Leveraging Deep Learning Techniques on Collaborative Filtering Recommender Systems

With the exponentially increasing volume of online data, searching and finding required information have become an extensive and time-consuming task. Recommender Systems as a subclass of information retrieval and decision support systems by providing personalized suggestions helping users access what they need more efficiently. Among the different techniques for building a recommender system, Collaborative Filtering (CF) is the most popular and widespread approach. However, cold start and data sparsity are the fundamental challenges ahead of implementing an effective CF-based recommender. Recent successful developments in enhancing and implementing deep learning architectures motivated many studies to propose deep learning-based solutions for solving the recommenders' weak points. In this research, unlike the past similar works about using deep learning architectures in recommender systems that covered different techniques generally, we specifically provide a comprehensive review of deep learning-based collaborative filtering recommender systems. This in-depth filtering gives a clear overview of the level of popularity, gaps, and ignored areas on leveraging deep learning techniques to build CF-based systems as the most influential recommenders.Comment: 24 pages, 14 figure

SOLUTIONS FOR THE MIXED SYLVESTER OPERATOR EQUATIONS

This paper is devoted to investigating some system of mixed coupled generalized Sylvester operator equations. The block operator matrix decomposition is used to find the necessary and sufficient conditions for the solvability to these systems. The solutions of the system are expressed in terms of the Moore--Penrose inverses of the coefficient operators

A Reliable Routing Algorithm for Delay Sensitive Data in Body Area Networks

Wireless body Area networks (WBANs) include a number of sensor nodes placed inside or on the human body to improve patient health and quality of life. Ensuring the transfer and receipt of data in sensitive data is a very important issue. Routing algorithms should support a variety of service quality such as reliability and delay in sending and receiving data. Loss of information or excessive data delay can lead to loss of human life. A proper routing algorithm in WBAN networks provides an efficient route with minimum delay and higher reliability for sensitive data. In this context, a routing algorithm, as it is proposed, categorizes patient data into sensitive and non-sensitive. Sensitive packets are transmitted to the destination through the shortest route to have less delay and non-sensitive packets are transmitted from other routes. Simulation shows that the proposed algorithm performs better, in terms of the throughput than the DMQoS and RL-QRP this superiority; as a result, decreases the latency of the end

The Prevalence of Allergy symptoms in Students in Rural Area

Background: Asthma, allergic rhinitis and eczema as a common disorder in childhood, has many epidemiologic variations in different geographic areas. This study aimed at determining the prevalence of pediatric allergic disease in rural area of Babol. Methods: This analytical-cross sectional study was performed in 2012 by random sampling on 2 groups of children; the first group aged 6-7 years (n=1735) and the second group aged 12-14 years (n=2080) during 2012. Data was collected by ISAAC first phase questionnaire and analyzed by SPSS 17 and Chi square test. Results: The prevalence of asthma in elementary school was 19% and in guidance school was 29.9% (p=0.000). The prevalence of allergic rhinitis in primary school in guidance school was 9.9% and 18.1%, respectively (p=0.000). There was no significant difference (p=0.223) between Elementary school (6.1%) and Guidance school (5.5%) in terms of prevalence of eczema. Conclusions: The results showed that the prevalence of asthma and allergic rhinitis in the rural area of Babol was remarkable that was high in older age group and needs to more attention in health program for decreasing this prevalence

COVID-19 control management in central corona hospitals using SWOT and QSPM matrices: A case study in Kashan central hospitals

Background: During the COVID-19 pandemic, hospitals have been the most important centers for the virus spread. Therefore, this study aimed to evaluate the management of infection control in central corona hospitals in Kashan using the quantitative strategic planning matrix (QSPM) matrix. Methods: The existing documents studied the strengths, weaknesses, opportunities, and threats of the organization identified by environmental health experts. The internal and external factors were identified as internal factor evaluation (IFE) and external factor evaluation (EFE) matrices, respectively, then, prioritized and weighted. In the next step, the SWOT matrix was formed and the type of used strategy by the organization was determined, and solutions to improve the current situation were presented by experts. Finally, the attractiveness table was compiled and weighted using the QSPM method to prioritize the proposed strategies. Results: After identifying 25 strengths, 28 weaknesses, 15 opportunities, and 13 threats, weighting was performed, the final score for internal and external factors was 2.6475 and 2.3825, respectively. The final strategy for implementing COVID-19 disease control in the studied hospitals was the Conservative Strategy (WO). Based on this, six control strategies were presented. The priority and attractiveness of each strategy were evaluated using the QSPM matrix. Finally, the strategy of “structuring the system and providing and upgrading the equipment and infrastructure facilities” was implemented as a priority. Conclusion: According to the results, the combination of SWOT (Strengths, Weaknesses, Opportunities, and Threats) and QSPM methods can play an efficient role in identifying and evaluating the factors affecting the management of the COVID-19 pandemic in hospitals and further developing and prioritizing control strategies for this infectious disease. Keywords: COVID-19, Environmental health, Hospitals, Research desig

The role of gray-scale ultrasound and elastography in differentiating benign from malignant axillary lymph nodes in patients with breast cancer

