Incident Duration Modeling Using Flexible Parametric Hazard-Based Models

Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time

Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection

In this paper, we introduce and evaluate PROPEDEUTICA, a novel methodology and framework for efficient and effective real-time malware detection, leveraging the best of conventional machine learning (ML) and deep learning (DL) algorithms. In PROPEDEUTICA, all software processes in the system start execution subjected to a conventional ML detector for fast classification. If a piece of software receives a borderline classification, it is subjected to further analysis via more performance expensive and more accurate DL methods, via our newly proposed DL algorithm DEEPMALWARE. Further, we introduce delays to the execution of software subjected to deep learning analysis as a way to "buy time" for DL analysis and to rate-limit the impact of possible malware in the system. We evaluated PROPEDEUTICA with a set of 9,115 malware samples and 877 commonly used benign software samples from various categories for the Windows OS. Our results show that the false positive rate for conventional ML methods can reach 20%, and for modern DL methods it is usually below 6%. However, the classification time for DL can be 100X longer than conventional ML methods. PROPEDEUTICA improved the detection F1-score from 77.54% (conventional ML method) to 90.25%, and reduced the detection time by 54.86%. Further, the percentage of software subjected to DL analysis was approximately 40% on average. Further, the application of delays in software subjected to ML reduced the detection time by approximately 10%. Finally, we found and discussed a discrepancy between the detection accuracy offline (analysis after all traces are collected) and on-the-fly (analysis in tandem with trace collection). Our insights show that conventional ML and modern DL-based malware detectors in isolation cannot meet the needs of efficient and effective malware detection: high accuracy, low false positive rate, and short classification time.Comment: 17 pages, 7 figure

Structural analysis of a novel rabbit monoclonal antibody R53 targeting an epitope in HIV-1 gp120 C4 region critical for receptor and co-receptor binding

The fourth conserved region (C4) in the HIV-1 envelope glycoprotein (Env) gp120 is a structural element that is important for its function, as it binds to both the receptor CD4 and the co-receptor CCR5/CXCR4. It has long been known that this region is highly immunogenic and that it harbors B-cell as well as T-cell epitopes. It is the target of a number of antibodies in animal studies, which are called CD4-blockers. However, the mechanism by which the virus shields itself from such antibody responses is not known. Here, we determined the crystal structure of R53 in complex with its epitope peptide using a novel anti-C4 rabbit monoclonal antibody R53. Our data show that although the epitope of R53 covers a highly conserved sequence (433)AMYAPPI(439), it is in the gp120 trimer and in the CD4-bound conformation. Our results suggest a masking mechanism to explain how HIV-1 protects this critical region from the human immune system

Rabbit anti-HIV-1 monoclonal antibodies raised by immunization can mimic the antigen-binding modes of antibodies derived from HIV-1-infected humans

The rabbit is a commonly used animal model in studying antibody responses in HIV/AIDS vaccine development. However, no rabbit monoclonal antibodies (MAbs) have been developed previously to study the epitope-specific antibody responses against HIV-1 envelope (Env) glycoproteins, and little is known about how the rabbit immune system can mimic the human immune system in eliciting such antibodies. Here we present structural analyses of two rabbit MAbs, R56 and R20, against the third variable region (V3) of HIV-1 gp120. R56 recognizes the well-studied immunogenic region in the V3 crown, while R20 targets a less-studied region at the C terminus of V3. By comparison of the Fab/epitope complex structures of these two antibodies raised by immunization with that of the corresponding human antibodies derived from patients chronically infected with HIV-1, we found that rabbit antibodies can recognize immunogenic regions of gp120 and mimic the binding modes of human antibodies. This result can provide new insight into the use of the rabbit as an animal model in AIDS vaccine development

Targeting immune checkpoints in anti-neutrophil cytoplasmic antibodies associated vasculitis: the potential therapeutic targets in the future

