Comprehensive planning for classification and disposal of solid waste at the industrial parks regarding health and environmental impacts

The aim of this study is the comprehensive planning for integrated management of solid waste at the industrial parks. The share of each industrial group including food, metal, chemical, non-metallic minerals, textile, electrical and electronical, and cellulose industries were 48.2, 14.9, 6.7, 22, 0.9, 0.6, and 6.5 percent, respectively. The results showed that nearly half of total industrial waste produced from the range of biological materials are biodegradable and discharging them without observing environmental regulations leads to short-term pollution and nuisance in the acceptor environment. Also some parts of case study waste were recyclable which is considerable from viewpoint of economical and environmental pollution. Long-term impacts will appear due to improper site selection of disposal from the spatial standpoint. In this way, an approach for site selection using several socioeconomic, physical, and environmental criteria based on multicriteria decision making model (MCDM) is introduced. Health risks and environment pollution such as soil and surface water may be done. It is essential to revise the studied industries layout, particularly those units which produce special waste which should be more cautious. Also stricter enforcement is required as an effective step in reducing the harmful impacts of it. © 2014 Hassan Hashemi et al

A two-stage method for assessing the efficiency of the three-stage series network data envelopment analysis model with two feedback

Data envelopment analysis models play an important role in decision making. In this paper, one-stage and two-stage nonlinear programming problems are investigated in order to evaluate the efficiency of two types of network data envelopment analysis model. The first type of network data envelopment analysis model has a series structure with three stages and a feedback between the last step and the middle step, the second model has a three-stage series structure with two feedback between the final step and the first step and the middle step. By examining the overall efficiency of the models based on the one-stage programming problem, a two-stage programming problem is also applied in order to evaluate the efficiency of each step. In order to solve one-stage nonlinear programming problems and two-stage linear and nonlinear programming problems derived from modeling, a linearization method based on coordinate transformation, and constant assumption and gradual growth of some variables is presented. In the last section, the proposed methods have been discussed using some numerical examples

Comparison of Intravenous Metoclopramide and Acetaminophen in Primary Headaches: a Randomized Controlled Trial

Introduction: Headache is the most common neurologic symptom among referees to the emergency department (ED), while the best treatment has not yet been found. Therefore, in the present study pain relief effects of metoclopramide and acetaminophen were compared in patients suffered acute primary headache. Methods: This study was a double-blind randomized clinical trial performed in Imam Khomeini Hospital, Urmia, Iran, through July to October 2014.  All adult patients, with acute primary (migraine, tension type and cluster) headache referred to the ED were included in this study. Pain Severity was measured with 10 centimeters numeric rating scales. The patients were randomized in to two groups of intravenous (IV) metoclopramide (10 milligrams) and acetaminophen (1 gram). Pain score, success rate, and complication of drugs were compared within administration time and 15, 30, 60, as well as 120 minutes after medication. Results: 100 patients were equally categorized in to two groups (mean age of 32 ± 13.2 years; 51.2% male). Initial pain score in metoclopramide and acetaminophen groups were 9.1 and 9.4, respectively (p=0.46). IV metoclopramide did not have any analgesic effect at 15 minutes, but had good effect at 30 minutes. While, the analgesic effect of acetaminophen initiated after 15 minutes. After 2 hours, both drugs had good treatment effect on primary headaches (p<0.001). Conclusion: The present study demonstrated that efficacy of metoclopramide for pain relief in primary headaches is lower than acetaminophen.  In this regard, success rate of acetaminophen was 42.0% versus 0% for metoclopramide within 15 minutes. The efficacy of acetaminophen continued until 60 minutes

Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing

Health monitoring applications increasingly rely on machine learning techniques to learn end-user physiological and behavioral patterns in everyday settings. Considering the significant role of wearable devices in monitoring human body parameters, on-device learning can be utilized to build personalized models for behavioral and physiological patterns, and provide data privacy for users at the same time. However, resource constraints on most of these wearable devices prevent the ability to perform online learning on them. To address this issue, it is required to rethink the machine learning models from the algorithmic perspective to be suitable to run on wearable devices. Hyperdimensional computing (HDC) offers a well-suited on-device learning solution for resource-constrained devices and provides support for privacy-preserving personalization. Our HDC-based method offers flexibility, high efficiency, resilience, and performance while enabling on-device personalization and privacy protection. We evaluate the efficacy of our approach using three case studies and show that our system improves the energy efficiency of training by up to $45.8\times$ compared with the state-of-the-art Deep Neural Network (DNN) algorithms while offering a comparable accuracy

