bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanochemical active ratchet
Authors: Ryabov Artem , Tasinkevych Mykola 
Published: November 2023

AbstractSelf-propelled nanoparticles moving through liquids offer the possibility of creating advanced applications where such nanoswimmers can operate as artificial molecular-sized motors. Achieving control over the motion of nanoswimmers is a crucial aspect for their reliable functioning. While the directionality of micron-sized swimmers can be controlled with great precision, steering nano-sized active particles poses a real challenge. One of the reasons is the existence of large fluctuations of active velocity at the nanoscale. Here, we describe a mechanism that, in the presence of a ratchet potential, transforms these fluctuations into a net current of active nanoparticles. We demonstrate the effect using a generic model of self-propulsion powered by chemical reactions. The net motion along the easy direction of the ratchet potential arises from the coupling of chemical and mechanical processes and is triggered by a constant, transverse to the ratchet, force. The current magnitude sensitively depends on the amplitude and the periodicity of the ratchet potential and the strength of the transverse force. Our results highlight the importance of thermodynamically consistent modeling of chemical reactions in active matter at the nanoscale and suggest new ways of controlling dynamics in such systems.
Visualization of hydrocarbon chain length and degree of saturation of fatty acids in mouse livers by combining near-infrared hyperspectral imaging and machine learning
Authors: Mori Akino , Umezawa Masakazu , Okubo Kyohei , Kamiya Tomonori , Kamimura Masao , Ohtani Naoko , Soga Kohei 
Published: November 2023

AbstractFatty acids play various physiological roles owing to their diverse structural characteristics, such as hydrocarbon chain length (HCL) and degree of saturation (DS). Although the distribution of fatty acids in biological tissues is associated with lipid metabolism, in situ imaging tools are still lacking for HCL and DS. Here, we introduce a framework of near-infrared (1000–1400 nm) hyperspectral label-free imaging with machine learning analysis of the fatty acid HCL and DS distribution in the liver at each pixel, in addition to the previously reported total lipid content. The training data of 16 typical fatty acids were obtained by gas chromatography from liver samples of mice fed with various diets. A two-dimensional mapping of these two parameters was successfully performed. Furthermore, the HCL/DS plot exhibited characteristic clustering among the different diet groups. Visualization of fatty acid distribution would provide insights for revealing the pathophysiological conditions of liver diseases and metabolism.
A machine learning method to process voice samples for identification of Parkinson’s disease
Authors: Iyer Anu , Kemp Aaron , Rahmatallah Yasir , Pillai Lakshmi , Glover Aliyah , Prior Fred , Larson-Prior Linda , Virmani Tuhin 
Published: November 2023

AbstractMachine learning approaches have been used for the automatic detection of Parkinson’s disease with voice recordings being the most used data type due to the simple and non-invasive nature of acquiring such data. Although voice recordings captured via telephone or mobile devices allow much easier and wider access for data collection, current conflicting performance results limit their clinical applicability. This study has two novel contributions. First, we show the reliability of personal telephone-collected voice recordings of the sustained vowel /a/ in natural settings by collecting samples from 50 people with specialist-diagnosed Parkinson’s disease and 50 healthy controls and applying machine learning classification with voice features related to phonation. Second, we utilize a novel application of a pre-trained convolutional neural network (Inception V3) with transfer learning to analyze the spectrograms of the sustained vowel from these samples. This approach considers speech intensity estimates across time and frequency scales rather than collapsing measurements across time. We show the superiority of our deep learning model for the task of classifying people with Parkinson’s disease as distinct from healthy controls.
Electricity consumption in Finland influenced by climate effects of energetic particle precipitation
Authors: Juntunen Veera , Asikainen Timo 
Published: November 2023

AbstractIt is known that electricity consumption in many cold Northern countries depends greatly on prevailing outdoor temperatures especially during the winter season. On the other hand, recent research has demonstrated that solar wind driven energetic particle precipitation from space into the polar atmosphere can influence the stratospheric polar vortex and tropospheric weather patterns during winter. These changes are significant, e.g., in Northern Europe, especially in Finland. In this study we demonstrate that geomagnetic activity, as a proxy of energetic particle precipitation, significantly influences Finland’s average temperature and total wintertime electricity consumption in Finland. This influence is only seen when the prevailing equatorial stratospheric winds, so called QBO winds, are easterly. The results demonstrate a previously unrecognized societal influence of space weather, and imply that long-term energy consumption forecasts could potentially be improved by considering long-term space weather predictions.
Quaternary ammonium-based coating of textiles is effective against bacteria and viruses with a low risk to human health
Authors: Meier Philipp , Clement Pietro , Altenried Stefanie , Reina Giacomo , Ren Qun , Züst Roland , Enger Olivier , Choi Francis , Nestle Nikolaus , Deisenroth Ted , Neubauer Peter , Wick Peter 
Published: November 2023

