Abstract Bovine tuberculosis (bTB) and brucellosis are significant zoonoses that pose serious challenges to the cattle industry and present risks to human health. This study focused on dairy and beef cattle farms in Hubei Province, China, with the aim of assessing the current seroprevalence and identifying risk factors associated with these diseases. A comprehensive serological survey was conducted in Hubei Province from May 2023 to January 2024. Using a stratified systematic sampling approach, we collected 5889 samples from 160 cattle farms across the province to evaluate the prevalence of bTB and brucellosis. The results indicated an overall individual seroprevalence of 1.9% for bTB, with notable regional variations, whereas brucellosis had a higher individual seroprevalence of 2.9%. At the herd level, the prevalence of bTB was 17.5%, whereas it was 8.1% for brucellosis. Notably, the highest individual prevalence of both diseases was recorded in southwestern Hubei. The analysis also revealed that dairy cattle were more frequently positive for both bTB (Odds ratio (OR) = 4.9, 95% CI: 3.3, 7.3) and brucellosis (OR = 11.8, 95% CI: 8.6, 16.1) than beef cattle were. Generalized linear mixed models also revealed that dairy cattle had greater odds of infection than beef cattle did for both bTB (OR = 6.01, 95% CI: 1.4, 25.9, p = 0.017) and brucellosis (OR = 8.11, 95% CI: 1.7, 38.1, p = 0.008) at the herd level. The herd size did not significantly affect disease incidence. These results highlight the critical need for focused intervention tactics, strengthened biosecurity protocols, and enhanced surveillance programs to protect public health and improve animal welfare.
Physical anthropology. Somatology, Veterinary medicine
Marina A. Negasheva, Olga A. Kuznetsova, Ainur A. Khafizova
et al.
Abstract Background Body mass index (BMI) is a key indicator of population health and often shifts alongside socio-economic change. Few studies have tracked these dynamics over long periods in transitional economies. Russia’s late-twentieth-century transformations offer a rare opportunity to examine such links. This study develops and validates a time-series model of BMI in 19 years old, relating changes in socio-economic and demographic indicators to BMI trends and producing scenario-based forecasts. Materials and methods We analyzed national time-series data published by the NCD Risk Factor Collaboration for 1975–2016 (males and females, age 19), along with indicators of urbanization, fertility, infant and all-cause mortality, life expectancy, and nutritional proxies (protein supply, animal-source calories, meat). Predictors were standardized. Per sex, we estimated the following: (i) first-difference OLS, (ii) dynamic regressions with a lagged BMI term (ARDL(1,0)), and (iii) smooth-trend models with a natural cubic spline in year. Diagnostics included augmented Dickey–Fuller and Durbin–Watson tests. Model selection triangulated elastic net, partial least squares, and stepwise regression. Rolling-origin one-step-ahead forecasts used only information available at time t; bootstrap resampling assessed sign stability. Results Across specifications, the urbanization share was the most robust correlate of BMI. For males, higher urbanization was consistently and inversely associated with BMI; for females, the association was small and model sensitive (frequently negative but not uniformly significant). Effects of life expectancy and mortality attenuated and often lost significance once smooth time structure was included, indicating shared long-run movement rather than distinct short-run covariation; infant mortality added little independent signal. Nutrition proxies contributed limited, non-robust information. ARDL(1,0) one-step-ahead forecasts outperformed random-walk and trend-only baselines. Under a baseline scenario (continuation of recent socio-economic patterns), projected BMI in 2050 is approximately 26.6 kg/m2 (males) and 26.7 kg/m2 (females). Forecasts use only information available at time t (lagged predictors/nowcasts) and are conditional on assumed exogenous trajectories; longer-horizon projections are scenario based rather than unconditional. Conclusions After explicit treatment of nonstationarity, macrodemographic structure, especially urbanization, shows the most consistent links to BMI at age 19, whereas national-scale nutrition proxies are weak at this grain. Findings are descriptive, not causal; forecasts should be interpreted with caution. Incorporating finer-grained behavioral, dietary, and environmental data will help clarify mechanisms and improve long-term forecasting.
Edgar Dubourg, Valentin Thouzeau, Quentin Borredon
et al.
