Femtosecond Laser-induced Crystallization of Amorphous Sb2Te3 film and Coherent Phonon Spectroscopy Characterization and Optical Injection of Electron Spins

A femtosecond laser-irradiated crystallizing technique is tried to convert amorphous Sb2Te3 film into crystalline film. Sensitive coherent phonon spectroscopy (CPS) is used to monitor the crystallization of amorphous Sb2Te3 film at the original irradiation site. The CPS reveals that the vibration strength of two phonon modes that correspond to the characteristic phonon modes of crystalline Sb2Te3, enhances with increasing laser irradiation fluence (LIF), showing the rise of the degree of crystallization with LIF and that femtosecond laser irradiation is a good post-treatment technique. Time-resolved circularly polarized pump-probe spectroscopy is used to investigate electron spin relaxation dynamics of the laser-induced crystallized Sb2Te3 film. Spin relaxation process indeed is observed, confirming the theoretical predictions on the validity of spin-dependent optical transition selection rule and the feasibility of transient spin-grating-based optical detection scheme of spin-plasmon collective modes in Sb2Te3-like topological insulators.Comment: 16 pages, 4 figure

Effects of toe-out and toe-in gaits on lower-extremity kinematics, dynamics, and electromyography

Toe-in and toe-out gait modifications have received increasing attention as an effective, conservative treatment for individuals without severe osteoarthritis because of its potential for improving knee adduction moment (KAM) and knee flexion moment (KFM). Although toe-in and toe-out gaits have positive effects on tibiofemoral (TF) joint pain in the short term, negative impacts on other joints of the lower extremity may arise. The main purpose of this study was to quantitatively compare the effects of foot progression angle (FPA) gait modification with normal walking speeds in healthy individuals on lower-extremity joint, ground reaction force (GRF), muscle electromyography, joint moment, and TF contact force. Experimental measurements using the Vicon system and multi-body dynamics musculoskeletal modelling using OpenSim were conducted in this study. Gait analysis of 12 subjects (n = 12) was conducted with natural gait, toe-in gait, and toe-out gait. One-way repeated measures of ANOVA (p < 0.05) with Tukey’s test was used for statistical analysis. Results showed that the toe-in and toe-out gait modifications decreased the max angle of knee flexion by 8.8 and 12.18 degrees respectively (p < 0.05) and the max angle of hip adduction by 1.28 and 0.99 degrees respectively (p < 0.05) compared to the natural gait. Changes of TF contact forces caused by FPA gait modifications were not statistically significant; however, the effect on KAM and KFM were significant (p < 0.05). KAM or combination of KAM and KFM can be used as surrogate measures for TF medial contact force. Toe-in and toe-out gait modifications could relieve knee joint pain probably due to redistribution of TF contact forces on medial and lateral condylar through changing lateral contact centers and shifting bilateral contact locations

Improved cultural algorithms for job shop scheduling problem

This paper presents a new cultural algorithm for job shop scheduling problem. Unlike the canonical genetic algorithm, in which random elitist selection and mutational genetics is assumed. The proposed cultural algorithm extract the useful knowledge from the population space of genetic algorithm to form belief space, and utilize it to guide the genetic operator of selection and mutation. The different sizes of the benchmark data taken from literature are used to analyze the efficacy of this algorithm. Experimental results indicate that it outperforms current approaches using canonical genetic algorithms in computational time and quality of the solutions

Exploring the Process of Fresh Produce Supply Within a Platform Ecosystem During City Lockdown Period

While the existing literature focusing on how organizations collaborate within ecosystems to overcome institutional logic conflicts and the information systems enabled inter-organizational cooperation, less is known on how information systems develop during crises and enable effective collaboration among stakeholders. Through an in-depth case study of Shenzhen Company H (pseudonym) platform ecosystem, we present an IT-enabled fresh produce supply process. Our findings reveal that this process unfolds across four dimensions - iterative IT tailoring, progressive system synergy, facilitative IT confluence, and user-attuned technological adaptation. Based on these dimensions, we propose an IT-enabled platform ecosystem orchestration mechanism in crisis situations. These mechanisms also offer practical implications not only for organizations\u27 strategies when facing crises but also for the enhancement of their daily operational competence

Effects of government subsidies on production and emissions reduction decisions under carbon tax regulation and consumer low‐carbon awareness

