Nanning Normal University

Abstract Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

The coronavirus disease (COVID-19) outbreak in December has seen more than 76,000 cases in China, causing more than 3,000 medical staff infections. As the disease is highly contagious, can be fatal in severe cases, and there are no specific medicines, it poses a huge threat to the life and health of nurses, leading to a severe impact on their emotional responses and coping strategies. Therefore, this study will investigate nurses' emotional responses and coping styles, and conduct a comparative study with nursing college students. This study was conducted through the online survey 'questionnaire star' from February 1st to February 20th, 2020 in Anhui Province, using the snowball sampling method to invite subjects. The results found that women showed more severe anxiety and fear than men. Participants from cities exhibited these symptoms more than participants from rural areas, however rural participants experienced more sadness than urban participants. The nearer a COVID-19 zone is to the participants, the stronger the anxiety and anger. The COVID-19 outbreak has placed immense pressure on hospitals and those nurses at the frontline are more seriously affected. Hospitals should focus on providing psychological support to nurses and training in coping strategies.

When the integrity of the skin got damaged, an endogenous electric field will be generated in the wound and a series of physiological reactions will be initiated to close the wound. The existence of the endogenous electric field of the wound has a promoting effect on all stages of wound healing. For wounds that cannot heal on their own, the exogenous electric field can assist the treatment. In this review, the effects of exogenous electrical stimulation on wound healing, such as the inflammation phase, blood flow, cell proliferation and migration, and the wound scarring is overviewed. This article also reviews the new electrical stimulation methods that have emerged in recent years, such as small power supplies, nanogenerators (NGs), and other physical, chemical or biological strategies. These new electrical stimulation methods and devices are safe, low-cost, stable, and small in size. The challenge and perspective are discussed for the future trends of the electrical stimulation treatment in accelerating skin wound healing.

A sensor is a tool used to directly measure the test compound (analyte) in a sample. Ideally, such a device is capable of continuous and reversible response and should not damage the sample. Nanosensor refers to a system in which at least one of the nanostructures is used to detect gases, chemicals, biological agents, electric fields, light, heat, etc. in its construction. The use of nanomaterials significantly increases the sensitivity of the system. In biosensors, the part of the system used to attach to the analyte and specifically detect it is a biological element (such as a DNA strand, antibody, enzyme, whole cell). The “Nano Biosensors” series reviews various types of biosensors and biochips (including an array of biosensors), emphasizing the role of nanostructures, developed for medical and biological applications. Nano Biosensors Electrochemical sensors are sensors that use the biological element as a diagnostic component and the electrode as a transducer. The use of nanostructures in these systems is usually done to fill the gap between the converter and the bioreceptor, which is at the nanoscale. Given the nature of the biomaterial detection process, electrochemical biosensors are divided into catalytic and propulsion. Common electrochemical techniques common in sensors include potentiometric, chronometry, voltammetry, impedance measurement, and field effect transistor (FET). Simultaneous use of the advantages of nanostructures and electrochemical techniques has led to the emergence of sensors with high sensitivity and decomposition power. The use of nanostructures in these sensors is usually done to fill the gap between the converter and the bioreceptor, which is at the nanoscale. Various types of nanostructures including nanoparticles, nanotubes and nanowires, nanopores, self-adhesive monolayers and nanocomposites can be used to improve the performance and efficiency of sensors in their structure. Simultaneous use of the advantages of nanostructures and electrochemical techniques has led to the emergence of sensors with high sensitivity and decomposition power.

Ultrasmall black phosphorus quantum dots (BPQDs) with an average size of 2.1 ± 0.9 nm are synthesized by using a solvothermal method in a N ‐methyl‐2‐pyrrolidone solution. Verified by femto‐second laser Z‐scan measurement, BPQDs exhibit excellent nonlinear optical response with a modulation depth of about 36% and a saturable intensity of about 3.3 GW cm −2 . By using BPQDs as optical saturable absorber, the ultrashort pulse with a pulse duration of about 1.08 ps centered at a wavelength of 1567.5 nm is generated in mode‐locked fiber laser. These results suggest that BPQDs may be developed as another kind of promising nanomaterial for ultrafast photonics.

