The curriculum reform of CAD graphic design for combining theory and practice

As a tool course, CAD graphic design in engineering is assisting other professional courses to achieve professional training goals. According to the characteristics and existing problems of CAD graphic design, this paper puts forward some constructive measures to connect the course with practice application and improve the students’ learning enthusiasm. The proposed measures include: teaching method combining theory with practice, teaching mode containing "teaching" and "learning" content, the matched evaluation mechanism guiding correctly students to learn

Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising

Image denoising is a fundamental and challenging task in the field of computer vision. Most supervised denoising methods learn to reconstruct clean images from noisy inputs, which have intrinsic spectral bias and tend to produce over-smoothed and blurry images. Recently, researchers have explored diffusion models to generate high-frequency details in image restoration tasks, but these models do not guarantee that the generated texture aligns with real images, leading to undesirable artifacts. To address the trade-off between visual appeal and fidelity of high-frequency details in denoising tasks, we propose a novel approach called the Reconstruct-and-Generate Diffusion Model (RnG). Our method leverages a reconstructive denoising network to recover the majority of the underlying clean signal, which serves as the initial estimation for subsequent steps to maintain fidelity. Additionally, it employs a diffusion algorithm to generate residual high-frequency details, thereby enhancing visual quality. We further introduce a two-stage training scheme to ensure effective collaboration between the reconstructive and generative modules of RnG. To reduce undesirable texture introduced by the diffusion model, we also propose an adaptive step controller that regulates the number of inverse steps applied by the diffusion model, allowing control over the level of high-frequency details added to each patch as well as saving the inference computational cost. Through our proposed RnG, we achieve a better balance between perception and distortion. We conducted extensive experiments on both synthetic and real denoising datasets, validating the superiority of the proposed approach

HDRFlow: Real-Time HDR Video Reconstruction with Large Motions

Reconstructing High Dynamic Range (HDR) video from image sequences captured with alternating exposures is challenging, especially in the presence of large camera or object motion. Existing methods typically align low dynamic range sequences using optical flow or attention mechanism for deghosting. However, they often struggle to handle large complex motions and are computationally expensive. To address these challenges, we propose a robust and efficient flow estimator tailored for real-time HDR video reconstruction, named HDRFlow. HDRFlow has three novel designs: an HDR-domain alignment loss (HALoss), an efficient flow network with a multi-size large kernel (MLK), and a new HDR flow training scheme. The HALoss supervises our flow network to learn an HDR-oriented flow for accurate alignment in saturated and dark regions. The MLK can effectively model large motions at a negligible cost. In addition, we incorporate synthetic data, Sintel, into our training dataset, utilizing both its provided forward flow and backward flow generated by us to supervise our flow network, enhancing our performance in large motion regions. Extensive experiments demonstrate that our HDRFlow outperforms previous methods on standard benchmarks. To the best of our knowledge, HDRFlow is the first real-time HDR video reconstruction method for video sequences captured with alternating exposures, capable of processing 720p resolution inputs at 25ms.Comment: CVPR 2024; Project website: https://openimaginglab.github.io/HDRFlow

Exploration on the Construction of Digital Content Security Course under the Background of "New Engineering Disciplines"

According to the development and construction of the "new engineering disciplines", the training requirements for talents and the construction of digital content security course are discussed in this paper. Based on the current development situation, this paper clarifies the tightness of digital content security and the development of "new engineering disciplines". The digital content security course has both a complete frontier theoretical system and close correlation with various new engineering disciplines. Combining these two characteristics, this paper proposes three aspects of construction: comprehensive social resources, the formation of a new curriculum teaching system, and the creation of a digital content security gold course; further introduction of school-enterprise cooperation, promotion of the combination of production and education, practical and targeted activities; training of students’ ability to master and apply digital content security and promotion of the construction of applied undergraduate programs

Tanshinone IIa protects retinal endothelial cells against mitochondrial fission induced by methylglyoxal through glyoxalase 1

Advanced glycation end products (AGEs) play an important role in the onset of diabetic retinopathy. Therefore, in the current study, we investigate whether and how Tanshinone IIa (Tan IIa) from Salvia miltiorrhiza protects bovine retinal endothelial cells (BRECs) against methylglyoxal (MGO) mediated cell dysfunction. The results showed that MGO reduced cell viability in dose dependent manner. The treatment of Tan IIa (50 μM) significantly improved cell viability induced by MGO in BRECs. MGO increased cellular reactive oxygen species formation and cellular nitric oxide (NO) level; enhanced nox1 and iNOS mRNA levels; inhibited prdx1 mRNA level. The treatment of Tan IIa effectually ameliorated cellular oxidative stress. Exposure of MGO resulted in mitochondrial fission and decrease of opa1 and mfn1. No significant difference in mRNA levels of mfn2 and drp1 was detected between MGO and medium. Tan IIa reduced mitochondrial fragmentation, enhanced the mRNA levels of mfn1 and opa1 in MGO cultured BRECs. The short time exposure of cellular antioxidatants, dimethylthiourea (10 mM) and tiron (10 mM) had no effect on mitochondrial fission although they ameliorated cellular reactive oxygen species level. Moreover, overexpression of glyoxalase 1 (GLO1) increased key proteins of mitochondrial fusion, including opa1 and mfn1 in BRECs cultured with MGO. However, inhibition of GLO1 by siRNA abolished the effect of Tan IIa on induction of mitochondrial fusion in MGO cultured BRECs. In conclusion, MGO caused the injury of retinal endothelial cells through induction of mitochondrial dysfunction and mitochondrial fission, the treatment of Tan IIa ameliorated mitochondrial dysfunction and fission induced by AGEs through enhancing GLO1

