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Chromium nitride (CrN) is a promising structural and protective material with excellent mechanical properties and good wear and corrosion resistance. However, CrN tends to decompose into Cr 2 N at high temperatures, which makes the fabrication of single-phase and dense bulk CrN ceramics extremely challenging. In this work, a novel routine, ammonolysis followed by plasma activated sintering (PAS), has been proposed to fabricate single-phase and dense CrN ceramics. Single-phase CrN ceramics with a relative density of 98.2 %, higher than those in previous work, were successfully fabricated at the sintering temperature of 1200 °C. Its hardness and fracture toughness reach 11.9 GPa and 3.98 MPa m1/2, respectively, better than other CrN ceramics in literature. It exhibits friction coefficients of 0.75 to 0.45 and wear rates of 2.31 × 10−6 to 3.06 × 10−5 mm3 N−1 m−1 at the friction loads of 5–20 N. The successful fabrication of single-phase CrN ceramics can be attributed to the combined effect of the sintering atmosphere of extra N 2 and rapid densification. During densification, N 2 injected into the furnace will be encapsulated rapidly, creating a localized high nitrogen pressure that suppresses CrN decomposition and ultimately results in single-phase and dense CrN ceramic bulk. [ABSTRACT FROM AUTHOR]

Free bending technology is an important bending process for forming spatial tubes with variable curvature. By continuously adjusting the position of the die, tube axis with complex shapes can be formed, so accurately obtaining process parameters is crucial for precisely forming complex tubes. According to the geometric characteristics of tubes formed by free bending technology, the tubes are divided into stable segments with constant curvature and transitional segments with variable curvature, and the process parameters and geometric parameters of the formed tubes are described by the parameter sets. In this paper, based on the knowledge base, a new acquisition strategy was proposed to obtain the process parameters of spatial tubes with variable curvature. Aim at forming transitional tubes, in order to establish an effective correlation between process and geometric parameters, a surrogate model based on SVD-RBF has been proposed to quickly predict the axis shape of the transitional tube. In addition, applying this strategy to the forming experiment of the typical tube, it was found that the shape deviation Emax/L is 0.7806%, which verifies the feasibility of this strategy. [ABSTRACT FROM AUTHOR]

Recently, the offline‐trained Siamese pipeline has drawn wide attention due to its outstanding tracking performance. However, the existing Siamese trackers utilise offline training to extract 'universal' features, which is insufficient to effectively distinguish between the target and fluctuating interference in embedding the information of the two branches, leading to inaccurate classification and localisation. In addition, the Siamese trackers employ a pre‐defined scale for cropping the search candidate region based on the previous frame's result, which might easily introduce redundant background noise (clutter, similar objects etc.), affecting the tracker's robustness. To solve these problems, the authors propose two novel sub‐network spatial employed to spatial feature embedding for robust object tracking. Specifically, the proposed spatial remapping (SRM) network enhances the feature discrepancy between target and distractor categories by online remapping, and improves the discriminant ability of the tracker on the embedding space. The MAML is used to optimise the SRM network to ensure its adaptability to complex tracking scenarios. Moreover, a temporal information proposal‐guided (TPG) network that utilises a GRU model to dynamically predict the search scale based on temporal motion states to reduce potential background interference is introduced. The proposed two network is integrated into two popular trackers, namely SiamFC++ and TransT, which achieve superior performance on six challenging benchmarks, including OTB100, VOT2019, UAV123, GOT10K, TrackingNet and LaSOT, TrackingNet and LaSOT denoting them as SiamSRMC and SiamSRMT, respectively. Moreover, the proposed trackers obtain competitive tracking performance compared with the state‐of‐the‐art trackers in the attribute of background clutter and similar object, validating the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Detachment faults at slow‐ and ultraslow‐spreading mid‐ocean ridges are essential for lithosphere‐hydrosphere interactions. However, their coupling with subseafloor hydrothermal circulation is poorly understood. Here, we investigated shallow hydrothermal fluid circulations in the active Dragon Horn detachment fault system of the Southwest Indian Ridge using combined near‐bottom magnetic anomaly data and rock magnetic analyses. We observed enhanced magnetic anomalies related to the high magnetization of basaltic country rocks and highly serpentinized (>80%) peridotite, whereas the hydrothermally altered basalts and sulfide deposits had weak magnetization and reduced magnetic anomalies. Therefore, the low‐magnetization zone was interpreted as a proxy for the hydrothermal fluid channel. The spatial distribution of the low‐magnetization zone revealed that the inactive Suye field expanded more than 500 m in diameter horizontally and ∼100 m vertically, and the active Longqi hydrothermal field had a >1 km fluid channel, both centered around the detachment fault fracture zone. Our results establish a robust link between detachment faulting and shallow hydrothermal circulation in which the detachment fault system provides critical fluid paths. Therefore, detachment tectonics are important elements for evolving seafloor hydrothermal fields along the Southwest Indian Ridge and possibly other slow‐ and ultraslow‐spreading mid‐ocean ridges globally. Plain Language Summary: The detachment faults of slow‐ and ultraslow‐spreading mid‐ocean ridges are geological structures motivated by seafloor spreading. Intermitted movements of detachment faults exhume deep oceanic crust or mantle rocks and provide pathways for seafloor hydrothermal systems. The magnetic properties of rocks in seafloor detachment fault systems are sensitive to hydrothermal fluids and can be used to study fluid circulation within seafloor detachment fault systems. Using magnetic methods, we found that magnetic minerals in fresh basalt and highly serpentinized peridotite created positive magnetic anomalies, whereas the absence of magnetic minerals in hydrothermally altered basalts and sulfides decreased the magnetic anomalies. As represented by the low‐magnetization zones, the shallow hydrothermal fluid channels sit on the detachment fault, highlighting the close relationship between detachment tectonics and the evolution of seafloor hydrothermal systems. We conclude that the detachment fault system primarily controls the formation of black‐smoker chimneys along the magma‐poor mid‐ocean ridges. Key Points: Altered basalt and sulfide deposits attenuated the magnetic anomaly of the normal‐polarity zone in the Dragon Horn areaSerpentinized peridotite (>80%) produced significant positive magnetic anomalies in the Dragon Horn areaDetachment faulting controls the formation of fluid channels for hydrothermal circulation [ABSTRACT FROM AUTHOR]

Chromium nitride (CrN) ceramics were sintered at various temperatures by plasma activated sintering, and their thermoelectric properties were explored. The formation of Cr 2 N phase can be suppressed by venting N 2 gas into the chamber before sintering and increasing the sintering temperature to accelerate the densification process. Sintering temperature significantly impacted the thermoelectric properties. Higher sintering temperature led to an increase in the N content, reducing the electrical and thermal conductivity, and increasing the Seebeck coefficient. The single-phased CrN ceramic sintered at 1573 K exhibited excellent thermoelectric performance with a maximum power factor of 1002 μW·m−1·K−2, a thermal conductivity of 4.78 W·m−1·K−1, and a zT value of 0.20 at 973 K. Furthermore, this CrN ceramic also exhibited a high relative density of 97 % and a hardness of ∼11.9 GPa. Enhanced high-temperature thermoelectric properties and excellent mechanical properties make CrN ceramics suitable for thermoelectric applications in extreme environments. [ABSTRACT FROM AUTHOR]

Ammonia is considered a potential zero-carbon energy option for ships. However, ammonia combustion in marine engines presents challenges due to its combustion disadvantages. To overcome these challenges, the study investigates the combustion process in an ammonia/diesel low-speed marine engine under different combustion modes using computational fluid dynamics coupled with chemical dynamics. The results reveal that a diesel energy fraction of 5% can be reliably ignited in both concentrated and diluted ammonia atmospheres. In contrast to ammonia combustion in the thermal and reactive diesel atmosphere, the ignition and combustion of diesel within an ammonia environment hold the potential to enhance combustion rate and thermal efficiency. However, this improvement is counterbalanced by the emergence of high NO X emissions accompanied by elevated peak pressure rise rates. By judiciously managing the quality of pre-injected ammonia and allowing a reasonable time for diffusion, the resulting ammonia environment can curtail peak pressure rise rates and NO X emissions subsequent to diesel ignition, all while minimizing unburned ammonia and N 2 O emissions. Additionally, reactions HONO(+M) <=> NO + OH(+M), N 2 + O <=> N + NO, NO 2 + OH <=> NO + HO 2 , and N 2 O + O <=> 2NO are key in instantaneous NO production at CA50. The interaction of NO 2 with species such as H 2 NO, HNO, NH 2 , generates HONO, which rapidly decomposes into NO and OH, contributing to the majority of instantaneous NO generation. Furthermore, the distribution region of N 2 + O <=> N + NO and N 2 O + O <=> 2NO is mainly attributed to high-temperature and lean combustion conditions. • A systematic comparative study of different combustion modes was carried out. • The distribution of ammonia has an important effect on the combustion process. • A reasonable ammonia atmosphere helps to improve the ITE. • Increasing the diffusion time of pre-injection ammonia helps to reduce NOx. [ABSTRACT FROM AUTHOR]

