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CO2 adsorption causes damage degradation to the coal body and thus reduces its stability, challenging the long-term safety of CO2 sequestration, and it is important to clarify the role of CO2 degradation and establish an ontological model. The damage mechanics theory and statistical theory were used to derive the calculation formula that can comprehensively reflect the total damage variables of the coal body under CO2 adsorption and load coupling, and focusing on the influence of the pressure-tight section, the fine statistical damage ontological equation of the coal body under the action of CO2 was established by segmentation, and the method of determining each parameter of the model was clarified. Finally, the parameters of the constitutive model were determined by CT scanning experiment system and MTS 816 experiment system, and the uniaxial compression experiments of coal body under different CO2 pressures were carried out by the self-developed gas-solid coupling experiment system to verify the rationality of the model. The results show that: ① The damage variables under adsorption and loading were defined based on the fracture rate obtained from CT scanning and by applying the Weibull distribution theory, respectively, and the total damage variable under the coupling of the two was further obtained by combining the damage theory, and a fine-scale statistical damage constitutive model was established; ② Three-dimensional reconstruction of the fracture based on CT scanning technology realistically reflects the fracture extension characteristics before and after CO2 interaction， the higher the CO2 pressure, the fuller the fracture expansion, the greater the three-dimensional fracture parameters and damage variables of the coal samples, and the more complex the spatial fracture network formed; ③ CO2 had a significant deterioration effect on the physical properties of the coal body, and the compressive strength and modulus of elasticity of the coal body were both reduced by 49.78% and 22.63%, respectively, with the increase of CO2 pressure, and the combined effect of dissolution, plasticization and air wedge effect of CO2 on the coal body led to the reduction of the mechanical parameters; ④ The theoretical curves of the fine statistical damage model of the coal body under the action of CO2 have a high degree of agreement with the uniaxial experimental curves, which indicates that the present structural model can better reflect the damage degradation effect of CO2 on the physical properties of the coal body, and embodies the reasonableness and applicability of the constitutive model and the method for determining the model parameters.

Summary: Calcitonin gene-related peptide (CGRP), a neuropeptide involved in nociceptor neuronal function, plays a critical role in mediating neuroinflammation and pain. In this study, we find that bladder group 2 innate lymphoid cells (ILC2s) function as primary producers of CGRP in the early phase of bacterial cystitis, contributing to increased inflammation, altered voiding behavior, and heightened pelvic allodynia. Furthermore, we demonstrate that interleukin (IL)-33, a cytokine secreted by urothelial cells, upregulates CGRP production by ILC2s in the bladder during uropathogenic Escherichia coli (UPEC) infection. Moreover, our research reveals that monocytes expressing high levels of receptor activity-modifying protein 1 (RAMP1), a CGRP receptor, mediate the pro-inflammatory effects of CGRP-producing ILC2s. In summary, our results underscore the significance of the immune cell-derived neuropeptides in the pathology of UPEC infection, suggesting a promising therapeutic approach targeting the IL-33-ILC2-CGRP axis for managing lower urinary tract symptoms in bacterial cystitis.

The evolution of fractures is affected by internal and external environments such as the distribution characteristics of mineral particles and confining pressure conditions. In order to explore the macro-meso evolution characteristics and influencing factors of fractures in fractured coal under different confining pressures, based on the industrial CT scanning system and its equipped triaxial loading system, the triaxial static load test of fractured coal was carried out. The interaction mechanism of internal and external conditions of primary fractures, mineral particles and confining pressure is reasonably explained by multi-angle joint characterization. the results showed：① The confining pressure will shift the significant area of the initial damage of the coal body, so that it transits from the fracture tip to the upper and lower ends of the coal body with the increase of confining pressure, and it is easier to connect between micropores and large-sized fractures than between micropores and micropores, and new macroscopic cracks are generated. ② The increase of confining pressure will lead to the change of three-dimensional dynamic fractal dimension from slow increase, rapid increase and steady increase to the development stage of steady increase, rapid increase and slow increase, which can be used to characterize the time evolution law of fractures. ③ The fractured coal body exhibits longitudinal tensile failure under uniaxial or low confining pressure. The high confining pressure will change its failure mode and tend to shear failure, and enhance the strength of the coal body through two ways. ④ The deviation between the theoretical value and the experimental value of the cracking angle increases with the increase of confining pressure, which is consistent with the discrete numerical relationship caused by the distribution of mineral particles in coal. ⑤ According to the stress composition of the fracture and the distribution characteristics of mineral particles, the fracture propagation behavior is divided into three types: direct drive, bypassing mineral particles and staggering mineral particles. The above propagation behavior depends on the confining pressure to change the force component of the crack. The cracks under the action of relative pure tensile stress, tensile-shear composite stress and relative pure shear stress correspond to the above three propagation behaviors, that is, the influence form of crack propagation is mainly confining pressure, supplemented by the occurrence form of mineral particles.

