bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailoring elastic and inelastic collisions of relativistic antiferromagnetic domain walls
Authors: Otxoa Rubén M. , Tatara Gen , Roy Pierre E. , Chubykalo-Fesenko Oksana 
Published: November 2023

AbstractSoliton-based computing relies on their unique properties for transporting energy and emerging intact from head-on collisions. Magnetic domain walls are often referred to as solitons disregarding the strict mathematical definition requiring the above scattering property. Here we demonstrate the conditions of elastic and inelastic scattering for spin–orbit torque-induced dynamics of relativistic domain walls on the technologically relevant Mn$$_2$$

2

Au antiferromagnetic material. We show that even domain walls with opposite winding numbers can experience elastic scattering and we present the corresponding phase diagram as a function of the spin–orbit field strength and duration. The elastic collision requires minimum domain walls speed, which we explain assuming an attractive potential created by domain wall pair. On the contrary, when the domain walls move at lower speeds, their collision is inelastic and results in a dispersing breather. Our findings will be important for the development of soliton-based computing using antiferromagnetic spintronics and we discuss their prospects for building NOT and XOR gates.
Undesirable dispersal via a river pathway of a single Argentine ant supercolony newly invading an inland urban area of Japan
Authors: Hayasaka Daisuke , Kato Kenshin , Hiraiwa Masayoshi K. , Kasai Hiro , Osaki Kazutaka , Aoki Retsushi , Sawahata Takuo 
Published: November 2023

AbstractInvasive ants pose a risk to human well-being and social/ecosystem stability. Linepithema humile Mayr is among the most damaging invasive ants worldwide. Most L. humile populations invade ports/wharfs isolated from surrounding landscapes, but unfortunately, a new population was discovered in an inland urban area (Nara Prefecture) of Japan in 2021. In this study, first, the supercolony type of the Nara L. humile population was identified via a hostility test, and then its distribution pattern was characterized. In aggression tests between L. humile from Nara and four supercolonies (haplotypes LH1, LH2, LH3, LH4), this ant showed extremely strong hostility against all supercolonies exept LH2, which was detected only in Japan in its introduced range. In Nara, L. humile was abundant in and around the urban river. Simulations revealed that using this environment for movement/dispersal increased the annual dispersal ability by 14 times compared with that achieved via ground (125 m), as mentioned in the literature. Therefore, river channels can serve as major pathways of long-distance dispersal for L. humile invading inland urban areas. Since applying chemical strategies around rivers is problematic, preventing L. humile from moving to rivers from initial invasion sites is crucial.
Magneto-hydrodynamic peristaltic flow of a Jeffery fluid in the presence of heat transfer through a porous medium in an asymmetric channel
Authors: Abd-Alla A. M. , Abo-Dahab S. M. , Salah Doaa. M. , Bayones F. S. , Abdelhafez M. A. 
Published: November 2023

AbstractIn the present paper, the effects of magnetic field and heat transfer on the peristaltic flow of a Jeffery fluid through a porous medium in an asymmetric channel have been studied. The governing non-linear partial differential equations representing the flow model are transmuted into linear ones by employing the appropriate non-dimensional parameters under the assumption of long wavelength and low Reynolds number. Exact solutions are presented for the stream function, pressure gradient, and temperature. The frictional force and pressure rise are both computed using numerical integration. Using MATLAB R2023a software, a parametric analysis is performed, and the resulting data is represented graphically. For all physical quantities considered, numerical calculations were made and represented graphically. Trapping phenomena are discussed graphically. The obtained results can be applied to enhance pumping systems in engineering and gastrointestinal functions. This analysis permits body fluids such as blood and lymph to easily move inside the arteries and veins, allowing oxygen supply, waste elimination, and other necessary elements.
Salt wedges and trapped brines of low-latitude endoreic saline lakes as potential modulators of GHG emission
Authors: Gibert-Brunet Elisabeth , Tudryn Alina , Kong Ting , Tucholka Piotr , Motavalli-Anbaran Seyed-Hani , Marlin Christelle , Noret Aurélie , Lankarani Mohammad , Ahmady-Birgani Hesam , Karimi Gilda 
Published: November 2023

