Variation in ecological scorecards and their potential for wider use.

Ecological monitoring is a vital tool to help us assess habitat condition and understand the mechanism(s) for habitat change. Yet many countries struggle to meet their monitoring requirements in part due to the high assessment workload. Rapid ecological assessment methods may have an important role to play in this regard. Following their success within several European habitats (e.g., semi-natural grasslands), they are now being developed for additional habitats such as heathlands, peatlands, and other agri-associated areas. Whilst some rapid assessments using ecological scorecards have been shown to be accurate compared to traditional ecological monitoring, less is known about the functionality of these scorecards in heterogenous landscapes. In this study, we selected four existing scorecards to test alongside a prototype. We assessed how these different scorecards measured habitat condition on the same heathland sites. We found that the choice of metrics, their score weighting, and the thresholds used for categorical scores cause scorecards to assess the same site with substantial variation (37%). Vegetation metrics were the primary cause of score variation, with vegetation structure and positive indicator species being the leading causes. Our study indicates that whilst current scorecards may be representative of project-specific goals, they may not be suitable for wider monitoring uses in their current form. Ecological scorecards have great potential to drastically increase the extent of monitoring, but caution is needed before adapting existing scorecards beyond the purposes from which they were designed.

Exploring the Linkages between farm efficiency, farm environmental performance, and agri-environmental scheme adoption: Lessons from France.

The agricultural detrimental effects on the environment are a source of concern. Public mea-sures, such as agri-environmental schemes (AES), have been designed to incentivize farmers to adopt more sound environmental practices on the farm. In this study, we examine the effects of past initial economic and environmental performances on AES adoption by focusing on crop farms. Using Firth's logistic regression to address small sample bias with French FADN data from 1997 to 2007, we mainly find that technical efficiency has heterogeneous effects on AES adoption, depending on environmental indexes. This result suggests the presence of windfall effects. We also show complex interactions (antagonism or synergy) between economic and environmental performances in adoption decisions, and heterogeneous effects depending on the type of farming. The agricultural detrimental effects on the environment are a source of concern. Public mea-sures, such as agri-environmental schemes (AES), have been designed to incentivize farmers to adopt more sound environmental practices on the farm. In this study, we examine the effects of past initial economic and environmental performances on AES adoption by focusing on crop farms. Using Firth's logistic regression to address small sample bias with French FADN data from 1997 to 2007, we mainly find that technical efficiency has heterogeneous effects on AES adoption, depending on environmental indexes. This result suggests the presence of windfall effects. We also show complex interactions (antagonism or synergy) between economic and environmental performances in adoption decisions, and heterogeneous effects depending on the type of farming.

Modelling enhancement of Ecosystem Services provision through integrated agri-environment and forestry measures.

Agri-environment and forest schemes can support landowners to conserve and enhance agricultural and forest ecosystems. The effectiveness of these schemes is often debated due to discrepancies that occur between the application of such measures and the delivery of Ecosystem Services (ES). We simulated the application of a suite of farmland and forest measures within a range of biophysical contexts in known High Nature Value landscapes across the Republic of Ireland. Three high resolution geospatial scenarios simulated the anticipated effects of the measures: i) a Baseline Scenario of current conditions, ii) an Enhanced Scenario simulated the application of measures, and iii) using the new 'Restoration Planner' freeware, an Enhanced + Connectivity Scenario simulated the application of additional targeted measures for ecosystem connectivity. Across all scenarios, we modelled and compared the responses of a range of ES including: habitat quality, carbon storage, production income and ecosystem connectivity. Multivariate analyses were used to ordinate and determine eight bundles of measures and their associated effect on ES and connectivity. These Bundles were subsequently contextualised by examining unique landscape characteristics in which they occurred. The results show that measures applied under the Enhanced Scenario resulted in weak gains to carbon storage (2 %), strong gains to habitat quality (28 %), and weak losses to production income (-7 %) and ecosystem connectivity (-2 %). Similarities were observed under the Enhanced + Connectivity Scenario, though with comparably stronger gains to ecosystem connectivity (15 %). This study is the first to demonstrate the potential synergies and trade-offs to ES that can result from the integrated and targeted application of both farmland and forest measures within a variety of landscape characteristics.

