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IntroductionIsokinetic exercise can improve joint muscle strength and stability, making it suitable for early rehabilitation of stroke patients. However, traditional isokinetic equipment is bulky and costly, and cannot effectively avoid external environmental interference.MethodsThis paper designed a lightweight upper limb joint isokinetic rehabilitation training equipment, with a control system that includes a speed planning strategy and speed control with disturbance rejection. Based on the established human-machine kinematic closed-loop model between the equipment and the user, a dynamic evaluation method of torque at the joint level was proposed.ResultsTo validate the effectiveness of the equipment, experiments were conducted by manually applying random disturbances to the equipment operated at an isokinetic speed. The results showed that the root mean square error between the observed torque curve of the second-order linear extended state observer used in this paper and the actual disturbance curve was 0.52, and the maximum speed tracking error of the speed control algorithm was 1.27%. In fast and slow sinusoidal speed curve tracking experiments, the root mean square errors of the speed tracking results for this algorithm were 9.65 and 5.27, respectively, while the tracking errors for the PID speed control algorithm under the same environment were 19.94 and 12.11.DiscussionThe research results indicate that compared with traditional PID control method, the proposed control strategy demonstrates superior performance in achieving isokinetic control and suppressing external disturbances, thereby exhibiting significant potential in promoting upper limb rehabilitation among patients.

Ground subsidence caused by underground coalmining result in the formation of ponding water on the ground surface. Monitoring the surface water level is crucial for studying the hydrologic cycle in mining areas. In this paper, we propose a combined technique using Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) and GNSS Interferometric Reflectometry (GNSS-IR) to estimate the surface water level in areas of ground subsidence caused by underground coal mining. GNSS RTK is used to measure the geodetic height of the GNSS antenna, which is then converted into the normal height using the local height anomaly model. GNSS-IR is employed to estimate the height from the water surface to the GNSS antenna (or, the reflector height). To enhance the accuracy of the reflector height estimation, a weighted average model has been developed. This model is based on the coefficient of determination of the signal fitted by the Lomb-Scargle spectrogram and can be utilized to combine the reflector height estimations derived from multiple GNSS system and band reflection signals. By subtracting the GNSS-IR reflector height from the GNSS RTK-based normal height, the proposed method-based surface water level estimation can be obtained. In an experimental campaign, a low-cost GNSS receiver was utilized for the collection of dual-frequency observations over a period of 60 days. The collected GNSS observations were used to test the method presented in this paper. The experimental campaign demonstrates a good agreement between the surface water level estimations derived from the method presented in this paper and the reference observations.

Abstract Background In the early stages of the coronavirus disease 2019 (COVID-19) outbreak, the most widely recognised symptoms of the disease were fever, cough, shortness of breath, myalgia, and fatigue. However, in addition to these symptoms, COVID-19 can cause systemic symptoms outside the lungs. Older patients with severe COVID-19 often require admission to the intensive care unit (ICU). Acute rectal ulcer bleeding, characterised by painless, profuse haematochezia, caused by solitary or multiple rectal ulcers, is one of the main causes of severe haematochezia in patients with COVID-19 in the ICU. However, recurrent duodenal ulcer bleeding followed by rectal ulcer bleeding has not previously been reported in older patients during ICU treatment for severe COVID-19. Cases presentation Herein, we report the case of an 81-year-old woman admitted to the emergency department due to severe COVID-19 and transferred to the ICU 2 days later for treatment. During treatment in the ICU, the patient developed recurrent duodenal ulcer bleeding and underwent endoscopic electrocoagulation haemostasis and gastroduodenal artery embolisation. However, the night after the final haemostatic operation, due to rectal ulcer bleeding, the patient discharged bloody stools intermittently, which was effectively controlled using endoscopic electrocoagulation, topical medication, blood transfusion, and haemostatic drugs. Conclusions To the best of our knowledge, this is the first report of duodenal ulcer bleeding followed by rectal ulcer bleeding in an older patient with severe COVID-19 infection. This report creates awareness for clinicians about the multiple and complex gastrointestinal symptoms that may occur during COVID-19 treatment.

