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The research on the source of marine sediments has a vital impact on identifying material sources, transport mechanism, and the evolution of sedimentary environments. Previous studies have shown many outstanding achievements on the source analysis of the South China Sea, but there are still some controversies over the complex source and transport mechanisms of the Zhongjiannan Basin. In this study, we took a gravity core (583cm) from the Zhongjiannan Basin and analyzed the particle size, rare earth elements, and Sr-Nd isotopes of the core sediments to further reveal the source and transport mechanism. The surface sediments in the Zhongjiannan Basin were relatively stable, with an average particle size ranging from 5.66 to 17.74 μm. The normalized standard curve of chondrite exhibited the depletion of Eu, with LREE dominated in REE. As the depth increased, 87Sr/86Sr ratios showed a gradually increasing trend, while δNd change was relatively complex. On the whole, 87Sr/86Sr ratios (from 0.721537 to 0.725322) and δNd (from -11.561617 to -12.289374) were in a relatively narrow range. Based on the particle size characteristics, we found the geochemical characteristics of sediment largely resulted from different sediment sources. By comparing rare earth elements and Sr-Nd isotopes, we concluded the sediment of the Zhongjiannan Basin was from mainly terrigenous contribution. In addition, taking into account factors such as terrain, migration distance, and river drainage system, we conclude the sediment were mainly from the Mekong River, the Red River, Taiwan Island, and Hainan Island. The surface current along the northeast direction was the main transportation route for the sediments of the Mekong River. The Guangdong coastal current and the southwest surface current transported sediment from the Red River and Hainan Island to the Zhongjiannan Basin. The surface current and deep-water current in the southwest direction carried sediment from Taiwan Island to the study area, while the Kuroshio also had some impacts on the sediment transportation of Taiwan Island. This study has reinforced the research on provenance in the South China Sea Basin and has an important significance on evolution of sedimentary environments, evolution of ancient oceans.

Abstract In this study, ordinary bamboo charcoal was activated at 750 °C with a steam flow rate of 6.25 L/min for 1.5 h. The effects of triglyceride adsorption by activated bamboo charcoal were investigated using an orthogonal design, and the adsorption mechanism was explored through molecular dynamics. Experimental results revealed that the adsorption capacity of activated bamboo charcoal for triglycerides reached 27.0%. The activated bamboo charcoal exhibited a specific surface area of 560.0 m2/g. The average pore diameter of activated bamboo charcoal was 1.6 nm, whereas that of ordinary bamboo charcoal was 7.2 nm. Molecular dynamics simulations revealed an interaction energy of − 145.12 kcal/mol between the molecular layers of activated bamboo charcoal and the triglyceride molecules, as well as an interaction energy of − 132.73 kcal/mol between the molecular layers of ordinary bamboo charcoal and the triglyceride molecules. The quantity of triglyceride molecules adsorbed by activated bamboo charcoal per gram was estimated to be 1.77 × 1021 while ordinary bamboo charcoal could adsorb merely 1.56 × 1019 triglyceride molecules per gram. This stark contrast in adsorption capacity underscores the superior performance of activated bamboo charcoal than its counterpart.

IntroductionHumanization is typically adopted to reduce the immunogenicity of murine antibodies generated by hybridoma technology when used in humans.MethodsTwo different strategies of antibody humanization are popularly employed, including “complementarity determining region (CDR) grafting” and “framework (FR) shuffling” to humanize a murine antibody against human programmed death-1 (PD-1), XM PD1. In CDR-grafting humanization, the CDRs of XM PD-1, were grafted into the human FR regions with high homology to the murine FR counterparts, and back mutations of key residues were performed to retain the antigen-binding affinities. While in FR-shuffling humanization, a combinatorial library of the six murine CDRs in-frame of XM PD-1 was constructed to a pool of human germline FRs for high-throughput screening for the most favorable variants. We evaluated many aspects which were important during antibody development of the molecules obtained by the two methods, including antibody purity, thermal stability, binding efficacy, predicted humanness, and immunogenicity, along with T cell epitope prediction for the humanized antibodies.ResultsWhile the ideal molecule was not achieved through CDR grafting in this particular instance, FR-shuffling proved successful in identifying a suitable candidate. The study highlights FR-shuffling as an effective complementary approach that potentially increases the success rate of antibody humanization. It is particularly noted for its accessibility to those with a biological rather than a computational background. DiscussionThe insights from this comparison are intended to assist other researchers in selecting appropriate humanization strategies for drug development, contributing to broader application and understanding in the field.

