Bayesian Nonparametric Dirichlet Process Mixture Modeling in Transportation Safety Studies

In transportation safety studies, it is often necessary to account for unobserved heterogeneity and multimodality in data. The commonly used standard generalized linear models (e.g., Poisson-gamma models) do not fully address unobserved heterogeneity, assuming unimodal exponential families of distributions. This thesis illustrates how restrictive assumptions (e.g., unimodality) common to most road safety studies can be relaxed employing Bayesian nonparametric Dirichlet process mixture models. We use a truncated Dirichlet process, so that our models reduce to the form of finite mixture (latent class) models, which can be estimated employing standard Markov chain Monte Carlo methods, emphasizing computational simplicity. Interestingly, our approach estimates the number of latent subpopulations as part of its analysis algorithm using an elegant mathematical framework. We use pseudo Bayes factors for model selection, showing how the predictive capability of models can be affected by different assumptions. In univariate settings, we extend standard generalized linear models to a Dirichlet process mixture generalized linear model in which the random intercepts density is modeled nonparametrically, thereby adding flexibility to the model. We examine the performance of the proposed approach using both simulated and real data. We also examine the performance of the proposed model in terms of replicating datasets with high proportions of zero crashes. In terms of engineering insights, we provide a policy example related to the identification of high-crash locations, a critical component of the transportation safety management process. With respect to multilevel settings, this thesis introduces a flexible latent class multilevel model for analyzing crash data that are of hierarchical nature. We extend the standard multilevel model by accounting for unobserved cross-group heterogeneity through multimodal intercepts (group effects). The proposed method allows identifying latent subpopulations (and consequently outliers) at the highest level of the hierarchy (e.g., geographic areas). We evaluate our method on two recent railway grade crossing crash datasets from Canada. This research confirms the need for a multilevel approach for both datasets due to the presence of spatial dependencies among crossings nested within the same region. We provide a novel approach to benchmark different regions based on their safety performance measures. To this end, we identify latent clusters among different regions that share similar unidentified features, stimulating further investigations to explore reasons behind such similarities and dissimilarities. This could have important policy implications for various safety management programs. This thesis also investigates inference for multivariate crash data by introducing two flexible Bayesian multivariate models: a multivariate mixture of points and a mixture of multivariate normal densities. We use a Dirichlet process mixture to keep the dependence structure unconstrained, relaxing the usual homogeneity assumptions. We allow for interdependence between outcomes through a Dirichlet process prior on the random intercepts density. The resulting models collapse into a form of latent class multivariate model, an appealing way to address unobserved heterogeneity in multivariate settings. Therefore, the multivariate models that we derive in this thesis account for correlation among crash types through a heterogeneous correlation structure, which better captures the complex structure of correlated data. To our knowledge, this is the first study to propose and apply such a model in the transportation literature. Using a highway injury-severity dataset, we illustrate how the robustness to homogeneous correlation structures can be examined using a multivariate mixture of points model that relaxes the homogeneity assumption with respect to the location of the dependence structure. We then use the mixture of multivariate normal densities model‒relaxing the homogeneity assumption with respect to both the location and the covariance matrix‒to investigate the effects of various factors on pedestrian and cyclist safety in an urban setting, modeling both outcomes simultaneously. To our knowledge, this is the first study to conduct a joint safety analysis of active modes at an intersection level, a micro-level, which is expected to provide more detailed insights. We show how spurious assumptions affect predictive performance of the multivariate model and the interpretation of the explanatory variables using marginal effects. The results show that our flexible model specification better captures the underlying structure of pedestrian/cyclist crash data, resulting in a more accurate model that contributes to a better understanding of safety correlates of non-motorist road users. This in turn helps decision-makers in selecting more appropriate countermeasures targeting vulnerable road users, promoting the mobility and safety of active modes of transportation

MMPP modeling of ATM multimedia traffic

Traffic control cannot be done without having a well-fit model to represent the traffic. Therefore traffic modeling is an essential part of any network control research project. Markov-Modulated Poisson Process (MMPP) shows the great flexibility and analytical tractibility which is needed in traffic control. MMPP model is not only capable of capturing the interframe correlation in the traffic, but also can be easily analysed by using well-known Matrix Geometric techniques. Our research in this project is focused on the study of MMPP for modeling of the traffic in the broadband networks. We first start with the simplest case, a two state MMPP, and study its performance for representing the ATM traffic. Starting with a superposition of voice sources, the performance of various techniques to model the superposed stream by a 2-state MMPP is compared. Then the techniques are generalized for an arbitrary aggregated ATM traffic, characterized only from a sequence of traffic samples. A refined moment-based technique to derive the parameters of a 2-state MMPP model to represent such an arbitrary traffic is proposed. In order to have a more general model applicable to various types of traffic, we propose a special type of multiple-state MMPP, a superposition of N 2-state MMPP minisources. (Abstract shortened by UMI.

