Search

A pair of atropisomers secofumitremorgins C (1a) and D (1b), together with fifteen known alkaloids (2-16), were isolated from a saltern-derived fungus Aspergillus fumigatus GXIMD00544. The structures of atropisomers 1a and 1b were elucidated by the detailed spectroscopic data, chemical reaction and quantum chemical calculations. Compounds 1 and 8 displayed antifungal spore germination effects against plant pathogenic fungus associated with sugarcane Fusarium sp. with inhibitory rates of 53% and 77% at the concentration of 100 µM, repectively. Atropisomers 1 also exhibited antifouling potential against Balanus amphitrite larval settlement with an inhibitory rate of 96% at the concentration of 100 µM. [ABSTRACT FROM AUTHOR]

Accurately obtaining wellbore-formation temperature distribution during drilling in fractured carbonate formations is the basis for effectively solving the problem of the well kick and loss circulation coexisting (WK-LC). Therefore, based on the energy conservation law and considering the convective heat transfer and variable mass flow caused by well kick and loss circulation, this paper developed a full transient heat transfer model of wellbore-formation coupled system under the WK-LC. The reliability of model was verified by field measured temperature data. Based on field well, the thermal behavior of wellbore-formation coupled system under normal condition, well kick, loss circulation and WK-LC were compared and studied. The results showed that the bottom-hole temperature of well kick and Case1-2 is higher than that of normal condition, while the bottom-hole temperature of loss circulation and Case3-4 is lower than that of normal condition. The temperature difference between annulus and drill string (TD-AD) shows a "wavy line" trend of increasing-decreasing-increasing-decreasing along the well depth. The TD-AD of wellhead is about 6 °C in normal and WK-LC conditions. The traditional wellhead temperature monitoring method can only distinguish well kick and leakage, and it is difficult to judge whether WK-LC occur. In addition, the influence of the distance and well kick/leakage rate difference between the well kick region and the leakage region on thermal behavior of wellbore-formation coupled system was discussed. Finally, a new auxiliary method is proposed to identify the well kick, the loss circulation and the WK-LC. Which will have a significant implication for well killing and leaking stoppage operations. • A new auxiliary method was proposed to identify the well kick, the loss circulation and the WK-LC. • A full transient heat transfer model of wellbore-formation coupled system under the WK-LC was developed. • Considered the convective heat transfer and variable mass flow caused by well kick and loss circulation. • Thermal behavior of wellbore-formation coupled system under WK-LC were studied. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms behind porcine primordial germ cell like cells (pPGCLCs) development, differentiation, and gametogenesis is crucial in the treatment of infertility. In this study, SOX9+ skin derived stem cells (SOX9+ SDSCs) were isolated from fetal porcine skin and a high-purity SOX9+ SDSCs population was obtained. The SOX9+ SDSCs were induced to transdifferentiate into PGCLCs during 8 days of cultured. The results of RNA-seq, western blot and immunofluorescence staining verified SDSCs have the potential to transdifferentiate into PGCLCs from aspects of transcription factor activation, germ layer differentiation, energy metabolism, and epigenetic changes. Both adherent and suspended cells were collected. The adherent cells were found to be very similar to early porcine primordial germ cells (pPGCs). The suspended cells resembled late stage pPGCs and had a potential to enter meiotic process. This SDSCs culture-induced in vitro model is expected to provide suitable donor cells for stem cell transplantation in the future. [Display omitted] • SOX9+ skin derived stem cells proliferated during cultured. • The adherent PGCLCs are similar as early PGCs in epigenetics and metabolism. • The suspended PGCLCs have potential to develop mature gamates. [ABSTRACT FROM AUTHOR]

• A double flow controlled discrete-time two-lane traffic system with vehicle-to-infrastructure communication is proposed. • A stable condition of the traffic system is derived with lyapunov stability theorem and given by linear matrix inequality. • The double flow control scheme can suppress traffic congestion efficiently. • The relative flow is more effective than the delayed flow in stabilizing traffic flow. • The control scheme can lower energy consumption of the traffic system. Through vehicle-to-infrastructure communication, the road-side units could collect traffic information of a selected road section and send the refined traffic information to the vehicles on the road after information processing with edge computing servers. To study the impact of traffic information in different road sections on traffic flow, a double flow controlled two-lane traffic system considering vehicle-to-infrastructure communication is introduced in this paper. The new traffic system is analyzed with Lyapunov stability theorem and a sufficient stable condition is provided in linear matrix inequality. Through simulation, the traffic flow evolution properties and energy consumption rules under different control gains and lane changing parameters are exhibited. The results show that traffic congestion and energy consumption of the two-lane traffic system can be suppressed by taking the delayed flow control information, the relative flow control information, and lane changing effect into account. Also, the role of the control strategy on traffic flow is revealed microscopically through a two-lane car-following model by transforming the macroscopic traffic flow to vehicle's velocity. It further proved the stabilization effect of the control information on traffic flow. This research can provide some theoretical guidance for traffic control through vehicle-to-infrastructure information interaction. [ABSTRACT FROM AUTHOR]

The North Konawe region in Indonesia, known for its lateritic nickel (Ni) deposits, holds significant potential for obtaining Ni resources. However, the complex topographic conditions of this area pose challenges. Exploring the application of remote sensing technology to reveal the spectral response mechanism of Ni grade from high-precision multispectral data and inversion of Ni grade represents a novel direction in future Ni resource exploration. Traditional remote sensing inversion methods solely consider the spectral characteristics of sample data and ignore vital geospatial location information. As a result, efficiently obtaining regional details of target substance content over large areas has become challenging. The introduction of the geographically weighted regression (GWR) method offers an opportunity for fine-grained Ni grade inversion based on remote sensing. This study focused on the E and K blocks within the lateritic Ni mining area in North Konawe. Through utilizing the WordView-3 multispectral data which exhibits immense potential in quantitative remote sensing inversion studies, GWR was employed to integrate spectral features and spatial information. The goal was to reveal the correlation between multispectral remote sensing data and Ni grade. The obtained results were then compared and analyzed with multiple linear regression (MLR) and back propagation neural network (BPNN) models. The findings revealed that GWR achieved the highest coefficient of determination R2 of 0.96, surpassing MLR and BPNN values of 0.05 and 0.17, respectively. Additionally, GWR exhibited the lowest root mean square error of 0.04, which was lower than those of MLR and BPNN with the values of 0.25 and 0.23, respectively. These results confirmed the enhanced stability and accuracy of the GWR method compared to MLR and BPNN. Furthermore, GWR effectively mapped the spatial distribution trends of Ni grades in the study area, providing evidence of the method's effectiveness in Ni grade inversion. The study also delved into the inversion effect of the GWR method in areas with varying weathering crust thickness and vegetation cover. The research revealed that higher values of weathering crust thickness negatively impacted the inversion effect. However, the influence mechanism of vegetation cover on Ni grade inversion necessitated further investigation. These results served as a significant demonstration of the remote sensing inversion of mineral resource grades in similar areas. They provided valuable insights for future exploration and decision-making processes. [ABSTRACT FROM AUTHOR]

