Unpredictable Changes Research Articles

Down-regulating the stress axis: Living in the present while preparing for the future

The measurement of glucocorticoid (GC) hormones provides us with a window into the stress physiology of vertebrates and the adaptative responses they use to cope with predictable and unpredictable changes in the environment. Baseline GCs inform us about the metabolic demands they are subject to at that point in their yearly life-history stage, whereas GC changes (often increases) in response to acute challenges inform us on their capacity to cope with more immediate environmental challenges. However, baseline GC levels and the kinetics of GC responses to acute stressors can vary substantially among and within species, depending on individual characteristics (age, sex, condition, life-history stage). In addition, a thorough understanding of the stress status of an animal requires moving beyond the measurement of GCs alone by focusing on downstream measures of metabolic activation, such as oxidative stress. Here, we evaluated the changes in blood cortisol and oxidative stress markers in wild adult Columbian ground squirrels (Urocitellus columbianus), following a 30-min capture-handling stress performed in mid-late June. Measurements were taken when males were post-reproductive and preparing for hibernation and adult females were weaning litters. We found three key results. First, the time-course of GC increase was markedly slower (by an order of magnitude) than what is currently reported in the literature for most species of mammals, birds and reptiles. Second, there were marked differences in the male and female response, linked to differences in life-history stage: females close to weaning had abolished GC responses, whereas post-reproductive males did not. Third, there were mild to moderate increases in oxidative damage and decreases in oxidative defenses in response to our short-term challenge, consistent with the idea that short-term acute metabolic activation may carry physiological costs. However, these changes were not correlated to the changes in GCs, a novel result suggesting a disconnect between the hormonal stress response and oxidative damage.

A new model for evaluating the impact of organizational culture variables on the success of knowledge management in organizations using the TOPSIS multi-criteria algorithm: Case study

In today's times, knowledge management has emerged as a critical pursuit for organizations in preserving and enhancing their intellectual assets. Organizational culture stands out as a key determinant of success in this regard, underlining the need for organizations to enhance their knowledge management methods amidst rapid and unpredictable changes. This paper evaluates how various aspects of organizational culture such as Job dissatisfaction, Emphasis on rewards, lack of infrastructure, Performance Orientation, Inadequate technology, Support Defend, Silo mentality in knowledge, Innovation, and Stability affect organizational knowledge management success. The urgency of this research is underscored by the critical need for organizations to enhance their knowledge management strategies amidst rapid and unpredictable changes. What distinguishes this research is its innovative model, offering a quantitative and systematic approach to assessing the impact of organizational culture on knowledge management success through the TOPSIS to measure knowledge management success in ten government organizations in East Azerbaijan province, Iran, each with one hundred employees. In this study, questionnaires based on organizational culture characteristics were given to employees to collect quantitative data and also to assess the level of knowledge management, data were analyzed using the TOPSIS algorithm. The results of the study showed that Organization 3, where at least 50% of the employees responded positively to indicators related to the emphasis on rewards and performance orientation, had the highest level of success in knowledge management compared to other organizations.

Virtual unmodeled dynamic and data-driven nonlinear robust predictive control

This study presents a novel approach for controlling an industrial process that exhibits uncertainty and significant nonlinear features. The proposed method utilizes a virtual unmodeled dynamic and data-driven nonlinear robust predictive control strategy. The representation of a controlled object involves a composite state space model that combines both linear and high-order nonlinear elements. Moreover, a robust model predictive controller is developed using the linear component. In addition, the notion of one-step optimal feedforward is used in combination with a compensating controller to handle the high-order nonlinear factor specifically. Subsequently, a compensation controller with incremental characteristics is developed for a modified version of the high-order nonlinear term. Furthermore, the stability conditions of the closed-loop system are derived, and an analysis is conducted on the stability and convergence of the proposed approach. The TTS20 three-capacity water tank was utilized in both simulations and practical scenarios. The study demonstrated that the suggested approach successfully reduces system output variations and enhances overall performance in response to unpredictable changes in the process’s dynamic features.

