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Objectives: Functional impairment can be an early indicator of cognitive decline. However, its predictive utility in cognitively normal (CN) older adults remains unclear. This study aimed to determine whether mild functional impairment (MFI) in CN older adults could predict incident dementia over 6 years, in addition to assessing its association with cognitive performance. Design: A longitudinal study with a 6-year follow-up. Participants: A cohort of 296 community-dwelling CN older adults. Measurements: MFI was defined by cutoffs for impairment on an objective performance-based and/or subjective questionnaire-based functional assessment. Cox regression analysis was conducted to assess the relationship between MFI and risk of incident dementia and cognitive performances over 6 years. Linear regression analysis examined the association between MFI and baseline cognitive performance. Results: There were no significant longitudinal associations between MFI and incident dementia or changes in cognitive performance over 6 years. Defining MFI using both performance-based and informant-reported assessments was predictive of dementia. Crosssectional analyses demonstrated significant associations between MFI and poorer baseline global cognition and performance in attention, visuospatial ability, and executive functioning. Conclusions: CN older adults with MFI were not at an increased risk of developing dementia over 6 years. A definition of functional impairment requiring both performance-based and informant-based assessments may be useful in predicting dementia. [ABSTRACT FROM AUTHOR]

Aiming at the problems that the edge of melanoma image is fuzzy, the contrast with the background is low, and the hair occlusion makes it difficult to segment accurately, this paper proposes a model MSCNet for melanoma segmentation based on U-net frame. Firstly, a multi-scale pyramid fusion module is designed to reconstruct the skip connection and transmit global information to the decoder. Secondly, the contextural information conduction module is innovatively added to the top of the encoder. The module provides different receptive fields for the segmented target by using the hole convolution with different expansion rates, so as to better fuse multi-scale contextural information. In addition, in order to suppress redundant information in the input image and pay more attention to melanoma feature information, global channel attention mechanism is introduced into the decoder. Finally, In order to solve the problem of lesion class imbalance, this paper uses a combined loss function. The algorithm of this paper is verified on ISIC 2017 and ISIC 2018 public datasets. The experimental results indicate that the proposed algorithm has better accuracy for melanoma segmentation compared with other CNN-based image segmentation algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a signal correlation-based two-sided detection method to detect delamination defects in widely used carbon fiber reinforced plastics with high accuracy and a convenient process. This method can improve the accuracy of ultrasonic testing and distinguish non-defective signals from defective signals, especially those with small amplitude, and to present the depth and size of defects by images. We combined the echo signals from both sides of ultrasonic detection at the same location to extract the weak defect signals and achieved the detection of materials with high ultrasonic attenuation. First, empirical mode decomposition filtering is performed on the ultrasonic raw signal. Then, the defect echoes are identified by smart thresholding and combined with the results of ultrasonic detection on both sides. Next, the defect depth and size are calculated, and the defect image is drawn. Finally, the ultrasonic phased array C-scan obtained by the ultrasonic phased array equipment was compared with the detection results of carbon fiber laminates with artificial delamination by the algorithm of the present invention, showing that the proposed algorithm defect depth calculation error is less than 4 %, the defect size calculation error is less than 0.5 mm, and it performs well in defect shape presentation and position calculation. [ABSTRACT FROM AUTHOR]

A series of large-scale direct shear tests were carried out to study the stress-strain relationship of the interface between the spoil mixture and concrete under different roughness conditions. The results showed that roughness significantly affects the shear strength properties and dilatancy characteristics of the interface. Under different roughness conditions, the shear stress ratio and the normal deformation of the interface tend to be stable after larger shear strain, and the interface presents the characteristics of a critical state. With the increase of shear strain, the void ratio of the interface shows the law of transformation from the initial void ratio to a certain stable void ratio. Based on the void ratio prediction formula of the interface, the relationship between roughness and critical state parameters was established, and the interface state parameters were introduced into the hyperbolic model. Finally, a state-dependent hyperbolic model of the interface considering the roughness was established. Importantly, the model can well reflect the shear stress-strain relationship of the interface under different roughness conditions. [ABSTRACT FROM AUTHOR]

