Analysis of the outage performance of energy-harvesting cooperative-NOMA system with relay selection methods.

Recent years have witnessed the remarkable progress in wireless communication systems due to the escalating demand for higher data rates, improved reliability, and increased energy efficiency. In this regard, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technology, enhancing spectral efficiency and accommodating multiple users concurrently within the same time and frequency resources. Simultaneously, the energy harvesting has surfaced as a sustainable solution, converting ambient environmental energy into usable electrical power for operating communication nodes. This paper proposes a cooperative NOMA transmission scheme integrating energy harvesting and utilizing Least Squares (LS) channel estimation for precise Channel State Information (CSI) acquisition. The objective is to establish an optimal communication path from source to destination. Relay selection methods: Optimal Relay Selection (ORS) and Max-Min Relay Selection (MMRS), are compared, focusing on their impact on the system performance. The analysis considers the influence of the number of relays and power allocation factor on the system, with a specific emphasis on the outage probability expressions. Comparative analysis between the cooperative-NOMA and the traditional cooperative relaying without NOMA reveals the superior performance of the cooperative-NOMA. Additionally, the ORS scheme outperforms MMRS in terms of the outage performance.

Spatio-Temporal Development of Vegetation Carbon Sinks and Sources in the Arid Region of Northwest China.

Drylands, which account for 41% of Earth's land surface and are home to more than two billion people, play an important role in the global carbon balance. This study analyzes the spatio-temporal patterns of vegetation carbon sinks and sources in the arid region of northwest China (NWC), using the net ecosystem production (NEP) through the Carnegie-Ames-Stanford approach (CASA). It quantitatively evaluates regional ecological security over a 20-year period (2000-2020) via a remote sensing ecological index (RSEI) and other ecological indexes, such as the Normalized Difference Vegetation Index (NDVI), fraction of vegetation cover (FVC), net primary productivity (NPP), and land use. The results show that the annual average carbon capacity of vegetation in NWC changed from carbon sources to carbon sinks, and the vegetation NEP increased at a rate of 1.98 gC m-2 yr-1 from 2000 to 2020. Spatially, the annual NEP in northern Xinjiang (NXJ), southern Xinjiang (SXJ) and Hexi Corridor (HX) increased at even faster rates of 2.11, 2.22, and 1.98 gC m-2 yr-1, respectively. Obvious geographically heterogeneous distributions and changes occurred in vegetation carbon sinks and carbon sources. Some 65.78% of the vegetation areas in NWC were carbon sources during 2000-2020, which were concentrated in the plains, and SXJ, the majority carbon sink areas are located in the mountains. The vegetation NEP in the plains exhibited a positive trend (1.21 gC m-2 yr-1) during 2000-2020, but this speed has slowed since 2010. The vegetation NEP in the mountain exhibited only intermittent changes (2.55 gC m-2 yr-1) during 2000-2020; it exhibited a negative trend during 2000-2010, but this trend has reversed strongly since 2010. The entire ecological security of NWC was enhanced during the study period. Specifically, the RSEI increased from 0.34 to 0.49, the NDVI increased by 0.03 (17.65%), the FVC expanded by 19.56%, and the NPP increased by 27.44%. Recent positive trends in NDVI, FVC and NPP have enhanced the capacity of vegetation carbon sinks, and improved the eco-environment of NWC. The scientific outcomes of this study are of great importance for maintaining ecological stability and sustainable economic development along China's Silk Road Economic Belt.

Long Non-coding RNA Peg13 Alleviates Hypoxic-Ischemic Brain Damage in Neonatal Mice via miR-20a-5p/XIAP Axis.