As a new generation of information technology, blockchain plays an important role in business and industrial innovation. The employment of blockchain technologies in industry has increased transparency, security and traceability, improved efficiency, and reduced costs of production activities. Many studies on blockchain technology-enabled system construction and performance optimization in Industry 4.0 have been carried out. However, blockchain technology and smart manufacturing have been individually researched in academia and industry, according to the literature. This survey aims to summarize the existing research to provide theoretical foundations for applying blockchain technology to smart manufacturing, thus creating a more reliable and authentic smart manufacturing system. In this regard, the literature related to four types of critical issues in smart manufacturing is introduced: data security, data sharing, trust mechanisms and system coordination issues. The corresponding blockchain solutions were reviewed and analyzed. Based on the insights obtained from the above analysis, a reference framework for blockchain technology-enabled smart manufacturing systems is put forward. The challenges and future research directions are also discussed to provide potential guides for achieving better utilization of this technology in smart manufacturing. [ABSTRACT FROM AUTHOR]

Under the condition of vehicle-to-vehicle communication, different information transmission mechanisms may have different effects on the cooperative performance of road traffic. In this paper, a new car-following model with consideration of the iterative traffic information transmission mechanism of vehicle-to-vehicle communication is proposed. The influence of the iterative traffic information transmission mechanism on the cooperative car-following behavior has been revealed. It is proved that based on the iterative traffic information transmission of vehicle-to-vehicle communication, the information of the two nearest preceding vehicles ahead of the ego vehicle has the most obvious role in stabilizing traffic flow. Also, the information of the third or fourth vehicles in front of the ego vehicle has a certain stabilizing effect, but the traffic information of the fifth or further preceding vehicles in front of the ego vehicle has little effect in enhancing traffic stability. This result provides a reference vehicle number for the cooperative car-following performance under the iterative traffic information transmission mechanism of vehicle-to-vehicle communication. [ABSTRACT FROM AUTHOR]

Calsequestrin 1 (CASQ1) is the most crucial Ca2+ binding protein localized in the sarcoplasmic reticulum (SR) of skeletal muscle. With high capacity and low affinity for Ca2+, CASQ1 plays a significant role in maintaining a large amount of Ca2+ necessary for muscle contraction. However, only five mutations in CASQ1 have been identified to date. Here, we report a 42‐year‐old Chinese female patient who presented with a 12 years history of slowly progressive upper limb weakness, predominantly affecting distal muscles, which was uncommon comparing to other CASQ1‐related patients. Next‐generation sequencing (NGS) analysis revealed a novel heterozygous mutation (c.766G > A, p.Val256Met) in CASQ1. Functional studies confirmed the likely pathogenicity of this variant. Muscle histopathology revealed rare optically empty vacuoles in myofibers and atypical eosinophilic granules in the cytoplasm, which has not been observed before. We also performed a literature review on all the pathogenic mutations in CASQ1 and summarized their genetic and clinical characteristics. This is the first report on CASQ1‐related myopathy from China, further expanding the mutation spectrum of CASQ1 gene and provides new insights into the function of CASQ1. [ABSTRACT FROM AUTHOR]

Automatic diagnosis of brain diseases based on brain connectivity network (BCN) classification is one of the hot research fields in medical image analysis. The functional brain network reflects the brain functional activities and structural brain network reflects the neural connections of the main brain regions. It is of great significance to explore and explain the inner mechanism of the brain and to understand and treat brain diseases. In this paper, based on the graph structure characteristics of brain network, the fusion model of functional brain network and structural brain network is designed to classify the diagnosis of brain mental diseases. Specifically, the main work of this paper is to use the Laplacian graph embed the information of diffusion tensor imaging, which contains the characteristics of structural brain networks, into the functional brain network with hyper-order functional connectivity information built based on functional magnetic resonance data using the sparse representation method, to obtain brain network with both functional and structural characteristics. Projection of the brain network and the two original modes data to the kernel space respectively and then classified by the multi-task learning method. Experiments on the epilepsy dataset show that our method has better performance than several state-of-the-art methods. In addition, brain regions and connections that are highly correlated with disease revealed by our method are discussed. [ABSTRACT FROM AUTHOR]

The relatively low light intensity during autumn–winter or early spring and inclement weather such as rain or fog may lead to extended production periods and decreased quality of greenhouse-grown tomato seedlings. To produce high-quality tomato seedlings rapidly, the influences of supplementary lights with different spectra on the morphological and physiological traits of tomato seedlings were measured in a greenhouse. Supplemental lighting with the same daily light integrals (DLI) of 3.6 mol m−2d−1 was provided by white (W) light-emitting diodes (LEDs), white plus red (WR) LEDs, and red plus blue (RB) LEDs, respectively, and tomato seedlings grown under only sunlight irradiation were regarded as the control. Our results demonstrate that raised DLI by supplementary light improved the growth and development of greenhouse-grown tomato seedlings, regardless of the spectral composition. Under conditions with the equal DLI, the tomato seedlings grown under supplementary WR LEDs with a red to blue light ratio (R:B ratio) of 1.3 obtained the highest values of the shoot and root fresh weights, net photosynthetic rate, and total chlorophyll content. The best root growth and highest root activity of tomato seedlings were also found under the supplementary WR LEDs. Supplementary WR LEDs remarkably increased the stem firmness of the greenhouse-grown tomato seedlings, and increased the starch content in the leaves of greenhouse-grown tomato seedlings compared to the control. However, statistically significant differences did not occur in the sucrose, carotenoid contents, superoxide dismutase (SOD), and catalase (CAT) activities among the different supplemental lighting treatments. In conclusion, supplemental LED lighting could promote the growth and development of greenhouse-grown tomato seedlings grown under insufficient sunlight conditions. In addition, WR LEDs could obtain tomato seedlings with a higher net photosynthetic rate, higher root activity, and higher starch content compared with other treatments, which could be applied as supplementary lights in greenhouse-grown tomato seedlings grown in seasons with insufficient light. [ABSTRACT FROM AUTHOR]

With the rapid development of the hydrogen energy industry, the number of hydrogen cylinders has reached a very large scale. At present, both domestic and international experiences of hydrogen cylinder inspection are zero, which makes the inspection work more challenging and unpredictable. In recent years, more and more attention has been paid to the responsibility of safety in production, but the research on the risk and safety of cylinder inspection institutions is very limited. In this paper, the Job safety analysis (JSA) method is used to carry out systematic risk identification, risk assessment, risk prevention, and other research work of the cylinder inspection station. After the JSA method and experience accumulation, the management strategy is continuously perfecting, and the security risk level is absolutely decreasing. [ABSTRACT FROM AUTHOR]

Sand deposition in the wellbore is one of the most common problems in oil–gas and hydrate exploitation work. A detailed understanding of the migration characteristics of the sand bed and accurate prediction of the starting velocity of the sand bed are key aspects of effective sand carrying. Therefore, this study conducted a large‐scale outdoor gas–water–sand three‐phase flow experiment. The effects of critical factors such as flow pattern, sand size, sand bed height, and pipe inclination angle on sand bed startup velocity and migration were studied experimentally. The experimental results indicated that during the startup process of the sand bed, sand particles exhibited three states: rolling, jumping, and suspension. During the experiment, the sand bed morphology included a static bed, rolling bed, jumping bed, and suspension bed. Compared to a stratified flow, intermittent flow and agitated flow were more beneficial for the startup velocity of sand beds. An increase in pipe inclination also reduced the starting velocity of the sand bed. With an increase in sand size, the startup velocity of the sand bed increased correspondingly. However, there was no significant influence on the migration morphology of the sand bed. Additionally, the greater the thickness of the sand bed, the lower the starting velocity of the sand bed. Based on the stress states of sand grains, in combination with experimental data, this study used least‐squares estimation to establish a prediction model for the startup velocity of sand beds. The model prediction results were in good agreement with the experimental data. This study will provide a basis for predicting the startup velocity of sand beds during the gas–liquid two‐phase sand‐carrying process. [ABSTRACT FROM AUTHOR]

Postmenopausal osteoporosis is a metabolic disease caused by an imbalance between osteoclasts and osteoblasts. At present, the drug strategy for treating postmenopausal osteoporosis has some limitations and is unable to satisfy the demands of patients. Phillyrin (Phil) is an herbal extract from Forsythiae Fructus, with an inhibitory effect on osteolysis. In this study, we described the role of Phil in ovariectomy-induced osteoporosis and its effect on osteoclast differentiation in vitro. Eighteen female C57BL/6 mice were randomly divided into three groups: sham group (sham surgery and injection with 0.9% normal saline), ovariectomized group (ovariectomy and injection with 0.9% normal saline), and Phil group (ovariectomy and injecting Phil with 100 mg/kg for 2 days). Mice were sacrificed after 6-week Phil administration and femurs were harvested for microcomputed tomography (micro-CT) and histomorphology analyses. In vitro, we used different concentrations of Phil to study its effect on osteoclastogenesis. The results showed that the BV/TV, Tb.Th, and Tb.N in trabecular bone were increased in the Phil group compared with the OVX group, and the trabecular bone mass was remarkably decreased in the OVX group compared with the sham group. The number of osteoclasts was increased in the OVX group compared to the sham group, and the number and area of osteoclasts were decreased in the Phil group compared to the control group. Compared with the OVX group, the number and area of osteoclasts were reduced in the Phil group. In conclusion, Phil could inhibit the formation of osteoclasts, promote the growth of bone trabecular, and relieve osteoporosis caused by ovariectomy, with a certain clinical adoption value. [ABSTRACT FROM AUTHOR]

[Display omitted] • Application of Aster, Gaofen-5 and Sentinel-2 data in mineral exploration. • Remote sensing geological exploration characteristics of Lala region were summarized. • Seven new metallogenic prospective areas were delineated in Lala region. The Lala Copper Deposit, situated in the Kangdian Copper Belt, is a substantial copper reservoir. In recent years, extensive exploration for copper resources in the region has become critically important due to the growing demand for Lala copper deposit resources. Alteration minerals, serving as crucial indicators for prospecting, have not undergone systematic study regarding their spatial distribution and remote sensing geological structural features in the Iron Oxide-Copper-Gold (IOCG) type deposits of the Lala region. Multispectral and hyperspectral remote sensing data prove to be effective tools for exploring mineralization information. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and Principal Component Analysis (PCA) are utilized to extract the distribution of carbonate, iron oxides/hydroxide and quartz minerals. Gaofen-5 (GF-5) data and the Spectral Angle Mapper (SAM) method are applied to extract minerals such as albite, biotite, chlorite, hornblende and muscovite. Sentinel-2 data are employed for remote sensing geological structure interpretation in the Lala region. The results of remote sensing alteration anomaly extraction are validated through field verification, indoor spectral scanning analysis, and the calculation of the SID_SAM index. The mineralization alteration information extracted through remote sensing aligns well with field conditions upon verification. The SID_SAM indices for ASTER and GF-5 extraction results are 0.0272 and 0.0177, respectively, indicating a 35% improvement in GF-5 performance. This suggests that GF-5 hyperspectral data demonstrate superior capability in identifying alteration minerals compared to ASTER multispectral data. Finally, through a comprehensive analysis of remote sensing alteration minerals and structural features of known deposits, the study summarized the remote sensing geological exploration characteristics of IOCG-type deposits in the Lala copper deposit area. Seven new prospective areas for copper mineralization are ultimately identified. These research findings provide valuable references for the next exploration phase of similar deposits in the region. [ABSTRACT FROM AUTHOR]

Keywords: crystal structure; electrochemistry; hydrogen evolution reaction; l-ascorbic acid sensing; Ni(II) coordination polymer EN crystal structure electrochemistry hydrogen evolution reaction l-ascorbic acid sensing Ni(II) coordination polymer 171 178 8 03/11/22 20220201 NES 220201 1 Introduction As the exhaust gas produced by commonly used energy sources such as petroleum, fossils, and coal continue to erode and destroy the environment on which humans depend, it is essential to develop green and sustainable energy sources to replace these non-regenerative energy sources [[1]]. Structural analysis shows that the NiCP has a corrugated layer structure due to the bridging effect of terephthalate anion and the ligand L. The composite electrode supported by the NiCP-CPE exhibits good hydrogen evolution activity, with a I i SB 10 sb overpotential of -521 mV, and a Tafel slope of 123 mA dec SP -1 sp . In combination with the auxiliary bridging ligand terephthalate anions and nickel cations a new 2D Ni(II) coordination polymer (NiCP) has been prepared. [Extracted from the article]

Aim: Exosomes has been shown to be involved in the regulation of cancer progression. However, the role of exosome miR‐134‐5p in breast cancer (BC) progression is unclear. Methods: Exosomes were extracted from BC cells (MCF‐7 and MDA‐MB‐231) using differential centrifugation and were observed by transmission electron microscope (TEM). The protein levels of exosome markers, apoptosis markers, Rho GTPase activating protein 1 (ARHGAP1, an important oncogene in BC) and phosphatidylinositol 3‐kinase (PI3K)/protein kinase B (AKT) markers were detected by western blot (WB) assay. Quantitative real‐time PCR was used to measure the expression levels of miR‐134‐5p and ARHGAP1. Cell cycle and apoptosis, colony number, viability, migration, and invasion were determined by flow cytometry, colony formation assay, MTT assay, and transwell assay, respectively. The interaction between miR‐134‐5p and ARHGAP1 was confirmed using a dual‐luciferase reporter assay. Xenograft models were constructed to verify the role of exosome miR‐134‐5p in BC tumor growth in vivo. Results: MiR‐134‐5p was lowly expressed in BC cells and in the exosomes of BC cells. Overexpressed exosome miR‐134‐5p suppressed the proliferation, migration, invasion, and promoted the apoptosis of BC cells. ARHGAP1 was a target of miR‐134‐5p, and its silencing could inhibit BC progression. In addition, ARHGAP1 overexpression could reverse the negative regulation of miR‐134‐5p on BC progression. MiR‐134‐5p could target ARHGAP1 to inhibit the activity of PI3K/AKT pathway. Exosome miR‐134‐5p overexpression could suppress BC tumor growth via targeting ARHGAP1 in vivo. Conclusion: Exosome miR‐134‐5p restrained BC progression through regulating ARHGAP1/PI3K/AKT signaling pathway, suggesting that miR‐134‐5p might be a therapeutic target for BC. [ABSTRACT FROM AUTHOR]

In the future, the Internet of things (IoT) may provide huge volumes of data. Smart grids are a class of IoT electricity distribution systems that can control bidirectional energy flows between consumers and service providers (Barman et al. "IOT Based Smart Energy Meter for Efficient Energy Utilization in Smart Grid", 978-1-5386-4769-1 1831.00, 2018 IEEE). A typical smart grid features an advanced metering infrastructure (AMI), which automatically collects meter data from widely distributed sensors. A utility company that intends to use AMI must deploy smart meters, data concentrator units, and a meter data management system (MDMS). Concentrators collect ubiquitous messages from smart meters and transmit aggregated data to their MDMS. Although ubiquitous messages may enhance the efficiency of some electricity grids, any excessive volume of messages causes data congestion. This research considers the Reference Energy Disaggregation Data Set. Our proposed algorithm can compress meter data efficiently. Our contributions are as follows: First, thus far, numerous researchers have attempted to address smart grid problems with AMI systems, and here, we provide a relatively complete review of these attempts. Second, this paper presents a strategy to analyze this problem and propose a compression algorithm to compress meter data. This proposed algorithm combines several existing compression algorithms and operates from 2 to 10% more efficiently than previously published algorithms. [ABSTRACT FROM AUTHOR]

