Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of computer vision techniques for 3D matching and retrieval of archaeological objects

Background: As cultural institutions embark in projects oriented to digitise art and archaeological collections in three dimensions, the need for developing means to access the resulting 3D models has become imperative. Shape recognition techniques developed in the field of computer vision can help in this task. Methods: This paper describes the implementation of three shape descriptors, specifically shape distributions, reflective symmetry and spherical harmonics as part of the development of a search engine that retrieves 3D models from an archaeological database without the need of using keywords as query criteria. Use case: The usefulness of this system is obvious in the context of cultural heritage museums, where it is essential to provide automatic access to archaeological and art collections. The prototype described in this paper uses, as study case, 3D models of archaeological objects belonging to Museo del Templo Mayor, a Mexican institution that preserves one of the largest collections of Aztec cultural heritage. Conclusions: This work is part of an ongoing project focused on creating generic methodologies and user-friendly computational tools for shape analysis for the benefit of scholars and students interested in describing, interpreting and disseminating new knowledge about the morphology of cultural objects.
Field assessment of yield and its contributing traits in cowpea treated with lower, intermediate, and higher doses of gamma rays and sodium azide

Across the globe, plant breeders of different organizations are working in collaboration to bring preferred traits to crops of economic importance. Among the traits, “high yielding potential” is the most important as it is directly associated with food security and nutrition, one of the sustainable development goals. The Food and Agriculture Organization acknowledges plant breeders’ role and efforts in achieving local and global food security and nutrition. Recognizing the importance of pulses and increasing pressure on food security, the United Nations General Assembly declared 2016 the “International year of Pulses” owing to their preferred traits such as climate change resilience, wide adaptability, low agriculture input, and protein- and nutrient-rich crops. Keeping all these developments in consideration, we initiated an induced mutagenesis program by treating cowpea (Vigna unguiculata L. Walp.) with different doses of gamma rays and sodium azide aiming to enhance the yielding potential of an otherwise outstanding variety viz., Gomati VU-89 and Pusa-578. We noticed a substantial increase in mean values of agronomic traits in putative mutants raised from seeds treated with lower and intermediate doses of mutagens. Statistical analysis such as correlation, path, hierarchical clustering analysis (HCA), and principal component analysis (PCA) were used to assess the difference between mutagenized and control populations. A significant and positive correlation of yield with yield-attributing traits was recorded. However, among all the yield attributing traits, seeds per pod (SPP) depicted the maximum direct impact upon yield, and therefore, working on this trait may yield better results. A widely used PCA revealed 40.46% and 33.47% of the total variation for var. Gomati VU-89 and var. Pusa-578, respectively. Cluster analysis clustered treated and control populations into separate clusters with variable cluster sizes. Cluster V in the variety Gomati VU-89 and cluster V and VI in the variety Pusa 578 comprised of putative mutants were higher yielding and hence could be recommended for selection in future breeding programs. We expect to release such mutant lines for farmer cultivation in Northern parts of India depending on the performance of such high-yielding mutant lines at multilocations.
Buckling analysis of composite plates using moving least squares differential quadrature method

ABSTRACT This work concerns with buckling and vibration analysis of composite plates based on a transverse shear theory. A numerical scheme is introduced to determine the angular frequencies and critical buckling loads of such plates. Moving least square differential quadrature method is employed to reduce the problem to that of eigen value problem. The accuracy and efficiency of the proposed scheme is examined with different computational characteristics, (radius of support domain, basis completeness order, and scaling factors). The obtained results agreed, at less execution time, with the previous ones. Further, a parametric study is introduced to investigate the influence of elastic and geometric characteristics, (Young's modulus gradation ratio, shear modulus gradation ratio, Poisson's ratio, loading parameter, and aspect ratio), of the composite on the values of critical buckling load, natural frequencies, and behavior of mode shape functions.
QUANTITATIVE METHODS IN PSYCHOLOGY Component Analysis Versus Common Factor Analysis: A Monte Carlo Study

