•A slack based data envelopment analysis is performed to measure environmental efficiency of U.S. transportation sector.•Environmental efficiency, carbon efficiency, and potential carbon reduction ...are estimated for states.•The analysis proves a significant reduction of carbon emission and high excess in capital expenses, labor use.
Sustainable transportation in the U.S. is essential for long-term economic growth and mobility, and environmental preservation. Using a non-radial slack-based measurement data envelopment analysis (SBM-DEA) model and state-level data, this study assesses the environmental efficiency of the transportation sector in the U.S. from years 2004 to 2012. In addition to environmental efficiency, carbon efficiency and potential carbon reduction were estimated for the 50 U.S. states. The findings of this study reveal that U.S. transportation sector was environmentally inefficient; U.S. states had an average transportation environmental efficiency score below 0.64. Therefore the states could substantially reduce carbon emissions to improve the environmental efficiency of their transportation sectors.
In this article, we propose a fault detection and assessment technique for instrumentation and control cables based on time-frequency image classification using the faster region-based convolutional ...neural network (R-CNN). To train the faster R-CNN while compensating for multiple reflections, the reflected signal estimation is utilized, which divides the reflected signal into the signal propagation along the cable and the reflection from the impedance discontinuity point. Experimental results on two fault scenarios under the circumstance of multiple faults detection and branched networks demonstrate the effectiveness of the proposed method.
Internet of Things (IoT)-generated data are characterized by its continuous generation, large amount, and unstructured format. The existing relational database technologies are inadequate to handle ...such IoT-generated data due to the limited processing speed and the significant storage-expansion cost. Thus, big data processing technologies, which are normally based on distributed file systems, distributed database management, and parallel processing technologies, have arisen as a core technology to implement IoT-generated data repositories. In this paper, we propose a sensor-integrated radio frequency identification (RFID) data repository-implementation model using MongoDB, the most popular big data-savvy document-oriented database system now. First, we devise a data repository schema that can effectively integrate and store the heterogeneous IoT data sources, such as RFID, sensor, and GPS, by extending the event data types in electronic product code information services standard, a de facto standard for the information exchange services for RFID-based traceability. Second, we propose an effective shard key to maximize query speed and uniform data distribution over data servers. Last, through a series of experiments measuring query speed and the level of data distribution, we show that the proposed design strategy, which is based on horizontal data partitioning and a compound shard key, is effective and efficient for the IoT-generated RFID/sensor big data.
DNA methylation is an epigenetic modification that plays an important role in regulating gene expression and therefore a broad range of biological processes and diseases. DNA methylation is ...tissue-specific, dynamic, sequence-context-dependent and trans-generationally heritable, and these complex patterns of methylation highlight the significance of profiling DNA methylation to answer biological questions. In this review, we surveyed major methylation assays, along with comparisons and biological examples, to provide an overview of DNA methylation profiling techniques. The advances in microarray and sequencing technologies make genome-wide profiling possible at a single-nucleotide or even a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, genomic region coverage, and bioinformatics analysis, and selecting a feasible method requires knowledge of these methods. We first introduce the biological background of DNA methylation and its pattern in plants, animals and fungi. We present an overview of major experimental approaches to profiling genome-wide DNA methylation and hydroxymethylation and then extend to the single-cell methylome. To evaluate these methods, we outline their strengths and weaknesses and perform comparisons across the different platforms. Due to the increasing need to compute high-throughput epigenomic data, we interrogate the computational pipeline for bisulfite sequencing data and also discuss the concept of identifying differentially methylated regions (DMRs). This review summarizes the experimental and computational concepts for profiling genome-wide DNA methylation, followed by biological examples. Overall, this review provides researchers useful guidance for the selection of a profiling method suited to specific research questions.
Many studies have reported the effect of hypertension on microcirculation of the retina. Advance of optical coherence tomography angiography (OCTA) allows us more detailed observations of ...microcirculation of the retina. Therefore, we compared OCTA parameters between chronic hypertension (disease duration of at least 10 yrs; Group A, 45 eyes), relieved hypertensive retinopathy (grade IV HTNR < 1 yr prior; Group B, 40 eyes), and normal controls Group C (50 eyes) ≥ 50 yrs old and Group D (50 eyes) < 50 yrs old. A 3 × 3 mm macular scan was performed in each group by OCTA. In vessel density of 3 mm full, group A and B were significantly decreased compared to normal control group (Group A vs. C; 19.4 mm
vs. 20.1 mm
, Group B vs. D; 19.8 mm
vs. 21.8 mm
, all p < 0.05). In foveal avascular zone, group A and B were significantly increased compared to normal control group (Group A vs. C; 0.35 mm
vs. 0.30 mm
, Group B vs. D; 0.36 mm
vs. 0.29 mm
, all p < 0.05). OCTA is useful for examining retinal microcirculatory changes in hypertension and we confirmed that hypertension affects the OCTA parameters. Considering the effect of hypertension on the change of microvasculature, care is required in the interpretation of OCTA parameters in various ophthalmic condition.
Treatment strategies for autoimmune encephalitis Shin, Yong-Won; Lee, Soon-Tae; Park, Kyung-Il ...
