We recently mapped a quantitative trait locus (QTL) with a major effect on milk composition--particularly fat content--to the centromeric end of bovine chromosome 14. We subsequently exploited linkage disequilibrium to refine the map position of this QTL to a 3-cM chromosome interval bounded by microsatellite markers BULGE13 and BULGE09. We herein report the positional candidate cloning of this QTL, involving (1) the construction of a BAC contig spanning the corresponding marker interval, (2) the demonstration that a very strong candidate gene, acylCoA:diacylglycerol acyltransferase (DGAT1), maps to that contig, and (3) the identification of a nonconservative K232A substitution in the DGAT1 gene with a major effect on milk fat content and other milk characteristics.
Joaquín Raul Rodríguez, Erik Esteban Ramírez, Mario González-Durán
Mexicali, capital of Baja California, has 1,049,792 inhabitants and lies in a high-seismic-hazard zone in northwestern Mexico, according to CENAPRED, the MDOC-CFE-2015 seismic regionalization, and the ASCE 7-22 “Hazard Toolkit”. This study develops a probabilistic seismic hazard map to estimate peak ground accelerations with a 2% probability of exceedance in 50 years, using the OpenQuake platform. The study area coincides with the 2025 urban development plan polygon for the central population area defined by the Municipal Institute for Research and Urban Planning of Mexicali. The Imperial and Cerro Prieto faults, the Pescaderos–Indiviso fault system, and the Laguna Salada fault were modeled as seismic sources. Four PEER-NGA ground motion prediction equations and regional geophysical and geotechnical data were employed to characterize shear-wave velocity (Vs30). Design response spectra were generated for each grid point for the 21 periods specified in ASCE 7-22. A representative Vs30 of 236 m/s was obtained, and the a, b, and Mc parameters were derived for the seismic catalog. Resulting peak ground accelerations range from 0.842 g to 1.221 g, with a maximum spectral pseudo-acceleration of 2.23 g at 0.30 s.
An identity map $(M,g)\longrightarrow(M,g)$ is a harmonic from a Riemannian manifold $(M,g)$ onto itself. In this paper, we study the harmonicity of identity maps $(M,g)\longrightarrow(M,g-df\otimes df)$ and $(M,g-df\otimes df)\longrightarrow(M,g)$ where $f$ is a smooth function with gradient norm $<1$ on $(M,g)$. We construct new examples of identity harmonic maps. We define a symmetric tensor field on $M$ whose properties are related to the harmonicity of these identity maps.
Online learning has become increasingly prevalent in real-world applications, where data streams often comprise heterogeneous feature types—both nominal and numerical—and labels may not arrive synchronously with features. However, most existing online learning methods assume homogeneous data types and synchronous arrival of features and labels. In practice, data streams are typically heterogeneous and exhibit asynchronous label feedback, making these methods insufficient. To address these challenges, we propose a novel algorithm, termed <i>Online Asynchronous Learning over Streaming Nominal Data</i> (OALN), which maps heterogeneous data into a continuous latent space and leverages a model pool alongside a hint mechanism to effectively manage asynchronous labels. Specifically, OALN is grounded in three core principles: (1) It utilizes a Gaussian mixture copula in the latent space to preserve class structure and numerical relationships, thereby addressing the encoding and relational learning challenges posed by mixed feature types. (2) It performs adaptive imputation through conditional covariance matrices to seamlessly handle random missing values and feature drift, while incrementally updating copula parameters to accommodate dynamic changes in the feature space. (3) It incorporates a model pool and hint mechanism to efficiently process asynchronous label feedback. We evaluate OALN on twelve real-world datasets; the average cumulative error rates are 23.31% and 28.28% under the missing rates of 10% and 50%, respectively, and the average AUC scores are 0.7895 and 0.7433, which are the best results among the compared algorithms. And both theoretical analyses and extensive empirical studies confirm the effectiveness of the proposed method.
Sunny Rhoades, Tucker Jones, Keerthi Vasan G. C.
et al.
