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Abstract Diagnosing pneumoconiosis is challenging because the lesions are not easily visible on chest X-rays, and the images often lack clear details. Existing deep detection models utilize Feature Pyramid Networks (FPNs) to identify objects at different scales. However, they struggle with insufficient perception of small targets and gradient inconsistency in medical image detection tasks, hindering the full utilization of multi-scale features. To address these issues, we propose an Optimized Multi-Scale Feature Fusion learning framework, OMSF2, which includes the following components: (1) Data specificity augmentation module is introduced to capture intrinsic data representations and introduce diversity by learning morphological variations and lesion locations. (2) Multi-scale feature learning module is utilized that refines micro-feature localization guided by heatmaps, enabling full extraction of multi-directional features of subtle diffuse targets. (3) Multi-scale feature fusion module is employed that facilitates the fusion of high-level and low-level features to better understand subtle differences between disease stages. Notably, this paper innovatively proposes a method for fine learning of low-resolution micro-features in pneumoconiosis, addressing the issue of maintaining cross-layer gradient consistency under multi-scale feature fusion. We established an enhanced pneumoconiosis X-ray dataset to optimize the lesion detection capability of the OMSF2 model. We also introduced an external dataset to evaluate other chest X-rays with complex lesions. On the AP-50 and R-50 evaluation metrics, OMSF2 improved by 3.25% and 3.31% on the internal dataset, and by 2.28% and 0.24% on the external dataset, respectively. Experimental results show that OMSF2 achieves significantly better performance than state-of-the-art baselines in medical image detection tasks.

In the past decade, there has been an increasing recognition of the role of computational design optimization in early-stage performance-based architectural design exploration. However, it remains challenging for designers to apply such optimization-based design explorations in practice. To address this issue, this paper introduces a design tool, called EvoMass, and an associated design method that facilitates design exploration for building massing typologies in performance-based design tasks. EvoMass is capable of offering architects design options reflecting performance-related building massing typologies for the design task, without necessitating advanced computational design skills. More importantly, it can provide architects with insights into the underlying performance implications, thereby enhancing early-stage performance-based design exploration. EvoMass and its associated design method overcome the limitation in the conventional typology-first-optimization-second design procedure adopted by most existing tools, and it promotes a typology-oriented design exploration method of using computational optimization in performance-based architectural design. To demonstrate the efficacy of EvoMass, case studies derived from architectural design studio tasks, incorporating daylighting, solar exposure, and subjective design intents, and the result of a user survey are presented, which highlights how EvoMass and the performance-based design optimization and exploration can enable architects to achieve a more performance-aware design.

Summary: During space travel, microgravity leads to disturbances in cognitive function, while the underlying mechanism is still unclear. Simulated microgravity mice showed neuronal age-like changes in the hippocampus of our study. In the context of microgravity, we discovered m6A modification reshapes in the hippocampal region. When paired with RNA-seq and MeRIP-seq, Shox2 was found to be a powerful regulator in hippocampal neuron that respondes to microgravity. Decreased expression of senescence-associated secretory phenotype factors and improved genes related to synapses led to the restoration of memory function in the hippocampus upon increased expression of Shox2. Moreover, we discovered that IGF2BP2 was required for the m6A modification of the Shox2, and overexpressed IGF2BP2 in the hippocampus protected against both neuronal senescence and learning and memory decline caused by loss of gravity. Accordingly, our research identified the hippocampal IGF2BP2-Shox2 axis as a possible therapeutic approach to maintaining cognitive function during space travel.

To investigate the effects of different aging times on the volatile flavor substances of rosy vinegar, headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used to investigate the physicochemical and volatile flavor components of fresh, one-year-old, three-year-old and ten-year-old samples. The results showed that the content of reducing sugars and amino acid nitrogen increased during aging, and promoted the flavor and color development of rosy vinegar. A total of 79 volatile flavor substances were detected in rosy vinegar by HS-SPME-GC-MS, among which most of the esters were degraded during aging, while the content of carbonyl compounds and pyrazines increased significantly during aging. 13 volatile compounds with odor activity value greater than 1 were calculated in rosy vinegar by odor threshold value, and the main odor-presenting compounds differed in different aging periods. Principal component and cluster analyses revealed significant separation among the rosy vinegar samples at different aging periods, indicated that the aging time has an important influence on the composition of volatile substances in rosy vinegar.

