A Lightweight and Accurate Face Detection Algorithm Based on Retinaface

In this paper, we propose a lightweight and accurate face detection algorithm LAFD (Light and accurate face detection) based on Retinaface. Backbone network in the algorithm is a modified MobileNetV3 network which adjusts the size of the convolution kernel, the channel expansion multiplier of the inverted residuals block and the use of the SE attention mechanism. Deformable convolution network(DCN) is introduced in the context module and the algorithm uses focal loss function instead of cross-entropy loss function as the classification loss function of the model. The test results on the WIDERFACE dataset indicate that the average accuracy of LAFD is 94.1%, 92.2% and 82.1% for the "easy", "medium" and "hard" validation subsets respectively with an improvement of 3.4%, 4.0% and 8.3% compared to Retinaface and 3.1%, 4.1% and 4.1% higher than the well-performing lightweight model, LFFD. If the input image is pre-processed and scaled to 1560px in length or 1200px in width, the model achieves an average accuracy of 86.2% on the 'hard' validation subset. The model is lightweight, with a size of only 10.2MB.Comment: 14 pages, 5 figures, 7 table

Style Matching or Content Matching? Moderating Role of Discrete Negative Emotions in the Effects of Managerial Responses Tailoring

Many firms are struggling with how to tailor their responses to online reviews expressing negative emotions. While most studies on the managerial response (MR) tailoring point to the importance of MR content, how the content is conveyed, often referred to as language style, has been underexplored. Drawing on the verbal mimicry and communication tailoring literature, we propose that style matching may be at least as important as content matching and play a different role when responding to reviews embedded with negative emotions. Further, we consider the differences among the various negative emotions expressed in reviews and explore how to tailor MR for reviews embedded with discrete negative emotions (anger, sadness, anxiety, and disgust) expressed in reviews. The results show that style matching is more effective for anger-embedded reviews and sadness-embedded reviews while content matching performs better for disgust-embedded reviews. However, these two tailoring strategies are not effective for anxiety-embedded reviews

Unsupervised Domain Adaptation GAN Inversion for Image Editing

Existing GAN inversion methods work brilliantly for high-quality image reconstruction and editing while struggling with finding the corresponding high-quality images for low-quality inputs. Therefore, recent works are directed toward leveraging the supervision of paired high-quality and low-quality images for inversion. However, these methods are infeasible in real-world scenarios and further hinder performance improvement. In this paper, we resolve this problem by introducing Unsupervised Domain Adaptation (UDA) into the Inversion process, namely UDA-Inversion, for both high-quality and low-quality image inversion and editing. Particularly, UDA-Inversion first regards the high-quality and low-quality images as the source domain and unlabeled target domain, respectively. Then, a discrepancy function is presented to measure the difference between two domains, after which we minimize the source error and the discrepancy between the distributions of two domains in the latent space to obtain accurate latent codes for low-quality images. Without direct supervision, constructive representations of high-quality images can be spontaneously learned and transformed into low-quality images based on unsupervised domain adaptation. Experimental results indicate that UDA-inversion is the first that achieves a comparable level of performance with supervised methods in low-quality images across multiple domain datasets. We hope this work provides a unique inspiration for latent embedding distributions in image process tasks

The profiles and clinical significance of extraocular muscle-expressed lncRNAs and mRNAs in oculomotor nerve palsy

IntroductionOculomotor nerve palsy (ONP) arises from primary abnormalities in the central neural pathways that control the extraocular muscles (EOMs). Long non-coding RNAs (lncRNAs) have been found to be involved in the pathogenesis of various neuroparalytic diseases. However, little is known about the role of lncRNAs in ONP.MethodsWe collected medial rectus muscle tissue from ONP and constant exotropia (CXT) patients during strabismus surgeries for RNA sequencing analysis. Differentially expressed mRNAs and lncRNAs were revealed and included in the functional enrichment analysis. Co-expression analysis was conducted between these differentially expressed mRNAs and lncRNAs, followed by target gene prediction of differentially expressed lncRNAs. In addition, lncRNA-microRNA and lncRNA-transcription factor-mRNA interaction networks were constructed to further elaborate the pathological changes in medial rectus muscle of ONP. Furthermore, RT-qPCR was applied to further validate the expression levels of important lncRNAs and mRNAs, whose clinical significance was examined by receiver operating characteristic (ROC) curve analysis.ResultsA total of 618 differentially expressed lncRNAs and 322 differentially expressed mRNAs were identified. The up-regulated mRNAs were significantly related to cholinergic synaptic transmission (such as CHRM3 and CHRND) and the components and metabolism of extracellular matrix (such as CHI3L1 and COL19A1), while the down-regulated mRNAs were significantly correlated with the composition (such as MYH7 and MYL3) and contraction force (such as MYH7 and TNNT1) of muscle fibers. Co-expression analysis and target gene prediction revealed the strong correlation between MYH7 and NR_126491.1 as well as MYOD1 and ENST00000524479. Moreover, the differential expressions of lncRNAs (XR_001739409.1, NR_024160.1 and XR_001738373.1) and mRNAs (CDKN1A, MYOG, MYOD1, MYBPH, TMEM64, STATH, and MYL3) were validated by RT-qPCR. ROC curve analysis showed that lncRNAs (XR_001739409.1, NR_024160.1, and NR_002766.2) and mRNAs (CDKN1A, MYOG, MYOD1, MYBPH, TMEM64, and STATH) might be promising biomarkers of ONP.ConclusionsThese results may shed light on the molecular biology of EOMs of ONP, as well as the possible correlation of lncRNAs and mRNAs with clinical practice

