bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal Formula of Angelica sinensis Ameliorates Memory Deficits in β-amyloid Protein-induced Alzheimer’s Disease Rat Model
Authors: Wang Hu-ping , Wu Hong-yan , Ma Chun-lin , Zeng Qing-tao , Zhu Kai-min , Cui Shu-mei , Li Hai-long , Wu Guo-tai , Wu Zhi-wei , He Jian-zheng 
Published: February 2022

Abstract
Objective
Angelica (A.) sinensis is used as a traditional medical herb for the treatment of neurodegeneration, aging, and inflammation in Asia. A. sinensis optimal formula (AOF) is the best combination in A. sinensis that has been screened to rescue the cognitive ability in β-amyloid peptide (Aβ25–35)-treated Alzheimer’s disease (AD) rats. The objective of this study was to investigate the effect of AOF on the learning and memory of AD rats as well as to explore the underlying mechanisms.

Methods
Male Wistar rats were infused with Aβ25–35 for AD model induction or saline (negative control). Five groups of AD rats were fed on AOF at 20, 40, or 80 mL/kg every day, donepezil at 0.9 mg/kg every day (positive control), or an equal volume of water (AD model) intragastrically once a day for 4 weeks, while the negative control rats were fed on water. The Morris water maze test was used to evaluate the cognitive function of the rats. The Aβ accumulation, cholinergic levels, and antioxidative ability were detected by ELISA. Additionally, the candidate mechanism was determined by gene sequencing and quantitative real-time polymerase chain reaction.

Results
The results showed that AOF administration significantly ameliorated Aβ25–35-induced memory impairment. AOF decreased the levels of amyloid-β precursor protein and Aβ in the hippocampus, rescued the cholinergic levels, increased the activity of superoxide dismutase, and decreased the malondialdehyde level. In addition, AOF inhibited the expression of IL1b, Mpo, and Prkcg in the hippocampus.

Conclusion
These experimental findings illustrate that AOF prevents the decrease in cognitive function and Aβ deposits in Aβ25–35-treated rats via modulating neuroinflammation and oxidative stress, thus highlighting a potential therapeutic avenue to promote the co-administration of formulas that act on different nodes to maximize beneficial effects and minimize negative side effects.
A scoping review of patient safety research carried out in the Republic of Ireland
Authors: O’Connor Paul , O’Malley Roisin , Kaud Yazeed , Pierre Emily St. , Dunne Rosie , Byrne Dara , Lydon Sinéad 
Published: February 2022

AbstractMaintaining the highest levels of patient safety is a priority of healthcare organisations. However, although considerable resources are invested in improving safety, patients still suffer avoidable harm. The aims of this study are: (1) to examine the extent, range, and nature of patient safety research activities carried out in the Republic of Ireland (RoI); (2) make recommendations for future research; and (3) consider how these recommendations align with the Health Service Executive’s (HSE) patient safety strategy. A five-stage scoping review methodology was used to synthesise the published research literature on patient safety carried out in the RoI: (1) identify the research question; (2) identify relevant studies; (3) study selection; (4) chart the data; and (5) collate, summarise, and report the results. Electronic searches were conducted across five electronic databases. A total of 31 papers met the inclusion criteria. Of the 24 papers concerned with measuring and monitoring safety, 12 (50%) assessed past harm, 4 (16.7%) the reliability of safety systems, 4 (16.7%) sensitivity to operations, 9 (37.5%) anticipation and preparedness, and 2 (8.3%) integration and learning. Of the six intervention papers, three (50%) were concerned with education and training, two (33.3%) with simplification and standardisation, and one (16.7%) with checklists. One paper was concerned with identifying potential safety interventions. There is a modest, but growing, body of patient safety research conducted in the RoI. It is hoped that this review will provide direction to researchers, healthcare practitioners, and health service managers, in how to build upon existing research in order to improve patient safety.
A machine learning model based on readers’ characteristics to predict their performances in reading screening mammograms
Authors: Gandomkar Ziba , Lewis Sarah J. , Li Tong , Ekpo Ernest U. , Brennan Patrick C. 
Published: February 2022

Abstract
Objectives
Proposing a machine learning model to predict readers’ performances, as measured by the area under the receiver operating characteristics curve (AUC) and lesion sensitivity, using the readers’ characteristics.

