Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved YOLOv5s Method for Light Guide Plate Defect Detection

Aiming at the problems of over 100 million pixels in a single image of a large-size light guide plate, only a dozen pixels in the defect size, uneven brightness, and slow detection speed, this paper designs an improved YOLOv5s method for light guide plate defect detection. YOLOv5s is used as the basic model, and the attention mechanism CBAM is added to the backbone feature extraction network (backbone) part; PAN-Net is replaced with Bi-FPN structure in the feature fusion network (Neck) part, and a small target detection layer is added at the same time; YOLOv5s Obtain higher accuracy and improve algorithm robustness. Finally, a comparative analysis is performed based on the self-built dataset LGPDD. The experimental results show that compared with the original YOLOv5s model, the average accuracy mAP is increased by 1.4%; the model detection speed can meet the production requirements, and has a good application prospect in industrial deployment.
Crowdsourcing Incident Information for Emergency Response using Open Data Sources in Smart Cities

Emergency events affect human security and safety as well as the integrity of the local infrastructure. Emergency response officials are required to make decisions using limited information and time. During emergency events, people post updates to social media networks, such as tweets, containing information about their status, help requests, incident reports, and other useful information. In this research project, the Latent Dirichlet Allocation (LDA) model is used to automatically classify incident-related tweets and incident types using Twitter data. Unlike the previous social media information models proposed in the related literature, the LDA is an unsupervised learning model which can be utilized directly without prior knowledge and preparation for data in order to save time during emergencies. Twitter data including messages and geolocation information during two recent events in New York City, the Chelsea explosion and Hurricane Sandy, are used as two case studies to test the accuracy of the LDA model for extracting incident-related tweets and labeling them by incident type. Results showed that the model could extract emergency events and classify them for both small and large-scale events, and the model’s hyper-parameters can be shared in a similar language environment to save model training time. Furthermore, the list of keywords generated by the model can be used as prior knowledge for emergency event classification and training of supervised classification models such as support vector machine and recurrent neural network.
OPTIGAN: TOPOLOGICAL OPTIMISATION IN DESIGN FORM-FINDING WITH CONDITIONAL GANS

With the rapid development of computers and technology in the 20th century, the topological optimisation (TO) method has spread worldwide in various fields. This novel structural optimisation approach has been applied in many disciplines, including architectural form-finding. Especially Bi-directional Evolutionary Structural Optimisation (BESO), which was proposed in the 1990s, is widely used by thousands of engineers and architects worldwide to design innovative and iconic buildings. To integrate topological optimisation with artificial intelligence (AI) algorithms and to leverage its power to improve the diversity and efficiency of the BESO topological optimisation method, this research explores a non-iterative approach to accelerate the topology optimisation process of structures in architectural form-finding via conditional generative adversarial networks (GANs), which is named as OptiGAN. Trained with topological optimisation results generated through Ameba software, OptiGAN is able to predict a wide range of optimised architectural and structural designs under defined conditions.
A Hybrid Transformer Model for Obstructive Sleep Apnea Detection Based on Self-Attention Mechanism Using Single-Lead ECG

Obstructive sleep apnea (OSA) is a widespread sleep disorder that seriously affects human health. Detection of OSA with low cost and high accuracy is of great clinical significance. This study proposes a hybrid transformer model based on self-attention mechanism for OSA detection using single-lead electrocardiogram. To reduce the introduction of expert knowledge, a new method for constructing raw inputs is proposed. The data inputs include the raw electrocardiogram (ECG) signal sequence, R-peak amplitude (RA) sequence, interbeat (RR) interval (RRI) sequence, and RR interval first-order difference (RRID) sequence. Then, a multiperspective channel-attention (MPCA) block is proposed to focus on the contribution of four input signals automatically and extract the fused multiperspective features. These features together with their position encodings were fed into transformer blocks to encode the most important information with self-attention mechanism. Finally, the prediction results were output through the linear layer. The proposed method was verified on the apnea-ECG database. The per-segment classification accuracy reached 0.91 and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.96. The per-recording classification accuracy reached 100% and the mean absolute error (MAE) was 2.71. Our method achieved better classification performance than other state-of-the-art algorithms. The proposed hybrid transformer model is able to detect OSA accurately using single-lead ECG in a manner similar to the detection process by human experts. Our method provides a convenient and precise solution for clinical OSA detection.
ConTra Preference Language: Privacy Preference Unification via Privacy Interfaces

