Search

Clay–gravel mixture is an increasingly popular material used in geotechnical engineering for its engineering adaptability and easy accessibility. Among various granulometric factors, gravel content plays a critical role in the alteration of mixture microstructure. Its influence on mechanical behavior has been comprehensively investigated, yet the hydraulic models accounting for the paired impact of clay and gravel particles are seldomly discussed. In an effort to enhance the permeability prediction capability of this soil, a generalized binary model derived from a theoretical hydraulic conductivity expression is proposed, with the participation of two fundamental compound seepage models. High accuracy between test and calculation results indicates the reliability of this model, as well as its supremacy over conventional models. The parameter sensitivity analysis demonstrates that the proposed model, being of convincing parametric stability regardless of variant particle size distribution characteristics, has the potential to be applicable to a wide range of engineering-adapted CGMs. The predictive formula for cohesive fraction and the anomaly coefficient, as is integrated into the binary model, are explicitly discussed. Suitable for clay–gravel materials under a transitional soil state for engineering applications, this model provides a quantitative and reasonable evaluation of hydraulic conductivity with high practicality. The above findings might work as a perspective for the credible assessment of structure seepage safety behavior, as well as a quantitative evaluation method regarding the mixing quality of CGMs. [ABSTRACT FROM AUTHOR]

This article presents an analysis of the grounds of sex and gender as understood in the judgment of King NO & Others v De Jager & Others. The King judgment raises a number of interesting questions for the South African law of succession in the future, including whether the testator in a private will has the right to discriminate against certain groups due to the broad freedom of testation recognised in South African law. This article analyses the judgment's approach to gender discrimination, and how that reflects South African law's current approach to the concepts of sex and gender in private law interactions. The South African legal system, like many others, is based on a binary model that uses sex and gender as interchangeable terms when faced with cases of discrimination based on either of these grounds. This perpetuates an erroneous assumption that biological sex and gender identity are interchangeable, as opposed to intersectional. [ABSTRACT FROM AUTHOR]

Kokoro as a broadly acknowledge maize snack is being consumed every day by both the children and grown-ups, but it is characterized by the low protein content required for survival. The blending of maize flour (MF), sesame flour (SF) and moringa flour (mF) to enhance the nutritional values of kokoro was optimize with response surface technique (RSM) and artificial neural network (ANN). MF, SF and mF were mixed at diverse proportion and the optimal blending ratio was gotten using D-optimal design method. The protein and carbohydrate actual contents were compared with their predicted values using RSM and ANN models. The performance of the developed RSM and ANN models were validated with coefficient of determination (R2) and mean square error (MSE). The optimal blending ratio of MF: SF: mF was 54.11: 37.06: 8.83. The optimal blending ratio gave 25.53% of protein content and 45.99% of carbohydrate content. The statistical analysis of the experimental data obtained using different statistical techniques shows that regression models by RSM gave R2 of 0.999 for protein yield and 0.983 for carbohydrate yield while ANN gave R2 of 0.999 with MSE 9.24184 × 10−1. Therefore, it can be concluded from the results that both the RSM and ANN gave good prediction of the model. [ABSTRACT FROM AUTHOR]

Online propaganda is a mechanism to influence the opinions of social media users. It is a growing menace to public health, democratic institutions, and public society. The present study proposes a propaganda detection framework as a binary classification model based on a news repository. Several feature models are explored to develop a robust model such as part-of-speech, LIWC, word uni-gram, Embeddings from Language Models (ELMo), FastText, word2vec, latent semantic analysis (LSA), and char tri-gram feature models. Moreover, fine-tuning of the BERT is also performed. Three oversampling methods are investigated to handle the imbalance status of the Qprop dataset. SMOTE Edited Nearest Neighbors (ENN) presented the best results. The fine-tuning of BERT revealed that the BERT-320 sequence length is the best model. As a standalone model, the char tri-gram presented superior performance as compared to other features. The robust performance is observed against the combination of char tri-gram + BERT and char tri-gram + word2vec and they outperformed the two state-of-the-art baselines. In contrast to prior approaches, the addition of feature selection further improves the performance and achieved more than 97.60% recall, f1-score, and AUC on the dev and test part of the dataset. The findings of the present study can be used to organize news articles for various public news websites.

