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Abstract Cervical cancer poses a significant health risk to women. Deep learning methods can assist pathologists in quickly screening images of suspected lesion cells, greatly improving the efficiency of cervical cancer screening and diagnosis. However, existing deep learning methods rely solely on single-scale features and local spatial information, failing to effectively capture the subtle morphological differences between abnormal and normal cervical cells. To tackle this problem effectively, we propose a cervical cell detection method that utilizes multi-scale spatial information. This approach efficiently captures and integrates spatial information at different scales. Firstly, we design the Multi-Scale Spatial Information Augmentation Module (MSA), which captures global spatial information by introducing a multi-scale spatial information extraction branch during the feature extraction stage. Secondly, the Channel Attention Enhanced Module (CAE) is introduced to achieve channel-level weighted processing, dynamically optimizing each output feature using channel weights to focus on critical features. We use Sparse R-CNN as the baseline and integrate MSA and CAE into it. Experiments on the CDetector dataset achieved an Average Precision (AP) of 65.3%, outperforming the state-of-the-art (SOTA) methods.

It is crucial for robotic picking fruit to recognize fruit accurately in orchards, this paper reviews the applications and research results of target recognition in orchard fruit picking by using machine vision and emphasizes two methods of fruit recognition: the traditional digital image processing method and the target recognition method based on deep learning. Here, we outline the research achievements and progress of traditional digital image processing methods by the researchers aiming at different disturbance factors in orchards and summarize the shortcomings of traditional digital image processing methods. Then, we focus on the relevant contents of fruit target recognition methods based on deep learning, including the target recognition process, the preparation and classification of the dataset, and the research results of target recognition algorithms in classification, detection, segmentation, and compression acceleration of target recognition network models. Additionally, we summarize the shortcomings of current orchard fruit target recognition tasks from the perspectives of datasets, model applicability, universality of application scenarios, difficulty of recognition tasks, and stability of various algorithms, and look forward to the future development of orchard fruit target recognition.

There exist some perovskites materials with no photoluminescence (PL), which will greatly limit the practical applications in photodetection, display and lighting. Here, we achieve an exotic pressure-induced emission (PIE) at a mild pressure of 0.8 GPa from initially non-emissive 2D all-inorganic perovskite Cs3Sb2Br9 quantum dots, when the sample was subjected to external pressure. With the increase of pressure, the PL intensity gradually increases and the emission color transforms from red to green. Combined with subsequent experiments and computations, thus PIE behavior and piezochromism result from the SbBr6 octahedral distortion, accompanied by a structural phase transition from trigonal to monoclinic under pressure. Our work provides a robust strategy to boost the emission efficiency and to construct multi-functional PIE materials with piezochromism in environmentally friendly perovskites, thus facilitating the diverse applications in futural practices.

Abstract Generally, the recognition performance of lightweight models is often lower than that of large models. Knowledge distillation, by teaching a student model using a teacher model, can further enhance the recognition accuracy of lightweight models. In this paper, we approach knowledge distillation from the perspective of intermediate feature-level knowledge distillation. We combine a cross-stage feature fusion symmetric framework, an attention mechanism to enhance the fused features, and a contrastive loss function for teacher and student models at the same stage to comprehensively implement a multistage feature fusion knowledge distillation method. This approach addresses the problem of significant differences in the intermediate feature distributions between teacher and student models, making it difficult to effectively learn implicit knowledge and thus improving the recognition accuracy of the student model. Compared to existing knowledge distillation methods, our method performs at a superior level. On the CIFAR100 dataset, it boosts the recognition accuracy of ResNet20 from 69.06% to 71.34%, and on the TinyImagenet dataset, it increases the recognition accuracy of ResNet18 from 66.54% to 68.03%, demonstrating the effectiveness and generalizability of our approach. Furthermore, there is room for further optimization of the overall distillation structure and feature extraction methods in this approach, which requires further research and exploration.

Abstract To understand aging impact on the circadian rhythm, we screened for factors influencing circadian changes during aging. Our findings reveal that LKRSDH mutation significantly reduces rhythmicity in aged flies. RNA-seq identifies a significant increase in insulin-like peptides (dilps) in LKRSDH mutants due to the combined effects of H3R17me2 and H3K27me3 on transcription. Genetic evidence suggests that LKRSDH regulates age-related circadian rhythm changes through art4 and dilps. ChIP-seq analyzes whole genome changes in H3R17me2 and H3K27me3 histone modifications in young and old flies with LKRSDH mutation and controls. The results reveal a correlation between H3R17me2 and H3K27me3, underscoring the role of LKRSDH in regulating gene expression and modification levels during aging. Overall, our study demonstrates that LKRSDH-dependent histone modifications at dilps sites contribute to age-related circadian rhythm changes. This data offers insights and a foundational reference for aging research by unveiling the relationship between LKRSDH and H3R17me2/H3K27me3 histone modifications in aging.