After the enactment of the GDPR in 2018, many companies were forced to rethink their privacy management in order to comply with the new legal framework. These changes mostly affect the Controller to achieve GDPR-compliant privacy policies and management.However, measures to give users a better understanding of privacy, which is essential to generate legitimate interest in the Controller, are often skipped. We recommend addressing this issue by the usage of privacy preference languages, whereas users define rules regarding their preferences for privacy handling. In the literature, preference languages only work with their corresponding privacy language, which limits their applicability. In this paper, we propose the ConTra preference language, which we envision to support users during privacy policy negotiation while meeting current technical and legal requirements. Therefore, ConTra preferences are defined showing its expressiveness, extensibility, and applicability in resource-limited IoT scenarios. In addition, we introduce a generic approach which provides privacy language compatibility for unified preference matching.
Effects of the Largest Metastatic Lymph Node Size on the Outcomes of Patients who Underwent Pancreaticoduodenectomy for Pancreatic Ductal Adenocarcinoma

Objectives: Prognostic importance of metastatic lymph nodes in pancreatic cancer is always garnered attention due to dismal prognosis, with some quantitative factors drawing attention for significantly predicting outcomes. Size is one of the easy approach morphological characteristics of the lymph node, and data for effect of largest metastatic lymph node (LMLN) size on survival outcomes are lacking in pancreatic cancer. We aim to evaluate the effect of LMLN size on the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). Methods: This retrospective study evaluates the effect of LMLN size on survival outcomes by grouping the patients who were surgically treated for PDAC, according to their lymph node stage and calculated cutoff value for LMLN size, between February 2015 and May 2020. Results: In the study cohort of 131 patients, the mean age was 63.9±10.8 years and 77 patients were female. Ninety-nine of the patients had pN1, 32 had pN2 stage disease. The optimal cutoff point of LMLN size for predicting the prognosis was calculated as 7.5 mm (sensitivity = 81% and specificity = 81%). 34 (34.3%) of pN1 and 7 (21.9%) of pN2-staged patients had lymph node smaller than 7.5 mm. Three-year survival was significantly longer for patients whose LMLN size was <7.5 mm (56.2–18.2%, p<0.001). Whereas, the patients with LMLN size <7.5 mm had statistically significant longer median survival rate in the subgroup of patients with pN1 lymph node stage, no significant difference in median survival rates was observed between subgroups of pN2 patients (p=0.237). Conclusion: The present study demonstrated that the LMLN size was one of the potential predictors of survival in patients with PDAC.
Inverse Eigenvalue Problem and Least-Squares Problem for Skew-Hermitian {P,K + 1}-Reflexive Matrices

This paper involves related inverse eigenvalue problem and least-squares problem of skew-Hermitian {P,k + 1}-reflexive(antireflexive) matrices and their optimal approximation problems. The above problems are studied by converting them into two simpler cases: k = 1 and k = 2. Firstly, with some special properties of skew-Hermitian {P,k + 1}-reflexive(antireflexive) matrices, the necessary and sufficient conditions for the solvability and the general solution are presented, and the solution of corresponding optimal approximation problems also given, respectively. Then, we give the least-squares solution of AX = B satisfying the special condition by the singular value decomposition. Finally, we give an algorithm and an example to illustrate our results.
Metastatic Lung Tumors from Colorectal Cancer with EGFR Mutations That Responded to Osimertinib

