Machine Learning Methods for Autonomous Flame Detection in Videos

Fire detection has attracted increasing attention from the public because of the huge loss caused by fires every year. Compared with the traditional fire detection techniques based on smoke or heat sensors, the frameworks using machine learning methods in videos for fire detection have the advantages of higher efficiency and accuracy of detection, robustness to various environments, and lower cost of the systems. The uniqueness of these frameworks stems from the developed machine learning approaches for autonomous information extraction and fire detection in sequential video frames. A framework for flame detection is proposed based on the synergy of the Horn-Schunck optical flow estimation method, a probabilistic saliency analysis approach and a temporal wavelet analysis scheme. The estimated optical flows, together with the saliency analysis method, work effectively in selecting moving regions by well describing the dynamic property of flames, which contributes to accurate detection of flames. Additionally, the temporal wavelet transform based analysis increases the robustness of the framework and provides reliable results by discarding non-flame pixels according to their temporally changing patterns. Apart from the dynamic characteristic of flames, the property of colours is also of crucial importance in describing flames. However, the colours of flames usually vary significantly with different illumination or burning material, which results in a wide diversity. To well model the various colours, a novel flame colour model is proposed based on the Dirichlet process Gaussian mixture model. The distribution of flame colours is represented by a Gaussian mixture model, of which the number of mixture components is learned from the training data autonomously by setting a Dirichlet process as the prior. Compared with those methods which set the number of mixture components empirically, the developed model can access a more accurate estimation of the distribution of flame colours. The inference is successfully implemented by two methods, i.e., the Gibbs sampling and variational inference algorithms, to manage different quantities of training data. The colour model can be incorporated into the framework of flame detection and the results show that the colour model achieves a highly accurate estimation of the distribution of flame colours, which contributes to the good performance of the whole framework. All the proposed approaches are tested on real videos of various environments and proved to be capable of accurate flame detection

Multi-wavelength Stellar Polarimetry of the Filamentary Cloud IC5146: I. Dust Properties

We present optical and near-infrared stellar polarization observations toward the dark filamentary clouds associated with IC5146. The data allow us to investigate the dust properties (this paper) and the magnetic field structure (Paper II). A total of 2022 background stars were detected in $R_{c}$-, $i'$-, $H$-, and/or $K$-bands to $A_V \lesssim 25$ mag. The ratio of the polarization percentage at different wavelengths provides an estimate of $\lambda_{max}$, the wavelength of peak polarization, which is an indicator of the small-size cutoff of the grain size distribution. The grain size distribution seems to significantly change at $A_V \sim$ 3 mag, where both the average and dispersion of $P_{R_c}/P_{H}$ decrease. In addition, we found $\lambda_{max}$ $\sim$ 0.6-0.9 $\mu$m for $A_V>2.5$ mag, which is larger than the $\sim$ 0.55 $\mu$m in the general ISM, suggesting that grain growth has already started in low $A_V$ regions. Our data also reveal that polarization efficiency (PE $\equiv P_{\lambda}/A_V$) decreases with $A_V$ as a power-law in $R_c$-, $i'$-, and $K$-bands with indices of -0.71$\pm$0.10, -1.23$\pm$0.10 and -0.53$\pm$0.09. However, $H$-band data show a power index change; the PE varies with $A_V$ steeply (index of -0.95$\pm$0.30) when $A_V < 2.88\pm0.67$ mag but softly (index of -0.25$\pm$0.06) for greater $A_V$ values. The soft decay of PE in high $A_V$ regions is consistent with the Radiative Aligned Torque model, suggesting that our data trace the magnetic field to $A_V \sim 20$ mag. Furthermore, the breakpoint found in $H$-band is similar to the $A_V$ where we found the $P_{R_c}/P_{H}$ dispersion significantly decreased. Therefore, the flat PE-$A_V$ in high $A_V$ regions implies that the power index changes result from additional grain growth.Comment: 31 pages, 17 figures, and 3 tables; accepted for publication in Ap

BPTF promotes tumor growth and predicts poor prognosis in lung adenocarcinomas.