We present a comprehensive analysis of the rise of fictions across human narratives, using large-scale datasets that collectively span over 65,000 works across various media (movies, literary works), cultures (over 30 countries, Western and non-Western), and time periods (2000 BCE to 2020 CE). We measured fictiveness – defined as the degree of departure from reality – across three narrative dimensions: protagonists, events, and settings. We used automatic annotations from large language models (LLMs) to systematically score fictiveness and ensured the robustness and validity of our measure, specifically by demonstrating predictable variations in fictiveness across different genres, in all media. Statistical analyses of the changes in fictiveness over time revealed a steady increase, culminating in the 20th and 21st centuries, across all narrative forms. Remarkably, this trend is also evident in our data spanning ancient times: fictiveness increased gradually in narratives dating back as far as 2000 BCE, with notable peaks of fictiveness during affluent periods such as the heights of the Roman Empire, the Tang Dynasty, and the European Renaissance. We explore potential psychological explanations for the rise in fictiveness, including changing audience preferences driven by ecological and social changes.
Joshua Dimasaka, Christian Geiß, Robert Muir-Wood
et al.
In the aftermath of disasters, many institutions worldwide face challenges in continually monitoring changes in disaster risk, limiting the ability of key decision-makers to assess progress towards the UN Sendai Framework for Disaster Risk Reduction 2015-2030. While numerous efforts have substantially advanced the large-scale modeling of hazard and exposure through Earth observation and data-driven methods, progress remains limited in modeling another equally important yet challenging element of the risk equation: physical vulnerability. To address this gap, we introduce Graph Categorical Structured Variational Autoencoder (GraphCSVAE), a novel probabilistic data-driven framework for modeling physical vulnerability by integrating deep learning, graph representation, and categorical probabilistic inference, using time-series satellite-derived datasets and prior expert belief systems. We introduce a weakly supervised first-order transition matrix that reflects the changes in the spatiotemporal distribution of physical vulnerability in two disaster-stricken and socioeconomically disadvantaged areas: (1) the cyclone-impacted coastal Khurushkul community in Bangladesh and (2) the mudslide-affected city of Freetown in Sierra Leone. Our work reveals post-disaster regional dynamics in physical vulnerability, offering valuable insights into localized spatiotemporal auditing and sustainable strategies for post-disaster risk reduction.
Dimitra Tseneklidou, Alejandro Torres-Forne, Pablo Cerda-Duran
The study of the gravitational wave signatures of neutron star oscillations may provide important information of their interior structure and Equation of State (EoS) at high densities. We present a novel technique based on physically informed neural networks (PINNs) to solve the eigenvalue problem associated with normal oscillation modes of neutron stars. The procedure is tested in a simplified scenario, with an analytical solution, that can be used to test the performance and the accuracy of the method. We show that it is possible to get accurate results of both the eigenfrequencies and the eigenfunctions with this scheme. The flexibility of the method and its capability of adapting to complex scenarios may serve in the future as a path to include more physics into these systems.
Coste San Giacomo (CSG) represents a significant paleontological site to investigate the faunal and environmental changes that occurred in Mediterranean Europe during the Early Pleistocene. In this work, we described for the first time the Carnivoran assemblage. We ascribed the fossil remains to the following taxa: <i>Ursus</i> sp., <i>Homotherium latidens</i>, <i>Canis etruscus</i>, <i>Pliocrocuta perrieri</i>, <i>Martellictis ardea</i> and <i>Vulpes alopecoides</i>. Considering the value of the carnivoran taxa here identified, we discuss their particular biochronological significance, since the CSG site records the last occurrence of <i>P. perrieri</i> and the first occurrences of <i>H. latidens</i>, <i>C. etruscus</i>, <i>M. ardea</i> and <i>V. alopecoides</i> for the Italian Peninsula. These results will allow us to improve the data of the biochronological scheme of the Villafranchian European Land Mammal Age, recognizing the earliest dispersals and latest occurrences across Europe.
Ekaterina Taldenkova, Yaroslav Ovsepyan, Olga Rudenko
et al.
