This study examines the relationship between entrepreneurship and sustainable devel-opment in Saudi Arabia from 2006 to 2022, focusing on the economic, social, and en-vironmental dimensions. Using the Autoregressive Distributed Lag (ARDL) model, the research investigates both short-run and long-run dynamics to understand how entre-preneurial activities influence sustainable development within the framework of Saudi Arabia's Vision 2030 initiative. The findings indicate that entrepreneurship significantly contributes to economic growth through job creation and innovation, thereby aiding in the diversification of the economy away from oil dependency. Socially, entrepreneurial ini-tiatives have a positive impact on gender equality and social inclusion by empowering women and integrating youth into the labour market. Environmentally, entrepreneurship helps reduce carbon emissions and promotes sustainable business practices. Despite these positive outcomes, challenges such as regulatory barriers, limited access to finance, and the need for a supportive entrepreneurial ecosystem remain. Recommendations include enhancing entrepreneurial education, providing financial incentives, and streamlining regulatory processes to better support start-ups and SMEs. The study highlights the ne-cessity of addressing these challenges to fully realize the potential of entrepreneurship for sustainable development in Saudi Arabia. By providing empirical evidence on the sig-nificant role of entrepreneurship in driving sustainable development, this research offers actionable insights for policymakers aiming to foster a more resilient and diversified economy in line with Vision 2030. .

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this paper uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the differential impact of digital transformation on enterprise ESG performance, and further tests the mediating role of absorptive capacity and the moderating role of regional digital level. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; Secondly, there are significant differences in the impact of digital transformation on the ESG performance of enterprises in terms of property rights and industry characteristics. The ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation; Thirdly, absorptive capacity plays a mediating role between digital transformation and corporate ESG performance; Fourthly, the positive regulation of regional digital level promotes the ESG performance of enterprises through digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

This paper investigates the impact of debt financing on dividend payments when they face the agency costs of free cash flow. Focusing on a sample of 120 firms listed on the Saudi Stock Exchange during the period 2011-2021. The study found a negative association between agency cost of free cash flow and dividend payment. More importantly, our research highlights the significant role of long-term debt in making more prudent use of free cash flow. The obligation to meet interest and principal payments acts as an incentive for them to steer clear of unprofitable expenses and risky investments. Concurrently, long-term debt imposes restrictive clauses in debt contracts, such as minimum dividend distribution requirements, which further encourage higher dividend payments. Since interest and debt repayments are fixed obligations, using free cash flow for dividend disbursement is considered a more profitable and beneficial approach for shareholders in the context of Saudi Arabia.

This research investigates the intricate dynamics between intellectual Capital (VAIC) and the stability of banks in the evolving context of Saudi Arabia's banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pan-demic, the research provides a nuanced analysis of how intellectual capital and intellectual capital's components—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—affect the financial stability of Saudi banks. The research analyses a decade-long panel dataset from 2012 to 2022, utilizing both fixed effects and cross-section random effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual compo-nents present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies lev-erage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector's stability. It provides a foundation for ongoing research in this vital area.

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. The research uses advanced econometric methods, including the Autoregressive Distributed Lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. The findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. Oil revenues also play a critical role, reflecting the country's economic reliance on oil. The study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. These findings also support the importance of consistent and predictable income sources for sustaining consumption. Additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

This study delves into the intricate interplay of economic growth components, specifically focusing on Consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and cointegration techniques, we analyze the short- and long-term dynamics within the relationship of Consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables' causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight Consumption and investment's statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%.Moreover, the Granger causality study demonstrates unidirectional causal linkages between Consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private Consumption and fostering other facets of economic growth.

This study aims to explore the link between public investment and private investment in South Africa, using time series data spanning 40 years (1980–2020). Private investment is subdivided into credit to private sector (CPS) and foreign direct investment (FDI). Several econometric methodologies were used in the study, including the unit root test, cointegration test, and Error Correction Method (ECM). The Phillips-Perron (PP) test results point out that all the variables are stationary at levels with the exception of public investment (PI) which is stationary at first difference. The co-integration test reveals that the variables have a long-run equilibrium relationship. According to the findings of the ECM, public investment has a negative relationship with private investment (as measured by credit to private sector and foreign direct investment). The conclusion implies that in South Africa, public investment crowds out private investment. Other results revealed that, RGDP crowds in credit to private sector while crowding out foreign direct investment. Finally, the ECM findings show that government consumption expenditure crowds out credit to private sector and foreign direct investment. The residuals are homoskedastic and show no serial correlation, indicating that the model is adequate, according to the test for adequacy.

Under the new pattern of “double carbon” development, good ESG performance is the best way to promote the sustainable development of enterprises, and the ESG investment strategies are directly affected by the strategic vision of managers. Based on the upper echelons theory and stakeholder theory, this paper takes Chinese A-share listed companies from 2011 to 2022 as samples to empirically analyze the impact of managerial myopia on corporate ESG performance. The results show that managerial myopia significantly inhibits corporate ESG performance, mainly by inhibiting corporate green investment and green innovation sustainability. Furthermore, for state-owned enterprises (SOE), heavy polluting enterprises (HPE) and non-high-tech enterprises, the inhibitory effect of manager myopia on ESG performance is stronger. When the enterprise is in the growth stage, the above inhibition effect is more severe. For external governance, the greater the analyst attention and public environmental attention are, the more conducive they are to alleviating the restraining effect of managerial myopia on enterprise ESG performance. Therefore, effectively improving the time cognition level of managers and strengthening external supervision have become important measures for comprehensively optimizing the ESG performance.

Environmental, social, and governance (ESG) investment has become a common trend in capital markets, and many institutional investors have publicly declared their long-term ESG investment target (ESGIT). This study focuses on investors who conduct strategic asset allocation (SAA) using composite indices but establish their ESGIT outside the SAA process. A mismatch could arise between investors’ planned and actual portfolios because they must pursue their ESGIT by asset selection, which inevitably makes the constituents of their portfolios different from those of composite indices. To scrutinize the potential existence of a misalignment between their SAA and ESGIT, this study analyzes actual stock and bond indices over the past decade using traditional mean-variance optimization. The results reveal significant differences between the expected and realized performances, and the misalignment is more significant when the analysis period is divided into two sub-periods: stable and volatile. Specifically, the results indicate that the efficient frontier constructed using ESG indices significantly differs from that constructed using composite indices, and that the difference between these two efficient frontiers becomes more significant during volatile periods. Furthermore, the results show that investors cannot meet their targets if their ESGIT is established outside the SAA process.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

This study examines whether government spending efficiency is associated with differential effects of public investment on debt-to-GDP ratio for a panel data consisting of 16 developing countries in Asia-Pacific region over the period 2007-2017. Public investment is central to implementing the UN 2030 Agenda for Sustainable Development — but high debt-to-GDP ratio poses a key risk. The empirical results indicate that public investment efficiency moderates debt-to-GDP ratio whereas public investment in the midst of public sector corruption accentuates debt-to-GDP ratio. The results have important policy implications.

This review examines the quality of capital investment. It explores the essential components and analysis involved in financially assessing an engineering project, including an assessment of various associated risks. Additionally, the review delves into the historical progression of current capital budgeting practices and surveys academic research in the field. The evaluation of investments has been a recognized challenge for the past thirty years, but it has recently gained renewed attention from both management and scholars. Investments constitute a significant and growing portion of organizations’ capital expenditures. However, assessing the impact of investments on pursued goals is challenging. Consequently, there is a strong demand for methods and techniques that can aid in evaluating investments during the proposal stage. This paper explores several investment strategies and Examines the criteria for investment.

Landraces are considered a crucial component of biodiversity conservation, serving as a reservoir of genetic diversity. Consequently, the collection, cultivation and detailed characterization of such landraces constitute an inherent aspect of the world’s natural resource heritage. This effort holds promise for the development of elite varieties capable of thriving amidst continuous global climate fluctuations. In this context, we conducted a comprehensive assessment of the main agronomic attributes, physico-chemical properties, and functional quality traits of the major hot pepper landraces adapted to diverse climatic conditions in Tunisia. These landraces include ‘Dhirat’, ‘Semmane’, ‘Beldi’, ‘Nabeul’, ‘Jerid’, ‘Mahdia’, ‘Cayenne’, ‘Kairouan’ and ‘Baklouti’. Most of the pepper landraces exhibited satisfactory yields, ranging from 1163.25 to 1841.67 g plant-1 in ‘Jerid’ and ‘Kairouan’, respectively, indicating robust productivity, especially under prevailing climatic changes and high temperatures. Landraces such as ‘Baklouti’, ‘Beldi’, ‘Nabeul’, ‘Semmane’, ‘Kairouan’ and ‘Mahdia’ appear suitable for both fresh consumption and processing, owing to their favorable average fruit weight and soluble solids content. Functional quality and the levels of antioxidants, as well as radical scavenging activity, emerged as key discriminating factors among pepper landraces. Irrespective of genotype, capsaicin and dihydrocapsaicin constituted the major capsaicinoids, accounting for at least 87% of the total. Total capsaicinoids ranged from 1.81 µg g−1 to 193.71 µg g−1, with ‘Baklouti’ and ‘Jerid’ identified as the most pungent landraces. Total carotenoids ranged from 45.94 µg g−1 to 174.52 µg g−1 with ‘Semmane and ‘Jerid’ exhibiting the highest levels. Considerable variation was observed in β-carotene content, spanning from 3% to 24% of the total carotenoids. α-Tocopherol content ranged from 19.03 µg g-1 fw in ‘Kair-ouan’ to 30.93 µg g-1 fw in ‘Beldi’, exerting a notable influence on the overall tocopherol content. Conversely, the other isomers were detected at very low concentrations. The total vitamin C content ranged from 132 mg 100g-1 fw in ‘Mahdia’ to 200 mg 100 g-1 fw in ‘Nabeul’, indicating relatively low genetic variability. However, large variability was detected in total phenolics content, ranging from 168.58 mg GAE kg-1 fw in ‘Beldi ‘to 302.98 mg GAE kg-1 fw in ‘Cayenne’. Among the pepper landraces tested, ‘Cayenne’ achieved the highest value of radical scavenging activity in both hydrophilic and lipophilic fractions (RSAHF and RSALF), with variations rang-ing from 59% to 120% for RSAHF and from 4% to 64% for RSALF. This study aims to: 1) preserve and enhance the value of local genetic resources, 2) identify desiderable traits for incorporation into breeding programs, and 3) develop high-quality, high-yielding cultivars capable of with-standing climate variations.

Background: Nowadays vital signs in clinics are electronically monitored excepted for urine output which still requires, manual recording, which is subject to human errors. We, in-vitro, assessed in this study the ability a novel electronic device to measure by a combination of two different methods, the real time flow-output, like urine output. Methods: Flow or urine output was measured by a combination technique of gravimetry using a dynamometer and capacitive sensing to improve precision. Data were obtained in 3 different situations, low, medium, and high flow. Results: Three different situations were tested: full or empty dead space and Pasteur’s chamber. The differences between the injected and measured volume varies from 0 to 5 ml representing a maximal error of 3 % regardless of the volume injected and the flow in ml/hour. The capacitive sensors behave as expected with a parallel curve of the expected and measured flow. Conclusion: We have shown in this in-vitro study that the combination of gravimetry and capacitive sensors analysis allow accurate measurement of volume and flow-output. Clinical trials should be conducted to confirm its usefulness in urine output measurement in the real life.

