Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Testable Theories with Discrete Flavour Symmetries

The leptonic mixing matrix may be understood as a consequence of remnant symmetries of the mass matrices, which emerge from the spontaneous breakdown of a larger symmetry into smaller non-commuting subgroups. The mixing patterns that may be obtained from groups of order smaller than 1556 are presented. To dynamically realize this symmetry breaking pattern an additional mechanism is needed. Here a minimal solution to this problem is provided, based on non-trivial extensions of the flavour group. A scan over possible extensions of popular flavour groups is presented and the smallest semidirect product extension of the group A4 is discussed. A model based on this symmetry group is constructed and it is shown to naturally give the required vacuum structure. Modifications that can account for the deviation from the predicted value for the mixing angle θ13 are presented. The vacuum alignment mechanism is applied in a model at the electroweak scale, which contains a dark matter candidate, and its phenomenology is studied. Consistency conditions for CP transformations in the context of discrete flavour groups are developed and they are shown to have non-trivial implications for existing models. Finally, we give an outlook about how the Standard Model may be viewed from a Planck scale perspective.
Zero Moment Two Edge Pushing of Novel Objects With Center of Mass Estimation

Pushing is one of the fundamental nonprehensile manipulation skills to impart to an object changes in position and orientation. To exploit this skill to manipulate novel objects, explicit knowledge of their physical properties should be given a priori. In this work, we estimate the center of mass (CoM) of an object by narrowing down its probable location with a deep learning model and Mason’s voting theorem. In addition, we propose the Zero Moment Two Edge Pushing (ZMTEP) method to translate a novel object without rotation to a goal pose. The proposed method enables a pusher to select the most suitable two-edge-contact configuration for a given object using the estimated CoM and the geometrical shape of the object. Notably, neither the friction between the object and its support plane nor the friction between the object and the pusher are assumed to be known. We evaluate the proposed CoM estimation and ZMTEP methods through a series of experiments in both simulation and real robotic pusher settings. The result shows that the CoM estimation method has good mean squared error properties and small standard deviation, and the ZMTEP method significantly outperforms competitive baseline methods. Note to Practitioners—This article aims to endow robotic arms with the capability of moving or aligning objects by pushing, which is much more simple and secure than pick-and-place or in-hand manipulations. Most in-demand manipulation skills require sophisticated hand design and control, which might not be affordable for industrial applications staying cost-competitive. In contrast, robot pushing can be implemented with different types of simple pushers and straightforwardly applied to pre-grasp manipulation. This article makes the estimation of an object’s CoM location practical. Building upon the estimation method, a robust and noise-tolerant two-edge-contact pushing configuration selection method is presented to translate an arbitrarily shaped unknown object to its goal pose.
Expression of p11 in Patients with Depression

(1) Background: Some studies suggest that the p11 protein, belonging to the so-called S100 family and located, i.a. , in the nucleus accumbens of the brain, is responsible for the occurrence of depression. This protein is encoded by the S100A10 gene. The aim of our study was to evaluate the expression of the S100A10 gene at the mRNA and protein levels in patients with depressive disorders and to determine the impact of p11 in the etiopathogenesis of depression; (2) Methods: A total of 290 people (190 depressed patients, 100 healthy controls) participated in the study. Socio-demographic and clinical data were collected. The severity of depressive symptoms was assessed using the Hamilton Depression Rating Scale (HDRS). Venous blood was collected from all participants. RT-PCR was used to evaluate gene expression at the mRNA level, while enzyme-linked immunosorbent assay (ELISA) was used to evaluate gene expression at the protein level; (3) Results: The results indicate slightly increased S100A10 gene expression (both at the protein and mRNA levels) in patients with depression, but these values do not reach statistical significance; (4) Conclusions: Due to the fact that the study was limited by the participation of patients already undergoing antidepressant treatment, its results may confirm that pharmacological treatment affecting serotonin neurotransmission is effective in upregulation of p11 in patients with depression.
An Extended Version of the Proportional Adaptive Algorithm Based on Kernel Methods for Channel Identification with Binary Measurements

In recent years, kernel methods have provided an important alternative solution, as they offer a simple way of expanding linear algorithms to cover the non-linear mode as well. In this paper, we propose a novel recursive kernel approach allowing to identify the finite impulse response (FIR) in non-linear systems, with binary value output observations. This approach employs a kernel function to perform implicit data mapping. The transformation is performed by changing the basis of the data In a high-dimensional feature space in which the relations between the different variables become linearized. To assess the performance of the proposed approach, we have compared it with two other algorithms, such as proportionate normalized least-meansquare (PNLMS) and improved PNLMS (IPNLMS). For this purpose, we used three measurable frequency-selective fading radio channels, known as the broadband radio access Network (BRAN C, BRAN D, and BRAN E), which are standardized by the European Telecommunications Standards Institute (ETSI), and one theoretical frequency selective channel, known as the Macchi’s channel. Simulation results show that the proposed algorithm offers better results, even in high noise environments, and generates a lower mean square error (MSE) compared with PNLMS and IPNLMS.
Study of equilibrium macrostates for two models in statistical mechanics