Atomically Well-defined Nitrogen Doping in the Cross-plane Transport through Graphene Heterojunctions

The nitrogen doping of graphene leads to graphene heterojunctions with a tunable bandgap, suitable for electronics, electrochemical, and sensing applications. However, the microscopic nature and charge transport properties of atomic-level nitrogen-doped graphene are still unknown, mainly due to the multiple doping sites with topological diversities. In this work, we fabricated the atomically well-defined N-doped graphene heterojunctions and investigated the cross-plane transport through these heterojunctions to reveal the effects of doping on their electronic properties. We found that different doping number of nitrogen atoms leads to a conductance difference of up to ~288, and the conductance of graphene heterojunctions with nitrogen-doping at different positions in the conjugated framework can also lead to a conductance difference of ~170. Combined ultraviolet photoelectron spectroscopy measurements and theoretical calculations reveal that the insertion of nitrogen atoms into the conjugation framework significantly stabilizes the frontier molecular orbitals, leading to a change in the relative positions of HOMO and LUMO to the Fermi level of the electrodes. Our work provides a unique insight into the role of nitrogen doping on the charge transport through graphene heterojunctions and materials at the single atomic level

Impact of a mobile health intervention based on multi-theory model of health behavior change on self-management in patients with differentiated thyroid cancer: protocol for a randomized controlled trial

IntroductionTheoretical models of health behavior are important guides for disease prevention and detection, treatment and rehabilitation, and promotion and maintenance of physical and mental health, but there are no intervention studies related to differentiated thyroid cancer (DTC) that use theoretical models of health as a guide. In this study, we used a microblogging platform as an intervention vehicle and mobile patient-doctor interactive health education as a means of intervention, with the aim of improving the health behaviors of DTC patients as well as the corresponding clinical outcomes.MethodsThis research project is a quantitative methodological study, and the trial will be a single-blind, single-center randomized controlled trial conducted at the Fourth Hospital of Harbin Medical University in Harbin, Heilongjiang Province. The study subjects are patients over 18 years of age with differentiated thyroid cancer who were given radioactive iodine-131 therapy as well as endocrine therapy after radical surgery for thyroid cancer. The intervention group will receive MTM-mhealth, and the realization of health education will rely on the smart terminal WeChat platform. Routine discharge education will be given to the control group at discharge. The primary outcome will be change in thyroid-stimulating hormone (TSH) from baseline and at 3 and 6 months of follow-up, and secondary outcomes will include change in self-management behavior, social cognitive and psychological, and metabolic control.DiscussionThis study will explore a feasible mHealth intervention program applied to a population of DTC patients using the Multi-theory model of health behavior change (MTM) as a guide, with the aim of evaluating the MTM-based intervention program for clinical outcome improvement in DTC patients, as well as determining the effectiveness of the MTM-based intervention program in improving self-management skills in DTC patients. The results of this study will indicate the feasibility as well as the effectiveness of the application of health theoretical modeling combined with mHealth applications in disease prognostic health management models, and provide policy recommendations and technological translations for the development of mobility-based health management applications in the field of health management

Gene Flow Risks From Transgenic Herbicide-Tolerant Crops to Their Wild Relatives Can Be Mitigated by Utilizing Alien Chromosomes