Colours are important features in human and natural environments and are related to several psychological functions. However, a possible relation between colour preferences and personality traits is scarcely investigated. The aim of the present study was to find out whether differences in preferences for colours also reflected differences in Big Five personality traits. The sample consisted of 206 individuals voluntarily recruited from a student sample. The participants chose one of six primary colours (blue, green, red, yellow, black, white) from the Natural Colour System (NCS) as their favorite colour. Personality traits were measured with the Big Five Inventory-44 (BFI-44. Blue and yellow was the most and least preferred chromatic colour, respectively. There were no gender differences in preferences for the chromatic colours, but more women preferred white and men preferred black. Compared to the rest of the sample, the blue group had higher scores on agreeableness and extraversion, and the red group had lower scores on agreeableness. Pairwise comparisons showed that the blue group had higher scores on agreeableness and extraversion than the red group, and higher scores on agreeableness compared to the green group. There were no significant personality differences for the other chromatic and achromatic colour groups.

To support the decision making process of new investors, this paper aims to implement Machine Learning algorithms to generate investment indications. Three artificial intelligence techniques were implemented, namely: Multilayer Perceptron, Logistic Regression and Decision Tree, which performed the classification of investments. The results of the different algorithms were compared to each other using the metrics: accuracy, precision, recall, and F1-score. The Decision Tree was the algorithm that obtained the best classification metrics and an accuracy of 77%.

Insulin-like Growth Factor 2 mRNA binding Protein 1 (IGF2BP1) is a promising candidate gene for influencing economic traits in livestock and poultry. The second intronic region of IGF2BP1 is closely related to growth traits, although the exact mechanism remains unclear. The preliminary resequencing results of goats in our laboratory demonstrated that the IGF2BP1 gene region was subject to strong selection, then we selected multiple single nucleotide polymorphisms (SNPs) to identify. Seven SNPs were located in the conserved region of the second intron, and their functions and relationship with growth traits require further clarification. This study selected 348 Nanjiang Yellow goats as experimental subjects, and chose Time of Flight Mass Spectrometer (MALDI-TOF) as the main method. Our results showed that six SNPs were significantly correlated with the growth traits of the Nanjiang yellow goat by association analysis. Among them, the rs652062749(A>G) was identified as the primary locus affecting the later stage of growth traits of Nanjiang yellow goat. Moreover, there was a strong linkage among three SNPs, and the rs638185407 (T>A) mutant type was observed to increase the luciferase activity in H293T cells extremely significantly. The TTAACT, TTCCCC, and ATCACT combination genotypes were dominant combination genotypes, which provided theoretical references for further genetic co-breeding. The results of our study demonstrate the potential role of the IGF2BP1 gene as a functional genetic marker in the breeding programs of Nanjiang Yellow goats.

This paper discusses corporate taxes and Foreign Direct Investment (FDI) in Nigeria. It is a review of literature that attempts to explore and give a reality on the response of FDI to corporate taxes. This paper shows in its introductory phase a prior discussion of the terms corporate tax and FDI and also elements of both terms and classifications. It follows with issues such as the effects of corporate taxes on FDI. This paper discusses the rhetoric whether reduced corporate taxes and other tax incentives has an effect on the inflow of FDI in Nigeria. To answer this question, the paper utilised information gathered from secondary sources including books, newspapers publications, working papers and research findings from studies. This paper shows that from surveyed empirical studies corporate taxes may have an important role in attracting FDI and have a rising effect on the development of the country, and as such recommends that tax incentives should be employed as a means to attracting FDI, a cost benefit analysis should be employed on the types of corporate taxes to determine the benefit from the perceived FDI inflow, in addition a review of the current tax policies should be carried out as they seem not to respond to the current economic situation.

This paper analyzes the causal effect between domestic private investment, public investment, foreign direct investment and economic growth in Tanzania during the 1970-2014 period. The modified neo-classical growth model is used to estimate the ieffect of investment on economic growth. Also, the economic growth models based on Phetsavong and Ichihashi (2012) [1], and Le and Suruga (2005) [2]are used to estimate the crowding out effect of public investment on domestic private investment on one hand and foreign direct investment on the other hand. In the same way, the crowding out effect of foreign direct investment on domestic private investment is estimated. A correlation test is applied to check the correlation among independent variables, and the results show that there is very low correlation suggesting that multicollinearity is not a serious problem. Moreover, the diagnostic tests including RESET regression errors specification test, Breusch-Godfrey serial correlation LM test, Jacque-Bera-normality test and white heteroskedasticity test reveal that the model has no signs of misspecification and that, the residuals are serially uncorrelated, normally distributed and homoskedastic. Broadly, the empirical results show that the domestic private investment and foreign direct investment play an important role in economic growth in Tanzania. Besides, a revealed negative, albeit weak, association between public and private investment suggests that the positive effect of domestic private investment on economic growth becomes smaller when public investment-to-GDP ratio exceeds 8-10 percent. Similarly, foreign direct investment tends to marginally reduce the impact of domestic private investment on growth. These results suggest that public investment and foreign direct investment need to be considered carefully in order to avoid a reduced positive impact of domestic private investment on growth. Domestic saving may be promoted to encourage domestic investment for economic growth.

Dearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava in Sierra Leone. This study aimed at assessing the genetic variability and relationships within 103 cassava genotypes using agro-morphological and culinary markers. A field trial was conducted in the School of Agriculture and Food Sciences research site. The experiment was laid in an augmented randomized block design. Morphological classification based on qualitative and quantitative traits categorized the germplasm into three different groups. A total of ten principal components (PCs) in the qualitative and six PCs in the quantitative trait sets accounted for 66.74% and 67.27% of the total genetic variation, respectively. Traits with significantly strong and positive correlations included presence of fruit (PFRT) and presence of seed (PSE)(r = 0.86***),root yield per plant (RYPP) and number of storage root (NSR) (r = 0.76***), RYPP and number of commercial root (NCR) (r = 0.68***), length of leaf lobe (LLL) and width of leaf lobe (WLL) (r = 0.66***),and between NSR and NCR (0.84***). Cooking time, cooking percentage, texture, mealiness, taste and aroma varied widely among the accessions. Findings established that the cassava germplasm possess useful genetic variability that could be exploited through selection for short term release programme, genetic conservation of valuable germplasm and genetic improvement of the crop.

The aim of this study is to empirically examine the link between foreign direct investment (FDI) and domestic investment (DI) in South Africa over the period of 41 years (1975-2016). Accurately, it attempts to determine whether FDI crowds in or crowds out DI in South Africa. DI is sub-divided into private domestic investment (credit to domestic private sector) and public corporation investment (state owned enterprises). We used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) technique to ascertain long run and short run effects concurrently after establishing that the variables were stationary (using the PP test). The results of the unit root test shows that all variables are integrated of order zero I(0) or integrated of order one I(1), indicating that the series of variables are stationary in the level or first difference form. The findings revealed that variables are cointegrated in the long run. The ARDL model found a negative link between FDI and domestic investment. The result implies that FDI crowds out domestic investment. Moreover, the long run estimate revealed that domestic investment is crowded in by government investment expenditure (GINV). Other findings uncovered that, GDP crowds out private domestic investment while crowding in public corporation investment. Moreover, the long run estimate revealed that domestic investment is crowded in by gross domestic savings (SAV). On the other hand, the real exchange rate (EXCR) crowds out private domestic investment while crowding in public corporation investment. Trade openness (TRA) crowds out domestic investment. Additionally, the short run estimate uncovered that private domestic investment is crowded out by FDI, EXCR, and TRA whereas GINV, GDP and SAV is crowding in private domestic investment. Other findings discovered that, in the short run, public corporation investment is crowded out by FDI, GDP, EXCR and TRA, while GINV and SAV crowd in public corporation investment. The CUSUM confirms that the models are structurally firmness.

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

This study investigated interactions between sugar-related dietary patterns (DP), personality traits, cognitive-behavioural, and emotional functioning. The study involved females aged 18-54. Data were collected between the Winter and Spring of 2020/21. The survey was conducted using anonymized questionnaires. The Ten-Item Personality Inventory (TIPI) was used to examine personality traits based on the Big Five Personality Trait Model. Three-Factor Eating Questionnaire (TFEQ) was used to measure eating behaviours: cogni-tive restraint (CR), uncontrolled eating (UE), and emotional eating (EE). The KomPAN question-naire collected the frequency of intake. Dietary patterns (DPs) were derived by principal component analysis (PCA). A logistic regression (OR) was applied to verify the association between the DPs, personality traits, cognitive-behavioural and emotional functioning. Three DPs were identified: sweet-western (SWDP), pro-healthy (PHDP) and dairy (DDP). Women with high conscientiousness were less likely, by 33%, to adhere to the upper tercile of SWDP and 80% more likely to the upper tercile of PHDP. Elevated CR intensity increased by almost 2-fold (OR: 1.93; p

This study examines the impact of executives implicated in fraud on firms' investment decisions using AAERs in the US, aiming to address the underexplored aspect of rationalization within the fraud triangle. Executives implicated in fraud often display abnormal attitudes to justify accounting irregularities, prompting an investigation into how abnormal investment decisions are used for rationalizing fraud, given their critical role in a firm's long-term sustainability. Analysis of AAERs spanning from 1981 to 2013 reveals that implicated executives, particularly CEOs and CFOs, tend to make abnormal investment decisions, and that collusive fraud exacerbates this behavior. Notably, such executives lean towards overinvestment, particularly in R&D expenditures, to hide or justify fraud; the duration of fraud amplifies its impact on investment decisions. By shedding light on the rationalization aspect of the fraud triangle, this research contributes valuable insights for investors, regulators, and academia emphasizing the significance of public disclosure of fraud to enhance transparency in capital markets and the importance of ethics-focused education in accounting to prevent corporate fraud.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

This paper studies a model of dynamic compensation and capital structure with managerial traits. We show that Optimistic manager perceives equity as more undervalued than debt, while, confident manager perceives debt as more undervalued than equity. Managerial risk aversion mitigates manager’s bias. The risk aversion of the optimistic manager has a convex effect on the optimal coupon. There exists the level of risk aversion eliminating the bias on the leverage. The managerial optimist has an ambiguous effect on the owner’s bankruptcy level. The risk aversion has a convex effect on the owner’s bankruptcy level. The optimistic/confident manager underestimates the credit spread. The risk aversion has convex effect on the credit spread. In contrast to rational manager, the optimistic/confident manger has higher level of effort. The risk aversion has a negative effect on the effort.

Companion animals play a central role in many families and are especially valued by those who are socially isolated. Crisis situations such as acute hospitalizations, homelessness and natural disasters can make it difficult to preserve the human-animal bond and can result in animals being surrendered or euthanized. Social support programs like the RSPCA NSW Emergency Boarding and Homelessness program support people experiencing crisis situations with emergency pet boarding, access veterinary treatment and individualized case management. This study aimed to estimate the social return on investment (SROI) for this program using standard SROI methodology. In-depth interviews were conducted with 13 program stakeholders and questionnaire responses were received from 29 program clients. Outcomes were quantified for four stakeholder groups: program clients, client’s animals, RSPCA Inspectors, animal pounds and shelters. Clients and their animals experienced the bulk of the benefit from the program, estimated to have a combined value of over $5 million AUD for the 2020-21 financial year. The estimated social return on investment was $8.21 for each $1 invested. The study demonstrates that keeping people together with their companion animals, or ensuring they are reunited as soon as possible, can reduce stressors, and improve outcomes for people and animals.

Academic and corporate research has been focusing on analyzing stock performances, financial markets, and investment strategies for decades. According to Lynch and Rothchild (1989), certain investments can be described as plays. In this work, the authors use the term for investments in value stocks, spin-offs, and turnarounds to analyze the long-term stock performance and risk-adjusted excess returns of up to five years for those stocks. Additionally, stocks with a supe-rior return performance are identified within an investment play based on low P/E and P/B mul-tiples. The study finds that value stocks, spin-offs, and turnarounds outperform the S&P 500 on average on a one-, three- and five-year investment horizon. The analysis of the three investment plays confirms earlier studies that investment plays constitute a profitable investment opportunity. Moreover, the research exemplifies that private investors could achieve an excess return (alpha) through a passive buy-and-hold investment strategy. Overall, the analysis provides a deeper in-sight into the long-term performance of value stocks, spin-offs, and turnarounds.

Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

. In this article, a search for a calculation method and an analysis of performance indicators of mutual investment funds is carried out. Many factors can influence the return on investments in portfolio investments, which makes the choice of the fund incredibly difficult. However, in addition to the fact that it is difficult to determine which indicators should be given more attention and which should be omitted, it is not so easy to get these data. Some of them are publicly available on the Internet, while others can only be found in trading systems that are not accessible to people outside of this area. The article proves that a well-trained neural network can easily find existing patterns between risk and expected return on investment. It is a well-trained neural network that provides the ability to use the "what-if" function to justify your choice on real factors, as well as the ability to download available data and calculate the estimated income and its changes. This makes it much easier to choose a Fund, especially for inexperienced investors. The article also presents the results of a study of the dependence of estimated income on correlation, standard deviation, and volatility using a trained neural network. According to the theory, higher values of these three factors correspond to a higher amount of income. The obtained graphs of the calculated income dependence on correlation, standard deviation, and volatility confirmed the correctness of the neural network training and compliance with the relations described in the theory. The paper presents graphs of the dependence of the estimated income on the beta and alpha coefficients. The higher the beta and alpha indicators, the higher the expected return on investment. This corresponds to the dependency accepted in the model. When the values of the beta and alpha coefficients increase, the income also increases, which is completely consistent with the theory.

In this article, a search for a calculation method and an analysis of performance indicators of mutual investment funds is carried out. Many factors can influence the return on investments in portfolio investments, which makes the choice of the fund incredibly difficult. However, in addition to the fact that it is difficult to determine which indicators should be given more attention and which should be omitted, it is not so easy to get these data. Some of them are publicly available on the Internet, while others can only be found in trading systems that are not accessible to people outside of this area. The article proves that a well-trained neural network can easily find existing patterns between risk and expected return on investment. It is a well-trained neural network that provides the ability to use the "what-if" function to justify your choice on real factors, as well as the ability to download available data and calculate the estimated income and its changes. This makes it much easier to choose a Fund, especially for inexperienced investors. The article also presents the results of a study of the dependence of estimated income on correlation, standard deviation, and volatility using a trained neural network. According to the theory, higher values of these three factors correspond to a higher amount of income. The obtained graphs of the calculated income dependence on correlation, standard deviation, and volatility confirmed the correctness of the neural network training and compliance with the relations described in the theory. The paper presents graphs of the dependence of the estimated income on the beta and alpha coefficients. The higher the beta and alpha indicators, the higher the expected return on investment. This corresponds to the dependency accepted in the model. When the values of the beta and alpha coefficients increase, the income also increases, which is completely consistent with the theory.

The structure and diversity of tropical vegetation are shaped by biotic and abiotic factors, which function as environmental filters affecting plant performance in different spatial and temporal scales. We compared soil traits, vegetation structure and leaf traits (i.e., specific leaf area, polyphenols and chlorophyll content a/b and total) in early, intermediate and late successional stages of a tropical dry forests in southeastern Brazil. For this purpose, we measured leaf traits of the most abundant species in the same 18 plots (50 x 20m/ six per successional stage) in 2009 and 2018. We tested whether tree species growing in early forests have a greater investment in conservative traits related to chemical defenses and tolerance to desiccation compared to late-stage tree species. We observed contrasting results when comparing the chronosequence differences in leaf traits both in 2009 and 2018 and the temporal changes along this period. Specific leaf area was lower than expected for all successional stages while polyphenol content increased along time, contrary to other studies in tropical dry forests. These results suggest that contrasting environmental conditions such as soil water holding capacity and light availability are responsible of the observed pattern. Total chlorophyll content increase lightly, while the a/b chlorophyll ratio doubled in all successional stages, contrary to our hypothesis. Therefore, we suggest that the conservative-acquisitive spectrum in successional gradients of TDFs should be further investigated for a better understanding of plant community assemblages.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p < 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p < 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

Quinoa is a resilient crop known for its adaptability to diverse environmental conditions. This study examined the agronomic performance and ecological adaptability of quinoa across four distinct altitudes in the northwestern regions of China. Six quinoa genotypes were assessed for agronomic traits, phenology and yield performances, and nutritional quality characteristics in Yining city, Nilka County, Tekes County and Zhaosu County under varied environmental conditions. Our findings demonstrate significant variations in all measured traits including agronomic and nutritional quality traits across the various altitudes and genotypes. In Yining City, a warmer and lower altitude area, genotypes exhibit superior traits for fodder production, including increased branches, longer panicles, robust stems, and high seed protein content. Genotypes Jinli 1 and Beijing 2 achieve yields exceeding 3 tons per hectare (T/ha), highlighting the region’s productivity. Nilka and Tekes counties boasted the shortest quinoa crop cycles, with Jinli 1 yielding 4.05 T/ha seeds in Tekes County, exhibiting high protein and fat content alongside low saponins, making it prime location for yield production. Zhaosu County, with its cooler climate and fertile chernozem soil, elicited high 1000 seed weight and more robust protein response than Nilka and Tekes counties, illustrating the impact of soil fertility on nutritional composition. Correlation analyses further elucidated that the plants characterized by shorter flowering times, crop cycles, compact inflorescence, and taller heights exhibited superior seed yields. Our study contributes significant insights into the ecological adaptability and nutritional dynamics of quinoa, with implications for sustainable crop production and food security in diverse agroecosystems.

Wheat is used for making many food products due to its diverse quality profile found among different wheat classes. Since laboratory analysis of these end-use quality traits is costly and time-consuming, genetic dissection of the traits is preferential. This study used a genome-wide association study (GWAS) of 10 end-use quality traits, including kernel protein, flour protein, flour yield, softness equivalence, solvent’s retention capacity, cookie diameter, and top-grain, in soft red winter wheat (SRWW) adapted to US southeast. The GWAS study included 266 SRWW genotypes that were evaluated in two locations over two years (2020-2022). A total of 27,466 single nucleotide markers were used and a total of 80 significant marker-trait associations were identified. There were 13 major effect quantitative trait loci (QTLs) explaining > 10% phenotypic variance out of which 12 were considered as novel. Five of the major effect QTLs were found to be stably expressed across multiple datasets, and four showed associations with multiple traits. Candidate genes were identified for eight of the major-effect QTLs including genes associated with starch biosynthesis and nutritional homeostasis in plants. These findings increase genetic comprehension of these end-use quality traits and could potentially be used for improving the quality of SRWW.

This paper investigates portfolio optimization methodologies and short-term investment strate-gies in the context of the cryptocurrency market, focusing on ten major cryptocurrencies from January 2020 to November 2023. We employ high frequency data and utilize the Kurtosis Mini-mization methodology, alongside other optimization strategies, to construct and evaluate port-folios under different rebalancing frequencies. The empirical analysis reveals that cryptocurren-cies exhibit significant volatility, skewness, and kurtosis, necessitating sophisticated portfolio management techniques. We find that the Kurtosis Minimization methodology consistently outperforms other optimization strategies, delivering optimal returns to investors, particularly in shorter-term investment horizons. We demonstrate the diversification benefits of integrating cryptocurrencies into multi-asset portfolios and emphasize the importance of regular portfolio rebalancing in the volatile cryptocurrency market. Our findings offer insights for portfolio man-agers and investors seeking to optimize their investment outcomes in the cryptocurrency market, highlighting the importance of risk management, diversification, and dynamic portfolio man-agement strategies.

There are many modern and traditional methods in valuing the performance of the company among them EVA, CVA are modern methods where as EPS, ROI, ROE etc. are some of the traditional methods. modern and traditional methods are not only used to check the performance of a company but it also used in investment decisions by the investors. Stern Stewart, managing partner of M/s Stern Stewart & Co. introduced a modified concept of economic profit in 1990 in the name of Economic Value Added (EVA) as measure of business performance and CVA is only a cash consideration in EVA. In this paper an attempt is made to study which method is used by the investors while taking the investment decisions i.e. traditional methods are modern methods. 100 respondents (Investors) are questioned and collected their views, we are assuming that there is no impact of traditional or modern methods while taking investment decisions by the investors.

In this paper, we investigate the proftability of investing in movies for retail investors, focusing on the return on investment (ROI) metric, which is calculated as revenue divided by budget. Our analysis encompasses 5000 movies from the movie database TMDB, examining factors such as production scale, genres, key actors, directors, and more. Additionally, we employ textual analysis techniques like Latent Semantic Analysis (LSA) on movie overviews and tags to incorporate movie themes. We then evaluate various supervised classifcation models including Logistic Regression, Random Forest, and Light Gradient Boosting (LightGBM), comparing their performance. Our fndings highlight the signifcance of production scale, team structure, and movie themes in identifying potential high-return opportunities for investors.

The digital economy is a fundamental feature of sustainability. The economic, social, and environmental dimensions of sustainability stand up for digitalization and digital transformation projects. In order to understand and practice the digital economy, the goal of our paper is to evaluate accurate variables regarding fintech scope for discussing the efficient implication of these projects. The principal component analysis is used to investigate and evaluate the sustainable digital economy indicators. An empirical case from health care services in Africa from World Bank projects discusses this challenge. Results help produce an effective understanding of how the digital economy enables facing fintech challenges in Africa.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Bacterial endophytes (120) were isolated from six halophytes (Distichlis spicata, Cynodon dactylon, Eragrostis obtusiflora, Suaeda torreyana, Kochia scoparia, and Baccharis salicifolia). These halophiles were molecularly identified and characterized with or without NaCl conditions. Characterization was based on tests such as indole acetic acid (IAA), exopolysaccharides (EPS), and siderophores (SID) production; solubilization of phosphate (P), potassium (K), zinc (Zn), and manganese (Mn); mineralization of phytate; enzymatic activity (acid and alkaline phosphatase, phytases, xylanases, and chitinases) and mineralization/solubilization mechanisms involved (organic acids and sugars). Eleven halophiles (tolerated NaCl 2.5 M) were identified as Oceanobacillus sp. (1), Bacillus sp. (2), Nesterenkonia sp. (3), Bacillus velezensis (4), Halobacillus sp. (5), Oceanobacillus sp. (6), B. velezensis (7) Halomonas sp. (8), B. pumilus (9), Pseudomonas sp. (10) and Oceanobacillus sp. (11). Biochemical responses of nutrient solubilization and enzymatic activity varied between bacteria and the presence of NaCl. Organic acids were involved in P-mineralization and nutrient solubilization. Tartaric acid was common in the solubilization of P, Zn, and K. Maleic and vanillic acid were only detected in Zn and K solubilization, respectively. Moreover, sugars appeared to be involved in the solubilization of nutrients; fructose was detected in solubilization tests. Therefore, these bacteria should be tested as a consortium to mitigate saline stress in glycophytes under a global climate change scheme that threatens to exacerbate soil salinity.

In this paper, we extend the Merton model of investment in discrete time to the cases when there is a finite number of investors and the market is with frictions represented by convex penalty functions defined for each investor. In the main result of this paper, we proved the existence of optimal strategy of investment by using a new approach based on the formulation of an equivalent general equilibrium economy model.

The present paper investigates the effect of poverty on foreign direct investment (FDI) inflows in developing countries. It complements the important extant literature on the effect of FDI inflows on poverty by examining the issue the other way around. The analysis is conducted using a sample of 117 countries over the period 1980-2017, and the two-step system Generalized Methods of Moments (GMM) technique. It has relied on two indicators of poverty, namely poverty headcount ratio and poverty gap. Findings indicate that over the full sample, poverty influences negatively FDI inflows, including through its adverse effect on human capital (that is, both education and health). Unsurprisingly, low-income countries (considered as poorest countries in the full sample) experience a higher negative effect of poverty on FDI inflows than other countries. On another note, participation in international trade matters for the effect of poverty on FDI inflows. In fact, an increase in poverty levels results in lower FDI inflows in countries that experience low workers' productivity, a less developed financial sector, and a low level of infrastructure development. Furthermore, the effect of poverty on FDI inflows does not depend on the prevailing economic growth rate. Finally, the analysis has revealed the existence of a non-linear effect of poverty on FDI inflows for the poverty headcount indicator, but not for the poverty gap indicator. The non-linear effect of poverty headcount on FDI inflows is such that a rise in poverty headcount ratio results in lower FDI inflows, but an additional increase in poverty more than further discourages FDI inflows. The conclusion discusses the implications of these findings.

