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颱風定量降雨預報是氣象防災的重中之重，建立在系集預報所提供的大數據基礎上，利用類神經網路技術建立颱風定量降雨預報校正模型，將是一個值得期待的趨勢。然而，由於雨量特殊的統計特性以及颱風個案稀少，因而使得應用類神經網路技術建立預報校正模型時將面臨相當的挑戰。本研究旨在探討類神經網路方法應用在台灣地區颱風雨量預報校正的可行性，以及在不同颱風雨量下的預報校正成效；特別是在雨量極大時，類神經網路校正模型是否能改善原始系集降雨機率預報。 以2015年蘇迪勒颱風為例，本研究建立3個淺層類神經網路與1個深層類神經網路，進行颱風未來24小時累積降雨預報校正，評比結果顯示淺層類神經網路有較佳的校正成效。本研究同時考量颱風快速變化的特性，使用非均等權重方法來建構模型，結果顯示非均等權重方法比均等權重方法所建立之淺層類神經網路模型有較佳的校正成效。本研究也將結果應用到2013-2015年間侵台的其他11個颱風，同樣發現非均等權重方法的淺層類神經網路能校正颱風原始系集降雨機率預報。 Focusing on typhoon precipitation, this study adopts the neural network (NN) technique to calibrate the bias of 0-24-h probabilistic quantitative precipitation forecasts (PQPF) over Taiwan produced by the WRF ensemble prediction system (WEPS) developed by the Central Weather Bureau. The goals are to explore whether the NN post-processing technique is suitable for the calibration of typhoon precipitation forecasts and to compare the calibration effects among different structures of NN models. Four NN models (three are shallow NNs and one is a deep NN) are developed and applied to calibrate the precipitation forecasts of Typhoons Soudelor, which brought torrential rain during the period of its passing through Taiwan. Evaluation results indicate that the post-processing procedures improve the performance of calibration of ensemble precipitation forecasts, especially for heavy precipitation. The simple shallow NNs perform better than the deep learning NN model. In addition, we compare the forecast performance of the NN models when equal temporal weights (unadjusted) or unequal weights are used for the training data. The results with unequal temporal weights have lower forecast errors than the model with equal weights. This model is then applied to other typhoons that attacked Taiwan during 1013-2015, and the finding remains that the unequal weights of simple shallow NN can improve the calibration. However, it is noted that the NN models in this study can correct only the values of forecast probability, not the precipitation pattern. &nbsp

Microphysical perturbation experiments were conducted to investigate the sensitivity of convective heavy rain simulation to cloud microphysical parameterization and its feasibility for ensemble forecasts. An ensemble of 20 perturbation members differing in either the microphysics package or process treatments within a single scheme was applied to simulate 10 summer-afternoon heavy-rain convection cases. The simulations revealed substantial disagreements in the location and amplitude of peak rainfall among the microphysics-package and single-scheme members, with an overall spread of 57%–161%, 66%–161%, and 65%–149% of the observed average rainfall, maximum rainfall, and maximum intensity, respectively. The single-scheme members revealed that the simulation of heavy convective precipitation is quite sensitive to factors including ice-particle fall speed parameterization, aerosol type, ice particle shape, and size distribution representation. The microphysical ensemble can derive reasonable probability of occurrence for a location-specific heavy-rain forecast. Spatial-forecast performance indices up to 0.6 were attained by applying an optimal fuzzy radius of about 8 km for the warning-area coverage. The forecasts tend to be more successful for more organized convection. Spectral mapping methods were further applied to provide ensemble forecasts for the 10 heavy rainfall cases. For most cases, realistic spatial patterns were derived with spatial correlation up to 0.8. The quantitative performance in average rainfall, maximum rainfall, and maximum intensity from the ensembles reached correlations of 0.83, 0.84, and 0.51, respectively, with the observed values. Significance Statement Heavy rainfall from summer convections is stochastic in terms of intensity and location; therefore, an accurate deterministic forecast is often challenging. We designed perturbation experiments to explore weather forecasting models’ sensitivity to cloud microphysical parameterizations and the feasibility of application to ensemble forecast. Promising results were obtained from simulations of 10 real cases. The cloud microphysical ensemble approach may provide reasonable forecasts of heavy rainfall probability and convincing rainfall spatial distribution, particularly for more organized convection.