R&D partner diversity (RPD) is crucial for enhancing a firm’s innovation level, with innovation quality being a pivotal indicator of the firm’s overall capacity for innovation. However, the relationship between RPD and innovation quality has received little attention in the literature. This paper aims to unravel the influence of RPD on innovation quality and the underlying mechanisms. We conduct empirical research utilizing data from 463 publicly listed Chinese manufacturing companies to achieve this goal. Using a negative binomial model for data analysis, we find that RPD has a positive impact on the quality of innovation. The micromechanism analysis reveals that both exploratory learning and exploitative learning play a mediating role in the relationship between RPD and innovation quality. Furthermore, we discover that the strength of the relationship between RPD and innovation quality varies depending on the types of R&D partners and corporate ownership. Specifically, firms that collaborate with universities, competitors, users, or research institutes strengthen the positive effect, whereas forming alliances with other entities within the same group mitigates it. RPD has a more significant positive influence on the quality of innovation in non-state-owned enterprises compared to state-owned enterprises. These findings are robust to a battery of sensitivity tests, which provide valuable insights for firms seeking to enhance their innovation quality by fostering diverse R&D partnerships.

Objectives To explore the association of KISS1, LIN28B, vitamin D receptor (VDR), and estrogen receptor α (ERα) gene polymorphisms and the risk of early with fast puberty (EFP) risk, and with hormone levels in EFP cases, in Chinese girls.Methods The analysis was based on the data of 141 girls with EFP and 152 girls without EFP. Clinical features were documented, and all SNP genotyping was conducted using SNaPshot method. Statistical analysis was performed to assess the association of the SNPs with EFP risk, and with hormone levels in EFP cases.Results There was a significant association between rs7759938-C polymorphism in the LIN28B gene and the risk for EFP in the recessive (TT + CT vs. CC) model (p = 0.040). Remarkably, rs5780218-delA polymorphism in the KISS1 gene and rs2234693-C polymorphism in the ERα gene were significantly associated with peak LH (luteinizing hormone) levels (p = 0.008, 0.045) and peak LH/FSH (follicle-stimulating hormone) ratio (p = 0.007, 0.006). Additionally, on 7 of the 8 variant loci the alleles associated with increased levels of both peak LH levels and peak LH/FSH ratio in EFP cases were also associated with increased CPP risk.Conclusions Our findings indicate that rs7759938-C polymorphism in the LIN28B gene might have a protective effect on EFP susceptibility. The most striking findings of this study is that, rs5780218-delA polymorphism in the KISS1 gene and rs2234693-C polymorphism in the ERα gene influenced levels of GnRH-stimulated peak LH and LH/FSH ratio, and in general CPP risk genes might also contributes to the abnormality of hormonal levels in EFP.

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth’s surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth’s surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions.

High-power light-emitting diodes (LEDs) and high-brightness LEDs have revolutionized the lighting industry. The availability of cost-effective LEDs with high luminous flux, efficacy, and reliability has expanded their application to replace incandescent and fluorescent light sources. They have also enabled many new applications that were considered infeasible before, due to the inherent limitations of traditional sources of light. This survey provides a comprehensive overview of ac- and dc-supplied LED lighting systems and their applications, corresponding specifications and their similarities to/differences from regular power supplies. Restrictions imposed by LEDs characteristics, safety considerations, and dimmers are discussed. Also, LED driving approaches are categorized and their suitability for different applications is provided.

The equilibrium between dc bus voltage and ac bus frequency (Udc-f equilibrium) is the algorithm core of unified control strategies for ac-dc interlinking converters (ILCs), because the equilibrium implements certain mechanism. However, what the mechanism is has not been explicitly explored, which hinders further studies on unified control. This paper reveals that the state-space model of a Udc-f equilibrium controlled ILC is highly similar to that of a shaft-to-shaft machines system. Hence a detailed mechanism is discovered and named “virtual shaft-to-shaft machine (VSSM)” mechanism. A significant feature of VSSM mechanism is self-synchronization without current sampling or ac voltage sampling.

