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Background: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index. Methods: We developed a dataset containing 3,923 lateral knee X-ray images. Notably, all X-ray images were from three tertiary level A hospitals, and 2,341 cases were included in the analysis after screening. By manually labeling key points, the model was trained using the residual network (ResNet) and high-resolution network (HRNet) for human pose estimation architectures to measure the patellar height index. Various data enhancement techniques were used to enhance the robustness of the model. The root mean square error (RMSE), object keypoint similarity (OKS), and percentage of correct keypoint (PCK) metrics were used to evaluate the training results. In addition, we used the intraclass correlation coefficient (ICC) to assess the consistency between manual and automatic measurements. Results: The HRNet model performed excellently in keypoint detection tasks by comparing different deep learning models. Furthermore, the pose_hrnet_w48 model was particularly outstanding in the RMSE, OKS, and PCK metrics, and the Insall–Salvati index (ISI) automatically calculated by this model was also highly consistent with the manual measurements (intraclass correlation coefficient [ICC], 0.809–0.885). This evidence demonstrates the accuracy and generalizability of this deep learning system in practical applications. Conclusion: We successfully developed a deep learning-based automatic measurement system for the patellar height. The system demonstrated accuracy comparable to that of experienced radiologists and a strong generalizability across different datasets. It provides an essential tool for assessing and treating knee diseases early and monitoring and rehabilitation after knee surgery. Due to the potential bias in the selection of datasets in this study, different datasets should be examined in the future to optimize the model so that it can be reliably applied in clinical practice. Trial registration: The study was registered at the Medical Research Registration and Filing Information System (medicalresearch.org.cn) MR-61-23-013065. Date of registration: May 04, 2023 (retrospectively registered). [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations were utilized to investigate the mechanical properties of the Al–Co–Cr–Fe–Ni high-entropy alloy and observe atomic microstructure and internal dislocation line changes under different parameter conditions. The findings demonstrate that the mechanical properties of the AlCoCrFeNi3 high-entropy alloy are significantly superior to those of conventional alloys in ambient temperature. During the tensile process, the face-centered structure undergoes interconversion with other structure types, while the internal dislocation lines gradually increase. The presence of grain boundaries impedes dislocation movement, resulting in lower deformation capacity and tensile strength in polycrystals compared to single crystals. Enhancing Ni content, increasing strain rate, and decreasing temperature during tensile process contributes to the enhancement of the mechanical properties of material. Among these factors, the Ni content exerts the most significant influence on the mechanical properties of the material. [ABSTRACT FROM AUTHOR]

Microfine low-rank coals are subject to metamorphic changes that hinder their floatability, impeding their clean and efficient utilization. The objective of this study was to refine the jet-slurry technique to enhance the floatability of microfine low-rank coals. Furthermore, advanced methods including Focused beam reflectance measurement (FBRM), high-sensitivity microelectromechanical balancer (DCAT), Fourier transform infrared spectrometer (FTIR), and scanning electron microscope (SEM) were employed to dissect the physicochemical effects of jet slurring on microfine low-rank coal particles. The study found that as the concentration of microfine coal particles increased, surface reagent adsorption initially rose and then fell with greater feed volumes. In contrast, adhesion forces displayed an inverse trend. Optimal results were achieved with a feed volume set at 25 L/min. This phenomenon is attributable to multiple regulatory factors. Within certain limits, intensifying conditioning promotes particle agglomeration, curtails fine gangue mineral coverage, boosts sodium dodecyl sulfate (SDS) adsorption, diminishes microfine coal wettability, and better kerosene-coal particle mixing. However, at excessive jet speeds (30 L/min), substantial physical pressure variances and mechanical dispersion forces arise, undermining SDS or kerosene’s chemical adsorption to coal or modified coal, thus reducing reagent attachment. The aforementioned study demonstrates that within certain parameters, jet slurring significantly betters coal-gangue separation, thereby amplifying the flotation efficacy of microfine low-rank coals. This research offers strategic insights into microfine low-rank coal flotation processes and lays a theoretical groundwork for the selection of suitable techniques and reagents. [ABSTRACT FROM AUTHOR]

Multiple Sclerosis (MS) is an immune-related disease and the relationship between MS and cancer has raised attention. Previous studies of the relationship between MS and cancer have reached conflicting conclusions. In this study, the two-sample MR method is used to investigate whether MS has a causal correlation with cancers and offer scientific evidence for cancer prevention. Single nucleotide polymorphisms (SNPs) related to MS were obtained from the genome-wide association study (GWAS) based on International Multiple Sclerosis Genetics Consortium (IMSGC) and SNPs related to 15 types of cancers were obtained from the GWASs based on UK Biobank. Inverse variance weighted (IVW) method was mainly used to assess causal effects. Sensitivity analyses were conducted with Cochran's Q-test, MR Egger intercept, leave-one-out test, and MR Steiger method. IVW analysis showed that MS was only associated with a marginal increased risk of cervical cancer (OR 1.0004, 95% CI 1.0002–1.0007, p = 0.0003). Sensitivity analyses showed that the results of MR analysis were robust and found no heterogeneity, no pleiotropy, and no reverse causation. In conclusion, this study finds no causal relationship between MS and 15 types of cancers except cervical cancer. [ABSTRACT FROM AUTHOR]

The PTEN-induced kinase 1 (PINK1)-Parkin pathway plays a vital role in maintaining a healthy pool of mitochondria in higher eukaryotic cells. While the downstream components of this pathway are well understood, the upstream triggers remain less explored. In this study, we conducted an extensive analysis of inhibitors targeting various mitochondrial electron transport chain (ETC) complexes to investigate their potential as activators of the PINK1–Parkin pathway. We identified cloflucarban, an antibacterial compound, as a novel pathway activator that simultaneously inhibits mitochondrial complexes III and V, and V. RNA interference (RNAi) confirmed that the dual inhibition of these complexes activates the PINK1–Parkin pathway. Intriguingly, we discovered that albumin, specifically bovine serum albumin (BSA) and human serum albumin (HSA) commonly present in culture media, can hinder carbonyl cyanide m-chlorophenyl hydrazone (CCCP)-induced pathway activation. However, cloflucarban's efficacy remains unaffected by albumin, highlighting its reliability for studying the PINK1–Parkin pathway. This study provides insights into the activation of the upstream PINK1–Parkin pathway and underscores the influence of culture conditions on research outcomes. Cloflucarban emerges as a promising tool for investigating mitochondrial quality control and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

PhotoVoltaic (PV) panels have been increasingly favored by residential users in recent years, due to noticeable reductions in their costs. The PV systems become more effective when combined with battery packages, which store the energy produced by the PV systems for later use. This way, the PV systems are able to provide flexible and reliable services even when the peak demand for electricity misalign with the window of most efficient PV power generation. In this study, we develop an integrated charge/discharge scheme for lithium-ion batteries to maximize their total expected benefit. Specifically, we develop a Markov Decision Process (MDP) model to maximize the battery utilization, subject to uncertainty in weather conditions and electricity demands, while accounting for battery degradation due to calendar aging and charging/discharging cycles. Due to the extremely slow rate of degradation in batteries, the state space of the MDP is excessively large. To solve the problem efficiently, we establish structural properties of the MDP and exploit them to solve the problem. We improve the backward induction algorithm with established structural properties. We further improve the Deep Q-network (DQN) algorithm by proposing two novel algorithms, the augmented DQN (ADQN) algorithm and the stochastic augmented DQN (SADQN) algorithm. Computational results indicate that ADQN and SADQN solve the problem much faster than DQN, with better solution qualities. The ADQN and SADQN algorithms provide flexibility for practitioners in real-world implementations. [ABSTRACT FROM AUTHOR]