BPTF, a subunit of NURF, is well known to be involved in the development of eukaryotic cell, but little is known about its roles in cancers, especially in non-small-cell lung cancer (NSCLC). Here we showed that BPTF was specifically overexpressed in NSCLC cell lines and lung adenocarcinoma tissues. Knockdown of BPTF by siRNA significantly inhibited cell proliferation, induced cell apoptosis and arrested cell cycle progress from G1 to S phase. We also found that BPTF knockdown downregulated the expression of the phosphorylated Erk1/2, PI3K and Akt proteins and induced the cleavage of caspase-8, caspase-7 and PARP proteins, thereby inhibiting the MAPK and PI3K/AKT signaling and activating apoptotic pathway. BPTF knockdown by siRNA also upregulated the cell cycle inhibitors such as p21 and p18 but inhibited the expression of cyclin D, phospho-Rb and phospho-cdc2 in lung cancer cells. Moreover, BPTF knockdown by its specific shRNA inhibited lung cancer growth in vivo in the xenografts of A549 cells accompanied by the suppression of VEGF, p-Erk and p-Akt expression. Immunohistochemical assay for tumor tissue microarrays of lung tumor tissues showed that BPTF overexpression predicted a poor prognosis in the patients with lung adenocarcinomas. Therefore, our data indicate that BPTF plays an essential role in cell growth and survival by targeting multiply signaling pathways in human lung cancers

GmWRKY16 Enhances Drought and Salt Tolerance Through an ABA-Mediated Pathway in Arabidopsis thaliana

The WRKY transcription factors (TFs) are one of the largest families of TFs in plants and play multiple roles in plant development and stress response. In the present study, GmWRKY16 encoding a WRKY transcription factor in soybean was functionally characterized in Arabidopsis. GmWRKY16 is a nuclear protein that contains a highly conserved WRKY domain and a C2H2 zinc-finger structure, and has the characteristics of transcriptional activation ability, presenting a constitutive expression pattern with relative expression levels of over fourfold in the old leaves, flowers, seeds and roots of soybean. The results of quantitative real time polymerase chain reaction (qRT-PCR) showed that GmWRKY16 could be induced by salt, alkali, ABA, drought and PEG-6000. As compared with the control, overexpression of GmWRKY16 in Arabidopsis increased the seed germination rate and root growth of seedlings in transgenic lines under higher concentrations of mannitol, NaCl and ABA. In the meantime, GmWRKY16 transgenic lines showed over 75% survival rate after rehydration and enhanced Arabidopsis tolerance to salt and drought with higher proline and lower MDA accumulation, less water loss of the detached leaves, and accumulated more endogenous ABA than the control under stress conditions. Further studies showed that AtWRKY8, KIN1, and RD29A were induced in GmWRKY16 transgenic plants under NaCl treatment. The expressions of the ABA biosynthesis gene (NCED3), signaling genes (ABI1, ABI2, ABI4, and ABI5), responsive genes (RD29A, COR15A, COR15B, and RD22) and stress-related marker genes (KIN1, LEA14, LEA76, and CER3) were regulated in transgenic lines under drought stress. In summary, these results suggest that GmWRKY16 as a WRKY TF may promote tolerance to drought and salt stresses through an ABA-mediated pathway

The genetic variants at the HLA-DRB1 gene are associated with primary IgA nephropathy in Han Chinese

BACKGROUND: Immunoglobulin A nephropathy (IgAN), an immune-complex-mediated glomerulonephritis defined immunohistologically by the presence of glomerular IgA deposits, is the most common primary glomerular disease worldwide and a significant cause of end-stage renal disease. Familial clustering of patients with IgAN suggests a genetic predisposition. METHODS: In this study, 192 patients with IgAN and 192 normal controls in the Sichuan cohort and 935 patients with IgAN and 2,103 normal controls in the Beijing cohort were investigated. HLA-DRB1*01–DRB1*10 specificities were genotyped by the PCR–SSP technique in both cohorts. Based on the HLA-DRB1*04-positive results, the subtypes of HLA-DRB1*04 were analyzed using sequencing-based typing (SBT) in 291 IgAN cases and 420 matched controls. RESULTS: The frequency of HLA-DRB1*04 in the IgAN group was significantly higher than that in the control group (0.129 vs. 0.092, P = 8.29 × 10(-5), odds ratio (OR) =1.381, 95% confidence interval (CI) 1.178–1.619). Other alleles at the HLA-DRB1 locus were observed with no significant differences between the case and control groups. The dominant alleles of the HLA-DRB1*04 subtypes were DRB1*0405 in both cohorts. The frequencies of HLA-DRB1*0405 and 0403 were significantly increased in the patients compared to healthy subjects. CONCLUSION: HLA-DRB1*04 was significantly associated with primary IgAN in Chinese population. This result implies that HLA-DRB1 gene plays a major role in primary IgAN

