Lower Tail Research Articles

The Association between Education and Cognitive Performance Varies at Different Levels of Cognitive Performance: A Quantile Regression Approach

Introduction: Educational differences in cognitive performance among older adults are well documented. Studies that explore this association typically estimate a single average effect of education on cognitive performance. We argue that the processes that contribute to the association between education and cognitive performance are unlikely to have equal effects at all levels of cognitive performance. In this study, we employ an analytical approach that enables us to go beyond averages to examine the association between education and five measures of global and domain-specific cognitive performance across the outcome distributions. Methods: This cross-sectional study included 1,780 older adults aged 58–68 years from the Longitudinal Aging Study Amsterdam. Conditional quantile regression was used to examine variation across the outcome distribution. Cognitive outcomes included Mini-Mental State Examination (MMSE) score, crystallized intelligence, information processing speed, episodic memory, and a composite score of global cognitive performance. Results: The results showed that the associations between education and different cognitive measures varied across the outcome distributions. Specifically, we found that education had a stronger association with crystallized intelligence, MMSE, and a composite cognitive performance measure in the lower tail of performance distributions. The associations between education and information processing speed and episodic memory were uniform across the outcome distributions. Conclusion: Larger associations between education and some domains of cognitive performance in the lower tail of the performance distributions imply that inequalities are primarily generated among individuals with lower performance rather than among average and high performers. Additionally, the varying associations across some of the outcome distributions indicate that estimating a single average effect through standard regression methods may overlook variations in cognitive performance between educational groups. Future studies should consider heterogeneity across the outcome distribution.

Morphometric and Genetic Characterization of Dominant Fish Species in Progo River, Yogyakarta, Indonesia

A study on the morphology and genetics of the three species of dominant wader that live in the Progo River has been conducted. This study aimed to identify the three kinds of dominant waders in the Progo River, their morphology, and their genetics to ensure their right identity. Fish characterization was done by morphological analysis using the truss-morphometric method and genetic analysis using molecular markers. Random amplified polymorphic DNA (RAPD) based on PCR was used for diversity identification for interspecies and between species. Several analyses of water quality parameters (temperature, nitrate, phosphate, and ammonia) were also carried out to determine the habitat’s suitability for the fish’s survival. Based on the results of discriminant function analysis, all wader fish from the Progo River used in this study were classified into three species with the highest differentiation character D4 (distance between the starting point of upper tail fin and the starting point of lower tail fin). Results also show that wader abang fish have similar morphometric characteristics and DNA closer to wader kepe compared to wader pari. The length-weight relationship of wader fish from the Progo River shows that the growth pattern of wader abang and wader kepe is allometric positive, while that of wader pari is allometric negative. The value of the condition factor for wader fish from the Progo River indicates that the environmental habitat of wader fish is good and stable so that it can support the fish growth.

Overcrowding and separation estimates for the Coulomb gas

AbstractWe prove several results for the Coulomb gas in any dimension that follow from isotropic averaging, a transport method based on Newton's theorem. First, we prove a high‐density Jancovici–Lebowitz–Manificat law, extending the microscopic density bounds of Armstrong and Serfaty and establishing strictly sub‐Gaussian tails for charge excess in dimension 2. The existence of microscopic limiting point processes is proved at the edge of the droplet. Next, we prove optimal upper bounds on the ‐point correlation function for merging points, including a Wegner estimate for the Coulomb gas for . We prove the tightness of the properly rescaled th minimal particle gap, identifying the correct order in and a three term expansion in , as well as upper and lower tail estimates. In particular, we extend the two‐dimensional “perfect‐freezing regime” identified by Ameur and Romero to higher dimensions. Finally, we give positive charge discrepancy bounds which are state of the art near the droplet boundary and prove incompressibility of Laughlin states in the fractional quantum Hall effect, starting at large microscopic scales. Using rigidity for fluctuations of smooth linear statistics, we show how to upgrade positive discrepancy bounds to estimates on the absolute discrepancy in certain regions.

A new class of copulas having dependence range larger than FGM-type copulas

We propose a new bivariate symmetric copula with positive and negative dependence properties. The main features of the proposed copula are its simple mathematical structure, wider dependence range compared to FGM copula and its generalizations, and no lower and upper tail dependence. The maximum range of Spearman’s Rho of the proposed copula is [−0.5866,0.5866], which improves the dependence range of the FGM copula and its various generalizations. A new bivariate Rayleigh distribution is developed using the proposed copula, and some statistical properties have been studied. A real data set is analysed to illustrate the proposed bivariate distribution’s relevance in practical contexts.