Understanding global perspectives for the acceptance of community sanitation welfare schemes through a localised qualitative survey in Kho Nagorian, Jaipur, India.

Community sanitation is a fundamental human right and need. Every year, as per the World Bank, total cost of providing sanitation services is estimated at around 114 billion USD per year. In India, Swachh Bharat Abhiyan (SBA), a public welfare scheme (PWS), is aimed at addressing community sanitation problems. Despite the successful implementation of SBA, local communities still practise open defaecation. To deduce the behavioural patterns governing communal toilet use, interviews were conducted with the local communities in the Kho Nagorian area of Jaipur, Rajasthan, India. This qualitative survey examined attitudes towards the construction of a toilet, awareness towards the SBA scheme, and the willingness to use excreta-based pit humus. The study then discusses the factors that increase the local community's willingness to use these toilets. Results show that open defaecation is still prevalent in society. One way to foster the adoption of toilets is that the construction materials should mainly consist of local materials. As a recourse, places of worship could be used to influence people's perception of hygiene. In addition, community toilets should be cleaned often as well. PWS should not be made accessible at no cost to prevent a sense of entitlement among the people. A small sum should be charged to increase social responsibility towards the PWS. Another way to curb open defaecation is to tap into the sense of entitlement by making effective use of social campaign programs. Further, cross-table analysis revealed that the locals were inclined to use a toilet if they have invested in it. Advertisements were found to be ineffective, and proposals were made to make them effective. These findings aid in understanding public perceptions and can guide the development of public policies. The findings also assist in making tax distribution decisions that reflect public concerns, attitudes, and values.

A low-activity cortical network selectively encodes syntax.

Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability.

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

Gradient-Robust Hybrid DG Discretizations for the Compressible Stokes Equations.

This paper studies two hybrid discontinuous Galerkin (HDG) discretizations for the velocity-density formulation of the compressible Stokes equations with respect to several desired structural properties, namely provable convergence, the preservation of non-negativity and mass constraints for the density, and gradient-robustness. The later property dramatically enhances the accuracy in well-balanced situations, such as the hydrostatic balance where the pressure gradient balances the gravity force. One of the studied schemes employs an H ( div ) -conforming velocity ansatz space which ensures all mentioned properties, while a fully discontinuous method is shown to satisfy all properties but the gradient-robustness. Also higher-order schemes for both variants are presented and compared in three numerical benchmark problems. The final example shows the importance also for non-hydrostatic well-balanced states for the compressible Navier-Stokes equations.

Ancestral reproductive bias in continuous-time branching trees under various sampling schemes.

Cheek and Johnston (JMB 86:70, 2023) consider a continuous-time Bienaymé-Galton-Watson tree conditioned on being alive at time T. They study the reproduction events along the ancestral lineage of an individual randomly sampled from all those alive at time T. We give a short proof of an extension of their main results (Cheek and Johnston in JMB 86:70, 2023, Theorems 2.3 and 2.4) to the more general case of Bellman-Harris processes. Our proof also sheds light onto the probabilistic structure of the rate of the reproduction events. A similar method will be applied to explain (i) the different ancestral reproduction bias appearing in work by Geiger (JAP 36:301-309, 1999) and (ii) the fact that the sampling rule considered by Chauvin et al. (SPA 39:117-130, 1991), (Theorem 1) leads to a time homogeneous process along the ancestral lineage.

An Arbitrarily High Order and Asymptotic Preserving Kinetic Scheme in Compressible Fluid Dynamic.

We present a class of arbitrarily high order fully explicit kinetic numerical methods in compressible fluid dynamics, both in time and space, which include the relaxation schemes by Jin and Xin. These methods can use the CFL number larger or equal to unity on regular Cartesian meshes for the multi-dimensional case. These kinetic models depend on a small parameter that can be seen as a "Knudsen" number. The method is asymptotic preserving in this Knudsen number. Also, the computational costs of the method are of the same order of a fully explicit scheme. This work is the extension of Abgrall et al. (2022) [3] to multi-dimensional systems. We have assessed our method on several problems for two-dimensional scalar problems and Euler equations and the scheme has proven to be robust and to achieve the theoretically predicted high order of accuracy on smooth solutions.

