Long Short-Term Memory Spatial Transformer Network

Spatial transformer network has been used in a layered form in conjunction with a convolutional network to enable the model to transform data spatially. In this paper, we propose a combined spatial transformer network (STN) and a Long Short-Term Memory network (LSTM) to classify digits in sequences formed by MINST elements. This LSTM-STN model has a top-down attention mechanism profit from LSTM layer, so that the STN layer can perform short-term independent elements for the statement in the process of spatial transformation, thus avoiding the distortion that may be caused when the entire sequence is spatially transformed. It also avoids the influence of this distortion on the subsequent classification process using convolutional neural networks and achieves a single digit error of 1.6\% compared with 2.2\% of Convolutional Neural Network with STN layer

Ge-Photodetectors for Si-Based Optoelectronic Integration

High speed photodetectors are a key building block, which allow a large wavelength range of detection from 850 nm to telecommunication standards at optical fiber band passes of 1.3–1.55 μm. Such devices are key components in several applications such as local area networks, board to board, chip to chip and intrachip interconnects. Recent technological achievements in growth of high quality SiGe/Ge films on Si wafers have opened up the possibility of low cost Ge-based photodetectors for near infrared communication bands and high resolution spectral imaging with high quantum efficiencies. In this review article, the recent progress in the development and integration of Ge-photodetectors on Si-based photonics will be comprehensively reviewed, along with remaining technological issues to be overcome and future research trends

Some recent studies on hohlraum physics

Some of our recent studies on hohlraum physics are presented, mainly including simulation study on hohlraum physics experiments on SGIII prototype, the design of Au + U + Au sandwich hohlraum for ignition target, and an initial design of elliptical hohlraum and pertinent drive laser power in order to generate an ignition radiation profile

Therapeutic and Prognostic Implications of BRAF V600E in Pediatric Low-Grade Gliomas.

Purpose BRAF V600E is a potentially highly targetable mutation detected in a subset of pediatric low-grade gliomas (PLGGs). Its biologic and clinical effect within this diverse group of tumors remains unknown. Patients and Methods A combined clinical and genetic institutional study of patients with PLGGs with long-term follow-up was performed (N = 510). Clinical and treatment data of patients with BRAF V600E mutated PLGG (n = 99) were compared with a large international independent cohort of patients with BRAF V600E mutated-PLGG (n = 180). Results BRAF V600E mutation was detected in 69 of 405 patients (17%) with PLGG across a broad spectrum of histologies and sites, including midline locations, which are not often routinely biopsied in clinical practice. Patients with BRAF V600E PLGG exhibited poor outcomes after chemotherapy and radiation therapies that resulted in a 10-year progression-free survival of 27% (95% CI, 12.1% to 41.9%) and 60.2% (95% CI, 53.3% to 67.1%) for BRAF V600E and wild-type PLGG, respectively ( P \u3c .001). Additional multivariable clinical and molecular stratification revealed that the extent of resection and CDKN2A deletion contributed independently to poor outcome in BRAF V600E PLGG. A similar independent role for CDKN2A and resection on outcome were observed in the independent cohort. Quantitative imaging analysis revealed progressive disease and a lack of response to conventional chemotherapy in most patients with BRAF V600E PLGG. Conclusion BRAF V600E PLGG constitutes a distinct entity with poor prognosis when treated with current adjuvant therapy

Therapeutic and Prognostic Implications of BRAF V600E in Pediatric Low-Grade Gliomas

