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Understanding the spatial distribution of soil texture is essential for healthy plant growth, soil fertility optimization, and sustainable soil management practices. In this study, the spatial distribution of clay, silt, and sand content at a 30-meter resolution in Anhui Province, China, were predicted at various depths (0–5, 5–15, 15–30, 30–60, 60–100, and 100–200 cm). A total of 413 soil profiles were used to estimate soil texture. Additionally, a dataset of environmental parameters was employed for modeling. The Random Forest (RF) model was utilized for three-dimensional soil texture prediction. Uncertainty was assessed by utilizing the lower (5%) and upper (95%) limits of the prediction interval. The results showed that using the RF method could produce highly accurate and detailed predicted soil texture maps for Anhui Province, displaying the three-dimensional spatial variations of soil texture. Additionally, the prediction interval coverage probability (PICP) index results, derived from uncertainty maps, indicated the high prediction accuracy of the methods utilized in this study. The findings also revealed that the main controlling factors of the soil texture pattern in Anhui Province are standh, tempSeason, NDVI, and slope. Elevation significantly affects soil texture by influencing temperature. Slope plays an important role by regulating erosion processes, while vegetation cover is key in controlling erosion and sedimentation. Overall, this study highlights that advanced methods for estimating soil properties represent a significant advancement in soil modeling, leading toward more effective soil resource management. [ABSTRACT FROM AUTHOR]

The accumulation of autotoxic substances and fungal pathogens in soil are the two leading causes of continuous cropping obstacles. In this context, the use of beneficial strains for the biological control of continuous cropping obstacles is a promising research direction. In this work, the functions of Pseudomonas chlororaphis ZH2 in antagonizing pathogenic fungi and degrading autotoxic substances during continuous cropping were studied via genome-wide sequence analysis, antifungal activity in vitro, and autotoxic substances degrading tests. The results revealed that the genome of ZH2 contains 7,249,755 base pairs, has a GC content of 62.61%, and is predicted to contain 6551 genes. The phylogenetic results of 16S rRNA, atpD, recA, and carA gene analysis and the average nucleotide identity analysis revealed that ZH2 belongs to P. chlororaphis subsp. aurantiaca. KEGG analysis revealed that some genes of ZH2 were annotated to the biodegradation pathway of benzoate, p-hydroxybenzoic acid, and other autotoxic substances. Nineteen types of secondary metabolite biosynthesis-related gene clusters were predicted to exist in ZH2 via antiSMASH software, and it is predicted that ZH2 can produce a variety of secondary metabolites with antifungal and siderophore functions. The autotoxic substance degradation tests confirmed that ZH2 can degrade benzoate, p-hydroxybenzoic acid, vanillin, and vanillic acid, and the antagonism tests confirmed that ZH2 can inhibit the growth of pathogenic fungi such as Fusarium solani, Rhizopus oryzea, Pestalotiopsis mangiferae, Fusarium oxysporum f.sp. cucumerinum and Botryosphaeria dothidea. These results show that ZH2 degrades autotoxic substances and antagonizes pathogens. Therefore, it is a promising strain that can be used for the biological control of continuous cropping obstacles. [ABSTRACT FROM AUTHOR]

Purpose: The rarity of breast mucinous carcinoma (BMC) makes it challenging to study the prognosis of this disease across diverse racial populations. This study aimed to leverage epidemiological data on immigrant populations to elucidate the prognostic differences in BMC patients from various racial/ethnic backgrounds. The goal was to help formulate more personalized clinical practice guidelines for the management of this rare malignancy. Methods: The study included 208 BMC patients from China and 10,322 BMC patients from the SEER database. Clinicopathological data, treatment information, and survival outcomes were compared across different racial/ethnic groups using statistical analyses. Results: Asian American BMC patients were younger at diagnosis and had more favorable tumor grade and stage compared to other racial groups. After adjusting for clinicopathological factors and treatments, Asian American BMC patients exhibited significantly better overall survival (OS) than black (HR = 1.53, 95% CI: 1.05–2.22, P = 0.027) and white patients (HR = 1.41, 95% CI: 1.03–1.94, P < 0.001). Specifically, non-Chinese American patients had a worse OS compared to Chinese patients (adjusted HR = 2.59, 95% CI: 1.15–5.83, P = 0.022). Chemotherapy significantly improved OS only in black BMC patients (adjusted HR = 0.52, 95% CI: 0.27–0.98, p = 0.045), but not in other racial/ethnic groups. Conclusion: Race is an independent prognostic factor for BMC. Compared with Chinese patients, black and white American patients have a worse prognosis in terms of OS. Treatment guidelines for BMC patients should be formulated with considerations of race factors. For patients with BMC originating from China, a more conservative treatment approach may be warranted. [ABSTRACT FROM AUTHOR]

The United Nations sustainable development agenda emphasizes the importance of forests. China's forests cover 5% of the world's forest area, significantly influencing global climate and ecology. In recent decades, China's forests have undergone notable changes. Accurate forest cover maps are crucial for understanding forest distribution, conducting ecological research and sustainable management. However, there is a lack of forest cover maps satisfying the criteria. To this issue, this study focuses on developing a precise 16-m resolution forest cover map of China. For this purpose, we propose a forest classification framework based on weakly supervised deep learning and prior knowledge from open datasets. Utilizing this framework and GF-1 WFV satellite images, we generated China's forest cover map in 2020 named FCM16. The FCM16 is evaluated using 136,385 sample points, achieving an overall accuracy of 94.64 ± 0.12%, producer's accuracy of 91.12 ± 0.27% and user's accuracy of 87.31 ± 0.34%. Additionally, FCM16 was compared with existing forest-related datasets, demonstrating its reliability. In general, FCM16 effectively represents China's forest cover in 2020, providing a valuable resource for social and ecological analysis. [ABSTRACT FROM AUTHOR]

Background: Targeted therapy for intrahepatic cholangiocarcinoma (ICC) shows superior survival outcomes but patients with certain targetable alterations are no more than 20%. Genetic alteration screening for all ICC patients is of high cost and not routinely performed. This study intends to develop a histopathology-based artificial intelligence (AI)-assisted system for predicting genetic alteration of ICC. Methods: We constructed a Genetic Alteration Prediction (GAP) system based on multi-instance learning and self-supervised learning to predict genetic alterations using whole-slide images (WSIs) of H&E-stained slides. A total of 2069 WSIs from 232 ICC patients underwent surgery of the FAH-SYSU dataset were used for model construction and adjustment by five-fold cross-validation. Another 150 patients from three medical centres were used as independent external validations. We also compared the cost-effectiveness of GAP-assisted precise treatment and all-sequencing strategy to non-sequencing strategy. Results: The GAP was able to predict actionable genetic alterations of ICC, including FGFR2 and IDH. The area under the receiver operating characteristic curves (AUC) for FGFR2 and IDH were 0.754 and 0.713 in the internal dataset, and 0.724 and 0.656 in the external dataset, respectively. Furthermore, compared to giving chemotherapy without sequencing for every patient, GAP-assisted precise treatment could increase 1 progression-free quality-adjusted life month with a cost of $13871.72, the co-responding figure for all-sequencing strategy is $44538.93. Decision curve analysis showed that AI-assisted strategy provides better clinical benefits. Conclusions: We constructed an AI-assisted genetic alteration screening system which is predictable to ICC actionable targets and has potential to assist precise targeted treatment of advanced ICC. [ABSTRACT FROM AUTHOR]

