驯化视角下“小号”的可供性分析

“小号”是一种非常态的社交媒体使用方式。本文通过半结构式访谈,在探寻用户使用动机的基础上展开研究,发现“小号”的可供性具有三重面向:承载多面人设的可重置性、保障私密安全的可撤展性、缓解倦怠情绪的可离场性。用户根据对“小号”可供性的把握与适配,能够再次驯化社交媒体。主次账号兼用,既可以在一定程度上规避社交媒体使用中伴生的失调问题,也是用户积极发挥能动性从而善用传媒的应有之义。

社交媒体用户“小号”使用行为定性研究

针对社交媒体平台普遍存在的“小号”现象,研究基于使用与满足理论,运用半结构化访谈,质性探究社交媒体用户“小号”使用行为与需求满足情况。发现社交媒体用户“小号”使用行为可分为匿名性参与、工具性使用、情感性表达和仪式性展演四种类型,分别满足在公共领域“隐身”需求、“双号并行”便利需求、“情感树洞”倾诉需求以及“私我”网络表露需求。

“Z世代”社交媒体隐匿账号上的自我呈现行为研究

为研究“Z世代”在社交媒体隐匿账号上的自我呈现行为,采用深度访谈法分析隐匿账号下“Z世代”的生存逻辑。研究认为,“Z世代”正处在自由表达与圈子束缚的矛盾之中,试图通过隐匿账号完成自我的身份构建和身份认同。

Application of fast wavelet transformation in signal processing of MEMS gyroscope

Decomposition and reconstruction of Mallat fast wavelet transformation （WT） is described. A fast algorithm, which can greatly decrease the processing burden and can be very easy for hardware implementation in real-time, is analyzed. The algorithm will no longer have the processing of decimation and interpolation of usual WT. The formulae of the decomposition and the reconstruction are given. Simulation results of the MEMS （micro-electro mechanical systems） gyroscope drift signal show that the algorithm spends much less processing time to finish the de-noising process than the usual WT. And the de-noising effect is the same. The fast algorithm has been implemented in a TMS320C6713 digital signal processor. The standard variance of the gyroscope static drift signal decreases from 78. 435 5 （°）/h to 36. 763 5 （°）/h. It takes 0. 014 ms to process all input data and can meet the real-time analysis of signal.

Small-Signal Equivalent Circuit Modeling of a Photodetector Chip

A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance into consideration,is first determined based on the device＇s physical structure. The photodetector＇s S parameters are then on-wafer measured, and the measured raw data are processed with further calibration. A genetic algorithm is used to fit the measured data, thereby allowing us to calculate each parameter value of the model. Experimental resuits show that the modeled parameters are well matched to the measurements in a frequency range from 130MHz to 20GHz, and the proposed method is proved feasible. This model can give an exact description of the photodetector chip＇s high frequency performance,which enables an effective circuit-level prediction for photodetector and optoelectronic integrated circuits.

Abstraction of Small Signal Equivalent Circuit Parameters of Enhancement-Mode InGaP/AlGaAs/InGaAs PHEMT

An extraction method of the component parameter values of an enhancement-mode InGaP/AIGaAs/In-GaAs PHEMT small signal equivalent circuit is presented,and these component parameter values are extracted by using the EEHEMT1 model of IC-CAP software. The extraction results are verified by ADS software,and the DC I-V curves and S parameters simulated by ADS are basically accordant with those of the test results. These results indicate that the EEHEMT1 model can be used for extracting the component parameters of an enhancement-mode PHEMT.

Application of wavelet package filtering in the de-noising of fiber optic gyroscopes

To reduce the drift error existing in the output signal of fiber optic gyroscopes （FOG）, a mathematical model of the FOG output signal is set up; the error characteristics of the FOG output signal are analyzed, and semi-soft threshold filtering is chosen based on the comparison of hard threshold and soft threshold filtering. The semi-soft threshold wavelet package filtering method is applied in the filtering of the FOG output signal. Experiments of the stationary and dynamic FOG output signals filtered with the wavelet package analysis are carried out in a lab environment, respectively. Experiments done with the real-time measured FOG signal show that the method of semi-soft threshold wavelet package filtering reduces the mean square error from 5 （°）/h to 1 （°）/h, so it is effective in eliminating the white noises and the fractal noises existing in the FOG. The novel method proposed here is proved valid in reducing the FOG drift error, satisfying the technical demands of high precision and realtime processing.

Analysis on Breeding Strategies of New Wheat Variety Jingdong 23, and its Characteristics and Application

In order to comprehensively analyze and compare the characteristics and utilization value of the new wheat variety Jingdong 23, the performance of Jingdong 23 was compared with a control variety based on the results in Beijing water con- servation regional test. The characteristics and yield structures of Jingdong 23 were analyzed. The results showed that the three factors of yield of Jingdong 23 were coordinated and the average yield of Jingdong 23 ranked in the first place among the 14 tested varieties （ten-location tests）. On average, the yield of Jingdong 23 was 4.5% more than that of the control Jingdong 8 in water conservation regional test and production test in Beijing. Jingdong 23 has a good adaptability, high and stable yield.

