Is Natural Resource Abundance a Stimulus for Financial Development in the USA?

This paper investigates the stimulating role of natural resource abundance in financial development for the case of the USA over the period of 1960-2016. We included education, economic growth and capitalization as additional determinants of financial development in finance demand function. Thus, we applied traditional and recent unit root tests, accommodating unknown structural breaks in the series for examining the unit root properties of the variables. To examine cointegration between the variables, we apply the Bayer-Hanck cointegration approach. The robustness of cointegration relationship is tested by applying the bounds testing approach to cointegration. The empirical results show the presence of cointegration between financial development and its determinants. In the long run, we observe that natural resource abundance contributes to financial development. Education has a positive impact on financial development. A positive relationship exists between economic growth and financial development. Capitalization is inversely linked with financial development. The causality analysis reveals a feedback effect between natural resource abundance and financial development i.e. natural resource abundance causes financial development; in turn, financial development Granger causes natural resource abundance. This empirical evidence provides new insights for policy makers to use natural resource abundance as an economic tool to improve the performance of financial sector by considering the role of economic growth and education

Is Natural Resource Abundance a Stimulus for Financial Development in the USA?

This paper investigates the stimulating role of natural resource abundance in financial development for the case of the USA over the period of 1960-2016. We included education, economic growth and capitalization as additional determinants of financial development in finance demand function. Thus, we applied traditional and recent unit root tests, accommodating unknown structural breaks in the series for examining the unit root properties of the variables. To examine cointegration between the variables, we apply the Bayer-Hanck cointegration approach. The robustness of cointegration relationship is tested by applying the bounds testing approach to cointegration. The empirical results show the presence of cointegration between financial development and its determinants. In the long run, we observe that natural resource abundance contributes to financial development. Education has a positive impact on financial development. A positive relationship exists between economic growth and financial development. Capitalization is inversely linked with financial development. The causality analysis reveals a feedback effect between natural resource abundance and financial development i.e. natural resource abundance causes financial development; in turn, financial development Granger causes natural resource abundance. This empirical evidence provides new insights for policy makers to use natural resource abundance as an economic tool to improve the performance of financial sector by considering the role of economic growth and education

Depression in stroke patients; a cross sectional study highlighting the association of stroke on age and gender basis.

Stroke is the second leading cause of death. Depressive disorder is characterized by period of sad mood and anhedonia occurring for two consecutive weeks. Among stroke survivors, the consequence of physical and psychological changes can be devastating. One of those psychological changes is post-stroke depression (PSD). Stroke itself has debilitating morbidity and superimposed PSD further decreases the quality of life of patients and impairs recovery. This study leads us to know the magnitude of post stroke depression

Loss of function mutations in RP1 are responsible for retinitis pigmentosa in consanguineous familial cases.

PurposeThis study was undertaken to identify causal mutations responsible for autosomal recessive retinitis pigmentosa (arRP) in consanguineous families.MethodsLarge consanguineous families were ascertained from the Punjab province of Pakistan. An ophthalmic examination consisting of a fundus evaluation and electroretinography (ERG) was completed, and small aliquots of blood were collected from all participating individuals. Genomic DNA was extracted from white blood cells, and a genome-wide linkage or a locus-specific exclusion analysis was completed with polymorphic short tandem repeats (STRs). Two-point logarithm of odds (LOD) scores were calculated, and all coding exons and exon-intron boundaries of RP1 were sequenced to identify the causal mutation.ResultsThe ophthalmic examination showed that affected individuals in all families manifest cardinal symptoms of RP. Genome-wide scans localized the disease phenotype to chromosome 8q, a region harboring RP1, a gene previously implicated in the pathogenesis of RP. Sanger sequencing identified a homozygous single base deletion in exon 4: c.3697delT (p.S1233Pfs22*), a single base substitution in intron 3: c.787+1G>A (p.I263Nfs8*), a 2 bp duplication in exon 2: c.551_552dupTA (p.Q185Yfs4*) and an 11,117 bp deletion that removes all three coding exons of RP1. These variations segregated with the disease phenotype within the respective families and were not present in ethnically matched control samples.ConclusionsThese results strongly suggest that these mutations in RP1 are responsible for the retinal phenotype in affected individuals of all four consanguineous families

Zinc nutrition application augments morpho-physiological attributes, productivity and grain zinc bioavailability of Paddy Rice

Zinc (Zn) deficiency is the most important micronutrient disorders affecting plants and human health. Present study evaluated the potential of various Zn application methods in improving the performance of selected rice genotypes and Zn bioavailability in grains. Pre-selected Zn application methods through pot experiments were validated in the field. Harvested grains were fed to albino rats for Zn bioavailability. Results revealed that soil + foliar application of Zn was effective in improving the seedling growth of rice genotypes by modulating the agronomic, water related and biochemical attributes. The rats gained more body weight fed with rice genotype Accession-164 (high Zn accumulator) compared with the minimum for Super Basmati (low Zn accumulator) feed. In crux, soil application of Zn at 15 kg ha-1 followed by foliar application of 0.25% ZnSO4.7H2O solution at tillering and heading stages produced the highest grain yield (26.25%, 29.11%) with maximum bioavailable Zn (21.02%, 22.50%) during both years, respectively, in the grains for combating malnutrition in the tested rats