Background: Evidence suggests that there is substantial comorbidity between fibromyalgia and Axis II pathology (i.e., personality disorders - PDs). The aim of the current study was to find out the exact cluster (A, B, C) PDs or traits that are more prominent in FM and may be predictors of FM diagnosis. Methods: Data from 86 subjects (53 with FM and 33 controls without FM) was analyzed in an observational, cross-sectional, comparative study. The assessment of categorical PDs and traits was performed independently with the Structured Clinical Interview for Personality Disorders (SCID-II). Binary logistic regression was used to determine FM predictors among PDs traits. Results. Compared with controls, FM patients had higher rate of PDs diagnoses (56.7 vs 18.2%, P<.001). However, the rate was significantly higher only for borderline PD diagnosis (28.3% vs 6.1% P<.05). The binary logistic regression analysis showed that schizotypal and schizoid (cluster A), borderline (cluster B), and dependent (cluster C) personality traits may be significant predictors of fibromyalgia (Nagelkerke R2 = 0.415). Conclusions: Our results may reflect association of FM with personality traits of all three PD clusters: A (eccentric), B (dramatic), C (anxious). However, the most consistent evidence seems to be for borderline PD.

The high genetic diversity of the tomato and its high micronutrient content make this fruit very interesting from an economic and nutritional point of view. The genetic erosion suffered by this crop, due to breeding objectives based on yield and marketing, makes it necessary to return to the origins in search of the nutritional and organoleptic quality lost in traditional varieties. In this study, the agronomic, physical, organoleptic and nutritional characteristics of eighteen F1 hybrids obtained by crossing fourteen traditional varieties, previously selected for their quality, were studied to select genotypes of superior quality that could be candidates for new. All parameters studied were strongly influenced by genotype, showing a wide range between cultivars. Principal Component Analysis revealed the characteristics of each hybrid that made it stand out from the others. Some hybrids (H3, H4, and H6) stand out because of their high concentration of active compounds, others (H16, H15, H10, H17, H9, and H11) because of agronomic performance and high content of β-carotene, and H5 was the only one to contain chlorophyll in their ripe fruits. Finally, the evaluation index allowed the selection of five hybrids with interesting characteristics, combining good yield performance and high quality

Global warming caused by climate change is a challenge for dairy farming, especially in sub-Saharan countries. Under high temperature and relative humidity dairy cows suffer from heat stress. The objective of this study was to investigate the effects and relationship of heat stress (HS) measured by temperature-humidity index (THI) on physiological parameters and milk yield and composition of lactating Holstein Friesian crosses reared in the humid coastal region of Tanzania. A total of 29 lactating Holstein Friesian x Zebu crossbred dairy cattle with 50% (HF50) and 75% (HF75) Holstein Friesian blood levels in their second and third month of lactation were used. Breed composition of Holstein Friesian was determined based on animal recording system used at the Tanzania Livestock Research Institute (TALIRI), Tanga. Data collected included daily temperature, relative humidity, daily milk yield, and physiological parameters (core-body temperature, rectal temperature, respiration rate, and panting score). The THI was calculated using the equation of National Research Council [39]. The THI values were categorized into three classes i.e. low THI (76-78), moderate THI (79-81) and high THI (82-84). The effects of THI on physiological parameters and milk yield and composition were assessed. Also, the effects of genotype, parity, lactation month, and interaction of these parameters with THI i on milk yield, milk composition, and physiological parameters were investigated. The results indicate that THI and its interaction with genotypes, parity, and lactation month had highly significant effect on all the parameters. THI affected (P ˂ 0.05) average daily milk yield and milk fat %, protein %, lactose %, and solids – not – fat %. When THI increased from moderate to high values, average daily milk yield declined from 3.49 ± 0.04 to 3.43 ± 0.05 liters/day while fat % increased from 2.66 ± 0.05% to 3.04 ± 0.06% and protein decreased from 3.15 ± 0.02% to 3.13 ± 0.03%. No decline was observed on lactose % whilst solids – not – fat % declined from 8.56 ± 0.08% to 8.55 ± 0.10%, when the THI values increased from moderate to high. Also, THI affected (P˂0.05) physiological parameters. Core-body temperature (CBT), rectal temperature (RT), respiration rate (RR) and panting score (PS) increased from 35.60 ± 0.01 to 36.00 ± 0.01oC, 38.03 ± 0.02 to 38.3.30 ± 0.02oC, 62.53 ± 0.29 to 72.35 ± 0.28 breaths/min and 1.35 ± 0.01 to 1.47 ± 0.09, respectively, when THI increased from low to high. THI showed a low positive correlation with average daily milk yield and fat percentage whilst protein, lactose, and solids – not - fat percentages showed negative relationships with THI (P ≤ 0.05). The CBT, RT, RR, and PS showed positive relationships (P ≤ 0.05) with THI. These negative relationships indicate that there is an antagonistic correlation between sensitivity to HS and degree of production. It is concluded that the THI, genotype, parity, and lactation month, and their interactions with THI significantly affected milk yield, milk composition, and physiological parameters of lactating Holstein Friesian dairy crosses at THI thresholds ranging from 77 to 84.

Abstract. Background: This paper investigates the propagation of behaviorally transmitted traits with negative effect on host fitness. Methods: We analyze equilibrium between genetically transmitted and behaviorally transmitted competing propagators and consider whether a behavioral propagator is linked to reproduction (e.g. vertical culture transmission), or not. We employ combined genetic and behavior-induced fitness components for hosts, while behavioral propagators have replication factors to distinguish from what’s good for the host (fitness). Results: A trait which spreads faster than its marginal host fitness contribution reduces population will establish itself. The often transient nature of laterally transmitted traits may be a defense against accumulation of deleterious traits. Laterally transmitted traits with high spreading rate often do not equalize with genetic traits, spreading outside natural selection of the hosts. Vertical transmission reduces replication rate and allows group selection against deleterious behaviorally transmitted traits. Competing mutually exclusive propagators contribute to inequality and altruism, but compete through adverse fitness since exclusivity assumes low conversion. Conclusion: Behaviorally transmitted traits, in some cases a tremendous advantage, may also be a significant problem in the development of societies.

This study investigates the complex role of financial risks in the context of public–private partnerships (PPPs) in India and their relationship to the amount and extent of investments made by private partners (s). We hypothesize that subsidies, bid criteria, and risk have a positive relationship with investments made by private partners. A project’s leverage moderates these relationships. Regression was used to analyze the hypotheses using SPSS 24 and PROCESS Macro. Data from the World Bank were collected from 2009 to 2019 for the study variables. Interestingly, our research finds support for these relationships that may seem contrary to some commonly-held notions of risk relationships, such as – the government using ‘viability gap’ funding to attract private investment and ‘leverage’ does not moderate the relationship between risk assumed and private investment. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially in emerging markets.

Accordingly, a lot of dry direct seeding rice would be dense planted, that the initial seedling quantity could approach or even exceed the targeted effective panicle number. While limit information is available to evaluate the effects of involved novel nitrogen application methods, that total nitrogen once applied at a determined leaf age stage, on the yield formation traits of such dense planted dry direct seeding rice. The two-year experiments with total 180 kg ha-1 nitrogen once applied time treatments at sixth (L6), seventh (L7), eighth (L8), ninth (L9) and tenth (L10) leaf age stages were carried out. Results showed that the above-ground dry matter weight at maturity and grain yield of L8 was 2.1% ~ 11.8% and 4.0% ~ 9.9% higher than those of other treatments. Compared to other treatments, the higher above-ground dry matter weight after heading stage, bigger mean leaf area index with higher leaf area index at heading stage, increased leaf area duration, crop growth rate and net assimilation rate from jointing to heading period were important traits of higher grain yield formation of L8. In addition, the L8 had relative higher grain-leaf ratio traits than other treatments. Overall, a total 180 kg ha-1 nitrogen with mixed urea and compound fertilizer once applied at eighth leaf age stage would be suggest a useful high yield cultivation method for dense planted dry direct seeding rice in rice-wheat rotation system.

Background: Residents of a large area of North-Eastern Italy were exposed for decades to high concentrations of perfluoroalkyl and polyfluoroalkyl substances (PFAS) via drinking water. Despite the large amount of evidence in adults of a positive association between serum PFAS and metabolic outcomes, studies focusing on children and adolescents are limited. We evaluated the associations between serum PFAS concentrations and lipid profile, blood pressure and body mass index (BMI) in highly exposed adolescents and children. Methods: A cross-sectional analysis was conducted in 6669 adolescents (14-19 years) and 2693 children (8-11 years) enrolled in the health surveillance program of the Veneto Region. Non-fasting blood samples were obtained and analyzed for perfluorooctanoic acid (PFOA) perfluorooctane sulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorononanoic acid (PFNA), total cholesterol (TC) high-density lipoprotein cholesterol (HDL-C) and triglycerides. Low-density lipoprotein cholesterol (LDL-C) was calculated. Systolic and diastolic blood pressure (BP) were measured and BMI z-score accounting for age and sex was estimated. The associations between ln-transformed PFAS (and categorized into quartiles) and continuous outcomes were assessed using generalized additive models. Analyses were stratified by gender and adjusted for potential confounders. Results: Among adolescents, significant associations were detected between all investigated PFAS and TC, LDL-C, and to a fewer extent HDL-C. Among children, PFOS and PFNA had significant associations with TC, LDL-C and HDL-C, while PFOA and PFHxS had significant associations with HDL-C only. Increased serum concentrations of PFAS, particularly PFOS, were associated with decreased BMI z-score. No statistically significant associations were observed between PFAS concentrations and BP. Conclusions: Our study supports a consistent association between PFAS concentration and serum lipids, stronger for PFOS and PFNA and with a greater magnitude among children compared to adolescents, and a negative association of PFAS with BMI.

Considering that traditional energy sources such as fossil fuel are about to deplete during the following decades, governments try to turn to renewable energy. It is commonly known that Greece has a natural advantage of abundant solar energy and wind power due to its geographical location and characteristics.The main focus of this study is to examine how wind energy potential across the Aegean Sea and continental Greece can provide a promising field for investments in Greece, considering the economic crisis, current trends and future perspectives.We firstly focus on current legislation framework considering that laws associated with such types of investment in Greece are very complex and rapidly changing. Furthermore, a case study for a hypothetical investment plan concerning a wind park located in an Aegean island will be presented. RetScreen which is a software made by the Canadian government, will be used as a decision support tool for analyzing the potential investment scenario and a financial report will follow with estimation of the overall cost, depreciation, upcoming benefits, and payback period of the investment.Data analysis concludes that wind parks still prove to be an economically viable investment, although incentives considering the guaranteed price per kwh and faster investment times must be provided by the government.

