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Printed and flexible electronics promises smart devices for application domains, such as smart fast moving consumer goods and medical wearables, which are generally untouchable by conventional rigid silicon technologies. This is due to their remarkable properties such as flexibility, non-toxic materials, and having low-cost per area. Combined with neuromorphic computing, printed neuromorphic circuits pose an attractive solution for these application domains. Particularly, the additive printing technologies can reduce large amount of fabrication complexities and costs. On the one hand, high-throughput additive printing processes, such as roll-to-roll printing, can reduce the per-device fabrication time and cost. On the other hand, jet-printing can provide point-of-use customization at the expense of lower fabrication throughput. In this work, we propose a machine learning based design framework, that respects the objective and physical constraints of split additive manufacturing for printed neuromorphic circuits. With the proposed framework, multiple printed neural networks are trained jointly with the aim to sensibly combine multiple fabrication techniques (e.g., roll-to-roll and jet-printing). This should lead to a cost-effective fabrication of multiple different printed neuromorphic circuits and achieve high fabrication throughput, lower cost, and point-of-use customization.

The Stellar Abundances and Galactic Evolution Survey (SAGES) of the northern sky is a specifically-designed multi-band photometric survey aiming to provide reliable stellar parameters with accuracy comparable to those from low-resolution optical spectra. It was carried out with the 2.3-m Bok telescope of Steward Observatory and three other telescopes. The observations in the $u_s$ and $v_s$ passband produced over 36,092 frames of images in total, covering a sky area of $\sim9960$ degree$^2$. The median survey completeness of all observing fields for the two bands are of $u_{\rm s}=20.4$ mag and $v_s=20.3$ mag, respectively, while the limiting magnitudes with signal-to-noise ratio (S/N) of 100 are $u_s\sim17$ mag and $v_s\sim18$ mag, correspondingly. We combined our catalog with the data release 1 (DR1) of the first of Panoramic Survey Telescope And Rapid Response System (Pan-STARRS1, PS1) catalog, and obtained a total of 48,553,987 sources which have at least one photometric measurement in each of the SAGES $u_s$ and $v_s$ and PS1 $grizy$ passbands, which is the DR1 of SAGES and it will be released in our paper. We compare our $gri$ point-source photometry with those of PS1 and found an RMS scatter of $\sim2$% in difference of PS1 and SAGES for the same band. We estimated an internal photometric precision of SAGES to be on the order of $\sim1$%. Astrometric precision is better than $0^{\prime\prime}.2$ based on comparison with the DR1 of Gaia mission. In this paper, we also describe the final end-user database, and provide some science applications., Comment: 49 pages, 21 figures, 5 table, accepted for publication in ApJS

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky., Comment: 46 pages, submitted to SCMPA

With the rapid growth of the Internet of Things, smart fast-moving consumer products, and wearable devices, requirements such as flexibility, non-toxicity, and low cost are desperately required. However, these requirements are usually beyond the reach of conventional rigid silicon technologies. In this regard, printed electronics offers a promising alternative. Combined with neuromorphic computing, printed neuromorphic circuits offer not only the aforementioned properties, but also compensate for some of the weaknesses of printed electronics, such as manufacturing variations, low device count, and high latency. Generally, (printed) neuromorphic circuits express their functionality through printed resistor crossbars to emulate matrix multiplication, and nonlinear circuitry to express activation functions. The values of the former are usually learned, while the latter is designed beforehand and considered fixed in training for all tasks. The additive manufacturing feature of printed electronics allows the design of highly-bespoke designs. In the case of printed neuromorphic circuits, the circuit is optimized to a particular dataset. Moreover, we explore an approach to learn not only the values of the crossbar resistances, but also the parameterization of the nonlinear components for a bespoke implementation. While providing additional flexibility of the functionality to be expressed, this will also allow an increased robustness against printing variation. The experiments show that the accuracy and robustness of printed neuromorphic circuits can be improved by 26% and 75% respectively under 10% variation of circuit components.

