Sequence-Level Reference Frames In Video Coding

The proliferation of low-cost DRAM chipsets now begins to allow for the consideration of substantially-increased decoded picture buffers in advanced video coding standards such as HEVC, VVC, and Google VP9. At the same time, the increasing demand for rapid scene changes and multiple scene repetitions in entertainment or broadcast content indicates that extending the frame referencing interval to tens of minutes or even the entire video sequence may offer coding gains, as long as one is able to identify frame similarity in a computationally- and memory-efficient manner. Motivated by these observations, we propose a “stitching” method that defines a reference buffer and a reference frame selection algorithm. Our proposal extends the referencing interval of inter-frame video coding to the entire length of video sequences. Our reference frame selection algorithm uses well-established feature descriptor methods that describe frame structural elements in a compact and semantically-rich manner. We propose to combine such compact descriptors with a similarity scoring mechanism in order to select the frames to be “stitched” to reference picture buffers of advanced inter-frame encoders like HEVC, VVC, and VP9 without breaking standard compliance. Our evaluation on synthetic and real-world video sequences with the HEVC and VVC reference encoders shows that our method offers significant rate gains, with complexity and memory requirements that remain manageable for practical encoders and decoders

Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks

Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs). However, when considering visual Internet-of-Things applications, surveillance systems and semantic crawlers of large video repositories, the video capture and the CNN-based semantic analysis parts do not tend to be colocated. This necessitates the transport of compressed video over networks and incurs significant overhead in bandwidth and energy consumption, thereby significantly undermining the deployment potential of such systems. In this paper, we investigate the trade-off between the encoding bitrate and the achievable accuracy of CNN-based video classification models that directly ingest AVC/H.264 and HEVC encoded videos. Instead of retaining entire compressed video bitstreams and applying complex optical flow calculations prior to CNN processing, we only retain motion vector and select texture information at significantly-reduced bitrates and apply no additional processing prior to CNN ingestion. Based on three CNN architectures and two action recognition datasets, we achieve 11%–94% saving in bitrate with marginal effect on classification accuracy. A model-based selection between multiple CNNs increases these savings further, to the point where, if up to 7% loss of accuracy can be tolerated, video classification can take place with as little as 3 kbps for the transport of the required compressed video information to the system implementing the CNN models

Rate-accuracy trade-off in video classification with deep convolutional neural networks

Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs). However, when considering visual Internet -of- Things applications, surveillance systems and semantic crawlers of large video repositories, the compressed video content and the CNN-based semantic analysis parts do not tend to be co-located. This necessitates the transport of compressed video over networks and incurs significant overhead in bandwidth and energy consumption, thereby significantly undermining the deployment potential of such systems. In this paper, we investigate the trade-off between the encoding bitrate and the achievable accuracy of CNN-based video classification that ingests AVC/H.264 encoded videos. Instead of entire compressed video bitstreams, we only retain motion vector and selected texture information at significantly reduced bitrates. Based on two CNN architectures and two action recognition datasets, we achieve 38%-59% saving in bitrate with marginal impact in classification accuracy. A simple rate-based selection between the two CNNs shows that even further bitrate savings are possible with graceful degradation in accuracy. This may allow for rate/accuracy-optimized CNN-based video classification over networks

An in vivo investigation of photoplethysmographic signals and preliminary pulse oximetry estimation from the bowel using a new fiberoptic sensor

BACKGROUND: The continuous monitoring of splanchnic organ oxygen saturation could make the early detection of inadequate tissue oxygenation feasible, reducing the risk of hypoperfusion, severe ischemia, multiple organ failure, and, ultimately, death. Current methods for assessing splanchnic perfusion have not been widely accepted for use in the clinical care environment. In an attempt to overcome the limitations of the current techniques, a new fiberoptic photoplethysmographic (PPG)/pulse oximetry sensor was developed as a means of assessing splanchnic organ perfusion during surgery in humans. METHODS: A new fiberoptic splanchnic pulse oximeter and an optically identical fiberoptic finger pulse oximeter have been developed. Simultaneous PPG signals and preliminary estimates of arterial oxygen saturation from the bowel (small and large) and finger were obtained in 17 patients (3 men and 14 women) undergoing open laparotomy. RESULTS: Good quality PPG signals were obtained from the small and large bowel and from the finger in all patients (lower 95% confidence limit for the proportion was 0.64). Comparisons of blood oxygen saturation values acquired when using the splanchnic and the finger fiberoptic sensors and a commercial finger pulse oximeter indicated that there was no statistically significant difference between them (all P > 0.454). A Bland and Altman plot of the difference between blood oxygen saturation values from the bowel fiberoptic pulse oximeter and the fiberoptic finger pulse oximeter against their mean showed that the limits of agreement between the 2 pulse oximeters were −3.8% and 4.2% for small bowel measurements, and −3.4% and 4.3% for large bowel measurements. The 95% prediction interval for the difference between the 2 devices was between −4.2% and 4.7%. CONCLUSION: This study demonstrated that good quality PPG signals can be obtained from the bowel using a new fiberoptic sensor. Further evaluation is required to determine whether fiberoptic pulse oximetry of the bowel may provide a suitable method for monitoring splanchnic perfusion