Epigenetic regulation is important for circadian rhythm. In previous studies, multiple histone modifications were found at the Period (Per) locus. However, most of these studies were not conducted in clock neurons. In our screen, we found that a CoREST mutation resulted in defects in circadian rhythm by affecting Per transcription. Based on previous studies, we hypothesized that CoREST regulates circadian rhythm by regulating multiple histone modifiers at the Per locus. Genetic and physical interaction experiments supported these regulatory relationships. Moreover, through tissue-specific chromatin immunoprecipitation assays in clock neurons, we found that the CoREST mutation led to time-dependent changes in corresponding histone modifications at the Per locus. Finally, we proposed a model indicating the role of the CoREST complex in the regulation of circadian rhythm. This study revealed the dynamic changes of histone modifications at the Per locus specifically in clock neurons. Importantly, it provides insights into the role of epigenetic factors in the regulation of dynamic gene expression changes in circadian rhythm.

ObjectiveTo characterize the gas production phenomenon in the animal model of left ventricular assist device (LVAD), and study its mechanism.MethodsAn in vitro bubble precipitation experiment was conducted, and the blood samples of Parma spp. animals were divided into ordinary group and oxygen-enriched group according to whether they were oxygenated or not at the time of blood collection, and a static control group was set up respectively. Blood gases were drawn and analyzed before and after the experiment. Activate the pump, and the number of air bubbles in the loop was measured by ultrasound at different rotational speeds; CFD was applied to simulate the flow field in the blood pump, and pressure, fluid velocity vector and shear force diagrams were plotted, and a thrombus model was constructed and the flow field was simulated and plotted as a cloud diagram.ResultsThere was a statistical difference in the number of bubbles in the inflow and outflow tubes of the blood pump (P values of 0.04 and 0.023, respectively), and the number of bubbles in the outflow tubes of both groups was significantly higher than the number of bubbles in the inflow tubes. The number of bubbles in the tubes of both the oxygen-enriched and normal groups was significantly higher than that in the inflow group. In both the normal and oxygen-enriched groups, more gas was produced at higher speeds than at lower speeds. Blood gas analysis showed that the reduced gas composition in the blood was mainly oxygen. Flow field simulation results: the high rotation speed group had lower central pressure and greater scalar shear. The thrombus simulation group was more prone to turbulence, sudden pressure changes, and greater shear than the normal group.ConclusionBlood gas production is associated with higher partial pressures of blood oxygen, higher rotation speed, and intrapump thrombosis, and the mechanism of pump gas production is degassing of dissolved gases rather than cavitation of water, and the gas released is most likely to have oxygen. The degassing phenomenon is an warning factor for pump thrombosis.

The integrated multi-satellite retrievals for the global precipitation measurement (IMERG) data, which is the latest generation of multi-satellite fusion inversion precipitation product provided by the Global Precipitation Measurement (GPM) mission, has been widely applied in hydrological research and applications. However, the quality of IMERG data needs to be validated, as this technology is essentially an indirect way to obtain precipitation information. This study evaluated the performance of IMERG final run (version 6.0) products from 2001 to 2020, using three sets of gauge-derived precipitation data obtained from the Integrated Surface Database, China Meteorological Administration, and U.S. Climate Reference Network. The results showed a basic consistency in the spatial pattern of annual precipitation total between IMERG data and gauge observations. The highest and lowest correlations between IMERG data and gauge observations were obtained in North Asia (0.373, p < 0.05) and Europe (0.308, p < 0.05), respectively. IMERG data could capture the bimodal structure of diurnal precipitation in South Asia but overestimates a small variation in North Asia. The disparity was attributed to the frequency overestimation but intensity underestimation in satellite inversion, since small raindrops may evaporate before arriving at the ground but can be identified by remote sensors. IMERG data also showed similar patterns of interannual precipitation variability to gauge observation, while overestimating the proportion of annual precipitation hours by 2.5% in North America, and 2.0% in North Asia. These findings deepen our understanding of the capabilities of the IMERG product to estimate precipitation at the hourly scale, and can be further applied to improve satellite precipitation retrieval.

Abstract In nature, spider web is an interwoven network with high stability and elasticity from silk threads secreted by spider. Inspired by the structure of spider webs, light‐driven liquid crystal elastomer (LCE) active yarn is designed with super‐contractile and robust weavability. Herein, a novel biomimetic gold nanorods (AuNRs) @LCE yarn soft actuator with hierarchical structure is fabricated by a facile electrospinning and subsequent photocrosslinking strategies. Meanwhile, the inherent mechanism and actuation performances of the as‐prepared yarn actuator with interleaving network are systematically analyzed. Results demonstrate that thanks to the unique “like‐spider webs” structure between fibers, high molecular orientation within the LCE microfibers and good flexibility, they can generate super actuation strain (≈81%) and stable actuation performances. Importantly, benefit from the robust covalent bonding at the organic–inorganic interface, photopolymerizable AuNRs molecules are uniformly introduced into the polymer backbone of electrospun LCE yarn to achieve tailorable shape‐morphing under different light intensity stimulation. As a proof‐of‐concept illustration, light‐driven artificial muscles, micro swimmers, and hemostatic bandages are successfully constructed. The research disclosed herein can offer new insights into continuous production and development of LCE‐derived yarn actuator that are of paramount significance for many applications from smart fabrics to flexible wearable devices.