Estimating traffic contribution to particulate matter concentration in urban areas using a multilevel Bayesian meta-regression approach.

Quantifying traffic contribution to air pollution in urban settings is required to inform traffic management strategies and environmental policies that aim at improving air quality. Assessments and comparative analyses across multiple urban areas are challenged by the lack of datasets and methods available for global applications. In this study, we quantify the traffic contribution to particulate matter concentration in multiple cities worldwide by synthesising 155 previous studies reported in the World Health Organization (WHO)'s air pollution source apportionment data for PM10 and PM2.5. We employed a Bayesian multilevel meta-regression that accounts for uncertainties and captures both within- and between-study variations (in estimation methods, study protocols, etc.) through study-specific and location-specific explanatory variables. The final sample analysed in this paper covers 169 cities worldwide. Based on our analysis, traffic contribution to air pollution (particulate matter) varies from 5% to 61% in cities worldwide, with an average of 27%. We found that variability in the traffic contribution estimates reported worldwide can be explained by the region of study, publication year, PM size fraction, and population. Specifically, traffic contribution to air pollution in cities located in Europe, North America, or Oceania is on average 36% lower relative to the rest of the world. Traffic contribution is 28% lower among studies published after 2005 than those published on or before 2005. Traffic contribution is on average 24% lower among cities with less than 500,000 inhabitants and 19% higher when estimated based on PM10 relative to PM2.5. This quantitative summary overcomes challenges in the data and provides useful information for health impact modellers and decision-makers to assess impacts of traffic reduction policies.This study was supported by the project “Towards an Integrated Global Transport and Health Assessment Tool (TIGTHAT)”, funded by Medical Research Council (MRC) Global Challenges Research Fund, UK (number: RG87632-SJ). The work of the first author was partly funded by the Natural Sciences and Engineering Research Council of Canada

Effects of Lactobacillus acidophilus and Bifidobacterium bifidum probiotics on the serum biochemical parameters, and the vitamin D and leptin receptor genes on mice colon cancer

Objective(s): The preclinical reports have shown that specific probiotics like Bifidobacterium bifidum (B. bifidum) and Lactobacillus acidophilus (L. acidophilus) can be applied as the biotherapeutic agents in the inhibition or therapy of colorectal cancer via the modification of gut bacteria. In the previous studies, we have assessed the impact of L. acidophilus and B. bifidum probiotics on gut bacteria concentration and also their chemo-protective impact on mice colon cancer. In the following, we assessed the effects of these probiotics on the  gene expression of vitamin D receptor (VDR) and the leptin receptor (LPR) and the serum biochemical parameters on mice colon cancer. Materials and Methods: Thirty-six male BALB/c mice were equally shared into 4 groups; (i) health with routine dietary foods without any treatment, (ii) azoxymethane (AOM)-induced mice colon cancer with common dietary foods, (iii) and (iv) AOM-induced mice colon cancer with oral consumption of L. acidophilus and B. bifidum (1×109 cfu/g) for 5 months, respectively. Then, the serum total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), alanine transaminase, alkaline phosphatase, and albumin and also VDR and LPR genes expression were evaluated. Results: Oral consumption of L. acidophilus and B. bifidum probiotics significantly decreased the triglycerides, alkaline phosphatase, LDL, and also the VDR and LPR gene expression in mice colon cancer (

