Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct and Coordinated Regulation of Small Non-coding RNAs by E2f1 and p53 During Drosophila Development and in Response to DNA Damage

Small non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs), play a pivotal role in biological processes. A comprehensive quantitative reference of small ncRNAs expression during development and in DNA damage response (DDR) would significantly advance our understanding of their roles. In this study, we systemically analyzed the expression profile of miRNAs and piRNAs in wild-type flies, e2f1 mutant, p53 mutant and e2f1 p53 double mutant during development and after X-ray irradiation. By using small RNA sequencing and bioinformatic analysis, we found that both miRNAs and piRNAs were expressed in a dynamic mode and formed 4 distinct clusters during development. Notably, the expression pattern of miRNAs and piRNAs was changed in e2f1 mutant at multiple developmental stages, while retained in p53 mutant, indicating a critical role of E2f1 played in mediating small ncRNAs expression. Moreover, we identified differentially expressed (DE) small ncRNAs in e2f1 mutant and p53 mutant after X-ray irradiation. Furthermore, we mapped the binding motif of E2f1 and p53 around the small ncRNAs. Our data suggested that E2f1 and p53 work differently yet coordinately to regulate small ncRNAs expression, and E2f1 may play a major role to regulate miRNAs during development and after X-ray irradiation. Collectively, our results provide comprehensive characterization of small ncRNAs, as well as the regulatory roles of E2f1 and p53 in small ncRNAs expression, during development and in DNA damage response, which reveal new insights into the small ncRNAs biology.
Simulating Defensive Trajectories in American Football for Predicting League Average Defensive Movements

American football is an appealing field of research for the use of information technology. While much effort is made to analyze the offensive team in recent years, reasoning about defensive behavior is an emergent topic. As defensive performance and positioning largely contribute to the overall success of the whole team, this study introduces a method to simulate defensive trajectories. The simulation is evaluated by comparing the movements in individual plays to a simulated league average behavior. A data-driven ghosting approach is proposed. Deep neural networks are trained with a multi-agent imitation learning approach, using the tracking data of players of a whole National Football League (NFL) regular season. To evaluate the quality of the predicted movements, a formation-based pass completion probability model is introduced. With the implementation of a learnable order invariant model, based on insights of molecular dynamical machine learning, the accuracy of the model is increased to 81%. The trained pass completion probability model is used to evaluate the ghosted trajectories and serves as a metric to compare the true trajectory to the ghosted ones. Additionally, the study evaluates the ghosting approach with respect to different optimization methods and dataset augmentation. It is shown that a multi-agent imitation learning approach trained with a dataset aggregation method outperforms baseline approaches on the dataset. This network and evaluation scheme presents a new method for teams, sports analysts, and sports scientists to evaluate defensive plays in American football and lays the foundation for more sophisticated data-driven simulation methods.
An Ontology-Based Framework for Psychological Monitoring in Education During the COVID-19 Pandemic

Background Especially in the current crisis of the COVID-19 pandemic and the lockdown it entailed, technology became crucial. Machines need to be able to interpret and represent human behavior, to improve human interaction with technology. This holds for all domains but even more so for the domain of student behavior in relation to education and psychological well-being. Methods This work presents the theoretical framework of a psychologically driven computing ontology, CCOnto, describing situation-based human behavior in relation to psychological states and traits. In this manuscript, we use and apply CCOnto as a theoretical and formal description system to categorize psychological factors that influence student behavior during the COVID-19 situation. By doing so, we show the added value of ontologies, i.e., their ability to automatically organize information from unstructured human data by identifying and categorizing relevant psychological concepts. Results The already existing CCOnto was modified to automatically categorize university students’ state and trait markers related to different aspects of student behavior, including learning, worrying, health, and socially based on psychological theorizing and psychological data conceptualization. Discussion The paper discusses the potential advantages of using ontologies for describing and modeling psychological research questions. The handling of dataset completion, unification, and its explanation by means of Artificial Intelligence and Machine Learning models is also discussed.
Sense of Coherence and Mental Health in College Students After Returning to School During COVID-19: The Moderating Role of Media Exposure