Feature selection is an indispensable step for the analysis of high-dimensional molecular data. Despite its importance, consensus is lacking on how to choose the most appropriate feature selection methods, especially when the performance of the feature selection methods itself depends on hyper-parameters. Bayesian optimization has demonstrated its advantages in automatically configuring the settings of hyper-parameters for various models. However, it remains unclear whether Bayesian optimization can benefit feature selection methods. In this research, we conducted extensive simulation studies to compare the performance of various feature selection methods, with a particular focus on the impact of Bayesian optimization on those where hyper-parameters tuning is needed. We further utilized the gene expression data obtained from the Alzheimer's Disease Neuroimaging Initiative to predict various brain imaging-related phenotypes, where various feature selection methods were employed to mine the data. We found through simulation studies that feature selection methods with hyper-parameters tuned using Bayesian optimization often yield better recall rates, and the analysis of transcriptomic data further revealed that Bayesian optimization-guided feature selection can improve the accuracy of disease risk prediction models. In conclusion, Bayesian optimization can facilitate feature selection methods when hyper-parameter tuning is needed and has the potential to substantially benefit downstream tasks. [ABSTRACT FROM AUTHOR]

Feature selection is an indispensable step for the analysis of high-dimensional molecular data. Despite its importance, consensus is lacking on how to choose the most appropriate feature selection methods, especially when the performance of the feature selection methods itself depends on hyper-parameters. Bayesian optimization has demonstrated its advantages in automatically configuring the settings of hyper-parameters for various models. However, it remains unclear whether Bayesian optimization can benefit feature selection methods. In this research, we conducted extensive simulation studies to compare the performance of various feature selection methods, with a particular focus on the impact of Bayesian optimization on those where hyper-parameters tuning is needed. We further utilized the gene expression data obtained from the Alzheimer's Disease Neuroimaging Initiative to predict various brain imaging-related phenotypes, where various feature selection methods were employed to mine the data. We found through simulation studies that feature selection methods with hyper-parameters tuned using Bayesian optimization often yield better recall rates, and the analysis of transcriptomic data further revealed that Bayesian optimization-guided feature selection can improve the accuracy of disease risk prediction models. In conclusion, Bayesian optimization can facilitate feature selection methods when hyper-parameter tuning is needed and has the potential to substantially benefit downstream tasks. [ABSTRACT FROM AUTHOR]

Simple Summary: The bamboo weevil beetle, Cyrtotrachelus buqueti (Coleoptera: Curculionidae) is the primary bamboo pest and seriously influences the development of the bamboo industry. Sensory neuron membrane proteins (SNMPs) play important roles in insect pheromone communication. However, SNMPs of C. buqueti are still uncharacterized. With the aim of developing control techniques to control this pest, one novel SNMP from C. buqueti, CbuqSNMP1b, was functionally characterized in this study. The results indicated that CbuqSNMP1b was predominantly expressed in the antennae of both sexes and showed significantly higher transcription levels in the adult stage, suggesting that CbuqSNMP1b is involved in the process of olfaction. Fluorescence binding assays revealed that CbuqSNMP1b could bind to three out of fourteen volatile compounds emitted from C. buqueti and showed the strongest binding affinity to dibutyl phthalate, demonstrating the role of SNMP1 in detecting odorants. Molecular docking was performed to further understand the binding mode between CbuqSNMP1b and these three ligands, and the results showed that hydrophobic interactions were the prevailing forces within the binding cavities of CbuqSNMP1b. The results of this study will be helpful to understand the function of SNMP1 in C. buqueti and lay a foundation for developing new methods to control this pest. Sensory neuron membrane proteins (SNMPs) play important roles in insect chemoreception and SNMP1s have been reported to be essential in detecting sex pheromones in Drosophila and some lepidopteran species. However, SNMPs for Cyrtotrachelus buqueti (Coleoptera: Curculionidae), a major insect pest of bamboo plantations, remain uncharacterized. In this study, a novel SNMP gene, CbuqSNMP1b, from C. buqueti was functionally characterized. The expression of CbuqSNMP1b was significantly higher in antennae than in other tissues of both sexes and the expression level was significantly male-biased. Additionally, CbuqSNMP1b showed significantly higher transcription levels in the adult stage and very low transcription levels in other stages, suggesting that CbuqSNMP1b is involved in the process of olfaction. Fluorescence binding assays indicated that CbuqSNMP1b displayed the strongest binding affinity to dibutyl phthalate (Ki = 9.03 μM) followed by benzothiazole (Ki = 11.59 μM) and phenol (Ki = 20.95 μM) among fourteen C. buqueti volatiles. Furthermore, molecular docking revealed key residues in CbuqSNMP1b that interact with dibutyl phthalate, benzothiazole, and phenol. In conclusion, these findings will lay a foundation to further understand the olfactory mechanisms of C. buqueti and promote the development of novel methods for controlling this pest. [ABSTRACT FROM AUTHOR]

Wolbachia is a maternally inherited endosymbiont of the phylum α‐Proteobacteria that is found widely in arthropods and nematodes. Cytoplasmic incompatibility (CI) is the commonest endosymbiotic manipulation among arthropods, namely reduced embryo viability when Wolbachia‐infected males fertilize Wolbachia‐uninfected females.In this study, endosymbiont infection was investigated and crossing experiments were performed in the wing‐dimorphic cricket Velarifictorus aspersus (Walker) (Orthoptera: Gryllidae) to clarify the effects of Wolbachia on host reproduction.All the tested individuals were infected with two Wolbachia strains, wAsp‐a and wAsp‐f, which belong to supergroup A and supergroup F, respectively.There were no obvious differences in the duration of nymph development or the proportions of females between the Wolbachia‐infected and Wolbachia‐free lines. However, crossing Wolbachia‐infected males with uninfected females reduced the hatching rate by 28% compared with that when infected males were crossed with infected females. The number of eggs laid by Wolbachia‐free females was significantly lower than laid by infected females, either mating with infected males or uninfected males.These results suggest that Wolbachia induced incomplete CI and enhanced female fertility in V. aspersus. Because no homologous cifA and cifB genes, which are involved in CI, were found in supergroups C, D and F, it might be considered that the CI of V. aspersus was induced by strain wAsp‐a of supergroup A. Moreover, the significant increase in the density of wAsp‐a Wolbachia with nymph development might be related to the regulation of CI. [ABSTRACT FROM AUTHOR]

Pheromone-binding proteins (PBPs) play important roles in binding and transporting sex pheromones. However, the PBP genes identified in coleopteran insects and their information sensing mechanism are largely unknown. Cyrtotrachelus buqueti (Coleoptera: Curculionidae) is a major insect pest of bamboo plantations. In this study, a novel PBP gene, CbuqPBP2, from C. buqueti was functionally characterized. CbuqPBP2 was more abundantly expressed in the antennae of both sexes than other body parts, and its expression level was significantly male-biased. Fluorescence competitive binding assays showed that CbuqPBP2 exhibited the strongest binding affinity to dibutyl phthalate (Ki = 6.32 μM), followed by styrene (Ki = 11.37 μM), among twelve C. buqueti volatiles. CbuqPBP2, on the other hand, showed high binding affinity to linalool (Ki = 10.55), the main volatile of host plant Neosinocalamus affinis. Furthermore, molecular docking also demonstrated the strong binding ability of CbuqPBP2 to dibutyl phthalate, styrene, and linalool, with binding energy values of −5.7, −6.6, and −6.0 kcal/mol, respectively, and hydrophobic interactions were the prevailing forces. The knockdown of CbuqPBP2 expression via RNA interference significantly reduced the electroantennography (EAG) responses of male adults to dibutyl phthalate and styrene. In conclusion, these results will be conducive to understanding the olfactory mechanisms of C. buqueti and promoting the development of novel strategies for controlling this insect pest. [ABSTRACT FROM AUTHOR]

