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Suicidal ideation is a substantial clinical challenge in treatment-resistant depression (TRD). Recent work demonstrated promising antidepressant effects in TRD patients with no or mild suicidal ideation using a specific protocol termed intermittent theta burst stimulation (iTBS). Here, we examined the clinical effects of accelerated schedules of iTBS and continuous TBS (cTBS) in patients with moderate to severe suicidal ideation. Patients with TRD and moderate to severe suicidal ideation (n = 44) were randomly assigned to receive accelerated iTBS or cTBS treatment. Treatments were delivered in 10 daily TBS sessions (1800 pulses/session) for 5 consecutive days (total of 90,000 pulses). Neuronavigation was employed to target accelerated iTBS and cTBS to the left and right dorsolateral prefrontal cortex (DLPFC), respectively. Clinical outcomes were evaluated in a 4-week follow-up period. Accelerated cTBS was superior to iTBS in the management of suicidal ideation (p week 1 =.027) and anxiety symptoms (p week 1 =.01). Accelerated iTBS and cTBS were comparable in antidepressant effects (p <.001; accelerated cTBS: mean change at weeks 1, 3, 5 = 49.55%, 54.99%, 53.11%; accelerated iTBS: mean change at weeks 1, 3, 5 = 44.52%, 48.04%, 51.74%). No serious adverse events occurred during the trial. One patient withdrew due to hypomania. The most common adverse event was discomfort at the treatment site (22.73% in both groups). These findings provide the first evidence that accelerated schedules of left DLPFC iTBS and right DLPFC cTBS are comparably effective in managing antidepressant symptoms and indicate that right DLPFC cTBS is potentially superior in reducing suicidal ideation and anxiety symptoms. [ABSTRACT FROM AUTHOR]

Accurately predicting the state of ship motion is crucial for ship navigation control with energy efficiency optimization studies. When modeling the motion of novel ships equipped with propulsion devices such as sails, it is essential to consider the effects of sail thrust and lateral forces on the ship's motion states. Building upon the analysis of sail force and sail-assisted ship motion modeling, this paper proposes a ship motion dynamic modeling method utilizing Kernel Extreme Learning Machine (KELM) regression. By optimizing the hyperparameters of the kernel function using the Grey Wolf Optimizer (GWO) algorithm and incorporating a sliding time window for dynamic model updating, the proposed approach combines the efficient learning mechanism of KELM with the global search capability of GWO, effectively enhancing prediction accuracy and timeliness. Utilizing KVLCC2 ship model motion data, simulation data from the sail-assisted ship "New Aden" and real ship data as case studies, comparative analysis with traditional models such as SVM and ELM. The results demonstrate that the GWO-KELM modeling approach exhibits robustness and high prediction accuracy, the MAE of the proposed model in the real ship motion prediction effect is reduced by 8.89% and the RMSE is reduced by 9.44% compared with the other models, which significantly enhance the predictive performance of sail-assisted ship maneuvering motion states. • The sail forces and moments have been decomposed from various degrees of freedom. • Combines the efficient computational speed of ELM with the high-dimensional mapping capability of kernel functions through KELM. • Improved the generalization and robustness of KELM using the Grey Wolf optimizer. • Enables continuous and reliable prediction of sail-assisted ship motions. • A case study was conducted on the navigation status of a sail-assisted ship during sail hoisting and lowering. [ABSTRACT FROM AUTHOR]

This paper presents an experimental and numerical study on the behavior of the high strength concrete-filled double-steel-plate composite (CDC) tower in large-span bridge under axial compression and out-of-plane bending moment. A novel rotation loading scheme with high axial load levels reaching 64000kN is proposed, which has been conducted on five full-scale specimens of the composite tower wall. Then finite element models for the tower wall specimens are established to conduct parametric analysis and calculation methods for compression-bending capacity are proposed for the CDC tower wall. Finally, a multi-scale finite element model for the whole tower is developed and design method for the tower section is proposed. The test and numerical results show that the full-scale CDC tower wall specimens exhibit excellent load-bearing capacity and ductility. The failure of the specimens is marked by localized concrete crushing and steel plates buckling on the compression side, rather than the yielding of steel plates. The effective composite performance among the concrete, steel plates, stiffeners and rebar are guaranteed by properly designed interfacial configuration including bidirectional perforated plate connectors as well as shear studs. The study provides insights into the mechanical behavior of the CDC composite structure and proposes a fiber section-based method for accurate calculation of the cross-sectional compression-bending capacity. • A novel rotation loading scheme with high axial load levels reaching 64000kN is proposed. • FE models for the tower wall specimens and multi-scale FE models for the whole tower is developed. • Failure of the specimens is marked by concrete crushing and steel buckling on the compression side. • The effective collaborative performance is guaranteed by properly designed interfacial configuration. • A fiber section-based method is proposed for the cross-sectional compression-bending capacity. [ABSTRACT FROM AUTHOR]

