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Objective This study aimed to investigate the use of three-dimensional visualization for preoperative evaluation of portal vein invasion in hilar cholangiocarcinoma (HCCA). Methods This recombination study for preoperative computerized tomography images was completed in 42 patients undergoing radical resection of HCCA combined with hepatectomy. Portal vein invasion with postoperative pathology was used as a gold standard to decide if the diagnosis was correct or not. We compared the sensitivity, specificity, positive predictive value, negative predictive value, and total correctness of radiologists and a three-dimensional (3D) visualization model for the assessment of tumor-caused portal vein invasion. Results The findings for the estimation of portal vein invasion by radiologists based on CT images were as follows: sensitivity = 90.9%; specificity = 83.8%; positive predictive value = 66.7%; negative predictive value = 96.3%; and overall accuracy = 85.7%. The findings for estimation by the 3D visualization model were as follows: sensitivity = 90.9%; specificity = 96.8%; positive predictive value = 90.9%; negative predictive value = 96.8%; and overall accuracy = 90.5%. Conclusion The positive predictive value of 3D visualization technology in the diagnosis of portal vein invasion is notably superior to that of subjective assessment by radiologists. This technique can thus play a significant role in preventing unnecessary resectioning of non-invaded portal veins and hepatectomy.

This paper provides an individualization approach for head-related transfer function (HRTF) in arbitrary directions based on deep learning by utilizing dual-autoencoder architecture to establish the relationship between HRTF magnitude spectrum and arbitrarily given direction and anthropometric parameters. In this architecture, one variational autoencoder (VAE) is utilized to extract interpretable and exploitable features of full-space HRTF spectra, while another autoencoder (AE) is employed for feature embedding of corresponding directions and anthropometric parameters. A deep neural networks model is finally trained to establish the relationship between these representative features. Experimental results show that the proposed method outperforms state-of-the-art methods in terms of spectral distortion.

Objective This study aimed to investigate the use of three-dimensional visualization for preoperative evaluation of portal vein invasion in hilar cholangiocarcinoma (HCCA). Methods This recombination study for preoperative computerized tomography images was completed in 42 patients undergoing radical resection of HCCA combined with hepatectomy. Portal vein invasion with postoperative pathology was used as a gold standard to decide if the diagnosis was correct or not. We compared the sensitivity, specificity, positive predictive value, negative predictive value, and total correctness of radiologists and a three-dimensional (3D) visualization model for the assessment of tumor-caused portal vein invasion. Results The findings for the estimation of portal vein invasion by radiologists based on CT images were as follows: sensitivity = 90.9%; specificity = 83.8%; positive predictive value = 66.7%; negative predictive value = 96.3%; and overall accuracy = 85.7%. The findings for estimation by the 3D visualization model were as follows: sensitivity = 90.9%; specificity = 96.8%; positive predictive value = 90.9%; negative predictive value = 96.8%; and overall accuracy = 90.5%. Conclusion The positive predictive value of 3D visualization technology in the diagnosis of portal vein invasion is notably superior to that of subjective assessment by radiologists. This technique can thus play a significant role in preventing unnecessary resectioning of non-invaded portal veins and hepatectomy.

The temperature of domestic drain water is relatively high, but its flux is sometimes insufficient as a heating source. Thus, the conventional wastewater source heat pump water heater is incapable of meeting user heating demand given the limited sensible heat temperature difference in many situations. To address this problem, a novel in–house heat pump water heater with a freezing latent heat evaporator and assisted by domestic drain water was proposed. A prototype of the system was first constructed to determine the performance of the system. An experiment was then conducted, in which a parallel helical coil tube evaporator was designed and developed to extract freezing latent heat from domestic drain water. Experimental data was obtained in different experimental conditions. Results of the investigation show that the heat pump water heater with a freezing latent evaporator recovers 3.4 times more energy than the conventional wastewater source heat pump water heater, and saves 60% energy compared with the traditional electric water heater. Furthermore, an interesting result is that the heat transfer coefficient increased significantly at the moment the wastewater was just frozen. This paper provides a reference for the wastewater source heat pump water heater to extract freezing latent heat from domestic drain water.

An array arrangement strategy of photovoltaic thermal modules and a connection form of refrigerant pipeline were innovatively proposed by author’s research group. Subsequently, the photovoltaic thermal heat pump system engineering was designed and constructed, and then the performance study of system heating in continuous operation and stage operation in winter was carried out in January 2021. During the system operation, the average coefficient of heating performance of the system was 2.95 in daytime stage operating, 2.55 in nighttime stage operating and 2.07 in continuous operating. To conduct the application simulation of photovoltaic thermal heat pump system, first the prediction model of system heating performance based on back propagation neural network was established and verified according to the operational parameters, then 12 cities of typical climate zone in China were selected to conduct operation simulation and performance prediction to analyze the regional applicability of the system, finally the performance prediction of system heating under variable working conditions was carried out to guide the design calculation of engineering application of photovoltaic thermal heat pump system engineering. It can be concluded that the system was more suitable for engineering application in cities of cold zone and hot summer and cold winter zone than that in severe cold zone. Besides that, the integration and operation optimization of system should be carried out to reduce the average temperature of the circulating hot water tank so that the energy efficiency of hot water system can be improved by 42%.

The condensates generated in the process of film condensation, such as condensing, falling, and acting condensates, are identified and defined to obtain precise inundation effect model of 3D finned tube bundle. Furthermore, the influence of three categories of condensates on the film condensation under different heat fluxes and condensing temperatures is experimentally investigated via the homologous method. A test bench with a test section contains two arrays of 8 horizontal tubes is initially constructed. Experimental results show that the inundation effect coefficient decreases from 1.00 to 0.78 as acting condensate Re increases from 75 to 1860. The influence of heat flux on three categories of condensates is more significant than that of condensing temperature. As tube row depth increases from 1 to 6, the proportion of condensing condensate Re to acting condensate Re decreases from 100% to 15.0%, whereas the proportion of falling condensate Re to acting condensate Re increases from 0 to 85.0%. Furthermore, the condensation heat transfer model of single 3D finned tube and inundation effect model are established, and the deviations of results between experiments and models are almost within ±3.0%. The deviations of inundation effect coefficients between experiment and model proposed in this study are 92.5% and 50.0% less than those between experiment and models using routine method and considering single condensate with homologous method, respectively. Moreover, the inundation effect model proposed in this study reveals that different proportions of condensing or falling condensates to acting condensate lead to different inundation effect coefficient at the same acting condensate Re. The research results will lay the foundation for further revealing the mechanism of film condensation on 3D finned tube bundle and guide the thermal design of 3D finned tubes applied in shell-and-tube condensers.

To accurately evaluate the condensation heat transfer performance of new 3D finned tubes in shell-and-tube condenser, the inundation effect of the film condensation of R-134a on an array of 6 horizontal new 3D (three-dimensional) finned tubes is experimentally investigated with a new experiment method of homologous method. And the precise inundation effect coefficient of film condensation is determined. A novel test facility, whose test section contains two arrays of 8 horizontal tubes to realize the homologous method, is developed and constructed. The outer diameter of the tube and effective tube length in the test section are 19.05 and 500 mm, respectively. The condensation heat transfer coefficient of new 3D finned tube and inundation effect coefficient of new 3D finned tube bundle are determined under different conditions. The results show that the inundation effect coefficient of new 3D finned tube bundle decreases from 1.00 to 0.78 as Re increases from 75 to 1860. And the effect of heat flux on the inundation effect is more sensitive than the condensing temperature. Furthermore, for new 3D finned tube, the condensation heat transfer and inundation effect models are established, and the deviations of results between experiment and models are almost within ±6.0%. In comparison with literatures, the average inundation effect coefficient of new 3D finned tube bundle is 10.0-25.0% higher than that of 3D finned tube bundle in literatures, within 3.0% lower than that of two-dimensional finned tube bundle, and 15.2% higher than that of plain tube bundle. And the average condensation heat transfer coefficient of new 3D finned tube bundle in this article is 5.0-25.0% higher than that of 3D finned tube bundle in literatures, 10.0-30.0% higher than that of 2D finned tube bundle, and more than 10 times that of plain tube bundle. The precise inundation effect coefficients can be used as benchmark data to build precise and universal inundation effect model of 3D finned tube, and the models established in this study will help guide the thermal design of the new 3D finned tube applied in shell-and-tube condenser.

Heat pumps are a part of the environmentally friendly technologies using renewable energy and have been utilized in HVAC systems. A heat pump water heater unit with frozen type evaporator was designed and developed. And a test bed was constructed to determine the performance of the unit. In the experiment, a parallel helical coil type evaporator was used in the unit to extract latent heat from the sewage. The data (dynamic COP and other parameters) was obtained in three processes(including the first freezing, melting, and the second freezing) at different water temperatures (8.2℃ and 13.8℃). Results show that compare with traditional water source heat pumps, the newly designed unit with the frozen evaporator can reduce the required water amounts as a heat source by more than 90%. The higher initial temperature of hot water and sewage, the higher temperature of sewage after melting. Meanwhile, with the increase of the initial temperature of hot water and sewage, the comprehensive COP was greater. This paper will provide a reference for the sewage source heat pump system to extract the latent heat from the sewage.

Emotional analysis of text has always been a hot topic in natural language research. In view of the long-term dependence of recurrent neural networks and the fact that most models do not consider the correlation between input and output, this paper proposes a bidirectional LSTM model based on attention mechanism to judge the comment emotion. This method vectorizes the semantics of comments into the LSTM model, improves the relevance of input and output through the attention mechanism, fuses the aspect category and aspect Term, and outputs the results through the classifier. The experimental results of Dianping.com review data set provided by AI Challenger competition show that the improved method adopted in this paper is better than the common deep learning method.

Employee training is not only important for the continuous growth of human resources but also guarantees sustainable human resource management in enterprises. It is very important to understand corporate behaviour related to employee training not only from the perspective of a single enterprise but also from that of multiple enterprises. The purpose of this study is to explore multiple enterprises’ employee training behaviours by conducting a content analysis of corporate social responsibility (sustainability) reports and a social network analysis. This study also seeks to find a way to achieve sustainable employee training by analysing the similarities in the different types of corporate training behaviours. Our analysis shows that, in 2017, 108 types of training activities were implemented by 53 enterprises, the key employee trainings (e.g., security training and skills training) and enterprises (e.g., bank of communication) are identified. The training behaviours of some of the enterprises are similar to some extent, and eight groups of firms that are very similar are identified. The results of this study show that social network analysis performs well for studying corporate employee training behaviours. Some suggestions to minimize the investment costs of training and to improve the sustainability of human resource management from the employee training perspective are provided.

A novel integrated home energy system with freezing latent heat collection was proposed to improve the overall efficiency of building energy usage. The novel unit can recycle waste heat (including sensible and freezing latent heat) from domestic drain water and condensing heat to efficiently provide space heating and cooling and domestic hot water for a household. A novel unit, whose core equipment was a parallel serpentine tube evaporator with a new de-icing technique to efficiently extract freezing latent heat, was initially constructed. The performance, annual thermal energy recycling rate, and life cycle cost of the novel unit were determined, studied, and discussed, respectively. Results showed that the coefficient of performance of the unit with de-icing technology is 10.00−20.00% higher than that of systems reported in extant literature under unfavorable condition. The annual thermal energy recycling rate was 25.00−30.00%, which is approximately 2.6 times that of systems described in literature. In addition, the life cycle cost of the unit is 10.00−35.00% lower than that of traditional units. The novel unit considerably reduces the energy consumption, environmental pollution, and related costs of buildings, thus providing practical importance and a scientific research value for improving energy efficiency, changing the original energy structure, and reducing the environmental load brought by energy conversion.