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Artificial intelligence (AI) tools have seen widespread adoption in the sales function. However, the pace of adoption means that sales researchers are often several steps behind the business world. A way to alleviate some of these concerns is to provide a practical, yet up-to-date understanding of AI in sales. Thus, the purpose of this manuscript is to clarify what AI is, the role of AI in sales, and its implications for multiple stakeholders in the sales organization (i.e. salespeople, sales managers, organizations, and customers). To achieve this objective, the authors provide an up-to-date examination of business practices that are interwoven with practitioner and academic literature. Next, based upon exploratory interviews with eighteen practitioners, the authors discuss challenges and opportunities that can arise due to AI adoption. Finally, the authors provide directions for future exploration of AI in the sales domain. [ABSTRACT FROM AUTHOR]

Acute inflammatory demyelinating polyneuropathy Guillain-Barre's syndrome is typically brought on by an immunological reaction following certain post-infections. GBS causes nerve damage resulting in muscle weakness, tingling sensation and paralysis due to nerve injury. (1) It can be comparable to Sarvangavata, according to Ayurveda. The fatty myelin coating that surrounds the nerve cells protects them. The neurological system requires an insulating layer to operate properly, which is created as a result. It can also be compared to medogata vata. Since myelin contains about 40% water, the dry mass is made up of 60% to 75% lipid and 15% to 25% protein. (2) Ayurveda offers Panchakarma therapy to lessen the sickness by easing the symptoms of GBS. A 55-year-old male patient was unable to sit, stand or walk due to abrupt onset of weakness in both lower limbs. The patient was also covid 19 positive, one month before the onset of these symptoms. For the same patient has been hospitalised and underwent proper covid management. Eventually complaints of weakness in the lower limbs and GBS led the patient to seek additional medical attention and receive IV Ig injections. After receiving immunoglobulin therapy there was no expected recovery. Hence the patient has been admitted to our hospital as in patient for further management. [ABSTRACT FROM AUTHOR]

Soil contamination with heavy metals presents a substantial environmental peril, necessitating the exploration of innovative remediation approaches. This research aimed to investigate the efficiency of nano-silica in stabilizing heavy metals in a calcareous heavy metal-contaminated soil. The soil was treated with five nano-silica levels of 0, 100, 200, 500, and 1000 mg/kg and incubated for two months. The results showed that nano-silica had a specific surface area of 179.68 m 2 / g . At 1000 mg/kg, the DTPA-extractable concentrations of Pb, Zn, Cu, Ni, and Cr decreased by 12%, 11%, 11.6%, 10%, and 9.5% compared to the controls, respectively. Additionally, as the nano-silica application rate increased, both soil pH and specific surface area increased. The augmentation of nano-silica adsorbent in the soil led to a decline in the exchangeable (EX) and carbonate-bound fractions of Pb, Cu, Zn, Ni, and Cr, while the distribution of heavy metals in fractions bonded with Fe–Mn oxides, organic matter, and residue increased. The use of 1000 mg/kg nano-silica resulted in an 8.0% reduction in EX Pb, 4.5% in EX Cu, 7.3% in EX Zn, 7.1% in EX Ni, and 7.9% in EX Cr compared to the control treatment. Overall, our study highlights the potential of nano silica as a promising remediation strategy for addressing heavy metal pollution in contaminated soils, offering sustainable solutions for environmental restoration and ecosystem protection. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are structured for monitoring an area with distributed sensors and built-in batteries. However, most of their battery energy is consumed during the data transmission process. In recent years, several methodologies, like routing optimization, topology control, and sleep scheduling algorithms, have been introduced to improve the energy efficiency of WSNs. This study introduces a novel method based on a deep learning approach that utilizes variational autoencoders (VAEs) to improve the energy efficiency of WSNs by compressing transmission data. The VAE approach is customized in this work for compressing WSN data by retaining its important features. This is achieved by analyzing the statistical structure of the sensor data rather than providing a fixed-size latent representation. The performance of the proposed model is verified using a MATLAB simulation platform, integrating a pre-trained variational autoencoder model with openly available wireless sensor data. The performance of the proposed model is found to be satisfactory in comparison to traditional methods, like the compressed sensing technique, lightweight temporal compression, and the autoencoder, in terms of having an average compression rate of 1.5572. The WSN simulation also indicates that the VAE-incorporated architecture attains a maximum network lifetime of 1491 s and suggests that VAE could be used for compression-based transmission using WSNs, as its reconstruction rate is 0.9902, which is better than results from all the other techniques. [ABSTRACT FROM AUTHOR]

The study probes comparative and additional value relevance of total comprehensive income and other comprehensive income, respectively, in the Indian context after adopting IFRS-converged accounting standards. The study sample comprises of 367 Indian non-financial companies. The period of study is F.Y. 2016–2017 to F.Y. 2019–2020. Results reveal both net profit and total comprehensive are value relevant, but the supremacy of neither of the two could be established based on our findings. Furthermore, other comprehensive income comes out to be additionally value relevant. The study's findings determine the decision usefulness of OCI and thus, provide useful insights to standard setting bodies. [ABSTRACT FROM AUTHOR]

This paper presents a design and analysis of novel DC-DC boost converter with a least component count. The proposed converter produces high DC gain voltage in comparison to some recently presented high voltage DC-DC converter. Here one switch, one inductor, two capacitors and one diode are used to achieved a high voltage gain without compromising efficiency of converter. The converter’s performance is evaluated using theatrical, simulation and experimental methods, with results indicating a four times of input voltage and a fast-transient response at various duty cycles is achieved. Due to its low component count the proposed converter is compact and hence it offers an effective solution for various power applications. [ABSTRACT FROM AUTHOR]

