Effect of mechanical ventilation under intubation on respiratory tract change of bacterial count and alteration of bacterial flora.

Background: The most common 'second strike' in mechanically ventilated patients is a pulmonary infection caused by the ease with which bacteria can invade and colonize the lungs due to mechanical ventilation. At the same time, metastasis of lower airway microbiota may have significant implications in developing intubation mechanical ventilation lung inflammation. Thus, we establish a rat model of tracheal intubation with mechanical ventilation and explore the effects of mechanical ventilation on lung injury and microbiological changes in rats. To provide a reference for preventing and treating bacterial flora imbalance and pulmonary infection injury caused by mechanical ventilation of tracheal intubation. Methods: Sprague-Dawley rats were randomly divided into Control, Mechanical ventilation under intubation (1, 3, 6 h) groups, and Spontaneously breathing under intubation (1, 3, 6 h). Lung histopathological injury scores were evaluated. 16SrDNA sequencing was performed to explore respiratory microbiota changes, especially, changes of bacterial count and alteration of bacterial flora. Results: Compared to groups C and SV, critical pathological changes in pulmonary lesions occurred in the MV group after 6 h (p < 0.05). The Alpha diversity and Beta diversity of lower respiratory tract microbiota in MV6, SV6, and C groups were statistically significant (p < 0.05). The main dominant bacterial phyla in the respiratory tract of rats were Proteobacteria, Firmicutes, Bacteroidetes, and Cyanobacteria. Acinetobacter radioresistens in group C was significant, Megaonas in group MV6 was significantly increased, and Parvibacter in group SV6 was significantly increased. Anaerobic, biofilm formation, and Gram-negative bacteria-related functional genes were altered during mechanical ventilation with endotracheal intubation. Conclusion: Mechanical ventilation under intubation may cause dysregulation of lower respiratory microbiota in rats.

General Anesthesia Versus Regional Anesthesia in the Elderly Patients Undergoing Hip Fracture Surgeries: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

BACKGROUND: Surgery is the preferred treatment option for the elderly patients with hip fractures. However, the choice of general anesthesia (GA) or regional anesthesia (RA) remains controversial. The quality of evidence has further improved with the advent of several high-quality randomized clinical trials (RCTs) in the last two years. The purpose of this study was to compare the clinical outcomes of two anesthetic techniques in elderly patients undergoing hip fracture surgeries. METHODS: Eligible studies were identified from PubMed/MEDLINE, Web of Science, Scopus, EMBASE and reference lists from January 2000 to June 2022 in this current systematic review and meta-analysis. The outcomes included the surgery-related outcomes (duration of surgery, duration of anesthesia, intraoperative blood loss and number of transfusions) and postoperative outcomes (30-day mortality, postoperative delirium,cardiovascular events and other complications). RESULTS: A total of 10 RCTs were included, and a total of 3594 patients were analyzed. RA was associated with shorter duration of surgery, shorter length of hospital stays and less intraoperative blood loss compared to GA. There were no significant differences between the two groups in the number of blood transfusions, duration of anesthesia, 30-day mortality or postoperative delirium. CONCLUSIONS: Our pooled analysis identified no significant differences in terms of the safety between RA and GA, while RA reduces intraoperative blood loss, length of hospital stays and duration of surgery. These results suggest that RA appears to be preferable for the elderly patients with hip fractures.

A USV-UAV Cooperative Trajectory Planning Algorithm with Hull Dynamic Constraints.

Efficient trajectory generation in complex dynamic environments remains an open problem in the operation of an unmanned surface vehicle (USV). The perception of a USV is usually interfered by the swing of the hull and the ambient weather, making it challenging to plan optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for a coupled USV-UAV system is proposed to ensure that a USV can execute a safe and smooth path as it autonomously advances through multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. An initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy.

OL-SLAM: A Robust and Versatile System of Object Localization and SLAM.

This paper proposes a real-time, versatile Simultaneous Localization and Mapping (SLAM) and object localization system, which fuses measurements from LiDAR, camera, Inertial Measurement Unit (IMU), and Global Positioning System (GPS). Our system can locate itself in an unknown environment and build a scene map based on which we can also track and obtain the global location of objects of interest. Precisely, our SLAM subsystem consists of the following four parts: LiDAR-inertial odometry, Visual-inertial odometry, GPS-inertial odometry, and global pose graph optimization. The target-tracking and positioning subsystem is developed based on YOLOv4. Benefiting from the use of GPS sensor in the SLAM system, we can obtain the global positioning information of the target; therefore, it can be highly useful in military operations, rescue and disaster relief, and other scenarios.