The hot deformation behavior of 301 L stainless steel is investigated at 1000–1250 °C and 0.1–50 s−1. Deformation characteristics are studied through compressive stress–strain curves and constitutive equations. According to the dynamic material model and a series of diffusion annealing experiments, the hot processing map of 301 L stainless steel is established to determine the suitable processing domain. The results show that the stable domain is located in 1085–1240 °C and high strain rate range of 4.5–50 s−1, and the strain rate is the main factor affecting the machinability. Based on the hot compression tests, δ‐ferrite gradually forms a network structure with the increase of temperature; however, it can be inhibited at high strain rate. Therefore, it is necessary to reduce the temperature and increase the strain rate in the actual processing of the machinable area. It is found that diffusion annealing can reduce the content of δ‐ferrite from 12% to 0.67%, and the dissolution of δ‐ferrite is controlled by the diffusion of Cr and Ni, especially noticeable at the interface between γ and δ phase. Finally, the optimum diffusion annealing process parameter is determined at 1300 °C and 10 min. [ABSTRACT FROM AUTHOR]

Background: The accumulation of myofibroblasts is the key pathological feature of pulmonary fibrosis (PF). Aberrant differentiation of lung-resident mesenchymal stem cells (LR-MSCs) has been identified as a critical source of myofibroblasts, but the molecular mechanisms underlying this process remain largely unknown. In recent years, N6-methyladenosine (m6A) RNA modification has been implicated in fibrosis development across diverse organs; however, its specific role in promoting the differentiation of LR-MSCs into myofibroblasts in PF is not well defined. Methods: In this study, we examined the levels of m6A RNA methylation and the expression of its regulatory enzymes in both TGF-β1-treated LR-MSCs and fibrotic mouse lung tissues. The downstream target genes of m6A and their related pathways were identified according to a literature review, bioinformatic analysis and experimental verification. We also assessed the expression levels of myofibroblast markers in treated LR-MSCs and confirmed the involvement of the above-described pathway in the aberrant differentiation direction of LR-MSCs under TGF-β1 stimulation by overexpressing or knocking down key genes within the pathway. Results: Our results revealed that METTL3-mediated m6A RNA methylation was significantly upregulated in both TGF-β1-treated LR-MSCs and fibrotic mouse lung tissues. This process directly led to the aberrant differentiation of LR-MSCs into myofibroblasts by targeting the miR-21/PTEN pathway. Moreover, inhibition of METTL3 or miR-21 and overexpression of PTEN could rescue this abnormal differentiation. Conclusion: Our study demonstrated that m6A RNA methylation induced aberrant LR-MSC differentiation into myofibroblasts via the METTL3/miR-21/PTEN signaling pathway. We indicated a novel mechanism to promote PF progression. Targeting METTL3-mediated m6A RNA methylation and its downstream targets may present innovative therapeutic approaches for the prevention and treatment of PF. [ABSTRACT FROM AUTHOR]

Coxsackievirus A10 (CVA10) has recently emerged as one of the major causative agents of hand, foot, and mouth disease. CVA10 may also cause a variety of complications. No approved vaccine or drug is currently available for CVA10. The residues of CVA10 critical for viral attachment, infectivity and in vivo pathogenicity have not been identified by experiment. Here, we report the identification of CVA10 residues important for binding to cellular receptor KREMEN1. We identified VP2 N142 as a key receptor-binding residue by screening of CVA10 mutants resistant to neutralization by soluble KREMEN1 protein. The receptor-binding residue N142 is exposed on the canyon rim but highly conserved in all naturally occurring CVA10 strains, which provides a counterexample to the canyon hypothesis. Residue N142 when mutated drastically reduced receptor-binding activity, resulting in decreased viral attachment and infection in cell culture. More importantly, residue N142 when mutated reduced viral replication in limb muscle and spinal cord of infected mice, leading to lower mortality and less severe clinical symptoms. Additionally, residue N142 when mutated could decrease viral binding affinity to anti-CVA10 polyclonal antibodies and a neutralizing monoclonal antibody and render CVA10 resistant to neutralization by the anti-CVA10 antibodies. Overall, our study highlights the essential role of VP2 residue N142 of CVA10 in the interactions with KREMEN1 receptor and neutralizing antibodies and viral virulence in mice, facilitating the understanding of the molecular mechanisms of CVA10 infection and immunity. Our study also provides important information for rational development of antibody-based treatment and vaccines against CVA10 infection. Author summary: Coxsackievirus A10 (CVA10) is an emerging pathogen that causes hand, foot, and mouth disease. No approved vaccines or antiviral treatments for CVA10 infection are yet available. Here we identified VP2 N142 of CVA10 as a key residue essential for viral recognition by KREMEN1 receptor by selection of soluble receptor neutralization-resistant mutant and mutational analysis. Residue N142 when mutated could significantly reduce receptor-binding activity, viral attachment, and infection in vitro. Mouse infection experiments show that residue N142 when mutated could reduce fatality rate and severity of symptoms by decreasing viral loads in limb muscle and spinal cord. Furthermore, residue N142 when mutated could confer resistance to neutralization by anti-CVA10 neutralizing antibodies. Additionally, N142, which is exposed on the canyon rim but highly conserved in CVA10, is identified as a key receptor-binding residue, providing a counterexample to the canyon hypothesis. Overall, our findings promote a better understanding of the molecular basis of CVA10 attachment and infection and in vivo pathogenicity, and also provide useful information for rational research and development of vaccines and antibody-based treatment against CVA10 infection. [ABSTRACT FROM AUTHOR]

To solve the problems mechanically caused by parallel direct‐drive permanent magnet motors (DD‐PMSM). This paper proposes a concave‐core stator direct‐drive permanent magnet motor (CCSDD‐PMSM) structure. In this study, an auxiliary yoke structure is proposed to optimise the magnetic circuit and analyse the cogging torque to achieve the minimum detent force. Based on the unit motor and combined with the magnetomotive force to analyse the symmetry of different winding distributions, the stability characteristics of the motor are studied. The magnetic field distribution of the motor load air gap is calculated using the finite element method. The contribution of different spatial order harmonics to the motor output torque is calculated using the Maxwell tensor method. The torque calculation expression of the CCSDD‐PMSM is given. Finally, an experimental prototype is made to verify the accuracy of the analysis in this paper. [ABSTRACT FROM AUTHOR]

Objectives: To assess the diagnostic performance of high-resolution contrast-enhanced MRI (hrMRI) with three-dimensional (3D) fast spin echo (FSE) sequence by comparison with conventional contrast-enhanced MRI (cMRI) and dynamic contrast-enhanced MRI (dMRI) with 2D FSE sequence for identifying pituitary microadenomas. Methods: This single-institutional retrospective study included 69 consecutive patients with Cushing's syndrome who underwent preoperative pituitary MRI, including cMRI, dMRI, and hrMRI, between January 2016 to December 2020. Reference standards were established by using all available imaging, clinical, surgical, and pathological resources. The diagnostic performance of cMRI, dMRI, and hrMRI for identifying pituitary microadenomas was independently evaluated by two experienced neuroradiologists. The area under the receiver operating characteristics curves (AUCs) were compared between protocols for each reader by using the DeLong test to assess the diagnostic performance for identifying pituitary microadenomas. The inter-observer agreement was assessed by using the κ analysis. Results: The diagnostic performance of hrMRI (AUC, 0.95–0.97) was higher than cMRI (AUC, 0.74–0.75; p ≤.002) and dMRI (AUC, 0.59–0.68; p ≤.001) for identifying pituitary microadenomas. The sensitivity and specificity of hrMRI were 90–93% and 100%, respectively. There were 78% (18/23) to 82% (14/17) of the patients, who were misdiagnosed on cMRI and dMRI and correctly diagnosed on hrMRI. The inter-observer agreement for identifying pituitary microadenomas was moderate on cMRI (κ = 0.50), moderate on dMRI (κ = 0.57), and almost perfect on hrMRI (κ = 0.91), respectively. Conclusions: The hrMRI showed higher diagnostic performance than cMRI and dMRI for identifying pituitary microadenomas in patients with Cushing's syndrome. Key Points: • The diagnostic performance of hrMRI was higher than cMRI and dMRI for identifying pituitary microadenomas in Cushing's syndrome. • About 80% of patients, who were misdiagnosed on cMRI and dMRI, were correctly diagnosed on hrMRI. • The inter-observer agreement for identifying pituitary microadenomas was almost perfect on hrMRI. [ABSTRACT FROM AUTHOR]

