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With the advancement of Internet of Things (IoT) technology, both the methods of data collection by citizen data collectors and the willingness of citizens to share data are evolving. To analyze the long-term impact of government reward-penalty mechanisms on citizen data collection, this paper constructed three evolutionary game models under scenarios of no reward-penalty, static reward-penalty, and dynamic reward-penalty mechanisms. The focus is on comparing and analyzing evolutionarily stable strategies of a collector and a citizen, followed by computational simulations. Key findings include: 1) Under no reward-penalty and static reward-penalty mechanisms, evolutionarily stable strategies typically result in either consistently active or consistently passive behaviors by both the collector and the citizen. Mixed strategies, which are evolutionarily stable, emerge only under dynamic reward-penalty mechanisms. 2) The balance between the risk associated with data security for the citizen and the benefits they gain from public services significantly influences evolutionary outcomes. 3) Policy directions may be influenced by initial conditions in the pre-collection stage, which can be mitigated by improving the benefit to citizen or reducing the cost during passive data collection. 4) While reward-penalty mechanisms may not directly enhance data collection success rates, they do accelerate the evolutionary process of data collection.

Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA.

At present, bone-based products are abundant, and the main sources are bovine bone and pig bone, but there are few studies on the development of deer bone as a bone repair material. Deer bone has important osteogenic effects in the theory of traditional Chinese medicine. It is rich in protein, ossein, and a variety of trace elements, with the effect of strengthening tendons and bones. Nanomaterials and their application in the repair of bone defects have become a research hotspot in bone tissue engineering. In this study, nano-deer bone meal (nBM), nano-calcined deer bone meal, and nano-demineralized bone matrix were successfully prepared. It was found that the Ca/P ratio in deer bone was significantly higher than that in cow bone and human bone tissue, and deer bone contained beneficial trace elements, such as potassium, iron, selenium, and zinc, which were not found in cow bone. The three kinds of deer bone powders prepared in this study had good biocompatibility and met the implantation standards of medical biomaterials. Cell function studies showed that compared with other bone powders, due to the presence of organic active ingredients and inorganic calcium and phosphate salts, nBM had excellent performance in the proliferation, adhesion, migration, and differentiation of bone marrow mesenchymal stem cells. These findings indicate that nBM can be used as a potential osteoinductive active nanomaterial to enhance bone tissue engineering scaffolds with certain application prospects.

Ecological security assessments are used to reflect the regional ecological security situation because they can provide a basis for the construction of regional ecological security patterns (ESPs). Using the land use/land cover (LULC) data, the ecological security status of the Hexi Region was analyzed. On this basis, the ecological source was extracted, the ecological resistance surface was established, and the ecological corridor and node were identified, and constructed the ESP of the Hexi Region. The results show that: 1) During 2000–2015, approximately 70% of the study area’s ecological security index values were

Urban street space is a critical reflection of a city’s vitality and image and a critical component of urban planning. While visual perceptual information about an urban street space can reflect the composition of place elements and spatial relationships, it lacks a unified and comprehensive quantification system. It is frequently presented in the form of element proportions without accounting for realistic factors, such as occlusion, light and shadow, and materials, making it difficult for the data to accurately describe the complex information found in real scenes. The conclusions of related studies are insufficiently focused to serve as a guide for designing solutions, remaining merely theoretical paradigms. As such, this study employed semantic segmentation and information entropy models to generate four visual perceptual information quantity (VPIQ) measures of street space: (1) form; (2) line; (3) texture; and (4) color. Then, at the macro level, the streetscape coefficient of variation (SCV) and K-means cluster entropy (HCK) were proposed to quantify the street’s spatial variation characteristics based on VPIQ. Additionally, we used geographically weighted regression (GWR) to investigate the relationship between VPIQ and street elements at the meso level as well as its practical application. This method can accurately and objectively describe and detect the current state of street spaces, assisting urban planners and decision-makers in making decisions about planning policies, urban regeneration schemes, and how to manage the street environment.

