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The cycle stability of manganese‐based oxides cathode for sodium‐ion supercapacitor is impeded by severe structural collapse due to the Jahn–Teller (J–T) distortion of [MnO6] octahedra as Mn4+ is reduced to Mn3+. Herein, MnO2 cathode is stabilized by Mg2+ ions confinement between transition metal slabs. The Mg2+ confinement induces the transformation from original cubic [MnO6] octahedra to compressed configuration (com‐MnO2), resulting in the elimination of Mn 3d orbital degeneracy, thereby alleviating the structural deformation of [Mn3+O6] octahedra by suppressing J–T distortion during the reduction of Mn4+. As a result, the prepared com‐MnO2 exhibits greatly improved cycling stability with 99.1% retention of its initial capacity after 20 000 cycles due to inhibited J–T distortion. Additionally, an enhanced capacity of 434 F g−1 at 1 A g−1, a rate capacity of 275 F g−1 at 20 A g−1 can be achieved by com‐MnO2. The in situ XRD, Raman spectra reveal the reversible structural transformation during a cycle. It is concluded that the elimination of Mn 3d orbital degeneracy plays a crucial role in suppressing J–T distortion, which is conducive to in‐depth understanding of electron structure of transition metal oxides toward cycling performance. [ABSTRACT FROM AUTHOR]

Background: Identifying lymph node metastasis areas during surgery for early invasive lung adenocarcinoma remains challenging. The aim of this study was to develop a nomogram mathematical model before the end of surgery for predicting lymph node metastasis in patients with early invasive lung adenocarcinoma. Methods: In this study, we included patients with invasive lung adenocarcinoma measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to January 2022. Preoperative biomarker results, clinical features, and computed tomography characteristics were collected. The enrolled patients were randomized into a training cohort and a validation cohort in a 7:3 ratio. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. Recipient operating characteristic (ROC) curves were used to assess the discrimination ability of the model. Calibration capability was assessed using the Hosmer–Lemeshow test and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA). Results: The overall incidence of lymph node metastasis was 13.23% (61/461). Six indicators were finally determined to be independently associated with lymph node metastasis. These six indicators were: age (P < 0.001), serum amyloid (SA) (P = 0.008); carcinoma antigen 125 (CA125) (P = 0. 042); mucus composition (P = 0.003); novel aspartic proteinase of the pepsin family A (Napsin A) (P = 0.007); and cytokeratin 5/6 (CK5/6) (P = 0.042). The area under the ROC curve (AUC) was 0.843 (95% CI: 0.779–0.908) in the training cohort and 0.838 (95% CI: 0.748–0.927) in the validation cohort. the P-value of the Hosmer–Lemeshow test was 0.0613 in the training cohort and 0.8628 in the validation cohort. the bias of the training cohort corrected C-index was 0.8444 and the bias-corrected C-index for the validation cohort was 0.8375. demonstrating that the prediction model has good discriminative power and good calibration. Conclusions: The column line graphs created showed excellent discrimination and calibration to predict lymph node status in patients with ≤ 2 cm invasive lung adenocarcinoma. In addition, the predictive model has predictive potential before the end of surgery and can inform clinical decision making. [ABSTRACT FROM AUTHOR]

Background: Frailty contributes to adverse outcomes in older adults and places a heavy burden on healthcare resources. Dysphagia is associated with frailty, but the mechanisms by which dysphagia affects frailty in older adults are unclear. This study aimed to investigate a serial mediating effect of self-perceived oral health and self-reported nutritional status in the relationship between dysphagia and frailty among hospitalized older patients in China. Methods: This cross-sectional study included 1200 patients aged ≥ 65 years in the Department of Geriatrics, Shaanxi Provincial People's Hospital. A structured face-to-face interview was used to survey the following questionnaires: General Information Questionnaire, Tilburg Frailty Indicators (TFI), Eating Assessment Tool-10 (EAT-10), 30mL Water Swallow Test (WST), Geriatric Oral Health Assessment Index (GOHAI), and Short-Form Mini-Nutritional Assessment (MNA-SF). A total of 980 participants with complete data were included in the analysis. Statistical analysis was performed using SPSS 26.0 and Amos 28.0 software. Spearman's correlation analysis was used for correlation analysis of study variables. The results of the multivariate linear regression analysis for frailty were used as covariates in the mediation analysis, and the structural equation model (SEM) was used to analyze the mediating effects among the study variables. Results: Dysphagia, self-perceived oral health, self-reported nutritional status, and frailty were significantly correlated (P<0.001). Dysphagia was found to directly affect frailty (β = 0.161, 95%CI = 0.089 to 0.235) and through three significant mediation pathways: (1) the path through self-perceived oral health (β = 0.169, 95%CI = 0.120 to 0.221), accounting for 36.98% of the total effect; (2) the path through self-reported nutritional status (β = 0.050, 95%CI = 0.023 to 0.082), accounting for 10.94% of the total effect; (3) the path through self-perceived oral health and self-reported nutritional status (β = 0.077, 95%CI = 0.058 to 0.102), accounting for 16.85% of the total effect. The total mediation effect was 64.77%. Conclusions: This study indicated that dysphagia was significantly associated with frailty. Self-perceived oral health and self-reported nutritional status were serial mediators of this relationship. Improving the oral health and nutritional status of hospitalized older patients may prevent or delay the frailty caused by dysphagia. [ABSTRACT FROM AUTHOR]

