We aim to map the ESG patterns of emerging-market companies from 2018 to 2021 in order to determine whether the COVID-19 pandemic exerted any influence on sustainable corporate behavior. Thus, the ESG performances were assessed by applying the Kohonen neural network for clustering purposes at three main levels: i) ESG overall, including country and sectoral perspectives; ii) ESG thematic; and iii) ESG four-folded (stakeholder, perspective, management level, and focus strategic views). Our results show that emerging-market companies focus their ESG efforts on social and governance issues rather than on environmental. However, environmental, and social behavior differ more acutely than governance behavior across clusters. The ESG pillars country-level and eleven market-based economic sectors analysis corroborate the geographic and sector dependence of ESG performance. The thematic-level analysis indicate that operational activities and community issues received more attention, which suggests that emerging-market companies address distinct ESG topics according to their particularities and competitiveness. Furthermore, our empirical findings provide evidence that the ESG behavior of companies has changed over the course of the COVID-19 pandemic. Thus, our findings are relevant to policymakers involved in regulating ESG disclosure practices, investors focused on enhancing their sustainable investment strategies, and firms engaged in improving their ESG involvement.

Nutraceuticals are combination of nutrients and pharmaceuticals and these are derived from various plants, microbes and animals too. The food products that are considered as nutraceuticals are categorised based on the availability in the market. It is a medical approach to improve health and remedy for illness. Nowadays there is an increase in shift towards use of nutraceuticals as its usage provides preventive therapies to various chronic diseases. Various natural nutraceuticals are based on extracts from Ginger, turmeric, garlic, amla, cinnamon, aloe vera etc. A wide variety of therapeutic values are provided by them such as anti-inflammatory, antibacterial, antifungal properties, allergy relief, antidiabetic and cardiovascular problems. India is in its infancy stage but have many emerging companies that are trying to meet the demand of growing population. Overall ‘Nutraceuticals’ has been known as a new era of well being, in which the food industry has become a main player.

In this paper, we focus on the impact of financial liberalization on stability of emerging stock market. We identify crises in a group of Latin American (Argentina, Brazil and Chile) and Asian countries (Philippines, Korea, Taiwan and Thailand) during 1975–2005. This paper aims to apply the methodology of CMAX method. Our results indicate that liberalization triggers more unstable stock market in the short run and generate several crises. Still, liberalization seems to generate more stable financial markets in the long run. Financial liberalization does not increase the frequency of crises in emerging countries and at long-term, crises are less several.

The aim of this study was to determine the impact of information technology in management of risks in the capital market-listed company is in Tehran Stock Exchange. The purpose of the present study is an applied descriptive approach. The target population for the survey, companies that from 2009 to the first half of 2015 have been a member of the Tehran Stock Exchange, through Cochranʼs sample size of 140 companies, respectively. We used cluster sampling method. In order to collect data from two questionnaires: risk management questionnaire Foakeh (2013) has 38 items and a standard questionnaire Chanvyas (2006) has 40 items, the whole five-item Likert scale questionnaire is above has been used. Data gathered through the questionnaire, sign the application was 21spss. For inferential analysis of the variables and to analyze the data from different statistical tests and regression was used Kolmogorov-Smirnov test. The results showed that information technology on risk management and its dimensions (primary market risk, market risk and the risk of secondary non-financial) impact.

This study examines the effect of market risk on the financial performance of 31 non-financial companies listed on the Casablanca Stock Exchange (CSE) over the period 2000-2016. We utilize three alternative variables to assess financial performance, namely return on assets, return on equity and profit margin. Next, we use the degree of financial leverage, the book-to-market ratio, and the gearing ratio as market risk variables. Besides, we employ the pooled OLS model, the fixed effects model, the random-effects model, the difference GMM and the system GMM models. The results show that market risk indicators have a negative and significant influence on the companies' financial performance. The elasticities are greater following the book-to-market ratio compared to the degree of financial leverage and the gearing ratio, respectively. In most cases, the firm size, the tangibility ratio, and the cash holdings ratio have a positive effect on financial performance, whereas the firms' age, the debt-to-income ratio, stock turnover, and leverage hurt the performance of these non-financial companies. Therefore, decision-makers and managers should mitigate market risk through appropriate strategies of risk management, such as derivatives and insurance techniques.

Futures markets are mainly used as a tool for price discovery and for risk management on the spot markets and enable diversification for international portfolio investments. With this study we aim (1) to investigate the causality relationship between futures markets and spot market and (2) to examine the causality relationship between futures markets and spot markets in different countries. We are interested in both the futures markets - spot market relations and the interactions between the markets at international level. For variables we used the the BIST30 spot index and BIST30 futures contract representing the Borsa Istanbul market and the Dow-Jones 30 index and Dow-Jones 30 futures contract, which are the most important indices representing the US markets. Daily closing price data for the period between 2nd January, 2009 and 18th June, 2018 were analyzed using correlation, unit root test, causality test and regression equations. The results of the study show that the futures markets continue their price discovery role for both the spot markets and futures markets and are influential on other futures and spot markets at international level. These findings are important for investors wanting to invest in Turkey and in similarly considered emerging market economies. It will help investors take informed decisions by providing them with a more efficient price estimations utilizing the futures markets.

This paper analyzes the relationship between corporate social responsibility (CSR) and social impact within the oil industry in an emerging market (Peru). Following the emerging literature on the social impact field, and using the case study methodology, the findings show that the expected positive relationship is diverse depending on several factors. Specifically, the results reveal that companies must focus on community and environmental responsibility, together with stakeholders' involvement to achieve social impact. However, when companies are weak in any of the previous factors, then the social impact is only partially accepted or even withdrawn.

(1) As the craft beer industry continues to expand in Canada, understanding the regional differences between the Eastern and Western markets becomes pivotal for brewing ingredient companies seeking to penetrate or expand within these regions. This study aims to provide a comprehensive review of these two distinctive markets, focusing on economic, logistical, ingredient, and cultural differences. (2) The study primarily relies on secondary data from government, industry reports, and scholarly publications, providing a holistic view of the Canadian craft beer landscape. It further highlights the need to consider market distinctions between Canada and the United States. (3) Findings reveal that Western Canadian breweries, unlike their Eastern counterparts, operate under constrained storage space, prefer locally-sourced ingredients, and offer a distinct variety of beer styles catering to local tastes. The study further uncovers the regulatory and financial complexities of the Canadian market compared to the United States. (4) Based on these findings, this study provides strategic recommendations for brewing ingredient companies, emphasizing domestic logistics, local sourcing, product adaptation, educational support, and regulatory navigation, fostering success in the Canadian craft beer landscape.

With the economic recession and the deterioration of the ecological environment becoming more and more prominent in the world, the sustainable operation of enterprises is facing the most difficult choice in history. For each responsible enterprise, it is crucial to choose the market power expansive strategy that can improve the realistic viability or the technological innovation strategy that can improve the future development potential. This is of great significance to reduce the negative external effects of the corporate social environment and ensure their sustainable development. In this paper, we select the data of 18 large listed petrochemical companies from 2003 to 2018 as samples and construct a linear regression model for empirical analysis. Meanwhile, we put forward more practical business management strategies for the sustainable development of petrochemical enterprises in developing countries in further research.

The penetration of modern supermarkets is believed to be the cause of the declining role of traditional markets and street vendors in Indonesia. But the competition between state-promoted markets and traditional markets is rarely discussed. This investigation focuses on traditional markets as social institutions, which continuously have developed a variety of strategies in order to remain competitive in the midst of intense rivalry. Firstly, we will outline a theoretical understanding of the traditional markets positioning along the concepts of flexibility and market devices. Secondly, we empirically reflect the strategies of four traditional vegetable markets in the District of Malang, East Java Province, as case studies. We show that the traditional markets build flexibility without governmental support by: (1) specifying commodities, (2) segmenting customers, (3) managing the load time, (4) modifying transportation to operate more efficiently, and (5) minimizing transaction costs by leveraging social capital. We argue that traditional vegetable markets institutionally reduce the potential of transaction costs to be competitive and avoid problems of coordination by building social capital through networks. All in all, market institutions supported by market devices are flexibly capable of adapting to the pressures of both selfishness among actors and competition with other markets.

Our aim is at three feels: i) study safe haven properties of sectoral CDS; ii) study hedging effectiveness and measure the diversification benefits of introducing them in both Conventional and Islamic stock markets portfolios and iii) compare these results with VSTOXX, Gold and Bitcoin indices. To do this, we estimate time varying hedge ratio using (A)DCC and GOGARCH models and then deduce hedging effectiveness.. We follow the same methodology for each sub-period and each refit to test the effect of bubble crypto currency and COVID-19 pandemic on hedging effectiveness. Empirical results show the superiority of industrial CDS sectoral index to hedge both conventional and Islamic stock markets whether long or short term despite that their performances were reduced slightly during the second and third periods. VSTOXX and Others sectoral CDS indices offers Hedging performances that are generally better than Bitcoin and gold.

The new regulation was introduced to the franchise market of South Korea in that an applicant who wants to be a franchiser must set up direct retail stores and run them for at least one year before recruiting franchisees. Considering the purpose of the regulation, it is inferred that once franchisers run their own stores, their franchisees would be better off than otherwise. This paper addresses one reason that the Korea Fair Trade Commission has no choice but to introduce the regulation. Along the line, this paper investigates whether franchisees would have the more likelihood to make profit in the case of that franchisers operate their own stores. The result demonstrates that this case could be true since the operation of franchiser owned stores could be helpful in reducing cost of franchisees.

We examine the use of deep learning (neural networks) to predict the movement of the S&P 500 Index using past returns of all the stocks in the index. Our analysis finds that the future direction of the S&P 500 index can be weakly predicted by the prior movements of the underlying stocks in the index. Decomposition of the prediction error indicates that most of the lack of predictability comes from randomness and only a little from nonstationarity. We believe this is the first test of S&P500 market efficiency that uses a very large information set, and it extends the domain of weak-form market efficiency tests.

The widespread integration and growing dependence among currency, stock and commodity markets make these markets often very vulnerable to shocks and at risk of collapse at the same time. As a result, these trends threaten the sustainability of the entire financial system. In this study, we explore the spillovers and nonlinear dependences between the seven major foreign ex-change rates, crude oil and gold prices, a global stock price index, and oil and stock implied volatility indices as proxy variables for global risk factors by em-ploying directional spillover network approach. We also use multi-scale de-composition method and nonlinear causality test between these variables to capture multi-level relationships at short and long horizons. Major findings are summarized as follows. First, from the multi-scale decomposition analysis, we identify that Granger causality test results and the direction and strength of return spillovers change with the level of decomposition. Second, the results of nonlinear causality tests show variation in both the significance and direction of Granger causality relationships between the decomposed currency and other series at different timescales, especially for the decomposed oil, gold, and OVX series. Third, the measured directional spillover indices identify the EUR as the largest contributor of connectedness to the other series. The central role of the EUR is a net transmitter of connectedness to gold, oil, the GBP, JPY, and CHF.

Market uncertainty has a significant impact on market performance. Previous studies put much efforts in investigations on market uncertainty related to information asymmetry and risk. However, they have neglected the uncertainty inherent in market transactions, which is also an important aspect of market performance, besides quantity of transactions and market efficiency. In this paper, we put forward the concept of transaction entropy to measure the market uncertainty and see how it changes with price. The definition of transaction entropy is the ratio of total information entropy of all traders to quantity of transactions, reflecting the level of uncertainty in making transactions. And the transaction entropy is the lowest at equilibrium, it will be decreasing in a shortage market, and increasing in a surplus market. Additionally, we make a comparison of total entropy of the centralized market with that of the decentralized market, revealing that the price filtering mechanism could effectively reduce market uncertainty. Overall, the introduction of transaction entropy enriches our understanding of market uncertainty and facilitates a more comprehensive assessment of market performance.

For a long-only active equity manager (or investor), the ability to hedge the downside risk before a significant price correction is a valuable skill. The authors proposed constructing a signal that provides timing information for a manager to hedge the downside risk. This systematic signal can help a manager put on a hedge before the price corrections of the dot com bubble in 2000 and the global financial crisis in 2008. The signal is constructed for each GICS sector index in the S&P 500. When a sector’s PE indicates a high valuation and, at the same time, if the high valuation sector’s correlations with some other sectors are out of their historical norm, then these two conditions contribute a timing signal for the significant price swing of the index during the following six months. After observing the timing signal, managers can benefit significantly by hedging the downside risk. The signal can also be interpreted as the beginning of a high volatility regime for a sector.

With the rise of internet technology and the growth of mobile communications, the global economy has undergone a significant transformation, shifting towards digital and soft markets. As a result, great efforts have been made to establish virtual marketplaces that provide customers with an exceptional shopping experience. One crucial aspect of this new paradigm is marketing, which has led to the emergence of a new stage known as E-marketing. In E-marketing, understanding customer behavior is of utmost importance. Marketing teams and companies are eager to gain insights into how different customer segments react to their products. Marketing strategies are now developed based on customer information such as financial status, location, age, gender, and more. As a result, the abundance of customer data generated by these new commerce technologies has surpassed the capabilities of traditional data analysis methods. To extract valuable knowledge from this vast amount of data, data mining technologies have come into play. Techniques such as clustering, classification, and prediction are utilized to mine marketing data and uncover hidden patterns and trends. The impact of data mining on E-marketing has been the subject of analysis in this study. A questionnaire-based review was conducted to collect the necessary data, which was then analyzed using SPSS 23 software. The study's results demonstrate that data mining can significantly enhance the performance of E-marketing by providing intelligent and efficient predictions of customer behaviour. Moreover, this technology offers similar advantages for end-customers as well. By leveraging the power of data mining, companies can gain valuable insights, tailor their marketing efforts, and ultimately provide better products and services to their customers in the digital marketplace.

Alfalfa (Medicago sativa L.) is one of the most important forage crops in the world. In Bolivia it is cultivated in different parts of the High Andes and in the Interandean Valleys. The species is affected by several fungal diseases which reduce production, but before 2016 hardly any mention had been made of virus disease in the region. The aims of the present work were: 1) to describe the symptomology of this apparent viral disease, and ii) determine its effects on the yield of different alfalfa cultivars available from the CIF-UMSS. In 2016, a plot was established at Tiquipaya (Dept. of Cochabamba) (altitude 2480 m) was planted with 12 alfalfa cultivars. Disease incidence values were estimated and the area under the disease progress curves (AUDPC) calculated. The disease progress curves themselves were analyzed using logit functions for polycyclic diseases, and yields were determined. Disease symptoms included deformation of the folioles, thickened veins, the presence of vein enations and papillae on the abaxial leaves, reduced plant size - all symptoms of infection apparently caused by Alfalfa Dwarf Virus. The different cultivars returned different incidence values. They also returned different apparent infection rates ranging from 0.072/day for Cóndor, to 0.113/day for Tamborada. The different cultivars returned different dry weight yields, with yields inversely related to the AUDPC. In conclusion, based on the foliar symptoms registered, the viral disease is associated with the Alfalfa Dwarf Virus. The twelve cultivars evaluated presented different incidence levels of the viral disease.

With the term neuroinflammation has defined the typical inflammatory response of the brain closely related to the onset of many neurological diseases. Neuroinflammation is well known, but its mechanisms and pathways are not entirely comprehended. Currently, some progress has been achieved through many efforts and research. Consequently, new cellular and molecular mecha-nisms, diverse from conventional ones, are emerging. In listing some of those that will be the sub-ject of our description and discussion, essential are the important role of peripheral and infiltrated monocytes and clonotypic cells, alterations in gut/brain axis, dysregulation of the apelinergic sys-tem, as well as changes in the endothelial glycocalyx of blood-brain barrier, variation in expres-sion of some genes and levels of the encoding molecules by microRNAs (miRNAs), or other epige-netic factors and distinctive transcriptional factors, as well as the role of autophagy, ferroptosis, sex differences and modifications in the circadian cycle. Such mentioned mechanisms can add significant pieces in understanding the complex etiological puzzle of neuroinflammation. In addi-tion, they could represent biomarkers and targets of neurodegenerative diseases, in increase in our old populations.

Energy resources are important sources of social and economic development, human survival and security. However, energy resources are objective and scarce, especially the fossil energy, such as coal, oil, natural gas, etc. Human survival environment is increasingly damaged, and the condition of energy is also gradually becoming deficient, so it is necessary to develop new energy resources to meet the increasing demand of material civilization. Solar energy can meet the needs of human development in the future as a kind of clean resource and it has been concerned by all countries in the world. We analyzed the effectiveness of subsidies to the PV industry of both the price and R&D by the spatial econometric model. In some region, the production capacity of photovoltaic industry has shown a significant spatial agglomeration situation in China since 2012. At the same time, benchmarking price and R&D subsidies played a positive incentive to the photovoltaic industry production capacity. It is a certain degree of inverse correlation between the scale of policy subsidies and the resource endowment of solar resources. Therefore, the countermeasures should be considered from the aspects of institutions, industry, technology and public financial policies.

The current study explores the problem of illiquidity in the corporate bond market and examines a broad set of liquidity proxies through empirical investigation. Purpose: The purpose of this paper is to give solution to the global issue of illiquidity in the corporate bond market. The problem is identified by many researchers and this paper attempts to find out the viable solution of the "fungibility route" as an alternative to the "liquidity route". Design/ Methodology: An Analysis of a sample size of 2,34,772 trade data of corporate bonds and a sample size of 2,00,607 trade data of G-securities is done to identify the problem. Findings / Solution proposed: A mathematical model based on credit risk differential and sensitivity differential is proposed to find out the fair value at which an illiquid bond can be swapped by a liquid bond. To arrive at the fair value of the illiquid bond, we have calculated risk adjusted discount rate using modified duration and credit risk differential. With our solution, it is possible to enhance the liquidity of the bond not directly but through fungibility route. Originality: the research is first of its kind in which solution is given to the global problem of corporate bond illiquidity. To execute the trade in the fungibility route, proposed parties involved are the Fungibility platform, the initiator, and the bidder. The derived fair value would facilitate trade and serve as an exit strategy for illiquid bond holders worldwide.

Does the choice of proxy for stock market development matter? This paper suggests that the growth effect of stock market development is sensitive to the choice of proxy and using alternative financial development indicators have practically no influence on the results. We found that using either the stock market capitalization to GDP ratio or the stock market returns; have a positive and significant effect on growth. However, we cannot make same conclusion when one uses either the ratio of total value of trades on the major stock exchanges to GDP or stock market turnover ratio to proxy for stock market development as the coefficient on these variables were found to be statistically insignificant. The indexes extracted from principal component analysis confirm the sensitivity of the effect to the choice of proxy. This finding suggest that stock market development is a conceptual terms, thus, representing it with single indicators make it impossible to identify which stock market development indicators have a significant positive growth effects.

Japanese encephalitis virus is a mosquito-borne member of the Flaviviridae family. JEV is the leading cause of viral encephalitis in Asia and is characterized by encephalitis, high lethality and neurological sequelae in survivors. The virus also causes severe disease in swine, which are an amplifying host in the transmission cycle, and in horses. US agricultural authorities have recently recognized the threat to the swine industry and initiated preparedness activities. Other mosquito-borne viruses exotic to the Western Hemisphere have been introduced and established in in recent years, including West Nile, Zika, and chikungunya viruses, and JEV has recently invaded continental Australia for the first time. These events amply illustrate the potential threat of JEV to US health security. Susceptible indigenous mosquito vectors, birds, feral and domestic pigs, and possibly bats, constitute the receptive ecological ingredients for spread of JEV in the US. Fortunately, unlike the other virus invaders mentioned above, an inactivated whole virus JE vaccine (IXIARO®) has been approved by the US Food & Drug Administration for human use in advance of a public health emergency, but there is no veterinary vaccine. This paper describes the risks and potential consequences of introduction of JEV in the US, the need to integrate planning for such an event in public health policy and the requirement for additional countermeasures, including antiviral drugs and an improved single dose vaccine that elicits durable immunity in both humans and livestock.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

Monkeypox is a rare disease which is rising nowadays in different countries since the first case in the UK was diagnosed on May 6, 2022, by the United Kingdom (UK) Health Security Agency. Then more than 12,500 cases were identified in over 68 countries up to July 18, 2022. In endemic areas, the monkeypox virus (MPXV) is commonly transmitted through zoonosis, while in non-endemic regions, it is spread through human-to-human transmission. Symptoms can include flu-like symptoms, rash, or sores in hands, feet, genitalia, or anus. In addition, people who did not take the smallpox vaccine were more liable to be affected than others. The exact pathogenesis and mechanisms are still unclear; however, most identified cases are reported in men who have sex with other men (MSM). According to the CDC, transmission can happen with any sexual or non-sexual contact with the infected person. However, a recent pooled meta-analysis reported that sexual contact is involved in more than 91% of the cases. Also, it is the first time that semen analysis for many patients has shown positive monkeypox virus DNA. Therefore, in this review, we will describe transmission methods for MPXV while focusing mainly on potential sexual transmission and associated sexually transmitted infections. We will also highlight the preventive measures that can limit the spread of the diseases in this regard.

This comprehensive review delves into gold market business management, covering historical perspectives, market dynamics, mining models, investment strategies, technology, regulations, global trends, and sustainability. Starting with a historical overview, it traces the gold market's evolution and analyzes supply-demand dynamics, price fluctuations, and geopolitical influences. The article scrutinizes gold mining models, evaluating environmental and social responsibilities, and explores financial management strategies, emphasizing risk and gold's role in portfolios. Examining technology's role, it highlights innovations in exploration, mining, and processing for improved efficiency and sustainability. The regulatory landscape analysis encompasses compliance challenges, environmental regulations, and ethical considerations, emphasizing global impacts. Global market trends are explored, identifying potential opportunities and challenges, offering strategic insights. The review concludes by evaluating sustainability practices, emphasizing environmental conservation, community engagement, and ethical sourcing.