Mitigation of the heat island effect is critical due to the frequency of extremely hot weather. Urban street greening can achieve this mitigation and improve the quality of urban spaces and people’s welfare. However, a clear definition of street green space morphology is lacking, and the nonlinear mechanism of its cooling effect is still unclear; the interaction between street green space morphology and the surrounding built environment has not been investigated. This study used machine learning, deep learning, and computer vision methods to predict land surface temperature based on street green space morphology and the surrounding built environment. The performances of the XGBoost, LightGBM, and CatBoost models were then compared, and the nonlinear cooling effects offered by the street green space morphology were analyzed using the Shapley method. The results show that streets with a high level of green environment exposure (GVI > 0.4, NDVI > 4) can accommodate more types of green space morphology while maintaining the cooling effect. Additionally, the proportion of vegetation with simple geometry (FI < 0.2), large leaves (FD < 0.65), light-colored leaves (CSI > 13), and high leaf density (TDE > 3) should be increased in streets with a low level of green environment exposure (GVI < 0.1, NDVI < 2.5). Meanwhile, streets with highly variable building heights (AFI > 1.5) or large areas covered by buildings (BC > 0.3) should increase large leaf vegetation (FD < 0.65) while decreasing dark leaf vegetation (CSI < 13). The study uses machine learning methods to construct a nonlinear cooling benefit model for street green space morphology, proposes design recommendations for different street green spaces that consider climate adaptation, and provides a reference for urban thermal environment regulation.

The host-guest chemistry of metal–organic frameworks (MOFs) has been attracting increasing attention owing to the outstanding properties derived from MOFs-guests combinations. However, there are large difficulties involved in the syntheses of the host-guest MOF systems with air-sensitive metal complexes. In addition, the behaviors on host-guest interactions in the above systems at high temperature are not clear. This study reported the synthetic methods for host-guest systems of metal–organic framework and air-sensitive metal complexes via a developed chemical vapor infiltration process. With the synchrotron X-ray powder diffraction (XRPD) measurements and Fourier Transform infrared spectroscopy (FTIR), the successful loadings of Fe(CO)5 in HKUST-1 and NH2-MIL-101(Al) have been confirmed. At high temperatures, the structural and chemical componential changes were investigated in detail by XRPD and FTIR measurements. HKUST-1 was proven to have strong interaction with Fe(CO)5 and resulted in a heavy loading amount of 63.1 wt%, but too strong an interaction led to deformation of HKUST-1 sub-unit under heating conditions. NH2-MIL-101(Al), meanwhile, has a weaker interaction and is chemically inert to Fe(CO)5 at high temperatures.

The rapid development of productivity and economy has led to a substantial change in global land use/land cover (LULC), which has caused a series of environmental problems. Therefore, it is particularly important to quantitatively grasp the spatiotemporal pattern of LULC to formulate and implement land use planning. This study extracted LULC by the combination of supervised classification and manual visual interpretation and quantitatively analyzed the spatiotemporal changes in LULC. Finally, the land use situation was simulated, and the driving forces affecting LULC changes were analyzed with the logistic regression-cellular automata-Markov chain (LR-CA-Markov) and FLUS models. The results showed that the ecological environment underwent more noticeable changes in approximately the year 2000. Relatively speaking, LULC changes were the most dramatic during 1987–1997. With the implementation of the Grain for Green Project (GFGP) in 1999, the ecological environment began to develop towards a positive trend, but built-up land area has also grown rapidly. The economy was the main factor influencing the change in LULC. The simulation results showed that the simulation accuracy and kappa coefficient of the LR-CA-Markov and FLUS models were both greater than 0.85, and the prediction results of the same land-type change trend were basically the same. On this basis, the land use scenario in 2027–2047 was predicted. The results showed that the LULC would change dramatically over the next 30 years (likely due to urban expansion). Therefore, LULC research in arid regions can provide theoretical guidance for protecting the ecological environment, rationally planning land use, and realizing the sustainable development of arid zones, such as the economy, society, and ecological environment.

Based on the separation voltage type of cascaded H bridge-modular multilevel converters (CHB-MMC) and current predictive model control (CPMC) technology, a novel flexible fault-current limiter (NFFCL) is firstly proposed for restraining the negative impact of the distribution network's disturbance in this paper. When a disturbance occurs, the inner-loop CPMC of the multilevel converters establish the value function to offer the specific current, thus increasing the voltage deviation at both ends of the series capacitor or generating reverse harmonic compensation voltage. In that case, three single-phase MNFFCLs can be regarded as variable voltage sources to eliminate the negative effects of faults or harmonics. Owing to the multi-capacitance series structure, the maximum voltage drops of the single capacitance can be predetermined by the number of capacitors. And with the low voltage drop of single capacitance, the output current of the CHB-MMC can also be controlled within an acceptable range. Through the simulation results, the disturbance's negative impact on the non-fault area can be eliminated almost 100%.

