Developing an abnormal high-Na-content P2-type layered oxide cathode with near-zero-strain for high-performance sodium-ion batteries.

Layered transition metal oxides (NaxTMO2) possess attractive features such as large specific capacity, high ionic conductivity, and a scalable synthesis process, making them a promising cathode candidate for sodium-ion batteries (SIBs). However, NaxTMO2 suffer from multiple phase transitions and Na+/vacancy ordering upon Na+ insertion/extraction, which is detrimental to their electrochemical performance. Herein, we developed a novel cathode material that exhibits an abnormal P2-type structure at a stoichiometric content of Na up to 1. The cathode material delivers a reversible capacity of 108 mA h g-1 at 0.2C and 97 mA h g-1 at 2C, retaining a capacity retention of 76.15% after 200 cycles within 2.0-4.3 V. In situ diffraction studies demonstrated that this material exhibits an absolute solid-solution reaction with a low volume change of 0.8% during cycling. This near-zero-strain characteristic enables a highly stabilized crystal structure for Na+ storage, contributing to a significant improvement in battery performance. Overall, this work presents a simple yet effective approach to realizing high Na content in P2-type layered oxides, offering new opportunities for high-performance SIB cathode materials.

Routes to high-performance layered oxide cathodes for sodium-ion batteries.

Sodium-ion batteries (SIBs) are experiencing a large-scale renaissance to supplement or replace expensive lithium-ion batteries (LIBs) and low energy density lead-acid batteries in electrical energy storage systems and other applications. In this case, layered oxide materials have become one of the most popular cathode candidates for SIBs because of their low cost and comparatively facile synthesis method. However, the intrinsic shortcomings of layered oxide cathodes, which severely limit their commercialization process, urgently need to be addressed. In this review, inherent challenges associated with layered oxide cathodes for SIBs, such as their irreversible multiphase transition, poor air stability, and low energy density, are systematically summarized and discussed, together with strategies to overcome these dilemmas through bulk phase modulation, surface/interface modification, functional structure manipulation, and cationic and anionic redox optimization. Emphasis is placed on investigating variations in the chemical composition and structural configuration of layered oxide cathodes and how they affect the electrochemical behavior of the cathodes to illustrate how these issues can be addressed. The summary of failure mechanisms and corresponding modification strategies of layered oxide cathodes presented herein provides a valuable reference for scientific and practical issues related to the development of SIBs.

Nickel Nanoparticles Protruding from Molybdenum Carbide Micropillars with Carbon Layer-Protected Biphasic 0D/1D Heterostructures for Efficient Water Splitting.

It remains a tremendous challenge to achieve high-efficiency bifunctional electrocatalysts for both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) for hydrogen production by water splitting. Herein, a novel hybrid of 0D nickel nanoparticles dispersed on the one-dimensional (1D) molybdenum carbide micropillars embedded in the carbon layers (Ni/Mo2C@C) was successfully prepared on nickel foam by a facile pyrolysis strategy. During the synthesis process, the nickel nanoparticles and molybdenum carbide were simultaneously generated under H2 and C2H2 mixed atmospheres and conformally encapsulated in the carbon layers. Benefiting from the distinctive 0D/1D heterostructure and the synergistic effect of the biphasic Mo2C and Ni together with the protective effect of the carbon layer, the reduced activation energy barriers and fast catalytic reaction kinetics can be achieved, resulting in a small overpotential of 96 mV for the HER and 266 mV for the OER at the current density of 10 mA cm-2 together with excellent durability in 1.0 M KOH electrolyte. In addition, using the developed Ni/Mo2C@C as both the cathode and anode, the constructed electrolyzer exhibits a small voltage of 1.55 V for the overall water splitting. The novel designed Ni/Mo2C@C may give inspiration for the development of efficient bifunctional catalysts with low-cost transition metal elements for water splitting.

Facilitating Layered Oxide Cathodes Based on Orbital Hybridization for Sodium-Ion Batteries: Marvelous Air Stability, Controllable High Voltage, and Anion Redox Chemistry.

Layered oxides have become the research focus of cathode materials for sodium-ion batteries (SIBs) due to the low cost, simple synthesis process, and high specific capacity. However, the poor air stability, unstable phase structure under high voltage, and slow anionic redox kinetics hinder their commercial application. In recent years, the concept of manipulating orbital hybridization has been proposed to simultaneously regulate the microelectronic structure and modify the surface chemistry environment intrinsically. In this review, the hybridization modes between atoms in 3d/4d transition metal (TM) orbitals and O 2p orbitals near the region of the Fermi energy level (EF) are summarized based on orbital hybridization theory and first-principles calculations as well as various sophisticated characterizations. Furthermore, the underlying mechanisms are explored from macro-scale to micro-scale, including enhancing air stability, modulating high working voltage, and stabilizing anionic redox chemistry. Meanwhile, the origin, formation conditions, and different types of orbital hybridization, as well as its application in layered oxide cathodes are presented, which provide insights into the design and preparation of cathode materials. Ultimately, the main challenges in the development of orbital hybridization and its potential for the production application are also discussed, pointing out the route for high-performance practical sodium layered oxide cathodes.

