The Impact of Digital Media, Virtual Reality, and Computer-generated art on Traditional Art Forms

This paper explores the profound influence of digital media, virtual reality (VR), and computer-generated art on traditional art forms. In the age of technological advancement, these digital mediums have not only redefined the boundaries of artistic expression but have also transformed how audiences engage with art. This study delves into the evolution of art in the digital era, emphasizing the ways in which traditional art forms are adapting, converging, and thriving within the digital landscape. Through case studies, historical analysis, and critical examination, we demonstrate the multifaceted impact of these digital innovations on the traditional arts. We also highlight the potential for synergy between digital and traditional art, fostering a new era of creativity and artistic exploration

SIAD: Self-supervised Image Anomaly Detection System

Recent trends in AIGC effectively boosted the application of visual inspection. However, most of the available systems work in a human-in-the-loop manner and can not provide long-term support to the online application. To make a step forward, this paper outlines an automatic annotation system called SsaA, working in a self-supervised learning manner, for continuously making the online visual inspection in the manufacturing automation scenarios. Benefit from the self-supervised learning, SsaA is effective to establish a visual inspection application for the whole life-cycle of manufacturing. In the early stage, with only the anomaly-free data, the unsupervised algorithms are adopted to process the pretext task and generate coarse labels for the following data. Then supervised algorithms are trained for the downstream task. With user-friendly web-based interfaces, SsaA is very convenient to integrate and deploy both of the unsupervised and supervised algorithms. So far, the SsaA system has been adopted for some real-life industrial applications.Comment: 4 pages, 3 figures, ICCV 2023 Demo Trac

Comparison of Newtonian and Non-newtonian Fluid Models in Blood Flow Simulation in Patients With Intracranial Arterial Stenosis

BACKGROUND: Newtonian fluid model has been commonly applied in simulating cerebral blood flow in intracranial atherosclerotic stenosis (ICAS) cases using computational fluid dynamics (CFD) modeling, while blood is a shear-thinning non-Newtonian fluid. We aimed to investigate the differences of cerebral hemodynamic metrics quantified in CFD models built with Newtonian and non-Newtonian fluid assumptions, in patients with ICAS. METHODS: We built a virtual artery model with an eccentric 75% stenosis and performed static CFD simulation. We also constructed CFD models in three patients with ICAS of different severities in the luminal stenosis. We performed static simulations on these models with Newtonian and two non-Newtonian (Casson and Carreau-Yasuda) fluid models. We also performed transient simulations on another patient-specific model. We measured translesional pressure ratio (PR) and wall shear stress (WSS) values in all CFD models, to reflect the changes in pressure and WSS across a stenotic lesion. In all the simulations, we compared the PR and WSS values in CFD models derived with Newtonian, Casson, and Carreau-Yasuda fluid assumptions. RESULTS: In all the static and transient simulations, the Newtonian/non-Newtonian difference on PR value was negligible. As to WSS, in static models (virtual and patient-specific), the rheological difference was not obvious in areas with high WSS, but observable in low WSS areas. In the transient model, the rheological difference of WSS areas with low WSS was enhanced, especially during diastolic period. CONCLUSION: Newtonian fluid model could be applicable for PR calculation, but caution needs to be taken when using the Newtonian assumption in simulating WSS especially in severe ICAS cases

Comparison of the effects of rumen-protected and unprotected L-leucine on fermentation parameters, bacterial composition, and amino acids metabolism in in vitro rumen batch cultures

This study was conducted to compare the effects of rumen-protected (RP-Leu) and unprotected L-leucine (RU-Leu) on the fermentation parameters, bacterial composition, and amino acid metabolism in vitro rumen batch incubation. The 5.00 g RP-Leu or RU-Leu products were incubated in situ in the rumen of four beef cattle (Bos taurus) and removed after 0, 2, 4, 6, 12, 16, and 24 h to determine the rumen protection rate. In in vitro incubation, both RP-Leu and RU-Leu were supplemented 1.5 mmol/bottle (L-leucine HCl), and incubated after 0, 2, 4, 6, 8, 12, and 16 h to measure gas production (GP), nutrient degradability, fermentation parameters, bacterial composition, and amino acids metabolism. Results from both in vitro and in situ experiments confirmed that the rumen protection rate was greater (p < 0.01) in RP-Leu than in RU-Leu, whereas the latter was slow (p < 0.05) degraded within incubation 8 h. Free leucine from RP-Leu and RU-Leu reached a peak at incubation 6 h (p < 0.01). RU-Leu supplementation increased (p < 0.05) gas production, microbial crude protein, branched-chain AAs, propionate and branched-chain VFAs concentrations, and Shannon and Sobs index in comparison to the control and RP-Leu supplementation. RU-Leu and RP-Leu supplementation decreased (p < 0.05) the relative abundance of Bacteroidota, which Firmicutes increased (p < 0.05). Correlation analysis indicated that there are 5 bacteria at the genus level that may be positively correlated with MCP and propionate (p < 0.05). Based on the result, we found that RP-Leu was more stable than RU-Leu in rumen fluid, but RU-Leu also does not exhibit rapid degradation by ruminal microbes for a short time. The RU-Leu was more beneficial in terms of regulating rumen fermentation pattern, microbial crude protein synthesis, and branched-chain VFAs production than RP-Leu in vitro rumen conditions

Eastern Cooperative Oncology Group, β2-microglobulin, hemoglobin, and lactate dehydrogenase can predict early grade ≥ 3 infection in patients with newly diagnosed multiple myeloma: A real-world multicenter study

IntroductionThis research explored the clinical application of grade ≥ 3 infection predictive models for the newly diagnosed multiple myeloma (NDMM) population.MethodsIt evaluated 306 patients with NDMM based on three different predictive models. The relationship between the grade ≥ 3 infection rates in NDMM and the scores was analyzed retrospectively. The cumulative incidence of early grade ≥ 3 infection was estimated using the Kaplan–Meier method and log-rank test to assess the statistical significance of the difference. To compare the predictive performance in the prediction of infection, the Receiver Operating Characteristic Curve (ROC) curve was used to show the area under the curve (AUC), and DeLong’s test was used to analyze the difference in AUC.ResultsThe incidence of grade ≥ 3 infection within the first 4 months of NDMM was 40.20%. Concerning the FIRST score (predictors: ECOG, β2-microglobulin, hemoglobin, and lactate dehydrogenase), GEM-PETHEMA score (predictors: albumin, male sex, ECOG, and non-IgA type MM), and Infection Risk model of Multiple Myeloma (IRMM) score (predictors: ECOG, serum β2-microglobulin, globulin, and hemoglobin), the probability of early grade ≥ 3 infection in the different groups showed statistically significant differences (low-risk vs. high-risk: 25.81% vs. 50.00%, p < 0.001; low-risk vs. moderate-risk vs. high-risk: 35.93% vs. 41.28% vs. 60.00%, p= 0.045; low-risk vs. moderate-risk vs. high-risk: 20.00% vs. 43.75% vs. 52.04%, p < 0.001). Statistical differences existed in the probability of early grade ≥ 3 infection among the different groups by the FIRST and IRMM scores but no statistical differences in the GEM-PETHEMA score (p < 0.001, p< 0.001, and p = 0.090, respectively). The FIRST score showed good discrimination and simple calculation with highest AUC. Further subgroup analysis showed that the FIRST score could still apply for patients treated with bortezomib-based regimen and frail patients.DiscussionOur findings indicate that the FIRST score (consisting of ECOG, β2-microglobulin, hemoglobin, and lactate dehydrogenase) is a simple and robust infection stratification tool for patients with NDMM and could be used in routine clinical work

Identification and validation of a platelet-related signature for predicting survival and drug sensitivity in multiple myeloma

Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma.Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups.Results: By using the platelet-related risk model, we were able to predict patients’ prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p < 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p < 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467–2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611–0.725) to an AUC = 0.721 (95% CI: 0.665–0.778).Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

COVID-19 cases correlate with greater acceptance coping in flexible cultures: A cross-cultural study in 26 countries

The current study examines whether the prevalence of COVID-19 cases and cultural flexibility correlate to one's use of acceptance coping across 26 cultures. We analyzed data from 7476 participants worldwide at the start of the first outbreak from March 2020 to June 2020. Results showed that cultural flexibility moderated the relationship between COVID-19 cases and individuals' acceptance coping strategies. Specifically, for cultures with high flexibility, COVID-19 cases correlated with more acceptance coping; for cultures with low flexibility, COVID-19 cases correlated with less acceptance coping. This result demonstrates how participants from flexible cultures can coexist with the realistic challenges and suffering faced during this pandemic