Reconstructing interglacial marine environments helps us understand the climate change mechanisms of the past. To contribute to this body of knowledge, we studied a high-resolution 455 cm-thick sediment sequence of the Boreal (Eemian) marine beds directly overlying Moscovian (Saalian) moraine in the Bychye-2 section on the Pyoza River. We analyzed lithological and microfossil (foraminifers, ostracods, pollen, aquatic palynomorphs) variations at the studied site. Stratigraphical zonation is based on the local and well-established regional pollen zones, correlated with the western European pollen zones. The studied marine beds accumulated from the end of the Moscovian glacial (>131 ka) until ca. 119.5 ka. We distinguished three successive phases: a seasonally sea-ice-covered, relatively deep, freshened basin in the initial rapid flooding stage (>131–130.5 ka); a deep basin in the maximum flooding phase with less extensive sea ice cover (130.5–130.25 ka); and a shallow basin with reduced sea ice cover (130.25–119.5 ka). According to a pollen zone comparison with other sites, the regional glacioisostatic rebound started ca. 130 ka. The diverse warm-water assemblages of benthic foraminifers and ostracods containing typical Baltic Sea species occurred during the regression, mainly 128–124 ka, thus giving evidence for a relatively long-lasting connection between the White and Baltic Seas.
Oliver Niggemann, Gautam Biswas, Alexander Diedrich
et al.
The workshop 'AI-based Planning for Cyber-Physical Systems', which took place on February 26, 2024, as part of the 38th Annual AAAI Conference on Artificial Intelligence in Vancouver, Canada, brought together researchers to discuss recent advances in AI planning methods for Cyber-Physical Systems (CPS). CPS pose a major challenge due to their complexity and data-intensive nature, which often exceeds the capabilities of traditional planning algorithms. The workshop highlighted new approaches such as neuro-symbolic architectures, large language models (LLMs), deep reinforcement learning and advances in symbolic planning. These techniques are promising when it comes to managing the complexity of CPS and have potential for real-world applications.
Jaime Rivera-Solís, Adolfo Quesada-Román, Fran Domazetović
Tropical coastal karst areas represent dynamic, fragile, and biodiverse environments. Central America’s karst regions have been scarcely studied, with most of the research focused on the northern part of the region and on several larger cave systems. The coastal carbonate zones of the Central American region represent a unique karstic landscape, which, so far, has been insufficiently studied. Therefore, in this paper, we aim to describe the (i) landscape geomorphology and (ii) chemical conditions that define Ciénega de El Mangle in Panama as a distinctive karstic site. Carried geomorphological mapping and the characterization of karstic features have resulted in the identification of the different karstic forms and processes that are present within this unique karstic area. Considering that the chosen karstic study area is located in a marine–coastal fringe on the periphery of a lagoon, it is affected by a combination of several factors and processes, including seawater intrusion (through sinkholes), the formation of conchiferous limestone (CaCO<sub>3</sub>), and NaCl precipitation related to efflorescence. Due to the seasonally humid tropical climate, the chemical weathering processes are intense, thus forming alkaline soils that are hindering the development of mangrove vegetation. The geomorphology of the area results from intense evaporation combined with an influx of brackish groundwater, due to which a landscape has evolved in the marine–coastal strips, of seasonal tropical climates, that exhibit saline beaches, known as a littoral shott. In total, 24 karstic microdolines have evolved within the shott, of which six represent domical geoforms formed by gradual evaporitic precipitation, while seven other geoforms represent active karstic sinkholes filled with brackish water. These results are key for understanding the past and present climate interactions and conditions that have led to the formation of tropical karst environments.
Sonali Patnaik, Lopamudra Nayak, Priyanka Sadangi
et al.
In this work, we investigate angular observables such as the longitudinal polarization of charged leptons, $τ$-polarization, and forward-backward asymmetry in semileptonic $B_c$ decays. Additionally, we provide predictions for lepton flavor violating observables, the $\mathcal{R}$ ratios in the decay channels $B_c \rightarrow η_c (J/ψ) l ν_l$ and $B_c \rightarrow D (D^*) l ν_l$ across the entire $q^2$ region. Our analysis is conducted within the Relativistic Independent Quark Model, focusing on the potential model-dependent aspects of these observables. We compare our model predictions with existing lattice predictions, highlighting the strong applicability of our framework in describing $B_c$ decays. Considering the forthcoming experimental upgrades and the Run 3 data results on $B_c$ meson decays, rapid confirmation of these quantities could indicate significant discoveries of physics beyond the Standard Model. This will open up new avenues for understanding the complex flavor dynamics in heavy meson decays.