Long noncoding RNA (LncRNA) Peg13 has been demonstrated to protect against neurological diseases. However, its underlying mechanism in the progression of hypoxic-ischemic brain damage (HIBD) has not been well investigated. The expression of target genes was determined in neonatal mice with HIBD and in mouse hippocampal neurons during oxygen-glucose deprivation (OGD) using quantitative real-time PCR (qRT-PCR) and immunoblotting. Functional assays, including CCK-8 cell viability and apoptotic cell detection using TdT mediated dUTP nick ending labeling (TUNEL) assay were used to examine the neuroprotective role of Peg13 in mouse hippocampal neurons. Luciferase assays were performed to determine the regulatory mechanism of Peg13 in OGD-induced neuronal apoptosis. Peg13 was reduced in HIBD mice and OGD-treated mouse hippocampal neurons. Altered Peg13 expression relieved OGD-induced neuronal apoptosis. Mechanistically, Peg13 may serve as a sponge for miR-20a-5p to increase the expression of X chromosome-linked inhibitor of apoptosis (XIAP), a downstream target of miR-20a-5p. Our study showed that Peg13 fulfilled its anti-apoptotic function in neurons through suppressing XIAP expression by sponging miR-20a-5p. Together, Peg13 binds to miR-20a-5p to upregulate XIAP and alleviate HIBD in neonatal mice. The Peg13/miR-20a-5p/XIAP competing endogenous RNA (ceRNA) axis could be a potential therapeutic target for HIBD.

Electrochemical properties of La0.5Sr0.5Fe0.95Mo0.05O3-δ as cathode materials for IT-SOEC.

Solid oxide electrolysis cells (SOECs) are a new type of high-efficiency energy conversion device that can electrolyze CO2 efficiently and convert electricity into chemical energy. However, the lack of efficient and stable cathodes hinders the practical application of CO2 electrolysis in SOECs. Herein, a novel perovskite oxide La0.5Sr0.5Fe0.95Mo0.05O3-δ (LSFMo) is synthesized and used as a cathode for SOECs. The introduction of Mo significantly improves the CO2 tolerance of the material in a reducing atmosphere and solves the problem of SrCO3 generation in the La0.5Sr0.5FeO3-δ material. Mo ion doping promotes the conductivity in a reducing atmosphere and increases the oxygen deficiencies of the material, which lowers the ohmic resistance (R s) of the material and significantly improves the CO2 adsorption and dissociation in the middle-frequency of polarization resistance (R p). For example, R p decreases from 0.49 to 0.24 Ω cm2 at 800 °C under 1.2 V. Further, the reduction of R s and R p increases the performance improvement, and the current density is increased from 1.56 to 2.13 A cm-2 at 800 °C under 2 V. Furthermore, LSFMo shows reasonable short-term stability during the 60 h stability test.

Explicit the urban waterlogging spatial variation and its driving factors: The stepwise cluster analysis model and hierarchical partitioning analysis approach.

Urban waterlogging is a hydrological cycle problem that seriously affects people's life and property. Characterizing waterlogging variation and explicit its driving factors are conducive to prevent the damage of such disasters. Conventional methods, because of the high spatial heterogeneity and the non-stationary complex mechanism of urban waterlogging, are not able to fully capture the urban waterlogging spatial variation and identify the waterlogging susceptibility areas. A more robust method is recommended to quantify the variation trend of urban waterlogging. Previous studies have simulated the waterlogging variation in relatively small areas. However, the relationship between variables is often ignored, which cannot comprehensively reveal the dominant drivers affecting urban waterlogging. Therefore, a novel approach is proposed that combined stepwise cluster analysis model (SCAM) and hierarchical partitioning analysis (HPA) within a general framework and verifies the applicability through logistic regression, artificial neural network, and support vector machine. According to the dominant driving factors, different simulation scenarios are established to analyze waterlogging density variation. Results found that the SCAM provides accurate and detailed simulated results both in urban centers where waterlogging frequently occurs and urban fringe with few waterlogging events, which shows an excellent performance with a high classification accuracy and generalization capability. HPA detected that the impervious surface abundance (28.07%), vegetation abundance (20.80%), and cumulate precipitation (16.25%) are the dominant drivers of waterlogging. This result suggests that priority should be given to controlling these three factors to mitigate the risk of waterlogging. It is interesting to note that under different urbanization and rainfall scenarios, the urban waterlogging susceptibility has a considerable variation. The watershed spatial location and watershed characteristics are relevant aspects to be considered in identifying and assessing waterlogging susceptibility, which provides original insights that urban waterlogging mitigation strategies should be developed according to different local conditions and future scenarios.

