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The paper aims to carry out a comprehensive literature mapping to synthesise and descriptively analyse the research trends of biodiversity accounting, providing implications for managers and policymakers, whilst also outlining a future agenda for scholars.

A bibliometric analysis is carried out by adopting the Preferred Reporting Items for Systematic Review and Meta-Analyses protocol for searching and selecting the scientific contributions to be analysed. Citation analysis is used to map a current research front and a bibliographic coupling is conducted to detect the connection networks in current literature.

Biodiversity accounting is articulated in five thematic clusters (sub-areas), such as “Natural resource management”, “Biodiversity economic evaluation”, “Natural capital accounting”, “Biodiversity accountability” and “Biodiversity disclosure and reporting”. Critical insights emerge from the content analysis of these sub-areas.

The analysis of the thematic evolution of the biodiversity accounting literature provides useful insights to inform both practice and research and infer implications for managers, policymakers and scholars by outlining three main areas of intervention, i.e. adjusting evaluation tools, integrating ecological knowledge and establishing corporate social legitimacy.

Currently, the level of biodiversity reporting is pitifully low. Therefore, organisations should properly manage biodiversity by integrating diverse and sometimes competing forms of knowledge for the stable and resilient flow of ecosystem services for future generations.

This paper not only updates and enriches the current state of the art but also identifies five thematic areas of the biodiversity accounting literature for theoretical and practical considerations.

Due to the continuous and rapid evolution of telecommunication equipment, the demand for more efficient and noise-robust detection of dual-tone multi-frequency (DTMF) signals is most significant.

A novel machine learning-based approach to detect DTMF tones affected by noise, frequency and time variations by employing the k-nearest neighbour (KNN) algorithm is proposed. The features required for training the proposed KNN classifier are extracted using Goertzel's algorithm that estimates the absolute discrete Fourier transform (DFT) coefficient values for the fundamental DTMF frequencies with or without considering their second harmonic frequencies. The proposed KNN classifier model is configured in four different manners which differ in being trained with or without augmented data, as well as, with or without the inclusion of second harmonic frequency DFT coefficient values as features.

It is found that the model which is trained using the augmented data set and additionally includes the absolute DFT values of the second harmonic frequency values for the eight fundamental DTMF frequencies as the features, achieved the best performance with a macro classification F1 score of 0.980835, a five-fold stratified cross-validation accuracy of 98.47% and test data set detection accuracy of 98.1053%.

The generated DTMF signal has been classified and detected using the proposed KNN classifier which utilizes the DFT coefficient along with second harmonic frequencies for better classification. Additionally, the proposed KNN classifier has been compared with existing models to ascertain its superiority and proclaim its state-of-the-art performance.

The primary aim of this paper is to present a novel design approach for a ring voltage-controlled oscillator (VCO) suitable for L-band applications, whose oscillation frequency is less sensitive to power supply variations. In a few decades, with the advancement of modern wireless communication equipment, there has been an increasing demand for low-power and robust communication systems for longer battery life. A sudden drop in power significantly affects the performance of the VCO. Supply insensitive circuit design is the backbone of uninterrupted VCO performance. Because of their important roles in a variety of applications, VCOs and phase locked loops (PLLs) have been the subject of significant research for decades. For a few decades, the VCO has been one of the major components used to provide a local frequency signal to the PLL.

First, this paper chose to present recent developments on implemented techniques of ring VCO design for various applications. A complementary metal oxide semiconductor (CMOS)-based supply compensation technique is presented, which aims to reduce the change in oscillation frequency with the supply. The proposed circuit is designed and simulated on Cadence Virtuoso in 0.18 µm CMOS process under 1.8 V power supply. Active differential configuration with a cross-coupled NMOS structure is designed, which eliminates losses and negates supply noise. The proposed VCO is designed for excellent performance in many areas, including the L-band microwave frequency range, supply sensitivity, occupied area, power consumption and phase noise.

This work provides the complete design aspect of a novel ring VCO design for the L-band frequency range, low phase noise, low occupied area and low power applications. The maximum value of the supply sensitivity for the proposed ring VCO is 1.31, which is achieved by changing the VDD by ±0.5%. A tuning frequency range of 1.47–1.81 GHz is achieved, which falls within the L-band frequency range. This frequency range is achieved by varying the control voltage from 0.0 to 0.8 V, which shows that the proposed ring VCO is also suitable for low voltage regions. The total power consumed by the proposed ring VCO is 14.70 mW, a remarkably low value using this large transistor count. The achievable value of phase noise is −88.76 dBc/Hz @ 1 MHz offset frequency, which is a relatively small value. The performance of the proposed ring VCO is also evaluated by the figure of merit, achieving −163.13 dBc/Hz, which assures the specificity of the proposed design. The process and temperature variation simulations also validate the proposed design. The proposed oscillator occupied an extremely small area of only 0.00019 mm² compared to contemporary designs.

