bluuebunny/crossref_metadata_2025 huggingface dataset:
Germination Ecology of African Lovegrass (Eragrostis curvula) and Herbicide Options for Its Control
Authors: Alagbo Oyebanji O. , Chauhan Bhagirath Singh
Published: April 2023

African lovegrass (Eragrostis curvula) is one of the invasive perennial grasses that continues to disturb natural ecosystems globally. Experiments were conducted in southeast Queensland, Australia, to evaluate the effects of temperature, salt stress, water stress, burial depth, and sorghum crop residue load on the emergence and efficacy of postemergence herbicides on two populations (Clifton and Crows Nest) of E. curvula. The optimal germination temperature regimes for E. curvula were 30/20 and 35/25 °C, but seeds did not germinate at temperatures commonly occurring in the Queensland winter (15/5 °C). Total darkness inhibited germination by 79%, indicating that the shade cover effect would reduce germination of E. curvula. The Clifton population tolerated a higher concentration of sodium chloride (160 mM) and osmotic potential (−0.8 MPa). Under both salt and water stress, germination was 31% and 20% greater in the Clifton population than in Crows Nest, respectively, suggesting that the Clifton population is more tolerant to salt and drought stress. The maximum germination was obtained for the surface seeds while emergence declined with increased burial depth up to 4 cm. No seedlings emerged from the 8 cm depth. The addition of sorghum residue amounts up to 8 Mg ha−1 to the soil surface inhibited emergence compared to the no-residue treatment, suggesting that retention of heavy cereal residue will further delay or restrict emergence. Several postemergence herbicides were found to be effective in controlling E. curvula at an early stage. Information from this study will further compliment earlier studies on the targeted management of E. curvula populations.
Arbuscular Mycorrhiza and Its Influence on Crop Production
Authors: Hristozkova Marieta , Orfanoudakis Michail
Published: April 2023

Arbuscular mycorrhizal fungi (AMF) have become attractive as bio stimulants in agriculture due to plant nutrient uptake enchantment and stress tolerance [...]
Research on Provincial-Level Soil Moisture Prediction Based on Extreme Gradient Boosting Model
Authors: Ren Yifang , Ling Fenghua , Wang Yong
Published: April 2023

As one of the physical quantities concerned in agricultural production, soil moisture can effectively guide field irrigation and evaluate the distribution of water resources for crop growth in various regions. However, the spatial variability of soil moisture is dramatic, and its time series data are highly noisy, nonlinear, and nonstationary, and thus hard to predict accurately. In this study, taking Jiangsu Province in China as an example, the data of 70 meteorological and soil moisture automatic observation stations from 2014 to 2022 were used to establish prediction models of 0–10 cm soil relative humidity (RHs10cm) via the extreme gradient boosting (XGBoost) algorithm. Before constructing the model, according to the measured soil physical characteristics, the soil moisture observation data were divided into three categories: sandy soil, loam soil, and clay soil. Based on the impacts of various factors on the soil water budget balance, 14 predictors were chosen for constructing the model, among which atmospheric and soil factors accounted for 10 and 4, respectively. Considering the differences in soil physical characteristics and the lagged effects of environmental impacts, the best influence times of the predictors for different soil types were determined through correlation analysis to improve the rationality of the model construction. To better evaluate the importance of soil factors, two sets of models (Model_soil&atmo and Model_atmo) were designed by taking soil factors as optional predictors put into the XGBoost model. Meanwhile, the contributions of predictors to the prediction results were analyzed with Shapley additive explanation (SHAP). Six prediction effect indicators, as well as a typical drought process that happened in 2022, were analyzed to evaluate the prediction accuracy. The results show that the time with the highest correlations between environmental predictors and RHs10cm varied but was similar between soil types. Among these predictors, the contribution rates of maximum air temperature (Tamax), cumulative precipitation (Psum), and air relative humidity (RHa) in atmospheric factors, which functioned as a critical factor affecting the variation in soil moisture, are relatively high in both models. In addition, adding soil factors could improve the accuracy of soil moisture prediction. To a certain extent, the XGBoost model performed better when compared with artificial neural networks (ANNs), random forests (RFs), and support vector machines (SVMs). The values of the correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), Nash–Sutcliffe efficiency coefficient (NSE), and accuracy (ACC) of Model_soil&atmo were 0.69, 11.11, 4.87, 0.12, 0.50, and 88%, respectively. This study verified that the XGBoost model is applicable to the prediction of soil moisture at the provincial level, as it could reasonably predict the development processes of the typical drought event.
Transform and Deep Learning Algorithms for the Early Detection and Recognition of Tomato Leaf Disease
Authors: Alzahrani Mohammed Saeed , Alsaade Fawaz Waselallah
Published: April 2023