When autonomous underwater vehicles (AUVs) perform underwater tasks, the absence of GPS position assistance can lead to a decrease in the accuracy of traditional navigation systems, such as the extended Kalman filter (EKF), due to the accumulation of errors. To enhance the navigation accuracy of AUVs in the absence of position assistance, this paper proposes an innovative navigation method that integrates a position correction model and a velocity model. Specifically, a velocity model is developed using a dynamic model and the Optimal Pruning Extreme Learning Machine (OP-ELM) method. This velocity model is trained online to provide velocity outputs during the intervals when the Doppler Velocity Log (DVL) is not updating, ensuring more consistent and reliable velocity estimation. Additionally, a position correction model (PCM) is constructed, based on a hybrid gated recurrent neural network (HGRNN). This model is specifically designed to correct the AUV’s navigation position when GPS data are unavailable underwater. The HGRNN utilizes historical navigation data and patterns learned during training to predict and adjust the AUV’s estimated position, thereby reducing the drift caused by the lack of real-time position updates. Experimental results demonstrate that the proposed VM-PCM-EKF algorithm can significantly improve the positioning accuracy of the navigation system, with a maximum accuracy improvement of 87.2% compared to conventional EKF algorithms. This method not only improves the reliability and accuracy of AUV missions but also opens up new possibilities for more complex and extended underwater operations.

This research focused on a newly developed heterojunction nanocomposite, TiO _2 /Ag _2 WO _4 , which combines titanium dioxide (TiO _2 ) and silver tungstate(VI) (TiO _2 /Ag _2 WO _4 ) to enhance the photocatalytic performance. The TiO _2 /Ag _2 WO _4 photocatalyst was characterized using FT-IR, XRD, DRS, PL, SEM, EDS, and XPS. TiO _2 /Ag _2 WO _4 proved to be an effective nanophotocatalyst for synthesizing chromeno[4,3-b]chromene derivatives, which exhibit potential antibacterial and antifungal properties relevant to oral health issues like dental caries and periodontal disease. TiO _2 can absorb light to generate electrons and holes when exposed to direct light; however, combining it with Ag _2 WO _4 enhances its photocatalytic activity. The study also examined the effects of various factors such as the amount of photocatalyst, reaction time, temperature, solvent choice, and the reusability of the nanocomposite. The best reaction condition involves 1 mmol of dimedone, benzaldehyde, and 4-hydroxycoumarin in the presence of 15 mg TiO _2 /Ag _2 WO _4 in 3 ml ethanol under irradiation of a green laser at room temperature for 60 min. Findings of this investigation show that TiO _2 /Ag _2 WO _4 heterojunction is one of the best among the similar introduced counterparts in photocatalytic synthesis of chromeno[4,3-b]chromene derivatives.

Warm WLED with high color rendering index (CRI) are greatly required for the widespread use of solid-state lighting especially indoors. Here, a remarkable improvement of CRI in alloyed CdS0.7Se0.3 QDs was achieved by pressure engineering. Notably, white light with enhanced CRI of 93, higher than pristine CRI of 47, was retained upon the complete release of pressure, accompanied by a color change from ‘natural’ (4298 K) to ‘warm’ white light (2170 K). Synchrotron ADXRD shows that CdS0.7Se0.3 QDs experienced an irreversible phase transition from the zinc blende phase to rocksalt structure.

The swirl ratio is the most critical parameter for determining the intensity and structure of tornado-like vortex, defined as the ratio of angular momentum to radial momentum. The angle of entry flow and the updraft radius are two key parameters affecting the swirl ratio. Many laboratory simulators have studied the effect of swirl ratio by changing the angle of entry flow, but there is a lack of research on the updraft radius. Therefore, for a deep sight of the impact of the updraft radius on the swirl ratio and tornado-like vortex, a laboratory tornado simulator capable of adjusting the updraft radius was designed, built, and tested. And, the effects of various swirl ratios caused by the updraft radius and the angle of entry flow on the tornado-like vortices were investigated, in terms of the dual-celled vortex transformation and vortex wandering. It was found that the effects of the updraft radius and the angle of turning vanes on the tornado-like vortices are quite different, and the formation of the dual-celled vortex is more sensitive to the updraft radius, because a larger angular momentum and axial pressure gradient can be provided. In addition, increasing the updraft radius has a greater inhibitory effect on the vortex wandering phenomenon compared to the angle of the turning vanes due to the flow fluctuations induced by turbulence.

Climate change research has received increasing attention from both researchers and the public, and the analysis of precipitation is one of the most important topics in this field. As a supplement to gauge observations, satellite-derived precipitation data present advantages, as they have high spatiotemporal resolution and good continuity. The Global Precipitation Measurement (GPM) mission is the newest generation of precipitation measurement products designed to conduct quasi-global satellite observations. This study used the latest Integrated Multi-satellitE Retrievals for GPM data collected between 2001 and 2020 to analyze changes in precipitation amount, frequency, and intensity on global land and ocean surfaces. The results showed that precipitation intensity over the ocean was generally higher than on land, and the two were more similar at the hourly scale than at the daily scale, as shown by the JS divergence statistics: 0.0323 and 0.0461, respectively. This may be due to the thermodynamic differences between land and the ocean, which can accumulate over a longer time scale. The average number of annual precipitation hours and days increased by 50 h and 5 days during 2011–2020 compared with the previous decade. The absence of obvious changes in annual precipitation amounts led to a decrease in annual precipitation intensity and the weakening of extreme precipitation on land. The analysis of precipitation regimes in nine mainland regions of the globe showed a significant increasing trend for both hourly and daily precipitation in North Asia, while insignificant changes or even decreasing trends were detected in the other regions. The results of this study elucidated the variations in precipitation between land and ocean areas and can contribute to the understanding of global precipitation.