In this work, the hydrogen embrittlement (HE) characteristics of 1400 MPa bolt steels with three different vanadium contents of 0, 0.17 wt% and 0.34 wt% were evaluated. The characteristics of the microstructure and dislocation density of the experimental steels were analyzed, and their effects on HE were also discussed. The results showed that with increasing V content, the HE resistance of the experimental steels was improved, and the experimental steel with the highest V content possessed the best HE resistance. The V-precipitates of steels with V contents of 0.17 wt% and 0.34 wt% were reversible hydrogen traps, and the inhibitory effect of V-precipitates on hydrogen-dislocation interactions improved HE resistance. In addition, a lower dislocation density and finer martensitic structure were also beneficial for hindering hydrogen-induced cracking (HIC). • Adding V to high strength bolt steels can reduce the hydrogen embrittlement. • The V addition resulted in change in precipitates, grain size and dislocations. • The increase of V content resulted in the decrease of hydrogen diffusion rate. • The V-precipitates of experimental steels were reversible hydrogen traps. • The V-precipitates inhibited the hydrogen-dislocation interactions. [ABSTRACT FROM AUTHOR]

The direct visualization of flow fields plays an important role in droplet evaporation. However, the refraction of light at the curved droplet surface makes it challenging to obtain the accurate flow field. To solve this problem in evaporating sessile droplets, a full-field flow visualization measurement employing the Scheimpflug principle is proposed and a mapping method to eliminate the perspective effects on the particle image velocimetry results is introduced. Compared with the distorted images captured from the side of the droplet, the proposed method can improve the measurement accuracy significantly and the flow details near the droplet surface can be obtained. [ABSTRACT FROM AUTHOR]

[Display omitted] • Introduce "millimeter-micrometer-nanometer" multi-hierarchical composite structures. • Multi-scale droplet manipulation on a metal platform without external energy input. • Provide mechanism explanation for the special interface behavior. • Validate multi-scale droplets manipulation behavior through various experiments. Droplets manipulation on functional biomimetic surfaces have been highly anticipated for their wide range of applications. However, preparing a metal platform for manipulating multi-scale droplets without external energy input remains a challenge. Herein, dual biomimetic surfaces (DBSs) were fabricated by twice laser and thiol modification. The unique interfacial behavior of the droplets can be realized under the synergistic effect of the special "millimeter-micrometer-nanometer" multi-hierarchical composite structure and chemical composition. The as-prepared DBSs can achieve multi-scale droplets manipulation, directional self-cleaning in various media, and efficient directional fog collection. Further, the mechanism of specific interface behavior is analyzed in depth. Nanoparticles endow DBSs with more capture points and condensation cores and micrometer mastoids realized the transmission and aggregation of microscopic droplets through the action of Laplace force. Based on resistance, energy barriers and three-phase contact line, influence of millimeter grooves on anisotropic wettability and directional transportation of the droplets is analyzed. Besides, the multi-hierarchical structure also endows DBSs with good droplets manipulation ability and stability. This work not only provides an advanced biomimetic platform, but also provides an important reference for metal-based lab-on-a-chip for multi-scale droplets manipulation. [ABSTRACT FROM AUTHOR]

Magnetic nitrogenous cobalt–carbon composites were synthesized via calcination of N-ZIF-67, where metal and N atoms were introduced into the conductive carbon matrix formed during carbonization of N-ZIF-67, and were applied, as catalysts, in the reduction reaction of p-nitrophenol, assisted by NaBH4. Characterization of the prepared composites was carefully performed using SEM, TEM, XRD, SQUID magnetometric analysis, XPS and nitrogen adsorption/desorption measurements. Compared to Co@C, which was similarly prepared, the N-Co@C catalyst exhibits much better catalytic activity for the reduction of 4-nitrophenol to 4-aminophenol. The pseudo-first-order rate constant for the N-Co@C catalyst is 4.47 times greater than that for the Co@C catalyst, and its stability shows little change after five reaction cycles. The superior catalytic properties of the N-Co@C catalyst are due to the presence of N moieties. Leaching out the cobalt cores was induced using FeCl3 and HCl to see what the active centers were. The results show that the majority of the catalytic activity is associated with the metal cores. [ABSTRACT FROM AUTHOR]