This research article focused on discovering appropriate liquidity risk concerns in the financial Sector. Primarily, it deals with the appropriate liquidity factors that affect financial performance services pertained to several liquidity crises and the respective liquidity measures. Liquidity is considered the primary constraint. The Liquidity Ratios are the defective condition of calculating the financial performance services and their respective status. For fulfilling this performance service status prediction, this research use calculation for consistency index procedure. Liquidity index-based predictions have collaborated concerning the price movement in the stock market. The Liquidity will affect the trading and market transparency whenever the price moment varies. To control this trading and not market transparency of liquidity index be employed the greedy approach for estimating the most factor affected by the liquid index. Hence, this research elaborates on the greedy approach today with 25 essential financial factors. Each Panther will have combined with the tractor-confirmed liquidity crisis whenever the factors of liquidity crisis are combined with the actual financial factor, the minimum and maximum Degree of matching are calculated. This calculation determines the factors that affected the Liquidity concerning their exact, Plugin, subsume, and fail condition. Eventually, the search concludes the determination of factors affecting Liquidity concerning the actual finance factor and liquidity crisis. Finally, the result was concluded with the Degree of matching and their efficiency of finding liquidity factors with a successful reasonable result. Based on the Degree of matching result, this research found the actual reason for Liquidity with the help of various financial factors

The deregulated markets have replaced the traditional way of trading electricity from the producers to the consumer, via government-owned organizations and regulated tariffs. Nowadays, electricity prices are determined by the offer-demand mechanism and consumers can negotiate tariffs with their supplier of choice. For classic wholesale suppliers, the tariffs are a result of the transactions performed on the wholesale market and the energy mix available in certain geographical regions. In parallel with becoming eligible and participating in retail electricity markets, the consumers use increasingly local generation sources based mostly on renewable energy technologies such as PV panels, and become prosumers. They want to be able to sell back to the market the generation surplus, in order to obtain the maximum benefits from their initial investment. Currently, several trading mechanisms for prosumers are available, ranging from the simplest, selling back the surplus to an aggregator at fixed tariffs, to more complex market schemes. This paper proposed a two-tier local market model for prosumers and consumers connected in microgrids, based on the blockchain technologies and other technologies and concepts such as remote sensing, smart grids, crowdsourcing and energy poverty.

The deregulated markets have replaced the traditional way of trading electricity from the producers to the consumer, via government-owned organizations and regulated tariffs. Nowadays, electricity prices are determined by the offer-demand mechanism and consumers can negotiate tariffs with their supplier of choice. For classic wholesale suppliers, the tariffs are a result of the transactions performed on the wholesale market and the energy mix available in certain geographical regions. In parallel with becoming eligible and participating in retail electricity markets, the consumers use increasingly local generation sources based mostly on renewable energy technologies such as PV panels, and become prosumers. They want to be able to sell back to the market the generation surplus, in order to obtain the maximum benefits from their initial investment. Currently, several trading mechanisms for prosumers are available, ranging from the simplest, selling back the surplus to an aggregator at fixed tariffs, to more complex market schemes. This paper proposed a two-tier local market model for prosumers and consumers connected in microgrids, based on the blockchain technologies and other technologies and concepts such as remote sensing, smart grids, crowdsourcing and energy poverty.

This paper examines the transformation of the Ukrainian stock market by analyzing daily returns from the PFTS stock index spanning 1995-2022. Segmented into sub-periods, it tests the hypothesis that the market's efficiency has grown over time. Various data properties, including persistence, volatility, normality, and resistance to anomalies, are explored using different statistical techniques and methods. Volatility, indicated by standard deviation, exhibits a general decreasing trend, suggesting a shift towards a more efficient market. Returns show no significant differences across sub-periods, except for 2005-2007. R/S analysis indicates the decrease of persistence in the market: a trend towards increased efficiency. Normality tests support a normal distribution of daily returns throughout sub-periods. An analysis of anomalies reveals the market's resilience to day-of-the-week effects, with no specific trends observed. The results suggest the absence of serious changes in data properties in the Ukrainian stock market over the time, means evolutionary processes over 25 years can’t be clearly observed. Reforms and changes have had limited impact, justifying continued reform for the market's evolution.

Climate change, the scarcity of fossil fuels, technical advances in clean energy, and the volatility of crude oil prices are just a few of the factors that have prompted the world to recognize clean energy as a viable alternative to dirty energy. As part of the Paris Climate Accord of 2015, many countries agreed to change their economies to be more sensitive to climate change. Due to this Accord, which increased interest from investors and decision-makers, investments in clean energy companies have benefited [1,2]. Clean energy stocks, which are a part of the larger world of tradable reserves, might experience pricing inefficiencies. In this paper, we investigate the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets like gold, crude oil, and natural gas between January 1, 2018, and March 9, 2023, which covers periods of low volatility and financial instability (2020 and 2022 events). To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings demonstrated that both periods exhibit severe multifractal and significant asymmetry, indicating that the price indices under study are not at all efficient.

The energy matrix worldwide has been going through difficulties in its discussions - such as irregular exploration, inefficient public policies, and arbitrariness concerning diplomatic and political definitions of those involved in this market. This work's general objective consists in analyzing associations and statistical inferences of the largest world oil producers, assimilating the contributions and singularities of this market from 1993 to 2020. Based on the Organization of the Petroleum Exporting Countries (OPEC), it was possible to identify the possible inferences and contributions of the ten largest oil producers in the world in more than two decades using statistical analysis through correlation, regression, and statistical analysis of variables. According to the research and the literature on the area, the oil market proposes support to its discussions, mainly in its productive approaches. It is possible to identify this market as a solid link to geopolitical actions, distributing the possibilities through economic bias and socio-cultural and historical factors on a global level.

The study tries to find out the impact of investors demographic variables on the return from the stock market. The data has been collected from the brokerage and Marchant banks for individual investors investments, return and demographic characteristics. The research covers the period from 2009 to 2021 and have a decade long enough to identify the trend. The structural break in the data also been adjusted to avoid any kind of endogeneity. The regression results suggest that demographic variables affect the investment pattern and beta return for the investors. the demographic variables such as education, location and experience have positive links with the beta whereas age and income show negative association. The education, income and experience variables are also found to be significant in the empirical analysis.

Climate adaptation is a major challenge. Chasing the sufficient amount of hay is getting in higher priority. Distant mass hay producers give favourable offers despite long distances. Quality is also gaining position and indicators like RFQ (Relative Forage Quality) is highlighting the marketing language. Hay market as we knew no longer exists in Hungary. Most farmers produce their own hay and do not spend extra cents to buy bales. Climate change however, force them to adapt and store more bales for the future. Horse owners and dairy farmers are the main driver to convince hay producers to provide high quality forage. We gathered Hungarian regional hay-price information and evaluated the trends in this sector. The demand-driven hay-price is in contradiction with premium quality timothy grass hay.

Many studies in the current literature annotate patterns in stock prices and use computer vision models to learn and recognize these patterns from stock price-action chart images. Additionally, current literature also use Long Short-Term Memory Networks to predict prices from continuous dollar amount data. In this study, we combine the two techniques. We annotate the consolidation breakouts for a given stock price data, and we use continuous stock price data to predict consolidation breakouts. Unlike computer vision models that look at the image of a stock price action, we explore using the convolution operation on raw dollar values to predict consolidation breakouts under a supervised learning problem setting. Unlike LSTMs that predict stock prices given continuous stock data, we use the continuous stock data to classify a given price window as breakout or not. Finally, we do a regularization study to see the effect of L₁, L₂, and Elastic Net regularization. We hope that combining regression and classification shed more light on stock market prediction studies.

This research discusses the business model challenges faced by cag aggregator platform models in developing countries. Technology-based platforms have been disrupting traditional businesses and rewriting the rules of the game. Ola cabs has been instrumental in shaping the Indian platform business landscape in a big way. Using case methodology the author analyses the situation and business model to present the salient features of Ola’s model. However, this paper also puts the spotlight on the inherent challenges in this model and warns the need for continuous business model innovation and service quality.

Fibromyalgia is a complex and often misunderstood chronic pain disorder. It is characterized by widespread musculoskeletal pain, fatigue, and heightened sensitivity, and has evolved in diag-nostic criteria and understanding over the years. Initially met with skepticism, fibromyalgia is now recognized as a global health concern affecting millions of people, with a prevalence trans-cending demographic boundaries. The clinical features and diagnosis of fibromyalgia encompass a range of symptoms beyond pain, including sleep disturbances and cognitive difficulties. The study emphasizes the importance of a comprehensive evaluation for accurate diagnosis, considering the shift from tender point reliance to a more holistic approach. Etiology and pathophysiology involve genetic predisposition, neurotransmitter dysregulation, central sensitization, and immune system involvement. Risk factors such as gender, age, family history, and comorbid conditions contribute to susceptibility. The impact on quality of life is profound, affecting physical and social aspects, often accompanied by mood disorders. Management approaches include pharmacological interventions, non-pharmacological therapies, lifestyle modifications, and alternative treatments. The study also delves into emerging research, exploring advances in neurobiological understanding, brain imaging, genetic markers, glutamate modulation, cannabinoids, gut microbiome, and digital health tools for fibromyalgia manage-ment. Overall, this study provides a nuanced and up-to-date overview of the complexities sur-rounding fibromyalgia, aiming to enhance understanding and support for individuals grappling with this challenging condition.

Metformin is an oral antidiabetic agent with antimicrobial properties, excreted in an active and unmetabolized form. Like some non-antibiotic drugs, subinhibitory concentrations of metformin may contribute to the expression of microbial resistance in wild-type strains. This work aimed to evaluate the biofilm formation of Pseudomonas aeruginosa TGC04 exposed to 100 and 200 µg/mL of metformin, varying the Chemical Oxygen Demand (COD) and flow regime. Biofilms were quantified after 2 and 24 hours, observing reductions and increases in biofilm growth around 13 and 64%, respectively. The greatest biofilm growth occurred in cells exposed to 200 µg/mL of metformin. Both the flow regime and COD concentration were important for the development of the biofilm, whose cells were mostly weakly to moderately adhered. The study provides evidence that in polluted aquatic systems with turbulent regimes, the inhibitory concentration of metformin promoted the least disturbances to the biofilm.

Emerging infectious disease threats are becoming more frequent due to various social, political and geographical pressures including increased human-animal contact, global trade, transportation and changing climate conditions. As a result, the threat that emerging agents can be spread by blood contact or transfusion of blood products also becomes increasingly problematic. Blood transfusion is essential in treating patients with anemia, blood loss, and other medical conditions. However, these lifesaving components can become a vector for spreading diseases, particularly to vulnerable populations. New methods have been implemented on a global basis for prevention of transfusion transmission via plasma, platelet, and whole blood products. Implementing proactive pathogen reduction methods can significantly reduce the likelihood of disease transmission via blood transfusion, even for newly emerging agents whose transmissibility and susceptibility are still being evaluated as they emerge. In this review, we consider the Mirasol PRT system for blood safety which is based on a photochemical method involving Riboflavin and UV light. We provide examples of how emerging threats such as Ebola, SARS-CoV-2, Hepatitis E, monkeypox and other agents have been evaluated in real time regarding effectiveness of this method for reducing the likelihood of disease transmission via transfusion. Keywords: transfusion; blood; pathogen reduction; emerging infectious diseases.

The global vaccination programme against smallpox (SPX) led to its successful eradication and averted millions of deaths. Monkeypox (MPX) is a close relative of SPX. Due to their antigenic similarity, SPX vaccines cross-protect against MPX. However, over 70% of people living today were never vaccinated. Symptoms of MPX infection include fever, head and muscle ache, lymphadenopathy and a characteristic rash that develops into papules, vesicles and pustules which eventually scab over and heal. MPX is less often fatal (case fatality rates range from less than 1% to up to 11%) than SPX (up to 30%). MPX is endemic in sub-Saharan Africa, infecting wild animals and causing zoonotic outbreaks. Exotic animal trade and international travel combined with the increasing susceptibility of the human population due to halted vaccination facilitated the spread of MPX to new areas. The ongoing outbreak with over 6500 confirmed cases in >50 countries between May and July 2022 shows that MPX can significantly spread between people, and may thus become a serious threat to public health with global consequences. Here, we summarize the current knowledge about this re-emerging virus, discuss available strategies to limit its spread and pathogenicity and evaluate its risk to the human population.

