Improving Age of Information with Interference Problem in Long-Range Wide Area Networks

Low Power Wide Area Networks (LPWAN) offer a promising wireless communications technology for Internet of Things (IoT) applications. Among various existing LPWAN technologies, Long-Range WAN (LoRaWAN) consumes minimal power and provides virtual channels for communication through spreading factors. However, LoRaWAN suffers from the interference problem among nodes connected to a gateway that uses the same spreading factor. Such interference increases data communication time, thus reducing data freshness and suitability of LoRaWAN for delay-sensitive applications. To minimize the interference problem, an optimal allocation of the spreading factor is requisite for determining the time duration of data transmission. This paper proposes a game-theoretic approach to estimate the time duration of using a spreading factor that ensures on-time data delivery with maximum network utilization. We incorporate the Age of Information (AoI) metric to capture the freshness of information as demanded by the applications. Our proposed approach is validated through simulation experiments, and its applicability is demonstrated for a crop protection system that ensures real-time monitoring and intrusion control of animals in an agricultural field. The simulation and prototype results demonstrate the impact of the number of nodes, AoI metric, and game-theoretic parameters on the performance of the IoT network

Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes

This paper analyzes the cross-quantile dependence and causality between non-ferrous metals and clean energy indices by employing data from November 2003 to May 2019. Specifically, we utilize the time-varying copulas to examine the asymmetric connectedness among the assets. Based on the assessed dependence, we utilize the time-static and time-varying cross-quantilogram approach to evaluate the asymmetric dependence across different quantiles. Finally, we employ a Granger-causality in quantiles analysis to assess the causal relationship across different quantiles of the return distributions of the underlying assets. By utilizing time-varying copulas, we report that the conditional dependence between the assets is time-varying and asymmetric with the potential for tail dependence. Our results from the cross-quantilogram analysis provide further evidence that the interconnectedness is asymmetric across quantiles, and it increases with the increase in lags. In addition, we report that extreme market conditions positively influence the dependence structure. Finally, our findings from Granger-causality in quantiles indicate bidirectional causality among assets that intensifies with the increase in lag order. These findings are important for governmental policies that aim at mitigating the impact of climate change by transforming the global energy landscape towards clean and renewable energy sources.©2020 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

An Energy Efficient Smart Metering System using Edge Computing in LoRa Network

An important research issue in smart metering is to correctly transfer the smart meter readings from consumers to the operator within the given time period by consuming minimum energy. In this paper, we propose an energy efficient smart metering system using Edge computing in Long Range (LoRa). We assume that all appliances in a house are connected to a smart meter that is affixed with Edge device and LoRa node for processing and transferring the processed smart meter readings, respectively. The energy consumption of the appliances can be represented as an energy multivariate time series. The system first proposes a deep learning-based compression-decompression model for reducing the size of the energy time series at the Edge devices. Next, it formulates an optimization problem for finding the suitable compressed energy time series to reduce the energy consumption and delay of the system. Finally, the system presents an algorithm for selecting the suitable spreading factors to transfer the compressed time series to the operator in the given time. Our simulation and prototype results demonstrate the impact of the parameters of the compression model, network, and the number of smart meters and appliances on delay, energy consumption, and accuracy of the system

Dydrogesterone usage pattern in India: a knowledge, attitude and practice survey among Indian gynaecologists