In order to study the ultrasonic propagation law and damage characteristics of the soft coal body, coal briquette is selected to replace raw coal, three wave propagation paths were set, and MTS rock mechanics experiment machine and PCI-II acoustic emission instrument were used to carry out the multi-path wave synchronization monitoring test of the coal body under the condition of uniaxial compression, and the anisotropy index was introduced to analyze the wave velocity evolution law. Three transverse and longitudinal sections were selected, and CT scanning equipment was used to carry out damage characterization experiments, reconstruct the micro-structure of the coal body after failure, and compare and study the differences in the distribution of the transverse and longitudinal fissures of two-dimensional slices, and to explore the relationship between the wave velocity and the three-dimensional volume of the fissures. Results show that: ① The parallel and vertical loading directions and the average wave velocity of the coal body show the basic law of smoothness followed by decrease and then smoothness with the increase of axial strain.The wave velocity anisotropy index has a smooth, then increasing and then smooth trend with the increase of axial strain, and the wave velocity in the vertical loading direction is the first to decrease, and the decrement is the largest. ② Compared with the vertical plane, the fracture spectral peak ratio and fractal dimension of the transverse plane of the damaged coal body are larger, the fracture density is higher, and the fracture morphology is also more complicated. ③ With the increase of fissure volume, the average wave velocity of the damaged coal body decreases roughly linearly, and the expansion of internal fissures in the coal body under uniaxial loading is dominated by the parallel loading direction, and the vertical linear expansion of the fissures is the main cause of the variability of the wave velocity in all directions and the damage characteristics of the transverse and longitudinal sections. ④ Compared with the parallel loading direction, the damage variables obtained by using the wave velocity in the vertical loading direction are larger and the evaluation of the damage state of the coal body is more reliable. When sound waves are used in the field to evaluate the damage state of coal , it is beneficial to improve the reasonableness of the prediction of instability accidents by making the sound wave propagation path perpendicular to the direction of the coal body loaded (maximum principal stress).

Nowadays, numerous countries are facing the challenge of aging population. Additionally, the number of people with reduced mobility due to physical illness is increasing. In response to this issue, robots used for walking assistance and sit-to-stand (STS) transition have been introduced in nursing to assist these individuals with walking. Given the shared characteristics of these robots, this paper collectively refers to them as Walking Support Robots (WSR). Additionally, service robots with assisting functions have been included in the scope of this review. WSR are a crucial element of modern nursing assistants and have received significant research attention. Unlike passive walkers that require much user’s strength to move, WSR can autonomously perceive the state of the user and environment, and select appropriate control strategies to assist the user in maintaining balance and movement. This paper offers a comprehensive review of recent literature on WSR, encompassing an analysis of structure design, perception methods, control strategies and safety & comfort features. In conclusion, it summarizes the key findings, current challenges and discusses potential future research directions in this field.

Abstract Learning visual predictive models has great potential for real-world robot manipulations. Visual predictive models serve as a model of real-world dynamics to comprehend the interactions between the robot and objects. However, prior works in the literature have focused mainly on low-level elementary robot actions, which typically result in lengthy, inefficient, and highly complex robot manipulation. In contrast, humans usually employ top–down thinking of high-level actions rather than bottom–up stacking of low-level ones. To address this limitation, we present a novel formulation for robot manipulation that can be accomplished by pick-and-place, a commonly applied high-level robot action, through grasping. We propose a novel visual predictive model that combines an action decomposer and a video prediction network to learn the intrinsic semantic information of high-level actions. Experiments show that our model can accurately predict the object dynamics (i.e., the object movements under robot manipulation) while trained directly on observations of high-level pick-and-place actions. We also demonstrate that, together with a sampling-based planner, our model achieves a higher success rate using high-level actions on a variety of real robot manipulation tasks.

