Developments of new probability models for data analysis are keen interest of importance for all fields. The log-Dagum distribution has a prominent role in the theory and practice of statistics. In this article, a new family of continuous distributions generated from a log Dagum random variable called the log-Dagum Weibull distribution is proposed. The key properties of the proposed distribution are derived. Its density function can be symmetrical, left-skewed, right-skewed and reversed-J shaped and can have increasing, decreasing, bathtub hazard rates shaped. The model parameters are estimated by the method of maximum likelihood and illustrate its importance by means of applications to real data sets.

Widespread poverty is the most serious threat and social problem that Bangladesh faces. Regional vulnerability to climate change threatens to escalate the magnitude of this poverty. It is essential that projections of poverty be made while bearing in mind the effects of climate change. The main purpose of this paper is to investigate the agrarian sub-national regional analysis of climate change vulnerability in Bangladesh under various climate change scenarios and its potential impact on poverty. This study is relevant to socio-economic research on climate change vulnerability and agriculture risk management and has the potential to contribute new insights to the complex interactions in household income and climate change risks to agricultural communities in Bangladesh and South Asia. The current study uses analysis of variance, cluster analysis, decomposition of variance and log-normal distribution to estimate the parameters of income variability that ascertain vulnerability levels and help us to understand the poverty levels that climate change could potentially incur. It is found that the income share in income sources revealed that income category shares across the various regions of Bangladesh are far from uniform. The variance decomposition of income showed that agricultural income in Mymensingh and Rangpur is the main cause of income difference. Moreover, large variance of agricultural income in the regions is induced by gross income from rice production. Additionally, constant reduction of rice yield due to climate change in Bangladesh is not such a severe problem for farmers, however, the extreme events like flood, flash flood, drought, sea level rise, and greenhouse gas emission based on RCPs could increase the poverty rates in Mymensingh, Rajshahi, Barisal, and Khulna regions that would be highly affected by unexpected yield loss due to extreme climatic events. Therefore, research and development of adaptation measures to climate change for regions where farmers are largely dependent on agricultural income is important.

It is quite easy to stochastically distort an original count variable to obtain a new count variable with relatively more variability than in the original variable. Many popular overdispersion models (variance greater than mean) can indeed be obtained by mixtures, compounding or randomlystopped sums. There is no analogous stochastic mechanism for the construction of underdispersed count variables (variance less than mean), starting from an original count distribution of interest. This work proposes a generic method to stochastically distort an original count variable to obtain a new count variable with relatively less variability than in the original variable. The proposed mechanism, termed condensation, attracts probability masses from the quantiles in the tails of the original distribution and redirect them toward quantiles around the expected value. If the original distribution can be simulated, then the simulation of variates from a condensed distribution is straightforward. Moreover, condensed distributions have a simple mean-parametrization, a characteristic useful in a count regression context. An application to the negative binomial distribution resulted in a distribution allowing under, equi and overdispersion. In addition to graphical insights, fields of applications of special cases of condensed Poisson and condensed negative binomial distributions were pointed out as an indication of the potential of condensation for a flexible analysis of count data

The planned closure of potash mines, achieved through the injection of highly mineralized brines into the worked-out area, is a complex and not fully studied process. A critical concern arises when brines obstruct the aerodynamic connections between the flooded mine's airspace and the atmosphere, potentially leading to the formation of closed cavities where explosive gases can accumulate. To address this hazard, it is imperative to develop systems capable of extracting the gas-air mixture from the unflooded domed portions of the worked-out area. This is the focus of this study, in which we analyze gas-dynamic processes within the potassium mine worked-out area during planned flooding. Two distinct scenarios are examined: the first involves controlled flooding with saturated brines, while the second contemplates flooding resulting from a hypothetical breakthrough of supra-salt strata, leading to the ingress of groundwater into the worked-out area. A novel mathematical model is introduced to predict the evolution of gas-air mixture parameters in the unflooded dome segment of the worked-out area. Utilizing this model, we assess the effectiveness of proposed measures designed to eliminate explosive gases from the worked-out area. Specifically, a pipeline system is proposed for the removal of gases, followed by their dilution below the maximum permissible concentrations in the effluent jet. The findings from this study contribute valuable insights into ensuring the safe and efficient closure of potash mines, shedding light on potential risks and effective mitigation strategies for gas-related hazards during planned flooding.

Safe water is a global public health concern amid increasing scarcity and pollution. Bottled water production and consumption contribute to these problems. This study examines tap water consumption in Italy, assessing associated sociodemographic factors and related health outcomes such as obesity and self-perceived health status. Data from the Italian National Statistics Institute's "Aspects of daily life" survey (N=45,597) were analyzed. Covariates included education, age, gender, economic status, region, concerns about waste and climate change, consumption of carbonated drinks excluding water, alcohol consumption, consumption of vegetables, consumption of snacks, body mass index, and self-perceived health status. Bivariate analyses and mixed-effect logistic regression models explored the associations. People who drink tap water were 19,674 with a higher prevalence in people aged 45 to 59 old, people with a graduate/post-graduate degree diploma, with optimal economic resources, and concerned about waste production and climate change, coming from the North-East regions of Italy. Underweight people showed a higher prevalence of TW assumption as well as those who drink less than occasionally carbonated drinks, drink alcohol, consume vegetables more than once a day, and snacks less than once a week with a satisfying level perceived health status. Regressions showed that all age classes are less likely to drink tap water than people younger than 20 years old. The category with “inadequate” economic resources is more likely to consume tap water. Low educational classes show a low likelihood of consuming tap water as well as Islands. A concern about waste production and climate change is associated with an increased likelihood of assuming tap water. Tap water consumption was negatively associate with obesity but not with a satisfactory Self-perceived health status. Insights from this study can inform public health strategies.

The sustainable development of mines has been the focus of attention in recent years, in China, there are a large number of untreated mined-out areas, and a series of disasters caused by instability of the goaf will bring heavy blows to people’s safety and financial resources. Mined-out areas management is an important part that cannot be ignored in mine sustainable development, and filling management is one of the most effective ways to solve the hidden danger of mined-out areas. Among them, cemented filling with tailings and the ultra-high-water backfilling are commonly used in mining enterprises. However, filling treatment will lead to increasing cost and the decreasing profits, which seriously depresses the motivation of mining enterprises and even leads to mor-al hazard. Therefore, the analysis of the economic benefits of goaf control plays a vital role in the sustainable construction and long-term development of mines. This paper proposed the mine-out area treatment economic model, the proposed method employs the guiding philosophy of news-boy model to create a mathematical economy model that provides the basis of goaf management mode for mine. The following research results are achieved: (1) The economic model of mined-out area backfilling treatment is constructed, and which is classified three different modes. (2) Com-bined with mathematical derivation and simulation, the influence of relevant variable parameters on each type of filling mode is discussed. (3) Various types of goaf filling treatment mode are com-pared with non-filling scheme (benchmark mode), so as to provide theoretical support for mining enterprises to choose the appropriate filling scheme. The results shows that the economic model of mined-out area management provides the optimal mode for mined-out area filling, the balance of tailings and ultra-high water filling materials procurement is realized, to making maximum profits. In this paper, the use of economic thinking has an important impact on the sustainable development of safety goaf management. To evaluate the sustainable development of goaf management by building economic models. It has important theoretical basis and practical guiding significance for the development and exploration of mined-out area management by combining economy with sustainable development.

Ciliopathies are genetic syndromes that link skeletal dysplasias to dysfunction of primary cilia. Primary cilia are sensory organelles synthesized by intraflagellar transport (IFT) - A and B complexes, which traffic protein cargo along a microtubular core. We have reported that deletion of IFT-A gene, Thm2, together with a null allele of its paralog, Thm1, causes a small skeleton with small mandible or micrognathia in juvenile mice. Using micro-computed tomography, here we quantify the craniofacial defects of Thm2^-/-;Thm1^aln/- triple allele mutant mice. At postnatal day 14, triple allele mutant mice exhibit micrognathia, maxillary hypoplasia, and a decreased facial angle due to shortened maxilla, premaxilla, and nasal bones, reflecting altered development of facial anterior-posterior elements. In contrast, other ciliopathy-related craniofacial defects, such as cleft lip and/or palate, hypo-/hypertelorism, broad nasal bridge, craniosynostosis, and facial asymmetry, were not observed, suggesting development of the facial transverse dimension is intact. Calvarial-derived osteoblasts of triple allele mutant mice showed reduced bone formation in vitro that was ameliorated by Hedgehog agonist, SAG. Together, these data indicate that Thm2 and Thm1 genetically interact to regulate bone formation and sculpting of the postnatal face. The triple allele mutant mice present as a novel model to study craniofacial bone development.

This article focuses on the issue of motor oils used in the engines of off-road mobile machinery (NRMM), more specifically tractors. The primary goal of the paper is to determine the appropriate replacement interval for these oils. The physical properties of the examined samples were first determined by conventional instruments. Furthermore, the concentration of abrasive metals, contaminants, and additive elements were measured using an optical emission spectrometer. Lastly, the content of water, fuel, glycol, and the products of oxidation, nitration, and sulphation were determined by using infrared spectrometry. The measured values were compared to the limit values. Based on the processing and evaluation of these analyses, the overall condition of the oils was assessed and subsequently the optimal exchange interval of the examined oils was determined. In addition, a risk analysis of the outage was performed. Due to the high yields of crops, farmers can lose a significant amount of product when a tractor is not functioning during the harvest period. This loss for calculated in the paper.

Biomarkers have the potential to aid in the study of Alzheimer’s disease (AD); unfortunately, AD biomarker values often have a high degree of overlap between healthy and AD individuals. This study investigates the potential utility of a series of novel AD biomarkers, the sixty second ¹²⁹Xe retention time, and the xenon washout parameter, based on the washout of hyperpolarized ¹²⁹Xe from the brain of AD participants following inhalation. The xenon washout parameter is influenced by cerebral perfusion, T1 relaxation of xenon, and the xenon partition coefficient, all factors influenced by AD. Participants with Alzheimer’s disease (n=4) and healthy volunteers (n=4) were imaged using hyperpolarized ¹²⁹Xe magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to determine the amount of retain xenon in the brain. At 60 sec post breath hold, AD patients retained significantly higher amounts of ¹²⁹Xe compared to healthy controls. Data was fit to a pharmacokinetic model and the xenon washout parameter was extracted. Xenon washout in white and grey matter occurs at a slower rate in Alzheimer’s participants (¹²⁹Xe half-life time of 42s and 43s, respectively) relative to controls (20s and 16s, respectively). Following larger scale clinical trials for validation, the xenon washout parameter has the potential to become a useful biomarker for the support of an AD diagnosis.

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.

Based on the engineering background of Daliuta mining area, the fracture distribution and water movement within the weakly cemented overlay strata are studied through liquid-solid coupling physical simulation and COMSOL numerical simulation test. 3D fracture network of overburden strata in mining is plotted based on the result of the physical simulation test. The results showed that the ‘fractured zone’ of the weakly cemented overburden strata in the western area develops more evidently than that in the eastern area ---- wide-opened fractures form at both ends of the working area and this leads to a wide distribution of fractures in the overlying strata.After the initial caving of the roof, height of the penetrating fractures increases rapidly and the separated strata space becomes the main channel for water flow. Under the action of water flow and rock strata movement, mining-induced fractures in overlying rock display cyclic change of expansion, penetration and closure. When the working face is fully mined, the penetrating fractures in the overlying strata and mining-induced fractures up in the working face become the main passages for water flow. The experimental result provides a reference for underground reservoirs layout and maintenance and water-conserved mining in western China.

