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【Objective】In order to identify the pathogenic bacteria causing the tilapia disease outbreak in the geese-fish polyculture system, the growth characteristics, pathogenicity and drug sensitivity of the pathogenic bacteria were analyzed, with an aim to provide scientific basis for further research and effective prevention and control of tilapia disease.【Method】The pathogenic bacteria were isolated from the organs of diseased tilapia and identified by various methods such as morphological observation, physiological and biochemical identification, and 16S rRNA gene sequence analysis. The impacts of temperature, salinity and pH on the growth of pathogenic bacteria were analyzed, and a growth curve for the strain was plotted. The pathogenicity of the bacterial strain was assessed by intraperitoneal injection and oral feeding of mixed materials. Additionally, the susceptibility of the strain to 26 different antimicrobial agents belonging to 11 classes was determined by the drug sensitive slips method.【Result】A dominant strain SAYJN was isolated and purified from the brain tissue of the diseased tilapia. Through morphological observation, physiological and biochemical identification, 16S rRNA gene sequence analysis and artificial regression infection test, the strain was identified as Streptococcus agalactiae. The growth retardation stage of SAYJN was 0-5 h, and its logarithmic stage was 5-12 h. The optimal conditions for growth were found at a temperature of 37 ℃, pH value of 7.0 and salinity of 5‰. The strain SAYJN with intraperitoneal injection and oral feeding of mixed materials could infect the healthy tilapia. In an artificial infection test by intrabitoneal injection, the strain SAYJN showed high pathogenicity to tilapia at a temperature of 29 (±1) ℃, with a lethal concentration of 2.4×108 CFU/mL. The pathogenicity of the strain SAYJN was found to be closely related to bacterial concentration and water temperature. Further, the strain SAYJN displayed resistance to six drugs such as trimethopridine, gentamicin, neomycin and etc. It showed moderate sensitivity to four drugs such as enrofloxacin, ciprofloxacin and amikacin. Additionally, it was found to be sensitive to 16 drugs such as doxycycline, flufenicol, rifampicin and etc.【Conclusion】The strain SAYJN of S. agalactiae is the primary pathogen responsible for the outbreak of tilapia disease in the goose-fish polyculture environment, and the pathogenicity of this pathogen is closely related to the bacterial concentration and water temperature.

This paper investigates rational solutions of an extended Camassa-Holm-Kadomtsev-Petviashvili equation, which simulates dispersion's role in the development of patterns in a liquid drop, and describes left and right traveling waves like the Boussinesq equation. Through its bilinear form and symbolic computation, we derive some multiple order rational and generalized rational solutions and analyze their dynamic features, such as the connection between rational solution and bilinear equation, scatter behavior, moving path, and exact location of the soliton. The obtained solutions demonstrate two wave forms: multi-lump and multi-wave that consist of three, six and eight lump waves or two, three and four line waves. Moreover, different from the multi-wave solitons, stationary multiple dark waves are presented.

Understanding the ripening of core-shell nanostructures is challenging. Here, the authors use liquid cell transmission electron microscopy to show that the atomic ripening pathway for Cd-CdCl2 core-shell nanoparticles is mediated by crack defects.

The hoist cage is used to lift miners in a coal mine’s auxiliary shaft. Monitoring miners’ unsafe behaviors and their status in the hoist cage is crucial to production safety in coal mines. In this study, a visual detection model is proposed to estimate the number and categories of miners, and to identify whether the miners are wearing helmets and whether they have fallen in the hoist cage. A dataset with eight categories of miners’ statuses in hoist cages was developed for training and validating the model. Using the dataset, the classical models were trained for comparison, from which the YOLOv5s model was selected to be the basic model. Due to small-sized targets, poor lighting conditions, and coal dust and shelter, the detection accuracy of the Yolov5s model was only 89.2%. To obtain better detection accuracy, k-means++ clustering algorithm, a BiFPN-based feature fusion network, the convolutional block attention module (CBAM), and a CIoU loss function were proposed to improve the YOLOv5s model, and an attentional multi-scale cascaded feature fusion-based YOLOv5s model (AMCFF-YOLOv5s) was subsequently developed. The training results on the self-built dataset indicate that its detection accuracy increased to 97.6%. Moreover, the AMCFF-YOLOv5s model was proven to be robust to noise and light.

