Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This paper identified that strategic autonomy can lead to several governance traps that can impact the efficiencies within a business. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Integrating AI in seed science: toward an intelligent design paradigm.

The emergence of personalized medicine represents a significant change in medicine and offers more accurate and personal approaches to treatment. Neurodegenerative diseases, based on progressive deterioration of the neurons, pose a considerable challenge because of their multifactorial etiological and heterogeneous clinical phenotypes. The present paper dwells on one of the prevalent neurodegenerative diseases: Parkinson's Disease. Parkinson's Disease is linked to motor symptoms, which include bradykinesia, tremor, rigidity, and posture instability. Parkinson's, as a significant movement disorder, reflects the urgency of the new treatment methods. The existing interventions, like Levodopa, Catechol-O-Methyltransferase inhibitors, and surgical procedures like Deep Brain Stimulation, are used as the current interventions. Nonetheless, these therapeutics cannot work in all patients with great success, and the response of the patients to them differs greatly. This contradiction especially highlights the gap in the contemporary paradigms of treatment and the need to transition into more individualized approaches. The use of personalized medicine with Parkinson's Disease marks a shift in the historically used one-size-fits-all approach, instead shifting to a more personalized approach. Through genetic, biomarker, and phenotypic information, personalized medicine will enhance the accuracy of diagnosis, disease progression forecasting, and treatment regimes. This literature review provides an explanation of the need for personalized medicine in Parkinson's, discusses the latest developments, techniques, limitations, and analyzes the innovative technologies and strategies. By identifying key developments and ongoing challenges, the paper aims to provide a comprehensive understanding of how personalized medicine could transform the future of Parkinson's disease management.

Gravitational fingering often occurs for water flow in the vadose zone and accurate modeling of this important flow process remains a significant scientific challenge. This paper presents the latest theoretical developments of the optimality-based active region model (ARM), a macroscopic framework developed for describing gravitational fingering flow in the vadose zone. ARM divides the soil into active (fingering) and inactive regions, introducing a relationship between water flux and hydraulic gradient derived from the principle of optimality that the system self-organizes to maximize water flow conductivity. Unlike traditional models, ARM’s hydraulic conductivity depends on both capillary pressure or water saturation and water flux, reflecting the unstable nature of fingering flow. The paper provides an updated mathematical derivation of ARM relationships using calculus of variations and extends ARM to account for small water flux in the non-fingering zone, resulting in a dual-flow field model. These new developments should make ARM more rigorous and realistic for field-scale applications.

Metal-organic frameworks (MOFs) possess ordered pore structure, high surface area, tunable composition and tailorable functionality, and thus present promising prospect in many applications. Among them, titanium-based MOFs (Ti-MOFs) composed of organic ligands and titanium-oxygen clusters exhibit great potential in photocatalysis, owing to their diverse topological configurations, outstanding photocatalytic activity, low toxicity, and easy production. The latest developments in Ti-MOFs, including the synthetic strategies, structural features, methods for enhancing catalytic performance, and typical applications, were reviewed in this paper. The application in CO2 reduction, hydrogen evolution, organic pollutant removal, and photocatalytic sensing were emphasized. Moreover, we present a distinctive perspective on the relationship between the structure and their applications of Ti-MOFs, and provide new information in the design and construction of advanced Ti-MOFs for high-efficiency photocatalytic conversion.

Urinary tumor DNA (utDNA) has emerged as a promising noninvasive biomarker that may complement or reduce the need for cystoscopies in the diagnosis, surveillance, and treatment monitoring of urothelial carcinoma. Unlike plasma circulating tumor DNA (ctDNA), which is heavily diluted by hematopoietic cell-derived DNA, utDNA originates directly from tumor cell shedding into urine and often appears at higher concentrations, improving molecular detection. While there is an increasing number of publications using utDNA with promising results, most of these studies were developed from a laboratory perspective, making it difficult to find a direct clinical application. This review aims to apply a clinical perspective for potential daily practice use of utDNA testing. This review summarizes the most recent literature on the potential clinical use of utDNA for diagnosis, follow-up, and response to treatment in nonmuscle-invasive bladder cancer, muscle-invasive bladder cancer, and upper tract urothelial carcinoma. There is accumulating evidence on the potential use of utDNA for the diagnosis of urothelial carcinoma in the bladder as well as in the upper tract, while preliminary studies show promising results with sensitivities around 80-90% and specificities 90-100%, further research is needed.

