Search

The potential of the combined application of Cloud computing and the fifth generation of cellular network technology (5G) in Smart Grid (SG) could be revolutionary in terms of empowering the Advanced Metering Infrastructure (AMI). The model of a real-time 5G-based communication system for remote reading of Smart Meters’ data is developed and presented in this paper. Online monitoring of power demand has been performed using the Cloud-based platform ThingSpeak. The proposed 5G communication model and online monitoring function have been tested and validated using a power demand variation scenario in a well-known IEEE 13 node network. The obtained results confirm the model accuracy and reveal the potential of AMI based on real-time data transmission between Smart meters (SM) and Cloud computing platform using a 5G communication network.

This study is focused on the application of high-voltage electric discharge (HVED) to recover some bioactive compounds from the cocoa bean shell. Different extraction times (30, 60, 90 min), frequencies (40, 70, 100 Hz) and solvent-solid ratios (10, 30 and 50 mL g–1) were used to obtain cocoa bean shell extracts. Desired bioactive compounds, methylxanthines and phenolic compounds were measured in obtained extracts by high-pressure liquid chromatography with diode array detector. The obtained extracts showed that theobromine was the most abundant, ranging from 2530.13 to 6031.51 mg kg–1, while caffeine content was in the range from 316.08 to 849.88 mg kg–1. In addition, significant amounts of phenolic compounds were found, namely catechin (115.91 to 284.33 mg kg–1), epicatechin (20.20 to 358.90 mg kg–1), and gallic acid (80.28 to 219.17 mg kg–1). Results showed that different parameters of HVED extraction have statistically significant influence on cocoa bean shell composition, suggesting how this byproduct can be used in the production of valuable extracts.

Cough, a symptom associated with many prevalent respiratory diseases, can serve as a potential biomarker for diagnosis and disease progression. Consequently, the development of cough monitoring systems and, in particular, automatic cough detection algorithms have been studied since the early 2000s. Recently, there has been an increased focus on the efficiency of such algorithms, as implementation on consumer-centric devices such as smartphones would provide a scalable and affordable solution for monitoring cough with contact-free sensors. Current algorithms, however, are incapable of discerning between coughs of different individuals and, thus, cannot function reliably in situations where potentially multiple individuals have to be monitored in shared environments. Therefore, we propose a weakly supervised metric learning approach for cougher recognition based on smartphone audio recordings of coughs. Our approach involves a triplet network architecture, which employs convolutional neural networks (CNNs). The CNNs of the triplet network learn an embedding function, which maps Mel spectrograms of cough recordings to an embedding space where they are more easily distinguishable. Using audio recordings of nocturnal coughs from asthmatic patients captured with a smartphone, our approach achieved a mean accuracyof 88 % ( ± 10 % SD) on two-way identification tests with 12 enrollment samples and accuracy of 80 % and an equal error rate (EER) of 20 % on verification tests. Furthermore, our approach outperformed human raters with regard to verification tests on average by 8% in accuracy, 4% in false acceptance rate (FAR), and 12% in false rejection rate (FRR). Our code and models are publicly available.

A female patient aged 42, started chemotherapy for advanced ovarian carcinoma in June 2016. Considering intraoperative findings, cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (HIPEC) were performed, followed by adjuvant chemotherapy. In March 2018, computed tomography (CT) examination showed disease progression in the form of pleural carcinomatosis with increased levels of tumor markers. In April 2018, total parietal pleurectomy, partial visceral pleurectomy, and then hyperthermic intrathoracic chemotherapy (HITHOC) with cisplatin were performed. The procedure was uneventful, as was the postoperative course. The patient was discharged on the 13th postoperative day with no major postoperative complications. Three months after surgery, CT showed no signs of disease relapse. Since this is a relatively new method of treating pleural carcinomatosis, real results are to be expected with larger series of patients and longer postoperative follow-up.

