In this paper, a voice coil motor (VCM) actuated fast tool servo (FTS) system is developed for diamond turning. To guide motions of the VCM actuator, a crossed double parallelogram flexure mechanism is selected featuring totally symmetric structure with high lateral stiffness. To facilitate the determination of the multi-physical parameters, analytical models of both electromagnetic and mechanical systems are developed. The designed FTS with balanced stroke and natural frequency is then verified through the finite element analysis. Finally, the prototype of the VCM actuated FTS is fabricated and experimentally demonstrated to have a stroke of ±59.02 μm and a first natural frequency of 253 Hz. By constructing a closed-loop control using PID controller with the internal-model based resonant controller, the error for tracking a harmonic trajectory with ±10 μm amplitude and 120 Hz frequency is obtained to be ±0.2 μm, demonstrating the capability of the FTS for high accuracy trajectory tracking.

Inland lake variations are considered sensitive indicators of global climate change. However, human activity is playing as a more and more important role in inland lake area variations. Therefore, it is critical to identify whether anthropogenic activity or natural event is playing as the dominant factor in inland lake surface area change. In this study, we proposed a Douglas-Peucker simplification algorithm and bend simplification algorithm combined method to locate major lake surface area disturbances; these disturbances were then characterized to extract the time series change features according to documented records; and the disturbances were finally classified into anthropogenic or natural. We took the nine lakes in Yunnan Province as test sites, a 31 years long (from 1987 to 2017) time series Landsat TM/OLI images and HJ-1A/1B used as data sources, the official records was used as references to aid the feature extraction and disturbance identification accuracy. Results of our method for both disturbance location and the disturbance identification could be concluded as follows: 1) The method can accurately locate the main lake changing events based on the time series lake surface area curve. The accuracy of this model for segmenting the lake area time series curves in our study area was 95.24%. 2) Our proposed method achieved an overall accuracy of 91.67%, with F-score of 94.67 for anthropogenic disturbances and F-score of 85.71 for natural disturbances. 3) According to our results, lakes in Yunnan Provence, China, have undergone extensive disturbances, and the human-induced disturbances occurred almost twice as often as natural disturbances, indicating intensified disturbances caused by human activities. This inland lake area disturbance identification method is expected to uncover whether a disturbance to inland lake area is human activity-induced or natural event.

Placental growth factor (PlGF or PGF) is a member of the VEGF family, which is known to play a critical role in pathological angiogenesis, inflammation, and endothelial cell barrier function. However, the molecular mechanisms by which PlGF mediates its effects in non-proliferative diabetic retinopathy (DR) remain elusive. In this study, we performed transcriptome-wide profiling of differential gene expression for human retinal endothelial cells (HRECs) treated with PlGF antibody. The effect of antibody treatment on the samples was validated using trans-endothelial electric resistance (TEER), and western blot. A total of 3760 genes (1750 upregulated and 2010 downregulated) were found to be differentially expressed between the control and PlGF antibody treatment group. These differentially expressed genes (DEGs) were used for gene ontology and enrichment analysis to identify gene function, signal pathway, and interaction networks. The gene ontology results revealed that catalytic activity (GO:0003824) of molecular function, cell (GO:0005623) of the cellular component, and cellular process (GO:0009987) were among the most enriched biological processes. Pathways such as TGF-β, VEGF-VEGFR2, p53, apoptosis, pentose phosphate pathway, and ubiquitin-proteasome pathway, were among the most enriched, and TGF-β1 was identified as a primary upstream regulator. These data provide new insights into the underlying molecular mechanisms of PlGF in mediating biological functions, in relation to DR.

Categorical variables are common in spatial data analysis. Traditional analytical methods for deriving probabilities of class occurrence, such as kriging-family algorithms, have been hindered by the discrete characteristics of categorical fields. This study introduces the theoretical backgrounds of linear Bayesian updating (LBU) approach for spatial classification through expert system. Transition probabilities are interpreted as expert opinions for updating the prior marginal probabilities of categorical response variables. The main objective of this paper is to present the solid theoretical foundations of LBU and provide a categorical random field prediction method which yields relatively higher classification accuracy compared with conventional Markov chain random field (MCRF) approach. A real-world case study has also been carried out to demonstrate the superiority of our method. Since the LBU idea is originated from aggregating expert opinions and not restricted to conditional independent assumption (CIA), it may prove to be reasonably adequate for analyzing complex geospatial data sets, like remote sensing images or area-class maps.

The study comprehensively evaluated the prognostic roles of PLR, NLR, MLR, BLR, and ELR in patients with acute exacerbation chronic obstructive pulmonary disease (AECOPD). 619 patients with AECOPD and 300 healthy volunteers were retrospectively included into the study. The clinical characteristics containing laboratory findings of the AECOPD patients and the blood cell counts (CBCs) of the healthy volunteers were collected. Compared with the healthy volunteers, PLR, NLR, and MLR were elevated in COPD patients in stable condition, and were further ele-vated during exacerbation. ELR showed the opposite trend. PLR, NLR, and MLR were all posi-tively correlated with hospital LOS as well as CRP. In contrast, ELR was negatively correlated with hospital LOS as well as CRP. Elevated PLR, NLR, and MLR were all associated with more serious airflow limitation in AECOPD. Elevated PLR, NLR, and MLR were all associated with increased in-hospital mortality while Elevated ELR was associated with decreased in-hospital mortality in AECOPD. A nomogram was construct to predict in-hospital mortality in AECOPD. The nomo-gram had a C-index of 0.850 (95% CI: 0.799 – 0.901) with good predictive value and clinical ap-plicability. In summary, PLR, NLR, MLR, and ELR served as predictors for clinical outcomes in patients with AECOPD.

The development of using mitochondrial transplantation in medical therapy are currently discussed. According to the endosymbiotic theory, the movement of mitochondria between different cells is possible. Therefore, an idea of transferring the mitochondria purified from the cells with a limited lifespan to shorten the lifespan of immortal cancer cells was generated. Human umbilical vein endothelial cell (HUVEC) is a kind of primary cell with a limited lifespan. In the present study, the mitochondria purified from HUVEC were applied to alter the malignance of B16F10 melanoma cell. In the comparison of the basic function of mitochondria, HUVEC mitochondria exhibited a higher mitochondrial membrane potential (MMP), while the lower levels in ATP, mitochondrial DNA (mt-DNA) and mitochondrial protein (mt-protein) as compared to melanoma B16F10. After transplanted the B16F10 with HUVEC mitochondria, the migration, invasion, and the proteins involved in cancer stemness were decreased, however, the proteins involved in cell proliferation, such as cyclin D1 and cyclin E1 were increased. In addition, the levels of ATP, mt-DNA and mt-protein of B16F10 were also reduced. As for the dynamics of mitochondria, the reduced expressions of DRP1 and LC3 II revealed that transferred mitochondria can attenuate the mitophagy of B16F10. In mice, inoculated the B16F10 carrying the transplanted HUVEC mitochondria resulted in the larger size of tumor, which is corresponded to the higher levels of cyclin D1 and E1. Interestingly, the lower expressions of N-cadherin, α-SMA and MMP-9 reveled the tumor were decreased in mesenchymal characteristics. Therefore, despite the HUVEC mitochondria did not inhibit the proliferation of B16F10, the metastatic characteristic was reduced.

Breast cancer is the most common malignancies in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER, PR and HER2 expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether HDACi would be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enrich breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence based live cell non-invasive apoptosis detection sensor (IADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also be accompanied with chemotherapeutic agent such as doxorubicin to synergic drug sensitivity on TNBC cell (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in clinic.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rain water. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima (2019). The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increases approximately 17%~18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

Abstract：The brain often switches freely between focused attention and divergent thinking, and the default mode network (DMN) is activated during brain rest. The discovery, function and characteristics of default mode network all indicate that learning does not stop when the brain "rests". Mental disease can lead to dysfunctional default mode networks, which affects learning adversely. Therefore, default mode network plays an important role in learning. Neural activities such as β-wave rhythm regulation, "subconscious" divergence mode initiation, hippocampal function and neural replay occur during default mode, which also explain that "rest" promotes learning. This paper reveals the role and neural mechanism of default mode network in learning from the neural level, discusses the essential role default mode network plays in learning, and default mode network enables rest to promote learning.

In order to better plan new or update sewer pipe condition assessment protocols, this paper presents systematic comparisons of four most widely-used sewer condition assessment protocols, including the fourth edition of Sewer Rehabilitation Manual (SRM-4) in UK, Pipeline Assessment and Certification Program (PACP) in America, Sewer Physical Condition Grading Protocols (SPCCM) in Canada, and Technical Specification for Inspection and Evaluation of Urban Sewer (TSIEUR) in China. In qualitative comparison, the defects, deduct values and assessment methods of the four protocols were analyzed; in quantitative comparison, protocols were used to evaluate the same 182 sewer pipe segments based on field data and the assessment results were compared. It was found that SRM-4 are the most optimistic with 59% pipes being Grade 1 and Grade 2, while SPCCM gives the most pessimistic results with 62% pipes being Grade 3 and Grade 4. Assessment results by PACP and TSIEUR are in the middle. The main reasons for the different evaluation results were due to the different weight of defect and evaluation methods used.

Coffee processing generates a huge amount of waste which contains many natural products. Here, we report the discovery of a panel novel cell-penetrating and metal-ion binding microproteins designated coffeetide cC1a-c and cL1-6 from the husk of two popular coffee plants, Coffea canephora and Coffea liberica, respectively. Combining sequence determination and database search, we showed that the prototypic coffeetide cC1a is a 37-residue, eight-cysteine microprotein with a hevein-like cysteine motif but without a chitin-binding domain. NMR determination of cC1a revealed a compact structure that confers it resistance to heat and proteolytic degradation. Disulfide mapping together with chemical synthesis revealed that cC1a has a ginsentide-like, and not a hevein-like, disulfide connectivity. In addition, transcriptomic analysis showed that the 98-residue micrcoproten-like coffeetide precursor contains a three-domain arrangement like ginsentide precursors. Molecular modeling together with experimental validation revealed a Mg2+ and Fe3+ binding pocket at the N-terminus formed by three glutamic acids. Importantly, cC1a is amphipathic with a continuous stretch of 19 apolar amino acids, and which enables its cell penetration to target intracellular proteins, despite being highly negatively charged. Our findings suggest that coffee by-products could provide a source of ginsentide-like bioactive peptides that have potential to target intracellular proteins.

In complex systems constrained by multiple factors, it is of great significance to accurately identify the key influencing factors for mastering the evolution and development law of the system and obtaining scientific decision-making suggestions or schemes. At present, the method based on experimental simulation is limited by the difficulty of system model construction; the method based on decision trial and Evaluation laboratory (DEMATEL) involves a wide range of subjects and is greatly influenced by subjective factors. In view of this, we propose a novel model based on heuristic causal inference. The model uses the FCI algorithm with prior knowledge to learn the global causal network among multiple factors of the complex system. The causal effect among variables in the causal network is calculated by using heuristic causal inference method. Specifically, the causal path contribution degree of cause variable to target variable is calculated to replace the causal effect of each cause variable to target variable. The key influencing factors in the system are screened out according to the contribution degree of causal pathways. Based on the dataset generated in the production process of a semiconductor manufacturing system, we carried out simulation experiments, identified several factors that have a key impact on product quality, and proved the feasibility and effectiveness of the proposed model.

COVID-19 may not be a ‘youth disease’ but nevertheless impacts the life of young people dramatically, loneliness and negative mood being an unexpected additional pandemic. Many young people rely on social media for their feeling of connectedness with others. However, social media are suggested to have many negative effects on people’s anxiety. Instead of self-disclosing to others, design may develop alternatives to employ social robots for self-disclosure. In a follow-up on Duan et al. (2021), we report on a lab experiment of self-disclosing negative emotions to a social-media group as compared to writing a conventional diary journal or to talk to an AI-driven social robot after negative mood induction (i.e. viewing shocking earthquake footage). Participants benefitted the most from talking to a robot rather than from writing a journal page or sharing their feelings on social media. Self-disclosure on social media or writing a journal page did not differ significantly. In the design of interventions for mental well-being, human helpers thus far took center stage. Based on our results, we propose design alternatives for an empathic smart-home, featuring social robots and chatbots for alleviating stress and anxiety: a social-media interference chatbot, smart watch plus speaker, and a mirror for self-reflection.