The landscape of molecular chaperones across human tissues reveals a layered architecture of core and variable chaperones

The sensitivity of the protein-folding environment to chaperone disruption can be highly tissue-specific. Yet, the organization of the chaperone system across physiological human tissues has received little attention. Through computational analyses of large-scale tissue transcriptomes, we unveil that the chaperone system is composed of core elements that are uniformly expressed across tissues, and variable elements that are differentially expressed to fit with tissue-specific requirements. We demonstrate via a proteomic analysis that the muscle-specific signature is functional and conserved. Core chaperones are significantly more abundant across tissues and more important for cell survival than variable chaperones. Together with variable chaperones, they form tissue-specific functional networks. Analysis of human organ development and aging brain transcriptomes reveals that these functional networks are established in development and decline with age. In this work, we expand the known functional organization of de novo versus stress-inducible eukaryotic chaperones into a layered core-variable architecture in multi-cellular organisms

Patient Satisfaction and Its Predictors in the General Hospitals of Southwest Saudi Arabia: A Cross-sectional Survey

Background: Patient satisfaction occupies a central position in measuring the quality of care as it provides information on the provider's success, meeting the patient’s values and expectations. Hence, it is an essential tool for assessing health services outcomes. This study aimed to assess patients' satisfaction level and factors influencing healthcare quality of general hospitals in the Jazan region, Saudi Arabia (SA). Methods: This observational cross-sectional study was conducted on a sample of 423 patients selected through stratified random sampling from general hospitals of the Jazan region. Results: The overall satisfaction rate among the study participants was 80.9%. Satisfaction with food services was the highest (91.15%) followed by doctor services (81.0%), reception and entry procedures (80%), and nursing services (78.15%). The various aspects of satisfaction with doctors and nurses included the treatment prescribed by physicians, clarity in communication with patients, compassion and providing clear explanation of what they were doing. However, about 27.3% of the patients were dissatisfied with the length of waiting period before seeing a doctor. Binary logistic regression analysis suggested that uneducated patients and patients with secondary school education were more likely to have higher satisfaction level than university-educated patients (OR = 3.40, 95% C.I. [1.56–7.45], p = 0.002), (OR = 2.66, 95% C.I. [1.28–5.55], p = 0.009), and (OR = 2.29, 95% C.I. [1.40–3.73], p = 0.001), respectively. Conclusion: The health services satisfaction level was high in the Jazan population. However, some aspects of dissatisfaction were reported, such as the long waiting period before seeing a doctor. These aspects are recommended to be improved to ensure that the services provided by general hospitals are of high quality

Using venous blood gas analysis in the assessment of COPD exacerbations: a prospective cohort study

Introduction: Identifying acute hypercapnic respiratory failure is crucial in the initial management of acute exacerbations of COPD. Guidelines recommend obtaining arterial blood samples but these are more difficult to obtain than venous. We assessed whether blood gas values derived from venous blood could replace arterial at initial assessment. Methods: Patients requiring hospital treatment for an exacerbation of COPD had paired arterial and venous samples taken. Bland–Altman analyses were performed to assess agreement between arterial and venous pH, CO2 and . The relationship between SpO2 and SaO2 was assessed. The number of attempts and pain scores for each sample were measured. Results: 234 patients were studied. There was good agreement between arterial and venous measures of pH and (mean difference 0.03 and −0.04, limits of agreement −0.05 to 0.11 and −2.90 to 2.82, respectively), and between SaO2 and SpO2 (in patients with an SpO2 of >80%). Arterial sampling required more attempts and was more painful than venous (mean pain score 4 (IQR 2–5) and 1 (IQR 0–2), respectively, p<0.001). Conclusions: Arterial sampling is more difficult and more painful than venous sampling. There is good agreement between pH and values derived from venous and arterial blood, and between pulse oximetry and arterial blood gas oxygen saturations. These agreements could allow the initial assessment of COPD exacerbations to be based on venous blood gas analysis and pulse oximetry, simplifying the care pathway and improving the patient experience

