α-Hydroxyphosphonates are a critically important class of organophosphorus compounds with broad applications across diverse fields. This review paper surveys recent advancements from 2010 to 2025, focusing on their synthesis, reactivity, and biological activities. Key studies published prior to 2010 are also cited to provide essential background and to acknowledge foundational contributions to the field. Emphasis is placed on key synthetic methodologies such as the Pudovik and Abramov reactions, developments in asymmetric synthesis using chiral catalysts, and the utility of the α-hydroxyl group as a reactive functional handle. Special attention is given to environmentally friendly strategies including catalytic processes, ultrasonication and microwave-assisted synthesis. Several examples of the diverse biological properties of α-hydroxyphosphonates are also discussed. In addition, theoretical studies using DFT and molecular modeling are highlighted for their role in elucidating structure-activity relationships and supporting drug discovery. This review aims to be a valuable reference for researchers working in the field of organophosphorus chemistry.

This review paper explores how digital twin technology has evolved and its increasing applications while focusing on turbomachinery, including pumps, gas turbines, steam turbines, and wind turbines. The paper highlights the impact of digital twins on performance optimization, reducing downtime, and fault detection. Digital twins are virtual prototypes of physical systems that can simulate real-time operation, monitoring, and predictive maintenance to achieve high-value operational improvements. Advanced methodologies, like hybrid modeling, data-driven approaches, and machine learning techniques such as CNN, RNN, and LSTM models, are underlined in this paper, which ensures better performance in fault detection, performance prediction, and process optimization. Such approaches have been used to provide an accurate prognosis for gas turbines, renewable energy forecasting, and the real-time estimation of unsteady flow states in pumping stations. Most importantly, the integration of ML algorithms into digital twin frameworks gives much promise for improving turbomachinery operation in various directions: efficiency, reliability, and cost-effectiveness. Because of that, digital twin technology will be very promising toward the changing of present industrial strategies of maintenance to proactive, data-driven management of equipment in advanced engineering practices.

Agriculture remains the backbone of many developing economies, particularly in countries like India, where a large proportion of farmers are small and marginal landholders. Despite advancements in agricultural machinery and mechanization, ownership of modern farm equipment remains economically unfeasible for many farmers due to high capital investment, maintenance costs, and seasonal usage. The Agriculture Equipment Rental System (AERS) has emerged as an effective solution to bridge this gap by enabling farmers to access modern machinery on a pay- per-use basis. This review paper examines the concept, evolution,technological frameworks, benefits, challenges, and future prospects of agriculture equipment rental systems. Various traditional and digital-based rental models, including government supported custom hiring centers and mobile/web-based platforms, are analyzed. The study highlights how AERS contributes to increased productivity, reduced operational costs, timely farm operations, and sustainable agricultural development. Challenges such as awareness, logistics, digital literacy, and policy limitations are also discussed. The paper concludes that agriculture equipment rental systems are a vital component of modern agrarian economies and hold significant potential for transforming smallholder farming when supported by robust technology and policy frameworks..

Borderline personality disorder (BPD) is often manifested during adolescence and is associated with substantial morbidity and mortality. Early disorder-specific treatment is considered state of the art but is hampered by discontinuities at the transition to adult services and limited resources. Digital technologies play an increasing key role in adolescents' daily lives. Presentation of key characteristics of adolescent BPD and psychiatric transition-focused care concepts, an overview of digital applications in BPD treatment and the possibilities and challenges in the clinical practice. Narrative review article based on selected literature on the prevalence, treatment and digital interventions in adolescent BPD, complemented by two clinical examples: asecure emergency chat for suicidal youths in Bern and digital routine outcome monitoring (ROM) in the Adolescent Center for Emotion Regulation in Mannheim. Meta-analyses show heterogeneous, predominantly small effects of digital interventions on mental health outcomes in children and adolescents; health economic data are limited. For BPD the findings suggest effectiveness for specific symptoms (e.g., suicidal ideation, paranoia) and high acceptance although adherence is variable. Telemedicine and ROM can improve the continuity of care and crisis management when embedded in structured services. Digital applications are promising components of blended care and transition-focused programs. They should complement face-to-face therapy and require careful attention to data protection, financing and technical reliability. Stepped-care approaches tailoring digital and personal contact to individual needs appear useful.

