A Novel Sep-Unet Architecture of Convolutional Neural Networks to Improve Dermoscopic Image Segmentation by Training Parameters Reduction

Nowadays, we use dermoscopic images as one of the imaging methods in diagnosis of skin lesions such as skin cancer. But due to the noise and other problems, including hair artifacts around the lesion, this issue requires automatic and reliable segmentation methods. The diversity in the color and structure of the skin lesions is a challenging reason for automatic skin lesion segmentation. In this study, we used convolutional neural networks (CNN) as an efficient method for dermoscopic image segmentation. The main goal of this research is to recommend a novel architecture of deep neural networks for the injured lesion in dermoscopic images which has been improved by the convolutional layers based on the separable layers. By convolutional layers and the specific operations on the kernel of them, the velocity of the algorithm increases and the training parameters decrease. Additionally, we used a suitable preprocessing method to enter the images into the neural network. Suitable structure of the convolutional layers, separable convolutional layers and transposed convolution in the down sampling and up sampling parts, have made the structure of the mentioned neural network. This algorithm is named Sep-unet and could segment the images with 98% dice coefficient

An Examination of Family Physicians Plan Implementation in Rural Areas from Perspectives of Managers, Personnel and Clients in Context of Health System: Strengths and Weaknesses

Background: Family physician plan (FPP) and referral system (RS) is one of the major plans in Iran’s health system with the aim of increasing the accountability in the health market, enhancing the public’s access to the health services, lowering the unnecessary costs and equitable distribution of health across the society. Aim: Taking these into consideration, this study assessed the strengths and weaknesses of the Family Physician Plan in the Iranian villages based on the perspectives of the family physicians, managers, employees and clients in the health system in 2014. Subjects and Methods: A descriptive-applied and cross-sectional design was used for this study. Its statistical population consisted of two groups: the first group included all the family physicians and the managers, employees practicing in the health system of Borujen town (n=62 subjects) who, using 2-round consensus Delphi technique, were asked what are 4 main strengths and 4 weaknesses of the Family Physician Plan implemented during the past few years. This was done using an open questionnaire. The second group included village households and clients. The size of the second group was 400 heads of the households. Similarly, using SERVQUAL questionnaire, their ideas regarding 4 strengths and 4 weaknesses observed for the Family Physician Plan were asked. Subsequently, their given responses were compared and similar ideas were merged into one and for prioritization, the second questionnaire was prepared. But, it was just given to the employees. The responses to the questionnaire were ranked according to Likert scale. Finally, the collected data were put into SPSS software 13 to be analyzed. Results: As the results indicated, among the strengths reported in the implementation of the Family Physician Plan by the respondents the following ones had the highest frequency: the timely follow-up care of the patients with mental disorders, blood pressure (hypertension) and diabetes (55.4%), permanent caring for the patients from the start of the disease stage to the treatment or death stage (54.3%), elderly care (45.7%), equal enjoyment of the right to health expenditure per capita by all the society members and implementing the principle of justice in the health-care and the presence of physician in all villages (44.6%). On the contrary, the following weaknesses had the highest frequency: lack of provision of transportation needs for the Family Physician Plan’s employees (53.2%), insufficient funding (48.4%), the high workload for the physician (46.8%).Conclusion: To enhance the public’s accessibility to the health services and enable their just utilization from such services, the Family Physician Plan must be assessed by the respective health care organization. In this way, it will be possible to identify its shortcomings paving the path to more effective measures towards promoting the quality of the medical-related activities.Keywords: Family Physician, Health system, Assessment, Employee

Evaluation of the Levels of Evidence in Three Clinical Chapters in Five Editions of the Textbook Pathways of the Pulp