Alejandro Sainz-Agost, Fernando Falo, Alessandro Fiasconaro
Polymer translocation has long been a topic of interest in the field of biological physics given its relevance in both biological (protein and DNA/RNA translocation through nuclear and cell membranes) and technological processes (nanopore DNA sequencing, drug delivery). In this work, we simulate the translocation of a semiflexible homopolymer through an extended pore, driven by both a constant and a time-dependent end-pulled force, employing a model introduced in previous studies. The time dependence is simplistically modeled as a cosine function, and we distinguish between two scenarios for the driving -- longitudinal force and transversal force -- depending on the relative orientation of the force, parallel or perpendicular respectively, with respect to the pore axis. Beside some key differences between the two drivings, the mean translocation times present a large minimum region as function of the frequency of the force that is typical of the Resonant Activation effect. The presence of the minimum is independent on the elastic characteristics of the polymeric chains and reveals a linear relation between the optimum mean translocation time and the corresponding period of the driving. The mean translocation times show different scaling exponent with the polymer length for different flexibilities. Lastly, we derive an analytical expression of the mean translocation time for low driving frequency, which clearly agrees with the simulations.
Maryam Zarkesh, Kimia Tabaei, Mahdi Akbarzadeh
et al.
Abstract Background Peroxisome proliferator-activated receptor gamma (PPARγ) is a promising therapeutic molecule. Epigenetic mechanisms, including non-coding RNAs, regulate the expression level of the PPARγ gene. Objective We aimed to examine the PPARγ expression in non-diabetic individuals in four body mass index (BMI) categories and its association with miR-34a and miR-143 expression. Methods Visceral and subcutaneous adipose tissues (VAT and SAT) samples were collected from patients undergoing bariatric or elective open abdominal surgeries. The subjects (mean age: 42±14.8 years) included 18 normal-weight, 19 overweight, 18 obese, and 19 morbidly obese individuals. The RNAs levels were determined by quantitative real-time PCR. Results The PPARγ expression was significantly upregulated in both adipose depots of the morbidly obese subjects compared to the normal group. SAT PPARγ level was significantly increased in the obese group compared to the normal-weight group (P<0.01); this increase was also significant in the SAT of morbidly obese subjects compared to the overweight cases (P=0.02). Differences in the regulation of PPARγ expression in both SAT and VAT were significant between the four groups (P<0.05). While miR-143 was overexpressed in the SAT of obese and morbidly obese individuals compared to the normal-weight group, the pairwise comparison showed no significant difference in the miR-34a expression of SAT between the four BMI groups (P>0.01). After controlling for the confounding factors, the expression of VAT PPARγ was directly associated with the miR-34a level in the normal-weight group (β=0.311, P=0.010). A negative association was observed between the VAT PPARγ expression and miR-34a expression in obese cases (β = − 0.594, P=0.039). Conclusion The results also confirmed the regulatory function of microRNAs in the PPARγ expression and adipogenesis.
Physics-informed Neural Networks (PINNs) often have, in their loss functions, terms based on physical equations and derivatives. In order to evaluate these terms, the output solution is sampled using a distribution of collocation points. However, density-based strategies, in which the number of collocation points over the domain increases throughout the training period, do not scale well to multiple spatial dimensions. To remedy this issue, we present here a curriculum-training-based method for lightweight collocation point distributions during network training. We apply this method to a PINN which recovers a full two-dimensional magnetohydrodynamic (MHD) solution from a partial sample taken from a baseline MHD simulation. We find that the curriculum collocation point strategy leads to a significant decrease in training time and simultaneously enhances the quality of the reconstructed solution.
Abstract This study explores body size in sepiids (Cephalopoda, Sepiidae) on the interspecific scale and provides an overview of their geographical distribution. Results reveal a highly skewed distribution of body size variation for raw values and a nearly normal distribution for log-transformed data. However, normality is not statistically validated due to the overrepresentation of small and large species. The geographical distribution of sepiids reveals five main clusters: Atlantic, Cape Basin, Indian Ocean, Asia-Pacific, and Australian. On average, clusters display more or less the same mean body size pattern except the Cape Basin cluster, which is statistically different from the others (smaller interspecific mean body size). The reasons remain unclear but a phylogenetic effect is suspected as southwest African coastal waters concentrate species from the ‘Hemisepius’ complex which is made up of small species. Sepiids do not obey Bergmann’s rule: species from high latitudes do not tend to be larger than species from low latitudes.
