In the (Bi1 − xCex)VO4 (0 ≤ x ≤ 1) system, we found that the (Bi1 − xCex)VO4 (0 ≤ x ≤ 0.1) belongs to the monoclinic scheelite phase and the (Bi1 − xCex)VO4 (0.7 ≤ x ≤ 1) belongs to the tetragonal ...zircon phase, while the (Bi1 − xCex)VO4 (0.1 < x < 0.7) belongs to the mixed phases of both monoclinic scheelite and tetragonal zircon structure. Interestingly, two components with near‐zero temperature coefficient of resonant frequency (TCF) appeared in this system. In our previous work, a near‐zero TCF of ~+15 ppm/°C was obtained in a (Bi0.75Ce0.25)VO4 ceramic with a permittivity (εr) of ~47.9 and a Qf (Q = quality factor = 1/dielectric loss; f = resonant frequency) value of ~18 000 GHz (at 7.6 GHz). Furthermore, in the present work, another temperature‐stable microwave dielectric ceramic was obtained in (Bi0.05Ce0.95)VO4 composition sintered at 950°C and exhibits good microwave dielectric properties with a εr of ~11.9, a Qf of ~22 360 GHz (at 10.6 GHz), and a near‐zero TCF of ~+6.6 ppm/°C. The results indicate that this system might be an interesting candidate for microwave device applications.
Analysis of gene expression data is an attractive topic in the field of bioinformatics, and a typical application is to classify and predict individuals’ diseases or tumors by treating gene ...expression values as predictors. A primary challenge of this study comes from ultrahigh-dimensionality, which makes that (i) many predictors in the dataset might be non-informative, (ii) pairwise dependence structures possibly exist among high-dimensional predictors, yielding the network structure. While many supervised learning methods have been developed, it is expected that the prediction performance would be affected if impacts of ultrahigh-dimensionality were not carefully addressed. In this paper, we propose a new statistical learning algorithm to deal with multi-classification subject to ultrahigh-dimensional gene expressions. In the proposed algorithm, we employ the model-free feature screening method to retain informative gene expression values from ultrahigh-dimensional data, and then construct predictive models with network structures of selected gene expression accommodated. Different from existing supervised learning methods that build predictive models based on entire dataset, our approach is able to identify informative predictors and dependence structures for gene expression. Throughout analysis of a real dataset, we find that the proposed algorithm gives precise classification as well as accurate prediction, and outperforms some commonly used supervised learning methods.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The BiVO
4
material has attracted much attention in recent years due to its active photocatalytic properties under visible light, bright yellow color as a nontoxic pigment, and its high relative ...permittivity (
r
) and
Qf
(quality factor,
Q
× resonant frequency,
f
) as a potential microwave dielectric ceramic. In this review, we introduce the origin, synthesis, crystal structure and phase transitions of the four polymorphic phases of BiVO
4
: orthorhombic (pucherite), zircon (dreyerite), scheelite monoclinic (clinobisvanite) and scheelite tetragonal. We then precis recent studies on doped BiVO
4
ceramics in terms of A site, B site and A/B site complex substitutions. Low sintering temperature (<800 °C) and high
r
values could be obtained in some solid solution ceramics and near zero temperature coefficient of resonant frequency (TCF/
τ
f
) values could be achieved in layered or granulated particle composite ceramics. Besides, a series of temperature stable high
r
microwave dielectric ceramics can also be obtained for many co-fired composite ceramics, such as BiVO
4
-TiO
2
, and BiVO
4
-TiO
2
-Bi
2
Ti
4
O
11
. The high
r
, high
Qf
value, low sintering temperature and chemical compatibility with some base metals suggest that BiVO
4
-based materials are strong candidates for both LTCC and other microwave device applications in current 4G and future 5G technologies.
We precis recent studies on doped BiVO
4
ceramics in terms of A site, B site and A/B site complex substitutions. Low sintering temperature (<800 °C), high
r
and near zero temperature coefficient values could be obtained in solid solution and composite ceramics.
Restoring intestinal flora may improve outcomes in children with acute gastroenteritis. In this multicenter trial, the administration of lactobacillus for 5 days in children with acute ...gastroenteritis was not associated with clinical benefit.