Background: Sodium-glucose cotransporter-2 (SGLT2) inhibitors have demonstrated reduction in heart failure outcomes in patients with type 2 diabetes mellitus, although the exact mechanism of benefit remains unclear. Alteration in left atrial (LA) function due to chronic pressure or volume overload is a hallmark of heart failure. Objective: To evaluate the effect of the SGLT2 inhibitor empagliflozin on LA volume and function. Methods: 90 patients with coronary artery disease and type 2 diabetes (T2DM) were randomized to empagliflozin (n = 44) or placebo (n = 46), and underwent cardiac magnetic resonance (CMR) imaging at baseline and after 6 months. The main outcome was change in LA volume; LA function, including active and passive components, was also measured by a blinded reader. Results: At baseline, there was no significant difference in LA volumes between the empagliflozin (indexed maximum LA volume 26.4 ± 8.4mL/m2, minimum LA volume 11.1 ± 5.7mL/m2) and placebo (indexed maximum LA volume 28.7 ± 8.2mL/m2, minimum LA volume 12.6 ± 5.0mL/m2) groups. After 6 months, changes in LA volumes did not differ with adjusted difference (empagliflozin minus placebo): 0.99 mL/m2 (95% CI: -1.7 to 3.7 mL/m2; p = 0.47) for indexed maximum LA volume, and 0.87 mL/m2 (95% CI: -0.9 to 2.6 mL/m2; p = 0.32) for indexed minimum LA volume. Changes in total LA emptying fraction were also similar, with between-group adjusted mean difference − 0.01 (95% CI: -0.05 to 0.03, p = 0.59). Conclusion: SGLT2 inhibition with empagliflozin for 6 months did not have a significant impact on LA volume and function in patients with T2DM and coronary artery disease. (Effects of Empagliflozin on Cardiac Structure in Patients with Type 2 Diabetes [EMPA-HEART]; NCT02998970). [ABSTRACT FROM AUTHOR]

Rosa davurica Pall. is widely used in traditional oriental herbal therapy, but its components and molecular mechanisms of action remain unclear. This study investigates the antidiabetic potential of Rosa davurica Pall. root extract (RDR) and elucidates its underlying molecular mechanisms with in vitro and in vivo models. Data from the current study show that RDR exhibits strong antioxidant activity and glucose homeostasis regulatory effects. It significantly impacts glucose homeostasis in C2C12 skeletal muscle cells by inhibiting α-glucosidase activity. Further molecular mechanistic studies revealed that RDR promoted glucose uptake by phosphorylation of AMP-activated protein kinase (AMPK)/acetyl-CoA carboxylase (ACC), but not Phosphatidylinositol 3-kinase (PI 3-kinase)/Akt in C2C12 skeletal muscle cells. These actions increased the expression and translocation of glucose transporter type 4 (GLUT4) to the plasma membrane. In addition, RDR treatment in the STZ-induced diabetic rats remarkably improved the low body weight, polydipsia, polyphagia, hyperglycemia, and islet architecture and increased the insulin/glucose ratio. The liver (ALT and AST) and kidney marker enzyme (BUN and creatinine) levels were restored by RDR treatment as well. Phytochemical analysis identified eight major constituents in RDR, crucial for its antioxidant and antidiabetic activity. Through the molecular docking of representative glucose transporter GLUT4 with these compounds, it was confirmed that the components of RDR had a significantly high binding score in terms of structural binding. These findings from the current study highlight the antidiabetic effects of RDR. Collectively, our data suggest that RDR might be a potential pharmaceutical natural product for diabetic patients. [ABSTRACT FROM AUTHOR]

Reinforcement learning (RL) has been applied to various domains in computational chemistry and has found wide‐spread success. In this review, we first motivate the application of RL to chemistry and list some broad application domains, for example, molecule generation, geometry optimization, and retrosynthetic pathway search. We set up some of the formalism associated with reinforcement learning that should help the reader translate their chemistry problems into a form where RL can be used to solve them. We then discuss the solution formulations and algorithms proposed in recent literature for these problems, the advantages of one over the other, together with the necessary details of the RL algorithms they employ. This article should help the reader understand the state of RL applications in chemistry, learn about some relevant actively‐researched open problems, gain insight into how RL can be used to approach them and hopefully inspire innovative RL applications in Chemistry. [ABSTRACT FROM AUTHOR]

Rear-end collision prediction has attracted more and more attention in order to increase safety in Autonomous Vehicles (AVs). It is critical to develop effective warning systems for autonomous vehicles because rear-end collisions are one of the major contributors to traffic accidents. The current research has been done to foresee collisions. We suggest learning-based approaches to address this complex problem, which the conventional approaches find challenging. However, due to non-optimized parameters in the Long Short Term Memory (LSTM), the prediction performance is degraded. To overcome this issue, Novel, optimized LSTM-based deep learning framework was proposed to enhance Crash Risk Prediction System effectiveness. This framework uses an Enhanced LSTM (EnLSTM) to improve the performance of Crash Risk Prediction system while extracting efficient features using a Convolutional Neural Network (CNN)-based feature extraction mechanism. Improved Grasshopper optimization Algorithm (IGOA) has been developed for hyper parameters optimization in the LSTM model. The proposed algorithm is assessed on the basis of metrics from confusion matrix. The experiment reveals that the Novel Optimized LSTM is superior to the current models based on precision, sensitivity, specificity, false and missed alarm rate. This efficient deep learning model may be applied in autonomous vehicles and accurately warns the driver when a collision is imminent. [ABSTRACT FROM AUTHOR]

