bluuebunny/crossref_metadata_2025_split huggingface dataset:
The potential distribution of Bacillus anthracis suitability across Uganda using INLA
Authors: Ndolo V. A. , Redding D. , Deka M. A. , Salzer J. S. , Vieira A. R. , Onyuth H. , Ocaido M. , Tweyongyere R. , Azuba R. , Monje F. , Ario A. R. , Kabwama S. , Kisaakye E. , Bulage L. , Kwesiga B. , Ntono V. , Harris J. , Wood J. L. N. , Conlan A. J. K. 
Published: November 2022

AbstractTo reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0–0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140–190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.
A comparative study of interfacial thermal conductance between metal and semiconductor
Authors: Wu Kongping , Zhang Leng , Wang Danbei , Li Fangzhen , Zhang Pengzhan , Sang Liwen , Liao Meiyong , Tang Kun , Ye Jiandong , Gu Shulin 
Published: November 2022

AbstractTo understand and control thermal conductance of interface between metal and semiconductor has now become a crucial task for the thermal design and management of nano-electronic and micro-electronic devices. The interfacial alignments and electronic characteristics of the interfaces between metal and semiconductor are studied using a first-principles calculation based on hybrid density functional theory. The thermal conductance of interfaces between metal and semiconductor were calculated and analyzed using diffuse mismatch model, acoustic mismatch model and nonequilibrium molecular dynamics methods. Especially, according to nonequilibrium molecular dynamics, the values of thermal conductance were obtained to be 32.55 MW m−2 K−1 and 341.87 MW m−2 K−1 at C–Cu and Si–Cu interfaces, respectively. These results of theoretical simulation calculations are basically consistent with the current experimental data, which indicates that phonon–phonon interaction play a more important role than electron–phonon interaction during heat transport. It may be effective way to improve the interfacial thermal conductance through enhancing the interface coupling strength at the metal–semiconductor interface because the strong interfacial scattering plays a role in suppressing in the weaker interface coupling heterostructure, leading to the lower thermal conductance of interfaces. This could provide a beneficial reference for the design of the Schottky diode and thermal management at the interfaces between metal and semiconductor.
GediNET for discovering gene associations across diseases using knowledge based machine learning approach
Authors: Qumsiyeh Emma , Showe Louise , Yousef Malik 
Published: November 2022

AbstractThe most common approaches to discovering genes associated with specific diseases are based on machine learning and use a variety of feature selection techniques to identify significant genes that can serve as biomarkers for a given disease. More recently, the integration in this process of prior knowledge-based approaches has shown significant promise in the discovery of new biomarkers with potential translational applications. In this study, we developed a novel approach, GediNET, that integrates prior biological knowledge to gene Groups that are shown to be associated with a specific disease such as a cancer. The novelty of GediNET is that it then also allows the discovery of significant associations between that specific disease and other diseases. The initial step in this process involves the identification of gene Groups. The Groups are then subjected to a Scoring component to identify the top performing classification Groups. The top-ranked gene Groups are then used to train a Machine Learning Model. The process of Grouping, Scoring and Modelling (G-S-M) is used by GediNET to identify other diseases that are similarly associated with this signature. GediNET identifies these relationships through Disease–Disease Association (DDA) based machine learning. DDA explores novel associations between diseases and identifies relationships which could be used to further improve approaches to diagnosis, prognosis, and treatment. The GediNET KNIME workflow can be downloaded from: https://github.com/malikyousef/GediNET.git or https://kni.me/w/3kH1SQV_mMUsMTS.
Improving the accuracy of estimates of the pulse sequence period using the methodology of complete sufficient statistics
Authors: Zhuchkov Konstantin , Vasilchenko Mikhail , Zagrebneva Anna , Zavyalov Alexey 
Published: November 2022

AbstractThis paper is devoted to the synthesis of new signal processing algorithms based on the methodology of complete sufficient statistics and the possibility of using the Lehmann–Scheffe theorem. Using the example of a sequence of quasi-rectangular pulses, an approach to estimating their period was illustrated, taking into account the duty-off factor and the pulse squareness coefficient. A mathematical model was developed, on the basis of which, estimates of the potential accuracy of the methods were carried out. It is established that for the sample size value (n > 8), the relative root-mean-square error of estimating the repetition period using the methodology of complete sufficient statistics is lower than that of the traditional estimate. In addition to theoretical calculations, simulation results confirming the achieved effect are presented. The results obtained have a wide range of applicability and can be used in the design of control and measuring equipment in the oil and gas industry, in the development of medical equipment, in the field of telecommunications, in the design of pulse-Doppler radars, etc.
A meta-analysis of effects of vitamin E supplementation alone and in combination with omega-3 or magnesium on polycystic ovary syndrome
Authors: Heidari Hajar , Hajhashemy Zahra , Saneei Parvane 
Published: November 2022

