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Abstract In the General Next-to-Minimal Supersymmetric Standard Model (GNMSSM), singlet particles may form a secluded sector of dark matter (DM), in which Singlino-like DM could achieve the observed relic abundance through various channels such as χ ~ 1 0 χ ~ 1 0 → h s h s $$ {\overset{\sim }{\chi}}_1^0{\overset{\sim }{\chi}}_1^0\to {h}_s{h}_s $$ , A s A s , h s A s , where h s and A s represent singlet-dominated CP-even and CP-odd Higgs bosons. We provide analytical formulas for both the spin-independent and spin-dependent cross sections of Singlino DM scattering with nucleons, illustrating their dependence on the model’s parameters in a clear manner. We also present analytic expressions for the annihilation cross sections of these three important channels. Based on these preparations, we conducted Bayesian analyses of the GNMSSM and concluded that the theory significantly favored Singlino-dominated DM over Bino-like DM across a much broader range of parameters. The combined results from our numerical analyses and the formulas distinctly highlight crucial aspects of DM physics within the GNMSSM.

Abstract Background Hypertension (HT) is one of the most common manifestations in patients with catecholamine-secreting neuroendocrine tumors. Although the cardiovascular manifestations of these tumors have been described, there have been no large-scale investigations of the profile of HT and changes in cardiac structure and function that occur in patients with pheochromocytomas and paragangliomas (PPGL). Materials and methods In this study, we investigated the prevalence of HT and left ventricular remodeling (LVR) in a cohort of 598 patients who underwent surgery for PPGL at our center between January 2001 and April 2022. Information on demographics, reason for hospitalization, medical history, biochemical parameters, findings on echocardiography, and tumor characteristics were recorded. The LVR index was compared according to whether or not there was a history of HT. Results The average age was 47.07 ± 15.07 years, and 277 (46.32%) of the patients were male. A history of HT was found in 423 (70.74%) of the 598 patients. Paraganglioma was significantly more common in the group with HT (26.00% vs. 17.71%, P = 0.030) and significantly less likely to be found incidentally during a health check-up in this group (22.93% vs. 59.43%, P

Highlights A unique approach is proposed: constructing a polymer fiber rigid network with high glass transition temperature. Frozen bulk heterojunction morphology impeded deterioration of exciton quenching, charge transport, and charge extraction properties during thermal aging. The strategy is universal and can be further optimized for enhanced thermal stability and improved mechanical resilience.

Abstract Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

Abstract Objective To evaluate the antibacterial effectiveness of a combination of ε-poly-L-lysine (ε-PL), funme peptide (FP) as well as domiphen against oral pathogens, and assess the efficacy of a BOP® mouthwash supplemented with this combination in reducing halitosis and supragingival plaque in a clinical trial. Materials and methods The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the compound against Fusobacterium nucleatum, Porphyromonas gingivalis, Streptococcus mutans, and Aggregatibacter actinomycetemcomitans were determined by the gradient dilution method. Subsequently, the CCK-8 assay was used to detect the toxicity of mouthwash on human gingival fibroblastst, and the effectiveness in reducing halitosis and supragingival plaque of the mouthwash supplemented with the combination was analyzed by a randomized, double-blind, parallel-controlled clinical trial. Results The combination exhibited significant inhibitory effects on tested oral pathogens with the MIC

This paper uses approximate analytical formulas and numerical results with the bino-dominated dark matter (DM) as an example to analyze the impact of the LUX-ZEPLIN (LZ) experiment on the DM phenomenology and naturalness in the Minimal Supersymmetric Standard Model (MSSM). We conclude that the limitation of the latest LZ experiment worsens the naturalness of the MSSM, as the predictions of the Z-boson mass and DM relic density demonstrate, particularly in the regions where the correct DM relic density is obtained by the Z- or h-mediated resonant annihilations.

Abstract Graph neural networks (GNNs) have shown powerful capabilities in modeling and representing graph structural data across various graph learning tasks as an emerging deep learning approach. However, most existing GNNs focus on single-relational graphs and fail to fully utilize the rich and diverse relational information present in real-world graph data. In addition, deeper GNNs tend to suffer from overfitting and oversmoothing issues, leading to degraded model performance. To deeply excavate the multi-relational features in graph data and strengthen the modeling and representation abilities of GNNs, this paper proposes a multi-channel deep graph convolutional neural network method called DeepMCGCN. It constructs multiple relational subgraphs and adopts multiple GCN channels to learn the characteristics of different relational subgraphs separately. Cross-channel connections are utilized to obtain interactions between different relational subgraphs, which can learn node embeddings richer and more discriminative than single-channel GNNs. Meanwhile, it alleviates overfitting issues of deep models by optimizing convolution functions and adding residual connections between and within channels. The DeepMCGCN method is evaluated on three real-world datasets, and the experimental results show that its node classification performance outperforms that of single-channel GCN and other benchmark models, which improves the modeling and representation capabilities of the model.

Abstract Background m6A modification is currently recognized as a major driver of RNA function that maintains cancer cell homeostasis. Long non-coding (Lnc) RNAs control cell proliferation and play an important role in the occurrence and progression of colorectal cancer (CRC). ZCCHC4 is a newly discovered m6A methyltransferase whose role and mechanism in tumors have not yet been elucidated. Methods The EpiQuik m6A RNA methylation kit was used to detect the level of total RNA m6A in six types of digestive tract tumors. The Kaplan-Meier method and receiver operating characteristic curve were used to evaluate the prognostic and diagnostic value of the newly discovered m6A methyltransferase, ZCCHC4, in CRC. The effects on CRC growth in vitro and in vivo were studied using gain- and loss-of-function experiments. The epigenetic mechanisms underlying ZCCHC4 upregulation in CRC were studied using RIP, MeRIP-seq, RNA pull-down, and animal experiments. Results We reported that the ZCCHC4-LncRNAGHRLOS-KDM5D axis regulates the growth of CRC in vitro and in vivo. We found that ZCCHC4 was upregulated in primary CRC samples and could predict adverse clinical outcomes in patients with CRC. Mechanistically, ZCCHC4 downregulated LncRNAGHRLOS to promote CRC tumorigenesis. As a downstream molecule of LncRNAGHRLOS, KDM5D directly controls CRC cell proliferation, migration, and invasion. Conclusion This study suggests that the ZCCHC4 axis contributes to the tumorigenesis and progression of CRC and that ZCCHC4 may be a potential biomarker for this malignancy.

AbstractThe Fushun West Open-pit Mine, recognized as Asia’s largest open-pit coal mine, transitioned to a closure management phase following the cessation of operations in 2019. This study presents a quantitative analysis of the water inflow sources by meticulously reviewing historical data on the mine’s drainage system and the hydrogeological conditions of the mining area. A numerical model representing the unsaturated-saturated groundwater dynamics was constructed to illustrate the spatial distribution of the groundwater flow. Employing the water storage analysis module within the WebGIS system, projections were made regarding the natural water accumulation process at varying water levels. The results indicate that, under natural conditions, an estimated 48 years would be required to reach a water level elevation of 50 m. However, this timeframe could be drastically reduced to approximately 3.3 years by implementing an accelerated filling strategy that channels water from the Hun River. Numerical simulations elucidate the failure mechanism of the water-sensitive slope on the northern bank during the water storage process, as well as the potential impact on the slopes above the water level. This comprehensive approach provides critical insights for managing decommissioned open-pit mines and optimizing water storage schemes.

