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Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.

The fifth generation (5G) cellular communication system is designed to support Time Difference of Arrival (TDOA), Round-Trip Time (RTT), and Direction of Arrival (DOA) measurements for indoor positioning. To mitigate the positioning error caused by non-line-of-sight (NLOS), existing base station selection methods identify channel conditions and only use line-of-sight (LOS) signals for positioning. However, different selected base station combination would lead to a different geometric dilution of precision (GDOP), base station selection based only on channel condition is not fully applicable for the hybrid positioning. This paper derives the GDOP for the hybrid TDOA, RTT, and DOA positioning, and proposes a GDOP-assisted base station selection method, which is based on both channel conditions and GDOP value changes. The simulation shows that using the proposed base station selection method could lead to higher positioning accuracy than base station selection based only on channel condition. In the simulation, in the side region of the scenario, where the change of selected base station combination causes a notable increment in GDOP value, the positioning accuracy improvement caused by the proposed method is greater than that in the center region.

Free amino acid compositions in Wuyi Rock Tea leaves from Yu (authentic rock region), Guiyan (semi-authentic rock region) and Qishan (ordinary region) tea plantations were analyzed. Results showed that contents of 18 free amino acids were 1.6-2.0 times higher in Yu and Guiyan than that in Qishan. The theanine contents reached to 17-20 mg g-1 in Yu and Guiyan, while it was less than 10 mg g-1 in Qishan. Hierarchical cluster analysis and principal component analysis were effective in distinguishing Rock Tea from different regions. The ratios of theanine, sweet and umami amino acids were 8%, 5% and 6% higher, respectively in Yu than that in Qishan. Sensory evaluation score were positively correlated with the ratios of theanine, sweet and umami amino acids (P < 0.05 or P < 0.01). Our results highlight that the favourite characteristic amino acids are dominant contributors to sweet aftertaste of Rock Tea.

A rapid, accurate and simple method was developed for the simultaneous determination of glutathione (GSH) and phytochelatins (PCs) by high-performance liquid chromatography (HPLC) with an evaporative light-scattering detector. GSH, phytochelatin 2 (PC2), PC3, PC4, PC5 and PC6 can be separated with baseline separation within 9 min using a Venusil AA column (250 mm × 4.6 mm i.d., 5 µm particle sizes). Acetonitrile and water containing 0.1% trifluoroacetic acid (0.1%) were employed as the mobile phase for the gradient elution. The drift tube temperature and flow rate of the carrier gas (N2) were 50°C and 1.5 l min−1, respectively. Under optimum conditions, good linear regression equations of six analytes were obtained with the detection limits ranging from 0.2 to 0.5 µg ml−1. The proposed method has been applied successfully for the quantification of GSH and PCs in Perilla frutescens (a cadmium hyperaccumulator) under cadmium stress. The recoveries were between 82.9% and 115.3%.

Falcarindiol (FAD) is a natural polyyne have been found in many food and dietary plants. It has been found to have various beneficial biological activities. In this study, we demonstrated its anticancer function and mechanism in breast cancer cells. We found that FAD preferentially induces cell death in breast cancer cells. FAD-induced cell death is caspase-dependent. However, FAD induces autophagy to contribute to the cell death. Blocking autophagy by either chemical inhibitors or genetic knockout of autophagy signaling component inhibits FAD-induced cell death. We further found that FAD-induced cell death is mediated by the induction of endoplasmic reticulum stress. We also identified that FAD has synergistic effect with approved cancer drugs 5-FU and Bortezomib in killing breast cancer cells. Summarily, these data demonstrate that FAD has strong and specific anticancer effect in breast cancer cells, and provide some insights about the roles of autophagy in FAD-induced cell death.

Cellular communication systems support mobile phones positioning function for Enhanced-911 (E-911) location requirements, but the positioning accuracy is poor. The fifth-generation (5G) cellular communication system can use indoor distribution systems to provide accurate multiple time-difference-of-arrival (TDOA) and single time-of-arrival (TOA) measurements, which could significantly improve the indoor positioning ability. Unlike iterative localization algorithms for TDOA or TOA, the existing closed-form algorithms, such as the Chan-Ho algorithm, do not have convergence problems, but can only estimate position based on one kind of measurement. This paper proposes a closed-form localization algorithm for multiple TDOAs and single TOA measurements. The proposed algorithm estimates the final position result using three-step weighted least squares (WLSs). The first WLS provides an initial position for the last two steps. Then the algorithm uses two WLSs to estimate position based on heteroscedastic TDOA and TOA measurements. In addition, the geometric dilution of precision (GDOP) of the proposed hybrid TDOA and TOA positioning has been derived. The analysis of GDOP shows that the proposed hybrid positioning has lower GDOP than TDOA-only positioning, which means the proposed hybrid positioning has a higher accuracy limitation than TDOA-only positioning. The simulation shows that the proposed localization algorithm could have better performance than closed-form TDOA-only positioning methods, and the positioning accuracy could approximate Cramer-Rao lower bound (CRLB) when the TDOA measurement errors are small.