The shape of ice crystals affects their radiative properties, growth rate, fall speed, and collision efficiency and thus, plays a significant role in cloud optical properties and precipitation formation. Ambient conditions like temperature and humidity determine the basic habit of ice crystals, while microphysical processes such as riming and aggregation further shape them, resulting in a diverse set of ice crystal shapes and densities. Current classification algorithms face two major challenges: (1) ice crystals are often classified as a whole (on the image scale), necessitating identification of the dominant component of aggregated ice crystals, and (2) single-label classifications lead to information loss because of the compromise between basic habit and microphysical process information. To address these limitations, here we present a two-pronged solution: a rotated object detection algorithm (IceDetectNet) that classifies each component of an aggregated ice crystal individually, and a multi-label classification scheme that considers both basic habits and physical processes simultaneously. IceDetectNet was trained and tested on two independent datasets obtained by a holographic imager during the NASCENT campaign in Ny-Ålesund, Svalbard, in November 2019 and April 2020. The algorithm correctly classifies 92 % of the ice crystals as either aggregate or non-aggregate and achieved an overall accuracy of 86 % for basic habits and 82 % for microphysical processes classification. On the component scale, IceDetectNet demonstrated high detection and classification accuracy across all sizes, indicating its ability to effectively classify individual components of aggregated ice crystals. Furthermore, the algorithm demonstrated good generalization ability by classifying ice crystals from an independent test dataset with overall accuracies above 70 %. IceDetectNet can provide a deeper understanding of ice crystal shapes, leading to better estimates of ice crystal mass, fall velocity, and radiative properties and thus, has the potential to improve precipitation forecasts and climate projections. [ABSTRACT FROM AUTHOR]

Uncrewed aerial vehicles (UAVs) have become widely used in a range of atmospheric science research applications. Because of their small size, flexible range of motion, adaptability, and low cost, multirotor UAVs are especially well-suited for probing the lower atmosphere. However, their use so far has been limited to conditions outside of clouds, first because of the difficulty of flying beyond visual line of sight and second because of the challenge of flying in icing conditions in supercooled clouds. Here, we present two UAVs for cloud microphysical research: one UAV (the measurement UAV) equipped with a Portable Optical Particle Spectrometer (POPS) and meteorological sensors to probe the aerosol and meteorological properties in the boundary layer and one UAV (the seeding UAV) equipped with seeding flares to produce a plume of particles that can nucleate ice in supercooled clouds. A propeller heating mechanism on both UAVs allows for operating in supercooled clouds with icing conditions. These UAVs are an integral part of the CLOUDLAB project in which glaciogenic cloud seeding of supercooled low stratus clouds is utilized for studying aerosol–cloud interactions and ice crystal formation and growth. In this paper, we first show validations of the POPS on board the measurement UAV, demonstrating that the rotor turbulence has a small effect on measured particle number concentrations. We then exemplify the applicability for profiling the planetary boundary layer, as well as for sampling and characterizing aerosol plumes, in this case, the seeding plume. We also present a new method for filtering out high-concentration data to ensure good data quality of POPS. We explain the different flight patterns that are possible for both UAVs, namely horizontal or vertical leg patterns or hovering, with an extensive and flexible parameter space for designing the flight patterns according to our scientific goals. Finally, we show two examples of seeding experiments: first characterizing an out-of-cloud seeding plume with the measurement UAV flying horizontal transects through the plume and, second, characterizing an in-cloud seeding plume with downstream measurements from a POPS and a holographic imager mounted on a tethered balloon. Particle number concentrations and particle number size distributions of the seeding plume from the experiments reveal that we can successfully produce and measure the seeding plume, both in-cloud (with accompanying elevated ice crystal number concentrations) and out-of-cloud. The methods presented here will be useful for probing the lower atmosphere, for characterizing aerosol plumes, and for deepening our cloud microphysical understanding through cloud seeding experiments, all of which have the potential to benefit the atmospheric science community. [ABSTRACT FROM AUTHOR]