Classification of forearm action surface EMG signals based on fractal dimension

Surface electromyogram （EMG） signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers＇ right forearm flexor respectively in the process of forearm supination （FS） and forearm pronation （FP）.After the raw action surface EMG （ASEMG） signal was decomposed into several sub-signals with wavelet packet transform （WPT）,five fractal dimensions were respectively calculated from the raw signal and four sub-signals by the method based on fuzzy self-similarity.The results show that calculated from the sub-signal in the band 0 to 125 Hz,the fractal dimensions of FS ASEMG signals and FP ASEMG signals distributed in two different regions,and its error rate based on Bayes decision was no more than 2.26%.Therefore,the fractal dimension is an appropriate feature by which an FS ASEMG signal is distinguished from an FP ASEMG signal.

An Improved Multi-scale Estimation Method of Signal

In this paper an improved multi_scale estimation method of signal is gaven.The detail signals on each scale are further more decomposed with wavelet transform.The subdetail signals and subsmoothing signals are processed with different threshold respectively. The smoothing signals on the coarsest scale are processed with Kalman fitering and reconstructed with the detail signal on each scale.At last the signal estimate value on the original scale is obtained.

Characteristics analysis of muzzle impulse noise based on wavelet energy spectrum

Because muzzle impulse noise could cause damage to or have an intluence on the operator, tiae ettecnve protecnve measures should be taken. Therefore, correct analysis of impulse noise characteristics is very significant. Considering the shortcomings of fast Fourier transform method （FFT） in analysis of muzzle impulse noise frequency characteristics, wavelet energy spectrum method is put forward. Based on specific experiment data, the frequency characteristics and spectral energy dis tribution can be obtained. The experiment results show that wavelet energy spectrum method is applicable in muzzle impulse noise characteristic analysis.

The Breeding and Application of a New Super High-yield Mini Watermelon Variety ‘Jinmi 2'

[Objective] The aim was to breed early ripening and high-yielding moderate or small watermelon variety prone to planting. [Method] ‘Jinmi 2＇ is a new super high-yielding hybrid mini watermelon developed by crossing J52 as female parent with X712 as a male parent. [Result] The variety is early maturing with 31 days fruit developing period and 108 days growth period. The average fruit weight is 2.4 kg and yield at 31 455 kg/hm2. The fruit is oblong shaped and it has a light green rind with jagged dark green stripes. The fresh is red, and tastes crisp and sweet, with center soluble solid content at 11.0% and margin at 7.8%. [Conclusion] The variety is suitable for production in most areas of Zhejiang.

Approach for epileptic EEG detection based on gradient boosting

The automatic seizure detection is significant for epilepsy diagnosis and it can alleviate the work intensity of inspecting prolonged electroencephalogram （EEG）. This paper presents and investigates a novel machine learning approach utilizing gradient boosting to detect seizures from long-term EEG. We apply relative fluctuation index to extract features of long-term intracranial EEG data. A classifier trained with the gradient boosting algorithm is adopted to discriminate the seizure and non-seizure EEG signals. Smoothing and collar technique are finally used as post-processing in order to improve the detection accuracy further. The seizure detection method is assessed on Freiburg EEG datasets from 21 patients. The experimental results indicate that the proposed method yields an average sensitivity of 94. 60% with a false detection rate of 0. 18/h.

基于小波消噪的EMD模型在GPS振动信号处理中的应用

经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具有其优缺点,适用于不同的应用。从对GPS振动信号的预处理、时域和频域处理入手,结果分析表明,对GPS振动信号先进行小波滤波消除随机噪声的干扰,再应用经验模式分解更有利于变形特征信息的分离和提取,提取的信号与振动平台记录数据更加吻合。

Down-regulation of mi R-30a-3p/5p promotes esophageal squamous cell carcinoma cell proliferation by activating the Wnt signaling pathway

AIM To investigate the potential role of micro RNA-30 a(mi R-30 a) in esophageal squamous cell carcinoma(ESCC).METHODS Expression of mi R-30 a-3 p/5 p was analyzed using microarray data and fresh ESCC tissue samples. Both in vitro and in vivo assays were used to investigate the effects of mi R-30 a-3 p/5 p on ESCC cell proliferation. Furthermore,Kyoto Encyclopedia of Genes and Genomes analysis was performed to explore underlying mechanisms involved in ESCC,and then,assays were carried out to verify the potential molecular mechanism of mi R-30 a in ESCC.RESULTS Low expression of mi R-30 a-3 p/5 p was closely associated with advanced ESCC progression and poor prognosis of patients with ESCC. Knock-down of mi R-30 a-3 p/5 p promoted ESCC cell proliferation. Increased mi R-30 a-3 p/5 p expression inhibited the Wnt signaling pathway by targeting Wnt2 and Fzd2.CONCLUSION Down-regulation of mi R-30 a-3 p/5 p promotes ESCC cell proliferation by activating the Wnt signaling pathway through inhibition of Wnt2 and Fzd2.

Wnt signaling and stem cell control

Wnt signaling has been implicated in the control over various types of stem cells and may act as a niche factor to maintain stem cells in a self-renewing state. As currently understood, Wnt proteins bind to receptors of the Frizzled and LRP families on the cell surface. Through several cytoplasmic relay components, the signal is transduced to β-catenin, which then enters the nucleus and forms a complex with TCF to activate transcription of Wnt target genes. Wnts can also signal through tyrosine kinase receptors, in particular the ROR and RYK receptors, leading to alternative modes of Wnt signaling. During the growth of tissues, these ligands and receptors are dynamically expressed, often transcriptionally controlled by Wnt signals themselves, to ensure the right balance between proliferation and differentiation. Isolated Wnt proteins are active on a variety of stem cells, including neural, mammary and embryonic stem cells. In general, Wnt proteins act to maintain the undifferentiated state of stem cells, while other growth factors instruct the cells to proliferate. These other factors include FGF and EGF, signaling through tyrosine kinase pathways.

Wavelet analysis of pressure fluctuation signals in a gas-solid fluidized bed

It has been shown that much dynamic information is hidden in the pressure fluctuation signals of a gas-solid fluidized bed. Unfortunately, due to the random and capricious nature of this signal, it is hard to realize reliable analysis using traditional signal processing methods such as statistical analysis or spectral analysis, which is done in Fourier domain. Information in different frequency band can be extracted by using wavelet analysis. On the evidence of the composition of the pressure fluctuation signals, energy of low frequency (ELF) is proposed to show the transition of fluidized regimes from bubbling fluidization to turbulent fluidization. Plots are presented to describe the fluidized bed's evolution to help identify the state of different flow regimes and provide a characteristic curve to identify the fluidized status effectively and reliably.

Genetic alterations in hepatocellular carcinoma: An update

Hepatocellular carcinoma(HCC) is one of the leading causes of cancer-related deaths worldwide. Although recent advances in therapeutic approaches for treating HCC have improved the prognoses of patients with HCC, this cancer is still associated with a poor survival rate mainly due to late diagnosis. Therefore, a diagnosis must be made sufficiently early to perform curative and effective treatments. There is a need for a deeper understanding of the molecular mechanisms underlying the initiation and progression of HCC because these mechanisms are critical for making early diagnoses and developing novel therapeutic strategies. Over the past decade, much progress has been made in elucidating the molecular mechanisms underlying hepatocarcinogenesis. In particular, recent advances in next-generation sequencing technologies have revealed numerous genetic alterations, including recurrently mutated genes and dysregulated signaling pathways in HCC. A better understanding of the genetic alterations in HCC could contribute to identifying potential driver mutations and discovering novel therapeutic targets in the future. In this article, we summarize the current advances in research on the genetic alterations, including genomic instability, single-nucleotide polymorphisms, somatic mutations and deregulated signaling pathways, implicated in the initiation and progression of HCC. We also attempt to elucidate some of the genetic mechanisms that contribute to making early diagnoses of and developing molecularly targeted therapies for HCC.

Filtering detecting signal of rockbolt with harmonic wavelet

Harmonic wavelets not only possess the traditional advantages of a wavelet function,they also have other merits such as clear expressions,more flexible time-frequency divisions,a simple transformation algorithm,a finer box-like frequency spectrum and others.Given the frequency distribution characteristics of the nondestructive testing signals from a rockbolt support system and based on the discrete harmonic wavelet transformation theory,we have effectively abstracted signals from frequency ranges concerned by removing useless high and low frequency signals from the testing signals of the rockbolt support system and obtained filtered signals with a reconstruction algorithm of harmonic wavelets.Finally,we applied the harmonic wavelet transformation in filtering analog signals and measured response signals of rockbolts.The results indicate that harmonic wavelets also have excellent filtering characteristics.

Influence of maximum decking charge on intensity of blasting vibration

Based on the character of short-time non-stationary random signal, the relationship between the maximum decking charge and energy distribution of blasting vibration signals was investigated by means of the wavelet packet method. Firstly, the characteristics of wavelet transform and wavelet packet analysis were described. Secondly, the blasting vibration signals were analyzed by wavelet packet based on software MATLAB, and the change of energy distribution curve at different frequency bands were obtained. Finally, the law of energy distribution of blasting vibration signals changing with the maximum decking charge was analyzed. The results show that with the increase of decking charge, the ratio of the energy of high frequency to total energy decreases, the dominant frequency hands of blasting vibration signals tend towards low frequency and hlasting vibration does not depend on the maximum decking charge.