Risk Factors for BK Virus Infection after Kidney Transplantation, London, Ontario 2016

Our objective was to determine the risk factors for BK virus infection in renal allograft recipients in the first year after transplantation. In this cohort, we included all patients who received renal allograft at London Health Sciences Centre (LHSC) between 2012 and 2014. We continued post-transplantation follow-up for one year. Of 175 patients (37% female) with median age (range) of 53 (14-82) years, 40 (22.9%) developed BK viremia (median interval:100 days, range: 35-264). Recipient age, recipient gender, hemodialysis (HD) vs peritoneal dialysis (PD), Human Leukocyte Antigens A1, B35 and Cw4 increased the risk of post-transplant BKV infection. However, donor gender, donor age, deceased vs living donor, delayed graft function, ABO incompatibility and retransplantation did not increase the risk. PD and HD patients do not appear to have equal risks at the time of transplantation. Further studies are required to determine the immunologic reasons for this difference

Finite Element Analysis of Contribution of Adhesion and Hysteresis to Shoe-floor Friction

Slips and falls are one of the leading causes of occupational accidents. Understanding the important factors that affect shoe-floor friction is vital for identifying unsafe surfaces and designing better footwear and flooring. While the shoe-floor coefficient of friction is known to be dependent on several factors including shoe and floor roughness, shoe speed, shoe material, and normal load, the mechanisms that cause these effects are not very well understood. The objective of this thesis is to develop a finite element model that simulates the microscopic asperity interaction between shoe and floor surfaces and apply it to quantify the effect of shoe material, topography, loading and sliding speed on shoe-floor adhesion and hysteresis friction. Recent studies have concluded that boundary lubrication is highly pertinent to slipping and that adhesion and hysteresis are the main friction components in boundary lubrication. To have a better knowledge about the mechanisms governing the boundary lubrication friction at the microscopic asperity interaction level, a three dimensional computational model of two rough surfaces is developed which calculates the friction force due to hysteresis and real area of contact (which is proportional to adhesion friction). The computer model includes two rough surfaces of rubber and rigid material. A viscoelastic material model based on parameters calculated from experiments is used to simulate the shoe material. In addition, surface to surface contact algorithm is used for simulating the interaction of the two rough surfaces. The results show that microscopic shoe and floor roughness, followed by material properties, shoe sliding speed, and normal loading affect hysteresis and adhesion coefficient of friction. The model provides an improved insight about the mechanisms that cause changes in adhesion and hysteresis when altering shoe and floor roughness, sliding speed, shoe material and normal loading and it can be useful in development of slip resistant shoes and floorings

A Novel Scheme for Intelligent Recognition of Pornographic Images

Harmful contents are rising in internet day by day and this motivates the essence of more research in fast and reliable obscene and immoral material filtering. Pornographic image recognition is an important component in each filtering system. In this paper, a new approach for detecting pornographic images is introduced. In this approach, two new features are suggested. These two features in combination with other simple traditional features provide decent difference between porn and non-porn images. In addition, we applied fuzzy integral based information fusion to combine MLP (Multi-Layer Perceptron) and NF (Neuro-Fuzzy) outputs. To test the proposed method, performance of system was evaluated over 18354 download images from internet. The attained precision was 93% in TP and 8% in FP on training dataset, and 87% and 5.5% on test dataset. Achieved results verify the performance of proposed system versus other related works

Surveying the prerequisites for establishing patient's rights charter in health centers of Iran- A Delphi study