MIDDLEWARE FOR SMART HETEROGENEOUS CRITICAL INFRASTRUCTURE NETWORKS INTERCOMMUNICATION

Svrha je ovog preglednog rada objasniti princip i izložiti rezultate dosadašnjih istraživanja nove SWEEPS tehnike ispiranja korijenskog kanala. Standardna obrada korijenskih kanala tijekom endodontskog liječenja uključuje mehaničku instrumentaciju ručnim ili strojnim instrumentima te kemijsku obradu sredstvima za ispiranje poput NaOCl i EDTA. Tijekom instrumentacije kanala formiraju se debris i zaostatni sloj, koje je potrebno ukloniti. U dezinfekciji endodontskog prostora zuba ključan je raspad bakterijskog biofilma koji se postiže brzim strujanjem sredstva za ispiranje u kanalu. Dinamičan protok sredstva za ispiranje u kanalu potreban je za dosezanje svih dijelova endodontskog prostora, održavanje učinkovite koncentracije sredstva i za stvaranje smičnog stresa na stijekama koji uklanja biofilm. Zbog ograničenja pasivnog ispiranja špricom i iglom (nedovoljna izmjena tekućine u korijenskom kanalu) došlo je do razvoja brojnih tehnika aktivacije sredstva za ispiranje, poput zvučno i ultrazvučno aktiviranog ispiranja. Noviji doprinos poboljšanju učinkovitosti dezinfekcije korijenskih kanala predstavlja laserski aktivirano ispiranje (engl. laser-activated irrigation, LAI) pomoću erbij lasera. Posebna tehnika LAI zove se fotonima inducirano fotoakustično strujanje (engl. photon-induced photoacoustic streaming, PIPS), a temelji se na nastanku kavitacija i šok-valova koji čiste stijenke kanala. Tehnološkim napretkom postavki lasera omogućen je razvoj novih tehnika. Emisija fotoakustičnog strujanja pojačana udarnim valom (engl. Shock Wave Enchanced Emission of Photoacoustic Streaming, SWEEPS) nova je tehnika ispiranja korijenskih kanala koja se temelji na pojačanju šok-valova dodatnim pulsom laserske zrake. U literaturi još nema dovoljno radova na temelju kojih bi se mogao jasno definirati učinak SWEEPS tehnike.The aim of this study is to explain the principles and present the results of past research of the new SWEEPS root canal irrigation technique. Standard procedure during endodontic therapy involves mechanical instrumentation using hand or rotary files and chemical treatment that uses irrigants such as NaOCl and EDTA. During root canal instrumentation, debris and smear layer are formed and they need to be removed. Deattachment of bacterial biofilm plays a key role in endodontic disinfection and is originated by a fast stream of irrigant inside the root canal. Dinamic flow of irrigant inside the root canal is necessary for reaching all parts of endodontic space, maintaining an effective irrigant concentration and producing shear stress on root canal walls, which removes the biofilm. Limitations of passive needle irrigation (insufficient exchange of irrigant in the root canal) induced the development of numerous irrigation activation techniques, such as sonic and ultrasonic activation of irrigation. A new contribution to improving the efficiency of root canal disinfection is laser-activated irrigation (LAI) using erbium lasers. A special technique that LAI uses is photon-induced photoacoustic streaming (PIPS) and it is based on producing cavitations and shockwaves which debride the root canal walls. Technological progress of laser settings enabled the development of new techniques. Shock Wave Enchanced Emission of Photoacoustic Streaming (SWEEPS) is a new irrigation activation technique based on the enchancement of shockwaves by using additional laser pulse. There have not been enough papers published to clearly define the efficacy of SWEEPS technique

Factors influencing the creativity and innovation in managers of military and civilian hospitals in Tehran, Iran

Introduction: Hospitals, like other organizations in the community for survival and development are managers need creative and innovative. Breeding and training of such managers Appropriate demand shall provide the platform that its determination requires the understanding of factors affecting innovation and creativity of people is. Aim : Factors influencing creativity and innovation managers, both military and civilian hospitals in Tehran. Methods: Cross-sectional study method was conducted. Senior managers and middle managers in nine selected military and civilian hospitals in Tehran (90) The study formed. Data collection was conducted by questionnaire. Data obtained from 90 questionnaires, using SPSS software for analysis and comparison of mean scores obtained in different groups ANOVA was used. Results: Results showed that the most organizational factors achieving points with 56.2 and the subsets of organizational factors, factors related to the reward system earned the highest score. The most important factors affecting innovation, hospital managers, and individual factors achieving points with 83.2 was identified among a subset of individual factors, factors related to science, knowledge and expertise manager earned the highest score. Conclusions : According to the results, providing a suitable environment and good for the field organization may encourage hospitals to create innovative managers. To create such an environment also reform the payment systems and designing a suitable payment system in hospitals, action seems necessary. Change the prevailing culture in hospitals and innovation become the norm and a positive value, the benefit is not empty

Is a Single dose of Prophylactic Antibiotics Sufficient in Patients with Acute Non-Complicated Appendicitis?