STUDY OF EQUILIBRIUM MACROSTATES FOR TWO MODELS IN STATISTICAL MECHANICS MAY 2004 PETER T. OTTO B.A., HAMILTON COLLEGE M.S., UNIVERSITY OF HARTFORD M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Richard S. Ellis In this dissertation we study the asymptotic behavior of two separate models in statistical mechanics. The first is a turbulence model that describes the long-time behavior of a class of dispersive wave equations of nonlinear Schrödinger-type. Numerical studies have shown that, in a bounded domain, solutions of these equations tend in the long-time limit toward a Gibbsian statistical equilibrium macrostate consisting of a ground state solitary wave on the large scales and Gaussian fluctuations on the small scales. A large deviation principle is proved for a mixed Gibbs ensemble that expresses this concentration phenomenon precisely in the relevant continuum limit.
Investigation and Optimization of the Impact of Printing Orientation on Mechanical Properties of Resin Sample in the Low-Force Stereolithography Additive Manufacturing

The mechanical properties of resin samples in low-force stereolithography additive manufacturing were affected by the printing orientation, and were investigated and optimized to achieve excellent single or comprehensive tensile strength, compressive strength, and flexural modulus. The resin samples were fabricated using a Form3 3D printer based on light curing technology according to the corresponding national standards, and they were detected using a universal testing machine to test their mechanical properties. The influence of the printing orientation was represented by the rotation angle of the resin samples relative to the x–axis, y–axis and z–axis, and the parameters was selected in the range 0°–90° with an interval of 30°. The multiple regression models for the mechanical properties of the prepared resin samples were obtained based on least square estimation, which offered a foundation from which to optimize the parameters of the printing orientation by cuckoo search algorithm. The optimal parameters for the tensile strength, compressive strength and flexural modulus were ‘α = 45°, β = 25°, γ = 90°’, ‘β = 0°, β = 51°, γ = 85°’ and ‘α = 26°, β = 0°, γ = 90°’, respectively, which obtained the improvements of 80.52%, 15.94%, and 48.85%, respectively, relative to the worst conditions. The mechanism was qualitatively discussed based on the force analysis. The achievements obtained in this study proved that optimization of the printing orientation could improve the mechanical properties of the fabricated sample, which provided a reference for all additive manufacturing methods.
On the growth of the first Betti number of arithmetic hyperbolic 3-manifolds

We calculate the Lefschetz number of a Galois automorphism in the cohomology of certain arithmetic congruence groups arising from orders in quaternion algebras over number fields. As an application we give a lower bound for the first Betti number of a class of arithmetically defined hyperbolic 3-manifolds and we deduce the following theorem: Given an arithmetically defined cocompact subgroup of SL(2,C), provided the underlying quaternion algebra meets some conditions, there is a decreasing sequence of finite index subgroups of such that the first Betti number grows at least as fast as the square root of the index.
One-dimensional Bose gases with N -body attractive interactions

We study the ground-state properties of a one-dimensional Bose gas with $N$-body attractive contact interactions. By using the explicit form of the bright soliton solution of a generalized nonlinear Schr\"odinger equation, we compute the chemical potential and the ground-state energy. For $N=3$, a localized soliton wave function exists only for a critical value of the interaction strength: in this case the ground state has an infinite degeneracy that can be parametrized by the chemical potential. The stabilization of the bright soliton solution by an external harmonic trap is also discussed, and a comparison with the effect of $N$-body attractive contact interactions in higher dimensions is presented.
How Should I Teach from This Month Onward? A State-Space Model That Helps Drive Whole Classes to Achieve End-of-Year National Standardized Test Learning Targets

Every month, teachers face the dilemma of what exercises their students should practice, and what their consequences are regarding long-term learning. Since teachers prefer to pose their own exercises, this generates a large number of questions, each one attempted by a small number of students. Thus, we could not use models based on big data, such as deep learning. Instead, we developed a simple-to-understand state-space model that predicts end-of-year national test scores. We used 2386 online fourth-grade mathematics questions designed by teachers, each attempted by some of the 500 students in 24 low socioeconomic schools. We found that the state-space model predictions improved month by month and that in most months, it outperformed linear regression models. Moreover, the state-space estimator provides for each month a direct mechanism to simulate different practice strategies and compute their impact on the end-of-year standardized national test. We built iso-impact curves based on two critical variables: the number of questions solved correctly in the first attempt and the total number of exercises attempted. This allows the teacher to visualize the trade-off between asking students to perform exercises more carefully or perform more exercises. To the best of our knowledge, this model is the first of its kind in education. It is a novel tool that supports teachers drive whole classes to achieve long-term learning targets.
Orbital diamagnetism in multilayer graphenes : Systematic study with the effective mass approximation

We present a theoretical study on the orbital magnetism in multilayer graphenes within the effective mass approximation. The Hamiltonian and thus susceptibility can be decomposed into contributions from sub-systems equivalent to monolayer or bilayer graphene. The monolayer-type subband exists only in odd layers and exhibits a delta-function susceptibility at $E_F=0$. The bilayer-type subband appearing in every layer number gives a singular structure in the vicinity of $E_F=0$ due to the trigonal warping as well as a logarithmic tail away from $E_F=0$. The integral of the susceptibility over energy is approximately given only by the layer number.
Critical Literature Review: Age Factors on Second Language Acquisition

Our understanding about second language acquisition is constantly updating itself due to new and compelling research. This article supports the idea that second language teachers should remain cognizant on the recent developments in research and critically reviews the literature regarding second language learning. This article also explores new theories regarding age factors in second language learning, with particular reference to the bilingual Chinese/English language context. This reviews found that teachers should understand the influence of critical age periods on language learners’ second language acquisition. The contextual focus is expanded to variations in the language learning environment, such as parental influence, bilingual schools and use of technology. This article concludes that understanding contextual factors such as age ranges and learning environments is paramount to delivering high-quality of second-language courses, and recommends methods for building an enjoyable and interactive second language learning environment with not much pressure, especially to young learners as well as adult learners. While this paper does review literature regarding adult learners of second languages, to understand more about the pedagogical differences and similarities of adults and children, as it progress, it will increasingly focus on the optimum teaching methods and environmental factors for supporting young learners. In doing so, it will consistently emphasize, based on the research, the importance of educators understanding children's social and emotional development alongside, and as part of, learning a second language. In its summary, some recommendations will be made for teachers of second language learners based on its findings.
Longitudinal Predictive Control for Vehicle-Following Collision Avoidance in Autonomous Driving Considering Distance and Acceleration Compensation

In response to the widespread adoption of vehicle-following systems in autonomous applications, the demand for collision warning to enable safer functionalities is increasing. This study provides an approach for automated vehicle guidance to follow the preceding vehicles longitudinally and puts emphasis on the performance of collision avoidance. The safety distance model is established, which contains a distance compensation algorithm to deal with the special case on curved roads. By introducing the algorithm of velocity and distance prediction, the collision risks are detected and measured in real time. The objective function is established based on optimal control theory to solve the desired following acceleration. The control system designed with the method of proportion integration differentiation combines throttle percentage and brake pressure as outputs to compensate acceleration. In the Carsim and Simulink co-simulation platform, the control system for longitudinal collision avoidance is simulated and analysed for four typical working conditions: the preceding vehicle drives at a constant speed on straight and curved roads, while the preceding vehicle drives at various speeds on straight and curved roads. The results validate the feasibility and effectiveness of the proposed method, which can be used for the longitudinal control of vehicle-following active collision avoidance.
Uma abordagem bayesiana para análise de dados intervalares

Em avaliações da qualidade de ensino ministrado por questionários, várias abordagens foram tentadas visando a objetividade e qualidade dos dados a serem fornecidos pelos alunos. Neste trabalho adota-se a proposta de Moraes (1999) que utiliza uma escala definida sobre um segmento de reta, com comprimento fixo para todas as questões e com indicações sobre o significado das extremidades direita e esquerda, onde os valores próximos a extremidade esquerda, revelam atitudes bastante positivas do professor, e os valores próximos a extremidade direita indicam atitudes negativas. Como as distâncias são usualmente medidas da esquerda para a direita, quanto mais próximo do ideal (à esquerda), menor será a distância obtida. O uso destas escalas permitiu observar um índice de respostas válidas muito próximo a 100% (Moraes, 1999), fato que pode ser atribuído a maior liberdade que o aluno teve para expressar suas respostas, por não apresentar “níveis” explícitos de reposta, mas apenas dois extremos que expressam sua positividade e negatividade. As escalas nãonuméricas eliminam também a dúvida sobre a quantificação dos níveis entre um intervalo e outro observado, por exemplo, nas escalas do tipo li kert (Pasquali , 1998). Neste trabalho utiliza-se um segmento de reta onde todos os valores à esquerda revelam “muita preocupação” e valores à direita indicam “pouca preocupação” do professor com o aluno.
ESTIMATES OF TECHNOLOGY AND CONVERGENCE: SIMULATION RESULTS

Using a Solow-Swan model with a stochastic saving rate and stochastic productivity we analyse the distributions of parameter estimates that emerge under various choices of technology, and of the dimension of the panel on which cross-section regressions are based. There are distinct asymmetries that characterize these distributions. These asymmetries become more pronounced when the effects of a near-unit root in the productivity shock become magnified over a longer time horizon and when the underlying production function is not Cobb-Douglas. Consequently, relying on traditional econometric transformations of these parameter estimates based on symmetric distributions, such as t-ratios, will be quite misleading if one tries to assess technology parameters and B-convergence.
Reactive strip method for mixing and reaction in two dimensions

A numerical method to efficiently solve for mixing and reaction of scalars in a two-dimensional flow field at large P\'eclet numbers but otherwise arbitrary Damk\"ohler numbers is reported. We consider a strip of one reactant in a pool of another reactant, both of which are advected with the known velocity field. We first establish that the system evolution for such a system under certain conditions is described by a locally one-dimensional reaction-diffusion problem. The approximation of a locally one-dimensional dynamics is true for cases where the strip thickness is smaller than the local radius of curvature and also when the strip thickness is smaller than the distance between adjacent strips. We first demonstrate the method for the transport of a conservative scalar under a linear shear flow, point vortex and a chaotic sine flow. We then proceed to consider the situation with a simple bimolecular reaction between two reactants to yield a single product. The methodology presented herewith essentially generalizes nontrivially the Diffusive Strip Method developed by Meunier and Villermaux (J. Fluid Mech. 662, 134-172 (2010)) to address passive scalar transport, to the generalized situation with multiple reacting species. In essence, the reduction of dimensionality of the problem, which renders the 2D problem 1D, allows one to efficiently model reactive transport under high P\'eclet numbers which are otherwise prohibitively difficult to resolve from classical finite difference or finite element based methods.
Clinical and Electrophysiological Changes in Pediatric Spinal Muscular Atrophy after 2 Years of Nusinersen Treatment

In the new therapeutic era, disease-modifying treatment (nusinersen) has changed the natural evolution of spinal muscular atrophy (SMA), creating new phenotypes. The main purpose of the retrospective observational study was to explore changes in clinical evolution and electrophysiological data after 2 years of nusinersen treatment. We assessed distal compound motor action potential (CMAP) on the ulnar nerve and motor abilities in 34 SMA patients, aged between 1 and 16 years old, under nusinersen treatment, using specific motor scales for types 1, 2 and 3. The evaluations were performed at treatment initiation and 26 months later. There were registered increased values for CMAP amplitudes after 2 years of nusinersen, significantly correlated with motor function evolution in SMA type 1 patients (p < 0.005, r = 0.667). In total, 45% of non-sitters became sitters and 25% of sitters became walkers. For SMA types 1 and 2, the age at the treatment initialization is highly significant (p < 0.0001) and correlated with treatment yield. A strong negative correlation (r = −0.633) was observed for SMA type 1 and a very strong negative correlation (r = −0.813) for SMA type 2. In treated SMA cases, the distal amplitude of the CMAP and motor functional scales are important prognostic factors, and early diagnosis and treatment are essential for a better outcome.
IMPACT OF ATMOSPHERIC CHROMATIC EFFECTS ON WEAK LENSING MEASUREMENTS

Current and future imaging surveys will measure cosmic shear with statistical precision that demands a deeper understanding of potential systematic biases in galaxy shape measurements than has been achieved to date. We use analytic and computational techniques to study the impact on shape measurements of two atmospheric chromatic effects for ground-based surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope (LSST): (1) atmospheric differential chromatic refraction and (2) wavelength dependence of seeing. We investigate the effects of using the point-spread function (PSF) measured with stars to determine the shapes of galaxies that have different spectral energy distributions than the stars. We find that both chromatic effects lead to significant biases in galaxy shape measurements for current and future surveys, if not corrected. Using simulated galaxy images, we find a form of chromatic “model bias” that arises when fitting a galaxy image with a model that has been convolved with a stellar, instead of galactic, PSF. We show that both forms of atmospheric chromatic biases can be predicted (and corrected) with minimal model bias by applying an ordered set of perturbative PSF-level corrections based on machine-learning techniques applied to six-band photometry. Catalog-level corrections do not address the model bias. We conclude that achieving the ultimate precision for weak lensing from current and future ground-based imaging surveys requires a detailed understanding of the wavelength dependence of the PSF from the atmosphere, and from other sources such as optics and sensors. The source code for this analysis is available at https://github.com/DarkEnergyScienceCollaboration/chroma.