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Abstract In recent years, electrolytic plasma polishing technology has attracted wide attention due to its advantages of shape adaptability, high efficiency, better precision, environmental friendliness, and non-contact polishing. However, the lack of research on the evolution mechanism of the gas layer at the anode interface restricts the improvement of the material removal mechanism and the regulation of the polishing effect. Firstly, the thermodynamic conditions of gas layer formation were analyzed based on the Clapeyron-Clausius equation, and the key parameters affecting the gas layer were identified. Secondly, the laws of voltage and electrolyte temperature on the dynamic evolution of the gas layer and its polishing effect were revealed. Additionally, the influence of the gas layer on the voltage-current characteristics was also investigated by analyzing the experimental phenomena. The results indicate that the optimal polishing effect is achieved at a voltage level of 300 V resulting in a decrease in Ra from 0.451 μm to 0.076 μm. Similarly, superior polishing results are obtained when the electrolyte temperature is 80 °C, with a decrease in R a from 0.451 μm to 0.075 μm. This study provides theoretical guidance for the further development and application of electrolytic plasma polishing technology.

Abstract Sensor fusion is very important for collaborative intelligent systems. A regional feature fusion network called ReFuNet for detecting 3D Object is proposed. It is difficult to detect distant or small objects accurately for the sparsity of LiDAR point cloud. The LiDAR point cloud and camera image information to solve the problem of point cloud sparsity is used, which can integrate image‐rich semantic information to enhance point cloud features. Also, the authors’ ReFuNet method segments the possible areas of objects by the results of 2D image detection. A cross‐attention mechanism adaptively fuses image and point cloud features within the areas. Then, the authors’ ReFuNet uses fused features to predict the 3D bounding boxes of objects. Experiments on the KITTI 3D object detection dataset showed that the authors’ proposed fusion method effectively improved the performance of 3D object detection.

During minimal invasive surgery (MIS), the laparoscope only provides a single viewpoint to the surgeon, leaving a lack of 3D perception. Many works have been proposed to obtain depth and 3D reconstruction by designing a new optical structure or by depending on the camera pose and image sequences. Most of these works modify the structure of the conventional laparoscopes and cannot provide 3D reconstruction of different magnification views. In this study, we propose a laparoscopic system based on double liquid lenses, which provide doctors with variable magnification rates, near observation, and real-time monocular 3D reconstruction. Our system composes of an optical structure that can obtain auto magnification change and autofocus without any physically moving element, and a deep learning network based on the Depth from Defocus (DFD) method, trained to suit inconsistent camera intrinsic situations and estimate depth from images of different focal lengths. The optical structure is portable and can be mounted on conventional laparoscopes. The depth estimation network estimates depth in real-time from monocular images of different focal lengths and magnification rates. Experiments show that our system provides a 0.68-1.44x zoom rate and can estimate depth from different magnification rates at 6fps. Monocular 3D reconstruction reaches at least 6mm accuracy. The system also provides a clear view even under 1mm close working distance. Ex-vivo experiments and implementation on clinical images prove that our system provides doctors with a magnified clear view of the lesion, as well as quick monocular depth perception during laparoscopy, which help surgeons get better detection and size diagnosis of the abdomen during laparoscope surgeries.

