bluuebunny/crossref_metadata_2025_split huggingface dataset:
Climate change and modernization drive structural realignments in European grain production
Authors: Pinke Z. , Decsi B. , Jámbor A. , Kardos M. K. , Kern Z. , Kozma Z. , Ács T. 
Published: May 2022

AbstractCharting the long-term trends in European wheat and maize yields and harvested areas and the relation of yields to climatic and economic drivers, two profound spatial processes become apparent. One consequence of the relatively late modernization of Eastern Europe has been to shift the focus of grain production from West to East. The warming trend prevailing over the past decades in the summer and winter seasons has been accompanied by a South to North shift in the harvested areas. The combination of these two processes has meant that the north-eastern sector of the European grain chessboard has emerged as the main beneficiary. There, the relatively low sensitivity of cereals to climatic change plus high economic growth rates have been accompanied by the most dynamic increases in cereal yields on the continent. As a result, a modern version of the 3000 year-old grain distribution system of the Ancient World is being restored before our eyes. One noteworthy finding is that increasing January–March temperatures have had a significant positive impact on wheat yields from Northern to South-Eastern Europe, and this is, at least in part, compensating for the negative impact of summer warming.
Non-circularly shaped conical diffraction
Authors: Iqbal Muhammad Waqar , Marsal Nicolas , Montemezzani Germano 
Published: May 2022

AbstractWaves with tailored shape and vectorial non-homogeneous polarization are of much interest due to the many prospects for relevant applications in the classical and quantum domains. Such vector beams can be generated naturally via conical diffraction in optically biaxial crystals. The recent strongly revived attention to this phenomenon is motivated by modern applications such as optical trapping, polarimetry or super-resolution imaging, partly enabled by new configurations increasing the beam complexity, like those with several crystals in cascade. However, up to now all beams generated by conical diffraction conserve at their sharpest plane the underlying circular shape connected with the planar section of light cones. Here we show that a proper manipulation in wave-vector space within a conical diffraction cascade produces vector beams with highly peculiar non-circular forms, leading to an interesting and reconfigurable platform for easily shaping all structured wave properties, increasing complexity and information content. The experimental observations are confirmed by numerical integration of a paraxial model incorporating the effects of the wave-vector space manipulation.
Rabies prevention practices and associated factors among household heads in Bure Zuria district, North West Ethiopia
Authors: Wolelaw Gedamu Ayalew , Yalew Worku Awoke , Azene Abebaw Gedef , Wassie Gizachew Tadesse 
Published: May 2022

AbstractRabies is a zoonotic viral disease that can occur in all warm blooded animals including humans. Vaccinating dogs can protect people from contracting rabies. Despite the availability of effective human and animal rabies vaccines, rabies prevention and control efforts are inadequate. The aim of the study was to determine the level of rabies prevention practices and associated factors among household heads in Bure Zuria district, North-west Ethiopia. Community based cross-sectional study was conducted at Bure Zuria from June 1 to 30, 2020. A total of 609 participants were selected using simple random sampling technique. Simple and multiple binary logistic regressions were applied to identify associated factors of rabies prevention practices. Of 609 participants, 413 (67.8%) were male and 289 (47.5%) were 30–45 years old. The level of good prevention practices of rabies at Bure Zuria district was 43.3%. Being males (AOR = 2.69 (1.72–4.22)), age group 18–29 years (AOR = 2.70 (1.20–6.10)), ever bitten by dog, (AOR = 2.40 (1.56–3.68)), got training (AOR = 1.70 (1.08–2.68)), had dog (AOR = 2.92 (1.62–5.26)), with good knowledge AOR (95% CI) = 3.42 (2.19–5.32), with good attitude AOR (95% CI) = 1.78 (1.16–2.73) and have 1001–2000 AOR (95% CI) = 2.29 (1.39–3.79) and > 2000 AOR (95% CI) = 2.02 (1.28–3.18)) monthly income were more likely to have good prevention practices of rabies. In this study, we found that the level of good prevention practices of rabies was low in Bure Zuria district. Therefore; awareness creation trainings and multi-sectoral collaborations to prevent rabies are needed in the district, zone and at large region level.
Green synthesis of bimetallic Ag/ZnO@Biohar nanocomposite for photocatalytic degradation of tetracycline, antibacterial and antioxidant activities
Authors: Hosny Mohamed , Fawzy Manal , Eltaweil Abdelazeem S. 
Published: May 2022