The detection, characterization, and monitoring of SARS-CoV-2 recombinant variants constitute a challenge for public health authorities worldwide. Recombinant variants, composed of two or more SARS-CoV-2 lineages, often have unknown impacts on transmission, immune escape, and virulence in the early stages of emergence. We examined 4213 SARS-CoV-2 recombinant SARS-CoV-2 genomes collected between 2020 and 2022 in California to describe regional and statewide trends in prevalence. Many of these recombinant genomes, such as those belonging to the XZ lineage or novel recombinant lineages, likely originated within the state of California. We discuss the challenges and limitations surrounding Pango lineage assignments, the use of publicly available sequence data, and adequate sample sizes for epidemiologic analyses. Although these challenges will continue as SARS-CoV-2 sequencing volumes decrease globally, this study enhances our understanding of SARS-CoV-2 recombinant genomes to date while providing a foundation for future insights into emerging recombinant lineages. [ABSTRACT FROM AUTHOR]

In recent days, cardiovascular disease (CVD) has been considered one of the significant causes of morbidity and mortality in the world. Arrhythmia, acute myocardial infarction (AMI), and other cardiac illnesses have always been serious disorders that put patients' lives in danger. Different studies have shown that substantial features play a foremost role in enhancing the machine learning (ML) technique's performance. Moreover, the dataset was imbalanced, and the researchers could not utilize any model to deal with this issue. Thus, the objective is to discover the substantial features and solve the class imbalance problem that can boost accuracy and lead to better predicting cardiovascular patient survivors. In this proposed work, a novel SMOTE-based hybrid deep learning (SMOTE-HDL) network is proposed for predicting the patient's survivors of cardiovascular disease. At first, the data acquisition stage collects the input data from the dataset and then pre-processes using data normalization and missing value imputation. In addition, the class imbalance problem is solved by an oversampling technique named the synthetic minority oversampling technique (SMOTE). To extract the substantial features, an attention-based perceptive long short-term extraction network (APLSTEN) is employed. The process of feature selection is accomplished through an adaptive coati optimization algorithm (ACOA). Finally, the selected features are served to a Kepler-optimized deep stacked recurrent network (KDSRN) for attaining enhanced classification. The proposed SMOTE-HDL network is implemented in the Python platform using the Heat-failure-clinical-records dataset and assessed the performance in response to dissimilar evaluation criteria. The maximum prediction accuracy obtained by the proposed SMOTE-HDL is 95.52%, superior to the existing classifiers. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for rapidly balancing lithium-ion batteries using a single DC–DC converter, enabling direct energy transfer between high- and low-voltage cells. Utilizing relays for cell pair selection ensures cost-effectiveness in the switch network. The control system integrates a battery-monitoring IC and an MCU to oversee cell voltage and ensure battery protection. A prototype circuit with twelve lithium-ion batteries demonstrates the method's efficacy, achieving a remarkable balancing time of 48 min during charging with a maximum efficiency of 89.85%. Comparative analysis with other methods underscores the superior performance of the proposed balancing circuit in terms of balancing time and implementation cost. Furthermore, this paper delves into hardware aspects of battery management systems (BMSs) for electric vehicles and stationary applications. It offers an overview of prevailing concepts in state-of-the-art systems, aiding readers in assessing considerations essential for BMS design in various applications. The discussion includes examples of battery packs sourced from commercially available electric vehicles. Subsequently, the manuscript addresses implementation aspects concerning the measurement of critical physical variables such as voltage, current, and temperature, alongside balancing strategies. [ABSTRACT FROM AUTHOR]

A wave active filter (WAF) based on a differential difference current conveyor (DDCC) is presented in this paper. An active filter formation depends entirely on wave quantity processing. The wave method is demonstrated for the basic wave active elements (WAEs) of active filters such as a series inductor and a shunt capacitor. The novelty of the proposed work is that the mathematical operations required to implement the wave active components, such as lossy integration-subtraction; subtraction; summation and inverter, are performed using the DDCC as an analog building block (ABB). Designing WAFs of lower to higher-order is extremely challenging, i.e., great motivation to propose a WFA using a CMOS-based DDCC for lower and higher-order low-pass Butterworth filter topologies. Additionally, the filter performances are verified through noise analysis, percentage total harmonic distortion (%THD) and Monte Carlo analysis. The proposed WFA is theoretically verified for n th order low-pass Butterworth filter designs (n = 2 , 3 , 4 , 5 , 6) using DDCC-based WAEs and validated using SPICE simulations with 0. 1 8 μ m TSMC CMOS technology parameters for DDCC, operating on ± 0. 9 0 V. [ABSTRACT FROM AUTHOR]

The theory of fuzzy sets has earned a lot of applications in science and engineering fields. Fuzzy sets include extensions such as intuitionistic and bipolar fuzzy sets. These concepts have now become significant in recent research projects. The union of these sets can be defined as a bipolar intuitionistic fuzzy set that offers more flexibility in analyzing real-life problems. It effectively analyses the systems by examining the involvement and non-involvement grades of the element in a bipolar view. A matrix is a collection of crisp numbers arranged in a rectangular array with rows and columns. The concept of the fuzzy matrix can be defined when a precise solution cannot be obtained from the crisp matrix. The theory of fuzzy matrix plays a vital role in the field of decision-making systems. The fuzzy matrix offers a clear outcome, when examined with a bipolar intuitionistic fuzzy environment. Therefore, the present study coined the notion of bipolar intuitionistic fuzzy matrix and its determinant. To depict the flexibility, its three-dimensional representations are visualized. Also, the fundamental operations such as addition, multiplication, max-min and min-max compositions are defined with illustrations. Moreover, some examples and properties are provided to support the proposed study. [ABSTRACT FROM AUTHOR]

