Rethink left-behind experience: new categories and its relationship with aggression

Left-behind experience refers to the experience of children staying behind in their hometown under the care of only one parent or their relatives while one or both of their parents leave to work in other places. College students with left-behind experience showed higher aggression levels. To further explore the relationship between left-behind experience and aggression, the current study categorized left-behind experience using latent class analysis and explored its relationship with aggression. One thousand twenty-eight Chinese college students with left-behind experience were recruited, and their aggression levels were assessed. The results showed that there were four categories of left-behind experience: “starting from preschool, frequent contact” (35.5%), “less than 10 years in duration, limited contact” (27.0%), “starting from preschool, over 10 years in duration, limited contact” (10.9%), and “starting from school age, frequent contact” (26.6%). Overall, college students who reported frequent contact with their parents during the left-behind period showed lower levels of aggression than others did. Females were less aggressive than males in the “starting from preschool, frequent contact” left-behind situation, while males were less aggressive than females in the “starting from school age, frequent contact” situation. These findings indicate that frequent contact with leaving parents contributes to decreasing aggression of college students with left-behind experience. Meanwhile, gender is an important factor in this relationship

Self-paced Weight Consolidation for Continual Learning

Continual learning algorithms which keep the parameters of new tasks close to that of previous tasks, are popular in preventing catastrophic forgetting in sequential task learning settings. However, 1) the performance for the new continual learner will be degraded without distinguishing the contributions of previously learned tasks; 2) the computational cost will be greatly increased with the number of tasks, since most existing algorithms need to regularize all previous tasks when learning new tasks. To address the above challenges, we propose a self-paced Weight Consolidation (spWC) framework to attain robust continual learning via evaluating the discriminative contributions of previous tasks. To be specific, we develop a self-paced regularization to reflect the priorities of past tasks via measuring difficulty based on key performance indicator (i.e., accuracy). When encountering a new task, all previous tasks are sorted from "difficult" to "easy" based on the priorities. Then the parameters of the new continual learner will be learned via selectively maintaining the knowledge amongst more difficult past tasks, which could well overcome catastrophic forgetting with less computational cost. We adopt an alternative convex search to iteratively update the model parameters and priority weights in the bi-convex formulation. The proposed spWC framework is plug-and-play, which is applicable to most continual learning algorithms (e.g., EWC, MAS and RCIL) in different directions (e.g., classification and segmentation). Experimental results on several public benchmark datasets demonstrate that our proposed framework can effectively improve performance when compared with other popular continual learning algorithms

P-Glycoprotein/MDR1 Regulates Pokemon Gene Transcription Through p53 Expression in Human Breast Cancer Cells

P-glycoprotein (Pgp), encoded by the multidrug resistance 1 (MDR1) gene, is an efflux transporter and plays an important role in pharmacokinetics. In this study, we demonstrated that the pokemon promoter activity, the pokemon mRNA and protein expression can be significantly inhibited by Pgp. Chromatin immunoprecipitation assay showed that Pgp can bind the pokemon prompter to repress pokemon transcription activity. Furthermore, Pgp regulated pokemon transcription activity through expression of p53 as seen by use of p53 siRNA transfected MCF-7 cells or p53 mutated MDA-MB-231 cells. Moreover, p53 was detected to bind with Pgp in vivo using immunoprecipitation assay. Taken together, we conclude that Pgp can regulate the expression of pokemon through the presence of p53, suggesting that Pgp is a potent regulator and may offer an effective novel target for cancer therapy

CLE Diffusion: Controllable Light Enhancement Diffusion Model

Low light enhancement has gained increasing importance with the rapid development of visual creation and editing. However, most existing enhancement algorithms are designed to homogeneously increase the brightness of images to a pre-defined extent, limiting the user experience. To address this issue, we propose Controllable Light Enhancement Diffusion Model, dubbed CLE Diffusion, a novel diffusion framework to provide users with rich controllability. Built with a conditional diffusion model, we introduce an illumination embedding to let users control their desired brightness level. Additionally, we incorporate the Segment-Anything Model (SAM) to enable user-friendly region controllability, where users can click on objects to specify the regions they wish to enhance. Extensive experiments demonstrate that CLE Diffusion achieves competitive performance regarding quantitative metrics, qualitative results, and versatile controllability. Project page: \url{https://yuyangyin.github.io/CLEDiffusion/

Two Heads Are Better Than One: Improving Fake News Video Detection by Correlating with Neighbors

The prevalence of short video platforms has spawned a lot of fake news videos, which have stronger propagation ability than textual fake news. Thus, automatically detecting fake news videos has been an important countermeasure in practice. Previous works commonly verify each news video individually with multimodal information. Nevertheless, news videos from different perspectives regarding the same event are commonly posted together, which contain complementary or contradictory information and thus can be used to evaluate each other mutually. To this end, we introduce a new and practical paradigm, i.e., cross-sample fake news video detection, and propose a novel framework, Neighbor-Enhanced fakE news video Detection (NEED), which integrates the neighborhood relationship of new videos belonging to the same event. NEED can be readily combined with existing single-sample detectors and further enhance their performances with the proposed graph aggregation (GA) and debunking rectification (DR) modules. Specifically, given the feature representations obtained from single-sample detectors, GA aggregates the neighborhood information with the dynamic graph to enrich the features of independent samples. After that, DR explicitly leverages the relationship between debunking videos and fake news videos to refute the candidate videos via textual and visual consistency. Extensive experiments on the public benchmark demonstrate that NEED greatly improves the performance of both single-modal (up to 8.34% in accuracy) and multimodal (up to 4.97% in accuracy) base detectors. Codes are available in https://github.com/ICTMCG/NEED.Comment: To appear in ACL 2023 Finding

Validation of a low-cost Electromyography (EMG) system via a commercial and accurate EMG device : pilot study

Electromyography (EMG) devices are well-suited for measuring the behaviour of muscles during an exercise or a task, and are widely used in many different research areas. Their disadvantage is that commercial systems are expensive. We designed a low-cost EMG system with enough accuracy and reliability to be used in a wide range of possible ways. The present article focuses on the validation of the low-cost system we designed, which is compared with a commercially available, accurate device. The evaluation was done by means of a set of experiments, in which volunteers performed isometric and dynamic exercises while EMG signals from the rectus femoris muscle were registered by both the proposed low-cost system and a commercial system simultaneously. Analysis and assessment of three indicators to estimate the similarity between both signals were developed. These indicated a very good result, with spearman’s correlation averaging above 0.60, the energy ratio close to the 80% and the linear correlation coefficient approximating 100%. The agreement between both systems (custom and commercial) is excellent, although there are also some limitations, such as the delay of the signal (1 s) and noise due to the hardware and assembly in the proposed system

Ferulic acid promoted in-situ generation of AgNPs@silk as functional colorants

A rapid, green and simple procedure for the in-situ generation of AgNPs@silk as functional colorant is described herein. Silver (Ag+) ions were first diffused into the silk fabric matrix by soaking into aqueous AgNO3 solution, subsequently, alcoholic solution of ferulic acid, a natural polyphenol, was added as an eco-friendly reductant for the generation of AgNPs@silk. The formation of AgNPs was confirmed by visible color changes and UV–visible absorption spectra. The residual AgNPs solution was characterized via UV–visible spectroscopy, TEM and DLS. The UV–visible spectra and TEM analyses confirmed the formation of more or less spherical well-dispersed AgNPs. The AgNPs@silk was characterized by SEM, EDS, XRD, XPS and FTIR. The Ag content of AgNPs@silk was determined by nitric acid digestion followed by ICP-OES. The color, antibacterial and UV protection characteristics of AgNPs@silk were also evaluated. AgNPs@silk produced a beautiful color pallete ranging from light creamish brown to dark golden brown. The AgNPs treated silk exhibited outstanding antibacterial activity (>99% bacterial reduction) and excellent laundering durability, where it inhibited >94% of E. coli even after 10 washing cycles. Moreover, AgNPs@silk was highly effective blocking of UV radiation in both UVA and UVB regions, and thus offered excellent UV protection

Transient receptor potential channel 1 deficiency impairs host defense and proinflammatory responses to bacterial infection by regulating protein kinase Cα signaling

Transient receptor potential channel 1 (TRPC1) is a nonselective cation channel that is required for Ca2+ homeostasis necessary for cellular functions. However, whether TRPC1 is involved in infectious disease remains unknown. Here, we report a novel function for TRPC1 in host defense against Gram-negative bacteria. TRPC1-/- mice exhibited decreased survival, severe lung injury, and systemic bacterial dissemination upon infection. Furthermore, silencing of TRPC1 showed decreased Ca2+ entry, reduced proinflammatory cytokines, and lowered bacterial clearance. Importantly, TRPC1 functioned as an endogenous Ca2+ entry channel critical for proinflammatory cytokine production in both alveolar macrophages and epithelial cells. We further identified that bacterium-mediated activation of TRPC1 was dependent on Toll-like receptor 4 (TLR4), which induced endoplasmic reticulum (ER) store depletion. After activation of phospholipase Cγ (PLC-γ), TRPC1 mediated Ca2+ entry and triggered protein kinase Cα (PKC-α) activity to facilitate nuclear translocation of NF-kB/Jun N-terminal protein kinase (JNK) and augment the proinflammatory response, leading to tissue damage and eventually mortality. These findings reveal that TRPC1 is required for host defense against bacterial infections through the TLR4-TRPC1-PKCγ signaling circuit.Fil: Zhou, Xikun. University Of North Dakota; Estados Unidos. West China Hospital Of Sichuan University; ChinaFil: Ye, Yan. University Of North Dakota; Estados UnidosFil: Sun, Yuyang. University Of North Dakota; Estados UnidosFil: Li, Xuefeng. West China Hospital Of Sichuan University; China. University Of North Dakota; Estados UnidosFil: Wang, Wenxue. University Of North Dakota; Estados UnidosFil: Privratsky, Breanna. University Of North Dakota; Estados UnidosFil: Tan, Shirui. University Of North Dakota; Estados UnidosFil: Zhou, Zongguang. West China Hospital Of Sichuan University; ChinaFil: Huang, Canhua. West China Hospital Of Sichuan University; ChinaFil: Wei, Yu-Quan. West China Hospital Of Sichuan University; ChinaFil: Birnbaumer, Lutz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Institute Of Environmental Health Sciences; Estados UnidosFil: Singh, Brij B.. University Of North Dakota; Estados UnidosFil: Wu, Min. University Of North Dakota; Estados Unido