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Background: Making clinical and economic decisions it is important to distinguish between the primary and the secondary cause of headache, which is often associated with brain pathology. Present study was aimed to study CT findings and MRI findings correlation in chronic headache and its outcome. Material and Methods: Present study was single-center, cross-sectional, observational study, conducted patients of age 10-70 years who are presented with chronic headache as chief complaint to the OPD, underwent imaging by CT & MRI. Results: The percentage of females (53%) was slightly higher than males (47%). M:F ratio was found to be 1:1.13. Average age of the population was 50.5± 13.8 years. Majority of the patient population were from urban areas (85%). 7% Patients were found to be overweight whereas 2% were underweight. Average BMI of the population was 22± 2.9 kg/m2. A vast majority (66%) of the patients had complaints between 6-9 months. Average duration of complaints was 8.72± 2.7 months. Majority of the patients (43%) had frontal headache. One sided headache was reported by 38% patients. 5% cases had headache at the back of the neck whereas 2% had it around the eyes. The most common detected pathology was paranasal sinusitis (n= 08), followed by brain tumours (5 %). 2 Pineal lesions were identified in MRI which were missed out by CT scans. 3 Vascular malformations were identified on MRI compared to 2 on CT. Calcified granuloma was defined better compared to CT. The detection rate of CT was found to be 20 % whereas detection rate of MRI was found to be 23%. Conclusion: This study has provided detection rate of 20-23% using CT and MRI and thus given reasonable evidence for radiodiagnosis of chronic headache cases with normal neurological examination and significant intracranial pathology. [ABSTRACT FROM AUTHOR]

Nowadays, product recovery and waste recycling are receiving more attention in order to reduce environmental pollution and production costs in the form of a closed-loop and sustainable supply chain. Also, designing a supply chain by considering resilience approaches can protect buyers against disruptions such as natural, human or technological disasters. On the other hand, efficient and effective financial supply chain management (FSCM) way is known as one of the main structures in line with the continuity and stability of the chain’s performance, and budget restrictions are of great importance considering the issue of scarcity of resources in the economy. This study has presented a multi-objective mixed integer linear programming (MOMILP) model of a single-period, multi-product and multi-level closed-loop supply chain, taking into account the dimensions of sustainability and resilience, emphasizing the balance between the initial budget and the cost of establishing facilities under uncertainty. subsequently, to eliminate the uncertainty of the demand parameters and costs, its robust counterpart was presented based on Pishvaee’s robust possibilistic programming (RPP) model. The augmented Epsilon Constraint method (AEC) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were used to solve and evaluate it. [ABSTRACT FROM AUTHOR]

The convergence of advanced detection mechanisms, engineering management, and intelligence analysis presents a disruptive model for local companies pursuing economic growth. The paper presents a thorough strategy meant to improve regional processes for making decisions to promote long-term economic growth by utilizing modern technology. Using deep learning techniques, such as neural networks and deep neural architectures, to examine large datasets that are pertinent to local businesses. This makes data-driven decision-making easier and empowers stakeholders to choose wisely and strategically for the best possible economic results. incorporating management of engineering concepts to optimize resource allocation, improve operational efficiency, and streamline operations. To guarantee the successful implementation of economic development programs, management of projects, quality control, and methods for optimization must be applied. The research's findings have great potential to further regional businesses' goals for economic development. Through the integration of robust engineering management concepts and the analytical capacity of deep learning, this framework aims to equip decision-makers with the essential skills to navigate the intricacies of local economic environments, propel sustainable expansion, and promote equitable prosperity. [ABSTRACT FROM AUTHOR]

This document provides a list of books on topics related to economics and social science. The books cover a range of subjects, including decision-making, sustainable food design, mass consumption, food policy, consumer behavior, the circular economy, customer satisfaction, data privacy, climate change, sustainable finance, social contracts, behavioral science, public policy, behavioral law and economics, and nudges. Each book is briefly described, highlighting its main focus and key arguments. [Extracted from the article]

Background and Objectives: Depression is associated with problems in social interaction and communication. Most of the research conducted in this field uses non-interactive tasks. The theory of economic games as a branch of behavioral economics can provide a new tool for investigating interactions and social decisions in interactive and dynamic conditions and help to better understand neuropsychiatric disorders. In this research, the decision making of depressed people in interactive situations is investigated with a systematic review of economic game theory articles. Methods: By systematic review method, 45 related articles from 2010 to 2023 were extracted from Scopus and Web of Science databases. After removing the duplicate articles and checking the exclusion criteria, finally, 23 articles that analyzed the decision-making process of patients with depression symptoms in economic games were analyzed. Results: The findings showed that the performance of depression sufferers in economic games is different from the healthy group. These differences can be discussed in two groups of cognitive and social components. The cognitive component was classified into the subcomponents of theory of mind, negative cognitive schema, bias in perception, and limited cognitive processing, and the social component was classified into the subcomponents of social avoidance, social comparison and competition, and interpersonal trust. Conclusion: Economic games may help identify suboptimal and maladaptive choices associated with depressive disorder and thus provide a powerful tool for discovering candidate cognitive and social markers of depressive disorder. [ABSTRACT FROM AUTHOR]

During the 1950s, numerous small-capacity hydroelectric power plants were built in Spain. Seventy-five years on, it must now be decided whether to continue their operation or demolish them. In order to provide a valid answer, it is necessary to have access to decision-making tools that enable sustainable economic and environmental decision making. The present work proposes a methodology that employs an economic indicator of life cycle cost and environmental indicators of carbon footprint and embodied energy by means of life cycle data analysis. Quantification of the impacts was carried out with the support of construction cost databases and the PREDICE software tool for the quantification of environmental impacts incorporated into maintenance tasks. The case study of the "Cerrajón" power plant was analyzed, where historical hydrological cycles were considered. A life cycle scenario was evaluated in which renovation extended the life of the power plant by a further 75 years. The results show savings in environmental impacts with respect to the impacts of the Spanish energy mix of up to 175 kgCO2 per MWh produced, although no economic benefit was found. It was also shown that in climate change scenarios, the profit price breakeven increases. Rehabilitation appears to present the best choice when combining the two criteria. [ABSTRACT FROM AUTHOR]