Investigation into white matter microstructure differences in visual training by using an automated fiber tract subclassification segmentation quantification method.

Visual training has emerged as a useful framework for investigating training-related brain plasticity, a highly complex task involving the interaction of visual orientation, attention, reasoning, and cognitive functions. However, the effects of long-term visual training on microstructural changes within white matter (WM) is poorly understood. Therefore, a set of visual training programs was designed, and automated fiber tract subclassification segmentation quantification based on diffusion magnetic resonance imaging was performed to obtain the anatomical changes in the brains of visual trainees. First, 40 healthy matched participants were randomly assigned to the training group or the control group. The training group underwent 10 consecutive weeks of visual training. Then, the fiber tracts of the subjects were automatically identified and further classified into fiber clusters to determine the differences between the two groups on a detailed scale. Next, each fiber cluster was divided into segments that can analyze specific areas of a fiber cluster. Lastly, the diffusion metrics of the two groups were comparatively analyzed to delineate the effects of visual training on WM microstructure. Our results showed that there were significant differences in the fiber clusters of the cingulate bundle, thalamus frontal, uncinate fasciculus, and corpus callosum between the training group compared and the control group. In addition, the training group exhibited lower mean fractional anisotropy, higher mean diffusivity and radial diffusivity than the control group. Therefore, the long-term cognitive activities, such as visual training, may systematically influence the WM properties of cognition, attention, memory, and processing speed.

An Intrinsic Stable Layered Oxide Cathode for Practical Sodium-Ion Battery: Solid Solution Reaction, Near-Zero-Strain and Marvelous Water Stability.

Non-aqueous solvents, in particular N,N-dimethylaniline (NMP), are widely applied for electrode fabrication since most sodium layered oxide cathode materials are readily damaged by water molecules. However, the expensive price and poisonousness of NMP unquestionably increase the cost of preparation and post-processing. Therefore, developing an intrinsically stable cathode material that can implement the water-soluble binder to fabricate an electrode is urgent. Herein, a stable nanosheet-like Mn-based cathode material is synthesized as a prototype to verify its practical applicability in sodium-ion batteries (SIBs). The as-prepared material displays excellent electrochemical performance and remarkable water stability, and it still maintains a satisfactory performance of 79.6% capacity retention after 500 cycles even after water treatment. The in situ X-ray diffraction (XRD) demonstrates that the synthesized material shows an absolute solid-solution reaction mechanism and near-zero-strain. Moreover, the electrochemical performance of the electrode fabricated with a water-soluble binder shows excellent long-cycling stability (67.9% capacity retention after 500 cycles). This work may offer new insights into the rational design of marvelous water stability cathode materials for practical SIBs.

Physical activity, problematic smartphone use, and burnout among Chinese college students.

The aim of this study was to investigate the association between physical activity (PA), problematic smartphone use (PSU), and burnout, as well as to identify whether there is a mediating role for PSU. We recruited 823 college students (Mage = 18.55, SD = 0.83) from Wuhan, China, in December 2022, including 499 males and 324 females. Demographic information, the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Smartphone Addiction Scale-Short Version (SAS-SV), and the Maslach Burnout Inventory-Student Survey (MBI-SS) were used for assessments. Pearson correlation analysis showed that PA was significantly associated with PSU (r = -0.151, p < 0.001), PSU was significantly associated with burnout (r = 0.421, p < 0.001), and the association between PA and burnout was not statistically significant (r = -0.046, p > 0.05). The results of the mediation model test showed that PA could not predict burnout directly; it instead predicted burnout entirely indirectly through PSU. Furthermore, PSU mediated the predictive effect of PA on exhaustion and cynicism. In conclusion, there is no direct connection between PA levels and burnout. PA indirectly affects burnout through PSU, but does not fully apply to the three different dimensions of exhaustion, cynicism, and professional efficacy.

Sodium Layered/Tunnel Intergrowth Oxide Cathodes: Formation Process, Interlocking Chemistry, and Electrochemical Performance.