Exceptional points (EPs), the degeneracy points of non-Hermitian systems, have recently attracted great attention because of their potential of enhancing the sensitivity of quantum sensors. Unlike the usual degeneracies in Hermitian systems, at EPs, both the eigenenergies and eigenvectors coalesce. Although EPs have been widely explored, the range of EPs studied is largely limited by the underlying systems, for instance, higher-order EPs are hard to achieve. Here we propose an extendable method to simulate non-Hermitian systems and study EPs with quantum circuits. The system is inherently parity-time (PT) broken due to the non-symmetric controlling effects of the circuit. Inspired by the quantum Zeno effect, the circuit structure guarantees the success rate of the post-selection. A sample circuit is implemented in a quantum programming framework, and the phase transition at EP is demonstrated. Considering the scalable and flexible nature of quantum circuits, our model is capable of simulating large-scale systems with higher-order EPs. [ABSTRACT FROM AUTHOR]

Summary: Wood formation, which occurs mainly through secondary xylem development, is important not only for supplying raw material for the 'ligno‐chemical' industry but also for driving the storage of carbon. However, the complex mechanisms underlying the promotion of xylem formation remain to be elucidated. Here, we found that overexpression of Auxin‐Regulated Gene involved in Organ Size (ARGOS) in hybrid poplar 84 K (Populus alba × Populus tremula var. glandulosa) enlarged organ size. In particular, PagARGOS promoted secondary growth of stems with increased xylem formation. To gain further insight into how PagARGOS regulates xylem development, we further carried out yeast two‐hybrid screening and identified that the auxin transporter WALLS ARE THIN1 (WAT1) interacts with PagARGOS. Overexpression of PagARGOS up‐regulated WAT1, activating a downstream auxin response promoting cambial cell division and xylem differentiation for wood formation. Moreover, overexpressing PagARGOS caused not only higher wood yield but also lower lignin content compared with wild‐type controls. PagARGOS is therefore a potential candidate gene for engineering fast‐growing and low‐lignin trees with improved biomass production. [ABSTRACT FROM AUTHOR]

A new aqueous slurry-based laminated object manufacturing process for porous ceramics is proposed: firstly, an organic mesh sheet is pre-paved as a pore-forming template before slurry layer scraping; secondly, the 2D pattern is built with laser outline cutting of the dried mesh–ceramic composite layer; finally, the pore structure is formed after degreasing and sintering. Alumina parts with porosities of 51.5 %, round hole diameters of 80 ± 5 μm were fabricated using 70 wt. % solid content slurry and 100 mesh nylon net. Using an organic mesh as the framework and template not only reduces the risk of damage of the green body but also ensures the regularity, uniformity and connectivity of the micron scaled pore network. The layer-by-layer drying method avoids the delamination phenomenon and improves the paving density. The new method can realize the flexible design of the pore structure by using various organic mesh templates. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a prevalent inflammatory disorder affecting about 1% of the global population. The ubiquitin-specific protease 2 (USP2) is known to have a substantial influence on the regulation of several cellular processes. Both in vivo (using rats with collagen-induced arthritis, CIA) and in vitro (using human fibroblast-like synoviocytes, HFLS-RA) models of RA were used to examine the role of USP2 in RA. The proliferation of HFLS-RA cells was assessed using the cell counting kit 8 test and EdU staining. The technique used for the assessment of gene expression was quantitative real-time PCR. Protein expression was quantified using Western blot (WB) analysis, while the quantities of inflammatory factors and matrix metalloproteinases were assessed using an ELISA test. The co-immunoprecipitation and ubiquitination tests investigated the relationships between proteins and the underlying molecular pathways. The results of this study demonstrate an upregulation of USP2 expression in both vivo and vitro models of RA. In addition, our findings indicate that the overexpression of USP2 notably exacerbates both proliferation and inflammation. The consistent downregulation of USP2 resulted in a reduction in the secretion of inflammatory cytokines and a suppression of cellular proliferation. Furthermore, it was shown that USP2 interacts with tumor necrosis factor receptor-associated factor 2 (TRAF2) and facilitates the removal of ubiquitination chains from TRAF2, enhancing its stability. Our findings propose that USP2 functions as a favorable modulator of proliferation and inflammatory reactions in HFLS-RA, thereby indicating its potential as a therapeutic target for the treatment of RA. [ABSTRACT FROM AUTHOR]

Assessing ethanol (EtOH) and acetaldehyde (AcH), metabolites of alcohol, enables more precise evaluation of alcohol metabolism. In this study, we developed a biosensor capable of concurrently measuring EtOH and AcH solutions with high sensitivity, utilizing a cycling reaction mediated by two enzymes: alcohol dehydrogenase (ADH) and alcohol oxidase (AOD). Within the cycling reaction, β-nicotinamide adenine dinucleotide (NADH, λ ex = 340 nm, λ em = 490 nm) is oxidized when AcH is reduced to EtOH by ADH, while the EtOH produced in this reaction is oxidized by AOD, regenerating AcH. By detecting the consumption of oxygen or NADH in this reaction cycle, highly sensitive measurements of AcH and EtOH can be achieved. Initially, an AOD-ADH electrosensor was constructed to validate the feasibility of the cycling reaction by applying EtOH solution to the sensor. This electrosensor quantifies alcohol metabolites via the oxygen consumed in the cycling reaction, demonstrating a dynamic range for EtOH solution from 700 nM to 500 µM—a sensitivity two-fold greater than that achieved with the AOD membrane (1.4 µM–1 mM) alone. Subsequently, an ADH-AOD fluorosensor was developed, measuring alcohol metabolites via NADH consumption within the cycling reaction. The ADH-AOD fluorosensor demonstrated a dynamic range of 59 pM–100 µM for AcH solution, representing approximately a 1000-fold increase in sensitivity compared to the ADH membrane (70 nM–100 µM) alone. In future work, it is anticipated that utilizing this cycling reaction for the highly sensitive measurement of skin gases (EtOH and AcH) and facilitating non-invasive metabolic evaluations. [Display omitted] • Two different biosensors for measuring alcohol metabolites, ethanol (EtOH) and acetaldehyde (AcH), have been developed. • The biosensors employed a cycling reaction facilitated by alcohol dehydrogenase (ADH) and alcohol oxidase (AOD). • The AOD-ADH electrosensor demonstrated a two-fold increase in sensitivity compared to using the AOD membrane alone. • The ADH-AOD fluorosensor achieved approximately a 1000-fold increase in sensitivity compared to using the ADH membrane alone. • Potential applications of this measurement principle include measuring skin gases for non-invasive metabolic evaluations. [ABSTRACT FROM AUTHOR]