Castanopsis hystrix, a precious tree species in Southeast Asia, has the advantages of rapid growth and high-quality wood materials. However, there are problems such as long breeding cycle, time-consuming and low efficiency, which greatly restricts the industrial development of C. hystrix. To perform the genome selection (GS) for growth and wood traits and the early selection of superior progeny have great significance for the rapid breeding of new superior varieties of C. hystrix. The 226 clones in the main distribution and 479 progenies within 23 half-sib families were used as experimental materials in this study. Genotyping datasets were obtained by high-throughput re-sequencing technology, and GS studies were conducted on the growth (tree height (H), diameter at breast height (DBH)) and wood (wood density (WD), fiber length (FL), and fiber length-width ratio (LWR)) traits. The coefficient of variation (CV) of five phenotypic traits ranged from 10.1% to 22.73%, the average CV of growth traits was 19.93%, and the average CV of wood traits was 9.72%. The Pearson correlation coefficients between the five traits were almost significantly positive. Based on the Genomic Best Linear Unbiased Prediction (GBLUP) model, the broad-sense heritabilities of growth traits were higher than those of wood quality traits, and the different number of SNPs had little effect on the heritability estimation. GS prediction accuracy first increased and then reached a plateau around 3K SNPs for all five traits. The broad-sense heritability of these five traits was significantly positively correlated with their GS predictive ability (r=0.564, P

This study explores the intriguing relationship between personality traits, self-rated fitness (SRF), and physical activity (PA) variables among German university students (N = 4,244), and sheds light on the impact of personality on adherence to PA guidelines. Employing an online cross-sectional study, the short-form of the Big Five Inventory-2 assessed five domains of personality traits (Extraversion, Negative Emotionality, Agreeableness, Conscientiousness, and Open-Mindedness). PA, including sitting time, was assessed using the International Physical Activity Questionnaire (short-form). SRF and muscle-strengthening activities (MSA) were assessed with one item each. Multiple linear and logistic regression analyses examined associations of individual personality trait domains and all domains combined with SFR, PA variables, and adherence to PA guidelines, controlling for sociodemographic, behavioral, and (mental) health covariates. Most reliably, Extraversion and Conscientiousness revealed positive associations with PA variables, while Negative Emotionality yielded inverse relationships with PA variables. For instance, each unit increase in Extraversion corresponded to additional 17 minutes weekly MSA. Contrary, daily sitting time was unrelated to personality. Of note, high Open-Mindedness was associated with lower odds for adhering to current PA guidelines. The findings have implications for developing targeted interventions that promote a physically active lifestyle and support students' well-being and academic success.

Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate ("hallucinated") content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and evaluation frameworks are available. This review aims to bridge this gap by assessing RAG-based approaches employed by LLMs in healthcare, focusing on the different steps of retrieval, augmentation and generation. Additionally, we identify the limitations, strengths and gaps in the existing literature. Our synthesis shows that proprietary models such as GPT-3.5/4 are the most used for RAG applications in healthcare. Also, there is a lack of standardized evaluation frameworks for RAG-based applications. In addition, the majority of the studies do not assess or address ethical considerations related to RAG in healthcare. It is important to account for ethical challenges that are inherent when AI systems are implemented in the clinical setting. Lastly, we highlight the need for further research and development to ensure responsible and effective adoption of RAG in the medical domain.

This paper explores the challenges and opportunities of balancing cultural preservation and tourism investment in historic Syrian cities in the post-war period. The Syrian conflict has caused significant damage to the country's cultural heritage, including its ancient cities, which are UNESCO World Heritage sites. Key issues raised include what challenges local governments to face, the impact of the war on the preservation of historic sites, how tourism can be used as a tool for economic development, and how to ensure that cultural heritage is preserved while also allowing for tourism investment. To gain an in-depth understanding of the old Syrian cities, extensive research has been conducted, including a review of existing literature and interviews with key stakeholders. The researcher found that rebuilding historic Syrian cities is a complex task that requires balancing cultural preservation with tourism investment. It will require collaboration between government officials, preservationists, developers, and local communities to ensure that these cities are restored in a way that respects their history and culture while also promoting economic growth through tourism.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

The present cultivated enset clonal landraces in Ethiopia originated from few wild progenitors. However, enset has a mixed mode of reproduction in which, the wild enset reproduces sexually through seeds, while cultivated enset is generally propagated vegetatively. The objective of this study was to understand the genetic structures of enset cultivars and estimate their genetic variability by evaluating the morphological data generated from progenies of cultivated and wild enset clones. Hence, seeds collected from six cultivated and four wild enset genotypes were used for this study. Data on four qualitative and six quantitative morphological traits were recorded from the progenies of the 10 enset genotypes. Progenies of seven enset genotypes segregated with 3:1 genetic ratio while progenies of the remaining genotypes segregated differently for the qualitative traits considered. With regard to the quantitative traits, the progenies of the 10 enset genotypes differed significantly for five of the six traits except pseudostem length. Generally the cultivated clones performed better than the wild types. This study demonstrated the possibility of creating genetic variation through selfing of the existing clones of enset for traits of interest and makes improvements either through selection or crossing the elite types to develop novel cultivar

The main objective of this study is to analyze the impact of investment in Research & Development on the performance and value of companies, that is, to try to explain how R&D investment influences the companies’ performance. For this purpose, a dynamic panel data model was estimated using the Generalized Method of Moments, which made possible to measure the impact of R&D investment on performance through the Return on Operating Assets ratio for the Portuguese companies that invested the most between 2012 to 2019. The results show that the investment in R&D is not statistically significant in explaining the operating return on assets. However, the lagged financial performance in one period, the leverage, the asset turnover ratio and the accounts payable turnover show to have impact on the variable under study.

Among the plethora of financial management tools available, stock investments stand out as the most recognizable and widely accepted option. However, investors often make buying and selling decisions based on unverified information provided by stock analysts. Since the credibility of this information remains uncertain, it frequently results in investment losses. Ordinary investors relying solely on rumors often miss out on prime opportunities for buying and selling stocks. In the current volatile investment landscape, various investment strategies cater to different situations. If individuals can effectively identify opportunities within this complex environment and dynamically adapt suitable investment strategies at any given time, substantial returns can be achieved. The ability of investors to promptly detect shifts in the current stock market environment and make accurate decisions regarding stock selection, timing, and capital allocation strategies is of utmost importance. This study presents a dynamic framework for investment decision support, which utilizes evolutionary strategies to determine the optimal timing for key strategic tools such as stock selection, timing, and capital allocation. By leveraging historical data for training and testing, this approach aims to assist investors in adapting to the ever-changing stock market environment. If investors can successfully identify and implement an appropriate investment strategy to aid in making accurate decisions, it is possible to achieve significant excess returns.

This study aims to explore predictors of the foreign investment from China coming into Rwanda. One of the components of Rwanda’s economy is the investment it receives from other countries. In order to achieve these objectives, the study gathers econometric secondary data from 2007 to 2020 quarterly which were availably provided by National Statistics of China, World Bank, UNCTAD, National Institute of Statistics of Rwanda, and the National bank of Rwanda. From literature and based on the availability of data, market size, trade openness, infrastructure, and human capital were measured as predictors of Chinese FDI. The data is analyzed using linear regression in Stata. The finding of the study showed that variables have a positive effect on FDI from China, and it found that though FDI had an effect on overall economy of Rwanda, the effect was not statistically significant. The study suggested that Rwanda’s policy on foreign investment should aim to attract and encourage Chinese investment to increase the economy of Rwanda. To encourage more FDI, the Rwandan government can offer Chinese investors greater ownership, locational, and internalization benefits. It also should continue to strengthen economic policy transparency since it lowers transaction costs and hence improves incentives for foreign investment.

Is human capital heterogeneity a decisive factor for Chinese enterprises to invest in Africa? Based on the Outward Foreign Direct Investment (OFDI） data of Chinese enterprises in 37 African countries from 2007 to 2017, this paper using the FGLS model, is the empirical analysis of the mechanism and effect of the human capital heterogeneity of host countries on OFDI location selection. The human capital heterogeneity can be divided into four dimensions: scale, quality, cost and structure, which can be measured by health level, education level, wage level, child dependency ratio and old-age dependency ratio. The results show that: (1) the host country's human capital scale and child dependency ratio structure have a significant positive impact on decision-making for OFDI; (2) the cost of human capital and the structure of old-age dependency ratio are negatively correlated with the inflow of OFDI; (3) different from the existing conclusions, the quality of human capital will inhibit the inflow of OFDI in the sample period; (4) the extended test shows that the quality of human capital has a significant positive impact on OFDI decision-making. The results of robustness test are reliable. Finally, according to the conclusion of this paper, policy recommendations are put forward.

Global financial investments in energy production and consumption are significant since all aspects of a country's economic activity, and development require energy resources. In this paper, we assess the investment trends in the global energy sector during, before and after financial crises of 2008 using two data sources: (1) Dealogic database providing cross‐border mergers and acquisitions (M&As), and (2) fDi Intelligence fDi Markets database providing greenfield (GF) foreign direct investments (FDIs). We highlight the changing role of China and compare its M&A and GF FDI activities to those of the United States, Germany, UK, Japan and others during this period. We analyze the investments along each segment of the energy supply chain of these countries to highlight the geographical origin and destination, sectoral distribution, and cross‐border M&As and GF FDI activities. Our paper shows that while energy accounts for nearly 25% of all GF FDI, it only accounts for 4.82% of total M&A FDI activity in the period 1996-2016. China's outbound FDI in the energy sector started its ascent around the time of the global recession and had accelerated in the post-recession phase. In the energy sector, the development of China's outbound cross‐border M&As is similar to USA or UK, located mostly in the developed countries in the west, while their outbound GF investments are spread across many countries around the world. Also, China's outbound energy M&As are concentrated in certain segments (extraction, and electricity generation) while their GF covers all segments of the energy supply chain.

The purpose of this paper is to evaluate the timing of innovative investment in technology product life cycles using a compound binomial option with management flexibility. Considering the business cycles changes in the macroeconomic will affect consumer purchasing power. The focus is how to evaluate the optimal investment strategy and the project value. It was applied to different product stages (three stages including production innovation, manufacture innovation, and operation innovation) and factored to different risks to build a technology innovation strategy model. An aim of this study is the options premium of the best strategy timing for each innovation stage. Its application of the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation. The same condition is applied to the operation innovation, which will only be considered after the execution of the manufacture innovation. Then, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and options premium for each stage under the possible change of Gross Domestic Product (GDP). This paper investigates the product life cycle innovation investment topic by using the compound binomial options method and will provide a more flexible strategy decision compared with other trend forecast criteria.

Oil has become the object of global exploits and fierce competition among the major world powers as it is a key strategic non-renewable resource. Transnational petroleum investment is therefore an important mechanism available to countries and international corporations to control oil resources even though there are numerous inherent uncertainties and risks. A new risk assessment index system is proposed in this paper based on use of the Delphi expert scoring system and fuzzy comprehensive evaluation that aims to minimize the potential risks inherent to multinational petroleum investment. This approach encapsulates political, legal, socioeconomic, and infrastructural factors to develop a technical method that can be used for transnational petroleum investment risk assessment. An evaluation of oil investment risk within a case study area is also presented; results provide reference data that can be applied by national and international oil companies to mitigate risks of transnational oil investment.

Evolutionary convergence provides natural opportunities to investigate how, when, and why novel traits evolve. Many convergent traits are complex, highlighting the importance of explicitly considering convergence at different levels of biological organization, or ‘multi‐level convergent evolution’. To investigate multi‐level convergent evolution, we propose a holistic and hierarchical framework that emphasizes breaking down traits into several functional modules. We begin by identifying long‐standing questions on the origins of complexity and the diverse evolutionary processes underlying phenotypic convergence to discuss how they can be addressed by examining convergent systems. We argue that bioluminescence, a complex trait that evolved dozens of times through either novel mechanisms or conserved toolkits, is particularly well suited for these studies. We present an updated estimate of at least 94 independent origins of bioluminescence across the tree of life, which we calculated by reviewing and summarizing all estimates of independent origins. Then, we use our framework to review the biology, chemistry, and evolution of bioluminescence, and for each biological level identify questions that arise from our systematic review. We focus on luminous organisms that use the shared luciferin substrates coelenterazine or vargulin to produce light because these organisms convergently evolved bioluminescent proteins that use the same luciferins to produce bioluminescence. Evolutionary convergence does not necessarily extend across biological levels, as exemplified by cases of conservation and disparity in biological functions, organs, cells, and molecules associated with bioluminescence systems. Investigating differences across bioluminescent organisms will address fundamental questions on predictability and contingency in convergent evolution. Lastly, we highlight unexplored areas of bioluminescence research and advances in sequencing and chemical techniques useful for developing bioluminescence as a model system for studying multi‐level convergent evolution.

