Nowadays, neurological diseases represent a medical emergency for which new prevention, monitoring and adequate treatment solutions are needed. ALAMEDA project proposes a monitoring solution for patients with Parkinso...
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The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aer...
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The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these *** the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired *** the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator *** translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking *** employ an exact tracking differentiator to handle variables that are challenging to differentiate *** paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.
The selection of chemical reactions is directly related to the quality of synthesis pathways,so a reasonable reaction evaluation metric plays a crucial role in the design and planning of synthesis *** reaction conditi...
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The selection of chemical reactions is directly related to the quality of synthesis pathways,so a reasonable reaction evaluation metric plays a crucial role in the design and planning of synthesis *** reaction conditions also need to be considered in synthesis pathway design,a reaction metric that combines reaction time,temperature,and yield is required for chemical reactions of different reaction *** this study,a chemical reaction graph descriptor which includes the atom-atom mapping relationship is proposed to effectively describe ***,through pre-training using graph contrastive learning and fine-tuning through supervised learning,we establish a model for generating the probability of reaction superiority(RSscore).Finally,to validate the effectiveness of the current evaluation index,RSscore is applied in two applications,namely reaction evaluation and synthesis routes analysis,which proves that the RSscore provides an important agents-considered evaluation criterion for computer-aided synthesis planning(CASP).
Mobile edge computing(MEC)is a promising technology for the Internet of Vehicles,especially in terms of application offloading and resource *** existing offloading schemes are sub-optimal,since these offloading strate...
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Mobile edge computing(MEC)is a promising technology for the Internet of Vehicles,especially in terms of application offloading and resource *** existing offloading schemes are sub-optimal,since these offloading strategies consider an application as a *** comparison,in this paper we propose an application-centric framework and build a finer-grained offloading scheme based on application *** our framework,each application is modelled as a directed acyclic graph,where each node represents a subtask and each edge represents the data flow dependency between a pair of *** vehicles and MEC server within the communication range can be used as candidate offloading ***,the offloading involves assigning these computing nodes to *** addition,the proposed offloading scheme deal with the delay constraint of each *** experimental evaluation show that,compared to existing non-partitioning offloading schemes,this proposed one effectively improves the performance of the application in terms of execution time and throughput.
Corrosion poses a significant challenge in industries due to material degradation and high maintenance costs, making effective inhibitors essential. Recent studies suggest expired pharmaceuticals as alternative corros...
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Zinc-air batteries(ZABs)are regarded as promising next-generation energy storage devices but limited by their sluggish oxygen reduction/evolution reactions(ORR/OER).Herein,the bifunctional catalyst consisting of MXene...
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Zinc-air batteries(ZABs)are regarded as promising next-generation energy storage devices but limited by their sluggish oxygen reduction/evolution reactions(ORR/OER).Herein,the bifunctional catalyst consisting of MXene and metal compounds has been constructed via a controllable *** demonstration,a 3D MXene framework with anchored heterostructure CoNi/CoNiP and nitrogen-doped carbon(NC)called H-CNP@M is constructed by metal-ion inducement and *** bimetal-semiconductor heterostructure greatly enhances the catalytic *** H-CNP@M exhibits superior activities to-Ward ORR(E_(i/2)=0.833V)and OER(η_(10)=294 mV).Both aqueous and all-solid-state ZAB assembled with H-CNP@M demonstrate superior performance(peak power density of 166.5 mW/cm^(2)in aqueous case).This work provides a facile and general strategy to prepare MXene-supported bimetallic heterostructure for high-performance electrochemical energy devices.
A cyclic quenching treatment(CQT)succeeded in turning a 2.3 GPa maraging steel with a Charpy impact energy of 9 J into a new grade with the same strength but a Charpy impact energy of 20 J upon 4 cyclic *** improvemen...
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A cyclic quenching treatment(CQT)succeeded in turning a 2.3 GPa maraging steel with a Charpy impact energy of 9 J into a new grade with the same strength but a Charpy impact energy of 20 J upon 4 cyclic *** improvement of mechanical properties is attributed to the refinement and increased chemical heterogeneity of the martensitic substructure,rather than the refinement of prior austenite grain(PAG),as well as the Transformation-Induced Plasticity(TRIP)effect facilitated by small austenite *** role of local segregation of Ni during CQT in the formation of Ni-rich austenite grains,Ni-rich martensite laths and Ni-poor martensite laths,was investigated and verified by DICTRA *** study highlights the important influence of Ni partitioning behavior during CQT,providing insights into microstructural evolution and mechanical properties.
With the growing demand for products nowadays, how to improve the efficiency of industrial production is a pressing issue. This study mainly completes the scheduling methods of RGV for two processes. Based on 0-1 plan...
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Spatio-temporal query services have been playing an increasingly important role in people's daily lives. While outsourcing such services to third parties (e.g., cloud servers) offers considerable benefits, it rais...
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Feature extraction is crucial in bioinformatics, as it converts genomic sequences into numerical feature vectors essential for machine learning algorithms, particularly in clustering, to identify the families of newly...
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Feature extraction is crucial in bioinformatics, as it converts genomic sequences into numerical feature vectors essential for machine learning algorithms, particularly in clustering, to identify the families of newly sequenced genomes. Traditional methods have relied on alignment-based techniques for clustering the genomic sequences. However, these methods are computationally intensive. In contrast, alignment-free methods are now more commonly used due to their reduced computational demands. Despite this, many alignment-free approaches may generate identical feature vectors for dissimilar sequences, as they focus solely on single nucleotide counts (1-gram) and their arrangement during feature extraction, often neglecting dinucleotide counts and their arrangement, which can degrade clustering performance. Furthermore, certain approaches include trinucleotide or higher-order compositions;they introduce high-dimensionality issues, resulting in inaccurate results. Additionally, some existing methods are not scalable and take substantial time to extract features from large genomic sequences. To address these issues, we proposed a novel 33-dimensional Scalable Alignment-Free Feature Vector (33d-SAFFV) approach to extract the significantly important features such as length of sequence, count of dinucleotides, and positional sum of dinucleotides, which produces a 33-dimensional feature vector. This approach leverages Apache Spark for scalability and efficient in-memory computations, making it suitable for large datasets. We evaluated the performance of our proposed method by applying the extracted 33-dimensional feature vectors to K-Means and Fuzzy C-Means (FCM) clustering algorithms. Performance is measured using the Silhouette Index (SI) and Calinski-Harabasz (CH) index. Experimental results on the gene sequences of four varieties of rice datasets and two varieties of soybean datasets show the effectiveness of the proposed 33d-SAFFV approach. In K-Means clustering with t
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