Three-dimensional wireless measurement of float–sink object motions in a gas–solid fluidized bed

We developed a Lagrangian sensor system capable of wirelessly measuring the 3D motions of objects and applied it to examine the floating and sinking behaviors in a gas–solid fluidized bed. The system consisted of a sensor particle, comprising a 9-axis sensor and a wireless module integrated into a spherical outer shell, and three pairs of magnetic coils. By utilizing this system, we can non-invasively measure the 3D motions of objects, which cannot be observed from the outside. In this study, we examined the motions of objects with various densities in the gas–solid fluidized bed. We found the similarity and dissimilarity between the float–sink motions of objects in fluidized beds and those in liquids. The experimental results revealed that the vertical motion of an object in the fluidized bed depends on its density and can be categorized into two distinct states: floating near the surface or settling down at the bottom. However, within a specific range of object densities close to the apparent density of the fluidized bed, the object exhibited complicated motions in the bed. In such cases, slight density variations induced unpredictable changes between the floating and sinking states. The results also suggested that the settling velocity of the objects in the fluidized bed varies with their vertical positions in the bed.

Study on the evolution law of physical mechanics and abrasion characteristics of granite under high temperature-water cooling treatment

During deep geothermal resource development, the estimation of drilling efficiency and tool wear in extremely hard rocks relies primarily on CAI testing. However, the degradation of rocks caused by high-temperature water cooling conditions leads to unpredictable changes in CAI. To address this issue, this study conducted P-wave velocity, hardness, thermal conductivity testing, BTS experiments, CAI testing, and NMR testing on granite samples subjected to water cooling at different temperatures (25–600 °C). The study analyzed the degradation mechanisms of granites under high temperature-water cooling conditions, the relationship between various parameters and the CAI index, and established a dual-parameter fitting model. The results indicate that the degradation of rocks under hightemperature-water cooling conditions is primarily attributed to mineral thermal reactions, thermal expansion effects at high temperatures, and rapid cooling-induced thermal contraction effects. Once the degradation effects exceed the skeleton constraint limit, macroscopic cracks gradually form within the granite. The formation of macroscopic cracks has a mitigating effect on abrasivity. The research findings on the correlation between CAI and various parameters can provide important theoretical support for the application of high-temperature rock breaking engineering.

Complex modeling of complicated processes: analytical model parameters adaptation in solving qualimetric problems

The relevance of the study is due to the fact that despite the sustainable development of methods and technologies for creating models of various classes and purposes, the tasks of managing their quality (the so-called inverse problems of theoretical qualimetry) are often neglected. For example, in the field of information technology, much more attention is paid to assessing the quality of software products, which is reflected in the corresponding standards. These tasks become especially relevant when models reflect a complex process (CP), and such processes may be unique, and obtaining complete objective data on such CPs prior to modeling is difficult or impossible (accidents and disasters models, military operations, natural disasters, and others like that). The article’s main purpose is to consider the issues of solving the inverse qualimetric problem by parametric adaptation of analytical models to unpredictable possible changes in the complex processes’ nature. The solution to this problem is based on the combined (analytical and simulation) modeling of unique processes. Theoretical qualimetry involves a quantitative assessment of any product's qualitative properties; to ensure the adequacy level of analytical models (based on the results of their parametric adaptation), it is planned to evaluate with the use of well-known metrology principles regarding relative measurement deviations. In this case, detailed simulation modelling results are used as a reference for combined modelling. The complexity of the processes conditiond by the expediency of their polymodel description in order to mutually compensate for the objective deficiencies of heterogeneous models, as well as the use of simulation capabilities to adjust the parameters of analytical models in cases where the use of the latter is due to strict time constraints on obtaining calculation results and developing control actions based onthem. A variant of the formalized statement of the problem of parametric adaptation of analytical models is presented. A presented example that considers the adaptation of parameters of the Lanchestertype analytical model conducted on simulation data. The adaptation of parameters could be carried out in different ways, and the expediency of choosing a certain one is determined by the assessment of mutual deviations of the results of heterogeneous modeling. The results of the calculations witnesses that parametric adaptation can be an effective element in solving one of the key tasks of model qualimetry, namely, ensuring their required qualitative properties. The prospect of further research is to consider the issues of structural adaptation of simulation models to the given conditions for displaying complex processes.