Abstract Aggressiveness and drug resistance are major challenges in the clinical treatment of glioblastoma (GBM). Our previously research reported a novel candidate oncogene ribosomal protein L22 like 1 (RPL22L1). The aim of this study was to elucidate the potential role and mechanism of RPL22L1 in progression and temozolomide (TMZ) resistance of GBM. Online database, tissue microarrays and clinical tissue specimens were used to evaluate the expression and clinical implication of RPL22L1 in GBM. We performed cell function assays, orthotopic and subcutaneous xenograft tumor models to evaluate the effects and molecular mechanisms of RPL22L1 on GBM. RPL22L1 expression was significantly upregulated in GBM and associated with poorer prognosis. RPL22L1 overexpression enhanced GBM cell proliferation, migration, invasion, TMZ resistance and tumorigenicity, which could be reduced by RPL22L1 knockdown. Further, we found RPL22L1 promoted mesenchymal phenotype of GBM and the impact of these effects was closely related to EGFR/STAT3 pathway. Importantly, we observed that STAT3 specific inhibitor (Stattic) significantly inhibited the malignant functions of RPL22L1, especially on TMZ resistance. RPL22L1 overexpressed increased combination drug sensitive of Stattic and TMZ both in vitro and in vivo. Moreover, Stattic effectively restored the sensitive of RPL22L1 induced TMZ resistance in vitro and in vivo. Our study identified a novel candidate oncogene RPL22L1 which promoted the GBM malignancy through STAT3 pathway. And we highlighted that Stattic combined with TMZ therapy might be an effective treatment strategy in RPL22L1 high-expressed GBM patients.

The incorporation of physical environmental performance as a primary consideration in building design can facilitate the harmonization of the built environment with the surrounding site and climate, enhance the building’s environmental adaptability and environmental friendliness, and contribute to the achievement of energy-saving and emission-reduction objectives through the integration of natural lighting and ventilation. General computational fluid dynamics (CFD) can help architects make accurate predictions and effectively control the building’s wind environment. However, CFD integration into the design workflow in the preliminary stages is frequently challenging due to program uncertainty, intricate parameter settings, and substantial computational expenses. This study offers a methodology and framework based on machine learning to overcome the complexity and computational cost barriers in simulating outdoor wind environments of buildings. In this framework, the machine learning model is trained using an automated CFD simulation system based on Butterfly and implemented within the Rhino and Grasshopper environment. This framework provides real-time simulation feedback within the design software and exhibits promising accuracy, with a Structural Similarity Index Measure (SSIM) ranging from 90–97% on a training dataset of 1200 unique urban geometries in Xinjiekou Area of Nanjing, China. Furthermore, we programmatically integrate various parts of the simulation and computation process to automate multiscenario CFD simulations and computations. This automation saves a significant amount of time in producing machine-learning training sets. Finally, we demonstrate the effectiveness and accuracy of the proposed working framework in the design process through a case study. Although our approach cannot replace CFD simulation computation in the later design stages, it can support architects in making design decisions in the preliminary stages with minimal effort and immediate performance feedback.

Based on five periods of Landsat remote sensing data from 1980 to 2020, this study constructs a landscape ecological risk-ecosystem service value evaluation model and integrates it with a geodetector model to analyse the environmental benefits of the development of the “production–living–ecological space” pattern and its driving factors in the Xuzhou planning area. The results of the study are as follows: (1) Over the past 40 years, the expansion of living spaces has significantly encroached upon adjacent agricultural production areas and ecological spaces, such as forests and grasslands. Specifically, the areas of agricultural land, forests, and grassland have been diminished by 277.39 km2, 23.8 km2 and 12.93 km2, respectively; in contrast, urban and rural living spaces have increased by 238.62 km2 and 58.92 km2, alongside a rise in industrial production areas, water bodies, and other ecological spaces. (2) Throughout the 40-year period, both the landscape ecological risk (ERI) and ecosystem service value (ESV) in the study area have shown a decreasing trend. The proportion of high- and medium-high-risk areas of the ERI have decreased by 5.19% and 7.50%, respectively, while low, lower, and medium ecological risk areas have increased by 6.40%, 3.22% and 3.07%, respectively. In addition, low-ESV areas have increased by 14.22%, while the proportion of high- and medium-high-ESV areas have decreased by 1.16%. (3) There is a significant positive spatial correlation between the ERI and ESV. Regions with dense ecological spaces comprising forests, water bodies, and grasslands, particularly in the northeastern part of the Jiawang District and the southeastern part of the Tongshan District, demonstrate superior regional ecosystem service quality. The ERI and ESV are dominated by “high–high” and “low–high” aggregation. Conversely, in the southwestern part of the study area, the expansion of living space has led to the transformation of some agricultural land, forest land, and grassland into less risky construction land, resulting in a decline in the quality of regional ecosystem services. The local spatial correlation between the ERI and ESV changed from “high–high”, “low–low”, “low–high” agglomeration to “low–low” agglomeration. (4) Key factors influencing the spatial differentiation of the “production–living–ecological space” include the GDP, population density, soil type, and the distance to towns and roads. Among these, the interaction between population density and soil type has the most significant effect on the changes in the pattern of the “production–living–ecological space”.

Abstract Background Most susceptible loci of hepatocellular carcinoma (HCC) identified by genome-wide association studies (GWAS) are located in non-coding regions, and the mechanism of action remains unclear. The objective of this study was to explore the association of single nucleotide polymorphisms (SNPs) on long non-coding RNAs (lncRNAs) that affect competing endogenous RNAs (ceRNA) regulation mechanism with the risk and prognosis of HCC. Methods Based on a set of bioinformatics strategies, eight lncRNA genes that affect HCC through the mechanism of lncRNA-mediated ceRNA were systematically screened, and 15 SNPs that affect microRNA (miRNA) binding in these lncRNA genes were annotated. Genotyping was performed in 800 HCC cases and 801 healthy controls to examine associations of these SNPs with HCC in a northeastern Chinese Han population. Results The GG, GC and GG + GC genotypes of HOTAIR rs7958904 were associated with a 0.65, 0.59 and 0.63-fold decreased HCC risk, respectively. In addition, HCC patients with PVT1 rs3931282 AA + GA genotypes were less prone to develop late-stage cancers in a stratified analysis of clinical characteristics. When stratified by clinical biochemical indexes, rs1134492 and rs10589312 in PVT1 and rs84557 in EGFR-AS1 showed significant associations with aspartate aminotransferase (AST), alanine aminotransferase (ALT) or AST/ALT ratio in HCC patients. Furthermore, we constructed potential ceRNA regulatory axes that might be affected by five positive SNPs to explain the causes of these genetic associations. Conclusions HOTAIR rs7958904, PVT1 rs3931282, rs1134492 and rs10589312, and EGFR-AS1 rs84557 might be predictors for HCC risk or prognosis. Our results provide new insights into how SNPs on lncRNA-mediated ceRNAs confer interindividual differences to occurrence and progression of HCC.

In performance-based architectural design optimization, the design of building massings and façades is commonly separated, which weakens the effectiveness in performance improvement. In response, this study proposes a hybrid massing-façade integrated design generation and optimization workflow to integrate the two elements in an evolutionary design process. Compared with the existing approaches, the proposed workflow emphasizes the diversity of building design generation, with which various combinations of building massing forms and façade patterns can be systematically explored. Two case studies and a corresponding comparison study are presented to demonstrate the efficacy of the proposed workflow. Results show that the optimization can produce designs coupling the potential of building massings and façades in performance improvement. In addition, the optimization can provide information that supports early-stage architectural design exploration. Such information also enables the architect to understand the performance implications associated with the synergy of building massing and façade design.

Abstract Precision medicine in hepatocellular carcinoma (HCC) relies on validated biomarkers that help subgroup patients for targeted treatment. Here, we identified a novel candidate oncogene, ribosomal protein L22-like1 (RPL22L1), which was markedly elevated in HCC, contributed to HCC malignancy and adverse patient survival. Functional studies indicated RPL22L1 overexpression accelerated cell proliferation, migration, invasion and sorafenib resistance. Mechanism studies revealed that RPL22L1 activated ERK to induce atypical epithelial-to-mesenchymal transition (EMT) progress. Importantly, the ERK inhibitor (ERKi) could potentiate sorafenib efficiency in RPL22L1-high HCC cells. In summary, these data uncover RPL22L1 is a potential marker to guide precision therapy for utilizing ERKi to enhance the sorafenib efficacy in RPL22L1-high HCC patients.

