Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks

Distributed transactions on high-overhead TCP/IP-based networks were conventionally considered to be prohibitively expensive and thus were avoided at all costs. To that end, the primary goal of almost any existing partitioning scheme is to minimize the number of cross-partition transactions. However, with the new generation of fast RDMA-enabled networks, this assumption is no longer valid. In fact, recent work has shown that distributed databases can scale even when the majority of transactions are cross-partition. In this paper, we first make the case that the new bottleneck which hinders truly scalable transaction processing in modern RDMA-enabled databases is data contention, and that optimizing for data contention leads to different partitioning layouts than optimizing for the number of distributed transactions. We then present Chiller, a new approach to data partitioning and transaction execution, which aims to minimize data contention for both local and distributed transactions. Finally, we evaluate Chiller using various workloads, and show that our partitioning and execution strategy outperforms traditional partitioning techniques which try to avoid distributed transactions, by up to a factor of 2

The impact of initial imperfections on the fatigue assessment of tower flange connections in floating wind turbines : a review

During the massive manufactures and installations of fixed offshore wind turbines in China, initial imperfections were often found in the inspection. As more and more attentions and efforts of the wind energy sector have been devoted to deep waters with fixed and floating wind turbines (FWTs), the impact of such initial imperfections on fatigue assessment is paramount to the reliable design and safe operation, which warrant rigorous study. This paper presents a comprehensive review of three different initial imperfections and their impacts on the fatigue lifetime of FWTs’ tower flange connections. A brief introduction on FWTs and flange connections is provided at first. This is followed by a detailed discussion of the environmental loadings and fatigue assessment on the flange bolted connections. Finally, a comprehensive review of the state-of-art research on three common initial imperfections, including flatness divergence, bolt loosening and tower inclination, are presented. Their impact on fatigue assessment is further discussed

Pre-anesthetic use of butorphanol for the prevention of emergence agitation in thoracic surgery: A multicenter, randomized controlled trial

BackgroundEmergence agitation (EA) is common in patients after general anesthesia (GA) and is associated with poor outcomes. Patients with thoracic surgery have a higher incidence of EA compared with other surgery. This study aimed to investigate the impact of pre-anesthetic butorphanol infusion on the incidence of EA in patients undergoing thoracic surgery with GA.Materials and methodsThis prospective randomized controlled trial (RCT) was conducted in 20 tertiary hospitals in China. A total of 668 patients undergoing elective video-assisted thoracoscopic lobectomy/segmentectomy for lung cancer were assessed for eligibility, and 620 patients were enrolled. In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. Patients in the intervention group received butorphanol 0.02 mg/kg 15 min before induction of anesthesia. Patients in the control group received volume-matched normal saline in the same schedule. The primary outcome was the incidence of EA after 5 min of extubation, and EA was evaluated using the Riker Sedation-Agitation Scale (RSAS). The incidence of EA was determined by the chi-square test, with a significance of P < 0.05.ResultsIn total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. The incidence of EA 5 min after extubation was lower with butorphanol treatment: 9.8% (29 of 296) vs. 24.5% (75 of 306) in the control group (P = 0.0001). Patients who received butorphanol had a lower incidence of drug-related complications (including injecting propofol pain and coughing with sufentanil): 112 of 296 vs. 199 of 306 in the control group (P = 0.001) and 3 of 296 vs. 35 of 306 in the control group (P = 0.0001).ConclusionThe pre-anesthetic administration of butorphanol reduced the incidence of EA after thoracic surgery under GA.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=42684], identifier [ChiCTR1900025705]

Down-Regulation of Neogenin Accelerated Glioma Progression through Promoter Methylation and Its Overexpression in SHG-44 Induced Apoptosis

