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Abstract A high baseline NLR is associated with a poor prognosis of immunotherapy in patients with advanced HCC. As anti-tumour immune activation takes time, early dynamic changes in NLR may serve as a biomarker for predicting immunotherapy response. We conducted a retrospective study in which we enrolled 209 patients with aHCC who received ICIs (training cohort: N = 121, validation cohort: N = 88). In the training cohort, we categorized the patients based on the early changes in their NLR. Specifically, we defined patients as NLR Stable-Responder, NLR Responder and NLR Non-Responder. We compared the outcomes of these three patient groups using survival analysis. Additionally, we shortened the observation period to 6 weeks and validated the findings in the validation cohort. In the training cohort, early dynamic changes in NLR (HR 0.14, 95%CI 0.03–0.65, p = 0.012, HR 0.19, 95%CI 0.07–0.54, p = 0.002; HR 0.21, 95%CI 0.10–0.42, p

Abstract Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide. Understanding the dysregulated epigenetics governing LUAD progression is pivotal for identifying therapeutic targets. CBX4, a chromobox protein, is reported to be upregulated in LUAD. This study highlights the dual impact of CBX4 on LUAD proliferation and metastasis through a series of rigorous in vitro and in vivo experiments. Further investigation into the underlying mechanism through high-throughput ChIP-seq and RNA-seq reveals that CBX4 functions in promoting LUAD proliferation via upregulating PHGDH expression and subsequent serine biosynthesis, while concurrently suppressing LUAD metastasis by inhibiting ZEB2 transcription. CBX4 facilitates PHGDH transcription through the interaction with GCN5, inducing heightened histone acetylation on the PHGDH promoter. Simultaneously, the inhibition of ZEB2 transcription involves CBX4-mediated recruitment of canonical PRC1 (cPRC1), establishing H2K119ub on the ZEB2 promoter. These findings underscore CBX4’s pivotal role as a regulator of LUAD progression, emphasizing its diverse transcriptional regulatory functions contingent upon interactions with specific epigenetic partners. Understanding the nuanced interplay between CBX4 and epigenetic factors sheds light on potential therapeutic avenues in LUAD.

Abstract The high salt content of food waste (FW) severely limits microbial physiological activity and reduces its biodegradability. In this study, a salt‐tolerant thermophilic bacterial agent that consists of four different substrate degradation functional strains was evaluated for efficient high salt and oily FW in solid‐state aerobic biodegradation disposers. The phy‐chemical properties, enzyme activities, microbial community structure, and function during the biodegradation process were evaluated under high salt (5%) stress. The results showed that the agent promoted the degradation rate, increased the matrix temperature, decreased the moisture content (MC), and enhanced enzyme activities without putrid smell. High‐throughput sequencing indicated community structure succession between different groups and the positive contribution of the inoculated functional strains. During the FW biodegradation process, the Bacillus sp. inoculated was the dominant genus in the agent group. Furthermore, CCA further confirmed the positive effects of the four inoculated strains on high salt and oily FW aerobic biodegradation. Functional prediction and metabolite results both confirmed that the agent was more efficient in carbon, amino acid, and lipid metabolism, which demonstrated that the synthetic microbial consortium holds a potential advantage for efficiency and subsequent resource utilization for organic fertilizer.

Based on its unique sensitivity to Earth's temporal gravity, and since 2002, the gravity recovery and climate experiment (GRACE) twin satellites, and its successor, GRACE follow-on (GRACE-FO) missions have accumulated a two-decade-long and continuing Earth's mass change climate data record. Additionally, the Chinese gravimetry mission was launched as the last polar-pair satellite formation in 2021. With the opportunity of two existing polar-pair gravity satellite formations (EPGF) in operations, we explore the ideal configuration to launch a third-pair satellite formation to construct the triple-pair gravity satellite constellation (TGSC). Here, we examine the selection of initial orbit parameters of the third satellite formation based on subcycles and orbit parameters of EPGF to augment TGSC. The simulation study explores the effectiveness of the monthly temporal gravity field from the TGSC in potential contributions to geosciences. Our study reveals that TGSC improves continental hydrological signal recovery by approximately 24% and 38% in large and small basins (above/below 106 km2), as compared with GRACE-FO, which would be the polar-pair gravity satellite in operations. TGSCs effectiveness varies across drainage systems of the Greenland ice sheet (GrIS) due to different ground track coverage. Compared with GRACE-FO, TGSC enhances GrIS mass balance recovery by 37%–56%. Simulations for six mega earthquakes (above Mw 7.7) reveal that TGSC outperforms GRACE-FO by approximately 46%–58% in extracting coseismic signals. Our study reveals the importance of incorporating existing on-orbit gravity missions into the design of future gravity satellite constellations. This strategy aims to not only accomplish the predefined objectives of gravity satellite missions but also potentially provide additional benefits to the field of geosciences.

This paper presents a hermitic fiber sensor packaging technique that enables fiber sensors to be embedded in energy systems for performing multi-parameter measurements in high-temperature and strong radiation environments. A high-temperature stable Intrinsic Fabry–Perot interferometer (IFPI) array, inscribed by a femtosecond laser direct writing scheme, is used to measure both temperature and pressure induced strain changes. To address the large disparity in thermo-expansion coefficients (TECs) between silica fibers and metal parts, glass sealants with TEC between silica optical fibers and metals were used to hermetically seal optical fiber sensors inside stainless steel metal tubes. The hermetically sealed package is validated for helium leakages between 1 MPa and 10 MPa using a helium leak detector. An IFPI sensor embedded in glass sealant was used to measure pressure. The paper demonstrates an effective technique to deploy fiber sensors to perform multi-parameter measurements in a wide range of energy systems that utilize high temperatures and strong radiation environments to achieve efficient energy production.

BackgroundTargeted and Immunotherapy has emerged as a new first-line treatment for advanced hepatocellular carcinoma (aHCC). To identify the appropriate targeted and immunotherapy, we implemented next generation sequencing (NGS) to provide predictive and prognostic values for aHCC patients.MethodsPretreatment samples from 127 HCC patients were examined for genomic changes using 680-gene NGS, and PD-L1 expression was detected by immunohistochemistry. Demographic and treatment data were included for analyses of links among treatment outcomes, drug responses, and genetic profiles. A prognostic index model for predicting benefit from treatment was constructed, taking into account of biomarkers, including TP53, TERT, PD-L1, and tumor mutation burden (TMB) as possible independent prognostic factors.ResultsThe multivariate Cox regression analyses showed that PD-L1≥1% (HR 25.07, 95%CI 1.56 - 403.29, p=0.023), TMB≥5Mb (HR 86.67, 95% CI 4.00 - 1876.48, p=0.004), TERT MU (HR 84.09, 95% CI 5.23 - 1352.70, p=0.002) and TP53 WT (HR 0.01, 95%CI 0.00 - 0.47, p=0.022) were independent risk factors for overall survival (OS), even after adjusting for various confounders. A prognostic nomogram for OS was developed, with an area under the ROC curve of 0.91, 0.85, and 0.98 at 1-, 2-, and 3- year, respectively, and a prognostic index cutoff of 1.2. According to the cutoff value, the patients were divided into the high-risk group (n=29) and low-risk group (n=98). The benefit of targeted and immunotherapy in the low-risk group was not distinguishable according to types of agents. However, treatment of Atezolizumab and Bevacizumab appeared to provide longer OS in the high-risk group (12 months vs 9.2, 9, or 5 months for other treatments, p