Integration of a transgene into chromosomes of the C-genomes of oilseed rape (AACC, 2n = 38) may affect their gene flow to wild relatives, particularly Brassica juncea (AABB, 2n = 36). However, no empiric evidence exists in favor of the C-genome as a safer candidate for transformation. In the presence of herbicide selections, the first- to fourth-generation progenies of a B. juncea × glyphosate-tolerant oilseed rape cross [EPSPS gene insertion in the A-genome (Roundup Ready, event RT73)] showed more fitness than a B. juncea × glufosinate-tolerant oilseed rape cross [PAT gene insertion in the C-genome (Liberty Link, event HCN28)]. Karyotyping and fluorescence in situ hybridization–bacterial artificial chromosome (BAC-FISH) analyses showed that crossed progenies from the cultivars with transgenes located on either A- or C- chromosome were mixoploids, and their genomes converged over four generations to 2n = 36 (AABB) and 2n = 37 (AABB + C), respectively. Chromosome pairing of pollen mother cells was more irregular in the progenies from cultivar whose transgene located on C- than on A-chromosome, and the latter lost their C-genome-specific markers faster. Thus, transgene insertion into the different genomes of B. napus affects introgression under herbicide selection. This suggests that gene flow from transgenic crops to wild relatives could be mitigated by breeding transgenic allopolyploid crops, where the transgene is inserted into an alien chromosome

Effects of dietary sodium butyrate on growth performance, immune function, and intestinal microflora of Chinese soft-shelled turtle (Pelodiscus sinensis)

The Chinese soft-shelled turtle (Pelodiscus sinensis) has become increasingly susceptible to frequent diseases with the intensification of farming, which severely impacts the development of the aquaculture industry. Sodium butyrate (SB) is widely used as a feed additive due to its promotion of growth, enhancement of immune function, and antioxidative properties. This study aimed to investigate the effects of dietary SB on the growth performance, immune function, and intestinal microflora of Chinese soft-shelled turtles. A total of 300 Chinese soft-shelled turtles (mean weight: 11.36 ± 0.21g) were randomly divided into four groups with three parallel sets in each group. Each group was fed a diet supplemented with 0%, 0.005%, 0.01%, or 0.02% SB for 60 days. The results demonstrated an upward trend in weight gain rate (WGR) and specific growth rate (SGR) with increasing SB supplementation, and the experimental group fed with 0.02% SB showed a significant increase in WGR and SGR compared to other groups (P< 0.05). These levels of SB also decreased the levels of feed conversion ratio (FCR) and the total cholesterol (TC) content of Chinese soft-shelled turtles, and the 0.02% SB was significantly lower than that of other groups (P< 0.05). The activity of complement protein in vivo increased with increases in SB content, and the activities of complement C3 and C4 reached the highest level with 0.02% SB. The species abundance of the experimental group D fed with 0.02% SB was significantly higher than that of other groups (P< 0.05). Furthermore, the relative abundance of Clostridium sensu stricto 1 was significantly increased with 0.02% SB (P< 0.05). In conclusion, adding 0.02% SB to the diet improves the growth performance, feed digestion ability, and intestinal microbiota of Chinese soft-shelled turtles

Intermolecular coupling enhanced thermopower in single- molecule diketopyrrolopyrrole junctions

Sorting out organic molecules with high thermopower is essential for understanding molecular thermoelectrics. The intermolecular coupling offers a unique chance to enhance the thermopower by tuning the bandgap structure of molecular devices, but the investigation of intermolecular coupling in bulk materials remains challenging. Herein, we investigated the thermopower of diketopyrrolopyrrole (DPP) cored single-molecule junctions with different coupling strengths by varying the packing density of the self-assembled monolayers (SAM) using a customized scanning tunneling microscope break junction (STM-BJ) technique. We found that the thermopower of DPP molecules could be enhanced up to one order of magnitude with increasing packing density, suggesting that the thermopower increases with larger neighboring intermolecular interactions. The combined density functional theory (DFT) calculations revealed that the closely-packed configuration brings stronger intermolecular coupling and then reduces the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, leading to an enhanced thermopower. Our findings offer a new strategy for developing organic thermoelectric devices with high thermopower

Network selection algorithm for heterogeneous wireless networks based on service characteristics and user preferences

Abstract Next generation heterogeneous wireless networks (HWNs) will integrate various wireless access technologies, such as cellular networks, wireless local area network (WLAN), and Worldwide Interoperability for Microwave Access (WiMAX), in order to support quality of service (QoS) requirements of various services. To connect mobile users to the best wireless network continuously, network selection has become a hotspot for research in HWNs. This paper designs a network selection algorithm based on service characteristics and user preferences. First, utility functions are used to calculate the utility value of each network attribute for different services. Next, the entropy method and the fuzzy-analytic hierarchy process (FAHP) are used to calculate the objective weight and subjective weight of network attributes respectively, with FAHP specifically being used to calculate the user preference values of services for candidate networks. Finally, simple additive weighting (SAW), multiplicative exponent weighting (MEW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used according to network attribute utility values and weights to calculate the score of each candidate network. These scores are converted into a comprehensive score for the candidate network based on such user preferences, thus obtaining the ranking of candidate networks. Simulation results show that the proposed algorithm can allow users to choose the most suitable network to access according to different service characteristics while reducing the number of network handovers