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In the previous work [Reddy et al., J. Chem. Phys. 151, 044307 (2019)], we have analyzed the dynamics of the intramolecular singlet fission process in a series of prototypical pentacene-based dimers, where the pentacene monomers are covalently bonded to a phenylene linker in ortho, meta, and para positions. The results obtained were qualitatively consistent with the experimental data available, showing an ultrafast population of the multiexcitonic state that mainly takes place via a mediated (superexchange-like) mechanism involving charge transfer and doubly excited states. Our results also highlighted the instrumental role of molecular vibrations in the process as a sizable population of the multiexcitonic state could only be obtained through vibronic coupling. Here, we extend these studies and investigate the effect of the laser field on the dynamics of intramolecular singlet fission by explicitly including the coupling to the laser field in our model. In this manner, and by selectively tuning the laser field to the different low-lying absorption bands of the systems investigated, we analyze the wavelength dependence of the intramolecular singlet fission process. In addition, we have also analyzed how the nature of the initially photoexcited electronic state (either localized or delocalized) affects its dynamics. Altogether, our results provide new insights into the design of intramolecular singlet fission-active molecules. [ABSTRACT FROM AUTHOR]

Purpose: In a patient with elevated thyroid stimulating hormone (TSH, >50 µIU/ml) with sellar mass, it is crucial to differentiate isolated pituitary hyperplasia (IPH) from primary hypothyroidism coexisting with nonfunctioning pituitary adenoma (PHCNFPA) pre-operatively to avoid unwarranted surgery in the former condition. Here, we describe patients having pituitary mass/enlargement with markedly elevated TSH (>50 µIU/ml) and attempt to find the differentiating features between IPH and PHCNFPA. Methods: This is a retrospective study conducted at a tertiary care center. Case records of patients presenting between January 2020 and December 2022 with elevated TSH (>50 µIU/ml) for whom magnetic resonance imaging (MRI) of the sella was available were reviewed. Demographic details, symptomatology, clinical examination findings, thyroid function tests, data on pituitary hormonal excess and deficiencies, MRI findings, and details regarding levothyroxine supplementation were noted. Based on the final diagnosis, the patients were categorized into two groups: PHCNFPA and IPH. Results: Five and 11 patients were diagnosed with PHCNFPA and IPH, respectively. The median (IQR) age at presentation of patients with PHCNFPA was significantly higher than that of IPH patients [37 (28–60.5) vs. 21 (10–21.5) years, p: 0.002]. A longer duration of hypothyroid symptoms was noted in the IPH group whereas visual field defects and corticotropin deficiency were more frequent and the pituitary lesion size was greater in PHCNFPA. Thyroid function tests were not different between the two groups. The pituitary enlargement in IPH was initially an increase in pituitary height that progressed to symmetrical nipple-, dome- or tent-shaped enlargement. Besides this characteristic enlargement pattern, isointense appearance on T1-weighted and T2-weighted images, homogeneous contrast enhancement, and prompt regression of pituitary lesion with levothyroxine replacement were characteristic of IPH whereas heterogeneous enhancement, cystic/hemorrhagic change, and ≥Knosp III invasion were characteristic of PHCNFPA. Peripheral rim enhancement and Knosp I-II parasellar extension were not uncommon in patients with IPH and did not distinguish it from PHCNFPA. Conclusions: The present study reports the radiological evolution of IPH and a unique series of PHCNFPA along with the distinguishing characteristics between them. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) based smart strategies are often resource constrained with respect to energy, computation and memory. Outdated communication protocols are inappropriate for IoT ecosystem because of large overhead, lack of Quality of Service (QoS) and increased complexity. As billions of devices are required to be deployed over diverse applications, the IoT communication system acts as a prominent aspect and so the selection of suitable IoT communication protocol is highly essential. Also, there is a greater need of analysing the protocol behaviour under diverse network conditions. Hence to select a suitable protocol by addressing the limitations, this research paper mainly focuses on comparing lightweight application layer protocols, including Message Queuing Telemetry Transport (MQTT), Constrained Application Protocol (CoAP) and MQTT for sensor Network (MQTTSN). Evaluating the performance of protocol libraries in real environment is highly significant because it helps to discover potential interoperability and compatibility challenges. Also, it can reveal the protocol's ability in handling scalability and its support in dealing a number of devices efficiently. A testbed named "ProtoLab" has been created for evaluating the performances of CoAP, MQTT and MQTTSN protocols under variable network condition. Using the testbed, the client and server can exchange the data packets under the variable network condition created with the help of network emulator. The data packets can be received and exported using the wireshark application to create a dataset for analysis. Different parameters like round trip time, duplication, round trip reliability, server response time, reliability towards the client to server and client overhead are analysed by configuring loss, corruption, reordering and network delay in the network emulator using wide area network emulator (WANEM) to evaluate the performance of IoT communication protocols. Variable network conditions are considered and analysed using real-time ProtoLab testbed by varying the parameters. The results and observations analyzed through this research can support IoT application developers in making informed decisions while selecting communication protocols for different applications. On analysing the parameters under diverse network conditions, the MQTTSN protocol performs comparatively better in terms of resource efficient delivery in constrained environment. Meanwhile, the MQTT protocol is analysed to be better when concerned with reliability. [ABSTRACT FROM AUTHOR]

