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Abstract Suicide is prevalent among young adults, and epidemiological studies indicate that insomnia, nightmares, and depression are significantly associated with a high incidence of suicidal ideation (SI). However, the causal relationship between these factors and SI remains unclear. Therefore, the purpose of this study was to examine the association between nightmares and depression and insomnia and SI in young adults, as well as to develop a mediation model to investigate the causal relationship between insomnia, nightmare, depression, and SI. We assessed insomnia, nightmares, depression, and SI in 546 young adults using the Insomnia Severity Scale (ISI), Disturbing Dream and Nightmare Severity Scale (DDNSI), Depression Study Scale (CESD-20), and Columbia-Suicide Severity Rating Scale (C-SSRS). Using the Bootstrap method, the mediation effects of nightmares and depression between insomnia and SI were calculated. The results demonstrated that nightmares and depression fully mediated the relationship between insomnia and SI, including the chain-mediation of insomnia and SI between nightmare and depression with an effect value of 0.02, 95% CI 0.01–0.04, and depression as a mediator between insomnia and SI with an effect value of 0.22, 95% CI 0.15–0.29. This study found that depression and nightmares may be risk and predictive factors between insomnia and SI, which implies that the assessment and treatment of depression and the simple or linked effect of nightmares play crucial roles in preventing SI in young adults.

Abstract Background This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD). Methods A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software. Results A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences. Conclusions The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

ObjectivePiperacillin/tazobactam (PIP/TAZ) is used for the treatment of lower respiratory tract bacterial infections in children. This study was performed to evaluate if the current dosing regimen results in therapeutic drug concentrations.Patients and methodsPatients suspected or proven to have lower respiratory tract bacterial infection and administrated PIP/TAZ intravenously for a duration of no less than 0.5 h, q6h–q12h daily, were enrolled. Blood samples were collected, and PIP concentrations were determined by high-performance liquid chromatography. The individual predicted concentration of PIP was evaluated using the individual empirical Bayesian estimate method. The evaluated PK/PD targets included (1) 70% time when the predicted free drug concentration exceeds the minimum inhibitory concentration (fT > MIC) and (2) 50% fT > 4× MIC. Probability of target attainment (PTA) was assessed by the proportion of patients who reached the PK/PD targets. The PIP concentrations between different groups of patients were compared.ResultsA total of 57 samples were collected from 57 patients with a median age of 2.26 years (0.17–12.58). For the PK/PD targets of 70% fT > MIC and 50% fT > 4× MIC for Pseudomonas aeruginosa and Klebsiella pneumoniae, the PTA was all 0. The median Cmin of PIP was significantly higher in infants than in children, and the median Cmin after administration in q8h was significantly higher than that after administration in q12h.ConclusionThe current dose regimen of PIP/TAZ leads to extremely low plasma concentrations in most children with lower respiratory tract bacterial infections. More optimized dosing regimens or better alternative therapies need to be further explored.

ABSTRACT: Goose astrovirus genotype 2 (GAstV-2) mainly causes gout in goslings; therefore, it is a major pathogen threatening to goose flocks. However, the mechanisms underlying host-GAstV-2 interactions remain unclear because host cells suitable for GAstV-2 replication have been unavailable. We previously noted that GAstV-2 is primarily located in goose renal epithelial cells, where it causes kidney damage. Therefore, here, we derived goose primary renal tubular epithelial (RTE) cells (GRTE cells) from the kidneys of goose embryos after collagenase I digestion. After culture in Dulbecco's modified Eagle medium/Nutrient mixture F-12 with 10% fetal bovine serum (FBS), the isolated cells had polygonal with roadstone-like morphology; they were identified to be epithelial cells based on the presence of cytokeratin 18 expression detected through immunofluorescence assay (IFA). GAstV-2 infection in GRTE cells led to no obvious cytopathic effects; the maximum amounts of infectious virions were observed 48 h post infection through IFA and quantitative PCR. Next, RNA-seq was performed to identify and map post–GAstV-2 infection differentially expressed genes. The downregulated pathways were mainly related to metabolism, including tryptophan metabolism, drug metabolism by cytochrome P450, xenobiotic metabolism by cytochrome P450, retinol metabolism, butanoate metabolism, starch and sucrose metabolism, ascorbate and aldarate metabolism, and drug metabolism by other enzymes and peroxisome. In contrast, the upregulated pathways were mostly related to the host cell defense and proliferation, including extracellular matrix–receptor interaction, complement and coagulation cascades, phagosome, PI3K-Akt signaling pathway, human T-lymphotropic virus 1 infection, lysosome, and tumor necrosis factor signaling pathway. In conclusion, we developed a GRTE cell line for GAstV-2 replication and analyzed the potential host–GAstV-2 interactions through RNA-seq; our results may aid in further investigating the pathogenic mechanisms underlying GAstV-2 infection and provide strategies for its prevention and control.

Abstract In the context of rare but high‐impact extreme scenarios, such as natural disasters, it is crucial to utilize all available resources, including microgrids and distributed power sources, to restore critical loads in the distribution network as much as possible. This paper proposes a two‐stage resilience enhancement strategy for distribution networks considering post‐disaster topology reconstruction and demand response, aiming to facilitate the recovery of critical loads after disasters. In the first stage, a heuristic algorithm is introduced to determine the post‐disaster topology of the distribution network. In the second stage, by employing a step‐wise elastic load curve, user demand response is incorporated to maximize the socio‐economic value of the restoration, and resilience metrics are computed. Finally, the effectiveness of the proposed resilience restoration strategy is validated through simulations on Case33 and Case69 systems.