Purpose BRAF V600E is a potentially highly targetable mutation detected in a subset of pediatric low-grade gliomas (PLGGs). Its biologic and clinical effect within this diverse group of tumors remains unknown. Patients and Methods A combined clinical and genetic institutional study of patients with PLGGs with long-term follow-up was performed (N = 510). Clinical and treatment data of patients with BRAF V600E mutated PLGG (n = 99) were compared with a large international independent cohort of patients with BRAF V600E mutated-PLGG (n = 180). Results BRAF V600E mutation was detected in 69 of 405 patients (17%) with PLGG across a broad spectrum of histologies and sites, including midline locations, which are not often routinely biopsied in clinical practice. Patients with BRAF V600E PLGG exhibited poor outcomes after chemotherapy and radiation therapies that resulted in a 10-year progression-free survival of 27% (95% CI, 12.1% to 41.9%) and 60.2% (95% CI, 53.3% to 67.1%) for BRAF V600E and wild-type PLGG, respectively (P < .001). Additional multivariable clinical and molecular stratification revealed that the extent of resection and CDKN2A deletion contributed independently to poor outcome in BRAF V600E PLGG. A similar independent role for CDKN2A and resection on outcome were observed in the independent cohort. Quantitative imaging analysis revealed progressive disease and a lack of response to conventional chemotherapy in most patients with BRAF V600E PLGG. Conclusion BRAF V600E PLGG constitutes a distinct entity with poor prognosis when treated with current adjuvant therapy. (C) 2017 by American Society of Clinical Oncolog

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Anti-Blocking Mechanism of Flocking Drainage Pipes in Tunnels Based on Mathematical Modeling Theory

Crystalline pipe plugging in tunnel drainage systems is one of the causes of tunnel lining cracking and water leakage. Therefore, effective prevention of crystalline pipe blockage in tunnel drainage systems is very important to ensure the safety and stability of the lining structure during tunnel operation. Combined with the theories of fluid mechanics, structural mechanics and basic physics, the flocking and anti-blocking mechanism of drainage pipe was comprehensively analyzed by using the method of mathematical modeling, including: (1) the calculation expression of average velocity of the flocked section of a flocked drainage pipe v&nbsp;=&nbsp;Q/(C1&nbsp;−&nbsp;C2(r + r′)) and the calculation formula of flowing water pressure under the action of groundwater Fw&nbsp;= &nbsp;KAγQ2/(2g(C1 − C2(r + r′))2); (2) the flow velocity v0 in the flocked drainage pipe shall meet v2 &lt; 4gπrlτ1/γKA, crystals will be attached to the fluff and the crystals will maintain dynamic balance; (3) the flow velocity v0 in the flocked drainage pipe shall meet v2&nbsp;≥ 4gπrlτ1/γKA, crystals will not adhere to the fluff and the flocked drainage pipe will remain unobstructed. The research on the mechanism of preventing blockage of flocking drainage pipes fills the gap in research theory in this regard, contributes to the popularization and application of blocking prevention technology of flocking drainage pipes, reduces the maintenance cost during operation of tunnel drainage systems and ensures the safe and normal operation of tunnels

Unconventional locomotion of liquid metal droplets driven by magnetic fields

The locomotion of liquid metal droplets enables enormous potential for realizing various applications in microelectromechanical systems (MEMSs), biomimetics, and microfluidics. However, current techniques for actuating liquid metal droplets are either associated with intense electrochemical reactions or require modification of their physical properties by coating/mixing them with other materials. These methods either generate gas bubbles or compromise the stability and liquidity of the liquid metal. Here, we introduce an innovative method for controlling the locomotion of liquid metal droplets using Lorentz force induced by magnetic fields. Remarkably, utilizing a magnetic field to induce actuation avoids the generation of gas bubbles in comparison to the method of forming a surface tension gradient on the liquid metal using electrochemistry. In addition, the use of Lorentz force avoids the need of mixing liquid metals with ferromagnetic materials, which may compromise the liquidity of liquid metals. Most importantly, we discover that the existence of a slip layer for liquid metal droplets distinguishes their actuation behaviors from solid metallic spheres. We investigate the parameters affecting the actuation behavior of liquid metal droplets and explore the science behind its operation. We further conducted a series of proof-of-concept experiments to verify the controllability of our method for actuating liquid metal droplets. As such, we believe that the presented technique represents a significant advance in comparison to reported actuation methods for liquid metals, and possesses the potential to be readily adapted by other systems to advance the fields of MEMS actuation and soft robotics

Construction of Classifier Based on MPCA and QSA and Its Application on Classification of Pancreatic Diseases

A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are optimized with quantum simulated annealing algorithm (QSA). In order to verify the effectiveness of the proposed algorithm, the normal SVM method has been chosen as comparing algorithm. The experimental results show that the proposed method can effectively extract the eigenfeatures and improve the classification accuracy of pancreatic images