Associating Academic Identity with Language Socialization in Virtual Community: A Case Study of a Chinese Graduate Student’s Learning Experiences in Religion Studies

This longitudinal case study explored the academic identity and language socialization of a Chinese graduate student enrolled in an online religion course at a U.S. university during the COVID-19 pandemic. Data were collected via online classroom observations, oral interviews, and artifacts. The theoretical framework was taken from language socialization and identity, together with positioning theory. The study differs from previous research, arguing that instead of language competence, the constructed academic identity is occasionally crucial for the successful academic discourse socialization of international students in bilingual and virtual settings. Moreover, the inclination toward interactive positioning between students and instructors can arise and advance in virtual academic communities and, while students’ academic identities might be resistant to change, they can be negatively impacted by disorganized course design. The conclusion sheds light on first and second language socialization through which international graduate students can navigate and maintain their academic identities within digitally mediated and multilingual learning environments

Learning Dense Correspondences between Photos and Sketches

Humans effortlessly grasp the connection between sketches and real-world objects, even when these sketches are far from realistic. Moreover, human sketch understanding goes beyond categorization -- critically, it also entails understanding how individual elements within a sketch correspond to parts of the physical world it represents. What are the computational ingredients needed to support this ability? Towards answering this question, we make two contributions: first, we introduce a new sketch-photo correspondence benchmark, $\textit{PSC6k}$, containing 150K annotations of 6250 sketch-photo pairs across 125 object categories, augmenting the existing Sketchy dataset with fine-grained correspondence metadata. Second, we propose a self-supervised method for learning dense correspondences between sketch-photo pairs, building upon recent advances in correspondence learning for pairs of photos. Our model uses a spatial transformer network to estimate the warp flow between latent representations of a sketch and photo extracted by a contrastive learning-based ConvNet backbone. We found that this approach outperformed several strong baselines and produced predictions that were quantitatively consistent with other warp-based methods. However, our benchmark also revealed systematic differences between predictions of the suite of models we tested and those of humans. Taken together, our work suggests a promising path towards developing artificial systems that achieve more human-like understanding of visual images at different levels of abstraction. Project page: https://photo-sketch-correspondence.github.ioComment: Accepted to ICML 2023. Project page: https://photo-sketch-correspondence.github.i

GPT-4-powered analysis and prediction of selective catalytic reduction experiments through an effective chain-of-thought prompting strategy

This study explores the use of Large Language Models (LLMs) in interpreting and predicting experimental outcomes based on given experimental variables, leveraging the human-like reasoning and inference capabilities of LLMs, using selective catalytic reduction of NOx with NH3 as a case study. We implement the Chain of Thought (CoT) concept to formulate logical steps for uncovering connections within the data, introducing an "Ordered-and-Structured" CoT (OSCoT) prompting strategy. We compare the OSCoT strategy with the more conventional "One-Pot" CoT (OPCoT) approach and with human experts. We demonstrate that GPT-4, equipped with this new OSCoT prompting strategy, outperforms the other two settings and accurately predicts experimental outcomes and provides intuitive reasoning for its predictions

Survey on Disposal Behaviour and Awareness of Mobile Phones in Chinese University Students

AbstractRetired mobile phones represent the most valuable electrical and electronic equipment in the main waste stream because of such characteristics as large quantity, high reuse/recovery value and fast replacement frequency. An online survey was conducted in the university students in China to identify the disposal behaviour and awareness of mobile phones, which will promote sustainable management of retired mobile phones. The results show that about 22% of the respondents replace their mobile phones annually, while most respondents replace their phones in 2-3 years. The most common reason for mobile phones replacement is the physical broken. 64% of the respondents stockpile their most recently retired phones mainly due to lack of formal management system. The survey results on mobile phones consumers’ environmental awareness also can help improve the policy-making. Nearly 50% of the respondents believe the recycling cost of the retired phones should be shared by all the stakeholders. The incentives with cash or voucher will be the efficient take-back approach. Some suggestions for constructing efficient management system for retired mobile phones are given based on the results and discussions, in which the important effects of the monetary incentives and targeted publicity are emphasized

Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

<p>Abstract</p> <p>Background</p> <p>WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of <it>OsWD40 </it>genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice.</p> <p>Results</p> <p>In this study, we identify and analyze 200 potential <it>OsWD40 </it>genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of <it>OsWD40 </it>were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 <it>OsWD40 </it>genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the <it>OsWD40 </it>genes in rice. The results suggested that <it>OsWD40 </it>genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that <it>OsWD40 </it>genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network.</p> <p>Conclusions</p> <p>All of these analyses suggest that the functions of <it>OsWD40 </it>genes are diversified, which provide useful references for selecting candidate genes for further functional studies.</p

Hydrological Drought Forecasting and Assessment Based on the Standardized Stream Index in the Southwest China

AbstractSouthwest China is abundant of rainfall and water resources, however, severe and extremely droughts hits it more frequently in recent years, caused huge loss of human lives and financial damages. To investigate the feasibility of the standardized stream index in Southwest China, the Nanpanjiang River basin above the Xiaolongtan hydrological station was selected as the case study site. Based on long-term daily hydrological and meteorological data series, the generated runoff was simulated by the daily Xinanjiang model, then the standardized stream index was calculated and its feasibility was explored by comparing it with other two hydrological drought index. The result revealed that the standardized stream index performed well in detecting the onset, severity and duration in 2009/2010 extremely drought. The output of the paper could provide valuable references for the regional and national drought monitoring and forecasting systems

Unconventional many-body phase transitions in a non-Hermitian Ising chain

We study many-body phase transitions in a one-dimensional ferromagnetic transversed field Ising model with an imaginary field and show that the system exhibits three phase transitions: one second-order phase transition and two $\mathcal{PT}$ phase transitions. The second-order phase transition occurring in the ground state is investigated via biorthogonal and self-normal entanglement entropy, for which we develop an approach to perform finite-size scaling theory to extract the central charge for small systems. Compared with the second-order phase transition, the first $\mathcal{PT}$ transition is characterized by the appearance of an exceptional point in the full energy spectrum, while the second $\mathcal{PT}$ transition only occurs in specific excited states. Furthermore, we interestingly show that both of exceptional points are second-order in terms of scalings of imaginary parts of the energy. This work provides an exact solution for unconventional many-body phase transitions in non-Hermitian systems.Comment: 7 pages, 5 figure

Solid solution softening or hardening induced by minor substitutional additions in a Hf20Nb31Ta31Ti18 refractory high entropy alloy

The effect of minor additions of substitutional elements such as Al, Cu, Mn, and Fe on the room-temperature (RT) and elevated-temperature hardness of a single bcc phase Hf20Nb31Ta31Ti18 refractory high entropy alloy is studied here. Interestingly, 2.5 at. % nominal addition of Fe hardened the base Hf20Nb31Ta31Ti18 alloy in the temperature range from RT to 800 \ub0C, while the same nominal content of addition of Al, Cu, and Mn softened the base alloy from RT to 1000 \ub0C. Regardless of solid solution hardening or solid solution softening, the hardness variation with temperature essentially showed the same three-stage pattern for all studied alloys here: a temperature-dependent decrease in hardness below 300 \ub0C/400 \ub0C, followed by a temperature-independent hardness plateau between 300/400 and 800 \ub0C, and finally a temperature-dependent decrease in hardness at temperatures higher than 800 \ub0C. The mechanism for solid solution hardening or softening in bcc-structured refractory high entropy alloys is discussed, together with their temperature dependence

Neural Super-Resolution for Real-time Rendering with Radiance Demodulation

Rendering high-resolution images in real-time applications (e.g., video games, virtual reality) is time-consuming, thus super-resolution technology becomes more and more crucial in real-time rendering. However, it is still challenging to preserve sharp texture details, keep the temporal stability and avoid the ghosting artifacts in the real-time rendering super-resolution. To this end, we introduce radiance demodulation into real-time rendering super-resolution, separating the rendered image or radiance into a lighting component and a material component, due to the fact that the light component tends to be smoother than the rendered image and the high-resolution material component with detailed textures can be easily obtained. Therefore, we perform the super-resolution only on the lighting component and re-modulate with the high-resolution material component to obtain the final super-resolution image. In this way, the texture details can be preserved much better. Then, we propose a reliable warping module by explicitly pointing out the unreliable occluded regions with a motion mask to remove the ghosting artifacts. We further enhance the temporal stability by designing a frame-recurrent neural network to aggregate the previous and current frames, which better captures the spatial-temporal correlation between reconstructed frames. As a result, our method is able to produce temporally stable results in real-time rendering with high-quality details, even in the highly challenging 4 $\times$ 4 super-resolution scenarios