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Supersymmetric quantum mechanics is an effective method to solve the exact solution of the Schrödinger equation. This paper studies the solution of the Schrödinger equation with the partner potentials generated by the superpotential (Bcscαx-Acotαx) with two parameters (A and B). Firstly, the shape invariance of the partner potentials generated by the superpotential is obtained. The parametric additivity of shape invariance satisfies a special additivity characteristic: the two-parameter cross-additivity(A→B+α2,B→A+α2), which is completely different from the general additivity characteristic(A→A+α2,B→B+α2). Secondly, we discuss the case that belongs to two-parameter cross additive shape invariance in detail, and find that this two-parameter cross-additivity resulted in partial states missing. The existing energy spectrum and eigenfunctions of the Schrödinger equation with this new parametric transformation are worked out. Thirdly, we discuss the Shape invariance of the partner potentials generated again by the two parameters with cross additive characteristics through the potential algebra method. Lastly, the conclusions and discussions are made.

This paper employs the discrete element method (DEM) to study the mechanical properties of artificial crushed stone. Different grain shapes and gradations are considered, and three types of 3D artificial stone models are generated based on the statistical conclusions in the relevant literature and the observed data. Concurrently, the 3D models of the artificial stones are divided into three groups by their shape parameters (elongation index and flatness index). Furthermore, three types of gradation with different Cu (coefficient of uniformity) and Cc (coefficient of curvature) are also considered. Then, several 3D triaxial compression tests are conducted with the numerical methods to determine the relationship between the grain shapes and their mechanical characteristics. The test results showed that there was a positive correlation between a particles’ angularities and the maximum deviatoric stress in the triaxial compression tests when there were obvious distinctions between the particles. In addition, gradations had a conspicuous impact on the stiffness of the sample. The stress–strain curve possessed a larger slope when the coefficient of curvature was bigger. In terms of shear strength, the results in this paper align well with the traditional shear strength envelope which are convincing for the dependability of the methods used in this paper. The radial deformation capacity and volume strain of the specimen during the triaxial compression tests are also examined. It is believed that there were great differences in deformability between different samples. At the mesoscopic level, the change in coordination number is identified as the fundamental reason for the change in volume strain trend.

Using remote sensing and GIS techniques to monitor long time series land cover changes is of great significance to understanding the impact of human activities on spatiotemporal conflicts and changes in cropland and forest ecosystems in the black soil region of Northeast China. Spatial analysis and dynamic degree were used to analyze the evolutionary process and spatiotemporal association of land cover from 1990 to 2020; the transfer matrix was used to analyze and reveal dynamic conversions of land cover from 1990 to 2000, 2000 to 2010, and 2010 to 2020; and the GM (1,1) model was used to forecast the changes in land cover by 2025 based on historical data. The results indicated that the dominance of forest and cropland did not change from 1990 to 2020, and the average area of forest and cropland was 512,713 km2 and 486,322 km2, respectively. The mutual conversion between cropland, forest, grassland, and bare areas was the most frequent. The area of cropland converted into forest and grassland was 14,167 km2 and 25,217 km2, respectively, and the area of forest and grassland converted into cropland was 27,682 km2 and 23,764 km2, respectively, from 1990 to 2000. A similar law of land cover change was also presented from 2000 to 2020. In addition, the predicted values of cropland, forest, grassland, shrubland, wetland, water bodies, impervious surfaces, and bare areas were 466,942 km2, 499,950 km2, 231,524 km2, 1329 km2, 11,775 km2, 18,453 km2, 30,549 km2, and 189,973 km2, respectively, by 2025. The maximum and minimum residuals between the predicted and actual values were 6241 km2 and −156 km2 from 1990 to 2020. The evaluation results of the GM (1,1) model showed that all of the evaluation indices were within an acceptable range, and that the posteriori error ratio and class ratio dispersion were both less than 0.25. Through comparison with other studies, this study is not only able to provide some experience for further analyzing the spatial and temporal changes in land cover and its future prediction but also provide a basis for comprehensive management in Northeast China.

Research on the bulk internal electric field (IEF) regulation is significant for designing high-efficiency photocatalysts. Here, the authors report distinctive bismuth oxyhydroxide nanorods photocatalyst and increase the bulk IEF intensity by halogen ions exchange.

Electroreduction of CO2 into chemical fuels holds promise for mitigating environmental pollution and energy crisis. This work presents a distinct design of ferroelectric catalysts with high catalytic activity and selectivity for efficient and controllable electrochemical CO2 reduction reaction.

PurposeTo identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.MethodsThis prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.ResultsAfter IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.ConclusionsThe pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.Clinical Trial RegistrationThis study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).

PurposeCognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.MethodsIn this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients.ResultsThe classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%.ConclusionsThe model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment.

BackgroundThe COVID-19 pandemic has profoundly influenced the world. In wave after wave, many countries suffered from the pandemic, which caused social instability, hindered global growth, and harmed mental health. Although research has been published on various mental health issues during the pandemic, some profound effects on mental health are difficult to observe and study thoroughly in the short term. The impact of the pandemic on mental health is still at a nascent stage of research. Based on the existing literature, we used bibliometric tools to conduct an overall analysis of mental health research during the COVID-19 pandemic.MethodResearchers from universities, hospitals, communities, and medical institutions around the world used questionnaire surveys, telephone-based surveys, online surveys, cross-sectional surveys, systematic reviews and meta-analyses, and systematic umbrella reviews as their research methods. Papers from the three academic databases, Web of Science (WOS), ProQuest Academic Database (ProQuest), and China National Knowledge Infrastructure (CNKI), were included. Their previous research results were systematically collected, sorted, and translated and CiteSpace 5.1 and VOSviewers 1.6.13 were used to conduct a bibliometric analysis of them.ResultAuthors with papers in this field are generally from the USA, the People's Republic of China, the UK, South Korea, Singapore, and Australia. Huazhong University of Science and Technology, Hong Kong Polytechnic University, and Shanghai Jiao Tong University are the top three institutions in terms of the production of research papers on the subject. The University of Toronto, Columbia University, and the University of Melbourne played an important role in the research of mental health problems during the COVID-19 pandemic. The numbers of related research papers in the USA and China are significantly larger than those in the other countries, while co-occurrence centrality indexes in Germany, Italy, England, and Canada may be higher.ConclusionWe found that the most mentioned keywords in the study of mental health research during the COVID-19 pandemic can be divided into three categories: keywords that represent specific groups of people, that describe influences and symptoms, and that are related to public health policies. The most-cited issues were about medical staff, isolation, psychological symptoms, telehealth, social media, and loneliness. Protection of the youth and health workers and telemedicine research are expected to gain importance in the future.

