bluuebunny/crossref_metadata_2025_split huggingface dataset:
Size‐dependent electrophoretic motion of polystyrene particles at polyethylene glycol–dextran interfaces
Authors: Chang Hui , Li Deyu , Zhang Xiangyu , Xu Runxin , Zhang Junyan , Song Yongxin 
Published: June 2022

AbstractCurrently, there is very limited information on the electrophoretic behavior of particles at a liquid–liquid interface formed by two conducting liquid solutions. Here, electrophoretic velocities of polystyrene particles at a polyethylene glycol (PEG)–dextran (DEX) interface were investigated in this paper. Experimental results show that the particle at the interface moves in the opposite direction to the applied electric field, with a velocity much lower than that in the PEG‐rich phase and a litter larger than that in the DEX‐rich phase. Similarly to the movement in Newtonian fluids, the velocity increases linearly with the increase in the applied electric field. Different to particle electrophoresis in Newtonian fluids, the velocities of the particles at the PEG–DEX interface increase linearly with the decrease in particle's diameters, implying a possible size‐based particle differentiation at an interface.
Blockchain enabled trusted task offloading scheme for fog computing: A deep reinforcement learning approach
Authors: Jain Vibha , Kumar Bijendra 
Published: June 2022

AbstractWith the recent advancements in the Internet of Things, cloud computing has emerged as an important industrial technology that assists in various data analysis operations. However, the remote locality of cloud servers and scalability issues of cloud computing make it unsuitable for real‐time computing‐intensive applications. Fog computing strives to support cloud computing in meeting scalability demands by providing location‐sensitive services closer to end devices. With decentralized heterogeneous resource capabilities, fog architecture can handle several computation‐intensive and delay‐sensitive user requests. Although deploying service providers in an untrustworthy environment makes it challenging to assess the trustworthy acquired services. Conspicuously, in this article, we present a trusted task offloading and resource allocation using blockchain technology. To start with, we analyze direct and indirect trust with a subjective logical aggregation approach using a distributed trust assessment approach. Additionally, we examined the various quality of service parameters and constructed a smart contract that utilizes the state‐of‐the‐art deep reinforcement learning algorithm, namely Deep Deterministic Policy Gradient, to maximize fog revenue while serving as many user requests as possible. The entire process from task generation to results calculation is assisted by blockchain and offloading task transactions are stored in the secure, immutable, and tamper‐resistant ledger. To assess the effectiveness of our proposed scheme, we compared the simulation results with other baseline schemes over different performance metrics in terms of reward, service latency, energy consumption, task drop ratio, and transaction success rate. The results suggest that enabling trust computation improves transaction success by 21%.
A new PM2.5 concentration forecasting system based on AdaBoost‐ensemble system with deep learning approach
Authors: Li Zhongfei , Gan Kai , Sun Shaolong , Wang Shouyang 
Published: June 2022

AbstractA reliable and efficient forecasting system can be used to warn the general public against the increasing PM2.5 concentration. This paper proposes a novel AdaBoost‐ensemble technique based on a hybrid data preprocessing‐analysis strategy, with the following contributions: (i) a new decomposition strategy is proposed based on the hybrid data preprocessing‐analysis strategy, which combines the merits of two popular decomposition algorithms and has been proven to be a promising decomposition strategy; (ii) the long short‐term memory (LSTM), as a powerful deep learning forecasting algorithm, is applied to individually forecast the decomposed components, which can effectively capture the long‐short patterns of complex time series; and (iii) a novel AdaBoost‐LSTM ensemble technique is then developed to integrate the individual forecasting results into the final forecasting results, which provides significant improvement to the forecasting performance. To evaluate the proposed model, a comprehensive and scientific assessment system with several evaluation criteria, comparison models, and experiments is designed. The experimental results indicate that our developed hybrid model considerably surpasses the compared models in terms of forecasting precision and statistical testing and that its excellent forecasting performance can guide in developing effective control measures to decrease environmental contamination and prevent the health issues caused by a high PM2.5 concentration.
Job loss and psychological distress during the COVID‐19 pandemic: Longitudinal Analysis from residents in nine predominantly African American low‐income neighborhoods
Authors: Baird Matthew D. , Cantor Jonathan , Troxel Wendy M. , Dubowitz Tamara 
Published: June 2022