Agronomic biofortification of staple food crops with external supply of micronutrients offers a viable solution to alleviate the plant diet-based micronutrient deficiency, without any yield trade-off. Zinc (Zn) has been one of the key targeted micronutrients in the biofortification program of Sub-Saharan Africa, Middle East and South-East Asia. Agronomic Zn biofortification, while promising for addressing Zn deficiencies in humans, raises valid concerns regarding its potential impact on grain iron (Fe) content. This is because Zn and Fe can interact at multiple levels, within soil, plant root, shoot, leaves and grains during transport and translocation. Emerging evidences suggest that biofortifying crops with Zn may trigger systemic responses that alter Fe homeostasis, potentially lowering Fe accumulation (antagonistic) in edible tissues of staples. Nevertheless, there is a lack of clarity in the field studies on the effects of Zn biofortification on Fe levels. This review article aims to synthesize a robust narrative on Zn-Fe interactions in biofortified crops and possible causes of negative interaction within plant body. Though, the additive or synergistic interaction between these two essential micronutrients is advantageous in a Zn biofortification program; but such interaction may be highly local stress specific. On the contrary, any loss of Fe during the process is undesirable, as the nutritional significance of Fe is comparable to that of Zn in human health. Yet, unlike other nutrient interactions (e.g., phosphorus (P) × Zn, nitrogen (N) × Zn), their interaction (Zn-Fe) is much less examined. But now, amid reports on unwitting depleting trend in grain micronutrients content in cereals, observed across the globe over the past 70 years, Zn - Fe interaction should apparently be given importance. In this review, we also highlighted on some possible interventions, agronomic or genetic or integrated approaches, to discard such negative interactions between Zn and Fe for future biofortification program. Addressing this trade-off (Zn-Fe interactions in crops) is the key to ensure that biofortification strategies do not inadvertently raise other micronutrient deficiencies. A focus on feasible management practices to curb such negative interaction between Zn and Fe will determine the success of agronomic Zn biofortification.

Type 2 diabetes (T2DM) is a complex chronic condition that is highly prevalent in the United States (U.S.). Self-management practices are a critical component in diabetes care. A patient's engagement with medication, glucose monitoring, intake of nutrient-dense foods, and participation in physical activity (PA) is influenced by the social determinants of health (SDOH). In this scoping review article, we assessed the use of structural interventions that targeted SDOH to impact two self-management strategies, healthy food consumption and PA uptake, and subsequent diabetes-related health outcomes. Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Google Scholar, PubMed, and Web of Science databases were utilised to identify relevant articles using MeSH terms, keywords and Boolean logic searching. We included articles with a focus on structural interventions to increase intake of nutrient-dense foods or PA for the management of T2DM. We reviewed four articles-two focused on improving access to healthy foods, while two focused on multi-component, multi-domain, and multi-level interventions; we did not find structural PA interventions. We found varying evidence for best practices regarding supportive elements embedded in interventions, but found there may be value in multi-component, multi-domain, and multi-level interventions to support T2DM self-management. Further research is needed to confirm value of multi-component, multi-domain, and multi-level interventions, particularly for underserved populations. In conclusion, there is not a one-size-fits-all approach to addressing determinants to healthy eating and PA, but interventions and outcomes may benefit when contributory factors beyond the individual level are addressed and communities affected are centred.

Abstract The solid–liquid suspension, which is a complex two‐phase flow, usually conducts in the stirred reactor. It is one of the typical unit operations in chemical engineering, food, biology, pharmaceutical, new energy industries, and so on. The research methods for solid–liquid suspension can be divided into two categories: experimental measurement and numerical simulation. In this paper, the experimental and numerical investigations on this topic since the beginning of the 21st century are comprehensively reviewed. The commonly used experimental measurement methods for the solid phase concentration distribution, flow field, just‐suspension speed, and mixing time are presented in detail, highlighting their advantages and limitations. Numerical simulations, employing various multi‐phase flow models, the Lattice‐Boltzmann method (LBM), the smoothed particle hydrodynamics (SPH) method, as well as the turbulence models and inter‐phase force models, are also reviewed. Their accuracy and applicability in predicting the complex solid–liquid suspension behaviour are discussed. Finally, an outlook for the future study on solid–liquid suspensions in stirred reactors is made. This review paper aims to enhance the understanding of solid–liquid flow dynamics and offers some insights for industrial applications.