Reasonable construction of high activity and low cost non-noble metal oxygen reduction reaction (ORR) catalyst is of great importance for the wide application of zinc-air batteries (ZABs). Using bimetallic MOF as a precursor combined with electrospinning, high-temperature carbonization and electrodeposition, we successfully developed a porous carbon nanofiber (Co@Fe-CNFs-1000) with bimetallic active center as an efficient catalyst for ORR. The successful construction of this special core-shell structure directly explores the synergy between different active centers. The results showed that the synthesized Co@Fe-CNFs-1000 catalyst exhibited ORR performance comparable to that of Pt/C in 0.1 mol/L KOH electrolyte, high half-wave potential (E1/2=0.81 V) and limiting current density (JL=5.4 mA-cm−2). In addition, homemade liquid ZABs with Co@Fe-CNFs-1000 as the air cathode showed excellent power density (155.8 mW·cm−2), specific capacity (780.6 mAh·gZn−1) and long-term stability (over 100 h at 2 mA·cm−2), surpassing even Pt/C-based batteries. In addition, the flexible solid-state ZABs assembled based on Co@Fe-CNFs-1000 demonstrates excellent flexibility and durability. This work provides a new idea for constructing ORR catalysts with high activity centers. [ABSTRACT FROM AUTHOR]

Introduction: The mitochondrial alanyl‐tRNA synthetase 2 (AARS2) as one of aminoacyl‐tRNA synthases (ARSs) performs amino acid transportation and involves protein synthesis. However, its role in cancer remains largely unexplored. Methods: In this study, more than 10,000 samples were enrolled to explore genomic alterations, biological function, prognosis, and clinical treatment based on AARS2 across pan‐cancer. The molecular characterization of AARS2 was confirmed in hepatocellular carcinoma (HCC) using proteomics analysis, quantitative real‐time PCR, western blotting, immunohistochemical staining, and cell experiments. Results: For genomic landscape, the AARS2 was dramatically upregulated in multiple cancers, which might be mainly caused by copy number alteration rather than mutation and methylation. The abnormal expression of AARS2 was prominently associated with activity of cancer pathways and performed oncogenic roles in most cancers. Systematic experiments in vitro substantiated the elevated expression of AARS2, and the deficiency of it inhibited cell proliferation and cell migration in HCC. Meanwhile, our findings suggested that AARS2 could serve as a novel promising and stable biomarker for assessing prognosis and immunotherapy. Moreover, a variety of therapeutic drugs and targeted pathways were proposed for cancer treatment, which might enhance clinical efficacy. Conclusion: The AARS2 could serve as a new oncogenic gene that promotes cell proliferation and migration in HCC. The comprehensive investigations increased the understanding of AARS2 across human cancers and generated beginning insights of AARS2 in genomic landscape, molecular biological function, prognosis, and clinical treatment. [ABSTRACT FROM AUTHOR]

In this paper, a reduced-order interval observer (R-IO) design technique is developed for continuous-time descriptor linear-parameter-varying systems with unknown-but-bounded uncertainties. First, by introducing an intermediate variable, the R-IO design amounts to estimating the linear functional of the system states. Then, with a parameter-dependent Luenberger-like structure, the R-IO existence condition is eventually formulated into a set of differential-algebraic equations, not involving any linear transformation process. Further, a parametric solution to such an R-IO is derived through solving the equation set, which clearly shows the design degrees of freedom. Finally, the correctness of the proposed results is verified by a numerical system and an electrical circuit system. [ABSTRACT FROM AUTHOR]

Background: Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored. Methods: 76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801). We collected 28 published signatures and collated clinical variables for comparison with MDILS to verify its efficacy. Subsequently, molecular mechanisms, immune status, mutation landscape, and pharmacological profile were further investigated in different stratified patients. Results: Patients with high MDILS displayed worse overall survival than those with low MDILS. The MDILS could independently predict overall survival and convey robust performance across five cohorts. MDILS has a significantly better performance compared with traditional clinical variables and 28 published signatures. Patients with low MDILS exhibited more abundant immune infiltration and higher potency of immunotherapeutic response, while patients with high MDILS might be more sensitive to multiple chemotherapeutic drugs (e.g., sunitinib and axitinib). Conclusion: MDILS is a robust and promising tool to facilitate clinical decision-making and precision treatment of RCC. [ABSTRACT FROM AUTHOR]

IL-H2O2 bicomponent hypergolic propellant is a new type of green and environmentally friendly hypergolic propellant, but its ignition delay time needs to be further reduced. In this paper, an iodine-containing ionic liquid of 1-methyl-4,5-diiodoimidazolium iodide ([Dmim]I) was synthesized and applied to the spontaneous combustion system of methylimidazolium borane (MIMB) and H2O2. When a small amount of [Dmim]I was added, the spontaneous combustion of MIMB was enhanced and the flame color becomes brighter as well as the ignition delay time can be reduced from 250 to 109 ms; the accelerator of [Dmim]I had less effect on the maximum specific impulse of MIMB, but the combustion mechanism of MIMB in 95% H2O2 was changed may be by lowering the Gibbs free energy of the dehydrocoupling reaction between the H2O2 and the MIMB. Thermal behavior of MIMB, [Dmim]I, and MIMB containing 2 mass% [Dmim]I were studied by thermogravimetric analysis. The decomposition temperature of MIMB is greatly delayed after adding 2 mass% of [dmim]I, and the maximum temperature delay is about 30 °C; the thermal decomposition of MIMB includes two thermal mass loss processes and the corresponding decomposition activation energy are increased with the addition of [Dmim]I; these indicate that MIMB is compatible with [Dmim]I without oxidizing agent, and [Dmim]I has a stabilizing effect on MIMB. [ABSTRACT FROM AUTHOR]

Due to the special characteristics of the shooting distance and angle of remote sensing satellites, the pixel area of ship targets is small, and the feature expression is insufficient, which leads to unsatisfactory ship detection performance and even situations such as missed and false detection. To solve these problems, this paper proposes an improved-YOLOv5 algorithm mainly including: (1) Add the Convolutional Block Attention Module (CBAM) into the Backbone to enhance the extraction of target-adaptive optimal features; (2) Introduce a cross-layer connection channel and lightweight GSConv structures into the Neck to achieve higher-level multi-scale feature fusion and reduce the number of model parameters; (3) Use the Wise-IoU loss function to calculate the localization loss in the Output, and assign reasonable gradient gains to cope with differences in image quality. In addition, during the preprocessing stage of experimental data, a median+bilateral filter method was used to reduce interference from ripples and waves and highlight the information of ship features. The experimental results show that Improved-YOLOv5 has a significant improvement in recognition accuracy compared to various mainstream target detection algorithms; compared to the original YOLOv5s, the mean Average Precision (mAP) improved by 3.2% and the Frames Per Second (FPN) accelerated by 8.7%. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is the second malignancy worldwide. POLA2 initiates DNA replication, regulates cell cycle and gene repair that promote tumorigenesis and disease progression. However, the prognostic and biological function roles of POLA2 in HCC had not been conclusively determined. Methods: The expression levels and prognosis role of POLA1 and POLA2 in HCC were analyzed based on TCGA-LIHC database and recruited 24 HCC patients. Gene mutations were analyzed using "maftools" package. POLA2 and immune cells correlations were analyzed by TIMER. POLA2 co-expressed genes functional enrichment were evaluated using Metascape. The mRNA and protein level of POLA2 was detected in HCC cells and tissues. Cell migration, invasion, proliferation, cell cycle and HCC cell lines derived xenograft model were performed to investigate POLA2 biological function. Results: POLA2 was significantly high expressed in HCC than in normal liver tissue in both TCGA-LIHC and our collected HCC samples. In validation cohort, POLA2 significantly related to tumor differentiation, tumor size and Ki-67 (p < 0.05). In TCGA-LIHC cohort, overexpression of POLA2 predicted a low OS and associated with different clinical stages. Multivariate Cox regression showed overexpression of POLA2 effectively distinguished the prognosis at different T, N, M, stages and grades of HCC. POLA2 expression correlated with mutation burden, immune cells infiltration and immune-associated genes expression of HCC. Functional enrichment revealed that POLA2 co-expressed genes were linked to cellular activity, plasma membrane protein complex and leukocyte activity, immune response-regulated cell surface receptor signaling pathway, and immune response-regulated signaling pathway. Moreover, POLA2 was also positively co-expressed with some immune checkpoints (CD274, CTL-4, HAVCR2, PDCD1, PDCD1LG2, TIGIT, and LAG3) (p < 0.001). Gene knockdown revealed that POLA2 promoted proliferation, migration, invasion, and cell cycle of SMMC-7721 and HepG2. The HCC xenograft tumor model also demonstrated remarkably tumor size inhibition, tumor proliferation inhibtion and tumor necrosis promotion when POLA2 knockdown. Conclusions: POLA2 influenced immune microenvironment and tumor progression of HCC indicated that it might be a potential molecular marker for prognostic evaluation or a therapeutic target for HCC. [ABSTRACT FROM AUTHOR]

