bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pollinator sex matters in competition and coexistence of co-flowering plants
Authors: Nakazawa Takefumi , Kishi Shigeki 
Published: March 2023

AbstractMale and female pollinators often exhibit sex-specific preferences for visiting different flowers. Recent studies have shown that these preferences play an important role in shaping the network structure of pollination mutualism, but little is known about how they can mediate plant-plant interactions and coexistence of competing plants. The ecological consequences of sex-specific pollination can be complex. Suppose that a plant is favoured by female pollinators. They produce male pollinators, who may prefer visiting other competing plants and intensify the negative effects of inter-plant competition. Here, we analysed a simple two plant-one pollinator model with the sex structure of the pollinator. We observed that (i) sex-specific pollination can have complex consequences for inter-plant competition and coexistence (e.g. the occurrence of non-trivial alternative stable states in which one plant excludes or coexists with the other depending on the initial conditions), (ii) male and female pollinators have distinct ecological consequences because female pollinators have a demographic impact owing to reproduction, and (iii) plants are likely to coexist when male and female pollinators prefer different plants. These results suggest that sex-specific pollination is crucial for competition and coexistence of co-flowering plants. Future, pollination research should more explicitly consider the sex-specific behaviour of pollinating animals.
Tropical surface urban heat islands in east Africa
Authors: Garuma Gemechu Fanta 
Published: March 2023

AbstractThe horn of Africa is susceptible to droughts because of the persistent heat waves and insufficient precipitation. The growth of urban population and built-up urban environments exacerbate the overheating problems due to the urban heat island effects. Understanding the impacts of anthropogenic activities in such dry environments is important to control or mitigate extreme heat leading to droughts. This is required to preserve soil moisture, pothole waters, lakes and rivers that are required for pasture and drinking water. Nonetheless, the intensity and duration of the urban heat island effects have not been investigated in this region resulting in the underestimation of the intensity and severity of the extreme heat events. This study therefore performs the quantitative analyses of the intensity, duration and causality of the tropical surface urban heat islands (TSUHIs) for the first time using earth observation information at a regional to local scale. It also identifies the factors that control TSUHIs, considering background climate, population, vegetation and the impervious urban fractions. Results showed that the TSUHI in the capital cities of tropical east Africa varies from 1 $$^{\circ }$$

∘

C in Dodoma to 4 $$^{\circ }$$

∘

C in Kampala and reaches up to 8 $$^{\circ }$$

∘

C in Khartoum. The mean temperature contribution to regional climate from 2000 to 2020 is 0.64 $$^{\circ }$$

∘

C during the day and 0.34 $$^{\circ }$$

∘

C during the night, a mean total of around 0.5 $$^{\circ }$$

∘

C, a 0.25 $$^{\circ }$$

∘

C increase per decade. This is a quarter of the increase in global surface temperature, which is $$\approx$$
≈
1.09 $$^{\circ }$$

∘

C from 2011 to 2020 compared to the 1850–1900 level. Most of these capital cities in this region exhibited high TSUHIs from late summer to winter and are dependent on mainly population, vegetation, evapotranspiration and soil moisture in different proportions. This urban induced additional temperature has been intensifying droughts in tropical east Africa. Therefore, urban planners are advised to consider the impacts of TSUHIs to reduce the severity of droughts in the tropical east Africa region.
The design of a point of care FET biosensor to detect and screen COVID-19
Authors: Alnaji Nisreen , Wasfi Asma , Awwad Falah 
Published: March 2023

AbstractGraphene field effect transistor (FET) biosensors have attracted huge attention in the point-of-care and accurate detection. With the recent spread of the new emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the need for rapid, and accurate detection & screening tools is arising. Employing these easy-to-handle sensors can offer cheap, rapid, and accurate detection. Herein, we propose the design of a reduced graphene oxide (rGO) FET biosensor for the detection of SARS-CoV-2. The main objective of this work is to detect the SARS-CoV-2 spike protein antigen on spot selectively and rapidly. The sensor consists of rGO channel, a pair of golden electrodes, and a gate underneath the channel. The channel is functionalized with COVID-19 spike protein antibodies to achieve selectivity, and with metal nanoparticles (MNPs) such as copper and silver to enhance the bio-sensing performance. The designed sensor successfully detects the SARS-CoV-2 spike protein and shows singular electrical behavior for detection. The semi-empirical modeling approach combined with none-equilibrium Green’s function were used to study the electronic transport properties of the rGO-FET biosensor before and after the addition of the target molecules. The sensor’s selectivity is also tested against other viruses. This study provides a promising guide for future practical fabrication.
Modeling the time-dependent transmission rate using gaussian pulses for analyzing the COVID-19 outbreaks in the world
Authors: Setianto Setianto , Hidayat Darmawan 
Published: March 2023

