Miracle-dz/UniFAR-FTUs huggingface dataset:
Polyopes affinis Suppressed IFN-γ- and TNF-α-Induced Inflammation in Human Keratinocytes via Down-Regulation of the NF-κB and STAT1 Pathways

Polyopes affinis is a red algal species commonly found on the South coast and near Jeju Island, Korea. This study aimed to determine whether P. affinis extracts can inhibit the pathogenesis of T-helper-2 (Th2)-mediated inflammation in a human keratinocyte cell line of atopic dermatitis (AD). Cells were incubated with 10 ng/mL of interferon gamma (IFN-γ) and 10 ng/mL of tumor necrosis factor-alpha (TNF-α) at various concentrations of PAB (10, 30, and 60 µg/mL) and PAA (100, 500, and 1000 µg/mL) extracts. A gene-ontology (GO)-enrichment analysis revealed that PAB significantly enriched the genes associated with biological processes such as cell adhesion, immune response, inflammation, and chemokine-mediated pathways. PAB suppressed the expression of the secretory proteins and mRNAs that are associated with the thymus and the production of activation-regulated chemokines (TARC/CCL17) and macrophage-derived chemokines (MDC/CCL22). The effect of the extract on mitogen-activated protein kinases (MAPKs) was related to its inhibition of TARC/CCL17 and MDC/CCL22 production by blocking NF-κB and STAT1 activation. These results suggest that seaweed extract may improve AD by regulating pro-inflammatory chemokines. In conclusion, we first confirmed the existence of phloroglucinol, a polyphenol formed from a precursor called phlorotannin, which is present in PAB, and this result proved the possibility of PAB being used as a treatment for AD.
A sentiment analysis model of Agritech startup on Facebook comments using naive Bayes classifier

Facebook page is a tool able to generate perceptions and acceptance, and support people and investors in making business decisions. Moreover, Facebook page plays a part in engaging people in the form of a community. People share experiences and opinions toward products, services, and trends in particular periods on the Facebook page community. Regarding sentiment analysis on Facebook pages, most education and other general topics in English have only been analyzed in English. However, sentiment analysis regarding Agritech startups topics in Thai language has not been done yet. This study analyzes opinions and categorizes positive and negative comments by using naive Bayes classifier to examine the sentiments and attitudes of people and investors. The results could possibly reflect the perception rate of Agritech startups in Thailand and could be applied to explain attentiveness and assess people’s engagement opinions. Furthermore, it could be applied in studying consumer behavior, marketing analysis, spread of information, and attitudes. The study's model is generic and could be applied in other contexts to provide insightful suggestions.
Two-Stage Strategy to Achieve a Reinforcement Learning-Based Upset Recovery Policy for Aircraft

Aircraft upset situations are the highest risk to civil aviation. Thus, a reliable upset recovery policy is necessary for aircraft. In this paper, a two-stage strategy to achieve a reinforcement learning (RL)-based upset recovery policy that takes time of recovery and loss of altitude into account is proposed for aircraft to recover from an arbitration upset situation to level flight. Based on the proposed two-stage strategy and Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, an algorithm to achieve a TD3-based upset recovery policy for aircraft is developed. Experiments are conducted based on X-Plane 11 to evaluate the effectiveness of the proposed two-stage strategy and the performance of the achieved upset recovery policy in stall recovery and spin recovery.
Grasp Planning Based on Deep Reinforcement Learning: A Brief Survey

Grasping is a fundamental ability for robots to inter-act with the environment. Recent advances show great progress on grasping unstructured household objects by leveraging deep reinforcement learning. This paper presents a brief survey on grasp planning based on deep reinforcement learning. The goal of grasp planning is to determine the actions of the robotic manipulator moving from its initial position to the target one so that the object could be grasped and manipulated. However, objects could be stacked or occluded, making the target object ungraspable by applying a simple grasp action. To tackle this issue, auxiliary actions (such as pushing) should be conducted along with grasping. According to whether auxiliary actions are performed, we categorize the existing grasping planning methods into two classes: methods without auxiliary actions and methods with auxiliary actions. We review them in details and show the advantages and limitations of each type. Furthermore, we show several popular evaluation metrics that are widely used in grasp planning. Finally, difficulties and future research directions are discussed.
The Hyperbranched Polyester Reinforced Unsaturated Polyester Resin

We report a method of reinforcing and toughening unsaturated polyester resin (UPR) with a kind of hyperbranched polyester (HBP-1). Polyethylene glycol with different molecular weight was used as the core molecule of the preparation reaction, and the reaction product of phthalic anhydride and glycerol was used as the branching unit. The esterification reaction of polycondensation occurred, and then the hydroxyl-terminated hyperbranched polyester was prepared. The reaction product of maleic anhydride and isooctanol was added to the prepared hydroxyl-terminated hyperbranched polyester for esterification reaction. Both ends of the hyperbranched polyester had unsaturated double bond to obtain the hyperbranched polyester (HBP-1). The effects of this treatment on the morphology, mechanical properties and thermal properties of the composites were studied in detail. The HBP-1 was investigated by Fourier Transform Infrared Spectroscopy (FT-IR). The HBP-1/UPR composites were investigated by Thermogravimetric Analysis (TGA), Dynamic Mechanical Analysis (DMA), mechanical properties analysis and Scanning Electron Microscope (SEM). The results showed that HBP-1 enhanced the thermostability and mechanical properties of UPR. However, DMA indicated that the addition of HBP-1 cannot effectively improve the thermodynamic properties of UPR due to the flexible chain in HBP-1 structure. The HBP-1 improves tensile strength, bending strength and impact strength compared to neat UPR.
An Asymmetric Direct-Connected Network for Rolling Bearing Fault Diagnosis

Rolling bearings have be extensively applied in applications of intelligent manufacturing, such as rotating machinery, and the fault diagnosis of rolling bearings is critical to mitigate the production and economics losses. Deep learning, taking the advantage in signal processing, have been widely used in fault diagnosis. However, existing deep-learning-based fault diagnosis cannot be directly and easily applied to process the signal of rolling bearing. In addition, some existing scheme suffer from severe performance degradation in variable noisy environments or variable working loads. To address these issues, in this paper, an asymmetric direct-connected network, namely ADNet, is proposed to effectively diagnose faults of rolling bearing with deep learning technologies. To be specific, in our ADNet, the one-dimensional bearing signal firstly is converted into the recurrence plot (i.e., two-dimensional image), and multiple direct connection blocks (DCBs) that are nested with asymmetric convolution transformation (ACT) modules are proposed to extracted the detailed convolved feature map of faults. Finally, through the softmax classifier, the faults can be effectively identified by our ADNet based on the detailed convolved feature map of faults. Via evaluations, the data demonstrate that our ADNet can achieve great scalability and accuracy on faults diagnosis of rolling bearing in both variable noisy environments and variable working loads.
Hyperspectral Image Classification for Foreign Bodies in Medicine Based on Spatial-Spectral Fusion Feature

As the cornerstone of the pharmaceutical industry and the important guarantee for people’s health, pharmaceutical safety has attracted more and more attention from both inside and outside the industry, in which the detection of foreign bodies has always been an important link. In view of the advantages of hyperspectral technology in material classification, a new hyperspectral classification method for foreign body detection in medicine based on spatial-spectral fusion feature is proposed in this paper, aiming at the problems of "dimension disaster" and low fusion degree of spectral feature and spatial feature. Firstly, a method combining PCA dimension reduction of band clustering grouping with semi-supervised LDA is proposed to extract spectral feature, while 2D Gabor filter is used to extract spatial feature. Then, a feature fusion network based on attention mechanism is proposed to fuse the spectral feature and spatial feature. Finally, the full connection layer and softmax classifier are used to realize the detection and classification of foreign bodies in medicine. The proposed method is applied to our own medicine data set, and the experiments constantly prove the effectiveness and superiority of our method.
COVID-19 Vaccination among Czech Dentists

This work describes and evaluates vaccination against COVID-19 among members of the Czech Dental Chamber during the pre-booster vaccination phase. A cross-sectional online survey was conducted between 23 June and 4 September 2021, among 2716 participants, representing 24.3% of all chamber members. A total of 89.5% of respondents stated that they were registered for vaccination against COVID-19, their vaccination had started or been completed, or had a medically relevant reason to avoid vaccination. A total of 79.6% of respondents stated that they were fully vaccinated, most of them with the Comirnaty (Pfizer–BioNTech) vaccine (88.3%). The vaccination rate among males was significantly higher than among females (p = 0.001, OR 1.48). The main reasons for vaccination were professional (91.5%). The share of fully vaccinated participants was significantly higher (p < 0.0001, OR = 8.17) compared to the Czech general population (30.8%). A COVID-19 vaccine breakthrough infection rate was 0.42%. The study shows that both the willingness to vaccinate and the proportion of fully vaccinated individuals among Czech dentists are high, and only about 10% of them refused vaccination based on reasons classified as not medically relevant.
Automatic recognition of Arabic alphabets sign language using deep learning

