On the training and generalization of deep operator networks

We present a novel training method for deep operator networks (DeepONets), one of the most popular neural network models for operators. DeepONets are constructed by two sub-networks, namely the branch and trunk networks. Typically, the two sub-networks are trained simultaneously, which amounts to solving a complex optimization problem in a high dimensional space. In addition, the nonconvex and nonlinear nature makes training very challenging. To tackle such a challenge, we propose a two-step training method that trains the trunk network first and then sequentially trains the branch network. The core mechanism is motivated by the divide-and-conquer paradigm and is the decomposition of the entire complex training task into two subtasks with reduced complexity. Therein the Gram-Schmidt orthonormalization process is introduced which significantly improves stability and generalization ability. On the theoretical side, we establish a generalization error estimate in terms of the number of training data, the width of DeepONets, and the number of input and output sensors. Numerical examples are presented to demonstrate the effectiveness of the two-step training method, including Darcy flow in heterogeneous porous media

B+-tree Index Optimization by Exploiting Internal Parallelism of Flash-based Solid State Drives

Previous research addressed the potential problems of the hard-disk oriented design of DBMSs of flashSSDs. In this paper, we focus on exploiting potential benefits of flashSSDs. First, we examine the internal parallelism issues of flashSSDs by conducting benchmarks to various flashSSDs. Then, we suggest algorithm-design principles in order to best benefit from the internal parallelism. We present a new I/O request concept, called psync I/O that can exploit the internal parallelism of flashSSDs in a single process. Based on these ideas, we introduce B+-tree optimization methods in order to utilize internal parallelism. By integrating the results of these methods, we present a B+-tree variant, PIO B-tree. We confirmed that each optimization method substantially enhances the index performance. Consequently, PIO B-tree enhanced B+-tree's insert performance by a factor of up to 16.3, while improving point-search performance by a factor of 1.2. The range search of PIO B-tree was up to 5 times faster than that of the B+-tree. Moreover, PIO B-tree outperformed other flash-aware indexes in various synthetic workloads. We also confirmed that PIO B-tree outperforms B+-tree in index traces collected inside the Postgresql DBMS with TPC-C benchmark.Comment: VLDB201

Object-Aware Impedance Control for Human-Robot Collaborative Task with Online Object Parameter Estimation

Physical human-robot interactions (pHRIs) can improve robot autonomy and reduce physical demands on humans. In this paper, we consider a collaborative task with a considerably long object and no prior knowledge of the object's parameters. An integrated control framework with an online object parameter estimator and a Cartesian object-aware impedance controller is proposed to realize complicated scenarios. During the transportation task, the object parameters are estimated online while a robot and human lift an object. The perturbation motion is incorporated into the null space of the desired trajectory to enhance the estimator accuracy. An object-aware impedance controller is designed using the real-time estimation results to effectively transmit the intended human motion to the robot through the object. Experimental demonstrations of collaborative tasks, including object transportation and assembly tasks, are implemented to show the effectiveness of our proposed method.Comment: 11 pages, 5 figures, for associated video, see https://youtu.be/bGH6GAFlRgA?si=wXj_SRzEE8BYoV2

An Examination On Factors That Influence The Creation Of Economic Value Added To The Professional Teams: Focusing On Korea Baseball Organization (KBO)

The research seeks to derive the economic value added (EVA) of 6 franchises from the Korea Baseball Organization (KBO) and concurrently investigate the revenue components contributing to EVA. EVA is regarded as one of the efficient methods on estimating or assessing corporations’ actual economic benefits. For the procedure, financial statements of domestic professional baseball teams for 3 consecutive years (2016-2018), which were released to the Data Analysis Retrieval and Transfer System (DART) of the Financial Supervisory Service (FSS), were utilized. First, NOPLAT, IC, ROIC, and WACC, which refer to essential elements of estimating the EVA, were calculated respectively. Second, Pearson's correlation analysis was conducted between the EVA and the profit indicated in the income statement of the 6 teams. The results of the study are as follows: In case of Doosan, LG and SK, main business revenues showed the highest correlation with EVA, and Kiwoom and Samsung showed the highest correlation with EVA through the contributing factor of ticket sales revenue. Finally, for Lotte, advertising revenue was highly correlated with bringing EVA to the tea

How Team-Level and Individual-Level Conflict Influences Team Commitment: A Multilevel Investigation

We investigate how two different types of conflict (task conflict and relationship conflict) at two different levels (individual-level and team-level) influence individual team commitment. The analysis was conducted using data we collected from 193 employees in 31 branch offices of a Korean commercial bank. The relationships at multiple levels were tested using hierarchical linear modeling (HLM). The results showed that individual-level relationship conflict was negatively related to team commitment while individual-level task conflict was not. In addition, both team-level task and relationship conflict were negatively associated with team commitment. Finally, only team-level relationship conflict significantly moderated the relationship between individual-level relationship conflict and team commitment. We further derive theoretical implications of these findings

Transgenic wheat expressing a barley class II chitinase gene has enhanced resistance against Fusarium graminearum

Fusarium head blight (FHB; scab), primarily caused by Fusarium graminearum, is a devastating disease of wheat worldwide. FHB causes yield reductions and contamination of grains with trichothecene mycotoxins such as deoxynivalenol (DON). The genetic variation in existing wheat germplasm pools for FHB resistance is low and may not provide sufficient resistance to develop cultivars through traditional breeding approaches. Thus, genetic engineering provides an additional approach to enhance FHB resistance. The objectives of this study were to develop transgenic wheat expressing a barley class II chitinase and to test the transgenic lines against F. graminearum infection under greenhouse and field conditions. A barley class II chitinase gene was introduced into the spring wheat cultivar, Bobwhite, by biolistic bombardment. Seven transgenic lines were identified that expressed the chitinase transgene and exhibited enhanced Type II resistance in the greenhouse evaluations. These seven transgenic lines were tested under field conditions for percentage FHB severity, percentage visually scabby kernels (VSK), and DON accumulation. Two lines (C8 and C17) that exhibited high chitinase protein levels also showed reduced FHB severity and VSK compared to Bobwhite. One of the lines (C8) also exhibited reduced DON concentration compared with Bobwhite. These results showed that transgenic wheat expressing a barley class II chitinase exhibited enhanced resistance against F. graminearum in greenhouse and field conditions

