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Abstract Vibration quality is a vital indicator for assessing the progress of modern equipment. The dynamic vibration absorber (DVA) based on the acoustic black hole (ABH) feature is a new passive control method that manipulates waves. It offers efficient energy focalization and broad-spectrum vibration suppression, making it highly promising for applications in large equipment such as aircraft, trains, and ships. Despite previous advancements in ABH-DVA development, certain challenges remain, particularly in ensuring effective coupling with host structures during control. To address these issues, this study proposes a partitioned ABH-featured dynamic vibration absorber (PABH-DVA) with partitions in the radial direction of the disc. By employing a plate as the host structure, simulations and experiments were conducted, demonstrating that the PABH-DVA outperforms the original symmetric ABH-DVA in terms of damping performance. The study also calculated and compared the coupling coefficients of the two ABH-DVAs to uncover the mechanism behind the enhanced damping. Simulation results revealed that the PABH-DVA exhibits more coupled modes, occasionally with lower coupling coefficients than the symmetric ABH-DVA. The influence of frequency ratio and modal mass was further analyzed to explain the reasons behind the PABH-DVA's superior damping performance. Additionally, the study discussed the impact of the number of slits and their orientation. This research further explains the coupling mechanism between the ABH-DVA and the controlled structure, and provides new ideas for the further application of ABH in engineering.

The escalating salinization of cultivated soil poses a significant threat to the ecological environment. It is imperative to establish a monitoring system and mitigate the spread of salinization in arid and coastal areas through remote sensing, incorporating high-precision cross-regional models for soil salt content inversion. This study focuses on typical saline-alkali soils in arid and coastal regions of China. Using Sentinel 2 data (including 6 bands and 27 spectral indices), along with soil texture, moisture content, temperature, precipitation, and digital elevation model (DEM) data to establish an arid-coastal salinity inversion model. Variable selection methods such as pearson correlation coefficient (PCC), variable importance in projection (VIP), gray relational analysis (GRA), and gradient boosting machine (GBM) were used, while using 9 models including adaptive boosting (Adaboost), extremely randomized trees (ERT), and light gradient boosting machine (LightGBM). The best model was further elucidated using the Shapley additive explanations method. Results indicate that the common sensitive characteristic variables of arid-coastal areas were spectral indices and soil properties in PCC, the spectral variable bands and indices in VIP, and all variables in GRA and GBM. The best inversion model GBM-ERT (R2 = 0.91, RMSE = 1.06) in arid areas exhibited higher accuracy than the best inversion model GBM-Adaboost (R2 = 0.77, RMSE = 1.74) in coastal areas. The arid-coastal inversion model PCC-LightGBM demonstrated the best inversion performance (R2 = 0.64, RMSE = 2.29) and simulation performance in arid (R2 = 0.67) and coastal areas (R2 = 0.63). Dead fuel index (DFI) had the most significant impact on model prediction (0.89) and the second ratio index (RI2) contributed the highest relative importance (18 %) to the model. Our analysis indicates that the arid-coastal model of PCC-LightGBM established using common characteristic variables, can effectively monitor large-scale soil salinity.

Soils are a major player in the global carbon (C) cycle and climate change by functioning as a sink or a source of atmospheric carbon dioxide (CO2). The largest terrestrial C reservoir in soils comprises two main pools: organic (SOC) and inorganic C (SIC), each having distinct fates and functions but with a large disparity in global research attention. This study quantified global soil C research trends and the proportional focus on SOC and SIC pools based on a bibliometric analysis and raise the importance of SIC pools fully underrepresented in research, applications, and modeling. Studies on soil C pools started in 1905 and has produced over 47,000 publications (>1.7 million citations). Although the global C stocks down to 2 m depth are nearly the same for SOC and SIC, the research has dominantly examined SOC (>96 % of publications and citations) with a minimal share on SIC (

Abstract Islands are special bodies of land surrounded by seawater. Many islands are facing water shortages as the demand for groundwater increases, thus, highlighting the importance and urgency of the assessment, planning, and management of island groundwater resources. To facilitate the same, the groundwater potential of the Penghu Islands in China was assessed for the first time using remote sensing (RS), geographic information system (GIS), and the analytic hierarchy process (AHP). Long‐term series remote sensing studies were also conducted to monitor the dynamic change in groundwater potential and to identify groundwater potential areas. In this study, the geological environment factors were normalized, and their weight was allocated based on the AHP of RS and GIS. The groundwater potential assessment (GPA) index, established using the weighted comprehensive algorithm, was used to analyse groundwater potential and demarcate groundwater potential zones. Finally, the trend in the spatio‐temporal variation of groundwater potential was analysed using long‐term series remote sensing data. The results from 2015 to 2021 showed that the Penghu Islands can be divided into five groundwater potential zones of different grades, such as 6.3%–8.1% of grade I, 22.2%–24.2% of grade II, 23%–24.4% of grade III, 19.6%–21% of grade IV, and 25.1%–25.5% of grade V. The results of the GPA were verified by comparing them with the abundance of water‐content rock formation in hydrogeologic maps, which yielded correlation coefficients of 78.3%–88.9%. Overall, the groundwater potential zones of different grades in the study area tended to be stable all year‐round, including the zones of grades I and II. The results of this study highlighted the reliability of predicting groundwater potential based on long‐term series remote sensing data and its usability to local personnel in appropriate groundwater resource planning and management.

Net primary productivity (NPP) has been the subject of numerous studies, but the qualitative and comparative study on NPP that considers human activities, climate change, and their interactions is still insufficient. The Grain for Green Program (GTGP) was established in the Loess Plateau since 1999, could be used as a reference study. The temporal and spatial patterns, change trend, and driving factors of vegetation NPP were analysed in Loess Plateau using data derived from GLASS NPP (the Global Land Surface Satellite Product), meteorology, atmospheric quality, hydrology and land use by correlation and improved residual trend analysis from 2000 to 2020. After GTGP implementation, the climate and human contributions to vegetation NPP were 62 % and 38 %. NPP increased at a rate of 6.3 g C m−2 a−1 from 2000 to 2020, which was higher in 2010–2020 (6.9 g C m−2 a−1) than it was in 2000–2010 (5.7 g C m−2 a−1). The same trend was followed by the contribution of climate change to NPP between 2010 and 2020 (70.6 %) and 2000–2010 (65 %). The GTGP core area was mostly where the vegetation NPP rising zone was located. From the original bare land in the desert area, 4442 km2 of vegetation grew and increased the NPP (68.7 g C m−2). Under the warm–humid climatic trend, the climate factors contributed to NPP more in grasslands (40 %) compared to woodlands (29 %) and precipitation (33 %) was more sensitive than temperature (12.7 %). Consequently, sediment transport, PM2.5 and dusty weather decreased significantly. In conclusion, although climate change has a greater impact on vegetation, human activities have enhanced the impact faster in the first decade, which benefit and profit from the environment finally.

Water N-NO3− (mg L−1) pollution is attracting global concern in the face of combating climate change and human health risks. However, there have been comparatively few comprehensively researched studies on water N-NO3− pollution with respect to N-NO3− deposition, soil nitrogen, and land-use changes. We collected a total of 7707 published sampling points on N-NO3− surface and groundwater during flooding and non-flooding seasons during 2000–2020 in China. The types of water N-NO3− pollution (>20) can be categorized as point pollution (ΔTN ≤ 0 or > 1.5) and non-point pollution (0 < ΔTN ≤ 1.5), which were then assessed with respect to soil nitrogen (ΔTN g kg−1) and water N-NO3− changes in this study. We found non-point pollution was concentrated in the Huaihe River Basin and Haihe River Basin with higher urbanization (+6%, +4%), cropland (72%, 45%), nitrogen fertilization (g m−2 yr−1) (>10), and increased wet N-NO3− deposition (WND) (kg ha−1 yr−1) (+4.6, +3). The Haihe River Basin was found to have the highest N-NO3− on its surface (306) and in its groundwater (868) and nitrogen fertilization (32). Point pollution was concentrated in the Songhua and Liaohe River Basin with the highest WND (+7.9) but slow urbanization (+1%). N-NO3− increased during the flooding season compared with the no-flooding season in serious pollution areas. N-NO3− increased in the Liaohe River and middle and low Yangtze River but was reduced in the Weihe River. Therefore, stringent criteria and management, especially during the flooding season are urgently required to mitigate the degree of N-NO3− water pollution that occurs due to intensive agriculture and urbanization with increased N-NO3− deposition.

