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Introduction: Robot-assisted radical cystectomy (RARC) has gained momentum in the management of muscle invasive bladder cancer (MIBC). Predictors of RARC outcomes are not thoroughly studied. We aim to investigate the implications of preoperative hydronephrosis on oncological outcomes. Patients and Methods: This study analysed data from the Asian RARC consortium, a multicentre registry involving nine Asian centres. Cases were divided into two groups according to the presence or absence of pre-operative hydronephrosis. Background characteristics, operative details, perioperative outcomes, and oncological results were reviewed. Outcomes were (1) survival outcomes, including 10-year disease-free survival (DFS) and overall survival (OS), and (2) perioperative and pathological results. Multivariate regression analyses were performed on survival outcomes. Results: From 2007 to 2020, 536 non-metastatic MIBC patients receiving RARC were analysed. 429 had no hydronephrosis (80.0%), and 107 (20.0%) had hydronephrosis. Hydronephrosis was found to be predictive of inferior DFS (HR = 1.701, p = 0.003, 95% CI = 1.196–2.418) and OS (HR = 1.834, p = 0.008, 95% CI = 1.173–2.866). Subgroup analysis demonstrated differences in the T2-or-above subgroup (HR = 1.65; p = 0.004 in DFS and HR = 1.888; p = 0.008 in OS) and the T3-or-above subgroup (HR = 1.757; p = 0.017 in DFS and HR = 1.807; p = 0.034 in OS). Conclusions: The presence of preoperative hydronephrosis among MIBC patients carries additional prognostic implications on top of tumour staging. Its importance in case selection needs to be highlighted.

There is an urgent need for a thorough assessment of forest landscape fragmentation to inform forest protection and restoration, and reforestation policies. However, there is currently a lack of an effective comprehensive index for forest landscape fragmentation, and detailed knowledge of the forest landscape fragmentation dynamics remains insufficient. Here, taking Putian City of Fujian Province in Southeastern China as a case, we employed a forest fragmentation comprehensive index (FFCI) to capture key features of forest landscape fragmentation, such as patch size, number, and distribution. Then, bivariate spatial autocorrelation analysis was employed to identify the spatial associations between the static forest landscape fragmentation (FFCI) and the dynamic forest landscape fragmentation (ΔFFCI), and the spatial coupling modes among the three individual components of FFCI (mean patch area, MPA; aggregation index, AI; patch density, PD) were identified to explore the detail process of forest landscape fragmentation. Finally, the random forest model was applied to observe the impact factors of forest landscape fragmentation dynamics. The findings showed that forest landscapes with different degrees of fragmentation exhibited more noticeable changes at both ends (i.e., either high or lower-level fragmentation), with the intermediate level remaining consistent from 2000 to 2020. Around 18.3% of forest landscapes experienced a decrease in fragmentation, particularly in the northern part of the study area, while approximately 81.7% of forest landscapes exhibited an increasing trend in fragmentation. The bivariate spatial autocorrelation analysis indicated that the proportion of Low–High-type grids was the highest at 17.3%, followed by the High–High type at 7.0%. We also identified eight forest landscape fragmentation modes, which indicate the most significant forest landscape fragmentation pattern is a decrease in MPA and an increase in PD. Moreover, the anthropogenic factors (e.g., population density and night light intensity) were found to dominate the FFCI dynamics during 2000–2020. This study offers an efficient research paradigm for the dynamics of forest landscape fragmentation. The outcomes are conducive to an in-depth comprehension of the detailed dynamic information of forest landscape fragmentation, and supply a scientific foundation for enhancing the overall ecological service function of the forest.

With the rapid development of fully automatic operation (FAO) and location-based services, the evaluation criteria of average localization accuracy can no longer meet our demands, in favor of deterministic localization. However, most localization researches modeled localization performance function and enhanced it by minimizing average localization root mean square error (RMSE). The performance degradation in a small region was not considered. In this paper, we present a survey of deterministic localization and analyze the relationship between accuracy and certainty. In this paper, two common solutions of localization enhancement are presented and their localization certainties are discussed. Furthermore, we carry out related localization enhancement experiments in rail transit line and analyze their improvement on deterministic localization. The experimental results show that the overall localization performance is improved, while the deterministic localization requires the stricter solution to promote.

Skeletal muscle satellite cells, the resident stem cells in pig skeletal muscle, undergo proliferation and differentiation to enable muscle tissue repair. The proliferative and differentiative abilities of these cells gradually decrease during in vitro cultivation as the cell passage number increases. Despite extensive research, the precise molecular mechanisms that regulate this process are not fully understood. To bridge this knowledge gap, we conducted transcriptomic analysis of skeletal muscle satellite cells during in vitro cultivation to quantify passage number-dependent changes in the expression of genes associated with proliferation. Additionally, we explored the relationships between gene transcriptional activity and chromatin accessibility using transposase-accessible chromatin sequencing. This revealed the closure of numerous open chromatin regions, which were primarily located in intergenic regions, as the cell passage number increased. Integrated analysis of the transcriptomic and epigenomic data demonstrated a weak correlation between gene transcriptional activity and chromatin openness in expressed genic regions; although some genes (e.g., GNB4 and FGD5) showed consistent relationships between gene expression and chromatin openness, a substantial number of differentially expressed genes had no clear association with chromatin openness in expressed genic regions. The p53-p21-RB signaling pathway may play a critical regulatory role in cell proliferation processes. The combined transcriptomic and epigenomic approach taken here provided key insights into changes in gene expression and chromatin openness during in vitro cultivation of skeletal muscle satellite cells. These findings enhance our understanding of the intricate mechanisms underlying the decline in cellular proliferation capacity in cultured cells.

The discharge of lead and cadmium wastewater, along with the pollution caused by phosphogypsum, represents a particularly urgent environmental issue. This study employed a straightforward hydrothermal method to convert phosphogypsum into porous calcium silicate hydrate (P-CSH), which was then used to remove and recover Pb(II) and Cd(II) from wastewater. The adsorption capacities of P-CSH for Pb(II) and Cd(II) were notably high at 989.3 mg/g and 290.3 mg/g, respectively. The adsorption processes adhered to the pseudo-second-order kinetics model and the Langmuir isotherm model. Due to identical adsorption sites on P-CSH for both Pb(II) and Cd(II), competitive interaction occurred when both ions were present simultaneously. Additionally, the adsorption efficacy was minimally impacted by the presence of common coexisting cations in wastewater. The dominant mechanisms for removing Pb(II) and Cd(II) via P-CSH were chemical precipitation and surface complexation. Moreover, the adsorbed heavy metals were efficiently separated and reclaimed from the wastewater through a stepwise desorption process. The primary components of the residue from stepwise desorption were quartz and amorphous SiO2. Following dissolution via pressurized alkaline leaching, this residue could be recycled for synthesizing P-CSH. This research offered a new strategy for the resourceful use of phosphogypsum and heavy metal wastewater.

Phosphonates are a class of organic phosphorus (P) compounds that contribute ~25% of dissolved organic P. Recent studies reveal the important role of phosphonates mediated by prokaryotes in the marine P redox cycle. However, its bioavailability by eukaryotic phytoplankton is under debate. 2-Aminoethylphosphonic acid (2-AEP) and 2-amino-3-phosphonopropionic acid (2-AP3) are two biogenic phosphonates in the marine environment. Here, Thalassiosira pseudonana, a common diatom species in the ocean, is able to recover growth from P starvation when provided with 2-AEP and 2-AP3. Moreover, 2-AEP cultures exhibited a more similar growth rate at 12 °C than at 25 °C when compared with inorganic P cultures. The cellular stoichiometry of 2-AEP groups was further determined, the values of which are in-between the P-depleted and DIP-replete cultures. This study provides evidence that biogenic phosphonates could be adopted as alternative P sources to support diatom growth and may provide physiological adaptation.