To study the development and application of biological intelligence technology in computers and realize high-precision network anomaly detection, a distributed intrusion detection system based on agent biological intelligence technology is proposed. The intrusion detection model is implemented based on commonly used traditional machine learning methods. According to the detection index data, the detection effect of each algorithm is analyzed. With the support of the overall structure of the system, analyze the control center, network host, partition control center, and Agent library; adopt corresponding response strategies according to the response rules in the response library, and use the communication module to timely judge whether the intrusion behavior is abnormal, using S5720S-28P-SI -AC24-port full-gigabit three-layer network management enterprise-level network core switch for data exchange; select AD2032 type alarm responder, which can monitor foreign intrusion; through V1.2 green computer information detector, system memory and drive disk All-round evaluation; analyze the realization mode, communication message format and communication protocol of the subject communication, design the data movement process based on the agent; realize the intrusion detection model with the help of the commonly used traditional machine learning method. According to the detection index data, the detection effect of each algorithm is analyzed. The experimental results show that, for the IDA system, when the first five clients suffer intrusion behavior, its detection function can check the abnormal situation in time. When the detection time is in the 40s, the detection accuracy is 70%. When the last five clients suffered intrusion behavior, their detection function was not perfect. When the detection time was 25s, the accuracy no longer increased, and the detection accuracy remained at 40% until 40s. When the first five clients of the Agent-based system suffer from intrusion, the detection accuracy is always high, up to 99%. When the last five clients suffer from intrusion, the detection accuracy can reach 95%. Therefore, the detection accuracy of this system is high. It is proved that the system has obvious advantages in terms of accuracy, which successfully proves that it can effectively solve the problem of network anomaly detection

The Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect is a net torque caused by solar radiation directly reflected and thermally re-emitted from the surface of small asteroids and is considered to be crucial in their dynamical evolution. By long-term photometric observations of selected near-Earth asteroids, it's hoped to enlarge asteroid samples with a detected YORP effect to facilitate the development of a theoretical framework. Archived light-curve data are collected and photometric observations are made for (1685) Toro and (85989) 1999 JD6, which enables measurement of their YORP effect by inverting the light curve to fit observations from a convex shape model. For (1685) Toro, a YORP acceleration $\upsilon=(3.2\pm0.3)\times10^{-9}\ \rm{rad\cdot d^{-2}}(1\sigma\ error)$ is updated, which is consistent with previous YORP detection based on different light-curve data; for (85989) 1999 JD6, it is determined that the sidereal period is $7.667749\pm 0.000009$ h, the rotation pole direction locates is at $\lambda=232\pm 2^{\circ},\ \beta = -59\pm 1^{\circ}$, the acceleration is detected to be $\upsilon = (2.4\pm0.3)\times10^{-8}\ \rm{rad\cdot d^{-2}}(1\sigma\ error)$ and in addition to obtaining an excellent agreement between the observations and model. YORP should produce both spin-up and spin-down cases. However, including (85989) 1999 JD6, the $\rm{d}\omega/\rm{d}t$ values of eleven near-Earth asteroids are positive totally, which suggests that there is either a bias in the sample of YORP detections or a real feature needs to be explained., Comment: 21 pages, 10 figures

Die Signalrekonstruktion ist immer ein wichtiges Thema, wobei das Kalman-Filter eine am weitesten verbreitete Methode ist. Aber wenn es viele Zustandsgrößen gibt, brauchen wir viele Messungen. Das Compressive-Sensing (CS) ist in letzter Zeit ein sehr beliebtes Thema. Man kann mit dem Compressive-Sensing ein Signal mit sehr wenigen Messungen zu rekonstruieren, aber das Compressive-Sensing hat viele Einschränkungen. Daher kombiniert diese Arbeit das Kalman-Filter und das Compressive-Sensing, um die Anzahl der benötigten Messungen zur Zustands-schätzung zu reduzieren. Erstens schlägt diese Arbeit drei Methoden vor, um die Anforderungen von dem Compressive-Sensing abzuschwächen: dünnbesetzte Änderung, Dimensionreduzierung und Sparse-Coding-Representation. Außerdem schlägt diese Arbeit zwei Methoden zur Fusion der Informationen aus dem Kalman-Filter und dem Compressive-Sensing vor: durch die Kalman-Gleichung und durch die Pseudo-Messungen. Darüber hinaus schlägt diese Arbeit ein iteratives Verfahren zur Verbesserung der Schätzung. Im idealen Fall kann die Schätzung mit dem neuen Verfahren im Vergleich zum traditionellen Kalman-Filter um 70 Prozent verbessert werden. Dann wendet diese Arbeit das Verfahren auf rauschbehaftete und zweidimensionale Signale an und stellt fest, dass das Verfahren die Schätzung im Vergleich zum traditionellen Kalman-Filter um 25 Prozent verbessert. Schließlich analysiert diese Arbeit den Zusammenhang zwischen Fehler und Systemrauschen sowie Messunsicherheiten und kommt zu dem Schluss, dass das Verfahren bei guter Modellierung und schlechten Sensoren deutlich gute Ergebnisse liefert.