A novel supramolecular complex (2C18@OPP) constructed from two kinds of unique nanorings, all-carboatomic cyclo[18]carbon (C18) and figure-of-eight carbon hoop (OPP), has been studied theoretically from the perspective of an extraordinary dual-motor nanorotator. The rotational barrier of C18 in OPP is extremely small at ambient temperature, implying the possibility of the host–guest complex as an ultrafast nanorotator. The rotational characteristics and thermodynamic stability of the nanorotator at different temperatures were then explored. The rotational behaviors of the two C18 rings in OPP are basically independent of each other. The supramolecule investigated in this work is the first example of a dual-motor nanorotator that promises to be an important building block for constructing complicated molecular machines. [ABSTRACT FROM AUTHOR]

Purpose: Considering the high susceptibility of patients with advanced non-small cell lung cancer (NSCLC) to COVID-19, we explored the susceptible cell types and potential routes of SARS-CoV-2 infection in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by analyzing the expression patterns of the entry receptor angiotensin converting enzyme 2 (ACE2) and the spike (S) protein priming proteases transmembrane serine protease 2 (TMPRSS2) and FURIN. Methods: Single-cell transcriptomic analysis of 14 LUSC and 12 LUAD samples was utilized to exhibit the heterogeneous expression of ACE2, TMPRSS2 and FURIN across different cell subsets and individuals. Results: 12 cell types and 33 cell clusters were identified from 26 cancer samples. ACE2, TMPRSS2 and FURIN were heterogeneously expressed across different patients. Among all cell types, ACE2, TMPRSS2 and FURIN were predominately expressed in cancer cells and alveolar cells, and lowly uncovered in other cells. Compared to LUSC, the protein priming proteases (TMPRSS2 and FURIN) were highly found in LUAD samples. However, ACE2 was not differentially expressed in cancer cells between the two cancer types. Moreover, ACE2, TMPRSS2, and FURIN expressions were not higher in any cell type of smokers than non-smokers. Conclusion: Our research first revealed the heterogeneous expression of ACE2, TMPRSS2, and FURIN in different cell subsets of NSCLC and also across different individuals. These results provide insight into the specific cells targeted by SARS-CoV-2 (i.e., cancer cells and alveolar cells) in patients with advanced NSCLC, and indicate that smoking may be not an independent risk factor for NSCLC combined with COVID-19. [ABSTRACT FROM AUTHOR]

Bisphenols are environmental toxins with endocrine disruptor activity, yet bisphenol A (BPA) and its analogs are still widely used in manufacturing plastic products. There is evidence showing that BPA elicits inflammation in humans and animals, but the target cell types of BPA are not well understood. In this study, we sought to determine BPA's direct effect on macrophages and BPA immunotoxicity in mouse intestine. Ghrelin is an important nutrient-sensing hormone, acting through its receptor growth hormone secretagogue receptor (GHSR) to regulate metabolism and inflammation. We found that BPA promotes intestinal inflammation, showing increased infiltrating immune cells in colons and enhanced expression of Ghsr and pro-inflammatory cytokines and chemokines, such as Il6 and Ccl2, in colonic mucosa. Moreover, we found that both long- and short-term BPA exposure elevated pro-inflammatory monocytes and macrophages in mouse peripheral blood mononuclear cells (PBMC) and peritoneal macrophages (PM), respectively. To determine the role of GHSR in BPA-mediated inflammation, we generated Ghsr deletion mutation in murine macrophage RAW264.7 using CRISPR gene editing. In wild-type RAW264.7 cells, the BPA exposure promotes macrophage pro-inflammatory polarization and increases Ghsr and cytokine/chemokine Il6 and Ccl2 expression. Interestingly, Ghsr deletion mutants showed a marked reduction in pro-inflammatory cytokine/chemokine expression in response to BPA, suggesting that GHSR is required for the BPA-induced pro-inflammatory response. Further understanding how nutrient-sensing GHSR signaling regulates BPA intestinal immunotoxicity will help design new strategies to mitigate BPA immunotoxicity and provide policy guidance for BPA biosafety. [ABSTRACT FROM AUTHOR]

Herein, the electronic structure and bonding character of the stable cyclo[18]carbon (C18) precursor, C18Br6, are thoroughly characterized by molecular orbital (MO), density of states (DOS), bond order (BO), and interaction region indicator (IRI) analyses. The delocalization characters of out‐of‐plane and in‐plane π‐electrons (labeled as πout‐ and πin‐electrons, respectively) in bonding regions were examined using localized orbital locator (LOL) and electron localization function (ELF). The aromaticity was investigated, studying the molecular magnetic response to external magnetic field by computing the magnetically induced current density (Jind), iso‐chemical shielding surface (ICSS), anisotropy of the induced current density (AICD), and the induced magnetic field (Bind). All these analyses indicate that C18Br6 is a globally aromatic species with lower aromaticity than C18, and the blocking of in‐plane π‐conjugation (labeled as πin‐conjugation) by the presence of ‐Br substituents in it is the underlying cause for the weakening of molecular aromaticity. [ABSTRACT FROM AUTHOR]

Background: The atherogenic index of plasma (AIP) is an important alternative metabolic biomarker of atherosclerosis and cardiovascular diseases. Nevertheless, the correlation between the AIP and carotid atherosclerosis is unknown among the general population. Methods: A total of 52,380 community residents, aged ≥ 40 years who underwentcervical vascular ultrasound from December 2017 to December 2020 in Hunan China, were selected for retrospective analysis. The AIP was calculated as a logarithmically converted ratio of triglycerides (TG) to high-density lipoprotein-cholesterol (HDL-C). The participants were divided into AIP quartile groups (Q1-Q4). Logistic regression models and restricted cubic spline analyses were used to examine the association of the AIP with carotid atherosclerosis. Stratified analyses were applied to control for confounding factors. The incremental predictive value of the AIP was further assessed. Results: After adjusting for traditional risk factors, an increased AIP was associated with a higher rate of carotid atherosclerosis (CA), increased carotid intima-media thickness (CIMT), and plaques [odds ratio, OR (95% confidence interval, CI): 1.06 (1.04, 1.08), 1.07 (1.05, 1.09), and 1.04 (1.02, 1.06) per 1-SD increase in the AIP, respectively]. Compared with those participants in the quartile 1 group, those in the quartile 4 group had a greater risk of CA [OR 1.18, 95% CI (1.12, 1.25)], increased CIMT [OR 1.20, 95% CI (1.13, 1.26)], and plaques [OR 1.13, 95% CI (1.06, 1.19)]. However, we did not observe an association between the AIP and stenosis [0.97 (0.77, 1.23), p for trend = 0.758]. Restricted cubic spline analyses also showed a cumulative increase in the risk of CA, increased CIMT, and plaques but not stenosis severity (> 50%) with an increase of the AIP. Subgroup analyses showed that a more significant association between the AIP and the prevalence of increased CA was detected in younger subjects (aged < 60 years) with a body mass index (BMI) of ≥ 24 and fewer comorbidities. Additionally, the AIP provided incremental predictive capacity over established risk factors for CA, as shown by an improvement in the net reclassification index (NRI) and integrated discrimination index (IDI) (all P < 0.05). Conclusions: An elevated AIP in a community-based population is associated with a higher rate of CA. the AIP could serve as a potential biomarker for CA risk assessment. [ABSTRACT FROM AUTHOR]

