Studying Malicious Websites and the Underground Economy on the Chinese Web

The World Wide Web gains more and more popularity within China with more than 1.31 million websites on the Chinese Web in June 2007. Driven by the economic profits, cyber criminals are on the rise and use the Web to exploit innocent users. In fact, a real underground black market with thousand of participants has developed which brings together malicious users who trade exploits, malware, virtual assets, stolen credentials, and more. In this paper, we provide a detailed overview of this underground black market and present a model to describe the market. We substantiate our model with the help of measurement results within the Chinese Web. First, we show that the amount of virtual assets traded on this underground market is huge. Second, our research proofs that a significant amount of websites within China’s part of the Web are malicious: our measurements reveal that about 1.49% of the examined sites contain some kind of malicious content

Modification of Transition-Metal Redox by Interstitial Water in Hexacyanometalate Electrodes for Sodium-Ion Batteries.

A sodium-ion battery (SIB) solution is attractive for grid-scale electrical energy storage. Low-cost hexacyanometalate is a promising electrode material for SIBs because of its easy synthesis and open framework. Most hexacyanometalate-based SIBs work with aqueous electrolyte, and interstitial water in the material has been found to strongly affect the electrochemical profile, but the mechanism remains elusive. Here we provide a comparative study of the transition-metal redox in hexacyanometalate electrodes with and without interstitial water based on soft X-ray absorption spectroscopy and theoretical calculations. We found distinct transition-metal redox sequences in hydrated and anhydrated NaxMnFe(CN)6·zH2O. The Fe and Mn redox in hydrated electrodes are separated and are at different potentials, leading to two voltage plateaus. On the contrary, mixed Fe and Mn redox in the same potential range is found in the anhydrated system. This work reveals for the first time how transition-metal redox in batteries is strongly affected by interstitial molecules that are seemingly spectators. The results suggest a fundamental mechanism based on three competing factors that determine the transition-metal redox potentials. Because most hexacyanometalate electrodes contain water, this work directly reveals the mechanism of how interstitial molecules could define the electrochemical profile, especially for electrodes based on transition-metal redox with well-defined spin states

Unified Joint Matrix-Monotonic Optimization of MIMO Training Sequences and Transceivers

Channel estimation and transmission constitute the most fundamental functional modules of multiple-input multiple-output (MIMO) communication systems. The underlying key tasks corresponding to these modules are training sequence optimization and transceiver optimization. Hence, we jointly optimize the linear transmit precoder and the training sequence of MIMO systems using the metrics of their effective mutual information (MI), effective mean squared error (MSE), effective weighted MI, effective weighted MSE, as well as their effective generic Schur-convex and Schur-concave functions. Both statistical channel state information (CSI) and estimated CSI are considered at the transmitter in the joint optimization. A unified framework termed as joint matrix-monotonic optimization is proposed. Based on this, the optimal precoder matrix and training matrix structures can be derived for both CSI scenarios. Then, based on the optimal matrix structures, our linear transceivers and their training sequences can be jointly optimized. Compared to state-of-the-art benchmark algorithms, the proposed algorithms visualize the bold explicit relationships between the attainable system performance of our linear transceivers conceived and their training sequences, leading to implementation ready recipes. Finally, several numerical results are provided, which corroborate our theoretical results and demonstrate the compelling benefits of our proposed pilot-aided MIMO solutions.Comment: 29 pages, 7 figure

Duplication and Remolding of tRNA Genes in the Mitochondrial Genome of \u3cem\u3eReduvius tenebrosus\u3c/em\u3e (Hemiptera: Reduviidae)

