Robust kernel regression function with uncertain scale parameter for high dimensional ergodic data using k k -nearest neighbor estimation

In this paper, we consider a new method dealing with the problem of estimating the scoring function $\gamma_a$, with a constant $a$, in functional space and an unknown scale parameter under a nonparametric robust regression model. Based on the $k$ Nearest Neighbors ($k$NN) method, the primary objective is to prove the asymptotic normality aspect in the case of a stationary ergodic process of this estimator. We begin by establishing the almost certain convergence of a conditional distribution estimator. Then, we derive the almost certain convergence (with rate) of the conditional median (scale parameter estimator) and the asymptotic normality of the robust regression function, even when the scale parameter is unknown. Finally, the simulation and real-world data results reveal the consistency and superiority of our theoretical analysis in which the performance of the $k$NN estimator is comparable to that of the well-known kernel estimator, and it outperforms a nonparametric series (spline) estimator when there are irrelevant regressors

Strong consistency rate in functional single index expectile model for spatial data

Analyzing the real impact of spatial dependency in financial time series data is crucial to financial risk management. It has been a challenging issue in the last decade. This is because most financial transactions are performed via the internet and the spatial dependency between different international stock markets is not standard. The present paper investigates functional expectile regression as a spatial financial risk model. Specifically, we construct a nonparametric estimator of this functional model for the functional single index regression (FSIR) structure. The asymptotic properties of this estimator are elaborated over general spatial settings. More precisely, we establish Borel-Cantelli consistency (BCC) of the constructed estimator. The latter is obtained with the precision of the convergence rate. A simulation investigation is performed to show the easy applicability of the constructed estimator in practice. Finally, real data analysis about the financial data (Euro Stoxx-50 index data) is used to illustrate the effectiveness of our methodology

Risk and diagnostic factors and therapy outcome of neonatal early onset sepsis in ICU patients of Saudi Arabia: a systematic review and meta analysis

BackgroundNeonatal early onset sepsis (NEOS) is a serious and potentially life-threatening condition affecting newborns within the first few days of life. While the diagnosis of NEOS was based on clinical signs and symptoms in the past, recent years have seen growing interest in identifying specific diagnostic factors and optimizing therapy outcomes. This study aims to investigate the diagnostic and risk factors and therapy outcomes of neonatal EOS in ICU patients in Saudi Arabia, with the goal of improving the management of neonatal EOS in the country.MethodsThis method outlines the protocol development, search strategy, study selection, and data collection process for a systematic review on neonatal early onset sepsis in Saudi Arabian ICU patients, following the PRISMA 2020 guidelines. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is a well-established guideline that provides a framework for conducting systematic reviews and meta-analyses in a transparent and standardized manner. It aims to improve the quality and reporting of such research by ensuring clear and comprehensive reporting of study methods, results, and interpretations. The search strategy included electronic databases (PubMed, Embase, Google Scholar, Science Direct, and the Cochrane Library) and manual search of relevant studies, and data were extracted using a standardized form.ResultsThe systematic review included 21 studies on neonatal sepsis in Saudi Arabia, with varying study designs, sample sizes, and prevalence rates of sepsis. Group B streptococcus and E. coli were the most commonly isolated pathogens. Various diagnostic factors and risk factors were reported, including hematological parameters, biomarkers, and blood cultures. The quality of the included studies was assessed using the Newcastle-Ottawa Scale and Joanna Briggs Institute critical checklist.ConclusionsThe review identified a number of risk and diagnostic factors and therapy outcomes for neonatal sepsis. However, most of the studies were having small scale cohort groups. Further research with controlled study designs is needed to develop effective prevention and management strategies for neonatal sepsis in Saudi Arabia

Temperature distribution in tumour tissue during targeted destruction by heat: A hyperbolic bioheat equation approach

Thermotherapy is a frequently used treatment to destroy malignant tumour. The procedure is carried-out using various techniques like radio frequency, laser, focused ultrasound, and microwaves to elevate the desired temperature at targeted tissues. However, it becomes indispensable to note that the impact of the high temperatures also expands to the peripherals of the targeted tissues and can harm the surrounding healthy tissue. This paper aims to find the temperature distribution in tumour tissue during the process and draw the corresponding graphical representation. A five-tine trocar has used to raise the temperature at the centre of the targeted tissue as much as to destroy the tumour tissue. A mathematical model based on the hyperbolic bioheat equation has been formulated and solved by variable separable method after converting the devised equation into dimensionless form. The heat waves make a significant contribution in the propagation of heat at high temperatures therefore, this paper can be viewed as an improvement of the models based on parabolic Penne’s bioheat equation. The results are helpful in estimating the temperature distribution on and around the targeted tissue and hence the therapist can be guided to prevent injuries during the treatment of therapeutic treatments