The unreasonable use of fertilizers is a significant cause of cultivated soil cadmium (Cd) accumulation. Although there is research about the effect of fertilizers on soil cadmium (Cd) accumulation under different crops, soils, and cultivation durations locally and specifically, its relative and determinant factors are seldom comprehensively and comparatively researched and evaluated. We used meta-analysis to analyze the effects of fertilizers (mineral fertilizer N, P, K (NPK) with manure (NPKM), NPK with straw (NPKS), and the mineral fertilizer N (N), NK (NK)), crops, duration, climate, and soil texture on the Chinese soil total and available Cd change during 1987–2022. The results showed that the order of the increased soil total and available Cd change was NPKM (total: 62%–104%, available: 61%–143%) > NPKS (50%–86%, 48%–116%) > NPK (25%–50%, 35%–75%) > NK (5%–19%, 19%–33%) > N (2%–6%, 7%–31%). NPKM and NPKS significantly increased the total Cd under maize (104%, 86%) and available Cd under rice (136%, 116%). Cd changed the fastest with the NPKM cultivation duration for total Cd under maize (slope: 5.9) and available Cd under rice (6.6). The change of the soil total and available Cd had the higher value in the semiarid region, clay soils, lower pH, and long cultivations. The change of the soil total and available Cd were highest (398%, 375%) in the semiarid region for clay loam after 20–25 years of NPKM fertilization, when the pH decreased to the lowest (−1.9). According to the aggregated boosted tree analysis, the fertilizers and duration were the best explanatory variable (>53%) for the soil total and available Cd. In conclusion, the soil Cd could be mitigated through reducing the long–term manure, straw, and P fertilizer content with Cd, and field managements such as liming, wetting, and drying according to the crops, climate, and soil texture.

The integration of sensory information from different modalities, such as touch and vision, is essential for organisms to perform behavioral functions such as decision-making, learning, and memory. Artificial implementation of human multi-sensory perception using electronic supports is of great significance for achieving efficient human–machine interaction. Thanks to their structural and functional similarity with biological synapses, memristors are emerging as promising nanodevices for developing artificial neuromorphic perception. Memristive devices can sense multidimensional signals including light, pressure, and sound. Their in-sensor computing architecture represents an ideal platform for efficient multimodal perception. We review recent progress in multimodal memristive technology and its application to neuromorphic perception of complex stimuli carrying visual, olfactory, auditory, and tactile information. At the device level, the operation model and undergoing mechanism have also been introduced. Finally, we discuss the challenges and prospects associated with this rapidly progressing field of research.

Abstract Auditory motion perception is one crucial capability to decode and discriminate the spatiotemporal information for neuromorphic auditory systems. Doppler frequency‐shift feature and interaural time difference (ITD) are two fundamental cues of auditory information processing. In this work, the functions of azimuth detection and velocity detection, as the typical auditory motion perception, are demonstrated in a WOx‐based memristive synapse. The WOx memristor presents both the volatile mode (M1) and semi‐nonvolatile mode (M2), which are capable of implementing the high‐pass filtering and processing the spike trains with a relative timing and frequency shift. In particular, the Doppler frequency‐shift information processing for velocity detection is emulated in the WOx memristor based auditory system for the first time, which relies on a scheme of triplet spike‐timing‐dependent‐plasticity in the memristor. These results provide new opportunities for the mimicry of auditory motion perception and enable the auditory sensory system to be applied in future neuromorphic sensing.

BackgroundLL-37 is the only member of the cathelicidin family of antimicrobial peptides in humans and is an autoantigen in several autoimmune diseases and in acute coronary syndrome (ACS). In this report, we profiled the specific T cell response to the autoimmune self-antigen LL-37 and investigated the factors modulating the response in peripheral blood mononuclear cells (PBMCs) of healthy subjects and ACS patients.Methods and resultsThe activation induced marker (AIM) assay demonstrated differential T cell profiles characterized by the persistence of CD134 and CD137, markers that impair tolerance and promote immune effector and memory response, in ACS compared to Controls. Specifically, CD8+CD69+CD137+ T cells were significantly increased by LL-37 stimulation in ACS PBMCs. T effector cell response to LL-37 were either HLA dependent or independent as determined by blocking with monoclonal antibody to either Class-I HLA or Class-II HLA. Blocking of immune checkpoints PD-1 and CTLA-4 demonstrated the control of self-reactive T cell response to LL-37 was modulated predominantly by CTLA-4. Platelets from healthy controls down-modulated CD8+CD69+CD137+ T cell response to LL-37 in autologous PBMCs. CD8+CD69+CD137+ T cell AIM profile negatively correlated with platelet count in ACS patients.ConclusionsOur report demonstrates that the immune response to the autoantigen LL-37 in ACS patients is characterized specifically by CD8+CD69+CD137+ T cell AIM profile with persistent T cell activation and the generation of immunologic memory. The results provide potentially novel insight into mechanistic pathways of antigen-specific immune signaling in ACS.

The Quasi-Analytical Algorithm (QAA) is effective in retrieving water inherent optical properties (IOPs) from remote sensing spectral reflectance and has wider applications in studies of the open ocean and coastal waters than of inland waters. This research aimed to modify the QAA model based on measured field spectral reflectance and absorption coefficients to render it applicable to studies of Daihai Lake, China. The improvements mainly included the reference wavelength selection, the power index of the particle backscattering coefficient and the exponential slope of the absorption coefficient of the colored detrital matter estimation. The average relative error between the inverse and measured absorption coefficients was less than 20%. A linear model was established between the phytoplankton absorption coefficient at a wavelength of 674 nm (aph(674)) and the chlorophyll-a (Chl-a) concentration, with a determination coefficient of 0.88. Additionally, the modified Quasi-Analytical Algorithm (MQAA) model was applied to the Ocean and Land Color Instrument (OLCI) data aboard the Sentinel-3 satellite. Finally, a spatial distribution map for the Chl-a concentrations in Daihai Lake on August 10, 2017, was drawn and the mid-eutrophication area was found to occur in the north and border. HIGHLIGHTS The quasi-analytical algorithm (QAA) is modified to MQAA.; The MQAA is useful in application to OLCI data for chlorophyll-a concentration retrieval.; The application of MQAA in Daihai is targeted.;

Abstract Psychological studies have generally shown that individuals with Autism Spectrum Disorder (ASD) have particularity in the processing of social information by using static or abstract images. Yet, a recent study showed that there was no difference in their use of social or non-social cues in dynamic interactive situations. To establish the cause of the inconsistent results, we added gaze cues in different directions to the chase detection paradigm to explore whether they would affect the performance of participants with ASD. Meanwhile, eye-tracking methodology was used to investigate whether the processing patterns of gaze cues were different between individuals with ASD and TD. In this study, unlike typical controls, participants with ASD showed no detection advantage when the direction of gaze was consistent with the direction of movement (oriented condition). The results suggested that individuals with ASD may utilize an atypical processing pattern, which makes it difficult for them to use social information contained in oriented gaze cues in dynamic interactive situations.

