Research Paths Research Articles

A Perspective on Green Solutions and Future Research Paths for Microplastic and Nanoplastic Contamination in Drinking Water

A Perspective on Green Solutions and Future Research Paths for Microplastic and Nanoplastic Contamination in Drinking Water

Core-Shell Composite Nanofibers with High Temperature Resistance, Hydrophobicity and Breathability for Efficient Daytime Passive Radiative Cooling.

Radiative cooling technology, which is renowned for its ability to dissipate heat without energy consumption, has garnered immense interest. However, achieving high performance, multifunctionality, and smart integration while addressing challenges such as film thickness and enhancing anisotropic light reflection remains challenging. In this study, a core-shell composite nanofiber, PVDF@PEI, is introduced and designed primarily from a symmetry-breaking perspective to develop highly efficient radiative cooling materials. Using a combination of solvent-induced phase separation (EIPS) inverse spinning and (aggregation) self-assembly methods (EISA or EIAA) and coaxial electrostatic spinning (ES), superconformal surface anisotropic porous nanofiber membranes are fabricated. These membranes exhibit exceptional thermal stability (up to 210°C), high hydrophobicity (contact angle of 126°), robust UV protection (exceeding 99%), a fluorescence multiplication effect (with a 0.6% increase in fluorescence quantum efficiency), and good breathability. These properties enable the material to excel in a wide range of application scenarios. Moreover, this material achieved a remarkable daytime cooling temperature of 8°C. The development of this fiber membrane offers significant advancements in the field of wearables and the multifunctionality of materials, paving new paths for future research and innovation.

Assessing the Complexity of Decarbonised Power Systems as a Means Towards a Sustainable Society: Trends and Hotspots

This paper aims to assess the complexity of decarbonized power systems by mapping the trends in the field of low carbon electricity over the period 2000-2023 employing an analysis of the scientific publications. This paper addresses the power sector as it plays an essential role in supporting global efforts towards a sustainable society. The paper provides an overview of decarbonised electricity trends by a quantitative analysis of publications, extracted from Dimensions database and explores relevant literature employing VOSviewer as a visualisation tool. The scientometric analysis reveals the main literature streams by using a semantic map, citation and co-citation analyses. The paper shows an increased preoccupation in the field, starting with 2000, and reveals the most relevant works. Moreover, by aggregating bibliometric data, the paper uncovers the social networks associated with the field and points the interested researchers towards the most influential works. By doing so, the paper provides a better understanding of the complexity of the field of decarbonised power system and allows the identification of current research directions and paves the way towards future research paths. Keywords: sustainable development, decarbonised power, quantitative research; climate change

Анализ профессиональной культуры сотрудников органов внутренних дел: философско-антропологический ракурс

The article provides an analysis of the professional culture of employees of internal affairs agencies from a philosophical and anthropological perspective. The work notes that two elements can be defined in the structure of professional culture - professional competence and personal qualities. A general description of each of these elements is given. It is noted that it is the philosophical and anthropological perspective that allows us to fully analyze the essence of the personal element in the structure of a certain type of professional culture. From the philosophical and anthropological perspective, three principles on which it is based have been identified: the unity of normativity and initiative; the unity of dynamism and statics; the need for systematic information exchange. These principles are of a dialectical nature and are defining, distinguishing the professional culture of employees of internal affairs agencies from other types. The personal component turns out to be of primary importance, influencing decision-making in a specific situation. Paths for further research into the professional culture of employees of internal affairs agencies are outlined.

Exploring the convergence of Metaverse, Blockchain, Artificial Intelligence, and digital twin for pioneering the digitization in the envision smart grid 3.0

The ongoing evolution of the Metaverse, digital twin (DT), artificial intelligence (AI), and Blockchain technologies is fundamentally transforming the utilization of sustainable energy resources (SERs) within smart grids (SGs), ushering in the era of smart grid 3.0 (SG 3.0). This paradigm shift presents unprecedented opportunities to establish robust and sustainable energy trading frameworks between consumers and utilities within the SG 3.0 environment. The integration of DT, AI, and Blockchain technologies in the context of the Metaverse’s smart grids, facilitated by optimized communication protocols, represents a transformative approach. AI models play a pivotal role in predictive energy trading analysis, while DT assumes a crucial role in effectively managing diverse SERs within SGs. Simultaneously, Blockchain technology holds the potential to create a trusted and decentralized environment, laying the foundation for an energy trading system within the SG 3.0 universe of the Metaverse. This visionary convergence of DT and Blockchain sets the stage for a futuristic paradigm in SGs, establishing a robust energy trading and management foundation. This paper embarks on exploring uncharted research paths and unlocking new dimensions by surveying and delving into the convergence of the Metaverse, Blockchain, AI, and DT. Its primary objective is to drive the digitization of SERs within SGs, to revolutionize energy systems. The envisioned SG 3.0 represents a significant leap by amalgamating cutting-edge technologies in sustainable energy, paving the way for revolutionary advancements in SGs’ digitization, which aligns with and contributes to achieving the sustainable development goals outlined by the United Nations.

