bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of the Fibrous Root of Polygonatum cyrtonema Hua on Growth Performance, Meat Quality, Immunity, Antioxidant Capacity, and Intestinal Morphology of White-Feathered Broilers
Authors: Zhang Tianlu , Zhou Dong , Chen Miaofen , Zou Hui , Tang Qi , Lu Ying , Zheng Yajie
Published: November 2023

This study was designed to evaluate the effects of different doses of the fibrous roots of Polygonatum cyrtonema Hua on the growth performance, slaughter parameters, meat quality, immune function, cytokines, antioxidant capacity, and intestinal morphology of white-feathered broilers. Also, the mechanism to improve immune functions of broilers was explored through network pharmacology and molecular docking technology. A total of 360 AA-white-feathered broilers were randomly divided into six groups (not separated by sex), with six repetitions per group (n = 10). The groups were as follows: basal diet (CON group), basal diet supplemented with 300 mg/kg aureomycin (ANT group), basal diet supplemented with 2%, 3%, and 4% fibrous root raw powder (LD, MD, and HD group), or basal diet supplemented with 3% fibrous root processed powder (PR group), in a 42-day experiment. The dietary inclusion of P. cyrtonema fibrous roots increased slaughter performance (p < 0.05), reduced the fat rate (p < 0.05), improved intestinal morphology (p < 0.05), and improved the immune organ index to varying degrees. It also significantly improved pH reduction, drip loss, and pressure loss of breast muscle and leg muscle (p < 0.05). Furthermore, it significantly improved immune and antioxidant functions including decreased MDA content of serum (p < 0.01), increased GSH-Px content (p < 0.01), IgG, IgA, and C4 contents (p < 0.05), and increased expression of IL-2 and IFN-γ (p < 0.01). Additionally, the mechanism by which fibrous roots improve immune function in broilers was explored using network pharmacology and molecular docking technology. Network pharmacology and molecular docking revealed that flavonoids such as baicalein, 4′,5-Dihydroxyflavone, 5,7-dihydroxy-6,8-dimethyl-3-(4′-hydroxybenzyl)-chroman-4-one, and 5,7-dihydroxy-3-(2′-hydroxy-4′-methoxybenzyl)-6,8-dimethyl-chroman-4-one were key components that enhanced immune function through the MAPK1 and other key targets involved in regulating the MAPK signaling pathway. From the findings, it can be concluded that incorporating P. cyrtonema Hua fibrous root as a natural feed supplement and growth promoter in broiler diets had a positive impact on bird health and performance.
Associations between the New DNA-Methylation-Based Telomere Length Estimator, the Mediterranean Diet and Genetics in a Spanish Population at High Cardiovascular Risk
Authors: Coltell Oscar , Asensio Eva M. , Sorlí José V. , Ortega-Azorín Carolina , Fernández-Carrión Rebeca , Pascual Eva C. , Barragán Rocío , González José I. , Estruch Ramon , Alzate Juan F. , Pérez-Fidalgo Alejandro , Portolés Olga , Ordovas Jose M. , Corella Dolores
Published: November 2023

Biological aging is a relevant risk factor for chronic diseases, and several indicators for measuring this factor have been proposed, with telomere length (TL) among the most studied. Oxidative stress may regulate telomere shortening, which is implicated in the increased risk. Using a novel estimator for TL, we examined whether adherence to the Mediterranean diet (MedDiet), a highly antioxidant-rich dietary pattern, is associated with longer TL. We determined TL using DNA methylation algorithms (DNAmTL) in 414 subjects at high cardiovascular risk from Spain. Adherence to the MedDiet was assessed by a validated score, and genetic variants in candidate genes and at the genome-wide level were analyzed. We observed several significant associations (p < 0.05) between DNAmTL and candidate genes (TERT, TERF2, RTEL1, and DCAF4), contributing to the validity of DNAmTL as a biomarker in this population. Higher adherence to the MedDiet was associated with lower odds of having a shorter TL in the whole sample (OR = 0.93; 95% CI: 0.85–0.99; p = 0.049 after fully multivariate adjustment). Nevertheless, this association was stronger in women than in men. Likewise, in women, we observed a direct association between adherence to the MedDiet score and DNAmTL as a continuous variable (beta = 0.015; SE: 0.005; p = 0.003), indicating that a one-point increase in adherence was related to an average increase of 0.015 ± 0.005 kb in TL. Upon examination of specific dietary items within the global score, we found that fruits, fish, “sofrito”, and whole grains exhibited the strongest associations in women. The novel score combining these items was significantly associated in the whole population. In the genome-wide association study (GWAS), we identified ten polymorphisms at the suggestive level of significance (p < 1 × 10−5) for DNAmTL (intergenics, in the IQSEC1, NCAPG2, and ABI3BP genes) and detected some gene–MedDiet modulations on DNAmTL. As this is the first study analyzing the DNAmTL estimator, genetics, and modulation by the MedDiet, more studies are needed to confirm these findings.
A Self-Calibration of Capacitor Mismatch Error for Pipeline ADCs
Authors: Seo Dong-Hwan , Cho Sunghoon , Kim Jung-Gyun , Lee Byung-Geun
Published: November 2023