Plant diseases pose the greatest threat to food supply integrity, and it is a significant challenge to identify plant diseases in their earliest stages to reduce the potential for associated economic damage. Through the use of computer vision, a cutting-edge artificial intelligence is offered as a solution to this problem so that tomato leaf diseases may be classified. The proposed network is expected to provide excellent results. Transfer learning is also used to make the model efficient and cost effective. Since tomato diseases may significantly influence crop output and quality, early identification and diagnosis of these diseases are essential for successful treatment. Deep learning has shown a great deal of promise in plant disease identification, providing excellent accuracy and efficiency. In this investigation, we compared the performance of three different deep learning models—DenseNet169, ResNet50V2, and a transform model, namely ViT, with regard to diagnosing diseases affecting tomatoes. Both diseased and healthy tomato samples were included in the dataset of photos of tomato diseases used for training and testing the models. The DenseNet121 model had the best results, with a training accuracy of (99.88%) and a testing accuracy of (99.00%). This gave it the greatest overall accuracy. Both the ResNet50V2 and VIT models attained high levels of accuracy, with testing accuracies of (95.60% and 98.00%), respectively. Our results demonstrate deep learning’s potential for accurate and efficient tomato disease detection, which could aid in early disease management and ultimately improve crop yield and quality. The experimental findings show that the suggested ensemble models stand out due to the short amount of time required for training and testing as well as their exceptional classification performances. Because of this study, professionals will be able to facilitate the early diagnosis of plant diseases in a straightforward and expedient way, thereby preventing the emergence of new infections.
Influence of Moisture in Museum Rooms on the State of Microbial Contamination of the Air and Decoration Surfaces: The Example of a 17th Century Monument in the Museum of King John III’s Palace at Wilanow (Warsaw, Poland)
Authors: Andres Bogusław , Betlej Izabela , Bagiński Wojciech
Published: April 2023

This article is a case study of museum premises at the Museum of King John III’s Palace at Wilanow (Warsaw, Poland), wetted as a result of a failure of the water supply system to the air conditioning unit located in the attic of the building. As a result of flooding, discoloration and cracks appeared on the plaster and stucco decoration of the ceiling, located mainly in the central part of the ceiling of the King’s Library. The paintings (plafonds) mounted on the ceiling of this room also became damp. The article analyzes the microbiological contamination of air and damp paintings in the context of promptly proceeding with the drying of damp building partitions. The obtained results of microbiological air pollution in the flooded rooms were significantly lower than the permissible values recommended by Interdepartmental Commission for Maximum Admissible Concentrations and Intensities for Agents Harmful to Health in the Working Environment. In the King’s Library, i.e., the room with the dampest plaster and stucco as a result of the accident, the concentration of mold spores in the air was only 15 cfu/m3. This means that the immediate commencement of intensive drying of the building partitions (walls, ceilings with wooden floors) brought very good results. The rapid reduction in the moisture of the building partitions contributed to the worsening conditions for the development of microorganisms, which can have an adverse effect on wooden building partitions, plaster, stucco, etc.
Revealing the Ion Chemistry Occurring in High Kinetic Energy-Ion Mobility Spectrometry: A Proof of Principle Study
Authors: Weiss Florentin , Schaefer Christoph , Zimmermann Stefan , Märk Tilmann D. , Mayhew Chris A.
Published: April 2023

Here, we present proof of principle studies to demonstrate how the product ions associated with the ion mobility peaks obtained from a High Kinetic Energy-Ion Mobility Spectrometer (HiKE-IMS) measurement of a volatile can be identified using a Proton Transfer Reaction/Selective Reagent Ion-Time-of-Flight-Mass Spectrometer (PTR/SRI-ToF-MS) when operating both instruments at the same reduced electric field value and similar humidities. This identification of product ions improves our understanding of the ion chemistry occurring in the ion source region of a HiKE-IMS. The combination of the two analytical techniques is needed, because in the HiKE-IMS three reagent ions (NO+, H3O+ and O2+•) are present at the same time in high concentrations in the reaction region of the instrument for reduced electric fields of 100 Td and above. This means that even with a mass spectrometer coupled to the HiKE-IMS, the assignment of the product ions to a given reagent ion to a high level of confidence can be challenging. In this paper, we demonstrate an alternative approach using PTR/SRI-ToF-MS that allows separate investigations of the reactions of the reagent ions NO+, H3O+ and O2+•. In this study, we apply this approach to four nitrile containing organic compounds, namely acetonitrile, 2-furonitrile, benzonitrile and acrylonitrile. Both the HiKE-IMS and the PTR/SRI-ToF-MS instruments were operated at a commonly used reduced electric field strength of 120 Td and with gas flows at the same humidities.
The Effect of [(D-Ala6, Pro9NEt)mGnRH-a + Metoclopramide] (Ovopel) on Propagation Effectiveness of Two Breeding Lines of Common Carp (Cyprinus carpio L.) and on Luteinizing Hormone and 17α,20β-Dihydroxyprogesterone Levels in Females during Ovulation Induction
Authors: Brzuska Elżbieta , Socha Magdalena , Chyb Jarosław , Sokołowska-Mikołajczyk Mirosława , Inglot Michał
Published: April 2023