Smart polymer-based drug and gene delivery systems are revolutionizing contemporary therapeutics with their increased specificity, efficacy, and safety. Compared to traditional carriers, smart polymers exhibit stimuli-responsive behavior, enabling controlled and site-specific drug release in response to physiological cues, such as pH, temperature, or enzyme activity. Such dynamic materials allow accurate drug delivery and minimize systemic toxicity, along with providing improved bioavailability. This review delves into some of the latest developments in stimuliresponsive polymers, nanoplatforms with multiple functions, and hybrid polymer systems, highlighting their potential in controlled drug delivery and theragnostics. Challenges, including biocompatibility, stability, and overcoming biological barriers, such as the blood-brain barrier, are also covered. By combining smart polymers with nanotechnology and targeted personalized medicine strategies, the discipline is set to redefine targeted therapy and maximize therapeutic outcomes.

The rapid progress in information technologies has driven a strong demand for memory devices that combine large storage capacity, high-speed operation, and reduced energy consumption. Magnetic tunnel junctions (MTJs) possessing significant tunnel magnetoresistance effects have considerable applications in magnetic random-access memory (MRAM), read heads, and magnetic sensors. In current MTJ technologies, data writing is predominantly achieved via electric currents, a method that consumes substantial energy. Replacing it with electric-field-driven switching could greatly improve energy efficiency. Considerable attention has been directed toward integrating ferroelectric materials into the MTJ barriers and utilizing voltage-controlled magnetic anisotropy. However, these approaches often face challenges such as low operating temperatures, assistance of external magnetic fields, or volatile control of resistance states. Recent advancements in strain-mediated manipulation of magnetism via electric field in ferroelectric/ferromagnetic multiferroic heterostructures provide practical strategies for implementing manipulation of MTJs via electric field. In this perspective, we present a concise summary of the latest developments concerning the modulation of MTJ resistance states via electric fields composed of multiferroic heterostructures and ferroelectric Pb(Mg1/3Nb2/3)0.7Ti0.3O3. Progress on both in-plane and perpendicular magnetic anisotropic MTJs is summarized, and the discussion concludes with an outlook on potential developments. Furthermore, this work concludes by outlining prospective research avenues for the manipulation of MTJs in multiferroic heterostructures via electric field based on strain-mediated magnetoelectric coupling, a mechanism that is expected to remain pivotal for advancing fundamental understanding and realizing next-generation MRAM technologies.

The evolutionary scale modeling (ESM) series is promising to revolutionize protein science and engineering through large language models (LLMs), providing a robust framework for understanding the relationships among sequences, structures, and functions of proteins. Trained on a large number of unlabeled protein sequences, ESM models are able to capture intricate patterns of mutation and conservation, yielding insights into the structural and functional properties of proteins. Despite a growing body of literature surrounding ESM, existing surveys often fail to comprehensively describe its advancements or applications in a focused manner. This survey covers the latest developments of ESM, categorizing them into techniques of using ESM and downstream applications. Approximately 100 papers are selected and analyzed, highlighting recognized and innovative studies that exemplify the impact of ESM. Furthermore, we critically discuss the strengths and limitations of ESM to envision future applications. This review provides a valuable resource for researchers seeking to explore the power of ESM models and the emerging applications of LLMs in biology and medicine.

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This paper explored how anti-money laundering systems can be improved to provide better results. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy to digest format.

The rapid increase in plastic production and use has caused a large buildup of microplastics (MPs) in land, freshwater, and ocean environments. This situation poses serious risks to ecosystems, biodiversity, and human health. Addressing this complex pollution problem requires accurate detection methods and sustainable strategies. This review provides a detailed look at the latest developments in techniques to identify and characterize microplastics. It covers traditional methods like microscopy, Fourier transform infrared (FTIR) spectroscopy, and Raman spectroscopy along with new methods such as hyperspectral imaging, atomic force microscopy, nuclear magnetic resonance (NMR), mass spectrometry-based techniques, and electrochemical biosensors. The review assesses microbial degradation of plastics. It highlights important bacterial, fungal, and algal groups involved in degrading common plastics like polyethylene (PE), polyethylene terephthalate (PET), polypropylene (PP), and polystyrene (PS). It also discusses genes, enzymatic processes and metabolic pathways involved in degradation process. By combining advancements in detection methods with findings from microbial and genomic studies, this review points out current challenges, new opportunities, and future directions for creating standardized, scalable, and effective strategies to tackle microplastic pollution.