Pigeonpea (Cajanus cajan) is one of the important grain legume crops cultivated in the semi-arid tropics, playing a crucial role in the economic well-being of subsistence farmers. India is the major producer of pigeonpea, accounting for over 75% of the world's production. Sterility mosaic disease (SMD), caused by Pigeonpea sterility mosaic virus (PPSMV) and transmitted by the eriophyid mite (Aceria cajani), is a major constraint to pigeonpea cultivation in the Indian subcontinent, leading to potential yield losses of up to 100%. The recent characterization of another Emaravirus associated with SMD has further complicated the etiology of this challenging viral disease. This review focuses on critical areas, including the current status of the disease, transmission and host-range, rapid phenotyping techniques, as well as available disease management strategies. The review concludes with insights into the future prospects, offering an overview and direction for further research and management strategies. [ABSTRACT FROM AUTHOR]

This study addresses the critical challenge of real-time identification of tomato leaf diseases using edge computing. Traditional plant disease detection methods rely on centralized cloud-based solutions that suffer from latency issues and require substantial bandwidth, making them less viable for real-time applications in remote or bandwidth-constrained environments. In response to these limitations, this study proposes an on-the-edge processing framework employing Convolutional Neural Networks (CNNs) to identify tomato diseases. This approach brings computation closer to the data source, reducing latency and conserving bandwidth. This study evaluates various pre-trained models, including MobileNetV2, InceptionV3, ResNet50, and VGG19 against a custom CNN, training and validating them on a comprehensive dataset of tomato leaf images. MobileNetV2 demonstrated exceptional performance, achieving an accuracy of 98.99%. The results highlight the potential of edge AI to revolutionize disease detection in agricultural settings, offering a scalable, efficient, and responsive solution that can be integrated into broader smart farming systems. This approach not only improves disease detection accuracy but can also provide actionable insights and timely alerts to farmers, ultimately contributing to increased crop yields and food security. [ABSTRACT FROM AUTHOR]