The study evaluates the impact of Ovopel on the reproductive effectiveness of carp from Polish line 6 and Lithuanian line B and the release of luteinizing hormone (LH) and 17α,20β-dihydroxyprogesterone (17α,20β-DHP) in females from these lines during ovulation induction. The levels of both hormones were determined in blood plasma samples taken just before the priming injection of Ovopel (0 h), at the time of administering the resolving dose of Ovopel (12 h), and after the next 12 h (24 h). Following Ovopel treatment, the mean egg weight obtained for line 6 was higher, but not statistically different, than that observed for line B. Egg quality, on the other hand, was significantly higher in line B. Female provenance did not significantly affect the number of eggs and living embryos after 70 h incubation. However, the total egg number for line 6 was higher. The mean number of living embryos (70 h) was similar for both lines. LH concentrations at 0, 12, and 24 h were not statistically different between the lines. A comparison of LH concentrations between ovulated and non-ovulated females at different sampling times revealed no significant differences either within or between the lines. Statistically significant differences in LH levels were found for both ovulated and non-ovulated females from a given line between the sampling times. The results for 17α,20β-DHP were similar, with only one difference: 24 h after the priming dose of Ovopel, 17α,20β-DHP levels in ovulated fish were significantly higher compared with non-ovulated females, but only in line 6.
Tissue-Specific Modulation of Gluco- and Growth-Regulatory Factor Abundance by Nesfatin-1 and Nesfatin-1-like Peptide in Goldfish
Authors: Rajeswari Jithine Jayakumar , Unniappan Suraj
Published: April 2023

Nesfatin-1 and nesfatin-1-like peptide (Nlp) are derived from precursors nucleobindin-2 and -1, two calcium and DNA binding proteins, respectively. Both peptides exhibit hormone-like actions in mammals and fish. These functions include insulinotropic effects of nesfatin-1 and Nlp seen in mice and their growth hormone suppressive actions reported in goldfish. We hypothesized that nesfatin-1 and Nlp are insulin stimulatory (in adipose tissue) and modulate growth hormone and insulin-like growth factors and glucose transporters in goldfish. To test this, goldfish were intraperitoneally injected with either nesfatin-1 or Nlp (50 ng/g BW) or saline alone (control) and sampled at one-hour post-injection (in vivo study). In a separate study, tissue samples were collected and were incubated with either nesfatin-1 or Nlp for one or six hours (in vitro study). Transcript (mRNA) abundance data from the adipose tissue suggest that both nesfatin-1 and Nlp significantly upregulate the abundance of preproinsulin, insulin receptors, and pcsk1 and pcsk2 mRNAs. Meanwhile, the abundance of preproglucagon mRNA in the adipose tissue was significantly downregulated in both in vivo and in vitro studies. These results agree with the insulinotropic and glucagonostatic roles for nesfatin-1 and Nlp reported in rodents. The transcript abundance of growth regulators (igf1, igf2a, and ghra) and glucose transporters (slc2a2 and slc5a1) were upregulated in the muscle, while an opposite effect on these mRNAs was found in the liver of goldfish following nesfatin-1 and Nlp administration. Our results suggest that both nesfatin-1 and Nlp have tissue-specific regulatory roles on growth and glucoregulatory elements in the liver and muscle of goldfish. This agrees with our previous studies that showed a suppressive action of nesfatin-1 on growth hormone in goldfish liver. The results presented here provide strong supportive/confirmatory evidence for tissue-specific insulinotropic and gluco- and growth-regulatory actions of nesfatin-1 and Nlp in goldfish.
Serum Metabolomics and Ionomics Analysis of Hoof-Deformed Cows Based on LC-MS/MS and ICP-OES/MS
Authors: Deng Chaoyang , Yue Yang , Zhang Hefei , Liu Meng , Ge Yansong , Xu Enshuang , Zheng Jiasan
Published: April 2023

In order to explore the metabolic and ionic changes of hoof-deformed cows, the serum samples of 10 healthy cows (group C) and 10 hoof-deformed cows (group T) were analyzed by LC-MS/MS and ICP-OES/MS. The pathway enrichment of differential metabolites was analyzed by screening and identifying differential metabolites and ions and using a bioinformatics method. The integration of metabolomics and ionics was analyzed with ggplot2 software in R language, and verified by MRM target metabolomics. The results showed that 127 metabolites were screened by metabolomics, of which 81 were up-regulated (p < 0.05) and 46 were down-regulated (p < 0.05). The results of ICP-OES/MS showed that 13 kinds of ions such as K, Li, and Pb in serum of dairy cows were up-regulated, while 18 kinds of ions such as Al, Cu and Sb were down-regulated. The integrated analysis of metabolomics and ionics found that potassium ions were positively correlated with L-tyrosine, L-proline, thiamine and L-valine. Sodium ions were positively correlated with L-valine and negatively correlated with α-D-glucose. The results of high-throughput target metabolomics showed that the contents of L-proline, L-phenylalanine and L-tryptophan in serum of dairy cows increased significantly, which was consistent with the results of non-target metabolomics. In a word, the metabolism and ion changes in dairy cows with hoof deformation were revealed by metabolomics and ionics.
Food Allocation under Asynchronous Hatching Conditions of Great Tits (Parus major)
Authors: Kang Ji-Won , Lee Jong-Koo
Published: April 2023