Objectives: To assess the feasibility of estimating an EQ-5D-5L value set using a small study design in cancer patients and to compare the EQ-5D-5L values based on the preferences of cancer patients with those of the general public. Methods: Patients with clinically diagnosed cancers were recruited from two hospitals in Shanghai, China. In face-to-face interviews using the EQ-PVT survey, health states were valued by cancer patients using both cTTO and DCE methods. cTTO data was modelled alone or jointly with DCE data. Forty-eight models using different model specifications (cross-attribute level effect [CALE] and additive models), random/fixed effects model assumptions, data heteroscedasticity and censoring were estimated. The best performed model was identified in terms of monotonicity of estimated model coefficients and out-of-sample prediction accuracy. Results: Data collected from 221 cancer patients who participated in the study were included. The hybrid CALE model using both TTO and DCE data performed best in terms of prediction accuracy (Lin's concordance coefficient = 0.989; root mean squared error = 0.058) and suggested that pain/discomfort and anxiety/depression were the most undesirable health problems. Compared to values based on general Chinese public's health preferences, the values based on cancer patients' preferences were much higher and lower for health states characterized by extreme mobility problems and severe/extreme pain or discomfort, respectively. Conclusion: This study demonstrated the feasibility of using a small design to develop EQ-5D-5L value sets based on cancer patients' health preferences. Since there were signs of differences between preferences of patients and general population, it may be valuable to develop patient-specific value sets and use them in clinical decision making and economic evaluations. [ABSTRACT FROM AUTHOR]

Bipolar psychometric scales data are widely used in psychologic healthcare. Adequate psychological profiling benefits patients and saves time and costs. Grant funding depends on the quality of psychotherapeutic measures. Bipolar Likert scales yield compositional data because any order of magnitude of agreement towards an item assertion implies a complementary order of magnitude of disagreement. Using an isometric log-ratio (ilr) transformation the bivariate information can be transformed towards the real valued interval scale yielding unbiased statistical results increasing the statistical power of the Pearson correlation significance test if the Central Limit Theorem (CLT) of statistics is satisfied. In practice, however, the applicability of the CLT depends on the number of summands (i.e., the number of items) and the variance of the data generating process (DGP) of the ilr transformed data. Via simulation we provide evidence that the ilr approach also works satisfactory if the CLT is violated. That is, the ilr approach is robust towards extremely large or infinite variances of the underlying DGP increasing the statistical power of the correlation test. The study generalizes former results pointing out the universality and reliability of the ilr approach in psychometric big data analysis affecting psychometric health economics, patient welfare, grant funding, economic decision making and profits. [ABSTRACT FROM AUTHOR]

Objective: Attention to levels of socioeconomic inequality has given rise to work investigating its potential to influence political actors and, thus, policy outcomes. These studies have focused on elected actors in legislative contexts. Ours fills this gap by assessing the consequences of a judge's wealth on decision making. Methods: We obtain data on federal appellate judges' wealth and explore its influence in cases involving economic issues. We estimate logit models controlling for other factors and include fixed effects for circuit, specific issue area, and year of the decision. The models consider both the main effects of wealth and its potential interaction with judicial ideology to influence decision making. Results: We find no direct relationship between a judge's wealth and her decision making in economic cases. However, wealth interacts with ideology to exert a significant influence on decision making; here, greater wealth amplifies the ideological predilections of more conservative judges. Conclusions: This is the first study to document a link between wealth and the choices judges make on the bench. It adds a new dimension to the ways economic inequality can influence political actors and raises new questions about the mechanisms by which such inequality is consequential for elite political behavior. [ABSTRACT FROM AUTHOR]

Climatic phenomena, particularly hydrological droughts, have led to significant changes in reservoir operation strategies. Multipurpose reservoir operations are essential for effectively managing stored water resources for various activities like electricity generation and agricultural irrigation. Despite considerable efforts to support decision making for each economic activity, there remains a weak integration across these sectors in joint analyses. To address this, an integrated approach combining a model of a large power system and a model at the basin scale is proposed to analyze the operation of both power and agricultural systems. This approach allows evaluation of the operating policies of a multipurpose reservoir and its performance at both the local and regional scales under different hydrological scenarios. A modification is implemented whereby the priority of water extraction to agricultural users is increased. Its effects are assessed for different hydrological trajectories in a case study in the Laja Lake basin in southern Chile, the biggest Chilean basin with a capacity of up to 5,500 Hm3. The Laja Lake, a multipurpose reservoir with substantial hydroelectric generation capacity and extensive agricultural areas plays a crucial role in the operation of the national power system. Based on an analysis of 2025, it is demonstrated that hydrological changes directly impact electrical and agricultural performance. Drought conditions increase thermal generation, costs, emission intensity, and water deficits. Furthermore, the policy modification reveals tradeoffs between the power sector's emissions and agricultural water deficits. For drier scenarios, increasing agricultural extraction priority results in low additional operational costs and emissions from the power system, which supports adopting a policy aligned with netzero objectives. [ABSTRACT FROM AUTHOR]