AbstractIn this work, a simple and green synthesis procedure for phytofabrication Zinc oxide-silver supported biochar nanocomposite (Ag/ZnO@BC) via Persicaria salicifolia biomass is investigated for the first time to uphold numerous green chemistry such as less hazardous chemical syntheses. XRD technique showed the crystal structure of the phytosynthesized Ag/ZnO@BC, whereas UV–visible spectroscopy, FT-IR, SEM, EDX, TEM, and XPS analyses indicated the successful biosynthesis of the nanocomposite. Testing the photocatalytic potential of this novel nanocomposite in the removal of TC under different conditions unraveled its powerful photodegradation efficiency that reached 70.3% under the optimum reaction conditions: TC concentration; 50 ppm, pH; 6, a dose of Ag/ZnO@BC; 0.01 g, temperature; 25 °C, and H2O2 concentration; 100 mM. The reusability of Ag/ZnO@BC was evident as it reached 53% after six cycles of regeneration. Ag/ZnO@BC was also shown to be a potent antimicrobial agent against Klebsiella pneumonia as well as a promising antioxidant material. Therefore, the current work presented a novel nanocomposite that could be efficiently employed in various environmental and medical applications.
Application of pulse-modulated radio-frequency atmospheric pressure glow discharge for degradation of doxycycline from a flowing liquid solution
Authors: Dzimitrowicz Anna , Caban Magda , Terefinko Dominik , Pohl Pawel , Jamroz Piotr , Babinska Weronika , Cyganowski Piotr , Stepnowski Piotr , Lojkowska Ewa , Sledz Wojciech , Motyka-Pomagruk Agata 
Published: May 2022

AbstractDoxycycline (DOX), an antibiotic commonly used in medicine and veterinary, is frequently detected in natural waterways. Exposition of bacteria to DOX residuals poses a selective pressure leading to a common occurrence of DOX-resistance genetic determinants among microorganisms, including virulent human pathogens. In view of diminishment of the available therapeutic options, we developed a continuous-flow reaction-discharge system generating pulse-modulated radio-frequency atmospheric pressure glow discharge (pm-rf-APGD) intended for DOX removal from liquid solutions. A Design of Experiment and a Response Surface Methodology were implemented in the optimisation procedure. The removal efficiency of DOX equalling 79 ± 4.5% and the resultant degradation products were identified by High-Performance Liquid Chromatography–Diode Array Detection, Liquid Chromatography Quadruple Time of Flight Mass Spectrometry, Ultraperformance Liquid Chromatography–Tandem Mass Spectrometry, total organic carbon, total nitrogen, Attenuated Total Reflectance Furrier Transform–Infrared, and UV/Vis-based methods. The pm-rf-APGD-treated DOX solution due to the generated Reactive Oxygen and Nitrogen Species either lost its antimicrobial properties towards Escherichia coli ATCC25922 or significantly decreased biocidal activities by 37% and 29% in relation to Staphylococcus haemolyticus ATCC29970 and Staphylococcus aureus ATCC25904, respectively. Future implementation of this efficient and eco-friendly antibiotic-degradation technology into wastewater purification systems is predicted.
Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage
Authors: Tata Alessandra , Massaro Andrea , Riuzzi Giorgia , Lanza Ilaria , Bragolusi Marco , Negro Alessandro , Novelli Enrico , Piro Roberto , Gottardo Flaviana , Segato Severino 
Published: May 2022

AbstractMetabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.
Discrimination of secondary hypsarrhythmias to Zika virus congenital syndrome and west syndrome based on joint moments and entropy measurements
Authors: Rocha Priscila Lima , Silva Washington Luis Santos , da Silva Sousa Patrícia , da Silva Antônio Augusto Moura , Barros Allan Kardec 
Published: May 2022