Amid advancements in aerospace technology and remote communication, a proliferation of Earth-observing satellites has been launched, creating a distinction between high- and low-altitude platforms. High-altitude satellites capture low-resolution (LR) aerial images, covering expansive areas, whereas their low-altitude counterparts provide high-resolution (HR) images of relatively confined spaces. The task of semantically categorizing LR aerial imagery is pivotal within numerous artificial intelligence (AI) systems but is encumbered by challenges including limited availability of labeled training data and the complexity of approximating human environmental perception through computational models. To address these challenges, this research proposes a novel strategy that marries active perception learning with Hessian-regularized feature selection (HRFS). This approach endeavors to procure perceptually and discriminatively potent visual representations for classifying LR aerial imagery. By emulating the human propensity to sequentially engage with salient regions within a visual field, an active learning paradigm is adopted to differentiate between salient and non-salient regions within LR aerial images. Theoretically, this methodology ensures that selected salient regions can reconstruct the aerial imagery in its entirety, thus mirroring the human visual system’s perception. Following this, a pioneering HRFS technique is devised to extract premium features from these selectively identified salient regions, distinguished by its semi-supervised operation, the capability for concurrent linear classifier training, and the preservation of the geometric distribution of samples within the feature space. Empirical assessments underscore the resilience and efficacy of the proposed classification framework.

In this work, we designed an effective ultra-high-definition (UHD) aerial photo categorization pipeline by designing an enhanced deep multi-clue matrix factorization (DMCMF). In detail, given a UHD aerial photo, those visually salient ground objects are extracted in the first place. In order to explicitly encode their spatial layout, multiple graphlets are constructed in each UHD aerial photo. Each is built by connecting those spatially neighboring object patches. Afterward, we propose a new matrix factorization (MF) model that intelligently uncover the underlying semantic features from graphlets. And multiple informative clues are encoded into the MF model. Notably, our DMCMF is optimized progressively. And we can represent each graphlet by a vector of binary hash codes. Lastly, each UHD aerial photograph can be effectively quantized into a feature vector by a kernel machine for multi-label categorization. Experiments have shown that our method is highly competitive in learning categorization model from imperfect labels at image-level.

Rockburst, one of the leading types of disaster in mining and rock engineering causing serious injuries and the loss of property, frequently occurs, involving various features and complex evolutionary mechanisms. Compared to rockbursts occurring at mining faces, those occurring in main roadways cause more serious problems for mine production. This paper first analyzes the characteristics of rockbursts in main roadways using two case studies involving the Gaojiapu and Cuimu coal mines. The causes of rockbursts in main roadways were studied using microseismic monitoring, energy density cloud maps, and seismic velocity tomography. During the mining of the 22306 working face in the Cuimu coal mine, targeted measures, such as deep-hole blasting of the roof strata and deep-hole blasting of the coal seam, were implemented to prevent rockbursts in the main roadways. The effectiveness of these measures was verified through long-term analysis of tremor activities. The study found that the influence of mining at two working faces on both sides of main roadways was significantly greater than that from a single-sided working face. The intensity of the tremor activities occurring near the main roadways was correlated with the distance from the working face to the main roadways. The closer the working face was to the main roadways, the stronger the tremor activities were near the main roadways. According to the distribution range of the tremors, the influence area of working face mining exceeded 800 m, with tremors distributed linearly along the main roadways. Even five months after the completion of working face mining, there were still a large number of tremors near the main roadways, which gradually disappeared after another five months. Mining activities were the main reason for the occurrence of main roadway rockbursts and the stress concentration within the main roadways themselves was another reason for the occurrence of rockbursts. The influence of working face mining could be reduced by deep-hole blasting of roof strata and the stress concentration within main roadways themselves could be reduced by large-diameter drilling. Those joint preventive measures effectively prevented the occurrence of rockbursts in main roadways. This study is of important theoretical and practical significance for further studies of rockburst mechanisms and prevention in regard to main roadways in coal mines, and the findings are significant in terms of the enhancement of safety in coal mines.

Chronic obstructive pulmonary disease (COPD) is characterized by dyspnea caused by airflow limitation. Further development may lead to decreased lung function and other lung diseases. Pyroptosis is a type of programmed cell death that involves multiple pathways. For example, the pathway induced by the NLR family pyrin domain containing 3 (NLRP3) inflammasome is closely associated with COPD exacerbation. Therefore, in this study, various machine learning algorithms were applied to screen for diagnostically relevant pyroptosis-related genes from the GEO dataset, and the results were verified using external datasets. The results showed that deep neural networks and logistic regression algorithms had the highest AUC of 0.91 and 0.74 in the internal and external test sets, respectively. Here, we explored the immune landscape of COPD using diagnosis-related genes. We found that the infiltrating abundance of dendritic cells significantly differed between the COPD and control groups. Finally, the communication patterns of each cell type were explored based on scRNA-seq data. The critical role of significant pathways involved in communication between DCS and other cell populations in the occurrence and progression of COPD was identified.

Energy is the fundamental prerequisite for human survival and development, as well as the driving force behind the progress of human civilization [...]

The unified power quality conditioner (UPQC), based on power angle control (PAC), addresses the power distribution issue and enhances equipment utilization between two active power filters (APF) of UPQC by employing conventional linear control algorithms that have complex control structures and exhibit challenges in adjusting controller parameters and control delays. This study proposes a UPQC predictive direct control strategy based on power angle control (PDCS-PAC). We combine the direct control strategy with the finite control set model predictive control (FCS-MPC) to establish the UPQC finite set model predictive direct control system model in the dq coordinate system. This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. Finally, we construct a simulation platform and a laboratory prototype to validate the feasibility and efficacy of the proposed control strategy.