Because osteoporotic vertebral fracture (OVF) on chest radiographs is commonly missed in radiological reports, we aimed to develop a software program which offers automated detection of compressive vertebral fracture (CVF) on lateral chest radiographs, and which emphasizes CVF detection specificity with a low false positivity rate.For model training, we retrieved 3,991 spine radiograph cases and 1,979 chest radiograph cases from 16 sources, with among them in total 1,404 cases had OVF. For model testing, we retrieved 542 chest radiograph cases and 162 spine radiograph cases from four independent clinics, with among them 215 cases had OVF. All cases were female subjects, and except for 31 training data cases which were spine trauma cases, all the remaining cases were post-menopausal women. Image data included DICOM (Digital Imaging and Communications in Medicine) format, hard film scanned PNG (Portable Network Graphics) format, DICOM exported PNG format, and PACS (Picture Archiving and Communication System) downloaded resolution reduced DICOM format. OVF classification included: minimal and mild grades with20% or ≥20-25% vertebral height loss respectively, moderate grade with ≥25-40% vertebral height loss, severe grade with ≥40%-2/3 vertebral height loss, and collapsed grade with ≥2/3 vertebral height loss. The CVF detection base model was mainly composed of convolution layers that include convolution kernels of different sizes, pooling layers, up-sampling layers, feature merging layers, and residual modules. When the model loss function could not be further decreased with additional training, the model was considered to be optimal and termed 'base-model 1.0'. A user-friendly interface was also developed, with the synthesized software termed 'Ofeye 1.0'.Counting cases and with minimal and mild OVFs included, base-model 1.0 demonstrated a specificity of 97.1%, a sensitivity of 86%, and an accuracy of 93.9% for the 704 testing cases. In total, 33 OVFs in 30 cases had a false negative reading, which constituted a false negative rate of 14.0% (30/215) by counting all OVF cases. Eighteen OVFs in 15 cases had OVFs of ≥ moderate grades missed, which constituted a false negative rate of 7.0% (15/215, i.e., sensitivity 93%) if only counting cases with ≥ moderate grade OVFs missed. False positive reading was recorded in 13 vertebrae in 13 cases (one vertebra in each case), which constituted a false positivity rate of 2.7% (13/489). These vertebrae with false positivity labeling could be readily differentiated from a true OVF by a human reader. The software Ofeye 1.0 allows 'batch processing', for example, 100 radiographs can be processed in a single operation. This software can be integrated into hospital PACS, or installed in a standalone personal computer.A user-friendly software program was developed for CVF detection on elderly women's lateral chest radiographs. It has an overall low false positivity rate, and for moderate and severe CVFs an acceptably low false negativity rate. The integration of this software into radiological practice is expected to improve osteoporosis management for elderly women.

Understanding fault zone dynamics in multi-scale is important to embrace the complexity of the earthquake behavior and its natural system. However, the opportunity to map and observe the fault zone behavior at depth with high spatial resolution are rare as also the challenge itself on targeting and identifying the fault zone at depth. We placed a 3D cross-fault fiber array with a downhole loop from surface to depth of 700m for Hole-A (Hanging wall site, crossing fault at depth), after drilling and coring to a frequent slip fault, Milun fault in a plate boundary zone, which ruptured during the 6 February 2018 Mw6.4 Hualien earthquake, and resulted in severe damage to several tall buildings with tens of casualties and injuries. Then, the surface segment crosses the surface fault rupture zone using commercial fiber, and to another downhole loop of 500m fiber for Hole-B (Footwall site). The high spatial resolution from distributed acoustic sensing (DAS) allows us to characterize the fault zone feature together with the retrieved core and geophysical logs after drilling through this frequent slip zone. This 3D route includes the experiment of using commercial fiber to the future application of surface rupture zone identification for seismic hazard mitigation. The project successfully retrieved the fault core associated with Milun fault zone, which could be also seen in geophysical logs with low velocity and resistivity, and mapped using Optical Fiber Sensing technique of the downhole fiber. Within the Milun fault zone, while a 20m thick fault core with grey and black gouge was discovered, a distinct seismic feature associated with this 20m fault gouge was found by its amplification of the strain records from DAS. This amplification ratio is about 2.5-3 when compared to the channels at deeper depth related to a consolidated rock material. This amplification factor was frequency and azimuth independently, as genuinely observed from all events (e.g. local, and teleseismic earthquakes) with similar amplification factor. Our study shows that the amplification from this 20m fault gouge zone is mainly from the nature of the heterogeneous medium in elastic constant while crossing the fault zone, especially the fault core. Similar feature at surface but with wider surface rupture zone (~ 200m) was found in DAS data as well although less evidence using commercial fiber, while could be validated from the densely deployed geophones crossing the surface rupture of the 2018 Hualien earthquake. Through the depth, a high-resolution asymmetric feature of this active fault was evidenced from the downhole optical fiber and cores. This fault zone behavior would be hardly seen or confirmed without continuous viewing of the wavefields to this high spatial resolution to meter scale. Although the narrow fault gouge, the nature of its amplification in strain due to its strong material contrast from fault gouge was intriguing, and requires intensive attention to consider the contribution of the fault zone heterogeneity in the medium. This might give hints on the understanding of the observation of earthquake dynamics triggering reported worldwide after the occurrence of a mega-earthquake.

