The Value Orientation of Teaching Reform in the Era of Smart Education

Based on the influence of the era of smart education on education and teaching, this article discusses the humanistic, social, cultural, and practical rationality of teaching reform in the era of smart education from the development trend of the integration of teaching reforms and information technology. Grasping the theoretical basis of teaching reform under the background of the new era will play a proper guiding role in the practice of teaching reform

Global existence of solutions for fuzzy second-order differential equations under generalized H-differentiability

AbstractIn this paper, we study the global existence of solutions for second-order fuzzy differential equations with initial conditions under generalized H-differentiability. Second derivative of the H-difference of two functions under generalized H-differentiability is obtained. Two theorems which assure global existence of solutions for second-order fuzzy differential equations are given and proved. Some examples are given to illustrate these results

In the Blink of an Eye: Event-based Emotion Recognition

We introduce a wearable single-eye emotion recognition device and a real-time approach to recognizing emotions from partial observations of an emotion that is robust to changes in lighting conditions. At the heart of our method is a bio-inspired event-based camera setup and a newly designed lightweight Spiking Eye Emotion Network (SEEN). Compared to conventional cameras, event-based cameras offer a higher dynamic range (up to 140 dB vs. 80 dB) and a higher temporal resolution. Thus, the captured events can encode rich temporal cues under challenging lighting conditions. However, these events lack texture information, posing problems in decoding temporal information effectively. SEEN tackles this issue from two different perspectives. First, we adopt convolutional spiking layers to take advantage of the spiking neural network's ability to decode pertinent temporal information. Second, SEEN learns to extract essential spatial cues from corresponding intensity frames and leverages a novel weight-copy scheme to convey spatial attention to the convolutional spiking layers during training and inference. We extensively validate and demonstrate the effectiveness of our approach on a specially collected Single-eye Event-based Emotion (SEE) dataset. To the best of our knowledge, our method is the first eye-based emotion recognition method that leverages event-based cameras and spiking neural network

Mechanical characteristics of twin tunnel underneath construction on existing high-speed railway tunnel

The running speed of high-speed trains in the tunnel is as high as 350 km, which is very sensitive to the construction disturbance of the new shield tunnel. Therefore, it is of positive significance to study the influence of shield tunneling on existing high-speed railway lines and tunnel structures and control standards. Combined with centrifuge test and three-dimensional numerical simulation, the dynamic response of shield tunnel undercrossing existing high-speed railway tunnel is studied, and the influence of settlement joint and steel pipe pile reinforcement on existing tunnel is analyzed. Studies have shown that the existence of existing tunnels will reduce the surface settlement caused by tunnel excavation, but this shielding effect will be reduced if the influence of construction joints is considered. Therefore, if the construction joint is not considered in the numerical calculation, the ground deformation will be underestimated and the mechanical performance of the existing tunnel structure will be overestimated. In addition, steel pipe piles can effectively control the settlement of existing tunnels

BMP4 inhibits myogenic differentiation of bone marrow–derived mesenchymal stromal cells in mdx mice

AbstractBackground aimsBone marrow–derived mesenchymal stromal cells (BMSCs) are a promising therapeutic option for treating Duchenne muscular dystrophy (DMD). Myogenic differentiation occurs in the skeletal muscle of the mdx mouse (a mouse model of DMD) after BMSC transplantation. The transcription factor bone morphogenic protein 4 (BMP4) plays a crucial role in growth regulation, differentiation and survival of many cell types, including BMSCs. We treated BMSCs with BMP4 or the BMP antagonist noggin to examine the effects of BMP signaling on the myogenic potential of BMSCs in mdx mice.MethodsWe added BMP4 or noggin to cultured BMSCs under myogenic differentiation conditions. We then injected BMP4- or noggin-treated BMSCs into the muscles of mdx mice to determine their myogenic potential.ResultsWe found that the expression levels of desmin and myosin heavy chain decreased after treating BMSCs with BMP4, whereas the expression levels of phosphorylated Smad, a downstream target of BMP4, were higher in these BMSCs than in the controls. Mdx mouse muscles injected with BMSCs pretreated with BMP4 showed decreased dystrophin expression and increased phosphorylated Smad levels compared with muscles injected with non-treated BMSCs. The opposite effects were seen after pretreatment with noggin, as expected.ConclusionsOur results identified BMP/Smad signaling as an essential negative regulator of promyogenic BMSC activity; inhibition of this pathway improved the efficiency of BMSC myogenic differentiation, which suggests that this pathway might serve as a target to regulate BMSC function for better myogenic differentiation during treatment of DMD and degenerative skeletal muscle diseases