ФІНАНСОВЕ ПРОГНОЗУВАННЯ В АНТИКРИЗОВОМУ УПРАВЛІННІ ПІДПРИЄМСТВ

Formulation of the problem. The article is devoted to the problem of financial forecasting as a tool of anti-crisis management. The purpose of the study is to develop the theoretical and methodological foundations of financial forecasting in anti-crisis management based on an integrated approach. The object of the study is financial forecasting in anti-crisis management of the enterprise. Methods used in the research: scientific knowledge, method of generalization, comparison, logical and meaningful, methods of induction and deduction, analysis. The research hypothesis consists in the assumption of the need to develop the theoretical and methodological foundations of financial forecasting in anti-crisis management based on a comprehensive approach, which involves the use of a flexible toolkit of diagnostics, analysis and forecasting, which provides an opportunity to identify the onset of the risk of crisis events and to form options for the development trends of enterprises and vectors of the anti-crisis strategy, taking into account changes in the economic environment. Presenting main material. The prerequisites, essence, subject field and fundamental characteristics of the conceptual provisions of financial forecasting in anti-crisis management are highlighted, which provides a holistic view of its organizational and methodological support based on a comprehensive approach. The methods of financial forecasting at the enterprise are systematized and the features of their scope of application, advantages and disadvantages, selection criteria are revealed. The expediency of using methods for diagnosing the bankruptcy of enterprises in conditions of instability is substantiated, and a list of critical indicators of the probability of bankruptcy of the enterprise is given. The sequence of the process of developing financial forecasts in the format of the balance sheet is proposed. Originality and practical significance are the recommendations regarding the proposed methodical approach to the development of financial forecasts in the format of a balance sheet model of itemized calculation of assets and liabilities, based on financial reporting data, which provides an opportunity to generate information to justify management decisions on the choice of an enterprise development strategy based on the criterion of value maximization. Conclusions. The implementation of recommendations for the development of theoretical and methodological provisions of financial forecasting in anti-crisis management based on an integrated approach provides a holistic view of the sequence of the forecasting process and the use of its tools to justify anti-crisis mechanisms aimed at finding reserves to ensure the continuity of business operations. The use of flexible financial forecasting tools allows to identify the onset and prospects of the risk of crisis events and to form options for the development trends of enterprises and vectors of anti-crisis strategy in conditions of unpredictability of changes in the economic environment.

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ПЕРЕХІДНИХ ПРОЦЕСІВ В ІЄРАРХІЧНИХ СТРУКТУРАХ ДЕРЖАВНОГО УПРАВЛІННЯ З НЕЛІНІЙНИМИ ХАРАКТЕРИСТИКАМИ

The last decades are characterized by a large number of studies of state and public figures, which can be called an era of deep (fundamental) and rapid changes. Society is experiencing qualitative changes and serious challenges, therefore there is a kind of paradox when the imperatives of a new era force the development of a theoretical basis in the semantic field of common sense, which is associated with permanence and qualitative changes in political, economic and social life [1, 2, 3] . In state administration and local self-government bodies, relations between people, rapid unpredictable changes in the situation in the country and in regions (political, economic, social, etc.) are non-linear management systems. Moreover, any physical system when examined in more detail is always nonlinear. The effectiveness of managing a nonlinear system, taking into account disturbing factors, depends on the accuracy of forecasting the dynamics of changes in individual elements of such a system. This is a multifaceted problem [15]. A characteristic feature of non-linear hierarchical structures (NIS) in the public service (state administration - DU and local self-government - MS) is a continuous and discrete change in the processes of development of events, which distinguishes them from other internal and external influences, such as those that cause the transformation of linear communication into non-linear, which ultimately leads to new changes. This is the first thing. Second, subject-object relationships can have uncoordinated actions caused by real-world circumstances. Such uncoordinated actions can occur even more in transitional processes of society (for example, the speed of their flow) due to the inertia of individual elements or the social system itself as a whole. As a result of these phenomena, the linear relationship between discrete changes is broken and the previous hierarchical structure changes, which leads to non-linear information relationships in the state administration (SU) and local self-government bodies (MS). For example, G. Pocheptsov and other scientists associate this nonlinearity with chaos, the growing complexity of social processes, globalization, with a threat to state security, with the manifestation of unpredictability and instability [1-5]. Strict requirements are imposed on the management process in the new state of DU and MS: - resilience of the management system; - the system should be described as continuous-discrete (its dynamics); - the management process must ensure the necessary accuracy of matching the indicators of the new state of the system with the previous one. A number of problems appear in newly formed non-linear hierarchical structures (NIS) in DU and MS: - lack of a priori information about processes with non-linear connections; - inaccuracy of structural identification; - inaccuracy in the choice of criteria for assessing the situation; - restructuring processes; - wrong choice of states of nature; - incorrect determination of the importance of the selected criteria according to the scale of importance; - incorrectly chosen dependence of alternatives on the criterion; - insufficient degree of awareness of the complexity of the situation. Solving the above problems requires experimental research. If the process of stabilization of the NIS in the DU is considered as an object of regulation, then it is enough to establish the dependence of this stability on the control action and the main disturbance, and all other actions are considered as disturbances on the object of study. Such a description will reflect the main dynamic characteristics of such a process and will be sufficient for the synthesis and development of an optimal regulation system with the aim of achieving stable (stable) processes in such systems (including DU and MS). In the future, we will approach the DU as a non-linear hierarchical system (NHS) and depict the NIS as a multidimensional continuous system, in which the state of nature is the regulated quantity, and the input is the action of managers in the DU and MS (management decisions made by them - PUR) regarding regulation , coordination and perturbations acting on the system.

