Tag: pubmed

J Phys Chem B. 2022 Oct 24. doi: 10.1021/acs.jpcb.2c04347. Online ahead of print.

ABSTRACT

Nanoconfined fluids exhibit remarkably different thermodynamic behavior compared to the bulk phase. These confinement effects render predictions of thermodynamic quantities of nanoconfined fluids challenging. In particular, confinement creates a spatially varying density profile near the wall that is primarily responsible for adsorption and capillary condensation behavior. Significant fluctuations in thermodynamic quantities, inherent in such nanoscale systems, coupled to strong fluid-wall interactions give rise to this near-wall density profile. Empirical models have been proposed to explain and model these effects, yet no first-principles based formulation has been developed. We present a statistical mechanics framework that embeds such a coupling to describe the effect of the fluid-wall interaction in amplifying the near-wall density behavior for compressible gases at elevated pressures such as pressurized methane in confinement. We show that the proposed theory predicts accurately the adsorbed layer thickness as obtained with small-angle neutron scattering measurements. Furthermore, the predictions of density under confinement from the proposed theory are shown to be in excellent agreement with available experimental and atomistic simulations data for a range of temperatures for nanoconfined methane. While the framework is presented for evaluating the near-wall density, owing to its rigorous foundation in statistical mechanics, the proposed theory can also be generalized for predicting phase-transition and nonequilibrium transport of nanoconfined fluids.

PMID:36279403 | DOI:10.1021/acs.jpcb.2c04347

Environ Sci Technol. 2022 Oct 24. doi: 10.1021/acs.est.2c05872. Online ahead of print.

ABSTRACT

The benchmark dose (BMD) methodology has significantly advanced the practice of dose-response analysis and created substantial opportunities to enhance the plausibility of BMD estimation by synthesizing dose-response information from different sources. Particularly, integrating existing toxicological information via prior distribution in a Bayesian framework is a promising but not well-studied strategy. The study objective is to identify a plausible way to incorporate toxicological information through informative prior to support BMD estimation using dichotomous data. There are four steps in this study: determine appropriate types of distribution for parameters in common dose-response models, estimate the parameters of the determined distributions, investigate the impact of alternative strategies of prior implementation, and derive endpoint-specific priors to examine how prior-eliciting data affect priors and BMD estimates. A plausible distribution was estimated for each parameter in the common dichotomous dose-response models using a general database. Alternative strategies for implementing informative prior have a limited impact on BMD estimation, but using informative prior can significantly reduce uncertainty in BMD estimation. Endpoint-specific informative priors are substantially different from the general one, highlighting the necessity for guidance on prior elicitation. The study developed a practical way to employ informative prior and laid a foundation for advanced Bayesian BMD modeling.

PMID:36279400 | DOI:10.1021/acs.est.2c05872

Vopr Kurortol Fizioter Lech Fiz Kult. 2022;99(5):28-36. doi: 10.17116/kurort20229905128.

ABSTRACT

Secondary focal lesions of the musculoskeletal system that occur with residual brucellosis are characterized by a variety of localizations and simultaneous damage to several groups of joints, a deterioration in the quality of life and a high percentage of disability in people of working age. At present, there are many different schemes for the treatment and rehabilitation of developed residual brucellosis, in which, in addition to the “basic” course, including systemic anti-inflammatory therapy, much attention is paid to physiotherapeutic procedures, but the choice of the most effective treatment tactics remains an unresolved problem.

PURPOSE OF THE STUDY: To determine the effectiveness of the use of options for non-drug methods of treatment in the complex rehabilitation of patients with residual brucellosis with lesions of musculoskeletal system.

MATERIAL AND METHODS: Study included 140 patients treated for osteoarthritis of brucellosis etiology, who were divided into three groups matched by age, gender, average duration and stage of the disease, place of residence. Patients of all groups received standard medical treatment and different sets of physiotherapeutic procedures: in the 1st group (45 patients) – electrophoresis of novocaine on the knee joints, therapeutic massage of the cervical-collar zone; in the 2nd group (45 patients) – magnetotherapy on the area of the knee joints, sinusoidal modulated currents (SMC) on the shoulder joints, decimeter wave therapy of the lumbosacral zone (DMW-therapy); in the 3rd group (50 patients) – magnetic laser therapy on the shoulder, elbow, knee joints, therapeutic massage of the lumbosacral zone. Complaints, clinical symptoms, goniometry results, and blood parameters were assessed: ESR, C-reactive protein, fibrinogen, before the start of treatment, immediately after the course of rehabilitation, and after 6 and 12 months. At the same time, testing was carried out according to the SF-36 Health Status Survey questionnaire to monitor the quality of life.

RESULTS: The applied scheme of drug treatment in combination with magnetic laser therapy and therapeutic massage in the 3rd group made it possible to achieve a significant reduction in arthralgic syndrome, a statistically significant increase in the range of motion in the joints, positive dynamics of laboratory data and an improvement in the psychological state and quality of life of patients compared to other observation groups.