Introduction: The levels of evidence (LOE) of dental education texts is critical from the educational point of view. The present study aimed to evaluate the levels of evidence of references used in three clinical chapters in the textbook Pathways of the Pulp. Material & Method: The references of three clinical chapters in the text book Pathways of the Pulp were assessed in five of its editions. The levels of evidence were ranked according to study type and the Oxford scale from 0 to 5. The chi-square test was used to compare the level of evidence between different editions of the "Retreatment," "Trauma," and "Surgery" chapters. Results: A total of 3656 references were reviewed and analyzed from the "Trauma" (928 references), "Re-treatment" (1906 references), and "Surgery" (822 references) chapters in the 1998, 2002, 2006, 2011, and 2016 editions. The percentage of the LOE 0 (no evidence) was high (>60%) in all three chapters in all editions (P<0.001). The levels of evidence had the same distribution in all editions (P=0.871). The LOE of the "Re-treatment" (P=0.044) and "Surgery" (P<0.001) chapters changed in some editions. Conclusion: The majority of references in the three clinical chapters of the book are low-level evidence. Encouragement policies for researchers to conduct studies with high LOE are necessary

Sample Size Calculation of Clinical Trials Published in Two Leading Endodontic Journals

Introduction: The purpose of this article was to evaluate the quality of sample size calculation reports in published clinical trials in Journal of Endodontics and International Endodontic Journal in years 2000-1 and 2009-10. Materials and Methods: Articles fulfilling the inclusion criteria were collected. The criteria were: publication year, research design, types of control group, reporting sample size calculation, the number of participants in each group, study outcome, amount of type I (α) and II (β) errors, method used for estimating prevalence or standard deviation, percentage of meeting the expected sample size and considering clinically importance level in sample size calculation. Data were extracted from all included articles. Descriptive analyses were conducted. Inferential statistical analyses were done using independent T-test and Chi-square test with the significance level set at 0.05. Results: There was a statistically significant increase in years between 2009 and 10 compared to 2000-1 in terms of reporting sample size calculation (P=0.002), reporting clinically importance level (P=0.003) and in samples size of clinical trials (P=0.01). But there was not any significant difference between two journals in terms of reporting sample size calculation, type of control group, frequency of various study designs and frequency of positive and negative clinical trials in different time periods (P>0.05). Conclusion: Sample size calculation in endodontic clinical trials improved significantly in 2009-10 when compared to 2000-1; however further improvements would be desirable

Introducing a comprehensive data reduction algorithm for high-precision U-Th geochronology with isotope dilution MC-ICP-MS

Multi collector inductively coupled plasma mass spectrometry (MC-ICP-MS) is being increasingly utilized for U-Th geochronology of carbonate deposits with comparable precision to thermal ionization mass spectrometry (TIMS) [1, 2]. While attention has been paid to propagation of uncertainties for U-Th-Pb analysis by TIMS and the isochron technique [3,4], a comprehensive data processing scheme is lacking for MC-ICP-MS. To address this need, we have developed an algorithm in Mathematica application to allow for step-by-step monitoring of the data reduction process. The program is flexible and affords the user easy control over input variables. Adjustments for background and spike isotope contributions, abundance sensitivity and instrumental mass bias are implemented through the code, followed by age calculation and propagation of uncertainties with Monte Carlo simulation. A rigorous standard bracketing procedure was adopted using Uranium (CRM-112A) and Th (IRMM-035) standard solutions, doped with IRMM-3636a ^(233)U/^(236)U “double-spike”, to account for deviations of isotope ratios from certificate values and improve accuracy. Following a single U/TEVA extraction chromatography step to separate U from Th, ten replicate ages from a speleothem in Cathedral Cave (CC), Utah showed excellent agreement (R^2 = 0.999) with results previously measured at the University of Minnesota by single collection ICP-MS [5]. The external reproducibility of our analytical technique was evaluated by analyzing six aliquots of an in-house standard, prepared by homogenizing a piece of the CC speleothem, which returned a mean age of 21468±120 y (2SD). A limited amount of the standard powder is available upon request for interlaboratory calibration. We have successfully dated 36 samples from caves in the Bahamas, the Dominican Republic and Iran

Recognizing the Emotional State Changes in Human Utterance by a Learning Statistical Method based on Gaussian Mixture Model