Are macroeconomic indices fool's gold?

This paper examines how closely aggregate macroeconomic indices such as the Gross Domestic Product (GDP) and market price volatility indices are associated with social welfare when heterogeneous beliefs are present. While it is widely recognised that the GDP fails to capture distributional effects, volatility measures are often argued to supplement the GDP with this regard. Although heterogeneous beliefs are known to be capable of generating large economic and/or price fluctuations, it is not straightforward whether volatility is closely associated with welfare when heterogeneous beliefs are present. By constructing a simulation model of a financial economy with production and credit constraints that allows for heterogeneous beliefs, we show that major discrepancies between aggregate measures, including volatility measures, and ex post welfare are not the exception, but the rule. Also, the paper analyses the mechanism that causes the discrepancies. Our results strongly suggest welfare be measured by observing the distribution of realised consumption across agents and over time — in particular, its lower tail. In short, macroeconomic indices may well easily become a fool's gold.

Discovering Intraday Tail Dependence Patterns via a Full-Range Tail Dependence Copula

In this research, we employ a full-range tail dependence copula to capture the intraday dynamic tail dependence patterns of 30 s log returns among stocks in the US market in the year of 2020, when the market experienced a significant sell-off and a rally thereafter. We also introduce a model-based unified tail dependence measure to directly model and compare various tail dependence patterns. Using regression analysis of the upper and lower tail dependence simultaneously, we have identified some interesting intraday tail dependence patterns, such as interactions between the upper and lower tail dependence over time among growth and value stocks and in different market regimes. Our results indicate that tail dependence tends to peak towards the end of the regular trading hours, and, counter-intuitively, upper tail dependence tends to be stronger than lower tail dependence for short-term returns during a market sell-off. Furthermore, we investigate how the Fama–French five factors affect the intraday tail dependence patterns and provide plausible explanations for the occurrence of these phenomena. Among these five factors, the market excess return plays the most important role, and our study suggests that when there is a moderate positive excess return, both the upper and lower tails tend to reach their lowest dependence levels.

Extreme contributions of conventional investments vis-à-vis Islamic ones to renewables

The growing global awareness of social and environmental issues has led investors to prioritize sustainable investments. This study examines the relationship between ten Islamic and conventional sector indices, which include stocks screened for environmental, social, and governance (ESG) factors, across three energy-related fields: renewable energy, energy efficiency, and oil equipment and services. Using a quantile cross-spectral approach, this research finds a high level of long-term synchronization among all energy-related sectors and indices. However, as markets shift from bearish to bullish, the current relationship between energy-related sectors and Islamic and conventional indices weakens. To support the findings in this research and investigate potential financial implications, this investigation applies a causality-in-quantiles approach. The research in this study shows a bidirectional causal relationship between conventional and Islamic indices, particularly in the energy efficiency sector during bearish market conditions. At lower tails, ESG market indices are found to cause renewable energy products, suggesting a hedging mechanism. The findings of this study assert that investments that do not possess any ESG shortcomings are imperative for effectively bolstering renewable energy companies and fostering opportunities for energy efficiency. These conclusions hold considerable ramifications for energy policymakers as they strive to devise more robust financial mechanisms that can provide substantial support to the burgeoning green sector.

99mTc/123I Dual-Radionuclide Correction for Self-Scatter, Down-Scatter, and Tailing Effect for a CZT SPECT with Varying Tracer Distributions.

SPECT systems distinguish radionuclides by using multiple energy windows. For CZT detectors, the energy spectrum has a low energy tail leading to additional crosstalk between the radionuclides. Previous work developed models to correct the scatter and crosstalk for CZT-based dedicated cardiac systems with similar 99mTc/123I tracer distributions. These models estimate the primary and scatter components by solving a set of equations employing the MLEM approach. A penalty term is applied to ensure convergence. The present work estimates the penalty term for any 99mTc/123I activity level. An iterative approach incorporating Monte Carlo into the iterative image reconstruction loops was developed to estimate the penalty terms. We used SIMIND and XCAT phantoms in this study. Distribution of tracers in the myocardial tissue and blood pool were varied to simulate a dynamic acquisition. Evaluations of the estimated and the real penalty terms were performed using simulations and large animal data. The myocardium to blood pool ratio was calculated using ROIs in the myocardial tissue and the blood pool for quantitative analysis. All corrected images yielded a good agreement with the gold standard images. In conclusion, we developed a CZT crosstalk correction method for quantitative imaging of 99mTc/123I activity levels by dynamically estimating the penalty terms.

Switch-Based Quorum Coordination for Low Tail Latency in Replicated Storage

Switch-Based Quorum Coordination for Low Tail Latency in Replicated Storage

Longitudinal Wind Tunnel Tests of the PROSIB 19-Pax Airplane

This research paper delves into the longitudinal wind tunnel tests conducted on the 19-passengers aircraft model of the Italian PROSIB project. The concept is an innovative small air transport airplane with distributed propellers and hybrid-electric powerplant. The primary objective was to assess its stability and control characteristics in power-off conditions. In addition to the usual investigation of the aircraft components, the study introduced a belly-mounted pod, which served as a battery storage unit, and explored two distinct tail configurations: a body-mounted (low) tail and a T-tail (high). The results obtained from these tests generally confirmed the anticipated characteristics of the aircraft design. The experiments provided data on aerodynamic forces and moments, giving useful indications on the effects of a belly-mounted battery storage unit and tail layout on the aircraft stability and control characteristics. This information could be used by aircraft designers to size an airplane of the same class.

Bivariate Analysis of Birth Weight and Gestational Age by Bayesian Distributional Regression with Copulas

We analyze perinatal data including biometric and obstetric information as well as data on maternal smoking, among others. Birth weight is the primarily interesting response variable. Gestational age is usually an important covariate and included in polynomial form. However, in opposition to this univariate regression, bivariate modeling of birth weight and gestational age is recommended to distinguish effects on each, on both, and between them. Rather than a parametric bivariate distribution, we apply conditional copula regression, where the marginal distributions of birth weight and gestational age (not necessarily of the same form) and the dependence structure are modeled conditionally on covariates. In the resulting distributional regression model, all parameters of the two marginals and the copula parameter are observation specific. While the Gaussian distribution is suitable for birth weight, the skewed gestational age data are better modeled by the three-parameter Dagum distribution. The Clayton copula performs better than the Gumbel and the symmetric Gaussian copula, indicating lower tail dependence (stronger dependence when both variables are low), although this non-linear dependence between birth weight and gestational age is surprisingly weak and only influenced by Cesarean section. A non-linear trend of birth weight on gestational age is detected by a univariate model that is polynomial with respect to the effect of gestational age. Covariate effects on the expected birth weight are similar in our copula regression model and a univariate regression model, while distributional copula regression reveals further insights, such as effects of covariates on the association between birth weight and gestational age.

Connectedness and spillover between African equity, commodity, foreign exchange and cryptocurrency markets during the COVID-19 and Russia-Ukraine conflict

Since the onset of the COVID-19 pandemic, financial and commodity markets have exhibited significant volatility and displayed fat tail properties, deviating from the normal probability curve. The recent Russia-Ukraine war has further disrupted these markets, attracting considerable attention from both researchers and practitioners due to the occurrence of consecutive black swan events within a short timeframe. In this study, we utilized the Quantile-VAR technique to examine the interconnectedness and spillover effects between African equity markets and international financial/commodity assets. Daily data spanning from January 3, 2020, to September 6, 2022, was analyzed to capture tail risks. Our main findings can be summarized as follows. Firstly, the level of connectedness in returns is more pronounced in the lower and upper tails compared to the median. Secondly, during times of crisis, African equity markets primarily serve as recipients of systemic shocks. Lastly, assets such as Silver, Gold, and Natural Gas exhibit greater resilience to systemic shocks, validating their suitability as hedging instruments for African equities, in contrast to cryptocurrencies and international exchange rates. These findings carry significant implications for policymakers and investors in Africa equities.

Developed and Validated for the Estimation of Tapinarof in Topical Formulation and Active Pharmaceutical Ingredients.

Its broad applicability and capacity to separate numerous components in a single chromatographic run led to the initial recognition of reversed-phase (RP)-HPLC as an analytical technique. The objective of this study was to create a straightforward and reliable method for accurately and precisely measuring the amount of tapinarof in both the topical formulation and the active pharmaceutical ingredient. Additionally, a robust HPLC assay was developed specifically for analyzing the topical formulation. In this study, chromatographic analysis was conducted using a Kromosil C18 column with dimensions of 250 × 4.6 mm and a particle size of 5 microns. The mobile phase consisted of a phosphate buffer and methanol in a ratio of 100:900 (v/v). The flow rate was set at 1.0 mL/min, with an injection volume of 10 µL and a run time of 6 min using isocratic elution. UV detection was performed at a wavelength of 313 nm, and the temperature was maintained at 30°C. The analysis showed well-separated peaks with a high number of theoretical plates, a low tailing factor, and consistent retention time. Validation of the method was conducted, and all validation parameters were found to be within the acceptable limits. A method that is simple, accurate, and precise has been developed to estimate the amount of tapinarof in a topical formulation and active pharmaceutical ingredient. The optimized method involved the use of a column temperature set at 30°C, 90% methanol as the mobile phase, and a flow rate of 1.0 mL/min. The retention time for tapinarof was determined to be 2.88 min. The method exhibited linearity in the concentration range of 5 to 30 µg/mL (with an R2 value greater than 0.999) for tapinarof. The topical formulated cream and active pharmaceutical ingredient showed more than 90% dissolution within 5 min. The method developed in this study utilized photo diode array (PDA) for peak integrity and purity confirmation, making it suitable for the quantification of tapinarof in both topical formulations and active pharmaceutical ingredients. The method was validated and can be recommended for routine analysis in QC laboratories.

The impact of economic policy uncertainty on stock types while considering the economic cycle. A quantile regression approach

PurposeThis study aims to analyse the effects of Economic Policy Uncertainty (EPU) on the return of growth/value and small/large-cap stocks during expansionary and recessionary periods across a conditional distribution.Design/methodology/approachThe authors selected a sample covering the period between 01/1995–05/2021. Quantile regressions were applied to the EPU and Russell indices. Business cycles were established following the NBER.FindingsThe results show that EPU has a negative effect on stocks with the intensity of the effect depending on the stock's profile. Small-cap and growth stocks were found to be most sensitive to EPU, especially during recessions. The negative effect is moderated by the economic cycle but is progressively diluted at the lower tail of the stock return distribution.Practical implicationsThe findings shed more light on investment strategies for growth/value investors that pursue opportunities arising from a changing economic cycle.Originality/valueThis study makes the following contributions: (1) explores the impact of EPU on the return of different stocks across a conditional distribution, and (2) provides evidence on how the economic cycle influences EPU impact on growth/value stocks and small/large stocks.

Asymptotic Predictive Inference of Negative Lower Tail Index Distributions

ABSTRACT In this paper, the results of El-Adll et al. [Asymptotic prediction for future observations of a random sample of unknown continuous distribution, Complexity 2022 (2022), Art. ID 4073799], are extended to the lower negative tail index distributions. Three distinct estimators of the lower negative tail index are proposed, as well as an asymptotic confidence interval. Moreover, different asymptotic predictive intervals for future observations are constructed for distributions attracted to the lower extreme value distribution with a negative tail index. Furthermore, the asymptotic maximum likelihood estimator (AMLE) of the shape parameter, as well as an asymptotic maximum likelihood predictor (AMLP), are obtained. Finally, extensive simulation studies are conducted to demonstrate the efficiency of the proposed methods.

Morphometrics and long-weight relationship Halmahera walking shark (Hemiscyllium halmahera, Allen, 2013) population in Morotai Island Sea, North Maluku, Indonesia

Morotai Island is under the influence of plates, Indonesian Throughflow, Halmahera Eddy, New Guinea Coastal Undercurrent (NGCUC) and is located in the coral reef triangle. Halmahera walking shark (Hemiscyllium halmahera) was found in the Morotai Island Sea. The aim was to study the morphometric and length-weight relationship of H. halmahera on Morotai Island. Sample collection of H. halmahera in South Morotai, North Morotai and South West Morotai. H. halmahera samples were taken using scuba diving at a depth of 3-10 meters. The morphometric measurements were 11 variables TL (total length)- LTL (lower tail length). The diversity of morphometric characteristics found was analyzed using the Principal Component Analysis (PCA) method. Analysis length-weight relationship using linear regression equation. The results found 30 individuals (South Morotai = 8, North Morotai = 9, South West Morotai = 8, and East Morotai = 5) and the frequency of sex presence individuals (male = 16 and female = 14). Morphometric parameters found variation in each individual. PCA analysis found that the distribution of morphometric characteristics had body size variation. Dendogram is divided into Cluster I (North Morotai dan South West Morotai) dan Cluster II (South Morotai dan East Morotai). The length-weight relationship found negative allometric growth.