Ticks drive a wide diversity of pathogens to a great variety of hosts, including humans. We conducted a tick surveillance study in northwestern Spain between 2014 and 2019. Ticks were removed from people and were identified. Tick numbers, species, development stages, evolution over time, seasonal and geographical distribution, and epidemiological characteristics of people bitten by ticks were studied. We collected ticks from 8143 people. Nymphs of Ixodes ricinus were the most frequently collected. Rhipicephalus bursa, Rhipicephalus sanguineus sensu lato (s.l), Hyalomma marginatum, Hyalomma lusitanicum, Dermacentor marginatus, Dermacentor reticulatus and Haemaphysalis punctata were also found, with adults as the main stage. Hyalomma spp. and R. bursa have been progressively increasing over time. Although bites occurred throughout the year, the highest number of incidents were reported from April to July. The distribution patterns of the tick species were different between the north and the south of the region, which was related to cases detected in humans of the pathogens they carried. Adult men were more likely to be bitten by ticks than women. Ticks were most frequently removed from adults from the lower limbs, while for children they were mainly attached to the head. Epidemiological surveillance is essential given the increase in tick populations in recent years, mainly of species potentially carrying pathogens causing emerging diseases in Spain, such as the Crimean Congo Hemorraghic Fever (CCFH).

All fundamental Planck scale symmetries are restored on a global level when a new charge is postulated in a finite, closed, Euclidean discrete space. Gravity emerges as a residual effect of the electromagnetic force in this scenario, resulting in a deterministic toy universe driven by a single input parameter. The model is developed using a constructive approach. Randomness is identified using a Chaintin argument. Aleph0 definite value is tied to the size of the universe. This is not an interpretation of Quantum Mechanics, but a deeper attempt to describe nature.

All fundamental Planck scale symmetries are restored on a global level when a new charge is postulated in a finite, closed, Euclidean discrete space. Gravity emerges as a residual effect of the electromagnetic force in this scenario, resulting in a deterministic toy universe driven by a single input parameter. Randomness is identified using a Chaintin argument. Aleph0 definite value is tied to the size of the universe. This is not an interpretation of Quantum Mechanics, but a deeper attempt to describe nature.

The COVID-19 pandemic and increased rates of documented Emerging Infectious Diseases (EIDs) in human populations over the last century have drawn attention on understanding pathogens spill over to humans and their zoonotic origin. In this paper we argue that we need to change the thinking about the fundamental cause of zoonoses. Our premise is that deforestation is the primary cause of EIDs events and that, to prevent future pandemics, it needs to be addressed without further delays. Therefore, we review recent trends of proximate and underlying determinants of deforestation, forest degradation and related biodiversity losses while seeking to clarify their links to the determinants of EIDs events. Acknowledging the magnitude of the challenge, we propose responses to stop global deforestation from a trans-disciplinary, intersectoral perspective led by indigenous people. While we envisage that stopping deforestation is the most important approach with long term direct and indirect effects on human, animal and plants health, providing climate changes mitigation and preventing otherwise difficult to predict EID events, we argue that such an initiative may usefully be complemented by reducing contacts between humans and wildlife animals and regulating rather than banning markets where wild animals are sold alive.Finally, we discuss transformative changes to improve planetary-wide forests preservation, soil, plants, animal, and human protection, together with a further understanding of EIDs transmission dynamics, public health veterinary and human disease surveillance, for improved global collective preparedness and action for the management of zoonotic EIDs.

This review analyzes the synthesis and characterization of biomass-derived carbons for adsorption of emerging contaminants from water. The study begins with the definition and different types of emerging contaminants more often founded in water streams and the different technologies available for their removal including adsorption. It also describes the biomass sources that could be used for the synthesis of biochars and activated carbons. The characterization of the adsorbents and the different approaches that could be employed for the study of the adsorption processes are also detailed. Finally, the work reviews in detail some studies of the literature focused on the adsorption of emerging contaminants on biochars and activated carbons synthesized from biomass precursors.

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.

The driving force behind adopting the idea of ​​sustainable development are producers and retailers. Unfortunately, when preparing their product range for consumers, many of them still only pay attention to the size of the customers’ earnings, how often they shop and how much they buy when shopping. In consumer segmentation, sustainable values ​​that consumers apply when making their purchasing decisions are rarely taken into account. The aim of this article is to show that values ​​such as environmental protection, the ethical behaviour of producers, fair trade or maximising the utility function of consumption are so important in the purchasing process in the coffee market that they can be used as segmentation variables. The Polish coffee market was selected to carry out segmentation taking into account the consumers' sustainable values. The main source of the article is the results of a standardized online survey conducted on a nationwide sample of 800 coffee consumers in July 2018. Multi-dimensional analyses such as extrapolative factor analysis (EFA) and cluster analysis (CA) were used to describe the obtained results. As a result, six segments of coffee consumers were identified and described: “responsible, aspiring to be connoisseurs”, “loyal coffee enthusiasts”, “pragmatic users”, “coffee laypersons”, “sophisticated connoisseurs”, “consumerists, connoisseurs, but not at any price”. Among the identified segments, the sustainable consumption values ​​most often mentioned refer to "responsible, aspiring to be connoisseurs", and the least often - ”consumerists, connoisseurs, but not at any price”. The conclusions presented in the last part of the article may be used by manufacturing and trade enterprises, operating on the coffee market, in order to respond to the identified needs and expectations of consumers and by governmental and social organisations so as to determine the directions of pro-ecological education of consumers.

Due to various industrial developments and artificial inputs, there are emerging environmental contaminats(ECs) of serious concern in a wide range of environmental media. With recent advancements in scientific knowledge and industrial technology, the definition of emerging environmental contaminats has expanded. Among them, emerging contaminants are typically present in trace amounts and pose serious ecological risks and potential hazards to human health, animals and plants, with cumulative effects on organisms. However, Traditional treatment techniques have proven ineffective in eliminating and preventing subsequent environmental problems from new pollutants such as microplastics, antibiotics and fluorocarbons. Consequently, extensive research has been conducted to address these issues. Effective removal methods prioritize not only removal efficiency, but also environmental friendliness and regenerative capacity. The purpose of this paper is to summarize the sources, forms of presence, environmental and human health hazards, and removal technologies of ECs, and to provide various examples of different sources.

Emerging infectious diseases (EIDs) continue to be a problem all across the world, but in certain areas the threat is greater than in others. The detection of new diseases will aid in the focus of surveillance efforts. Specifically, identifying a "patient zero" is critical step to help limit further transmission. In fact, several factors have been found to contribute to emerging infectious diseases emergence and transmission. Antigenic drift is an important factor that affects vaccine effectiveness and it is important for scientists and healthcare providers alike to understand how this process works in order to ensure that people receive effective vaccinations against infectious diseases. However, recent advances in biotechnology, immunology and artificial intelligence have enabled us to make progress in diagnosis, treatment, prevention and control of infectious diseases. The fight against infectious diseases will always be ongoing, but the advancement of bioscience offers a promising outlook for the near future. In the last two decades, several high impact zoonotic disease outbreaks have been linked to bat-borne viruses. These include SARS coronavirus, Hendra virus and Nipah virus. In addition, it has been suspected that ebolaviruses and MERS coronavirus are also linked to bats. It is being increasingly accepted that bats are potential reservoirs of a large number of known and unknown viruses, many of which could spillover into animal and human populations. In this article, we discuss the potential risk factors that contribute in emerging infectious diseases. Also, we discuss the management of disease prevention and control.

Influenza A viruses (IAV) are still a cause of concern for public health and veterinary services worldwide. With (-) RNA-segmented genome architecture, influenza viruses are prone to reassortment and can generate a great variety of strains, some capable of crossing interspecies barriers. The latest 2009 pandemic and numerous reports of zoonotic infections worldwide show that these capabilities cannot be underestimated. Seasonal IAV strains continuously spread from humans to pigs, leading to multiple reassortation events with strains endemic to swine. Due to high adaptability to human, reassortant strain based on “human-like” genes could potentially be a carrier of avian origin segments responsible for high virulence, hence become next pandemic strain with unseen pathogenicity. We must foresee this kind of event, paying close attention to the surveillance of common human-animal interfaces. The rapid evolution of sequencing methods has provided a fast and cost-efficient way to assess the genetic diversity of IAV. In this study, we investigated the genetic diversity of swine influenza viruses (swIAVs) collected from Polish farms. A total of 376 samples were collected from 11 farms. The infection was confirmed in 112 cases. The isolates were subjected to next-generation sequencing (NGS), resulting in 93 full genome sequences. Phylogenetic analysis classified 59 isolates as genotype T (H1avN2g) and 34 isolates as genotype P (H1pdmN1pdm), all of which had an internal gene cassette (IGC) derived from the H1N1pdm09-like strain. These data are consistent with evolutionary trends in European swIAVs. The applied methodology proved to be useful in monitoring the genetic diversity of IAV at the human-animal interface.

Parvovirus infections have been well known for around 100 years in domestic carnivores. However, the use of molecular assays and metagenomic approaches for virus discovery and characterization has led to the detection of novel parvovirus species and/or variants in dog. Although some evidence suggests that these emerging canine parvoviruses may act as primary causative agents or as synergistic pathogens in the diseases of domestic carnivores, several aspects regarding epidemiology and virus-host interaction remain to be elucidated.

The links between mindfulness, savoring positive experiences, and depressive symptoms have been well-established in the literature. Nevertheless, little has been done to disentangle the prospective relations among these constructs. Clarifying the longitudinal relations is crucial, as it enables researchers and practitioners to discern potential trajectories of mental health interventions. In this study, 180 emerging adults between 18 and 27 years old were recruited twice at 3 months apart to complete self-reported measures including mindfulness, savoring positive experiences, and depressive symptoms. Cross-lagged path analysis indicated that savoring the moment was predictive of mindfulness three months later, whereas depressive symptoms were predictive of both mindfulness and savoring the moment three months later, above and beyond the effects of age, gender, and family income. Additionally, mindfulness, savoring positive experiences, and depressive symptoms were significantly correlated at baseline. The present study evidenced short-term inversed effects of depressive symptoms on mindfulness and savoring the moment, as well as a positive effect of savoring the moment on mindfulness. Hence, interventions gearing towards symptom reduction of depression are likely to carry concurrent and prospective benefits of psychological functioning, namely the ability to be present in the moment and to savor. Taken together, reducing depressive symptoms may be crucial in fostering psychological well-being.

The last few years have witnessed an explosion of research on Sustainable development. Most of this research is concentrated on the developed countries related to the issues not compatible with developing countries. This paper fills the gap and reviews the literature related to developing and emerging economies and their environmental and social constraints under Renewable energy and sustainable development (RESD). It also investigates how RESD can be implemented in the presence of serious issues pertaining to population increase, shortage of energy supply, lack of transportation, shortage of clean water, less food production and bad environmental systems and these are coupled with war, and hunger and political instability. The main contribution of this paper is to present extensive discussion in the context of hypotheses of economic growth and its association with energy consumption, and renewable energy options for sustainable development.