Background: Interpretation bias (IB), pre- and post-event rumination are related to adolescent social anxiety (SA). However, although postulated theoretically, the mediating role of pre- and post-event rumination between IB and SA has not been examined in adolescents. In addition, post-event rumination was found to differ in varying social situations (e.g., speech vs. interaction). Therefore, by establishing social tasks, the current research investigated whether: (i) pre- and post-event rumination mediated the association between IB and SA among adolescents, and (ii) this mediation was moderated by situational type. Methods: In Study 1, 31 socially anxious adolescents and 37 controls were recruited and then primed with a speech task. In Study 2, 61 socially anxious adolescents were randomly assigned to a speech (n = 31) or interaction (n = 30) task. In both studies, baseline IB and SA, state pre-event rumination before starting the social task, post-event rumination and SA after social task were measured. Results: IB affected adolescents' SA via pre- and post-event rumination; however, the mediation effect was found only in the speech task. Conclusions: Findings provide potential approaches for reducing adolescent SA by targeting IB and rumination and showed the situational adaptability of the cognitive model of social anxiety disorder among adolescents. [ABSTRACT FROM AUTHOR]

There is limited research on the variations in brine element changes and the factors that influence them during large-scale exploitation. The Xitaijnar Salt Lake in the Qaidam Basin is a large brine lithium deposit. In this study, we investigated the variations in chemical composition and the factors that influence intercrystalline brine at different time periods. Hydrochemistry, mineralogy, and hydrogeochemical simulation methods were employed to understand the brine evolution. Our results indicate that after nearly 20 years of exploitation, the intercrystalline brine still belongs to the magnesium sulfate subtype, with only slight variations in salinity. The concentrations of Na, K, and SO4 showed a slight increase, while the content of Mg and Cl decreased slightly. The concentrations of B and Li exhibited minor fluctuations. The provenance, water level, and hydraulic connection had minimal influence on the chemical composition of the intercrystalline brine. By contrast, the dynamic dissolution and precipitation of sulfate minerals and halite, as well as drastic changes in hydrological conditions (such as floods), were identified as the main factors affecting the chemical composition of brine. With the large-scale extraction of intercrystalline brine, the content of elements in the salt lake showed a decreasing trend. This can be attributed to the fact that intercrystalline brine is formed through long-term evaporation and concentration. Therefore, during the exploitation process, it is crucial to monitor the hydrochemical variations of intercrystalline brine and understand the controlling factors. The results of this study may prove useful for the sustainable development and utilization of salt lake resources worldwide. [ABSTRACT FROM AUTHOR]

Accurate, fast and lightweight dense target detection methods are highly important for precision agriculture. To detect dense apricot flowers using drones, we propose an improved dense target detection method based on YOLOv8, named D-YOLOv8. First, we introduce the Dense Feature Pyramid Networks (D-FPN) to enhance the model's ability to extract dense features and Dense Attention Layer (DAL) to focus on dense target areas, which enhances the feature extraction ability of dense areas, suppresses features in irrelevant areas, and improves dense target detection accuracy. Finally, RAW data are used to enhance the dataset, which introduces additional original data into RAW images, further enriching the feature input of dense objects. We perform validation on the CARPK challenge dataset and constructed a dataset. The experimental results show that our proposed D-YOLOv8m achieved 98.37% AP, while the model parameters were only 13.2 million. The improved network can effectively support any task of dense target detection. [ABSTRACT FROM AUTHOR]

Groundwater modeling is essential for effective water resource management. However, the heterogeneous distribution of hydrogeological parameters, such as hydraulic conductivity (K), significantly impacts the accuracy and efficiency of simulations. This study investigates the accuracy and computational efficiency of K parameter inversion across varying dimensions. Heterogeneous logarithmic random K (lnK) fields were generated using the Karhunen-Loève Expansion. Three inversion algorithms—Genetic Algorithm, Markov Chain Monte Carlo, and Ensemble Smoother (ES)—were evaluated in conjunction with a Kriging surrogate model. These algorithms were used to invert parameters using different numbers of Inversion Target Features (ITFs) as prediction targets. Results indicate that ES consistently outperformed GA and MCMC in terms of inversion accuracy and computational efficiency across all ITF scenarios (7, 12, 34, 48, and 71 ITFs). Sensitivity analysis revealed that selecting parameters with higher total-order indices for inversion is crucial, as a small subset of ITFs often accounts for a majority of the sensitivity. While increasing the number of ITFs captures greater spatial variability in lnK, high-dimensional cases can lead to less responsive output heads. Furthermore, inadequate grid density may not adequately represent fine-scale lnK distributions. This study provides valuable insights into parameter inversion within heterogeneous groundwater models, furthering our understanding of these complex systems. [ABSTRACT FROM AUTHOR]

Leaf scald, caused by Xanthomonas albilineans, is a severe disease affecting sugarcane worldwide. One of the most practical ways to control it is by developing resistant sugarcane cultivars. It is essential to identify genes associated with the response to leaf scald. A panel of 170 sugarcane genotypes was evaluated for resistance to leaf scald in field conditions for 2 years, followed by a 1-year greenhouse experiment. The phenotypic evaluation data showed a wide continuous distribution, with heritability values ranging from 0.58 to 0.84. Thirteen single nucleotide polymorphisms (SNPs) were identified, significantly associated with leaf scald resistance. Among these, eight were stable across multiple environments and association models. The candidate genes identified and validated based on RNA-seq and qRT-PCR included two genes that encode NB-ARC leucine-rich repeat (LRR)-containing domain disease-resistance protein. These findings provide a basis for developing marker-assisted selection strategies in sugarcane breeding programs. [ABSTRACT FROM AUTHOR]

Vascular lesions frequently arise as complication in patients diagnosed with diabetes mellitus (DM). Presently, percutaneous coronary intervention (PCI) and antithrombotic therapy serve as primary treatments. However, in-stent restenosis persists as a challenging clinical issue following PCI, lacking sustained and effective treatment. Linarin (LN) exhibits diverse pharmacological activities and is regarded as a potential drug for treating various diseases, including DM. But its specific role in restenosis after vascular injury in DM patients remains unclear. A rat model of diabetes-related restenosis was established to evaluate the role of LN on neointimal hyperplasia. Vascular smooth muscle cells (VSMCs) stimulated by high glucose (HG, 30 mM) underwent LN treatment. Additionally, an overexpression plasmid of A disintegrin and metalloproteinases (ADAM10) was constructed to transfect VSMCs. We employed CCK-8, Brdu, wound-healing scratch, and transwell migration assays to evaluate the proliferation and migration of VSMCs. Furthermore, western blot and immunofluorescence assays were utilized to investigate the expressions of ADAM10 and the downstream Notch signaling pathway in vivo and in vitro models. LN notably alleviated intimal hyperplasia after vascular injury in DM rats and reduced the protein expression of ADAM10, alongside its downstream Notch1 signaling pathway-related proteins (Notch1, NICD and Hes1) in rat carotid artery tissues. LN effectively suppressed the proliferation and migration of VSMCs induced by HG, downregulating the protein expression of ADAM10, Notch1, NICD and Hes1. Moreover, our findings indicated that ADAM10 overexpression significantly reversed LN's effects on proliferation, migration, and the expression of Notch1 signaling pathway-related proteins in HG-treated VSMCs. LN demonstrates potential therapeutic efficacy in addressing restenosis after diabetic-related vascular injury, with the ADAM10 mediated Notch signaling pathway playing a pivotal role. [ABSTRACT FROM AUTHOR]

