Miracle-dz/UniFAR-FTUs huggingface dataset:
Front propagation for nematic liquid crystals

We study the gradient flow model of the Landau-de Gennes energy functional for nematic liquid crystals at the isotropic-nematic transition temperature on prototype geometries. We focus on the three-dimensional droplet, the disc and the square with Dirichlet boundary conditions and different types of initial conditions, with the aim of observing interesting transient dynamics which may be of practical relevance. We use a fourth-order Landau-de Gennes bulk potential which admits isotropic and uniaxial minima at the transition temperature. For a droplet with radial boundary conditions, a large class of physically relevant initial conditions generate dynamic solutions with a well-defined isotropic-nematic front which propagates according to mean curvature for significant times. We introduce radially symmetric obstacles into the droplet and prove the existence of pulsating wave solutions of the gradient flow model in certain parameter regimes. The average velocity of the pulsating wave is determined by some critical forcing which can be verified numerically. On the unit disc, we make a distinction between planar and non-planar initial conditions and minimal and non-minimal Dirichlet boundary conditions. Planar initial conditions generate solutions with an isotropic core for all times whereas non-planar initial conditions generate solutions that escape into the third dimension. Non-minimal boundary conditions result in solutions with boundary layers. These solutions can have either a largely nematic interior profile or a largely isotropic interior profile, depending on the initial conditions. On the square, we provide an analytic description of the Well Order Reconstruction solution first reported numerically by Kralj and Majumdar in 2014. We interpret the Well Order Reconstruction solution as a critical point of a related scalar variational problem and prove that the solution is globally stable on small domains. We use the gradient flow model of the Landau-de Gennes energy to numerically study the emergence of new solution branches from the Well Order Reconstruction solution. We conclude this thesis by studying a triple phase Landau-de Gennes model with a sixth-order bulk potential which admits isotropic, uniaxial and biaxial minima at a special temperature known as the triple point temperature. For some model problems, we can use asymptotic methods to prove that isotropic-uniaxial, uniaxial-biaxial and isotropic-biaxial fronts propagate according to mean curvature and to prove an angle condition that holds when the fronts intersect at a triple junction. We corroborate our formal calculations with a numerical investigation of the full Landau-de Gennes gradient flow system.
Assessment of Psychometric properties of Behavioral activation and Behavioral inhibition systems scale associated with impulsivity and anxiety

Background: Despite the efforts undertaken to measure the Reinforcement Sensitivity Theory, The main difficulties of this theory is not good psychometric scale. This study was performed to evaluate the psychometric properties of behavioral activation and behavioral inhibition systems’ scale in nonclinical groups. Methods: The study population includes Urmia and Kharazmi universities, among which 368 and 472 participants were selected randomly. For determining the psychometric properties of behavioral activation and behavioral inhibition systems’ scale, exploratory and confirmatory factor analyses were used. Then reliability of this scale were measured through the Cronbach's alpha coefficient, retest, and splitting, as well as criterion validity was examined with positive and negative affect scale sensitivity to punishment and reward scale. Results: Exploratory factor analysis revealed four factors. Also fit indictors in confirmatory factor analysis supported four-factor model. Alpha coefficients, retest and splitting showed satisfactory internal consistency, and patterns of correlation coefficients between subscales of Persian version of behavioral activation and behavioral inhibition systems with positive and negative affect scale and sensitivity to punishment and reward scale showed good criterion validity for this scale. Conclusion: The findings of the present study was similar to original culture, therefore the Persian version of behavioral activation and behavioral inhibition systems’ scale is a good tool for assessment characteristics consistent with BAS and BIS system and their subscales.
Stepwise modulation of apical orientational cell adhesions for vertebrate neurulation

Neurulation transforms the neuroectoderm into the neural tube. This transformation relies on reorganising the configurational relationships between the orientations of intrinsic polarities of neighbouring cells. These orientational intercellular relationships are established, maintained, and modulated by orientational cell adhesions (OCAs). Here, using zebrafish (Danio rerio) neurulation as a major model, we propose a new perspective on how OCAs contribute to the parallel, antiparallel, and opposing intercellular relationships that underlie the neural plate–keel–rod–tube transformation, a stepwise process of cell aggregation followed by cord hollowing. We also discuss how OCAs in neurulation may be regulated by various adhesion molecules, including cadherins, Eph/Ephrins, Claudins, Occludins, Crumbs, Na+/K+‐ATPase, and integrins. By comparing neurulation among species, we reveal that antiparallel OCAs represent a conserved mechanism for the fusion of the neural tube. Throughout, we highlight some outstanding questions regarding OCAs in neurulation. Answers to these questions will help us understand better the mechanisms of tubulogenesis of many tissues.
Parametric and nonparametric propensity score estimation in multilevel observational studies