Abstract Background To compare the efficacy and safety of postoperative extensive target volume irradiation with elevated radiation dose and concurrent chemotherapy with radiotherapy only for the postoperative treatment of esophageal squamous cell carcinoma. Methods This trial was a single-arm phase II trial. Patients who underwent a radical transthoracic resection with negative margins within 3 months and histologically confirmed esophageal squamous cell carcinoma (pT3-4N0M0 or pTxN + M0, AJCC 7th) were eligible for this study. Postoperative radiotherapy was performed at a total dose of 45 Gy in 25 fractions with clinical target volumes of the tumor bed, anastomosis, bilateral supraclavicular, mediastinal, left gastric and celiac trunk lymph node areas. Five cycles of weekly TC (paclitaxel 50 mg/m2, d1, carboplatin AUC = 2, d1) were given as concurrent chemotherapy. The primary endpoint was the 2-year local control rate, and the secondary endpoints were overall survival, disease free survival, local-regional recurrence free survival, distant metastasis free survival and adverse events. All endpoints were compared with those in ESO-Shanghai 8 study with postoperative radiotherapy alone (40 Gy/20Fx). Results A total of 70 patients were enrolled from 2016 to 2018. The 2-year local control rate was 87.9% (95% CI: 83.3–92.3) in this study, which achieved the hypothesized 2-year local control rate of at least 83%. Overall survival, disease free survival, local-regional recurrence free survival and distant metastasis free survival in this study were also longer than those in previous ESO-Shanghai 8 study while most toxicities were increased and two patients in this study died of radiation pneumonitis. Conclusions Postoperative extensive target volume irradiation with elevated radiation dose and concurrent chemotherapy was effective. Treatment related toxicity was increased due to higher treatment intensity. Trial registration clinicaltrials.gov: NCT02916511.

Solar energy has received increasing attention as renewable clean energy in recent years. Power grid operators and researchers widely value probabilistic solar irradiance forecasting because it can provide uncertainty measurement for future PV production. This paper proposes a probabilistic prediction model of solar irradiance based on XGBoost. Specifically, after data preprocessing, historical data is utilized for training a point prediction model based on XGBoost. Since XGBoost is obtained by minimizing the residuals of successive iterations of multiple trees, when predicting solar irradiance at a certain time in the future, these trees can generate multiple predicted values of irradiance iteratively. Finally, the kernel density estimation method is applied to transform the above prediction results in probability prediction intervals under different confidence levels. Experimental results on public data sets show that this method has better accuracy than other benchmark algorithms. The experiment also shows that the method proposed in this paper requires less training time and simple parameter adjustment, which is very suitable for application in engineering practice.

With the increasing penetration rate of electric vehicles, the spatiotemporal coupling relationship between the power distribution network and traffic network is stronger than ever before. Under the dynamic wireless charging mode, traffic jam charging is introduced and the dynamic loading process of traffic flow is described using a cellular transmission model. The charging load is related to traffic flow and serves as a bond between the power distribution network and traffic network. The traffic flow achieves balanced allocation under dynamic user equilibrium conditions, and cooperatively optimizes the power flow of the power distribution network in conjunction with charging loads. Numerical analysis shows that this model can accurately depict the congestion situation during peak travel periods, and alleviate traffic congestion and distribution network voltage out of range.

Central air conditioning in large buildings is an important demand-response resource due to its large load power and strong controllability. Demand-response-oriented air conditioning load modeling needs to calculate the room temperature. The room temperature calculation models commonly used in the existing research cannot easily and accurately calculate the room temperature change of large buildings. Therefore, in order to obtain the temperature change of a large building and its corresponding power potential, this paper first proposes a building model based on CNN (convolutional neural network). Then, in order to fully apply the demand-response potential of the central air conditioning load, this paper puts forward an evaluation method of the load-reduction potential of the central air conditioning cluster based on pre-cooling and develops an economic load-reduction strategy according to the different energy consumption of different buildings in the pre-cooling stage. Finally, multiple building examples with different building parameters and temperature comfort ranges are set up, and the economic advantages of the proposed strategy are illustrated by Cplex solution examples.

As nano-zinc oxide (Nano-ZnO), a new type of nanomaterial, has antioxidant and intestinal protection effects, we hypothesized that dietary Nano-ZnO could modulate poor meat quality, oxidative stress and disturbed gut microbiota in the finishing pig model of naturally occurring intrauterine growth retardation (IUGR). A total of 6 normal-born weight (NBW) and 12 IUGR piglets were selected based on birth weight. The pigs in the NBW group received a basal diet, and IUGR pigs were randomly divided into two groups and treated with basal diet and 600 mg/kg Nano-ZnO-supplemented diet. Dietary Nano-ZnO ameliorated IUGR-associated declined meat quality by lowering the drip loss48h, cooking loss, shearing force and MyHc IIx mRNA expression, and raising the redness (a*), peak area ratio of immobilized water (P22), sarcomere length and MyHc Ia mRNA expression. Nano-ZnO activated the nuclear factor erythroid 2-related factor 2-glutamyl cysteine ligase (Nrf2-GCL) signaling pathway by promoting the nuclear translocation of Nrf2, increasing the GCL activities, and mRNA and protein expression of its catalytic/modify subunit (GCLC/GCLM), thereby attenuating the IUGR-associated muscle oxidative injury. Additionally, the composition of IUGR pigs’ cecal microbiota was altered by Nano-ZnO, as seen by changes in Shannon and Simpson indexes, the enhanced UCG-005, hoa5-07d05 gut group and Rikenellaceae RC9 gut group abundance. The UCG-005 and hoa5-07d05 gut group abundance were correlated with indicators that reflected the meat quality traits and antioxidant properties. In conclusion, Nano-ZnO improved the IUGR-impaired meat quality by altering water holding capacity, water distribution and the ultrastructure of muscle, activating the Nrf2-GCL signaling pathway to alleviate oxidative status and regulating the cecal microbial composition.

Opioids are the last option for the pharmacological treatment of neuropathic pain, but their antinociceptive effects are limited. Decreased mu opioid receptor (MOR) expression in the peripheral nervous system may contribute to this. Here, we showed that nerve injury induced hypermethylation of the Oprm1 gene promoter and an increased expression of methyl-CpG binding protein 2 (MeCP2) in injured dorsal root ganglion (DRG). The downregulation of MOR in the DRG is closely related to the augmentation of MeCP2, an epigenetic repressor, which could recruit HDAC1 and bind to the methylated regions of the Oprm1 gene promoter. MeCP2 knockdown restored the expression of MOR in injured DRG and enhanced the analgesic effect of morphine, while the mimicking of this increase via the intrathecal infusion of viral vector-mediated MeCP2 was sufficient to reduce MOR in the DRG. Moreover, HDAC1 inhibition with suberoylanilide hydroxamic acid, an HDAC inhibitor, also prevented MOR reduction in the DRG of neuropathic pain mice, contributing to the augmentation of morphine analgesia effects. Mechanistically, upregulated MeCP2 promotes the binding of a high level of HDCA1 to hypermethylated regions of the Oprm1 gene promoter, reduces the acetylation of histone H3 (acH3) levels of the Oprm1 gene promoter, and attenuates Oprm1 transcription in injured DRG. Thus, upregulated MeCP2 and HDAC1 in Oprm1 gene promoter sites, negatively regulates MOR expression in injured DRG, mitigating the analgesic effect of the opioids. Targeting MeCP2/HDAC1 may thus provide a new solution for improving the therapeutic effect of opioids in a clinical setting.

Deficit irrigation is a common approach in water-scarce regions to balance productivity and water use, whereas drought stress still occurs to various extents, leading to reduced physiological performance and a decrease in yield. Therefore, seeking a rapid and reliable method to identify wheat varieties with drought resistance can help reduce yield loss under water deficit. In this study, we compared ten wheat varieties under three deficit irrigation systems (W0, no irrigation during the growing season; W1, irrigation at jointing; W2, irrigation at jointing and anthesis). UAV thermal imagery, plant physiological traits [leaf area index (LAI), SPAD, photosynthesis (Pn), transpiration (Tr), stomatal conductance (Cn)], biomass and yield were acquired at different growth stages. Wheat drought resistance performance was evaluated through using the canopy temperature extracted from UAV thermal imagery (CT-UAV), in combination with hierarchical cluster analysis (HCA). The CT-UAV of W0 and W1 treatments was significantly higher than in the W2 treatment, with the ranges of 24.8–33.3 °C, 24.3–31.6 °C, and 24.1–28.9 °C in W0, W1 and W2, respectively. We found negative correlations between CT-UAV and LAI, SPAD, Pn, Tr, Cn and biomass under the W0 (R2 = 0.41–0.79) and W1 treatments (R2 = 0.22–0.72), but little relevance for W2 treatment. Under the deficit irrigation treatments (W0 and W1), UAV thermal imagery was less effective before the grain-filling stage in evaluating drought resistance. This study demonstrates the potential of ensuring yield and saving irrigation water by identifying suitable wheat varieties for different water-scarce irrigation scenarios.