The reported findings help to understand the treatment technology for studying shipping emissions and air pollution, especially in the context of near-zero emissions. Ship emissions primarily consist of two categories: air pollutants such as SOx, NOx, PM, CO, and NMVOCs, as well as greenhouse gases, including CO SB 2 sb , CH SB 4 sb , and N SB 2 sb O [[5], [7]]. However, engine combustion will produce a lot of harmful emissions such as particulate matter (PM), sulfur oxides (SOx), and nitrogen oxides (NOx), which cause severe pollution to the atmosphere and marine environment [[4]]. [Extracted from the article]

Recent evidence suggests that bispecific antibodies (BsAbs) exhibit promising efficacy and low toxicity even in heavily treated non-Hodgkin B-cell lymphoma (B-NHL). However, the role of BsAbs in previously untreated NHL and the efficacy and safety of BsAbs used in combination remain uncertain. We summarized data published at the 64th American Society of Hematology (ASH) Annual Meeting on BsAb monotherapy or combination therapy for first-line or relapsed/refractory B-NHL. BsAb monotherapy in elderly/unfit newly diagnosed (ND) DLBCL patients achieved ORR and CR rates of 56% and 43%, respectively. In addition, BsAbs combined with chemotherapy or other novel agents raised the ORR higher than 50% without increasing the incidence of grade ≥ 3 CRS. We conclude that BsAb monotherapy or combination therapy for first-line or relapsed/refractory B-NHL has high efficacy and satisfactory safety. [ABSTRACT FROM AUTHOR]

Heavy-metal (Cd, Hg, and Pb)-containing semiconductor nanocrystals (NCs) have been explored widely due to their unique optical and electrical properties. However, the toxicity risks of heavy metals can be a drawback of heavy-metal-containing NCs in some applications. Anisotropic heavy-metal-free semiconductor NCs are desirable replacements and can be realized following the establishment of anisotropic growth mechanisms. These anisotropic heavy-metal-free semiconductor NCs can possess lower toxicity risks, while still exhibiting unique optical and electrical properties originating from both the morphological and compositional anisotropy. As a result, they are promising light-emitting materials in use various applications. In this review, we provide an overview on the syntheses, properties, and applications of anisotropic heavy-metal-free semiconductor NCs. In the first section, we discuss hazards of heavy metals and introduce the typical heavy-metal-containing and heavy-metal-free NCs. In the next section, we discuss anisotropic growth mechanisms, including solution–liquid–solid (SLS), oriented attachment, ripening, templated-assisted growth, and others. We discuss mechanisms leading both to morphological anisotropy and to compositional anisotropy. Examples of morphological anisotropy include growth of nanorods (NRs)/nanowires (NWs), nanotubes, nanoplatelets (NPLs)/nanosheets, nanocubes, and branched structures. Examples of compositional anisotropy, including heterostructures and core/shell structures, are summarized. Third, we provide insights into the properties of anisotropic heavy-metal-free NCs including optical polarization, fast electron transfer, localized surface plasmon resonances (LSPR), and so on, which originate from the NCs' anisotropic morphologies and compositions. Finally, we summarize some applications of anisotropic heavy-metal-free NCs including catalysis, solar cells, photodetectors, lighting-emitting diodes (LEDs), and biological applications. Despite the huge progress on the syntheses and applications of anisotropic heavy-metal-free NCs, some issues still exist in the novel anisotropic heavy-metal-free NCs and the corresponding energy conversion applications. Therefore, we also discuss the challenges of this field and provide possible solutions to tackle these challenges in the future. [ABSTRACT FROM AUTHOR]

In this study, the ammonia-diesel stratified injection (ADSI) is explored on a marine low-speed engine., The effect of three injection timings(IT S = −3°CA ATDC, −1°CA ATDC, and 1°CA ATDC) coupling with three diesel energy fractions (DEF S = 1%,5%, and 10%) on combustion and emission characteristics of the engine under full load is investigated. The results show that advancing IT has an obvious effect on increasing peak cylinder pressure while enhancing DEF can increase the heat release rate under ADSI mode, and the ignition delay time is less than original diesel engine. The ADSI has higher indicated thermal efficiency than original diesel engine except for IT of 1°CA ATDC coupling DEF of 1%, and its combustion efficiency can be significantly improved. Furthermore, the NO x increases with advancing IT and increasing DEF while the unburned ammonia is the opposite. The NO x emissions are all lower than original diesel engine under different IT coupling DEF. Advancing IT is an effective measure to reduce unburned ammonia. The greenhouse gas (GHG) can be greatly reduced. A priority strategy of the IT coupling DEF is proposed through comprehensive comparison under the ADSI mode, which can meet the Tier III regulations. This strategy reduces indicated specific fuel consumption and GHG around by 4% and 94% compared with the diesel engine respectively, and the combustion efficiency reaches more than 99%. The unburned ammonia is limited to less than 150 ppm. • A new ammonia-diesel stratified injection (ADSJ) mode was explored in detail. • The effect of multi-parameter coupling was studied on combustion and emissions. • The ADSJ mode was easier ignition than the original diesel engine. • The ADSJ had better combustion characteristics than the original diesel engine. • An optimized parameter control strategy is proposed. [ABSTRACT FROM AUTHOR]

Summary: A tunable circularly polarized square patch antenna with parasitic elements is designed for a wide frequency tuning range and high gain characteristics. The proposed antenna is constructed by one main patch and four semi‐elliptic parasitic units. By loading four varactor diodes and adjusting their capacitance values, the tunable feature is performed to reallocate the corresponding working frequency. Moreover, the diagonal corners of the antenna are cut and loaded with varactor diodes, which provide the appropriate perturbation between the two orthogonality modes of the antenna, so as to ensure the circular polarization characteristic in the entire operating tuning band. The experimental results demonstrate that the reflection coefficient and axial ratio are less than −13 dB and 3 dB, respectively. The proposed antenna features a relatively wide continuously tuning range of 24% within 1.9‐2.3 GHz and a stable gain of over 7 dBi with a radiation efficiency of above 85%. [ABSTRACT FROM AUTHOR]

Eusocial insects can employ various behavioural and physiological disease defences to avoid, resist and tolerate pathogen infections in their closely related and packed colonies, termed social immunity. Recent studies have shown that several molecules serve insect social immunity, including chemical odours, insect venoms, immune-related proteins, etc. However, whether and how microRNAs (miRNAs), whose precursors are processed by Dicer-1, drive social immunity in insect colonies is still unknown. Here, we used a 'host–pathogen' system (host: Reticulitermes chinensis; pathogen: Metarhizium anisopliae) to explore the impact of miRNAs on social immunity in termite colonies. We found that RNAi-mediated silencing of Dicer-1 led to decreased miRNA concentration, significantly inhibited carbohydrate and energy metabolism and affected other life processes, such as the immune response and oxidation–reduction reactions, in whole body of the termite. In behavioural defence, silencing Dicer-1 significantly diminished defensive social behaviours such as locomotion, grooming, cannibalism and burial in termite groups when encountering fungal contamination. In physiological defence, Dicer-1 silencing and miR-71-5 stimulation resulted in significantly decreased antifungal activities of termites. Furthermore, both Dicer-1-silenced and miR-71-5 stimulant-treated termite groups exhibited a high level of mortality during fungal contamination. Our findings demonstrated the important role of miRNAs in shaping social immunity in termite colonies, providing insights necessary to understand the potential mechanisms underlying behavioural and physiological disease defences in insects and hence laying the groundwork for miRNA-based pest control. [ABSTRACT FROM AUTHOR]

The voids in coarse aggregate (VCA) is an important volumetric index in the mineral aggregate gradation design of stone matrix asphalt (SMA) mixtures. To explore the law of variation for VCA formed by the packing of basalt and lime coarse aggregates, a uniform design method and vibrating compaction tests were used to establish the prediction model. Based on the test results and stepwise regression analysis, a reliable prediction model of VCA was obtained. There is a multiple nonlinear relationship between the VCA and the proportion of each coarse aggregate in the mixture. Regardless of the type of coarse aggregates used, the rule of VCA with different forms of aggregate gradation curves has universal significance. This conclusion can help to determine the aggregate gradation in the design of SMA mixtures. [ABSTRACT FROM AUTHOR]

Leukemia stem cells (LSCs) constitute the critical barrier to the cure of acute myeloid leukemia (AML) due to their chemoresistance and immune evasion property. Herein, the role of anlotinib, a multiple tyrosine kinase inhibitor, in killing LSCs and regulating chemoresistance and immune evasion was explored. Anlotinib treatment induced apoptosis of LSC-like cells as well as primary AML LSCs, while sparing the normal mononuclear cells in vitro. Moreover, anlotinib could impair the regeneration capacity of LSCs in the patient-derived leukemia xenograft mouse model. Mechanistically, anlotinib inhibited phosphorylation of c-kit, JAK2/STAT3, and STAT5, and downregulated STAT3 and STAT5 expression. In addition, anlotinib downregulated the anti-apoptotic proteins Bcl-2 and Bcl-xL, and upregulated Bax, thereby enhancing the sensitivity of LSCs to idarubicin in vitro. Intriguingly, anlotinib could also partially rescue the interferon-g production of T cells cocultured with LSCs by downregulating PD-L1 expression. In conclusion, anlotinib showed anti-LSC activity and the potential to enhance the sensitivity to idarubicin and inhibit the immunosuppressive feature of LSCs via JAK2/STAT signaling pathway downregulation in the preclinical study. Our results provided a rational basis for combinatory strategies involving anlotinib and chemotherapy or immunotherapy. [ABSTRACT FROM AUTHOR]

The programmed death ligand 1 (PD-L1) is a pivotal biomarker of immunotherapy in triple negative breast cancer (TNBC). TP53 is reported as a positive regulatory predictor of immune efficacy. The correlation of p53 expression or mutation and PD-L1 expression is explored. By immunohistochemistry, PD-L1 expression between p53 mutation (missense and nonsense) and wild type; p53 no-expression/loss vs. expression were compared. There was a significant association between p53 mutation, especially missense mutation with higher histological grade, and PD-L1 expression in immune cells (ICs). Both p53 missense mutation and PD-L1 expression may be potential targets for improving immunotherapy response in TNBC. [ABSTRACT FROM AUTHOR]

Cr coatings were deposited on both the polished and rough substrate using DC magnetron sputtering. The influence of substrate surface roughness on the morphology, crystalline phase and mechanical properties of the coatings were analyzed. The results showed that surface roughness had a significant effect on the surface morphology of the coating, as the coating inherited the surface morphology of the substrate. Surface roughness before and after coating for the polished and rough surfaces were 0.054–0.046 and 0.107–0.563μm, respectively. The hardness and Young’s modulus of the coating deposited on the polished surface were 5.5 and 188.6GPa, respectively, while the mechanical properties of the coating deposited on the rough surface are about the same. The results showed that the adhesion of the coating can be improved by appropriately increasing the surface roughness. [ABSTRACT FROM AUTHOR]

Background: Hepatitis B virus (HBV) causes acute and chronic infection in the clinic. Hepatocellular carcinoma (HCC) is closely linked to HBV infection. Serum Golgi protein 73 (GP73) increases during HBV infection. However, the role of GP73 during HBV infection and the occurrence of HBV-related HCC is still poorly understood. Methods: The underlying role of HBV-induced GP73 in regulating HCC development was investigated in this study. GP73 expression in HBV-related clinical HCC tissues and in HBV-infected hepatoma cells and primary human hepatocytes was evaluated by immunohistochemistry, ELISAs, Western blotting and quantitative real-time PCR (qRT-PCR) analysis. Tumorigenicity of GP73 overexpressed cells was detected by flow cytometry, qRT-PCR, xenograft nude mouse analyses and sphere formation assays. The effects of GP73 and HBV infection on host innate immune responses in hepatocytes were further investigated by Western blotting and qRT-PCR analysis. Results: Initially, we confirmed that HBV-positive HCC tissues had significantly higher expression of GP73. Ectopic expression of the HBV gene could induce GP73 expression in primary human hepatocytes and hepatoma cells in vitro. In addition, we discovered that GP73 promotes HCC in both normal liver cells and hepatoma cells. We also found that ectopic expression of HBV genes increases GP73 expression, suppressing the host's innate immune responses in hepatocytes. Conclusions: Our results demonstrate that HBV facilitates HCC development by activating GP73 to repress the host's innate immune response. This study adds to our understanding of the pathogenesis of HBV infection-induced HCC. The findings also provide preclinical support for GP73 as a potential HCC prevention or treatment target. [ABSTRACT FROM AUTHOR]

The Mg-6Zn-0.5Zr (ZK60) alloy has attracted extensive attention as one of the hopeful biomedical material candidates for bone implant applications on account of its unique degradability, favorable biocompatibility as well as mechanical compatibility. Nevertheless, the rapid degradation rate in the biological environment is the major hurdle for its clinical application in the field of bone implants. In this study, nanodiamond (ND) was incorporated into ZK60 alloy via selective laser melting technology to enhance its degradation resistance. The results showed that compared with selective laser-melted ZK60 (SLMed ZK60), the selective laser-melted ZK60 with 6 wt.% ND (SLMed ZK60−6ND) possessed the better degradation resistance with the lower degradation rate of 0.5 ± 0.1 mm/year. The enhancement of the degradation resistance was attributed to the fact that ND could promote the deposition of apatite and build up a dense and insoluble protective layer through the dissociation of the carboxyl groups on the ND surface, which could effectively hinder the further degradation of the Mg matrix. Meanwhile, the compressive strength and hardness were improved mainly due to grain refinement strengthening and ND dispersion strengthening. In addition, the SLMed ZK60−6ND possessed good cytocompatibility. These results suggested that the SLMed ZK60−6ND, with enhanced degradation resistance, improved mechanical properties, and good cytocompatibility, was an excellent biomedical material candidate for bone implant applications. [ABSTRACT FROM AUTHOR]

The exercise volume and exercise level can be quantitatively assessed by measuring and collecting athletes' health and exercise data. The protection of athletes' health information has lately become an important research topic due to a rise in sports activities. However, due to the nature of the data and the limits of protection models, protecting athlete health data is a complex undertaking. Machine learning and blockchain have caused worldwide technological innovation, and it is bound to bring deep modifications to the sports industry. The main purpose of blockchain is security, decentralization, traceability, and credibility of the athlete's health data protection and gathering system. To progress and increase the sports industry and methodically assess the physical fitness of sportspersons' health information, this study concentrates on the Machine Learning and Blockchain-based Athlete Health Information Protection System (MLB-AHIPS) proposed in the sports industry. The ML technique is utilized to clean and handle the information to comprehend the recognition and secure managing of the sportsperson's fitness information. The system uses attribute-based access control, which permits dynamic and fine-grained access to athlete health data, and then stores the health data in the blockchain, which can be secured and tamper-proof by expressing the respective smart contracts. The simulation outcomes illustrate that the suggested MLB-AHIPS attains a high accuracy ratio of 97.8%, security ratio of 98.3%, an efficiency ratio of 97.1%, scalability ratio of 98.9%, and data access rate of 97.2% compared to other existing approach. [ABSTRACT FROM AUTHOR]

