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Water data is a crucial asset for sustainable water resource management. However, the availability of China’s water datasets lags far behind modern expectations for open geoscientific data. This dataset is a part of the China Water Data Archive (CWDA), an upcoming national collection of water-related data covering all aspects of water data for boosting data sharing in China. The CWDA aims at providing free, clean, non-sensitive, coherent, and reliable water data within China for global researchers to support the national and global water resources management and the United Nations-Water Integrated Monitoring Initiative for Sustainable Development Goals 6 and 14. In this paper, we used Python and R language to collect, tidy, reorganize, and curate the publicly available inland and coastal/ocean surface water quality data in China, following a series of data quality dimensions (integrity, completeness, consistency, and accuracy). As the most comprehensive, publicly available, handy, and clean water quality dataset in China so far, it included water quality data for daily, weekly, and monthly in the period of 1980–2022, with 17 indicators for over 330,000 observations at 2384 sites from inland to coastal/ocean areas. This dataset will greatly support works relevant to the assessment, modelling, and projection of water quality, ocean biomass, and biodiversity in China.

Accurate, long time-series, high-resolution mapping of built-up land dynamics is essential for understanding urbanization and its environmental impacts. Despite advances in remote sensing and class...

Objective. To explore the influencing factors of knee osteoarthritis (KOA) severity and establish a KOA nomogram model. Methods. Inpatient data collected in the Department of Joint Surgery, Chengde Medical University Affiliated Hospital from January 2020 to January 2022 were used as the training cohort. Patients with knee osteoarthritis who were admitted to the Third Hospital of Hebei Medical University from February 2022 to May 2022 were taken as the external validation group of the model. In the training group, the least absolute shrinkage and selection operator (LASSO) method was used to screen the factors of KOA severity to determine the best prediction index. Then, after combining the significant factors from the LASSO and multivariate logistic regressions, a prediction model was established. All potential prediction factors were included in the KOA severity prediction model, and the corresponding nomogram was drawn. The consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), GiViTi calibration band, net classification improvement (NRI) index, and integrated discrimination improvement (IDI) index evaluation of a model predicted KOA severity. Decision curve analysis (DCA) and clinical influence curves were used to study the model’s potential clinical value. The validation group also used the above evaluation indexes to measure the diagnostic efficiency of the model. Spearman correlation was used to investigate the relationship between nomogram-related markers and osteoarthritis severity. Results. The total sample included 572 patients with knee osteoarthritis, including 400 patients in the training cohort and 172 patients in the validation cohort. The nomogram’s predictive factors were age, pulse, absolute value of lymphocytes, mean corpuscular haemoglobin concentration (MCHC), and blood urea nitrogen (BUN). The C-index and AUC of the model were 0.802. The GiViTi calibration band ( P = 0.065 ), NRI (0.091), and IDI (0.033) showed that the modified model can distinguish between severe KOA and nonsevere KOA. DCA showed that the KOA severity nomogram has clinical application value with threshold probabilities between 0.01 and 0.78. The external verification results also show the stability and diagnosis of the model. Age, pulse, MCHC, and BUN are correlated with osteoarthritis severity. Conclusions. A nomogram model for predicting KOA severity was established for the first time that can visually identify patients with severe KOA and is novel for indirectly evaluating KOA severity by nonimaging means.

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PURPOSE To investigate whether whole-body vibration (WBV) plus hip-knee muscle strengthening is more efficient in relieving pain and improving function than hip-knee strengthening alone. METHODS Thirty-six participants with patellofemoral pain syndrome (PFPS) were recruited and randomly allocated to either the (1) hip-knee strengthening only (HK group, n = 18) or (2) WBV plus hip-knee strengthening group (WHK group, n = 18). All participants attended 18 physiotherapy sessions (3 sessions/week, 40 min/session) over 6 weeks. Data on symptoms, function, surface electromyography (sEMG) signals from the vastus medialis and gluteus medius, and quality of life were evaluated at baseline (T0), 6 weeks after (T6), and the 12-week follow-up (T18). RESULTS Significant group × time interactions were found for the VAS score (p

Long-term, high-accuracy mapping of built-up land dynamics is essential for understanding urbanization and its consequences for the environment. Despite advances in remote sensing and classification algorithms, built-up land mapping using early satellite imagery (e.g., from the 2000s and earlier) remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-year intervals. Using dense time-stack Landsat data, we applied discrete Fourier transformation to create temporal predictors and reduce mapping uncertainties for early years. We improved overall accuracy by 8% compared to using spectral and indices predictors alone. We implemented a temporal correction algorithm to remove inconsistent pixel classifications, further improving accuracy to a consistently high level (>94%) across years. A cross-product comparison showed that our study achieved the highest levels of accuracy across years. Total built-up land in the North China Plain increased from 37,941 km2 in 1990–1992 to 131,578 km2 in 2017–2019. Consistent, high-accuracy built-up land mapping provides a reliable basis for policy planning in one of the most rapidly urbanizing regions of the planet.

