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Recently, data-driven algorithms such as deep neural networks have attracted a lot of attention and have become a popular area of research and development. This interest is driven by several factors, such as recent advances in processing power (cheap and powerful hardware), the availability of large datasets (big data), and several small but important algorithmic advances (e.g., convolutional layers). Nowadays, deep neural networks are the state-of-the-art for several computer vision tasks, such as the ones that require high-level understanding of image semantics, e.g., image classification, object segmentation, saliency detection, and also in low level image processing tasks, such as image denoising, inpainting, and super-resolution, among others. Deep learning can handle large volumes of video data by making use of its powerful non-linear mapping and extracting high-level features with very deep networks. Incorporating deep learning into the IoVT can provide radical innovations in video sensing, coding, enhancing, understanding, and evaluation areas making it easier to handle the enormous growth in video data compared to traditional methods.

Oil separation is commonly needed in air conditioning and refrigeration systems to reduce the oil circulation rate and keep the oil inside the compressor. For compactness, the oil separation structure integrated into the compressor is more and more popular than traditional external oil separators. However, a quantitative guideline for the design of oil separation structure is missing for irregular geometry and realistic flow condition at the compressor discharge. This paper presents impinging separation mechanism, one of the basic mechanisms of droplet separation. The separating structures are studied by flow visualization and experimental measurement under realistic compressor discharge conditions. The video of oil mist flowing through the baffles and plates is captured by a high-speed camera and analyzed quantitatively. The effect of the oil flow condition and the effect of separator geometry design are investigated based on the experimental data. With the help of flow visualization, the flow details are analyzed, and a semi-empirical model is proposed to predict the separation efficiency and pressure drop of a certain wave-plates structure. The results and conclusions from this study give useful guidelines about how to reduce the oil circulation ratio by designing oil separators.

In the framework of cooperative game theory, Sobolev (Advances in game theory, Izdat., “Minitis”, Vilnius, pp 151–153, 1973) axiomatized the well-known Shapley value by means of consistency property with reference to a specifically chosen reduced game. The goal of this paper is to generalize Sobolev’s consistency approach to the class of efficient, symmetric and linear values.

Based on the fishery resource investigation data in Pishan waters of Zhejiang coastal area in November of 2015 (autumn), February (winter), May (spring) and August (summer) of 2016, we analyzed the spatio-temporal niche characteristics and interspecific association of the domi-nant shrimp and crab species using the methods of niche test, variance ratio, chi-square test, Spearman test and redundancy analysis. A total of 34 shrimp and crab species belonging to 14 families and 20 genera were identified. Among them, 10 species were collected in all the four seasons. Dominant species were根据2015年11月(秋季)、2016年2月(冬季)、5月(春季)、8月(夏季)在浙江披山附近海域进行的渔业资源调查数据,运用生态位测定、方差比率、

鳀是重要的渔业资源捕捞对象,同时也是生态系统营养动力学研究的关键种。基于2020年和2008—2009年东海区采集的鳀样品,结合胃含物分析和肌肉碳、氮稳定同位素技术,分析了鳀的食物组成、食性昼夜差异、不同发育阶段的食性转变及其营养级,研究鳀的摄食生态。胃含物分析显示,鳀主要摄食浮游甲壳类和小型鱼类,优势饵料依次为太平洋磷虾[相对重要指数百分比(IRI)=87.6%,出现频率(