Methods
Data were collected from 905 radiologists and breast physicians who completed at least one case-set of 60 mammographic images containing 40 normal and 20 biopsy-proven cancer cases. Nine different case-sets were available. Using a questionnaire, we collected radiologists’ demographic details, such as reading volume and years of experience. These characteristics along with a case set difficulty measure were fed into two ensemble of regression trees to predict the readers’ AUCs and lesion sensitivities. We calculated the Pearson correlation coefficient between the predicted values by the model and the actual AUC and lesion sensitivity. The usefulness of the model to categorize readers as low and high performers based on different criteria was also evaluated. The performances of the models were evaluated using leave-one-out cross-validation.

Results
The Pearson correlation coefficient between the predicted AUC and actual one was 0.60 (p < 0.001). The model’s performance for differentiating the reader in the first and fourth quartile based on the AUC values was 0.86 (95% CI 0.83–0.89). The model reached an AUC of 0.91 (95% CI 0.88–0.93) for distinguishing the readers in the first quartile from the fourth one based on the lesion sensitivity.

Conclusion
A machine learning model can be used to categorize readers as high- or low-performing. Such model could be useful for screening programs for designing a targeted quality assurance and optimizing the double reading practice.
Uncovering the digitalization impact on consumer decision-making for checking accounts in banking
Authors: Dehnert Maik , Schumann Josephine 
Published: February 2022

AbstractChecking account providers must understand the importance of digital and non-digital service attributes across different customer segments to achieve a product-market fit in digitalization. In particular, various latent personal characteristics influence customer choices in digital banking. However, there is only limited research on banking customer behavior beyond the technology acceptance model, and none that explores customer preferences for checking accounts experimentally. Against this background, we present the results of a discrete choice experiment on customer preferences towards checking accounts in Germany. The outcome of the paper is a detailed quantitative assessment of the relationships between checking account service attributes and a set of latent influencing factors on choice. While customer service experience, the scope of services, and professional expertise are identified as re-occurring critical aspects for customers when choosing their banking service provider, the type of provider and digital product innovation showed little impact on customer choice overall. In multigroup analyses, we reveal the moderating impact of influencing factors on the preference of checking account service attributes. Additional segmentation analyses point to six customer segments from which four still prefer a traditional operating model. The largest segment of traditional product-innovative customers prefers digitalized, i.e., data-driven checking accounts in a mixed-mode with human customer advisory and on-site branch services from a traditional bank. At the other end of the spectrum, a small innovative Fintech customer segment, influenced by non-pragmatism and social norms, prefers a purely digital operating model with data-driven applications in banking.
Informal ready-to-eat food vending: a social practice perspective on urban food provisioning in Nigeria
Authors: Adeosun Kehinde Paul , Greene Mary , Oosterveer Peter 
Published: February 2022

AbstractThe way people access food in Nigeria is of central relevance for food security, health and sustainability. One key trend is the shift from household-based to primarily out-of-home food consumption as an increasing majority of the urban poor derive their daily nutrient intake from street foods. However, few studies have yet explored the role of the ready-to-eat food vending sector in urban food systems and the diets of the urban poor. This paper investigates the interrelations between these practices and the diversity of food groups provisioned among the urban poor in developing city contexts. A social practice approach is employed to explore differentiation among informal-ready-to-eat food vending practices in the city of Ibadan, Nigeria, in terms of their daily activities, competences and resources. Applied methods include GIS mapping, food log diaries, in-depth interviews and participant observation to map and classify informal-ready-to-eat food vending practices according to the nature of food provisioned and explore the everyday performances of different informal-ready-to-eat food vending practice initiatives and their relation to dietary diversity. The results reveal three key categories among these practices: traditional, processed and unprocessed—with varying levels of diversity in the food groups on offer. Traditional food vendors offer more diversified food compared to processed food vendors and unprocessed food vendors. The results reveal that material infrastructure, cooking bargaining and purchasing skills and nutritional knowledge are key to the diversity of food groups provisioned. The paper concludes by considering the wider relevance of these findings for urban food science and policy.
Zein and lignin-based nanoparticles as soybean seed treatment: translocation and impact on seed and plant health
Authors: Kacsó Tímea , Hanna Eban A. , Salinas Fallon , Astete Carlos E. , Bodoki Ede , Oprean Radu , Price Paul P. , Doyle Vinson P. , Bonser Colin A. R. , Davis Jeffrey A. , Sabliov Cristina M. 
Published: February 2022