Deep learning has been widely used in remote sensing image classification and achieves many excellent results. These methods are all based on relatively balanced data sets. However, in real-world scenarios, many data sets belong to the long-tailed distribution, resulting in poor performance. In view of the good performance of contrastive learning in long-tailed image classification, a new dualbranch fusion learning classification model is proposed to fuse the discriminative features of remote sensing images with spatial data, making full use of valuable image representation information in imbalance data. This paper also presents a hybrid loss, which solves the problem of poor discrimination of extracted features caused by large intra-class variation and inter-class ambiguity. Extended experiments on three long-tailed remote sensing image classification data sets demonstrate the advantages of the proposed dual-branch model based on contrastive learning in long-tailed image classification. [ABSTRACT FROM AUTHOR]

Research has shown that neoadjuvant immunotherapy may provide more significant clinical benefits to cancer patients undergoing surgery than adjuvant therapy. This study examines the development of neoadjuvant immunotherapy research using bibliometric analysis. As of 12 February 2023, articles on neoadjuvant immunotherapy in the Web of Science Core Collection were collected. Coauthorship and keyword co-occurrence analyses and visualizations were performed using VOSviewer, while CiteSpace was used to identify bursting keywords and references. The study analyzed a total of 1222 neoadjuvant immunotherapy publications. The top contributors to this field were the United States, China, and Italy, and the journal with the most publications was Frontiers in Oncology. Francesco Montorsi had the highest H-index. The most common keywords were 'immunotherapy' and 'neoadjuvant therapy'. The study conducted a bibliometric analysis of over 20 years of neoadjuvant immunotherapy research, identifying the countries, institutions, authors, journals, and publications involved in this field. The findings provide a comprehensive overview of neoadjuvant immunotherapy research. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the relationship between school culture (previous norms, values, and traditions) and the quality of life and the academic enthusiasm of students at Zhejiang College of Security Technology in the city of Wenzhou, China. The number of participants is 363 male students, they were selected using cluster-random sampling. Three standard questionnaires were utilized to collect data. With the use of SPSS software, Pearson's correlation coefficient and regression analysis were utilized to evaluate the data. The results show that the variables of school culture and quality of life at school jointly predicted 23.4% of the variance in academic enthusiasm. Also, the components of "relationship with teachers," "general satisfaction," and "opportunity" from the quality of life in school and the components of "student teacher relationships" and "educational opportunities" from the school culture played the most important role in predicting the academic enthusiasm of students. According to the results, it can be stated that the school's culture and quality of life have a significant impact on the academic enthusiasm of students. [ABSTRACT FROM AUTHOR]

This paper examines two Chinese working-class writers: Wanchun Hu (1929-98) and Lijia Zhang (1964-). With a focus on their working-class identity and its relation to their literary works, I discuss their struggles with what Hans-Georg Moeller and Paul J. D'Ambrosio refer to as different "identity technologies" and related internal and external conflicts. The specific identity technologies in question are those defined by Moeller and D'Ambrosio as rolerelated "sincerity" and individuality-oriented "authenticity." First, I offer a brief history of Chinese working-class literature to illustrate how "literature for the proletariat" was transformed into literature "by the real working class." I then discuss Hu's literary works and unpack his class identity formation under the regime of sincerity. I finish by looking at Zhang's undoing of her working-class background and experience to develop a different selfhood in authenticity. I argue that these two authors are shaped by different identity technologies in contrasting ways, resulting in different Chinese working-class writings. [ABSTRACT FROM AUTHOR]

Chigger mites are the vector of scrub typhus. This study estimates the infestation status and ecological characteristics of chiggers on the chestnut white-bellied rat Niviventer fulvescens in Southwest China between 2001 and 2019. Chiggers were identified under the microscope, and infestation indices were calculated. The Preston’s log-normal model was used to fit the curve of species abundance distribution. A total of 6,557 chiggers were collected in 136 of 342 N. fulvescens rats, showing high overall infestation indices (prevalence=39.8%, mean abundance=19.2, mean intensity=48.2) and high species diversity (S=100, H’=3.0). Leptotrombidium cangjiangense, Neotrombicula japonica, and Ascoschoengastia sifanga were the three dominant chigger species (constituent ratio=42.9%; 2,736/6,384) and exhibited an aggregated distribution among different rat individuals. We identified 100 chigger species, with 3 of them (Leptotrombidium scutellare, Leptotrombidium wenense, and Leptotrombidium deliense) as the main vectors of scrub typhus in China and nine species as potential vectors of this disease. Disease vector occurrence on N. fulvescens may increase the risk of spreading scrub typhus from rats to humans. Chigger infestation on N. fulvescens varied significantly in different environments. The species abundance distribution showed a log-normal distribution pattern. The estimated number of chigger species on N. fulvescens was 126 species. [ABSTRACT FROM AUTHOR]