In this work, zinc oxide (ZnO) nanoparticles were modified in a circulating fluidized bed through argon and hydrogen (Ar-H) alternative-current (AC) arc plasma, which shows the characteristics of non-equilibrium and equilibrium plasma at the same time. In addition, a circulating fluidized bed with two plasma jets was used for cyclic processing. The catalytic degradation performance on Rhodamine B (Rh B) by Ar-H plasma modified ZnO and pure ZnO was tested in aqueous media to identify the significant role of hydrogen atoms in Rh B degradation mechanism. Meanwhile, the effects of plasma treatment time on the morphology, size and photocatalytic performance of ZnO were also investigated. The results demonstrated that ZnO after 20 minutes-treatment by Ar-H plasma showed Rh B photocatalytic degradation rate is ten times greater than that of pure ZnO, and the reaction follows a first-kinetics for the Rh B degradation process. Furthermore, the photocatalyst cycle experiment curve exhibited that the modified ZnO still displays optimum photocatalytic activity after five cycles of experiment. The improvement of photocatalytic activity and luminescence performance attributes to the significant increase of the surface area, and the introduction of hydrogen atoms on the surface also could enhance the time of carrier existence where the hydrogen atoms act as shallow donors.

Establishing an accurate mathematical model is the foundation of simulating the motion of marine vehicles and structures, and it is the basis of modeling-based control design. System identification from observed input-output data is a practical and powerful method. However, for modeling objects with different characteristics and known information, a single modeling framework can hardly meet the requirements of model establishment. Moreover, there are some challenges in system identification, such as parameter drift and overfitting. In this work, three robust methods are proposed for generating ocean hydrodynamic models based on Bayesian regression. Two Bayesian techniques, semi-conjugate linear regression and noisy input Gaussian process regression, are used for parametric and nonparametric gray-box modeling and black-box modeling. The experimental free-running tests of the KVLCC2 ship model and a multi-freedom wave energy converter (WEC) are used to validate the proposed Bayesian models. The results demonstrate that the proposed schemes for system identification of the ship and WEC have good generalization ability and robustness. Finally, the developed modeling methods are evaluated considering the aspects required conditions, operating characteristics and prediction accuracy.

In this study, a three-dimensional bioelectrochemical reactor system (3D-BERs) with granular activated carbon (GAC) epitomizes a novel treatment technology for treating nitrate-polluted water. The conventional denitrification process faces many challenges, including the huge demand for organic carbon, long-term accumulation of intermediate products, and the adaptation period. Results shown that under the optimal conditions of the COD/NO3--N ratio was 1.5, the denitrification efficiency reached 98.62%, when compared to 81.12% at COD/ NO3--N ratio of 3.5, and the initial pH of 7.5 ± 0.5, NO3--N was entirely removed at 2.2 h without accumulation of nitrite. The high initial ratio of NO2--N/NO3--N is mainly to accelerate the denitrification rate by accelerating the reduction of nitrite. Denitrification process followed by zero-order kinetics linear model for at different concentrations of inlet NO3--N, and achieved higher denitrification rate at greater inlet NO3--N concentration. High-throughput sequencing shows that the community structure and relative abundance of bacteria changed significantly, especially at the genes and the phyla level in immobilized GAC particles. Microbial composition enhanced the removal of nitrogen at the inner surface (IS) and bottom surface (BS) of immobilized GAC carriers. Therefore, this system is expected to be a more efficient and useful supplement or a cost-effective alternative compared to the traditional low carbon to nitrogen wastewater treatment system.

Water quality retrieval for small urban waterbodies by remote sensing get used to be difficult due to coarse spatial resolution of the remote sensing imagery. The recently launched Sentinel-2 produces imagery with a spatial resolution of 10 m. It provides an opportunity to solve the problem of retrieving water quality for small waterbodies. Additionally, many water management issues also require fine resolution of imagery, e.g. illegal discharge to an urban waterbody. Since illegal discharges are an important issue for urban water management, chemical oxygen demand (COD), total phosphorous (TP), and total nitrogen (TN) were chosen as the target parameters for water quality retrieval in this study. COD, TP and TN, however, are non-optically active parameters. There were limited studies in the past to retrieve these parameters in comparison with optically active parameters, e.g. Chlorophyll-A etc. This study compared three machine learning models, namely Random Forest (RF), Support Vector Regression (SVR), and Neural Networks (NN), to investigate the opportunity to retrieve the above non-optically active parameters. Results showed that R² of TP, TN, and COD by NN, RF and SVR were 0.94, 0.88, and 0.86, respectively. The performances of water quality retrieval for these non-optically active parameters were significantly improved by the optimized machine learning models. These models hence solved the problem to use remote sensing data to retrieve these non-optically active water quality parameters and provided a new monitoring strategy for small waterbodies. Water quality mapping obtained by Sentinel-2 imagery provided a full spatial coverage of the water quality characterization for the entire water surface. Compared with water samples collecting and testing, it greatly reduced labor cost, reagents cost, and waste treatment cost. It also may help identify illegal discharges to urban waterbodies. The method developed in this research provides a new practical and efficient water quality monitoring strategy in managing water with consideration of environmental sustainability.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disorder most commonly caused by mutations disrupting the reading frame of the dystrophin (DMD) gene. DMD codes for dystrophin, which is critical for maintaining the integrity of muscle cell membranes. Without dystrophin, muscle cells receive heightened mechanical stress, becoming more susceptible to damage. An active body of research continues to explore therapeutic treatments for DMD as well as to further our understanding of the disease. These efforts rely on having reliable animal models that accurately recapitulate disease presentation in humans. While current animal models of DMD have served this purpose quite well, each comes with their own limitations. To help overcome this, clustered regularly interspaced short palindromic repeats (CRISPR)-based technology has been extremely useful in creating novel animal models for DMD. This review focuses on animal models developed for DMD that have been created using CRISPR, their advantages and disadvantages as well as their applications in the DMD field.

In the case that ship operators may not be aware of the potential risks of environmental factors in situation of high causation probability during the initial stage of the geometric probability analysis process, it is likely that higher-grade collision accident measures will not be taken. However, if any risks is told to the ship operators, more effective and intentional measures can be taken in time. Moreover, if the causation probability corresponding to environmental factors is no less than the risk early warning critical value calculated based on historical collision accident data, there would be a high-risk level that a collision may occur. A new method is put forward based on quantitative analysis of environmental factors and previous collision statistics to provide early warning of any accident risk, and a risk early-warning critical value (REWCV) can be obtained based on this simple but highly operational and practical method. A case study of Three Gorges Reservoir in China indicates that the range of environmental factors where the probability of collision accident grows rapidly is consistent with environmental limits defined by Chinese maritime standards. In addition, the relationship between the risk early-warning critical value and the number of previous collision accident is also clarified.

The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.

Copper mine tailings are the residual products after the purification of precious copper from copper ores, and their storage can create numerous environmental problems. Many researchers have used copper mine tailings for preparation of geopolymer. This paper studies the enhancement of the cementitious activity of copper mine tailings in geopolymer system. First, copper mine tailings are activated through a mechanical grinding activation. Afterward, the mechanically activated copper mine tailings are further processed through thermal activation and alkaline roasting activating. The cementitious activity index of copper mine tailings is characterized through the degree of concentration of alkali leaching silicon and aluminum. It was observed that the Si and Al alkali leaching concentration of mechanical activated tailings was increased by 26.03% and 93.33%, respectively. The concentration of Si and Al was increased by 54.19% and 119.92%, respectively. For alkaline roasting activating, roasting time, temperature and (C/N ratio) were evaluated through the orthogonal test, and the best condition was activation for 120 min at 600℃ with C/N ratio is 5:1. In this study, the SEM, XRD and IR analysis show that mechanically activation, thermal activation and alkaline roasting activating can improve the cementitious activity index of copper mine tailings.

The aim of this study was to examine usual daily micronutrient intake of Chinese children based on data from the 2011 China Health and Nutrition Survey. We analyzed data from 4 to 17-year-old participants, who provided dietary data on 3 consecutive days combined with the household weighing method in 2011. Usual daily intake of each nutrient was estimated using a mixed effects model based on the China Food Composition published in 2002 and 2004. The means, medians and percent below Estimated Average Requirements (EAR) were reported for selected micronutrients, including calcium, sodium, potassium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C. For sodium and potassium, means and the distribution of intakes were compared to the Adequate Intake (AI) level. The average usual daily intakes of all micronutrients increase with age and the intakes of boys higher than girls in the same age group. The average of calcium intakes increased from 272mg/d in 4-6y to 391mg/d in 14-17y, but the percentage of inadequate calcium intake remained very high (>96%). The prevalence of inadequacy of calcium was the highest among the mineral nutrients reported in this study. As the requirement of micronutrient increased with age, the percentage of subjects with inadequate intake increased in 11-17 age groups. Among the 14-17y, the percentages of study participants with dietary intakes of calcium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C below the EAR were 96.8%, 18.8%, 37.6%, 72.8%, 36.8%, 91.8%. 85.9% and 75.5%, respectively. Among the 11-13y, the percentages of study participants with dietary intakes of iron, zinc and vitamin A below the EAR were 23.5%, 41.5%, and 41.6%, respectively. Thus, the micronutrients deficiency is a problem in Chinese Children. Nutrition education and intervention programs are needed to address the nutritional gaps.

a sensorless control scheme based on novel power converging law sliding mode observer is suggested to realize the sensorless control for the permanent magnet synchronous motor (PMSM). Firstly, by introducing a new power converging law, the problem of slow converging speed/large chattering value dilemma in the conventional converging law is solved; Secondly, in view of the shortcomings of the conventional position and speed estimation algorithm, the high-frequency buffeting in the sliding mode observer will be expanded, a phase-locked loop (PLL) velocity and position estimation strategy is adopted to replace it. Finally, through Matlab/Simulink modeling and motor speed regulation platform experimental results, the sensorless position and speed estimation technology proposed in this paper can respond to the starting speed command of 1000 r/min within 0.05 s, and the starting process has no overshoot. When disturbed by 10Nm loading, the speed fluctuation value can be controlled within 1%.

With the development of the volume of information exchange and perception increases, the demands for intelligent, miniaturized and integrated optical devices for information acquisition are also increasing. As the core component of optical networks for transmitting information, how to further optimize its structural characteristics to generate richer optical characteristics and apply them to information exchange and optical field control has become a key research hotspot. The introduction of chiral twist characteristics has led to new phenomena and applications in optical field transmission and transformation for traditional optical fibers or microstructured optical fibers (MOF). Therefore, this review mainly starts from the principle of chiral optical fibers, introduces their preparation and latest application scenarios, and finally looks forward to their potential future development prospects.

As hematite ores become lower in grade, finer in grain size, and more complex in compositions, their beneficiation by froth flotation to produce the high Fe grade concentrate has become increasingly more difficult. A systematic and in-depth process mineralogy study based on the multi-element chemical and MLA analysis combined with other characterization techniques was conducted to explore the fundamental reasons for difficulties in refractory hematite flotation separation. The results show that the valuable mineral in the sample was mainly hematite and gangue mineral was primarily quartz. Hematite had a fine particle size distributed over a range of 0~45 μm with a degree of mineral liberation of 90.19%. The particle size of quartz was relatively coarse and was mainly distributed in the range of 20~150 μm with a liberation degree of only 67.72%. Unliberated quartz was mainly associated with hematite and the composite particle content was 36.44%. The rougher flotation tests produced a flotation concentrate of 66.71% TFe grade at a recovery of 65.47%. The screening analysis results with rougher flotation products indicated that the main reasons for the poor performance of rougher flotation were the serious entrainment of fine hematite particles and the difficulty in effective collection of coarse low-grade composite particles. Possible approaches for improving hematite flotation performance have been proposed based on the results from this study.

This study presents a novel approach to analyzing the present value of total profit for non-participating and participating insurance policies in order to determine the optimal profitability of non-participating and participating insurance policies based on applying the approach used in operations research to the field of finance. As such, a comprehensive insurance product evaluation model was developed using both mathematical models and numerical analysis to evaluate the demand for non-participating and participating life insurance policies in response to changes in interest rates. The findings indicate that non-participating life insurance policies offer greater solvency for insurance companies compared to participating policies. The study also highlights the significance of spontaneous and induced demand in determining the total profit of both types of policies. The study concludes that life insurance companies should focus on generating spontaneous consumer demand, reducing induced demand, and implementing the optimal pricing strategy to achieve maximum profits.

Tea (Camellia sinensis) is one of the most popular beverages worldwide. Many types of tea prod-ucts continuously emerge in an endless stream; so, the classification or verification of tea be-comes more difficult. Aroma is a vital indicator of tea quality. The present study deals with the identification of aroma compounds in 18 different kinds of tea belonging to three typical tea va-rieties, including green tea, oolong tea, and black tea, using GC-IMS and GC×GC-O-MS. More-over, the clustering of all 18 tea samples and the in-depth correlation analysis between sensory evaluation and instrumental data were performed using the PCA and OPLS-DA. The results re-vealed that in all 18 kinds of tea, a total of 85 aroma compounds were detected by GC-IMS, whereas 318 were detected by GC×GC-O-MS. The PCA result revealed that green tea, oolong tea, and black tea could be clearly separated based on their peak areas. The OPLS-DA result showed that a total of 49 aroma compounds with VIP value > 1.0 could be considered as the potential in-dicators to quickly classify or verify tea types. This study not only compared the aroma differ-ences across different types of teas, but also provided ideas for the rapid monitoring of tea qual-ity and variety.