Black Tea: Chemical and Pharmacological Appraisal

Medicinal plants are gaining popularity as folk medicine due to future demand to get rid of synthetic health promoting medicines. Nowadays, black tea is gaining interest as the most frequently consumed therapeutic drink after the water. The importance of black tea is due to existence of flavonoids such as (Thearubigins (TRs) and theaflavins (TFs) and catechins) that are the main therapeutic agents and are more bio-direct and stable compounds compared to those exist in other herbal plants alongside some other promising compounds which enhance is credentials as therapeutic drug. Numerous scientific explorations have elucidated the biological worth of these bioactive moieties against plethora of ailments with special reference to metabolic disorder. The mandate of current chapter is to discuss the black tea chemistry for elucidating its pharmacological worth

Concept mapping and conceptual change texts: a constructivist approach to address the misconceptions in nanoscale science and technology

Nanoscale Science and Technology (NST) is a rapidly evolving field with profound implications for various industries and our everyday lives. However, misconceptions among learners can hinder their ability to grasp the fundamental concepts of NST, thereby impeding their potential contributions to this advancing domain. Concept maps (CM) and conceptual change texts (CCT) are graphical and written representations of knowledge that enable learners to visualize relationships between concepts and assess the coherence of their understanding. In this pursuit, we engage with the concept of rehabilitation for misconceptions, viewing the learning process as a transformative journey akin to cognitive rehabilitation. Through this CM-CCT constructivist approach, learners are encouraged to engage in critical reflection, self-questioning, and peer discussions, which facilitate the identification of misconceptions. Moreover, CM-CCT provide a structured framework for presenting accurate information about NST, offering a clear depiction of the hierarchical and interconnected nature of nanoscale phenomena. The aim of this study was to evaluate the effectiveness of CM-CCT in correcting the misconceptions of undergraduate university students regarding nanotechnology and the taxonomy of nonmaterial. Prior to the implementation of the CM-CCT, an assessment of pre-existing knowledge of the students was performed through the structure of the observed learning outcomes (SOLO) taxonomy. A quasi-experimental research design was carried out. A total of 70 undergraduate university students, divided into two intact groups, were cross-examined for the study. Further, before and after the instructional tools, an achievement test based on nanotechnology and classification of nonmaterial was conducted, covering all six cognitive domains of the Bloom taxonomy of educational objectives. Data analysis revealed that the instructional tools based on constructivist approach had a statistically significant impact on students for elimination of their misconceptions about nanotechnology, nano science and classification of nonmaterial

Agronomic and physiological indices for reproductive stage heat stress tolerance in green super rice

Optimum growing temperature is necessary for maximum yield-potential in any crop. The global atmospheric temperature is changing more rapidly and irregularly every year. High temperature at the flowering/reproductive stage in rice causes partial to complete pollen sterility, resulting in significant reduction in grain yield. Green Super Rice (GSR) is an effort to develop an elite rice type that can withstand multiple environmental stresses and maintain yield in different agro-ecological zones. The current study was performed to assess the effect of heat stress on agronomic and physiological attributes of GSR at flowering stage. Twenty-two GSR lines and four local checks were evaluated under normal and heat-stress conditions for different agro-physiological parameters, including plant height (PH), tillers per plant (TPP), grain yield per plant (GY), straw yield per plant (SY), harvest index (HI), 1000-grain weight (GW), grain length (GL), cell membrane stability (CMS), normalized difference vegetative index (NDVI), and pollen fertility percentage (PFP). Genotypes showed high significant variations for all the studied parameters except NDVI. Association and principal component analysis (PCA) explained the genetic diversity of the genotypes, and relationship between the particular parameters and grain yield. We found that GY, along with other agronomic traits, such as TPP, SY, HI, and CMS, were greatly affected by heat stress in most of the genotypes, while PH, GW, GL, PFP, and NDVI were affected only in a few genotypes. Outperforming NGSR-16 and NGSR-18 in heat stress could be utilized as a parent for the development of heat-tolerant rice. Moreover, these findings will be helpful in the prevention and management of heat stress in rice

Risk analysis of high frequency precious metals returns by using long memory model

This paper examines the long memory feature in the conditional volatility and Value at Risk calculations of precious metals returns at different time frequencies. In doing so, we employ high frequency data while using FIGARCH models. Furthermore, significant long memory characteristics have been detected in absolute returns by using semiparametric Local Whittle (LW) approximation. The empirical evidence of the local memory parameter across different time intervals gives consistent approximates of the long memory parameter which indicates that the series show some degree of self-similarity. Further, empirical results show that the long memory characteristics remains fully consistent across different time intervals of data for conditional and unconditional volatility measures. This study is useful for investors and traders (with different trading horizons) with regard to forecasting volatility and calculating or implementing trading strategies at different time frequencies

Learning Finite State Models of Observable Nondeterministic Systems in a Testing Context

International audienceLearning models from test observations can be adapted to the case when the system provides nondeterministic answers. In this paper we propose an algorithm for inferring observable nondeterministic finite state machines (ONFSMs). The algorithm is based on Angluin L* algorithm for learning DFAs. We define rules for constructing and updating learning queries taking into account the properties of ONFSMs. Application examples, complexity analysis and an experimental evaluation of the proposed algorithm are provided