With the rapid development of advanced manufacturing and information technologies, smart manufacturing has been proposed and gained wide attention. As the crucial section of achieving smart manufacturing, machining quality prediction aims to use data and statistical methods to predict the quality level of products or services during manufacturing, service provision, or product delivery. However, most data-driven methods suffer from using unimodal data, ignoring the complementary of other modal data, and using a single model in one prediction task, ignoring model unstable fluctuations corresponding to different features. To bridge these gaps, a novel self-adaptive hybrid approach is proposed for obtaining high accuracy of machining quality prediction in the industrial IoT environment. Firstly, a prototype system is designed to collect and perceive multimodal data in the manufacturing workshop/system, which enables the collection and perception of more comprehensive multimodal data of physical space. Secondly, the integration of sensors, data acquisition instruments, and ontology models is used to perform the process environment, which enables the construction of information space to store and transmit multimodal data. Meanwhile, the principal component analysis and model training sensed data are used to perform the machine learning model, which enables the construction of different information models. Thirdly, a probability model matrix-based self-adaptive hybrid prediction strategy is used to perform the machining quality prediction, which enables a better fitting degree for the quality prediction task. Finally, a real-life case study and extensive experiments are conducted to verify the effectiveness and superiority of the proposed self-adaptive hybrid approach. [ABSTRACT FROM AUTHOR]

Purpose: In an intelligent transportation system (for short, ITS) environment, a vehicle's motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles' delayed velocities on traffic flow. Design/methodology/approach: This paper constructed a new car-following model to study the integration effect of multiple vehicles' delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation. Findings: It is found out that the integration of preceding vehicles' delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles' delayed velocities information should be considered in real traffic. Originality/value: The new car-following model by considering the integration effect of multiple vehicles' delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles' delayed velocities information is the best choice to stabilizing traffic flow. [ABSTRACT FROM AUTHOR]

A new one-dimensional Zn(II) coordination polymer, {[ZnCl2(BBM)]·CH3OH}n (2,2-(1,4-butanediyl)bis-1,3-benzimidazole [BBM]), has been obtained from the hydrothermal reaction of zinc chloride with the flexible bis-benzimidazole ligand BBM and characterized by single-crystal X-ray diffraction, elemental analysis, IR and UV–vis spectra. Structural analysis has revealed that the BBM ligand connects the Zn(II) atoms to form a square-wave chain, which is further extended into supramolecular layers through hydrogen bonds and π···π stacking interactions. Solid-state fluorescence investigations showed that the Zn(II) coordination polymer has an emission peak at 381 nm upon excitation at 330 nm, which is attributed to ligand-centered luminescence. It is only slightly red shifted as compared to the ligand but partially quenched due to the strong π···π stacking interactions. [ABSTRACT FROM AUTHOR]

Characterizing long‐term prescription data is challenging due to the time‐varying nature of drug use. Conventional approaches summarize time‐varying data into categorical variables based on simple measures, such as cumulative dose, while ignoring patterns of use. The loss of information can lead to misclassification and biased estimates of the exposure‐outcome association. We introduce a classification method to characterize longitudinal prescription data with an unsupervised machine learning algorithm. We used administrative databases covering virtually all 1.3 million residents of Manitoba and explicitly designed features to describe the average dose, proportion of days covered (PDC), dose change, and dose variability, and clustered the resulting feature space using K‐means clustering. We applied this method to metformin use in diabetes patients. We identified 27,786 metformin users and showed that the feature distributions of their metformin use are stable for varying the lengths of follow‐up and that these distributions have clear interpretations. We found six distinct metformin user groups: patients with intermittent use, decreasing dose, increasing dose, high dose, and two medium dose groups (one with stable dose and one with highly variable use). Patients in the varying and decreasing dose groups had a higher chance of progression of diabetes than other patients. The method presented in this paper allows for characterization of drug use into distinct and clinically relevant groups in a way that cannot be obtained from merely classifying use by quantiles of overall use.Distinction between stable and varying patterns of metformin use. [ABSTRACT FROM AUTHOR]

While sentiment analysis has been widely used in public opinion to explore tendency of users for a target product from large online review data, less work focus on aspect-level or fine-grained sentiment analysis in which the polarity of not only the aspect of a target object but also the attribute of that given aspect should be determinated. Recent work regards aspect-level sentiment analysis as two separate tasks, i.e., aspect classification and sentiment analysis, and this pipeline method leads to error propagation. To address this issue, this paper proposes an improved multi-way matching deep neural network model for fine-grained sentiment analysis, which jointly models the two tasks in one phase and improves current attention by directly capturing past attention in the multi-round alignment architecture, so as to prevent error propagation and attention deficiency problems. Experimental results on fine-grained sentiment analysis data sets of catering industry indicate that the F1 score of this model in actual test set reaches 0.7302 and EM score 87.1973, which are higher than baseline DocRNN model by 3.8% and 0.88% in F1 and EM, and are higher than SVM by 15.4% and 25.6%, which verified that our model could effectively predict fine-grained sentiment and have better generalization performance. [ABSTRACT FROM AUTHOR]

It is a great challenge to fabricate electrode with simultaneous high activity for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). Herein, a high‐performance bifunctional electrode formed by vertically depositing a porous nanoplate array on the surface of nickel foam is provided, where the nanoplate is made up by the interconnection of trinary Ni–Fe–Mo suboxides and Ni nanoparticles. The amorphous Ni–Fe–Mo suboxide and its in situ transformed amorphous Ni–Fe–Mo (oxy)hydroxide acts as the main active species for HER and OER, respectively. The conductive network built by Ni nanoparticles provides rapid electron transfer to active sites. Moreover, the hydrophilic and aerophobic electrode surface together with the hierarchical pore structure facilitate mass transfer. The corresponding water electrolyzer demonstrates low cell voltage (1.50 V @ 10 mA cm−2 and 1.63 V @ 100 mA cm−2) with high durability at 500 mA cm−2 for at least 100 h in 1 m KOH. [ABSTRACT FROM AUTHOR]

Reaction of 1,4-bis(benzo[d]oxazol-2-yl)butane (BBO) with [Ag(CH3CN)4(ClO4)] afforded a new binuclear silver(I) complex, with composition [Ag2(BBO)2(ClO4)2], characterized by elemental analysis, UV/Vis and IR spectroscopy, and single-crystal X-ray diffraction. The results show that the Ag(I) complex consists of a centrosymmetric dimetallacyclic structure assembled from two Ag(I) atoms and two bridging BBO ligands. The coordination environment of silver(I) complex can be described as distorted trigonal planar, with one oxygen atom from a perchlorate anion and two nitrogen atoms from two BBO ligands. The luminescence properties of the ligand and the Ag(I) complex were studied in the solid state. The emission peaks of the Ag(I) complex are attributed to ligand-centered transitions. There is no effect of the complexation except for a partial quenching. The cyclic voltammograms of the Ag(I) complex indicated an irreversible Ag+/Ag couple. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma (NPC) is a malignant tumor with poor prognosis, high morbidity, and mortality. Currently, immunocheckpoint therapy has led to new treatment strategies for almost all cancers, including nasopharyngeal carcinoma. Inducible T-cell aggregation ligand (ICOSL) belongs to the b7-cd28 immunoglobulin superfamily, which is a ligand of ICOS, and also begins to draw attention for its potential usage in cancer treatment. Previous studies from our laboratory have suggested that ICOS expression in tumor-infiltrating lymphocytes is correlated with beneficial outcome, but little is known about the role of ICOSL in NPC. In the current study, ICOSL expression in NPC tumor sections was stained by immunohistochemistry (IHC), and both lymphatic metastasis and distant metastasis showed decreased expression, which was negatively correlated with TNM stage of nasopharyngeal carcinoma. Importantly, high ICOSL expression was significantly associated with overall survival (OS) in patients with NPC (n = 225, p < 0.001), and multivariate analysis confirmed that high ICOSL expression was an independent prognostic factor. Fresh nasopharyngeal carcinoma specimens were excised, and the specific expression of cytokines was analyzed by enzyme-linked immunosorbent assay (ELISA). The expression level of ICOSL is positively correlated with interferon-gamma (IFN-γ) concentration in tumor tissues, which is characteristic of T helper 1 (Th1) cells. Knocking down ICOSL by RNAi did not influence the proliferation, migration, and invasion ability of NPC cells. Conclusively, ICOSL expression is associated with increased survival rate in patients with nasopharyngeal carcinoma, which may be a clinical biomarker for prognosis of nasopharyngeal carcinoma. [ABSTRACT FROM AUTHOR]