Mesothelioma is a cancer arising from mesothelial cells lining the thoracic (pleura) or the abdominal (peritoneum) cavities, and more rarely from transformed mesothelial cells of pericardium or tunica vaginalis testis. The development of mesothelioma has been related to the exposure to carcinogenic mineral fibers, mainly asbestos. Malignant mesothelioma is an aggressive disease with diffuse nature, low median survival, and prolonged latency presenting difficulty in prognosis, diagnosis, and treatment. We here review all these aspects to underline the progress being made in investigation and to emphasise how much work remains to be done to improve prognosis and treatment.

Socially Responsible Investments, also referred to as ethical or sustainable investments, have experienced rapid global growth in recent years. They represent an investment approach that incorporates social, environmental, and ethical considerations into decision-making processes. Consequently, the significance of SRIs has captured the attention of academics, prompting inquiries into the impact of integrating social criteria on portfolio performance. The primary objective of this work was to conduct a comparative study of the performance between socially responsible and non-socially responsible investment funds, using funds domiciled in Portugal and Spain. Various multi-factor models, including the three-factor model of Fama and French (1992), the four-factor model of Carhart (1997), and the five-factor model of Fama and French (2015), were employed to assess performance. The sample comprised 125 investment funds, with 43 identified as socially responsible and 82 as non-socially responsible. The study's findings indicate that there are no significant differences between socially responsible funds and their conventional counterparts. The majority of funds experience performance alterations during periods of crisis compared to crisis-free periods. Additionally, when comparing non-conditional models with conditional models, an improvement in the explanatory power of the latter is observed. This suggests that the inclusion of the dummy variable enhances the quality of fit for the models.

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7,738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method. We further applied Cochran’s Q statistical analysis, MR-Egger intercept, and MR-PRESSO for heterogeneity and pleiotropy assessment, alongside a Bonferroni correction ((P

Sorghum (Sorghum bicolor L.) ranks fifth as the most crucial cereal crop globally, yet its seed morphology remains relatively unexplored. This study investigated seed morphology in sorghum based on 115 mini core and 130 Senegalese germplasms. Eight seed morphology traits encompassing size, shape, and color parameters were assessed. Statistical analyses explored potential associations between these traits and resistance to three major sorghum diseases: anthracnose, head smut, and downy mildew. Furthermore, genome-wide association studies (GWAS) were conducted using phenotypic data from over 24,000 seeds and over 290,000 publicly available single nucleotide polymorphisms (SNPs) through the Genome Association and Prediction Integrated Tool (GAPIT) R package. Significant SNPs associated with various seed morphology traits were identified and mapped onto the reference sorghum genome to identify novel candidate defense genes.

The study was conducted at El-Sabahia Research Station (latitude 31°12'N, longitude 29°58'E), Alexandria, Egypt, to evaluate the effect of Spirulina platensis algae extract on the growth, yield, and juice quality of four sugarcane genotypes during the 2020/2021 and 2021/2022 seasons. The sugarcane genotypes tested (G.T. 54-9, G. 2003-47, G. 84-47, and G. 2004-27) were treated with four concentrations (0, 0.1, 0.2, and 0.3%) of Spirulina algae extract (SE) during their development as plant cane and first ratoon crops. At harvest, the growth, physiological, and juice quality characteristics were documented, while chlorophyll content was measured 210 days after sowing. Spraying canes with 0.2% of SE was the most effective treatment in enhancing all of the evaluated characteristics compared to those left without SE. Cane yield was more closely correlated with stalk weight (r = 0.88), followed by leaf area index (r = 0.82), chlorophyll content (r = 0.82), stalk length (r = 0.76), and number of tillers (r = 0.73), while recoverable sugar yield was closely correlated (P < 0.01) with sugar content% (r = 0.76).

Genes encoding retinol binding protein 4 (RBP4), follicle stimulating hormone subunit beta (FSHB) and epidermal growth factor (EGF) have been proposed as candidate genes for reproduction traits in pigs. The study presented in this paper aimed to find associations between variants of these genes and reproduction traits in pigs reared in Poland. Investigation included Polish Large White x Polish Landrace (n=288) and Yorkshire (n=195) sows. Individual genotypes were determined by means of PCR-RFLP (single nucleotide polymorphism in RBP4, FSHB) or PCR (insertion/deletion in EGF) methods. Obtained result showed that RBP4 variants were related to total number born (TNB) and number born alive (NBA) in 1st, 2nd and 5th parities, FSHB to TNB and NBA in first two parities, however EGF with both traits in all parities (P≤0.05 or P≤0.01). In case of RBP4 gene, heterozygous genotype (AB) was favorable for analyzed traits, however in case of FSHB and EGF homozygous genotype, AA and BB respectively. Obtained results indicate that polymorphism in three analyzed genes is associated with important reproductive traits of pigs kept in Poland.

Aims: Adolescence is a critical period because the brain is involved in the process of maturation that entails cognitive functions. On the way of maturation, an individual’s inhibitory control undergoes many changes and becomes vulnerable to different thrill-seeking like smoking, drinking, and so on. Smoking is highly prevalent among teenagers that are trying to take control of their behaviors in order to join society. They experience antisocial behavior too which is a trait that can lead adolescents to addiction. This trait is an inevitable part of psychopathy. Inhibitory deficits and psychopathy have been widely reported in addiction studies. The current study tried to investigate the relationship between psychopathic traits and behavioral inhibition between male smokers and non-smoker teenage students.Materials & Methods: Statistical sample of this research is 62 teenage students aged 17 years that are divided into smoker and non-smoker groups. The participants have been chosen through random sampling from the population of 10 high schools. The data have been gathered in Kordkoy and Gorgan in Golestan province. Behavioral bias has been measured by Go/NoGo task and psychopathic traits through youth psychopathic traits inventory. Also, the short form of Wechsler Adult Intelligence Scale test has been executed and used as a control variable.Findings: A meaningful difference has been found between the performance of smoker and non-smoker groups in Go/No Go task and psychopathic traits that are smokers performed weaker in comparison with non-smokers and psychopathic traits of smokers were meaningfully higher than non-smokers. On the other hand, there was no significant difference between these two groups in their Wechsler Adult Intelligence Scale scores.Conclusion: The results have shown that smokers have higher psychopathic traits and lower behavioral inhibition when compared with their non-smoker peers. According to the results of current research, smoking can decline the cognitive functions.

Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES). The RES investment is characterized by uncertainty, which is long-term, costly, depend on feed-in-tariff and support schemes. In this paper, we address the real option valuation (ROV) of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price, furthermore the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assess the value of deferred option are discussed. The new three stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM) methods. The numerical methods are integrated with concept of Black-Scholes option pricing theory, and applied in option valuation for solar energy investment with uncertainty. The numerical results of L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our data set refers to the Arab Republic of Egypt.

Acquisition traits are those that depend for their evolutionary (fitness) value on the acquisition of something that gradually accumulates during an organism’s life but is not transmitted genetically to descendants. This situation causes these traits including language, immunity, intelligence, and social status to represent a special need for evolvability and programmed aging. Programmed aging refers to the idea that mammals and some other multiparous sexually reproducing organisms evolved complex biological mechanisms that cause gradually increasing fitness deterioration and internally limit individual organism lifetimes. The rationale is that this process enhances the survival (non-extinction) of a species population. Evolvability theories propose that mammals have evolved design characteristics that aid their ability to evolve, that is, reduce the time required for a particular increment of evolutionary adaptation and/or increase the precision with which the adaptation can be performed. Because an increase in evolvability aids a population in escaping extinction, evolution selects the associated design characteristics. Both concepts conflict with traditional (Darwinian) theory regarding details of the nature of evolution. However, more recent genetics discoveries have exposed rich detail regarding the nature of the evolution process including the fact that biological inheritance involves the transmission of organism design information from parent to descendant in digital form. These discoveries have acted to support both programmed aging and evolvability theories.

The objective of this study were to conduct association mapping for drought tolerance at the seedling stage and yield-related traits. 60 cowpea accessions were used in the study. Single-nucleotide polymorphisms (SNPs) discovered through genotyping by sequencing (GBS) were used for genotyping. Association mapping was conducted using single-marker regression (SMR) in Q Gene, and general linear model (GLM) and mixed linear model (MLM) built in TASSEL. The population of the cowpea accessions were analysed using STRUCTURE 2.3.4 and the peak of delta K in the greenhouse showed seven population types, whereas the peak of delta K in the glasshouse indicated the presence of six population types. One SNP marker, 14083649|F|0-9 was associated with NP with a p value <0.001. Fifty SNP markers were associated with PWT at p <0.001. Four SNP markers, 14074781|F|0-16, 100047392|F|0-36, 14083801|F|0-28 and 100051488|F|0-49 were associated with AVSPD at p <0.001. SNP markers, 14074781|F|0-16, 14083801|F|0-28 and 100051488|F|0-49 were associated with PL at P <0.001. Five SNP markers, 100047392|F|0-36, 14083801|F|0-28, 100072738|F|0-34, 14076881|F|0-49 and 14076881|F|0-49 were associated with PWDTH at p <0.001. The 65 SNP markers identified can be used in cowpea molecular breeding to select for AVSPD, NP, PL, PWDTH, PWT, and RR through marker assisted selection (MAS).

The development of transport infrastructure is a key element of economic growth, social connectivity, and sustainable development. Many countries have historically underinvested in transport infrastructure, necessitating more efficient strategic planning in transport infrastructure investment projects implementation. This article addresses the selecting and scheduling of transport infrastructure projects, specifically within the context of drawing available resources from pre-allocated funds within a multi-annual budget investment program. The current decision-making process is largely based on expert judgment, lacking quantitative decision support methods. The authors propose a genetic algorithm as a decision-support tool that frames the problem as an NP-hard 0-1 multiple knapsack problem. The proposed genetic algorithm is unique for its matrix-encoded chromosomes, specially designed genetic operators, and a customized repair operator, which is implemented to address the large number of invalid chromosomes generated during the GA computation. The goal is to maximize the impact of allocated funds over a seven-year programming period, while respecting constraints specified by the funding authorities. In computational experiments, proposed GA is compared to an exact solution and is proved to be efficient in terms of quality of obtained solutions and computational time, highlighting its potential for enhancing strategic decision-making in transport infrastructure development.

The aim of this cross-country research is to examine how the profit and loss sharing mudarabah investment deposits are classified and disclosed in the financial statement of Islamic banks. The cross-country study examined the financial statements of fifty-one fully-fledged Islamic banks. The results of the data analysis show that Islamic banks disclose the mudarabah investment account in different ways. The absence of standardized disclosure for mudarabah investment deposit confuses the stakeholders. This research suggests to the regulators to fully or partially adopt the AAOIFI standards specifically for Islamic financial institutions.

This paper studies the influence mechanism of industrial agglomeration and foreign direct investment (FDI) on green total factor productivity (GTFP). We use the SBM Directional Distance Function to measure the GTFP of Chongqing's manufacturing industry from 1999 to 2015. The results show that the level of GTFP in Chongqing's manufacturing industry is relatively low, which is contrary to the current green development mode. By clarifying the conduction path of industrial agglomeration and FDI on GTFP, we use the panel Tobit model to study the effect of industrial agglomeration and FDI on GTFP. The main findings are: the higher the level of industrial agglomeration, the more beneficial it is to increase GTFP. FDI has an inhibitory effect on GTFP. The spillover effect of FDI on GTFP is not significant. At the same time, FDI counteracts the role of industrial agglomeration in promoting GTFP. The findings in a present study indicate that, according to Chongqing's experience, the "pollution haven" is established. Therefore, relying solely on foreign technology to promote the development of the manufacturing industry has many drawbacks clearly. Only by improving the ability of independent innovation is the reliable way to enhance GTFP effectively.