Three decades have now passed since the first papers linking climate change to issues in human disease and healthcare. One of the most active topics in this area has been the implication of climate change events, particularly temperature and humidity fluctuations, in the northward spread of vector-borne viruses from more tropical regions into Europe and North America. However, some detailed studies of one such emerging disease, tick-borne encephalitis virus (TBEv), have called the connection into question, concentrating the debate on the investigation of precise mechanisms for the spread of viral disease. More recently, firmer statistical correlations have been made between climate variables, the presence of insect vectors and the prevalence of viral disease, particularly for West Nile Virus (WNV). These insights suggest avenues for mechanistic confirmation of the involvement of climate change in other diseases where the connection remains conjectural.

Currently, the COVID‐19 has directly affected the millions of humans lives. The symptoms of the disease involving fever, malaise, chest infection, and breathing difficulties, were identified, and its existence is continuously becoming restructured. The World Health Organization (WHO) had mentioned the wide diagnostics test besides COVID-19 that would also assist medical facilities to recognize infectious diseases as well as currently focusing efficiently on preventing and afterward defeating this viral disease. The infection is usually transmitted among human beings in direct contact, greatest through the liquid bubbles generated through cough, sneeze, or speaking. This paper reviews the COVID 19 pandemic, its history, current updates, contact tracing applications, and use of emerging technologies like the Internet of Things (IoT) and Blockchain for stopping the spreading and provide service online to the patient from a distance.

Perfluorooctanoic acid (PFOA), C7F15COOH, has been widely employed over the past fifty years, causing an environmental problem due to its dispersion and low biodegradability. Furthermore, the high stability of this molecule, conferred by the high strength of the C-F bond makes it very difficult to remove. In this work, electrochemical techniques are applied for PFOA degradation in view to study the influence of the cathode on defluorination. For this purpose, boron doped diamond (BDD), Pt, Zr and stainless steel have been tested as cathodes working with BDD anode at low electrolyte concentration (3.5 mM) to degrade PFOA at 100 mg/L. Among these cathodic materials, Pt improves the defluorination reaction. The electro-degradation of a PFOA molecule starts by a direct exchange of one electron at the anode and then follows a complex mechanism involving reaction with hydroxyl radicals and adsorbed hydrogen on the cathode. It is assumed that Pt acts as an electrocatalyst, enhancing PFOA defluorination by the reduction reaction of perfluorinated carbonyl intermediates on the cathode. The defluorinated intermediates are then more easily oxidized by HO• radicals. Hence, high mineralization (xTOC: 76.1%) and defluorination degrees (xF-: 58.6%) were reached with Pt working at current density j = 7.9 mA/cm2. This BDD-Pt system reaches a higher efficiency in terms of defluorination for a given electrical charge than previous works reported in literature. Influence of the electrolyte composition and initial pH are also explored.

This exploration delves into the intricacies of decision-making in business management. It covers decision-making models, influencing factors, real-world case studies, and strategies for effectiveness. Emphasizing the role of data-driven approaches, the exploration highlights the transformative impact of effective decisions on organizational success. Challenges and pitfalls are addressed, providing insights for overcoming obstacles. The importance of mastering decision-making is underlined as a strategic advantage in the competitive landscape of business management. In summary, this exploration offers a nuanced understanding, empowering leaders to make informed choices that shape organizational destinies.

This paper aims to measure the effects of delisting on stock returns for Vietnam stock market. The study employs a sample of 118 stocks that were compulsorily delisted from the market between January 2011 and December 2021. Using an event study methodology, the empirical findings confirm that the delisting has negative effects on stock returns in the Vietnam stock market. Specifically, results derived from tests show that the average abnormal return of delisted stocks continuously declines during three trading days following the announcement of delisting. Moreover, it is found that the differences in cumulative abnormal returns between post-delisting and pre-delisting periods are significantly negative for all tracking periods. Apart from the negative effect of delisting on stock abnormal returns, we also find that the impact of delisting on stock returns for smaller companies is greater than bigger companies.

In an increasingly changing world, critical thinking is one of the key skills that ensure organisations' competitive advantage. Thus, in higher education institutions there is an accelerating emphasis on developing critical thinking (CT) among students. This paper presents the results of three experimental courses (Pedagogy and didactics of financial accounting, Virtual Learning Environments in Economics, Business Communication), using a blended learning method, aimed at improving students' CT skills. The three courses were delivered by both higher education teachers and trainers from the labour market. After analysing the data from the three experimental courses, it will be possible to assess whether the intervention of labour market trainers contributed to the improvement of students' critical thinking skills, and, in particularly at the level of which components improvements have been identified.

The present study reports a critical review of NIO's business model, considering the evolving landscape of the electric vehicle market and servicing. The objective of this study is to develop a comprehensive framework that facilitates the identification of key elements characterizing a company's business model and highlights ongoing transformations, crucial for adaptation and survival in a rapidly changing environmental context. Focusing on the case study of NIO, a relatively young Chinese original equipment manufacturer (OEM) specializing in high-tech electric cars, the research delves into the challenging scenario of the Chinese electric vehicle market, which has recently faced a bubble in 2023. The market proliferation, supply chain disruptions, and price wars triggered by Tesla have resulted in a survival struggle for numerous automotive startups, leaving larger companies with increasing market shares. Despite facing adversities, NIO managed to secure a promising segment, catering to premium-range battery electric vehicles (BEVs), establishing a competitive advantage through differentiation. By pursuing ambitious investments, the company aims to create economies of scope and achieve cost leadership, venturing into new market sectors and vertically integrating the production chain. Given NIO's agility in adapting to market conditions, aggressive entry into new segments, and a strategic vision for the future, it serves as an excellent candidate for testing and validating the proposed framework. The research sheds light on NIO's trajectory and offers insights into its potential for sustained growth in the dynamic electric vehicle market.

The idea of the current research started from noticing a major gap in the customer behavior literature - researchers scarcely analyzed the impact of scandals on the customer purchase decision in the case of celebrity endorsement. Using a quantitative approach based on questionnaires, 101 people were asked about their opinions, the goals being to find out if people are influenced by the celebrity scandals, if people tend to have different reactions in terms of consumer purchase decision when it comes to various different negative actions carried on by the endorsers - will a murder upset the customers more than an infidelity scandal? - and if there are any differences in treating Romanian and foreign celebrities once they would enter into such a scandal.

The purpose of this paper is to identify factors that influenced customer satisfaction in the Moscow taxi market. The previous researches in customer satisfaction of transportation services laid the foundation of factor model. The resulting list of factors was revised by taxi market experts. The augmented model provided the basis for quantitative survey. The research sample included 310 respondents who have been using taxi services in Moscow during past 2 years. Survey data was analyzed using multiple choice regression method. Analysis results show significant differences between frequent and casual taxi users and a certain number of passenger experience factors that have no influence on customer satisfaction:for frequent users it is discount, for regular users - trip environment, and for rare clients - technical support&security and trip comfort.

An evaluation of emerging issues in One Health (OH) in Sub-Saharan Africa was undertaken to map the existing OH initiatives in Sub-Saharan African (SSA) countries. Desk review, expert opinions survey, limited interviews and wider consultations with selected OH stakeholders were conducted. The strengths, weaknesses, opportunities and threats to OH initiatives were identified. OH influence, interest and impacts were evaluated. One Health is transiting from multidisciplinary to transdisciplinary concepts and OH viewpoint should move from ‘proxy for zoonoses’, to include issues of climate change, nutrition and food safety, social sciences, geography, policy and planning, economics, welfare and well-being, antimicrobial resistance (AMR), vector-borne diseases, toxicosis and pesticides issues. While the identified major strengths should be boosted, the weaknesses should be addressed.OH Networks in SSA were spatially and temporally spread across SSA and stakeholders were classified as key, latent, marginal and OH defenders. Imbalance in stakeholders’ representation led to hesitation in buying-in from stakeholders who are outside the main networks. Theory of change, monitoring and evaluation frameworks, and tools to standardized evaluation of OH policies is needed for sustained future of OH and the future OH engagement should be outputs and outcomes-driven and not activity-driven.National roadmap for OH implementation and institutionalization is necessary and proofs of concepts in OH should be verified and scaled-up. Dependence on external funding is unsustainable and must be addressed. Necessary policy and legal instrument to support OH nationally and sub-nationally should be implemented taking cognizance of contemporary issues like urbanization, endemic poverty and other emerging issues. Utilizing current technologies and OH approach to address ongoing pandemic of COVID-19 and other emerging diseases is desirable. Finally, OH implementation should be anticipatory and not reactive to significantly benefit budgeting and contain disease outbreaks in animal sources before the risk of spillover to human can be envisaged.

We study in this paper the time evolution of stock markets using a statistical physics approach. We consider an ensemble of agents who sell or buy a good according to several factors acting on them: the majority of the neighbors, the market ambiance, the variation of the price and some specific measure applied at a given time. Each agent is represented by a spin having a number of discrete states q or continuous states, describing the tendency of the agent for buying or selling. The market ambiance is represented by a parameter T which plays the role of the temperature in physics: low T corresponds to a calm market, high T to a turbulent one. We show that there is a critical value of T, say T_c, where strong fluctuations between individual states lead to a disordered situation in which there is no majority: the numbers of sellers and buyers are equal, namely the market clearing. The specific measure, by the government or by economic organisms, is parameterized by $H$ applied on the market at the time t₁ and removed at the time t₂. We have used Monte Carlo simulations to study the time evolution of the price as functions of those parameters. In particular we show that the price strongly fluctuates near T_c and there exists a critical value H_c above which the boosting effect remains after H is removed. Our model replicates the stylized facts in finance (time-independent price variation), volatility clustering (time-dependent dynamics) and persistent effect of a temporary shock. The second party of the paper deals with the price variation using a time-dependent mean-field theory. By supposing that the sellers and the buyers belong to two distinct communities with their characteristics different in both intra-group and inter-group interactions, we find the price oscillation with time. Results are shown and discussed.

The study explores how different dimensions of perfectionism influence psychological well-being (PWB) in emerging adults. Literature has deepened the relationships between maladaptive perfectionism (e.g., excessive self-criticism, perceived discrepancy from the standards) and low PWB. Less is known about whether and how adaptive perfectionism (e.g., pursuing personal standards) relates to PWB. Secondly, the study has investigated whether self-compassion (i.e., self-benevolence, seeing personal imperfections as a common condition) may mediate the relationships between adaptive/maladaptive perfectionism and PWB. Participants (N=217, 18-35 y. o.) completed self-report questionnaires measuring: adaptive/maladaptive perfectionism (Almost Perfect Scale-Revised, APS-R: high standards and order/discrepancy, respectively), PWB, and self-compassion (SCS). Adaptive perfectionism resulted associated with PWB, particularly higher presence of purpose in life, environmental mastery, self-acceptance, and personal growth. Conversely, discrepancy resulted the most robust predictor of low PWB (β=-.68), followed by high standards with a positive direction (β=.23; Rc²=.514, p<.001). A strong negative association emerged between discrepancy and SCS (r=-.67, p<.001). A mediation analysis shows that self-compassion has an indirect effect reducing the strength of the relationship between discrepancy and low PWB. Results suggest focusing on self-compassion as a buffer factor that reduces the negative impact of maladaptive perfectionism on psychological well-being. Implications for education and health psychology are discussed.