Background and Aim. Little information is available about the assessment and optimal use of the gamma-glutamyl transpeptidase-to-platelet ratio (GPR) and transient elastography (TE) in predicting liver cirrhosis in patients with chronic hepatitis B (CHB) and concurrent nonalcoholic fatty liver disease (NAFLD). This study is aimed at comparing their diagnostic performances and developing an optimal approach for predicting liver cirrhosis in CHB patients with NAFLD. Methods. Consecutive CHB patients with NAFLD were enrolled. The GPR was calculated, and TE was performed using liver biopsy as a reference standard. The accuracy of predicting liver cirrhosis using GPR and TE was assessed and compared, and an optimal approach was developed. Results. Both TE and GPR correlated significantly with the histological fibrosis stage. TE and GPR had excellent performance in predicting liver cirrhosis, and the comparison of areas under the receiver operating characteristic curves revealed that TE was superior to GPR (0.95 vs. 0.85, P=0.039). Moreover, the dual cutoffs established by the likelihood ratio showed that GPR had a similar misclassification but higher indeterminate rate than TE (54.5% vs. 11.7%, P<0.001). Additionally, a 2-step approach using GPR followed by TE had comparable performance to that of both GPR and TE tests for all patients (misclassification: 8.9% vs. 8.3%, P=0.866; indeterminate rate: 15.2% vs. 17.2%, P=0.750) but could reduce TE scans by approximately one-third. Conclusions. Both TE and GPR show excellent performance in predicting liver cirrhosis in CHB patients with NAFLD. The 2-step approach using GPR followed by TE may be optimal for the assessment of cirrhosis in CHB patients with NAFLD. [ABSTRACT FROM AUTHOR]

A novel strategy by incorporating TMAH (C 4 H 13 NO·5H 2 O) for the rapid synthesis of hierarchically porous ZIF-8 was proposed, which shortened the synthesis time, introduced mesopores and boosted the yield, leading to a significant improvement in the MB (methylene blue) adsorption performance. [Display omitted] Zeolitic imidazolate frameworks (ZIFs) have been widely applied in many research fields, such as catalysts and adsorption. To meet the needs of scale applications, the development of simple, rapid and high-yield synthesis is a great necessity. In this work, a novel and facile strategy for the rapid synthesis of micro-mesoporous ZIF-8-H at room temperature within a very short time of 16 min using inexpensive quaternary ammonium base (tetramethylammonium hydroxide pentahydrate, TMAH) as a template was proposed. Results showed that in addition to significantly shortening crystallization time, the TMAH template also induced abundant mesopores for ZIF-8-H, which can improve the adsorption rate and fully use the adsorption active sites. More importantly, the ZIF-8-H yield of the proposed strategy is 3.6 times more than that of the conventional method, which is conducive to the realization of large-scale production. Among ZIF-8-H- x - t , ZIF-8-H-0.8-16 prepared with TMAH/Zn2+ molar ratio x of 0.8 and reaction time t of 16 min exhibited the highest MB removal effectiveness of 96.3 ± 0.8%, a remarkable increase of 127% compared to ZIF-8-M prepared by conventional method (42.5 ± 0.9%). Additionally, the MB adsorption onto ZIF-8-M and ZIF-8-H-0.8-16 fitted well with the pseudo-first-order kinetics model and Langmuir isothermal model, suggesting the monolayer adsorption behavior is dominant. The ZIF-8-H-0.8-16 showed a maximum adsorption capacity of 47.90 mg/g, which is higher than that of ZIF-8-M. [ABSTRACT FROM AUTHOR]

Background and Aims: Serum immunoglobulins are frequently increased in patients with chronic liver disease, but little is known about the role of serum immunoglobulins and their correlations with interleukin-27 (IL-27) in patients with HBV-related acute-on-chronic liver failure (HBV-ACLF). This study was aimed at determining the role of serum immunoglobulin (IgG, IgA, and IgM) levels and their associations with IL-27 in noncirrhotic patients with HBV-ACLF.Methods: Samples were assessed from thirty patients with HBV-ACLF, twenty-four chronic hepatitis B (CHB) subjects, and eighteen normal controls. Disease severity of HBV-ACLF was evaluated. Serum IL-27 levels were examined by enzyme-linked immunosorbent assay. Immunoglobulin levels were assessed using immunoturbidimetric assay. Correlations between immunoglobulin levels and IL-27 were analyzed. Receiver operating characteristic (ROC) curves were used to predict the 3-month mortality.Results: 25 (83.3%) HBV-ACLF patients had elevated serum IgG levels (>1 ULN), 14 (46.7%) patients had elevated IgA, and 15 (50%) had raised IgM. IgG, IgA, and IgM levels were higher in HBV-ACLF patients than in CHB patients and normal controls. Moreover, IgG, IgA, and IgM levels were positively correlated with Tbil levels but negatively correlated with prothrombin time activity (PTA) levels. Additionally, IgG levels were significantly increased in nonsurviving patients than in surviving HBV-ACLF patients (P = 0.007) and positively correlated with MELD score (r = 0.401, P = 0.028). Also, IgG levels were positively correlated with IL-27 levels in HBV-ACLF patients (r = 0.398, P = 0.029). Furthermore, ROC curve showed that IgG levels could predict the 3-month mortality in HBV-ACLF patients (the area under the ROC curve: 0.752, P = 0.005).Conclusions: Our findings demonstrated that serum immunoglobulins were preferentially elevated in HBV-ACLF patients. IgG levels were positively correlated with IL-27 and may predict prognosis in HBV-ACLF patients. [ABSTRACT FROM AUTHOR]

A novel traffic lattice hydrodynamic model considering the effect of density integration is proposed and analyzed in the paper. Via linear stability theory, linear stability condition of the new model is derived, which reveals an improvement of traffic stability by considering the integration of continuous historical density information. Moreover, the nonlinear properties of the extended model are revealed through nonlinear analysis. The propagating backwards kink–antikink waves are generated by deriving the mKdV equation near the critical point and verified by numerical simulation. All the results show that the density integration effect can suppress traffic congestion efficiently in traffic lattice hydrodynamic modeling. [ABSTRACT FROM AUTHOR]

The paper presents the ring formation during the course of filamentation in laser and weak inhomogeneous plasma interaction. Due to the combined influence of off-axial component and plasma density ripple, normal single ring changed into abnormal splitted ring during the course of filamentation. With increase in off-axial component and plasma density ripple, the abnormal splitted ring became stronger. [ABSTRACT FROM AUTHOR]

Abstract A novel load transfer path analysis in mechanical structures is realized by using deep learning (DL) approach with high efficiency and accuracy. The load transfer paths on plate structures considering the light-weight and reinforcement designs are obtained through a mathematical index of the load transfer calculation, U*, which is generated by a proposed DL model. Finite element models (FEM) of different sample plates are firstly built to generate the corresponding U* data used as training data set. The DL model is then trained by a small amount of U* data set obtained from FEM with an optimized network structure by random search for hyper-parameters. U* index and load transfer paths on plates with any random hole openings and stiffeners are then obtained from the trained DL model and compared with the ground true results from FEM to prove the efficiency and accuracy of the DL model after training. Feasibility of the DL application to the load transfer path derivation on varying design of mechanical structure is proven for efficient structural analysis and design improvement without re-modeling and numerical calculations. [ABSTRACT FROM AUTHOR]