Background: This study focussed on exploring the prognostic prediction performance of the growth arrest and DNA damage-inducible 45 beta (GADD45B) and its associations with T-cell activity and immune soakage in different malignancies, especially lung squamous cell carcinoma (LUSC). Methods: We applied TIMER database for comparing the expressions of GADD45B among different cancers. OncoLnc, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Kaplan-Meier Plotter were utilised to evaluate the prognostic prediction performance of GADD45B. Besides, the associations of GADD45B with clinical stage, associated gene markers, and immune infiltration were examined through TISIDB, GEPIA2, and Tumour Immune Estimation Resource (TIMER). Biological processes (BPs) and KEGG enrichment analyses were performed to illustrate the possible role of GADD45B in LUSC. The miRWalk database was adopted to analyse the gene miRNA interaction network of GADD45B in LUSC. Results: GADD45B expression was decreased in most of the malignancies, with relation to the poor prognosis in LUSC. GADD45B also significantly affected the survival of LUSC subgroups divided by clinic data. GADD45B significantly correlates with and may stimulate T cell exhaustion in LUSC. Conclusions: GADD45B is a prognostic indicator in multiple tumours, especially in LUSC. Moreover, modulating GADD45B expression may improve immunotherapy efficacy in LUSC. [ABSTRACT FROM AUTHOR]

Uranium extraction from seawater (UES), a potential approach to securing the long-term uranium supply and sustainability of nuclear energy, has experienced significant progress in the past decade. Promising adsorbents with record-high capacities have been developed by diverse innovative synthetic strategies, and scale-up marine field tests have been put forward by several countries. However, significant challenges remain in terms of the adsorbents' properties in complex marine environments, deployment methods, and the economic viability of current UES systems. This review presents an up-to-date overview of the latest advancements in the UES field, highlighting new insights into the mechanistic basis of UES and the methodologies towards the function-oriented development of uranium adsorbents with high adsorption capacity, selectivity, biofouling resistance, and durability. A distinctive emphasis is placed on emerging electrochemical and photochemical strategies that have been employed to develop efficient UES systems. The most recent achievements in marine tests by the major countries are summarized. Challenges and perspectives related to the fundamental, technical, and engineering aspects of UES are discussed. This review is envisaged to inspire innovative ideas and bring technical solutions towards the development of technically and economically viable UES systems. [ABSTRACT FROM AUTHOR]

Shrinkage greatly influences the mechanical and fatigue properties of compacted graphite iron and it is necessary in order to study the causes of shrinkage in compacted graphite iron and to predict it effectively. In this paper, a kind of cylindrical necking test sample was designed to evaluate the shrinkage in compacted graphite iron, and a method to calculate the size of shrinkage was proposed. By observing the microstructure around the shrinkage zone, it is concluded that concentrated shrinkage mainly appears in the solidification region where the dendritic gap is closed, and the isolated shrinkage mainly occurs in the final solidification region, and the supersaturated carbon elements are gathered on the surface of the shrinkage. The cause of shrinkage in compacted graphite iron is caused by its solidification method, where the austenite dendrites and the eutectic clusters are generated close to the melt zone during the solidification process, leading to the inability to feed the shrinkage. Based on the thermodynamic analysis, the equations between the volume change of each phase, solid phase rate, and time during solidification of compacted graphite iron were established to theoretically explain the formation mechanism of the shrinkage. Taking nine parameters such as the chemical elements and characteristic values of thermal analysis as the input nods, a four-layer BP neural network model for predicting the size of shrinkage in compacted graphite iron was constructed, and the R-squared of the model reached 97%, which indicates it could be used to predict the shrinkage tendency. [ABSTRACT FROM AUTHOR]

Converting triacylgycerols (TAGs) from edible oils and fats into structured diacylglycerols (DAGs) is meaningful for reducing obesity. Camellia oil, rich in linoleic acid, has the potential to form structured linoleic acid‐1,3‐diacylglycerol (LA‐1,3‐DAG) nutrients in the industry. In this research, the physicochemical properties of modified Camellia oil (MCO) by enzymatic esterification were analyzed by Gas Chromatography‐Mass Spectrometry (GC‐MS), Differential Scanning Calorimetry (DSC), High Performance Liquid Chromatography‐Evaporative Light Scattering Detection (HPLC‐ELSD), and Ultra Performance Liquid Chromatography‐Tandem Mass Spectrometry (UPLC‐MS/MS). The relationship between reaction conditions and the DAG compositions is disclosed using multiple factors. It is found that high constituents of DAG increase the melting and crystallization temperature of MCO, lipase Novozym 435 gives the best yield of targeted nutrients (DAG, 1,3‐DAG, LA‐DAG), and the mixture of lipases, Lipozyme TL IM and Lipozyme RM IM, shows a synergistic effect in the synthetic process of DAG. Subsequently, MCO containing 65.4% DAG, 54.7% LA‐DAG, and 47.6% 1,3‐DAG content at optimal conditions (2% enzyme dosage, 4 h reaction time, 2.4:1 substrate molar ratio, 25.8% t‐butanol as solvent, 60°C temperature) has been obtained and purified using silica column to obtain the final DAG oil containing 96.1% DAG, 64.7% 1,3‐DAG, and 78.4% LA‐DAG. High constituents of structured DAG oil rich in LA‐1,3‐DAG can be obtained by enzymatic esterification for industrial production. [ABSTRACT FROM AUTHOR]

• White matter (WM) microstructures are altered in rheumatoid arthritis (RA) • Fractional anisotropy of prefrontal WM tracts is reduced in RA patients. • WM abnormalities in RA patients are significantly associated with pain scores. • Prefrontal cortex is a potential target for neuromodulation in RA treatment. Structural and functional brain imaging studies have reported abnormalities of gray matter morphology and functional activities in patients with rheumatoid arthritis (RA). However, it is largely unknown whether patients with RA show alterations of white matter microstructural organization. To automatically identify alteration of white matter microstructure in patients with RA and further examine how this alteration associates with clinical characteristics. This single-institutional prospective study included 66 participants (33 patients with RA [52 ± 9 years, 29 women] and 33 sex/age-matched healthy controls [53 ± 12 years, 27 women]), who underwent diffusion MRI scan from January 2021 to December 2021. The white matter microstructure was assessed using fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. Voxelwise analyses were conducted on white matter skeleton using an automated, observer-independent tract-based spatial statistics analysis. The relationship between white matter microstructural alterations and clinical and neuropsychological variables was evaluated using correlation analysis. Compared with healthy controls, patients with RA exhibited lower fractional anisotropy in several major white matter tracts (threshold-free cluster enhancement at P < 0.05 for multiple comparison correction, permutation test), involving the forceps minor, bilateral inferior fronto-occipital fasciculus, bilateral anterior thalamic radiation, and bilateral uncinate fasciculus. Lower fractional anisotropy values in the patients with RA were significantly associated with pain-related assessments, including tender joint count (r = -0.43, P = 0.015), Clinical Disease Activity Index score (r = -0.36, P = 0.049), pain severity rated through visual analogue scale (r = -0.45, P = 0.012), and Simplified Disease Activity Index score (r = -0.36, P = 0.045). No significant group difference was found in mean diffusivity, axial diffusivity, and radial diffusivity. We report the first anatomical evidence for aberrant microstructure organization of several major white matter tracts and its associations with pain processing in patients with rheumatoid arthritis. [ABSTRACT FROM AUTHOR]