Comparison of non-invasive to invasive oxygenation ratios for diagnosing acute respiratory distress syndrome following coronary artery bypass graft surgery: a prospective derivation-validation cohort study

Objective: To determine if non-invasive oxygenation indices, namely peripheral capillary oxygen saturation (SpO2)/ fraction of inspired oxygen (Fi O2) and partial pressure of alveolar oxygen (PAO2)/Fi O2 may be used as effective surrogates for the partial pressure of arterial oxygen (PaO2)/Fi O2. Also, to determine the SpO2/Fi O2 and PAO2/Fi O2 values that correspond to PaO2/Fi O2 thresholds for identifying acute respiratory distress syndrome (ARDS) in patients following coronary artery bypass graft (CABG) surgery. Methods: A prospective derivation-validation cohort study in the Open-Heart ICU of an academic teaching hospital. Recorded variables included patient demographics, ventilator settings, chest radiograph results, and SPO2, PaO2, PAO2, SaO2, and Fi O2. Linear regression modeling was used to quantify the relationship between indices. Receiver operating characteristic (ROC) curves were used to determine the sensitivity and specificity of the threshold values. Results: One-hundred seventy-five patients were enrolled in the derivation cohort, and 358 in the validation cohort. The SPO2/Fi O2 and PAO2/Fi O2 ratios could be predicted well from PaO2/Fi O2, described by the linear regression models SPO2/Fi O2 = 71.149 + 0.8PF and PAO2/Fi O2 = 38.098 + 2.312PF, respectively. According to the linear regression equation, a PaO2/Fi O2 ratio of 300 equaled an SPO2/Fi O2 ratio of 311 (R2 0.857, F 1035.742, < 0.0001) and a PAO2/Fi O2 ratio of 732 (R2 0.576, F 234.887, < 0.0001). The SPO2/Fi O2 threshold of 311 had 90% sensitivity, 80% specificity, LR+ 4.50, LR- 0.13, PPV 98, and NPV 42.1 for the diagnosis of mild ARDS. The PAO2/Fi O2 threshold of 732 had 86% sensitivity, 90% specificity, LR+ 8.45, LR- 0.16, PPV 98.9, and NPV 36 for the diagnosis of mild ARDS. SPO2/ Fi O2 had excellent discrimination ability for mild ARDS (AUC ± SE = 0.92 ± 0.017; 95% CI 0.889 to 0.947) as did PAO2/ Fi O2 (AUC ± SE = 0.915 ± 0.018; 95% CI 0.881 to0.942). Conclusions: PaO2 and SaO2 correlated in the diagnosis of ARDS, with a PaO2/Fi O2 of 300 correlating to an SPO2/ Fi O2 of 311 (Sensitivity 90%, Specificity 80%). The SPO2/ Fi O2 ratio may allow for early real-time rapid identification of ARDS, while decreasing the cost, phlebotomy, blood loss, pain, skin breaks, and vascular punctures associated with serial arterial blood gas measurements

Visualization of the joining of ribosomal subunits reveals the presence of 80S ribosomes in the nucleus

In eukaryotes the 40S and 60S ribosomal subunits are assembled in the nucleolus, but there appear to be mechanisms preventing mRNA binding, 80S formation, and initiation of translation in the nucleus. To visualize association between ribosomal subunits, we tagged pairs of Drosophila ribosomal proteins (RPs) located in different subunits with mutually complementing halves of fluorescent proteins. Pairs of tagged RPs expected to interact, or be adjacent in the 80S structure, showed strong fluorescence, while pairs that were not in close proximity did not. Moreover, the complementation signal is found in ribosomal fractions and it was enhanced by translation elongation inhibitors and reduced by initiation inhibitors. Our technique achieved 80S visualization both in cultured cells and in fly tissues in vivo. Notably, while the main 80S signal was in the cytoplasm, clear signals were also seen in the nucleolus and at other nuclear sites. Furthermore, we detected rapid puromycin incorporation in the nucleolus and at transcription sites, providing an independent indication of functional 80S in the nucleolus and 80S association with nascent transcripts