A Robust Classification-autoencoder to Defend Outliers and Adversaries

In this paper, we present a robust classification-autoencoder (CAE) which has strong ability to recognize outliers and defend adversaries. The basic idea is to change the autoencoder from an unsupervised learning method into a classifier. The CAE is a modified autoencoder, where the encoder is used to compress samples with different labels into disjoint compression spaces and the decoder is used to recover a sample with a given label from the corresponding compression space. The encoder is used as a classifier and the decoder is used to decide whether the classification given by the encoder is correct by comparing the input sample with the output. Since adversary samples are seeming inevitable for the current DNN framework, we introduce the list classification based on CAE to defend adversaries, which outputs several labels and the corresponding samples recovered by the CAE. The CAE is evaluated using the MNIST dataset in great detail. It is shown that the CAE network can recognize almost all outliers and the list classification contains the correct label for almost all adversaries

KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization

We consider the image classification problem via kernel collaborative representation classification with locality constrained dictionary (KCRC-LCD). Specifically, we propose a kernel collaborative representation classification (KCRC) approach in which kernel method is used to improve the discrimination ability of collaborative representation classification (CRC). We then measure the similarities between the query and atoms in the global dictionary in order to construct a locality constrained dictionary (LCD) for KCRC. In addition, we discuss several similarity measure approaches in LCD and further present a simple yet effective unified similarity measure whose superiority is validated in experiments. There are several appealing aspects associated with LCD. First, LCD can be nicely incorporated under the framework of KCRC. The LCD similarity measure can be kernelized under KCRC, which theoretically links CRC and LCD under the kernel method. Second, KCRC-LCD becomes more scalable to both the training set size and the feature dimension. Example shows that KCRC is able to perfectly classify data with certain distribution, while conventional CRC fails completely. Comprehensive experiments on many public datasets also show that KCRC-LCD is a robust discriminative classifier with both excellent performance and good scalability, being comparable or outperforming many other state-of-the-art approaches

Dynamical and finite-size effects on the signal of first-order phase transition

We study the dynamical behaviors of the criterion identifying the first-order phase transition in the matter generated by the relativistic heavy-ion collisions, by explicitly involving the dynamical effects based on the Fokker-Plank framework. The perspectives we taken into account range from phase transition scenarios, initial temperatures, volume effect, relaxation rates, and evolution trajectories. Our numerical calculations show that the dynamical signal of the first-order phase transition can be reserved in certain conditions. Besides the delaying effects due to a finite relaxation time, a larger initial temperature, a smaller volume, a larger relaxation rate, or bending of the trajectory will lead to reduction of the signal. Our discussions on the criterion offer valuable reference information for the experimental detection of the first-order phase transition signal.Comment: 9 pages, 7 figure

Robust generalized filter bank multicarrier based optical access system with electrical polar coding

A robust generalized filter bank multicarrier (GFBMC) optical access system with polar coding is proposed in the letter. Cyclic redundancy check combined polar code has been adopted to improve the performance of the access system with lower computational time. An experiment with a 40 Gb/s polar coded GFBMC access system is successfully demonstrated with the proposed method. The results indicate a prospect solution for the forward error correction (FEC) in optical access system

Application of a digital twin for highway tunnels based on multi-sensor and information fusion

Due to the harsh environment of highway tunnels and frequent breakdowns of various detection sensors and surveillance devices, the operational management of highway tunnels lacks effective data support. This paper analyzes the characteristics of operational surveillance data in highway tunnels. It proposes a multimodal information fusion method based on CNN–LSTM–attention and designs and develops a digital twin for highway tunnel operations. The system addresses issues such as insufficient development and coordination of the technical architecture of operation control systems, weak information service capabilities, and insufficient data application capabilities. The system also lacks intelligent decision-making and control capabilities. The developed system achieves closed-loop management of “accurate perception–risk assessment–decision warning–emergency management” for highway tunnel operations based on data-driven approaches. The engineering demonstration application underscores the system’s capacity to enhance tunnel traffic safety, diminish tunnel management costs, and elevate tunnel driving comfort

High Viral Load of Human Bocavirus Correlates with Duration of Wheezing in Children with Severe Lower Respiratory Tract Infection

Background: Human bocavirus (HBoV) is a newly discovered parvovirus and increasing evidences are available to support its role as an etiologic agent in lower respiratory tract infection (LRTI). The objective of this study is to assess the impact of HBoV viral load on clinical characteristics in children who were HBoV positive and suffered severe LRTI. Methods: Lower respiratory tract aspirates from 186 hospitalized children with severe LRTI were obtained by bronchoscopy. HBoVs were detected by real-time PCR and other 10 infectious agents were examined using PCR and/or direct fluorescent assay. Results: Thirty-one patients (24.6%) were tested positive for HBoV in the respiratory tract aspirates. Fifteen samples had a high viral load (.10 4 copies/mL) and the other sixteen samples had a low viral load (,10 4 copies/mL). The duration of presented wheezing and hospitalization was longer in children with high viral load of HBoV than that in children with low viral load. The days of wheezing showed a correlation with viral load of HBoV. Conclusion: We confirmed that HBoV was frequently detected in patients with severe LRTI. Wheezing was one of the most common symptoms presented by patients with positive HBoV. A high HBoV viral load could be an etiologic agent for LRTI