The COVID-19 pandemic not only threatens people’s physical health, but also affects their mental health in the long term. Although people had returned to work and school, they are closely monitoring the development of the epidemic and taking preventive measures. This study attempted to examine the relationship between media exposure, sense of coherence (SOC) and mental health, and the moderating effect of media exposure in college students after returning to school. In the present study, we conducted a cross sectional survey on 424 college students returning to school around May 2020. Self-report questionnaires were used to assess media exposure scale, SOC, depression, anxiety and stress. Correlation and moderation analysis was conducted. The results showed that (1) negative epidemic information exposure, rather than positive epidemic information exposure, was significantly associated with depression, anxiety, and stress. (2) SOC was also associated with depression, anxiety, and stress. (3) The effect of SOC on depression was modified by negative epidemic information exposure. With the increase of negative epidemic information exposure, the predictive effect of SOC on depression is increasing gradually. These findings demonstrated that negative epidemic information exposure was associated with an increased psychological distress in the sample. A high SOC played a certain protective role in the adaptation of college students in the post-epidemic period. It is important to find more ways to increase the colleges’ SOC level and avoid negative information exposure.
Development and Validation of the Prognostic Index Based on Inflammation-Related Gene Analysis in Idiopathic Pulmonary Fibrosis

Background: Historically, idiopathic pulmonary fibrosis (IPF) was considered a chronic inflammation disorder, but this conception was reassessed in the past decades. Our understanding of the role of inflammation in IPF and its association with clinical significance remained incomplete. Methods: We downloaded mRNA expression data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus (GEO) repository. Inflammation-related genes (IRGs) expressed differently between IPF and control (CTRL) were determined. In this study, we systemically analyzed the expression of differently expressed IRGs by comprehensive bioinformatic analysis, and then investigated their potential prognostic values. The related prognostic gene expressions were verified in our cohort. Results: 110 differently expressed IRGs were identified in this study, including 64 upregulated and 46 downregulated IRGs. Three IRGs (S100A12, CCR7, and TNFSF4) were identified as potential hub genes for prognosis. Those genes were subsequently subjected to the construction of the prognostic models. In the results, IPF patients categorized as high risk demonstrated a poor overall survival rate compared to patients categorized as low risk. Based on this prognostic model, the area under the curve (AUC) of the survival-dependent receiver operator characteristic (ROC) for 1-year, 2-year, and 3-year survival rates was 0.611, 0.695, and 0.681, respectively, in the GSE28042 cohort. These observations were validated in the GSE27957 cohort, confirming the good prognostic effect of this model. The expression of the three genes was validated in our cohort. We also conducted a nomogram based on the three IRGs’ mRNA for quantitative IPF prognosis. Conclusion: Three IRGs (S100A12, CCR7, and TNFSF4) were identified as potential markers for the prognosis of IPF.
Real Men Don’t Say ‘‘Cute’’: Using Automatic Language Analysis to Isolate Inaccurate Aspects of Stereotypes

People associate certain behaviors with certain social groups. These stereotypical beliefs consist of both accurate and inaccurate associations. Using large-scale, data-driven methods with social media as a context, we isolate stereotypes by using verbal expression. Across four social categories—gender, age, education level, and political orientation—we identify words and phrases that lead people to incorrectly guess the social category of the writer. Although raters often correctly categorize authors, they overestimate the importance of some stereotype-congruent signal. Findings suggest that data-driven approaches might be a valuable and ecologically valid tool for identifying even subtle aspects of stereotypes and highlighting the facets that are exaggerated or misapplied.
Chemical Composition, Antioxidant, Anti-inflammatory and Anticancer Activities of Bark Essential Oil of Cryptocarya amygdalina from India