CONCLUSION: The results of the study indicate the high efficiency of magnetic laser therapy in the complex treatment of patients with residual brucellosis with lesions of the musculoskeletal system.

PMID:36279374 | DOI:10.17116/kurort20229905128

IEEE Trans Vis Comput Graph. 2022 Oct 24;PP. doi: 10.1109/TVCG.2022.3216712. Online ahead of print.

ABSTRACT

Image-warping, a per-pixel deformation of one image into another, is an essential component in immersive visual experiences such as virtual reality or augmented reality. The primary issue with image warping is disocclusions, where occluded (and hence unknown) parts of the input image would be required to compose the output image. We introduce a new image warping method, Metameric image inpainting – an approach for hole-filling in real-time with foundations in human visual perception. Our method estimates image feature statistics of disoccluded regions from their neighbours. These statistics are inpainted and used to synthesise visuals in real-time that are less noticeable to study participants, particularly in peripheral vision. Our method offers speed improvements over the standard structured image inpainting methods while improving realism over colour-based inpainting such as push-pull. Hence, our work paves the way towards future applications such as depth image-based rendering, 6-DoF 360 rendering, and remote render-streaming.

PMID:36279345 | DOI:10.1109/TVCG.2022.3216712

IEEE Trans Neural Netw Learn Syst. 2022 Oct 24;PP. doi: 10.1109/TNNLS.2022.3213522. Online ahead of print.

ABSTRACT

Real-world data usually present long-tailed distributions. Training on imbalanced data tends to render neural networks perform well on head classes while much worse on tail classes. The severe sparseness of training instances for the tail classes is the main challenge, which results in biased distribution estimation during training. Plenty of efforts have been devoted to ameliorating the challenge, including data resampling and synthesizing new training instances for tail classes. However, no prior research has exploited the transferable knowledge from head classes to tail classes for calibrating the distribution of tail classes. In this article, we suppose that tail classes can be enriched by similar head classes and propose a novel distribution calibration (DC) approach named as label-aware DC (). transfers the statistics from relevant head classes to infer the distribution of tail classes. Sampling from calibrated distribution further facilitates rebalancing the classifier. Experiments on both image and text long-tailed datasets demonstrate that significantly outperforms existing methods. The visualization also shows that provides a more accurate distribution estimation.

PMID:36279339 | DOI:10.1109/TNNLS.2022.3213522

IEEE Trans Neural Netw Learn Syst. 2022 Oct 24;PP. doi: 10.1109/TNNLS.2022.3213518. Online ahead of print.

ABSTRACT

The finite inverted beta mixture model (IBMM) has been proven to be efficient in modeling positive vectors. Under the traditional variational inference framework, the critical challenge in Bayesian estimation of the IBMM is that the computational cost of performing inference with large datasets is prohibitively expensive, which often limits the use of Bayesian approaches to small datasets. An efficient alternative provided by the recently proposed stochastic variational inference (SVI) framework allows for efficient inference on large datasets. Nevertheless, when using the SVI framework to address the non-Gaussian statistical models, the evidence lower bound (ELBO) cannot be explicitly calculated due to the intractable moment computation. Therefore, the algorithm under the SVI framework cannot directly use stochastic optimization to optimize the ELBO, and an analytically tractable solution cannot be derived. To address this problem, we propose an extended version of the SVI framework with more flexibility, namely, the extended SVI (ESVI) framework. This framework can be used in many non-Gaussian statistical models. First, some approximation strategies are applied to further lower the ELBO to avoid intractable moment calculations. Then, stochastic optimization with noisy natural gradients is used to optimize the lower bound. The excellent performance and effectiveness of the proposed method are verified in real data evaluation.

PMID:36279334 | DOI:10.1109/TNNLS.2022.3213518

IEEE Trans Neural Netw Learn Syst. 2022 Oct 24;PP. doi: 10.1109/TNNLS.2022.3213589. Online ahead of print.

ABSTRACT

Multimodal data provide complementary information of a natural phenomenon by integrating data from various domains with very different statistical properties. Capturing the intramodality and cross-modality information of multimodal data is the essential capability of multimodal learning methods. The geometry-aware data analysis approaches provide these capabilities by implicitly representing data in various modalities based on their geometric underlying structures. Also, in many applications, data are explicitly defined on an intrinsic geometric structure. Generalizing deep learning methods to the non-Euclidean domains is an emerging research field, which has recently been investigated in many studies. Most of those popular methods are developed for unimodal data. In this article, a multimodal graph wavelet convolutional network (M-GWCN) is proposed as an end-to-end network. M-GWCN simultaneously finds intramodality representation by applying the multiscale graph wavelet transform to provide helpful localization properties in the graph domain of each modality and cross-modality representation by learning permutations that encode correlations among various modalities. M-GWCN is not limited to either the homogeneous modalities with the same number of data or any prior knowledge indicating correspondences between modalities. Several semisupervised node classification experiments have been conducted on three popular unimodal explicit graph-based datasets and five multimodal implicit ones. The experimental results indicate the superiority and effectiveness of the proposed methods compared with both spectral graph domain convolutional neural networks and state-of-the-art multimodal methods.