Abstract: A new method for constructing exact solutions of the General Relativity equations for a dusty matter with fractal property is proposed. This method allows to find the solution of the GR-equations in terms of matter velocities : the connection coefficients and the Ricci tensor of space-time are expressed in terms of matter velocities; the metric tensor and the matter density are found as functions of velocity from the GR-equations. The connection coefficients and the Ricci tensor are invariant with respect to the discrete scaling transformation of velocity , where is constant. Therefore, the found solution can be used to simulate the fractal properties of the cosmic web in terms of matter velocities. This solution includes isotropic and anisotropic distributions of matter density. In an isotropic case, there is a class of exact solutions including both the well-known Friedmann’s solution and a solution with a periodic distribution of the matter density in space. This last solution may be used to simulate the quasi-periodic distribution of matter in the cosmic web. It is possible that, the cosmic web and its fractal properties are the space-time primary properties. These properties are described with a deformation tensor of the space-time.

There are rich proper noun derivative semantic relationships in geographic entity vector data. The identification of traditional proper noun derivative semantic relationships usually requires toponym researchers to examine the source of derived toponyms by consulting a large number of toponym documents. This method cannot adapt to the mining of proper noun derivative semantic relationships for large-scale geographical entity. In this regard, this paper proposes a method of identifying the proper noun derivative semantic relationships for geographical entity by combining prompt learning and XGBoost model. This method transforms the extraction problem of proper noun derivative semantic relationships into a binary classification problem by analyzing the characteristics of the derivation relationship of toponyms in the form of toponyms and the spatial and temporal distribution of geography. Firstly, prompt learning and gaussian mixture model are used to extract and cluster the derivation words of toponyms, so as to realize the recognition of derived toponyms collections. Then, enumerate the possible proper noun derivations in the toponym set, and then the XGBoost model is used to identify the semantic relations derived from the proper noun of geographical entities. In the experiment, the recognition method of proper noun derivative semantic relationships based on prompt learning and XGBoost proposed in this paper has achieved good relationship recognition effect in the experiment. This method has certain practical value in the fields of toponym management and toponym translation.

The study delves into the critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of Loss data, insurers and regulators gain essential insights into the probabilities and magnitudes of insurance claims, informing the determination of precise insurance premiums and the management of case reserving. This approach aids in fostering fair competition, ensuring equitable premium rates, and preventing discriminatory pricing practices, thereby promoting a balanced insurance landscape. The research further investigates the transformative impact of the COVID-19 pandemic on these Size of Loss patterns, given the substantial shifts in driving behaviors and risk landscapes. Also, the research contributes to the literature by addressing the need for more studies focusing on the implications of the COVID-19 pandemic on pre- and post-pandemic auto insurance loss patterns, thus offering a holistic perspective encompassing both insurance pricing and regulatory dimensions.

The influence of the Fe2O3 addition amount on the dephosphorization of hot metal at 1623 K with the slag of the low basicity (CaO/SiO2) of about 1.5 was investigated by using high-temperature laboratorial experiments. With increasing the Fe2O3 addition amount, the contents of [C], [Si], [Mn] and [P] in hot metal at the end of dephosphorization decrease, and the corresponding removal ratios increase. The P2O5 content in slag increases, and the CaO and SiO2 contents in slag decrease. The phosphorus mainly exists in the form of the nCa2SiO4-Ca3(PO4)2 solid solution in the phosphorus-rich phase and the value of coefficient n decreases from 20 to 1 with increasing the Fe2O3 addition amount from 5 g to 30 g. With increasing the Fe2O3 addition amount, the oxygen potential and activity at the interface between the slag and hot metal increase. When the oxygen potential and the oxygen activity at the interface are greater than 0.72×10-12 and 7.1×10-3, respectively, the dephosphorization ratio begins to increase rapidly. With increasing the Fe2O3 addition amount to 30 g, the ratio of the Fe2O3 addition amount to theoretical calculation consumption is around 175%, and the dephosphorization ratio reaches the highest value of 83.3%.

Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

With the rapidly increasing of people’s purchasing power, the fast moving consumer goods (FMCG) industry is supposed to grow dramatically. In order to gain more market access and profile, it is important for the FMCG manufacturers and retailers to find the preferences and provincial characteristics of consumers, to develop more suitable goods distribution strategy. Based on retails marketing data with geographic characteristics, this paper proposes a new combination of geography methods to solve the problems in distribution of FMCG. Via multiple K-means clustering and cross validation of KNN half off, the mesoscopic sales features are extracted through the classification of retails, which can indirectly grasp the consumer behavior characteristics. Based on space division and Moran’ I spatial autocorrelation arithmetic, two strategies are developed to satisfy consumer’s needs and promote sales, including conservative and positive strategies. According to our analysis, the total sales volume of the regions will increase by 5.1% and 10.3%. This study can be applied to the provide purchase strategies for FMCG retails according to their locations. The research can explore the consumption potential of different areas, thus improving the profile of retails and the development of economy in more mesoscopic scale.

The availability rating of any system is the probability that it will be able to operate for a given time in other words, to restore the system in the case of a system failure, or during the failure it is a measure of the availability index of resource system. We aimed to complete the study for the reasons as below. The rating and upgrading of underground mine radio communication system availability is to ensure operation reliability of the underground mine and to establish reliable radio communication system for miner’s safety during failure. Therefore, our study is contributed to reveal system availability rating of single resource (with two parallel connections) system and two resources (with three parallel connections) system. The study is related to not only practical contribution but also reliability engineering theory. To achieve this result, we have used Exponential, Weibull, and Poisson distributions. The readiness rating of single resource (with two parallel connections) and two resources (with three parallel connections) systems were calculated using Matlab software and the simulation results were introduced. This result confirms that any system has a resource system, which increases its readiness rating. The study was in examples of single resource radio communication system on the two shafts of the underground mine and two resource radio communication system for three shafts. During the initial system reliability enhancement study, the readiness of the dual resource system was assessed. The rating shows a 99 percent result, which is very meaningless for systems with more than two n-resources and we have revealed that it can show more than 100 percent result. In the process of the study on system reliability improvement the rating availability of system which has two resources was 99 % result. It is very meaningless for systems with more than two n-resources or more than 100% result.

The present paper investigates flaw strength distributions established using various flexural tests on batches of SiC bar test specimens: 4-point bending as well as 3-point bending with different span lengths. Flaw strength is given by the elemental stress operating on the critical flaw at fracture of a test specimen. Fracture inducing flaws and their locations are identified by fractography. A single population of pores was found to dominate fracture. The construction of diagrams of p-quantile vs elemental strengths was aimed at assessing the Gaussian nature of flaw strengths. Then, empirical cumulative distributions of strengths were constructed using the normal distribution function. Weibull cumulative probability distributions were derived from the mean and the standard deviation using the first moment equation. Agreement was obtained between both Weibull and normal flaw strengths distributions. The cumulative distributions for the different bending tests were predicted satisfactorily from the flaw strength density function using the elemental strength model. Flaw strength distributions that include potential weaker flaws encountered in larger test pieces are extrapolated using the p-quantile diagrams. Implications are discussed about the pertinence of an intrinsically representative flaw strength distribution, about failure predictions, about size effects, and about the significance of flaw spatial distributions.

Two extensions of the generalized double Lomax distribution are introduced - the spliced-scale generalized double Lomax distribution and the exponentiated generalized double Lomax distribution. Their properties are studied. Usefulness of the new distributions is shown by fitting them to stock returns datasets.

The decapod fauna in intertidal rocky shore in continental Chile has high species diversity mainly in northern and central Chile due high productivity of these coast due influence of cold Humboldt stream. One of the abundant species in these ecosystems is decapod Cyclograpsus cinereus Dana, 1851. The aim of the present study was determine the spatial distribution pattern of C. cinereus along rocky shore in Antofagasta bay, north of Chile between spring and summer 2018-2020. Data was obtained counting individuals from random quadrants in intertidal zones, to the obtained data was applied the variance mean ratio for determine if the specimens have random, aggregate or uniform distribution, that are associated to Poisson, negative binomial or positive binomial distributions respectively. Data obtained revealed the existence of associated distribution with respective negative binomial distribution pattern in 16 observations, and uniform distribution for 3 observations. The sites corresponds to rocky shores in urban zones, and in a protected zone, and the density does not have significant differences for both kind of sites. The observed data about aggregated pattern agree with observations for decapods for rocky shore in central and southern Chile, specifically in interpretative probabilistic models.

In this research first, a sequence of properties called delta is assigned to each prime number and then examined. Deltas are only dependent on the distribution of prime numbers, so the results obtained for the delta distribution can be considered as a proxy for the distribution of prime numbers. The first observation was that these properties are not unique and different prime numbers may have the same value of delta of a given order. It was found that a small number of deltas cover a large portion of prime numbers, so by recognizing repetitive deltas, the next prime numbers can be predicted with a certain probability, but the most important observation of this study is the normal distribution of deltas. This research has not tried to justify the obtained observations and instead of answering the questions, it seeks to ask the right question.

The asymmetric bimodal exponential power (ABEP) distribution is an extension of the generalized gamma distribution to the real line via adding two parameters which fit the shape of peakedness in bimodality on real line. The special values of peakedness parameters of the distribution are combination of half Laplace and half normal distributions on real line. The distribution has two parameters fitting the height of bimodality, so capacity of bimodality is enhanced by using these parameters. Adding a skewness parameter is considered to model asymmetry in data. The location-scale form of this distribution is proposed. The Fisher information matrix of these parameters in ABEP is obtained explicitly. Properties of ABEP are examined. Real data examples are given to illustrate the modelling capacity of ABEP. The replicated artificial data from maximum likelihood estimates of parameters of ABEP and distributions having an algorithm for artificial data generation procedure are provided to test the similarity with real data.

In this paper we consider type II bivariate generalized power series Poisson distribution as a compound Poisson distribution with bivariate generalized power series compounding distribution. We obtain some properties, p.m.f. and conditional distributions. In addition we also give a brief discussion about the multivariate extension of this case. Then we introduce type II bivariate generalized power series Poisson process and consider a bivariate risk model with type II bivariate generalized power series Poisson model as the counting process. For this model we derive distribution of the time to ruin and bounds for the probability of ruin. We obtain partial integro-differential equation for the ruin probabilities and express its bivariate transform through two univariate boundary transforms,where one of the initial capitals is fi xed at zero.

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

Based on the 2013–2017 Chinese Family Database and China Household Finance Survey, the study examines the impact of farmland transfer on the income structure of agricultural households. We observe a significant rise in the income of transferred-out households, while that of transferred-in households is unchanged. A further empirical decomposition of income shows a significant increase in both the wage and asset generated incomes of transferred-out households. Although the income generated by transferred-in households through agricultural production and management increases significantly, the decrease in wage income is larger. The study’s empirical designs are robustly tested with propensity score matching and instrumental variables. Moreover, we conduct a comparative analysis of the external constraints faced by the two groups to explore the reasons for the divergence of the income effect. The results show that transferred-in households face highly pronounced external constraints in terms of capital, technology, and farmland size, while transferred-out households face relatively fewer impediments to non-agricultural employment. Our empirical results imply that external constraints can limit the social welfare improvements of agricultural land reform, suggesting that other complementary measures would be required for future policy improvements to work better.

This study assesses the pursued impacts of Tulsi value chain development intervention on the livelihoods of rural poor in Uttarakhand state of India. Tulsi as an alternative livelihood, particularly for the rural poor, is less explored. With increased crop depredation of major cereal crops grown in the district by wild animals and pests, and decreasing availability of water agriculture, attempts were made to improve earnings from Tulsi as an alternative livelihood. Findings suggest that the average households’ gross profit from Tulsi farming increases by more than double within a span of two years. Total crop income of beneficiary farmers’ increases by 0.8 percent for every 1 percent increase in Tulsi income. Intervention helped enhance productivity of Tulsi, thereby enhancing earnings from Tulsi farming. Most importantly, intervention has shown a tremendous adoption rate. Towards the end of the intervention, the value chain work was out-scaled to another 19 villages in Chamoli district, thereby reaching out to more than 400 households.