Objectives The promotion of the COVID-19 vaccine is key to controlling the spread of COVID-19. One of the most significant obstacles in tackling the pandemic is vaccine hesitancy. While many published studies have examined vaccine hesitancy among adults, there is a dearth of such studies exploring vaccine hesitancy among adults in Taiwan, China.Study design and Methods We surveyed 384 adults in Taiwan from July 14 to September 23, 2021. Using a Chi-square test and a binary logistic regression, we examined the prevalence of COVID-19 vaccine hesitancy and the factors influencing this. In addition, we summarized the regional differences in vaccine hesitancy across China that was reported by previous research.Results Overall, 64.3% of participants were hesitant to be vaccinated. Gender and perception of the safety of the COVID-19 vaccine was identified as a risk factor for vaccine hesitancy. Additionally, hesitancy in mainland China was found to be lower than that in Taiwan and Hong Kong.Conclusion The results of this study highlight the attitudes of the adults towards vaccination and the factors that influence it. The results can inform the government’s development of epidemic prevention and control policies that would improve vaccine uptake.

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EGFR blocking antibodies are approved for the treatment of colorectal cancer and head and neck squamous cell carcinoma (HNSCC). Although ERBB3 signaling has been proposed to limit the effectiveness of EGFR inhibitors, the underlying molecular mechanisms are not fully understood. To gain insight into these mechanisms, we generated potent blocking antibodies against ERBB3 (REGN1400) and EGFR (REGN955). We show that EGFR and ERBB3 are coactivated in multiple HNSCC cell lines and that combined blockade of EGFR and ERBB3 inhibits growth of these cell lines more effectively than blockade of either receptor alone. Blockade of EGFR with REGN955 strongly inhibited activation of ERK in HNSCC cell lines, whereas blockade of ERBB3 with REGN1400 strongly inhibited activation of Akt; only the combination of the 2 antibodies blocked both of these essential downstream pathways. We used a HER2 blocking antibody to show that ERBB3 phosphorylation in HNSCC and colorectal cancer cells is strictly dependent on association with HER2, but not EGFR, and that neuregulin 1 activates ERBB3/HER2 signaling to reverse the effect of EGFR blockade on colorectal cancer cell growth. Finally, although REGN1400 and REGN955 as single agents slowed the growth of HNSCC and colorectal cancer xenografts, the combination of REGN1400 plus REGN955 caused significant tumor regression. Our results indicate that activation of the Akt survival pathway by ERBB3/HER2 limits the effectiveness of EGFR inhibition, suggesting that REGN1400, which is currently in a phase I clinical trial, could provide benefit when combined with EGFR blocking antibodies. Mol Cancer Ther; 13(5); 1345–55. ©2014 AACR.

PDF - 78K, Effect of REGN1400 and REGN955 on ligand-induced signaling by ERBB3 and EGFR, respectively.

Supplementary Figures S1 - S8 as referenced in the main article

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Additional details of methods covered in the main materials and methods section