Underground coal-mining-induced ground subsidence deformation is a common geological disaster impacting buildings, transportation and water supplies. Models predicting ground subsidence dynamically with high precision are important for the prevention of damage derived from ground subsidence. In this paper, the Hook function is utilized to develop a model describing the velocity of ground subsidence due to underground coal mining. Based on the subsidence velocity model, a dynamic subsidence model is established by taking an integral of the velocity model. Coefficients of the model, which depend on maximum subsidence, maximum subsidence velocity and the time corresponding to the maximum subsidence velocity, are related to the geological and mining conditions of the coal seam being investigated. A Levenberg–Marquardt-algorithm-based method is also proposed to calculate the optimal model coefficients based on subsidence velocity observations. Four continuously operating Global Navigation Satellite System (GNSS) stations were constructed above a typical longwall coal mining working face in the Jining mining area, China. These GNSS stations collected subsidence observations over two years, which were used to validate the developed prediction model. The results show that the root-mean-square (RMS) of the model-predicted ground subsidence error is 56.1 mm, and the maximum relative error is 2.5% for all four GNSS stations, when the ground subsidence is less than 6000 mm.

Direct power generation near gas fields offers numerous benefits, including optimized economic efficiency and reduced environmental impact. Moreover, building on-site greenhouses emerges as a promising approach to further minimize carbon emissions and residual heat, greatly promoting resource utilization. However, such power plants generally have access to a weak grid due to their remote locations, and they also contain nonlinear local loads, such as the grow lights in the greenhouses. Consequently, the generation system is susceptible to power quality issues, manifested in overvoltage and harmonics. To address these issues, a smart back-to-back converter is employed to interconnect the gas turbine generator and the utility grid. This smart converter not only enhances power quality but also offers potential ancillary services that contribute to the dynamics of the gas generation system, such as damping low-frequency oscillation among parallel-connected generators. In this paper, three control configurations for the back-to-back converter are developed, enabling the coordinated regulation of exported active power, AC voltage, and DC-link voltage in either a grid-following or grid-forming manner. Furthermore, comparative studies are conducted to provide guidelines for selecting an appropriate control strategy that ensures stable operation under various short circuit ratios. A practical gas cogeneration system is chosen to evaluate the performance of the back-to-back converter, and real-time simulations based on RT-LAB are carried out to validate the effectiveness of the methodology.

Comparisons between different global navigation satellite system (GNSS) signals and GNSS-reflectometry (GNSS-R) satellite systems can provide valuable suggestions for future development of the GNSS-R instrument and signal processing method. This article evaluates the ocean altimetry performance of multiple GNSS constellation signals using raw intermediate frequency data collected by Cyclone GNSS (CYGNSS) and TechDemoSat-1 (TDS-1) satellites. Data used for the evaluation include observations of GPS L1, Galileo E1, and BDS B1 band signal. The specular point position and the ground-truth bistatic delay are calculated through the HALF method. After ionospheric, tropospheric, and tide corrections, the sea surface height can be retrieved; and then the height is compared with the DTU18 mean sea surface model derived one. Based on the GNSS-R satellite-collected observations, an optimal incoherent integral duration is determined. By making use of the optimal duration, the CYGNSS-based ranging delay estimating accuracy can reach up to 2.38 m, 1.98 m, and 1.91 m for GPS, Galileo and BDS, respectively; and the TDS-1 based one can reach up to 5.46 m and 3.84 m for GPS and Galileo, respectively. The results can provide suggestion on the strategies of multi-constellation observations fusion to improve the altimetry accuracy.

Backgroud: Renal fibrosis is the common characteristic of chronic kidney disease. Circular RNA plays an essential role in the occurrence and development of Renal fibrosis, but its regulative mechanism remains elusive.Methods: The animal and cell model of Renal fibrosis was established, and RNA-sequencing and real-time polymerase chain reaction (qRT-PCR) experiments were implemented. Subsequently, experiments for detecting apoptosis and proliferation of cell, were carried out, and the isobaric tags for relative and absolute quantification proteomics analyses were performed accordingly.Results: It was found that a newly discovered Circular RNA (circRNA_0002158), is highly expressed in kidneys or cells with fibrosis, implying that this Circular RNA might be associated with the occurrence and development of Renal fibrosis. Subsequently, the overexpression and knockdown of circRNA_0002158 were conducted in the human kidney epithelial cell line (HK-2) cells, and the results indicated that the circRNA_0002158 could inhibit apoptosis, and promote proliferation of cells. The kidney injury-related factors, including Fibronectin and plasminogen activator inhibitor-1 (PAI-1), were decreased in HK-2 cells with overexpression of circRNA_0002158, while the results were reversed in cells with knockdown of circRNA_0002158. Finally, to explore the regulative mechanism of circRNA_0002158, the iTRAQ proteomics analyses were implemented for the cell samples with OE of circRNA_0002158 and its control, it showed that multiple genes and functional pathways were associated with the occurrence and development of Renal fibrosis.Conclusion: CircRNA_0002158 is associated with regulating Renal fibrosis, and may contribute to ameliorating the progression of Renal fibrosis in the future.