AbstractZein nanoparticles (ZNPs) were synthesized with a cationic surfactant, didodecyldimethylammonium bromide (122.9 ± 0.8 nm, + 59.7 ± 4.4 mV) and a non-ionic surfactant, Tween 80 (118.7 ± 1.7 nm, + 26.4 ± 1.1 mV). Lignin-graft-poly(lactic-co-glycolic) acid nanoparticles (LNPs) were made without surfactants (52.9 ± 0.2 nm, − 54.9 ± 0.5 mV). Both samples were applied as antifungal seed treatments on soybeans, and their impact on germination and plant health was assessed. Treated seeds showed high germination rates (> 90% for all treatment groups), similar to the control group (100%). Root and stem lengths and the dry biomass of treated seeds were not statistically distinguishable from the control. Foliage from seed-treated plants was fed to larvae of Chrysodeixis includens with no differences in mortality between treatments. No translocation of fluorescently tagged particles was observed with fluorescence microscopy following seed treatment and germination. Nano-delivered azoxystrobin provided ~ 100% protection when LNPs were used. Results suggest ZNPs and LNPs are safe and effective delivery systems of active compounds for seed treatments.
Statistical properties of the MetaCore network of protein–protein interactions
Authors: Kotelnikova Ekaterina , Frahm Klaus M. , Lages José , Shepelyansky Dima L. 
Published: February 2022

AbstractThe MetaCore commercial database describes interactions of proteins and other chemical molecules and clusters in the form of directed network between these elements, viewed as nodes. The number of nodes goes beyond 40 thousands with almost 300 thousands links between them. The links have essentially bi-functional nature describing either activation or inhibition actions between proteins. We present here the analysis of statistical properties of this complex network applying the methods of the Google matrix, PageRank and CheiRank algorithms broadly used in the frame of the World Wide Web, Wikipedia, the world trade and other directed networks. We specifically describe the Ising PageRank approach which allows to treat the bi-functional type of protein–protein interactions. We also show that the developed reduced Google matrix algorithm allows to obtain an effective network of interactions inside a specific group of selected proteins. In addition to already known direct protein–protein interactions, this method allows to infer non trivial and unknown interactions between proteins arising from the summation over all the indirect pathways passing via the global bi-functional network. The developed analysis allows to establish an average action of each protein being more oriented to activation or inhibition. We argue that the described Google matrix analysis represents an efficient tool for investigation of influence of specific groups of proteins related to specific diseases.
Inversion of damage inducement of wharf pile foundation under heaped load based on parametric model
Authors: Zuo Liangdong , Cao Shibao , Zhou Shiliang , Wu Jun 
Published: February 2022

Abstract
Uneven stowage of wharf is one of the main external loads during its service period. The main load-bearing structure of the overhead vertical wharf is the lower pile foundation. Under the action of the upper pile load, the pile foundation will be damaged to varying degrees, and the local damage may cause adverse effects on the overall structural safety of the wharf. In order to realize the inversion analysis of the adverse damage inducement of wharf stowage, the stress detection results of the lower pile foundation are taken as inversion data samples, and 10,000 sets of stress data are obtained by establishing a parameterized numerical calculation model. After normalization and dimension reduction, they are input into the established neural network model, and the action position and strength of stowage damage inducement are identified. The results show that the inversion analysis samples obtained by the parameterized model in this paper have higher accuracy and generalization in the calculation of neural network model.