Summary Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder; however, it remains underdiagnosed and undertreated. Although screening tools such as the Berlin questionnaire (BQ), ...STOP-BANG questionnaire (SBQ), STOP questionnaire (STOP), and Epworth sleepiness scale (ESS) are widely used for OSA, the findings regarding their diagnostic accuracy are controversial. Therefore, this meta-analysis investigated and compared the summary sensitivity, specificity, and diagnostic odds ratio (DOR) among the BQ, SBQ, STOP, and ESS according to the severity of OSA. Electronic databases, namely the Embase, PubMed, PsycINFO, ProQuest dissertations and theses A&I databases, and China knowledge resource integrated database, were searched from their inception to July 15, 2016. We included studies examining the sensitivity and specificity of the BQ, SBQ, STOP, and ESS against the apnea–hypopnea index (AHI) or respiratory disturbance index (RDI). The revised quality assessment of diagnostic accuracy studies was used to evaluate the methodological quality of studies. A random-effects bivariate model was used to estimate the summary sensitivity, specificity, and DOR of the tools. We identified 108 studies including a total of 47 989 participants. The summary estimates were calculated for the BQ, SBQ, STOP, and ESS in detecting mild (AHI/RDI ≥ 5 events/h), moderate (AHI/RDI ≥ 15 events/h), and severe OSA (AHI/RDI ≥ 30 events/h). The performance levels of the BQ, SBQ, STOP, and ESS in detecting OSA of various severity levels are outlined as follows: for mild OSA, the pooled sensitivity levels were 76%, 88%, 87%, and 54%; pooled specificity levels were 59%, 42%, 42%, and 65%; and pooled DORs were 4.30, 5.13, 4.85, and 2.18, respectively. For moderate OSA, the pooled sensitivity levels were 77%, 90%, 89%, and 47%; pooled specificity levels were 44%, 36%, 32%, and 621%; and pooled DORs were 2.68, 5.05, 3.71, and 1.45, respectively. For severe OSA, the pooled sensitivity levels were 84%, 93%, 90%, and 58%; pooled specificity levels were 38%, 35%, 28%, and 60%; and pooled DORs were 3.10, 6.51, 3.37, and 2.10, respectively. Therefore, for mild, moderate, and severe OSA, the pooled sensitivity and DOR of the SBQ were significantly higher than those of other screening tools ( P < .05); however, the specificity of the SBQ was lower than that of the ESS ( P < .05). Moreover, age, sex, body mass index, study sample size, study populations, presence of comorbidities, PSG or portable monitoring performance, and risk of bias in the domains of the index test and reference standard were significant moderators of sensitivity and specificity ( P < .05). Compared with the BQ, STOP, and ESS, the SBQ is a more accurate tool for detecting mild, moderate, and severe OSA. Sleep specialists should use the SBQ to conduct patient interviews for the early diagnosis of OSA in clinical settings, particularly in resource-poor countries and sleep clinics where PSG is unavailable.
Ultrahigh-dimensional data analysis has been a popular topic in decades. In the framework of ultrahigh-dimensional setting, feature screening methods are key techniques to retain informative ...covariates and screen out non-informative ones when the dimension of covariates is extremely larger than the sample size. In the presence of incomplete data caused by censoring, several valid methods have also been developed to deal with ultrahigh-dimensional covariates for time-to-event data. However, little approach is available to handle feature screening for survival data subject to biased sample, which is usually induced by left-truncation. In this paper, we extend the C-index estimation proposed by Hartman et al. (2023) to develop a valid feature screening procedure to deal with left-truncated and right-censored survival data subject to ultrahigh-dimensional covariates. The sure screening property is also rigorously established to justify the proposed method. Numerical results also verify the validity of the proposed procedure.
•This manuscript explores ultrahigh-dimensional survival data with biased and incomplete responses.•The C-index approach is applied and is robust regardless of regression models and truncation rates.•The sure screening property is established.•Numerical studies show the satisfactory performance of the method.
