Fleminglane4204

Salient object detection, which simulates human visual perception in locating the most significant object(s) in a scene, has been widely applied to various computer vision tasks. Now, the advent of depth sensors means that depth maps can easily be captured; this additional spatial information can boost the performance of salient object detection. Although various RGB-D based salient object detection models with promising performance have been proposed over the past several years, an in-depth understanding of these models and the challenges in this field remains lacking. In this paper, we provide a comprehensive survey of RGB-D based salient object detection models from various perspectives, and review related benchmark datasets in detail. Further, as light fields can also provide depth maps, we review salient object detection models and popular benchmark datasets from this domain too. Moreover, to investigate the ability of existing models to detect salient objects, we have carried out a comprehensive attribute-based evaluation of several representative RGB-D based salient object detection models. Finally, we discuss several challenges and open directions of RGB-D based salient object detection for future research. All collected models, benchmark datasets, datasets constructed for attribute-based evaluation, and related code are publicly available at https//github.com/taozh2017/RGBD-SODsurvey.

The estimation of the stature of human beings is a major part of medicolegal investigation when only body parts are found. The study aimed to estimate the stature from different handprint measurements in a Bangladeshi population using statistical considerations. A sample of 200 young Bangladeshi adults (100 men and 100 women) with no physical disabilities participated in this study. Stature and seven anthropometric measurements were measured using standard anthropometric measurements. The bilateral asymmetry was tested using the independent

test. The Pearson's correlation coefficient (

) between the stature and different handprint measurements was calculated. Consequently, the simple and multiple linear regression models were developed to estimate the stature from the handprint measurements.

The bilateral asymmetry was statistically not significant (

> 0.05) in right and left handprints. Sex difference significantly (

< 0.05) influences the relationship between stature and handprint measuremof stature from handprint measurements is possible and reliable. The findings of this study are very useful from the forensic and medicolegal point of view and can use to estimate the stature in Bangladeshi population.This special report was developed to communicate policy and procedures for free-standing acute inpatient rehabilitation hospitals (AIRHs) to protect patients and healthcare personnel and to prevent further spread of severe acute respiratory syndrome coronavirus 2. The recommended policies were developed in conjunction with the New Mexico Department of Health and hospital leadership. As we attain additional knowledge and experience during this pandemic, suggestions of best practice will continue to evolve for AIRHs. The authors encourage readers to work with local regulatory officials to ensure regulatory compliance as well as respect of the availability of local resources.

Cancer patients are considered a highly fragile group in the current coronavirus disease 2019 (COVID-19) pandemic.

In this study, patients with COVID-19 and cancer, hospitalized in Piacenza, Italy, from 4 April to 4 May 2020 were included. selleck chemicals Risk factors for death were analyzed.

Fifty-one COVID-19 cancer patients were included, of which themedian age was 71.02years (range 51-86) and70.59% were male. Cancer types includedgastrointestinal (25.49%), genitourinary (25.49%)and lung (23.53%). Forty-five (88.24%) patients received hydroxychloroquine-based therapy. In addition, 25 of51 patients died (49%) 12 of51 (23.53%) owing to cancer and 13 of51 (25.49%) owing to COVID-19.

The risks for death were related to later onset of treatment for COVID-19, severe/critical COVID-19, age, elevated basal CRP and elevated lactate dehydrogenase.

The risks for death were related to later onset of treatment for COVID-19, severe/critical COVID-19, age, elevated basal CRP and elevated lactate dehydrogenase.

As coronavirus (CoV)disease 2019-associated pneumonia spreads globally, there has been an urgent need to combat the spread and develop vaccines.

We used an integrated computational algorithmto explore the binding mechanism of TMC-310911/ritonavir (RVT) with SARS-CoV-2and SARS-CoV main proteases.

RVT and TMC-310911 had favorable interactions with the proteases, andthese high interactions are facilitated by some significant residues such as Asn133, Gly195and Gln192. Our study further implicated two important rings in the structure of RVTas a possible chemical culprit in its therapeutic activity.

Although there are conflicting clinical results on the therapeutic potency of RVTin the treatment of coronavirus disease 2019, our findings provided molecular insight into the binding mechanism of TMC-310911 and RVTwith SARS-CoV-2 and SARS-CoV main proteases.

Although there are conflicting clinical results on the therapeutic potency of RVT in the treatment of coronavirus disease 2019, our findings provided molecular insight into the binding mechanism of TMC-310911 and RVT with SARS-CoV-2 and SARS-CoV main proteases.

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)virus-specific reverse transcriptase-polymerase chain reaction(RT-PCR) represents the diagnostic gold standard. We explored the value of chest ultrasonography to predict positivity to SARS-CoV-2 on RT-PCR in suspected COVID-19cases.

Consecutive patients with suspect COVID-19 were included if they had fever and/or history of cough and/or dyspnea. Lung ultrasound score (LUSS) was computed according to published methods.

A total of 76 patients were included. A 3-variable model based on aspartate transaminase(AST)>upper limit of normal, LUSS>12 and body temperature>37.5°C yielded an overall accuracy of 91%.

A simple LUSS-based model may represent a powerful tool for initial assessment in suspected cases of COVID-19.

A simple LUSS-based model may represent a powerful tool for initial assessment in suspected cases of COVID-19.