Article Highlights

The difference of recognition indexes between training samples and test samples is small, and there is no lack of fitting ability, and the generalization ability is strong.

The regression learner network has two hidden layers, and the number of nodes is 10 and 4, respectively. The parameter setting with the activation function as identity can meet the inversion needs of the heap damage inducement.

Inversion calculation of wharf damage incentives needs to establish samples with large data space, while materialization model calculation takes up a lot of computer memory and takes time.
An adaptive fuzzy PID controller for speed control of brushless direct current motor
Authors: Wang Tingting , Wang Hongzhi , Hu Huangshui , Lu Xiaofan , Zhao Siyuan 
Published: February 2022

AbstractAiming at the problems of the poor adaptive ability in the current control methods for brushless DC motor, an adaptive fuzzy proportional integral derivative controller (AFPID) is proposed to realize the better control performance of speed for brushless DC motor. AFPID includes a conventional PID controller (C-PID) and PI + PD architectures with a configurable fuzzy logic controller (C-PID-FLC). The FLC in C-PID-FLC consists of two fuzzy inference engines, one is used to self-tune the parameters for PI control, the other is for the scaling factor self-tuning of PI control parameters. The PD structure in C-PID-FLC is mainly to reduce oscillation, overcome overshoot and speed up system response while effectively eliminating static errors. When the system reaches a certain stable state of rotation, AFPID adjusts the C-PID controller ground on the speed error, which saves control costs under the premise of ensuring control performance. AFPID adaptively realizes the respective advantages of C-PID and C-PID-FLC. Compared with other control methods, the merits of the proposed controller are highlighted. The results show that the AFPID controller has a better control performance regardless of changes in load disturbance and parameter variations. And through the change of mechanical parameters of brushless DC motor, the sensitivity of AFPID is analyzed.
The COVID-19 emergency as an opportunity to co-produce an innovative approach to health services provision: the women's antenatal classes move on the web
Authors: Bonciani Manila , Corazza Ilaria , De Rosis Sabina 
Published: February 2022

AbstractThe COVID-19 pandemic has strongly affected healthcare organizations, leading to the need for reorganizing also maternal care services during pregnancy. The Regional Health Authorities in Tuscany (Italy) promoted the creation of online antenatal classes (ACs). This study illustrates the innovative approach to deliver ACs online and discusses how the collaborative approach in co-producing this innovative solution co-creates value in healthcare. The action research design was based, on one hand, on the indirect involvement of users by analyzing qualitative data collected through a continuous survey to pregnant women and, on the other one, on the direct involvement of managers and health professionals in meetings and workshops. The authors encompassed all necessary changes in organizational practices and facilitated the collaborative process implementation and analysis. The main findings are that moving ACs online has been a relevant choice, since the need of pregnant women to share information and receive emotional support increased in times of crisis. Additionally, in the perspective of health professionals, the new online ACs model emerged as a valuable solution not only for the contingent situation, but also in a long-term perspective to reach more women during pregnancy and to early support them throughout the maternal care pathway. This study shows that the collaborative approach to co-innovate healthcare services provision, such as with ACs online, facilitates the creation of, long-lasting, and integrated solutions in healthcare, to be used also after pandemic period. Finally, despite this action-research is context-specific, the findings presented in this paper may help other healthcare organizations innovate their own strategies in ACs’ provision.
Microbiome engineering and plant biostimulants for sustainable crop improvement and mitigation of biotic and abiotic stresses
Authors: Lau Su-Ee , Teo Wee Fei Aaron , Teoh Ee Yang , Tan Boon Chin 
Published: February 2022