Abstract Several species of Cryptocarya (Lauraceae) are traditionally used in folk medicines for the treatment of various diseases and disorders in tropical and subtropical countries. The essential oil extracted from the leaves and barks of Cryptocarya species are reported to possess antimicrobial, insecticidal, antioxidant, and antitumoral activities. However, there are no scientific reports on the biological activity of essential oil extracted from the tropical Asiatic species Cryptocarya amygdalina. The present study was undertaken to determine the chemical composition and evaluate the antioxidant, anticancer, and anti-inflammatory activities of bark essential oil of C. amygdalina. A total of 57 constituents accounting for 99.05 % of the total essential oil content were identified by GC/MS. The bark essential oil was dominated by sesquiterpene hydrocarbons (78.71 %) with β- caryophyllene (34.77 %), α-copaene (14.26 %), bicyclogermacrene (7.65 %), and δ-cadinene (4.42 %) as the major constituents. The essential oil exhibited good radical scavenging activity against DPPH, ABTS, and Reducing power assay with half-maximal inhibitory concentration (IC50) values of 6.97 ± 0.24, 1.28 ± 0.07, and 9.23 ± 0.34 μg/mL, respectively compared to ascorbic acid and BHT. The Pearson’s coefficient analysis showed a significant correlation between TPC, TFC, and an antioxidant assay of C. amygdalina essential oil. The essential oil also showed potent cytotoxicity against human colon (HCT-116) and ovarian (PA-1) cancer cell lines with IC50 values lesser than 50 μg/mL in both cases. Besides, this bark essential oil at 50 μg/mL concentration exhibited significant anti-inflammatory activity in lipopolysaccharide-activated RAW 264.7 macrophages by inhibiting nitric oxide production.
Branding Rhetoric in Times of a Global Pandemic: A Text-Mining Analysis

Abstract As the Covid-19 pandemic unfolded, academics and practitioners alike wondered how and to what extent brands should adapt their advertising and communication efforts to remain resonant and to engage their audiences. Gathering and processing a unique data set composed of about 12,000 tweets of 76 leading brands associated with seven Italian industries, this research examines how rhetorical appeals that brands adopted evolved on Twitter during the pandemic. Theoretically, the research is grounded on an institutional logic perspective and resorts to the Aristotelian categories of logos, ethos, and pathos to make sense of the rhetorical appeals brands adopted. Methodologically, we relied on the most recent text-mining protocols in marketing studies. Our analyses outline that during the lockdown brands resorted to emotive appeals characterized by intense ethical and social overtones. Regarding consumers’ response in their social media engagement, we find they appreciated this strategy the brands followed.
The Facial Expression Recognition Method Based on Image Fusion and CNN

Abstract Facial expression recognition (FER) is an important task in the field of human-computer interaction. However, the traditional facial expression recognition task needs to be based on the hand-crafted features, and the feature extraction method is single; the facial expression recognition task based on deep learning cannot extract local texture features of the image and loss more information. Therefore, a facial expression recognition method based on image fusion and convolution neural network (FERFC) is proposed in this paper. Which fused the facial expression images after extracted by the local binary pattern (LBP) with the original images. It can effectively improved the utilization of images. Firstly, some image pre-processing approaches are used in this paper, such as data augmentation, face detection and data normalization. Secondly, the images of local texture features extracted by the LBP and the original images are fused in this step. Finally, the task of facial expression features learning and classification is completed by convolution neural network (CNN). The results show that the method proposed in this paper can accomplish the facial expression recognition task accurately. The recognition rate of reference database ‘Jaffe’, ‘CK+’ and ‘FER2013’ is 91.9%, 95.6% and 75.9%. The results show that the FERFC has significant advantages than traditional facial expression recognition. At the same time, the number of training samples is small, the FERFC still has obvious advantages and a higher robustness.
From customer value co-creation behaviour to customer perceived value