Study on Universal Health Coverage Scheme in India - The Stumper to Private Hospitals.

BACKGROUND: Many governments have introduced health insurance schemes for the poor sections of society to save them from catastrophic health expenditure. Private hospitals play a key role in India, as they are in significant number in secondary and tertiary care services. Private hospitals have to fund their infrastructure, staff salaries from the revenue of previous year. In this study, we compared money received by a private medical college hospital bed through government insurance scheme patient and private paying patient. METHODS: Observational study, comparing money reimbursed for top ten procedures treated in private medical college hospitals by Ayushman Bharat (AB) fund and the price offered by a paying patient in similar bed. RESULTS: On average 600 patients received medical care through the AB scheme per month at our tertiary care super-specialty hospital. Highest numbers were seen in specialties like cardiovascular, and cancer treatments and infectious diseases under general medicine specialty. The costs considered were surgeon's cost, medicines, devices, and hospitalization costs. The laparoscopic procedures were incurring a loss of 130%, knee replacements about 50%, coronary bypass grafting thankfully due to controlling of prices by central government is incurring a loss of 10%. The package amount offered accounts to 26-52% only of the costs incurred by the private hospitals. CONCLUSION: The private academic hospitals need 25% to 50% more than current prices offered, across various procedures.

Vulnerability Assessment and Protection Zone Delineation for Water Supply Schemes in the Upper Awash Subbasin, Ethiopia, Sub-Saharan Africa.

Water quality issues in Ethiopia necessitate the implementation of the Water Safety Plan (WSP) to safeguard drinking water. Despite its benefits, WSP implementation is underutilized, a situation exacerbated by urbanization, agriculture, pollution, and climate change. This study evaluated water supply system vulnerability and delineated protection zones in the Upper Awash River subbasin. By employing the DRASTIC model, the National WASH Inventory-2 (NWI-2), and qualitative methods, this research aims to integrate the NWI-2 with vulnerability assessments. The study revealed that, among 2864 schemes, only 14.4% had a water safety plan, while 20.7% practiced water safety, and 6% reported the occurrence of waterborne diseases. Over 39.23% of the schemes were in high vulnerability areas, 12.32% were in very high vulnerability areas, and only 8% were in low vulnerability areas. The validation revealed a 61.7% association between the vulnerability indices and nitrate concentration. The strengths of the strategy included coordination and guideline development, but challenges such as institutionalization, catchment protection, the legal framework, and climate information remain for the Water Safety Plan. To promote public health, these findings help to demonstrate and integrate the NWI-2 with vulnerability assessments to protect drinking water sources. The conclusion also calls for all concerned authorities to implement water source protection, emphasizing the use of GIS technology and the adoption of integrated watershed management practices, which encompass regulatory control and conservation strategies. Furthermore, more research on the pollutant time of travel, assimilation capacity, and land use priorities is needed to delineate specific protection zones.

Numerical study of diffusive fish farm system under time noise.

In the current study, the fish farm model perturbed with time white noise is numerically examined. This model contains fish and mussel populations with external food supplied. The main aim of this work is to develop time-efficient numerical schemes for such models that preserve the dynamical properties. The stochastic backward Euler (SBE) and stochastic Implicit finite difference (SIFD) schemes are designed for the computational results. In the mean square sense, both schemes are consistent with the underlying model and schemes are von Neumann stable. The underlying model has various equilibria points and all these points are successfully gained by the SIFD scheme. The SIFD scheme showed positive and convergent behavior for the given values of the parameter. As the underlying model is a population model and its solution can attain minimum value zero, so a solution that can attain value less than zero is not biologically possible. So, the numerical solution obtained by the stochastic backward Euler is negative and divergent solution and it is not a biological phenomenon that is useless in such dynamical systems. The graphical behaviors of the system show that external nutrient supply is the important factor that controls the dynamics of the given model. The three-dimensional results are drawn for the various choices of the parameters.

