Using online linear classifiers to filter spam Emails

The performance of two online linear classifiers - the Perceptron and Littlestone’s Winnow – is explored for two anti-spam filtering benchmark corpora - PU1 and Ling-Spam. We study the performance for varying numbers of features, along with three different feature selection methods: Information Gain (IG), Document Frequency (DF) and Odds Ratio. The size of the training set and the number of training iterations are also investigated for both classifiers. The experimental results show that both the Perceptron and Winnow perform much better when using IG or DF than using Odds Ratio. It is further demonstrated that when using IG or DF, the classifiers are insensitive to the number of features and the number of training iterations, and not greatly sensitive to the size of training set. Winnow is shown to slightly outperform the Perceptron. It is also demonstrated that both of these online classifiers perform much better than a standard Naïve Bayes method. The theoretical and implementation computational complexity of these two classifiers are very low, and they are very easily adaptively updated. They outperform most of the published results, while being significantly easier to train and adapt. The analysis and promising experimental results indicate that the Perceptron and Winnow are two very competitive classifiers for anti-spam filtering

Circulations in the Pearl River Estuary: Observation and Modeling

This chapter reports a cruise survey on the Pearl River Estuary (PRE) and adjacent costal water in the period between May 3, 2014 and May 11, 2014. The circulation and salinity structure were sampled for different tidal phases. With the cruise data, a “sandwich” structure of the lateral salinity distribution and a two-layer structure of longitudinal circulation were identified, together with high variations influenced by wind and tide. Furthermore, longitudinally orientated convergence or divergence of the lateral velocity close to the channel location for certain tidal conditions was observed. The finite volume community ocean model (FVCOM) is configured and run with high spatial resolution of 100 m in the PRE. An atmospheric model, the Weather Research and Forecasting (WRF) Model, is also run to provide high spatial and temporal resolution of atmospheric forcing for the FVCOM. The FVCOM modeling skill assessment is conducted using the cruise salinity and velocity data, as well as water levels, showing that the model can well simulate the velocity and salinity structures. The numerical model reveals that there is a strong neap-spring cycle for the PRE de-tided circulation with 0.37 m s−1 during the neap tide about 42% stronger than that (0.26 m s−1) during the spring tide in the surface layer

Research on Some Phenomenon of E-Government Service Capacity Distribution in Mainland China Based on Multi-channel Perspective

In the context of the government\u27s increasing emphasis on e-government services, this is an urgent need for empirical research of large sample and multi-channels. Therefore, based on the government website, WeChat, Micro-blog, app, by using the existing mature evaluation index system, this paper analyzes e-government service capacity of the city above prefecture- level and provincial. Then, this paper selects the administrative level, economic level, regional balance as the differentiation attribute. It is found that both administrative level and economic level are positively correlated with government service capacity in all the channels. The channel capacity distribution varies related to attribute of administrative and economic, government type of city and province, but it is not restricted by level and region. It provides direction and intensity management to balance and promote channel service capacity for China government

A global dataset of spatiotemporally seamless daily mean land surface temperatures: generation, validation, and analysis

Daily mean land surface temperatures (LSTs) acquired from polar orbiters are crucial for various applications such as global and regional climate change analysis. However, thermal sensors from polar orbiters can only sample the surface effectively with very limited times per day under cloud-free conditions. These limitations have produced a systematic sampling bias (ΔT$_{sb}$) on the daily mean LST (T$_{dm}$) estimated with the traditional method, which uses the averages of clear-sky LST observations directly as the T$_{dm}$. Several methods have been proposed for the estimation of the T$_{dm}$, yet they are becoming less capable of generating spatiotemporally seamless T$_{dm}$ across the globe. Based on MODIS and reanalysis data, here we propose an improved annual and diurnal temperature cycle-based framework (termed the IADTC framework) to generate global spatiotemporally seamless T$_{dm}$ products ranging from 2003 to 2019 (named the GADTC products). The validations show that the IADTC framework reduces the systematic ΔT$_{sb}$ significantly. When validated only with in situ data, the assessments show that the mean absolute errors (MAEs) of the IADTC framework are 1.4 and 1.1 K for SURFRAD and FLUXNET data, respectively, and the mean biases are both close to zero. Direct comparisons between the GADTC products and in situ measurements indicate that the MAEs are 2.2 and 3.1 K for the SURFRAD and FLUXNET datasets, respectively, and the mean biases are −1.6 and −1.5 K for these two datasets, respectively. By taking the GADTC products as references, further analysis reveals that the T$_{dm}$ estimated with the traditional averaging method yields a positive systematic ΔT$_{sb}$ of greater than 2.0 K in low-latitude and midlatitude regions while of a relatively small value in high-latitude regions. Although the global-mean LST trend (2003 to 2019) calculated with the traditional method and the IADTC framework is relatively close (both between 0.025 to 0.029 K yr$^{–1}$), regional discrepancies in LST trend do occur – the pixel-based MAE in LST trend between these two methods reaches 0.012 K yr$^{–1}$. We consider the IADTC framework can guide the further optimization of T$_{dm}$ estimation across the globe, and the generated GADTC products should be valuable in various applications such as global and regional warming analysis