Alunite is used as a representative mineral for indicating deposits in lithocaps, and lithocaps are generally related to the porphyry–(high-sulfidation) epithermal mineralization system. The study of alunite is of theoretical and exploration significance for prospecting potential underlying porphyry and epithermal deposits. Studies on alunite geochemistry have made breakthroughs, but there is little research on alunite mineralogy, for example, using scanning electron microscopy (SEM) images, differential thermal analysis (DTA), and Fourier-transform infrared spectroscopy (FT-IR). This study mainly focuses on alunite micromorphological characteristics, weight loss changes with temperature, and ionic group structure, aiming to identify the relationship between these features and indications for prospecting. The Fanshan lithocap is located in the northwest part of the Luzong basin, Anhui province of China, and it can potentially be used for exploring porphyry and epithermal deposits. Fanshan alunite is formed in two stages with three types of alunite. IA alunite is formed in the early hydrothermal stage and replaces felsic minerals in the Zhuanqiao Formation, IB alunite is formed in the later hydrothermal stage and fills in open spaces with bladed particles, and II alunite is the product of pyrite oxidation and reaction with other minerals in the supergene stage. Alunite electron microprobe data and energy-dispersive spectroscopy data further confirm temperature decreases with hydrothermal evolution, and the presence of a high-sulfidation epithermal system in the Luzong basin. Aside from the forming environment, SWIR, and geochemistry of alunite, there are other indication indexes; for example, the larger peak values at 3480 cm−1 and smaller peak values at 1080 cm−1 in FT-IR spectra and the deeper exothermic valleys at 750 °C and steeper weight loss slopes in the DTA curve suggest a favorable formation environment for alunite and provide valuable indications for deposit exploration and assessments of mineralization potential.

This study investigated combustion characteristics of composite fuel grains designed based on a modular fuel unit strategy. The modular fuel unit comprised a periodical helical structure with nine acrylonitrile–butadiene–styrene helical blades. A paraffin-based fuel was embedded between adjacent blades. Two modifications of the helical structure framework were researched. One mirrored the helical blades, and the other periodically extended the helical blades by perforation. A laboratory-scale hybrid rocket engine was used to investigate combustion characteristics of the fuel grains at an oxygen mass flux of 2.1–6.0 g/(s·cm2). Compared with the composite fuel grain with periodically extended helical blades, the modified composite fuel grains exhibited higher regression rates and a faster rise of regression rates as the oxygen mass flux increased. At an oxygen mass flux of 6.0 g/(s·cm2), the regression rate of the composite fuel grains with perforation and mirrored helical blades increased by 8.0% and 14.1%, respectively. The oxygen-to-fuel distribution of the composite fuel grain with mirrored helical blades was more concentrated, and its combustion efficiency was stable. Flame structure characteristics in the combustion chamber were visualized using a radiation imaging technique. A rapid increase in flame thickness of the composite fuel grains based on the modular unit was observed, which was consistent with their high regression rates. A simplified numerical simulation was carried out to elucidate the mechanism of the modified modular units on performance enhancement of the composite hybrid rocket grains.

The transmission spectrum of a narrow-band interference filter is crucial and highly influenced by factors such as the temperature and angle, thus requiring precise and online measurements. The traditional method of measuring the transmission spectrum of an interference filter involves the use of a spectrometer, but the accuracy of this method is limited. Moreover, placing a narrow-band interference filter inside a spectrometer hinders real-time online measurements. To address this issue, there is demand for high-precision online spectral testing methods. In response to this demand, we propose and experimentally validate a fine spectral characterization method for narrow-band interference filters. This method uses a narrow-linewidth tunable laser, achieving a spectral resolution in the MHz range for online testing. Two types of narrow-band interference filters were tested using the constructed laser spectroscopy experimental system, obtaining a transmission spectrum with a spectral resolution of 318 MHz. In comparison to spectrometer-based methods, our proposed method demonstrates higher spectral accuracy, enables online measurements, and provides more accurate measurements for special spectral interference filters. This approach has significant application value and promising development prospects.

The excessive accumulation of foam in wastewater treatment plant (WWTP) tanks can impede proper aeration, hindering the effective removal of organic matter from the water. This study proposes a novel technique to monitor in real time the presence of foams in WWTP tanks by using texture segmentation models trained with centralized and federated approaches. These models are designed to segment the foam and quantify the percentage of foam coverage across the entire tank surface. This data provides plant operators with crucial information for identifying the optimal time for foam removal. The proposed methodology is integrated into an image processing pipeline that involves acquiring images using a PTZ camera, ensuring the absence of anomalies in the captured images, and implementing a real-time communication method for event notifications to plant operators. The models exhibit noteworthy performance, achieving an 86% Dice score in foam segmentation, with comparable results obtained through both centralized and federated training. Implemented in a wastewater treatment plant, this integrated pipeline enhances operational efficiency while concurrently reducing costs.

Anisotropic plasmonic metasurfaces have attracted broad research interest since they possess novel optical properties superior to natural materials and their tremendous design flexibility. However, the realization of multi-wavelength selective plasmonic metasurfaces that have emerged as promising candidates to uncover multichannel optical devices remains a challenge associated with weak modulation depths and narrow operation bandwidth. Herein, we propose and numerically demonstrate near-infrared multi-wavelength selective passive plasmonic switching (PPS) that encompasses high ON/OFF ratios and strong modulation depths via multiple Fano resonances (FRs) in anisotropic plasmonic metasurfaces. Specifically, the double FRs can be fulfilled and dedicated to establishing tailorable near-infrared dual-wavelength PPS. The multiple FRs mediated by in-plane mirror asymmetries cause the emergence of triple-wavelength PPS, whereas the multiple FRs governed by in-plane rotational asymmetries avail the implementation of the quasi-bound states in the continuum-endowed multi-wavelength PPS with the ability to unfold a tunable broad bandwidth. In addition, the strong polarization effects with in-plane anisotropic properties further validate the existence of the polarization-resolved multi-wavelength PPS. Our results provide an alternative approach to foster the achievement of multifunctional meta-devices in optical communication and information processing.

Screening and identifying the active compounds in foods are important for the development and utilization of functional foods. In this study, the anti-enteritis activity of ethanol extract from Camellia oleifera oil (PECS) was quickly evaluated using a Smurf Drosophila model and the metabolomics approach, combined with molecular docking techniques, were performed to rapidly screen and identify compounds with potential anti-enteritis activity in PECS. PECS showed good anti-enteritis activity and inhibited the activity of 5-lipoxygenase (LOX), cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS). In particular, wighteone and p-octopamine were newly identified in C. oleifera oil and were proven to have good anti-enteritis activity. The inhibitory activity of kaempferitrin (IC50 = 0.365 mmol L−1) was higher than that of wighteone (IC50 = 0.424 mmol L−1) and p-octopamine (IC50 = 0.402 mmol L−1). Of note, the IC50 value of salazosulfapyridine was 0.810 mmol L−1. Inhibition of LOX activity is likely one of the anti-enteritis mechanisms of PECS. These new findings lay the foundation for further investigations into the underlying mechanisms of anti-enteritis activity in C. oleifera oil.