Background: Patients with resected pancreatic adenocarcinoma (PAAD) often experience short-term relapse and dismal survival, suggesting an urgent need to develop predictive and/or prognostic biomarkers for these populations. Given the potential associations of the human leukocyte antigen class I (HLA-I) genotype with oncogenic mutational profile and immunotherapy efficacy, we aimed to assess whether differential HLA-I genotype could predict the postoperative outcomes in resected PAAD patients. Materials and Methods: HLA-I (A, B, and C) genotyping and somatic variants of 608 Chinese PAAD patients were determined by targeted next-generation sequencing of matched blood cells and tumor tissues. HLA-A/B alleles were classified with the available definition of 12 supertypes. The Kaplan--Meier curves of disease-free survival (DFS) and multivariable Cox proportional-hazards regression analyses were performed to determine the survival difference in 226 selected patients with radical resection. Early-stage (I-II) patients constituted the majority (82%, 185/226) and some stage I-II individuals with high-quality tumor samples were analyzed by RNA-sequencing to examine immunophenotypes. Results: Patients with HLA-A02+B62+B44- had significantly shorter DFS (median, 239 vs. 410 days; hazard ratio = 1.65, P =0.0189) than patients without this genotype. Notably, stage I-II patients carrying HLA-A02+B62+B44- had sharply shorter DFS than those without HLA-A02+B62+B44- (median, 237 vs. 427 days; hazard ratio=1.85, P=0.007). Multivariate analysis revealed that HLA-A02+B62+B44- was associated with significantly inferior DFS (P=0.014) in stage I--II patients but not in stage III patients. Mechanistically, HLA-A02+B62+B44- patients were associated with a high rate of KRAS G12D and TP53 mutations, lower HLA-A expression, and less inflamed T-cell infiltration. Conclusion: The current results suggest that a specific combination of germline HLA-A02/B62/B44 supertype, HLA-A02+B62+B44-, was a potential predictor for DFS in early-stage PAAD patients after surgery. [ABSTRACT FROM AUTHOR]

The use of Bayes factors is becoming increasingly common in psychological sciences. Thus, it is important that researchers understand the logic behind the Bayes factor in order to correctly interpret it, and the strengths of weaknesses of the Bayesian approach. As education for psychological scientists focuses on frequentist statistics, resources are needed for researchers and students who want to learn more about this alternative approach. The aim of the current article is to provide such an overview to a psychological researcher. We cover the general logic behind Bayesian statistics, explain how the Bayes factor is calculated, how to set the priors in popular software packages to reflect the prior beliefs of the researcher, and finally provide a set of recommendations and caveats for interpreting Bayes factors. The current article discusses two statistical approaches that are commonly used in psychological sciences: a Bayesian approach and a frequentist approach. While a frequentist approach is generally taught to aspiring psychology researchers, the Bayesian approach is becoming increasingly popular. Here, we provide an introduction and tutorial on using the Bayesian approach to test hypotheses. We cover the general logic behind Bayesian statistics, explain how the Bayes factor is calculated and the settings in popular software packages, and finally provide a set of recommendations and caveats for interpreting Bayes factors. [ABSTRACT FROM AUTHOR]

This paper considers the jointly active and passive beamforming design in the IRS-aided MISO downlink vehicle communication system where both V2I and V2V communication paradigms coexist. We formulate the problem as an optimization problem aiming to minimize the total transmit power of the base station subject to SINR requirements of both V2I and V2V users, total transmit power of base station and IRS's phase shift constraints. To deal with this non-convex problem, we propose a method which can alternately optimize the active beamforming at the base station and the passive beamforming at the IRS. By using first-order Taylor expansion, matrix analysis theory and penalized convex-concave process method, the non-convex optimization problem with coupled variables is converted into two decoupled convex sub-problems. The simulation results show that the proposed alternate optimization algorithm can significantly decrease the total transmit power of the vehicle base station. [ABSTRACT FROM AUTHOR]