Climate and human activities change spatial and temporal distribution of water and land use. The Tarim River, the largest inland river in China, faced a long-term exploitation of land and water over a rapid economic development. We analyzed land and water use from 1997 to 2019 in Tarim River Basin by Landsat images, and data on hydrology, climate, population, economy and PM2.5 (air particulate matter ≤2.5 μm). Agricultural land expanded the fastest (4–11%), followed by natural vegetation (15–16%) and water area (4–5%) with population and economic increase. Air quality (PM2.5 μg m−3) improved in upper (62–27) and middle (48–17) reaches. The water area in lower increase 5% because of ecological water delivery since 2000. Land use in the lower reach was dominated by agriculture, where the downstream runoff consumption increased by 6.8 times. The average annual air temperature and precipitation gradually increased by 0.5 °C and 51 mm in source and 0.9 °C and 30 mm in main reaches. The average annual water consumption in upper and middle reaches was 4 × 109 m3, accounting for 87% of input runoff in the main reach. Water consumption in middle reach increased by 33 times in 2009–2017. The industry structure was changing from primary to secondary and tertiary industry. To sum up, implementation of water saving strategies and ecological water delivery restored local ecology. Sustainable strategies should be applied facing industrialization. Furthermore, changing the industry structure and restoring the degraded farmlands to grasslands or forests would keep sustainability of Tarim River Basin.

This paper mainly researches the application method of red edge band in water body remote sensing extraction. Gaofen-6 (GF-6) WFV data were chosen for the high spatial resolution, more bands, and wide width. Two new methods were proposed: the single-band threshold method based on the red edge 2 band and the decision tree model method based on the combined operation of the green band, red band, near infrared band, red edge 1 band, and red edge 2 band. Four traditional methods were used for comparing the extraction accuracy. Two study areas with different characteristics were chosen to analyze the reliability of the proposed method, one mountainous and one urban region, both located in Minqin, Gansu, China, which is a typical arid area. The results showed that the two red edge bands of the GF-6 WFV data can be utilized to extract water body information. Kappa coefficients extracted from the single-band threshold method based on the red edge 2 band in water bodies in mountainous and urban areas reached 96.18% and 93.21%, respectively. The decision tree method has the best extraction effect. Kappa coefficients of this method in mountain and urban water bodies were 97.73% and 94.41%, respectively. HIGHLIGHTS The red edge band of Chinese Gaofen-6 WFV date was found to be applicable to the extraction of surface water.; A decision tree model based on the joint operation of five bands was established, which can effectively extract surface water.;

For the CH3NH3PbI3-based optoelectronic memristor, the high ion-migration randomness induces high fluctuation in the resistive switching (RS) parameters. Grain boundaries (GBs) are well known as the ion-migration sites due to their low energy barrier. Herein, a polyacrylonitrile (PAN) passivation method is developed to reduce GBs of the CH3NH3PbI3 film and improve the switching uniformity of the memristor. The crystal grain size of CH3NH3PbI3 increases with the addition of PAN, and the corresponding number of GBs is consequently reduced. The fluctuations of the RS parameters of the memristor device are significantly reduced. With the memristor, nonvolatile image sensing, image memory, and image Boolean operations are demonstrated. This work proposes a strategy for developing high-performance CH3NH3PbI3 optoelectronic memristors.

Alluvial fan and Fluvial facies sand bodies are important reservoirs for oil and gas resources. In this study, the sedimentary characteristics and evolutionary patterns of Alluvial fan and fluvial deposits in the Neogene Guantao Formation of the Dongying Sag, Bohai Bay Basin were analyzed using cores, well logs and three-dimensional seismic data, and the quantitative information of the sand bodies in different deposits were characterized with dense well-net constraints. Through the calibration between the core and wireline logging data, the developmental characteristics of the sand bodies in the Alluvial fan and fluvial deposits were clearly defined base on sedimentary microfacies and seismic facies interpretation. Using the RMS amplitude attribute and reconstructed Wave Impedance Inversion, the sand bodies of Guantao Formation in this area were carefully described and studied, and the effective reservoir range was predicted on the basis of fully understanding the oil test data. Results: The top and bottom interface of Guantao Formation are characterized by strong continuous reflection on seismic section, exist within the guantao on seismic section three continuous or intermittent peaks, from bottom to top respectively represent the interface between Ng4 and Ng3 sand group, the interface between Ng3 and Ng2 sand group,the interface between Ng2 and Ng1 of the Guantao Formation, and Ng4 sand group of the Guantao Formation is the key layer; The boundary Growth Fault and Binxian high jointly controlled the deposition of Guantao Formation. The sedimentary thickness of the strata decreased on the north and west sides of the sag, and increased from the core to the edge of the Binxian high; The sedimentary facies of Guantao Formation in the study area can be divided into three types: alluvial fan facies, braided river facies and meandering river facies, and various corresponding subfacies and microfacies can be subdivided into different types. Ng4 sand group of the Guantao Formation is identified as alluvial fan-braided river model; Based on the analysis of the distribution and physical properties of alluvial and fluvial facies sand bodies in the study area, it is considered that the effective reservoir of Ng4 sand group of the Guantao Formation is mainly developed in the nose structure around Binxian high, and is semicircular in distribution.

Electronic devices with biomaterials have paved a way toward “green electronics” to create a sustainable future. Memristors are drawing growing attention with integrated sensing, memory, and computing for future artificial intelligence applications. Biomaterial is an emerging class of memristive materials (the device is called as biomemristor) for transient and/or biodegradable purpose. Importantly, several unique features such as faithful synaptic behaviors, bimodal switching, and biovoltage operations are observed in biomemristors. Moreover, the biomemristors are suitable for human‐related applications due to the inherent biocompatibility of biomaterials and flexibility of the device with ultrathin thickness. These features make the biomemristors promising for biorealistic neuromorphic applications. Herein, the state of the art of biomemristors are comprehensively summarized and systematically discussed with particular attention on their unique biorealistic features. Challenges and prospects toward the further development of biomemristors are also provided and discussed.

The intriguing properties of two-dimensional (2D) transition metal dichalcogenides (TMDCs) enable the exploration of new electronic device architectures, particularly the emerging memristive devices for in-memory computing applications. Implementation of arithmetic logic operations taking advantage of the non-linear characteristics of memristor can significantly improve the energy efficiency and simplify the complexity of peripheral circuits. Herein, we demonstrate an arithmetic logic unit function using a lateral volatile memristor based on layered 2D tungsten disulfide (WS2) materials and some combinational logic circuits. Removable oxygen ions were introduced into WS2 materials through oxygen plasma treatment process. The resistive switching of the memristive device caused by the thermophoresis-assisted oxygen ions migration has also been revealed. Based on the characteristics of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and spike rate dependent plasticity (SRDP), a real-time numerical system convertor was successfully accomplished, which is a significant computing function of arithmetic logic unit. This work paves a new way for developing 2D memristive devices for future arithmetic logic applications.

Active immunization with the apolipoprotein B-100 (ApoB-100) peptide P210 reduces experimental atherosclerosis. To advance this immunization strategy to future clinical testing, we explored the possibility of delivering P210 as an antigen using nanoparticles, given this approach has been used clinically. We first characterized the responses of T cells to P210 using PBMCs from patients with atherosclerotic cardiovascular disease (ASCVD). We then investigated the use of P210 in self-assembling peptide amphiphile micelles (P210-PAMs) as a vaccine formulation to reduce atherosclerosis in B6.129P2-Apoetm1Unc/J (ApoE–/–) mice and P210’s potential mechanisms of action. We also generated and characterized a humanized mouse model with chimeric HLA-A*02:01/Kb in ApoE–/– background to test the efficacy of P210-PAM immunization as a bridge to future clinical testing. P210 provoked T cell activation and memory response in PBMCs of patients with ASCVD. Dendritic cell uptake of P210-PAM and its costaining with MHC-I molecules supported its use as a vaccine formulation. In ApoE–/– mice, immunization with P210-PAMs dampened P210-specific CD4+ T cell proliferative response and CD8+ T cell cytolytic response, modulated macrophage phenotype, and significantly reduced aortic atherosclerosis. Potential clinical relevance of P210-PAM immunization was demonstrated by reduced atherosclerosis in the humanized ApoE–/– mouse model. Our data support experimental and translational use of P210-PAM as a potential vaccine candidate against human ASCVD.