This study proposes self-calibration of capacitor mismatch errors for high-resolution pipeline analog-to-digital converters (ADCs). The proposed calibration circuit recursively amplifies the capacitor mismatch error by re-utilizing a multiplying digital-to-analog converter in a pipeline stage without increasing the circuit complexity, and the amplified error voltage is converted into digital code by utilizing the remaining pipeline stages. Error correction is performed by subtracting the digital code from the ADC output during normal operation. A prototype of a 12-bit pipeline ADC is fabricated in a 0.18 µm standard CMOS process. The ADC comprises eight 1.5-bit stages, followed by a 4-bit flash ADC as the final stage; the capacitor mismatch errors in the first two pipeline stages are corrected by utilizing the proposed self-calibration technique. Although the calibration method is employed in a 1.5-bit stage architecture, which uses a gain-of-two switched-capacitor amplifier, it is applicable to different bit-per-stage architectures. The ADC linearity significantly improves after calibration, and this is verified through simulations and measurements.
Cell Formation and Intra-Cell Optimal Machine Location in CMS: A Novel Genetic Algorithm (GA) Based on Machine Encoding
Authors: Wu Xuanyi , Li Wenling , Rizwan Muhammad , Khalid Qazi Salman , Alkahtani Mohammed , Alqahtani Fahad M.
Published: November 2023

Manufacturing industries are in a constant state of competition to attract customers in a variety of methods. Group Technology (GT) is a term used in the field of manufacturing for grouping similar elements based on their similarities in production and design. Cellular manufacturing (CM) is an application of Group Technology (GT) that has gained widespread traction in Small- and Medium-Sized Enterprises (SMEs) during the recent years in order to increase the production floor’s efficiency and output. A Cell Formation consists of grouping identical machinery and assigning them on similar functions. There are three main decisions involved in designing the Cellular Manufacturing System (CMS): Group Scheduling (GS), Group Layout (GL), and Cell Formation (CF). In this study, the primary challenge associated with the CMS is not only the formation of cells but also the optimal placement of machinery within each cell. This paper’s objectives are therefore twofold: the formation of cells and the optimal placement of machinery within cells. For the purpose of Cell Formation and the position of machinery within the cell, a Genetic Algorithm (GA) and Encoding Scheme are employed. In this study, a Genetic Algorithm is used to classify machines and parts, while MATLAB is used for the simulation and encoding scheme. To evaluate the developed objective function and GA, a layout problem of medium size is solved. Results indicate that the proposed strategy is effective for resolving CMS issues and increasing productivity by 8.85%.
Evaluation of the Critical Parameters Involved in Decisions to Control Bactrocera oleae in Olive Orchards in the Southern Region of Lebanon
Authors: Kfoury Linda , Afram Michel , Chehade Ali , Choueiri Elia , Youssef Amira , El Romeh Samer , Joumaa Ihab , Arafat Ghazi , Elbitar Ahmad
Published: November 2023

Modern agriculture requires technology to give precise measures of relevant parameters, such as those associated with pest control. Here, we developed an algorithm model as the basis for a bait spray intervention by monitoring the olive fruit fly Bactrocera oleae (Rossi) with conventional traps covering 24.3 hectares of non-irrigated Baladi olive cultivars in the Hasbaya region. We installed 49 yellow sticky traps with ammonium bicarbonate. The adults, both males and females, were monitored on a weekly basis. The traps and trees were georeferenced, and parameters such as the temperature, relative humidity, tree phenology (BBCH), and fruit load rate were compiled. The results show that the infested fruits were correlated equally with the fruit load rate and the number of adults captured, which in turn were correlated more with the temperature than the relative humidity. The number of males captured was higher than that of females throughout the cultivation period. The first symptoms of the fruits were observed on 22 September, when the BBCH was equal to 85, with an average number of adult captures of less than five when using traps over 7 days.
Innovative Acoustic-Hydraulic Method for High-Performance Fine Liquid Atomization
Authors: Kudryashova Olga , Shalunov Andrey , Genne Dmitry , Dorovskikh Roman , Titov Sergey
Published: November 2023

Spray technology is widely used in various industries, including medicine, food production, mechanical engineering, and nanopowder manufacturing. Achieving high dispersion and a narrow particle size distribution is crucial for many applications. Ultrasonic spraying is commonly used to achieve this. On the other hand, hydraulic nozzles provide high atomization performance. Combining these two technologies promises to offer significant benefits, but the complex processes that occur simultaneously in such a device require careful study. This work proposes a fundamental design for an acoustic-hydraulic nozzle and investigates the physical processes when a liquid is sprayed using this nozzle, both theoretically and experimentally. The study identifies the critical modes of spraying and confirms that the simultaneous use of ultrasound and hydraulic pressure can produce a fine spray (droplet size less than 50 μm vs. 150–500 μm for hydrodynamic spray) with high productivity (5–10 mL/s vs. 0.5 mL/min for ultrasonic spray). This approach has significant potential for modern industries and technologies.
A Novel Method for Multistage Degradation Predicting the Remaining Useful Life of Wind Turbine Generator Bearings Based on Domain Adaptation
Authors: Tian Miao , Su Xiaoming , Chen Changzheng , An Wenjie
Published: November 2023

