coefficient properties with respect to the inverse functions of various classes of univalent functions. [ABSTRACT FROM AUTHOR]

In the recent decade, the citation recommendation has emerged as an important research topic due to its need for the huge size of published scientific work. Among other citation recommendation techniques, the widely used content-based filtering (CBF) exploits research articles' textual content to produce recommendations. However, CBF techniques are prone to the well-known cold-start problem. On the other hand, deep learning has shown its effectiveness in understanding the semantics of the text. The present paper proposes a citation recommendation system using deep learning models to classify rhetorical zones of the research articles and compute similarity using rhetorical zone embeddings that overcome the cold-start problem. Rhetorical zones are the predefined linguistic categories having some common characteristics about the text. A deep learning model is trained using ART and CORE datasets with an accuracy of 76 per cent. The final ranked lists of the recommendations have an average of 0.704 normalized discounted cumulative gain (nDCG) score involving ten domain experts. The proposed system is applicable for both local and global context-aware recommendations. [ABSTRACT FROM AUTHOR]

Misuse of antibiotics leads to the worldwide spread of antibiotic resistance, which motivates scientists to create new antibiotics. The recurring UTI due to antibiotics-resistant microorganism's challenges scientists globally. The biogenic nanoparticles have the potential to meet the escalating requirements of novel antimicrobial agents. The green synthesis of nanoparticles (NPs) gained more attention due to their reliable applications against resistant microbes. The current study evaluates the biogenic ZnO NPs of Mentha piperata extract against resistant pathogens of urinary tract infections by agar well diffusion assay. The biogenic ZnO NPs revealed comparatively maximum inhibition in comparison to synthetic antibiotics against two bacterial strains (Proteus mirabilis, Pseudomonas aeruginosa) and a fungal strain (Candida albicans).The synthesized biogenic ZnO NPs alone revealed maximum activities than the combination of plant extract (PE) and ZnO NPs, and PE alone. The physiochemical features of ZnO NPs characterized through UV–Vis spectroscopy, FTIR, XRD, SEM, and EDX. The UV–Vis spectroscopy revealed 281.85 nm wavelengths; the XRD pattern revealed the crystalline structure of ZnO NPs. The FTIR analysis revealed the presence of carboxylic and nitro groups, which could be attributed to plant extract. SEM analysis revealed spherical hollow symmetry due to electrostatic forces. The analysis via EDX confirmed the presence of Zn and oxygen in the sample. The physiochemical features of synthesized ZnO NPs provide pivotal information such as quality and effectiveness. The current study revealed excellent dose-dependent antimicrobial activity against the pathogenic isolates from UTI-resistant patients. The higher concentration of ZnONPs interacts with the cell membrane which triggers oxidative burst. They may bind with the enzymes and proteins and brings epigenetic alteration which leads to membrane disruption or cell death. [ABSTRACT FROM AUTHOR]

Carbon neutrality hinges on effectively harnessing renewable energy sources, a critical factor as countries worldwide enact low-carbon legislation to mitigate global warming. In this context, this study introduces an innovative soft-computing framework based on the adaptive neuro-fuzzy inference system (ANFIS) for predicting wave height and wave period, which are crucial parameters for energy harvesting. This model incorporates inputs such as temperature, wind speed, and wind direction to predict wave energy. The model was trained using data from the Lianyungang (LYG) and Dachen (DCN) stations in the East China Sea, and its performance was contrasted with that of artificial neural networks (ANNs) encompassing 10–50 neurons and utilizing subtractive clustering (SC) and grid partition (GP) techniques. The ANFIS SC method, with a 0.1 cluster radius (C.R), outperformed both the ANNs and ANFIS GP in wave energy prediction. The statistical analysis confirmed that this model yielded root-mean-squared error, R, and R2 values of 0.0017, 0.987, and 0.974 for the LYG station and 0.0152, 0.93, and 0.867 for the DCN station. These metrics imply that the ANFIS SC algorithm excels in wave energy prediction, thus rendering it a potent instrument for wave-powered ship navigation. This study underscores the value of soft-computing techniques in pursuing renewable energy forecasting, contributing to sustainable and efficient marine transportation. [ABSTRACT FROM AUTHOR]

