Multi-Objective Robust Design of New Rotate Barrel Based on Satisfaction Function

R E T R A C T E D A R T I C L E In this paper, a multi-objective robust design method based on satisfaction function was proposed by combining satisfaction function with Taguchi robust to solve the multi-objective optimization problem, which was easily interfered by noise factor. This method converted the signal-to-noise ratio of product quality characteristics into the expected smaller-the-better of Taguchi robust design, and realized the multi-objective robust design by weighted geometric mean, so as to solve the multi-objective optimization problem easily affected by noise factors. Under the premise of without changing rotate barrel of basic size by LS-DYNA FE model of rotary guardrail, the proposed method was carried out on the rotate barrel of multi-objective robust design, in order to solve the new rotary guardrail section parameter uncertain multi-objective optimization design. The results showed that the robust design of the new rotate barrel could resist the interference of the noise, the structure was more robust, and it conformed to the relevant laws and regulations by which was realized the purpose of lightweight of the new rotary guardrail. The research results had certain theoretical and engineering significance in improving the robustness of the new rotary guardrail

Wide‐bandwidth nanocomposite‐sensor integrated smart mask for tracking multiphase respiratory activities

Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID-19) even in its coming endemic phase. Therefore, deploying a “smart mask” to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure-based soundwave sensor (≈400 µm), which allows the high sensitivity in a wide-bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty-one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro-recalls of ≈95% in both individual and generalized models. With rich high-frequency (≈4000 Hz) information recorded, the two-/tri-phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life

A Design of UHF-RFID Reader Antenna with Circular Polarization

A UHF-RFID reader antenna with circular polarization is designed in the present paper. In order to achieve the requirements of RFID reader applications, three measures are adopted. First way is to use a modified Minkowski fractal as radiating element for compacting dimension and broadening bandwidth. The second is to utilize the square truncation to obtain the circular polarization. In order to promote the gain of the proposed antenna, the slot-opened technology is employed lastly

Outlier Reconstruction of NDVI for Vegetation-Cover Dynamic Analyses

The normalized difference vegetation index (NDVI) contains important data for providing vegetation-cover information and supporting environmental analyses. However, understanding long-term vegetation cover dynamics remains challenging due to data outliers that are found in cloudy regions. In this article, we propose a sliding-window-based tensor stream analysis algorithm (SWTSA) for reconstructing outliers in NDVI from multitemporal optical remote-sensing images. First, we constructed a tensor stream of NDVI that was calculated from clear-sky optical remote-sensing images corresponding to seasons on the basis of the acquired date. Second, we conducted tensor decomposition and reconstruction by SWTSA. Landsat series remote-sensing images were used in experiments to demonstrate the applicability of the SWTSA. Experiments were carried out successfully on the basis of data from the estuary area of Salween River in Southeast Asia. Compared with random forest regression (RFR), SWTSA has higher accuracy and better reconstruction capabilities. Results show that SWTSA is reliable and suitable for reconstructing outliers of NDVI from multitemporal optical remote-sensing images

A Sigmoidal and Distance Combined Transformation Method for Nearly Singular Integral on Asymmetric Patch

This paper is devoted to developing a new computational method for nearly singular integral computation in the application of the boundary element method for the analysis of thin-shell-like structures in mechanical engineering. Based on the traditional distance transformation method, a sigmoidal transformation method is introduced to further cluster the integral points around the source point with respect to the circumferential direction. The combined method provides accurate results without employing a large quantity of integral points. Numerical examples demonstrate that the computational accuracy and efficiency of the proposed method is significantly higher than that of the traditional single distance transformation method, especially in the case of the asymmetric integral patch

Formation of Yolk–Shell MoS₂@void@Aluminosilica Microspheres with Enhanced Electrocatalytic Activity for Hydrogen Evolution Reaction

The development of low-cost electrode materials with enhanced activity and favorable durability for hydrogen evolution reactions (HERs) is a great challenge. MoS2 is an effective electrocatalyst with a unique layered structure. In addition, aluminosilica shells can not only provide more hydroxyl groups but also improve the durability of the catalyst as a protective shell. Herein, we have designed a hard-template route to synthesize porous yolk–shell MoS2@void@Aluminosilica microspheres in a NaAlO2 solution. The alkaline solution can directly etch silica (SiO2) hard templates on the surface of MoS2 microspheres and form a porous aluminosilica outer shell. The electrocatalytic results confirm that the MoS2@void@Aluminosilica microspheres exhibit higher electrocatalytic activity for HERs with lower overpotential (104 mV at the current density of −10 mA cm−2) and greater stability than MoS2 microspheres. The superior electrocatalytic activity of MoS2@void@Aluminosilica microspheres is attributed to the unique structure of the yolk@void@shell geometric construction, the protection of the aluminosilica shell, and the greater number of active sites offered by their nanosheet subunits. The design of a unique structure and new protection strategy may set up a new method for preparing other excellent HER electrocatalytic materials

The complete mitochondrial genome sequence of snake mackerels Paradiplospinus antarcticus (Scombroidei, Gempylidae)