Although a number of studies have provided information on soil texture, soil classification, and depth to bedrock throughout China, few studies have combined this information, which is the basis for agricultural field management. A total of 81% of China’s cultivated lands are distributed among the Middle–Lower Yangtze Plain (18.2%), arid and semiarid North China Plain (18.2%), Northeast Plain (17%), Huang-Huai-Hai Plain (16.1%), and Yunnan–Guizhou Plateau (11.6%). The Huang-Huai-Hai Plain has the highest density of agricultural land (58.5%) and the greatest depth to bedrock of cultivated land (243–402 m). The lowest cultivated depth to bedrock (4–84 m) is concentrated in the Sichuan Basin and its surrounding regions. The main cultivated soil types are Anthrosols, Fluvisols, Cambisols, Phaeozems, Luvisols, Kastanozems, Leptosols, and Acrisols, under the main topsoil texture classes of loam, clay loam, silty clay loam, silt loam, sandy loam, and clay. The Fluvisols had the largest depth to bedrock (156 m) on the Middle–Lower Yangtze Plain and Huang-Huai-Hai Plain, with the highest silt soil distributions but comparable lower sand contents. The Yunnan–Guizhou Plateau had the highest clay soil content. The cultivation under Kastanozems and Leptosols on the Qinghai–Tibet Plateau and in arid and semiarid North China and under Phaeozems on the Northeast Plain should be restricted and managed very cautiously facing erosion risk. The higher percentages of Anthrosols are on the Middle–Lower Yangtze Plain (37%), in Southern China (32%), and on the Yunnan–Guizhou Plateau (26%). The same cultivation aim (i.e., more crop 0production) has produced a similar range of properties over time among the soils developed on agricultural fields, which are classified as Anthrosols. However, various soil types can still be found in agroecosystems because of the variations in climate and topography. Our results highlight that the agriculture-based soil climate and topography shape the interaction of the soil development and not only the pedogenic history of the soil development under variations in the soil depth to bedrock but also the cultivation of distinct pedogenic features. This study provides cultivated soil information on the depth to bedrock, soil classification, and soil texture in China, as well as instructions for field strategies for sustainable agricultural development.

Over-fertilization has a significant impact on soil microbial properties and its ecological environment. However, the effects of long-term fertilization on microbial properties on a large scale are still vague. This meta-analysis collected 6211 data points from 109 long-term experimental sites in China to evaluate the effects of fertilizer type and fertilization duration, as well as soil and climate conditions, on the effect sizes on various microbial properties and indices. The organic fertilizers combined with straw (NPKS) and manure (NPKM) had the highest effect sizes, while the chemical fertilizers N (sole N fertilizer) and NPK (NPK fertilizer) had the lowest. When compared with the control, NPKM treatment had the highest effect size, while N treatment had the lowest effect size on MBN (111% vs. 19%), PLFA (110% vs. −7%), fungi (88% vs. 43%), Actinomycetes (97% vs. 44%), urease (77% vs. 25%), catalase (15% vs. −11%), and phosphatase (58% vs. 4%). NPKM treatment had the highest while NPK treatment had the lowest effect size on bacteria (123% vs. 33%). NPKS treatment had the highest while N treatment had the lowest effect sizes on MBC (77% vs. 8%) and invertase (59% vs. 0.2%). NPKS treatment had the highest while NPK treatment had the lowest effect size on the Shannon index (5% vs. 1%). The effect sizes of NPKM treatment were the highest predominantly in arid regions because of the naturally low organic carbon in soils of these regions. The effect sizes on various microbial properties were also highly dependent on soil texture. In coarse-textured soils the effect sizes on MBC and MBN peaked sooner compared with those of clayey or silty soils, although various enzymes were most active in silty soils during the first 10 years of fertilization. Effect sizes on microbial properties were generally higher under NPKM and NPKS treatments than under NPK or N treatments, with considerable effects due to climate conditions. The optimal field fertilizer regime could be determined based on the effects of fertilizer type on soil microorganisms under various climate conditions and soil textures. This will contribute to the microbial biodiversity and soil health of agricultural land. Such controls should be used for adaptation of fertilization strategies to global changes.

Abstract Background Ectopic expression of CDX2 is associated with the development and progression of gastric cancer. Previous studies showed that CDX2 may be an upstream regulator of Reg IV expression in gastric cancer, and our previous report showed that Reg IV upregulated SOX9 expression and enhanced cell migration and invasion in gastric cancer cells. However, the regulatory roles of CDX2 have not been clarified in gastric cancer, and the correlation between CDX2 and Reg IV requires further study. Methods CDX2 and Reg IV were examined in gastric cancer specimens and paired adjacent tissues via real-time PCR and immunohistochemistry (IHC). The association between CDX2 and Reg IV was assessed using the χ2-test and Spearman’s rank correlation. To verify their relationship, knockdown and exogenous expression of CDX2 or Reg IV were performed in AGS and MKN-45 gastric cancer cells, and their expression was subsequently analyzed via a real-time PCR and western blotting. Wound-healing and Transwell assays were used to examine migration and invasion in AGS and MKN-45 cells following CDX2 silencing or overexpression. Results A positive correlation was observed between CDX2 and Reg IV expression at the mRNA and protein levels in gastric cancer tissues. CDX2 silencing significantly downregulated Reg IV expression, and CDX2 overexpression significantly upregulated Reg IV expression in AGS and MKN-45 cells. Neither Reg IV silencing nor overexpression had any effect on CDX2 protein expression in AGS or MKN-45 cells, even though both affected the expression of CDX2 mRNA. Functionally, CDX2 silencing significantly inhibited cell migration and invasion, and CDX2 overexpression significantly promoted cell migration and invasion in AGS and MKN-45 cells. Conclusions Our findings demonstrate that CDX2 expression was positively correlated with that of Reg IV in gastric cancer, and CDX2 promoted cell migration and invasion through upregulation of Reg IV expression in AGS and MKN-45 cells.

Spiking neural network (SNN), widely known as the third-generation neural network, has been frequently investigated due to its excellent spatiotemporal information processing capability, high biological plausibility, and low energy consumption characteristics. Analogous to the working mechanism of human brain, the SNN system transmits information through the spiking action of neurons. Therefore, artificial neurons are critical building blocks for constructing SNN in hardware. Memristors are drawing growing attention due to low consumption, high speed, and nonlinearity characteristics, which are recently introduced to mimic the functions of biological neurons. Researchers have proposed multifarious memristive materials including organic materials, inorganic materials, or even two-dimensional materials. Taking advantage of the unique electrical behavior of these materials, several neuron models are successfully implemented, such as Hodgkin–Huxley model, leaky integrate-and-fire model and integrate-and-fire model. In this review, the recent reports of artificial neurons based on memristive devices are discussed. In addition, we highlight the models and applications through combining artificial neuronal devices with sensors or other electronic devices. Finally, the future challenges and outlooks of memristor-based artificial neurons are discussed, and the development of hardware implementation of brain-like intelligence system based on SNN is also prospected.