Identifying informative tweets during a pandemic via a topic-aware neural language model.

Every epidemic affects the real lives of many people around the world and leads to terrible consequences. Recently, many tweets about the COVID-19 pandemic have been shared publicly on social media platforms. The analysis of these tweets is helpful for emergency response organizations to prioritize their tasks and make better decisions. However, most of these tweets are non-informative, which is a challenge for establishing an automated system to detect useful information in social media. Furthermore, existing methods ignore unlabeled data and topic background knowledge, which can provide additional semantic information. In this paper, we propose a novel Topic-Aware BERT (TABERT) model to solve the above challenges. TABERT first leverages a topic model to extract the latent topics of tweets. Secondly, a flexible framework is used to combine topic information with the output of BERT. Finally, we adopt adversarial training to achieve semi-supervised learning, and a large amount of unlabeled data can be used to improve inner representations of the model. Experimental results on the dataset of COVID-19 English tweets show that our model outperforms classic and state-of-the-art baselines.

20 watt-level single transverse mode narrow linewidth and tunable random fiber laser at 1.5 µm band.

High power 1.5 µm band fiber lasers are of great importance for many practical applications. Generally, the technical targets including high average output power, narrow linewidth, temporally suppressed intensity dynamics, high spectral purity, single transverse mode lasing, and excellent robustness are the major concerns when constructing a high-performance laser source. Here, we demonstrate the highest output power of a wavelength tunable 1.5 µm band random fiber laser based on the active fiber gain mechanism to the best of our knowledge. A master oscillator power-amplifier (MOPA) configuration is employed to greatly boost the output power to 20 watt-level with a single transverse mode lasing and the same linewidth as the seed, benefiting from the spectral broadening free feature when employing the random fiber laser as the seed. This work not only enriches the progress of random fiber laser, but also provides an attractive alternative in realizing high performance lasing light source at 1.5 µm band.

Role of van der Waals forces in the metal-insulator transition of transition metal oxides.

Transition metal oxides (TMOs) exhibit great potential in technological applications due to their ability to undergo a rapid metal-insulator transition (MIT). However, the phase stability of TMOs, which models the on/off voltages of electronic devices, remains controversial due to the incomplete knowledge of the determinants of its stability. Herein, we study the effect of van der Waals (vdW) interactions on the phase stability of TMOs by employing the pairwise and screened vdW methods. Our calculations manifest that the vdW interactions are crucial to the TMOs' phase stability and tend to stabilize the insulating phase. Furthermore, the long-range electrodynamic screening interactions correct the TMOs' phase stability by revising the vdW term.

Understanding the oxygen-evolution-reaction catalytic activity of metal oxides based on the intrinsic descriptors.

Metal oxides show great potential in catalyzing the oxygen evolution reaction (OER), which is taken as the bottleneck of many energy-conversion and -storage processes. However, it is still a major challenge to deeply understand the catalytic mechanism and to rapidly screen out novel metal-oxide catalysts. Herein, we find that the trend of adsorption energies of O-intermediates and the theoretical overpotentials on metal monoxides (MO), metal dioxides (MO2), and perovskite oxides (ABO3) can be determined using the descriptor ψ, which is related to the valence-electron numbers and the electronegativities of the active center. The underlying mechanism is that ψ reflects the p-band properties of superficial and adsorbed O atoms of metal oxides and thus can reveal the commonality and difference of adsorption and catalysis of the three types of metal oxides. Moreover, the ψ-determined relationships indicate the possibility of breaking the previously proposed thermodynamic limitation on the post-transition metal oxides and rationalizing the trend of experimental OER catalytic activity of metal oxide catalysts. With this easily accessible intrinsic descriptor ψ, we provide a convenient and feasible scheme for designing new candidates for OER catalysts.

The Efficacy and Safety of Intravenous Iron in Geriatric Hip Fracture Surgeries: A Systematic Review and Meta-Analysis.

