Three-stage Procedure Research Articles

Stochastic dominance rankings of consumption expenditure amongst arable crop farming households in Delta State, Nigeria

Finessing the question on household settlement choice is to enquire the income/consumption expenditure distribution that either makes her better-off or worse-off. Using 430 household-level micro-data from a three-stage sampling procedure, the study ranked consumption expenditure by household attributes in Delta state, Nigeria on axiomatic poverty measure. Results showed that household heads in the widowed and 0<𝑎𝑔𝑒≤20 years categories in Delta-North first-order stochastically dominated Delta-South (𝑁≻𝑠=1𝑆), 20<𝑎𝑔𝑒≤40 years household heads in 𝑆≻𝑠=1𝐶 and 𝑁≻𝑠=1𝐶, household heads in the widowed, vocational education holder and 0<𝑎𝑔𝑒≤20 years, 20<𝑎𝑔𝑒≤40 years and 𝑎𝑔𝑒>60 years categories in 𝑁≻𝑠=1𝐶, while household heads in the vocational education holder, 0<𝑎𝑔𝑒≤20 years, 20<𝑎𝑔𝑒≤40 years and 𝑎𝑔𝑒>60 years categories in 𝑆≻𝑠=1𝐶. Household heads in the female, single, medium household-size, tertiary education holder and 0<𝑎𝑔𝑒≤20 years categories in 𝑁≻𝑠=2𝑆 and 𝑁≻𝑠=3𝑆. Household heads in the single, medium-size, 20<𝑎𝑔𝑒≤40 years and tertiary education holder categories in 𝑁≻𝑠=2𝐶 and 𝑁≻𝑠=3𝐶. Household heads in the separated spouse and small household-size categories in 𝐶≻𝑠=2𝑁 and 𝐶≻𝑠=3𝑁 while household heads that are in the single category in 𝐶≻𝑠=2𝑆 and 𝐶≻𝑠=3𝑆. There is, generally, no stochastic dominance between pairwise comparisons by district in the state, in terms of consumption expenditure, except by other household attributes.

Parameter sensitivity analysis of a reduced-order electrochemical-thermal model for heat generation rate of lithium-ion batteries

A reduced-order electrochemical-thermal model is capable of accurately estimating heat generation rate of lithium-ion batteries with high accuracy. However, as the number of parameters drastically increases, an identification of the parameters becomes essential but challenging. In this paper, a sensitivity analysis of its physical parameters is conducted to study the influence of the parameters on the heat generation rate for the first time. First, 23 potential parameters are selected, where the ranges of the parameters are assumed based on the literature. The parameters are then varied, and the corresponding heat generation rate is calculated to quantify their effects. The analysis has shown various tendencies of the sensitivity of the parameters, and their behavior is explained from further analysis. Based on their sensitivities, the parameters are clustered into three groups dependent upon dominant ranges of state of charge, where insensitive parameters are excluded. Finally, the parameters in each group are identified in their dominant ranges of the state of charge separately based on a three-stage identification procedure. For the identification, the genetic algorithm is used, where the objective function is to minimize the model error for the battery temperature. The results of the identification have shown that the parameters are converged within an optimal solution. The model with the identified parameters is further validated against the experimental data using a pouch type large format lithium-manganese-cobalt-oxide/ Graphite cell at constant charge and discharge profiles over the full range of the state of charge and driving cycles, which has shown a good agreement.

Econometric Analysis of Dairy Farmer’s Access to Agricultural Information in Ada’A District

This study set out to analyze the determinants of Dairy Farmer’s access to agricultural information in Ada’a District, East Shoa Zone, Central Ethiopia. A three-stage sampling procedure was employed in which both non-probability sampling for the study area and probability sampling procedures were followed to select the three kebele and 136 respondents. The binary logit model analysis result revealed that sex, education level, social participation, extension contact, credit access, and innovation proneness have significant and positive influence on access to Agricultural information, where as age of household head has significant negative influence on Dairy farmer’s access to Agricultural information at different significant levels. Therefore , focus ought to be given regarding Gender difference; improving literacy rate, increasing extension worker and creating strong linkage with financial organizations to foster provision of credit service for farmer are strongly recommended to enhance agricultural Development through increasing provision of agricultural information. Keywords : access, Agricultural information, Dairy farmer, Binary logit DOI: 10.7176/JESD/12-19-02 Publication date: October 31 st 2021