Marine aquaculture plays an important role in seafood supplement, economic development, and coastal ecosystem service provision. The precise delineation of marine aquaculture areas from high spatial resolution (HSR) imagery is vital for the sustainable development and management of coastal marine resources. However, various sizes and detailed structures of marine objects make it difficult for accurate mapping from HSR images by using conventional methods. Therefore, this study attempts to extract marine aquaculture areas by using an automatic labeling method based on the convolutional neural network (CNN), i.e., an end-to-end hierarchical cascade network (HCNet). Specifically, for marine objects of various sizes, we propose to improve the classification performance by utilizing multi-scale contextual information. Technically, based on the output of a CNN encoder, we employ atrous convolutions to capture multi-scale contextual information and aggregate them in a hierarchical cascade way. Meanwhile, for marine objects with detailed structures, we propose to refine the detailed information gradually by using a series of long-span connections with fine resolution features from the shallow layers. In addition, to decrease the semantic gaps between features in different levels, we propose to refine the feature space (i.e., channel and spatial dimensions) using an attention-based module. Experimental results show that our proposed HCNet can effectively identify and distinguish different kinds of marine aquaculture, with 98% of overall accuracy. It also achieves better classification performance compared with object-based support vector machine and state-of-the-art CNN-based methods, such as FCN-32s, U-Net, and DeeplabV2. Our developed method lays a solid foundation for the intelligent monitoring and management of coastal marine resources.

In this paper, a soft fiber Bragg grating (FBG) strain sensor was constructed of a rubber strip, FBGs and steel plates, which exhibits the advantages of high precision and a small size. A series of FBGs was uniformly pasted on a flexible rubber strip which can monitor the slope deformation by measuring the bending deformation of the rubber strip. Most notably, this sensor can be used to monitor horizontal displacement in the subsurface of the slope model. The relationships among the bending angle of the rubber strip, the strain of the rubber strip, and the subsurface deformation of the slope model were established. In addition, the subsurface deformation of the slope model can be obtained by the FBG strain sensor monitoring. Since a rigid-flexible structure was formed by uniformly pasting a series of steel plates on the other side of the rubber strip, the sensitivity of the FBG strain sensor was improved to be 1.5425 nm/°. The measurement results verify that the FBG strain sensor shows good performance, and the model test results demonstrate that the FBG strain sensor can be used for monitoring the subsurface deformation of the slope model.

Survey data describing land cover information such as type and diversity over several decades are scarce. Therefore, our capacity to reconstruct historical land cover using field data and archived remotely sensed data over large areas and long periods of time is somewhat limited. This study explores the relationship between CORONA texture—a surrogate for actual land cover type and complexity—with spectral vegetation indices and texture variables derived from Landsat MSS under the Spectral Variation Hypothesis (SVH) such as to reconstruct historical continuous land cover type and complexity. Image texture of CORONA was calculated using a mean occurrence measure while image textures of Landsat MSS were calculated by occurrence and co-occurrence measures. The relationship between these variables was evaluated using correlation and regression techniques. The reconstruction procedure was undertaken through regression kriging. The results showed that, as expected, texture based on the visible bands and corresponding indices indicated larger correlation with CORONA texture, a surrogate of land cover (correlation >0.65). In terms of prediction, the combination of the first-order mean of band green, second-order measure of tasseled cap brightness, second-order mean of Normalized Visible Index (NVI) and second-order entropy of NIR yielded the best model with respect to Akaike’s Information Criterion (AIC), r-square, and variance inflation factors (VIF). The regression model was then used in regression kriging to map historical continuous land cover. The resultant maps indicated the type and degree of complexity in land cover. Moreover, the proposed methodology minimized the impacts of topographic shadow in the region. The performance of this approach was compared with two conventional classification methods: hard classifiers and continuous classifiers. In contrast to conventional techniques, the technique could clearly quantify land cover complexity and type. Future applications of CORONA datasets such as this one could include: improved quality of CORONA imagery, studies of the CORONA texture measures for extracting ecological parameters (e.g., species distributions), change detection and super resolution mapping using CORONA and Landsat MSS.