BackgroundEarly neurological deterioration (END) is a frequent complication in patients with perforating artery territory infarction (PAI), leading to poorer outcomes. Therefore, we aimed to apply machine learning (ML) algorithms to predict the occurrence of END in PAI and investigate related risk factors.MethodsThis retrospective study analyzed a cohort of PAI patients, excluding those with severe stenosis of the parent artery. We included demographic characteristics, clinical features, laboratory data, and imaging variables. Recursive feature elimination with cross-validation (RFECV) was performed to identify critical features. Seven ML algorithms, namely logistic regression, random forest, adaptive boosting, gradient boosting decision tree, histogram-based gradient boosting, extreme gradient boosting, and category boosting, were developed to predict END in PAI patients using these critical features. We compared the accuracy of these models in predicting outcomes. Additionally, SHapley Additive exPlanations (SHAP) values were introduced to interpret the optimal model and assess the significance of input features.ResultsThe study enrolled 1,020 PAI patients with a mean age of 60.46 (range 49.11–71.81) years. Of these, 30.39% were women, and 129 (12.65%) experienced END. RFECV selected 13 critical features, including blood urea nitrogen (BUN), total cholesterol (TC), low-density-lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB), atrial fibrillation, loading dual antiplatelet therapy (DAPT), single antiplatelet therapy (SAPT), argatroban, the basal ganglia, the thalamus, the posterior choroidal arteries, maximal axial infarct diameter (measured at < 15 mm), and stroke subtype. The gradient-boosting decision tree had the highest area under the curve (0.914) among the seven ML algorithms. The SHAP analysis identified apoB as the most significant variable for END.ConclusionOur results suggest that ML algorithms, especially the gradient-boosting decision tree, are effective in predicting the occurrence of END in PAI patients.

Objective: Preventing adverse events due to unstable oxygen saturation (SpO2) at night in pregnant women is of utmost importance. Poor sleep has been demonstrated to impact SpO2 levels. Nowadays, many gravida have a habit of prolonged exposure to light before sleep, which can disrupt their sleep. Therefore, this study aimed at investigate the relationship between lights-out time, sleep parameters and SpO2, exploring the underlying mechanisms. Methods: The data of 2881 eligible subjects from the Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-be and Sleep Disordered Breathing (nuMOM2b-SDB) database were analyzed. Multiple linear regression models were used to investigate the relationship between lights-out time and SpO2. In addition, restricted cubic splines (RCS) were employed to fit the nonlinear correlation between the two variables. The smoothing curve method was further utilized to depict the relationship between lights-out time and SpO2 based on various subgroup variables. Results: All participants were categorized according to race/ethnicity. A negative correlation was observed between nighttime lights-out time and average value of SpO2 (Avg-SpO2) (β = −0.05, p = 0.010). RCS revealed a U-shaped relationship between lights-out time and Avg-SpO2, with the turning point at 22:00. The subcomponent stratification results indicated that the Avg-SpO2 and minimum value of SpO2(Min-SpO2) of advanced maternal age decreased as the lights-out time was delayed. Furthermore, overweight and obese gravida showed lower Avg-SpO2 and Min-SpO2 levels than normal weight. Conclusions: A U-shaped relationship was identified between lights-out time and nocturnal Avg-SpO2 during early pregnancy, with the inflection at 22:00. Notably, later lights-out times are associated with lower levels of Min-SpO2 for advanced maternal age. The findings suggest that appropriately adjusting the duration of light exposure before sleep and maintaining a relatively restful state may be more beneficial for the stability of SpO2 in pregnant women. Conversely, deviations from these practices could potentially lead to pathological alterations in SpO2 levels.

ABSTRACT: Goose astrovirus (GAstV)-2, a novel pathogen identified in 2018, mainly causes visceral gout in goslings, leading to approximately 50% mortality. At present, no commercial veterinary products are available to prevent and treat the disease. Our previous studies showed that nitric oxide (NO) and inducible NO synthase (iNOS) were markedly higher in the kidney and spleen of goslings infected with GAstV-2, but their effects during GAstV-2 infection remain unclear. In the present study, goslings were intraperitoneally injected with aminoguanidine (AG)—an iNOS inhibitor—to examine the role of NO during GAstV-2 infection. AG significantly decreased the serum NO concentration and iNOS mRNA expression in the kidney. Moreover, AG reduced the mortality, serum uric acid and creatinine content, and urate deposition in visceral organs and joints. Histopathological analysis demonstrated that AG reduced renal tubular cell necrosis, inflammatory cell infiltration, glycogen deposition in glomerular mesangium, and interstitial fibrosis, suggesting alleviation of kidney lesions. Furthermore, AG decreased the expression of renal injury markers such as KIM-1 and desmin; inflammatory cytokine-related genes such as IL-1β, IL-8, and MMP-9; and autophagy-related genes and proteins such as LC3II, ATG5, and Beclin1. However, quantitative real-time PCR and immunohistochemistry showed that treatment with AG did not affect the kidney and liver viral load. These findings suggest that AG decreases the mortality rate and kidney lesions in goslings infected with GAstV-2 through mechanisms associated with autophagy and inhibition of inflammatory cytokine production in the kidney but not with GAstV-2 replication.

Abstract Over the years, people paid more attention to using renewable energy such as geothermal energy to decrease the dependency on fossil fuel energy. Organic Rankine cycle (ORC) can generate electricity by using low‐temperature heat sources, and geothermal energy is an ideal pollution‐free heat source that can provide continuous and stable energy. Meanwhile, the turbo expander, one of the essential components in ORC, has the advantages of high speed and single‐stage expansion ratio. In this work, we simulated and analyzed the flow field characteristics of the turbo expander under the assigned working conditions using CFX software. The results showed that the working fluid distributed uniformly in the volute, and there was no apparent whirlpool flow or secondary flow. The pressure near the leading edge of the impeller blade was sparse but became dense at the vicinity of the trailing edge. When the speed of the expander was 15000rad min−1 and the inlet pressure was 0.59 MPa, the isentropic efficiency reached the maximum value, and the change of the inlet temperature had little effect on the isentropic efficiency, which can be ignored in actual operation. The results guide in improving the practical application of geothermal energy.