Abstract Background Social networks are associated with better cognitive health in older people, but the role of specific aspects of the social network remains unclear. This is especially the case in Central and Eastern Europe. This study examined associations between three aspects of the social network (network size of friends and relatives, contact frequency with friends and relatives, and social activity participation) with cognitive functions (verbal memory, learning ability, verbal fluency, processing speed, and global cognitive function) in older Czech, Polish, and Russian adults. Methods Linear regression estimated associations between baseline social networks and cognitive domains measured at both baseline and follow-up (mean duration of follow-up, 3.5 ± 0.7 years) in 6691 participants (mean age, 62.2 ± 6.0 years; 53.7% women) from the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study. Results Cross-sectional analyses, adjusted for country, age, and sex, showed positive associations of global cognitive function with social activity participation and network size of friends and relatives, but not with contact frequency in either network. Further adjustment for sociodemographic, behavioural, and health characteristics attenuated the associations with network size of relatives (P-trend = 0.074) but not with network size of friends (P-trend = 0.036) or social activities (P-trend

As thermoplastic materials are widely used in buildings, the fire hazards of thermoplastic materials are increasingly becoming a central issue in fire safety research due to their unique pyrolysis and melting mechanisms. In this paper, the features and common types of thermoplastic materials are introduced first. Then, the combustion behavior of thermoplastic materials is theoretically analyzed based on the empirical formulas and heat balance equations, such as the pyrolysis kinetics, ignition time, melting and dripping, flame, burning rate and mass loss rate, temperature and heat flow, gas products, and influencing factors. The influencing factors basically include the sample properties (width, incline angle, and thickness, etc.), the façade structure (sidewalls, curtain wall, etc.), the ambient conditions (altitude, pressure, and gravity, etc.), and the flame retardant treatment. Similarly, this study also illustrates the vertical and horizontal flame spread behavior of the thermoplastic materials and the influencing factors. The utilized methods include the experimental methods, the analytical methodologies, and the approaches for numerical simulation. Finally, the problems encountered at this stage and worthy of further study in the future are presented.

Summary: Various recycling technologies have been developed to deal with plastic problems, but they face considerable economic and technological challenges in practice. An attractive alternative is upcycling, which aims to dig out the embedded value to incentivize large-scale valorization of plastic wastes. The degradation of nonrecoverable plastic wastes is another necessity to treat the omnipresent pollution. This review presents an overview on the conversion of plastic wastes toward value-added products and the catalytic degradation of nonrecoverable plastic wastes. Based on an examination of traditional recycling technologies and products, we summarize the state-of-the-art design and development of plastic conversion to high-value and high-performance fuels, chemicals, and materials. Subsequently, we highlight the advances in catalytic degradation of plastics to environmentally benign or degradable products and mineralization into carbon dioxide and water. We conclude with our perspective on the ongoing challenge and opportunities.

In this paper, to identify the roof unconfined compressive strength (UCS) in the process of coal mine roadway support in real-time and optimize the real-time drilling speed while drilling, this paper proposes and establishes a drilling test method for assessing the uniaxial compressive strength (UCS) of a roof. This method can be used to optimize the speed of drilling. Moreover, a mathematical model of the power output is developed for a roof-strata identification system with a drilling test system. The results were as follows: (1) the system was able to identify the uniaxial compressive strength of roof rock; (2) the pressure of the drill leg of the pneumatic bolt did not match the output power of the pneumatic motor, the pneumatic motor could not reach the maximum power point, and the insufficient thrust of the pneumatic leg led to failure of the maximum output power of the pneumatic motor; (3) to increase the output power of the air motor and thus improve the drilling speed, we applied a booster valve for the system. The experimental results show that the power of the air motor has a linear relationship with drilling speed. In this way, the speed of the drill can be increased by increasing the motor power.

