Epidemic encephalitis B is an acute infectious disease of the central nervous system caused by the encephalitis B virus, which is neurotropic in nature, with inflammation of the brain parenchyma as the main change. The disease is also called Japanese encephalitis because it was the first successful isolation of B encephalitis virus in Japan. The virus is transmitted between animal and human hosts through mosquito vectors and is prevalent in summer and autumn, mostly affecting children. The virus multiplies in the mononuclear phagocyte system after being bitten by a virulent mosquito and then enters the bloodstream to form viremia. The onset and severity of the disease depends mainly on the number of viruses, their virulence, and the immunity of the infected individuals. In people with competent immunity, the infection is mostly latent, while in people with weak immunity, the encephalitis B virus destructs the blood-brain barrier and invades the central nervous system, causing encephalitis, which has a high mortality rate and is prone to sequelae. Most infected individuals do not develop the disease and are latent infected. Epidemic encephalitis B mainly affects children under the age of 10. It is more frequent in the population aged 2–6 and more often in male than in female. Epidemic encephalitis B can also occur in adults in non-endemic areas. Clinical symptoms such as acute fever, convulsions, impaired consciousness, meningeal irritation, and respiratory failure with sequelae may occur in severe cases [1].
With the advance of hardware and network technologies, video transmission becomes increasingly popular, especially through mobile networks. Take different networks and displays into account, a hybrid video transmission architecture is presented. Firstly, captured videos are compressed using a H.264/AVC hard coding module, packed with RTP/RTCP protocols, and sent based on UDP sockets. Secondly, a cloud server is built to forward video streams to end users. To improve the security, Ngrok, an open source reverse proxy project, is included. Finally at the client side, video data are unpacked and decompressed, and then post-processed according to the types of end devices. Experimental results show that no obvious time delays are observed, whereas the transmission bandwidths and packet loss rates are acceptable.
Poliomyelitis is an acute infectious disease caused by infections of poliovirus, with humans as the only natural host, and mostly occurs in children. The incidence rate gradually increases over 6 months of age and decreases after 5 years of age, and rare in adults. Poliomyelitis is a contact infectious disease that is highly contagious and is transmitted mainly through fecal-oral infection from patients in the acute phase and asymptomatic poliovirus carriers, with an incubation period of 3–35 days, mostly 5–14 days [1]. After poliovirus infection, most people are asymptomatic or have nonspecific symptoms, including mild fever, malaise, headache, sore throat, and gastrointestinal discomfort. Of patients with nonspecific disease symptoms, 1–2% may develop paralytic disease. Paralysis progresses rapidly with fever, often resulting in asymmetric muscle atrophy, but there is no impairment of sensation and bladder or rectal function. Poliomyelitis is also known as "poliomyelitis" or "infantile paralysis" because of the clinical manifestations of decreased muscle tone and asymmetric flaccid paralysis [2]. Patients with poliomyelitis are more commonly seen with occult infection and non-paralytic cases, most of which can be cured, with a few patients left with paralytic sequelae. With the extent of vaccination and improved immunity in the population, the incidence has decreased significantly, and the disease is almost exclusively seen in vaccine-associated cases, namely, vaccine-associated paralytic poliomyelitis (VAPP). WHO defines VAPP as acute flaccid paralysis occurring in 4–40 days after oral administration of live-attenuated polio vaccine, in which vaccine-like poliovirus is isolated from fecal samples of patients and the virus is identified as the cause. In addition, polio-associated neurological sequelae must occur at least 60 days after the onset of paralysis [3]. The incidence of VAPP neonates in the country is 1–2.4/1 million [4].
Model order selection approaches are usually evaluated in simulations by comparing the resulting model orders to the true model order. In this paper, the mean Kullback-Leibler divergence (MKD) between the selected model and the true model is proposed as an objective measure for evaluating different model order selection approaches in simulations. For Gaussian linear model order selection problems the Kullback-Leibler divergence are reduced to simple forms and the MKD can be easily computed. Simulation results show that the MKD is a reasonable measure to evaluate different Gaussian linear model order selection approaches, in terms of signal processing.
Sign language processing has traditionally relied on task-specific models,limiting the potential for transfer learning across tasks. We introduce SHuBERT (Sign Hidden-Unit BERT), a self-supervised transformer encoder that learns strong representations from approximately 1,000 hours of American Sign Language (ASL) video content. Inspired by the success of the HuBERT speech representation model, SHuBERT adapts masked prediction for multi-stream visual sign language input, learning to predict multiple targets for corresponding to clustered hand, face, and body pose streams. SHuBERT achieves state-of-the-art performance across multiple benchmarks. On sign language translation, it outperforms prior methods trained on publicly available data on the How2Sign (+0.7 BLEU), OpenASL (+10.0 BLEU), and FLEURS-ASL (+0.3 BLEU) benchmarks. Similarly for isolated sign language recognition, SHuBERT's accuracy surpasses that of specialized models on ASL-Citizen (+5\%) and SEM-LEX (+20.6\%), while coming close to them on WLASL2000 (-3\%). Ablation studies confirm the contribution of each component of the approach.
Model order selection approaches are usually evaluated in simulations by comparing the resulting model orders to the true model order. In this paper, the mean Kullback-Leibler divergence (MKD) between the selected model and the true model is proposed as an objective measure for evaluating different model order selection approaches in simulations. For Gaussian linear model order selection problems the Kullback-Leibler divergence are reduced to simple forms and the MKD can be easily computed. Simulation results show that the MKD is a reasonable measure to evaluate different AR model order selection approaches, in terms of signal processing.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)