Amlapitta is among the most prevalent illnesses in the community. Every age group, every class, and every community experience it. The term "amlapitta corelated with hyperacidity" describes a group of symptoms brought on by an imbalance between the proximal intestine's and stomach's acid-secreting processes and the defences that keep them safe. Acid secreted by the stomach is typically necessary for digestion. Acidity is the term for the condition that arises when the stomach produces too much acid. Because amlapitta develops from the vitiation of Kapha Pitta Doshas, according to our Acharyas, it is treated by Pitta Shaman along with Vamana and Virechana. For the treatment of Amlapitta, Swamarg Chikitsta is described. In Ayurveda, Urdwarg Amplapitta, Vidagdhajeerna, Samapitta Lakshanas, and Pittaja Grahani Lakshana can all be used to explain hyperacidity. This indicates a reduction in symptoms including flatulence, nausea, indigestion, burning in the retrosternum, and acid reflux eructation.With particular reference to Dyspepsia or gastroesophageal reflux disease (GERD), Laghu Sutshekhar Rasa, Avipattikar Churna, and Patoladi kwatha, in conjunction with lifestyle and food change, offered significant improvement in Amlapitta symptoms. [ABSTRACT FROM AUTHOR]

In this paper, a review of advances in total maximum daily load (TMDL) implementation planning by modeling best management practices (BMPs) and green infrastructure (GI) practices along with enhanced (hybrid/streamlining) approaches is presented. The review emanates from Chapter 12 of the recent ASCE Manual of Practice on TMDLs. The latest models and modeling tools, specifically the United States Environmental Protection Agency's (USEPA's) GI Modeling Toolkit and the Landscape and Green Infrastructure Design (L-GrlD) model for formulating GI strategies with flexibility to support stakeholder engagement, are reviewed. In addition, other decision support tools that can help advance the state-of-the-practice of TMDL implementation are included in the synthesis. Advances in incorporating model uncertainties related to BMPs and GI practices in TMDL analysis are briefly discussed. Furthermore, enhanced approaches to cost-effective TMDL implementation measures are discussed, which can be combined with other watershed management strategies for greater synergy between TMDL modelers and other watershed stakeholders. Some emerging technologies such as remote sensing can be useful for monitoring the effectiveness of the TMDL implementation measures over time. Several emerging technologies are discussed through an example illustrating the long-term efficacy of implementation practices. Finally, an enhanced approach to the full TMDL life cycle that explicitly incorporates BMPs and GI practices in the TMDL is proposed, and expected benefits of this approach are demonstrated with conceptual diagrams. [ABSTRACT FROM AUTHOR]

Industrial IoT (IIoT) applications are widely used in multiple use cases to automate the industrial environment. Industry 4.0 presents challenges in numerous areas, including heterogeneous data, efficient data sensing and collection, real‐time data processing, and higher request arrival rates, due to the massive amount of industrial data. Building a time‐sensitive network that supports the voluminous and dynamic IoT traffic from heterogeneous applications is complex. Therefore, the authors provide insights into the challenges of industrial networks and propose a strategy for enhanced traffic management. An efficient multivariate forecasting model that adapts the Multivariate Singular Spectrum Analysis is employed for an SDN‐based IIoT network. The proposed method considers multiple traffic flow parameters, such as packet sent and received, flow bytes sent and received, source rate, round trip time, jitter, packet arrival rate and flow duration to predict future flows. The experimental results show that the proposed method can effectively predict by contemplating every possible variation in the observed samples and predict average load, delay, inter‐packet arrival rate and source sending rate with improved accuracy. The forecast results shows reduced error estimation when compared with existing methods with Mean Absolute Percentage Error of 1.64%, Mean Squared Error of 11.99, Root Mean Squared Error of 3.46 and Mean Absolute Error of 2.63. [ABSTRACT FROM AUTHOR]

The response from many firms to the recent COVID-19 crisis underscores a more fundamental and overarching question: How should salespeople and their firms prepare for and respond to sales crises more generally? In response, a group of sales scholars recently convened at the American Marketing Association's Winter Conference to discuss the challenges and opportunities facing salespeople and their firms before, during, and after a sales crisis. Thus, based on this session and subsequent follow-up discussions, this paper develops a framework detailing how the sales function should prepare for, withstand, and learn from a sales crisis. In so doing, we argue that sales crises can originate internally and externally to an organization and can impact the entire sales organization, the sales manager, and/or individual salespeople. Moreover, viewing a sales crisis simply as a turning point rather than a devastating event, we highlight the implications for salespeople and their managers who must inevitably deal with sales crises and the changes involved. Finally, we conclude with potential future directions for sales scholars interested in exploring the impact of crises on the sales function, as the next sales crisis is likely just around the corner. [ABSTRACT FROM AUTHOR]