We previously demonstrated that glycyrrhizin (GL) suppressed inflammation and carcinogenesis in an azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced murine model of colorectal cancer (CC). In this study, we found an accumulation of regulatory T cells (Tregs) in the spleen and suppression by GL in model mice. ICR mice were divided into four groups: Control, GL, CC, and GL-treated CC (CC+GL), and were sacrificed 20 weeks after AOM/DSS treatment. We measured spleen weight, areas of white and red pulp, and CD8+ T cells (cytotoxic T lymphocytes, CTL), and CD11c-positive cells (dendritic cells) in splenic tissues and forkhead box protein 3 (FoxP3)-positive cells (Tregs) in colorectal and splenic tissues. In all cases, the CC group showed a significant increase compared with those in Control group, and GL administration significantly attenuated this increase. These results indicate that Tregs accumulated in the spleen may participate in inflammation-related carcinogenesis by suppressing CTL. We also suggest that GL which binds to high-mobility group box 1 (HMGB1), suppresses carcinogenesis with decreasing Tregs in the spleen. Furthermore, there was an expression of FoxP3 in cancer cells, indicating that it may be involved in the malignant transformation of cancer cells.

To study the influence of inclusions on the fracture evolution and mechanical properties of mortar structures, a series of uniaxial compression tests for mortar samples containing cylinder inclusions of varying mechanical properties were conducted. The digital image correlation (DIC) technique was employed for the analysis of deformation characteristics. In addition, failure modes for each sample were determined using self-documenting code. The result shows that inclusions filled in holes significantly influence the mechanical properties and failure characteristics of mortar structures as they can change the stress distribution and cracking process. Cracks are typically initiated at the boundaries of the inclusions but will only extend into the inclusion if it is less robust than the surrounding matrix. Sample strength increases significantly with an increase in sample strength when the inclusion’s strength does not surpass that of the surrounding material. Once the inclusion’s strength exceeds that of the surrounding matrix, the strength of the specimen remains relatively unchanged.

This paper investigates the asynchronous motors driven by a Three-Level Neutral-Point-Clamped Voltage Source Inverter (3L-NPC-VSI) and aims to achieve control without weight factors and reduce torque ripple. It puts forward a non-weighted two-stage Finite-Control-Set Model Predictive Control (FCS-MPC) strategy. First, a hierarchical optimization method is adopted to address the difficulty of setting weight factors in traditional FCS-MPC applications. The method offers stratified designs of three performance indices, voltage jump, common-mode voltage, and current tracking, obviating the need for weight factor setting and reducing the calculation load of predictions. Secondly, to further mitigate torque ripple, an optimal vector or vector combination is implemented at the current control layer by adhering to the principle of minimal current tracking error. During the selection of the optimal vector combination, the first vector of the combination is chosen to be the vector at the end of the present cycle. This ensures that there is at most one switch within each control period, reducing the switching losses of the two-stage FCS-MPC. Lastly, detailed simulation and experimental analyses are conducted to verify the feasibility and effectiveness of the proposed strategy.

Wild soybean (Glycine soja L.), drought-tolerant cultivar Tiefeng 31 (Glycine max L.), and drought-sensitive cultivar Fendou 93 (Glycine max L.) were used as materials to investigate the drought tolerance mechanism after 72 h 2.5 M PEG 8000 (osmotic potential −0.54 MPa)-simulated drought stress at the seedling stage. The results indicated that the leaves of the G. soja did not wilt under drought stress. However, both the drought-tolerant and drought-sensitive cultivated soybean cultivars experienced varying degrees of leaf wilt. Notably, the drought-sensitive cultivated soybean cultivars exhibited severe leaf wilt after the drought stress. Drought stress was determined to have a significant impact on the dry matter of the above-ground part of the drought-sensitive cultivar Fendou 93, followed by the drought-tolerant cultivar Tiefeng 31, with the lowest reduction observed in G. soja. Furthermore, the presence of drought stress resulted in the closure of leaf stomata. G. soja exhibited the highest proportion of stomatal opening per unit area, followed by the drought-tolerant cultivar Tiefeng 31, while the drought-sensitive cultivar Fendou 93 displayed the lowest percentage. Photosynthesis-related indexes, including photosynthetic rate, intercellular CO2, transpiration rate, and stomatal conductance, decreased in Fendou 93 and Tiefeng 31 after drought stress, but increased in G. soja. In terms of the antioxidant scavenging system, lower accumulation of malondialdehyde (MDA) was observed in G. soja and Tiefeng 31, along with higher activities of superoxide dismutase (SOD, EC 1.15.1.1) and catalase (CAT, EC 1.11.1.6) to counteract excess reactive oxygen species and maintain cell membrane integrity. In contrast, the drought-sensitive cultivar Fendou 93 had higher MDA content and higher activities of ascorbate peroxidase (APX, EC 1.11.1.11) and peroxidase (POD, 1.11.1.7). G. soja and Tiefeng 31 also exhibited less accumulation of osmolytes, including soluble sugar, soluble protein, and free proline content. The activities of δ-OAT, ProDH, and P5CS, key enzymes in proline anabolism, showed an initial increase under drought stress, followed by a decrease, and then an increase again at the end of drought stress in G. soja. Before drought stress, Tiefeng 31 had higher activities of ProDH and P5CS, which decreased with prolonged drought stress. Fendou 93 experienced an increase in the activities of δ-OAT, ProDH, and P5CS under drought stress. The δ-OAT gene expression levels were up-regulated in all three germplasms. The expression levels of the P5CS gene in Fendou 93 and Tiefeng 31 were down-regulated, while G. soja showed no significant change. The expression of the P5CR gene and ProDH gene was down-regulated in Fendou 93 and Tiefeng 31, but up-regulated in G. soja. This indicates that proline content is regulated at both the transcription and translation levels.