Power industry is the largest carbon emission sector in China. Therefore, this industry will play an important role in achieving the carbon peaking and carbon neutrality goals (“dual carbon” goals) for the whole society. For this purpose, it is critical to balance four relationships, i.e. relationship between carbon mitigation and energy security, carbon peaking in the short term and carbon neutrality in the long term, the coordinated carbon mitigation in power industry and other industries, and technical feasibility and economic efficiency. This paper proposes the China’s Energy Interconnection scenario to promote carbon peaking and carbon neutrality of the society, which can be divided into three stages, i.e. peaking carbon emissions before 2030, rapid emission reduction during 2030–2050, and comprehensive carbon neutrality before 2060. It is expected that the power system will achieve zero emissions before other industries and contribute negative emissions afterwards, providing emission space for carbon neutrality in other industries across the society. Looking into the future, China’s electricity demand will continue to grow. Clean energy will become the main power source, the use of coal-fired power will be gradually reduced, and gas-fired power will undertake the function of peak-load regulation. Faster progress will be made in forming an overall grid pattern with ultra-high voltage (UHV) grid as the backbone and featuring “west-to-east and north-to-south power transmission, a balanced energy mix, and transnational power interconnection.” Finally, this paper discusses a new-type of power system characterized by a high proportion of electricity generated from clean energy, high ratio of electric and electronic equipment, and a high proportion of power transmission and reception, together with summer and winter high load periods, and points out the challenges faced by the new-type power system with a high proportion of renewable energy sources in terms of flexibility, safety, and economic efficiency, and proposes corresponding policy recommendations.

Abnormal refraction and reflection refers to the phenomenon in which light does not follow its traditional laws of propagation and instead is subject to refraction and reflection at abnormal angles that satisfy a generalization of Snell’s law. Metasurfaces can realize this phenomenon through appropriate selection of materials and structural design, and they have a wide range of potential applications in the military, communications, scientific, and biomedical fields. This paper summarizes the current state of research on abnormal refractive and reflective metasurfaces and their application scenarios. It discusses types of abnormal refractive and reflective metasurfaces based on their tuning modes (active and passive), their applications in different wavelength bands, and their future development. The technical obstacles that arise with existing metasurface technology are summarized, and prospects for future development and applications of abnormal refractive and reflective metasurfaces are discussed.

In epidemiological studies, type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment and dementia, but studies about functional network connectivity in T2DM without cognitive impairment are limited. This study aimed to explore network connectivity alterations that may help enhance our understanding of damage-associated processes in T2DM. MRI data were analyzed from 82 patients with T2DM and 66 normal controls. Clinical, biochemical, and neuropsychological assessments were conducted in parallel with resting-state functional magnetic resonance imaging, and the cognitive status of the patients was assessed using the Montreal Cognitive Assessment-B (MoCA-B) score. Independent component analysis revealed a positive correlation between the salience network and the visual network and a negative connection between the left executive control network and the default mode network in patients with T2DM. The differences in dynamic brain network connectivity were observed in the precuneus, visual, and executive control networks. Internal network connectivity was primarily affected in the thalamus, inferior parietal lobe, and left precuneus. Hemoglobin A1c level, body mass index, MoCA-B score, and grooved pegboard (R) assessments indicated significant differences between the two groups (p < 0.05). Our findings show that key changes in functional connectivity in diabetes occur in the precuneus and executive control networks that evolve before patients develop cognitive deficits. In addition, the current study provides useful information about the role of the thalamus, inferior parietal lobe, and precuneus, which might be potential biomarkers for predicting the clinical progression, assessing the cognitive function, and further understanding the neuropathology of T2DM.

Tomatoes (Solanum lycopersicum L. Micro-Tom) were grown in a plastic greenhouse. When plants anthesis, the 100 μmol m–2 s–1 blue light-emitting diode (LED) light (430 ± 10 nm) was supplemented from 6:00 to 18:00. There were 5 treatments, which contained different blue light frequencies with the same intensity: S6 (30 min blue light and 30 min pause), S8 (30 min blue light and 15 min pause), S10 (30 min blue and 8 min pause), S12 (continuous blue light for 12 h), and control (CK) (natural light, without any supplemental light). Agronomic traits and nutritional qualities of tomato fruits were measured at 30, 34, 38, 42, and 46 days after anthesis (DAA), respectively. Different frequencies of supplemental blue light could accelerate flowering of tomato plants and promote fruit ripening about 3–4 days early via promoting ethylene evolution of fruits, which significantly facilitated the processes of color change and maturity in tomato fruits. The contents of lycopene, total phenolic compounds, total flavonoids, vitamin C, and soluble sugar, as well as the overall antioxidant activity of tomato fruits were significantly enhanced by all the supplemental blue light treatments. In all, different frequencies of supplemental blue light prominently reinforced the antioxidant levels and nutritional qualities of tomato fruits, especially lycopene content, and S10 was more optimal for tomato fruits production in a plastic greenhouse.

In order to effectively improve the accuracy of delta sedimentary facies simulation, based on integrated analysis of seismic, core and logging data of Tahe Block T to quantitatively evaluate the complex relationship between recommendation, source supply and transportation, multi-condition constraint is used to create the sedimentary forward model of braided delta sandbody as the 3D training image of multipoint geostatistical simulation.The study shows that the sand body distribution in the braided river delta is affected by the control parameters of sedimentary forward modeling, and the percentage of sandstone supply, the ratio of sediment flow, the discharge and the flood interval are all strong sensitivity parameters, which have a great influence on the distribution of delta sand bodies in the study area; The sandstone content model embodies the retrogradation sedimentary process of the braided river delta, and conforms to the sedimentary characteristics of the study area.Then it is converted to 3D training image, and the multipoint simulation result is characterized by the training image constraints in the three-dimensional space, revealing the facies contact relationship reflected by the training image, and consistent with the drilling knowledge.This study proposes a new method for acquiring 3D training images, which combines the advantages of sedimentary forward modeling and multipoint geostatistical simulation, and has achieved certain application effect, which has a certain reference for the similar 3D geological modeling of sediments.

The understanding of catalytic reactions at the atomic interface is vital; however, the characterization and mechanism studies of atomically dispersed catalysts remain challenging. Here, the authors demonstrate Cu–Sn surface alloys with isolated Sn atoms on a Cu host to achieve efficient CO2 to CO conversion.