Predicting the remaining useful life (RUL) of wind turbine generator rolling bearings can effectively prevent damage to the transmission chain and significant economic losses resulting from sudden failures. However, the working conditions of generator bearings are variable, and the collected run-to-failure data combine multiple working conditions, which significantly impacts the accuracy of model predictions. To solve the problem, a local enhancement temporal convolutional network with multistage degenerate distribution matching based on domain adaptation (MDA-LETCN) is proposed, extracting degradation features of wind turbine generator bearings and predicting their remaining service life in composite working conditions. This method first utilizes the local enhancement temporal convolutional network (LETCN) to extract time series features and used the K-means method for unsupervised division of the degradation status of rolling bearings. Secondly, the multistage degradation stage distribution matching (MDSDM) module is proposed to learn domain-invariant temporal features at different stages of bearing degradation under composite working conditions. Finally, the model is transferred to the target bearing using some health data that are easily available from the target bearing to solve the problem of individual differences in the degradation of generator bearings in different wind turbines. Comparative experiments were conducted using actual wind farm data, and the results showed that MDA-LETCN has high prediction accuracy.
Lagrangian Vortices Interactions Using Large-Eddy Simulation (LES) and Surface Roughness Model—Application for Aircraft Wake Vortices with Crosswind
Authors: Carvalho Gabriel Ferraz Marcondes de , Vidille Marília Fernandes , Bimbato Alex Mendonça , Alcântara Pereira Luiz Antonio
Published: November 2023

A new technique for two-dimensional vortex methods is presented. The vorticity field is discretized and represented by vortex blobs. Viscosity and roughness are incorporated into vortex simulations by means of the corrected core-spreading method with LES theory. A deterministic and efficient grid-free method simulates viscous effects by maintaining small vortex core sizes through a splitting algorithm that controls the consistency error. The LES theory also enables the implementation of the roughness model. The effectiveness of this method is shown in calculating vortex interactions and decay in aircraft wakes with crosswind near a rough ground plane. The numerical results of the trajectory of primary vortical structures are compared with experimental data (when possible), suggesting the validity of the method. In general, the control of the roughness height size appears as an important factor to interfere on the trajectory of primary vortical structures in the ground effect with crosswind. The effect of the relative roughness height of ε/Δs = 0.001 shows that the primary vortical structures survive the interaction with the ground plane and can attain a maximum height in the order of 0.95 h (h is the release height of the primary vortical structures) during the loop for crosswind velocity of U∞ = 0.02 at Re = 7650. On the other hand, the combined effects of roughness ε/Δs = 0.001 and of crosswind U∞ = 0.04 at Re = 75,000 indicate that the primary vortical structures attain a maximum height about 0.83 h during the loop, tending to leave the runway faster, with sufficient intensity to disturb a smaller aircraft operating on a parallel runway.
Ex Vivo Analysis of Ability of Osseodensification to Improve Dental Implant Primary Stability Using Xenograft Bone Walls
Authors: Ferreira Henrique , Mourão Carlos Fernando , Mello-Machado Rafael Coutinho , Javid Kayvon , dos Santos Pereira Rodrigo , Senna Plinio Mendes
Published: November 2023

Osseodensification is a technique that involves compressing bone using specialized drilling instruments to increase bone–implant contact. The present study aimed to evaluate the structure of a xenograft bone (XB) wall created within an implantation site and how it affects the initial stability of dental implants. Six segments of pig ribs, representing low-density bone, were used in the experiment. Four different drilling conditions were created for each section using a tapered bur system associated with bovine xenograft bone: clockwise (cutting mode—CW) or counterclockwise (densification mode—CCW). The bone samples were then placed individually in microtomography equipment to define a volume of interest (VOI) 50% larger than the osteotomy. Mathematical calculations of bone volume, trabecular thickness and separation, and total porosity were performed. An implant with a diameter of 4.0 mm and a length of 11.5 mm was then inserted into each osteotomy. The final insertion torque (IT) and resonance frequency analysis/implant stability quotient (ISQ) values were recorded. The groups were compared using ANOVA and Tukey’s post hoc test. The results show that the use of xenograft bone produced densification at the apex region, with higher bone volume and trabecular thickness, and reduced trabecular separation compared with the CW group (p < 0.05). The CW + XB group demonstrated a similar porosity to the CCW group and similar values of IT and ISQ (p > 0.05). Compared with the other groups, CCW + XB exhibited the lowest percentual porosity and the highest values of IT and ISQ (p < 0.05). We concluded that the use of a xenograft bone wall before implant placement can improve the primary stability of dental implants.
Long Short-Term Memory Recurrent Neural Network and Extreme Gradient Boosting Algorithms Applied in a Greenhouse’s Internal Temperature Prediction
Authors: Esparza-Gómez Juan M. , Luque-Vega Luis F. , Guerrero-Osuna Héctor A. , Carrasco-Navarro Rocío , García-Vázquez Fabián , Mata-Romero Marcela E. , Olvera-Olvera Carlos Alberto , Carlos-Mancilla Miriam A. , Solís-Sánchez Luis Octavio
Published: November 2023