Utilizing genomic prediction to boost hybrid performance in a sweet corn breeding program.

Sweet corn breeding programs, like field corn, focus on the development of elite inbred lines to produce commercial hybrids. For this reason, genomic selection models can help the in silico prediction of hybrid crosses from the elite lines, which is hypothesized to improve the test cross scheme, leading to higher genetic gain in a breeding program. This study aimed to explore the potential of implementing genomic selection in a sweet corn breeding program through hybrid prediction in a within-site across-year and across-site framework. A total of 506 hybrids were evaluated in six environments (California, Florida, and Wisconsin, in the years 2020 and 2021). A total of 20 traits from three different groups were measured (plant-, ear-, and flavor-related traits) across the six environments. Eight statistical models were considered for prediction, as the combination of two genomic prediction models (GBLUP and RKHS) with two different kernels (additive and additive + dominance), and in a single- and multi-trait framework. Also, three different cross-validation schemes were tested (CV1, CV0, and CV00). The different models were then compared based on the correlation between the estimated breeding values/total genetic values and phenotypic measurements. Overall, heritabilities and correlations varied among the traits. The models implemented showed good accuracies for trait prediction. The GBLUP implementation outperformed RKHS in all cross-validation schemes and models. Models with additive plus dominance kernels presented a slight improvement over the models with only additive kernels for some of the models examined. In addition, models for within-site across-year and across-site performed better in the CV0 than the CV00 scheme, on average. Hence, GBLUP should be considered as a standard model for sweet corn hybrid prediction. In addition, we found that the implementation of genomic prediction in a sweet corn breeding program presented reliable results, which can improve the testcross stage by identifying the top candidates that will reach advanced field-testing stages.

Decentralized multi-agent reinforcement learning based on best-response policies.

Introduction: Multi-agent systems are an interdisciplinary research field that describes the concept of multiple decisive individuals interacting with a usually partially observable environment. Given the recent advances in single-agent reinforcement learning, multi-agent reinforcement learning (RL) has gained tremendous interest in recent years. Most research studies apply a fully centralized learning scheme to ease the transfer from the single-agent domain to multi-agent systems. Methods: In contrast, we claim that a decentralized learning scheme is preferable for applications in real-world scenarios as this allows deploying a learning algorithm on an individual robot rather than deploying the algorithm to a complete fleet of robots. Therefore, this article outlines a novel actor-critic (AC) approach tailored to cooperative MARL problems in sparsely rewarded domains. Our approach decouples the MARL problem into a set of distributed agents that model the other agents as responsive entities. In particular, we propose using two separate critics per agent to distinguish between the joint task reward and agent-based costs as commonly applied within multi-robot planning. On one hand, the agent-based critic intends to decrease agent-specific costs. On the other hand, each agent intends to optimize the joint team reward based on the joint task critic. As this critic still depends on the joint action of all agents, we outline two suitable behavior models based on Stackelberg games: a game against nature and a dyadic game against each agent. Following these behavior models, our algorithm allows fully decentralized execution and training. Results and Discussion: We evaluate our presented method using the proposed behavior models within a sparsely rewarded simulated multi-agent environment. Although our approach already outperforms the state-of-the-art learners, we conclude this article by outlining possible extensions of our algorithm that future research may build upon.

External quality assurance program for diagnostic complement laboratories: evaluation of the results of the past seven years.