The brood reduction hypothesis, which explains asynchronous hatching in birds, as an adaptation that enables selective survival of older nestlings when availability of food is unpredictable. This study was conducted in order to determine whether the brood reduction hypothesis can explain asynchronous hatching in passerines. Infrared cameras were installed inside nest boxes where great tits (Parus major) were attempting to reproduce in order to determine whether the parents practiced selective feeding of older nestlings. According to the results of the study, no significant difference was observed between the hatching order and the average number of feedings per nestling. In addition, when examining the distribution of food according to hatching order over time, every 30 min, beginning at 9 a.m., selective distribution of food to older nestlings was not observed. In conclusion, use of the brood reduction hypothesis, which supports selective provision of beneficial feeding of older and larger nestlings, to explain the asynchronous hatching of passerines is problematic, thus conduct of future studies focusing on other hypotheses in order to explain the asynchronous hatching of this passerine bird will be necessary.
Is Penguin Circovirus Circulating Only in the Antarctic Circle? Lack of Viral Detection in Namibia
Authors: Roberts Laura C. , Molini Umberto , Coetzee Lauren M. , Khaiseb Siegfried , Roux Jean-Paul , Kemper Jessica , Roberts David G. , Ludynia Katrin , Doherr Marcus , Abernethy Darrell , Franzo Giovanni
Published: April 2023

The known host range of circoviruses is continuously expanding because of more intensive diagnostic activities and advanced sequencing tools. Recently, a new circovirus (penguin circovirus (PenCV)) was identified in the guano and cloacal samples collected from Adélie penguins (Pygoscelis adeliae) and chinstrap penguins (Pygoscelis antarcticus) in Antarctica. Although the virus was detected in several asymptomatic subjects, a potential association with feather disease was speculated. To investigate the occurrence and implications of PenCV in other penguin species located outside of Antarctica, a broad survey was undertaken in African penguins (Spheniscus demersus) on two islands off the southern Namibian coast. For this purpose, specific molecular biology assays were developed and validated. None of the 151 blood samples tested positive for PenCV. Several reasons could explain the lack of PenCV positive samples. African penguins and Pygoscelis species are separated by approximately 6000 km, so there is almost no opportunity for transmission. Similarly, host susceptibility to PenCV might be penguin genus-specific. Overall, the present study found no evidence of PenCV in African penguin colonies in Namibia. Further dedicated studies are required to assess the relevance of PenCV among different penguin species.
Effectiveness of Antimicrobial Lock Therapy for the Treatment of Catheter-Related and Central-Line-Associated Bloodstream Infections in Children: A Single Center Retrospective Study
Authors: Signorino Claudia , Fusco Eleonora , Galli Luisa , Chiappini Elena
Published: April 2023

Antimicrobial lock solutions (ALT) in combination with systemic antibiotics can represent a valid option to attempt central venous catheter (CVC) salvage in the case of catheter-related and central-line-associated bloodstream infections (CRBSI and CLABSI). However, data concerning the effectiveness and safety of ALT in children are limited. We aimed to share our center’s experience in order to contribute to investigations into the causes of ALT failure in the pediatric population. All children consecutively admitted to Meyer Children’s Hospital, University of Florence, Italy, from 1 April 2016 to 30 April 2022, who received salvage ALT to treat an episode of CRBSI/CLABSI, were reviewed. According to ALT failure or success, children were compared with the aim of identifying the risk factors for unsuccessful ALT outcome. Data from 28 children, 37 CLABSI/CRBSI episodes, were included. ALT was associated with clinical and microbiologic success in 67.6% (25/37) of children. No statistically significant differences were observed between the two groups, successes and failures, considering age, gender, reason for use, duration, insertion, type and presence of insertion site infection of the CVC, laboratory data and number of CRBSI episodes. Nevertheless, a trend towards a higher success rate was observed for a dwell time of 24 h for the entire duration of ALT (88%; 22/25 vs. 66.7%; 8/12; p = 0.1827), while the use of taurolidine and the infections sustained by MDR bacteria were associated with a tendency toward greater failure (25%; 3/12 vs. 4%; 1/25; p = 0.1394; 60%; 6/10 vs. 33.3%; 8/24; p = 0.2522). No adverse events, except one CVC occlusion, were observed. ALT combined with systemic antibiotics appears to be an effective and safe strategy for treating children with CLABSI/CRBSI episodes.
Grape Pomace as a Cardiometabolic Health-Promoting Ingredient: Activity in the Intestinal Environment
Authors: Taladrid Diego , Rebollo-Hernanz Miguel , Martin-Cabrejas Maria A. , Moreno-Arribas M. Victoria , Bartolomé Begoña
Published: April 2023

Grape pomace (GP) is a winemaking by-product particularly rich in (poly)phenols and dietary fiber, which are the main active compounds responsible for its health-promoting effects. These components and their metabolites generated at the intestinal level have been shown to play an important role in promoting health locally and systemically. This review focuses on the potential bioactivities of GP in the intestinal environment, which is the primary site of interaction for food components and their biological activities. These mechanisms include (i) regulation of nutrient digestion and absorption (GP has been shown to inhibit enzymes such as α-amylase and α-glucosidase, protease, and lipase, which can help to reduce blood glucose and lipid levels, and to modulate the expression of intestinal transporters, which can also help to regulate nutrient absorption); (ii) modulation of gut hormone levels and satiety (GP stimulates GLP-1, PYY, CCK, ghrelin, and GIP release, which can help to regulate appetite and satiety); (iii) reinforcement of gut morphology (including the crypt-villi structures, which can improve nutrient absorption and protect against intestinal damage); (iv) protection of intestinal barrier integrity (through tight junctions and paracellular transport); (v) modulation of inflammation and oxidative stress triggered by NF-kB and Nrf2 signaling pathways; and (vi) impact on gut microbiota composition and functionality (leading to increased production of SCFAs and decreased production of LPS). The overall effect of GP within the gut environment reinforces the intestinal function as the first line of defense against multiple disorders, including those impacting cardiometabolic health. Future research on GP’s health-promoting properties should consider connections between the gut and other organs, including the gut-heart axis, gut-brain axis, gut-skin axis, and oral-gut axis. Further exploration of these connections, including more human studies, will solidify GP’s role as a cardiometabolic health-promoting ingredient and contribute to the prevention and management of cardiovascular diseases.
Protective Effect of Dexmedetomidine against Hyperoxia-Damaged Cerebellar Neurodevelopment in the Juvenile Rat
Authors: Puls Robert , von Haefen Clarissa , Bührer Christoph , Endesfelder Stefanie
Published: April 2023