Retargeting aims at displaying a photo with an arbitrary aspect ratio, wherein the visually/semantically prominent objects are appropriately preserved and visual distortions can be well alleviated. Conventional retargeting models are built upon the visual perception of photos from a family of prespecified communities (e.g., “portrait”), wherein the underlying community-specific features are not learned explicitly. Thus, they cannot appropriately retarget aerial photos, which contains a rich variety of objects with different scales. In this article, a novel aerial photo retargeting framework is designed by encoding the deep features from automatically detected Google Maps (https://www.google.com/maps) communities into a regularized probabilistic model. Specifically, we first propose an enhanced matrix factorization (MF) algorithm to calculate communities based on million-scale Google Maps pictures, for each of which deep feature is learned simultaneously. The enhanced MF incorporates label denoising, between-communities correlation, and deep feature encoding collaboratively. Subsequently, a probabilistic model called latent topic model (LTM) is designed that quantifies the spatial layouts of multiple Google Maps communities in the underlying hidden space. To alleviate the overfitting from Google Maps communities with imbalanced numbers of aerial photos, a regularizer is added into the LTM. Finally, by leveraging the regularized LTM, we shrink the test photo horizontally/vertically to maximize the posterior probability of the retargted photo. Comprehensive subjective evaluations and visualizations have demonstrated the advantages of our method. Besides, our calculate Google Maps communities are competitively consistent with the ground truth, according to the quantitative comparisons on the 2 M Google Maps photos.

Current treatment options for diabetic neuralgia are limited and unsatisfactory. Tanezumab, a monoclonal antibody that blocks nerve growth factor (NGF) signaling, has been shown to be effective in relieving the clinical symptoms of osteoarthritis pain, chronic low back pain, cancer pain induced by bone metastasis, and diabetic neuralgia. However, the clinical development of tanezumab has been terminated due to the risk of induction of rapidly progressive osteoarthritis (RPOA), and no other NGF antibodies have been examined for their ability to treat diabetic neuralgia in either animal models or clinical trials. In this study, a humanized high‐affinity NGF monoclonal antibody (mAb), huAb45 that could neutralize the interaction between NGF and its high‐affinity receptor TrkA. In a mouse diabetic neuralgia model, it effectively relieved neuropathic pain. This study may serve as the necessary foundation for future studies of huAb45 to potentially treat diabetic neuralgia.

To elucidate ths chemical composition of Lilium brownii var. Viridulum Baker and the impact of primary processing on its quality, a comparison was made on the polysaccharide and extract contents of ten batches of Lilium from different regions, including Lilium lancifolium Thunb., Lilium brownii var. Viridulum Baker, and Lilium davidi var. unicdor cotton. The chemical composition differences of the three Lilium species mentioned above were compared using high-performance liquid chromatography (HPLC) fingerprinting. The chemical components of Lilium brownii var. Viridulum Baker were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MSE). The boiling time and drying temperature of fresh Lilium brownii var. Viridulum Baker were investigated using the comprehensive scoring method based on the polysaccharide and extract contents. The results showed that the polysaccharide content of ten batches of Lilium from different origins ranged from 13.34% to 34.00%, and the extract content ranged from 27.10% to 47.10%. The HPLC fingerprinting results showed that the similarity of the three Lilium species ranged from 0.796 to 0.999, and the chemical components of Lilium davidi var. unicdor cotton differed significantly from those of Lilium lancifolium Thunb. and Lilium brownii var. Viridulum Baker. UPLC-Q-TOF-MSE identified 22 phenolic compounds, 35 steroidal saponins, and 6 alkaloids in Lilium brownii var. Viridulum Baker. Boiling for 5 min and drying at 85 °C has the least effect on the quality of fresh Lilium.