AbstractWhile psychological distress is a common sequelae of job loss, how that relationship continued during the COVID‐19 pandemic is unclear, for example, given higher health risk to working due to disease exposure. This paper examines changes in psychological distress depending on job loss among a cohort of randomly selected residents living in nine predominantly African American low‐income neighborhoods in Pittsburgh PA across four waves between 2013 and 2020. Between 2013 and 2016, we found an increase in psychological distress after job loss in line with the literature. In contrast, between 2018 and 2020 we found change in psychological distress did not differ by employment loss. However, residents who had financial concerns and lost their jobs had the largest increases in psychological distress, while residents who did not have serious financial concerns—potentially due to public assistance—but experienced job loss had no increase in distress, a better outcome even than those that retained their jobs. Using partial identification, we find job loss during the pandemic decreased psychological distress for those without serious financial concerns. This has important policy implications for how high‐risk persons within low‐income communities are identified and supported, as well as what type of public assistance may help.
Are European commercial banks more profitable than cooperative banks? Evidence from a low interest rate environment
Authors: Kuc Matěj , Teplý Petr 
Published: June 2022

AbstractOur aim is to compare empirically the profitability of European cooperative and commercial banks in a low interest rate environment. We employ dynamic panel data methods on a data set of nearly 1000 banks from 11 European countries where both ownership structures compete on the same market. We observed different banking strategies during the 2009–2015 period, when market interest rates reached an all‐time low. Our analysis produced four main conclusions. First, we find that commercial banks maintain superior profitability over cooperative banks in an environment of low interest rates. Second, commercial banks unjustifiably decreased their loan loss provisioning in a low interest rate environment in order to maintain their profitability. This trend is not present in cooperative banks. Third, decreased provisioning is present mainly in smaller institutions. Fourth, cooperative banks are significantly more stable than commercial banks in terms of their Z‐score in a low interest rate environment. This finding is in line with existing findings during normal interest rates. In addition, the Z‐score of cooperative banks increased during the observation period, whereas the Z‐score of commercial banks remained stable. Our findings survive a battery of robustness checks. Our results also show differences in the strategies and priorities of both competing ownership types in a low interest rate environment: commercial banks focus on maintaining their profitability by decreasing loan loss provisions, whereas cooperative banks seek to increase their stability. Therefore, regulators pursuing stability in a low interest rate environment should focus on the credit risk management of small commercial banks.
Repairing attachment in families with depressed adolescents: A task analysis
Authors: Stern Richard S. , King Ashley A. , Diamond Guy 
Published: June 2022

AbstractAimsThis exploratory pilot study (N = 3 sessions, 793 speech units) used task analysis to refine an early model of the attachment task in attachment‐based family therapy (ABFT). The attachment task aims to repair long‐standing parent–adolescent relational ruptures that inhibit parents from being a resource for adolescents recovering from depression and/or suicidality.MethodsVideo recordings of three attachment task sessions with strong adherence to the model were selected for intensive study. Two sessions were rated as successful (i.e., attachment was repaired) and one as unsuccessful (i.e., attachment repair did not occur). Sessions were then coded using Structural Analysis of Social Behavior (SASB).ResultsThe current SASB analysis provided empirical support for our previous clinical impression that the task involves three parts: (I) adolescent disclosure of attachment rupture, (II) parent disclosure, and (III) a more mutual conversation. SASB also provided insights into more subtle elements of the model.ConclusionSuccessful attachment sessions were associated with high parent affiliation and autonomy—both while affirming the adolescent's story and when disclosing their own experience. Unsuccessful task attempts were associated with parental enmeshment and hostile belittling, blaming, and distancing. An enhanced model of ideal parent behaviors during the attachment task is offered, including space for parent disclosure—perhaps even apology—that is both warm and independent, leading to a more mutual parent–adolescent conversation. Clinically, the findings support the importance of the therapist focusing on the process and quality of parent–child interactions to facilitate attachment repair.
Envisioning the manureshed: Toward comprehensive integration of modern crop and animal production
Authors: Kleinman Peter J. A. , Spiegal Sheri A. , Silviera Maria L. , Baker John M. , Dell Curtis J. , Bittman Shabtai , Cibin Raj , Vadas Peter A. , Buser Michael D. , Tsegaye Teferi 
Published: June 2022

AbstractThe specialization and intensification of agriculture have produced incredible gains in productivity, quality, and availability of agricultural commodities but have resulted in the separation of crop and animal production. A by‐product of this separation has been the accumulation of manure regions where animal production is concentrated. Enter the “manureshed,” an organizing framework for integrating animal and crop production where budgeting of manure nutrients is used to strategically guide their recycling and reuse in agricultural production systems where manure resources are of highest value. To move beyond regional nutrient balance analyses into the transformational realm required to mitigate “wicked” manure problems, manureshed management requires recognition of the challenges to systematically reorganizing resource flows. In better integrating crop and livestock systems, manureshed management must account for the unique nature of managing manure nutrients within individual livestock industries, anticipate trade‐offs in substituting manure for commercial fertilizer, promote technologies to refine manure, and engage extensive social networks across scales that range from the farmgate to nation and beyond.
Modulation of western North Pacific tropical cyclone formation by central Pacific El Niño–Southern Oscillation on decadal and interannual timescales
Authors: Song Jinjie , Klotzbach Philip J. , Wei Na , Duan Yihong 
Published: June 2022

