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This study aims to utilize a hybrid approach of phantom correction and deep learning for synthesized CT (sCT) images generation based on cone-beam CT (CBCT) images for nasopharyngeal carcinoma (NPC). 52 CBCT/CT paired images of NPC patients were used for model training (41), validation (11). Hounsfield Units (HU) of the CBCT images was calibrated by a commercially available CIRS phantom. Then the original CBCT and the corrected CBCT (CBCT_cor) were trained separately with the same cycle generative adversarial network (CycleGAN) to generate SCT1 and SCT2. The mean error and mean absolute error (MAE) were used to quantify the image quality. For validations, the contours and treatment plans in CT images were transferred to original CBCT, CBCT_cor, SCT1 and SCT2 for dosimetric comparison. Dose distribution, dosimetric parameters and 3D gamma passing rate were analyzed. Compared with rigidly registered CT (RCT), the MAE of CBCT, CBCT_cor, SCT1 and SCT2 were 346.11 ± 13.58 HU, 145.95 ± 17.64 HU, 105.62 ± 16.08 HU and 83.51 ± 7.71 HU, respectively. Moreover, the average dosimetric parameter differences for the CBCT_cor, SCT1 and SCT2 were 2.7% ± 1.4%, 1.2% ± 1.0% and 0.6% ± 0.6%, respectively. Using the dose distribution of RCT images as reference, the 3D gamma passing rate of the hybrid method was significantly better than the other methods. The effectiveness of CBCT-based sCT generated using CycleGAN with HU correction for adaptive radiotherapy of nasopharyngeal carcinoma was confirmed. The image quality and dose accuracy of SCT2 were outperform the simple CycleGAN method. This finding has great significance for the clinical application of adaptive radiotherapy for NPC.

To compare dosimetric differences among graphical-based manual planning (MA), simulated annealing inverse optimization (IPSA), and hybrid inverse optimization (HIPO) for cervical cancer in both intra-cavitary brachytherapy (ICBT) and interstitial brachytherapy combined with ICBT (IC/ISBT) settings, providing evidence for clinical optimization method selection. This study consisted of 60 cervical cancer patients undergoing CT-guided three-dimensional brachytherapy, including 30 ICBT patients and 30 IC/ISBT patients. Plans were generated using MA, IPSA, and HIPO. The dosimetric parameters for the high-risk clinical target volume (HRCTV) including D100%, V150%, V200%, conformity index (CI), homogeneity index (HI) were compared. Meanwhile, the dosimetric parameters D1cc, D2cc for the bladder, rectum, sigmoid, and total treatment time were evaluated. Compared with MA, both IPSA and HIPO delivered lower doses to organs at risk (OARs). The total treatment time was significantly shorter for HIPO compared to IPSA and MA (P < 0.05). In ICBT patients, the D1cc and D2cc of OARs were lower for IPSA compared to HIPO (P > 0.05), while the CI was significantly better for HIPO (P < 0.05). Nevertheless, in IC/ISBT patients, D2cc of rectum for HIPO was significantly lower compared to IPSA (P < 0.05), with better CI. Inverse optimization effectively reduces doses to OARs while maintaining target coverage. HIPO appears to be the preferred choice for IC/ISBT, due to shortened treatment time, superior CI and rectal protection compared with IPSA.

The aim of this study is to demonstrate the feasibility of a commercially available Auto-Planning module for the radiation therapy treatment planning for locally advanced nasopharyngeal carcinoma (NPC). 22 patients with locally advanced NPC were included in this study. For each patient, volumetric modulated arc therapy (VMAT) plans were generated both manually by an experienced physicist and automatically by the Auto-Planning module. The dose distribution, dosimetric parameters, monitor units and planning time were compared between automatic plans (APs) and manual plans (MPs). Meanwhile, the overall stage of disease was factored into the evaluation. The target dose coverage of APs was comparable to that of MPs. For the organs at risk (OARs) except spinal cord, the dose parameters of APs were superior to that of MPs. The D max and V 50 of brainstem were statistically lower by 1.0 Gy and 1.32% respectively, while the D max of optic nerves and chiasm were also lower in the APs (p < 0.05). The APs provided a similar or superior quality to MPs in most cases, except for several patients with stage IV disease. The dose differences for most OARs were similar between the two types of plans regardless of stage while the APs provided better brainstem sparing for patients with stage III and improved the sparing of the parotid glands for stage IV patients. The total monitor units and planning time were significantly reduced in the APs. Auto-Planning is feasible for the VMAT treatment planning for locally advanced NPC.