Impaired cerebellar development of premature infants and the associated impairment of cerebellar functions in cognitive development could be crucial factors for neurodevelopmental disorders. Anesthetic- and hyperoxia-induced neurotoxicity of the immature brain can lead to learning and behavioral disorders. Dexmedetomidine (DEX), which is associated with neuroprotective properties, is increasingly being studied for off-label use in the NICU. For this purpose, six-day-old Wistar rats (P6) were exposed to hyperoxia (80% O2) or normoxia (21% O2) for 24 h after DEX (5 µg/kg, i.p.) or vehicle (0.9% NaCl) application. An initial detection in the immature rat cerebellum was performed after the termination of hyperoxia at P7 and then after recovery in room air at P9, P11, and P14. Hyperoxia reduced the proportion of Calb1+-Purkinje cells and affected the dendrite length at P7 and/or P9/P11. Proliferating Pax6+-granule progenitors remained reduced after hyperoxia and until P14. The expression of neurotrophins and neuronal transcription factors/markers of proliferation, migration, and survival were also reduced by oxidative stress in different manners. DEX demonstrated protective effects on hyperoxia-injured Purkinje cells, and DEX without hyperoxia modulated neuronal transcription in the short term without any effects at the cellular level. DEX protects hyperoxia-damaged Purkinje cells and appears to differentially affect cerebellar granular cell neurogenesis following oxidative stress.
Unfolding the Interactions between Endoplasmic Reticulum Stress and Oxidative Stress
Authors: Ong Gideon , Logue Susan E.
Published: April 2023

Oxidative stress is caused by an imbalance in cellular redox state due to the accumulation of reactive oxygen species (ROS). While homeostatic levels of ROS are important for cell physiology and signaling, excess ROS can induce a variety of negative effects ranging from damage to biological macromolecules to cell death. Additionally, oxidative stress can disrupt the function of redox-sensitive organelles including the mitochondria and endoplasmic reticulum (ER). In the case of the ER, the accumulation of misfolded proteins can arise due to oxidative stress, leading to the onset of ER stress. To combat ER stress, cells initiate a highly conserved stress response called the unfolded protein response (UPR). While UPR signaling, within the context of resolving ER stress, is well characterised, how UPR mediators respond to and influence oxidative stress is less defined. In this review, we evaluate the interplay between oxidative stress, ER stress and UPR signaling networks. Specifically, we assess how UPR signaling mediators can influence antioxidant responses.
Antioxidant and Anti-Inflammatory Properties of Walnut Constituents: Focus on Personalized Cancer Prevention and the Microbiome
Authors: Fan Nuoxi , Fusco Jennifer L. , Rosenberg Daniel W.
Published: April 2023

Walnuts have been lauded as a ‘superfood’, containing a remarkable array of natural constituents that may have additive and/or synergistic properties that contribute to reduced cancer risk. Walnuts are a rich source of polyunsaturated fatty acids (PUFAs: alpha-linolenic acid, ALA), tocopherols, antioxidant polyphenols (including ellagitannins), and prebiotics, including fiber (2 g/oz). There is a growing body of evidence that walnuts may contribute in a positive way to the gut microbiome, having a prebiotic potential that promotes the growth of beneficial bacteria. Studies supporting this microbiome-modifying potential include both preclinical cancer models as well as several promising human clinical trials. Mediated both directly and indirectly via its actions on the microbiome, many of the beneficial properties of walnuts are related to a range of anti-inflammatory properties, including powerful effects on the immune system. Among the most potent constituents of walnuts are the ellagitannins, primarily pedunculagin. After ingestion, the ellagitannins are hydrolyzed at low pH to release ellagic acid (EA), a non-flavonoid polyphenolic that is subsequently metabolized by the microbiota to the bioactive urolithins (hydroxydibenzo[b,d]pyran-6-ones). Several urolithins, including urolithin A, reportedly have potent anti-inflammatory properties. These properties of walnuts provide the rationale for including this tree nut as part of a healthy diet for reducing overall disease risk, including colorectal cancer. This review considers the latest information regarding the potential anti-cancer and antioxidant properties of walnuts and how they may be incorporated into the diet to provide additional health benefits.
Wetting of Cu-SiC Composite Material Modified by Nanosecond Laser Radiation and Liquid Spreading over It
Authors: Orlova Evgeniya , Feoktistov Dmitriy , Dorozhkin Alexander , Kotelnikov Gleb
Published: April 2023