Introduction: Breast cancer is one of the most common cancers in women. Involvement of regional lymph nodes by breast cancer has shown to be a significant marker in the overall diagnosis of patients. In this study, we aimed to investigate the role of gray-scale ultrasound and elastography in discriminating benign from malignant axillary lymph nodes in patients with breast cancer. Methods: In this analytical study, patients with breast cancer who were referred to sonography ward of a tertiary medical educational center and found to have suspicious lymph nodes were investigated. Formal properties were evaluated by grayscale ultrasound and tissue properties were assessed by elastography. Biopsies were performed on all cases and suspicious tissues were removed. Results: This study was conducted on 50 patients with the mean age of 48.54±10.58 years. 52% of patients had a mass in their right breast and the most prevalent type of breast cancer was intra-ductal carcinoma. 60% of the lymph nodes were reported to be malignant. In 56% of the lymph nodes, grayscale ultrasound tests demonstrated unusual findings and the most common finding was the removal of fat from lymph node hilum. Moreover, elastography results indicated that 36% of the cases have grade 4 (blue) lesions. Conclusion: This study indicated that grayscale ultrasound and elastography have high sensitivity and specificity in detecting metastatic lymph nodes. This finding was in line with the findings reported in many of the previous studies

Green Synthesis of Silver Nanoparticles using Achillea biebersteinii Flower Extract and Its Anti-Angiogenic Properties in the Rat Aortic Ring Model

Silver nanoparticles display unique physical and biological properties which have attracted intensive research interest because of their important medical applications. In this study silver nanoparticles (Ab.Ag-NPs) were synthesized for biomedical applications using a completely green biosynthetic method using Achillea biebersteinii flowers extract. The structure and properties of Ab.Ag-NPs were investigated using UV-visible spectroscopic techniques, transmission electron microscopy (TEM), zeta potential and energy dispersive X-ray spectrometers (EDS). The UV-visible spectroscopic analysis showed the absorbance peak at 460 nm, which indicates the synthesis of silver nanoparticles. The average particle diameter as determined by TEM was found to be 12 ± 2 nm. The zeta potential analysis indicated that Ab.Ag-NPs have good stability EDX analysis also exhibits presentation of silver element. As angiogenesis is an important phenomenon and as growth factors imbalance in this process causes the acceleration of several diseases including cancer, the anti-angiogenic properties of Ab.Ag-NPs were evaluated using the rat aortic ring model. The results showed that Ab.Ag-NPs (200 μg/mL) lead to a 50% reduction in the length and number of vessel-like structures. The synthesized silver nanoparticles from the Achillea biebersteinii flowers extract, which do not involve any harmful chemicals were well-dispersed and stabilized through this green method and showed potential therapeutic benefits against angiogenesis

Immediate Results of Percutaneous Mitral Balloon Valvuloplasty in Patients with Mitral Stenosis

Introduction: Mitral stenosis is a prevalent valvular disease in developing countries. Percutaneous mitral balloon valvuloplasty (PMBV) is the gold standard treatment. The main objective of this study was to assess the initial results of PMBV in patients with mitral stenosis during 16 years (2002-2018) in Mashhad, Iran. Materials and Methods: From April 2002 to March 2018, 770 patients underwent PMV in department of cardiology. PMV was performed by the antegrade transseptal method using the Inoue balloon. Results: The obtained success rate was 97%. In this study, the valve area increased from 0.9±1.1 to 1.8±0.2 cm2 (

Comparative Study of Hearing Impairment among Healthy and Intensive Care unit Neonates in Mashhad, North East Iran.

INTRODUCTION According to World Health Organization (WHO) 2001 statistics, hearing disorders are the most common congenital disease, and the incidence rate among high-risk newborns is as much as ten times as high as that in healthy neonates. However, 78% of screening test failures are well-baby nursery babies. The Joint Committee on Infants' Hearing (JCIH) has emphasized the importance of early diagnosis and treatment in neonates with hearing impairments in order to preserve their maximum linguistic skills. The aim of our study was to compare the prevalence of hearing loss among babies in the neonatal intensive care unit (NICU) and the rooming-in unit (RIU). MATERIALS AND METHODS Neonates born in three hospitals in Mashhad between 2008 to 2010 were studied prospectively and screened for auditory disorders using the oto acoustic emission (OAE) test at the time of discharge and 3 weeks later. To confirm hearing loss, the auditory steady state response (ASSR) test was used among those participants who failed both OAE tests. RESULTS Two-thousand and sixty-three neonates from the NICU were screened and compared with a control group consisting of 8,724 neonates from the RIU or the well-baby nursery. At the end of the study, hearing impairment as confirmed by failure in the ASSR test was diagnosed in 31 neonates (26 in the control group [0.30%] and five in the NICU group [1.94%]). CONCLUSION In our study, the prevalence of hearing disorders among NICU neonates was 6.5-times greater than that among babies from the RIU or well-baby unit. This observation demonstrates the importance of universal screening programs particularly for high-risk population neonates

Relationship between platelet count and platelet width distribution and serum uric acid 1 concentrations in patients with untreated essential hypertension

Hematological parameters have emerged as independent determinants of high serum concentrations of uric-acid and predictive-factors in the evaluation of the total cardiovascular-risk in patients with essential-hypertensive. Here we have investigated the possible relationships between hematological-factors and serum uric-acid levels in hypertensive-patients recruited as part of Mashhad-Stroke and Heart-Atherosclerotic-Disorders cohort study. Two-thousand three-hundred and thirty four hypertensive individuals were recruited from this cohort and these were divided into two groups; those with either high or low serum uric acid concentrations. Demographic, biochemical and hematological characteristics of population were evaluated in all the subjects. Logistic-regression-analysis was performed to determine the association of hematological-parameters with hypertension. Of the 2334 hypertensive-subjects, 290 cases had low uric-acid, and 2044 had high serum uric acid concentrations. Compared with the low uric acid group, the patients with high serum uric acid, had higher values for several hematological parameters, whilst platelet counts (PLT) were lower. Multiple linear regression analysis showed that PLT and serum hs-CRP were correlated with serum uric acid level. Stepwise multiple logistic regression model confirmed that PDW and gender were independent determinant of a high serum uric acid. PDW and PLT appear to be independently associated with serum uric acid level in patients with hypertension