Glutamine synthetase (GS) is a key enzyme involved in nitrogen metabolism. GS can be divided into cytosolic and plastidic subtypes and has been reported to respond to various biotic and abiotic stresses. However, little research has been reported on the function of GS in mulberry. In this study, the full length of MaGS2 was cloned, resulting in 1302 bp encoding 433 amino acid residues. MaGS2 carried the typical GS2 motifs and clustered with plastidic-subtype GSs in the phylogenetic analysis. MaGS2 localized in chloroplasts, demonstrating that MaGS2 is a plastidic GS. The expression profile showed that MaGS2 is highly expressed in sclerotiniose pathogen-infected fruit and sclerotiniose-resistant fruit, demonstrating that MaGS2 is associated with the response to sclerotiniose in mulberry. Furthermore, the overexpression of MaGS2 in tobacco decreased the resistance against Ciboria shiraiana, and the knockdown of MaGS2 in mulberry by VIGS increased the resistance against C. shiraiana, demonstrating the role of MaGS2 as a negative regulator of mulberry resistance to C. shiraiana infection.

Flexible sensors play an important role in simulation, brain-computer interaction, intelligent robots, and biological detection. Due to the progress of modern medical means, the construction of wearable flexible sensors to realize remote and continuous monitoring of human physical indicators and physiological parameters has become a hot research topic. Non-invasive sensor is a device that can detect physiological parameters without cutting the skin or puncturing the body. They have wide application prospects in the fields of medical treatment, fitness, and daily care due to the following advantages: real-time monitoring, portability, accuracy, and cost reduction. Liquid metal has become a great candidate for constructing flexible biosensors because of its high conductivity, deformability, self-healing, and bio-friendly properties, its spontaneous formation of an oxide film due to exposure to oxygen provides a convenient reaction platform for the preparation of other materials. Two-dimensional materials are inherently superior in preparing sensors due to their great advantages unique chemical and physical properties, their high surface area-to-volume ratios and ultra-high surface sensitivity to the environment also can be used to prepare flexible sensor. This study presents an overview and introduction of biosensors fabricated by liquid metal and two-dimensional materials, including how to prepare specific two-dimensional materials based on liquid metal, and the stripping method is also included. Three kinds of applications are discussed in detail, including the detection of human glucose concentration, pulse detection, and sweat analysis, whose sensing principles depend on piezoelectric, optical, and electrochemical. At the end of the article, we summarized the current challenges faced by biosensors based on liquid metal and looked forward to its future development and future directions of advances.

Superionic and electride behaviors in materials, which induce a variety of exotic physical properties of ions and electrons, are of great importance both in fundamental research and for practical applications. However, their coexistence in hot alkali-metal borides has not been observed. In this work, we apply first-principles structure search calculations to identify eight Na–B compounds with host–guest structures, which exhibit a wide range of building blocks and interesting properties linked to the Na/B composition. Among the known borides, Na-rich Na9B stands out as the composition with the highest alkali-metal content, featuring vertex- and face-sharing BNa16 polyhedra. Notably, it exhibits electride characteristics and transforms into a superionic electride at 200 GPa and 2000 K, displaying unusual Na atomic diffusion behavior attributed to the modulation of the interstitial anion electrons. It demonstrates semiconductor behavior in the solid state, and metallic properties associated with Na 3p/3s states in the superionic and liquid regions. On the other hand, B-rich NaB7, consisting of a unique covalent B framework, is predicted to exhibit low-frequency phonon-mediated superconductivity with a Tc of 16.8 K at 55 GPa. Our work advances the understanding of the structures and properties of alkali-metal borides.

Wind power generation is generally a large-capacity low-switching frequency power station, and photovoltaic power generation is generally a small-capacity high-switching frequency power station. Large-scale access of different types of new energy power stations increased risk of grid voltage fluctuations. Therefore, in order to analyze the variation law of the stability of different types of new energy sources connected to the weak grid, it is very important to analyze the stability of inverters with different switching frequencies, but there are few studies on this issue. In this paper, the detailed sequence impedance model of the current-controlled inverter is firstly established, and its correctness is verified by frequency sweeping. Secondly, considering the control bandwidth, ripple suppression and filtering performance, the filtering parameters of inverters with different switching frequencies are designed using a unified standard. On this basis, the stability criterion based on impedance ratio is used to analyze the stability variation law of inverters with different switching frequencies under strong and weak grid conditions. Finally, the correctness and accuracy of the theoretical analysis are verified by simulation experiments.

Droop control inverters are widely used because of their plug-and-play characteristics, no need for communication, and adaptability to weak power grids. However, because of the difficulty of islanding detection, after the grid is restored, drooping control inverters may cause security problems. In order to address this issue, this paper proposes an islanding detection method for droop control inverters based on impedance identification. By injecting current disturbance into common coupling points (PCC), the impedance is identified by the current response, and then the islanding can be determined by the impedance change. On the one hand, a signal extraction method based on positive–negative notch filters is proposed to reduce the content and impact on the power quality of the disturbance injection. On the other hand, this paper uses a signal processing method based on recursive discrete Fourier transform (RDFT), which can effectively reduce the computational burden. Moreover, the proposed method can eliminate the non-detection zone of the island detection. The experimental results verify the effectiveness of the proposed method.