Component analysis and common factor analysis are competing exploratory procedures used to analyze variables into components or factors. The characteristics that distinguish the two procedures can be understood in terms of theoretical and empirical differences. Gorsuch (1974, 1983) noted that the main theoretical difference between the two is that the common factor analysis includes error explicitly in the model. Gorsuch (1983) illustrated this by showing that common factor analyses are derived from the following equation: Z = FP + UEX, where Z represents the standard score data matrix of n individuals and v variables, F is the standardized factor score matrix for the same individuals but with/factors, and P is the factor by variable matrix. Error is represented by UD1; "U is a matrix of unique factor scores with one unique factor for each variable, and D is a diagonal matrix giving each unique factor weight for reproducing the variable with which the weight is associated" (Gorsuch, 1983, p. 53). Gorsuch noted that component analysis is derived from the following equation: Z = FF. This model differs from the common factor model in that it has no error and therefore assumes that the data matrix is perfectly reproducible from the factor scores. These theoretical differences between component analysis and common factor analysis can be viewed as paradigmatic. Gorsuch (1988) noted that the component model follows the mathematical paradigm in that it perfectly reproduces each variable. In essence, component analysis assumes that the sample correlation matrix perfectly reflects the population correlation matrix. The common factor model reflects the statistical paradigm. Gorsuch (1988) stated, "In common factor analysis it is explicitly noted that the variables may be fallible and that
Bayesian (mean) most powerful tests

A fundamental theorem in hypothesis testing is the Neyman‐Pearson (N‐P) lemma, which creates the most powerful test of simple hypotheses. In this article, we establish Bayesian framework of hypothesis testing, and extend the Neyman‐Pearson lemma to create the Bayesian most powerful test of general hypotheses, thus providing optimality theory to determine thresholds of Bayes factors. Unlike conventional Bayes tests, the proposed Bayesian test is able to control the type I error.
A psychological study of unconnected conditionals

ABSTRACT Unconnected conditionals, also called irrelevant conditionals, are sentences of form if A, C, whose antecedent and consequent bear no connection. According to the main theories of conditional reasoning, the truth or high probability of an antecedent and a consequent is sufficient to make true or highly probable the corresponding conditional. We tested this assumption and showed that it does not hold for unconnected conditionals. Furthermore, we investigated experimentally the factors which favour the endorsement of irrelevant conditional constructions and found that this rate increases when an analogy can be built between the antecedent and the consequent or when the conditional is asserted before its components.
NUMERICAL SOLUTIONS FOR AXISYMMETRIC NON-NEWTONIAN STAGNATION ENROBING FLOW, HEAT, AND MASS TRANSFER WITH APPLICATION TO CYLINDRICAL PIPE COATING DYNAMICS

Heat and mass transfer in variable thermal conductivity micropolar axisymmetric stagnation enrobing flow on a cylinder is studied. Numerical solutions are obtained with an optimized variational finite element procedure and also a finite difference method. Graphical variations of velocity, angular velocity, temperature and concentration are presented for the effects of Reynolds number, viscosity ratio, curvature parameter, Prandtl number and Schmidt number. Excellent agreement is obtained for both finite element method (FEM) and finite difference method (FDM) computations. Further validation is achieved with a Chebyshev spectral collocation method (SCM). Skin friction is elevated with greater Reynolds number whereas it is suppressed with increasing micropolar parameter. Heat transfer rate decreases with an increase in the thermal conductivity parameter. Temperature and thermal boundary layer thickness is reduced with increasing thermal conductivity parameter and Reynolds number. Greater Reynolds number accelerates the micro-rotation values. Higher Schmidt number reduces the mass transfer function (species concentration) values. The mathematical model is relevant to polymeric manufacturing coating (enrobing) flows.
Bose-Einstein Condensation of Confined Atomic Gases at Ultra Low Temperatures

In this work I solve the Gross-Pitaevskii equation describing an atomic gas confined in an isotropic harmonic trap by introducing a variational wavefunction of Gaussian type. The chemical potential of the system is calculated and the solutions are discussed in the weakly and strongly interacting regimes. For the attractive system with negative scattering length the maximum number of atoms that can be put in the condensate without collapse begins is calculated.
Initiation of positive streamer corona in low thundercloud fields

Formation of filamentary gas discharge forms, commonly referred to as streamers, is one of the conditions required for initiation and subsequent propagation of lightning leaders. It is quantitatively demonstrated that streamers can be initiated under thunderstorm conditions when two precipitation particles cause an enhancement of the electric field by passing in close vicinity of each other. Conditions for avalanche‐to‐streamer transition are documented using a model of two spherical hydrometeor particles placed in uniform ambient field. The results are presented in scaled form using similarity relations for gas discharges and can be applied for a wide range of thunderstorm conditions, including different air pressures, electric fields, and particle dimensions.
Nucleation and growth of Y2O3 nanoparticles in a RF-ICTP reactor: a discrete sectional study based on CFD simulation supported with experiments