RNA interference (RNAi) is one of the main mechanisms for disease resistance and small RNA production in plants. The main proteins involved in RNAi include Dicer-like (DCL), RNA-dependent RNA polymerase (RDR), double-stranded RNA-binding (DRB), and Argonaute (AGO). Juglandaceae contains a variety of important woody plants, and walnuts are one of the four major woody plant groups and one of the four major dried fruits in the world. To clarify the evolution and functional differentiation of RNAi-related proteins in the walnut (Juglans regia) genome, this study integrated various web resources from gene family acquisition to structural analysis and transcriptome data to correlate walnuts and their congeners. The walnut genome has 5 DCL, 13 RDR, 15 DRB and 15 AGO genes, similar genes encoding conserved protein structural domains and conserved motifs with similar subcellular localization. Walnut AGO proteins are classified into three classes and seven subclasses. The DCL is divided into four categories, while RDR is mainly divided into four categories, and DRB can be divided into six categories. The exception is that the copy number of walnut RDR1 is 9, in which seven RDR1 are distributed in clusters on chromosome 16. Purifying selection drove the formation of walnut genes, but protein classes were subjected to varying degrees of purifying selection. Additionally, these results showed some similarity in other plants of the walnut family. Moreover, different RNAi-related genes of walnut produced abundant selective expression in response to different tissues and stresses. In this study, DCL, RDR, DRB and AGO gene families were identified and analysed in the genome of the walnut family for the first time and preliminarily examined the evolution, structure and expression characteristics of these families to provide a preliminary basis for the evolution of the walnut RNAi pathway and breeding research.

Objective: To explore the efficacy and safety of breathing exercises for pain management in cancer survivors. Design: A systematic review. Data sources: Thirteen databases, including PubMed, EMBase, CENTRAL, Medline, CINAHL, JBI, Science Direct, Scopus, SocINDEX, Web of Science, PsycINFO, CNKI, and Wan Fang, were searched from inception to May 24, 2021. Review/analysis methods: Studies that focused on the efficacy of breathing exercises for pain management in cancer survivors were included. Cochrane tools were used for the quality appraisal of the included studies. Due to the heterogeneity of the studies, descriptive data analysis was used to summarize the results. Results: A total of 10 studies were included in this systematic review. Slow pursed lip breathing showed benefits for post-surgical pain. Contradictory findings were identified in the Enhanced Recovery After Surgery breathing exercise for post-surgical pain. Slow deep breathing and Hey-Hu regular breathing techniques were effective for pain management in pediatric cancer patients. The Active Cycle of Breathing Technique and five-minute mindful breathing did not have any statistically significant effects on pain relief. Quality of life was measured in three studies, with some improvement. Only one study addressed adverse events and reported that no adverse events associated with the breathing exercises occurred during the study. Conclusion: This review found some evidence of positive effects of breathing exercises for pain relief in cancer survivors. However, the unsatisfactory methodological quality of the studies prevents its generalizability. More large-scale studies are needed to assess the efficacy and safety of breathing exercises for pain relief in cancer survivors.

We explore the implementation of specific optical properties of armchair graphene nanoribbons (AGNRs) through edge-defect manipulation. This technique employs the tight-binding model in conjunction with the calculated absorption spectral function. Modification of the edge states gives rise to the diverse electronic structures with striking changes in the band gap and special flat bands at low energy. The optical-absorption spectra exhibit exotic excitation peaks and they strongly depend on the type and period of the edge extension. Remarkably, there exist the unusual transition channels associated with the flat bands for selected edge-modified systems. We discover the special rule governing how the edge-defect influences the electronic and optical properties in AGNRs. Our theoretical prediction demonstrates an efficient way to manipulate the optical properties of AGNRs. This might be of importance in the search for suitable materials designed to have possible technology applications in nano-optical, plasmonic and optoelectronic devices.

This paper considers a new approach to the modeling of the vacuum infusion process at the manufacturing three-dimensional composite parts of complex shape. The developed approach and numerical methods are focused on the reliable prediction with the needed accuracy and elimination the unrecoverable defect of composite structure such as the dry spots. The paper presents some experimental results, which demonstrate two cases of dry spots formation in large aircraft composite panels, and analyses the reasons of these defects arising. Our numerical technique is based on the vacuum infusion of the liquid resin into porous preform as the two phase flow, which is described by the phase field equation coupled with the Richards equation describing the fluid motion in unsaturated soils with spatially varied pressure dependant porosity and saturation. This problem statement allowed to correctly reconstruct the resin front motion and formation of inner and outer dry spots depending on its movement. For the rapid detection of preform zones that are suspicious for defect formation two indicators calculated during process simulation are proposed and tested at the numerical experiments. The auxiliary program tool has been developed in MATLAB environment to correctly detect the times of formation, localization and dimensions of the arising dry spots by using the results of the finite element model simulation.

To explore the characteristics of the concentric eyewall of a typhoon during its formation and replacement processes, with Super Typhoon Muifa in 2011 as the example case, the Weather Research and Forecast (WRF) mode was used to carry out a numerical simulation to reproduce the entire formation and replacement processes of the concentric eyewall. The physical quantities such as the tangential wind speed, radar echo, radial wind speed, vertical wind speed, and potential vortex were diagnosed and analyzed. The results of the analysis show that the outward expansion of the isovelocity in the lower troposphere was the early signal of the formation of the outer eyewall. After the outer eyewall formed, there was a center of second-highest tangential wind speed in the corresponding area. The second-highest wind speed increased as the strength of the outer eyewall increased, and the position of the second-highest wind speed center was retracted with the retraction of the outer eyewall. The tangential wind speed of the moat area was smaller than that corresponding to the concentric eyewall and this feature gradually disappeared with the increase of the height. The echo in the moat area was weak, and this characteristic was particularly evident when the moat area was relatively wide and the outer eyewall was relatively strong. With the formation and development of the outer eyewall, the intensity of the inflow in the boundary layer corresponding to the inner eyewall was reduced, the intensity of the outflow in the upper layers declined, and the intensities of the inflow and outflow corresponding to the outer eyewall were enhanced. After the second outer eyewall matured, there was a significant inflow in the upper layer of the moat area. Once the outer eyewall formed, a large amount of hydrometeors appeared in the corresponding area, and there was a strong ascending motion inside that area. The strength of the ascending motion and the content of hydrometeors increased as the outer eyewall increased. When the moat area was relatively wide, the divergent airflow generated by the developed outer eyewall in the upper layer would produce a significant descending motion in the moat area.

Chaenomeles plants are adapted to diverse ecological zones particularly the temperate areas of Korea, Japan and China. In China, Chaenomeles speciosa mainly planted in Chongqing, Anhui and Hubei provinces. Most of the studies till date have been focused on the anti-inflammatory activities of C. speciosa fractions. The present study aimed to review the maximum literature reported for the presence of various phytochemicals in C. speciosa. In addition, the pharmacological properties of these chemical compounds of this plant shall also be discussed. The extracts of the various parts of the plant are rich in diversity of antioxidants, organic acids, phenolics, terpenoides and many different phytochemicals that bear strong anticancer, antioxidant, anti-viral, antibacterial properties, anti-inflammation, anti-hyperlipidemic, anti-hyperglycemic and anti-parkinson properties. C. speciosa fruits have broad scope in industry as well as in medicines. Not only the leaves and fruits of C. speciosa plant, but various other parts including roots, seeds, bark twigs, and flowers all have long history of clinical trials in curing many human ailments. However, the maximum accessible data concerning the chemical composition and their broad pharmacological properties of C. speciosa plant parts is pretty restricted that make it more appealing for indepth investigations.

This study presents application of demand response strategy in a standalone wind-solar-battery hybrid energy system (HES). Inputs for the designed HES are wind speed, solar radiation, temperature and load demand which is variable with time. In this study, hourly values of meteorological data and hourly load demand are considered in one year. An improved gravitational search algorithm (IGSA) is used to optimize the configuration of the standalone wind-solar-battery hybrid power system. The optimal objectives of the system are cost of the system in life cycle, the loss of power supply probability（LPSP）and the energy excess percentage（EXC）.The effect of demand response on economic benefit and energy storage allocation of the standalone wind-solar-battery system is studied. The obtained optimal configuration of the proposed HES can provide minimal energy cost with excellent performance and reduced waste and unmet load.

The study aimed to investigate the effects of colonization with two arbuscular mycorrhizal (AM) fungi, Funneliformis mosseae , Diversispora versiformis , alone and in combination on the growth and nutrient acquisition of NaCl-stressed Chrysanthemum morifolium (Hangbaiju) plants in the greenhouse experiment. Mycorrhizal and non-mycorrhizal Hangbaiju plants were grown under different salinity levels imposed by 0, 50 and 200 mM NaCl for five months, following 6 weeks of non-saline pre-treatment. The results showed that root length, shoot and root dry weight, total dry weight, shoot and root N concentration were higher in mycorrhizal than in non-mycorrhizal plants under moderate saline conditions especially with D. versiformis colonization. As salinity increased, the mycorrhizal colonization, the mycorrhizal dependence (MD) decreased. Enhancement of tissue N acquisition is probably the main mechanism underlying salt tolerance in AM plants. It is suggested that the symbiotic associations between D. versiformis fungus and C. morifolium plants may be taken as a biotechnological practice in culture.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

We introduce Get Free Copy (getfreecopy.com), a web-based platform designed to streamline the search for biomedical literature across major repositories like arXiv, bioRxiv, medRxiv, and PubMed Central (PMC). Addressing challenges posed by paywalls and fragmented databases, it offers a unified interface for efficient retrieval of free, legitimate copies of biomedical literature. The platform's implementation involves a Node.js backend and dynamic front-end display, enhancing accessibility and research efficiency. As an open-source project, Get Free Copy represents a significant contribution to the open-access movement, inviting global researcher collaboration for further development.

End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

The exceptional performance advantages of the fiber optic gyroscope (FOG) position it as a dominant player in middle and high-end inertial navigation systems. To prevent the loss of sensor precision caused by algorithm design and simplify the complex modeling strategy in traditional methods. We gradually demonstrate the significant role of Convolutional Neural Network (CNN) in the navigation system based on FOG, and utilize the particle swarm optimization algorithm (PSO) to expedite the convergence of the network. The experimental results demonstrate that the initial alignment method based on deep learning is more accurate than the traditional method. The attitude angle error is reduced by 81.25%, 92.54% and 36.53% respectively. The research provides support for the future application of deep learning in optical navigation systems.

Electrocatalytic reduction of CO2 to valuable chemicals can alleviate the energy crisis, and solve the greenhouse effect. The key is to develop non-noble metal electrocatalysts with high activity, selectivity and stability. Herein, bimetallic MOF materials (BiZn-MOF, BiSn-MOF and BiIn-MOF) were constructed by coordinating the P-zone transition metals Zn, In, Sn and Bi with the organic ligand 3-amino-1H-1,2,4-triazole-5-carboxylic acid (H2atzc) through a rapid microwave synthesis approach. The coordination centers in bimetallic MOF Catalyst were regulated to optimize the catalytic performance to CO2RR. The optimized catalyst BiZn-MOF exhibited high catalytic activity than those of Bi-MOF, BiSn-MOF and BiIn-MOF. The BiZn-MOF exhibited a higher selectivity for formate production with a Faradic efficiency (FE=92%) at a potential of -0.9 V (vs. RHE) with a current density of 13 mA/cm2. The current density maintained for 13 h continuous electrolysis. The electrochemical conversion of CO2 to formic acid mainly follows the *OCHO pathway. The good catalytic performance of BiZn-MOF may be attributed to the Bi-Zn bimetallic coordination centers in the MOF, which can reduce the binding energies of the reaction intermediates by tuning the electronic structure and atomic arrangement. This study provides a feasible strategy for performance optimization of bismuth-based catalysts.