A 64-year-old woman was admitted to the hospital for sudden weakness in one of her left limbs. The patient was diagnosed with acute ischemic stroke (IS) of undetermined cause and received intravenous thrombolysis. Following thrombolysis, the patient’s left limb weakness improved, but she subsequently developed recurrent high fever and delirium. Further diagnostic tests revealed that she had been infected with Brucella melitensis. The patient showed significant improvement during anti-infection treatment for Brucellosis and secondary prevention treatment for IS. However, her condition unexpectedly worsened on the 44th day after admission due to a hemorrhagic stroke (HS), which required an urgent craniotomy. Immunohistochemical analysis of the hematoma sample collected during the operation showed the presence of CD4+ and CD8+ T lymphocytes surrounding the blood vessels. This case highlights the unique challenge of managing IS in brucellosis and sheds light on the potential role of T lymphocytes in the immune response related to stroke.

A deep-seated landslide could release numerous microseismic signals from creep-slip movement, which includes a rock-soil slip from the slope surface and a rock-soil shear rupture in the subsurface. Machine learning can effectively enhance the classification of microseismic signals in landslide seismic monitoring and interpret the mechanical processes of landslide motion. In this paper, eight sets of triaxial seismic sensors were deployed inside the deep-seated landslide, Jiuxianping, China, and a large number of microseismic signals related to the slope movement were obtained through 1-year-long continuous monitoring. All the data were passed through the seismic event identification mode, the ratio of the long-time average and short-time average. We selected 11 days of data, manually classified 4131 data into eight categories, and created a microseismic event database. Classical machine learning algorithms and ensemble learning algorithms were tested in this paper. In order to evaluate the seismic event classification performance of each algorithmic model, we evaluated the proposed algorithms through the dimensions of the accuracy, precision, and recall of each model. The validation results demonstrated that the best performing decision tree algorithm among the classical machine learning algorithms had an accuracy of 88.75%, while the ensemble algorithms, including random forest, Gradient Boosting Trees, Extreme Gradient Boosting, and Light Gradient Boosting Machine, had an accuracy range from 93.5% to 94.2% and also achieved better results in the combined evaluation of the precision, recall, and F1 score. The specific classification tests for each microseismic event category showed the same results. The results suggested that the ensemble learning algorithms show better results compared to the classical machine learning algorithms.

In this paper, a novel 4H-SiC deep-trench super-junction MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) with a split-gate is proposed and theoretically verified by Sentaurus TCAD simulations. A deep trench filled with P-poly-Si combined with the P-SiC region leads to a charge balance effect. Instead of a full-SiC P region in conventional super-junction MOSFET, this new structure reduces the P region in a super-junction MOSFET, thus helping to lower the specific on-resistance. As a result, the figure of merit (FoM, BV2/Ron,sp) of the proposed new structure is 642% and 39.65% higher than the C-MOS and the SJ-MOS, respectively.

Background: Chukrasia tabularisis, a well-known tropical tree native to southeastern China, has anti-inflammatory and antioxidant activities, and contains large amounts of limonoids and triterpenoids. Objective: The aim of this study was to investigate the potential anti-inflammatory activity of limonoids from C. tabularis on lipopolysaccharide (LPS)-mediated RAW264.7 cells. Methods and results: Using a bioassay-guided approach, the chemical fraction with high anti-inflammatory activity was found and its chemical constituents were investigated. Phytochemical studies on active extracts resulted in the separation of three novel phragmalin limonoids (1–3), together with two known limonoids (4–5) and 11 tirucallane triterpenes (6–16). The activity of these isolated compounds in the production of nitric oxide (NO) on LPS-reated macrophages was evaluated. Limonoid 2 indicated significant anti-inflammatory activities with IC50 value of 4.58 μM. Limonoid 2 notably inhibited the production of NO, interleukin- 6 and tumor necrosis factor-α on macrophage. Signal transduction and activation of STAT and NF-κB activators were effectively blocked by limonoid 2. Conclusions: These results indicate that limonoid 2 has an anti-inflammatory effect by the inhibiting JAK2/STAT3, iNOS/eNOS, and NF-κB signaling pathways and regulating inflammatory mediators.

BackgroundImmunotherapy based on immune checkpoint inhibitors (ICIs) has become the first-line treatment for unresectable hepatocellular carcinoma (uHCC). However, only a small portion of patients are responsive to ICIs. It is important to identify the patients who are likely to benefit from ICIs in clinical practice. We aimed to examine the significance of serum IL-6 and CRP levels in predicting the effectiveness of ICIs for uHCC.MethodsWe retrospectively recruited 222 uHCC patients who received ICIs treatment (training cohort: 124 patients, validation cohort: 98 patients). In the training cohort, patients are categorized into the response group (R) and no-response group (NR). The levels of serum IL-6 and CRP were compared between the two groups. Internal validation was performed in the validation cohort. Survival analysis was carried out using the Kaplan-Meier method and Cox proportional hazard regression model. The nomograms were developed and assessed using the consistency index (C-index) and calibration curve.ResultsSerum levels of IL-6 and CRP were significantly lower in the R group than in the NR group (9.94 vs. 36.85 pg/ml, p< 0.001; 9.90 vs. 24.50 mg/L, p< 0.001, respectively). An ROC curve was employed to identify the optimal cut-off values for IL-6 and CRP in both groups, resulting in values of 19.82 pg/ml and 15.50 mg/L, respectively. Multivariate Cox regression analysis revealed that MVI (HR 1.751, 95%CI 1.059-2.894, p=0.029; HR 1.530, 95%CI 0.955-2.451, p=0.077), elevated IL-6 (HR 1.624, 95%CI 1.016-2.596, p=0.043; HR 2.146, 95%CI 1.361-3.383, p =0.001) and high CRP (HR 1.709, 95%CI 1.041-2.807, p=0.034; HR 1.846, 95%CI 1.128-3.022, p = 0.015) were independent risk factors for PFS and OS, even after various confounders adjustments. Nomograms are well-structured and validated prognostic maps constructed from three variables, as MVI, IL6 and CRP.ConclusionLow levels of IL-6 and CRP have a positive correlation with efficacy for uHCC patients receiving ICIs.

As agents in an emerging technology, Hermetia illucens (Linnaeus, 1758) (Diptera: Stratiomyidae) larvae, black soldier fly, have shown exciting potential for degrading antibiotics in organic solid waste, a process for which gut microorganisms play an important role. This study investigated the characteristics of larval gut bacterial communities effected by typical antibiotics. Initially, antibiotics significantly reduced the diversity of gut bacterial species. After 8 days, diversity recovered to similar to that of the control group in the chlortetracycline, tylosin, and sulfamethoxazole groups. Proteobacteria, Firmicutes, and Actinobacteriota were the dominant phyla at the initial BSFL gut. However, after 4 days treatment, the proportion of Actinobacteriota significantly decreased, but Bacteroidota notably increased. During the conversion process, 18, 18, 17, 21, and 19 core genera were present in the chlortetracycline, sulfamethoxazole, tylosin, norfloxacin, and gentamicin groups, respectively. Pseudomonas, Actinomyces, Morganella, Providencia and Klebsiella might be the important genera with extraordinary resistance and degradation to antibiotics. Statistical analyses of COGs showed that antibiotics changed the microbial community functions of BSFL gut. Compared with the control group, (i) the chlortetracycline, sulfamethoxazole, and tylosin groups showed significant increase in the classification functions of transcription, RNA processing and modification，and so on, (ii) the norfloxacin and gentamicin groups showed significant increase in defense mechanisms and other functions. Note that we categorized the response mechanisms of these classification functions to antibiotics into resistance and degradation. This provides a new perspective to deeply understand the joint biodegradation behavior of antibiotics in environments, and serves as an important reference for further development and utilization of microorganisms-assisted larvae for efficient degradation of antibiotics.