Technological advancements are helping people with special needs overcome many communications’ obstacles. Deep learning and computer vision models are innovative leaps nowadays in facilitating unprecedented tasks in human interactions. The Arabic language is always a rich research area. In this paper, different deep learning models were applied to test the accuracy and efficiency obtained in automatic Arabic sign language recognition. In this paper, we provide a novel framework for the automatic detection of Arabic sign language, based on transfer learning applied on popular deep learning models for image processing. Specifically, by training AlexNet, VGGNet and GoogleNet/Inception models, along with testing the efficiency of shallow learning approaches based on support vector machine (SVM) and nearest neighbors algorithms as baselines. As a result, we propose a novel approach for the automatic recognition of Arabic alphabets in sign language based on VGGNet architecture which outperformed the other trained models. The proposed model is set to present promising results in recognizing Arabic sign language with an accuracy score of 97%. The suggested models are tested against a recent fully-labeled dataset of Arabic sign language images. The dataset contains 54,049 images, which is considered the first large and comprehensive real dataset of Arabic sign language to the furthest we know.
Impact assessments of wind farms on seabird populations that overlook existing drivers of demographic change should be treated with caution

Population viability analyses (PVA) are now routinely used during the consenting process for offshore wind energy developments to assess potential impacts to vulnerable species, such as seabirds. These models are typically based on mean vital rates, such as survival and fecundity, with some level of environmental stochasticity (i.e., temporal variation). However, many species of seabird are experiencing population decline due to temporal (i.e., directional) trends in their vital rates. We assess the prevalence of temporal trends in rates of fecundity for a sentinel species of seabird, the black‐legged kittiwake Rissa tridactyla, and examine how accounting for these relationships affects the predictive accuracy of PVA, as well as the projected population response to an extrinsic threat. We found that temporal trends in kittiwake rates of fecundity are widespread, and that including these trends in PVA assessments dramatically influences the projected rate of population decline. We advocate that model validation become a prerequisite step in seabird PVA assessments to identify potential biases influencing the projected population response. We also argue that environmental factors driving current population dynamics need to be incorporated in PVA impact assessments as potential “worst‐case” scenarios. These findings have immediate application for improving and reducing uncertainty in impact assessments conducted as part of the consenting process for offshore wind energy developments.
Emerging Role of Nuclear Receptors for the Treatment of NAFLD and NASH

Non-alcoholic fatty liver (NAFLD) over the past years has become a metabolic pandemic linked to a collection of metabolic diseases. The nuclear receptors ERRs, REV-ERBs, RORs, FXR, PPARs, and LXR are master regulators of metabolism and liver physiology. The characterization of these nuclear receptors and their biology has promoted the development of synthetic ligands. The possibility of targeting these receptors to treat NAFLD is promising, as several compounds including Cilofexor, thiazolidinediones, and Saroglitazar are currently undergoing clinical trials. This review focuses on the latest development of the pharmacology of these metabolic nuclear receptors and how they may be utilized to treat NAFLD and subsequent comorbidities.
The Evolution of the Library Media Center: A Study of the Past, Current, and Projected Future Library Services Available in Johnson City, Tennessee

The purpose of this qualitative study was to indicate changes in library services available to the citizens of Johnson City, Tennessee. The study covered library services available in educational and public settings for patrons from preschool to adult ages. Librarians in this study all worked in either a public library located in Johnson City, TN or worked in the Johnson City School System as a media specialist in either an elementary, middle, or high school. This qualitative study was conducted using interviews of librarians to gain their perceptions of the library and their roles within the libraries of Johnson City. Librarians were interviewed to determine their views in the past, present, and future of the library as an establishment. Documents from the various libraries were also analyzed to determine changes in library services. Various themes emerged from the data analysis. Participants discussed their roles as librarians, the library as an institution, and collection development. Other themes that emerged were discussions of library materials that were now or would become archaic. Participants also made projections as to the future of the library itself and whether or not it would become obsolete. 3 The results of this study suggest that libraries will continue to evolve as technologies and community needs and expectations change. The appearance of the library will evolve to contain more learning spaces for active and group learning. The role of the librarian will evolve as the technology evolves. It will become more focused upon teaching patrons how to use learning tools and access information rather than simply managing and controlling the library's assets. The librarians' role has the potential to become one of service leadership in the community and in the school setting. The impact of the library and the librarians' role will directly affect students, teachers, and community members. Recommendations from this study may assist in transitioning the librarian/media specialist's role to a great service leadership model that supports individual growth and community development. 4 DEDICATION I would like to dedicate this study to my many family members who were there for me throughout this process. To my husband Craig Hawley, thank you for your patience as this endeavor took much more time for me to complete than it should have. To my children Gabe and Isabel Hawley, thank you for constantly encouraging me and being my special cheerleaders. The dedication you show in your undertakings encouraged me. …
Impedance control of slag removal robot based on Q-Learning