Spatial patterns of vegetation carbon sinks and sources dataset in Central Asia.

This dataset includes land use/cover change data with a spatial resolution of 300 m, net ecosystem productivity data based on the monthly grid data of the temperature and precipitation series data from the Climatic Research Unit, terrestrial net primary production data from MOD17 of the Central Asia that underlies the article entitled "Spatial patterns of vegetation carbon sinks and sources under water constraint in Central Asia". We explain the details of the dataset, the data harmonization procedures, and the spatial coverage. We also provide the validation result of NPP data from MOD17. We unified the spatiotemporal resolution of these data from different sources, based on re-sampling (nearest neighbor interpolation) and re-classification techniques, and combined the data from the different source datasets to form comprehensive records.

Research Trends of Acupuncture Therapy on Knee Osteoarthritis from 2010 to 2019: A Bibliometric Analysis.

BACKGROUND: Acupuncture has been widely applied to relieve knee osteoarthritis (KOA) in many countries. However, the bibliometric analysis of the global use of acupuncture on KOA is largely unknown. Therefore, this study aimed to explore the current status and trends of the global use of acupuncture on KOA in recent 10 years by using CiteSpace (5.6.R3). METHODS: Publications regarding acupuncture therapy for treating KOA between 2010 and 2019 were extracted from the Web of Science database. CiteSpace was used to analyze the number of publications, countries, institutions, journals, authors, cited references and keywords by using standard bibliometric indicators. RESULTS: A total of 343 publications were retrieved from 2010 to 2019. The total number of publications continually increased over the past four years, and the most active journals, countries, institutions and authors in the field of acupuncture therapy on patients with KOA were identified. The Evid Based Complement Alternat Med (28) was the most prolific journal, and the Ann Intern Med (202) was the most cited journal. The most productive country and institution in this field was China (115) and University of York (18), respectively. Hugh Macpherson (18) was the most prolific author and Witt C ranked the first in the cited authors. In the ranking of frequency in cited reference, the first article was published by Scharf HP (54). The keyword of 'randomized controlled trial' ranked first for research developments with the highest citation burst (3.9486). Besides, there were three main frontiers in keywords for KOA research, including 'research method, 'age' and 'measure of intervention'. CONCLUSION: The findings from this bibliometric study provide current status and trends in clinical research of acupuncture therapy on patients with KOA over the past ten years, which may help researchers identify hot topics and explore new directions for future research in this field.

Identifying dominant factors of waterlogging events in metropolitan coastal cities: The case study of Guangzhou, China.