The influence of boundary layer flow of heat transfer analysis on hybrid nanofluid across an extended cylinder is the main focus of the current research. In addition, the impressions of magnetohydrodynamic, porous medium and thermal radiation are part of this investigation. Arrogate similarity variables are employed to transform the governing modelled partial differential equations into a couple of highly nonlinear ordinary differential equations. A numerical approach based on the BVP Midrich scheme in MAPLE solver is employed for solution of the set of resulting ordinary differential equations and obtained results are compared with existing literature. The effect of active important physical parameters like Magnetic Field, Porosity parameter, Eckert number, Prandtl number and thermal radiation parameters on dimensionless velocity and energy fields are employed via graphs and tables. The velocity profile decreased by about 65% when the magnetic field parameter values increases from 0.5 to 1.5. On the other hand increased by 70% on energy profile. The energy profile enhanced by about 62% when the Radiation parameter values increases from 1.0 < Rd < 3.0. The current model may be applicable in real life practical implications of employing Engine oil-SWCNTs-MWCNTs-TiO2 nanofluids on cylinders encompass enhanced heat transfer efficiency, and extended component lifespan, energy savings, and environmental benefits. This kind of theoretical analysis may be used in daily life applications, such as engineering and automobile industries. [ABSTRACT FROM AUTHOR]

The article presents a study on the genetic parameters for yield and its component traits in urd bean of Vigna mungo L. Hepper, one of the important pulse crops in India. Topics include genetic variability for all characters, estimates of heritability for all the traits, and path coefficient analysis at phenotypic level.

This paper aims to underscore the pivotal role of higher-order thinking skills (HOTs) within engineering education, recognizing their fundamental importance for students in this domain. In an era defined by rapid technological advancements and continual change, the imperative for engineering educators is to equip students with the requisite abilities to thrive in today's landscape. Meeting this challenge necessitates innovative pedagogical approaches aligned with contemporary teaching and learning paradigms. Consequently, this paper introduces a comprehensive framework comprising six distinct teaching-learning strategies designed to cultivate crucial attributes in engineering students. These strategies focus on nurturing creativity and critical thinking, fostering collaborative learning environments, harnessing teaching as a learning tool, incorporating thematic-based case studies for enhanced comprehension, facilitating group-based learning opportunities, and refining communication skills alongside effective problem-solving techniques. Together, these methodologies form an integrated educational strategy that not only enhances students' cognitive capacities but also addresses the interpersonal and adaptive skills crucial for success in the intricate and ever-changing realm of engineering. As engineering education navigates the modern landscape, these outlined methodologies serve as a guide for instructors to empower their students with the multifaceted proficiencies demanded by today's evolving technological sphere. [ABSTRACT FROM AUTHOR]

In the future, intelligent transportation systems will rely heavily on vehicle to vehicle (V2V) communication-based cooperative vehicular networks since they can provide several applications for tackling traffic congestion and road safety. Future 6G and New Radio 5G (NR5G) technology will facilitate improving cellular vehicle to everything (CV2X) communication performance. Cellular-assisted V2V communications, in which cellular evolved Node base stations (eNBs) relay the transmission from one vehicle to another, have lately been proposed to overcome the performance restrictions of conventional dedicated short-range communication (DSRC) protocols (Kimura in IEEE Trans Veh Technol 70(4): 3396–3411, 2021. 10.1109/TVT.2021.3063694). These cellular-aided communications have demonstrated the potential for more reliable V2V communications with a larger capacity and longer transmission distances. In this paper, we theoretically examine the effectiveness of cellular vehicle to everything communications, where a vehicle broadcasts a message to its nearby vehicles or user equipment (UEs). It happens in two ways, i.e., direct vehicle to vehicle and via the closest eNB through an uplink. Then the closest eNB forwards the message to the destination vehicle via downlink i.e., vehicle to network (V2N) or vehicle to infrastructure (V2I). To obtain a suitable model for estimating the Bit Error Rate (BER) and the Packet Error Rate (PER), we consider the movement of three vehicles are in a straight line on the roadways with different velocities. Using numerical examples, we assess the analytical findings and show how different system factors affect the effectiveness of CV2X communications. A simulation has been carried out in the network (system) level context. [ABSTRACT FROM AUTHOR]

