Enhancing the lift-off performance of EMATs by applying an Fe3O4 coating to a test specimen

Electromagnetic acoustic transducers (EMATs) are non-contact ultrasonic transducers. The transduction efficiency of a particular EMAT on a given specimen is dependent on the lift-off distance, which is the distance between the EMAT coil and the specimen surface. The transduction efficiency drops dramatically with increased lift-off distance, requiring EMATs to be in close proximity to the specimen, usually within a few millimetres. This paper proposes a new EMAT method of applying an Fe 3 O 4 coating to the test specimen, and quantitatively studying the enhancement effect of Fe 3 O 4 coating on lift-off distance. To eliminate the interference of the electrical and magnetic properties of the tested specimen, a non-magnetic and non-conductive glass specimen is selected. The experimental results on a glass substrate coated with Fe 3 O 4 demonstrate the feasibility of EMATs generating and receiving ultrasonic waves through the coating, by a magneto-elastic mechanism. The transduction efficiency of EMATs on an Fe 3 O 4 coating does not increase linearly with the bias static magnetic field, and the maximum measured signal amplitude value occurs at a relatively low flux density of ~0.12 T. More specifically, it has been shown the Fe 3 O 4 coating can significantly enhance the lift-off distance of EMATs operating at 4 MHz to 8 mm on coated stainless steel. The performance of the Fe 3 O 4 coating can be optimized, showing considerable potential to expand the application range of EMATs

Population genomics of an icefish reveals mechanisms of glacier-driven adaptive radiation in Antarctic notothenioids

Background Antarctica harbors the bulk of the species diversity of the dominant teleost fish suborder—Notothenioidei. However, the forces that shape their evolution are still under debate. Results We sequenced the genome of an icefish, Chionodraco hamatus, and used population genomics and demographic modelling of sequenced genomes of 52 C. hamatus individuals collected mainly from two East Antarctic regions to investigate the factors driving speciation. Results revealed four icefish populations with clear reproduction separation were established 15 to 50 kya (kilo years ago) during the last glacial maxima (LGM). Selection sweeps in genes involving immune responses, cardiovascular development, and photoperception occurred differentially among the populations and were correlated with population-specific microbial communities and acquisition of distinct morphological features in the icefish taxa. Population and species-specific antifreeze glycoprotein gene expansion and glacial cycle-paced duplication/degeneration of the zona pellucida protein gene families indicated fluctuating thermal environments and periodic influence of glacial cycles on notothenioid divergence. Conclusions We revealed a series of genomic evidence indicating differential adaptation of C. hamatus populations and notothenioid species divergence in the extreme and unique marine environment. We conclude that geographic separation and adaptation to heterogeneous pathogen, oxygen, and light conditions of local habitats, periodically shaped by the glacial cycles, were the key drivers propelling species diversity in Antarctica.info:eu-repo/semantics/publishedVersio

An empirical study of Agile planning critical success factors

Context. With the popularity of Agile methods, many studies about Agile software development has been done by researchers. Among the phases in Agile software projects, planning is critical because it provides an overview of the project and a guiding of future work. In addition, success factors are also mandatory to the success of Agile software development. The current literature focus on the success factors during the whole lifecycle rather than planning phase, and they don’t make an in-depth analysis on the factors. In this thesis, we perform an empirical study to deeply study the critical success factors at agile planning phase. Objectives. The main aim of our research is to identify the critical success factors at Agile planning phase and challenges associated with each factor. We list four objectives to support our main aim. First is to investigate the factors that are mandatory to the success of Agile software development at planning phase. Second is to investigate the challenges associated with each factor. Third is to find out the ways to address these challenges. The last is to identify the consequence of not ensuring these factors. Methods. We employed two research methods: systematic mapping and survey. Systematic mapping is used to identify the critical success factors of entire lifecycle in current literature. To find critical success factors at agile planning phase and make in-depth analysis, we conducted a survey based on an online questionnaire. The online questionnaire was consisted of open-ended questions and was sent to respondents who have experience on Agile development. Results. Through systematic mapping, we identified 13 papers and 47 critical success factors for Agile software development. We also made a frequency analysis for these factors and they will be the effective evidence to support the results of survey. Through the survey, we identified 13 critical success factors at agile planning and made an in-depth analysis for these 13 factors. These 13 factors are divided into two categories: people factor (individual-level, team-level) and process factor. Through the contrastive analysis of mapping results and survey results, we found that 7 factors of survey results are same or similar with some factors shown in mapping. The other 6 factors of survey are first shown. Conclusions. The factors proposed in this thesis are proved that they are important to the success of the project at planning phase. Failure to consider these critical success factors may lead to inefficient planning and even result in the failure ofthe whole project. The challenges and corresponding solutions can help organizations well manage these critical success factors. In conclusion, these detailed descriptions of critical success factors can be used as a guideline to help people increase the chance of successfully developing software with high quality and low cost in practice.