Many of the great strategies of companies with good plans and program face failure. If the managers’ mental models as the source of their thinking contradict these plans, these plans will not be successful. Managers can increase the probability of success of strategies by shaping their minds and examining and developing their mental image. One of the products with high potential in export and foreign exchange in the country and especially in Khuzestan province is dates, which has many areas of growth and progress in this field by creating an efficient marketing and structuring approach. Important and basic export of Khuzestan dates; Presented a mental model of date export obstacles in Khuzestan province. This research was a type of exploratory mixed research, in the qualitative part based on the theory derived from the data and in the quantitative part based on the descriptive-survey method. The qualitative part of the tool was a semi-structured interview and the quantitative part was based on a questionnaire. The statistical population in the qualitative section included experts, specialists, and date exporters, and saturation was achieved after interviewing 20 people. In this research, the qualitative part was analyzed with Max Kyuda software and the quantitative part was analyzed based on Lisrel software. The results showed that individual thinking; collective thinking; decision-making power; direct individual understanding; type of individual behavior; Creativity; developing a mental image of oneself; Understanding export behavior and simplifying complex issues is one of the obstacles to exporting dates. Based on the impact on the central category of the mental model of date export obstacles, in addition to the quantitative model, the pattern obtained based on the qualitative model was confirmed. Based on the findings, a multi-dimensional marketing system should be created based on the related structure and commercial knowledge to reduce the barriers to date export, and macro laws and regulations can help in improving and speeding up the barriers in this field. [ABSTRACT FROM AUTHOR]

In the studies of human cooperation, the problem is always the choice between individual benefit and collective benefit, which is modeled by the game. On the other hand, based on the Dual processing of decision-making, whether cooperative decision-making is the type I or type II has been discussed a lot. Some studies consider cooperative decision-making as type 1 and others as type 2. According to some theories, the human self is inter-subjective, and it is created by the interaction between I and Me. The classical model of game theory does not consider it. In this article, we first enter common sense and intersubjectivity into the game theory model and show that a level of estimation of the intention of the opposite player is necessary for cooperation. Then we show that if the individual perceives himself in a joint situation through the knowledge of the opposite player’s intention, the cooperative decision-making process is carried out Fast, and therefore it must be considered type 1, and if he considers himself as an individual, his decision-making must be considered type 2. As a result, belonging to a social environment has priority over the type of decision-making. The statistical population includes 20 master’s students who each made 100 binary decisions and produced a total of 2000 data. The analysis method is regression analysis. Based on an intersubjective model of game theory the result of the analysis of a linear regression model shows that the response time decreases and the level of cooperation increases significantly as people’s understanding of another’s intention increases, and also the response time increases and the level of cooperation decreases at the same time as this intention decreases. Because collaborative decision-making takes place in an intersubjective space, it is said that it is influenced by common sense before than dual cognitive processing. Therefore, if there is a community of common sense, collective rationality and as result cooperation is internalized and shows itself as system 1. But if there is no common sense, people decide to cooperate or not as separate individual atoms. [ABSTRACT FROM AUTHOR]

On June 30, 2022, judicial deference toward actions of administrative agencies took a significant hit. In West Virginia v. EPA, the Court formally recognized--for the first time--the major questions doctrine, which requires agencies to identify clear congressional authorization when claiming the authority to make decisions of vast economic and political significance. Since June 30, 2022, the Supreme Court has utilized the major questions doctrine in decisions of national importance, including topics ranging from environmental protection efforts to canceling student debt. This note offers a snapshot of how the major questions doctrine has been applied by federal courts across the country since West Virginia was decided. Beginning with the nondelegation doctrine, this note traces the rise and the beginning of the fall of congressional delegations of power to administrative agencies. This note then summarizes the major questions doctrine and shows how the doctrine has been applied by federal courts in forty-six cases since West Virginia was decided. [ABSTRACT FROM AUTHOR]

Younger and older adults often differ in their risky choices. Theoretical frameworks on human aging point to various cognitive and motivational factors that might underlie these differences. Using a novel computational model based on the framework of resource rationality, we find that the two age groups rely on different strategies. Importantly, older adults did not use simpler strategies than younger adults, they did not select among fewer strategies, they did not make more errors, and they did not put more weight on cognitive costs. Instead, older adults selected strategies that had different risk propensities than those selected by younger adults. Our modeling approach suggests that age differences in risky choice are not necessarily a consequence of cognitive decline; instead, they may reflect motivational differences between age groups. Author summary: What are the psychological mechanisms underlying adult age differences in economic decision making? We investigated this question with a model based on the framework of resource rationality, which posits that people adaptively use the cognitive resources available to them. Unlike commonly used economic models of decision making, this model can shed light on the cognitive processes that drive age differences in choice. Our findings show that younger and older adults use different decision strategies and that the age differences are not necessarily the result of cognitive decline; instead, they may be a result of age differences in motivational factors. By providing novel insights into the psychological mechanisms of age differences in decision making, our modeling approach can inform interventions and choice architectures supporting older adults' decision making. [ABSTRACT FROM AUTHOR]

This research was conducted to measure the effect of individuals' economic literacy levels on consumer decision-making styles. In addition, the study examines whether there is a difference in consumer decision-making styles according to whether the participants have received economics education or not. The sample of the research consists of 426 participants residing in Balıkesir. As a result of the study, it has been determined that the effect of economic literacy on consumer decision-making styles is significant (R=0.325 R2=0.105 F=49.999 p<0.01). The economic literacy levels of the participants differ depending on whether they have received economics education or not. (F=14,510 p<0.05). Consumer decision-making styles differ depending on whether the participants received economics education or not (F=3.914 p<0.05). [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Ilmu Ekonomi Terapan is the property of Universitas Airlangga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Industry‐level figures suggest that up to two‐thirds of Thoroughbred breeding operations in the UK are unprofitable and that around half of sales transactions of Thoroughbred yearlings, commercial breeders' predominant income source, return a loss. The industry strategy currently endorses investment in stallion covering fee; however, to date, a comprehensive evaluation of sales price determinants in the UK setting is lacking and could better inform economic decision making to improve profitability. Methods: Sales catalogue and Weatherbys' stud book data from all Thoroughbred yearlings sold at the 2020 Tattersalls October yearling sale in the UK were used to build a hedonic sales price model. Explanatory variables representing sire, dam, yearling and sales attributes were evaluated. The final model's accuracy was assessed using out‐of‐sample data from all yearlings sold in the equivalent 2021 sale. Results: In 2020, a total of 1506 catalogued yearlings, representing around 30% of the UK Thoroughbred foal crop, were sold, with a median price of £42,575 (interquartile range 15,750‒105,000; range 840‒3,570,000). The sires' covering fee, maternal siblings' race performance attributes, whether the yearling was the dams' first foal, consignment size, catalogue book and day of sale within book significantly influenced auction price; however, relationships were complex with significant interaction and confounding observed. The mean model forecasting error was £2074. The use of data from only one sale could affect generalisability. Conclusions: These novel findings can inform breeding decisions to maximise profitability, give context for current industry strategies and can inform valuations of breeding stock. [ABSTRACT FROM AUTHOR]

