Classical Distribution Research Articles

Evolution of the ukrainian eurobond market

The Ukrainian Eurobond market will become a critically important source for raising funds in the post-war years. This requires a quantitative analytical study of the factors affecting this market, but such studies are practically non-existent today. The aim of the article is to design the periodization of the Ukrainian Eurobond market, reveal the regularities of its functioning and analyze the interrelation of the risk and return. There is an hypothesis, as: Eurobond return rate can be positively correlated with the systematic risk. Five main stages of development of the Ukrainian Eurobond market (including corporate issues) were found. The main factors were analyzed that influenced the volumes and the coupon rate at the placement of the 2001–2021 issues at each of the first four stages of market development. It is shown that the distribution of issuers of corporate Eurobonds by the total volume of issues is a classic distribution with the "fat tail" and the reason for this distribution were shown. Regression analy­sis methods were used to analyze the relation­ship between sovereign risk of Ukraine and coupon rate at the placement of the corporate Ukrainian Eurobonds. Two market "anomalous" in the Ukrainian Eurobond market were found out: periods with exceeding of average coupon rate at the placement of the government Ukrainian Eurobonds over the same rate of the corporate Ukrainian Eurobonds; decree­sing of the sovereign risk statistically accompa­nied with increasing of the average coupon rate at the placement of the corporate Ukrainian Euro­bonds. The first "anomaly" explained by the increased optimism of investors in the late 10s and early 20s. The second "anomaly" associated with the rapid expansion of the market and the attraction of relatively risky corporate issues. Using the example of "Voda­fone Ukraine" Eurobonds, the influence was analyzed of the introduction of martial law and restructuring events on prices and yield to maturity of the Ukrainian corporate Eurobonds in 2021–2023 years.

Research on the Validity of Bootstrap LM-Error Test in Spatial Random Effect Models

Under the condition of non-classical distributed errors, the test for spatial dependence in spatial panel data models is still a problem waiting to be solved. In this paper, we apply the FDB (Fast Double Bootstrap) method to spatial panel data models to test spatial dependence. In order to research the validity of the Bootstrap LM-Error test in spatial random effect models under the condition that the error term obeys a normal distribution, heteroscedasticity, or time-series correlation, we construct Bootstrap LM-Error statistics and make use of Monte Carlo simulation from size distortion and power aspects to carry out our research. The Monte Carlo simulation results show that the asymptotic LM-Error test in the spatial random effects model has a large size of distortion when the error term disobeys classical distribution. However, the FDB LM-Error test can effectively correct the size distortion of the asymptotic test with the precondition that there is nearly no loss of power in the FDB test. Obviously, compared to the asymptotic LM-Error test, the FDB LM-Error test is a more valid method to test spatial dependence in a spatial random effects model.

Optimizing berth-crane allocation considering tidal effects using chaotic quantum whale optimization algorithm

With the normalization of the global epidemic, shipping has gradually resumed, resulting in a surge in port throughput. Terminal managers are having great difficulty in making container ports be stable, orderly, and efficient. For small and medium-sized ports, making full use of the tidal water level to increase the operation time of large ships significantly improves the efficiency of port operations. Therefore, considering the impact of tidal factors on the operation of container ports, this paper firstly proposes a new berths and quay cranes allocation optimization model, T-B&QC, that minimizes the distance between the actual berthing berth and the preferred berth, the port time cost of ships and the number of quay crane movements as the optimization objectives, under constraints that consider tidal factors. Then, to solve the T-B&QC model using chaotic mapping and quantum theory, the Whale Optimization Algorithm (WOA) is integrated by using the Chaotic Quantum Rotating Gate Algorithm (CQRGA) and the Quantum Not Gate Algorithm (QNGA), whale coding rules are designed, and the Feasible-Integer Processing Algorithm (WF-IP) is established. Afterwards, the Chaotic Quantum Whale Optimization Algorithm, CQWOA, is proposed. Finally, the CQWOA is used to develop a new berth and quay crane allocation optimization method, T-B&QC_CQWOA. Subsequently, data from an actual seaport container port is used to test the reliability and superiority of the proposed distributing approach and the established optimizing algorithm. Numerical results demonstrate that the proposed distributing approach outperforms the classical distribution models that are selected herein, and the CQWOA yields a coordinated schedule of higher quality than the others in the process of solving the model.

