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Cruise ships are distinguished as special passenger ships, transporting passengers to various ports and giving importance to comfort. High comfort can attract lots of passengers and generate substantial profits. Vibration and noise are the most important indicators for assessing the comfort of cruise ships. Existing methods for analyzing vibration and noise data have shown limitations in uncovering essential information and discerning critical disparities in vibration and noise levels across different ship districts. Conversely, the rapid development in machine learning present an opportunity to leverage sophisticated algorithms for a more insightful examination of vibration and noise aboard cruise ships. This study designed a machine learning-driven approach to analyze the vibration and noise data. Drawing data from China’s first large-scale cruise ship, encompassing 127 noise samples, this study sets up a classification task, where decks were assigned as labels and frequencies served as features. Essential information was extracted by investigating this problem. Several machine learning algorithms, including feature ranking, selection, and classification algorithms, were adopted in this method. One or two essential noise frequencies related to each of the decks, except the 10th deck, were obtained, which were partly validated by the traditional statistical methods. Such findings were helpful in reducing and controlling the vibration and noise in cruise ships. Furthermore, the study develops a classifier to distinguish noise samples, which utilizes random forest as the classification algorithm with eight optimal frequency features identified by LightGBM. This classifier yielded a Matthews correlation coefficient of 0.3415. This study gives a new direction for investigating vibration and noise in ships.

RNA methylation is an important regulatory process to determine immune cell function but how it affects the anti-tumor activity of CD8 T cells is not fully understood. Here we show that the N 6 -methyladenosine (m 6 A) RNA reader YTHDF2 is highly expressed in early effector or effector-like CD8 T cells. We find that YTHDF2 facilitates nascent RNA synthesis, and m 6 A recognition is fundamental for this distinctively nuclear function of the protein, which also reinforces its autoregulation at the RNA level. Loss of YTHDF2 in T cells exacerbates tumor progression and confers unresponsiveness to PD-1 blockade in mice and in humans. In addition to initiating RNA decay that is necessary for mitochondrial fitness, YTHDF2 orchestrates chromatin changes that promote T cell polyfunctionality. YTHDF2 interacts with IKZF1/3, which is important for sustained transcription of their target genes. Accordingly, immunotherapy-induced efficacy could be largely restored in YTHDF2-deficient T cells through combinational use of IKZF1/3 inhibitor lenalidomide in a mouse model. Thus, YTHDF2 coordinates epi-transcriptional and transcriptional networks to potentiate T cell immunity, which could inform therapeutic intervention. RNA methylation has recently identified as an important regulatory mechanism governing functional cellular states, but its effect on the antitumour activity of CD8  +  T cells is not fully explored. Here authors assign an essential nuclear, m 6 A-recognition-dependent function to YTHDF2, which, in conjunction with its regulatory role in IKZF1/3-mediated gene transcription, governs anti-tumor activity in CD8  +  T cells.

The propagation of uncertainties in structural dynamic responses, arising from variations in material properties, geometry, and boundary conditions, is of critical concern to researchers in a variety of engineering instances. Conventional methods like high-fidelity Monte Carlo simulation are computationally prohibitive, while existing surrogate models can improve efficiency at the expense of accuracy. To achieve a trade-off between accuracy and efficiency, a Physics-Informed Conditional Variational Autoencoder (PI-CVAE) model is proposed. It integrates a novel dual-branch encoder for time-frequency feature extraction, a learnable frequency-filtering decoder, and a holistic physics-informed loss function so as to enable efficient generation of dynamic responses with high accuracy and adequate physics consistency. Comprehensive numerical analysis of plate structures demonstrates that the proposed approach achieves remarkable accuracy (maximum FRF error < 0.2% and R2 > 0.99) and a computational speedup of 8–11 times in comparison with conventional simulation techniques. By maintaining high accuracy while efficiently propagating uncertainties, the PI-CVAE model provides a practical framework for probabilistic vibration analysis, especially during the acoustic design phase.