Introduction: The complement external quality assurance (EQA) program was first organized in 2010 by a group of researchers working in diagnostic complement laboratories. Starting in 2016, INSTAND e.V., a German, non-profit interdisciplinary scientific medical society dedicated to providing expert EQA programs for medical laboratories, started organizing the EQAs for complement diagnostic laboratories together with the same group of experienced scientists and doctors who also work as EQA experts. The aim of the current work is to provide descriptive analysis of the past seven years' complement EQA results and evaluate timeline changes in proficiency testing. Methods: Each year, in March and October, blinded samples (normal, pathological) were sent to the participating diagnostic laboratories, where complement parameters were evaluated exactly as in daily routine samples. Since no reference method/target values exist for these parameters, and participants used different units for measurement, the reported results were compared to the stable mean (Algorithm A) of the participants using the same method/measurement units. A reported result was qualified as "passed" if it fell into the 30-50% evaluation/target range around the mean of reported results (depending on the given parameter). Results: While the number of participating laboratories has increased in the past years (from around 120 to 347), the number of complement laboratories providing multiple determinations remained mostly unchanged (around 30 worldwide). C3, C4, C1-inhibitor antigen and activity determinations provided the best proficiency results, with >90% passing quotas in the past years, independent of the applied method. Determination of the functional activity of the three activation pathways was good in general, but results showed large variance, especially with the pathological samples. Complement factor C1q and regulators FH and FI are determined by only a few laboratories, with variable outcomes (in general in the 85-90% pass range). Activation products sC5b-9 and Bb were determined in 30 and 10 laboratories, respectively, with typical passing quotas in the 70-90% range, without a clear tendency over the past years. Conclusion: With these accumulated data from the past seven years, it is now possible to assess sample-, method-, and evaluation related aspects to further improve proficiency testing and protocolize diagnostic complement determinations.

Clustering user preferences for personalized teleoperation control schemes via trajectory similarity analysis.

Successful operation of a teleoperated robot depends on a well-designed control scheme to translate human motion into robot motion; however, a single control scheme may not be suitable for all users. On the other hand, individual personalization of control schemes may be infeasible for designers to produce. In this paper, we present a method by which users may be classified into groups with mutually compatible control scheme preferences. Users are asked to demonstrate freehand motions to control a simulated robot in a virtual reality environment. Hand pose data is captured and compared with other users using SLAM trajectory similarity analysis techniques. The resulting pairwise trajectory error metrics are used to cluster participants based on their control motions, without foreknowledge of the number or types of control scheme preferences that may exist. The clusters identified for two different robots shows that a small number of clusters form stably for each case, each with its own control scheme paradigm. Survey data from participants validates that the clusters identified through this method correspond to the participants' control scheme rationales, and also identify nuances in participant control scheme descriptions that may not be obvious to designers relying only on participant explanations of their preferences.

A review of functional neuromodulation in humans using low-intensity transcranial focused ultrasound.

Transcranial ultrasonic neuromodulation is a rapidly burgeoning field where low-intensity transcranial focused ultrasound (tFUS), with exquisite spatial resolution and deep tissue penetration, is used to non-invasively activate or suppress neural activity in specific brain regions. Over the past decade, there has been a rapid increase of tFUS neuromodulation studies in healthy humans and subjects with central nervous system (CNS) disease conditions, including a recent surge of clinical investigations in patients. This narrative review summarized the findings of human neuromodulation studies using either tFUS or unfocused transcranial ultrasound (TUS) reported from 2013 to 2023. The studies were categorized into two separate sections: healthy human research and clinical studies. A total of 42 healthy human investigations were reviewed as grouped by targeted brain regions, including various cortical, subcortical, and deep brain areas including the thalamus. For clinical research, a total of 22 articles were reviewed for each studied CNS disease condition, including chronic pain, disorder of consciousness, Alzheimer's disease, Parkinson's disease, depression, schizophrenia, anxiety disorders, substance use disorder, drug-resistant epilepsy, and stroke. Detailed information on subjects/cohorts, target brain regions, sonication parameters, outcome readouts, and stimulatory efficacies were tabulated for each study. In later sections, considerations for planning tFUS neuromodulation in humans were also concisely discussed. With an excellent safety profile to date, the rapid growth of human tFUS research underscores the increasing interest and recognition of its significant potential in the field of non-invasive brain stimulation (NIBS), offering theranostic potential for neurological and psychiatric disease conditions and neuroscientific tools for functional brain mapping.

Between nature and culture - Interpreting students' sexuality in physical education.