This paper presents the design and construction of the facade renovation project ("Bamboo Cubic" project) of Huangqiao Square in Shaowu City, Fujian Province, China. In this project, the structural form and cross-sectional dimensions were determined using a combination of manual and finite element analysis to meet relevant regulations. Once the structural form was confirmed, primary structural components such as the foundation, the column base, and the connection between frame elements were designed to comply with design requirements. Innovative connections were used to install a unique curved design, which required curved LBL members to be prefabricated with precision. The total height of the LBL bamboo frame part is 16.86 m. This project clearly showed that engineered bamboo can be used both as a structural primary member as well as for aesthetic purpose. Use of steel and LBL frames in the "Bamboo Cubic" facade project highlighted the prospect of future hybrid construction.

Sulfur-oxidizing bacteria play a crucial role in various processes, including mine bioleaching, biodesulfurization, and treatment of sulfur-containing wastewater. Nevertheless, the pathway involved in sulfur oxidation is highly intricate, making it complete comprehension a formidable and protracted undertaking. The mechanisms of sulfur oxidation within the Acidithiobacillus genus, along with the process of energy production, remain areas that necessitate further research and elucidation. In this study, a novel strain of sulfur-oxidizing bacterium, Acidithiobacillus Ameehan, was isolated. Several physiological characteristics of the strain Ameehan were verified and its complete genome sequence was presented in the study. Besides, the first genome-scale metabolic network model (AMEE_WP1377) was reconstructed for Acidithiobacillus Ameehan to gain a comprehensive understanding of the metabolic capacity of the strain.The characteristics of Acidithiobacillus Ameehan included morphological size and an optimal growth temperature range of 37-45°C, as well as an optimal growth pH range of pH 2.0-8.0. The microbe was found to be capable of growth when sulfur and K2O6S4 were supplied as the energy source and electron donor for CO2 fixation. Conversely, it could not utilize Na2S2O3, FeS2, and FeSO4·7H2O as the energy source or electron donor for CO2 fixation, nor could it grow using glucose or yeast extract as a carbon source. Genome annotation revealed that the strain Ameehan possessed a series of sulfur oxidizing genes that enabled it to oxidize elemental sulfur or various reduced inorganic sulfur compounds (RISCs). In addition, the bacterium also possessed carbon fixing genes involved in the incomplete Calvin-Benson-Bassham (CBB) cycle. However, the bacterium lacked the ability to oxidize iron and fix nitrogen. By implementing a constraint-based flux analysis to predict cellular growth in the presence of 71 carbon sources, 88.7% agreement with experimental Biolog data was observed. Five sulfur oxidation pathways were discovered through model simulations. The optimal sulfur oxidation pathway had the highest ATP production rate of 14.81 mmol/gDW/h, NADH/NADPH production rate of 5.76 mmol/gDW/h, consumed 1.575 mmol/gDW/h of CO2, and 1.5 mmol/gDW/h of sulfur. Our findings provide a comprehensive outlook on the most effective cellular metabolic pathways implicated in sulfur oxidation within Acidithiobacillus Ameehan. It suggests that the OMP (outer-membrane proteins) and SQR enzymes (sulfide: quinone oxidoreductase) have a significant impact on the energy production efficiency of sulfur oxidation, which could have potential biotechnological applications.

Summary: This paper proposed a method based on heart rate variability (HRV) for evaluating the accuracy of wearable devices in measuring heart rate. HRV refers to the variation in time intervals between successive heartbeats, widely used in many fields such as clinical and sports fields. Wearable devices such as Electrocardiogram (ECG) electrode patches have gained popularity due to their portability and ease of use. However, they can be prone to measurement interference caused by environmental noise, human respiration, etc. The proposed method consists of four main components: selection of “gold standard measurement devices”, identification of HRV measurement metrics, construction of an HRV evaluation framework, and quantification of measurement errors. The method is validated through simulated experiments using ECG patches. The evaluation framework and quantification model established in this method have significant implications in establishment of industry standards and diagnosis of diseases in clinical practice.

Based on the hail data of the China Meteorological Administration, the spatial and temporal distributions of hail disaster eents in China during 2010-2020 are studied by using the statistical method and GIS technology. The result is shown below. (1) The number of stations and the days of hails in China increase, while the number of severe hails decreases during 2010-2020. (2) The seasonal change is significant for the number of stations and the days of hails with the maximum in summer and the minimum in winter. In terms of monthly variation, hail occurs most often in June and least often in November. In southwest and central China, the monthly variation of the number of stations and the days of hails is bimodal. The monthly distribution of severe hail is similar to that of hail, but it occurs least often in December. The severe hail occurs most frequently in southwest China. (3) For diurnal variation, hail or severe hail mainly occurrs from afternoon to evening. The peak appears 1-hour later in northwest China than in other areas. (4) In terms of spatial distribution, the number of stations and the days of hail or severe disaster in Northwest, Southwest, and North China are significantly higher than those in the other regions, and the proportion of severe hail in Northeast and South China is higher than that in the other regions. The annual average days of hail or severe hail are distributed in multi-zone bands, and the multi-hail area extends along the mountains, with the largest value located in the Yunnan-Guizhou Plateau, followed by the mountains of Qinling, Yinshan, Daxing 'anling, and Tianshan. In addition, the low-incidence area of eastern China in spring has become a high-incidence area of hail. (5)From the elevation distribution, hail is most likely to occur at the altitude of 1.5-2 km, and severe hail is most likely to occur at the altitude of 1-1.5 km. In winter, hail is mainly below 2 km. With the rise of temperature, hail gradually increases in the high-altitude areas, and the proportion of hailstones in the high-altitude areas reaches the maximum in September.

