Empirical Modeling of Variance in Medium Frequency R-Mode Time-of-Arrival Measurements

The R-Mode system, an advanced terrestrial integrated navigation system, is designed to address the vulnerabilities of global navigation satellite systems (GNSS) and explore the potential of a complementary navigation system. This study aims to enhance the accuracy of performance simulation for the medium frequency (MF) R-Mode system by modeling the variance of time-of-arrival (TOA) measurements based on actual data. Drawing inspiration from the method used to calculate the standard deviation of time-of-reception (TOR) measurements in Loran, we adapted and applied this approach to the MF R-Mode system. Data were collected from transmitters in Palmi and Chungju, South Korea, and the parameters for modeling the variance of TOA were estimated.Comment: 4 pages, 2 figure

Anti-obesity effects of heat-transformed green tea extract through the activation of adipose tissue thermogenesis

Abstract Background Adipose tissue thermogenesis is a potential therapeutic target to increase energy expenditure and thereby combat obesity. The aim of the present study was to investigate the thermogenic and anti-obesity effects of heat-transformed green tea extract (HTGT) and enzymatically modified isoquercetin (EMIQ). Methods Immortalized brown pre-adipocytes and C3H10T1/2 cells were used for in vitro analyses. A high-fat diet (HFD)-induced obesity mouse model and CIDEA-reporter mice were used for in vivo experiments. The effects of HTGT and EMIQ on mitochondrial metabolism were evaluated by immunoblot, mitochondrial staining, and oxygen consumption rate analyses. In vivo anti-obesity effects of HTGT and EMIQ were measured using indirect calorimetry, body composition analyses, glucose tolerance tests, and histochemical analyses. Results Co-treatment with HTGT and EMIQ (50μg/mL each) for 48h increased brown adipocyte marker and mitochondrial protein levels (UCP1 and COXIV) in brown adipocytes by 2.9-fold, while the maximal and basal oxygen consumption rates increased by 1.57- and 1.39-fold, respectively. Consistently, HTGT and EMIQ treatment increased the fluorescence intensity of mitochondrial staining in C3H10T1/2 adipocytes by 1.68-fold. The combination of HTGT and EMIQ (100mg/kg each) increased the expression levels of brown adipocyte markers and mitochondrial proteins in adipose tissue. Two weeks of HTGT and EMIQ treatment (100mg/kg each) led to a loss of 3% body weight and 7.09% of body fat. Furthermore, the treatment increased energy expenditure by 8.95% and improved glucose tolerance in HFD-fed mice. Conclusions The current study demonstrated that HTGT and EMIQ have in vivo anti-obesity effects partly by increasing mitochondrial metabolism in adipocytes. Our findings suggest that a combination of HTGT and EMIQ is a promising therapeutic agent for the treatment of obesity and related metabolic diseases

Sustainable energy technologies for the Global South: Challenges and solutions toward achieving SDG 7

The United Nations (UN) expectations for 2030 account for a renewable, affordable, and eco-friendly energy future. The 2030 agenda includes 17 different Sustainable Development Goals (SDGs) for countries worldwide. In this work, the 7th SDG: Affordable and Clean Energy, is brought into focus. For this goal, five main challenges are discussed: (i) limiting the use of fossil fuels; (ii) migrating towards diversified and renewable energy matrices; (iii) decentralizing energy generation and distribution; (iv) maximizing energy and energy storage efficiency; and (v) minimizing energy generation costs of chemical processes. These challenges are thoroughly scrutinized and surveyed in the context of recent developments and technologies including energy planning and supervision tools employed in the Global South. The discussion of these challenges in this work shows that the realization of SDG 7, whether partially or in full, within the Global South and global contexts, is possible only if existing technologies are fully implemented with the necessary international and national policies. Among the key solutions identified in addressing the five main challenges of SDG 7 are a global climate agreement; increased use of non-fossil fuel energy sources; Global North assistance and investment; reformed global energy policies; smart grid technologies and real time optimization and automation technologies

Sustainable energy technologies for the Global South: challenges and solutions toward achieving SDG 7

The United Nations (UN) expectations for 2030 account for a renewable, affordable, and eco-friendly energy future. The 2030 agenda includes 17 different Sustainable Development Goals (SDGs) for countries worldwide. In this work, the 7th SDG: Affordable and Clean Energy, is brought into focus. For this goal, five main challenges are discussed: (i) limiting the use of fossil fuels; (ii) migrating towards diversified and renewable energy matrices; (iii) decentralizing energy generation and distribution; (iv) maximizing energy and energy storage efficiency; and (v) minimizing energy generation costs of chemical processes. These challenges are thoroughly scrutinized and surveyed in the context of recent developments and technologies including energy planning and supervision tools employed in the Global South. The discussion of these challenges in this work shows that the realization of SDG 7, whether partially or in full, within the Global South and global contexts, is possible only if existing technologies are fully implemented with the necessary international and national policies. Among the key solutions identified in addressing the five main challenges of SDG 7 are a global climate agreement; increased use of non-fossil fuel energy sources; Global North assistance and investment; reformed global energy policies; smart grid technologies and real time optimization and automation technologies

Excitation Intensity Dependent Carrier Dynamics of Chalcogen Heteroatoms in Medium-Bandgap Polymer Solar Cells

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Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A GPU Scheduling Framework to Accelerate Hyper-Parameter Optimization in Deep Learning Clusters

This paper proposes Hermes, a container-based preemptive GPU scheduling framework for accelerating hyper-parameter optimization in deep learning (DL) clusters. Hermes accelerates hyper-parameter optimization by time-sharing between DL jobs and prioritizing jobs with more promising hyper-parameter combinations. Hermes’s scheduling policy is grounded on the observation that good hyper-parameter combinations converge quickly in the early phases of training. By giving higher priority to fast-converging containers, Hermes’s GPU preemption mechanism can accelerate training. This enables users to find optimal hyper-parameters faster without losing the progress of a container. We have implemented Hermes over Kubernetes and compared its performance against existing scheduling frameworks. Experiments show that Hermes reduces the time for hyper-parameter optimization up to 4.04 times against previously proposed scheduling policies such as FIFO, round-robin (RR), and SLAQ, with minimal time-sharing overhead

Development and Performance Analysis of Soil Flow Protector to Reduce Soft Soil Settlement Caused by Cavity Formation

Settlement of a relatively small magnitude occurs in box structures supported by pile foundations. However, if cavities are generated under the box structure, ground settlement can be accelerated by surrounding soil entering the cavities. In order for the structure to maintain stability for a long period of time, sustainable development to maintain the stability of the building must be continued. Preventing rapid ground settlement can lead to long-term structural stability and prevent the occurrence of life-threatening damage, thereby helping to maintain and build a sustainable urban infrastructure. Thus, in this study, a soil flow protector (SFP) that can be easily installed on the sides of the structure was developed to mitigate the aforementioned problem. Field tests and numerical analysis were performed to investigate the effect of SFP installation on structural stability and settlement reduction. After performing field experiments, it was found that SFP installation could reduce ground settlement and ground horizontal displacement. Moreover, for a 79.9-mm settlement, the safety factor was 1.315, which remained stable even when the settlement reached 345 mm. Hence, the developed SFP can be used to reduce soft ground settlement affecting box structures supported by pile foundations