One of the main challenges agricultural greenhouses face is accurately predicting environmental conditions to ensure optimal crop growth. However, the current prediction methods have limitations in handling large volumes of dynamic and nonlinear temporal data, which makes it difficult to make accurate early predictions. This paper aims to forecast a greenhouse’s internal temperature up to one hour in advance using supervised learning tools like Extreme Gradient Boosting (XGBoost) and Recurrent Neural Networks combined with Long-Short Term Memory (LSTM-RNN). The study uses the many-to-one configuration, with a sequence of three input elements and one output element. Significant improvements in the R2, RMSE, MAE, and MAPE metrics are observed by considering various combinations. In addition, Bayesian optimization is employed to find the best hyperparameters for each algorithm. The research uses a database of internal data such as temperature, humidity, and dew point and external data such as temperature, humidity, and solar radiation, splitting the data into the year’s four seasons and performing eight experiments according to the two algorithms and each season. The LSTM-RNN model produces the best results for the metrics in summer, achieving an R2 = 0.9994, RMSE = 0.2698, MAE = 0.1449, and MAPE = 0.0041, meeting the acceptability criterion of ±2 °C hysteresis.
Evaluation of Forest Ecological Security and Its Influencing Factors in Multi-Climatic Zones: A Case Study of Yunnan Province
Authors: Chen Zhe , Zhang Chunhong , Raza Syed Turab
Published: November 2023

Forest ecological security is related to national ecological security. Yunnan Province has a significantly stereoscopic climate characterized by diverse and complex vegetation. Therefore, the ecological security of Yunnan Province’s forests, which span multiple climate zones, must be carefully considered. The purpose of this study is to evaluate the forest ecological security situation and influencing factors in Yunnan Province in 2017. Utilizing data from remote sensing, the Yunnan Province Yearbooks, socioeconomic statistical data, and better pressure-state-response modeling, this work produced an index system containing state and societal pressure. The evaluation indicators were weighted using a combination of entropy weighting and expert weighting, using 16 prefectures in Yunnan Province as samples. Using the fuzzy matter-element technique, the forest ecological security situation in Yunnan Province in 2017 was assessed, and the contributing causes were examined. Results indicate that there are spatial distribution differences in ecological security in various regions of Yunnan Province. The regions with the greatest indices of forest ecological security were found in Xishuangbanna in the south and Nujiang and Diqing in the northwest of Yunnan Province, while those areas with the lowest indices were distributed in Qujing and Zhaotong in the northeast and Baoshan in the west. Results of the grey relation analysis show that those factors that influence forest ecological security across different prefectures showed significant diversity. In Yunnan Province, the main influencing factors include days when the air quality reaches Level 2 or higher, the percentage of natural forest acreage and accumulation, the value of forest ecological service function per unit area, the annual average temperature, and forest coverage. The influence of the forest status index was greater than that of the forest pressure index. The findings of this work can guide decisions related to regional forest ecological security construction across multiple climate zones. In view of the differences in ecological security status and influencing factors in different regions, ecological environment governance should be adapted to local conditions to ensure the coordinated development of nature, the economy, and the ecological environment.
Natural Language Processing Adoption in Governments and Future Research Directions: A Systematic Review
Authors: Jiang Yunqing , Pang Patrick Cheong-Iao , Wong Dennis , Kan Ho Yin
Published: November 2023

Natural language processing (NLP), which is known as an emerging technology creating considerable value in multiple areas, has recently shown its great potential in government operations and public administration applications. However, while the number of publications on NLP is increasing steadily, there is no comprehensive review for a holistic understanding of how NLP is being adopted by governments. In this regard, we present a systematic literature review on NLP applications in governments by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The review shows that the current literature comprises three levels of contribution: automation, extension, and transformation. The most-used NLP techniques reported in government-related research are sentiment analysis, machine learning, deep learning, classification, data extraction, data mining, topic modelling, opinion mining, chatbots, and question answering. Data classification, management, and decision-making are the most frequently reported reasons for using NLP. The salient research topics being discussed in the literature can be grouped into four categories: (1) governance and policy, (2) citizens and public opinion, (3) medical and healthcare, and (4) economy and environment. Future research directions should focus on (1) the potential of chatbots, (2) NLP applications in the post-pandemic era, and (3) empirical research for government work.
Mushrooms as Functional Foods for Ménière’s Disease
Authors: Bell Victoria , Fernandes Tito Horácio
Published: November 2023

Food, not nutrients, is the fundamental unit in nutrition, and edible mushrooms are fungi that supply unique biological bioactive compounds, different from plant or animal origin, which significantly impact human health status. However, to date all these concepts are interpreted in different ways, with rapidly increasing knowledge on nutrition, medicine, molecular biology, and plant biotechnology changing the concepts of food, health, and agriculture. The bioactive elements conveyed by foodstuffs as nutrients or non-nutrients interfere with human metabolism and have influence on health, aging, and well-being. The influence of edible mushrooms on medicinal interventions has been known and studied for many years and their latest role in neurodegenerative disorders has been recently investigated, while their significance on many other diseases has been well demonstrated. Despite considerable research, the etiology and pathogenesis of Ménière’s disease remains controversial and undefined, although usually associated with allergic, genetic, or trauma sources, and with viral infections and/or immune system-mediated mechanisms. With treatment still unknown, our attention is towards the eventual impact of complementary dietary interventions, synthesizing the recent knowledge of some edible mushrooms and preparations on Ménière’s disease, which is a lifelong condition that can develop at any age, but most commonly emerges between 40 and 60 years of age. It is demonstrated that the oral administration of a biomass preparation, with 3 g/day of the mushroom Coriolus versicolor for 2 to 6 months, on some 40 human Ménière’s disease patients reduced systemic oxidative stress and cellular stress response, decreased the number of crises and their duration, and the frequency of symptoms, improving the clinical grading of tinnitus severity.
Icarifil, a Natural Mixture Based on L-Citrulline and L-Carnitine as a Novel Multicomponent Nutraceutical to Modulate ROS and PDE5
Authors: Amante Chiara , De Soricellis Chiara , Luccheo Gianni , Di Vernieri Anna , Luccheo Luigi , Falcone Giovanni , Del Gaudio Pasquale
Published: November 2023