The traditional risk management and control mode (RMCM) in regional sites has the defects of low efficiency, high cost, and lack of systematism. Trying to resolve these defects and explore the application possibility of machine learning, a characteristic dataset for RMCM in regional sites was established. Three decision tree (DT) algorithms (CHAID, EXHAUSTIVE CHAID, and CART) and two artificial neural network (ANN) algorithms [back propagation (BP) and radial basis function (RBF)] were implemented to predict RMCM in regional sites. The results showed that in the aspects of accuracy (ACC), precision (PRE), recall ratio (REC), and F1 value, CART–DT was superior to CHAID–DT and EXHAUSTIVE CHAID–DT (E-CHAID–DT); and BP–ANN was superior to RBF–ANN. However, CART–DT was inferior to BP–ANN in ACC, PRE, REC, and F1 value. BP–ANN model is good at non-linear mapping, and it has a flexible network structure and a low risk of over-fitting. The case study of a typical county demonstration area confirmed the extensibility of the method, and the method has great potential in RMCM prediction in regional sites in the future.

A large number of aerospace practices have confirmed that the aerospace microgravity environment can lead to cognitive function decline. Mitochondria are the most important energy metabolism organelles, and some studies demonstrate that the areospace microgravity environment can cause mitochondrial dysfunction. However, the relationships between cognitive function decline and mitochondrial dysfunction in the microgravity environment have not been elucidated. In this study, we simulated the microgravity environment in the Sprague-Dawley (SD) rats by -30° tail suspension for 28 days. We then investigated the changes of mitochondrial morphology and proteomics in the hippocampus. The electron microscopy results showed that the 28-day tail suspension increased the mitochondria number and size of rat hippocampal neuronal soma. Using TMT-based proteomics analysis, we identified 163 differentially expressed proteins (DEPs) between tail suspension and control samples, and among them, 128 proteins were upregulated and 35 proteins were downregulated. Functional and network analyses of the DEPs indicated that several of mitochondrial metabolic processes including the tricarboxylic acid (TCA) cycle were altered by simulating microgravity (SM). We verified 3 upregulated proteins, aconitate hydratase (ACO2), dihydrolipoamide S-succinyltransferase (DLST), and citrate synthase (CS), in the TCA cycle process by western blotting and confirmed their differential expressions between tail suspension and control samples. Taken together, our results demonstrate that 28-day tail suspension can cause changes in the morphology and metabolic function of hippocampus mitochondria, which might represent a mechanism of cognitive disorder caused by aerospace microgravity.

Abstract Background Synpolydactyly type 1 (SPD1), also known as syndactyly type II, is an autosomal dominant limb deformity generally results in webbing of 3rd and 4th fingers, duplication of 4th or 5th toes. It is most commonly caused by mutation in HOXD13 gene. In this study, a five-generation Chinese family affected with SPD1 disease were collected. We tried to identify the pathogenic variations associated with SPD1 involved in the family. Methods We used the whole genome sequencing (WGS) to identify the pathogenic variant in this family which was later confirmed by PCR-Sanger sequencing. The genetic variation were evaluated with the frequencies in the 1000 Genome Project and Exome Aggregation Consortium (ExAC) dataset. The significance of variants were assessed using different mutation predictor softwares like Mutation Taster, PROVEAN and SIFT. The classification of variants was assessed according to American College of Medical Genetics and Genomics (ACMG) guidelines. Results Our results showed the mutation of 24-base pair duplication (c.183_206dupAGCGGCGGCTGCGGCGGCGGCGGC) in exon one of HOXD13 in heterozygous form which was predicted to result in eight extra alanine (A) residues in N-terminal domain of HOXD13 protein. The mutation was detected in all affected members of the family. Conclusion Based on our mutation analysis of variant c.183_206dupAGCGGCGGCTGCGGCGGCGGCGGC in HOXD13 and its cosegregation in all affected family members, we found this variant as likely pathogenic to this SPD1 family. Our study highlights variable expressivity of HOXD13 mutation. Our results also widen the spectrum of HOXD13 mutation responsible for SPD1.