This article delves into the concept of interculturalism and its potential to reshape democratic systems by incorporating diverse cultural perspectives, particularly those of Latinos and Indigenous communities. It argues that interculturalism goes beyond assimilation and integration, aiming to build pluri-national states where Indigenous and Western cultures coexist. The article also highlights the importance of individuals who navigate between multiple worlds, known as Nepantleras, in challenging restrictive beliefs and fostering intercultural understanding. Additionally, it emphasizes the significance of embracing non-human entities, such as animals and the land, in order to fully embrace interculturalism. The article proposes a transformative journey called the Nepantla-Spider process, which involves shedding old perspectives and embracing differences to create a more inclusive and interconnected framework. [Extracted from the article]

Expected utility theory is critical for modeling rational decision making under uncertainty, guiding economic agents as they seek to optimize outcomes. Traditional methods often require restrictive assumptions about underlying stochastic processes, limiting their applicability. This paper expands the theoretical framework by considering investment returns modeled by a stochastically ordered family of random variables under the convolution order, including Poisson, Gamma, and exponential distributions. Utilizing fractional calculus, we derive explicit, closed-form expressions for the derivatives of expected utility for various utility functions, significantly broadening the potential for analytical and computational applications. We apply these theoretical advancements to a case study involving the optimal production strategies of competitive firms, demonstrating the practical implications of our findings in economic decision making. [ABSTRACT FROM AUTHOR]

To estimate a Saudi-specific value set for the EQ-5D-5L questionnaire using the EuroQol Valuation Technology program and the EuroQol Group's standard protocol. Participants were quota-sampled from the Saudi adult population based on residency location, age group, gender, education level, and employment status. The participants were guided through the completion of composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks by trained interviewers using EuroQol Valuation Technology software. Quality control (QC) measures were used to ensure good data quality. Random intercept and Tobit models analyzed the cTTO data, as well as models correcting for heteroskedasticity. DCE data were analyzed using conditional logit models, whereas hybrid models were used to analyze the cTTO and DCE data jointly. To evaluate model performance, prediction accuracy, logical consistency, significance level, and goodness of fit were used. The valuation study included a representative sample of the Saudi population (N = 1000). The hybrid heteroskedastic model without a constant was chosen as the preferred model for generating the value set. The predicted values ranged from −0.683 for the worst health state ("55555") to 1 for the full health state ("11111"). Pain and discomfort had the largest impact on health-state preference values, whereas usual activities had the least. The value set for the Kingdom of Saudi Arabia is the first value set for the EQ-5D-5L for any country in the Middle East. The value set can be used in Saudi health system economic evaluations and decision making. • The absence of a Kingdom of Saudi Arabia (KSA)-specific EQ-5D-5L value set prompted the Ministry of Health to develop a value set specific for the country. • The objective of this study was to generate the EQ-5D-5L value set for the KSA based on the EuroQol Valuation Technology protocol. • This is the first value set for EQ-5D-5L generated for the KSA and countries in the Gulf Cooperation Council. This value set will be crucial to economic assessments, health technology assessments, and clinical research in the region. [ABSTRACT FROM AUTHOR]

This article makes the case for a specific variety of what we call Collective Capital Institutions (CCIs), by returning to the idea of Wage‐Earner Funds (WEFs) – a 1970s Swedish policy proposal designed gradually to shift ownership and control over parts of the economy to democratically controlled institutions. We identify two attractive rationales in favour of such a scheme and argue that both can fruitfully be transposed to the current worldwide economic situation. The egalitarian rationale is that WEFs could help in the pursuit of equality by giving a wider set of people a stake in collectively owned companies and a right to their profits. The democratic rationale is that WEFs redistribute not only these profits, but also the power over economic decisions made within companies. We then contrast such schemes for collective capital ownership with the similar but much more privatised proposals set out in, for instance, John Rawls's idea of a 'property‐owning democracy'. We argue that CCIs ultimately are more likely to contribute to the development of the 'sense of justice' within society that is needed for a stable just society. We conclude that CCIs deserve a great deal more exploration in academic and political discussions of egalitarian economic systems. [ABSTRACT FROM AUTHOR]

The article discusses two books, "Political Conflict in Pakistan" and "India Is Broken," which examine the current state of affairs in India and Pakistan. Both countries are facing political and economic challenges, with deeply embedded social, economic, and political structures hindering progress. The book on Pakistan explores conflicts within society and politics, including the design of the state, the relationship with religion, the political elite's connection with subalterns, and sub-national tensions based on ethnic identity. The book on India focuses on the country's economic trajectory and the rise of majoritarian cultural nationalism. Both books provide critical analysis and raise important questions about the future of these nations. [Extracted from the article]