Abstract Objective Streptococcus pneumoniae (Spn) is a common pathogen for pediatric pneumonia and leads to severe lung injury. This study is conducted to analyze the role of F-box and leucine rich repeat protein 19 (FBXL19) in Spn-induced lung injury in immature mice. Methods Immature mice were infected with Spn to record the survival rates and bacterial loads in bronchoalveolar lavage fluid. Levels of FBXL19 and FOXM1 in lung tissues were determined via real-time quantitative polymerase chain reaction or Western blotting. After the interference of FBXL19, its impacts on lung inflammatory injury were appraised by the lung wet/dry weight ratio, myeloperoxidase activity, hematoxylin and eosin staining, and enzyme-linked immunosorbent assay. The binding of FBXL19 to forkhead box M1 (FOXM1) in mouse lung epithelial cells was determined. After MG132 treatment, the protein and ubiquitination levels of FOXM1 were measured. The functional rescue experiments were performed to analyze the role of FOXM1 in FBXL19-regulated lung injury. Results FBXL19 was downregulated while FOXM1 was upregulated in lung tissues of Spn-infected immature mice. Overexpression of FBXL19 reduced the degree of lung injury and inflammation. FBXL19 can bind to FOXM1 to reduce its protein level via ubiquitination degradation. MG132 reduced the ubiquitination and increased the protein level of FOXM1. Overexpression of FOXM1 reversed the protective role of FBXL19 overexpression in lung injury of Spn immature mice. Conclusion FBXL19 was downregulated by Spn and FBXL19 overexpression alleviated lung injury by inducing ubiquitination and degradation of FOXM1 in Spn immature mice.

Some long non-coding RNAs (lncRNAs) have been documented to be involved in cancer progression and anticancer drug resistance in hepatocellular carcinoma (HCC). Thus, approaches designed to target these genes may facilitate the development of promising strategies for treating HCC. Previously, we showed that lncRNA BBOX1-AS1 was highly expressed and played an oncogenic role in HCC. However, the potential functions and mechanisms through which BBOX1-AS1 regulates HCC progression and drug resistance remain unclear. This study revealed that BBOX1-AS1 could promote tumor progression, autophagy, and drug resistance by upregulating PHF8 in HCC cells. Mechanistically, BBOX1-AS1 enhanced the stability of PHF8 mRNA by targeting the PHF8 inhibitor miR-361-3p to regulate tumor progression and autophagy in HCC. The functional rescue experiments showed that PHF8 acted as a key factor in regulating the biological effects induced by BBOX1-AS1 and miR-361-3p in HCC, indicating that BBOX1-AS1 promotes tumor progression and sorafenib resistance by regulating miR-361-3p/PHF8. Finally, mouse tumor models and patient-derived organoid models were established to further confirm these findings. Taken together, the results demonstrate that BBOX1-AS1 promotes HCC progression and sorafenib resistance via the miR-361-3p/PHF8 axis.

The marine bacterium Streptomyces sp. HNS054 shows promise as a platform for producing natural products. Isolated from a marine sponge, HNS054 possesses several desirable traits for bioengineering: rapid growth, salt tolerance, and compatibility with genetic tools. Its genome contains 21 potential biosynthetic gene clusters, offering a rich source of natural products. We successfully engineered HNS054 to increase the production of aborycin and actinorhodin by 4.5-fold and 1.2-fold, respectively, compared to S. coelicolor M1346 counterparts. With its unique features and amenability to genetic manipulation, HNS054 emerges as a promising candidate for developing novel marine-derived drugs and other valuable compounds.

The manual interpretation of ground-penetrating radar images is characterised by long interpretation cycles and high staff requirements. The automated interpretation schemes based on support vector machines, digital images, convolutional neural networks and other techniques proposed in recent years mainly detect features from B-scan slices of 3D ground-penetrating radar data, without taking full advantage of the multi-channel acquisition of data from 3D ground-penetrating radar and joint discrimination. This paper proposes a void recognition algorithm based on cluster analysis algorithm, using VRADI algorithm to process 3D ground-penetrating radar B-Scan, using DBSCAN clustering algorithm to divide clusters and remove noise; proposes correlation weighting coefficient Wi,j to quantitatively evaluate the degree of correlation of different survey channels, proposes prime relative position coefficient Pd indicator to quantitatively evaluate the position similarity, and proposes weighted homocentric overlap coefficient Pr indicator to quantify signal similarity. This paper applies the algorithm to carry out physical engineering experiments and uses binary logistic regression analysis to develop a correlation model. The experimental results show that significance of Pd and Pr are less than 0.05, both of which are important influencing indicators for the determination of the presence or absence of void. With an optimal critical probability of 0.4, the recognition accuracy of VRADI algorithm increases from 71.7% to 92.2%. The VRADI algorithm combined with the cluster analysis algorithm outperforms manual recognition in terms of accuracy (92.2% > 83.9%) and recall (90.5% > 86.9%), and the algorithm has good engineering application value.

With the rapid advancement of digital technology, artificial intelligence has ushered in a digital society. In this era, digital literacy has become a prerequisite for individuals, as its absence can lead to new vulnerabilities and inequalities, hindering the pursuit of sustainable development goals. Previous researches predominantly relied on questionnaires to assess digital literacy, often focusing on specific groups due to survey costs, making their methodology unsuitable for comprehensive countrywide measurement. To address these limitations, we propose FLAKE, a national digital literacy assessment framework. Within this framework, we devise a multi-task deep learning model called DLMaN, which employs mobile big data, such as users’ digital behaviors, to predict citizens’ digital literacy. FLAKE enables cost-effective assessment of digital literacy for massive citizens by surveying only a fraction of them and it also has valuable implications for other social research tasks. We test the framework’s performance using authentic survey data and mobile big data, achieving RMSE and MAPE of 5.233 and 8.65% respectively, and the improvement is significant compared to the baseline model. We further employ this model to assess the digital literacy of numerous citizens in China and explore the implications for the society and individuals based on the obtained results.

Abstract Objective To investigate the predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy (HCM) complicated by arrhythmias. Methods The clinical data of 158 patients with hypertrophic cardiomyopathy were retrospectively collected from July 2019 to December 2021, and additionally divided into training group 106 cases, validation group 26 cases and test group 26 cases according to the ratio of 4:1:1, and divided into concurrent and non-concurrent groups according to whether they were complicated by arrhythmia or not, respectively. General data of patients (age, gender, BMI, systolic blood pressure, diastolic blood pressure, HR) were collected, a deep learning model for cardiac ultrasound flow imaging was established, and image data, LVEF, LAVI, E/e', vortex area change rate, circulation intensity change rate, mean blood flow velocity, and mean EL value were extracted. Results The differences in general data (age, gender, BMI, systolic blood pressure, diastolic blood pressure, HR) between the three groups were not statistically significant, P > 0.05. The differences in age, gender, BMI, systolic blood pressure, diastolic blood pressure, HR between the patients in the concurrent and non-concurrent groups in the training group were not statistically significant, P > 0.05. Conclusions Deep learning-based cardiac ultrasound flow imaging can identify cardiac ultrasound images more accurately and has a high predictive value for arrhythmias complicating hypertrophic cardiomyopathy, and vortex area change rate, circulation intensity change rate, mean flow velocity, mean EL, LAVI, and E/e' are all risk factors for arrhythmias complicating hypertrophic cardiomyopathy.