Graph Neural Networks (GNNs) have demonstrated significant potential as powerful tools for handling graph data in various fields. However, traditional GNNs often encounter limitations in information capture and generalization when dealing with complex and high-order graph structures. Concurrently, the sparse labeling phenomenon in graph data poses challenges in practical applications. To address these issues, we propose a novel graph contrastive learning method, TP-GCL, based on a tensor perspective. The objective is to overcome the limitations of traditional GNNs in modeling complex structures and addressing the issue of sparse labels. Firstly, we transform ordinary graphs into hypergraphs through clique expansion and employ high-order adjacency tensors to represent hypergraphs, aiming to comprehensively capture their complex structural information. Secondly, we introduce a contrastive learning framework, using the original graph as the anchor, to further explore the differences and similarities between the anchor graph and the tensorized hypergraph. This process effectively extracts crucial structural features from graph data. Experimental results demonstrate that TP-GCL achieves significant performance improvements compared to baseline methods across multiple public datasets, particularly showcasing enhanced generalization capabilities and effectiveness in handling complex graph structures and sparse labeled data.

The distributed permutation flowshop scheduling is a critical issue in various industries, involving jobs allocation and scheduling among multiple flowshops. This paper extends the research to explore the Distributed Mixed No-Wait Permutation Flowshop Scheduling Problems (DMNWPFSP) with minimizing makespan. The innovation lies in an optimized mathematical model, hybrid heuristic algorithms, an improved iterated greedy algorithm (IIG), and high-quality solutions. Extensive experimental results demonstrate the effectiveness and superiority of the proposed IIG in terms of scheduling quality, computational efficiency, and robustness compared to existing approaches. The outcomes of this work contribute to the field of distributed flowshop scheduling, providing valuable insights for practitioners seeking to enhance production efficiency and competitiveness.

Abstract Series of giant molecule acceptors DY, TY and QY with two, three and four small molecule acceptor subunits are synthesized by a stepwise synthetic method and used for systematically investigating the influence of subunit numbers on the structure-property relationship from small molecule acceptor YDT to giant molecule acceptors and to polymerized small molecule acceptor PY-IT. Among these acceptors-based devices, the TY-based film shows proper donor/acceptor phase separation, higher charge transfer state yield and longer charge transfer state lifetime. Combining with the highest electron mobility, more efficient exciton dissociation and lower charge carrier recombination properties, the TY-based device exhibits the highest power conversion efficiency of 16.32%. These results indicate that the subunit number in these acceptors has significant influence on their photovoltaic properties. This stepwise synthetic method of giant molecule acceptors will be beneficial to diversify their structures and promote their applications in high-efficiency and stable organic solar cells.

Abstract The present-day globalized economy and diverse market demands have compelled an increasing number of manufacturing enterprises to move toward the distributed manufacturing pattern and the model of multi-variety and small-lot. Taking these two factors into account, this study investigates an extension of the distributed hybrid flowshop scheduling problem (DHFSP), called the distributed hybrid flowshop scheduling problem with consistent sublots (DHFSP_CS). To tackle this problem, a mixed integer linear programming (MILP) model is developed as a preliminary step. The NP-hard nature of the problem necessitates the use of the iterated F-Race (I/F-Race) as the automated algorithm design (AAD) to compose a metaheuristic that requires minimal user intervention. The I/F-Race enables identifying the ideal values of numerical and categorical parameters within a promising algorithm framework. An extension of the collaborative variable neighborhood descent algorithm (ECVND) is utilized as the algorithm framework, which is modified by intensifying efforts on the critical factories. In consideration of the problem-specific characteristics and the solution encoding, the configurable solution initializations, configurable solution decoding strategies, and configurable collaborative operators are designed. Additionally, several neighborhood structures are specially designed. Extensive computational results on simulation instances and a real-world instance demonstrate that the automated algorithm conceived by the AAD outperforms the CPLEX and other state-of-the-art metaheuristics in addressing the DHFSP_CS.

The electromagnetic transient (EMT)-type impedance scanning methods conducted in positive sequence domain and dq-frame (p-scan and dq-scan, respectively) have been widely used for identifying inverter-based resource (IBR) instabilities. They obtain the sequence domain single-input single-output (sequence-SISO) and dq-frame multi-input multi-output (dq-MIMO) impedance models of an IBR, respectively. The dq-MIMO impedance-based stability assessment (IBSA) is more accurate compared to the sequence-SISO IBSA as it considers the mirror frequency effect (MFE). However, unlike the sequence-SISO, the dq-MIMO IBSA cannot differentiate the resonance frequency from its mirror frequency, because the dynamics in dq-frame incorporate both the positive and negative sequence impedances of IBR. This paper proposes a new IBSA scheme to eliminate this shortcoming. First, a dq-MIMO IBSA is carried out to obtain the accurate dq-frame resonance frequency and stability margin. Then a sequence-SISO IBSA is conducted to determine the phase domain resonance frequency. The sequence-SISO impedance models are transformed from the dq-MIMO model. The proposed scheme has lower computational costs than the existing dq-MIMO IBSA methods. The effectiveness of the proposed scheme is validated on a test system incorporating full-size converter-based wind park (FSC-based WP). This paper also demonstrates the possibility of weak grid instability occurrence in supersynchronous frequency range.

AIM: To investigate the effect of modified Chufeng Yisun Decoction on ocular surface inflammation after pterygium surgery.METHODS: A total of 60 patients(60 eyes)with primary pterygium who underwent pterygium surgery were randomly divided into control group and study group, with 30 cases(30 eyes)in each group. In the control group, patients were treated with pranoprofen eye drops, tobramycin dexamethasone eye drops, and deproteinized calf blood extract eye gel after the surgery. In the study group, patients were treated by oral modified Chufeng Yisun Decoction in addition to the treatments in the control group. The changes of ocular irritation symptoms, ocular inflammatory signs, tear interleukin 6(IL-6)levels, and tear ferning test(TFT)of patients in the two groups were assessed.RESULTS: The visual analogue scale(VAS)in patients of both groups was significantly lower at 2d and 1wk after the surgery than that at 1d after the surgery(all P

IntroductionStatistical methods such as empirical orthogonal functions (EOFs) are often used to model the sound speed profile (SSP). However, their statistical nature often leads to the sample dependence and physical fuzziness.MethodThis study proposes a technique for modeling the SSP from the perspective of ocean dynamics. It employs the ocean normal mode, which is the mode of fluid particles motion, to deduce perturbations in the SSP, which is called the ocean mode basis (OMB).ResultThe results of SSP reconstruction of in-situ samples showed that a few leading orders of the OMB can provide a compact representation of the SSP. Oscillations of the contours and gradient of the sound speed in thermocline were analyzed by using the first two orders of the projection coefficients of the relationship between the OMB and the baroclinic mode. As a physical model, this technique can also be used to characterize the dynamics of internal solitary waves. Furthermore, the OMB derived from archival date was used for SSP inversion. The results showed that the OMB can reconstruct SSP of a reasonable resolution without requiring in-situ samples.DiscussionCompared with statistical models, the OMB can better explain the ocean dynamics underlying variations in the SSP while requiring fewer samples.

