Nondestructive Measurement Material Characterization of Thermal Sprayed Nickel Aluminum Coatings by using Laser Ultrasound Technique

AbstractThis research focused on characterization of mechanical properties in Nickel-Aluminum coating with different thermal technique and processing parameters at high temperature environment up to 295°C. With the laser ultrasound technique (LUT), guided acoustic waves are generated to propagate on the Ni-Al sprayed coatings. By measuring dispersive phase velocity followed by SCE-UA inversion algorithm. The Young's modulus of coatings which fabricated by HVOF technique is higher than APS technique. This technique is potentially useful to probe the material characterization at high temperature environment in a remote and non-destructive way

Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation

Recently, deep convolutional neural networks (CNNs) have achieved many eye-catching results. However, deploying CNNs on resource-constrained edge devices is constrained by limited memory bandwidth for transmitting large intermediated data during inference, i.e., activation. Existing research utilizes mixed-precision and dimension reduction to reduce computational complexity but pays less attention to its application for activation compression. To further exploit the redundancy in activation, we propose a learnable mixed-precision and dimension reduction co-design system, which separates channels into groups and allocates specific compression policies according to their importance. In addition, the proposed dynamic searching technique enlarges search space and finds out the optimal bit-width allocation automatically. Our experimental results show that the proposed methods improve 3.54%/1.27% in accuracy and save 0.18/2.02 bits per value over existing mixed-precision methods on ResNet18 and MobileNetv2, respectively

The Impacts Of Presentation Modes And Product Involvements On “Line” Short Message Service (SMS) Advertising Effectiveness

In today’s ubiquitous commerce (UC) era, short message service (SMS) advertisement has played an important role in the world of marketing. Convenience and economical reasons influence SMS usage frequency along with social involvement to influence attitudes towards SMS advertising. SMS advertising creates numerous opportunities for the marketers in promoting their products effectively. Adopting the competition for attention theory as the theoretical framework, we developed hypotheses to investigate the influences of presentation mode and involvement on SMS advertising performance (recall of advertising information). An experiment was conducted to examine the effects of three types of information presentation modes (text-only, image-text, and emoji-text) in the contexts of two product types (high- versus low-involvement products) in the “LINE” SMS environment. Specifically, in this current study, we allocate participants to six experimental environments (text-only for high-involvement products, text-only for low-involvement products, image-text for high-involvement products, image-text for low-involvement products, emoji-text for high-involvement products and emoji-text for low-involvement products) randomly to collected empirical data to examine the proposed hypotheses. The research findings are expected to provide instrumental guidelines for the practitioners to better achieve the goals of ads in the “LINE” SMS environment. Also, the empirical results may provide insights into the research of advertising interface design of SMS and integrating efforts from cognitive science and vision research to understand users’ involvement of SMS advertising processes

Seismic analysis of the condensate storage tank in a nuclear power plant

Following the nuclear power plant accident in Fukushima Japan, seismic capacity evaluation has become a crucial issue in combination building safety. Condensate storage tanks are designed to supplies water to the condensate transfer pumps, the control rod drive hydraulic system pumps, and the condenser makeup. A separate connection to the condensate storage tank is used to supply water for the high pressure coolant injection system, reactor core isolation cooling system, and core spray system pumps. A condensate storage tank is defined as a seismic class I structure, playing the important role of providing flow to the operational system and the required static head for the suction of the condensate transfer pumps and the normal supply pump. According to the latest nuclear safety requirements, soil structure interaction must be considered in all seismic analyses. This study aims to rebuild the computer model of condensate storage tanks in Taiwan using the SAP 2000 program in conjunction with the lumped mass stick model and to evaluate the soil structure interaction by employing the SASSI 2000 program. The differences between the results with the soil structure interaction and spring model are compared via natural frequency and response spectrum curves. This computer model enables engineers to rapidly evaluate the safety margin of condensate storage tank following the occurrence of earthquakes or tsunamis

Designing primers and evaluation of the efficiency of propidium monoazide – Quantitative polymerase chain reaction for counting the viable cells of Lactobacillus gasseri and Lactobacillus salivarius

