The condition combining a dislocated humeral head fracture and an ipsilateral humeral shaft fracture is seen to be rare in literature, which is limited to case report or case series. Furthermore, ...effective management of these coexistent injuries is still a subject of debate. The essential purpose of this article is to report another treatment method for this condition. We present a case of a 79-year-old female patient who suffered a three-part humeral head fracture-dislocation associated with the ipsilateral humeral shaft fracture. The combined injuries were managed by minimal invasive plate osteosynthesis (MIPO) through the deltopectoral approach with the eventual result of bone healing and good function after thirty-three months of follow-up. In conclusion, MIPO should be considered a safe and effective option, however, the risk of traumatic osteonecrosis of the humeral head is taken into account before operation decision-making.
: COVID-19 is a respiratory disease caused by a novel coronavirus (SARS-CoV-2) and causes substantial morbidity and mortality. There is currently no vaccine to prevent COVID-19 or therapeutic agent ...to treat COVID-19. This clinical trial is designed to evaluate chloroquine as a potential therapeutic for the treatment of hospitalised people with COVID-19. We hypothesise that chloroquine slows viral replication in patients with COVID-19, attenuating the infection, and resulting in more rapid decline of viral load in throat/nose swabs. This viral attenuation should be associated with improved patient outcomes.
: The study will start with a 10-patient prospective observational pilot study following the same entry and exclusion criteria as for the randomized trial and undergoing the same procedures. The main study is an open label, randomised, controlled trial with two parallel arms of standard of care (control arm) versus standard of care with 10 days of chloroquine (intervention arm) with a loading dose over the first 24 hours, followed by 300mg base orally once daily for nine days. The study will recruit patients in three sites in Ho Chi Minh City, Vietnam: the Hospital for Tropical Diseases, the Cu Chi Field Hospital, and the Can Gio COVID hospital. The primary endpoint is the time to viral clearance from throat/nose swab, defined as the time following randomization until the midpoint between the last positive and the first of the negative throat/nose swabs. Viral presence will be determined using RT-PCR to detect SARS-CoV-2 RNA.
The results of the study will add to the evidence-based guidelines for management of COVID-19. Given the enormous experience of its use in malaria chemoprophylaxis, excellent safety and tolerability profile, and its very low cost, if proved effective then chloroquine would be a readily deployable and affordable treatment for patients with COVID-19.
Clinicaltrials.gov NCT04328493 31/03/2020.
Abstract
Background
Little is known about the natural history of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.
Methods
We conducted a prospective study at a ...quarantine center for coronavirus disease 2019 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with reverse-transcription polymerase chain reaction (RT-PCR)–confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrollment and daily nasopharyngeal/throat swabs (NTSs) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals.
Results
Between 10 March and 4 April 2020, 14 000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13 (43%) never had symptoms and 17 (57%) were symptomatic. Seventeen (57%) participants imported cases. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS collected at enrollment (8/13 62% vs 17/17 100%; P = .02). SARS-CoV-2 RNA was detected in 20 of 27 (74%) available saliva samples (7 of 11 64% in the asymptomatic group and 13 of 16 81% in the symptomatic group; P = .56). Analysis of RT-PCR positivity probability showed that asymptomatic participants had faster viral clearance than symptomatic participants (P < .001 for difference over the first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit SARS-CoV-2 to 4 contacts.
Conclusions
Asymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTSs. The NTS viral loads fall faster in asymptomatic individuals, but these individuals appear able to transmit the virus to others.
Forty-three percent (13/30) of confirmed SARS-CoV-2–infected individuals were asymptomatic, with the virus detected in both saliva and nasopharyngeal/throat swabs. Viral clearance was faster in asymptomatic individuals, but they still appeared able to pass the infection to others.
One hundred days after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Vietnam on 23 January, 270 cases were confirmed, with no deaths. We describe the control ...measures used by the government and their relationship with imported and domestically acquired case numbers, with the aim of identifying the measures associated with successful SARS-CoV-2 control.
Clinical and demographic data on the first 270 SARS-CoV-2 infected cases and the timing and nature of government control measures, including numbers of tests and quarantined individuals, were analyzed. Apple and Google mobility data provided proxies for population movement. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of presymptomatic transmission events and time-varying reproduction numbers.