Abstract Coalbed gas extraction is an important means of exploiting and utilizing gas resources, as well as a means of preventing coal mine disasters. In view of the low gas extraction rate from coalbeds with high gas content and low permeability, a method of improving permeability through deep-hole cumulative blasting is applied to develop initial directional fractures using a jet flow. Under the action of the blasting stress wave and detonation gas wedge, the fractures extend over a large range within the coal, thereby improving coalbed permeability. This study focuses on the criteria of cumulative blasting-induced coalbed fracturing based on a literature review of the penetration effect of cumulative blasting. On this basis, we summarize the coal fracturing zone, crack extension process, and the key technologies of charging and hole sealing for cumulative blasting. In addition, the latest research progress in the optimization of field test drilling and blasting parameters for cumulative blasting is introduced. Research findings indicate that the permeability improvement mechanism of cumulative blasting could be further enhanced, and the technology and technical equipment are in urgent need of improvement. Finally, development trends in the cumulative blasting permeability improvement technique are identified.

Radix Paeoniae Rubra (Chishao), a typical multi-origin Chinese medicinal material, originates from the dried roots of Paeonia lactiflora or P. veitchii. The previous study suggested that these two commonly used Chishao showed variation in their chemical compositions and clinical efficacies. Therefore, accurate identification of different Chishao species was of great significance for the guide of clinical medication, and timely treatment of patients. In this study, the chloroplast genome sequences of P. lactiflora and P. veitchii were obtained by next-generation sequencing (NGS) technology, and then the hypervariable regions were selected to design two mini-barcode candidates for species identification. Combined with DNA metabarcoding technology, we performed qualitative and quantitative analysis on the artificially mixed samples of P. lactiflora and P. veitchii and evaluated the identification ability of these mini-barcode candidates. Furtherly, the mini-barcode with good performance was applied to distinguish the Chinese patent medicine “cerebral thrombosis tablets” containing Chishao. The results indicated that the chloroplast genomes of P. lactiflora and P. veitchii were 152,750 and 152,527 bp, respectively. As published previously, they exhibited a typical quadripartite structure including a large single-copy region (LSC), a small single-copy region (SSC) and a pair of inverted repeat regions (IRs). The nucleotide polymorphism analysis revealed seven variable protein-coding regions as petL, psaI, psbJ, rpl16, ycf1b, psaC, and ndhF, and two mini-barcodes were developed from ycf1b and ndhF respectively. The result suggested that both two mini-barcodes performed well distinguishing P. lactiflora from P. veitchii. Besides, P. lactiflora was the only raw material of Chishao in all collected “cerebral thrombosis tablets” samples. In general, this study has established a method to realize the qualitative and quantitative identification of Chishao as multi-origin Chinese medicinal materials, which can be applied to Chinese patent medicines containing Chishao.

In order to remedy the defects of single sensor in robustness, accuracy, and redundancy of target detection, this paper proposed a method for detecting obstacles in farmland based on the information fusion of a millimeter wave (mmWave) radar and a camera. Combining the advantages of the mmWave radar in range and speed measurement and the camera in type identification and lateral localization, a decision-level fusion algorithm was designed for the mmWave radar and camera information, and the global nearest neighbor method was used for data association. Then, the effective target sequences of the mmWave radar and the camera with successful data association were weighted to output, and the output included more accurate target orientation, longitudinal speed, and category. For the unassociated sequences, they were tracked as new targets by using the extended Kalman filter algorithm and were processed and output during the effective life cycle. Lastly, an experimental platform based on a tractor was built to verify the effectiveness of the proposed association detection method. The obstacle detection test was conducted under the ROS environment after solving the external parameters of the mmWave radar and the internal and external parameters of the camera. The test results show that the correct detection rate of obstacles reaches 86.18%, which is higher than that of a single camera with 62.47%. Furthermore, through the contrast experiment of the sensor fusion algorithms, the detection accuracy of the decision level fusion algorithm was 95.19%, which was higher than 4.38% and 6.63% compared with feature level and data level fusion, respectively.

Triboelectric nanogenerator (TENG), as a green energy harvesting technology, has aroused tremendous interest across many fields, such as wearable electronics, implanted electronic devices, and human-machine interfaces. Fabric and fiber-structured materials are excellent candidates for TENG materials due to their inherent flexibility, low cost, and high wearing comfort. Consequently, it is crucial to combine TENG with fabric/fiber materials to simultaneously leverage their mechanical energy harvesting and wearability advantages. In this review, the structure and fundamentals of TENG are briefly explained, followed by the introduction of three distinct methods for preparing fabric/fiber structures: spinning and weaving, wet spinning, and electrospinning. In the meantime, their applications have been discussed, focusing primarily on energy harvesting and wearable self-powered sensors. Finally, we discussed the future and challenges of fabric and fiber-based TENGs.