AbstractIn this work, an SEIR epidemic model with time-dependent transmission rate parameters for the multiple waves of COVID-19 infection was investigated. It is assumed that the transmission rate is determined by the superposition of the Gaussian pulses. The interaction of these dynamics is represented by recursive equations. Analysis of the overall dynamics of disease spread is determined by the effective reproduction numberRe(t) produced throughout the infection period. The study managed to show the evolution of the epidemic over time and provided important information about the occurrence of multiple waves of COVID-19 infection in the world and Indonesia.
Infarct growth velocity predicts early neurological outcomes in single subcortical infarction
Authors: Nam Ki-Woong , Kwon Hyung-Min , Lee Yong-Seok 
Published: March 2023

AbstractIn single subcortical infarction (SSI), changes in lesion size are a major determinant of early neurological deterioration. We evaluated the association between END and infarct growth velocity (IGV) in patients with SSI. We included consecutive patients with SSI who underwent MRI within 24 h of symptom onset between 2010 and 2020. END was defined as an increase of ≥ 2 in the total National Institutes of Health Stroke Scale (NIHSS) score or ≥ 1 in the motor NIHSS score. IGV was calculated using the following formula: IGV (mL/h) = diffusion-weighted imaging volume (mL)/time to MRI (h). A total of 604 patients with SSI were evaluated. Multivariable logistic regression analysis showed that IGV remained significant after adjusting for confounders (aOR = 1.34, 95% CI 1.12–1.61). In a subgroup analysis based on the type of SSI, only patients with distal SSI showed an association between IGV and END (aOR = 1.64, 95% CI 1.24–2.16). In patients with proximal SSI, IGV did not show any statistical association with END. In conclusion, IGV was positively associated with END in patients with SSI. IGV should be interpreted differently in clinical settings depending on the location of the SSI lesion.
A dynamic clamping approach using in silico IK1 current for discrimination of chamber-specific hiPSC-derived cardiomyocytes
Authors: Altomare Claudia , Bartolucci Chiara , Sala Luca , Balbi Carolina , Burrello Jacopo , Pietrogiovanna Nicole , Burrello Alessio , Bolis Sara , Panella Stefano , Arici Martina , Krause Rolf , Rocchetti Marcella , Severi Stefano , Barile Lucio 
Published: March 2023

AbstractHuman induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents.
Transient interactions drive the lateral clustering of cadherin-23 on membrane
Authors: Srinivas Cheerneni S. , Singaraju Gayathri S. , Kaur Veerpal , Das Sayan , Ghosh Sanat K. , Sagar Amin , Kumar Anuj , Bhatia Tripta , Rakshit Sabyasachi 
Published: March 2023

AbstractCis and trans-interactions among cadherins secure multicellularity. While the molecular structure of trans-interactions of cadherins is well understood, work to identify the molecular cues that spread the cis-interactions two-dimensionally is still ongoing. Here, we report that transient, weak, yet multivalent, and spatially distributed hydrophobic interactions that are involved in liquid-liquid phase separations of biomolecules in solution, alone can drive the lateral-clustering of cadherin-23 on a membrane. No specific cis-dimer interactions are required for the lateral clustering. In cells, the cis-clustering accelerates cell-cell adhesion and, thus, contributes to cell-adhesion kinetics along with strengthening the junction. Although the physiological connection of cis-clustering with rapid adhesion is yet to be explored, we speculate that the over-expression of cadherin-23 in M2-macrophages may facilitate faster attachments to circulatory tumor cells during metastasis.
Enhanced excitability but mature action potential waveforms at mossy fiber terminals of young, adult-born hippocampal neurons in mice
Authors: Vyleta Nicholas P. , Snyder Jason S. 
Published: March 2023

AbstractAdult-born granule neurons pass through immature critical periods where they display enhanced somatic excitability and afferent plasticity, which is believed to endow them with unique roles in hippocampal learning and memory. Using patch clamp recordings in mouse hippocampal slices, here we show that young neuron hyper-excitability is also observed at presynaptic mossy fiber terminals onto CA3 pyramidal neurons. However, action potential waveforms mature faster in the bouton than in the soma, suggesting rapid efferent functionality during immature stages.
Elucidating the reaction mechanism of a palladium-palladium dual catalytic process through kinetic studies of proposed elementary steps
Authors: Ivančič Anže , Košmrlj Janez , Gazvoda Martin 
Published: March 2023