This paper introduces an effective blind watermarking algorithm for double-color images utilizing the Walsh–Hadamard Transform (WHT) with symmetric embedding locations to enhance imperceptibility. The proposed algorithm leverages the energy accumulation capability and significant correlations among coefficients of the WHT. First, the color host image undergoes partitioning into its respective red (R), green (G), and blue (B) channels, followed by further subdivision into 4 × 4 blocks. Through research, the algorithm determines which WHT coefficients are least visually sensitive to embedding a color image, and as a result, optimizes the embedding locations to achieve better imperceptibility. The extensive simulation results verify the superior performance of the proposed algorithm compared to other related approaches, showcasing its excellence not only in imperceptibility but also in embedding capacity and robustness. [ABSTRACT FROM AUTHOR]

A study of capital structure involves an examination of long term as well as short term sources that a company taps to meet its requirement of finance. This study covers introduction to ultra tech cement and making of the investment in an appropriate manner to maintain the company's sustainability to serve in the market. The scope of the study confined to the sources that ultratech cements tapped over the years knowing the relationship between capital structure and value of firm value. [ABSTRACT FROM AUTHOR]

Mutual fund investments are important if you want to build yourself financially in the long term. A mutual fund is a financial vehicle that is composed of money collected from investors for investing in bonds, stocks, and other assets. These are operated by professional oney managers who allocate fund assets to produce gains for fund investors. This article will help your journey of mutual fund investments. [ABSTRACT FROM AUTHOR]

Every organization needs inventory for the smooth running of its activities. It serves as a link between production and distribution processes. The investment in inventories constitutes the most significant part of current assets/working capital in most of the undertakings. Thus, it is essential to have proper control and management of inventories. The purpose of inventory management is to ensure availability of materials in sufficient quantity as and when required and to minimize investment in inventories. So, to understand the nature of inventory management of the organization, I took this Inventory Management as a topic for my project, to give findings and suggestions by adopting and analyzing different inventory control techniques. [ABSTRACT FROM AUTHOR]

One plus one makes three: this equation is the special alchemy of a merger or an acquisition. The key principle behind buying a company is to create shareholder value over and above that of the sum of the two companies. Two companies together are more valuable than two separate companies - at least, that's the reason behind M&A. This rationale is particularly alluring to companies when times are tough. Strong companies will act to buy other companies to create a more competitive, cost-efficient company. The companies will come together hoping to gain a greater market share or to achieve greater efficiency. Because of these potential benefits, target companies will often agree to be purchased when they know they cannot survive alone. [ABSTRACT FROM AUTHOR]

In today's competitive world, a lot of investment alternatives in banking are being provided by both public sector and private sector financial institutions. But we have no idea about how much people are aware of these opportunities and able to access those services especially in rural villages. This study also facilitates to analyse various guiding factors for making a good banking decision. The aim of this study is to examine the behaviour of the middle-income class people in ICICI bank and also to identify various factors influencing their banking decisions. So analyzing and evaluating various guiding factors that influences their behaviour of middle class people. [ABSTRACT FROM AUTHOR]

Working capital gives investors an idea of the company's underlying operational efficiency. Money that is tied up in inventory or money that customers still owe to the company can't be used to pay off any of its obligations. So, if a company is not operating in the most efficient manner (slow collection) it will show up in the working capital. This can be seen by comparing the working capital from one period of time to another; slow collection may signal an underlying problem in the company's operations. [ABSTRACT FROM AUTHOR]

The customer visits the financial institution's secure website, and enters the E-banking facility using the customer number and credentials previously set up. The types of financial transactions which a customer may transact through E-banking are determined by the financial institution, but usually includes obtaining account balances, a list of the recent transactions, electronic bill payments and funds transfers between a customer's or another's accounts. Most banks also enable a customer to download copies of bank statements, which can be printed at the customer's premises (some banks charge a fee for mailing hard copies of bank statements). Some banks also enable customers to download transactions directly into the customer's accounting software. The facility may also enable the customer to order a cheque book, statements, report loss of credit cards, stop payment on a cheque, advise change of address and other routine actions. Today, many banks are internet-only institutions. These "virtual banks" have lower overhead costs than their brick-and-mortar counterparts. In the United States, many online banks are insured by the Federal Deposit Insurance Corporation (FDIC) and can offer the same level of protection for the customers' funds as traditional banks. [ABSTRACT FROM AUTHOR]

