Analyzing the influential factors of industry 4.0 in precision machinery industry

Abstract. Nowadays the science and technology progresses not only create the change to have a big impact on various industries, but also stimulate Industry 4.0 being applied in the manufacturing industry to achieve manufacturing efficiency and to reduce its cost to increase additional values. This study uses the Analytical Hierarchical Process (AHP) evaluation method, which considers four criteria layers: Internet of things factors, Automationfactors, Intelligent factors, Big data factors, and twelve influence factors in sub-layer are: perceived layer, network layer, application layer, field layer, management layer, control layer, process control visualization, system supervisory and control omni bearing, green energy manufacturing production, variety, volume, and velocity. Then, the relative risk indicator (RRI) is obtained by the Analytical Hierarchical Process method, and the overall risk indicator (ORI) can be obtained after introducing the evaluation value of each impact factor through the case. The research results confirm that the risk assessment values obtained the hierarchical analysis method are consistent. This research through the Analytic Hierarchy Process, then discusses Industry 4.0 pair of Taiwan's precision machinery industry management pattern institute emphatically face with target, expected will provide the existing machine manufacture industry as well as the future wants to invest the precision machine industry the management policy-maker reference value, also might take the government policy consideration factors and the machine manufacture industry scholars study the academic for reference.Keywords. Industry 4.0, Precision machine industry, Analytic Hierarchy Process.JEL. L22, M11, O14

Investigation of Effects of Strouhal and Reynolds numbers on Propulsive Efficiency of Plunging and Pitching Foils

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P2

The PSEA promoter element of the Drosophila U1 snRNA gene is sufficient to bring DmSNAPc into contact with 20 base pairs of downstream DNA

Most of the major spliceosomal small nuclear RNAs (snRNAs) (i.e. U1, U2, U4 and U5) are synthesized by RNA polymerase II (pol II). In Drosophila melanogaster, the 5′-flanking DNA of these genes contains two conserved elements: the proximal sequence element A (PSEA) and the proximal sequence element B (PSEB). The PSEA is essential for transcription and is recognized by DmSNAPc, a multi-subunit protein complex. Previous site-specific protein–DNA photo-cross-linking assays demonstrated that one of the subunits of DmSNAPc, DmSNAP43, remains in close contact with the DNA for 20 bp beyond the 3′ end of the PSEA, a region that contains the PSEB. The current work demonstrates that mutation of the PSEB does not abolish the cross-linking of DmSNAP43 to the PSEB. Thus the U1 PSEA alone is capable of bringing DmSNAP43 into close contact with this downstream DNA. However, mutation of the PSEB perturbs the cross-linking pattern. In concordance with these findings, PSEB mutations result in a 2- to 4-fold reduction in U1 promoter activity when assayed by transient transfection

Diffusion Model-Augmented Behavioral Cloning

Imitation learning addresses the challenge of learning by observing an expert's demonstrations without access to reward signals from environments. Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probability p(a|s) (e.g., behavioral cloning, BC) or the joint probability p(s, a) (e.g., implicit behavioral cloning). Despite its simplicity, modeling the conditional probability with BC usually struggles with generalization. While modeling the joint probability can lead to improved generalization performance, the inference procedure can be time-consuming and it often suffers from manifold overfitting. This work proposes an imitation learning framework that benefits from modeling both the conditional and joint probability of the expert distribution. Our proposed diffusion model-augmented behavioral cloning (DBC) employs a diffusion model trained to model expert behaviors and learns a policy to optimize both the BC loss (conditional) and our proposed diffusion model loss (joint). DBC outperforms baselines in various continuous control tasks in navigation, robot arm manipulation, dexterous manipulation, and locomotion. We design additional experiments to verify the limitations of modeling either the conditional probability or the joint probability of the expert distribution as well as compare different generative models

Dynamic Finite Element Analysis on Underlay Microstructure of Cu/low-k Wafer during Wirebonding

