In home-based elderly care service, how to precisely recognize activities is a key issue in the design and implementation of context-aware service for people. Existing research works reveal that those approaches ignore characteristics activity diversity, similarity features people at home, so recognition accuracy are not high enough real-life applications. Thus, this paper, we first study types service. Then, propose two-stage home method based on random forest similarity. The uses improved...

The cryopreservation of red blood cells (RBCs) plays a key role in transfusion therapy. Traditional cryoprotectants (CPAs) are mostly organic solvents and may cause side effects to RBCs, such as hemolysis membrane damage. Therefore, it is necessary find CPAs with better performance lower toxicity. Herein, we report for the first time that N-[Tri(hydroxymethyl)methyl]glycine (tricine) showed great potential sheep RBCs. addition tricine significantly increased thawed RBCs' recovery from 19.5 ±...

Accurate assessment of wound healing may require invasive tissue biopsies, limiting its clinical usefulness in humans. Optical coherence tomography (OCT) is a novel, high-resolution method using light reflection to obtain noninvasive cross sectional imaging biological tissues.To evaluate the utility OCT for assessing reepithelialization porcine model.The authors conducted an animal study with two domestic pigs. Excisional cutaneous wounds were created over ventral surface animals electric...

The cryopreservation of red blood cells (RBCs) is essential for transfusion therapy and maintaining the inventory RBCs units. existing cryoprotectants (CPAs) have many defects, search novel CPAs becoming a research hotspot. Sodium hyaluronate (SH) polymerized from sodium glucuronate N-acetylglucosamine, which has good water binding capacity biocompatibility. Herein, we reported first time that under action medium molecular weight (MSH), thawed recovery increased 33.1 ​± ​5.8% to 63.2 ​3.5%....

Hierarchical Imitation Learning (HIL) is a promising approach for tackling long-horizon decision-making tasks. While it challenging task due to the lack of detailed supervisory labels sub-goal learning, and reliance on hundreds thousands expert demonstrations. In this work, we introduce SEAL, novel framework that leverages Large Language Models (LLMs)'s powerful semantic world knowledge both specifying space pre-labeling states semantically meaningful representations without prior...

Non-small cell lung cancer (NSCLC) accounts for 81% of cases, among which over 47% presented with distant metastasis at the time diagnosis. Despite introduction targeted therapy and immunotherapy, enhancing survival rate overcoming development resistance remain a big challenge. Thus, it is crucial to find potential new therapeutics targets that can mitigate investigate its effects on biomarkers, such as cellular metabolomics. In current study, we investigated role cyproheptadine (CPH), an...

Learning an optimal policy for autonomous driving task to confront with complex environment is a long- studied challenge. Imitative reinforcement learning accepted as promising approach learn robust through expert demonstrations and interactions environments. However, this model utilizes non-smooth rewards, which have negative impact on matching between navigation commands trajectory (state-action pairs), degrade the generalizability of agent. Smooth rewards are crucial discriminate actions...

Multi-objective reinforcement learning (MORL) excels at handling rapidly changing preferences in tasks that involve multiple criteria, even for unseen preferences. However, previous dominating MORL methods typically generate a fixed policy set or preference-conditioned through training iterations exclusively sampled preference vectors, and cannot ensure the efficient discovery of Pareto front. Furthermore, integrating into input value functions presents scalability challenges, particular as...

Light switchable two-component protein dimerization systems offer versatile manipulation and dissection of cellular events in living systems. Over the past 20 years, field has been driven by discovery photoreceptor-based interaction systems, engineering light-actuatable binder proteins, development photoactivatable compounds as inducers. This perspective is to categorize mechanisms design approaches these compare their advantages limitations, bridge them emerging applications. Our goal...

This paper proposes a multimodal fusion model for 3D car detection inputting both point clouds and RGB images generates the corresponding bounding boxes. Our is composed of two subnetworks: one point-based method another multi-view based method, which then combined by decision model. can absorb advantages these sub-networks restrict their shortcomings effectively. Experiments on KITTI benchmark show that our work achieve state art performance.

Computer vision model using deep learning requires a lot of high-quality data for training. However, obtaining amounts well-annotated is too expensive. The state-of-the-art automatic annotation tools can accurately detect and segment few objects. We bring together the crowed engineering into framework object detection instance-level segmentation. input are image need to annotate constraints: precision, utility cost. output set detected objects segmentation results. integrate computer with...

Inverse reinforcement learning (IRL) aims to explicitly infer an underlying reward function based on collected expert demonstrations. Considering that obtaining demonstrations can be costly, the focus of current IRL techniques is a better-than-demonstrator policy using derived from sub-optimal However, existing algorithms primarily tackle challenge trajectory ranking ambiguity when function. They overlook crucial role considering degree difference between trajectories in terms their returns,...

A fluorescence-image-guided OCT (FIG-OCT) system is described, and its ability to enhance the sensitivity specificity examined in an animal bladder cancer model. Total 97 specimens were by fluorescence imaging, histological microscopy. The of FIG-OCT 100% 93% respectively, compared 79% 53% for while examination time has been dramatically decreased 3~4 times. In combination endoscopic OCT, a promising technique effective early diagnosis.

3D object detection has become a hot topic in intelligent vehicle applications recent years. Generally, deep learning been the primary framework used detection, and regression of location classification objectness are two indispensable components. In process training, ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> (n=1,2) focal loss considered as frequent solutions to minimize loss, respectively. However, there problems be solved...