AbstractWhile the global healthcare system is slowly recovering from the COVID-19 pandemic, new multi-drug-resistant pathogens are emerging as the next threat. To tackle these challenges there is a need for safe and sustainable antiviral and antibacterial functionalized materials. Here we develop an 'easy-to-apply' procedure for the surface functionalization of textiles, rendering them antiviral and antibacterial and assessing the performance of these textiles. A metal-free quaternary ammonium-based coating was applied homogeneously and non-covalently to hospital curtains. Abrasion, durability testing, and aging resulted in little change in the performance of the treated textile. Additionally, qualitative and quantitative antibacterial assays on Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumanii revealed excellent antibacterial activity with a CFU reduction of 98–100% within only 4 h of exposure. The treated curtain was aged 6 months before testing. Similarly, the antiviral activity tested according to ISO-18184 with murine hepatitis virus (MHV) showed > 99% viral reduction with the functionalized curtain. Also, the released active compounds of the coating 24 ± 5 µg mL−1 revealed no acute in vitro skin toxicity (IC50: 95 µg mL−1) and skin sensitization. This study emphasizes the potential of safe and sustainable metal-free textile coatings for the rapid antiviral and antibacterial functionalization of textiles.
Biodegradable ether amines for reverse cationic flotation separation of ultrafine quartz from magnetite
Authors: Gouvêa Junior José Tadeu , Chipakwe Vitalis , de Salles Leal Filho Laurindo , Chehreh Chelgani Saeed 
Published: November 2023

AbstractA considerable amount of ultrafine magnetite as the iron source will end up in the tailing dams since the magnetic separation process markedly drops as the particle size. Cationic reverse flotation could be one of the main alternatives for recovering ultrafine magnetite. As a systematic approach, this study explored the flotation efficiency and interaction mechanisms of two biodegradable ether amines (diamine and monoamine) to separate ultrafine quartz from magnetite (− 20 µm). Several assessments (single and mixed mineral flotation, zeta potential, contact angle, surface tension measurement, turbidity, and Fourier transform infrared) were conducted to explore the efficiency of the process and the interaction mechanisms. Results indicated that ether diamine and monoamine could highly float ultrafine quartz particles (95.9 and 97.7%, respectively) and efficiently separate them from ultrafine magnetite particles. Turbidity assessments highlighted that these cationic collectors could aggregate magnetite particles (potentially hydrophobic coagulation) and enhance their depression. Surface analyses revealed that the collector mainly adsorbed on the quartz particles, while it was essentially a weak interaction on magnetite.
Methodological pipeline for monitoring post-harvest quality of leafy vegetables
Authors: Tonto T. C. , Cimini S. , Grasso S. , Zompanti A. , Santonico M. , De Gara L. , Locato V. 
Published: November 2023

AbstractPlants are primary source of nutrients for humans. However, the nutritional value of vegetables tends to decrease once organ and tissue sinks are detached from the plant. Minimal processing of leafy vegetables involves cutting and washing before packaging and storage. These processing procedures result in stressful conditions and post-harvest disorders senescence-related can also occur. The aim of this work is to define a methodological pipeline to evaluate the “quality” changes of fresh cut leafy vegetables over their shelf-life. At this purpose, intra-species variability has been investigated considering two varieties of Lactuca sativa (var. longifolia and capitata), showing different susceptibility to browning. Since browning mainly depends on phenol oxidation, redox parameters as well as the activity of the enzymes involved in phenol biosynthesis and oxidation have been monitored over storage time. At the same time, the metabolic changes of the lettuce leaves have been estimated as response patterns to chemical sensors. The obtained sensor outputs were predictive of browning-related biological features in a cultivar-dependent manner. The integration of the results obtained by this multivariate methodological approach allowed the identification of the most appropriate quality markers in lettuce leaves from different varieties. This methodological pipeline is proposed for the identification and subsequent monitoring of post-harvest quality of leafy vegetables.
A three-dimensional model with two-body interactions for endothelial cells in angiogenesis
Authors: Sakai Kazuma , Hayashi Tatsuya , Sakai Yusuke , Mada Jun , Tonami Kazuo , Uchijima Yasunobu , Kurihara Hiroki , Tokihiro Tetsuji 
Published: November 2023