The secondary-phase grating-based tomographic microscopy system, which is widely used in the biological and life sciences, can observe all the sample multilayer image information simultaneously because it has multifocal points. However, chromatic aberration exists in the grating diffraction, which seriously affects the observation of the image. To correct the chromatic aberration of the tomographic microscope system, this paper proposes a system that adopts blazed gratings and angle-variable reflectors as chromatic aberration correction devices according to the principle of dispersion compensation and Fourier phase-shift theory. A reflector-separated light dispersion-compensated 3D microscopy system is presented to achieve chromatic aberration correction while solving the problem of multilayer image overlap. The theoretical verification and optical design of the system were completed using ZEMAX software. The results show that the proposed system reduced the chromatic aberration of ordinary tomographic microscopy systems by more than 90%, retaining more wavelengths of light information. In addition, the system had a relatively wide range in the color difference compensation element installation position, reducing the difficulty of dispersion compensation element installation. Overall, the results indicate that the proposed system is effective in reducing chromatic aberration in grating diffraction.

Infrared signature of targets is one important approach for target detection and recognition. When measuring the infrared signature of a target in the atmosphere, it is necessary to take the atmospheric transmittance and atmospheric radiation between the measured target and the observer into account. In this study, a blackbody-based approach for estimating atmospheric transmittance and atmospheric radiation is proposed to improve accuracy. Radiometric calibration is first carried out in the laboratory for the infrared thermal imager to determine the slope and offset used in the linear regression. With a set of different temperatures, radiance of the blackbody and digital number value of images are calculated. Finally, according to the analytical expressions derived, the atmospheric transmittance and atmospheric radiation are determined, and actual radiance for the cooperative target is calculated. Results demonstrate that the uncertainty of the actual radiance of measured cooperative target calculated via the proposed method is lower than that by MODTRAN, from MODTRAN at 5.7% and 16.7%, from proposed method at 2.56% and 10.2% in two experiments.

The differential microphone array, or differential beamformer, has attracted much attention for its frequency-invariant beampattern, high directivity factor and compact size. In this work, the design of differential beamformers with small inter-element spacing planar microphone arrays is concerned. In order to exactly control the main lobe beamwidth and sidelobe level and obtain minimum main lobe beamwidth with a given sidelobe level, we design the desired beampattern by applying the Chebyshev polynomials at first, via exploiting the structure of the frequency-independent beampattern of a theoretical Nth-order differential beamformer. Next, the so-called null constrained and least square beamformers, which can obtain approximately frequency-invariant beampattern at relatively low frequencies and can be steered to any direction without beampattern distortion, are proposed based on planar microphone arrays to approximate the designed desired beampatterns. Then, for dealing with the white noise amplification at low-frequency bands and beampattern divergence problems at high-frequency bands of the null constrained and least square beamformers, the so-called minimum norm and combined solutions are deduced, which can compromise among the white noise gain, directivity factor and beampattern distortion flexibly. Preliminary simulation results illustrate the properties and advantages of the proposed differential beamformers.

This paper proposes an efficient dynamic reconfigurable CNN accelerator (EDRCA) for FPGAs to tackle the issues of limited hardware resources and low energy efficiency in the deployment of convolutional neural networks on embedded edge computing devices. First, a configuration layer sequence optimization method is proposed to minimize the configuration time overhead and improve performance. Second, accelerator templates for dynamic regions are designed to create a unified high-speed interface and enhance operational performance. The dynamic reconfigurable technology is applied on the Xilinx KV260 FPGA platform to design the EDRCA accelerator, resolving the hardware resource constraints in traditional accelerator design. The YOLOV2-TINY object detection network is used to test the EDRCA accelerator on the Xilinx KV260 platform using floating point data. Results at 250 MHz show a computing performance of 75.1929 GOPS, peak power consumption of 5.25 W, and power efficiency of 13.6219 GOPS/W, indicating the potential of the EDRCA accelerator for edge intelligence computing.

BackgroundVaccine hesitancy is responsible for low vaccine coverage and increased risk of epidemics. The purpose of this study was to assess whether public knowledge, attitudes, practices, and willingness to vaccinate against COVID-19 have changed over time and at different stages of vaccination.MethodsTwo consecutive surveys were conducted among residents of the Leshan Community in Jinan from May to June, 2021 (n = 423) (basic dose vaccination phase) and from December, 2021 to January, 2022 (n = 470) (booster vaccination phase). Randomly sampling was used in residents to complete an anonymous questionnaire. Chi-square test was used to compare the changes in knowledge, attitudes and practices of the subjects in different survey stages. Multivariable logistic regression analysis was used to explore factors related to vaccination hesitancy.ResultsIn the booster vaccination phase, protective behaviors (89.9%) of residents increased significantly compared with the basic vaccination phase (74.5%). Residents were more hesitant to receive booster doses than basal doses of COVID-19 vaccine (OR: 18.334, 95% CI: 9.021–37.262). Residents with other marital statuses (OR: 2.719, 95% CI: 1.632–4.528), negative attitudes toward government measures were more hesitant to get vaccinated (OR: 2.576, 95% CI: 1.612–4.118). People who thought their physical condition was very good or good were more likely to be vaccinated than those who thought they were in fair or poor health (OR: 0.516, 95% CI: 0.288–0.925; OR: 0.513, 95% CI: 0.295–0.893). Young people inclined to use new media (such as WeChat and microblog) to obtain information, while the elderly inclined to use traditional methods (such as television). Government propaganda, residents' perception of the importance of vaccines and the risk of disease were the main reasons for accelerating residents to vaccinate. The main reasons affecting residents' lack of vaccination were contraindications to the vaccine or inconvenient time for vaccination.ConclusionsVaccine hesitancy increased significantly with change in vaccination stage. Strategies should be adopted to increase vaccination coverage such as improving the convenience of vaccination, promoting through multiple channels.

Abstract The rational construction of earth‐abundant and advanced electrocatalysts for oxygen evolution reaction (OER) is extremely desired and significant to seawater electrolysis. Herein, by directly etching Ni3S2 nanosheets through potassium ferricyanide, a novel self‐sacrificing template strategy is proposed to realize the in situ growth of NiFe‐based Prussian blue analogs (NiFe PBA) on Ni3S2 in an interfacial redox reaction. The well‐designed Ni3S2@NiFe PBA composite as precursor displays a unique spherical magic cube architecture composed of nanocubes, which even maintains after a phosphating treatment to obtain the derived Ni3S2/Fe‐NiPx on nickel foam. Specifically, in alkaline seawater, the Ni3S2/Fe‐NiPx as OER precatalyst marvelously realizes the ultralow overpotentials of 336 and 351 mV at large current densities of 500 and 1000 mA cm–2, respectively, with remarkable durability for over 225 h, outperforming most reported advanced OER electrocatalysts. Experimentally, a series of characterization results confirm the reconstruction behavior in the Ni3S2/Fe‐NiPx surface, leading to the in situ formation of Ni(OH)2/Ni(Fe)OOH with abundant oxygen vacancies and grain boundaries, which constructs the Ni3S2/Fe‐NiPx reconstruction system responsible for the remarkable OER catalytic activity. Theoretical calculation results further verify the enhanced OER activity for Ni3S2/Fe‐NiPx reconstruction system, and unveil that the Fe‐Ni2P/FeOOH as active origin contributes to the central OER activity.

