The intermittency of solar energy resources has brought a big challenge for the optimization and planning of a future smart grid. To reduce the intermittency, an accurate prediction of photovoltaic ...(PV) power generation is very important. Therefore, this paper proposes a new forecasting method based on the recurrent neural network (RNN). At first, the entire solar power time series data is divided into inter-day data and intra-day data. Then, we apply RNN to discover the nonlinear features and invariant structures exhibited in the adjacent days and intra-day data. After that, a new point prediction model is proposed, only by taking the previous PV power data as input without weather information. The forecasting horizons are set from 15 to 90 min. The proposed forecasting method is tested by using real solar power in Flanders, Belgium. The classical persistence method (Persistence), back propagation neural network (BPNN), radial basis function (RBF) neural network and support vector machine (SVM), and long short-term memory (LSTM) networks are adopted as benchmarks. Extensive results show that the proposed forecasting method exhibits a good forecasting quality on very short-term forecasting, which demonstrates the feasibility and effectiveness of the proposed forecasting model.
The purpose of this study was to provide observational indicators for clinically predicting cardiovascular events in patients with diabetic nephropathy (DN) undergoing peritoneal dialysis by ...determining the effects of nuclear enriched abundant transcript 1 (NEAT1) levels on the cardiovascular events and prognosis in DN patients receiving continuous ambulatory peritoneal dialysis (CAPD). A retrospective analysis was conducted on the data of 80 DN patients undergoing CAPD. Patients were assigned to NEAT1 high expression group and NEAT1 low expression group. NEAT1 had a substantially increased expression in the serum of DN patients, and it could serve as a potential biomarker for predicting the development of DN. Patients with highly expressed NEAT1 had an higher level of high-sensitivity C-reactive protein (hs-CRP), larger cardiac structural parameters left ventricular end-diastolic diameter (LVED), left ventricular end-systolic diameter (LVESD), interventricular septal diameter (IVSD) and left ventricular posterior wall diameter (LVPWD), but a notably lower cardiac function evaluation indicator left ventricular ejection fraction (LVEF) than those with lowly expressed NEAT1. The coefficient (r) of correlation between NEAT1 and hs-CRP level was 0.3585 (P=0.0011). The incidence rates of acute myocardial infarction, congestive heart failure and angina in NEAT1 high expression group were higher than those in NEAT1 low expression group. Patients with NEAT1 high expression exhibited a higher mortality rate than NEAT1 low expression group. With the increase in NEAT1 levels, the level of hs-CRP rose in DN patients undergoing CAPD. A higher expression level of NEAT1 indicates poorer cardiac function, higher incidence rates of cardiovascular adverse events and a poorer prognosis in diabetics undergoing CAPD.
The conventional two-way relaying (TWR) protocol requires that the transmitter (receiver) in one direction must be the receiver (transmitter) in the other direction, a limitation precluding the ...application of the TWR for sophisticated real-world wireless networks. In this paper, we study a more general multicell system consisting of a downlink (DL) traffic in one cell and an uplink (UL) traffic in an adjacent cell, with a multiantenna relay located in the cell edge and shared by both cells. For the coexistence of DL and UL transmissions, we propose exploiting the overheard signals from the adjacent cell (commonly known as the intercell interference) to improve the quality of signal reception in both cells. To reduce the power consumption to suit for green networks, we design the optimum relay precoder to minimize the total power at the relay yet satisfying the rate constraints for both the DL and UL traffic flows. The original precoder design is a nonconvex problem that is difficult to solve. To make the problem tractable, we transform the nonconvex problem to an equivalent quadratically constrained quadratic program (QCQP), which is then solved by the semidefinite relaxation (SDR) technique. Finally, simulations validate the effectiveness of our proposed protocol together with the optimized relay precoder.
Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-β (Aβ) and human islet ...amyloid polypeptide (hIAPP), respectively. The co-aggregation of the two amyloid proteins is regarded as the fundamental molecular mechanism underlying their pathological association. The green tea extract epigallocatechin-3-gallate (EGCG) has been extensively demonstrated to inhibit the amyloid aggregation of Aβ and hIAPP proteins. However, its potential role in amyloid co-aggregation has not been thoroughly investigated. In this study, we employed the enhanced-sampling replica exchange molecular dynamics simulation (REMD) method to investigate the effect of EGCG on the co-aggregation of Aβ and hIAPP. We found that EGCG molecules substantially diminish the β-sheet structures within the amyloid core regions of Aβ and hIAPP in their co-aggregates. Through hydrogen-bond, π-π and cation-π interactions targeting polar and aromatic residues of Aβ and hIAPP, EGCG effectively attenuates both inter-chain and intra-chain interactions within the co-aggregates. All these findings indicated that EGCG can effectively inhibit the co-aggregation of Aβ and hIAPP. Our study expands the potential applications of EGCG as an anti-amyloidosis agent and provides therapeutic options for the pathological association of amyloid misfolding disorders.
Signal features can be obscured in noisy environments, resulting in low accuracy of radar emitter signal recognition based on traditional methods. To improve the ability of learning features from ...noisy signals, a new radar emitter signal recognition method based on one-dimensional (1D) deep residual shrinkage network (DRSN) is proposed, which offers the following advantages: (i) Unimportant features are eliminated using the soft thresholding function, and the thresholds are automatically set based on the attention mechanism; (ii) without any professional knowledge of signal processing or dimension conversion of data, the 1D DRSN can automatically learn the features characterizing the signal directly from the 1D data and achieve a high recognition rate for noisy signals. The effectiveness of the 1D DRSN was experimentally verified under different types of noise. In addition, comparison with other deep learning methods revealed the superior performance of the DRSN. Last, the mechanism of eliminating redundant features using the soft thresholding function was analyzed.