The kinematics of star-forming galaxy populations at high redshifts are integral to our understanding of disk properties, merger rates, and other defining characteristics. Nebular gas emission is a common tracer of galaxies’ gravitational potential and angular momenta, but is sensitive to nongravitational forces as well as galactic outflows, and thus might not accurately trace the host galaxy dynamics. We present kinematic maps of young stars from rest-ultraviolet photospheric absorption in the star-forming galaxy CASSOWARY 13 (a.k.a. SDSS J1237+5533) at z = 1.87 using the Keck Cosmic Web Imager, alongside nebular emission measurements from the same observations. Gravitational lensing magnification of the galaxy enables good spatial sampling of multiple independent lensed images. We find close agreement between the stellar and nebular velocity fields. We measure a mean local velocity dispersion of σ = 64 ± 12 km s ^−1 for the young stars, consistent with that of the H ii regions traced by nebular C iii ] emission (52 ± 9 km s ^−1 ). The ∼20 km s ^−1 average difference in line-of-sight velocity is much smaller than the local velocity width and the velocity gradient (≳100 km s ^−1 ). We find no evidence of asymmetric drift nor evidence that outflows bias the nebular kinematics, and thus we conclude that nebular emission appears to be a reasonable dynamical tracer of young stars in the galaxy. These results support the picture of star formation in thick disks with high velocity dispersion at z ∼ 2, and they represent an important step toward establishing robust kinematics of early galaxies using collisionless tracers.
As the 6G era approaches, wireless communication faces challenges such as massive user numbers, high mobility, and spectrum resource sharing. Radio maps are crucial for network design, optimization, and management, providing essential channel information. In this paper, we propose an innovative learning framework for Radio Map Estimation (RME) based on cycle-consistent generative adversarial networks. Traditional RME methods are often constrained by model complexity and interpolation accuracy, while learning-based methods require strictly paired datasets, making their practical application difficult. Our method overcomes these limitations by enabling training with unpaired data, efficiently converting local features into radio maps. Our experimental results demonstrate the effectiveness of the proposed method in two scenarios: accurate map data and map data with dynamic errors. To address dynamic interference, we designed a two-stage learning process that uses sparse observations to correct local details in the radio map, and the model's accuracy and practicality.
Gregory Sallaberry, Benjamin W. Priest, Robert Armstrong
et al.
Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.
Dominika Kuźma, Oleksandr Pastukh, Piotr Zieliński
Micromagnetic computations were performed to predict the magnetisation maps in thin elliptically shaped nanoparticles under a variable external magnetic field. Two materials were compared as the constituents of the nanoparticles: permalloy as an example of an isotropic magnet and cobalt, i.e., a hard magnetic material marked with a single easy axis. The interplay of the shape and magnetocrystalline anisotropy gives rise to a variety of switching scenarios, which may be of interest in designing memory storage devices. A fairly periodic shape-induced superlattice-like spin configuration occurs when the shape and magnetocrystalline easy axes are orthogonal. Possible applications as magnonic devices are discussed.
The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5–43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the ‘S-A’ axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.
Athanasia Chroni, Christos Vasilakos, Marianna Christaki
et al.
Spectral confusion among land cover classes is quite common, let alone in a complex and heterogenous system like the semi-arid Mediterranean environment; thus, employing new developments in remote sensing, such as multispectral imagery (MSI) captured by unmanned aerial vehicles (UAVs) and airborne light detection and ranging (LiDAR) techniques, with deep learning (DL) algorithms for land cover classification can help to address this problem. Therefore, we propose an image-based land cover classification methodology based on fusing multispectral and airborne LiDAR data by adopting CNN-based semantic segmentation in a semi-arid Mediterranean area of northeastern Aegean, Greece. The methodology consists of three stages: (i) data pre-processing, (ii) semantic segmentation, and (iii) accuracy assessment. The multispectral bands were stacked with the calculated Normalized Difference Vegetation Index (NDVI) and the LiDAR-based attributes height, intensity, and number of returns converted into two-dimensional (2D) images. Then, a hyper-parameter analysis was performed to investigate the impact on the classification accuracy and training time of the U-Net architecture by varying the input tile size and the patch size for prediction, including the learning rate and algorithm optimizer. Finally, comparative experiments were conducted by altering the input data type to test our hypothesis, and the CNN model performance was analyzed by using accuracy assessment metrics and visually comparing the segmentation maps. The findings of this investigation showed that fusing multispectral and LiDAR data improves the classification accuracy of the U-Net, as it yielded the highest overall accuracy of 79.34% and a kappa coefficient of 0.6966, compared to using multispectral (OA: 76.03%; K: 0.6538) or LiDAR (OA: 37.79%; K: 0.0840) data separately. Although some confusion still exists among the seven land cover classes observed, the U-Net delivered a detailed and quite accurate segmentation map.