Photocatalytic hydrogen evolution from water has received enormous attention due to its ability to address a number of global environmental and energy-related issues. Here, we synthesize 2D/2D Ti3C2/g-C3N4 composites by electrostatic self-assembly technique and demonstrate their use as photocatalysts for hydrogen evolution under visible light irradiation. The optimized Ti3C2/g-C3N4 composite exhibited a 10 times higher photocatalytic hydrogen evolution performance (72.3 μmol h-1 gcat-1) than that of pristine g-C3N4 (7.1 μmol h-1 gcat-1). Such enhanced photocatalytic performance was due to the formation of 2D/2D heterojunctions in the Ti3C2/g-C3N4 composites. The intimate contact between the monolayer Ti3C2 and g-C3N4 nanosheets promotes the separation of photogenerated charge carriers at the Ti3C2/g-C3N4 interface. Furthermore, the ultrahigh conductivity of Ti3C2 and the Schottky junction formed between g-C3N4/MXene interfaces facilitate the photoinduced electron transfer and suppress the recombination with photogenerated holes. This work demonstrates that the 2D/2D Ti3C2/g-C3N4 composites are promising photocatalysts thanks to the ultrathin MXenes as efficient co-catalysts for photocatalytic hydrogen production.

Aliovalent A-site engineering enables superior energy storage density in AgNbO₃ lead-free antiferroelectric ceramics.

Abstract Background Affected by a Corona Virus Disease 2019 (COVID-19) outbreak, Since December 2019, there have been more than 76,000 cases of COVID-19 in China, causing more than 3,000 medical staff infections. Due to COVID-19 spreads quickly, is highly contagious, and can be fatal in severe cases, and there are no specific medicines, it poses a huge threat to the life and health of nurses and has a large impact on their emotional responses and coping strategies. Methods This study conducted an online questionnaire survey from February 1 to 9, 2020 to investigate the current state of emotional responses and coping strategies of nurses and college nursing students in Anhui Province. This study used a modified Brief COPE (Carver, 1997) and a emotional responses scale. Results The results found that women showed more severe anxiety and fear than men. Participants from cities showed more anxiety and fear than participants from rural, but rural participants showed more sadness than urban participants. The closer COVID-19 is to the participants, the stronger the anxiety and anger. Compared with Nursing college students, nurses have stronger emotional responses and are more willing to use Problem-focused coping. People may have a cycle of “the more fear, the more problem-focused coping”. And people may “The more angry, the more emotion-focused coping”, “the more problem-focused coping, the more anxious, the more angry, the more sadness”. Conclusion COVID-19 is a pressure source with great influence, both for individuals and for the social public groups. Different individuals and groups may experience different levels of psychological crisis, and those nurses at the core of the incident are affected. Hospitals should focus on providing psychological support to nurses and providing timely psychological assistance and training in coping strategies.Improving nurses’ ability to regulate emotions and effective coping strategies, providing a strong guarantee for resolutely winning the battle against epidemic prevention and control.

In this review, intra- and intermolecular engineering strategies for improving the efficiencies of porphyrin based dye-sensitized solar cells are briefly summarized, revealing the in-depth structure–photovoltaic performance correlations.

The transition from childhood to adolescence is marked by pronounced shifts in brain structure and function that coincide with the development of physical, cognitive, and social abilities. Prior work in adult populations has characterized the topographical organization of the cortex, revealing macroscale functional gradients that extend from unimodal (somatosensory/motor and visual) regions through the cortical association areas that underpin complex cognition in humans. However, the presence of these core functional gradients across development as well as their maturational course have yet to be established. Here, leveraging 378 resting-state functional MRI scans from 190 healthy individuals aged 6 to 17 y old, we demonstrate that the transition from childhood to adolescence is reflected in the gradual maturation of gradient patterns across the cortical sheet. In children, the overarching organizational gradient is anchored within the unimodal cortex, between somatosensory/motor and visual territories. Conversely, in adolescence, the principal gradient of connectivity transitions into an adult-like spatial framework, with the default network at the opposite end of a spectrum from primary sensory and motor regions. The observed gradient transitions are gradually refined with age, reaching a sharp inflection point in 13 and 14 y olds. Functional maturation was nonuniformly distributed across cortical networks. Unimodal networks reached their mature positions early in development, while association regions, in particular the medial prefrontal cortex, reached a later peak during adolescence. These data reveal age-dependent changes in the macroscale organization of the cortex and suggest the scheduled maturation of functional gradient patterns may be critically important for understanding how cognitive and behavioral capabilities are refined across development.