Compacted graphite iron (CGI) is increasingly used in industrial production due to its excellent mechanical property, especially in the field of high-performance automotive engine manufacturing, and has become a substitute for gray cast iron (GCI). However, the hard-to-machine problem caused by its excellent physical properties was the main issue affecting the surface quality of the CGI workpiece. As a new type of tool, the wiper insert could effectively improve the surface quality. In order to develop a long lifespan and high-stability wiper insert tool for CGI milling, this study conducted a series of experiments, including tool design and simulation, coating preparation and testing, and tool cutting performance testing. In the optimization of simulation analysis of tool geometric parameters, it was found that the numerical value of curved cutting-edge radius had a more significant impact on the cutting performance of wiper insert. In the coating test, AlCrN-coated wiper insert C with a coating thickness of 2.84 µm had the best load bearing and fracture toughness performance in the coating mechanic test and had the best coating bonding performance in the scratch test. In the milling experiment with a cutting speed of 125.7 mm/min, a feed rate of 0.15 mm/r, and a cutting depth of 0.5 mm, the coated wiper insert C had the longest tool life and the best machined surface quality of the workpiece. Compared to other coated tools, the tool life was extended by at least 15.7%, and the effective cutting area was increased by 20%, which means it was the most suitable tool for machining CGI. [ABSTRACT FROM AUTHOR]

There has been a long-standing debate as to how many hydrogen bonds a peptide backbone amide can form in aqueous solution. Hydrogen-bonding structural dynamics of N-ethylpropionamide (a β-peptide model) in water was examined using infrared (IR) spectroscopy. Two amide-I sub bands arise mainly from amide C=O group that forms strong H-bonds with solvent water molecules (SHB state), and minorly from that involving one weak H-bond with water (WHB state). This picture is supported by molecular dynamics simulations and ab-initio calculations. Further, thermodynamics and kinetics of the SHB and WHB species were examined mainly by chemical-exchange two-dimensional IR spectroscopy, yielding an activation energy for the SHB-to-WHB exchange of 13.25 ± 0.52 kJ mol‒1, which occurs in half picosecond at room temperature. Our results provided experimental evidence of an unstable water molecule near peptide backbone, allowing us to gain more insights into the dynamics of the protein backbone hydration. Water at the surface of proteins is known to be critically important in maintaining their conformation and function, but the dynamics of the backbone hydration of peptides remains somewhat elusive. Here, the authors study the hydrogen-bonding structural dynamics of N-ethylpropionamide, a β-peptide model, in heavy water using nonlinear infrared spectroscopy and MD simulations. [ABSTRACT FROM AUTHOR]

Li-ion batteries (LIBs) for electric vehicles and aviation demand high energy density, fast charging and a wide operating temperature range, which are virtually impossible because they require electrolytes to simultaneously have high ionic conductivity, low solvation energy and low melting point and form an anion-derived inorganic interphase1–5. Here we report guidelines for designing such electrolytes by using small-sized solvents with low solvation energy. The tiny solvent in the secondary solvation sheath pulls out the Li+ in the primary solvation sheath to form a fast ion-conduction ligand channel to enhance Li+ transport, while the small-sized solvent with low solvation energy also allows the anion to enter the first Li+ solvation shell to form an inorganic-rich interphase. The electrolyte-design concept is demonstrated by using fluoroacetonitrile (FAN) solvent. The electrolyte of 1.3 M lithium bis(fluorosulfonyl)imide (LiFSI) in FAN exhibits ultrahigh ionic conductivity of 40.3 mS cm−1 at 25 °C and 11.9 mS cm−1 even at −70 °C, thus enabling 4.5-V graphite||LiNi0.8Mn0.1Co0.1O2 pouch cells (1.2 Ah, 2.85 mAh cm−2) to achieve high reversibility (0.62 Ah) when the cells are charged and discharged even at −65 °C. The electrolyte with small-sized solvents enables LIBs to simultaneously achieve high energy density, fast charging and a wide operating temperature range, which is unattainable for the current electrolyte design but is highly desired for extreme LIBs. This mechanism is generalizable and can be expanded to other metal-ion battery electrolytes.An electrolyte design using small-sized fluoroacetonitrile solvents to form a ligand channel produces lithium-ion batteries simultaneously achieving high energy density, fast charging and wide operating temperature range, desirable features for batteries working in extreme conditions. [ABSTRACT FROM AUTHOR]

Scheelite, one kind of common REE-rich and U-bearing hydrothermal mineral, is extensively developed in various types of gold deposits, which can be used to record nature and timing of metallogenesis. The Zhaishang Carlin-like gold deposit in the Qinling Orogen is a giant Au deposit, hosting 127t of Au @ 2.67 g/t with economic concentrations of tungsten and antimony. The study reports two types of scheelite based on the characteristics of petrography and geochemistry. Sch A shows significant oscillatory zoning with dark gray cathodoluminescence (CL) response, whereas Sch B displays patchy textures with brighter CL response. Systematic LA-ICP-MS U–Pb dating of Sch A and Sch B yields ages of 227.1 ± 3.2 Ma and 226.2 ± 6.9 Ma, respectively. The new dates, constraining the Zhaishang Au–W mineralization to ~ 227Ma, coincide well with the western Qinling magmatism, metallogenic and tectonic events. There are significant variations in concentration, the Sch A has low REE content (mean = 41.3 ppm), negative Eu-anomaly with slightly positive Ce-anomaly, whereas Sch B, with small negative or positive Eu-anomaly, has higher REE content (mean = 247 ppm) and higher positive Ce-anomaly. The positive correlation of EuN and EuN* records oxidizing condition during the whole W mineralization event. Additionally, Sch B intergrown with selenides with an increase in the Ce-anomaly supports that the latter has higher oxygen fugacity environment. The Sr isotope signature for scheelite supports that ore-forming metals mostly inherited the host rock component, while the proportion of magma-derived Sr increased in the Sch B. Fluid–rock interactions co-precipitated Au and W caused by the release of Fe and Ca cations and the increase of pH. The study highlights that scheelite as a recorder can help in deciphering the nature and timing of metallogenesis of the studied Au–Sb–W deposit, and thus other similar Au–W deposits. [ABSTRACT FROM AUTHOR]

Predicting groundwater potential is crucial for identifying the spatial distribution of groundwater in a region. It serves as an essential guide for the development, utilization, and protection of groundwater resources. Previous studies have primarily emphasized finding the most accurate prediction model for groundwater potential while giving less attention to the selection of training features and sample sizes. This study aims to predict groundwater potential within Qinghai Province using automated machine learning technology and assess the influence of sample sizes and feature selection on prediction accuracy. Sixteen groundwater conditioning factors were categorized into categorical and numerical variables. Four feature selection modes were utilized as input in training the model. The results indicated that, except for correlations between evaporation and landforms (− 0.8) and precipitation and normalized difference vegetation index (0.8), the Pearson correlation coefficients among the remaining sixteen factors were ≤ 0.5 or ≥ − 0.5. The models XGB-ALL, RF-Entropy, ET-CRITIC, and XGB-PCA yielded accuracy scores of 0.783, 0.685, 0.745, and 0.703, and area under curve (AUC) of 0.819, 0.724, 0.779, and 0.747, respectively. If enough samples are available with the tree model, an increased number of features can improve prediction accuracy. The principal component analysis method showed difficulty in reducing the dimensionality of the input space, while the Entropy method proved efficient. The accuracy and AUC value of the prediction model improved with an increasing number of samples. Training with 8 features and 200 data points achieved an accuracy of 0.745, sufficient to evaluate regional groundwater potential. As for training with 600 samples, the model's performance accuracy rose to 0.9, enabling precise groundwater potential prediction. The outputs of this research can provide decision-makers in groundwater resource management in Qinghai Province with crucial theoretical and practical support. The lessons learned can have future applications in similar situations. [ABSTRACT FROM AUTHOR]

