Creating First-Mover Advantages: The Case of Samsung Electronics

This paper analyzes the sources of first-mover advantages by examining the case of Samsung Electronics, a firm which has maintained and strengthened the technological leadership in the DRAM industry since 1992. The focus is on endogeneity of first-mover advantages under changing technological and competitive environments, part of which are also shaped by the technology leader. The paper also discusses general implications of this case study for strategy and organization for innovation.First-mover advantages, innovation, firm growth, Samsung Electronics, semiconductors

High-Throughput Screening of Acyl-CoA Thioesterase I Mutants Using a Fluid Array Platform

Screening target microorganisms from a mutated recombinant library plays a crucial role in advancing synthetic biology and metabolic engineering. However, conventional screening tools have several limitations regarding throughput, cost, and labor. Here, we used the fluid array platform to conduct high-throughput screening (HTS) that identified Escherichia coli ???TesA thioesterase mutants producing elevated yields of free fatty acids (FFAs) from a large (106) mutant library. A growth-based screening method using a TetA-RFP fusion sensing mechanism and a reporter-based screening method using high-level FFA producing mutants were employed to identify these mutants via HTS. The platform was able to cover >95% of the mutation library, and it screened target cells from many arrays of the fluid array platform so that a post-analysis could be conducted by gas chromatography. The ???TesA mutation of each isolated mutant showing improved FFA production in E. coli was characterized, and its enhanced FFA production capability was confirmed

AD-YOLO: You Look ONly Once in Training Multiple Sound Event Localization and Detection

Sound event localization and detection (SELD) combines the identification of sound events with the corresponding directions of arrival (DOA). Recently, event-oriented track output formats have been adopted to solve this problem; however, they still have limited generalization toward real-world problems in an unknown polyphony environment. To address the issue, we proposed an angular-distance-based multiple SELD (AD-YOLO), which is an adaptation of the "You Look Only Once" algorithm for SELD. The AD-YOLO format allows the model to learn sound occurrences location-sensitively by assigning class responsibility to DOA predictions. Hence, the format enables the model to handle the polyphony problem, regardless of the number of sound overlaps. We evaluated AD-YOLO on DCASE 2020-2022 challenge Task 3 datasets using four SELD objective metrics. The experimental results show that AD-YOLO achieved outstanding performance overall and also accomplished robustness in class-homogeneous polyphony environments.Comment: 5 pages, 3 figures, accepted for publication in IEEE ICASSP 202

Two opposite hysteresis curves in semiconductors with mobile dopants

Recent experimental researches on semiconductors with mobile dopants (SMD) have reported unconventional hysteretic current-voltage (I-V) curves, which form dynamically in either one of the two opposite directions, the counter-figure-eight and figure-eight ways. However the fundamental theory for the formation of the two directions is still absent, and this poses a major barrier for researches oriented to applications. Here, we introduce a theoretical model to explain the origin of the two directions, and find that the two ways originate from the spatial inhomogeneity of the dopant distribution in SMD. The counter-figure-eight (figure-eight) way of the hysteretic curve is obtained when dopants are driven from far from (near) the Schottky interface to the opposite side in the SMD. This finding indicates that the directions of hysteretic curve in SMD can be controlled.Comment: 5 pages, 4 figure

Development of Prediction Method for Dimensional Stability of 3D-Printed Objects

Fused deposition modeling (FDM), as one of the additive manufacturing processes, is known for strong layer adhesion suitable for prototypes and end-use items. This study used a multiple regression model and statistical analysis to explore the dimensional accuracy of FDM objects. Factors such as inclination angle, layer thickness, support space, and raster angle were examined. Machine learning models (Gaussian process regression (GPR), support vector machines (SVM), and artificial neural network (ANN)) predicted dimensions using 81 datapoints. The mean squared dimensional error (MSDE) between the measured and designed surface profiles was selected as an output for the dimensional accuracy. Support spacing, layer thickness, and raster angle were determined to be statistically significant, and all factors were confirmed as significant predictors. The coefficients of determination for multiple linear regression, GPR, SVM, and ANN models were 76%, 98%, 93%, and 99%, respectively. The mean absolute errors (MAEs)—errors between the measured and the predicted MSDEs—were 0.020 mm and 0.034 mm, respectively, for GPR and SVM models. The MAEs for ANN models were 0.0055 mm for supporting cases and 2.1468 x 10 -5 mm for non-supporting cases

Examining the links between burnout and suicidal ideation in diverse occupations

IntroductionIt is uncertain whether burnout is associated with suicidal ideation among workers not in health care services. The aim of this study was to identify how burnout and suicidal ideation are linked among employees in various occupations and whether depression affects this link.MethodsThis cross-sectional study collected data from 12,083 participants aged 19–65 years from 25 companies and public institutions who underwent workplace mental health screening. Burnout and depression were assessed using both the Oldenburg Burnout Inventory and the Center for Epidemiologic Studies Depression Scale. Suicidal ideation was assessed by a self-rated questionnaire from the Korea National Health and Nutrition Examination Survey.ResultsExhaustion but not the cynicism dimension of burnout was associated with increased odds of suicidal ideation after adjustment for depression and other covariates (odds ratio [OR] = 1.47, 95% CI = 1.26–1.72). The association of exhaustion with suicidal ideation was significant in both depressed (OR = 1.36, 95% CI = 1.14–1.61) and not depressed (OR = 1.77, 95% CI = 1.13–2.76) participants. In exhausted participants, insufficient job control, an unfavorable occupational climate, low educational level, and depression were associated with increased odds of suicidal ideation.ConclusionExhaustion is linked with risk of suicidal ideation in employees not in health care service, regardless of depression status. Exhausted employees, particularly those having poor job resources, should be recognized as an at-risk group