Sophisticated Products Research Articles

Marketing Harm to Children: Children’s exposure to unhealthy commodity marketing using body cameras

Abstract Background Sophisticated, persuasive and extensive product marketing is a key driver of unhealthy commodity (UHC) consumption. This study aims to identify the nature and extent of children’s exposure to UHC marketing. Methods The study is a secondary analysis of Kids’Cam, a cross-sectional study in which 168 New Zealand 12-year-old children wore body cameras that automatically captured images of their environment every 7 seconds over four days. Images were analysed for exposure to UHC, Healthy and ‘Other’ marketing. Results Children were exposed to UHC marketing on average 76.2 times/day, nearly 2.5 times their daily exposure to ‘Healthy’ marketing. Exposure included: unhealthy food marketing (68.4/day), alcohol (5.7/day), gambling (2.1/day) and tobacco marketing (0.1/day). These exposure rates align with the level of statutory regulation each UHC faces in NZ. Food outlets were the most common setting for UHC marketing exposures, while product packaging was the most common medium. Coca-Cola (6.3/day) was the most common UHC exposure, followed by Cadbury, Tip Top, Bluebird and Powerade. Over half of children’s unhealthy food (54.9%) and alcohol (51.9%) marketing exposures were attributed to multinational corporations. In contrast, statutory bodies are responsible for almost all (97.4%) of children’s gambling marketing exposure. Conclusions Children currently grow up in an environment in which they are constantly persuaded to consume products that directly harm their health - an environment in which the profits of corporations are favoured over public health. Statutory regulation of UHC marketing is urgently needed to protect children from harm. Key messages • Children were exposed to unhealthy commodity marketing on average 76.2 times/day, nearly 2.5 times their daily exposure to ‘healthy’ marketing. • Statutory regulation of unhealthy commodity marketing is urgently needed to protect children from harm.

Exploring the nexus between exports’ economic complexity and institutional quality: insights from Italian provinces

ABSTRACT The present research aims to investigate the determinants of economic development and productivity by proposing an empirical analysis of the economic effects of institutional quality on the economic complexity of export at the intra-national level, focusing on 103 Italian provinces from 2004 to 2016. Using the System Generalised Method of Moments (System-GMM) estimator, the study assesses the influence of various institutional dimensions on provincial economic complexity, as measured by the Economic Complexity Index (ECI). The findings indicate that institutional quality, particularly rule of law, regulatory quality, and voice and accountability, significantly enhances economic complexity. Better formal and informal institutions such as completeness of contracts, social cohesion, contract enforcement, by reducing transaction costs and uncertainty, and by favouring knowledge dissemination and security of investments, are source of comparative advantage in complex industries that lead to diversified and sophisticated production, fostering economic growth and innovation. Moreover, the study emphasises the importance of related activities, which interact with institutions to support complex and innovative export-related activities through knowledge spillovers and related diversification. The analysis also highlights the pivotal role of human capital, social capital, and innovation, which should remain focal points for policymakers.

Research and Application Progress of Aerogel Materials in the Field of Batteries and Supercapacitors

Aerogels, characterized by their exceptional porosity, vast specific surface areas, minimal density, and unparalleled thermal insulation capabilities, have become a focal point of attention in the energy sector over the past decade, particularly in the realms of batteries and supercapacitors. This comprehensive review delves into aerogels and their preparation methods, while reviewing their recent applications in batteries and supercapacitors. It delves deeply into the research and development progress, as well as the application advancements of aerogel materials in separators, electrolytes, and electrodes. Furthermore, this article highlights that the research on aerogels still faces some challenges, such as steep costs, sophisticated production steps, and relatively weak overall mechanical strength. Therefore, in the future, it is necessary to further strengthen the fundamental research and technological innovation of aerogel materials, and promote their industrialization process and wide application in the field of energy storage, particularly in the areas of batteries and supercapacitors.