In the framework of this work, the surface properties of Cu-SiC composite material were studied when spreading micro- and nanoliter liquids. The Cu-SiC samples with a SiC content of 5 to 20 wt.% were fabricated by spark plasma sintering at temperatures from 700 to 850 °C. The Cu-SiC surfaces were processed by two different methods: using abrasive materials and nanosecond laser radiation. Surface analysis was performed by scanning electron microscopy, profilometry, energy dispersive spectroscopy and Vickers methods. The surface properties (wetting and dynamic characteristics of spreading) were studied using a shadow optical technique when interacting the Cu-SiC surfaces with water (up to 10 μL). It was proved that the recorded deterioration of the wettability properties of Cu-SiC surfaces processed by abrasive materials with an increase in their sintering temperature and the reason for the spontaneous hydrophobization of the Cu-SiC composite materials modified by nanosecond laser radiation, are due to the adsorption of airborne hydrocarbon contaminants, similar to the known wetting inversion of metal surfaces. It was established that the wetting properties of materials prior to modification by laser radiation do not affect the intensity, duration of stages, and steady-state values of contact angles upon wetting inversion of Cu-SiC composite materials. It was also found that the processing of Cu-SiC surfaces by laser radiation makes it possible to change the dynamic characteristics of the liquid spreading (at a flow rate of 5 μL/min, the liquid front speed is more than three times, and the dynamic contact angles are in the range of 30°).
Wave Propagation in Laminated Cylinders with Internal Fluid and Residual Stress
Authors: Manconi Elisabetta , Mace Brian R. , Garziera Rinaldo
Published: April 2023

Numerical computation of wave propagation in laminated cylinders with internal fluid and residual stress is obtained using a Wave Finite Element formulation for 2D waveguides. Only a very small segment of the system is modelled, resulting in a very low-order finite element (FE) model to which the theory of wave propagation in 2D periodic structures is applied. The method uses standard FE formulations and exploits the capability of commercial FE software to model both fluid and structure and their interaction, resulting in a very large reduction in computational time. The presented approach is general, and can be applied without the need to make assumptions related to shell theory or low-frequency analysis. In particular, the laminated structure is discretised using 3D solid elements, thus representing the through-thickness dynamics with high accuracy. Residual radial and hoop stresses are included in the model by adding the FE pre-stress stiffness matrix to the original stiffness matrix of the system. The method provides simultaneously a very substantial reduction of computational cost, accurate solutions up to very high frequency and prediction of the dispersion curves for selected circumferential orders without the need for any further analysis. Here, the formulation of the method is introduced and its application to laminated cylinders filled with an acoustic fluid is presented. A composite, reinforced rubber cylinder, pre-stressed by a circumferential tension, is also shown as an example of a laminated pipe for high-pressure applications.
Assessing Dynamic Changes, Driving Mechanisms and Predictions of Multisource Vegetation Remote Sensing Products in Chinese Regions
Authors: Han Yang , Lin Yilin , Zhou Peng , Duan Jinjiang , Cao Zhaoxiang , Wang Jian , Yang Kui
Published: April 2023

Terrestrial vegetation, a critical component of the Earth’s land surface, directly impacts the planet’s material and energy balance. This study investigated the dynamics of terrestrial vegetation in China from 2000 to 2019 using three remote sensing products (NDVI, EVI, and SIF) and explored the driving mechanisms behind these changes. We considered three meteorological factors, nine land use types, and two socio-economic factors while employing mathematical models to analyze the data. Additionally, we used the CA–Markov model to predict the spatial distribution of vegetation remote sensing products for 2020–2025. Our findings indicate the following: (1) Throughout the study period, the vegetation indices, NDVI, EVI, and SIF, all exhibited increasing trends. The SIF showed a more direct response to vegetation cover changes and was less influenced by other driving factors. The SIF outperforms the NDVI and EVI in detecting vegetation trend changes, particularly regarding sensitivity. (2) Vegetation cover changes are driven by multiple meteorological factors, such as temperature, precipitation, and relative humidity. These factors exhibit a strong spatial correlation with the distribution of vegetation remote sensing products. Among these factors, the SIF shows a higher sensitivity to temperature compared to the NDVI and EVI, while the NDVI and EVI display greater sensitivity to precipitation and relative humidity. (3) Within the study area, land use types reveal a gradient from northwest to southeast, which is consistent with the spatial distribution of the vegetation remote sensing products. For green vegetation types, the three remote sensing products exhibit varying sensitivity levels, with the SIF demonstrating the highest sensitivity to green vegetation types. (4) Overall, the future vegetation outlook in China is promising, especially in the southeastern regions where significant vegetation improvement trends are evident. However, the vegetation conditions in some northwestern areas remain less favorable, necessitating the reinforcement of ecological construction and improvement measures. Additionally, a significant positive correlation exists between population size, GDP, and vegetation remote sensing products. This study highlights the variability in the dynamics and driving mechanisms of terrestrial vegetation remote sensing products in China and employs the CA–Markov model for predicting future vegetation patterns. Our research contributes to the theoretical and technical understanding of remote sensing for terrestrial vegetation in the Chinese context.
Small-Target Detection Based on an Attention Mechanism for Apron-Monitoring Systems
Authors: Liu Hao , Ding Meng , Li Shuai , Xu Yubin , Gong Shuli , Kasule Abdul
Published: April 2023