The grouting quality of the grouting sleeve connector is crucial for ensuring the stability of prefabricated building components. In practical engineering, the grouting sleeve is often arranged with multiple sleeves, and there is no feasible nondestructive testing method for testing the complex arrangement of the sleeve grouting joints in the embedded state. Building upon the feasibility of nondestructive detection of single socket grouting connectors, this study discusses the feasibility of defect detection and the severity of defects. Simulation results are used to investigate the choice of the best excitation signal. For different simulated damage cases, it is proven that the selected damage index can be very sensitive, and both the location and the extent of the damage can be detected successfully. The results demonstrate that with the section injury rate ranging from 10% to 40%, the reverse focus peak decreased from 20% to 60% compared to no injury. The effectiveness of the Lamb−wave−based time reversal method in detecting the internal grouting defects of multiple grouting sleeve joints is proven. This paper focuses on the detection study of the Lamb−wave−based time reversal method and proves its ability to perform the detection task effectively and accurately.

Vast amounts of monitoring data can be obtained through various optical sensors, and mask detection based on deep learning integrates neural science into a variety of applications in everyday life. However, mask detection poses technical challenges such as small targets, complex scenes, and occlusions, which necessitate high accuracy and robustness in multi-scene target detection networks. Considering that multi-scale features can increase the receptive field and attention mechanism can improve the detection effect of small targets, we propose the YOLO-MSM network based on the multi-scale residual (MSR) block, multi-scale residual cascaded channel-spatial attention (MSR-CCSA) block, enhanced residual CCSA (ER-CCSA) block, and enhanced residual PCSA (ER-PCSA) block. Considering the performance and parameters, we use YOLOv5 as the baseline network. Firstly, for the MSR block, we construct hierarchical residual connections in the residual blocks to extract multi-scale features and obtain finer features. Secondly, to realize the joint attention function of channel and space, both the CCSA block and PCSA block are adopted. In addition, we construct a new dataset named Multi-Scene-Mask, which contains various scenes, crowd densities, and mask types. Experiments on the dataset show that YOLO-MSM achieves an average precision of 97.51%, showing better performance than other detection networks. Compared with the baseline network, the mAP value of YOLO-MSM is increased by 3.46%. Moreover, we propose a module generalization improvement strategy (GIS) by training YOLO-MSM on the dataset augmented with white Gaussian addition noise to improve the generalization ability of the network. The test results verify that GIS can greatly improve the generalization of the network and YOLO-MSM has stronger generalization ability than the baseline.

Objectives: To develop and validate a prognostic nomogram based on baseline nutritional and inflammatory parameters for risk stratification in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC) receiving chemotherapy combination programmed death-1 (PD-1) inhibitor. Methods: This retrospective study analyzed 131 patients with dmNPC (88 and 43 in the training and validation cohorts, respectively) between March 2017 and November 2020. All these patients received chemotherapy combined with PD-1 inhibitor treatment. We identified independent risk factors using univariate and multivariate Cox regression analyses and established a nomogram to predict the progression-free survival (PFS). The predictive accuracy of the nomogram was evaluated and independently validated. Results: Baseline nutritional risk index (NRI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), uric acid (UA), and post-treatment Epstein–Barr virus (EBV) DNA were used to develop a nomogram that could divide patients into favorable- and unfavorable-prognosis groups. The median PFS (mPFS) was significantly longer in the favorable-prognosis group compared to the unfavorable-prognosis group (35.10 months [95% CI: 27.36–42.84] vs. 7.23 months [95% CI: 6.50–7.97]; p = 0.001). All results were confirmed in the validation cohort. Conclusions: The proposed model improved the prognostic risk stratification for patients with dmNPC undergoing chemotherapy combined with PD-1 inhibitor treatment.

To investigate the differences in the volatile compounds of plum fruit samples from different cultivars, the volatile compounds of the ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum fruits were analyzed using headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME-GC-MS). The results demonstrated that a total of 938 volatile compounds were identified in three plum fruits, including 200 terpenoids, 171 esters, 116 heterocyclic compounds, 89 hydrocarbons, 82 ketones and alcohols, 63 aldehydes, 54 aromatic hydrocarbons, 21 amines, 18 acids, 17 phenols, 10 nitrogenous compounds, 7 sulfur compounds, and other compounds, 470 of which were common to all the cultivars. Moreover, 704, 691, and 704 volatile substances were detected, respectively, in the ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum, with terpenoids, esters, and heterocycles as the main compounds, accounting for 62.12~72.03% of the volatile compounds. The results of principal component analysis (PCA) and cluster analysis (CA) illustrated that the ‘Fengtang’ plum and ‘Cuihong’ plum were similar in terms of volatile compounds; the ‘Kongxin’ plum compounds were different from those in the other cultivars. Orthogonal partial least squares discriminant analysis was performed, revealing the typical volatile compounds that differed among the plum fruits of the different varieties; thus, the three plum fruits could be better distinguished. These results can provide a theoretical basis for the studies of plum fruit flavor, quality, and geographical origin identification.

Sonodynamic therapy (SDT) induces reactive oxygen species (ROS) to kill tumor cells. Heme oxygenase-1 (HO-1), as an important antioxidant enzyme, resists killing by scavenging ROS. Zinc protoporphyrin (ZnPP) not only effectively inhibits HO-1 activity, but also becomes a potential sonosensitizer. However, its poor water solubility limits its applications. Herein, we developed an improved water-soluble method. It was proved that pegylated zinc protoporphyrin-mediated SDT (PEG-ZnPP-SDT) could significantly enhance ROS production by destroying the HO-1 antioxidant system in ovarian cancer. Increased ROS could cause mitochondrial membrane potential collapse, release cytochrome c from mitochondria to the cytoplasm, and trigger the mitochondrial–caspase apoptotic pathway. In conclusion, our results demonstrated that PEG-ZnPP-SDT, as a novel sonosensitizer, could improve the antitumor effects by destroying the HO-1 antioxidant system. It provided a new therapeutic strategy for SDT to treat cancers, especially those with higher HO-1 expression.

The combustion characteristics of a swirl-radial-injection composite fuel grain were experimentally and numerically investigated. This composite grain permits swirl-radial oxidizer injection based on three hollow helical blades, each having a constant hollow space allowing uniform oxidizer injection into the main chamber along the axial direction. The oxidizer enters from channel inlets located along a hollow outer wall. This wall, together with the three blades, is fabricated as one piece from acrylonitrile-butadiene-styrene using three-dimensional printing. Paraffin-based fuel is embedded in the spaces between adjacent blades. Firing tests were conducted with gaseous oxygen as the oxidizer, using oxidizer mass flow rates ranging from 7.45 to 30.68 g/s. Paraffin-based fuel grains using conventional fore-end injection were used for comparison. Regression rate boundaries were determined taking into account the erosion of the oxidizer channels. The data show that the regression rate was significantly increased even at the lower limit. Images of the combustion chamber flame and of the exhaust plume were also acquired. The flame was found to be concentrated in the main chamber and a smoky plume was observed, consistent with the high regression rate. A three-dimensional simulation was employed. The present design was found to improve fuel/oxidizer mixing and combustion efficiency compared with a fuel grain using fore-end injection. Both the experimental results and numerical simulations confirmed the potential of this swirl-radial-injection fuel grain.

