We present a class of display designs combining holographic optics, directional backlighting, laser illumination, and polarization-based optical folding to achieve thin, lightweight, and high ...performance near-eye displays for virtual reality. Several design alternatives are proposed, compared, and experimentally validated as prototypes. Using only thin, flat films as optical components, we demonstrate VR displays with thicknesses of less than 9 mm, fields of view of over 90° horizontally, and form factors approaching sunglasses. In a benchtop form factor, we also demonstrate a full color display using wavelength-multiplexed holographic lenses that uses laser illumination to provide a large gamut and highly saturated color. We show experimentally that our designs support resolutions expected of modern VR headsets and can scale to human visual acuity limits. Current limitations are identified, and we discuss challenges to obtain full practicality.
Abstract
Food supply chains are essential for distributing goods from production to consumption points. These complex supply chains are important for food security and availability. Recent research ...has developed novel methods to estimate food flows with high spatial resolution, but we do not currently understand how fine-grained food supply chains vary in time. In this study, we use an improved version of the Food Flow Model to estimate food flows (kg) between all county pairs across all food commodity groups for the years 2007, 2012, and 2017 (which requires estimating 206.3 million links). We then determine the core counties to the US food flow networks through time with a multi-criteria decision analysis technique. Our estimates of county-to-county food flows in time are freely available with this paper and could be useful for future research, policy, and decision-making.
The application of Internet of Things (IoT) technology in news media communication has significantly enhanced the effectiveness and coverage of news data releases. However, as the scale of news data ...continues to grow, traditional IoT approaches face challenges such as slow data processing speed and low mining efficiency. To address these issues, a novel news feature mining system combining IoT and Artificial Intelligence (AI) has been developed. The hardware components of the system include a data collector, a data analyzer, a central controller, and sensors. The GJ-HD data collector is utilized to gather news data. Multiple network interfaces are designed at the device terminal to ensure data extraction from the internal disk in case of device failure. The central controller integrates the MP/MC and DCNF interfaces for seamless information interconnection. In the software aspect of the system, the network transmission protocol of the AI algorithm is embedded, and a communication feature model is constructed. This enables fast and accurate mining of news data communication features. Experimental results demonstrate that the system achieves a mining accuracy of over 98%, enabling efficient processing of news data. Overall, the proposed IoT and AI-based news feature mining system overcomes the limitations of traditional approaches, allowing for efficient and accurate processing of news data in a rapidly expanding digital landscape.
Metastasis accounts for the majority of cases of cancer recurrence and death in patients with advanced non-small cell lung cancer (NSCLC). Farnesoid X Receptor (FXR) is a bile acid nuclear receptor ...that was recently found to be upregulated in NSCLC tissues. However, whether and how FXR regulates NSCLC metastasis remains unclear. In the present study, it was found that FXR promoted the migration, invasion, and angiogenic ability of NSCLC cells in vitro, and increased NSCLC metastasis in a mouse model in vivo. Mechanistic investigation demonstrated that FXR specifically bound to the promoters of IL-6ST and IL-6 genes to upregulate their transcription, thereby leading to activation of the Jak2/STAT3 signaling pathway, which facilitated tumor migration, invasion, and angiogenesis in NSCLC. Notably, Z-guggulsterone, a natural FXR inhibitor, significantly reduced FXR
NSCLC metastasis, and decreased the expression of FXR, IL-6, IL-6ST, and p-STAT3 in the mouse model. Clinical analysis verified that FXR was positively correlated with IL-6, IL-6ST and p-STAT3 expression in NSCLC patients, and was indicative of a poor prognosis. Collectively, these results highlight a novel FXR-induced IL-6/IL-6ST/Jak2/STAT3 axis in NSCLC metastasis, and a promising therapeutic means for treating FXR
metastatic NSCLC.
To combat/control the COVID-19 pandemic, a complete lockdown was implemented in China for almost 6 months during 2020.
To determine the impact of a long-term lockdown on the academic performance of ...first-year nursing students via mandatory online learning, and to determine the benefits of online teaching.
The recruitment and academic performance of 1st-year nursing students were assessed between 2019 prior to COVID-19, n = 195, (146 women) and 2020 during COVID-19, n = 180 (142 women). The independent sample t test or Mann-Whitney test was applied for a comparison between these two groups.
There was no significant difference in student recruitment between 2019 and 2020. The overall performance of the first-year students improved in the Biochemistry, Immunopathology, Traditional Chinese Medicine Nursing and Combined Nursing courses via mandatory online teaching in 2020 compared with traditional teaching in 2019.
Suspension of in-class learning but continuing education virtually online has occurred without negatively impacting academic performance, thus academic goals are more than achievable in a complete lockdown situation. This study offers firm evidence to forge a path for developments in teaching methods to better incorporate virtual learning and technology in order to adapt to fast-changing environments. However, the psychological/psychiatric and physical impact of the COVID-19 lockdown and the lack of face-to-face interaction on these students remains to be explored.