Dependence receptors have been proved to act as tumor suppressors in tumorigenesis. Neogenin, a DCC homologue, well known for its fundamental role in axon guidance and cellular differentiation, is also a dependence receptor functioning to control apoptosis. However, loss of neogenin has been reported in several kinds of cancers, but its role in glioma remains to be further investigated.Western blot analysis showed that neogenin level was lower in glioma tissues than in their matching surrounding non-neoplastic tissues (n = 13, p<0.01). By immunohistochemical analysis of 69 primary and 16 paired initial and recurrent glioma sections, we found that the loss of neogenin did not only correlate negatively with glioma malignancy (n = 69, p<0.01), but also glioma recurrence (n = 16, p<0.05). Kaplan-Meier plot and Cox proportional hazards modelling showed that over-expressive neogenin could prolong the tumor latency (n = 69, p<0.001, 1187.6 ± 162.6 days versus 687.4 ± 254.2 days) and restrain high-grade glioma development (n = 69, p<0.01, HR: 0.264, 95% CI: 0.102 to 0.687). By Methylation specific polymerase chain reaction (MSP), we reported that neogenin promoter was methylated in 31.0% (9/29) gliomas, but absent in 3 kinds of glioma cell lines. Interestingly, the prevalence of methylation in high-grade gliomas was higher than low-grade gliomas and non-neoplastic brain tissues (n = 33, p<0.05) and overall methylation rate increased as glioma malignancy advanced. Furthermore, when cells were over-expressed by neogenin, the apoptotic rate in SHG-44 was increased to 39.7% compared with 8.1% in the blank control (p<0.01) and 9.3% in the negative control (p<0.01).These observations recapitulated the proposed role of neogenin as a tumor suppressor in gliomas and we suggest its down-regulation owing to promoter methylation is a selective advantage for glioma genesis, progression and recurrence. Furthermore, the induction of apoptosis in SHG-44 cells after overexpression of neogenin, indicated that neogenin could be a novel target for glioma therapy

Association between Crash Attributes and Drivers’ Crash Involvement: A Study Based on Police-Reported Crash Data

Understanding the association between crash attributes and drivers&rsquo; crash involvement in different types of crashes can help figure out the causation of crashes. The aim of this study was to examine the involvement in different types of crashes for drivers from different age groups, by using the police-reported crash data from 2014 to 2016 in Shenzhen, China. A synthetic minority oversampling technique (SMOTE) together with edited nearest neighbors (ENN) were used to solve the data imbalance problem caused by the lack of crash records of older drivers. Logistic regression was utilized to estimate the probability of a certain type of crashes, and odds ratios that were calculated based on the logistic regression results were used to quantify the association between crash attributes and drivers&rsquo; crash involvement in different types of crashes. Results showed that drivers&rsquo; involvement patterns in different crash types were affected by different factors, and the involvement patterns differed among the examined age groups. Knowledge generated from the present study could help improve the development of countermeasures for driving safety enhancement

Plasmonic photothermal accumulation of particles by a microfiber decorated with gold nanostructures

This paper introduces an efficient method for accumulation of particles via thermophoresis and thermal convection sustained by localized surface plasmon energy. Gold nanorods were deposited on the designated surface of a microfiber, when a 808 nm laser at an optical power of 12 mV launched into the microfiber, particles dispersed in the water were massively trapped and aggregated on the substrate. This work is envisioned to have application in photothermal cancer therapy, photothermal imaging, and targeted drug delivery

UAV Cluster Task Assignment Algorithm Based on Improved Artificial Gorilla Troops Optimizer

Efficient task execution and optimized combat effectiveness can be achieved when a cluster of Unmanned Aerial Vehicles (UAVs) work collaboratively by assigning various tasks to each UAV reasonably. This paper suggests an algorithm for assigning tasks to a cluster of UAVs using an improved version of the Artificial Gorilla Troops Optimizer (GTO) that incorporates multiple strategies. The proposed algorithm adopts the Halton sequence to generate the initial population to ensure diversity. It uses an information sharing search strategy to enhance communication between the silverback gorilla and the population, effectively jumping out of the local optimal solution. In addition, the problem of inadequate solution accuracy caused by rapid convergence in the middle and later stages of iteration is improved using the golden sine strategy to coordinate GTO&#x2019;s global searching and local mining capabilities. Based on the experimental results, it has been determined that the proposed algorithm outperforms other swarm intelligence algorithms in terms of convergence value and rate across various test functions. Additionally, it has been found to achieve faster and more stable task assignment results

Piano multipitch estimation using sparse coding embedded deep learning

Abstract As the foundation of many applications, multipitch estimation problem has always been the focus of acoustic music processing; however, existing algorithms perform deficiently due to its complexity. In this paper, we employ deep learning to address piano multipitch estimation problem by proposing MPENet based on a novel multimodal sparse incoherent non-negative matrix factorization (NMF) layer. This layer originates from a multimodal NMF problem with Lorentzian-BlockFrobenius sparsity constraint and incoherentness regularization. Experiments show that MPENet achieves state-of-the-art performance (83.65% F-measure for polyphony level 6) on RAND subset of MAPS dataset. MPENet enables NMF to do online learning and accomplishes multi-label classification by using only monophonic samples as training data. In addition, our layer algorithms can be easily modified and redeveloped for a wide variety of problems