Disruption of the epithelial-mesenchymal transition (EMT) of activated lung cells is an important strategy to inhibit the progression of idiopathic pulmonary fibrosis (IPF). The present study investigated the role of exosomes derived from airway basal cells on EMT of lung cells and elucidate the underlying mechanism. Exosomes were characterized by nanoparticle tracking analysis, transmission electron microscopy imaging and markers detection. The role of exosome on the EMT of lung epithelial cells and lung fibroblasts induced by TGF-β1 was detected. RNA sequencing screened dysregulated genes in exosome-treated group, followed by the bioinformatical analysis. One of the candidates, anoctamin-1 (ANO1), was selected for further gain-and-loss phenotype assays. A bleomycin-induced pulmonary fibrosis model was used to evaluate the treatment effect of exosomes. Exosomes were round-like and positively expressed CD63 and tumor susceptibility gene 101 protein. Treatment with exosomes inhibited the EMT of lung cells activated by TGF-β1. 4158 dysregulated genes were identified in exosome-treated group under the threshold of |log2 fold-change| value >1 and they were involved in the metabolism of various molecules, as well as motility-related biological processes. A key gene, ANO1, was verified by reverse transcription-quantitative PCR, whose overexpression induced the EMT of lung cells. By contrast, ANO1 knockdown reversed the EMT induced by TGF-β1. In vivo assay indicated that exosome treatment ameliorated pulmonary fibrosis and inhibited the upregulation of ANO1 induced by bleomycin. In conclusion, airway basal cell-derived exosomes suppressed the EMT of lung cells via the downregulation of ANO1. These exosomes represent a potential therapeutic option for patients with IPF. [ABSTRACT FROM AUTHOR]

Sepsis is a life-threatening condition, caused by the body's extreme response to an infection. In the United States, 1.7 million cases of sepsis occur annually, resulting in 265,000 deaths. Delayed diagnosis and treatment are associated with higher mortality rates. An exponential rise in the availability of medical data has allowed for the development of sophisticated machine learning algorithms to predict sepsis earlier than the onset. However, these models often underperform, as the training data are retrospective and do not fully capture the uncertain future. In this study, we develop a novel framework, which we refer to as MLePOMDP, to leverage and combine the underlying, high-level knowledge about sepsis progression and machine learning (ML) for classification. Specifically, we use a hidden Markov model to describe sepsis development at a high level, where the ML model makes the higher-order "observations" from temporal data. Consequently, a partially observable Markov decision process (POMDP) model is developed to make classification decisions. We analytically establish that the optimal policy is of threshold-type, which we exploit to efficiently optimize MLePOMDP. MLePOMDP is calibrated and tested using high-frequency physiological data collected from bedside monitors. Different from past POMDP-based frameworks, MLePOMDP is developed for a prediction task using a very small state definition, produces highly interpretable results, and accounts for a novel and clinically meaningful action space. Our results show that MLePOMDP outperforms machine learning–based benchmarks by up to 8% in precision. Importantly, MLePOMDP is able to reduce false alarms by up to 28%. An additional experiment is conducted to show the generalizability of MLePOMDP to different patient cohorts. Summary of Contribution: This study develops a novel real-time decision support framework for early sepsis prediction by integrating well-known machine learning models (random forest and neural networks) with a well-established sequential decision-making model, namely, a partially observable Markov decision process (POMDP). The structural properties of the optimal policy are further explored and a threshold-type structure is established, which is then leveraged to develop a customized algorithm to solve the problem more efficiently. The resulting framework demonstrates the benefit of applying POMDPs to augment machine learning outputs. Specifically, the framework results in the reduction of false alarms in sepsis predictions where decisions are made in real time, hence improving the overall prediction precision. [ABSTRACT FROM AUTHOR]

This article presents a novel asymmetric spoke‐type rotor structure. It is used to reduce rotor magnetic flux leakage, torque ripple and no‐load back‐EMF distortion rate while increasing the motor output torque. The traditional method of optimizing torque pulsation is the inverse cosine function, which gives a sinusoidal distribution of the air‐gap magnetic field under no‐load conditions of the motor. The fundamental wave magnetic field of the air‐gap synthetic magnetic field under the load is offset from the no‐load air‐gap magnetic field. This paper presents the design theory and method of the new type of the asymmetric rotor. Asymmetric spatial harmonics are introduced to the rotor so that the motor has a sinusoidal distribution of the rated load air‐gap field under MTPA control. In order to verify the superiority of the new rotor, the performance of four different spoke‐type rotor structure motors under the same pole‐slot combination was compared. Finally, an experimental prototype is built to verify the theoretical reliability against the design of this paper. [ABSTRACT FROM AUTHOR]

A binary solvent synthetic strategy is proposed for the construction of C2‐symmetric molecule‐based hydrogen‐bonded organic frameworks (HOFs) with permanent ultra‐micropores and surface polarization derived from tunable coplanar open oxygen atoms. The activated HOFs BTBA‐1 a and PTBA‐1 a show highly selective separation of CO2/N2 with a record high ideal adsorbed solution theory (IAST) selectivity >2000 under ambient temperature and pressure. [ABSTRACT FROM AUTHOR]

A binary solvent synthetic strategy is proposed for the construction of C2‐symmetric molecule‐based hydrogen‐bonded organic frameworks (HOFs) with permanent ultra‐micropores and surface polarization derived from tunable coplanar open oxygen atoms. The activated HOFs BTBA‐1 a and PTBA‐1 a show highly selective separation of CO2/N2 with a record high ideal adsorbed solution theory (IAST) selectivity >2000 under ambient temperature and pressure. [ABSTRACT FROM AUTHOR]

Doping alkali metal atoms, especially lithium (Li), in nanocarbon materials has always been considered to be one of the most effective methods to improve the optical properties of the system. In this theoretical work, we doped a Li atom to the recently observed all-carboatomic molecule, cyclo[18]carbon (C 18), and finally obtained two stable configurations with Li inside and outside the ring. The calculation results show that the energy barrier of transition between the two Li@C 18 configurations is low, so the conversion is easy to occur at ambient temperature. Further study reveals that the state of Li@C 18 complex, namely its dominant configuration, can be switched by applying a proper external electric field (EEF). The electronic structure, absorption spectrum, and optical nonlinearity of the two configurations are found to be significantly different, which indicates that the optical properties of the Li@C 18 complex can be effectively regulated by switching the location of doped Li atom between inside and outside the carbon ring. With the help of various wavefunction analysis methods, the nature of the discrepancies in the properties of Li@C 18 complex with different configurations was deeply revealed. The relevant results are expected to provide theoretical guidance for development of cyclocarbon-based optical molecular switches. [Display omitted] [ABSTRACT FROM AUTHOR]

The bonding character, electron delocalization, and aromaticity of the cyclo[18]carbon (C18) precursors, C18‐(CO)n (n=6, 4, and 2), have been studied by combining quantum chemical calculations and various electronic wavefunction analyses with different physical bases. It was found that C18‐(CO)n (n=6, 4, and 2) molecules exhibit alternating long and short C−C bonds, and have out‐of‐plane and in‐plane dual π systems (πout and πin) perpendicular to each other, which are consistent with the relevant characteristics of C18. However, the presence of carbonyl (‐CO) groups significantly reduced the global electron conjugation of C18‐(CO)n (n=6, 4, and 2) compared to C18. Specifically, the ‐CO group largely breaks the extensive delocalization of πin system, and the πout system is also affected by it but to a much lesser extent; as a consequence, C18‐(CO)n (n=6, 4, and 2) with larger n shows weaker overall aromaticity. Mostly because of the decreased but still apparent πout electron delocalization in the C18‐(CO)n (n=6, 4, and 2), a notable diatropic induced ring current under the action of external magnetic field is observed, demonstrating the clear aromatic characteristic in the molecules. The correlation between C18‐(CO)n (n=6, 4, and 2) and C18 in terms of the gradual elimination of ‐CO from the precursors showed that the direct elimination of two CO molecules in C18‐(CO)n (n=6, 4, and 2) has a synergistic mechanism, but it is kinetically infeasible under normal conditions due to the high energy barrier. [ABSTRACT FROM AUTHOR]