The financial market is the driver of the economic growth and development of any country. A sound financial market can take the country to the apex. Financial resources were by allocating the resources through one of the ways such as portfolios, which are combinations of various securities. Portfolio analysis includes analyzing the range of possible portfolios that can be constituted from a given set of securities. [ABSTRACT FROM AUTHOR]

The 5G-heterogeneous system has become worldwide in the current life scenario, advancing in many wireless applications. However, managing Handoff is a major issue because the improper Handoff procedure leads to high power consumption and less throughput ratio. Hence, the lower throughput ratio tends to report a poor data transmission rate. So, the current research work has planned to end these issues by executing a novel Wolf-based Power-Optimized Handoff (WbPOH) strategy for managing signal drop and power usage. WiMax and cellular network macrocells are created with several Small Cells (SC) to make the heterogeneous system. Hereafter, the fitness process of the grey wolf has afforded continuous monitoring for forecasting the nearest incoming signal of Handoff and work-free node prediction. Moreover, the power usage in this designed system has been optimized by making the workless node the sleep position. Apart from that, during the Handoff process, the designed WbPOH first enabled the single strongest near signal, and then the previous signal was lost. After that, parameters like throughput, network efficiency, and Handoff behaviour have been measured and validated with other conventional models. Furthermore, in the proposed novel WbPOH, 5Mbps throughput is obtained for the cellular network, and 5.2Mbps throughput is gained for the Worldwide Inter-operability for Microwave Access (WiMax) network. In addition, the recorded cellular network efficiency is 95%, and the WiMax network efficiency is 96%. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing is one of the important approaches in the area of remote sensing owing to the latest enhancements in the Hyper Spectral Imaging (HSI) technology. The classification represents a direct approach in the HSI field that provides every pixel a particular semantic label based on its behavior automatically. Nowadays, deep learning-oriented techniques have gained wide attention in the area of HSI classification. Although Convolutional Neural Network (CNN)-oriented techniques are subjected to the HSI classification, their performances are not up to the expectation. This is because; the majority of the traditional techniques cannot utilize the intrinsic behavior of distinct pixels in HSI efficiently. The inherent relationships are ignored between distinct category dependencies, distinct spectral bands, and distinct spatial pixels. Moreover, deep learning methods are required to build a huge and complicated network, and hence the training process tends to be time-consuming. Hence, these work tactics to design and implement a novel HSI classification method using deep structured architectures. The major stages of the offered method are feature extraction, and classification. Initially, the HSI from RIT-18 benchmark sources is collected. Before processing it for feature extraction, the images are split into 'n' number of patches, where the length of every patch is 16 × 16. Then the feature extraction begins, in which the spatial and spectral features, as well as the Enhanced CNN, are utilized for acquiring the deep features from the entire patches. In the CNN, the architecture is enhanced by the "Modified Velocity-based Colliding Bodies Optimization (MV-CBO)". Then, the entire features acquired from all the patches are concatenated. Finally, the utilization of deep structured architectures termed modified Recurrent Neural Network (RNN) is utilized in the classification phase, which classifies the images into different categories as per the dataset. The RNN architecture is also modified by the MV-CBO to attain high classification accuracy. From the simulation results, the accuracy rate of the MV-CBO-M-RNN at a 75% learning rate is correspondingly secured at 3.16%, 4.26%, 1.03%, and 2.08% more advanced than DNN, RNN, CNN, and NN. The validation of the recommended technique on challenging public datasets, and the experimental evaluation over baseline approaches validates the efficiency and robustness of the suggested model. [ABSTRACT FROM AUTHOR]