US economic sanctions targeting Latin America: Recent changes, developments and compliance challenges

The United States — specifically through the US Department of the Treasury's Office of Foreign Assets Control (OFAC) and the Department of State — has maintained economic sanctions against certain Latin American countries since the 1950s. Starting with broad-based sanctions against Cuba, where OFAC prohibited virtually all transactions, the Department of the Treasury has instituted more-targeted sanctions regimes against Venezuela and Nicaragua, where non-government dealings are, for the most part, authorised. Together, the Departments of State and the Treasury also administer sanctions against various narcotics and terrorist organisations operating in Latin America. Most notable is the Foreign Narcotics Kingpin Designation Act, which has targeted trafficking organisations, foreign officials and their money laundering empires. To that end, sanctions, while initially imposed to fight certain political regimes, have developed into sanctions targeting all kinds of wrongdoing such as sponsoring terrorism, aiding and abetting drug trafficking, corruption and the commission of human rights violations. US sanctions violations are assessed under a strict liability standard (ie, no knowledge of the violation is required to trigger liability) and impact not only those directly subject to the jurisdiction of the US but also may carry implications for non-US persons undertaking certain ‘significant transactions' with sanctioned persons and jurisdictions. Further, while sanctions apply to US persons, OFAC can institute penalties on non-US persons for causing a US person to violate their compliance obligations. In addition, OFAC (or the Department of State) may sanction persons (individuals or entities) by adding them to the Specially Designated and Blocked Nationals (SDN) List. US persons must block the property and interests in property of SDNs, and are prohibited from virtually all, direct and indirect, transactions involving an SDN. SDN restrictions also apply to ‘Shadow SDNs' which are entities owned 50 per cent or more, directly or indirectly, by one or more SDNs in the aggregate. A Shadow SDN receives the same treatment as SDNs, regardless of whether such entity is itself on the SDN List. The challenge with Shadow SDNs is that they can only be discovered through rigorous due diligence into beneficial ownership structures of sometimes opaque corporate entities. This is where the world of sanctions compliance and enforcement crosses with that of anti-money laundering. The evolving customer due diligence, ongoing customer monitoring, suspicious activity investigations and reporting, and know your customer (KYC) (and know your customer's customer [KYCC]) evidenced are reflected through the evolving Financial Action Task Force (FATF) Recommendations, the Financial Action Task Force on Money Laundering in South America (GAFISUD) and domestic regulations. As a result of the increasingly unpredictable political changes in Latin America, and the concurrent changes in sanctions regimes, financial institutions (FIs) should maintain a proper understanding of the current sanctions prohibitions, the trends and updates in the area, but equally important, they should also maintain a good understanding of the complex legal provisions authorising certain behaviours — including the general licences and exemptions — that may apply. FIs must balance mitigating the risks of sanctions violations, and the associated hefty penalties, with the risks of a cumbersome and overly restrictive compliance regimen. An appropriately risk-based compliance programme that achieves both of these objectives is very much an art and not a ‘one size fits all’ model.

Unveiling the epigenetic landscape of plants using flow cytometry approach.