This study aims to investigate the impact of the fiscal decentralization on economic growth in the context of Pakistan. Focusing on key factors such as revenue decentralization, expenditure decentralization, own-source revenue, and fiscal balance, the study employs empirical analysis to unravel the impact of decentralization mechanisms on the country economic growth. While plugging in the Eviews, the Augmented Dickey-Fuller (ADF) test indicated that, in the beginning, all variables demonstrated non-stationary characteristics at the integrated of order zero (I(0)) level. However, through first differencing (I(1)), the variables became stationary, setting the stage for further analysis. Based on time series data set spanning the years 2000 to 2022, following the Pooled OLS estimation technique, the research reveals a positive correlation between revenue decentralization and economic growth, advocating for a judicious distribution of revenue-raising authority. Similarly, a moderate positive relationship is identified between expenditure decentralization and economic growth, emphasizing the potential benefits of local autonomy in resource allocation. The study underscores the importance of fostering self-sufficiency at the subnational level, as evidenced by the positive correlation with own-source revenue. However, a cautionary note is sounded on the negative relationship between fiscal balance and economic growth, urging policymakers to maintain fiscal discipline. The findings contribute nuanced insights and actionable recommendations for policymakers seeking to navigate the intricate dynamics of fiscal decentralization in Pakistan, providing a foundation for informed decision-making in the pursuit of sustainable economic development. [ABSTRACT FROM AUTHOR]

Cognitive skills affect individual choices. Researchers commonly use Raven's Progressive Matrices (RPM) tests and the Cognitive Reflection Test (CRT) to assess the relationship between cognitive abilities and economic decision making. In this paper, we study the relationship between these measures, and investigate the extent to which they are correlated and whether they are best described as substitutes or complements. Combining a sample of 686 children and a sample of 2,332 adults, we compare individual performances in the RPM test and CRT test. First, we report a significant positive correlation between the two measures of 0.3. Second, we document that performance in both the RPM test and CRT are significant predictors of behavioral inconsistency observed in incentivized time and risk preference elicitation tasks for children and risk preference elicitation task for adults. [ABSTRACT FROM AUTHOR]

Romania faced the highest inflation rate in the European Union at the beginning of 2024, but progress has been made compared to that in 2023 due to the increasing interest rate. This inflation stemmed from a combination of global and domestic factors (global factors such as the Russia-Ukraine war, supply chain disruptions caused by the COVID-19 pandemic and war, rising commodity prices, domestic factors such as wage and pension increases, tax and charge hikes, and a strategy of gradual increase in the monetary policy interest rate). The National Bank of Romania (NBR) uses a combination of monetary policy instruments to target inflation and provides quarterly forecasts. However, under uncertain conditions, numerical forecasts are less reliable, and the inclusion of sentiment analysis in forecasts might lead to innovation in the field by improving the prediction accuracy. Sentiment analysis has become increasingly important in the field of economics, offering valuable insights and potentially improving economic forecasting and decision-making due to rapid technological progress. Sentiment analysis can identify potential changes in consumer behaviour and business decisions before they are translated into actual economic data, providing an early warning system for economic trends and potential crises. The methodological background relies on natural language processing to extract sentiment indices for large amounts of texts in Inflation Reports provided by NBR. Moreover, the sentiment indices calculated by IntelliDocker are incorporated into autoregressive distributed lag (ARDL) models to provide quarterly inflation forecasts. This type of econometric model has the advantage of addressing endogeneity. Moreover, the unemployment rate is considered an inflation predictor since tensions in the labour market might impact inflation. This paper contributes to empirical forecasting by proposing sentiment forecasts that are more accurate than NBR numerical forecasts corresponding to the 2006: Q1-2023: Q4 horizon. The new forecasting method might be used to make inflation predictions for the next quarters. More accurate forecasts would be valuable for businesses, the central bank, policymakers, and the general public. However, while sentiment analysis offers valuable insights, it is important to remember that human judgment and expertise remain essential for interpreting the data and making informed economic decisions. [ABSTRACT FROM AUTHOR]

Animals are often assumed to follow a strategy of energy maximization, and therefore should evaluate feeding options based on energy intake rates. However, at the proximal level, a direct estimate of energy intake rates, if that is possible at all, might require postabsorptive senses with relatively longer processing times, whereas an indirect estimate of energy intake through proxies like pre-absorptive senses of different sensory food properties might support rapid foraging decisions. Here, we show that nectar sugar concentration (sweetness) and nectar viscosity (resistance) drive preferences of bumble bees, Bombus terrestris , classical models for economic and foraging decision making. Using a tasteless/odourless biopolymer (Tylose), we created feeding options that differed in sweetness and resistance, properties that affect energy intake rate and can be immediately sensed. When energy intake rates were similar, bumble bees developed preferences based on sweetness and resistance. When energy intake rates were different, but sweetness and resistance were balanced against each other, bees developed no preferences. Decision dynamics during training indicated that bumble bees simultaneously evaluated sweetness and resistance to make decisions quickly (in seconds). These results suggest that bumble bees' food preferences are jointly affected by the immediate sensation of nectar sweetness and resistance as positively and negatively reinforcing properties, respectively, indicating a pre-absorptive proximate mechanism for rapid energy-sensitive decisions in bumble bees. • Bumble bees develop preferences based on nectar sugar concentration and viscosity. • Bumble bees quickly sample and compare the sensory properties of feeding options. • Pre-ingestive information contributes to bumble bees' floral preferences. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Administrative & Legal Sciences is the property of Arab Journal of Sciences & Research Publishing (AJSRP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Capital is considered the engine of economic growth and development in all economic growth theories and models. Therefore, providing direct financing and attracting enough capital to implement economic plans is one of the most critical concerns of economic decision-makers in every society. By understanding this issue, compilers of Iran's economic development programs have stated that one of the crucial goals in the country is to provide the necessary grounds for developing monetary and financial markets. Currently, there are many financing tools in the world, most of which cannot be used in Islamic societies due to their nature of usury. The data from 2001 to 2018 for selected countries were extracted from WDI, ICRG, and IIFM databases and analyzed through the econometric method. The results showed a positive and significant effect of Sukuk issuance on the economic growth of Islamic countries. In the end, implications were made to attract liquidity using this tool. In Iran, the role of Sukuk on economic growth has not been investigated, and the critical point is that in this research, the data related to economic risk and political risk have been used and simultaneously, along with other variables, its effect on economic growth has been evaluated and analyzed. [ABSTRACT FROM AUTHOR]