FITTING G-FAMILY PROBABILITY DISTRIBUTION AT THE RAINFALL DATA OF RAJSHAHI DISTRICT, BANGLADESH

Classical statistical distributions were recognized tool in case of different areas such as biological science, economics, finance, engineering and environmental science. But these types of distribution have some limitations for modeling real data. Researchers are trying to find out the best performing statistical distribution for modeling environmental data by adding extra parameters in these existing distributions which provide super flexibility in modeling. These extend to new families of these distributions generally defined as G-family distribution. Rainfall is one of the most important natural resources for agricultural production. The excess and deficit amount of rainfall sometimes be dangerous for agriculture production. So, the prior knowledge about the pattern of rainfall will help to solve food insecurity, water erosion and water pollution problems. In this study we compare the performance of Gamma uniform G, Log gamma G type-I, Log gamma G type-II , Marshall-Olkin G and Weibull G distribution where we consider lomax, f, chen and Weibull distribution as baseline distribution for modeling the rainfall data in case of Rajshahi district Bangladesh. The monthly rainfall data from January 1971 to December 2020 consider as study period. The empirical study shows that Marshall-Olkin Chen distribution gives better fitting results in case of Rajshahi district. This study will help policy makers to become aware of upcoming situations for solving water related problems.

DIVERSITY AND REGENERATION OF WOODY PLANTS OF LOGONE BIRNI FLOODPLAIN VEGETATION IN THE FAR NORTH REGION OF CAMEROON

This study aims to contribute to the conservation and sustainable management of the Logone-Birni floodplains in Cameroon. In total, 27 plots of 100 m x 100 m plots of were laid out in 3 land use types (protected area, grazing area and agricultural area). Within each plot, all woody individuals having ≥ 10 cm circumference at breast height (> 1.3 m) were identified, and all the stems with a circumference ≤ 10 cm were considered as seedlings. A total of 43 timber species belonging to 35 genera and 21 families were harvested. Shannon-Weaver diversity ranged from 1.77-2.39 and the Pielou equitability index from 0.84-0.88 with low values in agricultural areas and higher values in protected and grazing areas. The distribution of stems according to diameter and height showed that all stands exhibit classic exponential decay distribution ‘‘L’’ or ‘‘J’’ inverted, reflecting the predominance of individuals with small diameters. The regeneration rates of the stand vary from 0.81 to 51.56%, indicating a difficult regeneration due partly to anthropogenic activities. It also appears that given the low diversity and the difficult regeneration of the stand, it is important, even crucial, to manage this plain to ensure the conservation and sustainable management of the biological resources that it hosts.

ON THE MOMENTS OF THE 3-PARAMETER GOMPERTZ DISTRIBUTION

Gompertz distribution is a classical probability distribution extensively used in actuarial science, reliability, and survival analysis. Gompertz distribution also plays a role in various fields, such as biology, economics, and marketing analysis. Some extensions of this distribution have been studied and applied to various problems. In this article, we are concerned with some statistical properties of a 3-parameter Gompertz distribution. This extension of the Gompertz distribution introduced has been used in studying competing risk survival analysis. Our main results are the derivation of moments of this distribution and other statistical properties related to moments, such as moment generating function, mean residual life function, mean inactivity time and Lorenz curve. These results will serve as a complement to the theoretical aspect of the analysis of the distribution.

Modeling COVID-19 data with a novel neutrosophic Burr-III distribution

In this study, we have presented a novel probabilistic model called the neutrosophic Burr-III distribution, designed for applications in neutrosophic surface analysis. Neutrosophic analysis allows for the incorporation of vague and imprecise information, reflecting the reality that many real-world problems involve ambiguous data. This ability to handle vagueness can lead to more robust and realistic models especially in situation where classical models fall short. We have also explored the neutrosophic Burr-III distribution in order to deal with the ambiguity and vagueness in the data where the classical Burr-III distribution falls short. This distribution offers valuable insights into various reliability properties, moment expressions, order statistics, and entropy measures, making it a versatile tool for analyzing complex data. To assess the practical relevance of our proposed distribution, we applied it to real-world data sets and compared its performance against the classical Burr-III distribution. The findings revealed that the neutrosophic Burr-III distribution outperformed than the classical Burr-III distribution in capturing the underlying data characteristics, highlighting its potential as a superior modeling toolin various fields.

