Intuitive Information Research Articles

Intuitive Spatial Tactile Feedback for Better Awareness about Robot Trajectory during Human-Robot Collaboration.

In this work, we extend the previously proposed approach of improving mutual perception during human–robot collaboration by communicating the robot’s motion intentions and status to a human worker using hand-worn haptic feedback devices. The improvement is presented by introducing spatial tactile feedback, which provides the human worker with more intuitive information about the currently planned robot’s trajectory, given its spatial configuration. The enhanced feedback devices communicate directional information through activation of six tactors spatially organised to represent an orthogonal coordinate frame: the vibration activates on the side of the feedback device that is closest to the future path of the robot. To test the effectiveness of the improved human–machine interface, two user studies were prepared and conducted. The first study aimed to quantitatively evaluate the ease of differentiating activation of individual tactors of the notification devices. The second user study aimed to assess the overall usability of the enhanced notification mode for improving human awareness about the planned trajectory of a robot. The results of the first experiment allowed to identify the tactors for which vibration intensity was most often confused by users. The results of the second experiment showed that the enhanced notification system allowed the participants to complete the task faster and, in general, improved user awareness of the robot’s movement plan, according to both objective and subjective data. Moreover, the majority of participants (82%) favoured the improved notification system over its previous non-directional version and vision-based inspection.

Modified Takazawa anatomical classification of renal pelvicalyceal system based on three-dimensional virtual reconstruction models.

BackgroundPrevious classification of renal pelvicalyceal anatomical structure may be difficult to intuitively understand and unpractical for endourological surgery. We aim to put forward a modified Takazawa anatomical classification of renal pelvicalyceal system based on three-dimensional (3D) virtual reconstruction models for endourological surgery.MethodsWe retrospectively collected data on 225 patients (320 kidneys) in total between Apr. 2017 and Dec. 2020, spatial anatomical structure of renal pelvis and calyces were modeled and corresponding morphological parameters were measured after 3D virtual reconstruction of computed tomography urography (CTU). The modified Takazawa renal pelvicalyceal anatomical classification was advanced based on the renal pelvicalyceal morphological parameters [bifurcated branches of renal pelvis, cross sectional area of renal pelvis and ureteropelvic junction (UPJ), infundibuloureteral angle (IUA), lower pole infundibular calyceal length (IL)] by 3D virtual reconstruction models, and comparison of renal pelvicalyceal system morphological parameters were performed to evaluate the differences in various classification types of renal pelvis and calyces.ResultsAnatomical structure of renal pelvis and calyces were divided into two main types (Type A and Type B) according to renal pelvic branch patterns. A single pelvis without bifurcated branch was regarded as Type A (62%) and subclassified into three subtypes: Type A1 (22%), Type A2 (27%) and Type A3 (13%), the slimline pelvis was classified as Type A1, the typical pelvis as Type A2 and the broad pelvis as Type A3. A divided pelvis with bifurcated branches was seen as Type B (38%) and subclassified into two subtypes: Type B1 (15%) with the wide and flat lower calyx branch, Type B2 (23%) with the narrow and steep lower calyx branch.ConclusionsPrevious studies have reported that the visualization and classification of renal pelvicalyceal anatomical structure by endocast, autopsy, ultrasonography and excretory urography, the modified Takazawa classification system based on 3D virtual reconstruction models enables to standardized different anatomical morphology of renal pelvicalyceal system and provide intuitive and concise information on anatomy, thus leading to the improvement in treatment modality.

High-resolution functional photoacoustic monitoring of vascular dynamics in human fingers

Functional imaging of microvascular dynamics in extremities delivers intuitive information for early detection, diagnosis, and prognosis of vascular diseases. High-resolution and high-speed photoacoustic microscopy (PAM) visualizes and measures multiparametric information of microvessel networks in vivo such as morphology, flow, oxygen saturation, and metabolic rate. Here, we demonstrate high-resolution photoacoustic monitoring of vascular dynamics in human fingers. We photoacoustically monitored the position displacement of blood vessels associated with arterial pulsation in human fingers. Then, during and after arterial occlusion, we photoacoustically quantified oxygen consumption and blood perfusion in the fingertips. The results demonstrate that high-resolution functional PAM could be a vital tool in peripheral vascular examination for measuring heart rate, oxygen consumption, and/or blood perfusion.