The value for core hysteresis loss (CHL) resistance in Buntenbach's analogy hysteresis model does not consider the impact of frequency variations. In order to address this issue, this paper proposes a calculation expression for CHL resistance that takes into account the influence of frequency variation through a variable coefficient. The paper analyzes changes in CHL resistance values at different frequencies using hysteresis loss characteristics and circuit theory. To validate the proposed calculation method for CHL resistance, Buntenbach's analogy hysteresis model is applied to model the Epstein frame and magnetically saturated controllable reactor. The comparative results reveal that the proposed calculation expression for CHL resistance is effective. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is a limited nutrient for both plants and herbivores. How plants reallocate N upon herbivore attack is vital for plant tolerance to herbivores. Here we investigated N reallocation in rice during a 2‐day herbivore attack by a generalist herbivore Spodoptera litura and 2 days after herbivore removal. Labeled 15N was translocated during insect attack from feeding‐damaged leaves to roots, particularly to young roots. The amounts of chlorophyll and Rubisco were significantly reduced in the attacked leaves. Both free amino acids and nitrate accumulated in the damaged leaves and young roots, while ammonium content was decreased. Activities of nitrate reductase and glutamine synthetase were enhanced in feeding‐damaged leaves but inhibited in young roots. The expression of amino acid transporters OsAAP6, OsAAT15, and jasmonate‐responsive genes OsAOS, OsMAPK3, OsMAPK6 was induced in the damaged leaves. However, 2 days after herbivore removal, N uptake was increased and herbivory‐induced 15N transfer to roots was partially reverted back to the damaged leaves, resulting in N levels in the previously damaged leaves were even higher than that in control leaves. Collectively, our results indicate a dynamic N reallocation in rice responses to insect herbivory. Summary statement: Leaf herbivory by a polyphagous pest leads to chlorophyll breakdown, increased free amino acids and nitrate and induction of amino acid transporters for N reallocation from feeding‐damaged leaf to roots in rice, suggesting a key role of N reallocation in plant tolerance to insect herbivory. [ABSTRACT FROM AUTHOR]

In this paper, fixed‐time synchronization of nonlinear stochastic coupling multilayer neural networks is studied. The neural subnets in the multilayer networks are delay Cohen–Grossberg neural networks (DCGNNs). To overcome uncertain factors, we designed an adaptive delay‐dependent controller in synchronization. To describe constraints of communication and other related problems in networks, which are due to limitations for bit rates and bandwidths in communication channels, an adaptive fixed‐time control strategy is purposed by introducing quantization signal input. A theoretical framework about fixed‐time synchronization in multilayer delay Cohen–Grossberg neural networks (MDCGNNs) is established. We find that fixed settling time is related to the scale of MDCGNNs, characteristics of the designed controller parameters, and level of quantization. Finally, the effective of the theoretical framework is validated in an example. [ABSTRACT FROM AUTHOR]

The electrochemical N2 oxidation reaction (NOR) has emerged as a promising approach for achieving high selectivity in nitric acid (HNO3) production. However, the sluggish N2 activation process in NOR due to the high cleavage energy barrier of the N≡N bond remains a challenge. Herein, a novel orbital hybridization strategy for tuning the NOR performance through the construction of cerium (Ce) 4f–O 2p–Co 3d network in Ce‐doped Co3O4 (Ce–Co3O4) is proposed. The Ce–Co3O4 catalyst exhibits an enhanced HNO3 yield of 24.76 µg h−1 mgcat−1 and a promoted Faradaic efficiency of 31.93% in 0.1 m Na2SO4 electrolyte under ambient conditions compared to those of the pure Co3O4 (13.75 µg h−1 mgcat−1 and 23.43%). Density functional theory caculations demonstrate the strong 4f–2p–3d orbital hybridization and electron transfer in Ce–Co3O4. Moreover, a series of in situ techniques provide direct evidence of stronger adsorption peaks for Co─N bond and the key intermediate *NO formed after N2 activation on the surface of Ce–Co3O4. This work provides a promising route for the preparation of efficient NOR catalysts and sheds light on the mechanism of N2 activation through orbital hybridization. [ABSTRACT FROM AUTHOR]

In the post-COVID-19 era, extensive quantities of antipyretic drugs are being haphazardly released from households into the environment, which may pose potential risks to ecological systems and human health. Identification of the mobility behaviors of these compounds in the subsurface environment is crucial to understand the environmental fate of these common contaminants. The mobility properties of three broad-spectrum antipyretic drugs, including ibuprofen (IBF), indometacin (IMC), and acetaminophen (APAP), in porous soil media, were investigated in this study. The results showed that the mobility of the three drugs (the background electrolyte was Na+) through the soil column followed the order of APAP > IBF > IMC. The difference in the physicochemical characteristics of various antipyretic drugs (e.g., the molecular structure and hydrophobicity) could explain this trend. Unlike Na+, Ca2+ ions tended to serve as bridging agents by linking the soil grains and antipyretic molecules, leading to the relatively weak mobility behaviors of antipyretic drugs. Furthermore, for a given antipyretic drug, the antipyretic mobility was promoted when the background solution pH values were raised from 5.0 to 9.0. The phenomenon stemmed from the improved electrostatic repulsion between the dissociated species of antipyretic molecules and soil grains, as well as the weakened hydrophobic interactions between antipyretic drugs and soil organic matter. Furthermore, a two-site non-equilibrium transport model was used to estimate the mobility of antipyretic drugs. The results obtained from this work provide vital information illustrating the transport and retention of various antipyretic drugs in aquifers. [ABSTRACT FROM AUTHOR]