IntroductionOne of the most common mental disorders in the perinatal period is depression, which is associated with impaired emotional functioning due to alterations in different cognitive aspects including thought and facial emotion recognition. These functional impairment may affect emerging maternal sensitivity and have lasting consequences for the dyadic relationship. The current study aimed to investigate the impact of depressive symptoms on the attention bias of infant stimuli during pregnancy.MethodsEighty-six pregnant women completed the Edinburgh Postnatal Depression Scale and an eye-tracking task comprising infant-related emotion images. All participants showed biased attention to infant-related images.ResultsFirst, compared to healthy pregnant women, pregnant women with depression symptoms initially directed their attention to infant-related stimuli more quickly (F (1, 84) = 6.175, p = 0.015, η2 = 0.068). Second, the two groups of pregnant women paid attention to the positive infant stimuli faster than the neutral infant stimuli, and the first fixation latency bias score was significantly smaller than that of the infant-related negative stimulus (p = 0.007). Third, compared with the neutral stimulus, the non-depression group showed a longer first gaze duration to the negative stimulus of infants (p = 0.019), while the depressive symptoms group did not show this difference.ConclusionWe speculate that structural and functional changes in affective motivation and cognitive-attention brain areas may induce these attentional bias patterns. These results provide suggestions for the implementation of clinical intervention programs to correct the attention bias of antenatal depressed women.

AbstractObjective This study aims to investigate the association between miR-203 expression and the prognostic value in patients with esophageal cancer by the method of systematic review and meta-analysis.Methods We searched PubMed, Web of Science, Embase, and Cochrane Library to collect studies on the relationship between miR-203 expression and the prognostic value of esophageal cancer up to July 2023. Stata 15.0 statistical software was used for data analysis. Hazard ratio (HR) and 95% confidence interval (CI) were used as effect sizes.Results A total of 6 studies were included in this review, including 476 patients with esophageal cancer. The results showed that miR-203 low expression was associated with worse overall survival (OS) in patients with esophageal cancer compared with miR-203 high expression (HR = 2.80, 95%CI: 1.99 ∼ 3.93, p

Abstract Purpose Esophageal squamous cell carcinoma (ESCC) remains one of the most common causes of cancer death due to the lack of effective therapeutic options. New targets and the targeted drugs are required to be identified and developed. Methods Highly expressed genes in ESCA were identified using the edgeR package from public datasets. Immunostaining assay verified the high expression level of EFNA1 in ESCC. CCK-8, colony formation and wound healing assays were performed to examine the role of EFNA1 and EPHA2 in ESCC progression. Cell cycle was analyzed by flow cytometry and autophagy activation was determined by autophagolysosome formation using transmission electron microscopy. The small molecule targeting to EFNA1 was identified by molecular docking and the anti-tumor effects were verified by in vitro and in vivo models with radiation treatment. Results EFNA1 was highly expressed in esophageal cancer and significantly associated with poor prognosis. Downregulation of EFNA1 remarkably inhibited cell proliferation and migration. Furthermore, decreased EFNA1 significantly suppressed the expression of cMYC along with its representative downstream genes involved in cell cycle, and activated autophagy. Similar effects on ESCC progression were obtained from knockdown of the corresponding receptor, EPHA2. The potential small molecule targeting to EFNA1, salvianolic acid A (SAA), could significantly suppress ESCC progression and increase the sensitivity to radiotherapy. Conclusion We revealed that EFNA1 facilitated the ESCC progression via the possible mechanism of activating cMYC-modulated cell proliferation and suppressing autophagy, and identified SAA as a potential drug targeting EFNA1, providing new options for the future treatments for ESCC patients.

Abstract Goal-conditioned rearrangement of deformable objects (e.g. straightening a rope and folding a cloth) is one of the most common deformable manipulation tasks, where the robot needs to rearrange a deformable object into a prescribed goal configuration with only visual observations. These tasks are typically confronted with two main challenges: the high dimensionality of deformable configuration space and the underlying complexity, nonlinearity and uncertainty inherent in deformable dynamics. To address these challenges, we propose a novel representation strategy that can efficiently model the deformable object states with a set of keypoints and their interactions. We further propose local-graph neural network (GNN), a light local GNN learning to jointly model the deformable rearrangement dynamics and infer the optimal manipulation actions (e.g. pick and place) by constructing and updating two dynamic graphs. Both simulated and real experiments have been conducted to demonstrate that the proposed dynamic graph representation shows superior expressiveness in modeling deformable rearrangement dynamics. Our method reaches much higher success rates on a variety of deformable rearrangement tasks (96.3% on average) than state-of-the-art method in simulation experiments. Besides, our method is much more lighter and has a 60% shorter inference time than state-of-the-art methods. We also demonstrate that our method performs well in the multi-task learning scenario and can be transferred to real-world applications with an average success rate of 95% by solely fine tuning a keypoint detector. A supplementary video can be found at https://youtu.be/AhwTQo6fCM0 .