Background Bacterial contamination of implants has been linked to biofilm formation and subsequent infection, capsular contracture, and breast implant–associated anaplastic large cell lymphoma. Reducing contamination during implant insertion should therefore reduce biofilm formation disease sequelae. Objectives The aim of this study was to compare levels of contamination between preventative techniques. Methods A model to simulate the passage of implants through a skin incision was designed that utilized a sterile textured polyvinyl plastic sheet contaminated with Staphylococcus epidermidis. In the first stage of the polyvinyl contamination model, implants were subject to infection-mitigation techniques and passed through the incision, then placed onto horse blood agar plates and incubated for 24 hours. In the second stage of the study the same contamination was applied to human abdominal wall specimens. A 5 cm incision was made through skin and fat, then implants were passed through and levels of contamination were measured as described. Results Smooth implants grew a mean of 95 colony-forming units (CFUs; approximately 1 CFU/cm2) and textured implants grew 86 CFUs (also approximately 1 CFU/cm2). CFU counts were analyzed by the Mann-Whitney U -test which showed no significant difference between implant types (P <.05); independent-sample t -tests showed a significant difference. The dependent-variable techniques were then compared as groups by one-way analysis of variance, which also showed a significant reduction compared with the control group (P <.01). Conclusions This in vitro study has shown the effectiveness of antiseptic rinse and skin/implant barrier techniques for reducing bacterial contamination of breast implants at the time of insertion. [ABSTRACT FROM AUTHOR]

Hyaluronan (HA) plays well-recognized mechanical and biological roles in articular cartilage and synovial fluid, where it contributes to tissue structure and lubrication. An understanding of how HA contributes to the structure of other musculoskeletal tissues, including muscle, bone, tendon, and intervertebral discs, is growing. In addition, the use of HA-based therapies to restore damaged tissue is becoming more prevalent. Nevertheless, the relationship between biomechanical stimuli and HA synthesis, degradation, and signaling in musculoskeletal tissues remains understudied, limiting the utility of HA in regenerative medicine. In this review, we discuss the various roles and significance of endogenous HA in musculoskeletal tissues. We use what is known and unknown to motivate new lines of inquiry into HA biology within musculoskeletal tissues and in the mechanobiology governing HA metabolism by suggesting questions that remain regarding the relationship and interaction between biological and mechanical roles of HA in musculoskeletal health and disease. [ABSTRACT FROM AUTHOR]

Strigolactones are a class of phytohormones with various functions in plant development, stress responses, and in the interaction with (micro)organisms in the rhizosphere. While their effects on vegetative development are well studied, little is known about their role in reproduction. We investigated the effects of genetic and chemical modification of strigolactone levels on the timing and intensity of flowering in tomato (Solanum lycopersicum L.) and the molecular mechanisms underlying such effects. Results showed that strigolactone levels in the shoot, whether endogenous or exogenous, correlate inversely with the time of anthesis and directly with the number of flowers and the transcript levels of the florigen-encoding gene SINGLE FLOWER TRUSS (SFT) in the leaves. Transcript quantifications coupled with metabolite analyses demonstrated that strigolactones promote flowering in tomato by inducing the activation of the microRNA319-LANCEOLATE module in leaves. This, in turn, decreases gibberellin content and increases the transcription of SFT. Several other floral markers and morpho-anatomical features of developmental progression are induced in the apical meristems upon treatment with strigolactones, affecting floral transition and, more markedly, flower development. Thus, strigolactones promote meristem maturation and flower development via the induction of SFT both before and after floral transition, and their effects are blocked in plants expressing a miR319-resistant version of LANCEOLATE. Our study positions strigolactones in the context of the flowering regulation network in a model crop species. [ABSTRACT FROM AUTHOR]

Background: Seaweeds contain a widespread range of fatty acids (FA), and several of them have potential bioactivity. FAs are dynamic members of all biota, as well as being acknowledged for their critical function in initiating phytohormone interactions and acting as important participants in many defense signalling pathways of the plant system. The current study looks at the defense-eliciting potentials of fatty acids from the green seaweed Chaetomorpha antennina (Bory) Kützing and their impact on the polyphagous insect pest Spodoptera litura (Fab). Results: The seaweed was detected with 19 fatty acids, with larger proportion of hexa and octadecanoic and linoleic acids. The algal fatty acid compounds (CFA) were successful in eliciting salicylic acid and phenolic compounds biosynthesis along with defense enzymes peroxidase (PO) and polyphenol oxidase (PPO). CFA enhanced the synthesis of defense enzymes, PO and PPO and phenols, post infestation with S. litura (> 50%) compared to control plants exposed to the pest. CFA was also effective in causing direct mortalities (96–98%) to the larvae (II-V instars). S. litura larvae exposed to elicited tomato plants displayed physiological incursions that extended larval-pupal duration to 26–28 days, preventing both morphogenetic transitions as well as affecting their morphology, that lead to the emergence of adults with malformed wings, legs. As a consequence, the fecundity was reduced by 60% affecting the reproductive performances of second-generation adults. The consumption rate (RCR) of larvae exposed to CFA was decreased by 84%, depicting feeding deterrence. These larvae were also observed with > 50% reduction in the levels of phosphatase enzyme secretion, bringing down larval growth rate from 0.58 to 0.34 mg/day. Histological analysis of exposed larvae displayed midgut cell disruption. Conclusion: Hence, the study finally confirms the elicitor potentials of fatty acid compounds from C. antennina, by inducing natural systemic defenses. This investigation unlocks novel forecasts besides delivering an unconventional method for crop protection to moderate or interchange the solicitation of chemical pesticides. [ABSTRACT FROM AUTHOR]