BACKGROUND: With the increasing evidence provided by recent high-quality studies, the intravenous iron appears to be a reliable therapy for blood administration in geriatric patients with hip fractures. Here, this systematic review and meta-analysis were aimed to assess the effectiveness and safety of intravenous iron in geriatric patients sustaining hip fractures. METHODS: Potential pertinent literatures evaluating the effects of intravenous iron in the geriatric patients undergoing hip fractures were identified from Web of Science, PubMed, Embase, and Scopus. We performed a pairwise meta-analysis using fixed- and random-effects models, and the pooling of data was carried out by using RevMan 5.1. RESULTS: Four randomized controlled trials and four observational studies conform to inclusion criteria. The results of meta-analysis showed that intravenous iron reduced transfusion rates compared to the control group, yet the result did not reach statistical significance. The intravenous iron was related to lower transfusion volumes, shorter length of stay, and a reduced risk of nosocomial infections. And there was no significant difference in terms of the mortality and other complications between the treatment group and the control group. CONCLUSION: Current evidence suggests that intravenous iron reduces the transfusion volume, length of hospital stay, and risk of nosocomial infections. It takes about 7 days for intravenous iron to elevate hemoglobin by 1 g/dl and about 1 month for 2 g/dl. The safety profile of intravenous iron is also reassuring, and additional high-quality studies are needed.

Deep Learning-Based Intelligent Forklift Cargo Accurate Transfer System.

In this research, we present an intelligent forklift cargo precision transfer system to address the issue of poor pallet docking accuracy and low recognition rate when using current techniques. The technology is primarily used to automatically check if there is any pallet that need to be transported. The intelligent forklift is then sent to the area of the target pallet after being recognized. Images of the pallets are then collected using the forklift's camera, and a deep learning-based recognition algorithm is used to calculate the precise position of the pallets. Finally, the forklift is controlled by a high-precision control algorithm to insert the pallet in the exact location. This system creatively introduces the small target detection into the pallet target recognition system, which greatly improves the recognition rate of the system. The application of Yolov5 into the pallet positional calculation makes the coverage and recognition accuracy of the algorithm improved. In comparison with the prior approach, this system's identification rate and accuracy are substantially higher, and it requires fewer sensors and indications to help with deployment. We have collected a significant amount of real data in order to confirm the system's viability and stability. Among them, the accuracy of pallet docking is evaluated 1000 times, and the inaccuracy is kept to a maximum of 6 mm. The recognition rate of pallet recognition is above 99.5% in 7 days of continuous trials.

Understanding water slippage through carbon nanotubes.

It is a formidable challenge to understand water slippage through carbon nanotubes (CNTs), despite its great significance in fundamental research and technology. Herein, we propose an effective scheme to describe water slippage properties by extending two friction models - the phononic friction model and Einstein's diffusion model, both relying on the potential corrugation of water slippage. Our scheme effectively captures the tube-size effect on the viscosity and slippage of water molecules through CNTs. It also identifies the experimentally reported size-dependent transition from continuum to sub-continuum flow and further reveals that this transition is likely to be determined by the hydrogen bond instead of the structural transition or entropic change. Besides, the size-dependence of slip lengths is found to be controllable by temperature. Our methods are thus expected to be a useful basis for further studies on substance transport under confinement.

Well-tempered MCMC simulations for population pharmacokinetic models.

A full Bayesian statistical treatment of complex pharmacokinetic or pharmacodynamic models, in particular in a population context, gives access to powerful inference, including on model structure. Markov Chain Monte Carlo (MCMC) samplers are typically used to estimate the joint posterior parameter distribution of interest. Among MCMC samplers, the simulated tempering algorithm (TMCMC) has a number of advantages: it can sample from sharp multi-modal posteriors; it provides insight into identifiability issues useful for model simplification; it can be used to compute accurate Bayes factors for model choice; the simulated Markov chains mix quickly and have assured convergence in certain conditions. The main challenge when implementing this approach is to find an adequate scale of auxiliary inverse temperatures (perks) and associated scaling constants. We solved that problem by adaptive stochastic optimization and describe our implementation of TMCMC sampling in the GNU MCSim software. Once a grid of perks is obtained, it is easy to perform posterior-tempered MCMC sampling or likelihood-tempered MCMC (thermodynamic integration, which bridges the joint prior and the posterior parameter distributions, with assured convergence of a single sampling chain). We compare TMCMC to other samplers and demonstrate its efficient sampling of multi-modal posteriors and calculation of Bayes factors in two stylized case-studies and two realistic population pharmacokinetic inference problems, one of them involving a large PBPK model.

