Miracle-dz/UniFAR-FTUs huggingface dataset:
Lie Groups in Atomic and Molecular Spectroscopy

Lie groups enter in three principal ways in atomic spectroscopy: (a) as the rotation group $R_3 $ in three dimensions and through its consequent usefulness in determining selection rules; (b) as the noninvariance groups of Racah, which serve to classify the states of complex electronic configurations of the type $f^N $ and enable their properties to be more easily determined ; and (c) as the dynamical groups and their subgroups for simple systems such as the hydrogen atom, where their role is essentially interpretive. For molecules, all three roles suffer extensive limitations and loss of effectiveness, though new areas of application open up. The relevance of the symmetry properties of the rigid rotator is an obvious example. More striking is Wulfman’s analysis of the expansion of single-electron molecular eigenfunctions in terms of four-dimensional spherical harmonics, and his selection of basis functions spanning a single irreducible representation of $R_5 $. The different character of the problems occ.
Heart Rate as a Correlate for the Emotional Processing of Body Stimuli in Anorexia Nervosa

In anorexia nervosa, aberrant emotional reactions toward body stimuli have been discussed. We investigated heart rate as a physiological marker when viewing body stimuli and hypothesized altered HR reactions toward those highly significant and emotional stimuli in anorexia nervosa. In total, 37 anorexia nervosa patients and 43 control participants viewed pictures of women of five different weight categories, while their cardiac activity was recorded. R-R intervals following picture onset were determined, and means were calculated for three distinct time periods. The overall change in HR relative to baseline across all picture categories was greater in the patient group than in the control group (significant effect of “group”, p = 0.002, partial η2 = 0.120). A significant decrease in HR 2 to 8 s after picture presentation was found for pictures of women of extreme weight in both participant groups (significant “category ∗ time segment interaction”, p = 0.01, partial η2 = 0.037) and correlated with scores of sociocultural attitudes toward the appearance for the extremely underweight category (r = −0.33, p = 0.005). Therefore, differential HR reactions for anorexia nervosa patients and control participants were found for body stimuli in general. The highest HR decelerations in response to pictures of strongly underweight and overweight women may reflect emotional processes such as anxiety due to social comparison.
Competition and Cooperation: Global Task Assignment in Spatial Crowdsourcing

Online spatial crowdsourcing platforms provide popular O2O services in people's daily. Users submit real-time tasks through the Internet and require the platform to immediately assign workers to serve them. However, the imbalance distribution of tasks and workers leads to the rejection of some tasks, which reduces the profit of the platform. In this paper, we propose that similar platforms can form an alliance to make full use of the global service supply through cooperation. We name the problem as Global Task Assignment (GTA), in which platforms are allowed to hire idle workers from other platforms to improve the profit of all the platforms together. Different from relevant works, the decision-makers in GTA are platforms rather than individual workers, which can better assign workers in all platforms and improve the overall profit. We design an auction-based incentive mechanism (AIM), to motivate platforms to rent idle workers to other platforms so that increase their own profit. Based on the mechanism, we propose a greedy-based assignment algorithm (BaseGTA), in which platforms greedily maximizes their current profit. We further propose a prediction-based assignment algorithm (ImpGTA), in which platforms make decisions based on the spatial-temporal distribution in the future time. Experimental results show that platforms using our algorithms can achieve higher profit than the existing studies.
ECG Analysis to Study Social Connections in Older Cardiac Patients

Loneliness in older adults is associated with functional decline, depression and even death. Given the prevalence of loneliness, the aim of this study was to examine the association between loneliness and cardiac biomarkers in older people that attend to cardiology consultation. The results showed that loneliness was more prevalent in women than in men, and it was associated with marital status too. ECG recording were analyzed and QT interval and T-wave length showed higher values in people suffering from loneliness, as well as higher cardiac frequency, where the presence of meaning in life be a protective factor. Studies with a larger sample size are needed, but these results appear to show a relationship between biomarkers and mental state.
Effect of Inoculum Size and Age, and Sucrose Concentration on Cell Growth to Promote Metabolites Production in Cultured Taraxacum officinale (Weber) Cells