Abstract Cybercriminals continually advance their tactics, exploit novel attack vectors, and target emerging technologies. To mitigate these risks, cyber insurance policies must remain abreast of the latest technological developments. Staying technologically updated enables an Insurance Company (IC) to assess risks more precisely, tailor policies to a potential potential Policyholder (PH), and accurately calculate fair premiums. By incorporating innovative risk assessment methodologies, robust Know-Your-Customer protocols, and automated claims-handling processes, ICs can offer tailored and cost-effective solutions to their PHs. Embracing technological advancements enables the field of cyber insurance to adapt to the ever-changing landscape of cyber threats, providing comprehensive protection to organizations. This article introduces , an innovative privacy-preserving framework designed to deliver robust security and privacy assurances to PHs against honest but inquisitive entities within the cyber insurance ecosystem. also equips ICs with automated processes for claims management. At the core of lies Hyperledger Aries, leveraging verifiable credentials to empower PHs with identity ownership and data control. Our framework is complemented by Hyperledger Fabric, which imbues with intelligent functionalities enabling PHs and ICs to autonomously execute actions related to cyber insurance and gather historical cybersecurity data. In this direction, we have successfully implemented the key components of and conducted a quantitative performance assessment. We also substantiate its security and privacy attributes, confirming that effectively achieves its objectives. In summary, represents a forward-thinking solution poised to enhance cyber insurance in an era of ever-evolving cyber threats, offering a promising avenue for safeguarding organizations and policyholders in the digital landscape.

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This paper identified that digital literacy does have an impact on how generative artificial intelligence can support sustainable development outcomes. Research limitations/implications The paper identified the different contextual factors that can be necessary when considering the use of artificial intelligence within sustainability realms. Practical implications The paper offered practical solutions that can assist in the achievement of sustainability goals. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Telecom Rapid expansion of video conferencing, is a critical communication media, collaboration and Training to most of the verticals, especially after the outbreak is over. In this paper, the summary of the recent studies on the concepts of Evolution of video, ease of use and future direction in conference system is provided. There are early theories (Technology Acceptance Model (TAM) and Media Simultaneity Theory (MST) which explain adoption habits and user-involvement. User satisfaction fatigue Digital conferencing and QoE research has given latency and interface design and cognitive aspects as roles in User satisfaction. The latest developments introduce artificial intelligence, Real-time streaming (WebRTC), and 3D/volumetric streaming telepresence to offer a better degree of immersion and social presence, users with vision and hearing impairments do not enjoy the same degree of accessibility, scaling fatigue remain issues to allow a seamless experience. Some of the new trends that are increasingly being adopted are mixed reality, augmented reality based on communication and gesture support, and artificial intelligence. Debriefs will become the virtual world of interactivity and inclusivity that will transform the world, and they are justified. The information presented in this article gives a glimpse of the theoretical knowledge and Empirical information to comprehend the development of video conferencing by two domains: Immersive, intelligent, Human Centric communication ecosystems.

This perspective piece illustrates the synergy between digital twins and extended reality (XR) technologies and calls for their integration in future research. Through a brief example of the latest developments around Pokémon Go, this piece argues that digital twins and XR technologies share fundamental properties and a connected future trajectory. In turn, both stand to benefit from a mutual integration into one another’s conceptual repertoire, particularly at a time when digital twins are rapidly expanding, albeit with socio-cultural blind spots, and XR technologies have often not lived up to their corporate hype, leaving the field in search of new, meaningful directions. Furthermore, as this article is part of a special issue that focuses on ‘meaningful XR’ (interpreted as moving XR research beyond games and gaming), it also reflects briefly upon the very notion of what makes XR ‘meaningful’, as well as how the synergy between digital twins and XR complicates this concept.

The chronic evolving neurodegenerative disorder Alzheimer's Disease (AD) presents with memory deficits, cognitive impairment, and loss of abilities. AD prevalence is increasing as the world ages, necessitating more precise and easily obtainable diagnostic and treatment approaches. Artificial Intelligence (AI) technologies, and more specifically, machine learning and deep learning, have become game-changers in Alzheimer's disease patient care, including optimizing care, enabling early diagnosis, supporting differential diagnosis, and predicting disease progression over the last few years. To detect amyloid plaques and hippocampal atrophy, this study investigates how AI-driven imaging analysis, specifically convolutional neural networks applied to MRI (Magnetic Resonance Imaging) and PET (Positron Emission Tomography) scans, provides higher sensitivity and specificity. Artificial intelligence models are also being used to analyze clinical and genomic data to identify biomarkers and support risk stratification. AI-assisted cognitive tests provide scalable, non-invasive, and real-time screening. Telemedicine platforms and AI-based Clinical Decision Support Systems (CDSS) are also improving patient management, particularly in remote or underserved areas. Heterogeneity of data, model explainability, ethics, and regulatory guideline requirements remain issues, despite these latest developments. Beyond recent developments such as federated learning and digital twins, the study comprehensively reviews AI's contributions to AD diagnosis and therapy. It also establishes a guide for future research directions for the ethical and equitable integration of AI in clinical practice.