Erectile dysfunction (ED) is a pathology that affects both an individual’s life and their partner’s, representing an increasing health concern. Currently, phosphodiesterase type 5 inhibitors (PDE5i) remain the first-line therapy for erectile dysfunction, and no other drugs are approved. However, the high cost of these drugs and related adverse events limit their use. Since the concept of nutraceuticals has been extended from health promotion to the treatment of diseases, in this work, a novel mixture of different natural substances named Icarifil (L-Citrulline, L-Carnitine, Eruca vesicaria, Panax ginseng, Tribulus terrestris, Turnera diffusa, Taurine, Vitamin E, Zinc) was studied to verify its ability to increase the proliferation of muscle epithelium cells and cell turgor, as well as, due to containing antioxidants, its ability to reduce the amount of ROS that are mediators in the pathophysiological process of ED. Moreover, Icarifil showed efficacy in inhibiting PDE5 levels higher than 65% compared to the control and 35% compared to the mixture of L-Citrulline and L-Carnitine, the major components of the formulation. In association with the low dosage of a phosphodiesterase (PDE) inhibitor (tadalafil), the inhibitory capacity of tadalafil was significantly increased and comparable to high-dosage drug response, promoting the possibility of reducing the daily dosage of the drug and consequently its adverse effects.
3D Printing Progress in Gluten-Free Food—Clustering Analysis of Advantages and Obstacles
Authors: Lisovska Tetiana , Harasym Joanna
Published: November 2023

Gluten-free food is a huge group of products whose common characteristics are recipes containing non-gluten flour or starches. Most of them are bakery-related products which initially were manufactured based on the recipe containing wheat/wheat flour. Nowadays, the growth of the gluten-free food sector is mainly powered more by trends and personal choices of consumers following the “healthy choice” diet than patients with real medical conditions, who need to follow the strict gluten-free diet. 3D printing is considered a disruptive technology, and being an additive manufacturing technique contributes directly to structure/texture creation. Food 3D printing as a manufacturing technology is struggling with repeatability and precision but is still very promising as a potential problem solver, especially in texture creation, which is the main technological problem for the gluten-free bakery. The article aims to analyze, using clustering analysis, the main obstacles so far identified for gluten-free 3D printing. Meanwhile, the prospects of producing personalized food products using 3D printing and its relationship with the UN Sustainable Development Goals 2030 as the advantages of this technology were discussed. The up-to-date exploitations of 3D printing techniques in gluten-free food manufacturing were discussed.
Comparison of Steviol Glycosides or Stevia Leaves Addition to the Hypercholesterolemic Diet on Selected Biochemical Parameters of Experimental Rats
Authors: Piątkowska Ewa , Leszczyńska Teresa , Piekło Barbara , Kopeć Aneta , Bieżanowska-Kopeć Renata
Published: November 2023

Stevia rebaudiana, as a plant with favorable technological features, and, above all, with potential health-promoting properties, seems to be an ideal sugar substitute. The aim of this study was to compare the effect of adding pure steviol glycosides or Stevia leaves to a hypercholesterolemic diet on selected growth and biochemical parameters of experimental (non-diabetes) rats. The research material consisted of dried leaves of Stevia (Stevia rebaudiana Bertoni, Polish, Brazilian and Paraguayan origin) and steviol glycosides (GS). In the animal experiment, young male Wistar rats were used. The animals were divided into six experimental groups, six rats per group, and placed in individual metabolic cages, provided with drinking bowls and feeders. The animals from particular groups received a semi-synthetic AIN-93G diet for growing rats or its modification (group I—AIN-93G diet; group II—hypercholesterolemic diet; group III—hypercholesterolemic diet with 0.28 g of GS/kg of diet; group IV; V; VI—hypercholesterolemic diet with dried Stevia leaves addition from Polish (PL), Brazilian (BR) and Paraguayan (PR) cultivation) in amounts providing GS as in group III, i.e., 10, 17 and 18%, respectively. The addition of GS to the hypercholesterolemic diet resulted only in a tendency to lower the weight of the kidneys, heart and liver compared to animals fed with the hypercholesterolemic diet. The lowest glucose concentration was found in animals receiving the 17%BR diet. In general, all lipid profile parameters were similar or increased in rats fed the hypercholesterolemic diet with the addition of steviol glycosides and Stevia leaves, respectively. The highest antioxidant activity was recorded in the blood serum of rats fed the hypercholesterolemic diet with 10%PL dried Stevia leaves addition.
Relationship between Carotid Artery Calcification and Periodontitis in the Saudi Population: A Retrospective Study
Authors: Ibraheem Wael I. , Bhati Ashok Kumar , Alhomood Manar Ali , Allayl Omaima Ahmed , Qsadi Alzhouor Ali , Mohammed Tahani Ibrahim Mnaji , Aljabri Yahya Sulaiman
Published: November 2023