Current‐induced magnetization switching without the assistance of an in‐plane magnetic field by using the spin orbit torque (SOT) has attracted lots of attention for the novel energy‐efficient and nonvolatile spintronics devices. In this study, a full‐scale field‐free SOT switching in perpendicularly magnetized Ru/Pt/HoCo/Ru multilayers with a designed vertical composition gradient is reported. Through annealing the multilayers at 150 °C for 0–40 min, a structural change from a multilayer to an alloying structure with mixed distribution of Ho and Co is found. Simultaneously, the field‐free switching gradually turns from a full‐scale to a partial switching with the structural change. The multiple mechanisms brought by fabricating the HoCo layers with vertical composition gradient (including the non‐uniform Dzyaloshinskii–Moriya interaction (DMI), the defects, the inevitable lateral gradient, or the exchange bias effect along the thickness direction) lead to the deterministic field‐free switching. In addition, a detailed study on the stack of Ru/gradient HoCo/Ru shows that HoCo itself can also produce a certain amount of SOT to realize a partial switching in the absence of the in‐plane field. This work provides a route via engineering rare‐earth‐transition‐metal ferrimagnet to manipulate DMI and SOT for fully electrically controlled spintronics devices. [ABSTRACT FROM AUTHOR]

Premixed combustion mode dual-fuel (DF) engines are widely used in large-bore marine engines due to their great potential to solve the problem of CO2 emissions. However, detonation is one of the main problems in the development of marine engines based on the premixed combustion mode, which affects the popularization of liquefied natural gas (LNG) engines. Due to the large bore and long stroke, marine dual-fuel engines have unique flow characteristics and a mixture mechanism of natural gas and air. Therefore, the purpose of this study is to present a simulated investigation on the influence of swirl on multiscale mixing and the concentration field, which provides a new supplement for mass transfer theory and engineering applications. It is suggested that the phenomenon of abnormal combustion occurs on account of the distribution of the mixture being uneven in a super-large-bore dual-fuel engine. Further analysis showed that the level of swirl at the late compression stage and the turbulence intensity are the decisive factors affecting the transmission process of natural gas (NG) and distribution of methane (CH4) concentration. Finally, a strategy of improving mixture quality and the distribution of the mixture was proposed. [ABSTRACT FROM AUTHOR]

Background: Motor cortex stimulation applied as a clinical treatment for neuropathic disorders for decades. With stimulation electrodes placed directly on the cortical surface, this neuromodulation method provides higher spatial resolution than other non-invasive therapies. Yet, the therapeutic effects reported were not in conformity with different syndromes. One of the main issues is that the stimulation parameters are always determined by clinical experience. The lack of understanding about how the stimulation current propagates in the cortex and various stimulation parameters and configurations obstruct the development of this method.Methods: In this study, we investigated the effect of different stimulation configurations on cortical responses to motor cortical stimulations using intrinsic optical imaging.Results: Our results showed that the cortical activation of electrical stimulation is not only related to the current density but also related to the propagation distance. Besides, stimulation configurations also affect the propagation of the stimulation current.Conclusions: All these results provide preliminary experimental evidence for parameter and electrode configuration optimizations. [ABSTRACT FROM AUTHOR]

The landscape is driven by innovative design, adhering to the concept of "poetic residence, inheritance, and innovation," which has long served China's urban and rural development and the construction of ecological civilization and provided high-quality planning and design services for governments at all levels throughout the country; we construct a particle swarm optimization (PSO) landscape pattern spatial optimization model and solution algorithm to optimize the spatial layout of the landscape for economic development, ecological protection, and integrated scenarios in a city in southwest China. The results show that the PSO-based landscape pattern spatial optimization model and algorithm can use particle position to simulate landscape distribution for spatial pattern optimization. In the development of landscape pattern optimization methods, the landscape pattern optimization model with landscape simulation evolution as the core has shown its advantages. In the target year, the dominant landscape of economic development scenario is urban and orchards, and the landscape pattern shows the distribution characteristics of urban, farmland in the western dam area, and orchards in the eastern mountainous area; the dominant landscape of ecological protection scenario is forest, urban, and rural residential and industrial mining; and the landscape pattern shows the distribution characteristics of urban and rural residential and industrial mining, orchards, farmland in the western dam area, and forest in the eastern mountainous area. The landscape pattern shows that the western dam area is dominated by urban and rural residential and industrial, while the eastern mountainous area is dominated by forests and orchards. The integrated scenario has the highest potential for the future, and its economic, ecological, and comprehensive benefits can be optimized, which is the best spatial layout of the landscape pattern in the study area in the target year. [ABSTRACT FROM AUTHOR]

Background: Patients with follicular lymphoma (FL) who experience disease progression within 24 months (POD24) have inferior outcomes. The tumor immune microenvironment (TIME) plays a crucial role in pathogenesis and progression of follicular lymphoma (FL). However, TIME evolution during progression of disease within 24 months (POD24) is elusive. Methods: Spatially resolved and single-cell image mass cytometry with a panel of 36 metal-tagged antibodies was used to quantitatively analyze the TIME structure in 13 paired FLs at diagnosis and POD24. Results: Follicles and peri-follicular regions were well dissected in structure. Peri-follicular regions represented a barrier for immune infiltration into the follicles. More FL-cells in the peri-follicular regions suffered CD8+T cells attacks under simultaneous protection of regulatory T cells (Tregs) and/or macrophages compared with that in the follicles irrespective of POD24. During POD24, increased CD163− macrophages with PD-1 ligand upregulation and decreased CD8+T cells with upregulated LAG-3 expression around FL-cells were observed in the follicles. Spatial analyses demonstrated that FL-cells interacted more intimately with macrophages than with Tregs and less with cytotoxic T cells in both peri-follicular regions and follicles during POD24. In comparison, macrophages also cooperated more frequently with Tregs to simultaneously hijack FL-cells, creating an enhanced immunosuppressive environment in both peri-follicular and follicular regions during POD24. Conclusions: Peri-follicular regions function as a barrier by recruiting both CD8+T cells and immunosuppressive cells, protecting follicular FL-cells from immune attack at diagnosis or POD24. FL-cells reside in a more immune-compromised microenvironment and evade immune cell attacks during POD24. Novel immunotherapeutic approaches harnessing LAG-3, macrophages, and Tregs will be empowered to overcome poor outcomes in patients with FL POD24. [ABSTRACT FROM AUTHOR]

The 74Se is one of 35 p-nuclei, and 82Se is a r-process only nucleus, and their (n, Îł) cross sections are vital input parameters for nuclear astrophysics reaction network calculations. The neutron capture cross section in the resonance range of isotopes and even natural selenium samples has not been measured. Prompt Îł -rays originating from neutron-induced capture events were detected by four C6D6 liquid scintillator detectors at the Back-n facility of China Spallation Neutron Source (CSNS). The pulse height weighting technique (PHWT) was used to analyze the data in the 1 eV to 100 keV region. The deduced neutron capture cross section was compared with ENDF/B-VIII.0, JEFF-3.2, and JENDL-4.0, and some differences were found. Resonance parameters were extracted by the R -matrix code SAMMY in the 1 eVâ€"1 keV region. All the cross sections of natSe and resonance parameters are given in the datasets. The datasets are openly available at http://www.doi.org/10.11922/sciencedb.j00113.00019. [ABSTRACT FROM AUTHOR]