AbstractVitamin E supplementation might have favorable effects on risk factors of polycystic ovary syndrome (PCOS). This systematic review and meta-analysis aimed to summarize the effects of vitamin E supplementation or vitamin E in combination with omega-3 or magnesium on PCOS. PubMed, Scopus, ISI Web of Science, Cochrane, Embase electronic databases, and Google scholar were searched for all available articles up to September 2022. Randomized controlled trials (RCTs) that examined the effect of vitamin E supplementation or vitamin E in combination with omega-3 or magnesium on lipid and glycemic profiles, anthropometric measurements, biomarkers of inflammation and oxidative stress, hormonal profile, and hirsutism score in patients with PCOS were included. Ten RCTs (with 504 participants) fulfilled the eligible criteria. Vitamin E supplementation or vitamin E in combination with omega-3 or magnesium in comparison to placebo could significantly reduce serum levels of TG (weighted mean difference: − 18.27 mg/dL, 95% CI − 34.68 to − 1.87), VLDL (− 5.88 mg/dL, 95% CI − 8.08 to − 3.68), LDL-c (− 12.84 mg/dL, 95% CI − 22.15 to − 3.52), TC (− 16.30 mg/dL, 95% CI − 29.74 to − 2.86), TC/HDL-c ratio (− 0.52, 95% CI − 0.87 to − 0.18), hs-CRP (− 0.60 ng/mL, 95% CI − 0.77 to − 0.44), hirsutism score (− 0.33, 95% CI − 0.65 to − 0.02) and significantly increase nitric oxide levels (2.79 µmol/L, 95% CI 0.79–4.79). No significant effect was found on HDL-c, glycemic indices, hormonal profile, anthropometric measurements, and other biomarkers of inflammation or oxidative stress. This meta-analysis highlights the potential anti-hyperlipidemic, anti-oxidant, and anti-inflammatory properties of vitamin E supplementation alone or in combination with omega-3 or magnesium on PCOS patients.
Identifying a suitable model for predicting hourly pollutant concentrations by using low-cost microstation data and machine learning
Authors: Yang Rongjin , Yin Lizeyan , Hao Xuejie , Liu Lu , Wang Chen , Li Xiuhong , Liu Qiang 
Published: November 2022

AbstractAccurately predicting the concentration of PM2.5 (fine particles with a diameter of 2.5 μm or less) is essential for health risk assessment and formulation of air pollution control strategies. At present, there is also a large amount of air pollution data. How to efficiently mine its hidden features to obtain the future concentration of pollutants is very important for the prevention and control of air pollution. Therefore we build a pollutant prediction model based on Lightweight Gradient Boosting Model (LightGBM) shallow machine learning and Long Short-Term Memory (LSTM) neural network. Firstly, the PM2.5 pollutant concentration data of 34 air quality stations in Beijing and the data of 18 weather stations were matched in time and space to obtain an input data set. Subsequently, the input data set was cleaned and preprocessed, and the training set was obtained by methods such as input feature extraction, input factor normalization, and data outlier processing. The hourly PM2.5 concentration value prediction was achieved in accordance with experiments conducted with the hourly PM2.5 data of Beijing from January 1, 2018 to October 1, 2020. Ultimately, the optimal hourly series prediction results were obtained after model comparisons. Through the comparison of these two models, it is found that the RMSE predicted by LSTM model for each pollutant is nearly 50% lower than that of LightGBM, and is more consistent with the fitting curve between the actual observations. The exploration of the input step size of LSTM model found that the accuracy of 3-h input data was higher than that of 12-h input data. It can be used for the management and decision-making of environmental protection departments and the formulation of preventive measures for emergency pollution incidents.
Doping-dependent superconducting physical quantities of K-doped BaFe$$_2$$As$$_2$$ obtained through infrared spectroscopy
Authors: Lee Seokbae , Seo Yu-Seong , Roh Seulki , Song Dongjoon , Eisaki Hiroshi , Hwang Jungseek 
Published: November 2022

AbstractWe investigated four single crystals of K-doped BaFe$$_2$$

2

As$$_2$$

2

(Ba-122), Ba$$_{1-x}$$

1
-
x

K$$_x$$

x

Fe$$_2$$

2

As$$_2$$

2

with $$x =$$

x
=

0.29, 0.36, 0.40, and 0.51, using infrared spectroscopy. We explored a wide variety of doping levels, from under- to overdoped. We obtained the superfluid plasma frequencies ($$\Omega _{\textrm{sp}}$$