Accurately recognizing aerial photographs is a useful technique in many domains like autonomous driving and environmental evaluation. In practice, both low-resolution and high-resolution aerial photos are captured asynchronistically for each region, as there are hundreds of Earth observation satellites orbitting the Earth. Realizing such multiresolution-based region semantic understanding is a difficult task due to three challenges: 1) mimicking human visual perception when they actively viewing the semantic objects inside each aerial photo; 2) deeply modeling the visually/semantically salient objects sequentially perceived by human visual system; and 3) developing a cross-resolution knowledge transferal module to enhance the feature representation for an area. To solve these challenges, we propose a cross-domain aerial photograph categorization system by leveraging the low-resolution spatial composition to enhance the deep encoding of human gaze shifting path (GSP) with a high-resolution. More specifically, we first use an active learning algorithm to discover multiple visually/semantically salient object patches for constructing GSP from a high-resolution aerial photo. Then, an aggregation-based deep model is formulated to sequentially link the deep features learned from the object patches inside each GSP. Subsequently, a novel knowledge transferal algorithm leverages the global spatial composition from low-resolution counterparts to upgrade the deeply-learned GSP feature of the high-resolution aerial photo. Using the upgraded deep GSP feature, a multilabel SVM classifier is trained for categorizing aerial photographs. Comparative studies on our million-scale aerial photograph set have demonstrated the competitiveness of our approach.

(1) Background: It is our purpose to identify the differences in the changes in Complement C5a receptor 1 (C5aR1) levels showing the degree of inflammation at onset and Immunoglobulin G (IgG) levels showing the extent of survival of the virus fragments after recovery between coronavirus disease 2019 (COVID-19) and pneumonia coronavirus disease (non-COVID-19) for saving patients’ lives. (2) Methods: First, the studies showing these markers’ levels in individual patients before and after the passage of time were selected from the PubMed Central® databases with the keywords (((COVID-19) AND individual) NOT review) AND C5a/IgG. Then, no changes in these markers’ levels with conventional analyses were selected from the studies. Finally, the no changes were reexamined with our new two-tailed t-test using the values on the regression line between initial levels and changed levels instead of the mean or median of changed levels as the expected values of changed levels. (3) Results: Not conventional analyses but our new t-test suggested a greater increase in C5aR1-levels at onset and a smaller decrease in IgG-levels after recovery in COVID-19 patients than non-COVID-19 patients. (4) Conclusion: Our new t-test also should be used in clinics for COVID-19 patients.

Abstract The evolution of coronaviruses, such as SARS-CoV-2, makes broad-spectrum coronavirus preventional or therapeutical strategies highly sought after. Here we report a human angiotensin-converting enzyme 2 (ACE2)-targeting monoclonal antibody, 3E8, blocked the S1-subunits and pseudo-typed virus constructs from multiple coronaviruses including SARS-CoV-2, SARS-CoV-2 mutant variants (SARS-CoV-2-D614G, B.1.1.7, B.1.351, B.1.617.1, and P.1), SARS-CoV and HCoV-NL63, without markedly affecting the physiological activities of ACE2 or causing severe toxicity in ACE2 “knock-in” mice. 3E8 also blocked live SARS-CoV-2 infection in vitro and in a prophylactic mouse model of COVID-19. Cryo-EM and “alanine walk” studies revealed the key binding residues on ACE2 interacting with the CDR3 domain of 3E8 heavy chain. Although full evaluation of safety in non-human primates is necessary before clinical development of 3E8, we provided a potentially potent and “broad-spectrum” management strategy against all coronaviruses that utilize ACE2 as entry receptors and disclosed an anti-coronavirus epitope on human ACE2.

Abstract Because cotton is the most important fiber crop, the differentiation and development mechanism of cotton fiber cells has been a hot topic in cotton research. NAC (for NAM, ATAF, and CUC2) is a class of plant‐specific transcription factor families that regulate multiple aspects of plant growth and development. Previously, we identified 33 differentially expressed NAC genes in upland cotton based on fiber‐related transcriptome profiling. In this study, we conducted chromosome localization, systematic evolution, and gene structural analysis of 242 NAC genes genome‐wide based on a high‐quality reference genome of upland cotton. In addition, the expression pattern analysis of 16 differentially expressed GhNACs was carried out by RT–PCR using ovules at early fiber initiation stages of n2 recessive naked seed mutant (n2NSM) and Xuzhou142 fuzzless–lintless mutant (Xu142fl). The results showed that GhNAC230 and GhNAC115 were most closely related to AtSND1 and downregulated in ovules of Xu142fl compared with n2NSM. Quantitative RT–PCR (qRT–PCR) analysis of GhNAC230 demonstrated its gradual accumulation from −1 days postanthesis (DPA) to 1 DPA in n2NSM and further confirmed its downregulated expression in 1 DPA ovules of Xu142fl compared to n2NSM. The current study predicted a pair of NAC genes that might be key candidate genes that are crucial for lint fiber development.

