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Abstract In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656–0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237–0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

To solve the problems of low spectral efficiency and poor performance of physical layer security (PLS) in single-input single-output (SISO) wireless systems with adaptive modulation in the presence of an active eavesdropper, multiple-input multiple-output (MIMO) wireless systems with secure adaptive modulation (SAM) were proposed.The design idea was to improve the spectral efficiency of the main channel by antenna diversity technology, which used the transmit antenna selection (TAS) at the transmitter and the maximal ratio combining (MRC) at the legitimate receiver to improve the signal-to-noise ratio.Simultaneously, the PLS of the legitimate receiver was guaranteed by limiting the bit error rate of the active eavesdropper so that it could not demodulate the confidential information from the main channel.With the joint constraints of the average transmission power and PLS, the optimal switching thresholds and the analytical expressions of spectral efficiency and the eavesdropper’s average bit error rate of the SAM-MIMO systems were derived.Numerical and simulation results show that SAM systems using TAS/MRC technology can not only improve the spectral efficiency of the main channel, but also ensure the PLS against the active eavesdropper, compared with the SAM-SISO systems.

In this study, the transcriptome profiles of tissue–cultured grapevine (Vitis vinifera L. × Vitis labrusca L.: Rose Honey) seedlings inoculated with fungal endophytes Epicoccum layuense R2-21 (Epi R2-21) and Alternaria alternata XHYN2 (Alt XHYN2), were analyzed at three different time points (6 h, 6 d, and 15 d). A total of 4783 differentially expressed genes (DEGs) was found, of which 1853 (6 h), 3878 (6 d), and 4732 (15 d) were differentially expressed relative to those of the control in endophyte Epi R2-21 treatments, while a total of 5898 DEGs, of which 2726 (6 h), 4610 (6 d), and 3938 (15 d) were differentially expressed in endophyte Alt XHYN2 treatments. DEGs enriched in secondary metabolic pathways, plant–pathogen interaction, and hormone signalling were further analysed. The upregulated DEGs in the Epi R2-21 and Alt XHYN2 treatments, both enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG), were mainly involved in flavonoid biosynthesis, phenylpropanoid biosynthesis, stilbenoid, diarylheptanoid and gingerol biosynthesis, phenylalanine metabolism, and circadian rhythms–plant and plant–pathogen interactions, similar to the trend observed in our previous study conducted on the cultivar ‘Cabernet Sauvignon’ (Vitis vinifera L.). Taken together with the results obtained from the cultivar ‘Cabernet Sauvignon’, it was found that tissue-cultured seedlings of the cultivar ‘Rose Honey’ induced a stronger defence response to fungal endophyte infection than that of the cultivar ‘Cabernet Sauvignon’, and inoculation with the endophyte Alt XHYN2 triggered a stronger response than inoculation with the endophyte Epi R2-21. In addition, the protein–protein interaction (PPI) network revealed that the genes VIT_16s0100g00910, encoding CHS, and VIT_11s0065g00350, encoding CYP73A, were involved in secondary metabolism and thus mediated in the resistance mechanism of grapevine on both the cultivars. The results showed that inoculation with the endophytes Epi R2-21 and Alt XHYN2 had a great ability to induce defence responses and reprogram the gene expression profiles in different grapevine cultivars, which deepens our knowledge of the interaction between fungal endophytes and grapevine and gives hints for grape quality management in viticulture using candidate fungal endophytes.

The long short-term memory (LSTM) recurrent neural network algorithm in deep learning has demonstrated significant superiority in predicting the realized volatility (RV) of crude oil prices. However, there is no robust and consistent conclusion regarding the handling of microstructural noise from high-frequency data during the prediction process. Therefore, this study utilizes six commonly used data decomposition methods, as documented in the literature, to address the issue of noise handling and decompose the RV series of Chinese crude oil futures. Subsequently, LSTM is integrated with the decomposed data to model and forecast RV. The empirical findings provide compelling evidence that the LSTM model based on neural networks outperforms traditional econometric models in out-of-sample forecasting. Furthermore, the LSTM model with data noise decomposition consistently exhibits superior out-of-sample prediction performance compared to the model without noise decomposition. Among the various data noise decomposition models examined, this study highlights the significant out-of-sample predictive power of variational mode decomposition (VMD), a nonrecursive signal decomposition method, that outperforms other methods. In the scenario of predicting one step ahead, the VMD-LSTM model demonstrates MAE, MSE, and HMAE values of 7.5×10−2, 1.10×10−4, and 0.423, respectively.