Strain engineering of the electronic and transport properties of monolayer tellurenyne.

Two-dimensional (2D) materials exhibiting quality electronic properties such as suitable band gap, giant Rashba effect and high carrier mobility are essential for promising applications in electronics and spintronics. Strain engineering has been recognized as an effective strategy to engineer the atomic and electronic properties of 2D materials. Herein, based on density functional theory, we demonstrate that the electronic properties of tellurenyne can be tuned well by using uniaxial strain. We find that tellurenyne retains the unique noncovalent bond structure and exhibits good stability under the uniaxial strain. Meanwhile, the band gap of tellurenyne can be tuned to a large scale (0.33-1.18 eV and 0.73-1.27 eV under the uniaxial strain along and perpendicular to the chain direction, respectively). Under 10% tension strain along the chain direction, the Rashba constant reaches 2.96 eV Å, belonging to giant Rashba systems. More importantly, the hole mobility of tellurenyne along the chain direction reaches 1.1 × 105 cm2 V-1 s-1 under 10% tension strain along the chain direction, which is one order of magnitude larger than that of phosphorene. Therefore, these remarkable electronic properties of tellurenyne engineered by using strain indicate its potential applications in electronics and spintronics.

Effects of atomic species and interatomic distance on the interactions in one-dimensional nanomaterials.

Noncovalent van der Waals (vdW) interactions are significant for the constitution of nanomaterials; however, they are not well understood in one-dimensional materials. Herein, we employ density functional theory (DFT) methods to address this issue and find that the many-body effects of vdW interactions within the one-dimensional wires composed of atoms chosen from the second period (B, C, N, O, F) vary with the interatomic distance of the wires. Furthermore, the atomic species effectively regulate the transition threshold of the many-body effects of vdW interactions. In the case of the adsorption of n-heptane (C7H16) on the wires, the atomic species alters the interactions between the wires and the molecule by modulating the coupling vibration between wires and C7H16 molecules. Correspondingly, replacing a portion of Pb with Tl atoms could contribute to the stability of the organic-inorganic hybrid halide perovskites with one-dimensional structures. Our findings not only contribute to the understanding of vdW interactions in one-dimensional structures with second-period atoms (B, C, N, O, F) but also provide clues for improving the stability of perovskites with one-dimensional structures.

Support Vector Machine for Regional Ionospheric Delay Modeling.

The distribution of total electron content (TEC) in the ionosphere is irregular and complex, and it is hard to model accurately. The polynomial (POLY) model is used extensively for regional ionosphere modeling in two-dimensional space. However, in the active period of the ionosphere, the POLY model is difficult to reflect the distribution and variation of TEC. Aiming at the limitation of the regional POLY model, this paper proposes a new ionosphere modeling method with combining the support vector machine (SVM) regression model and the POLY model. Firstly, the POLY model is established using observations of regional continuously operating reference stations (CORS). Then the SVM regression model is trained to compensate the model error of POLY, and the TEC SVM-P model is obtained by the combination of the POLY and the SVM. The fitting accuracies of the models are verified with the root mean square errors (RMSEs) and static single-frequency precise point positioning (PPP) experiments. The results show that the RMSE of the SVM-P is 0.980 TECU (TEC unit), which produces an improvement of 17.3% compared with the POLY model (1.185 TECU). Using SVM-P models, the positioning accuracies of single-frequency PPP are improved over 40% compared with those using POLY models. The SVM-P is also compared with the back-propagation neural network combined with POLY (BPNN-P), and its performance is also better than BPNN-P (1.070 TECU).

An Integrated Design with new Metal-Functionalized Covalent Organic Frameworks for the Effective Electroreduction of CO2.