Background and aims: Patient's rights are one of pivotal elements of clinical governance and important indicators of quality care in health area. Patient's rights in Iran are stated in patient's rights charter and its establishing need to lying plots a set of prerequisites. The aim of this study was to survey prerequisites and to develop a bill for establishing patient rights in Iranian health centers using expert's ideas and comments. Methods: The study was conducted using the Delphi’s approach, and 30 purposefully selected participants include experts in law, medical groups and ethics, as panelists were enrolled in 4 rand Delphi technique. In first rand, the ideas of panelists in response to question" what prerequisites are needed to establishing patients rights in hospitals" were collected and then a bill including 7 domain was developed and then entered in Delphi process. The comments of panelist were collected by E- Mail and face interview through April 2012 to September 2013. Final document was developed in the end of 4th rand. Results: A consensuses bill for establishing patient rights was main result of this study that developed in 82 items in 7 domains including: academic education, research, supervision, process management, building, organization and manpower. At al, out of 178 items that judged by panelist, finally 51 items (34.8%) consist many suggestion were agreed and entered in final document. Conclusion: Results of this study recognize the areas which need to takeover and correction in order to improve patients’ rights observance. In addition, the results showed that goal of bill of patients’ rights can be achieved with minimal cost and changes such as correcting organizational processes and empowering staff

Two Efficient Meta-Heuristic Algorithms for the Robust Inventory Routing Problem with Backhaul

The inventory routing problem (IRP) involves the integration and coordination of two components of the logistics value chain: inventory management and vehicle routing. Therefore, consideration of this issue can be effective in decision making of the organization and will lead to lower costs or other goals. Our objective in this article is to examine a new inventory-routing model and solve it with meta-heuristic methods. For more flexibility of the model, and approaching the real world, the model of this article is considered multi-period and multi-product. Also, two objective functions, including minimizing system costs and transportation risk, are included in this model. Given that the main parameter of the model, that is, demand, is uncertain, we have used a robust optimization approach to solve it, and since this model is in the classification of NP-Hard problems, we have used two meta-heuristic algorithms consisting of non-dominated sorting genetic algorithm (NSGA-II) and a multi-objective imperialist competitive algorithm (MOICA). By examining the model in two deterministic and robust conditions, according to two criteria, the mean values of the objective function and its standard deviation, it has been determined that in almost all cases, the robust optimization model produces better solutions. Also, between the two meta-heuristics method, the NSGA-II algorithm has shown better quality according to the mentioned criteria. Obviously, taking into account the different features of a model increases its efficiency. But this, obviously, makes the model even more complex. However, this complexity of models can work like a real system. Our attention in this article has been to this subject. To analyze such models, exact methods do not have the required performance and paying attention to heuristic and meta-heuristic methods is very effective. In this paper, a robust optimization and meta-heurictic approaches focus on these goals

Formulation and Evaluation of Lorazepam Orally Disintegrating Tablet

Introduction: oral dosage forms are the safest, the most convenient and the most economical method of drug delivery system in the pharmaceutical industry but, in geriatric and pediatric patients who have swallowing difficulty and in the emergency situations, we need the fastest therapeutic effects on conventional oral drug delivery because  of time issue. To troubleshoot? such problems a new dosage form known as orally disintegrating tablets (ODT) can be useful and more effective. Lorazepam is  a benzodiazepine drug that stimulates GABA receptor and is used in the prevention of panic attack, management of anxiety disorders, treatment of status epilepticus andetc. Based on these details, ODT form of Lorazepam can be helpful for geriatric and pediatric patients and also handling emergency situations. Methods and Results: In this study, various formulations were designed and prepared by using direct compression method. All of our formulations contained 2 mg of Lorazepam as API. We used 3 differences bulking agents (mannitol, lactose, avicel) and the percentages of disintegrating agent (5%, 10%, 15% of crosscarmelose).then, for examining our formulations and choosing the best formulation we carried out or conducted physicochemical tests like flowability of powder, tablet appearance, thickness, uniformity of weight, hardness, friability and disintegration time. Finally, one of these formulations (lactose as bulking agent and 10% crosscarmelose as disintegrating agent) which showed optimum physicochemical properties was selected for further studies. Conclusions:  regarding our study and literatures, we attempted to evaluate a novel formulation of Lorazepam ODT. physicochemical test results showed this formulation  ideal for developing new dosage forms of Lorazepam for resolving some of the patient's problems