Existing graph contrastive learning methods often rely on differences in node features within subgraphs, lacking effective capture of the global structural information of the graph. To address this issue, we propose a novel graph contrastive learning method, Line Graph Contrastive Learning (LineGCL), aimed at overcoming the deficiencies in understanding the overall characteristics and topological structures of graphs found in current methods. LineGCL utilizes the characteristics of line graphs to transform the original graph into corresponding line graphs, presenting edge information in the form of node features, effectively capturing the global structural information of the graph. Additionally, LineGCL adopts a novel multi-view contrastive learning approach, characterizing the similarity and differences between the original graph and line graph comprehensively from the perspectives of node features and spectral features, further enhancing the model's understanding and learning capabilities of the global structure of graphs. Experimental results on public datasets demonstrate that LineGCL outperforms baseline models, achieving performance improvements ranging from 0.5% to 28.5%. These results validate the effectiveness and superiority of LineGCL in capturing and understanding global structural information, surpassing the limitations of baseline methods in graph contrastive learning.

The positive effects of afforestation in karst rocky desertification areas are often limited by soil nitrogen (N) availability. However, how plant N limitation evolves in response to prolonged afforestation as well as the mechanisms underlying plant N limitation and soil N availability are poorly understood. In this study, plant leaves and soil samples were collected from cropland, Dodonaea viscosa plantations 10, 20 and 40 years after their establishment on abandoned cropland in a karst rocky desertification area. The natural succession of shrubland served as the control. Foliar N/phosphorus (P) stoichiometry was used to evaluate plant N limitation, and the N concentration and δ15N value of foliar and soil were measured to evaluate the changes in soil N availability. Soil N transformation rates were also determined, using 15N tracing technique to elucidate the mechanism underlying soil inorganic N availability. The plant community-level foliar N/P ratio (13.5) was lower than 14 following 10-y afforestation, indicating that plant growth is predominantly N limited. With the prolonged afforestation, the plant community-level foliar N/P ratio increased to 14.0–15.5, suggesting decreased plant N limitation. This could be attributed to increased soil N availability confirmed by the raises in the N concentration and δ15N of plant community-level foliar and soil δ15N with prolonged afforestation. Compared to cropland, D. viscosa afforestation increased the soil inorganic N supply capacity, by stimulating organic N mineralization, heterotrophic nitrification and the release of adsorbed ammonium, more obviously with prolonged afforestation. The rates of mineralization, heterotrophic nitrification and the release of adsorbed ammonium correlated significantly and positively with the plant community-level foliar N concentration, N/P ratio, and δ15N, indicating that a larger soil inorganic N supply alleviates plant N limitation. This effect can be attributed to the increases in organic matter content, bacterial and fungal abundances and soil structure improvement following afforestation, all of which facilitate mineralization and heterotrophic nitrification. However, plant N limitation after 40 years of afforestation still exists, suggesting that monoculture afforestation may need to be adapted to maximize soil N availability and to alleviate plant N limitation in karst rocky desertification areas.

IntroductionExisting methods primarily focus on earth acoustic parameters inversion under specific layered structures. However, they face challenges with experimental data from unknown seabed stratification, hindering accurate parameter inversion.MethodsTo address this, a novel algorithm combines Back Propagation Neural Network (BPNN) for distinguishing seabed stratification and inverting acoustic parameters. Simulated sound pressure data disturb seabed parameters as input, enabling feature recognition for training the neural network inversion model. Acoustic parameters are then estimated under identified stratification using the sound field model.ResultsThe inversion model is validated using simulation and pool shrinkage data. Results show the neural network model effectively stratifies simulation and experimental data, providing accurate inversion results for acoustic parameters corresponding to distinct layers.DiscussionThe neural network model's accuracy and practicality are confirmed through hierarchical judgment of scale test data and acoustic parameter inversion. This approach introduces a new perspective for shallow sea acoustic parameter inversion, offering a promising application scenario.

Copper (Cu) is a key cofactor in ammonia monooxygenase functioning responsible for the first step of nitrification, but its excess availability impairs soil microbial functions and plant growth. Yet, the impact of Cu on nitrogen (N) cycling and process-related variables in cropland soils remains unexplored globally. Through a meta-analysis of 1209-paired and 319-single observations from 94 publications, we found that Cu (Cu addition or Cu-polluted soil) reduced soil potential nitrification by 33.8% and nitrite content by 73.5% due to reduced soil enzyme activities of nitrification and urease, microbial biomass content, and ammonia oxidizing archaea abundance. The response ratio of potential nitrification decreased with increasing Cu concentration, soil total N, and clay content. We further noted that soil potential nitrification inhibited by 46.5% only when Cu concentration was higher than 150 mg kg−1, while low Cu concentration (less than 150 mg kg−1) stimulated soil nitrate by 99.0%. Increasing initial soil Cu content stimulated gross N mineralization rate due to increased soil organic carbon and total N, but inhibited gross nitrification rate, which ultimately stimulated gross N immobilization rate as a result of increased the residence time of ammonium. This resulted in a lower ratio of gross nitrification rate to gross N immobilization rate, implying a lower potential risk of N loss as evidenced by decreased nitrous oxide emissions with increasing initial soil Cu content. Our analysis offers initial global evidence that Cu has an important role in controlling soil N availability and loss through its effect on N production and consumption.

The carbon nanotube (CNT)-polyetherimide (PEI) was successfully grafted onto the surface of carbon fibers (CF) through chemical grafting method for constructing a CF-g-CNT reinforcing phase. Results show the construction of CF-g-CNT fiber can effectively improve the interface, impact resistance and bending properties of the composites. Considering the effect of strengthening phase on the mechanical properties of composites, the interfacial shear strength, impact strength, flexural modulus and flexural strength of CF-g-CNT/BMI composites respectively increase by 48.8%, 10.8%, 5.2% and 14.6%, companed with those of CF/BMI. In addition, the interfacial shear strength, impact strength, flexural modulus and flexural strength of CF-g-CNT/BMI-PEI-CNT composites are 56.9%, 27.1%, 12.5% and 16.1% higher than those of CF/BMI-PEI-CNT, respectively. The interfacial shear strength, impact strength, flexural modulus and flexural strength of CF-g-CNT/BMI-PEI-CNT composites increase by 57.7%, 33.7%, 20.0% and 23.7% compared with CF/BMI. The CNT-PEI in CF-g-CNT can effectively change the interface composition and change the expansion path of horizontal stress or vertical stress at the interface, which is beneficial to disperse the stress concentration as well as improve the mechanical properties of the composites.