2000-2020 NHIS Studies: Factors affecting medication adherence rate in the pediatric population with medical complexity

Introduction Children with medical complexity belong to a vulnerable patient population group that is defined by the interplay of chronic health conditions, high healthcare utilization, and severe limitations in cognitive and/or physical functioning. Members of this patient population often require a complex management and/or treatment regimen with the use of more than one medication. Pediatric nonadherence in medication can lead to increases in microbial resistance, adverse drug reactions, morbidity, and mortality. The consequences of this medication nonadherence may also cause slower recovery times, increased number of emergency department visits, and hospitalizations, which subsequently substantiates higher medical costs for families along with the healthcare system. General factors for pediatric medical adherence include age, culture, family structure, socioeconomic status, schedule of medication therapy, and taste/formulation of therapy. Continual studies on these medical adherence factors are of the utmost importance to mitigate nonadherence improving quality of life and reducing medical costs. This study examines the variables and confounding factors that may be responsible for the prevalence of nonadherence in this patient population. Methods Twelve primary articles using data collected through the National Health Interview Survey (NHIS) – focused on medication adherence secondary to medication therapy management (MTM) in the pediatric population across various chronic disease states –were examined and analyzed to collect the variables and factors of interest. Each article in the review was chosen to analyze a national representation of U.S. children between the years 2000-2020. The age perimeter was between ages zero (infants) to eighteen. Results Among the fifteen NHIS papers measuring medication adherence outcomes, three addressed financial and family disparities, three focused on the racial disparities’ association, and the remaining nine papers address other confounding factors (including but not limited to geographic location, patient education, and healthcare access). Results from the analysis confirmed the influence that racial/ethnic and/or socioeconomic disparities have on the medication adherence rate of the US pediatric population with medical complexity. Conclusion The medication adherence rate is affected by racial and ethnic disparities, financial hardships, socioeconomic status, family background education, poverty status, children’s health status, quality of patient education, and religious beliefs. This calls for more public health policies to alleviate the financial burden of medication costs, as well as efforts to improve medication education for the caregivers of children with medical complexity population in the U.S. The data-collecting phase of this research reveals the scarcity of studies on this topic – as reflected in the small number of articles found and reviewed. For a better understanding of the medication adherence rate among the medically complex pediatric population of the U.S., further research on this topic should be conducted

The Highest Melting Point Material: Searched by Bayesian Global Optimization with Deep Potential Molecular Dynamics

The interest in refractory materials is increasing rapidly in recent decades due to the development of hypersonic vehicles. However, which substance has the highest melting point keeps a secret, since precise measurements in extreme condition are overwhelmingly difficult. In the present work, an accurate deep potential model of Hf-Ta-C-N system was firstly trained, and then applied to search for the highest melting point material by using molecular dynamics simulation and Bayesian global optimization. The predicted melting points agree well with experiments, and confirm that the carbon site vacancy can enhance melting points of rock-salt structure carbides. Solid solution with N is verified as another new and more effective melting point enhancing approach for HfC, while the conventional routing of solid solution with Ta (e.g. HfTa4C5) is not suggested to result in a maximum melting point. The highest melting point (~ 4236 K) is achieved with composition of HfC0.638N0.271, which is ~ 80 K higher than the highest value in Hf-C binary system. The dominating mechanism of N addition is believed to be the instable C-N and N-N bonds in liquid phase, which reduces the liquid phase entropy and renders the liquid phase less stable. The improved melting point and fewer gas generation during oxidation by addition of N provides new routing to modify the thermal protection materials for hypersonic vehicles

Unpacking How Decentralized Autonomous Organizations (DAOs) Work in Practice

Decentralized Autonomous Organizations (DAOs) have emerged as a novel way to coordinate a group of (pseudonymous) entities towards a shared vision (e.g., promoting sustainability), utilizing self-executing smart contracts on blockchains to support decentralized governance and decision-making. In just a few years, over 4,000 DAOs have been launched in various domains, such as investment, education, health, and research. Despite such rapid growth and diversity, it is unclear how these DAOs actually work in practice and to what extent they are effective in achieving their goals. Given this, we aim to unpack how (well) DAOs work in practice. We conducted an in-depth analysis of a diverse set of 10 DAOs of various categories and smart contracts, leveraging on-chain (e.g., voting results) and off-chain data (e.g., community discussions) as well as our interviews with DAO organizers/members. Specifically, we defined metrics to characterize key aspects of DAOs, such as the degrees of decentralization and autonomy. We observed CompoundDAO, AssangeDAO, Bankless, and Krausehouse having poor decentralization in voting, while decentralization has improved over time for one-person-one-vote DAOs (e.g., Proof of Humanity). Moreover, the degree of autonomy varies among DAOs, with some (e.g., Compound and Krausehouse) relying more on third parties than others. Lastly, we offer a set of design implications for future DAO systems based on our findings