Two types of magnetic nanocomposites, Co-carbon composite (Co@C) and Zn/Co-carbon composite (Zn/Co@C), were synthesized by one-step calcinations of hollow Co-ZIF (ZIF-67) and Zn/Co-ZIF (ZIF-67@ZIF-8) (ZIF = zeolitic imidazolate framework), as well as applied as adsorbents in the reduction of Rhodamine B (RhB). The prepared composites were carefully analyzed by SEM, TEM-EDXS (EDXS = energy-dispersive X-ray specroscopy), XRD, SQUID, and nitrogen adsorption/desorption measurements. Co@C and Zn/Co@C showed the maximum adsorption capacities of 48 mg g-1 and 101.93 mg g-1, respectively, toward RhB. The adsorption isotherms of RhB on the Zn/Co@C nanocomposites were well fitted with the Langmuir model, and the pseudo-second-order model accurately describes the adsorption kinetic process for the adsorption of RhB on the materials. The results show that the composite materials of Zn/Co@C possess higher porosity and magnetic properties and exhibit higher adsorption capacity, convenient separation ability, along with good reusability of the adsorbent. The theoretical calculations also clarify that RhB on the distorted Co-Zn surface is much more stable than that on Co(111), in good agreement with the experimental observations. [ABSTRACT FROM AUTHOR]

[Display omitted] • GABA biosynthetic pathways and related genes were identified in P. ostreatus. • GABA accumulation were suppressed by heat stress and excessive maturity of fruiting bodies. • Most genes of GABA metabolism were downregulated under heat stress and during over-ripening period. • GABA deficiency inhibited mycelial growth and primordial formation and aggravated heat damage. • GABA treatment enhanced thermotolerance and promoted the development of fruiting bodies. GABA is a health-promoting bioactive substance. Here, the GABA biosynthetic pathways were investigated, and then the dynamic quantitative changes in GABA and the expression levels of genes related to GABA metabolism under heat stress or at different developmental stages of fruiting bodies in Pleurotus ostreatus (Jacq. ex Fr.) P. Kumm were determined. We found that the polyamine degradation pathway was the main route of GABA production under growth normal condition. The accumulation of GABA and the expression of most genes related to GABA biosynthesis, including genes encoding glutamate decarboxylase (PoGAD-2), polyamine oxidase (PoPAO-1), diamine oxidase (PoDAO) and aminoaldehyde dehydrogenase (PoAMADH-1 and PoAMADH-2), were significantly suppressed by heat stress and the excessive maturity of fruiting bodies. Finally, the effects of GABA on the mycelial growth, heat tolerance and the morphogenesis and development of fruiting bodies were studied, the results showed that the deficiency of endogenous GABA inhibited the mycelial growth and primordial formation and aggravated heat damage, whereas exogenous application of GABA could improve thermotolerance and promote the development of fruiting bodies. [ABSTRACT FROM AUTHOR]

Pyraclostrobin (PYR), a strobilurin fungicide, has been widely used to control fungal diseases, posing potential risk to aquatic organisms. However, the toxic effects of PYR to fish remained largely unknown. In this study, common carp (Cyprinus carpio L.) was exposed to environmentally relevant levels of PYR (0, 0.5 and 5.0 μg/L) for 30 days to assess its chronic toxicity and potential toxicity mechanism. The results showed that long-term exposure to PYR induced hepatopancreas damage as evident by increased in serum transaminase activities (AST and ALT). Moreover, PYR exposure remarkably enhanced the expressions of hsp70 and hsp90 , decreased the levels of antioxidant enzymes and biomarkers and promoted the reactive oxygen species (H 2 O 2 and O 2 ‐) and MDA contents in carp hepatopancreas. PYR exposure also upregulated apoptosis-related genes (bax , apaf-1 , caspase-3 and caspase-9) and reduced anti-apoptosis gene bcl-2 in fish hepatopancreas. Moreover, PYR exposure altered the expressions of inflammatory cytokines (IL-1β, IL-6, TNF-α and TGF-β) in the serum and hepatopancreas and the level of NF-κB p65 in the hepatopancreas. Further research indicated that PYR exposure markedly changed the levels of immune parameters (LYZ, C3, IgM, ACP and AKP) in the serum and/or hepatopancreas, indicating that chronic PYR exposure also has immunotoxicity on fish. Additionally, we found that PYR exposure upregulated p38 and jnk MAPK transcription levels, suggesting that MAPK may be play important role in PYR-induced apoptosis and inflammatory response in the hepatopancreas of common carp. In summary, PYR exposure induced oxidative stress, triggered apoptosis, inflammatory and immune response in common carp, which can help to elucidate the possible toxicity mechanism of PYR in fish. [Display omitted] • Pyraclostrobin has hepatopancreas toxicity on common carp. • Pyraclostrobin has immunotoxicity on common carp. • Oxidative stress may play an important role in pyraclostrobin-induced hepatopancreas toxicity. • MAPK pathway is probably involved in pyraclostrobin-induced inflammatory response and apoptosis. [ABSTRACT FROM AUTHOR]