This study investigates the flexural strength of simply supported steel-concrete composite beams under hogging moment. A total of 24 composite beams are included in the experiments, and ABAQUS software is used to establish finite element (FE) models that can simulate the mechanical properties of composite beams. In a parametric study, the influences of several major parameters, such as shear connection degree, stud arrangement and diameter, longitudinal and transverse reinforcement ratios, loading manner, and beam length, on flexural strength were investigated. Thereafter, three standards, namely, GB 50017, Eurocode 4, and BS 5950, were used to estimate the flexural strength of the composite beams. These codes were also compared with experimental and numerical results. Results indicate that GB 50017 may provide better estimations than the other two codes.

This article presents the experimental and finite element (FE) analyses of two conventional rectangular concrete-filled steel tubular (CFT) stub columns, two stiffened rectangular concrete-filled steel tubular (SCFT) stub columns, and two stirrup confinement rectangular concrete-filled steel tubular (CCFT) stub columns concentrically loaded in compression to failure. The influences of the ductility and ultimate bearing strength of these stub columns with stiffening ribs or spiral stirrup confinement were discussed. Abaqus was used to establish a 3D FE model and analyze the properties of CFT stub columns subjected to axial compression. The effect of the concrete core and rectangular steel tube under loop stirrup confinement was discussed. Analytical results showed that spiral stirrup confinement can availably retard the local bucking of the rectangular steel pipe, and the effect of the spiral stirrup confinement was stronger than that of stiffeners. The DI values of SCFT and CCFT were 21.9% and 31.9% larger than those of CFT, respectively. The ultimate capacity values of SCFT and CCFT were 10.2% and 18% larger than those of CFT, respectively. The ductility and ultimate bearing strength of the specimens improved effectively under spiral stirrup confinement, and the ductility of the CCFT columns was preferable to that of the SCFT columns.

Analyzing the importance of the factors which influence the flow safety of the heated oil pipeline is an important part of the whole assessment process, which is of great significance on the results analysis, phenomenon explanation, and risk control after the assessment. Focusing on the problems in the influencing factors' importance analysis on crude oil pipeline flow assurance assessment, a new method to analyze the importance of the influencing factors is proposed which considers the factors' fluctuations. Based on the actual probability distribution of the influencing factors during the stable operation of the pipeline, a new measure standard of the factors' importance is defined which can measure different factors importance and realize the importance sorting of each factor. The influence of different factors on the inlet temperature is taken as an example. The importance analysis and sensitivity analysis of the influencing factors on the actual pipeline have been done, the results of which are also compared. The results show that this method can combine the pipeline actual operating conditions and the influencing factors' actual fluctuation, reflecting the effect on the results' importance in different values of each factor and different fluctuation. This method can make comprehensive analysis on the importance of the influencing factors effectively.

To meet the requirements of rail-bottom flaw detection, we use a differential-triple-coil sensor at low frequencies to detect rail-bottom flaws. Aiming at its online application to railways, we propose a single-cycle demodulation algorithm. To increase the ability to remove multiple interference signals in an electromagnetic environment, we analyze the anti-interference performance of the proposed algorithm in the frequency domain. We also discuss a method of achieving high anti-noise performance in rail-bottom flaw detection. In addition, we form artificial horizontal rail-bottom flaws in a standard rail specimen and carry out experiments on four horizontal rail-bottom flaws with different depths using the embedded inspection system. The experimental results demonstrate that the differential-triple-coil sensor with the proposed single-cycle demodulation algorithm can be used for horizontal rail-bottom flaw detection. Furthermore, horizontal rail-bottom flaws with a depth of less than 7 mm can be detected. [ABSTRACT FROM AUTHOR]