Oil separation is commonly needed in air conditioning or refrigeration systems to reduce the oil circulation rate and keep the oil inside the compressor. For compactness, the oil separation structure integrated into the compressor is more and more popular than traditional external oil separator. However, a quantitative guideline for the design of oil separation structure is missing for irregular geometry and realistic flow condition at the compressor discharge. This paper presents coalescence, one of the basic mechanisms of droplet separation, studied by flow visualization and analytical models. The misty oil flow through separator is visualized by a high-speed camera and analyzed quantitatively. Oil droplet size distribution is estimated by video processing. Important flow details are revealed, including oil droplet collision, oil droplet coalescence, oil film breakup, and re-entrainment. Separation efficiency is estimated by the ratio between drained and incoming oil mass flow rate. Pressure drop is also measured to evaluate the cost brought by separation structures. An analytical model for coalescing oil separator is developed based on the mass flow balance through multiple layers of coalescing separators. Development of the model starts with the experimental and analytical analysis of first one wire, then a serious of wires to come to a wire pad. The results of the model are verified by experimental measurements in a full vapor compression system with R134a and PAG oil. The results of the model show good agreement with experiment and conclusion provides guidelines for oil separator design and operation.

Objectives: To synthesize folate acid conjugated quantum dots (QDs) by a simple and green method and explore endocytosis of the QD-folic acid conjugates (FA-QDs) into hepG2 cells. Methods: CdS QDs were prepared using stearic acid as synthetic medium, and were conjugated with mercaptoacetic acid (MAA) to be water-soluble. Then folic acid moiety was coupled to the surface of the QDs using EDC (1-ethyl-3-(3-dimethylamino propyl)carbodiimide) as a coupling agent. The CdS QDs and FA-QDs were characterized by X-ray spectroscopy (XRD), transmission electron microscopy (TEM), spectro fluorimetry and infrared spectroscopy. Endocytosis of the FA-QDs into hepG2 cells was observed by confocal microscopy and TEM. Results: TEM shows that the CdS QDs and FA-QDs were spherical in shape and had a diameter of 10 nm. Fluorescence spectrum of the QDs also shows their narrow size distribution. Confocal microscopic and TEM results show that FA-QDs were successfully internalized into the hepG2 cells. In addition, confocal results show that when the cells were first be saturated with excess free FA, the endocytosis of the FA-QDs became less, and CdS QDs that were not conjugated with FA were not able to be internalized into the hepG2 cells. Conclusions: The FA-QDs can be synthesized by a simple and green method and be used to successfully target tumor cells: hepG2 cell lines, which was probably mediated by the FA receptor.

We, for the first time, report the preparation of enhanced photoluminescent Mg:CdZnS/Mg:ZnS core/shell quantum dots (QDs) realized via facile organometallic approach. Inductively coupled plasma-atomic emission spectroscopy (ICP-AES) results revealed that Mg2+ is introduced as dopant in the cores and shells of the host material. Mg:CdZnS showed a slight blue shift in the photoluminescence (PL) spectra to be due to the replacement of Cd2+ or Zn2+ with smaller Mg2+. The prepared Mg:CdZnS/Mg:ZnS QDs showed higher PL QY and longer PL lifetime with narrow spectral bandwidth and only band edge emission. Mg:CdZnS/Mg:ZnS exhibited the highest photoluminescence quantum yield (PL QY) of 48.8% when the nominal added mole ratio of Mg/(Cd+Zn) was 1%, and its average PL lifetime (τav = 727 ns) is observed to be longer than that of CdZnS/ZnS (τav = 535 ns). Enhanced PL QY and PL lifetime could be attributed to the wider band gap of Mg:ZnS than ZnS, which could confine electrons to the cores region more effectively.

With the progress of speech retrieval technology in the cloud, it brings a lot of conveniences for speech user. Yet, the inquiry encrypted speech results from the speech retrieval system are faced with some secure issues to settle, such as integrity authentication and tampering recovery. In this paper, an encrypted speech authentication and tampering recovery method based on perceptual hashing is proposed. Firstly, the original speech is scrambled by Duffing mapping to construct an encrypted speech library in the cloud, through extracting product of uniform sub-band spectrum variance and spectral entropy of encrypted speech and constructing a perceptual hashing sequence to generate the hashing template of the cloud. From this, a one-to-one correspondence between the encrypted speech and perceptual hashing sequence is established. Secondly, the authentication digest of encrypted speech is extracted according to the inquiry result during the retrieval. Then, the authentication digest and the perceptual hashing sequence of the hashing template in the cloud are matched by the Hamming distance algorithm. Finally, for encrypted speech that fails authentication, tampering detection and location are performed, and the tampered samples are recovered by the least square curve fitting method. The simulation results show that the proposed method can extract the authentication digest directly in the encrypted speech, and the authentication digest not only has good discrimination and robustness, but it accurately locates the tampered area for malicious substitution and mute attacks. In addition, the proposed method can recover tampered speech signals in high quality without any extra information.

