Miracle-dz/UniFAR-FTUs huggingface dataset:
A Computer-Aided Assessment and Evaluation System for Modern Apprenticeship of Accounting Class On-the-Job Training

With China’s economy and the accelerated pace of globalization, the accounting environment is constantly changing, some accounting laws and regulations are constantly being revised or promulgated, and the accounting system and system are gradually being improved. At the same time, breach of trust in economic activities and violation of financial laws and regulations are common, making the accounting environment more complex. All these have put forward higher requirements for accounting practitioners, which require accounting personnel to receive systematic and professional accounting professional training. Therefore, it is very important for the construction of the assessment and evaluation system for accounting internship. Based on this paper, we study the construction of the computer-aided implementation of the assessment and evaluation system of accounting internship for modern apprenticeship in order to improve the practical and effective help for the employment of accounting students.
Γ‐convergence of stratified media with measure‐valued limits

We consider energy functionals, or Dirichlet forms, [GRAPHICS] for a class G of bounded domains Omega subset of R-N, with epsilon>0 a fine structure parameter and with symmetric conductivity matrices A(epsilon) = (a(ij)(epsilon)) is an element of L-loc(infinity)(R)(NxN) which are functions only of the first coordinate x(1) and which are locally uniformly elliptic for each fixed epsilon>0. We show that if the functions (of x(1)) b(11)(epsilon) = 1/a(11)(epsilon), b(1j)(epsilon) = a(1j)(epsilon)/a(11)(epsilon) (j greater than or equal to 2), b(ij)(epsilon) = a(ij)(epsilon) - a(i1)(epsilon)a(1j)(epsilon)/ a(11)(epsilon) (i, j greater than or equal to 2) converge weakly* as measures towards corresponding limit measures b(ij) as epsilon --> 0, if the (1,1)-coefficient m(11)(epsilon) of (A(epsilon))(-1) is bounded in L-loc(1)(R) and if none of its weak* cluster measures has atoms in common with b(ii), i greater than or equal to 2, then the family J(epsilon) = {J(Omega)(epsilon)}(Omega is an element of g) Gamma-converges in a local sense towards a naturally defined limit family J = {J(Omega))(Omega is an element of G) as epsilon-->0. An alternative way of formulating the conclusion is to say that the energy densities (A(epsilon)del u,del u) Gamma-converge in a distributional sense towards the corresponding limit density. Writing J(Omega)(epsilon) in terms of B-epsilon = (b(ij)(epsilon)) it becomes [GRAPHICS] and the definition of J(Omega) and the limit density (A del u, del u) is obtained by properly replacing the b(ij)(epsilon) is an element of L-loc(infinity)(R) by the limit measures b(ij) and making sense to everything for u in a certain linear subspace of L-loc(2)(R-N).
Mutations and short geodesics in hyperbolic 3-manifolds

In this paper, we explicitly construct large classes of incommensurable hyperbolic knot complements with the same volume and the same initial (complex) length spectrum. Furthermore, we show that these knot complements are the only knot complements in their respective commensurabiltiy classes by analyzing their cusp shapes. The knot complements in each class differ by a topological cut-and-paste operation known as mutation. Ruberman has shown that mutations of hyperelliptic surfaces inside hyperbolic 3-manifolds preserve volume. Here, we provide geometric and topological conditions under which such mutations also preserve the initial (complex) length spectrum. This work requires us to analyze when least area surfaces could intersect short geodesics in a hyperbolic 3-manifold.
Long transient response of vegetation dynamics after four millennia of anthropogenic impacts in an island ecosystem

Agents of global change commonly have a higher impact on island ecosystem dynamics. In the Mediterranean region, those dynamics have historically been influenced by anthropogenic impacts, for example, the introduction of invasive species and overharvesting of resources. Here, we analysed the spatio‐temporal dynamics of vegetation in sa Dragonera island, which experienced a large environmental change ca. 4000 years ago by the arrival of humans. Anthropogenic impacts, such as herbivory by goats and over‐logging, ended in the 1970s, while in 2011 the site became the largest Mediterranean island where rats were eradicated. Invasive rats and goats played the ecological role of two endemic species, the cave goat and the giant dormouse, which inhabited the island for more than 5 million years and were rapidly extinct by humans. We used Landsat imagery to explore NDVI as a proxy of vegetation productivity over the years 1984–2021, orthophotos to assess changes in land and vegetation covers and historical plant inventories to study the dynamics in plant diversity. Results showed that those indicators steadily increased both in spring and in summer, while the noise around the trends was partially explained by climate variability. The regime shifts in the temporal dynamics of vegetation productivity suggested a transient from a perturbed to a non‐perturbed stable state. Trends in successional dynamics, spatial self‐organization and plant diversity also showed the same type of transient dynamics. Historical perturbations related to harvesting (mainly the synergies between goat browsing, burning and forest over‐logging) were more important than rat eradication or the influence of climate to explain the vegetation dynamics. Our study shows the transient nature of this small island ecosystem after 4000 years of perturbations and its current path towards vegetation dynamics more controlled by ecological interactions lacking large herbivores and omnivores, drought dynamics and the carrying capacity of the island.
Nonlinear growing neutrino cosmology

The energy scale of Dark Energy, $\sim 2 \times 10^{-3}$ eV, is a long way off compared to all known fundamental scales - except for the neutrino masses. If Dark Energy is dynamical and couples to neutrinos, this is no longer a coincidence. The time at which Dark Energy starts to behave as an effective cosmological constant can be linked to the time at which the cosmic neutrinos become nonrelativistic. This naturally places the onset of the Universe's accelerated expansion in recent cosmic history, addressing the why-now problem of Dark Energy. We show that these mechanisms indeed work in the Growing Neutrino Quintessence model - even if the fully nonlinear structure formation and backreaction are taken into account, which were previously suspected of spoiling the cosmological evolution. The attractive force between neutrinos arising from their coupling to Dark Energy grows as large as $10^6$ times the gravitational strength. This induces very rapid dynamics of neutrino fluctuations which are nonlinear at redshift $z \approx 2$. Nevertheless, a nonlinear stabilization phenomenon ensures only mildly nonlinear oscillating neutrino overdensities with a large-scale gravitational potential substantially smaller than that of cold dark matter perturbations. Depending on model parameters, the signals of large-scale neutrino lumps may render the cosmic neutrino background observable.
Effects of Gravidity on Atherogenic Indices in Normotensive and Hypertensive Second Trimester Pregnant Women

Background: Pregnancy results in certain physiological and metabolic changes that results to shift in certain biochemical markers and could even result in hypertension in some women thus predisposing them to risk of cardiovascular disease. While this is true, some women express these predisposing risk factors in subsequent pregnancies. Therefore, it may be a significant contribution to understand the dynamics of artherogenic indices with increasing number of pregnancies. Aim: The goal of the study was aimed to assess gravidity effect on artherogenic indices in both normotensive and hypertensive second-trimester pregnant women. Materials and Methods: At Rivers State University Teaching Hospital, a cross-sectional study was carried out with 100 pregnant women. The consenting patients who met the inclusion criteria were classified into two groups: normotensive (50 normotensive pregnant women in their second trimester) and hypertensive (50 hypertensive pregnant women in their second trimester) (HPW2T). The participants were subsequently split into three subgroups depending on gravidity: primigravida (no of pregnancy=1), multigravida (no of pregnancies>1), and grand multigravida (no of pregnancies≥5). For the assessment of TC, TG, HDL, and LDL, fasting blood samples were taken using the venepuncture technique. Mathematically, artheriogenic indices (AIP, CR-I, CR-II, AC, and APoB/APoA1) were calculated. At a P-value>0.05, the data was examined using ANOVA and the Tukey comparison test. Results: There was no significant difference in artheriogenic indices between the gravidity groups in the normotensive group, with a P-value>0.05, which was also the cases among those in the hypertensive group. Conclusion: The study has shown that gravidity does not have any effect on artheriogenic indices among normotensive and hypertensive pregnant women in the second trimester in Rivers State University Teaching Hospital.
Novel efficient precoding techniques for multiuser MIMO systems

In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI). However, the design of a suitable precoding algorithm with good overall performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions. In this thesis, we explore the art of novel low-complexity high-performance precoding algorithms with both linear and non-linear processing strategies. Block diagonalization (BD)-type based precoding techniques are well-known linear precoding strategies for MU-MIMO systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel SU-MIMO channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this thesis, two categories of low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. One is based on multiple LQ decompositions and lattice reductions. The other one is based on a channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Both of the two proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity. Tomlinson-Harashima precoding (THP) is a prominent nonlinear processing technique employed at the transmit side and is a dual to the successive interference cancelation (SIC) detection at the receive side. Like SIC detection, the performance of THP strongly depends on the ordering of the precoded symbols. The optimal ordering algorithm, however, is impractical for MU-MIMO systems with multiple receive antennas. We propose a multi-branch THP (MB-THP) scheme and algorithms that employ multiple transmit processing and ordering strategies along with a selection scheme to mitigate interference in MU-MIMO systems. Two types of multi-branch THP (MB-THP) structures are proposed. The first one employs a decentralized strategy with diagonal weighted filters at the receivers of the users and the second uses a diagonal weighted filter at the transmitter. The MB-MMSE-THP algorithms are also derived based on an extended system model with the aid of an LQ decomposition, which is much simpler compared to the conventional MMSE-THP algorithms. Simulation results show that a better BER performance can be achieved by the proposed MB-MMSE-THP precoder with a small computational complexity increase.
A Blueprint for a Topologically Fault-tolerant Quantum Computer

The advancement of information processing into the realm of quantum mechanics promises a transcendence in computational power that will enable problems to be solved which are completely beyond the known abilities of any "classical" computer, including any potential non-quantum technologies the future may bring. However, the fragility of quantum states poses a challenging obstacle for realization of a fault-tolerant quantum computer. The topological approach to quantum computation proposes to surmount this obstacle by using special physical systems -- non-Abelian topologically ordered phases of matter -- that would provide intrinsic fault-tolerance at the hardware level. The so-called "Ising-type" non-Abelian topological order is likely to be physically realized in a number of systems, but it can only provide a universal gate set (a requisite for quantum computation) if one has the ability to perform certain dynamical topology-changing operations on the system. Until now, practical methods of implementing these operations were unknown. Here we show how the necessary operations can be physically implemented for Ising-type systems realized in the recently proposed superconductor-semiconductor and superconductor-topological insulator heterostructures. Furthermore, we specify routines employing these methods to generate a computationally universal gate set. We are consequently able to provide a schematic blueprint for a fully topologically-protected Ising based quantum computer using currently available materials and techniques. This may serve as a starting point for attempts to construct a fault-tolerant quantum computer, which will have applications to cryptanalysis, drug design, efficient simulation of quantum many-body systems, solution of large systems of linear equations, searching large databases, engineering future quantum computers, and -- most importantly -- those applications which no one in our classical era has the prescience to foresee.
Feature-Based Texture Synthesis and Hierarchical Tensor Approximation

Texture synthesis has always been an interesting research topic in Graphics. Neighborhood-based algorithms have two common stages: search for most similar neighborhoods in the sample texture; merge a local neighborhood into the (partially) synthesized output texture. When the first stage can not find good neighbors, the second stage may generate seams. We propose to extract a feature map from the input texture and synthesize a feature map for output. We develop novel algorithms to perform feature matching and alignment. This approach significantly reduces feature discontinuities and related artifacts. For 3D surfaces, things get more complicated as continuity constraints restrict the variability of synthesized textures. We propose to relax the restrictions and decompose synthesis into two stages: feature map synthesis and Laplacian texture reconstruction. Experiments indicate that this relaxation can produce desirable results for regular texture synthesis as well as texture mixing from multiple sources. Visual data approximation is another important issue in Graphics. We propose hierarchical tensor approximation to expose multi-scale and inhomogeneous structures in visual datasets. The blocks on each level in the hierarchy are pruned and approximated as a tensor ensemble, and residual tensors are subdivided to form the next level in the hierarchy. Experiments prove that the hierarchical multilinear models can achieve higher compression ratios and quality on high-dimensional visual data than wavelet (packet) transforms and single-level tensor approximation. Finally, we propose to apply multilinear models to wavelet domain to reduce overhead. High-frequency wavelet sub-bands are subdivided into small blocks most of which get pruned. The blocks are usually correlated especially when properly classified. Different channels and sub-bands may exhibit strong redundancy as well. We reorganize the subdivided blocks into small tensors, classify the unpruned ones and approximate each cluster as a tensor ensemble. Experiments on images and medical volume data indicate that this approach achieves better approximation quality than wavelet (packet) transforms and hybrid linear models.
Women and Labour Force Participation in Malaysia

One of the best ways for Malaysia to develop and advance in the future is by increasing economic prospects for women. In this light, even though women’s educational attainment has significantly improved, their participation in the labour force is still significantly lower than men’s. It is believed that this is due to the burden of doing housework and caring for children and the elderly, which women mostly shoulder. This study used the Fifth Malaysian Population and Family Survey (MPFS-5), a nationally representative survey to investigate factors influencing labour force participation among Malaysian women. The probit regression model of participation decision among women, which considers common socio-demographic parameters such as parents and parents-in-law’s presence, marital status, education, age, and the number of children, was applied in this study. The results suggest that the government must devise strategies to help women achieve work-life balance, particularly in improving access to childcare services.
Toward Systems Models for Obesity Prevention: A Big Role for Big Data

ABSTRACT The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project “BigO: Big data against childhood obesity” used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions.
FORMAÇÃO/PRÁTICA DE PROFESSORES QUE ENSINAM ESTATÍSTICA, PROBABILIDADE E COMBINATÓRIA: UM ESTUDO BASEADO EM PERIÓDICOS CIENTÍFICOS BRASILEIROS

Este trabalho tem como objetivo inventariar, sistematizar e descrever a produção científica do conhecimento sobre a temática formação/prática de professores que ensinam Estatística, Probabilidade e Combinatória, publicada em periódicos científicos brasileiros. Metodologicamente, o admitimos como sendo uma pesquisa do tipo estado do conhecimento e de caráter essencialmente analítico-descritivo, tendo como material de análise 34 artigos relacionando e articulando Educação Estatística e Formação de Professores como objeto de estudo. As pesquisas foram categorizadas em quatro eixos temáticos: Compreensão/Concepção e Saberes Docentes; Formação Inicial/Continuada e Desenvolvimento Profissional; Formação/Prática mediada por grupos colaborativos; Prática/Trabalho Docente. Em cada uma dessas categorias, são apontadas e descritas as características e, a posteriori, são expostos, para o conjunto de artigos analisados, os sujeitos pesquisados, os conteúdos enfocados, os principais aportes teóricos e abordagens metodológicas adotadas. Os principais resultados apontam para o fato de que muitos dos artigos analisados parecem convergir para a ideia de que os professores pesquisados apresentam, em geral, dificuldades em compreender conceitos estatísticos, probabilísticos e combinatórios, o que, por sua vez, levanta questionamentos a respeito da forma como esses assuntos são tratados nos cursos de formação inicial. Também foi observada uma ênfase em pesquisas categorizadas na temática Formação Inicial/Continuada e Desenvolvimento Profissional (47,1% dos artigos analisados).
Addressing conservation practice limitations and trade‐offs for reducing phosphorus loss from agricultural fields

Conservation practices that reduce nutrient and soil loss from agricultural lands to water are fundamental to watershed management programs. Avoiding trade‐offs of conservation practices is essential to the successful mitigation of watershed phosphorus (P) losses. We review documented trade‐offs associated with conservation practices, particularly those practices that are intended to control and trap P from agricultural sources. A regular theme is the trade‐off between controlling P loss linked to sediment while increasing dissolved P losses (no‐till, cover crops, vegetated buffers, constructed wetlands, sediment control basins). A variety of factors influence the degree to which these trade‐offs occur, complicated by their interaction and uncertainties associated with climate change. However, acknowledging these trade‐offs and anticipating their contribution to watershed outcomes are essential to the sustainability of conservation systems.
Block Bootstrap and Long Memory

We consider the issue of Block Bootstrap methods in processes that exhibit strong dependence. The main difficulty is to transform the series in such way that implementation of these techniques can provide an accurate approximation to the true distribution of the test statistic under consideration. The bootstrap algorithm we suggest consists of the following operations: given x t ~ I(d 0 ) , 1) estimate the long memory parameter and obtain dˆ , 2) difference the series dˆ times, 3) apply the block bootstrap on the above and finally, 4) cumulate the bootstrap sample dˆ times. Repetition of steps 3 and 4 for a sufficient number of times, results to a successful estimation of the distribution of the test statistic. Furthermore, we establish the asymptotic validity of this method. Its finite-sample properties are investigated via Monte Carlo experiments and the results indicate that it can be used as an alternative, and in most of the cases to be preferred than the Sieve AR bootstrap for fractional processes.
Interface Homem-máquina Android para Sistemas Embarcados com Recursos Restritos

Os sistemas embarcados (SEs) estão presentes em uma infinidade de equipamentos, sendo que muitos necessitam apresentar baixo consumo de energia e/ou baixo custo. Isso leva à interfaces homem-máquina (IHM) muito limitadas, compostas por LEDs e teclas, e sem conexão com a internet. Dada essa limitação, o objetivo desse trabalho foi desenvolver uma IHM para smartphones Android configurável. A IHM desenvolvida (protocolo + aplicativo Android) permite ao usuário interagir com qualquer SE por meio da tela do smartphone e uma conexão Bluetooth. Dado que os componentes visualizados no smartphone são definidos pelo próprio SE, por meio de comandos via Bluetooth, a IHM pode ser utilizada para interagir com diferentes equipamentos.