Manganese-based layered oxides are prospective cathode materials for sodium-ion batteries (SIBs) due to their low cost and high theoretical capacities. The biphasic intergrowth structure of layered cathode materials is essential for improving the sodium storage performance, which is attributed to the synergistic effect between the two phases. However, the in-depth formation mechanism of biphasic intergrowth materials remains unclear. Herein, the layered/tunnel intergrowth Na0.6MnO2 (LT-NaMO) as a model material was successfully prepared, and their formation processes and electrochemical performance were systematically investigated. In situ high-temperature X-ray diffraction displays the detailed evolution process and excellent thermal stability of the layered/tunnel intergrowth structure. Furthermore, severe structural strain and large lattice volume changes are significantly mitigated by the interlocking effect between the phase interfaces, which further enhances the structural stability of the cathode materials during the charging/discharging process. Consequently, the LT-NaMO cathode displays fast Na+ transport kinetics with a remarkable capacity retention of ∼70.5% over 300 cycles at 5C, and its assembled full cell with hard carbon also exhibits high energy density. These findings highlight the superior electrochemical performance of intergrowth materials due to interlocking effects between layered and tunnel structures and also provide unique insights into the construction of intergrowth cathode materials for SIBs.

A Universal Strategy Based on Bridging Microstructure Engineering and Local Electronic Structure Manipulation for High-Performance Sodium Layered Oxide Cathodes.

Due to their high capacity and sufficient Na+ storage, O3-NaNi0.5Mn0.5O2 has attracted much attention as a viable cathode material for sodium-ion batteries (SIBs). However, the challenges of complicated irreversible multiphase transitions, poor structural stability, low operating voltage, and an unstable oxygen redox reaction still limit its practical application. Herein, using O3-NaNi0.5Mn0.5-xSnxO2 cathode materials as the research model, a universal strategy based on bridging microstructure engineering and local electronic structure manipulation is proposed. The strategy can modulate the physical and chemical properties of electrode materials, so as to restrain the unfavorable and irreversible multiphase transformation, improve structural stability, manipulate redox potential, and stabilize the anion redox reaction. The effect of Sn substitution on the intrinsic local electronic structure of the material is articulated by density functional theory calculations. Meanwhile, the universal strategy is also validated by Ti substitution, which could be further extrapolated to other systems and guide the design of cathode materials in the field of SIBs.

Local white matter abnormalities in Parkinson's disease with mild cognitive impairment: Assessed with neurite orientation dispersion and density imaging.

Mild cognitive impairment is a nonmotor complication in Parkinson's disease (PD) that have a high risk of developing dementia. White matter is associated with cognitive function in PD and the alterations may occur before the symptoms of the disease. Previous diffusion tensor imaging (DTI) studies lacked specificity to characterize the concrete contributions of distinct white matter tissue properties. This may lead to inconsistent conclusions about the alteration of white matter microstructure. Here, we used neurite orientation dispersion and density imaging (NODDI) and white matter fiber clustering method to uncover local white matter microstructures in PD with mild cognitive impairment (PD-MCI). This study included 23 PD-MCI and 20 PD with normal cognition (PD-NC) and 21 healthy controls (HC). To probe specific and fine-grained differences, metrics of NODDI and DTI in white matter fiber clusters were evaluated using along-tract analysis. Our results showed that PD-MCI patients had significantly lower neurite density index (NDI) and orientation dispersion index (ODI) in white matter fiber clusters in the prefrontal region. Correlation analysis and receiver operating characteristic (ROC) analysis revealed that the diagnostic performance of NODDI-derived metrics in cingulum bundle (2 clusters) and thalamo-frontal (2 clusters) were superior to DTI metrics. Our study provides a more specific insight to uncover local white matter abnormalities in PD-MCI, which benefit understanding the underlying mechanism of cognitive decline in PD and predicting the disease in advance.

How do extrinsic cues influence consumers' online hotel booking decisions? An event-related potential experiment.

Booking decision is a typical decision-making behavior in hospitality, while the neural processing of it is still unclear. To address this issue, with the help of event-related potential (ERP), this work uncovered the neural mechanism of the influence of two extrinsic cues, namely, brand familiarity (familiar vs. unfamiliar) and online reviews (positive vs. negative) on online hotel booking decisions. Behavioral results indicated that the booking rate under the condition of positive reviews was higher than that of negative reviews. In addition, the response time in the case of familiar brands was longer than that of unfamiliar brands. ERP results showed that the P200 amplitude of familiar brands was smaller than that of unfamiliar brands, while for the late positive potential amplitude, the opposite was the case. It is suggested that in the early stage of cognitive processing, unfamiliar brands evoke more automatic and unconscious attention while in the later stage, familiar brands attract more conscious attention. This study also found that the N400 amplitude of negative online reviews was larger than that of positive online reviews, indicating that negative stimuli can result in a larger emotional conflicts than that of positive stimuli. This study provides new insights into the neural mechanism of online booking decisions in the hospitality.