AbstractLarge salt lakes are long-term witnesses to climatic conditions and land use in their basins. The majority are experiencing a drastic drop in water levels due to climate change and human impact. Endoreic Lake Urmia (NW Iran), the sixth largest salt lake worldwide, is a striking example of this decline. Quantification of the relative contributions of natural variability and human impact on the lake's water supply is therefore essential. Here we present isotopic and radiocarbon analyses of surface and groundwater from the Shahr Chay River catchment, entering Lake Urmia on its western shore, and radiocarbon dating of a sedimentary core. Lake Urmia behaves like a large saltwater wedge almost entirely fed by the river and shallow groundwater. This leads to trapping of residual brines and formation of CH4 and secondary CO2 greenhouse gases, impacting sediment geochemical records and corresponding time scales for paleoenvironmental reconstructions. We conclude that (1) salt lakes functioning like a saline wedge, allowing organic matter oxidation, could contribute to increasing methane sources or reducing carbon sinks globally, and (2) endoreic basins worldwide need to be monitored before aridification-related salinization leads to the establishment of a saline wedge precluding any possibility of return to an equilibrium state.
Insufficient sleep and weekend recovery sleep: classification by a metabolomics-based machine learning ensemble
Authors: Gombert Marie , Reisdorph Nichole , Morton Sarah J. , Wright Kenneth P. , Depner Christopher M. 
Published: November 2023

AbstractAlthough weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.
A prospective cohort study on the association between dietary fatty acids intake and risk of hypertension incident
Authors: Shakiba Ebrahim , Najafi Farid , Pasdar Yahya , Moradinazar Mehdi , Navabi Jafar , Shakiba Mohammad Hossein , Bagheri Amir 
Published: November 2023

AbstractThere are inconclusive results available on the association between dietary fatty acid intake and the risk of hypertension (HTN) incident. In this study, we investigate the relationship between baseline dietary fatty acids intake including polyunsaturated fatty acid (PUFA), trans fatty acids (TFA), monounsaturated fatty acid (MUFA), and saturated fatty acid (SFA), and the risk of first incidence hypertension. The current prospective cohort study was carried out from the Ravansar Non-Communicable Diseases (RaNCD) cohort. A food frequency questionnaire (FFQ) with 118 items was used for the assessment of dietary data. Cox proportional hazards analyses were done to estimate hazard ratios (HR) and 95% confidence intervals (CIs) of the highest versus lowest quartile intake of SFA, PUFA, MUFA, and SFA and risk of HTN. Out of 7359 eligible participants, 597 new cases of HTN were identified over an average of 6.4 ± 1.33 years of follow-up. No significant relationship was observed between the fourth compared to the first categories of dietary SFA (HR: 0.82, 95% CI 0.55, 1.21; P trend: 0.476), MUFA (HR: 0.71, 95% CI 0.48, 1.06; P trend: 0.252), PUFA (HR: 0.86, 95% CI 0.62, 1.19; P trend: 0.315) and TFA (HR: 0.99, 95% CI 0.76, 1.27; P trend: 0.675), and risk of HTN. However, a significant inverse association between each 1 g per day increase in dietary MUFA intake during 6.4 years of follow up and HTN incident (HR: 0.97; 95% CI 0.94, 0.99; P 0.044) was observed. In brief, our study revealed that higher dietary MUFA intake was protectively associated with HTN incident. Dietary MUFA-rich foods should be encouraged to improve blood pressure.
Evaluation of repositioning care provided by non-professionals using a caregiver-assistive device: an experimental study
Authors: Omura Yuka , Watanabe Atsuko , Shibata Kasumi , Inoue Tomoko 
Published: November 2023