Allelopathy has garnered considerable attention, but the effects of different allelochemicals on invasive plants remain unclear. This study addressed the knowledge gap surrounding allelopathy and its impact on native and invasive plant species. We focused on the impact of caffeic acid and its derivatives on the growth and competitiveness of the native Lantana indica and the invasive plant Solidago canadensis. We selected three allelochemicals, caffeic acid, methyl caffeic acid, and ethyl caffeic acid, for evaluation at two concentrations (0.1 mM and 1.0 mM). Three planting methods were employed: (1) a single species of S. canadensis, (2) a single species of L. indica, and (3) a combination of S. canadensis and L. indica. In addition, a control group was also included. Results revealed that high concentrations (1 mM) of methyl caffeate (MC) and ethyl caffeate (EC) significantly reduced seed germination rate, seed germination index, and seed germination speed index of L. indica compared to a low concentration (0.1 mM). Plant height, stem diameter, biomass, and root length in the control group (CK) of S. canadensis were significantly higher than those in the treated groups. However, with increasing allelochemical concentration, L. indica’s relative competitiveness gradually decreased. These findings provide insights into the concentration-dependent effects of allelopathic compounds on the growth of L. indica and S. canadensis. By analyzing how these allelochemicals influence the growth and competitiveness of native and invasive plants, the study sheds light on the dynamics of allelochemical interactions between these species. This knowledge can be pivotal for understanding plant competition dynamics in ecosystems and could inform strategies to control invasive species or promote native plant growth.

Photocatalytic degradation plays a crucial role in wastewater treatment, and the key to achieving high efficiency is to develop photocatalytic systems that possess excellent light absorption, carrier separation efficiency, and surface-active sites. Among various photocatalytic systems, S-type heterojunctions have shown remarkable potential for efficient degradation. This work delves into the construction of S-type heterojunctions of ternary indium metal sulfide and bismuth ferrite nanofibers with the introduction of sulfur vacancy defects and morphology modifications to enhance the photocatalytic degradation performance. Through the impregnation method, BiFeO3/ZnIn2S4 heterojunction materials were synthesized and optimized. The 30% BiFeO3/ZnIn2S4 heterojunction exhibited superior photocatalytic performance with higher sulfur vacancy concentration than ZnIn2S4. The in-situ XPS results demonstrate that the electrons between ZnIn2S4 and BFO are transferred via the S-Scheme, and after modification, ZnIn2S4 has a more favorable surface morphology for electron transport, and its flower-like structure interacts with the nanofibers of BFO, which has a further enhancement of the reaction efficiency for degrading pollutants. This exceptional material demonstrated a remarkable 99% degradation of Evans blue within 45 min and a significant 68% degradation of ciprofloxacin within 90 min. This work provides a feasible idea for developing photocatalysts to deal with the problem of polluted water resources under practical conditions.

In the process of recycling, dismantling, and reusing household appliances, implementing extended producer responsibility (EPR) has become increasingly important. Designing a reasonable pricing mechanism for waste household appliance recycling is critical for the implementation of EPR. To address the problem of labor-intensive and experience-dependent traditional manual methods for assessing the value of waste household appliances, in this paper, we propose an evaluation method based on the subtractive clustering method and an adaptive neuro fuzzy inference system (SCM–ANFIS), which outperforms traditional neural networks such as LSTM, BP neural network, random forest and Takagi–Sugeno fuzzy neural network (T–S FNN). Moreover, in this paper, we combine the five aforementioned algorithms to design a combination evaluation model based on maximum ratio combination (CEM–MRC), which can achieve a performance improvement of 0.1% in terms of mean absolute percentage error (MAPE) compared to the suboptimal BP neural network. Furthermore, an enhanced evaluation model based on classification selection (EEM–CS) is designed to automatically select the evaluation results between the optimal SCM–ANFIS and the suboptimal CEM–MRC, resulting in a 0.73% reduction in MAPE compared to the optimal SCM–ANFIS and a 1.42% reduction compared to the suboptimal CEM–MRC. In this paper, we also validate the performance of the proposed algorithms using a dataset of waste television recycling, which demonstrates the high accuracy of the proposed value assessment mechanisms achieved without human intervention and a significant improvement in evaluation accuracy as compared to conventional neural-network-based algorithms.

The fault detection time identified by relying on the over-voltage criterion of zero-sequence voltage often lags behind the actual occurrence time of ground faults, which may cause fault protection methods based on transient quantity principles to miss fault characteristics and lose their protection capability. To accurately estimate the time of occurrence of a single-phase-to-ground fault, this paper proposes a two-step dimensionality reduction algorithm for estimating the time of occurrence of a single-phase-to-ground fault in a distribution network. This algorithm constructs a filter based on Empirical Mode Decomposition (EMD) to establish a high-dimensional feature dataset based on the zero-sequence current of all feeders. After Principal Component Analysis and Hilbert Mapping Algorithm, the high-dimensional data are reduced to two dimensions to construct a two-dimensional feature dataset. The density-based clustering method is used to adaptively divide the data into two categories, fault data and non-fault data, so as to estimate the time of occurrence of the fault. The paper designs 11 sets of experiments including 7 common high-resistance grounding mediums to verify the accuracy of the fault time recognition of this algorithm. The accuracy of this algorithm is within 7.3 ms and it exhibits better detection performance compared to the threshold detection method.

The research and development of deep learning methods are heavily reliant on large datasets, and there is currently a lack of scene-rich datasets for synthetic aperture radar (SAR) image vehicle detection. To address this issue and promote the development of SAR vehicle detection algorithms, we constructed the SAR Image dataset for VEhicle Detection (SIVED) using Ka, Ku, and X bands of data. Rotatable bounding box annotations were employed to improve positioning accuracy, and an algorithm for automatic annotation was proposed to improve efficiency. The dataset exhibits three crucial properties: richness, stability, and challenge. It comprises 1044 chips and 12,013 vehicle instances, most of which are situated in complex backgrounds. To construct a baseline, eight detection algorithms are evaluated on SIVED. The experimental results show that all detectors achieved high mean average precision (mAP) on the test set, highlighting the dataset’s stability. However, there is still room for improvement in the accuracy with respect to the complexity of the background. In summary, SIVED fills the gap in SAR image vehicle detection datasets and demonstrates good adaptability for the development of deep learning algorithms.

According to the 2020 global cancer data released by the World Cancer Research Fund (WCRF) International, gastric cancer (GC) is the fifth most common cancer worldwide, with yearly increasing incidence and the second-highest fatality rate in malignancies. Despite the contemporary ambiguous molecular mechanisms in GC pathogenesis, numerous in-depth studies have demonstrated that zinc finger proteins (ZFPs) are essential for the development and progression of GC. ZFPs are a class of transcription factors with finger-like domains that bind to Zn2+ extensively and participate in gene replication, cell differentiation and tumor development. In this review, we briefly outline the roles, molecular mechanisms and the latest advances in ZFPs in GC, including eight principal aspects, such as cell proliferation, epithelial–mesenchymal transition (EMT), invasion and metastasis, inflammation and immune infiltration, apoptosis, cell cycle, DNA methylation, cancer stem cells (CSCs) and drug resistance. Intriguingly, the myeloid zinc finger 1 (MZF1) possesses reversely dual roles in GC by promoting tumor proliferation or impeding cancer progression via apoptosis. Therefore, a thorough understanding of the molecular mechanism of ZFPs on GC progression will pave the solid way for screening the potentially effective diagnostic indicators, prognostic biomarkers and therapeutic targets of GC.