Nitrogen tetroxide (N2O4) is commonly used as an oxidizer for bipropellant liquid, and galvanic corrosion of its storage tanks was a serious problem. The immersion and electrochemical experiments of Al 6061-SS 304 galvanic pair were carried out in 30% nitric acid at different temperatures. The accelerated galvanic corrosion of Al 6061 and the effect of different temperatures on its corrosion behavior were studied. The surface morphology, number of corrosion pits and electrochemical parameters of Al 6061 before and after corrosion were measured and analyzed by means of SEM, EDS and electrochemical methods. The results show that when Al 6061 was coupled with SS 304 at 10 °C, the driving potential difference between them reached 366 mVSCE, and Al 6061 was used as the corrosion anode. In the SEM images, three kinds of galvanic corrosion phenomena can be seen obviously after coupling. When the temperature is between 10 °C and 30 °C, the corrosion pits are mainly composed of aluminum matrix coupled with second phase particles with positive or negative volt potential relative to it. When the temperature was between 40 °C and 50 °C, the corrosion pits showed mainly intergranular corrosion at the interface of different grains. At the same time, the increase in temperature led to the decrease in galvanic potential and the change in corrosion current. There was no simple linear relationship between galvanic current and temperature, but it satisfied a certain quantitative relationship, and the theoretical ratio was highly consistent with the actual ratio by the K–S test.

Abstract To explore temporal and spatial effects on the planktonic prokaryotic community composition (PCC) in the coastal region of the Bohai Sea, surface water samples were collected from 12 to 28 regularly distributed sites in Bohai Bay across 3 months from different seasons to characterize the PCC using high-throughput sequencing of the 16S rRNA V4 region. Prokaryotic α- and β-diversity showed significant temporal variation during the three sampling months. VPA analysis based on both weighted and unweighted UniFrac distances exhibited a shift of environmental and spatial effects on PCC variation with temporal variation. Quantification analysis of assembly processes on community turn over showed that “heterogeneous selection” dominated for PCC temporal variation, with basic abiotic parameters such as temperature, pH, ammonia nitrogen as the driving factors. Analysis of seasonal features showed that seasonal specific OTUs (ssOTUs) exhibited different seasonal attributions under the same phylum; meanwhile, the ssOTUs showed significant correlations with the driving environmental factors, which suggested that finer-level analysis was needed to more strictly reflect the temporal variation. Moreover, predicted nitrogen and sulfur metabolism were significantly shifted during the temporal variation. Our results clearly showed that seasonally varied environmental factors drive the “heterogeneous selection” process for PCC assembly in seawaters of Bohai Bay during different sampling seasons.

This paper investigates the average peak age-of-information (APAoI) in a cooperative wireless sensor network (WSN), which deploys non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) techniques. To assist the poor source–destination direct link, the relay can utilize the harvested energy to decode the superposition-coded signal sent by the source and send its decoded information to the remote destination. With the aim of minimizing APAoI for long-term transmission, we formulate an energy allocation policy problem to trade off rate, energy, and time under certain constraints. To overcome the difficulties caused by time-varying parameters and non-convexity constraints, we perform a quasi-static transformation to obtain a simplified optimization model and some energy allocation criteria. Based on this work, we propose a heuristic APAoI real-time adaptive optimization (APRAO) algorithm that decomposes the original problem into multiple sub-problems for each transmission. During the sub-problem solving process, we introduce the static energy allocation criteria, which let the obtained solutions help our APRAO algorithm track the optimal solution as the transmission number increases. Finally, we evaluate and verify the performance of the proposed algorithm through numerical experiments.

For the typical magnetically coupled wireless power transmission system, power consumption is often caused by the impedance effect of the primary and secondary sides, the loss and heat generation of the actual semiconductor devices and the change of the coupling coefficient caused by distance. The uncertainty of frequency tracking efficiency caused by high enough coil transmission with low load receiving efficiency and load impedance changes makes it difficult to stabilize the output of the optimal efficiency point of the system. In order to solve this problem, a wireless power transmission system is proposed based on the traditional wireless power transmission system a wireless power transmission system is proposed to predict and stabilize the variable impedance, so as to stably track the efficiency of the system in the resonant frequency range. It is not affected by load jitter, actual circuit parameters and environmental disturbance. The test results show that the transmission efficiency of tracking frequency and predicting impedance can be realized at a certain distance, and the difference between the prediction error and the actual efficiency is about 1%–3%.

Abstract Stigmasterol (ST) has been shown to improve both lipid and bile acid (BA) metabolism. However, the mechanism(s) by which ST prevents dyslipidemia via BA metabolism, and the potential involvement of other regulatory mechanisms, remains unclear. Here, we found that ST treatment effectively alleviates lipid metabolism disorder induced by a high-fat diet (HFD). Moreover, we also show that fecal microbiota transplantation from ST-treated rats displays similar protective effects in rats fed on an HFD. Our data confirm that the gut microbiota plays a key role in attenuating HFD-induced fat deposition and metabolic disorders. In particular, ST reverses HFD-induced gut microbiota dysbiosis in rats by reducing the relative abundance of Erysipelotrichaceae and Allobaculum bacteria in the gut. In addition, ST treatment also modifies the serum and fecal BA metabolome profiles in rats, especially in CYP7A1 mediated BA metabolic pathways. Furthermore, chenodeoxycholic acid combined with ST improves the therapeutic effects in HFD-induced dyslipidemia and hepatic steatosis. In addition, this treatment strategy also alters BA metabolism profiles via the CYP7A1 pathway and gut microbiota. Taken together, ST exerts beneficial effects against HFD-induced hyperlipidemia and obesity with the underlying mechanism being partially related to both the reprogramming of the intestinal microbiota and metabolism of BAs in enterohepatic circulation. This study provides a theoretical basis for further study of the anti-obesity effects of ST and consideration of the gut microbiota as a potential target for the treatment of HFD-induced dyslipidemia.

Study region: The Dongting Lake Basin is a typical regional study in humid southern China with data-scarce areas. Study focus: This study improved the streamflow simulation by coupling hydrological and hydrodynamic models and considering water yields in data-scarce areas. We constructed a soil and water assessment tool (SWAT) hydrological model of the Dongting Lake Basin to simulate the streamflow in the data-scarce areas, which was further coupled into the MIKE21 hydrodynamic model as additional boundary conditions. New hydrological insights: The results showed that the relative error of streamflow simulation was reduced from 24.64 % to 10.50 % in the coupled hydrological-hydraulic model over the singular hydrodynamic model, which also indirectly verified the results of streamflow simulation in the data-scarce area. Based on the coupled model, the annual water yields in the data-scarce areas were estimated to be 38.95 × 109 m3, representing 15.13 % of the yearly water yields in the basin. The water yields in the data-scarce areas showed a seasonal variation, which was concentrated from April to July. The monthly water balance error of the Dongting Lake Basin was significantly reduced (57.42 %) when considering the water yields in data-scarce areas. The model-coupling approach in this study can be applied to other data-scarce areas to improve streamflow simulation.

Additive manufacturing (AM) has a bright application prospect because of its ability to efficiently manufacture complex and precise parts. However, defects such as pores and surface roughness produced in the manufacturing process severely restrict its application. Here ultrasonic fatigue test is conducted to evaluate the effects of sandblasting and hot isostatic pressing (HIP) on the VHCF performance of IN718 fabricated by selective laser melting (SLM). X-ray computed tomography (CT) and a 3D-optical profiler are used to characterize the defects, including size and location. After sandblasting, the crack initiation sites transfer from surface to interior, which is attributed to the improved surface state. Kurtosis, rather than the often-employed arithmetical mean height, is used to evaluate the contribution of sandblasting on surface state due to its ability to characterize surface defect morphology. With the elimination of defects and the introduction of the compressive residual stress under the combination of sandblasting and HIP, the potential initiation sites are transferred from the locations of defects to the weak microstructure, which still significantly improves the fatigue resistance. The tensile test reveals that the VHCF performance was more sensitive to small defects than the tensile properties. Finally, the influence of defects on fracture behavior is analyzed in the framework of fracture mechanics.

Cholangiocarcinoma (CCA) is a rare and aggressive type of malignant tumor. In the past few years, there has been an increase in the incidence of CCA. Surgery is the only effective treatment but is only suitable for a small percentage of patients. Comprehensive treatment is the normal therapy for terminal CCA patients, depending basically on gemcitabine and cisplatin combination chemotherapy. In the past decade, the emergence of next-generation sequencing technology can be used for the identification of important molecular features of CCA, and several studies have demonstrated that different CCA subtypes have unique genetic aberrations. Targeting fibroblast growth factor receptor (FGFR), isocitrate dehydrogenase (IDH) and epidermal growth factor receptor 2 (EGFR2) are emerging targeted therapies. In addition, researches have indicated that immunotherapy has a key function in CCA. There is ongoing research on programmed cell death protein 1 inhibitors (PD-1), chimeric antigen receptor T cells (CAR-T) and tumor-infiltrating leukocyte (TILs). Researches have shown that targeted therapy, immunotherapy, and conventional chemotherapy in CCA had certain mechanistic links, and the combination of those can greatly improve the prognosis of advanced CCA patients. This study aimed to review the research progress of targeted therapy and immunotherapy for CCA.

Abstract CD73, a cell surface‐bound nucleotidase, facilitates extracellular adenosine formation by hydrolyzing 5′‐AMP to adenosine. Several studies have shown that CD73 plays an essential role in immune escape, cell proliferation and tumor angiogenesis, making it an attractive target for cancer therapies. However, there are limited clinical benefits associated with the mainstream enzymatic inhibitors of CD73, suggesting that the mechanism underlying the role of CD73 in tumor progression is more complex than anticipated, and further investigation is necessary. In this study, CD73 is found to overexpress in the cytoplasm of pancreatic ductal adenocarcinoma (PDAC) cells and promotes metastasis in a nucleotidase‐independent manner, which cannot be restrained by the CD73 monoclonal antibodies or small‐molecule enzymatic inhibitors. Furthermore, CD73 promotes the metastasis of PDAC by binding to the E3 ligase TRIM21, competing with the Snail for its binding site. Additionally, a CD73 transcriptional inhibitor, diclofenac, a non‐steroidal anti‐inflammatory drug, is more effective than the CD73 blocking antibody for the treatment of PDAC metastasis. Diclofenac also enhances the therapeutic efficacy of gemcitabine in the spontaneous KPC (LSL‐KrasG12D/+, LSL‐Trp53R172H/+, and Pdx‐1‐Cre) pancreatic cancer model. Therefore, diclofenac may be an effective anti‐CD73 therapy, when used alone or in combination with gemcitabine‐based chemotherapy regimen, for metastatic PDAC.

Microbial inoculation with plant growth-promoting microorganisms (PGPMs) is one of the most promising technologies to solve the current global challenges. Co-inoculants is more efficient and stable than mono-inoculants. However, the growth promoting mechanism of co-inoculants in complex soil system is still poorly understood. In this study, the effects on rice, soil and the microbiome of the mono-inoculant Bacillus velezensis FH-1 (F) and Brevundimonas diminuta NYM3 (N) and the co-inoculant FN obtained in previous works were compared. Correlation analysis and PLS-PM were used to explore the primary mechanism of different inoculants promoting rice growth. We hypothesized that inoculants promoted plant growth (i) by themselves, (ii) by improving soil nutrient availability or (iii) by regulating the rhizosphere microbiome in complex soil system. We also assumed that different inoculants had different ways of promoting plant growth. The results showed that FN significantly promoted rice growth and nitrogen absorption and slightly increased soil total nitrogen and microbial network complexity compared with F, N and the control (CK). B. velezensis FH-1 and B. diminuta NYM3 interfered with each other’s colonization in FN. FN increased the complexity of the microbial network compared to F and N. The bacterial community of FN was quite different from CK and N, while the fungal community was not significantly different from other treatments. The species and functions enriched or inhibited by FN are part of F. The correlation analysis and PLS-PM results showed that inoculants (F/N/FN) promoted the growth of rice mainly by regulating the rhizosphere microbiome rather than by themselves or by improving soil nutrient availability. Co-inoculant FN promotes rice growth specifically by enhancing microbial nitrification function through enriching related species compared with F or N. This may provide theoretical guidance for the construction and application of co-inoculants in the future.

In order to analyze the thixotropy of mastic asphalt concrete during the mixing process, the factors affecting the thixotropy of mastic asphalt binder and asphalt mastic are studied, and the measures to shorten the mixing time of mastic asphalt mixture are given. The dynamic viscosity of mastic asphalt binder and asphalt mastic with time and shear rate is obtained via the step frequency method, and the thixotropic constitutive models of mastic asphalt binder and asphalt mastic are constructed by structural dynamics model, exponential equation, and extended exponential equation respectvely. The improved time thixotropy index is used to analyze the effects of asphalt type, asphalt–aggregate ratio, filler type, heating temperature, and shear rate, and the laws of various factors affecting the thixotropy of mastic asphalt binder and asphalt mastic are obtained. The research shows that the extended exponential model can better characterize the thixotropy of mastic asphalt binder and asphalt mastic under different shear rates. When the amount of lake asphalt or cement is increased, the viscosity of the system and the mixing time to reach a steady viscosity increases; that is, the mixing time needs to be increased. Increasing shear temperature does not change the time parameter to reach steady viscosity; that is, it cannot shorten mixing time. When the shear rate is increased, the time for the system to reach the steady viscosity will be shortened; that is, the time for mixing the mixture can be shortened.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment in recent years and provide new opportunities to treat hepatocellular carcinoma (HCC). To date, several ICIs have been approved by the FDA for advanced HCC in first-line or second-line therapy. Downstaging conversion therapy for potentially resectable HCC to provide opportunities for surgical intervention is challenging. ICIs have become a hot spot in this field due to their high response rate. However, HCC has various etiologies and can evade the immune system through multiple mechanisms, which limit the efficacy of ICI monotherapy and demand novel combination strategies. Radiation therapy (RT) is also a candidate for conversion therapy in HCC and is currently gaining increasing attention as a good combination partner with ICIs due to its ability to modulate the tumor microenvironment. In this review, we illustrate the current indications for ICIs and RT in HCC, the rationale for their synergistic combination, and the current clinical trials in combination therapy. We also speculate on predictive biomarkers and novel future strategies to further enhance the efficacy of this combination. This review aims to provide references for future research on radiation and immunotherapy to arrive at a promising new era of HCC treatment.

