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Osteoarthritis (OA) is the most common form of arthritis. According to the evidence presented on both sides of the knee bones, radiologists assess the severity of OA based on the Kellgren–Lawrence (KL) grading system. Recently, computer-aided methods are proposed to improve the efficiency of OA diagnosis. However, the human interventions required by previous semiautomatic segmentation methods limit the application on large-scale datasets. Moreover, well-known CNN architectures applied to the OA severity assessment do not explore the relations between different local regions. In this work, by integrating the object detection model, YOLO, with the visual transformer into the diagnosis procedure, we reduce human intervention and provide an end-to-end approach to automatic osteoarthritis diagnosis. Our approach correctly segments 95.57% of data at the expense of training on 200 annotated images on a large dataset that contains more than 4500 samples. Furthermore, our classification result improves the accuracy by 2.5% compared to the traditional CNN architectures.

ln this paper, a distributed beamforming algorithm is proposed for downlink multicell network when the intra-cell local channel state informations (CSIs) are available at each base station (BS). The proposed algorithm includes three parts, firstly, an algorithm is proposed to estimate the direction vectors of the inter-cell local channels. The algorithm above utilizes a set of random orthogonal bases and the known training formula to get all basis vectors of orthogonal complement space of the inter-cell local channel vector. Secondly, a proposition based on singular value decomposition of all local channel vectors is presented for the distributed beamforming causing minimum intra-cell interference (InCI) and inter-cell interference (ICI) toward other users. Thirdly, with only intra-cell local CSIs at BS, a training algorithm is proposed to obtain the amplitudes of the whole local channel vectors. This training algorithm exploits the unit matrix and unit transmit power to perform fixed steps of training process, and the amplitude of inter-cell local channel vector is estimated by the observations of BS or user. Finally, simulation results demonstrate that the proposed algorithm can achieve higher user rate while offering more advantages to suppress InCI and ICI than the traditional ones.

To support the multicast and unicast services in the orthogonal frequency division multiplexing system simultaneously, a channel-aware adaptive resource allocation algorithm is proposed to maximise the total throughput of the unicast service while guaranteeing the required quality of service (QoS) for the multicast service. The two-step optimisation scheme is developed to solve the problem based on the perfect channel state information at the base station: first, subcarriers are allocated to the multicast and the unicast services under the assumption that power is divided equally to every subcarrier. Especially, the noisy chaotic neural network with a new parameter set is applied to allocate the subcarriers to the unicast service by elaborately constructing the energy function to fully exploit the multiuser diversity gain, the optimal solution is found successfully through its rich neurodynamics; Secondy, the power averagely allocated to the unicast service is reallocated quickly in a linear water-filling fashion. Compared with existing algorithms the proposed algorithm achieves higher spectrum efficiency and better bit-error rate for the multicast service, also higher throughput for the unicast service.

In this paper, an iterative algorithm for decentralized beamforming with internal penalty function is proposed. This algorithm utilizes the property that a stationary point corresponding to local maximum of the objective function is found when gradient is zero. The convergence of the proposed algorithm is proved. The simulation results show that the proposed algorithm is more robust against intra-cell and inter-cell interference than the traditional ones. Especially the proposed algorithm has higher rates as the number of users increases.

We propose two generalized block-diagonalization (BD) schemes for multiple-input multiple-output (MIMO) relay broadcasting systems with no channel state information (CSI) at base station. We first introduce a generalized zero forcing (ZF) scheme that reduces the complexity of the traditional BD scheme. Then the optimal power loading matrix for the proposed scheme is analyzed and the closed-form solution is derived. Furthermore, an enhanced scheme is proposed by employing the minimum-mean-squared-error (MMSE) criterion. Simulation results show that the proposed generalized MMSE scheme outperforms the other schemes and the optimal power loading scheme improves the sum-rate performance efficiently.

In this paper, new transmission schemes are proposed to deal with the CCI (co-channel interference) in wireless relay transmission. We first introduce an optimal decoding process to fully utilize the information forwarded by relay. Then based on conventional transmission schemes, two modified transmission schemes and a novel adaptive scheme are proposed. Furthermore, we derive the outage probabilities and throughput for all the proposed schemes in closed form. Numerical simulations are presented to validate the analytical results and it shows that the adaptive scheme improves the spectral efficiency significantly compared to others in most condition.

Intracellular free calcium ([Ca2+]i) has multiple functional roles in renal epithelia, including mediating ligand- and volume-activated K+ and Cl- channels, modulating the permeability of apical membrane to Na+, and regulating tubuloglomerular feedback. We investigated glucose effects on intracellular pH (pHi) and [Ca2+]i in Madin-Darby canine kidney (MDCK) cells using fluorescent probes, SNARF-1 and fura 2, respectively. The addition of glucose decreased both pHi and [Ca2+]i in a dose-dependent fashion. Thapsigargin (TG) and cyclopiazonic acid (CPA), well-known endoplasmic reticulum (ER) Ca(2+)-adenosinetriphosphatase (Ca(2+)-ATPase) inhibitors, abolished the glucose-induced [Ca2+]i decrease. Without glucose, 1 microM TG induced a sustained elevation in [Ca2+]i, which increased further with glucose addition, whereas 15 microM CPA induced a transient increase in [Ca2+]i that was not affected by further addition of glucose. The sustained elevation in [Ca2+]i induced by TG was dependent on extracellular Ca2+. TG-induced [Ca2+]i increase was modulated by glucose, i.e., at higher glucose concentrations, TG induced a larger and more rapid rise in [Ca2+]i. We conclude that glucose has dual effects on [Ca2+]i regulation. Glucose alone reduces [Ca2+]i by activating ER-type Ca(2+)-ATPase, since this phenomenon is TG and CPA sensitive. In the presence of TG, glucose increases [Ca2+]i probably by increasing Ca2+ entry. Our data suggest a model in which TG activates capacitative Ca2+ entry by depletion of the ER Ca2+ pool. Glucose increases TG-induced [Ca2+]i elevation by further enhancing capacitative Ca2+ entry.