Background: Predicting the postoperative visual outcome of pituitary adenoma patients is important but remains challenging. This study aimed to identify a novel prognostic predictor which can be automatically obtained from routine MRI using a deep learning approach. Materials and methods: A total of 220 pituitary adenoma patients were prospectively enrolled and stratified into the recovery and nonrecovery groups according to the visual outcome at 6 months after endoscopic endonasal transsphenoidal surgery. The optic chiasm was manually segmented on preoperative coronal T2WI, and its morphometric parameters were measured, including suprasellar extension distance, chiasmal thickness, and chiasmal volume. Univariate and multivariate analyses were conducted on clinical and morphometric parameters to identify predictors for visual recovery. Additionally, a deep learning model for automated segmentation and volumetric measurement of optic chiasm was developed with nnU-Net architecture and evaluated in a multicenter data set covering 1026 pituitary adenoma patients from four institutions. Results: Larger preoperative chiasmal volume was significantly associated with better visual outcomes (P=0.001). Multivariate logistic regression suggested it could be taken as the independent predictor for visual recovery (odds ratio= 2.838, P<0.001). The auto-segmentation model represented good performances and generalizability in internal (Dice =0.813) and three independent external test sets (Dice =0.786, 0.818, and 0.808, respectively). Moreover, the model achieved accurate volumetric evaluation of the optic chiasm with an intraclass correlation coefficient of more than 0.83 in both internal and external test sets. Conclusion: The preoperative volume of the optic chiasm could be utilized as the prognostic predictor for visual recovery of pituitary adenoma patients after surgery. Moreover, the proposed deep learning-based model allowed for automated segmentation and volumetric measurement of the optic chiasm on routine MRI. [ABSTRACT FROM AUTHOR]

Tight sandstone gas has become one of the important unconventional resources. In this study, the tight sandstone reservoir of Sulige gas field in Ordos Basin is taken as the research object, and a variety of experimental comprehensive analysis methods are used to reveal the pore size distribution, pore shape and pore type. The pore and throat are distinguished by NMR, and the radius distribution of pore and throat is determined. The pore structure classification model of tight reservoir is used to accurately divide the types of pore structure and evaluate the seepage characteristics of reservoir. The experimental results show that the pores in the study area are mainly secondary dissolved pores, heterobasic pores, intergranular pores and micro-fractures. From the three-dimensional pore network, it is observed that the pore shape is mainly columnar and spherical, and the distribution is uneven, and there are more isolated pores in tight sandstone. NMR T2 spectrum has bimodal characteristics, indicating that pore size is mainly distributed in two ranges. A new pore structure classification parameter PSCI is determined by using the improved K-C equation. Using this classification model, the tight sandstone samples from Sulige gas field are divided into four categories, the pore relation curves are fitted according to the categories, and the porosity-permeability relations of various pore structures are obtained, which is helpful to predict the permeability more accurately through porosity. [ABSTRACT FROM AUTHOR]

Damaged image inpainting is one of the hottest research fields in computer image processing. In view of the problem that existing image inpainting methods lead to an increase in network model parameters and unstable training processes due to the deepening of network layers and the direct connection between layers, as well as the problem that the edge features of damaged areas are discontinuous and the details are blurred in the image inpainting results, a novel generative image inpainting model with dense gated convolutional network(DGCN) by modifying the gated convolutional network structure is proposed in this paper. First, holistically-nested edge detector (HED) is utilized to predict the edge information of the missing areas to assist the subsequent inpainting task to reduce the generation of blur and artifacts. Then, dense connections and indirect connections are added to the generative network to reduce the network parameters while reducing the risk of instability in the training process. Finally, experimental results on the CelebA and Places2 datasets show that the proposed model achieves better inpainting results in terms of PSNR, SSIM and visual effects compared with other classical image inpainting models. [ABSTRACT FROM AUTHOR]