Urban waterlogging disasters are affected by environmental conditions and human activities. Previous studies had explored the effect of land-use type on waterlogging in relatively small watersheds. Few, however, have comprehensively revealed the relative contributions of the environmental and anthropogenic factors to urban waterlogging concerning different scales of analysis. Indeed what is less known, are the dominant factors and the appropriate scale of analysis. To overcome this limitation, a novel method that integrates the stepwise regression model with hierarchical partitioning analysis is presented. The purpose is to investigate the complex mechanism of urban waterlogging by identifying the relative contribution of each environmental and anthropogenic factor and the stability linking waterlogging to influencing factors at multiple scales of analysis (i.e. 1 km, 2 km, 3 km, 4 km, and 5 km). We consider waterlogging events in the central urban districts of Guangzhou (PR China) from 2009 to 2015 as a case study. The results show that the spatial distribution of waterlogging events in the central urban area presents a strong agglomeration pattern. The waterlogging hot spots are mainly concentrated in the historical area of Guangzhou. Under all analysis scales, we find that the percent cover of urban green spaces (44.74%), percent cover of residential area (41.03%), and slope.std (36.85%) both have a dominant contribution to urban waterlogging, which suggests the importance of land cover composition in determining urban waterlogging. However, the relative contribution and dominant factors of waterlogging varied across different analysis scales, presenting a strong scale effect. Under a small analysis scale (1 km), the topography factors (slope.std and relative elevation) are confirmed as the dominant variables; however, with the increase of analysis scale, the influence of land cover composition (greenspace, residence area, grassland) and land cover spatial configuration (LPI, AI, Cohesion index) on waterlogging magnitude is greater than other factors. This finding provides additional insights that the urban waterlogging can be alleviated by balancing the relative composition of land cover features as well as by optimizing their spatial configuration. Since the optimal statistical scale for urban waterlogging studies only worked for specific influencing factors, the appropriate analysis scale for urban waterlogging study should be determined by the characteristics of study areas. This study has the capability to extend our scientific understanding of the complex mechanisms of waterlogging in the highly urbanized coastal city, providing useful support for the prevention and management of urban waterlogging.

Electroacupuncture therapy for change of pain in classical trigeminal neuralgia.

INTRODUCTION: Classical trigeminal neuralgia (CTN) is a kind of trigeminal neuralgia which is due to neurovascular compression. The common neurological treatment CTN drug called carbamazepine is the main measure, although it usually has side effects and a high-rate of relapse. As a critical alternative therapy, electroacupuncture (EA) has been shown to benefit for neuropathic pain. The aims of this study are to observe the therapeutic effect and safety of EA for CTN, to evaluate whether EA has the advantage over carbamazepine in the analgesia of CTN. Furthermore, we would to establish a standardized, effective, and convenient therapy program of EA. METHODS AND ANALYSIS: One hundred twenty patients diagnosed with CTN will be randomized for a 4-week intervention. The interventions will be different according to the four groups (EA + carbamazepine group, sham EA + carbamazepine group, EA + placebo group and sham EA + placebo group). EA therapy will be performed in specific acupoints with a dilute wave (2/100 Hz) for 60 minutes. Carbamazepine tablets will be taken orally with 0.1 g each time, thrice daily. Sham EA and placebo intervention will not receive EA and drug treatment. The main outcomes are the change from baseline intensity of pain at 6 months (pain evaluation by visual analogue score) and the change from baseline brief introduction of 2-week pain to evaluate pain comprehensively. The data management and statistical analysis will be conducted by third party statisticians. Incidence of adverse events will be investigated. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Clinical Trial Ethics Committee of The Third Affiliated Hospital of Zhejiang Chinese Medical University (NO. ZSLL-KY-2017-033) and Jiaxing Hospital of Traditional Chinese Medicine (NO. 2018-JZLK-002). The results will be disseminated by presentation at peer-reviewed journals.

Different kinds of acupuncture treatments for knee osteoarthritis: a multicentre, randomized controlled trial.

INTRODUCTION: Knee osteoarthritis (KOA) is a chronic disease with symptoms of persistent pain or resting pain, joint stiffness, numbness, limitation of activity and even disability, with significant associated costs and effects on individuals' life quality. The use of acupuncture for the management of chronic pain is receiving increasing recognition from both the public and professionals. The aim of this study is to identify the effects of three commonly used acupuncture treatments for KOA. METHODS/ANALYSIS: In a prospective trial involving six hospitals in Zhejiang Province (China), 360 patients with KOA will be included. Eligible patients will be randomized into six groups: Acupuncture, Electro-acupuncture, Mild moxibustion, Warm-needling, Sham acupuncture and Celebrex treatment. Twelve treatment sessions will be performed over a 4-week period. The primary outcome will be the visual analogue scale and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function scores (the average of the past 3 days) at weeks 2 and 4 and at 3-month and 6-month follow-up. Secondary outcome measures will be as follows: the WOMAC pain score and WOMAC stiffness score (the average of the past 3 days); the Physical Activity Scale of the Elderly (PASE); knee joint swelling measurement; the WHO Quality Of Life-BREF (WHOQOL-BREF) life quality scale; and the incidence of adverse events. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03563690. Registered on 2rd July 2018.