Due to the time-varying contact force of molten metal, it is a challenging work to realize the accurate slag pushing of industrial robot. In order to solve this problem, this paper proposes an impedance control method based on reinforcement learning. Firstly, the impedance model of the industrial robot system is established, and the Maxwell stress model which describes the contact between the end-effector of the manipulator and the molten metal surface is established. Then, on the basis of the idea of Q-learning and system linearization, an online correction strategy of impedance parameters based on reinforcement learning is designed. At the same time, the stability of the proposed method is analyzed theoretically. Finally, the proposed intelligent impedance control strategy is successfully applied to the slag pushing simulation of Rokae robot. And compared with the existing control methods, the superiority of the control method is proved to a certain extent.
Formation and Ensuring Multi-Level System of Social Security of Ukraine in the Context of State Regulation

Creating conditions for the safety of man, society and the state is an important strategic priority of public administration in Ukraine. The practice of state regulation in our country is not based on a multi-level system of social security of a person, society and the state. The purpose of the article is to study the problems of formation and ensuring social security of a person, society and the state in Ukraine as a multi-level system. It is based on security and balance of social interests of a person, state and society. A multi-level system is capable of ensuring socio-economic stability and internal stability in the face of increasing external and internal threats. The authors determined the essence of social security as a multi-level system from the standpoint of systemic, structural-functional, substantial approaches. The authors also identified the relationship of subjects and objects in the social security system, assessed the impact of the areas of national security on the level of social security in Ukraine; revealed the main obstacles to the implementation of a multi-level system of social security of a person, society and the state in Ukraine. The authors substantiated the structural model of a multi-level system of social security based on the relationship and balance of the social interests of a person, society and the state.
Influence of the dominant thinking style in the degree of novelty of designs in virtual and traditional working environments

ABSTRACT One's thinking and reasoning style defines individual preferences when interacting and communicating with others. This work aims to analyse whether the thinking and reasoning style of the design teams exerts an influence on the degree of novelty of the design outcomes in two working environments: a face-to-face environment and a virtual environment. To address this, an experiment was set up in which 21 teams, each made up of 3 design students, were asked to obtain new solutions to 2 design problems, one of them in a face-to-face environment and the other in a virtual environment. The teams were defined according to their thinking and reasoning style, and the novelty of the design outcomes was measured with the SAPPhIRE model of causality. The results show that, overall, the degree of novelty is very similar in both environments, although it is a little higher in virtual environments. Teams with a rational style produce more novel results when using information and communication technologies than in a face-to-face environment. Teams with an interpersonal style, on the other hand, generate the least novel solutions when using technologies and produce the most novel solutions when they work in a face-to-face environment.
Evidence of Influenza A Virus Infection in Cynomolgus Macaques, Thailand

Little is known about the ecology of influenza A virus (IAV) in nonhuman primates (NHPs). We conducted active surveillance of IAV among 672 cynomolgus macaques (Macaca fascicularis) living in 27 free-ranging colonies in Thailand between March and November 2019. A hemagglutination inhibition (HI) assay was employed as the screening test against 16 subtypes of avian influenza virus (AIV) and two strains of the H1 subtype of human influenza virus. The serum samples with HI titers ≥20 were further confirmed by microneutralization (MN) assay. Real-time RT-PCR assay was performed to detect the conserved region of the influenza matrix (M) gene. The seropositive rate for subtypes of IAV, including AIV H1 (1.6%, 11/672), AIV H2 (15.2%, 102/672), AIV H3 (0.3%, 2/672), AIV H9 (3.4%, 23/672), and human H1 (NP-045) (0.9%, 6/672), was demonstrated. We also found antibody against more than one subtype of IAV in 15 out of 128 positive tested sera (11.7%). Moreover, influenza genome could be detected in 1 out of 245 pool swab samples (0.41%). Evidence of IAV infection presented here emphasizes the role of NHPs in the ecology of the virus. Our findings highlight the need to further conduct a continuous active surveillance program in NHP populations.
Robotic Arm Intelligent Grasping System for Garbage Recycling

The recycling of garbage is an effective way to protect environment. However, garbage recycling is still adopting manual sorting which is of low efficiency and may damage to the health of operators. To improve the efficiency of the garbage recycling, it is considered to use an automated robot system which integrates modern control method of robots and machine vision to replace manual sorting. Using a robotic arm and a RGB-D camera, a visual servo robotic arm grasping system was produced, which mainly depends on tools in robot operating system (ROS). The object recognition kitchen (ORK) in ROS is used to identify and locate the grasping targets. The relationship between the camera coordinate system and the robot coordinate system is established by hand-eye calibration technology. The kinematics calculation and motion planning of the robotic arm are completed with the help of ROS-Moveit! Through experimental testing, it is estimated that the hand-eye calibration is accurate, and the robotic arm can perfectly grasp the target object.