Diabetes mellitus is a leading global health problem, with type 2 diabetes being the main type and already very inefficient treatments posing a challenge. Plant-based compounds, especially those that are naturally occurring have become very popular lately and are regarded as major sources of new antidiabetic drugs owing to the diversity of their structures and the fact that they act on multiple targets at the same time. One of these groups of compounds is coumarins, which have proved to be an important class of bioactive substances with considerable antidiabetic properties. The review that we are presenting gives an inclusive report on the occurrence of natural coumarins and their derivatives with antidiabetic activity being reported, along with the discussion of their mechanisms of action that include among others the inhibition of the enzymes that digest carbohydrates, increase of the insulin sensitivity, regulation of the glucose uptake, protection of the pancreatic β-cells and regulation of oxidative stress and inflammation. Also, the structure-activity relationships of coumarin derivatives are discussed to bring out the important functional features that are responsible for the biological activity. Moreover, the latest developments in drug design, molecular docking studies and the therapeutic prospects of coumarin-based antidiabetic agents have been reviewed. Overall, this review has pointed out the plant-based coumarins as being very versatile scaffolds in the development of antidiabetic therapeutics that are both safe and effective with fewer side effects.

ABSTRACT This paper quantifies the net contribution of information and communication technologies (ICTs) to sustainable development using the latest World Development Indicators (WDI) in a country–year panel (2000 to each country's most recent year). We combine panel econometrics with a data‐driven fuzzy inference system to model ICTs' enabling effects (efficiency, inclusion, dematerialization) alongside their footprints (energy use, materials, e‐waste), with attention to rebound dynamics. In a MENA‐wide sample, we construct an interpretable, policy‐oriented Fuzzy Net‐Sustainability Gain (FNSG) index from WDI‐only inputs and estimate heterogeneous associations moderated by electricity mix and access conditions. Results indicate that ICTs' net sustainability effect is conditional rather than uniform: cleaner power and broad, reliable access are associated with more favorable outcomes, whereas carbon‐intensive grids or exclusion constraints mute gains. A Tunisia case study applies the same measurement and fuzzy logic to current levels, trajectories, and counterfactuals; joint scenarios that deepen fixed broadband while increasing the renewable share yield the largest net gains. Findings are robust to quasi‐balanced windows, alternative standard errors, and membership shapes, and they translate into concrete levers for “greening the digital stack” while amplifying enablement.

Considering the increasing demand for environmentally friendly and economically viable transportation options, this in-depth analysis of fault-tolerant control (FTC) in the context of electric vehicles (EVs) covers all the latest developments and applications in the field. Maintaining vehicle stability and handling component failures with minimal or acceptable loss of performance are the primary goals of FTC systems in EVs. Thus, the FTC's crucial role in improving EV dependability is examined in this study. An explanation of the control strategies employed in EVs is followed by a description of the several types of FTC, including active, passive, and hybrid systems. The study aims to objectively evaluate advancements in tracking accuracy and robust performance by thoroughly reviewing FTC systems for modern EVs. This discusses various strategies as well as the challenges of integrating them into EV subsystems. Real-time deployment, validation against coupled failures, and the incorporation of learning-based FTC into safety-critical EV systems are some suggestions for future research. This study will help identify research gaps and topics that require additional investigation in order to advance the discipline.

Food waste is one of the most important world-wide challenges whose environmental, economic and social impacts have far-reaching effects that include contributing to greenhouse gas emissions, resources depletion as well as the rising levels of food insecurity. These problems are further intensified in Asia due to high rate of urbanization, population growth, changing dietary habits, and lack of waste management facilities. These conditions complicate the fact that countries are increasingly struggling to achieve the United Nations Sustainable Development Goal (SDG) 12.3, which is to ensure that by 2030, half of the world has dropped per-capita food waste, and food losses at the entire supply chain spectrum are cut by half. This review discusses the latest food waste management activities, challenges, and developments in Asian nations based on the evidence found in 170 academic articles published between 2015 and 2025 and chosen according to PRISMA guidelines. This research paper assesses food waste sources different region, treatment, and policy responses, but with special attention to the realm of sustainability and a circular economy. The results indicate that East Asian nations have developed policy-making and waste-to-energy technologies. South Asian countries, on the contrary, remain plagued by structural issues, such as poor waste separation, lack of experience, low awareness of the population, and poor infrastructure. Such cross-cutting concerns as land shortages, financial constraints, and ineffective policy enforcement also make it less likely to achieve SDG 12.3. In general, the review determines some important gaps, regional differences and potential areas of improvement of food waste management systems in Asia. Therefore, this review shows the necessity of consistent strategies, more coordination, and better interaction with the population to contribute to sustainable and effective food waste reduction solutions throughout the region.