ABSTRACT This study investigates the chain effect of customer value co-creation behaviour on the customerization capability and service capability of service firms and, ultimately, customer perceived value. The study evaluates the moderating roles of the level of technologization and relationship marketing orientation in the relationship between customer value co-creation behaviour and the capabilities of firms. The data were collected from dyadic interaction between customers and the service staff of service firms in Vietnam through surveys. The results show that customer citizenship behaviour and participation behaviour are differentially linked to the customerization capability, and service capability of service firms, which in turn affect customer perceived values. Relationship marketing orientation serves as a significant moderator for customerization capability, yet it is not a significant moderator for service capability. Surprisingly, the level of technologization does not significantly moderate for both customerization capability and service capability. The study advances the literature of value co-creation and offers useful managerial implications.
COVID-19 Uncertainty and Temporal Framing in Advertising for Online Experiential Consumption

Abstract During the period of uncertainty and lack of control caused by the COVID-19 pandemic, we investigated how consumers evaluate online experiences using messages framed in different temporal perspectives. In the midst of the coronavirus outbreak, companies have been offering their experiential services online either in single long sessions (i.e., proximal framed message) or multiple short sessions over time (i.e., distal framed message). We found significant two-way interactions between temporal frames and levels of uncertainty, such that consumers with high (vs. low) levels of uncertainty respond more favorably when a distal (vs. proximal) framed message is applied. The path from fluency to high-control coping explained the interaction effect between temporal framing and levels of uncertainty on behavioral outcomes toward experience goods.
Kombucha based synbiotic beverage using Yacon (Smallanthus sonchifolius) as a fermentation substrate: development and sensorial analysis

Probiotic and prebiotic beverages are promoters of the growth and maintenance of healthy intestinal microbiota composition. However, a drink that gathers the therapeutic attributes of Yacon with symbiotic multiple yeast-bacteria colonies, like Kombucha, has not yet been explored and appears to be potentially beneficial for human health. The objectives of this work were to develop a low-sugar Kombucha beverage using Yacon as fermentation substrate, labelled as Yacon-Kombucha (YK), with physical-chemical properties and sensorial acceptability compatible with the traditional Sugar-Kombucha (SK). Two beverages were prepared following standard procedures and fermented for 14 days. The pH, acidity, Brix and glucose content were evaluated at days 0, 4, 7, 9 and 14. The sensorial panel used a hedonic scale of 7 points considering colour, aroma, taste and global acceptability attributes for SK and YK final product. At the end of fermentation, obtained were beverages in which YK was less acidic and had the lowest glucose content when compared to SK. The sensorial analysis revealed no significant differences between the two samples for the tested attributes, also no rejection was observed. However, the scores received for both drinks were moderate, with the Index of acceptability for SK as 75% and YK 72%. Improvements in the aroma and taste are necessary for an accessible yacon-Kombucha beverage. The development of a low-sugar synbiotic beverage was possible and it may present benefits to gut microbiota and other health properties and can be consumed by individuals with diabetes.
Exponential Runge ‐ Kutta methods for stiff stochastic differential equations

It is well known that the numerical solution of stiff stochastic differen‐ tial equations (SDEs) leads to a stepsize reduction when explicit methods are used. However, there are some classes of explicit methods that are well suited to solv‐ ing some types of stiff SDEs. One such class is the class of stochastic orthogonal Runge‐Kutta Chebyshev (SROCK) methods. SROCK methods reduce to Runge‐ Kutta Chebyshev methods when applied to ordinary differential equations (ODEs). Another promising class of methods is the class of explicit methods that reduce to ex‐ plicit exponential Runge‐Kutta (RK) methods when applied to semilinear ODEs. In the present paper, such explicit methods are considered. As a result, the stochastic exponential Euler scheme will be derived for strong approximations to the solution of stiff Itô SDEs with a semilinear drift term. In addition, stochastic exponential RK methods will be derived for weak approximations.
Influence of Interphase Properties on the Behavior of Wavy Carbon Nanotube Reinforced Composites