Abstract Recent studies have shown that the high incidence and low cure rate of hepatocellular carcinoma (HCC) have not improved significantly. Surgery and liver transplantation are the mainstays of prolonging the survival of HCC patients. However, the surgical resection rate of HCC patients is very low, and even after radical surgical resection, the recurrence rate at 5 years postoperatively remains high and the prognosis is very poor, so more treatment options are urgently needed. Increasing evidence suggests that cellular senescence is not only related to cancer development but may also be one of its primary driving factors. We aimed to establish a prognostic signature of senescence-associated genes to predict the prognosis and therapeutic response of HCC patients. The aim of this study was to develop a risk model associated with cellular senescence and to search for potential strategies to treat HCC. We divided HCC patients into two clusters and identified differentially expressed genes (DEGs) between clusters. In this study, low-risk patients had a better prognosis, higher levels of immune cell infiltration, and better efficacy to fluorouracil, Paclitaxel and Cytarabine chemotherapy compared to high-risk patients. To further identify potential biomarkers for HCC, we further validated the expression levels of the four signature genes in HCC and neighbouring normal tissues by in vitro experiments. In conclusion, we identified and constructed a relevant prognostic signature, which performed well in predicting the survival and treatment response of HCC patients. This helps to differentiate between low-score and high-risk HCC, and the results may contribute to precise treatment protocols in clinical practice.

Abstract Background Drug resistance is a main factor affecting the chemotherapy efficacy of gastric cancer (GC), in which meiosis plays an important role. Therefore, it is urgent to explore the effect of meiosis related genes on chemotherapy resistance. Methods The expression of meiotic nuclear divisions 1 (MND1) in GC was detected by using TCGA and clinical specimens. In vitro and in vivo assays were used to investigate the effects of MND1. The molecular mechanism was determined using luciferase reporter assay, CO-IP and mass spectrometry (MS). Results Through bioinformatics, we found that MND1 was highly expressed in platinum-resistant samples. In vitro experiments showed that interference of MND1 significantly inhibited the progression of GC and increased the sensitivity to oxaliplatin. MND1 was significantly higher in 159 GC tissues in comparison with the matched adjacent normal tissues. In addition, overexpression of MND1 was associated with worse survival, advanced TNM stage, and lower pathological grade in patients with GC. Further investigation revealed that forkhead box protein A1 (FOXA1) directly binds to the promoter of MND1 to inhibit its transcription. CO-IP and MS assays showed that MND1 was coexpressed with transketolase (TKT). In addition,TKT activated the PI3K/AKT signaling axis and enhanced the glucose uptake and lactate production in GC cells. Conclusions Our results confirm that FOXA1 inhibits the expression of MND1, which can directly bind to TKT to promote GC progression and reduce oxaliplatin sensitivity through the PI3K/AKT signaling pathway.

Impedance-based stability analysis (IBSA) is an effective method to identify subsynchronous interaction (SSI) problem between the inverter-based resources (IBRs) and series compensated or weakly tied AC grids. The electromagnetic transient (EMT) level positive sequence and dq-frame frequency scanning methods (p-scan and dq-scan, respectively) are used to obtain the sequence single-input single-output (SISO) and dq multi-input multi-output (MIMO) impedance of IBRs, respectively. The dq MIMO impedance usage in IBSA provides more accurate results compared to the sequence SISO impedance. This paper proposes an EMT-level αβ-frame frequency scanning method (αβ-scan) to obtain the αβMIMO impedance and its usage in IBSA. The αβ-scan requires significantly less time compared to dq-scan for the convergence of MIMO IBR impedance representation and offers similar accuracy with dq-scan in IBSA. The accuracy of the proposed αβMIMO IBSA is validated by comparing with dq MIMO IBSA and EMT simulations on series capacitor SSI cases with different type IBRs (Doubly-fed induction generator (DFIG)-based wind park (WP) and full-scale converter (FSC)-based WP). This paper also uses a multivariable structure function(MSF)-based method for the first time in IBSA of SSI to achieve Bode plot-based analysis for providing better visualized presentation of resonance frequency and stability margins compared to generalized Nyquist criterion.

Abstract Link prediction is a widely adopted method for extracting valuable data insights from graphs, primarily aimed at predicting interactions between two nodes. However, there are not only pairwise interactions but also multivariate interactions in real life. For example, reactions between multiple proteins, multiple compounds, and multiple metabolites cannot be mined effectively using link prediction. A hypergraph is a higher-order network composed of nodes and hyperedges, where hyperedges can be composed of multiple nodes, and can be used to depict multivariate interactions. The interactions between multiple nodes can be predicted by hyperlink prediction methods. Since hyperlink prediction requires predicting the interactions between multiple nodes, it makes the study of hyperlink prediction much more complicated than that of other complex networks, thus resulting in relatively limited attention being devoted to this field. The existing hyperlink prediction can only predict potential hyperlinks in uniform hypergraphs, or need to predict hyperlinks based on the candidate hyperlink sets, or only study hyperlink prediction for undirected hypergraphs. Therefore, a hyperlink prediction framework for predicting multivariate interactions based on graph representation learning is proposed to solve the above problems, and then the framework is extended to directed hyperlink prediction (e.g., directed metabolic reaction networks). Furthermore, any size of hyperedges can be predicted by the proposed hyperlink prediction algorithm framework, whose performance is not affected by the number of nodes or the number of hyperedges. Finally, the proposed framework is applied to both the biological metabolic reaction network and the organic chemical reaction network, and experimental analysis has demonstrated that the hyperlinks can be predicted efficiently by the proposed hyperlink prediction framework with relatively low time complexity, and the prediction performance has been improved by up to 40% compared with the baselines.

Abstract Cardiovascular diseases (CVDs) continue to exert a significant impact on global mortality rates, encompassing conditions like pulmonary arterial hypertension (PAH), atherosclerosis (AS), and myocardial infarction (MI). Oxidative stress (OS) plays a crucial role in the pathogenesis and advancement of CVDs, highlighting its significance as a contributing factor. Maintaining an equilibrium between reactive oxygen species (ROS) and antioxidant systems not only aids in mitigating oxidative stress but also confers protective benefits on cardiac health. Herbal monomers can inhibit OS in CVDs by activating multiple signaling pathways, such as increasing the activity of endogenous antioxidant systems and decreasing the level of ROS expression. Given the actions of herbal monomers to significantly protect the normal function of the heart and reduce the damage caused by OS to the organism. Hence, it is imperative to recognize the significance of herbal monomers as prospective therapeutic interventions for mitigating oxidative damage in CVDs. This paper aims to comprehensively review the origins and mechanisms underlying OS, elucidate the intricate association between CVDs and OS, and explore the therapeutic potential of antioxidant treatment utilizing herbal monomers. Furthermore, particular emphasis will be placed on examining the cardioprotective effects of herbal monomers by evaluating their impact on cardiac signaling pathways subsequent to treatment. Graphical Abstract

