Cerebral hemodynamics underlying ankle force sense modulated by high-definition transcranial direct current stimulation.

This study aimed to investigate the effects of high-definition transcranial direct current stimulation on ankle force sense and underlying cerebral hemodynamics. Sixteen healthy adults (8 males and 8 females) were recruited in the study. Each participant received either real or sham high-definition transcranial direct current stimulation interventions in a randomly assigned order on 2 visits. An isokinetic dynamometer was used to assess the force sense of the dominant ankle; while the functional near-infrared spectroscopy was employed to monitor the hemodynamics of the sensorimotor cortex. Two-way analyses of variance with repeated measures and Pearson correlation analyses were performed. The results showed that the absolute error and root mean square error of ankle force sense dropped more after real stimulation than after sham stimulation (dropped by 23.4% vs. 14.9% for absolute error, and 20.0% vs. 10.2% for root mean square error). The supplementary motor area activation significantly increased after real high-definition transcranial direct current stimulation. The decrease in interhemispheric functional connectivity within the Brodmann's areas 6 was significantly correlated with ankle force sense improvement after real high-definition transcranial direct current stimulation. In conclusion, high-definition transcranial direct current stimulation can be used as a potential intervention for improving ankle force sense. Changes in cerebral hemodynamics could be one of the explanations for the energetic effect of high-definition transcranial direct current stimulation.

Dissociable rhythmic mechanisms enhance memory for conscious and nonconscious perceptual contents.

Understanding the neural mechanisms of conscious and unconscious experience is a major goal of fundamental and translational neuroscience. Here, we target the early visual cortex with a protocol of noninvasive, high-resolution alternating current stimulation while participants performed a delayed target-probe discrimination task and reveal dissociable mechanisms of mnemonic processing for conscious and unconscious perceptual contents. Entraining ß-rhythms in bilateral visual areas preferentially enhanced short-term memory for seen information, whereas α-entrainment in the same region preferentially enhanced short-term memory for unseen information. The short-term memory improvements were frequency-specific and long-lasting. The results add a mechanistic foundation to existing theories of consciousness, call for revisions to these theories, and contribute to the development of nonpharmacological therapeutics for improving visual cortical processing.

Novel 10q21.1-q22.1 Duplication in a Boy with Minor Facial Dysmorphism, Mild Intellectual Disability, Autism Spectrum Disorder-Like Phenotype, and Short Stature.

INTRODUCTION: Duplications reported in 10q21-q22 include borderline to moderate intellectual disability, growth retardation, autism, attention deficit hyperactivity disorder, and minor craniofacial dysmorphism. CASE PRESENTATION: We present a patient with a novel 14.7-Mb de novo interstitial duplication at 10q21.1-q22.1 delineated by a high-definition (HD) single nucleotide polymorphism (SNP) array. The boy had minor facial dysmorphism, mild intellectual disability, an autism spectrum disorder-like phenotype, and short stature. CONCLUSION: This is the first case in which a novel 10q21.1-q22.1 duplication was detected by the HD SNP array, expanding the spectrum of duplications seen in 10q21-q22. This report provides a detailed clinical examination of a patient with a 10q21.1-q22.1 duplication and suggests that brain development and cognitive function may be affected by an increased dosage sensitivity of the involved JMJD1C and EGR2 genes. This case contributes to the understanding of the genotype-phenotype relationship for genetic counseling and provides further evidence for the identification of a novel microduplication syndrome in 10q21-q22.

Differential effects of high-definition transcranial direct current stimulation (HD-tDCS) on attentional guidance by working memory in males with substance use disorder according to memory modality.

Information stored in working memory can guide perception selection, and this process is modulated by cognitive control. Although previous studies have demonstrated that neurostimulation over the left dorsolateral prefrontal cortex (lDLPFC) contributes to restore cognitive control among individuals with substance use disorder (SUD), there remains an open question about the potential stimulation effects on memory-driven attention. To address this issue, the present study adopted a combined working memory/attention paradigm while employing high-definition transcranial direct current stimulation (HD-tDCS) to stimulate the lDLPFC. Observers were asked to maintain visual or audiovisual information in memory while executing a search task, while the validity of the memory contents for the subsequent search task could be either invalid or neutral. The results showed a faint memory-driven attentional suppression effect in sham stimulation only under the audiovisual condition. Moreover, anodal HD-tDCS facilitated attentional suppression effect in both the strength and temporal dynamics under the visual-only condition, whereas the effect was impaired or unchanged under the audiovisual condition. Surprisingly, cathodal HD-tDCS selectively improved temporal dynamics of the attentional suppression effect under the audiovisual condition. The present study revealed the differential enhancement of HD-tDCS on cognitive control over visual and audiovisual memory-driven attention among individuals with SUD.

Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency.

Considerable evidence highlights the dorsolateral prefrontal cortex (DLPFC) as a key region for hierarchical (i.e. multilevel) learning. In a previous electroencephalography (EEG) study, we found that the low-level prediction errors were encoded by frontal theta oscillations (4-7 Hz), centered on right DLPFC (rDLPFC). However, the causal relationship between frontal theta oscillations and hierarchical learning remains poorly understood. To investigate this question, in the current study, participants received theta (6 Hz) and sham high-definition transcranial alternating current stimulation (HD-tACS) over the rDLPFC while performing the probabilistic reversal learning task. Behaviorally, theta tACS induced a significant reduction in accuracy for the stable environment, but not for the volatile environment, relative to the sham condition. Computationally, we implemented a combination of a hierarchical Bayesian learning and a decision model. Theta tACS induced a significant increase in low-level (i.e. probability-level) learning rate and uncertainty of low-level estimation relative to sham condition. Instead, the temperature parameter of the decision model, which represents (inverse) decision noise, was not significantly altered due to theta stimulation. These results indicate that theta frequency may modulate the (low-level) learning rate. Furthermore, environmental features (e.g. its stability) may determine whether learning is optimized as a result.

Ability of detection in different resolution endoscopy for upper gastrointestinal mucosal lesions.

BACKGROUND: Most endoscopists believe that higher resolution improves lesion detection rates. However, existing studies primarily compared the detection rates of white light endoscopy (WLE) and other imaging modalities. Our previous study demonstrated the advantages of magnifying endoscopy from general endoscopy for lesion detection, prompting further investigation into the variations in lesion detection rates across endoscopes with different resolutions. METHODS: Endoscopic and corresponding pathological data from our medical unit over the past 5 years were analyzed. We excluded specific-purpose endoscopic procedures to ensure the natural randomization of the data. Baseline adjustment and risk factor analyses used multi-group propensity score matching and logistic regression. RESULTS: The overall lesion detection rate was significantly higher with high-quality endoscopy (Q-endoscopy) compared to high-definition endoscopy (H-endoscopy) and high definition and quality endoscopy (HQ-endoscopy) (34.4% vs. 30.2% vs. 29.6%, P = 0.001). Similar results were observed for elevated lesions (25.7% vs. 21.0% vs. 22.9%, P = 0.001) and depressed lesions (6.6% vs. 6.2% vs. 3.6%, P < 0.001). HQ-endoscopy had a superior detection rate for superficial lesions compared to both H- and Q-endoscopies (3.0% vs. 2.8% vs. 1.8%, P = 0.041). However, there were no significant differences in neoplastic detection rate or missed neoplastic lesion rate among the three groups. CONCLUSION: Q-endoscopy is superior in detecting non-superficial lesions, while HQ-endoscopy is better at detecting superficial lesions. However, there were no statistically significant differences in detecting or omitting neoplastic lesions among the three endoscopic examinations.

Assessing the effectiveness of high-definition transcranial direct current stimulation for treating obsessive-compulsive disorder: Results from a randomized, double-blind, controlled trial.

OBJECTIVE: Characterized by its disabling nature, obsessive compulsive disorder (OCD) affects individuals profoundly, with nearly 40% of patients showing resistance to initial treatment methods. Despite being safe and easily accessible, transcranial direct current stimulation (tDCS) lacks extensive substantiation supporting its efficacy in treating OCD. The objective of this study was to evaluate how cathodal high-definition transcranial direct current stimulation (HD-tDCS) applied to the right orbitofrontal cortex affected patients with OCD in terms of efficacy. METHOD: 47 patients with OCD were enrolled. They were randomly allocated to active or sham stimulation groups, and underwent HD-tDCS stimulation treatment for 2 weeks. The central electrode located in the right orbitofrontal cortex region was cathodic. The severity of the patients' obsessive-compulsive symptoms, depression and anxiety were assessed before and after treatment. RESULT: Out of the total, 44 patients concluded the treatment, comprising 23 participants from the active stimulation group and 21 from the sham stimulation group. Notably, substantial reductions in symptoms related to OCD, depression, and anxiety were exhibited in both groups. With a response rate of 26.1% in the active stimulation group and 23.8% in the sham stimulation group, there was no significant difference in efficacy observed. Furthermore, the reduction in depression and anxiety symptoms at the conclusion of the treatment was not notably superior in the active stimulation group. CONCLUSION: This study provided evidence for the acceptability and safety of HD-tDCS. Nevertheless, the study did not reveal notable clinical effectiveness of tDCS in addressing moderate to severe OCD in comparison to the sham stimulation group.