The aim of present research is to investigate dynamic stress analysis for microstructure of Cu/Low-K wafer subjected to wirebonding predicted by finite element software ANSYS/LS-DYNA. Two major analyses are conducted in the present research. In the first, the characteristic of heat affected zone (HAZ) and free air ball (FAB) on ultra thin Au wire have been carefully experimental measured. Secondary, the dynamic response on Al pad/beneath the pad of Cu/low-K wafer during wirebonding process has been successfully predicted by finite element analysis (FEA). Tensile mechanical properties of ultra thin wire before/after electric flame-off (EFO) process have been investigated by self-design pull test fixture. The experimental obtained hardening value has significantly influence on localize stressed area on Al pad. This would result in Al pad squeezing around the smashed FAB during impact stage and the consequent thermosonic vibration stage. Microstructure of FAB and HAZ are also carefully measured by micro/nano indentation instruments. All the measured data serves as material inputs for the FEA explicit software ANSYS/LS-DYNA. Because the crack of low-k layer and delamination of copper via are observed, dynamic transient analysis is performed to inspect the overall stress/strain distributions on the microstructure of Cu/low-k wafer. Special emphasizes are focused on the copper via layout and optimal design of Cu/low-k microstructure. It is also shown that the Al pad can be replaced by Al-Cu alloy pad or Cu pad to avoid large deformation on pad and cracking beneath the surface. A series of comprehensive experimental works and FEA predictions have been performed to increase bondability and reliability in this study

Fabrication of multianalyte CeO2 nanograin electrolyte–insulator–semiconductor biosensors by using CF4 plasma treatment

Multianalyte CeO2 biosensors have been demonstrated to detect pH, glucose, and urine concentrations. To enhance the multianalyte sensing capability of these biosensors, CF4 plasma treatment was applied to create nanograin structures on the CeO2 membrane surface and thereby increase the contact surface area. Multiple material analyses indicated that crystallization or grainization caused by the incorporation of flourine atoms during plasma treatment might be related to the formation of the nanograins. Because of the changes in surface morphology and crystalline structures, the multianalyte sensing performance was considerably enhanced. Multianalyte CeO2 nanograin electrolyte–insulator–semiconductor biosensors exhibit potential for use in future biomedical sensing device applications

Neel tensor torque at the ferromagnet/antiferromagnet interface

Antiferromagnets (AFMs) exhibit spin arrangements with no net magnetization, positioning them as promising candidates for spintronics applications. While electrical manipulation of the single-crystal AFMs, composed of periodic spin configurations, is achieved recently, it remains a daunting challenge to characterize and to manipulate polycrystalline AFMs. Utilizing statistical analysis in data science, we demonstrate that polycrystalline AFMs can be described using a real, symmetric, positive semi-definite, rank-two tensor, which we term the Neel tensor. This tensor introduces a unique spin torque, diverging from the conventional field-like and Slonczewski torques in spintronics devices. Remarkably, Neel tensors can be trained to retain a specific orientation, functioning as a form of working memory. This attribute enables zero-field spin-orbit-torque switching in trilayer devices featuring a heavy-metal/ferromagnet/AFM structure and is also consistent with the X-ray magnetic linear dichroism measurements. Our findings uncover hidden statistical patterns in polycrystalline AFMs and establishes the presence of Neel tensor torque, highlighting its potential to drive future spintronics innovations.Comment: main text 18 pages, supplementary information 10 page

MiR-21 induced angiogenesis through AKT and ERK activation and HIF-1α expression.

MicroRNAs (miRNAs) are endogenous, small noncoding RNAs that play important roles in various cellular functions and tumor development. Recent studies have indicated that miR-21 is one of the important miRNAs associated with tumor growth and metastasis, but the role and molecular mechanism of miR-21 in regulating tumor angiogenesis remain to be elucidated. In this study, miR-21 was overexpressed by transfecting pre-miR-21 into human prostate cancer cells and tumor angiogenesis was assayed using chicken chorioallantoic membrane (CAM). We found that overexpression of miR-21 in DU145 cells increased the expression of HIF-1α and VEGF, and induced tumor angiogenesis. AKT and extracellular regulated kinases (ERK) 1/2 are activated by miR-21. Inhibition of miR-21 by the antigomir blocked this process. Overexpression of the miR-21 target, PTEN, also inhibited tumor angiogenesis by partially inactivating AKT and ERK and decreasing the expression of HIF-1 and VEGF. The AKT and ERK inhibitors, LY294002 and U0126, suppressed HIF-1α and VEGF expression and angiogenesis. Moreover, inhibition of HIF-1α expression alone abolished miR-21-inducing tumor angiogenesis, indicating that HIF-1α is required for miR-21-upregulated angiogenesis. Therefore, we demonstrate that miR-21 induces tumor angiogenesis through targeting PTEN, leading to activate AKT and ERK1/2 signaling pathways, and thereby enhancing HIF-1α and VEGF expression; HIF-1α is a key downstream target of miR-21 in regulating tumor angiogenesis