Most assassin bugs are predators that act as important natural enemies of insect pests. Mitochondrial (mt) genomes of these insects are double-strand circular DNAs that encode 37 genes. In the present study, we explore the duplication and rearrangement of tRNA genes in the mt genome of Reduvius tenebrosus, the first mt genome from the subfamily Reduviinae. The gene order rearranges from CR (control region)-trnI-trnQ-trnM-ND2 to CR-trnQ-trnI2-trnI1-trnM-ND2. We identified 23 tRNA genes, including 22 tRNAs commonly found in insects and an additional trnI (trnI2), which has high sequence similarity to trnM. We found several pseudo genes, such as pseudo-trnI, pseudo-CR, and pseudo-ND2, in the hotspot region of gene rearrangement (between the control region and ND2). These features provided evidence that this novel gene order could be explained by the tandem duplication/random loss (TDRL) model. The tRNA duplication/anticodon mutation mechanism further explains the presence of trnI2, which is remolded from a duplicated trnM in the TDRL process (through an anticodon mutation of CAT to GAT). Our study also raises new questions as to whether the two events proceed simultaneously and if the remolded tRNA gene is fully functional. Significantly, the duplicated tRNA gene in the mitochondrial genome has evolved independently at least two times within assassin bugs

Capturing the Phylogeny of Holometabola with Mitochondrial Genome Data and Bayesian Site-Heterogeneous Mixture Models

After decades of debate, a mostly satisfactory resolution of relationships among the 11 recognized holometabolan orders of insects has been reached based on nuclear genes, resolving one of the most substantial branches of the tree-of-life, but the relationships are still not well established with mitochondrial genome data. The main reasons have been the absence of sufficient data in several orders and lack of appropriate phylogenetic methods that avoid the systematic errors from compositional and mutational biases in insect mitochondrial genomes. In this study, we assembled the richest taxon sampling of Holometabola to date (199 species in 11 orders), and analyzed both nucleotide and amino acid data sets using several methods. We find the standard Bayesian inference and maximum-likelihood analyses were strongly affected by systematic biases, but the site-heterogeneous mixture model implemented in PhyloBayes avoided the false grouping of unrelated taxa exhibiting similar base composition and accelerated evolutionary rate. The inclusion of rRNA genes and removal of fast-evolving sites with the observed variability sorting method for identifying sites deviating from the mean rates improved the phylogenetic inferences under a site-heterogeneous model, correctly recovering most deep branches of the Holometabola phylogeny. We suggest that the use of mitochondrial genome data for resolving deep phylogenetic relationships requires an assessment of the potential impact of substitutional saturation and compositional biases through data deletion strategies and by using site-heterogeneous mixture models. Our study suggests a practical approach for how to use densely sampled mitochondrial genome data in phylogenetic analyses

What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning

Visual instruction tuning is an essential approach to improving the zero-shot generalization capability of Multi-modal Large Language Models (MLLMs). A surge of visual instruction datasets with various focuses and characteristics have been proposed recently, enabling MLLMs to achieve surprising results on evaluation benchmarks. To develop more capable MLLMs, in this paper, we aim to investigate a more fundamental question: ``what makes for good visual instructions?''. By conducting a comprehensive empirical study, we find that instructions focused on complex visual reasoning tasks are particularly effective in improving the performance of MLLMs on evaluation benchmarks. Building upon this finding, we design a systematic approach to automatically creating high-quality complex visual reasoning instructions. Our approach employs a synthesis-complication-reformulation paradigm, leveraging multiple stages to gradually increase the complexity of the instructions while guaranteeing quality. Based on this approach, we create the synthetic visual reasoning instruction dataset consisting of 32K examples, namely ComVint, and fine-tune four MLLMs on it. Experimental results demonstrate that our dataset consistently enhances the performance of all the compared MLLMs, e.g., improving the performance of MiniGPT-4 and BLIP-2 on MME-Cognition by 32.6% and 28.8%, respectively. Our code and data are publicly available at the link: https://github.com/RUCAIBox/ComVint.Comment: Work in progres

Origination, Expansion, Evolutionary Trajectory, and Expression Bias of AP2/ERF Superfamily in Brassica napus

