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Intergenerational relationships that highlight learning characteristics are created in interpersonal conflicts and lifelong education. Realizing the high-quality development of intergenerational learning has become a key problem. A primary school in eastern China united communities and families to create an efficient intergenerational learning project. This study aims to explore how this intergenerational learning is created. A principal, a teacher, two community educators, and five family members were recruited as the unstructured interview participants to collect data. This study finds that the school, community, and families play irreplaceable roles in creating intergenerational learning. Influenced by educational policies and education responsibilities, the school proactively designed the intergenerational learning project that takes grandparents to school in interaction with the community and families. Adhering to the principle of social services and age-friendly, the community provides sufficient educational resources for implementing intergenerational learning through collaborative support. Considering the generation gap and integration between grandparents and grandchildren, families as participating identities make intergenerational learning from possible imagination into real practice. This study highlights the theoretical framework of how intergenerational learning is created in school-community-family collaboration. The practical implications for optimizing intergenerational relationships and coping with population aging are further emphasized. [ABSTRACT FROM AUTHOR]

This study focused on producing metal matrix composite (MMC) coatings on Ti–6Al–4V alloy through laser surface alloying using a novel combination of Inconel 625 and SiC precursor materials. Various ratios of alloying powders were examined to evaluate surface properties such as microhardness, wear resistance, and friction coefficient, along with analyzing the phase composition and microstructure of the coatings. The in situ synthesized MMC coatings exhibited the presence of α-Ti, NiTi, NiTi2, and TiC phases. Additionally, Ti5Si3 and α-Ti/Ti5Si3 eutectic structures were observed when the SiC content exceeded 20%. In comparison to the titanium substrate, the MMC coating significantly enhanced microhardness by over threefold and reduced wear by 95%. However, it was crucial to carefully select the appropriate combination of alloying powders to avoid a substantial decrease in friction performance and excessive formation of cracks. Through a comparative analysis of experimental results, the optimal precursor material composition was identified as 85% Inconel 625 and 15% SiC. This study demonstrated the effective utilization of Inconel 625 and SiC alloying materials to enhance the surface properties of titanium alloys, thereby expanding their application in challenging environments. [ABSTRACT FROM AUTHOR]

The valuable metals copper and zinc were successfully recovered from a water-quenched lead smelting slag containing zinc in Gansu Province. This study focuses on the application of the direct reduction roasting-flotation process for extracting these metals from the slag phase. To comprehend the recovery principle of copper and zinc minerals in the slag phase, various techniques including thermodynamic analysis, scanning electron microscopy, energy dispersive spectrometry, and mineral liberation analyzer were employed. The findings demonstrate that zinc minerals can be easily recovered through reduction roasting processes. Following roasting, chalcopyrite within the slag phase recrystallizes into larger particles which become exposed on the surface of vitreous gangue material. By optimizing parameters such as roasting time (90 min), coke dosage (12.5%), and roasting temperature (1250°C), a remarkable volatilization rate of 99.27% for zinc in the slag phase was achieved while successfully recovering high-purity zinc oxide dust. Copper ores undergo a transition from being difficult to dissociate into monomers to becoming easier to dissociate, thereby enhancing their flotation recovery potential. Through one rough flotation followed by three cleaning flotation during process, a concentrate with an impressive copper grade of 18.24% and copper recovery rate of 56.22% was obtained. [ABSTRACT FROM AUTHOR]

Human action recognition from skeleton motion sequences is widely applied in various fields such as virtual reality, human-computer interaction and kinematic rehabilitation. With the wide use of graph neural networks for extracting spatial features from skeleton anatomy connectivity, spatial-temporal extension of single graph models on human skeleton may improve the network performance. In this paper, we propose a priori separation graph convolution (PS-GCN) network composition with a priori mixed GCN by introducing a hypergraph representation of the skeleton spatial features, and a dynamic adaptive GCN to describe the respective graph model for each sample at each layer of the network of spatial features. For temporal feature analysis, a global attention unit is added to describe the long-term relationship. Moreover, a feature fusion structure is applied for short-term temporal features in the input of the network. The proposed model is evaluated on the NTU-RGB+D, NTU-RGB+D 120 and NW-UCLA datasets via a comprehensive ablative study. The results show that our model is comparable in accuracy to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

An adaptive control method based on immersion and invariance (I&I) is presented in a class of nonlinear systems with time-varying uncertain parameters. A parameter estimation law based on reference models using I&I is designed to accelerate the convergence of estimated parameters to the true value, enabling the closed-loop system to reach the predefined target system on the manifold more quickly and reducing the energy consumption of the system. The inherent integrability obstacles in I&I are overcome by using dynamic scaling techniques, reducing the complexity of controller design. Stability analysis of the closed-loop system demonstrates that the proposed control method can achieve asymptotic stability control of the target system, and verified the robustness of the closed-loop system in the face of external disturbances. Finally, simulations of attitude tracking control demonstrate the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