Purpose: Presence of metastasis in sentinel lymph node (SLN) is considered to be the most important factor in terms of patient survival. The main aim of this study was to identify predictors of positive SLN in Serbian patients with melanoma., Methods: This retrospective study was conducted on 147 patients. Univariate chi-square and univariate logistic regression analyses were used to identify the association between prognostic factors and positive SLN. Receiver Operating Characteristics (ROC) was conducted to find the Breslow thickness cutoff point at which to perform SLN biopsy (SLNB). Kaplan-Meier analysis was used to evaluate disease-free survival (DFS), and log rank test was applied to compare differences between groups., Results: Breslow thickness and Clark level (p≤0.05), presence of ulceration and a high mitotic rate (>6 mitoses/mm 2 ) (p<0.001) were significant independent predictors of SLN metastasis. ROC curve showed that Breslow thickness of 2.8 mm was the most suitable cutoff point for SLN positivity (sensitivity 86%, specificity 67%). Furthermore, Breslow thickness and presence of ulceration were found to be associated with DFS (p<0.05)., Conclusions: Patients with Breslow thickness ≥2.8 mm, ulceration, and high mitotic rate are at higher risk for SLN metastasis. In addition, high Breslow thickness and presence of ulceration are associated with decreased DFS. These results indicate that multiple selection criteria should be used when performing and predicting SLN metastasis and disease recurrence.

Purpose: The effectiveness of barcode-assisted medication preparation (BCMP) technology on detecting oral liquid dose preparation errors., Methods: From June 1, 2013, through May 31, 2014, a total of 178,344 oral doses were processed at Children's Mercy, a 301-bed pediatric hospital, through an automated workflow management system. Doses containing errors detected by the system's barcode scanning system or classified as rejected by the pharmacist were further reviewed. Errors intercepted by the barcode-scanning system were classified as (1) expired product, (2) incorrect drug, (3) incorrect concentration, and (4) technological error. Pharmacist-rejected doses were categorized into 6 categories based on the root cause of the preparation error: (1) expired product, (2) incorrect concentration, (3) incorrect drug, (4) incorrect volume, (5) preparation error, and (6) other., Results: Of the 178,344 doses examined, 3,812 (2.1%) errors were detected by either the barcode-assisted scanning system (1.8%, n = 3,291) or a pharmacist (0.3%, n = 521). The 3,291 errors prevented by the barcode-assisted system were classified most commonly as technological error and incorrect drug, followed by incorrect concentration and expired product. Errors detected by pharmacists were also analyzed. These 521 errors were most often classified as incorrect volume, preparation error, expired product, other, incorrect drug, and incorrect concentration., Conclusion: BCMP technology detected errors in 1.8% of pediatric oral liquid medication doses prepared in an automated workflow management system, with errors being most commonly attributed to technological problems or incorrect drugs. Pharmacists rejected an additional 0.3% of studied doses., (Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.)

Purpose: To analyze the correlation of primary tumor (PT) pathological characteristics (size, stage, type and grade) and the extent of initial surgical treatment of non small cell lung cancer (NSCLC) with the incidence and time to local recurrence (LR) and disease-free survival (DFS), as well as to determine in what way these parameters and LR localizations affect the possibility for surgical retreatment., Methods: The research was conducted on 114 patients with NSCLC and LR that had initial surgery in two reference institutes in Serbia from January 2002 to December 2010. PT size and disease stage were defined according to the revised 2004 WHO classification. PTs were grouped by size into 3 categories. Due to great diversity, surgical procedures were sorted into 6 operation types. Standard statistical methods and tests were used for data analysis., Results: Statistical analyses showed significant difference in DFS and LR reoperability that were related to PT size, disease stage and the extent of initial surgery. LR localization on the chest wall was favorable for secondary surgery due to LR., Conclusions: Squamous cell lung carcinoma relapses locally more frequently than other lung tumor types, and the commonest LR site is the chest wall. This localization provides high possibility for surgical retreatment. Adequate staging, proper indications for surgical treatment and quality surgery provide longer DFS in patients with NSCLC. All these suggest that the surgeon may be considered as the most significant factor of prognosis.