Multi-chiplet technique is expected to be a promising solution to achieve high-density system integration with low power consumption and high usage ratio. This technique can be integrated with glass interposer to accomplish a competitive low fabrication cost compared with the silicon-based interposer architecture. In this study, process-oriented stress simulation is performed by the element activation and de activation technique in finite element analysis architecture. Submodeling technique is also utilized to mainly conquer the scale mismatch and difficulty in mesh gridding design. It is used as well to analyze the thermomechanical responses of glass interposer with chiplet arrangement and capped epoxy molding compound (EMC) during curing. A three-factor, three-level full factorial design is applied using the analysis of variance method to explore the significance of various structural design parameters on stress generation. Analytic results reveal that the maximum first principal stresses of 130.75 and 17.18 MPa are introduced on the sidewall of Cu-filled via and the bottom of glass interposer, respectively. Moreover, the EMC thickness and through glass via pitch are the dominant factors in the adopted vehicle. They significantly influence the stress magnitude during heating and cooling.

pH is the major factor that makes producers in aquaponics frustrated, since the main three organisms (aquatic animal, plant, and microbes) in the system with different preferences. Yet, amending the growing environment with additional C is a potential method to improve the growth of shrimp and plants as well as the establishment of microbe. A detailed study of the effects of pH and additional C on aquaponics under saline conditions has not been investigated. In this study, the effect of pH and additional C on the growth performance of shrimp (Litopenaeus vannamei) and five edible plants in marine aquaponic systems using the nutrient film technique (NFT) was evaluated. The results indicated that at both pH 6.5 treatments, plants grew better; nevertheless, the growth performance of plants in pH 7.5 with additional C was improved and showed a similar yield to lower pH treatments. On the other hand, shrimp growth was little affected by pH and additional C. A higher impact of imbalanced ionic composition on shrimp performance may have contributed to this trend. Hence, we suggest that only if the ionic composition is managed can make RO water a suitable source of water for shrimp-based aquaponic. In spite of this, more research is required.

This paper studied the combined influences of the hot streak and swirl on the cooling performances of the NASA C3X guide vane coated with or without TBCs. The results show that: (1) Even under uniform velocity inlet conditions, the hot streak core can be stretched as it impinges the leading edge which causes higher heat load on the suction side of the forward portion. (2) The swirl significantly affects circumferential and radial migration of the hot streak core in the NGV passage. On the passage inlet plane, positive swirl leads to a hotter tip region on the suction side. In comparison, negative swirl leads to a hotter hub region on the pressure side. (3) Under the influence of swirl, migration of coolant improve the coverage of film cooling close to the midspan, while in the regions close to the hub and tip end-wall, the overall cooling performance decrease simultaneously. (4) In the regions with enough internal cooling, the cooling effectiveness increment is always larger than that in other regions. Besides, the overall cooling effectiveness increment decreases on the region covered by film cooling for the coated vane, especially in the region with negative local heat flux.

The underground complicated testing environment and the fan operation instability cause large random errors and outliers of the wind speed signals. The outliers and large random errors result in distortion of mine wind speed monitoring, which possesses safety hazards in mine ventilation system. Application of Kalman filter in velocity monitoring can improve the accuracy of velocity measurement and eliminate the outliers. Adaptive Kalman Filter was built by automatically adjusting process noise covariance and measurement noise covariance depending on the differences between measured and expected speed signals. We analyzed the fluctuation of airflow flow using data of wind speed flow and distribution characteristics of the tunnel obtained by the Laser Doppler Velocimetry system (LDV) studies. A state-space model was built based on the tunnel airflow fluctuations and wind speed signal distribution. The adaptive Kalman Filter was calculated according to the actual measurement data and the Expectation Maximization (EM) algorithm. The adaptive Kalman filter was used to shield fluid pulsation while preserving system-induced fluctuations. Using the Kalman filter to treat offline wind speed signal acquired by LDV, the reliability of Kalman filter wind speed state model and the characteristics of adaptive Kalman Filter were investigated. Results showed that the adaptive Kalman filter effectively eliminated the outliers and reduced the root-mean-squares error (RMSE), and the adaptive Kalman filter had better performance than the traditional Kalman filter in eliminating outliers and reducing RMSE. Field experiments in online wind speed monitoring were conducted using the optimized adaptive Kalman Filter. Results showed that adaptive Kalman filter treatment could monitor the wind speed with smaller RMSE compared with LVD monitor. The study data demonstrated that the adaptive Kalman filter is reliable and suitable for online signal processing of mine wind speed monitor.

Numerical modeling of sedimentation and erosion in reservoirs is an active field of reservoir research. However, simulation of bed-load transport phenomena has rarely been applied to other water bodies, in particular, the fluctuating backwater area. This is because the complex morphological processes between hydrodynamics and sediment transport are generally challenging to accurately predict. In this study, the refinement and application of a two-dimensional shallow-water and bed-load transport model to the fluctuating backwater area is described. The model employs the finite volume method of the Godunov scheme and saturated sediment transport equations. The model was verified against experimental data of a scaled physical model. It was then applied to actual reservoir operation, including reservoir storage, reservoir drawdown and continuous flood process, to predict the morphology of reservoir sedimentation and sediment transport rates and bed level changes in the fluctuating backwater area. It was found that the location and morphology of sedimentation effected by the downstream water level results in random evolution of the river bed, and bed-load sedimentation is transported from upstream to downstream with the slope of the longitudinal section of the river bed generally reduced. Moreover, the sediment is mainly deposited in the main channel and the elevation difference between the riverbank and channel decreases gradually.

Microbiota-based strategies are a novel auxiliary therapeutic and preventative way of moderating chronic kidney disease. Lactobacillus mixture (Lm) was previously demonstrated to exert a renal-protective function in the CKD mice model. The efficacy of probiotics in pet foods is a relatively new area of study, and thus verifying the potential health benefits is necessary. This study evaluated the efficacy of Lm treats in feline CKD and elucidated the mechanisms underlying host-microbe interactions. CKD cats (2 and 3 stages) were administrated probiotic pet treats daily (10 g) for 8 weeks. The results demonstrated that during the eight weeks of Lm administration, creatinine was reduced or maintained in all cats with CKD. Similarly, gut-derived uremic toxins (GDUT), IS, and TMAO were significantly downregulated in the serum (confidence intervals = 90%). The life quality of the cats also improved. Feline gut microbiome data, KEGG pathway, and renal function indicator analyses revealed the possible mechanisms involved in modulating CKD feline microbial composition. Further regulation of the microbial functions in amino acid metabolism after Lm administration contributed to downregulating deleterious IS, PCS, and TMAO. The current study provides potential adjuvant therapeutic insights into probiotic pet foods or treats for pets with CKD.

The ATP-binding cassette (ABC) transporter ABCG2 is a significant urate transporter with a high capacity, and it plays a crucial role in the development of hyperuricemia and gout. Therefore, it has the potential to be targeted for therapeutic interventions. Cortex Fraxini, a traditional Chinese medicine (TCM), has been found to possess anti-hyperuricemia properties. However, the specific constituents of Cortex Fraxini responsible for this effect are still unknown, particularly the compound that is responsible for reducing uric acid levels in vivo. In this study, we propose a target screening protocol utilizing bio-affinity ultrafiltration mass spectrometry (BA-UF-MS) to expediently ascertain ABCG2 ligands from the plasma of rats administered with Cortex Fraxini. Our screening protocol successfully identified fraxin as a potential ligand that interacts with ABCG2 when it functions as the targeted protein. Subsequent investigations substantiated fraxin as an activator of ABCG2. These findings imply that fraxin exhibits promise as a drug candidate for the treatment of hyperuricemia. Furthermore, the utilization of BA-UF-MS demonstrates its efficacy as a valuable methodology for identifying hit compounds that exhibit binding affinity towards ABCG2 within TCMs.

This paper proposes a novel symmetrical active-switched coupled-inductor high-step-up DC/DC converter. A new active-switched coupled inductor is used to allow much higher voltage gain of the proposed converter. The symmetrical circuit structure of the proposed converter evenly divides large input currents and reduce input current ripple by operating in interleaved mode so power density is increased. The switches also have low voltage stress. The operating principle and design considerations for the converter topology are described. The proposed converter with an input voltage of 40 V, an output voltage of 400 V and an output of 1000 W at a switching frequency of 50 kHz is implemented. The simulations and experimental results are thus depicted to verify the theoretical analysis. The highest efficiency is 95.5% at 200 W measured by using a HIOKI 3390. Consequently, the proposed converter is suitable for renewable energy generation systems that require high power, high voltage gain and high efficiency.

With the global outbreak of COVID-19, the panic buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. Based on the theory of evolution game, the evolutionary process of the strategy selection of game subjects is studied, and the strategy selection of the three-game subjects under different scenarios is compared and analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that: the evolution process of the mass panic buying event is characterized by six stages: the initial stage E1(0,0,0); the outbreak stage E3(0,1,0);the spread stage E7(0,1,1);the climax stage E8(1,1,1);the relief stage E5(1,1,0);and the recovery stage E4(1,0,0); there are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying), and the strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger; under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward; the parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. This study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.

Chemical safety is related to public health, safety and environmental concerns, and the dangerous chemicals safety problem is becoming the one that people commonly pay attention to. Strengthening chemical safety supervision not only involves safe production, but also is an important link to maintain social safety. Most related studies focus on chemical safety under normal regulation, this paper addresses the perspective of ‘special rectification’ and ‘normal regulation’, and establishes an evolutionary game model between chemical enterprises and government supervision departments under different supervision modes. Based on the evolutionary game theory, this paper studies the evolution process of the two game players' strategy choices, and compares and analyzes the evolution, stability and equilibrium between the chemical safety and the behavior strategies of government regulatory departments. The model is effectively analyzed based on numerical simulation, and the results show that: Under the ‘special rectification’ mode, the strategic choice of chemical enterprises engaging in safety without investment depends on the difference between the benefits and costs of safety without investment; In the ‘normal regulation’ mode, the choice of its safety non-investment strategy depends on the difference between the cost of engaging in safety investment and the cost of safety non-investment; Increasing the government's punishment will encourage chemical enterprises to take safety investment behavior under the two supervision modes. Increasing the punishment has a significant impact on the safety investment behavior of chemical enterprises under the ‘normal regulation’ mode, but it has no significant impact on the behavior of chemical enterprises under the ‘special rectification’ mode. At the same time, increasing the punishment will inhibit the strict supervision behavior of the government. The research conclusion provides important decision support for government departments to effectively supervise the safety production of chemical enterprises.

Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high density storage and in-memory computing applications. However, the traditional RRAM, which accommodates two states depending on applied voltage, cannot meet the high density requirement in the era of big data. Many research groups have demonstrated that RRAM possesses the possibility of multi-level cell to overcome the demand of mass storage. Among numerous semiconductor materials, gallium oxide, as the fourth-generation semiconductor material, is highly-profile due to its excellent material proper-ties, and already be widely used in optoelectronics, high-power, resistive switching device and so on, due to its wide bandgap and transparent properties. In this study, we have successfully demonstrated the Al/GO/Ga2O3/ITO RRAM to achieve the possibility of two-bit storage. Compared to the single-layer counterpart, the bilayer structure has excellent electrical properties and stable reliability. The endurance characteristics could be enhanced above 100 switching cycles with an ON/OFF ratio of over 103. Moreover, the filament models are also described in this thesis to clarify the transport mechanisms.

Blood testing is a crucial medical application. In this study, we applied Raman spectroscopy to test blood samples and obtained complete biological information, including the main components and compositions in these samples. Short-wavelength (532-nm green light) Raman scattering spectroscopy was conducted on samples of normal blood, abnormal blood in 3 types of preparation including whole blood, plasma, and serum, and the underlying information reflected by the biological characteristics detected in each sample type were analyzed. Raman spectroscopy results indicated that normal blood had high hemoglobin content, which suggests that hemoglobin is a major component of blood. Hemoglobin affects blood oxygen level. The characteristic peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562–1649 cm−1. Analysis of plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm−1. In addition, surface-enhanced Raman spectroscopy was used to collect biological signals that are difficult to obtain in conventional Raman spectroscopy, including those of small molecules such as hormones, antibodies, and enzymes. Changes in biological information collected in this manner can be used as a basis for potentially diagnosing clinical diseases.

Heavy metal contaminants have serious consequences for the environment and human health. Consequently, effective methods for detecting their presence, particularly in water and food, are urgently required. Accordingly, the present study proposes a sensor for the detection of mercury Hg(II) and lead Pb(II) ions using graphene oxide (GO) as a quenching agent and aptamer solu-tion as a reagent. In the proposed device, the aptamer sequences are labeled by FAM and HEX fluorescent dyes, respectively, and are mixed with 500 ppm GO solution in a microfluidic device. The presence of Hg(II) and Pb(II) ions is then detected by measuring the change in the fluores-cence intensity of the GO/aptamer suspension as the aptamer molecules undergo fluorescence resonance energy transfer (FRET). The experimental results show that the aptamer sensors have a linear range of 10~250 nM (i.e., 2.0~50 ppb) for Hg(II) ions and 10~100 nM (i.e., 2.1~20.7 ppb) for Pb(II) ions. Furthermore, the limit of detection is around 2 ppb for both metals, which is signifi-cantly lower than the maximum limits of 6 ppb and 10 ppb prescribed by the World Health Or-ganization (WHO) for Hg(II) and Pb(II) in drinking water, respectively.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

This study aims to develop an elderly care system for improving the interpersonal relationship of the elderly with mild cognitive impairment (MCI) by employing the speaker recognition technique and association functionality of social network platforms. Firstly, the speaker recognition units based on the Gaussian Mixture Model (GMM) and Gaussian Mixture Model-Universal Background Model (GMM-UBM) are implemented to identify the visitor via individual input utterance. After the visitor is identified, the proposed system will be linked to the private database and social network platforms to extract the associated message of two parties. Experimental results indicate that the speaker recognition unit based on GMM-UBM achieves the best performance. Finally, five elderly persons are invited to measure the usability of the proposed system. A questionnaire is used to survey the five elderly persons, and the result indicates that the proposed system is highly potentially applicable in improving the interpersonal relationship of the elderly with MCI.