Synthesis of yttria (Y2O3) nanoparticles in an atmospheric pressure radiofrequency inductively coupled thermal plasma (RF-ICTP) reactor has been investigated using the discrete-sectional (DS) model of particle nucleation and growth with argon as the plasma gas. Thermal and fluid dynamic information necessary for the investigation have been extracted through rigorous computational fluid dynamic (CFD) study of the system with coupled electromagnetic equations under the extended field approach. The theoretical framework has been benchmarked against published data first, and then applied to investigate the nucleation and growth process of yttrium oxide nanoparticles in the plasma reactor using the discrete-sectional (DS) model. While a variety of nucleation and growth mechanisms are suggested in literature, the study finds that the theory of homogeneous nucleation fits well with the features observed experimentally. Significant influences of the feed rate and quench rate on the distribution of particles sizes are observed. Theoretically obtained size distribution of the particles agrees well with that observed in the experiment. Different thermo-fluid dynamic environments with varied quench rates, encountered by the propagating vapor front inside the reactor under different operating conditions are found to be primarily responsible for variations in the width of the size distribution.
Quality Management and Work Culture on Employee Performance:Mediating Role of Work Loyalty

This study aims to determine and analyze the impact of Quality Management and Work Culture on Employee Performance mediated by the role of Work Loyalty in DKI Jakarta Regional Owned Enterprises (BUMD) in the Property Sector group. The object of research is company employees in the DKI Jakarta Regional Owned Enterprises group in the Property Sector. Respondents who were sampled in this study amounted to 250 samples. The method used in this study is quantitative, using the Structural Equation Modeling (SEM) program with the help of SmartPLS software version 3.29. Quantitative data were obtained from distributing questionnaires by measuring them using a Likert scale to respondents. The results show that work culture is the variable that has the greatest influence on employee performance. This study also found that the second biggest influence that can increase employee performance is the work culture. It is also known that quality management, works culture, and works loyalty simultaneously influence employee performance. The next finding from this study is that works loyalty is an effective mediating variable to bridge the effect of quality management and works culture on employee performance.
Dual spherical single-mode-multimode-single-mode optical fiber temperature sensor based on a Mach–Zehnder interferometer

A dual spherical single-mode-multimode-single-mode (DSSMS) optical fiber temperature sensor based on a Mach–Zehnder interferometer (MZI) was designed and implemented in this paper. Theoretical and experimental results indicated that the LP01 mode in the core and the LP09 mode excited by the spherical structure were maintained and transmitted via multimode fiber and interfered at the second spherical structure, resulting in the interference spectrum. An increase or decrease in temperature can cause significant red-shift or blue-shift of the spectrum, respectively. The linearity of the spectral shift due to the temperature change is ~0.999, the sensitivity at 30 °C–540 °C is ~37.372 pm °C−3, and at −25 °C–25 °C is ~37.28 pm °C−1. The reproducibility error of this all-fiber temperature sensor at 30 °C–540 °C is less than 0.15%. Compared with the optical fiber sensor with a tapered structure and fiber core offset structure, this MZI-based DSSMS optical fiber temperature sensor has higher mechanical strength. Moreover, benefiting from low-cost and environmentally friendly materials, it is expected to be a novel micro-nano all-fiber sensor.
Blind Separation of Tampered Image Based on JPEG Double Quantization Effect

The double quantization effect of JPEG provides important clue for detecting image tampering. Whenever an original JPEG image has undergone a localized tampering and saved in JPEG again, the DCT coefficients of the areas without tampering will be compressed for twice while the tampered areas only suffered once. The Alternating Current (AC) coefficient distribution accord with a Laplace probability density distribution described with parameter  . This paper proposed a new double compression probability model of JPEG image to describe the change of DCT coefficients’ statistical properties after the double compression. According to Bayes’ theorem, using the posterior probability, the model can also show the eigenvalues of the double and single compressed block. We assign a dynamic adaptive threshold for the eigenvalues with the Particle Swarm Optimization Algorithm. Then the tampered region is detected and separated automatically by using the threshold. The experimental results show that the method can detect and separate the tamped area effectively and it outperforms other algorithms in terms of the detection result especially when the second compression factor is smaller than the first one. Compared with other traditional methods, the proposed approach could effectively separate the tampered regions from the tampered image without respect to the location, size and number of tampered images.
A lightweight model for efficient identification of plant diseases and pests based on deep learning