Background: Atherosclerosis is the primary cause of cardiovascular death, wherein plaque accumulates in the carotid artery, resulting in the formation of carotid artery calcification (CAC). Chronic infections emulate atherosclerosis development. Periodontitis is a chronic disease commenced by biofilm aggregation on the surface of teeth, which then progresses via deregulated local and inflammatory immune responses. Aim: The aim of this study was to determine the prevalence of calcification in periodontitis patients and to determine if there is a relationship between carotid calcification and periodontitis with risk factors such as age, gender, hypertension, diabetes, smoking. Methods: The data and panoramic radiographs (PR) of 3000 patients from January 2017 to February 2022 were examined. On the basis of the inclusion and exclusion criteria, 500 patients were selected for determining carotid calcification. Non-periodontitis patients, patients <40 years of age, patients without any medical data or incomplete medical records and cases where the OPG was not clear were not included in this study. The data were analyzed using R and GraphPad Prism software version 4.1.2 and Microsoft Excel Worksheet Office 2019. Chi-square tests were used to check the dependency among the categorical variables. Mann–Whitney U-tests were used to compare the distribution of the variables across the groups, and p-values < 0.05 were interpreted as statistically significant. Result: Twenty-five (5%) patients showed carotid calcification. Carotid calcification was seen more in females than in males, which was statistically significant. Gender, percentage of alveolar bone loss and periodontal risk were found to be statistically significantly related to carotid artery calcification. Factors such as age, diabetes and hypertension were found to be statistically nonsignificant. Conclusions: More periodontal destruction was present in the CAC patients. Within the limitations of this study, it can be concluded that CAC is associated with periodontitis. Early recognition of carotid calcification is important, and patients in whom carotid artery calcification is observed via their PR should be referred to medical practitioners for further investigation and treatment care.
Fulvic Acid Alleviates the Toxicity Induced by Calcium Nitrate Stress by Regulating Antioxidant and Photosynthetic Capacities and Nitrate Accumulation in Chinese Flowering Cabbage Seedlings
Authors: Wu Xue , Zhang Ying , Chu Yufeng , Yan Yifei , Wu Cuinan , Cao Kai , Ye Lin
Published: November 2023

Continuous cropping can lead to an excessive accumulation of nitrate in facility-cultured soil. Excessive accumulation of nitrate gradually becomes the main reason for crop failure in vegetables and endangers human health. Therefore, the exploration of effective measures to decrease abundant nitrate accumulation in Chinese flowering cabbage is indispensable. In this study, a kind of plant growth regulator, fulvic acid (FA), was used to study its positive effect on alleviating the growth inhibition induced by excessive Ca(NO3)2 in Chinese flowering cabbage. Meanwhile, we conducted hydroponic cultivation and measured the growth indices, photosynthetic and oxidation-reduction characteristics of Chinese flowering cabbage with different treatments. After determining the optimal treatment concentration, we mainly designed four treatment groups, including Con, FA, Ca(NO3)2 and FA + Ca(NO3)2 cotreatment, to explore the regulatory mechanism by which FA alleviates Ca(NO3)2 stress in Chinese flowering cabbage. The results showed that FA can effectively alleviate the inhibitory effect of excessive Ca(NO3)2 on the growth of Chinese flowering cabbage seedlings. FA recovered the photosynthetic capacity of seedlings under Ca(NO3)2 stress. In addition, FA depressed the accumulation of O2·−, H2O2, malondialdehyde (MDA) and relative electrical conductivity, but increased the activity of antioxidant enzymes, including SOD, POD, CAT and APX, which finally enhanced the stress resistance of Chinese flowering cabbage to Ca(NO3)2. The expression of nitrate-related transporters, BcNRT1.1 and BcNRT1.5, was depressed by FA, which inhibited redundant nitrate absorption and restricted more nitrate from being stored in the roots instead of being transferred to the shoot. Ultimately, nitrate accumulation in the edible part was reduced in Chinese flowering cabbage seedlings. In general, exogenous FA may alleviate nitrate stress by improving oxidation resistance, photosynthetic capacity and redundant Ca(NO3)2 accumulation in Chinese flowering cabbage.
On the Use of Drilling Degrees of Freedom to Stabilise the Augmented Finite Element Method
Authors: Essongue Simon , Couégnat Guillaume , Martin Eric
Published: November 2023

The augmented finite element method (AFEM) embeds cracks within solid elements. These cracks are modelled without additional degrees of freedom thanks to a dedicated static condensation process. However, static condensation can induce a lack of constraint problem, resulting in singular stiffness matrices. To address this issue, we propose a new method called the stabilised augmented finite element method (SAFEM), which produces non-singular stiffness matrices. We conducted 2D experiments involving stationary traction-free cracks and propagating cohesive discontinuities to compare the performance of the SAFEM with the AFEM. The SAFEM outperforms the AFEM in modelling traction-free cracks.
Guiding as a General Consequence of the Charged Particle Interaction with the Inner Surface of an Insulator Capillary—Guiding of 1 MeV Proton Microbeam through Polytetrafluoroethylene Macrocapillary
Authors: Tőkési Károly , Rajta István , Nagy Gyula , Bereczky Réka Judit
Published: November 2023

