Estimation of near fault ground motion based on a hybrid source model and a theoretical Green’s function method

One of the most important challenges in seismic evaluation of structures comes from wide variability of possible motions that a specific site may experience. This variability arises from the intrinsic randomness of seismic motions (aleatory uncertainty) and lack of knowledge about the physical process behind an earthquake (epistemic uncertainty). The epistemic uncertainty in estimating ground motion can be properly characterized by providing an understanding of the physical aspects of earthquake source models. In this paper, a combination of the theoretical-based Green’s function method and hybrid slip source model is used to reduce the source uncertainty. The procedure is implemented on the 1994 Northridge earthquake as a case study. For this purpose, the method is validated against recordings stations through demonstrating a good agreement between the elastic response spectra corresponding to the simulated and recorded data, confirming the reliability of the procedure. A simple additive weighting algorithm is used to select the best fit amongst simulated waveforms and optimal source model

A Bayesian approach for seismic recurrence parameters estimation

Recurrence models apply historical seismicity information to seismic hazard analysis. These models that play an important role in the obtained hazard curve are determined by their parameters. Recurrence parameters estimation has some features that lie in missing-data problems category. Thus, the observed data cannot be used directly to estimate model parameters. Furthermore discussion about results reliability and probable conservatism is impossible. The present study aims at offering an approach for Gutenberg-Richter parameters (a and b-values) estimation and determine their variation. Applying the proposed method to analyses of the heterogeneous data sets of seismic catalog, one would calculate valid estimates for recurrence parameters. This method has the capability to reflect all known sources of variability. The results of the case study clearly demonstrate applicability and efficiency of the proposed method, which can easily be implemented not only in advanced but also in practical seismic hazard analyses

Applying b-value variation to seismic hazard analysis using closed-form joint probability distribution

Reliable use of b-value in log[N(M)]=a-bM is critical in seismicity comparisons, seismic hazard analysis, prediction and comparative mechanism studies. Since earthquakes and the b-value are considered as stochastic processes and random variable, respectively, applying the probability distribution of b-value is necessary in its temporal and spatial variations assessment. In this paper, we propose a novel method that employs the b-value uncertainty in probabilistic seismic hazard analysis using normal-exponential joint distribution function. To this end, we calculate b-value statistics based on bootstrap sampling of the seismic catalog. Our analytical and experimental evaluations show that the proposed joint distribution results in a more precise closed-form relation for the probabilistic seismic hazard analysis accurately reducing the hazard in comparison to conventional methods. The benefit of the proposed approach here is improving the ability of assessing the effectiveness of various seismic risk mitigation strategies and so, allocates the available resources more efficiently

A Bayesian approach for seismic recurrence parameters estimation

Recurrence models apply historical seismicity information to seismic hazard analysis. These models that play an important role in the obtained hazard curve are determined by their parameters. Recurrence parameters estimation has some features that lie in missing-data problems category. Thus, the observed data cannot be used directly to estimate model parameters. Furthermore discussion about results reliability and probable conservatism is impossible. The present study aims at offering an approach for Gutenberg-Richter parameters (a and b-values) estimation and determine their variation. Applying the proposed method to analyses of the heterogeneous data sets of seismic catalog, one would calculate valid estimates for recurrence parameters. This method has the capability to reflect all known sources of variability. The results of the case study clearly demonstrate applicability and efficiency of the proposed method, which can easily be implemented not only in advanced but also in practical seismic hazard analyses