AbstractIn the synergistic dual catalytic process, the kinetics of the catalytic cycles must be balanced for the successful outcome of the reaction. Therefore, the analysis of the kinetics of the independent catalytic cycles is essential for such reactions, as it enables their relational optimization as well as their design. Here we describe an analysis of the mechanism of a catalytic synergistic bimetallic reaction through the experimental study of a palladium-catalysed cross-coupling of aryl halides with terminal alkynes, an example of a monometallic dual catalytic process. The proposed mechanism of the investigated reaction was disassembled into two palladium catalytic cycles and further into elementary reactions, and each step was studied independently. The described mechanistic analysis allowed us to identify the rate-determining step of the catalytic process by comparing the rates of the elementary reactions under similar reaction conditions, balanced kinetics of the palladium catalytic cycles, and also in which step which reagent enters the catalytic cycle and how.
Evidence for late winter biogeochemical connectivity in permafrost soils
Authors: Hirst Catherine , Monhonval Arthur , Mauclet Elisabeth , Thomas Maxime , Villani Maëlle , Ledman Justin , Schuur Edward. A. G. , Opfergelt Sophie 
Published: March 2023

AbstractThe permafrost active layer is a key supplier of soil organic carbon and mineral nutrients to Arctic rivers. In the active layer, sites of soil-water exchange are locations for organic carbon and nutrient mobilization. Previously these sites were considered as connected during summer months and isolated during winter months. Whether soil pore waters in active layer soils are connected during shoulder seasons is poorly understood. In this study, exceptionally heavy silicon isotope compositions in soil pore waters show that during late winter, there is no connection between isolated pockets of soil pore water in soils with a shallow active layer. However, lighter silicon isotope compositions in soil pore waters reveal that soils are biogeochemically connected for longer than previously considered in soils with a deeper active layer. We show that an additional 21% of the 0–1 m soil organic carbon stock is exposed to soil - water exchange. This marks a hot moment during a dormant season, and an engine for organic carbon transport from active layer soils. Our findings mark the starting point to locate earlier pathways for biogeochemical connectivity, which need to be urgently monitored to quantify the seasonal flux of organic carbon released from permafrost soils.
Magmatic addition rates differentiate periods of steady-state versus flare-up magmatism in the Central Andean arc
Authors: Bertin Daniel , de Silva Shanaka L. , Lindsay Jan M. , Cronin Shane J. , Caffe Pablo J. , Connor Charles B. , Grosse Pablo , Báez Walter , Bustos Emilce , Constantinescu Robert 
Published: March 2023

AbstractCordilleran arcs are built by long periods of steady-state magmatism punctuated by transient high-flux magmatic episodes or flare-ups. Such flare-ups, manifested as periods of prodigious silicic volcanism and magmatism, result from geodynamic perturbations that cause elevated rates of magma addition to the crust. Questions remain, however, about how magmatic addition rates quantitatively compare between steady-state and flare-up modes of arc magmatism, and how long after the major geodynamic perturbation the flare-up begins. Here, we compute new estimates of erupted volumes over the last 35 Myr for the 22.5–29°S segment of the Central Andes based on a new volcanic geospatial database. These yield magmatic addition rates at least an order of magnitude higher during flare-up compared to steady-state conditions. A lag time of ~8–12 Myr between ocean ridge subduction (the major geodynamic perturbation in the Central Andean arc) and the onset of flare-up conditions is estimated.
Iterative learning tracking control for second‐order nonlinear hyperbolic impulsive partial differential systems
Authors: Dai Xisheng , Wu Jing , Zhang Jianxiang , Zhou Guopeng 
Published: March 2023

AbstractThis paper studies the iterative learning control (ILC) for a class of second‐order nonlinear hyperbolic impulsive partial differential systems. Firstly, to follow the discontinuous desired output, a P‐type learning law is adopted, and sufficient conditions for the convergence of the tracking error is established under identified initial state value. The rigorous analysis is also given using the impulsive Gronwall inequality. Secondly, the tracking error of output trajectory is considered in systems with state initial values shifting based on an initial learning algorithm. These results of this paper show that the tracking error on the finite time interval can uniform converge to 0 as the iteration index goes to infinity if impulse number of the systems is only a finite numbers. Finally, two numerical simulation examples are given to verify the effectiveness of the theoretical results.
Mask‐guided image person removal with data synthesis
Authors: Jiang Yunliang , Gu Chenyang , Xue Zhenfeng , Zhang Xiongtao , Liu Yong 
Published: March 2023

AbstractAs a special case of common object removal, image person removal is playing an increasingly important role in social media and criminal investigation domains. Due to the integrity of person area and the complexity of human posture, person removal has its own dilemmas. In this paper, a novel idea is proposed to tackle these problems from the perspective of data synthesis. Concerning the lack of a dedicated dataset for image person removal, two dataset production methods are proposed to automatically generate images, masks and ground truths, respectively. Then, a learning framework similar to local image degradation is proposed so that the masks can be used to guide the feature extraction process and more texture information can be gathered for final prediction. A coarse‐to‐fine training strategy is further applied to refine the details. The data synthesis and learning framework combine well with each other. Experimental results verify the effectiveness of the method quantitatively and qualitatively, and the trained network proves to have good generalization ability either on real or synthetic images.
A new adaptive window‐based guided filtering and interpolation for polarization image demosaicing
Authors: Xie Fei , Liu Shumin , Chen Jiajia 
Published: March 2023