Neutrosophic Topp-Leone Distribution for Interval-Valued Data Analysis

Many issues in real life are riddled with confusion, vagueness, and ambiguity. The Topp-Leone distribution is a significant one-parameter probability distribution in the context of classical probability theory. There is a gap in the literature when it comes to dealing with circumstances involving interval-valued data with a classical Topp-Leone distribution. So, in this connection, neutrosophic Topp-Leone distribution is presented in this paper as an extension of the traditional Topp-Leone distribution. The new neutrosophic distribution takes into account the indeterminacy and crisp form of interval-valued distributions. The suggested distribution's mathematical features were derived, including moments and related measures, quantile function, survival, hazard, inverted hazard functions, and mills ratio. Maximum likelihood is used to estimate model parameters. Finally, a complex dataset is utilized to show the usefulness of the proposed distributions.

Self-defining memories in older adults: Distribution across lifespan and characteristics of the reminiscence bump

Many studies have investigated the temporal distribution of autobiographical memories, but none has focused on Self-Defining Memories (SDMs), i.e. memories that are particularly important for personal identity, in a large non-clinical sample. No study has examined the temporal distribution of Self-Defining Memories (SDMs), i.e. memories that are particularly important for personal identity, in a large non-clinical sample of older adults. Moreover, we examined for the first time the characteristics of SDMs located in RB. Two hundred and eighty elderly adults aged from 65 to 90 years old reported three SDMs. Participants were non-institutionalized retirees screened for global cognitive function. Participants were asked to recall three SDMs. They also completed the Mini-Mental State Examination. The period from 0 to 9 years corresponds to a very limited recall of SDMs. A RB appears between for the 10–24 years period. Recalled memories are enhanced after the age of 50. The temporal distribution of recalled SDMs differed according to thematic content and emotion. The percentage of positive SDMs was the highest in RB compared with other life periods. Specificity, meaning-making, tension, redemption and contamination did not differ for bump SDMs versus non-bump SDMs. In addition, differences between men and women were observed. Our results confirm the existence of the classical temporal distribution of autobiographical memories for SDMs. Recalling positive bump SDMs might improve well-being in older adults.

Postural control in gymnasts: anisotropic fractal scaling reveals proprioceptive reintegration in vestibular perturbation.

Dexterous postural control subtly complements movement variability with sensory correlations at many scales. The expressive poise of gymnasts exemplifies this lyrical punctuation of release with constraint, from coarse grain to fine scales. Dexterous postural control upon a 2D support surface might collapse the variation of center of pressure (CoP) to a relatively 1D orientation-a direction often oriented towards the focal point of a visual task. Sensory corrections in dexterous postural control might manifest in temporal correlations, specifically as fractional Brownian motions whose differences are more and less correlated with fractional Gaussian noises (fGns) with progressively larger and smaller Hurst exponent H. Traditional empirical work examines this arrangement of lower-dimensional compression of CoP along two orthogonal axes, anteroposterior (AP) and mediolateral (ML). Eyes-open and face-forward orientations cultivate greater variability along AP than ML axes, and the orthogonal distribution of spatial variability has so far gone hand in hand with an orthogonal distribution of H, for example, larger in AP and lower in ML. However, perturbing the orientation of task focus might destabilize the postural synergy away from its 1D distribution and homogenize the temporal correlations across the 2D support surface, resulting in narrower angles between the directions of the largest and smallest H. We used oriented fractal scaling component analysis (OFSCA) to investigate whether sensory corrections in postural control might thus become suborthogonal. OFSCA models raw 2D CoP trajectory by decomposing it in all directions along the 2D support surface and fits the directions with the largest and smallest H. We studied a sample of gymnasts in eyes-open and face-forward quiet posture, and results from OFSCA confirm that such posture exhibits the classic orthogonal distribution of temporal correlations. Head-turning resulted in a simultaneous decrease in this angle Δθ, which promptly reversed once gymnasts reoriented their heads forward. However, when vision was absent, there was only a discernible negative trend in Δθ, indicating a shift in the angle's direction but not a statistically significant one. Thus, the narrowing of Δθ may signify an adaptive strategy in postural control. The swift recovery of Δθ upon returning to a forward-facing posture suggests that the temporary reduction is specific to head-turning and does not impose a lasting burden on postural control. Turning the head reduced the angle between these two orientations, facilitating the release of postural degrees of freedom towards a more uniform spread of the CoP across both dimensions of the support surface. The innovative aspect of this work is that it shows how fractality might serve as a control parameter of adaptive mechanisms of dexterous postural control.