BackgroundBrain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions.MethodA total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the “Segment” tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions.ResultsOur findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (β = −0.428, p = 0.007) and density (β = −0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear.ConclusionThe morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

NeRF has garnered extensive attention from researchers due to its impressive performance in three-dimensional scene reconstruction and realistic rendering. It is perceived as a potential pivotal technology for scene reconstruction in fields such as virtual reality and augmented reality. However, most NeRF-related research and applications heavily rely on precise pose data. The challenge of effectively reconstructing scenes in situations with inaccurate or missing pose data remains pressing. To address this issue, we examine the relationship between different resolution encodings and pose estimation and introduce BiResNeRF, a scene reconstruction method based on both low and high-resolution hash encoding modules, accompanied by a two-stage training strategy. The training strategy includes setting different learning rates and sampling strategies for different stages, designing stage transition signals, and implementing a smooth warm-up learning rate scheduling strategy after the phase transition. The experimental results indicate that our method not only ensures high synthesis quality but also reduces training time. Compared to other algorithms that jointly optimize pose, our training process is sped up by at least 1.3×. In conclusion, our approach efficiently reconstructs scenes under inaccurate poses and offers fresh perspectives and methodologies for pose optimization research in NeRF.

The large-scale access of renewable energy generation has caused weak grid and a series of instability issues. Virtual synchronous generators (VSG), which can support the voltage and frequency, are gaining increasing applications. At present, there are two main types of VSG. One is single-loop VSG containing only a power control loop. The other is multi-loop VSG containing not only a power control loop, but also a voltage inner loop and a current inner loop. Although both VSGs exhibit the external characteristics of synchronous generators, there are still some differences between them. However, there are few studies on this issue, which makes it difficult to choose which type VSG to use in practical application. This paper analyzes the differences between the two VSGs in terms of broadband stability and current distortion suppression capabilities, so as to provide a reference for related applications.

Abstract Current‐controlled inverters (CCIs), often used in renewable power generation, are prone to harmonic instability under weak grids with a low short‐circuit ratio (SCR). This paper proposes that this type of instability can be prevented by configuring part of the energy storage system (ESS) converters in the distribution network as voltage‐controlled inverters (VCIs). The main contributions of this paper are as follows: (1) A model of the CCI/VCI hybrid grid‐connected system is established, which can characterize not only the plant‐level stability, but also the unit‐level stability. (2) A rapid power control method for VCIs is proposed, which can improve the power control bandwidth of VCIs to tens of Hz to meet the rapidity requirements for ESS power control. (3) A capacity planning method is proposed, which can give the required minimum VCI/ESS capacity for a specific stability margin and SCR range. Analysis shows that as long as the ESS converters with a capacity of no less than 6% of the CCIs are configured as VCIs, large‐scale CCIs that are originally critically stable at SCR = 1.9 can operate stably under the very weak grid with SCR = 1.2. Finally, the proposed method is verified by simulations and experiments.

In clinic, the acquisition of airflow with nasal prongs, masks, thermistor to monitor respiratory function is more uncomfortable and inconvenience than surface diaphragm electromyography (EMGdi) using electrode pads. The EMGdi with strong electrocardiograph (ECG) interference affect the extraction of its characteristic information. In this work, surface EMGdi and airflow signals of 20 subjects were collected under 5 incremental inspiratory threshold loading protocols from quiet breathing to maximum forced breathing. First, we filtered out the ECG interference in EMGdi based on the combination of stationary wavelet transform and the positioning of ECG to obtain pure EMGdi (EMGdip). Second, the Spearman’s rank correlation coefficients between EMGdi and EMGdip quantified by time series fixed sample entropy (fSampEn), root mean square (RMS), and envelope were compared to verify the robustness of the fSampEn to ECG. A comparative analysis of correlation between fSampEn of EMGdi and inspiratory airflow and the correlation between envelope of EMGdip (EMGdie) and inspiratory airflow found that there was no significant difference between the two, indicating the feasibility of using fSampEn to predict airflow. Moreover, fSampEn of EMGdi was used as characteristic parameter to build a quantitative relationship with the airflow by polynomial regression analysis. Mean coefficient of determination of all subjects in any breathing state is greater than 0.88. Finally, nonlinear programming method was used to solve a universal fitting coefficient between fSampEn of EMGdi and airflow for each subject to further evaluate the possibility of using surface EMGdi to monitor and control respiratory activity.

So–called ‘kentriodontids’ are extinct dolphin–like odontocetes known from the Early to Late Miocene worldwide. Although recent studies have proposed that they were monophyletic, their taxonomic relationships still remain controversial. Such a controversy exists partly because of the predominance of primitive morphologies in this taxon, but the fact is that quite a few ‘kentriodontids’ are known only from fragmentary skulls and/or isolated periotics. A new ‘kentriodontid’ Platysvercus ugonis gen. et sp. nov. is described based on a nearly complete skull from the upper Lower Miocene Sugota Formation, Akita Prefecture, northern Japan. Based on the phylogenetic analysis of P. ugonis described here, the monophyly of the ‘kentriodontids’ is confirmed, and it is recognized as the superfamily Kentriodontoidea. This new superfamily is subdivided into two families as new ranks: Kentriodontidae and Lophocetidae. Based on the paleobiogeographic analysis of the Kentriodontoidea, their common ancestor emerged in the North Pacific Ocean and spread over the Northern Hemisphere. Initial diversification of the Kentriodontidae in the North Pacific Ocean and the Lophocetidae in the North Atlantic Ocean was recognized as a vicariance event. The diversification and extinction of the Kentriodontoidea could have been synchronously influenced by climate events during the Middle Miocene.