Long short-term memory (LSTM) neural networks and attention mechanism have been widely used in sentiment representation learning and detection of texts. However, most of the existing deep learning models for text sentiment analysis ignore emotion's modulation effect on sentiment feature extraction, and the attention mechanisms of these deep neural network architectures are based on word- or sentence-level abstractions. Ignoring higher level abstractions may pose a negative effect on learning text sentiment features and further degrade sentiment classification performance. To address this issue, in this article, a novel model named AEC-LSTM is proposed for text sentiment detection, which aims to improve the LSTM network by integrating emotional intelligence (EI) and attention mechanism. Specifically, an emotion-enhanced LSTM, named ELSTM, is first devised by utilizing EI to improve the feature learning ability of LSTM networks, which accomplishes its emotion modulation of learning system via the proposed emotion modulator and emotion estimator. In order to better capture various structure patterns in text sequence, ELSTM is further integrated with other operations, including convolution, pooling, and concatenation. Then, topic-level attention mechanism is proposed to adaptively adjust the weight of text hidden representation. With the introduction of EI and attention mechanism, sentiment representation and classification can be more effectively achieved by utilizing sentiment semantic information hidden in text topic and context. Experiments on real-world data sets show that our approach can improve sentiment classification performance effectively and outperform state-of-the-art deep learning-based methods significantly.

Tourists like to share their memorable experiences on mobile social media. This sharing behaviour may stimulate tourists’ future holiday intentions. Within an ethnic minority tourism setting in Guangxi Zhuang, this study examines the relationship between sharing memorable ethnic minority tourism experiences (MEMTEs) on mobile social media and intentions to visit other ethnic destinations. Partial least squares structural equation modelling and Sobel tests were performed to analyse survey data from 279 tourists. The results indicate that three dimensions of MEMTEs (scenery, entertainment, and interaction) affect tourists’ sharing behaviour and that sharing behaviour during trips mediates the effects of during-trip experiences (scenery and interaction) on tourists’ post-trip intentions to visit other destinations. This study explores MEMTE as the source of during- and post-trip behaviours, explains the role of sharing experiences, contributes a scale for measuring sharing behaviour, and makes recommendations for developing ethnic minority tourism.

Lead-free antimony based metal halide perovskites were used as photoactive materials in solar cell devices and exhibited maximum power conversion efficiency of 2.04%.

High energy density was achieved by designing a AgNbO₃ based lead-free system.

The study of land use transition has generally become an important breakthrough point to deeply understand the human-land interaction and reveal major socio-economic development issues and related environmental effects. Attempting to provide scientific support for sustainable land use and environmental management, this review systematically analyzes the overall picture, development trends, key fields and hot topics of land use transition research in the past two decades from a comprehensive perspective, which incorporates two complementary parts including the systematic quantitative literature review (based on CiteSpace) and the traditional literature review. The results reveal that: a. current research presents three characteristics, i.e., focusing on complex social issues, driven by realistic demand, and research branches becoming clearer and more systematic; b. there are four key fields and hot topics in land use transition research, i.e., i. theories and hypothesis of land use transition; ii. measuring land use transition; iii. the impacts of land use transition on “social-economic-ecological” system; iv. drivers and regulation of land use transition. However, challenges remain, current land use transition research is still to some extent fragmented, and it should be enriched by integrating with land system science. The dominant morphology biased should be redressed by underlining the recessive morphology transition process. Meanwhile, new techniques and methods are necessary to observe, track, monitor and model the recessive attributes. Finally, distant drivers of land use transition should not be ignored in this rapidly globalizing world.