Pentacyclic triterpenes, including lupeol, α- amyrin, and β-amyrin, present a large range of biological activities including anti-inflammatory, anti-cancer, and gastroprotective properties. The phytochemistry of dandelion (Taraxacum officinale) tissues has been widely described. Plant biotechnology offers an alternative for secondary metabolite production and several active plant ingredients are already synthesized through in vitro cultures. This study aimed to establish a suitable protocol for cell growth and to determine the accumulation of α-amyrin and lupeol in cell suspension cultures of T. officinale under different culture conditions. To this end, inoculum density (0.2% to 8% (w/v)), inoculum age (2- to 10-week-old), and carbon source concentration (1%, 2.3%, 3.2%, and 5.5% (w/v)) were investigated. Hypocotyl explants of T. officinale were used for callus induction. Age, size, and sucrose concentrations were statistically significant in cell growth (fresh and dry weight), cell quality (aggregation, differentiation, viability), and triterpenes yield. The best conditions for establishing a suspension culture were achieved by using a 6-week-old callus at 4% (w/v) and 1% (w/v) of sucrose concentration. Results indicate that 0.04 (±0.02) α-amyrin and 0.03 (±0.01) mg/g lupeol can be obtained in suspension culture under these starting conditions at the 8th week of culture. The results of the present study provide a backdrop for future studies in which an elicitor could be incorporated to increase the large-scale production of α-amyrin and lupeol from T. officinale.
Moonlight Is Perceived as a Signal Promoting Genome Reorganization, Changes in Protein and Metabolite Profiles and Plant Growth

Rhythmic exposure to moonlight has been shown to affect animal behavior, but its effects on plants, often observed in lunar agriculture, have been doubted and often regarded as myth. Consequently, lunar farming practices are not well scientifically supported, and the influence of this conspicuous environmental factor, the moon, on plant cell biology has hardly been investigated. We studied the effect of full moonlight (FML) on plant cell biology and examined changes in genome organization, protein and primary metabolite profiles in tobacco and mustard plants and the effect of FML on the post-germination growth of mustard seedlings. Exposure to FML was accompanied by a significant increase in nuclear size, changes in DNA methylation and cleavage of the histone H3 C-terminal region. Primary metabolites associated with stress were significantly increased along with the expression of stress-associated proteins and the photoreceptors phytochrome B and phototropin 2; new moon experiments disproved the light pollution effect. Exposure of mustard seedlings to FML enhanced growth. Thus, our data show that despite the low-intensity light emitted by the moon, it is an important environmental factor perceived by plants as a signal, leading to alteration in cellular activities and enhancement of plant growth.
A method for resolving organisation‐enterprise system misfits: An action research study in a pluralistic organisation

Although off‐the‐shelf enterprise systems (ES) have been widely adopted in organisations, the extant literature repeatedly documents ES failures caused by misfits between organisational processes and the ES. Although some misfits can be identified early in the ES lifecycle, others emerge in the onward and upward phase (i.e., after the implementation) and, hence, must be resolved reactively. Prior research on misfits and resolution strategies has primarily focused on the implementation phase, often assuming that close‐to‐perfect information on the misfit's nature and characteristics is available. However, no study has examined how to effectively complete a shared diagnosis and resolution of misfits when diverging individual user perceptions are taken as the starting point. Such situations may be particularly pronounced in pluralistic organisations, where a variety of interdependent processes and potentially competing perceptions of processes are prevalent. The main objective of this study is to address this gap. To this end, we propose a pragmatic method for the diagnosis and resolution of misfits between organisational processes and enterprise systems, which builds on an actionable conceptualization of misfits. This method builds on theoretical concepts of affordances, affordance actualization, user participation, and change agentry. To demonstrate the feasibility and effectiveness of the proposed method, we conducted an action research study in a university hospital. Our analysis focused on a specific misfit involving the hospital's ES‐supported clinical processes. The findings suggest that the method effectively diagnoses and resolves misfits and optimises the resources required for their resolution through efficient management of user participation. We conclude with a discussion of the theoretical and practical contributions of our work.
Comparison of Be and C diffusion in heavily doped polycrystalline GaAs

The diffusion of Be and C in heavily doped polycrystalline GaAs grown by molecular beam epitaxy and metalorganic chemical vapor deposition has been studied by secondary‐ion mass spectrometry and Hall measurement. It is found that Be rapidly diffuses into the undoped buffer layer at a growth temperature of 450 °C. Concentration‐depth profiles of Be in AlGaAs/GaAs heterojunction bipolar transistor layers indicate that Be diffuses mainly along polycrystal grain boundaries. On the other hand, C diffusion is negligible even for post‐growth annealing at 800 °C. However, annealing increases the resistivity of C‐doped GaAs, which is probably due to a change in the occupation site preference of C atoms from As sites.
Fuzzy Decision Rule-Based Online Classification Algorithm in Fuzzy Formal Decision Contexts

Formal concept analysis (FCA) extracts interpretable rules by using implication relationships between concepts, which is an effective method for acquiring knowledge. In this article, a fuzzy decision rule-based online classification algorithm called OFRCA is designed by combining online learning theory and FCA in a fuzzy formal decision context. First, the original weight vector of all attributes is obtained by fusing the original deterministic decision rules. Second, incremental fuzzy decision rules are obtained according to the added objects. Then, for the incremental fuzzy decision rules, OFRCA updates the weight vector based on minimizing the loss function. At the end of the process, all the rules are fused into an attribute-weighted classifier with the final weight vector. In this article, we employ the regret to obtain a learning guarantee for OFRCA. The growth rate of OFRCA's regret converges to 0 as the number of iterations increases in the ideal state, which provides an effective learning guarantee for OFRCA. To verify the effectiveness of the proposed algorithm, this article conducted numerical experiments and systematically analyzed the experimental results, which demonstrated that OFRCA achieved the highest advanced classification performance among the compared algorithms.
Height/width aspect ratio controllable two-dimensional sub-micron arrays fabricated with two-photon photopolymerization