By looking at previous literature, this study aimed to analyze the construct of plyometric exercise variation. Comprehensive methods are used for these articles, such as searching for articles in database research journals. Semantic, Scopus, Scholar, and Crossref are the data sources for this database. The variety of plyometric exercises and vertical jump skills are the main themes. Fifty-one articles were verified, and then 12 articles were evaluated based on objectives, topics, sample size, research protocols, and results. Plyometric exercises are exercises in which the movements are explosive and, besides being practical, also train muscle strength, muscular endurance, flexibility, and agility. The purpose of volleyball training is so that players can acquire good basic techniques, strengthen physical strength, and develop interests and talents. To improve jumping ability, various exercises are performed from the beginner level. Therefore, the ability to jump and jump is essential for the volleyball game. The novelty in this study is the using a form of plyometric exercise that is varied according to the characteristics of athletes aged 14-17 years that have never previously been applied in volleyball clubs, which is the focus in this study of plyometric exercise variation methods, namely plyometric squat jump, skipping and hurdle hopping. The intensity of the exercise will be adjusted to the characteristics, and physiological development of male athletes aged 14-17 years. [ABSTRACT FROM AUTHOR]

Due to recent rainfall extremes and tropical cyclones that form over the Bay of Bengal during the pre- and post-monsoon seasons, the Nagavali and Vamsadhara basins in India experience frequent floods, causing significant loss of human life and damage to agricultural lands and infrastructure. This study provides an integrated hydrologic and hydraulic modeling system that is based on the Soil and Water Assessment Tool model and the 2-Dimensional Hydrological Engineering Centre-River Analysis System, which simulates floods using Global Forecasting System rainfall forecasts with a 48-h lead time. The integrated model was used to simulate the streamflow, flood area extent, and depth for the historical flood events (i.e., 1991–2018) with peak discharges of 1200 m3/s in the Nagavali basin and 1360 m3/s in the Vamsadhara basin. The integrated model predicted flood inundation depths that were in good agreement with observed inundation depths provided by the Central Water Commission. The inundation maps generated by the integrated modeling system with a 48-h lead time for tropical cyclone Titli demonstrated an accuracy of more than 75%. The insights gained from this study will help the public and government agencies make better decisions and deal with floods. [ABSTRACT FROM AUTHOR]

Soil moisture is among the most essential variables in hydrology and earth science. Many satellite missions, such as AMSR-E/2, have been launched to observe it in broader spatial coverage to overcome the shortage of in situ observations. However, the satellite soil moisture products have been reported to comprise errors caused by the so-called "temperature effects" widely observed in dielectrically measured in situ volumetric soil water content (SWC). In this work, we confirmed the existence of these errors in AMSR2 soil moisture products. A new algorithm was developed to remove these errors using satellite data at ascending and descending overpasses. The application of this algorithm to both satellite and in situ data of SWC and soil temperature at the Mongolia site shows that the difference between SWC values at ascending and descending overpasses caused by temperature effects is effectively removed. We assess the impact of this removal method on satellite data by comparing it with in situ data, utilizing metrics such as the correlation coefficient and other widely adopted evaluation methods. It is shown that the difference between the original and corrected in situ SWC is much smaller than that between AMSR2 and in situ SWC, either corrected or not. The results indicate that the metric values between the corrected AMSR2 and in situ SWC, after removing apparent differences caused by temperature effects, slightly improved compared to those between the original AMSR2 and in situ SWC. Though these findings imply that the removed errors may not be the most dominant, considering the current significant difference between AMSR2 and in situ SWC, the removal makes the ascending and descending data have close characteristics. It may allow using data at both ascending and descending overpasses and double the temporal resolution of AMSR2 SWC data. [ABSTRACT FROM AUTHOR]

In this paper a Hetero-Dielectric Macaroni Channel Cylindrical Gate All Around FET (HD-MC CGAA FET) is proposed for reduced gate leakage analog application. The proffered device is also compared with a conventional Nanowire FET (NW-FET) and Dual Metal Hetero-Dielectric Cylindrical Gate All Around FET (DM-HD CGAA FET) so as to indicate the device efficiency of HD-MC CGAA FET. Both DM-HD CGAA FET and HD-MC CGAA FET have a combined vacuum dielectric at the drain with a silicon dioxide (SiO2) gate dielectric at the source. The structure has a symmetric gate oxide that is excellent for low power applications because of its considerably lower BTBT and OFF state gate leakages. GIDL of the HD-MC CGAA FET is lower, suggesting that this device has better insulation against leakages and its ION/IOFF ratio is higher making it better for digital applications. Based on the qualitatively obtained results, ION/IOFF ratio of HD-MC CGAA FET is 856 times better than NW-FET and 309 times better than DM-HD CGAA FET. GIDL current of HD-MC CGAA FET is measured to be 10–14 A as compared to 10–12 A of DM-HD CGAA FET and 10–10 A of NW-FET. It has also been entrenched that HD-MC CGAA FET has more promising IDS, gm, gd, GIDL, hole concentration, Transconduction Generation Factor and ION/IOFF ratio than the existing NW-FET and DM-HD CGAA FET making it highly applicable for low leakage and high frequency digital and analog application. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market. Design/methodology/approach: Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model. Findings: The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant. Practical implications: The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases. Originality/value: To the best of the authors' knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market. [ABSTRACT FROM AUTHOR]