Pancreatic cancer is the deadliest malignancy of the digestive system and is the seventh most common cause of cancer-related deaths worldwide. The incidence and mortality of pancreatic cancer continue to increase, and its 5-year survival rate remains the lowest among all cancers. N6-methyladenine (m6A) is the most abundant reversible RNA modification in various eukaryotic messenger and long noncoding RNAs and plays crucial roles in the occurrence and development of cancers. However, the role of m6A in pancreatic cancer remains unclear. The present study aimed to explore the role of m6A and its regulators in pancreatic cancer and assess its underlying molecular mechanism associated with pancreatic cancer cell proliferation, invasion, and metastasis. Reduced expression of the m6A demethylase, fat mass and obesity-associated protein (FTO), was responsible for the high levels of m6A RNA modification in pancreatic cancer. Moreover, FTO demethylated the m6A modification of praja ring finger ubiquitin ligase 2 (PJA2), thereby reducing its mRNA decay, suppressing Wnt signaling, and ultimately restraining the proliferation, invasion, and metastasis of pancreatic cancer cells. Altogether, this study describes new, potential molecular therapeutic targets for pancreatic cancer that could pave the way to improve patient outcome.

Abstract The cost of energy should be minimised to increase market penetration of wind energy conversion systems. The existing wind farm control strategies are not helpful since they speed up the damage in upstream wind turbines. Therefore, a control strategy is proposed to maximise the energy yield while equalising lifetime of one of the most fragile sub‐system of the wind turbines. The DC‐link capacitor bank of the back‐to‐back converters is considered to this end. The proposed control strategy can be directly applied in systems based on type 4 wind turbines with full power converters. This exposition reveals the formulation of the control strategy by analysing the strengths and weaknesses of the existing strategies based on the maximum power output. The lifetime‐based control strategy is extended to formulate a multi‐stage reactive power dispatch method with the help of a total energy‐based strategy. The effectiveness of all control strategies is validated using the model‐based simulations.

Blockchain technology and, in particular, smart contracts based on it, offers a new, decentralized mechanism for entering into and fulfilling contracts in diverse markets. Energy markets are no exception, and indeed, the decentralized nature of the blockchain may be particularly important for them as the penetration of residential prosumers offering microgeneration to the grid grows. At this time, however, the literature on smart contracts in energy markets—and particularly their interaction with the technical infrastructure of the smart grid—is limited and scattered. There is a need to consolidate these studies into a comprehensive understanding of the state-of-the-art in smart contract design for the smart grid. However, no existing reviews focus on smart contracts in energy systems. The scope of our study is the role of smart contracts in energy systems and what limitations they encounter. We conduct a systematic review of this topic, focusing on systems that have been implemented as prototypes. These studies provide key evidence on the scalability of smart contracts for energy systems and their interaction with the technical elements of the smart grid. We selected a pool of 76 papers meeting our criteria, with three others excluded for misinterpreting fundamental aspects of blockchains and smart contracts. After reviewing each paper, we found that this literature falls into four categories: market operations, ancillary services, auditing and monitoring, and cybersecurity. We then identify and examine the cross-cutting concerns of data storage in and interoperability between blockchains. We finally discuss the implications of our findings for future research. In particular, there is likely to be a complex interplay between the data generated and stored via the blockchain versus the data required to meet energy system reliability targets and market obligations for participants.