• Anisotropic HDDR powder was prepared from wasted (Ce, Pr, Nd)-Fe-B sinter magnets. • Coercivity of optimized HDDR powder has the recovery rate of 83%. • Optimized HDDR powder is consisted of flake particles with hierarchical structure. • The width of grain boundary phase determines the coercivity of HDDR powder. • Texture of HDDR particles benefits from composed nanograins with (0 0 1) orientation. With the wide application of Ce-contained rare earth (RE) permanent magnets, recycling of wasted Ce-contained magnets has drawn more and more attention. Hydrogenation-disproportionation-desorption-recombination (HDDR) method was used to prepare anisotropic magnetic powder from wasted (Ce, Pr, Nd)-Fe-B sintered magnet (N45 magnet). The influence of hydrogen pressure in disproportionation (P dis) and desorption (P des) and the disproportionation time (t dis) on the magnetic properties and microstructures of HDDR powders was studied. The P dis , P des and t dis were optimized to be 50 kPa, 5 kPa and 5 h, respectively. The optimized anisotropic HDDR (Ce, Pr, Nd)-Fe-B powder possessed the coercivity of 10.15 kOe, remanence of 11.14kG and the degree of alignment of 0.77. This coercivity has reached 83 % of that of the recycled N45 magnet. Microstructure examination with scanning electron microscope revealed that the optimized HDDR powder is consisted of flake-shaped particles with hierarchical structure. The distribution of rE-rich phase has been significantly influenced by P dis , P des and t dis. The optimized HDDR particles exhibited the best homogeneous distribution of rE-rich phase. The result of transparent electron microscopy (TEM) and energy dispersive spectrometry demonstrated the nature of (Ce, Pr, Nd)-rich phase and (Ce, Pr, Nd) 2 Fe 14 B for the rE-rich phase and RE 2 Fe 14 B grain phase, respectively. Examination with high-resolution TEM revealed that the optimized t dis resulted in the largest thickness of (Ce, Pr, Nd)-rich phase at grain boundaries and the consequent maximum coercivity of HDDR particles. The orientation of the optimized HDDR particles was analyzed with X-ray diffractometer and electron back-scatter diffractometer. The result revealed well textured HDDR particles and the subordinate nanograins with preferred (0 0 1) orientation, suggesting the inherited texture of these HDDR particles from the initial (Ce, Pr, Nd) 2 Fe 14 B grains in N45 sintered magnet. This HDDR method was proved to be a prospective strategy in recycling of Ce-contained sintered magnets. [ABSTRACT FROM AUTHOR]

To assess the efficacy and safety of Vortioxetine and Escitalopram in improving cognition in patients with major depressive disorder (MDD). Methods: At baseline, 131 MDD patients and 70 healthy controls completed the Hamilton Depression Scale (HAMD-17), Hamilton Anxiety Scale (HAMA), Snaith-Hamilton Pleasure Scale (SHAPS) and MATRICS Consensus Cognitive Battery (MCCB). Patients with MDD were randomly divided into Vortioxetine (n = 62) and Escitalopram (n = 69) groups with an 8-week follow-up research. ANOVA for repeated measurement was utilized to compare the efficacy of Vortioxetine and Escitalopram. Results: The total scores of HAMD-17, HAMA and SHAPS scales had statistical difference between MDD cases and healthy controls (P < 0.001) at baseline. After 8 weeks of treatment, the scale scores of the HAMD-17, HAMA and SHAPS had lowered in both groups, with no statistical difference between two groups (P > 0.05). At baseline, MDD patients had defects in Speed of Processing, Attention Vigilance, Verbal Learning, Visual Learning, Reasoning and Problem Solving, and Social Cognition, compared with healthy controls. After 8 weeks of treatment with Vortioxetine or Escitalopram, the patients had improved in the aspects of cognitive functions above except Social Cognition. Numerical improvements of MCCB scale were found in the two groups, P > 0.05. Most adverse events were mild or moderate, with nausea being the most common adverse event. Conclusion: Both Vortioxetine and Escitalopram can improve the mental status and cognitive functions in MDD patients, with mild or moderate adverse events. Trial Registration: www.chictr.org.cn , identifier: ChiCTR1900024858. [ABSTRACT FROM AUTHOR]

The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking. In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance. Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %. This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability. In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD. • Significant changes observed in the levels of various plasma proteins and neuroimaging alterations in MDD. • Altered indicators of protein levels and neuroimaging are correlated with clinical features. • Pioneered the development of a novel algorithm integrating graph neural networks and attention modules. [ABSTRACT FROM AUTHOR]