Coral-algal interactions at Weizhou Island in the northern South China Sea: variations by taxa and the exacerbating impact of sediments trapped in turf algae

Competitive interactions between corals and benthic algae are increasingly frequent on degrading coral reefs, but the processes and mechanisms surrounding the interactions, as well as the exacerbating effects of sediments trapped in turf algae, are poorly described. We surveyed the frequency, proportion, and outcomes of interactions between benthic algae (turf algae and macroalgae) and 631 corals (genera: Porites, Favites, Favia, Platygyra, and Pavona) on a degenerating reef in the northern South China Sea, with a specific focus on the negative effects of algal contact on corals. Our data indicated that turf algae were the main algal competitors for each surveyed coral genus and the proportion of algal contact along the coral edges varied significantly among the coral genera and the algal types. The proportions of algal wins between corals and turf algae or macroalgae differed significantly among coral genera. Compared to macroalgae, turf algae consistently yielded more algal wins and fewer coral wins on all coral genera. Amongst the coral genera, Porites was the most easily damaged by algal competition. The proportions of turf algal wins on the coral genera increased 1.1–1.9 times in the presence of sediments. Furthermore, the proportions of algal wins on massive and encrusting corals significantly increased with the combination of sediments and turf algae as the algal type. However, the variation in proportions of algal wins between massive and encrusting corals disappeared as sediments became trapped in turf algae. Sediments bound within turf algae further induced damage to corals and reduced the competitive advantage of the different coral growth forms in their competitive interactions with adjacent turf algae

Rehabilitation recognition skeleton data depth learning based on RNN

With the extensive application of deep learning in the field of human rehabilitation, skeleton based rehabilitation recognition is becoming more and more concerned with large-scale bone data sets. The key factor of this task is the two intra frame representations of the combined co-and the inter-frame. In this paper, an inter frame representation method based on RNN is proposed. Pointtion of each joint is joint-coded they are assembled into semantic both spatial and temporal domains.we introduce a global spatial aggregation which is able to learn superior joint co features over local aggregation

Acteoside From Ligustrum robustum (Roxb.) Blume Ameliorates Lipid Metabolism and Synthesis in a HepG2 Cell Model of Lipid Accumulation

We aimed to ascertain the mechanism underlying the effects of acteoside (ACT) from Ligustrum robustum (Roxb.) Blume (Oleaceae) on lipid metabolism and synthesis. ACT, a water-soluble phenylpropanoid glycoside, is the most abundant and major active component of L. robustum; the leaves of L. robustum, known as kudingcha (bitter tea), have long been used in China as an herbal tea for weight loss. Recently, based on previous studies, our team reached a preliminary conclusion that phenylpropanoid glycosides from L. robustum most likely contribute substantially to reducing lipid levels, but the mechanism remains unclear. Here, we conducted an in silico screen of currently known phenylethanoid glycosides from L. robustum and attempted to explore the hypolipidemic mechanism of ACT, the representative component of phenylethanoid glycosides in L. robustum, using RNA-seq technology, quantitative real-time PCR (qPCR) and Western blotting. First, the screening results for six compounds were docked with 15 human protein targets, and 3 of 15 protein targets were related to cardiovascular diseases. Based on previous experimental data and docking results, we selected ACT, which exerted positive effects, for further study. We generated a lipid accumulation model using HepG2 cells treated with a high concentration of oleic acid and then extracted RNA from cells treated for 24 h with 50 μmol/L ACT. Subsequently, we performed a transcriptomic analysis of the RNA-seq results, which revealed a large number of differentially expressed genes. Finally, we randomly selected some genes and proteins for further validation using qPCR and Western blotting; the results agreed with the RNA-seq data and confirmed their reliability. In conclusion, our experiments proved that ACT from L. robustum alters lipid metabolism and synthesis by regulating the expression of multiple genes, including Scarb1, Scarb2, Srebf1, Dhcr7, Acat2, Hmgcr, Fdft1, and Lss, which are involved several pathways, such as the glycolytic, AMPK, and fatty acid degradation pathways

Ground beetle assemblages in Beijing’s new mountain forests

Mature forests have been almost completely destroyed in China’s northern regions, but this has been followed by large-scale reforestation in the wake of environmental degradation. Although future forest plantations are expected to expand over millions of hectares, knowledge about the ecology and biodiversity of China’s replanted forests remains very limited. Addressing these knowledge gaps, we recorded ground beetle (Coleoptera: Carabidae) communities in five secondary forest types: plantations of Chinese Pine (Pinus tabulaeformis) and Prince Rupprecht’s Larch (Larix principis-rupprechtii), Oak (Quercus wutaishanica) and Asian White Birch (Betula platyphylla) woodlands, and naturally regenerated mixed forest. Species richness peaked in mixed forests, while pine and oak woodlands harboured discrete communities of intermediate species richness. Oak, pine and mixed forest habitats also showed high levels of species turnover between plots. Canopy closure was an important factor influencing ground beetle assemblages and diversity, and a number of forest specialist species only occurred in pine or oak forests. We believe that some forest specialists have survived earlier deforestation and appear to be supported by new plantation forests, but maintenance of secondary native oak and mixed forests is crucial to safeguard the overall species pool