Plant diseases and pests have always been major contributors to losses that occur in agriculture. Currently, the use of deep learning-based convolutional neural network models allows for the accurate identification of different types of plant diseases and pests. To enable more efficient identification of plant diseases and pests, we design a novel network architecture called Dise-Efficient based on the EfficientNetV2 model. Our experiments demonstrate that training this model using a dynamic learning rate decay strategy can improve the accuracy of plant disease and pest identification. Furthermore, to improve the model’s generalization ability, transfer learning is incorporated into the training process. Experimental results indicate that the Dise-Efficient model boasts a compact size of 13.3 MB. After being trained using the dynamic learning rate decay strategy, the model achieves an accuracy of 99.80% on the Plant Village plant disease and pest dataset. Moreover, through transfer learning on the IP102 dataset, which represents real-world environmental conditions, the Dise-Efficient model achieves a recognition accuracy of 64.40% for plant disease and pest identification. In light of these results, the proposed Dise-Efficient model holds great potential as a valuable reference for the deployment of automatic plant disease and pest identification applications on mobile and embedded devices in the future.
New Optical Properties of Ice Crystals for Multiclass Cloud Microphysics

New optical properties of ice crystals were implemented in a general circulation model. Ebert and Curry's (1992, https://doi.org/10.1029/91JD02472) and Fu's (1996, https://doi.org/10.1175/1520‐0442(1996)009<2058:AAPOTS>2.0. CO;2) parameterizations are widely used in the general circulation model radiation scheme. However, the validity of the data is limited to an effective radius (size) of 130 or 140 μm. This limit exceeds the median of the effective radius of snow (~200 μm), which is computed from the multiclass cloud microphysics scheme. A comparable amount of snow exists in the upper atmosphere near the lower part of ice clouds. Although the cross section of snow (extinction probability) is smaller than cloud ice, its impact on radiation has not been properly considered so far. We constructed a new lookup table of optical properties based on recent data for an extended effective radius up to 500 μm. The old data (<130 μm) also need to be updated with a more recent and elaborate method. We processed extensive data provided by Yang et al. (2013, https://doi.org/10.1175/JAS‐D‐12‐039.1) and linked to the radiation module of the Korean Integrated Model (KIM). The new optical properties change the shortwave scattering features, thus increasing the heating rate. This tendency is checked in both one‐dimensional and global weather forecast simulations. With the new optical properties, KIM shows better performance by reducing bias with respect to the Integrated Forecasting Systems (IFS) analysis data.
Association between superior longitudinal fasciculus, motor recovery, and motor outcome after stroke: a cohort study

Introduction Parieto-frontal interactions are mediated by the superior longitudinal fasciculus (SLF) and are crucial to integrate visuomotor information and mediate fine motor control. In this study, we aimed to characterize the relation of white matter integrity of both parts of the SLF (SLF I and SLF II) to both motor outcome and recovery and its evolution over time in stroke patients with upper limb motor deficits. Materials and methods Fractional anisotropy (FA) values over the SLF I, SLF II, and corticospinal tract (CST) and upper limb motor performance evaluated by both the upper limb Fugl-Meyer Assessment score and maximum grip strength were measured for 16 patients at 3 weeks, 6 weeks, and 12 weeks poststroke. FA changes were assessed over time using repeated-measures Friedman ANOVA, and correlations between motor recovery, motor outcome at 12 weeks, and FA values in the CST, SLF I, and SLF II at 3 weeks were performed using Spearman's rank-order correlation. Results FA values in the affected hemisphere's SLF I and SLF II at 3 weeks correlated with motor recovery at 12 weeks when assessed by the Fugl-Meyer Assessment for upper limb extremity (rho: 0.502, p: 0.04 and rho: 0.510, p: 0.04, respectively) but not when assessed by grip strength. FA values in the SLF I and SLF II were not correlated with motor outcomes. FA values in the SLF II in the affected hemisphere changed significantly over time (p: 0.016). Conclusion Both SLF I and SLF II appeared to participate in poststroke motor recovery of complex movements but not in the motor outcome. These results argue that visually/spatially oriented motor tasks as well as more complex motor tasks using parietal associative areas should be used for poststroke rehabilitation strategies.
Consensus for discrete-time heterogeneous networked systems consisting of third-order and first-order agents under fixed and switching topologies

This paper investigates the consensus problem for heterogeneous multi-agent systems consisting of third-order and first-order agents. The interaction topology includes both fixed and switching cases. First, by a model transformation, heterogeneous multi-agent systems are converted into equivalent error systems. Then we analyze the consensus problem of the multi-agent systems by analyzing the stability problem of the error systems. For a fixed topology, a sufficient condition for consensus of heterogeneous multi-agent systems is obtained based on algebraic graph theory and linear system theory. For a switching topology, a necessary and sufficient condition for mean-square consensus of multi-agent systems is obtained based on algebraic graph theory and Markovian jump system theory. Finally, we give some simulation examples.