Traditional edible barbecue products use with lemon juice not only make the barbecue more delicious but also reduce the risk of PAHs in the barbecue products. One of the major economics crops in Taiwan, the waste from citrus fruits was very tremendous mass. However, the peelings of citrus fruits are rich in essential oil, especially, the limonene is the major. Whether the anti-carcinogenesis activities of terpene, such as limonene, in citrus fruits essential oil extraction. This study to demonstrate the PAHs content in fish skin increased markedly after being roasted at 210℃ for 20 minutes and greater mutagenicity risk of roasted fish skin was observed by Ame's test. The reduction of mutagenicity risk of roasted fish skin, which the antimutagenic abilities of substances in descending order were limonene > cold pressure oil > lemon >grapefruit. The antimutagenicity rate and ability of the three extracts were limonene: 18–23%; cold-pressed lemon oil: 18–22%; and steam distilled lemon essential oil: 8–16%. The obvious anti- mutagenicity effects against the PAHs mutagenicity of roasted fish skins can be found in citrus fruits essential oil extraction.

The increased consumption of high fat-containing foods has been linked to the prevalence of obesity and abnormal metabolic syndromes. Rhizopus oligosporus, a fungus in the family Mucoraceae, is widely used as a starter for homemade tempeh. Although R. oligosporus can prevent the growth of other microorganisms, it grows well with lactic acid bacteria (LAB). Lactobacillus plantarum can produce β-glucosidase, which catalyzes the hydrolysis of glucoside isoflavones into aglycones (with greater bioavailability). Therefore, the development of a soybean-based functional food by the co-inoculation of R. oligosporus and L. plantarum is a promising approach to increase the bioactivity of tempeh. In this study, the ameliorative effect of L. plantarum in soy tempeh on abnormal carbohydrate metabolism in high-fat diet (HFD)-induced hyperglycemic rats was evaluated. The co-incubation of L. plantarum with R. oligosporus during soy tempeh fermentation reduced the homeostatic model assessment of insulin resistance, HbA1c, serum glucose, total cholesterol, triglyceride, free fatty acid, insulin, and low-density lipoprotein contents and significantly increased the high-density lipoprotein content in HFD rats. It also increased the LAB counts as well as the bile acid, cholesterol, triglyceride, and short-chain fatty acid contents in the feces of HFD rats. Our results suggested that the modulation of serum glucose and lipid levels by LAB occurs via alterations in the internal microbiota, leading to the inhibition of cholesterol synthesis and promotion of lipolysis. Tempeh, produced with both L. plantarum and R. oligosporus, may be a beneficial dietary supplement for individuals with abnormal carbohydrate metabolism.

Ferulic acid esters have been suggested as a group of natural chemicals with sunscreen function. The study aimed to utilize an environment-friendly enzymatic method to produce octyl ferulate by esterification of ferulic acid with octanol. The Box-Behnken design with response surface methodology (RSM) was adopted to evaluate the effects of synthesis variables, including reaction temperature (70–90 °C), enzyme amount (1000–2000 PLU) and stir speed (50–150 rpm), on the molar conversion of octyl ferulate. According to the joint test, both the reaction temperature and enzyme amount had great impacts on the molar conversion. RSM-developed second-order polynomial equation further showed great ability on data-fitting. Based on ridge max analysis, the optimum parameters for the biocatalyzed reaction were: 72 h reaction time, 92.2 °C reaction temperature, 1831 PLU enzyme amount and 92.4 rpm stir speed, respectively. Finally, the molar conversion of octyl ferulate under optimum condition was verified to be 93.2 ± 1.5%. In conclusion, high yield of octyl ferulate synthesized by commercial immobilized lipase under elevated temperature conditions has been suggested, which our findings could broaden the utilization of the lipase and provide a biocatalytic approach, instead of the chemical method, for ferulic acid ester synthesis.

Stress relaxation tests in cantilever bending were performed on the C7025 and C7035 alloys at 298K and 393K，respectively. The effect of stress-relief treatments on stress relaxation properties was investigated. The structural changes associated with the stress relaxation process were examined using transmission electron microscope. The stress relaxation curve fits well to empirical formula σ*=[Kˊln(t+α₀)+C]^-n for stress relaxation. The curves can be split into two stages. The stress relax quickly in the first stage, slows down in the second stage, and tends to be a certain limit value after a long time. The curve and microstructure reveals that the C7035 alloy has a lower rate of stress relaxation and a higher anti-stress relaxation capacity than the C7025. The first reason is that the movement of vacancies required by spinodal decomposition is inhibited, and the quantity of cobalt -containing vacancies decreases dramatically in the C7035 alloy. The other reason is that the precipitated phases became uniformly diffused in the C7035 alloy. The precipitate phase uniformly distributes in the grain boundaries and the matrix, during the relaxed condition, and thus the dislocations moving is blocked by the precipitates.

Background: Few studies have investigated the longitudinal association between cervical spondylosis (CS) and migraine by using a nationwide population-based database. Methods: We conducted a retrospective cohort study from 2000 to 2011 identifying 27,930 cases of cervical spondylosis and 111,720 control subjects (those without cervical spondylosis) from a single database. The subjects were frequency-matched on the basis of sex, age, and diagnosis date. The non- cervical spondylosis cohort was four times the size of the cervical spondylosis cohort. To quantify the effects of cervical spondylosis on the risk of migraine, univariate and multivariate Cox proportional hazard regression analyses were used to calculate the hazard ratio (HR) and 95% confidence interval (CI). Results: After a 10-year follow-up controlling for potential confounding factors, overall migraine incidence was higher in the cervical spondylosis cohort than in the non- cervical spondylosis cohort (5.16 and 2.09 per 1,000 people per year, respectively; crude hazard ratio = 2.48, 95% confidence interval = 2.28–2.69) with an adjusted hazard ratio of 2.03 (95% confidence interval = 1.86–2.22) after accounting for sex, age, comorbidities, and medication. Individuals with myelopathy in the cervical spondylosis cohort had a 2.19 times (95% confidence interval = 1.80–2.66) higher incidence of migraine compared than did those in the non- cervical spondylosis cohort. Conclusion: Individuals with cervical spondylosis exhibited a higher risk of migraine than those without cervical spondylosis. The migraine incidence rate was even higher among individuals with cervical spondylotic myelopathy.

This study examined the use of high dosages of ultraviolet germicidal irradiation (UVGI) (253.7 nm) to deal with various concentrations of air pollutants, such as formaldehyde (HCHO), total volatile organic compounds (TVOC), under various conditions of humidity. We also estimated the emission of ozone as a secondary pollutant of UVGI as treatment. A number of irradiation methods were applied for various durations in field studies to examine the efficiency of removing HCHO, TVOC, bacteria, and fungi. The removal efficiency of air pollutants (HCHO and bacteria) through long-term exposure to UVGI appears to increase with time. The effects on TVOC and fungi concentration were insignificant in the first week; however, improvements were observed in the second week. No differences were observed among the various irradiation methods in this study regarding the removal of HCHO and TVOC; however significant differences were observed in the removal of bacteria and fungi.

The king ratsnake (Elaphe carinata) of the genus Elaphe is a common large non-venomous snake that is widely distributed in Southeast and East Asia, and is an economically important farmed snake species. As a non-venomous snake, the king snake that is predatory on venomous snakes such as cobras and pit vipers. The immune mechanisms of which has been unclear. Despite their economic and research importance, genomic resources which will benefit studies in toxicology, phylogeography and immunogenetics are lacking. In this study, we use single-tube long fragment read (stLFR) sequencing to display the first complete genome of a King ratsnake from Huangshan City, Anhui province in China. The genome size is 1.56GB with a scaffold N50 of 6.53M, the total length of the genome is approximately 621Mb, and the repeat content is 38.90%. Additionally, we predicted 22,339 protein-coding genes, of which 22,065 had functional annotations. Our genome is a potentially useful addition to those currently available for snakes.

A large number of microplastics (MPs) have been found in various stages of wastewater treatment plants, which may affect the functional microbial activity in activated sludge and lead to unstable pollutant removal performance. In this study, the effects of different concentrations of polylactic acid microplastics (PLA MPs) on system performance, nitrification and phosphorus (P) removal activities, and extracellular polymeric substances (EPS) were evaluated. The results showed that under the same influent conditions, low concentrations (50 particles/(g TS)) of PLA MPs had no significant effect on effluent quality. The average removal efficiencies of chemical oxygen demand, phosphate and ammonia were all above 80%, and the average removal efficiencies of total nitrogen remained above 70%. High concentrations (200 particles/(g TS)) of PLA MPs inhibited the activities of polyphosphate accumulating organisms (PAOs) and nitrifying bacteria. The specific anaerobic P release rate decreased from 37.7 to 23.1 mg P/(g VSS·h), and the specific aerobic P uptake rate also decreased significantly. The specific ammonia oxidation rate decreased from 0.67 to 0.34 mg N/(g VSS·h), while the change in specific nitrite oxidation rate was not significant. The dosing of PLA MPs decreased the total EPS and humic acid content. As the concentration of PLA MPs increased, microbial community diversity increased. The relative abundance of potential PAOs (i.e., Acinetobacter) increased from 0.08% to 12.57%, while the relative abundance of glycogen accumulating organisms (i.e., Competibacter and Defluviicoccus) showed no significant changes, which would lead to improved P removal performance. The relative abundance of denitrifying bacteria (i.e., Pseudomonas) decreased from 95.43% to 58.98%, potentially contributing to the decline in denitrification performance.

A common spinal condition, spondylolisthesis is the presence of a relative back or forth displacement between the upper and lower vertebra due to one vertebra being oriented away from the smooth curvature of a normal spine. Aging-related illnesses such as degenerative spondylolisthesis are especially burdensome on social welfare and health-care systems in an aging society, especially radiologists and clinical physicians. Therefore, we proposed a computer aided diagnosis algorithm, named LumbarNet, for vertebral slippage detection on clinical X-ray images. Collaborating with i) a P-grade, ii) a piecewise slope detection scheme, and iii) a dynamic shift detection routine, LumbarNet was thus specialized for analyzing complex structural patterns in lumbar spine X-ray images and outcompeted other U-Net based methods. Extensive experiments on lumbar spine X-ray images in standard clinical practices showed that LumbarNet achieved a mean intersection over union value of 0.88 in vertebral region detection and an accuracy of 88.83% in vertebral slippage detection.

When a grid-forming (GFM) inverter is connected to a low or medium voltage weak power grid, the line impedance with resistive-inductive characteristics will cause power coupling. Typical GFM decoupling control strategies are designed under nominal line impedance parameters. However, there are deviations between the nominal line impedance and actual parameters, resulting in poor decoupling effects. Aiming at this problem, this paper proposes a power decoupling strategy based on a reduced-order extended state observer (ESO). Firstly, the power dynamic model of GFM is established based on the dynamic phasor method. Then, the model deviation and power coupling due to line impedance parameter perturbation are estimated as internal disturbances of the system, and the disturbances are compensated on the basis of typical power control strategy and virtual impedance decoupling. Good decoupling performance is obtained under different impedance parameters, improving the control strategy's robustness. Finally, the effectiveness of the proposed method is verified by the results of RT Box hardware-in-the-loop experiments.

Fully mechanized mining face production involves complex geological conditions; mining pressure; gas, water, fire and other mining environments. The working face needs a shearer, hydraulic support, a scraper conveyor and other equipment for coordination. The deep integration of intelligent technology with factors such as "humans, machines, the environment, and management" in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for coal mining robot technology systems, including single robots, robotized equipment, robot clusters and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve customized research and development and standardized production of various types of robots. A specific analysis was conducted on the research progress of common key technologies such as explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mine robot research and development is proposed. Moreover, robotic mining systems should be promoted to enhance the overall intelligence level and mining efficiency of mining equipment. To develop human‒machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots. The digital twinning of the entire mine robot system should be accelerated, the normalized operation level of coal mine robots should be improved, research on coal mining robots, support robots, and transportation robots should be carried out, intelligence should be achieved in fully mechanized mining faces, and equipment support for fewer and unmanned fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization has been summarized, and the technical and engineering feasibility of the coal mining machine population has been verified.

