bluuebunny/crossref_metadata_2025 huggingface dataset:
Absorption of Millimeter-band CO and CN in the Early Universe: Molecular Clouds in the Radio Galaxy B2 0902+34 at Redshift 3.4
Authors: Emonts Bjorn H. C. , Curran Steve J. , Miley George K. , Lehnert Matthew D. , Carilli Chris L. , Yoon Ilsang , Morganti Raffaella , van Weeren Reinout J. , Villar-Martín Montserrat , Guillard Pierre , Cordun Cristina M. , Oosteroo Tom A.
Published: February 2024

Using the Karl G. Jansky Very Large Array, we have detected absorption lines due to carbon monoxide, CO(J = 0 → 1), and the cyano radical, CN(N = 0 → 1), associated with radio galaxy B2 0902+34 at redshift z = 3.4. The detection of millimeter-band absorption observed 1.5 Gyr after the Big Bang facilitates studying molecular clouds down to gas masses inaccessible to emission-line observations. The CO absorption in B2 0902+34 has a peak optical depth of τ ≥ 8.6% and consists of two components, one of which has the same redshift as previously detected 21 cm absorption of neutral hydrogen (H i) gas. Each CO component traces an integrated H2 column density of

N

H

2

≳ 3 × 1020 cm−2. CN absorption is detected for both CO components, as well as for a blueshifted component not detected in CO, with CO/CN line ratios ranging from ≲0.4 to 2.4. We discuss the scenario that the absorption components originate from collections of small and dense molecular clouds that are embedded in a region with more diffuse gas and high turbulence, possibly within the influence of the central active galactic nucleus or a starburst region. The degree of reddening in B2 0902+34, with rest-frame color B − K ∼ 4.2, is lower than the very red colors (B − K > 6) found among other known redshifted CO absorption systems at z < 1. Nevertheless, when including the many nondetections from the literature, a potential correlation between the absorption-line strength and B − K color is evident, giving weight to the argument that the red colors of CO absorbers are due to a high dust content.
A Comparative Analysis of the Solar Ultraviolet Spectral Irradiance Measured from Earth and Mars: Toward a General Empirical Model for the Study of Planetary Aeronomy
Authors: Xu Zhen , Qin Jianqi
Published: February 2024

Accurate estimation of the solar vacuum ultraviolet irradiance between 0.1 and 200 nm is critical for the study of planetary aeronomy. Previous empirical models have relied on a limited number of reference spectra, or on multiple data sets with various degrees of uncertainty, and on an empirical selection of solar proxies. Here we propose a novel method for the development of empirical models based on Fourier transform and least-squares fitting of the long-term measurements from the Solar EUV Experiment on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission. A Fourier transform analysis is performed to examine a large number of solar proxies, which reveals that the solar radio flux at 10.7 cm and the solar Lyα flux at 121.6 nm are better proxies for solar irradiance below and above ∼120 nm, respectively. Using these two proxies, a nonlinear empirical model is developed through Fourier transform and least-squares fitting of solar irradiance measurements, which can reproduce the solar irradiance with uncertainties of only ∼1%–2% above ∼120 nm, ∼2%–4% within ∼45–120 nm, and ∼4%–8% below ∼45 nm. Comparison with measurements from the Extreme Ultraviolet Monitor on the Mars Atmosphere and Volatile Evolution mission indicates that the solar irradiance at Mars can be predicted with uncertainties of less than ∼8% by geometric extrapolation of the solar irradiance measured from Earth, provided that the measurements from Earth can be calibrated accurately. Our study provides a general method for the development of empirical models using long-term observations in planetary aeronomy.
Identification of Carbon Stars from LAMOST DR7
Authors: Li Linlin , Zhang Kecheng , Cui Wenyuan , Shi Jianrong , Ji Wei , Huo Zhenyan , Gao Yawei , Zhang Shuai , Sun Mingxu
Published: February 2024

Carbon stars are excellent kinematic tracers of galaxies and play important roles in understanding the evolution of the Galaxy. Therefore, it is worthwhile to search for them in a large number of spectra. In this work, we build a new carbon star catalog based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) DR7 spectra. The catalog contains 4542 spectra of 3546 carbon stars, identified through line index and near-infrared color–color diagrams. Through visual inspection of the spectra, we further subclassify them into 925 C–H, 384 C–R, 608 C–N, and 1292 Ba stars. However, 437 stars could not be subclassified due to their low signal-to-noise. Moreover, by comparing with the LAMOST DR7 pipeline we find 567 more carbon stars and visually subclassify them. We find that on the J − H versus H − K

s
two-color diagram, C–N stars can be reliably distinguished from the other three subtypes. Additionally, by utilizing the Gaia distance, we study the distribution of carbon stars in the H-R diagram and identify 258 dwarf carbon stars by the criterion M

G
> 5.0 mag. Finally, we present the spatial distribution in Galactic coordinates of the 3546 carbon stars. The majority of C–N, C–R, and Ba stars are distributed at low Galactic latitudes, while most C–H and dwarf carbon stars are distributed at high Galactic latitudes.
Voyager 1 Electron Densities in the Very Local Interstellar Medium to beyond 160 au
Authors: Kurth W. S.
Published: February 2024

The two Voyager spacecraft have been exploring the interstellar medium beyond the heliopause since 2012 (Voyager 1) and 2018 (Voyager 2). Electron plasma oscillations and a quasi-thermal noise line at the electron plasma frequency have enabled the determination of the electron density in this region, revealing a radial density gradient convolved with shocks and pressure fronts. Voyager 1 has a functioning wideband receiver that provides high-spectral-resolution observations allowing the detection of the quasi-thermal noise line and has now provided electron densities to 161.4 au. Since a pressure pulse observed in 2020 around day 146 at about 149 au, the density has remained relatively constant at 0.147 cm−3 based on the most recent observations from 2023, suggesting that Voyager 1 has reached a broad density peak and possibly a new regime.
Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings
Authors: Almudaris Sally Ayad , Gatea Fouad Kadhim
Published: February 2024

Aim: investigate the possible anti-psoriatic effect of ivermectin in mice based on observational and histopathological outcomes and biomarkers.

Methods: Sixty male Swiss Albino Mice were divided into six groups (Groups I–VI); each group contained ten mice with shaved dorsal skin. The clinical, pathological, and laboratory effects were measured.

Results: Topical Ivermectin significantly decreased vascular endothelial growth factor levels. At the same time, the combination of ivermectin plus Clobetasol showed a more significant reduction in tumor necrosis factor-alpha (TNF-α) and Interleukin-17 (IL-17) levels. Regarding the Interleukin-10 (IL-10) level, the Ivermectin and Ivermectin/Clobetasol combination groups showed a significant increase in IL-10.

Conclusion: Topical Ivermectin’s anti-psoriasis activity increases IL-10 levels and could be used efficiently to alleviate psoriatic symptoms. Its combination treatment with Clobetasol holds promise for the management of psoriasis.
Cas en logistique et Supply Chain Management
Authors: Hamouda Ibtissem
Published: February 2024

Énoncé
Cas en logistique et Supply Chain Management
Authors: Guillaud Romain , Huc Morgan , Fulconis François , Paché Gilles
Published: February 2024

Énoncé Avec quatre hôpitaux (Centre Hospitalier de la Timone, Hôpital Nord, Hôpital de la Conception et Hôpitaux Sud [Sainte-Marguerite et Salvator]), un Espace Santé (lieu de santé hors les murs dans les lieux de vie des plus défavorisés) et 3 200 lits, l’Assistance Publique-Hôpitaux de Marseille (AP-HM) est le troisième Centre Hospitalier Universitaire (CHU) de France, dont le budget 2022 est d’environ 1,4 milliard d’euros. C’est aussi le premier employeur de la région PACA, avec plus de 15 000 salariés et près de 2 000 médecins. Ses différents établissements offrent toute la gamme des spécialités, du soin de proximité aux traitements de pointe de pathologies complexes et rares, pour adultes et pour enfants. Ses missions sont le soin, la formation, la recherche, ainsi que la prévention et l’éducation à la santé. L’AP-HM a rejoint par ailleurs Aix-Marseille Université (AMU) et Avignon Université (AU) dans le cadre de l’incubateur inter-universitaire Impulse. L’objectif de cet incubateur est d’encourager des démarches de création d’entreprises innovantes susceptibles d’apporter aux patients une meilleure qualité de soins, mais également de générer des innovations de rupture concernant les traitements de pathologies lourdes. Pour une meilleure compréhension des forces, faiblesses, menaces et opportunités, le tableau 1 présente un diagnostic SWOT de l’AP-HM réalisé par l’Agence régionale de santé PACA en 2020.
Cas en logistique et Supply Chain Management
Authors: Merminod Nathalie , Allègre Thierry
Published: February 2024