The good indoor light environment and comfort of the teaching space are very important for students’ physical and mental health. Meanwhile, China advocates energy conservation and emission reduction policies. However, in order to obtain lower building energy consumption, higher thermal comfort, and daylighting, architects use performance simulation software to repeatedly simulate and refine, which is time-consuming and difficult to obtain the best results from three performances. Given this problem, we constructed the design framework in the early stage of the architectural design of the teaching building. In the first stage of the framework, architects optimized the performance objectives of lighting, thermal comfort, and energy consumption, and performed a cluster analysis on the optimized non-dominated solution to provide a reference for the architect. In the second stage of the framework, architects used the data generated in the optimization process to train the BP neural network and use the trained BP neural network to predict the performance of the building. In this paper, we selected Nanjing Donglu Middle School as a case study. The optimization of the building performance was assessed by a genetic algorithm, generating 3000 sets of sample data during the optimization iteration. Then, we analyzed the non-dominated solution of the sample data through the method of cluster analysis and trained the BP neural network with the sample data as a data set. The prediction model with R-values of 0.998 in the training set and test set was obtained by repeatedly debugging the number of neurons in the BP neural network. Finally, five groups of design parameters were randomly selected and brought into the trained BP neural network, and the predictive value was close to the simulated value. The construction of the framework provides design ideas for architects in the early teaching of building design and helps designers to make better decisions.

Abstract Background Polycystic kidney disease (PKD) is an inherited disease that is life‐threatening. Multiple cysts are present in the bilateral kidneys of PKD patients. The progressively enlarged cysts cause structural damage and loss of kidney function. Methods This study examined and analyzed 12 families with polycystic kidney disease. Whole exome sequencing (WES) or whole genome sequencing (WGS) of the probands was performed to detect the pathogenic genes. The candidate gene segments for lineal consanguinity in the family were amplified by the nest PCR followed by Sanger sequencing. The variants were assessed by pathogenic and conservational property prediction analysis and interpreted according to the American College of Medical Genetics and Genomics. Results Nine of the 12 pedigrees were identified the disease causing variants. Among them, four novel variants in PKD1, c.6930delG:p.C2311Vfs*3, c.1216T>C:p.C406R, c.8548T>C:p.S2850P, and c.3865G>A:p.V1289M (NM_001009944.2) were detected. After assessment, the four novel variants were considered to be pathogenic variants and cause autosomal dominant polycystic kidney disease in family. The detected variants were interpreted. Conclusion The four novel variants in PKD1, c.6930delG:p.C2311Vfs*3, c.1216T>C:p.C406R, c.8548T>C:p.S2850P, and c.3865G>A:p.V1289M (NM_001009944.2) are pathogenic variants and cause autosomal dominant polycystic kidney disease in family.

The circadian clock controls the physiological functions of many tissues including the liver via an autoregulatory transcriptional−translational feedback loop, of which CLOCK is a core positive component. In addition, many studies have indicated that microRNAs (miRNAs) regulate liver function. However, how CLOCK-regulated miRNAs are linked to liver function remains largely unknown. In this study, miRNAs expression profiles were performed in the liver of ClockΔ19 mutant mice. Compared to wild type mice, totals of 61 and 57 putative CLOCK-regulated miRNAs were differentially expressed (fold change absolute value ≥2) at zeitgeber time 2 and zeitgeber time 14, respectively. According to the pathway analyses, the target genes of differentially expressed miRNAs were mainly involved in pathways in cancer, the PI3K-Akt signaling pathway and the MAPK signaling pathway. Protein−protein interaction analyses revealed that the hub genes were primarily associated with pathway in cancer and circadian rhythms. Expression validation showed that while the expression levels of miR-195 and miR-340 were up-regulated, the rhythms of these two miRNAs were always maintained. The expression level of nr1d2 mRNA was down-regulated. We identified a number of prospective CLOCK-regulated miRNAs that play roles in the various physiological processes of the liver, providing a reference to better understanding the potential regulatory mechanisms in the liver.

BackgroundIntegrated 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is widely performed for staging solitary pulmonary nodules (SPNs). However, the diagnostic efficacy of SPNs based on PET/CT is not optimal. Here, we propose a method of detection based on PET/CT that can differentiate malignant and benign SPNs with few false-positives.MethodOur proposed method combines the features of positron-emission tomography (PET) and computed tomography (CT). A dynamic threshold segmentation method was used to identify lung parenchyma in CT images and suspicious areas in PET images. Then, an improved watershed method was used to mark suspicious areas on the CT image. Next, the support vector machine (SVM) method was used to classify SPNs based on textural features of CT images and metabolic features of PET images to validate the proposed method.ResultsOur proposed method was more efficient than traditional methods and methods based on the CT or PET features alone (sensitivity 95.6%; average of 2.9 false positives per scan).