Effects of high-definition tDCS targeting individual motor hotspot with EMG-driven robotic hand training on upper extremity motor function: a pilot randomized controlled trial.

BACKGROUND: Delivering HD-tDCS on individual motor hotspot with optimal electric fields could overcome challenges of stroke heterogeneity, potentially facilitating neural activation and improving motor function for stroke survivors. However, the intervention effect of this personalized HD-tDCS has not been explored on post-stroke motor recovery. In this study, we aim to evaluate whether targeting individual motor hotspot with HD-tDCS followed by EMG-driven robotic hand training could further facilitate the upper extremity motor function for chronic stroke survivors. METHODS: In this pilot randomized controlled trial, eighteen chronic stroke survivors were randomly allocated into two groups. The HDtDCS-group (n = 8) received personalized HD-tDCS using task-based fMRI to guide the stimulation on individual motor hotspot. The Sham-group (n = 10) received only sham stimulation. Both groups underwent 20 sessions of training, each session began with 20 min of HD-tDCS and was then followed by 60 min of robotic hand training. Clinical scales (Fugl-meyer Upper Extremity scale, FMAUE; Modified Ashworth Scale, MAS), and neuroimaging modalities (fMRI and EEG-EMG) were conducted before, after intervention, and at 6-month follow-up. Two-way repeated measures analysis of variance was used to compare the training effect between HDtDCS- and Sham-group. RESULTS: HDtDCS-group demonstrated significantly better motor improvement than the Sham-group in terms of greater changes of FMAUE scores (F = 6.5, P = 0.004) and MASf (F = 3.6, P = 0.038) immediately and 6 months after the 20-session intervention. The task-based fMRI activation significantly shifted to the ipsilesional motor area in the HDtDCS-group, and this activation pattern increasingly concentrated on the motor hotspot being stimulated 6 months after training within the HDtDCS-group, whereas the increased activation is not sustainable in the Sham-group. The neuroimaging results indicate that neural plastic changes of the HDtDCS-group were guided specifically and sustained as an add-on effect of the stimulation. CONCLUSIONS: Stimulating the individual motor hotspot before robotic hand training could further enhance brain activation in motor-related regions that promote better motor recovery for chronic stroke. TRIAL REGISTRATION: This study was retrospectively registered in ClinicalTrials.gov (ID NCT05638464).

Feasibility of IAPWG protocol in performing high-definition three-dimensional anorectal manometry: A prospective, multicentric italian study.

BACKGROUND: The International Anorectal Physiology Working Group (IAPWG) suggests a standardized protocol to perform high-resolution anorectal manometry. The applicability and possible limitations of the IAPWG protocol in performing three-dimensional high-definition anorectal manometry (3D-ARM) have still to be extensively evaluated. METHODS: The IAPWG protocol was applied in performing 3D-ARM. Anorectal manometry (ARM) and a balloon expulsion test (BET) were performed according to IAPGW protocol in 290 patients. KEY RESULTS: A total of 84 males and 206 females (mean age 57.1 ± 15.7 years) were enrolled in six Italian centers. The reasons for which the patients were sent to perform 3D-ARM were: constipation (53.1%), fecal incontinence (26.9%), anal pain (3.1%), postsurgical (3.8%) and presurgical evaluation (4.8%), prolapse (3.4%), anal fissure (2.8%), and other (2.1%). Due to organic and functional conditions (low rectal anterior resections, rectal prolapses, and J-pouch after colectomy), we were unable to perform a complete 3D-ARM on six patients. Overall, a complete 3D-ARM and BET following IAPWG protocol was carried out in 284 patients (97.9%). The following were recorded: rest pressure (81.9 ± 32.0 mmHg) and length of the anal sphincter (37.0 ± 6.2 cm), maximum anal squeeze pressure (201.6 ± 81.3 mmHg), squeeze duration (22.0 ± 8.8 s), maximum rectal (48.7 ± 41.0 mmHg) and minimum anal pressure (73.3 ± 36.5 mmHg) during push, presence/absence of a dyssynergic pattern, cough reflex and rectal sensations (first constant sensation 48.4 ± 29.5 mL, desire to defecate 83.7 ± 52.1 mL, and maximum tolerated volume 149.5 ± 72.6 mL), and presence/absence of rectoanal inhibitory reflex. Mean 3D-ARM registration time was 14 min 7 s ± 3 min 12 s. CONCLUSIONS: This is the first multicentric study that evaluates the applicability of the IAPWG protocol in 3D-ARM performed in different manometric laboratories (both gastroenterological and surgical). The IAPWG protocol was easy to perform and was not time consuming. A diagnosis according to the London Classification was easily obtained in most patients in which 3D-ARM was carried out. No clear limitations to the applicability of the IAPWG protocol were detected.