AbstractHypsarrhythmia is a specific chaotic morphology, present in the interictal period of the electroencephalogram (EEG) signal in patients with West Syndrome (WS), a severe form of childhood epilepsy and that, recently, was also identified in the examinations of patients with Zika Virus Congenital Syndrome (ZVCS). This innovative work proposes the development of a computational methodology for analysis and differentiation, based on the time-frequency domain, between the chaotic pattern of WS and ZVCS hypsarrhythmia. The EEG signal time-frequency analysis is carried out from the Continuous Wavelet Transform (CWT). Four joint moments—joint mean—$$\mu _{(t,f)}$$

μ

(
t
,
f
)

, joint variance—$$\sigma _{(t,f)}^2$$

σ

(
t
,
f
)

2

, joint skewness—$$\lambda _{(t,f)}$$

λ

(
t
,
f
)

, and joint kurtosis—$$\kappa _{(t,f)}$$

κ

(
t
,
f
)

—and four entropy measurements—Shannon, Log Energy, Norm, and Sure—are obtained from the CWT to compose the representative feature vector of the EEG hypsarrhythmic signals under analysis. The performance of eight classical types of machine learning algorithms are verified in classification using the k-fold cross validation and leave-one-patient-out cross validation methods. Discrimination results provided 78.08% accuracy, 85.55% sensitivity, 73.21% specificity, and AUC = 0.89 for the ANN classifier.
Quantitative and qualitative analysis of pulmonary arterial hypertension fibrosis using wide-field second harmonic generation microscopy
Authors: Padrez Yaraslau , Golubewa Lena , Kulahava Tatsiana , Vladimirskaja Tatyana , Semenkova Galina , Adzerikho Igor , Yatsevich Olga , Amaegberi Nadezda , Karpicz Renata , Svirko Yuri , Kuzhir Polina , Rutkauskas Danielis 
Published: May 2022

AbstractWe demonstrated that wide-field second harmonic generation (SHG) microscopy of lung tissue in combination with quantitative analysis of SHG images is a powerful tool for fast and label-free visualization of the fibrosis pathogenesis in pulmonary arterial hypertension (PAH). Statistical analysis of the SHG images revealed changes of the collagen content and morphology in the lung tissue during the monocrotaline-induced PAH progression in rats. First order statistics disclosed the dependence of the collagen overproduction on time, the second order statistics indicated tightening of collagen fiber network around blood vessels and their spreading into the alveolar region. Fourier analysis revealed that enhancement of the fiber orientation in the collagen network with PAH progression was followed with its subsequent reduction at the terminating phase of the disease. Proposed approach has potential for assessing pulmonary fibrosis in interstitial lung disease, after lung(s) transplantation, cancer, etc.
Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder
Authors: Megerian Jonathan T. , Dey Sangeeta , Melmed Raun D. , Coury Daniel L. , Lerner Marc , Nicholls Christopher J. , Sohl Kristin , Rouhbakhsh Rambod , Narasimhan Anandhi , Romain Jonathan , Golla Sailaja , Shareef Safiullah , Ostrovsky Andrey , Shannon Jennifer , Kraft Colleen , Liu-Mayo Stuart , Abbas Halim , Gal-Szabo Diana E. , Wall Dennis P. , Taraman Sharief 
Published: May 2022

AbstractAutism spectrum disorder (ASD) can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the United States. This double-blinded, multi-site, prospective, active comparator cohort study tested the accuracy of an artificial intelligence-based Software as a Medical Device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral features from three distinct inputs (a caregiver questionnaire, analysis of two short home videos, and an HCP questionnaire) in a gradient boosted decision tree machine learning algorithm to produce either an ASD positive, ASD negative, or indeterminate output. This study compared Device outputs to diagnostic agreement by two or more independent specialists in a cohort of 18–72-month-olds with developmental delay concerns (425 study completers, 36% female, 29% ASD prevalence). Device output PPV for all study completers was 80.8% (95% confidence intervals (CI), 70.3%–88.8%) and NPV was 98.3% (90.6%–100%). For the 31.8% of participants who received a determinate output (ASD positive or negative) Device sensitivity was 98.4% (91.6%–100%) and specificity was 78.9% (67.6%–87.7%). The Device’s indeterminate output acts as a risk control measure when inputs are insufficiently granular to make a determinate recommendation with confidence. If this risk control measure were removed, the sensitivity for all study completers would fall to 51.6% (63/122) (95% CI 42.4%, 60.8%), and specificity would fall to 18.5% (56/303) (95% CI 14.3%, 23.3%). Among participants for whom the Device abstained from providing a result, specialists identified that 91% had one or more complex neurodevelopmental disorders. No significant differences in Device performance were found across participants’ sex, race/ethnicity, income, or education level. For nearly a third of this primary care sample, the Device enabled timely diagnostic evaluation with a high degree of accuracy. The Device shows promise to significantly increase the number of children able to be diagnosed with ASD in a primary care setting, potentially facilitating earlier intervention and more efficient use of specialist resources.
Functional role of the Frizzled linker domain in the Wnt signaling pathway
Authors: Ko Seung-Bum , Mihara Emiko , Park Yedarm , Roh Kyeonghwan , Kang Chanhee , Takagi Junichi , Bang Injin , Choi Hee-Jung 
Published: May 2022

AbstractThe Wnt signaling pathway plays a critical role in the developmental and physiological processes of metazoans. We previously reported that the Frizzled4 (FZD4) linker domain plays an important role in Norrin binding and signaling. However, the question remains whether the FZD linker contributes to Wnt signaling in general. Here, we show that the FZD linker is involved in Wnt binding and affects downstream Wnt signaling. A FZD4 chimera, in which the linker was swapped with that of the non-canonical receptor FZD6, impairs the binding with WNT3A and suppresses the recruitment of LRP6 and Disheveled, resulting in reduced canonical signaling. A similar effect was observed for non-canonical signaling. A FZD6 chimera containing the FZD1 linker showed reduced WNT5A binding and impaired signaling in ERK, JNK, and AKT mediated pathways. Altogether, our results suggest that the FZD linker plays an important role in specific Wnt binding and intracellular Wnt signaling.
The gut efflux pump MRP-1 exports oxidized glutathione as a danger signal that stimulates behavioral immunity and aversive learning
Authors: Lalsiamthara Jonathan , Aballay Alejandro 
Published: May 2022

AbstractInnate immune surveillance, which monitors the presence of potentially harmful microorganisms and the perturbations of host physiology that occur in response to infections, is critical to distinguish pathogens from beneficial microbes. Here, we show that multidrug resistance-associated protein-1 (MRP-1) functions in the basolateral membrane of intestinal cells to transport byproducts of cellular redox reactions to control both molecular and behavioral immunity in Caenorhabditis elegans. Pseudomonas aeruginosa infection disrupts glutathione homeostasis, leading to the excess production of the MRP-1 substrate, oxidized glutathione (GSSG). Extracellular GSSG triggers pathogen avoidance behavior and primes naïve C. elegans to induce aversive learning behavior via neural NMDA class glutamate receptor-1 (NMR-1). Our results indicate that MRP-1 transports GSSG, which acts as a danger signal capable of warning C. elegans of changes in intestinal homeostasis, thereby initiating a gut neural signal that elicits an appropriate host defense response.
Patient-Reported Qualitative Analysis of Chronic Refractory Cough
Authors: Wright Miranda L. , Fujiki Robert Brinton , Lunga Tadeas , Thibeault Susan L. 
Published: May 2022

Purpose:
Chronic cough has been shown to be associated with adverse effects on quality of life. There is a paucity of research characterizing quality-of-life factors associated with chronic refractory cough (CRC), a cough persisting > 8 weeks despite evaluation and treatment of possible etiologies. The purpose of this study was to elucidate the features of CRC from the patient's perspective, including presenting symptoms, past treatment methods, and quality-of-life factors.

Method:
Prospective semistructured interviews were conducted, recorded, and transcribed for 20 patients diagnosed with CRC. Exclusion criteria included lung disease, smoking history, laryngeal cancer, and neurological disease. Grounded theory analysis was completed on transcribed interviews.

Results:

Eighteen participants were women. Mean participant age was 53.5 years (
SD
= 1.41), and average cough duration was 52 months (
SD
= 71.6 months). Responses to 30 open-ended questions revealed four dominant themes with 24 subthemes.

Conclusions:
CRC affects patient quality of life. Understanding patient perspective on CRC diagnosis and treatment helps providers better understand the physical and emotional toll CRC takes on patients. Findings suggest that providers should spend more time counseling patients regarding their treatment and diagnosis, as patients with CRC do not always fully understand their diagnosis and resort to self-blame.
Optimal planning of uncertain renewable energy sources in unbalanced distribution systems by a multi‐objective hybrid PSO–SCO algorithm
Authors: Ali Eman S. , El‐Sehiemy Ragab A. , El‐Ela Adel A. Abou , Kamel Salah , Khan Baseem 
Published: May 2022

AbstractHigh penetration of Renewable Energy Sources into unbalanced distribution systems faces many challenges due to the uncertainty nature of both Renewable Energy Sources and loads as well as the unbalance degree of the distribution systems. This paper proposes the planning of Renewable Energy Sources in unbalanced distribution systems. Different types of Renewable Energy Sources, photo‐voltaic and Wind are considered. A multi‐objective optimisation problem is formulated using non‐dominated sort and crowing distance for multi objective hybrid algorithm that combines the merits of Particle Swarm Optimisation and Sine Cosine Optimisation algorithms. Three objectives, improving voltage profile, power losses minimisation, and minimisation of voltage unbalance, are considered. The proposed method determines the optimal Renewable Energy Sources' specifications such as site/size/type of distributed generators, number of photo‐voltaic modules or wind turbines in each distributed generator and their power factor and connection phases. Also, it determines the optimal setting of substation tap changer and system voltage regulators. Moreover, both Renewable Energy Sources and loads uncertainty are considered and modelled using Monte Carlo simulations. An improved matrix‐based backward–forward load flow method is developed by using coefficient matrices. The proposed procedure is conducted on IEEE 13‐node, 37‐node, and 123‐node unbalanced distribution systems. The proposed algorithm results compared with individual optimisers show significant performance improvements. The optimal plans resulted by using the proposed hybrid algorithm achieve a reduction in power losses that reached 89% in some cases. Also, the system unbalance index is reduced with a ratio reached 34%. Large improvement in the system voltages profile all over the year is achieved as the system voltage profile index is reduced by a ratio reached 70%.
A hybrid model for forecasting the consumption of electrical energy in a smart grid
Authors: Souhe Felix Ghislain Yem , Mbey Camille Franklin , Boum Alexandre Teplaira , Ele Pierre , Kakeu Vinny Junior Foba 
Published: May 2022

AbstractThis paper develops a novel hybrid model for forecasting electrical consumption based on several deep learning and optimization models such as Support Vector Regression (SVR), Firefly Algorithm (FA) and Adaptive Neuro‐Fuzzy Inference System (ANFIS). The process is focused on the minimization of error and risk. FA is used to optimize the forecasting performance using its higher optimization ability. The proposed SVR‐FA‐ANFIS model is based on historical data from smart meters in order to estimate and improve the accuracy of forecasting electrical consumption. Several accuracy coefficients such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to characterize the superior performance of the proposed model. The consumption data in Cameroon over the 24‐year period are used to evaluate the performance of the models. The simulation results show that the proposed method outperforms other models such as Long Short‐Term Memory (LSTM) and Random Forest (RF).
Structural design and magnetic field analysis on magnetic fluid lubricated bearings
Authors: Wang Ao , Pan Jiabao , Ye Jin , Wu Huaibiao 
Published: May 2022

AbstractA structural model of a bearing is proposed based on a general standard bearing structure and magneto‐fluidic lubrication, and the magnetic field of the bearing lubrication gap is analyzed under the action of an applied magnetic source. Results show that the magnetic field can form a magnetic circuit in the bearing structure, and a significant magnetic flux density is formed in the contact area of the rolling element of the bearing. The magnetic induction intensity in the contact area of the rolling element of the thrust bearing can provide magnetic fluid lubrication, and the magnetic induction intensity in the contact area of the rolling element of the point contact bearing is greater than that of the linear bearing. The magnetic inductance of the rolling elements in the rolling element contact area of a double row point contact bearing is greater than that of a single ring. The double permanent magnet ring structure has a more advantageous magnetic field effect than a single ring, and the magnetic inductance in the rolling element contact area of both rows of a double row point contact bearing is relatively the same.