In order to quantify the contribution of the mitigation strategies, an extended Kaya identity has been proposed in this paper for decomposing the various factors that influence the CO2 emission. To this end, we provided a detailed decomposition of the carbon intensity and energy intensity, which enables the quantification of clean energy development and electrification. The logarithmic mean divisia index (LMDI) has been applied to the historical data to quantify the contributions of the various factors affecting the CO2 emissions. Further, the global energy interconnection (GEI) scenario has been introduced for providing a systematic solution to meet the 2°C goal of the Paris Agreement. By combining LMDI with the scenario analysis, the mitigation potential of the various factors for CO2 emission has been analyzed. Results from the historical data indicate that economic development and population growth contribute the most to the increase in CO2 emissions, whereas improvement in the power generation efficiency predominantly helps in emission reduction. A numerical analysis, performed for obtaining the projected future carbon emissions, suggests that clean energy development and electrification are the top two factors that can decrease CO2 emissions, thus showing their great potential for mitigation in the future. Moreover, the carbon capture and storage technology serves as an important supplementary mitigation method.

Background: The antiviral effects of Novaferon, a potent antiviral protein drug, on COVID-19 was evaluated in the laboratory, and in a randomized, open-label, parallel-group trial. Methods: In the laboratory, Novaferon's inhibition of viral replication in cells infected with SARS-CoV-2, and prevention of SARS-CoV-2 entry into healthy cells was determined. Antiviral effects of Novaferon in COVID-19 patients with treatment of Novaferon, Novaferon plus Lopinavir/Ritonavir, or Lopinavir/Ritonavir were evaluated. The primary endpoint was the SARS-CoV-2 clearance rates on day six of treatment, and the secondary endpoint was the time to SARS-CoV-2 clearance. Results: Novaferon inhibited viral replication (EC50 = 1.02 ng/ml), and prevented viral infection (EC50 = 0.10 ng/ml). Results from the 89 enrolled COVID-19 patients showed that both Novaferon and Novaferon plus Lopinavir/Ritonavir groups had significantly higher viral clearance rates on day six than Lopinavir/Ritonavir group (50.0% vs. 24.1%, p = 0.0400, and 60.0% vs. 24.1%, p = 0.0053). The median time to viral clearance was six days, six days, and nine days for three groups, respectively, a 3-day reduction in both the Novaferon and Novaferon plus Lopinavir/Ritonavir groups compared with the Lopinavir/Ritonavir group. Conclusions: Novaferon exhibited anti-SARS-CoV-2 effects in vitro and in COVID-19 patients. These data justify further evaluation of Novaferon. Trial registration number: Number ChiCTR2000029496 at the Chinese Clinical Trial Registry (http://www.chictr.org.cn/).

The quantitative functions for climate damages provide theoretical ground for the cost-benefit analysis in climate change economics, and they are also critical for linking climate module with economic module in the Integrated Assessment Models (IAMs). Nevertheless, it is necessary for IAMs to update sectoral climate impacts in order to catch up the advance in climate change studies. This study updates the sectoral climate damage function at global scale from climate Framework for Uncertainty, Negotiation and Distribution (FUND) model and develops the aggregate climate damage function in a bottom-up fashion. Besides conventional sectors such as agriculture, forestry, water resources, energy consumption and ecosystems, this study expands climate disaster types, assesses human health impacts caused by various air pollutants, and updates coastal damage by sea level rise. The Beijing Climate Center Simple Earth System Model (BCC_SESM) is used to project climate system based on Business-as-Usual (BAU) scenario, and the 2 °C and 1.5 °C scenarios based on RCPs and SSP2 databases. Sectoral results show that the agricultural sector is projected to suffer 63% of the total damage, followed by water resources (16%) and human health (12%) sectors in 2100. The regression results indicate that the aggregate climate damage function is in positive quadratic form for zero discounting. Under BAU scenario, the aggregate climate damage is projected to be 517.7 trillion USD during 2011–2100. Compared to that, the 2 °C and 1.5 °C scenarios are projected to respectively reduce climate damages by 215.6 trillion USD (approximately 41.6%) and 263.5 trillion USD (50.9%) in 2011–2100.

The production of hydrogen peroxide by electrochemical oxygen reduction is an attractive alternative to the industrial process, but catalysts should be optimized. Here, the authors enhance hydrogen peroxide production in acidic media with epoxy groups near cobalt centers on carbon nanotubes.

Producing H2 from water using electricity and earth-abundant elements is necessary for worldwide renewable fuel production, yet most electrocatalysts have sluggish activities or poor stabilities. Here, authors show vanadium oxide modified copper-doped nickel to enable active and durable H2 evolution.

Abstract In this article, we first put forward a new definition of probabilistic Gel’fand- ( N , δ ) $(N,\delta )$ -width which is the classical Gel’fand-N-width in a probabilistic setting. Then we estimate the sharp order of the probabilistic Gel’fand- ( N , δ ) $(N,\delta )$ -width of finite-dimensional space. Furthermore, we obtain the exact order of probabilistic Gel’fand- ( N , δ ) $(N, \delta )$ -width of univariate Sobolev space by the discretization method according to the result of finite-dimensional space.

Abstract Background Hemagglutinin (HA), as the surface immunogenic protein, is the most important component of influenza viruses. Previous studies showed that the stability of HA was significant for HA’s immunogenicity, and many efforts have been made to stabilize the expressed HA proteins. Methods In this study, the protein disulfide isomerases (PDIs) were investigated for the ability to improve the stability of HA protein. Two members of the PDIs family, PDI and ERp57, were over-expressed or down-expressed in 293 T cells. The expression of H3 HA and PDIs were investigated by real-time qPCR, western-blot, immunofluorescence assay, and flow cytometry. The stability of HA was investigated by western-blot under non-reducing condition. Moreover, BALB/c mice were immunized subcutaneously twice with the vaccine that contained HA proteins from the ERp57-overexpressed and conventional 293 T cells respectively to investigate the impact of ERp57 on the immunogenicity of H3N2 HA. Results The percentage of the disulfide-bonded HA trimers increased significantly in the PDIs-overexpressed 293 T cells, and ERp57 was more valid to the stability of HA than PDI. The knockdown of ERp57 by small interfering RNA significantly decreased the percentage of the disulfide-bonded HA trimers. HA proteins from ERp57-overexpressed 293 T cells stimulated the mice to generate significantly higher HA-specific IgG against H1N1 and H3N2 viruses than those from the conventional cells. The mice receiving H3 HA from ERp57-overexpressed 293 T cells showed the better resistance against H1N1 viruses and the higher survival rate than the mice receiving H3 HA from the conventional cells. Conclusion ERp57 could improve the stability and immunogenicity of H3N2 HA.