To promote low-carbon production, the government simultaneously provides some subsidies under carbon tax regulations. Two government subsidies are widely adopted: one is based on emissions reduction quantity and the other is based on emissions reduction investment cost. Additionally, consumer low-carbon awareness has also been enhanced. Considering the aforementioned circumstances, this paper investigates the effects of different government subsidies on production and emissions reduction decisions under a carbon tax regulation by formulating three decision-making optimization models. The results show that (1) although the carbon tax regulation cannot guarantee further improvement of emissions reduction levels, government subsidies could make the corresponding conditions of improving emissions reduction investments wider; (2) a heavy carbon tax or stronger consumer low-carbon awareness would make the positive effect of government subsidies more apparent; and (3) subsidy policies may also be selected by the government from different perspectives, such as manufacturer development, consumer surplus, environmental damage and social welfare. Especially, from the perspective of maximizing social welfare, investment cost (IC) subsidy is not always advantageous, while emissions reduction (ER) subsidy can always bring higher social welfare compared with the case under no government subsidy

Effect of 5-aminolevulinic acid on yield and quality of lettuce in sunlit greenhouse

The role of 5-aminolevulinic acid (ALA) as a precursor of chlorophyll and heme is well documented. Low concentration of exogenous ALA has been found to regulate plant growth and increase crop yield, but there is little information on how ALA influences the yield and quality of lettuce in sunlit greenhouse. Here, we report the effects of ALA on photosynthetic rate, yield and quality of lettuce in sunlit greenhouse.5-aminolevulinic acid and 5-aminolevulinic acid with nitrogen fertilizer (ALA+N) were applied by foliage and soil. The results showed that application of ALA improved the photosynthetic rate of lettuce leaves by 23.9 to 34.7% and by 35.3 to 41.6%. Moreover, exogenous ALA increased vitamin C and soluble sugar content, reduced nitrate and crude fiber content and lead to better quality and taste of lettuce.Keywords: 5-aminolevulinic acid, lettuce, plant growth, promotive effects, yield, vegetable qualit

FeatAug: Automatic Feature Augmentation From One-to-Many Relationship Tables

Feature augmentation from one-to-many relationship tables is a critical but challenging problem in ML model development. To augment good features, data scientists need to come up with SQL queries manually, which is time-consuming. Featuretools [1] is a widely used tool by the data science community to automatically augment the training data by extracting new features from relevant tables. It represents each feature as a group-by aggregation SQL query on relevant tables and can automatically generate these SQL queries. However, it does not include predicates in these queries, which significantly limits its application in many real-world scenarios. To overcome this limitation, we propose FEATAUG, a new feature augmentation framework that automatically extracts predicate-aware SQL queries from one-to-many relationship tables. This extension is not trivial because considering predicates will exponentially increase the number of candidate queries. As a result, the original Featuretools framework, which materializes all candidate queries, will not work and needs to be redesigned. We formally define the problem and model it as a hyperparameter optimization problem. We discuss how the Bayesian Optimization can be applied here and propose a novel warm-up strategy to optimize it. To make our algorithm more practical, we also study how to identify promising attribute combinations for predicates. We show that how the beam search idea can partially solve the problem and propose several techniques to further optimize it. Our experiments on four real-world datasets demonstrate that FeatAug extracts more effective features compared to Featuretools and other baselines. The code is open-sourced at https://github.com/sfu-db/FeatAu

Longitudinal and Cross-sectional Reference Curves of Gross Motor Function in Children

Title: Longitudinal and Cross-sectional Reference Curves of Gross Motor Function in Children, Author: Weiling Wang, Location: ThodeReference curves are the most popular tool to monitor the time-related growth in children. Both cross-sectional and longitudinal studies are widely used to collect the reference samples. The methods used for constructing the reference curves and the interpretation of the curves for longitudinal studies should be different from those for the cross-sectional studies. However misunderstanding in constructing and interpreting the reference curves for the cross-sectional and longitudinal studies is common, especially the concerning of the effect of regression to the mean in the longitudinal studies. The LMS models of Cole and Green[1,2] using penalized likelihood are considered to be the most powerful methods to construct the reference curves for both cross-sectional and longitudinal studies. This thesis focuses on the comparison of the conditional LMS regression approach for drawing the median conditional centiles for longitudinal data to the conventional LMS model for constructing the distance centiles for cross-sectional data. It describes the different interpretations of the two approaches. The application of the two methods to a study of Gross Motor Function is investigated in detail to illustrate the difference between them.ThesisMaster of Science (MS