Abstract Background Pancreatic cancer is a fatal malignancy of the digestive system and the 5-year survival rate remains low. Therefore, new molecular therapeutic targets are required to improve treatments, prognosis, and the survival of patients. N6-methyladenosine (m6A) is the most prevalent reversible methylation in mammalian messenger RNA (mRNA) and has critical roles in the tumorigenesis and metastasis of various malignancies. However, the role of m6A in pancreatic cancer is still unclear. Exploring genetic alterations and functional networks of m6A regulators in pancreatic cancer may provide new strategies for its treatment. Methods In this study, we used data from the Cancer Genome Atlas (TCGA) database and other public databases through cBioPortal, LinkedOmics, UALCAN, GEPIA, STRING, and the database for annotation, visualization, and integrated discovery (DAVID) to systematically analyze the molecular alterations and functions of 20 main m6A regulators in pancreatic cancer. Results We found that m6A regulators had widespread genetic alterations, and that their expression levels were significantly correlated with pancreatic cancer malignancy. Moreover, m6A regulators were associated with the prognosis of pancreatic cancer patients. Conclusions m6A regulators play a crucial part in the occurrence and development of pancreatic cancer. Our study will guide further studies of m6A RNA modification in pancreatic cancer and could potentially provide new strategies for pancreatic cancer treatment.

There are the problems of low flow control accuracy, small flow control difficulty, and limited flow range in the traditional pressure-compensation flow-control valve. For this, a method of continuous control pressure drop $\Delta p_{\mathrm {rated}}$ to control flow-control valve flow is proposed. And the precise control of small flow is realized by reducing the pressure drop $\Delta p_{\mathrm {rated}}$ . In the research, the flow-control valve with controllable pressure compensation capability (FVCP) was designed firstly and theoretically analyzed. Then the sub-model model of PPRV and traditional flow-control valve were established and verified through experiments respectively. Finally, the accurate co-simulation model of the FVCP was established. The continuous control characteristics of pressure drop $\Delta p_{\mathrm {rated}}$ , the flow characteristics of FVCP, and the influence of different parameters $d_{2}$ were studied. The research results demonstrate that, compared with the traditional flow-control valve, the designed FVCP can adjust the compensation pressure difference in the range of 0.3 ~ 1.7 MPa in real-time. And the flow rate can be altered within the range of 44% ~ 100% of the rated flow. The diameter $d_{2}$ of the console shoulder has almost no effect on the compensator operating characteristics.

Since China’s reform and opening up, the urban economy has substantially developed, and the nation’s urbanization process has advanced to gradually enter a “new normal” phase. In this process, China’s population and industries continue to inundate its cities, and environmental pollution has become a critical problem. This study uses panel data spanning 1998 to 2015 from 29 Chinese provinces and a comprehensive framework of well-designed generalized method of moments (GMM) models to accurately examine the relationships between urbanization and per capita sulfur dioxide (PSO2), per capita industrial soot (PSOOT), and per capita industrial waste gas (PIWG). A newly developed dynamic threshold panel model that incorporates GMM characteristics is utilized to explore how urbanization affects environmental pollution under different industrial structures. This study finds evidence of a comprehensive relationship among urbanization development, the industrial structure, and environmental pollution. Urbanization has contributed to increased environmental pollution. A nonlinear relationship exists between urbanization and environmental pollution in China. Further, urbanization increasingly promotes environmental pollution with an increase in the proportion of secondary industries; however, such promotion decreases with an increase in the proportion of tertiary industries.