It is very important to effectively describe the sweep characteristics of CO2 miscible flooding based on physical models for actual reservoir development. In this study, based on the geological characteristics of the Jilin ultra-low permeability reservoir, which has significant vertical heterogeneity, a two-dimensional double-layer heterogeneous visualization model with a permeability contrast of 10 and thickness contrast of 2 was designed to perform experimental research on the sweep law of CO2 miscible flooding with an injection-production mode of “united injection and single production”. With the goal of determining the obvious differences in the gas absorption capacity and displacement power of the two layers, the CO2 dynamic miscible flooding characteristics were comprehensively analyzed, and the sweep law of CO2 miscible flooding, including the oil and gas flow trend, migration direction of the oil–gas interface, and distribution characteristics of the miscible zone, was further studied in combination with the oil displacement effect. In this experiment, the gas absorption capacity was the key factor affecting the sweep efficiency of the CO2 miscible flooding. Under the combined influence of the internal and external control factors of the reservoir thickness, permeability, and injection-production mode, the gas absorption capacity of the high-permeability layer was much greater than that of the low-permeability layer, resulting in the retention of a large amount of remaining oil in the low-permeability layer, which effectively displaced and swept the oil in the high-permeability layer. The gas absorption capacity of the reservoir, gravitational differentiation, and miscible mass transfer were key factors affecting the migration of the oil–gas interface and distribution of the miscible zone. The entire displacement process could be divided into three stages: ① The gas-free rapid oil production stage, which was dominated by the displacement; ② the low gas–oil ratio stable oil production stage, which was jointly affected by the displacement and miscible mass transfer; and ③ the high gas–oil ratio slow oil production stage, which was dominated by the effect of CO2 carrying.

Protein arginine methyltransferase 5 (PRMT5) catalyzes the formation of mono- or symmetric dimethylarginine residues on histones and non-histone substrates and has been demonstrated to play important roles in many biological processes. In the present study, we observed that PRMT5 is abundantly expressed in spermatogonial stem cells (SSCs) and that Prmt5 deletion results in a progressive loss of SSCs and male infertility. The proliferation of Prmt5-deficient SSCs cultured in vitro exhibited abnormal proliferation, cell cycle arrest in G0/G1 phase and a significant increase in apoptosis. Furthermore, PLZF expression was dramatically reduced in Prmt5-deficient SSCs, and the levels of H3K9me2 and H3K27me2 were increased in the proximal promoter region of the Plzf gene in Prmt5-deficient SSCs. Further study revealed that the expression of lysine demethylases (JMJD1A, JMJD1B, JMJD1C, and KDM6B) was significantly reduced in Prmt5-deficient SSCs and that the level of permissive arginine methylation H3R2me2s was significantly decreased at the upstream promoter region of these genes in Prmt5-deficient SSCs. Our results demonstrate that PRMT5 regulates spermatogonial stem cell development by modulating histone H3 lysine modifications.

Nerve injury-induced gene expression change in the spinal cord is critical for neuropathic pain genesis. RNA N6-methyladenosine (m6A) modification represents an additional layer of gene regulation. We showed that spinal nerve ligation (SNL) upregulated the expression of matrix metallopeptidase 24 (MMP24) protein, but not Mmp24 mRNA, in the spinal cord neurons. Blocking the SNL-induced upregulation of spinal MMP24 attenuated local neuron sensitization, neuropathic pain development and maintenance. Conversely, mimicking MMP24 increase promoted the spinal ERK activation and produced evoked nociceptive hypersensitivity. Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) and RNA Immunoprecipitation (RIP) assay indicated the decreased m6A enrichment in the Mmp24 mRNA under neuropathic pain condition. Moreover, fat-mass and obesity-associated protein (FTO) was colocalized with MMP24 in spinal neurons and shown increased binding to the Mmp24 mRNA in the spinal cord after SNL. Overexpression or suppression of FTO correlates with promotion or inhibition of MMP24 expression in cultured spinal cord neurons. In conclusion, SNL promoted the m6A eraser FTO binding to the Mmp24 mRNA, which subsequently facilitated the translation of MMP24 in the spinal cord, and ultimately contributed to neuropathic pain genesis.