In this study, under the open-close conditions of a roadway outlet, ANSYS/LS-DYNA was used to build models of explosions on roadways with 0° and 90° bending angles, to compare and analyze the shock wave propagation characteristics and variation laws. Combined with the damage degree classification of shock wave overpressure to human body, the destructive effect zoning of explosion in roadway under the condition of opening and closing of roadway entrance was studied. The results showed that as the bending angle increased, the peak overpressure attenuation of the shock waves became prominent, and the arrival time for the same distance increased. The closure of the roadway outlet had a distance effect on the peak overpressure of the shock waves. The explosion shock waves caused the peak overpressure to rise sharply owing to the reflection and stacking effects near the closure. In the far zone of the outlet, the attenuation of the shock waves was too fast and had minimal impact on the peak overpressure. In addition, the existence of the roadway closure increased the damage area and the severity of the blast wave to human body as a whole. With an increase in the bending angle, the damage range and severity decreased.

Explosion accidents usually lead to serious fatality and disability. To investigate the patterns of Fatal Explosion Accidents (FEA), a database containing 1835 FEA that happened in China during 2001–2018 was built. Statistical analysis was made based on the year, month, time interval of day, day of week, province, type of accident, place of occurrence and severity of accident. The result shown that, (1) FEA were more likely to occur in November; (2) 08: 00-10: 00 and 14: 00-16: 00 were two time intervals of frequent accident occurrence; (3) hazardous chemical FEA mostly happened on Tuesday and Wednesday, whereas pressurized container FEA often happened on Saturday; (4) coal mine gas FEA still accounted for a dominant proportion with the highest fatality rate. In addition, the correlation was measured by calculating Cramer’s coefficients, which indicated that the severities and types of FEA were significantly correlated with month. To be specific, (1) major and extraordinarily serious FEA were more likely to occur in November; (2) most of gas FEA were observed in April; (3) gunpowder and dust FEA happened most commonly in May; (4) more fireworks FEA happened in November. The patterns found in this study will provide explosion accident prevention and control with references.

Titanium dioxide (TiO2) nanofibers have been widely applied in various fields including photocatalysis, energy storage and solar cells due to the advantages of low cost, high abundance and nontoxicity. However, the low conductivity of ions and bulk electrons hinder its rapid development in lithium-ion batteries (LIB). In order to improve the electrochemical performances of TiO2 nanomaterials as anode for LIB, hierarchically porous TiO2 nanofibers with different tetrabutyl titanate (TBT)/paraffin oil ratios were prepared as anode for LIB via a versatile single-nozzle microemulsion electrospinning (ME-ES) method followed by calcining. The experimental results indicated that TiO2 nanofibers with the higher TBT/paraffin oil ratio demonstrated more axially aligned channels and a larger specific surface area. Furthermore, they presented superior lithium-ion storage properties in terms of specific capacity, rate capability and cycling performance compared with solid TiO2 nanofibers for LIB. The initial discharge and charge capacity of porous TiO2 nanofibers with a TBT/paraffin oil ratio of 2.25 reached up to 634.72 and 390.42 mAh·g−1, thus resulting in a coulombic efficiency of 61.51%; and the discharge capacity maintained 264.56 mAh·g−1 after 100 cycles, which was much higher than that of solid TiO2 nanofibers. TiO2 nanofibers with TBT/paraffin oil ratio of 2.25 still obtained a high reversible capacity of 204.53 mAh·g−1 when current density returned back to 40 mA·g−1 after 60 cycles at increasing stepwise current density from 40 mA·g−1 to 800 mA·g−1. Herein, hierarchically porous TiO2 nanofibers have the potential to be applied as anode for lithium-ion batteries in practical applications.

Using the hydrodynamic software Fluidyn, a numerical model comprising a top-sealed vertical inspection well and a horizontal well with openings at both ends was built based on symmetry, to study the explosion propagation of flammable gases in typical municipal sewage pipelines. The vertical well had a diameter of 0.7 m and different depths (2 m, 4 m, and 6 m), and the horizontal well had a diameter of 0.8 m and a length of 20 m at both sides. The effects of different ignition positions, well depths, and gas compositions and concentrations on the explosion characteristics and rules governing the propagation of flammable gases in a municipal sewage pipeline were investigated. The findings suggest that different ignition positions (at the top, middle, and bottom of the inspection well) did not lead to a significant difference between peak explosion pressure and temperatures but had a substantial influence on the propagation velocity of the explosion flame near the corner of the junction between the vertical inspection well and the horizontal well. Different inspection well depths had no significant impact on the peak explosion pressure or temperature but had a substantial effect on the propagation velocity of the explosion flame at the bottom of the well. Compared with a methane (CH4) explosion at a concentration of 6%, the peak explosion pressure, peak explosion temperature, and flame propagation velocity of a CH4 and oil-gas mixture at a concentration ratio of 6% : 1% were found to be significantly higher. With increasing oil-gas concentrations (2%, 4%, and 6%), the peak pressure, temperature, and flame propagation velocity continued to decrease. The findings of this study can help prevent explosion accidents in municipal sewage pipelines and provide a reference to support the establishment of related standards.