The transmission of energetic, 1 MeV proton microbeam through a single, cylindrical shaped, macrometer-sized polytetrafluoroethylene capillary was studied experimentally. The capillary axis was tilted with respect to the axis of the incident ion beam. The tilting, the aspect ratio of the capillary and the small beam divergence disabled the geometrical transmission of the beam through the target. The intensity, energy, deflection and charge state of the transmitted beam were investigated. We found that the pure guided transmission of a MeV/amu energy ion beam is observable. We clearly identified three completely different stages during the guiding process according to the measured energy distribution of transmitted particles. At the beginning the transmission intensity was low and only inelastic contributions with energy lower than 1 MeV were found in the spectrum. Later, in the second stage, the elastic peak appeared and became more and more significant. Finally, when the stable transmission evolved, only the elastic peak was present and the inelastic area was totally absent as a direct consequence of the ion guiding and as a result of the charged particle interaction with a charged inner surface of the insulator capillary.
The Vortex Surface in a Three-Body Quantum System
Authors: Guarda Tamara A. , Navarrete Francisco , Barrachina Raúl O.
Published: November 2023

Vortices are structures known in our daily lives and observed in a wide variety of systems, from cosmic to microscopic scales. Relatively recent studies showed that vortices could also appear in simple quantum systems. For instance, they were observed experimentally and theoretically as isolated zeros in the differential cross section in atomic ionization processes by the impact of charged particles. In this work, we show that the appearance of these quantum vortices as point structures was not due to any intrinsic property of them, but to the use of restrictive geometries in their visualization. In particular, we show that by studying the fully differential cross section for hydrogen ionization by positron impact, these vortex points are actually a manifestation of a more complex and hitherto unexplored structure, a 3D “vortex surface”.
A Hyperparameter Self-Evolving SHADE-Based Dendritic Neuron Model for Classification
Authors: Yang Haichuan , Zhang Yuxin , Zhang Chaofeng , Xia Wei , Yang Yifei , Zhang Zhenwei
Published: November 2023

In recent years, artificial neural networks (ANNs), which are based on the foundational model established by McCulloch and Pitts in 1943, have been at the forefront of computational research. Despite their prominence, ANNs have encountered a number of challenges, including hyperparameter tuning and the need for vast datasets. It is because many strategies have predominantly focused on enhancing the depth and intricacy of these networks that the essence of the processing capabilities of individual neurons is occasionally overlooked. Consequently, a model emphasizing a biologically accurate dendritic neuron model (DNM) that mirrors the spatio-temporal features of real neurons was introduced. However, while the DNM shows outstanding performance in classification tasks, it struggles with complexities in parameter adjustments. In this study, we introduced the hyperparameters of the DNM into an evolutionary algorithm, thereby transforming the method of setting DNM’s hyperparameters from the previous manual adjustments to adaptive adjustments as the algorithm iterates. The newly proposed framework, represents a neuron that evolves alongside the iterations, thus simplifying the parameter-tuning process. Comparative evaluation on benchmark classification datasets from the UCI Machine Learning Repository indicates that our minor enhancements lead to significant improvements in the performance of DNM, surpassing other leading-edge algorithms in terms of both accuracy and efficiency. In addition, we also analyzed the iterative process using complex networks, and the results indicated that the information interaction during the iteration and evolution of the DNM follows a power-law distribution. With this finding, some insights could be provided for the study of neuron model training.
The Multivariable Zhang–Zhang Polynomial of Phenylenes
Authors: Tratnik Niko
Published: November 2023

The Zhang–Zhang polynomial of a benzenoid system is a well-known counting polynomial that was introduced in 1996. It was designed to enumerate Clar covers, which are spanning subgraphs with only hexagons and edges as connected components. In 2018, the generalized Zhang–Zhang polynomial of two variables was defined such that it also takes into account 10-cycles of a benzenoid system. The aim of this paper is to introduce and study a new variation of the Zhang–Zhang polynomial for phenylenes, which are important molecular graphs composed of 6-membered and 4-membered rings. In our case, Clar covers can contain 4-cycles, 6-cycles, 8-cycles, and edges. Since this new polynomial has three variables, we call it the multivariable Zhang–Zhang (MZZ) polynomial. In the main part of the paper, some recursive formulas for calculating the MZZ polynomial from subgraphs of a given phenylene are developed and an algorithm for phenylene chains is deduced. Interestingly, computing the MZZ polynomial of a phenylene chain requires some techniques that are different to those used to calculate the (generalized) Zhang–Zhang polynomial of benzenoid chains. Finally, we prove a result that enables us to find the MZZ polynomial of a phenylene with branched hexagons.
Empowering Propaganda Detection in Resource-Restraint Languages: A Transformer-Based Framework for Classifying Hindi News Articles
Authors: Chaudhari Deptii , Pawar Ambika Vishal
Published: November 2023