Urban Agriculture and Food Security in Development Planning

With the world population anticipated to reach over nine billion in 2050, and the majority of whom will live in cities, feeding a predominantly urban population will pose additional challenges to a predominantly rural-based agrifood system. Further, with the focus of economic activity being centered in cities, a development question is whether agriculture in cities should be an integral part of national planning. This is particularly when food insecurity is expected to challenge the poor in cities much more than in the countryside. Urban and peri-urban agriculture has been practiced in many parts of the world through activities ranging from community gardens to commercial farms of varying sizes. A major change, accelerated by supply chain disruptions and the COVID-19 pandemic in the early 2020s, has been the rapid development of technologies (digital, physical, biotechnological) that increases food production capabilities in urban areas and provide economic opportunity for entrepreneurship. Additionally, sizable investments from private equity have seen sophisticated food production facilities, such as indoor vertical vegetable and fish farms and precision fermentation factories, produce novel food such as alternative proteins in city spaces. Apart from the economic and food security benefits arising from urban agriculture, environmental and social benefits have also been demonstrated in cities that have adopted a clear mandate to become “green” and reduce their carbon footprints. This paper provides a background on urban farming, its justification as a worthwhile activity, and the rationale for explicitly including urban agriculture in national planning.

Synthesis of Heptacyclic Compounds through C-H Bond Activation-Initiated Cascade Reactions.

Presented herein is an atom- and step-economical method enabling the precise assembly of a heptacyclic scaffold containing both azocine and indoline units through the cascade reactions of indolin-1-yl(aryl)methanimines with diazo indanediones. The formation of products involves C-H bond activation and double carbene insertion followed by intramolecular condensation, retro-[2 + 2] cycloaddition, and recyclization. This cascade reaction not only provided a concise and straightforward strategy for the synthesis of the otherwise difficult to obtain heptacyclic compounds from readily available substrates but also disclosed an unprecedented reaction mode for indoline derivatives and diazo compounds. In general, this novel synthetic protocol has advantages, such as easily obtainable substrates, structurally sophisticated products, concise synthetic procedure, good compatibility with diverse functional groups, and ready scalability. Moreover, the products thus obtained showed decent antiproliferative activity against three human cancer cell lines.

Direct Ink Writing of Highly Conductive and Strongly Adhesive PEDOT:PSS-EP Coatings for Antistatic Applications

As the information age progresses, the electronics industry is evolving towards smaller and more sophisticated products. However, electrostatic potentials easily penetrate these components, causing damage. This underscores the urgent need for materials with superior antistatic properties to safeguard electronic devices from such damage. Antistatic coatings typically rely on polymers as the primary material, enhanced with conductive fillers and additives to improve performance. Despite significant progress, these coatings still face challenges related to advanced processing technologies and the integration of electrical and mechanical properties. Among various conductive fillers, the conducting polymer PEDOT:PSS stands out for its exceptional conductivity, environmental stability, and long cycle life. Additionally, epoxy resin (EP) is widely utilized in polymer coatings due to its strong adhesion to diverse substrates during curing. Here, we develop highly conductive and strongly adhesive PEDOT:PSS inks by combining PEDOT:PSS with EP using a composite engineering approach. These inks are used to fabricate PEDOT:PSS coatings by direct ink writing (DIW). We systematically evaluate the DIW of PEDOT:PSS-EP coatings, which show high electrical conductivity (ranging from 0.59 ± 0.07 to 41.50 ± 3.26 S cm−1), strong adhesion (ranging from 15.84 ± 2.18 to 99.3 ± 9.06 kPa), and robust mechanical strength (8 MPa). Additionally, we examine the surface morphology, wettability, and hardness of the coatings with varying PEDOT:PSS content. The resultant coatings demonstrate significant potential for applications in antistatic protection, electromagnetic shielding, and other flexible electronic technologies.