3D Behaviour of Buildings due to Tunnel Induced Ground Movement

Ground subsidence from tunnel excavation below existing buildings may result in building distortion and develop structural damage. Previous case histories have shown that buildings may deform three-dimensionally when the tunnel alignment is orientated to the building facade. The authors incorporated a three-dimensional distortion parameter called twist into damage assessment by extending the current beam model to three dimensions. In this study, the new method is reviewed, and the concepts of the local and global twists are discussed. Results of a 3D Finite Element (FE) parametric study of global and local twist deformations of buildings due to tunnel-induced ground movement are compared in temporary and permanent cases during and after the construction of the tunnel. To investigate the behaviour of a twisted building, varying building stiffness, building geometry, and orientation angle are considered in the analyses. Comparison of the global and local twist shows that the global twist is not always the maximum twist during or after excavation of the tunnel. However, because of the temporary nature of the local twist, the global twist is still considered more critical than the local twist in terms of damage to the building. A new modification factor for the twist for different building stiffness factor is being proposed in the form of design graph. The design graph is included in the current three-stage procedure for assessing potential building damage. The modified procedure is used to predict the performance of a case study building affected by tunnel construction.

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach.

Globally, arthropod-borne virus (arbovirus) infections continue to pose substantial threats to public health and economic development, especially in developing countries. In Kenya, although arboviral diseases (ADs) are largely endemic, little is known about the factors influencing livestock farmers' knowledge, beliefs, and management (KBM) of the three major ADs: Rift Valley fever (RVF), dengue fever and chikungunya fever. This study evaluates the drivers of livestock farmers' KBM of ADs from a sample of 629 respondents selected using a three-stage sampling procedure in Kenya's three hotspot counties of Baringo, Kwale, and Kilifi. A multivariate fractional probit model was used to assess the factors influencing the intensity of KBM. Only a quarter of the farmers had any knowledge of ADs while over four-fifths of them could not manage any of the three diseases. Access to information (experience and awareness), income, education, religion, and distance to a health facility considerably influenced the intensity of farmers' KBM of ADs in Kenya. Thus, initiatives geared towards improving access to information through massive awareness campaigns are necessary to mitigate behavioral barriers in ADs management among rural communities in Kenya.

THỰC TRẠNG VÀ ĐỀ XUẤT QUY TRÌNH SỬ DỤNG VIDEO LÀM MẪU GIÁO DỤC KĨ NĂNG KẾT BẠN CHO THIẾU NIÊN RỐI LOẠN PHỔ TỰ KỈ

Using videos as a model in the process of educating how to make friends for adolescents with autism spectrum disorders has a number of benefits: assist them in recognizing the processes necessary to put skills into practice, generalize, and improve their ability to apply skills in real-life situations. In order to generalize the current state of knowledge of teachers and parents about the level of necessity, meaning, steps to use, advantages, and challenges in the process of using video as a model for adolescents with ASD, the paper conducts a survey on 125 teachers and 101 parents. On this foundation, a three-stage procedure for using video as a model is proposed: (1) Stage 1: Getting ready to watch video; (2) Stage 2: Using video; (3) Stage 3: Wrapping up and practicing. For the most effective education process of life skills education for adolescents with ASD, it is vital to have synchronous coordination between forces and to build technological basis.

Methodology for Digital Transformation with Internet of Things and Cloud Computing: A Practical Guideline for Innovation in Small- and Medium-Sized Enterprises.

Researches on the Internet of Things (IoT) and cloud computing have been pervasive in both the academic and industrial world. IoT and cloud computing are seen as cornerstones to digital transformation in the industry. However, restricted by limited resources and the lack of expertise in information and communication technologies, small- and medium-sized enterprises (SMEs) have difficulty in achieving digitalization of their business. In this paper, we propose a reference framework for SMEs to follow as a guideline in the journey of digital transformation. The framework features a three-stage procedure that covers business, technology, and innovation, which can be iterated to drive product and business development. A case study about digital transformation taking place in the vertical plant wall industry is detailed. Furthermore, some solution design principles that are concluded from real industrial practice are presented. This paper reviews the digital transformation practice in the vertical plant wall industry and aims to accelerate the pace of SMEs in the journey of digital transformation.