Central precocious puberty (CPP) is associated with adverse health outcomes in females; however, CPP pathogenesis remains unclear. In this study, we investigated the association of 20 single nucleotide polymorphisms (SNPs) in eight genes with CPP risk and hormone levels. A case-control study on 247 and 243 girls with and without CPP, respectively, was conducted at Kunming Children’s Hospital, China, from September 2019 to August 2020. The genotype of the SNPs and their haplotypes were identified. Additionally, the effects of the polymorphisms on hormone levels were investigated. Three variants (rs10159082, rs7538038, and rs5780218) in KISS1 and two variants (rs7895833 and rs3758391) in SIRT1 were related to an increased CPP risk (odds ratio (OR) = 1.524, 1.507, 1.409, 1.348, and 1.737; 95% confidence interval (CI) = 1.176–1.974, 1.152–1.970, 1.089–1.824, 1.023–1.777, and 1.242–2.430, respectively). Rs3740051in SIRT1 and rs1544410 in VDR reduced CPP risk (OR = 0.689, 0.464; 95% CI, 0.511–0.928, 0.232–0.925, respectively). Rs1544410, rs7975232, and rs731236 in VDR were negatively correlated with peak follicle-stimulating hormone (FSH; β = −2.181; P=0.045), basal FSH (β = −0.391; P=0.010), and insulin-like growth factor (β = −50.360; P=0.041) levels, respectively. KISS1, SIRT1, and VDR variants were associated with CPP susceptibility, and VDR SNPs influenced hormonal levels in Chinese females with CPP. In particular, VDR polymorphism rs1544410 was associated with both CPP risk and GnRH-stimulated peak FSH levels. Further functional research and large-scale genetic studies of these loci and genes are required to confirm our findings.

In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based on the laws of reflection in geometric optics, model of GNSS signal-to-noise (SNR) observation for the tilt surface, which results from differential subsidence of ground points, is derived. Semi-cycle SNR observations fitting method is used to determine the phase of the SNR series. Phase variation of the SNR series is used to calculate reflector height of ground specular reflection point. Based on the reflector height and ground tilt angle, an iterative algorithm is proposed to determine coefficients of PIM, and thus subsidence of the ground reflection point. By using the low-cost navigational GNSS receiver and antenna, an experimental campaign was conducted to validate the proposed method. The results show that, when the maximum subsidence is 3076 mm, the maximum relative error of the proposed method-based subsidence estimation is 5.5%. This study also suggests that, based on the proposed method, the navigational GNSS instrument can be treated as a new type of sensor for continuously measuring ground subsidence deformation in a cost-effective way.

Chronic obstructive pulmonary disease (COPD) is a multifactorial and heterogeneous disease that creates public health challenges worldwide. The underlying molecular mechanisms of COPD are not entirely clear. In this study, we aimed to identify the critical genes and potential molecular mechanisms of COPD by bioinformatic analysis. The gene expression profiles of lung tissues of COPD cases and healthy control subjects were obtained from the Gene Expression Omnibus. Differentially expressed genes were analyzed by integration with annotations from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by construction of a protein‐protein interaction network and weighted gene coexpression analysis. We identified 139 differentially expressed genes associated with the progression of COPD, among which 14 Hub genes were identified and found to be enriched in certain categories, including immune and inflammatory response, response to lipopolysaccharide and receptor for advanced glycation end products binding; in addition, these Hub genes are involved in multiple signaling pathways, particularly hematopoietic cell lineage and cytokine‐cytokine receptor interaction. The 14 Hub genes were positively or negatively associated with COPD by wgcna analysis. The genes CX3CR1, PTGS2, FPR1, FPR2, S100A12, EGR1, CD163, S100A8 and S100A9 were identified to mediate inflammation and injury of the lung, and play critical roles in the pathogenesis of COPD. These findings improve our understanding of the underlying molecular mechanisms of COPD.

We aim to explore the intestinal microbial metabolites in preterm infants with noninvasive methods and analyze the effects of initial feeding methods. Preterm infants with gestational weeks lower than 34 were recruited for fecal sample collection every 7 days. Fecal pH, ammonia, bile acid, and secretory IgA (sIgA) were tested. A 1:10 fecal slurry was inoculated into different culture media containing different carbohydrates as the only carbon source: lactose (LAT), fructooligosaccharide (FOS), galactooligosaccharide (GOS), and 2′-fucosyllactose (FL2). After 24 h of anaerobic culture through an in vitro fermentation system, air pressure difference, carbohydrate degradation rate, and short-chain fatty acids (SCFAs) content in fermentation pots were measured. Preterm infants were assigned into two groups: group A, preterm infants fed by human milk, including mother’s own milk and donor human milk (DHM); group B, preterm infants fed by preterm formula at first 3 days and fed by human milk (including mother’s own milk and DHM) from day 4 to discharge. Group A included 90 samples and group B included 70 samples. Group A had lower fecal pH (p = 0.023), ammonia (p = 0.001), and bile acids (p = 0.025). Group B also had higher fecal sIgA levels, both in OD (p = 0.046) and concentration (p < 0.0001) methods. Carbohydrates degradation rates in group A were higher than group B, especially in LAT medium (p = 0.017) and GOS medium (p = 0.005). Gas production amount had no significant difference in all four media. Several different SCFAs in four kinds of different culture media in group A were higher than in group B, but valeric acid was lower in group A. The initial feeding methods may affect the preterm infants’ intestinal microecology and microbial metabolites for at least several weeks.