We analyze whether the central banks of a selected sample of emerging economies respond to exchange rate movements. We use economies that are inflation targters and exporters of a limited number of commodities. The latter renders them vulnerable to terms of trade shocks. The sample comprises Brazil, the Czech Republic, India, Indonesia, Russia and South Africa. We also investigate the role played by the terms of trade in explaining their business cycles. We estimate, for each economy separately and using Bayesian techniques, a regime switching open new Keynesian model. This model allows the parameters of the policy rule and the structural shocks to switch between periods of low and high regimes. We perform posterior simulation and find that, when compared to a constant parameters model, the regime switching fits the data better. The results indicate that, in some periods, the different economies respond strongly to exchange rate, while in others, some respond weakly. A terms of trade improvement leads to a currency appreciation. However, this is reversed for those economies that respond strongly to exchange rate movements. This leads to a rise in output and inflation even for economies that do not respond strongly but play a major role in international trade. This is the case of Russia. The terms of trade are found to play a major rule in explaining business cycles in emerging economies. Thus, although these economies follow an inflation targeting framework, they may set their respective policy rate in a manner to take into account exchange rate developments. This insulates themselves against adverse terms of trade shocks.

Emerging pollutants (EPs) encompass natural or synthetic substances in the environment that pose potential risks but have only recently been recognized or monitored. EPs consist of various categories including pesticides, pharmaceuticals, hormones, mycotoxins, and endocrine disrupting chemicals (EDCs). Through several pathways, EPs can access food, potentially leading to health impacts when their safe concentrations are exceeded. Milk, being a highly nutritious and a heavily consumed food product by many consumers of different ages, is a crucial food matrix where EPs should be regularly monitored. In literature, large number of studies was dedicated for the determination of different EPs in dairy milk, employing different analytical techniques. Chromatographic based techniques were the most prevalent means for analysis of EPs in milk, which demonstrated significant efficiency, sensitivity and accuracy for this specific purpose. Prior to chromatographic analysis, extraction of EPs from a complex matrix like milk, is essential. This review comprehensively covers relevant research papers on extraction and subsequent detection and determination of EPs in milk by chromatographic methods from 2018 and until 2023.

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phy-topathological research. This review analyzes current applications and future directions of AI in addressing evolving agricultural challenges. Plant diseases annually cause 10-16% yield losses in major crops, prompting urgent innovations. Artificial intelligence (AI) shows aptitude for auto-mated disease detection and diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% and surpassing human visual assessment. Forecasting models inte-grating weather, soil, and crop data enable preemptive interventions by predicting spa-tial-temporal outbreak risks weeks in advance at 81-95% precision, minimizing pesticide usage. Precision agriculture powered by AI optimizes data-driven, tailored crop protection strategies boosting resilience. Real-time monitoring leveraging AI discerns pre-symptomatic anomalies from plant and environmental data for early alerts. These applications highlight AI's proficiency in il-luminating opaque disease patterns within increasingly complex agricultural data. Machine learning techniques overcome human cognitive constraints by discovering multivariate correla-tions unnoticed before. AI is poised to transform in-field decision making around disease pre-vention and precision management. Overall, AI constitutes a strategic innovation pathway to strengthen ecological plant health management amidst climate change, globalization, and agri-cultural intensification pressures. With prudent and ethical implementation, AI-enabled tools promise to enable next-generation phytopathology, enhancing crop resilience worldwide.Artificial Intelligence, Phytopathology, Emerging Disease, Climate Change, Control diseases.

We seek to examine effective collaboration when engaging in value cocreation with the customer for mobile financial services in EMs. Our study is a motivation for multi-stakeholder engagement in value cocreation with financial inclusion of all consumers including marginalized populations. Furthermore, our work discovers that social sustainability is a product of social creativity and results in financial inclusion. We apply a qualitative descriptive methodology utilizing exemplars from extant research and phenomenology to analyze the data from the contexts of Ghana and Kenya. The results show that value is co-created for mobile financial services in networks in emerging markets when actors integrate resources for social and environmental sustainability as essential elements for mobile financial inclusion.

The digital economy, driven by information and communication technologies (ICT), has profoundly transformed in recent decades. The digitalization of society has given rise to an economic environment in which information, connectivity, and innovation play fundamental roles. In this context, a technology that has emerged as a fundamental pillar of the digital economy is the chain of blocks, commonly known as blockchain. Blockchain is a technology that has revolutionized the way online data and transactions are managed and shared. Through its ability to create secure, transparent, and decentralized ledgers, blockchain has paved the way for the digital economy, facilitating trust in digital transactions and enabling various applications ranging from cryptocurrencies to supply chain management and intellectual property. This study will delve into blockchain and its influence on the digital economy. It will explore how this technology has reshaped how companies interact, how consumers access services, and how new business models are developed in a constantly evolving digital environment. Additionally, the challenges and opportunities that blockchain presents in the context of the digital economy will be analyzed, and how it is helping to shape the future of business and society in general. As the exploration of blockchain and its impact on the digital economy progresses, it becomes evident how these two forces converge, generating a promising digital landscape full of significant opportunities and transformations. This phenomenon is consistently supported by a growing body of research and analysis, which underlines the growing influence of blockchain on the global economy (Smith, 2020; Johnson, 2019). The dynamic interplay between these two spheres, blockchain and the digital economy, constantly evolves and offers an exciting glimpse into the future regarding innovation and disruption across various sectors (Jones, 2021; Brown, 2018). As a result, significant opportunities are looming for those seeking to understand and capitalize on these emerging trends (García, 2022). Throughout this study, the current trends and most intriguing perspectives that shape this landscape will be broken down, offering a deeper insight into how blockchain and the digital economy are shaping an extraordinary digital future

Smart Cities leverage technology to address various urban challenges and creating disaster resilience is one of them. Technology is a vast and ever-evolving field, and hence the research on technology for improving disaster resilience is scattered. A major drawback of prevailing studies is that they continue to overlook the bottlenecks to effectively harness the benefits of technological innovations and that includes the need for a holistic and multidisciplinary approach. Therefore, this research intends to address that need by methodising the scattered research to provide meaningful insights towards the linkages between society and technological innovations through an urban scholar’s perspective. A comprehensive literature review was conducted to explore emerging and disruptive technologies for improving disaster resilience in Smart Cities. The review findings identified the emerging and disruptive technologies for improving disaster resilience in Smart Cities which were then classified. The findings suggested 4 key criteria to classify technologies including their impact the society, adoption speed, technology maturity and capabilities offered to the community. A Smart City which plans the technologies/ tools for disaster resilience may conduct the assessments under the aforementioned criteria, together with their context-specific feasibility assessments to make informed decisions and ultimately prioritise the most suitable for them.

This paper examines the influence of informal competition on SMEs innovation in the Eastern European transition economies. It investigates whether credit constraints mediate this relation. SMEs innovation is presented through four measures: Product innovation, Process innovation, Radical innovation and Green innovation. Using the BEEPs VI that covers the period from 2018-2020, we show that informal competition affects positively the product, process and radical innovation. Yet, it has a non-significant effect on green innovation. Besides, the informal sector increases SMEs credit constraints, which indirectly leads to less corporate innovation. The negative indirect effect restrains the positive direct effect. Hence, a partial mediation effect of credit constraints on the informal competition and the innovation proxies is reported with the exception of green innovation.

Candida auris is an emerging multidrug resistant yeast causing nosocomial infections and associated with high mortality in immunocompromised patients. Rapid identification and characterisation is necessary for its diagnosis and containing spread. In this study, we present a selective culture medium for all C. auris clades. This medium is sensitive with a limit of detection of 102 CFU/ml. The 100% specificity of SCA (Specific C. auris) medium is confirmed on a set of 134 Candida strains, 50 bacterial species and 200 human stool samples. Thus, this medium specifically selects for C. auris isolation from clinical samples, and allows studying its phenotypic profile.

High throughput multiplex serological systems enable the small developer to set up tests at small cost, for microbes for which there are no commercial tests, and for aspects which have not been addressed by them. An example is testing for Zika and Tick Borne Encephalitis virus antibodies, where antigenic cross-reactions make diagnosis problematic. Our technique variant, Suspension Multiplex Immunoassay (SMIA) allows many samples to be tested for antibodies to many antigens in a short time. Computational compensation for cross-reactions is possible if a SMIA panel contains most of the potentially cross-reacting antigens. Using antibody avidity and pattern of reactivity to whole virus and nonstructural protein, antibodies due to vaccination and infection, respectively, as well as probable degree of protection, can be determined with high throughput. These multiplex techniques hold great promise for future diagnostic development. Theoretically, even large scale serological monitoring, like blood donor pathogen testing, could be done inexpensively and rationally with multiplex serology developed in house. However, the quality control demands are steep and in most cases out of scope for a single laboratory. There remain however a number of clinical applications where in house multiplex serology can be performed with adequate quality control under high throughput conditions.

Small and medium enterprises (SMEs) are the biggest group of enterprises in the European Union (EU); they are also characteristic for emerging economies. Given this situation, there is a need to provide instruments such as processes, which allows them to realize a model of sustainable development. The ability to classify processes and occurrences happening inside these processes often affects the condition of the enterprises. The implementation of innovations, as identified process, enables the directions of SME development towards sustainable development. The purpose of this article is to find out if the identification of processes such as innovations, have any influence on the competitiveness and sustainable development of SMEs. This study was based on pilot research, which examined small and medium enterprises at the regional level, at the example of Polish emerging economy region. It was researched under the angle of the identification of processes and changes happening inside enterprises in terms of understanding the sustainable development concept. Research composition allows to present an understanding by the SMEs of the problems analyzed. The novelty was in the new questionnaire, the definition of sustainable development, and matching those processes identified by the enterprises analyzed with the particular sustainable development dimensions suggested by the authors. In light of the analysis of the literature and the results of this research the important contributions of this study are as follows. This approach pointed the understanding and practical meaning of the identification of processes to be understood. The most important finding was that there is a need to make entrepreneurs aware of the fact that innovations are also processes in themselves, which often constitutes the sum of other supporting processes occurring in the enterprise. Support in the form of knowledge transfer from experts to SMEs would also be recommended.

In the dynamic landscape of Sabah's socio-economic development, the integration of AI technologies holds both promise and challenge. While AI has the potential to drive economic growth, enhance productivity, and elevate quality of life, it also brings forth concerns regarding job displacement, skill gaps, and unequal distribution of benefits. The latest research problem in the realm of AI and employment in Sabah revolves around ensuring inclusive and sustainable development amidst this technological disruption. This encompasses two key dimensions: skill development and education, and labor market dynamics. Addressing the research questions necessitates a multifaceted approach. Firstly, in the realm of skill development and education, there is a critical need to assess the adequacy of existing programs in equipping the workforce with AI-driven skills. Strategies such as promoting STEM education, fostering digital literacy, and facilitating lifelong learning initiatives, particularly among marginalized communities, are essential. Additionally, fostering collaboration between stakeholders and implementing curriculum reforms are pivotal steps in enhancing the alignment between educational curricula and the demands of an AI-driven economy.

In this paper, we consider an economy, in which consumers exhibit unrealistic optimism, and show that such an economy is more likely to undergo early recessions and underinvestment rather than experiencing bubbles or overinvestment. In this model, each consumer incorrectly believes that a negative aggregate preference shock will hit all other consumers, but not herself. When consumers have such an unrealistic optimism, the output price must fall prematurely before the aggregate shock occurs. The reason is that if the price does not plummet today, all consumers would postpone making purchases by falsely expecting that an arbitrage opportunity will arise in the future when the aggregate shock hits the economy, in which case, the output market cannot clear. We also show that the government has the potential to improve welfare of the economy by providing subsidies, if the government judiciously selects the right timing for intervention.