For the better design and monitoring of gearboxes operating under nonstationary conditions, the dynamic interaction behavior of an electric motor drive multistage gear set is investigated in this study. Initially, dynamic mathematical models of an asynchronous motor and a multistage gear set are established by using the equivalent circuit method and the lumped parameter method, respectively. An electromechanical model coupling the asynchronous motor and the gearbox is subsequently developed, which is suitable for nonstationary conditions. The system transient responses under an impact external load are analyzed, and the mechanical torsional-vibration and electric current response are compared. Finally, the dynamic load propagation mechanism and the interaction effect on different gears are examined. The results demonstrate that the vibration frequencies of the multistage gearbox in steady and transient states both can be captured in the current. Electric current can be applied to reflect the external load variation and the internal vibration status of the driven gearbox under stationary or nonstationary conditions. The mutual excitation effects between adjacent gear pairs change the respective dynamic characteristics of the gears, and gears with small nominal loads are susceptible.

Background: Human respiratory syncytial virus (RSV) is one of the most important pathogens that cause acute respiratory infections in children and immunocompromised adults. This work was conducted to understand the epidemiological and phylogenetic features of RSV in southern China during 2011–2016. Methods: A total of 16 024 nasopharyngeal swabs were collected from patients with respiratory infections in 14 hospitals, and screened for RSV and seven other respiratory viruses using real-time PCR. Six hundred and twenty-three RSV-positive samples from 13 hospitals were further analyzed for subtypes. G gene sequencing and phylogenetic analysis were performed based on 46 RSV-A and 15 RSV-B strains. Results: RSV was detected in 9.5% of the 16 024 specimens, the highest among the eight respiratory viruses screened. Most of these specimens came from inpatients and children under 3 years of age. The incidence of RSV-A (9.4%) was higher than that of RSV-B (4.4%) in children (

To address the shortcomings in many traditional spectral feature extraction algorithms in practical application of low modeling accuracy and poor stability, this paper introduces the “Boruta algorithm-based local optimization process“ based on the traditional simulated annealing algorithm and proposes the “two-step simulated annealing algorithm (TSSA)”. This algorithm combines global optimization and local optimization. The Boruta algorithm ensures that the feature extraction results are all strongly correlated with the dependent variable, reducing data redundancy. The accuracy and stability of the algorithm model are significantly improved. The experimental results show that compared with the traditional feature extraction method, the accuracy indexes of the inversion model established by using the TSSA algorithm for feature extraction were significantly improved, with the determination coefficient R2 of 0.9654, the root mean square error (RMSE) of 3.6723 μg/L, and the mean absolute error (MAE) of 3.1461 μg/L.

Objective: We aimed to explore whether the percent amplitude of fluctuation (PerAF) measurement could provide supplementary information for amplitude of low-frequency fluctuation (ALFF) about spontaneous activity alteration in type 2 diabetes mellitus (T2DM) subjects without mild cognitive impairment (MCI). Then we further evaluated the synchronization through the method of functional connectivity (FC) to better demonstrate brain changes in a more comprehensive manner in T2DM.Methods: Thirty T2DM subjects without MCI and thirty well-matched healthy subjects were recruited in this study. Subjects’ clinical data, neuropsychological test results, and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired. Voxel-based group difference comparisons between PerAF and ALFF were conducted. Then, seed-based FC between the recognized brain regions based on PerAF and ALFF and the rest of the whole brain was performed.Results: Compared with healthy group, T2DM group had significantly decreased PerAF in the bilateral middle occipital gyrus and the right calcarine, increased ALFF in the right orbital inferior frontal gyrus and decreased ALFF in the right calcarine. Seed-based FC analysis showed that the right middle occipital gyrus of T2DM subjects exhibited significantly decreased FC with the right caudate nucleus and right putamen. According to the partial correlation analyses, hemoglobin A1c (HbA1c) and immediate memory scores on the auditory verbal learning test (AVLT) were negatively correlated in the T2DM group. However, we found that total cholesterol was positively correlated with symbol digit test (SDT) scores.Conclusion: PerAF and ALFF may have different sensitivities in detecting the abnormal spontaneous brain activity in T2DM subjects. We suggest PerAF values may add supplementary information and indicate additional potential neuronal spontaneous activity in T2DM subjects without MCI, which may provide new insights into the neuroimaging mechanisms underlying early diabetes-associated cognitive decline.

Passively Q-switching and mode-locking technologies can generate short pulses with durations that differ by several orders of magnitude widely used in different applications. Recently, Q-switching and mode-locking realized in an identical laser cavity with saturable absorbers was reported. The analysis of pulse conversion is helpful for us to further understand the pulse dynamics of a laser. In this paper, the pulse evolution from Q-switching, Q-switched mode-locking to mode-locking, is demonstrated by using a tungsten trioxide saturable absorber in a ring-cavity erbium-doped fiber laser. Firstly, self-started Q-switching at 1563 nm is observed, the repetition rate continuously increases, and the duration decreases when the pump power increased. Then, with an adjusting intra-cavity state of polarization under a high pump power level, stable Q-switched mode-locking pulses evolved from Q-switching, are observed. The amplitude of the emerged pulse sequence with a period of 36.8 ns, determined by cavity length, is modulated by the Q-switched envelope with the period of 10.3 μs. By optimizing the intracavity polarization carefully, stable continuous wave mode-locking operation is achieved eventually. To the best of our knowledge, this is the first experimental demonstration of Q-switching and mode-locking, respectively, in an identical transition-metal-oxides-based pulsed fiber laser without modification of cavity structure.