By analyzing 63 English-speaking institutions that offer ALA-accredited master's programs in library and information studies, this research aims to explore the education for knowledge organization (KO) at different levels and across fields. This research examines the KO courses that are the required courses and elective courses in the MLIS programs, that are offered in other master's programs and graduate certificate programs, that are adapted to the undergraduate degree and certificate programs, and that are particularly developed for programs other than MLIS. The findings indicate that the great majority of MLIS programs still have a focus on or a significant component of knowledge organization as their required course and include the knowledge organization elective courses, particularly library cataloging and classification, on their curriculum. However, there is a variety of the offerings of KO related courses across the programs in an institution or in the same program across the institutions. It shows a promising trend that the traditional and new KO courses play an important role in many other programs, at different levels and across fields. With the conventional, adapted, or innovative content, these courses demonstrate that the principles and skills of knowledge organization are applicable to a wide variety of settings, can be integrated with other disciplinary knowledge and emerging technologies, and meet the needs of different career pathways and groups of learners. [ABSTRACT FROM AUTHOR]

This paper describes research on the effect of structural form on hydration-heat-related changes in large-scale precast concrete lining segments. These segments of mass concrete were used in the construction of an underground metro transit station in Changchun, China, a location where conventional cast-in-place construction is interrupted for months by cold winter weather. Heat of hydration analysis of closed-cavity and solid lining segments was conducted using the finite element method (FEM). Two ambient temperatures of 25°C and 10°C (77°F and 50°F) were selected to simulate segment manufacturing conditions in summer and winter, respectively. The FEM and selected parameters were found to be reasonable because the numerical predictions and experimental observations from the closed-cavity segment were consistent. At both of the ambient temperatures, the maximum internal concrete temperature of the closed-cavity segment was much lower than that in the solid one and the temperature distribution in the closed-cavity segment was more uniform. As a result, thermal stress was lower in the closed-cavity segment than in the solid segment, which reduced the risk for cracking. The closed-cavity form of the lining segments enhanced the structural integrity and durability, and the ability to prefabricate these segments in cold ambient temperatures effectively accelerated construction on this project. [ABSTRACT FROM AUTHOR]

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Building a harmonious Teacher-Student Relationship (TSR) is a necessary work for college student management, because different TSRs can result in different effects in student management and cultivation. However, in existing studies, the definitions of harmonious TSR given by different scholars are dimensionless, the understandings of the nature of TSR is not thorough enough, and the analysis of the influencing factors of TSR often lacks the support of theoretical evidences. To overcome these shortcomings, this paper aims to study the construction and adjustment methods for the TSR in college student management based on big data analysis. At first, the paper investigated the daily behavioral features of college students on online management platforms; then, with the help big data analysis and data processing techniques, this paper calculated the fitness degree of harmonious TSR between college students and the counselors and other administrators who engaged in student management works and have interacted with them. After that, based on the calculation results of the said fitness degree, this paper built a basic interactive network for college student management works, and gave the method for dividing student management groups. At last, experimental results verified the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper presents an optimization model to complete the missing data in the energy matchup matrix which compares different players' energy. The optimization model searched for the solutions that can make the eigenvalue of the energy matrix the biggest that should be the principle one. To test the model, we built a Bayesian matrix of energy matchup which mixes the judgments of energy in a matchup between players given by experts and the statistical data gotten from each game in different positions. The proposed method can complete the probabilities given by the Bayesian matrix. Finally, an implementation shows the effectiveness and rationality of the model. [ABSTRACT FROM AUTHOR]

Diabetes departments of hospitals provided more and more professional data from each case for data-driven learning. However, experts in hospitals argue that their experience can provide more reliable information than statistical data. This paper presents a Data-Experience intelligent model to predict the possibilities of diabetes complications with the occurrence of abnormal signs. The model merges data and experience mathematically by mixing human judging behavior from traditional Chinese medicine and statistical patient data from western medicine, which is under a particular situation. The probabilities given by the model can value the distributions of each diabetic complication while estimating the posterior when multi-abnormal signs occurred. An implement in a specific case is analyzed based on the statistical data and human judging performance, which shows the effectiveness and rationality of the Data-Experience Intelligent model for predicting diabetic complications proposed in this paper. The results give a more comprehensive prediction by synthesizing subjective information and objective information. [ABSTRACT FROM AUTHOR]