SOD2 (superoxide dismutase 2) is one of the endogenous antioxidant enzymes that protect against reactive oxygen species. While explorations of SOD2 expression regulation are mainly focused on transcriptional and post-translational activation, there are few reports about the post-transcriptional regulation of SOD2. MicroRNAs (miRNAs) are 21nt-25nt (nucleotide) small noncoding RNAs that have emerged as indispensable regulators of gene expression. Here we show that miR-146a, a widely expressed miRNA, is up-regulated by H2O2-induced stress. By sequence analysis we found a binding site for miR-146a in the sod2 mRNA 3'UTR, and a luciferase reporter assay confirmed that miR-146a can interact with this sod2 regulatory region. Our results further show that miR-146a could down-regulate the SOD2 protein expression, and antisense-miR-146a could reverse the decrease of both the SOD2 level and cell viability in H2O2 treated PC12 cells. In conclusion, here we have identified a novel function of miR-146a in the post-transcriptional regulation of SOD2 expression.

Abstract Background Diabetic polyneuropathy (DPN) is a common diabetes complication with limited treatment options. We aimed to identify circulating plasma proteins as potential therapeutic targets for DPN using Mendelian Randomization (MR). Methods The protein quantitative trait loci (pQTLs) utilized in this study were derived from seven previously published genome-wide association studies (GWASs) on plasma proteomics. The DPN data were obtained from the IEU OpenGWAS project. This study employed two-sample MR using MR-Egger and inverse-variance weighted methods to evaluate the causal relationship between plasma proteins and DPN risk, with Cochran’s Q test, and I2 statistics, among other methods, used to validate the robustness of the results. Results Using cis-pQTLs as genetic instruments, we identified 62 proteins associated with DPN, with 33 increasing the risk and 29 decreasing the risk of DPN. Using cis-pQTLs + trans-pQTLs, we identified 116 proteins associated with DPN, with 44 increasing the risk and 72 decreasing the risk of DPN. Steiger directionality tests indicated that the causal relationships between circulating plasma proteins and DPN were consistent with expected directions. Conclusion This study identified 96 circulating plasma proteins with genetically determined levels that affect the risk of DPN, providing new potential targets for DPN drug development, particularly ITM2B, CREG1, CD14, and PLXNA4.

Objective Few studies have explored the relationship between the pathological characteristics of hallux valgus and surgical outcomes. The aim of our study was to report the influence of pathological characteristics such as the tibial sesamoid position (TSP) and first metatarsal pronation on postoperative functional scores and patient satisfaction with hallux valgus surgery. Methods From June 2017 to December 2022, a retrospective analysis was conducted on patients who underwent hallux valgus surgery at our hospital. Anteroposterior (AP) x‐ray parameters (hallux valgus angle [HVA], intermetatarsal angle [IMA], distal metatarsal articular angle [DMAA], TSP, first metatarsal pronation, and first metatarsophalangeal joint dislocation) (preoperative weight‐bearing, immediate postoperative non‐weight‐bearing, and early postoperative weight‐bearing), visual analog scale (VAS) scores, American Orthopaedic Foot and Ankle Society (AOFAS) forefoot scores, SAFE‐Q self‐administered foot evaluation questionnaire (excluding the Sports Activity subscale), complications, and patient satisfaction were used to describe the outcomes. Correlation analysis and multiple linear regression models were used to identify factors influencing postoperative functional scores and patient satisfaction after hallux valgus surgery. Results Eighty‐one patients (92 feet) whose early radiographic parameters and latest follow‐up scores improved significantly (p 0.05). The R 2 values of the multiple linear regression models predicting postoperative functional scores and patient satisfaction ranged from 0.042 to 0.351. Conclusion TSP and first metatarsal pronation were unrelated to postoperative functional scores or patient satisfaction. This finding enhances surgeons' understanding of the functional prognosis of hallux valgus surgery, particularly aiding in explaining the condition and assessing surgical outcomes.

