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Le caspasi, una famiglia di proteasi della cisteina, sono i principali mediatori dell'apoptosi e dell'infiammazione. La caspasi-6 è classificata come effettore apoptotico e media il restringimento nucleare durante l'apoptosi, ma possiede meccanismi di attivazione e regolazione unici che differiscono da quelli di altre caspasi effettrici. Inoltre, crescenti prove hanno dimostrato che la caspasi-6 è...
Evaporation duct is an anomalous atmospheric surface layer over the sea surface and has severe influence on the microwave propagation. The evaporation duct height, which implies the strength of the evaporation duct, is an important physical quantity. Based on National Centers for Environmental Prediction Climate Forecast System Reanalysis data and the evaporation duct model, high spatial resolution...
This paper presents the theory of passive localization for underwater sources based on multipath arrival structures. The principles of channel modelling in Ray-theory, determination of eigenrays which connect source and receiver, the information of source range and source depth is included primarily in arrival angles and time delays. The weighted-subspace-fitting (WSF) technique is used to minimize...
This paper describes the principle and composition of an acoustic simulation system which processes functional and accurate calibration of broadband ADCPs. The simulation system simulates backscatter signal that an ADCP would receive, reloads backscatter signal to ADCP by a transducer array docked with the ADCP transducer through coupling medium. According to the profiling range and current velocity...
Evaporation duct has strong impacts on the performance of marine radar and communication systems. Evaporation duct channel is a promising channel for marine high capacity data transmission. Wave propagation models and evaporation duct models are well studied, and statistical features of duct channel has been observed. However, the work on the physical model of small-scale characteristics of evaporation...
Data retrieval serves a critical role in the development of multimedia applications. However, due to the exponential growth of multimedia data, high-speed and efficient indexing is becoming more and more difficult than ever. In this paper, we propose a novel approach to speed up the retrieval process by adopting a distributed computing paradigm through the Apache Spark framework. Utilizing search...
Automatically generating images from text by using generative adversarial networks (GANs) has been actively investigated. To the best of our knowledge, there is no method of generating images with consideration of the given text and its context; therefore, representing a story describing a series of related actions is insufficient for applications such as generating image sequences. In this paper,...
A compact narrow-band low temperature co-fíred ceramic (LTCC) filter with a fractional bandwidth of 3% is proposed. The proposed filter consists of five cascaded half-wavelength resonators vertically arrayed on each LTCC layer. End-coupling between adjacent resonators is precisely controlled by rectangle-shaped slot on intermediate ground layer. The overall size of the filter is only 8 × 6 × 0.89...
This paper presents a novel local posture orientation-context descriptor, and proposes a FDDL(Fisher discriminant dictionary learning) method based on local orientation-preserving(LOP-FDDL) for sparse coding in action recognition task. To take full use of the information about the position of the local body-part related to the center of the torso, ant the spatial-temporal shape changes of the human...
Clustering cancer patients into subgroups and identifying cancer subtypes is an important task in cancer genomics. Clustering based on comprehensive multi-omic molecular profiling can often achieve better results than those using a single data type, since each omic data type may contain complementary information. However, it is challenging to integrate heterogeneous omic data directly. Based on one...
Stroke is a leading cause of long-term adult disability. Stroke patients can recover through rehabilitation programs prescribed by occupational therapists (OT); however, an individualized rehabilitation program can reduce recovery times compared to traditional ones. In this paper, we propose a daily activity observation system (DAOS) that uses a Kinect v2 sensor to collect and retrieve motion data...
This paper considers the application of finite-time control to a Cucker-Smale flocking model of autonomous agents with collision avoidance. A mathematical expression for the upper bound on the flocking time is derived. Previous results without considering collision avoidance showed that the flocking time decreases as the number of robots in the flock increases, which is counter-intuitive. We showed...
The forthcoming fifth generation (5G) wireless network is envisioned as highly heterogeneous that can support future applications demanding seamless coverage, low latency and high throughput. These requirements pose stringent challenges on the handover authentication design. In this article, we present a fast and efficient physical layer authentication scheme for software-defined-radio (SDN) enabled...
In this work, we propose a novel adaptive control on digital Doherty Power Amplifier (DPA) for efficiency and gain enhancement. Unlike traditional DPA design, we propose Simultaneously Perturbated Stochastic Approximation (SPSA) optimization algorithm by considering phase difference, power distribution and gate voltage parameters of main and peak amplifiers in order to achieve optimal performance...
Financial time series prediction is remains a challenge, due to the nonstationary and fuzziness financial data. In this paper, we propose and achieve a hybrid financial time series model by combining the Maximum Entropy (ME), Support Vector Regression (SVR) and Trend model based on Artificial neural networks (ANNs) for forecasting financial time series. The method contains three steps. The first step...
In recent years, predicting future hot events in online social networks is becoming increasingly meaningful in marketing, advertisement, and recommendation systems to support companies' strategy making. Currently, most prediction models require long-term observations over the event or depend a lot on other features which are expensive to extract. However, at the early stage of an event, the temporal...
Multi-view graph embedding and hub detection have both become widely studied problems in the area of graph learning. Both graph embedding and hub detection relate to the node clustering structure of graphs. The multi-view graph embedding usually implies the node clustering structure of the graph based on the multiple views, while hubs are the boundary-spanning nodes across different node clusters...
Predicting patients' risk of developing certain diseases is an important research topic in healthcare. Personalized predictive modeling, which focuses on building specific models for individual patients, has shown its advantages on utilizing heterogeneous health data compared to global models trained on the entire population. Personalized predictive models use information from similar patient cohorts,...
Integrated modular avionics (IMA) is one of the most significant systems which can affect the performance of civil aircraft. The structure of IMA is an open standard platform, on which amount of functionalities are hosted. This structure makes avionics more flexible and more powerful, while it makes avionics more complexity and more critical. For improving the safety and reliability of aircraft, a...
Many applications demand proper design and implementation of 0-1 binary compressive sensing (CS) measurement matrices. This paper presents a construction method for such binary CS measurement matrices by training a convolutional neural network (CNN) with 0-1 weights. The desired CS performance of resultant binary measurement matrices can be achieved by designing a proper CNN training procedure. For...
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