PlantscRNAdb: A database for plant single-cell RNA analysis

PlantscRNAdb: A database for plant single-cell RNA analysis

Clinical Intuition under Scrutiny: From Potholes to Possibilities

ABSTRACT The two commentaries on “Varieties of Clinical Intuition: Explicit, Implicit, and Nonlocal Neurodynamics” approach the subject from radically different perspectives. While de Peyer focuses on clinical aspects of utilizing local and nonlocal informational channels within analytic work, Butler brings up wider socio-political implications involved in the collaboration between psychoanalysis and the natural sciences. We affirm Butler’s social justice agenda while taking issue with his unwitting form of reductionism inherent in his post-modernist argument for hermeneutics in rejection of science’s role in psychoanalysis and confusion about different levels of self-organization in informational dynamics. We are entirely in agreement with de Peyer’s suggestion that affect is the connecting thread between all forms of intuition, including its uncanny dimensions. Our fractal epistemology supports her suggestion of fuzzy boundaries between local-interactive and nonlocal-participatory forms of intuitive knowing. We end with de Peyer’s questions surrounding the clinical value of intuitive information sharing, methods for its enhancement, and the importance of clinical judgment in working with “extraordinary knowing.”

42‐2: Distinguished Paper: Effects of Luminance Contrast and Font Size on Dual‐Plane HUD Legibility (“The Double 007 Rule for HUDs”)

Head‐up displays (HUDs) can provide important driving information such as speed and navigation directly to a driver within their immediate field of view, and thus improve driving experience. Specifically, a dual‐plane AR‐HUD can provide drivers with larger images with richer information, more intuitive information presentation, and enhanced navigation features. To ensure driver comfort, proper presentation format of the text on the dual‐plane HUD needs to be investigated. A human factors experiment was conducted to explore proper luminance contrast and font size of the text on a HUD. Twenty older and nine mid‐age drivers were instructed to recognize letters in fourteen levels of font size under each of eight levels of luminance contrast (ranging from 1.2:1, to 8:1) on each plane. The best test performance was observed at a luminance contrast of 7:1. We report the minimum and upper bound of 95% confidence interval of legible vertical visual angle for 99.5% of older drivers at each level of luminance contrast. While the typical legibility rule of thumb for font height vs. distance on standard displays is .007 (also known as the Bond rule), our experiment suggests that double that size (0.014) was needed to cover 99.5% of older drivers at a contrast ratio of 1.2:1 on a HUD.

Automatic identification of sweet spots from MERs for electrodes implantation in STN-DBS.

Microelectrode recordings (MERs) are a significant clinical indicator for sweet spots identification of implanted electrodes during deep brain stimulation of the subthalamic nucleus (STN) surgery. As 1D MERs signals have the unboundedness, large-range, large-amount and time-dependent characteristics, the purpose of this study is to propose an automatic and precise identification method of sweet spots from MERs, reducing the time-consuming and labor-intensive human annotations. We propose an automatic identification method of sweet spots from MERs for electrodes implantation in STN-DBS. To better imitate the surgeons' observation and obtain more intuitive contextual information, we first employ the 2D Gramian angular summation field (GASF) images generated from MERs data to perform the sweet spots determination for electrodes implantation. Then, we introduce the convolutional block attention module into convolutional neural network (CNN) to identify the 2D GASF images of sweet spots for electrodes implantation. Experimental results illustrate that the identification result of our method is consistent with the result of doctor's decision, while our method can achieve the accuracy and precision of 96.72% and 98.97%, respectively, which outperforms state-of-the-art for intraoperative sweet spots determination. The proposed method is the first time to automatically and accurately identify sweet spots from MERs for electrodes implantation by the combination an advanced time series-to-image encoding way with CBAM-enhanced networks model. Our method can assist neurosurgeons in automatically detecting the most likely locations of sweet spots for electrodes implantation, which can provide an important indicator for target selection while it reduces the localization error of the target during STN-DBS surgery.

Effects of luminance contrast and font size on dual‐plane head‐up display legibility (“The Double 007 Rule for HUDs”)

AbstractHead‐up displays (HUDs) can provide important driving information such as speed and navigation directly to a driver within their immediate field of view. Specifically, a dual‐plane AR‐HUD can provide drivers with larger images with richer information, more intuitive information presentation, and enhanced navigation features. To ensure driver comfort, proper presentation format of the text on the dual‐plane HUD needs to be investigated. A human factors experiment was conducted to explore proper luminance contrast and font size of the text on a HUD. Twenty older and nine mid‐age drivers were instructed to recognize letters in 14 levels of font size under each of eight levels of luminance contrast (ranging from 1.2:1, to 8:1) on each plane. The best test performance was observed at a luminance contrast of 7:1. We report the minimum and upper bound of 95% confidence interval of legible vertical visual angle for 99.5% of older drivers at each luminance contrast level. Although the typical legibility rule of thumb for font height versus distance on standard displays is 0.007 (known as the Bond rule), our experiment suggests that double that size (0.014) was needed to cover 99.5% of older drivers at a contrast ratio of 1.2:1 on a HUD.

In vivoMulti-scalePhotoacoustic Imaging Guided Photothermal Therapy of Cervical Cancer based on Customized Laser System and Targeted Nanoparticles.

BackgroundEffective treatment strategy for cervical carcinoma is subject to the limitation of its anatomical location and histological characteristics. Comprehensive imaging before cervical carcinoma treatment is of great significance for the patients. Current imaging methods cannot meet the requirements of high resolution, deep imaging depth and non-invasive imaging at the same time. Fortunately, Photoacoustic imaging (PAI) is a novel imaging method that combines rich optical contrast, high ultrasonic spatial resolution, and deep penetration depth in a single modality. Moreover, PAI-guided photothermal therapy (PTT) by aid of targeting nanoparticles is an emerging and effective cancer treatment in recent years.MethodsHere, strong near-infrared region (NIR) absorption-conjugated polymer PIIGDTS (PD) nanoparticles with folic acid (FA) modification (namely, PD-FA) that targeted at Hela cell were specifically designed as cervical tumor imaging contrast agents and photothermal agents.ResultsThe obtained PD-FA nanoparticles exhibited admirable photoacoustic contrast-enhancing ability and desirable PTT behavior with the photothermal conversion efficiency as high as 62.6% in vitro. Furthermore, the PAI performance and PTT efficiency were tested in HeLa tumor-bearing nude mice after injection of PD-FA nanoparticles. In vivo multi-scale, PAI provided B-san and 3D dimension imaging for intuitive and comprehensive information of Hela tumor. Moreover, the Hela tumor can be completely eliminated within 18 days after PTT, with no toxicity and side effects.ConclusionIn summary, PD-FA injection combined with PAI and PTT systems provides a novel powerful tool for early diagnosis and precise treatment of cervical cancer.

3D Reconstruction and Augmented Reality Display of Bone Structure Based on Ultrasound Segmentation with Feature-Reweighted U-Net

<p indent=0mm>During the minimally invasive orthopedic surgery, surgeons insert surgical instruments under the guidance of two-dimensional (2D) X-ray images of bone structures that displayed on a screen. This method not only lacks of intuitive three-dimensional (3D) information, but also exposes patients and surgeons to significant amounts of ionizing radiations. To solve these problems, this paper proposes 3D reconstruction and augmented reality display of bone structure based on Free-hand ultrasound segmentation with feature-reweighted U-Net, and provides doctors with 3D bone structure for radiation-free surgical navigation. Firstly, a feature-reweighted U-Net is developed for accurate segmentation of bone surfaces from Free-hand ultrasound scans. Then, the segmented bone surfaces are reconstructed to acquire 3D bone structure according to the locations of ultrasound images. Finally, the bone structure is further rendered using integral photography techniques for augmented reality guidance. The experiments are finished on ultrasound data set of phantom and patients. The bone segmentation accuracy of (88.51±1.44)% and bone reconstruction error of <sc>(1.29±0.11) mm</sc> are acquired during the experiments. The proposed method can provide surgeons with intuitive intraoperative 3D navigation information.

FOPR test: a virtual reality-based technique to assess field of perception and field of regard in hemispatial neglect

BackgroundWe previously proposed a novel virtual reality-based method to assess human field of perception (FOP) and field of regard (FOR), termed the FOPR test. This study assessed the diagnostic validity of the FOPR test for hemispatial neglect (HSN).MethodsWe included 19 stroke patients with a lesion in the right hemisphere and with HSN (HSN+SS), 22 stroke patients with a lesion in the right hemisphere and without HSN (HSN−SS), and 22 healthy controls aged 19–65 years. The success rate (SR) and response time (RT) in the FOPR test for both FOP and FOR were assessed (FOP-SR, FOR-SR, FOP-RT, and FOR-RT, respectively). Using a Bland–Altman plot, agreements between the FOPR test and conventional tests were confirmed, and the FOPR test accuracy was verified using the support vector machine (SVM). Measured values were analysed using ANOVA and Kruskall–Wallis tests for group comparison.ResultsThe Bland–Altman plot showed good agreement between FOPR test and conventional tests; individuals within 95% agreement limits were within the range of 94.8–100.0%. The SVM classification accuracy, using FOP and FOR variables from the left hemispace, ranged from 83.3 to 100.0% in a binary classification (HSN vs non-HSN). The FOPR test demonstrated differences in SR and RT for both FOP and FOR across the groups.ConclusionThe FOPR test was valid for the HSN diagnosis and provided quantitative and intuitive information regarding visuospatial function. Furthermore, it might enhance our understanding of visuospatial function including HSN by applying the time relative component and concepts of perception and exploration, FOP and FOR.Trial registration: NCT03463122. Registered 13 March 2018, retrospectively registered.