The flame propagation characteristic of polyethylene dust cloud inside a semi-open tube is studied in virtue of high-speed photographing technology. The rules of the influence of initial distribution range of polyethylene dust cloud on flame speed and shape is focused on. Studies show that flame propagation range generally exceed the initial distribution range of dust cloud and is positively correlated to it. Flames within certain dust cloud distribution range can accelerate continuously; however, flames will decelerate after its initial acceleration when dust clouds are too centralized or decentralized. When dust mass is constant, the maximum flame speed and average flame speed generally increase and then decrease with the increasing initial distribution range. Initial distribution range affects flame shape evolution significantly, such as its influence on the flame width along the radial direction, flame brightness, front smoothness, fault, etc. The conclusions provide scientific basis for flame monitoring and safety control at the initial stage of accident.

A one-step method for laccase production and immobilization using the waste culture of Ganoderma lucidum (G. lucidum) was developed, and the laccase was immobilized by the mycelium, which was in the form of a white membrane consisting of superfine fibers. This medical and edible membrane was characterized by scanning electron microscope (SEM), and the fiber diameter was found to be between 1 and 3 μm, with a porous structure formed in the membrane. Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric analysis (TGA) showed that the membrane contained polysaccharide groups and had good thermal resistivity. The membrane was used for the decolorization of methyl violet and malachite green, while the MTT test showed that the membrane had good biocompatibility. The experimental results indicated that the membrane might be applicable for other environmental protection applications in the future.

The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

On the basis of the principle of breaker failure protection delay and the analysis of the main factors which affect the protection, a sub-station-area breaker failure and dead-zone protection technical scheme based on the current differential principle is proposed. In this scheme, an incomplete current differential protection is structured by the breakers current transformer (CT) of the non-fault area, which is adjacent to the fault area. When the criteria of the incomplete current differential protection are satisfied, the adjacent breakers will trip to realise the isolation of the fault. This scheme is not only affected by the CT tailing and CT saturation, but also greatly reduces the time delay of breaker failure protection and achieves the free protection setting. The implementation of the project adopts an expandable architecture designed with the master slave mode, which could be achieved by high reliability with a flexible configuration of engineering and not relying on external time signals. Moreover, this scheme has the advantages of versatility and easier to implement. Also, it is preferable due to practicability and extended significance to popularise.

NiCu alloy nanoparticle-loaded carbon nanofibers (NiCuCNFs) were fabricated by a combination of electrospinning and carbonization methods. A series of characterizations, including SEM, TEM and XRD, were employed to study the NiCuCNFs. The as-prepared NiCuCNFs were then mixed with laccase (Lac) and Nafion to form a novel biosensor. NiCuCNFs successfully achieved the direct electron transfer of Lac. Cyclic voltammetry and linear sweep voltammetry were used to study the electrochemical properties of the biosensor. The finally prepared biosensor showed favorable electrocatalytic effects toward hydroquinone. The detection limit was 90 nM (S/N = 3), the sensitivity was 1.5 µA µM−1, the detection linear range was 4 × 10−7–2.37 × 10−6 M. In addition, this biosensor exhibited satisfactory repeatability, reproducibility, anti-interference properties and stability. Besides, the sensor achieved the detection of hydroquinone in lake water.

Camphor sulfonic acid (CSA)-doped polyamide 6/polyaniline (PA6/PANI) composite nanofibers were fabricated using in situ polymerization of aniline under different CSA concentrations (0.02, 0.04, 0.06, 0.08 and 0.10 M) with electrospun PA6 nanofibers as templates. The structural, morphological and ammonia sensing properties of the prepared composite nanofibers were studied using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), four-point probe techniques, X-ray diffraction (XRD) and a home-made gas sensing test system. All the results indicated that the CSA concentration had a great influence on the sensing properties of CSA-doped PA6/PANI composite nanofibers. The composite nanofibers doped with 0.02 M CSA showed the best ammonia sensing properties, with a significant sensitivity toward ammonia (NH3) at room temperature, superior to that of the composite nanofibers doped with 0.04–0.10 mol/L CSA. It was found that for high concentrations of CSA, the number of PANI–H+ reacted with NH3 would not make up a high proportion of all PANI–H+ within certain limits. As a result, within a certain range even though higher CSA-doped PA6/PANI nanofibers had better conductivity, their ammonia sensing performance would degrade.

Molybdenum disulfide has been one of the most studied hydrogen evolution catalyst materials in recent years, but its disadvantages, such as poor conductivity, hinder its further development. Here, we employ the common hydrothermal method, followed by an additional solvothermal method to construct an uncommon molybdenum disulfide with two crystal forms of 1T and 2H to improve catalytic properties. The low overpotential (180 mV) and small Tafel slope (88 mV/dec) all indicated that molybdenum disulfide had favorable catalytic performance for hydrogen evolution. Further conjunctions revealed that the improvement of performance was probably related to the structural changes brought about by the 1T phase and the resulting sulfur vacancies, which could be used as a reference for the further application of MoS2.

In the present study, formal safety assessment (FSA) is introduced to investigate lockage safety of LNG-fueled ships. Risk sources during lockage of LNG-fueled ships in four typical scenarios, namely, navigation between two dams, lockage, anchorage, and fueling, are identified, and studied in combination with fundamental leakage probabilities of various components of LNG storage tanks, and simulation results of accident consequences. Some suggestions for lockage safety management of LNG-fueled ships are then proposed. The present research results have certain practical significance for promoting applications of LNG-fueled ships along Chuanjiang River and in Three Gorges Reservoir Region.