Objective: Cognitive impairment in type 2 diabetes mellitus (T2DM) patients is related to changes in hippocampal structure and function. However, the alternation of hippocampal subfields volumes and their relationship with cognitive function are unclear. This study explored morphological alterations in the hippocampus and its subfields in T2DM patients and their relationship with cognitive function.Methods: Thirty T2DM patients and 20 healthy controls (HCs) were recruited and underwent 3-dimensional, high-resolution T1-weighted sequence (3D-T1) and a battery of cognitive tests. Freesurfer 6.0 was performed to segment the hippocampus into 12 subregions automatically. Then relationships between hippocampal subfield volumes and neurocognitive scale scores in the T2DM group were evaluated.Results: Immediate memory scores on the auditory verbal learning test (AVLT) and Montreal Cognitive Assessment (MoCA) scores in T2DM patients were lower than in the HCs. T2DM patients showed that volumes of the bilateral hippocampus were significantly reduced, mainly in the bilateral molecular layer, granule cell and molecular layer of the dentate gyrus (GC-ML-DG), cornu ammonis 4 (CA4), fimbria, and left subiculum and the right hippocampus amygdala transition area (HATA) compared to HCs. In addition, T2DM patients showed the FINS was negatively correlated with volume of left GC-ML-DG (r = −0.415, P = 0.035) and left CA4 (r = −0.489, P = 0.011); the FBG was negatively correlated with volume of right fimbria (r = −0.460, P = 0.018); the HOMA-IR was negatively correlated with volume of left GC-ML-DG (r = −0.367, P = 0.046) and left CA4(r = 0.462, P = 0.010). Partial correlation analysis found that the volume of right HATA in T2DM group was positively correlated with AVLT (immediate) scores (r = 0.427, P = 0.03).Conclusion: This study showed the volumes of multiple hippocampal subfields decreased and they were correlated with FINS, FBG and HOMA-IR in T2DM patients. We hypothesized that decreased hippocampal subfields volumes in T2DM patients was related to insulin resistance and impaired vascular function. In addition, we also found that abnormal hippocampal subfields volumes were related to memory function in T2DM patients, suggesting that reduced volumes in specific hippocampal subfields may be the potential mechanism of memory dysfunction in these patients.

The spatial variability of soil properties is inherent. A series of direct shear tests were carried out on strongly weathered slates samples with weak bedding planes, the result of which indicates the existence of variability of shear strength parameters. Based on the testing results, several numerical simulations of slopes were conducted considering such a variability of shear strength. The results had shown that the weak bedding planes affect the shape of sliding arc as well as the factor of safety of slopes. As the dip angle of bedding planes increases, the shape of the sliding surface changes from circular to a mixed form of circular and planner. When incorporating the spatial variability of weak planes’ shear strength into the stability analysis, the safety factors of slopes would reduce, in which the sliding arc exhibited a sliding band comprising multiple sets of sliding arcs.

Diabetes with high blood glucose levels may damage the brain nerves and thus increase the risk of dementia. Previous studies have shown that dementia can be reflected in altered brain structure, facilitating computer-aided diagnosis of brain diseases based on structural magnetic resonance imaging (MRI). However, type 2 diabetes mellitus (T2DM)-mediated changes in the brain structures have not yet been studied, and only a few studies have focused on the use of brain MRI for automated diagnosis of T2DM. Hence, identifying MRI biomarkers is essential to evaluate the association between changes in brain structure and T2DM as well as cognitive impairment (CI). The present study aims to investigate four methods to extract features from MRI, characterize imaging biomarkers, as well as identify subjects with T2DM and CI.

Background: Structural and functional brain alterations that underlie cognitive decline have been observed in elderly adults with type 2 diabetes mellitus (T2DM); however, whether these alterations can be observed in patients with early-onset T2DM remains unclear. Therefore, we aimed to describe the abnormalities in brain volume and functional patterns in patients with early-onset T2DM in the present study.Methods: We enrolled 20 patients with early-onset T2DM and 20 healthy controls (HCs). Changes in brain volume were assessed using voxel-based morphology (VBM), while changes in brain function were assessed using degree centrality (DC) and functional connectivity (FC).Results: Compared to HCs, patients with early-onset T2DM exhibited gray matter reductions in the left orbital superior, middle, and inferior frontal gyri as well as the right superior frontal gyrus. The gray matter reductions in the right superior frontal gyrus were negatively associated with the urine albumin to creatinine ratio. Furthermore, increased DC values were observed in the left superior temporal gyrus, left Heschl gyrus, and left hippocampus in patients with early-onset T2DM. An FC analysis of these regions revealed elevated connectivity in the right precuneus, left inferior parietal gyrus, left Heschl gyrus, bilateral post-central gyrus, bilateral insula, bilateral superior temporal gyrus, and bilateral medial and paracingulate gyrus. Furthermore, the FC of the hubs to the superior temporal gyrus, insula, and Heschl gyrus was increased and positively correlated with trail making test-B.Conclusion: Decreased local gray matter volume and increased DC and FC may represent the neurobiological mechanism underlying cognitive dysfunction in patients with early-onset T2DM.

The Qinghai–Tibetan Plateau (QTP) is one of the most vulnerable ecosystems worldwide. Over the last few decades, the QTP has been subjected to increasing external pressures, such as climate change, human activity, and natural hazards. Therefore, ecological risk assessment is vital for the environmental protection and sustainable development of the QTP. A landscape ecological risk (LER) assessment based on landscape disturbance and vulnerability was performed to explore the spatiotemporal characteristics associated with LER in the QTP from 1990 to 2020. Furthermore, the impact of LER was quantitatively evaluated with a boosted regression tree model. Results showed that more than 70% of the locations in the QTP exhibited below-medium LER. The LER for the QTP demonstrated downward trends from 1990 to 2020. The LER presented downward trends during the periods from 1990 to 2001 and from 2012 to 2020 and no significant trend during the period from 2002 to 2011. Additionally, high-LER areas were concentrated in the northwestern QTP, whereas low-LER areas were mainly in the southeastern QTP. The LER displayed clustering characteristics across the QTP. Changes in climate, topographic distribution, and human activity influenced the ecological stability of the study area. Precipitation and temperature had the strongest effects on the LER, followed by elevation and grazing intensity. Lower precipitation and temperatures were associated with higher LER. Our results provide precise and specific support for the environmental protection and ecological management of the QTP and other ecologically fragile areas.

Objective: Aortic dissection (AD) is characterized by an acute onset, rapid progress, and high mortality. Levels of soluble ST2 (sST2) on presentation are elevated in patients with acute AD, which can be used to discriminate AD patients from patients with chest pain. sST2 concentrations were found to be highly heritable in the general population. The aim of this study was to investigate the associations of variations in ST2-related gene expression with sST2 concentrations and AD risk.Methods: This case-control study involving a total of 2,277 participants were conducted, including 435 AD patients and age- and sex-matched 435 controls in the discovery stage, and 464 patients and 943 controls in the validation stage. Eight ST2-related genes were selected by systematic review. Tag single-nucleotide polymorphisms (SNPs) were screened out from the Chinese population of the 1,000 Genomes Database. Twenty-one ST2-related SNPs were genotyped, and plasma sST2 concentrations were measured.Results: In the discovery stage, rs13019803 located in IL1R1 was significantly associated with AD after Bonferroni correction (p = 0.0009) and was correlated with circulating sST2 levels in patients with type A AD(AAD) [log-sST2 per C allele increased by 0.180 (95%) CI: 0.002 – 0.357] but not in type B. Combining the two stages together, rs13019803C was associated with plasma sST2 level in AAD patients [log-sST2 increased by 0.141 (95% CI: 0.055–0.227) for per C allele]. Odds ratio of rs13019803 on the risk of AAD is 1.67 (95% CI: 1.33–2.09).Conclusions: The IL1R1 SNP rs13019803C is associated with higher sST2 levels and increased risk of AAD.