In this study, the emission and performance characteristics of single-cylinder diesel engines were tested using various biodiesel blends prepared by mixing diesel with mango seed oil biodiesel (MSOB). Furthermore, the effect of n-amyl and n-hexanol alcohol additions on the performance and emission results of manufactured biodiesel blends is investigated and compared with diesel fuel. On the other hand, a hybrid deep neural network (DNN) based on the manta ray foraging optimization (MRFO) method is developed to forecast ideal biodiesel blends in order to reduce emissions from diesel engines while improving performance. The optimal brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) for this study were 32.3916 % for 75 % diesel + 20 % MSOB + 5 % n-hexanol fuel and 0.0453 kg/kWh for 75 % diesel + 20 % MSOB + 5 % n-amyl fuel, respectively. The optimal emissions from the test engine were 0.1034 % CO from 60 % diesel + 20 % MSOB + 20 % n-hexanol and 28.886 ppm HC from 75 % diesel + 20 % MSOB + 5 % n-hexanol fuel. The optimal smoke and NOx levels are achieved with a blend of 60 % diesel, 20 % MSOB, 5 % n-amyl, and 5 % n-hexane. Moreover, the developed DNN-MRFO achieved 0.9979, 0.9992 and 0.9975 overall regression coefficients during training, validation and testing. The root mean square error (RMSE) of DNN-MRFO also ranges from 0.019 to 0.032. [ABSTRACT FROM AUTHOR]

The physiological system loses heat energy through the bloodstream to nearby cells. Such energy loss can lead to a quick death, anemia, severe hypothermia and high or low blood pressure to heart surgery. As a result, biomedical engineers and physicians are increasingly attracted to the study of entropy production to calculate the energy loss of biological systems. Furthermore, the thermodynamic state of entropy production is used to access cancer cells during chemotherapy treatment and heat transfer in tissues. The current model intends to explore the significance of the non-Fourier heat flux model on Eyring–Powell/Maxwell hybrid nanofluid (Fe3O4–CuO/blood) flow in a linear extending sheet with induced magnetic field and entropy generation. Suitable self-similarity variables are performed to convert momentum and thermal equations determined using the homotopy perturbation method into ordinary differential equations. The significance of distinct physical parameters such as thermal relaxation parameter, volume fraction, fluid parameter, magnetic Prandtl number, Biot number, Brinkman number, heat source, Eckert number, radiation and heat source on velocity, temperature, skin friction coefficient, Nusselt number, entropy production, streamlines and isotherm are represented through figures. It is recognized that the fluid friction irreversibility is comparatively higher than thermal irreversibility and highly dominates the total entropy generation. The nanoparticle volume fraction diminishes the velocity and induced magnetic field of both Eyring–Powell and Maxwell hybrid nanofluid. Fluid friction irreversibility is more in Maxwell fluid compared to the Eyring–Powell fluid. [ABSTRACT FROM AUTHOR]

Though biosecurity and best management practices (BMPs), vaccines, immunostimulants, probiotics and prebiotics are often used for health management in aquaculture, the use of chemotherapeutics/antibiotics often becomes the preferred method of choice once the infectious disease outbreak occurs. Phage-based control of bacterial pathogens (phage therapy) has recently re-emerged as an attractive therapeutic alternative due to the global emergence of antimicrobial-resistant bacterial pathogens. Target specificity with minimal disruption of natural microbiota, auto-dosing, safety, no production of toxic metabolites/residues and relatively inexpensive production are some of the distinct advantages of phages over antibiotics. In vivo, experimental studies have demonstrated the efficacy of phage therapy through immersion, oral, injection, topical application, and anal intubation routes against Aeromonas hydrophila, A. salmonicida, Edwardsiella tarda, Flavobacterium columnare, Pseudomonas aeruginosa, Streptococcus iniae, Vibrio anguillarum, V. harveyi, V. parahaemolyticus, etc. in aquaculture. Several factors such as phage selection, therapeutic dose, age of fish, specific targeting of the pathogen, disease condition of fish, environmental conditions, and administration route influence the efficacy of phage therapy in aquaculture. The application of a mixture of phages (phage cocktail) has also been suggested to overcome the narrow host range of phages and the development of phage resistance in bacteria. At present, a few commercial phage cocktail-based products are also available for control of Yersinia ruckeri, Aeromonas spp., Pseudomonas spp., and shrimp pathogenic vibrios in aquaculture. To successfully implement phage therapy, there is a need to develop region-specific/localized phage repositories with associated safety and efficacy data which could be used to quickly formulate effective phage cocktails after the identification of pathogenic bacterial strains in specific aquaculture areas. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications. [ABSTRACT FROM AUTHOR]