Abstract Exploration of optoelectronic memristors with the capability to combine sensing and processing functions is required to promote development of efficient neuromorphic vision. In this work, the authors develop a plasmonic optoelectronic memristor that relies on the effects of localized surface plasmon resonance (LSPR) and optical excitation in an Ag–TiO2 nanocomposite film. Fully light‐induced synaptic plasticity (e.g., potentiation and depression) under visible and ultraviolet light stimulations is demonstrated, which enables the functional combination of visual sensing and low‐level image pre‐processing (including contrast enhancement and noise reduction) in a single device. Furthermore, the light‐gated and electrically‐driven synaptic plasticity can be performed in the same device, in which the spike‐timing‐dependent plasticity (STDP) learning functions can be reversibly modulated by visible and ultraviolet light illuminations. Thereby, the high‐level image processing function, i.e., image recognition, can also be performed in this memristor, whose recognition rate and accuracy are obviously enhanced as a result of image pre‐processing and light‐gated STDP enhancement. Experimental analysis shows that the memristive switching mechanism under optical stimulation can be attributed to the oxidation/reduction of Ag nanoparticles due to the effects of LSPR and optical excitation. The authors' work proposes a new type of plasmonic optoelectronic memristor with fully light‐modulated capability that may promote the future development of efficient neuromorphic vision.

Pyrrolizidine alkaloids (PAs) constitute a class of phytotoxin which demonstrates strong hepatotoxicity. In China, many plants containing PAs are used as traditional medicines or medicinal preparations, which could harm human health and safety. Xiaoyao Tablet (XYT) is an antidepressant drug registered in the European Union (EU), Compound Danshen Dropping Pills (CDDP) is a commonly used drug for coronary heart disease, and phase III clinical study is ongoing in the United States. The purpose of this study is to provide data to support the use of Chinese medicine preparations internationally and to establish analytical methods for 32 PAs in XYT and CDDP. The extraction parameters that were optimized include solid-phase extraction (SPE) cartridge, extraction method, and extraction solvent. Then ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-traptandem mass spectrometry (UPLC-MS/MS) was developed to effectively and efficiently quantify the 32 PAs of the XYT and CDDP. The analytical methods for XYT and CDDP were verified respectively. For XYT, the analytical method for 32 PAs was linear, and the correlation coefficient r was greater than 0.994; the recovery (REC%) at 10–2000 μg/kg was 73.3%–118.5%, and the relative standard deviation (RSD%) was 2.1%–15.4%. The CDDP REC% was 71.8%–112.0%, and the RSD% was 2.0%–17.1%. This study provides technical and data support for the registration of Chinese patented medicines in the EU, controls quality and ensures safety, and is committed to the internationalization and standardization of Chinese patented medicines.

Designing reliable and energy efficient neuromorphic computing systems for spatiotemporal coding remains a challenge. Here, the authors demonstrate a type of spike-rate-dependent plasticity based on a triplet learning scheme in a WO3−x-based second-order memristor network for spatiotemporal patterns.

Soil salinization is one of the main causes of global desertification and soil degradation. Although previous studies have investigated the hyperspectral inversion of soil salinity using machine learning, only a few have been based on soil types. Moreover, agricultural fields can be improved based on the accurate estimation of the soil salinity, according to the soil type. We collected field data relating to six salinized soils, Haplic Solonchaks (HSK), Stagnic Solonchaks (SSK), Calcic Sonlonchaks (CSK), Fluvic Solonchaks (FSK), Haplic Sonlontzs (HSN), and Takyr Solonetzs (TSN), in the Hetao Plain of the upper reaches of the Yellow River, and measured the in situ hyperspectral, pH, and electrical conductivity (EC) values of a total of 231 soil samples. The two-dimensional spectral index, topographic factors, climate factors, and soil texture were considered. Several models were used for the inversion of the saline soil types: partial least squares regression (PLSR), random forest (RF), extremely randomized trees (ERT), and ridge regression (RR). The spectral curves of the six salinized soil types were similar, but their reflectance sizes were different. The degree of salinization did not change according to the spectral reflectance of the soil types, and the related properties were inconsistent. The Pearson’s correlation coefficient (PCC) between the two-dimensional spectral index and the EC was much greater than that between the reflectance and EC in the original band. In the two-dimensional index, the PCC of the HSK-NDI was the largest (0.97), whereas in the original band, the PCC of the SSK400 nm was the largest (0.70). The two-dimensional spectral index (NDI, RI, and DI) and the characteristic bands were the most selected variables in the six salinized soil types, based on the variable projection importance analysis (VIP). The best inversion model for the HSK and FSK was the RF, whereas the best inversion model for the CSK, SSK, HSN, and TSN was the ERT, and the CSK-ERT had the best performance (R2 = 0.99, RMSE = 0.18, and RPIQ = 6.38). This study provides a reference for distinguishing various salinization types using hyperspectral reflectance and provides a foundation for the accurate monitoring of salinized soil via multispectral remote sensing.

Both cropland management and slop erosion are important factors influencing soil properties, but there are relatively few studies on their combined effects. Studies at the agricultural watershed scale can satisfy both of these conditions, and to reduce the effects of soil heterogeneity due to differences in spatial scale, it is better to select different slopes in the same small watershed. To understand how soil properties will respond to the variation of slope position and cropland management at an agricultural watershed, we present the distribution of soil bulk density (BD), saturated hydraulic conductivity (Ks), water-stable aggregates, soil organic carbon (OC), nitrogen (N), and phosphorus (P) at four slope positions in two cropland management systems of a small agricultural watershed in the black soil region of northeast China. The selected four slope positions include upper slope, middle slope, lower slope, and footslope positions. The two cropland management systems consist of a sustainable cropland system (i.e., contour ridge tillage at upper slope position, longitudinal ridge tillage at middle slope and lower slope positions, and grassland at footslope position) and a conventional cropland system (i.e., contour ridge tillage at upper slope position, longitudinal ridge tillage at middle slope, lower slope positions, and footslope positions). The results showed that soil bulk density and microaggregates decreased but the concentration of OC and nutrients, Ks, and small-macroaggregate increased from the upper slope position to the lower slope position in both the conventional and sustainable croplands, which was due to the interaction effect of cultivation with erosion. In comparison with conventional cropland, sustainable cropland has greater Ks, large-macroaggregate, small-macroaggregate, microaggregate, and concentrations and stocks of OC, N, and P, but showed lower bulk density and silt + clay fraction. However, the prominent differences in both croplands were presented in the footslope position, which is ascribed to the interaction of cultivation, erosion, and cropland management. These results highlighted that sustainable cropland management practice has the potential to improve soil structure and prevent soil and nutrient loss.

The long-term overuse of fertilizers negatively affects soil chemical properties and health, causing unsustainable agricultural development. Although many studies have focused on the effects of long-term fertilization on soil properties, few comparative and comprehensive studies have been conducted on fertilization management over the past 35 years in China. This meta-analysis (2058 data) evaluated the effects of the fertilizer, climate, crop types, cultivation duration and soil texture on the soil chemical properties of Chinese croplands. NPKM (NPK fertilizers + manure) led to the highest increase in pH (−0.1), soil organic carbon (SOC) (+67%), total nitrogen (TN) (+63%), alkali-hydrolysable nitrogen (AN) (+70%), total phosphorus (TP) (+149%) and available potassium (AK) (+281%) compared to the unfertilized control, while the sole nitrogen fertilizer (N) led to the lowest increase. The SOC (+115%) and TN (+84%) showed the highest increase under the influence of NPKM in an arid region. The increase in the chemical properties was higher in unflooded crops, with the maximum increase in the wheat–maize rotation, compared to rice, under NPKM. The SOC and TN increased faster under the influence of organic fertilizers (manure or straw) compared to mineral fertilization. Fertilizers produced faster effects on the change in the SOC and TN in sandy loam compared to the control. Fertilizers showed the highest and lowest effects on change in pH, organic C to total N ratio (C/N), TP and TK in clay loam with the cultivation duration. NPKM greatly increased the C/N compared to NPK in an arid region by 1.74 times and in wheat by 1.86 times. Reaching the same SOC increase, the lowest TN increase was observed in wheat, and the lowest increase in TP and AK was observed in rice, compared to the other crops. These results suggest that organic fertilizers (manure or straw) play important roles in improving soil fertility and in acidification. NPKM greatly increased the potential for soil C sequestration in wheat and in the arid region. The small increases in TP and TK can increase the SOC in rice and in the humid region. Therefore, considering the crop types and climatic conditions, reduced fertilization and the combination of mineral fertilizers with manure may be the best ways to avoid agricultural soil deterioration and increase soil carbon sequestration.

