Variability and Spectral Behavior of Gamma-ray Flares of 3C 279

3C 279 showed enhanced flux variations in Fermi-LAT {\gamma}-ray observations from January to June 2018. We present a detailed Fermi-LAT analysis to investigate the variability and spectral behaviors of 3C 279 during the {\gamma}-ray flares in 2018. In this work, we analyzed the {\gamma}-ray spectra and found that the spectra in either the flaring or quiescent states do not show any clear breaks (or cutoffs). This indicates that the dissipation region is outside the broad-line region, and the energy dissipation may be due to the inverse Compton process of scattering the dust torus infrared photons, this result is also consistent with that in Tolamatti et al. An external inverse Compton scattering of dusty torus (DT) photons is employed to calculate the broadband spectral energy distribution (SED). This model was further supported by the fact that we found flare decay timescale was consistent with the cooling time of relativistic electrons through DT photons. During the SED modeling, a relatively harder spectrum for the electron energy distribution (EED) is found and suggests these electrons may not be accelerated by the shock that happened in the dissipation region. Besides, the magnetic reconnection is also ruled out due to a low magnetization ratio. Thus, we suggest an injection of higher-energy electrons from outside the blob and raising the flare.Comment: 12 pages, 6 figures, published in the Publications of the Astronomical Society of the Pacifi

Doubly High-Dimensional Contextual Bandits: An Interpretable Model for Joint Assortment-Pricing

Key challenges in running a retail business include how to select products to present to consumers (the assortment problem), and how to price products (the pricing problem) to maximize revenue or profit. Instead of considering these problems in isolation, we propose a joint approach to assortment-pricing based on contextual bandits. Our model is doubly high-dimensional, in that both context vectors and actions are allowed to take values in high-dimensional spaces. In order to circumvent the curse of dimensionality, we propose a simple yet flexible model that captures the interactions between covariates and actions via a (near) low-rank representation matrix. The resulting class of models is reasonably expressive while remaining interpretable through latent factors, and includes various structured linear bandit and pricing models as particular cases. We propose a computationally tractable procedure that combines an exploration/exploitation protocol with an efficient low-rank matrix estimator, and we prove bounds on its regret. Simulation results show that this method has lower regret than state-of-the-art methods applied to various standard bandit and pricing models. Real-world case studies on the assortment-pricing problem, from an industry-leading instant noodles company to an emerging beauty start-up, underscore the gains achievable using our method. In each case, we show at least three-fold gains in revenue or profit by our bandit method, as well as the interpretability of the latent factor models that are learned

Dual-view photoacoustic microscopy for quantitative cell nuclear imaging

Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging imaging modality for studying biological tissues. However, in conventional single-view OR-PAM, the lateral and axial resolutions—determined optically and acoustically, respectively—are highly anisotropic. In this Letter, we introduce dual-view OR-PAM to improve axial resolution, achieving three-dimensional (3D) resolution isotropy. We first use 0.5 μm polystyrene beads and carbon fibers to validate the resolution isotropy improvement. Imaging of mouse brain slices further demonstrates the improved resolution isotropy, revealing the 3D structure of cell nuclei in detail, which facilitates quantitative cell nuclear analysis

Dual-view photoacoustic microscopy for quantitative cell nuclear imaging

Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging imaging modality for studying biological tissues. However, in conventional single-view OR-PAM, the lateral and axial resolutions—determined optically and acoustically, respectively—are highly anisotropic. In this Letter, we introduce dual-view OR-PAM to improve axial resolution, achieving three-dimensional (3D) resolution isotropy. We first use 0.5 μm polystyrene beads and carbon fibers to validate the resolution isotropy improvement. Imaging of mouse brain slices further demonstrates the improved resolution isotropy, revealing the 3D structure of cell nuclei in detail, which facilitates quantitative cell nuclear analysis

Quantitative cell nuclear imaging by dual-view optical-resolution photoacoustic microscopy

An estimated ~250,000 new cases of both invasive and non-invasive breast cancer were diagnosed in US women almost every year. To reduce the local recurrence rate, the breast conserving surgery (BCS) is widely used as the initial therapy, which is to excise the tumor with a rim of normal surrounding tissue such that no cancer cells remain at the cut margin, Patients with positive margin commonly require a second surgical procedure to obtain clear margins. To this end, optical-resolution photoacoustic microscopy (OR-PAM) with ultraviolet (UV) laser illumination (OR-UV-PAM) has been developed for providing label-free, high-resolution, and histology like imaging of fixed, unprocessed breast tissue. To further improve the performance of OR-UV-PAM, here, we introduce dual-view UV-PAM (DV-UV-PAM) to significantly improve the axial resolution, achieving three-dimensional (3D) resolution isotropy. We first use 0.5 μm polystyrene beads and carbon fibers to validate the resolution isotropy improvement. Imaging of mouse brain slices further demonstrates the improved resolution isotropy, revealing the 3D structure of cell nuclei in detail, which facilitates quantitative cell nuclear analysis

Decision Tree Classification Model In Water Supply Network

With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future

Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China.

BACKGROUND: We aimed to establish a Medical-Insurance-System-based Cancer Surveillance System (MIS-CASS) in China and evaluate the completeness and timeliness of this system through reporting cancer incidence rates using claims data in two regions in northern and southern China. METHODS: We extracted claims data from medical insurance systems in Hua County of Henan Province, and Shantou City in Guangdong Province in China from Jan 1, 2012 to Jun 30, 2019. These two regions have been considered to be high risk regions for oesophageal cancer. We developed a rigorous procedure to establish the MIS-CASS, which includes data extraction, cleaning, processing, case ascertainment, privacy protection, etc. Text-based diagnosis in conjunction with ICD-10 codes were used to determine cancer diagnosis. FINDINGS: In 2018, the overall age-standardised (Segi population) incidence rates (ASR World) of cancer in Hua County and Shantou City were 167·39/100,000 and 159·78/100,000 respectively. In both of these areas, lung cancer and breast cancer were the most common cancers in males and females respectively. Hua County is a high-risk region for oesophageal cancer (ASR World: 25·95/100,000), whereas Shantou City is not a high-risk region for oesophageal cancer (ASR World: 11·43/100,000). However, Nanao island had the highest incidence of oesophageal cancer among all districts and counties in Shantou (ASR World: 36·39/100,000). The age-standardised male-to-female ratio for oesophageal cancer was lower in Hua County than in Shantou (1·69 vs. 4·02). A six-month lag time was needed to report these cancer incidences for the MIS-CASS. INTERPRETATION: MIS-CASS efficiently reflects cancer burden in real-time, and has the potential to provide insight for improvement of cancer surveillance in China. FUNDING: The National Key R&D Program of China (2016YFC0901404), the Digestive Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals (XXZ0204), the Sanming Project of Shenzhen (SZSM201612061), and the Shantou Science and Technology Bureau (190829105556145, 180918114960704)

Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women

Background The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years. Principal findings We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders. Conclusions In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype