Detect-and-forward relaying aided cooperative spatial modulation for wireless networks

A novel detect-and-forward (DeF) relaying aided cooperative SM scheme is proposed, which is capable of striking a flexible tradeoff in terms of the achievable bit error ratio (BER), complexity and unequal error protection (UEP). More specifically, SM is invoked at the source node (SN) and the information bit stream is divided into two different sets: the antenna index-bits (AI-bits) as well as the amplitude and phase modulation-bits (APM-bits). By exploiting the different importance of the AI-bits and the APM-bits in SM detection, we propose three low-complexity, yet powerful relay protocols, namely the partial, the hybrid and the hierarchical modulation (HM) based DeF relaying schemes. These schemes determine the most appropriate number of bits to be re-modulated by carefully considering their potential benefits and then assigning a specific modulation scheme for relaying the message. As a further benefit, the employment of multiple radio frequency (RF) chains and the requirement of tight inter-relay synchronization (IRS) can be avoided. Moreover, by exploiting the benefits of our low-complexity relaying protocols and our inter-element interference (IEI) model, a low-complexity maximum-likelihood (ML) detector is proposed for jointly detecting the signal received both via the source-destination (SD) and relay-destination (RD) links. Additionally, an upper bound of the BER is derived for our DeF-SM scheme. Our numerical results show that the bound is asymptotically tight in the high-SNR region and the proposed schemes provide beneficial system performance improvements compared to the conventional MIMO schemes in an identical cooperative scenario.<br/

Open World Object Detection Combining Graph-FPN and Robust Optimization

Open world object detection (OWOD) requires detecting all known and unknown object categories in the image, and the model must gradually learn new categories to adaptively update knowledge. Aiming at the problems of low recall rate of unknown objects and catastrophic forgetting of incremental learning in ORE (open world object detection) method, this paper proposes adjustable robust optimization of ORE based on graph feature pyramid (GARO-ORE). Firstly, using the superpixel image structure in Graph-FPN and the hierarchical design of context layer and hierarchical layer, rich semantic information can be obtained and the model can accurately locate unknown object. Then, using the robust optimization method to comprehensively consider the uncertainty, a base class learning strategy based on flat minimum is proposed, which greatly ensures that the model avoids forgetting the previously learnt category knowledge while learning new categories. Finally, the classification weights initiali-zation method based on knowledge transfer is used to improve the adaptability of the model to new classes. Experimental results on the OWOD dataset show that GARO-ORE achieves better detection results on the recall rate of unknown categories. In the three types of incremental object detection tasks of 10 + 10, 15 + 5, and 19 + 1, the mAP is increased by 1.38, 1.42 and 1.44 percentage points, respectively. It can be seen that GARO-ORE can improve the recall rate of unknown object detection, and promote the learning of subsequent tasks while effectively alleviating the catastrophic forgetting problem of old tasks

Epileptiform response of CA1 neurones to convulsant stimulation by cyclothiazide, kainic acid and pentylenetetrazol in anaesthetized rats

AbstractWe have previously reported that cyclothiazide (CTZ) evokes epileptiform activities in hippocampal neurons and induces seizure behavior. Here we further studied in vivo the sensitivity of the hippocampal CA1 neurons in response to CTZ in epileptogenesis in comparison with two other classic convulsants of kainic acid (KA) and pentylenetetrazol (PTZ).CTZ administered intracerebral ventricle (i.c.v.) induced epileptiform activities from an initial of multiple evoked population spikes, progressed to spontaneous spikes and finally to highly synchronized burst activities in hippocampal CA1 neurons. PTZ, when given by subcutaneously, but not by intracerebral ventricle injection, evoked similar progressive epileptiform activities. In contrast, KA given by i.c.v. induced a quick development of epileptiform burst activities and then shortly switched to continuous high frequency firing as acute status epilepticus (ASE). Pharmacologically, alprazolam, a high-potency benzodiazepine ligand, inhibited CTZ and PTZ, but not KA, induced epileptiform burst activities while GYKI 53784, an AMPA receptor antagonist, suppressed CTZ and KA but not PTZ evoked epileptiform activities.In conclusion, CTZ and PTZ induced epileptiform activities are most likely to share a similar progressive pattern in hippocampus with GABAergic mechanism dominant in epileptogenesis, while CTZ model involves additional glutamate receptor activation. KA induced seizure in hippocampus is different to that of both CTA and PTZ. The results from this study indicate that hippocampal neurons respond to various convulsant stimulation differently which may reflect the complicated causes of the seizure in clinics

Revisiting the application of molecular probe diagnostics on quantifying aqueous OH radicals in plasma–liquid systems

AbstractWe revisit one of the most used techniques for quantifying the aqueous OH radicals (OHaq) in plasma–liquid systems, the molecular probe method which obtains the [OHaq] by measuring a stable material formed through a rapid reaction between the molecular probe and the OHaq. In this study, we used disodium terephthalate (NaTA) as the molecular probe; the experimental results with a theoretical analysis suggest that to obtain the correct OHaq concentration, the concentration of the molecular probe should be greater than a certain value, which depends on the types of the plasma–liquid systems. However, this is not the case in most of the existing reports in which the NaTA is often much less than the requisite value.</jats:p

Automatic classification method of coal mine safety hidden danger informatio

Manual classification method is difficult to meet classification requirements of massive coal mine safety hidden danger information, and automatic text classification method based on probability statistics has low classification accuracy rate. In view of the above problems, an automatic classification method of coal mine safety hidden danger information was proposed which was based on Word2vec and convolutional neural network. Firstly, hidden danger information is pre-processed through word segmentation and stop word deletion. Then semantic similarity between words is represented by employing Word2vec. Finally, local context high-level features of hidden danger information are extracted by use of convolutional neural network, and Softmax classifier is used to realize automatic classification of hidden danger information. The experimental results show that the method realizes end-to-end automatic classification and can effectively improve accuracy and comprehensiveness of classification

A Compact Novel Slot-Loaded Dual-Frequency H-Shaped Antenna

A novel compact single-layer dual frequency microstrip antenna which uses an H-shaped geometry with two U-shaped slots embedded near the radiation edges, is presented. By changing the design parameters, the lower and higher resonant frequencies can be controlled easily, and a range of frequency ratios (1.716-2.363) can be obtained in this design. For the two operating frequencies of the proposed antenna, the same polarization planes and broadside radiation patterns are achieved. Compared to the regular dualfrequency patch antenna, this antenna can realize a significant size reductio

Adsorption Characteristics of Several Bioretention-Modified Fillers for Phosphorus

To optimize the bioretention mixed fillers with better removal of phosphorus, this paper studies the adsorption characteristics of single filler and modified mixed filler through static adsorption experiments, and adopts the dynamical mini-column experiments to examine the adsorption capacities of the soil and modified mixed fillers. Results show that, in the static adsorption experiments, both water treatment residual (WTR) and fly ash exhibit good adsorption capacity when used as a single filler and modifier. Adsorption capacity increases with increasing WTR and fly ash dosage in the mixed filler. The modified mixed filler with WTR exerts a clear effect in the dynamic adsorption experiment, which is unsaturated when influent phosphorus concentration is 1 mg/L and inflow amount is equivalent to 15 years of precipitation. The adsorption capacity of WTR is 3.5&ndash;4.5 times that of other mixed fillers. Fly ash as a modifier shows a poor dynamic adsorption effect and thus must be continuously studied. In this study, WTR is recommended as a bioretention phosphorus removal additive. In engineering applications, the amount of WTR added can be controlled within 5&ndash;10% (by mass) according to influent phosphorus concentration

Variability modeling of coal mine safety monitoring and control field

Traditional software development methods rarely can reuse accumulated development experiments when developed same system, and cause vast repetitive work. In view of the problem, development method of software product line was proposed and applied into the software development for coal mine safety monitoring and control system. On the basis of analysis of product line of the system, relationships among characteristics of the system were discussed according to commonality and variability characteristics of the system, variability model of the coal mine safety monitoring and control field based on feature modeling method of variability was built. The model can effectively manage variability of the system, and can quickly complete requirements analysis of specific customized monitoring and control system under guidance of the characteristics dependency rules at the same time, which lays foundation for following realization of reusable framework in the coal mine safety monitoring and control field

Study on the Thermal Conductivity Characteristics for Ultra-Thin Body FD SOI MOSFETs Based on Phonon Scattering Mechanisms

The silicon-on-insulator (SOI) metal-oxide-semiconductor field-effect transistors (MOSFETs) suffer intensive self-heating effects due to the reduced thermal conductivity of the silicon layer while the feature sizes of devices scale down to the nanometer regime. In this work, analytical models of thermal conductivity considering the self-heating effect (SHE) in ultra-thin body fully depleted (UTB-FD) SOI MOSFETs are presented to investigate the influences of impurity, free and bound electrons, and boundary reflection effects on heat diffusion mechanisms. The thermal conductivities of thin silicon films with different parameters, including temperature, depth, thickness and doping concentration, are discussed in detail. The results show that the thermal dissipation associated with the impurity, the free and bound electrons, and especially the boundary reflection effects varying with position due to phonon scattering, greatly suppressed the heat loss ability of the nanoscale ultra-thin silicon film. The predictive power of the thermal conductivity model is enhanced for devices with sub-10-nm thickness and a heavily doped silicon layer while considering the boundary scattering contribution. The absence of the impurity, the electron or the boundary scattering leads to the unreliability in the model prediction with a small coefficient of determination