The accuracy of data-driven landslide susceptibility mapping (LSM) is closely affected by the quality of non-landslide samples. This research proposes a method combining a self-organizing-map (SOM) and a one-class SVM (SOM-OCSVM) to generate more reasonable non-landslide samples. We designed two steps: first, a random selection, a SOM network, a one class SVM model, and a SOM-OCSVM model were used to generate non-landslide sample datasets. Second, four machine learning models (MLs)—namely logistic regression (LRG), multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF)—were used to verify the effects of four non-landslide sample datasets on LSM. From the region along the Sichuan-Tibet Highway, we selected 11 conditioning factors and 1186 investigated landslides to perform the aforementioned experiments. The results show that the SOM-OCSVM method achieves the highest AUC (>0.94) and minimum standard deviation (

Objective: Diaphragm pacing (DP) is a long-term and effective respiratory assist therapy for patients with central alveolar hypoventilation and high cervical spinal cord injury. The existing DP system has some limitations, especially high price, inconvenience preoperative evaluation methods and diaphragm fatigue easily. Our objective was to develop a DP system and evaluated reliability through hardware testing and animal experiments.Methods: A DP system with bidirectional constant current was designed, manufactured and tested. Effects of a wide range of stimulus amplitudes (range: .5–2.5 mA) and frequencies (range: 10–250 Hz) on airflow and corresponding inspired volume were investigated during DP. Differences in airflow characteristics under various stimulation parameters were evaluated using power function. ECG interference in diaphragm electromyography (EMGdi) was filtered out using stationary wavelet transform to obtain pure EMGdi (EMGdip). 80-min period with a tendency for diaphragm fatigue by root mean square (RMS) and centroid frequency (fc) of EMGdip was studied.Results: The increase of stimulus frequency and amplitude in animals resulted in different degrees of increase in envoked volume. Significant difference in Airflow Index (b) between anesthesia and DP provided a simple, non-invasive and feasible solution for phrenic nerve conduction function test. Increased stimulation duration with the developed DP system caused less diaphragm fatigue.Conclusion: A modular, inexpensive and reliable DP was successfully developed. Its effectiveness was confirmed in animal experiments.Significance: This study is useful for design of future implantable diaphragmatic pacemakers for improving diaphragm fatigue and convenient assessment of respiratory activity in experiments.

Background and objectiveThe pathological type of non–small cell lung cancer is considered to be an important factor affecting the treatment and prognosis. The purpose of this study was to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in determining efficacy to distinguish adenocarcinoma (AC) and squamous cell carcinoma (SC), and their combined diagnostic efficacy was also analyzed.MethodsThis is a single-center prospective study, and we collected 70 patients with lung SC and 127 patients with lung AC confirmed by histopathological examination. Morphological parameters, plain scan CT value, biphasic enhanced CT value, and spectral parameters were calculated. The diagnostic efficiency of morphological parameters, spectral parameters, and spectral parameters combined with morphological parameters was obtained by statistical analysis.ResultsIn univariate analysis, seven morphological CT features differed significantly between SC and AC: tumor location (distribution), lobulation, spicule, air bronchogram, vacuole sign, lung atelectasis and/or obstructive pneumonia, and vascular involvement (all p < 0.05). In the arterial phase and the venous phase, the spectral parameters of AC were higher than those of SC (AP-Zeff: 8.07 ± 0.23 vs. 7.85 ± 0.16; AP-ID: 1.41 ± 0.47 vs. 0.94 ± 0.28; AP-NID: 0.13 ± 0.04 vs. 0.09 ± 0.03; AP-λ: 3.42 ± 1.10 vs. 2.33 ± 0.96; VP-Zeff: 8.26 ± 0.23 vs. 7.96 ± 0.16; VP-ID: 1.18 ± 0.51 vs. 1.16 ± 0.30; VP-NID: 0.39 ± 0.13 vs. 0.29 ± 0.08; VP-λ: 4.42 ± 1.28 vs. 2.85 ± 0.72; p < 0.001). When conducting multivariate analysis combining CT features and DLCT parameters with the best diagnostic efficacy, the independent predictors of AC were distribution on peripheral (OR, 4.370; 95% CI, 1.485–12.859; p = 0.007), presence of air bronchogram (OR, 5.339; 95% CI, 1.729–16.484; p = 0.004), and presence of vacuole sign ( OR, 7.330; 95% CI, 1.030–52.184; p = 0.047). Receiver operating characteristic curves of the SC and AC showed that VP-λ had the best diagnostic performance, with an area under the curve (AUC) of 0.864 and sensitivity and specificity rates of 85.8% and 74.3%, respectively; the AUC was increased to 0.946 when morphological parameters were combined, and sensitivity and specificity rates were 89.8% and 87.1%, respectively.ConclusionThe quantitative parameters of the DLCT spectrum are of great value in the diagnosis of SC and AC, and the combination of morphological parameters and spectral parameters is helpful to distinguish SC from AC.

Abstract Recently, long noncoding RNAs (lncRNAs) have attracted great attention from researchers. LncRNAs are non-protein-coding RNAs of more than 200 nucleotides in length. Multiple studies have been published on the relationship between lncRNA expression and the progression of human diseases. LncRNA small nucleolar RNA host gene 4 (SNHG4), a member of the lncRNA SNHG family, is abnormally expressed in a variety of human diseases, including gastric cancer, renal cell carcinoma, glioblastoma, neuroblastoma, prostate cancer, colorectal cancer, osteosarcoma, cervical cancer, liver cancer, lung cancer, non-small-cell lung cancer, neonatal pneumonia, diabetic retinopathy, neuropathic pain, acute cerebral infarction, acute myeloid leukaemia, and endometriosis. In this paper, the structure of SNHG4 is first introduced, and then studies in humans, animal models and cells are summarized to highlight the expression and function of SNHG4 in the above diseases. In addition, the specific mechanism of SNHG4 as a competing endogenous RNA (ceRNA) is discussed. The findings indicate that SNHG4 can be used as a biomarker for disease prognosis evaluation and as a potential target for disease diagnosis and treatment.