To tackle the prevalent challenges encountered with polyamine-based non-aqueous absorbents (NAAs), particularly the formation of viscous products and inferior regeneration performance, this study proposed an innovative synergistic regulation strategy that integrated 2-amino-2-methyl-1-propanol (AMP) and n-propanol (NPA). Accordingly, a novel tertiary tetraethylenepentamine (TEPA)-AMP-NPA (T-A-N) NAA was devised. The optimized T-A-N maintained complete homogeneity throughout the entire CO2 absorption process and achieved an impressive CO2 loading of 1.15 mol·mol−1 while maintaining a low viscosity of merely 22.47 mPa·s. Remarkably, its absorption capacity showed little decrement after four consecutive absorption-desorption cycles, underscoring its exceptional recyclability. Within the T-A-N system, AMP underwent a reaction with CO2, yielding AMP-carbamate and protonated AMP, while TEPA engaged in CO2 absorption to form zwitterionic carbamates. During the desorption process, NPA served as a regeneration activator, facilitating the conversion of stable TEPA-carbamates into less stable alkyl carbonate intermediates, thereby enhancing the T-A-N's regeneration performance. Moreover, the T-A-N system addressed the issue of TEPA-carbamate self-aggregation into insoluble gelatinous substances by leveraging the synergistic enhancement effects between AMP derivatives and NPA. Specifically, these components effectively bound TEPA-carbamate species via robust electrostatic affinity and intermolecular hydrogen-bond interactions, inhibiting their self-aggregation and preventing the formation of insoluble products. Furthermore, T-A-N exhibited a significant reduction in both sensible and latent heat requirements, by 67 % and 82 % respectively, compared to 30 wt% MEA, highlighting its advantageous energy-saving potential for CO2 capture. Overall, harnessing the synergistic enhancement effects of AMP and NPA was conducive to the development of polyamine-based NAAs that offered superior CO2 capture reversibility, low energy consumption, and resistance to insoluble product formation.

Abstract An adaptively hybrid method was proposed to improve the performance of fractal coding methods. First, it is found that the range blocks with large variances (RBLVs) play a crucial role in degrading decoded images, and the effect of the remaining range blocks with small variances (RBSVs) can be ignored. Then, an adaptive method was proposed to divide the range blocks into the above two categories: RBLVs and RBSVs. Second, RBLVs were designed to be encoded in an extended domain block pool (EDBP). Then, better block‐matching effect can be obtained, which will result in better decoded image quality. Further, the no‐search fractal encoding method is adopted for RBSVs to achieve faster encoding speed and fewer bits per pixel (bpp). Finally, four fractal coding methods were adopted to assess the performance of the proposed method. Experimental results show that compared with the previous methods, the PSNR quality of decoded images in the proposed method can be improved by about 0.15–0.4 dB, about 20%–35% of the total computations in encoding process can be saved, and about 0.2 bpp can be saved. Moreover, under the same decoding time, the proposed method can achieve comparable or smaller deviations regarding the decoded image.

To suppress the influence of aerosols scattering on the double-edge detection technique and achieve high-accuracy measurement of the wind field throughout the troposphere to the lower stratosphere, an ultraviolet 355 nm Rayleigh–Brillouin Doppler lidar technology based on a dual-pass dual Fabry–Perot interferometer (FPI) is proposed. The wind speed detection principle of this technology is analyzed, and the formulas for radial wind speed measurement error caused by random noise and wind speed measurement bias caused by Mie scattering signal contamination are derived. Based on the detection principle, the structure of the lidar system is designed. Combining the wind speed measurement error and measurement bias on both sides, the parameters of the dual-pass dual-FPI are optimized. The free spectral range (FSR) of the dual-pass dual-FPI is selected as 12 GHz, the bandwidth as 1.8 GHz, and the peak-to-peak spacing as 6 GHz. Further, the detection performance of this new type of Rayleigh–Brillouin Doppler lidar with the designed system parameters is simulated and analyzed. The simulation results show that at an altitude of 0–20 km, within the radial wind speed dynamic range of ±50 m/s, the radial wind speed measurement bias caused by aerosol scattering signal is less than 0.17 m/s in the cloudless region; within the radial wind speed dynamic range of ±30 m/s, the bias is less than 0.44 m/s and 0.91 m/s in the simulated cumulus cloud at 4 km where aerosol backscatter ratio Rβ = 3.8 and cirrus cloud at 9 km where Rβ = 2.9, respectively; using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz, a 450 mm aperture telescope, setting the detection zenith angle of 30°, vertical resolution of 26 m@0–10 km, 78 m@10–20 km, and 260 m@20–30 km, and a time resolution of 1 min, with the daytime sky background brightness taking 0.3 WSr−1m−2nm−1@355 nm, the radial wind speed measurement errors of the system during the day and night are below 2.9 m/s and 1.6 m/s, respectively, up to 30 km altitude, below 0.28 m/s at 10 km altitude, and below 0.91 m/s at 20 km altitude all day.