Exploration of the Application of Artificial Intelligence in High School English Speaking Teaching

With the remarkable strides in artificial intelligence (AI) technology, a range of sophisticated techniques and products have sprung forth, including speech recognition and semantic analysis. These advancements have propelled the application of AI to new heights, particularly in the realm of education. Notably, AI applications such as speech recognition, human-computer interaction, and automated evaluation have revolutionized traditional English speaking teaching, introducing unprecedented changes to the way students learn and interact. The paper aims to investigate how AI might enhance high school pupils' English-speaking proficiency, which employs a literature review methodology to examine and illustrate the smooth integration of AI technology with high school English speaking instruction. This approach enhances speaking learning materials and fosters creativity in teaching strategies and assessment techniques. In addition, it creates room for the evolution of the oral teaching style and broadens the learning environment. This intelligent transformation of the oral teaching mode is expected to effectively enhance the effectiveness of high school oral English teaching and ultimately improve students' language proficiency.

Sophisticated natural products as antibiotics.

In this Review, we explore natural product antibiotics that do more than simply inhibit an active site of an essential enzyme. We review these compounds to provide inspiration for the design of much-needed new antibacterial agents, and examine the complex mechanisms that have evolved to effectively target bacteria, including covalent binders, inhibitors of resistance, compounds that utilize self-promoted entry, those that evade resistance, prodrugs, target corrupters, inhibitors of 'undruggable' targets, compounds that form supramolecular complexes, and selective membrane-acting agents. These are exemplified by β-lactams that bind covalently to inhibit transpeptidases and β-lactamases, siderophore chimeras that hijack import mechanisms to smuggle antibiotics into the cell, compounds that are activated by bacterial enzymes to produce reactive molecules, and antibiotics such as aminoglycosides that corrupt, rather than merely inhibit, their targets. Some of these mechanisms are highly sophisticated, such as the preformed β-strands of darobactins that target the undruggable β-barrel chaperone BamA, or teixobactin, which binds to a precursor of peptidoglycan and then forms a supramolecular structure that damages the membrane, impeding the emergence of resistance. Many of the compounds exhibit more than one notable feature, such as resistance evasion and target corruption. Understanding the surprising complexity of the best antimicrobial compounds provides a roadmap for developing novel compounds to address the antimicrobial resistance crisis by mining for new natural products and inspiring us to design similarly sophisticated antibiotics.

The Impact of Investor Expectation on the Financial Decision-Making

Unlike traditional finance, behavioral finance challenges the traditional financial theory of investor rationality, emphasizing that investors are not absolutely rational in real life. This perspective provides new insights for understanding and predicting financial markets. This study examines core concepts in behavioral finance, such as loss aversion, market anomalies, momentum effects, reversal effects, endowment effects, and framing effects, and analyzes how they influence investors' financial decisions. These concepts highlight the significant role of human psychology and behavior in shaping financial decisions, thus aiding investors in making more rational choices in complex financial markets. Loss aversion, for instance, suggests that investors are more sensitive to losses than to gains, leading to suboptimal decision-making. Market anomalies, such as price bubbles and crashes, indicate that markets are not always efficient. Momentum effects suggest that past stock performance can predict future trends, while reversal effects point to the tendency of extreme stock performances to revert to the mean. The endowment effect reveals that individuals value their own possessions more highly than similar items they do not own. Lastly, framing effects demonstrate how the presentation of information can influence decision-making. Future research can delve deeper into how the framing effect can be harnessed to improve the design and marketing strategies of financial products, thereby enhancing the efficiency and effectiveness of investment decisions. This exploration could lead to more sophisticated financial products and better-informed investors, ultimately contributing to a more stable and efficient financial market.

Leveraging Artificial Intelligence and Machine Learning for Digital Transformation in the Banking Sector

Over the years, technology has revolutionized our world. It has changed our lives from barter system to currency system, and now it has upgraded to Artificial Intelligence powered system. It has also changed the way we think, the way we communicate, the way we bank and transact. The technology is getting better and smarter day-by-day leading human life become easier, faster, and convenient. In this digitalized era, like all other industrial sectors, it has become imperative for banking sectors to embrace digital transformation and to adopt new technologies like artificial intelligence and machine learning. Banks that fail to make the leap to digital transformation will risk being overtaken by competition and deserted by their customers.This paper provides a detailed review about Artificial Intelligence and Machine learning in banking, covering key areas such as customer services, fraud detection, personalised banking services, credit scoring, operational efficiency, and sophisticated product development.

The Relationship between Commercial, Technological, Research (Multidimensional) Complexity Indices and Financial Development

The source of economic growth is the supply-demand balance. Demand refers to consumption and supply refers to production. Producing quality products plays an important role on the production side of this balance. The country, which has a wide range of qualified products called sophisticated products, continues to grow with financial development. The concept of economic complexity refers to product diversity. This concept has taken its place in the literature by being expanded into commercial, technological, and research complexity indices as the content of the multidimensional complexity index. In this study, the relationship between multidimensional complexity indices and financial development indicators of E7 (Emerging) countries (Brazil, China, India, Indonesia, Mexico, Russia, Turkey) is analyzed with Gengenbach, Urbain, and Westerlund Cointegration Test and Mean Group Estimator applied in case of cointegration. It has been determined that these variables are cointegrated, and this relationship between the commercial and technological complexity index and financial development is significant. As a result of the analysis with the mean group estimator, it was concluded that the technological complexity index has a greater impact on financial development than the commercial and research complexity indices.

The Role of European Supervisory Authorities in Consumer Protection Standard Setting on the Financial Services Market – Based on the Example of the European Banking Authority

The purpose of the article is to present the genesis of the emergence and the scope of powers of the European Supervisory Authorities (ESAs) (the EBA, ESMA, and EIOPA), with particular reference to the EBA as regards the building of its supervisory normative standard and the protection of the consumer of financial services. The authors will propose de lege ferenda postulates which, in their view, would allow for an improvement in the quality of the financial services offered to consumers and ensure a higher level of protection of their interests and, at the same time, legal certainty for their providers. Increasingly sophisticated and complex financial products cause interpretation difficulties for both the courts and consumer protection authorities, but above all for consumers themselves, which consequently poses a challenge for both sides of the market (supply and demand). It is also a challenge for the post-crisis ESAs as the EU bodies not only designated to monitor and manage both the stability and security of the financial market, along with the actual level of consumer protection within it. In the preparation of the article, the legal-dogmatic and legal-theoretical method, which is standard for such studies, was applied, which allows for an analysis of the provisions of EU law and the identification of the norms stemming from them using interpretation and the assessment of the content of the provisions through the prism of the principle of consumer protection from Articles 12 and 169 TFEU and the EBAs’ competence provisions. Due to the fact that, in principle, the powers and competences of all three ESAs are analogous and only differ in terms of the scope of their application (i.e., financial institutions operating in the relevant financial market sectors – banking, insurance, and pension and investment), the authors will present their considerations with reference to the European Banking Authority (EBA), which is an exemplification of the powers of the other supervisory authorities. Thus, the secondary piece of EU legislation to be considered in this article will be the Council and European Parliament Regulation, hereinafter known as “EBA Regulation” and the actions taken by the EBA on that basis.

Integrasi Kecerdasan Buatan Dalam Sistem Rekomendasi Produk Untuk E-Commerce

The increasing popularity of e-commerce has driven the development of more sophisticated product recommendation systems to enhance user experience. Within this framework, the incorporation of Artificial Intelligence (AI) has become essential for enhancing the caliber of product suggestions through the examination of user behavioral patterns and product attributes. This paper explores the incorporation of artificial intelligence into e-commerce product recommendation systems. This strategy integrates AI methodologies like machine learning, data mining, and natural language processing (NLP) to produce recommendation systems that are personalized and pertinent. Through in-depth analysis of user data and product information, the system can predict user preferences with higher accuracy, improve user engagement levels, and ultimately increase sales conversions. By combining domain knowledge, technical expertise, and the latest research methodologies, This research offers valuable insights for both e-commerce system developers and artificial intelligence researchers. The integration of artificial intelligence into product recommendation systems represents a critical measure in facilitating growth and fostering innovation within the ever-changing e-commerce landscape.

Analysis of the Impact of Globalization Trends in the Digital Economy on Business Management and Administration Systems of Enterprises

Aim. This study aims to investigate the impact of globalization trends on the business management and administration systems. Methodology. The scoping review of the literature included 123 articles through desk research and in-house material. Upon categorizing typologies as qualitative, quantitative, or mixed, an assessment was made regarding the performance and consequences of globalization from 1990 to 2022. Results. Developing country managers are more likely to depend on international sales as a means to augment revenue, due to the greater saturation of sales in developed markets. Developed economies focus on advanced, possibly automated production methods, whereas developing nations employ the digital economy to compete in less automated industries. This creates a more specialized global market..E-commerce in the digital economy makes it easier for developing nations to enter the global market and reach a global audience. In their pursuit of financial gain, corporations based in affluent nations are more likely to employ sophisticated production methods, while those situated in developing countries are more likely to utilize less advanced ones. A number of prevalent issues and trends—including economics, politics, emerging markets, corporate social responsibility, and emerging markets—were recognized as critical for the development of global markets. While past research has focused on globalization's effects on developed economies, this study examines emerging country managers' unique difficulties and opportunities. The emphasis on expanding international sales and potential manufacturing process reduction can inform management approaches in similar situations. Conclusion. The recommendations underscore the critical necessity for further investigation into the aforementioned impacts across diverse economies, ranging from developing to developed. Although this study encountered difficulties due to inconsistent and limited data, it established a strong foundation for subsequent investigations in the field through the application of operationalization, methodologies, and analyses discovered in the business literature.

Strategies for Smart Manufacturing Industry 5.0: High Quality Development for the Future

The proposal of Industry 5.0 is an effort and attempt to shape a new type of industrialization using human defined values. The core elements of Industry 5.0, including human centeredness, sustainable development, and resilience, are all different forms of high-quality development. This article proposes four corporate value innovation strategies - rainforest strategy, wetland strategy, grassland strategy, and oasis strategy - to provide management suggestions for traditional manufacturing enterprises to shift to smart manufacturing Industry 5.0. Human-robot collaboration, AI and machine learning, IoT and cyber-physical systems, sustainable manufacturing, human-centered workplace designs, resilient and flexible supply chains, and digital twin and simulation technologies are covered in the text. This article presents a detailed plan for the shift towards Industry 5.0, emphasizing the advantages and real-world uses of these sophisticated production techniques. On the new journey, what kind of response can smart manufacturing Industry 5.0 makes and how can they make forward-looking strategic preparations?

Comprehensive Assessment and Analysis of the Current Global Aerosol Optical Depth Products

Aerosol Optical Depth (AOD) is one of the most important optical properties of aerosols that may affect the energy budgets of our Earth–atmosphere system significantly. Currently, while regional and even global AOD knowledge has been given by various satellites or models, these products are still fraught with uncertainties. In this study, one sophisticated satellite-derived AOD product from MODIS (MODerate resolution Imaging Spectral-radiometer) and two state-of-the-art model-based AOD products from CAMS (Copernicus Atmosphere Monitoring Service) and MERRA-2 (Modern-Era Retrospective analysis for Research and Application Version 2), based on AERONET measurements from 2000–2022, analyzed the spatial distribution characteristics of global AOD. Then using the Mann-Kendall (MK) trend test, the AOD changing trends revealed by the three products were also computed and analyzed. The accuracies of these products and the reliabilities of changing trends derived are discussed and concluded finally. Our study demonstrates that MODIS products have wider applicability, matching best with AERONET globally, while CAMS and MERRA-2 products are only reliable in North America, South America, and Europe. Through comparative analysis of the AOD trends, we found that MODIS, CAMS, and MERRA-2 AOD consistently exhibited decreasing trends in eastern Asia, Europe, and eastern North America. On the other hand, different products showed increasing trends in regions like West Asia, South Asia, and South Africa, suggesting their limited reliability. The reliability assessment shows that 41.45% of the areas have consistent trends among the three products, with approximately 3.2% showing significant and consistent results. When using site trend validation, the proportions of sites with consistent trends are highest at 64.56% and 46.84% respectively. The regions with the best reliability of global trend changes are mainly distributed in North America, Europe, Australia, eastern Asia, and Central South America. This study provides new insights for validating aerosol changes using remote sensing and has the potential to enhance future monitoring and evaluation methods of aerosol products.