Carbon dots (CDs), a new zero-dimensional material, have ignited a revolution in the fields of sensing, bioimaging, and biomedicine. However, the difficulty of preparing CDs with Fenton-like catalytic properties has seriously hindered their application in the diagnosis of oxidation/reduction biomolecules or metal ions. Here, an innovative method was successfully established to synthesize Mn3+/Mn4+ ion-doped blue-green fluorescent CDs with Fenton-like catalytic properties using manganese acetate as the manganese source. Specifically, the CDs prepared here were equipped with functional groups of -COOH, NH2, C=O, and Mn-O, offering the possibility to function as a fluorescence sensor. More importantly, the introduction of manganese acetate resulted in the preparation of CDs with Fenton-like catalytic properties, and the dual-signal fluorescence detection of dopamine (DA) was realized with linear ranges of 100–275 nM and 325–525 nM, and the detection limits were 3 and 12 nM, respectively. In addition, due to the Fenton-like catalytic activity of Mn3+/Mn4+ ion-doped CDs, the material has broad application prospects in the detection of oxidation/reduction biomolecules or metal ions related to disease diagnosis and prevention.

Inputting text is a prevalent requirement among various virtual reality (VR) applications, including VR-based remote collaboration. In order to eliminate the need for complex rules and handheld devices for typing within virtual environments, researchers have proposed two mid-air input methods—the trace and tap methods. However, the specific impact of these input methods on performance in VR remains unknown. In this study, typing tasks were used to compare the performance, subjective report, and cognitive load of two mid-air input methods in VR. While the trace input method was more efficient and novel, it also entailed greater frustration and cognitive workload. Fortunately, the levels of frustration and cognitive load associated with the trace input method could be reduced to the same level as those of the tap input method via familiarity with VR. These findings could aid the design of virtual input methods, particularly for VR applications with varying text input demands.

Acral melanoma (AM) exhibits a high incidence in Asian patients with melanoma, and it is not well treated with immunotherapy. However, little attention has been paid to the characteristics of the immune microenvironment in AM. Therefore, in this study, we collected clinical samples from Chinese patients with AM and conducted single-cell RNA sequencing to analyze the heterogeneity of its tumor microenvironments (TMEs) and the molecular regulatory network. Our analysis revealed that genes, such as TWIST1, EREG, TNFRSF9, and CTGF could drive the deregulation of various TME components. The molecular interaction relationships between TME cells, such as MIF-CD44 and TNFSF9-TNFRSF9, might be an attractive target for developing novel immunotherapeutic agents.

Exonuclease III (Exo III) has been generally used as a double-stranded DNA (dsDNA)-specific exonuclease that does not degrade single-stranded DNA (ssDNA). Here, we demonstrate that Exo III at concentrations above 0.1 unit/μL can efficiently digest linear ssDNA. Moreover, the dsDNA specificity of Exo III is the foundation of many DNA target recycling amplification (TRA) assays. We demonstrate that with 0.3 and 0.5 unit/μL Exo III, the degradation of an ssDNA probe, free or fixed on a solid surface, was not discernibly different, regardless of the presence or absence of target ssDNA, indicating that Exo III concentration is critical in TRA assays. The study has expanded the Exo III substrate scope from dsDNA to both dsDNA and ssDNA, which will reshape its experimental applications.

Point cloud filtering is a preliminary and essential step in various applications of airborne light detection and ranging (LiDAR) data, with progressive triangulated irregular network (TIN) densification (PTD) being one of the classic methods for filtering LiDAR point clouds. The PTD algorithm densifies ground points through iteration operation based on initial ground seed points. However, the poor performance in steeply sloped areas and time-consuming processing are serious drawbacks for PTD algorithms. In this article, we propose a fast progressive TIN densification (FPTD) filtering algorithm for airborne LiDAR data using adjacent surface information. After carefully establishing parameters and removing outliers, our improved FPTD uses a sliding window to obtain significantly more initial ground seed points. And we modified some iterative determination criterion, including the definition of maximum relative elevation threshold and the introduction of signed computation, to eliminate avoidable nonground points. Then, adjacent surface information was utilized to iterate each point cloud block, which is the smallest unit that point cloud can be segmented. Additionally, the algorithm is easily run in a multithreaded environment, further accelerating the filtering process to some extent. Experiments show that our proposed FPTD filtering algorithm is fast and robust. Compared to the PTD, the FPTD algorithm yields better error rates and kappa coefficients in 1/12 of the average time required by the PTD.

The photovoltaic virtual synchronous generator (PV-VSG) solves the problem of lack of inertia in the PV power-generation system. The existing PV plants without energy storage are required to participate in the power grid's frequency modulation (FM), but existing PV-VSGs with energy storage have high requirements for coordinated control. Therefore, the active power reserve PV-VSG (APR-PV-VSG) is studied. Based on the different methods to obtain the maximum power point (MPP), the peer-to-peer and master-slave APR-PV-VSG strategies are proposed. The PV inverters are deviated from the MPP to reserve active power, which is used as the virtual inertia and primary FM power. These methods equip the PV power station with FM capability. The effectiveness of the proposed control strategies is verified by simulation results.

Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation, photovoltaic grid-connected systems are usually equipped with energy storage units. Most of the structures combined with energy storage are used as the DC side. At the same time, virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation. For the PV-storage grid-connected system based on virtual synchronous generators, the existing control strategy has unclear function allocation, fluctuations in photovoltaic inverter output power, and high requirements for coordinated control of PV arrays, energy storage units, and photovoltaic inverters, which make the control strategy more complicated. In order to solve the above problems, a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed. In this strategy, the energy storage unit implements maximum power point tracking, and the photovoltaic inverter implements a virtual synchronous generator algorithm, so that the functions implemented by each part of the system are clear, which reduces the requirements for coordinated control. At the same time, the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter. The simulation validates the effectiveness of the proposed method from three aspects: grid-connected operating conditions, frequency-modulated operating conditions, and illumination sudden-drop operating condition. Compared with the existing control strategies, the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter. Keywords: Photovoltaic power generation, Energy storage unit, Virtual synchronous generator, Smooth fluctuation, Coordinated control

UMo/Zr monolithic fuel plates have a promising application prospect in high flux research reactors. To prolong the service life and achieve safety design, the in-pile macro-mesoscale thermal-mechanical behavior of the fuel plate needs further simulation research. In this study, for the fuel meat, the theoretical models of the equivalent fission gas bubble volume fraction, the gas-bubble inner pressure and the maximum skeleton stress are developed, with the effects of bubble distribution pattern involved. The application into the simulation of the in-pile macro-mesoscale thermal-mechanical behavior of the UMo/Zr monolithic fuel plate indicates that the maximum skeleton stress of the fuel meat basically rises with the burn-up, and may reach four times of the macroscale first principal stress of the fuel meat. The distribution patterns of the gas bubbles in the fuel meat might have a distinct influence on the maximum skeleton stress, and the most conservative results of the simple cubic arrangement can be used for the failure prediction of the fuel meat.