Data Discovery for Digital Building Logbook (DBL): Directly Implementing and Enabling a Smarter Urban Built Environment

Digital Building Logbooks (DBLs) are the EU repositories for all building-related data. Logbook implementation conveys challenges, but it must be recognised that relevant things already exist. This article bridges the gap at the data discovery level by assessing the existing data and comparing it with EU DBL studies. Action research is the methodology, employing Portugal as an example. A deductive approach and interpretivism are used, supporting the data discovery journey. When evaluating existing datasets with DBL EU guidelines data requirements, the findings demonstrate a match from 90.6% to 82.6%, depending on the level: cadastral parcel, building or building unit. Several additional observed datasets suit the DBL framework, constituting a path for future research. Insights into the dataset landscape from a specific perspective are offered. Given the deliverables’ characteristics, the study results can be generalised. The data discovery journey led to the understanding that duplicates and inconsistencies exist. A strategic approach for data sharing, governance and usage should be established to solve them, increasing digital maturity, integration and interoperability. Revising the legal framework is found to be paramount. Working from the existing elements and aligning them with data space assumptions can make DBL implementation more straightforward.

Mapping the landscape of financial knowledge and financial socialization: Evidence from bibliometric and systematic analysis

This study makes an essential contribution by bringing together the various literature in the field, highlighting the important sources, authors, and documents, and investigating the relationship between financial literacy and financial behavior. Bibliometric analysis was performed on the keywords “financial literacy” and “financial behavior”. A sample of 203 documents was taken for the study from the Scopus database for the period 2014-2023 insightful information about the status of research today. This study combines systematic and bibliometric analyses to demonstrate the essential association between financial literacy and financial behavior. It also makes recommendations for future research paths at some point. This study can provide valuable insights for formulating financial literacy and education policies. By employing this study, researchers can also determine future research areas in financial literacy and financial behavior. Biblioshiny, a web-based application in the bibliometric package developed in R, was used for the study. An in depth, systematic analysis of the top 20 cited papers provides.

One Hundred Years of Pyrethroid Chemistry: A Still-Open Research Effort to Combine Efficacy, Cost-Effectiveness and Environmental Sustainability

A century after the first scientific research on the chemical structures of pyrethrins was published (in 1923), this paper aims to provide an exhaustive review of the historical research pathways and relative turning points that led to the discovery and mass production of pyrethroids, which have become among the most commercially successful insecticides. These compounds, which are not specific to any particular pest, are used globally and offer cost-effective advantages against a broad spectrum of pests in both agricultural and non-agricultural situations. They are utilized in the context of both harvest and post-harvest applications, as well as in the implementation of public health programs and veterinary applications. Currently, the research for new pyrethroids has essentially reached a standstill due to the increasingly widespread occurrence of insecticide resistance in pests. Nevertheless, several research paths remain open regarding these pesticides. This paper represents the current state of knowledge regarding pyrethroids, exposing both their advantages and disadvantages. Moreover, further investigation, at the molecular level, on their mode of action (MoA) could be very useful to improve their specificity. The results of this review may stimulate additional research for the development of novel pyrethroids having enhanced efficacy, low cost and reduced environmental impact.

Exploring empathy in artificial intelligence: synthesis and paths for future research

Purpose The current research elucidates the role of empathy in design of artificial intelligence (AI) systems in healthcare context, through a structured literature review, analysis and synthesis of academic literature published between 1990 and 2024. Design/methodology/approach This study aims to advance the domain of empathy in AI by adopting theory constructs context method approach using the PRISMA 2020 framework. Findings The study presents a current state-of-the-art literature to review the connections between empathy and AI and identifying four clusters showing the emerging trajectories in the field of AI and empathy in healthcare setting. Originality/value Despite a rise in empirical research, the potential pathways enhancing AI accountability by incorporation of empathy is unclear. The research aims to contribute to the existing literature on AI and empathy in the healthcare sector by carving out four distinct clusters depicting the future research avenues.