Speech is one of the most opulent and instant methods to express emotional characteristics of human beings, which conveys the cognitive and semantic concepts among humans. In this study, a statistical-based method for emotional recognition of speech signals is proposed, and a learning approach is introduced, which is based on the statistical model to classify internal feelings of the utterance. This approach analyzes and tracks the emotional state changes trend of speaker during the speech. The proposed method classifies utterance emotions in six standard classes including, boredom, fear, anger, neutral, disgust and sadness. For this purpose, it is applied the renowned speech corpus database, EmoDB, for training phase of the proposed approach. In this process, once the pre-processing tasks are done, the meaningful speech patterns and attributes are extracted by MFCC method, and meticulously selected by SFS method. Then, a statistical classification approach is called and altered to employ as a part of the method. This approach is entitled as the LGMM, which is used to categorize obtained features. Aftermath, with the help of the classification results, it is illustrated the emotional states changes trend to reveal speaker feelings. The proposed model also has been compared with some recent models of emotional speech classification, in which have been used similar methods and materials. Experimental results show an admissible overall recognition rate and stability in classifying the uttered speech in six emotional states, and also the proposed algorithm outperforms the other similar models in classification accuracy rates

Effect of Field of View and Resolution in Detection of Horizontal Root Fractures in CBCT images: An In Vitro Study

Introduction: New cone-beam computed tomography (CBCT) devices are capable of imaging with different resolutions and field of views (FOVs), in which higher resolutions and FOVs impose a higher dose to the patient. This study was an attempt to investigate the detection accuracy from different FOVs and resolutions in detection of horizontal root fractures.  Methods and Materials: Through this experimental study, in five different field of views (FOV) and resolutions (voxel size) of New Tom VGi CBCT (Italy) system was used to scan fifty teeth with horizontal root fractures in half of them. The images were evaluated by four observers (two maxillofacial radiologists and two general dentists) who recorded the presence or absence of horizontal root fractures. The data were analyzed by SPSS 22 software and MacNemar and kappa test were used to compare results with reality. Results: The highest sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (AZ) were attributed to 8×8 FOV and high resolutions (0.125 mm voxel size) but the difference between sensitivity, specificity, PPV and NPV was not significant. Kappa values for inter-observer agreement between radiologists and general dentists and also intra-observer agreement were in excellent ranges. The highest Kappa in both cases was attributed to 8×8 FOV and high resolutions. Conclusion: There was no significant difference to diagnose of horizontal root fracture between two observer groups and for all of the FOVs and voxel sizes. Keywords: Cone-Beam Computed Tomography; Field of View; Horizontal Root Fracture

In silico characterization of competing endogenous RNA network in glioblastoma multiforme with a systems biology approach

Glioblastoma multiforme (GBM) is the most frequent malignant type of primary brain cancers and is a malignancy with poor prognosis. Thus, it is necessary to find novel therapeutic modalities based on molecular events occur at different stages of tumor progression. We used expression profiles of GBM tissues that contained long non-coding RNA (lncRNA), microRNA (miRNA) and mRNA signatures to make putative ceRNA networks. Our strategy led to identification of 1080 DEmRNAs, including 777 downregulated DEmRNAs (such as GJB6 and SLC12A5) and 303 upregulated DEmRNAs (such as TOP2A and RRM2), 19 DElncRNAs, including 16 downregulated DElncRNAs (such as MIR7-3HG and MIR124-2HG) and 3 upregulated DElncRNAs (such as CRNDE and XIST) and 49 DEmiRNAs, including 10 downregulated DEmiRNAs (such as hsa-miR-10b-5p and hsa-miR-1290) and 39 upregulated DEmiRNAs (such as hsa-miR-219a-2-3p and hsa-miR-338-5p). We also identified DGCR5, MIAT, hsa-miR-129-5p, XIST, hsa-miR-128-3p, PART1, hsa-miR-10b-5p, LY86-AS1, CRNDE, and DLX6-AS1 as 10 hub genes in the ceRNA network. The current study provides novel insight into molecular events during GBM pathogenesis. The identified molecules can be used as therapeutic targets for GBM