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This study aimed to pursue more sustainable agriculture in a new rapeseed–maize rotation system. We assessed the effects of organic fertilizer and straw on soil quality and crop yield through a 15-year field experiment: mainly applied organic fertilizer (MM); mainly applied inorganic fertilizer with straw (MCS); mainly applied inorganic fertilizer (MC); applied only inorganic fertilizer with straw (CS); and applied only inorganic fertilizer (C) as a control. Compared to the C treatment, crop yields, soil organic carbon (SOC), available nitrogen (AN), phosphorus (AP), potassium (AK), soil porosity (SP), field capacity (FC), and 0.250–2.000 mm large aggregates in soil water-stable aggregates (WA0.250-2.000) were significantly ( P <0.05) increased by organic fertilization treatments (MCS, MC, and MM); and soil bulk density (SBD) and WA<0.053 were significantly decreased. Similarly, straw addition (CS and MCS) treatments also had significant effects on soil nutrients, structure, and yield, compared to the C and MC treatments, respectively. However, compared to the MC treatment, applying more organic fertilizers (MM) had no significant effect. The highest nutrient comprehensive evaluation value (NCEV), SP, FC, MA>2.000, WA0.053–0.250, and crop yields were observed in the MCS treatment. Compared to C treatment, rapeseed and maize yield significantly increased by 36.0% and 11.8% in response to MCS treatment, respectively. Pearson correlations showed that total nitrogen (TN), total potassium (TK), AK, SBD, and WA<0.053 were the strongest correlates of crop yields, followed by SOC, FC, WA>2, and WA0.250–2.000. This suggests that MCS was the best fertilization method to increase crop yields by improving SOC, AK, FC, and WA>0.250, and reducing SBD and WA<0.053.

Natural stilbenes have shown significant potential in the prevention and treatment of diseases due to their diverse pharmacological activities. Here we present a mild and effective Ti-catalyzed intermolecular radical-relay [2σ + 2π] cycloaddition of bicyclo[1.1.0]-butanes and 1,3-dienes. This transformation enables the synthesis of bicyclo[2.1.1]hexane (BCH) scaffolds containing aryl vinyl groups with excellent regio- and trans -selectivity and broad functional group tolerance, thus offering rapid access to structurally diverse stilbene bioisosteres. Natural stilbenes show significant potential in the prevention and treatment of diseases due to their diverse pharmacological activities. Here the authors present a mild and effective Ti-catalyzed intermolecular radical-relay cycloaddition reaction with good regio- and trans-selectivity offering rapid access to structurally diverse stilbene bioisosteres.

The isolation and identification of an increasing number of secondary metabolites featuring unique skeletons and possessing diverse bioactivities sourced from marine microorganisms have garnered the interest of numerous natural product chemists. There has been a growing emphasis on how to cultivate microorganisms to enhance the chemical diversity of metabolites and avoid the rediscovery of known ones. Given the significance of secondary metabolites as a means of communication among microorganisms, microbial co-culture has been introduced. By mimicking the growth patterns of microbial communities in their natural habitats, the co-culture strategy is anticipated to stimulate biosynthetic gene clusters that remain dormant under traditional laboratory culture conditions, thereby inducing the production of novel secondary metabolites. Different from previous reviews mainly focusing on fermentation conditions or metabolite diversities from marine-derived co-paired strains, this review covers the marine-derived co-culture microorganisms from 2012 to 2022, and turns to a particular discussion highlighting the selection of co-paired strains for marine-derived microorganisms, especially the fermentation methods for their co-cultural apparatus, and the screening approaches for the convenient and rapid detection of novel metabolites, as these are important in the co-culture. Finally, the structural and bioactivity diversities of molecules are also discussed. The challenges and prospects of co-culture are discussed on behave of the views of the authors.

Smart beds have become increasingly accepted, and are concurrently reshaping their lifestyles. Addressing the limited ability of smart beds to cater to health requirements, this study investigated smart bed comfort across diverse typical conditions. Objective body pressure distribution and participant-reported perceived comfort were recorded during typical smart bed usage. Statistical analysis was utilized to investigate overall and local comfort variations across different conditions and the correlation between perceived comfort and body pressure distribution. Statistical analysis highlighted the importance of equalizing forces and minimizing peak pressures. Alongside mean pressure, peak pressure—particularly in the buttock, thigh, and shank areas—played a pivotal role in comfort evaluation. Optimal bed board partitioning and interlinked mechanisms between adjacent boards enhance body curve fit and overall comfort. Balancing body forces and preventing feelings of weightlessness significantly improve user comfort and health. This analysis has been used to develop a comfort prediction model for smart bed design.