The global water demand and supply situation is becoming increasingly severe due to water shortage and uneven distribution of water resources. The highest water demand in the energy sector is attributable to power generation. With cross-country and cross-continental power grid interconnections becoming a reality, electricity trading across countries and the creation of new opportunities for re-allocation of water resources are possible. This study expands the concept of virtual water and proposes a generalized virtual water flow in an interconnected power grid system to accurately estimate water resource benefits of clean power transmission from both the production and the consumption sides. By defining the water scarcity index as a price mechanism indicator, the benefits of water resources allocation through power grid interconnections are evaluated. Taking the Africa-Asia-Europe interconnection scenario as an example, the total water saving would amount to 88.95 million m3 by 2030 and 337.8 million m3 by 2050. This result shows that grid interconnections could promote the development of renewable energy and expand the benefits of available water resources. Keywords: Power grid interconnection, Virtual water, Water resources allocation

Abstract Background The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging (DTI), fibre bundle/tract-based spatial statistics (TBSS) and machine learning methods to study changes in the white matter (WM) structure and whole brain WM network in different periods of the nasopharyngeal carcinoma (NPC) patients after radiotherapy (RT), 2) identify the most discriminating WM regions and WM connections as biomarkers of radiation brain injury (RBI), and 3) supplement the understanding of the pathogenesis of RBI, which is useful for early diagnosis in the clinic. Methods A DTI scan was performed in 77 patients and 67 normal controls. A fractional anisotropy map was generated by DTIFit. TBSS was used to find the region where the FA differed between the case and control groups. Each resulting FA value image is registered with each other to create an average FA value skeleton. Each resultant FA skeleton image was connected to feature vectors, and features with significant differences were extracted and classified using a support vector machine (SVM). Next, brain segmentation was performed on each subject’s DTI image using automated anatomical labeling (AAL), and deterministic white matter fiber bundle tracking was performed to generate symmetrical brain matrix, select the upper triangular component as a classification feature. Two-sample t-test was used to extract the features with significant differences, then classified by SVM. Finally, we adopted a permutation test and ROC curves to evaluate the reliability of the classifier. Results For FA, the accuracy of classification between the 0–6, 6–12 and > 12 months post-RT groups and the control group was 84.5, 83.9 and 74.5%, respectively. In the case groups, the FA with discriminative ability was reduced, mainly in the bilateral cerebellum and bilateral temporal lobe, with prolonged time, the damage was aggravated. For WM connections, the SVM classifier classification recognition rates of the 0–6, 6–12 and > 12 months post-RT groups reached 82.5, 78.4 and 76.3%, respectively. The WM connections with discriminative ability were reduced. Conclusions RBI is a disease involving whole brain WM network anomalies. These brain discriminating WM regions and WM connection modes can supplement the understanding of RBI and be used as biomarkers for the early clinical diagnosis of RBI.

Supersymmetric quantum mechanics has wide applications in physics. However, there are few potentials that can be solved exactly by supersymmetric quantum mechanics methods, so it is undoubtedly of great significance to find more potentials that can be solved exactly. This paper studies the supersymmetric quantum mechanics problems of the Schrödinger equation with a new kind of generalized trigonometric tangent superpotential: Atannpx+Btanmpx. We will elaborate on this new potential in the following aspects. Firstly, the shape invariant relation of partner potential is generated by the generalized trigonometric tangent superpotential. We find three shape invariance forms that satisfy the additive condition. Secondly, the eigenvalues and the eigenwave functions of the potential are studied separately in these three cases. Thirdly, the potential algebra of such a superpotential is discussed, and the discussions are explored from two aspects: one parameter’s and two parameters’ potential algebra. Through the potential algebra, the eigenvalue spectrums are given separately which are consistent with those mentioned earlier. Finally, we summarize the paper and give an outlook on the two-parameter shape-invariant potential.

The random nature of wind energy is an important reason for the low energy utilization rate of wind farms. The use of a compressed air energy storage system (CAES) can help reduce the random characteristics of wind power generation while also increasing the utilization rate of wind energy. However, the unreasonable capacity allocation of the CAES system results in high capital investment and a long payback period. In order to improve the economic benefits of energy storage, this paper studies the capacity configuration of compressed air energy storage systems under the condition of wind energy uncertainty. First, the typical hourly power distribution of wind power generation was obtained using historical data. Factors such as user load demand, time-of-use price of the power grid, system investment cost, power shortage cost, and power sales revenue were considered. Then, a model was built with the charging and discharging power and gas storage capacity of the CAES system as constraints, and the maximum return on investment and the minimum volume of the gas storage tank as targets. NSGA-II and TOPSIS optimal selection methods were used to solve the problem. Finally, the model was used to optimize a power operation case. The results show that in the case of an hourly load power demand of a factory using 3.2 MW, a wind farm would need to keep four wind turbines running every day, and a compressed air energy storage system with a rated power of 1 MW and a rated capacity of 7 MW would ensure the best project benefit. In this mode, 1.24 × 103 MWh of wind abandoning power could be reduced annually, 2.6 × 104 kg of carbon emissions could be reduced by increasing energy storage within the operation cycle, and the payback period of investment would only be 4.8 years.

This paper focuses on image segmentation, image correction and spatial-spectral dimensional denoising of images in hyperspectral image preprocessing to improve the classification accuracy of hyperspectral images. Firstly, the images were filtered and segmented by using spectral angle and principal component analysis, and the segmented results are intersected and then used to mask the hyperspectral images. Hyperspectral images with a excellent segmentation result was obtained. Secondly, the standard reflectance plates with reflectance of 2 and 98% were used as a priori spectral information for image correction of samples with known true spectral information. The mean square error between the corrected and calibrated spectra is less than 0.0001. Comparing with the black-and-white correction method, the classification model constructed based on this method has higher classification accuracy. Finally, the convolution kernel of the one-dimensional Savitzky-Golay (SG) filter was extended into a two-dimensional convolution kernel to perform joint spatial-spectral dimensional filtering (TSG) on the hyperspectral images. The SG filter (m = 7,n = 3) and TSG filter (m = 3,n = 4) were applied to the hyperspectral image of Pavia University and the quality of the hyperspectral image was evaluated. It was found that the TSG filter retained most of the original features while the noise information of the filtered hyperspectral image was less. The hyperspectral images of sample 1–1 and sample 1–2 were processed by the image segmentation and image correction methods proposed in this paper. Then the classification models based on SG filtering and TSG filtering hyperspectral images were constructed, respectively. The results showed that the TSG filter-based model had higher classification accuracy and the classification accuracy is more than 98%.