Background: Acute appendicitis is one of the most common acute surgery events. Its main treatment is surgery. However medical management before and after the surgery has an important impact on the treatment. Objective: The aim of study was evaluating the outcomes of single dose and quadruple doses of prophylactic antibiotic therapy in patients with acute non-complicated appendicitis. Methods: This randomized double blind clinical trial was carried out on 294 patients in single dose (136 patients) and the quadruple doses (158 patients) groups. In single dose group, a dose of 1g Cefazolin + 500mg Metronidazole was prescribed intravenously about half an hour before surgery. The quadruple doses group received three more doses after surgery.  Two groups were followed for fever, erythema, seroma, wound infection, intra-abdominal abscess formation and readmissions within one month after discharge. Results: The mean age of patients was 31±5.14 years. 203(69%) of patients were men while 91(31%) were women. There were no significant statistical differences between groups in age, sex and body mass index (BMI) variables. No significant statistical differences were observed during surgery and hospitalization period between two groups. In the single dose group, wound infection was 8(5.9%), while it was 6(3.8%) in the quadruple doses group; hence, there were no significant statistical differences in this regard. There was no abdominal abscess in groups. There were significant statistical differences regarding erythema, seroma and antibiotics consumption costs between groups. Conclusion: A single dose of prophylactic antibiotics is sufficient in patients with acute suppurative non-complicated appendicitis

Effect of saffron supplementation on oxidative stress parameters: A systematic review and meta‐analysis of randomized placebo‐controlled trials

Oxidative stress (OS), the absence of equilibrium between prooxidants and antioxi dants in the body, has been shown to play a pivotal role in the initiation and pro gression of many diseases. Saffron has been noted for its antioxidant capacity and can be used to improve OS parameters in unhealthy patients. Our aim was to evalu ate the efficacy of saffron supplementation on OS parameters in unhealthy patients in randomized controlled trials (RCTs). We searched Medline, EMBASE, Cochrane CENTRAL, Scopus, and Web of Science without language restrictions for RCTs up until April 2021. Studies were included if they compared any form of saffron sup plementation to placebo or no supplementation on OS parameters in unhealthy pa tients. Using a random-effects model with calculated standardized mean difference (SMD) and 95% confidence intervals (CI), we quantitatively synthesized the data. Heterogeneity was assessed using Cochrane's I 2 values. Ten randomized controlled trials were eligible for this review. Seven were included in the meta-analysis and indicated an association between saffron intake and a statistically significant decrease in malondialdehyde (MDA) levels (SMD: −0.40; 95% CI: −0.63, −0.17; I 2 = 32.6%) and a significant increase in total antioxidant capacity (TAC, SMD: 0.24; 95% CI: 0.05, 0.42; I 2 = 00.0%). Saffron intake was shown to significantly impact MDA and TAC, indicating its beneficial properties in improving OS in unhealthy patients. However, additional RCTs are required to evaluate the effect on other OS parameters.info:eu-repo/semantics/publishedVersio

The Minimum Dataset and Inclusion Criteria for the National Trauma Registry of Iran: A Qualitative Study

Background Burden of injuries is an important public health problem, especially in developing countries. However, a national standard tool for data collection of trauma registry has not been developed in Iran yet. Objectives The present study aimed to describe the steps undertaken in the development of the minimum dataset (MDS) and define the inclusion and exclusion criteria for a case of trauma registry by the national trauma registry of Iran (NTRI). Methods The working group consists of sixteen elected expert representatives from seven established countrywide active trauma research centers. Following a structured extensive review of the literature, the working party identified the data variables that included key registry goals for pre-hospital and hospital, outcome and quality assurance information. We used data variables from three trauma registry centers: National trauma data standard questionnaire, European trauma care (UT stein version), and Sina trauma and surgery research center. Then, we performed two email surveys and three focus group discussions and adapted, modified and finally developed the optimized MDS in order to prepare the quality care registry for injured patients. Results The finalized MDS consisted of 109 data variables including demographic information (n = 24), injury information (n = 19), prehospital information (n = 26), emergency department information (n = 25), hospital procedures (n = 2), diagnosis (n = 2), injury severity (n = 3), outcomes (n = 5), financial (n = 2), and quality assurance (n = 1). For a patient sustained one or more traumatic injury in a defined diagnostic ICD-10 codes, the inclusion criteria considered as one of the followings: If the patient stayed > 24 hours in the hospital, any death after hospital arrival, any transfer from another hospital during the first 24 hours from injury. Conclusions This study presents how we developed the MDS in order to uniform data reporting in the NTRI and define our inclusion and exclusion criteria for trauma registry. Applying the MDS and the case definition in pilot studies are needed in next steps