The Circular economy (CE) is an economic model and a way to resource management that targets for the maximum use of resources and minimizing the production of wastes and environmental degradation. On contrary to the traditional linear economy which follows a ‘’take-make-dispose’’ pattern, where resources are mined are used to manufacture different commodities and then finally disposed off as wastes. The main objective of the circular economy is to revive and renew the materials, while maintaining the quality of the commodities at every stage of the product’s life. This approach attempts to reduce the production of wastes and ultimately close the loop by enabling high value recycling processes. The incorporation of circular economy principles into wastes management signifies a crucial shift towards sustainable development, addressing the widespread challenges of increasing wastes generation and environmental destruction. The aim of this review paper is to explore the potential and limitations of the circular economy and is based on broad literature review. The concept of the circular economy should be viewed through the framework of Sustainable Development, recognizing the synergy between economic practices, social well-being and environmental conservation.

Corporate finance functions are moving through a new digital inflection point. Earlier waves of automation in finance centered on robotic process automation, rules engines, workflow tools, and predictive analytics that standardized high-volume transactions and reduced cycle times. The current wave is different because large language models, generative AI, and agentic systems can interpret unstructured data, coordinate across tools, and recommend or execute multi-step decisions. Yet the finance function cannot adopt autonomy in the same way as less regulated business areas. Financial reporting, planning, controllership, treasury, tax, internal audit, and investor-facing processes are constrained by internal controls, segregation of duties, auditability, data lineage, policy compliance, and accountability to boards, regulators, and external assurance providers. This review paper examines how the literature from 2020 to 2026 explains the shift from automation to augmentation and develops a constraint-aware framework for adopting agentic AI in corporate finance. Following a structured review and content analysis of recent academic studies, standards, and practitioner reports, the paper synthesizes four themes: the evolution of AI use cases in finance and accounting; the distinction between automation, augmentation, and bounded autonomy; the organizational and technical constraints that shape deployment; and the governance mechanisms needed for reliable value capture. The review argues that the most realistic pathway for finance is not unrestricted autonomy but graduated augmentation, in which AI agents expand analytical capacity, accelerate close and planning cycles, and improve stakeholder alignment while humans retain accountability over material judgments and irreversible actions. Building on the synthesis, the paper proposes a five-layer framework that aligns use-case selection, autonomy design, control requirements, human oversight, and performance metrics. The framework helps organizations match agentic capability to task criticality, data quality, reversibility, and regulatory exposure. The paper contributes a finance-specific conceptualization of agentic adoption, unique research objectives, an implementation sequence for CFO organizations, and a future research agenda focused on control redesign, explainability, operating models, and the changing role of finance professionals.

Abstract -The development in technology has facilitated the creation and collection of large volumes of data, mostly images. Nevertheless, there are still challenges in terms of protection, associated with the need to protect people from violating the rules of using someone else's data in accordance with privacy regulations. In the more recent past, the use of deep learning-based models has seen increased interest due to their capability of embedding and extracting adaptive watermarks while ensuring visually pleasing results with resilience to geometrical manipulations as well as adversarial attacks. The combination of classical and intelligent approaches for watermarking has also shown enhanced results in the context of security and robustness. While significant progress has been made, there is still much room left for improvement when balancing invisibility, robustness, and computational complexity. Thus, this review paper explores the use of a state of art watermarking techniques. Key Words: Copyright Protection, Neural Network, SWT (Stationary Wavelet Transform), DWT (Discrete Wavelet Transform), IWT (Integer Wavelet Transform), Robustness, Imperceptibility, Security, Entropy.

Abstract As machine learning technologies advance rapidly across various domains, concerns over data privacy and model security have grown significantly. These challenges are particularly pronounced when models are trained and deployed on cloud platforms or third-party servers due to the computational resource limitations of users’ end devices. In response, zero-knowledge proof (ZKP) technology has emerged as a promising solution, enabling effective validation of model performance and authenticity in both training and inference processes without disclosing sensitive data. Thus, ZKP ensures the verifiability and security of machine learning models, making it a valuable tool for privacy-preserving AI. Although some research has explored the verifiable machine learning solutions that exploit ZKP, a comprehensive survey and summary of these efforts remains absent. This survey paper aims to bridge this gap by reviewing and analyzing all the existing Zero-Knowledge Machine Learning (ZKML) research from June 2017 to August 2025. We begin by introducing the concept of ZKML and outlining its ZKP algorithmic setups under three key categories: verifiable training, verifiable inference, and verifiable testing. Next, we provide a comprehensive categorization of existing ZKML research within these categories and analyze the works in detail. Furthermore, we explore the implementation challenges faced in this field and discuss the improvement works to address these obstacles. Additionally, we highlight several commercial applications of ZKML technology. Finally, we propose promising directions for future advancements in this domain.