Misinformation, fake news, and various propaganda techniques are increasingly used in digital media. It becomes challenging to uncover propaganda as it works with the systematic goal of influencing other individuals for the determined ends. While significant research has been reported on propaganda identification and classification in resource-rich languages such as English, much less effort has been made in resource-deprived languages like Hindi. The spread of propaganda in the Hindi news media has induced our attempt to devise an approach for the propaganda categorization of Hindi news articles. The unavailability of the necessary language tools makes propaganda classification in Hindi more challenging. This study proposes the effective use of deep learning and transformer-based approaches for Hindi computational propaganda classification. To address the lack of pretrained word embeddings in Hindi, Hindi Word2vec embeddings were created using the H-Prop-News corpus for feature extraction. Subsequently, three deep learning models, i.e., CNN (convolutional neural network), LSTM (long short-term memory), Bi-LSTM (bidirectional long short-term memory); and four transformer-based models, i.e., multi-lingual BERT, Distil-BERT, Hindi-BERT, and Hindi-TPU-Electra, were experimented with. The experimental outcomes indicate that the multi-lingual BERT and Hindi-BERT models provide the best performance, with the highest F1 score of 84% on the test data. These results strongly support the efficacy of the proposed solution and indicate its appropriateness for propaganda classification.
Quantitative Evaluation of Caries and Calculus with Ultrahigh-Resolution Optical Coherence Tomography
Authors: Wang Tai-Ang , Trung Nguyễn Hoàng , Lee Hsiang-Chieh , Lee Cheng-Kuang , Tsai Meng-Tsan , Wang Yen-Li
Published: November 2023

Dental caries on the crown’s surface is caused by the interaction of bacteria and carbohydrates, which then gradually alter the tooth’s structure. In addition, calculus is the root of periodontal disease. Optical coherence tomography (OCT) has been considered to be a promising tool for identifying dental caries; however, diagnosing dental caries in the early stage still remains challenging. In this study, we proposed an ultrahigh-resolution OCT (UHR-OCT) system with axial and transverse resolutions of 2.6 and 1.8 μm for differentiating the early-stage dental caries and calculus. The same teeth were also scanned by a conventional spectral-domain OCT (SD-OCT) system with an axial resolution of 7 μm. The results indicated that early-stage carious structures such as small cavities can be observed using UHR-OCT; however, the SD-OCT system with a lower resolution had difficulty identifying it. Moreover, the estimated surface roughness and the scattering coefficient of enamel were proposed for quantitatively differentiating the different stages of caries. Furthermore, the thickness of the calculus can be estimated from the UHR-OCT results. The results have demonstrated that UHR-OCT can detect caries and calculus in their early stages, showing that the proposed method for the quantitative evaluation of caries and calculus is potentially promising.
The Role of the Insulin/Glucose Ratio in the Regulation of Pathogen Biofilm Formation
Authors: Plotkin Balbina J. , Halkyard Scott , Spoolstra Emily , Micklo Amanda , Kaminski Amber , Sigar Ira M. , Konaklieva Monika I.
Published: November 2023

During the management of patients in acute trauma the resulting transient hyperglycemia is treated by administration of insulin. Since the effect of insulin, a quorum sensing compound, together with glucose affects biofilm formation in a concentration-specific manner, we hypothesize that the insulin/glucose ratio over the physiologic range modulates biofilm formation potentially influencing the establishment of infection through biofilm formation. Methods: A variety of Gram-positive and Gram-negative bacteria were grown in peptone (1%) yeast nitrogen base broth overnight in 96-well plates with various concentrations of glucose and insulin. Biofilm formation was determined by the crystal violet staining procedure. Expression of insulin binding was determined by fluorescent microscopy (FITC-insulin). Controls were buffer alone, insulin alone, and glucose alone. Results: Overall, maximal biofilm levels were measured at 220 mg/dL of glucose, regardless of insulin concentration (10, 100, 200 µU/mL) of the organism tested. In general, insulin with glucose over the range of 160–180 mg/dL exhibited a pattern of biofilm suppression. However, either above or below this range, the presence of insulin in combination with glucose significantly modulated (increase or decrease) biofilm formation in a microbe-specific pattern. This modulation appears for some organisms to be reflective of the glucose-regulated intrinsic expression of bacterial insulin receptor expression. Conclusion: Insulin at physiologic levels (normal and hyperinsulinemic) in combination with glucose can affect biofilm formation in a concentration-specific and microbe-specific manner. These findings may provide insight into the importance of co-regulation of the insulin/glucose ratio in patient management.
Ellagic Acid and Cancer Hallmarks: Insights from Experimental Evidence
Authors: Čižmáriková Martina , Michalková Radka , Mirossay Ladislav , Mojžišová Gabriela , Zigová Martina , Bardelčíková Annamária , Mojžiš Ján
Published: November 2023

Cancer is a complex and multifaceted disease with a high global incidence and mortality rate. Although cancer therapy has evolved significantly over the years, numerous challenges persist on the path to effectively combating this multifaceted disease. Natural compounds derived from plants, fungi, or marine organisms have garnered considerable attention as potential therapeutic agents in the field of cancer research. Ellagic acid (EA), a natural polyphenolic compound found in various fruits and nuts, has emerged as a potential cancer prevention and treatment agent. This review summarizes the experimental evidence supporting the role of EA in targeting key hallmarks of cancer, including proliferation, angiogenesis, apoptosis evasion, immune evasion, inflammation, genomic instability, and more. We discuss the molecular mechanisms by which EA modulates signaling pathways and molecular targets involved in these cancer hallmarks, based on in vitro and in vivo studies. The multifaceted actions of EA make it a promising candidate for cancer prevention and therapy. Understanding its impact on cancer biology can pave the way for developing novel strategies to combat this complex disease.