A 50-year-old woman who had previously undergone right hemicolectomy and chemotherapy for colorectal cancer was hospitalized with respiratory failure. Chest computed tomography showed reticulonodular opacities and enlarged lymph nodes. A transbronchial biopsy revealed adenocarcinoma with epidermal growth factor receptor (EGFR) mutations T790M and L861Q. Treatment with the EGFR-tyrosine kinase inhibitor (TKI) osimertinib was started, and she achieved a partial response. We diagnosed her with metastatic lung tumors from colorectal cancer based on additional immunohistochemical staining and the EGFR mutation status (L861Q) of the specimens. Although cases with EGFR mutations have been rarely reported, an EGFR-TKI can be an effective treatment option for colorectal cancer.
Yohimbine, an α2-Adrenoceptor Antagonist, Suppresses PDGF-BB-Stimulated Vascular Smooth Muscle Cell Proliferation by Downregulating the PLCγ1 Signaling Pathway

Yohimbine (YOH) has antiproliferative effects against breast cancer and pancreatic cancer; however, its effects on vascular proliferative diseases such as atherosclerosis remain unknown. Accordingly, we investigated the inhibitory mechanisms of YOH in vascular smooth muscle cells (VSMCs) stimulated by platelet-derived growth factor (PDGF)-BB, a major mitogenic factor in vascular diseases. YOH (5–20 μM) suppressed PDGF-BB-stimulated a mouse VSMC line (MOVAS-1 cell) proliferation without inducing cytotoxicity. YOH also exhibited antimigratory effects and downregulated matrix metalloproteinase-2 and -9 expression in PDGF-BB-stimulated MOVAS-1 cells. It also promoted cell cycle arrest in the initial gap/first gap phase by upregulating p27Kip1 and p53 expression and reducing cyclin-dependent kinase 2 and proliferating cell nuclear antigen expression. We noted phospholipase C-γ1 (PLCγ1) but not ERK1/2, AKT, or p38 kinase phosphorylation attenuation in YOH-modulated PDGF-BB-propagated signaling pathways in the MOVAS-1 cells. Furthermore, YOH still inhibited PDGF-BB-induced cell proliferation and PLCγ1 phosphorylation in MOVAS-1 cells with α2B-adrenergic receptor knockdown. YOH (5 and 10 mg/kg) substantially suppressed neointimal hyperplasia in mice subjected to CCA ligation for 21 days. Overall, our results reveal that YOH attenuates PDGF-BB-stimulated VSMC proliferation and migration by downregulating a α2B-adrenergic receptor–independent PLCγ1 pathway and reduces neointimal formation in vivo. Therefore, YOH has potential for repurposing for treating atherosclerosis and other vascular proliferative diseases.
Recent Progress in Flexible Pressure Sensor Arrays

Flexible pressure sensors that can maintain their pressure sensing ability with arbitrary deformation play an essential role in a wide range of applications, such as aerospace, prosthetics, robotics, healthcare, human–machine interfaces, and electronic skin. Flexible pressure sensors with diverse conversion principles and structural designs have been extensively studied. At present, with the development of 5G and the Internet of Things, there is a huge demand for flexible pressure sensor arrays with high resolution and sensitivity. Herein, we present a brief description of the present flexible pressure sensor arrays with different transduction mechanisms from design to fabrication. Next, we discuss the latest progress of flexible pressure sensor arrays for applications in human–machine interfaces, healthcare, and aerospace. These arrays can monitor the spatial pressure and map the trajectory with high resolution and rapid response beyond human perception. Finally, the outlook of the future and the existing problems of pressure sensor arrays are presented.
Characterization of the MADS-Box Gene CmFL3 in chrysanthemum