Global warming has significantly reduced summer ice coverage in the Arctic region, providing long-awaited opportunities for the shipping industry to open new routes through a region known for its harsh navigational conditions. If a shortcut between Asia and Europe via the Northern Sea Route (NSR) is adopted, significant energy saving and pollution reduction are possible compared with conventional southern routes. However, opinions in literature differ regarding this shortcut’s economic viability. We present an analysis from the perspective of COSCO, China’s largest container sea freight operator. We perform a cost–benefit analysis under several scenarios considering the following current realities: (1) declining oil prices not seen for decades, even lower than the lowest prices assumed in previous studies; (2) declining Russian NSR tariff as an effort to attract shipping traffic; (3) possible emission control areas along a northern route may require much cleaner energy and thus impact costs not studied in previous models; and (4) the capital cost difference between a hired and a self-owned vessel. Classical case studies of shipping routes between Shanghai and Rotterdam are adopted for comparison. We explain how different factors impact the shipping costs and to what extent can the NSR be economically viable. Occasional usage of NSR (e.g., one time transit) is unlikely to be more profitable given the higher unit transportation cost, but the route could be economically competitive in terms of the total profits earned for continuous usage. A more aggressive scenario which requires ships on the NSR to switch to much cleaner fuel would erode this route’s competitiveness, but extra environmental benefits should be taken into consideration if future carbon emission trading schemes include the shipping industry.

Background The efficient utilization of lignocellulosic biomass for biofuel production has received increasing attention. Previous studies have investigated the pretreatment process of biomass, but the detailed enzymatic hydrolysis process of pretreated biomass remains largely unclear. Thus, this study investigated the pretreatment efficiency of dilute alkali, acid, hydrogen peroxide and its ultimate effects on enzymatic hydrolysis. Furthermore, to better understand the enzymatic digestion process of alkali-pretreated sweet sorghum straw (SSS), multimodal microscopy techniques were used to visualize the enzymatic hydrolysis process. Result After pretreatment with alkali, an enzymatic hydrolysis efficiency of 86.44% was obtained, which increased by 99.54% compared to the untreated straw (43.23%). The FTIR, XRD and SEM characterization revealed a sequence of microstructural changes occurring in plant cell walls after pretreatment, including the destruction of lignin–polysaccharide interactions, the increase of porosity and crystallinity, and reduction of recalcitrance. During the course of hydrolysis, the cellulase dissolved the cell walls in the same manner and the digestion firstly occurred from the middle of cell walls and then toward the cell wall corners. The CLSM coupled with fluorescent labeling demonstrated that the sclerenchyma cells and vascular bundles in natural SSS were highly lignified, which caused the nonproductive bindings of cellulase on lignin. However, the efficient delignification significantly increased the accessibility and digestibility of cellulase to biomass, thereby improving the saccharification efficiency. Conclusion This work will be helpful in investigating the biomass pretreatment and its structural characterization. In addition, the visualization results of the enzymatic hydrolysis process of pretreated lignocellulose could be used for guidance to explore the lignocellulosic biomass processing and large-scale biofuel production.

Objective To evaluate the effectiveness of the remote management based on the Internet Hospital and Family-Sicked Bed strategy under the Four-Party Linkage model among patients with maintenance peritoneal dialysis (PD). Methods Bao’an People’s Hospital (Group) utilized its internet hospital platform to conduct a retrospective cohort observational study on the Remote Management (RM) of PD patients. The study further established​a four-party collaborative disease management model comprising “residents-communities-community health centers-the hospital”. A total of 150 insured patients were randomly assigned into three groups—Non-RM-PD group, RM-PD group, and Family-Sicked Bed group—using the random number table method. After a six-month intervention period, clinical indicators across the groups were compared, and analyses were conducted on time consumption, economic costs, as well as the potential benefits for patients, healthcare providers, and society in each group. Results The clinical outcomes, including hospitalization rates, blood pressure levels, the proportion of patients requiring antihypertensive medications, the number of antihypertensive agents used, fluid overload, edema, hypokalemia, peritonitis incidence, and the rate of Kt/V meet the standard, demonstrated that RM-PD group and Family-Sicked Bed group were superior to the Non RM-PD group( P  < 0.05). Multidimensional improvements were observed in the RM-PD and Family-Sickbed groups, such as enhanced quality of home-based PD, improved work efficiency of healthcare staff, greater social benefits, and reduced economic burden on patients. The Non RM-PD group had the highest total annual medical costs after reimbursement, whereas the Family-Sicked Bed group had the lowest (mean ± SD)(Non RM-PD = 39,383 ± 2678, RM-PD = 34,369 ± 2898, Family-Sicked Bed = 25,250 ± 2763, based on Chinese Yuan CNY, P  < 0.05). Conclusion Within the 6-month follow-up period of this study, remote management supported by the internet hospital and Family-Sicked Bed management under the Four-Party Linkage model have demonstrated effectiveness in PD patients; their long-term sustainability requires further verification with extended follow-up. Clinical trial number Not applicable.