Applications of Three-Dimensional Printing Technology in Radiotherapy

Nowadays, three-dimensional (3D) printing technology has been used for rapid prototyping of high quality printed objects. This technology has taken a special place in the field of medicine, and today this technology plays an important role, especially in the field of radiotherapy. Radiotherapy is a main option for treating and management of various types of cancers. Personalized radiotherapy requires precise details. For this reason, it is very important to carry out the exact treatment design at the clinical. 3D printing technology is considered a promising method that can be effective in the treatment of each person in a specific way and as a complementary and promising method to help in integrated treatment and special equipment for each patient. In this chapter, various applications of this technology in radiation therapy have been discussed. This narrative review summarizes the applications of 3D printing technology to develop patient-specific bolus, brachytherapy applicators, phantoms, filters, immobilization and grid therapy devices for more personalized radiation treatment

Computational Models for Predicting Shoe Friction and Wear

Slips and falls are a serious occupational and health problem. Insufficient friction between a shoe and flooring, quantified by the coefficient of friction (COF), increases the likelihood of slips and falls. Moreover, shoe’s slip-resistant properties change over its lifetime due to wear. This dissertation applies physics-based computational finite element modeling techniques to predict shoe-floor-contaminant friction. Computational models that simulate COF due to hysteresis are developed using multiscale methods. These models are used to assess the effects of shoe design factors and biomechanical parameters of human gait on the predicted COF. To address a gap in the literature regarding models that simulate shoe wear progression, this dissertation develops and validates an innovative finite element modeling process utilizing Archard’s law that predicts shoe wear. Models introduced in this dissertation not only increase the understanding of slips and falls but also offer a valuable tool that can be used in designing slip-resistant and durable shoes in order to achieve the ultimate goal of reducing slip and fall injuries

A Cooperative Resilience-Oriented Planning Framework for Integrated Distribution Energy Systems and Multi-Carrier Energy Microgrids Considering Energy Trading

Integrated distribution systems (IDSs) and multi-carrier energy microgrids (MCEMs) can play a crucial role in enhancing distribution energy systems’ overall efficiency and flexibility. By cascading energy usage and cooperating through energy trading, IDSs and MCEMs can reduce overall system costs and provide more flexibility for system operators. Adding resilience to the planning problem of IDSs can reduce planning costs in the long term, as proactive preparedness is key to coping with high-impact rare (HR) events. Adding resilience to the planning problem of IDSs can reduce the planning costs in the long term since proactive preparedness is a key necessity to cope with high-impact rare (HR) events. This paper proposes a resilience-oriented stochastic tri-level and two-stage cooperative expansion planning of IDSs and MCEMs, considering energy trading between IDSs and MCEMs. The first stage comprises two levels; the first level minimizes the investment and operation costs of IDSs and MCEMs, while the second level desires to maximize the energy exchange profit for MCEMs and thus reduce the overall costs. The second stage includes the third level problem involving two objective functions: resilience cost minimization and resilience index (RI) maximization. The multi-objective problem in the second stage is converted into a single-objective problem using the min–max regret method. The DC and AC configurations for the power distribution system (PDS) and power microgrids (PMGs) are studied to identify the optimal configuration of these networks in the expansion planning problem. A new framework is proposed based on an aggregator-agent splitting solution using the aggregator coupling coordinator unit (ACC) responsible for coordinating IDNs and MCEMs. The studied large-scale complex optimization problem is efficiently solved computationally by introducing a combined adaptive dynamic programming (ADP) and linearized alternating direction method of multipliers with parallel splitting (LADMMPSAP) algorithm. Three cases are studied to demonstrate the effectiveness of the proposed model and method. The results depict that MCEMs help reduce expansion planning costs and improve the system’s resilience. Adding resilience to the expansion planning problem enhances the resilience of the whole system and simultaneously reduces the costs by 2.7%. The expansion planning costs for the AC and DC configuration are close, and the AC is the optimal choice in all case studies. By increasing the planning horizon from 5 to 10 years, DC will be the optimal solution since network reinforcement costs and power losses are significantly lower.<br/