The relay aided device to device (D2D) network can improve the spectrum efficiency of D2D users and the physical layer security of cellular user (CU) by sharing spectrum with the cellular network.To further improve their performance, transmit antenna selection can be used at the base station and the relay node of the D2D link, and full duplex technology can be used in the relay node.However, due to the feedback delay and mobility, the channel state information (CSI) used for the antenna selection of cellular link and all D2D links may be outdated.For the physical layer security and reliability in the above scenario, security model of a full duplex relay aided D2D network was proposed in the presence of active eavesdropping and outdated CSI, in which the base station and relay nodes both used transmit antenna selection.The closed-expressions for outage probability, ergodic capacity, probability of non-zero secrecy capacity, secure outage probability, asymptotic secure outage probability of relay aided D2D networks were derived.The numerical calculation and simulation results show that the more the number of base station transmit antennas and relay jamming antennas are, the better the CU security performance is.The outdated CSI will deteriorate the outage and security performance of CU.

Abstract The attack price of higher order side channel attacks (HOSCA) grows exponentially with the mask order. When the mask order is larger than 3, HOSCA can be inapplicable. In light of this, the distance similarity measure based profiling attack (DSMPA) is proposed. In DSMPA, the leakage property of masks can be characterised in a profiling scenario and the so called templates can be obtained. Then, DSM can be used to recover mask values with templates. With mask values recovered, the effect of masking disappears and one can use first‐order side‐channel attacks to recover the secret key used by a masked chip. The key‐recovery efficiency of DSMPA is evaluated in real scenarios, and the advantage of DSMPA over HOSCA in terms of the key‐recovery efficiency can be obvious under the success rate metric. Overall, the contribution of this work may provide evaluators a powerful tool to evaluate the security of masked chips.

Water and carbon exchanges between grassland and the atmosphere are important processes for water balance and carbon balance. Based on eddy covariance observations over a semiarid alpine steppe ecosystem in Bange on the Tibetan Plateau during the growing season from 2014 to 2017, the variations in evapotranspiration (ET), net ecosystem exchange (NEE), and their components and the associated driving factors were analyzed. Linear and nonlinear models were applied to investigate the relationships between fluxes and their controlling factors over different timescales. The results show that the average ET for the growing season ranged from 1.1 to 2.4 mm/d with an average of 2.0 mm/d for the four consecutive years. Drought conditions reduced the surface conductance and hence the Priestley–Taylor coefficient. Mean T/ET was low (0.34) due to low vegetation cover. Plant growth increased the T/ET ratio during the growing season, whereas soil water content (SWC) explained most of the variation of ET and E on daily and monthly scales. The Enhanced Vegetation Index (EVI) was the most important controlling factor for temperature. Transpiration increased with SWC in dry conditions. For the growing season in 2014, 2016, and 2017, Bange was a carbon sink, while it was a carbon source in 2015. The largest CO2 flux was higher and the temperature sensitivity coefficient (Q10) was lower for 2015 than for the other three years. SWC affected these photosynthesis and respiration parameters. The ratio of respiration (Re) to gross primary production (GPP) was the highest during the 2015 growing season. Both on daily and monthly scales, Re was positively and linearly correlated with GPP. The most important controlling factor for the CO2 flux was EVI on daily and monthly scales.

Development of high-performance graphene-based microwave absorbing materials with low density and strong absorption is of great significance to solve the growing electromagnetic pollution. Herein, a controllable open-cell structure is introduced into graphene aerogels by the graphene oxide (GO) Pickering emulsion. The open-cell graphene aerogel (OCGA) with multiple microstructures shows a significantly enhanced microwave absorption ability without any additions. A high microwave absorption performance with the minimum value of reflection loss (RLmin) of −51.22 dB was achieved, while the material density was only 4.81 mg/cm3. Moreover, by means of centrifugation, the graphene cells were arranged by their diameter, and a gradient, open-cell graphene structure was first fabricated. Based on this unique structure, an amazing microwave absorption value of −62.58 dB was reached on a condition of ultra-low graphene content of 0.53 wt%. In our opinion, such excellent microwave absorption performance results from multiple reflection and well-matched impedance brought by the open-cell and gradient structure, respectively. In addition, the structural strength of the OCGA is greatly improved with a maximum increase of 167% due to the introduction of cell structure. Therefore, the OCGAs with the gradient structure can be an excellent candidate for lightweight, efficient microwave absorption materials.

The Surface Urban Energy and Water Balance Scheme (SUEWS) has recently been introduced to include a bottomup approach to modelling carbon dioxide (CO2) emissions and sink in urban areas. In this study, SUEWS is evaluated against radiation flux observations and eddy covariance (EC) measured turbulent fluxes of sensible heat (QH), latent heat (QE), and CO2 (FC) at a densely built neighborhood in Beijing. The model sensitivity to maximum conductance (gmax) and leaf area index (LAI) is examined. Site-specific gmax is obtained from observations over local vegetation species, and LAI parameters by optimization with remotely sensed LAI obtained from a MODIS/Terra data product. For simulation of anthropogenic CO2 components, local traffic and population data are collected. In model evaluation, the mismatch between the measurement source area and simulation domain is also considered. Using the optimized gmax and LAI, the modelling of heat fluxes is noticeably improved, showing higher correlation with observations, lower bias, and more realistic seasonal dynamics of QE and QH. In comparison to heat fluxes, the FC module shows lower sensitivity to the choice of gmax and LAI. This can be explained by the low relative contribution of vegetation to net FC in the modelled area. SUEWS successfully reproduces the average diurnal cycle of FC and annual cumulative sums. Depending on the size of the simulation domain, the modelled annual accumulated FC ranges from 7.2 to 8.5 kg C m-2 yr-1, when compared to 7.5 kg C m-2 yr-1 observed by EC. Traffic is the dominant CO2 source, contributing 63-73% to the annual total CO2 emissions, followed by human metabolism (14-18%), respiration released by vegetation and soil (6-11%) and building heating (6-9%). Vegetation photosynthesis offsets only 4-8% of the total CO2 emissions. We highlight the importance of choosing optimal LAI parameters and gmax when SUEWS is used to model surface fluxes. The FC module of SUEWS is a promising tool in quantifying urban CO2 emissions at the local scale, and therefore assisting to mitigate urban CO2 emissions. [ABSTRACT FROM AUTHOR]