Abstract Background From January 2020 to December 2022, China implemented “First-level-response”, “Normalized-control” and “Dynamic-COVID-zero” to block the COVID-19 epidemic; however, the immediate and long-term impact of three strategies on other infectious diseases and the difference in their impact is currently unknown. We aim to provide a more comprehensive understanding of the impact of non-pharmacological interventions (NPIs) on infectious diseases in China. Methods We collected data on the monthly case count of infectious diseases in China from January 2015 to July 2022. After considering long-term trends using the Cox-Stuart test, we performed the two ratio Z tests to preliminary analyze the impact of three strategies on infectious diseases. Next, we used a multistage interrupted-time-series analysis fitted by the Poisson regression to evaluate and compare the immediate and long-term impact of three strategies on infectious diseases in China. Results Compared to before COVID-19, the incidence of almost all infectious diseases decreased immediately at stages 1, 2, and 3; meanwhile, the slope in the incidence of many infectious diseases also decreased at the three stages. However, the slope in the incidence of all sexually transmitted diseases increased at stage 1, the slope in the incidence of all gastrointestinal infectious diseases increased at stage 2, and the slope in the incidence of some diseases such as pertussis, influenza, and brucellosis increased at stage 3. The immediate and long-term limiting effects of “Normalized-control” on respiratory-transmitted diseases were weaker than “First-level-response” and the long-term limiting effects of “Dynamic-COVID-zero” on pertussis, influenza, and hydatid disease were weaker than “Normalized-control”. Conclusions Three COVID-19 control strategies in China have immediate and long-term limiting effects on many infectious diseases, but there are differences in their limiting effects. Evidence from this study shows that pertussis, influenza, brucellosis, and hydatid disease began to recover at stage 3, and relaxation of NPIs may lead to the resurgence of respiratory-transmitted diseases and vector-borne diseases.

Abstract Remote monitoring systems has emerged to automate public services, where Internet of Things (IoT) devices are deployed to collect and relay streams of status updates to a remote control centre. The freshness of collected data is of critical importance to system performance, which can be quantified by the concept of age of information (AoI). To obtain timely perception of the monitored area, each sensor tends to sample status updates at the maximum frequency, which may lead to device drop‐outs due to limited battery capacity. Simultaneous wireless information and power transfer (SWIPT) is considered as a promising technology to prolong network lifetime. In this paper, a SWIPT‐enabled two‐hop relay network, where a relay node uses power splitting protocol to assist data transmissions from multiple source nodes to the destination is considered. The impact of power splitting coefficients, data arrival pattern and time‐varying channel conditions on the averaged age performance and expected lifetime of the system is theoretically analysed. Moreover, a lightweight relay strategy which selectively forward packets based on a reward function consisting of energy level at relay node and expected age reduction is developed. Simulation results show that the proposed strategy outperforms existing schemes in collecting status updates in a timely and energy‐efficient manner.

Abstract Stroke has caused tremendous social stress worldwide, yet despite decades of research and development of new stroke drugs, most have failed and rt-PA (Recombinant tissue plasminogen activator) is still the accepted treatment for ischemic stroke. the complexity of the stroke mechanism has led to unsatisfactory efficacy of most drugs in clinical trials, indicating that there are still many gaps in our understanding of stroke. Pyroptosis is a programmed cell death (PCD) with inflammatory properties and are thought to be closely associated with stroke. Pyroptosis is regulated by the GSDMD of the gasdermin family, which when cleaved by Caspase-1/Caspase-11 into N-GSDMD with pore-forming activity can bind to the plasma membrane to form small 10–20 nm pores, which would allow the release of inflammatory factors IL-18 and IL-1β before cell rupture, greatly exacerbating the inflammatory response. The pyroptosis occurs mainly in the border zone of cerebral infarction, and glial cells, neuronal cells and brain microvascular endothelial cells (BMECs) all undergo pyroptosis after stroke, which largely exacerbates the breakdown of the blood-brain barrier (BBB) and thus aggravates brain injury. Therefore, pyroptosis may be a good direction for the treatment of stroke. In this review, we focus on the latest mechanisms of action of pyroptosis and the process by which pyroptosis regulates stroke development. We also suggest potential therapeutic stroke drugs that target the pyroptosis pathway, providing additional therapeutic strategies for the clinical management of stroke. The role of pyroptosis after stroke. After stroke, microglia first rush to the damaged area and polarize into M1 and M2 types. Under the influence of various stimuli, microglia undergo pyroptosis, release pro-inflammatory factors, and are converted to the M1 type; astrocytes and neuronal cells also undergo pyroptosis under the stimulation of various pro-inflammatory factors, leading to astrocyte death due to increased osmotic pressure in the membrane, resulting in water absorption and swelling until rupture. BMECs, the main structural component of the BBB, also undergo pyroptosis when stimulated by pro-inflammatory factors released from microglia and astrocytes, leading to the destruction of the structural integrity of the BBB, ultimately causing more severe brain damage. In addition, GSDMD in neutrophils mainly mediate the release of NETs rather than pyroptosis, which also aggravates brain injury. IL-10=interleukin-10; TGF-β = transforming growth factor-β; IL-18=interleukin-18; IL-1β = interleukin-1β; TNF-α = tumor necrosis factor-α; iNOS=induced nitrogen monoxide synthase; MMPs=Matrix metalloproteinases; GSDMD = gasdermin D; BMECs=brain microvascular endothelial cells; BBB = blood-brain barrier.

A subcutaneous abscess of the penis is a rare condition. It can be idiopathic or have an underlying cause, such as intracavernous injection therapy, foreign body, dilated perineal abscess, abnormal erection, or trauma. Clinical signs are mainly swelling in the penis, penile pain, and swelling. Conventional treatment is primarily surgical incision and drainage, followed by systemic antibiotic therapy. In recent years, with the development of medical technology, minimally invasive interventions and less invasive techniques, such as ultrasound-guided aspiration, are being developed. This article aims to report a case of ultrasound-guided successful diagnosis and treatment of an aseptic idiopathic subcutaneous abscess at the root of the penis and to review the literature on penile abscesses. The patient, a 61-year-old male, underwent ultrasound-guided puncture and drainage using a coaxial aspiration/flushing technique in combination with antibiotics to treat this rare urinary tract condition. The patient recovered well postoperatively and was discharged 3 days later. At a 2-week postoperative follow-up, an ultrasound showed a marked reduction in the penile abscess mass.

Cosmic hydrogen reionization and cosmic production of the first metals are major phase transitions of the Universe occurring during the first billion years after the Big Bang; however, these are still underexplored observationally. Using the JWST/NIRSpec prism spectroscopy, we report the discovery of a sub- L _* galaxy at z _spec = 8.1623 ± 0.0007, dubbed RX J2129–z8He II , via the detection of a series of strong rest-frame UV/optical nebular emission lines and the clear Lyman break. RX J2129–z8He II shows a pronounced UV continuum with an extremely steep (i.e., blue) spectral slope of $\beta =-{2.53}_{-0.07}^{+0.06}$ , the steepest among all spectroscopically confirmed galaxies at z _spec ≳ 7, in support of its very hard ionizing spectrum that could lead to a significant leakage of its ionizing flux. Therefore, RX J2129–z8He II is representative of the key galaxy population driving the cosmic reionization. More importantly, we detect a strong He II λ 1640 emission line in its spectrum, one of the highest redshifts at which such a line is robustly detected. Its high rest-frame equivalent width (EW = 21 ± 4 Å) and extreme flux ratios with respect to UV metal and Balmer lines raise the possibility that part of RX J2129–z8He II ’s stellar population could be Pop III (Pop III)-like. Through careful photoionization modeling, we show that the physically calibrated phenomenological models of the ionizing spectra of Pop III stars with strong mass loss can successfully reproduce the emission line flux ratios observed in RX J2129–z8He II . Assuming the Eddington limit, the total mass of the Pop III stars within this system is estimated to be 7.8 ± 1.4 × 10 ^5 M _⊙ . To date, this galaxy presents the most compelling case in the early Universe where trace Pop III stars might coexist with metal-enriched populations.