Small-target detection suffers from the problems of low average precision and difficulties detecting targets from airport-surface surveillance videos. To address this challenge, this study proposes a small-target detection model based on an attention mechanism. First, a standard airport small-target dataset was established, where the absolute scale of each marked target meets the definition of a small target. Second, using the Mask Scoring R-CNN model as a baseline, an attention module was added to the feature extraction network to enhance its feature representation and improve the accuracy of its small-target detection. A multiscale feature pyramid fusion module was used to fuse more detailed shallow information according to the feature differences of diverse small targets. Finally, a more effective detection branch structure is proposed to improve detection accuracy. Experimental results verify the effectiveness of the proposed method in detecting small targets. Compared to the Mask R-CNN and Mask Scoring R-CNN models, the detection accuracy of the proposed method in two-pixel intervals with the lowest rate of small targets increased by 10%, 3.04% and 16%, 15.15%, respectively. The proposed method proved to have a higher accuracy and be more effective at small-target detection.
Big Data Analytics Framework Using Squirrel Search Optimized Gradient Boosted Decision Tree for Heart Disease Diagnosis
Authors: Shaik Kareemulla , Ramesh Janjhyam Venkata Naga , Mahdal Miroslav , Rahman Mohammad Zia Ur , Khasim Syed , Kalita Kanak
Published: April 2023

Disease detection is a critical issue in the field of medical diagnostics. Failure to identify heart disease (HD) at an early stage can lead to mortality. The lack of access to expert physicians in remote areas further exacerbates the problem. Big data analytics (BDA) is an emerging area that can help extract valuable information from vast amounts of data and improve medical diagnosis while reducing costs. Machine learning (ML) algorithms have been effectively employed in many fields, including medical diagnostics. ML methods can help doctors detect and forecast illnesses at an early stage by creating classifier systems. In this article, we propose a unique ML- and BDA-based squirrel search-optimized Gradient Boosted Decision Tree (SS-GBDT) for the detection of heart disease. The effectiveness of the proposed method is demonstrated through various performance indicators. The results show that the proposed method is highly efficient in medical diagnosis, with 95% accuracy rate, 95.8% precision, 96.8% recall and 96.3% F1-measure achieved by the SS-GBDT. The use of BDA and ML can greatly enhance medical diagnosis and this proposed method is a significant step in this direction.
Ocular Motility Abnormalities in Ehlers-Danlos Syndrome: An Observational Study
Authors: Comberiati Anna Maria , Iannetti Ludovico , Migliorini Raffaele , Armentano Marta , Graziani Marika , Celli Luca , Zambrano Anna , Celli Mauro , Gharbiya Magda , Lambiase Alessandro
Published: April 2023

Purpose: To evaluate ocular motility (OM) abnormalities associated with Ehlers-Danlos Syndrome (EDS). Materials and methods: In this cross-sectional observational study, patients with EDS underwent a complete orthoptic examination. The following orthoptic tests were performed: corneal light reflex test, stereoscopic test, cover test, OM assessment, evaluation of eye pain in different gaze positions and red filter test for diplopia. Results: The corneal light reflex test at 33 cm showed an intermittent divergent deviation in 31.7% of patients and an intermittent horizontal deviation associated with a vertical deviation in 4.9% of patients. A manifest strabismus was observed in 2.4% of patients, whereas 2.4% of patients showed a microstrabismus. The corneal light reflex test at 5 m revealed microstrabismus in 9.8% and manifest strabismus in 2.4% of our patients. Moreover, intermittent exotropia was observed in 2.4% of cases. No significant alterations involving the inferior rectus and the superior oblique muscles were observed. Significant associations were observed between medial rectus muscle deficit of both eyes with pain (p = 0.020) and diplopia (p = 0.014). Furthermore, a significant association between lateral rectus muscle alteration of both eyes and pain was observed (p = 0.004). Conclusions: Our results show various OM alterations in patients with EDS, specifically superior and medial rectus muscle hypofunction. A full orthoptic evaluation in these patients is recommendable to detect OM involvement and possible ligamentous laxity changes over time through an accurate OM assessment.
Simultaneous Classification and Regression for Zakat Under-Reporting Detection
Authors: Ben Ismail Mohamed Maher , AlSadhan Nasser
Published: April 2023