Co-inhibitory receptors (Co-IRs) are essential in controlling the progression of immunopathology in rheumatoid arthritis (RA) by limiting T cell activation. The objective of this investigation was to determine the phenotypic expression of Co-IRs T cells and to assess the levels of serum soluble PD-1, PDL-2, and Tim3 in Taiwanese RA patients. Co-IRs T cells were immunophenotyped employing multicolor flow cytometry, and ELISA was utilized for measuring soluble PD-1, PDL-2, and Tim3. Correlations have been detected across the percentage of T cells expressing Co-IRs (MFI) and different indicators in the blood, including ESR, high sensitivity CRP (hsCRP), 28 joint disease activity scores (DAS28), and soluble PD-1/PDL-2/Tim3. In RA patients, we recognized elevated levels of PD-1 (CD279), CTLA-4, and TIGIT on CD4+ T cells; TIGIT, HLA-DR, TIM3, and LAG3 on CD8+ T cells; and CD8+CD279+TIM3+, CD8+HLA-DR+CD38+ T cells. The following tests proved to be correlated with hsCRP: CD4/CD279 MFI, CD4/CD279%, CD4/TIM3%, CD8/TIM3%, CD8/TIM3 MFI, CD8/LAG3%, and CD8+HLA-DR+CD38+%. CD8/LAG3 and CD8/TIM3 MFIs are linked to ESR. DAS28-ESR and DAS28-CRP exhibited relationships with CD4/CD127 MFI, CD8/CD279%, and CD8/CD127 MFI, respectively. CD4+CD279+TIM3+% was correlated with DAS28-ESR (p=0.0084, N=46), DAS28-CRP (p=0.007, N=47), and hsCRP (p=0.002, N=56), respectively. In the serum of patients with RA, levels of soluble PD-1, PDL-2, and Tim3 were extremely elevated. CD4+ TIM3+% (p=0.0089, N=46) and CD8+ TIM3+% (p=0.0305, N=46) were correlated with sTIM3 levels; sPD1 levels were correlated with CD4+CD279+% (p<0.0001, N=31) and CD3+CD279+% (p=0.0084, N=30). Co-IRs expressions on CD4+ and CD8+ T cells, as well as soluble PD-1, PDL-2, and Tim3 levels, could function as indicators of disease activity and potentially play crucial roles in the pathogenesis of RA, in accordance to our findings.

A number of epidemiological studies have implicated elevated iron levels with higher risks of cardiometabolic diseases, including the metabolic syndrome (MetS). MetS is a pathologic clustering of metabolic derangements characterized by central obesity, insulin resistance, hypertension, and dyslipidemia, which can all lead to increased cardiovascular disease morbidity and mortality. However, it remains unclear whether a causal association exists between higher iron status and MetS and its associated risk components. Using the data from the Taiwan Biobank (TWB) (19,012 males; 42,340 females) and of the European Whites from the UK Biobank (UKB) (128,549 males; 142,817 females), we first constructed ethnic- and sex-specific hemoglobin-polygenic risk scores (Hb-PRS) as instrumental variable (IV) for iron status with the Hb-associated SNPs we previously identified from genome-wide association studies (GWAS). We then conducted Mendelian randomization (MR) analyses to elucidate the causal role of elevated iron (either Hb-PRS quintiles or continuous Hb-PRS) on various metabolic components. MR-Egger regressions determined the potential pleiotropic effects of the constructed Hb-PRSs, while the causal relationship of Hb-PRS with anemia served as a control in the analyses. The mean Hb concentration range corresponding to the Hb-PRS quintiles is relatively narrow in both UKB (14.91-15.21 g/dL for males and 13.39-13.71 g/dL for females) and TWB (14.79-15.28 g/dL for males and 12.78-13.21 g/dL for females). In these windows of Hb-PRSs, we found differential associations of Hb-PRS with diabetes (T2D) or hyperglycemia (HGY) as compared to other MetS components. The highest quintiles of Hb-PRSs were causally associated with greater risks of hypertension (HTN) and hypertriglyceridemia (DLP) (i.e., [Taiwanese HC males: Q5 vs. Q1 ORHTN = 1.10 (1.00–1.21), p = 0.0473, Q4 vs. Q1 ORDLP = 1.10 (1.00–1.22), p = 0.0485; European White males: ORHTN = 1.05 (1.01–1.09), p = 0.0194, ORDLP = 1.04 (1.00–1.08), p = 0.0468]). Interestingly, we obtained a consistent negative causal association between increasing Hb-PRS quintiles and T2D or HGY risk across all sex subgroups (i.e., [Taiwanese HC females: ORHGY = 0.89 (0.84–0.95), 0.88 (0.83–0.94), 0.87 (0.82–0.93), 0.86 (0.81–0.92) from Q2 to Q5; European White females: ORHGY = 0.92 (0.87–0.98), 0.91 (0.86–0.97), 0.93 (0.87–0.98), 0.87 (0.82–0.93) from Q2 to Q5; all p &lt; 0.05]. The positive causal relationships between Hb-PRSs and diastolic blood pressure (DBP) and triglycerides (TG) but inverse causal association with glucose (GLU) and glycated hemoglobin (HbA1c) further corroborated such findings. There is, however, a lack of causal association with central obesity (CO), while a U-shaped type of causality was observed for gout (GT) or hyperuricemia (HUA). Sensitivity analyses, which excluded subjects based on self-reports of health conditions or medications and hospital episode statistics data, revealed similar results. Our MR studies confirm a modest causal relationship between propensity of elevated iron status and increased risk of HTN and DLP. We have further observed that modestly lower iron levels causally contribute to the development of T2D. Further validation and elucidation of the underlying biological mechanisms are highly warranted.

In this paper, a method for the preparation of ultrasound-responsive microgels was developed based on RAFT-HDA dynamic covalent bonding. First, a styrenic cross-linked network was suc-cessfully prepared by DA reaction between phosphoryl dithioester and furan using double-ended BDEPDF as RAFT reagent mediated St polymerization as double-ended dienophile linker and co-polymer of FMA and St as dienophile. Subsequently, the microgel system was constructed by the HDA reaction between phosphoryl disulfide and furan groups using the copolymer of polyethylene glycol monomethyl ether acrylate (OEGMA) and FMA as the dienophore building block and hy-drophilic segment, and the polystyrene pro-dienophile linker as the cross-linker and hydrophobic segment. The number of furans in the dienophile chain and the length of the dienophile linker were regulated by RAFT polymerization to investigate the effects of single-molecule chain functional group degree (f), furan/dithioester ratio (r), and hydrophobic linker length (D) on the microgel system. These microgels can achieve the reversible transformation of materials under force re-sponsiveness, and the steps are simple and adaptive, which are expected to show important po-tential applications in the fields of biomedical materials and adaptive electrical materials.

Calligraphy works have high artistic value, but there is a rampant problem of forgery. Indeed, authentication of traditional calligraphy heavily relies on calligraphers' subjective judgment. Therefore, spurred by the recent development of neural networks, this paper proposes a method for authenticating calligraphy works based on an improved EfficientNet network. Specifically, the developed method utilizes the character box algorithm and the centroid algorithm to extract individual calligraphy characters, which are then augmented and used as the training set for the model. The training process employs CBAM and Self-Attention modules to enhance the attention mechanism of the EfficientNet network. The model is tested on authentic works, imitated works, and works from other calligraphers and is compared with other networks. The experimental results demonstrate that the proposed method effectively achieves the authentication of calligraphy works, and the improved CBAM-EfficientNet network and SA-EfficientNet network achieve better authentication performance.

To evaluate the effect of middle meningeal artery embolization (MMAE) on chronic subdural hematoma (CSDH). We enrolled consecutive patients with CSDH who underwent burr hole craniostomy (BHC) between January 2021 and February 2023. The primary outcome was recurrence rate, defined as an increase of hematoma width on imaging compared with the immediate postoperative imaging at a 3-month follow-up. Secondary outcomes included the rate of complications and adverse prognosis. Cohorts were balanced using 1:2 propensity score matching (PSM). A total of 271 patients were eligible for this study and divided into the MMAE group (n=23) and the BHC group (n=205). Compared with the BHC group, there was more use of anticoagulant or antiplatelet medication (47.8% vs 22.4%, P=0.008), bilateral hematoma (19.5% vs 19.5%, P=0.043) and hematoma with septations (47.8% vs 21.5%, P=0.005) in the MMAE group. After PSM, 64 cases were finally successfully matched. The logistic analysis result showed that MMAE was associated with the decreased recurrence rate of CSDH in the cohort after PSM (OR 0.072, 95%CI 0.322~0.746, P=0.028) but not with the improved clinical prognosis (OR 0.065, 95%CI 0.533~4.786, P=0.562). MAAE has a positive therapeutic effect on reducing the recurrence rate of CSDHs as an adjunct postoperative treatment after burr hole surgery.

Wearing gloves while operating machinery in workshops is an essential precaution to prevent mechanical injuries and burns from high temperatures, among other potential hazards. Ensuring workers are properly equipped with gloves, which is a crucial measure in accident prevention. Glove images often occupy a minimal proportion of the frame and are easily obscured by cluttered backgrounds, especially with limited edge computing resources. Consequently, this study proposes a glove detection algorithm called YOLOv8-AFPN-M-C2f based on YOLOv8, offering swifter detection speeds, lower computational demands, and enhanced accuracy for workshop scenarios. This research innovates by substituting the head of YOLOv8 with the AFPN-M-C2f network, amplifying the pathways for feature vector propagation, and mitigating semantic discrepancies between non-adjacent feature layers. Additionally, the introduction of a superficial feature layer enriches surface feature information, augmenting the model's sensitivity to smaller objects. To assess the performance of the YOLOv8-AFPN-M-C2f model, we conducted multiple experiments using a factory glove detection dataset compiled for this study. The results indicate that the enhanced YOLOv8 model surpasses other network models. Compared to the baseline YOLOv8 model, the refined version shows a 2.6% increase in mAP@50%, a 90.1% rise in FPS, and a 13% reduction in the number of parameters. This research contributes an effective solution for the detection of glove adherence.

Facial emotion detection is a challenging task that deals with emotion recognition. It has applications in various domains, such as behavior analysis, surveillance systems and human-computer interaction (HCI). Numerous studies have been implemented to detect emotions, including classical machine learning algorithms and advanced deep learning algorithms. For the machine learning algorithm, the hand-crafted feature needs to be extracted, which is a tiring task and requires human effort. Whereas in deep learning models, automated feature extraction is employed from samples. Therefore, in this study, we have proposed a novel and efficient deep learning model based on Neural Architecture Search Network utilizing superior artificial networks such as RNN and child networks. We performed the training utilizing the FER 2013 dataset comprising seven classes: happy, angry, neutral, sad, surprise, fear, and disgust. Furthermore, we analyzed the robustness of the proposed model on CK+ datasets and comparing with existing techniques. Due to the implication of reinforcement learning in the network, most representative features are extracted from the sample network. It extracts all key features without losing the key information. Our proposed model is based on one stage classifier and performs efficient classification. Our technique outperformed the existing models attaining an accuracy of 98.14%, recall of 97.57%, and precision of 97.84%.

The quasi-beta processing was considered as a promising processing technology to obtain a component with an excellent mechanical properties. To achieve an optimized quasi-beta processing parameter of TC21 alloy, the hot deformation behavior in near β phase region for the alloy with a forged structure was investigated by the thermal compression test and finite element (FEM) simulation. The obtained results indicated that the flow behavior of the samples was significantly influenced by the hot deformation parameters and it exhibited a flow hardening behavior at the start stage of deformation. Based on the experimental data, the constitutive equation and processing maps were obtained. The optimum hot processing parameters was 986℃/10^-3s^-1. Based on the FEM simulation results, the evolution of temperature field, strain field and stress field in the deformed samples at different strains exhibited a similar trend in the unstable region, which distributed symmetrically along the center line of the samples, and the center area of the samples was the highest and the center area of the section was the lowest.