Orosomucoid (ORM) has been reported as a biomarker of carotid atherosclerosis, but the role of ORM 2, a subtype of ORM, in carotid atherosclerotic plaque formation and the underlying mechanism have not been established. Plasma was collected from patients with carotid artery stenosis (CAS) and healthy participants and assessed using mass spectrometry coupled with isobaric tags for relative and absolute quantification (iTRAQ) technology to identify differentially expressed proteins. The key proteins and related pathways were identified via western blotting, immunohistochemistry, and polymerase chain reaction of carotid artery plaque tissues and in vitro experiments involving vascular smooth muscle cells (VSMCs). We screened 33 differentially expressed proteins out of 535 proteins in the plasma. Seventeen proteins showed increased expressions in the CAS groups relative to the healthy groups, while 16 proteins showed decreased expressions during iTRAQ and bioinformatic analysis. The reactive oxygen species metabolic process was the most common enrichment pathway identified by Gene Ontology analysis, while ORM2, PRDX2, GPX3, HP, HBB, ANXA5, PFN1, CFL1, and S100A11 were key proteins identified by STRING and MCODE analysis. ORM2 showed increased expression in patients with CAS plaques, and ORM2 was accumulated in smooth muscle cells. Oleic acid increased the lipid accumulation and ORM2 and PRDX6 expressions in the VSMCs. The recombinant-ORM2 also increased the lipid accumulation and reactive oxygen species (ROS) in the VSMCs. The expressions of ORM2 and PRDX-6 were correlated, and MJ33 (an inhibitor of PRDX6-PLA2) decreased ROS production and lipid accumulation in VSMCs. ORM2 may be a biomarker for CAS; it induced lipid accumulation and ROS production in VSMCs during atherosclerosis plaque formation. However, the relationships between ORM2 and PRDX-6 underlying lipid accumulation-induced plaque vulnerability require further research. • ORM2 may be a biomarker of carotid plaques. • ORM2 correlated with PRDX6. • ORM2 promoted the lipid content via ROS specifically produced by PRDX-6-PLA2 at the cellular level. [ABSTRACT FROM AUTHOR]

Gender plays a role in the mechanisms of depression, but fewer studies have focused on gender differences in the abnormal activation of brain regions when patients perform specific cognitive tasks. A total of 110 major depressive disorder (MDD) patients and 106 healthy controls were recruited. The relative change in oxygen-haemoglobin (oxy-Hb) concentration during the verbal fluency task were measured by a 52-channel near-infra-red spectroscopy (NIRS) system. Differences in brain region activation between patients and healthy controls and between genders of depression patients were compared. MDD patients demonstrated significantly decreased [oxy-Hb] changes in the right inferior frontal gyrus (p = 0.043) compared to healthy controls. A marked increase in leftward functional language lateralisation in the inferior frontal gyrus was observed in the MDD group in contrast to the HC group (p = 0.039). Furthermore, female patients in the MDD group exhibited significant reductions in [oxy-Hb] changes in the right frontal region (specifically, the superior and middle frontal gyrus; p = 0.037) compared with male patients. Gender impacts depression-related brain activation during cognitive tasks, potentially influencing depression's pathogenesis. [ABSTRACT FROM AUTHOR]

Several pieces of evidence show that signaling via brain-derived neurotrophic factor (BDNF) and its receptor, tropomycin receptor kinase B (TrkB), as well as inflammation, play a crucial part in the pathophysiology of depression. The purpose of our study was to evaluate plasma levels of BDNF-TrkB signaling, which are inflammatory factors in major depressive disorder (MDD) patients, and assess their associations with clinical performance. This study recruited a total sample of 83 MDD patients and 93 healthy controls (CON). All the participants were tested with the Hamilton Depression Scale (HAMD), the Beck Scale for Suicide Ideation, and the NEO Five-Factor Inventory. The plasma level of selected BDNF-TrkB signaling components (mature BDNF (mBDNF), precursor BDNF (proBDNF), tyrosine kinase B (TrkB), and tissue plasminogen activator (tPA)) and selected inflammatory factors (interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α)) were measured using an enzyme-linked immunosorbent assay (ELISA). Further, we performed correlation analysis to indicate the relationship between the plasma levels of the factors and clinical characteristics. Results: (i) A higher level of mBDNF and lower openness were observed in MDD patients with higher suicidal ideation than patients with lower suicidal ideation. (ii) In MDD patients, mBDNF was positively correlated with the sum score of the Beck Scale for Suicide Ideation (BSS). (iii) The levels of mBDNF, tPA, IL-1 β and IL-6 were significantly higher in all MDD subjects compared to the healthy controls, while the levels of TrkB and proBDNF were lower in MDD subjects. Conclusion: Our study provides novel insights regarding the potential role of mBDNF in the neurobiology of the association between depression and suicidal ideation and, in particular, the relationship between BDNF-TrkB signaling, inflammatory factors, and clinical characteristics in MDD. [ABSTRACT FROM AUTHOR]