A national lockdown was implemented between 1 and 22 April. Around 200 000 people were quarantined and 266 122 reverse transcription polymerase chain reaction (RT-PCR) tests conducted. Population mobility decreased progressively before lockdown. In total, 60% (163/270) of cases were imported; 43% (89/208) of resolved infections remained asymptomatic for the duration of infection. The serial interval was 3.24 days, and 27.5% (95% confidence interval CI, 15.7%-40.0%) of transmissions occurred presymptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% CI, .·37-2.·36). No community transmission has been detected since 15 April.
Vietnam has controlled SARS-CoV-2 spread through the early introduction of mass communication, meticulous contact tracing with strict quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic and imported cases, and evidence for substantial presymptomatic transmission.
Imitation learning is an effective approach for an autonomous agent to learn control policies when an explicit reward function is unavailable, using demonstrations provided from an expert. However, ...standard imitation learning methods assume that the agents and the demonstrations provided by the expert are in the same domain configuration. Such an assumption has made the learned policies difficult to apply in another distinct domain. The problem is formalized as domain adaptive imitation learning, which is the process of learning how to perform a task optimally in a learner domain, given demonstrations of the task in a distinct expert domain. We address the problem by proposing a model based on Generative Adversarial Network. The model aims to learn both domain-shared and domain-specific features and utilizes it to find an optimal policy across domains. The experimental results show the effectiveness of our model in a number of tasks ranging from low to complex high-dimensional.
In video streaming services, predicting the continuous user's quality of experience (QoE) plays a crucial role in delivering high quality streaming contents to the user. However, the complexity ...caused by the temporal dependencies in QoE data and the non-linear relationships among QoE influence factors has introduced challenges to continuous QoE prediction. To deal with that, existing studies have utilized the Long Short-Term Memory model (LSTM) to effectively capture such complex dependencies, resulting in excellent QoE prediction accuracy. However, the high computational complexity of LSTM, caused by the sequential processing characteristic in its architecture, raises a serious question about its performance on devices with limited computational power. Meanwhile, Temporal Convolutional Network (TCN), a variation of convolutional neural networks, has recently been proposed for sequence modeling tasks (e.g., speech enhancement), providing a superior prediction performance over baseline methods including LSTM in terms of prediction accuracy and computational complexity. Being inspired of that, in this paper, an improved TCN-based model, namely CNN-QoE, is proposed for continuously predicting the QoE, which poses characteristics of sequential data. The proposed model leverages the advantages of TCN to overcome the computational complexity drawbacks of LSTM-based QoE models, while at the same time introducing the improvements to its architecture to improve QoE prediction accuracy. Based on a comprehensive evaluation, we demonstrate that the proposed CNN-QoE model can provide a high QoE prediction performance on both personal computers and mobile devices, outperforming the existing approaches.
Transfer learning is an effective approach for adapting an autonomous agent to a new target task by transferring knowledge learned from the previously learned source task. The major problem with ...traditional transfer learning is that it only focuses on optimizing learning performance on the target task. Thus, the performance on the target task may be improved in exchange for the deterioration of the source task’s performance, resulting in an agent that is not able to revisit the earlier task. Therefore, transfer learning methods are still far from being comparable with the learning capability of humans, as humans can perform well on both source and new target tasks. In order to address this limitation, a task adaptation method for imitation learning is proposed in this paper. Being inspired by the idea of repetition learning in neuroscience, the proposed adaptation method enables the agent to repeatedly review the learned knowledge of the source task, while learning the new knowledge of the target task. This ensures that the learning performance on the target task is high, while the deterioration of the learning performance on the source task is small. A comprehensive evaluation over several simulated tasks with varying difficulty levels shows that the proposed method can provide high and consistent performance on both source and target tasks, outperforming existing transfer learning methods.
Stereo cameras allow mobile robots to perceive depth in their surroundings by capturing two separate images from slightly different perspectives. This is necessary for tasks such as obstacle ...avoidance, navigation, and spatial mapping. By utilizing a convolutional neural network (CNN), existing works in stereo cameras based on depth estimation have achieved superior results. However, the critical requirement for depth estimation for mobile robots is to have an optimal tradeoff between computational cost and accuracy. To achieve such a tradeoff, attention-aware feature aggregation (AAFS) has been proposed for real-time stereo matching on edge devices. AAFS includes multistage feature extraction, an attention module, and a 3D CNN architecture. However, its 3D CNN architecture learns contextual information ineffectively. In this paper, a deep encoder–decoder architecture is applied to an AAFS 3D CNN to improve depth estimation accuracy. Through evaluation, it is proven that the proposed 3D CNN architecture provides significantly better accuracy while keeping the inference time comparable to that of AAFS.
PDF