AbstractThis study investigates the impact of central Pacific (CP) El Niño–Southern Oscillation (ENSO) on tropical cyclone (TC) frequency over the western North Pacific (WNP) on decadal and interannual timescales. The CP ENSO‐TC frequency relationship is strong and significant only on decadal timescales, with enhanced TC formation over most of the WNP associated with warm CP ENSO phases. TC formation changes, driven by CP ENSO, exhibit a southeast–northwest dipole pattern on interannual timescales, similar to the typical pattern induced by eastern Pacific ENSO. Associated with warm CP ENSO phases on decadal timescales are increases in TC formation east of 125°E, while increases in TC formation east of 140°E are observed with warm CP ENSO phases on interannual timescales. These increases in TC activity are primarily caused by favourable dynamic conditions, including increased 850‐hPa relative vorticity and 200‐hPa divergence and decreased 850–200‐hPa vertical wind shear. The main TC formation difference on decadal and interannual timescales is concentrated over the longitudinal band of 125°–140°E, where reduced TC formation is observed on interannual timescales during CP El Niño years, predominately due to suppressed thermodynamic factors, for example, reduced maximum potential intensity and 700–500‐hPa relative humidity. We find insignificant (significant) changes in thermodynamic conditions between 125°E and 140°E due to weak (strong) descending motion in the western cell of the anomalous Walker circulation on decadal (interannual) timescales. This can be explained by different patterns of CP ENSO‐induced sea surface temperature anomalies on different timescales.
Effects of multi‐temporal environmental variables on SOC spatial prediction models in coastal wetlands of a Chinese delta
Authors: Xu Yiming , Li Bin , Bai Junhong , Zhang Guangliang , Wang Xin , Smith Scot E. , Du Shudong 
Published: June 2022

AbstractMapping soil organic carbon (SOC) distributions in coastal wetlands plays an important role in assessing ecosystem services and investigating the global carbon cycle. Little research has explored the effects of environmental variables with seasonal variations on digital soil mapping (DSM). Our research utilized machine learning methods and established multiple prediction models of SOC based on multi‐temporal data from dry and wet seasons, and mono‐temporal data from April. The results showed that the relationships between SOC and environmental variables in different months varied significantly in coastal wetlands of the Yellow River Delta (YRD). In general, the environmental variables in the wet season showed stronger correlations and higher importance scores with SOC compared with those in the dry season. In addition, SOC prediction models in wet season and April had stronger prediction performance compared with those in the dry season. As a result, data fusion of multi‐temporal data did not necessarily contribute to the model performance enhancement. Relative homogenous soil‐landscape attributes and spectral characteristics in dry season could not accurately explain the strong spatial variation of SOC in this area, and it might be the major reason that caused the stronger model performance of soil prediction models in wet season than those in dry season. Therefore, the accurate spatial prediction of soil properties requires the characterization of the seasonal dynamics of soil‐landscape relationships. In general, the findings of this research demonstrated that seasonal variation of environmental variables should be considered in the establishment of a DSM model in coastal wetland.
Development of a microstructured tissue phantom with adaptable optical properties for use with microscopes and fluorescence lifetime imaging systems
Authors: Freymüller Christian , Ströbl Stephan , Aumiller Maximilian , Eisel Maximilian , Sroka Ronald , Rühm Adrian 
Published: June 2022

AbstractObjectivesFor the development and validation of diagnostic procedures based on microscopic methods, knowledge about the imaging depth and achievable resolution in tissue is crucial. This poses the challenge to develop a microscopic artificial phantom focused on the microscopic instead of the macroscopic optical tissue characteristics.MethodsAs existing artificial tissue phantoms designed for image forming systems are primarily targeted at wide field applications, they are unsuited for reaching the formulated objective. Therefore, a microscopy‐ and microendoscopy‐suited artificial tissue phantom was developed and characterized. It is based on a microstructured glass surface coated with fluorescent beads at known depths covered by a scattering agent with modifiable optical properties. The phantom was examined with different kinds of microscopy systems in order to characterize its quality and stability and to demonstrate its usefulness for instrument comparison, for example, regarding structural as well as fluorescence lifetime analysis.ResultsThe analysis of the manufactured microstructured glass surfaces showed high regularity in their physical dimensions in accordance with the specifications. Measurements of the optical parameters of the scattering medium were consistent with simulations. The fluorescent beads coating proved to be stable for a respectable period of time (about a week). The developed artificial tissue phantom was successfully used to detect differences in image quality between a research microscope and an endoscopy based system. Plausible causes for the observed differences could be derived based on the well known microstructure of the phantom.ConclusionsThe artificial tissue phantom is well suited for the intended use with microscopic and microendoscopic systems. Due to its configurable design, it can be adapted to a wide range of applications. It is especially targeted at the characterization and calibration of clinical imaging systems that often lack extensive positioning capabilities such as an intrinsic z‐stage.
Solving the Dichotomy between Self‐Healing and Mechanical Properties in Rubber Composites by Combining Reinforcing and Sustainable Fillers
Authors: Araujo‐Morera Javier , Utrera‐Barrios Saul , Doral Olivares Raúl , Reyes Verdugo Manzanares María de los , López‐Manchado Miguel Ángel , Verdejo Raquel , Hernández Santana Marianella 
Published: June 2022

