Maps of forest stand condition—the current phase of the forest-forming process—will be useful for foresters in their forest management in addition to the forest planning and cartographic materials. The mapping methodology was applied in the test area of the Bolshemurtinsky forest district of the Krasnoyarsk region, which is typical for the southern taiga forests of East Siberia. Source data for mapping was obtained on the basis of descriptions of the forest subcompartments on the GIS attribute table of the forest district. Forest stand confinement to the terrain relief indicators was identified on the basis of the SRTM 55-01 digital terrain model data. Spatial analysis has been performed using the ArcGIS Spatial Analyst module. Mapping capability has been shown not only for the year of forest inventory but also for the earlier period of time. To determine the predominant species and the age of the 100-year-old forest stand, a scheme was proposed in which the conceivable options are typified depending on the succession trend, the forest stand age prior to disturbance, and the period of reforestation. Map fragments of the test area as of 2006—the year of forest inventory—and as of 1906—the year of the intensive colonization beginning in southern Siberia—are demonstrated. Maps of forest condition in the test area represent successions that are typical in the southern taiga forests of Siberia: post-harvest, pyrogenic, and biogenic. The methodology of forest condition mapping is universal.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.

In April 2023, the government of Changshu City, in Jiangsu Province, China, announced that it would officially use digital Chinese Yuan (E-CNY) as a method of wage payment to the government and state-owned enterprises staff starting in May. With the gradual improvement and application of E-CNY technologies, such as no electricity, no internet payment (offline payment), and the programmability of smart contracts, E-CNY will be officially used in China. CNN said China is on the verge of a cashless society. The advantages of E-CNY have a positive role in promoting the Chinese government’s implementation of the development goals of a low-carbon and sustainable economy. However, artificial intelligence (AI) trust concerns are the primary bottleneck in the current development based on intelligent algorithms and digital information technology. AI trust concerns are affecting the scope of use of E-CNY, and it may need to achieve effective scale-use, making it promote low-carbon and sustainable development. From the industry perspective, this article selects the housing rental enterprises, which are challenging to develop and energy-intensive, to analyze the theoretical approach and practical impact of E-CNY in promoting the low-carbon and sustainable development of China’s rental housing economy. Meanwhile, from the perspective of Chinese consumers, the impact of AI trust concerns on E-CNY in promoting low-carbon and sustainable development is analyzed in this article.

Objective: To investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and cirrhotic nodules via radiomics models based on magnetic resonance images. Background: This study is to distinguish hepatocellular carcinoma and cirrhotic nodules using MR-radiomics features extracted from four different phases of MRI images, concluded T1WI, T2WI, T2 SPIR and delay phase of contrast MRI. Methods: In this study, the four kind of magnetic resonance images of 23 patients with hepatocellular carcinoma (HCC) were collected. Among them, 12 patients with liver cirrhosis were used to obtain cirrhotic nodules (CN). The dataset was used to extract MR-radiomics features from regions of interest (ROI). The statistical methods of MRradiomics features could distinguish HCC and CN. And the ability of radiomics features between HCC and CN was estimated by receiver operating characteristic curve (ROC). Results: A total of 424 radiomics features were extracted from four kind of magnetic resonance images. 86 features in delay phase of contrast MRI，86 features in spir phase of T2WI，86 features in T1WI and 88 features in T2WI showed statistical difference (p < 0.05). Among them, the area under the curves (AUC) of these features larger than 0.85 were 58 features in delay phase of contrast MRI, 54 features in spir phase of T2WI, 62 features in T1WI and 57 features in T2WI. Conclusions: Radiomics features extracted from MRI images have the potential to distinguish HCC and CN.

Eco-friendly and greener barrier materials are required to replace the synthetic packaging materials as they produce a threat to environment. These can be fabricated by natural polymers such as cellulose nanofiber (CNF). The sustainability of CNF was so amazing due to its potential for circular economy and provides alternative platform for synthetic plastics. The challenging task to fabricate CNF films still existed and also current methods have various limitations. CNF films have good oxygen permeability and the value was lower than synthetic plastics. However, CNF films have poor water vapour permeability and higher than that of synthetic plastics. The fabrication method is one of strong parameters to impact on the water permeability of CNF films. The deposition of CNF suspension on the stainless-steel plate via spraying, is a potential process for fabrication for CNF films acting as barrier material against water vapour. In spraying process, the time required to form CNF films in diameter of 15.9 cm was less than 1 min and it is independent of CNF content in the suspension. The uniqueness of CNF films via the spraying process was their surfaces, such as rough surface exposed to air and smooth surface exposed to stainless steel. Their surfaces were investigated by SEM, AFM and optical profilometry micrographs, confirming that the smooth surface was evaluated notable lower surface roughness. The spray coated surface was smooth and glossy and its impact on the water vapor permeability remains obscure. The spraying process is a flexible process to tailor the basis weight and thickness of CNF films can be adjusted by the spraying of CNF suspension with varying fibre content. The water vapour permeability of CNF films can be tailored via varying density of CNF films. The plot between water vapour transfer rate (WVTR)/water vapour and density of CNF films has been investigated. The WVP of spray coated CNF films varied from 6.99 ± 1.17 × 10⁻¹¹ to 4.19 ± 1.45 × 10⁻¹¹ g/m.s.Pa. with the density from 664 Kg/m³ to 1,412.08 Kg/m³. The WVP of CNF films achieved with 2 wt% CNF films (1,120 Kg/m³) was 3.91 × 10⁻¹¹ g/m.s.Pa. These values were comparable with the WVP of synthetic plastics. Given this correspondence, CNF films via spraying have a good barrier against water vapour. This process is a potential for scale up and commercialization of CNF films as barrier materials.