Terrestrial carbon (C) is an important element in terrestrial ecosystems. However, urban development reduces terrestrial C storage causing damage to local ecosystems. Toward this end, this research has investigated the C loss caused by urban expansion in the Three Gorges Reservoir (TGR), China. The Multi-Layer Perceptron (MLP) model was adopted to simulate a future land use map in the year 2025. The InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was then chosen to calculate the C loss in terrestrial ecosystems (above ground carbon, below ground carbon, soil organic carbon and dead organic matter carbon) over the thirty-year period from 1995 to 2025. Results were as follows: the urban area of the TGR had increased 9788.36 km2 from 1995 to 2015 and is predicted to increase 9834.29 km2 from 2015 to 2025; terrestrial C lost 7.57 Tg from 1995 to 2015 and is predicted to lose another 6.04 Tg from 2015 to 2025. Terrestrial C losses are consistent with urban area expansion, showing a trend toward increase initially, followed by maintenance at a high level. Spatially, urban expansion and C loss at the TGR are predicted to begin at the Chongqing Central City then decrease outward.

Energy crops are a basic material in the bioenergy industry, and they can also mitigate carbon emissions and have environmental benefits when planted on marginal lands. The aim of this study was to evaluate the potential productivity of energy crops on marginal lands in China. A mechanistic model, combined with energy crop and land use characteristics, and meteorological and soil parameters, was used to simulate the potential productivity of energy crops. There were three main results. 1) The total marginal land in China was determined to be 104.78 × 106 ha. The 400-mm precipitation boundary line, which is the dividing line between the semi-humid and semi-arid zones in China, also divided the marginal land into shrub land and sparse forest land in the southeast and bare land, bare rock land, and saline alkali land in the northeast. 2) The total area of the marginal land suitable for planting energy crops was determined to be 55.82 × 106 ha, with Xanthoceras sorbifolia and Cerasus humilis mainly grown in the northern China, Jatropha curcas and Cornus wilsoniana mainly grown in the southwest and southeast, and Pistacia chinensis mainly grown in the central area, while also having a northeast-southwest zonal distribution. 3) Taking the highest yield in overlapping areas, the potential productivity of target energy crops was determined to be 32.63 × 106 t/yr. Without considering the overlapping areas, the potential productivity was 6.81 × 106 t/yr from X. sorbifolia, 8.86 × 106 t/yr from C. humilis, 7.18 × 106 t/yr from J. curcas, 9.55 × 106 t/yr from P. chinensis, and 7.78 × 106 t/yr from C. wilsoniana.

The Three Gorges Project (TGP) is a mega-water conservancy and hydropower project that have attracted worldwide attention. Under the influence of human activities, the landscape pattern has changed greatly. Using landscape metrics to analyze landscape pattern changes is the critical to understanding landscape pattern and ecological process. In this study, Landsat TM/ETM+/OLI images are used to extract indices for area edge, shape, spatial distribution, and diversity. Additionally, 19 landscape indices are taken to scale the granularity of the landscape level and the class level. An analysis of appropriate size is used to quantify the response of landscape indices to change landscape patterns during the four stages and a Crosstab model is used for pattern presentation. Finally, landscape indices are analyzed utilizing of Pearson correlation method to identify the landscape indicators suitable for the Three Gorges Reservoir. We have found that both the class level and landscape level indices are sensitive to grain size changes. Our results suggest that the suitable grain size is 30–60 m. Furthermore, the indicators suitable applied to analyzing changes in the landscape patterns in the TGR are Class Area (CA), Number of Patch (NP), Largest Patch Index (LPI), Landscape Shape Index (LSI), Effective Mesh Size (MESH), and Patch Density (PD). The main reasons for the change of landscape pattern in the Three Gorges Reservoir are land consolidation project, returning farmland to forest project, nature reserve construction, hydropower station construction and urbanization development.