Anti-neutrophil cytoplasmic autoantibodies (ANCA) associated vasculitis (AAV) is a necrotizing vasculitis mainly involving small blood vessels. It is demonstrated that T cells are important in the pathogenesis of AAV, including regulatory T cells (Treg) and helper T cells (Th), especially Th2, Th17, and follicular Th cells (Tfh). In addition, the exhaustion of T cells predicted the favorable prognosis of AAV. The immune checkpoints (ICs) consist of a group of co-stimulatory and co-inhibitory molecules expressed on the surface of T cells, which maintains a balance between the activation and exhaustion of T cells. CD28, inducible T-cell co-stimulator (ICOS), OX40, CD40L, glucocorticoid induced tumor necrosis factor receptor (GITR), and CD137 are the common co-stimulatory molecules, while the programmed cell death 1 (PD-1), cytotoxic T lymphocyte-associated molecule 4 (CTLA-4), T cell immunoglobulin (Ig) and mucin domain-containing protein 3 (TIM-3), B and T lymphocyte attenuator (BTLA), V-domain Ig suppressor of T cell activation (VISTA), T‐cell Ig and ITIM domain (TIGIT), CD200, and lymphocyte activation gene 3 (LAG-3) belong to co-inhibitory molecules. If this balance was disrupted and the activation of T cells was increased, autoimmune diseases (AIDs) might be induced. Even in the treatment of malignant tumors, activation of T cells by immune checkpoint inhibitors (ICIs) may result in AIDs known as rheumatic immune-related adverse events (Rh-irAEs), suggesting the importance of ICs in AIDs. In this review, we summarized the features of AAV induced by immunotherapy using ICIs in patients with malignant tumors, and then reviewed the biological characteristics of different ICs. Our aim was to explore potential targets in ICs for future treatment of AAV

Homozygous p.Ser267Phe in SLC10A1 is associated with a new type of hypercholanemia and implications for personalized medicine.

SLC10A1 codes for the sodium-taurocholate cotransporting polypeptide (NTCP), which is a hepatocellular transporter for bile acids (BAs) and the receptor for hepatitis B and D viruses. NTCP is also a target of multiple drugs. We aimed to evaluate the medical consequences of the loss of function mutation p.Ser267Phe in SLC10A1. We identified eight individuals with homozygous p.Ser267Phe mutation in SLC10A1 and followed up for 8-90 months. We compared their total serum BAs and 6 species of BAs with 170 wild-type and 107 heterozygous healthy individuals. We performed in-depth medical examinations and exome sequencing in the homozygous individuals. All homozygous individuals had persistent hypercholanemia (P = 5.8 × 10-29). Exome sequencing excluded the involvement of other BA metabolism-associated genes in the hypercholanemia. Although asymptomatic, all individuals had low vitamin D levels. Of six adults that were subjected to bone mineral density analysis, three presented with osteoporosis/osteopenia. Sex hormones and blood lipids were deviated in all subjects. Homozygosity of p.Ser267Phe in SLC10A1 is associated with asymptomatic hypercholanemia. Individuals with homozygous p.Ser267Phe in SLC10A1 are prone to vitamin D deficiency, deviated sex hormones and blood lipids. Surveillance of these parameters may also be needed in patients treated with drugs targeting NTCP.This project is supported by the National Natural Science Foundation of China (31471193, 81570539, 81370535, 91331204 and 31525014). S.X. acknowledges financial support from the Strategic Priority Research Program (XDB13040100) and Key Research Program of Frontier Sciences (QYZDJ-SSW-SYS009) of the Chinese Academy of Sciences (CAS)

High-efficiency in situ resonant inelastic x-ray scattering (iRIXS) endstation at the Advanced Light Source

An endstation with two high-efficiency soft x-ray spectrographs was developed at Beamline 8.0.1 of the Advanced Light Source, Lawrence Berkeley National Laboratory. The endstation is capable of performing soft x-ray absorption spectroscopy, emission spectroscopy, and, in particular, resonant inelastic soft x-ray scattering (RIXS). Two slit-less variable line-spacing grating spectrographsare installed at different detection geometries. The endstation covers the photon energy range from 80 to 1500 eV. For studying transition-metal oxides, the large detection energy window allows a simultaneous collection of x-ray emission spectra with energies ranging from the O K-edge to the Ni L-edge without moving any mechanical components. The record-high efficiency enables the recording of comprehensive two-dimensional RIXS maps with good statistics within a short acquisition time. By virtue of the large energy window and high throughput of the spectrographs, partial fluorescence yield and inverse partial fluorescence yield signals could be obtained for all transition metal L-edges including Mn. Moreover, the different geometries of these two spectrographs (parallel and perpendicular to the horizontal polarization of the beamline) provide contrasts in RIXS features with two different momentum transfers

A global view of porcine transcriptome in three tissues from a full-sib pair with extreme phenotypes in growth and fat deposition by paired-end RNA sequencing