Advancements in Optimization: Critical Analysis of Evolutionary, Swarm, and Behavior-Based Algorithms

The research work on optimization has witnessed significant growth in the past few years, particularly within multi- and single-objective optimization algorithm areas. This study provides a comprehensive overview and critical evaluation of a wide range of optimization algorithms from conventional methods to innovative metaheuristic techniques. The methods used for analysis include bibliometric analysis, keyword analysis, and content analysis, focusing on studies from the period 2000–2023. Databases such as IEEE Xplore, SpringerLink, and ScienceDirect were extensively utilized. Our analysis reveals that while traditional algorithms like evolutionary optimization (EO) and particle swarm optimization (PSO) remain popular, newer methods like the fitness-dependent optimizer (FDO) and learner performance-based behavior (LPBB) are gaining attraction due to their adaptability and efficiency. The main conclusion emphasizes the importance of algorithmic diversity, benchmarking standards, and performance evaluation metrics, highlighting future research paths including the exploration of hybrid algorithms, use of domain-specific knowledge, and addressing scalability issues in multi-objective optimization.

Uncovering the coronavirus outbreak: present understanding and future research paths.

The review discusses the pathophysiological mechanisms of SARS-CoV-2, the modes of transmission, and the long-term health consequences of COVID-19, emphasizing the importance of research and successful public health initiatives. COVID-19 taxonomy, pathophysiology, symptomatology, and epidemiological importance are the key objects of this research paper. This review explains how COVID-19 affects different systems of the body, including respiratory, cardiovascular, and reproductive systems of the human body. It describes the modes of entry of the virus into the cell; more precisely, ACE2 and TMPRSS2 in viral entry. In addition, the present study analyzes the situation of COVID-19 in India regarding vaccine development and the transmission rate related to socioeconomic factors. The manifestation of COVID-19 presents a lot of symptoms and post-acute problems, issues which are seriously impacting mental health and physical health as well. The present review summarizes current research into pathogenicity and the mode of virus transmission, together with immunological responses. Coupled with strong vaccination programs, public health initiatives should hold the key to fighting this pandemic. Long-term effects and the development of treatment methods will need further study, as ambiguities on COVID-19 remain. Multidisciplinary collaboration across healthcare sectors in this respect is of paramount importance for the prevention of further spread and protection of public health.

Adapting the ‘study and research path’ methodology in strength of materials to online teaching and resource-constrained scenarios

The Study and Research Path (SRP) methodology, emphasizing exploration of answers to open questions, has recently gained recognition as an effective active and inquiry-based learning approach, notably in the realm of Mechanical Engineering education. This study investigates the adaptation of SRPs to online and resource-constrained environments. We present and compare eight SRP-based Strength of Material courses conducted before, during, and after the COVID-19 pandemic. Our analysis focuses on the transformations observed in SRPs, encompassing shifts in course organization, question-answer maps, media-milieu dialectics, resource utilization, and inquiry procedures. Our findings demonstrate the successful adaptation of the SRP course to online teaching during the unprecedented remote conditions brought about by the pandemic. This adaptation resulted in a more guided Q-A map, innovative practical experiences with homemade setups, increased use of simulations, and parallelized inquiry by different groups. Importantly, materials and strategies developed during this transformation proved invaluable in subsequent post-pandemic courses, particularly in hybrid or constrained space and cohort settings. Our study highlights the adaptability and efficacy of SRPs in diverse teaching environments, providing valuable insights for educators seeking to implement SRPs and other active-learning, inquiry-based methodologies to challenging ecological conditions.

The Research Advances in Distant Hybridization and Gynogenesis in Fish

ABSTRACTDistant hybridization and gynogenesis are two prevalent breeding techniques for fishes. Drawing from the research achievements of our team and the existing literature, we summarize the reproductive traits and genetic features of fishes derived from distant hybridizations and gynogenesis, and we deduce the fundamental mechanisms of these two methods and compare them, discerning their common and different characteristics. Both distant hybridization and gynogenesis techniques can alter genotypes and phenotypes, thus establishing them as significant breeding methods. Additionally, the genetic principles and the basic biological characteristics of distant hybridization and gynogenesis in fish have been inferred. We propose the concepts of macro‐hybrid and micro‐hybrid based on extensive experimental findings from fish distant hybridizations and gynogenesis. The term “macro‐hybrid” refers to offspring from distant hybridization that possess two distinct subgenomes, each inherited from one of the two parental species, such as allodiploid and allotetraploid lineages. The concept of “micro‐hybrid” refers to offspring, including autodiploid and autotetraploid lineages, as well as those resulting from artificial gynogenesis, whose genome almost originates solely from the maternal parent but in which certain DNA fragments derived from the paternal parent insert. Distant hybridization and gynogenesis are vital techniques in fish genetics, breeding, and evolution. We highlight the prospective paths for research and application of distant hybridization and gynogenesis in fishes.