To facilitate natural heritage protection, ecological protection, and tourism development, farmers in natural heritage tourist destinations are often relocated and resettled, thus becoming land-lost farmers. Because of the COVID-19 pandemic, the livelihood vulnerability of land-lost farmers in natural heritage tourist destinations has become particularly prominent. In this paper, the Yinhuwan resettlement community in China's Mount Sanqingshan Scenic Area is taken as an example and changes in stock and livelihood capital structure of farmers after relocation are analyzed. Based on the "exposure-sensitivity-adaptability" framework, an evaluation index system of farmers' livelihood vulnerability is constructed to evaluate farmers' livelihood vulnerability. The multiple linear regression model is used to empirically analyze the influencing factors of livelihood vulnerability. The results show: (1) Relocation and resettlement induced considerable changes to the livelihood of farmers. After relocation, the livelihood capital of farmers has generally increased. The physical capital and financial capital of farmers increased significantly, while natural capital was replaced by tourism capital. This led to a decrease in human capital of farmers compared with tourism operations. (2) The COVID-19 pandemic has greatly impacted the livelihood of farmers in this resettlement community. (3) Under the influence of the COVID-19 pandemic, the livelihood vulnerability of the main Nongjiale operators has become relatively high, while that of part-time Nongjiale operators and non-Nongjiale operators is moderate. (4) Tourism capital, tourism market seasonality, and livelihood diversification are significant factors influencing the livelihood vulnerability of farmers in this resettlement community. In this paper, the original natural capital is replaced with tourism capital, and a new analysis framework of livelihood capital is constructed. This provides a reference for future research on the livelihood of farmers in tourist destinations. This reference helps to study the sustainability of the livelihoods of land-lost farmers, and to evaluate the feasibility of the resettlement policy of farmers in tourist destinations. Several suggestions are presented that provide a basis for the formulation of relevant policies for reducing farmers' livelihood vulnerability. [ABSTRACT FROM AUTHOR]

Life education is increasingly recognized as one of the potentially effective ways to reduce unnatural deaths. Existing research focuses mainly on classroom knowledge transfer and extracurricular practical activities, which has been criticized for their effectiveness due to insufficient interaction between teachers and students. Creating high-quality life education, therefore, has become a demand for human happiness. Intergenerational learning embedded in life education, developed by collaborating with primary schools and older adult schools in China, has become an effective practice. Two teachers, seven primary school students, and seven older adult learners were interviewed to reveal the characteristics and impact of this effective practice. This model of practice establishes a dual subject of teachers and students in breaking the boundary between teachers as subjects and students as objects, while recognizing diverse lives in the interaction and reflection of intergenerational learning. In addition, this study constructs a classroom teaching model of teachers, primary school students, and older adult learners jointly creating knowledge, skills, emotions, attitudes, and values, and I put forward the life education thought of 'seeing life through life'. This study has implications for policymakers on improving educational policies and practitioners on innovating life education models in cross-cultural contexts. [ABSTRACT FROM AUTHOR]

Background: Migraine, a widespread neurological condition, substantially affects the quality of life, particularly for adolescents and young adults. While its impact is significant, there remains a paucity of comprehensive global research on the burden of migraine in younger demographics. Our study sought to elucidate the global prevalence, incidence, and disability-adjusted life-years (DALYs) associated with migraine in the 15–39 age group from 1990 to 2021, utilizing data from the Global Burden of Disease (GBD) 2021 study. Methods: Our comprehensive study analyzed migraine data from the GBD 2021 report, examining the prevalence, incidence, and DALYs across 204 countries and territories over a 32-year span. We stratified the information by age, sex, year, geographical region, and Socio-demographic Index (SDI). To evaluate temporal trends in these metrics, we employed the estimated annual percentage change (EAPC) calculation. Results: Between 1990 and 2021, the worldwide prevalence of migraine among 15–39 year-olds increased substantially. By 2021, an estimated 593.8 million cases were reported, representing a 39.52% rise from 425.6 million cases in 1990. Global trends showed increases in age-standardized prevalence rate, incidence rate, and DALY rate for migraine during this period. The EAPC were positive for all three metrics: 0.09 for ASPR, 0.03 for ASIR, and 0.09 for DALY rate. Regions with medium SDI reported the highest absolute numbers of prevalent cases, incident cases, and DALYs in 2021. However, high SDI regions demonstrated the most elevated rates overall. Across the globe, migraine prevalence peaked in the 35–39 age group. Notably, female rates consistently exceeded male rates across all age categories. Conclusion: The global impact of migraine on youths and young adults has grown considerably from 1990 to 2021, revealing notable variations across SDI regions, countries, age groups, and sexes. This escalating burden necessitates targeted interventions and public health initiatives, especially in areas and populations disproportionately affected by migraine. [ABSTRACT FROM AUTHOR]

A highly sensitive surface-enhanced Raman scattering (SERS) biosensor has been developed for the detection of microRNA-21 (miR-21) using an isothermal enzyme-free cascade amplification method involving catalytic hairpin assembly (CHA) and hybridization chain reaction (HCR). The CHA reaction is triggered by the target miR-21, which causes hairpin DNA (C1 and C2) to self-assemble into CHA products. After AgNPs@Capture captures the resulting CHA product, the HCR reaction is started, forming long-stranded DNA on the surface of AgNPs. A strong SERS signal is generated due to the presence of a large amount of the Raman reporter methylene blue (MB) in the vicinity of the SERS "hot spot" on the surface of AgNPs. The monitoring of the SERS signal changes of MB allows for the highly sensitive and specific detection of miR-21. In optimal conditions, the biosensor exhibits a satisfactory linear range and a low detection limit for miR-21 of 42.3 fM. Additionally, this SERS biosensor shows outstanding selectivity and reproducibility. The application of this methodology to clinical blood samples allows for the differentiation of cancer patients from healthy controls. As a result, the CHA-HCR amplification strategy used in this SERS biosensor could be a useful tool for miRNA detection and early cancer screening. [ABSTRACT FROM AUTHOR]

Emerging non-thermal technologies are widely applied in storage and processing of aquatic products, especially ultrasound-assisted technology. Frequency is an important component of ultrasound, and the effects of different ultrasound frequencies are obviously different. This research evaluated the effects of single-frequency (28 kHz, 40 kHz) and dual-frequency (28/40 kHz) ultrasound-assisted thawing (UAT) treatment on physicochemical quality, myofibril characteristics, and microstructure of large yellow croaker during frozen to refrigeration. The results revealed that UAT treatment retained a better performance, such as water-holding capacity (WHC), color, texture, and water distribution, and relieved disruption of microstructure, especially DUAT-28/40 treatment. The total volatile basic nitrogen (TVB-N) obtained the most desirable freshness property under the DUAT-28/40 treatment, as well as the free amino acids analysis. In addition, it reduced the myofibril denaturation during frozen to refrigeration, as shown in protein primary structure, infrared detection, and fluorescence intensity analysis. Therefore, DUAT-28/40 treatment could be a possible thawing method for relieving the quality deterioration of large yellow croaker during frozen to refrigeration. [ABSTRACT FROM AUTHOR]