Background: Diabetic foot ulcers (DFUs) are among the most prevalent and dangerous complications of diabetes. Angiogenesis is pivotal for wound healing; however, its role in the chronic wound healing process in DFU requires further investigation. We aimed to investigate the pathogenic processes of angiogenesis in DFU from a molecular biology standpoint and to offer insightful information about DFU prevention and therapy. Methods: Differential gene and weighted gene co-expression network analyses (WGCNA) were employed to screen for genes related to DFU using the downloaded and collated GSES147890 datasets. With the goal of identifying hub genes, an interaction among proteins (PPI) network was constructed, and enrichment analysis was carried out. Utilizing a variety of machine learning techniques, including Boruta, Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), we were able to determine which hub genes most strongly correspond to DFU. This allowed us to create an ideally suited DFU forecasting model that was validated via an external dataset. Finally, by merging 36 angiogenesis-related genes (ARGs) and machine learning models, we identified the genes involved in DFU-related angiogenesis. Results: By merging 260 genes located in the green module and 59 differentially expressed genes (DEGs), 35 candidate genes highly associated with DFU were found for more investigation. 35 candidate genes were enriched in epidermal growth factor receptor binding, nuclear division regulation, fluid shear stress, atherosclerosis, and negative regulation of chromosomal structure for the enrichment study. Fifteen hub genes were found with the aid of the CytoHubba plug. The LASSO method scored better in terms of prediction performance (GSE134341) (LASSO:0.89, SVM:0.65, Boruta:0.66) based on the validation of the external datasets. We identified thrombomodulin (THBD) as a key target gene that potentially regulates angiogenesis during DFU development. Based on the external validation dataset (GSE80178 and GSE29221), receiver operating characteristic (ROC) curves with higher efficiency were generated to confirm the potential of THBD as a biomarker of angiogenesis in DFU. Furthermore supporting this finding were the results of Western blot and real-time quantitative polymerase chain reaction (RT-qPCR), which showed decreased THBD expression in human umbilical vein endothelial cells (HUVECs) cultivated under high glucose. Conclusions: The findings implicate that THBD may influence DFU progression as a potential target for regulating angiogenesis, providing a valuable direction for future studies.

The prevention of diabetic foot ulcers (DFU) precedes treatment, in that early prevention significantly reduces the incidence of foot ulcers. The main objectives of this study were to examine the current prevalence of proactive foot ulcer examinations among diabetic patients and analyze influencing factors, in order to provide a scientific reference for the prevention of DFU in diabetic patients. The National Health and Nutrition Examination Survey (NHANES) 2011–2018 (n = 1278) data were utilized in this cross-sectional study. The dependent variable was whether patients underwent self-initiated foot ulcer inspections; risk factors that may lead to foot ulcers were included as independent variables. To explore the connection between the patient’s subjective motivation to inspect foot ulcers and risk variables, the weighted logistic regression model was further carried out. Among all risk factors, race, body mass index (BMI) and hypertension were statistically significant between whether patients were examined for foot ulcers or not. In the fully adjusted logistic regression model, only hypertension was positively correlated with diabetic patient-initiated examination for foot ulcers. This study suggests that there is still room for improvement in the knowledge and behavior of diabetic patients to be proactive in preventing DFU. Health care and community workers should conduct targeted training on diabetic foot prevention to reduce and prevent DFU by reinforcing knowledge to build positive attitudes and drive preventive behavior change.

Abstract With the rapid progress of dark matter direct detection experiments, the attractiveness of the popular bino-dominated dark matter in economical supersymmetric theories is fading. As an alternative, the singlino-dominated dark matter in general Next-to-Minimal Supersymmetric Standard Model (NMSSM) is paying due attention. This scenario has the following distinct characteristics: free from the tadpole problem and the domain-wall problem of the NMSSM with a Z 3-symmetry, predicting more stable vacuum states than the Z 3-NMSSM, capable of forming an economical secluded dark matter sector to yield the dark matter experimental results naturally, and readily weaken the restrictions from the LHC search for SUSY. Consequently, it can explain the muon g-2 anomaly in broad parameter space that agrees with various experimental results while simultaneously breaking the electroweak symmetry naturally. In this study, we show in detail how the scenario coincides with the experiments, such as the SUSY search at the LHC, the dark matter search by the LZ experiment, and the improved measurement of the muon g-2. We provide a simple and clear picture of the physics inherent in the general NMSSM.

Reducing energy loss of sub-cells is critical for high performance tandem organic solar cells. Here, the authors design and synthesize an ultra-narrow bandgap acceptor through replacement of terminal thiophene by selenophene in the central fused ring, achieving efficiency of 19% for tandem cells.

Abstract Pulmonary hypertension (PH) was a cardiovascular disease with high morbidity and mortality. PH was a chronic disease with complicated pathogenesis and uncontrollable factors. PH was divided into five groups according to its pathogenesis and clinical manifestations. Although the treatment and diagnosis of PH has made great progress in the past ten years. However, the diagnosis and prognosis of the PAH had a great contrast, which was not conducive to the diagnosis and treatment of PH. If not treated properly, it will lead to right ventricular failure or even death. Therefore, it was necessary to explore the pathogenesis of PH. The problem we urgently need to solve was to find and develop drugs for the treatment of PH. We reviewed the PH articles in the past 10 years or so as well as systematically summarized the recent advance. We summarized the latest research on the key regulatory factors (pyroptosis, apoptosis, necroptosis, ferroptosis, and endoplasmic reticulum stress) involved in PH. To provide theoretical basis and basis for finding new therapeutic targets and research directions of PH.

Many croplands in the tropics of China have been converted over the last decades into areca nut plantations due to their high economic returns. This land-use transition was accompanied by changes in agricultural practices such as soil moisture regimes and fertilizer inputs, which may affect soil organic carbon (SOC) and its fractions, especially in tropical soils with low fertility and high nitrogen loss. Yet, how the time since land-use transition from rice paddy cultivation to areca nut plantations affects soil carbon dynamics and their underlying mechanisms in the tropics of China remains elusive. Here, areca nut plantation soils with different ages (2, 5, 10, 14, and 17 years) and paddy fields in the tropical region of China were investigated. The study result indicates that the contents of dissolved organic carbon (DOC), particulate organic carbon (POC), easily oxidized organic carbon (EOC), light organic carbon (LFOC), and microbial biomass carbon (MBC) decreased significantly with increased time since land-use transition from rice paddy cultivation to areca nut plantations. Similarly, the ratios of DOC/SOC, MBC/SOC, POC/SOC, LFOC/SOC, and EOC/SOC decreased significantly with increased time since land-use transition. Compared with the paddy soil, the carbon pool management index decreased by 36.6–76.7% under the areca nut plantations, concluding that increasing the time since land-use transition from rice paddy cultivation to areca nut plantations with high application rates of chemical fertilizers resulted in reduced soil active carbon fractions and SOC supply capacity. Therefore, agricultural practices such as the use of organic fertilizers should be applied to improve the soil’s ability to supply organic carbon in managed plantation ecosystems in the tropics of China.

Habitat suitability analysis is essential in habitat and species conservation. Anatidae are known for their migratory behaviour, high population density, and wide distribution range. Understanding their habitat utilzation and influencing factors is crucial in targeted conservation and management. In this study, we collected Anatidae diversity data, including the number of species, through field surveys from October 2021 to March 2022 and thirty habitat variables through an online database in Anhui Province, China. By using MaxEnt, we simulated the habitat suitability of twenty-one Anatidae species, revealing potential distribution sites in Anhui Province. Generalized linear mixed models (GLMM) were employed to identify factors affecting the distribution of geese and ducks. The results showed that high-suitability habitats were predominantly located in the large lakes of the Yangtze River floodplain. The GLMM analysis showed significant correlations between Anatidae richness and altitude, distribution of farmland, and human footprint. In addition, ducks were more sensitive to the human interference factor than geese. In summary, the lakes in the Yangtze River floodplain emerged as the most important Anatidae habitats in Anhui Province due to their abundant wetland resources, flat terrain, and high distribution of farmlands. These findings provide a scientific basis for the development of relevant conservation strategies and measures, aiding in wildlife epidemic monitoring, prevention, and control.

Although cellular metabolic states have been shown to modulate bacterial susceptibility to antibiotics, the interaction between glutamate (Glu) and chloramphenicol (CAP) resistance remains unclear because of the specificity of antibiotics and bacteria. We found that the level of Glu was upregulated in the CAP-resistant strain of Edwardsiella tarda according to a comparative metabolomics approach based on LC–MS/MS. Furthermore, we verified that exogenous metabolites related to Glu, the tricarboxylic acid (TCA) cycle, and glutathione (GSH) metabolism could promote CAP resistance in survival assays. If GSH metabolism or the TCA cycle is inhibited by L-buthionine sulfoximine or propanedioic acid, the promotion of CAP resistance by Glu in the corresponding pathway disappears. According to metabolomic analysis, exogenous Glu could change pantothenate metabolism, affecting GSH biosynthesis and the TCA cycle. These results showed that the glutamate-pantothenate pathway could promote CAP resistance by being involved in the synthesis of GSH, entering the TCA cycle by direct deamination, or indirectly affecting the metabolism of the two pathways by pantothenate. These results extend our knowledge of the effect of Glu on antibiotic resistance and suggest that the potential effect, which may aggravate antibiotic resistance, should be considered before Glu and GSH administration in the clinic.

We demonstrate improved performance of quantum dot solar cells (QDSCs) by type-II InAs/GaAsSb structure. With a moderate Sb composition of 18% and high quality QDs, a high efficiency of 17.31% under AM1.5 G illumination is achieved, showing an improvement of 11.25% in efficiency relative to type-I InAs/InGaAs QDSC. This improvement can be attributed to a high fill factor (FF) of 72.37% compared to 63% of the latter because the type-II structure effectively suppresses carrier recombination losses in QDs. As Sb composition increases to 24%, the FF maintains at a high level of 72.67%, but the efficiency drops to 17% because the elevation of valence band (VB) in GaAsSb capping layer further enhances the hole confinement. And the confinement reduces external quantum efficiency (EQE) and short-circuit current density (Jsc). These results prove the potential of improving efficiency of QDSCs by type-II structure.

The carbon dioxide electroreduction reaction (CO2RR) represents a sustainable way to store intermittent renewable energy in a manner that generates virtually zero net emissions, yet the energy efficiency remains a significant bottleneck due to its sluggish kinetics and complex reaction pathways. There is a strong demand for highly efficient electrocatalysts that can achieve high energy and Faradaic efficiency, as well as rapid conversion. Among various developed CO2RR catalysts, nickel-based materials have garnered increasing attention due to their outstanding performance and low cost. In this review, the relevant CO2RR mechanisms are firstly discussed in detail. Following this, several typical Ni-based catalysts including Ni-based complexes catalysts, nanoparticles and alloys, Ni-based compounds, and atomically dispersed Ni catalysts are summarized. The preparation strategies for industrial level electrocatalysts are also highlighted in this review. Finally, the opportunities, challenges and future outlooks of CO2RR technology are summarized. This review introduces the recent advances and frontiers of nickel-based CO2RR catalysts, which enlightens the path for further exploration of highly efficient CO2RR electrocatalysts.

BackgroundDiabetic osteoporosis exhibits heterogeneity at the molecular level. Ferroptosis, a controlled form of cell death brought on by a buildup of lipid peroxidation, contributes to the onset and development of several illnesses. The aim was to explore the molecular subtypes associated with ferroptosis in diabetic osteoporosis at the molecular level and to further elucidate the potential molecular mechanisms.MethodsIntegrating the CTD, GeneCards, FerrDb databases, and the microarray data of GSE35958, we identified ferroptosis-related genes (FRGs) associated with diabetic osteoporosis. We applied unsupervised cluster analysis to divide the 42 osteoporosis samples from the GSE56814 microarray data into different subclusters based on FRGs. Subsequently, FRGs associated with two ferroptosis subclusters were obtained by combining database genes, module-related genes of WGCNA, and differentially expressed genes (DEGs). Eventually, the key genes from FRGs associated with diabetic osteoporosis were identified using the least absolute shrinkage and selection operator (LASSO), Boruta, support vector machine recursive feature elimination (SVM ­ RFE), and extreme gradient boosting (XGBoost) machine learning algorithms. Based on ROC curves of external datasets (GSE56815), the model’s efficiency was examined.ResultsWe identified 15 differentially expressed FRGs associated with diabetic osteoporosis. In osteoporosis, two distinct molecular clusters related to ferroptosis were found. The expression results and GSVA analysis indicated that 15 FRGs exhibited significantly different biological functions and pathway activities in the two ferroptosis subclusters. Therefore, we further identified 17 FRGs associated with diabetic osteoporosis between the two subclusters. The results of the comprehensive analysis of 17 FRGs demonstrated that these genes were heterogeneous and had a specific interaction between the two subclusters. Ultimately, the prediction model had a strong foundation and excellent AUC values (0.84 for LASSO, 0.84 for SVM ­ RFE, 0.82 for Boruta, and 0.81 for XGBoost). IDH1 is a common gene to all four algorithms thus being identified as a key gene with a high AUC value (AUC = 0.698).ConclusionsAs a ferroptosis regulator, IDH1 is able to distinguish between distinct molecular subtypes of diabetic osteoporosis, which may offer fresh perspectives on the pathogenesis of the disease’s clinical symptoms and prognostic heterogeneity.

This paper demonstrates the risk of a new control interaction phenomenon between a large-scale type-4 wind park (WP) and a 500 kV transmission grid in a super-synchronous frequency range. This study aims at (i) using the impedance-based stability assessment (IBSA) method to investigate this new interaction phenomenon, (ii) analyzing the impact of various transmission grid topologies, WP operating conditions, and wind turbine (WT) converter control parameters on the severity of the interaction. For ultimate accuracy, the frequency-dependent impedance characteristics of the WP are extracted using the electromagnetic transient (EMT)-type impedance scanning instead of a simplified analytical model. The performed analyses demonstrate that the WP generation capacity, length of the transmission lines, applied series and shunt compensation levels, presence of parallel lines, and grid side converter (GSC) control parameters of the WT can significantly affect the identified instability risk. The obtained results are validated through detailed EMT simulations. Although the type-4 WP is considered in this paper, the presented results can be generalized to any inverter-based resource (IBR) with a full-size converter (FSC), such as photovoltaic (PV) power stations.