Plants are sessile creatures that have to adapt constantly changing environmental circumstances. Plants are subjected to a range of abiotic stressors as a result of unpredictable climate change. Understanding how stress-responsive genes are regulated can help us better understand how plants can adapt to changing environmental conditions. Epigenetic markers that dynamically change in response to stimuli, such as DNA methylation and histone modifications are known to regulate gene expression. Individual cells or particles' physical and/or chemical properties can be measured using the method known as flow cytometry. It may therefore be used to evaluate changes in DNA methylation, histone modifications, and other epigenetic markers, making it a potent tool for researching epigenetics in plants. We explore the use of flow cytometry as a technique for examining epigenetic traits in this thorough discussion. The separation of cell nuclei and their subsequent labeling with fluorescent antibodies, offering information on the epigenetic mechanisms in plants when utilizing flow cytometry. We also go through the use of high-throughput data analysis methods to unravel the complex epigenetic processes occurring inside plant systems.

Assessing Genetic Relationships, Trait Associations and Diversity Patterns in Sorghum Germplasm Through Correlation, Cluster and Principal Component Analysis

Background: The loss of biodiversity has a significant impact on the fundamental services provided by ecosystems to humanity, including plant development and genetic improvement. Germplasm serves as the foundational material for identifying genetic variations. In this context, the examination of sorghum germplasm diversity has been conducted. Methods: The study involved 86 different sorghum germplasm samples that were assessed alongside three control groups, each replicated three times, during the Rabi season of 2021. This evaluation was conducted using augmented block design I (ABD I) at the Department of Millets, Tamil Nadu Agricultural University in Coimbatore. Result: The results of the Pearson correlation analysis revealed significant relationships notably, traits such as plant height, number of leaves, panicle length, panicle width, panicle weight, hundred seed weight and dry fodder yield exhibited positive and significant correlations with grain yield per plant. Cluster analysis identified four distinct groupings among the 86 accessions, with clusters 1 and 4 displaying the greatest diversity. Principal component analysis indicated that PC1 accounted for the largest variability. The genotypes were identified through PCA analysis is having greater variation and better performance. The findings of this study suggest that the identified sorghum genotypes could serve as valuable genetic resources for enhancing sorghum productivity in dry and semi-arid regions, particularly in the face of unpredictable climate change.

Orientation and contrast deviance examined: Contrast effects mimic deviant-related negativity yet neither produce the canonical neural correlate of prediction error.

The visual mismatch negativity (vMMN) is a negative-going event-related potential (ERP) component that is largest somewhere between 100 and 300 ms after the onset of an unpredictable visual event (i.e., a deviant) in an otherwise predictable sequence of visual events (i.e., standards). Many have argued that the vMMN allows us to monitor our ever-changing visual environment for deviants critical to our survival. Recently, however, it has become unclear whether unpredicted changes in low-level features of visual input, like orientation, can evoke the vMMN. I address this by testing isolated orientation changes, to confirm recent findings, and isolated contrast changes, to determine whether other low-level features of visual input do not evoke the vMMN in a traditional oddball paradigm. Eighteen participants saw sequences of rare, unanticipated, and different deviant stimuli, interspersed among frequent, anticipated, and identical standard stimuli. Stimuli were Gabor patches. Neither deviant produced a vMMN. Therefore, changes in low-level visual properties of well-controlled stimuli-a stimulus in which one property can be manipulated while all others remain unaffected-like Gabor patches do not yield a vMMN.

Challenges And Opportunities: Unravelling The Dynamics Of Entrepreneurship Disruptions In Nigeria

Entrepreneurship disruptions have become a pervasive and transformative force in today's global business landscape. These disruptions are characterized by the rapid and often unpredictable changes that impact the way entrepreneurs conceive, launch, and operate businesses. In the modern era, the rapid pace of technological advancement and the rise of disruptive innovations have presented a significant challenge for entrepreneurs and established businesses alike. As entrepreneurs strive to identify and leverage disruptive opportunities, they face complex issues related to market dynamics, economic instability resource allocation, and competitive pressures. Moreover, the ever-accelerating rate of disruption necessitates a deeper understanding of how entrepreneurs can effectively navigate these challenges while staying innovative and sustainable. This study seeks to identify and analyse the experiences and challenges faced by businesses in their pursuit of sustainability during this disruptive era. Data were generated via the internet, newspapers, newsletters, libraries and other documented materials pertinent to the study. Findings revealed that there is a positive relationship between entrepreneurship disruptions and business sustainability in Nigeria. To fully harness disruptive entrepreneurship and achieve sustainability, regulatory reforms, technological advancements, changing consumer behaviour, infrastructure development, and increased access to funding are crucial. Consequently, to address these challenges and promote sustainability, it is imperative to conduct a comprehensive analysis of the experiences and challenges faced by businesses and individuals in the disruption era, businesses in Nigeria need to adopt innovative solutions, and collaborate with relevant stakeholders while keeping a close eye on regulatory changes and global trends.