Cotton cultivation and sustaining its productivity is challenging in temperate arid regions around the globe. Exploring suitable cotton cultivation areas to improve productivity in such climatic regions is essential. Thus, this study explores the ecologically suitable areas of cotton cultivation using the Maxent model, having 375 distribution points of long-staple cotton and various factors, including 19 climatic factors, 2 terrain factors, and 6 soil factors in Xinjiang. The area under the curve (AUC) of the predicted results was greater than 0.9, indicating that the model's predictions had fairly high accuracy. However, the main environmental factors that affect cotton's growth are the lowest temperature in the coldest month, the hottest month, the precipitation in the driest season, and the monthly average temperature difference. Further, the temperature factors contribute 71%, while the contribution ratio of terrain and soil factors is only 22%. The research shows that the current planting area is consistent with the predicted area in many areas of the study. Still, some areas, such as the Turpan region, northwest of Bayingolin Mongol Autonomous Prefecture, are supposed to be suitable for planting cotton, but it is not planted. The current potential distribution area of long-staple cotton is mainly located in Aksu Prefecture and the northern part of the Kashgar Prefecture region. The climatic prediction shows that the growing area of long-staple cotton may expand to southern Altay, central Aksu, and Bortala Mongol Autonomous Prefecture. This study will be helpful for cotton cultivation suitability areas in Xinjiang and other regions with similar environments.

In this paper a more flexible extension of the Fréchet distribution is introduced. The new distribution is defined by means of the stochastic representation as the quotient of two independent random variables, a Fréchet distribution and the power of a random variable with uniform distribution in the interval (0,1). We will call this new extension the Slash Fréchet distribution and one of its main characteristics is that its tails are heavier than the Fréchet distribution. The general density of this distribution and some basic properties are determined. Its moments, skewness coefficients and kurtosis are calculated. In addition, the estimation of the model parameters is obtained by the method of moments and maximum likelihood. Finally, two applications with real data are performed by fitting the new model and comparing it with the Fréchet distribution.

The goal of clustering is to identify common structures in a data set by forming groups of homogeneous objects. The observed characteristics of many economic time series motivated the development of classes of distributions that can accommodate properties such as heavy tails and skewness. Thanks to its flexibility, the Skewed Exponential Power Distribution (also called Skewed Generalized Error Distribution) ensures a unified and general framework for clustering possibly skewed and heavy tailed time series. This paper develops a clustering procedure of model-based type, assuming that the time series are generated by the same underlying probability distribution but with different parameters. Moreover, we propose to optimally combine the estimated parameters to form the clusters with an entropy weighing $k$-means approach. The usefulness of the proposal is showed by means of application to financial time series, demonstrating also how the obtained clusters can be used to form portfolio of stocks.

Pelagic stingray (Pteroplatytrygon violacea) is the only species of stingray (Dasyatidae) that utilizes both pelagic and demersal habitats. It is the main bycatch species in pelagic longline fisheries targeting bluefin tuna in the Gulf of Lions. In the Mediterranean Sea, their stock structure, behavioural ecology and movements are unknown. For the first time in the Mediterranean, 17 individuals (39 to 60 cm disc width) were tagged with pop-up satellite archival transmitting tags using a novel method of tag attachment, to investigate horizontal and vertical movements. The tags were attached for between two and 60 days. Between the months of July and October, pelagic stingray occupied a temperature range of 12.5 to 26.6°C, and a depth range extending from the surface to 480 m. Monthly trends in catch-per-unit-effort (CPUE) of pelagic stingray peaked in August and decreased by late autumn. Pelagic stingray may aggregate on the continental shelf during summer, and move southwards in early autumn, and this movement pattern is considered in relation to the reproductive cycle and overwintering. Future work and options for bycatch mitigation are discussed.

The age of information (AoI) metric was proposed to measure the freshness of messages obtained at the terminal node of a status updating system. In this paper, the AoI of discrete time status updating system with probabilistic packet preemption is investigated by analyzing the steady state of a three-dimensional discrete stochastic process. Assuming the queue used in system is Ber/Geo/1/2*/η, which represents that the system size is 2 and the packet in buffer can be preempted by fresher packet with probability η. Instead of considering system’s AoI separately, we use a three-dimensional state vector (n,m,l) to simultaneously track the real time changes of the AoI, the age of packet in server, and the age of packet waiting in buffer. We give the explicit expression of system’s average AoI, and show that the average AoI of system without packet preemption is obtained by letting η=0. When η is set to 1, the mean of AoI of system having Ber/Geo/1/2* queue is obtained as well. Combining the results we have obtained and comparing them with corresponding average continuous AoIs, we propose a possible relationship between average discrete AoI with Ber/Geo/1/c queue and the average continuous AoI with M/M/1/c queue. For each of two extreme cases where η=0 and η=1, we also determine the stationary distribution of AoI using the probability generation function (PGF) method. The relations between average AoI and the packet preemption probability η, as well as AoI’s distribution curves in two extreme cases are illustrated by numerical simulations. Notice that the probabilistic packet preemption may occur, for example, in an energy harvest (EH) node of wireless sensor network, where the packet in buffer can be replaced only when the node collects enough energy. In particular, to exhibit the usefulness of our idea and methods and highlight the merits of considering discrete time systems, in this paper we give much more explanations showing that how the results about continuous AoI is derived by analyzing the corresponding discrete time system, and how the discrete age analysis is generalized to the system with multiple sources. In terms of packet service process, we also propose our idea to analyze system’s AoI when the service time distribution is relaxed to be arbitrary.

This paper discusses a possible approach to validate the Goldbach conjucture which states that all even numbers can be expressed as a summation of two prime numbers. For this purpose the paper begins with the concept of successive-addition-of-digits-of-an-integer-number (SADN) and its properties in terms of basic algebraic functions like addition, multiplication and subtraction. This concept of SADN forms the basis for classifying all odd numbers into 3 series- the S1, S3 and S5 series- which comprise of odd numbers of SADN(7,4,1), SADN(3,9,6) and SADN(5,2,8) respectively and follow a cyclical order. The S1 and S5 series are of interest in the analysis since they include both prime and composite numbers while the S3 series exclusively consists of composite numbers. Furthermore, the multiplicative property of SADN shows why composites on the S1 series are derived as products of intra-series elements of the S1 and S5 series while composites on the S5 series are derived as products of inter-series elements of the S1 and S5 series. The role of SADN is also important in determining the relevant series for identifying the combination of primes for a given even number since it shows why such combinations for even numbers of SADN(1,4,7) will be found on the S5 series while those for even numbers of SADN(2,5,8) will lie on the S1 series and both the series have a role to play in identifying the prime number combinations for even numbers with SADN(3,6,9). Thereafter, the analysis moves to calculating the total number of acceptable combinations for a given even number that would include combinations in the nature of two composites (c1+c2), one prime and one composite (p+c) and two primes (p1+p2). A cyclical pattern followed by even numbers is also discussed in this context. Identifying the c1+c2 and p+c combinations and thereafter subtracting them from the total number of combinations will yield the number of p1+p2 combinations. For this purpose the paper discusses a general method to calculate the number of composites on the S1 and S5 series for a given number and provides a detailed method for deriving the number of c1+c2 combinations. The paper presents this analysis as a proof to validate the Goldbach conjecture. Since even numbers can be of SADN 1 to 9 and the relation between nTc (i.e. total number of acceptable combinations) and nc(i.e. number of composites) for all even numbers can either be of nTc > nc or nTc ≤ nc, the paper shows that the Goldbach conjecture is true for both these categories of even numbers. In this manner this analysis is totally inclusive of all even numbers in general terms and since the analysis of every even number is common in methodology but unique in compilation, apart from being totally inclusive, it is also mutually exclusive in nature. This proves that the Goldbach conjecture which states that all even numbers can be expressed as atleast one combination of two prime numbers holds true for all even numbers, across all categories possible. Additionally this approach proves that the identification of p1+p2 combinations which would validate the Goldbach conjecture lies in the identification of c1+c2 combinations.

In this paper we define a continuous wavelet transform of a Schwartz tempered distribution $f \in S^{'}(\mathbb R^n)$ with wavelet kernel $\psi \in S(\mathbb R^n)$ and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of $S^{'}(\mathbb R^n)$. It turns out that the wavelet transform of a constant distribution is zero and our wavelet inversion formula is not true for constant distribution, but it is true for a non-constant distribution which is not equal to the sum of a non-constant distribution with a non-zero constant distribution.

The Amazon region has the most incredible diversity of freshwater stingrays; however, there are still places where information about this group is scarce. The present work aims to record the occurrence of freshwater stingrays in the Uatumã river basin, Amazonas, Brazil. For this, collections were carried out in three municipalities bathed by the Uatumã River, Presidente Figueiredo, Itapiranga and São Sebastião do Uatumã. The rays were collected through fishing using a hand net and, after capture, were identified through the pattern of the dorsal and ventral color of the disc, the absence or presence of the labial groove and the organization of the row of spines on the tail, too were also measured, weighed and sexed. In total, 69 specimens of Potamotrygonines were captured, 59 of which were from the genus Potamotrygon and ten individuals from the genus Paratrygon. The present study provides preliminary information on the characteristics of freshwater stingray species that may occur in the Uatumã River. Furthermore, new research is necessary to improve the identification of specimens to determine the diversity and elucidate aspects related to the biology of elasmobranchs in the Uatumã River Basin, Brazil.

Este estudio empleó el algoritmo MaxEnt para evaluar la distribución potencial de la serpiente de cascabel de cola larga, Crotalus stejnegeri , una especie amenazada endémica de México. Los resultados demuestran una buena fiabilidad del modelo, alcanzando un AUC de 0,879. Destacan una distribución potencial concentrada en las estribaciones de la Sierra Madre Occidental, principalmente en el centro-sur de Sinaloa, suroeste de Durango y norte de Nayarit, caracterizada por bosque seco tropical. La temperatura durante el trimestre más seco y la estacionalidad de la precipitación se identifican como factores determinantes, mientras que la baja idoneidad en Chihuahua sugiere una afinidad tropical de la especie. La variabilidad en las precipitaciones durante el trimestre más frío enfatiza la importancia de ampliar el número de registros de ocurrencia de la especie mediante una mayor exploración de campo dentro de su área de distribución. Estos hallazgos proporcionan información valiosa para los esfuerzos de conservación y subrayan áreas clave para futuras investigaciones.

This paper examines the regional changes of corn production and the relationship between ethanol production and corn production. The underlying hypothesis is that the rapid growth in ethanol production causes regional expansion of corn production outside the traditional regions. This paper introduces the information approach developed by entropy theory to describe these regional changes. The results support the hypothesis that ethanol production leads to expansion of corn production outside traditional corn producing regions.

Currently, there is no widely accepted consensus regarding a consistent thermodynamic framework within the special relativity paradigm. However, by postulating that the inverse temperature 4-vector, denoted as β, is future-directed and timelike, intriguing insights emerge. Specifically, it is demonstrated that the q-dependent Tsallis distribution can be conceptualized as a de-Sitterian deformation of the relativistic Maxwell-Jüttner distribution. In this context, the curvature of the de Sitter space-time is characterized by Λ/3, where Λ represents the cosmological constant within the ΛCDM standard model for Cosmology. For a simple gas composed of particles with proper mass m, and within the framework of quantum statistical de Sitterian considerations, the Tsallis parameter q exhibits a dependence on the cosmological constant given by q=1+ℓcΛ/n where ℓc=ℏ/mc is the Compton length of the particle and n is a positive numerical factor. This formulation establishes a novel connection between the Tsallis distribution, quantum statistics, and the cosmological constant, shedding light on the intricate interplay between relativistic thermodynamics and fundamental cosmological parameters.