The AP2/ERF superfamily, one of the most important transcription factor families, plays crucial roles in response to biotic and abiotic stresses. So far, a comprehensive evolutionary inference of its origination and expansion has not been available. Here, we identified 515 AP2/ERF genes in B. napus, a neo-tetraploid forming ~7500 years ago, and found that 82.14% of them were duplicated in the tetraploidization. A prominent subgenome bias was revealed in gene expression, tissue-specific, and gene conversion. Moreover, a large-scale analysis across plants and alga suggested that this superfamily could have been originated from AP2 family, expanding to form other families (ERF, and RAV). This process was accompanied by duplicating and/or alternative deleting AP2 domain, intragenic domain sequence conversion, and/or by acquiring other domains, resulting in copy number variations, alternatively contributing to functional innovation. We found that significant positive selection occurred at certain critical nodes during the evolution of land plants, possibly responding to changing environment. In conclusion, the present research revealed origination, functional innovation, and evolutionary trajectory of the AP2/ERF superfamily, contributing to understanding their roles in plant stress tolerance

Cellular Origins of EGFR-Driven Lung Cancer Cells Determine Sensitivity to Therapy

Targeting the epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors (TKIs) is one of the major precision medicine treatment options for lung adenocarcinoma. Due to common development of drug resistance to first- and second-generation TKIs, third-generation inhibitors, including osimertinib and rociletinib, have been developed. A model of EGFR-driven lung cancer and a method to develop tumors of distinct epigenetic states through 3D organotypic cultures are described here. It is discovered that activation of the EGFR T790M/L858R mutation in lung epithelial cells can drive lung cancers with alveolar or bronchiolar features, which can originate from alveolar type 2 (AT2) cells or bronchioalveolar stem cells, but not basal cells or club cells of the trachea. It is also demonstrated that these clones are able to retain their epigenetic differences through passaging orthotopically in mice and crucially that they have distinct drug vulnerabilities. This work serves as a blueprint for exploring how epigenetics can be used to stratify patients for precision medicine decisions

QTL Mapping of Six Spike and Stem Traits in Hybrid Population of Agropyron Gaertn. in Multiple Environments

Most Agropyron Gaertn. species are excellent sources of forage. The derivative lines of wheat-Agropyron cristatum show elite agronomic traits, and some are valuable for wheat breeding. The species of Agropyron Gaertn. was mainly recognized by the spike morphology in traditional taxon. Six traits, including spike length (SL), ear stem length (ESL), the second internodes length (SIL), spikelet number per spike (SNS), floret number per spikelet (FNS), and grain number per spikelet (GNS), are vital to morphology studies and also influences the forage crop yield. To elucidate the genetic basis of spike and stem traits, a quantitative trait locus (QTL) analysis was conducted in a cross-pollinated (CP) hybrid population derived from a cross between two diverse parents, Agropyron mongolicum Keng Z2098 and A. cristatum (L.) Gaertn. Z1842, evaluated across three ecotopes (Langfang, Changli, and Guyuan of Hebei, China) over 3 years (from 2014 to 2016). Construction of a high-density linkage map was based on 1,023 single-nucleotide polymorphism (SNP) markers, covering 907.8 cM of the whole Agropyron genome. A total of 306 QTLs with single QTL in different environments explaining 0.07–33.21% of the phenotypic variation were detected for study traits. Seven major-effect QTLs were identified, including one for ESL on chromosome 3, one for SIL on chromosome 5, three for SL (two on chromosome 2 and one on chromosome 4), and two for SNS on chromosomes 3 and 7. Also, seven stable QTLs, including four for ESL, one for SL, one for GNS, and one for FNS, were mainly mapped on chromosomes 2, 3, 4, 5, and 7, respectively, elucidating 0.25–14.98% of the phenotypic variations. On the use of Agropyron CP hybrid population to identify QTL determining spike and stem traits for the first time, these QTLs for six traits would provide a theoretical reference for the molecular marker-assisted selection in the improvement of forage and cereal crop species