Information System Model and Key Technologies of High-Definition Maps in Autonomous Driving Scenarios.

Background: High-definition maps can provide necessary prior data for autonomous driving, as well as the corresponding beyond-line-of-sight perception, verification and positioning, dynamic planning, and decision control. It is a necessary element to achieve L4/L5 unmanned driving at the current stage. However, currently, high-definition maps still have problems such as a large amount of data, a lot of data redundancy, and weak data correlation, which make autonomous driving fall into difficulties such as high data query difficulty and low timeliness. In order to optimize the data quality of high-definition maps, enhance the degree of data correlation, and ensure that they better assist vehicles in safe driving and efficient passage in the autonomous driving scenario, it is necessary to clarify the information system thinking of high-definition maps, propose a complete and accurate model, determine the content and functions of each level of the model, and continuously improve the information system model. Objective: The study aimed to put forward a complete and accurate high-definition map information system model and elaborate in detail the content and functions of each component in the data logic structure of the system model. Methods: Through research methods such as the modeling method and literature research method, we studied the high-definition map information system model in the autonomous driving scenario and explored the key technologies therein. Results: We put forward a four-layer integrated high-definition map information system model, elaborated in detail the content and functions of each component (map, road, vehicle, and user) in the data logic structure of the model, and also elaborated on the mechanism of the combined information of each level of the model to provide services in perception, positioning, decision making, and control for autonomous driving vehicles. This article also discussed two key technologies that can support autonomous driving vehicles to complete path planning, navigation decision making, and vehicle control in different autonomous driving scenarios. Conclusions: The four-layer integrated high-definition map information model proposed by this research institute has certain application feasibility and can provide references for the standardized production of high-definition maps, the unification of information interaction relationships, and the standardization of map data associations.

An Object-Centric Hierarchical Pose Estimation Method Using Semantic High-Definition Maps for General Autonomous Driving.

To achieve Level 4 and above autonomous driving, a robust and stable autonomous driving system is essential to adapt to various environmental changes. This paper aims to perform vehicle pose estimation, a crucial element in forming autonomous driving systems, more universally and robustly. The prevalent method for vehicle pose estimation in autonomous driving systems relies on Real-Time Kinematic (RTK) sensor data, ensuring accurate location acquisition. However, due to the characteristics of RTK sensors, precise positioning is challenging or impossible in indoor spaces or areas with signal interference, leading to inaccurate pose estimation and hindering autonomous driving in such scenarios. This paper proposes a method to overcome these challenges by leveraging objects registered in a high-precision map. The proposed approach involves creating a semantic high-definition (HD) map with added objects, forming object-centric features, recognizing locations using these features, and accurately estimating the vehicle's pose from the recognized location. This proposed method enhances the precision of vehicle pose estimation in environments where acquiring RTK sensor data is challenging, enabling more robust and stable autonomous driving. The paper demonstrates the proposed method's effectiveness through simulation and real-world experiments, showcasing its capability for more precise pose estimation.

Ultrasound and Helium Plasma-Assisted Liposuction for Body Contouring: A Single-Retrospective Cohort Study of 639 Patients.