In this study, we investigate the growth of EV ownership among Swedish households. Through detailed socio-economic data and the Swedish vehicle register, we are able compare characteristics of households that bought an EV in 2016 with those that became EV owners in 2020. We are thus able to describe and analyse the transition from the early EV owners to the early majority. Unlike many prior studies in the field, which are based on surveys or interviews, this study relies on registry data, thereby encompassing all car owners in Sweden. In this study, we have also scrutinized the significance of ownership mode by distinguishing between households that have chosen to purchase a car and those that have chosen to lease one. The results show that the demand for EVs has reached new consumer groups, e.g. both younger and older car buyers, and that the option to lease a car privately has broadened the market for new cars in general, and for EV’s in particular.

In this study, we employ the GARCH-MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the predictability of commodity return volatility in relation to US climate policy uncertainty (CPU). Our analysis utilizes the 20-day annualized realized commodity volatility returns of nine global commodities (Aluminium, Cocoa, Coffee, Copper, Cotton, Rice, Soybean, Sugar, and Wheat) to construct the GARCH-MIDAS model, with Climate Policy Uncertainty (CPU) serving as the predictive variable. The outcomes of our investigation reveal a consistently positive and statistically significant relationship between CPU and the selected commodities. This implies that CPU effectively serves as a robust predictor of volatility in commodity returns. The implications drawn from our results suggest that climate change policies play a pivotal role in influencing economic activities within the commodity market. This underscores the substantial impact of climate change considerations on investment decisions and further emphasizes the integral role of climate change in shaping economic choices.

Artificial Intelligence (AI) stands as an emerging technology poised to reshape various facets of our daily lives, with a particularly noteworthy influence on the labor market. In Morocco, AI adoption has commenced in diverse sectors, including finance, insurance, and telecommunications, opening up fresh avenues for employment. Nevertheless, this technological shift also ushers in challenges for Moroccan workers, necessitating training and upskilling to effectively engage with AI-driven systems. Within this article, we delve into the burgeoning impact of AI on the Moroccan economy and job landscape, delving into both the opportunities and obstacles that accompany its proliferation. Furthermore, we explore strategies that authorities and businesses can employ to harness the benefits of AI while mitigating its potential adverse effects on Morocco's workforce.

Food insecurity remains a critical challenge in developing countries like Ethiopia. Majority of its population derive their livelihood from agriculture characterized by mixed farming systems. Smallholder farmers the principal actors of agriculture are also facing a rapidly increasing population and urbanization had been unable to be self-sufficient in food. This paper examines the role of commercialization on food security and its determinants in rural settings. We used cross-sectional data from 295 households randomly selected in northwest Ethiopia. Results from bivariate Tobit regression revealed both crop and livestock commercialization improves household food security but in quite different ways. The income from crop sales was instrumental in allowing households to buy additional foods while livestock sales foster crop diversity for own consumption by allowing them to purchase nonfood items. Thus, agriculture-food security nexus may not require the production systems to be subsistent. Improving commercialization with better access to off-farm employment and institutional services (credit and market infrastructure), and enhanced awareness of the extension towards promoting commercialization and diversified food consumption seem to be more promising. The research paper concludes commercialization is vital not just for economic growth and food security, but also for the smallholder agriculture in providing additional nutrition.

This paper considers the theoretical framework of the consumption-based asset-pricing model and derives successive approximations of the modified basic pricing equation using Taylor series expansions of the investor’s utility function during the averaging time interval Δ. For linear and quadratic Taylor approximations we derive new expressions for the mean asset price, mean payoff, their volatilities, skewness and amount of asset that delivers max to investor’s utility. We introduce new market-based price probability determined by statistical moments of the market trade values and volumes. We show that the market-based price probability results zero correla-tions between time-series of n-th power of price pn and trade volume Un, but doesn’t cause statis-tical independence and we derive correlation between time-series of price p and squares of trade volume U2. The market-based treatment of the random trade price describes impact of the size of market trade values and volumes on price probability. Predictions of the market-based price probability at horizon T should match forecasts of statistical moments of the trade values and volumes at the same horizon T. The market-based price probability emphasizes direct dependence on random properties of market trades.

In every economy, Stock markets are part of the key elements the build it up. A few decades ago, there has been a significant change in Ghana stock market returns (GSE). Our study examines the statistical and economic significance of investor sentiment, based on weather conditions/changes, on stock market returns. OLS models, assisted by unit root tests were employed in analyzing the data obtained from the Ghana stock exchange platform from 2000 to 2017. From our literature review, we discovered that investors’ perceptions play a central role in finalizing the direction of stock market returns. Regarding our empirical results, we tested whether weather variations influence the investment decisions of investors; we discovered that temperature and cloud cover significantly influences stock market returns. This is because of mood changes is associated with weather conditions variations. However, sunshine per our regression coefficient shows a statistically insignificant impact on investors’ investment choices. Precipitation to a large extend influence stock market activities further affecting its results negatively as our regression results depicted. We concluded stock brokerage firms, companies, and investors (foreign/local) must incorporate weather changes/effects when strategizing about their investment outcomes.

Pearl millet is an important food crop in the arid and semi-arid tropical regions of Africa and Asia. These regions are home to millions of poor smallholder’s households living in harsh agro ecology and reported higher prevalence of malnutrition. Such poor households have few options in terms of food crops, besides the limited markets. Indeed, pearl millet is one of the food crops they continue to grow for their food and nutritional security. Pearl millet is important sources of dietary carbohydrates, energy, protein, and important minerals such as calcium, iron and zinc. Considering inherent high nutritional values and climate resilient nature (drought and heat), demand for pearl millet as food, beside valued for its Stover as a source of livestock fodder, is projected to grow strongly in Asia (India) and Africa (West and Central Africa). Iron (cause anemia) and zinc (cause stunting) deficiencies are widespread and serious public health problems worldwide, including India and Africa. Biofortification is a cost-effective and sustainable agricultural strategy to address this problem. Research on pearl millet has shown that large genetic variability (30-140 mg/kg Fe and 20-90 mg/kg Zn) available in this crop can be effectively utilized to develop high-yielding cultivars with high iron and zinc densities. Both Open –pollinated varieties (Dhanshakti and Chakti) and hybrids (ICMH 1202, ICMH 1203 and ICMH 1301) of pearl millet with high grain yield (>3.5 tons/ha in hybrids) and high levels of iron (70-75 mg/kg) and zinc (35-40 mg/kg) densities have been developed and released. Currently, India growing >70,000 ha of biofortified pearl millet, besides more pipeline hybrids and varieties are under various stage of testing at the national (India) and international (west Africa) trials for possible release. Genomic tools will be an integral part of breeding program particularly for nutritional traits to use diagnostic markers and genomic selection. Clinical studies showed that 200g grains from biofortified cultivar would provide bioavailable Fe to meet full recommended daily allowance (RDA) in children, adult men and 80% of the RDA in women. Till today, no markets to promote biofortified cultivars/grains/products as no incentive price and such products aims to address food and nutritional security challenges simultaneously. The demand is likely to increase only after investment and integration into modern public distribution system, nutritional intervention schemes, private seed and food companies with strong mainstreaming nutritional policies. In the non-traditional regions, this will contribute to livestock and poultry feed industry as spill-over benefits to improve nutrition.

The article addresses the issue of consumer preferences for types of coffee in Poland (ground coffee, instant coffee, coffee beans, instant coffee mixes and instant cappuccino). The main source of the study is the results of primary research conducted using a structured interview (CAPI—Computer Assisted Personal Interview) on a nationwide sample of 800 coffee consumers. The research was conducted by Grupa IQS Sp. z o.o. from Warsaw in January 2016 for the MOKATE Group based on the assumptions and guidelines developed by the authors of the article. The main purpose of the article is to present the identified coffee consumer preferences in Poland with regard to various kinds of coffee. The results of the research which have been included in the article indicate, among others, ongoing changes in the preferences of Polish consumers regarding their coffee choices. They prove that Polish consumers are drinking ground coffee more and more often. The consumption of instant coffee is decreasing.

Background: This research examines how market knowledge and artificial intelligence (AI) interact in different market designs such as business-to-business (B2B) settings while taking emerging technologies and the changing digitalization landscape into account. Objective: The main goal is to understand how AI affects market knowledge in different market designs such as business-to-business (B2B) contexts, taking into account language barriers, practical difficulties, and the revolutionary effects on decision-making and customer interactions. Result: They underscore the transformative potential of artificial intelligence (AI) by highlighting how it shapes market knowledge, encourages customized approaches, and improves marketing efficacy in the business-to-business (B2B) space. Conclusion: In order to create a path for responsible AI integration in B2B marketing, the study concludes with recommendations for standardized terminology related to AI, practical insights into implementation challenges, and ethical issues.

Childhood emotional abuse (CEA) has been linked to a range of unfavorable outcomes, including the development of unhealthy personality traits and maladaptive coping mechanisms and behaviors. In this study, our objective was to investigate whether neuroticism and perfectionism act as mediators in the relationship between CEA and workaholism, while also evaluating the gender invariance of the hypothesized model. A cohort of 1176 young workers, with a balanced gender representation (50% female), aged 18-25, participated in the study by completing self-report questionnaires. The results revealed significant connections between all direct and indirect links, indicating a complex interplay between childhood emotional abuse, neuroticism, perfectionism, and workaholism. Importantly, the mediation model exhibited no significant differences between genders, suggesting that the identified relationships are consistent across both male and female participants. This research underscores the critical importance of early identification of childhood emotional abuse and advocates for the implementation of trauma-informed care to address the negative consequences of emotional abuse, ultimately aiming to prevent the development of workaholism. Furthermore, the findings emphasize the necessity for tailored prevention strategies, focusing on mitigating neuroticism and perfectionism as potential pathways for effective therapeutic interventions.

The primary objective of this study is to examine the extent of financial integration between Latin American and US financial markets, particularly in light of recent efforts to foster integration through trade agreements. Spanning from January 1, 1990, to December 31, 2019, the sample focuses on major market indices and key sectors. Financial integration is quantified using a DCC multivariate GARCH model, incorporating a smooth transition model, structural breaks, and regression-based approaches. Results indicate increased comovement with the US for main market indices in Argentina, Chile, Colombia, Mexico, and Peru, while Brazil shows a decrease. Similar trends are observed in sectoral analyses. The study also reveals heightened correlation post-trade agreements. Structural break analysis highlights significant shifts in dynamic correlations for countries with US free trade agreements. These findings support the argument of increased financial integration, bearing significance for portfolio diversification and international policy formulation.

In May 2022, WHO reported an outbreak of Mpox in several European countries which were previously Mpox free. Mpox (formerly known as monkeypox) is a zoonotic viral disease endemic in Central and West Africa. The sudden emergence of Mpox outside Africa and its subsequent rapid spread lead the WHO to declare the outbreak as Public Health Emergency of International Concern. As of May 15, 2023, a total of 87,704 confirmed cases and 140 deaths had been reported from 111 countries and territories worldwide. Looking back on this outbreak one year later, several important questions have arisen. Here, we address these questions using the classic five Ws: What, When, Where, Who and Why? We discuss these questions and outline what needs to be done to prevent, or at least minimize, outbreaks from emerging and re-emerging viral infection.

Glitter particles are considered a model of microplastics, which are used in a wide range of products. In this study, we evaluated the toxicity of green and white glitter dispersions on the embryonic development of the sea urchins Echinometra lucunte, Arbacia lixula, and the mussel Perna perna. The Toxicity Identification and Evaluation (TIE) approach was used to identify possible chemicals related to toxicity. Glitter dispersions were prepared using 0.05% ethanol. The tested dispersions ranged from 50 to 500 mg/L. The white glitter was composed of a vinyl chloride-methyl acrylate copolymer. The effective concentrations of green glitter to 50% embryos (EC50) were 246.1 (235.8 – 256.4) mg/L to A. lixula, 23.0 (20.2 - 25.8) mg/L to P. perna and 105.9 (61.2 - 150.2) mg/L, whereas the EC50 of white glitter to E. lucunter was 272.2 (261.5 – 282.9) mg/L. The EC50 for P. perna could not be calculated; however, the lowest effect concentration was 10 mg/L. The filtered suspension of green glitter had Ag levels exceeding the legal standards for marine waters. TIE showed that metals, volatiles, and oxidant compounds contribute to toxicity. The results showed that glitter may adversely affect marine organisms; however further studies are necessary to determine its environmental risks.

The global warming our generation is experiencing is just one of the great environmental crises of the Anthropocene, a geological period that began with the use of fossil fuels and that, in merely one century and a few decades of industrial activity, has altered ecosystemic processes that sustain human health and well-being. Beyond the loss of the “intrinsic value of nature”, changes in the magnitude and direction of biogeochemical cycles and increases in temperature are phenomena that not only accompany the loss of habitats and species but impair resilience by ultimately generating greater and more complex numbers and types of exposures that constitute a danger to human health. In this study, we attempted to offer some notes about the margin, understood as that space with the greatest inequity and therefore the fastest growth of risk: the collision area where deprivation marks the social determinants of health and where the greatest interaction with causes of disease occur.

The multidrug-resistant fungal pathogens belonging to the Candida haemulonii complex and the phylogenetically related species Candida auris are well-known for causing infections that are difficult to treat due to their multidrug-resistance profile. C. auris is even more worrisome due to its ability to cause outbreaks in healthcare settings. These emerging yeasts produce a wide range of virulence factors that facilitate the development of the infectious process. In recent years, the aggregative phenotype has been receiving attention, as it is mainly associated with defects in cellular division and its possible involvement in helping the fungus to escape from host immune responses. In this study, we initially investigated the aggregation ability of 18 clinical isolates belonging to the C. haemulonii species complex and C. auris. Subsequently, we evaluated the effects of physicochemical factors on the fungal aggregation competence. The results demonstrated that cell aggregation was a typically time-dependent event, in which almost all studied fungal isolates exhibited high aggregation after 2 h of incubation at 37°C. The aggregation was not impacted by pH, temperature, -mercaptoethanol (a protein-denaturing agent) and EDTA (a chelator agent). Conversely, proteinase K, trypsin and sodium dodecyl sulfate significantly diminished the aggregation. Collectively, our results demonstrated that the aggregation ability in these opportunistic yeast pathogens is time-dependent, and surface proteins and hydrophobic interactions seem to mediate cell aggregation, since the presence of proteases and anionic detergent affected the aggregation ability. However, further studies are necessary to better elucidate this phenomenon.

Haemaphysalis longicornis (Neumann, 1901) (Acari: Ixodidae), the Asian longhorned tick, is an invasive tick species present in the USA since at least 2017 and has been detected in one-third of Virginia counties. While this species is associated with the transmission of multiple pathogens in its native geographical range of eastern Asia, little is known about its ability to acquire and transmit pathogens in the USA, specifically those that are transmissible to humans, although from an animal health perspective it has already been shown to vector Theileria orientalis Ikeda strains. Emerging tick-borne viruses such as Bourbon virus (genus: Thogotovirus) are of concern as these newly discovered pathogenic agents have caused fatal clinical cases, and little is known about their distribution or enzootic maintenance. This study examined H. longicornis collected within Virginia (from ten counties) for Bourbon and Heartland virus using PCR methods. All ticks tested negative for Heartland virus via qRT-PCR. Bourbon virus-positive samples were confirmed on two different gene targets, and with Sanger sequencing of the PB2 (segment 1) gene. Bourbon virus RNA was detected in one nymphal stage H. longicornis from Patrick County, one nymph from Staunton City, one larval pool and one adult female tick from Wythe County, Virginia. An additional 100 Amblyomma americanum (Linnaeus 1758; lone star tick) collected at the same Patrick County site revealed one positive nymphal pool, suggesting that Bourbon virus may have spilled over from the native vector, potentially by co-feeding on a shared Bourbon virus-infected vertebrate host. Blood tested from local harvested deer revealed a 12.0% antibody seroprevalence against Bourbon virus, exposure which further corroborates that this tick-borne virus is circulating in the Southwest Virginia region. Through these results it can be concluded that H. longicornis can carry Bourbon virus and that pathogen spillover may occur from native to invasive tick species.

This study investigates the country level determinants of liquidity synchronization and degrees of liquidity synchronization during economic growth volatility. As a non-diversifiable risk factor, liquidity co-movement shock spreads market wide and thus disrupts the overall functioning of the financial market. Firms in Asian markets operate in legal and regulatory environments distinct from those of firms analyzed in the previous literature. Comprehensive analyses of liquidity synchronicity in emerging markets are limited. A major knowledge gap pertaining to Asian emerging markets serves as the primary motivation for this study. Seven Asian emerging economies are selected from the MSCI emerging market index: Bangladesh, China, India, Indo-nesia, Malaysia, Pakistan and the Philippines for analysis from 2010 to 2019. The empirical findings show high levels of liquidity synchronicity in weaker economic and financial environments with low GDP growth, high inflation and interest rates and underdeveloped financial systems taking the form of low levels of private credit. Liquidity synchronicity is also affected by poor investor protection, political instability, weak rule of law and government ineffectiveness. Moreover, levels of liquidity synchronicity are higher in period of economic growth volatility.

Deforestation and associated changing landscapes are major components of environmental changes, with important implications for ecosystem functioning and biodiversity conservation. Tropical forests are hot spots of biodiversity and provide multiple goods and ecosystem services which benefit people in many ways Forest also play an important role in health-related legends, myths, and fairy tales from all over the world, and are important sources of new potential emerging microbial threats to human. Although plausibly numerous abundant microbial forms with a forest origin may exist, our systematic literature review shows that forest-derived infection studies are relatively unexplored, and both taxonomically and geographically biased. Since biodiversity has been associated with emergence of novel infectious diseases at macro-scale, we describe the main biogeographical patterns in the emerging infection-biodiversity-forest loss nexus. Then, we illustrate four fine-scale case studies to decipher the underlying processes of increased infection risk in changing forest clearing landscapes. Finally, we identify scientific challenges and regional management measures required to mitigate these important new emerging threats.

We are currently witnessing a strong global transition towards new, more sustainable models of development and consumption. This transition is both activating and highlighting a series of discrepancies between the various actors in agri-food marketing systems, including the institutions that govern regulatory and trade aspects. These discrepancies highlight how, on a global level, the agri-marketing system is unable to provide adequate responses to the new principles of sustainability that are increasingly expected by civil society. This inability is often linked to the phenomena of opportunism, information asymmetries and lock-in effects (resulting from the slowness or inability of some sectors or actors to evolve technologically and culturally). The control of all these factors is often ineffective and often involves high transaction costs . These conditions lead the global market into an ongoing state of failure, creating structural holes, in which new forms of exchange are born, in response to the principles mentioned above. We identify these as nested markets: hybrid market forms that, thanks to new information technologies, create a new form of proximity that transcends the classical concept of physical proximity. This new proximity directly links producers and consumers in relationships based mainly on two substantial values: reciprocity and reputation. Both of these values significantly reduce transaction costs which today play an increasing role in determining the form and repetition of exchanges. This condition is difficult to interpret from classical and neo-classical economic theories. To do so it is necessary to use a multidisciplinary approach. In this article we combine neo-institutional theory and network analysis to interpret phenomena that are increasingly emerging in all areas of the world. Using these two theories, and case studies from Brasil, North America, China and Europe, we try to highlight how the market is not only the place where the price of products and of their quantities are formed. Market is a complex social spaces, where more-or-less stable relationships are formed, based on the values of reciprocity and reputation that determine behaviour and codes of conduct aimed at containing opportunism and encouraging sustainable, autonomous, forms of self-regulation. These relationships are also the driving forces that ensure the ongoing continuation of the exchanges and the diffusion and preservation of knowledge over time and space. These relationships represent the beating heart of nested markets and their dynamic ability to adapt to the continuous changes that occur in the socio-economic and environmental context in which they are rooted. In this way sustainability is built as an expression of the co-production between different actors (producers, consumers, institutions) and natural resources.

Keywords: Forest management; sustainability; FSC; PEFC; research; market share

Renewable energy sources are increasingly crucial for meeting global energy demands in an eco-friendly manner, particularly as the world shifts away from fossil fuels and faces higher volatility of the market prices. Portugal, a country with limited fossil fuel reserves and high energy dependency, has heavily invested in renewables in recent years. However, renewables like sunlight, wind, and water are inherently unsteady due to climate influences, resulting in energy production fluctuations. To mitigate this issue, energy storage systems are being deployed to stabilize renewable energy supply during production lulls. This project aims to assess an energy storage system and define technical specification in order to maximize profitability at the Finerge-owned Alto Douro wind farm. To achieve this, we've conducted an energy demand analysis, followed by simulations to assess system performance in relation to energy use and profit, while varying parameters such as power and efficiency. We've also compared commercial proposals from different battery manufacturers utilizing various technologies. Our findings suggest that high-power, quick charge-discharge lithium-ion batteries are the most suitable solution, given their efficiency and modularity. These attributes are vital for achieving current and future profitability.

Financial bubble prediction has been a significant area of interest in empirical finance, garnering substantial attention in the literature. This study aimed to detect and forecast financial bubbles in the Vietnamese stock market from 2001 to 2021. The PSY procedure, which involves a right-tailed unit root test to identify the existence of financial bubbles, was employed to achieve this goal. Machine learning algorithms were then utilized to predict real-time financial bubble events. The results revealed the presence of financial bubbles in the Vietnamese stock market during 2006-2007 and 2017-2018. Additionally, the empirical evidence supported the superior performance of the Random Forest and Artificial Neural Network algorithms over traditional statistical methods in predicting financial bubbles in the Vietnamese stock market.

Today's unstable labor market increasingly requires flexibility and adaptability to cope with the threat of unemployment. It can cause distress in people and have a more significant negative impact on fragile workers, such as migrants. This study aimed to test whether a Career Counseling intervention designed for Migrants (CCfM) can develop Career Adaptability and, therefore, both Work Self-efficacy (WSe) and Job Search Self-efficacy (JSSe) perceptions. It was conducted in Italy and involved a sample of 233 migrants, who were asked to respond to a questionnaire available in three languages (Italian, French, and English). Data analysis showed that an improvement was demonstrated in all the variables considered, namely career adaptability (including concern, control, confidence, and curiosity), WSe, and JSSe, even though the CCfM was not directly designed to increase the last one. In addition, the development of career adaptability explained the increase in migrants' WSe and JSSe, and the initial level of career adaptability was found to explain the increase in WSe due to the initial positive level of curiosity.