Practical Distributed Control for VTOL UAVs to Pass a Tunnel

Unmanned Aerial Vehicles (UAVs) are now becoming increasingly accessible to amateur and commercial users alike. An air traffic management (ATM) system is needed to help ensure that this newest entrant into the skies does not collide with others. In an ATM, airspace can be composed of airways, intersections and nodes. In this paper, for simplicity, distributed coordinating the motions of Vertical TakeOff and Landing (VTOL) UAVs to pass an airway is focused. This is formulated as a tunnel passing problem, which includes passing a tunnel, inter-agent collision avoidance and keeping within the tunnel. Lyapunov-like functions are designed elaborately, and formal analysis based on invariant set theorem is made to show that all UAVs can pass the tunnel without getting trapped, avoid collision and keep within the tunnel. What is more, by the proposed distributed control, a VTOL UAV can keep away from another VTOL UAV or return back to the tunnel as soon as possible, once it enters into the safety area of another or has a collision with the tunnel during it is passing the tunnel. Simulations and experiments are carried out to show the effectiveness of the proposed method and the comparison with other methods

Practical formula to calculate tension of vertical cable with hinged-fixed conditions based on vibration method

Vertical cables are widely used in the tied-arch bridges and suspension bridges as the vital components to transfer load. It is very important to accurately estimate the cable tensions in the cable supported bridges during both construction and in-service stages. Vibration method is the most widely used method for in-situ measurement of cable tensions. But for the cables with hinged-fixed boundary conditions, no analytical formulas can be used to describe the relationship between the frequencies and the cable tension. According to the general solution of the vibration equation and based on its numerical computational results, practical formula to calculate tensions of vertical cables by multiple natural frequencies satisfying hinged-fixed boundary conditions is proposed in this paper. The expression of the practical formula is the same as the solution derived from an axially loaded beam with simple supported ends and can use the first 10 order frequencies to calculate the cable tension conveniently and accurately. Error analysis showed that when using the fundamental frequency to estimate cable force, the estimated tension errors of the cables with its dimensionless parameter ξ≥ 2.8 are less than 2 %. It contained nearly all of the vertical cables used in bridge engineering. In addition, with multiple natural frequencies being measured, bending stiffness of the cable can be identified by using the formulas presented in this paper with an iterative method. At last, the practical formula in this paper is verified to have high precision with several numerical examples, and can be conveniently applied to field test for cable-supported bridges

Advances in Non-Invasive Blood Pressure Monitoring

This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities

Tension estimation of hangers with shock absorber in suspension bridge using finite element method

Accurate and efficient estimation of tension in hangers is very important since hangers are the vital component of suspension bridges. But for hangers with shock absorber, the existing tension estimation methods are not suitable because they are based on a single cable model and cannot consider the effect of shock absorbers. To this end, the effect of the shock absorber is taken into account by using the degree-of-freedom condensation method, and a finite element method for tension estimation of hangers with shock absorber is proposed in this paper. Finally, the proposed method is applied in the Aizhai Bridge and Huangpu Pearl River Bridge to estimate the tension of hangers with shock absorber, the tested results show that as compared with other methods, the proposed method is a more accurate and convenient method for engineering application

Deep Learning vs. Atlas-Based Models for Fast Auto-Segmentation of the Masticatory Muscles on Head and Neck CT Images

BACKGROUND: Impaired function of masticatory muscles will lead to trismus. Routine delineation of these muscles during planning may improve dose tracking and facilitate dose reduction resulting in decreased radiation-related trismus. This study aimed to compare a deep learning model with a commercial atlas-based model for fast auto-segmentation of the masticatory muscles on head and neck computed tomography (CT) images. MATERIAL AND METHODS: Paired masseter (M), temporalis (T), medial and lateral pterygoid (MP, LP) muscles were manually segmented on 56 CT images. CT images were randomly divided into training (n = 27) and validation (n = 29) cohorts. Two methods were used for automatic delineation of masticatory muscles (MMs): Deep learning auto-segmentation (DLAS) and atlas-based auto-segmentation (ABAS). The automatic algorithms were evaluated using Dice similarity coefficient (DSC), recall, precision, Hausdorff distance (HD), HD95, and mean surface distance (MSD). A consolidated score was calculated by normalizing the metrics against interobserver variability and averaging over all patients. Differences in dose (∆Dose) to MMs for DLAS and ABAS segmentations were assessed. A paired t-test was used to compare the geometric and dosimetric difference between DLAS and ABAS methods. RESULTS: DLAS outperformed ABAS in delineating all MMs (p \u3c 0.05). The DLAS mean DSC for M, T, MP, and LP ranged from 0.83 ± 0.03 to 0.89 ± 0.02, the ABAS mean DSC ranged from 0.79 ± 0.05 to 0.85 ± 0.04. The mean value for recall, HD, HD95, MSD also improved with DLAS for auto-segmentation. Interobserver variation revealed the highest variability in DSC and MSD for both T and MP, and the highest scores were achieved for T by both automatic algorithms. With few exceptions, the mean ∆D98%, ∆D95%, ∆D50%, and ∆D2% for all structures were below 10% for DLAS and ABAS and had no detectable statistical difference (P \u3e 0.05). DLAS based contours had dose endpoints more closely matched with that of the manually segmented when compared with ABAS. CONCLUSIONS: DLAS auto-segmentation of masticatory muscles for the head and neck radiotherapy had improved segmentation accuracy compared with ABAS with no qualitative difference in dosimetric endpoints compared to manually segmented contours