Calibration-Based Mean Estimators under Stratified Median Ranked Set Sampling

Using auxiliary information, the calibration approach modifies the original design weights to enhance the mean estimates. This paper initially proposes two families of estimators based on an adaptation of the estimators presented by recent researchers, and then, it presents a new family of calibration estimators with the set of some calibration constraints under stratified median ranked set sampling (MRSS). The result has also been implemented to the situation of two-stage stratified median ranked set sampling (MRSS). To best of our knowledge, we are presenting for the first time calibration-based mean estimators under stratified MRSS, so the performance evaluation is made between adapted and proposed estimators on behalf of the simulation study with real and artificial datasets. For real-world data or applications, we use information on the body mass index (BMI) of 800 people in Turkey in 2014 as a research variable and age as an auxiliary variable

Asymptotic Normality of Nonparametric Kernel Regression Estimation for Missing at Random Functional Spatial Data

This study investigates the estimation of the regression function using the kernel method in the presence of missing at random responses, assuming spatial dependence, and complete observation of the functional regressor. We construct the asymptotic properties of the established estimator and derive the probability convergence (with rates) as well as the asymptotic normality of the estimator under certain weak conditions. Simulation studies are then presented to examine and show the performance of our proposed estimator. This is followed by examining a real data set to illustrate the suggested estimator’s efficacy and demonstrate its superiority. The results show that the proposed estimator outperforms existing estimators as the number of missing at random data increases

Impact of induced magnetic field on Darcy–Forchheimer nanofluid flows comprising carbon nanotubes with homogeneous-heterogeneous reactions

The appealing traits of carbon nanotubes (CNTs) encompassing mechanical and chemical steadiness, exceptional electrical and thermal conductivities, lightweight, and physiochemical reliability make them desired materials in engineering gadgets. Considering such stimulating characteristics of carbon nanotubes, our goal in the current study is to scrutinize the comparative analysis of Darcy–Forchheimer nanofluid flows containing CNTs of both types of multi and single-wall carbon nanotubes (MWCNTs, SWCNTs) immersed into two different base fluids over a stretched surface. The originality of the model being presented is the implementation of the induced magnetic field that triggers the electric conductivity of carbon nanotubes. Moreover, the envisioned model is also analyzed with homogeneous-heterogeneous (h-h) chemical reactions and heat source/sink. The second-order slip constraint is assumed at the boundary of the surface. The transmuted high-nonlinearity ordinary differential equations (ODEs) are attained from the governing set of equations via similarity transformations. The bvp4c scheme is engaged to get the numerical results. The influence of different parameters is depicted via graphs. For both CNTs, the rate of heat flux and the surface drag coefficient are calculated using tables. It is highlighted that an increase in liquid velocity is witnessed for a varied counts volume fraction of nanoparticles. Also, Single-wall water-based carbon nanotube fluid has comparatively stronger effects on concentration than the multi-walled carbon nanotubes in water-based liquid. The analysis also indicates that the rate of heat flux and the surface drag coefficient are augmented for both SWCNTs and MWCNTs for different physical parameters. The said model is also validated by comparing it with a published result

The accuracy of gypsum casts obtained from the disinfected extended-pour alginate impressions through prolonged storage times