COVID-19 Pandemic: Stock Markets Reaction to the Mortality Rates and Lockdown Policies

The coronavirus (COVID-19) pandemic is disrupting the world as we knew it, with a heavy toll on economic activities and the structure of politics. Governments, media websites, and research institutions update information about the changes in the COVID-19 epidemic every day. The most intuitive information may be the changes in the number of confirmed cases and deaths, which shape investors’ sentiments and confidence in the financial markets. The goal of this study is to investigate the impact of new mortality rates of COVID-19 on the UK and US stock markets over the period January 1 – September 30, 2020. We employed a simple regression model to examine whether new mortality rates contain information beyond the lagged market volatility. By constructing a lockdown dummy variable, we further control for the impact of government lockdown policies on market volatility in our model. Our findings show that new mortality rates caused by COVID-19 pandemic have significant positive impact on volatility of the UK and the US stock markets. We also find that the implementation of lockdown policies provided by the governments reduced the effects of new mortality rates on stock market volatility. In addition, our results are robust to other measurements of volatility. Together our findings suggest that new mortality rates do matter for stock market volatility of these two markets, and lockdown policies mitigate market volatile caused by new mortality rates.

Design and implementation of remote image processing system for space launch site

Telemetry image has the characteristics of intuitive image in the process of rocket flight. Through real-time acquisition of rocket flight video image, it can provide the working status of key nodes in the process of rocket flight, and provide intuitive decision-marking auxiliary information for commanders. This paper analyzes the design content of the image processing system of the space launch site from the aspects of image transmission mechanism, information flow, image data processing and image decoding, so as to provide technical basis for the image receiving, transmission and decoding process in the engineering practice of the image processing system.

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and deep learning techniques are valuable resources in achieving this identification. We propose automated techniques that can process raw EEG waveforms to identify children who may have an increased risk of schizophrenia compared to typically developing children. We also analyse abnormal features that remain during developmental follow-up over a period of ∼4 years in children with a vulnerability to schizophrenia initially assessed when aged 9 to 12 years. EEG data from participants were captured during the recording of a passive auditory oddball paradigm. We undertake a holistic study to identify brain abnormalities, first by exploring traditional machine learning algorithms using classification methods applied to hand-engineered features (event-related potential components). Then, we compare the performance of these methods with end-to-end deep learning techniques applied to raw data. We demonstrate via average cross-validation performance measures that recurrent deep convolutional neural networks can outperform traditional machine learning methods for sequence modeling. We illustrate the intuitive salient information of the model with the location of the most relevant attributes of a post-stimulus window. This baseline identification system in the area of mental illness supports the evidence of developmental and disease effects in a pre-prodromal phase of psychosis. These results reinforce the benefits of deep learning to support psychiatric classification and neuroscientific research more broadly.

Random Region Matting for the High-Resolution PolSAR Image Semantic Segmentation

Polarimetric synthetic aperture radar (PolSAR) imagery can provide more intuitive and detailed SAR polarization information, and it is widely used in the classification and semantic segmentation of remote sensing. To bridge the PolSAR data and application, the 2020 Gaofen Challenge on Automated High-Resolution Earth Observation Image Interpretation provides a set of high-quality PolSAR semantic segmentation dataset. A series of preprocessing methods is first used to analyze the PolSAR images to improve the semantic segmentation performance of the PolSAR imagery. A special polarimetric decomposition method is used to extract the features, and the filter and the data truncation are implemented to enhance local and global information of images. And the random region matting method is proposed to expand the training samples. Finally, the DeepLabV3+ method with the ResNet101-V2 is employed to achieve the semantic segmentation. A variety of comparison experiments verifies the effectiveness of our methods. Simultaneously, compared with the classification methods of other groups in the competition, our methods have obvious advantages in the inference time and semantic segmentation accuracy. The proposed method achieved a frequency weighted intersection over union of 75.29% in the contest.