PMID:36279325 | DOI:10.1109/TNNLS.2022.3213589

Oper Dent. 2022 Oct 21. doi: 10.2341/21-148-L. Online ahead of print.

ABSTRACT

STATEMENT OF PROBLEM: Advertisements of glass-ionomer-containing restorative materials recommend suitability as load-bearing permanent or semi-permanent restorations. Historically, unacceptably high wear rates limit clinical indications of glass-ionomer-containing restorations in this regard.

OBJECTIVE: To compare the in vitro wear of contemporary glass-ionomer-containing dental materials commercially advertised for use in permanent dentition as load-bearing restorations in a chewing simulator. Resin composite was tested as a control.

METHODS AND MATERIALS: A resin-modified glass ionomer (Ionolux, VOCO gmbH), a high viscosity glass-ionomer hybrid system (Equia Forte HT with Equia Coat, GC America), and a bioactive ionic resin with reactive glass filler (Activa Bioactive Restorative, Pulpdent) were evaluated. Filtek Supreme Ultra (3M ESPE) is a visible light-activated resin composite that served as a control. Standardized flat disk-shaped specimens (n=12/group) were submitted to 500,000 cycles with continuous thermal cycling against steatite antagonists. Volumetric wear was measured at 1000, 10,000, 200,000, and 500,000 cycles.

RESULTS: There was a statistically significant difference in mean volumetric wear for Activa Bioactive Restorative (p=0.0081, 95% CI: 0.3973, 0.4982) and Equia Forte HT (p<0.001, 95% CI: 1.2495, 1.8493), but no statistically significant difference in mean volumetric wear for Ionolux (p=0.6653) compared to control. Activa Bioactive Restorative wore approximately 60% less than, and Equia Forte HT twice more than Filtek Supreme Ultra on average, respectively.

CONCLUSIONS: Compared to a resin composite, contemporary glass-ionomer-containing restorative materials advertised for use as load-bearing restorations display measurably variable in vitro wear rates.

PMID:36279318 | DOI:10.2341/21-148-L

Dermatol Ther. 2022 Oct 24:e15958. doi: 10.1111/dth.15958. Online ahead of print.

ABSTRACT

BACKGROUND: Secukinumab demonstrated high efficacy and favorable safety profile in patients with moderate-to-severe plaque psoriasis (PsO) in clinical trials. However, understanding of patient characteristics and clinical outcomes in real world in Thailand is still limited.

AIMS: To describe patient characteristics, effectiveness and safety of secukinumab in Thai PsO patients.

METHODS: This retrospective study analyzed data from medical records of adult PsO patients who initiated secukinumab at 7 dermatology centers from September 2017 to April 2021. Study outcomes included patient characteristics and changes in Psoriasis Area and Severity Index (PASI) score from baseline at weeks 4 and 16 after secukinumab initiation. Adverse events were recorded. Subgroup analyses by adherence rate and completeness of loading dose were performed.

RESULTS: Of 163 patients, the mean (SD) age was 44.0 (14.0) years. Most patients (84.7%) were previously treated with topical therapy while 62.0% and 21.5% of patients had received systemic and biologic therapy, respectively. The mean baseline PASI score was 15.4 (9.3). Overall, the mean PASI score improved by 58.0% at week 4 and 78.4% at week 16. Statistically significant differences in PASI approvement were revealed among subgroups of patients with different loading dose and adherence rate. Adverse effects were reported in 8.0% of patients.

CONCLUSION: The characteristics of patients in this study were slightly different from clinical trials in terms of demographic and clinical characteristics, as well as PsO treatment. Secukinumab was effective and safe in Thai patients with PsO, especially among those with complete loading dose and a higher adherence rate. This article is protected by copyright. All rights reserved.

PMID:36279306 | DOI:10.1111/dth.15958

PLoS One. 2022 Oct 24;17(10):e0276514. doi: 10.1371/journal.pone.0276514. eCollection 2022.

ABSTRACT

Ranked set sampling (RSS) has created a broad interest among researchers and it is still a unique research topic. It has at long last begun to find its way into practical applications beyond its initial horticultural based birth in the fundamental paper by McIntyre in the nineteenth century. One of the extensions of RSS is median ranked set sampling (MRSS). MRSS is a sampling procedure normally utilized when measuring the variable of interest is troublesome or expensive, whereas it might be easy to rank the units using an inexpensive sorting criterion. Several researchers introduced ratio, regression, exponential, and difference type estimators for mean estimation under the MRSS design. In this paper, we propose three new mean estimators under the MRSS scheme. Our idea is based on three-fold utilization of supplementary information. Specifically, we utilize the ranks and second raw moments of the supplementary information and the original values of the supplementary variable. The appropriateness of the proposed group of estimators is demonstrated in light of both real and artificial data sets based on the Monte-Carlo simulation. Additionally, the performance comparison is also conducted regarding the reviewed families of estimators. The results are empowered and the predominant execution of the proposed group of estimators is seen throughout the paper.

PMID:36279286 | DOI:10.1371/journal.pone.0276514