(CrFeNiCu)100–xTix (x = 0, 3, 5, 7 and 10; at%) high-entropy alloys have been designed by the consideration of the thermophysical relationship between Ti and other principal elements to investigate the influence of Ti on the microstructural evolution and mechanical properties of (CrFeNiCu)100–xTix high-entropy alloys. The addition of Ti content in HEAs leads to a change in phase formation from dual-phase (FCC1 and FCC2, FCC: face-centered cubic) to the mixture of FCC1, FCC2 phases, and an additional body-centered cubic (BCC) phase. The yield strength and Vickers hardness of the alloys are enhanced from 291 to 1511 MPa and HV 134 to HV 531, respectively, which depends strongly on the volume fraction of BCC phase. On the one hand, the plasticity of the alloys reduces from 45.00% to 24.09%, but it could be considered reasonable plasticity. These results revealed that the addition of a minor alloying element in high-entropy alloys with consideration of thermophysical parameters led to the formation of a multiple solid solution structure with excellent mechanical properties. [ABSTRACT FROM AUTHOR]

The optimal multi-degree reduction of ball Said–Ball curves is an unsolved and knotty important technique in computer aided design (CAD) and computer graphics (CG) and is potentially used in many engineering fields involving geometric modeling. In this paper, an improved chimp optimization algorithm (ICHOA, for short) is used to solve the degree reduction of BSB curves. Firstly, the multi-degree reduction of BSB curves is mathematically an optimization problem that can be efficiently dealt with by a swarm intelligence algorithm. In this regard, a novel enhanced version of CHOA called ICHOA, combined with the proportional weight, dimension learning-based hunting search and fractional order strategies, is developed to enhance its capability of jumping out of the local minima and improve the calculation accuracy of the native algorithm. Furthermore, the superiority of the ICHOA is verified by comparing it with standard CHOA, other improved CHOA and popular nature-inspired optimization algorithms on 23 classical benchmark functions, the CEC'17 test suite and five engineering optimization problems, respectively. Secondly, the optimization models of multi-degree reduction for the center curve and radius function of BSB curves are established, respectively; meanwhile, the proposed ICHOA is utilized to solve the established optimization models, and the optimal center curve and radius function with a minimum distance of the approximating BSB curves of lower degree are also obtained. Finally, experimental results illustrate the ability of the proposed ICHOA to effectively solve the optimization problems of multi-degree reduction of BSB curves in terms of precision, robustness, and convergence characteristics. [ABSTRACT FROM AUTHOR]

Remdesivir is among the SARS-CoV-2 (severe acute respiratory syndrome coronavirus type 2) drugs with great potential. However, its poor aqueous solubility restricts its therapeutic action. Therefore, the aim was to develop the nasal delivery of Remdesivir with solubilizing polymers, poloxamer 407, and β-cyclodextrin, which resulted in significant solubility enhancement. In addition, this nanosuspension was developed for the first time for pulmonary delivery to enhance the in vivo performance of remdesivir. Remdesivir solubility and biocompatibility were greatly improved by polymeric encapsulation at the nanoscale. The nanosuspension was prepared by the modified precipitation-ultra sonication process and showed a good particle size 500 nm ± 20 nm, with polydispersity (0.226 ± 0.02) and zeta potential (-16.0 ± 2 mV). The nasal formulation was also assessed for in vitro dissolution and diffusion, in addition to toxicity investigations (Hemolysis, MTT assay). The conversion of remdesivir crystals to an amorphous form was verified by characterization studies (XRD and DSC). The morphology of the nano particles was determined by SEM method and found to be spherical and of uniform shape. FTIR study was performed to determine the drug compatibility with the polymers and was satisfactory. Histopathology study on goat nasal mucosa showed no adverse effects of the formulation on nasal tissues. Analysis using reverse transcription polymerase chain reaction revealed noticeably reduced levels of IL-4 mRNA expression (pro-inflammatory cytokines). In comparison to intravenous delivery, nasal delivery of remdesivir nanosuspension is patient-complaint and easy to use. The outcomes of this study demonstrate the potential for delivering remdesivir nanosuspension via the nasal route. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the estimates of some coefficient-related problems for the class B T 3 ℓ of bounded turning functions connected to a three-leaf shaped domain. We calculate the upper bounds of the second and third order Hankel determinants with the coefficients of the inverse functions. The bounds are proved to be sharp. [ABSTRACT FROM AUTHOR]