AbstractWe introduce a three-dimensional mathematical model for the dynamics of vascular endothelial cells during sprouting angiogenesis. Angiogenesis is the biological process by which new blood vessels form from existing ones. It has been the subject of numerous theoretical models. These models have successfully replicated various aspects of angiogenesis. Recent studies using particle-based models have highlighted the significant influence of cell shape on network formation, with elongated cells contributing to the formation of branching structures. While most mathematical models are two-dimensional, we aim to investigate whether ellipsoids also form branch-like structures and how their shape affects the pattern. In our model, the shape of a vascular endothelial cell is represented as a spheroid, and a discrete dynamical system is constructed based on the simple assumption of two-body interactions. Numerical simulations demonstrate that our model reproduces the patterns of elongation and branching observed in the early stages of angiogenesis. We show that the pattern formation of the cell population is strongly dependent on the cell shape. Finally, we demonstrate that our current mathematical model reproduces the cell behaviours, specifically cell-mixing, observed in sprouts.
Psychological disturbances encountered by selected undergraduates studying at the University of Ruhuna, Sri Lanka during the Covid-19 pandemic: a cross-sectional study
Authors: Kaushani T. H. M. , Weeratunga E. B. 
Published: November 2023

AbstractUniversity undergraduates are increasingly recognized as a vulnerable population with a higher level of psychological disturbances. During the Covid-19 pandemic, universities closed all over the world, resulting in the psychological well-being of this population being severely affected across the globe. This study examined the prevalence of stress, anxiety, and depressive symptoms encountered by undergraduates of the selected five faculties at the University of Ruhuna in Southern Sri Lanka due to the Covid-19 pandemic, its associated factors, and the correlations between stress, anxiety, and depressive symptoms. An online, cross-sectional, descriptive study was conducted among undergraduates using pre-tested, self-administered questionnaires from the randomly selected five faculties: Allied Health Sciences, Engineering, Humanities and Social Sciences, Management and Finance, and Medicine. Undergraduates were invited to complete the Google Form. Socio-demographic details and a 21-item Depression, Anxiety, and Stress Scale (21-DASS) were used for data collection. Stress, anxiety, and depressive symptoms were evaluated using a Sinhala version of the 21-DASS scale. Ethical permission was granted by the Ethics Review Committee of the Faculty of Allied Health Sciences, University of Ruhuna. Among the 359 undergraduates, the majority were represented by females (62.1%). The mean age of the sample was 23.67 years (SD ± 1.6). Stress, anxiety, and depressive symptoms were found to be prevalent in 53.7%, 41.8%, and 63.8% of undergraduates respectively. Younger and female undergraduates had more impact on psychological issues than their counterparts. It revealed a significant positive correlation between anxiety and depressive symptoms (r = 0.646, p < .001), anxiety and stress (r = 0.868, p < .001), and stress and anxiety (r = 0.786, p < .001). Most undergraduates experienced considerable levels of stress, anxiety, and depressive symptoms during the Covid-19 as increasing stress, anxiety, or depressive symptoms, tend to increase all types of psychological disturbances. The development of mental health among undergraduates is essential and needs innovative strategies to improve the psychological well-being of undergraduates. The initiation of a stress management programme and expanded available counseling services are also important. Further studies are needed to be conducted on the extended topic of how the Covid-19 era is affecting the psychological well-being of undergraduates from different universities (state/non-state), locations, and different study departments.
Effects of temperature and humidity on cerebrovascular disease hospitalization in a super-aging society
Authors: Doi Shunichi , Yoneyama Kihei , Yoshida Toshiya , Kawagoe Yasuhito , Nakai Michikazu , Sumita Yoko , Ishibashi Yuki , Izumo Masaki , Tanabe Yasuhiro , Harada Tomoo , Akashi Yoshihiro J. 
Published: November 2023

AbstractWeather conditions influence the incidence of cardiovascular disease. However, few studies have investigated the association between weather temperature and humidity and cerebrovascular disease hospitalizations in a super-aging society. We included 606,807 consecutive patients with cerebrovascular disease admitted to Japanese acute-care hospitals between 2015 and 2019. The primary outcome was the number of cerebrovascular disease hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of mean temperature and humidity, 1 day before hospital admission, with cerebrovascular disease hospitalizations, after adjusting for air pollution, hospital, and patient demographics. Lower mean temperatures and humidity < 70% or humidity ≧ 70% are associated with an increased incidence of cerebrovascular disease hospitalization (coefficient, − 1.442 [− 1.473 to − 1.411] per °C, p < 0.001, coefficient, − 0.084 [− 0.112 to − 0.056] per%, p < 0.001, and coefficient, 0.136 [0.103 to 0.168] per %, p < 0.001, respectively). Lower mean temperatures and extremely lower or higher humidity are associated with an increased incidence of cerebrovascular disease hospitalization in a super-aging society.
The PREMISE database of 20 Macaca fascicularis PET/MRI brain images available for research
Authors: Chalet Lucie , Debatisse Justine , Wateau Oceane , Boutelier Timothe , Wiart Marlène , Costes Nicolas , Mérida Inés , Redouté Jérôme , Langlois Jean-Baptiste , Lancelot Sophie , Léon Christelle , Cho Tae-Hee , Mechtouff Laura , Eker Omer Faruk , Nighoghossian Norbert , Canet-Soulas Emmanuelle , Becker Guillaume 
Published: November 2023