By utilizing low-grade bauxite desilication solution as raw material and adding lime after thermal reaction, adsorbent MCS was synthesized. X-ray diffraction, Brunauer–Emmett–Teller, Fourier transform infrared spectroscopy, and scanning electron microscopy were used to characterize the MCS, MCS-Pb, and MCS-Cu. The Freundlich model was found to be more suitable for isothermal adsorption, suggesting that the adsorption of Cu2+ and Pb2+ by MCS is not limited to monolayer adsorption. According to the results of the experiment, the maximum adsorption capacities of lead ion and copper ion were found to be Pb2+ (1921.506 mg/g) > Cu2+ (561.885 mg/g), and the adsorption was controlled by chemical reactions following pseudo-second-order kinetics. Electrolyte study results indicated that the presence of background electrolyte did not affect the adsorption of Cu2+ and Pb2+ by MCS.

In the present study, the cuticular wax morphology, composition and the relationship with storage quality in three plum cultivars of Prunus salicina ‘Kongxin’ (KXL), Prunus salicina ‘Fengtang’ (FTL) and Prunus salicina ‘Cuihong’ (CHL) were investigated during storage at room temperature of 25 ± 1 °C. The results illustrated that the highest cuticular wax concentration was discovered in KXL, followed by FTL and the lowest in CHL. The fruit wax composition of the three plum cultivars was similar and principally composed of alkanes, alcohols, fatty acids, ketones, aldehydes, esters, triterpenes and olefins. Alcohols, alkanes and triterpenes were the dominant fruit wax compounds of the three plum cultivars. After storage for 20 d at room temperature, the variation of cuticular wax crystal structure and composition showed significant cultivar-associated differences. The total wax content decreased for FTL and CHL and increased for KXL, and the wax crystal degraded and melted together over time. The higher contents of the main components in the three plum cultivars were nonacosane, 1-triacontanol, 1-heneicosanol, nonacosan-10-one, octacosanal, ursolic aldehyde and oleic acid. Alcohols, triterpenes, fatty acids and aldehydes were most dramatically correlated with the softening of fruit and storage quality, and alkanes, esters and olefins were most significantly correlated with the water loss. Nonacosane and ursolic aldehyde can enhance the water retention of fruit. Overall, this study will provide a theoretical reference for the further precise development of edible plum fruit wax.

Botryosphaeria dothidea is the source of the deadly kiwifruit disease known as soft rot. In order to explore the role of melatonin in regulating the postharvest quality and disease resistance of kiwifruit at different growth and development stages, in this study, we applied melatonin at different concentrations to kiwifruit at the young fruit, expansion, and late expansion stages to assess its effect on fruit resistance to B. dothidea, minimize soft rot, and maintain postharvest fruit quality. The results showed that melatonin significantly suppressed the mycelial growth of B. dothidea, with 1.0 mmol/L melatonin inhibiting it by up to 50%. However, 0.1–0.3 mmol/L melatonin had the best control over soft rot. Furthermore, spraying MT during kiwifruit growth can successfully increase fruit weight; preserve postharvest fruit firmness; reduce respiration intensity in the early stages of storage; delay the rise in soluble solids, while maintaining a high titratable acid content to ensure suitable solid acid ratio; increase total phenol, flavonoid, chlorophyll, carotenoid, and ascorbic acid contents; and delay the rise in soluble sugar contents in the late stages of storage. These results have a positive effect on maintaining the nutritional composition of kiwifruit. However, the effects on weight loss, dry matter content, and soluble protein content were not significant. In addition, the results of the principal component analysis demonstrated that 0.3 mmol/L MT increased kiwifruit’s resistance to soft rot while preserving postharvest fruit quality.

The access control (AC) system in an IoT (Internet of Things) context ensures that only authorized entities have access to specific devices and that the authorization procedure is based on pre-established rules. Recently, blockchain-based AC systems have gained attention within research as a potential solution to the single point of failure issue that centralized architectures may bring. Moreover, zero-knowledge proof (ZKP) technology is included in blockchain-based AC systems to address the issue of sensitive data leaking. However, current solutions have two problems: (1) systems built by these works are not adaptive to high-traffic IoT environments because of low transactions per second (TPS) and high latency; (2) these works cannot fully guarantee that all user behaviors are honest. In this work, we propose a blockchain-based AC system with zero-knowledge rollups to address the aforementioned issues. Our proposed system implements zero-knowledge rollups (ZK-rollups) of access control, where different AC authorization requests can be grouped into the same batch to generate a uniform ZKP, which is designed specifically to guarantee that participants can be trusted. In low-traffic environments, sufficient experiments show that the proposed system has the least AC authorization time cost compared to existing works. In high-traffic environments, we further prove that based on the ZK-rollups optimization, the proposed system can reduce the authorization time overhead by 86%. Furthermore, the security analysis is presented to show the system’s ability to prevent malicious behaviors.

Gemcitabine (GEM) is the gold-standard therapeutic regimen for patients with pancreatic cancer (PC); however, patients may receive limited benefits due to the drug resistance of GEM. LncRNA SNHG6 is reported to play key roles in drug resistance, but its role and molecular mechanism in PC remain incompletely understood. We found that LncRNA SNHG6 is drastically downregulated in GEM-resistant PC and is positively correlated with the survival of PC patients. With the help of bioinformatic analysis and molecular approaches, we show that LncRNA SNHG6 can sponge miR-944, therefore causing the upregulation of the target gene KPNA5. In vitro experiments showed that LncRNA SNHG6 and KPNA5 suppress PC cell proliferation and colony formation. The Upregulation of LncRNA SNHG6 and KPNA5 increases the response of GEM-resistant PANC-1 cells to GEM. We also show that the expression of KPNA5 is higher in patients without GEM resistance than in those who developed GEM resistance. In summary, our findings indicate that the LncRNA SNHG6/miR944/KPNA5 axis plays a pivotal role in overcoming GEM resistance, and targeting this axis may contribute to an increasing of the benefits of PC patients from GEM treatment.

Extremely rapid heating and cooling rates during the additive manufacturing (AM) process generate complicated thermal cycles, which affect the microstructure evolution and ultimate mechanical properties of the alloy. In this paper, FGH96 blocks with a height of 6 mm were prepared by selective laser melting (SLM) and the microstructure was characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Comparing specimens of varying heights, it was found that subsequent thermal cycles (STC) coarsened some solidified grains and accelerated the grain growth along the build direction, together with an increase in texture intensity and high-angle grain boundaries (HAGBs). After coarsening the grains in the middle portion of the built block, finer grains were observed near the top area due to a faster cooling rate. There were numerous dislocations in the grain because of the occurrence of unequal internal tension. In the middle of the sample with stable thermal cycles, the dislocations were both perpendicular to the grain growth direction and 45° off it. In spite of the texture characteristics, the segregation of elements was also found to be influenced by thermal cycling. Inherent reheating leads to the increase in the Laves phase and the decrease in the γ’ phase as subsequent deposition. This was also one of the reasons why the microhardness of the sample decreased as the building height and the other reason being the decrease in the solution treatment of the later sediments.