It has been reported that introducing Ag interlayer at the Cu/Bi 2 Te 3 interface can achieve ultra-low electrical contact resistivity. However, there is no consensus on the influence of Ag diffusion induced by Ag interlayer on electrical contact. Thus, the impact of Ag diffusion on electrical contact conductivity for Cu/Ag/Bi 2 Te 3 multilayers was investigated. The generation of interfacial compounds induced by Ag diffusion was analyzed and the contact resistivity was measured in Cu/Ag/Bi 2 Te 3 multilayers with different Ag interlayer thickness before and after annealing. It was found that Ag diffusion induced interfacial compounds Cu 4 Ag 3 Te 4 at the Cu/Ag interface before annealing, which could decrease contact resistivity to 3.728×10−12 Ω∙m2. After annealing, the relative amount of Cu 4 Ag 3 Te 4 at the Cu/Ag interface slightly decreased, and the Ag 2 Te was found to appear at the Ag/Bi 2 Te 3 interface, which could further decrease contact resistivity to 3.187×10−12 Ω∙m2. With Ag interlayer thickness increasing from 50 nm to 300 nm, the contact resistivity decreased from 3.726×10−10 Ω∙m2 to 3.728×10−12 Ω∙m2 before annealing because the relative amount of Cu 4 Ag 3 Te 4 increased about 5 times, after annealing the contact resistivity further decreased by 10.27∼41.7 % because the relative amount of Ag 2 Te increased about 1.1 times. In addition, we had optimized the ultra-low contact resistivity test method by redesigning the structure of test samples and modifying the formula of contact resistivity to eliminate two errors. One is caused by Cu electrode short-circuit resistance due to the test current being short-circuited by the middle electrode between two test electrodes. The other is caused by the increased electrical resistance of Bi 2 Te 3 thin film due to Te atom volatilization after annealing. The results showed that the errors of the test results were reduced by at least 21.50 %. Our work provides guidance for further optimizing electrical contact of thin-film thermoelectric devices. [Display omitted] • The influence of Ag diffusion on contact resistivity is investigated. • The variation of contact resistivity with Ag interlayer thickness is studied. • Interfacial compounds induced by Ag diffusion is semi-quantitatively analyzed. • Ultra-low contact resistivity test method is optimized by eliminating two errors. [ABSTRACT FROM AUTHOR]

[Display omitted] • The incorporation of Al provided abundant As 2 O 3 adsorption sites. • Facilitates the dissociation of O 2 and promotes reaction with chained As 2 O 3. • Lower activation energy for the oxidation of As(III) to As(V). • Transformation of the Ca site from physisorption sites to chemisorption sites. Doping techniques have the potential to enhance the adsorption and oxidation of As 2 O 3 by metal oxides for the augmentation of arsenic capture. However, the mechanisms of this facilitating effect, especially concerning the oxidation of As 2 O 3 , require further exploration. This study focuses on the effect of Al doping on As 2 O 3 adsorption and oxidation through experimental and density functional theory calculations. The introduction of aluminum increases the specific surface area and stimulates charge transfer, converting Ca atoms into new As 2 O 3 adsorption sites with strong adsorption capacity. The arsenic capture capacity of Al 2 O 3 /CaO is almost twice that of CaO when the molar ratio of Al and Ca is 1:6. For arsenic oxidation, Al doping promotes the dissociation of O 2 adsorbed on the sorbent surface, making it more prone to react with As 2 O 3. This catalytic effect lowered the activation energy for the conversion of As(III) to As(V), increasing the oxidation efficiency by 2–10%. These results serve as valuable references for the development of efficient arsenic sorbents. [ABSTRACT FROM AUTHOR]

[Display omitted] • Dynamic hydrothermal method could accelerate the Ni-phyllosilicate synthesis. • Glycerol modification significantly reduced the thickness of Ni-phyllosilicate nanosheets. • Synergistic effect of stirring and viscous solvent led to enhanced activity for CO 2 methanation. • Viscous solvent-assisted dynamic hydrothermal method was competitive to synthesize Ni-phyllosilicate. To address the shortcomings of poor convection and product agglomeration of the static hydrothermal method, the dynamic hydrothermal method together with the viscous solvent-assisted dynamic hydrothermal method were proposed to synthesize Ni-phyllosilicate in this work. Stirring seemed to be powerful to accelerate the synthesis with significant increase of Ni content from 11.80 wt% (static synthesis) to 23.13 wt% (dynamic synthesis). The further modification of glycerol increased the shearing force to exfoliate the Ni-phyllosilicate nanosheets during dynamic synthesis, whose thickness could reach 1.17 nm with improved metal utilization ratio after reduction. As a result, the activity of CO 2 methanation was enhanced with large TOF CO2 of 3.5 × 10−2 s−1 and small E a of 65.13 kJ·mol−1. In situ DRIFTS analysis confirmed the existence of high actively intermediate of m -HCOO− and *CO, which could be further hydrogenated into CH x species. In short, the synergistic effect of dynamic stirring and glycerol modification drove the enhancement of catalytic activity, and also provided the possibility of large-scale production of Ni-phyllosilicate using hydrothermal method. [ABSTRACT FROM AUTHOR]

Diamond-like cubic silicon (d-Si) has become a mainstay material for new energy and modern electronics industries. Nevertheless, such material hosts a high lattice thermal conductivity, resulting in a small thermoelectric figure of merit (ZT), which greatly limits its applications in thermoelectric conversion field. tP36-Si is a newly predicted allotrope of silicon with direct band gap, and its total energy is close to d-Si, which indicates that it is likely to be experimentally prepared in years to come. In this article, the thermoelectric properties of this novel new silicon allotrope are researched by combining semi-classical Boltzmann transport theory with first-principles calculation. Electron transport of this new silicon allotrope possesses obvious anisotropy, while the anisotropy of phonon thermal conductivity is slight. Compared to d-Si and other silicon allotropes (Si 24 , oP32-Si), lower lattice thermal conductivity (23.68 W/mK) and higher power factor (72.63 W/mK 2) are revealed in tP36-Si. Further analysis shows that the lower phonon thermal conductivity principally comes from the inhibition of group velocity and relaxation time of phonon. The thermoelectric performance of tP36-Si is evaluated according to the electronic relaxation time obtained from the deformation potential (DP) theory, where the peak value of ZT along the xx lattice direction of n-type (p-type) under 700 K is close to 2.18 (0.64), which is much above that of Si24(0.69, 0.51) and d-Si(0.07). The finding illustrates the excellent thermoelectric property of tP36-Si and demonstrate that this new silicon allotrope is an appropriate and promising potential thermoelectric materials. [ABSTRACT FROM AUTHOR]

