Miracle-dz/UniFAR-FTUs huggingface dataset:
¹H-NMR Metabolic Profiling, Antioxidant Activity, and Docking Study of Common Medicinal Plant-Derived Honey

The purpose of this investigation was to determine ¹H-NMR profiling and antioxidant activity of the most common types of honey, namely, citrus honey (HC1) (Morcott tangerine L. and Jaffa orange L.), marjoram honey (HM1) (Origanum majorana L.), and clover honey (HT1) (Trifolium alexandrinum L.), compared to their secondary metabolites (HC2, HM2, HT2, respectively). By using a ¹H-NMR-based metabolomic technique, PCA, and PLS-DA multivariate analysis, we found that HC2, HM2, HC1, and HM1 were clustered together. However, HT1 and HT2 were quite far from these and each other. This indicated that HC1, HM1, HC2, and HM2 have similar chemical compositions, while HT1 and HT2 were unique in their chemical profiles. Antioxidation potentials were determined colorimetrically for scavenging activities against DPPH, ABTS, ORAC, 5-LOX, and metal chelating activity in all honey extract samples and their secondary metabolites. Our results revealed that HC2 and HM2 possessed more antioxidant activities than HT2 in vitro. HC2 demonstrated the highest antioxidant effect in all assays, followed by HM2 (DPPH assay: IC50 2.91, 10.7 μg/mL; ABTS assay: 431.2, 210.24 at 50 ug/mL Trolox equivalent; ORAC assay: 259.5, 234.8 at 50 ug/mL Trolox equivalent; 5-LOX screening assay/IC50: 2.293, 6.136 ug/mL; and metal chelating activity at 50 ug/mL: 73.34526%, 63.75881% inhibition). We suggest that the presence of some secondary metabolites in HC and HM, such as hesperetin, linalool, and caffeic acid, increased the antioxidant activity in citrus and marjoram compared to clover honey.
A Review of: “Design and Analysis of Quality of Life Studies in Clinical Trials, 2nd ed., by D. L. Fairclough, Boca Raton”

As the title states, this book reviews statistical problems that arise in the design and analysis of clinical studies where health-related quality of life (HRQoL) scales are commonly used. Although a broad range of topics common to HRQoL are discussed in this 16-chapter text, this book does not discuss in detail issues pertaining to the development and/or evaluation of HRQoL scales (a thorough review can be found in Streiner and Norman, 2008). Rather, the primary focus is on longitudinal data analysis and, in particular, the impact and handling of missing data. A specific objective of this book is to provide “enough detail to enable readers to apply the methods” to appropriately design and analyze longitudinal HRQoL studies. To meet that goal, each chapter is generally comprised of the underlying concepts integral to the methodology, the statistical formulas, and corresponding coding (primarily in SAS but often also in SPSS and R). Topics are illustrated through the use of six clinical trials, which are described in depth in chapter 1. The first two chapters are introductory and cover basic concepts central to HRQoL scales (e.g., generic versus disease-specific, recall period, response format, and scoring, to name a few) and their inclusion in clinical trials (e.g. design and protocol development, and, in particular, strategies to avoid missing data). Chapters 3 and 4 discuss modeling longitudinal data using repeated-measures models for event-driven designs (chapter 3) and mixed-effects growth curve models for timedriven designs (chapter 4). In-depth descriptions for building various mean and covariance structures are presented. A key focus to the model building is the inherent interpretation of the parameters or combinations of parameters. Univariate and longitudinal models exploring the presence of moderators (interaction effects) and mediators (variable through which the predictor effects the outcome variable) are illustrated in chapter 5. The next seven chapters (chapters 6 through 12) address the issue of longitudinal analyses in the presence of missing data. Chapters 6 and 7 provide a broad overview. Common terminology, such as missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR), is discussed in chapter 6. Graphical and statistical procedures to investigate MCAR versus MAR are illustrated in this chapter, along with the use of surrogate measures to identify the potential for nonrandom missingness. Chapter 7 reviews methods of analysis under each type of missing data mechanism. Watch-outs for methods requiring MCAR are illustrated, along with theoretical justification of
How Facial Symmetry Influences the Learning Effectiveness of Computer Graphic Design in Makeup Design