This study examined the relationship between perfectionism and eating pathology, and investigated the mediating role of body dissatisfaction and alexithymia in the relationship. Two studies were employed in the current research. A large sample (N = 2420) with cross-sectional data was used to determine the relationship between perfectionism and eating pathology, whereas three-wave longitudinal data (N = 312) with three-month intervals were used to examine the mediation models. The results indicated that: (1) Perfectionism was significantly associated with eating pathology, after controlling for relevant demographic factors. (2) Both body dissatisfaction and alexithymia fully mediated the relationship between perfectionism and eating pathology in the single mediation models. (3) Body dissatisfaction emerged as the stronger mediator in the relationship in the parallel mediation model. The results indicated that among Chinese college students, perfectionism had an indirect effect on eating pathology, through body dissatisfaction and alexithymia, and body dissatisfaction was shown to be a stronger pathway. The current findings highlighted the need to focus on college students with higher levels of perfectionism and mitigate the risk of eating pathology by improving body image and enhancing emotion awareness and expression. [ABSTRACT FROM AUTHOR]

White shrimp typically surface to breathe in the absence of adequate oxygen, and detecting this abnormal behavior can help better exploit the benefits of white shrimp farming. Therefore, an accurate and efficient model for detecting white shrimp surfacing was developed in this study. The proposed method is based on the YOLOv5 model, which utilizes ghost convolution to optimize standard convolution. A ghost bottleneck was constructed to improve the performance of the original bottleneck, and a more efficient detection layer was built based on the data. The model was trained and verified using a self-built white shrimp surfacing dataset. The mAP@0.5 of this model was 98.139%, while the size and floating-point operations were only 1.76 MB and 2.1 G, respectively. Compared with Faster-RCNN, single-shot multi-box detector (SSD), and YOLOv4-tiny, our model presents higher detection accuracy and speed, as well as lower computation cost and smaller model size. Finally, based on the proposed method, we developed related applications for detecting shrimp surfacing. [ABSTRACT FROM AUTHOR]

This article is concerned with a chemotaxis-Stokes system with porous medium diffusion and singular sensitivity: { n t + u ⋅ ∇ n = ∇ ⋅ (D (n) ∇ n) − ∇ ⋅ (n S (x , n , c) ⋅ ∇ c) , x ∈ Ω , t > 0 , c t + u ⋅ ∇ c = Δ c − n c , x ∈ Ω , t > 0 , u t + ∇ P = Δ u + n ∇ Φ , ∇ ⋅ u = 0 , x ∈ Ω , t > 0 in a bounded domain Ω ⊂ R N with 2 ≤ N ≤ 3 , where D ∈ C 0 ([ 0 , ∞)) ∩ C 2 ((0 , ∞)) and S ∈ C 2 (Ω ¯ × [ 0 , ∞) 2 ; R N × N) . The global solvability of the system in a natural weak sense is obtained under the conditions that D (n) ≥ k D n m − 1 and | S (x , n , c) | ≤ S 0 (c) c α for all (x , n , c) ∈ Ω × (0 , ∞) 2 with some k D > 0 , m > 3 N − 2 2 N , α ∈ [ 0 , 1) and some nondecreasing S 0 : (0 , ∞) → (0 , ∞) . Moreover, in the case that m = 3 N − 2 2 N and α ∈ [ 0 , 1) , we also get the global weak solutions under smallness assumptions on the initial data ∥ n 0 ∥ L 1 (Ω) and ∥ c 0 ∥ L ∞ (Ω) . [ABSTRACT FROM AUTHOR]

We present a weakly-coupled air-hole-bow-tie-assisted few-mode fiber (AH-BT-FMF) supporting 26 eigenmodes for short-haul communication systems across the C + L band. The elliptical core, air holes, and bow-tie stress-applying area are introduced to effectively split adjacent eigenmodes. We evaluate the impact of fiber parameters on minimum effective refractive index difference (min Δneff) between adjacent modes, birefringence (B), and bending loss at a wavelength of 1550 nm. The broadband performance of the fiber is further investigated across the C + L band, including the effective refractive index difference (Δneff) between adjacent modes, differential mode delay (DMD), dispersion, and effective area (Aeff). Simulated results indicate that the 26 eigenmodes supported by the designed fiber are completely separated. The min Δneff between adjacent modes is larger than 1.982 × 10−4 over the whole C + L band. And the designed fiber has a higher effective area (66.56 –131.1 µm2), lower DMD (− 8.07 to 10.96 ns/km), and good bending resistance (< 10–4 dB/m). The designed fiber can be used for short-haul multiple-input multiple-output-free eigenmode-division multiplexing systems to improve transmission capacity and expand bandwidth. [ABSTRACT FROM AUTHOR]

A credible, validated measure of cognitive behavioral therapy (CBT) skill, an essential indicator of treatment progress, is currently missing in China. Competencies of Cognitive Therapy Scale-Self Report (CCTS-SR) is a brief and convenient instrument assessing the cognitive skills patients learn through CBT, even among individuals without any therapeutic experiences. Therefore, the current study sets out to examine the psychometric properties of CCTS-SR. A sample of 1090 Chinese university students completed a Chinese version of the CCTS-SR, Automatic Thought Scale, and Beck Depression Inventory. Factor structure and reliability were examined. We evaluated the CCTS-SR in 50 extra university students with subthreshold depression before and after a group CBT. The original uni-factor model of CCTS-SR was not confirmed, and a two-factor solution (identification and evaluation of negative thoughts and coping strategies) in accord with therapeutic theory was replicated and supported. Good internal consistency (Cronbach's alpha = 0.86 ~ 0.93) and test–retest reliability (r = 0.61 ~ 0.73) were observed. The change of two factors of CCTS-SR during CBT was significant (p < 0.001); however, only the change of factor coping strategies was significantly associated with the change of depression (β =-0.18, SE = 0.08, p = 0.031). The current study established preliminary evidence for the reliability and validity of the Chinese version of CCTS-SR. It provided a valuable tool to measure the level of cognitive behavioral therapeutic competency in the Chinese population. Moreover, it can help capture the acquisition of cognitive behavioral therapy skills during treatment. Future research is needed to replicate this two-factor structure in other samples (e.g., community and clinical samples) and their relations with depression. [ABSTRACT FROM AUTHOR]

In order to study the comfort of tight-fitting sportswear in winter, this paper designed a series of motions, and explored the distribution of comfort perception under different sports conditions by evaluating the wearing perception of human body. Finally, through the acquired experimental data, intelligent prediction models were established, and the prediction results were visualized, which makes the comfort distribution more intuitive. The results show that there are great differences in the parts that affect the overall comfort perception under different sports conditions; different ages subjects have different perceptions of comfort; Particle Swarm Optimization-Cuckoo Search-Adaptive Network-based Fuzzy Inference System has better prediction accuracy, and could replace the wearing trials. [ABSTRACT FROM AUTHOR]