The commentary encourages supplementing the geological and natural concept of the Anthropocene with a cultural and political aspect. These two perspectives are not mutually exclusive but are complementary. This approach can facilitate its transition from the language of academic debate to practical and necessary actions at the societal level. According to the authors, the slightly abstract and impersonal Anthropocene should be shown in the context of cultural, economic and political dependencies and choices that created it and continue to reproduce its logic. This turn also opens up a new area for analyzing the Anthropocene from the perspective of a critique of political economy (an analysis of the costs of economic policies that reproduce and accelerate successive stages of the ecological catastrophe) as well as of civic culture (research "anthropocentric awareness" or "anthropocentric citizenship" in entire societies). Thus, the authors suggest rejecting the fatalistic determinism of the Anthropocene as a process that, although originally caused by abstract (devoid of historical, economic and political contexts) humans, is now often treated as a phenomenon beyond the reach of social action. Plain Language Summary: Can the concept of the Anthropocene, which originated in the geological sciences, but is now increasingly used by the media and in public space, be clearly defined from the perspective of the social sciences? In our opinion, the social understanding of the Anthropocene can facilitate its transition from the academic debate and the image of the Pop‐Anthropocene disseminated by the media to the creation of a necessary and practical policy framework. We also suggest treating the Anthropocene not as an abstract idea in the geological and natural sciences, which is difficult for common people to understand, but as a phenomenon that brings political and economic consequences in the real social world. What is more, this phenomenon depends on political and economic forces that have never been anonymous. This turn breaks with the lack of political responsibility for the ecological consequences of decisions made by political and economic decision‐makers, as well as for the thoughtless attitudes of all other participants in social life. Key Points: From a cultural perspective, the Anthropocene should be treated in two ways: as a "geological" state and as a model of "social and economic"In the third decade of the 21st century, it is important to give social analyses and concepts of the Anthropocene a political perspectiveIt is time for the Anthropocene to move permanently from academic halls to the main agenda of political challenges globally and locally [ABSTRACT FROM AUTHOR]

The COVID 19 pandemic has transformed the entire world's strategy. The governmental oversight, fundamental and significant views were renewed and prioritized according to the unpredictable pandemic process and force-majeure demand. The world's governments and private sectors have faced new socio-political and economic problems and challenges that require quick, effective and powerful solutions. The nation's economic viability during the pandemic and post-pandemic periods depended on these decisions and their effectiveness. Monetary, fiscal, and financial policies suffered significant difficulties in maintaining the economic system. Covid 19 has created difficulties in predicting economic sequences alongside social problems and the complete lack of economic precision in all segments has caused macroeconomic uncertainty. This paper deals with the microeconomic analysis of Georgia in the post-pandemic period, discussing both the main economic parameters of the country and its dynamics, as well as the analysis of its impact on the microeconomic situation. The paper analyzes the impact of the pandemic on the main sectors, as well as the decisions made by the state for economic stimulation and its effect. The work is mainly based on the official information of state structures and international organizations, as well as the works of Georgian and foreign scientists, and based on them, a coherent, multi-component analysis is presented. The theoretical framework of the article is based on fundamental, conceptual studies of Georgian and foreign authors in the field of our research. The paper presents conclusions and recommendations based on a complex study of macroeconomic factors, which are important for scientific circles, both the state and the private sector. [ABSTRACT FROM AUTHOR]

The literacy-targeted (LT) introductory economics course seeks to reduce the quantity of economic concepts under study and increase students' ability to apply those concepts to improve their own decisions and to make sense of economic news. The assessment strategy of the course must target students' ability to transfer their conceptual knowledge to new situations. Assessments can include authentic and ill-structured problems. Frequent formative assessment with feedback gives students sufficient practice to develop deep understanding. Social learning pedagogy makes possible many more practice opportunities with immediate feedback than are possible in instructor-centered pedagogy. Regular writing assignments further develop students' ability to apply economic concepts to real-world problems. Strategies from the writing across the curriculum (WAC) movement can limit the resulting increase in instructor workload. [ABSTRACT FROM AUTHOR]

This article discusses the use of behavioral science to improve cardiovascular health. It highlights the importance of understanding human behavior and decision-making processes in order to design effective programs that promote healthier choices without limiting freedom of choice. The article also explores the role of financial incentives, defaults, and nudges in influencing behavior and improving adherence to recommended treatments. Additionally, it discusses the potential of social incentives, gamification, and access to healthy food in promoting healthy behaviors. The article emphasizes the need for training clinicians in behavioral economics to positively influence clinician and patient behavior and ultimately improve health outcomes. [Extracted from the article]

We study a standard real-option problem in which sequential decisions are made through voting by a group of members with heterogeneous beliefs. We show that, when facing both investment and abandonment timing decisions, the group behavior cannot be replicated by that of a representative "median" member. As a result, members' disagreement generates inertia—the group delays investment relative to a single-agent case—and underinvestment—the group rejects projects that are supported by a majority of members, acting in autarky. These coordination frictions hold in groups of any size, for general voting protocols, and are exacerbated by belief polarization. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine on the ways in which a company's sustainability reporting (SR) differs depending on the types of ownership it has, notably director ownership (DO), institutional ownership (IO), and foreign ownership (FO). This paper uses a sample of 145 firm-year observations from 29 listed banks in the Dhaka Stock Exchange (DSE) of Bangladesh from 2016 to 2020 and regression analysis to test the relationship between different ownership structures and SR. The study also employed the generalized method of moments (GMM) to deal with the endogeneity issue. The findings show that investors have varying perspectives on SR disclosure activity. The findings show that two stockholding patterns, DO and FO, significantly impact SR disclosure in Bangladesh but that there is no significant association between IO and SR disclosure. In constructing SR, this paper depends on only the quantity of disclosure, not the quality, and is solely based on the published annual report. The study findings also provide a comprehensive overview of the SR practice of Bangladeshi banks, which may be helpful to regulators, policymakers, management, creditors, and other stakeholders in making investment and economic decisions. To encourage SR commitment, the government may need to keep an eye on the ownership structure and implement policies that encourage foreign investment. To the best of the authors' knowledge, this is the first study to look at how ownership structure influence SR practices in the banking industry of Bangladesh over five years. [ABSTRACT FROM AUTHOR]