This study explored the learning effectiveness of drawing makeup designs by computer graphic design and compared the learning differences between traditional hand-drawn and computer-assisted teaching in cosmetology students at universities. The statistical analysis methods of factor analysis, descriptive statistical analysis, and paired sample t-test are used to analyze the difference in students’ learning attitudes before and after the course. It also explored students’ learning effectiveness. The subjects were 55 students from a cosmetology department of a university in Taiwan. The results showed that using a computer tool to create makeup designs improved the overall student learning effectiveness and effectively promoted students’ interest in learning. Moreover, through focus group interviews, changes in the learning effectiveness that were brought about by the use of computer graphic design tools were obtained. Among them, the mirror function could best meet the needs of students for makeup symmetry and design drawing speed and improve their satisfaction with computer graphic makeup. The results of this study are improving the learning effectiveness, maintaining a positive attitude and increasing willingness to learn, and the systematization and digitization of makeup design, and the results could promote teachers to obtain more efficient teaching quality, improve students’ professional skills, and result in better learning results.
3D Broadband Propagation in a Fluctuating Shallow Water Environment

Abstract : LONG-TERM GOAL. The long-term goal of this project is to provide a numerically efficient and robust acoustic model for the propagation of waves in a three-dimensional fluctuating shallow water environment. OBJECTIVES. The scientific objectives of this work, as a first step toward the long-term goal, are: 1: Develop a new, more efficient 2D propagation model based on the coupled mode method which is more efficient but as accurate as the parabolic equation (PE) model. 2: Use this model to study how signal coherence in the ocean is affected by sound speed fluctuations caused by internal waves. APPROACH Coupled mode equations are generally derived from the wave equation by dividing a range dependent waveguide into range independent sections where in each section the wave equation can be solved as a sum of local normal modes [1]. The coupling between modes are expressed as integrals with respect to depth of the local modes and their range derivatives. The use of the wave equation in deriving the coupled mode equations results in two coupling matrices: one which involves first and another which involves second derivatives of the local modes with respect to range. Computation of the coupling matrices, particularly the one which involves the second derivative of the modes with respect to range, is impractical and inaccurate at best. It is therefore common to resort to approximations, which, among other things, destroy the anti-symmetry of the coupling matrices [2], [3], [4]. An energy conserving solution requires the coupling matrices to be anti-symmetric. Instead of using the wave equation, our approach is to use the equations of motion to derive the coupled mode equations. By this method only one coupling matrix is obtained. What is more important is that this coupling matrix is simple to compute since it involves the depth derivatives rather than the range derivatives of the local modes. Furthermore, this method guarantees energy conservation since the coupling matrix ob
Generalized individual-based epidemic model for vulnerability assessment of correlated scale-free complex networks

Many complex networks exhibit vulnerability to spreading of epidemics, and such vulnerability relates to the viral strain as well as to the network characteristics. For instance, the structure of the network plays an important role in spreading of epidemics. Additionally, properties of previous epidemic models require prior knowledge of the complex network structure, which means the models are limited to only well-known network structures. In this paper, we propose a new epidemiological SIR model based on the continuous time Markov chain, which is generalized to any type of network. The new model is capable of evaluating the states of every individual in the network. Through mathematical analysis, we prove an epidemic threshold exists below which an epidemic does not propagate in the network. We also show that the new epidemic threshold is inversely proportional to the spectral radius of the network. In particular, we employ the new epidemic model as a novel measure to assess the vulnerability of networks to the spread of epidemics. The new measure considers all possible effective infection rates that an epidemic might possess. Next, we apply the measure to correlated networks to evaluate the vulnerability of disassortative and assortative scalefree networks. Ultimately, we verify the accuracy of the theoretical epidemic threshold through extensive numerical simulations. Within the set of tested networks, the numerical results show that disassortative scale-free networks are more vulnerable to spreading of epidemics than assortative scale-free networks.
Qualitative probabilities: a normative framework for commonsense reasoning

