Vector-based Representation is the Key: A Study on Disentanglement and Compositional Generalization

Recognizing elementary underlying concepts from observations (disentanglement) and generating novel combinations of these concepts (compositional generalization) are fundamental abilities for humans to support rapid knowledge learning and generalize to new tasks, with which the deep learning models struggle. Towards human-like intelligence, various works on disentangled representation learning have been proposed, and recently some studies on compositional generalization have been presented. However, few works study the relationship between disentanglement and compositional generalization, and the observed results are inconsistent. In this paper, we study several typical disentangled representation learning works in terms of both disentanglement and compositional generalization abilities, and we provide an important insight: vector-based representation (using a vector instead of a scalar to represent a concept) is the key to empower both good disentanglement and strong compositional generalization. This insight also resonates the neuroscience research that the brain encodes information in neuron population activity rather than individual neurons. Motivated by this observation, we further propose a method to reform the scalar-based disentanglement works ($\beta$-TCVAE and FactorVAE) to be vector-based to increase both capabilities. We investigate the impact of the dimensions of vector-based representation and one important question: whether better disentanglement indicates higher compositional generalization. In summary, our study demonstrates that it is possible to achieve both good concept recognition and novel concept composition, contributing an important step towards human-like intelligence.Comment: Preprin

Post-stroke experiences and health information needs among Chinese elderly ischemic stroke survivors in the internet environment: a qualitative study

BackgroundElderly stroke survivors are encouraged to receive appropriate health information to prevent recurrences. After discharge, older patients seek health information in everyday contexts, examining aspects that facilitate or impair healthy behavior.ObjectivesTo explore the experiences of older stroke patients when searching for health information, focusing on search methods, identification of health information, and difficulties faced during the search process.MethodsUsing the qualitative descriptive methodology, semi-structured interviews were conducted with fifteen participants.ResultsParticipants associated the health information they sought with concerns about future life prospects triggered by perceived intrusive changes in their living conditions. Based on the participants’ descriptions, four themes were refined: participants’ motivation to engage in health information acquisition behavior, basic patterns of health information search, source preferences for health information, and difficulties and obstacles in health information search, and two search motivation subthemes, two search pattern subthemes, four search pathway subthemes, and four search difficulty subthemes were further refined.ConclusionOlder stroke patients face significant challenges in searching for health information online. Healthcare professionals should assess survivors’ health information-seeking skills, develop training programs, provide multichannel online access to health resources, and promote secondary prevention for patients by improving survivors’ health behaviors and self-efficacy

EST analysis of gene expression in the tentacle of Cyanea capillata

AbstractJellyfish, Cyanea capillata, has an important position in head patterning and ion channel evolution, in addition to containing a rich source of toxins. In the present study, 2153 expressed sequence tags (ESTs) from the tentacle cDNA library of C. capillata were analyzed. The initial ESTs consisted of 198 clusters and 818 singletons, which revealed approximately 1016 unique genes in the data set. Among these sequences, we identified several genes related to head and foot patterning, voltage-dependent anion channel gene and genes related to biological activities of venom. Five kinds of proteinase inhibitor genes were found in jellyfish for the first time, and some of them were highly expressed with unknown functions

Bi-Functional Silica Nanoparticles Doped with Iron Oxide and CdTe Prepared by a Facile Method

Cadmium telluride (CdTe) and iron oxide nanoparticles doped silica nanospheres were prepared by a multistep method. Iron oxide nanoparticles were first coated with silica and then modified with amino group. Thereafter, CdTe nanoparticles were assembled on the particle surfaces by their strong interaction with amino group. Finally, an outer silica shell was deposited. The final products were characterized by X-ray powder diffraction, transmission electron microscopy, vibration sample magnetometer, photoluminescence spectra, Fourier transform infrared spectra (FT-IR), and fluorescent microscopy. The characterization results showed that the final nanomaterial possessed a saturation magnetization of about 5.8 emu g−1and an emission peak at 588 nm when the excitation wavelength fixed at 380 nm

Mask-based Latent Reconstruction for Reinforcement Learning

For deep reinforcement learning (RL) from pixels, learning effective state representations is crucial for achieving high performance. However, in practice, limited experience and high-dimensional input prevent effective representation learning. To address this, motivated by the success of masked modeling in other research fields, we introduce mask-based reconstruction to promote state representation learning in RL. Specifically, we propose a simple yet effective self-supervised method, Mask-based Latent Reconstruction (MLR), to predict the complete state representations in the latent space from the observations with spatially and temporally masked pixels. MLR enables the better use of context information when learning state representations to make them more informative, which facilitates RL agent training. Extensive experiments show that our MLR significantly improves the sample efficiency in RL and outperforms the state-of-the-art sample-efficient RL methods on multiple continuous and discrete control benchmarks. The code will be released soon.Comment: A latent-space masked modeling method for improving RL sample efficienc