In studies of dynamic stability and power quality, it is necessary to know the mechanical parameters that determine the transient response of a wind turbine. The exact value of these parameters is not as decisive as the power curve can be, but an estimate that is far from reality can distort or even invalidate the simulation results. Despite its importance, this information, especially the inertia, but also the stiffness and damping constant of the drive-train, is hardly available for the turbine model under investigation. In this work, the different bibliographical sources that provide values of blade inertia in kg·m2 will be reviewed, and above all, those that provide a distribution of masses along the span of the blade. With this, different reliable relations will be obtained that allow calculating the inertia of the turbine rotor, based on the mass and length of the blade. When the center of gravity is also available, a very correlated expression is provided to obtain the inertia. The even rarer references to the stiffness and damping constant of the drive-train will also be reviewed.

In this work, we explore the extreme searching of multidimensional functions by natural gradient descent based on Dirichlet and generalized Dirichlet distributions. The natural gradient is based on describing multidimensional surface with probability distributions, which allows us to reduce changing the accuracy of gradient and step-size. In this article, we propose an algorithm of natural gradient descent based on Dirichlet and generalized Dirichlet distributions. We demonstrate that the natural gradient descent with step-size adaptation with Dirichlet and generalized Dirichlet distributions has higher accuracy and does not take a large number of iterations for minimizing test functions than gradient descent and Adam.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

Background: Obesity and its attendant conditions have become major health problems worldwide and is currently ranked as the fifth most common leading cause of death globally. Complex environmental and genetic factors are the cause of the current obesity epidemic. Diet, lifestyle, chemical exposures, and other confounding factors are difficult to manage in humans. The mice model is helpful in researching genetics BW gain because genetic and environmental risk factors can be controlled in mice. Studies in mouse strains with various genetic backgrounds and established genetic structures provide unparalleled opportunities to find and analyze trait-related genomic loci. In this study, we used the Collaborative Cross (CC), a large panel of recombinant inbred mouse strains, to present a predictive study using CC mice SMAD4 knockout profiles to understand and effectively identify predisposition to body weight gain. Materials and Methods: Male C57Bl / 6J Smad4+/- mice were mated with female mice from 10 different CC lines to create F1 mice (Smad4+/- x CC). Body weight (BW) was measured weekly until week 16, then monthly until the end (week 48). The heritability H2 of the assessed traits was estimated and presented. Comparative analysis of various machine learning algorithms for predicting the BW changes and genotype of mice was conducted. Results and conclusions: Our data showed that the body weight records of F1 mice with different CC lines differed between wildtype and mutant Smad4 mice during the experiment. Genetic background affects weight gain and some lines gained more weight in the presence of Smad4 knockout, while others gained less, but in general, the mutation caused overweight mice, except for a few lines. In both control and mutant groups, female %BW had a higher heritability H2 value than males. Additionally, both sexes with wildtype genotypes showed higher heritability values than the mutant group. Logistic Regression provides the most accurate mouse genotype predictions using machine learning. We plan to validate the proposed method on more CC lines and mice per line to expand machine learning for BW prediction.

According to the structural features, sedimentary evolution, types of sedimentary facies, source rocks features, diagenesis evolution, reservoir features and hydrocarbon formation mechanism, exploration status and hydrocargon resource potential, this article analyzed the major control fac-tors and hydrocarbon distribution rules of the lithologic reservoirs in continental fault basin. The research shows that three major control factors and one coupled factor (fractures act as a tie) in-fluence hydrocarbon formation of lithologic traps in Nantun Formation of Tanan Sag, which in-clude sand body types, effective source rocks and effective reservoirs. With the increase in depth, enough hydrocarbon generate in source rock under thermal evolution. Hydrocarbon generation and expulsion are more intensive when it comes to the depth threshold and critical conditions of hydrocarbon supplying are met. Traps that surrounded or contacted by source rock, or communi-cated by fault are qualified to form reservoirs. As buried depth increases, hydrocarbon genera-tion-expulsion intensity grows and the trap is more petroliferous. Hydrocarbon accumulation and reservoir formation are also controlled by sandbody accumulation conditions. When it meets the critical conditions of hydrocarbon generation and concrete oil and gas are charged in, better phys-ical properties of sandbody always indicate more hydrocarbon accumulation in the trap. Alloca-tion of sand type, effective source rock and effective reservoir is optimized under the effect of fractures, and coupled hydrocarbon reservoir with these three elements.

The main purpose of this paper is to introduce and investigate degenerate Poisson distrib- ution which is a new extension of the Poisson distribution including the degenerate expo- nential function. We then provide several properties of the degenerate Poisson distribution such as the first and the second raw moments and di¤erence operator property. Moreover, we acquired the skewness and the kurtosis for the degenerate Poisson distribution. We also derive its moment generating function by which we define the degenerate Bell polynomials and give a connection for these polynomials related to the unsigned Stirling numbers of the …rst kind.

This work presents a new algorithm to resolve the problem of distribution network reconfiguration using the Tabu Search metaheuristic and voltage drop. The proposed method presents a different way to obtain the initial solution using the voltage drop, as well as a new way to generate a neighborhood of candidate solutions, based on randomness and the voltage drop, to perform a smooth and steady descent execution of the algorithm. The proposed algorithm has the main objective to reduce the active power losses in distribution networks, but it also achieves an refinement in the voltage profile. The proposed method was tested in two distribution systems, the 33-Bus and 94-Bus systems, commonly found and tested in the literature. The results of the tests show that the proposed method presents a low computational cost, achieves good solutions, and is better than the other methods found in the literature.

The purpose of this paper is to summarize and share the field experiment results of KEPCO's project consortium to create a TSO-DSO-DERA interaction scheme. The field experiment was conducted based on the prequalification algorithm proposed in the previous research from the same consortium and was designed to verify the validity of the algorithm under realistic grid conditions. In addition, during the course of the field experiment, it was found that points that were missed or not given much importance in the existing prequalification algorithm could affect the completeness of the overall system, and then practical improvements were made to improve it. The demonstration results confirm that the proposed algorithm is effective in real-world grid environments and can help DSOs ensure the reliability of the distribution system while supporting DERA's participation in the wholesale market using the proposed prequalification scheme.

The power function distribution is a flexible waiting time model that may provide better fit for some failure data. This paper presents the comparison of the maximum likelihood estimates and the Bayes estimates of two-parameter power function distribution. The Bayes estimates are obtained, using conjugate priors, under five loss functions consist of square error, precautionary, weighted, LINEX and DeGroot loss function. The Gibbs sampling algorithm is proposed to generate samples from posterior distributions and in result the Bayes estimates are computed. The comparison of the maximum likelihood estimates and the Bayes estimates are done through the root mean squared errors. One real-life data set is analyzed to illustrate the evaluation of proposed methods of estimation. Finally, results from the simulation are discussed to assess the performance behavior of the maximum likelihood estimates and the Bayes estimates.

While lidar-based forest inventory methods have been widely demonstrated, prediction of tree diameters with lidar is not well understood. The performance metrics typically used in studies for prediction of diameters can be difficult to interpret and may not support comparative inferences between sampling designs or study areas. We evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions using two indices which are easier to interpret and compare. The indices are based on the coefficient of determination (R²), and root mean square deviation (RMSD). These indices facilitate comparisons with alternative (non-lidar) inventory strategies, and with other project areas. We evaluate k nearest neighbors (k-NN) dbh density (relative frequency by dbh class) prediction strategies with lidar for 190 training plots distribute across the 800 km² Savannah River Site in South Carolina, USA. We evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. Amongst the examined strategies we found Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.

We conducted a monocentric observational study aimed at evaluating the pharmaceutical service provided at a Community Pharmacy (C.PH.) during pandemia in our Puglia Region in the period from 29.12.2021 to 12.03.2022 on 550 patients of various ages, sexes, and with concomitant diseases. We collected anamnestic data and any post-vaccination adverse reactions. Interviews with the integrated EQ5 method on evaluating the quality of the service offered and any therapy preference were also performed. As expected, the vaccines were reactogenic after the first dose in the patients with mild-moderate reactions with younger age and female gender as risk factors. Immune-allergic reactions of moderate-severe degree were observed in adult females. In the elderly, the vaccination procedure was well tolerated. Comirnaty showed a favorable O.R.<;1 vs other vaccines. No myocarditis and thromboembolic events in our population were observed. All treatments in May 2023 were correlated with a viremia trend, Paxlovid was prescribed in 3% of the patients in our center and in 1.46% in the Puglia Region with no effects in the hospitalization. It was distributed/dispensed by a novel on behalf of third parties distribution/dispensation (D.P.C.) protocol by the C.PH. The C.PH. resulted in a safe vaccination center providing appropriate patient inclusion during vaccination.

Recent astronomical observations with respect to measurements in distant supernovas, cosmic microwave background and weak gravitational lensing confirm that the Universe is undergoing a phase of accelerated expansion and it has been proposed that this cosmological behavior is caused by a hypothetical dark energy which has a strong negative pressure that allows explain the expanding universe. Several theoretical ideas and models related dark the energy includes the cosmological constant, quintessence, Chaplygin gas, braneworld and tachyonic scalar fields. In this paper, we have obtained new relativistic stellar configurations considering an anisotropic fluid distribution with a charge distribution which could represents a potential model of a dark energy star. In order to investigate the effect of a quadratic equation of state in this anisotropic model we specify particular forms for the gravitational potential that allow solving the Einstein-Maxwell field equations. For these new solutions we checked that the radial pressure, metric coefficients, energy density, anisotropy factor, charge density , mass function are well defined and are regular in the interior of the star. The solutions found can be used in the development of dark energy stars models satisfying all physical acceptability conditions but the causality condition and strong energy condition are violated. We expect that these models have multiple applications in astrophysics and cosmology.

Variable cross-section arch is widely used in practical engineering because of its beautiful arc and excellent mechanical properties. However, there is still no systematic and comprehensive study on the out-plane buckling of variable cross-section arch. In view of this, this paper is concentrated on an elastic analytical research of out-plane buckling of arches with variable cross-section under a uniformly distributed radial local load. The pre-buckling and out-plane buckling behaviour of a variable cross-sectional arch under an external load is quite different from that of an arch with uniform cross-section. The Castigliano's second theorem is used to establish pre-buckling force method equilibrium equations for variable cross-sectional arches under a uniformly distributed radial local load, and corresponding analytical solutions of normal stress, axial compression and the bending moment are obtained. Based on the energy method and the Ritz method, analytical solutions of the critical load for the elastic out-plane buckling of arches with variable cross-section are derived. Comparisons with ANSYS results indicated that the analytical solutions are able to accurately predict the pre-buckling internal forces and critical out-plane buckling load of variable cross-section arches subjected to a uniformly distributed radial local load. It is found that the internal forces and the out-plane buckling load of an arch are significantly affected by the variation of cross-sectional height. With the ratio of cross-sectional height of the top to the end increase, the bending moment decreases and the axial force and critical out-plane buckling load increase. Analytical solutions of pre-buckling internal force and critical out-plane buckling load problems for arches with variable cross-section have a wider significance, since they can provide an effective explicit analytic method for the optimal design of arch structure.

The broad global distribution of freshwater clams belonging to the genus Corbicula is driven by multiple hermaphroditic lineages. These lineages, characterized by shared morphological traits and phenotypic plasticity, pose challenges to morphological identification. Genetic markers, such as the mitochondrial COI gene, play a crucial role in delineating these lineages and their ranges. Morphotypes represent observed phenotypic variations, while lineages are defined based on genetic markers. Here, we comprehensively review Corbicula's distribution in Argentina, dis-criminate extant lineages based on both morphological and genetic (COI) data, and describe variation in internal and external morphology using 15 Argentine populations. Haplotype net-works identified two mitochondrial lineages: A/R morphotype (FW5 haplotype) and C/S mor-photype (FW17 haplotype). Strikingly, despite having similar vectors, origins, and invasive stages, Corbicula lineages exhibit virtually segregated distributions. However, intermediate morphotypes and both mitochondrial haplotypes are found in sympatry in northeastern Argen-tina, suggesting the presence of hybrids due to maternal genome retention. These findings con-tribute to the clarification of the identity and distribution of Corbicula lineages in Argentina, where the genus has been found for over half a century. Similar studies are needed in other areas to better understand the invasion patterns of a successful and plastic group.