The key to direct methanol fuel cells (DMFCs) is the anode catalyst for methanol oxidation reaction (MOR) which has good catalytic activity and stability. Pt@CoO x @N-C catalysts were synthesized by compounding Pt nanoparticles and CoO x with nitrogen-doped porous carbon (N-C). Pt nanoparticles were prepared by solution plasma technique. CoO x @N-C are derived from zeolitic-imidazolate-framework-67 (ZIF-67) by heat treatment at 700 °C. For MOR, Pt@CoO x @N-C exhibits an outstanding electrocatalytic performance (mass activity of 2400 mA mg Pt −1) and stability (70% remained after 300 cycles) under acidic condition, which owing to the synergistic effects among the Pt nanoparticles, CoO x and nitrogen-doped porous carbon. Pt@CoO x @N-C shows such mass activity superior to that of Pt/C (460 mA mg Pt −1) due to the fact that CoO can adsorb –OH in the solution and then assist Pt to oxidize the CO-like intermediates to CO 2 which improves the resistance to CO poisoning of Pt nanoparticles. Therefore, solution plasma method assisted with metal-organic frameworks have good development prospects on synthesis of highly efficient electrocatalysts. [Display omitted] • The Pt@CoO x @N-C was synthesized by solution plasma assisted with MOF. • The Pt@CoO x @N-C deliver a high mass activity of 2400 mA mg Pt −1 for MOR. • The Pt@CoO x @N-C exhibits good stability (70% remained after 300 cycles). • Nitrogen-doped carbon and CoO x can increase MOR performance together. [ABSTRACT FROM AUTHOR]

This paper makes use of the characteristics of initial sensitivity and randomness of the chaotic map to design an image encryption algorithm based on the sine map and the tent map. The sine map is used to improve the tent map; then, the improved sine-tent map is proposed. The traditional tent map proposed in this paper has an expanded control parameter range and better chaos. In this algorithm, bit rearrangement is adopted to further improve the improved sine-tent map, which can reconstruct the output value and expand the chaotic characteristics of the map. In this algorithm, the image parameters are connected with the algorithm to generate the key. In the encryption step, a method of replacing the most significant bit and scrambling-diffusion algorithm is designed to encrypt the plaintext image. Finally, the algorithm is simulated with the experiment and evaluated with analysis; then, the experimental results are given. The evaluation results show that the ciphertext of the algorithm has high randomness, strong robustness, and better resistance to differential attacks after comparison. The correlation of the ciphertext image pixels is very low, and the algorithm is highly secure as a conclusion. [ABSTRACT FROM AUTHOR]

WO3 nanowires (NWs) have emerged as a promising alternative electrocatalyst for the photoelectrochemical (PEC) oxygen evolution reaction (OER), due to their nontoxicity, low cost, good stability, and strong photocatalytic oxidation ability. However, a significant challenge is limited by the poor electrical conductivity and the rapid recombination rate of photogenerated carriers. This paper reports a facile and effective way to synthesize the WO3 NWs with oxygen vacancies (Ov-WO3 NWs), which have high PEC OER activity and good stability. Photoelectric measurements indicate that the Ov-WO3 NW-based device shows a good light-harvesting property under visible light and a prolonged photoresponse time. Electrochemical impedance spectra measurements reveal a reduced value of Rct denoting an improved electrical conductivity, which should be responsible for the superior PEC OER performance. Our work provides a strategy for fabricating efficient water-splitting electrodes to help establish rational design principles for future OER catalysts. [ABSTRACT FROM AUTHOR]

Inspired by recent experimental observation of molecular morphology and theoretical predictions of multiple properties of cyclo[18]carbon, we systematically studied the photophysical and nonlinear optical properties of cyclo[2N]carbons (N=3–15) allotropes through density functional theory. This work unveils the unusual optical properties of the sp‐hybridized carbon rings with different sizes. The remarkable size dependence of the optical properties of these systems and their underlying nature are profoundly explored, and the relevance between aromaticity and optical properties are highlighted. The extrapolation curves fitted for energy level of frontier molecular orbitals, maximum absorption wavelength, and (hyper)polarizability of considered carbon rings are presented, which can be used to reliably predict corresponding properties for arbitrarily large carbon rings. The findings in this study will facilitate the exploration of potential application of cyclocarbons in the field of optical materials. [ABSTRACT FROM AUTHOR]

The online version of the original article can be found at https://doi.org/10.1186/s12933-023-01839-y B Correction to: Cardiovascular Diabetology (2023) 22:125 b https://doi.org/10.1186/s12933-023-01839-y Following publication of the original article [[1]], the author noticed the error in figure. In the image of Figure 1D, the forest plot of Figure 1D does not match the corresponding odds ratio (OR) and 95% confidence interval (CI). [Extracted from the article]

With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impact-increment method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy. [ABSTRACT FROM AUTHOR]

The Storm Water Management Model (SWMM) is a hydrological model for simulating and predicting runoff. Although powerful, SWMM can be computationally demanding. Therefore, we develop machine learning (ML) models to approximate the behavior of SWMM and expedite the task of predicting runoff. We perform a case study for the First Creek watershed in Knoxville, Tennessee, USA. We train ML models using rainfall data and subcatchment characteristics and apply feature engineering and clustering to objectively compare the outputs from SWMM and ML models. The results show that random forests can predict runoff volume accurately, with a Mean Absolute Error (MAE) of 0.006 (0.001) ${10^6}$ 10 6 gallons, where predictions are made almost instantaneously. Hence, our proposed ML-based approach can accurately predict runoff while greatly reducing computational requirements, filling a critical need in the field. [ABSTRACT FROM AUTHOR]

Recently, Shuhong Xu et al. reported theoretical calculation of molecular structure, bonding, aromaticity, electron delocalization, and electronic spectrum of cyclo[18]carbon in J. Mol. Model., 26, 111 (2020). Due to inappropriate consideration of calculation strategy, misunderstanding of some analysis methods and concepts, and some errors in the data, there are misleading statements and unconvincing conclusions in their paper. Here, we will point out inadequacies of Shuhong Xu's paper and put forward our own views. The contents of this comment will also help those who are studying cyclo[18]carbon to better understand this system and its analogues. [ABSTRACT FROM AUTHOR]

Over the past decades, complex deposition patterns after the evaporation of particle-laden droplets spark intense interest in interpreting the formation of deposition patterns due to their numerous applications in biomedicine, ink-jet printing, biopsy, etc. This work experimentally studies the formation of deposition patterns during evaporation of the magnetic nanofluid (MNF) droplet stands on a smooth glass/hydrophobic surface at different substrate temperatures. A CCD camera mounted on the microscopy is used to capture the process of droplet evaporation. An infrared camera is applied to quantify the temperature distribution along the vapour-liquid interface of the evaporating droplet. Additionally, 3 μm sized microbeads are applied to track the flow motion of the solute inside for different temperatures. The evaporation of sessile droplets has been conducted by controlling substrate temperature, which ranges from 10 °C to 70 °C. The experimental results show that there are three distinct patterns with the increasing temperature, namely a uniform pattern, a typical 'coffee ring' pattern, and a dual ring pattern. The experimental results show that Marangoni flow becomes essential for the formation of a secondary ring pattern with increasing substrate temperatures. This study shows that controlling substrate temperature is an efficient and simple method to control the formation of the sessile droplet. [ABSTRACT FROM AUTHOR]

Regional integrated system (RIES) bridges the gaps among different energy systems by various energy conversion equipment. While this integration brings forth numerous benefits, it introduces cross-system failures, where a contingency in one system may affect others. This poses significant challenges when evaluating the consequences of such contingencies. To address this, a risk assessment approach is developed for RIES, considering cross-system failures, as well as fluctuations in renewable generation and multi-energy loads. Event tree analysis (ETA) is adopted to simulate the propagation of failures and identify the affected components. Nine risk indices are proposed to quantify the operational risk of RIES at various levels. Additionally, root cause identification and weak point location are developed to formulate risk alleviation strategies. To validate the proposed method, a RIES with 101 nodes is utilized for risk assessment, and multiple risk alleviation strategies are determined. The results demonstrate the effectiveness of the proposed method, providing valuable insights for operators in ensuring the safety of RIES. • RIES risk assessment approach quantifies uncertainties of component failure and source-load fluctuation with nine indices. • Cross-system failures in RIES are classified into three categories to describe the interaction between subsystems. • Techniques for root cause identification and weak point location are proposed to alleviate risk. [ABSTRACT FROM AUTHOR]