For the first time, we illuminate the complete mitochondrial genome (mitogenome) sequence of the Paradiplospinus antarcticus, which is 16,988 bp in size and contains 13 protein-coding (PCGs), 2 rRNA genes, 22 tRNA genes, and one control region.The base composition of the mitogenome is 26.08% A, 26.77% T, 28.46% C and 18.69% G. Here, we selected 11 genera of species from the mostly monotypic snake mackerel family, including representative Antarctic Paradiplospinus antarcticus that have been identified, and constructed phylogenetic trees to better study the snake mackerel family

Active Retrieval Augmented Generation

Despite the remarkable ability of large language models (LMs) to comprehend and generate language, they have a tendency to hallucinate and create factually inaccurate output. Augmenting LMs by retrieving information from external knowledge resources is one promising solution. Most existing retrieval-augmented LMs employ a retrieve-and-generate setup that only retrieves information once based on the input. This is limiting, however, in more general scenarios involving generation of long texts, where continually gathering information throughout the generation process is essential. There have been some past efforts to retrieve information multiple times while generating outputs, which mostly retrieve documents at fixed intervals using the previous context as queries. In this work, we provide a generalized view of active retrieval augmented generation, methods that actively decide when and what to retrieve across the course of the generation. We propose Forward-Looking Active REtrieval augmented generation (FLARE), a generic retrieval-augmented generation method which iteratively uses a prediction of the upcoming sentence to anticipate future content, which is then utilized as a query to retrieve relevant documents to regenerate the sentence if it contains low-confidence tokens. We test FLARE along with baselines comprehensively over 4 long-form knowledge-intensive generation tasks/datasets. FLARE achieves superior or competitive performance on all tasks, demonstrating the effectiveness of our method. Code and datasets are available at https://github.com/jzbjyb/FLARE

Association Between Prekallikrein and Stroke: A Mendelian Randomization Study

Background High plasma prekallikrein was reported to be associated with increased risks of stroke, but the causality for these associations remains unclear. We aimed to investigate the associations of genetically predicted plasma prekallikrein concentrations with all‐cause stroke, ischemic stroke, 3 ischemic stroke subtypes, and intracerebral hemorrhage (ICH) using a 2‐sample Mendelian randomization approach. Methods and Results Seven independent prekallikrein‐related single‐nucleotide polymorphisms were identified as genetic instruments for prekallikrein based on a genome‐wide association study with 1000 European individuals. The summary statistics for all‐cause stroke, ischemic stroke, and ischemic stroke subtypes were obtained from the Multiancestry Genome‐wide Association Study of Stroke Consortium with 40 585 cases and 406 111 controls of European ancestry. The summary statistics for ICH were obtained from the ISGC (International Stroke Genetics Consortium) with 1545 ICH cases and 1481 controls of European ancestry. In the main analysis, the inverse‐variance weighted method was applied to estimate the associations of plasma prekallikrein concentrations with all‐cause stroke, ischemic stroke, ischemic stroke subtypes, and ICH. Genetically predicted high plasma prekallikrein levels were significantly associated with elevated risks of all‐cause stroke (odds ratio [OR] per SD increase, 1.04 [95% CI, 1.02–1.06]; P=5.44×10−5), ischemic stroke (OR per SD increase, 1.05 [95% CI, 1.03–1.07]; P=1.42×10−5), cardioembolic stroke (OR per SD increase, 1.08 [95% CI, 1.03–1.12]; P=3.75×10−4), and small vessel stroke (OR per SD increase, 1.11 [95% CI, 1.06–1.17]; P=3.02×10−5). However, no significant associations were observed for genetically predicted prekallikrein concentrations with large artery stroke and ICH. Conclusions This Mendelian randomization study found that genetically predicted high plasma prekallikrein concentrations were associated with increased risks of all‐cause stroke, ischemic stroke, cardioembolic stroke, and small vessel stroke, indicating that prekallikrein might have a critical role in the development of stroke

3D Open-Framework Vanadoborate as a Highly Effective Heterogeneous Pre-catalyst for the Oxidation of Alkylbenzenes

Three three-dimensional (3D) open-framework vanadoborates, denoted as SUT-6-Zn, SUT-6-Mn, and SUT-6-Ni, were synthesized using diethylenetriamine as a template. SUT-6-Zn, SUT-6-Mn, and SUT-6-Ni are isostructural and built from (VO)₁₂O₆ B₁₈O₃₆(OH)₆ clusters bridged by ZnO₅, MnO₆, and NiO₆ polyhedra, respectively, to form the 3D frameworks. SUT-6 is the first vanadoborate with a 3D framework. The framework follows a semiregular <i><b>hxg</b></i> net topology with a 2-fold interpenetrated diamond-like channel system. The amount of template used in the synthesis played an important role in the dimensionality of the resulting vanadoborate structures. A small amount of diethylenetriamine led to the formation of this first 3D vanadoborate framework, while an increased amount of diethylenetriamine resulted in vanadoborates with zero-dimensional (0D) and one-dimensional (1D) structures. SUT-6-Zn was proved to be an efficient heterogeneous precatalyst for the oxidation of alkylbenzenes