Ω
sp

) and corresponding London penetration depths ($$\uplambda _{\textrm{L}}$$

λ
L

) from the measured optical conductivity spectra. We also extracted the electron-boson spectral density (EBSD) functions using a two-parallel charge transport channel approach in the superconducting (SC) state. From the extracted EBSD functions, the maximum SC transition temperatures ($$T_c^{\textrm{Max}}$$

T
c
Max

) were determined using a generalized McMillan formula and the SC coherence lengths ($$\xi _{\textrm{SC}}$$

ξ
SC

) were calculated using the timescales encoded in the EBSD functions and reported Fermi velocities. We identified some similarities and differences in the doping-dependent SC quantities between the K-doped Ba-122 and the hole-doped cuprates. We expect that the various SC quantities obtained across the wide doping range will provide helpful information for establishing the microscopic pairing mechanism in Fe-pnictide superconductors.
An epidemiological model for mosquito host selection and temperature-dependent transmission of West Nile virus
Authors: Fasano Augusto , Riccetti Nicola , Angelou Anastasia , Gomez-Ramirez Jaime , Ferraccioli Federico , Kioutsioukis Ioannis , Stilianakis Nikolaos I. 
Published: November 2022

AbstractWe extend a previously developed epidemiological model for West Nile virus (WNV) infection in humans in Greece, employing laboratory-confirmed WNV cases and mosquito-specific characteristics of transmission, such as host selection and temperature-dependent transmission of the virus. Host selection was defined by bird host selection and human host selection, the latter accounting only for the fraction of humans that develop symptoms after the virus is acquired. To model the role of temperature on virus transmission, we considered five temperature intervals (≤ 19.25 °C; > 19.25 and < 21.75 °C; ≥ 21.75 and < 24.25 °C; ≥ 24.25 and < 26.75 °C; and > 26.75 °C). The capacity of the new model to fit human cases and the week of first case occurrence was compared with the original model and showed improved performance. The model was also used to infer further quantities of interest, such as the force of infection for different temperatures as well as mosquito and bird abundances. Our results indicate that the inclusion of mosquito-specific characteristics in epidemiological models of mosquito-borne diseases leads to improved modelling capacity.
Wave induced coastal flooding along the southwest coast of India during tropical cyclone Tauktae
Authors: Ramakrishnan Ratheesh , Remya P. G. , Mandal Anup , Mohanty Prakash , Arayakandy Prince , Mahendra R. S. , Nair T. M. Balakrishnan 
Published: November 2022

AbstractThe coastal flood during the tropical cyclone Tauktae, 2021, at Chellanam coast, Kerala, India, has invited wide attention as the wave overtopping severely affected coastal properties and livelihood. We used a combination of WAVEWATCHIII and XBeach to study the coastal inundation during high waves. The effect of low-frequency waves and the rise in the coastal water level due to wave setup caused the inundation at Chellanam, even during low tide with negligible surge height. Wave setup raised the water level at the coast with steep slopes to more than 0.6 m and peaked during low tide, facilitating wave breaking at the nearshore region. The coastal regions adjacent to these steep slopes were subjected to severe inundation. The combined effect of long and short waves over wave setup formed extreme wave runups that flooded inland areas. At gently sloping beaches, the longwave component dominated and overtopped the seawalls and damaged households along the shoreline. The study emphasizes the importance of longwave and wave setup and its interaction with nearshore bathymetry during the high wave. The present study shall lead to the development of a coastal inundation prediction system for the low-lying hot spots using the combination of WAVEWATCHIII and XBeach models.
Selective migration and mortality by economic status in Lolland-Falster, Denmark, 1992–2018
Authors: Holmager Therese Lucia Friis , Lophaven Søren Nymand , Mortensen Laust Hvas , Lynge Elsebeth 
Published: November 2022

AbstractDuring the past 30 years, a mortality gap developed between Lolland-Falster (the rural-provincial southeastern part) and the rest of Denmark. A main driver was selective in-migration of Danes with a high risk of death, especially of working-ages. In the present study, we determined the role of economic status in this selective in-migration. We used individual-level data from the Central Population Register and data on income source; self- or publicly supported. The study population included people aged 30–64 and living in Denmark at any time between 1992 and 2018. Mortality rate ratios (MRR) were calculated using Poisson regression for three time-periods: 1992–1999, 2000–2009 and 2010–2018. Two in five in-migrants to Lolland-Falster were people on public support. In 2010–2018, they had an MRR of 8.71 (95% confidence interval (CI): 8.05–9.42) compared with self-supported people, and an MRR of 1.49 (95% CI: 1.38–1.61) compared with publicly supported people elsewhere in Denmark. In-migration of working-aged people on public support was a main contributor to the excess mortality in Lolland-Falster as compared with the rest of Denmark. To understand urban–rural differences in health, population movements and national income patterns are important to take into account.
Adult sex ratios: causes of variation and implications for animal and human societies
Authors: Schacht Ryan , Beissinger Steven R. , Wedekind Claus , Jennions Michael D. , Geffroy Benjamin , Liker András , Kappeler Peter M. , Weissing Franz J. , Kramer Karen L. , Hesketh Therese , Boissier Jérôme , Uggla Caroline , Hollingshaus Mike , Székely Tamás 
Published: November 2022