Background: Psoriasis vulgaris is an inflammatory skin disease. Observational studies have shown associations between circulating cytokine levels and psoriasis vulgaris. But the causal relationship between circulating cytokine and psoriasis vulgaris remains elusive.Methods: To assess the causal effects of cytokine levels on the risk of psoriasis vulgaris and vice versa, we performed a two-sample Mendelian randomization (MR) study by using the inverse-variance weighted (IVW), weighted median, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) in genome-wide association summary statistics of 41 circulating cytokines in up to 8,293 individuals and psoriasis vulgaris in 399,883 individuals.Results: We identified that increasing RANTES level induced an elevated risk of psoriasis vulgaris in IVW (β = 0.33, S.E. = 0.12, p = 0.006). This causal effect showed consistency across the weighted median (β = 0.35, S.E. = 0.15, p = 0.022) and MR-PRESSO method (β = 0.33, S.E. = 0.11, p = 0.028).Conclusions: Our results suggest a potential causal effect of elevated RANTES concentration on the increased risk of psoriasis vulgaris.

Aiming at the delay caused by the phase-locked loop (PLL) and harmonic detection in the traditional control of a series active power filter (SAPF), a deadbeat direct control (DBDC)-based finite control set model predictive control (FCS-MPC) strategy for the SAPF is proposed in this work. Firstly, a reference voltage generation mechanism based on direct control is established, which avoids the delay in harmonic detection, thus improving the dynamic response performance of the system. Secondly, the reference current generation mechanism suitable for the SAPF is derived and established using the deadbeat control (DBC) in the αβ coordinate system, based on which the FCS-MPC system is constructed. It eliminates the complex coordinate transformation and PLL and effectively compensates for the full-frequency harmonic voltage. Finally, the proposed control strategy is verified by a simulation and an experiment. The results suggest that the proposed control strategy can effectively compensate for the load voltage and suppress harmonic distortion for the temporary swell and sag of the grid voltage, sudden load changes, and harmonic distortion conditions.

Intercropping has been widely adopted by farmers because it often enhances crop productivity and economic returns. However, to increase the comprehensive production benefits of agricultural cultivation and increase the economic benefits of cotton in Northwest Shandong Province, a set of green, ecological, and efficient intercropping mode suitable for Northwest Shandong Province was preliminarily formed. A 2-year intercropping experiment was conducted in Xiajin and Dongping counties in Shandong Province, with six alternative intercropping patterns proposed. After analyzing the experimental data, it was determined that the traditional cotton–peanut intercropping method is not mechanized and that a new intercropping mode has been proposed: four rows of cotton and six rows of peanut. We selected the appropriate intercropping mode for Xiajin and Dongping counties. The production efficiency of 4:4 cotton intercropping in Peanut Ridge was the best in Dongping and Xiajin counties, which was 28–123% higher than that of monoculture. This planting pattern is suitable for demonstration and promotion in the two counties, as well as in the traditional cotton area of the old Yellow River in Northwest Shandong.

Machining feature recognition is a key technology to realize CAD/CAPP/CAM system integration. Aiming at high robustness of traditional processing feature recognition in image reasoning, an automatic processing shape recognition method based on fuzzy learning of processing surrounding point black data is proposed. The Cloud RNN in the PointNet stage strongly demonstrates that the framework originates from convolutional neural spider webs. Protector shape for detailed discoloration data on constructed prominence surfaces for automatic rifle recognition is conducted. Spot staining data sample library is also constructed. The prosecuting feature recognizer gained advantages through sample training, which realized robot-style notification of 36 processing shapes. This is conducted with a recognition accuracy rate of over 90%. The method is simple and efficient, although it is not suitable for point cloud data with backlash and defects. It is sensible and still has usable robustness and confirmation performance against mischief around shape peripheries due to shape intersections.

The machine-driven products processed by CNC machine tools are divided into multiple parts, which are often transmitted to unqualified processing crystals due to the error of the part’s posture, thus affecting the projection effect. Aiming at handling this problem, we, in this work, propose a method for locating and correcting machine capabilities based on bicycle visual recognition. The robot obtains coordinates and offset points through the vision system. In order to satisfy the requirement of fast sorting of the robot parts, a robot species method (BAS-GA) that supports machine vision and improved genetic algorithm rules is proposed. The rank method first preprocesses the part copies, then uses the Sift feature twin similarity notification algorithm to filter the part idols, and finally uses in-law deformation to place the target parts. Afterward, an particular model is built for the maintenance of the nurtural skill, and the mathematical mold is solved using the BAS-GA algorithmic program authority. The close trail of the robot is maintained to manifest the marijuana of the robot. Experimental inference have shown that the BAS-GA algorithm rule achieves the optimal conclusion similar to the pseudo-annealing algorithmic program plant. Meanwhile, the genetic algorithm rule is modified ant settlement algorithm program. Knife sharpening was also reduced by 7%, inferring that this process can effectively improve the robot’s action success rate.