With the continuous exploration of low-dimensional nanomaterials, two dimensional metal oxides (2DMOs) has been received great interest. However, their further development is limited by the high cost in the preparation process and the unstable states caused by the polarization of surface chemical bonds. Recently, obtaining mental oxides via liquid metals have been considered a surprising method for obtaining 2DMOs. Therefore, how to scientifically choose different preparation methods to obtain 2DMOs applying in different application scenarios is an ongoing process worth discussing. This review will provide some new opportunities for the rational design of 2DMOs based on liquid metals. Firstly, the surface oxidation process and in situ electrical replacement reaction process of liquid metals are introduced in detail, which provides theoretical basis for realizing functional 2DMOs. Secondly, by simple sticking method, gas injection method and ultrasonic method, 2DMOs can be obtained from liquid metal, the characteristics of each method are introduced in detail. Then, this review provides some prospective new ideas for 2DMOs in other energy-related applications such as photodegradation, CO2 reduction and battery applications. Finally, the present challenges and future development prospects of 2DMOs applied in liquid metals are presented.

Objectives: To evaluate whether 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis can be used as a novel imaging marker to distinguish amnestic mild cognitive impairment (aMCI) patients from the normal elderly population by measuring changes in APTw signal intensity in the hippocampus and amygdala.Materials and Methods: Seventy patients with aMCI and 74 age- and sex-matched healthy volunteers were recruited for routine MRI and APT imaging examinations. Magnetic transfer ratio asymmetry (MTRasym) of the amide protons (at 3.5 ppm), or APTw values, were measured in the bilateral hippocampus and amygdala on three consecutive cross-sectional APT images and were compared between the aMCI and control groups. The independent sample t-test was used to evaluate the difference in APTw values of the bilateral hippocampus and amygdala between the aMCI and control groups. Receiver operator characteristic analysis was used to assess the diagnostic performance of the APTw. The paired t-test was used to assess the difference in APTw values between the left and right hippocampus and amygdala, in both the aMCI and control groups.Results: The APTw values of the bilateral hippocampus and amygdala in the aMCI group were significantly higher than those in the control group (left hippocampus 1.01 vs. 0.77% p < 0.001; right hippocampus 1.02 vs. 0.74%, p < 0.001; left amygdala 0.98 vs. 0.70% p < 0.001; right amygdala 0.94 vs. 0.71%, p < 0.001). The APTw values of the left amygdala had the largest AUC (0.875) at diagnosis of aMCI. There was no significant difference in APTw values between the left and right hippocampus and amygdala, in either group. (aMCI group left hippocampus 1.01 vs. right hippocampus 1.02%, p = 0.652; healthy control group left hippocampus 0.77 vs. right hippocampus 0.74%, p = 0.314; aMCI group left amygdala 0.98 vs. right amygdala 0.94%, p = 0.171; healthy control group left amygdala 0.70 vs. right amygdala 0.71%, p = 0.726).Conclusion: APTw can be used as a new imaging marker to distinguish aMCI patients from the normal elderly population by indirectly reflecting the changes in protein content in the hippocampus and amygdala.

Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF6 gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an HVCB based on the vibrational signal. First, for a 40.5-kV SF6 HVCB prototype, a mechanical vibration detection system along with a high-current generator to provide the test current is designed. Given this, vibration test experiments are carried out, and the vibration signal data under various currents and corresponding contact states are obtained. Afterward, a feature extraction method based on the frequency is designed. The state of the HVCB contacts is then determined using optimized deep neural networks (DNNs) along with the method of adaptive moment estimation (Adam) on the obtained experimental data. Finally, the hyperparameters for the DNNs are tuned using the Bayesian optimization (BO) technique, and a global HVCB contact state recognition model at various currents is proposed. The obtained results clearly depict that the proposed recognition model can accurately identify five various contact states of HVCBs for the currents between 1000 A and 3500 A, and the recognition accuracy rate is above 96%. The designed experimental and theoretical analysis in our study will provide the references for future monitoring and diagnosis of faults in HVCBs.

A good lighting environment for roads at night is essential for traffic safety. Accurate and timely knowledge of road lighting quality is meaningful for the planning and management of urban road lighting systems. Traditional field observations and mobile observations have limitations for road lightning quality evaluation at a large scale. This study explored the potential of 0.92 m resolution JL1-3B nighttime light remote sensing images to evaluate road lighting quality in Nanjing, China. Combined with synchronous field measurements and JL1-3B data, multiple regression and random forest regression with several independent variable combinations were developed and compared to determine the optimal model for surface illuminance estimation. Cross validation results showed that the random forest model with Hue, saturability, ln(Intensity), ln(Red), ln(Green) and ln(Blue) as the input independent variables had the best performance (R2 = 0.75 and RMSE = 9.79 lux). Then, this model was used to map the surface illuminance. The spatial scopes of roads were extracted from Google Earth images, and the illuminance within roads was derived to calculate the average, standard deviation and coefficient of variation to indicate the overall brightness level and brightness uniformity of the roads. This study provides a quantitative and effective reference for road lighting evaluation.