AbstractConverging lines of inquiry from across the social and biological sciences target the adult sex ratio (ASR; the proportion of males in the adult population) as a fundamental population-level determinant of behavior. The ASR, which indicates the relative number of potential mates to competitors in a population, frames the selective arena for competition, mate choice, and social interactions. Here we review a growing literature, focusing on methodological developments that sharpen knowledge of the demographic variables underlying ASR variation, experiments that enhance understanding of the consequences of ASR imbalance across societies, and phylogenetic analyses that provide novel insights into social evolution. We additionally highlight areas where research advances are expected to make accelerating contributions across the social sciences, evolutionary biology, and biodiversity conservation.
Defect dynamics in active smectics induced by confining geometry and topology
Authors: Huang Zhi-Feng , Löwen Hartmut , Voigt Axel 
Published: November 2022

AbstractThe persistent dynamics in systems out of equilibrium, particularly those characterized by annihilation and creation of topological defects, is known to involve complicated spatiotemporal processes and is deemed difficult to control. Here the complex dynamics of defects in active smectic layers exposed to strong confinements is explored, through self-propulsion of active particles and a variety of confining geometries with different topology, ranging from circular, flower-shaped epicycloid, to hypocycloid cavities, channels, and rings. We identify a wealth of dynamical behaviors during the evolution of complex spatiotemporal defect patterns as induced by the confining shape and topology, particularly a perpetual creation-annihilation dynamical state at intermediate activity with large fluctuations of topological defects and a controllable transition from oscillatory to damped time correlation of defect number density via mechanisms governed by boundary cusps. Our results are obtained by using an active phase field crystal approach. Possible experimental realizations are also discussed.
The unexpected radiative impact of the Hunga Tonga eruption of 15th January 2022
Authors: Sellitto P. , Podglajen A. , Belhadji R. , Boichu M. , Carboni E. , Cuesta J. , Duchamp C. , Kloss C. , Siddans R. , Bègue N. , Blarel L. , Jegou F. , Khaykin S. , Renard J. -B. , Legras B. 
Published: November 2022

AbstractThe underwater Hunga Tonga-Hunga Ha-apai volcano erupted in the early hours of 15th January 2022, and injected volcanic gases and aerosols to over 50 km altitude. Here we synthesise satellite, ground-based, in situ and radiosonde observations of the eruption to investigate the strength of the stratospheric aerosol and water vapour perturbations in the initial weeks after the eruption and we quantify the net radiative impact across the two species using offline radiative transfer modelling. We find that the Hunga Tonga-Hunga Ha-apai eruption produced the largest global perturbation of stratospheric aerosols since the Pinatubo eruption in 1991 and the largest perturbation of stratospheric water vapour observed in the satellite era. Immediately after the eruption, water vapour radiative cooling dominated the local stratospheric heating/cooling rates, while at the top-of-the-atmosphere and surface, volcanic aerosol cooling dominated the radiative forcing. However, after two weeks, due to dispersion/dilution, water vapour heating started to dominate the top-of-the-atmosphere radiative forcing, leading to a net warming of the climate system.
Correlated petrology and seismicity indicate rapid magma accumulation prior to eruption of Kizimen volcano, Kamchatka
Authors: Ostorero Lea , Balcone-Boissard Hélène , Boudon Georges , Shapiro Nikolai M. , Belousov Alexander , Belousova Marina , Auer Andreas , Senyukov Sergey L. , Droznina Svetlana Ya. 
Published: November 2022

AbstractThe increase in number and intensity of earthquakes during a pre-eruptive crisis is the main basis of seismic volcano monitoring. However, a strong understanding of how these seismic signals relate to magmatic processes in the magma plumbing systems prior to volcanic eruptions is crucial for these efforts. Here we compare the characteristics of a seismo-volcanic crisis prior to the 2010–2013 explosive-extrusive eruption of Kizimen volcano, Kamchatka with the timescales of processes in the magma plumbing system. These timescales are inferred from the numerical modelling of iron-magnesium intracrystalline interdiffusion in 88 zoned orthopyroxene crystals from dacites and silica-rich andesites collected after the eruption. We find that the eruptible magmas were assembled rapidly during a magma mixing process beginning around 1.5 years before the eruption, which is well correlated with the onset of the seismic crisis. We conclude that the observed seismic re-activation marked the onset of magma mixing and led to destabilization of the reservoir, followed by the eruption.