Line-graph (LG) lattices are known for having flat bands (FBs) from the destructive interference of Bloch wavefunctions encoded in pure lattice symmetry. Here, we develop a generic atomic/molecular orbital design principle for FBs in non-LG lattices. Based on linear-combination-of-atomic-orbital (LCAO) theory, we demonstrate that the underlying wavefunction symmetry of FBs in a LG lattice can be transformed into the atomic/molecular orbital symmetry in a non-LG lattice. We illustrate such orbital-designed topological FBs in three 2D non-LG, square, trigonal, and hexagonal lattices, where the designed orbitals faithfully reproduce the corresponding lattice symmetries of checkerboard, Kagome, and diatomic-Kagome lattices, respectively. Interestingly, systematic design of FBs with a high Chern number is also achieved based on the same principle. Fundamentally our theory enriches the FB physics; practically it significantly expands the scope of FB materials, since most materials have multiple atomic/molecular orbitals at each lattice site, rather than a single s orbital mandated in graph theory and generic lattice models.
Efimov physics at $p$-wave unitarity for three equal mass fermions in multiple symmetries interacting via Lennard-Jones potentials is predicted to modify the long range interaction potential energy, but without producing a true Efimov effect. This analysis treats the following total orbital angular momenta and parities, $J^Π=0^{+}, 1^{+}, 1^{-}$ and $2^{-}$, for either three spin-polarized fermions ($\uparrow \uparrow \uparrow $), or two spin-up and one spin-down fermion ($\downarrow \uparrow \uparrow $). Our results for the long range interaction in some of those cases agree with previous work by Werner and Castin and by Blume {\it et al.}, namely in cases where the $s$-wave scattering length goes to infinity. The present results extend those calculated interaction energies to small and intermediate hyperradii comparable to the van der Waals length, and we consider additional unitarity scenarios where the $p$-wave scattering volume approaches infinity. The crucial role of the diagonal hyperradial adiabatic correction term is identified and characterized.
During my attendance at the ‘Transeurasian Millets and Beans, Words and Genes’ conference in Jena (January 2019), Martine Robbeets invited me to comment on the articles that are published in this Special Collection in the journal Evolutionary Human Sciences. My comments are focused on the seven articles that deal with the ‘Farming/Language Dispersal Hypothesis’, one of the key theoretical constructs discussed during the conference. I consider how the hypothesis might aid an understanding of the prehistory and early history of the Transeurasian language family.
The systematic investigation of the ground state and fission properties of even-even actinides and superheavy nuclei with $Z=90-120$ from the two-proton up to two-neutron drip lines with proper assessment of systematic theoretical uncertainties has been performed for the first time in the framework of covariant density functional theory (CDFT). These results provide a necessary theoretical input for the r-process modeling in heavy nuclei and, in particular, for the study of fission recycling. Four state-of-the-art globally tested covariant energy density functionals (CEDFs), namely, DD-PC1, DD-ME2, NL3* and PC-PK1, representing the major classes of the CDFT models are employed in the present study. Ground state deformations, binding energies, two neutron separation energies, $α$-decay $Q_α$ values and half-lives and the heights of fission barriers have been calculated for all these nuclei. Theoretical uncertainties in these physical observables and their evolution as a function of proton and neutron numbers have been quantified and their major sources have been identified. Spherical shell closures at $Z=120$, $N=184$ and $N=258$ and the structure of the single-particle (especially, high-$j$) states in their vicinities as well as nuclear matter properties of employed CEDFs are two major factors contributing into theoretical uncertainties. However, different physical observables are affected in a different way by these two factors. For example, theoretical uncertainties in calculated ground state deformations are affected mostly by former factor, while theoretical uncertainties in fission barriers depend on both of these factors.
Wolfgang Gregor Hollik, Matthias Linster, Mustafa Tabet
Searches for New Physics focus either on the direct production of new particles at colliders or at deviations from known observables at low energies. In order to discover New Physics in precision measurements, both experimental and theoretical uncertainties must be under full control. Laser spectroscopy nowadays offers a tool to measure transition frequencies very precisely. For certain molecular and atomic transitions the experimental technique permits a clean study of possible deviations. Theoretical progress in recent years allows us to compare ab initio calculations with experimental data. We study the impact of a variety of New Physics scenarios on these observables and derive novel constraints on many popular generic Standard Model extensions. As a result, we find that molecular spectroscopy is not competitive with atomic spectroscopy and neutron scattering to probe new electron-nucleus and nucleus-nucleus interactions, respectively. Molecular and atomic spectroscopy give similar bounds on new electron-electron couplings, for which, however, stronger bounds can be derived from the magnetic moment of the electron. In most of the parameter space H_2 molecules give stronger constraints than T_2 or other isotopologues.