In order to weaken the influence of temperature on photoacoustic (PA) measurements and compensate PA signals with a proposed theoretical model, the relationship of PA signal amplitude with temperature, under the condition of different glucose concentrations and different light intensities, was studied in this paper. First, the theoretical model was derived from the theory of the PA effect. Then, the temperature characteristics of the PA signals were investigated, based on the analyses of the temperature-dependent Grüneisen parameter in glucose solution. Next, the concept of a PA temperature coefficient was proposed in this paper. The result of the theoretical analysis shows that this coefficient is linear to light intensity and irrelevant to the concentration of glucose solution. Furthermore, a new concept of a PA temperature coefficient of unit light intensity was proposed in this paper. This coefficient is approximately constant, with different light intensities and solution concentrations, which is similar to the thermal expansion coefficient. After calculation, the PA temperature coefficient by the unit light intensity of glucose solution is about 0.936 bar/K. Finally, relevant experiments were carried out to verify the theoretical analysis, and the PA temperature coefficient of the unit light intensity of glucose solution is about 0.04/°C. This method can also be used in sensors measuring concentrations in other aqueous solutions.

14-3-3β has been demonstrated to possess the oncogenic potential, and its increased expression has been detected in multiple types of carcinomas. However, majority of previous studies focused on the role of 14-3-3β in tumor cell proliferation and apoptosis, leaving much to be elucidated about its function in tumor cell invasion and metastasis. Hence, the present study aimed to investigate the role of 14-3-3β in the invasion of hepatocellular carcinoma (HCC) cells and the implications in the prognosis of HCC patients. We first examined the expression of 14-3-3β in the primary tumors of HCC patients with or without portal vein tumor thrombus (PVTT), and found that 14-3-3β expression was higher in the primary tumors with PVTT, and the level was even higher in the PVTTs. Kaplan-Meier curves and multivariate analysis revealed that high expression of 14-3-3β was associated with overall survival (OS) and time to recurrence (TTR) of HCC patients. In addition, ectopic expression of 14-3-3β in HCC cell lines led to enhanced migration ability and invasiveness, as well as up-regulation of matrix metalloproteinase 2 and 9, which could be suppressed by inhibiting the activation of Akt and nuclear factor-κB (NF-κB) signaling. Furthermore, we identified a correlated elevation of 14-3-3β and p-Akt in the primary tumors of HCC patients, and showed that a combinatory detection of 14-3-3β and p-Akt could better predict post-surgical outcome of HCC patients.

The CO2-brine dissolution homogenizes the distribution of residual CO2 and reduces the leakage risk in the saline aquifer. As a key parameter to immobilize the free CO2, the dissolution rate of CO2-brine could be accelerated through mechanisms like diffusion and dispersion, which are affected by the subsurface condition, pore structure, and background hydrological flow. This study contributed the calculated dissolution rates of both gaseous and supercritical CO2 during brine imbibition at a pore-scale. The flow development and distribution in porous media during dynamic dissolution were imaged in two-dimensional visualization using X-ray microtomography. The fingerings branching and expansion resulted in greater dissolution rates of supercritical CO2 with high contact between phases, while the brine bypassed the clusters of gaseous CO2 with a slower dissolution and longer duration due to the isolated bubbles. The dissolution rate of supercritical CO2 was about two or three orders of magnitude greater than that of gaseous CO2, while the value distributions both spanned about four orders of magnitude. The dissolution rates of gaseous CO2 increased with porosity, but the relationship was the opposite for supercritical CO2. CO2 saturation and the Reynolds number were analyzed to characterize the different impacts on gaseous and supercritical CO2 at different dissolution periods.

Autophagy is a conserved process in eukaryotes required for metabolism and is involved in diverse diseases. To investigate autophagy in skeletal muscle under hyperglycemia status, we established two hyperglycemia-rat models that differ in their circulating insulin levels, by glucose infusion and singe high-dose streptozotocin injection. We then detected expression of autophagy related genes with real-time PCR and western blot. We found that under hyperglycemia status induced by glucose-infusion, autophagy was inhibited in rat skeletal muscle, whereas under streptozotocin-induced hyperglycemia status autophagy was enhanced. Meanwhile, hyperglycemic gastrocnemius muscle was more prone to autophagy than soleus muscle. Furthermore, inhibition of autophagy in skeletal muscle in glucose-infusion hyperglycemia rats was mediated by the m-TOR pathway while m-TOR and FoxO3 both contributed to enhancement of autophagy in gastrocnemius muscle in streptozotocin-induced hyperglycemia rats. These data shows that insulin plays a relatively more important role than hyperglycemia in regulating autophagy in hyperglycemia rat muscle through selectively activating the m-TOR or FoxO3 pathway in a fiber-selective manner.