First-principles calculations have been carried out to investigate the adsorption of a hydrogen adatom on 24 metal doped α-Zr (0 0 0 1) surfaces in both a vacuum and an implicit solvation environment. The dopant are the elements in the 4th and 5th periods in the periodic table. Doping elements at the tail of the 4th and 5th periods can significantly reduce the hydrogen pickup in a vacuum environment. A weighted d-band center theory is used to analyze the doping effect. On the other hand, the hydrogen adsorption energies in water are relatively lower for all doped slabs and the surface adsorption of hydrogen adatom is stronger than that in a vacuum environment, especially, for the slabs with doping elements at the tail of the 4th and 5th periods. In the solvation environment, electronegativity difference affects the adsorption. Doping elements Ag, Ga, Ge, Sn, and Sb can reduce the hydrogen pickup in vacuum, while Ag and Cu can reduce the hydrogen pickup of the zirconium alloys in solvent environment.

Abstract Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

This paper presents the design and experimental study of a voice coil motor (VCM)-based Stewart platform used for active vibration isolation. The high precision payloads carried on the satellites always require an extremely stable environment to work properly. Installing a vibration isolation device between the vibration sources and precision payloads is an efficient method for dissipating vibration energy. A Stewart platform with active damping is designed to isolate the vibration transferring from the satellite to the payloads in six degrees-of-freedom. First, the kinematics and dynamical equations of a Stewart platform with spherical joints at both the base and top of each leg are established with Newton-Euler Method in task space and joint space. Second, the H∞ Control Theory is employed to design a robust controller for the linearized system with parameter uncertainty, noise and sensor errors. Finally, an experimentation study on the vibration of the payload supported by a Stewart platform with VCM actuator is conducted. The feasibility and effectiveness of the vibration isolation system are verified by comparing the amplitude-frequency characteristics of the active control system with that of the passive control system and the system without damping.

Furfural is a versatile platform molecule for the synthesis of various chemicals and fuels, and it can be produced by acid-catalyzed dehydration of xylose derived from renewable biomass resources. A series of metal salts and ionic liquids were investigated to obtain the best combination of catalyst and solvent for the conversion of xylose into furfural. A furfural yield of 71.1% was obtained at high xylose loading (20 wt%) from the single-phasic reaction system whereby SnCl4 was used as catalyst and ionic liquid 1-ethyl-3-methylimidazolium bromide (EMIMBr) was used as reaction medium. Moreover, the combined catalyst consisting of 5 mol% SnCl4 and 5 mol% MgCl2 also produced a high furfural yield (68.8%), which was comparable to the furfural yield obtained with 10 mol% SnCl4. The water⁻organic solvent biphasic systems could improve the furfural yield compared with the single aqueous phase. Although these organic solvents could form biphasic systems with ionic liquid EMIMBr, the furfural yield decreased remarkably compared with the single EMIMBr phase. Besides, the EMIMBr/SnCl4 system with appropriate water was also efficient to convert xylan and lignocellulosic biomass corn stalk into furfural, obtaining furfural yields as high as 57.3% and 54.5%, respectively.