In the current scenario, renewable energy sources (RES) are used in transport applications to minimise the dependency on fossil fuels. The electrical vehicle (EV) has contributed a vital role in smart grids with the penetration of RES. The battery connected EVs have increased in the past few years owing to numerous benefits. Thus, it is necessary to develop an optimum charging controller for the charging station to meet the energy demand. In order to accomplish this goal, hybrid fuzzy fractional order proportional integral derivative (HF2OPID) is proposed. Meanwhile, the controlling parameters of the HF2OPID are tuned by all member based optimisation algorithms (AMBO). Alongside, a hybrid honey badger recurrent neural network (H2B-RNN) provides peak power from the solar photovoltaic (SPV) module. The honey badger optimisation algorithm examines the optimum weights of the layers. The proposed method is implemented on the MATLAB/Simulink platform, and the results are compared with the existing methods. The obtained results demonstrate the proposed method's compatibility with the available techniques in the literature. [ABSTRACT FROM AUTHOR]

Ternary logic has an advantage over conventional binary logic since it uses less power and promises to take up less space on chips and in interconnects. When ternary logic is used to design multiplier circuits, they exhibit good efficiency. A device known as a carbon nanotube field-effect transistor (CNTFET) offers more benefits than a MOSFET, including low off-current characteristics like low power and good performance. In this paper, a new 1-trit multiplier design is suggested along with a comparison of four 1-trit multiplier ideas based on CNTFETs. Power, latency, PDP, and the number of transistors is compared. Power, speed, and PDP are all improved by the suggested 1-trit multiplier. There are fewer transistors required. The Cadence Virtuoso Tool simulates each of these circuits using CNTFET 32 nm technology. [ABSTRACT FROM AUTHOR]

In this study, the influence of surfactant on the specific capacitance of nickel oxide nanoparticles (NiO NPs) for supercapacitor applications is studied. We synthesized nickel oxide (NiO) and nickel oxide with sodium dodecyl sulphate (NiO/SDS) NPs using solution combustion synthesis SDS is significant in synthesizing nanomaterials that allow control over particle size, shape and stability. They can enhance the performance of nanoscale materials as energy storage materials by improving their electrochemical activity and charge transfer kinetics. The synthesized material’s performance was further characterized using X-ray diffraction (XRD), UV–vis spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscope, energy dispersive spectroscopy and transmission electron microscopy. The typical crystalline sizes of NiO and NiO/SDS nanomaterials were 28 and 22 nm, respectively. XRD analysis reveals that the structure of NiO is FCC. In addition, the electrochemical performance of the active material was investigated in the electrolyte 6M with potassium hydroxide. Accordingly, specific capacitances of NiO and NiO/SDS are observed as 955 and 1024 F g–1 at a 2 mV s–1 scan rate. It was established that NiO/SDS NPs offer considerably superior electrochemical performance due to the surfactant SDS’s inclusion in contrast to NiO NPs. [ABSTRACT FROM AUTHOR]