Background: There is limited data about the knowledge, perception, and routine clinical usage pattern of dydrogesterone among medical practitioners in India. Therefore, the present survey was undertaken to assess attitudes and perception/practices of obstetrician and gynaecologists towards use of dydrogesterone in the real-life setting.Methods: Total 1168 gynaecologists across India participated in the KAP survey. Sixteen questions which explored indications, dosages, duration, efficacy, tolerability and comparison were asked and results were expressed as percentages.Results: Dydrogesterone has been marketed since the 1960s and has been extensively used worldwide for the treatment of threatened miscarriage (TM) and recurrent miscarriage (RM). Dydrogesterone is approved for hormone replacement therapy (HRT), as well as pregnancy and non-pregnancy-related conditions where there is a progesterone deficiency. In the present survey, dydrogesterone 10 mg twice daily was found to be the most commonly preferred dosage by 823 (73%) gynaecologists. Poor tolerability, compliance and lower efficacy were reported as major limitations of micronized progesterone by 68% of doctors. The average clinical pregnancy rate noted at 12 weeks after Dydrogesterone usage was around 40% by majority of the doctors. However, 30% of doctors noted more than 40% of clinical pregnancy rate after dydrogesterone usage. Almost 35% of doctors reported that the average live birth rate noticed after dydrogesterone usage is around 40%.Conclusions: The present KAP survey highlights that the effectiveness and the tolerability of dydrogesterone is valued by Indian gynaecologists which accounts for its robust clinical utility

Glycosylation of Erythrocyte Spectrin and Its Modification in Visceral Leishmaniasis

Using a lectin, Achatinin-H, having preferential specificity for glycoproteins with terminal 9-O-acetyl sialic acid derivatives linked in α2-6 linkages to subterminal N-acetylgalactosamine, eight distinct disease-associated 9-O-acetylated sialoglycoproteins was purified from erythrocytes of visceral leishmaniaisis (VL) patients (RBCVL). Analyses of tryptic fragments by mass spectrometry led to the identification of two high-molecular weight 9-O-acetylated sialoglycoproteins as human erythrocytic α- and β-spectrin. Total spectrin purified from erythrocytes of VL patients (spectrinVL) was reactive with Achatinin-H. Interestingly, along with two high molecular weight bands corresponding to α- and β-spectrin another low molecular weight 60 kDa band was observed. Total spectrin was also purified from normal human erythrocytes (spectrinN) and insignificant binding with Achatinin-H was demonstrated. Additionally, this 60 kDa fragment was totally absent in spectrinN. Although the presence of both N- and O-glycosylations was found both in spectrinN and spectrinVL, enhanced sialylation was predominantly induced in spectrinVL. Sialic acids accounted for approximately 1.25 kDa mass of the 60 kDa polypeptide. The demonstration of a few identified sialylated tryptic fragments of α- and β-spectrinVL confirmed the presence of terminal sialic acids. Molecular modelling studies of spectrin suggest that a sugar moiety can fit into the potential glycosylation sites. Interestingly, highly sialylated spectrinVL showed decreased binding with spectrin-depleted inside-out membrane vesicles of normal erythrocytes compared to spectrinN suggesting functional abnormality. Taken together this is the first report of glycosylated eythrocytic spectrin in normal erythrocytes and its enhanced sialylation in RBCVL. The enhanced sialylation of this cytoskeleton protein is possibly related to the fragmentation of spectrinVL as evidenced by the presence of an additional 60 kDa fragment, absent in spectrinN which possibly affects the biology of RBCVL linked to both severe distortion of erythrocyte development and impairment of erythrocyte membrane integrity and may provide an explanation for their sensitivity to hemolysis and anemia in VL patients

Fuel demand, carbon tax and electric vehicle adoption in India's road transport

To reduce oil import dependence and carbon emission from road transport, the study estimates the demand for gasoline, high-speed diesel and electric vehicles (EV) in India using non-linear cointegration techniques. The data spans from November 2014 to April 2022. Gasoline, high-speed diesel and EV demand are found to be asymmetric in mean and quantiles, exhibiting extreme tail dependence. Gasoline and high-speed diesel demand are price inelastic, which means that taxation is an ineffective policy instrument to reduce their demand and carbon emissions. However, such taxation could increase the demand for EV. A decrease in electricity prices would also increase the demand for EV while negatively impacting high-speed diesel demand. The study recommends that reducing electricity prices and imposing an additional carbon tax on gasoline and high-speed diesel could encourage electric mobility, eventually reinforcing India’s ‘net zero’ target by 2070. Future studies could focus on forecasting EV demand under different scenarios.©2024 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed