If it looks like a spammer and behaves like a spammer,it must be a spammer: analysis and detection of microblogging spam accounts

Spam in online social networks (OSNs) is a systemic problem that imposes a threat to these services in terms of undermining their value to advertisers and potential investors, as well as negatively affecting users’ engagement. As spammers continuously keep creating newer accounts and evasive techniques upon being caught, a deeper understanding of their spamming strategies is vital to the design of future social media defense mechanisms. In this work, we present a unique analysis of spam accounts in OSNs viewed through the lens of their behavioral characteristics. Our analysis includes over 100 million messages collected from Twitter over the course of 1 month. We show that there exist two behaviorally distinct categories of spammers and that they employ different spamming strategies. Then, we illustrate how users in these two categories demonstrate different individual properties as well as social interaction patterns. Finally, we analyze the detectability of spam accounts with respect to three categories of features, namely content attributes, social interactions, and profile properties.     

Enthalpy landscapes and the glass transition

A fundamental understanding of the glass transition is essential for enabling future breakthroughs in glass science and technology. In this paper, we review recent advances in the modeling of glass transition range behavior based on the enthalpy landscape approach. We also give an overview of new simulation techniques for implementation of enthalpy landscape models, including techniques for mapping the landscape and computing the long-time dynamics of the system. When combined with these new computational techniques, the enthalpy landscape approach can provide for the predictive modeling of glass transition and relaxation behavior on a laboratory time scale. We also discuss new insights from the enthalpy landscape approach into the nature of the supercooled liquid and glassy states. In particular, the enthalpy landscape approach provides for natural resolutions of both the Kauzmann paradox and the question of residual entropy of glass at absolute zero. We further show that the glassy state cannot be described in terms of a mixture of equilibrium liquid states, indicating that there is no microscopic basis for the concept of a fictive temperature distribution and that the glass and liquid are two fundamentally different states. We also discuss the connection between supercooled liquid fragility and the ideal glass transition.     

Substrate Doping Effect and Unusually Large Angle van Hove Singularity Evolution in Twisted Bi‐ and Multilayer Graphene

Graphene has demonstrated great potential in new‐generation electronic applications due to its unique electronic properties such as large carrier Fermi velocity, ultrahigh carrier mobility, and high material stability. Interestingly, the electronic structures can be further engineered in multilayer graphene by the introduction of a twist angle between different layers to create van Hove singularities (vHSs) at adjustable binding energy. In this work, using angle‐resolved photoemission spectroscopy with sub‐micrometer spatial resolution, the band structures and their evolution are systematically studied with twist angle in bilayer and trilayer graphene sheets. A doping effect is directly observed in graphene multilayer system as well as vHSs in bilayer graphene over a wide range of twist angles (from 5° to 31°) with wide tunable energy range over 2 eV. In addition, the formation of multiple vHSs (at different binding energies) is also observed in trilayer graphene. The large tuning range of vHS binding energy in twisted multilayer graphene provides a promising material base for optoelectrical applications with broadband wavelength selectivity from the infrared to the ultraviolet regime, as demonstrated by an example application of wavelength selective photodetector.     

Integrating multi-temporal spectral and structural information to map wetland vegetation in a lower Connecticut River tidal marsh

This study examines the effectiveness of using multi-temporal satellite imagery, field spectral data, and LiDAR top of canopy data to classify and map the common plant communities of the Ragged Rock Creek marsh, located near the mouth of the Connecticut River. Visible to near-infrared (VNIR) reflectance spectra were measured in the field over the 2004–2006 growing seasons to assess the phenological variability of the dominant marsh plant species, Spartina patens, Phragmites australis and Typha spp. Phragmites was best distinguished from other species by its high NIR response late in the growing season. Typha spp. had a high red/green ratio and S. patens had a unique green/blue ratio relative to other species throughout the bulk of the growing season. The field spectra and single date (2004) LiDAR canopy height data were used to define an object-oriented classification methodology for the three plant communities in multi-temporal QuickBird multispectral imagery collected over the same time interval. The classification was validated using an extensive field inventory of marsh species. Overall maximum fuzzy accuracy for the classification was 97% for Phragmites, 63% for Typha spp. and 80% for S. patens meadows and improved to 97%, 76%, and 92%, respectively, using a fuzzy acceptable match measure. This study demonstrated the importance of the timing of image acquisition for the identification of targeted plant species in a heterogeneous marsh. These datasets and protocols may provide coastal resource managers, municipal officials and researchers a set of recommended guidelines for remote sensing data collection for marsh inventory and monitoring.     

Nonlinear features of heart rate variability in paranoid schizophrenic

Cardiovascular mortality is significantly increased in patients suffering from schizophrenia. However, psychotic symptoms are quantified by means of the scale for the assessment of positive and negative symptoms, but many investigations try to introduce new etiology for psychiatric disorders based on combination of biological, psychological and social causes. Classification between healthy and paranoid cases has been achieved by time, frequency, Hilbert–Huang (HH) and a combination between those features as a hybrid features. Those features extracted from the Hilbert–Huang transform for each intrinsic mode function (IMF) of the detrended time series for each healthy case and paranoid case. Short-term ECG recordings of 20 unmedicated patients suffering from acute paranoid schizophrenia and those obtained from healthy matched peers have been utilized in this investigation. Frequency features: very low frequency (VLF), low frequency (LF), high frequency (HF) and HF/LF (ratio) produced promising success rate equal to 97.82 % in training and 97.77 % success rate in validation by means of IMF1 and ninefolds. Time–frequency features [LF, HF and ratio, mean, maximum (max), minimum (min) and standard deviation (SD)] provided 100 % success in both training and validation trials by means of ninefolds for IMF1 and IMF2. By utilizing IMF1 and ninefolds, frequency and Hilbert–Hang features [LF, HF, ratio, mean value of envelope ( \(\bar{a}\) )] produced 96.87 and 95.5 % for training and validation, respectively. By analyzing the first IMF and using ninefolds, time and Hilbert–Hang features [mean, max, min, SD, median, first quartile (Q1), third quartile (Q3), kurtosis, skewness, Shannon entropy, approximate entropy and energy, ( \(\bar{a}\) ), level of envelope variation ([ \(\dot{a}\) (t)]^2), central frequency \((\bar{W})\) and number of zero signal crossing \((\left| {\bar{W}} \right|)\) ] produced a 100 % success rate in training and 90 % success rate in validation. Time, frequency and HH features [energy, VLF, LF, HF, ratio and ( \(\bar{a}\) )] provided 97.5 % success rate in training and 95.24 % success rate in validation using IMF1 and sixfolds. However, frequency features have produced promising classification success rate, but hybrid features emerged the highest classification success rate than using features in each domain separately.     

Off-grid energy services for the poor: Introducing LED lighting in the Millennium Villages Project in Malawi

Lanterns that use light-emitting diodes (LEDs) powered by batteries, which are in turn charged by grid electricity or small solar panels, have emerged as a cost-competitive alternative to kerosene and other fuel-based lighting technologies, offering brighter light for longer duration at equal or lower cost over time. This paper presents lessons learned from the introduction of solar LED lanterns in rural Malawi. We discuss a market-based program using new and existing local commercial structures such as vendors and cooperatives to sell lanterns to village households without subsidy. The paper addresses issues of enterprise development, community interactions, and survey data on lighting use and expenditure patterns before and after LED lantern introduction. Households that purchased a lantern reported high levels of satisfaction with the LED lanterns as well as savings in annual kerosene expenditure comparable to the price of the lantern. These households also reported monthly incomes comparable to the price of the LED lanterns whereas non-adopters surveyed reported monthly incomes about half this level, suggesting a need for financing options to maximize adoption among poorer populations in rural areas. These results suggest that similar market based models of LED lighting technology dissemination have the potential to be replicated and scaled up in other off-grid regions in developing countries. However, viability of local cooperatives and supply chains for lantern products over the medium-to-long term remain to be assessed.     

采用GC/MSD DRS对残留农药进行全面筛查

1 引言 根据农药手册，目前世界上正在使用的农药有700多种。大约600种农药是过去使用的，但现在已经禁用或不再销售。有一些农药早已不再使用，但它们仍然存在干环境中，还可能在植物和动物体内生物富集。在食品和饮料、在土壤、水和大气、在水生和陆生的动植物、在人类血液、脂肪组织和乳汁中，都能检测到痕量的农药或它们的代谢物。世界卫生组织根据农药对人的急性毒性将农药分成五类。所分成的类别从“有急性毒性”到那些“正常使用时没有急性毒性”的种类。     

An explorative study on the cell wall polysaccharides in the pulp and peel of dragon fruits (Hylocereus spp.)

The pectic and hemicellulosic cell wall polysaccharides from the pulp and the peel of white-flesh and red-flesh dragon fruits (Hylocereus spp.) were isolated and compared in terms of degree of methoxylation (DM), solubility properties (relative content of uronic acids and neutral sugars in different fractions), neutral sugar composition, molar mass distribution, and affinity toward some specific anti-pectin antibodies. Hereto, the alcohol-insoluble residues were extracted and sequentially fractionated using hot water, a chelating agent, sodium carbonate, and potassium hydroxide solutions to obtain different pectin fractions and a hemicellulose fraction. Chemical analyses were used to characterize these polysaccharide fractions. The results show that cell wall polysaccharides of the pulp and especially of the peel from white-flesh and red-flesh dragon fruits contain significant amounts of pectic substances that are lowly methyl-esterified. The cell wall polysaccharides of the peel as well as those of the pulp contain high amounts (38–47 %) of loosely bound (water-soluble) pectic substances. In the water-soluble fraction (WSF) of the peel samples, uronic acids are the predominant monomers. On the contrary, rhamnogalacturonan-I type neutral sugars, and especially arabinose and galactose, contribute equally, as compared to uronic acid, to the WSF of the pulp samples. Despite the low average DM value of pulp and peel pectin, pectic substances in both samples showed affinity for antibodies with different specificities indicating that a wide range of epitopes, including long blocks of unesterified galacturonic acids (GalA) residues as well as (short) blocks of esterified GalA residues, is present. No large differences between the pectic substances among the different dragon fruit varieties were observed.