The collective pressurized irrigation system (CPIS), by definition, is expressed as a process of implementing unified pressurized irrigation systems on adjacent lands along with the participation of smallholders and the government and utilizing a public well on integrated lands. This study investigates the factors that affect the tendency to adopt CPIS in Takestan County of Qazvin Province (Iran) over the years 2016–2017. The statistical population of this study includes farmers who use groundwater for irrigation in Takestan County (N = 1740). Of these farmers, 210 were selected as the sample size using Cochran formula, Chi-square, Phi and Cramer's V, and Lambda tests that were used to investigate the relationship between the proposed irrigation system adoption and different dependent variables. Seven research hypotheses were proposed and tested. Since there is a positive and significant relationship between all social communication features and the adoption of CPIS, it is, therefore, recommended that city officials provide more promotional/educational classes and necessary facilities to increase farmers' acquaintance with new irrigation methods and raise their awareness about the benefits of such a participation in these schemes and programs. In doing so, there is a higher chance that farmers would cooperate to a greater degree in water management. [ABSTRACT FROM AUTHOR]

Clinical retinal image analysis is an import aspect of clinical diagnosis in ophthalmology. Retinopathy of Prematurity (ROP) represents one of the most severe retinal disorders in prematurely born infants. One of the ROP clinical signs is the presence of retinal lesions endangering the vision system. Unfortunately, the stage and progress of these findings is often only subjectively estimated. A procedure such as this is undoubtedly linked to subjective inaccuracies depending on the experience of the ophthalmologist. In our study, a fully autonomous segmentation algorithm to model retinal lesions found using RetCam 3 is proposed. The proposed method used a combination of retinal image preprocessing and active contours for retinal lesion segmentation. Based on this procedure, a binary model of retinal lesions that allowed retinal lesions to be classified from a retinal image background was obtained. Another important aspect of the model was feature extraction. These features reliably and automatically described the development stage of an individual lesion. A complex procedure such as this has significant implications for ophthalmic clinical practice in substituting manual clinical procedures and improving the accuracy of routine clinical decisions.

Biofuels are socially and politically accepted as a form of sustainable energy in numerous countries. However, cases of environmental degradation and land grabs have highlighted the negative effects to their adoption. Smallholder farmers are vital in the development of a biofuel industry. The study sought to assess the implications in the adoption of biofuel crops by smallholder farmers. A semi-structured questionnaire was administered to 129 smallholder farmers who were sampled from the Eastern Cape Province in South Africa. A binary probit model was used to investigate the determinants of smallholder farmers adopting biofuel crops. The empirical results showed that the variables, such as membership in association, occupation and incentives were statistically significant in influencing farmers’ decision to adopt biofuel crops. Furthermore, it was discovered that the studied areas have a potential to grow biofuel crops.

Clinical retinal image analysis is an import aspect of clinical diagnosis in ophthalmology. Retinopathy of Prematurity (ROP) represents one of the most severe retinal disorders in prematurely born infants. One of the ROP clinical signs is the presence of retinal lesions endangering the vision system. Unfortunately, the stage and progress of these findings is often only subjectively estimated. A procedure such as this is undoubtedly linked to subjective inaccuracies depending on the experience of the ophthalmologist. In our study, a fully autonomous segmentation algorithm to model retinal lesions found using RetCam 3 is proposed. The proposed method used a combination of retinal image preprocessing and active contours for retinal lesion segmentation. Based on this procedure, a binary model of retinal lesions that allowed retinal lesions to be classified from a retinal image background was obtained. Another important aspect of the model was feature extraction. These features reliably and automatically described the development stage of an individual lesion. A complex procedure such as this has significant implications for ophthalmic clinical practice in substituting manual clinical procedures and improving the accuracy of routine clinical decisions. [ABSTRACT FROM AUTHOR]

As the dry bulk shipping market seems to have been stuck in a trough period for a long time, investors need to pay more attention to their investment strategies to survive during this period. This study aimed to find a suitable model to assess dry bulk ship investment decisions in the tough and peak periods based on real options theories. Two options, involving an abandonment option and a deferrable option, were used to define investors' responses to the uncertainty in investment processes such as stopping or selling vessels. The option valuation was solved by using a binomial valuation model, due to data limitations. In accordance with shipping cycle theories, different volatility parameters for the tough and peak periods were calculated using a generalized autoregressive conditional heteroskedasticity (GARCH) model. The application of the real options model to a case study involving secondhand ship trading indicated its viability. According to the results of the case study, the new model has advantages over the traditional net present value (NPV) method in uncertain investment environments. Thus, the results demonstrate that the real options model is a more suitable method for use in the current dry bulk shipping market. [ABSTRACT FROM AUTHOR]

[Objective]The alloinetrie growth equation is the most simple and commonly used method for constructing forest biomass. This study aims to provide an elfective research method for estimating the biomass and carbon storage of alpine forests in Western Sichuan, while optimizing the allometric growth model and vegetation native. The succession process research provides the basis for the study. [Method] Based on the measured biomass of the main tree species in the primary succession of vegetation in the Hailuogou glacial retreat, the total biomass of the trees and the biomass of different components (such as branches, leaves, trunks, roots, etc. ) together with the breast diameter and tree height are easily measured, and the total biomass of each tree species and the allometric growth equation of each component biomass are established. [Result] Binary model with a parameter of tree height (H) is much better than that of the univariate model in estimating the biomass of the concerned tree species. All the three allometric equations are more excellent in estimating the biomass of the aboveground and stem than those of the branches and roots. [Conclusion] The model with D2/H as independent variable is excellent in estimating the biomass of stem as well as the total aboveground part, while the model with D3/H has a better prediction on the biomass of twigs and roots. Nevertheless, the model W = aDb is still applicable in the field in order to facilitate the investigation processes. The results are valuable in promoting studies on the primary vegetation succession, as well as the productivity estimation of subalpine forests in the eastern slope of Tibetan Plateau. [ABSTRACT FROM AUTHOR]

This study addresses the configuration of economies dominated by the tourism industry and investigates whether tourism-led growth applies to them. The results show that small countries tend to base their economy largely on tourism. High tourism industry shared countries are also likely to have low economic openness and established domestic markets. Additionally, economically booming countries are unlikely to be tourism-dominated. In summary, the tourism-led growth hypothesis applies to small countries with established domestic economies and limited economic openness, while it may not apply to developing countries, especially those in the process of an economic boom. [ABSTRACT FROM AUTHOR]

In this paper, the particle size, structure, physical and geometric constitute of Pisha sandstone were studied. The sw-elling mecha nism and collapse process in w-ater of Pisha sandstone were analyzed, and it analyzed the key influence factors on the sw-elling and cementatio] of Pisha sandstone, and the swelling-cementation two binar^^ of Pisha sandstone based on the studies was established. The results show- that th< physics constitute of Pisha sandstone can be divided into three categories, such as coarse particulate matter, cement and filler matter； the effec of swelling of filler matter stronger than cementation is the main reason of Pisha sandstone collapse after immersed in water. In order to contro the collapse of Pisha sandstone, the filler matter sw-ell should be reduced and the cementing properties should be enhanced. Based on the stud ied results of the swelling collapse and inhibit mechanism of Pisha sandstone, the modification scheme of Pisha sandstone was given. [ABSTRACT FROM AUTHOR]

In this paper we propose and realize an algorithm for exact calculation of partition function for planar graph models with binary variables. The complexity of the algorithm is O( N ) Experiments show good agreement with Onsager's analytical solution for the two-dimensional Ising model of infinite size. [ABSTRACT FROM AUTHOR]

This paper focuses on comparison of two different elicitation formats commonly used in the Willingness-to-pay method. It compares the difference in influence of chosen respondents’ characteristics on their willingness to pay for evaluated non-market good applying the take-it-or-leave-it (single-bounded choice) and take-it-it-or-leave-it with follow-up (double-bounded choice) elicitation formats. The good evaluated in the presented article is recreation in nature-based areas. The research is conducted in two primer nature-based recreational areas in the Czech Republic (National Park Sumava, National Park Podyji). The data sources are gathered from a tourist survey carried out in both the studied areas. A logistic regression is used for evaluation of the results. Based on the analysed method, two models are developed. The binary model elaborates the take-it-or-leave-it approach and the ordinal model elaborates the extended approach – take-it-it-or-leave-it with follow-up. The influence of personal and socioeconomic tourists’ characteristics on their willingness to pay is predicted in both models and consequently compared. The predictors analysed include sex, age, education, frequency of visitation of studied areas, and total costs spent during the actual visit.

In biomedical and epidemiological studies, often outcomes obtained are of mixed discrete and continuous in nature. Furthermore, due to some technical inconvenience or else, continuous responses are censored and also a few covariates cease to be observed completely. In this paper, we develop a model to tackle these complex situations. Our methodology is developed in a more general framework and provides a full-scale robust analysis of such complex models. The proposed robust maximum likelihood estimators of the model parameters are resistant to potential outliers in the data. We discuss the asymptotic properties of the robust estimators. To avoid computational difficulties involving irreducibly high-dimensional integrals, we propose a Monte Carlo method based on the Metropolis algorithm for approximating the robust maximum likelihood estimators. We study the empirical properties of these estimators in simulations. We also illustrate the proposed robust method using clustered data on blood sugar content from a clinical trial of individuals who were investigated for diabetes. [ABSTRACT FROM AUTHOR]

Thallium (Tl) is a non-essential element in humans and it is considered to be highly toxic. In this study, the contents, sources, and dispersal of Tl were investigated in surface sediments from a riverine system (the western Pearl River Basin, China), whose catchment has been contaminated by mining and roasting of Tl-bearing pyrite ores. The isotopic composition of Pb and total contents of Tl and other relevant metals (Pb, Zn, Cd, Co, and Ni) were measured in the pyrite ores, mining and roasting wastes, and the river sediments. Widespread contamination of Tl was observed in the sediments across the river, with the highest concentration of Tl (17.3 mg/kg) measured 4 km downstream from the pyrite industrial site. Application of a modified Institute for Reference Materials and Measurement (IRMM) sequential extraction scheme in representative sediments unveiled that 60–90% of Tl and Pb were present in the residual fraction of the sediments. The sediments contained generally lower 206 Pb/ 207 Pb and higher 208 Pb/ 206 Pb ratios compared with the natural Pb isotope signature (1.2008 and 2.0766 for 206 Pb/ 207 Pb and 208 Pb/ 206 Pb, respectively). These results suggested that a significant fraction of non-indigenous Pb could be attributed to the mining and roasting activities of pyrite ores, with low 206 Pb/ 207 Pb (1.1539) and high 208 Pb/ 206 Pb (2.1263). Results also showed that approximately 6–88% of Tl contamination in the sediments originated from the pyrite mining and roasting activities. This study highlights that Pb isotopic compositions could be used for quantitatively fingerprinting the sources of Tl contamination in sediments. [ABSTRACT FROM AUTHOR]

Online propaganda is a mechanism to influence the opinions of social media users. It is a growing menace to public health, democratic institutions, and public society. The present study proposes a propaganda detection framework as a binary classification model based on a news repository. Several feature models are explored to develop a robust model such as part-of-speech, LIWC, word uni-gram, Embeddings from Language Models (ELMo), FastText, word2vec, latent semantic analysis (LSA), and char tri-gram feature models. Moreover, fine-tuning of the BERT is also performed. Three oversampling methods are investigated to handle the imbalance status of the Qprop dataset. SMOTE Edited Nearest Neighbors (ENN) presented the best results. The fine-tuning of BERT revealed that the BERT-320 sequence length is the best model. As a standalone model, the char tri-gram presented superior performance as compared to other features. The robust performance is observed against the combination of char tri-gram + BERT and char tri-gram + word2vec and they outperformed the two state-of-the-art baselines. In contrast to prior approaches, the addition of feature selection further improves the performance and achieved more than 97.60% recall, f1-score, and AUC on the dev and test part of the dataset. The findings of the present study can be used to organize news articles for various public news websites., Competing Interests: The authors declare there are no competing interests., (©2023 Malik et al.)

This paper presents a probabilistic approach to measure the crash risk associated to an urban segment. This approach leads to a hotspot definition and identification using a probabilistic model defining the dependent variable as an indicator of a discrete choice. A binary choice model is used considering a binary dependent variable that differentiates a hotspot from a safe site set by the number of crashes per year per kilometre. The explanatory variables to set similar segments are based on average annual daily traffic, segment length, density of minor intersections. A threshold value for the number of crashes per kilometre is set to distinguish hotspots from safe sites. Based on this classification, a binary model is applied that allows the construction of an ordered site list using the probability of a site being a hotspot. A demonstration of the proposed methodology is provided using urban segment data from Porto, Portugal, covering a five-year period. The results of the binary model show a good fit. To evaluate and compare the probabilistic method with three usual hotspot identification methods described in the Highway Safety Manual, measures are used to test the performance of each method. Depending on the tests, actual data or simulated input, which are usually considered to set the “true” hotspots, were used. In general, the tests results indicate that the binary model performs better than the other three models. Nevertheless, it should be noted that the probabilistic approach provides an outcome that is quite different from the other methods, thus making difficult to ensure a linear comparison with the other methods. Overall, the study shows an alternative to hotspot identification using a risk measure in which the gains are the simplicity, the reliability, and the efficiency of model outcome. [ABSTRACT FROM AUTHOR]

In this article, we model the government expenditure on the welfare change of general public by means of static and dynamic binary response model for panel data. We analyse the effectiveness of the total magnitude and the structure of the Chinese government expenditure on the basis of its effects on the welfare of Chinese citizens. We construct both the static and dynamic models. And we also do a further analysis of the state dependence of the welfare change of Chinese citizens by means of the survival analysis. The estimation results imply that the total amount of the Chinese government expenditure is not oversized but its allocation is not efficient. And expenditures in some fields are not utilized efficiently. [ABSTRACT FROM AUTHOR]

Abstract: Complex mixtures and LtDNA profiles are difficult to interpret. As yet there is no consensus within the forensic biology community as to how these profiles should be interpreted. This paper is a review of some of the current interpretation models, highlighting their weaknesses and strengths. It also discusses what a forensic biologist requires in an interpretation model and if this can be realistically executed under current justice systems. [Copyright &y& Elsevier]