STUDY DESIGN: Meta-analysis. BACKGROUND: Bilateral pedicle screw fixation (PS) after lumbar interbody fusion is a widely accepted method of managing various spinal diseases. Recently, unilateral PS fixation has been reported as effective as bilateral PS fixation. This meta-analysis aimed to comparatively assess the efficacy and safety of unilateral PS fixation and bilateral PS fixation in the minimally invasive (MIS) lumbar interbody fusion for one-level degenerative lumbar spine disease. METHODS: MEDLINE/PubMed, EMBASE, BIOSIS Previews, and Cochrane Library were searched through March 30, 2014. Randomized controlled trials (RCTs) and controlled clinical trials (CCTs) on unilateral versus bilateral PS fixation in MIS lumbar interbody fusion that met the inclusion criteria and the methodological quality standard were retrieved and reviewed. Data on participant characteristics, interventions, follow-up period, and outcomes were extracted from the included studies and analyzed by Review Manager 5.2. RESULTS: Six studies (5 RCTs and 1 CCT) involving 298 patients were selected. There were no significant differences between unilateral and bilateral PS fixation procedures in fusion rate, complications, visual analogue score (VAS) for leg pain, VAS for back pain, Oswestry disability index (ODI). Both fixation procedures had similar length of hospital stay (MD = 0.38, 95% CI = -0.83 to 1.58; P = 0.54). In contrast, bilateral PS fixation was associated with significantly more intra-operative blood loss (P = 0.002) and significantly longer operation time (P = 0.02) as compared with unilateral PS fixation. CONCLUSIONS: Unilateral PS fixation appears as effective and safe as bilateral PS fixation in MIS lumbar interbody fusion but requires less operative time and causes less blood loss, thus offering a simple alternative approach for one-level lumbar degenerative disease.

Palladium nanoparticle-bacterial cellulose (PdBC) hybrid nanofibers were synthesized by in-situ chemical reduction method. The obtained PdBC nanofibers were characterized by a series of analytical techniques. The results revealed that Pd nanoparticles were evenly dispersed on the surfaces of BC nanofibers. Then, the as-prepared PdBC nanofibers were mixed with laccase (Lac) and Nafion to obtain mixture suspension, which was further modified on electrode surface to construct novel biosensing platform. Finally, the prepared electrochemical biosensor was employed to detect dopamine. The analysis result was satisfactory, the sensor showed excellent electrocatalysis towards dopamine with high sensitivity (38.4 µA·mM−1), low detection limit (1.26 µM), and wide linear range (5–167 µM). Moreover, the biosensor also showed good repeatability, reproducibility, selectivity and stability and was successfully used in the detection of dopamine in human urine, thus providing a promising method for dopamine analysis in clinical application.

Radix Paeoniae Rubra (Chishao), a typical multi-origin Chinese medicinal material, originates from the dried roots of Paeonia lactiflora or P. veitchii. The previous study suggested that these two commonly used Chishao showed variation in their chemical compositions and clinical efficacies. Therefore, accurate identification of different Chishao species was of great significance for the guide of clinical medication, and timely treatment of patients. In this study, the chloroplast genome sequences of P. lactiflora and P. veitchii were obtained by next-generation sequencing (NGS) technology, and then the hypervariable regions were selected to design two minibarcode candidates for species identification. Combined with DNA metabarcoding technology, we performed qualitative and quantitative analysis on the artificially mixed samples of P. lactiflora and P. veitchii and evaluated the identification ability of these minibarcode candidates. Furtherly, the mini-barcode with good performance was applied to distinguish the Chinese patent medicine "cerebral thrombosis tablets" containing Chishao. The results indicated that the chloroplast genomes of P. lactiflora and P. veitchii were 152,750 and 152,527 bp, respectively. As published previously, they exhibited a typical quadripartite structure including a large single-copy region (LSC), a small single-copy region (SSC) and a pair of inverted repeat regions (IRs). The nucleotide polymorphism analysis revealed seven variable protein-coding regions as petL, psaI, psbJ, rpl16, ycf1b, psaC, and ndhF, and two mini-barcodes were developed from ycf1b and ndhF respectively. The result suggested that both two mini-barcodes performed well distinguishing P. lactiflora from P. veitchii. Besides, P. lactiflora was the only raw material of Chishao in all collected "cerebral thrombosis tablets" samples. In general, this study has established a method to realize the qualitative and quantitative identification of Chishao as multi-origin Chinese medicinal materials, which can be applied to Chinese patent medicines containing Chishao. [ABSTRACT FROM AUTHOR]

Weather derivatives pricing is one of the central issues in the study of this type of financial product, and there is no uniform methodology. To price the temperature option with Shanghai temperature as the underlying and explore how to improve the accuracy of option pricing, firstly, the time-varying O-U model is combined with Monte Carlo simulation to obtain the Shanghai-based temperature option pricing, and then Shanghai and its neighboring Dongtai, Quxian, and Dinghai are selected to constitute an option portfolio and priced using the same method. The results are obtained: 1) the predicted price of each unit of Shanghai temperature option is 1732.33 yuan, and the actual price is 1557.84 yuan, with a relative error of 9.1%; 2) the predicted price of each unit of option portfolio is 1598.12 yuan, and the actual price is 1500.72 yuan, with a relative error of 6.5%; and 3) the same pricing steps are repeated several times, with a very robust relative error. It can be seen that the pricing method has stability and higher prediction accuracy and can be used in practice. At the same time, pricing after selecting multiple cities to form a weather derivative portfolio has higher accuracy i.e. less risk than pricing only for a single city. [ABSTRACT FROM AUTHOR]