Development of a magnetostrictive Fe3O4-film electromagnetic acoustic transducer

The magnetostrictive Fe3O4-film electromagnetic acoustic transducer (EMAT) consists of a magnet, a coil, and a magnetostrictive Fe3O4-film bonded to a sample, which can be implemented on parts that are complex shaped, or have uneven or rough surfaces. In this short communication, high transduction efficiency of the proposed EMAT is demonstrated, with a signal-to-noise ratio of up to 50.3 dB, which is beneficial for industrial ultrasonic testing. The proposed EMAT is studied under varying bias magnetic fields and dynamic alternating magnetic fields, to improve transduction efficiency by optimizing the transducer design. The experimental results show a significant nonlinear relationship between the amplitude of the received signal and the strength of the bias magnetic field strength. The horizontal and vertical bias magnetic fields corresponding to the maximum amplitude of the received signal are approximately 0.1 T and 0.14 T, respectively. The amplitude of the received signal varies linearly with the strength of the dynamic magnetic field provided by the EMAT. This investigation represents a further development of magnetostrictive film EMATs, and widens the potential for industrial applications

Cut-off frequency analysis of SH-like guided waves in the three-dimensional component with variable width

The component with variable width (such as railway turnout) is one of the most critical configurations in infrastructure. Guided waves have already been employed for flat plates, however, the influence of cross-section width change for guided waves can’t be ignored. In this study, the theoretical cut-off frequency of shear-horizontal (SH)-like guided waves in rectangular plate was analysed. The dispersion curves of rectangular plate with different widths were calculated by the periodic finite element (FE) method. Theoretical calculations and dispersion curves both show that the cut-off frequency of SH-like guided waves decreases when the width of rectangular plate increases. A periodic-permanent-magnet (PPM) electromagnetic-acoustic-transducer (EMAT) at the excitation frequency of 200 kHz was constructed and used in the experiments to generate SH-like guided waves on rectangular plates with the widths of 12 mm and 20 mm, respectively. Experimental results show that multiple wave modes of SH-like guided waves appear as the width of the rectangular plate increases. When the SH-like guided waves propagates in a rectangular plate with variable width, the high-order modes will be cut-off and reflected as the width decreases

A New Adjustment Strategy to Relieve Inhibition during Anaerobic Codigestion of Food Waste and Cow Manure

A new adjustment strategy (controlling temperature, pH, inoculum dose, and liquid supernatant replacement in different digestion stages) was used to relieve volatile fatty acid (VFA) inhibition during anaerobic codigestion of FW and CM. Three digestion stages and groups were designed: initial stage (on days 1−5 the temperature was 45 °C), the second stage (on days 6−10 the temperature was 35 °C and inoculum was supplied), and the third stage (on days 11−50 the temperature was 35 °C and liquid supernatant was replaced). Groups A, B, and C had initial inoculums of 0, 100, and 200 mL and were supplied inoculums of 200, 100, and 0 mL, respectively. Results showed that in the initial stage, Group A had the highest VFA concentration (876.54 mg/L) and the lowest pH (3.6). In the second and third stages, pH (~5.5 and ~7.5) and VFA concentrations showed no significant differences in all groups. The highest VFA concentration (3248 mg/L), volatile solid (VS) removal rate (49.72%), and total methane production (TMP) (10,959 mL), the shortest λ (19.92 d), and the T90% (39.25 d) were obtained in Group B (pH 8.5). Group C had the highest chemical oxygen demand (COD) removal rate (96.91%). Group A obtained the maximal TBP of 25,626 mL (pH 8.0)

CoreRec: A Counterfactual Correlation Inference for Next Set Recommendation

Next set recommendation aims to predict the items that are likely to be bought in the next purchase. Central to this endeavor is the task of capturing intra-set and cross-set correlations among items. However, the modeling of cross-set correlations poses challenges due to specific issues. Primarily, these correlations are often implicit, and the prevailing approach of establishing an indiscriminate link across the entire set of objects neglects factors like purchase frequency and correlations between purchased items. Such hastily formed connections across sets introduce substantial noise. Additionally, the preeminence of high-frequency items in numerous sets could potentially overshadow and distort correlation modeling with respect to low-frequency items. Thus, we devoted to mitigating misleading inter-set correlations. With a fresh perspective rooted in causality, we delve into the question of whether correlations between a particular item and items from other sets should be relied upon for item representation learning and set prediction. Technically, we introduce the Counterfactual Correlation Inference framework for next set recommendation, denoted as CoreRec. This framework establishes a counterfactual scenario in which the recommendation model impedes cross-set correlations to generate intervened predictions. By contrasting these intervened predictions with the original ones, we gauge the causal impact of inter-set neighbors on set prediction—essentially assessing whether they contribute to spurious correlations. During testing, we introduce a post-trained switch module that selects between set-aware item representations derived from either the original or the counterfactual scenarios. To validate our approach, we extensively experiment using three real-world datasets, affirming both the effectiveness of CoreRec and the cogency of our analytical approach

A 1+1 D Multiphase Proton Exchange Membrane Fuel Cell Model for Real-Time Simulation

International audienceA 1+1-dimensional(1+1D) multiphase model of proton exchangemembrane fuel cell (PEMFC) is developed to simulate the dynamicbehaviors of the fuel cell under various operating conditions.Electrochemical, fluidic, and thermal physical phenomena are takeninto account, and the model can accurately describe themulti-physical processes inside the PEMFC. Meanwhile, the waterphase change and nitrogen crossover are also considered in thismodel. The developed model can simulate the fuel cell behaviors inboth normal temperature and cold start conditions. Selection of thetime step size is discussed, and the solution method of thereal-time model is proposed. Computational efficiency is greatlyimproved by simplifying the multicomponent diffusion inside themembrane electrode assembly (MEA), which results in the shortercalculation time than the simulated physical time. The proposedmodel is suitable for embedded applications, such as real-timesimulation or online diagnostic control. The comprehensive modelvalidation is carried out by comparing the simulation results,including polarization curves, ohmic resistance, local currentdensity distribution, and voltage evolution, under various workingconditions of steady state, load change, and cold start, and a goodagreement is achieved. Finally, some simulation cases are studiedto further demonstrate the simulation ability of the model