Background： Sepsis-induced acute lung injury (ALI) is characterized by disruption of the epithelial barrier and activation of alveolar macrophages (AMs), which leads to uncontrolled pulmonary inflammation. However, effective treatments for ALI are unavailable. This study aimed to discover potential diagnostic molecular biomarkers based on bioinformatics, which will benefit the diagnosis and treatment of sepsis-induced ALI. Methods: GSE10474 was analyzed for differentially expressed genes (DEGs) in sepsis patients with ALI (sepsis + ALI) compared with sepsis patients without ALI. Functional enrichment analysis and protein-protein interaction (PPI) network were performed. on the DEGs via R package “clusterProfiler”, and visualized via Cytoscape. Prediction analysis of microarrays (PAM) was performed to identify diagnostic biomarkers and the diagnostic ability of diagnostic biomarkers was accessed via receiver operating characteristic (ROC) curves. Moreover, interactions among diagnostic biomarkers were analyzed via GeneMANIA. We also analyzed the function of diagnostic biomarkers and predicted their corresponding drugs via Cytoscape plugin BiNGO and web tool DGIdb. At last, we analyzed the transcriptional regulation of the diagnostic biomarkers via the web tool miRNet. Results: 71 genes were found to be differentially expressed in the sepsis + ALI group, mainly involved in immune-related biological processes and pathways. STRING database indicated 31 DEGs have protein-protein interactions. In addition, the PAM identified 6 diagnostic biomarkers, including HIST1H4H, CDKN1A, HMOX1, NQO2, RHOB, and TREM1, from these 31 DEGs. Conclusion: In conclusion, through bioinformatics analyses, we identified 6 potential diagnostic biomarkers and targets for sepsis-induced ALI.

In the past decades, the world is actively working towards the global goal of net-zero emission. To decrease emissions, there is a notable trend of electrification in transportation, which is a transition from traditional fuel-based systems to electrical power systems onboard different transportation platforms. For this transition, it is important to study the electrical structure, specifically the onboard microgrid, powered by various energy sources. In this paper, traditional energy management strategies for onboard microgrid systems are discussed, which usually require complicated optimization algorithms and high computation capabilities. Driven by the recent advancements in information technologies, artificial intelligence and digital twin have gained much interest within the transportation sector. These technologies can effectively utilize data to achieve intelligent decision-making, optimize resource utilization, and save energy consumption. This paper presents an overview of the usage of these emerging information technologies in energy management strategies, providing an overall summary and classification of the practical applications. In addition, after examining the potential challenges associated with artificial intelligence and digital twin, this paper also discusses future trends in this field.

Background: Depression is a common mental health problem that can affect everyone at different stages of development. Though the prevalence rate of depression among university students is rising, exploration among engineering students is limited. The aim of the study was to examine the prevalence of depression and its associated factors of among engineering students in Thailand. Methods: 346students participated in this study. All completed the outcome inventory-depression subscale (OI-D) to evaluate the level and prevalence of depression. Other variables assessed included social skill, learning styles, relationship satisfaction, interpersonal difficulty, alcohol use, internet addiction, and neuroticism. Correlation and regression analysis were applied to test the association between sociodemographic and psychosocial factors and depression. Results. Of 346 students with the mean age was 20.25 (SD, 1.33), 52.31% was male. Based on the OI-D, 35.3% of participants exhibited symptoms indicative of major depression. Multiple regression showed that only neuroticism, interpersonal difficulties, social skills, and self-esteem appeared to be the significant predictors of depression. Conclusion: the prevalence of depression among engineering students is unexpectedly high. Intra and interpersonal factors were found to be associated with depression. Further study on identifying these risk factors should be encouraged.

Laser additively manufactured (LAM) Ti–6Al–4V alloy has huge application potential in aerospace structural parts such as turbine blades. However, there are few studies on the fatigue properties of such LAM parts under vibration loading, particularly with regard to anisotropy. In this paper, vibration fatigue properties of LAM Ti-6Al-4V by laser melted deposition process were investigated along the transversely deposited (TD) direction and parallelly deposited (PD) direction. Through the first-order bending vibration experiments, LAM Ti-6Al-4V alloy exhibits obvious anisotropic fatigue properties and significant dispersion in fracture position. The fracture morphology analysis reveals that the vibration fatigue failure was mainly dominated by the LAM process-induced defects and the microstructure. For the LAM samples without defects at crack initiation sites, the fatigue behavior is controlled by the prior β columnar grains with preferential orientation, which leads to enhanced fatigue crack propagation resistance for the PD samples. For the LAM samples with defects at initiation sites, having lower fatigue lives, the fatigue anisotropy strongly depends on the projection area of the lack-of-fusion defects relative to the loading direction, resulting in better fatigue performance for the TD samples.

With the development of free trade port in Hainan Island, the construction of tourist roads around the island is also in full swing. Under the weather conditions of strong typhoon and rainstorm in Hainan, the highway cutting slope built on the coastal weak sandy terraces has strong sand loss and is easy to be scour by rainfall. MICP green spray irrigation solidification technology is used to strengthen the sandy cutting, and pore water pressure monitoring is carried out on the slope model during MICP solidification and rainfall scour. Combined with the model pore water pressure and flow slip failure pattern, dynamic analysis was carried out. The results show that MICP sprinkler irrigation technology can solidified the surface of the slope model in a short time, and the cementation depth of the model reaches 4cm after three sets of rotation reinforcement. The surface reinforcement effect is good, and the sand samples are closely connected. Under the erosion effect of simulated rainfall intensity, the sand loss of the slope is weakened, and no sand binding damage occurs, and the integrity is enhanced. Due to the cementation between sand grains, most of the rainfall was converted into runoff, and the slope slid after 150s. When the slope began to slip, the leading edge of the slope model lost sand and unloaded, and the failure mode was graded creep slip failure. Finally, the slope was divided into several blocks due to the continuous expansion of cracks after the slope failure. The erosion stability of the sandy slope under heavy rains is optimized and the sand loss is prevented effectively. In this study, a new method of MICP remediation techniques is proposed, which provides a new test basis for the application of MICP technology in practical engineering.

“Gray zone” category tumors in thyroid follicular tumors are difficult to diagnose, especially to distinguish between follicular thyroid adenoma (FTA) and follicular thyroid carcinoma (FTC). This study aimed to assess the diagnostic performance of metabolite enzymes using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to develop a classification model for the characteristics of thyroid follicular tumors among 24 samples. We analyzed the expression of metabolic enzyme markers in an independent validation set of 133 cases and evaluated the potential biological behavior of 19 borderline thyroid lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than in FTC (P<0.001). The metabolic enzyme panel—including FA synthase and Ca²⁺-independent PLA2, which are closely associated with altered metabolic pathways—was further identified in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the receiver operating characteristic curve, sensitivity, and specificity: 73.6%, 82.1%, 60.6%, respectively). The diagnostic strategy suggested considering a putative role of AFAIDESI-MSI in routine clinical triage for strict follow-up, with low metabolic enzyme expression combined with diagnostic in patients with a thyroid follicular borderline tumor diagnosis.

In this paper, in order to provide proper parameters for the preparation of semi-solid billets, the semi-solid annealing of hot-rolled 2A14 Al alloy was investigated. The microstructure was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) with X-ray energy dispersive spectrometer (EDS) and electron backscattered diffraction (EBSD), scanning transmission electron microscope (STEM). XRD results show that with the increase of temperature, equilibrium θ-Al2Cu gradually dissolved in the matrix. The EDS results of SEM and STEM show that there were coarse θ-Al2Cu phase, ultra-fine precipitate Al(MnFeSi) or (Mn, Fe)Al6 phase and atomic clusters in the microstructure. EBSD results show that the recrystallization mechanism was dominated by continuous static recrystallization (CSRX), the homogeneous nucleation occurred when the sample was heated to near solidus temperature, and CSRX happened in the semi-solid temperature. In the process of recrystallization, the micro-texture changed from preferred orientation to random orientation. A variety of experimental results show that static recrystallization (SRX) occurred at semi-solid temperature due to the blocking effect of atomic clusters on dislocation slip and the Zener drag effect of fine precipitates on low angle grain boundaries (LAGBs) disappeared with melting at semi-solid temperature.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

Electromagnetic sensing has been used for diverse applications of non-destructive testing, including the surface inspection, measurement of properties, object characterization. However, the measurement accuracy could be significantly influenced by the lift-off between sensors and samples. To address the issue caused by lift-offs, various strategies have been proposed for the permeability measurement of ferromagnetic steels, which mainly involves different sensor designs and signal features (e.g., the zero-crossing feature). In this paper, a single high-frequency scenario for the permeability retrieval is introduced. By combining the signal of two sensing pairs, the retrieval of magnetic permeability is less affected by the lift-off of sensors. Unlike the previous strategy on reducing the lift-off effect (directly taking the phase term out of the integration) using the Dodd-Deeds analytical method, the proposed method is based on a high-frequency linear feature of the phase term. Therefore, this method has the merit of high accuracy and fast processing for the permeability retrieval (a simplified version of Dodd-Deeds analytical formulas after the integration). Experimental measurement has been carried out on the impedance measurement of designed sensors interrogating ferromagnetic dual-phase steels. For sensor lift-offs of up to 10 mm, the error of the permeability retrieval is controlled within 4 % under the optimal frequency.

The 3D reconstruction method using RGB-D camera has a good balance in hardware cost, point cloud quality and automation. However, due to the limitation of inherent structure and imaging principle, the acquired point cloud has problems such as a lot of noise and difficult registration. This paper proposes a three-dimensional reconstruction method using Azure Kinect to solve these inherent problems. Shoot color map, depth map and near-infrared image of the target from six perspectives by Azure Kinect sensor. Multiply the 8-bit infrared image binarization with the general RGB-D image alignment result provided by Microsoft to remove ghost images and most of the background noise. In order to filter the floating point and outlier noise of the point cloud, a neighborhood maximum filtering method is proposed to filter out the abrupt points in the depth map. The floating points in the point cloud are removed before generating the point cloud, and then using the through filter filters out outlier noise. Aiming at the shortcomings of the classic ICP algorithm, an improved method is proposed. By continuously reducing the size of the down-sampling grid and the distance threshold between the corresponding points, the point clouds of each view are continuously registered three times, until get the complete color point cloud. A large number of experimental results on rape plants show that the point cloud accuracy obtained by this method is 0.739mm, a complete scan time is 338.4 seconds, and the color reduction is high. Compared with a laser scanner, the proposed method has considerable reconstruction accuracy and a significantly ahead of the reconstruction speed, but the hardware cost is much lower and it is easy to automate the scanning system. This research shows a low-cost, high-precision 3D reconstruction technology, which has the potential to be widely used for non-destructive measurement of crop phenotype.

Eddy current testing can be used to interrogate steels but it is hampered by the lift-off distance of the sensor. Previously, the lift-off point of intersection (LOI) feature has been found for the pulsed eddy current (PEC) testing. In this paper, a lift-off invariant inductance (LII) feature is proposed for the multi-frequency eddy current (MEC) testing, which merely targets the ferromagnetic steels. That is, at a certain working frequency, the measured inductance signal is found nearly immune to the lift-off distance of the sensor. Such working frequency and inductance are termed as the lift-off invariant frequency (LIF) and LII. Through simulations and experimental measurements of different steels under the multi-frequency manner, the LII has been verified to be merely related to the sensor parameters and independent of different steels. By referring to the LIF of the test piece and using an iterative inverse solver, one of the steel properties (either the electrical conductivity or magnetic permeability) can be reconstructed with a high accuracy.

In many advanced industrial applications, the thickness is a critical index, especially for metallic coatings. However, the variance of lift-off spacing between sensors and test pieces affects the measured voltage or impedance, which leads to unreliable results from the sensor. Massive research works have been proposed to address the lift-off issue, but few of them applies to the thickness measurement of planar metallic films with finite-size circular (disk) geometry. Previously, a peak-frequency feature from the swept-frequency inductance was used to compensate the measurement error caused by lift-offs, which was based on the slow-changing rate of impedance phase term in the Dodd-Deeds formulas. However, the phase of measured impedance is nearly invariant merely on a limited range of sample thicknesses and working frequencies. Besides, the frequency sweeping is time-consuming, where a recalibration is needed for different sensor setups applied to the online real-time measurement. In this paper, a single-frequency algorithm has been proposed, which is embedded in the measurement instrument for the online real-time retrieval of thickness. Owing to the single-frequency measurement strategy, the proposed method does not need to recalibrate for different sensor setups. The thickness retrieval is based on a triple-coil sensor (with one transmitter and two receivers). The thickness of metallic disk foils is retrieved from the measured electrical resistance of two transmitter-receiver sensing pairs. Experiments on materials of different electrical conductivities (from direct current), thicknesses and planar sizes (radii) have been carried out to verify the proposed method. The error for the thickness retrieval of conductive disk foils is controlled within 5 % for lift-offs up to 5 mm.

Eddy current sensors can be used to test the characteristics and measure the parameters of the conductive samples. As the main obstacle of the multi-frequency eddy current sensor, the lift-off distance affects the effectiveness and accuracy of the measurement. In this paper, a material-independent algorithm has been proposed for the restoration of the lift-off distance when using the multi-frequency eddy current sensor, which is based on the approximation under the thin-skin effect. Experiment testing on the performance of the proposed method is presented. Results show that from the dual-frequency inductance, the lift-off distance could be restored with a maximum error of 0.24 mm for the distance up to 12 mm. Besides, the derived lift-off distance is used for the inversion of the magnetic permeability. Based on a lift-off insensitive inductance (LII) feature, the magnetic permeability of steels can be inversed in an iterative manner, with an error of less than 0.6 % for the lift-off distance up to 12 mm.