Background and Aims. Concordance between transient elastography (TE) and ultrasonography (US) in assessing liver fibrosis in patients with chronic hepatitis B (CHB) and concurrent nonalcoholic fatty liver disease (NAFLD) has been rarely studied. This study aimed to evaluate the individual and combined performances of TE and US in assessing liver fibrosis and cirrhosis. Patients and Methods. Consecutive CHB patients with NAFLD were prospectively enrolled. TE and US examinations were performed, with liver biopsy as a reference standard. Receiver operating characteristic (ROC) curves were obtained to evaluate the diagnostic performance. Differences between the areas under the ROC curves (AUCs) were compared using DeLong's test. Results. TE and US scores correlated significantly with the histological fibrosis staging scores. TE was significantly superior to US in the diagnosis of significant fibrosis (AUC, 0.84 vs 0.73; P=0.02), advanced fibrosis (AUC, 0.95 vs 0.76; P<0.001), and cirrhosis (AUC, 0.96 vs 0.71; P<0.001). Combining TE with US did not increase the accuracy of detecting significant fibrosis, advanced cirrhosis, or cirrhosis (P=0.62, P=0.69, and P=0.38, respectively) compared to TE alone. However, TE combined with US significantly increased the positive predictive value for significant fibrosis when compared to TE alone. The optimal cut-off values of TE for predicting advanced fibrosis and cirrhosis were 8.7 kPa and 10.9 kPa, with negative predictive values of 92.4% and 98.7%, respectively. Conclusions. TE is useful for predicting hepatic fibrosis and excluding cirrhosis in CHB patients with NAFLD. A combination of TE and US does not improve the accuracy in assessing liver fibrosis or cirrhosis. [ABSTRACT FROM AUTHOR]

Low-light stereo vision is a challenging problem because images captured in dark environment usually suffer from strong random noises. Some widely adopted algorithms, such as semiglobal matching, mainly depend on pixel-level information. The accuracy of local feature matching and disparity propagation decreases when pixels become noisy. Focusing on this problem, we proposed a matching algorithm that utilizes regional information to enhance the robustness to local noisy pixels. This algorithm is based on the framework of ADCensus feature and semiglobal matching. It extends the original algorithm in two ways. First, image segmentation information is added to solve the problem of incomplete path and improve the accuracy of cost calculation. Second, the matching cost volume is calculated with AD-SoftCensus measure that minimizes the impact of noise by changing the pattern of the census descriptor from binary to trinary. The robustness of the proposed algorithm is validated on Middlebury datasets, synthetic data, and real world data captured by a low-light camera in darkness. The results show that the proposed algorithm has better performance and higher matching rate among top-ranked algorithms on low signal-to-noise ratio data and high accuracy on the Middlebury benchmark datasets. [ABSTRACT FROM AUTHOR]

Background: IL-17-producing CD8+ T (Tc17) cells promote inflammation and have been identified in chronic hepatitis. However, the role of Tc17 cells in patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (HBV-ACLF) remains unclear.Methods: The frequency of Tc17 cells in blood samples from 66 patients with HBV-ACLF was determined by flow cytometry. The levels of Tc17 cell-related cytokines were measured by FlowCytomix assays. The prognostic prediction accuracy was evaluated by the receiver operating characteristic (ROC) curve analysis. Survival was analyzed using Kaplan-Meier curves. Mortality predictors were determined by the Cox regression analysis.Results: The frequency of Tc17 cells was markedly higher in patients with HBV-ACLF than in those with chronic hepatitis B and normal control subjects. Increased frequencies of Tc17 cells may indicate liver injury and were positively correlated with disease severity. The Tc17 cell frequency was significantly higher in non-surviving patients with HBV-ACLF than in surviving patients. The ROC curve analysis showed that Tc17 cell frequency accurately predicted 90-day survival in patients with HBV-ACLF, with an accuracy equivalent to those of the Model for End-Stage Liver Disease (MELD), MELD-Na, and Chronic Liver Failure Consortium ACLF scores. Kaplan-Meier analysis showed an association between the increase in circulating Tc17 cells and poor overall survival in patients with HBV-ACLF. Moreover, the multivariate Cox regression analysis showed that Tc17 cell frequency was an independent predictor of overall survival in patients with HBV-ACLF.Conclusion: Tc17 cells may play a proinflammatory role in HBV-ACLF pathogenesis. Furthermore, the increased frequency of circulating Tc17 cells could be an independent prognostic biomarker in patients with HBV-ACLF. [ABSTRACT FROM AUTHOR]

• An interrupted time series analysis of impact of USIVP in Manitoba. • Increased absolute change in SIV uptake percentage in the lowest income quintiles and with less healthcare utilization among 5–17-year-olds. • An upward annual trend in SIV uptake percentage among 5–17-year-olds. • A downward annual trend in SIV uptake percentage among 45–64-year-olds. • A downward annual trend across all strata of assessed population characteristics within all age groups in Northern Manitoba. Universal seasonal influenza vaccination policy (USIVP) was introduced in Manitoba, Canada in 2010. Its impact on seasonal influenza vaccine (SIV) uptake remains underexplored. We used population-wide data from Manitoba to assess the impact of the USIVP on SIV uptake. The study covered twenty influenza seasons (2000/01–2019/20). We summarized SIV uptake for influenza seasons before and after the USIVP. Utilizing a single-group interrupted time series analysis and appropriately accounting for autocorrelation, we estimated absolute change and annual trend in SIV uptake percentages among 5–17-, 18–44-, and 45–64-year-olds across strata of certain population socioeconomic and health-related characteristics following the USIVP. Average SIV uptake percentage in all age groups was significantly higher after compared with before the USIVP. Following the USIVP, there was no significant absolute change in SIV uptake percentage among 18–44- and 45–64-year-olds overall; however, a significant decrease was observed among 18–44-year-old males in the higher income quintiles, across healthcare utilization, and in some regions of residence. A significant increase was observed among 5–17-year-olds in the lowest income quintiles, in Northern Manitoba, and among those with less healthcare utilization, and no chronic disease. Overall, there was mostly no significant annual trend in SIV uptake percentage among 18–44-year-olds, and while a significant upward and downward trend was observed among 5–17-year-olds and 45–64-year-olds, respectively, a significant downward trend was observed across all strata of population characteristics within all age groups in Northern Manitoba. The USIVP in Manitoba was followed by an absolute increase in SIV uptake percentage only in some socioeconomically disadvantaged subpopulations among 5–17-year-olds. While there was mostly an upward annual trend in SIV uptake percentage among 5–17-year-olds, a downward trend was observed among 45–64-year-olds and across all age groups and subpopulations in socioeconomically disadvantaged Northern Manitoba. These findings are novel for Manitoba and require investigation and public health attention. [ABSTRACT FROM AUTHOR]