Snow depth and snow water equivalent (SWE) are two parameters for measuring snowfall. By exploiting the Global Navigation Satellite System reflectometry (GNSS-R) technique and thousands of existing GNSS Continuous Operating Reference Stations (CORS) deployed in the cryosphere, it is possible to improve the temporal and spatial resolutions of the SWE measurement. In this paper, a fusion model for combining multi-satellite SNR (Signal to Noise Ratio) snow depth estimations is proposed, which uses peak spectral powers associated with each of the snow depth estimations. To simplify the estimation of SWE, the complete snowfall period over a winter season is split into snow accumulation, transition, and melting period in accordance with the variation characteristics of snow depth and SWE. By extensively using in situ snow depth and SWE observations recorded by snow telemetry network (SNOTEL) and regression analysis, three empirical models are developed to describe the relationship between snow depth and SWE for the three periods, respectively. Based on the snow depth fusion model and the SWE empirical models, an SWE estimation algorithm is proposed. Three data sets recorded in different environments are used to test the proposed method. The results demonstrate that there exists good agreement between the in situ SWE measurements and the SWE estimates produced by the proposed method; the root-mean-square error of SWE estimations is smaller than 6 cm when the SWE is up to 80 cm.

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation.

Soil moisture is an important variable in ecological, hydrological, and meteorological studies. An effective method for improving the accuracy of soil moisture retrieval is the mutual supplementation of multi-source data. The sensor configuration and band settings of different optical sensors lead to differences in band reflectivity in the inter-data, further resulting in the differences between vegetation indices. The combination of synthetic aperture radar (SAR) data with multi-source optical data has been widely used for soil moisture retrieval. However, the influence of vegetation indices derived from different sources of optical data on retrieval accuracy has not been comparatively analyzed thus far. Therefore, the suitability of vegetation parameters derived from different sources of optical data for accurate soil moisture retrieval requires further investigation. In this study, vegetation indices derived from GF-1, Landsat-8, and Sentinel-2 were compared. Based on Sentinel-1 SAR and three optical data, combined with the water cloud model (WCM) and the advanced integral equation model (AIEM), the accuracy of soil moisture retrieval was investigated. The results indicate that, Sentinel-2 data were more sensitive to vegetation characteristics and had a stronger capability for vegetation signal detection. The ranking of normalized difference vegetation index (NDVI) values from the three sensors was as follows: the largest was in Sentinel-2, followed by Landsat-8, and the value of GF-1 was the smallest. The normalized difference water index (NDWI) value of Landsat-8 was larger than that of Sentinel-2. With reference to the relative components in the WCM model, the contribution of vegetation scattering exceeded that of soil scattering within a vegetation index range of approximately 0.55–0.6 in NDVI-based models and all ranges in NDWI1-based models. The threshold value of NDWI2 for calculating vegetation water content (VWC) was approximately an NDVI value of 0.4–0.55. In the soil moisture retrieval, Sentinel-2 data achieved higher accuracy than data from the other sources and thus was more suitable for the study for combination with SAR in soil moisture retrieval. Furthermore, compared with NDVI, higher accuracy of soil moisture could be retrieved by using NDWI1 (R2 = 0.623, RMSE = 4.73%). This study provides a reference for the selection of optical data for combination with SAR in soil moisture retrieval.

