Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users

A Power-Efficient Multiband Planar USB Dongle Antenna for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) had been applied in Internet of Things (IoT) and in Industry 4.0. Since a WSN system contains multiple wireless sensor nodes, it is necessary to develop a low-power and multiband wireless communication system that satisfies the specifications of the Federal Communications Commission (FCC) and the Certification European (CE). In a WSN system, many devices are of very small size and can be slipped into a Universal Serial Bus (USB), which is capable of connecting to wireless systems and networks, as well as transferring data. These devices are widely known as USB dongles. This paper develops a planar USB dongle antenna for three frequency bands, namely 2.30–2.69 GHz, 3.40–3.70 GHz, and 5.15–5.85 GHz. This study proposes a novel antenna design that uses four loops to develop the multiband USB dongle. The first and second loops construct the low and intermediate frequency ranges. The third loop resonates the high frequency property, while the fourth loop is used to enhance the bandwidth. The performance and power consumption of the proposed multiband planar USB dongle antenna were significantly improved compared to existing multiband designs

Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology; this research solves the problem that the original cutting technology cannot extract certain single teeth; and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN); which can identify caries and restorations from the bitewing images. Moreover; it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image; which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization; (2) a dental image cropping procedure to obtain individually separated tooth samples; and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks; namely; AlexNet; GoogleNet; Vgg19; and ResNet50; experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%; respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film

Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion

Decomposition and Mineralization of Dimethyl Phthalate in an Aqueous Solution by Wet Oxidation

Dimethyl phthalate (DMP) was treated via wet oxygen oxidation process (WOP). The decomposition efficiency ηDMP of DMP and mineralization efficiency ηTOC of total organic carbons were measured to evaluate the effects of operation parameters on the performance of WOP. The results revealed that reaction temperature T is the most affecting factor, with a higher T offering higher ηDMP and ηTOC as expected. The ηDMP increases as rotating speed increases from 300 to 500 rpm with stirring enhancement of gas liquid mass transfer. However, it exhibits reduction effect at 700 rpm due to purging of dissolved oxygen by overstirring. Regarding the effects of pressure PT, a higher PT provides more oxygen for the forward reaction with DMP, while overhigh PT increases the absorption of gaseous products such as CO2 and decomposes short-chain hydrocarbon fragments back into the solution thus hindering the forward reaction. For the tested PT of 2.41 to 3.45 MPa, the results indicated that 2.41 MPa is appropriate. A longer reaction time of course gives better performance. At 500 rpm, 483 K, 2.41 MPa, and 180 min, the ηDMP and ηTOC are 93 and 36%, respectively

Cytolethal Distending Toxin Enhances Radiosensitivity in Prostate Cancer Cells by Regulating Autophagy

Cytolethal distending toxin (CDT) produced by Campylobacter jejuni contains three subunits: CdtA, CdtB, and CdtC. Among these three toxin subunits, CdtB is the toxic moiety of CDT with DNase I activity, resulting in DNA double-strand breaks (DSB) and, consequently, cell cycle arrest at the G2/M stage and apoptosis. Radiation therapy is an effective modality for the treatment of localized prostate cancer (PCa). However, patients often develop radioresistance. Owing to its particular biochemical properties, we previously employed CdtB as a therapeutic agent for sensitizing radioresistant PCa cells to ionizing radiation (IR). In this study, we further demonstrated that CDT suppresses the IR-induced autophagy pathway in PCa cells by attenuating c-Myc expression and therefore sensitizes PCa cells to radiation. We further showed that CDT prevents the formation of autophagosomes via decreased high-mobility group box 1 (HMGB1) expression and the inhibition of acidic vesicular organelle (AVO) formation, which are associated with enhanced radiosensitivity in PCa cells. The results of this study reveal the detailed mechanism of CDT for the treatment of radioresistant PCa

Extracorporeal Shock Wave Therapy Reverses Ischemia-Related Left Ventricular Dysfunction and Remodeling: Molecular-Cellular and Functional Assessment

An optimal treatment for patients with diffuse obstructive arterial disease unsuitable for catheter-based or surgical intervention is still pending. This study tested the hypothesis that extracorporeal shock wave (ECSW) therapy may be a therapeutic alternative under such clinical situation. Myocardial ischemia was induced in male mini-pigs through applying an ameroid constrictor over mid-left anterior descending artery (LAD). Twelve mini-pigs were equally randomized into group 1 (Constrictor over LAD only) and group 2 (Constrictor over LAD plus ECSW [800 impulses at 0.09 mJ/mm2] once 3 months after the procedure). Results showed that the parameters measured by echocardiography did not differ between two groups on days 0 and 90. However, echocardiography and left ventricular (LV) angiography showed higher LV ejection fraction and lower LV end-systolic dimension and volume in group 2 on day 180 (p<0.035). Besides, mRNA and protein expressions of CXCR4 and SDF-1α were increased in group 2 (p<0.04). Immunofluorescence staining also showed higher number of vWF-, CD31-, SDF-1α-, and CXCR4-positive cells in group 2 (all p<0.04). Moreover, immunohistochemical staining showed notably higher vessel density but lower mean fibrosis area, number of CD40-positive cells and apoptotic nuclei in group 2 (all p<0.045). Mitochondrial protein expression of oxidative stress was lower, whereas cytochrome-C was higher in group 2 (all p<0.03). Furthermore, mRNA expressions of MMP-9, Bax and caspase-3 were lower, whereas Bcl-2, eNOS, VEGF and PGC-1α were higher in group 2 (all p<0.01). In conclusion, ECSW therapy effectively reversed ischemia-elicited LV dysfunction and remodeling through enhancing angiogenesis and attenuating inflammation and oxidative stress

Plastidial Starch Phosphorylase in Sweet Potato Roots Is Proteolytically Modified by Protein-Protein Interaction with the 20S Proteasome

Post-translational regulation plays an important role in cellular metabolism. Earlier studies showed that the activity of plastidial starch phosphorylase (Pho1) may be regulated by proteolytic modification. During the purification of Pho1 from sweet potato roots, we observed an unknown high molecular weight complex (HX) showing Pho1 activity. The two-dimensional gel electrophoresis, mass spectrometry, and reverse immunoprecipitation analyses showed that HX is composed of Pho1 and the 20S proteasome. Incubating sweet potato roots at 45°C triggers a stepwise degradation of Pho1; however, the degradation process can be partially inhibited by specific proteasome inhibitor MG132. The proteolytically modified Pho1 displays a lower binding affinity toward glucose 1-phosphate and a reduced starch-synthesizing activity. This study suggests that the 20S proteasome interacts with Pho1 and is involved in the regulation of the catalytic activity of Pho1 in sweet potato roots under heat stress conditions