Phase field simulation of dendritic microstructure in additively manufactured titanium alloy

Additive manufacturing (AM) processes for metals, such as selective laser sintering and electron beam melting, involve rapid solidification process. The microstructure of the fabricated material and its properties strongly depend on the solidification. Therefore, in order to control and optimize the AM process, it is important to understand the microstructure evolution. In this work, using Ti-6Al-4V as a model system, the phase field method is applied to simulate the microstructure evolution in additively manufactured metals. First, the fundamental governing equations are presented. Then the effects of various processing related parameters, including local temperature gradient, scan speed and cooling rate, on dendrites’ morphology and growth velocity are studied. The simulated results show that the dendritic arms grow along the direction of the heat flow. Higher temperature gradient, scan speed and cooling rate will result in small dendritic arm spacing and higher growth velocity. The simulated dendritic morphology and arm spacings are in good agreement with experimental data and theoretical predictions

Collaborative Representation based Classification for Face Recognition

By coding a query sample as a sparse linear combination of all training samples and then classifying it by evaluating which class leads to the minimal coding residual, sparse representation based classification (SRC) leads to interesting results for robust face recognition. It is widely believed that the l1- norm sparsity constraint on coding coefficients plays a key role in the success of SRC, while its use of all training samples to collaboratively represent the query sample is rather ignored. In this paper we discuss how SRC works, and show that the collaborative representation mechanism used in SRC is much more crucial to its success of face classification. The SRC is a special case of collaborative representation based classification (CRC), which has various instantiations by applying different norms to the coding residual and coding coefficient. More specifically, the l1 or l2 norm characterization of coding residual is related to the robustness of CRC to outlier facial pixels, while the l1 or l2 norm characterization of coding coefficient is related to the degree of discrimination of facial features. Extensive experiments were conducted to verify the face recognition accuracy and efficiency of CRC with different instantiations.Comment: It is a substantial revision of a previous conference paper (L. Zhang, M. Yang, et al. "Sparse Representation or Collaborative Representation: Which Helps Face Recognition?" in ICCV 2011

Reduced glutamine synthetase activity alters the fecundity of female Bactrocera dorsalis (Hendel)

Glutamine synthetase (GS) is a key enzyme in glutamine synthesis and is associated with multiple physiological processes in insects, such as embryonic development, heat shock response, and fecundity regulation. However, little is known about the influence of GS on female fecundity in the oriental fruit fly, Bactrocera dorsalis. Based on the cloning of BdGSs, mitochondrial BdGSm and cytoplasmic BdGSc, we determined their expressions in the tissues of adult B. dorsalis. BdGSm was highly expressed in the fat body, while BdGSc was highly expressed in the head and midgut. Gene silencing by RNA interference against two BdGSs isoforms suppressed target gene expression at the transcriptional level, leading to a reduced ovarian size and lower egg production. The specific inhibitor L-methionine S-sulfoximine suppressed enzyme activity, but only the gene expression of BdGSm was suppressed. A similar phenotype of delayed ovarian development occurred in the inhibitor bioassay. Significantly lower expression of vitellogenin and vitellogenin receptor was observed when GS enzyme activity was suppressed. These data illustrate the effects of two GS genes on adult fecundity by regulating vitellogenin synthesis in different ways

Information Transparency and Impression Management in AI Interviews: The Mediating Role of Perceived Safety

AI interviews have emerged as a critical tool for businesses to perform talent screening. Interviewees frequently use impression management tactics to cope with interview stress. However, the influence of information transparency—a fundamental feature of AI system—on the selection of these tactics remains unclear. Based on transparency research and the Transactional Theory of Stress, we propose that different levels of transparency (through information type combinations) impact interviewees’ perceived safety, thereby affecting their choice of impression management tactics. Furthermore, this study explores the moderating effect of AI familiarity. An experimental approach is proposed to test the conceptual model. This study contributes to the literature by establishing a taxonomy for transparency and shedding light on the nuanced effects of transparency on interviewees’ perceptions and behaviors. The findings are expected to provide insights for refining AI interview systems and management practices, paving the way for future research

Is Natural More Beautiful? Research on Natural Product Preference Based on IAT

This study aims at testing consumers’ preference for natural products behind buying decisions and exploring moderating factors as rural life experience and gender for their effects on natural preference. With the help of implicit association theory, we used IAT (Implicit Association Test) to measure the remoteness between positive words and natural products to identify whether there is an implicit preference. And we examined the moderating effects through online research in China. Three hundred one participants have joined this experiment. The result shows that Chinese consumers do have an implicit preference for natural products. When consumers had more than five years of rural life experience, their preference for natural products was significantly higher than those without. However, gender did not make any significant difference, except that women have more preference for nature in the field of food. Our conclusion not only enriches the understanding of consumer behavior but could also help product designing and development, particularly in the food area

Atomistic modeling of resistivity evolution of copper nanoparticle in intense pulsed light sintering process

In this work, the intense pulsed light (IPL) sintering process of copper nanoparticle ink is simulated using molecular dynamics (MD) method. First, the neck size growth between the two copper nanoparticles during the IPL sintering process is computed. The resultant electrical resistivity is then calculated by substituting the neck size into the Reimann-Weber formula. Overall, a rapid decrease of electric resistivity is observed in the beginning of the sintering, which is caused by quick neck size growth, followed by a gradually decrease of resistivity. In addition, the correlation of the simulated temperature dependent resistivity is similar to that of the experimentally measured resistivity. The MD model is an effective tool for designers to optimize the IPL sintering process

Comparative proteomic profiling reveals molecular characteristics associated with oogenesis and oocyte maturation during ovarian development of Bactrocera dorsalis (Hendel)

Time-dependent expression of proteins in ovary is important to understand oogenesis in insects. Here, we profiled the proteomes of developing ovaries from Bactrocera dorsalis (Hendel) to obtain information about ovarian development with particular emphasis on differentially expressed proteins (DEPs) involved in oogenesis. A total of 4838 proteins were identified with an average peptide number of 8.15 and sequence coverage of 20.79%. Quantitative proteomic analysis showed that a total of 612 and 196 proteins were differentially expressed in developing and mature ovaries, respectively. Furthermore, 153, 196 and 59 potential target proteins were highly expressed in early, vitellogenic and mature ovaries and most tested DEPs had the similar trends consistent with the respective transcriptional profiles. These proteins were abundantly expressed in pre-vitellogenic and vitellogenic stages, including tropomyosin, vitellogenin, eukaryotic translation initiation factor, heat shock protein, importin protein, vitelline membrane protein, and chorion protein. Several hormone and signal pathway related proteins were also identified during ovarian development including piRNA, notch, insulin, juvenile, and ecdysone hormone signal pathways. This is the first report of a global ovary proteome of a tephritid fruit fly, and may contribute to understanding the complicate processes of ovarian development and exploring the potentially novel pest control targets