Énoncé
Cas en logistique et Supply Chain Management
Authors: Capo Claire , Michon Valérie
Published: February 2024

Énoncé La mutualisation de drives urbains réalisée par FM Logistic pour son client distributeur 1 de mars 2020 à début 2022 relève du développement d’une nouvelle solution logistique par l’entreprise dans le secteur de la grande distribution. Après avoir présenté l’entreprise, FM Logistic, un point sur le contexte du projet spécifique des drives en milieu urbain sera fait avant de décrire le partenariat construit autour du projet de mutualisation.
Cas en logistique et Supply Chain Management
Authors: Oruezabala Gwenaëlle , Bidan Marc
Published: February 2024

Énoncé
Asymptotic behavior of a Balakrishnan-Taylor suspension bridge
Authors: Hajjej Zayd
Published: February 2024

In this manuscript, we examine a nonlinear Cauchy problem aimed at describing the deformation of the deck of either a footbridge or a suspension bridge in a rectangular domain $ \Omega = (0, \pi)\times (-d, d) $, with $ d < < \pi $, incorporating hinged boundary conditions along its short edges, as well as free boundary conditions along its remaining free edges. We establish the existence of solutions and the exponential decay of energy.
The multiplicative degree-Kirchhoff index and complexity of a class of linear networks
Authors: Liu Jia-Bao , Wang Kang
Published: February 2024

In this paper, we focus on the strong product of the pentagonal networks. Let $ R_{n} $ be a pentagonal network composed of $ 2n $ pentagons and $ n $ quadrilaterals. Let $ P_{n}^{2} $ denote the graph formed by the strong product of $ R_{n} $ and its copy $ R_{n}^{\prime} $. By utilizing the decomposition theorem of the normalized Laplacian characteristics polynomial, we characterize the explicit formula of the multiplicative degree-Kirchhoff index completely. Moreover, the complexity of $ P_{n}^{2} $ is determined.
Oncolysis by SARS-CoV-2: modeling and analysis
Authors: Agha Afnan Al , Garalleh Hakim Al
Published: February 2024

The relationship between cancer and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is controversial. While SARS-CoV-2 can worsen the status of a cancer patient, many remission cases after SARS-CoV-2 infection have been recorded. It has been suggested that SARS-CoV-2 could have oncolytic properties, which needs further investigations. Mathematical modeling is a powerful tool that can significantly enhance experimental and medical studies. Our objective was to propose and analyze a mathematical model for oncolytic SARS-CoV-2 with immunity. The basic properties of this model, including existence, uniqueness, nonnegativity, and boundedness of the solutions, were confirmed. The equilibrium points were computed, and their existence conditions were determined. The global stability of the equilibria was proven using the Lyapunov theory. Numerical simulations were implemented to validate the theoretical results. It was found that the model has thirteen equilibrium points that reflect different infection states. Based on the model's results, the infection of cancer cells by SARS-CoV-2 can lead to a reduction in the concentration of cancer cells. Additionally, the induction of cytotoxic T lymphocytes (CTLs) decreases the number of cancer cells, potentially resulting in cancer remission or an improvement in the overall health of cancer patients. This theoretical result aligns with numerous studies highlighting the oncolytic role of SARS-CoV-2. In addition, given the limited availability of real data, further studies are essential to better comprehend the role of immune responses and their impact on the oncolytic role of SARS-CoV-2.
Exploring Multiple-Objective Optimization for Efficient and Effective Test Paper Design with Dynamic Programming Guided Genetic Algorithm
Authors: Wang Han , Zhuge Qingfeng , Sha Edwin Hsing-Mean , Xia Jianghua , Xu Rui
Published: February 2024