Dispensing and manipulation of small droplets is important in bioassays, chemical analysis and patterning of functional inks. So far, dispensing of small droplets has been achieved by squeezing the liquid out of a small orifice similar in size to the droplets. Here we report that instead of squeezing the liquid out, small droplets can also be dispensed advantageously from large orifices by draining the liquid out of a drop suspended from a nozzle. The droplet volume is adjustable from attolitre to microlitre. More importantly, the method can handle suspensions and liquids with viscosities as high as thousands mPa s markedly increasing the range of applicable liquids for controlled dispensing. Furthermore, the movement of the dispensed droplets is controllable by the direction and the strength of an electric field potentially allowing the use of the droplet for extracting analytes from small sample volume or placing a droplet onto a pre-patterned surface. Dispensing small droplets is essential to many ink printing, chemical and biological technologies, but the conventional orifice-based methods fail when the size of droplets approaches sub-micrometre range. Here, Zhang et al. show dispensing of viscous droplets down to attolitre in a controllable way.

Background Tillage measures have been effectively adopted for mitigating waterlogging damage in field crops, yet little is known about the role of tillage measures in crop responses to waterlogging. A field experiment was performed to investigate the effect of conventional planting (CK), small ridge planting (SR), big ridge planting (BR) and film side planting (FS) on soil available nutrients and enzymatic activity, chlorophyll contents, leaf nutrients, soluble protein, soluble sugar, nitrate reductase, antioxidant enzyme activity, lipid peroxidation, agronomic traits and yield of rapeseed under waterlogging stress conditions. Results Tillage measures remarkably improved rapeseed growth and yield parameters under waterlogging stress conditions. Under waterlogging conditions, rapeseed yield was significantly increased by 33.09 and 22.70% in the SR and BR groups, respectively, compared with CK. Correlation analysis showed that NO 3 − -N, NH 4 + -N, and urease in soils and malonaldehyde (MDA), superoxide dismutase (SOD), and nitrate reductase in roots were the key factors affecting rapeseed yield. The SR and BR groups had significantly increased NO 3 − -N by 180.30 and 139.77%, NH 4 + -N by 115.78 and 66.59%, urease by 41.27 and 26.45%, SOD by 6.64 and 4.66%, nitrate reductase by 71.67 and 26.67%, and significantly decreased MDA content by 14.81 and 13.35% under waterlogging stress, respectively, compared with CK. In addition, chlorophyll and N content in leaves, soluble sugar and POD in roots, and most agronomic traits were also significantly enhanced in response to SR and BR under waterlogging conditions. Conclusion Overall, SR and BR mitigated the waterlogging damage in rapeseed mainly by reducing the loss of soil available nitrogen, decreasing the MDA content in roots, and promoting urease in soils and SOD and nitrate reductase in roots. Finally, thorough assessment of rapeseed parameters indicated that SR treatment was most effective followed by BR treatment, to alleviate the adverse effects of waterlogging stress.

Due to simultaneous horizontal and vertical displacement during vertical evacuation, the consequences of stampede congestion accidents can be more severe. Generally, pedestrians trigger a synchronization mechanism at some point during the vertical evacuation process. This synchronization behavior helps prevent stampede congestion and improves evacuation efficiency. This paper designs a well-controlled single-file vertical evacuation experiment. After the experiment, the video footage is imported into the TRACKER system to extract the coordinates of pedestrian step movements, after which the experimental data undergo calculations and visual analysis. The research findings indicate the following: Firstly, when the crowd coordinates trigger the synchronization mechanism, this behavior remains stable as long as pedestrian speed and direction are unchanged; Secondly, the variation in footstep speed over time is not directly related to the footstep synchronization rate of the crowd; Lastly, this study calculated the characteristic density value most likely to trigger the synchronization mechanism during vertical evacuation. This research deepens our understanding of crowd dynamics, reveals the characteristics of pedestrian movement during vertical evacuation, and proposes evacuation guidance strategies based on these features.

This study provides an accurate method for evaluating the fit of earphones, which could be used for establishing a linkage between interference/gap values with human perception. Seven commercial CAD software tools stood out and were explored for the analysis of the deviation between earphone and ear. However, the current deviation analysis method remains to be improved for earphone fit evaluation due to excessive points in the calculation (Geomagic Wrap and Siemens NX), lack of value on interference (Geomagic Control X), computation boundary required (Rapidform XOR/Redesign), repetitive computation with same points and inclined calculation line segment or even invalid calculation (Solidworks, Creo). Therefore, an accurate deviation analysis algorithm was promoted, which calculated the deviation between earphone and ear exactly and classified the interference set and gap set precisely. There are five main procedures of this algorithm, which are point cloud model pre-processing, the generation of distance vectors, the discrimination of interference set and gap set, the discrimination of validity, and statistical analysis and visualization. Furthermore, the usability and validity of the deviation analysis algorithm were verified through statistical analysis and comparing visual effects based on the earphone-wearing experiment. It is certified that the deviation analysis algorithm is appropriate for earphone fit evaluation and the eight indexes of this algorithm were proved to be related to subjective comfort scores. It is meaningful for ear-worn product fit analysis, design, and development phases.

•Even without IEDs, there is a generalized acceleration of brain activity in TLE patients.•Brain network in TLE patients were highly synchronized yet highly unstable, which might be related to epileptogensis.•Highly independent, highly stable, and highly synchronized activity in bilateral frontal regions and left temporal region, might be related to drug resistance in TLE.•Machine learning approach using spatiotemporal metrics can accurately distinguish TLE patients from HC and DRE patients from DSE. Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.