AbstractAs the population ages in Japan and worldwide, the number of informal caregivers, such as family members, providing nursing care to older individuals is increasing. Among caregiving tasks, repositioning care, which causes lower back pain, is frequent and burdensome for caregivers. Therefore, we developed a position-changing device that can adjust and support the care recipient’s body in the lateral position. This was a feasibility study of the device-assisted care provided by non-professionals using the device we developed. Of the 40 healthy volunteers enrolled, 17 simulated caregivers and 17 simulated care recipients finally participated in the study. One caregiver and one care recipient were paired to engage in two types of care: device-assisted care and manual care. Furthermore, the care provided by the caregiver and received by the care recipient were evaluated. Non-professionals were able to use the device successfully and safely after a short period of practice, and both caregivers and care recipients rated the device-assisted care positively. The study results suggest that informal caregivers can also provide safe and comfortable care that is less burdensome than manual care by using a caregiver-assistive device.
Development of postoperative delirium prediction models in patients undergoing cardiovascular surgery using machine learning algorithms
Authors: Nagata Chie , Hata Masahiro , Miyazaki Yuki , Masuda Hirotada , Wada Tamiki , Kimura Tasuku , Fujii Makoto , Sakurai Yasushi , Matsubara Yasuko , Yoshida Kiyoshi , Miyagawa Shigeru , Ikeda Manabu , Ueno Takayoshi 
Published: November 2023

AbstractAssociations between delirium and postoperative adverse events in cardiovascular surgery have been reported and the preoperative identification of high-risk patients of delirium is needed to implement focused interventions. We aimed to develop and validate machine learning models to predict post-cardiovascular surgery delirium. Patients aged ≥ 40 years who underwent cardiovascular surgery at a single hospital were prospectively enrolled. Preoperative and intraoperative factors were assessed. Each patient was evaluated for postoperative delirium 7 days after surgery. We developed machine learning models using the Bernoulli naive Bayes, Support vector machine, Random forest, Extra-trees, and XGBoost algorithms. Stratified fivefold cross-validation was performed for each developed model. Of the 87 patients, 24 (27.6%) developed postoperative delirium. Age, use of psychotropic drugs, cognitive function (Mini-Cog < 4), index of activities of daily living (Barthel Index < 100), history of stroke or cerebral hemorrhage, and eGFR (estimated glomerular filtration rate) < 60 were selected to develop delirium prediction models. The Extra-trees model had the best area under the receiver operating characteristic curve (0.76 [standard deviation 0.11]; sensitivity: 0.63; specificity: 0.78). XGBoost showed the highest sensitivity (AUROC, 0.75 [0.07]; sensitivity: 0.67; specificity: 0.79). Machine learning algorithms could predict post-cardiovascular delirium using preoperative data.Trial registration: UMIN-CTR (ID; UMIN000049390).
LMFD: lightweight multi-feature descriptors for image stitching
Authors: Fan Yingbo , Mao Shanjun , Li Mei , Kang Jitong , Li Ben 
Published: November 2023

AbstractImage stitching is a fundamental pillar of computer vision, and its effectiveness hinges significantly on the quality of the feature descriptors. However, the existing feature descriptors face several challenges, including inadequate robustness to noise or rotational transformations and limited adaptability during hardware deployment. To address these limitations, this paper proposes a set of feature descriptors for image stitching named Lightweight Multi-Feature Descriptors (LMFD). Based on the extensive extraction of gradients, means, and global information surrounding the feature points, feature descriptors are generated through various combinations to enhance the image stitching process. This endows the algorithm with formidable rotational invariance and noise resistance, thereby improving its accuracy and reliability. Furthermore, the feature descriptors take the form of binary matrices consisting of 0s and 1s, not only facilitating more efficient hardware deployment but also enhancing computational efficiency. The utilization of binary matrices significantly reduces the computational complexity of the algorithm while preserving its efficacy. To validate the effectiveness of LMFD, rigorous experimentation was conducted on the Hpatches and 2D-HeLa datasets. The results demonstrate that LMFD outperforms state-of-the-art image matching algorithms in terms of accuracy. This empirical evidence solidifies the superiority of LMFD and substantiates its potential for practical applications in various domains.
AUCReshaping: improved sensitivity at high-specificity
Authors: Bhat Sheethal , Mansoor Awais , Georgescu Bogdan , Panambur Adarsh B. , Ghesu Florin C. , Islam Saahil , Packhäuser Kai , Rodríguez-Salas Dalia , Grbic Sasa , Maier Andreas 
Published: November 2023