Enhancing Unmanned Aerial Vehicle Security: A Zero-Knowledge Proof Approach with Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge for Authentication and Location Proof.

UAVs are increasingly being used in various domains, from personal and commercial applications to military operations. Ensuring the security and trustworthiness of UAV communications is crucial, and blockchain technology has been explored as a solution. However, privacy remains a challenge, especially in public blockchains. In this work, we propose a novel approach utilizing zero-knowledge proof techniques, specifically zk-SNARKs, which are non-interactive cryptographic proofs. This approach allows UAVs to prove their authenticity or location without disclosing sensitive information. We generated zk-SNARK proofs using the Zokrates tool on a Raspberry Pi, simulating a drone environment, and analyzed power consumption and CPU utilization. The results are promising, especially in the case of larger drones with higher battery capacities. Ethereum was chosen as the public blockchain platform, with smart contracts developed in Solidity and tested on the Sepolia testnet using Remix IDE. This novel proposed approach paves the way for a new path of research in the UAV area.

Acidified sucralfate encapsulated chitosan derivative nanoparticles as oral vaccine adjuvant delivery enhancing mucosal and systemic immunity

Oral vaccines are generally perceived to be safe, easy to administer, and have the potential to induce both systemic and mucosal immune responses. However, given the challenges posed by the harsh gastrointestinal environment and mucus barriers, the development of oral vaccines necessitates the employment of a safe and efficient delivery system. In recent years, nanoparticle-based delivery has proven to be an ideal delivery vector for the manufacture of oral vaccines. Hence, considering the above, the sucralfate acidified (SA) encapsulated N-2-Hydroxypropyl trimethyl ammonium chloride chitosan (N-2-HACC)/N,O-carboxymethyl chitosan (CMCS) nanoparticles (SA@N-2-HACC/CMCS NPs) were prepared, and the BSA was used as a model antigen to investigate the immune responses. The SA@N-2-HACC/CMCS NPs had a particle size of 227 ± 7.0 nm and a zeta potential of 8.43 ± 2.62 mV. The NPs displayed slow and sustained release and high stability in simulated gastric juice and intestinal fluid. RAW 264.7 macrophage-like cell line demonstrated enhanced uptake of the SA@N-2-HACC/CMCS/BSA Nps. The vaccine via oral administration markedly enhanced the residence time of BSA in the intestine for more than 12 h and elicited the production of IgG and sIgA. The SA@N-2-HACC/CMCS NPs developed here for oral administration is an excellent technique for delivering antigens and provides a path of mucosal vaccine research.

Bibliometric analysis of internet of things (IoT) in the construction industry using Scopus database: Trends, characteristics, and future directions

This research examines the Internet of Things (IoT), a fast-developing technology that has transformed several industries, through bibliometric analysis of the building and construction sector. The current state of research, its features, and possible future paths are evaluated using the Scopus database. A thorough search of the literature conducted with Scopus produced a total of 2070 publications published between 2004 and 2022. Over the past five years, the number of IoT articles in the construction industry has significantly increased, according to the research. The study found that the top five countries for publications on this issue were China, Hong Kong, India, Portugal, and Sweden. The data suggests that a number of topics, such as energy management, construction automation, and smart buildings, have attracted a lot of attention. Additionally, the survey found that wireless networks and sensors were the IoT technology most frequently employed in the construction sector. The paper also makes recommendations for potential research directions, including the employment of cutting-edge technologies like blockchain and artificial intelligence, as well as the application of IoT in the building sector. The study’s results shed light on market trends, unmet needs in the field, and prospective directions for Internet of Things applications in the construction sector.

Mitophagy in acute central nervous system injuries: regulatory mechanisms and therapeutic potentials.

Acute central nervous system injuries, including ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage, traumatic brain injury, and spinal cord injury, are a major global health challenge. Identifying optimal therapies and improving the long-term neurological functions of patients with acute central nervous system injuries are urgent priorities. Mitochondria are susceptible to damage after acute central nervous system injury, and this leads to the release of toxic levels of reactive oxygen species, which induce cell death. Mitophagy, a selective form of autophagy, is crucial in eliminating redundant or damaged mitochondria during these events. Recent evidence has highlighted the significant role of mitophagy in acute central nervous system injuries. In this review, we provide a comprehensive overview of the process, classification, and related mechanisms of mitophagy. We also highlight the recent developments in research into the role of mitophagy in various acute central nervous system injuries and drug therapies that regulate mitophagy. In the final section of this review, we emphasize the potential for treating these disorders by focusing on mitophagy and suggest future research paths in this area.