Investigating the impact of field plot size on the performance of estimation models for forest inventory attributes could help optimize the technical schemes for an operational airborne LiDAR-assisted forest resource inventory. However, few studies on the topic have focused on subtropical forests. In this study, 104 rectangular plots of 900 m2 (subdivided into nine quadrats with an area of 10 × 10 m) in subtropical planted forests (Chinese fir, pine, eucalyptus, and broad-leaved forest, 2–56 years old) were used to establish four datasets with six different plot sizes (100, 200, 300, 400, 600, and 900 m2) by combining quadrats. The differences in the LiDAR-derived metrics and forest attributes between plots of different sizes were statistically analyzed. Based on the multivariate power models with stable structures, the differences in estimation accuracies of the stand volume (VOL) and basal area (BA) using plot data of different sizes were compared. The results indicated that: (1) the mean differences in LiDAR-derived metrics of the plots of different sizes in all forest types were small, and most of them had no statistically significant differences (α = 0.05) between the plots of different sizes and the 900 m2 plots; however, the standard deviation of the difference increased rapidly with decreasing plot size; (2) except for the maximal tree height of the plots, the other forest attributes, including the mean tree height, diameter at breast height, BA, and VOL of all forest types, showed no statistically significant differences between the plots of different sizes and the 900 m2 plots; and (3) with increasing plot size, the accuracies of VOL and BA estimations improved markedly, and the effects of plot size on the estimation accuracies of the different forest attributes and different forest types were essentially the same. Spatial averaging resulted in the variations in the independent variables (LiDAR variables) and dependent variables (forest attributes) decreasing gradually with the increasing plot size, which was the main reason for the model’s accuracy improving. In applying airborne LiDAR to a large-scale subtropical planted forest inventory, the plot size should be at least 600 m2 for all forest types.

Cuticular wax is an essential barrier against biological and abiotic stress and is also an important factor affecting fruit storage quality. This paper investigated the effect of melatonin treatment on cuticular wax and the storage quality of plum fruit at low temperature storage of 4 ± 1 °C. ‘Kongxin’ plum was treated with 150 μmol·L−1 melatonin, dried overnight at room temperature 25 ± 1 °C, and then stored at 4 ± 1 °C for 40 d. The microstructure of the fruit epidermis was examined after 0, 20, and 40 d of storage, and the wax composition and fruit storage quality were measured at 10 d intervals. The results demonstrated that melatonin promoted the disintegration and thickening of rod-shaped waxy crystals of ‘Kongxin’ plum fruit and inhibited the combination of disintegrated wax and inner wax. Melatonin maintained fruit firmness and decreased the correlation between fruit firmness and other storage quality parameters. The correlation between firmness and wax composition was enhanced. Melatonin promoted long-chain alkanes that were positively correlated with firmness and water retention and strengthened the correlation between the length of the alkane chain and storage quality parameters but reduced the difference between alkane isomers and storage quality parameters.

Complex thermal cycles and stress fields commonly occur in the selective laser melting process for nickel-based superalloys, which are prone to generating cracks and decreasing the performance of forming parts. In this paper, the reasons for cracking were analyzed by combining the experiment with the evolution behavior of the temperature field/stress field during the solidification process of a nickel-based superalloy (FGH96) via a three-dimensional finite element thermo-mechanical coupling model. It showed that a radial temperature distribution of the melting pool led to a similar distributed stress; as a result, the value declined slowly along the scanning direction but declined quickly along the direction perpendicular to the scanning direction. A stress concentration with maximum stress up to 339 MPa was found at the center of the molten pool, easily causing a crack in SLM. It was found that both the initiation and propagation of the cracks were along the grain growth direction and were affected by the epitaxial growth of columnar crystals. For the case of process parameters with relatively high power or low scanning speed, the stress value of the molten pool during solidification was more than 370 MPa so as to form a large area of cracks. The adjustment of the rotation angle between the adjacent layers was effective at avoiding stress accumulation in the building direction and prevent the formation of long grain boundaries, thus avoiding crack propagation. The present study lays a foundation for the wide applications of selective laser melting technologies in nickel-based superalloys.

Background: ABO-incompatible liver transplantation (ABOi LT) under the desensitization protocol with rituximab had excellent survival outcomes comparable to those of ABO-compatible liver transplantation (ABOc LT). In this work, we explored the effect of ABOi LT on recipients from the perspective of biliary microbiota and metabonomics. Methods: Liver transplant (LT) recipients treated at our center were enrolled in the study. In total, 6 ABOi LT recipients and 12 ABOc LT recipients were enrolled, and we collected their bile five times (during LT and at 2 days, 1 week, 2 weeks and 1 month after LT). The collected samples were used for 16S ribosomal RNA sequencing and liquid chromatography mass spectrometry analysis. Results: We obtained 90 bile samples. Whether in group ABOi LT or ABOc LT, the most common phyla in all of the samples were Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria. The most common genera were Lactobacillus, Weissella, Klebsiella, Pantoea and Lactococcus. There was no significant difference in the diversity between the two groups at 1 week, 2 weeks and 1 month after LT. However, the biggest disparities between the ABOi LT recipients and ABOc LT recipients were observed 2 days after LT, including increased biodiversity with a higher ACE, Chao1, OBS and Shannon index (p < 0.05), and more Staphylococcus in ABOi LT and binary–Jaccard dissimilarity, which indicated varying β-diversity (p = 0.046). These differences were not observed at 1 week, 2 weeks and 1 month after LT. The principal coordinate analysis (PCoA) revealed that the composition of the bile microbiota did not change significantly within 1 month after LT by longitudinal comparison. In an analysis of the bile components, the metabolites were not significantly different every time. However, four enrichment KEGG pathways were observed among the groups. Conclusion: These findings suggest that ABOi LT under the desensitization protocol with rituximab did not significantly affect the biliary microbiota and metabolites of recipients.

Kapok fiber (KF), with the characteristics of a natural hollow structure, light weight, and low density, can be used as acoustic and thermal insulation, buoyancy, adsorption, filling, and composite material. The flame-retardant treatment can expand the functionality and application of KF. In this work, the phosphorylation of KF using phytic acid (PA) in the presence of urea at a high temperature was used to enhance its flame retardancy. The phosphorylation reaction conditions were discussed, and the surface topography, thermal degradation, heat release, and combustion properties of phosphorylated KF were studied. The Fourier transform infrared spectroscopy and 31P solid-state nuclear magnetic resonance spectroscopy analyses confirmed the grafting of PA on cellulose by the formation of phosphate ester bonds. Due to the covalent binding of PA, phosphorylated KF exhibited good washing durability. The surface topography, Raman spectroscopy, thermogravimetric (TG), and microcalorimetry analyses revealed the excellent charring ability of phosphorylated KF. In the TG test in nitrogen, the char residue increased to 42.6% of phosphorylated KF from 8.3% of raw KF at 700 °C. In the vertical combustion, raw KF sheet was almost completely burned out within 30 s, while phosphorylated KF was very difficult to catch fire. In the microcalorimetry analysis, the heat release capacity and total heat release of phosphorylated KF decreased to 67 J/g∙K and 3.9 kJ/g, respectively from 237 J/g∙K and 18.1 kJ/g of raw KF. This work suggests that phosphorylated KF is an excellent flame-retardant material.

Fano resonances that feature strong field enhancement in the narrowband range have motivated extensive studies of light–matter interactions in plasmonic nanomaterials. Optical metasurfaces that are subject to different mirror symmetries have been dedicated to achieving nanoscale light manipulation via plasmonic Fano resonances, thus enabling advantages for high-sensitivity optical sensing and optical switches. Here, we investigate the plasmonic sensing and switches enriched by tailorable multiple Fano resonances that undergo in-plane mirror symmetry or asymmetry in a hybrid rotational misalignment metasurface, which consists of periodic metallic arrays with concentric C-shaped- and circular-ring-aperture unit cells. We found that the plasmonic double Fano resonances can be realized by undergoing mirror symmetry along the X-axis. The plasmonic multiple Fano resonances can be tailored by adjusting the level of the mirror asymmetry along the Z-axis. Moreover, the Fano-resonance-based plasmonic sensing that suffer from mirror symmetry or asymmetry can be implemented by changing the related structural parameters of the unit cells. The passive dual-wavelength plasmonic switches of specific polarization can be achieved within mirror symmetry and asymmetry. These results could entail benefits for metasurface-based devices, which are also used in sensing, beam-splitter, and optical communication systems.