AbstractThe evaluation of deep-learning (DL) systems typically relies on the Area under the Receiver-Operating-Curve (AU-ROC) as a performance metric. However, AU-ROC, in its holistic form, does not sufficiently consider performance within specific ranges of sensitivity and specificity, which are critical for the intended operational context of the system. Consequently, two systems with identical AU-ROC values can exhibit significantly divergent real-world performance. This issue is particularly pronounced in the context of anomaly detection tasks, a commonly employed application of DL systems across various research domains, including medical imaging, industrial automation, manufacturing, cyber security, fraud detection, and drug research, among others. The challenge arises from the heavy class imbalance in training datasets, with the abnormality class often incurring a considerably higher misclassification cost compared to the normal class. Traditional DL systems address this by adjusting the weighting of the cost function or optimizing for specific points along the ROC curve. While these approaches yield reasonable results in many cases, they do not actively seek to maximize performance for the desired operating point. In this study, we introduce a novel technique known as AUCReshaping, designed to reshape the ROC curve exclusively within the specified sensitivity and specificity range, by optimizing sensitivity at a predetermined specificity level. This reshaping is achieved through an adaptive and iterative boosting mechanism that allows the network to focus on pertinent samples during the learning process. We primarily investigated the impact of AUCReshaping in the context of abnormality detection tasks, specifically in Chest X-Ray (CXR) analysis, followed by breast mammogram and credit card fraud detection tasks. The results reveal a substantial improvement, ranging from 2 to 40%, in sensitivity at high-specificity levels for binary classification tasks.
Application of human platelet lysate in chondrocyte expansion promotes chondrogenic phenotype and slows senescence progression via BMP–TAK1–p38 pathway
Authors: Chitchongyingcharoen Narong , Tawonsawatruk Tulyapruek , Phetfong Jitrada , Aroontanee Wrattya , Supokawej Aungkura 
Published: November 2023

AbstractOsteoarthritis (OA) is one of the most common musculoskeletal degenerative. OA treatments are aiming to slow down disease progression; however, lack of cartilage regeneration efficacy. Autologous chondrocyte implantation (ACI) is a promising cartilage-regeneration strategy that uses human articular chondrocytes (HACs) as cellular materials. However, the unreadiness of HACs from prolonged expansion, cellular senescence, and chondrogenic dedifferentiation occurred during conventional expansion, thus, minimizing the clinical efficacy of ACI. We aimed to examine the effects of a human platelet lysate (HPL) as an alternative human-derived HAC medium supplement to overcome the limitations of conventional expansion, and to explain the mechanism underlying the effects of HPL. During passages 2–4 (P2-P4), HPL significantly increased HAC proliferation capacities and upregulated chondrogenic markers. Simultaneously, HPL significantly reduced HAC senescence compared with conventional condition. HACs treated with LDN193189 exhibited a reduction in proliferation capacity and chondrogenic marker expression, whereas the HAC senescence increased slightly. These findings indicated involvement of BMP-2 signaling transduction in the growth-assistive, anti-senescent, and chondrogenic-inductive properties of HPL, which demonstrated its beneficial effects for application as HAC medium supplement to overcome current expansion limitations. Finally, our findings support the roles of platelets in platelet-rich plasma as a promising treatment for patients with OA.
Investigation of an efficient multi-modal convolutional neural network for multiple sclerosis lesion detection
Authors: Raab Florian , Malloni Wilhelm , Wein Simon , Greenlee Mark W. , Lang Elmar W. 
Published: November 2023