BACKGROUND: Over the past two decades, liposuction techniques have significantly evolved, moving from basic fat removal to sophisticated methods aimed at improving safety, efficiency, and cosmetic outcomes. This study evaluates the efficacy and safety of a combined approach using ultrasound-assisted liposuction (UAL) and helium plasma radiofrequency (HPRF) technology to enhance skin tightening without the need for extensive surgical interventions. METHODS: We conducted a retrospective analysis of 639 patients who underwent the combined UAL and HPRF liposuction technique. The patient cohort had an average age of 31.5 years and a mean BMI of 27.9 kg/m2. The procedure predominantly targeted the abdomen, with an average of 2.4 body areas treated per patient. Surgical duration averaged 118 minutes, with a mean aspirate volume of 1698 mL. RESULTS: Minimal residual skin laxity was observed in 87% of patients, and 91% achieved excellent improvement in body contouring. The complication rates were low, with minor occurrences of seroma (5.6%) and a very low incidence of infection (0.3%). This combined technique demonstrated safety and efficacy, providing significant skin tightening and reducing recovery time compared to more invasive procedures. CONCLUSIONS: The combined use of UAL and HPRF technology offers a safe and effective method for enhancing skin tightening and improving body contouring outcomes. Despite the promising results, this study acknowledges the limitations of its retrospective design. Future prospective, multicenter studies are recommended to further validate these findings. This technique represents a significant advancement in the field of cosmetic surgery, emphasizing minimally invasive solutions with substantial esthetic benefits. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

A role for laparoscopy in the age of robotics: a retrospective cohort study of perioperative outcomes between 2D laparoscopic radical prostatectomy vs 3DHD laparoscopic radical prostatectomy.

PURPOSE: Our study compares perioperative outcomes between two-dimensional (2D) laparoscopic radical prostatectomy (LRP) and the 4th generation three-dimensional/high definition (3DHD) LRP. METHODS: Retrospectively acquired data from patients that underwent 2D LRP (n = 75) and 3DHD LRP (n = 75) from March 2013 to October 2015 were evaluated. Procedures were performed by a single surgeon. The extra-peritoneal approach with 5 trocars was utilized. Perioperative outcomes, potency, and continence were compared between groups. RESULTS: Patient characteristics were similar between the two groups in terms of age (p = 0.44), prostate-specific antigen (PSA) levels (p = 0.34), and Gleason scores (p = 0.14). Body mass index (BMI) was significantly higher in the 3DHD group (p = 0.0036). Postoperatively, no significant differences were observed in Hgb loss (p = 0.50), positive surgical margins (p = 1.00), and post-op Gleason scores (p = 0.30). Significant differences were observed for length of hospital stay (p < 0.001) and Jackson-Pratt (JP) drainage (p < 0.001). Regarding potency, 73.7% and 51.6% of the patients in the 3DHD and 2D groups regained potency at 6 months, respectively (p = 0.0025). Almost 43% of the patients in the 3DHD group regained continence at 1 month while for the 2D groups it was only 17.3% (p = 0.0008). CONCLUSION: 3DHD and 2D LRP have resulted in good outcomes in the perioperative periods. Our results show decreased JP drainage, shorter length of hospital stay, earlier return of urinary control, and earlier return of sexual function in the 3DHD LRP group. In lower volume centers where robotics equipment is not feasible due to economic barriers 3DHD can be safely performed as a minimally invasive alternative.

Effects of High-Definition Transcranial Direct Current Stimulation Targeting the Anterior Cingulate Cortex on the Pain Thresholds: A Randomized Controlled Trial.

BACKGROUND: The majority of existing clinical studies used active transcranial direct current stimulation (tDCS) over superficial areas of the pain neuromatrix to regulate pain, with conflicting results. Few studies have investigated the effect of tDCS on pain thresholds by focusing on targets in deep parts of the pain neuromatrix. METHODS: This study applied a single session of high-definition tDCS (HD-tDCS) targeting the anterior cingulate cortex (ACC) and used a parallel and sham-controlled design to compare the antinociceptive effects in healthy individuals by assessing changes in pain thresholds. Sixty-six female individuals (mean age, 20.5 ± 2.4 years) were randomly allocated into the anodal, cathodal, or sham HD-tDCS groups. The primary outcome of the study was pain thresholds (pressure pain threshold, heat pain threshold, and cold pain threshold), which were evaluated before and after stimulation through the use of quantitative sensory tests. RESULTS: Only cathodal HD-tDCS targeting the ACC significantly increased heat pain threshold (P < 0.05) and pressure pain threshold (P < 0.01) in healthy individuals compared with sham stimulation. Neither anodal nor cathodal HD-tDCS showed significant analgesic effects on cold pain threshold. Furthermore, no statistically significant difference was found in pain thresholds between anodal and sham HD-tDCS (P > 0.38). Independent of HD-tDCS protocols, the positive and negative affective schedule scores were decreased immediately after stimulation compared with baseline. CONCLUSIONS: The present study has found that cathodal HD-tDCS targeting the ACC provided a strong antinociceptive effect (increase in pain threshold), demonstrating a positive biological effect of HD-tDCS.