Precise diagnosis of early prostate cancer (PCa) is critical for preventing tumor progression. However, the diagnostic outcomes of currently used markers are far from satisfactory due to the low sensitivity or specificity. Here, we identified a diagnostic subpopulation in PCa tissue with the integrating analysis of single-cell and bulk RNA-seq. The representative markers of this subpopulation were extracted to perform intersection analysis with early-PCa-related gene module generated from weighted correlation network analysis (WGCNA). A total of 24 overlapping genes were obtained, the diagnostic roles of which were validated by distinguishing normal and tumorous prostate samples from the public dataset. A least absolute shrinkage and selection operator (LASSO) model was constructed based on these genes and the obtained 24-gene panel showed high sensitivity and specificity for PCa diagnosis, with better identifying capability of PCa than the commercially used gene panel of Oncotype DX. The top two risk factors, TRPM4 and PODXL2, were verified to be highly expressed in early PCa tissues by multiplex immunostaining, and PODXL2 was more sensitive and specific compared to TRPM4 and the pathologically used marker AMACR for early PCa diagnosis, suggesting a novel and promising pathology marker.

Abstract Tainan, a city that prospered early in Taiwan, has a hot and humid atmosphere. Hence, the grilled doors in numerous old buildings for ventilation and lighting to conserve energy. This study analyzed a fire incident that occurred during the late night of March 17, 2019 in a 38-year-old dwelling, where three residents were severely covered with soot. The site investigation showed that eight staircases lead to the same basement, which apparently created a stack effect and a makeup air phenomenon. Numerical simulations have been performed in this study to reconstruct the fire scene, whose results were consistent with the actual fire scene. In particular, the results showed that some staircases in the fire were blackened by smoke, while others acted as makeup air inlets. The temperature at the households’ doors on all floors of Staircase 2, which was closest to the fire, exceeded 60 °C after four minutes. Furthermore, two immediately feasible improvement strategies according to the control volume theory of fluid mechanics were proposed in this study. Firstly, changing the grilled doors in the basement to a closed flat door style could effectively prevent smoke from flowing up in the staircases. Secondly, residents may consider closing the windows of the stairs at night to improve fire safety. The results showed that the chimney effect can be significantly reduced. These improvements could be a reference for other old dwellings to enhance their fire safety.

Sustainable development is the global overarching paradigm and essential for achieving economic, social, and environmental development. The primary goal of this study is to compare the efficiency of sustainable development and evaluate its influencing factors across the BRICS (Brazil, Russia, India, China, and South Africa) and G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and United States) countries by examining total factor productivity, efficiency change, and technological change. For this, we adopted the super-efficiency SBM-DEA model with undesirable output and Global Malmquist-Luenberger (GML) productivity index model to overcome inaccurate efficiency results while avoiding environmentally unwanted outputs and to resolve the shortcomings of the conventional Malmquist-Luenberger index. It is also necessary to explore relevant influencing factors on the environmental pollution thereby affects the sustainable development efficiency of the study countries, thus, this study employed STIRPAT approach. A panel data of BRICS and G7 countries from 2005 to 2015 is used. The findings reveal that sustainable total factor productivity (GML) in China (1.0165), the US (1.0150), and UK (1.0024) is on the rise. China is also one of the countries that experienced the highest positive efficiency change (GMLEC) (1.0147) and the US has the highest positive technical change (GMLTC) (1.0103). Contrarily, Russia experienced the highest decline in GMLTC (0.9316) as well as GML indexes (0.9337), whereas South Africa experienced the highest decline in GMLEC (0.9707). Additionally, GDP per capita (.0969) and population (.4178) have a positive influence on CO2 emissions in the BRICS countries, whereas in the G7 nations, GDP per capita (−.2180) and population (−.1249) have negative influences on CO2 emissions. The study also offers practical recommendations to address identified limitations and improve sustainable productivity and environmental efficiency. The inverse link between GDP and CO2 emissions might imply that the G7 nations have passed the turning point on an environmental Kuznets curve (EKC), but this finding does not support the EKC hypothesis in the BRICS nations.

Abstract Background KDM6A, a histone demethylase, is frequently mutated in bladder cancer (BCa). However, the role and detailed molecular mechanism of KDM6A involved in bladder cancer progression remains unknown. Methods Tissue specimens were used to determine the expression levels and prognostic values of KDM6A and ARHGDIB. The MTT, colony formation, wound healing and Transwell migration and invasion assays were employed to detect the BCa cell proliferation, migration and invasion, respectively. Chemotaxis of macrophages was used to evaluate the ability of KDM6A to recruit macrophages. A subcutaneous tumour model and tail vein tumour injection in nude mice were used to assess the role of KDM6A in vivo. RNA sequencing, qPCR, Western blot, ChIP and phalloidin staining assay were performed to investigate the molecular functions of KDM6A. Dual-luciferase reporter assay was used to determine the effects of KDM6A and FOXA1 on the promoters of the ARHGDIB and KDM6A. Results We showed that the KDM6A inhibited the motility and invasiveness of the BCa cells. Mechanistically, KDM6A promotes the transcription of ARHGDIB by demethylating histone H3 lysine di/trimethylation (H3K27me2/3) and consequently leads to inhibition of Rac1. EZH2, which catalyses the methylation of H3K27, functions to silence ARHGDIB expression, and an EZH2 inhibitor can neutralize the metastatic effect caused by KDM6A deficiency. Furthermore, we demonstrated that FOXA1 directly binds to the KDM6A promoter and thus transactivates KDM6A, leading to diminished metastatic potential. Conclusion Our findings establish the critical role of the FOXA1-KDM6A-ARHGDIB axis in restraining the malignancy of BCa and identify KDM6A and EZH2 as potential therapeutic targets in the management of BCa.

Abstract Background The highly intra-tumoral heterogeneity and complex cell origination of prostate cancer greatly limits the utility of traditional bulk RNA sequencing in finding better biomarker for disease diagnosis and stratification. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel biomarkers. However, this technique has yet been used in the study of prostate cancer heterogeneity. Methods Cell types and the corresponding marker genes were identified by single-cell RNA sequencing. Malignant states of different clusters were evaluated by copy number variation analysis and differentially expressed genes of pseudo-bulks sequencing. Diagnosis and stratification of prostate cancer was estimated by receiver operating characteristic curves of marker genes. Expression characteristics of marker genes were verified by immunostaining. Results Fifteen cell groups including three luminal clusters with different expression profiles were identified in prostate cancer tissues. The luminal cluster with the highest copy number variation level and marker genes enriched in prostate cancer-related metabolic processes was considered the malignant cluster. This cluster contained a distinct subgroup with high expression level of prostate cancer biomarkers and a strong distinguishing ability of normal and cancerous prostates across different pathology grading. In addition, we identified another marker gene, Hepsin (HPN), with a 0.930 area under the curve score distinguishing normal tissue from prostate cancer lesion. This finding was further validated by immunostaining of HPN in prostate cancer tissue array. Conclusion Our findings provide a valuable resource for interpreting tumor heterogeneity in prostate cancer, and a novel candidate marker for prostate cancer management.

The occurrence of severe mine pressure in stope is of high risk, and the mining depth is the main control factor which affecting the occurrence of mine pressure in stope. In order to study the influence law of mining depth on stope strata behavior, taking 11318E fully mechanized working face in Xieqiao Coal Mine of Huainan Mining Group as the engineering background, the stress distribution and evolution characteristics of stope surrounding rock under mining depth were studied by similar material simulation. And the evolution laws of mechanical characteristics of stope surrounding rock under different mining depths of 600 m and 1200 m were simulated. It is concluded that with the increase of mining depth, the damage range of surrounding rock on the mining field increases significantly. The initial collapse of the immediate roof above the working face is not affected by the mining depth. The periodic weighting caving step decreases with the increase of mining depth, and the height of two zones above the working face increases with the increase of mining depth. The stress transfer and evolution characteristics of the strata above the stope were revealed. The increase of front caving angle indicates that the pressure on the support of the working face is greater, indicating that the support of the working face should be strengthened with the increase of mining depth. The research results have a guiding role in the control of surrounding rock and disaster prevention of deep mine stope.