As a promising antitumor strategy, combination oncotherapy can achieve better therapeutic efficacy. However, given the different properties of drugs, carriers need to meet requirements for efficient encapsulation and controllable release of multi-drugs. Herein, we propose a graphene oxide (GO)-templated biomineralization nanosystem to optimize oncotherapy. For preparation, GO is conjugated with polyethylene glycol (PEG) to improve biostability, and glyeyrrhetinic acid (GA) is further grafted onto PEG chains for site-specific targeting. The generated nanosheet structure and large specific surface area support high doxorubicin (DOX) encapsulation and mineralized deposition of siRNA via π-π stacking and calcium phosphate co-precipitation, respectively. Followed by highly efficient penetration into tumor cells, GO-templated nanosystem performs swift drug release in response to tumor acidic microenvironment through dissolution of calcium phosphate and disruption of molecular interactions. After administration, the GO-templated nanosystem performs superior pharmacy properties and significant antitumor efficacy via the synergy of chemotherapy and RNA interference therapy. Collectively, a GO-templated biomineralization nanosystem provides an innovative delivery system for multi-drug administration in combinative tumor therapy. [ABSTRACT FROM AUTHOR]

Hemodynamic parameters derived from pulse wave analysis have been shown to predict long-term outcomes in patients with heart failure (HF). Here we aimed to develop a deep-learning based algorithm that incorporates pressure waveforms for the identification and risk stratification of patients with HF. The first study, with a case–control study design to address data imbalance issue, included 431 subjects with HF exhibiting typical symptoms and 1545 control participants with no history of HF (non-HF). Carotid pressure waveforms were obtained from all the participants using applanation tonometry. The HF score, representing the probability of HF, was derived from a one-dimensional deep neural network (DNN) model trained with characteristics of the normalized carotid pressure waveform. In the second study of HF patients, we constructed a Cox regression model with 83 candidate clinical variables along with the HF score to predict the risk of all-cause mortality along with rehospitalization. To identify subjects using the HF score, the sensitivity, specificity, accuracy, F1 score, and area under receiver operating characteristic curve were 0.867, 0.851, 0.874, 0.878, and 0.93, respectively, from the hold-out cross-validation of the DNN, which was better than other machine learning models, including logistic regression, support vector machine, and random forest. With a median follow-up of 5.8 years, the multivariable Cox model using the HF score and other clinical variables outperformed the other HF risk prediction models with concordance index of 0.71, in which only the HF score and five clinical variables were independent significant predictors (p < 0.05), including age, history of percutaneous coronary intervention, concentration of sodium in the emergency room, N-terminal pro-brain natriuretic peptide, and hemoglobin. Our study demonstrated the diagnostic and prognostic utility of arterial waveforms in subjects with HF using a DNN model. Pulse wave contains valuable information that can benefit the clinical care of patients with HF. [ABSTRACT FROM AUTHOR]

High-selenium areas are often accompanied by high soil cadmium (Cd) concentrations, which increases the potential risk to agricultural product safety in these selenium-rich areas. Therefore, this study investigated Cd absorption and accumulation in rice plants and explored the effects of rice plant growth and development when different soil amendment combinations were added to the high-Cd soils. Combination design experiments were conducted in different proportions, using biochar, trace element fertilisers and clay minerals as raw materials. Investigations showed that soil amendments significantly improved chlorophyll, root vitality and antioxidant enzyme activity. We also observed that all soil amendment treatments added to the high-Cd soils reduced the water-soluble and ion-exchangeable cadmium content in these soils. However, the maximum effect treatment was 21.46% lower than that of CK (no use of soil amendment). Furthermore, T2 (1.2% rapeseed meal + 0.3% calcium–magnesium–phosphate fertiliser + 2.4% sepiolite + 0.1% silicon fertiliser) and T8 (3% rice biochar + 0.3% silicon–calcium–potassium–magnesium fertiliser + 1.8% vermiculite + 0.1% silicon fertiliser) treatments could significantly reduce malondialdehyde content in leaves, decreasing Cd transfer in the plant. Moreover, while the Cd content in roots, stems and leaves, respectively, was reduced by 57.34% and 71.64% following the T2 treatment, a decrease by 46.20% and 67.03% following the T8 treatment was observed. After comprehensive analysis and comparison, we propose that the T2 and T8 treatments can protect rice growth and reduce Cd accumulation of plant in naturally high-Cd areas. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355 K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274 kb region on chromosome 15 (1,110,567 bp to 1,384,173 bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding. [ABSTRACT FROM AUTHOR]

Mars exploration significantly advances our understanding of planetary evolution, the origin of life, and possibilities for Earth's future. It also holds potential for discovering new mineral resources, energy sources, and potential settlement sites. Navigating Mars' complex environment and unknown terrain is a formidable challenge, particularly for autonomous exploration. The hexapod walking robot, inspired by ant morphology, emerges as a robust solution. This design offers diverse gait options, mechanical redundancy, high fault tolerance, and stability, rendering it well suited for Martian terrain. This paper details the development of an ant-inspired hexapod robot, emphasizing its terrain adaptability on Mars. A novel terrain detection method utilizing a convolutional neural network enables efficient identification of varied terrain types through semantic segmentation of visual images. Additionally, we introduce a comprehensive motion performance evaluation index for the hexapod robot, including speed and stability. These metrics facilitate effective performance assessment in different environments. A key innovation is the proposed gait switching method for the hexapod robot. This approach allows seamless transition between gaits while in motion, enhancing the robot's ability to traverse challenging terrains. The experimental results validate the effectiveness of this method. Utilizing gait switching leads to a significant improvement in robot performance and stability—58.5% and 41.4% better than using tripod and amble gaits, respectively. Compared to single tripod, amble, and wave gaits, the comprehensive motion performance indices of the robot improved by 36.3%, 30.6%, and 41.1%, respectively. This study can provide new ideas and methods for the motion evaluation and adaptive gait switching of multilegged robots in complex terrains. It significantly enhances the mobility and adaptability of such robots in challenging environments, contributing valuable knowledge to the field of planetary exploration robotics. [ABSTRACT FROM AUTHOR]

Over the past decade, the academic community has been increasingly interested in the impact of "unreasonable tasks," a work-related stressor. Extensive research has consistently demonstrated the detrimental effects of these tasks. However, a notable research gap exists in understanding the potential double-edged sword effect they have. To address this gap, the present study developed a moderated dual-mediation model rooted in the cognitive appraisal theory of stress. The primary objective was to investigate the dual nature of unreasonable tasks, specifically examining their influence on thriving at work while considering the underlying factors that shape these effects. Drawing from a sample of 522 participants collected from China, the analysis revealed intriguing findings. On the one hand, unreasonable tasks were found to foster thriving at work by eliciting challenge appraisals. On the other hand, they were also found to impede thriving at work through hindrance appraisals. Moreover, the study uncovered an important moderating role of learning goal orientation for the relationship between unreasonable tasks and cognitive appraisals. These findings make a significant contribution to enhancing understanding of the intricate dynamics associated with unreasonable tasks. They offer pragmatic implications for managers seeking effective strategies to navigate this terrain. [ABSTRACT FROM AUTHOR]

The failure of soil slopes is usually triggered by rainfall infiltration. Under the rainfall infiltrating, soils transform from unsaturated state to saturated state, the matric suction gradually disappears, pore water pressure increases, and the safety factor of soil slopes decreases. In this paper, a novel rigorous limit equilibrium method is proposed to investigate the stability of unsaturated–saturated soil slopes under rainfall infiltration. The force equilibrium conditions along three coordinate axes and the overall moment equilibrium conditions around three coordinate axes are all strictly satisfied, which are more coincident with the real force state of the slopes. In addition, the seepage fields of soil slopes are investigated by using SEEP/W software. Then, the seepage fields are introduced to the rigorous limit equilibrium method. The effects of rainfall intensity, rainfall patterns and rainfall duration on the stability of the unsaturated–saturated soil slopes are investigated using the proposed method. For the unsaturated soils, in which there exists the matric suction, and the matric suction can improve the stability of soil slopes. The safety factors of soil slops under the different rainfall intensity and rainfall patterns are investigated. Moreover, the stability of Fanlingqian slope under rainfall infiltration is analyzed to verify the correctness and precision of the proposed method. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) involving massive neural nodes grouped into different neural layers have been a promising innovation for function approximation and inference, which have been widely applied to various vertical applications such as image recognition. However, the computing burdens to train a DNN model with a limited latency may not be affordable for the user equipment (UE), which consequently motivates the concept of splitting the computations of DNN layers to not only the edge server but also the cloud platform. Despite the availability of more computing resources, computing tasks with such split computing also suffer packet transmission unreliability, latency, and significant energy consumption. A practical scheme to optimally split the computations of DNN layers to the UE, edge, and cloud is thus urgently desired. To solve this optimization, we propose a multi-tier deep reinforcement learning (DRL) scheme for the UE and edge to distributively determine the splitting points to minimize the overall training latency while meeting the constraints of overall energy consumption and image recognition accuracy. The performance evaluation results show the outstanding performance of the proposed design as compared with state-of-the-art schemes, to fully justify the practicability in the next-generation smart networks. [ABSTRACT FROM AUTHOR]

This study explores the purification effect of micro–nano-bubble-based two-stage air flotation on syrup using raw sugar-redissolved syrup as the research object and adopting indicators such as decolourisation and turbidity removal rates. Based on a single-factor experiment, an orthogonal experiment was designed to optimise the process conditions. The optimal process conditions were as follows: magnesium oxide (calculated by magnesium ions), 500 mg/L; pH in the primary air flotation, 11.3; phosphoric acid concentration, 250 mg/L; and pH in the secondary air flotation, 9.0. Under these conditions, the decolourisation rate was 55.83% and the turbidity removal rate was 83.5%. Furthermore, the relevant mechanism is discussed and it is based on the zeta potential of the pure water and syrup systems as well as the infrared absorption spectra of the scum. [ABSTRACT FROM AUTHOR]

Common wisdom suggests that cross-holdings can lead to significant output contraction, and thus hurt consumers. On the contrary, we demonstrate that cross-holdings may increase industry output and benefit consumers in an asymmetric Cournot oligopoly with the presence of a welfare-maximizing tax/subsidy policy. The government will strategically use the tax/subsidy policy to regulate the market outcomes in anticipation of the adverse effect of cross-holdings, which could raise industry output and benefit consumers in certain situations depending on the cost distributions and cross-holding structures. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] is an important seed crop with agricultural sustainability that can be used to meet the growing demand for plant-based oil and protein worldwide. Expanding the cultivation of soybean to high-latitude regions could be an effective strategy for enhancing soybean production. Low temperatures in these regions can inhibit seed germination during the planting season. Despite their importance, many cold tolerance-related genes in soybean remain unidentified. Here, we carried out a genome-wide association study (GWAS) in a diverse soybean population with large variations in cold tolerance-related germination traits. The analyses led to the identification of a total of 46 single-nucleotide polymorphisms (SNPs) that were significantly associated with cold tolerance-related traits. We identified a new locus on chromosome 18, qCold-18–3, that was associated with both the low-temperature germination rate and potential. Furthermore, Abscisic Acid-Deficient4 (GmABA4) was prioritized as the most promising candidate gene. In addition, GmABA4 was strongly induced in a cold-tolerant accession by cold stress during germination, and it contains cis-acting elements associated with low temperature in its promoter region. Haplotype analysis revealed that the accessions harboring Hap3 of GmABA4 were more tolerant to low temperature than those harboring the other haplotypes. In this study, a new cold tolerance-related candidate gene, GmABA4, was identified through GWAS, and further study could advance our understanding of the underlying genetic mechanisms and facilitate the breeding of soybean with improved cold tolerance. [ABSTRACT FROM AUTHOR]