In the manufacturing process of free-form complex surfaces, various problems occur which degraded the performance and can be resolved by using an optimization technique. Thousands of real-world problems can be converted into optimization techniques with distinct objective functions to acquire the optimal solution. In this paper, an assembly of GHT-Bézier developable surfaces by using a nature-inspired particle swarm optimization technique combined with optimal parameters are constructed from two GHT-Bézier boundary curves to improve the efficiency of complex engineering products. For this purpose, the control points of GHT-Bézier surface are chosen as design variables. The objective function is defined as the developability degree of the ruled surface and the shape parameters are considered to be optimization variables. So, we search for the optimum shape control parameters within the value range of shape parameters by using the PSO technique, then the developable surfaces with highly accurate developability can be visualized. The modeling examples demonstrate the effectiveness of the proposed method with the fairness of the surfaces and its approximation to the original surface. [ABSTRACT FROM AUTHOR]

The science of DNA nanotechnology has led to the synthesis of size-controllable materials with uniformed geometries at nano- and micro-scales. Herein, we proposed the double-crossover (DX), antiparallel, and even half-turns perimeter tiles (DAE tiles) to synthesize intact, mono-crystalline, and giant 2D DNA micro-assemblies. The DNA tiles with 10-half-turns perimeter were synthesized via self-assembly of 106 nucleotides (NT) circular scaffold along with the complimentary staple strands. The DAE DNA tiles were successfully polymerized to achieve stable lattices by adjusting the inter-tile distances of certain lengths for attaining torsional (or twisting) chirality. We determined that the inter-tile connections affected the degree of coiling (or super-coiling) and twisting forces (right- or left-handed twists) in the DNA helix. While the degree of polymerization of DNA tiles was also tune-able by controlling the lengths and structural designs of the circular core of the DNA tiles. Furthermore, the number of half-turns in the core and on the connection arms (4 or 5) with even "E" or odd "O" half-turns was crucial. It affected the direction of winding of DNA duplexes to alter the overall stiffness and sturdiness of DNA lattices. The number of half-turns in the connections were either "4 or Even (21 NT); E with 5 NT sticky ends" or "5 Odd (26 NT); O with 6 NT sticky ends" (DAE-E or DAE-O tile systems). The AFM results revealed that the above tile systems (DAE-E or DAE-O) together with the locations of crossovers, and holiday junctions along the DNA tiles controlled the left- or right-handed coiling of DNA double strands. This phenomenon affected the compactness of resulting DNA motifs, the overall intrinsic curvatures, double-strand packing, and the geometry of DNA lattices. [ABSTRACT FROM AUTHOR]

This article presents that acrylate copolymers are the potential candidate against the adsorption of bovine serum albumin (BSA). A series of copolymers poly(methyl methacrylate) (pMMA), poly(3-sulfopropyl methacrylate-co-methyl methacrylate) p(SPMA-co-MMA), and poly(dimethylaminoethyl methacrylate-co-methyl methacrylate) p(DMAEMA-co-MMA) were synthesized via free radical polymerization. These amphiphilic copolymers are thermally stable with a glass transition temperature (Tg) 50–120 °C and observed the impact of surface charge on amphiphilic copolymers to control interactions with the bovine serum albumin (BSA). These copolymers pMD1 and pMS1 have surface charges, − 56.6 and − 72.6 mV at pH 7.4 in PBS buffer solution that controls the adsorption capacity of bovine serum albumin (BSA) on polymers surface. Atomic force microscopy (AFM) analysis showed minimum roughness of 0.324 nm and 0.474 nm for pMS1 and pMD1. Kinetic studies for BSA adsorption on these amphiphilic copolymers showed the best fitting of the pseudo-first-order model that showed physisorption and attained at 25 °C and pH 7.4 within 24 h. [ABSTRACT FROM AUTHOR]

Recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a stakeholder proposes a new requirement, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. Several NLP approaches for similarity computation between requirements are available. However, there is little empirical evidence on their effectiveness for code retrieval. This study compares different NLP approaches, from lexical ones to semantic, deep-learning techniques, and correlates the similarity among requirements with the similarity of their associated software. The evaluation is conducted on real-world requirements from two industrial projects from a railway company. Specifically, the most similar pairs of requirements across two industrial projects are automatically identified using six language models. Then, the trace links between requirements and software are used to identify the software pairs associated with each requirements pair. The software similarity between pairs is then automatically computed with JPLag. Finally, the correlation between requirements similarity and software similarity is evaluated to see which language model shows the highest correlation and is thus more appropriate for code retrieval. In addition, we perform a focus group with members of the company to collect qualitative data. Results show a moderately positive correlation between requirements similarity and software similarity, with the pre-trained deep learning-based BERT language model with preprocessing outperforming the other models. Practitioners confirm that requirements similarity is generally regarded as a proxy for software similarity. However, they also highlight that additional aspect comes into play when deciding software reuse, e.g., domain/project knowledge, information coming from test cases, and trace links. Our work is among the first ones to explore the relationship between requirements and software similarity from a quantitative and qualitative standpoint. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and change impact analysis. [ABSTRACT FROM AUTHOR]

Cancer development is a long-lasting process during which macrophages play a pivotal role. However, how macrophages maintain their cellular identity, persistence, expanding and pro-tumor property during malignant progression remains elusive. Inspired by the recent report of the activation of stem cell-like self-renewal mechanism in mature macrophages, we postulate that intra-tumoral macrophages might be trained to assume stem-like properties and memory-like activity favoring cancer development. Herein we demonstrated that tumor infiltrating macrophages rapidly converted into the CD11b+F4/80+Ly6C−Bcl6+ phenotype, and adopted stem cell-like properties involving expression of stemness-related genes, long-term persistence and self-renewing. Importantly, Bcl6+ macrophages stably maintained cell identity, gene signature, metabolic profile, and pro-tumor property even after long-term culture in tumor-free medium, which were hence termed stem cell-like memory macrophages (SMMs). Mechanistically, we showed that transcriptional factor Bcl6 co-opted the demethylase Tet2 and the deacetylase SIRT1 to confer the epigenetic imprinting and mitochondrial metabolic traits to SMMs, bolstering the stability and longevity of trained immunity in tumor-associated macrophages (TAMs). Furthermore, tumor-derived redHMGB1 was identified as the priming signal, which, through TLR4 and mTOR/AKT pathway, induced Bcl6-driven program underpinning SMMs generation. Collectively, our study uncovers a distinct macrophage population with a hybrid of stem cell and memory cell properties, and unveils a regulatory mechanism that integrates transcriptional, epigenetic and metabolic pathways to promote long-lasting pro-tumor immunity. [ABSTRACT FROM AUTHOR]

A new species in the genus Acarospora (Acarosporaceae, lichenized ascomycetes), from Darel Valley, Gilgit Baltistan, Pakistan, is described and illustrated here under the name Acarospora pakistanica. It is characterized by thicker epihymenium 30–60 µm, taller hymenium 100–150 µm, and larger ascospores 5–7 × 1–3 μm. A detailed description of this taxon is provided. [ABSTRACT FROM AUTHOR]

The aim of this manuscript is to find the analytical solutions of the Korteweg–de Vries (KdV) equation with dual power law nonlinearity using the exp-function method. The KdV equation is used to study the shallow water wave behavior of long wavelengths and small amplitude. With the help of the exp-function method, a variety of exact wave solutions of the KdV equation are obtained including kink, anti-kink, and bell-shaped traveling wave solutions. The various kinds of solutions to the considered nonlinear KdV equation may help to explore the relevant nonlinear phenomena in fluid dynamics. The presented results are novel and the KdV equation with dual power law nonlinearity has been evaluated using the presented technique for the first time in this work. In addition, some of the exact solutions have been shown by contour planes, 3D plots, and 2D graphics for visualizing the underlying dynamics of the results. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. However, the lack of human cardiomyocytes with proper genetic backgrounds limits the study of disease mechanisms. Human pluripotent stem cell–derived cardiomyocytes (hPSC-CMs) have significantly advanced the study of these conditions. Moreover, hPSC-CMs made it easy to study CVDs using genome-editing techniques. This article discusses the applications of these techniques in hPSC for studying CVDs. Recently, several genome-editing systems have been used to modify hPSCs, including zinc finger nucleases, transcription activator-like effector nucleases, and clustered regularly interspaced short palindromic repeat-associated protein 9 (CRISPR/Cas9). We focused on the recent advancement of genome editing in hPSCs, which dramatically improved the efficiency of the cell-based mechanism study and therapy for cardiac diseases. [ABSTRACT FROM AUTHOR]