Multi-spectral imaging technologies have made great progress in the past few decades. The development of snapshot cameras equipped with a specific multi-spectral filter array (MSFA) allow dynamic scenes to be captured on a miniaturized platform across multiple spectral bands, opening up extensive applications in quantitative and visualized analysis. However, a snapshot camera based on MSFA captures a single band per pixel; thus, the other spectral band components of pixels are all missed. The raw images, which are captured by snapshot multi-spectral imaging systems, require a reconstruction procedure called demosaicing to estimate a fully defined multi-spectral image (MSI). With increasing spectral bands, the challenge of demosaicing becomes more difficult. Furthermore, the existing demosaicing methods will produce adverse artifacts and aliasing because of the adverse effects of spatial interpolation and the inadequacy of the number of layers in the network structure. In this paper, a novel multi-spectral demosaicing method based on a deep convolution neural network (CNN) is proposed for the reconstruction of full-resolution multi-spectral images from raw MSFA-based spectral mosaic images. The CNN is integrated with the channel attention mechanism to protect important channel features. We verify the merits of the proposed method using 5 × 5 raw mosaic images on synthetic as well as real-world data. The experimental results show that the proposed method outperforms the existing demosaicing methods in terms of spatial details and spectral fidelity. [ABSTRACT FROM AUTHOR]

Background: Stanford type B aortic dissection (TB‐AD) is a life‐threatening vascular condition with high rates of morbidity and mortality. Currently, thoracic endovascular aortic repair (TEVAR) is widely performed to treat TB‐AD, and some studies have analyzed the influence of stents on hemodynamics using computational fluid dynamics (CFD) models. However, the accuracy of TB‐AD simulation models are not satisfactory, they are often constructed as a regular ideal model. Furthermore, it is unclear which tear should be closed for the best treatment when there are multi entry tears. Purpose: The aims of this paper were to provide an assessment method for the selection of the surgical closure location for type B aortic dissection. Five 3D models of multiple entry tears in type B aortic dissection were produced using real patient computed tomography (CT) images to perform hemodynamic analyses of flow velocity streamlines, wall pressure, and wall shear stress. Methods: A Boolean operation was adopted to establish 3D models with multiple entry tears in type B aortic dissection based on patient‐specific CT images. The Mimics and Ansys plug‐in The Integrated Computer Engineering and Manufacturing code for Computational Fluid Dynamics (ICEM CFD) software were applied to mesh the 3D models. The flow velocity streamlines, wall pressures, and wall shear stresses were then analyzed in the finite element analysis software Fluent. Five 3D models were produced to compare the hemodynamic characteristics of different entry tear numbers, as well as the changes of different closure positions before and after closure. Results: The false lumen of the model with two entry tears had a higher wall pressure than that of model with multiple entry tears, which may tend to squeeze the true lumen and expand the false lumen. The load distribution of the vessel in the model with multiple entry tears had a more balanced flow velocity, and its wall pressure and shear stress were lower than that of model with two entry tears. For aortic dissection with two entry tears, the closure of the proximal entry tear was recommended, which helped to isolate and thrombose the false lumen, thereby improving the blood supply function of the true lumen. Because the postoperative vascular flow velocity and mechanical load performance of the vascular wall were still higher than those of normal blood vessels, the postoperative blood vessels remained pathological, and TEVAR did not restore the blood vessels to their original healthy state. Conclusions: Type B aortic dissection with two entry tears tend to squeeze the true lumen and expand the false lumen, resulting in a new entry tear and deterioration into multiple entry type B aortic dissection. The model of the vessel with multiple entry tears had a more balanced distribution in flow velocity and a smaller wall pressure and shear stress than that of the vessel with two entry tears. The closure of the proximal entry tear was considered an ideal solution for type B aortic dissection with two entry tears. [ABSTRACT FROM AUTHOR]

The freeze drying-based additive manufacturing can be used to process porous ceramics. However, the lack of freezing direction leads to the disorderly porous structure. This paper proposes a frozen slurry-based laminated object manufacturing (FS-LOM) for processing porous ceramics. Slurry was composed of water, alumina powder, and organic binder. The water in the fresh slurry layer crystallized to obtain a good support strength. The outline of 2D pattern was cut with laser to gasify ice crystal and binder. After stacking, the ice crystal freeze dried to obtain a porous structure. The lamellar ice crystals were induced to growth vertically by layer-by-layer freezing. The uniformity and orientation of the pore structure were improved, and the compression strength of the parts were improved. Due to the support of frozen slurry, the deformation of the green part was avoided. [ABSTRACT FROM AUTHOR]

In this paper, an extended car-following model accounting for cooperation driving system with vehicle’s velocity uncertainty is proposed based on the full velocity difference car-following model. To analyze the influence of vehicle’s velocity uncertainty on traffic evolution properties, the asymptotic and local stability conditions of the new car-following model are derived respectively by using the stability theory in control theory. Numerical simulation is carried out and it shows that the vehicle’s velocity uncertainty can impact vehicle starting process and the stability of traffic flow importantly. [ABSTRACT FROM AUTHOR]

A novel traffic lattice hydrodynamic model with consideration of varying time delay is proposed. The asymptotic stability condition of the new model is derived in the form of linear matrix inequality through Lyapunov stability theory and the traffic disturbance appearing in the new model can be suppressed under this stable condition. Numerical simulation shows that varying time delay affects the stability of traffic flow importantly and the traffic flow with consideration of varying time delay is more likely to develop into traffic congestion. [ABSTRACT FROM AUTHOR]

Abstract A new traffic lattice hydrodynamic model with consideration of historical current integration effect is proposed in this paper and the influence of current integration effect on traffic flow is studied through linear and nonlinear analyses. The linear stability condition obtained by linear analysis reveals that the traffic stability can be enhanced by considering the impact of historical current integration effect. Also the nonlinear analysis shows that the traffic density wave in the unstable region near the critical point can be described by the kink–antikink solution of the mKdV equation. Finally, numerical simulation is carried out to verify the analytical results and it is proved that the historical current integration effect can improve the stability of traffic flow importantly. Highlights • A new lattice hydrodynamic model considering historical current integration is built. • Linear analysis reveals the stability condition of the new model. • Nonlinear analysis uncovers the density wave in the unstable region. • The historical current integration effect can enhance traffic stability efficiently. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy and stability of K-means algorithm and solve the problem of determining the most appropriate number K of clusters and best initial seeds, an improved K-means algorithm based on density Canopy is proposed. Firstly, the density of sample data sets, the average sample distance in clusters and the distance between clusters are calculated, choosing the density maximum sampling point as the first cluster center and removing the density cluster from the data sets. Defining the product of sample density, the reciprocal of the average distance between the samples in the cluster, and the distance between the clusters as weight product, the other initial seeds is determined by the maximum weight product in the remaining data sets until the data sets is empty. The density Canopy is used as the preprocessing procedure of K-means and its result is used as the cluster number and initial clustering center of K-means algorithm. Finally, the new algorithm is tested on some well-known data sets from UCI machine learning repository and on some simulated data sets with different proportions of noise samples. The simulation results show that the improved K-means algorithm based on density Canopy achieves better clustering results and is insensitive to noisy data compared to the traditional K-means algorithm, the Canopy-based K-means algorithm, Semi-supervised K-means++ algorithm and K-means-u* algorithm. The clustering accuracy of the proposed K-means algorithm based on density Canopy is improved by 30.7%, 6.1%, 5.3% and 3.7% on average on UCI data sets, and improved by 44.3%, 3.6%, 9.6% and 8.9% on the simulated data sets with noise signal respectively. With the increase of the noise ratio, the noise immunity of the new algorithm is more obvious, when the noise ratio reached 30%, the accuracy rate is improved 50% and 6% compared to the traditional K-means algorithm and the Canopy-based K-means algorithm. [ABSTRACT FROM AUTHOR]