An efficient approach addressing the chemical complexity of Jiawei Fangji Huangqi decoction by integrating ultra-high-performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry and intelligent data processing workflows.

A challenge in the quality control of traditional Chinese medicine is the systematic multicomponent characterization of the compound formulae. Jiawei Fangji Huangqi, a modified form of Fangji Huangqi, is a prescription comprising seven herbal medicines. To address the chemical complexity of the Jiawei Fangji Huangqi decoction, we integrated ion mobility-quadrupole time-of-flight high-definition MSE coupled to ultra-high-performance liquid chromatography and intelligent data processing workflows available in the UNIFI software package. Good chromatographic separation was achieved on CORTECS UPLC T3 column within 52 min, and high-accuracy MS2 data were acquired using high-definition MSE in the negative and positive modes. A chemical library of 1250 compounds was created and incorporated into the UNIFI software to enable automatic peak annotation of the high-definition MSE data. We identified or tentatively characterize 430 compounds in the Jiawei Fangji Huangqi decoction. The potential superiority of high-definition MSE over conventional MS data acquisition approaches was revealed in its spectral quality (MS2 ), differentiation of isomers, separation of coeluting compounds, and target mass coverage. The multiple components of the Jiawei Fangji Huangqi decoction were elucidated, offering insight into its improved pharmacological action compared with that of the Fangji Huangqi formula.

Correlation between characteristics of intracranial atherosclerotic plaques and ischemic stroke in high-resolution vascular wall MRI.

BACKGROUND: Intracranial atherosclerotic stenosis is a major cause of ischemic stroke, accounting for 30% of ischemic strokes in Asian populations. PURPOSE: To investigate the relationship between the degree of arterial stenosis and enhancement grade of intracranial atherosclerotic disease (ICAD), the plaque characteristics in different remodeling patterns, and its potential impact. MATERIAL AND METHODS: A total of 210 patients diagnosed with ICAD were enrolled in this retrospective study. Patients were divided into the middle cerebral artery (MCA) group (101 cases), posterior cerebral artery (PCA) group (14 cases), basilar artery (BA) group (71 cases), and intracranial segment of vertebral artery (VA) group (90 cases) according to the difference of diseased vessels. Data on presence or absence of ischemic infarction, intracranial vascular position of lesions, plaque characteristics, ICAD enhancement grade, remodeling index, and degree of arterial stenosis were collected for analysis. RESULTS: The incidence of ischemic infarction in enhancement grade 2 was significantly higher than that in enhancement grade 1 in MCA group (P = 0.019). Enhancement grade 2 of ICAD was an independent risk factor for the development of ischemic infarction (odds ratio = 4.60; 95% confidence interval: 1.91-11.03; P = 0.001). There was no significant statistical difference in infarct rate between different remodeling modalities (P>0.05). CONCLUSION: Enhancement grade of ICAD is significantly associated with the degree of stenosis and the occurrence of ischemic stroke, which varies in different intracranial vessels. The pattern of vascular remodeling varies among different intracranial vessels, and the pattern of vascular remodeling has a significant impact on plaque characteristics.

Blind Video Quality Assessment for Ultra-High-Definition Video Based on Super-Resolution and Deep Reinforcement Learning.

Ultra-high-definition (UHD) video has brought new challenges to objective video quality assessment (VQA) due to its high resolution and high frame rate. Most existing VQA methods are designed for non-UHD videos-when they are employed to deal with UHD videos, the processing speed will be slow and the global spatial features cannot be fully extracted. In addition, these VQA methods usually segment the video into multiple segments, predict the quality score of each segment, and then average the quality score of each segment to obtain the quality score of the whole video. This breaks the temporal correlation of the video sequences and is inconsistent with the characteristics of human visual perception. In this paper, we present a no-reference VQA method, aiming to effectively and efficiently predict quality scores for UHD videos. First, we construct a spatial distortion feature network based on a super-resolution model (SR-SDFNet), which can quickly extract the global spatial distortion features of UHD videos. Then, to aggregate the spatial distortion features of each UHD frame, we propose a time fusion network based on a reinforcement learning model (RL-TFNet), in which the actor network continuously combines multiple frame features extracted by SR-SDFNet and outputs an action to adjust the current quality score to approximate the subjective score, and the critic network outputs action values to optimize the quality perception of the actor network. Finally, we conduct large-scale experiments on UHD VQA databases and the results reveal that, compared to other state-of-the-art VQA methods, our method achieves competitive quality prediction performance with a shorter runtime and fewer model parameters.