Experimental investigation of hybrid vacuum tube solar water heater/parabolic concentrator integrated with phase change material and nanofluid as HTF simultaneously; energy and exergy assessments

ABSTRACT Solar water heaters suffer from fluctuating hot water production due to unpredictable weather changes throughout the day. In this study, the hybrid configuration of a vacuum tube solar water heater with a parabolic solar concentrator, in conjunction with the application of paraffin as a phase change material, is employed as a novel approach to address this problem. Furthermore, the study investigates the utilisation of a nanofluid (0.05%, 0.1%, and 0.2% mass) containing Al2O3 and ZnO nanoparticles dispersed in water-ethylene glycol (base fluid) as the medium fluid to enhance thermal performance. The experimental results revealed that the utilisation of 0.2% mass ZnO and Al2O3 nanofluids led to a considerable increase of 10.74% and 7.25%, respectively, in the maximum reservoir temperature. This resulted in a respective average thermal efficiency improvement of 41.6% and 33.9% compared to the base fluid. Furthermore, the maximum exergy efficiency of the system exhibited a significant increment of 54% and 40.1% compared to the base fluid. Moreover, the incorporation of phase change material in the system effectively minimised temperature fluctuations.

Self-directed professional development used as intervention to enhance teachers’ curriculum as praxis

School teachers must be prepared for ongoing, unpredictable and rapid changes in the world, therefore, they need specialised and general knowledge to be able to think independently and imaginatively. The purpose with this article was thus to report on the effectiveness of a self-directed professional development (SDPD) intervention that guided teachers to enhance their curriculum as praxis, especially for 21st-century education. Self-directed learning (SDL) and the capability approach were used to support teachers, through SDPD, to become the teachers they would want to be or could be in the 21st century, in terms of enhancing their curriculum as praxis. Qualitative research was conducted in South-Africa with Grade 9 teachers. Pre- and post-SDPD interviews were conducted, and the SDPD-intervention continued for 3 to 5 months. The results from our research show that the SDPD-intervention effectively supported the participating teachers to enhance their curriculum as praxis.

Harnessing the potential of sugarcane-based liquid byproducts—molasses and spentwash (vinasse) for enhanced soil health and environmental quality. A systematic review

Farming practices reliant solely on synthetic agrochemicals face unreliability in the current era marked by unpredictable climate changes and rapid soil health deterioration. Consequently, a shift towards sustainable approaches is imperative to ensure both food security and environmental quality. Molasses and vinasse, abundant organic liquid by-products from sugar processing and distillery industries respectively, have historically served as soil conditioners and biofertilizers. Despite their potential, their effectiveness as organic amendments remain relatively unknown globally. In response, we conducted a systematic literature review to unveil the benefits of molasses and vinasse as organic amendments. Our findings reveal that these by-products consist of both inorganic and organic compounds that enhance soil and aquatic ecosystem performance. These compounds include essential plant nutrients as mineral elements and organic matter, contributing to improved soil physico-chemical and biological properties. Notably, the application of molasses and vinasse in crop production has demonstrated superiority over chemical fertilizers, particularly when combined with other inorganic amendments. Molasses and vinasse have been reported to significantly increase yield in several crops including sugarcane (Saccharum officinarum), tomatoes (Solanum lycopersicum), soybean (Glycine max), maize (Zea mays) and rice (Oryza sativa). Strategic utilization of vinasse has the potential to enhance environmental quality by reducing soil heavy metal loads and mitigating negative impacts associated with synthetic fertilizers. However, it is crucial to note that irregular disposal or misuse of these by-products can result in detrimental effects on the environment and human health. To encourage sustainable utilization on a global scale, it is essential to establish appropriate dosages, raise awareness among farmers and stakeholders regarding judicious use, and develop effective methods for handling and application of molasses and vinasse. This approach ensures cost-effective and environmentally friendly organic amendments, fostering a harmonious balance between agricutural productivity and ecological well-being.