One of the long-standing issues that prohibits large-scale CO2 reutilization is the low aqueous solubility of CO2 and the incurring inefficient mass transport of CO2 . Herein, we suggest a feasible way to promote the CO2 reutilization by integrating the storage and reduction, with a new covalent organic framework (COF) series constituted by cobalt-phthalocyanine and boronic acid linkers. We find that the porous structure of the cobalt COF is competitive in the CO2 storage and can sustain a high CO2 concentration around the reduction center, whereas the mass transport of CO2 as well as the efficiency of the CO2 reduction is significantly improved. The predicted cobalt COF exhibits an overpotential of 0.27 V and a CO production rate, which is 97.7 times higher than in aqueous solution, for the CO2 reduction. Our work provides a promising candidate for the CO2 reutilization, with valuable insights and an important prototype for future practical design.

Geometric and electronic structure of multilayered graphene: synergy of the nondirective ripples and the number of layers.

According to the Mermin-Wagner theorem, ripple deformation is ubiquitous in a two-dimensional (2D) free-standing sheet, influencing the electronic properties. However, the synergistic effects of the unrestricted ripples and the number of layers have still been a topic of extensive debate. To address this issue, we employed density functional theory including many-body van der Waals (vdW) correction to investigate the effects of the nondirective ripples on the geometric and electronic structures of multilayered graphene. We found that the many-body effects of vdW forces were essential for the binding of multilayered rippled graphene. The increase of curvature affects the electronic structures of rippled graphene by modifying stacking modes, while the increase in the number of layers can reduce band gap and work function directly. The coupling of these two effects can enhance the chemical activity of rippled graphene. Our results facilitate new insights into the geometric and electronic properties of rippled graphene, which can be generalized to other layered materials.

Different effects of water molecules on CO oxidation with different reaction mechanisms.

The effects of water molecules (promotion/prohibition) on CO oxidation remain debated. Herein, using density functional theory calculations, we demonstrate that water molecules can facilitate the CO + O/O2 oxidation process, but prohibit the CO + OH oxidation process, which is consistent with the experimental finding that water molecules have two distinct effects on CO oxidation. For the CO + O/O2 oxidation mechanisms, we find that the reactants were pushed towards each other due to the steric effect of the water molecules, which decreases the reaction barriers and promotes the CO + O/O2 oxidation process. For the CO + OH oxidation mechanisms, water molecules increase the stability of the COOH* intermeditae by H-bonds and van der Waals forces, which increase the barriers of the COOH* transformation process and the COOH*-tra dissociation process, and prohibit the CO + OH oxidation process. These results clarify the different effects of water molecules on CO oxidation and shed light on catalyst usage in the CO oxidation industry.

Unconventional Behavior of Friction at the Nanoscale beyond Amontons' Law.

By means of a many-body van der Waals (vdW)-corrected density functional theory approach, the atomic-scale friction of a prototypical tip-substrate system consisting of an Si tip and a graphene substrate is studied. In a loading-sliding process, the tip-substrate distance is found to be essential for nanofrictional behavior, through determining the competition between vdW contributions and electronic contributions. As the tip approaches the substrate, this competition results in a smooth transition of normal forces from attraction to repulsion, and the friction coefficient in turn undergoes a sign change from negative to positive with possible giant magnitude and strong anisotropy. The loading-sliding process does not introduce any chemical modification of the underlying system. These findings reveal the boundary of validity of Amontons' law, unify negative and giant friction coefficients, rationalize the experimentally observed anisotropy of nanofriction, and are universal when vdW interactions are crucial, all of which are helpful to establish a comprehensive picture of nanofriction.

Cobalt-porphine catalyzed CO2 electro-reduction: a novel protonation mechanism.

The urgent need for artificially fixing CO2 calls for catalysts of high efficiency. The transition metal functionalized porphyrin (TMP) is one of the most important types of organic catalysts for CO2 reduction. However, the catalytic mechanisms of TMP in CO2 reduction still remain controversial. Starting from the previously neglected catalyst self-protonation model, we uncover a new CO2 reduction mechanism on cobalt-porphine, which involves an indirect proton transfer step occurring at the beginning of the reduction cycle. Based on this protonation mechanism, we demonstrate the different correlations between producing rate and pH for the formation of CO and methane, in good agreement with available experimental observations. Our results reveal how pH and potential affect the CO2 reduction process, providing important clues and insights for further optimization of TMP catalysts.