Edge-centric Optimization of Multi-modal ML-driven eHealth Applications

Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics. Smart eHealth applications sense input data from multiple modalities, transmit the data to edge and/or cloud nodes, and process the data with compute intensive machine learning (ML) algorithms. Run-time variations with continuous stream of noisy input data, unreliable network connection, computational requirements of ML algorithms, and choice of compute placement among sensor-edge-cloud layers affect the efficiency of ML-driven eHealth applications. In this chapter, we present edge-centric techniques for optimized compute placement, exploration of accuracy-performance trade-offs, and cross-layered sense-compute co-optimization for ML-driven eHealth applications. We demonstrate the practical use cases of smart eHealth applications in everyday settings, through a sensor-edge-cloud framework for an objective pain assessment case study

Diode Laser in Minor Oral Surgery: A Case Series of Laser Removal of Different Benign Exophytic Lesions

Introduction: The role of laser in conservative management of oral disease is well established. Laser procedures are common in the fields of oral surgery, implant dentistry, endodontic, and periodontic therapy.Case: This case series describes the use of diode laser for the excision of oral exophytic lesions. All the patients attended the oral medicine department of Shahid Beheshti University of Medical Sciences, Tehran, Iran. Criteria in patient selection were accessibility to lesions, patient fear from blade surgery, aesthetics, and probability of bleeding. An informed consent was filled by every patient. All of the lesions were completely excised under local anaesthesia by diode laser with 300 μm-fibre tip, 808 nm continuous wavelength and 3-3.5 W power for 3×60 seconds (Dr Smile, Italia). During surgery, the fibre tip was in contact with lesions. No analgesics were prescribed to the patients. The patients were followed for the first, second, and forth week after treatment.Conclusion: The lesions could be excised using the diode laser. This procedure was a quick clinical technique without bleeding

Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images

BACKGROUND: Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images. METHODS: A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR. RESULTS: A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P \u3c .001; κ = 0.806; P \u3c .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P \u3c .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less. CONCLUSION: A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia

High-dose vitamin D supplementation is associated with an improvement in several cardio-metabolic risk factors in adolescent girls: a nine-week follow up study

Background: Vitamin D deficiency is a prevalent and important global health problem. Because of its role in growth and development, vitamin D status is likely to be particularly important in adolescent girls. Here we explored the effects of high-dose vitamin D supplementation on cardiometabolic risk factors. Methods: We have examined the effects of vitamin D supplementation on cardio-metabolic risk factors in 988 healthy adolescent girls in Iran. Fasting blood samples and anthropometric measurements were obtained at baseline and after supplementation with high dose vitamin D. All individuals took a capsule of 50000 IU vitamin D/ week for nine weeks. The study was completed by 940 participants. Results: the prevalence of vitamin D deficiency was 90% at baseline, reducing to16.3% after vitamin D supplementation. Vitamin supplementation was associated with a significant increase in serum levels of 25 (OH) vitamin D and calcium. There were significant reductions in diastolic blood pressure, heart rate, waist circumference, and serum fasting blood glucose, total- and low density lipoprotein-cholesterol after the nine-week period on vitamin D treatment, but no significant effects were observed on body mass index, systolic blood pressure, or serum high density lipoprotein-cholesterol and triglyceride. Conclusion: vitamin D supplementation had beneficial effects on cardio-metabolic profile in adolescent girls

Predication of steady-state thermal characteristics of a resistance spot welding transformer in battery manufacturing application

This paper introduces a novel finite-element-method-based model designed to analyze the electromagnetic–thermal dynamics of resistance spot welding (RSW) transformers used in battery manufacturing. The RSW process, inherently multiphysics and sensitive to temperature fluctuations, involves phase changes within the metal materials. This complexity, combined with frequent electrode connections and disconnections during welding (variable structure), renders traditional steady-state analysis methods inadequate for accurately capturing temperature and electromagnetic parameters under thermal steady-state conditions, and the effect of changing power electronics parameters (frequency, number of cycles, and firing angle) on continuous operation is also unpredictable. The article proposes a method capable of determining temperature trends during electrode opening (rest period). It simplifies the temperature characteristics and material properties of the welding spot. These variations are equated and simplified as a constant temperature and an equivalent material, respectively. The proposed model, rooted in finite-element analysis and experimentally validated, enables a bidirectional electromagnetic–thermal simulation through steady-state thermal analysis. This simulation generates results for temperature and electromagnetic values during steady-state operation, demonstrating close agreement with experimental results. Consequently, the developed model showcases its capability in predicting the impacts and sensitivities of various factors, such as voltage cycle number, firing angle, and rest period duration within the RSW process

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