Augmented Holographic HPB Surgical Navigation Using Extended Reality: XR (VR/AR/MR)

Surgical navigation have become essential for surgeons to accurately and safely perform HPB operations. HPB surgery requires a high degree of spatial awareness and orientation because of complex anatomies and procedures. The traditional navigation for HPB surgery was displayed only for 2D observation on a flat screen by surgeons, the image-based navigation interface is separated from the operating area, and the surgeon needs to switch the field of vision between the screen and the patient´s lesion area. We developed extended reality (XR) navigation that combines virtual reality (VR), augmented reality (AR), and mixed reality (MR), and holographic technology for HPB surgery to provide more spatial and intuitive information to surgeons. From patient´s individual CT data, organs and abnormal lesions were extracted into individually colored 3D polygons, and represented into real space with a transparent holographic wearable glasses built-in position sensors (HoloLens and MagicLeap) using our original XR application. In Results, each organ was floated in the actual surgical space These holographic organ models were able to share and move freely in all directions by gesture interface, and complex procedures could be confirmed with pointing by all surgeons. The ability to spatial awareness for understanding the extent of resection, blood vessel processing, and lymph node dissection were improved during surgery. Our XR navigation system has high accuracy and stability for registration. Our patient-specific XR surgical navigation is highly effective and reduce surgical time, blood loss, and adverse event. This system must have value for future HPB surgeons

An Ice Core Slice Scanning Tool based on Line-scan Camera

The ice core from polar ice sheet is one of the most valuable archives of past climate and environment. The ice core visual stratigraphy, based on optical scanning analysis, provides the most intuitive information of the micro-particles and/or air bubbles in the ice. At present, only few labs can perform high quality visual stratigraphy analysis in the world. Here, we develop an ice core slice scanning tool based on line-scan camera. The machine uses the high-resolution characteristics of the line-scan camera to complete high-resolution imaging of the ice core slices through linkage with the linear light sources. A motor drive and control system is developed to complete the uniform scanning control of the line-scan camera and light sources. A special control program and human-computer interaction interface are developed to realize the parameter setting, motor control and imaging result display. The test results show that the proposed ice core slice scanning tool meets the design requirements and its imaging results are significantly better than area-scan cameras under the same conditions.

The Effect of Risk Representation Using Colors and Symbols in Business Process Models on Operational Risk Management Performance

The operational management of risk and internal controls (RIC) makes increasing use of visual representations to support tasks such as risk assessment and control activity definition. The strengths and weaknesses of different representations are typically assessed by cognitive theories that assume an analytical and an intuitive mode of information processing. Previous research has focused mainly on the analytical risk assessment while intuitive information processing has largely been neglected. We develop a theoretical argument based on dual-process theory, which explains why RIC representational alternatives influence different levels of information processing. We test our hypotheses with the help of an online experiment using accountants and operation managers recruited via MTurk (N = 166). Our results suggest that highlighting risk and controls in business process modeling and notation (BPMN) by using color improves risk understanding, control understanding, and the identification of control improvements, which help reduce the risk in a given process. Furthermore, we do not find evidence that the inclusion of color leads to perception biases. This has implications for information systems research, which has primarily addressed the analytical processing of conceptual models. Our findings extend cognitive research on such models by adding an intuitive processing path that can improve the user’s risk management performance. For practitioners, our findings are particularly relevant because colors can be easily added as a secondary notation element without disguising the factual risk situation in processes.

Visualization System for Traffic Accident Data

At present, the traffic problem is a problem that the government attaches great importance to. Many papers also put forward their own visualization models for traffic problems. This research focused on the Map-matching and Spatial-temporal Visualization of Expressway Traffic Accident Information and improves the original two-dimensional visual model of accident rate into a three-dimensional model. The goal is to represent more attributes in a visual model and make them easier to compare, so as to provide users with more intuitive visual information.

Intuitive Judgments in Depression and the Role of Processing Fluency and Positive Valence: A Preregistered Replication Study.

Recent preliminary evidence indicates that depression is associated with impaired intuitive information processing. The current study aimed at replicating these findings and to move one step further by exploring whether factors known as triggering intuition (positivity, processing fluency) also affect intuition in patients with depression. We pre-registered and tested five hypotheses using data from 35 patients with depression and 35 healthy controls who performed three versions of the Judgment of Semantic Coherence Task (JSCT, Bowers et al., 1990). This task operationalizes intuition as the inexplicable and sudden detection of semantic coherence. Results revealed that depressed patients and healthy controls did not differ in their general intuitive performance (Hypothesis 1). We further found that fluency did not significantly affect depressed patients' coherence judgments (H2a) and that the assumed effect of fluency on coherence judgments was not moderated by depression (H2b). Finally, we found that triads positive in valence were more likely to be judged as coherent as compared to negative word triads in the depressed sample (H3a), but this influence of positive (vs. negative) valence on coherence judgments did not significantly differ between the two groups (H3b). Overall the current study did not replicate findings from previous research regarding intuitive semantic coherence detection deficits in depression. However, our findings suggest that enhancing positivity in depressed patients may facilitate their ability to see meaning in their environment and to take intuitive decision.