Polyurethane is widely used in building facades as a good energy-saving and environment-friendly organic material, and the U-shaped structure is a common facade form as it could improve indoor lighting and ventilation. Through numerical simulation and theoretical analysis, this study found the flame spread rate of polyurethane foam over a U-shaped facade was affected by the structural dimensions due to three main factors: lateral air entrainment restriction, bottom air entrainment restriction, and flame fusion between the back wall flame and side wall flame. The average flame spread rate was negative linearly correlated with the back wall width and positive exponentially correlated with the side wall length. This was due to that the side walls caused lateral air entrainment restriction, reduced the heat loss, enhanced the thermal feedback, generated an upward induced airflow close to the back wall, elongated the flame, and also caused the flame fusion between side walls and the back wall, thus accelerated the flame spread process compared to the flat structures. [ABSTRACT FROM AUTHOR]

By investigating the bulk superconducting state via dc magnetization measurements, we have discovered a common resurgence of the superconducting transition temperatures (Tcs) of the monolayer Bi2Sr2CuO6+d (Bi2201) and bilayer Bi2Sr2CaCu2O8+d (Bi2212) to beyond the maximum Tcs (Tc-maxs) predicted by the universal relation between Tc and doping (p) or pressure (P) at higher pressures. The Tc of underdoped Bi2201 initially increases from 9.6 K at ambient to a peak at 23 K at 26 GPa and then drops as expected from the universal Tc-P relation. However, at pressures above 40 GPa, Tc rises rapidly without any sign of saturation up to 30 K at 51 GPa. Similarly, the Tc for the slightly overdoped Bi2212 increases after passing a broad valley between 20 and 36 GPa and reaches 90 K without any sign of saturation at 56 GPa. We have, therefore, attributed this Tc resurgence to a possible pressure-induced electronic transition in the cuprate compounds due to a charge transfer between the Cu 3dx2-y2 and the O 2p bands projected from a hybrid bonding state, leading to an increase of the density of states at the Fermi level, in agreement with our density functional theory calculations. Similar Tc-P behavior has also been reported in the trilayer Br2Sr2Ca2Cu3O10+d (Bi2223). These observations suggest that higher Tcs than those previously reported for the layered cuprate high-temperature superconductors can be achieved by breaking away from the universal Tc-P relation through the application of higher pressures. [ABSTRACT FROM AUTHOR]

In this Letter, we use first-principles simulations to demonstrate the absence of Fermi-level pinning when graphene is in contact with transition metal dichalcogenides (TMDs). We find that formation of either an ohmic or Schottky contact is possible. Then we show that, due to the shallow density of states around its Fermi level, the work function of graphene can be tuned by ion adsorption. Finally we combine work function tuning of graphene and an ideal contact between graphene and TMDs to propose an ionic barristor design that can tune the work function of graphene with a much wider margin than current barristor designs, achieving a dynamic switching among p-type ohmic contact, Schottky contact, and n-type ohmic contact in one device. [ABSTRACT FROM AUTHOR]

Chemical and physical adsorption of a H2O molecule on a Zr (0001) surface is studied by first principle calculations. A surface zirconium atom is substituted by a metal element atom in the 4th and 5th period of the periodic table to investigate the doping effect on the water adsorption. Doping elements Ge, Sn, Sb, Zn, Ga, Ru, Rh, Pd, Ag, Cr, Mn, Fe, Co, Ni, Cu, Nb, and Mo can increase the oxidation resistance. This strategy can be used to design high oxidation resistance cladding material for light water reactor. [ABSTRACT FROM AUTHOR]

Biological Event Extraction is an important task towards the goal of extracting biomedical knowledge from the scientific publications by capturing biomedical entities and their complex relations from the texts. As a crucial step in event extraction, event trigger identification, assigning words with suitable trigger category, has recently attracted substantial attention. As triggers are scattered in large corpus, traditional linguistic parsers are hard to generate syntactic features from them. Thereby, trigger sparsity problem restricts the model's learning process and becomes one of the main hinder in trigger identification. In this paper, we employ Noise Contrastive Estimation with Multi-Layer Perceptron model for solving triggers' sparsity problem. Meanwhile, in the light of recent advance in word distributed representation, word-embedding feature generated by language model is utilized for semantic and syntactic information extraction. Finally, experimental study on commonly used MLEE dataset against baseline methods has demonstrated its promising result.