This paper investigates a novel problem concerning material delivery in a matrix manufacturing workshop, specifically the multi-automated guided vehicle (AGV) dispatching problem with unloading setup time (MAGVDUST). The objective of the problem is to minimize transportation costs, including travel costs, time penalty costs, AGV costs, and unloading setup time costs. To solve the MAGVDUST, this paper builds a mixed-integer linear programming model and proposes an improved genetic algorithm (IGA). In the IGA, an improved nearest-neighbor-based heuristic is proposed to generate a high-quality initial solution. Several advanced technologies are developed to balance local exploitation and global exploration of the algorithm, including an optimal solution preservation strategy in the selection process, two well-designed crossovers in the crossover process, and a mutation based on Partially Mapped Crossover strategy in the mutation process. In conclusion, the proposed algorithm has been thoroughly evaluated on 110 instances from an actual electronic factory and has demonstrated its superior performance compared to state-of-the-art algorithms in the existing literature.

Abstract Currently, most researchers only utilize the network information or node characteristics to calculate the connection probability between unconnected node pairs. Therefore, we attempt to project the problem of connection probability between unconnected pairs into the physical space calculating it. Firstly, the definition of gravitation is introduced in this paper, and the concept of gravitation is used to measure the strength of the relationship between nodes in complex networks. It is generally known that the gravitational value is related to the mass of objects and the distance between objects. In complex networks, the interrelationship between nodes is related to the characteristics, degree, betweenness, and importance of the nodes themselves, as well as the distance between nodes, which is very similar to the gravitational relationship between objects. Therefore, the importance of nodes is used to measure the mass property in the universal gravitational equation and the similarity between nodes is used to measure the distance property in the universal gravitational equation, and then a complex network model is constructed from physical space. Secondly, the direct and indirect gravitational values between nodes are considered, and a novel link prediction framework based on the gravitational field, abbreviated as LPFGF, is proposed, as well as the node similarity framework equation. Then, the framework is extended to various link prediction algorithms such as Common Neighbors (CN), Adamic-Adar (AA), Preferential Attachment (PA), and Local Random Walk (LRW), resulting in the proposed link prediction algorithms LPFGF-CN, LPFGF-AA, LPFGF-PA, LPFGF-LRW, and so on. Finally, four real datasets are used to compare prediction performance, and the results demonstrate that the proposed algorithmic framework can successfully improve the prediction performance of other link prediction algorithms, with a maximum improvement of 15%.

This paper addresses the permutation flowshop scheduling problem with peak power consumption constraints (PFSPP). The real-time power consumption of the PFSPP cannot exceed a given peak power at any time. First, a mathematical model is established to describe the concerned problem. The sequence of operations is taken as a solution and the characteristics of solutions are analyzed. Based on the problem characteristics, eight heuristics are proposed, including balanced machine-job decoding method, balanced machine-job insert method, balanced job-machine insert method, balanced machine-job group insert method, balanced job-machine group insert method, greedy algorithm, beam search algorithm, and improved beam search algorithm. Similarly, the canonical artificial bee colony algorithm and iterated local search algorithm are modified based on the problem characteristics to solve the PFSPP. A large number of experiments are carried out to evaluate the performance of new proposed heuristics and metaheuristics. The results and discussion show that the proposed heuristics and metaheuristics perform well in solving the PFSPP.

Abstract Background OSBPL3 is overexpressed in a variety of malignancies and is closely associated with tumor growth and metastasis. However, its expression and function in colorectal cancer (CRC) are unclear. We aimed to investigate its prognostic and therapeutic value in this disease by detecting its expression in CRC and its correlation with the clinicopathological characteristics and prognosis of patients. Methods A total of 92 CRC samples were included in this study. According to the 2020 WHO diagnostic criteria, the criteria of the American Joint Committee on Cancer (AJCC) 8th edition staging system were used. OSBPL3 and Ki-67 expression in these samples was detected by immunohistochemistry. OSBPL3 mRNA expression was detected by qRT-PCR. KRAS/NRAS mutations were detected by an amplification refractory mutation system (ARMS). Data analysis was performed using the statistical analysis software Prism 8. Results OSBPL3 was found to be significantly overexpressed in CRC tumor tissues and was associated with worse progression-free survival and overall survival in patients. Additionally, OSBPL3 expression was negatively correlated with the degree of tumor differentiation. KRAS mutations were detected in approximately 32.6% of patients and were significantly associated with high OSBPL3 expression. In addition, OSBPL3 and Ki-67 expression was significantly correlated. Conclusions OSBPL3 is highly expressed in CRC samples and predicts a worse prognosis. OSBPL3 may become a new potential therapeutic target for CRC.

Abstract Background The left atrium (LA) is closely related to left ventricular diastolic function. Two-dimensional speckle tracking strain and strain rate (SR) imaging has been applied in the study of LA function. We intended to explore the relationship between global LA deformation parameters and plasma NTproBNP levels in asymptomatic community residents with normal ejection fraction and normal LA volume. Methods A cross-sectional sample of Beijing residents underwent comprehensive Doppler echocardiography and medical record review in 2009. Global LA longitudinal strain and SR indexes were obtained in the apical four-chamber view. LA stiffness index (LASI) was calculated as the ratio of early diastolic velocity of transmitral flow/early diastolic mitral annular motion velocity (E/E') to LA reservoir strain. Results A total of 620 individuals (mean age = 65.8 years, left ventricular ejection fraction = 70.8%, LA volume index = 17.9 ml/m2) were investigated in our study. 117 individuals had increased plasma NTproBNP (≥ 125 pg/ml). LA reservoir and contractile function by LA strain and SR indexes were significantly reduced in the abnormal NTproBNP group compared with the normal NTproBNP group. Multiple regression analysis indicated that LA contractile strain was a negative predictor of plasma NTproBNP in addition to indexed LA volume and E/E'. LASI was higher in the abnormal NTproBNP group and was significantly correlated with NTproBNP (r = 0.342, P

Segmental testicular infarction is a rare clinical condition most often seen as acute unilateral scrotal pain. Segmental testicular infarction should be suspected in patients with scrotal pain; when an ultrasound shows hypoechoic or mixed echogenic lesions within the testicular parenchyma; contrast-enhanced ultrasound shows a little or no contrast filling, along with negative multiple tumor markers. This report presents a 60-year-old male who presented with sudden onset of left testicular pain with no apparent cause. Emergency Doppler ultrasound, contrast-enhanced ultrasound, and laboratory tests showed findings characteristic of Segmental testicular infarction. The patient the final diagnosis was based on a combination of clinical findings (regression or cessation of symptoms, no tumor marker abnormalities, no palpable testicular mass) and ultrasound evidence of improvement (size reduction or shape change from oval to wedge) during a follow-up period of at least 3 months.