Ship Fuel Consumption Prediction (SFCP) is the foundation of ship energy efficiency assessment and optimization. However, existing research neglects to examine the model extrapolation performance, leading to significant degradation in predictive accuracy when models face dataset shift. To address this, a novel dual-stage grey-box stacking (DSGBS) model is proposed. First, based on the traditional grey-box model (GBM), a light grey-box model (LGBM) is proposed to enhance the extrapolation ability by incorporating more prior knowledge. Then, an improved stacking framework is used to fuse multiple GBMs to build the DSGBS model. Finally, a physics-based white-box model (WBM) is established, along with black-box model (BBM), traditional GBM, and LGBM based on nine machine learning algorithms. The extrapolation performance of these models is compared using data from three independent voyages. Results show that DSGBS model has a significant advantage in extrapolation performance, reducing its RMSE by about 63.51 %, 10.91 %, and 52.52 %, respectively, compared to the best model in BBMs, the best model among GBMs and LGBMs, and WBM. Therefore, the DSGBS model mitigates prediction accuracy loss from dataset shift, significantly improve the extrapolation performance, and support the practical application of ship energy efficiency management, with great significance for reducing operation cost and emission. • A DSGBS model with high extrapolation performance is proposed for ship fuel consumption prediction. • Reveals that BBM's predicted performance significantly degrades in extrapolation. • An LGBM is proposed that relies only on the physical model to generate input features. • First full revelation of the differences in extrapolation performance across models. • DSGBS model improves extrapolation performance by 63.51 %, 52.52 % and 10.91 % compared to BBM, WBM and GBM. [ABSTRACT FROM AUTHOR]

Aim: Clinical and preclinical studies suggest that alterations in the peripheral and brain immune system are associated with the pathophysiology of depression, also leading to changes in local glucose metabolism in the brain. Here, the authors identified Yin‐Yang 1 (YY1), a transcription factor closely associated with central and peripheral inflammation. Methods: Plasma levels of YY1, interleukin (IL) 6, and IL‐1β in major depressive disorder (MDD) were collected before and after treatment with vortioxetine, and correlation with clinical and cognitive scores was studied. Chronic unpredictable mild stress was treated with vortioxetine. Micropositron emission tomography (microPET) was used to analyze glucose metabolism and mRNA, and the protein level of the YY1–nuclear factor κB (NF‐κB)–IL‐1β inflammatory pathway were measured in related brain regions. Results: Plasma levels of YY1 and IL‐1β were significantly increased in MDD and decreased after treatment with vortioxetine. Meanwhile, the level of YY1 in plasma was negatively correlated with cognitive functions in patients with MDD and positively correlated with the level of IL‐1β in plasma. Compared with the control group, in chronic unpredictable mild stress rats, (microPET) analysis showed that the decrease of glucose metabolism in the hippocampus, entorhinal cortex, amygdala, striatum, and medial prefrontal cortex was reversed after treatment. mRNA and protein level of related molecular in YY1–NF‐κB–IL‐1β inflammatory pathway decreased in the hippocampus and was reversed by vortioxetine. Conclusion: The current study suggests that the YY1–NF‐κB–IL‐1β inflammatory pathway may play an essential role in both mood changes and cognitive impairment in depression, and may be associated with changes in glucose metabolism in emotion regulation and cognition. These findings provide new evidence for the inflammatory mechanisms of depression. [ABSTRACT FROM AUTHOR]

The drastic increase of microplastics (MPs) in aquatic environment has become a serious threat to marine and freshwater ecosystems. However, little information is available regarding the potential detrimental effects of polyvinyl chloride microplastics (PVC-MPs) on aquatic organisms. This study investigated the changes of reproduction parameters, oxidative stress and the expression of reproduction and detoxification-related genes in Daphnia magna after exposed to 2 ± 1 and 50 ± 10 μm PVC-MPs. The results showed that chronic exposure to 2 ± 1 μm PVC-MPs prolonged days to the first brood, increased total number of broods per female and frequency of molting per adult, decreased offspring number at first brood and total number of offspring per female in D. magna. Moreover, 2 ± 1 μm PVC-MPs also disturbed the activities of SOD and CAT, increased GSH and MDA levels. The expression of Vtg , SOD , CAT , CYP314 and CYP360A8 genes also exhibited different response patterns depending on exposure time. Furthermore, 50 ± 10 μm PVC-MPs decreased offspring at first brood and Vtg mRNA level, increased the transcription levels and activities of SOD and CAT. These results suggest that the presence of PVC-MPs in aquatic environment may cause reproduction toxicity by disrupting the reproduction and detoxification-related genes expression and inducing oxidative stress in D. magna. [Display omitted] • PVC-MPs disturb the reproduction of D. magna. • PVC-MPs were found to exhibit size-dependent toxicity toward D. magna. • Oxidative stress may play an important role in PVC-MPs-induced reproduction toxicity. • PVC-MPs affect the reproduction and detoxification-related genes in D. magna. [ABSTRACT FROM AUTHOR]