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

A metal-free visible-light photoredox-catalyzed intermolecular cyclization reaction of O-2,4-dinitrophenyl oximes to phenanthridines was developed. In this study, the organic dye eosin Y and i-Pr2NEt were used as photocatalyst and terminal reductant, respectively. The oxime substrates were transformed into iminyl radical intermediates by single-electron reduction, which then underwent intermolecular homolytic aromatic substitution (HAS) reactions to give phenanthridine derivatives.

OBJECTIVE: Legumain, a novel asparaginyl endopeptidase, has been observed to be highly expressed in several types of tumors, which may play a vital role in carcinogenesis. However, there is no study investigating the relationship among Legumain expression, clinicopathologic, biological variables and patient prognosis in gastric carcinoma. METHODS: In this study, a tissue microarray (TMA) containing 282 samples of primary gastric cancer was assessed for Legumain expression by immunohistochemistry. The TMA included 98 lymph node metastasis samples. The protein expression levels of Legumain were evaluated by Western blot analysis. RESULTS: Cytoplasmic immunoreactivity of Legumain was over-expressed in gastric cancer compared with paired normal gastric mucosa. Increased Legumain levels were significantly correlated with clinical stage, presence of distant metastasis. Legumain was significantly over-expressed in primary gastric cancer with metastasis than without metastasis. Patients with Legumain-positive localized tumors had lower 5-year overall survival (OS) than those with Legumain-negative tumors. Multivariate survival analysis showed that Legumain was an independent prognostic marker for OS (HR 1.459, 95% CI 1.251-1.703, P = 0.007). CONCLUSIONS: Legumain expression could serve as a prognostic biomarker in patients at risk of developing metastasis or recurrence with gastric carcinoma.

Detailed and precise information of land-use and land-cover (LULC) in rural area is essential for land-use planning, environment and energy management. The confusion in mapping residential and industrial areas brings problems in energy management, environmental management and sustainable land use development. However, they remain ambiguous in the former rural LULC mapping, and this insufficient supervision leads to inefficient land exploitation and a great waste of land resources. Hence, the extent and area of residential and industrial cover need to be revealed urgently. However, spectral and textural information is not sufficient for classification heterogeneity due to the similarity between different LULC types. Meanwhile, the contextual information about the relationship between a LULC feature and its surroundings still has potential in classification application. This paper attempts to discriminate settlement and industry area using landscape metrics. A feasible classification scheme integrating landscape metrics, chessboard segmentation and object-based image analysis (OBIA) is proposed. First LULC map is generated from GeoEye-1 image, which delineated distribution of different land-cover materials using traditional OBIA method with spectrum and texture information. Then, a chessboard segmentation of the whole LULC map is conducted to create landscape units in a uniform spatial area. Landscape characteristics in each square of chessboard are adopted in the classification algorithm subsequently. To analyze landscape unit scale effect, a variety of chessboard scales are tested, with overall accuracy ranging from 75% to 88%, and Kappa coefficient from 0.51 to 0.76. Optimal chessboard scale is obtained through accuracy assessment comparison. This classification scheme is then compared to two other approaches: a top-down hierarchical classification network using only spectral, textural and shape properties, and lacunarity based hierarchical classification. The distinction approach proposed is overwhelming by achieving the highest value in overall accuracy, Kappa coefficient and McNemar test. The results show that landscape properties from chessboard segment squares could provide valuable information in classification.