In this study, mesoporous TiO2 with various hydrolysis rates were prepared and combined with H2O2 for the photodegradation of unsymmetrical dimethylhydrazine (UDMH) under VUV irradiation. Results showed that the mesoporous TiO2 synthesized by the hydrolysis in water (MT100) exhibited a good mesoporous structure and the largest specific surface area (178.85 m2 g−1). Consequently, MT100 showed the best degradation efficiency, with the rate constant (k) for VUV/MT100 and VUV/MT100/H2O2 of 0.0185 and 0.2595 min−1, respectively, which was 1.4 and 4.0 times of that of P25. The addition of H2O2 significantly enhanced the degradation efficiency by photoactivation of H2O2 and the synergistic effect. The rate constant and the mineralization rate (after a 3-h treatment) increased by 13 and 3.8 times when 40 mM H2O2 was added into VUV/MT100. The weak alkaline condition (pH = 9) would facilitate the degradation of UDMH. The ⋅OH was the key oxidizing species in VUV/MT100/H2O2. Eight intermediates were detected during the degradation and the possible pathways of UDMH degradation in VUV/MT100/H2O2 process were proposed. VUV/MT100/H2O2 provides an efficient method to degrade UDMH.

Anti-PD-1/PD-L1 therapy has shown significant benefits in the treatment of a variety of malignancies. However, not all cancer patients can benefit from this strategy due to drug resistance. Therefore, there is an urgent need for methods that can effectively improve the efficacy of anti-PD-1/PD-L1 therapy. Combining anti-PD-1/PD-L1 therapy with regorafenib has been demonstrated as an effective method to enhance its therapeutic effect in several clinical studies. In this review, we describe common mechanisms of resistance to anti-PD-1/PD-L1 therapy, including lack of tumor immunogenicity, T cell dysfunction, and abnormal expression of PD-L1. Then, we illustrate the role of regorafenib in modifying the tumor microenvironment (TME) from multiple aspects, which is different from other tyrosine kinase inhibitors. Regorafenib not only has immunomodulatory effects on various immune cells, but can also regulate PD-L1 and MHC-I on tumor cells and promote normalization of abnormal blood vessels. Therefore, studies on the synergetic mechanism of the combination therapy may usher in a new era for cancer treatment and help us identify the most appropriate individuals for more precise treatment.

Domain pattern is the carrier of electromechanical property. A novel domain pattern will open a gate for ferroelectric nanodevice. A distinctive topological domain pattern termed as hierarchical vortex (Hvo) has been found in polycrystalline ferroelectric based on the first-principles-based atomistic method. The Hvo pattern displays a unique structure, which is a flux-closing vortex encircle an anti-vortex or a vortex and anti-vortex pair (VA). Each Hvo structure could be regarded as a single vortex to forming a vortex–anti-vortex pair with anti-vortex or forming a vortex–vortex array with the vortex. The mechanism of HVo obtained in polycrystalline ferroelectric has been found that the grain boundary (GB) equals the domain wall when the first-order vortex is in the vortex. The HVo will open a new view of the domain topology pattern and its evolution.

Chitin is the second-largest natural polymer polysaccharide in nature. Due to its important physical and chemical properties and excellent biocompatibility, safety, and biodegradability, it is widely used in agriculture, medicine, food, environmental protection, and other fields. However, traditional extraction methods cause environmental pollution and damage the structure of chitin. Bioprocessing is an emerging technology that shows great potential. In this research, the puparia and adults of black soldier fly (BSF) (Hermetia illucens L.) were used as raw materials. A continuous fermentation method was designed to extract chitin, by using Bacillus subtilis S4 and Acetobacter pasteurianus AS1.41. The Fourier transform infrared spectroscopy identification results showed that the extracted sample was α-chitin. Under continuous fermentation conditions, the deproteinization (DP) rate, demineralization (DM) rate, chitin yield (CY), and deacetylation degree (DD) of puparium chitin were 33.33%, 94.92%, 59.90%, and 18.52%, respectively. Meanwhile, the DP rate, DM rate, CY, and DD of adult chitin were 46.63%, 90.93%, 47.31%, and 37.38%, respectively. For BSF, B. subtilis S4 had a certain DP ability, and A. pasteurianus AS1.41 had a good DM effect. Moreover, BSF at different developmental stages could affect CY, and a higher concentration of NaOH was more favorable for deacetylation. Overall, simultaneous continuous fermentation could be a new biological approach to extract chitin from BSF.

The asymmetric deformation of glass-to-metal seals is an important defect that would lead to the failure of the pressure boundary in nuclear reactors. In this research, an efficient approach to measure the asymmetric deformation and prevent the potential failure was proposed based on the spectrum characterization of fiber Bragg grating (FBG) sensors. The asymmetric deformation was induced from small-size large-gradient nonuniform strain in sealing materials; as a result, it could be monitored through the spectra of embedded FBGs affected by strain variations. The theoretical analysis of the FBG spectrum was carried out using the transfer matrix model (TMM) to validate the measuring feasibility and reliability. Based on the theoretical results, the asymmetric deformation was measured by the distributed embedded FBG experimentally. By combining the reconstructed spectrum and the experimental results, the asymmetric deformation of glass-to-metal was proved to be monitored, and the defect was able to be prevented during the manufacturing process effectively via the proposed method.

The homojunction provides an effective way to extend the properties of stainless steel, but also leaves more weak points for small atoms to penetrate. In this study, the effects of hydrogen, carbon, and nitrogen atoms at the interface on the austenite/ferrite homojunction were investigated using first principles. This study found that low concentrations of carbon/nitrogen are favorable for the pairing of FCC with BCC compared to hydrogen, which can effectively improve the bonding energy and stability of homogeneous junctions. However, at high concentrations, the interfacial hydrogen can partially act as a mediator for interfacial bonding, which results in a slower decrease in bonding energy. On the contrary, nitrogen causes a sharp decrease in interfacial matching due to excessive strengthening of austenite, which reduces both the binding energy and the stability of the overall system. This study provides valid data and a unique perspective on the development of the austenite/ferrite homojunction.

The three-dimensional ground-penetrating radar system is an effective method to detect road void disease. Ground penetrating radar image interpretation has the characteristics of multi-solution, long interpretation period, and high professional requirements of processors. In recent years, researchers have put forward solutions for automatic interpretation of ground-penetrating radar images, including automatic detection algorithm for subgrade diseases based on support vector machines, etc., but there are still some shortcomings such as training models with a large amount of data or setting parameters. In this article, a three-dimensional ground-penetrating radar void signal recognition algorithm based on the digital image is proposed, and the algorithm uses digital images to characterize radar signals. With the help of digital image processing methods, the images are processed by binarization, corrosion, expansion, connected area inspection, fine length index inspection, and three-dimensional matching inspection, so as to identify and determine the void signals and extract the void area volume index. The algorithm has been verified by laboratory tests and engineering projects, and the results show that the void identification algorithm can accurately identify the void area position; the error level between the measured values and the measured values of length, width, buried depth, and area is between 2.2 and 17.3%, and the error is generally within the engineering acceptance range. The volume index calculated by the algorithm has a certain engineering application value; compared with the support vector machine, the regressive convolution neural network, and other recognition methods, it has the advantage of not needing a large amount of data to train or modify parameters.