Depression involves a heterogenous collection of symptoms. Network perspective views depressive symptoms as an interrelated network. The current study aimed to replicate network analyses on adolescent depression in three samples assessed with three instruments to examine the consistency of network structures and also examine the variance of networks between genders. Three samples of adolescents (total N = 4375, mean age = 15, 49.1% boys) were assessed with PHQ-9, SMFQ and CDI, respectively. Network analyses were carried out on depression symptoms. Network stability, node centrality and network comparisons between genders were examined. Three networks were reliably stable. Sadness and self-hatred were unanimously identified to be central symptoms of adolescent depression in three networks. In addition, fatigue, no good, everything wrong and loneliness also appeared to be central in specific networks. Among three depression networks, PHQ-9 network demonstrated gender difference in network structure. The current study is exploratory in nature. The differences in three networks can be due to various samples or different node inclusions. Further, the study is cross-sectional precluding causal interpretation and the samples are nonclinical. Besides "hallmark" symptom sadness, self-hatred was also identified unanimously in three networks, which demonstrated the significant role self-worth played in adolescent depression. The results also suggested that differences in node inclusion may have influence on the network structure. [ABSTRACT FROM AUTHOR]

Emodin is applied as an antitumor drug in many tumor therapies. However, its pharmacology performances are limited due to its low solubility. Herein, we fused erythrocyte and macrophage to form a hybrid membrane (EMHM) and encapsulated emodin to form hybrid membrane-coated nanoparticles. We employed glycyrrhizin to increase the solubility of emodin first and prepared the hybrid membrane nanoparticle-coated emodin and glycyrrhizin (EG@EMHM NPs) which exhibited an average particle size of 170 ± 20 nm and encapsulation efficiency of 98.13 ± 0.67%. The half-inhibitory concentrations (IC50) of EG@EMHM NPs were 1.166 μg/mL, which is half of the free emodin. Based on the photosensitivity of emodin, the reactive oxygen species (ROS) results disclosed that ROS levels of the photodynamic therapy (PDT) section were higher than the normal section (P < 0.05). Compared to the normal section, PDT-mediated EG@EMHM NPs could induce an early stage of apoptosis of B16. The western blot and flow cytometry results verified that PDT-mediated EG@EMHM NPs can significantly improve the solubility of emodin and perform a remarkably antitumor effect on melanoma via BAX and BCL-2 pathway. The application of the combined chemical and PDT therapy could provide an improving target therapy for cutaneous melanoma and also may offer an idea for other insoluble components sources of traditional Chinese medicine. [ABSTRACT FROM AUTHOR]

This study is aimed at investigating the effect of dietary zinc deficiency (ZnD) on skin breaking strength and skin chemical and fatty acid composition in broiler chickens and Pekin ducks. A total of 200 1-day-old male broiler chickens and 200 1-day-old male ducklings were used in a 2 × 2 factorial design and randomly allocated to 4 treatments with 10 replicated cages of 10 birds per cage. Diets containing zinc at 84.77 mg/kg and 20.42 mg/kg were regarded as the control diet and zinc-deficient diet, respectively. The results showed the following: (1) dietary ZnD decreased (P < 0.05) the breast skin weight (day 21), breast skin index (day 21), skin fat content (day 7), and skin Zn content (days 7, 14, and 21) of ducks, but only increased (P < 0.05) the skin fat content of broiler chickens at 7 days of age; ducks had a higher (P < 0.05) breast skin weight, breast skin index, and skin breaking strength as well as a lower skin fat content (days 7 and 14) than those in broiler chickens. (2) Dietary ZnD decreased the content of myristic acid (day 21) and increased the content of oleic acid (day 7) content in the skin of ducks and increased the palmitic acid (day 7) content in the skin of broiler chickens (P < 0.05) and increased the MUFA (day 7) content in the skin and the atherogenic index (day 21) in ducks. The contents of myristic acid (day 21), stearic acid (day 21), and oleic acid (days 7, 14, and 21) in the skin of broiler chickens were lower (P < 0.05) than those in ducks of the same age. In conclusion, using skin weight, skin index and skin MUFA content as criteria, the results indicated that meat ducks were more sensitive to dietary ZnD than broiler chickens. Using skin fat content as criterion, the results indicated that broiler chickens were more sensitive to dietary ZnD than meat ducks. [ABSTRACT FROM AUTHOR]

Compared to the well-studied model legumes, where symbiosis is established via root hair entry, the peanut is infected by Bradyrhizobium through the crack entry, which is less common and not fully understood. Crack entry is, however, considered a primitive symbiotic infection pathway, which could be potentially utilized for engineering non-legume species with nitrogen fixation ability. We utilized a fluorescence-labeled Bradyrhizobium strain to help in understanding the crack entry process at the cellular level. A modified plasmid pRJPaph-bjGFP, harboring the codon-optimized GFP gene and tetracycline resistance gene, was created and conjugated into Bradyrhizobium strain Lb8, an isolate from peanut nodules, through tri-parental mating. Microscopic observation and peanut inoculation assays confirmed the successful GFP tagging of Lb8, which is capable of generating root nodules. A marking system for peanut root potential infection sites and an optimized sample preparation protocol for cryostat sectioning was developed. The feasibility of using the GFP-tagged Lb8 for observing crack entry was examined. GFP signal was detected at the nodule primordial stage and the following nodule developmental stages with robust GFP signals observed in infected cells in the mature nodules. Spherical bacteroids in the root tissue were visualized at the nodules' inner cortex under higher magnification, reflecting the trace along the rhizobial infection path. The GFP labeled Lb8 can serve as an essential tool for plant-microbe studies between the cultivated peanut and Bradyrhizobium, which could facilitate further study of the crack entry process during the legume-rhizobia symbiosis. [ABSTRACT FROM AUTHOR]

SUMOylation (SUMO modification) has been confirmed to play an essential role in the progression of various malignancies. As the value of SUMOylation-related genes (SRGs) in prognosis prediction of hepatocellular carcinoma (HCC) has not been explored, we aim to construct an HCC SRGs signature. RNA sequencing was utilized to identify differentially expressed SRGs. The 87 identified genes were used in Univariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) analysis to build a signature. The accuracy of the model was validated by the ICGC and GEO datasets. The GSEA revealed that the risk score was associated with common cancer-related pathways. The ssGSEA showed that NK cells in the high-risk group were significantly reduced. The sensitivities of anti-cancer drugs confirmed the sensitivity of the high-risk group to sorafenib was lower. Further, our cohort showed that risk scores were correlated with advanced grade and vascular invasion (VI). Finally, the results of H&E staining and immunohistochemistry of Ki67 showed that higher-risk patients are more malignant. [ABSTRACT FROM AUTHOR]

Two experiments were performed to assess maternal zinc (Zn) depletion in broiler chickens and Pekin ducks fed a Zn-deficient diet. The time of Zn depletion was assessed based on growth performance, and sensitive biomarkers were determined based on tissue Zn content via a linear regression model. A total of 200 1-day-old male broiler chickens (experiment 1) and 200 1-day-old male Pekin ducks (experiment 2) were randomly allocated to 2 diets with 10 replicate cages (10 birds/cage). The two diets were a zinc-deficient diet (ZnD, 20.42 mg Zn/kg) and a control zinc diet (CON, 84.77 mg Zn/kg). In experiment 1, compared to CON, ZnD decreased (P < 0.05) the body weight (days 7, 14, and 21), body weight gain, feed intake (days 1–7, 1–14, and 1–21), and the Zn content of plasma (days 7 and 21), pancreas (days 7, 14, and 21), and tibia in broiler chickens. The R2 of a linear model was greater at day 7 than at day 14 or day 21 for pancreatic Zn content in broiler chickens. In experiment 2, compared to CON, ZnD also decreased (P < 0.05) the body weight (days 7, 14, and 21), body weight gain (days 1–7, 1–14, and 1–21), and feed intake (days 1–14 and 1–21) and increased (P < 0.05) the feed-to-gain ratio (days 1–7 and 1–14) in ducks. Compared with CON, ZnD reduced (P < 0.05) the Zn content of the pancreas (days 7, 14, and 21), tibia (days 7, 14, and 21), and skin (days 14 and 21) and increased (P < 0.05) the Zn content of the plasma (day 21) and skin (day 7) in ducks. The R2 of a linear model was greater at day 7 than at days 14 or 21 for skin Zn content in ducks. The results indicated that the maternal Zn was depleted by 7 days of age in both birds; the sensitive biomarker for broiler chickens is pancreatic Zn content, and for ducks, it is skin Zn content. [ABSTRACT FROM AUTHOR]