Summary We reported in this paper the use of annular beam illumination to control the transverse and vertical sizes of two-dimensional dot array structures fabricated with two-photon photopolymerization. Dot arrays with an element diameter of less than 300 nm, a lattice spacing less than 1 μm has been produced. At the same time, the structure height exhibits a 1.94 times increase averagely and the height/width aspect ratio is improved from 1.21, for the circular beam illumination case, to 2.76 after using annular beam illumination.
How social media expression can reveal personality

Background Personality psychology studies personality and its variation among individuals and is an essential branch of psychology. In recent years, machine learning research related to personality assessment has started to focus on the online environment and showed outstanding performance in personality assessment. However, the aspects of the personality of these prediction models measure remain unclear because few studies focus on the interpretability of personality prediction models. The objective of this study is to develop and validate a machine learning model with domain knowledge introduced to enhance accuracy and improve interpretability. Methods Study participants were recruited via an online experiment platform. After excluding unqualified participants and downloading the Weibo posts of eligible participants, we used six psycholinguistic and mental health-related lexicons to extract textual features. Then the predictive personality model was developed using the multi-objective extra trees method based on 3,411 pairs of social media expression and personality trait scores. Subsequently, the prediction model’s validity and reliability were evaluated, and each lexicon’s feature importance was calculated. Finally, the interpretability of the machine learning model was discussed. Results The features from Culture Value Dictionary were found to be the most important predictors. The fivefold cross-validation results regarding the prediction model for personality traits ranged between 0.44 and 0.48 (p < 0.001). The correlation coefficients of five personality traits between the two “split-half” datasets data ranged from 0.84 to 0.88 (p < 0.001). Moreover, the model performed well in terms of contractual validity. Conclusion By introducing domain knowledge to the development of a machine learning model, this study not only ensures the reliability and validity of the prediction model but also improves the interpretability of the machine learning method. The study helps explain aspects of personality measured by such prediction models and finds a link between personality and mental health. Our research also has positive implications regarding the combination of machine learning approaches and domain knowledge in the field of psychiatry and its applications to mental health.
Supervised disparity estimation

We introduce supervised disparity estimation in which an operator can steer the disparity estimation process. Instead of correcting errors, we view the estimation process as a constrained process where the constraints are indicated by the user in the form of control points, scribbles and contours. Control points are used to obtain accurate disparity estimates that can be fully controlled by the operator. Scribbles are used to force regions to have a smooth disparity, while contours create a disparity discontinuity in places where diffusion or energy minimization fail. Control points, scribbles and contours are propagated through the video sequence to create temporally stable results.
Order α2 theory of the atomic electric dipole moment due to an electric dipole moment on the electron

The theory of the electric dipole moment (EDM) of an atom caused by an EDM on the electron is discussed in detail. The absence of an atomic EDM is the non-relativistic limit is examined both formally and numerically. The two strategies which are used in practice to calculate the leading relativistic terms of order alpha 2 are extended by the inclusion of all terms of this order. One-transverse-photon exchange involving the EDM and effects due to the Breit interaction are included; the terms so generated are new, occur only in many-electron atoms, and can be identified semiclassically with the nu *B and delta A/ delta t contributions to the electric field seen by the atomic electrons. The need for projection operators to avoid negative energy states is examined. Numerical calculations are made for caesium and thallium; these show that the contribution from the central potential is dominant.
BIOMIMETIC MATERIALS IN PEDIATRIC DENTISTRY: FROM PAST TO FUTURE

With the arrival of technology, during the last two decades, various changes have been made in the field of restorative dentistry. Hence, this article reviews the numerous biomimetic materials and its biological properties in the field of restorative and preventive dentistry and endodontics. Biomimetic materials, with their biocompatible nature and physio-chemical properties are widely used nowadays.1 They can function as long-lasting aesthetic and restorative materials, cements, root repair materials, root canal sealers and filling materials, which have the advantages of enhanced biocompatibility, high strength, sealing ability and antibacterial properties. Newer biomimetic materials have the ability to overcome limitations of earlier generation materials.1
Molecular imaging of HER2 receptor: Targeting HER2 for imaging and therapy in nuclear medicine