In this paper, we study a two-phase underlay cognitive relay network, where there exists an eavesdropper who can overhear the message. The secure data transmission from the secondary source to ...secondary destination is assisted by two decode-and-forward (DF) relays. Although the traditional opportunistic relaying technique can choose one relay to provide the best secure performance, it needs to continuously have the channel state information (CSI) of both relays, and may result in a high relay switching rate. To overcome these limitations, a secure switch-and-stay combining (SSSC) protocol is proposed where only one out of the two relays is activated to assist the secure data transmission, and the secure relay switching occurs when the relay cannot support the secure communication any longer. This security switching is assisted by either instantaneous or statistical eavesdropping CSI. For these two cases, we study the system secure performance of SSSC protocol, by deriving the analytical secrecy outage probability as well as an asymptotic expression for the high main-to-eavesdropper ratio (MER) region. We show that SSSC can substantially reduce the system complexity while achieving or approaching the full diversity order of opportunistic relaying in the presence of the instantaneous or statistical eavesdropping CSI.
The data center network (DCN), wired or wireless, features large amounts of many-to-one (M2O) sessions. Each M2O session is currently established using point-to-point (P2P) communications and ...store-and-forward (SAF) relays, and is generally followed by a certain computation at the destination, typically a weighted summation of the received information digits. Fundamentally different from this separate P2P/SAF-based-transmission and computation framework, this paper proposes simultaneous transmission and air computation (STAC), a novel physical layer scheme that achieves STAC in wireless DCNs. In particular, STAC builds on a number of distinguishing characteristics of DCs to take advantage of the superposition nature of electromagnetic signals. With STAC, multiple sources transmit in the same time slot with appropriately chosen parameters, such that the superimposed signal can be directly transformed to the desired summation at the receiver. To enable STAC, we propose an enhanced software-defined network architecture, where a wired low-bandwidth backbone provides wireless transceivers with external reference signals. We also discuss some new challenges that STAC brings to scheduling and routing. Theoretical analysis and simulation results show that STAC can significantly improve both bandwidth and energy efficiency in DCNs.
Energy efficiency is a key issue in wireless body area networks (WBANs). A number of transmission power control (TPC) schemes have been developed to improve the efficiency of transmission, which is ...one of the most energy consuming operations in WBAN. To save energy, these schemes only probe the link quality from the received data packets. However, due to large intervals between data packets and fast dynamic on-body link characteristics in WBAN, the obtained link information is usually outdated. In this case, the performance of the current TPC scheme is poor. This paper proposes an accelerometer-assisted TPC (AA-TPC) scheme, which exploits the periodic fluctuations of link qualities to improve the transmission energy efficiency. Consider the relationship between link quality and body movement, AA-TPC makes transmissions at ideal channel points that are identified by using the local accelerometer. We first conduct experiments to investigate the correlation between periodic movements and link quality. Then, we propose an algorithm to locate the time point in each period with the best link quality to transmit packets. The specific transmission power is then determined by the feedback information from the receiver. Finally, we evaluate the energy efficiency of AA-TPC based on a CC2420 platform in both a periodic scenario (without any aperiodic movement to break the periodicity) and a realistic scenario (which has aperiodic movements 20% of the time). The results show that about 26.4% and 18% of total energy consumption can be saved on average in the periodic and realistic scenarios, respectively.
Rationale: The clinical manifestations of Fabry disease affect the nerves, kidneys, heart, skin, gastrointestinal tract and eyes. Our aim is to familiarize people with the FD diagnostic process by ...reporting this case. Patient concerns: A 79-year-old-male patient presented with muscle pain and weakness in the extremities, also with an increasing erythrocyte sedimentation rate and C-reactive protein. Further examinations revealed that multiple organ involvement, such as rash, myocardial hypertrophy, peripheral neuropathy. Diagnoses: Cardiac MR demonstrated hypertrophic cardiomyopathy, myocardial fibrosis and low myocardial T1 value. The patient was eventually diagnosed with Fabry disease through proteomics and genetic testing. Interventions: The treatment is enzyme replacement therapy (ERT). But this patient could not afford ERT and was given only general symptomatic treatment, pregabalin, and a gradual reduction in glucocorticoid. Outcomes: The patient’s symptoms of joint pain and muscle weakness reduced significantly, and ESR and CRP had decreased to normal. Lessons: FD is a rare disease and difficult to diagnose, but rare does not mean invisible. FD may present with signs and symptoms of rheumatic diseases. Rheumatologists should be aware and concerned about this disease.
Traditional centralized commerce on the Internet relies on trusted third parties to process electronic payments. It suffers from the weakness of the trust-based model. A pure decentralized mechanism ...called blockchain tackles the above problem and has become a hot research area. However, since each node in a blockchain system needs to store all transactions of the other nodes, as time continues, the storage room required to store the entire blockchain will be huge. Therefore, the current storage mechanism needs to be revised to cater to the rapidly increasing need for storage. Network coded (NC) distributed storage (DS) can significantly reduce the required storage room. This paper proposes a NC-DS framework to store the blockchain and proposes corresponding solutions to apply the NC-DS to the blockchain systems. Analysis shows that the proposed scheme achieves significant improvement in saving storage room.
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