ABSTRACT Early life events can lead to multiple diseases in adulthood. Previous studies suggested that polysorbate 80 (P80) as a widely used emulsifier in pharmaceutical formulations and food industries could impair the intestinal barrier. However, whether maternal P80 (MP80) exposure could affect the long-term health of offspring remains unknown. In this study, we found that maternal P80 intake could retard intestinal development, disrupt the intestinal barrier, and cause low-grade intestinal inflammation in 3-week-old offspring. 16S rRNA sequencing and correlation analysis revealed that Mucispirillum, Clostridium XI, and Parabacteroides, which positively correlated with intestinal proliferation and differentiation, were decreased in the maternal P80 group. Interestingly, the increase in some harmful bacteria, including Proteobacteria, Helicobacteraceae, Campylobacterales, and Desulfovibrionales, persisted from the weaning period to adulthood (3 to 8 weeks). Furthermore, a fecal microbiota transplantation assay showed that the mice gavaged with feces from 3-week-old offspring of the MP80 group presented more severe intestinal inflammation and barrier disruption than the mice that received feces from the offspring of the control group. Finally, maternal P80 intake remarkably aggravated the structural disorder of intestinal crypt, increased proinflammatory factors, and exacerbated dextran sulfate sodium (DSS)-induced colitis in adulthood. Conclusively, maternal P80 intake could induce gut dysbiosis and promote colitis susceptibility in adulthood. This study provides new insights into the prevention of inflammatory bowel disease (IBD). IMPORTANCE The main findings of this research showed that maternal P80 intake could disrupt the intestinal barrier, induce gut dysbiosis, and promote colitis susceptibility in adulthood. This study will enhance understanding of the prevention of IBD.

A new species of an extinct dolphin belonging to the kentriodontids, i.e., Kentriodon sugawarai sp. nov., is described from the upper lower to lowest middle Miocene Kadonosawa Formation in Ninohe City, Iwate Prefecture, northern Japan. The holotype of Kentriodon sugawarai sp. nov., consists of a partial skull with ear bones, mandibular fragments, and some postcranial bones. This new species shares five unique characters with other species of Kentriodon. In addition, the new species differs from other species of the genus in displaying a narrow width of the squamosal lateral to the exoccipital in posterior view, the dorsolateral edge of the opening of the ventral infraorbital foramen that is formed by the maxilla and the lacrimal or the jugal, and at least three anterior dorsal infraorbital foramina. Our phylogenetic analysis based on 393 characters for 103 Odontoceti taxa yielded a consensus tree showing all previously identified kentriodontids as a monophyletic group that comprises the sister group of the crown Dephinoidea, which in turn include Delphinidae, Phocoenidae and Monodontidae. Our analysis also indicates that the distinct innovation of the acoustic apparatus (i.e., 13 out of 29 derived characters are from tympanoperiotic) would have occurred in the ancestral lineage of the Delphinoidea (sensu lato) including the monophyletic Kentriodontidae during their initial evolution and diversification.

Background: Accumulating evidence shows that high fat diet is closely associated with inflammatory bowel disease. However, the effects and underlying mechanisms of maternal high fat diet (MHFD) on the susceptibility of offspring to colitis in adulthood lacks confirmation.Methods: C57BL/6 pregnant mice were given either a high fat (60 E% fat, MHFD group) or control diet [10 E% fat, maternal control diet (MCD) group] during gestation and lactation. The intestinal development, mucosal barrier function, microbiota, and mucosal inflammation of 3-week old offspring were assessed. After weaning all mice were fed a control diet until 8 weeks of age when the microbiota was analyzed. Offspring were also treated with 2% DSS solution for 5 days and the severity of colitis was assessed.Results: The offspring in MHFD group were significantly heavier than those in MCD group only at 2–4 weeks of age, while no differences were found in the body weight between two groups at other measured time points. Compared with MCD group, MHFD significantly inhibited intestinal development and disrupted barrier function in 3-week old offspring. Although H&E staining showed no obvious microscopic inflammation in both groups of 3-week old offspring, increased production of inflammatory cytokines indicated low-grade inflammation was induced in MHFD group. Moreover, fecal analysis of the 3-week old offspring indicated that the microbiota compositions and diversity were significantly changed in MHFD group. Interestingly after 5 weeks consumption of control diet in both groups, the microbiota composition of offspring in MHFD group was still different from that in MCD group, although the bacterial diversity was partly recovered at 8 weeks of age. Finally, after DSS treatment in 8-week old offspring, MHFD significantly exacerbated the severity of colitis and increased the production of proinflammatory cytokine.Conclusions: Our data reveal that MHFD in early life can inhibit intestinal development, induce dysbiosis and low-grade inflammation and lead to the disruption of intestinal mucosal barrier in offspring, and enhance DSS-induced colitis in adulthood.

An hourglass in-fiber air microcavity Fabry-Perot interferometer is proposed in this paper, and its second reflecting surface of in-fiber microcavity is designed to be a concave reflector with the best curvature radius in order to improve the spectral characteristics. Experimental results proved that the extinction ratio of Fabry-Perot interferometer with cavity length of 60 μm and concave reflector radius of 60 μm is higher than for a rectangular Fabry-Perot interferometer with cavity length of 60 μm (14 dB: 11 dB). Theory and numerical simulation results show that the strain sensitivity of sensor can be improved by reducing the microcavity wall thickness and microcavity diameter, and when the in-fiber microcavity length is 40 μm, the microcavity wall thickness is 10 μm, the microcavity diameter is 20 μm, and the curvature radius of reflective surface II is 50 μm, the interference fringe contrast of is greater than 0.97, an Axial-pull sensitivity of 20.46 nm/N and resolution of 1 mN can be achieved in the range of 0–1 N axial tension. The results show that the performance of hourglass in-fiber microcavity interferometer is far superior to that of the traditional Fabry-Perot interferometer.