There has been growing interest in using nonparametric machine learning approaches for propensity score estimation in order to foster robustness against misspecification of the propensity score model. However, the vast majority of studies focused on single‐level data settings, and research on nonparametric propensity score estimation in clustered data settings is scarce. In this article, we extend existing research by describing a general algorithm for incorporating random effects into a machine learning model, which we implemented for generalized boosted modeling (GBM). In a simulation study, we investigated the performance of logistic regression, GBM, and Bayesian additive regression trees for inverse probability of treatment weighting (IPW) when the data are clustered, the treatment exposure mechanism is nonlinear, and unmeasured cluster‐level confounding is present. For each approach, we compared fixed and random effects propensity score models to single‐level models and evaluated their use in both marginal and clustered IPW. We additionally investigated the performance of the standard Super Learner and the balance Super Learner. The results showed that when there was no unmeasured confounding, logistic regression resulted in moderate bias in both marginal and clustered IPW, whereas the nonparametric approaches were unbiased. In presence of cluster‐level confounding, fixed and random effects models greatly reduced bias compared to single‐level models in marginal IPW, with fixed effects GBM and fixed effects logistic regression performing best. Finally, clustered IPW was overall preferable to marginal IPW and the balance Super Learner outperformed the standard Super Learner, though neither worked as well as their best candidate model.
Hydrodynamic schooling of multiple self-propelled flapping plates

While hydrodynamic interactions for aggregates of swimmers have received significant attention in the low Reynolds number realm ( $Re\ll 1$ ), there has been far less work at higher Reynolds numbers, in which fluid and body inertia are involved. Here we study the collective behaviour of multiple self-propelled plates in tandem configurations, which are driven by harmonic flapping motions of identical frequency and amplitude. Both fast modes with compact configurations and slow modes with sparse configurations were observed. The Lighthill conjecture that orderly configurations may emerge passively from hydrodynamic interactions was verified on a larger scale with up to eight plates. The whole group may consist of subgroups and individuals with regular separations. Hydrodynamic forces experienced by the plates near their multiple equilibrium locations are all springlike restoring forces, which stabilize the orderly formation and maintain group cohesion. For the cruising speed of the whole group, the leading subgroup or individual plays the role of ‘leading goose’.
Theoretical and computational tools to model multistable gene regulatory networks

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and ‘classical’ systems typically studied in non-equilibrium statistical and quantum mechanics.
Singular value decomposition based model order reduction techniques

This thesis investigates the development of new singular value decomposition based model order reduction techniques. Firstly a solution to the controller reduction problem via a parameterized doublesided frequency weighted controller reduction technique is developed for the feedback control of MIMO discrete time systems particularly for non-unity feedback control system configurations which have the controller located in the feedback path. Secondly, new frequency interval cross gramians are developed for both linear and bilinear systems. New generalized Sylvester equations for calculating the frequency interval cross gramians are derived in order to be used to obtain information regarding controllability and observability of a system within a single matrix and therefore leading to increased computational efficiency. Thirdly, a new model reduction method for discrete-time bilinear systems is developed based on newly derived frequency interval controllability and observability gramians for discrete-time bilinear systems. Fourthly, time weighted cross gramians are developed and applied to a state space model derived from two partial differential equations representing the thermal dynamics of a flat plate solar collector. Fifthly, generalized frequency interval controllability and observability gramians are introduced in order to obtain the frequency interval controllability and observability gramians for continuous-time linear systems which do not have a solution to the standard Lyapunov equation. Finally, a new frequency weighted partial fraction expansion based model reduction technique is developed based on the partial fraction expansion approach. In order to further reduce the frequency weighted approximation error, singular perturbation approximation is incorporated into the algorithm.
On sharp bounds for spectral radius of nonnegative matrices

Abstract We give sharp upper and lower bounds for the spectral radius of a nonnegative matrix with positive row sums using average 3-row sums, compare these bounds with the existing bounds using the average 2-row sums by examples, and apply them to the adjacency matrix and the signless Laplacian matrix of a digraph or a graph.
The Cambridge Handbook of Expertise and Expert Performance: Eliciting and Representing the Knowledge of Experts

The transgenerational transmission of thewisdom of elders via storytelling is as oldas humanity itself. During the Middle Agesand Renaissance, the Craft Guilds had well-speciﬁed procedures for the transmission ofknowledge, and indeed gave us the develop-mental scale that is still widely used: initi-ate, novice, apprentice, journeyman, expert,and master (Hoffman, 1998). Based oninterviews and observations of the work-place, Denis Diderot (along with 140 oth-ers, including Emile Voltaire) created one ofthegreatworksoftheEnlightenment,the17volume
Enabling Viewpoint Learning through Dynamic Label Generation

Optimal viewpoint prediction is an essential task in many computer graphicsapplications. Unfortunately, common viewpoint qualities suffer from majordrawbacks: dependency on clean surface meshes, which are not alwaysavailable, insensitivity to upright orientation, and the lack of closed-formexpressions, which requires a costly sampling process involving rendering.We overcome these limitations through a 3D deep learning approach, whichsolely exploits vertex coordinate information to predict optimal viewpointsunder upright orientation, while reflecting both informational content andhuman preference analysis. To enable this approach we propose a dynamiclabel generation strategy, which resolves inherent label ambiguities dur-ing training. In contrast to previous viewpoint prediction methods, whichevaluate many rendered views, we directly learn on the 3D mesh, and arethus independent from rendering. Furthermore, by exploiting unstructuredlearning, we are independent of mesh discretization. We show how the pro-posed technology enables learned prediction from model to viewpoints fordifferent object categories and viewpoint qualities. Additionally, we showthat prediction times are reduced from several minutes to a fraction of asecond, as compared to viewpoint quality evaluation. We will release thecode and training data, which will to our knowledge be the biggest viewpointquality dataset available.
Cosmic evolution in DHOST theories with scaling solutions

We study cosmic evolution based on the fixed points in the dynamical analysis of the Degenerate Higher-Order Scalar-Tensor (DHOST) theories. We consider the DHOST theories in which the propagation speed of gravitational waves is equal to the speed of light, the tensor perturbations do not decay to dark energy perturbations, and the scaling solutions exist. The scaling fixed point associated with late time acceleration of universe can be either stable or saddle depending on the parameters of the theory. For some ranges of the parameters, the accelerated scaling point and the field dominated point can be simultaneously stable. Cosmic evolution will reach the accelerated scaling point if the time derivative of the scalar field in the theory is positive during the matter domination. If the time derivative of the scalar field is negative during the matter domination, the background universe will evolve towards the field dominated point. The density parameter of the matter can be larger than unity before reaching the scaling fixed point if the deviation from the Einstein theory of gravity is too large and the initial conditions for the dynamical variables during the matter domination are significantly different from the accelerated scaling point. The stabilities of φMDE fixed point are similar to the coupled dark energy models. In our consideration, the universe can only evolve from the φMDE to the field dominated point.
The First Familiar Case of PTEN-Related Disorder Reported in Albania

559 PTEN hamartoma tumor syndromes (PHTS) are a group of genetic disorders inherited in an autosomal dominant manner and linked to the germ line of the tumor suppressor gene PTEN located on 10q23 (OMIM 601728). 1-4 The PHTS, characterized by a broad, extremely variable, and often overlapping spectrum of clinical features, comprises different disorders such as Cowden syndrome (CS, OMIM 158350), Banna yan-R ileyRuval caba syndrome (BRRS, OMIM 153480), PTEN-related Proteus syndrome (OMIM 176920), and PTEN-related Proteuslike syndrome.1-4 The PTEN germline mutations have also been described in ∼10%-20% of those with macrocephaly and autism spectrum disorder (ASD), as well as in a few cases of megalencephaly and hemimegalencephaly, and VATER syndrome (vertebral abnormalities, anal atresia, tracheoesophageal fistula with esophageal atresia, and radial or renal dysplasia). 1-3,5
DhHP-6 alleviates inflammation and reduces vascular permeability by eliminating reactive oxygen species

Abstract Inflammation is a defensive immune response to external stimuli. However, uncontrolled inflammation may cause potential damage to the host. Therefore, timely control of uncontrolled inflammation is particularly important. Previous studies have found that small molecules with antioxidant activity, such as peroxidase mimic enzymes, can inhibit the development of inflammation. DhHP-6 is a new peptide mimic of peroxidase previously designed by our laboratory. Here, we explored its anti-inflammatory activity in vitro and in vivo. Our results showed that treatment with DhHP-6 significantly reduced the production of reactive oxygen species (ROS), NO, IL-6, and TNF-α in RAW264.7 cells induced by lipopolysaccharides (LPS); in addition, it also blocked the phosphorylation of extracellularly regulated kinase 1 and 2 (ERK1/2) and ribosomal s6 kinase 1 (RSK1), thereby blocking the phosphorylation and degradation of IκBα, and inhibiting the nuclear translocation of p65. Interestingly, treatment with DhHP-6 blocked the phosphorylation of ERK1/2 and myosin light chain kinase (MLCK) in HUVECs induced by LPS. Finally, we found that DhHP-6 treatment significantly reduced the infiltration of immune cells in balloon model rats. Therefore, we believe that DhHP-6 is a potent inhibitor of inflammation.
Sorry, not sorry: Unpopular individuals report but don’t display empathy and prosocial behaviors

ABSTRACT The resource control theory postulates that the combination of prosocial strategies and coercive strategies are useful in gaining and maintaining resources that allow one to be perceived popular within society. Often prosocial behaviors appear in conjunction with empathy. The social-reconnection hypothesis suggest that prosocial behaviors might be executed when an individual fears they are or might be socially excluded. However, some research shows that mixed feelings arise and increased attendance to acceptance might take place but not actual helping behaviors. The current study examined eighty-six individuals and the impact of perceived popularity on empathy and prosocial behaviors. Specifically, self-reported popular and unpopular individuals were examined based on resource control strategy usage, empathy quotient (EQ) scores, helping behavior, and galvanic skin response to an emotion inducing video about rejection and bullying. Unpopular individuals self-reported higher levels of empathy but did not display greater galvanic skin responses or more helping behavior than popular self-reported individuals.
Incorporating Goal Analysis in Database Design: A Case Study from Biological Data Management

We present a case study of a real-world industrial application which produced several versions of conceptual schema design for a biological database during its evolution. We apply the techniques of early requirements analysis to produce a goal model of the problem domain. We then show that by incorporating goal analysis in the design process we can account for the original schemas by tracing them back to stakeholder goals. Moreover, the goal-oriented analysis supports the systematic examination of the space of design alternatives, and better explains what the output of the design process (a conceptual schema) really means. Our results advocate the need for an extended design methodology for databases driven by stakeholder goals
Algorithms that "Don't See Color": Comparing Biases in Lookalike and Special Ad Audiences

Today, algorithmic models are shaping important decisions in domains such as credit, employment, or criminal justice. At the same time, these algorithms have been shown to have discriminatory effects. Some organizations have tried to mitigate these effects by removing demographic features from an algorithm's inputs. If an algorithm is not provided with a feature, one might think, then its outputs should not discriminate with respect to that feature. This may not be true, however, when there are other correlated features. In this paper, we explore the limits of this approach using a unique opportunity created by a lawsuit settlement concerning discrimination on Facebook's advertising platform. Facebook agreed to modify its Lookalike Audiences tool - which creates target sets of users for ads by identifying users who share "common qualities" with users in a source audience provided by an advertiser - by removing certain demographic features as inputs to its algorithm. The modified tool, Special Ad Audiences, is intended to reduce the potential for discrimination in target audiences. We create a series of Lookalike and Special Ad audiences based on biased source audiences - i.e., source audiences that have known skew along the lines of gender, age, race, and political leanings. We show that the resulting Lookalike and Special Ad audiences both reflect these biases, despite the fact that Special Ad Audiences algorithm is not provided with the features along which our source audiences are skewed. More broadly, we provide experimental proof that removing demographic features from a real-world algorithmic system's inputs can fail to prevent biased outputs. Organizations using algorithms to mediate access to life opportunities should consider other approaches to mitigating discriminatory effects.
Structure of the connexin-43 gap junction channel in a putative closed state

Gap junction channels (GJCs) mediate intercellular communication by connecting two neighbouring cells and enabling direct exchange of ions and small molecules. Cell coupling via connexin-43 (Cx43) GJCs is important in a wide range of cellular processes in health and disease (Churko and Laird, 2013; Liang et al., 2020; Poelzing and Rosenbaum, 2004), yet the structural basis of Cx43 function and regulation has not been determined until now. Here, we describe the structure of a human Cx43 GJC solved by cryo-EM and single particle analysis at 2.26 Å resolution. The pore region of Cx43 GJC features several lipid-like densities per Cx43 monomer, located close to a putative lateral access site at the monomer boundary. We found a previously undescribed conformation on the cytosolic side of the pore, formed by the N-terminal domain and the transmembrane helix 2 of Cx43 and stabilized by a small molecule. Structures of the Cx43 GJC and hemichannels (HCs) in nanodiscs reveal a similar gate arrangement. The features of the Cx43 GJC and HC cryo-EM maps and the channel properties revealed by molecular dynamics simulations suggest that the captured states of Cx43 are consistent with a closed state.