Synergistic removal of NOx and CB by Co-MnOx catalysts in a low-temperature window

The simultaneous removal of NOx and CVOCs in a deNOx unit has gained significant attention in recent years. However, efficient co-removal of NOx and CVOCs is still a challenge due to the low tail gas emission temperatures in the non-electric industry. To address this, m-MnOx (m = Sn or Co) catalysts were prepared based on the Mn-based catalyst to investigate their catalytic performance in removing NOx and CB.The results demonstrated that the Co-MnOx catalyst exhibited the best catalytic activity, achieving over 90 % NOx conversion within the temperature window of 105–275 °C, while CB conversion rates surpassed 90 % above 180 °C. The characterization results revealed that Co doping formed MnCo2O4 adding additional Lewis acid sites and promoted the conversion of Mn2+ to Mn3+ and Mn4+, thereby improving the redox ability and surface acidity of the Co-MnOx catalyst. DFT simulations revealed that Co addition improved the adsorption of NH3 and CB on the Co-MnOx catalyst and effectively reduced the energy barriers for N-H cleavage and oxygen vacancy formation. This work is hoped to provide an important reference for the further design and optimization of efficient low-temperature NOx/CB synergistic removal catalysts.

Molecular mass engineering for filaments in material extrusion additive manufacture

Abstract3D printing of thermoplastics through local melting and deposition via material extrusion additive manufacturing provides a simple route to the near net‐shape manufacture of complex objects. However, the mechanical properties resulting from these 3D printed structures tend to be inferior when compared to traditionally manufactured thermoplastics. These unfavorable characteristics are generally attributed to the structure of the interface between printed roads. Here, we illustrate how the molecular mass distribution for a model thermoplastic, poly(methyl methacrylate) (PMMA), can be tuned to enhance the Young's modulus of 3D printed plastics. Engineering the molecular mass distribution alters the entanglement density, which controls the strength of the PMMA in the solid state and the chain diffusion in the melt. Increasing the low molecular mass tail increases Young's modulus and ultimate tensile strength of the printed parts. These changes in mechanical properties are comparable to more complex routes previously reported involving new chemistry or nanoparticles to enhance the mechanical performance of 3D printed thermoplastics. Controlling the molecular mass distribution provides a simple route to improve the performance in 3D printing of thermoplastics that can be as effective as more complex approaches.

Trend analysis of dependence between rainfall and storm tides in coastal cities.

Compound flooding from rainfall and storm tides is prone to occur in coastal cities. The identification of them is essential for controlling urban flooding. First, the dependence between rainfall and storm tides is quantified by Kendall's τ, Spearman's ρ, and tail dependence coefficient. Then, a bivariate copula-based probability distribution model is built to calculate the joint and conditional probability of rainfall and storm tides. Finally, MK and SQMK methods are employed to detect the trends of the dependence and joint probability. The results show that: (1) The dependence between strong rainfall and corresponding storm tides is much higher than that of small rainfall and storm tides, and the effect of tropical cyclones may be one of the reasons. (2) The dependence between rainfall and storm tides is the largest in October and the smallest in July. More attention should be paid to the compound flooding caused by rainfall and storm tides in October for Haikou. (3) The upper tail dependence coefficient of the rainfall and storm tides is significantly greater than the lower tail dependence coefficient and exhibits a significant positive trend. The results can provide additional insights into the effect of rainfall and storm tides for coastal flood management.

Pitch posture regulation in Peking geckos (Gekko swinhonis): assessing the role of tails before take-off in upward jumping

Abstract Small vertebrates, such as geckos, often use their tails to regulate their posture after take-off and suppress abnormal rotations in mid-air (such as sliding and falling). However, research on tail function before take-off remains scarce, particularly when animals overcome gravity to jump upward. This study examined tailed and tailless geckos’ ability to jump over obstacles. The tails swung up and reached their upper limits during take-off, corresponding to a continuous increase in their trunk elevation angle. Compared to tailless geckos, geckos with intact tails had lower body and tail angular velocities. In addition, tailed geckos achieved larger take-off angles and higher jumps; moreover, their take-off angles were consistent with their velocity angles. Theoretical analyses demonstrated that the tail and its upward swing before take-off could benefit lifting the forelimb and hindlimbs off the ground, expanding the stability area of their centre of mass (COM). A robot prototype verified the effect of the tail and its swing on trunk elevation before take-off. Other parameters, such as the posture of the hindlimbs (support length and angle) and initial angle of the trunk, affect posture regulation. This study significantly extends our knowledge in animal locomotion and provides indispensable information for improving robot jumping ability.