Establishing an accurate fuel consumption prediction model is essential to optimize energy efficiency in wing-diesel hybrid ships. This study proposes an improved Blending ensemble learning method for predicting fuel consumption. Initially, the original data is cleaned using artificial experience and Interquartile Range (IQR) method. A high-dimensional feature selection method, variance analysis- Pearson correlation-mutual information-permutation importance (VA-PC-MI-PI), is then proposed to identify 16 key features from the initial 111 features. Furthermore, 9 algorithms are employed for prediction analysis under different temporal resolution data conditions. Based on the results, optimal time step and algorithm models are determined to construct the Blending ensemble model (BEM). Subsequently, the feature data of "sailing speed" and "bow draft", which account for the highest permutation importance, are imported into the metadata set to alleviate insufficient BEM data utilization. Additionally, Extra Trees (ET) model is chosen as the meta-learner for adaptation and Bayesian method is employed for global optimization. The resulting improved Blending ensemble model (IBEM) exhibits optimal prediction accuracy and generalization ability with an RMSE of 66.04 kg/h, representing a reduction of 16.99% and 13.86% compared to the Support Vector Machine (SVM) model and BEM, respectively. Additionally, the IBEM exhibits significantly smaller residuals and absolute residuals, demonstrating superior predictive stability and consistency. This study provides an important reference and basis for energy efficiency prediction, control, and optimization of wing-diesel hybrid ships. [Display omitted] • Highly accurate prediction of fuel consumption for wing-diesel hybrid ships. • Proposed a high-dimensional feature selection method based on the combined application of VA-PC-MI-PI. • Explored the influence of temporal resolution on each algorithmic model. • Analyzed the permutation importance of each feature in different algorithmic models. • Improved the Blending ensemble learning method based on enhanced metadata set, optimized meta learner and Bayesian global optimization. [ABSTRACT FROM AUTHOR]

The utilization of wind-assisted propulsion technology could reduce ship fuel consumption and emission of pollutants. In the study, the effect of steady heel angles on the aerodynamic characteristics of wing sails was investigated. Full-scale three-dimensional simulations with the ship's superstructure were conducted at heel angles of 0°–15° in all apparent wind directions. The correctness of the numerical computations is verified by comparing them with the wind tunnel experimental data. Overall, the heel is detrimental to the capture of wind energy by the wing sails. The aerodynamic forces of the sail system decrease with increasing heel angles. Specifically, the average thrust performance is attenuated by 4.7%, 13.5% and 20.5%, respectively, at heel angles of 5°, 10°, and 15° compared to the upright condition. Due to changes in the airflow distribution around the sails, the aerodynamic force of sails in heeled to windward and heeled to leeward decreases by the reduced area of the low-pressure zone on the suction side and the high-pressure zone on the pressure side, respectively. Finally, a prediction scheme for assessing the effect of rolling motion on sail performance is proposed by steady heel results. • The effect of the heel on the aerodynamic performance of wing sails is determined. • The aerodynamic forces of the sail system decrease with increasing heel angles. • Thrust performance reduction of the sail system up to 20.5% at a 15° heel angle. • Pressure distribution variations on both sides lead to sail performance reduction. [ABSTRACT FROM AUTHOR]

• The initiation of HICs is mainly dominated by planar dislocation slips at a slower strain rate for high-Mn TWIP/TRIP steels with the lower PVFM. • The initiation of HICs is mainly dominated by deformation twins at faster a strain rate for high-Mn TWIP/TRIP steels with the lower PVFM. • The inconsistent deformation of ε-martensite promotes the initiation of HICs at the two strain rate for high-Mn TWIP/TRIP steels with the higher PVFM. • The ε/γ interfaces with the orientation of the N-W orientation play a role in arresting the propagation of HICs. • The ε-martensite with <0001>||RD microscopic crystallographic orientation promotes the formation of cleavage or quasi-cleavage fracture morphology. The initiation and propagation of hydrogen-induced cracks (HICs) in high-Mn twinning/transformation-induced plasticity (TWIP/TRIP) steels were explored by slow strain rate tension test. For TWIP/TRIP steels with 10% phase volume fractions of ε-martensite (PVFM), the initiation of HICs is dominated by dislocation slips at 1 × 10−6 s−1, but, at 1 × 10−5 s−1, it is dominated by deformation twins. For TWIP/TRIP steels with 45% PVFM, inconsistent deformation of ε-martensite promotes HICs initiation. Both Σ3 grain boundary and γ/ε phase interface with Nishiyama-Wassermann orientation could prevents HICs propagation. And ε-martensite with <0001>||RD microscopic orientation at the crack tip is more likely to induce transgranular crack propagation. [ABSTRACT FROM AUTHOR]