• A discrete computing method for fuel–air mixing of various fuels is proposed. • A unified turbulent combustion model for direct injection engines is developed. • Collision map is used to refine collision regimes and mimic real-time mixing mode. • Fuel-air exchange mechanisms of various effective collision regimes are quantified. • Flexible fuels' spray combustion behaviors are accurately predicted. Application of low- and zero-carbon fuels is a prevailing trend to reduce engine emissions, while fuel direct injection (DI) is an important way. But the increasing fuel type diversity and injection strategy complexity are beyond the application scope of existing model-based prediction tools. To fill in the gaps, this study developed a unified turbulent mixing and combustion model applicable for various gaseous and liquid fuels. The jet model could accurately capture the penetration under varying injection strategies. Considered the effects of fuel thermo-physical properties and dynamic states, a probability density function (PDF)-particle collision map coupling model was proposed and applied to various fuels. The particles' discrete method greatly cut down the number of particles processed, remarkably speeding up the computation; and the regions of effective particles collision regimes were refined, vividly mimicking the real-time fuel–air mixing mode, with the specific binary particles exchange mechanisms proposed. Besides, the influence factors from practical engine operations on fuel–air mixing rate were thoroughly considered. Finally, the model accuracy was validated by various fuels with different injection strategies. The results showed that, regardless of the minor difference due to the assumption of constant jet cone angle, the prediction error was generally within 5% for spray tip penetration (S tip ) and heat release rate (HRR), with a prediction accuracy over 96% offered for the combustion efficiency (CE). The high accuracy and robustness guarantee a trustworthy prediction and analysis on the spray combustion behaviors of flexible-fuel DI engines with variable injection strategies, which greatly benefits the engine builders to deliver quick and pragmatic industry feasible solutions for engine performance optimization. [ABSTRACT FROM AUTHOR]

Building an accurate disease risk prediction model is an essential step in the modern quest for precision medicine. While high-dimensional genomic data provides valuable data resources for the investigations of disease risk, their huge amount of noise and complex relationships between predictors and outcomes have brought tremendous analytical challenges. Deep learning model is the state-of-the-art methods for many prediction tasks, and it is a promising framework for the analysis of genomic data. However, deep learning models generally suffer from the curse of dimensionality and the lack of biological interpretability, both of which have greatly limited their applications. In this work, we have developed a deep neural network (DNN) based prediction modeling framework. We first proposed a group-wise feature importance score for feature selection, where genes harboring genetic variants with both linear and non-linear effects are efficiently detected. We then designed an explainable transfer-learning based DNN method, which can directly incorporate information from feature selection and accurately capture complex predictive effects. The proposed DNN-framework is biologically interpretable, as it is built based on the selected predictive genes. It is also computationally efficient and can be applied to genome-wide data. Through extensive simulations and real data analyses, we have demonstrated that our proposed method can not only efficiently detect predictive features, but also accurately predict disease risk, as compared to many existing methods. Author summary: Accurate disease risk prediction is an essential step towards precision medicine. Deep learning models have achieved the state-of-the-art performance for many prediction tasks. However, they generally suffer from the curse of dimensionality and lack of biological interpretability, both of which have greatly limited their applications to the prediction analysis of whole-genome sequencing data. We present here an explainable deep transfer learning model for the analysis of high-dimensional genomic data. Our proposed method can detect predictive genes that harbor genetic variants with both linear and non-linear effects via the proposed group-wise feature importance score. It can also efficiently and accurately model disease risk based on the detected predictive genes using the proposed transfer-learning based network architecture. Our proposed method is built at the gene level, and thus is much more biologically interpretable. It is also computationally efficiently and can be applied to whole-exome sequencing data that have millions of potential predictors. Through both simulation studies and the analysis of whole-exome data obtained from the Alzheimer's Disease Neuroimaging Initiative, we have demonstrated that our method can efficiently detect predictive genes and it has better prediction performance than many existing methods. [ABSTRACT FROM AUTHOR]

If the load exercise exceeds a certain degree, it will lead to sports injury. The main reason for this phenomenon is that the human body produces a lot of free radicals after sports training. Free radicals can attack human cells and cause lipid peroxidation to damage cell membrane. The human body can improve the antioxidant capacity of the body by supplementing some trace elements. Selenium, iodine, zinc, iron, and calcium are all trace elements that contribute to antioxidants in the body. Nanoselenium is of great interest among many immune modulators because of its high antioxidant properties and remarkable immune protective function. In this paper, grey rabbits were used as the research object to carry out aerobic endurance training. Nanoselenium and placebo were supplemented in each group. The evaluation model of nanoselenium on aerobic endurance exercise was established by system control method, exhaustion compensation method, and analytic hierarchy process. The adaptive changes of nanoselenium on aerobic endurance exercise of grey rabbits were studied in detail, and the effects of exercise and antioxidant on the body were observed. Compared with the previous research methods, the difference is that the decentralized control theory is introduced as the guiding ideology of the research. According to the experimental results, the accuracy of the overall experimental results is improved by about 20%, and the accuracy is higher, which has certain practical value. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: The dimethylpyridylamidohafnium catalyst was used to synthesize 1‐butene/cyclohexene and 1‐butene/vinylcyclohexane random copolymers, which have extra six‐membered cyclic co‐units in main chain and side chain, respectively. For the obtained copolymers of different incorporations, the crystallization from amorphous melt and the solid phase transition from tetragonal to trigonal phases were investigated with differential scanning calorimetry. Both of the incorporated cyclic co‐units decrease the crystallization kinetics, but the presence of cyclohexene keeps the melting temperature of copolymers constant. Interestingly, the strong memory effect of crystallization can appear at the elevated temperature even above the equilibrium melting temperature, as the content of co‐units was increased. The 1‐butene/vinylcyclohexane copolymer with 1.52 mol% co‐units exhibits a rather strong memory effect with the broad Domain IIa width of 43°C and the crystallization temperature raising of 24°C. Furthermore, the transition of tetragonal phase into trigonal phase was also explored for different co‐units and incorporations. It was found that both of the cyclohexene co‐units and vinylcyclohexane co‐units effectively slow down the kinetics of phase transition. However, the vinylcyclohexane co‐units have a much higher efficiency in suppressing phase transition than the cyclohexene co‐units, where 0.53 mol% vinylcyclohexane can completely stop phase transition within 1320 h. Considering the fact that copolymers with vinylcyclohexane co‐units actually have lower glass transition temperatures, it was indicated that the suppression of phase transition is also largely influenced by the steric co‐units in the side chain for the helical and positional adjustments, not only by the segmental mobility. [ABSTRACT FROM AUTHOR]

Mesoporous bioactive glass (MBG) is a potential biomedical material in bone defect repairment because of its bioactivity, biocompatibility, and osteoinduction properties. Here we report that Mg-doped MBG scaffold with 3:1 Ca/Mg ratio (MBG-Ca/Mg-3) is good for MC3T3-E1 osteoblast differentiation and mineralization. Mimicking bone extracellular matrix structure by electrospinning, we used MBG-Ca/Mg-3 adsorbed with Osteocalcin-Osteopontin-Biglycan (OOB), a new unique matrix fusion protein, to form OOB@MBG-Ca/Mg-3 scaffold, which has multifunctional ability in calvarial bone defect repairment in vivo. Intriguingly, we found that OOB@MBG-Ca/Mg-3 scaffold increases the expression of osteoblastic marker genes, including bone morphogenetic protein (Bmp2), osteopontin (Opn), Osterix , Runx2 through activation of ERK1/2. We concluded that OOB@MBG-Ca/Mg-3 scaffold promotes osteoblast differentiation and mineralization through ERK1/2 pathway and it can also enhance bone formation in vivo , which provides a new biomaterial in bone tissue engineering. [ABSTRACT FROM AUTHOR]

We derive the solvability conditions and a formula of a general solution to a Sylvester-type matrix equation over Hamilton quaternions. As an application, we investigate the necessary and sufficient conditions for the solvability of the quaternion matrix equation, which involves η -Hermicity. We also provide an algorithm with a numerical example to illustrate the main results of this paper. [ABSTRACT FROM AUTHOR]

This article investigates the state interval observation problem for a class of continuous and discrete‐time linear time‐varying (LTV) systems with bounded uncertainties separately. First, by utilizing both the LTV transformation and the solutions to a type of time‐varying fully‐actuated Sylvester equations, a time‐dependent standard interval observer (IO) is established in a parametric form with some design degrees of freedom. Second, a new time‐dependent structure of Luenberger‐type IOs is proposed to relax the limitation of the LTV transformation‐based design method. Further, its sufficient existence conditions are given in virtue of positive system theory. Meanwhile, a parametric design technique of such an IO for uncertain LTV systems is also raised under rank conditions. Third, the obtained results are extended to the discrete‐time systems. Finally, the correctness and benefits of the proposed methods are verified using some numerical examples. [ABSTRACT FROM AUTHOR]