An efficient method for decellularization of the rat liver

Background/PurposeUsing gradient ionic detergent, we optimized the preparation procedure for the decellularized liver biologic scaffold, and analyzed its immunogenicity and biocompatibility.MethodsEDTA, hypotonic alkaline solution, Triton X-100, and gradient sodium dodecyl sulfate (1%, 0.5%, and 0.1%, respectively) were prepared for continuous perfusion through the hepatic vascular system. The decellularization of the liver tissue was performed with the optimized reagent buffer and washing protocol. In addition, the preservation of the original extracellular matrix was observed. To analyze its biocompatibility, the scaffold was embedded in a heterologous animal and the inflammation features, including the surrounding cell infiltration and changes of the scaffold architecture, were detected. The cell-attachment ability was also validated by the perfusion culture of HepG2 cells with the scaffold.ResultsBy using gradient ionic detergent, we completed the decellularization process in approximately 5 h, which was shorter than >10 hours in previous experiments (p<0.001). The extracellular matrix was kept relatively intact, with no obvious inflammatory cellular infiltration or structural damage in the grafted tissue. The engraftment efficiencies of HepG2 were 86±5% (n=8). The levels of albumin and urea synthesis were significantly superior to the ones in traditional two-dimensional culture.ConclusionThe current new method can be used efficiently for the decellularization of the liver biologic scaffold with satisfying biocomparability for application both in vivo and in vitro

Generative Multimodal Models are In-Context Learners

The human ability to easily solve multimodal tasks in context (i.e., with only a few demonstrations or simple instructions), is what current multimodal systems have largely struggled to imitate. In this work, we demonstrate that the task-agnostic in-context learning capabilities of large multimodal models can be significantly enhanced by effective scaling-up. We introduce Emu2, a generative multimodal model with 37 billion parameters, trained on large-scale multimodal sequences with a unified autoregressive objective. Emu2 exhibits strong multimodal in-context learning abilities, even emerging to solve tasks that require on-the-fly reasoning, such as visual prompting and object-grounded generation. The model sets a new record on multiple multimodal understanding tasks in few-shot settings. When instruction-tuned to follow specific instructions, Emu2 further achieves new state-of-the-art on challenging tasks such as question answering benchmarks for large multimodal models and open-ended subject-driven generation. These achievements demonstrate that Emu2 can serve as a base model and general-purpose interface for a wide range of multimodal tasks. Code and models are publicly available to facilitate future research.Comment: Accepted to CVPR 2024. Project page: https://baaivision.github.io/emu

catena-Poly[[bis­(methanol-κO)bis­(pyridine-κN)nickel(II)]-μ-tetra­fluoro­terephthalato-κ2 O:O′]

In the title compound, [Ni(C8F4O4)(C5H5N)2(CH4O)2]n, the NiII ion is located on an inversion center and is coordinated by four O atoms [Ni—O = 2.079 (4) Å] from two tetra­fluoro­terephthalate ligands and two methanol mol­ecules, and by two N atoms [Ni—N = 2.127 (4) Å] from two pyridine ligands in a distorted octa­hedral geometry. The NiII ions are connected via the tetra­fluoro­terephthalate anions into a one-dimensional chain running along the crystallographic [011] direction

Unified Multi-Objective Genetic Algorithm for Energy Efficient Job Shop Scheduling

In recent years, people have paid more and more attention to traditional manufacturing’s environmental impact, especially in terms of energy consumption and related emissions of carbon dioxide. Except for adopting new equipment, production scheduling could play an important role in reducing the total energy consumption of a manufacturing plant. Machine tools waste a considerable amount of energy because of their underutilization. Consequently, energy saving can be achieved by switching machines to standby or off when they lay idle for a comparatively long period. Herein, we first introduce the objectives of minimizing non-processing energy consumption, total weighted tardiness and earliness, and makespan into a typical production scheduling model-the job shop scheduling problem, based on a machine status switching framework. The multi-objective genetic algorithm U-NSGA-III combined with MME (a heuristic algorithm combined with the MinMax (MM) and Nawaz–Enscore–Ham (NEH) algorithms) population initialization method is used to solve the problem. The multi-objective optimization algorithm can generate a Pareto set of solutions so that production managers can flexibly select a schedule from these non-dominated schedules based on their priorities. Three sets of numerical experiments have been carried out on the extended Taillard benchmark to verify this three-objective model’s effectiveness and the multi-objective optimization algorithm. The results show that U-NSGA-III has obtained better Pareto solutions in most test problem instances than NSGA-II and NSGA-III. Furthermore, the non-processing energy consumption is reduced by 46%-69%, which is 13-83% of the total energy consumption

Efficient Polymer Light‐Emitting Diode Using Air‐Stable Metal Oxides as Electrodes

Poly(phenylenevinylene)‐based organic light‐emitting diodes (OLEDs) are fabricated using air‐stable metal oxides as electrodes, producing very efficient and bright electroluminescent devices. Efficiencies of 8 cd A−1 and luminances above 20000 cd m−2 are obtained, comparable to the values reported for classic OLED structures using reactive metals as cathodes