AbstractThe dichotomy between mechanical performance and repairability is a well‐known fact in the self‐healing field. One alternative to overcome this trade‐off is the inclusion of reinforcing fillers. In this research, hybrid reinforced self‐healing styrene‐butadiene rubber (SBR) composites are developed by combining mechano‐chemically modified ground tire rubber (mGTR) with carbon black (CB). The SBR matrix is systematically analyzed by means of dynamic mechanical analysis and broadband dielectric spectroscopy. The SBR composite reinforced with 20 phr mGTR and 20 phr CB maintains the healing efficiency of the unfilled SBR (80%) and improves its tensile strength by 300%, balancing perfectly well both properties. The healing efficiency is determined at different damage levels. The damage at the microscopic scale is easier to recover and does not depend on the presence of fillers, while the recovery at the macroscopic level clearly relies on the addition of filler, with more demanding healing conditions.
A novel sequential‐phase quad‐feed circularly polarized microstrip antenna for INMARSAT and GPS applications
Authors: Fu Shiqiang , Liu Lu , Li Chanjuan , Wang Zhongbao 
Published: June 2022

AbstractIn this letter, a compact circularly polarized microstrip antenna has been developed with a new type of feed structure. The key feature of the antenna is the integrated design of the quad‐feed network coplanar with the driven patch, which makes the antenna simple in structure and has good circular polarization performance. A parasitic patch is used to expand the impedance bandwidth, while a round hole in the center of the driven patch is used to improve impedance matching. In addition, a cavity is utilized to reduce the transverse size of the antenna and improve the front‐to‐back ratio. The simulation and experimental results show that the VSWR of the antenna is lower than 1.5 and the average gain is higher than 8dBic in the L‐band for International Maritime Satellite applications. Due to the centrosymmetric feed configuration, the antenna can also be used as a global positioning system antenna, which requires high stability of the phase center.
Acid‐base disorders: A primer for clinicians
Authors: Tucker Anne M. , Johnson Tami N. 
Published: June 2022

AbstractAn understanding of acid‐base physiology is necessary for clinicians to recognize and correct problems that may negatively affect provision of nutrition support and drug therapy. An overview of acid‐base physiology, the different acid‐base disorders encountered in practice, a stepwise approach to evaluate arterial blood gases, and other key diagnostic tools helpful in formulating a safe and effective medical and nutrition plan are covered in this acid‐base primer. Case scenarios are also provided for the application of principles and the development of clinical skills.
ASAP‐MS and DART‐MS as ancillary tools for direct analysis of the lichen metabolome
Authors: Ollivier Simon , Jéhan Philippe , Lambert Fabian , Olivier‐Jimenez Damien , Boustie Joël , Lohézic‐Le Dévéhat Françoise , Le Yondre Nicolas 
Published: June 2022

AbstractIntroductionLichens contain unique metabolites that most often need to be characterized from a limited amount of material. While thin layer chromatography is still the preferred analysis method for most lichenologists, liquid chromatography gives a deeper insight in the lichen metabolome, but an extractive step is needed before any analysis. Therefore, ambient ionization mass spectrometry (MS) analysis of lichen samples using Atmospheric Solid Analysis Probe (ASAP) and Direct Acquisition in Real Time (DART) techniques is evaluated.ObjectiveWe looked for a faster method to screen the metabolome by disrupting the classical workflow of analysis.MethodsFour lichens selected for their metabolic diversity were analyzed with MS; namely Evernia prunastri, Lichina pygmaea, Parmelia saxatilis, and Roccella fuciformis. ASAP and DART analyses were compared against the reference electrospray ionization with a bioinformatic process including Van Krevelen diagrams as well as the multivariate comparison of the ionization methods in positive and negative modes.ResultsMetabolite profiles obtained from DART and ASAP analyses of lichen samples are consistent with classical analyses of lichen extracts. Through an easy and rapid experiment and without any extraction solvent, a large and informative profile of lichen metabolites is obtained when using complementary ionization modes of these high resolution mass spectrometry methods.ConclusionASAP‐MS and DART‐MS are two ancillary methods that provide a comprehensive evaluation of the lichen metabolome.