Elderly care institutions in Taiwan are mostly equipped with ceiling fans to enhance their indoor ventilation. However, detectors are usually installed above ceiling fans. It is necessary to evaluate the influence of the airflow field on the functions of the detectors. The airflow fields generated by ceiling fans are complex due to the rotation of blades during operation. Using burning smokeless candles as the fire sources, the temperature distribution recorded by model experiments and the flow patterns recorded by Schlieren photography were analyzed. Effective fire detectors are important in institutions, as they can detect fires early. Unfortunately, the results of this study proved that the airflow fields significantly and negatively influence the functions of fire detectors. According to the results, the airflow generated by fans can destroy fire plume patterns and significantly reduce the temperature near the ceiling. The Schlieren images showed a significant entrained airflow. The rising heat was found to be taken by one side above the fans, causing the ceiling temperature distribution to change. The temperature was high on one side and low on the other side. Fire detectors are less likely to detect when the fire source is far from the ceiling fan.

Aim: The role of plasma heat shock protein 90 alpha (HSP90α) in colorectal cancer patients remains unclear. This study aimed to evaluate the relationship between HSP90α and the occurrence and development of colorectal cancer through diagnosis and prognosis value.Methods: 635 colorectal cancer patients and 295 healthy controls were recruited. The HSP90α was measured by using the ELISA kit in all objects and the immune cells and common biomarkers as CEA, AFP, CA125, CA153 and CA199 were measured in all colorectal cancer patients. The relationship between plasma HSP90α with clinical features, common tumor markers and immune cells were also conducted. The survival analysis endpoint was progression-free survival (PFS).Results: The levels of plasma HSP90α were significantly higher in colorectal cancer patients compared to healthy controls [51.4 (ng/ml) vs. 43.7 (ng/ml), p < 0.001]. In additional, the levels of plasma HSP90α were associated with gender and disease progress as stage, lymphatic and distant metastasis. Furthermore, plasma HSP90α was closed correlation with CEA, CA125, CA199 and percentage of B cells. However, the initial expression level of plasma HSP90α failed to show a prognostic value for progression-free survival in colorectal cancer.Conclusion: The plasma Hsp90α was remarkable higher in colorectal cancer and correlated with common tumor biomarkers and immune cells. Plasma Hsp90α levels were associated with disease progress but a poor diagnosis performance and also failed to show a prognostic value in colorectal cancer.

Wogonin, an active component derived from Scutellaria baicalensis, has shown anti-tumor activities in several malignancies. However, the roles of wogonin in RCC cells remain elusive. Here, we explored the effects of wogonin on RCC cells and the underlying mechanisms. We found that wogonin showed significant cytotoxic effects against RCC cell lines 786-O and OS-RC-2, with much lower cytotoxic effects on human normal embryonic kidney cell line HEK-293 cells. Wogonin treatment dramatically inhibited the proliferation, migration, and invasion of RCC cells. We further showed that by inhibiting CDK4-RB pathway, wogonin transcriptionally down-regulated CDC6, disturbed DNA replication, induced DNA damage and apoptosis in RCC cells. Moreover, we found that the levels of p-RB, CDK4, and Cyclin D1 were up-regulated in sunitinib resistant 786-O, OS-RC-2, and TK-10 cells, and inhibition of CDK4 by palbociclib or wogonin effectively reversed the sunitinib resistance, indicating that the hyperactivation of CDK4-RB pathway may at least partially contribute to the resistance of RCC to sunitinib. Together, our findings demonstrate that wogonin could induce apoptosis and reverse sunitinib resistance of RCC cells via inhibiting CDK4-RB pathway, thus suggesting a potential therapeutic implication in the future management of RCC patients.

S concentric threshing device can improve rice crop separation and transportation capabilities. As one of the main factors affecting the threshing performance of rice combine harvesters, the threshing gap can influence the grain unthreshed rate and the grain damage rate directly. However, the clearance between any threshing cylinder tooth and the concave grid is constant for the traditional threshing device, named the single threshing gap in this paper, resulting in a consistently high total loss rate (the sum of unthreshed and damaged grains). Therefore, multi-threshing gaps are proposed in this paper for the concentric threshing device to solve the above problem. To compare the threshing performance between the single threshing gap and the multi-threshing gaps, the movement process of rice mixture (grain, short straw, and long straw) was simulated using the discrete element method (DEM). The simulation results showed that the separation and transportation abilities of the multi-threshing gaps were not decreased, but the distribution of threshed output mixture was more even for the multi-threshing gaps. Furthermore, a field experiment was also carried out on a combine harvester to compare the total loss rate. The experiment results showed that the total loss rate of the concentric threshing device with multi-threshing gaps was reduced by 0.0593%, which was 5.77% less than the total loss rate of the concentric threshing device with a single threshing gap.