AbstractGlobally, despite the intense agricultural production, the output is expected to be limited by emerging infectious plant diseases and adverse impacts of climate change. The annual increase in agricultural output to sustain the human population at the expense of the environment has exacerbated the current climate conditions and threatened food security. The demand for sustainable agricultural practice is further augmented with the exclusion of synthetic fertilizers and pesticides. Therefore, the application of plant microbiome engineering and (natural) biostimulants has been at the forefront as an environment-friendly approach to enhance crop production and increase crop tolerance to adverse environmental conditions. In this article, we explore the application of microbiome engineering and plant biostimulants as a sustainable approach to mitigating biotic and abiotic stresses and improving nutrient use efficiency to promote plant growth and increase crop yield. The advancement/understanding in plant-biostimulant interaction relies on the current scientific research to elucidate the extent of benefits conferred by these biostimulants under adverse conditions.
Ozone‐Forced Southern Annular Mode During Antarctic Stratospheric Warming Events
Authors: Jucker M. , Goyal R. 
Published: February 2022

AbstractSouthern Hemisphere (SH) Stratospheric Warming Events (SWEs) are usually associated with a negative phase of the tropospheric Southern Annular Mode (SAM) during the following summer. In contrast, using ensemble climate model simulations we show that the anomalously high ozone concentrations typically occurring during SWEs can force periods of persistent positive tropospheric SAM in austral spring by increasing lower stratospheric static stability and changing troposphere‐to‐stratosphere wave propagation. Eventually, the tropospheric SAM switches sign to its negative phase in late spring/early summer, but this ‘downward propagation’ of the stratospheric signal does not occur in simulations without seasonal cycle. We find that the downward propagation is forced both dynamically by adiabatic heating and radiatively by increased shortwave absorption by ozone due to the seasonal cycle. Capturing this ozone forcing mechanism in models requires the inclusion of interactive ozone, which has important implications for the predictive skill of current seasonal forecasting systems.
The Extraordinary Equatorial Atlantic Warming in Late 2019
Authors: Richter Ingo , Tokinaga Hiroki , Okumura Yuko M. 
Published: February 2022

AbstractSea‐surface temperatures (SSTs) in the eastern equatorial Atlantic are subject to variability on interannual timescales but during the last 20 years, this variability has shown comparatively little activity. In late 2019, however, the warmest event in the satellite observation period developed. Analysis suggests that zonal wind stress anomalies in the western equatorial Atlantic contributed to the development of the warm SST anomalies. Furthermore, wind stress curl anomalies north of the equator generated downwelling Rossby waves that propagated to the western boundary and were reflected into downwelling Kelvin waves that helped to precondition the event. Neither the contemporaneous positive Indian Ocean Dipole nor the El Niño Modoki appears to have contributed substantially to the Atlantic warming, though some uncertainty remains. Based on large‐scale multidecadal variability patterns, a return to enhanced variability is not imminent but careful monitoring will be important.
First Observations of G‐Band Radar Doppler Spectra
Authors: Courtier Benjamin M. , Battaglia Alessandro , Huggard Peter G. , Westbrook Chris , Mroz Kamil , Dhillon Ranvir S. , Walden Christopher J. , Howells Gareth , Wang Hui , Ellison Brian N. , Reeves Richard , Robertson Duncan A. , Wylde Richard J. 
Published: February 2022

AbstractThe first Doppler spectra ever acquired by an atmospheric radar at 200 GHz (G‐band) are presented. The observations were taken during a light precipitation event in May (rain rates <2 mm hr−1) at Chilbolton Observatory, UK, with coincident Ka‐band and W‐band Doppler radar measurements. The collected rain spectra agree with Mie theory predictions: at G‐band they show significant reductions in the spectral power return—as compared to theoretical Rayleigh scattering—corresponding to high Doppler velocities (i.e., large raindrops) with the presence of multiple peaks and “Mie notches” in correspondence to the maxima and minima of the raindrop backscattering cross sections. The first two G‐band Mie troughs correspond to smaller velocities/sizes than the first W‐band Mie notch. These features offered by G‐band radars pave the way toward applying, in rain, Mie notch vertical wind retrievals and multifrequency drop size distribution microphysical retrievals to smaller rain rates and smaller characteristic sizes than ever before.