In order to present a clear and realistic display effect of community ecological environment, an interactive method of community ecological environment adaptation based on virtual reality technology is designed. Through 3DMAX software, a three-dimensional community ecological environment model based on virtual reality technology is designed and the single modeling and scene merging of ecological environment landscapes such as community buildings and vegetation are realized. Texture processing is used to enhance the authenticity of the model, multi-dimensional spatial texture rendering technology is combined with scene database import, multi-dimensional spatial visual data is input to the 3D model of the community ecological environment and the dynamic feature quantity of the multi-vision 3D image of the model is obtained. Combined with the joint sparse feature recognition technology, the Construct multi-vision 3D images, complete model scene rendering and improve realistic effects; the user realizes virtual scene roaming by inputting and modifying the interactive address, direction and angle of view and based on the physical, sensory cognitive and functional affordances, an aging-friendly interactive interface is designed to improve the user's aging-friendly interactive experience. The experimental results show that the three-dimensional community ecological environment display effect of this method is clearer and more realistic. The overall community ecological environment has better lighting and layout and the modeling time is only 5s, the overall error is less than 3%, the fluctuation of the error curve is small and uniform, the stability is good, the scene roaming process is relatively smooth and no stuck pause. [ABSTRACT FROM AUTHOR]

Background and purpose: Despite the significant advancements that have been made in the treatment of gastric cancer, there are still problems such as poor prognosis and low five-year survival rate in advanced gastric cancer. Therefore, exploring effective treatment options remains a key focus of clinical research. As a new type of immune checkpoint inhibitor, the clinical efficacy and safety of pembrolizumab still need to be confirmed by extensive research. Therefore, this study conducted regression analysis of the effect of pembrolizumab combined with XELOX regimen in the treatment of advanced gastric cancer, providing a reference for clinical treatment. Methods: Clinical data of patients with advanced gastric cancer who were admitted to Shanxi Province Cancer Hospital from March 2020 to August 2022 were retrospectively collected. Inclusion criteria: patients with HER2-negative, untreated advanced gastric cancer or adenocarcinoma of the esophagogastric junction, confirmed by clinical histopathological examination and meeting relevant diagnostic criteria; TNM stage Ⅳ; age ≥20 years; expected survival ≥6 months; no severe organ damage before treatment; Karnofsky score >60; patients with complete clinical data. Exclusion criteria: patients with concurrent major organ dysfunction; hypothyroidism or hyperthyroidism; blood or coagulation disorders; autoimmune diseases; lactating or pregnant women; individuals with mental illnesses or a history of mental illness; those with concurrent other malignancies; those with severe liver or kidney dysfunction; patients with incomplete clinical data. Based on the inclusion and exclusion criteria, 91 patients with advanced gastric cancer were selected. Among them, 45 received XELOX regimen treatment (control group), and 46 received pembrolizumab combined with XELOX regimen treatment (observation group). After establishing the database, one patient in the observation group was found to have logical errors in their treatment information and was therefore excluded. Ultimately, 90 patients were included in the study, with 45 in each of the control and observation groups. The efficacy, median overall survival (OS), median progression-free survival (PFS), toxic side effects, improvement in quality of life, and levels of carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), Escherichia coli, Bifidobacterium and Lactobacillus before and after treatment were compared between the two groups. This study was approved by the ethics committee of Shanxi Province Cancer Hospital (ethics number: KY2023081). Results: After treatment, the proportion of progressive disease (PD) in the observation group was 20.0% (9/45), which was lower than that in the control group (40.0%, 18/45). However, there was no significant difference between the two groups in proportion of stable disease (SD), complete response (CR) and partial response (PR) (P>0.05). The improvement rate of quality of life in the observation group after treatment was 60.0% (27/45), which was higher than that in the control group, with a rate of 37.8% (17/45) (P 0.05). Conclusion: The combination of pembrolizumab and XELOX regimen can regulate the expression levels of tumor markers in patients with advanced gastric cancer, prevent disease progression, improve patient quality of life, and help maintain intestinal microecology balance.