Based on seasonal bottom trawl surveys in November 2015 (autumn), February (winter), May (spring) and August (summer) in 2016, the index of relative importance (IRI), Shannon index and Pianka index were used to analyze the breadth and overlap of spatio-temporal niche of major fish species in the Pishan waters off Zhejiang Province. Redundancy analysis and interspecific competition coefficient were used to examine the competition relationship and niche differentiation of those major fish species. The results showed that a total of 61 fish species were recorded throughout the year, which belonged to 13 orders, 29 families and 48 genera. A total of 19 species with IRIgt;100 were identified as major fish species. The temporal niche overlap value between依据2015年11月(秋)、2016年2月(冬)、5月(春)、8月(夏)4个航次的渔业资源底拖网调查数据,运用相对重要性指数(IRI)、Shannon指数和Pianka指数对浙江披山海域主要鱼类的时空生态位宽度和重叠进行分析,并结合冗余分析和种间竞争系数研究了主要鱼类间的竞争共存关系及生态位分化。结果表明: 研究期间共采集鉴定鱼类61种,隶属13目29科48属,其中主要鱼类(IRIgt;100)有19种。绿鳍鱼与丽叶鲹的时间生态位重叠值最高,二者对时间资源利用的同步性最强;孔虾虎鱼与断线舌鳎的空间生态位重叠值和时空生态位重叠值均最高,二者在空间资源序列上的同域性最强,同时,物种对时空二维资源的利用趋于一致。披山海域时空二维生态位显著重叠(

Additional file 1. Multiple linear regression results for the three collapse modes.

Oil is important to compressors, but it brings some side effects on the performance of refrigeration systems. Discharge valve or orifice in the compressor plenum is the gateway for the oil to leave the compressor and circulate in the system. The space of the compressor plenum has the potential to separate the oil mist from the refrigerant so that oil circulation ratio (OCR) is reduced. In this study, the formation, distribution, and movement of oil droplets in the plenum are investigated through visualization and CFD simulation. Videos of oil atomization are captured by the high-speed camera to describe how oil mist is formed. The distribution of droplet size and velocity is quantified by video processing techniques. Discrete phase model gives the numerical approach to study the oil droplet movement inside the compressor plenum. The numerical simulation is verified by comparing visualization results with simulation results. The oil flow phenomenon and its quantification provide important information for the design of separation structure incorporated in the compressor. Also, a set of tools are developed and verified to study the oil droplets behavior in different types of compressor plenums.

This paper aims at the problems of small Radar Cross-Section (RCS) and short coherent accumulation time in radar detection of low altitude small UAVs. An Inverse Synthetic Aperture Radar (ISAR) super-resolution imaging method based on Bayesian Statistical Machine Learning is proposed. The sparse prior characteristics of UAV with respect to the air-background is utilized by introducing a heavy-tailed Laplacian prior probability distribution, and a Bayesian posterior inference model is derived based on the Gaussian distribution assumption of observation system noise. In view of the non-conjugation of prior distribution, a hierarchical Bayesian model is introduced. Finally, the variational Bayesian expectation maximization algorithm is applied, and the posterior probability density function of the target is solved analytically. Meanwhile, the imaging defocus caused by the non-systematic translational error of the target is corrected, cooperatively. Compared with traditional methods, this method can effectively solve the problem of low imaging signal-to-noise ratio caused by the small RCS of UAV target and low imaging resolution caused by the short coherent accumulation time. The experimental results of simulation and radar data prove the effectiveness and superiority of the proposed method.