Flexible-dimensional L-statistic for mean estimation of symmetric distributions

Estimating the mean of a population is a recurrent topic in statistics because of its multiple applications. If previous data is available, or the distribution of the deviation between the measurements and the mean is known, it is possible to perform such estimation by using L-statistics, whose optimal linear coefficients, typically referred to as weights, are derived from a minimization of the mean squared error. However, such optimal weights can only manage sample sizes equal to the one used to derive them, while in real-world scenarios this size might slightly change. Therefore, this paper proposes a method to overcome such a limitation and derive approximations of flexible-dimensional optimal weights. To do so, a parametric family of functions based on extreme value reductions and amplifications is proposed to be adjusted to the cumulative optimal weights of a given sample from a symmetric distribution. Then, the application of Yager’s method to derive weights for ordered weighted average (OWA) operators allows computing the approximate optimal weights for sample sizes close to the original one. This method is justified from the theoretical point of view by proving a convergence result regarding the cumulative weights obtained for different sample sizes. Finally, the practical performance of the theoretical results is shown for several classical symmetric distributions.

SISTEM AVANSAT DE ÎNCĂRCARE WIRELESS DE MARE PUTERE CU TRANSFORMATOR ELECTRONIC PENTRU VEHICULE ELECTRICE

"The rapid transition from internal combustion engine (ICE) vehicles to electric vehicles (EVs) is accompanied by many technical and economic challenges. One is related to the improvements the power distribution grid requires due to the increasing number of charging power stations, which will require important investments and improvements. A promising technology that may contribute to these improvements is the solid-state transformer (SST), which could be used to replace the classical distribution transformers. Such an SST is made of complex power electronics components and is more flexible than the classical transformers, being able to regulate easily the voltage and frequency in the secondary circuit. This paper is focused on the numerical simulation of a flexible high-power wireless charging system that may be used for heavy-duty and commercial electric vehicles. The numerical computations are carried out using Matlab/Simulink environment and allow us to estimate the performance of such complex systems."

Acoustic Target Strength of Thornfish (Terapon jarbua) Based on the Kirchhoff-Ray Mode Model

Thornfish (Terapon jarbua) is a significantly commercial species inhabiting the shallow coastal waters of the Indo-Pacific Ocean. To achieve effective underwater acoustic (UWA) monitoring on the abundance and population dynamics of this species, the comprehensive target strength (TS) characteristics should be investigated and understood. In this study, the Kirchhoff-ray mode (KRM) model was adopted to evaluate and analyze the acoustic TS of T. jarbua and its variations with the sound wave frequency, pitch angle distributions as well as morphological characteristics in the South China Sea. A total of 19 samples were captured and evaluated at four types of frequencies of 38 kHz, 70 kHz, 120 kHz, and 200 kHz. The results demonstrated that the TS of T. jarbua varied with the pitch angle shifts, and the number of secondary TS peaks increased as the increasing frequency accordingly. Two classic pitch angle distributions that included N[−5°, 15°] and N[0°, 10°] were adopted to calculate the average TS of T. jarbua. The fitted TS-L regression formulations and the standard b20 form equations were determined at different pitch angle distributions as well as frequencies. These results could support the accurate and reliable UWA abundance estimation in the South China Sea to facilitate a better understanding of the abundance and population dynamics of T. jarbua.