Baseline left ventricular (LV) dysfunction is associated with subsequent risks of acute kidney injury (AKI) and mortality in patients with sepsis. This study investigated the therapeutic effects of continuous renal replacement therapy (CRRT) in hemodynamically unstable patients with severe sepsis and septic shock combined with LV dysfunction. In this multicenter retrospective study, severe sepsis and septic shock patients with LV dysfunction were classified into one of two groups according to the timing of CRRT: the early group (before AKI was detected) or the control group (patients with AKI). Patients from the control group received an accelerated strategy or a standard strategy of CRRT. The primary outcome was all-cause intensive care unit (ICU) mortality. Patients were weighted by stabilized inverse probability of treatment weights (sIPTW) to overcome differences in baseline characteristics. After sIPTW analysis, the ICU mortality was significantly lower in the early group than the control group (27.7% vs. 63.5%, p  < 0.001). Weighted multivariable analysis showed that early CRRT initiation was a protective factor for the risk of ICU mortality (OR 0.149; 95% CI 0.051–0.434; p  < 0.001). The ICU mortality was not different between the accelerated- and standard-strategy group (52.5% vs. 52.9%, p  = 0.970). Early CRRT in the absence of AKI is suggested for hemodynamically unstable patients with severe sepsis and septic shock combined with LV dysfunction since it benefits survival outcomes.

In this study, nitrogen- and sulfur-co-doped MXene (NS-MXene) was developed as a high-performance cathode material for lithium–sulfur (Li-S) batteries. Heterocyclic Se2S6 molecules were successfully confined within the NS-MXene structure using a simple melt impregnation method. The resulting NS-MXene exhibited a unique wrinkled morphology with a stable structure which facilitated rapid ion transport and provided a physical barrier to mitigate the shuttle effect of polysulfide. The introduction of nitrogen and sulfur heteroatoms into the MXene structure not only shifted the Ti d-band center towards the Fermi level but also significantly polarizes the MXene, enhancing the conversion kinetics and ion diffusion capability while preventing the accumulation of Li2S6. Additionally, the incorporation of Se and S in Se2S6 improved the conductivity compared to S alone, resulting in reduced polarization and enhanced electrical properties. Consequently, NS-MXene/Se2S6 exhibited excellent cycling stability, high reversible capacity, and reliable performance at high current densities and under extreme conditions, such as high sulfur loading and low electrolyte-to-sulfur ratios. This work presents a simple and effective strategy for designing heteroatom-doped MXene materials, offering promising potential for the development of high-performance, long-lasting Li-S batteries for practical applications.

Neuropathic pain, a debilitating nerve injury-induced condition, remains a significant clinical challenge. This study evaluates the effect of histone deacetylase 6 (HDAC6) inhibition in a spared nerve injury (SNI) mouse model. Systemic administration of the selective HDAC6 inhibitor ACY-1215 (20 mg/kg/day, 14 days), alleviated SNI-induced pain in mice of both sexes. ACY-1215 increased acetylated signal transducer and activator of transcription 3 (Ac-STAT3) and reduced phosphorylated STAT3 (p-STAT3) in the lumbar spinal cord of SNI mice. HDAC6 and p-STAT3 were expressed in spinal dorsal horn neurons, and SNI-enhanced HDAC6/STAT3 interaction was reversed by ACY-1215. Neuronal STAT3 overexpression induced pain hypersensitivity and elevated p-STAT3, tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β), effects suppressed by ACY-1215. Cytokine profiling identified CC-chemokine ligand 7 (CCL7) as a key downstream effector of the HDAC6/STAT3 axis, with ACY-1215 attenuating SNI-induced CCL7 upregulation. HDAC6 knockdown in neurons reduced p-STAT3, while HDAC6 or STAT3 knockdown diminished CCL7 production. These findings demonstrate that ACY-1215 mitigates neuropathic pain by modulating STAT3 acetylation/phosphorylation and suppressing HDAC6/STAT3-driven CCL7 and cytokine release. This study underscores the role of the HDAC6/STAT3/CCL7 signaling axis in neuropathic pain and highlights the therapeutic potential of HDAC6 inhibitors for pain management.

Background Nebulization combined with intravenous polymyxin B (PMB) for carbapenem-resistant gram-negative bacilli (CRGNB) pneumonia still has a number of failures that may be related to insufficient alveolar epithelial lining fluid (ELF) concentration of PMB. This study aimed at determining the relationship between the alveolar ELF concentration of PMB and clinical efficacy after intravenous (IV) plus inhaled (IH) PMB. Methods Seventy-five patients with pneumonia caused by CRGNB were treated with IH plus IV PMB. Alveolar lavage fluid was collected before and after nebulization, and ELF was calculated according to the urea dilution equation. Differences in clinical outcomes between patients with high and low peak and trough concentrations of ELF concentration of PMB were compared separately according to the ROC curve grouping strategy. The primary outcome was favorable clinical outcome. The secondary outcomes included microbiological outcome and time to bacterial eradication, time to renormalize body temperature, CRGNB-related and all-cause mortality, 28-day survival, length of hospitalization, inflammation marker levels and side effects related to PMB. Results Clinical efficacy and bacterial clearance were higher in the high ELF peak concentration group than in the low one (total efficacy: 94.44% vs. 48.72%, total bacterial clearance: 63.89% vs. 38.46%, both P  < 0.05). The clinical effective rate was higher in the high ELF trough concentration group than in the low one (88.89% vs. 43.33%, P  < 0.05). The 28-day survival rate was higher in the high ELF peak and trough concentration group than in the low one (peak: 86.11% vs. 38.46%, trough: 75.56% vs. 40.00%, both P  < 0.05). Conclusions Patients with high PMB alveolar ELF concentrations demonstrated more favorable clinical outcomes than those with low concentrations. Trial registration This trial was registered. The Chinese trial registration number is ChiCTR2100044087. The date of registration is 9-3-2021. The registered name is that clinical study on intravenous drip and aerosol inhalation of polymyxin B for the treatment of pneumonia due to multidrug-resistant gram-negative bacteria.