Objective: To retrospectively assess changes in economic status, psychosocial status and empowerment among women who participated in Beyond Fistula reintegration programming following fistula repair. Methods: We conducted a retrospective study among 100 Beyond Fistula program participants capturing sociodemographic characteristics, obstetric and fistula history, program participation, and our primary outcomes: economic status, psychosocial status, and empowerment via quantitative survey at two time points: before program participation and currently. Data were collected from November 2020 to July 2021 from 2013 to 2019 program participants. We compared outcomes across these two time points using paired t tests or McNemar's tests. Results: The proportion of individuals owning property (28.0% vs. 38.0%, P = 0.006), having a current source of income (19.0% vs. 56.0%, P < 0.001), and saving or investing income (11.0% vs. 37.0%, P < 0.001) increased significantly from pre‐ to post‐programming. We also identified statistically significant increases from pre‐ to post‐programming in self‐esteem (5.0 [IQR 4.0–5.0] vs. 5.0 [IQR 5.0–5.0], P < 0.001), reintegration (53.0 [IQR 43.0–69.0] vs. 65.0 [IQR 51.0–72.0], P < 0.001) and level of input into household economic decision making (2.0 [SD 1.0] vs. 2.3 [SD 1.0], P = 0.004). Conclusion: Beyond Fistula programming likely improved economic status, psychosocial status, and empowerment of participants. Post‐surgical interventions incorporating a holistic approach can advance recovery through supporting psychosocial and economic wellbeing and should be offered to women undergoing genital fistula repair. Synopsis: A retrospective impact evaluation of the Beyond Fistula post‐surgical reintegration program in Kenya identified significant improvements in economic status, psychosocial status and empowerment. [ABSTRACT FROM AUTHOR]

The article discusses the impact of SEC regulation on crypto assets, specifically focusing on the collapse of the TerraLuna crypto asset ecosystem. It highlights the lack of government intervention and immediate recourse for investors, resulting in significant financial losses. The article provides an overview of the history and development of crypto assets, emphasizing their decentralized nature and growing acceptance by mainstream financial institutions. It acknowledges the regulatory challenges posed by the rapid growth of the crypto industry and the need for effective regulation. The article also discusses the SEC's attempts to regulate crypto assets through selective enforcement and the challenges faced by the industry in accepting traditional finance laws. It mentions recent court cases that have challenged the SEC's classification of crypto assets as securities and the need for a resolution on the regulatory status of crypto assets. The article concludes by recommending that courts follow the approach of the Terraform Labs case and properly apply the Howey test to protect investors. [Extracted from the article]

Copyright of Serbian Journal of Management is the property of Serbian Journal of Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data on the long-term and comprehensive cost of violence are essential for informed decision making regarding the future benefits of resources directed toward violence prevention. This review aimed to summarize original per-person estimates of the attributable cost of interpersonal violence to support public health economic research and decision making. In 2023, English-language peer-reviewed journal articles published in 2000–2022 with a focus on high-income countries reporting original per-person average cost of violence estimates were identified using index terms in multiple databases. Study contents, including violence type (e.g., adverse childhood experiences), timeline and payer cost perspective (e.g., hospitalization event-only healthcare payer cost), and associated per-person cost estimates, were summarized. Costs were in 2022 U.S. dollars. Per-person cost estimates related to adverse childhood experiences, community violence, sexual violence, intimate partner violence, homicide, firearm violence, youth violence, workplace violence, and bullying from 73 studies (majority focusing on the U.S.) were summarized. For example, among 23 studies with a focus on adverse childhood experiences, monetary estimates ranged from $390 for adverse childhood experience–related annual healthcare out-of-pocket costs per U.S. adult with ≥3 adverse childhood experiences to $20.2 million for the lifetime societal economic burden of a U.S. child maltreatment fatality. This review provides a descriptive summary of available per-person cost of violence estimates. Results can help public health professionals to describe the economic burden of violence, identify the best available estimate for a particular public health question, and address data gaps. Ultimately, understanding the long-term and comprehensive cost of violence is necessary to anticipate the economic benefits of prevention. [ABSTRACT FROM AUTHOR]

When decision makers use a financial approach to review the costs and benefits of new renewable energy projects, the economic value of changes in social welfare resulting from impacts on natural resources is not included in the analysis. Iceland's policy objective for carbon neutrality by 2040 will require constructing new power plants. This study aimed to estimate the economic preservation value for the Hólmsá and Tungufljót river basins in southern Iceland using the contingent valuation method. A web-based survey of Icelandic residents was conducted between 13 November 2022 and 19 December 2022 using a stratified random sample of 2909 adults. The response rate was 46.6%, with 35.1% of respondents indicating a willingness to pay (WTP) to protect the area from hydropower development. After excluding protest voters and accounting for those with and without WTP, the estimated mean WTP equaled ISK 5515. When scaled to the adult population of Icelandic residents, that equates to a total environmental and social cost of between ISK 1.52 and 1.70 billion. Compared to the estimated levelized cost of energy for the Hólmsárvirkjun at Atley hydropower project, this aggregation equates to an estimated 5.6% markup in total project costs, excluding transmission lines. Accounting for these economic costs in decision making allows for a more holistic understanding of new energy project costs and net present benefits. [ABSTRACT FROM AUTHOR]