Commercial Saccharomyces cerevisiae plays an important role in the traditional winemaking industry. In this study, the correlation of microbial community and aroma compound in the process of alcohol fermentation of Cabernet Sauvignon by four different commercial starters was investigated. The results showed that there was no significant difference in the fermentation parameters of the four starters, but there were differences in microbial diversity among the different starters. The wine samples fermented by CEC01 had higher microbial abundance. GC-MS detected a total of 58 aromatic compounds from the fermentation process by the experimental yeasts. There were 25 compounds in the F6d variant, which was higher than in other samples. The PCA score plot showed that 796 and F15 yeast-fermented wines had similar aromatic characteristic compositions. According to partial least squares (PLS, VIP > 1.0) analysis and Spearman’s correlation analysis, 11, 8, 8 and 10 microbial genera were identified as core microorganisms in the fermentation of 796, CEC01, CECA and F15 starter, respectively. Among them, Leuconostoc, Lactobacillus, Sphingomonas and Pseudomonas played an important role in the formation of aroma compounds such as Ethyl caprylate, Ethyl caprate and Ethyl-9-decenoate. These results can help us to have a better understanding of the effects of microorganisms on wine aroma and provide a theoretical basis for improving the flavor quality of Cabernet Sauvignon wine.

A neuromorphic computing chip that can imitate the human brain’s ability to process multiple types of data simultaneously could fundamentally innovate and improve the von-neumann computer architecture, which has been criticized. Memristive devices are among the best hardware units for building neuromorphic intelligence systems due to the fact that they operate at an inherent low voltage, use multi-bit storage, and are cost-effective to manufacture. However, as a passive device, the memristor cell needs external energy to operate, resulting in high power consumption and complicated circuit structure. Recently, an emerging self-powered memristive system, which mainly consists of a memristor and an electric nanogenerator, had the potential to perfectly solve the above problems. It has attracted great interest due to the advantages of its power-free operations. In this review, we give a systematic description of self-powered memristive systems from storage to neuromorphic computing. The review also proves a perspective on the application of artificial intelligence with the self-powered memristive system.

Abstract Organic‐inorganic halide perovskites (OHPs) have been intensively studied for application in solar cells with high conversion efficiency exceeding 22%. The unique electrical and optical properties of OHPs have led to their use in optoelectronic device applications beyond photovoltaics, such as light‐emitting diodes, photodetectors, transistors. New information storage technologies and computing architectures are being researched extensively with the aim of addressing the growing challenge of approaching end of Moore's law and von Neumann bottleneck. As the fourth basic circuit element, memristor is a leading candidate with powerful capabilities in information storage and neuromorphic computing applications. Recently, OHPs have received growing attention as promising materials for memristors. In particular, their mixed ionic‐electronic conduction ability paired with light sensitivity provide OHPs with the opportunity to display novel functions such as optical‐erase memory, optogenetics‐inspired synaptic functions, and light‐accelerated learning capability. This review covers recent advances in OHP‐based memristors development including memristive mechanism and analytical models, universal memristive characteristics for memory and neuromorphic computing applications, and novel multi‐functionalization. Challenges and future prospects of OHP‐based memristors are also discussed.

An accurate estimation of soil electrical conductivity (EC) using hyperspectral techniques is of great significance for understanding the spatial distribution of solutes and soil salinization. Although spectral transformation has been widely used in data pre-processing, the performance of different pre-processing techniques (or combination methods) on different models of the same data set is still ambiguous. Moreover, extremely randomized trees (ERT) and light gradient boosting machine (LightGBM) models are new learning algorithms with good generalization performance (soil moisture and above-ground biomass), but are less studied in estimating soil salinity in the visible and near-infrared spectra. In this study, 130 soil EC data, soil measured hyperspectral data, topographic factors, conventional salinity indices such as Salinity Index 1, and two-band (2D) salinity indices such as ratio indices, were introduced. The five spectral pre-processing methods of standard normal variate (SNV), standard normal variate and detrend (SNV-DT), inverse (1/OR) (OR is original spectrum), inverse-log (Log(1/OR) and fractional order derivative (FOD) (range 0–2, with intervals of 0.25) were performed. A gradient boosting machine (GBM) was used to select sensitive spectral parameters. Models (extreme gradient boosting (XGBoost), LightGBM, random forest (RF), ERT, classification and regression tree (CART), and ridge regression (RR)) were used for inversion soil EC and model validation. The results reveal that the two-dimensional correlation coefficient highlighted EC more effectively than the one-dimensional. Under SNV and the second order derivative, the two-dimensional correlation coefficient increased by 0.286 and 0.258 compared to the one-dimension, respectively. The 13 characteristic factors of slope, NDI, SI-T, RI, profile curvature, DOA, plane curvature, SI (conventional), elevation, Int2, aspect, S1 and TWI provided 90% of the cumulative importance for EC using GBM. Among the six machine models, the ERT model performed the best for simulation (R2 = 0.98) and validation (R2 = 0.96). The ERT model showed the best performance among the EC estimation models from the reference data. The kriging map based on the ERT simulation showed a close relationship with the measured data. Our study selected the effective pre-processing methods (SNV and the 2 order derivative) using one- and two-dimensional correlation, 13 important factors and the ERT model for EC hyperspectral inversion. This provides a theoretical support for the quantitative monitoring of soil salinization on a larger scale using remote sensing techniques.

The increases in crop yield in China are linked to massive increases in fertilizer and water input, which have also accelerated the degradation of soil and environmental pollution. Nevertheless, the long-term changes in crop yield and water use efficiency (WUE) of three major cereals (maize, wheat and rice) in response to field management practices are rarely reported. This meta-analysis evaluated the effect of field management (nitrogen input (N), irrigation, fertilizer type, fertilization frequency, and irrigation method) on crop yield and WUE between 1990 and 2020 based on 3152 observations. We found that the N thresholds for maize, wheat, and rice were 150–200 kg ha−1, 140–210 kg ha−1, and 90–135 kg ha−1, respectively. N fertilization within the threshold levels increased the crop yield and WUE of maize (84% and 74%), wheat (47% and 41%), and rice (55% and 30%). The irrigation (mm) thresholds for maize and wheat were 180–240 mm and 300–400 mm and crop yield and WUE were increased by 37% and 13% for maize and by 84% and 41% for wheat. Agricultural management increased yield and WUE (% and %) through drip irrigation (23 and 13 maize; 31 and 14 wheat), alternate wetting and drying (AWD) (26 and 30 rice), split fertilization (31 and 21 maize; 64 and 40 wheat; 33 and 25 rice) and organic–inorganic fertilizer (43 and 39 maize; 68 and 66 wheat; 38 and 34 rice). With the increase in HI (humidity index) from 10 to 30, the contribution of irrigation to WUE decreased, but that of fertilization increased. This study concludes that N fertilizer and irrigation applications between threshold levels along with suitable field management is a win–win strategy to achieve climate-smart agricultural production with minimum damages to soil and environment and at lower dependence on fertilizer and irrigation.