AbstractIn this study, an automated 2D machine learning approach for fast and precise segmentation of MS lesions from multi-modal magnetic resonance images (mmMRI) is presented. The method is based on an U-Net like convolutional neural network (CNN) for automated 2D slice-based-segmentation of brain MRI volumes. The individual modalities are encoded in separate downsampling branches without weight sharing, to leverage the specific features. Skip connections input feature maps to multi-scale feature fusion (MSFF) blocks at every decoder stage of the network. Those are followed by multi-scale feature upsampling (MSFU) blocks which use the information about lesion shape and location. The CNN is evaluated on two publicly available datasets: The ISBI 2015 longitudinal MS lesion segmentation challenge dataset containing 19 subjects and the MICCAI 2016 MSSEG challenge dataset containing 15 subjects from various scanners. The proposed multi-input 2D architecture is among the top performing approaches in the ISBI challenge, to which open-access papers are available, is able to outperform state-of-the-art 3D approaches without additional post-processing, can be adapted to other scanners quickly, is robust against scanner variability and can be deployed for inference even on a standard laptop without a dedicated GPU.
Association between invasively measured central aortic pulse pressure and diameter of ascending aorta
Authors: Kim Hack-Lyoung , Joh Hyun Sung , Lim Woo-Hyun , Seo Jae-Bin , Kim Sang-Hyun , Zo Joo-Hee , Kim Myung-A 
Published: November 2023

AbstractData on the relationship between arterial pulsatile hemodynamics and aortic root geometry, using invasive hemodynamic measurement, has been scarce. Thus, this study aimed to assess the relationship between invasively measured aortic pulse pressure (aPP) and the diameter of ascending aorta (AoD). We analyzed 665 subjects (64.3 ± 11.0 years; 34.6% female) who underwent elective invasive coronary angiography (ICA) for the evaluation of coronary artery disease. Transthoracic echocardiography was performed on the same day, and AoD was measured at the level of 1 cm above the sinotubular junction at the end-diastole. Body surface area (BSA)-adjusted AoD (AoD/BSA) was used for the analysis. A pig-tail catheter was used to measure aortic pressures at a level approximately 3 cm above the aortic valve just before ICA. aPP was calculated as the difference between systolic and diastolic pressures of the aorta. In multiple linear regression analyses, aPP (β = 0.259; P < 0.001) was found to be significantly correlated with AoD/BSA even after controlling for potential confounders. This correlation power was stronger than aortic systolic pressure (β = 0.189; P < 0.001) and brachial pulse pressure (β = 0.091; P = 0.018) at the same multivariable analyses. In conclusion, our study demonstrated a significant association between invasively measured aPP and AoD/BSA, providing stronger evidence for the link between central aortic pulsatile hemodynamics and aortic root geometry.
Single-molecule visualization of human A2A adenosine receptor activation by a G protein and constitutively activating mutations
Authors: Wei Shushu , Pour Niloofar Gopal , Tiruvadi-Krishnan Sriram , Ray Arka Prabha , Thakur Naveen , Eddy Matthew T. , Lamichhane Rajan 
Published: November 2023

AbstractMutations that constitutively activate G protein-coupled receptors (GPCRs), known as constitutively activating mutations (CAMs), modify cell signaling and interfere with drugs, resulting in diseases with limited treatment options. We utilize fluorescence imaging at the single-molecule level to visualize the dynamic process of CAM-mediated activation of the human A2A adenosine receptor (A2AAR) in real time. We observe an active-state population for all CAMs without agonist stimulation. Importantly, activating mutations significantly increase the population of an intermediate state crucial for receptor activation, notably distinct from the addition of a partner G protein. Activation kinetics show that while CAMs increase the frequency of transitions to the intermediate state, mutations altering sodium sensitivity increase transitions away from it. These findings indicate changes in GPCR function caused by mutations may be predicted based on whether they favor or disfavor formation of an intermediate state, providing a framework for designing receptors with altered functions or therapies that target intermediate states.