Rim Elfahem, Bastien Bouchet, Boussad Abbes
et al.
This study aims to investigate the impact of body heat loss on the thermal and aerodynamic conditions in a whole-body cryotherapy chamber. The underlying hypothesis is that the heat generated by the human body alters the thermal and aerodynamic environment inside the cabin. A numerical study was conducted to test this hypothesis and analyze the thermodynamic exchanges between the human body and the cabin during a 3 min whole-body cryotherapy session. The computational fluid dynamics (CFD) approach was used to study the unsteady heat transfer between the human body and the interior of the cryotherapy cabin. A thermal boundary condition, based on a mathematical model developed from experimental data, was applied to simulate skin cooling kinetics over time. The post-processing of the 3D results, including temperature, velocity fields, and thermal flux maps at the body surface, provided insight into the thermo-convective mechanisms involved in a whole-body cryotherapy session. The study found that body heat loss significantly affects the temperature fields inside the cabin, leading to global modifications of the aeraulic and thermal conditions. These findings suggest that cryotherapy protocols may need to be adjusted or the cabin set temperature optimized to enhance the therapeutic benefits.
Thermodynamics, Descriptive and experimental mechanics
Aditia Yudhistira, Imas Sukaesih Sitanggang, Hari Agung Adrianto
The SOLAP system for Indonesian Agricultural Commodities is a successful development based on previous studies. Agricultural commodity data are managed in a data warehouse with a galactic schema, which has 7 fact tables, namely cut flower horticulture, ornamental plant horticulture, horticulture, food crops, plantation, livestock population, and livestock production, as well as 3 dimensional tables, namely location, time, and commodity. The results of SOLAP operations on the system can be visualized in the form of crosstabs, graphs and maps. The system uses a web platform so that it can be accessed by the public. However, the SOLAP system cannot update data in real time. This study aims to develop a data warehouse for Indonesian Agricultural Commodities SOLAP in real time by creating a scraping system. This study has succeeded in developing a data warehouse in real time on the indonesian agricultural commodity SOLAP system by creating a real time scraping system that is applied to the SOLAP server and has succeeded in making the ETL process run in real time on the SOLAP server and optimizing polygon-based spatial data visualization using the Douglas-Peucker. This study has also carried out functional testing of OLAP features and functions on the Indonesian Agricultural Commodity SOLAP system using the black box testing method. The results of this study provide accurate and real-time data on the SOLAP of Indonesian Agricultural Commodities, with the results of SOLAP feature testing achieving 100 percent pass and the data conformity test results of OLAP function as expected. In addition, the results of this study make it possible to automatically update the data according to a predetermined schedule to provide real-time information.
Giuseppe della Sala, Bernhard Lamel, Michael Reiter
et al.
For $N \geq 4$ we classify the $(N-3)$-degenerate smooth CR maps of the three-dimensional unit sphere into the $(2N-1)$-dimensional unit sphere. Each of these maps has image being contained in a five-dimensional complex-linear space and is of degree at most two, or equivalent to one of the four maps into the five-dimensional sphere classified by Faran. As a byproduct of our classification we obtain new examples of rational maps of degree three which are $(N-3)$-degenerate only along a proper real subvariety and are not equivalent to polynomial maps. In particular, by changing the base point, it is possible to construct new families of nondegenerate maps.
We introduce a heat flow associated to half-harmonic maps, which have been introduced by Da Lio and Rivière. Those maps exhibit integrability by compensation in one space dimension and are related to harmonic maps with free boundary. We consider a new flow associated to these harmonic maps with free boundary which is actually motivated by a rather unusual heat flow for half-harmonic maps. We construct then weak solutions and prove their partial regularity in space and time via a Ginzburg-Landau approximation. The present paper complements the study initiated by Struwe and Chen-Lin.