The study on sediments in the marginal basins of the Tibetan Plateau is of great significance for global climate change. The geological information of the Linxia Basin has been intensely investigated; however, the profiles of the microbial communities in this basin remain largely unknown. Here, based on the 16S rRNA high-throughput sequencing method, the bacterial community structure vertical succession is studied with different thicknesses of sedimentary samples. The bacterial community with a total of 1,729,658 paired reads distributed within 1,042 phylogenetic amplicon sequence variants (ASVs) from twenty sediments, and three surrounding soil samples were sequenced. First, high-throughput sequencing results highlight the surrounding soil sample bacterial community structures were significantly different from those recovered from the sediment samples. In addition, as observed in the PCoA and PERMANOVA, there is a dramatic change shift event of the community structure at M311. Our data suggest that shifts in relative abundances of the abundant taxa (˃1%) and the significant variations in the diversity of bacterial community implied community structure responses to changes in different sedimentary layers. Predicted community function changes demonstrate that the sediment bacterial community aerobic chemoheterotrophy has been significantly increased, and we believe that the possible influence of the lithofacies changes from the anaerobic system to the aerobic environment, possibly accompanied by the significant uplift of the plateau that has previously been associated with enhanced aridity in Central Asia at ∼8 Ma. Taken together, these results illustrate the potential for the microbial community as a biological indicator in sediment ecosystems to reconstruct paleoenvironments.

With the aging of the human body and the reduction in its physiological capacities, falls have become a huge threat to individuals’ physical and mental health, leading to serious bodily damage to the elderly and financial pressure on their families. As a result, it is vital to design a fall detection algorithm that monitors the state of human activity. This work designs a human fall detection algorithm based on hierarchical decision making. First, this work proposes a dimensionality reduction approach based on feature importance analysis (FIA), which optimizes the feature space via feature importance. This procedure reduces the dimension of features greatly and reduces the time spent by the model in the training phase. Second, this work proposes a hierarchical decision-making algorithm with an XGBoost model. The algorithm is divided into three levels. The first level uses the threshold approach to make a preliminary assessment of the data and only transfers the fall type data to the next level. The second level is an XGBoost-based classification algorithm to analyze again the type of data which remained from the first level. The third level employs a comparison method to determine the direction of the falling. Finally, the fall detection algorithm proposed in this paper has an accuracy of 98.19%, a sensitivity of 97.50%, and a specificity of 98.63%. The classification accuracy of the fall direction reaches 93.44%, and the algorithm can efficiently determine the fall direction.

Three-dimensional (3D) ground-penetrating radar is an effective method for detecting internal crack damage in pavement structures. Inefficient manual interpretation of radar images and high personnel requirements have substantially restrained the generalization of 3D ground-penetrating radar. An improved Crack Unet model based on the Unet semantic segmentation model is proposed herein for 3D ground-penetrating radar crack image processing. The experiment showed that the MPA, MioU, and accuracy of the model were improved, and it displayed better capacity in the radar image crack segmentation task than current mainstream algorithms do, such as deepLabv3, PSPNet, and Unet. In the test dataset without cracks, Crack Unet is on the same level as deepLabv3 and PSPNet, which can meet engineering requirements and display a significant improvement compared with Unet. According to the ablation experiment, the MPA and MioU of Unet configured with PMDA, MC-FS, and RS modules were larger than those of Unet configured with one or two modules. The PMDA module adopted by the Crack Unet model showed a higher MPA and MioU than the SE module and the CBAM module did, respectively. The results show that the Crack Unet model has a better segmentation ability than the current mainstream algorithms do in the task of the crack segmentation of radar images, and the performance of crack segmentation is significantly improved compared with the Unet model. The Crack Unet model has excellent engineering application value in the task of the crack segmentation of radar images.

To address the limitations in global seafloor topography model construction, a scheme is proposed that takes into account the efficiency of seafloor topography prediction, the applicability of inversion methods, the heterogeneity of seafloor environments, and the inversion advantages of sea surface gravity field element. Using the South China Sea as a study area, we analyzed and developed the methodology in modeling the seafloor topography, and then evaluated the feasibility and effectiveness of the modeling strategy. Based on the proposed modeling approach, the STO_IEU2020 global bathymetry model was constructed using various input data, including the SIO V29.1 gravity anomaly (GA) and vertical gravity gradient anomaly (VGG), as well as bathymetric data from multiple sources (single beam, multi-beam, seismic, Electronic Navigation Chart, and radar sensor). Five evaluation areas located in the Atlantic and Indian Oceans were used to assess the performance of the generated model. The results showed that 79%, 89%, 72%, 92% and 93% of the checkpoints were within the ±100 m range for the five evaluation areas, and with average relative accuracy better than 6%. The generated STO_IEU2020 model correlates well with the SIO V20.1 model, indicating that the proposed construction strategy for global seafloor topography is feasible.

In this paper, a 650 V 4H-SiC trench Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) with a hetero-junction diode (HJD) and double current spreading layers (CSLs) is proposed and studied based on Sentaurus TCAD simulation. The HJD suppresses the turn-on of the parasitic body diode and improves the performance in the third quadrant. CSLs with different doping concentrations help to lower the on-state resistance as well as the gate-drain capacitance. As a result, the on-state resistance is decreased by 47.82% while the breakdown voltage remains the same and the turn-on and turn-off losses of the proposed structure are reduced by 83.39% and 68.18% respectively, compared to the conventional structure.

In order to improve the prediction accuracy regarding low compaction level of asphalt pavement, this paper carries out indoor tests to detect the voids and dielectric constants of AC-13, AC-16 and AC-25 asphalt mixtures, obtaining their relationship equations via linear fitting and determining the dielectric constant judgment threshold of low compaction level segregation risk points ε1. Based on the common mid-point method, three-dimensional ground-penetrating radar is used to obtain the dielectric constant of the physical engineering test section. The researcher can draw the distribution map of the low compaction level segregation risk area according to the judgment threshold ε1 of the rough segregation risk points; divide the connected risk areas; determine the regional convex hull; and calculate the regional indicators such as the regional area, the ratio of the convex risk points and the mean value of the regional dielectric constant. The response surface analysis method is used to acquire the model of risk area index and core void ratio. The model is employed to predict and verify the core void ratio in the risk area of the road section and verify the accuracy of the model. The results show that the error range between the predicted voids and the measured voids is −0.4%~+0.4%, and the mean absolute value of the error is 0.25%. Compared with the mean measured voids of 6.63%, the relative error is 3.77%, indicating that the model can accurately predict the regional low compaction level segregation degree.

Compliant bipedal robots demonstrate a potential for impact resistance and high energy efficiency through the introduction of compliant elements. However, it also adds to the difficulty of stable control of the robot. To motivate the control strategies of compliant bipedal robots, this work presents an improved control strategy for the stable and fast planar jumping of a compliant one-legged robot designed by the authors, which utilizes the concept of the virtual pendulum. The robot was modeled as an extended spring-loaded inverted pendulum (SLIP) model with non-negligible torso inertia, leg inertia, and leg damping. To enable the robot to jump forward stably, a foot placement method was adopted, where due to the asymmetric feature of the extended SLIP model, a variable time coefficient and an integral term with respect to the forward speed tracking error were introduced to the method to accurately track a given forward speed. An energy-based leg rest length regulation method was used to compensate for the energy dissipation due to leg damping, where an integral term, regarding jumping height tracking error, was introduced to accurately track a given jumping height. Numerical simulations were conducted to validate the effectiveness of the proposed control strategy. Results show that stable and fast jumping of compliant one-legged robots could be achieved, and the desired forward speed and jumping height could also be accurately tracked. In addition to that, using the proposed control strategy, the robust jumping performance of the robot could be observed in the presence of disturbances from state variables or uneven terrain.