Background: Familial 46, XY Disorder of Sexual Development (DSD) was discovered in a Ph+, BCR::ABL1P210+ Acute Lymphoblastic Leukemia (ALL) female with RCBTB2::LPAR6 fusion gene. Siblings developing 46, XY DSD are extremely rare. Patients with 46, XY DSD have much higher rates of gonadal cancers. Nevertheless, the incidence of hematologic malignancies in patients with DSDs has received little attention. RCBTB2::LPAR6 is a rarely reported fusion gene in ALL. Case presentation: Herein, we report a rare case of a newly diagnosed Ph+, BCR::ABL1P210+ ALL patient who was 77 years old and female by social sex. Whole Exome Sequencing (WES) and RNA sequencing revealed TET2 and NF1 mutations in addition to a rarely reported RCBTB2::LPAR6 fusion gene and 17 other genes with uncertain clinical significance. The patient was surprisingly found to have a male karyotype. On ultrasound, neither the uterus nor the ovaries were discernible. A detailed family and marital history revealed that the patient had undergone surgery at an early age for an unexplained inguinal mass. She had slow pubertal development, scanty menstruation, and few overtly feminine characteristics. She had three marriages, but none succeeded in getting pregnant. The patient had never sought therapy for infertility due to the inaccessibility of medical treatment and a lack of medical knowledge. Her sister, 73 years old and female by social sex, who had amenorrhea in adolescence and was unable to conceive, had the same experience. To our surprise, she also had a male karyotype. Conclusions: Due to the absence of long-term social attention and follow-up, studies on the incidence of hematologic malignancies in patients with 46, XY DSD are incredibly uncommon. Siblings developing 46, XY DSD is extremely rare. We report the oldest patient diagnosed with 46, XY DSD. There have not yet been any reports of familial 46, XY DSD with a concurrent diagnosis of Ph+BCR:: ABL1P210+ALL with a rarely reported RCBTB2::LPAR6 fusion gene. [ABSTRACT FROM AUTHOR]

Background: N-lactoylphenylalanine (Lac-Phe) is a new form of "exerkines" closely related to lactate (La), which may be able to inhibit appetite. Blood flow restriction (BFR) can lead to local tissue hypoxia and increase lactate accumulation. Therefore, this study investigated the effects of combining Moderate-intensity Continuous Exercise (MICE) with BFR on Lac-Phe and appetite regulation in obese adults. Methods: This study employed the cross-design study and recruited 14 obese adults aged 18-24 years. The participants were randomly divided into three groups and performed several tests with specific experimental conditions: (1) M group (MICE without BFR, 60%VO2max, 200 kJ); (2) B group (MICE with BFR, 60% VO2max, 200 kJ); and (3) C group (control session without exercise). Participants were given a standardized meal 60 min before exercise and a ad libitum 60 min after exercise. In addition, blood and Visual Analogue Scale (VAS) were collected before, immediately after, and 1 hour after performing the exercise. Results: No significant difference in each index was detected before exercise. After exercise, the primary differential metabolites detected in the M and B groups were xanthine, La, succinate, Lac-Phe, citrate, urocanic acid, and myristic acid. Apart from that, the major enrichment pathways include the citrate cycle, alanine, aspartate, and glutamate metabolism. The enhanced Lac-Phe and La level in the B group was higher than M and C groups. Hunger of the B group immediately after exercise substantially differed from M group. The total ghrelin, glucagon-like peptide-1 and hunger in the B group 1 hour after exercise differed substantially from M group. The results of calorie intake showed no significant difference among the indexes in each group. Conclusions: In conclusion, this cross-design study demonstrated that the combined MICE and BFR exercise reduced the appetite of obese adults by promoting the secretion of Lac-Phe and ghrelin. However, the exercise did not considerably affect the subsequent ad libitum intake. [ABSTRACT FROM AUTHOR]

Background and aims: Gender nonconformity (GNC), which refers to an individual's expression of gender that does not align with the socially prescribed norms for their biological sex, may be associated with adverse behavioral problems, such as problematic smartphone use (PSU) and problematic internet use (PIU). This study examined the associations between GNC and PSU and GNC and PIU among Chinese adolescents. Methods: This cross-sectional study utilized data from the 2021 School-based Chinese Adolescents Health Survey, recruiting 23,054 eligible adolescents aged 11 to 21, with an average age of 14.9 (SD: 1.7) years from 504 classes in 84 public high schools across 7 cities in China. Gender nonconformity, PSU/PIU, and demographics were measured. Mixed-effect linear regression models were performed. Results: Among the participants (51.0% male), 5.3% reported high GNC and 26.9% reported moderate GNC. After adjusting for covariates, high GNC was significantly and positively associated with PSU (B 5 1.11, 95% CI 5 0.49-1.72) and PIU severity (B 5 2.16, 95% CI 5 1.40-2.93). Stratified analyses indicated that the associations between GNC and PSU differed between males and females, with a significant association observed only among male students (B 5 1.91, 95% CI 5 0.97-2.86). Discussion and conclusions: GNC is positively associated with the severity of PSU and PIU among Chinese adolescents, with male gender-nonconforming adolescents being more vulnerable to PSU. These results highlight the importance of implementing education on gender expression diversity in schools to create an inclusive school environment, which may potentially help prevent PSU and PIU among gender-nonconforming adolescents. [ABSTRACT FROM AUTHOR]