FPGA Hardware Implementation of DOA Estimation Algorithm Employing LU Decomposition

In this paper, authors present their work on field-programmable gate array (FPGA) hardware implementation of proposed direction of arrival estimation algorithms employing LU factorization. Both L and U matrices were considered in computing the angle estimates. Hardware implementation was done on a Virtex-5 FPGA and its experimental verification was performed using National Instruments PXI platform which provides hardware modules for data acquisition, RF down-conversion, digitization, etc. A uniform linear array consisting of four antenna elements was deployed at the receiver. LabVIEW FPGA modules with high throughput math functions were used for implementing the proposed algorithms. MATLAB simulations of the proposed algorithms were also performed to validate the efficacy of the proposed algorithms prior to hardware implementation of the same. Both MATLAB simulation and experimental verification establish the superiority of the proposed methods over existing methods reported in the literature, such as QR decomposition-based implementations. FPGA compilation results report low resource usage and faster computation time compared with the QR-based hardware implementation. Performance comparison in terms of estimation accuracy, percentage resource utilization, and processing time is also presented for different data and matrix sizes

A Machine Learning-Based Communication-Free PV Controller for Voltage Regulation

Due to the recent advancements in the manufacturing process of solar photovoltaics (PVs) and electronic converters, solar PVs has emerged as a viable investment option for energy trading. However, distribution system with large-scale integration of rooftop PVs, would be subjected to voltage upper limit violations, unless properly controlled. Most of the traditional solutions introduced to address this problem do not ensure fairness amongst the on-line energy sources. In addition, other schemes assume the presence of communication linkages between these energy sources. This paper proposes a control scheme to mitigate the over-voltages in the distribution system without any communication between the distributed energy sources. The proposed approach is based on artificial neural networks that can utilize two locally obtainable inputs, namely, the nodal voltage and node voltage sensitivity and control the PV power. The controller is trained using extensive data generated for various loading conditions to include daily load variations. The control scheme was implemented and tested on a 12.47 kV feeder with 85 households connected on the 220 V distribution system. The results demonstrate the fair control of all the rooftop solar PVs mounted on various houses to ensure the system voltage are maintained within the allowed limits as defined by the ANSI C84.1-2016 standard. Furthermore, to verify the robustness of the proposed PV controller, it is tested during cloudy weather condition and the impact of integration of electric vehicles on the proposed controller is also analyzed. The results prove the efficacy of the proposed controller

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research