Chrysanthemummorifolium is one of the four major cut flowers in the world, with high ornamental and economic value. Flowering time is an important ornamental characteristic of chrysanthemum that affects its value in the market. In Arabidopsis, the FRUITFULL (FUL) gene plays a key role in inducing flowering. Here, we isolated an FUL clade MADS-box gene, CmFL3, from chrysanthemum inflorescence buds. CmFL3 localized in the cellular membrane and nucleus, and showed no transcriptional activity in yeast. The qRT-PCR assay showed that CmFL3 was strongly expressed in the leaves, receptacles, and disc floret petals. Furthermore, CmFL3 was mainly detected in the inflorescence meristem and bract primordia using in situ hybridization. Similar to Arabidopsis, overexpression of CmFL3 in chrysanthemum induced early flowering. Particularly, the expression level of CmAFT was downregulated, whereas that of CmFTL3 was upregulated in the leaves of transgenic chrysanthemum lines. Meanwhile, the overexpression of CmFL3 in Arabidopsis also led to earlier flowering. Furthermore, the expression of AtFT, AtAP1, AtLFY, and AtFUL was significantly increased in CmFL3 transgenic Arabidopsis. The present study verified the function of CmFL3 in regulating flowering time and further revealed that it could affect the expression of other flowering-related genes—CmAFT and CmFTL3. Therefore, the CmFL3 gene may be an important candidate for genetic breeding aimed at regulating flowering.
Conservación de aves marinas y actividad pesquera comercial en Argentina: ¿problemática o conflicto ambiental?

El Mar Argentino es un ambiente de gran riqueza; su productividad lo convierte en una zona marítima por excelencia para la pesca comercial. Dicha actividad productiva se superpone espacial y temporalmente con especies que dependen de esta zona como área de alimentación. Una de las consecuencias de esta cohabitación es la captura incidental de aves marinas en las artes de pesca. Esta situación pone en tensión la actividad productiva y los compromisos internacionales de conservación marina asumidos por el Estado argentino. El presente trabajo hace un recorrido desde la concepción que primaba respecto a los recursos naturales hasta el surgimiento de nuevas formas de abordaje como el Enfoque Ecosistémico de la Pesca (EEP). Se describe la repercusión e incidencia que ello tiene en las economías latinoamericanas y en las políticas de gestión, que hacen a un modo de habitar el territorio, cargado de significados y construcciones sociales, en dialéctica constante con el sistema natural. Finalmente, se concluye que la problemática asociada a las aves marinas no constituye en el presente un conflicto ambiental, pero posee el potencial de convertirse en tal.
Modeling and Evaluating the Gate Length Dependence of BTI

Bias temperature instability (BTI) is a major reliability concern in the current and upcoming technologies. Current mitigation techniques mainly target circuit and system levels through reducing the stimuli that govern BTI. Such mitigation techniques typically come with non-negligible overheads, which might not be acceptable—especially in smaller technology nodes where the available design margins are tighter. Semiconductor vendors report different BTI degradations in their technology and hence circuit designers need to consider such technology features when designing for reliability. Recently, TSMC reported that BTI strongly depends on the gate length (<inline-formula> <tex-math notation="LaTeX">${L}$ </tex-math></inline-formula>) of transistors in their 10nm technology node. In this brief, we are the first to investigate the role that gate length dependence of BTI may play as a new degree of freedom in the design for reliability. Based on the reported data from TSMC, we propose to incorporate the gate length dependency into a state-of-the-art physics-based BTI model. Then, we propose a new method of transistor stacking that optimizes circuits (e.g., SRAM cells) with respect to on/off current ratios in which <inline-formula> <tex-math notation="LaTeX">${L}$ </tex-math></inline-formula>-dependency of BTI is taken into account. Compared to state of the art, our approach results in BTI-hardened SRAM cells with 50% better on/off current ratio along with <inline-formula> <tex-math notation="LaTeX">$3\times$ </tex-math></inline-formula> better reliability at the cost of a 20% area overhead.
Developing an Augmented Reality System with Real-Time Reflection for Landscape Design Visualization, Using Real-Time Ray Tracing Technique