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggregated bids parameters used in linear programming constraints and incorporating them into the auction model is another contributing factor of this paper, allowing the scheduling of storage-based participants economically. The proposed methodology has been verified on a recently published case study of a real-world bus service operated on the Ohio State University campus. We show that the auction-based charging of all 22 buses outperforms as-soon-as-possible schedules by 7% to even 28% of daily cost savings. Thanks to the aggregated bids, buses can flexibly shift charges between high- and low-price periods while preserving constraints of the charging equipment and timetables.

Investigation of anomalous hydrogen evolution from anodized magnesium using a polarization routine for scanning electrochemical microscopy

• SECM investigation of anomalous hydrogen evolution on 99.9% Mg and AZ63 alloy. • Three-stage anodization procedure for the monitoring the rates of hydrogen evolution reaction (HER) • Separation of the effects of noble impurities from the reactivity of the oxy-hydroxide layer on Mg. • Enhanced H 2 evolution by facilitating the formation of the oxy-hydroxide layer on either pure Mg and AZ63 alloy. • Greater H 2 evolution on pre-polarized surfaces compared to the non-polarized ones. With the goal to facilitate a new experimental procedure for the monitoring of anomalous hydrogen evolution from anodically-polarized magnesium-based materials, this paper presents the application of the three-step (off-on-off) anodization operation sequence for amperometric scanning electrochemical microscopy (SECM) recently proposed by our group to the characterization of 99.9% magnesium in aqueous saline solution. The SECM measurements done above prepolarized and nonpolarized magnesium provided new information on the hydrogen evolution reaction (HER) on this metal, whereas other experiments are presented that enable to monitor the effect of the oxy-hydroxide layer formed on the metal under anodic polarization. In addition, direct comparison of the data obtained for 99.9% magnesium with those previously obtained for AZ63 magnesium alloy contributed to separate the effect of noble impurities from the catalytic effect of the oxy-hydroxide layer formed on magnesium for the hydrogen-evolution reaction.

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer.

Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC). Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options. Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy. Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

Weighted functional linear Cox regression model.

The aim of this paper is to develop a weighted functional linear Cox regression model that accounts for the association between a failure time and a set of functional and scalar covariates. We formulate the weighted functional linear Cox regression by incorporating a comprehensive three-stage estimation procedure as a unified methodology. Specifically, the weighted functional linear Cox regression uses a functional principal component analysis to represent the functional covariates and a high-dimensional Cox regression model to capture the joint effects of both scalar and functional covariates on the failure time data. Then, we consider an uncensored probability for each subject by estimating the important parameter of a censoring distribution. Finally, we use such a weight to construct the pseudo-likelihood function and maximize it to acquire an estimator. We also show our estimation and testing procedures through simulations and an analysis of real data from the Alzheimer's Disease Neuroimaging Initiative.

Effects of various treatment procedures and pulse power modes on the photoelectric efficiency of Ti-PEO photocatalysts

In this study, various treatment methods were developed to achieve suitable structural phase control for the oxide layer of Ti plasma electrolytic oxidation (PEO) photocatalysts to improve their photoelectric conversion efficiency. To achieve the aforementioned purpose and to increase the doping efficiency, a three-stage PEO manufacturing procedure was developed and applied. In the first stage, the porous morphology and specific structural phases of a pretreated layer were controlled for doping preparation. In the second stage, doping elements were added into the surface and pores of the pretreated layer using the impregnation method. Finally, in the third stage, PEO was performed with different control parameters. The treatment factors in this study were the amount of manganese ion impregnation; the porosity, pore diameter, crystal structure, and carrier used in the treatment process; and the applied power mode. The effects of structural phase control, the Mn+ impregnation concentration, and the applied power modes on the carrier concentration were studied. The results indicated that the designed treatment method can effectively control the characteristics of oxide layers. By applying the impregnation method, the doping amount of Mn+ was increased more than five-fold compared with that in the single-step PEO treatment. Furthermore, to understand the treatment mechanism, the absorption spectrum, doping efficiency, Mn+ distribution, and mass transfer mechanism (of anions and cations) were investigated under direct, pulsed unipolar, and pulsed bipolar current. Finally, the functioning of the manufactured Mn: TiO2 (PEO) photocatalyst was verified with toluene under ultraviolet A, blue, and white LED light.