Abstract The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

Fusarium graminearum is the main pathogenic fungus causing wheat head blight. It not only causes severe crop yield reduction, but also produces fungal toxins such as deoxynivalenol (DON) and 15-acetyl deoxynivalenol (15-ADON), which are dangerous food pollutants to people and livestock. For the genetic functional study of Fusarium graminearum, it is often necessary to culture mycelium on LTB medium in the laboratory to investigate its regulatory effect on DON and 15-ADON synthesis. However, the detection of DON and 15-ADON in the mycelium is focused on extracellular, with less focus on the detection of intracellular. Simultaneous detection of intracellular and extracellular DON and 15-ADON can provide more in-depth information of fungal toxin production and secretion functions. In the study, a method based on gas chromatography-mass spectrometry (GC-MS) for simultaneous detection of DON and 15-ADON was developed. The solvents for extracting DON and 15-ADON can be completely separated and the calibration curves of each extract show good linear relationship within a certain range. The mass spectrometric characteristic scan shows high ionization efficiency for both DON and 15-ADON. The retention time of DON and 15-ADON in chromatogram are 6.98 and 7.68 min, respectively. Qualitative analysis of DON was performed using m/z 295, 235, and 193 under single ion monitor (SIM) mode, while m/z 392, 235, and 193 were used for 15-ADON. The highest intensity ion m/z 235 was selected for the quantification of DON, and m/z 193 for the quantification of 15-ADON. This method was used to detect the intracellular and extracellular levels of DON and 15-ADON in wild-type PH-1 and tri5 mutant with DON biosynthesis deficiency. The intracellular DON and 15-ADON levels in PH-1 are determined to be (149.13±9.15) μg/g and (1833.31±185.33) μg/g, extracellular levels are (5910.35±468.23) μg/g and (45222.12±2726.81) μg/g, respectively. The study identified a mutant strain with the deletion of the first enzyme involved in the synthesis pathway of DON and 15-ADON，both DON and 15-ADON are not detected in the extracellular and intracellular of the tri5 mutant. Additionally, this research confirms that after 7 days of cultivation in LTB medium, the wild-type strain exhibits higher levels of 15-ADON in both intracellular and extracellular compared to DON, with extracellular levels of DON and 15-ADON being higher than intracellular levels. This method can provide a methodological reference for the functional study of toxin synthesis in Fusarium graminearum.

Abstract Purpose Liver was one of the most common distant metastatic sites in breast cancer. Patients with distant metastasis were identified as American Joint Committee on Cancer (AJCC) stage IV indicating poor prognosis. However, few studies have predicted the survival in females with T1-2N0-1 breast cancer who developed liver metastasis. This study aimed to explore the clinical features of these patients and establish a nomogram to predict their overall survival. Results 1923 patients were randomly divided into training (n = 1154) and validation (n = 769) cohorts. Univariate and multivariate analysis showed that age, marital status, race, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), chemotherapy, surgery and bone metastasis, brain metastasis were considered the independent prognostic indicators. We developed a nomogram according to these ten parameters. The consistency index (c-index) was 0.72 (95% confidence interval CI 0.70–0.74) in the training cohort, 0.72 (95% CI 0.69–0.74) in the validation cohort. Calibration plots indicated that the nomogram-predicted survival was consistent with the recorded 1-, 3- and 5-year prognoses. Decision curve analysis curves in both the training and validation cohorts demonstrated that the nomogram showed better prediction than the AJCC TNM (8th) staging system. Kaplan Meier curve based on the risk stratification system showed that the low-risk group had a better prognosis than the high-risk group (P

Purpose: Function impairment is an early stage of disability in older adults and requires timely intervention. We have previously developed Function Impairment Screening Tool (FIST) based on the Delphi method, which has good reliability and validity, but the predictive effect is unknown. Therefore, we aimed to explore the role of FIST in predicting long-term mortality in community-dwelling older adults. Participants and methods: Data were from the Beijing Longitudinal Study of Aging. A total of 1,833 older adults with 8 years of follow-up were included. Function impairment was assessed using FIST. Cox proportional hazards model was used to calculate the predictive effect of FIST on 8-year all-cause mortality. Results: According to FIST, approximately half of the older adults had function impairment (47.6%). The prevalence of function impairment varied across populations. Logistic regression analysis showed that age, female, rural, poor health satisfaction, not drinking tea, and low Mini-Mental State Examination and intrinsic capacity score were associated with function impairment. Furthermore, function impairment was associated with poor physical function and high mortality. Cox analysis showed that FIST could predict 8-year mortality (hazard ratio [HR] = 3.26, 95% confidence interval [CI] 2.74–3.87), and this relationship persisted after adjusting for age, sex, area, marital status, live alone, educational level, smoking, drinking alcohol, and chronic diseases (HR = 1.79, 95% CI 1.45–2.17). Discussion: FIST can predict 8-year mortality in community-dwelling older adults. More attention should be paid to older adults with function impairment and early intervention should be provided.