The rapid development of blockchain technology has garnered increasing attention, particularly in the field of edge computing. It has become a significant subject of research in this area due to its ability to protect the privacy of data. Despite the advantages that blockchain technology offers, there are also security threats that must be addressed. Attackers may manipulate certain nodes in the blockchain network, which can result in tampering with transaction records or other malicious activities. Moreover, the creation of a large number of false nodes can be utilized to gain control and manipulate transaction records of the blockchain network, which can compromise the reliability and security of edge computing. This paper proposes a blockchain node detection method named T 2 A 2 v e c that provides a more secure, credible, and reliable solution to address these challenges. In order to achieve T 2 A 2 v e c , a transaction dataset that is evenly distributed in both space and time was collected. The transaction dataset is constructed as a transaction graph, where nodes represent accounts and edges describe transactions. BP neural network is used to extract account features, and a random walk strategy based on transaction time, type, and amount is used to extract transaction features. The obtained account features and transaction features are fused to obtain account representation. Finally, the obtained node representation is fed into different classifiers to identify malicious nodes. [ABSTRACT FROM AUTHOR]

Fit evaluation plays an important role in garment products development and sales. Effective clothing fit evaluation methods can reduce the development cost of apparel products and the return rate of online apparel sales. In this research, we proposed an intelligent fit evaluation technology to predict clothing fit. The mathematical relationship model between clothing fit levels and indexes reflecting the clothing fit levels was constructed by using decision tree C4.5 algorithm. Then, two experiments were carried out to collect input and output training data. After learning from the collected data, the proposed model can predict clothing fit accurately. Next, we validated our proposed model's prediction accuracy using K-fold cross validation. Finally, we gave two applications of the proposed model for clothing products development and shopping online. Results show that our proposed method has high prediction accuracy and less requirement for the number of learning samples, and can predict clothing fit automatically and rapidly without real try-on. [ABSTRACT FROM AUTHOR]

Groundwater plays a crucial role in sustaining industrial and agricultural production and meeting the water demands of the growing population in the semi-arid Guanzhong Basin of China. The objective of this study was to evaluate the groundwater potential of the region through the use of GIS-based ensemble learning models. Fourteen factors, including landform, slope, slope aspect, curvature, precipitation, evapotranspiration, distance to fault, distance to river, road density, topographic wetness index, soil type, lithology, land cover, and normalized difference vegetation index, were considered. Three ensemble learning models, namely random forest (RF), extreme gradient boosting (XGB), and local cascade ensemble (LCE), were trained and cross-validated using 205 sets of samples. The models were then applied to predict groundwater potential in the region. The XGB model was found to be the best, with an area under the curve (AUC) value of 0.874, followed by the RF model with an AUC of 0.859, and the LCE model with an AUC of 0.810. The XGB and LCE models were more effective than the RF model in discriminating between areas of high and low groundwater potential. This is because most of the RF model's prediction outcomes were concentrated in moderate groundwater potential areas, indicating that RF is less decisive when it comes to binary classification. In areas predicted to have very high and high groundwater potential, the proportions of samples with abundant groundwater were 33.6%, 69.31%, and 52.45% for RF, XGB, and LCE, respectively. In contrast, in areas predicted to have very low and low groundwater potential, the proportions of samples without groundwater were 57.14%, 66.67%, and 74.29% for RF, XGB, and LCE, respectively. The XGB model required the least amount of computational resources and achieved the highest accuracy, making it the most practical option for predicting groundwater potential. The results can be useful for policymakers and water resource managers in promoting the sustainable use of groundwater in the Guanzhong Basin and other similar regions. [ABSTRACT FROM AUTHOR]

Groundwater is a vital resource in arid areas that sustains local industrial development and environmental preservation. Mapping groundwater potential zones and determining high-potential regions are essential for the responsible use of the local groundwater resource. When utilizing machine learning or deep learning algorithms to forecast groundwater potential in arid areas, difficulties such as inaccurate and overfitting predictions might occur due to a shortage of borehole samples. In this study, a database of groundwater conditioning factors with a size of 275,157 × 9 was created in the Qaidam Basin, and 85 known borehole samples were collected. The groundwater potential was evaluated using a combination of rank sum ratio (RSR), projection pursuit regression (PPR) and random forest (RF) algorithms, resulting in four models: PPR, RSR-PPR, RSR-RF, and RF. Results indicated that the groundwater potential was higher in mountainous regions surrounding the Qaidam Basin and decreased progressively towards the central and northwestern regions where most industries and facilities are located. The two primary factors, according to the PPR and RF models, were evapotranspiration (0.246, 0.225) and landform (0.176, 0.294). In terms of their ability to accurately forecast the borehole samples, the four models ranked as follows: RF > RSR-RF > RSR-PPR > PPR. The accuracy of the four models in the low-potential area was 0.73 (PPR), 0.60 (RSR-PPR), 0.87 (RSR-RF), and 0.80 (RF), respectively. However, the RF model showed overfitting due to a lack of samples, especially in high-potential regions, which limits its applicability. The RSR-RF method was applied directly to evaluate the entire factor database, avoiding the risk of overfitting caused by a limited number of training samples. The results demonstrate that the RSR-RF model is effective for classifying groundwater potential types in samples and mapping groundwater potential of the study area. This research presents a novel approach for groundwater potential predictions in areas with insufficient sample sizes, providing a reference for policymakers and researchers. [ABSTRACT FROM AUTHOR]

This paper is concerned with a doubly tactic resource consumption model with nonlinear diffusions: u t = ∇ · ((u + 1) h - 1 ∇ u) - ∇ · (u ∇ w) , v t = ∇ · ((v + 1) l - 1 ∇ v) - ∇ · (v ∇ u) , w t = Δ w - (u + v) w - w + r (x , t) , where r is a nonnegative bounded function. This system describes the so-called forager–exploiter interaction. It is shown that if h ≥ 2 - 1 / n and l ≥ 2 , then the system has a global weak solution; if in addition min 1 + 1 / n + (h - 2) + , 1 / n + l - 1 > n / 4 + 1 / 2 , then the system has a unique global classical solution. [ABSTRACT FROM AUTHOR]