Background Microbial communities are of critical importance in the human host. The lung and gut microbial communities represent the most essential microbiota within the human body, collectively referred to as the gut-lung axis. However, the differentiation between these communities and their influence on clinical outcomes in critically ill patients remains uncertain. Methods An observational cohort study was obtained in the intensive care unit (ICU) of an affiliated university hospital. Sequential samples were procured from two distinct anatomical sites, namely the respiratory and intestinal tracts, at two precisely defined time intervals: within 48 h and on day 7 following intubation. Subsequently, these samples underwent a comprehensive analysis to characterize microbial communities using 16S ribosomal RNA (rRNA) gene sequencing and to quantify concentrations of fecal short-chain fatty acids (SCFAs). The primary predictors in this investigation included lung and gut microbial diversity, along with indicator species. The primary outcome of interest was the survival status at 28 days following mechanical ventilation. Results Sixty-two mechanically ventilated critically ill patients were included in this study. Compared to the survivors, the diversity of microorganisms was significantly lower in the deceased, with a significant contribution from the gut-originated fraction of lung microorganisms. Lower concentrations of fecal SCFAs were detected in the deceased. Multivariate Cox regression analysis revealed that not only lung microbial diversity but also the abundance of Enterococcaceae from the gut were correlated with day 28 mortality. Conclusion Critically ill patients exhibited lung and gut microbial dysbiosis after mechanical ventilation, as evidenced by a significant decrease in lung microbial diversity and the proliferation of Enterococcaceae in the gut. Levels of fecal SCFAs in the deceased served as a marker of imbalance between commensal and pathogenic flora in the gut. These findings emphasize the clinical significance of microbial profiling in predicting the prognosis of ICU patients.

The anechoic coating capable of absorbing sound energy in low frequencies within broadband is essential to conceal underwater vehicles. However, the geometric deformation and modification of mechanical parameters under hydrostatic pressure affect the prediction of absorption performance in deep water environments. An anechoic coating embedded with tandem resonant voids is proposed in this work to achieve quasi-perfect low-frequency and broadband absorption. The analytical method based on the effective medium approach and numerical simulation are performed to estimate the effects of hydrostatic pressure on sound absorption. When additionally considering the dynamic mechanical parameters of the compressed viscoelastic medium, the original absorption humps in low frequencies are inclined to higher band, accompanied by the expanded absorption bandwidth. Then, the tandem coating specimen is measured in a water-filled impedance tube. The experimental spectra are consistent with the analytical and numerical results under various hydrostatic pressures, demonstrating the efficient absorption (α > 0.7) in broadband low frequencies via ordinary pressure. At the same time, the absorption spectrum under higher hydrostatic pressures is also verified in the tube. Consequently, this work paves the way for a broadband low-frequency underwater absorber design and provides an efficient method to characterize the low-frequency and broadband absorption from the coupled resonant coatings in deep water environments.

The dynamic stiffness method (DSM) is proposed for vibration transmission from a machine with three degree of freedoms (DOFs) to its supporting beam structures. The machine is idealized as a rigid mass with three major degrees of freedom, namely, heave, roll, and pitch. It implies that the moments of inertia and torques due to unbalanced parts can be taken into consideration. The three types of vibration within beam structures, i.e., bending, longitudinal, and torsional motions, are formulated in terms of dynamic stiffness matrices. The finite element techniques can be applied similarly to assemble the developed dynamic stiffness matrices of both the machine and its supporting beam structures. A beam-like raft carrying a machine is designed to illustrate the accuracy of the proposed method in numerical simulation, where the differences brought by three-DOF modeling in vibration transmission analysis are discussed as well. This work would provide a novel and easy-to-use alternative to the existing mobility method and finite element method due to low discretization requirements, high efficiency, and high accuracy.