The human cationic anti-microbial peptide LL-37 is a T cell self-antigen in patients with psoriasis, who have increased risk of cardiovascular events. However, the role of LL-37 as a T cell self-antigen in the context of atherosclerosis remains unclear. The objective of this study was to test for the presence of T cells reactive to LL-37 in patients with acute coronary syndrome (ACS). Furthermore, the role of T cells reactive to LL-37 in atherosclerosis was assessed using apoE−/− mice immunized with the LL-37 mouse ortholog, mCRAMP. Peripheral blood mononuclear cells (PBMCs) from patients with ACS were stimulated with LL-37. PBMCs from stable coronary artery disease (CAD) patients or self-reported subjects served as controls. T cell memory responses were analyzed with flow cytometry. Stimulation of PBMCs with LL-37 reduced CD8+ effector T cell responses in controls and patients with stable CAD but not in ACS and was associated with reduced programmed cell death protein 1 (PDCD1) mRNA expression. For the mouse studies, donor apoE−/− mice were immunized with mCRAMP or adjuvant as controls, then T cells were isolated and adoptively transferred into recipient apoE−/− mice fed a Western diet. Recipient mice were euthanized after 5 weeks. Whole aortas and hearts were collected for analysis of atherosclerotic plaques. Spleens were collected for flow cytometric and mRNA expression analysis. Adoptive transfer experiments in apoE−/− mice showed a 28% reduction in aortic plaque area in mCRAMP T cell recipient mice (P < 0.05). Fifty six percent of adjuvant T cell recipient mice showed calcification in atherosclerotic plaques, compared to none in the mCRAMP T cell recipient mice (Fisher’s exact test P = 0.003). Recipients of T cells from mice immunized with mCRAMP had increased IL-10 and IFN-γ expression in CD8+ T cells compared to controls. In conclusion, the persistence of CD8+ effector T cell response in PBMCs from patients with ACS stimulated with LL-37 suggests that LL-37-reactive T cells may be involved in the acute event. Furthermore, studies in apoE−/− mice suggest that T cells reactive to mCRAMP are functionally active in atherosclerosis and may be involved in modulating plaque calcification.

A significant body of work implicates the adaptive immune response in atherosclerosis, the main underlying cause of coronary artery disease (CAD), yet specific antigens involved remain to be fully identified. The pathobiology of CAD is influenced by sex with many factors that may be involved in the underlying mechanisms. Given the reported sexual dimorphic nature of immune-inflammatory responses, we investigated the influence of sex on potential CAD self-antigens from acute coronary syndrome (ACS) patients using immune-precipitation of soluble HLA Class-I/peptide complexes and mass spectrometry. Relevance of identified self-antigens to atherosclerosis, the major underlying cause of CAD, was tested in the apoE–/– atherosclerotic mouse model. Soluble HLA Class-I complexes from ACS patients and self-reported controls were immune-precipitated and subjected to elution, denaturation and size-exclusion to obtain HLA-bound peptides. Peptides were then subjected to mass spectrometry and patient-unique self-peptides were grouped as common to both female and male, or unique to either sex. Three peptides common to both female and male patients (COL6A1, CDSN, and SAA2), and 2 peptides each unique to female (COL1A1 and COL5A2) or male (SAA1 and KRT 9) patients were selected and mouse homologs of the peptides were screened for self-reactive immune responses in apoE–/– mice. The screening step revealed potential sex-influenced immune responses which was associated with differential immune profiles. Based on the frequency in patient plasma, COL6A1, COL5A2, and KRT 9 peptides were then tested in immunization studies. Neither COL5A2 nor KRT 9 peptide immunization resulted in significant effects on atherosclerosis compared to controls. On the other hand, female mice immunized with COL6A1 peptide had significantly reduced atherosclerosis whereas male mice had significantly increased atherosclerosis, associated with differential immune profiles. Our study identified potential self-antigens involved in atherosclerosis using the immune peptidome of CAD patients. Altering self-reactive immune responses to COL6A1 in apoE–/– mice resulted in differential effects on atherosclerosis burden with sex as a determinant of outcome.

Abstract Transition-metal nitrides exhibit wide potential windows and good electrochemical performance, but usually experience imbalanced practical applications in the energy storage field due to aggregation, poor circulation stability, and complicated syntheses. In this study, a novel and simple multi-phase polymeric strategy was developed to fabricate hybrid vanadium nitride/carbon (VN/C) membranes for supercapacitor negative electrodes, in which VN nanoparticles were uniformly distributed in the hierarchical porous carbon 3D networks. The supercapacitor negative electrode based on VN/C membranes exhibited a high specific capacitance of 392.0 F g−1 at 0.5 A g−1 and an excellent rate capability with capacitance retention of 50.5% at 30 A g−1. For the asymmetric device fabricated using Ni(OH)2//VN/C membranes, a high energy density of 43.0 Wh kg−1 at a power density of 800 W kg−1 was observed. Moreover, the device also showed good cycling stability of 82.9% at a current density of 1.0 A g−1 after 8000 cycles. This work may throw a light on simply the fabrication of other high-performance transition-metal nitride-based supercapacitor or other energy storage devices.

Modulating inflammation by targeting IL-1β reduces recurrent athero-thrombotic cardiovascular events without lipid lowering. This presents an opportunity to explore other pathways associated with the IL-1β signaling cascade to modulate the inflammatory response post-myocardial infarction (MI). IL-7 is a mediator of the inflammatory pathway involved in monocyte trafficking into atherosclerotic plaques and levels of IL-7 have been shown to be elevated in patients with acute MI. Recurrent athero-thrombotic events are believed to be mediated in part by index MI-induced exacerbation of inflammation in atherosclerotic plaques. The objective of the study was to assess the feasibility of IL-7R blockade to modulate atherosclerotic plaque inflammation following acute MI in ApoE−/- mice. Mice were fed Western diet for 12 weeks and then subjected to coronary occlusion to induce an acute MI. IL-7 expression was determined using qRT-PCR and immuno-staining, and IL-7R was assessed using flow cytometry. Plaque inflammation was evaluated using immunohistochemistry. IL-7R blockade was accomplished with monoclonal antibody to IL-7R. IL-7 mRNA expression was significantly increased in the cardiac tissue of mice subjected to MI but not in controls. IL-7 staining was observed in the coronary artery. Plaque macrophage and lipid content were significantly increased after MI. IL-7R antibody treatment but not control IgG significantly reduced macrophage and lipid content in atherosclerotic plaques. The results show that IL-7R antibody treatment reduces monocyte/macrophage and lipid content in the atherosclerotic plaque following MI suggesting a potential new target to mitigate increased plaque inflammation post-MI. Keywords: IL-7R, Plaque inflammation, Myocardial infarction

BackgroundInflammation is an important risk factor in atherosclerosis, the underlying cause of coronary artery disease (CAD). Unresolved inflammation may result in maladaptive immune responses and lead to immune reactivity to self-antigens. We hypothesized that inflammation in CAD patients would manifest in immune reactivity to self-antigens detectable in soluble HLA-I/peptide complexes in the plasma.MethodsSoluble HLA-I/peptide complexes were immuno-precipitated from plasma of male acute coronary syndrome (ACS) patients or age-matched controls and eluted peptides were subjected to mass spectrometry to generate the immunopeptidome. Self-peptides were ranked according to frequency and signal intensity, then mouse homologs of selected peptides were used to test immunologic recall in spleens of male apoE-/- mice fed either normal chow or high fat diet. The peptide detected with highest frequency in patient plasma samples and provoked T cell responses in mouse studies was selected for use as a self-antigen to stimulate CAD patient peripheral blood mononuclear cells (PBMCs).ResultsThe immunopeptidome profile identified self-peptides unique to the CAD patients. The mouse homologs tested showed immune responses in apoE-/- mice. Keratin 8 was selected for further study in patient PBMCs which elicited T Effector cell responses in CAD patients compared to controls, associated with reduced PD-1 mRNA expression.ConclusionAn immunopeptidomic strategy to search for self-antigens potentially involved in CAD identified Keratin 8. Self-reactive immune response to Keratin 8 may be an important factor in the inflammatory response in CAD.