With the help of an automatic servo-controlled triaxial rock creep system, typical whole process rheological curve is obtained through laboratory experiment on the surrounding diorite rock of a large underground water-sealed cavern project. Creep experiments show that diorite exhibits obvious creep behaviour under the high in situ stress. Based on the experiment results, this article studies the creep behaviour under different stress levels, analyses the creep failure mode and mechanism, and obtains the triaxial creep properties of diorite. Using a three-dimensional nonlinear numerical method and the modified hydro-mechanical coupled Cvisc creep model, creep behaviour of the surrounding rock during the long-term operation is simulated and time-dependent stability is analysed. The results indicate that creep deformation is evident, and local stress concentration is relieved due to stress redistribution. After a period of time, the creep rate becomes stable and the deformation is stabilised. Because of its ...

Introduction The aim of this study was to investigate the roles of connective tissue growth factor (CTGF) in the development of anastomotic strictures after surgical repair of the esophagus. Material and methods Tissues collected from the patients were divided into three groups based on the results of endoscopy and clinical grading. Patients without dysphagia after esophagectomy were used as the control population. The protein levels of CTGF, TGF-β1, Smad2, and Smad4 were determined by immunohistochemistry (IHC) and western blot analyses, while the mRNA levels of the two growth factors were evaluated by real-time polymerase chain reaction. Results Compared with the control group, significantly increased (p < 0.01) levels of CTGF and TGF-β1 protein were observed in the anastomotic stenosis (AS) group, and levels of the two proteins detected by the IHC and western blot analyses were also significantly increased with the increasing severity of stenosis (p < 0.05). The mRNA levels of CTGF and TGF-β1 in the tissues collected from the patients with stenosis were significantly up-regulated (p < 0.05) as compared with those from the control group. In addition, the levels of Smad2 and Smad4 protein were also significantly increased (p < 0.05) with the increasing severity of stenosis, and the protein levels were positively correlated with the levels of CTGF (r = 0.59, p < 0.05) and TGF-β1 (r = 0.63, p < 0.05). Conclusions Inhibition of CTGF protein or mRNA expression may be a distinctive and effective therapy for the treatment of postoperative anastomotic strictures.

Multisensor integration systems are used to fulfill the increasing requirements on the complexity and accuracy of coordinate metrology. This thesis investigates on the achievement of multisensor integration in coordinate metrology from two main parts: function and data modeling; and discrete geometry processing. Function and data modeling allow obtaining clear understanding of the system and guiding the system development. Hierarchical function models of the system are built using IDEF0 methodology. An ontology based method is employed to model the various data and their relationships in the system with structured representation. Efficient methods for discrete geometry processing to support multisensor integration are the main focus of this dissertation. Reliable estimation of the curvatures is essential for discrete shapes processing. A tensor based method is proposed for discrete curvature estimation. The proposed method provides better performance according to a comparative analysis. Registration is one of the most important and decisive steps of multisensor integration. Registration algorithms enable to align the different point data captured in the respective sensor's coordinate systems. A registration method is proposed to align different discrete shapes with unknown correspondences. A combination of curvature information and Euclidean distance is used to improve the registration performance. A new method is developed for shape recognition and segmentation based on shape index and curvedness. The local surface type of a vertex is recognized according to its shape index and curvedness. The vertices are then clustered according to their local surfaces. A connected region generation algorithm is then implemented to generate the segmentation results. Considerable cases are tested and the method provides satisfying results. A new software framework DSP-COMS is developed as the testing platform of the developed methods. A detailed case study of an industrial workpiece digitized by laser scanning and touch probing is presented. The measured point data are then processed using DSP-COMS. The results show that the proposed methods can provide satisfying results for the studied case., L'intégration de systèmes multi-capteurs est la réponse la plus adaptée aux besoins croissants en matière de complexité et d'exactitude de mesures en métrologie par coordonnées. Cette thèse a pour objectif l'intégration de systèmes multi-capteurs en métrologie par coordonnées selon deux aspects: la modélisation des fonctions et des données; et le traitement de la géométrie discrète. La modélisation des fonctions et des données permet une meilleure compréhension des exigences des fonctions du système et des spécifications des données pour l'intégration de systèmes multi-capteurs. Des modèles hiérarchiques fonctionnels du système sont construits en utilisant la méthodologie IDEF0. Une démarche à base d'ontologies est utilisée pour modéliser les différentes données et de leurs relations par leur représentation structurée. Des méthodes efficaces et robustes pour le traitement de la géométrie discrète dans le cadre de l'intégration multi-capteurs sont l'objet principal de cette thèse à travers le développement de méthodes robustes. Une méthode basée sur le tenseur de courbure est utilisée pour l'estimation des courbures discrètes. Une analyse comparative montre que la méthode proposée fournit de meilleures performances par rapport à d'autres méthodes existantes. Le recalage est l'une des étapes les plus importantes de l'intégration multi-capteurs. Les algorithmes de recalage permettent de recaler les ensembles de points mesurés issus de différents capteurs ou de plusieurs vues. Une méthode de recalage sans correspondance connue est proposée dans cette thèse. Une combinaison de la courbure et de la distance euclidienne est utilisée pour améliorer les performances de l'algorithme classique de recalage ICP. Une nouvelle méthode basée sur l'indice de forme (shape index) et ll'intensité de courbure (curvedness) est développée pour la reconnaissance et la segmentation des formes discrètes. Le type de surface locale d'un sommet est reconnu par l'intermédiaire de son indice de forme. Les sommets sont ensuite groupés en fonction de leurs surfaces locales. Un algorithme de connexité par région est mis en œuvre pour produire les résultats de segmentation. Plusieurs exemples ont été testés et la méthode proposée fournit des résultats satisfaisants. Ces différentes méthodes de traitement géométriques ont été implémentés dans un nouveau système informatisé appelé DSP-COMS. Une étude de cas détaillée d'une pièce industrielle numérisée par laser scanning et par palpage est présentée dans cette thèse. Les points mesurés sont ensuite traités dans DSP-COMS. Les résultats obtenus montrent bien la robustesse des méthodes développés dans cette thèse.

Signal demodulation is a key technique for the fiber grating sensor. A new fiber Bragg grating dynamic signal demodulation method based on work-point controlling is present in the paper. The operation principle of the new method and the signal processing scheme of the work-point controlling are expounded systematically. The experiment measurement device is built using the tunable narrow-band laser, which has achieved signal demodulation with high precision. The influence of temperature drift on the measurement results is eliminated with work-point controlling scheme and the ability of dynamic signal detection capability of the fiber grating is greatly improved.

A simulator for studying jammerpsilas disturbance to passive broadband sonar is introduced. Its architecture is described. The architecture consists of four stages: signal generation, conventional beamforming, beam power accumulation and bearing time history display. Basic design decisions of each stage are discussed in detail. An example is then given to demonstrate the simulatorpsilas function. Finally, concluding remarks are also given.

A brain-computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In this paper, we used a new method: relative wavelet energy (RWE) for feature selection in BCI design. Linear discriminant analysis (LDA) and support vector machine (SVM) were utilized to classify the pattern of left and right hand movement imagery. Its performance was evaluated by mutual information (MI) using the data set III of BCI competition 2003. From the results of the experiment, we can get that RWE is a very good method for feature selection in BCI research and there is not much difference between LDA and SVM.

The critical issues in brain-computer interface (BCI) research is how to translate a person's intention into brain signals for controlling computer program or wheelchair. In this paper, we used a new method: relative wavelet energy (RWE) for feature selection in BCIs design and linear discriminant analysis (LDA) and support vector machine (SVM) were utilized to classify the pattern of left and right hand movement imagery. Its performance was evaluated by mutual information (MI) using the data set Mb of BCI Competition III. This technology provides another useful way to EEG feature selection in BCIs research.