AbstractThis paper presents a new adaptive window‐based guided filtering and interpolation for polarization image demosaicing. Considering the correlation between the polarization channels, the authors use the total intensity S0 as a guide image to guide the interpolation of all channels. The guided filtering is performed with a new adaptive window size selection technique. A novel iterative residual interpolation is proposed to construct accurate full resolution polarization. Experiments are conducted with the sample images from the demosaicking algorithms dataset. Objective evaluations demonstrate that the proposed algorithm can reduce root mean squared error by at least 27% over other methods. Subjective visual inspection can also verify the improvements in the clarity of objects in angle and degree of the linear polarization images.
An energy‐efficient train control approach with dynamic efficiency of the traction system
Authors: Fu Chengcheng , Sun Pengfei , Zhang Jiahui , Yan Keqin , Wang Qingyuan , Feng Xiaoyun 
Published: March 2023

AbstractThe efficiency of the train traction system (TTS) changes dynamically with operating conditions. In this paper, a more realistic dynamic efficiency model of TTS is established considering the power flow and non‐linear loss of TTS. Based on the real model, the optimal control problem of the train with the minimum electric power consumption on the grid side is constructed. The optimal control condition (OCC) and corresponding control force are derived based on the Pontryagin maximum principle (PMP). A dynamic programming algorithm (DP2) with the OCC curve as the state space is designed to obtain optimal results. The proposed model and the method are validated by the comparison of conventional dynamic programming (DP1) and automatic train operation (ATO) measured data. The simulation results show that compared with the traditional TTS constant efficiency model, considering that the TTS dynamic efficiency model has a better energy‐saving effect, and the designed DP2 algorithm has a more obvious energy‐saving effect than DP1.
A deep neural network model with GCN and 3D convolutional network for short‐term metro passenger flow forecasting
Authors: Zhang Xuanrong , Wang Cheng , Chen Jianwei , Chen Ding 
Published: March 2023

AbstractRail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers. Deep learning has become an effective method for short‐term rail passenger flow prediction. A deep learning model which combines a graph convolutional network and a three‐dimensional Convolutional Neural Network improved by a residual module and an attention mechanism (ARConv‐CGN) is proposed. First, historical passenger inflow and outflow data are aggregated into three patterns: recent pattern, daily pattern, and weekly pattern separately. The GCN is applied to capture the spatiotemporal and topological information of passenger flows in each pattern. Second, a three‐dimensional convolutional neural network is used to deeply integrate three patterns of passenger flow information. Additionally, a residual module is used to increase the number of neural network layers and prevent the gradient of the deep neural network from disappearing. Finally, an attention mechanism is also introduced to adjust the importance of passenger flow in different pattern, so that improving the performance of the model. Training with passenger flow data from automatic fare collection on weekdays in Beijing and Xiamen provides a good demonstration of the superiority of ARConv‐CGN in metro passenger flow forecasting.
Endoscope reprocessing: Retrospective analysis of 90,311 samples
Authors: Pineau Lionel 
Published: March 2023

Abstract
Background and study aims The contamination level of ready-to-use endoscopes published in the literature varies from 0.4 % to 49.0 %. Unfortunately, the comparison and the interpretation of these results are quite impossible, given the limited number of samples and sites included and the differences observed between sampling, culturing methods, and interpretation criteria.
Methods The objective of this retrospective study was to analyze the results of 90,311 endoscope samples collected between 2004 and 2021 in 490 private or public hospitals in France.
Results Through the full test period, the mean ratio of endoscopes at the action level was 12.6 % (19.5 % including alert level). Of the endoscopy units, 23.0 % had a ratio of compliant endoscopes ≤ 70.0 %. The overall microbial quality of gastroscopes, duodenoscopes, and colonoscopes is improving year by year, whereas an opposite trend is observed for ultrasound endoscopes and bronchoscopes. In 2021, following French guidelines, 13.0 % of the endoscopes should have been quarantined and 8.1 % were at the alert level, meaning that the contamination level of 21.1 % of the endoscopes exceeded what was defined as a maximum acceptable value.
Conclusions This study demonstrates that additional efforts, including implementation of microbial surveillance strategies using a standardized sampling method and periodic observational audits, must be made to improve the overall microbiological quality of endoscopes and reduce the risk associated with their use.