Abstract 7494: Pan-cancer analysis of circulating tumor organoid drug sensitivity revealed differential distribution of viability dependence among cancer hallmark modules

Abstract Background: Patient-derived organoids represent an opportunity into deciphering human cancer biology at the personal-level resolution. Phenotyping living cell properties, such as drug sensitivity, complements deep sequencing to improve the prediction of cancer treatment response and holds promises for functional precision medicine. Modern cancer therapeutics target genetic alterations in modular networks, also known as cancer hallmarks, which drive biological essentialities for cancer progression. However, it remains elusive the relative robustness of each module among the naturally occurring solid tumors. Methods: In order to explore this issue, we analyzed a drug sensitivity database of a collection of circulating tumor cells-derived organoids (CDO) from 532 patients with advanced/metastatic solid tumors to 15 chemicals. In this collection, each CDO was derived from 20 ml peripheral blood on a binary colloid crystal cell culture system over 4 weeks. CDO were tested for survival fraction at the Cmax of the designated chemicals. Cell viability was measured with ATP abundance normalized to vehicle controls. For each chemical tested, the probability density function (PDF) of drug sensitivity was fitted to log normal distribution and goodness of fit was analyzed with Kolmogorov Smirnov test with the significance cut-off set to 0.05. The targeted biological pathway of each chemical was mapped to canonical human pathways in the Gene Ontology and KEGG databases. Strength of the specific evolution conserved module (ECM) was evaluated with the published analysis using clustering by inferred models of evolution (CLIME) algorithm. Results: There were 25 types of tumors in the database. The top 3 tumor types were soft-tissue sarcoma, breast cancers, central nervous system tumor. The average number in each tumor type was 21. The PDF of commonly known chemotherapeutic agents, such as gemcitabine, doxorubicin, docetaxel followed log normal distribution. In contrast, the PDF of commonly known biological targeted agents such as everolimus, cabozantinib or enzalutamide do not. For chemicals whose PDF followed a log normal distribution, the biological pathways that were affected tend to have a higher strength of ECM value. Conclusions: Our early analysis revealed the feasibility to quantitatively estimate the robustness of biological pathways in the cancer hallmark modules with a CDO bank. The biological implication of deviation from classical log normal distribution for biologically targeted agents warrants further investigation. Citation Format: Yihsuan Chen, Shih-Pei Wu, Yin-Ju Chen, Long-Sheng Lu. Pan-cancer analysis of circulating tumor organoid drug sensitivity revealed differential distribution of viability dependence among cancer hallmark modules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7494.

Lessons from a scoping review: Clinical presentations of central centrifugal cicatricial alopecia

Central centrifugal cicatricial alopecia (CCCA) nomenclature describes a typical clinical presentation of cicatricial hair loss that begins on the vertex scalp with progressive, symmetric, and centrifugal evolution. However, atypical presentations have been noted clinically by the authors and reported in the literature. We sought to characterize the distribution of hair loss in published cases of adult patients with CCCA. A 3-step search process was used to evaluate research articles in Cumulative Index to Nursing & Allied Health, EMBASE, Google Scholar, MEDLINE, Scopus, and Web of Science databases. Studies with scalp photography or description of hair loss distribution were included. Three researchers evaluated eligible studies for clinical subtypes. Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review was used to report results. Ninety-nine studies consisting of 281 cases of CCCA were included. Hair loss distributions included variants of the classic presentation along with distinct subtypes such as patchy, occipital, parietal, frontal, temporal, and trichorrhexis. Studies had significant homogeneity, as the classic distribution of CCCA was commonly reported. Additionally, clinically diagnosed cases may have concurrent diagnoses, and numerous studies did not report trichoscopy findings. CCCA terminology may not always be reflective of clinical presentation. Understanding atypical presentations is essential to inform appropriate and targeted treatment.

