Effective Screening and Texture Segmentation of Green Vegetation Cover Based on UAV Images

As an important part of the ecosystem, green vegetation coverage is crucial to people's sensory and mental health. Using reliable data sets to classify and identify the green vegetation cover on the land surface and explore its spatial distribution law can provide important reference for the work of regional ecosystem managers and urban planners. The optimization of effective screening methods for green vegetation coverage areas is an important requirement to measure the surface vegetation status. UAV aerial images feature high definition, large scale, small area and high up-to-dateness. However, at present, there are few studies based on the reliable UAV aerial image system to identify green vegetation cover and further explore its spatial changes. In this study, 701 residential neighborhoods in Beijing were taken as the research objects, and the green vegetation of 7,695 sample points was identified by UAV. The green vegetation coverage was measured, and the spatial distribution pattern of green vegetation in different land surface areas was quantitatively compared. The results show that the image processing method proposed in this paper can effectively detect the boundary of green vegetation cover area from UAV aerial images, the correlation of texture segmentation is good, and the segmentation performance is better than other methods. The distribution of green vegetation cover in the research target area is uneven, with 63.79% of the research area having relatively low (Level 2) and medium (Level 3) green vegetation coverage, which indicates that the green vegetation coverage area in the research area is insufficient to meet the needs of regional ecosystem development. The characteristics of green vegetation cover in 16 districts in the study area are different, showing different spatial distribution patterns;except Xicheng District, there are 211 points without landscape in the area covered by green vegetation in 15 districts. The results can provide support for urban land surface planning and management.

Techniques for Detecting Video Shot Boundaries: A Review

Due to the Corona Virus Diseases (COVID-19) pandemic, education is completely dependent on digital platforms, so recent advances in technology have made a tremendous amount of video content available. Due to the huge amount of video content, content-based information retrieval has become more and more important. Video content retrieval, just like information retrieval, requires some pre-processing such as indexing, key frame selection, and, most importantly, accurate detection of video shots. This gives the way for video information to be stored in a manner that will allow easy access. Video processing plays a vital role in many large applications. The applications required to perform the various manipulations on video streams (as on frames or say shots). The high definition of video can take a lot of memory to store, so compression techniques are huge in demand. Also, object tracking or object identification is an area where much considerable research has taken place and it is in progress.

Non-invasive brain stimulation for fatigue in post-acute sequelae of SARS-CoV-2 (PASC).

BACKGROUND: and purpose: Fatigue is among the most common persistent symptoms following post-acute sequelae of Sars-COV-2 infection (PASC). The current study investigated the potential therapeutic effects of High-Definition transcranial Direct Current Stimulation (HD-tDCS) associated with rehabilitation program for the management of PASC-related fatigue. METHODS: Seventy patients with PASC-related fatigue were randomized to receive 3 mA or sham HD-tDCS targeting the left primary motor cortex (M1) for 30 min paired with a rehabilitation program. Each patient underwent 10 sessions (2 sessions/week) over five weeks. Fatigue was measured as the primary outcome before and after the intervention using the Modified Fatigue Impact Scale (MFIS). Pain level, anxiety severity and quality of life were secondary outcomes assessed, respectively, through the McGill Questionnaire, Hamilton Anxiety Rating Scale (HAM-A) and WHOQOL. RESULTS: Active HD-tDCS resulted in significantly greater reduction in fatigue compared to sham HD-tDCS (mean group MFIS reduction of 22.11 points vs 10.34 points). Distinct effects of HD-tDCS were observed in fatigue domains with greater effect on cognitive (mean group difference 8.29 points; effect size 1.1; 95% CI 3.56-13.01; P < .0001) and psychosocial domains (mean group difference 2.37 points; effect size 1.2; 95% CI 1.34-3.40; P < .0001), with no significant difference between the groups in the physical subscale (mean group difference 0.71 points; effect size 0.1; 95% CI 4.47-5.90; P = .09). Compared to sham, the active HD-tDCS group also had a significant reduction in anxiety (mean group difference 4.88; effect size 0.9; 95% CI 1.93-7.84; P < .0001) and improvement in quality of life (mean group difference 14.80; effect size 0.7; 95% CI 7.87-21.73; P < .0001). There was no significant difference in pain (mean group difference -0.74; no effect size; 95% CI 3.66-5.14; P = .09). CONCLUSION: An intervention with M1 targeted HD-tDCS paired with a rehabilitation program was effective in reducing fatigue and anxiety, while improving quality of life in people with PASC.