Dissolved oxygen is a critical water quality factor, and its prediction and control have long been a research hotspot in the aquaculture industry. This study aims to address the limitations of poor population diversity and the ease of falling into local optima in the basic sparrow search algorithm (SSA). Herein, we improved this methodology in many aspects and proposed a hybrid improved SSA (HISSA) to enhance optimization performance. First, in the global search process of the sparrow producer, the position update strategy is modified to enhance the global search ability of the algorithm. Second, a butterfly algorithm is incorporated to replace the position update strategy in the escape stage of the producer to promote information exchange between individuals. Third, the Cauchy mutation strategy and greedy rule are used to perturb and update the current optimal solution to improve the algorithm's ability to jump out of local optima. The performance of the proposed HISSA was verified on 10 benchmark functions. The experimental results illustrate that the proposed algorithm outperformed the four intelligent algorithms evaluated herein. In addition, the proposed HISSA was separately applied to the parameter optimization of the two most commonly used engineering methods: the back propagation neural network (BPNN) and proportional-integral-derivative (PID) controller. Compared with other intelligent algorithm-optimized methods, the error evaluation index values of the HISSA-BPNN and HISSA-PID controllers are small, indicating that the proposed HISSA is highly effective and practical for engineering parameter optimization, and can be competent for the prediction and control of dissolved oxygen. [ABSTRACT FROM AUTHOR]

This study examined the mediating role of self-esteem in the relationship between perceived discrimination and subjective wellbeing and explored how resilience and belief in a just world interact to buffer the detrimental influences of perceived discrimination on subjective wellbeing. A questionnaire survey was conducted on 872 impoverished college students in China. The results indicated that: (1) Self-esteem mediated the relationship between perceived discrimination and subjective wellbeing. (2) Belief in a just world played a moderating role between perceived discrimination and subjective wellbeing, and the harmful impact of perceived discrimination on wellbeing was weaker for those who had higher (vs.lower) levels of belief in a just world. (3) Resilience moderated the relationship between perceived discrimination and self-esteem, and the harm of discrimination on self-esteem was weakened for those who had lower (vs.higher) levels of resilience. Poverty indeed has a non-negligible and vital impact on the mental health of college students. Among impoverished Chinse college students, resilience and belief in a just world play a protective role in the relationship between discrimination and subjective wellbeing. However, the current finding suggests that we should not exaggerate the protective effect of resilience. It is crucial to change unfavorable factors in the environment, such as discrimination against poverty. [ABSTRACT FROM AUTHOR]

This study aimed to adapt and validate the Posttraumatic Growth Inventory in Chinese shidu parents (PTGI-CS) and to develop its short form (PTGI-CS-SF). A convenience sample of 899 participants across China was included in the analyses. Results of parallel analysis and confirmatory factor analysis suggested that a bifactor model (a general posttraumatic growth factor with three specific factors: philosophy of life, changes in self and relationships with others) of the PTGI-CS had an optimal fit (root mean square error of approximation =.065, comparative fit index =.927, Tucker-Lewis index =.902, standardized root mean squared residual =.054). The 17-item PTGI-CS had satisfactory convergent and discriminant validity, internal consistency (Cronbach's alpha =.906) and test–retest reliability (r =.776, p <.01). However, omega hierarchical coefficients for three subscales were low (.202 to.391), which indicated that only the total scores of PTGI, and not the subscale scores, should be used. Additionally, a 9-item short form of PTGI-CS has been developed and was shown to be a reliable instrument to assess Chinese shidu parents' PTG. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the efficacy of Iodine-125 (I-125) brachytherapy in a mouse model of non-small cell lung cancer, to further explore the efficacy and appropriate method of implantation of the I-125 radioactive seed. This study also aimed to determine the impact of brachytherapy on bone metabolism. A total of 18 mice were used to establish H1299 xenograft models, and were randomly assigned to three groups. These included non-radioactive seed implantation (Sham IM), fractionated I-125 seed implantation (Fractionated IM) and single I-125 seed implantation (Single IM) groups. Mice were euthanized after 28 days of implantation. H&E staining, Ki67 immunohistochemistry, CD31 morphometric analysis and TUNEL immunofluorescence assays were respectively used to determine the histopathological changes, proliferation, micro-angiogenesis and apoptosis of tumors. In addition, bone volume and microstructure were evaluated using trabecular bone area (Tb.Ar), trabecular thickness (Tb.Th), trabecular number (Tb.N) and cortical thickness. Bone metabolic status was analyzed using histomorphometric staining of tartrate-resistant acid phosphate (TRAP) and alkaline phosphatase (ALP) expression in the femur, and using an ELISA assay to determine the expression of C-telopeptide of type 1 collagen (CTX-1) and procollagen type 1 n-terminal propeptide (P1NP) in the serum. Moreover, reverse transcription-quantitative PCR and western blotting were carried out for the analysis of bone remodeling-related gene expression in the bone tissue. Results of the present study demonstrated that compared with the Sham IM group, both the I-125 seed implantation groups, including Fractionated IM and Single IM, demonstrated significant therapeutic effects in both tumor volume and weight. More specifically, the most significant therapeutic effects on tumor inhibition were observed in the Fractionated IM group. Results of Ki67 and CD31 immunohistochemical staining suggested a notable reduction in tumor cell proliferation and micro-angiogenesis, and results of the TUNEL assay demonstrated an increase in tumor cell apoptosis. Although the cortical bone appeared thinner and more fragile in both I-125 seed implantation groups, no notable adverse changes in the morphology of the cancellous bone were observed, and the index of Tb.Ar, Tb.Th and Tb.n was not significantly different among Sham IM and I-125 implantation groups. However, alterations in bone metabolism were characterized by a decrease in CTX-1 and P1NP expression, accompanied by an increase in TRAP activity and a decrease in ALP activity. Results of the present study also demonstrated the notable suppression of osteocalcin and runt-related transcription factor 2. I-125 seed implantation may be an effective and safe antitumor strategy. Moreover, the use of fractionated implantation patterns based on tumor shape exhibited improved therapeutic effect on tumor suppression when the total number of I-125 seeds was equivalent along with reduced complications associated with bone loss. [ABSTRACT FROM AUTHOR]

Stretchable and transparent electrodes (STEs) based on silver nanowires (AgNWs) have garnered considerable attention due to their unique optoelectronic features. However, the low oxidation resistance of AgNWs severely limits the reliability and durability of devices based on such STEs. The present work reports a type of core-sheath silver@gold nanowires (Ag@Au NWs) with a morphology resembling dual-headed matchsticks and an average Au sheath thickness of 2.5 nm. By starting with such Ag@Au NWs, STEs with an optical transmittance of 78.7%, a haze of 13.0%, a sheet resistance of 13.5 Ω·sq.−1, and a maximum tensile strain of 240% can be formed with the aid of capillary-force-induced welding. The resultant STEs exhibit exceptional oxidation resistance, high-temperature resistance, and chemical/electrochemical stability owing to the conformal and dense Au sheath. Furthermore, non-enzymatic glucose biosensors are fabricated employing the Ag@Au NW STEs. The electrocatalytic oxidation currents are proportional to glucose concentrations with a high sensitivity of 967 µA·mM−1·cm−2 and a detection limit of 125 µM over a detection range of 0.6 to 16 mM. Additionally, the biosensors demonstrate an appealing robustness and anti-interference characteristics, high repeatability, and great stability that make them adequate for practical use. [ABSTRACT FROM AUTHOR]

Calcium alginate hollow fibers have been used as bionic vascular channels in thick tissue and organ regeneration studies, whose permeability determines the transport efficiency of nutrients and oxygen. CaCl2 was dissolved in the solvent mixed with isopropyl alcohol (IPA) and deionized water to obtain a series of crosslinking agents with different polarities. Calcium alginate hollow fibers were fabricated by the coaxial flow, and the influence of interfacial polarity on its permeability was studied. The polarity evaluation results showed that the polarity index of the crosslinking agents decreased from 9.00 to 3.90 with the increase in IPA mass concentration. Scanning electron microscopy observations indicated that with the weakening of the interfacial polarity of the coaxial flow, the gel units tended to be shorter and denser along the flow direction. It was worth noting that the permeability did not change synchronously with the polarity, but first enhanced and then weakened with the decrease in the polarity. When the mass concentration of IPA exceeded 60%, the regulation ability of interfacial polarity on permeability was significantly improved. The research results will have a positive effect on the customization of physicochemical properties of alginate. [ABSTRACT FROM AUTHOR]