Overuse of antibiotics in clinical medicine has contributed to the global spread of multidrug-resistant bacterial pathogens, including Acinetobacter baumannii. We present a case of an 88-year-old Chinese man who developed hospital-acquired pneumonia caused by carbapenem-resistant A. baumannii (CRAB). A personalized lytic pathogen-specific single-phage preparation was nebulized to the patient continuously for 16 days in combination with tigecycline and polymyxin E. The treatment was well tolerated and resulted in clearance of the pathogen and clinical improvement of the patient’s lung function.

This paper studies an efficient computing resource offloading mechanism for UAV-enabled edge computing. According to the interests of three different roles: base station, UAV, and user, we comprehensively consider the factors such as time delay, operation, and transmission energy consumption in a multi-layer game to improve the overall system performance. Firstly, we construct a Stackelberg multi-layer game model to get the appropriate resource pricing and computing offload allocation strategies through iterations. Base stations and UAVs are the leaders, and users are the followers. Then, we analyze the equilibrium states of the Stackelberg game and prove that the equilibrium state of the game exists and is unique. Finally, the algorithm’s feasibility is verified by simulation, and compared with the benchmark strategy, the Stackelberg game algorithm (SGA) has certain superiority and robustness.

Background: Type 2 diabetes mellitus (T2DM)-related cognitive decline is associated with neuroimaging changes. However, only a few studies have focused on early functional alteration in T2DM prior to mild cognitive impairment (MCI). This study aimed to investigate the early changes of global connectivity patterns in T2DM by using a resting-state functional magnetic resonance imaging (rs-fMRI) technique.Methods: Thirty-four T2DM subjects and 38 age-, sex-, and education-matched healthy controls (HCs) underwent rs-fMRI in a 3T MRI scanner. Degree centrality (DC) was used to identify the functional hubs of the whole brain in T2DM without MCI. Then the functional connectivity (FC) between hubs and the rest of the brain was assessed by using the hub-based approach.Results: Compared with HCs, T2DM subjects showed increased DC in the right cerebellum lobules III–V. Hub-based FC analysis found that the right cerebellum lobules III–V of T2DM subjects had increased FC with the right cerebellum crus II and lobule VI, the right temporal inferior/middle gyrus, and the right hippocampus.Conclusions: Increased DC in the right cerebellum regions III–V, as well as increased FC within cerebellar regions and ipsilateral cerebrocerebellar regions, may indicate an important pathophysiological mechanism for compensation in T2DM without MCI.

The activation of microglia and inflammatory responses is essential for the process of intracerebral hemorrhage (ICH)-induced secondary brain injury (SBI). In this study, we investigated the effects of luteolin on ICH-induced SBI and the potential mechanisms. Autologous blood was injected to establish the ICH model in vivo, and oxyhemoglobin (OxyHb) was used to mimic the ICH model in vitro. We found that the administration of luteolin significantly improved motor and sensory impairments and inhibited neuronal cell degeneration in vivo. In the in vitro study, the decrease of the neuronal cell viability induced by activated microglia was alleviated by luteolin treatment. Furthermore, by antagonizing the activation of the Toll-like receptor 4 (TLR4)/TNF receptor-associated factor 6 (TRAF6)/nuclear transcription factor-κB (NF-κB) signaling pathway, the ICH-induced elevation of cytokine release was decreased after treatment with luteolin, which was confirmed both in vivo and in vitro. Additionally, we found that luteolin engaged with TRAF6 and inhibited the ubiquitination of TRAF6. Taken together, our findings demonstrate the neuroprotective effects of luteolin after ICH and the potential mechanisms, which suggest that luteolin is a potential therapeutic candidate for ICH treatment.

Nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO) coupling to Anaerobic ammonium oxidation (Anammox) provides an opportunity for simultaneous nitrogen removal and methane emissions mitigation from wastewater. However, to achieve high nitrogen removal rate in such a process remains a critical challenge in practical application. This work investigated the interactions between n-DAMO and Anammox in membrane biofilm reactor (MBfR) and then developed operational strategies of MBfR for high rate nitrogen removal from landfill leachate. Initially, influent containing nitrate and ammonium facilitated the development of n-DAMO and Anammox microorganisms in MBfR, but nitrogen removal performance is hard to be further improved even deteriorated. Detailed investigations of interactions among n-DAMO and Anammox microorganisms confirmed that extra addition of nitrite into MBfR fed with nitrate and ammonium not only stimulated the activities of Anammox bacteria, but also enhanced the activities of n-DAMO archaea from 172.3 to 356.9 mg NO3−-N L−1 d−1. Functional gene analysis also indicated that mcrA and hzsA genes increased after nitrite addition. Based on this finding, influent containing NO3−, NO2− and NH4+ enabled nitrogen removal rates of MBfR increase from 224.9 to 888.2 mg N L−1 d−1. Finally, nitrate in the influent was gradually replaced with nitrite to mimic the effluent from partial nitriation of landfill leachate, but maintain the nitrate availability for n-DAMO archaea through increasing nitrate production from Anammox. These operation strategies enabled MBfR achieve the steady state with a nitrogen removal rate of 6.1 kg N m−3 d−1. Microbial community analysis revealed n-DAMO archaea, n-DAMO bacteria and Anammox bacteria jointly dominated the biofilm, and their relative abundance dynamically shifted with feeding regime. This work provides promising operational strategies for high rate of nitrogen removal from landfill leachate through integrating n-DAMO and Anammox process.

The outbreak of SARS-CoV-2 began in December 2019 and rapidly became a pandemic. The present study investigated the significance of lymphopenia on disease severity. A total of 115 patients with confirmed COVID-19 from a tertiary hospital in Changsha, China, were enrolled. Clinical, laboratory, treatment and outcome data were gathered and compared between patients with and without lymphopenia. The median age was 42 years (1-75). Fifty-four patients (47.0%) of the 115 patients had lymphopenia on admission. More patients in the lymphopenia group had hypertension (30.8% vs. 10.0%, P = 0.006) and coronary heart disease (3.6% vs. 0%, P = 0.029) than in the nonlymphopenia group, and more patients with leukopenia (48.1% vs 14.8%, P