AbstractNon-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [15O]H2O and [11C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository.
Surveys of clumps, cores, and condensations in Cygnus-X
Authors: Yang Kai , Qiu Keping , Pan Xing 
Published: November 2023

Context. The SiO emissions are usually used to trace high-velocity outflow shocks in star-forming regions. However, several studies have found low-velocity and widespread SiO emissions not associated with outflows in molecular clouds.Aims. We aim to detect and characterize the SiO emissions in massive dense cores (MDCs), and explore the properties of the central sources of SiO emission.Methods. We present high-angular-resolution (~1.5″) observations of the SiO (5−4) line made with the Submillimeter Array towards a sample of 48 MDCs in the Cygnus-X star-forming complex. We studied the SiO emission structures, including their morphologies, kinematics, and energetics, and investigated their relationship with the evolution of the central sources.Results. The SiO (5−4) emission is detected in 16 out of 48 MDCs. We identify 14 bipolar and 18 unipolar SiO (5−4) outflows associated with 29 dust condensations. Most outflows (24 out of 32) are associated with excessSpitzer4.5 μm emissions. We also find diffuse low-velocity (Δv≤ 1.2 km s−1) SiO (5−4) emission closely surrounding the dust condensations in two MDCs, and suggest that it may originate from decelerated outflow shocks or large-scale shocks from global cloud collapse.Conclusions. We find that the SMA SiO (5−4) emission in MDCs is mostly associated with outflows. Probably due to the relatively high excitation of SiO (5−4) compared to SiO (2−1) and due to the spatial filtering effect, we do not detect large-scale low-velocity SiO (5−4) emission, but detect more compact low-velocity emission in close proximity to the dust condensations. We group the sources into different evolutionary stages based on the infrared emission, radio continuum emission, and gas temperature properties of the outflow central sources, and find that the 24 μm luminosity tends to increase with evolution.
Repeating flaring activity of the blazar AO 0235+164
Authors: Escudero Pedrosa J. , Agudo I. , Tramacere A. , Marscher A. P. , Jorstad S. , Weaver Z. R. , Casadio C. , Thum C. , Myserlis I. , Fuentes A. , Traianou E. , Kim J.-Y. , Kramer J. , López-Coto R. , D’Ammando F. , Bernardos M. , Bonnoli G. , Blinov D. A. , Borman G. A. , Grishina T. S. , Hagen-Thorn V. A. , Kopatskaya E. N. , Larionova E. G. , Larionov V. M. , Larionova L. V. , Morozova D. A. , Savchenko S. S. , Troitskiy I. S. , Troitskaya Y. V. , Vasilyev A. A. 
Published: November 2023

Context. Blazar AO 0235+164, located at a redshift of z = 0.94, has undergone several sharp multi-spectral-range flaring episodes over recent decades. In particular, the episodes that peaked in 2008 and 2015, which were subject to extensive multi-wavelength coverage, exhibited an interesting behavior.
Aims. We study the actual origin of these two observed flares by constraining the properties of the observed photo-polarimetric variability as well as of the broadband spectral energy distribution and the observed time-evolution behavior of the source. We use ultra-high-resolution total-flux and polarimetric very-long-baseline interferometry (VLBI) imaging.
Methods. The analysis of VLBI images allowed us to constrain kinematic and geometrical parameters of the 7 mm jet. We used the discrete correlation function to compute the statistical correlation and the delays between emission at different spectral ranges. The multi-epoch modeling of the spectral energy distributions allowed us to propose specific models of the emission; in particular, with the aim to model the unusual spectral features observed in this source in the X-ray region of the spectrum during strong multi spectral-range flares.
Results. We find that these X-ray spectral features can be explained by an emission component originating in a separate particle distribution than the one responsible for the two standard blazar bumps. This is in agreement with the results of our correlation analysis, where we did not find a strong correlation between the X-ray and the remaining spectral ranges. We find that both external Compton-dominated and synchrotron self-Compton-dominated models are able to explain the observed spectral energy distributions. However, the synchrotron self-Compton models are strongly favored by the delays and geometrical parameters inferred from the observations.