Tax revenue represents an essential budget source for most countries around the world. Accordingly, the modernization of relevant technological infrastructure has become a key factor of tax administration strategy for improving tax collection efficiency. In particular, the fiscal consolidation of the Kingdom of Saudi Arabia has been supported by considerable development in tax policy and administration, aimed at raising more taxes from non-oil activities. In fact, non-Saudi investors are liable for income tax in Saudi Arabia. On the other hand, Saudi citizen investors (and citizens of the GCC countries) are liable for Zakat, an Islamic assessment. Typically, taxpayers are in charge of preparing and accurately reporting their Zakat declaration. This allows tax authorities to overview and audit their business activities. However, despite administration efforts to increase taxpayer compliance, considerable revenue remains at under-reporting risk. In this paper, we introduce a novel intelligent approach to support tax authority efforts in detecting under-reporting among Zakat payer declarations. In particular, the proposed solution aims at improving detection accuracy and determining the fraud cases that correspond to a higher revenue at risk. Specifically, we formulate Zakat under-reporting detection as a supervised machine learning task through the design of a deep neural network that performs simultaneous classification and regression tasks. In particular, the proposed network contains an input layer, five hidden layers, and two output layers for classification and regression. Zakat declarations are mapped into the predefined “under-reporting” or “actual declaration” classes. Moreover, the revenue at risk caused by the predicted fraud cases is learned by the designed model. This allows the proposed approach to prioritize the auditing of specific Zakat payers based on the corresponding predicted revenue at risk. A real dataset including 51,919 Zakat declarations was used to validate and assess the designed model. Further, the Synthetic Minority Oversampling Technique (SMOTE) boosted the proposed model performance in terms of classification and prioritization.
Restriction of Mouth Opening, Reduction in Pressure Pain Thresholds and Activation of Myofascial Trigger Points in Mandibular and Cervical Regions after Root Canal Therapy: A Quasi-Experimental Study
Authors: Albarova-Corral Isabel , Alonso-Ezpeleta Óscar , Poc-Sola Santiago , Cardiel-Sánchez Silvia , Carrasco-Uribarren Andoni , Malo-Urriés Miguel
Published: April 2023

Background: In daily clinical practice, patients often refer temporomandibular or cervical complaints after different oral procedures, especially in lengthy procedures that can result in iatrogenic postures or trauma that can affect the temporomandibular joint (TMJ). This study aimed to evaluate the clinical and functional changes of the temporomandibular joint (TMJ) and cervical region immediately after a session of root canal therapy. Methods: Twenty-nine subjects who received a session of root canal therapy were included. Clinical assessments included mouth opening, cervical mobility, pain intensity, pressure pain thresholds (PPTs), and myofascial trigger points (MTrPs) of the jaw and neck muscles. Results: After the intervention, a significant reduction in mouth opening (41.90 mm; SD = 6.21) was observed compared to baseline (46.28 mm; SD = 6.17) (p < 0.001). A significant reduction in PPTs and cervical mobility (p < 0.05), and an increase in MTrPs (p = 0.002–0.026) were demonstrated after the intervention. Conclusions: A session of root canal therapy can produce an immediate significant reduction in mouth opening, PPTs, and cervical mobility, and an increase in MTrPs. The risk can be higher if there is a previous TMJ limitation.
The Accuracy of Dynamic Sound Source Localization and Recognition Ability of Individual Head-Related Transfer Functions in Binaural Audio Systems with Head Tracking
Authors: Planinec Vedran , Reijniers Jonas , Horvat Marko , Peremans Herbert , Jambrošić Kristian
Published: April 2023

The use of audio systems that employ binaural synthesis with head tracking has become increasingly popular, particularly in virtual reality gaming systems. The binaural synthesis process uses the Head-Related Transfer Functions (HRTF) as an input required to assign the directions of arrival to sounds coming from virtual sound sources in the created virtual environments. Generic HRTFs are often used for this purpose to accommodate all potential listeners. The hypothesis of the research is that the use of individual HRTF in binaural synthesis instead of generic HRTF leads to improved accuracy and quality of virtual sound source localization, thus enhancing the user experience. A novel methodology is proposed that involves the use of dynamic virtual sound sources. In the experiments, the test participants were asked to determine the direction of a dynamic virtual sound source in both the horizontal and vertical planes using both generic and individual HRTFs. The gathered data are statistically analyzed, and the accuracy of localization is assessed with respect to the type of HRTF used. The individual HRTFs of the test participants are measured using a novel and efficient method that is accessible to a broad range of users.
An Attention-Based Residual Neural Network for Efficient Noise Suppression in Signal Processing
Authors: Lan Tianwei , Han Liguo , Zeng Zhaofa , Zeng Jingwen
Published: April 2023

The incorporation of effective denoising techniques is a crucial requirement for seismic data processing during the acquisition phase due to the inherent susceptibility of the seismic data acquisition process to various forms of interference, such as random and coherent noise. For random noise, the Residual Neural Network (Resnet), with its notable ability to effectively suppress noise in seismic data, has garnered widespread utilization in removing unwanted disturbances or interference due to its elegant simplicity and outstanding performance. Despite the considerable advancements achieved by conventional Resnet in the field of suppressing noise, it is irrefutable that there is still room for amelioration in their ability to filter out unwanted disturbances. As a result, this paper puts forth a novel attention-based methodology for Resnet, intended to overcome the present constraints and attain an optimal seismic signal enhancement. Specifically, we add the convolutional block attention module (CBAM) after the convolutional layer of the residual module and add channel attention on the shortcut connections to filter out the disturbance. We replace the commonly used ReLU activation function in the network with ELU, which is better suited for suppressing seismic noise. Empirical assessments conducted on both synthetic and authentic datasets have demonstrated the efficacy of the proposed methodology in amplifying the denoising prowess of Resnet. Our proposed method remains stable even when dealing with seismic data that has complex waveforms. The findings of this investigation evince that the recommended approach furnishes a substantial augmentation in the signal-to-noise ratio (SNR), thereby facilitating the efficient and robust extraction of the underlying signal from the noisy observations.