One of the problems of optical remote sensing of crop above-ground biomass (AGB) is that vegetation indices (VIs) often saturate from the middle to late growth stages. This study focuses on combining VIs acquired by a consumer-grade multiple-spectral UAV and machine learning regression techniques to (i) determine the optimal time window for AGB estimation of winter wheat and to (ii) determine the optimal combination of multi-spectral VIs and regression algorithms. UAV-based multi-spectral data and manually measured AGB of winter wheat, under five nitrogen rates, were obtained from the jointing stage until 25 days after flowering in the growing season 2020/2021. Forty-four multi-spectral VIs were used in the linear regression (LR), partial least squares regression (PLSR), and random forest (RF) models in this study. Results of LR models showed that the heading stage was the most suitable stage for AGB prediction, with R2 values varying from 0.48 to 0.93. Three PLSR models based on different datasets performed differently in estimating AGB in the training dataset (R2 = 0.74~0.92, RMSE = 0.95~2.87 t/ha, MAE = 0.75~2.18 t/ha, and RPD = 2.00~3.67) and validation dataset (R2 = 0.50~0.75, RMSE = 1.56~2.57 t/ha, MAE = 1.44~2.05 t/ha, RPD = 1.45~1.89). Compared with PLSR models, the performance of the RF models was more stable in the prediction of AGB in the training dataset (R2 = 0.95~0.97, RMSE = 0.58~1.08 t/ha, MAE = 0.46~0.89 t/ha, and RPD = 3.95~6.35) and validation dataset (R2 = 0.83~0.93, RMSE = 0.93~2.34 t/ha, MAE = 0.72~2.01 t/ha, RPD = 1.36~3.79). Monitoring AGB prior to flowering was found to be more effective than post-flowering. Moreover, this study demonstrates that it is feasible to estimate AGB for multiple growth stages of winter wheat by combining the optimal VIs and PLSR and RF models, which overcomes the saturation problem of using individual VI-based linear regression models.

Fixed-pattern noise seriously affects the clinical application of optical coherence tomography (OCT), especially, in the imaging of tumorous tissue. We propose a Hough transform-based fixed-pattern noise reduction (HTFPNR) method to reduce the fixed-pattern noise for optimizing imaging of tumorous tissue with OCT system. Using by the HTFPNR method, we detect and map the outline of fixed-pattern noise in the OCT images, and finally efficiently reduce the fixed-pattern noise by the longitudinal and horizontal intelligent processing procedure. We adopt the image-to-noise ratio with full information (INRfi) and the noise reduction ratio (NRR) to evaluate the outcome of fixed-pattern noise reduction ratio, respectively. The INRfi of OCT image's noise reduction of ex vivo brainstem tumor is approximate 21.92 dB. Six groups of OCT images, including three types of fixed-pattern noises, have been validated via experimental evaluation of the ex vivo gastric tumor. In the different types of fixed-pattern noise, the mean INRfis are 25.24, 23.04, and 19.35 dB, respectively. This result demonstrates that it is highly efficient and useful in fixed-pattern noise reduction. The fluctuating range of the NRR is 0.84-0.88 for three types of added noise in the OCT images. This result demonstrates that the HTFPNR method can as possible as save useful information by comparing to previous research. This proposed HTFPNR method can be used into the fixed-pattern noise reduction of OCT images in other soft biological tissue in the future.