Lift-offs of the sensor could significantly affect the measurement signal and reconstruction of material properties when using the electromagnetic (inductive) eddy current sensor. Previously, various methods (including novel sensor designs, and features like zero-crossing frequency, lift-off point of intercept) have been used for eliminating the measurement error caused by the lift-off distance effect of the sensor. However, these approaches can only be applied for a small range of lift-off variations. In this paper, a linear relationship has been found between the sensor lift-off and ratio of dual-frequency eddy current signals, particularly under the high working dual frequencies. Based on this linear relationship, the lift-off variation can be reconstructed firstly with a small error of 2.5 % when its actual value is up to 10 mm (10.1 % for 20 mm). The reconstructed lift-off is used to further get the property of the material under a low single frequency. Experiments on different ferrous metals have been carried out for the testing of the reconstruction scheme. Since the inductance is more sensitive to the material property (and less sensitive to the lift-off) under low frequencies, the reconstruction error of the material property is much smaller than that of the lift-off, with 1.4 % under 12 mm (and 4.5 % under 20 mm).

Previously, various techniques have been proposed for reducing the lift-off effect on the thickness measurement of the non-magnetic films, including the peak-frequency feature and phase feature in the Dodd-Deed analytical formulation. To realise a real-time feedback response on the thickness monitoring, the phase term in the Dodd-Deeds formulation must be taken off the integration. Previous methods were based on the slow change rate of the phase term when compared to the rest of the term – the magnitude term. However, the change rate of the phase term is still considerable for a range of working frequencies. In this paper, a high-frequency feature has been found. That is, the ratio between the imaginary and real part of the phase term is proportional to the integral variable under high frequencies. Based on this proportion relationship, the phase term has been taken out; and a thickness algorithm has been proposed. By combing the measured impedance from the custom-built sensor (three coils), the thickness of the metallic film can be reconstructed. Experiments have been carried out for the verification of the proposed scenario. Results show that the thickness of the metal film can be reconstructed with a small error of less than 2 %, and immune to a reasonable range of lift-offs.

Epoxy asphalt (EA) concrete is widely used in constructing long-span steel bridge pavements (SBDPs). This study aims to derive a fatigue damage evolution law, conducting an experimental investigation of SBDP. First, a general theoretical form of the fatigue damage evolution law of materials is established based on the thermal motion of atoms. Then, fatigue experiments demonstrate that this evolution law well represents the known damage–life relationships of SBDP. Taking into account the experimental relationships between damage and fatigue life under symmetrical cyclic loadings with different overload amplitudes and temperature variations, a detailed damage evolution law is deduced. Finally, the role of damage accumulation is discussed on the basis of the proposed damage evolution law for the extreme situation of heavy overload and severe environments. The results show that both heavy loading and falling temperatures increase the fatigue damage of SBDP considerably; therefore, SBDP should avoid heavy loading combined with winter temperatures. EA shows a fatigue life two to three times longer than that of modified matrix asphalt (SMA) or guss asphalt (GA). For the same thickness, EA pavement is demonstrated to be more suitable for an anti-fatigue design of large-span SBDP under high traffic flows and low temperatures.

The type of tail of sheep is an important economic trait. However, the candidate genes associated with the tail type are uncertain. The objective of this study was to identify the genetic region and genotype responsible for the tail type phenotype. Here we perform a genome-wide association study (GWAS) in 40 large tailed Han sheep and 40 Altay sheep as case and 40 Tibetan sheep as control. The results indicated that a total 31 genome-wide significant SNPs associated with type of tail traits were detected. For significant SNPS loci, determine its physical location, and screening of candidate genes within section. By combining information of previously reported and annotated biological functional genes, we identified SPAG17, Tbx15, VRTN, NPC2, BMP2 and PDGFD as the most promising candidate genes for type of tail traits. Based on the above identified candidate genes on type of tail traits, we selected BMP2 and PDGFD to conduct the genetic effect analysis in a large Altay sheep and Tibetan sheep population. Rs119 T>C in the exon1 of BMP2 gene and 1 SNPs in the exon4 (rs69 C>A) of PDGFD gene were detected, rs119 that located on exon1 of BMP2 gene was TT genotype in Altay sheep, while with CC genotype in Tibetan sheep. On rs69 of PDGFD gene, Altay sheep with CC genotype, however, Tibetan sheep with AA genotype. These results indicated that the significant associations of SNPs detected in GWAS were indirectly caused by the genetic effects of BMP2 and PDGFD on sheep tail fat deposition.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

A phenomenological constitutive model is developed to describe the uniaxial transformation ratcheting behaviors of super–elastic shape memory alloy (SMA) by employing a cosine–type phase transformation equation with the initial martensite evolution coefficient that can capture the feature of the predictive residual martensite accumulation evolution and the nonlinear hysteresis loop on a finite element (FE) analysis framework. The effect of the applied loading level on transformation ratcheting are considered in the proposed model. The evolutions of transformation ratcheting and transformation stresses are constructed as the function of the accumulated residual martensite volume fraction. The FE implementation of the proposed model is carried out for the numerical analysis of transformation ratcheting of the SMA bar element. The integration algorithm and the expression of consistent tangent modulus are deduced in a new form for the forward and reverse transformation. The numerical results are compared with those of existing model and the experimental results to show the validity of the proposed model and its FE implementation in transformation ratcheting. Finally, a FE modeling is established for a repeated preload analysis of SMA bolted joint

Integrated ultra-low-loss waveguides are highly desired for integrated photonics to enable applications that require long delay lines, high-Q resonators, narrow filters, etc. Here we present an ultra-low-loss silicon waveguide on 500 nm thick SOI platform. Meter-scale delay lines, million-Q resonators and tens of picometer bandwidth grating filters are experimentally demonstrated. We design a low-loss low-reflection taper to seamlessly integrate the ultra-low-loss waveguide with standard heterogeneous Si/III-V integrated photonics platform to allow realization of high-performance photonic devices such as ultra-low-noise lasers and optical gyroscopes.

Halloysite nanotubes (HNTs) are natural occurring mineral clay nanotubes that have excellent application potential in different fields. However, HNTs are heterogeneous in size, surface charge and formation of surfacial hydrogen bond, which lead to weak affinity and aggregation at a certain extent. It is very important to modify the HNTs’ surface to expand its applications. In this review, the structural characteristics, performance and the related applications of surface-modified HNTs are reviewed. We focus on the surface-modified variation of HNTs, the effects of surface modification on the materials and related applications in various regions. In addition, future prospects and the meaning of surface modification were also discussed in HNTs studies. This review provides a reference for the application of HNTs modifications in the field of new nanomaterials.

Railway transportation is one of the main modes of long-distance coal transportation, and it is inevitable to cause environmental pollution during the transportation process. In order to improve the environment along the railway and increase the utilization rate of coal resources, this paper proposes a detection algorithm for scattered coal solidification layer during transportation based on the YOLO v8 model, and designs an intelligent recognition model suitable for coal solidification layer detection devices by combining fluorescence detection methods. Through experimental analysis, the model meets the requirements of practical detection and plays a crucial role in environmental protection, with strong practical application value.

Streptomyces sp. HNS054, which was previously isolated from a marine sponge, demonstrates vigorous growth and facile genetic modification. This study explores its potential as a marine ac-tinomycete chassis through complete genome sequencing and genetic engineering. With a 7.5 Mb genome containing 6678 predicted genes, 21 secondary metabolic biosynthetic gene clusters (BGCs), and 8 common site-specific recombination (SSR) system attB loci, HNS054 shows a close phylogenetic relation to S. griseoincarnatus strain RB7AG. Utilizing multiplexed site-specific ge-nome engineering (MSGE) and the CRISPR/Cas9 method, engineered strains derived from HNS054 (with three copies of the target BGCs) produce higher amounts of aborycin and ac-tinorhodin than S. coelicolor M1346 (containing three copies of the same BGCs). HNS054 stands out for its remarkable characteristics, including salt tolerance, rapid growth, and compatibility with synthetic biology tools, and positions it as a promising candidate for developing marine ac-tinomycete hosts to enhance secondary metabolite production.

Percutaneous kyphoplasty (PKP) is a highly successful treatment option for Kümmell's disease (KD). Due to the obstruction of the fibrocartilaginous membrane at the periphery of the intervertebral vacuum cleft (IVC) and inadequate osteointegration of conventional bone cement, there is insufficient locking strength between trabecular bone and bone cement in Kümmell's disease (KD), leading to postoperative displacement of the bone cement and sub-sequent early surgical failure. However, there is no standard strategy managing this complica-tion at present. We reported a rare case of premature bone cement displacement resulting in adjacent vertebra fracture. An 80-year-old male with Kümmell's disease at T10 received per-cutaneous kyphoplasty (PKP) with bone cement leaking into the upper disc. Only 3 days after the surgery, the patient complained of severe back pain again. X-ray and MRI showed bone cement displacement at T10, adjacent vertebra fracture at T9. In consideration of poor toler-ance of open surgery for the old patient, we successfully revised by using percutaneous ky-phoplasty with multi-point anchoring technique (A-PKP). During a 10-month postoperative follow-up, the patient reported pain relief. X-ray and three-dimensional CT scan revealed no obvious progress of bone cement displacement. Although the exact mechanism underlying this rare complication remains unclear, we observed that the premature bone cement dis-placement can result in adjacent vertebra fracture especially when the pattern of bone cement is blocky. Percutaneous kyphoplasty with multi-point anchoring technique (A-PKP) appears effective in managing this complication.

Subway construction is often in a complex natural and human-machine operating environment, and that complicated setting leads to subway construction more prone to safety accidents, which can cause substantial casualties and monetary losses. Thus, it is necessary to investigate the safety risks of subway construction. The existing literature on the identification and assessment of subway construction safety risks(SCSR) is susceptible to the influence of subjective factors. Moreover, although existing studies have explored the interrelationships between different risks, these studies usually analyze the interrelationships of single risks, lack the study of risk chain transfer relationships, and fail to find out the key path of risk transfer. Therefore, this paper innovatively combines text mining, association rules and complex networks to deep mine subway construction safety incident reports and explore risk transfer process. Firstly, it uses text mining technology to identify subway construction safety risk; Then, association rules are introduced to explore the causal relationships among safety risk; Finally, the key safety risk and important transfer paths of subway construction safety accidents (SCSA) are obtained based on the complex network model. Research results show that (a) improper safety management, unimplemented safety subject responsibilities, violation of operation rules, non-perfect safety responsibilities system and insufficient safety education and training are the key safety risk in SCSA; (b) two shorter key risk transfer paths in the subway construction safety network can be obtained: insufficient safety education and training→lower safety awareness→violation of operation rules→safety accidents; insufficient safety checks or hidden trouble investigations→violation of operation rules→safety accidents; (c) in the process of risk transfer, the risk can be controlled by controlling the key nodes or cutting off the transfer path. The results of the study provide new ideas and methods for SCSR identification and influence element mining, which help safety managers propose accurate subway construction safety risk control measures.

Breast cancer is the most common malignancy in women worldwide. The pathogenesis of this disease is closely related to the estrogen receptor alpha subtype (ERα). Therefore, it is of great importance to develop effective inhibitors of ERα activity for the treatment of breast cancer. In this paper, we propose a novel ensemble machine learning model for quantitative structure-activity relationship of anti-breast cancer drugs, which can effectively predict drug activity in small samples with multiple characteristic variables. To avoid the problem of over-fitting caused by low-correlation independent variables, the scoring mechanism of random forest was improved by incorporating three relevance indicators, including the maximum mutual information number, Pearson correlation coefficient and distance correlation coefficient, and 20 optimal molecular descriptors were selected. The Bayesian hyperparameter optimization method was used to optimize the parameters of multiple linear regression (MLR), support vector regression (SVR), and extreme gradient boosting (XGBoost), respectively. The AdaBoost strong learner was constructed by combining the weak learner with the weighted linear addition method. The results show that the proposed ensemble learning model has the best prediction performance compared to the three basic learner models and the CNN-LSTM combination prediction model. The root mean square error was reduced by 7.60%-26.51%. The mean relative error was reduced by 6.46%-30.92%. Goodness of fit increased by 9.57%-36.94%. Finally, the biological activities of 50 candidate compounds for ERα inhibitors were predicted, and it was found that 4-[2-benzyl-1-[4-(2-pyrrolidin-1-ylethoxy)phenyl]but-1-enyl]phenol had an excellent biological activity value pIC50, which had the potential to be an ERα inhibitor. The model proposed in this paper has good prediction accuracy, which can provide an effective reference for the discovery and development of anti-breast cancer drugs.