Neuroevolution-Based Network Architecture Evolution in Semiconductor Manufacturing
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PROVIDER: S-EPMC10413832 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe semiconductor industry is known to use a number of chemicals, but little is known about the exact chemicals used due to the ingredients being kept as a trade secret.ObjectivesThe objective of this study was to analyze chemical use using a safety data sheet (SDS) and chemical inventory provided by a major semiconductor company, which operated two factories (A and B).MethodsDescriptive statistics were obtained on the number of chemical products and ingredients, photoresists, and carcinogens, classified by the International Agency for Research on Cancer (IARC), as well as trade secret ingredients. The total chemical use per year was estimated from chemical inventories mass (kg).ResultsA total of 428 and 432 chemical products were used in factories A and B, respectively. The number of pure chemical ingredients, after removing both trade secret ingredients and multiple counting, was 189 and 157 in factories A and B, respectively. The number of products containing carcinogens, such as sulfuric acid, catechol, and naphthalene was 47/428 (A) and 28/432 (B). Chemicals used in photolithography were 21% (A) and 26% (B) of all chemical products, and more than 97% among them were chemicals containing trade secret ingredients.ConclusionsEach year, 4.3 and 8.3 tons of chemicals were used per person in factories A and B, respectively. Because of the high level of commercial secrecy and the use of many unregulated chemicals, more sustainable policies and methods should be implemented to address health and safety issues in the semiconductor industry.
| S-EPMC6237170 | biostudies-literature
Project description:BackgroundWe aimed to examine the lymphohematopoietic cancer mortality in a cohort of workers at a semiconductor manufacturing company in South Korea according to their jobs.MethodsA retrospective cohort was constructed using the personnel records of semiconductor manufacturing workers who were employed in a semiconductor company in South Korea in 1998-2012. Data on their vital status and causes of death were obtained from the National Statistical Office of South Korea. The standardized mortality ratios (SMRs) of lymphohematopoietic cancer were calculated.ResultsA total of 288 deaths were reported, of which 22 were caused by lymphohematopoietic cancer, among 65,782 workers in 878,325 person-years. The SMRs for lymphohematopoietic cancer were 0.78 (95% confidence interval [CI] = 0.39-1.40; the number of observed cases [Obs] = 11) among male workers and 1.71 (95% CI = 0.85-3.06; Obs = 11) among female workers. Among female operators, excess deaths due to lymphohematopoietic cancer (SMR = 2.59, 95% CI = 1.24-4.76) and leukemia (SMR = 2.92, 95% CI = 1.26-5.76) were observed. However, they were not observed among office workers, facility managers, utility managers, or process managers.ConclusionFemale operators involved in the semiconductor wafer fabrication process had higher risk of mortality from lymphohematopoietic cancer.
| S-EPMC10398905 | biostudies-literature
Project description:The 2D van der Waals crystals have shown great promise as potential future electronic materials due to their atomically thin and smooth nature, highly tailorable electronic structure, and mass production compatibility through chemical synthesis. Electronic devices, such as field effect transistors (FETs), from these materials require patterning and fabrication into desired structures. Specifically, the scale up and future development of "2D"-based electronics will inevitably require large numbers of fabrication steps in the patterning of 2D semiconductors, such as transition metal dichalcogenides (TMDs). This is currently carried out via multiple steps of lithography, etching, and transfer. As 2D devices become more complex (e.g., numerous 2D materials, more layers, specific shapes, etc.), the patterning steps can become economically costly and time consuming. Here, we developed a method to directly synthesize a 2D semiconductor, monolayer molybdenum disulfide (MoS2), in arbitrary patterns on insulating SiO2/Si via seed-promoted chemical vapor deposition (CVD) and substrate engineering. This method shows the potential of using the prepatterned substrates as a master template for the repeated growth of monolayer MoS2 patterns. Our technique currently produces arbitrary monolayer MoS2 patterns at a spatial resolution of 2 μm with excellent homogeneity and transistor performance (room temperature electron mobility of 30 cm2 V-1 s-1 and on-off current ratio of 107). Extending this patterning method to other 2D materials can provide a facile method for the repeatable direct synthesis of 2D materials for future electronics and optoelectronics.
| S-EPMC6397508 | biostudies-literature
Project description:We propose a method for evolving neural network controllers robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediately, without the need to adapt to variations). The method specifies how the fitness of candidate solutions can be evaluated, how the environmental conditions should vary during the course of the evolutionary process, which algorithm can be used, and how the best solution can be identified. The obtained results show how the method proposed is effective and computational tractable. It allows to improve performance on an extended version of the double-pole balancing problem, outperform the best available human-designed controllers on a car racing problem, and generate effective solutions for a swarm robotic problem. The comparison of different algorithms indicates that the CMA-ES and xNES methods, that operate by optimizing a distribution of parameters, represent the best options for the evolution of robust neural network controllers.
| S-EPMC6396973 | biostudies-literature
Project description:BACKGROUND:The genetic architecture of a quantitative trait influences the phenotypic response to natural or artificial selection. One of the main objectives of genetic mapping studies is to identify the genetic factors underlying complex traits and understand how they contribute to phenotypic expression. Presently, we are good at identifying and locating individual loci with large effects, but there is a void in describing more complex genetic architectures. Although large networks of connected genes have been reported, there is an almost complete lack of information on how polymorphisms in these networks contribute to phenotypic variation and change. To date, most of our understanding comes from theoretical, model-based studies, and it remains difficult to assess how realistic their conclusions are as they lack empirical support. RESULTS:A previous study provided evidence that nearly half of the difference in eight-week body weight between two divergently selected lines of chickens was a result of four loci organized in a 'radial' network (one central locus interacting with three 'radial' loci that, in turn, only interacted with the central locus). Here, we study the relationship between phenotypic change and genetic polymorphism in this empirically detected network. We use a model-free approach to study, through individual-based simulations, the dynamic properties of this polymorphic and epistatic genetic architecture. The study provides new insights to how epistasis can modify the selection response, buffer and reveal effects of major loci leading to a progressive release of genetic variation. We also illustrate the difficulty of predicting genetic architecture from observed selection response, and discuss mechanisms that might lead to misleading conclusions on underlying genetic architectures from quantitative trait locus (QTL) experiments in selected populations. CONCLUSION:Considering both molecular (QTL) and phenotypic (selection response) data, as suggested in this work, provides additional insights into the genetic mechanisms involved in the response to selection. Such dissection of genetic architectures and in-depth studies of their ability to contribute to short- or long-term selection response represents an important step towards a better understanding of the genetic bases of complex traits and, consequently, of the evolutionary properties of populations.
| S-EPMC2194667 | biostudies-literature
Project description:The ability to build upon previous knowledge-cumulative cultural evolution-is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.
| S-EPMC7944107 | biostudies-literature
Project description:The recent development of a semiconductor-based, non-optical DNA sequencing technology promises scalable, low-cost and rapid sequence data production. The technology has previously been applied mainly to genomic sequencing and targeted re-sequencing. Here, we demonstrate the utility of Ion Torrent semiconductor-based sequencing for sensitive, efficient and rapid chromatin immunoprecipitation followed by sequencing (ChIP-seq) through the application of sample preparation methods that are optimized for ChIP-seq on the Ion Torrent platform. We leverage this method for epigenetic profiling of tumor tissues.
2013-10-25 | GSE49477 | GEO
Project description:BackgroundResearch on the status of many chemicals used in the semiconductor industry is needed. The purpose of this study was to describe the overall status of chemical use in the semiconductor industry in Korea and to examine it from a health perspective.MethodsData on the status of chemical use and safety data sheets at 11 of 12 major semiconductor workplaces in Korea were collected. The number of chemical products and chemical constituents, quantities of chemicals, and trade secret ingredients used, as well as the health hazards were examined.ResultsOn average, 210 chemical products and 135 chemical constituents were used at the surveyed workplaces. Among all chemical products, 33% (range: 16-56%) contained at least one trade secret ingredient. Most of the trade secret ingredients were used in the photolithography process. Several carcinogens, including sulfuric acid, chromic acid, ethylene oxide, crystalline silica, potassium dichromate, and formaldehyde were also used. Only 29% (39 of 135) of the chemical constituents had occupational exposure limits, and more than 60% had no National Fire Protection Association health, safety, and reactivity ratings. Based on the aforementioned results, this study revealed the following. First, many chemical products and constituents are being used in the semiconductor industry and many products contained trade secret ingredients. Second, many products contained significant amounts of carcinogenic, mutagenic, and reproductive toxicant materials.ConclusionWe conclude that protecting workers in the semiconductor industry against harm from chemical substances will be difficult, due to widespread use of trade secret ingredients and a lack of hazard information. The findings of the status of chemical use and the health and safety risks in semiconductor industry will contribute to epidemiological studies, safe workplace, and worker health protection.
| S-EPMC7728705 | biostudies-literature
Project description:Coal and gas outburst (CGO) is a complicated natural disaster in underground coal mine production. In constructing smart mines, predicting CGO risks efficiently and accurately is necessary. This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. It solves the problems of imbalanced data samples and insufficient diversity. Second, the feature importance score sorting and Sparse PCA dimensionality reduction are performed on the data-augmented samples. It provides the initial genome code for the evolutionary neural network. Finally, an evolutionary neural network for CGO prediction is constructed through population initialization, fitness evaluation, species differentiation, genome mutation, and recombination. The optimal phenotype is obtained in the evolutionary generations. In the experiment, we verify the effectiveness of ANEAT from multiple aspects such as data augmentation effectiveness analysis, deep learning model comparison, swarm intelligence optimization algorithm comparison, and other method comparisons. The results show that the MAE, RMSE, and EVAR indexes of ANEAT on the test set are 0.0816, 0.1322, and 0.8972, respectively. It has the optimal CGO prediction effect. ANEAT realizes the high-precision mapping of feature parameters and outburst risk with a lightweight network architecture, which can be well applied to CGO prediction.
| S-EPMC11841871 | biostudies-literature
Project description:The recent development of a semiconductor-based, non-optical DNA sequencing technology promises scalable, low-cost and rapid sequence data production. The technology has previously been applied mainly to genomic sequencing and targeted re-sequencing. Here, we demonstrate the utility of Ion Torrent semiconductor-based sequencing for sensitive, efficient and rapid chromatin immunoprecipitation followed by sequencing (ChIP-seq) through the application of sample preparation methods that are optimized for ChIP-seq on the Ion Torrent platform. We leverage this method for epigenetic profiling of tumor tissues. Examination of histone modifications in mouse dendentic cells stimulated with LPS, matched melanoma derived cell line, melanoma tumor tissue
2013-10-25 | E-GEOD-49477 | biostudies-arrayexpress