Sequential Frame-Interpolation and DCT-based Video Compression Framework

Video data is ubiquitous; capturing, transferring, and storing even compressed video data is challenging because it requires substantial resources. With the large amount of video traffic being transmitted on the internet, any improvement in compressing such data, even small, can drastically impact resource consumption. In this paper, we present a hybrid video compression framework that unites the advantages of both DCT-based and interpolation-based video compression methods in a single framework. We show that our work can deliver the same visual quality or, in some cases, improve visual quality while reducing the bandwidth by 10--20%

Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma.

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 (HK2) and Enolase 1 (ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an approach for identifying novel potential therapeutic targets in human HCC with mutated p53. These approaches can take advantage of the massive next-generation sequencing (NGS) data generated worldwide and make more out of it by exploring new potential therapeutic targets

Diamond machining of freeform-patterned surfaces on precision rollers

Rapid development of freeform surfaces faces the challenges of not only higher form accuracy and smoother surface finishing, but also high machining efficiency and lower manufacturing cost. Combining diamond turning and roll-to-roll embossing technologies is a promising solution to fulfil these requirements. This paper presents a generic method to design and machine freeform surfaces on precision rollers. The freeform surface designed on the flat substrate is first transferred onto the cylindrical roller surface. The freeform-patterned roller surface is then diamond turned using the toolpath generated by a purposely developed toolpath generator. With the proposed method, the complex freeform surfaces designed on flat substrate can be transferred to and precisely machined on the cylindrical roller surfaces. A cutting experiment has been conducted to demonstrate the capability of the proposed method. In the experiment, a sinusoidal surface was designed and diamond turned on a precision roller. The results demonstrate that the proposed method is accurate and effective. The proposed method provides guidance for the design and precision manufacturing of freeform-patterned surfaces on precision rollers

The Effect of Lavender Aromatherapy on Autonomic Nervous System in Midlife Women with Insomnia

The objective of this study is to determine the effects of 12 weeks of lavender aromatherapy on self-reported sleep and heart rate variability (HRV) in the midlife women with insomnia. Sixty-seven women aged 45–55 years, with a CPSQI (Chinese version of Pittsburgh Sleep Quality Index) greater than 5, were recruited from communities in Taiwan. The experimental group (n = 34) received lavender inhalation, 20 min each time, twice per week, for 12 weeks, with a total of 24 times. The control group (n = 33) received health education program for sleep hygiene with no intervention. The study of HRV was analyzed by time- and frequency-domain methods. Significant decrease in mean heart rate (HR) and increases in SDNN (standard deviation of the normal-to-normal (NN) intervals), RMSDD (square root of the mean squared differences of successive NN intervals), and HF (high frequency) of spectral powers analysis after lavender inhalation were observed in the 4th and 12th weeks of aromatherapy. The total CPSQI score of study subjects was significantly decreased in the experimental group (P < 0.001), while no significant difference was observed across the same time period (P = 0.776) in the control group. Resting HR and HRV measurements at baseline 1 month and 3 months after allocation showed no significant difference between the experimental and control groups. The study demonstrated that lavender inhalation may have a persistent short-term effect on HRV with an increase in parasympathetic modulation. Women receiving aromatherapy experienced a significant improvement in sleep quality after intervention. However, lavender aromatherapy does not appear to confer benefit on HRV in the long-term followup

Simulation of High-Altitude Meteorological Data Used to Environment Impact Assessment by MM5 Model

AbstractThe high-altitude meteorological data on the 27km resolution, with 149×149 grids in the whole country, are generated by application of mesoscale numerical model MM5. The raw data used by the model include the United States USGS data, including terrain, land use, the composition of the vegetation data, and so on. Original meteorological data are the reanalysis data of the US National Centers for Environmental Prediction of the NCEP/NCAR. According to the need of environment impact assessment (EIA), the high-altitude meteorological data contain 21 layers below 550 hPa height. The data mainly include atmospheric pressure, altitude, dry bulb temperature, dew point temperature, wind direction, wind speed, relative humidity. High-altitude meteorological data generated in this study, can be directly applied to the EIA prediction model and serve for EIA

Optimization-Based Motion Planning for Autonomous Parking Considering Dynamic Obstacle: A Hierarchical Framework

We present a hierarchical framework based on graph search and model predictive control (MPC) for electric autonomous vehicle (EAV) parking maneuvers in a tight environment. At high-level, only static obstacles are considered, and the scenario-based hybrid A* (SHA*), which is faster than the traditional hybrid A*, is designed to provide an initial guess (also known as a global path) for the parking task. To extract the velocity and acceleration profile from an initial guess, an optimal control problem (OCP) is built. At the low level, an NMPC-based strategy is used to avoid dynamic obstacles (also known as local planning). The efficacy of SHA* is evaluated through 148 different simulation schemes and the proposed hierarchical parking framework is demonstrated through a real-time parallel parking simulation

Magnetic oscillations driven by the spin Hall effect in 3-terminal magnetic tunnel junction devices

We show that direct current in a tantalum microstrip can induce steady-state magnetic oscillations in an adjacent nanomagnet through spin torque from the spin Hall effect (SHE). The oscillations are detected electrically via a magnetic tunnel junction (MTJ) contacting the nanomagnet. The oscillation frequency can be controlled using the MTJ bias to tune the magnetic anisotropy. In this 3-terminal device the SHE torque and the MTJ bias therefore provide independent controls of the oscillation amplitude and frequency, enabling new approaches for developing tunable spin torque nano-oscillators

AdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition

Raw videos have been proven to own considerable feature redundancy where in many cases only a portion of frames can already meet the requirements for accurate recognition. In this paper, we are interested in whether such redundancy can be effectively leveraged to facilitate efficient inference in continuous sign language recognition (CSLR). We propose a novel adaptive model (AdaBrowse) to dynamically select a most informative subsequence from input video sequences by modelling this problem as a sequential decision task. In specific, we first utilize a lightweight network to quickly scan input videos to extract coarse features. Then these features are fed into a policy network to intelligently select a subsequence to process. The corresponding subsequence is finally inferred by a normal CSLR model for sentence prediction. As only a portion of frames are processed in this procedure, the total computations can be considerably saved. Besides temporal redundancy, we are also interested in whether the inherent spatial redundancy can be seamlessly integrated together to achieve further efficiency, i.e., dynamically selecting a lowest input resolution for each sample, whose model is referred to as AdaBrowse+. Extensive experimental results on four large-scale CSLR datasets, i.e., PHOENIX14, PHOENIX14-T, CSL-Daily and CSL, demonstrate the effectiveness of AdaBrowse and AdaBrowse+ by achieving comparable accuracy with state-of-the-art methods with 1.44$\times$ throughput and 2.12$\times$ fewer FLOPs. Comparisons with other commonly-used 2D CNNs and adaptive efficient methods verify the effectiveness of AdaBrowse. Code is available at \url{https://github.com/hulianyuyy/AdaBrowse}.Comment: ACMMM202