Intelligent agents are expected to generate plausible predictions and explanations in partially unknown and highly dynamic environments. Thus, they should be able to retract old conclusions in light of new evidence and to efficiently manage wide fluctuations of uncertainty. Neither mathematical logic nor numerical probability fully accommodates these requirements. In this dissertation I propose a formalism that facilitates reasoning with qualitative rules, facts, and deductively closed beliefs (as in logic), yet permits us to retract beliefs in response to changing contexts and imprecise observations (as in probability). Domain knowledge is encoded as if-then rules admitting exceptions with different degrees of abnormality, and queries specify contexts with different levels of precision. I develop effective procedures for testing the consistency of such knowledge bases and for computing whether (and to what degree) a given query is confirmed or denied. These procedures require a polynomial number of propositional satisfiability tests and hence are tractable for Horn expressions. Finally, I show how to give rules causal character by enforcing a Markovian condition of independence. The resulting formalism provides the necessary machinery for embodying belief updates and belief revision, generating explanations, and reasoning about actions and change.
La monodromie Hamiltonienne des cycles évanescents

We study the monodromy of vanishing cycles for map-germs $f:(C^{2n},0) \to (\CM^k,0)$ whose components are in involution. Although the singular fibres of such maps have non-isolated singularities, it is shown that the regular fibres are $2(n-k)$-connected and that the vanishing homology group of rank $2(n-k)+1$ is freely generated by the vanishing cycles. As corollaries, we get that the multiplicity of the discriminant is equal to the dimension of the vanishing homology group of rank $2(n-k)+1$ and that the Variation operator is an isomorphism. These results are proved under two assumptions: 1. the pyramidality assumptions which states that the singular locus is propagated along the Hamilton flow of the components of $f$ 2. the generic singular fibres should have transverse Morse singularities and their locus should be connected. It is conjectured that outside a set of infinite codimension the first condition holds and that there exists an involutive deformation of $f$ which satisfies condition 2.
Major outburst of periodic comet Halley at a heliocentric distance of 14 AU

The properties and evolution of the major outburst experienced by Comet Halley at 14 AU during February-March 1991 are studied. It is found that the observed halo is a segment of a conical surface populated by solid particles ejected from a localized, temporarily activated region on the sunlit hemisphere of the spinning nucleus. The total mass of the ejecta was at least 10 exp 12 g and CO was probably the prime driver, accelerating the smallest grains to a terminal velocity of about 45 m/s. The mass loading of the gas flow by particulate matter is enormous, with the mass production rate exceeding the expected production rate of CO by a factor of several tens.
Emerging Roles of Ceramides in Breast Cancer Biology and Therapy

One of the classic hallmarks of cancer is the imbalance between elevated cell proliferation and reduced cell death. Ceramide, a bioactive sphingolipid that can regulate this balance, has long been implicated in cancer. While the effects of ceramide on cell death and therapeutic efficacy are well established, emerging evidence indicates that ceramide turnover to downstream sphingolipids, such as sphingomyelin, hexosylceramides, sphingosine-1-phosphate, and ceramide-1-phosphate, is equally important in driving pro-tumorigenic phenotypes, such as proliferation, survival, migration, stemness, and therapy resistance. The complex and dynamic sphingolipid network has been extensively studied in several cancers, including breast cancer, to find key sphingolipidomic alterations that can be exploited to develop new therapeutic strategies to improve patient outcomes. Here, we review how the current literature shapes our understanding of how ceramide synthesis and turnover are altered in breast cancer and how these changes offer potential strategies to improve breast cancer therapy.
A comparative study of phytochemical, antioxidant, anticarcinogenic, and antidiabetic potential of coriander (Coriandrum sativum L.): Microgreen and mature plant