Neural Network-Based Ultra-High-Definition Video Live Streaming Optimization Algorithm

Online live streaming has been widely used in distant teaching, online live shopping, and so on. Particularly, online teaching live streaming breaks the time and space boundary of teaching and has better interactivity, which is a new distant education mode. As a new online sales model, online live shopping promotes the rapid development of Internet economy. However, the quality of live video affects the user experience. This paper studies the optimization algorithm of ultra-high-definition live streaming, focusing on superresolution technology. Convolutional neural network (CNN) is a multilayer artificial neural network designed to process two-dimensional input data. It takes advantage of CNN in image processing. This paper proposes an image superresolution algorithm based on hybrid dilated convolution and Laplacian pyramid. By mixing the dilated convolution module, the receptive field of the network can be improved more effectively to obtain more context information so that the high-frequency features of the image can be extracted more effectively. Experiment was running on Set5, Set14, Urban100, and BSD100 datasets, and the results reveal that the proposed algorithm outperforms baselines with respect to peak signal to noise ratio (PSNR), structural similarity index measurement (SSIM), and image quality.

Treatment of Memory Disorders in Gulf War Illness with High-Definition Transcranial Direct Cortical Stimulation

The present study consists of the application of 1 ma anodal HD tDCS over the preSMA for 20 minutes a session for 10 sessions over a two week period. The treatment is hypothesized to lead to improvement in verbal retrieval, detectable in both performance measures of verbal retrieval tasks and in ERP markers of verbal retrieval processing. Our objective is to determine if 10 sessions of 1 ma anodal HD tDCS to the preSMA for 20 minutes a session are an effective treatment for verbal retrieval deficits in GWI. We have established the research team, laboratory setting, obtained approval of all regulatory documents for the study, and established recruiting procedures. In the first half of the year, we screened 8 veterans and enrolled 5 in the baseline testing and treatment phase of the study. We were required to halt in person human subject research for the second half of the year due to the Covid-19 pandemic.

A High-Definition 3-Dimensional Exoscope With the ARTip Cruise System as an Effective New Tool for Phonosurgery: A Preliminary Report.

The aim of phonosurgery is to improve voice quality and efficiency by performing precise, minimally invasive, conservative treatment. Magnified visualization of the vocal folds is mandatory to achieve optimal results; operative microscopy has been utilized so far to perform phonosurgery. In recent decades, the use of an exoscope (extracorporeal telescope) has been proposed in several fields of surgery that necessitate magnification. Further technological advancements have enabled 3-dimensional (3D) technology to be added to existing exoscopes. Recently, a motorized holding arm (the ARTip Cruise System) was developed to allow smooth precise positioning of the 3D Vitom exoscope (Karl Storz, Tuttlingen, Germany) by the surgeon without need for assistance. To evaluate the feasibility of phonosurgery by means of this innovative system, we utilized it for six consecutive procedures for benign laryngeal pathologies, including two vocal fold polyps, two cysts, one Reinke's edema and one unilateral vocal fold paralysis treated by fat augmentation. All procedures were performed without any technical difficulty and with excellent results at follow-up, as demonstrated by GRBAS, VHI-10 and maximal phonation time evaluations. Main advantages of this technique were the enhanced depth of field and high definition of anatomical details. Communication with the operating room team was facilitated by the shared view of the same images on screen; furthermore, the surgeon could perform the procedures visualizing the surgical site without need to position the eyes on the microscope eyepieces and so being able to wear full face protection, which was of paramount importance in the era of the COVID-19 pandemic. In conclusion, the 4K 3D exoscope system with the ARTip Cruise System represents a promising innovation in the field of voice surgery to allow highly precise procedures optimizing safety and co-operation with the operating room team.

Evaluation of a High-Definition PCR Assay for the Detection of SARS-CoV-2 in Extracted and Nonextracted Respiratory Specimens Collected in Various Transport Media.

OBJECTIVES: We conducted an analytic and clinical comparison of a novel high-definition polymerase chain reaction PCR (HDPCR) assay to traditional real-time PCR (RT-PCR) for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in upper respiratory specimens. METHODS: Analytic performance of RT-PCR, HDPCR, and extraction-free HDPCR was established through replicate testing of a serially diluted clinical specimen containing SARS-CoV-2. A clinical comparison of all 3 assays was conducted using 351 prospectively collected upper respiratory swab specimens obtained from symptomatic and asymptomatic individuals collected in various transport media. RESULTS: RT-PCR and HDPCR assays using extracted nucleic acid demonstrated similar analytic limits of detection (LoD) and clinical performance, with 100% positive and negative agreement. Extraction-free HDPCR demonstrated a 1.5 to 2.0 log10 increase in LoD based on cycle threshold values. However, clinical performance of extraction-free HDPCR remained high, demonstrating 97.8% positive and 99.6% negative agreement with RT-PCR. An overall increase in "invalid" and "presumptive" results was observed when using the extraction-free method, but this was highly variable based on transport medium used. CONCLUSIONS: HDPCR performs similar to RT-PCR for the detection of SARS-CoV-2. The use of an extraction-free HDPCR protocol maintained high clinical performance despite reduced analytic LoD, with the benefit of reduced hands-on time and cost of reagents associated with nucleic acid extraction.