Considering the Secondary Use of Clinical and Educational Data to Facilitate the Development of Artificial Intelligence Models.

Medical training programs and health care systems collect ever-increasing amounts of educational and clinical data. These data are collected with the primary purpose of supporting either trainee learning or patient care. Well-established principles guide the secondary use of these data for program evaluation and quality improvement initiatives. More recently, however, these clinical and educational data are also increasingly being used to train artificial intelligence (AI) models. The implications of this relatively unique secondary use of data have not been well explored. These models can support the development of sophisticated AI products that can be commercialized. While these products have the potential to support and improve the educational system, there are challenges related to validity, patient and learner consent, and biased or discriminatory outputs. The authors consider the implications of developing AI models and products using educational and clinical data from learners, discuss the uses of these products within medical education, and outline considerations that should guide the appropriate use of data for this purpose. These issues are further explored by examining how they have been navigated in an educational collaborative.

Application for Machine Learning Methods in Financial Risk Management

Financial risk management has significant importance and implications for individuals, businesses, investors, and even the whole nation. As the financial markets and institutes grow complex so does the risk associated with financial management. The spectrum of financial risks includes market risk, liquidity risk, credit risk, and a range of others. With a multitude of portfolios and sophisticated products, financial firms require apt tools that can accurately measure the risk, returns, and exposure. The growing complexity has also made statistical and simulation tools ineffective and there is a growing emergence of machine learning. Machine learning is a sub-category of artificial intelligence that uses algorithms. These algorithms analyze data and then learn from it so that a decision based on a certain experience or criteria can be made. Machine language tools provide data protection as the information is only accessible to the key decision-makers. Deep learning is modeled like a human brain and therefore it operates using multiple layers of artificial networks and can process and use a very vast amount of data.

Dentifrices. Part 2: the evidence behind their formulation

The intricate formulations of modern dentifrices position them as one of the most sophisticated pharmaceutical products available today. Dental care professionals, tasked with providing evidence-based recommendations, encounter numerous challenges with this everyday product. This necessitates a thorough grasp of dentifrice formulations, familiarity with testing procedures, profound insights into (clinical) trials regarding proven efficacy and safety, and staying updated on current scientific literature. Additionally, recommendations must be tailored to integrate with each individual patient's oral health status, needs, and preferences. CPD/Clinical Relevance: Dentifrices are complex formulations, carefully prepared by the industry, which need to be proven effective in (clinical) trials, receive evidence-based recommendation from professionals, and be appreciated by end users.

Prospects and challenges of sensor materials: A comprehensive review

Sensor materials have become more important in several industries as they facilitate the development of advanced sensing technologies in the modern day. These materials, specifically engineered to transform physical, chemical, or biological stimuli into quantifiable signals, play a crucial role in gathering vital data for controlling, monitoring, and making informed decisions. It is essential to comprehend the obstacles and prospects linked to sensor materials, given the escalating demand for sensor systems that are both efficient and versatile. The sensing qualities of a material refer to its capacity to detect and quantify alterations in its surroundings. These properties encompass a range of approaches, including optical, chemical, piezoelectric, capacitive, and resistive interactions. Although these materials are utilized in various industries such as transportation, medicine, agriculture, industrial operations, and environmental monitoring, persistent issues are still related to improved reaction speed, selectivity, and sensitivity. Nevertheless, the outlook for sensor materials seems optimistic, as current research and advancements are anticipated to result in materials that exhibit enhanced performance, durability, and energy economy. Developing nanomaterials and sophisticated production processes facilitates the potential for creating highly selective and sensitive sensors with new functionalities. This advancement contributes to the growth of the Internet of Things (IoT) and its applications in massive data collection, leading to enhanced automation and decision-making capabilities. This review article examines the recent advancements, applications, and research in sensor materials while also discussing the obstacles they encounter and the potential opportunities that enable them to significantly impact multiple industries and society.