Abstract In this review article, an exhaustive study has been conducted regarding several scientific papers on diverse 3D viewing systems and 3D projection techniques developed over the time span of 2020 to 2025. With advancements in computer vision, computer graphics, and artificial intelligence, there has been a significant utilization of 3D visualization and projection techniques in multiple industries including virtual reality, augmented reality, medicine, robots, entertainment, and intelligent space construction. In this literature review, 30 research papers are mentioned based on different themes of 3D reconstruction, Gaussian splatting, neural rendering, depth perception, panoramas, structured light setup, and real-time rendering techniques. The new trends in the fields of single view reconstruction, Multiview reconstruction, sparse view reconstruction, dynamic reconstruction, and material-aware rendering are explored in these papers. However, although all these advancements have been made, there are still issues of computation efficiency, memory efficiency, robustness, and ethics that must be addressed. Contemporary 3D viewing and projection techniques have established themselves as efficient tools but there is always room for improvement. Keywords 3D Visualization, 3D Reconstruction, Gaussian Splatting, Virtual Reality, Augmented Reality, Depth Estimation, View Synthesis

Retraction Note: Review paper on technology adoption and sustainability in India towards smart cities

This article presents a systematic review of eleven experimental studies on metaphoric anaphor processing. Beyond predicating specific properties to a subject (e.g., “Peter is an angel”, where angel conveys a set of possible features, such as kindness and helpfulness), metaphors can simultaneously fulfill a referential function, re mentioning an established discourse entity through a metaphorical noun, in this case called a ‘metaphorical anaphor’ (e.g., “That angel is always willing to help”, where angel also serves to refer to Peter). Given the experimental evidence that a higher processing cost is involved for referential metaphors relative to their literal counterparts and predicative metaphors, a special nature of metaphorical anaphors has been proposed. In this review paper, we offer a comprehensive overview of the recurrent research topics and findings on metaphorical anaphor by adopting a structured procedure of study identification and selection. We systematically compare the methodological and stimuli design variables to highlight their implications for processing and experimental outcomes. The review concludes with a discussion on the procedural costs of referential metaphors and a preliminary framework advocating for the development of an interactive model of processing.

Low back pain is a common musculoskeletal disorder that has a significant impact on physical function, work productivity, and quality of life. The majority of low back pain cases are classified as non-specific and are associated with impaired neuromuscular control and segmental instability of the lumbar spine. Core stability training is a conservative exercise approach that focuses on the activation and strengthening of deep trunk muscles to enhance lumbopelvic stability and reduce mechanical stress on passive spinal structures. This review article aimed to evaluate the effectiveness of core stability training in the prevention of low back pain related to physical activity. The article was developed through a review of experimental studies, randomized controlled trials, and meta-analyses that assessed the effects of core stability training on postural stability, neuromuscular control, trunk muscle strength and endurance, as well as the incidence and recurrence of low back pain. The findings indicated that core stability training improved functional spinal stability, enhanced neuromuscular coordination, and reduced the risk of low back pain as both a primary and secondary preventive intervention. Given its safety and ease of implementation, core stability training can be recommended as an effective preventive strategy.

Mindless scrolling has emerged as a pervasive yet understudied phenomenon in the digital age, often used as a means to cope with boredom, anxiety, and emotional discomfort. Characterized by passive and purposeless social media consumption, it is typically accompanied by reduced awareness of time and content. This review article aimed to explore the concept of mindless scrolling, factors that contribute to this behavior, and its influence on users’ well-being across psychological, neurological, and physical domains. It also explored the transition from mindless to mindful scrolling, emphasizing intentional and conscious engagement with digital content. After reviewing existing literature, including scholarly articles, media sources, and relevant websites, this study identified persuasive platform design, emotional avoidance and other factors contributing to the habit of mindless scrolling. The findings highlighted the negative influence of mindless scrolling on mental health and cognitive functioning, while also outlining practical strategies to promote mindful social media use. These include awareness-based practices, introduction of design friction through reaction-based interfaces and mindful scrolling feedback nudges, and the use of various digital well-being tools. The findings offer valuable insights for researchers, educators, and policymakers to better understand mindless scrolling and implement practical strategies that foster mindful technology use.