AbstractThe purpose of this study is to evaluate the efficiency of using propidium monoazide (PMA) real-time quantitative polymerase chain reaction (qPCR) to count the viable cells of Lactobacillus gasseri and Lactobacillus salivarius in probiotic products. Based on the internal transcription spacer and 23S rRNA genes, two primer sets specific for these two Lactobacillus species were designed. For a probiotic product, the total deMan Rogosa Sharpe plate count was 8.65±0.69 log CFU/g, while for qPCR, the cell counts of L. gasseri and L. salivarius were 8.39±0.14 log CFU/g and 8.57±0.24 log CFU/g, respectively. Under the same conditions, for its heat-killed product, qPCR counts for L. gasseri and L. salivarius were 6.70±0.16 log cells/g and 7.67±0.20 log cells/g, while PMA-qPCR counts were 5.33±0.18 log cells/g and 5.05±0.23 log cells/g, respectively. For cell dilutions with a viable cell count of 8.5 log CFU/mL for L. gasseri and L. salivarius, after heat killing, the PMA-qPCR count for both Lactobacillus species was near 5.5 log cells/mL. When the PMA-qPCR counts of these cell dilutions were compared before and after heat killing, although some DNA might be lost during the heat killing, significant qPCR signals from dead cells, i.e., about 4–5 log cells/mL, could not be reduced by PMA treatment. Increasing PMA concentrations from 100 μM to 200 μM or light exposure time from 5 minutes to 15 minutes had no or, if any, only minor effect on the reduction of qPCR signals from their dead cells. Thus, to differentiate viable lactic acid bacterial cells from dead cells using the PMA-qPCR method, the efficiency of PMA to reduce the qPCR signals from dead cells should be notable

Mutations in the PKM2 exon-10 region are associated with reduced allostery and increased nuclear translocation.

PKM2 is a key metabolic enzyme central to glucose metabolism and energy expenditure. Multiple stimuli regulate PKM2's activity through allosteric modulation and post-translational modifications. Furthermore, PKM2 can partner with KDM8, an oncogenic demethylase and enter the nucleus to serve as a HIF1α co-activator. Yet, the mechanistic basis of the exon-10 region in allosteric regulation and nuclear translocation remains unclear. Here, we determined the crystal structures and kinetic coupling constants of exon-10 tumor-related mutants (H391Y and R399E), showing altered structural plasticity and reduced allostery. Immunoprecipitation analysis revealed increased interaction with KDM8 for H391Y, R399E, and G415R. We also found a higher degree of HIF1α-mediated transactivation activity, particularly in the presence of KDM8. Furthermore, overexpression of PKM2 mutants significantly elevated cell growth and migration. Together, PKM2 exon-10 mutations lead to structure-allostery alterations and increased nuclear functions mediated by KDM8 in breast cancer cells. Targeting the PKM2-KDM8 complex may provide a potential therapeutic intervention

Modularity of Escherichia coli sRNA regulation revealed by sRNA-target and protein network analysis

<p>Abstract</p> <p>Background</p> <p>sRNAs, which belong to the non-coding RNA family and range from approximately 50 to 400 nucleotides, serve various important gene regulatory roles. Most are believed to be <it>trans</it>-regulating and function by being complementary to their target mRNAs in order to inhibiting translation by ribosome occlusion. Despite this understanding of their functionality, the global properties associated with regulation by sRNAs are not yet understood. Here we use topological analysis of sRNA targets in terms of protein-protein interaction and transcription-regulatory networks in <it>Escherichia coli </it>to shed light on the global correlation between sRNA regulation and cellular control networks.</p> <p>Results</p> <p>The analysis of sRNA targets in terms of their networks showed that some specific network properties could be identified. In protein-protein interaction network, sRNA targets tend to occupy more central positions (higher closeness centrality, <it>p-val </it>= 0.022) and more cliquish (larger clustering coefficient, <it>p-val </it>= 0.037). The targets of the same sRNA tend to form a network module (shorter characteristic path length, <it>p-val </it>= 0.015; larger density, <it>p-val </it>= 0.019; higher in-degree ratio, <it>p-val </it>= 0.009). Using the transcription-regulatory network, sRNA targets tend to be under multiple regulation (higher indegree, <it>p-val </it>= 0.013) and the targets usually are important to the transfer of regulatory signals (higher betweenness, <it>p-val </it>= 0.012). As was found for the protein-protein interaction network, the targets that are regulated by the same sRNA also tend to be closely knit within the transcription-regulatory network (larger density, <it>p-val </it>= 0.036), and inward interactions between them are greater than the outward interactions (higher in-degree ratio, <it>p-val </it>= 0.023). However, after incorporating information on predicted sRNAs and down-stream targets, the results are not as clear-cut, but the overall network modularity is still evident.</p> <p>Conclusions</p> <p>Our results indicate that sRNA targeting tends to show a clustering pattern that is similar to the human microRNA regulation associated with protein-protein interaction network that was observed in a previous study. Namely, the sRNA targets show close interaction and forms a closely knit network module for both the protein-protein interaction and the transcription-regulatory networks. Thus, targets of the same sRNA work in a concerted way toward a specific goal. In addition, in the transcription-regulatory network, sRNA targets act as "multiplexor", accepting regulatory control from multiple sources and acting accordingly. Our results indicate that sRNA targeting shows different properties when compared to the proteins that form cellular networks.</p