Innovative Telerehabilitation Enhanced Care Programme (ITECP) in young and middle-aged patients with haemorrhagic stroke to improve exercise adherence: protocol of a multicentre randomised controlled trial

Introduction Exercise rehabilitation is crucial for promoting the rehabilitation of limb motor function in people who had stroke and is related to a better prognosis. However, the exercise adherence of patients is low, which affects the effect of exercise rehabilitation. This study aims to evaluate the effects of the Innovative Telerehabilitation Enhanced Care Programme (ITECP) on exercise adherence in young and middle-aged patients with haemorrhagic stroke. We hypothesise that patients trained with ITECP will show greater improvement in exercise adherence and muscle strength than patients with routine exercise rehabilitation.Methods and analysis This is a randomised controlled, evaluator-blinded multicentre superiority trial to be implemented at four tertiary grade-A hospitals in eastern, western, northern and central China. Patients in the experimental group will receive ITECP while those in the control group will receive routine exercise rehabilitation. Both groups will receive routine care. The primary outcome measure is exercise adherence, while secondary outcome measures include muscle strength, activities of daily living, exercise self-efficacy, quality of life, rate of exercise-related adverse events and readmission. These will be measured at baseline, predischarge as well as 1 and 3 months postdischarge.Ethics and dissemination The study has obtained ethical approval from the Medical Ethics Committee of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School (2021-381-02). The results will be shared with young and middle-aged patients with haemorrhagic stroke, policy-makers, the general public, as well as academia.Trial registration number Chinese Clinical Trials Registry (ChiCTR 2200066498)

Generalizing to Unseen Domains: A Survey on Domain Generalization

Machine learning systems generally assume that the training and testing distributions are the same. To this end, a key requirement is to develop models that can generalize to unseen distributions. Domain generalization (DG), i.e., out-of-distribution generalization, has attracted increasing interests in recent years. Domain generalization deals with a challenging setting where one or several different but related domain(s) are given, and the goal is to learn a model that can generalize to an unseen test domain. Great progress has been made in the area of domain generalization for years. This paper presents the first review of recent advances in this area. First, we provide a formal definition of domain generalization and discuss several related fields. We then thoroughly review the theories related to domain generalization and carefully analyze the theory behind generalization. We categorize recent algorithms into three classes: data manipulation, representation learning, and learning strategy, and present several popular algorithms in detail for each category. Third, we introduce the commonly used datasets, applications, and our open-sourced codebase for fair evaluation. Finally, we summarize existing literature and present some potential research topics for the future.Comment: 19 pages (add more related work as of 12/2021); short version (6 pages) has been accepted by IJCAI-21 survey track; codebase: https://github.com/jindongwang/transferlearning/tree/master/code/DeepD

Pretreatment with coenzyme Q10 improves ovarian response and embryo quality in low-prognosis young women with decreased ovarian reserve: a randomized controlled trial

Abstract Background Management of women with reduced ovarian reserve or poor ovarian response (POR) to stimulation is one of the major challenges in reproductive medicine. The primary causes of POR remain elusive and oxidative stress was proposed as one of the important contributors. It has been suggested that focus on the specific subpopulations within heterogeneous group of poor responders could assist in evaluating optimal management strategies for these patients. This study investigated the effect of anti-oxidant treatment with coenzyme Q10 (CoQ10) on ovarian response and embryo quality in young low-prognosis patients with POR. Methods This prospective, randomized controlled study included 186 consecutive patients with POR stratified according to the POSEIDON classification group 3 (age < 35, poor ovarian reserve parameters). The participants were randomized to the CoQ10 pre-treatment for 60 days preceding IVF-ICSI cycle or no pre-treatment. The number of high quality embryos was a primary outcome measure. Results A total of 169 participants were evaluated (76 treated with CoQ10 and 93 controls); 17 women were excluded due to low compliance with CoQ10 administration. The baseline demographic and clinical characteristics were comparable between the groups. CoQ10 pretreatment resulted in significantly lower gonadotrophin requirements and higher peak E2 levels. Women in CoQ10 group had increased number of retrieved oocytes (4, IQR 2–5), higher fertilization rate (67.49%) and more high-quality embryos (1, IQR 0–2); p < 0.05. Significantly less women treated with CoQ10 had cancelled embryo transfer because of poor embryo development than controls (8.33% vs. 22.89%, p = 0.04) and more women from treatment group had available cryopreserved embryos (18.42% vs. 4.3%, p = 0.012). The clinical pregnancy and live birth rates per embryo transfer and per one complete stimulation cycle tended to be higher in CoQ10 group but did not achieve statistical significance. Conclusion Pretreatment with CoQ10 improves ovarian response to stimulation and embryological parameters in young women with poor ovarian reserve in IVF-ICSI cycles. Further work is required to determine whether there is an effect on clinical treatment endpoints