Currently, fossil fuels play a major role in meeting the world's energy demand. Fossil fuels, in contrast, threaten the planet's ecosystems and biological processes, contribute to global warming, and result in unfavorable climatic shifts. These energy sources are also finite and will eventually deplete. Thus, energy transition, which is the key from fossil fuels to renewable energy sources, is regarded as an essential course of action for decarbonizing the global economy and reducing the catastrophic and irreversible effects of climate change. Thereby using/consuming green hydrogen energy is a vital solution to meet the world's challenges. Subsequently, the pros and cons of several hydrogen generation methods, such as the conversion of fossil fuels, biomass, water electrolysis, microbial fermentation, and photocatalysis, are then compared and outlined in terms of their technologies, economies, consumption of energy, environmental aspects, and costs. Currently, the chemical industry uses green hydrogen (H2) primarily to produce green emerging fuels methanol and ammonia (NH3), which are regarded as alternate sources of energy. Finally, the current state of energy demands, recent developments in renewable energy sources, and the potential of hydrogen as a future fuel are outlined. Moreover, the discussion concludes with predicted opportunities and challenges. [ABSTRACT FROM AUTHOR]

Background: While personality predominantly influences human cognition, emotion, and behavior, there is still an unresolved research gap concerning the association between personality and substance use within the Sri Lankan context. Methods: This descriptive cross-sectional study aimed to investigate the association between personality traits and substance use among advanced-level students aged over 18 in Western province, Sri Lanka, in 2023. Data collection was carried out using selfadministered paper-pencil questionnaires. The study variables were measured using the brief version of the Big Five Personality Inventory and the Alcohol, Smoking, and Substance Involvement Questionnaire. Data analysis involved the use of the chi-square test and Spearman correlation. Findings: Of the 441 enrolled participants, 422 provided correct responses to the questionnaire. Among them, 154 (36.5%) reported substance use. The majority of students initiated substance use at the age of 17. The results reveal a significant association between the openness personality trait and substance use among advanced-level students in Western province. Additionally, there was a statistically significant positive correlation between the extroversion personality trait and amphetamine use among advanced-level students. Conclusion: The findings highlight a significant association between specific personality traits, particularly openness and extroversion, and substance use among advanced-level students in Western province, Sri Lanka. These results emphasize the significance of considering personality factors in understanding and addressing substance use behaviors among youth populations. Further research and targeted interventions are necessary to delve deeper into these associations and develop effective prevention and intervention strategies. [ABSTRACT FROM AUTHOR]

Introduction: Skin injuries represent a prevalent form of physical trauma, necessitating effective therapeutic strategies to expedite the wound healing process. Hesperidin, a bioflavonoid naturally occurring in citrus fruits, exhibits a range of pharmacological attributes, including antimicrobial, antioxidant, antiinflammatory, anticoagulant, and analgesic properties. The main objective of the study was to formulate a hydrogel with the intention of addressing skin conditions, particularly wound healing. Methods: This research introduces a methodology for the fabrication of a membrane composed of a Polyvinyl alcohol - Sodium Alginate (PVA/A) blend, along with the inclusion of an anti-inflammatory agent, Hesperidin (H), which exhibits promising wound healing capabilities. A uniform layer of a homogeneous solution comprising PVA/A was cast. The process of crosslinking and the enhancement of hydrogel characteristics were achieved through the application of gamma irradiation at a dosage of 30 kGy. The membrane was immersed in a Hesperidin (H) solution, facilitating the permeation and absorption of the drug. The resultant system is designed to deliver H in a controlled and sustained manner, which is crucial for promoting efficient wound healing. The obtained PVA/AH hydrogel was evaluated for cytotoxicity, antioxidant and free radical scavenging activities, anti-inflammatory and membrane stability effect. In addition, its action on oxidative stress, and inflammatory markers was evaluated on BJ-1 human normal skin cell line. Results and Discussion: We determined the effect of radical scavenging activity PVA/A (49 %) and PVA/AH (87%), the inhibition of Human red blood cell membrane hemolysis by PVA/AH (81.97 and 84.34 %), hypotonicity (83.68 and 76.48 %) and protein denaturation (83.17 and 85.8 %) as compared to 250 mg/ml diclofenac (Dic.) and aspirin (Asp.), respectively. Furthermore, gene expression analysis revealed an increased expression of genes associated with anti-oxidant and anti-inflammatory properties and downregulated TNFa, NFkB, iNOS, and COX2 by 67, 52, 58 and 60%, respectively, by PVA/AH hydrogel compared to LPSstimulated BJ-1 cells. The advantages associated with Hesperidin can be ascribed to its antioxidant and anti-inflammatory attributes. The incorporation of Hesperidin into hydrogels offers promise for the development of a novel, secure, and efficient strategy for wound healing. This innovative approach holds potential as a solution for wound healing, capitalizing on the collaborative qualities of PVA/AH and gamma irradiation, which can be combined to establish a drug delivery platform for Hesperidin. [ABSTRACT FROM AUTHOR]

Background: Surgical procedures in the anterior mandibular region require a profound understanding of the complex anatomical structures to ensure patient safety. The lingual foramen (LF) and its intra-osseous canal are pivotal structures, supplying vascular and neural support to the mental region. The prevalence of LF is widely recognized, with variations among populations. Methods: The study involved 650 adult participants. Data were collected using high-resolution cone-beam computed tomography (CBCT), and statistical analysis was conducted, establishing inter-rater agreement. Results: The population had a varied age distribution, with males comprising 53.23% and females comprising 46.77%. The median lingual canal was found in the Supra and Infra spinosum (65.38%). Most participants had lateral lingual canals (60.92%). The most prevalent lingual foramina was 4 (30.62%). The study found no significant associations between gender and LF diameter, distribution in different travel directions, or LF locations. However, males had a slightly larger diameter. Conclusion: The findings provide valuable insights into LF variations based on anatomical locations, and there were no statistically significant differences in measurements across different age groups. This knowledge contributes to the evolving field of oral and maxillofacial surgery, ensuring better patient outcomes. [ABSTRACT FROM AUTHOR]

Every nation treasures its handloom heritage, and in India, the handloom industry safeguards cultural traditions, sustains millions of artisans, and preserves ancient weaving techniques. To protect this legacy, a critical need arises to distinguish genuine handloom products, exemplified by the renowned "gamucha" from India's northeast, from counterfeit powerloom imitations. Our study's objective is to create an AI tool for effortless detection of authentic handloom items amidst a sea of fakes. Six deep learning architectures—VGG16, VGG19, ResNet50, InceptionV3, InceptionResNetV2, and DenseNet201—were trained on annotated image repositories of handloom and powerloom towels (17,484 images in total, with 14,020 for training and 3464 for validation). A novel deep learning model was also proposed. Despite respectable training accuracies, the pre-trained models exhibited lower performance on the validation dataset compared to our novel model. The proposed model outperformed pre-trained models, demonstrating superior validation accuracy, lower validation loss, computational efficiency, and adaptability to the specific classification problem. Notably, the existing models showed challenges in generalizing to unseen data and raised concerns about practical deployment due to computational expenses. This study pioneers a computer-assisted approach for automated differentiation between authentic handwoven "gamucha"s and counterfeit powerloom imitations—a groundbreaking recognition method. The methodology presented not only holds scalability potential and opportunities for accuracy improvement but also suggests broader applications across diverse fabric products. [ABSTRACT FROM AUTHOR]

Introduction: Second-generation supraglottic airway devices that provide high seal pressures are found to be suitable for patients undergoing laparoscopic surgery, as they have a separate port for gastric tube insertion, effectively separating the airway and the oesophagus. The present study compares the usage of two such second-generation supraglottic devices-AuraGain™ and i-gel® in patients undergoing gynaecological laparoscopic surgeries. Aim: To compare the Oropharyngeal Leak Pressure (OLP) and airway pressures achieved by the i-gel® and Ambu AuraGain™ after insertion in the supine position and during laparoscopic carbon dioxide peritoneum in the Trendelenburg position. Materials and Methods: This randomised clinical, singleblinded study conducted at the Department of Anaesthesiology, Narayana Medical College, Nellore, Andhra pradesh, India involved 100 female patients undergoing elective gynaecological laparoscopic surgeries under general anaesthesia with controlled ventilation. The primary objective was to compare the clinical performance of Ambu AuraGain™ (Group-A) and i-gel® (Group-I) concerning their oropharyngeal seal pressures and airway pressures in gynaecological laparoscopic surgeries. The secondary outcomes measured included the time taken for insertion, ease of insertion of the device, effects on postinsertion haemodynamic parameters like heart rate, blood pressure, oxygen saturation, ease of gastric tube insertion, and fibreoptic bronchoscopic grading of the visualised glottic structures after device placement, as well as postoperative side effects like blood staining upon removal of the device and sore throat. Data were analysed using Student's t-test and chi-square test. Results: The mean age in Group-A was 39.62±4.085 years, and in Group-I, it was 39.48±2.468 years. The mean peak inspiratory pressures after device insertion were 14.34 mmHg in Group-A and 16.66 mmHg in Group-I. Haemodynamic parameters postinsertion were similar in both groups {Group-A: Mean Heart Rate (HR) 87.22 bpm, Mean Arterial Pressure (MAP) 89.72 mmHg, Oxygen Saturation (SpO2) 99.58%; Group-I: Mean HR 87.50 bpm, MAP 89.72 mmHg, SpO2 99.72%). Fibreoptic bronchoscopic grading in Group-A was 0/0/9/41, and in Group-I, it was 0/0/11/39. Blood staining upon removal was noted in four patients (8%) in Group-A and in 3 patients (6%) in Group-I. Sore throat in the postoperative period was noted in 14% of patients in Group-A and 8% in Group-I. Conclusion: Ambu AuraGain™ was found to provide a better seal and higher OLP compared to the i-gel® in gynaecological laparoscopic surgeries and therefore provide safer and more effective ventilation for patients undergoing such surgeries. I-gel® was found to be easier and quicker to insert than the AuraGain™. [ABSTRACT FROM AUTHOR]

Summary: The thrombotic risk with haemoglobin C trait (HbAC) or haemoglobin C disease (HbCC) is unclear. However, individuals with HbCC have demonstrated chronic haemolysis, higher blood viscosity and altered rheology when compared to individuals with wild‐type haemoglobin (HbAA). These physiological alterations may theoretically translate to increased risk of thrombosis; therefore, a systematic literature review was performed to investigate the possible association between HbAC and/or HbCC and thrombosis. Twenty‐two studies met inclusion criteria representing 782 individuals with HbAC (n = 694) or HbCC (n = 88). Fifteen studies described the presence/absence of venous thromboembolism (VTE) in patients with HbAC (n = 685) or HbCC (n = 79), while seven studies described patients with HbAC (n = 9) or HbCC (n = 9) and arterial thrombosis. Most (n = 20) studies were case reports or case series; however, two studies suggested a potential increased VTE risk with HbAC compared to HbAA in (i) all patients (OR 2.2, 95% CI: 0.9–5.5) and in (ii) pregnant individuals (RR 3.7, 95% CI 0.9–16). This review is the largest assessment of patients with HbC trait or disease and thrombosis to date; despite its limitations, the findings suggest HbC may be a predisposing risk factor to thrombosis. Prospective cohort studies are warranted to definitively elucidate the risk of thrombosis in this population. [ABSTRACT FROM AUTHOR]