Understanding the relationship between sugar yield and related traits is crucial for successfully breeding this important industrial crop. Thirteen sugar beet monogram cultivars were evaluated during 2018-2019. The study used a split-factorial design with two planting dates as the main plot, while cultivars and harvesting dates were laid out as CRBD as subplots. Significant differences were observed among the cultivars for all measured traits. The genetic correlation coefficients showed the highest positive and significant correlations between sugar yield and white sugar yield (WSY) (0.88**), sugar content (SC) (0.71**), and white sugar content (0.65**). Conversely, the highest negative and significant correlations were found between sugar yield and molasses sugar content (-0.62**), alkalinity coefficient (-0.58**), and root potassium content (-0.52**). In the stepwise multiple regression analysis, white sugar content (WSC), sugar content (SC), root α-amino nitrogen content, and root yield were included in the regression model, explaining 84% of the total variance in the sugar yield. Path analysis revealed that sugar content (1.12) and root yield (1.03) had the highest direct effects on sugar yield. These traits can be used as key criteria for developing superior hybrids with high economic productivity, thereby accelerating the selection process in various breeding programs.

In the research, we studied the typical functional plant traits and life forms of plants that colonize forest gaps. In the research, we analysed functional plant traits of plant species growing on five forest gaps in the Dinaric fir-beech forest in Slovenia. The forest gaps were created as a result of natural disturbances. We selected 18 functional plant traits, whose values were obtained from the BiolFlor database. With the help of the JUICE program, we calculated the frequency of its occurrence on individual forest gap for each functional plant trait. Then we calculated Sperman's correlation coefficient at p&lt;0.05, between the occurrence of individual functional plant traits and single forest gap. We found out that forest gaps are mainly colonized by perennials and herbaceous perennials and hamephytes. These are plant species that begin to flower in June and July, bloom for two or three months and are pollinated by insects, mainly hover flys and wild bees. Characteristic of colonizing plant species is also that, in addition to reproducing by seeds and spores, they also reproduce vegetatively. Besides that, birds and forest mammals are the vectors of fruit and seed dispersal of colonizing plant species.

Wheat is the essential constituent of cereal-based diets and one of the most significant sources of calories. However, there is an inherently low bioavailability of proteins, mineral, and vitamins in modern wheat grains. Biofortification has earned recognition as an outstanding approach, at the same time as a cure for world hunger. The developments in the identifications of quantitative trait loci (QTL) analysis and understanding of the physiological and molecular basis of QTLs controlling the biofortification traits in wheat has revealed new horizons for the improvement of modern wheat varieties. Within this review, we have compiled the information from the studies carried out in wheat using QTL mapping methodologies that is among the best methods for biofortification traits. We hope this review will serve as an essential reference for the QTLs identified for the several important biofortification traits in wheat.

This study aims to analyse whether Chinese companies' R&amp;D investment affects management innovation performance. Also, this dissertation defines management innovation as diversification strategies such as technology and industry diversification and analyzes the impact of these diversification strategies. In particular, this paper analyzes whether R&amp;D investment leads to technology and industry diversification and whether technology diversification creates a mediating effect in the process of R&amp;D investment leading to industry diversification. The analysis results can be summarized as follows: First, R&amp;D investment showed a significant positive relationship with industry diversification. Second, R&amp;D investment shows a significantly positive relationship with technology diversification. Third, technology and industry diversification showed a positive relationship. Fourth, this study examined the mediating role of technology diversification, and it was confirmed that technology diversification plays a mediating role in the effect of R&amp;D investment on industry diversification. R&amp;D investment and business innovation play a key role in the sustainable development of enterprises, and the findings of this paper have important reference value for enterprises' R&amp;D investment decision-making. The results of this study provide the following implications that Chinese companies improve business innovation performance by increasing their R&amp;D investment, promoting innovative R&amp;D, and improving technology diversification and industry diversification strategies.

Investment management is a common process and practice used for achieving a desirable investment goal or outcome. Investment assessment should be carried out at various stages of project realization in accordance with capital investment volume. Investment risk management implies the effective control of all procedures and monitoring of risks in all phases of the investment project. Because of the reason that a single indicator in probability calculation of achieving optimal return from the investment does not exist, performing sufficiently reliable estimates of the quality of investments becomes a tedious task. There are many indicators, factors, and criteria required for consideration to reach the effective solution of the investment problem. Unfortunately, the systematic variation of economic situations in the marketplace stipulates the continuous and frequent changes of investment conditions and environment in which the investor should act and operate. Hence, the rules required for providing a reasonable quality of investment projects can be based only on investor’s management strategy and rely on investor’s intuition and practice. The importance of classification in investment management and decision making process is undeniable. The objects to be classified are described using assessments in accordance with various criteria which can be both quantitative and qualitative. With a competent formulation of the investment process, both methods are used in parallel. There exist various decision making approaches for the investment management, and simple additive weighting (SAW) is one of the well-known multi-criteria decision making (MCDM) methods aiming to provide an optimal decision for decision maker when solving various real-life problems, and particularly, investment problem. In this paper, fuzzy simple additive weighting (FSAW) method in group decision making is applied to undertake the capital investment expenditure for purchasing cars with the purpose of renting them to the public. The development of existing FSAW method is accomplished and this process involves the sensibility of outcomes to changes in the rate of fuzziness represented with decisions taken. Eventually, the degree of fuzziness involved in an analysis that directly attempts to model the immanent vagueness and imperfectness in particular precedency judgments made, is determined. A numerical example illustrates the importance and effectiveness of the suggested approach with the aim of ranking alternatives and hence, determining the most preferred alternative in MCDM problem.

The winged bean is an underutilized legume that has the potential to contribute to nutrition and food security globally, especially in sub-Saharan Africa (SSA). However, very little research attention is paid to exploiting its full potential due to a lack of adequate knowledge of the existing genetic diversity in the available winged bean germplasm. To bridge this gap, seed morphometric and selected agro-morphological traits which are crucial for yield and seed quality determination in crop plants were used to assess the genetic diversity of thirty accessions of winged bean sourced from the Gene bank of the International Institute of Tropical Agriculture (IITA), Ibadan. The thirty winged accessions were evaluated under field trials at three agro-ecological zones in Nigeria. The agro-morphological data as well as the seed morphometric dataset obtained from a Multi-Spectral Imaging (MSI) system were subjected to Analysis of Variance (ANOVA), Principal Component (PC) analysis, cluster analysis, and correlation analysis. Significant differences (p &lt; 0.05) were observed among the accessions for all measured traits. The first three PCs accounted for 93% of the variation observed among the accessions for all measured traits. Accessions were grouped into three clusters based on the agro- morphological traits and three clusters under the MSI system. Seed yield per plant had the highest estimates of significant positive correlation with hundred seed weight, pod weight per plant, etc. at both phenotypic and genotypic levels. TPt-31 had the highest seed yield per plant, pod weight per plant, and early maturity while TPt-7 had an extended flowering and maturity period, the highest number of pods per peduncle and pods per plant as well as the lowest seed yield. These accessions could serve as a good resource for future winged bean improvement programs. The result also confirmed that the MSI system is an invaluable tool for discriminating among accessions of the same crop species.

Recent findings support an association between childhood maltreatment and the presence of elevated psychopathic traits in adulthood. Using a community sample recruited online (N = 210), we sought to (1) confirm the relationship between childhood traumas and psychopathic traits, and (2) investigate the role of parenting styles in psychopathic traits. Consistent with our predictions, we found an association between all types of childhood traumas and disinhibition. Age and gender moderated the relations between psychopathic traits and childhood maltreatments. Parental rejection and overprotection were positively correlated with the presence of psychopathic traits, while parental emotional warmth was negative correlated. Although our results converge with previous findings, the strength of the correlations observed was not as compelling as in research on undergraduate students. We discuss the numerous interpretations for our findings, and highlight the limitations of research in the field of psychopathy and childhood trauma in the general population.

Studies have shown that nearly half of rural toddlers in China have cognitive delays due to an absence of stimulating parenting practices, such as early childhood reading, during the critical first three years of life. However, few studies have examined the reasons behind these low levels of stimulating parenting, and no studies have sought to identify the factors that limit caregivers from providing effective early childhood reading practices (EECRP). This mixed-methods study investigates the perceptions, prevalence and correlates of EECRP in rural China, as well as associations with child cognitive development. We use quantitative survey results from 1,720 caregiver-child dyads across 100 rural villages/townships in northwestern China and field observation and interview data with 60 caregivers from these same sites. The quantitative results show significantly low rates of EECRP despite positive perceptions of early reading and positive associations between EECRP and cognitive development. Qualitative results suggest that low rates of EECRP in rural China are not due to the inability to access books, financial or time constraints, or the absence of aspirations. Rather, the low rate of book ownership and absence of reading to young children is driven by the insufficient and inaccurate knowledge of EECRP among caregivers, which leads to their delayed, misinformed reading decisions with their young children, ultimately contributing to developmental delays.

Barnyardgrass (Echinochloa spp.) is a prevalent type of weed in rice fields worldwide. Despite the growing knowledge concerning allelopathic interference with barnyardgrass, little is understood regarding the competitive mechanisms between allelopathic rice and herbicide-resistant barnyardgrass at the plant physiological level. In this context, a hydroponic system was employed to investigate the root morphological traits and different phytohormones levels of two rice cultivars, i.e., the allelopathic rice cultivar “PI312777” (PI) and the non-allelopathic rice cultivar “Lemont” (LE), when co-planted with quinclorac-resistant and -susceptible barnyardgrass, respectively. The results showed that the shoot and root biomass were greater in the allelopathic rice cultivar. Moreover, the treatments at the two time points induced an increase in shoot and root biomass of PI when subjected to barnyardgrass stress. In terms of root morphology, PI exhibited significantly higher fine-root length in diameters &lt;0.5 mm, a greater number of root tips, and longer root tips compared to LE. In addition, the levels of different plant hormones, including auxin (IAA), abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA), known for their diverse adaptation strategies to biotic stress, were analysed. The response to quinclorac-resistant barnyardgrass stress was consistent in terms of the content of well-known stress-related hormones, namely SA and JA. The accumulation of SA and JA was observed in both rice cultivars under the stress of quinclorac-resistant barnyardgrass, with higher contents of these hormones in PI than that in LE. The most significant change was observed in IAA and ABA contents in rice, which decreased significantly from 7 days to 14 days under co-culture stress. Additionally, PI contained higher levels of IAA and ABA than LE in the presence of barnyardgrass stress. This research may aid in the development of strategies for reducing the environmental impact of herbicides through the prudent selection of non-chemical herbicide control tactics.

(1) Background: The goal of our study was to identify SNPs, metabolic pathways (KEGG), and gene ontology (GO) terms significantly associated with calving and workability; (2) Methods: Based on the EuroGenomics reference data set, we analyzed direct (DCE) and maternal (MCE) calving ease, direct (DSB), and maternal (MSB) stillbirth, milking speed (MSP), and temperament (TEM). We estimated SNP effects using a multi-SNP mixed-model. Further, SNP positions were mapped to genes, and GO terms/KEGG pathways of the corresponding genes were assigned. The estimation of GO term/KEGG pathway effects was based on a mixed-model using SNP effects as dependent variables; (3) Results: The number of significant SNPs comprised 59 for DCE, 25 for DSB and MSP, 17 for MCE and MSB, and 7 for TEM. Significant KEGG pathways were found for MSB (2), TEM (2), and MSP (1), while 11 GO terms were significant for MSP, 10 for DCE, 8 for DSB and TEM, 5 for MCE, and 3 for MSB.; (4) Conclusions: From the perspective of a better understanding of the genomic background of the phenotypes, traits with low heritabilities suggest that the focus should be moved from single genes to metabolic pathways or gene ontologies significant for the phenotype.