Introduction: As sexuality in physical education (PE) is often treated as a taboo subject, social media platforms, online chats, and internet forums are emerging as spaces where it is negotiated more openly and broadly by current and former actors of the field. This paper contributes to a better understanding of the discursive construction of sexuality in PE in such online communication. Methods: In line with The Sociology of Knowledge Approach to Discourse (SKAD) we investigate basic schemes of interpretation of sexuality with a heterogeneous sample of threads (17 threads from seven different online forums) on different PE situations in Germany. The threads are analyzed using grounded theory coding procedures. Results: Our discourse analysis reveals that the multifaceted and often controversial online discussions are structured by two dominant schemes of interpreting students' sexuality in PE, both of which are differentiated in complex ways: The online communication draws on - and by that reproduces - a nature and a culture perspective on constellations of body, sex, gender, and sexuality. We detail how from each perspective, different knowledge about these constellations, different everyday phenomena and problems in PE, and different norms for dealing with these phenomena and problems become important. Discussion: Discussing these results in the context of previous literature, we argue that it is important to address sexuality in a subject-specific approach and take the discursive knowledge and fundamental schemes of interpretation into account that shape the (im-)possibilities of addressing sexuality in PE.

Quality assessment of glucose measurement with regard to epidemiology and clinical management of diabetes mellitus in Germany.

Background: During the last decade, Germany has seen an increased prevalence and a redistribution from undetected to diagnosed diabetes mellitus. Due to this substantial epidemiological development, the number of people with documented type 2 diabetes was 8.7 million in 2022. An estimated two million undiagnosed subjects are to be added. Beyond that, the life expectancy of diabetic subjects is increasing due to more responsive health systems in terms of care. Possible reasons include improved screening of at-risk individuals, the introduction of HbA1c for diagnosis in 2010, and the higher use of risk scores. Additionally, quality aspects of the laboratory methodology should be taken into consideration. Methods: Epidemiology and clinical management of diabetes in Germany are presented in the light of publications retrieved by a selective search of the PubMed database. Additionally, the data from German external quality assessment (EQA) surveys for the measurands glucose in plasma and HbA1c in whole blood, reviewed from 2010 until 2022, were evaluated. Above this, data concerning the analytical performance of near-patient glucometer devices, according to the ISO norm 15197:2013, were analyzed. Results: Two laboratory aspects are in good accordance with the observation of an increase in the diabetes mellitus prevalence when retrospectively reviewing the period 2010 to 2022: First, the analytical performance according to the ISO norm 15197:2013 of the glucometer devices widely used by patients with diabetes for the glucose self-testing, has improved during this period. Secondly, concerning the EQA program of INSTAND, the number of participating laboratories raised significantly in Germany. The spreads of variations of the specified results for plasma glucose remained unchanged between 2010 and 2022, whereas for HbA1c a significant decrease of the result scattering could be observed. Conclusion: These retrospectively established findings testify to an excellent analytical quality of laboratory diagnostics for glucose and HbA1c throughout Germany which may be involved in a better diagnosis and therapy of previously undetected diabetes mellitus.

Synthetic Strategies of Thiazolidine-2,4-dione Derivatives for the Development of New Anti-diabetic Agents: Compressive Review.

BACKGROUND: Thiazolidine-2,4-dione (2,4-TZD) is a flexible pharmacophore and a privileged platform and contains a five-membered ring with a 2-oxygen atom with double bond 2,4- position and one nitrogen atom as well as sulphur containing in the heterocyclic compound. A famous electron-rich nitrogen transporter combines invigorating electronic properties with the prospective for elemental applications. Thiazolidine-2,4-dione analogues have been synthesized using a variety of methods, all of which have shown to have a strong biological effect. OBJECTIVES: The study of the biological activity of Thiazolidine-2,4-dione derivatives has been a fascinating field of pharmaceutical chemistry and has many purposes. This derivative described in the literature between 1995 to 2023 was the focus of this study. Thiazolidine-2,4-diones have been discussed in terms of their introduction, general method, synthetic scheme and antidiabetic significance in the current review. CONCLUSION: Thiazolidine-2,4-diones are well-known heterocyclic compounds. The synthesis of Thiazolidine-2,4-diones has been described using a variety of methods. Antidiabetic activity has been discovered in several Thiazolidine-2,4-dione derivatives, which enhance further research. The use of Thiazolidine-2,4-diones to treat antidiabetics has piqued researchers' interest in learning more about thiazolidine-2,4-diones.