Distractor-aware Event-based Tracking

Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture light intensity changes, event camera has an inherent advantage to capture moving objects in challenging scenarios including objects under low light, high dynamic range, or fast moving objects. Thus event camera are natural for visual object tracking. However, the current event-based trackers derived from RGB trackers simply modify the input images to event frames and still follow conventional tracking pipeline that mainly focus on object texture for target distinction. As a result, the trackers may not be robust dealing with challenging scenarios such as moving cameras and cluttered foreground. In this paper, we propose a distractor-aware event-based tracker that introduces transformer modules into Siamese network architecture (named DANet). Specifically, our model is mainly composed of a motion-aware network and a target-aware network, which simultaneously exploits both motion cues and object contours from event data, so as to discover motion objects and identify the target object by removing dynamic distractors. Our DANet can be trained in an end-to-end manner without any post-processing and can run at over 80 FPS on a single V100. We conduct comprehensive experiments on two large event tracking datasets to validate the proposed model. We demonstrate that our tracker has superior performance against the state-of-the-art trackers in terms of both accuracy and efficiency

The existence of solutions for -Laplacian boundary value problems at resonance on the half-line

The concept of collective efficacy, defined as the combination of mutual trust and willingness to act for the common good, has received widespread attention in the field of criminology. Collective efficacy is linked to, among other outcomes, violent crime, disorder, and fear of crime. The concept has been applied to geographical units ranging from below one hundred up to several thousand residents on average. In this paper key informant- and focus group interview transcripts from four Swedish neighborhoods are examined to explore whether different sizes of geographical units of analysis are equally important for collective efficacy. The four studied neighborhoods are divided into micro-neighborhoods (N=12) and micro-places (N=59) for analysis. The results show that neighborhoods appear to be too large to capture the social mechanism of collective efficacy which rather takes place at smaller units of geography. The findings are compared to survey responses on collective efficacy (N=597) which yield an indication in the same direction through comparison of ICC-values and AIC model fit employing unconditional two-level models in HLM 6

Molecular differences in brain regional vulnerability to aging between males and females

BackgroundAging-related cognitive decline is associated with brain structural changes and synaptic loss. However, the molecular mechanisms of cognitive decline during normal aging remain elusive.ResultsUsing the GTEx transcriptomic data from 13 brain regions, we identified aging-associated molecular alterations and cell-type compositions in males and females. We further constructed gene co-expression networks and identified aging-associated modules and key regulators shared by both sexes or specific to males or females. A few brain regions such as the hippocampus and the hypothalamus show specific vulnerability in males, while the cerebellar hemisphere and the anterior cingulate cortex regions manifest greater vulnerability in females than in males. Immune response genes are positively correlated with age, whereas those involved in neurogenesis are negatively correlated with age. Aging-associated genes identified in the hippocampus and the frontal cortex are significantly enriched for gene signatures implicated in Alzheimer’s disease (AD) pathogenesis. In the hippocampus, a male-specific co-expression module is driven by key synaptic signaling regulators including VSNL1, INA, CHN1 and KCNH1; while in the cortex, a female-specific module is associated with neuron projection morphogenesis, which is driven by key regulators including SRPK2, REPS2 and FXYD1. In the cerebellar hemisphere, a myelination-associated module shared by males and females is driven by key regulators such as MOG, ENPP2, MYRF, ANLN, MAG and PLP1, which have been implicated in the development of AD and other neurodegenerative diseases.ConclusionsThis integrative network biology study systematically identifies molecular signatures and networks underlying brain regional vulnerability to aging in males and females. The findings pave the way for understanding the molecular mechanisms of gender differences in developing neurodegenerative diseases such as AD