Effective management of water distribution systems requires an integrated approach, but none of the available frameworks for one are in broad use in the water supply industry. Frameworks developed include a management standard of the American Water Works Association and Distribution System Optimization, a methodology for physical, hydraulic, and water quality performance assessment. The intelligent systems framework also offers a pathway to integration, but it lacks a definite structure. The voluntary aspect of adopting innovations within the fragmented and unregulated nature of the water utility industry poses a barrier to adoption of such innovations. Another barrier is the uncoordinated arrangements of water research stakeholders with different incentive structures. Intelligent water systems offer a way to incentive utilities to encourage implementation. They can provide a bottom-up approach where utilities see advantages, as opposed to a top-down approach where they are expected to adopt a method without seeing clear benefits. Research to develop new and improved tools is needed, but the research roadmap should prioritize implementation.

Paramacrobiotus species has been described from almost every corner of the world. To date 45 species have been reported from this genus. The species’ presence in different climatic conditions and habitat provides evidence of their adaptation to various harsh environments. In this review, we provide a concise summary of changes observed due to various cryptobiotic conditions in many species of this genus, geographical distribution of all the species, feeding behaviour, life history, microbiome community, Wolbachia endosymbiont identification, reproduction, phylogeny and general taxonomy of the species from genus Paramacrobiotus. Furthermore, we provide a new diagnostic key to the genus Paramacrobiotus based on the morphological and morphometric characters of adults and eggs.

Wireless sensor networks are usually applied in hostile areas where nodes are easy to be moni-tored and captured by adversary. Key distribution is an essential primitive to provide most of security mechanism. However, the characteristic of limited resources of sensors restricts the direct use of conventional key distribution schemes. In this paper, a complete security key distribution scheme based on asymmetric cryptography technology is proposed in both static and mobile scenarios. Mutual authentication is guaranteed using challenge-response mechanism. The per-formance evaluation and security analysis show that the proposed scheme with low complexity not only provides better security for wireless sensor networks, but also reduces storage overhead and key exposure risks.

Four decades of snooker rankings are analyzed in terms of prize money distributions. In particular, it is investigated how much these rankings are dominated by the top players, and also by players from the UK. The main conclusions are that (1) with an increasing total amount of available prize money, the rankings are less dominated by the top players, and (2) players from the UK have historically earned a significantly larger share of the available prize money than could reasonably be expected based on the overall percentage of UK players.

Motivated by empirical observations, we propose a possible extension of Gibrat's law. By applying it into the random growth theory of income distribution (Gabaix, 2009), we find that the income distribution is described by a generalized Pareto-type distribution (GPD) with three parameters. We observe that there is a parameter /elta in the GPD that plays a key role in determining the shape of income distribution. By using the Kolmogorov-Smirnov test, we empirically show that, for typical market-economy countries, /elta is close to 0 significantly, such that the income distribution is characterized by a two-class pattern in which the bottom 90% of the population is approximated by an exponential distribution and the richest 1%~3% is approximated by an asymptotic power law. However, we empirically find that, for China both in planned economy period and in early stages of market reformation (from 1978 to 1990), /elta is significantly deviated from 0, such that the bottom of the population no longer conforms to an exponential distribution.

Original and improved version of the Hardy Cross iterative method with related modifications are today widely used for calculation of fluid flow through conduits in loops-like distribution networks of pipes with known node fluid consumptions. Fluid in these networks is usually natural gas for distribution in the municipalities, water in waterworks or hot water in district heating system, air in the case of ventilation systems in buildings or mines, etc. Since, the resistances in these networks depend of flow, problem is not linear like in electrical circuits, and iterative procedure must be used. In both version of the Hardy Cross method, in original and in the improved one, initial results of calculation in iteration procedure is not flow, but rather the correction of flow. Unfortunately, these corrections should be added to or subtracted from a flow calculated in previous iteration according to complicate algebraic rules. After the here presented node-loop method, final results in each of the iterations is flow directly rather than flow correction. In that way complex algebraic scheme for sign of flow correction is avoided, while the final results still remain unchanged. Numbers of required iterations for the same results are comparable with the improved Hardy Cross method.

We present a novel passive satellite remote sensing approach for observing the three-dimensional distribution of aerosols emitted from wildfires. This method, called AEROS5P, retrieves vertical profiles of aerosol extinction from measurements of the TROPOMI satellite sensor onboard the Sentinel 5 Precursor mission. It uses a Tikhonov-Phillips regularization which iteratively fits cloud-free near-infrared and visible selected reflectances to simultaneously adjust the vertical distribution and abundance of aerosols. The information on the altitude of the aerosol layers is provided by TROPOMI measurements of the reflectance spectra at the oxygen A-band near 760 nm. In the present paper, we use this new approach for observing the daily evolution of the three-dimensional distribution of biomass burning aerosols emitted by Australian wildfires on 20-24 December 2019. Aerosol optical depths (AOD) derived by vertical integration of the aerosol extinction profiles retrieved by AEROS5P are compared with MODIS, VIIRS and AERONET coincident observations. They show a good agreement in the horizontal distribution of biomass burning aerosols, with a correlation coefficient of 0.86 and a mean absolute error of 0.2 with respect to VIIRS. A fair agreement is found between coincident transects of vertical profiles of biomass burning aerosols derived from AEROS5P and from the CALIOP spaceborne lidar. The mean altitude of these aerosols derived from these two measurements show a good agreement, with a small mean bias (185 m) and a correlation coefficient of 0.83. Moreover, AEROS5P observations reveal the height of injection of the biomass burning aerosols in 3D. The highest injection heights during the period of analysis are coincident with the largest fire radiative power derived from MODIS. Consistency is also found with respect to the vertical stability of the atmosphere.

Due to the increase in the emission of greenhouse gases, the hydrologic cycle is being altered on the daily basis. This has affected the variations in relations of intensity, duration, and frequency of rainfall events. Intensity Duration Frequency (IDF) curves describe the relationship between rainfall intensity, rainfall duration and return period. IDF curves are one of the most often applied implements in water resource engineering, in areas such as for operating, planning and designing of water resource projects, or for numerous engineering projects aimed at controlling floods. In particular, IDF curves for precipitation answer problems of improper drainage systems or conditions and extreme characters of precipitation which are the main cause of floods in Nyabugogo catchment. This study aims to establish Rainfall IDF empirical equations, curves and hydrological discharge (predicted peak rate of runoff (Qlogy)) equations for eight Districts that will be used for designing an appropriate and sustainable hydraulic structures for controlling flood to reduce potential loss of human and aquatic life, degradation of water, air and soil quality and property damage and economic lessen caused by flood in Nyabugogo catchment. However Goodness of Fit tests revealed that Gumbel’s Extreme-Value Distribution method appears to have the most appropriate fit compared with Pearson type III distribution for validating the Intensity-Duration-Frequency curves and equations through the use of daily annual for each meteorological station. The findings of the study show that the intensity of rainfall increases with a decrease in rainfall duration. Additionally, a rainfall of every known duration will have a higher intensity if its return period is high, while the predicted peak rate of runoff (Qlogy) increases also with an increase in the intensity of rainfall.

This paper deals with experimental study of the influence of conductive (Fe₃O₄) and insulating (Al₂O₃) nanostructured particles at various concentrations on the dielectric strength of transformer mineral oil. The method of preparation and characterization of these nanofluids (NFs) through the measurements of zeta potential, the real and imaginary parts of dielectric constant as well as the concentration and size of nanoparticles using Scanning Electron Microscope (SEM) images of nanoparticles powders and Dispersive x-ray Spectroscopy (EDS) analysis are presented. Experimental findings reveal that these two types of nanoparticles materials significantly improve AC breakdown voltage and the magnitude of this improvement depends on the concentration, size and nature (material) of nanoparticles. For a given type of nanoparticles, the effect is more marked with the smallest nanoparticles. The conductive nanoparticles offer higher enhancement of dielectric strength compared with insulating nanoparticles based nanofluids. With Fe₃O₄, the breakdown voltage (BDV) can exceed twice that of mineral oil and it increases by more than 76% with Al₂O₃. The physicochemical mechanisms implicated in this improvement are discussed.

A The aim of this study is to analyze the effect of different endodontic irrigants and adhesive systems on resin bond strength of fiber post cementation. 144 single-rooted, unrestored human teeth were endodontically treated and randomly divided into 12 groups according to 4 endodontic irrigants (distilled water as control; EDTA 17%; NaOCl 5%; clorhexidine 2%) and 3 different adhesive/resin cement systems (etch-and-rinse: ortofosforic acid, Parabond® A+B/Paracore®; self-etch: ParaBond® Non-Rinse Conditioner, Parabond® A+B /Paracore®; Universal: ClearfilTM Universal Bond/ ClearfilTM DC Core Plus). 48 h after post cementation ten teeth from each group were cross sectioned into 3 discs (cervical, middle and apical regions). 30 specimens of each group (n=30) were submitted to push-out test at a crosshead speed of 1 mm/min. The remaining 2 teeth of each group were sectioned in the same manner and the resin-dentin interface was evaluated using scanning electron microscopy (SEM). The results were statistically analyzed with the ANOVA and Tukey’s test (< 0,01). The adhesive protocols and post space region showed no significant effect on bond strength (> 0.01). The combination of NaOCl 5% and ClearfilTM Universal Bond reduced the adhesive strength (< 0.01). The NaOCl 5%, in relation with other irrigants, significantly decreased the push-out bond strength.

The rodents of Saudi Arabia consist of 20 species and 12 genera within four families (Gliridae, Dipodidae, Muridae, and Hystricidae). Details on the past and present distribution of the rodents were included along with available data on their habitat preference and biology. The eastern central part of Saudi Arabia covering Tuwiq mountains plateau, including the vicinity of Riyadh, hosts the highest number of rodent species. Analysis of the rodent fauna of Saudi Arabia revealed that they have four major zoogeographical affinities; Palaearctic-Oriental (one species), Afrotropical- Palaearctic (six species), Palaearctic (four species), endemic to Saudi Arabia and Yemen (three species), Afrotropical-Palaearctic-Oriental (three species) and three cosmopolitan species. According to the National Red List, the Euphrates Jerboa, S. euphratica, is listed as Endangered, Near Threatened for the Indian Crested Porcupine, H. indica, three species as Data Deficient, while the rest are considered as Least Concern.

Energy and information are fundamental concepts that play crucial roles in the foundations of science, each contributing to different aspects of our understanding of the natural world. Here we encounter that Fisher' measure is able to link them. We also investigate some interesting relations between Fisher's information, Poisson's distribution, and thermal quantifiers in a grand canonical ensemble. These connections permit one to visualize interesting novel artifacts in statistical mechanics. We clearly see them emerge in discussing the ideal gas. For example, we encounter that the Poisson distribution is intrinsically involved in the physics of the ideal gas, and we are able to give a Fisher-estimation of the difference in informational content between the grand canonical and canonical ensembles.