Promotions of Manipuri Garments – A Study on Garments Retailers of Sylhet City

The Manipuri tribe of Bangladesh mostly live in Sylhet division possesses a rich culture, history, and tradition. But nowadays, there is an excellent interaction between Manipuri and mainstream Bengali culture, such as; Manipuri traditional clothes (Sari, Blouse, Chador, Scarf, Muffler etc.) have gained huge popularity among common Bangladeshi people. Especially Manipuri sari has a great reputation like Dhakai Jamdani, Tangail Jamdani, Rajshahi Silk and Mirpur Silk. Though there is a huge potentiality of Manipuri garments in Bangladesh as well as abroad, its market size is very small and not much available due to some socio-economic and technological problems. However, there are not much more initiatives to search the hindrances and opportunities of this sector. The purpose of this study is to find out the promotional activities of Manipuri garments retailers in Sylhet city and their perceptions about the effectiveness of different promotional elements. This study is mainly based on primary data and some statistical measures such as frequency distribution and multiple regression analysis have been used to assess some important findings. We observe several promotional elements like TV Advertising, Digital Marketing, Online selling and Retail Outlet & Decoration have a greater effect on customer’s attention to Manipuri Garments. We recommend that retailers of Manipuri Garments  should emphasize more on these promotional elements

The Prevalence of Renal Scar in Urinary Tract Infection Using Dimercaptosuccinic Acid (DMSA) Scan, and Related Factors in Children under 16 Years Old during the Years 2012-2016 in Sari City, Iran

Background: Urinary tract infection is one of the main causes of renal scar that can lead to serious complications such as hypertension or chronic renal failure. Therefore, accurate and timely diagnosis of urinary tract infection and other risk factors related to scar is very important. This study aimed to determine the prevalence of renal scar using dimercaptosuccinic acid (DMSA) scan after urinary tract infection in children under 16 years old in Bu Ali Sina hospital located in Sari City, Iran, during the years 2012 to 2016. Methods: In this cross-sectional study, the data were extracted from files related to those patients suffering UTI referred to Bu Ali Sina hospital, for whom DMSA scan was performed. Results: Of 208 enrolled children, 83.2% were girls and 16.8% were boy with mean age of 32.80 ± 32.57 months. Based on the first DMSA scan, the prevalence of scars was about 40%; and based on second DMSA scan (delayed), the prevalence was about 34%. In people who had scar, the frequency of UTI was more. In these patients, the most common organisms were Escherichia coli (71.4%), Proteus (14.3%), and Klebsiella (10.7%). Proteus significantly led to scar formation more than the others. Vesicoureteral reflux (VUR) with prevalence of 67.9% was the most common observed disease; and all patients with severe scars suffered from VUR. Scar in DSMA scan had no significant relationship with age and gender. Conclusion: Scar is a relatively common complication of UTI in children and VUR is an important risk factor for permanent damage. It is mandatory to think to this critical complications in children with UTI. Keywords Urinary tract infection; Scar; DMS

Global systematic review of primary immunodeficiency registries

Introduction During the last 4 decades, registration of patients with primary immunodeficiencies (PID) has played an essential role in different aspects of these diseases worldwide including epidemiological indexes, policymaking, quality controls of care/life, facilitation of genetic studies and clinical trials as well as improving our understanding about the natural history of the disease and the immune system function. However, due to the limitation of sustainable resources supporting these registries, inconsistency in diagnostic criteria and lack of molecular diagnosis as well as difficulties in the documentation and designing any universal platform, the global perspective of these diseases remains unclear. Areas covered Published and unpublished studies from January 1981 to June 2020 were systematically reviewed on PubMed, Web of Science and Scopus. Additionally, the reference list of all studies was hand-searched for additional studies. This effort identified a total of 104614 registered patients and suggests identification of at least 10590 additional PID patients, mainly from countries located in Asia and Africa. Molecular defects in genes known to cause PID were identified and reported in 13852 (13.2% of all registered) patients. Expert opinion Although these data suggest some progress in the identification and documentation of PID patients worldwide, achieving the basic requirement for the global PID burden estimation and registration of undiagnosed patients will require more reinforcement of the progress, involving both improved diagnostic facilities and neonatal screening.Peer reviewe

Preliminary report of a nationwide case-control study for identifying risk factors of tuberculosis following renal transplantation