Meiosis is the key step in gametogenesis. However, the mechanism of mammalian meiosis remains poorly understood due to the lack of an in vitro model. Here, we report that retinoic acid (RA) is sufficient for inducing leptotene/zygotene spermatocytes from cultured mouse spermatogonial stem cells. Multiple genes regulated by RA were identified by RNA sequencing. RA in combination with pup Sertoli cell co-culture resulted in a higher induction efficiency of 28%. Comparisons in the transcriptomic profiles of the induced spermatogenic cells and the isolated ones revealed the progressive induction of the germ cells. Using this model, we showed that Stra8, Agpat3, Fam57a, Wdr91, and Sox30 contributed to the proliferation and meiosis initiation differentially. In conclusion, we have efficiently generated spermatocytes using an RA/pup Sertoli cell-based in vitro model and provided proof-of-concept evidence for its application in identifying genes involved in mammalian meiosis.

Neuropathic pain (NP) is a type of chronic pain that is different from the common type of pain. The mechanisms of NP are still poorly understood. Exploring the key genes and neurobiological changes in NP could provide important diagnostic and treatment tools for clinicians. GSE24982 is an mRNA-seq dataset that we downloaded from the Gene Expression Omnibus database to identify key genes in NP. Differentially expressed genes (DEGs) were identified using the BRB-ArrayTools software and R. Functional and pathway enrichment analyses of the DEGs were performed using Metascape. A protein–protein interaction network was created and visualized using Cytoscape. A total of 123 upregulated DEGs were obtained. Among these genes, p53 was the node with the highest degree; hence, we validated it experimentally using a chronic constriction injury mouse model. Our results showed that overexpression of the p53 gene, and the subsequent increase in caspase-3 expression, in dorsal root ganglion neurons led to increased apoptotic changes in these neurons. p53 may therefore be partly responsible for the development of chronic constriction injury-induced NP.

A series of donor–acceptor type co-crystals of fullerene (as the acceptor) and arylthio-substituted tetrathiafulvalene derivatives (Ar-S-TTF, as the donor) were prepared and their structural features were thoroughly investigated. The formation of co-crystals relies on the flexibility of Ar-S-TTF and the size matches between Ar-S-TTF and fullerene. Regarding their compositions, the studied co-crystals can be divided into two types, where types I and II have donor:acceptor ratios of 1:1 and 1:2, respectively. Multiple intermolecular interactions are observed between the donor and acceptor, which act to stabilize the structures of the resulting co-crystals. In the type I co-crystals, the fullerene molecule is surrounded by four Ar-S-TTF molecules, that is, two Ar-S-TTF molecules form a sandwich structure with one fullerene molecule and the other two Ar-S-TTF molecules interact with the fullerene molecule along their lateral axes. In the type II co-crystals, one fullerene molecule has the donor–acceptor mode similar to that in type I, whereas the other fullerene molecule is substantially surrounded by the aryl groups on Ar-S-TTF molecules and the solvent molecules.

The combination of CuBr2 and arylthio-substituted tetrathiafulvalene derivatives (1–7) results in a series of charge-transfer (CT) complexes. Crystallographic studies indicate that the anions in the complexes, which are derived from CuBr2, show diverse configurations including linear [Cu(I)Br2]–, tetrahedral [Cu(II)Br4]2–, planar [Cu(II)2Br6]2–, and coexistence of planar [Cu(II)Br4]2– and tetrahedral [Cu(II)Br3]– ions. On the other hand, the TTFs show either radical cation or dication states that depend on their redox potentials. The central TTF framework on most of TTFs is nearly planar despite the charge on them, whereas the two dithiole rings on molecule 4 in complex 4·CuBr4 are significantly twisted with a dihedral angle of 38.3°. The magnetic properties of the complexes were elucidated. The temperature-dependent magnetic susceptibility of complex 5·Cu2Br6 shows the singlet–triplet transition with coupling constant J = −248 K, and that of 3·(CuBr4)0.5·CuBr3·THF shows the abrupt change at 270 K caused by the modulation of intermolecular interactions. The thermo variation of magnetic susceptibility for the other complexes follows the Curie–Weiss law, indicating the weak antiferromagnetic interaction at low temperature.

Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.