HM-Array: A Novel Haptic Magnetism-based Leader-follower Platform for Minimally Invasive Robotic Surgery.

Ensuring the safety and authenticity of haptic feed2 back is crucial in the domain of surgical operations, particularly in procedures like Natural Orifice Transluminal Endoscopic Surgery (NOTES) and Minimally Invasive Robotic Surgery (MIRS). To enhance the control efficiency of the robotic operating console, we propose a haptic magnetism-based array (HM7 Array). This system employs a solenoid array and a detection stylus to achieve controller localization without the need for additional sensors, while simultaneously generating haptic effects.

Update on a brain-penetrant cardiac glycoside that can lower cellular prion protein levels in human and guinea pig paradigms.

Lowering the levels of the cellular prion protein (PrPC) is widely considered a promising strategy for the treatment of prion diseases. Building on work that established immediate spatial proximity of PrPC and Na+, K+-ATPases (NKAs) in the brain, we recently showed that PrPC levels can be reduced by targeting NKAs with their natural cardiac glycoside (CG) inhibitors. We then introduced C4'-dehydro-oleandrin as a CG with improved pharmacological properties for this indication, showing that it reduced PrPC levels by 84% in immortalized human cells that had been differentiated to acquire neural or astrocytic characteristics.

The importance of prion research.

Over the past four decades, prion diseases have received considerable research attention owing to their potential to be transmitted within and across species as well as their consequences for human and animal health. The unprecedented nature of prions has led to the discovery of a paradigm of templated protein misfolding that underlies a diverse range of both disease-related and normal biological processes. Indeed, the "prion-like" misfolding and propagation of protein aggregates is now recognized as a common underlying disease mechanism in human neurodegenerative disorders such as Alzheimer's and Parkinson's disease, and the prion principle has led to the development of novel diagnostic and therapeutic strategies for these illnesses.

Confusion Region Mining for Crowd Counting.

Existing works mainly focus on crowd and ignore the confusion regions which contain extremely similar appearance to crowd in the background, while crowd counting needs to face these two sides at the same time. To address this issue, we propose a novel end-to-end trainable confusion region discriminating and erasing network called CDENet. Specifically, CDENet is composed of two modules of confusion region mining module (CRM) and guided erasing module (GEM).

Nowhere to Disguise: Spot Camouflaged Objects via Saliency Attribute Transfer.

Both salient object detection (SOD) and camouflaged object detection (COD) are typical object segmentation tasks. They are intuitively contradictory, but are intrinsically related. In this paper, we explore the relationship between SOD and COD, and then borrow successful SOD models to detect camouflaged objects to save the design cost of COD models.

Interactive Feature Embedding for Infrared and Visible Image Fusion.

General deep learning-based methods for infrared and visible image fusion rely on the unsupervised mechanism for vital information retention by utilizing elaborately designed loss functions. However, the unsupervised mechanism depends on a well-designed loss function, which cannot guarantee that all vital information of source images is sufficiently extracted. In this work, we propose a novel interactive feature embedding in a self-supervised learning framework for infrared and visible image fusion, attempting to overcome the issue of vital information degradation.

Defocus Blur Detection Attack via Mutual-Referenced Feature Transfer.

Benefiting from deep learning, defocus blur detection (DBD) has made prominent progress. Existing DBD methods generally study multiscale and multilevel features to improve performance. In this article, from a different perspective, we explore to generate confrontational images to attack DBD network.

Cardiac glycoside-mediated turnover of Na, K-ATPases as a rational approach to reducing cell surface levels of the cellular prion protein.

It is widely anticipated that a reduction of brain levels of the cellular prion protein (PrPC) can prolong survival in a group of neurodegenerative diseases known as prion diseases. To date, efforts to decrease steady-state PrPC levels by targeting this protein directly with small molecule drug-like compounds have largely been unsuccessful. Recently, we reported Na,K-ATPases to reside in immediate proximity to PrPC in the brain, unlocking an opportunity for an indirect PrPC targeting approach that capitalizes on the availability of potent cardiac glycosides (CGs).

RAD-seq as an effective strategy for heterogenous variety identification in plants-a case study in Italian Ryegrass (Lolium multiflorum).

The primary approach for variety distinction in Italian ryegrass is currently the DUS (distinctness, uniformity and stability) test based on phenotypic traits. Considering the diverse genetic background within the population and the complexity of the environment, however, it is challenging to accurately distinguish varieties based on DUS criteria alone. In this study, we proposed the application of high-throughput RAD-seq to distinguish 11 Italian ryegrass varieties with three bulks of 50 individuals per variety.

SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data.

Convolutional neural networks (CNNs) have shown promising results in classifying individuals with mental disorders such as schizophrenia using resting-state fMRI data. However, complex-valued fMRI data is rarely used since additional phase data introduces high-level noise though it is potentially useful information for the context of classification. As such, we propose to use spatial source phase (SSP) maps derived from complex-valued fMRI data as the CNN input.

The cellular prion protein interacts with and promotes the activity of Na,K-ATPases.

The prion protein (PrP) is best known for its ability to cause fatal neurodegenerative diseases in humans and animals. Here, we revisited its molecular environment in the brain using a well-developed affinity-capture mass spectrometry workflow that offers robust relative quantitation. The analysis confirmed many previously reported interactions.

Three mutations repurpose a plant karrikin receptor to a strigolactone receptor.

Uncovering the basis of small-molecule hormone receptors' evolution is paramount to a complete understanding of how protein structure drives function. In plants, hormone receptors for strigolactones are well suited to evolutionary inquiries because closely related homologs have different ligand preferences. More importantly, because of facile plant transgenic systems, receptors can be swapped and quickly assessed functionally in vivo.

Defocus Blur Detection via Boosting Diversity of Deep Ensemble Networks.

Existing defocus blur detection (DBD) methods usually explore multi-scale and multi-level features to improve performance. However, defocus blur regions normally have incomplete semantic information, which will reduce DBD's performance if it can't be used properly. In this paper, we address the above problem by exploring deep ensemble networks, where we boost diversity of defocus blur detectors to force the network to generate diverse results that some rely more on high-level semantic information while some ones rely more on low-level information.

The effects of physical photostimulable phosphor plate artifacts on the radiologic interpretation of periapical inflammatory disease.

Objective: To evaluate how physical photostimulable phosphor (PSP) plate artifacts, such as those created by scratches, phosphor degradation, and surface peeling, affect the radiologic interpretation of periapical inflammatory disease.

Study Design: A novel technique was developed to digitally superimpose 25 real PSP artifact masks over 100 clinical complementary metal oxide semiconductor (CMOS) periapical images with known radiologic interpretations. These images were presented to 25 general dentists, who were asked to state their radiologic interpretations, their confidence in their interpretations, and their opinions on whether the plates should be discarded.

Towards weakly-supervised focus region detection via recurrent constraint network.

Recent state-of-the-art methods on focus region detection (FRD) rely on deep convolutional networks trained with costly pixel-level annotations. In this study, we propose a FRD method that achieves competitive accuracies but only uses easily obtained bounding box annotations. Box-level tags provide important cues of focus regions but lose the boundary delineation of the transition area.

Defocus Blur Detection via Multi-Stream Bottom-Top-Bottom Network.

Defocus blur detection (DBD) is aimed to estimate the probability of each pixel being in-focus or out-of-focus. This process has been paid considerable attention due to its remarkable potential applications. Accurate differentiation of homogeneous regions and detection of low-contrast focal regions, as well as suppression of background clutter, are challenges associated with DBD.

Genetic Structure and Eco-Geographical Differentiation of Wild Sheep Fescue (Festuca ovina L.) in Xinjiang, Northwest China.

Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt.

Biochemical sensing by nanofluidic crystal in a confined space.

Electrokinetics at nanoscale has attracted broad attention as a promising conductivity based biochemical sensing principle with a good selectivity. The nanoparticle crystal, formed by self-assembling nanoparticles inside a microstructure, has been utilized to fulfill a nanoscale electrokinetics based biochemical sensing platform, named nanofluidic crystal in our previous works. This paper introduces a novel nanofluidic crystal scheme by packing nanoparticles inside a well-designed confined space to improve the device-to-device readout consistency.

Guide filter-based gradient vector flow module for infrared image segmentation.

Infrared image segmentation is a challenging topic since infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow (GVF), have better segmentation performance for clear images. However, the GVF model has the drawbacks of sensitivity to noise and adaptability of the parameters, decreasing the effect of infrared image segmentation significantly.

Infrared image detail enhancement based on the gradient field specification.

Human vision is sensitive to the changes of local image details, which are actually image gradients. To enhance faint infrared image details, this article proposes a gradient field specification algorithm. First we define the image gradient field and gradient histogram.