Ku80 cooperates with CBP to promote COX-2 expression and tumor growth.

Cyclooxygenase-2 (COX-2) plays an important role in lung cancer development and progression. Using streptavidin-agarose pulldown and proteomics assay, we identified and validated Ku80, a dimer of Ku participating in the repair of broken DNA double strands, as a new binding protein of the COX-2 gene promoter. Overexpression of Ku80 up-regulated COX-2 promoter activation and COX-2 expression in lung cancer cells. Silencing of Ku80 by siRNA down-regulated COX-2 expression and inhibited tumor cell growth in vitro and in a xenograft mouse model. Ku80 knockdown suppressed phosphorylation of ERK, resulting in an inactivation of the MAPK pathway. Moreover, CBP, a transcription co-activator, interacted with and acetylated Ku80 to co-regulate the activation of COX-2 promoter. Overexpression of CBP increased Ku80 acetylation, thereby promoting COX-2 expression and cell growth. Suppression of CBP by a CBP-specific inhibitor or siRNA inhibited COX-2 expression as well as tumor cell growth. Tissue microarray immunohistochemical analysis of lung adenocarcinomas revealed a strong positive correlation between levels of Ku80 and COX-2 and clinicopathologic variables. Overexpression of Ku80 was associated with poor prognosis in patients with lung cancers. We conclude that Ku80 promotes COX-2 expression and tumor growth and is a potential therapeutic target in lung cancer

Automated Movement Detection with Dirichlet Process Mixture Models and Electromyography

Numerous sleep disorders are characterised by movement during sleep, these include rapid-eye movement sleep behaviour disorder (RBD) and periodic limb movement disorder. The process of diagnosing movement related sleep disorders requires laborious and time-consuming visual analysis of sleep recordings. This process involves sleep clinicians visually inspecting electromyogram (EMG) signals to identify abnormal movements. The distribution of characteristics that represent movement can be diverse and varied, ranging from brief moments of tensing to violent outbursts. This study proposes a framework for automated limb-movement detection by fusing data from two EMG sensors (from the left and right limb) through a Dirichlet process mixture model. Several features are extracted from 10 second mini-epochs, where each mini-epoch has been classified as 'leg-movement' or 'no leg-movement' based on annotations of movement from sleep clinicians. The distributions of the features from each category can be estimated accurately using Gaussian mixture models with the Dirichlet process as a prior. The available dataset includes 36 participants that have all been diagnosed with RBD. The performance of this framework was evaluated by a 10-fold cross validation scheme (participant independent). The study was compared to a random forest model and outperformed it with a mean accuracy, sensitivity, and specificity of 94\%, 48\%, and 95\%, respectively. These results demonstrate the ability of this framework to automate the detection of limb movement for the potential application of assisting clinical diagnosis and decision-making

Docking rings in a solid: reversible assembling of pseudorotaxanes inside a zirconium metal–organic framework

An unprecedented zirconium metal–organic framework featuring a T-shaped benzimidazole strut was constructed and employed as a sponge-like material for selective absorption of macrocyclic guests. The neutral benzimidazole domain of the as-synthesized framework can be readily protonated and fully converted to benzimidazolium. Mechanical threading of [24]crown-8 ether wheels onto recognition sites to form pseudorotaxanes was evidenced by solution nuclear magnetic resonance, solid-state fluorescence, and infrared spectroscopy. Selective absorption of [24]crown-8 ether rather than its dibenzo counterpart was also observed. Further study reveals that this binding process is reversible and acid–base switchable. The success of docking macrocyclic guests in crystals via host–guest interactions provides an alternative route to complex functional materials with interpenetrated structures