Aiming at the problems of small sample size and large feature dimension in the identification of ipsilateral supraclavicular lymph node metastasis status in breast cancer using ultrasound radiomics, ...an optimized feature combination search algorithm is proposed to construct linear classification models with high interpretability. The genetic algorithm (GA) is used to search for feature combinations within the feature subspace using least absolute shrinkage and selection operator (LASSO) regression. The search is optimized by applying a high penalty to the L1 norm of LASSO to retain excellent features in the crossover operation of the GA. The experimental results show that the linear model constructed using this method outperforms those using the conventional LASSO regression and standard GA. Therefore, this method can be used to build linear models with higher classification performance and more robustness.
Immune checkpoint inhibitors (ICIs), such as programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T lymphocyte antigen 4 (CTLA-4) antibodies, etc, have revolutionized cancer ...treatment strategies, including non-small cell lung cancer (NSCLC). While these immunotherapy agents have achieved durable clinical benefits in a subset of NSCLC patients, they bring in a variety of immune-related adverse events (irAEs), which involve cardiac, pulmonary, gastrointestinal, endocrine and dermatologic system damage, ranging from mild to life-threatening. Thus, there is an urgent need to better understand the occurrence of irAEs and predict patients who are susceptible to those toxicities. Herein, we provide a comprehensive review of what is updated about the clinical manifestations, mechanisms, predictive biomarkers and management of ICI-associated toxicity in NSCLC. In addition, this review also provides perspective directions for future research of NSCLC-related irAEs.
Hippocampal sclerosis (HS) is the most common pathological type of temporal lobe epilepsy (TLE) and one of the important surgical markers. Currently, HS is mainly diagnosed manually by radiologists ...based on visual inspection of MRI, which greatly relies on MRI quality and physician experience. In clinical practice, non-thin MRI scans are often used due to the time and efficiency needed for the acquisition. However, these scans can be difficult for junior physicians to interpret accurately. Thus, the rapid and accurate diagnosis of HS using real-world MRI images in clinical settings is a challenging task.
Our aim was to explore the feasibility of using computer vision methods to diagnose HS on real-world clinical MRI images and to provide a reference for future clinical applications of artificial intelligence methods to aid in detecting HS.
We proposed a deep learning algorithm called "HS-Net" to discriminate HS using real-world clinical MRI images. First, we delineated and segmented a region of interest (ROI) around the hippocampus. Then, we utilized the fractional differential (FD) method to enhance the textures of the ROIs. Finally, we used a small-sample image classification method based on transfer learning to fine-tune the feature extraction part of a pretrained model and added two fully connected layers and an output layer. In the study, 96 TLE patients with HS confirmed by postoperative pathology and 89 healthy controls were retrospectively enrolled. All subjects were cross-validated, and models were evaluated for performance, robustness, and clinical utility.
The HS-Net model achieved an area under the curve (AUC) of 0.894, an accuracy of 82.88%, an F1-score of 84.08% in the test cohort based on real, routine, clinical T2-weighted fluid attenuated inversion recovery (FLAIR) sequence MRI images. Additionally, the AUC, accuracy and F1 scores of our model all increased by around 3 percentage points when the inputs were augmented with the ROIs of the textures enhanced using the FD method.
Our computational model has the potential to be used for the diagnosis of HS in real clinical MRI images, which could assist physicians, particularly junior physicians, in improving the accuracy of discrimination.
Controlling and optimising the alignment of liquid crystals is a crucial process for display application. Here, we investigate the effects of humidity and surface types on photoalignment of an ...azo-dye brilliant yellow (BY). Specifically, the effect of humidity on the photoalignment of BY was studied at the stage of substrate storage before coating, during the spin-coating process, between film coating and exposure, and after exposure. Surprising results are the drastic effect of humidity during the spin-coating process, the humidity annealing to increase the order of the BY layer after exposure and the dry annealing to stabilise the layer. Our results are interpreted in terms of the effect of water on the aggregation of BY. The type of surface studied had minimal effects. Thin BY films (about 3 nm thickness) were sensitive to the hydrophilicity of the surface while thick BY films (about 30 nm thickness) were not affected by changing the surface. The results of this paper allow for the optimisation of the BY photoalignment for liquid crystal display application as well as a better understanding of the BY photoalignment mechanism.
In this work, the detailed studies of surface polymerization stabilizing liquid crystal formed on an azodye sublayer are presented. The surface localized stabilization is obtained by free-radical ...polymerization of a dilute solution of a bi-functional reactive monomer (RM) in a liquid crystal (LC) solvent. To optimize the process for surface localized stabilization, we investigate the effects of several process parameters including RM concentration in LC hosts, the types of materials (either RM or LC), the photo-initiator (PI) concentration, ultra-violet (UV) polymerization intensity, and the UV curing temperature. The quality of surface localized stabilization is characterized and/or evaluated by optical microscopy, electro-optical behavior (transmission/voltage curve), the life test, and photo-bleaching. Our results show that, by carefully selecting materials, formulating mixtures, and controlling the polymerizing variables, the RM polymerization can be realized either at the surface or through the bulk. Overall, the combination of surface localized stabilization and photo-alignment offers an elegant and dynamic solution for controlling the alignment for LC, which could play a profound role in almost all liquid crystal optical devices.
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