Accurate fuel consumption prediction is essential for optimizing the operation of wing-diesel hybrid vessels and improving energy efficiency. This paper proposes a grey box model (GBM) for wing-diesel hybrid vessel fuel consumption prediction based on feature construction. Both parallel and series grey box modelling methods, as well as six machine learning (ML) algorithms are adopted to establish twelve combinations of prediction models. Then, a feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is proposed. Three types of wing features, namely wing thrust, wing thrust power, and wing fuel consumption savings are constructed and introduced into each combination respectively. Finally, based on noon report data of a wing-diesel hybrid vessel, the combinations are trained and validated. The best combination is obtained by considering the root mean square error (RMSE), which is parallel modeling method, random forest (RF) algorithm, and wing fuel consumption savings feature. Its RMSE decreased by 41.7 % compared to the white box model (WBM). Therefore, the GBM proposed in this paper can predict the daily fuel consumption of wing-diesel hybrid vessels with high accuracy, facilitating operational optimization and contributing to the greenization and decarbonization of the shipping industry. • A GBM for predicting fuel consumption of wing-diesel hybrid ships is proposed. • Method proposed for constructing wing features to improve GBM prediction performance. • The data integration method is adopted to improve the quality of meteorological data. • The GBM prediction error (RMSE) is reduced by 41.7 % compared to the original WBM. • The GBM can predict the fuel consumption of hybrid system under various conditions. [ABSTRACT FROM AUTHOR]

• Plasma reelin levels were decreased in MDD patients and increased after treatment. • Reelin-ApoER2-NR2A/NR2B signaling might play a vital role in pathological mechanism depression. • Peripheral reelin may be a biological marker of great diagnostic value for MDD. • Reelin in the hippocampus might be more involved in the antidepressant effects of vortioxetine. Major depressive disorder (MDD) is a devastating mental illness and the leading cause of disability worldwide. Previous studies have suggested that synaptic plasticity in the hippocampus plays an important role in depression pathogenesis. Reelin is expressed mainly in the frontal lobe and hippocampus, and is closely associated with neurodevelopment and synaptic plasticity. However, few studies have investigated its role in MDD combining clinical trials and animal experiments. We show that in a clinical trial, plasma reelin levels decreased in patients with first-episode drug-naïve MDD and increased after treatment; further, plasma reelin levels allowed to distinguish drug-naïve patients with first-episode MDD from healthy individuals. In rats, chronic mild and unpredictable stress led to a decrease in both reelin mRNA and protein levels in the hippocampus, which could be reversed by vortioxetine. Subsequent experiments confirmed that the reelin-ApoER2-NR2A /NR2B pathway regulates hippocampal synaptic plasticity and may be involved in depression or antidepressant responses. Our work contributes to a deeper understanding of MDD pathogenesis and provides new evidence that reelin should be considered a potential therapeutic target for MDD. [ABSTRACT FROM AUTHOR]

The adsorption of anionic surfactant sodium dodecylbenzenesulfonate (SDBS) onto preformed particle gels (PPGs) and the effect of SDBS on the swelling ratio and rheology of PPGs were investigated. SDBS molecules can adsorb onto PPGs because of the hydrophobic association with the chain of PPGs at low concentration and the association of the SDBS micelles with the chains of PPGs at high concentration. PPGs contract and the shear stress of PPGs decreases after adsorption of SDBS. In addition, the storage modulus decreases first and then increases with increasing SDBS concentration. [ABSTRACT FROM PUBLISHER]

A Co/Fe–N–C catalyst layer (CL) with highly dispersed CoFe nanoalloy is obtained by careful design of a Co/Fe-ZIF precursor, resulting in a high oxygen reduction reaction site density with good stability in both 0.1 M KOH and 0.1 M HClO 4. A multi-scale study of different current density ranges (RDE, HCT, and SCT) indicates the CL performance is dominated by comprehensive properties, which include gas diffusion, ion conductivity, and catalyst activity. [Display omitted] • Co/Fe–N–C cathode catalyst layers with high active site density were synthesized. • Synergistic effect of CoFe nanoalloy and M–N 4 enhances ORR activity. • Half-cell setup shows a high current density (>100 mA cm−2) comparing with the RDE. • Multi-scale evaluation favors in-depth understanding of catalyst layer properties. Recently, much work has been devoted to designing catalysts with high porosity and efficient active sites. Although very promising results are achieved using Co/Fe–N–C catalysts based on rotating disk electrode (RDE) tests, actual fuel cell performance is below expectations, probably due to insufficient understanding of the catalyst layer (CL). Therefore, catalyst design should be considered holistically by taking into account CL performance, not only intrinsic activity. Here, Co/Fe–N–C with highly dispersed CoFe nanoalloy in the carbon network is obtained by careful design of Co/Fe-ZIF precursor, resulting in a high oxygen reduction reaction (ORR) site density with good stability. Concerning RDE test in the kinetic region and single cell test (SCT) with complex influence factors, the half-cell test (HCT) is introduced to more accurately evaluate the quality of the Co/Fe–CL. Multi-scale measurements (RDE, HCT and SCT) in different current density ranges allows targeting the key CL influence factors for fuel cell performance. [ABSTRACT FROM AUTHOR]