Scene categorization by Hessian-regularized active perceptual feature selection.

Decoding the semantic categories of complex sceneries is fundamental to numerous artificial intelligence (AI) infrastructures. This work presents an advanced selection of multi-channel perceptual visual features for recognizing scenic images with elaborate spatial structures, focusing on developing a deep hierarchical model dedicated to learning human gaze behavior. Utilizing the BING objectness measure, we efficiently localize objects or their details across varying scales within scenes.

[Effect of different degrees of primary varus knee on short-term effectiveness of anterior cruciate ligament reconstruction].

Objective: To investigate whether different degrees of primary varus knee affect joint function and stability in patients undergoing anterior cruciate ligament (ACL) reconstruction.

Methods: A clinical data of 160 patients with primary varus knee, who were admitted between January 2020 and December 2021 and met the selection criteria, was retrospectively analyzed. All patients underwent primary ACL reconstruction using autologous single-bundle hamstring tendon.

Incidence of acute Deep Vein Thrombosis in pediatric and adolescent orthopedic trauma hospitalized patients and effect of rivaroxaban treatment.

Objective: Deep vein thrombosis (DVT) provoked by orthopedic trauma is increasing in pediatric hospitalized patients. The purpose of our study is to identify the prevalence of acute DVT in pediatric and adolescent orthopedic trauma hospitalized patients and focus on evaluating the anticoagulation strategies and the clinical outcomes after a confirmed acute DVT.

Methods: Patients (age ≤18 years) with a confirmed acute DVT admitted for orthopedic trauma between September 2017 and December 2023 were included.

It is time to move forward: a bibliometric analysis of top 50 cited articles in elbow arthroscopy.

Objectives: To analyze the bibliometric characteristics of the top 50 cited articles in elbow arthroscopy.

Methods: The Web of Science Core Collection was employed to systematically retrieve publications related to elbow arthroscopy. Subsequently, the top 50 cited articles meeting the predefined inclusion criteria were meticulously documented and subjected to comprehensive bibliometric analysis.

[Research progress on pathological mechanism and clinical correlation between medial meniscus posterior root tear and tibial rotation].

Objective: To summarize the current research progress on the concept, clinical presentation, diagnosis, biomechanical changes, and pathological mechanisms of the medial meniscus posterior root tear (MMPRT), and its clinical correlations with tibial rotation.

Methods: The research literature on MMPRT and its relationship with tibial rotation at home and abroad in recent years was extensively consulted and summarized.

Results: MMPRT is a specific and common type of medial meniscus injury of the knee joint.

[Study on clinical characteristics and surgical methods of bucket-handle meniscal tears].

Objective: To summarize the clinical features, surgical methods, and prognosis of bucket-handle meniscal tears (BHMTs), and provide guidance for clinical treatment.

Methods: The clinical data of 91 BHMTs patients (91 knees), who met the selection criteria and were admitted between January 2015 and January 2021, was retrospectively analyzed. There were 68 males and 23 females.

Enhancing Offensive Language Detection with Data Augmentation and Knowledge Distillation.

Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms, as well as promoting the safe deployment of large language models. Training data is the basis for developing detectors; however, the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English resources. This significantly affects the accuracy of Chinese offensive language detectors in practical applications, especially when dealing with hard cases or out-of-domain samples.

A Fuzzy Clustering Validity Index Induced by Triple Center Relation.

The existing clustering validity indexes (CVIs) show some difficulties to produce the correct cluster number when some cluster centers are close to each other, and the separation processing mechanism appears simple. The results are imperfect in case of noisy data sets. For this reason, in this study, we come up with a novel CVI for fuzzy clustering, referred to as the triple center relation (TCR) index.

Arthroscopy combined with high tibial osteotomy promotes cartilage regeneration in osteoarthritis.

Background: To investigate the effect of arthroscopy combined with high tibial osteotomy (HTO) on cartilage regeneration in patients with knee osteoarthritis.

Methods: A retrospective analysis of 50 patients with varus and medial compartment osteoarthritis of the knee treated by arthroscopy combined with HTO. One year after the operation, a second-look arthroscopy was performed to observe the cartilage regeneration.

[Management status of anterior cruciate ligament injury in children and adolescents].

Objective: To summarize the current management of anterior cruciate ligament (ACL) injury in children and adolescents, in order to provide reference for the management of ACL injury in children and adolescents.