As a marine engine fuel of great concern, ammonia needs to be mixed with another high reactive fuel to improve its combustion performance. In this work, the combustion performance of NH 3 /NH 4 NO 2 and NH 3 /H 2 was compared under different boundary conditions (excess air coefficient, initial temperature, pressure and mixing ratio). The numerical simulation of compression combustion is carried out under different power loads. The addition of ammonium nitrite decreases the ignition requirement of ammonia and shortens the ignition delay time of the mixture fuel. The boundary conditions of compression ignition can be reduced by mixing hydrogen and mixing ammonium nitrite, but it is not enough to achieve compression ignition under NH 3 /H 2 mode. The addition of 30% ammonium nitrite can reduce the intake temperature to 300–360 K, which makes the compression ignition of the mixed fuel feasible. Meanwhile, in order to reduce the high in-cylinder combustion pressure and improve the combustion performance of the mixed fuel, the fuel injection strategy was proposed to achieve constant combustion pressure of 30 MPa under the premise of less power loss, which is a potential solution for the combustion of ammonia fuel. • The combustion law of NH 3 /NH 4 NO 2 is studied. • Temperature affects ammonia combustion performance more than other conditions. • The higher mixing ratio within the study, the better the combustion performance. • NH 4 NO 2 reduces the compression ignition boundary more than H 2. • A reliable compression ignition improvement scheme is proposed. [ABSTRACT FROM AUTHOR]

Urban commercial complex is the product of social and economic development, as well as the inevitable trend of commercial development. The public space design of urban complex project is an important link in its development process, which is the link between the contact and the building, the city and the building, and the external image display of the complex. Therefore, choosing a suitable and excellent public space design scheme is of great significance to show the superiority of the complex project and improve the project satisfaction and the sustainable operation in the later stage. This paper first defines the concept of urban complex public space and focuses on the analysis of the urban complex public space from four aspects of constituent elements, functional classification, design theory, and principle. Then, the Delphi method is used to determine 26 evaluation indicators to evaluate the urban complex public space design scheme, and the relevant index data of 20 urban complex public space design schemes are collected. The grey correlation analysis method is used to analyze the correlation degree between each indicator and the scheme winning bid. The final evaluation system of urban complex public space design scheme is obtained after removing the 8 indicators with low correlation degree. Support vector mechanism was used to build the optimization model of urban complex public space design scheme, and its accuracy was verified, which provides a relatively simple and quantitative method for urban public space design in the future, helps to improve the city's business structure, improves the business environment of the city, makes the commercial complex more effectively play its own characteristics and advantages, effectively stimulates the vitality of urban space, and creates more perfect architectural space and urban space for people. [ABSTRACT FROM AUTHOR]

Purpose: Embedding carbon fiber reinforced plastics (CFRP) bars in the tension zone of reinforced concrete (RC) beams is a widely used reinforcement method, which has the advantages of strong anti-peel ability and high utilization of tensile materials. To further improve the flexural bearing capacity of RC beams, a new composite reinforcement method using the UHPC layer in the compressive zone of RC beams is proposed based on embedding CFRP bars in the tension zone of RC beams. Design/methodology/approach: The finite element model of an RC experimental beam with CFRP bars embedded in the tension zone was carried out by ABAQUS. Besides, the reliability of the finite element model results was verified by comparing with the experimental results. On this basis, the flexural reinforcement effect of CFRP bars and UHPC layers on RC beams was analyzed. Findings: Calculation results show the flexural bearing capacity of the beam strengthened by the new method is 15.9%, which is higher than that of the unreinforced beam, and 10.4% higher than that of the beam strengthened only with CFRP bars. The beam ductility ratio of the new method is 8.25%, which is slightly higher than that of the unreinforced beam and equal to that of the beam reinforced only with CFRP bars embedded in the tension zone. The effectiveness of the new method is further verified by using the analytical calculation method. Originality/value: A new flexural reinforcement method for reinforced concrete beams is proposed, and the effectiveness of the method was verified by experiments and finite element model. The flexural bearing capacity and ductility of the new method were analyzed based on the load-deflection curve. Finally, the possibility of the new method was verified by analytical analysis. [ABSTRACT FROM AUTHOR]

Global warming issues and fossil fuel depletion crisis have forced transportation industry to seek clean engine fuels both liquid and gaseous. Dual-fuel mode with high-pressure direct injection (HPDI) has been recognized as mainstream method in developing flexible-fuel internal combustion engines (ICEs). But flexible-fuels' physicochemical properties and spray combustion characteristics under HPDI have changed a lot. Unfortunately, there is currently no universal model for predicting spray combustion behaviors and analyzing performance of flexible-fuel ICEs. Therefore, this paper aims to develop a novel spray combustion model and provide optimal injection and combustion strategies for performance improvement of low- and zero-carbon HPDI ICEs. Based on balance of momentum change and vortex ring drag force, the jet spray effective injection velocity is obtained. Then the jet spray penetration under varying injection rate is solved. Finally, the developed model is established and validated experimentally, with the spray combustion characteristics of various fuels investigated. The results show that the developed model has a good accuracy and robustness for flexible-fuels' characteristic analysis. Meanwhile, multiple-injection could increase the combustion efficiency (CE) over 10.27 % than single-injection, and CE increases with dwell time. Moreover, CE of H 2 in nitrogen-oxygen (N 2 –O 2) atmosphere is 10.15 % higher than that in argon-oxygen (Ar–O 2) atmosphere. [Display omitted] • A universal spray combustion model for direct injection engines is developed. • The developed model applies to both liquid and gaseous fuels. • Spray combustion characteristics under varying injection rates can be predicted. • The effective injection velocity of vortex ring is derived. • Optimization strategies for various fuels' combustion efficiency are concluded. [ABSTRACT FROM AUTHOR]

Multi-source unsupervised domain adaptation aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain. Existing methods either seek a mixture of distributions across various domains or combine multiple single-source models for weighted fusion in the decision process, with little insight into the distributional discrepancy between different source domains and the target domain. Considering the discrepancies in global and local feature distributions between different domains and the complexity of obtaining category boundaries across domains, this paper proposes a novel Active Dynamic Weighting (ADW) for multi-source domain adaptation. Specifically, to effectively utilize the locally advantageous features in the source domains, ADW designs a multi-source dynamic adjustment mechanism during the training process to dynamically control the degree of feature alignment between each source and target domain in the training batch. In addition, to ensure the cross-domain categories can be distinguished, ADW devises a dynamic boundary loss to guide the model to focus on the hard samples near the decision boundary, which enhances the clarity of the decision boundary and improves the model's classification ability. Meanwhile, ADW applies active learning to multi-source unsupervised domain adaptation for the first time, guided by dynamic boundary loss, proposes an efficient importance sampling strategy to select target domain hard samples to annotate at a minimal annotation budget, integrates it into the training process, and further refines the domain alignment at the category level. Experiments on various benchmark datasets consistently demonstrate the superiority of our method. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the design and optimization of landing gear buffers to improve the landing-phase comfort of civil aircraft. Design/methodology/approach: The vibration comfort during the landing and taxiing phases is calculated and evaluated based on the flight-testing data for a type of civil aircraft. The calculation and evaluation are under the guidance of the vibration comfort standard of GB/T13441.1-2007 and related files. The authors establish here a rigid-flexible coupled multibody dynamics finite element model of one full-size aircraft. Furthermore, the authors also implement a dynamic simulation for the landing and taxiing processes. Also, an analysis of how the main parameters of the buffers affect the vibration comfort is presented. Finally, the optimization of the single-chamber and double-chamber buffers in the landing gear is performed considering vibration comfort. Findings: The double-chamber buffer with optimized parameters in landing gear can improve the vibration comfort of the aircraft during the landing and taxiing phases. Moreover, the comfort index can be increased by 25.6% more than that of a single-chamber type. Originality/value: To the best of the authors' knowledge, this study first investigates the evaluation methods and evaluation indexes on the aircraft vibration comfort, then further conducts the optimization of the parameters of landing gear buffer with different structures, so as to improve the comfort of aircraft passengers during landing process. Most of the current studies on aircraft landing gear have focused on the strength and safety of the landing gear, with very limited research on cabin vibration comfort during landing and subsequent taxiing because of the coupling of runway surface unevenness and airframe vibration. [ABSTRACT FROM AUTHOR]