Cisco IOS is an operating system that runs on Cisco routing and switching equipment. Its security is important to the entire network. Since vulnerability attacks have become one of the main sources of threat to Cisco IOS security, it is necessary to analyze the defense mechanism of IOS against vulnerability attacks. The purpose of this paper is to find out the deficiencies of IOS vulnerability defense mechanism in time and put forward improvement methods and preventive measures. Firstly, this paper introduces the protection mechanism of Cisco IOS vulnerability, including CheckHeaps, DEP, ASLR. The principle of these mechanisms and the idea of vulnerability protection are analyzed. And then, after analyzing the shortcomings of these protection mechanisms, the basic idea of bypassing these protection mechanisms is proposed. Finally, in view of the shortcomings of Cisco IOS vulnerability defense mechanism and the proposed bypass methods, some advices about how to better protect Cisco IOS from vulnerability exploitation are given.

As the spatial carrier of the emission sources and influencing factors of PM2.5, land use and its changes can inevitably affect local and regional PM2.5 concentrations. The relationship between the growth of PM2.5 and the changes of land use in China during 1998-2015 was explored in this paper using the Theil-Sen median trend analysis, Mann-Kendall and spatial econometric model. The results showed that the area where PM2.5 concentration was less than 10 μg/m3 accounted for a small portion (18.33%) of the land area in China, and the area where PM2.5 concentration was more than 35 μg/m3 accounted for 31.30% of the land area. High PM2.5 concentration was found in the East China Plain and Taklimakan desert; artificial surfaces, cultivated land and deserts were coated with high PM2.5 concentration more frequently, while the forest, grassland and unused land were usually covered with low PM2.5 concentration. PM2.5 concentration in desert land and artificial surfaces respectively increased at a pace of 1.07 μg/m3 and 0.80 μg/m3 per year during 1998–2015, higher than those in other land use types. They mainly came from the sand dust aerosol in northwest China, while those in the other areas mainly came from emissions in the human activities. Therefore, reasonable coordinating the proportion of construction land, cultivated land, forest land and grassland in eastern China, and strengthening desert governance in northwest China, are suggested to reduce PM2.5 concentration in China.

Wireless laser communication is a cutting edge technology combining laser communication and wireless communication. The author proposes a laser wireless communication solution based on single chip microcomputer. The system adopts STC12C5A60S2 MCU as the main control chip and encodes laser as communication carrier to realize short-range wireless optical communication. Through Optisystem simulation, the line-of-sight communication within 7.2 m can be achieved without blocking at a laser power of 5 mW and a Beam divergence of 170 mrad.

In view of the fact that when BP neural network algorithm is trapped into local extremum and the extremum converges to local minimum point, the convergence rate becomes slow, neural network structures are different, and there is a contradiction between application examples and network scale, this paper uses particle swarm optimization algorithm to optimize initial weights and thresholds of BP neural network. This method effectively enhances the ability of BP algorithm to handle nonlinear problems, and improves BP algorithm's convergence speed and ability to search global optimal values at the same time. A project case was selected for empirical analysis. The empirical results show that the new algorithm model has a significant improvement in algorithm efficiency, accuracy and other aspects, and it is of high practical value.

The traditional BP neural network has a slow convergence speed and requires a long training time; it is easy to fall into a local optimum; the network is always of high redundancy; the learning and memory of the network are unstable. This paper uses a genetic algorithm to modify weights and thresholds of the neural network in order to obtain the global optimal value. The simulation results show that this method has the characteristics of strong detection ability of pollution concentration and high detection efficiency, which can help improve the accuracy and speed of detection of SO2 pollution concentration in urban air.

Background The aim of this study was to explore the effects of different tidal volume (VT) ventilation on paraquat-induced acute lung injury or acute respiratory distress syndrome (ALI/ARDS) in piglets. Material/Methods We developed ALI/ARDS models in piglets by intraperitoneal injection of paraquat (PQ). The piglets were randomly divided into three groups: small VT group (VT=6 ml/kg, n=6), middle VT group (VT=10 ml/kg, n=6), and large VT group (VT=15 ml/kg, n=6), with the positive end-expiratory pressure (PEEP) set as 10 cmH2O. The hemodynamics were monitored by pulse-indicated continuous cardiac output (PiCCO) and the airway pressure changes and blood gas analysis indexes were recorded at different time points. The pathological changes were observed by lung puncture. Results The piglets showed ALI/ARDS in 4.5±0.8 hours after PQ intraperitoneal injection. PH, PaO2 and oxygenation indexes in the three groups all decreased after modeling success compared with baseline, and PaCO2 increased significantly. PH in the small VT group decreased most obviously after ventilation for 6 hours. PaO2 and oxygenation indexes in the small VT group showed the most obvious increase after ventilation for 2 hours and were much higher than the other two groups after ventilation for 6 hours. PaCO2 increased gradually after mechanical ventilation and the small VT group showed most obvious increase. The ELWI increased obviously after ventilation for 2 hours and then the small VT group clearly decreased. PIP and plateau pressure (Pplat) in the small VT group decreased gradually and in the middle and large VT group they increased after ventilation. The lung histopathology showed that the large VT group had the most severe damage and the small VT group had only minimal damage. Conclusions Small tidal volume ventilation combined with PEEP could alleviate the acute lung injury induced by paraquat and improve oxygenation.

