Conditional bounds for small prime solutions of linear equations

Let a 1, a 2, a 3 be non-zero integers with gcd(a 1 a 2, a 3)=1 and let b be an arbitrary integer satisfying gcd (b, a i, a j) =1 for i≠j and b≡a 1+a 2+a 3 (mod 2). In a previous paper [3] which completely settled a problem of A. Baker, the 2nd and 3rd authors proved that if a 1, a 2, a 3 are not all of the same sign, then the equation a 1 p 1+a 2 p 2+a 3 p 3=b has a solution in primes p j satisfying {Mathematical expression} where A>0 is an absolute constant. In this paper, under the Generalized Riemann Hypothesis, the authors obtain a more precise bound for the solutions p j . In particular they obtain A0. An immediate consquence of the main result is that the Linnik's courtant is less than or equal to 2. © 1992 Springer-Verlag.postprin

Pairwise Confusion for Fine-Grained Visual Classification

Fine-Grained Visual Classification (FGVC) datasets contain small sample sizes, along with significant intra-class variation and inter-class similarity. While prior work has addressed intra-class variation using localization and segmentation techniques, inter-class similarity may also affect feature learning and reduce classification performance. In this work, we address this problem using a novel optimization procedure for the end-to-end neural network training on FGVC tasks. Our procedure, called Pairwise Confusion (PC) reduces overfitting by intentionally {introducing confusion} in the activations. With PC regularization, we obtain state-of-the-art performance on six of the most widely-used FGVC datasets and demonstrate improved localization ability. {PC} is easy to implement, does not need excessive hyperparameter tuning during training, and does not add significant overhead during test time.Comment: Camera-Ready version for ECCV 201

A Provable Semi-Outsourcing Privacy Preserving Scheme for Data Transmission From IoT Devices

A semi-outsourcing privacy-preserving scheme is proposed in this paper for the IoT data collection named semi-outsourcing privacy-preserving (SOPP), which supports delegated identity authentication for the IoT devices without revealing the transmitted data. Compared with other schemes that implement the authentication based upon using trusted cloud services, the design of our scheme SOPP can achieve the delegated authentication on untrusted public clouds while providing privacy-preserving data transmission. Meanwhile, the implemented one-way authentication can reduce the communication cost for the IoT devices (especially for the low-resource ones) to prolong their battery life. The performance of the SOPP scheme is demonstrated for its use in the resource-constrained IoT devices and compared with a benchmark trusted cloud scheme including one based upon certificates and an interactive (two-way) authentication scheme

Channel Prediction Using Ordinary Differential Equations for MIMO systems

Channel state information (CSI) estimation is part of the most fundamental problems in 5G wireless communication systems. In mobile scenarios, outdated CSI will have a serious negative impact on various adaptive transmission systems, resulting in system performance degradation. To obtain accurate CSI, it is crucial to predict CSI at future moments. In this paper, we propose an efficient channel prediction method in multiple-input multiple-output (MIMO) systems, which combines genetic programming (GP) with higher-order differential equation (HODE) modeling for prediction, named GPODE. In the first place, the variation of one-dimensional data is depicted by using higher-order differential, and the higher-order differential data is modeled by GP to obtain an explicit model. Then, a definite order condition is given for the modeling of HODE, and an effective prediction interval is given. In order to accommodate to the rapidly changing channel, the proposed method is improved by taking the rough prediction results of Autoregression (AR) model as a priori, i.e., Im-GPODE channel prediction method. Given the effective interval, an online framework is proposed for the prediction. To verify the validity of the proposed methods, We use the data generated by the Cluster Delay Line (CDL) channel model for validation. The results show that the proposed methods has higher accuracy than other traditional prediction methods

Sensitivity and Asymptotic Analysis of Inter-Cell Interference Against Pricing for Multi-Antenna Base Stations

We thoroughly investigate the downlink beamforming problem of a two-tier network in a reversed time-division duplex system, where the interference leakage from a tier-2 base station (BS) toward nearby uplink tier-1 BSs is controlled through pricing. We show that soft interference control through the pricing mechanism does not undermine the ability to regulate interference leakage while giving flexibility to sharing the spectrum. Then, we analyze and demonstrate how the interference leakage is related to the variations of both the interference prices and the power budget. Moreover, we derive a closed-form expression for the interference leakage in an asymptotic case, where both the charging BSs and the charged BS are equipped with a large number of antennas, which provides further insights into the lowest possible interference leakage that can be achieved by the pricing mechanism

Systemic lupus erythematosus (SLE) is associated with telomerase activation

published_or_final_versio

Learning to Construct Nested Polar Codes: An Attention-Based Set-to-Element Model

As capacity-achieving codes under successive cancellation (SC) decoding, nested polar codes have been adopted in 5G enhanced mobile broadband. To optimize the performance of the code construction under practical decoding, e.g. SC list (SCL) decoding, artificial intelligence based methods have been explored in the literature. However, the structure of nested polar codes has not been fully exploited for code construction. To address this issue, this letter transforms the original combinatorial optimization problem for the construction of nested polar codes into a policy optimization problem for sequential decision, and proposes an attention-based set-to-element model, which incorporates the nested structure into the policy design. Based on the proposed architecture for the policy, a gradient based algorithm for code construction and a divide-and-conquer strategy for parallel implementation are further developed. Simulation results demonstrate that the proposed construction outperforms the state-of-the-art nested polar codes for SCL decoding

High fundamental-repetition-rate bound solitons in carbon nanotube-based fiber lasers

© 2015 IEEE.We demonstrate bound solitons formation with a high fundamental-repetition-rate of 211.8 MHz from an all-fiber linear-configuration mode-locked laser incorporating a carbon-nanotube-based saturable absorber for the first time. By adjusting the polarization state of laser cavity, bound solitons exhibit a large change of pulse separation in a range of 3.5-73 times longer than the pulsewidth, while the phase difference of the tightly bound solitons switches between pm π 2. Numerical simulations confirm the experimental observations about the dependence of spectral profile of bound solitons on the pulse separation and the phase difference

Long-term survival after intraluminal brachytherapy for inoperable hilar cholangiocarcinoma: A case report

Surgical resection with a tumor-free margin is the only curative treatment for hilar cholangiocarcinoma (Klatskin tumor). However, over half of the patients present late with unresectable tumors. Radiotherapy using external beam irradiation or intraluminal brachytherapy (ILBT) has been used to treat unresectable hilar cholangiocarcinoma with satisfactory outcome. We reported a patent with unresectable hilar cholangiocarcinoma surviving more than 6 years after combined external beam irradiation and ILBT. © 2005 The WJG Press and Elsevier Inc. All rights reserved.published_or_final_versio