Mortality of emergency abdominal surgery in high-, middle- and low-income countries

Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low- or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI). Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression. Results: Data were obtained for 10 745 patients from 357 centres in 58 countries; 6538 were from high-, 2889 from middle- and 1318 from low-HDI settings. The overall mortality rate was 1⋅6 per cent at 24 h (high 1⋅1 per cent, middle 1⋅9 per cent, low 3⋅4 per cent; P < 0⋅001), increasing to 5⋅4 per cent by 30 days (high 4⋅5 per cent, middle 6⋅0 per cent, low 8⋅6 per cent; P < 0⋅001). Of the 578 patients who died, 404 (69⋅9 per cent) did so between 24 h and 30 days following surgery (high 74⋅2 per cent, middle 68⋅8 per cent, low 60⋅5 per cent). After adjustment, 30-day mortality remained higher in middle-income (odds ratio (OR) 2⋅78, 95 per cent c.i. 1⋅84 to 4⋅20) and low-income (OR 2⋅97, 1⋅84 to 4⋅81) countries. Surgical safety checklist use was less frequent in low- and middle-income countries, but when used was associated with reduced mortality at 30 days. Conclusion: Mortality is three times higher in low- compared with high-HDI countries even when adjusted for prognostic factors. Patient safety factors may have an important role. Registration number: NCT02179112 (http://www.clinicaltrials.gov)

Power and Thermal Modeling

The Tegra is a processor made by Nvidia which is used in many mobile applications. In designing advanced digital systems like the Tegra processor, it is essential to perform detailed simulations to understand and optimize the behaviors of many aspects of the chip. Specifically, power and thermal considerations are two co-dependent parameters that must be understood during the design phase. This project developed a flow to import existing power and thermal models of the Tegra processor into a new software package from Docea Power that integrated the power and thermal domains for simulations and architectural analysis

EMS Communication Systems Data Analysis

The exponential growth of the human population requires an increasingly efficient EMS infrastructure and service. The purpose of this project was to examine and analyze various aspects of the EMS communication system within the United States of America, and identify areas that could be improved. Current operation and maintenance of EMS communication system were investigated, including input and retrieval of information, data storage, infrastructure and modes of communication. Areas for improvement were recognized, and feasible solutions that could improve time response, were researched. A medical database was developed to store and retrieve patient information and delay differential equations were formulated to reduce system dynamic delays

Power and Thermal Modeling

The Tegra is a processor made by Nvidia which is used in many mobile applications. In designing advanced digital systems like the Tegra processor, it is essential to perform detailed simulations to understand and optimize the behaviors of many aspects of the chip. Specifically, power and thermal considerations are two co-dependent parameters that must be understood during the design phase. This project developed a flow to import existing power and thermal models of the Tegra processor into a new software package from Docea Power that integrated the power and thermal domains for simulations and architectural analysis

A Construction of High Performance Quasicyclic LDPC Codes: A Combinatoric Design Approach

This correspondence presents a construction of quasicyclic (QC) low-density parity-check (LDPC) codes based on a special type of combinatorial designs known as block disjoint difference families (BDDFs). The proposed construction of QC-LDPC codes gives parity-check matrices with column weight three and Tanner graphs having a girth lower-bounded by 6. The proposed QC-LDPC codes provide an excellent performance with iterative decoding over an additive white Gaussian-noise (AWGN) channel. Performance analysis shows that the proposed short and moderate length QC-LDPC codes perform as well as their competitors in the lower signal-to-noise ratio (SNR) region but outperform in the higher SNR region. Also, the codes constructed are quasicyclic in nature, so the encoding can be done with simple shift-register circuits with linear complexity

TEZEM: A new energy-efficient routing protocol for next-generation wireless sensor networks

The design and implementation of energy-efficient routing protocols for next-generation wireless sensor networks is always a challenge due to limited power resource capabilities. Hierarchical (clustering) routing protocols appeared to be a remarkable solution for extending the lifetime of wireless sensor networks, particularly in application-aware (threshold-sensitive) and heterogeneity-aware cluster-based routing protocols. In this article, we propose a protocol, namely, Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol. It is a heterogeneity-aware and threshold-based protocol that provides a better solution to existing problems in next-generation wireless sensor networks. During execution, the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol splits the entire network area into several zones to manage network traffic efficiently. In the first step, Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol is designed for a homogeneous network where the initial energy of all the nodes is the same. Thereafter, we bring in heterogeneity in the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol execution environment to optimize its energy consumption. By investigating the performance of the various numbers of divisions, it is proved that the Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol with 9 zonal divisions has higher stability and throughput. The performance of the proposed Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol is compared with those of Stable Election Protocol, Low-Energy Adaptive Clustering Hierarchy, Modified Low-Energy Adaptive Clustering Hierarchy, and Gateway-Based Energy-Efficient Routing Protocol through computer simulations. Simulation results verify the improved performance of the proposed Threshold-based Energy-aware Zonal Efficiency Measuring hierarchical routing protocol in terms of network stability, lifetime, and throughput