An efficient and facile route to chiral dihydrodibenzothiazepines has been successfully developed via palladium-catalyzed asymmetric hydrogenation of the dibenzothiazepines with Bronsted acid as activator with up to 94% ee.

Chunfeng Oilfield in the Junggar Basin has shallow burial depth (400–570 m), low formation temperature (22–28 °C), thin reservoirs (2–6 m, averaging 3.5 m), high underground crude oil viscosity (50 000–90 000 mPa·s), but high sensitivity to heat, it is suitable for thermal recovery. In view of these features, a development method for this oilfield combining horizontal well, viscosity reducer, nitrogen and steam flooding (HDNS) was put forward, and pilot test was carried out in Northern Pai 601 sand body. The results show: injecting nitrogen through annulus can insulate thermal, high expansibility of nitrogen works to compensate formation energy, and nitrogen overlapping in reservoir has insulation effect. The combination effect of all parts of HDNS significantly increased steam sweep volume, oil displacement efficiency and crude oil flow ability, and reduced oil viscosity. Thanks to this technique, Chunfeng Oilfield has built up a production capacity of 40×104 t, with an oil recovery rate of 3%, marking the successful high-speed and high-efficiency development of low-grade shallow thin super heavy oil. Key words: shallow and thin bed, super heavy oil, enhanced thermal recovery, horizontal well, steam huff and puff, nitrogen, oil-soluble viscosity reducer

Single nucleotide polymorphisms of XPA gene have been studied in several cancers such as rs10817938, rs2808668. However, the role of XPA polymorphisms in patients with oral squamous cell carcinoma (OSCC) remains unclear. Thus, we analyzed the association of XPA polymorphisms with OSCC risk, clinicopathological characteristics and prognosis in the present study. TaqMan genotyping was used to evaluate the frequency of rs10817938, rs2808668 polymorphisms in OSCC patients. The prognostic significance of these polymorphisms was evaluated using Kaplan-Meier curves, Log-Rank analyses, and the Cox proportional hazard model. Luciferase reporter assay, RT-PCR and western blot were used to determine whether rs10817938 could influence transcription activity and XPA expression. The results showed that individuals carrying TC and CC genotypes had significantly greater risk of developing OSCC (OR = 1.42, 95% CI 1.04–1.93; OR = 2.75, 95% CI 1.32–5.71, respectively) when compared with wild-type TT genotype at rs10817938. OSCC patients with C allele at rs10817938 were more susceptible to lymph metastases, poor pathological differentiation and late TNM stage (OR = 1.67, 95% CI 1.17–2.37; OR = 1.64, 95% CI 1.18–2.28; OR = 1.54, 95% CI 1.11–2.14; respectively). A significant gene-environment interaction between smoking and CC genotype at rs10817938 was observed (COR = 3.60, 95% CI 1.20–10.9) and data also showed that OSCC patients with CC genotype and C allele had worse survival (p

It is difficult to verify the reliability of a new type of ammunition components through traditional statistical testing methods. And the accelerated life test of ammunition components at the present often requires a large amount of sample size. The calculation model for minimum sample size of the Inertial Gyro has been established by clearing the accelerated life test method of Inertial Gyro, considering the Weibull distribution is assumed to product life, and taking advantage of a priori information. And the minimum sample size of the Inertial Gyro that step-stress accelerated life-test required has been calculated out.

Presence is a service that allows a user to be informed about the specified state of another user. Presence service has become a key enabler for next-generation applications such as instant messaging, push-to-talk and web2.0. However, recent studies show that the notification traffic of presence service causes heavy signaling load on IP multimedia subsystem (IMS) network. This paper introduced a token-bucket based notification traffic control (TNTC) mechanism, which is an application layer solution deployed at the presence server. The TNTC aims at upgrading valid access probability while controlling the notification traffic. A mathematical model of a queuing system is proposed to describe TNTC. We analyzed its main probability features and investigated the effects of different parameters on the performance of TNTC. Extensive simulations verified that TNTC can effectively control notification traffic and perform better than the existing schemes in terms of valid access probability and update arrival rate.