Targeting HER 2 for imaging and therapy in nuclear medicine has been used with a special emphasis on developing more powerful radiopharmaceuticals. Zirconium-89 plays an essential role in immune PET imaging so was used labeled with anti-HER2 antibody (Trastuzumab and Pertuzumab). Also there were attempts with other PET tracers as Cuprum-64 and Galium-68, as well as SPECT radiopharmaceuticals Indium-111 and Technetium- 99m. Regarding antibody pharmacokinetic that is not quite appropriate for imaging acquisition, several smaller molecules with shorter residence times have been developed. These molecules called nanobody, affibody, minibody do not compromize HER2 receptor affinity and specificity. Excess of Trastuzumab do not block the affinity of labeled affibodies. Silica nanoparticles have been conjugated to anti-HER2 antibodies to enable targeting of HER2 expressing cells with potential of drug delivery carry for antitumor agents and b(beta) or a(alfa) emitting radioisotopes commonly used for radionuclide therapy, as Iodine-131, Lutetium-177, Yttrium-90, Rhenium-188 and Thorium-277.
Skeletal myotube-derived extracellular vesicles enhance itaconate production and attenuate inflammatory responses of macrophages

Introduction Macrophages play an important role in the innate immunity. While macrophage inflammation is necessary for biological defense, it must be appropriately controlled. Extracellular vesicles (EVs) are small vesicles released from all types of cells and play a central role in intercellular communication. Skeletal muscle has been suggested to release anti-inflammatory factors, but the effect of myotube-derived EVs on macrophages is unknown. As an anti-inflammatory mechanism of macrophages, the immune responsive gene 1 (IRG1)-itaconate pathway is essential. In this study, we show that skeletal muscle-derived EVs suppress macrophage inflammatory responses, upregulating the IRG1-itaconate pathway. Methods C2C12 myoblasts were differentiated into myotubes and EVs were extracted by ultracentrifugation. Skeletal myotube-derived EVs were administered to mouse bone marrow-derived macrophages, then lipopolysaccharide (LPS) stimulation was performed and inflammatory cytokine expression was measured by RT-qPCR. Metabolite abundance in macrophages after addition of EVs was measured by CE/MS, and IRG1 expression was measured by RT-PCR. Furthermore, RNA-seq analysis was performed on macrophages after EV treatment. Results EVs attenuated the expression of LPS-induced pro-inflammatory factors in macrophages. Itaconate abundance and IRG1 expression were significantly increased in the EV-treated group. RNA-seq analysis revealed activation of the PI3K-Akt and JAK-STAT pathways in macrophages after EV treatment. The most abundant miRNA in myotube EVs was miR-206-3p, followed by miR-378a-3p, miR-30d-5p, and miR-21a-5p. Discussion Skeletal myotube EVs are supposed to increase the production of itaconate via upregulation of IRG1 expression and exhibited an anti-inflammatory effect in macrophages. This anti-inflammatory effect was suggested to involve the PI3K-Akt and JAK-STAT pathways. The miRNA profiles within EVs implied that miR-206-3p, miR-378a-3p, miR-30d-5p, and miR-21a-5p may be responsible for the anti-inflammatory effects of the EVs. In summary, in this study we showed that myotube-derived EVs prevent macrophage inflammatory responses by activating the IRG1-itaconate pathway. Graphical Abstract
Diamagnetic equilibrium of spherical torus obtained in a two-fluid model with flow

Two-fluid flowing equilibrium configurations of a helicity-driven spherical torus (HD-ST) in the realistic region including the spherical flux conserver and the coaxial helicity source are numerically determined by using the combination of the finite difference and the boundary element methods. It is found from the numerical results that the ultra low-$q$ HD-ST with diamagnetic toroidal field and high-$\beta$ (volume average $\beta$ value, $\langle\beta\rangle\cong 18\%$) can be obtained by reversing the toroidal field over the whole region and by increasing the toroidal ion flow up to the Alfv${\rm \acute e}$n Mach number $M_{\rm A}\cong 0.7$. The ion diamagnetic drift velocity is larger than the ${\bf E}\times {\bf B}$ drift velocity and has the same direction.
Bootstrap confidence intervals and hypothesis tests for extrema of parameters

The bootstrap provides effective and accurate methodology for a wide variety of statistical problems which might not otherwise enjoy practicable solutions. However, there still exist important problems where standard bootstrap estimators are not consistent, and where alternative approaches, for example the m-out-of-n bootstrap and asymptotic methods, also face significant challenges. One of these is the problem of constructing confidence intervals or hypothesis tests for extrema of parameters, for example for the maximum of p parameters where each has to be estimated from data. In the present paper we suggest approaches to solving this problem. We use the bootstrap to construct an accurate estimator of the joint distribution of centred parameter estimators, and we base the procedure, either a confidence interval or a hypothesis test, on that distribution estimator. Our methodology is designed so that it errs on the side of conservatism, modulo the small inaccuracy of the bootstrap step. Copyright 2010, Oxford University Press.