<p>Abstract</p> <p>Background</p> <p>Elucidation of the pig transcriptome is essential for interpreting functional elements of the genome and understanding the genetic architecture of complex traits such as fat deposition, metabolism and growth.</p> <p>Results</p> <p>Here we used massive parallel high-throughput RNA sequencing to generate a high-resolution map of the porcine mRNA and miRNA transcriptome in liver, longissimus dorsi and abdominal fat from two full-sib F₂hybrid pigs with segregated phenotypes on growth, blood physiological and biochemical parameters, and fat deposition. We obtained 8,508,418-10,219,332 uniquely mapped reads that covered 78.0% of the current annotated transcripts and identified 48,045-122,931 novel transcript fragments, which constituted 17,085-29,499 novel transcriptional active regions in six tested samples. We found that about 18.8% of the annotated genes showed alternative splicing patterns, and alternative 3' splicing is the most common type of alternative splicing events in pigs. Cross-tissue comparison revealed that many transcriptional events are tissue-differential and related to important biological functions in their corresponding tissues. We also detected a total of 164 potential novel miRNAs, most of which were tissue-specifically identified. Integrated analysis of genome-wide association study and differential gene expression revealed interesting candidate genes for complex traits, such as <it>IGF2, CYP1A1, CKM </it>and <it>CES1 </it>for heart weight, hemoglobin, pork pH value and serum cholesterol, respectively.</p> <p>Conclusions</p> <p>This study provides a global view of the complexity of the pig transcriptome, and gives an extensive new knowledge about alternative splicing, gene boundaries and miRNAs in pigs. Integrated analysis of genome wide association study and differential gene expression allows us to find important candidate genes for porcine complex traits.</p

Efficient image restoration algorithms for near-circulant systems

The problem of image restoration has been extensively studied for its practical importance as well as its theoretical interest. Restoration problem arises in almost every branch of engineering and applied physics. The goal of image restoration is to recover the original scene from the degraded observations. It seeks to model the degradations, blur and noise, and apply an inverse procedure to obtain an approximation of the original scene. Due to the fact that image restoration requires a huge amount of computation and storage, techniques and algorithms that can improve the speed or quality are desirable. A great variety of fast restoration methods have been proposed. The most well known fast restoration algorithms involve the use of fast Fourier transforms (FFT's) to implement shift-invariant deblurring. However, in the face of unknown boundaries, shift-variant smoothing, and other conditions, FFT's cannot be used in a straightforward manner in the inversion process. A group of efficient image restoration algorithms for circulant or near-circulant systems are proposed in this dissertation that overcome some of these limitations in the direct application of fast transforms. We assume that the system is a circulant or near-circulant system so that the convolution property of the FFT can be used. The regularization of the least-squares criterion is an effective approach in image restoration to reduce noise amplification. To avoid the smoothing of edges, edge-preserving regularization using a Gaussian Markov random field (GMRF) model is often used to allow realistic edge modeling and provide stable maximum a posteriori (MAP) solutions. However, this approach is computationally demanding because the introduction of a non-Gaussian image prior makes the restoration problem shift-variant. In this case, a direct solution using FFT's is not possible even when the blurring is shift-invariant. We consider a class of edge-preserving GMRF functions that are convex and have non-quadratic regions that impose less smoothing on edges. We propose a decomposition-enabled edge-preserving image restoration (DEEPIR) algorithm for maximizing the likelihood function. By decomposing the problem into two sub-problems with one shift-invariant and the other shift-variant, our algorithm exploits the sparsity of edges to define an FFT-based iteration that requires few iterations and is guaranteed to converge to the MAP estimate. The assumption of a circulant system does not always hold under certain circumstances. Many problems in signal and image processing require the solution of systems with a Toeplitz-block-Toeplitz (TBT) structure in which both the Toeplitz blocks and the block structure are banded. Some fast algorithms make use of the persymmetry (symmetry about the main antidiagonal) of the Toeplitz blocks, while the "bandedness" remains unexplored. Other algorithms exploit block bands but not banded blocks (or vice versa). We present a fast algorithm that exploits both the bandedness of the blocks and the block-bandedness of the block Toeplitz structure by extending the system to a circulant-block-circulant (CBC) system and solve for the original image by solving a larger system. Since a Toeplitz-block-Toeplitz system has a near-circulant structure, the computation involved in the extending and solving is comparatively small. Other published algorithms for TBT matrices typically involves O(M5) operations or O(6M3) operations with 'bandlimited assumption'. This method requires O( k2M3) operations for an M2 × M2 Toeplitz-block-Toeplitz matrix with bandwidth k without any assumptions about the system. The edge-preserving regularization method proposed for edge preserving also has applications in deblocking JPEG images where the block discrete cosine transform and quantization cause contouring and blocky artifacts in the compressed image. By integrating regularization into decompression of a compressed JPEG image, this algorithm significantly reduces blocky effects in the image. The proposed edge-preserving regularization scheme can be applied to reduce ringing artifacts on edges and smooth block boundaries in JPEG images. When the image restoration system is a TBT system instead of a CBC system, we can still make use of the FFT by extending and displacing the system to achieve a fast solution. In general, the proposed techniques in this dissertation improve the quality of restored images and improve the computational performance