Ultra-uniform MIL-88B(Fe)/Fe3S4 hybrids engineered by partial sulfidation to boost catalysis in electro-Fenton treatment of micropollutants: Experimental and mechanistic insights

Fe-based metal-organic frameworks are promising catalysts for water treatment, although their viability is hampered by the slow regeneration of active Fe(II) sites. A facile sulfidation strategy is proposed to boost the catalytic activity of MIL-88B(Fe) in heterogeneous electro-Fenton (HEF) treatment of organic micropollutants at mild pH. The synthesized MIL-88B(Fe)/Fe3S4 hybrids possessed numerous and durable unsaturated iron sites, acting the S2- atoms as electron donors that enhanced the Fe(II) recycling. The sulfidated catalyst outperformed the MIL-88B(Fe), as evidenced by the 7-fold faster degradation of antibiotic trimethoprim by HEF and the fast destruction of micropollutants in urban wastewater. The hybrid catalyst was reused, obtaining >90% drug removal after four runs and, additionally, its inherent magnetism facilitated the post-treatment recovery. Electrochemical tests and DFT calculations provided mechanistic insights to explain the enhanced catalysis, suggesting that the accelerated Fe(III)/Fe(II) cycling and the enhanced mass transport and electron transfer accounted for the efficient trimethoprim degradation

Surgical treatment of patellar dislocation: A network meta-analysis of randomized control trials and cohort studies

BackgroundCurrently, there are many surgical options for patellar dislocation. The purpose of this study is to perform a network meta-analysis of the randomized controlled trials (RCTs) and cohort studies to determine the better treatment.MethodWe searched the Pubmed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, clinicaltrials.gov and who.int/trialsearch. Clinical outcomes included Kujala score, Lysholm score, International Knee Documentation Committee (IKDC) score, redislocation or recurrent instability. We conducted pairwise meta-analysis and network meta-analysis respectively using the frequentist model to compare the clinical outcomes.ResultsThere were 10 RCTs and 2 cohort studies with a total of 774 patients included in our study. In network meta-analysis, double-bundle medial patellofemoral ligament reconstruction (DB-MPFLR) achieved good results on functional scores. According to the surface under the cumulative ranking (SUCRA), DB-MPFLR had the highest probabilities of their protective effects on outcomes of Kujala score (SUCRA 96.5 %), IKDC score (SUCRA 100.0%) and redislocation (SUCRA 67.8%). However, DB-MPFLR (SUCRA 84.6%) comes second to SB-MPFLR (SUCRA 90.4%) in Lyshlom score. It is (SUCRA 70%) also inferior to vastus medialis plasty (VM-plasty) (SUCRA 81.9%) in preventing Recurrent instability. The results of subgroup analysis were similar.ConclusionOur study demonstrated that MPFLR showed better functional scores than other surgical options

Surface Acting or Deep Acting, Who Need More Effortful? A Study on Emotional Labor Using Functional Near-Infrared Spectroscopy

Emotional labor is characterized by two main regulation strategies: surface acting and deep acting. However, which strategy consumes more energy? To explore this, we used functional near-infrared spectroscopy (fNIRS) to measure changes in hemoglobin density while participants performed a task requiring them to make the opposite emotional facial expression of that presented in a picture. We found that (1) neither surface nor deep acting led to a significant change in hemoglobin concentration in the prefrontal cortex; (2) making negative and positive facial expressions activated the same left front and middle areas of the prefrontal cortex; and (3) making positive facial expressions activated the rear portion of the prefrontal cortex, but making negative facial expressions did not. Based on these findings and past work, we can infer that deep and surface acting may not significantly differ in terms of the activity in the prefrontal cortex energy consumed. Furthermore, engaging in positive and negative emotional labor appear to utilize some of the same neurological mechanisms, although they differ in others

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.This work was supported by National Natural Science Foundation of China (No.30571409), Educational and scientific research program for young and middle-aged instructor of Fujian province (No.JAT160161) and the earmarked fund for Modern Agro-industry Technology Research System (No.CARS-45-KXJ3