The relationship between exercise intention and behavior of Chinese college students: A moderated mediation model.

Inconsistency between intention and behavior is very common in daily life. This study explored the intention-behavior relationship in exercise, focusing on the mediating effect of action planning and the moderating effects of habit strength and gender. For the purpose of providing theoretical reference for the implementation of intervention strategies in the volitional phase, a total of 489 college students (M-age = 20.61, 57.46% female) from Hubei Province, China, were recruited to complete the questionnaire at two time points. The findings showed that exercise intention could positively predict exercise behavior via the mediating effect of action planning, with the mediating effect accounting for 48.52% of the total effect. The predictive effect of action planning × habit strength interaction on exercise behavior was statistically significant. As individuals' levels of habitual strength increased, so did the relationship between action plans and exercise behavior. The action planning-exercise behavior relationship was stronger in males than in females. In summary, action planning is a very important predictor of the post-intentional phase and has many advantages. For individuals whose exercise has become habitualized, forming a plan is not counterproductive and can still promote more exercise rather than in a mutually compensating manner.

Metaphorical or Straightforward? Comparing the Effectiveness of Different Types of Social Media Advertising.

The existing studies have analyzed the advertising effects of metaphorical advertisements and straightforward adverts in traditional advertising media. However, their advertising effects on social media are still unclear. To address this issue, this study uses eye-tracking and questionnaires to examine two types of social media tourism advertising-metaphorical and straightforward in posts with both high and low popularity. This within-subject (n = 55) experiment was designed to examine the effects of social media tourism advertising types on visual attention and tourism intention and to identify the moderating role of post popularity based on the elaboration likelihood model (ELM). We found that advertising types had no significant effect on visual attention, but metaphorical advertisements increased tourism intention compared with straightforward adverts. Furthermore, we found that the level of post popularity moderated the effect of advertising types on visual attention. Specifically, metaphorical adverts in highly popular posts attracted more visual attention in the advertising text area and in the whole advert. Straightforward adverts in posts with low popularity attracted more visual attention in the advertising text area. This research advances the current literature by exploring the effects of social media tourism advertising types and has implications for managers deciding on strategies for social media tourism marketing.

Automated quantification of brain connectivity in Alzheimer's disease using ClusterMetric.

Diffusion magnetic resonance imaging tractography allows investigating brain structural connections in a noninvasive way and has been widely used for understanding neurological disease. Quantification of brain connectivity along with its length by dividing a fiber bundle into multiple segments (node) is a powerful approach to assess biological properties, which is termed as tractometry. However, current tractometry methods face challenges in node identification along with the length of complex bundles whose morphology is difficult to summarize. In addition, the anatomic measure reflecting the macroscopic fiber cross-section has not been followed in previous tractometry. In this paper, we propose an automated fiber bundle quantification, which we refer to as ClusterMetric. The ClusterMetric uses a data-driven approach to identify fiber clusters corresponding to subdivisions of the white matter anatomy and identify consistent space nodes along the length of clusters across individuals. The proposed method is demonstrated by applicating to our collected dataset including 23 Alzheimer's disease (AD) patients and 22 healthy controls (HCs) and a public dataset of ADNI including 53 AD patients and 85 HCs. The altered white matter tracts in AD group are observed using both datasets, which involve several major fiber tracts including the corpus callosum, corona-radiata-frontal, arcuate fasciculus, inferior occipito-frontal fasciculus, uncinate fasciculus, thalamo-frontal, superior longitudinal fasciculus, inferior cerebellar peduncle, cingulum bundle, and extreme capsule. These fiber clusters represent the white matter connections that could be most affected in AD, suggesting the ability of our method in identifying potential abnormalities specific to local regions within a fiber cluster.

Brain network connectivity feature extraction using deep learning for Alzheimer's disease classification.

Early diagnosis and therapeutic intervention for Alzheimer's disease (AD) is currently the only viable option for improving clinical outcomes. Combining structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) to diagnose AD has yielded promising results. Most studies assume fixed time lags when constructing functional networks. Since the propagation delays between brain signals are constantly changing, these methods cannot reflect more detailed relationships between brain regions. In this work, we use a deep learning-based Granger causality estimator for brain connectivity construction. It exploits the strength of long short-term memory in ever-changing time series processing. This research involves data analysis from sMRI and rs-fMRI. We use sMRI to analyze the cerebral cortex properties and use rs-fMRI to analyze the graph metrics of functional networks. We extract a small subset of optimal features from both types of data. A support vector machine (SVM) is trained and tested to classify AD (n = 27) from healthy controls (n = 20) using rs-fMRI and sMRI features. Using a subset of optimal features in SVM, we achieve a classification accuracy of 87.23% for sMRI, 78.72% for rs-fMRI, and 91.49% for combined sMRI with rs-fMRI. The results show the potential to identify AD from healthy controls by integrating rs-fMRI and sMRI. The integration of sMRI and rs-fMRI modalities can provide supplemental information to improve the diagnosis of AD relative to either the sMRI or fMRI modalities alone.