Hainan Island, the largest island in the northwestern South China Sea (SCS), is characterized by many tropical mountainous rivers that flow into the SCS. The geochemistry of these riverine sediments and the factors controlling the weathering intensity are still not well understood. In this study, sedimentary geochemistry has been investigated by using 45 riverine sediments collected from 18 major rivers on Hainan Island. The Hainan riverine sediments are only first-cycle rather than polycyclic sediments, and they faithfully reflect the present weathering intensity. The high and steady values of the Chemical Index of Alteration (CIA) indicate that the riverine sediments at different parts of the Hainan Island have overall undergone intensive chemical weathering. The low values of Weathering Index of Parker (WIP) and high αCa, αK, αSr, and αBa values of north Hainan indicate the highest weathering degree, which is mainly influenced by the flat topography. The values of αNa, αK, αSr, and αBa of southwest Hainan which are higher than those of east Hainan suggest that the leaching of elements such as Na, K, Sr, and Ba is more extreme (i.e., more intensive weathering). These are mainly caused by the different physical denudation due to different summer precipitation. Overall, the Hainan Island is featured by intensive chemical weathering and is classified as a typical transport-limited weathering regime. Therefore, the geochemistry of the riverine sediments of the Hainan Island is different from that of sediments in tectonically active regions (e.g., Taiwan Island).

The balance between vegetative and reproductive growth is the central objective in the cotton production system, which is associated with cotton maturity and yield. In China, manual topping (MT) has been performed many years prior to or during the flowering period to inhibit vegetative growth and enhance reproductive growth. MT is gradually being replaced by chemical topping (CT) with mepiquat chloride (MC, 180 g ha−1, 98% soluble powder) due to labor shortages and increasing labor cost. To determine whether CT influences cotton maturity and yield relative to MT, we carried out field experiments at four locations in the Yellow River Valley of China during 2018–2020. The results showed that CT did not alter the boll age, and although it produced taller and slender spatial boll distribution under several environments, it had little effect on the accumulation of boll fraction (the number of bolls in a given period divided by total boll number) over time at the end of blooming across locations. As a result, there were no significant differences between MT and CT in boll opening percentage in the late season. CT did not influence yield or yield components, except under severe drought. Therefore, CT with MC (180 g/ha, 98% soluble powder) during the flowering period will not compromise the maturity or yield of cotton in the Yellow River Valley of China. Similar outcomes would be achieved in other areas with similar ecological conditions and social conditions that require an alternative to extensive manual labor.

In practical engineering, coal burst is usually caused by the combination of high geo-stress and dynamic loading. To study the dynamic response of coal in geo-stress conditions, numerical models of a coupled static–dynamic split Hopkinson pressure bar (SHPB) test system were established, based on which impact tests for coal specimens at different impact speeds and static pre-stress levels were conducted. The mechanical properties, energy characteristics and failure patterns of coal specimens under coupled static and dynamic loads were analyzed. The results show that when the pre-stress is constant, peak stress, the maximum strain energy and the maximum kinetic energy increase significantly with impact speed. Nevertheless, they are less affected by the static pre-stress, increasing linearly with a pre-stress level under lower impact speeds but becoming stable under higher impact speeds. In addition, weak dynamic loads may trigger the instability of the coal specimen in a high pre-stress condition. Overall, both the impact speed and static pre-stress have influence on the mechanical behavior and energy characteristics of coal specimens under coupled static and dynamic loads, but the influence of the impact speed outweighs that of the static pre-stress.

Given their sessile nature, plants have evolved sophisticated regulatory networks to confer developmental plasticity for adaptation to fluctuating environments. Epigenetic codes, like tri-methylation of histone H3 on Lys27 (H3K27me3), are evidenced to account for this evolutionary benefit. Polycomb repressive complex 2 (PRC2) and PRC1 implement and maintain the H3K27me3-mediated gene repression in most eukaryotic cells. Plants take advantage of this epigenetic machinery to reprogram gene expression in development and environmental adaption. Recent studies have uncovered a number of new players involved in the establishment, erasure, and regulation of H3K27me3 mark in plants, particularly highlighting new roles in plants’ responses to environmental cues. Here, we review current knowledge on PRC2-H3K27me3 dynamics occurring during plant growth and development, including its writers, erasers, and readers, as well as targeting mechanisms, and summarize the emerging roles of H3K27me3 mark in plant adaptation to environmental stresses.

Numerous tremors occur during excavation and mining periods in coal mines, and low-energy tremors often occur before strong tremors. In addition, it is found that not all strong tremors cause rockbursts. Therefore, generating behaviors of strong tremors and the triggering criterion for the occurrence of the rockburst must be investigated. In this study, generating behaviors of strong tremors were inferred by velocity tomograms and energy density clouds. An innovative facility capable of applying dynamic disturbance to roadway models was developed to study the triggering criterion for rockbursts. Velocity tomograms indicated that the stress concentration extended to the syncline region with the advance of the coalface. High-energy-density clouds expanded rapidly and regularly in some areas that were parts of the high-velocity region, indicating that the stress increased rapidly in these areas, until strong tremors took place nearby. AE activities suggested that the modelled roadway offered good resistance as the dynamic loading energy grew from 29.4 J to 117.6 J. Then, sharp AE activity at the dynamic loading energy of 147 J indicated the ultimate shock resistance of the roadway was almost reached. Finally, bursting failure of the modelled roadway was observed at a dynamic loading energy of 176.4 J.