Microgreens are immature edible leafy greens with a higher concentration of phytonutrients than in mature leaves, which makes them a novel functional food. This research featured antioxidant, anticarcinogenic, and antidiabetic properties of coriander microgreens. Aqueous and ethanolic extractions of coriander microgreens and mature leaves underwent a phytochemical analysis of antioxidant potential using the DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) free radical method and the ferric reducing antioxidant power (FRAP) assay. The analysis of antidiabetic and anticarcinogenic properties included the method of α-amylase enzyme inhibition and the MTT colorimetric assay. The screening test inferred the presence of alkaloids, terpenoids, glycosides, steroids, tannins, flavonoids, phenols, carbohydrates, and proteins in both microgreens and mature leaves. The quantitative analysis showed that the ethanolic extract of the microgreen sample exhibited higher total phenols. Total flavonoids, steroids, carbohydrates, and proteins were higher both in microgreen extracts, if compared with those of mature leaves. Ascorbic acid, chlorophyll-a, chlorophyll-b, and carotenoids demonstrated a more substantial presence in mature leaves. The gas chromatography-mass spectrometry (GC/MS) analysis of coriander microgreens revealed such bioactive compounds as thienopyrimidines, phenolic amide, imidazo pyridazine, phenolic constituents, and essential oil. Mature leaves were rich in phenolic compounds, steroids, terpenoids, essential oils, and fatty acid esters. All these substances are known for their therapeutic antioxidant, antidiabetic, and anticarcinogenic properties. The microgreen samples exhibited greater ferric reducing antioxidant power, α-amylase enzyme inhibition, and cytotoxicity activity at a lower concentration of extract than mature leaves. Coriander microgreens proved to have a promising antioxidant, anticarcinogenic, and antidiabetic potential and can be used in daily food additives.
Antitrust Unchained: The EU’s Case Against Self-Preferencing

Self-preferencing is the symbol of the competition policy Zeitgeist in digital markets. Large online platforms acting as gatekeepers to their ecosystems and engaging in a dual mode intermediation are accused of taking advantage of their hybrid business model by granting preferential treatment to their own products and services. Alongside the recent legislative initiatives undertaken around the world to impose a neutrality regime over digital gatekeepers by targeting different forms of self-preferencing, this practice is also emerging in Europe as a new antitrust theory of harm advanced by courts and competition authorities. In the aftermath of the General Court’s decision in Google Shopping and against the risk that the new label may merely provide antitrust enforcers with the opportunity to skip the legal standards and evidentiary burdens required to prove traditional anticompetitive behavior, this paper investigates whether and to what extent self-preferencing could be considered a new standalone offence in EU competition law.
Staying Anxious or Being Optimistic? Understanding Apparel and Merchandising Students’ Psychological Well-Being During the Pandemic of COVID-19

Introduction and Purpose In March 2021, university campuses across the United States had to close due to an unprecedented challenge caused by the pandemic of COVID-19. College students have been under higher levels of stress due to unexpected changes in their schools and limited social interactions with peers. A survey indicated that 32% of college student participants knew a close family member or a friend who had been sick with COVID-19, and 60% of them had lost incomes (Whilans, Giurge, Macchia, & Yemiscigil, 2020). The purpose of the study was to understand how university students managed their personal and school lives while facing the pandemic. Specifically, the study had two specific research questions: (1) what were the common environmental stressors for university students during the pandemic and (2) how did the university students respond to the pandemic and manage their school, work, and social lives while maintaining personal well-being during the unexpected shift in their routines?
Activity-Based Person Identification Using Multimodal Wearable Sensor Data