Isolation of mouse pancreatic islet Procr+ progenitors and long-term expansion of islet organoids in vitro.

Insulin production is required for glucose homeostasis. Pancreatic islet ß cells are the only cells that produce insulin in humans; however, generation of functional ß cells in vitro from embryonic or adult tissues has been challenging. Here, we describe isolation of pancreatic islet progenitors from adult mice, which enables the efficient generation and long-term expansion of functional islet organoids in vitro. This protocol starts with purification of protein C receptor (Procr)-expressing islet progenitors. Coculture with endothelial cells generates islet organoids in vitro that can be expanded by passage. Functional maturation is achieved as a consequence of a prolonged culture period and cyclic glucose stimulation. Primary islet organoids form in 7-10 days. Subsequently, each passage takes 1 week, with the final maturation step requiring 3 weeks of additional culture. The resulting organoids are predominantly composed of ß cells but also contain small proportions of α, δ and pancreatic polypeptide cells. The organoids sense glucose and secrete insulin. This approach thus provides a strategy for ß cell generation in vitro and an organoid system to study islet regeneration and diseases.

Alterations of white matter tracts and topological properties of structural networks in hemifacial spasm.

Hemifacial spasm (HFS) is characterized by involuntary and paroxysmal muscle contractions on the hemiface. It is generally believed that HFS is caused by neurovascular compression at the root exit zone of the facial nerve. In recent years, the structural alterations of brains with HFS have aroused growing concern. However, little attention has been directed towards the possible involvement of specific white matter (WM) tracts and the topological properties of structural networks in HFS. In the present study, diffusion magnetic resonance imaging tractography was utilized to construct structural networks and perform tractometric analysis. The diffusion tensor imaging scalar parameters along with the WM tracts, and the topological parameters of global networks and subnetworks, were assessed in 62 HFS patients and 57 demographically matched healthy controls (HCs). Moreover, we investigated the correlation of these parameters with disease-clinical-level (DCL) and disease-duration-time (DDT) of HFS patients. Compared with HCs, HFS patients had additional hub regions including the amygdala, ventromedial putamen, lateral occipital cortex, and rostral cuneus gyrus. Furthermore, HFS patients showed significant alternations with specific topological properties in some structural subnetworks, including the limbic, default mode, dorsal attention, somato-motor, and control networks, as well as diffusion properties in some WM tracts, including the superior longitudinal fasciculus, cingulum bundle, thalamo-frontal, and corpus callosum. These subnetworks and tracts were associated with the regulation of emotion, motor function, vision, and attention. Notably, we also found that the parameters with subnetworks and tracts exhibited correlations with DCL and DDT. In addition to corroborating previous findings in HFS, this study demonstrates the changed microstructures in specific locations along with the fiber tracts and changed topological properties in structural subnetworks.

Selective YAP activation in Procr cells is essential for ovarian stem/progenitor expansion and epithelium repair.

Ovarian surface epithelium (OSE) undergoes recurring ovulatory rupture and OSE stem cells rapidly generate new cells for the repair. How the stem cell activation is triggered by the rupture and promptly turns on proliferation is unclear. Our previous study has identified that Protein C Receptor (Procr) marks OSE progenitors. In this study, we observed decreased adherent junction and selective activation of YAP signaling in Procr progenitors at OSE rupture site. OSE repair is impeded upon deletion of Yap1 in these progenitors. Interestingly, Procr+ progenitors show lower expression of Vgll4, an antagonist of YAP signaling. Overexpression of Vgll4 in Procr+ cells hampers OSE repair and progenitor proliferation, indicating that selective low Vgll4 expression in Procr+ progenitors is critical for OSE repair. In addition, YAP activation promotes transcription of the OSE stemness gene Procr. The combination of increased cell division and Procr expression leads to expansion of Procr+ progenitors surrounding the rupture site. These results illustrate a YAP-dependent mechanism by which the stem/progenitor cells recognize the murine ovulatory rupture, and rapidly multiply their numbers, highlighting a YAP-induced stem cell expansion strategy.