Purpose: Surgery for esophageal squamous cell carcinoma (ESCC) is characterized by a poor prognosis and high complication rate, resulting in a heavy symptom burden and poor health-related quality of life (QOL). We evaluated longitudinal patient-reported outcomes (PROs) to analyze the correlations between symptoms and QOL and their changing characteristics during postoperative rehabilitation. Methods: We investigated patients with ESCC who underwent minimally invasive McKeown esophagectomy at Sichuan Cancer Hospital between April 2019 and December 2019. Longitudinal data of the clinical characteristics and PROs were collected. The MD Anderson Symptom Inventory and European Organization for Research and Treatment of Cancer (EORTC) QOL questionnaires were used to assess symptoms and QOL and compare the trajectories of PROs during the investigation. Results: A total of 244 patients with ESCC were enrolled in this study. Regarding QOL, role and emotional functions returned to baseline at 1 month after surgery, and cognitive and social functions returned to baseline at 3 months after surgery. However, physical function and global QOL did not return to baseline at 1 year after surgery. At 7 days and 1, 3, 6, and 12 months after surgery, the main symptoms of the patients were negatively correlated with physical, role, emotional, cognitive, and social functions and the overall health status (P < 0.05). Conclusion: Patients with ESCC experience reduced health-related QOL and persisting symptoms after minimally invasive McKeown esophagectomy, but a recovery trend was observed within 1 month. The long-term QOL after esophagectomy is acceptable. [ABSTRACT FROM AUTHOR]

Although the number of journals that have adopted the registered report format has increased rapidly in recent years, they still account for only a tiny portion of academic journals. This article provides a summary and overview of the number and proportion of journals that accept the registered report format in the various scientific domains. The Center for Open Science was searched for journals that have adopted the registered report as a regular submission option. The numbers of such journals in each scientific domain were then counted based on their group and category classification in the Journal Citation Reports (JCR). In July 2023, 278 journals had adopted the registered report format, with 186 of these journals included in the JCR. The percentage of journals that had adopted the registered report format ranged from 0 to 7% across the different major research fields (groups in JCR) and from 0 to 34% across the research subfields (categories in JCR). The group "Psychiatry/Psychology" and category "Psychology, Experimental" had the highest percentage of journals that had adopted registered reports. Four large-scale replication projects have been published, focusing on psychology, social science, medicine, and economics, respectively. Although all four studies showed unsatisfactory replication success rates, ≤ 1% of the journals in the corresponding scientific domains had adopted registered reports, with the exception of psychology (7%). To improve research reliability and transparency, it is critical to increase the use of the registered report publishing format. [ABSTRACT FROM AUTHOR]

This article discusses the isolation and characterization of ten terpenoids from the leaves and stems of the plant Alangium barbatum. The plant is widely distributed in Southern China, India, Myanmar, Bhutan, Thailand, and Vietnam and has been used in traditional medicine. Previous studies on the genus Alangium have identified various compounds with interesting biological properties. The compounds isolated in this study were identified using spectroscopic methods and compared with literature data. The article provides detailed information on the chemical structures and properties of each compound, including their molecular formulas, mass spectrometry data, and nuclear magnetic resonance data. This research was supported by the Key Laboratory and Science and Technology Innovation Team of Higher Education in Yunnan, China. [Extracted from the article]

Background: Type I interferons (IFNs) are an essential class of cytokines with antitumor, antiviral and immunoregulatory effects. However, over-productive the type I IFNs are tightly associated with autoimmune disorders. Thus, the induction of type I interferons is precisely regulated to maintain immune hemostasis. This study aimed to identify a novel regulator of type I interferon signaling. Methods and results: Primary BMDMs, isolated from mice, and human cell lines (HEK293 cells, Hela cells) and murine cell line (MEF cells) were cultured to generate in vitro models. After knockdown VRK1, real-time PCR and dual-luciferase reporter assay were performed to determine the expression level of the type I IFNs and ISGs following HTDNA and Poly (dA:dT) stimulation. Additionally, cells were treated with the VRK1 inhibitor, and the impact of VRK1 inhibition was detected. Upon HTDNA and Poly (dA:dT) stimulation, knockdown of VRK1 attenuated the induction of the type I IFNs and ISGs. Consistently, VRK-IN-1, a potent and selective VRK1 inhibitor, significantly suppressed the induction of the type I IFNs and ISGs in human and murine cell lines. Further, VRK-IN-1 inhibited induction of the type I IFNs in mouse primary BMDMs. Intriguingly, VRK1 potentiated the cGAS-STING- IFN-I axis response at STING level. Conclusions: Our study reveals a novel function of VRK1 in regulating the production of type I IFNs. VRK-IN-1 might be a potential lead compound for suppressing aberrant type I IFNs in autoimmune disorders. [ABSTRACT FROM AUTHOR]