Dust Ion Acoustic Solitary Waves in Plasma with Cairns Distributed Electrons and New Classical Distribution of Ions

Dust Ion Acoustic Solitary Waves in Plasma with Cairns Distributed Electrons and New Classical Distribution of Ions

Impact of european funds upon rural development in the European Union

Rural Development Funds are an important part of the European Union strategies, under the Common Agricultural Policy. They should help in the development of rural areas, which are the most subjected to poverty and social depravation. The aim of this study is to evaluate the impact of these funds upon rural development in an attempt to assess the efficiency of their usage. To do this, we use data for the 27 European Union members states for the 2000 – 2022 period. Data related to productivity in agriculture, employment and poverty in rural areas is used as dependent and modelled with the help of dynamic panel regression against the amount of money used from these funds. We show that as rural development funds increased in time, poverty decreased, which is an important indicator of efficiency. Additionally, while the variables related to the rural areas, like importance of agriculture in the national economy, employment and poverty in rural areas follow the classical spatial distributions on the West-East direction, the use of rural development funds does not. Absorbed rural development funds have significantly impacted the gross value added in agriculture, employment, and poverty in rural areas. Our most important result is the inverse relationship between rural development funds absorbed and the percentage of rural people at risk of poverty and social exclusion, clearly pointing out the need for continuous support for rural development.

Python Software Tool for Diagnostics of the Global Navigation Satellite System Station (PS-NETM)–Reviewing the New Global Navigation Satellite System Time Series Analysis Tool

The time series of GNSS coordinates contain signals caused by the age-related movement of tectonic plates, the deformation of the Earth’s surface, as well as errors at different time scales from sub-daily tidal deformation to the long-term deformation of the surface load. Depending on the nature of the signal, specific approaches are used for both the visual interpretation and pre-processing of time series and their statistical analysis. However, none of the present software analyzes the nature of the residual errors but assumes their random nature and obedience to the classical normal distribution. One of the methods for analyzing the time series of coordinates with residual, unaccounted-for systematic errors is the non-classical error theory of measurements. The result of this work is a developed software solution for analyzing the time series of GNSS coordinates to test their normality, or in other words, to test whether a particular GNSS station is subject to the influence of small, unaccounted-for errors. Conclusions: After testing our software on four reference stations in Europe, we concluded that none of the chosen stations followed the normal law of distribution; thus, it is vital to perform such tests before conducting any experiments on the time series from reference stations.

10 Gb/s classical secure key distribution based on temporal steganography and private chaotic phase scrambling

Secure distribution of high-speed digital encryption/decryption keys over a classical fiber channel is strongly pursued for realizing perfect secrecy communication systems. However, it is still challenging to achieve a secret key rate in the order of tens of gigabits per second to be comparable with the bit rate of commercial fiber-optic systems. In this paper, we propose and experimentally demonstrate a novel solution for high-speed secure key distribution based on temporal steganography and private chaotic phase scrambling in the classical physical layer. The encryption key is temporally concealed into the background noise in the time domain and randomly phase scrambled bit-by-bit by a private chaotic signal, which provides two layers of enhanced security to guarantee the privacy of key distribution while providing a high secret key rate. We experimentally achieved a record classical secret key rate of 10 Gb/s with a bit error rate lower than the hard-decision forward error correction (HD-FEC) over a 40 km standard single mode fiber. The proposed solution holds great promise for achieving high-speed key distribution in the classical fiber channel by combining steganographic transmission and chaotic scrambling.

Brown adipose tissue – magnetic resonance imaging (MRI) appearance of these physiological fat deposits in a newborn

Brown adipose tissue (BAT) is responsible for thermogenesis in neonates and infants in response to cold environment. 18F-fluorodeoxyglucose positron emission tomography is the reference for imaging of BAT, but it is a functional imaging modality and hence lacks sensitivity due to varying patient and environmental factors. Magnetic resonance imaging (MRI) lacks the use of radioactivity and ionizing radiation and can prove to be an excellent imaging modality to study the distribution of BAT. We report a neonate with sepsis whose MRI study of the neck and upper chest done to look for infective focus revealed classical distribution and signal intensity of BAT.