The proposed CMOS-based supply compensation method is a unique design with the size and other parameters of the components used. All the data and results obtained show its originality in comparison with other designs. The obtained results are preserved to the fullest extent.

In this study a numerical analysis of the elastohydrodynamic lubrication point contact problem in the unsteady state of reciprocating motion is presented. The effects of frequency, stroke length and load on film thickness and pressure variation during one operating cycle are discussed. The general tribological behavior of elastohydrodynamic lubrication during reciprocating motion is explained.

The system of equations of Reynolds, film thickness considering surface deformation and load balance equations are solved using the Newton-Raphson technique with the Gauss-Seidel iteration method. Numerical solutions were performed with a sinusoidal contact surface velocity to simulate reciprocating elastohydrodynamics. The methodology is validated using historical experimental measurements/observations and numerical predictions from other researchers.

The numerical results showed that the change in oil film during a stroke is controlled by both wedge and squeeze effects. When the surface velocity is zero at the stroke end, the squeeze effect is most noticeable. As the frequency increases, the general trend of central and minimum film thickness increases. With the same entraining speed but different stroke lengths, the properties of the oil film differ from one another, with an increase in stroke length leading to a reduction in film thickness. Finally, the numerical results showed that the overall film thickness decreases with increasing load.

General tribological behaviors of elastohydrodynamic lubricating point contact, represented by pressure and film thickness variations over time and profiles, are analyzed under reciprocating motion during one working cycle to show the effects of frequency, stroke length and applied load.

Traditional level inverter technology has drawbacks in the aspect of Total harmonic distortion (THD) and switching losses for higher frequencies. Due to these drawbacks, two-level inverters have become unprofitable for high-power applications. Multilevel inverters (MLIs) are used to enhance the output waveform characteristics (i.e. low THD) and to offer various inverter topologies and switching methods.

MLIs are upgraded versions of two-level inverters that offer more output levels in current and voltage waveforms while lowering the dv/dt and di/dt ratios. This paper aims to review and compare the different topologies of MLI used in high-power applications. Single and multisource MLI's working principal and switching states for each topology are demonstrated and compared. A Simulink model system integrated using detailed circuit simulations in developed in MATLAB®–Simulink program. In this system, a constant voltage source connected to MLI to feed asynchronous motor with squirrel cage rotor type is used to demonstrate the efficacy of the MLI under different varying speed and torque conditions.

MLI has presented better control and good range of system parameters than two-level inverter. It is suggested that the MLIs like cascade-five-level and NPC-five-level have shown low current harmonics of around 0.43% and 1.87%, respectively, compared to two-level inverter showing 5.82%.

This study is the first of its kind comparing the different topologies of single and multisource MLIs. This study suggests that the MLIs are more suitable for high-power applications.

This paper aims to obtain a symmetrical step-down topology with lower equivalent capacity and wider step-down range under the condition of the same output. Two new symmetrical step-down topologies of star-connected autotransformers are proposed in this paper. Taking the equivalent capacity as the main parameter, the obtained topologies are modeled and analyzed in detail.

This paper adopts the research methods of design, modeling, analysis and simulation verification. First, the star-connected autotransformer is redesigned according to the design objective of symmetrical step-down topology. In addition, the mathematical model of two topologies is established and a detailed theoretical analysis is carried out. Finally, the theoretical results are verified by simulation.

Two symmetrical star-connected autotransformer step-down topologies are designed, the winding configurations of the corresponding topology are presented, the step-down ranges of these three topologies are calculated and the influence of step-down ratio on the equivalent capacity of autotransformer are analyzed. Through analysis, the target step-down topologies are obtained when the step-down ratio is [1.1, 5.4] and [1.1, 1.9] respectively.

Because the selected research object is only a star-connected autotransformer, the research results may lack generality. Therefore, researchers are encouraged to further study the topologies of other autotransformers.

This paper includes the implications of the step-down ratio on the equivalent capacity of autotransformers and the configuration of transformer windings.

The topologies designed in this paper enable star-connected autotransformer in the 12-pulse rectifier to be applied in step-down circumstances rather than situations of harmonic reduction only. At the same time, this paper provides a way that can be used to redesign the autotransformer in other multi-pulse rectifier systems, so that those transformers can be used in voltage regulation.