The modernization of the electrical grid into a smart grid has been widely recognized as a major technological advancement. Communication networks and digital control systems have been integrated to improve efficiency and reliability. However, it has also been observed that such integration introduces new cybersecurity risks. This paper presents a detailed review of cybersecurity in smart grids, including threats, impacts, standards, resilience strategies, and real-world applications. The study highlights the need for strong protection mechanisms and continuous research to ensure secure and reliable grid operations. This review paper explores the current landscape of cybersecurity within smart grid infrastructures, focusing on the critical balance between system performance and data integrity. We examine three primary pillars of modern defense: advanced threat modeling, robust data protection, and intelligent intrusion detection. Specifically, the paper discusses how secondary substations—often the weakest link in the grid can be protected through sophisticated risk assessment and information-theoretic metrics that quantify measurement vulnerability Keywords: Smart Grid, Cybersecurity, SCADA Systems, Data Integrity, Threat Modeling

Abstract - Successful disaster management and early warning are essential in reducing the effects of natural and human-induced hazards. Advances in real-time monitoring, data analysis, and communication technologies have greatly enhanced the forecast, detection, and response to disasters. This review paper presents a critical evaluation of contemporary methods, such as, geospatial analysis, and artificial intelligence-based prediction models. It also brings to light the shortcomings of current systems and delves into possibilities of building better real-time decision-making, timely warnings, and synchronized response strategies, leading the way for more adaptive and anticipatory disaster management solutions. Key Words: Disaster Management, Early Warning Systems, Artificial Intelligence, GIS, Citizen Reporting, Real-time Alerts, Machine Learning.

The aquaculture and fisheries industries are famed for producing wholesome waste and/or by-products, mostly underrated or downgraded to insignificant grounds. Even so, this ignored sector fosters high-price bioactive molecules that exhibit value added derivatives and their invaluable applications. Reinforcement of the blue economy along with vibrant expansion of fisheries prioritizes a wild as well as sustainable exploitation of marine resources. The increasing demand for sustainable and eco-friendly practices in various industries has led to a growing interest in the utilization of biowaste, particularly from the fishing industry. Fish biowaste, including skin, bones, and scales, is rich in valuable compounds such as gelatin, a protein with diverse applications in food, pharmaceuticals, cosmetics, and agriculture. Recovering gelatin from fish biowaste not only provides a sustainable solution for waste management but also offers a promising alternative to traditional mammalian-derived gelatin. Fish gelatin is a propitious substitute to innate gelatin, which faces religious restrictions. Gelatin derived from fish skin and bones is recognized for being biodegradable, with good film-forming capacity, making it a potential replacement for natural gelatin. Applications include edible coatings, microencapsulation and active packaging, benefiting from gelatin’s antioxidant and antimicrobial qualities. In this review article, we discuss a comprehensive summary of gelatin recovered from fish biowastes and their recent multifarious advances.

Medical terminology is a term or expression that is often made up of words with Latin and Greek suffixes, used to briefly and concisely describe the human body, diseases and causes that affect it, medical conditions, treatments and medications, and medical devices. These terms constitute the specific terminology used by health professionals. However, technological and social changes have caused new words to be added to the obstetrics vocabulary or have given new meanings to the words that are already in use. Advanced technological developments such as in vitro fertilization applications, biological banking, and genome technology have led to the formation and use of new concepts. These concepts are: Medicalization of the female body, biological product, object of desire, egg brotherhood, genetic kinship, genetic parenting, stored sperm, surrogate motherhood, commercial motherhood, designed baby, trafficking in biological women, reproductive exploitation. In conclusion, developments in the field of medicine and technology have contributed a lot to obstetrics but have also led to the emergence of new terms and problems expressed by these terms. The aim of this review article is to create a resource that can prevent confusion regarding new terms and their meanings that have gradually begun to be used in obstetrics.