Recent Lake Area Changes in Central Asia.

Using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m spatial resolution global water product data, Least Squares Method (LSM) was applied to analyze changes in the area of 14 lakes in Central Asia from 2001 to 2016. Interannual changes in lake area, along with seasonal change trends and influencing factors, were studied for the months of April, July and September. The results showed that the total lakes area differed according to interannual variations and was largest in April and smallest in September, measuring -684.9 km2/a, -870.6 km2/a and -827.5 km2/a for April, July and September, respectively. The change rates for the total area of alpine lakes during the same three months were 31.1 km2/a, 29.8 km2/a and 30.6 km2/a, respectively, while for lakes situated on plains, the change rates were -716.1 km2/a, -900.5 km2/a, and -858 km2/a, respectively. Overall, plains lakes showed a declining trend and alpine lakes showed an expanding trend, the latter likely due to the warmer and wetter climate. Furthermore, there was a high correlation (r = 0.92) between area changes rate of all alpine lakes and the lakes basin supply coefficient, although there was low correlation (r = 0.43) between area changes rate of all alpine lakes area and glacier area/lake area. This indicates that lakes recharge via precipitation may be greater than lakes recharge via glacier meltwater. The shrinking of area changes for all plains lakes in the study region was attributable to climate change and human activities.

A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG.

Motion artifacts and myoelectrical noise are common issues complicating the collection and processing of dynamic electrocardiogram (ECG) signals. Recent signal quality studies have utilized a binary classification metric in which ECG samples are determined to either be clean or noisy. However, the clinical use of dynamic ECGs requires specific noise level classification for varying applications. Conventional signal processing methods, including waveform discrimination, are limited in their ability to remove motion artifacts and myoelectrical noise from dynamic ECGs. As such, a novel cascaded convolutional neural network (CNN) is proposed and demonstrated for application to the five-classification problem (low interference, mild motion artifacts, mild myoelectrical noise, severe motion artifacts, and severe myoelectrical noise). Specifically, this study finally categorizes dynamic ECG signals into three levels (low, mild, and severe) using the proposed CNN to meet clinical requirements. The network includes two components, the first of which was used to distinguish signal interference types, while the second was used to distinguish signal interference levels. This model does not require feature engineering, includes powerful nonlinear mapping capabilities, and is robust to varying noise types. Experimental data are composed of private dataset and public dataset, which were acquired from 90,000 four-second dynamic ECG signals and MIT-BIH Arrhythmia database, respectively. Experimental results produced an overall recognition rate of 92.7% on private dataset and 91.8% on public dataset. These results suggest the proposed technique to be a valuable new tool for dynamic ECG auxiliary diagnosis.

Effects of laser needle-knife therapy on vertebroarterial morphology and protein expression of PI-3K, AKT and VEGF in the carotid artery in a rabbit model of cervical spondylotic arteriopathy.