François-Xavier Crahay, Guillaume Debellemanière, Stephan Tobalem
et al.
Abstract Keratoconus is a highly prevalent corneal disorder characterized by progressive corneal thinning, steepening and irregular astigmatism. To date, pathophysiology of keratoconus development and progression remains debated. In this study, we retrospectively analysed topographic elevation maps from 3227 eyes of 3227 patients (969 keratoconus and 2258 normal eyes) to calculate anterior and posterior corneal surface area. We compared results from normal eyes and keratoconus eyes using the Mann–Whitney U test. The Kruskal–Wallis test was used to compare keratoconus stages according to the Amsler–Krumeich classification. Keratoconus eyes were shown to have statistically significantly larger corneal surface areas, measured at the central 4.0 mm and 8.0 mm, and total corneal diameter. However, no significant increase in corneal surface area was seen with increasing severity of keratoconus. We suggest that these results indicate redistribution, rather than increase, of the corneal surface area with keratoconus severity.
Abstract The present paper aims to quantify how human-made changes in the upstream exacerbate climate change impacts on water birds’ habitat in the downstream. To reduce climate change effects and design adaptation policies, it is important to identify whether human activities understate or overstate the effects of climate change in a region on its inhabitants. This paper also shows how human activities may magnify climate change impacts both locally and regionally. Land-use/land-cover change as the important sign of human-made destruction in an ecosystem was detected in the upstream of the Helmand basin over 40 years. Owing to conflicts in Afghanistan, studies on this basin are rare. The water bird’s habitat suitability maps during the study period were created using the maximum entropy model and the multi-criteria evaluation method. The post-classification method was applied to show the land-use/land-cover change over 40 years. These results were compared to the area of suitable habitat for water birds. The findings of these analyses indicated that the irrigated farming was expanded in the upstream despite climate change and water limitation, while the water birds’ habitat in the downstream was declined. These results revealed that the unsustainable pattern of farming and blocking water behind dams in the upstream exacerbated the negative effects of climate change on water birds’ habitat in the downstream. The significance of this study is to demonstrate the role of human in exacerbating climate change impacts both locally and regionally.
Introduction. The article continues a series of publications on the linguistics of the relationship (hereafter R-linguistics) and is concerned with the semantic interpretation in terms of the linguistic model that is the initial stage to consider the logic of natural language (external logic).Methodology and sources. The results obtained in the previous parts of the series are used as research tools. In particular, the verbal categorization method is used to represent concepts and verbs. To develop the necessary mathematical representations in the field of logic and semantics of natural language, the previously formulated concept of the interpretation operator is used. The interpretation operator maps the sentences of the language into the model, taking into account the previously interpreted sentences.Results and discussion. The problems that arise during the operation of the natural language interpretation operator are analyzed using examples of text translation and utterance algebra. The source of problems is the dependence of the interpretation of sentences on the already accumulated results of interpretation. The features of the interpretation of negation and double negation in the language are analyzed. In particular, the negation of a sentence affects the interpretation of previous sentences, and double negation usually denotes a single negation with an indication of its scope. It is shown that even from the point of view of classical logic, linguistic negation is not unconditional, and the operation of concatenation is not commutative and associative. General rules of text interpretation in the form of step-by-step mapping of sentence elements into a linguistic model are formulated.Conlcusion. From the considered examples of the implementation of the interpretation operator, it follows that the negation of a sentence requires a change in the meaning of the operation of attributing sentences in the text. For this reason, the negative particle ”not” in the language is actually a label for changing the interpretation rule. The double negation rule in sentence logic does not hold, so sentences containing double negations are likely to contain information about the scope of the sentence negation in the text. Based on the analysis, the contours of the interpretation operator for the linguistic model are indicated.
We give an elementary proof of a theorem that characterizes quasisymmetric maps of the unit circle in terms of shear coordinates on the Farey tesselation. The proof only uses the normal family argument for quasisymmetric maps and some elementary hyperbolic geometry.