• Open-cage fullerene derivatives react readily with ortho -phenylenediamine. • Open-cage fullerenes form stable mono-Pt and bis-Pt complexes. • Fullerene C C on the rim of the orifice form η 2-type coordination complex with Pt. Three new open-cage fullerene derivatives with a 19-membered orifice have been prepared, two of which readily formed Pt complexes when treated with Pt(PPh 3) 4. Several related open-cage fullerene derivatives were also found to form very stable platinum complexes, which could be purified by chromatography on silica gel under ambient conditions. Single crystal X-ray diffraction data revealed that the Pt metal formed η 2-type coordination pattern with a fullerene double bond on the rim of the orifice. Regio-selectivity of the platinum coordination is determined by the electron density of double bonds on the cage. The most electron deficient double bond shows the highest reactivity. [ABSTRACT FROM AUTHOR]

• GHz acoustic resonator based microfluidic sonoelectrochemical platform was developed. • Flexibly and accurately controlling the fluid flow in microfluidic channel was achieved. • On-chip sonoelectrochemical deposition of nanoparticles and sensing of H 2 O 2 was improved. • Tracking intracellular H 2 O 2 release to identify the cancer cells from normal cells was evaluated. Developing effective strategies for the flexible control of fluid is vital for microfluidic electrochemical biosensing. In this study, a gigahertz (GHz) acoustic streaming (AS) based sonoelectrochemical system was developed to realize an on-chip surface modification and sensitive hydrogen peroxide (H 2 O 2) detection from living cells. The flexible and controlled fluid surrounding the electrochemical chip was optimized theoretically and applied in the sonoelectrochemical deposition of Au nanoparticles (AuNPs) first. Under the steady and fast flow stimulus of AS, AuNPs could be synthesized with a smaller and evener size distribution than the normal condition, allowing AuNPs to show an excellent peroxidase-like activity. Moreover, the AS also accelerated the mass transport of target molecules and improved the catalytic rate, leading to the enhancement of H 2 O 2 detection, with an extremely low detection limit of 32 nM and a high sensitivity of 4.34 μA/ (mM·mm2). Finally, this system was successfully applied in tracking H 2 O 2 release from different cell lines to distinguish the cancer cells from normal cells. This study innovatively integrated the surface modification and molecules detection process on a chip, and also proposed a simple but sensitive platform for microfluidic biosensing application. [ABSTRACT FROM AUTHOR]

Superconducting metallic transition-metal nitrides, especially from the family of NbNx, are promising in various applications. Due to the fact that the lattice constants and the crystal structures are similar to those of GaN, GaN/NbN heterostructures have been grown to combine the benefits of superconductors and semiconductors, where the thermal transport property is of great significance. In this Letter, the thermal transport property of metallic hexagonal NbN is studied using a first-principles approach with the consideration of both electron and phonon scatterings. It is interesting to find that unlike most metals, phonons play a bigger role in hexagonal NbN compared to electrons, due to a relatively small electron density of states near the Fermi level. At room temperature, our calculated thermal conductivity is close to the experimental data. Our findings can provide a deeper understanding of how heat is transported in metallic transition-metal nitrides and may help design semiconductor/superconductor heterostructures. [ABSTRACT FROM AUTHOR]

The vibrational spectra of cyclo[18]carbon and its analogues, cyclo[2n]carbon (n=3 to 15), were carefully simulated and characterized. The in‐plane C−C stretching vibrations shows strong rigidity, while out‐of‐plane motions seem to be extremely flexible. The solvation effect can enhance signal strengths of the vibrational spectra, but does not evidently change the shape of the spectral curves. The infrared and Raman spectra of cyclo[2n]carbons are quite sensitive to ring size in the range of n=3 to 7, while the size only modestly affects peak positions and strengths for larger rings. Molecular dynamic trajectories show that the fluctuation period of the skeleton of cyclo[18]carbon is basically constant at different temperatures, and they are all about 300 fs. With increase of simulation temperature, the ring distortion due to thermal motion is notable and becomes much stronger. However, neither ring breaking nor isomerization in cyclo[18]carbon is observed during the simulations untill 298.15 K. [ABSTRACT FROM AUTHOR]

Recently, an intriguing all-carboatomic ring, cyclo[18]carbon, was observed in the condensed phase for the first time, and it quickly attracted widespread attention. In this article, we first investigated the interaction of the cyclo[18]carbon with external environment through electrostatic potential and our recently proposed van der Waals potential, and then examined the strength and nature of the intermolecular interactions between cyclo[18]carbon and various small molecules in detail by state-of-art quantum chemistry calculations and elaborate wavefunction analyses. Finally, we studied the cyclo[18]carbon dimer, which is closely related to actual status of the cyclo[18]carbon in condensed phase. These researches show that the cyclo[18]carbon has a strong tendency to adsorb small molecules to or near its ring center, and the dispersion attraction is found to play a leading role in the binding interaction, while the electrostatic effect has a nonnegligible influence on the configuration of the molecular complexes. Two cyclo[18]carbon molecules can form a relatively stable dimer through prominent π-π stacking effect. Its ideal configuration is found to have a face-to-face D 9d symmetry, but this geometry can be easily broken by relative sliding between the two rings due to thermal motion, as revealed by ab initio molecular dynamic simulation. Image 1 [ABSTRACT FROM AUTHOR]

The Roman domination problem (RDP) aims to find an optimal strategy to defend a graph or network with the least number of defenders. Although it holds great application potential to many fields, the RDP is mostly studied from theoretical aspects. In this paper, we extend the RDP and bridge the gap between theory and practice. Specifically, we define the k -strong Roman domination problem (k -SRDP), where defenders are assigned to a network to repel multiple simultaneous attacks. We propose an integer programming formulation of the problem, as well as a two-stage stochastic formulation using Benders decomposition. We show that the problem scale grows rapidly as the instance becomes larger. We prove the integrality of the second stage and propose two algorithms based on the L -shaped method. The algorithms are compared using randomly generated graph instances. Experimental results suggest that the proposed algorithms can solve the k -SRDP efficiently. • We defined the k strong Roman domination problem (k -SRDP). • We formulated an integer programming model for k -SRDP. • We proposed a two-stage stochastic programming model for k -SRDP. • We developed efficient solutions methods. • We evaluated the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

β-Ga2O3 is a wide-bandgap semiconductor of significant technological importance for electronics, but its low thermal conductivity is an impeding factor for its applications. In this work, an interatomic potential is developed for β-Ga2O3 based on a deep neural network model to predict the thermal conductivity and phonon transport properties. Our potential is trained by the ab initio energy surface and atomic forces, which reproduces phonon dispersion in good agreement with first-principles calculations. We are able to use molecular dynamics (MD) simulations to predict the anisotropic thermal conductivity of β-Ga2O3 with this potential, and the calculated thermal conductivity values agree well with experimental results from 200 to 500 K. Green–Kubo modal analysis is performed to quantify the contributions of different phonon modes to the thermal transport, showing that optical phonon modes play a critical role in the thermal transport. This work provides a high-fidelity machine learning-based potential for MD simulation of β-Ga2O3 and serves as a good example of exploring thermal transport physics of complex semiconductor materials. [ABSTRACT FROM AUTHOR]