Studies on the Property and Application of Starch Sugar Ester Dodecenylsuccinic

In this study, we have prepared starch and Brown algae sugar ester dodecenylsuccinic, and by using infrared rays, scanning electron microscopy (SEM), and differential scanning calorimetry (DSC), we studied the structures and properties of the starch and Brown algae sugar ester dodecenylsuccinic. In addition, we studied the possibility of using this modified starch and Brown algae as emulsifier that can be used in ice cream

Investigations on the second-order transient gap resonance induced by focused wave groups

Two or more marine structures deployed side by side may encounter strong water-body resonances within narrow gaps between them. It may cause significant wave loads on structures and the green water phenomenon on the deck. In this article, the transient fluid motion within a narrow gap formed by two fixed boxes suffered from incident focused wave groups is investigated using a two-dimensional viscous flow numerical wave flume. The focused wave groups adopted have the spectral peak frequency equal to half the fluid resonant frequency inside the gap. The wave fields both inside the gap and around the two-box system, the response/damping time of the transient wave surfaces inside the gap, the maximum wave forces and the ratios of the 2nd-order to the corresponding 1st-order wave surfaces/forces are investigated. It is revealed that the most dangerous place to green water is always the front edge of the two-box system. The damping time of the 2nd-order wave surface is significantly larger than that of the 1st-order one. As the incident wave amplitude rises, the ratios of the 2nd-order to the first-order wave surfaces/forces becomes increases gradually and can even exceed 100% for the wave surface, the horizontal wave force and the moment.</p

Scene Graph Lossless Compression with Adaptive Prediction for Objects and Relations

The scene graph is a new data structure describing objects and their pairwise relationship within image scenes. As the size of scene graph in vision applications grows, how to losslessly and efficiently store such data on disks or transmit over the network becomes an inevitable problem. However, the compression of scene graph is seldom studied before because of the complicated data structures and distributions. Existing solutions usually involve general-purpose compressors or graph structure compression methods, which is weak at reducing redundancy for scene graph data. This paper introduces a new lossless compression framework with adaptive predictors for joint compression of objects and relations in scene graph data. The proposed framework consists of a unified prior extractor and specialized element predictors to adapt for different data elements. Furthermore, to exploit the context information within and between graph elements, Graph Context Convolution is proposed to support different graph context modeling schemes for different graph elements. Finally, a learned distribution model is devised to predict numerical data under complicated conditional constraints. Experiments conducted on labeled or generated scene graphs proves the effectiveness of the proposed framework in scene graph lossless compression task

LT4REC:A Lottery Ticket Hypothesis Based Multi-task Practice for Video Recommendation System

Click-through rate prediction (CTR) and post-click conversion rate prediction (CVR) play key roles across all industrial ranking systems, such as recommendation systems, online advertising, and search engines. Different from the extensive research on CTR, there is much less research on CVR estimation, whose main challenge is extreme data sparsity with one or two orders of magnitude reduction in the number of samples than CTR. People try to solve this problem with the paradigm of multi-task learning with the sufficient samples of CTR, but the typical hard sharing method can't effectively solve this problem, because it is difficult to analyze which parts of network components can be shared and which parts are in conflict, i.e., there is a large inaccuracy with artificially designed neurons sharing. In this paper, we model CVR in a brand-new method by adopting the lottery-ticket-hypothesis-based sparse sharing multi-task learning, which can automatically and flexibly learn which neuron weights to be shared without artificial experience. Experiments on the dataset gathered from traffic logs of Tencent video's recommendation system demonstrate that sparse sharing in the CVR model significantly outperforms competitive methods. Due to the nature of weight sparsity in sparse sharing, it can also significantly reduce computational complexity and memory usage which are very important in the industrial recommendation system.Comment: 6 pages,4 figure

Modifiable pathways for longevity:A Mendelian randomization analysis

Background: A variety of factors, including diet and lifestyle, obesity, physiology, metabolism, hormone levels, psychology, and inflammation, have been associated with longevity. The specific influences of these factors, however, are poorly understood. Here, possible causal relationships between putative modifiable risk factors and longevity are investigated. Methods: A random effects model was used to investigate the association between 25 putative risk factors and longevity. The study population comprised 11,262 long-lived subjects (≥90 years old, including 3484 individuals ≥99 years old) and 25,483 controls (≤60 years old), all of European ancestry. The data were obtained from the UK Biobank database. Genetic variations were used as instruments in two-sample Mendelian randomization to reduce bias. The odds ratios for genetically predicted SD unit increases were calculated for each putative risk factor. Egger regression was used to determine possible violations of the Mendelian randomization model. Results: Thirteen potential risk factors showed significant associations with longevity (≥90th) after correction for multiple testing. These included smoking initiation (OR:1.606; CI: 1.112–2.319) and educational attainment (OR:2.538, CI: 1.685–3.823) in the diet and lifestyle category, systolic and diastolic blood pressure (OR per SD increase: 0.518; CI: 0.438–0.614 for SBP and 0.620; CI 0.514–0.748 for DBP) and venous thromboembolism (OR:0.002; CI: 0.000–0.047) in the physiology category, obesity (OR: 0.874; CI: 0.796–0.960), BMI (OR per 1-SD increase: 0.691; CI: 0.628–0.760), and body size at age 10 (OR per 1-SD increase:0.728; CI: 0.595–0.890) in the obesity category, type 2 diabetes (T2D) (OR:0.854; CI: 0.816–0.894), LDL cholesterol (OR per 1-SD increase: 0.743; CI: 0.668–0.826), HDL cholesterol (OR per 1-SD increase: 1.243; CI: 1.112–1.390), total cholesterol (TC) (OR per 1-SD increase: 0.786; CI: 0.702–0.881), and triglycerides (TG) (OR per 1-SD increase: 0.865; CI: 0.749–0.998) in the metabolism category. Both longevity (≥90th) and super-longevity (≥99th), smoking initiation, body size at age 10, BMI, obesity, DBP, SBP, T2D, HDL, LDL, and TC were consistently associated with outcomes. The examination of underlying pathways found that BMI indirectly affected longevity through three pathways, namely, SBP, plasma lipids (HDL/TC/LDL), and T2D (p &lt; 0.05). Conclusion: BMI was found to significantly affect longevity through SBP, plasma lipid (HDL/TC/LDL), and T2D. Future strategies should focus on modifying BMI to improve health and longevity.</p

Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events

Along with the development of modern smart cities, human-centric video analysis has been encountering the challenge of analyzing diverse and complex events in real scenes. A complex event relates to dense crowds, anomalous, or collective behaviors. However, limited by the scale of existing video datasets, few human analysis approaches have reported their performance on such complex events. To this end, we present a new large-scale dataset, named Human-in-Events or HiEve (Human-centric video analysis in complex Events), for the understanding of human motions, poses, and actions in a variety of realistic events, especially in crowd and complex events. It contains a record number of poses (>1M), the largest number of action instances (>56k) under complex events, as well as one of the largest numbers of trajectories lasting for longer time (with an average trajectory length of >480 frames). Based on this dataset, we present an enhanced pose estimation baseline by utilizing the potential of action information to guide the learning of more powerful 2D pose features. We demonstrate that the proposed method is able to boost the performance of existing pose estimation pipelines on our HiEve dataset. Furthermore, we conduct extensive experiments to benchmark recent video analysis approaches together with our baseline methods, demonstrating that HiEve is a challenging dataset for human-centric video analysis. We expect that the dataset will advance the development of cutting-edge techniques in human-centric analysis and the understanding of complex events. The dataset is available at http://humaninevents.orgComment: Dataset for Large-scale Human-centric Video Analysis in Complex Events (http://humaninevents.org

Doped Titanium Dioxide Films Prepared by Pulsed Laser Deposition Method

TiO2 was intensively researched especially for photocatalystic applications. The nitrogen-doped TiO2 films prepared by pulsed laser deposition (PLD) method were reviewed, and some recent new experimental results were also presented in this paper. A new optical transmission method for evaluating the photocatalystic activity was presented. The main results are (1) PLD method is versatile for preparing oxide material or complex component films with excellent controllability and high reproducibility. (2) Anatase nitrogen-doped TiO2 films were prepared at room temperature, 200°C, and 400°C by PLD method using novel ceramic target of mixture of TiN and TiO2. UV/Vis spectra, AFM, Raman spectra, and photocatalystic activity for decomposition of methyl orange (MO) tests showed that visible light response was improved at higher temperature. (3) The automatic, continuous optical transmission autorecorder method is suitable for detecting the photodecomposition dynamic process of organic compound

Use acupuncture to relieve perimenopausal syndrome: study protocol of a randomized controlled trial

Law Number 11 / 2008 on Information and Electronic Transaction (UU ITE) is the regulation concerning on criminal law in addition to the Criminal Code (KUHP). UU ITE is commonly regarded additional regulation of the Criminal Code as a special law (lex specialis) in which Penal Code is deemed as lex generalis. It is based on the principle of lex specialis derogate legi generalis. This article uses legal research to review the decision of District Court in Bandung Number 1033/PID.B/2014/PN.BDG where it comprises legislation and cases. It concludes that the judge is not frugal in applying the principle lex specialis derogat legi generalis in the consideration. This is associated with the indictment of public prosecutor which only prejudges with article 303 paragraph (1) to 2. In contrast, the indictment which does not meet the requirement of a careful, clear, and complete description asserts to become void by law. Keywords: Online Gambling, Criminal Principle, Indictmen

Applications of Catalytic Hairpin Assembly Reaction in Biosensing.

Nucleic acids are considered as perfect programmable materials for cascade signal amplification and not merely as genetic information carriers. Among them, catalytic hairpin assembly (CHA), an enzyme-free, high-efficiency, and isothermal amplification method, is a typical example. A typical CHA reaction is initiated by single-stranded analytes, and substrate hairpins are successively opened, resulting in thermodynamically stable duplexes. CHA circuits, which were first proposed in 2008, present dozens of systems today. Through in-depth research on mechanisms, the CHA circuits have been continuously enriched with diverse reaction systems and improved analytical performance. After a short time, the CHA reaction can realize exponential amplification under isothermal conditions. Under certain conditions, the CHA reaction can even achieve 600 000-fold signal amplification. Owing to its promising versatility, CHA is able to be applied for analysis of various markers in vitro and in living cells. Also, CHA is integrated with nanomaterials and other molecular biotechnologies to produce diverse readouts. Herein, the varied CHA mechanisms, hairpin designs, and reaction conditions are introduced in detail. Additionally, biosensors based on CHA are presented. Finally, challenges and the outlook of CHA development are considered