Abstract The absence of an effective approach to achieve free‐standing inorganic memristors seriously hinders the development of transferable artificial synapses. Here, a transferable WOx‐based memristive synapse is demonstrated using a nondestructive water‐dissolution method in which the NaCl substrate is selected as the sacrificial layer due to its thermotolerance and water‐solubility. The essential synaptic learning functions are achieved to comprehensively mimic the biological synapse, such as short‐term/long‐term plasticity, paired‐pulse facilitation, and spike‐timing‐dependent plasticity. This artificial synapse can be transferred and conformed onto various unconventional substrates to manifest the flexibility, 3D conformality, and biocompatibility. There is no mechanical damage during the transfer process, and all these transferred devices present excellent synaptic emulations. The memristive behavior shows no degeneration after large‐angle bending or 100 times bending tests. This result may pave a feasible way for the realization of wearable neuromorphic computing systems in the future.

The Tarim River Basin, the largest area of Chinese cotton production, is receiving increased attention because of serious environmental problems. At two experimental stations (Korla and Aksu), we studied the influence of salinity on cotton yield. Soil chemical and physical properties, soil water content, soil total suction and matric suction, cotton yield and water use efficiency under plastic mulched drip irrigation in different saline soils was measured during cotton growth season. The salinity (mS·cm−1) were 17–25 (low) at Aksu and Korla, 29–50 (middle) at Aksu and 52–62 (high) at Aksu for ECe (Electrical conductivity measured in saturation-paste extract of soil) over the 100 cm soil profile. The soil water characteristic curves in different saline soils showed that the soil water content (15%–23%) at top 40 cm soil, lower total suction power (below 3500 kPa) and lower matric suction (below 30 kPa) in low saline soil at Korla had the highest water use efficiency (10 kg·ha−1·mm−1) and highest irrigation water use efficiency (12 kg·ha−1·mm−1) and highest yield (6.64 t·ha−1). Higher water content below 30 cm in high saline soil increased the salinity risk and led to lower yield (2.39 t·ha−1). Compared to low saline soils at Aksu, the low saline soil at Korla saved 110 mm irrigation and 103 mm total water to reach 1 t·ha−1 yield and increased water use efficiency by 5 kg·ha−1·mm−1 and 7 kg·ha−1·mm−1 for water use efficiency (WUE) and irrigation water use efficiency (IWUE) respectively.

The Xinjiang Region in Northwest China is known as the “dust center” of the Eurasian mainland. Dust on the leaf surface affects overall plant development. While emphasis was on studying the impacts of industrial dust particles on crop development, the effect of natural dust deposition on the physiological parameters of cotton had not been studied before. The objective of this study was to examine the effects of dust deposits on cotton leaves and to estimate their impact on crop development and yield. For this purpose, an experiment was set up having two treatments and a control. In Treatment 1, cotton leaves were cleaned with water at three-day intervals or after a natural dust fall. In Treatment 2, 100 g·m−2 of dust was applied at 10-day intervals. The control received neither additional dust nor cleaning. In all of the treatments, stomatal conductance, leaf temperature, biomass and yield were measured. The results show a 28% reduction in yield and 30% reduction in stomatal conductance of the dust treatment compared to the control treatment. This indicates blocking of the stomata on the top of the leaf surface. In addition, the canopy temperature of the dust-applied leaves was always higher than the control and treatment.

BackgroundT cells are found in atherosclerotic plaques, with evidence supporting a potential role for CD8+ T cells in atherogenesis. Prior studies provide evidence of low‐density lipoprotein and apoB‐100 reactive T cells, yet specific epitopes relevant to the disease remain to be defined. The current study was undertaken to identify and characterize endogenous, antigen‐specific CD8+ T cells in atherosclerosis. Methods and ResultsA peptide fragment of apoB‐100 that tested positive for binding to the mouse MHC‐I allele H2Kb was used to generate a fluorescent‐labeled H2Kb pentamer and tested in apoE−/− mice. H2Kb pentamer(+)CD8+ T cells were higher in apoE−/− mice fed an atherogenic diet compared with those fed a normal chow. H2Kb pentamer (+)CD8+ T cells in atherogenic diet–fed mice had significantly increased effector memory phenotype with a shift in Vβ profile. H2Kb pentamer blocked lytic activity of CD8+ T cells from atherogenic diet–fed mice. Immunization of age‐matched apoE−/− mice with the apoB‐100 peptide altered the immune‐dominant epitope of CD8+ T cells and reduced atherosclerosis. ConclusionsOur study provides evidence of a self‐reactive, antigen‐specific CD8+ T‐cell population in apoE−/− mice. Immune modulation using the peptide antigen reduced atherosclerosis in apoE−/− mice.

Auto-immunity is believed to contribute to inflammation in atherosclerosis. The antimicrobial peptide LL-37, a fragment of the cathelicidin protein precursor hCAP18, was previously identified as an autoantigen in psoriasis. Given the reported link between psoriasis and coronary artery disease, the biological relevance of the autoantigen to atherosclerosis was tested in vitro using a truncated (t) form of the mouse homolog of hCAP18, CRAMP, on splenocytes from athero-prone ApoE(-/-) mice. Stimulation with tCRAMP resulted in increased CD8+ T cells with Central Memory and Effector Memory phenotypes in ApoE(-/-) mice, differentially activated by feeding with normal chow or high fat diet. Immunization of ApoE(-/-) with different doses of the shortened peptide (Cramp) resulted in differential outcomes with a lower dose reducing atherosclerosis whereas a higher dose exacerbating the disease with increased neutrophil infiltration of the atherosclerotic plaques. Low dose Cramp immunization also resulted in increased splenic CD8+ T cell degranulation and reduced CD11b+CD11c+ conventional dendritic cells (cDCs), whereas high dose increased CD11b+CD11c+ cDCs. Our results identified CRAMP, the mouse homolog of hCAP-18, as a potential self-antigen involved in the immune response to atherosclerosis in the ApoE(-/-) mouse model.

Range-free localization algorithms have caused widespread attention due to their low cost and low power consumption. However, such schemes heavily depend on the assumption that the hop count distance between two nodes correlates well with their Euclidean distance, which will be satisfied only in isotropic networks. When the network is anisotropic, holes or obstacles will lead to the estimated distance between nodes deviating from their Euclidean distance, causing a serious decline in localization accuracy. This paper develops HCD-DV-Hop for node localization in anisotropic sensor networks. HCD-DV-Hop consists of two steps. Firstly, an anisotropic network is decomposed into several different isotropic subnetworks, by using the proposed Hop Count Based Decomposition (HCD) scheme. Secondly, DV-Hop algorithm is carried out in each subnetwork for node localization. HCD first uses concave/convex node recognition algorithm and cleansing criterion to obtain the optimal concave and convex nodes based on boundary recognition, followed by segmentation of the network's boundary. Finally, the neighboring boundary nodes of the optimal concave nodes flood the network with decomposition messages; thus, an anisotropic network is decomposed. Extensive simulations demonstrated that, compared with range-free DV-Hop algorithm, HCD-DV-Hop can effectively reduce localization error in anisotropic networks without increasing the complexity of the algorithm.