The fluctuations that occurred between the power requirements have shown a higher range of voltage regulations and frequency. The fluctuations are caused because of substantial changes in the energy dissipation. The operational efficiency has been reduced when the power grid is enabled with the help of electric vehicles (EVs) that were created by the power resources. The model showed an active load matching for regulating the power and there occurred a harmonic motion in energy. The main purpose of the proposed research is to handle the energy sources for stabilization which has increased the reliability and improved the power efficiency. This study or paper aims to elaborate the security and privacy challenges present in the vehicle 2 grid (V2G) network and their impact with grid resilience.

The smart framework is proposed which works based on Internet of Things and edge computations that managed to perform an effective V2G operation. Thus, an optimum model for scheduling the charge is designed on each EV to maximize the number of users and selecting the best EV using the proposed ant colony optimization (ACO). At the first, the constructive phase of ACO where the ants in the colony generate the feasible solutions. The constructive phase with local search generates an ACO algorithm that uses the heterogeneous colony of ants and finds effectively the best-known solutions widely to overcome the problem.

The results obtained by the existing in-circuit serial programming-plug-in electric vehicles model in terms of power usage ranged from 0.94 to 0.96 kWh which was lower when compared to the proposed ACO that showed power usage of 0.995 to 0.939 kWh, respectively, with time. The results showed that the energy aware routed with ACO provided feasible routing solutions for the source node that provided the sensor network at its lifetime and security at the time of authentication.

The proposed ACO is aware of energy routing protocol that has been analyzed and compared with the energy utilization with respect to the sensor area network which uses power resources effectively.

The fiscal outlay efficiency matters when the performance-based allocation of funds is made to state governments by the central government in a federal structure of an economy like India. Also the efficiency cannon of public expenditure is a key aspect in the field of public economics. Thus, a study to evaluate the efficiency in fiscal outlay of Indian states has been conducted.

The paper offers a three divisions–based paradigm under Network Data Envelopment Analysis framework to compare the performance of fiscal entities (say Indian state governments) in converting available fiscal resources into desired short-run and long-run growth and development objectives. The network efficiency score has been taken as a measure of the quality of fiscal outlay management that is trifurcated into divisional efficiencies representing budgeting process, fiscal outlay efficiency process and fiscal outlay effectiveness process.

It has been noticed that the states are under performing in achieving short-run growth targets and so the efficiency process division has been identified a major source of fiscal under performance. Suboptimum allocation of fiscal expenditure under various heads within the fiscal resources, as explained under budgeting process, is another major cause of fiscal under performance.

The study purposes a three divisions–based paradigm that takes into account efficiency of a state in (1) planning budget, (2) achieving short-run growth targets and (3) achieving long-run development targets. These three stages are named as budgeting process efficiency, fiscal outlay efficiency and fiscal outlay effectiveness, respectively. Therefore, a new paradigm called BEE paradigm is proposed to evaluate performance of fiscal entities in terms of fiscal outlay efficiency.

In existing literature on measuring efficiency of public expenditure, the public sector outputs have been made as function of fiscal expenditure as input treating the said outlay as an exogenous variable. In present context, the fiscal expenditure has been treated endogenous to the budgeting process. A high inefficiency on account of budgeting process supports this treatment too.

This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

Innovation ambidexterity is crucial for fostering growth and gaining a competitive advantage in small and medium enterprises (SMEs). Previous research indicates that achieving a balance between exploration and exploitation is a multifaceted phenomenon occurring across various levels. This paper aims to examine the influence of individual, organizational and institutional factors on the ambidextrous innovation of Chinese niche leaders using a configurational perspective.

This study uses secondary data collected from 69 Chinese niche leaders in the new equipment manufacturing industry. The authors use fuzzy-set qualitative comparative analysis to investigate how owner openness, age, digitization, the formal institutional environment and the informal institutional environment jointly influence innovation ambidexterity.

By using fuzzy set analysis, this study categorizes combinations of interdependent factors that promote innovation ambidexterity. In particular, the authors pinpoint three configurations that foster high innovation ambidexterity and two configurations that lack such high levels of innovation ambidexterity. The analysis results suggest that innovation paradoxes in SMEs are linked to a nested system comprising leadership, organizational factors and the institutional environment.

This study elucidates the mechanism of innovation ambidexterity through a configurational perspective. This research proposes and validates a framework that enables SMEs to develop ambidextrous innovation capabilities, thereby integrating organizational ambidexterity theory and shedding light on the intricately complex nature of innovation ambidexterity.