Abstract Background Manufacturers of the extended-pour alginates claimed their dimensional stability through prolonged storage. No data confirmed the ability of these materials to maintain their dimensions and the reproduced oral details following their chemical disinfection. Therefore, this study evaluated the dimensional stability and surface detail reproduction of gypsum casts obtained from disinfected extended-pour alginate impressions through different storage time intervals. Methods Two hundred and forty three hydrocolloid impressions were made from one conventional (Tropicalgin) and two extended-pour (Hydrogum 5 and Chromaprint premium) alginates. These impressions were subjected to none, spray and immersion disinfection before their storage in 100% humidity for 0, 72 and 120 h. The dimensional stability and the surface detail reproduction were indirectly evaluated under low angle illumination on the resulted gypsum casts. At α = 0.05, the parametric dimensional stability data were analyzed using One-Way ANOVA and Tukey’s comparisons, while the nonparametric detail reproduction data were analyzed using KrusKal Wallis and Mann–Whitney's tests. Results All gypsum casts exhibited a degree of expansion; however, the recorded expansion values did not differ between test categories (P > 0.05). Generally, casts obtained from spray-disinfected impressions showed lower detail accuracy (P < 0.05). Immersion-disinfected extended-pour alginates produced casts with better detail accuracy following 120 h of storage (P < 0.05). Conclusion All alginates materials offer comparable cast dimensions under different testing circumstances. Extended-pour alginates offer casts with superior surface details following their immersion disinfection and 120 h of storage. Spray-disinfection using 5.25% sodium hypochlorite affects the surface details of casts obtained from conventional and extended-pour alginates adversely

Physical, Optical, and Mechanical Properties of Ceramic Materials after Coffee Immersion and Evaluation of Cleaning Impact with Different Oral Hygiene Tools

This study aimed to evaluate the effect of three oral hygiene tools, a regular toothbrush, an electronic toothbrush, and mouthwash, on the color stability of three different computer-aided design (CAD) and computer-aided manufactured (CAM) ceramic blocks. Feldspathic ceramic (Vita Triluxe Forte), hybrid resin ceramic (Vita Enamic), and lithium disilicate glass-ceramic (IPS e.max CAD) were used in this study. A CAD/CAM system and 81 (27 of each material) samples of ceramic blocks were used. All samples were immersed in black coffee for 15 days, and the coffee was changed twice per day. Using a spectrophotometer probe, samples on a grey background were scanned, and physical properties like surface hardness and depth were measured using interferometry and a 3D non-contact surface metrology. After 30 days of application of oral hygiene tools, instruments were used to measure various physical, mechanical, and optical properties. Vita Triluxe had the highest average color variation values (&Delta;E00) after 15 and 30 days of immersion in coffee in both regular and electronic toothbrushes. Moreover, IPS e.max CAD had the least &Delta;E00 values with no significant differences among the groups. The surface roughness (Ra) of the Vita Enamic ceramic increased when using a regular toothbrush, and the surface height (Rz) for the Vita Enamic ceramic increased when an electronic toothbrush was used. IPS e.max CAD had the greatest modules of elasticity forces, and Vita Triluxe Forte had the lowest when used with a regular toothbrush. The &Delta;E00 values of the tested materials were minimally increased or decreased after 30 days of cleaning, and all were clinically acceptable. Ra and Rz were the highest for Vita Enamic in comparison to the other groups. The highest percentage in IPS e.max CAD was associated with a type 1 fracture, whereas type 3 was predominantly observed with Vita Enamic, and type 2 in the Vita Triluxe group without significant differences

The Effect of a Digital Manufacturing Technique, Preparation Taper, and Finish Line Design on the Marginal Fit of Temporary Molar Crowns: An In-Vitro Study

The aim of this study is to investigate the combined effect of a digital manufacturing technique (subtractive vs. additive), preparation taper (10° vs. 20° TOC), and finish line (chamfer vs. shoulder) on the marginal adaptation of temporary crowns following cementation with a compatible temporary cement. Four mandibular first molar typodont teeth were prepared for full coverage crowns with standard 4 mm preparation height as follows: 10° TOC with the chamfer finish line, 10° TOC with the shoulder finish line, 20° TOC with the chamfer finish line and 20° TOC with the shoulder finish line. Each of the four preparation designs were subdivided into two subgroups to receive CAD/CAM milled and 3D-printed crowns (n = 10). A total of 80 temporary crowns (40 CAD/CAM milled and 40 3D-printed) were cemented to their respective die using clear temporary recement in the standard cementation technique. The samples were examined under a stereomicroscope at ×100 magnification following calibration. Linear measurements were performed at seven equidistant points on each axial surface and five equidistant points on each proximal surface. One-way ANOVA analysis and Tukey HSD (Honestly Significance Difference) were performed. The best marginal fit was seen in group 8, while the poorest fit was noted in group 2. Shoulder finish lines and 10° TOC resulted in higher marginal gaps, especially in CAD/CAM milled group. The selection of 3D-printed crowns may provide a better marginal fit within the range of clinical acceptability. Marginal gaps were within clinical acceptability (50 and 120 µm) in all groups except group 2