Investigating the Improvement of Autonomous Vehicle Performance through the Integration of Multi-Sensor Dynamic Mapping Techniques.

The emergence of autonomous vehicles marks a shift in mobility. Conventional vehicles have been designed to prioritize the safety of drivers and passengers and increase fuel efficiency, while autonomous vehicles are developing as convergence technologies with a focus on more than just transportation. With the potential for autonomous vehicles to serve as an office or leisure space, the accuracy and stability of their driving technology is of utmost importance. However, commercializing autonomous vehicles has been challenging due to the limitations of current technology. This paper proposes a method to build a precision map for multi-sensor-based autonomous driving to improve the accuracy and stability of autonomous vehicle technology. The proposed method leverages dynamic high-definition maps to enhance the recognition rates and autonomous driving path recognition of objects in the vicinity of the vehicle, utilizing multiple sensors such as cameras, LIDAR, and RADAR. The goal is to improve the accuracy and stability of autonomous driving technology.

Online Quantitative Analysis of Perception Uncertainty Based on High-Definition Map.

Environmental perception plays a fundamental role in decision-making and is crucial for ensuring the safety of autonomous driving. A pressing challenge is the online evaluation of perception uncertainty, a crucial step towards ensuring the safety and the industrialization of autonomous driving. High-definition maps offer precise information about static elements on the road, along with their topological relationships. As a result, the map can provide valuable prior information for assessing the uncertainty associated with static elements. In this paper, a method for evaluating perception uncertainty online, encompassing both static and dynamic elements, is introduced based on the high-definition map. The proposed method is as follows: Firstly, the uncertainty of static elements in perception, including the uncertainty of their existence and spatial information, was assessed based on the spatial and topological features of the static environmental elements; secondly, an online assessment model for the uncertainty of dynamic elements in perception was constructed. The online evaluation of the static element uncertainty was utilized to infer the dynamic element uncertainty, and then a model for recognizing the driving scenario and weather conditions was constructed to identify the triggering factors of uncertainty in real-time perception during autonomous driving operations, which can further optimize the online assessment model for perception uncertainty. The verification results on the nuScenes dataset show that our uncertainty assessment method based on a high-definition map effectively evaluates the real-time perception results' performance.

An Efficient Deep Learning-Based High-Definition Image Compressed Sensing Framework for Large-Scene Construction Site Monitoring.

High-definition images covering entire large-scene construction sites are increasingly used for monitoring management. However, the transmission of high-definition images is a huge challenge for construction sites with harsh network conditions and scarce computing resources. Thus, an effective compressed sensing and reconstruction method for high-definition monitoring images is urgently needed. Although current deep learning-based image compressed sensing methods exhibit superior performance in recovering images from a reduced number of measurements, they still face difficulties in achieving efficient and accurate high-definition image compressed sensing with less memory usage and computational cost at large-scene construction sites. This paper investigated an efficient deep learning-based high-definition image compressed sensing framework (EHDCS-Net) for large-scene construction site monitoring, which consists of four parts, namely the sampling, initial recovery, deep recovery body, and recovery head subnets. This framework was exquisitely designed by rational organization of the convolutional, downsampling, and pixelshuffle layers based on the procedures of block-based compressed sensing. To effectively reduce memory occupation and computational cost, the framework utilized nonlinear transformations on downscaled feature maps in reconstructing images. Moreover, the efficient channel attention (ECA) module was introduced to further increase the nonlinear reconstruction capability on downscaled feature maps. The framework was tested on large-scene monitoring images from a real hydraulic engineering megaproject. Extensive experiments showed that the proposed EHDCS-Net framework not only used less memory and floating point operations (FLOPs), but it also achieved better reconstruction accuracy with faster recovery speed than other state-of-the-art deep learning-based image compressed sensing methods.