Herein, we have reported the synthesis of a macrocyclic organosulfur ligand (L1) having a seventeen‐membered macrocyclic ring. Subsequently, the corresponding trans‐palladium complex (C1) of bulky macrocyclic organosulfur ligand (L1) was synthesized by reacting it with PdCl2(CH3CN)2 salt. The newly synthesized ligand and complex were characterized using various analytical and spectroscopic techniques. The complex showed a square planar geometry with trans orientation of two ligands around the palladium center. The complex possesses intramolecular SCH...Cl interactions of 2.648 Å between the macrocyclic ligand and palladium dichloride. The potential energy surface (PES) for the rotational process of C1 suggested a barrier of ~23.81 kcal/mol for chlorine rotation. Furthermore, the bulky macrocyclic organosulfur ligand stabilized palladium complex (C1) was used as a catalyst (2.5 mol %) for α‐olefination of nitriles by primary alcohols. The α,β‐unsaturated nitrile compounds were found to be the major product of the reaction (57–78 % yield) with broad substrate scope and large functional group tolerance. Notably, the saturated nitrile product was not observed during the reaction. The mechanistic studies suggested the formation of H2 and H2O as only by‐products of the reaction, thereby making the protocol greener and sustainable. [ABSTRACT FROM AUTHOR]

Background: Lentil is one of the most significant pulse crops, frequently referred to as "poor man's meat" because of its high protein content and inexpensive price. The present study was assessed for eleven morphological and yield variables to determine genetic variability, correlation and path co-efficients. Methods: The experiment was conducted in a randomized complete block design using 56 different homogeneous progenies of a spontaneous mutant of lentil variety DPL 62 and four control varieties in triple replica during rabi 2017-18. Result: Significant amount of variability was observed for all the traits. High phenotypic coefficients of variance and genotypic coefficients of variance coupled with high heritability and genetic advance were observed for peduncle length, number of pods per plant, seed width, seed yield per plant suggesting that these traits are genetically controlled by additive gene action. Seed yield per plant exhibited significant positive association with number of branches/plant and number of pods/plant while number of pods/plant revealed highest positive direct effect on seed yield per plant followed by 100-seed weight, number of branches per plant, days to maturity and leaflet breadth. Therefore, selection for these characters will directly lead to improvement in the yielding ability of lentil genotypes. [ABSTRACT FROM AUTHOR]

The exponential growth of Internet of Things (IoT) devices has resulted in an unparalleled surge in the need for energy-efficient strategies to guarantee the sustainability and durability of IoT networks. This study article provides a thorough examination of energyefficiency optimization in Internet of Things (IoT) networks, with a specific emphasis on the creation of algorithms, methodologies, and empirical investigations. The article commences by providing an overview of the significant significance of energy efficiency in Internet of Things (IoT) networks and its direct influence on the lifetime of devices, scalability of networks, and environmental sustainability. This emphasizes the urgent need for inventive approaches to tackle the difficulties presented by resource-limited Internet of Things (IoT) devices. Subsequently, the present study undertakes an in-depth examination of existing methodologies and algorithms for optimizing energy efficiency in Internet of Things (IoT) networks. This paper presents a comprehensive examination of each category, including insights into their respective strengths, limits, and suitability for various Internet of Things (IoT) applications. This study presents innovative algorithms and strategies that are especially developed to improve energy efficiency in Internet of Things (IoT) networks. These advancements use cutting-edge technology such as machine learning, edge computing, and low-power device design. The paper provides comprehensive explanations of these methodologies, accompanied by simulations and performance assessments, to showcase their efficacy in attaining energy conservation while maintaining network dependability and service excellence. The case studies presented provide valuable perspectives on the practical use of energy-efficient technologies, demonstrating their effectiveness in reducing operating expenses, carbon emissions, and system downtime. Moreover, this study aims to discuss the many problems and unresolved research inquiries pertaining to energy-efficient Internet of Things (IoT) networks. The aforementioned points underscore the need for further investigation in several aspects, including scalability challenges, security implications, and standardization efforts. These areas of focus are crucial in order to foster the ongoing expansion and long-term viability of Internet of Things (IoT) ecosystems. [ABSTRACT FROM AUTHOR]