Dielectric materials with high power density, fast charge and discharge rates, and high energy-storage density are urgently required due to the rapid development of hybrid vehicles and pulse power ...boosting technology. In this work, the novel environment-friendly (1-x)(Ba0.8Sr0.2)TiO3-xBi(Zn2/3Nb1/3)O3 (0.04 ≤ x ≤ 0.16) (1-x)BST-xBZN ceramics were designed and synthesized by traditional solid-state reaction method, exhibiting ultrahigh energy efficiency and super stability against temperature. The results show that the recoverable energy density (Wrec) and the energy efficiency (η) of the (1-x)BST-xBZN ceramics are increase sharply then decrease slightly with increasing of x value. The 0.88BST-0.12BZN ceramic demonstrated a recoverable energy density of ≈ 1.62 J/cm3 and an extreme high energy efficiency of ∼ 99.8 % at 225 kV/cm at room temperature. These extreme high efficiency and high breakdown strength would make (Ba,Sr)TiO3-based lead-free ceramic systems might be good candidate for high power energy-storage applications pulsed power systems.
Summary
Graphical modelling is an important branch of statistics that has been successfully applied in biology, social science, causal inference and so on. Graphical models illuminate connections ...between many variables and can even describe complex data structures or noisy data. Graphical models have been combined with supervised learning techniques such as regression modelling and classification analysis with multi‐class responses. This paper first reviews some fundamental graphical modelling concepts, focusing on estimation methods and computational algorithms. Several advanced topics are then considered, delving into complex graphical structures and noisy data. Applications in regression and classification are considered throughout.
Microelectronics and electrical power systems require dielectric polymer-based dielectrics with high energy density that are simple to process. However, the currently available polymer-based ...dielectric materials require demanding process conditions and relatively low energy density. Herein, we propose P(VDF-HFP)-based nanocomposite by a simple and practical mechanical method based on a combination of solid phase reaction and sieving to prepare 0.88BaTiO3-0.12Bi(Li0.5Nb0.5)O3 nanoparticles (BT-BLN nps). The experimental and simulation result verify that the BT-BLN nps significantly improve the breakdown strength and energy storage performance of dielectric materials. Remarkably, the highest discharge energy density of the BT-BLN/P(VDF-HFP) nanocomposite film reached 14.2 J/cm3 with the addition of 3 vol% BT-BLN nanofiller at 497 MV/m, which is much higher than that of pure P(VDF- HFP) (Ud ≈ 6.6 J/cm3 and Eb ≈ 391.3 MV/m). Encouragingly, the Young's modulus of BLN-3vol%/P(VDF-HFP) reached 2.6 GPa, which is approximately 2.65 times higher than that of pure P(VDF-HFP) (0.98 GPa). This work established a simple and effective strategy, for solution casting processable dielectrics with performance comparable to that of fillers prepared by the liquid phase method.
Significantly energy storage performance with the discharge energy density (Ud) of 14.2 J/cm3 and energy storage efficiency (η) of 55.5% can be achieved by introducing an improved solid-state reaction method to prepare BT-BLN nanofillers. Display omitted
•BT-BLN nanoparticles were first reported as nanocomposite filler for dielectric energy storage capacitors.•The optical image of the BT-BLN/P(VDF-HFP) nanocomposite film shows high transparency and flexibility.•The highest discharge energy density reached 14.2 J/cm3 with the addition of 3 vol% BT-BLN nanofiller at 497 MV/m.
Recently, dielectric capacitors have attracted much attention due to their high power density based on fast charge–discharge capability. However, their energy storage applications are limited by ...their low discharge energy densities. In this work, we designed novel lead-free relaxor-ferroelectric 0.88BaTiO 3 –0.12Bi(Li 0.5 Nb 0.5 )O 3 (0.88BT–0.12BLN) ceramics with high breakdown strength and high discharge energy density. The 0.88BT–0.12BLN ceramics were prepared by a conventional solid state reaction method. Optimal energy storage properties were obtained in 0.88BT–0.12BLN ceramics sintered at 1220 °C with an impressive discharge energy density of 2.032 J cm −3 and a charge–discharge efficiency of beyond 88% at 270 kV cm −1 . The energy storage properties of the 0.88BT–0.12BLN also displayed good thermal stability from 20 to 120 °C at an electric field of 150 kV cm −1 . Moreover, the discharge speed behavior was investigated by using pulsed current. The pulsed discharge current waveforms showed that all the samples have fast discharge times (less than 0.5 μs) under different electric fields. This work significantly increases the intrinsic breakdown strength and discharge energy density of BaTiO 3 -based materials with high charge–discharge efficiency for high power energy storage devices.
PDF