PURPOSE: To explore how the use of a laser needle-knife affects vertebroarterial morphology and protein expression of PI-3K, AKT and VEGF in the carotid artery of a rabbit model of cervical spondylotic arteriopathy (CSA), and to determine its primary treatment mechanism. METHODS: The CSA rabbit model consisted of 30 rabbits with CSA that were randomly divided into a model group (n = 10), an acupuncture group (n = 10) and a laser needle-knife group (n = 10) plus a further 10 wild type rabbits placed into a normal group. Rabbits in the acupuncture group were treated by needling the Fengchi (GB 20) and Jiaji (EX-B2) acupoints, while those in the laser needle-knife group were treated with a laser needle-knife on the Jiaji (EX-B2) near the spinous process of the fifth cervical vertebra, the rabbit in both groups immobilized during treatment. Rabbits in the other two groups received no treatment, but were immobilized for a similar duration. The morphology of the right vertebral artery and the distribution of pore size before and after treatment were compared using BET and SEM, and the protein expression of PI-3K, AKT and VEGF in the carotid artery of the four groups measured using Western blot analysis. RESULTS: The pore diameter and specific surface area of the right vertebral artery increased after treatment, as did the number of micropores. Compared with the normal group, the protein expression of PI-3K, AKT and VEGF in the carotid artery of the model group was significantly lower (P < 0.05), while that of the laser needle-knife group was significantly higher (P < 0.05 and P < 0.01). In addition, rabbits from the acupuncture and laser needle-knife groups demonstrated significantly higher levels of protein expression of PI-3K and VEGF in the carotid artery compared with the model group (P < 0.05 and P < 0.01). CONCLUSIONS: By promoting micrangium hyperplasia within the vertebral artery of rabbits with CSA, treatment with a laser needle-knife modified the protein expression of PI-3K, AKT and VEGF, suggesting that laser needle-knife therapy possibly treats CSA though these signaling pathways.

Glucose-6-phosphate dehydrogenase mutant D306C has a higher inhibition rate for enzyme multiplied immunoassay of cholyglycine.

Glucose-6-phosphate dehydrogenase (G6PDH) has been used in enzyme multiplied immunoassay technique (EMIT) assays for detecting small molecule metabolites such as cholyglycine (CG). A key parameter for successful EMIT CG assay development is the inhibition rate of the G6PDH-CG conjugate, measured as the decrease in enzyme activity upon CG antibody binding. Several commonly used G6PDH cysteine mutants including A45C and K55C have been labeled with CG-maleimide derivative, but inhibition rates of are unsatisfactory. Herein, we investigated whether other mutation sites can achieve better inhibition rates. We generated eight cysteine mutants (K106C, Y155C, A201C, T258C, D306C, D375C, G426C, and D480C) of G6PDH, measured their inhibition rates, and evaluated the performance of the D306C mutant using EMIT CG assays. One of the eight mutants (D306C) displayed improved inhibition rate, whereas all others exhibited inhibition similar to or lower than that of A45C and K55C. The enhanced inhibition rate of D306C improved the EMIT CG assay calibration curve, using an Abbott c16000 automated biochemical analyzer, resulting in better repeatability, precision, and linearity than with K55C assays and a commercially available EMIT CG kit. The G6PDH mutant D306C has a higher inhibition rate in EMIT CG assays and improves assay performance.

A novel three-round multiplex PCR for SNP genotyping with next generation sequencing.

Owing to the high throughput and low cost, next generation sequencing has attracted much attention for SNP genotyping application for researchers. Here, we introduce a new method based on three-round multiplex PCR to precisely genotype SNPs with next generation sequencing. This method can as much as possible consume the equivalent amount of each pair of specific primers to largely eliminate the amplification discrepancy between different loci. After the PCR amplification, the products can be directly subjected to next generation sequencing platform. We simultaneously amplified 37 SNP loci of 757 samples and sequenced all amplicons on ion torrent PGM platform; 90.5 % of the target SNP loci were accurately genotyped (at least 15×) and 90.4 % amplicons had uniform coverage with a variation less than 50-fold. Ligase detection reaction (LDR) was performed to genotype the 19 SNP loci (as part of the 37 SNP loci) with 91 samples randomly selected from the 757 samples, and 99.5 % genotyping data were consistent with the next generation sequencing results. Our results demonstrate that three-round PCR coupled with next generation sequencing is an efficient and economical genotyping approach. Graphical Abstract The schematic diagram of three-round PCR.