Background. Tuberculosis (TB) is an important infection encountered posttransplantation, especially among patients in developing countries, where there are high incidences of morbidity and mortality. Materials and Methods. One hundred and twenty subjects (1) from 15 major kidney transplantation centers in Iran from 1984 to 2003 were compared with 440 controls who were matched for operative time, treatment center, and surgical team. Results. Mean ages of research subjects and controls were 38.6 and 36.6 years (P = .04), respectively. The mean duration of pretransplantation hemodialysis was 29 months (range, 2 to 192 months) in research subjects and 20 months (range, 1 to 180 months) in controls (P = .003). Positive past history of tuberculosis was detected in 4 (3.3) research subjects and in 7 (1.5) controls (P = .2). Fifty-two research subjects (43.3) and 241 controls (54.8) had pretransplantation purified protein derivative of tuberculin less than 5 mm (P = .02). Mean dosages of initial and maintenance immunosuppressive drugs in research subjects and in controls were not significantly different. Sixty research subjects (50) and 152 controls (34.5) had rejection prior to diagnosis of TB (P = .03). Conclusion. To our knowledge, this is the first study that demonstrates an increased risk of posttransplant TB by prolonged duration of pretransplant hemodialysis and number of posttransplant rejection episodes. Further study is needed to clarify these findings specifically with respect to various immunosuppressive regimens. © 2005 by Elsevier Inc. All rights reserved

Consensus Middle East and North Africa Registry on Inborn Errors of Immunity

Background: Inborn errors of immunity (IEIs) are a heterogeneous group of genetic defects of immunity, which cause high rates of morbidity and mortality mainly among children due to infectious and non-infectious complications. The IEI burden has been critically underestimated in countries from middle- and low-income regions and the majority of patients with IEI in these regions lack a molecular diagnosis. Methods: We analyzed the clinical, immunologic, and genetic data of IEI patients from 22 countries in the Middle East and North Africa (MENA) region. The data was collected from national registries and diverse databases such as the Asian Pacific Society for Immunodeficiencies (APSID) registry, African Society for Immunodeficiencies (ASID) registry, Jeffrey Modell Foundation (JMF) registry, J Project centers, and International Consortium on Immune Deficiency (ICID) centers. Results: We identified 17,120 patients with IEI, among which females represented 39.4%. Parental consanguinity was present in 60.5% of cases and 27.3% of the patients were from families with a confirmed previous family history of IEI. The median age of patients at the onset of disease was 36 months and the median delay in diagnosis was 41 months. The rate of registered IEI patients ranges between 0.02 and 7.58 per 100,000 population, and the lowest rates were in countries with the highest rates of disability-adjusted life years (DALY) and death rates for children. Predominantly antibody deficiencies were the most frequent IEI entities diagnosed in 41.2% of the cohort. Among 5871 patients genetically evaluated, the diagnostic yield was 83% with the majority (65.2%) having autosomal recessive defects. The mortality rate was the highest in patients with non-syndromic combined immunodeficiency (51.7%, median age: 3.5 years) and particularly in patients with mutations in specific genes associated with this phenotype (RFXANK, RAG1, and IL2RG). Conclusions: This comprehensive registry highlights the importance of a detailed investigation of IEI patients in the MENA region. The high yield of genetic diagnosis of IEI in this region has important implications for prevention, prognosis, treatment, and resource allocation

A hybrid multiobjective RBF-PSO method for mitigating DoS attacks in Named Data Networking

Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based (host-centric) Internet infrastructure. NDN can overcome the fundamental limitations of the current Internet, in particular, Denial-of-Service (DoS) attacks. However, NDN can be subject to new type of DoS attacks namely Interest flooding attacks and content poisoning. These types of attacks exploit key architectural features of NDN. This paper presents a new intelligent hybrid algorithm for proactive detection of DoS attacks and adaptive mitigation reaction in NDN. In the detection phase, a combination of multiobjective evolutionary optimization algorithm with PSO in the context of the RBF neural network has been applied in order to improve the accuracy of DoS attack prediction. Performance of the proposed hybrid approach is also evaluated successfully by some benchmark problems. In the adaptive reaction phase, we introduced a framework for mitigating DoS attacks based on the misbehaving type of network nodes. The evaluation through simulations shows that the proposed intelligent hybrid algorithm (proactive detection and adaptive reaction) can quickly and effectively respond and mitigate DoS attacks in adverse conditions in terms of the applied performance criteria