In landscape design, visualization of a new design on the site with clients can greatly improve communication efficiency and reduce communication costs. The use of augmented reality (AR) allows the projection of design models into the real environment, but the relationship between the models and the physical environment, such as reflections, which are often thoughtfully considered in waterfront landscape design, is difficult to express in existing AR systems. The aim of this study is to accurately render and express the reflections of virtual models in the physical environment in an AR system. Different from traditional rasterized rendering, this study used physically correct ray-tracing algorithms for reflection rendering calculations. Using a smartphone and a computer, we first constructed a basic AR system using a game engine and then performed ray-tracing computations using a shader kernel in the game engine. Finally, we combined the rendering results of reflections with the video stream from a smartphone camera to achieve the reflection effect of a virtual model in a physical environment. Both designers and clients could review the design with a realistic reflection on an actual water surface and discuss design decisions through this system.
Changes in a Comprehensive Profile of Saliva Analytes in Fattening Pigs during a Complete Productive Cycle: A Longitudinal Study

Simple Summary The aim of this study was to evaluate whether a panel of 29 salivary biomarkers of stress, immunity, inflammation, redox homeostasis and other physiological functions can change in healthy fattening pigs when monitoring the different phases of their productive cycle and can be influenced by various sources of variations such as gender and performance parameters. Several analytes showed changes due to the productive cycle, with a majority of the analytes showing higher values at lactation and at the beginning of nursery. Additionally, differences were seen due to sex. These differences can be related in some cases with performance parameters and should be taken into consideration for an appropriate interpretation of the analytes. Abstract A comprehensive panel of 29 salivary analytes was measured in fattening pigs to evaluate its possible changes along their productive cycle. The identification of those changes would allow a better interpretation of the results according to the productive phase of the animal. Saliva samples were obtained from 49 Large-White pigs (24 females, 25 males) in suckling phase, at the beginning and the end of the nursery phase, and at the beginning and the end of the growing phase. Several analytes changed according to the phase of the productive cycle, with most of the analytes showing higher values at lactation and at the beginning of nursery. Additionally, differences were seen due to sex. When possible relations between performance parameters and analytes were evaluated, significant positive but weak relationships were found between weight at birth and salivary γ-glutamyl transferase, and between back-fat thickness and salivary lactate dehydrogenase. In conclusion, differences in the values of salivary analytes can be found in fattening pigs depending on the productive phase and sex of the animals.
Salidroside Ameliorates Radiation Damage by Reducing Mitochondrial Oxidative Stress in the Submandibular Gland

Radiotherapy for patients with head and neck cancer inevitably causes radiation damage to salivary glands (SGs). Overproduction of reactive oxygen species (ROS) leads to mitochondrial damage and is critical in the pathophysiology of SG radiation damage. However, mitochondrial-targeted treatment is unavailable. Herein, both in vitro and in vivo models of radiation-damaged rat submandibular glands (SMGs) were used to investigate the potential role of salidroside in protecting irradiated SGs. Cell morphology was observed with an inverted phase-contrast microscope. Malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), mitochondrial ROS, mitochondrial membrane potential (MMP), and ATP were measured using relevant kits. The mitochondrial ultrastructure was observed under transmission electron microscopy. Cell apoptosis was determined by Western blot and TUNEL assays. Saliva was measured from Wharton’s duct. We found that salidroside protected SMG cells and tissues against radiation and improved the secretion function. Moreover, salidroside enhanced the antioxidant defense by decreasing MDA, increasing SOD, CAT, and GSH, and scavenging mitochondrial ROS. Furthermore, salidroside rescued the mitochondrial ultrastructure, preserved MMP and ATP, suppressed cytosolic cytochrome c and cleaved caspase 3 expression, and inhibited cell apoptosis. Together, these findings first identify salidroside as a mitochondrial-targeted antioxidant for preventing SG radiation damage.