CNTs (carbon nanotubes) are ideal reinforcing materials for high strength polymer nanocomposites because of their high stiffness, strength and resilience properties. CNT-matrix interface is one of the parameters effecting the stiffness of nanocomposites. In this study, the effect of CNT-matrix interface properties on the effective global stiffness of nanocomposites is investigated numerically. A representative volume element (RVE) is modeled by using the finite element method (FEM) to predict the elastic behavior in micro level. The finite element model consists of three phases namely matrix, CNT and interphase. The stiffness is obtained from the elastic response of RVE subjected to an axial loading. The stiffness values are obtained for several thickness and modulus values of the interface and the waviness of CNT. Effective global stiffness is calculated by using Mori-Tanaka method where CNTs have varying amount of waviness, interphase properties and random orientations. It is found that there are significant effects of the interface on the effective global stiffness.
Anion and Cation Order in Iodide-Bearing Mg/Zn–Al Layered Double Hydroxides

Uptake of iodine in hydrotalcite-like minerals is a potential retardation mechanism for dose-relevant 129I in the near-field of a deep repository for radioactive waste. The location of iodide in (Zn/Mg)Al layered double hydroxides (LDH) was investigated using a combination of advanced atomic-scale techniques. Wavelet transform analysis of Zn K-edge extended X-ray absorption fine structure (EXAFS) spectra and geometry optimization based on ab initio density functional calculations allowed the distribution of Al3+ in the cationic layer to be determined. Using Rietveld refinement of synchrotron X-ray powder diffraction data (XRD) and EXAFS at the I K-edge enabled the average location of iodide in the interlayer to be established. Additional short- and medium-range structural information was also obtained from the pair distribution function analysis of the XRD data in support of the findings obtained with the long- and short-range techniques. By combining the results, a local order of Al3+ in Zn2Al–I and Zn3A.
Laryngeal mask airway protector generates higher oropharyngeal leak pressures compared to the laryngeal mask airway supreme: A randomized clinical trial in the ambulatory surgery unit

Background and Aims: The Laryngeal Mask Airway (LMA) Protector™ is one of the latest introduced supraglottic airway devices. It provides access and functional separation of the respiratory and digestive tracts. Compared to the LMA Supreme™, it has two digestive ports, one to provide suction in the pharyngeal region and one for gastric tube insertion. High oropharyngeal leak pressure is a marker for safe ventilation when using LMA devices. We hypothesized that oropharyngeal leak pressure of the LMA Protector™ is 5 cm H2O higher than the oropharyngeal leak pressure of the LMA Supreme™ at various cuff volumes. Secondary outcome measures were ease of insertion of both masks, fiberoptic confirmation of correct positioning, failures of insertion, presence of blood staining, sore throat, presence of air leak and insertion time. < Material and Methods: American Society of Anesthesiologists (ASA) I-III patients aged >18 years, scheduled for elective minor ambulatory surgery under general anesthesia with a LMA were included. Patients were randomized in the LMA Protector™ or LMA Supreme™ group based on a computer-generated random sequence table. After general anesthesia induction, oropharyngeal leak pressures were measured. < Results: Oropharyngeal leak pressures were significantly higher (P < 0.0001) for LMA Protector™ compared to LMA Supreme™ at different cuff volumes and a cuff pressure of 65 cm H2O. Insertion time was significantly higher for the LMA Protector™ (29 sec) [interquartile range (IQR) 23, 35] compared to the LMA Supreme™ (19 sec) (IQR 16, 22) (P < 0.0001). There were no statistically significant differences in ease of insertion (number of attempts for succesful positioning), failures of insertion, presence of blood staining, sore throat or presence of air leak. Conclusion: Oropharyngeal leak pressures were consistently higher (>5 cm H2O) for LMA Protector™ compared to LMA Supreme™. LMA Protector™, therefore, allows effective ventilation at higher airway pressures than LMA Supreme™. Trial Registration: http://clinicaltrials.gov. NCT03462550.