It has long been a challenge to accurately and efficiently simulate exciton–phonon dynamics in mesoscale photosynthetic systems with a fully quantum mechanical treatment due to extensive computational resources required. In this work, we tackle this seemingly intractable problem by combining the Dirac–Frenkel time-dependent variational method with Davydov trial states and implementing the algorithm in graphic processing units. The phonons are treated on the same footing as the exciton. Tested with toy models, which are nanoarrays of the B850 pigments from the light harvesting 2 complexes of purple bacteria, the methodology is adopted to describe exciton diffusion in huge systems containing more than 1600 molecules. The superradiance enhancement factor extracted from the simulations indicates an exciton delocalization over two to three pigments, in agreement with measurements of fluorescence quantum yield and lifetime in B850 systems. With fractal analysis of the exciton dynamics, it is found that exciton transfer in B850 nanoarrays exhibits a superdiffusion component for about 500 fs. Treating the B850 ring as an aggregate and modeling the inter-ring exciton transfer as incoherent hopping, we also apply the method of classical master equations to estimate exciton diffusion properties in one-dimensional (1D) and two-dimensional (2D) B850 nanoarrays using derived analytical expressions of time-dependent excitation probabilities. For both coherent and incoherent propagation, faster energy transfer is uncovered in 2D nanoarrays than 1D chains, owing to availability of more numerous propagating channels in the 2D arrangement.

Photosynthesis is one of the most essential biological processes in which specialized pigment-protein complexes absorb solar photons, and with a remarkably high efficiency, guide the photo-induced excitation energy toward the reaction center to subsequently trigger its conversion to chemical energy. In this work, we review the principles of optimal energy transfer in various natural and artificial light harvesting systems. We begin by presenting the guiding principles for optimizing the energy transfer efficiency in systems connected to dissipative environments, with particular attention paid to the potential role of quantum coherence in light harvesting systems. We will comment briefly on photo-protective mechanisms in natural systems that ensure optimal functionality under varying ambient conditions. For completeness, we will also present an overview of the charge separation and electron transfer pathways in reaction centers. Finally, recent theoretical and experimental progress on excitation energy transfer, charge separation, and charge transport in artificial light harvesting systems is delineated, with organic solar cells taken as prime examples.

This paper proposes a new method to detect and identify foreign matter mixed in a plastic bottle filled with transfusion solution. A spin-stop mechanism and mixed illumination style are applied to obtain high contrast images between moving foreign matter and a static transfusion background. The Gaussian mixture model is used to model the complex background of the transfusion image and to extract moving objects. A set of features of moving objects are extracted and selected by the ReliefF algorithm, and optimal feature vectors are fed into the back propagation (BP) neural network to distinguish between foreign matter and bubbles. The mind evolutionary algorithm (MEA) is applied to optimize the connection weights and thresholds of the BP neural network to obtain a higher classification accuracy and faster convergence rate. Experimental results show that the proposed method can effectively detect visible foreign matter in 250-mL transfusion bottles. The misdetection rate and false alarm rate are low, and the detection accuracy and detection speed are satisfactory.

We explore, by theoretical modeling and computer simulations, how nonadiabatic couplings of excited electronic states of a polyatomic chromophore manifest themselves in single-molecule signals on femtosecond timescales. The chromophore is modeled as a system with three electronic states (the ground state and two non-adiabatically coupled excited states) and a Condon-active vibrational mode which, in turn, is coupled to a harmonic oscillator heat bath. For this system, we simulate double-pump single-molecule signals with fluorescence detection for different system-field interaction strengths, from the weak-coupling regime to the strong-coupling regime. While the signals are determined by the coherence of the electronic density matrix in the weak-coupling regime, they are determined by the populations of the electronic density matrix in the strong-coupling regime. As a consequence, the signals in the strong coupling regime allow the monitoring of nonadiabatic electronic population dynamics and are robust with respect to temporal inhomogeneity of the optical gap, while signals in the weak-coupling regime are sensitive to fluctuations of the optical gap and do not contain information on the electronic population dynamics.