A microseismic (MS) monitoring system was established, and numerical modeling was performed using Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) to examine the evolution characteristics of MS events during the excavation of underground caverns under high geostress. Specifically, the spatial and temporal damage characteristics of the rock mass, the dynamic relationship between the evolution of MS events, the site construction conditions, and the geological structures under high geostress were also analyzed. In addition, a three-dimensional numerical model of underground caverns was built to demonstrate the deformation characteristics of the rock mass. As a result, the characteristics of a large number of MS events, multiple concentration zones of MS events, and long periods of stress adjustment were discovered in underground caverns under high geostress. It was found that the primary cause of MS events was site blasting construction. In particular, the distribution of the MS events was strongly correlated with the location of the site blasting construction, and the frequency of the MS events was positively correlated with it. The structural plane is a discontinuous plane with very low or no tensile strength, and its presence also increased the number of MS events and raised the possibility of the surrounding rock becoming unstable. Moreover, the MS monitoring data agreed with the numerical modeling results, which can be useful in estimating damage to underground caverns under high geostress and predicting disasters.

Reducing radiation dose to patients without compromising imaging quality has been an important issue in the medical use of X-ray computed tomography (CT). In this study, based on the conceptual designs of different types of attenuation filters, the radiation doses to patients who undergo a typical head, thorax and abdomen scan using a cone-beam CT with different scanning protocols were simulated using the Monte Carlo method, and the isotropy of the noise power spectrum (NPS) of the reconstructed images was also calculated. Compared to the scanning protocol without attenuation and tube current modulation (TCM), the results showed that the fluid dynamic bowtie filter (FDB) combined with the TCM technique reduced the average organ dose by 70%, 34% and 60% for a typical head, thorax and abdomen scan, respectively, and the NPS isotropy of the reconstructed images was also significantly improved. Compared to most currently used static bowtie filters, the FDB has a higher potential to reduce the dose for patients undergoing CT scans. Further efforts are warranted to make the FDB technique clinically useful.

SF6, which is currently widely used in gas-insulated power transmission equipment, is a greenhouse gas with a very strong greenhouse effect. Therefore, developing environmentally friendly gas insulation equipment to gradually reduce the use of SF6 has become a hot research topic. As the most potential alternative gas, C4F7N is of great significance to study the electrical characteristics of the medium-voltage switching field to promote the green development of the power industry. Based on multi-physical field coupling to construct the 40.5 kV circuit breaker mode, this paper uses C4F7N/CO2 mixed gas to compare and study the dynamic characteristics of a C4F7N/CO2 mixed gas circuit breaker when breaking the short-circuit current and the dielectric recovery strength with no-load breaking, as well as to evaluate the electrical performance of C4F7N mixed gas in a 40.5 kV breaker with the gas breakdown criterion. The results show that mixing O2 in a high current can improve the breaking performance of an environmental protection circuit breaker and increasing the C4F7N mass fraction can enhance the dielectric recovery strength of the environmentally friendly circuit breaker. Considering the overall performance of the gas, the 5%C4F7N/90% CO2/5%O2 mixed gas has some alternative potential.

Plums are one of the most popular stone fruits worldwide owing to their high nutritional value. After harvest, plum fruit quality and flavor change during storage; however, little is known about the changes in metabolites during this period. A comprehensive comparison of primary metabolites in ‘Fengtang’ plum fruits during storage is performed using widely targeted primary metabolomics. A total of 272 primary metabolites were identified by means of ultra-performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS) in the plums at different storage periods. There was a significant increase in the relative amounts of twenty-eight lipids, twenty amino acids and their derivatives, thirteen organic acids, ten saccharides and alcohols, six nucleotides and their derivatives, and two vitamins. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential metabolites revealed that glucosinolate biosynthesis, starch and sucrose metabolism, ascorbate and aldarate metabolism, lysine degradation, and other metabolic pathways were significantly enriched; therefore, changes in these metabolic pathways may be key to the quality and flavor change in ‘Fengtang’ plum fruits during storage. Our results provide a theoretical foundation and technical support to evaluate ‘Fengtang’ plum fruit quality.

Photodynamic therapy (PDT) has significant advantages in the treatment of malignant tumors, such as high efficiency, minimal invasion and less side effects, and it can preserve the integrity and quality of the organs. The power density, irradiation time and photosensitizer (PS) concentration are three main parameters that play important roles in killing tumor cells. However, until now, the underlying relationships among them for PDT outcomes have been unclear. In this study, human malignant glioblastoma U-118MG and melanoma A375 cells were selected, and the product of the power density, irradiation time and PS concentration was defined as the total photodynamic parameter (TPP), in order to investigate the mechanisms of PS sinoporphyrin sodium (DVDMS)-mediated PDT (DVDMS-PDT). The results showed that the survival rates of the U-118MG and A375 cells were negatively correlated with the TPP value in the curve, and the correlation exactly filed an e-exponential function. Moreover, according to the formula, we realized controllable killing effects of the tumor cells by randomly adjusting the three parameters, and we finally verified the accuracy and repeatability of the formula. In conclusion, the establishment and implementation of a newly functional relationship among the PDT parameters are essential for predicting PDT outcomes and providing personalized precise treatment, and they are contributive to the development of PDT dosimetry.

The closely related species Helicoverpa armigera (H. armigera) and Helicoverpa assulta (H. assulta) have different host plant ranges and share two principal components of sex pheromones but with reversed ratios. The antennae are the main olfactory organ of insects and play a crucial role in host plant selection and mate seeking. However, the genetic basis for gene expression divergence in the antennae of the two species is unclear. We performed an allele-specific expression (ASE) analysis in the antennal transcriptomes of the two species and their F1 hybrids, examining the connection between gene expression divergence and phenotypic differences. The results show that the proportion of genes classified as all cis was higher than that of all trans in males and reversed in females. The contribution of regulatory patterns to gene expression divergence in males was less than that in females, which explained the functional differentiation of male and female antennae. Among the five groups of F1 hybrids, the fertile males from the cross of H. armigera female and H. assulta male had the lowest proportion of misexpressed genes, and the inferred regulatory patterns were more accurate. By using this group of F1 hybrids, we discovered that cis-related regulations play a crucial role in gene expression divergence of sex pheromone perception-related proteins. These results are helpful for understanding how specific changes in the gene expression of olfactory-related genes can contribute to rapid evolutionary changes in important olfactory traits in closely related moths.