A Comprehensive Study on Advanced Video Data Preprocessing Techniques for Enhanced Object Detection

Video processing has become a vital area in computer vision and deep learning, with diverse applications including crowd analysis, anomaly identification, and activity tracking. Although numerous surveys have examined various aspects of these functionalities, there is still a requirement for a complete review that combines these findings into a coherent perspective. This survey study provides a comprehensive analysis of several model architectures, emphasising their advantages, shortcomings, and constraints. We also emphasise the profound influence of these technologies in several fields, such as surveillance, healthcare, and autonomous systems, specifically focussing on the applications of deep learning in video processing. Our review not only analyses the latest advancements but also explores the complex processes and tactics used by deep learning models to derive valuable insights from video data. Furthermore, we examine the importance of accessible datasets and their crucial role in propelling research progress in this field. By outlining the obstacles and concerns that researchers have while adopting these systems, we offer a clear plan for future research paths. We want to stimulate ongoing innovation and advancement in the domain of video processing using deep learning techniques.

Study of peak Laminar Burning Velocity of several syngas compositions at different temperatures

In the context of the current energy transition, the use of biomass-derived syngas (BDS) is often recognized as a fundamental path towards decreasing fossil fuel dependency and greenhouse gas emissions. However, hydrogen-containing BDS are prone to flame instability problems. More efforts are being carried out aiming at efficiently adopting BDS in industrial combustors with CH4 co-firing or inert gas dilutions by exploring accurate knowledge of burning velocity. To do so, a deeper knowledge of the syngas combustion behaviour is strictly necessary. The objective of this study fits in this framework: in particular, a computational study has been carried out to evaluate kinetic models and present fresh insights on the effects of varying syngas mixtures such as CO/H2, CO/H2/CO2 and CO/H2/CH4 on Laminar Burning Velocity (LBV) and peak LBV location (ΦLBV=max). In-detail chemical kinetic simulations of equimolar (CO: H2 = 1:1) forestry waste syngas were systematically carried out taking advantage of the open-source CANTERA solver. Three detailed kinetic models i.e., newly released FFCM-2, USC mech II, and modified GRI mech III were implemented to report accurate flame parameters at 1 bar and different temperature levels (from 300 K up to 450 K). On comparing the results with experiments, FFCM-2 proved to be a good kinetic model for the considered syngas mixtures CO/H2, CO/H2/CO2 and especially for CO/H2/CH4 for mixtures containing a limited share of 30 % methane at normal and moderately elevated temperature at 0.4 ≤ Φ ≤ 2.1. The USC mech II performed very well for CO/H2, and CO/H2/CO2, while the modified GRI mech III model also gave agreeable predictions for CO/H2/CH4 mixture having rich methane content. Additionally, when varying syngas composition analysis was conducted at different temperatures, the progressive CO2 dilution and CH4 addition of up to 30 % reduced the peak LBV and moved the peak LBV locations (ΦLBV=max) towards lean ER conditions with 9 % and 40 % reductions, respectively; however, only the latter effect was enhanced at the elevated initial temperature. Furthermore, sensitivity analysis of respective syngas mixtures is reported at normal and elevated temperatures to explore the most sensitive intermediate reactions relative to LBV. The shift of peak LBV locations and their enhancement at elevated temperatures also open the research path to study the underlying impacts on the flame modes/regimes and structure, especially CO emissions pathways in syngas with 30 % of CH4 and CO2 additions.

An effective imaging based diagnosis of Solar Photovoltaic System and performance parameters for smart solar power grid

Another of the most attractive power generation sources for residential, corporate, and commercial operations is energy production. Due to this compelling qualities, photovoltaic systems (PV) electricity production have increasingly attracted the attention of researchers and professionals. Nonetheless, the greatest obstacle in generating energy from the sun is the predictable discontinuous output power from photovoltaic (PV) systems, which is largely caused by climate. The power differential of a photovoltaic panels may considerably reduce the financial profit of large scale solar fields. For everyday proper management of electricity supply production, distribution, and storing as well as for judgement on the electricity market, results were consistent prediction of the electricity output of solar PV systems is essential. The 5 subjects mentioned in this article are: The varied faults which might occur in PV panels; internet Photovoltaic panels monitoring; Use of machine learning approaches in Photovoltaic module damage detection; Advantages of fault diagnosis in PV panels and the various motion sensors used for this purpose are discussed. Recommendation for future possible research paths are given in view of the evaluated research.