Investor sentiment response to COVID-19 outbreak-related news: A sectoral analysis of US firms

Capital markets literature has challenged the efficient market hypothesis, and one of the factors that explain unpredictable changes in stock prices is investor sentiment. In this study, we examine the investor sentiment index’s response to COVID-19 outbreak-related events in 2020, based on a sample of the S&P 500 companies from the sectors most severely affected by the pandemic: healthcare, industrials, consumer goods and consumer services. Using principal component analysis, we determine objective market-based measures of the investor sentiment, both for sectors, and individual companies. Taking advantage of the event study methodology and using the Daily News Sentiment Index as a benchmark, we found that the abnormal investor sentiment index’s response to COVID-19 outbreak-related news was highly negative, with a few exceptions of positive reaction on selected announcements in the healthcare and industrials sectors.

Optimizing Agricultural Yields with Artificial Intelligence-Based Climate Adaptation Strategies

In the face of climate change, agricultural productivity is severely threatened by unpredictable weather patterns and changing environmental conditions, underscoring the critical need for innovative solutions to bolster agricultural resilience and optimize yields. This study delves into the potential of artificial intelligence (AI), specifically through the use of machine learning and deep learning techniques, to develop climate adaptation strategies aimed at enhancing agricultural outcomes. By integrating AI with climatological data, the research predicts and mitigates the adverse impacts of climate on crop yields, utilizing a combination of machine learning and deep learning models to analyze historical climate data alongside crop performance. These models, trained on datasets including temperature, rainfall, soil moisture, and crop genetic information, are adept at forecasting future agricultural outcomes under varied climatic scenarios and suggest optimal adaptation strategies that significantly improve crop yields. Consequently, these AI-based models serve as robust tools for farmers and agricultural policymakers, enabling them to make informed decisions that are aligned with anticipated climatic conditions. The findings not only underscore the efficacy of AI in transforming data into actionable insights that enhance agricultural productivity but also contribute to the field of agricultural science by providing a technologically advanced approach to climate adaptation. Furthermore, this research paves the way for future studies on the integration of AI with real-time environmental sensing technologies, thereby offering a dynamic framework for agricultural management that supports sustainable farming practices and global food security amid climate challenges.

The role of priming and memory in rice environmental stress adaptation: Current knowledge and perspectives.

Plant responses to abiotic stresses are dynamic, following the unpredictable changes of physical environmental parameters such as temperature, water and nutrients. Physiological and phenotypical responses to stress are intercalated by periods of recovery. An earlier stress can be remembered as 'stress memory' to mount a response within a generation or transgenerationally. The 'stress priming' phenomenon allows plants to respond quickly and more robustly to stressors to increase survival, and therefore has significant implications for agriculture. Although evidence for stress memory in various plant species is accumulating, understanding of the mechanisms implicated, especially for crops of agricultural interest, is in its infancy. Rice is a major food crop which is susceptible to abiotic stresses causing constraints on its cultivation and yield globally. Advancing the understanding of the stress response network will thus have a significant impact on rice sustainable production and global food security in the face of climate change. Therefore, this review highlights the effects of priming on rice abiotic stress tolerance and focuses on specific aspects of stress memory, its perpetuation and its regulation at epigenetic, transcriptional, metabolic as well as physiological levels. The open questions and future directions in this exciting research field are also laid out.

Impact of Climate Change on Vegetable Production and Management Strategies

Vegetables are an important component of human nutrition that encompasses great species diversity and are very sensitive to unpredictable climatic changes. In recent decades, there has been an increase in the frequency of events like drought, flooding, high-temperature, low temperature, salinity and changes of atmospheric CO2 or ozone level which considerably affect morphological, physiological and biochemical changes in the plants. The occurrences of these types of abiotic stresses lead to membrane damage, oxidative burst, reduction of chlorophyll content and photosynthesis rate which ultimately affect the yield and quality of vegetable crops. The adoption of appropriate crop management practices and climate-resilient cultivars would help immensely in dealing with the adverse impacts of abiotic stresses. Alteration in planting dates, advanced irrigation technology, moisture-saving methods, use of plant growth regulators, use of plant growth promoting rhizobacteria, grafting technology, use of climate resilient cultivars and protected cultivation-like management practices can reduce the impact and intensity of abiotic stress enhance the production as well. Overall in this review, we have summarized the adverse effects of abiotic stresses that are induced by climate change and management strategies that enable to overcome the ill effects and sustain the production of vegetable crops.