Non-stationary 3-D GBSM channel model for V2Vcommunications

The spatial characteristics of the propagation channel have a considerable impact onthe applicability of multi-antenna systems. In this paper, a non-stationary 3-D GBSMvehicle-to-vehicle channel model is proposed in the tunnel environment based on massivemultiple-input multiple-output antenna arrays. Instead of the plane wavefront assumptionsutilized in traditional multiple-input multiple-output systems, the proposed channel modelfor vehicle-to-vehicle communications uses spherical wavefront assumptions. Initially, thechannel impulse response and closed-form expression for the probability density func-tion of angle-of-departure and angle-of-arrival are derived in the elevation and azimuthplanes. Following that, due to the mobility of transmitting and receiving antenna arrays,expressions for the delay spread (DS), Doppler power spectrum density, temporal cross-correlation function, and channel capacity are extracted by examining line of sight andthe non line of sight propagation paths. The influence of numerous model parameterson the temporal cross-correlation function is also investigated, including antenna arrayspacing,K-factor, movement velocity, and time separation. The proposed 3-D model’s sta-tistical characteristics are verified through measurements, simulations, and analytical results,revealing its adaptability and effectiveness in the high-speed-train environment

Phytochemical Composition and Pharmacological Potential of Lemongrass (Cymbopogon) and Impact on Gut Microbiota

Phytochemicals are versatile plant secondary metabolites with therapeutic properties. In this review, we explore lemongrass&rsquo;s phytochemistry and pharmacological potential (Cymbopogon) as well as its impact on gut microbiota. Lemongrass is well-known for its antioxidant, anti-microbial, anti-inflammatory, anti-hypertensive, anti-diabetic, anti-mutagenicity, anxiolytic properties, and for its hypoglycemic and hypolipidemic activities. Therefore, it is widely used in pharmaceuticals, food, feed, and the cosmetics industry. Lemongrass contains phenolic metabolites (including phenolic acids, flavonoids, stilbenes, and lignans), terpenoids, and alkaloids, which are potent bioactive ingredients. Lemongrass is a precious medicinal plant. Furthermore, lemongrass phytochemicals are considered potential agents to improve health by establishing a balanced gut ecosystem. Lemongrass is considered a quintessential food and feed additive at the industrial level, since there are no issues with residue or toxins. Lemongrass powder and essential oils are used to modulate the gut ecosystem by generating anti-microbial, anti-inflammatory, and antioxidant responses, increasing the optimum nutrient absorption in the gut system. This review will further explore lemongrass&rsquo;s phytochemical, pharmacological, and therapeutic potential

Phytochemical Composition and Pharmacological Potential of Lemongrass (Cymbopogon) and Impact on Gut Microbiota

Phytochemicals are versatile plant secondary metabolites with therapeutic properties. In this review, we explore lemongrass’s phytochemistry and pharmacological potential (Cymbopogon) as well as its impact on gut microbiota. Lemongrass is well-known for its antioxidant, anti-microbial, anti-inflammatory, anti-hypertensive, anti-diabetic, anti-mutagenicity, anxiolytic properties, and for its hypoglycemic and hypolipidemic activities. Therefore, it is widely used in pharmaceuticals, food, feed, and the cosmetics industry. Lemongrass contains phenolic metabolites (including phenolic acids, flavonoids, stilbenes, and lignans), terpenoids, and alkaloids, which are potent bioactive ingredients. Lemongrass is a precious medicinal plant. Furthermore, lemongrass phytochemicals are considered potential agents to improve health by establishing a balanced gut ecosystem. Lemongrass is considered a quintessential food and feed additive at the industrial level, since there are no issues with residue or toxins. Lemongrass powder and essential oils are used to modulate the gut ecosystem by generating anti-microbial, anti-inflammatory, and antioxidant responses, increasing the optimum nutrient absorption in the gut system. This review will further explore lemongrass’s phytochemical, pharmacological, and therapeutic potential