The growing environmental concerns and the significant energy consumption in hotel buildings make the ability to proactively manage energy and lower carbon intensity essential in the global hospitality industry. Activating guests’ energy-conservation behaviours is a potential strategy for sustainable hotel operation and maintenance. Yet, the psychological mechanism of hotel building energy-conservation intention and the roles of personality traits have not been sufficiently investigated. This study aims to examine the role of guests’ extraversion levels in their hotel building energy-conservation behavioural intention using a modified theory of planned behaviour (TPB) model. The study extends the TPB model with personal norms and past behaviour as two additional factors and employs past behaviour as a moderator to bridge extraversion and other psychological factors. A field experiment was conducted consisting of 530 hotel guests in Shanghai, China. The results demonstrate the relationships between attitude, behavioural control, personal norms, past behaviour and energy-conservation intention. Specifically, extraversion negatively influences perceived behavioural control (PBC) (β = −0.176, p < 0.001) and positively impacts on personal norms (β = 0.290, p < 0.001), both of which significantly contribute to guest energy-saving intention. In addition, past behaviours positively moderate the effects of extraversion on subjective norms and personal norms. This research enriches the hospitality and tourism management literature by shedding novel light on how guests’ personality characteristics influence their pro-environment intentions during their stays in hotel buildings. The findings would drive the hotel building energy management forward through actionable and effective energy-conservation interventions and enhanced guest satisfaction.

Accurate medical imaging segmentation of the retinal fundus vasculature is essential to assist physicians in diagnosis and treatment. In recent years, convolutional neural networks (CNN) are widely used to classify retinal blood vessel pixels for retinal blood vessel segmentation tasks. However, the convolutional block receptive field is limited, simple multiple superpositions tend to cause information loss, and there are limitations in feature extraction as well as vessel segmentation. To address these problems, this paper proposes a new retinal vessel segmentation network based on U-Net, which is called multi-scale cross-position attention network (MCPANet). MCPANet uses multiple scales of input to compensate for image detail information and applies to skip connections between encoding blocks and decoding blocks to ensure information transfer while effectively reducing noise. We propose a cross-position attention module to link the positional relationships between pixels and obtain global contextual information, which enables the model to segment not only the fine capillaries but also clear vessel edges. At the same time, multiple scale pooling operations are used to expand the receptive field and enhance feature extraction. It further reduces pixel classification errors and eases the segmentation difficulty caused by the asymmetry of fundus blood vessel distribution. We trained and validated our proposed model on three publicly available datasets, DRIVE, CHASE, and STARE, which obtained segmentation accuracy of 97.05%, 97.58%, and 97.68%, and Dice of 83.15%, 81.48%, and 85.05%, respectively. The results demonstrate that the proposed method in this paper achieves better results in terms of performance and segmentation results when compared with existing methods.

In this study, a strategy was developed for in situ, non-intrusive, and quantitative measurement of the oxides of nitrogen (NO and NO2) to describe emission characteristics in gas turbines. The linear calibration-free wavelength modulation spectroscopy (LCF-WMS) approach combined with the temperature profile-fitting strategy was utilized for trace NO and NO2 concentration detection with broad spectral interference from gaseous water (H2O). Transition lines near 1308 nm, 5238 nm, and 6250 nm were selected to investigate the H2O, NO, and NO2 generated from combustion. Experiments were performed under different equivalence ratios in a combustion exhaust tube, which was heated at 450–700 K, with an effective optical length of 1.57 m. Ultra-low NOx emissions were captured by optical measurements under different equivalence ratios. The mole fractions of H2O were in agreement with the theoretical values calculated using Chemkin. Herein, the uncertainty of the TDLAS measurements and the limitation of improving the relative precision are discussed in detail. The proposed strategy proved to be a promising combustion diagnostic technique for the quantitative measurement of low-absorbance trace NO and NO2 with strong H2O interference in real combustion gases.

Brain tumor semantic segmentation is a critical medical image processing work, which aids clinicians in diagnosing patients and determining the extent of lesions. Convolutional neural networks (CNNs) have demonstrated exceptional performance in computer vision tasks in recent years. For 3D medical image tasks, deep convolutional neural networks based on an encoder–decoder structure and skip-connection have been frequently used. However, CNNs have the drawback of being unable to learn global and remote semantic information well. On the other hand, the transformer has recently found success in natural language processing and computer vision as a result of its usage of a self-attention mechanism for global information modeling. For demanding prediction tasks, such as 3D medical picture segmentation, local and global characteristics are critical. We propose SwinBTS, a new 3D medical picture segmentation approach, which combines a transformer, convolutional neural network, and encoder–decoder structure to define the 3D brain tumor semantic segmentation job as a sequence-to-sequence prediction challenge in this research. To extract contextual data, the 3D Swin Transformer is utilized as the network’s encoder and decoder, and convolutional operations are employed for upsampling and downsampling. Finally, we achieve segmentation results using an improved Transformer module that we built for increasing detail feature extraction. Extensive experimental results on the BraTS 2019, BraTS 2020, and BraTS 2021 datasets reveal that SwinBTS outperforms state-of-the-art 3D algorithms for brain tumor segmentation on 3D MRI scanned images.

Imidazole compounds are important constituents of atmospheric brown carbon. The imidazole components of aqueous secondary organic aerosol (aqSOA) that are generated from the evaporation of droplets containing pyruvaldehyde and inorganic ammonium are on-line characterized by an aerosol laser time-of-flight mass spectrometer (ALTOFMS) and off-line detected by optical spectrometry in this study. The results demonstrated that the laser desorption/ionization mass spectra of aqSOA particles that were detected by ALTOFMS contained the characteristic mass peaks of imidazoles at m/z = 28 (CH2N+), m/z = 41 (C2H3N+) and m/z = 67 (C3H4N2+). Meanwhile, the extraction solution of the aqSOA particles that were measured by off-line techniques showed that the characteristic absorption peaks at 217 nm and 282 nm appeared in the UV-Vis spectrum, and the stretching vibration peaks of C-N bond and C=N bond emerged in the infrared spectrum. Based on these spectral information, 4-methyl-imidazole and 4-methyl-imidazole-2-carboxaldehyde are identified as the main products of the reaction between pyruvaldehyde and ammonium ions. The water evaporation accelerates the formation of imidazoles inside the droplets, possibly owing to the highly concentrated environment. Anions, such as F−, CO32−, NO3−, SO42− and Cl− in the aqueous phase promote the reaction of pyruvaldehyde and ammonium ions to produce imidazole products, resulting in the averaged mass absorption coefficient () in the range of 200–600 nm of aqSOA increases, and the order of promotion is: F− > CO32− > SO42− ≈ NO3− ≈ Cl−. These results will help to analyze the constituents and optics of imidazoles and provide a useful basis for evaluating the formation process and radiative forcing of aqSOA particles.

Retinal vessel segmentation is extremely important for risk prediction and treatment of many major diseases. Therefore, accurate segmentation of blood vessel features from retinal images can help assist physicians in diagnosis and treatment. Convolutional neural networks are good at extracting local feature information, but the convolutional block receptive field is limited. Transformer, on the other hand, performs well in modeling long-distance dependencies. Therefore, in this paper, a new network model MTPA_Unet is designed from the perspective of extracting connections between local detailed features and making complements using long-distance dependency information, which is applied to the retinal vessel segmentation task. MTPA_Unet uses multi-resolution image input to enable the network to extract information at different levels. The proposed TPA module not only captures long-distance dependencies, but also focuses on the location information of the vessel pixels to facilitate capillary segmentation. The Transformer is combined with the convolutional neural network in a serial approach, and the original MSA module is replaced by the TPA module to achieve finer segmentation. Finally, the network model is evaluated and analyzed on three recognized retinal image datasets DRIVE, CHASE DB1, and STARE. The evaluation metrics were 0.9718, 0.9762, and 0.9773 for accuracy; 0.8410, 0.8437, and 0.8938 for sensitivity; and 0.8318, 0.8164, and 0.8557 for Dice coefficient. Compared with existing retinal image segmentation methods, the proposed method in this paper achieved better vessel segmentation in all of the publicly available fundus datasets tested performance and results.