Wearable devices equipped with a variety of sensors facilitate the measurement of physiological and behavioral characteristics. Activity-based person identification is considered an emerging and fast-evolving technology in security and access control fields. Wearables, such as smartphones, Apple Watch, and Google glass can continuously sense and collect activity-related information of users, and activity patterns can be extracted for differentiating different people. Although various human activities have been widely studied, few of them (gaits and keystrokes) have been used for person identification. In this article, we performed person identification using two public benchmark data sets (UCI-HAR and WISDM2019), which are collected from several different activities using multimodal sensors (accelerometer and gyroscope) embedded in wearable devices (smartphone and smartwatch). We implemented eight classifiers, including an multivariate squeeze-and-excitation network (MSENet), time-series transformer (TST), temporal convolutional network (TCN), CNN-LSTM, ConvLSTM, XGBoost, decision tree, and $k$ -nearest neighbor. The proposed MSENet can model the relationship between different sensor data. It achieved the best person identification accuracies under different activities of 91.31% and 97.79%, respectively, for the public data sets of UCI-HAR and WISDM2019. We also investigated the effects of sensor modality, human activity, feature fusion, and window size for sensor signal segmentation. Compared to the related work, our approach has achieved the state of the art.
Dental Biofilm Removal and Bacterial Contamination of a New Doubled-Side Thermoplastic Polyurethane-Based Toothbrush: A Crossover Study in Healthy Volunteers

Multiple toothbrush designs have been developed to enhance dental biofilm removal and decrease bacterial contamination and retention over time. Therefore, the aim of this clinical study was to compare the efficacy of a prototype of a new double-sided thermoplastic polyurethane-based toothbrush with that of a conventional nylon-bristle toothbrush. A crossover study was conducted in systemically healthy volunteers (n = 24) for two one-week periods plus one washout week. As outcome variables, plaque and gingival indices, total bacterial contamination of the toothbrushes by quantitative polymerase chain reaction (qPCR), and patient-reported outcomes were measured. Clinical and microbiological variables were analysed using a general linear model and Friedman and Wilcoxon signed-rank tests. No statistically significant differences between toothbrushes were detected neither for full-mouth PlI (p > 0.05) nor for GI (p > 0.05). Similarly, no statistically significant differences were detected for bacterial contamination after 40 seconds or 1 week of use, with results expressed either in CFU/mL or in CFU/mm2 (p > 0.05). In conclusion, the tested prototype toothbrush was as effective and safe as the control toothbrush, and the participating subjects did not experience any adverse effects from its use and rated its efficiency and effectiveness in cleaning their teeth as satisfactory.
Misfit strain dependence of electrocaloric effect in epitaxial Pb(Zr1-xTix)O3 thin films

A phenomenological Landau–Devonshire thermodynamic theory is employed to investigate the effect of the misfit strain on the electrocaloric effect of single domain epitaxial Pb(Zr1−xTix)O3 thin films grown on thick cubic substrates. Theoretical analysis indicates that the epitaxial Pb(Zr1−xTix)O3 thin films have the large electrocaloric coefficient at room temperature and the electrocaloric properties largely depend on the misfit strain and the applied electric field. Furthermore, the applied field decreases the electrocaloric coefficient and reduces its misfit strain dependence.
An Update on Effectiveness and Practicability of Plant Essential Oils in the Food Industry

Consumer awareness and demands for quality eco-friendly food products have made scientists determined to concentrate their attention on sustainable advancements in the utilization of bioactive compounds for increasing safety and food quality. Essential oils (EOs) are extracted from plants and exhibit antimicrobial (antibacterial and antifungal) activity; thus, they are used in food products to prolong the shelf-life of foods by limiting the growth or survival of microorganisms. In vitro studies have shown that EOs are effective against foodborne bacteria, such as Escherichia coli, Listeria monocytogenes, Salmonella spp. , and Staphylococcus aureus. The growing interest in essential oils and their constituents as alternatives to synthetic preservatives has been extensively exploited in recent years, along with techniques to facilitate the implementation of their application in the food industry. This paper’s aim is to evaluate the current knowledge on the applicability of EOs in food preservation, and how this method generally affects technological properties and consumers’ perceptions. Moreover, essential aspects concerning the limitation of the available alternatives are highlighted, followed by a presentation of the most promising trends to streamline the EOs’ usability. Incorporating EOs in packaging materials is the next step for green and sustainable foodstuff production and a biodegradable method for food preservation.