All-polymer solar cells (all-PSCs) offer improved morphological and mechanical stability compared with those containing small-molecule-acceptors (SMAs). They can be processed with a broader range of conditions, making them desirable for printing techniques. In this study, we report a high-performance polymer acceptor design based on bithiazole linker (PY-BTz) that are on par with SMAs. We demonstrate that bithiazole induces a more coplanar and ordered conformation compared to bithiophene due to the synergistic effect of non-covalent backbone planarization and reduced steric encumbrances. As a result, PY-BTz shows a significantly higher efficiency of 16.4% in comparison to the polymer acceptors based on commonly used thiophene-based linkers (i.e., PY-2T, 9.8%). Detailed analyses reveal that this improvement is associated with enhanced conjugation along the backbone and closer interchain π-stacking, resulting in higher charge mobilities, suppressed charge recombination, and reduced energetic disorder. Remarkably, an efficiency of 14.7% is realized for all-PSCs that are solution-sheared in ambient conditions, which is among the highest for devices prepared under conditions relevant to scalable printing techniques. This work uncovers a strategy for promoting backbone conjugation and planarization in emerging polymer acceptors that can lead to superior all-PSCs. All-polymer solar cells comprising both polymeric donors and acceptors offer better morphological and mechanical stability, and a broader processing window for printing. Here, the authors report a polymer acceptor based on bithiazole linker with more coplanar and ordered molecular conformation. [ABSTRACT FROM AUTHOR]

In recent years, under the influence of changes in natural conditions and human social activities, the issue of global warming has become increasingly prominent. So it is crucial to effectively predict the future trend of temperature changes. In this regard, from the perspective of statistical models, this paper studies a new combination model, namely the new GM-ARIMA model, based on linear combination of weight calculation. Furthermore, it also analyzes the prediction effect through comparative experiments and uses multiple performance evaluation indicators, so as to prove the scientificity and effectiveness of the proposed combination model in this paper. Finally, according to the experimental results, it can be clearly found that among the four methods for calculating the weights of linear combination, namely the equal weight method, the variance reciprocal method, the residual reciprocal method and the standard deviation method, the combination model using the standard deviation method for calculation has the highest prediction accuracy, so it is finally decided to use this method to build the combination model (namely S-GM-ARIMA). In addition, the experimental results show that the S-GM-ARIMA model achieves the best prediction results compared to other existing prediction models. Among them, the MAE of S-GM-ARIMA decreases by 10.38% and 16.22% compared to the GM(1,1) model and ARIMA model, respectively. The RMSE of S-GM-ARIMA decreases by 4.52% and 10.03% compared to the GM(1,1) model and ARIMA model, respectively. And the MAPE of S-GM-ARIMA decreases by 10.34% and 16.17% compared to the GM(1,1) model and ARIMA model, respectively. Therefore, the new GM-ARIMA combination model studied in this paper has relatively higher prediction accuracy when making predictions, and can be used to make more effective and accurate predictions of global average temperature. This study can also provide reference for countries in making decisions to address global warming issues. [ABSTRACT FROM AUTHOR]

Background: Cancer is still a leading cause of mortality. Over the years, cancer therapy has undergone significant advances driven by advancements in science and technology. A promising area of drug discovery in this field involves the development of therapeutic targets for cancer treatment. The urgent need to identify new pharmacological targets arises from the impact of tumor resistance on the effectiveness of current medications. Specifically, the RPS6KB2 gene on chromosome 11 has been implicated in cell cycle regulation and exhibits higher expression levels in tumor tissue. Given this association, there is a potential for this gene to serve as a target for cancer treatment. Methods: We conducted an analysis using the GTEx, TCGA, and CCLE databases to explore the relationship between RPS6KB2 and immune infiltration, the tumor microenvironment (TME), microsatellite instability (MSI), and more. Cell proliferation was assessed using EDU detection, while cell invasion and migration were evaluated via wound healing and Transwell assays. Additionally, western blot analysis was employed to measure expression of Bax, Bcl-2, MMP2, MMP9, PCNA, and proinflammatory factors. Results: Through data analysis and molecular biology methods, our study carefully examined the potential role of RPS6KB2 in cancer therapy. The data revealed that RPS6KB2 is aberrantly expressed in most cancers and is associated with poor prognosis. Further analysis indicated its involvement in cancer cell apoptosis and migration, as well as its role in cancer immune processes. We validated the significance of RPS6KB2 in hepatocellular carcinoma (HCC), highlighting its capacity to upregulate proinflammatory cytokines. Conclusion: Our research indicates that RPS6KB2 is a prognostic biomarker associated with immune infiltration in cancer that can affect antitumor immunity by increasing secretion of proinflammatory factors, providing a potential drug target for cancer treatment. [ABSTRACT FROM AUTHOR]

Piezoelectrics are a class of functional materials that have been extensively used for application in modern electro-mechanical and mechatronics technologies. The sign of longitudinal piezoelectric coefficients is typically positive but recently a few ferroelectrics, such as ferroelectric polymer poly(vinylidene fluoride) and van der Waals ferroelectric CuInP2S6, were experimentally found to have negative piezoelectricity. Here, using first-principles calculation and measurements, we show that the sign of the longitudinal linear piezoelectric coefficient of HfO2 can be tuned from positive to negative via epitaxial strain. Nonlinear and even parabolic piezoelectric behaviors are further found at tensile epitaxial strain. This parabolic piezoelectric behavior implies that the polarization decreases when increasing the magnitude of either compressive or tensile longitudinal strain, or, equivalently, that the strain increases when increasing the magnitude of electric field being either parallel or antiparallel to the direction of polarization. The unusual piezoelectric effects are from the chemical coordination of the active oxygen atoms. These striking piezoelectric features of positive and negative sign, as well as linear and parabolical behaviors, expand the current knowledge in piezoelectricity and broaden the potential of piezoelectric applications towards electro-mechanical and communications technology. The sign of longitudinal piezoelectric coefficients is typically positive. Here, the authors tune the sign of the linear piezoelectric coefficient of HfO2 from positive to negative via epitaxial strain, finding nonlinear and parabolic piezoelectric behaviors at tensile epitaxial strain. [ABSTRACT FROM AUTHOR]