In order to study functions of spectral signal and intelligent spectrometer in materials analysis, this paper designs the signal processing and analysis test of micro-spectrometer. The study object is spectral signal. This paper deeply discusses about problems on signal processing and analysis techniques of micro- spectrometer, establishes a model structure of signal processing and analysis system of micro-spectrometer, deeply studies the selection of wavelength and spectral recognition problems, and puts forward corresponding algorithm and strategies. This paper also discusses the wavelength selection during quantitative analysis of spectral signal and puts forward the method for selecting segmented wavelength based on particle swarm optimization algorithm. Test results prove that this algorithm can be used to solve the subjective randomness for wavelength selection during quantitative analysis and complexity and slow convergence of the existing methods. In addition, this paper also researches the module transformation of spectral signal and puts forward that segmented direct correction method of support vector machine is used to solve data conversion problems of different spectrometers among measuring signals in different solutions under same measuring conditions, so as to provide basis for universality and comparability of measurement data of different spectrometers. It can be known herein that spectrum research experiment of micro-spectrometer lays a foundation for its application and development in each field in the future.

The purpose of this paper is to research on the design of wireless sensor system for soil temperature detection based on sensor network. Based on the mathematical model and the state space equation which reflect the actual situation of system, the simulation calculation can be achieved as the basis of choosing control scheme and parameters. The control scheme of temperature control system proposed in the research has good control effects which are optimized by the particle swarm optimization. And the influence of environment temperature is smaller than the normal system. The temperature controller can be in heat preservation condition is not very good, and easy to affected by ambient temperature under the condition of constant temperature control.

Microgrids are being developed as a building block for future smart grid system. Key issues for the control and operation of microgrid include integration technologies and energy management schemes. This paper presents an overview of grid integration and energy management strategies of microgrids. It covers a review of power electronics interface topologies for different types of distributed generation (DG) units in a microgrid, a discussion of energy management strategies, as well as the DG interfacing converter control schemes. Considering the intermittent nature of many renewable energy based DG units, the ancillary services of DGs using the available interfacing converter rating are also discussed in the paper.

Global navigation satellite system (GNSS) multipath signals received by a geodetic-quality GNSS receiver can be used to estimate the water content of soil around the antenna. The direct signals from satellite to GNSS antenna are the most valuable signals in geodetic measurement, such as positioning, navigation, GNSS control network, deformation monitoring, and so on. However, the GNSS antenna also captures the reflected signals from the ground, which contain information of surrounding environment, so that useful information about the reflection surface can be inferred by analyzing the reflected signal. This technique is termed as GNSS-interferometric reflectometry. The signal-to-noise ratio (SNR) data recorded by a receiver contains SNR component of reflected signals, which is related to the soil moisture of the ground. The changes of soil moisture content will cause the change of soil permittivity and reflectivity which are the key factors that make further change of the SNR of reflected signals. We used the measured data to evaluate the correlation between amplitude of multipath induced SNR time series and real soil moisture. An improved soil moisture estimation algorithm based on multipath induced SNR amplitude data is proposed in this paper. The performance of the proposed soil moisture estimation method is evaluated using the 15-month data recorded by PBO H2O GNSS station and a 14-day experiment in Wuhan, China. The experimental results show that the estimated soil moisture has a strong correlation with the real soil moisture and the estimation accuracy in terms of root-mean-square error (RMSE) is 0.0345 cm3cm−3 and 0.0339 cm3cm−3, respectively. Meanwhile, the application scope of the method is given.

Two estimation methods using a dual GNSS (Global Navigation Satellite System) receiver system are proposed. The dual-frequency combination method combines the carrier phase observations of dual-frequency signals, whereas the single-frequency combination method combines the pseudorange and carrier phase observations of a single-frequency signal, both of which are geometry-free strictly combination and free of the effect of ionospheric delay. Theoretical models are established in the offline phase to describe the relationship between the spectral peak frequency of the combined sequence and the antenna height. A field experiment was conducted recently and the data processing results show that the root mean squared error (RMSE) of the dual-frequency combination method is 5.04 cm with GPS signals and 6.26 cm with BDS signals, which are slightly greater than the RMSE of 4.16 cm produced by the single-frequency combination method of L1 band with GPS signals. The results also demonstrate that the proposed two combination methods and the SNR method achieve similar performance. A dual receiver system enables the better use of GNSS signal carrier phase observations for snow depth estimation, achieving increased data utilization.