In this work a new method is proposed to tackle down the multiple objective optimization problem of the calculation of cation distribution in spinels structure, through the difference of intensity ratios between experimental and calculated intensities of cation sensitive Bragg planes, by introducing a new factor, Rabs, in Bertaut method. This factor is introduced as the sum of absolute R factors, and it is minimized by varying cation distribution. To test this method aluminate manganese spinel where synthesized though modified Pechini method and characterized though XRD. The results show to be in agreement with literature for the aluminum inversion in tetrahedral sites, which is near to the reported value of 10%. Also, it was noticed that the manganese atoms are present in octahedral sites with a mixed valence state of +2 and +3. Which might be an indicator that oxygen vacancies are present in the structure, so the vacancies value of oxygen is proposed considering the total charge of cations and thus proposing the value of 3.678 mol per formula unit of the spinel, thus having the next stoichiometry considering normalized Al and Mn, MnAl2O3.678. Finally, the last cation distribution proposed was [Mn0.867^(+2) Al0.129^(+3) ][Mn0.034^(+2) Mn0.098^(+3) Al1.871^(+3) ] O3.678 with a Rabs factor value of 0.6466, which considers the cation distribution and oxygen vacancies.

Hexabromocyclododecane (HBCD) was most important flame retardant in Expanded Polystyrene foam and Extruded Polystyrene foam in the past forty years in the world. China was the major producer and user of HBCD, and the total HBCD production was about 0.3 million tons. Although HBCD has been completely banned in China in 2021 because of its long-range transport, bioaccumulation and toxicity, there's still a lot of residues in environment. Therefore, we reviewed multiple studies concerning the distribution of HBCD in diverse environmental matrices, such as air, dust, soil, water, sediment and biota. Results revealed that HBCD levels in different environments in China present a geographical variation and were at high level compared with other countries. In all environmental media, relatively high HBCD concentrations have been found in industrial and urban areas. Industrialization and urbanization are two important factors that influence the concentration and distribution of HBCD in the environment. In terms of isomer, γ-HBCD was the dominant isomer in soil, water, and sediment, while in the biota, α-HBCD was the predominant isomer.

Spectrum distribution is a classical licensed spectrum accessing method in mobile communication networks. The licensed idle spectrum resources are authorized and distributed from spectrum owners to mobile users. However, the exponential growth of user capacity brings excessive load pressure on the traditional centralized network architecture. As lack of sufficient supervision and penalty measures, dishonest behaviors of spectrum owners and spectrum users will lead to the unfair status in the distribution process. As a result, the honest participants’ interest will be harmed. As an important supporting infrastructure of Internet of things technology, 6G cannot completely follow the existing spectrum distribution method. Towards 6G network spectrum distribution, an blockchain based licensed spectrum fair distribution method is proposed. A lightweight consensus mechanism named as proof of trust (PoT) is applied to reduce computational power consumption and consensus time overhead. We deploy the method on the Ethereum test chain, theoretical analysis and experimental results demonstrate the fairness, effectiveness and security of the method.

Imidacloprid is the first-generation neonicotinoid insecticide. But, the long-term use of im-idacloprid as a pesticide has caused severe water pollution. Recently, the toxicity of imidacloprid to aquatic organisms has received increasing attention. This study aimed to investigate the ab-sorption and distribution of imidacloprid in various tissues (gills, intestine, liver, muscle, brain, and gonads) of goldfish through short-term and continuous exposure tests for 28 days. The re-sults of short-term exposure indicated that the concentration of imidacloprid and its metabolites in tissues at the transfer stage decreased steadily after 1 day of 40 mg/l imidacloprid water treatment and was below the detection limit after 3 days. Continuous exposure for 28 days at various treatment concentrations showed that the concentrations of imidacloprid and its metab-olites differed significantly among the different tissues of the goldfish. In the 20 mg/l treatment group (S1), the highest concentration of imidacloprid was found in the liver (12.04 μg /gtissue), followed by the intestine (9.91 μg /gtissue), muscle (6.20 μg /gtissue), gill (6.11 μg /gtissue), gonads (5.22 μg /gtissue), and brain (2.87 μg /gtissue). In the 40 mg/l treatment group (S2), the order of tissue concentrations was similar to that of the S1 group, with the highest concentration observed in the liver (12.04 μg/gtissue), followed by the intestine (9.91 μg/gtissue), muscle (6.20 μg/gtissue), gill (6.11 μg/gtissue), gonads (5.22 μg/gtissue), and brain (2.87 μg/gtissue). Fur-thermore, the study detected 5-hydroxyimidacloprid, imidacloprid urea, and 6-chloronicotinic acid in imidacloprid metabolites in all tissues, while imidacloprid was detected only in the intes-tine and liver. Overall, the results of this study contribute to a better understanding of the met-abolic behavior of imidacloprid in organisms and provide new data to support the assessment of imidacloprid toxicity in fish.

The spatiotemporal variations of rainfall erosivity in the Hengduan Mountains, charac-terized by rugged terrain and high potential soil erosion risks, over the past 30 years was exam-ined. The changing trends of rainfall erosivity for 2025-2040 was also be investigated under the comprehensive scenario of moderate socio-economic development (SSP2-4.5) combined with me-dium-low radiative forcing, using four global climate models (GCMs) based on CMIP6. The results indicated that: (1) The annual distribution of rainfall erosivity in the Hengduan Mountains exhib-ited significant seasonal variations, with the order of erosivity being summer > autumn > spring > winter on a seasonal scale. (2) Over the past 30 years, there has been a slight decrease in annual precipitation and a slight increase in rainfall erosivity, with periodic extreme values occurring every 6-8 years. (3) Rainfall erosivity showed a decreasing gradient from southeast to northwest in terms of spatial distribution. There was a significant positive correlation between rainfall ero-sivity and precipitation, while a significant negative correlation existed with elevation in the ver-tical direction. Moreover, there was an increasing trend of rainfall erosivity in the northeastern part of the Hengduan Mountains and a decreasing trend in the southern region. (4) Under the joint driving forces of increased precipitation and erosive rainfall events, rainfall erosivity in the future is expected to significantly increase, posing a more severe risk of soil erosion in the Heng-duan Mountains.

Inflammation is the response of the immune system to infection and injury, with complex interactions with the body, tissues and cells, and plays an important role in the initiation and progression of many diseases such as cancer and cardiovascular disease. Traditional excipients functioning as drug delivery systems can reduce the side effects of systemic distribution of inflammatory drugs. Oil phase, a common excipient in nanoemulsions (NEs), has the advantages of assisting the formation of emulsions, loading lipophilic drugs, thermodynamic stability, wide sources, low price and easy availability. In particular, some of them, like linolenic acid and medium chain triglyceride (MCT), also function as inhibitors of systemic inflammation marker and vascular inflammation marker. However, the influences of different oil phases on the construction of NEs and their distribution in vivo have not been fully investigated. Herein, Tween 80 and ethyl alcohol were screened out as emulsifiers and co-emulsifiers, and three different oil phases used in clinical practice widely, including MCT, oleic acid (OA), and ethyl oleate (EO), were selected as the oil phase to prepare NEs delivery platform. Three NEs had consistent size, potential, morphology, excellent stability and mitochondrial localization function. Importantly, they exhibited superior cellular uptake capacity in inflammatory-injuried human umbilical vein endothelial cells and significantly targeted the brain, lung, heart and thoracic aorta in the lipopolysaccharide-induced mouse and zebrafish larvae inflammation models. Meanwhile, the fluorescence intensities of three NEs were different in these organs, suggesting that their differential enrichment might provide alternative delivery platform for disease treatment in the corresponding organs.

In recent years, with the rapid development of technology, artificial intelligence(AI) security issues represented by adversarial sample attack have aroused widespread concern in society. Adversarial samples are often generated by surrogate models and then transfer to attack the target model, and most AI models in real-world scenarios belong to black boxes, thus transferability becomes a key factor to measure the quality of adversarial samples. The traditional method relies on the decision boundary of the classifier and takes the boundary crossing as the only judgment metric without considering the probability distribution of the sample itself, which results in an irregular way of adding perturbations to the adversarial sample, an unclear path of generation, and a lack of transferability and interpretability. In the probabilistic generative model, after learning the probability distribution of the samples, a random term can be added to the sampling to gradually transform the noise into a new independent and identically distributed sample. Inspired by this idea, we believe that by removing the random term, the adversarial sample generation process can be regarded as static sampling of the probabilistic generative model, which guides the adversarial samples out of the original probability distribution and into the target probability distribution, and helps to improve transferability and interpretability. Therefore, we propose a Score Matching-Based Attack(SMBA) method to perform the adversarial sample attacks by manipulating the probability distribution of the samples, which can show good transferability in the face of different datasets and models, and give reasonable explanations from the perspective of mathematical theory and feature space. In conclusion, our research establishes a bridge between probabilistic generative models and adversarial samples, provides a new entry angle for the study of adversarial samples, and brings new thinking to AI security.

This paper discusses and reviews the current taxonomic status and zoogeographical distribution of the mammals of Yemen. Data were collected from previous literature in addition to field observations during 2017–2018. This checklist includes 100 species of wild (terrestrial and marine) mammals currently occurring and those that went extinct within the last century in Yemen. Only wild mammals were included and domesticated species were excluded. These 100 species belong to 11 orders, 28 families, and 64 genera. In this paper, the current status and distribution of three Erinaceomorphs, seven Soricomorphs, 34 Bats, 16 Carnivores, seven Artiodactyls, one Lagomorph, 20 Rodents, one Hyracoidea, nine Cetaceans, one Sirenia, and one Primate were reported. According to the evaluation of the International Union for the Conservation of Nature and Natural Resources (IUCN): 70 species were listed as Least Concern (LC), two as Extinct (EX), one as Critically Endangered (CR), two as Endangered (EN), eight as Vulnerable (VU), five as Near Threatened (NT), and 12 as Data Deficient (DD). This paper also discusses the current main threats to the wild mammals in Yemen.

Monitoring is an important component of pest management, to prevent or mitigate outbreaks of native pests, and to check for quarantine organisms. Surveys often rely on trapping, especially when the target species respond to semiochemicals. Many traps are available for this purpose, but they are bulky in most cases, which raises transportation and deployment issues, and they are expensive, which limits the size and accuracy of any network. To overpass these difficulties, entomologists have used recycled material, such as modified plastic bottles, producing cheap and reliable traps but at the cost of recurrent handywork, not necessarily possible for all end-users (e.g., for national plant protection organizations). These bottle-traps have allowed very large surveys which would have been impossible with standard commercial traps, and we illustrate this approach with a few examples. Here we present, under a Creative Commons BY-SA License, the blueprint of a fan-trap, a foldable model, laser-cut from a sheet of polypropylene, that can rapidly be produced in large numbers, and could be transported and deployed in the field with very little efforts. Our first field comparisons show that fan-traps are as efficient as bottle-traps, and we describe two cases where they are being used for monitoring.

When a microgrid is grid-tied to a distribution system, it can provide surplus power generation to the distribution system, if any abnormality or interruption occurs in the distribution system, the microgrid can operate in standalone mode to isolate the impact of the abnormality or interruption. However, if the microgrid can not collect enough information from the distribution system, it may cause the failure of generation transferring of distribution feeders, or even further influence the stability of the distribution system. In this paper, a strategy for the resilient control of a microgrid is proposed. It can solve the above-mentioned problem, reduce the duration of the outage of loads. This strategy is experimented in the microgrid in the Institute of Nuclear Energy Research (INER), the reliability is also analyzed to evaluate the unavailability of the microgrid in INER, and it is verified that the proposed strategy can reduce the duration of the outage of loads, and hence the reliability of a microgrid can be upgraded.

Bemisia tabaci (Gennadius) is a polyphagous, highly destructive pest capable of vectoring viruses in most agricultural crops. Currently, information on the distribution and genetic diversity of B. tabaci in South Sudan is not available. The objectives of this study were to investigate the genetic variability of B. tabaci infesting sweet potato and cassava in South Sudan. Field surveys were conducted between August 2017 and July and August 2018 in 10 locations in Juba County, Central Equatoria State, South Sudan. Sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) were used to determine the phylogenetic relationships between sampled B. tabaci. Six distinct genetic groups of B. tabaci were identified including three non-cassava haplotypes (Mediterranean (MED), Indian Ocean (IO) and Uganda) and three cassava haplotypes (Sub-Saharan Africa 1 sub-group 1 (SSA1-SG1), SSA1-SG3 and SSA2). MED predominated on sweet potato and SSA2 on cassava in all the sampled locations. The Uganda haplotype was also widespread, occurring in five of the sampled locations. This study provides important information on the diversity of B. tabaci species in South Sudan. A comprehensive assessment of the genetic diversity, geographical distribution, population dynamics and host range of B. tabaci species in South Sudan is vital for its effective management.