The fully automatic chromosome analysis system plays an important role in the detection of genetic diseases, which in turn can reduce the diagnosis burden for cytogenetic experts. Chromosome segmentation is a critical step for such a system. However, due to the non-rigid structure of chromosomes, chromosomes may curve in any direction, and two or more chromosomes may touch or overlap to form unpredictable chromosome clusters in metaphase chromosome images, leading to automatic chromosome segmentation as a challenge. In this paper, we propose an automatic progressive segmentation approach to perform the entire metaphase chromosome image segmentation using deep learning with traditional image processing. It follows three stages. In the first stage, thresholding-based and geometric-based methods are employed to divide all chromosomes as single ones and chromosome clusters. To tackle the segmentation for unpredictable chromosome clusters, we first present a new chromosome cluster identification network named CCI-Net to classify all chromosome clusters into different types in the second stage, and then in the third stage, we combine traditional image processing with deep CNNs to accomplish chromosome instance segmentation from different types of clusters. Evaluation results on a clinical dataset of 1148 metaphase chromosome images show that the proposed automatic progressive segmentation method achieves 94.60% chromosome cluster identification accuracy and 99.15% instance segmentation accuracy. The experimental results exhibit that our proposed approach can effectively identify chromosome clusters and successfully perform fully automatic chromosome segmentation. [ABSTRACT FROM AUTHOR]

This article discusses the isolation and characterization of 15 phenolic compounds from the leaves and stems of Caesalpinia enneaphylla, a plant used in Chinese traditional medicine. The compounds include flavonoids, lignans, coumarin, and simple aromatics. The chemical structures of these compounds were identified through spectroscopic analysis. This research contributes to the search for new bioactive metabolites from Caesalpinia enneaphylla and provides valuable information for further studies on the medicinal properties of this plant. The document provides information on various compounds isolated from C. enneaphylla, including their chemical formula, physical properties, and spectroscopic data. The research was supported by the Key Laboratory and Science and Technology Innovation Team of Higher Education in Yunnan, China. [Extracted from the article]

MIL-101(Fe)/WS2 catalyst was composited using a solvothermal method. To study the physical and chemical properties of the composite material, a series of characterizations such as scanning electron microscope (SEM), X-ray diffraction (XRD), and catalytic experiments were carried out. The photocatalysis of the prepared catalyst in the degradation of tetracycline was investigated using persulfate (PS, Na2S2O8) as a cocatalyst under visible light illumination. The above system can remove about 80% of tetracycline within 40 min. After three cyclic experiments, the material showed good recycling. According to material characterization and various experimental results, the enhanced performance of the material was attributed to the reduction of the recombination efficiency of photogenerated e− and h+, and activated persulfate to produce a large number of free radicals such as O2•−, SO4•− and 1O2 produced by the active sites provided by the catalyst's high specific surface area. [ABSTRACT FROM AUTHOR]

In this paper, we consider the backward problem for a time fractional diffusion-wave equation in a cylinder. The ill-posedness and a conditional stability of the inverse problem are proved. Based on the generalized quasi-boundary value regularization method, we propose an iterative generalized quasi-boundary value regularization method to deal with the inverse problem, and this iterative method has a higher convergence rate. The convergence rates of the regularized solution under an a priori regularization parameter choice rule and an a posteriori regularization parameter choice rule are obtained. Numerical examples illustrate the effectiveness and stability of our proposed method. [ABSTRACT FROM AUTHOR]

The combination of feature extraction and classification methods is an often used approach for wafer map failure pattern recognition. Recently, the convolutional neural network (CNN) method is used to raw wafer map data without feature extraction. CNN can improve the accuracy, but the drawback is the expensive computation cost. In our study, we have extracted local property analysis based features and used them with the traditional classification methods, ensemble methods, and CNN for wafer map failure pattern recognition. The decision tree showed better performance than the other methods when evaluating single traditional classification methods. Therefore, we used the decision tree as the base classifier of the proposed ensemble learning. We built a constituent model on a single type of feature set first and then made an ensemble of models to produce the final decision. We found that it is better than directly building a model on total features. Also, we have tested and compared CNN on extracted feature sets and raw wafer map image data. The results showed that raw image based CNN outperforms extracted features under the same number of epochs. However, the training cost of the raw image is much expensive. Furthermore, the performance of extracted features becomes closer to the raw image when increasing the number of epochs with a much lower training cost. [ABSTRACT FROM AUTHOR]

