The authors present results of ablation on silicon with ultrafast laser radiation featuring burst pulses using an amplified burst-mode solid-state laser, featuring an emitting wavelength of 1030 nm ...to generate single burst cavities on silicon. Laser parameter are varied for different pulse durations from 270 fs up to 10 ps, burst fluences, and number of sub-pulses per burst in the respective burst regime with sub-pulse repetition rates of 65 MHz and 5 GHz. The resulting ablated volume per burst and per sub-pulse in a burst as well as the topography are investigated and discussed.
Our country has a vast territory, and rail transit is very important to the development of our country's national economy. In this paper, key technologies for a digital twin-based shop floor ...management and control system are investigated, and the concept is designed and implemented. By adding a digital twin between the business management layer and the production execution layer of the traditional workshop management and control system through the fuzzy rule neural network, a new workshop management and control system architecture on the basis of the virtual is formed, enabling intellectual management and control of the workshop. The results of the study found that the integration of the digital twin into the conventional shop floor management and control system led to changes in the composition, processes and information integration of the management and support system. For the purpose of comparing the system scheduling of the high-speed railway on the basis of the vague rule neural network with the traditional method, we made statistics on the system scheduling before and after the transformation. In terms of manufacturing volume, after the output exceeds 200, the speed of the traditional manufacturing method lags behind the fuzzy rule neural network by nearly 50%.
The purpose of this paper is to study the rough concept lattice and use the information flow to construct a second-order cone programming model for big data. Through the construction of the model, ...attribute reduction is performed on the original data of the noise in the formal background. Then, construct the concept lattice according to the reduced formal background, and then analyze the big data in the form of information flow. Then, based on the advantages of the β-upper and lower distribution reduction algorithms of the variable-precision rough set, combine the rough concept. The characteristics of the background of the lattice form, the second-order cone thought method theory is applied, and then a second-order cone calculation model is constructed. The rough concept lattice is applied to the processing of big data, and then it is analyzed and researched through concrete examples. The time required in traditional mode is between 118.3 min and 123.6 min, while the time required for second-order cone and concept lattice fitting is 92.4 min and 98.5 min. Experimental data show that the rough concept lattice uses information flow to construct a second-order cone programming model for big data, which results in a greatly reduced number of nodes in the rough concept lattice and an enhanced anti-noise capability of the system, which saves data statistics and calculation time. The traditional concept lattice algorithm can be traced back to the purification of the formal background, and the purification of the formal background can simplify the concept connotation and study attribute reduction from the perspective of lattice isomorphism. Experimental data show that the rough concept lattice uses information flow to construct a second-order cone programming model for big data, which greatly guarantees the integrity and security of the data by about 15%, and saves 20% of the data processing time compared with traditional and algorithms. It has guiding significance for the efficient and secure development of big data in the future. In this paper, data feature mining and information flow model construction are carried out, the power spectral density feature extraction of big data is carried out from a large number of noisy and fuzzy data, and the second-order cone programming model of big data information flow is carried out by rough concept lattice method.
Cet article fait suite à un article précédent qui résumait et commentait les recommandations de l’American Association of Physical Therapy (APTA) de 2012. L’objectif du présent article est de donner ...une synthèse traduite en français des récentes révisions de ces recommandations publiées par l’APTA en 2021, et de discuter de leur importance dans le domaine de la rééducation des patients lombalgiques. Les recommandations antérieures sont majoritairement confirmées, et enrichies de nouvelles techniques. Les recommandations ont été organisées par domaines – exercice, thérapies manuelles et traitements dirigés, classifications, éducation thérapeutique du patient – appliqués à des sous-groupes de patients – lombalgie aiguë ou chronique, lombalgie avec douleur du membre inférieur, lombalgie chez l’adulte âgé, lombalgie après opération. Les systèmes de classification des patients actuellement documentés sont étudiés et comparés. De nouvelles techniques, comme l’éducation à la neurophysiologie de la douleur, le dry needling et la thérapie fonctionnelle cognitive ont été documentées depuis 2012. Le massage et les techniques tissulaires font maintenant partie des recommandations. L’exercice, les traitements actifs, l’éducation à la neurophysiologie de la douleur et la thérapie manuelle sont les plus validés. Ces recommandations sont en accord avec les recommandations de la Haute Autorité de Santé de 2019. Les recommandations de l’APTA peuvent servir de base pour mettre à jour ses scripts cliniques et faire évoluer sa pratique, organiser les enseignements ou pour guider des projets de recherche sur le traitement des lombalgies.
NA.
This article is a follow-up to a previous article summarizing and commenting on the 2012 American Association of Physical Therapy (APTA) recommendations. The purpose of this article is to provide a French-language summary of the recent revisions of these recommendations published by the APTA in 2021, and to discuss their importance in the rehabilitation of low back pain patients. The majority of the previous recommendations were confirmed, and new techniques were added. The recommendations were organized by domains-exercise, manual therapies and directed treatments, classifications, patient education-applied to patient subgroups-acute or chronic LBP, LBP with lower extremity pain, LBP in older adults, LBP after surgery. Currently documented patient classification systems are reviewed and compared. New techniques, such as pain neurophysiology education, dry needling, and cognitive functional therapy have been documented since 2012. Massage and tissue techniques are now part of the recommendations. Exercise, active treatments, pain neurophysiology education, and manual therapy are the most validated. These recommendations are consistent with the 2019 HAS Guidelines. The APTA guidelines can be used as a basis for clinicians to update their clinical scripts and improve their practice, to organize teachings and to guide research about LBP.
Level of evidence NA.
Bagaza virus emerged in Spain in 2010 and was not reported in other countries in Europe until 2021, when the virus was detected by molecular methods in a corn bunting and several red-legged ...partridges in Portugal. Sequencing revealed high similarity between the 2021 strains from Portugal and the 2010 strains from Spain.
•SVC-onGoing is the first on-going competition for on-line signature verification.•Researchers can easily benchmark their systems using public databases and platform.•Fair comparison of the state of ...the art: traditional vs deep learning approaches.•Analysis of popular scenarios (office/mobile) and writing inputs (stylus/finger).•Analysis of multiple types of attacks.
This article presents SVC-onGoing11https://competitions.codalab.org/competitions/27295., an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB22https://github.com/BiDAlab/DeepSignDB. and SVC2021_EvalDB33https://github.com/BiDAlab/SVC2021_EvalDB., and standard experimental protocols. SVC-onGoing is based on the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021), which has been extended to allow participants anytime. The goal of SVC-onGoing is to evaluate the limits of on-line signature verification systems on popular scenarios (office/mobile) and writing inputs (stylus/finger) through large-scale public databases. Three different tasks are considered in the competition, simulating realistic scenarios as both random and skilled forgeries are simultaneously considered on each task. The results obtained in SVC-onGoing prove the high potential of deep learning methods in comparison with traditional methods. In particular, the best signature verification system has obtained Equal Error Rate (EER) values of 3.33% (Task 1), 7.41% (Task 2), and 6.04% (Task 3). Future studies in the field should be oriented to improve the performance of signature verification systems on the challenging mobile scenarios of SVC-onGoing in which several mobile devices and the finger are used during the signature acquisition.