In order to study the influence of freeze-thaw alternation process on biodegradation of BTEX in seasonal frozen soil area. The author took chernozem polluted by BTEX in Daqing area as the research object, through indoor simulation experiment, controlled - 15 °C ~ 5 °C, - 10 °C ~ 5 °C, - 5 °C ~ 5 °C and 5 °C, simulated freeze-thaw alternation and freezing process, combined with 16SrDNA DGGE technology to study the effect of different freezing factors Biodegradation and transformation of BTEX and change of microbial community structure. The results showed that the community structure of BTEX contaminated soil was affected by temperature, freezing and thawing frequency, freezing time and BTEX concentration. The results show that the change of microbial community structure under 5 °C low temperature is mainly controlled by the concentration of BTEX, and the microbial abundance is high under low concentration; the change of microbial community structure under freeze-thaw condition is affected by the triple effects of freeze-thaw temperature, freeze-thaw frequency and BTEX concentration. With the decrease of freeze-thaw temperature, the increase of freeze-thaw frequency, the increase of BTEX content, the decrease of microbial abundance and the increase of microbial evenness. Biodiversity studies showed that freeze-thaw temperature had the greatest impact on microbial community structure. When the temperature reached - 10 °C, the microbial community would not change. Stenotrophomonas, Arthrobacter sp. and uncultured Ethanoligenens were dominant in the environment containing BTEX under freeze-thaw conditions. [ABSTRACT FROM AUTHOR]

Physical activity is known to confer numerous health benefits. However, few studies have assessed the prolonged impact of participation in different sports on health and fitness. The purpose of this cross-sectional study was to compare the impact of long-term participation (i.e., =9 years) in four different sports, including two traditional Chinese (Tai Chi; diabolo) and two modern sports (aerobics; track and field [TF]) on health and fitness measures among middle-aged and older adults. Participants (n=252, 56.6±8.5y, 66% female) completed the following measures: height, weight, BMI, waist circumference, waist-hip ratio (WHR), body fat%, resting blood pressure (BP) and heart rate, vital capacity, grip strength, reaction time, flexibility, balance. Compared to Tai Chi, aerobics was associated with lower systolic BP and fat%, and greater vital capacity, while TF was associated with lower systolic BP, shorter reaction time, greater vital capacity and better balance (p-values<0.05). Diabolo was associated with lower WHR compared to aerobics and Tai Chi, and greater vital capacity than Tai Chi (p-values<0.05). No significant differences were observed across sports in other measures. Long-term participation in four sports might have different effects on BP, vital capacity, balance, reaction time, body fat, and central adiposity. Individuals who prefer to choose traditional sports (Tai Chi, diabolo) may anticipate similar long-term effects on resting heart rate, BMI, muscle mass, and grip strength compared to those who perform modern sports (aerobics, TF). Information presented in this study may be valuable when designing population, group and individually-tailored PA recommendations in culturally diverse individuals. [ABSTRACT FROM AUTHOR]

Membrane coupling with electrochemical processes has proven to be an effective way for wastewater treatment. However, it still suffering from high energy consumption and low operational stability. Three different forms nanosheet-MoO3 were prepared by hydrothermal synthesis method via adjusting various additives to ammonium heptamolibdate. MoO3 loaded porous Ti membranes was employed as anode to constitute fixed-bed electrocatalytic reactor (FBER) for synthetic dye wastewater treatment to overcome the drawback of three different forms. The electrochemical properties of MoO3/Ti membranes were investigated, results showed that the MoO3/Ti membranes with hexadecyltrimethylammonium bromide (CTAB) additive exhibited the best electrochemical performance. Meanwhile, three MoO3/Ti membranes were used to constitute FBER for 100 mg l−1 MO wastewater treatment, the MO and COD removal rate of MoO3/Ti without additive, MoO3/Ti with CrCl3 additive and MoO3/Ti with CTAB additive were 78.6% and 65.3%, 83.2% and 72.9%, 90.3% and 81.6%, respectively. Furthermore, the energy consumption of MoO3/Ti with CTAB additive was only 0.76 kWh·kg−1·COD. After 3 repeated stabilities experiment of 12 h MO wastewater treatment, the removal rate of MO and COD remained above 97.2% and 88.6%. In sum, the FBER exhibits a great potential in the dye wastewater treatment with high efficiency and excellent stability. [ABSTRACT FROM AUTHOR]