Abstract Human respiration is an indispensable physiological behavior of the body, which is an important indicator to evaluate health status, especially for sleep‐related diseases. A real‐time respiratory monitoring and sleep breathing detecting system with convenience, high sensitivity, simple fabrication, and wearing comfort still remains a challenge and urgently desirable. Here, a breathable, highly sensitive, and self‐powered electronic skin (e‐skin) based on a triboelectric nanogenerator (TENG) is reported for real‐time respiratory monitoring and obstructive sleep apnea‐hypopnea syndrome (OSAHS) diagnosis. By using multilayer polyacrylonitrile and “polyamide 66” nanofibers as the contact pairs, and deposited gold as the electrodes, a contact‐separation type of TENG‐based all‐nanofiber e‐skin is developed. The e‐skin has a peak power density of 330 mW m −2 , high pressure sensitivity of 0.217 kPa −1 , excellent working stability, and good air permeability. Therefore, the e‐skin is simultaneously capable of energy autonomy and accurate real‐time subtle respiration monitoring. Meanwhile, a self‐powered diagnostic system for real‐time detection and severity evaluation of obstructive sleep apnea‐hypopnea syndrome are further developed to prevent the occurrence of OSAHS, delay its development, and improve sleep quality. This study hopes to pave a new and practical pathway for real‐time respiration monitoring and sleep breathing diseases clinical detection.

Abstract As a new kind of two‐dimensional material, MXene is first discovered in 2011. Because of its diverse chemical composition with excellent physical and chemical properties, the family of MXenes has attracted people's extensive research interest in various fields, such as energy storage, environment, catalysis and biomedical applications, among which the researches about biomedical applications are relatively more burgeoning than that in other fields. This review concludes the progress and biomedical applications of MXenes. Firstly, the development background of MXenes is introduced. Then, the synthesis methods, structures and properties, surface modification strategies, biomedical applications, cytotoxicity and biocompatibility of MXenes are demonstrated in each chapter successively. At last, the materials of MXenes are summarized, besides, the opportunities and challenges faced by MXenes in the future are prospected. This review will provide some help for the advancement and application of MXenes.

An ultrahigh energy storage density up to 4.87 J cm⁻³ was achieved in Sm/Ta co-doped AgNbO₃ ceramics, by decreasing the cation displacement and [Nb/TaO₆] octahedral tilting angle.

As a ubiquitous degradation process in cells, autophagy plays important roles in various biological activities. However, the abnormality of autophagy is closely related to many diseases, such as aging, neurological disorder, and cancer. Thus, monitoring the process of autophagy in living cells has high significance in biological studies and diagnosis of related diseases. In order to real-time and in situ monitor the process of autophagy, various organic fluorescent probes have been explored in recent years owing to the advantages such as handy staining processes, flexible molecular design strategies, and near-nondestructive detection. However, this interesting and frontier topic has not been reviewed so far. In this tutorial review, we will focus on the latest breakthrough results of organic fluorescent probes in monitoring autophagy of living cells, especially the probe design strategies based on the several microenvironment changes of the autophagy process, and the responding mechanisms and bio-imaging applications in the autophagy process. In addition, we will discuss the shortcomings and limitations of the probes developed, such as susceptible to interference, unable to monitor the whole process, and lack of clinical applications. Finally, we will highlight some challenges and further opportunities in this field. This tutorial review may promote the development of more robust fluorescent probes to further reveal the mechanisms of autophagy, which is the basis of degradation and recycling of cell components.

There are thousands of lipid species existing in cells, which belong to eight different categories. Lipids are the essential building blocks of cells. Recent studies have started to unveil the important functions of lipids in regulating cell metabolism. However, we are still at a very early stage in fully understanding the physiological and pathological functions of lipids. The application of lipidomics for studying lipid metabolism can provide a direct readout of the cellular status and broadens our understanding of the mechanisms that underpin metabolic disease states. This review provides an introduction to lipid metabolism and its role in modulating homeostasis and immunity. We also describe representative applications of lipidomics for studying lipid metabolism in inflammation-related diseases.