The paper analyzes the probability distribution of the occupancy numbers and the entropy of a system at the equilibrium composed by an arbitrary number of non-interacting bosons. The probability distribution is derived both by tracing out the environment from a bosonic eigenstate of the union of environment and system of interest (the empirical approach) and by tracing out the environment from the mixed state of the union of environment and system of interest (the Bayesian approach). In the thermodynamic limit, the two coincide and are equal to the multinomial distribution. Furthermore, the paper proposes to identify the physical entropy of the bosonic system with the Shannon entropy of the occupancy numbers, fixing certain contradictions that arise in the classical analysis of thermodynamic entropy. Finally, by leveraging an information-theoretic inequality between the entropy of the multinomial distribution and the entropy of the multivariate hypergeometric distribution, Bayesianism of information theory and empiricism of statistical mechanics are integrated into a common ''infomechanical'' framework.

Air pollution includes particle-bound Polycyclic Aromatic hydrocarbons (PAHs) which eventually reach the placenta triggering adverse perinatal outcomes by long-term exposure. Late-ly, air pollution has increased over the Metropolitan Area of Medellin-Colombia (MAMC) but its effects on pregnancy are still unknown. In this research, we made a real-time analysis of airborne total PAHs using a photoelectric sensor for residential places influenced by industrial and traffic sources contrasting southern and northern MAMC during the second peak of the bimodal ten-dency for PM2.5 emissions in this region. Additionally, we analyzed individual PAHs by GC/MS coupled to pressurized hot water extraction methodology. Data was applied in an Inhalation In-take Model to assess pregnancy exposure. The average concentration of PAHs over southern MAMC was three times higher than over northern MAMC where the abortion rate has been 1.4 times higher presented in database. Previous research found that PAHs act as an Endo-crine-Disrupting Chemical (EDC) during pregnancy and even heavy congeners could reside in umbilical cord blood. Finally, the annual series of abortion rates in the MAMC showed a signifi-cant correlation with the annual average levels of PM2.5 which are associate to PAHs. Although this significant correlation does not imply causality, our results suggest an important connection between both variables. This latter finding opens a gap in deeply understanding how regions with high PAHs-convergence influences abortion rates in MAMC.

Shear connectors are used in steel beam–concrete slabs of composite frame and bridge structures to transfer shear force according to design loads. The existing Y-type perfobond rib shear connectors are designed for girder slabs of composite bridges. Therefore, the rib and transverse rebars of the conventional Y-type perfobond rib shear connectors are extremely large for the composite frames of building structures. We performed push-out tests of stubby Y-type perfobond rib shear connectors for composite frames. These shear connectors have relatively small ribs than conventional Y-type perfobond rib shear connectors. To confirm the shear resistance of these stubby shear connectors, we performed an experiment by using transverse rebars D13 and D16. The results indicate that these shear connectors have suitable shear strength and ductility for application in composite frame structures. The shear strengths obtained using D13 and D16 were not significantly different. However, the ductility of the shear connectors with D16 was 45.1% higher than that of the shear connectors with D13.

In order to achieve its carbon peak and neutrality targets, a high proportion of distributed power sources are connected to the distribution network in China, which greatly increases the risk of distribution network operation. Aiming at the above problems, this paper proposes an active distribution network risk planning model based on multi-source data from carbon capture and power internet of things, and conducts exceeding testing of distribution network based on the stochastic load flow algorithm with semi-invariant and level expansion, calculates the semi-invariant of each order of node state vectors and branch current vectors, and then utilizes the Gram-Charlier level expansion to obtain the exceeding probability density function and probability distribution function of the node voltages and line powers of the distribution network. The probability density function and probability distribution function of the exceeding are obtained using the Gram-Charlier series expansion. Combined with multi-source data, the active distribution network with integrated energy system considering carbon capture is modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model are simplified by the second-order cone relaxation, and the optimal planning scheme of the distribution network is solved by combining the gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verify the effectiveness of the proposed model.

Tourism is increasingly becoming one of the most important components of the economy. Coastal tourism is of particular importance in our country, this is because Albania has a very favorable geographical position. The tourist destination chosen for study in this paper is Durrës. It is analyzed as a complex dynamic system that evolves with a series of techniques and methods drawn from the area of network theory. The main objective of this paper is the comparison of technological and socio-economic networks, through different methods and techniques. The methodology of this research includes different data collection methods for both networks and their analysis. 504 nodes were taken into consideration. A significant part of the research is based on network theory, using algorithms and network analysis techniques to reveal their static and dynamic characteristics. Through this paper we show that the internet network and the socio-economic network of Durrës are similar in some aspects and have a great impact on the development of the tourist destination. The analysis of these two networks provides a deeper picture of the relations between the actors of the destination and helps to improve the tourism strategies and the economic development of the area. Thus, the research is an attempt to better understand the impact of technological and socio-economic networks in the development of the tourist destination of Durrës and uses different ways of network analysis to discover the similarities and differences between them.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

The migration paths and distribution driving factors of heavy metals in dry and windy area polluted by their production in the North China need a further research. To address this research gap, we collected 675 soil samples, 72 atmospheric deposition samples and 20 water samples around a production area and measured its heavy metal concentrations. Results showed that the Cu, Zn, As and Pb in 0-10 cm soil layer showed a fan-shaped distribution, which was consistent with their atmospheric deposition fluxes. It indicated the distribution patterns of these heavy metals were driven by strong winds in studied area. Although Cr concentrated to the production area in the 0-10 cm soil layer, principal component analysis showed that this migration was through wind as well. The concentration of Cd in the river increased from 0.257 mg/L to 0.460 mg/L along water flowing, and caused the same distribution trend in soil near the river from upstream to downstream. Unlike the above, surface runoff should drive the Cd migration. The concentration of Pb in the river was over threshold of pollution, and also led to an accumulation in the 5-10 cm soil layer. It suggested that the migration of Pb was through both wind and surface runoff. Six studied heavy metals showed different migration behaviors, and specific control strategies for individual heavy metal should be concerned.

Dengue virus is becoming a major public health threat worldwide principally in Africa. From 2016 to 2020, 23 outbreaks were reported in Africa principally in West Africa. In Senegal outbreak are reported yearly since 2017 ; data about the circulating serotypes and their spatial and temporal distribution are limited to 2017 – 2018 period. Herein we describes up to date molecular surveillance of circulating DENV serotypes in Senegal between 2019 to 2023 and their temporal and spatial distribution around the country. For this purpose collected suspected DENV infections samples were subjected to dengue detection and serotyping using RT-qPCR methods. Positive samples subjected to temporal and spatial mapping. Subset of DENV+ samples were then sequenced and subjected to phylogenetic analysis. Results show a co-circulation of three DENV serotypes with a overall predominance of DENV-3 followed by DENV-1 with scarce cases of DENV-2 from 02_2019 to 02_2022. Interestingly data shows extinct of both serotype 1 and serotype 2 and the only circulation of DENV-3 from March 2022 to July 2023. At the genotype level analysis shows that sequenced strains belong to same genotype as previously described DENV-1 belong to genotype V, DENV-2 to cosmopolitan genotype and DENV-3 to Genotype III. Interestingly newly obtained DENV 1-3 sequences cluster in different clades within genotypes. This co-circulation of strains belonging to different clades could have effect on virus epidemiology and transmission dynamic. Overall our results highlight DENV serotypes replacement by DENV-3 accompanied by wider geographic distribution in Senegalese regions. All unmentioned results highlight the importance of virus genomic surveillance and call for further fitness studies using both in vitro and in vivo model as well as in depth phylogeographic study to uncover the virus dispersal patterns across the country.

Background – Mali was one of the first countries in sub-Saharan Africa to initiate a National Schistosomiasis Control Programme (NSCP) in 1982. The WHO's 2021-30 roadmap sets out criteria for eliminating and controlling schistosomiasis as a public health problem. Our study aimed to assess the impact of annual Mass Drug Distribution (MDD) with praziquantel (PZQ) among school-age children in the sentinel sites (SS) of the NSCP. Methods –The study took place at twelve SS in Kayes and Koulikoro regions. Two-round observational cross-sectional studies were carried out in December 2014-2015 and in April 2018 after four to five years of annually MDD. Overall, 2442 schoolchildren aged 7 to 14 were successfully examined. The urine filtration and Kato-Katz method were used for determining Schistosoma haematobium and S. mansoni eggs, respectively. Results –Of the twelve SS treated from 2014-2015, one has achieved the criterion of elimination of S. haematobium as a public health problem (prevalence of heavy intensity infection PHI < 1%) (ie, ≥50 S. haematobium eggs per 10 mL of urine or ≥400 S. mansoni eggs per g of stool), four met the morbidity control criterion (PHI< 5%) while two sites remained confined below the morbidity control criterion (PHI>5%). Five SS had no heavy intensity infection. The prevalence of S. mansoni was less than 1%. Conclusion –The impact evaluation of MDD with praziquantel in the SS of NSCP highlights that MDD has significantly reduced the PHI of schistosomiasis. However, the high prevalence of schistosomiasis or its increase in some sites requires in-depth studies.

Incidence of COVID-19 has been associated with sociodemographic factors. We investigated variations in SARS-CoV-2 seroprevalence at sub-national levels in the Dominican Republic and assessed potential factors influencing variation in regional-level seroprevalence. Data were collected in a three-stage cross-sectional national serosurvey from June to October 2021. Seroprevalence of antibodies against the SARS-CoV-2 spike protein (anti-S) was estimated and adjusted for selection probability, age, and sex. Multilevel logistic regression was used to estimate the effect of covariates on seropositivity for anti-S and correlates of 80% protection (PT80) against symptomatic infection for ancestral and Delta strains. A total of 6,683 participants from 134 clusters in all 10 regions were enrolled. Anti-S, PT80 for ancestral and Delta strains odds ratio varied across regions, Enriquillo presented significant higher odds for all outcomes compared with Yuma. Compared to unvaccinated, receiving ≥2doses of COVID-19 vaccine was associated with a significantly higher odds of anti-S positivity (OR 85.94, [10.95-674.33]), and PT80 for ancestral (OR 4.78, [2.15-10.62]) and Delta strains (OR 3.08, [1.57-9.65]) nationally, and also for each region. Our results can help inform regional-level public health response, such as strategies to increase vaccination coverage in areas with low population immunity against currently circulating strains.

Taxes on the consumption of certain products have played a key role in public revenue analysis in European countries. This work aims to assess the differences in tax planning on new non-combustion products across some European territories. Through theoretical analysis, the paper has three distinct aspects. Firstly, we show the taxpayer profile in different countries. Secondly, the study analyzes the risks for the health system and the individual. Thirdly, the design of the land tax is based on previous experience and planning in Europe. This paper concludes with a case study for different countries: 1) Spain “vapers” and “smokers”, where the analysis is based on micro-data from the European Health Interview Survey 2020. 2) Sweden with the analysis of snus, shows it as a practice to reach economic savings while decreasing economic costs thanks to the nudging of consumers towards better products. The results show taxation and, specially, land taxation, should consider differences in planning in the case of new products, such as the non-combustion products, given the user per capita income and the potential lower health risks involved.

Currently, there are different types of technology for the production of electricity that use various energy sources, this causes the establishment of generation centers that provide from a small amount to tens of megawatts of electrical energy. These centers are built to supply electricity to nearby loads through networks integrated into a large electrical system or in isolation with their electrical system. The technological evolution, the different energy sources, and the generation centers close to the consumers entail what has been called a distributed generation (DG), the DG carries with it aspects that need to be analyzed. In this paper, the impact of wind generation on the medium voltage energy distribution network is studied, it was determined that the addition to the distribution network of power by wind turbines less than the transmission center does not produce an impact on the network. Simulated results obtained using SIMULINK and DIgSILENT are presented and discussed.

The issue of polarization, as opposed to inequality, has been little explored for European countries. in this paper, using harmonized data produced by Luxembourg Income Study Database, observes income trends for 12 European countries, showing an increase in polarization in many of the countries considered. the drivers that led to this concentration of income are also analyzed, noting heterogeneous factors within countries.

Water distribution networks are vital infrastructure, needed for providing consumers with sufficient water of appropriate quality. The cost of construction, operation, and maintenance of such networks is extremely large. The problem of optimization of a water distribution network is governed by the type of water distribution network and the size of pipelines placed in the distribution network. This problem of the optimal diameter allocation of pipes in a distribution network has been heavily researched over the past few decades. This study describes the development of a computer program, ‘Smart Optimization Program for Water Distribution Networks’ (SOP–WDN), which applies Genetic Algorithm to the problem of the least-cost design of water distribution networks. SOP–WDN demonstrates the application of an evolutionary optimization technique, Genetic Algorithm, linked with a hydraulic simulation solver EPANET, for the optimal design of water distribution networks. The developed program was applied to three benchmark water distribution network optimization problems and produced consistently good results. SOP–WDN can be utilized as a tool for guiding engineers during the design and rehabilitation of water distribution pipelines.

Revealing the binding properties of calcium ion (Ca2+) and magnesium ion (Mg2+) to chromophoric dissolved organic matter (CDOM) facilities understanding the effect of natural water composition on the photophysics of dissolved organic matter. Steady-state and time-resolved fluorescence spectrometry, and dynamic light scattering were applied to investigate the fluorescence quenching process of CODM by Ca2+ and Mg2+. The binding of Ca2+ and Mg2+ preferred terrestrial CDOM to aquatic CDOM. The fluorescence quenching of CDOM by cations mainly occurred in a static process, which was based on the fact that the decrease of steady-state fluorescence intensity was greater than fluorescence lifetime. The fluorescence quenching was profound under longer excitation and emission wavelength. The binding constant (K, L/mol) for Ca2+ to CDOM from terrestrial source ranged from 4.29 to 5.09 (lgK), which was approximately one order of magnitude higher than that of Mg2+ to CDOM (3.86 to 4.56). Fluorescence decay became faster in the presence of Ca2+ and Mg2+. Lifetime distribution of CDOM excited states shifted to small value side in the presence of metal ions, particularly for Ca2+, indicating fluorescence quenching of CDOM mainly through the interaction of Ca2+/Mg2+ with relatively long-lived fluorophores.

Chemotherapy-related deaths, the result of treatment with faulty medications, account for nearly 10% of all breast cancer deaths (Rashbass, 2016). Patient-specific, personalized medicine is evidently required to administer optimized therapeutics and prevent treatment-related mortality. In order to develop a predictive model for breast cancer therapy, the following study analyzed the mRNA data of 4,704 genes derived from 20 breast cancer patients before and after doxorubicin treatment for 16 weeks (O’brien et al., 2006; Perou et al., 2000). The genomic data of each patient was first stratified into 9 groups (corresponding to the 9 Mechanisms defined in Figure 4) based on mRNA expression in response to the tumor and to the doxorubicin treatment. The study then employed the Planckian Distribution Equation (PDE) discovered at Rutgers University to model the stratified samples by transforming each mechanism into a single long-tailed histogram fitted by the PDE. Our PDE model is based on 3 parameters - A, B, and C - of which 2 were extracted from each model to generate the plots seen in figures 5e and 5f. The drug-induced slopes of the A vs C plots were then determined for all 9 mechanisms of each patient. The study observed an increase in post-treatment mRNA levels for longer surviving patients in 6 mechanisms. Further analysis displayed how the drug treatment uniquely altered each of the mechanisms based on the length of patient survival. These results indicate that the PDE-based procedures described herein may provide a novel tool for discovering potential anti-breast cancer pharmaceuticals.

The study presents an updated overview of the 14 non-endemic threatened Crop Wild Relatives (CWR) in Italy: Aegilops biuncialis, Ae. uniaristata, Ae. ventricosa, Asparagus pastorianus, Beta macrocarpa, Brassica insularis, B. montana, Crambe hispanica subsp. hispanica, C. tataria subsp. tataria, Ipomoea sagittata, Lathyrus amphicarpos, L. palustris, Vicia cusnae and V. serinica. Geographical distribution, ecology (with plant communities and habitat 92/43/EEC aspects), genetics (focused on gene pools), property, and in situ and ex situ conservation were analyzed. In addition, with the aim of their protection and valorization, specific actions are recommended.

Based on recent contributions regarding the treatment of unsteady hydraulic conditions into the state-of-the-art of scour literature, the theoretically derived probability distribution of bridge scour is introduced. The model is derived assuming a rectangular hydrograph shape with a given duration, and random flood peak following a Gumbel distribution. A model extension for a more complex flood event is also presented, assuming a synthetic exponential hydrograph shape. The mathematical formulation can be extended to any flood-peak probability distribution. The aim of the manuscript is to move forward the current approaches adopted for the bridge design coupling hydrological, hydraulic, and erosional models in a mathematical closed form.

This study generalized the best copula to characterize the joint probability distribution between rainfall severity and duration in Peninsular Malaysia using two dimensional copulas. Specifically, to construct copulas, Inference Function for Margins (IFM) and Canonical Maximum Likelihood (CML) methods were specially exploited. For the purpose of achieving copula fitting, the derived rainfall variables by making use of the Standardized Precipitation Index (SPI) were fitted into several distributions. Five copulas, namely Gaussian, Clayton, Frank, Joe and Gumbel were put to the tests to establish the best data fitted copula. The tests produced acknowledged and satisfactory results of copula fitting for rainfall severity and duration. Surveying the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), only three copulas produced a better fit for parametric and semi parametric approaches. Finally, two consistency tests were conducted and the results had shown that Frank Copula produced consistent results.

The management of existing water distribution system (WDS) is challenged by ageing of infrastructure, population growth, increasing of urbanization, climate change impacts and environmental pollution. Therefore, there is a need for integrated solutions that support decision makers to plan today, while taking into account the effect of these factors in the mid and long term. The paper is part of a more comprehensive project, where advanced hydraulic analysis for WDS is coupled with a dynamic resources input-output analysis model. The proposed modeling solution can be used to optimize the performance of a water supply system while considering also the energy consumption and consequently the environmental impacts. Therefore, as a support tool in the management of a water supply system also in the intervention planning. Here a possible application is presented for rehabilitation/replacement planning while maximizing the network mechanical reliability and minimizing risk of unsupplied demand and pressure deficit, under given economic constraints.

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

The compilation summarizes results so far gathered in a project that investigates the atom with classical (Newtonian) physics. It posits that the atom’s wave-particle dual nature is real, objective and intrinsic; the wave gives rise to the cosmic vacuum field while the particle, of course, manifests condensed matter. Light’s π radians oscillation manifests, on molar scale, significant radial tension in the vacuum field, the effect, amongst others, causes molecular matter to precipitate out of the vacuum – so-called ‘molecular outflow’. Cosmic vacuum field radial tension relates to molecular mass, in other words, a mass-radius (M-R) relationship is uncovered. It is argued that using the M-R relation it is possible to perform a valid simulation of the cosmic physical reality. The three states of matter are meaningfully accounted for using the atom’s e-m radiation wavelength. It is explained that force, be it of any kind whatsoever, originates in the atomic waveform, i.e., the cosmic vacuum field.

Laportea bulbifera (Sieb. et Zucc.) Wedd. (L. bulbifera) is a significant plant belonging to the Laportea genus. It has been traditionally used in ethnomedicine to treat various conditions such as rheumatic arthralgia, fractures, falling injuries, nephritis dropsy, limb numbness, pruritus, fatigue-induced internal imbalances, and irregular menstruation. Modern pharmacological studies have confirmed its therapeutic potential, as it exhibits anti-inflammatory, immunosuppressive, analgesic, and anti-rheumatoid arthritis properties. In order to gather in-depth information on L. bulbifera, a comprehensive literature search was conducted using databases such as Web of Science, PubMed, ProQuest, and CNKI. This review aims to provide a comprehensive understanding of L. bulbifera by covering various aspects, including ethnomedicinal uses, geographical distribution, botanical description, phytochemistry, pharmacology, and quality control. By doing so, this review intends to lay a strong foundation and propose new research avenues for the exploration and development of potential applications of L. bulbifera. Thus far, a total of 189 compounds have been isolated and identified from L. bulbifera. These compounds include flavonoids, phenolics, nitrogen compounds, steroids, terpenoids, coumarins, phenylpropanoids, fatty acids and their derivatives, and other compounds. Notably, flavonoids and fatty acids in L. bulbifera have demonstrated remarkable antioxidant and anti-inflammatory properties. Furthermore, these compounds show promising potential in activities such as analgesia, hypoglycemia, and hypolipidemia, as well as toxicity. Despite the extensive fundamental studies conducted on L. bulbifera, further research is still needed to enhance our understanding of its credible mechanism of action and improve its quality control. This necessitates more comprehensive investigations to explore the specific material basis, uncover new mechanisms of action, and refine the quality control methods related to L. bulbifera. By doing so, we could contribute to the further development and utilization of this plant.

Continuous-variable quantum key distribution (CV-QKD) shows potential for the rapid development of an information-theoretic secure global communications network; however, the complexities of CV-QKD implementation remain a restrictive factor. Machine learning (ML) has recently shown promise in alleviating these complexities. ML has been applied to almost every stage of CV-QKD protocols, including ML-assisted phase error estimation, excess noise estimation, state discrimination, parameter estimation and optimization, key sifting, information reconciliation, and key rate estimation. This survey provides a comprehensive analysis of the current literature on ML-assisted CV-QKD. In addition, the survey compares the ML algorithms assisting CV-QKD with the traditional algorithms they aim to augment, as well as providing recommendations for future directions for ML-assisted CV-QKD research.

Deep Learning (DL) and Machine Learning (ML) are widely used in many fields, but rarely used in Frequency Estimation (FE) and Slope Estimation (SE) of signals. Frequency and slope estimation for Frequency-Modulated (FM) and single-tone sinusoidal signals are essential in various applications, such as wireless communications, sonar, and radar measurements. In this work, artificial neural network (ANN) and convolutional neural network (CNN) are used in frequency and slope estimation for FM signals under Additive White Gaussian Noise (AWGN) and Additive Symmetric alpha Stable Noise (SαSN). SαS distributions are impulsive noise disturbances found in many communication environments like marine systems; their distribution lacks a closed-form Probability Density Function (PDF), except for specific cases, and infinite second-order statistic, hence Geometric SNR (GSNR) is used in this work to determine the impulsiveness of noise in a mixture of Gaussian and SαS noise processes. ANN is a machine learning classifier, designed with few layers for reducing FE and SE complexity while getting higher accuracy as compared with classical techniques. CNN is a deep learning classifier, designed with many layers for FE and SE, and proved to be more accurate than ANN when dealing with big data and finding optimal features. Simulation results show that SαS noise can be much more harmful for FE and SE of FM signals than Gaussian noise. DL and ML can significantly reduce FE complexity, memory cost, and power consumption, which is important in many systems such as some Internet of Things (IoT) sensor applications. After training DCNN for frequency and slope estimation of LFM signals, the performance of DCNN (in terms of accuracy) can give acceptable results at very low signal-to-noise ratios where TFD fails, giving more than 20dB difference in the GSNR working range.