Therapeutic Advances in Neurological Disorders,
01/2018, Letnik:
11
Book Review, Journal Article
Recenzirano
Odprti dostop
Autoimmune encephalitis is one of the most rapidly growing research topics in neurology. Along with discoveries of novel antibodies associated with the disease, clinical experience and outcomes with ...diverse immunotherapeutic agents in the treatment of autoimmune encephalitis are accumulating. Retrospective observations indicate that early aggressive treatment is associated with better functional outcomes and fewer relapses. Immune response to first-line immunotherapeutic agents (corticosteroids, intravenous immunoglobulin, plasma exchange, and immunoadsorption) is fair, but approximately half or more of patients are administered second-line immunotherapy (rituximab and cyclophosphamide). A small but significant proportion of patients are refractory to all first- and second-line therapies and require further treatment. Although several investigations have shown promising alternatives, the low absolute number of patients involved necessitates more evidence to establish further treatment strategies. In this review, the agents used for first- and second-line immunotherapy are discussed and recent attempts at finding new treatment options are introduced.
This paper introduces a novel convolution method, called generative convolution (GConv), which is simple yet effective for improving the generative adversarial network (GAN) performance. Unlike the ...standard convolution, GConv first selects useful kernels compatible with the given latent vector, and then linearly combines the selected kernels to make latent-specific kernels. Using the latent-specific kernels, the proposed method produces the latent-specific features which encourage the generator to produce high-quality images. This approach is simple but surprisingly effective. First, the GAN performance is significantly improved with a little additional hardware cost. Second, GConv can be employed to the existing state-of-the-art generators without modifying the network architecture. To reveal the superiority of GConv, this paper provides extensive experiments using various standard datasets including CIFAR-10, CIFAR-100, LSUN-Church, CelebA, and tiny-ImageNet. Quantitative evaluations prove that GConv significantly boosts the performances of the unconditional and conditional GANs in terms of Frechet inception distance (FID) and Inception score (IS). For example, the proposed method improves both FID and IS scores on the tiny-ImageNet dataset from 35.13 to 29.76 and 20.23 to 22.64, respectively.
FTO (fat mass and obesity associated) was identified as an obesity-susceptibility gene by several independent large-scale genome association studies. A cluster of SNPs (single nucleotide ...polymorphism) located in the first intron of FTO was found to be significantly associated with obesity-related traits, such as body mass index, hip circumference, and body weight. FTO encodes a protein with a novel C-terminal α-helical domain and an N-terminal double-strand β-helix domain which is conserved in Fe(II) and 2-oxoglutarate-dependent oxygenase family. In vitro, FTO protein can demethylate single-stranded DNA or RNA with a preference for 3-methylthymine or 3-methyluracil. Its physiological substrates and function, however, remain to be defined. Here we report the generation and analysis of mice carrying a conditional deletion allele of Fto. Our results demonstrate that Fto plays an essential role in postnatal growth. The mice lacking Fto completely display immediate postnatal growth retardation with shorter body length, lower body weight, and lower bone mineral density than control mice, but their body compositions are relatively normal. Consistent with the growth retardation, the Fto mutant mice have reduced serum levels of IGF-1. Moreover, despite the ubiquitous expression of Fto, its specific deletion in the nervous system results in similar phenotypes as the whole body deletion, indicating that Fto functions in the central nerve system to regulate postnatal growth.
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•Rapid degradation of organic pollutants via electrochemical oxidation on BDD anode.•Toxic chlorine oxyanions formed during electrolysis due to high current density.•Optimization of ...FCDI operation based on process performance and energy consumption.•Successful treatment of organic-rich high salinity water via hybrid ECO-FCDI system.
This study aimed to assess the application of an electrochemical oxidation (ECO) and flow-electrode capacitive deionization (FCDI) sequential hybrid process for the treatment of high-concentration ions, organic pollutants (i.e., humic acid, alginate, benzoic acid, phenol, and 4-chlorophenol), and marine algae. The ECO system led to the rapid generation of reactive chlorine species (RCS) via anodic oxidation of the boron-doped diamond (BDD) electrode under optimum current in the NaCl-based feed solution, which caused the reduction of total organic carbon (TOC) and the degradation of algae cells. However, the formation of undesirable by-products (i.e., toxic perchlorate) was triggered by direct electrolysis. Concurrently, the optimal operational conditions of the FCDI system were evaluated based on the monitoring of process performance according to various parameters (i.e., applied voltage, electrode mass loading, electrolyte concentration in the flow electrode, feed solution concentration, and adsorption/desorption phase operation). Finally, the superiority of the ECO–FCDI hybrid process was confirmed and clearly demonstrated via the effective decomposition of organic compounds and the complete removal of toxic perchlorate by-product together with the effect of deionization. To the best of our knowledge, this work is the first to develop and apply the ECO–FCDI integrated process for the removal of a broad spectrum of pollutants (including both organics and ions) and to attain successful desalination.
Intratumoral heterogeneity (ITH) refers to the presence of distinct tumor cell populations. It provides vital information for the clinical prognosis, drug responsiveness, and personalized treatment ...of cancer patients. As genomic ITH in various cancers affects the expression patterns of genes, the expression profile could be utilized for determining ITH level. Herein, we present a novel approach to directly detect high ITH defined as a larger number of subclones from the gene expression pattern through machine learning approaches. We examined associations between gene expression profile and ITH of 12 cancer types from The Cancer Genome Atlas (TCGA) database. Using stomach adenocarcinoma (STAD) showing high association, we evaluated the performance of our method in predicting ITH by employing three machine learning algorithms using gene expression profile data. We classified tumors into high and low heterogeneity groups using the learning model through the selection of LASSO feature. The result showed that support vector machines (SVMs) outperformed other algorithms (AUC = 0.84 in SVMs and 0.82 in Naïve Bayes) and we were able to improve predictive power by using both combined data from mutation and expression. Furthermore, we evaluated the prediction ability of each model using simulation data generated by mixing cell lines of the Cancer Cell Line Encyclopedia (CCLE), and obtained consistent results with using real dataset. Our approach could be utilized for discriminating tumors with heterogeneous cell populations to characterize ITH.
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