Corona textures, characterized by specific mineral assemblages as layers between existing phases, are frequently observed in high-grade metamorphic rocks. The mechanisms of corona formation have been extensively investigated, however direct dating of corona phases has rarely to be attempted. In order to decipher the timing and duration of corona formation and its implications for metamorphic processes, an integrated garnet Lu–Hf and Sm–Nd and zircon U–Pb petrochronological study was conducted on a corona-bearing granulite from the Miyun region in the North China Craton. The Miyun region, located at the joint area of the Archean Eastern Block and the Paleoproterozoic Trans-North China Orogen, offers a distinctive opportunity to study polymetamorphic processes within the North China Craton. The sample shows a corona texture, primarily composed of garnet, minor clinopyroxene and quartz, that formed at the boundary between plagioclase and orthopyroxene. Pseudosection modelling for the effective bulk composition of reactive domains and conventional thermobarometric calculations indicate that the anhydrous corona assemblage (comprising clinopyroxene, garnet and quartz) formed at ~ 0.9 GPa and ~ 740 ℃. The subsequent hydrous retrogression took place at ~ 0.5 GPa and ~ 670 ℃ and led to the growth of amphibole and biotite. A Lu–Hf garnet date of 1864 ± 3 Ma is significantly younger than the U–Pb date of ca. 2454 Ma for metamorphic zircons in the sample, consistent with the disequilibrium partitioning of rare earth elements between the two phases. The well-preserved Lu zoning in garnet supports the interpretation that the Lu–Hf date represents the age of garnet growth and approximates the timing of formation of the anhydrous corona assemblage. Thus, the U–Pb age reflects a distinct Archean metamorphic event that has been widely documented in high-grade rocks across the Eastern Block of the North China Craton. The garnet Sm–Nd date of 1817 ± 6 Ma is indistinguishable from an amphibole-biotite Lu–Hf date of 1819 ± 16 Ma and ~ 47 Myr younger than the corresponding garnet Lu–Hf date. The younger Sm–Nd age represents the timing of cooling and post-dates retrogression. The Paleoproterozoic and Archean ages in the Miyun granulite align with the major tectonic events in the Trans-North China Orogen and the Eastern Block, respectively. This consistency suggests that the Miyun region likely experienced concurrent metamorphic events in both the Trans-North China Orogen and the Eastern Block. This texture-based Lu–Hf and Sm–Nd dating approach has wide applicability for rocks with explicit textures, facilitating precise extraction of temporal intervals in the metamorphic process. [ABSTRACT FROM AUTHOR]

Feasibility and applicability of rhamnolipid (RL) microbial biosurfactant-based reverse micellar non-aqueous system in different solvent medium for dyeing of cotton fabrics was investigated. In this study, several solvents, including heptane, octane, nonane, decamethylcyclopentasiloxane (D5), and paraffin liquid (PL), were chosen as the dyeing medium for non-aqueous dyeing of cotton fabrics with fixed dyeing parameters. The dyeing properties of these RL reverse micellar dyed samples in different solvent medium were examined and compared with the conventional water-dyed samples in terms of color yield (K/Ssum value), CIE L*a*b* values, color levelness and reflectance. Most non-aqueous RL reverse micellar dyed samples exhibited better color yield than conventional water-dyed samples. The surface morphology of dyed cotton samples and the dye encapsulation morphology in different solvent medium were observed by SEM and TEM, respectively. Most non-aqueous dyed samples yielded good to excellent levelness comparable to water-dyed samples. However, poor levelness and bad levelness were found for D5-and PL-dyed samples. Further modification of dyeing parameters would be needed to obtain the best dyeing results for D5-dyed and PL-dyed samples. [ABSTRACT FROM AUTHOR]

In the article, we develop a quantile varying-coefficient structural equation model in which the coefficients are allowed to vary as smooth functions of other variable at different quantiles. A new local-polynomial-based (LP) estimation method is proposed for estimating the model flexibly. A class of estimated loading coefficients and path coefficients is obtained to capture the dynamic relations among latent variables and observed variables at different quantiles. In addition, the distinct advantages of the proposed LP estimation method consists of making minimal assumptions on the distribution of data and enabling to calculate the values of latent variables. Simulation studies are carried out to further investigate the performances of the proposed LP estimation method. Finally, we further illustrate our proposed model and estimation method by two real data examples: Air pollution monitoring and talent flow exploring. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy (DMD) is a genetic disease characterized by progressive muscle weakness with increased neuromechanical challenge and fall risks, especially during obstructed locomotion. This study aimed to identify the kinematic strategies for obstacle-crossing in DMD via synthesizing the changes in the joint kinematics and associated end-point control. Fourteen boys with DMD (age: 9.0 ± 2.5 years) and fourteen typically developed controls (age: 9.0 ± 2.8 years) each crossed obstacles of three different heights (10%, 20% and 30% of leg length) while the angular motions of the trunk-pelvis-leg apparatus and foot-obstacle clearances were measured. Two-way analyses of variance were used to analyze group and obstacle height effects. Compared to the controls, the DMD group crossed obstacles with significantly increased step width, but decreased crossing speed, crossing step length, trailing toe-obstacle clearance and leading heel-obstacle horizontal distance (p < 0.05). When the leading toe was above the obstacle, the patients showed significantly increased pelvic hiking, pelvic and trunk anterior tilt and ankle plantarflexion, but decreased hip flexion in both limbs (p < 0.05). Similar kinematic changes were found during trailing-limb crossing, except for an additional increase in swing-hip abduction and decrease in contralateral trunk side-bending and stance-knee flexion. Patients with DMD crossed obstacles via a specific kinematic strategy with altered end-point control, predisposing them to a greater risk of tripping during trailing-limb crossing. These results suggest that crossing kinematics in DMD should be monitored—especially in the proximal segments of the pelvis-leg apparatus—that may lead to an increased risk of falling. [ABSTRACT FROM AUTHOR]

We study quantum hypothesis testing between orthogonal states under restricted local measurements in the many-copy scenario. For testing arbitrary multipartite entangled pure state against its orthogonal complement state via the local operation and classical communication (LOCC) operation, we prove that the optimal average error probability always decays exponentially in the number of copies. Second, we provide a sufficient condition for the LOCC operations to achieve the same performance as the positive-partial-transpose (PPT) operations. We further show that testing a maximally entangled state against its orthogonal complement and testing extremal Werner states both fulfill the above-mentioned condition. Hence, we determine the explicit expressions for the optimal average error probability, the optimal trade-off between the type-I and type-II errors, and the associated Chernoff, Stein, Hoeffding, and strong converse exponents. Then, we show an infinite asymptotic separation between the separable (SEP) and PPT operations by providing a pair of states constructed from an unextendible product basis (UPB). The quantum states can be distinguished perfectly by PPT operations, while the optimal error probability, with SEP operations, admits an exponential lower bound. On the technical side, we prove this result by providing a quantitative version of the well-known statement that the tensor product of UPBs is a UPB. [ABSTRACT FROM AUTHOR]