The cognitive model of social anxiety disorder hypothesized that socially anxious individuals tend to negatively interpret ambiguous scenarios, which was termed an Interpretation bias (IB). The Adolescents' Interpretation Bias Questionnaire (AIBQ) is a widely used self-report instrument to measure IB towards social situations for adolescents. The main objective of the current study was to culturally revise AIBQ in Chinese adolescents. In total, 960 adolescents participated, and four weeks later, 185 of them were re-measured with Chinese version of AIBQ (C-AIBQ). We tested construct validity, examined internal consistency and test-retest reliability, and assessed convergent and divergent validity of the C-AIBQ subscales. Overall, C-AIBQ variables showed satisfactory construct validity, internal consistency, test-retest reliability and convergent and discriminant validity, in particular the social negative interpretation subscale. Our results indicate that this instrument is adequate to measure interpretation bias in Chinese adolescents. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel design of trench-nanopore-assisted double-clad few-mode fiber, which can support 14 linearly polarized (LP) modes. The trench-nanopore structure is introduced to effectively split adjacent modes and decrease bending loss. We evaluate the impact of parameters on the effective modal index (neff), the minimum effective refractive index difference (minΔneff) and modal effective area (Aeff) by using the finite element. The bending loss and broadband performance of the entire C+L bands, including neff, Δneff, differential mode delay (DMD) and dispersion, are also investigated. The simulated results show that all modes supported by the designed fiber are completely separated with Δneff between adjacent modes larger than 6 × 10–4 over the whole C+L-band. Bending loss is lower than 10−5 dB/m. The designed trench-nanopore-assisted fiber has the potential applications for short-haul mode division multiplexing systems to improve transmission capacity. [ABSTRACT FROM AUTHOR]

Background: Agroforestry has been advocated as a climate-smart agricultural approach to counter extreme climate and as an important sustainable intensification practice to meet Sustainable Development Goals (SDGs). However, its efficacy remains under dispute in drylands where resources, especially water, are limited. Aim and methods: This study aimed to study how annual bioenergy crops, soybean (Glycine max) and canola (Brassica rapa), influence soil water availability and fine root distribution in a young apple orchard exposed to varying to drought intensity on the semiarid Loess Plateau of China. Drought was simulated by reducing natural precipitation by 15% (moderate drought) and 25% (severe drought). Result and conclusions: Intercropping soybean and canola increased the fine root biomass (FRB) of apple trees in the 80–180 cm soil layer, improved moisture status below the 80 cm soil layer in the wet season, and promoted apple tree growth. Under moderate drought, FRB in the 0–80 cm soil layer increased, making use of the shallow soil water replenished by precipitation. However, the trees switched to absorbing soil water in the 80–180 cm in the dry season. Under severe drought, the apple trees increased FRB in the 0–80 cm and 180–280 cm soil layers and increased the proportion of the total roots in the 180–280 cm layer, aggravating the deep soil desiccation and inhibiting apple tree growth. These findings offer insights into drought effects on root plasticity and soil management practices in rainfed orchards. [ABSTRACT FROM AUTHOR]

In this paper, a scheme of optical encryption system for color code is proposed which is based on double random polarization encryption and exclusive-OR operation. First, an original image is generated into a color code according to the rules of color code generation, then the color code is encoded by exclusive-OR operation, finally, the coded color code is used as the input image for double-random polarization encryption. The original image can be recovered only if all the keys are correct. If the ciphertext is tampered or cut, the image cannot be recovered or even displayed on the computer. This method can apply the double random polarization encryption method used for binary image encryption to color code encryption, and the exclusive-OR operation can improve the security of the system. Numerical experimental results show the feasibility and effectiveness of this method. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes mellitus (GDM) reflects a deficiency in the relative need for insulin during pregnancy, as well as temporary metabolic stress in the placenta and fetus. Our study aimed to research the potential diagnostic value of transforming growth factor-beta-induced protein ig-h3 (TGFBI) and transforming growth factor beta-2 proprotein (TGFB2) for GDM patients. Methods: Online database Gene Expression Omnibus (GEO) was used to screen for different expressed genes (DEGs) associated with GDM. Meanwhile, KEGG and GO were used to analyze the molecular functions as well as pathways of enriched DEGs. One hundred ten pregnant women diagnosed with GDM and 110 healthy controls were enrolled, of whose placenta and fasting venous blood samples were collected. mRNA expression levels were determined by real-time quantitative polymerase chain reaction (RT-qPCR), and fasting blood glucose (FBG) was measured by the clinical lab of hospital. Furthermore, receiver operating characteristics curve (ROC) analysis was performed to evaluate the sensitivity and specificity of detection indexed in the placenta and plasma of GDM patients. Finally, Pearson and Spearman analysis was used for the correlation analysis. Results: After GEO data analysis, TGFBI and TGFB2 were identified as the most significantly up-regulated genes of GDM. TGFBI and TGFB2 expressions in placenta and plasma samples of GDM patients were in line with bioinformatic analysis. Meanwhile, the area under the curve (AUC) of TGFBI in the placenta and plasma for the diagnosis of GDM were 0.8783 (95% CI, 0.8281 to 0.9284) and 0.7832 (95% CI, 0.7215 to 0.8449) while for TGFB2 were 0.9225 (95% CI, 0.8829 to 0.9621) and 0.8961 (95% CI, 0.8526 to 0.9396). Besides, levels of TGFBI along with TGFB2 in the placenta were positively correlated with that in the plasma of GDM patients. Furthermore, both TGFBI and TGFB2 expressions in the plasma were positively correlated with FBG levels of the GDM patients. Conclusions: TGFBI and TGFB2 were up-regulated in the placenta and plasma of GDM patients, and TGFBI and TGFB2 in the plasma are potent to be diagnostic markers for the GDM. [ABSTRACT FROM AUTHOR]

Purpose: Discovery of noninvasive urinary biomarkers for the early diagnosis of esophageal squamous carcinoma (ESCC). Methods: We conducted proteomic analyses of 499 human urine samples obtained from healthy individuals (n = 321) and ESCC (n = 83), bladder cancer (n = 17), breast cancer (n = 12), colorectal cancer (n = 16), lung cancer (n = 33) and thyroid cancer (n = 17) patients from multiple medical centers. Those samples were divided into a discovery set (n = 247) and an independent validation set (n = 157). Results: Among urinary proteins identified in the comprehensive quantitative proteomics analysis, we selected a panel of three urinary biomarkers (ANXA1, S100A8, TMEM256), and established a logistic regression model in the discovery set that can correctly classify the majority of ESCC cases in the validation sets with the area under the curve (AUC) values of 0.825. This urinary biomarker panel not only discriminates ESCC patients from healthy individuals but also differentiates ESCC from other common tumors. Notably, the panel distinguishes stage I ESCC patients from healthy individuals with AUC values of 0.886. On the analysis of stage-specific biomarkers, another combination panel of protein (ANXA1, S100A8, SOD3, TMEM256) demonstrated a good AUC value of 0.792 for stage I ESCC. Conclusions: Urinary biomarker panel represents a promising auxiliary diagnostic tool for ESCC, including early-stage ESCC. [ABSTRACT FROM AUTHOR]