The harmonic reducer is an essential kinetic transmission component in the industrial robots. It is easy to be fatigued and resulted in physical malfunction after a long period of operation. Therefore, an accurate in-situ fault diagnosis for the harmonic reducers in an industrial robot is especially important. This paper proposes a fault diagnosis method based on deep learning for the harmonic reducer of industrial robots via consecutive time-domain vibration signals. Considering the sampling signals from industrial robots are long, narrow, and channel-independent, this method combined a 1-dimensional convolutional neural network with matrix kernels (1-D MCNN) adaptive model. By adjusting the size of the convolution kernels, it can concentrate on the contextual feature extraction of consecutive time-domain data while retaining the ability to process the multi-channel fusion data. The proposed method is examined on a physical industrial robot platform, which has achieved a prediction accuracy of 99%. Its performance is appeared to be superior in comparison to the traditional 2-dimensional CNN, deep sparse automatic encoding network (DSAE), multilayer perceptual network (MLP), and support vector machine (SVM).

Purpose: To develop and evaluate an automatic intensity-modulated radiation therapy (IMRT) program for cervical cancer, including a Convolution Neural Network (CNN)-based prediction model and an automated optimization strategy. Methods: A CNN deep learning model was trained to predict a patient-specify set of IMRT objectives based on overlap volume histograms (OVH) and high-quality plan of previous patients. A total of 140 cervical cancer patients were enrolled in this study, including 100 patients in the training set, 20 patients in the validation set and 20 patients in the testing set. The input of this model was OVH data and the output were values of IMRT plan objectives. For patients in the testing set, the set of planning objectives were predicted by the CNN model and used to automatically generate IMRT plans. Meanwhile, manual plans of these patients were generated by 1 beginner planner and 1 senior planner respectively. Finally, dose distribution, dosimetric parameters and planning time were analyzed. In addition, the 3 types of plans were blinded compared and ranked by an experienced oncologist. Results: There were almost no statistically differences among these 3 types of plans in target coverage and dose conformity. Dose homogeneity were slightly decreased while the average dose and parameters for most organs-at-risk (OARs) were decreased in automatic plans. Especially in comparison with manual plans by the beginner planner, V40 of bladder and rectum decreased 6.3% and 12.3%, while mean dose of rectum and marrow were 1.1 Gy and 1.8 Gy lower with automatic plans (either P < 0.017). In the blinded comparison, automatic plans were chosen as best plan in 14 cases. Conclusions: For cervical cancer, automatic IMRT plans optimized from the CNN generated objectives have superior dose sparing without compromising of target dose. It significantly reduced the planning time.

Developing a green and smart port is a significant progress in the specific application of energy conservation and emission reduction as well as intelligent technologies in global ports and maritime shipping sectors. The paper aims to analyze the inherent relationships among different structural factors and proposes specific countermeasures and governance policies for green and smart port construction. It uses interpretive structural modeling analysis to divide the factors into different levels, and draws a model map of green and smart port construction structure. The research result contributes to providing a theoretical basis for governments to formulate a green and smart port policies and establishing effective method systems and technical means for the port industry and stakeholders to leverage intelligent port technologies for the port development.

This study employed a commercial software velocity to perform deformable registration and dose calculation on deformed CT images, aiming to assess the accuracy of dose delivery during the radiotherapy for lung cancers. A total of 20 patients with lung cancer were enrolled in this study. Adaptive CT (ACT) was generated by deformed the planning CT (pCT) to the CBCT of initial radiotherapy fraction, followed by contour propagation and dose recalculation. There was not significant difference between volumes of GTV and CTV calculated from the ACT and pCT. However, significant differences in dice similarity coefficient (DSC) and coverage ratio (CR) between GTV and CTV were observed, with lower values for GTV volumes below 15 cc. The mean differences in dose corresponding to 95% of the GTV, GTV-P, CTV, and CTV-P between ACT and pCT were − 0.32%, 4.52%, 2.17%, and 4.71%, respectively. For the dose corresponding to 99%, the discrepancies were − 0.18%, 8.35%, 1.92%, and 24.96%, respectively. These differences in dose primarily appeared at the edges of the target areas. Notably, a significant enhancement of dose corresponding to 1 cc for spinal cord was observed in ACT, compared with pCT. There was no statistical difference in the mean dose of lungs and heart. In general, for lung cancer patients, anatomical motion may result in both CTV and GTV moving outside the original irradiation region. The dose difference within the original target area was small, but the difference in the planning target area was considerable.