At present, coal bursts in working faces of steeply inclined coal seams (SICSs) have rarely been investigated, and current research focuses on the influences of roof breaking and instability of overlying structures in goaf on coal bursts; however, the stress state of coal masses in working faces being subjected to coal bursts is rarely researched. To overcome the above defects, a model for analysing stresses on coal masses in horizontal section of SICSs was established based on the coal burst that occurred in LW5521-20, Yaojie No. 3 Coal Mine, Lanzhou, Gansu Province, China. Moreover, the mechanism underpinning such a coal burst in SICSs was analysed based on the superposition mechanism of dynamic and static loads. The results show that the side abutment pressure near the roof and floor under the horizontal sections of SICSs is asymmetrically distributed in the vertical direction in which the peak of side abutment pressure near the roof is closer to the working face and therefore is taken as the source of static loads for coal bursts in working faces. When the superimposed dynamic load caused by hanging roof breaking and high static load borne in the coal masses is larger than the critical load for coal burst inception, a coal burst will occur. Furthermore, the superimposed dynamic load induced by coal bursts on the support and the initial static load on the supports are larger than their limiting load, which leads to support collapse and eventually causes dynamic failure of the working face. The coal burst in working faces in horizontal sections of SICSs can be prevented by using deep-hole presplit blasting in a hard roof, destress blasting in coal masses, and support optimisation of working faces, showing a favourable preventative effect.

Understanding the dynamic mechanical behaviors and microstructural properties of outburst-prone coal is significant for preventing coal and gas outbursts during underground mining. In this paper, the split Hopkinson pressure bar (SHPB) tests were completed to study the strength and micro-structures of outburst-prone coal subjected to compressive impact loading. Two suites of coals—outburst-prone and outburst-resistant—were selected as the experimental specimens. The characteristics of dynamic strength, failure processes, fragment distribution, and microstructure evolution were analyzed based on the obtained stress-strain curves, failed fragments, and scanning electron microscopy (SEM) and nuclear magnetic resonance (NMR) images. Results showed that the dynamic compressive strength inclined linearly with the applied strain rate approximately. The obtained dynamic stress-strain responses could be represented by a typical curve with stages of compression, linear elasticity, microcrack evolution, unstable crack propagation, and rapid rapture. When the loading rate was relatively low, fragments fell in tension. With an increase in loading rates, the fragments fell predominantly in shear. The equivalent particle size of coal fragments decreased with the applied strain rate. The Uniaxial compressive strength (UCS) of outburst-prone coal was smaller than that of resistant coal, resulting in its smaller equivalent particle size of coal fragments. Moreover, the impact loading accelerated the propagation of fractures within the specimen, which enhanced the connectivity within the porous coal. The outburst-prone coal with behaviors of low strength and sudden increase of permeability could easily initiate gas outbursts.

Cereal storage proteins are major nitrogen sources for humans and livestock. Prolamins are the most abundant storage protein in most cereals. They are deposited into protein bodies (PBs) in seed endosperm. The inner structure and the storage mechanism for prolamin PBs is poorly understood. Maize opaque10 (o10) is a classic opaque endosperm mutant with misshapen PBs. Through positional cloning, we found that O10 encodes a novel cereal-specific PB protein. Its middle domain contains a seven-repeat sequence that is responsible for its dimerization. Its C terminus contains a transmembrane motif that is required for its ER localization and PB deposition. A cellular fractionation assay indicated that O10 is initially synthesized in the cytoplasm and then anchored to the ER and eventually deposited in the PB. O10 can interact with 19-kD and 22-kD α-zeins and 16-kD and 50-kD γ-zeins through its N-terminal domain. An immunolocalization assay indicated that O10 co-localizes with 16-kD γ-zein and 22-kD α-zein in PBs, forming a ring-shaped structure at the interface between the α-zein-rich core and the γ-zein-rich peripheral region. The loss of O10 function disrupts this ring-shaped distribution of 22-kD and 16-kD zeins, resulting in misshapen PBs. These results showed that O10, as a newly evolved PB protein, is essential for the ring-shaped distribution of 22-kD and 16-kD zeins and controls PB morphology in maize endosperm.

Genomic imprinting is an epigenetic phenomenon causing parent-of-origin specific differential expression of maternally and paternally inherited alleles. While many imprinted genes have been identified in plants, the functional roles of most of them are unknown. In this study, we systematically examine the functional requirement of paternally expressed imprinted genes (PEGs) during seed development in Arabidopsis thaliana. While none of the 15 analyzed peg mutants has qualitative or quantitative abnormalities of seed development, we identify three PEGs that establish postzygotic hybridization barriers in the endosperm, revealing that PEGs have a major role as speciation genes in plants. Our work reveals that a subset of PEGs maintains functional roles in the inbreeding plant Arabidopsis that become evident upon deregulated expression.