P1123 - Suprapubic phalloplasty in transmen: Surgical results and critical review

This article presents the surgical outcomes of a consecutive series of 71 transmen undergoing pre-expanded suprapubic phalloplasty (SPP) in a specialized center. The median [IQR] duration to finalize this three-stage phalloplasty procedure was 7 months [6–7]. Median [IQR] follow-up was 39.4 months [19.7–81.2]. Among those included, 25 (35.2%) had a urethroplasty, and 40 (56.3%) a penile prosthesis as additional procedures. Complications were the result of disorders of wound healing (dehiscence, infection, partial necrosis) or tissue expander (migration, infection). Sixty patients (84.5%) experienced at least one complication during the phalloplasty procedure, mostly minor complications Clavien < IIIa (81.8%). Among these, 16 (22.5%) underwent at least one reintervention, 2 of whom underwent two reinterventions (18 reinterventions in total for Clavien ≥ IIIa complication). There was no loss of phalloplasty. Among the wide variety of techniques developed for phalloplasty, the suprapubic technique seems to be a valuable option for transmen on the path to genital gender affirming surgery.

Mathematical modelling of the CHP plant-10 power unit No 5 of “Baikal Energy Company” LLC to assess the efficiency of its modernisation

The work aims to study the effect of changes in the drain scheme of the low-pressure regeneration on the energy and economic efficiency of the CHP plant-10 power unit No 5 of “Baikal Energy Company” LLC. In this study, we used a mathematical model of the power unit adjusted to the measurements results. The mathematical modelling of the power unit was performed using the “Computer-assisted programming system” application package. The created matematical model of the heat and power plant was tailored to the current state of the study object according to the three-stage identification procedure of the mathematical model parameters. We proposed a cycle arrangement under which three streams of the low-pressure drainages were redirected to the pump suction of the low-pressure heater. The improved mathematical model of the power unit allows the calculation of the parameters of both the existing and proposed cycle arrangements. According to the calculations, the temperature difference between the main condensate after the low-pressure heater 1 and the investigated drains after mixing is minimal and amounts to 3.2 °C. The suggested modernisation increases the energy efficiency of the power unit by 0.007% under the nominal operating conditions of the existing and proposed thermal circuit. In addition, the specific standard fuel consumption for electric generation is reduced by 0.052 g.s.s.f./kWh. The operating costs to implement the proposed engineering solutions amounted to 34,191 roubles. Considering the annual power plant extensive consumption factor, the payback period of the proposed modernisation will be 5.5 months. The savings for the first operation year are estimated at 18,423 roubles, based on the rate of return and depreciation expenses. The proposed approach combines mathematical modelling of operating power plants with a technique of increasing the efficiency of technical decision-making. The proposed versatile approach can be used for the modernisation of CHPs and other plants.

Determinants of Rural Women’s Adaptation Measures to Climate Change in Yeki Woreda, Sheka Zone of South Western Ethiopia

Climate change is a global challenge that burdens all of humanity. However, the world’s poor, the majority of whom are women, are encumbered disproportionately. Adaptation is, therefore, considered as an important response, especially for those groups who are most exposed to and affected by its adverse effect. Hence, this study assessed the determinants of women’s choices of adaptation strategies to climate change in Yeki Woreda, Sheka Zone of South Western Ethiopia using a multinomial logit model. A three-stage sampling procedure was followed in selecting 150 women farmers from three kebeles. The result revealed that productive labor force, farm size, farming experience, wealth status, access to climate information, credit service usage and extension visit were found to influence women’s choice of adaptation strategies positively and significantly (P ≤ 10%). Therefore, development interventions, policies and supportive services should be designed at a different level to ensure effective access to climate information and affordable credit schemes for women households to enable them to plan and adapt in the face of the changing climate. Keywords : Adaptation strategy, Climate change, MNL, Women, Yeki DOI: 10.7176/JAAS/72-01 Publication date: May 31 st 2021

Composite quantile regression for ultra-high dimensional semiparametric model averaging

To estimate the joint multivariate regression function, a robust ultra-high dimensional semiparametric model averaging approach is developed. Specifically, a three-stage estimation procedure is proposed. In the first step, the joint multivariate function can be approximated by a weighted average of one-dimensional marginal regression functions which can be estimated robustly by the composite quantile marginal regression. In the second step, a nonparametric composite quantile correlation screening technique is proposed to robustly choose relative important regressors whose marginal regression functions have significant effects on estimating the joint regression function. In the third step, based on these significant regressors that survive the screening procedure, a penalized composite quantile model averaging marginal regression is considered to further achieve sparse model weights and estimate the joint regression function. The sure independence screening property of the proposed screening procedure and sparse property of the penalized estimator are established under some regularity conditions. Numerical studies including both extensive simulation studies and an empirical application are considered to verify the merits of our proposed approach.

Estimation of the association parameters in hierarchically clustered survival data by nested Archimedean copula functions

Statisticians are frequently confronted with highly complex data such as clustered data, missing data or censored data. In this manuscript, we consider hierarchically clustered survival data. This type of data arises when a sample consists of clusters, and each cluster has several, correlated sub-clusters containing various, dependent survival times. Two approaches are commonly used to analysis such data and estimate the association between the survival times within a cluster and/or sub-cluster. The first approach is by using random effects in a frailty model while a second approach is by using copula models. Hereby we assume that the joint survival function is described by a copula function evaluated in the marginal survival functions of the different individuals within a cluster. In this manuscript, we introduce a copula model based on a nested Archimedean copula function for hierarchical survival data, where both the clusters and sub-clusters are allowed to be moderate to large and varying in size. We investigate one-stage, two-stage and three-stage parametric estimation procedures for the association parameters in this model. In a simulation study we check the finite sample properties of these estimators. Furthermore we illustrate the methods on a real life data-set on Chronic Granulomatous Disease.

Suprapubic phalloplasty in transmen: surgical results and critical review.

This article presents the surgical outcomes of a consecutive series of 71 transmen undergoing pre-expanded suprapubic phalloplasty (SPP) in a specialized center. The median [IQR] duration to finalize this three-stage phalloplasty procedure was 7 months [6-7]. Median [IQR] follow-up was 39.4 months [19.7-81.2]. Among those included, 25 (35.2%) had a urethroplasty, and 40 (56.3%) a penile prosthesis as additional procedures. Complications were the result of disorders of wound healing (dehiscence, infection, partial necrosis) or tissue expander (migration, infection). Sixty patients (84.5%) experienced at least one complication during the phalloplasty procedure, mostly minor complications Clavien < IIIa (81.8%). Among these, 16 (22.5%) underwent at least one reintervention, 2 of whom underwent two reinterventions (18 reinterventions in total for Clavien ≥ IIIa complication). There was no loss of phalloplasty. Among the wide variety of techniques developed for phalloplasty, the suprapubic technique seems to be a valuable option for transmen on the path to genital gender affirming surgery.

Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces

Popularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite potential benefits, a practical obstacle hindering widespread metasurface utilization is the lack of systematic design procedures. Conventional approaches are largely intuition-inspired and demand heavy designer's interaction while exploring the parameter space and pursuing optimum unit cell geometries. Not surprisingly, these are unable to identify truly optimum solutions. In this article, we introduce a novel machine-learning-based framework for automated and computationally efficient design of metasurfaces realizing broadband RCS reduction. Our methodology is a three-stage procedure that involves global surrogate-assisted optimization of the unit cells, followed by their local refinement. The last stage is direct EM-driven maximization of the RCS reduction bandwidth, facilitated by appropriate formulation of the objective function involving regularization terms. The appealing feature of the proposed framework is that it optimizes the RCS reduction bandwidth directly at the level of the entire metasurface as opposed to merely optimizing unit cell geometries. Computational feasibility of the optimization process, especially its last stage, is ensured by high-quality initial designs rendered during the first two stages. To corroborate the utility of our procedure, it has been applied to several metasurface designs reported in the literature, leading to the RCS reduction bandwidth improvement by 15%-25% when compared with the original designs. Furthermore, it was used to design a novel metasurface featuring over 100% of relative bandwidth. Although the procedure has been used in the context of RCS design, it can be generalized to handle metasurface development for other application areas.

Measuring cost inefficiency: A dual approach

Total cost inefficiency comprises technical inefficiency and allocative inefficiency. Measuring cost inefficiency with these two components has been challenging both theoretically and empirically. Current literature has provided some solutions. However, these solutions are restricted to specific functions and their empirical estimations are complicated to implement, which lead to limited applications. Using the duality between production and cost functions, this paper proposes a new approach that is simple for estimation and applicable to general cases. Firstly, we define two types of allocative inefficiency and derive their input cost share inequalities. Secondly, a three-stage procedure is developed to estimate total cost inefficiency and its two components. Finally, an empirical presentation based on the existing data supplements the theory. Our results show that this solution can identify the inefficiency for each input and derive robust estimates of economies of scale, which are important for both policy implications and managerial decisions.