Screening of pollen traits in diploid wild potatoes (Solanum sect. Petota, Solanaceae) is desirable to develop heat-tolerant potato (S. tuberosum) cultivars. To accomplish this goal requires exploring potato genetic resources that are conserved in genebanks. The goal of this study was to assess pollen viability and 2n pollen production of the diploid potato wild relatives under heat stress condition. We assessed pollen viability and size of nine potato accessions conserved at the Embrapa Potato Gene Bank, including eight wild potatoes S. chacoense (BRA 00167447-2, BRA 00167017-3, BRA 00167023-1, BRA 00167028-0), S. commersonii (BRA00167007-4, BRA00167420-9, BRA00183760-8), and S. malmeanum (BRA 00183755-8), along with a control accession from the cultivated species S. tuberosum (BRA 00167251-8). The plant accessions were cultivated in different growth chambers, subjected to both control temperature (ranging from 14 to 27°C) and supraoptimal temperature conditions (ranging from 24 to 34°C). At heat stress, the accessions BRA 00167251-8 did not bloom, and BRA 00167023-1 did not produce pollen. The remaining accessions did not exhibit a significant reduction in pollen viability as the temperature increased. Pollen viability at the control temperature had the lowest value in BRA-00167420-9 (S. commersonii) with 68.5% and the highest in BRA 00183755-8 (S. malmeanum) with 100%. At the supraoptimal temperature the lowest value was in BRA 00167420-9 (S. commersonii) with 54.5% and the highest in BRA 00167017-3 (S. chacoense) with 94%. The average of pollen diameter was 20 μm in all wild potato genotypes, and the increase of temperature did not lead to 2n pollen production. Estimated Genotypic Coefficient of Variation (GCV) was lower than Phenotypic Coefficient of Variation (PCV) for pollen viability. The observed heritability values ranged from 58.82% in BRA00167007-4 to 91.32% in BRA 00183755-8. Our results highlight the genetic variability available in wild potato germplasm concerning pollen viability under heat stress. Furthermore, these first insights offer valuable guidance for ongoing and future endeavors in diploid potato breeding.

Rice (Oryza sativa L.) supplies nourishment to about half of the population of the world's inhabitants. Of them, more than 2 billion people suffer from "hidden hunger" in which they are unable to meet the recommended nutrients or micronutrients from their daily dietary intake. Bio-fortification refers to developing micronutrient-rich diet foods using traditional breeding methods and modern biotechnology, a promising approach to nutrition enrichment as part of an integrated strategy for food systems. To improve the profile of rice grain for the biofortification related traits, understanding the genetics of important biofortification traits is required. Moreover, these attributes are quantitative in nature and are influenced by several genes and environmental variables. In the course of past decades, several endeavours such, as finding the important quantitative trait loci (QTLs) for improving the nutrient profile of rice seeds were successfully undertaken. In this review, we have presented the information regarding the QTLs identified for the biofortification traits in the rice.

According to Hofstede’s theory of cultural dimensions, cultures differ in cultural values and norms; values and norms that may influence differences in trendsetting, creative traits and behaviors, and pro-environmental behaviors. Further, because men and women have been socialized within particular cultures, gender differences may exist in trendsetting, creative traits and behaviors, and pro-environmental behaviors. Trendsetters have characteristics that are interrelated with creative traits and behaviors, perhaps inclining them to endorse pro-environmental behaviors. However, the interrelationships among these variables remain unexplored. Thus, the purpose of this study was to examine these three variables among college students in South Korea and the United States, specifically looking at cultural and gender differences. Participants were 225 Korean college students and 221 U.S. college students. Questionnaires included demographic items and scales measuring trendsetting, creative traits and behaviors, and pro-environmental behaviors. Data analyses included descriptive statistics, Cronbach’s alpha reliability, MANOVA, ANOVA and SNK posthoc test. Results show that U.S. (vs Korean) students indicated greater trendsetting and creative traits and behaviors but not greater pro-environmental behaviors. Fashion trendsetting groups in both Korea and the U.S. differed in creative traits and behaviors and pro-environmental behaviors. Among Korean trendsetting groups, reluctant adopters scored lowest on creative traits and behaviors and pro-environmental behaviors. Among U.S. trendsetting groups, trendsetters scored highest on creative traits and behaviors and pro-environmental behaviors; reluctant adopters scored lowest on pro-environmental behaviors. Theoretical and practical implications are provided for researchers and marketers.

Uzbekistan, as an emerging national economy, aims to attract foreign direct investment (FDI) to foster the development of its free economic zones (FEZs). While recent policy reforms have enhanced the country's appeal to investors and facilitated the inflow of international capital, challenges persist in attracting investment. This study employs an economic geographical approach to analyze and propose solutions to these obstacles. By examining the spatial patterns of FEZs and FDI through a comprehensive geographical lens, this research utilizes document analysis as an alternative to empirical analysis, considering the broader context rather than focusing on a specific FEZ. The findings reveal that the insufficiency of an innovation-driven environment, logistical systems, energy resource-related issues, among others, negatively impact the inflow of FDI into FEZs. Moreover, the study underscores the significance of economic geography in understanding these factors. Finally, relevant insights and recommendations are provided from an economic geographical perspective.

This study examines the spatial impact of FDI on the poverty of 44 African countries. In achieving this, the study uses the Driscoll-Kraay fixed effect instrumental variable regression, instrumental variable generalised method of moments estimator (IV-GMM), and the spatial durbin model. The empirical investigation of this study yielded four significant findings: (1) neighbouring countries’ FDI has a positive and significant impact on the incidence and intensity of host country’s poverty. (2) Improved institutional quality in neighbouring countries has a significant impact on FDI-poverty reduction nexus of the host country. (3) the empirical results lend support for a significant spatial spillover of poverty in the region. (4) the marginal effect results indicate that countries within the region are no longer in isolation or independent, i.e., the level of poverty in a particular country is influenced by its determinants in the neighbouring country. This result is robust to the alternative proximity matrix, which is the inverse distance. Since there is spatial interdependence among African countries, we recommend that African governments through the African Union (AU) should not only champion the institutional reform in the region, but also establish a binding mechanism to ensure reform implementation.

Fostering innovation is considered one of the key policy priorities in most governments' agendas in developing countries, and foreign direct investment (FDI) is considered a principal resource for financing sustainable development, corresponding to 17 sustainable development goals (SDGs). This study analyzes the extent to which inward FDI affects innovation (proxied with patent applications) in Sri Lanka using secondary data from 1990 to 2019. We used the Autoregressive Distributed Lag (ARDL) cointegration procedure to examine the long-run relationships between variables. As per the study results, the coefficient of inward FDI is a negative sign while the coefficients of per capita gross domestic product (GDP) and high technology exports (HEX) show positive signs 2.142 and 0.414, respectively, and statistically significant in the long run. It is demonstrated that per capita GDP and high technology exports are an important variable in explaining technological innovation, and inward FDI and education expenditure (EDU) did not contribute towards widening technological innovation in Sri Lanka. Shaping the future of FDI in Sri Lanka is essential to foster innovation capability.

Owing to the rising demand for vegetable soybean products, there is an increasing need for high-yield soybean varieties to raise the output. However, complex correlation patterns among quantitative traits with genetic interactions bring a challenge for vegetable soybean breeding. Here, a genome-wide association study (GWAS) was applied for six yield-related traits with 188 vegetable soybean accessions. A total of 81 SNPs were identified for pod length, plant height, pods number, pod thickness, pod width, and seed weight per plant by Blink model. Among these significant SNPs, 79 were novel SNPs, while 2 overlapped with previously reported SNPs. A total of 220 genes were found in 100 kb upstream and downstream regions of significant SNPs, of which 17 genes were functional proteins. Among these function proteins, four candidate genes, Glyma.13G109100, Glyma.03G183200, Glyma.09G102200, and Glyma.09G102300 were analyzed as significant haplotype variations, which encode MYB-related transcription factor, auxin-responsive family protein, F-box protein and CYP450, respectively. In addition, the relative expression with four candidate genes in the V030 and V071 (Among them, the plant height, pod number and fresh pod weight of V030 were lower than V071 strains) vegetable soybean were significantly different and these genes could be involved in plant growth and development via various pathways. Therefore, we proposed four genes from vegetable soybean germplasm that could be the key candidate genes for pod yield and plant height and these studies will accelerate the process of high-yield vegetable soybean breeding.

Increasing genetic diversity in crop plants has been used for chemical mutagenesis. Through the application of various mutagenic agents, over 430 new varieties have been derived as rice mutants (Oryza sativa L.) Chemical mutagens such as ethyl methane sulphonate (EMS), diepoxybutane derivative (DEB), sodium azide, and gamma ray, x-ray, and quick neutron irradiation have been commonly used to induce a large number of functional variations in rice and others crops. Among chemical mutagens, ethyl methane sulfonate (EMS) is the alkylating agent most widely used in plants because it induces nucleotide substitutions to be extremely frequent, as detected in various genomes. In this study, seeds of potential genotype of the popular variety, (Oryza sativa L. Super Basmati variety) were treated with EMS at concentrations of 0.25%, 0.50%, 0.75%, 1% and 1.5%. Various measurements on the M1 generation determined EMS sensitivity. As concentration of applied EMS increased, will decrease in germination, shoot length, root length, plant height, productive tillers, Panicle Length, Total Spikelet, sterile spikelet and fertility under field conditions were observed in M1 generation as compared to the non-treatment control. Emergence, shoot length, root length, plant height, productive tillers, Panicle Length, Total Spikelet, sterile spikelet and fertility also decreased with increases in EMS mutagenesis in an approximately linear fashion. The LD₅₀ values were observed based on growth reduction of seedlings after EMS treatment with 0.25% and 0.50% on the rice variety (Oryza sativa L. spp.).

We report, for the first time in onychophorans, food hiding, parental feeding investment and an ontogenetic diet shift, from adhesive to prey, after their first two weeks of life.

The Double U-pipe ground heat exchanger, recognized for its straightforward process, cost-effectiveness, high heat exchange efficiency, and low thermal resistance, stands as the predominant ground heat exchanger type in today's shallow geothermal energy development and utilization. Recent years have seen significant research into the heat transfer influencing factors and heat exchange performance of Double U-pipe ground heat ex-changers via experimental testing methods. Yet, studies integrating numerical simulation with in-situ testing have been less frequent. Drawing on the cylindrical heat source model theory and the outcomes of regional in-situ thermal response tests, this paper develops a Double U-pipe ground heat transfer model by establishing physical, mathematical, and heat transfer geometric models. It assesses the impact of varying inlet temperatures, flow rates, and initial ground temperatures on heat exchange efficiency under heating conditions. The results validate the precision of the double U-pipe ground heat exchanger model based on in-situ testing. They show that enhancing the temperature differential between the inlet and initial temperatures, elevating the initial ground temperature, and moderately increasing the flow rate can boost the system's heat exchange efficiency.

This study seeks to determine how economic policy uncertainty (EPU) influences investment decisions and the market value of the Pakistan Stock Exchange. The study examines investment and operational data from 249 energy and petroleum companies between 2015 and 2020, in addition to macroeconomic variables such as EPU. This study investigates the moderating effects of EPU on investments in fixed and intangible assets, as well as its effect on Tobin's Q and the market price per share. The outcomes demonstrate that EPU reduces the costs of both tangible and intangible assets for businesses. In addition, companies with a greater Tobin's Q and market price per share are more impacted by uncertain corporate investment policies. However, financial leverage is found to be negatively correlated with share price and positively correlated with earnings per share and earnings per unit. Tobin's Q is positively correlated with financial leverage, indicating that firms that raise capital through debt are more likely to create value for investors. The research indicates that market-dependent enterprises are more susceptible to the unpredictability of monetary policy. Eventually, the findings suggest that consistent and transparent economic policies may increase the efficiency of corporate investment.