Methods: The relevant literature at home and abroad in recent years was extensively accessed to summarize the management status of ACL injury in children and adolescent.

Results: The number of ACL injury in children and adolescents is increasing every year.

[Experience in diagnosis and treatment of KD- M dislocation of knee joint].

Objective: To explore the effectiveness of one-stage posterior medial corner (PMC) repair or reconstruction combined with anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) reconstruction in treating KD-ⅢM dislocation.

Methods: The clinical data of 15 patients with knee KD-ⅢM dislocation who met the selection criteria between January 2016 and July 2019 were retrospectively analyzed. There were 9 males and 6 females, aged 22-61 years (mean, 40.

Hierarchical Network with Label Embedding for Contextual Emotion Recognition.

Emotion recognition has been used widely in various applications such as mental health monitoring and emotional management. Usually, emotion recognition is regarded as a text classification task. Emotion recognition is a more complex problem, and the relations of emotions expressed in a text are nonnegligible.

CERG: Chinese Emotional Response Generator with Retrieval Method.

The dialogue system has always been one of the important topics in the domain of artificial intelligence. So far, most of the mature dialogue systems are task-oriented based, while non-task-oriented dialogue systems still have a lot of room for improvement. We propose a data-driven non-task-oriented dialogue generator "CERG" based on neural networks.

A Robust Parameter-free Thresholding Method for Image Segmentation.

In this work we presented a new parameter-free thresholding method for image segmentation. In separating an image into two classes, the method employs an objective function that not only maximizes the between-class variance but also the distance between the mean of each class and the global mean of the image. The design of the objective function aims to circumvent the challenge that many existing techniques encounter when the underlying two classes have very different sizes or variances.

Reinforcement Emotion-Cognition System: A Teaching Words Task.

The goal of this paper is to suggest a system for intelligent learning environments with robots modeling of emotion regulation and cognition based on quantitative motivation. A detailed interactive situation for teaching words is proposed. In this study, we introduce one bottom-up collaboration method for emotion-cognition interplay and behaviour decision-making.

Emotion classification using a CNN_LSTM-based model for smooth emotional synchronization of the humanoid robot REN-XIN.

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which the Emotional Trigger is an emotion classification model trained from our proposed Word Mover's Distance(WMD) based algorithm. Due to the long time delay of the WMD-based Emotional Trigger System, we propose an enhanced Emotional Trigger System to enable a smooth interaction with the robot in which the Emotional Trigger is replaced by a conventional convolution neural network and a long short term memory network (CNN_LSTM)-based deep neural network. In our experiments, the CNN_LSTM based model only need 10 milliseconds or less to finish the classification without a decrease in accuracy, while the WMD-based model needed approximately 6-8 seconds to give a result.

Emotion computing using Word Mover's Distance features based on Ren_CECps.

In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chinese emotional corpus Ren_CECps. Inspired by the enormous improvement of the visualization map propelled by the changed distances among the sentences, we being the first group utilizes the Word Mover's Distance(WMD) algorithm as a way of feature representation in Chinese text emotion classification. Our experiments show that both in 80% for training, 20% for testing and 50% for training, 50% for testing experiments of Ren_CECps, WMD features get the best f1 scores and have a greater increase compared with the same dimension feature vectors obtained by dimension reduction TF·IDF method.

LED Phototherapy with Gelatin Sponge Promotes Wound Healing in Mice.

Tiny but highly efficient, a light-emitting diode (LED) can power a therapy device, such as a phototherapy device, and, at the same time, decrease the device's size requirements. In this study, a LED phototherapy device was designed to investigate the possible impact on wound healing using a mouse model and a cell line exposed to red and blue light. To enhance wound phototherapy, a gelatin sponge was fabricated.

GlycCompSoft: Software for Automated Comparison of Low Molecular Weight Heparins Using Top-Down LC/MS Data.

Low molecular weight heparins are complex polycomponent drugs that have recently become amenable to top-down analysis using liquid chromatography-mass spectrometry. Even using open source deconvolution software, DeconTools, and automatic structural assignment software, GlycReSoft, the comparison of two or more low molecular weight heparins is extremely time-consuming, taking about a week for an expert analyst and provides no guarantee of accuracy. Efficient data processing tools are required to improve analysis.

An unsupervised text mining method for relation extraction from biomedical literature.

The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs.