Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ROLE OF HUMAN CAPITAL FOR EMPLOYMENT GROWTH: A CASE STUDY OF HEIS IN JAMSHORO EDUCATION CITY

The scope and purpose of this paper is to examine the influence and extent of human capital on the employment growth. Such measurement is taken from the higher educational Institutes (HEIs) as empirical evidence. The paper would measure the important factors of the human capital such as education, training and experience as the basic catalysts for the formation of the human capital and when it’s utilized in organized manner it’s incidence on the employment opportunities at micro level and on economy at macro level. Quantitative method is used for this paper, because the aim is to classify features, count them, and construct analysis in an attempt to explain what is observed during the research. It is found that whether it is the general or specific human capital, there should be an urgency to develop customized (need based) skills and competencies to cater the needs of certain industries. It is further transpired that the blend of general (education) and specific (training & experience) human capital ensures the positive growth of employment, as both these factors complement each other.
Pseudospin magnetism in graphene

We predict that neutral graphene bilayers are pseudospin magnets in which the charge density contribution from each valley and spin spontaneously shifts to one of the two layers. The band structure of this system is characterized by a momentum-space vortex, which is responsible for unusual competition between band and kinetic energies, leading to symmetry breaking in the vortex core. We discuss the possibility of realizing a pseudospin version of ferromagnetic metal spintronics in graphene bilayers based on hysteresis associated with this broken symmetry.
Research on the Authenticity of Mutton Based on Machine Vision Technology

To realize the real-time automatic identification of adulterated minced mutton, a convolutional neural network (CNN) image recognition model of adulterated minced mutton was constructed. Images of mutton, duck, pork and chicken meat pieces, as well as prepared mutton adulterated with different proportions of duck, pork and chicken meat samples, were acquired by the laboratory’s self-built image acquisition system. Among all images were 960 images of different animal species and 1200 images of minced mutton adulterated with duck, pork and chicken. Additionally, 300 images of pure mutton and mutton adulterated with duck, pork and chicken were reacquired again for external validation. This study compared and analyzed the modeling effectiveness of six CNN models, AlexNet, GoogLeNet, ResNet-18, DarkNet-19, SqueezeNet and VGG-16, for different livestock and poultry meat pieces and adulterated mutton shape feature recognition. The results show that ResNet-18, GoogLeNet and DarkNet-19 models have the best learning effect and can identify different livestock and poultry meat pieces and adulterated minced mutton images more accurately, and the training accuracy of all three models reached more than 94%, among which the external validation accuracy of the optimal three models for adulterated minced mutton images reached more than 70%. Image learning based on a deep convolutional neural network (DCNN) model can identify different livestock meat pieces and adulterated mutton, providing technical support for the rapid and nondestructive identification of mutton authenticity.
A proof that the square root of s for s not a perfect square is simply normal to base 2

Since E. Borel proved in 1909 that almost all real numbers with respect to Lebesgue measure are normal to all bases, an open problem has been whether simple irrationals like square root of 2 are normal to any base. We show that each number of the form square root of s for s not a perfect square is simply normal to base 2, that is, the averages of the first n digits of its dyadic expansion converge to 1/2. The proof is mostly elementary and self contained but some basic probability is used. The main idea centers on the notion of tails of an expansion, that is, the sequence of digits with index larger than any fixed integer n.
OFFS-Net: Optimal Feature Fusion-Based Spectral Information Network for Airborne Point Cloud Classification

Airborne laser scanning (ALS) point cloud classification is a necessary step for understanding 3-D scenes and their applications in various industries. However, the classification accuracy and efficiency are low: 1) point cloud classification methods lack effective filtering of the large number of traditional features, 2) significant category imbalance and coordinate scale problems in ALS point cloud classification. To address these problems, this article proposes an airborne LiDAR point cloud classification method based on deep learning network with optimal feature fusion-based spectral information. This method involves the following steps: First, multiscale point cloud features are extracted, and random forest method is used to filter the features, while spectral information is fused to obtain a point cloud feature dataset with less but better data. Second, to adapt to the characteristics of the airborne point cloud, the improved RandLA-Net can simultaneously retain the advantages of random sampling and learn deeper semantic information by fusing the constructed point cloud features with the local feature aggregation module in the network. Third, four fusion models are constructed to verify the effectiveness of the optimal feature fusion-based spectral information network (OFFS-Net) model for airborne point cloud classification. Last, these models are trained and tested on Vaihingen 3-D dataset. The OFFS-Net achieves overall accuracy score of 84.9% and F1-score of 72.3%, which are better than the mainstream methods. This also validates that the proposed OFFS-Net point cloud classification method, based on the advantages of geometric feature and spectral information is excellent.
Underlying Event Simulation in the Herwig++ Event Generator

We study Quantum Chromodynamics (QCD) at hadron colliders. This is done in the context of general purpose Monte Carlo event generators. The aim of this thesis is to develop and implement a model for the so–called underlying event for the program Herwig++. We discuss multiple parton-parton scattering as source of the underlying event and show that our implementation is able to describe existing data from the Tevatron collider very well. Nevertheless we extend this model by a soft, non-perturbative component. This allows us to use the so–called minimum bias data, where only a minimum amount of requirements on the final-state are imposed, to challenge our model. This extension additionally allows us to couple the underlying event activity to measurements of total and elastic cross sections and therefore offers a powerful constraint to reduce the extrapolation uncertainties. Zusammenfassung Wir untersuchen die Quanten-Chromodynamik (QCD) an Hadron-Kollidern. Dies geschieht im Rahmen eines Monte Carlo Ereignis Generators, Herwig++. Das Ziel dieser Arbeit ist die Entwicklung und Implementierung eines Modelles für das sogenannte underlying event. Wir diskutieren mehrfache Parton-Parton Wechselwirkungen als Quelle und zeigen, dass unsere Implementierung in der Lage ist existierende Daten des Tevatron Beschleunigers sehr gut zu beschreiben. Gleichwohl erweitern wir dieses Modell um eine nicht-störungstheoretische Komponente. Diese erlaubt uns den Vergleich mit sogenannten minimum bias Daten, welche sich durch eine minimale Anzahl an Einschränkungen an die Endzustandsteilchen auszeichnen. Zusätzlich ermöglicht es diese Erweiterung, die Aktivität im underlying event an Messungen des totalen und elastischen Wirkungsquerschnittes zu koppeln, wodurch die Unsicherheiten der Vorhersage reduziert werden.
Coming to see fractions on the numberline

The aim of this paper is to present a didactical sequence that fosters the development of meanings related to fractions, conceived as numbers that can be placed on the number line. The sequence was carried out in various elementary school classes, containing students certified to have mathematical learning disabilities (MLD). Thus, our didactical aim is to make accessible meaning related to fractions to all students of the class, including MLD students, by means of a common didactical sequence, that is, a sequence proposed to the entire class. Our research is based on a range of different perspectives, from mathematics education to neuroscience and cognitive psychology. We discuss how such perspectives can be combined and provide the theoretical bases to design an outline of the didactical sequence, which allows us to implement and strengthen inclusive education.
Multi-scenario millimeter wave wireless channel measurements and sparsity analysis

Wireless channel characteristics have significant impacts on channel modeling, estimation, and communication performance. While the channel sparsity is an important characteristic of wireless channels. Utilizing the sparse nature of wireless channels can reduce the complexity of channel modeling and estimation, and improve system design and performance analysis. Compared with the traditional sub-6 GHz channel, millimeter wave (mmWave) channel has been considered to be more sparse in existing researches. However, most research only assume that the mmWave channel is sparse, without providing quantitative analysis and evaluation. Therefore, this paper evaluates the sparsity of mmWave channels based on mmWave channel measurements. A vector network analyzer (VNA)-based mmWave channel sounder is developed to measure the channel at 28 GHz, and multi-scenario channel measurements are conducted. The Gini index, Rician K factor and root-mean-square (RMS) delay spread are used to measure channel sparsity. Then, the key factors affecting mmWave channel sparsity are explored. It is found that antenna steering direction and scattering environment will affect the sparsity of mmWave channel. In addition, the impact of channel sparsity on channel eigenvalue and capacity is evaluated and analyzed.
Induced Fibration of Suspensions

This paper describes some of the phenomena found to have their origin in electrically induced fibration of small particles in fluid liquid suspension. Particular attention is given to induced shear resistances found in layers of the fluid (0.01 to 0.15 cm) when bounded by potentialized electrode surfaces. Ingredients and manner of compounding concentrated fluids capable of reversible shear resistance up to several hundred grams per cm2 are described. Dynamic induced shear resistance or the corresponding induced bulk viscosity are shown to be a parabolic function of field strength wherein parameters dependent on surface conditions of the particles are involved. Various properties of these fluids are discussed with regard to the mechanism of induced fibration, its application in slip clutches and other hydraulic devices, and some of the factors for best results. Consideration is given to the analogous magnetically induced fibration of ferromagnetic particles in fluid suspension. It is found that the observe.
Superconformal index of  = 3 orientifold theories

We analyze the superconformal index of the  = 3 supersymmetric generalized orientifold theories recently proposed. In the large N limit we derive the index from the Kaluza–Klein modes in AdS 5 × S 5 / Z k , which are obtained from ones in AdS 5 × S 5 by a simple Z k projection. For the ordinary Z 2 orientifold case the agreement with the gauge theory calculation is explicitly confirmed, and for Z k ≥ 3 we perform a few consistency checks with known results for  = 3 theories. We also study finite N corrections by analyzing wrapped D3-branes and discrete torsions in the dual geometry.
Weyl gravity and Cartan geometry

We point out that the Cartan geometry known as the second-order conformal structure provides a natural differential geometric framework underlying gauge theories of conformal gravity. We are concerned by two theories: the first one will be the associated Yang-Mills-like Lagrangian, while the second, inspired by J.T. Wheeler in Phys. Rev. D90 (2014), will be a slightly more general one which will relax the conformal Cartan geometry. The corresponding gauge symmetry is treated within the BRST language. We show that the Weyl gauge potential is a spurious degree of freedom, analogous to a Stueckelberg field, that can be eliminated through the dressing field method. We derive sets of field equations for both the studied Lagrangians. For the second one, they constrain the gauge field to be the `normal conformal Cartan connection'. Finally, we provide in a Lagrangian framework a justification of the identification, in dimension $4$, of the Bach tensor with the Yang-Mills current of the normal conformal Cartan connection, as proved in Class. Quant. Grav. 20 (2003).
Splitting theorems on complete manifolds with Bakry-Émery curvature

In this paper we study some splitting properties on complete noncompact manifolds with smooth measures when $\infty$-dimensional Bakry-\'Emery Ricci curvature is bounded from below by some negative constant and spectrum of the weighted Laplacian has a positive lower bound. These results extend the cases of Ricci curvature and $m$-dimensional Bakry-\'Emery Ricci curvature.
Faber–Krahn type inequality for unicyclic graphs

The Faber–Krahn inequality is related to the smallest nonzero eigenvalue of the Laplacian operator with Dirichlet boundary condition on a bounded domain in ℝ n . In this article, we investigate some properties of the first Dirichlet eigenvalue of unicyclic graphs. These results are used to show that the Faber–Krahn type inequality also holds for unicyclic graphs with a given graphic unicyclic degree sequence with minor conditions.
Consistency in responses to conspecific advertisement calls with various signal-to-noise ratios in both sexes of the Anhui tree frog

Abstract Environmental noise has a significant negative impact on acoustic communication in most situations, as it influences the production, transmission, and reception of acoustic signals. However, how animals respond to conspecific sounds when there is interference from environmental noise, and whether males and females display convergent behavioral responses in the face of noise masking remain poorly understood. In this study, we investigated the effects of conspecific male advertisement calls with different signal-to-noise ratios on male–male competition and female choice in the Anhui tree frog Rhacophorus zhoukaiyae using playback and phonotaxis experiments, respectively. The results showed that (1) female Anhui tree frogs preferentially selected the conspecific calls with higher SNR compared to calls with lower SNR; (2) males preferentially responded vocally to the conspecific calls with higher SNR compared to calls with lower SNR; and (3) males’ competitive strategies were flexible in the face of noise interference. These results suggest that preferences of both sexes converge in outcome, and that male competitive strategies may depend on predictable female preferences. This study will provide an important basis for further research on decision-making in animals.
Use of bayesian analysis to design of clinical trials with one treatment

Assuming a Weibull distribution, the posterior distribution for the median survival time is derived in the presence of arbitrary right censorship. In the design of clinical triaLs, suppose k follow-up periods have been completed and it is desired to plan the follow-up period k+1. In this context, criteria are presented that can be employed in determining the number of new patients to be enrolled in the follow-up period k+1.
Assessing the Underestimation of HIV Risk Infection among Young Men Who Have Sex with Men in Argentina

The aim of this study is to describe the discordance between the self-perceived risk and actual risk of HIV among young men who have sex with men (YMSM) and its associated factors. An online, cross-sectional study was conducted with 405 men recruited from an Argentinian NGO in 2017. Risk discordance (RD) was defined as the expression of the underestimation of risk, that is, as a lower self-perception of HIV risk, as measured with the Perceived Risk of HIV Scale, than the current risk of HIV infection, as measured by the HIV Incidence Risk Index. Multivariate logistic regression models were used to analyze the associations between the RD and the explanatory variables. High HIV risk was detected in 251 (62%), while 106 (26.2%) showed high self-perceived risk. RD was found in 230 (56.8%) YMSM. The predictors that increased RD were consistent condom use with casual partners (aOR = 3.8 [CI 95:1.5–11.0]), the use of Growler to meet partners (aOR = 10.38 [CI 95:161–121.94]), frequenting gay bars (aOR = 1.9 [95% CI:1.1–3.5]) and using LSD (aOR = 5.44 [CI 95:1.32–30.29]). Underestimation of HIV risk in YMSM is associated with standard HIV risk behavior and modulated by psychosocial aspects. Thus, prevention campaigns aimed at YMSM should include these factors, even though clinical practice does not. Health professionals should reconsider adapting their instruments to measure the risk of HIV in YMSM. It is unknown what score should be used for targeting high-risk YMSM, so more research is needed to fill this gap. Further research is needed to assess what score should be used for targeting high-risk in YMSM.
MASS GROWTH OF OBJECTS AND CATEGORICAL ENTROPY

In the pioneering work by Dimitrov–Haiden–Katzarkov–Kontsevich, they introduced various categorical analogies from the classical theory of dynamical systems. In particular, they defined the entropy of an endofunctor on a triangulated category with a split generator. In the connection between the categorical theory and the classical theory, a stability condition on a triangulated category plays the role of a measured foliation so that one can measure the “volume” of objects, called the mass, via the stability condition. The aim of this paper is to establish fundamental properties of the growth rate of mass of objects under the mapping by the endofunctor and to clarify the relationship between it and the entropy. We also show that they coincide under a certain condition.
Projective and polynomial superflows. I

Let $x\in\mathbb{R}^{n}$. For $\phi:\mathbb{R}^{n}\mapsto\mathbb{R}^{n}$ and $t\in\mathbb{R}$, we put $\phi^{t}=t^{-1}\phi(xt)$. A projective flow is a solution to the projective translation equation $\phi^{t+s}=\phi^{t}\circ\phi^{s}$, $t,s\in\mathbb{R}$. Previously we have developed an arithmetic, topologic and analytic theory of $2$-dimensional projective flows: rational, algebraic, unramified, abelian flows, commuting flows. The current paper is devoted to highly symmetric flows - superflows. Within flows with a given symmetry, superflows are unique and optimal. Our first result classifies all $2$-dimensional superflows. For any positive integer $d$, there exists the superflow $\phi_{\mathbb{D}_{2d+1}}$ whose group of symmetries is the dihedral group $\mathbb{D}_{2d+1}$. In the current paper we explore the superflow $\phi_{\mathbb{D}_{5}}$, which leads to investigation of abelian functions over curve of genus $6$. The $3$-dimensional theory of projective flows is more involved. We investigate two different $3$-dimensional superflows, whose group of symmetries are, respectively, the full tetrahedral group $\widehat{\mathbb{T}}$ (all symmetries of a tetrahedron), and the octahedral group $\mathbb{O}$ (orientation preserving symmetries of an octahedron), both isomorphic, though non-equivalent as representations. The generic orbits of the first flow are space curves of genus $1$, and the flow itself can be analytically described in terms of Jacobi elliptic functions. The generic orbits of the second flow are curves of genus $9$, and the flow itself can be described in terms of Weierstrass elliptic functions (via reduction of hyper-elliptic functions to elliptic). In the second part of this work we will classify all $3$-dimensional superflows (including the icosahedral superflow), and in the third we investigate superflows over $\mathbb{C}$.
The Analysis of Relevant Gene Networks Based on Driver Genes in Breast Cancer

Background: The occurrence and development of breast cancer has a strong correlation with a person’s genetics. Therefore, it is important to analyze the genetic factors of breast cancer for future development of potential targeted therapies from the genetic level. Methods: In this study, we complete an analysis of the relevant protein–protein interaction network relating to breast cancer. This includes three steps, which are breast cancer-relevant genes selection using mutual information method, protein–protein interaction network reconstruction based on the STRING database, and vital genes calculating by nodes centrality analysis. Results: The 230 breast cancer-relevant genes were chosen in gene selection to reconstruct the protein–protein interaction network and some vital genes were calculated by node centrality analyses. Node centrality analyses conducted with the top 10 and top 20 values of each metric found 19 and 39 statistically vital genes, respectively. In order to prove the biological significance of these vital genes, we carried out the survival analysis and DNA methylation analysis, inquired about the prognosis in other cancer tissues and the RNA expression level in breast cancer. The results all proved the validity of the selected genes. Conclusions: These genes could provide a valuable reference in clinical treatment among breast cancer patients.
Measures and applications of quantum correlations

Quantum information theory is built upon the realisation that quantum resources like coherence and entanglement can be exploited for novel or enhanced ways of transmitting and manipulating information, such as quantum cryptography, teleportation, and quantum computing. We now know that there is potentially much more than entanglement behind the power of quantum information processing. There exist more general forms of non-classical correlations, stemming from fundamental principles such as the necessary disturbance induced by a local measurement, or the persistence of quantum coherence in all possible local bases. These signatures can be identified and are resilient in almost all quantum states, and have been linked to the enhanced performance of certain quantum protocols over classical ones in noisy conditions. Their presence represents, among other things, one of the most essential manifestations of quantumness in cooperative systems, from the subatomic to the macroscopic domain. In this work we give an overview of the current quest for a proper understanding and characterisation of the frontier between classical and quantum correlations (QCs) in composite states. We focus on various approaches to define and quantify general QCs, based on different yet interlinked physical perspectives, and comment on the operational significance of the ensuing measures for quantum technology tasks such as information encoding, distribution, discrimination and metrology. We then provide a broader outlook of a few applications in which quantumness beyond entanglement looks fit to play a key role.