The Consumer Price Index (CPI) is an indicator of inflation and is tracked by many government and economic agencies to make decisions of major importance. Its prediction is a valuable input into government policies such as taxation, and it greatly impacts the cost of borrowing money. The CPI has been traditionally predicted with statistical methods such as the Autoregressive Integrated Moving Average (ARIMA) model. In this paper, we forecast the Saudi Arabian Consumer Price Index with six machine learning (ML) methods, using the Orange 3 data mining and analytics tool, and based on the published historical January 2013 to November 2020 CPI data. We compare the performances of Decision Tree (Tree), k-Nearest Neighbors (kNN), Linear Regression (LR), Neural Networks (NN), Random Forest (RF), and Support Vector Machine (SVM), all applied to the 2013-2020 Saudi Arabian CPI dataset. Multiple experiments were conducted to vary the training and testing sets, optimize the machine learning parameters, and improve the MSE and R² metrics. The predicted CPI values of these ML methods were also compared to the 2021-2024 International Monetary Fund (IMF) CPI forecast and the actual 2021-2024 CPIs (post mortem). The results indicate that the multilayer perceptron neural network model outperforms the other ML models, is nearest to the actual CPI, and may be used to forecast the CPI for up to 3 years from the latest CPI data in the training dataset. The kNN model follows the neural network model in second place. The best fitting Excel trend line underperformed all ML methods in forecasting the Saudi Arabian CPI. [ABSTRACT FROM AUTHOR]

While the Consumer Price Index (CPI) has its flaws, I chose to analyze it rather than any other data because it is an essential component for both businesses and consumers to make informed economic decisions as it indicates the change in consumers purchasing power. It is a standard used to guide nationwide economic decisions of government, business, labor, and private citizens. This paper assesses how well ARIMA models perform in different economic regimes to give a historical factor to these functions. This is important because if one uses an ARIMA model to make forecasts, one needs to be aware of how it behaves in different market conditions. This is not a prediction, as the cluster year is required beforehand. This paper investigates different economic regimes using autoregressive integrated moving average (ARIMA) models and a K-means clustering model. In this paper, I utilized the K-means model to first identify clusters of similar years of data. Then, I was able to apply that information to the ARIMA model to compare actual and predicted economic data for similar years (determined by the K-means clustering). The reason for applying this model to years with the same cluster label was to avoid massive fluctuations in economic data across an expansive range of years (1922 to 2022) that might have confused the model. [ABSTRACT FROM AUTHOR]

Unemployment prediction is an important topic in economics and finance. The stock market is considered as one of the key indicators of economic performance. Therefore, using stock market data to predict unemployment is an interesting and valuable research area. In this paper, a neural network-based approach has been proposed for unemployment prediction using stock market data. Specifically, it uses a Recurrent Neural Network (RNN) architecture to model the time-series relationship between stock market data and unemployment rate. Moreover, S&P 500 index, the NASDAQ index, and the Dow Jones Industrial Average (DJIA) index are used as predictors for unemployment rate. The proposed model was trained and tested on historical data from 1990 to 2020. The experimental results showed that the proposed RNN model achieved an accuracy rate of 96.24% which outperformed the baseline model that used a simple linear regression algorithm. This result suggests that proposed RNN-based models provide accurate predictions of unemployment rates. Predicting unemployment rates accurately can help policymakers make informed decisions on economic policies and programs. Additionally, investors can use this prediction model to make informed decisions about their investment strategies in the stock market. [ABSTRACT FROM AUTHOR]

This study will discuss about the important issues related to balance of trade of Pakistan by covering the time period 2000 to 2023. It is analyzed that there is positive impact of market size and infrastructure on balance of trade of Pakistan in such a way that if market size which is used as proxy for Gross Domestic Product (GDP) will improve that will increase the production of goods and services and ultimately it will impact positively on balance of trade of Pakistan. In the same line if infrastructure will be improved then it will also support to balance of trade of Pakistan positively, whereas, the exchange rate is impacting negatively for balance of trade of Pakistan because it is analyzed to be under estimated or overestimated for the economy of Pakistan. The data is analyzed through error correction mechanism and co-integration after testing the stationarity of data. Few important policy directions are given on the basis of available data that described about core variables of economy that may impact in right direction for economic analysis of Pakistan. In addition to this the annual data is utilized for policy making in this research for the analysis. [ABSTRACT FROM AUTHOR]

This document, titled "Grassland Ecological Management and Utilization for Sustainability," provides an overview of research articles focused on grassland management and utilization. The articles are grouped into three categories: the management and utilization of traditional grasslands, the restoration and management of degraded grasslands, and shrub encroachment in grasslands. The document highlights various factors and strategies related to grassland species, production, grazing, nutrient management, and health evaluation. It emphasizes the importance of effective ecological management and sustainable utilization of grasslands for maintaining ecosystem services and long-term environmental sustainability. The authors conclude that innovative approaches, integrated land use planning, and collaborative models are necessary for the long-term sustainability of grasslands and pastures. [Extracted from the article]

This summary is about a special issue of the journal Europe-Asia Studies that focuses on the relationship between ideology and economic policy in the Soviet Union and post-Soviet Russia. The essays in the special issue explore various aspects of this relationship, including the impact of the Kosygin reforms, the Soviet Union's engagement with international finance, the adaptation of World Bank development policies, and the critique of "capitalist realism" in Russian studies. The essays highlight the complex and contingent nature of Soviet economic development and its connection to ideology and sovereignty. The special issue aims to contribute to the understanding of socialism and capitalism in the context of Soviet and post-Soviet Russia. [Extracted from the article]

Neoclassical economics has established itself as the discipline of rational choice. Consequently, under methodological individualism and in the context of consumption, an agent's choice is based on the ordering of preferences determined exogenously, disregarding any emotional, biological influences, or factors from socio-economic dynamics. Therefore, this paper aims to present an alternative framework for the decision-making of economic individuals at a theoretical and formal-mathematical level, grounded in the principles of evolutionary economics and complex adaptive systems. It is argued that the process of making choices in consumption is inherent to social dynamics. From an individual-holistic perspective, the mechanism motivating action can be characterized as an evolutionary algorithm that integrates biological, historical, cultural, social class, and market competition influences as endogenous elements in determining choice and consumption behavior. [ABSTRACT FROM AUTHOR]