Tumor necrosis factor-α-induced protein-8 like-2 (TIPE2) as a novel negative immune regulator plays an important role in several human diseases. However, its influences in cervical cancer and preeclampsia (PE) remain unclear. This study aims to explore the important role of TIPE2 in cervical cancer and PE via regulating cell invasion. TIPE2 expression in the cervical cancer tissues or the placenta of PE patients was detected. Human cervical cancer cell lines and trophoblasts were transfected with adenovirus expressing human TIPE2 and green fluorescent protein (GFP) (Ad-TIPE2), or the control adenovirus expressing GFP (Ad-GFP). Xenograft models were also constructed on nude mice, aiming to clarify how TIPE2 affects in vivo growth of cervical cancer cells. TIPE2 was down-regulated in the tumor tissues or placenta of patients with cervical cancer or PE. As a result, CaSKi and Hela cells in the Ad-TIPE2 group had decreased migration and invasion, with significant up-regulations of TIPE2 and E-cadherin, but down-regulations of β -catenin and N-cadherin. Ad-TIPE2 decreased the volume and weight of xenograft tumors in the nude mice, with the down-regulation of Ki67. The quantity of cells (HTR8/SVneo and JEG3 cells) transfected with Ad-TIPE2 had increased, with up-regulations of TIPE2, matrix metalloproteinase (MMP)-2 and MMP-9. TIPE2 overexpression could reduce the invasion and migration of cervical cancer cells via inhibiting the epithelial-mesenchymal transition (EMT) process, and promote trophocyte invasion via upregulating the expression of MMPs, and it may be used as a potential therapeutic target for cervical cancer and PE. [ABSTRACT FROM AUTHOR]

In this study, the reservoir characteristics and gas-bearing properties of organic-rich shales in the Wufeng-Longmaxi Formations were systematically studied. The results of petrographic analysis showed that the early Wufeng Formation was dominated by clay and clay-siliceous mixed shale facies, while in the middle and late periods, the siliceous shale facies was mainly developed. It proves that in the early period of the Ordovician-Silurian transition, the tectonic activity in the study area was violent, and the terrestrial source input was large; however, when the Wufeng Formation entered the middle and late depositional periods, the structure tended to be stable, and the bio-siliceous shale was mainly deposited. The lithofacies of the Longmaxi Formation are dominated by siliceous shale deposits, and no clay shale deposits were found. It reflects the stable structure and depositional environment in the early deposition stage of Longmaxi Formation. The TOC content of Wufeng and Longmaxi Formations are generally greater than 2%. Moreover, the type of adsorption and desorption curve of Wufeng-Longmaxi Formation shale is mainly type IV. Organic pores are the main pore types in shale reservoirs in the study area, and TOC content has the most important effect on the gas content of shale reservoirs. [ABSTRACT FROM AUTHOR]

At present, little research focuses on the application of pan-sharpening methods to SuperView-1 satellite imagery. There is a lack of suitability assessment for existing pan-sharpening methods applied to SuperView-1 images. This study proposes an evaluation method that integrates visual evaluation, spectral analysis of typical objects, and quantitative indicators to evaluate the advantages of different pansharpening methods in different scenes of SuperView-1 imagery. Four scenes (urban areas, farmland, sparse vegetation, mixed surfaces) are selected to evaluate eight typical pan-sharpening methods (Brovey, principal component analysis (PCA), Gram-Schmidt (GS), banddependent spatial-detail (BDSD), high-pass filtering (HPF), smoothing filter-based intensity modulation (SFIM), modulation transfer function-generalized Laplacian pyramid (MTF-GLP), MTF-GLP-high pass modulation (MTF-GLP-HPM). The results show that the suitability of each pan-sharpening method is different in various scenes. PCA, Brovey, and GS distort the spectral information greatly, and the stability of the pan-sharpening results in different scenes which are poor. BDSD has strong stability and can better balance the relationship between spectral distortion and spatial distortion in different scenes. The multi-resolution analysis method has better applicability and stability for SuperView-1 imagery, among which MTF-GLP and MTF-GLP-HPM perform better in the pan-sharpening results. This study provides a reference for the selection of pan-sharpening methods for SuperView-1 imagery in different application fields. [ABSTRACT FROM AUTHOR]