Examining the transcriptional response in wheat Fhb1 near-isogenic lines to Fusarium graminearum infection and deoxynivalenol treatment

Citation: Hofstad, A. N., Nussbaumer, T., Akhunov, E., Shin, S., Kugler, K. G., Kistler, H. C., . . . Muehlbauer, G. J. (2016). Examining the transcriptional response in wheat Fhb1 near-isogenic lines to Fusarium graminearum infection and deoxynivalenol treatment. Plant Genome, 9(1). https://doi.org/10.3835/plantgenome2015.05.0032Fusarium head blight (FHB) is a disease caused predominantly by the fungal pathogen Fusarium graminearum that affects wheat and other small-grain cereals and can lead to severe yield loss and reduction in grain quality. Trichothecene mycotoxins, such as deoxynivalenol (DON), accumulate during infection and increase pathogen virulence and decrease grain quality. The Fhb1 locus on wheat chromosome 3BS confers Type II resistance to FHB and resistance to the spread of infection on the spike and has been associated with resistance to DON accumulation. To gain a better genetic understanding of the functional role of Fhb1 and resistance or susceptibility to FHB, we examined DON and ergosterol accumulation, FHB resistance, and the whole-genome transcriptomic response using RNA-seq in a near-isogenic line (NIL) pair carrying the resistant and susceptible alleles for Fhb1 during F. graminearum infection and DON treatment. Our results provide a gene expression atlas for the resistant and susceptible wheat–F. graminearum interaction. The DON concentration and transcriptomic results show that the rachis is a key location for conferring Type II resistance. In addition, the wheat transcriptome analysis revealed a set of Fhb1-responsive genes that may play a role in resistance and a set of DON-responsive genes that may play a role in trichothecene resistance. Transcriptomic results from the pathogen show that the F. graminearum genome responds differently to the host level of resistance. The results of this study extend our understanding of host and pathogen responses in the wheat–F. graminearum interaction. © Crop Science Society of America

Substrate-Dependent Differences in the Crystal Structures and Optical Properties of ZnSe Nanowires

The optical and structural properties of ZnSe nanowires directly grown on three different substrates, SiO2, ITO, and graphene, were investigated. ZnSe nanowires grown on graphene and SiO2 were found to have cubic structures, while ZnSe nanowires grown on ITO had a mixed cubic and hexagonal structure. The main peaks in the photoluminescence spectra of ZnSe nanowires grown on SiO2, ITO, and graphene were located at 459, 627, and 627/460 nm, respectively. In addition, a field-emission light-emitting device was fabricated using ZnSe nanowires as a phosphor and graphene as an electrode. The device showed a red emission peak with Commission Internationale de L’Eclairage coordinates of (0.621, 0.315)

Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach

Understanding the concentration and distribution of cyanobacteria blooms is an important aspect of managing water quality problems and protecting aquatic ecosystems. Airborne hyperspectral imagery (HSI)-which has high temporal, spatial, and spectral resolutions-is widely used to remotely sense cyanobacteria bloom, and it provides the distribution of the bloom over a wide area. In this study, we determined the input spectral bands that were relevant in effectively estimating the main two pigments (PC, Phycocyanin; Chl-a, Chlorophyll-a) of cyanobacteria by applying data-driven algorithms to HSI and then evaluating the change in the spatio-temporal distribution of cyanobacteria. The input variables for the algorithms consisted of reflectance band ratios associated with the optical properties of PC and Chl-a, which were calculated by the selected hyperspectral bands using a feature selection method. The selected input variable was composed of six reflectance bands (465.7-589.6, 603.6-631.8, 641.2-655.35, 664.8-679.0, 698.0-712.3, and 731.4-784.1 nm). The artificial neural network showed the best results for the estimation of the two pigments with average coefficients of determination 0.80 and 0.74. This study proposes relevant input spectral information and an algorithm that can effectively detect the occurrence of cyanobacteria in the weir pool along the Geum river, South Korea. The algorithm is expected to help establish a preemptive response to the formation of cyanobacterial blooms, and to contribute to the preparation of suitable water quality management plans for freshwater environments

REEP5 depletion causes sarco-endoplasmic reticulum vacuolization and cardiac functional defects

The sarco-endoplasmic reticulum (SR/ER) plays an important role in the development and progression of many heart diseases. However, many aspects of its structural organization remain largely unknown, particularly in cells with a highly differentiated SR/ER network. Here, we report a cardiac enriched, SR/ER membrane protein, REEP5 that is centrally involved in regulating SR/ER organization and cellular stress responses in cardiac myocytes. In vitro REEP5 depletion in mouse cardiac myocytes results in SR/ER membrane destabilization and luminal vacuolization along with decreased myocyte contractility and disrupted Ca2+ cycling. Further, in vivo CRISPR/Cas9-mediated REEP5 loss-of-function zebrafish mutants show sensitized cardiac dysfunction upon short-term verapamil treatment. Additionally, in vivo adeno-associated viral (AAV9)-induced REEP5 depletion in the mouse demonstrates cardiac dysfunction. These results demonstrate the critical role of REEP5 in SR/ER organization and function as well as normal heart function and development