Automatic test paper design is critical in education to reduce workloads for educators and facilitate an efficient teaching process. However, current designs fail to satisfy the realistic teaching requirements of educators, including the consideration of both test quality and efficiency. This is the main reason why teachers still manually construct tests in most teaching environments. In this paper, the quality of tests is quantitatively defined while considering multiple objectives, including a flexible coverage of knowledge points, cognitive levels, and question difficulty. Then, a model based on the technique of linear programming is delicately designed to explore the optimal results for this newly defined problem. However, this technique is not efficient enough, which cannot obtain results in polynomial time. With the consideration of both test quality and generation efficiency, this paper proposes a genetic algorithm (GA) based method, named dynamic programming guided genetic algorithm with adaptive selection (DPGA-AS). In this method, a dynamic programming method is proposed in the population initialization part to improve the efficiency of the genetic algorithm. An adaptive selection method for the GA is designed to avoid prematurely falling into the local optimal for better test quality. The question bank used in our experiments is assembled based on college-level calculus questions from well-known textbooks. The experimental results show that the proposed techniques can construct test papers with both high effectiveness and efficiency. The computation time of the test assembly problem is reduced from 3 hours to 2 seconds for a 5000-size question bank as compared to a linear programming model with similar test quality. The test quality of the proposed method is better than the other baselines.
A predator-prey fractional model with disease in the prey species
Authors: Domínguez-Alemán Ilse , Domínguez-Alemán Itzel , Hernández-Gómez Juan Carlos , Ariza-Hernández Francisco J.
Published: February 2024

In this paper, we study a generalized eco-epidemiological model of fractional order for the predator-prey type in the presence of an infectious disease in the prey. The proposed model considers that the disease infects the prey, causing them to be divided into two classes, susceptible prey and infected prey, with different density-dependent predation rates between the two classes. We propose logistic growth in both the prey and predator populations, and we also propose that the predators have alternative food sources (i.e., they do not feed exclusively on these prey). The model is evaluated from the perspective of the global and local generalized derivatives by using the generalized Caputo derivative and the generalized conformable derivative. The existence, uniqueness, non-negativity, and boundedness of the solutions of fractional order systems are demonstrated for the classical Caputo derivative. In addition, we study the stability of the equilibrium points of the model and the asymptotic behavior of its solution by using the Routh-Hurwitz stability criteria and the Matignon condition. Numerical simulations of the system are presented for both approaches (the classical Caputo derivative and the conformable Khalil derivative), and the results are compared with those obtained from the model with integro-differential equations. Finally, it is shown numerically that the introduction of a predator population in a susceptible-infectious system can help to control the spread of an infectious disease in the susceptible and infected prey population.
Drawing a parallel between the trend of confirmed COVID-19 deaths in the winters of 2022/2023 and 2023/2024 in Italy, with a prediction
Authors: Roccetti Marco
Published: February 2024

We studied the weekly number and the growth/decline rates of COVID-19 deaths of the period from October 31, 2022, to February 9, 2023, in Italy. We found that the COVID-19 winter wave reached its peak during the three holiday weeks from December 16, 2022, to January 5, 2023, and it was definitely trending downward, returning to the same number of deaths as the end of October 2022, in the first week February 2023. During this period of 15 weeks, that wave caused a number of deaths as large as 8,526. Its average growth rate was +7.89% deaths per week (10 weeks), while the average weekly decline rate was -15.85% (5 weeks). At the time of writing of this paper, Italy has been experiencing a new COVID-19 wave, with the latest 7 weekly bulletins (October 26, 2023 – December 13, 2023) showing that deaths have climbed from 148 to 322. The weekly growth rate had risen by +14.08% deaths, on average. Hypothesizing that this 2023/2024 wave will have a total duration similar to that of 2022/2023, with comparable extensions of both the growth period and the decline period and similar growth/decline rates, we predict that the number of COVID-19 deaths of the period from the end of October 2023 to the beginning of February 2024 should be less than 4100. A preliminary assessment of this forecast, based on 11 of the 15 weeks of the period, has already confirmed the accuracy of this approach.
Predicting the cognitive function status in end-stage renal disease patients at a functional subnetwork scale
Authors: Lu Yu , Liu Tongqiang , Sheng Quan , Zhang Yutao , Shi Haifeng , Jiao Zhuqing
Published: February 2024

Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are taken as the features from the overall perspective. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. To address this issue, we proposed a framework to predict the cognitive function status in the patients with end-stage renal disease (ESRD) at a functional subnetwork scale (CFSFSS). The nodes from different network indicators were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combination with improved fitness was searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the parameters of support vector regression (SVR) and solve the global optimization problem of the predictive model. Experimental results indicated that CFSFSS achieved superior predictive performance compared to other methods, by which the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were up to 0.5951, 0.0281 and 0.9994, respectively. The functional subnetwork effectively identified the active brain regions associated with the cognitive function status, which offered more precise features. It not only helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients.
Excess Deaths During the COVID-19 Pandemic in Southern Iran: Estimating the Absolute Count and Relative Risk Using Ecological Data
Authors: Zakeri Mohammadreza , Mirahmadizadeh Alireza , Azarbakhsh Habibollah , Dehghani Seyed Sina , Janfada Maryam , Moradian Mohammad Javad , Moftakhar Leila , Sharafi Mehdi , Heiran Alireza
Published: February 2024

Objectives: The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran.Methods: The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic.Results: Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22).Conclusions: There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.
Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand
Authors: Roudreo Benjawan , Puangthongthub Sitthichok
Published: February 2024

Objectives: Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous.Methods: This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand’s Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels.Results: Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak.Conclusions: Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.
Rafael Cansinos Assens y su crítica adversa del ultraísmo, 1922-1929
Authors: Anderson Andrew A.
Published: February 2024

Rafael Cansinos Assens desempeñó un papel clave en la fundación y el lanzamiento del movimiento ultraísta, y durante sus primeros años de existencia lo apoyó con entusiasmo. Sin embargo, gradualmente se desilusionó y se distanció del grupo, llegando a escribir la novela satírica El movimiento V.P. en 1921. En sus escritos periodísticos posteriores, de 1922 a 1929, vuelve sobre el tema del ultraísmo con frecuencia, y aquí manifiesta actitudes dispares, con algunas notas de nostalgia, pero principalmente la neutralidad de un historiador objetivo o la negatividad de un crítico adverso. El análisis de este corpus demuestra que no existe ninguna correlación cronológica entre la actitud adoptada y la fecha de la columna, lo que deja al lector con la impresión de una profunda ambivalencia en la perspectiva de Cansinos. Además, se nota que intenta reivindicar su propia actuación dentro del movimiento al insistir en los logros posteriores del «ultraísmo argentino».
Lorca en Cortázar: estudio de una influencia inexplorada
Authors: Herrera Cepero Daniel
Published: February 2024

La obra de Federico García Lorca ejerció una influencia en Julio Cortázar que se prolongó a lo largo de toda su vida. Así lo evidencian numerosas fuentes entre las que se encuentran el epistolario del argentino, algunas entrevistas, escritos autobiográficos, alusiones y citas al poeta español en numerosas obras, una serie de romances de evidente filiación lorquiana, una obra de teatro dedicada al granadino, un texto de homenaje, además de la referencia a un «estudio crítico», hoy en paradero desconocido, sobre el autor español. Es sorprendente, dada la indudable conexión entre dos cumbres indiscutibles de las letras en español, que la crítica no se haya detenido en absoluto en el examen de la misma. El objeto de este trabajo es agotar la exploración de la pieza formativa que constituye para Cortázar la influencia del autor español al que llega a referirse como «maestro» y como «cúspide», así como evaluar su alcance estético y los modos en los que cristaliza en la obra del argentino.
Deep Transfer Learning Based on LSTM Model for Reservoir Flood Forecasting
Authors: Zhu Qiliang , Wang Changsheng , Jin Wenchao , Ren Jianxun , Yu Xueting
Published: February 2024

In recent years, deep learning has been widely used as an efficient prediction algorithm. However, this algorithm has strict requirements on the size of training samples. If there are not enough samples to train the network, it is difficult to achieve the desired effect. In view of the lack of training samples, this article proposes a deep learning prediction model integrating migration learning and applies it to flood forecasting. The model uses random forest algorithm to extract the flood characteristics, and then uses the transfer learning strategy to fine-tune the parameters of the model based on the model trained with similar reservoir data; and is used for the target reservoir flood prediction. Based on the calculation results, an autoregressive algorithm is used to intelligently correct the error of the prediction results. A series of experimental results show that our proposed method is significantly superior to other classical methods in prediction accuracy.
Design and Practice of Japanese Interactive Teaching Systems in Colleges and Universities Under the Background of Big Data
Authors: Xiao Hong
Published: February 2024

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and effective, this paper refers to a large number of literature materials. First, the purpose, content, and methods of this research are clarified; secondly, the relevant literature is sorted out and summarized. The SPOC blended teaching design was carried out, and teaching experiments were carried out accordingly. Finally, the data collected during the experiment were compared and analyzed, and the research results were verified with objective data. Research has shown that the use of a Japanese language teaching system enhances students' learning experience, promotes effective use of time, and improves overall learning outcomes.
Construction and Implementation of Application-Oriented Undergraduate Teaching and Teaching Evaluation System Based on Multiple Information Fusion
Authors: Zhang Taolin , Jia Shuwen
Published: February 2024

At present, many schools implement teaching quality evaluation systems with student performance and practical activities as the core data of evaluation. Based on the introduction of the training objectives and discipline nature of the information management and information system specialty, this paper analyzes the construction principles of the multi-disciplinary curriculum system of the specialty and puts forward relevant countermeasures for the construction of the multi-disciplinary education system. This paper introduces the definition of practical teaching evaluation system and teaching evaluation algorithm. Among them, naive Bayesian algorithm can improve the sample accuracy by 95%, so it is necessary to build an application-oriented undergraduate practice teaching evaluation system.
Visual-and-Language Multimodal Fusion for Sweeping Robot Navigation Based on CNN and GRU
Authors: Zhang Yiping , Wilker Kolja
Published: February 2024

Effectively fusing information between the visual and language modalities remains a significant challenge. To achieve deep integration of natural language and visual information, this research introduces a multimodal fusion neural network model, which combines visual information (RGB images and depth maps) with language information (natural language navigation instructions). Firstly, the authors used faster R-CNN and ResNet50 to extract image features and attention mechanism to further extract effective information. Secondly, GRU model is used to extract language features. Finally, another GRU model is used to fuse the visual- language features, and then the history information is retained to give the next action instruction to the robot. Experimental results demonstrate that the proposed method effectively addresses the localization and decision-making challenges for robotic vacuum cleaners.
Numerical Analysis Implementing Composite Materials in a Speed Flex Football Helmet Simulating Frontal Impact Conditions
Authors: Trejo-Enriquez A. , Urriolagoitia-Sosa Guillermo , Romero-Ángeles Beatriz , Maya-Anaya Daniel , Sánchez-Cervantes Arturo , Urriolagoitia-Luna Alejandro , Urriolagoitia-Calderón Guillermo Manuel
Published: February 2024

The National Football League (NFL) is the most successful professional league in the United States. It is also a popular sport around the world. However, for the NFL the strongest problem it has faced is the high rate of concussions, because between seasons and during practices frontal collisions in the head are very recurrent, this concern has led to improve and modify issues in the design of helmets to protect the integrity of the player, Developed by the companies responsible for the manufacture of protective equipment, although in recent decades technological evolution has been an auxiliary tool for the improvement of equipment in this sport discipline there is still a gap to guarantee the total safety of the player. According to the literature, the changes that the helmet structure has undergone are observed and have the perspective, but with regard to the materials that integrate the same materials are still preserved. Therefore, for this research work, the interest arises in developing a numerical analysis that considers new materials, since from 1939 to 2018 the shell material has not been innovated. For this reason, the Speed Flex football helmet that the company Riddell brought to market in 2018 is designed, respecting the helmet structure, where the comparison of the material that is currently used against a composite material, such as carbon fiber, is made, to visualize the results for displacements, Stresses, and total strain during a frontal impact.
Clinicopathological features of oral squamous cell carcinoma
Authors: Adikari L. A. T. I. , Joseph M. , Bandaranayake V. , Asanthi N. J.
Published: February 2024

NA
Distribution of atypical histological features among different subtypes of WHO grade 1 meningiomas: a single-centre descriptive study
Authors: De Silva L.  J. , De Silva L. S. D. , Jayawickrama M. M. A. , De Silva M. V. C.
Published: February 2024

NA
Correlation of prostate specific antigen values with tumour burden in prostate cancer biopsies
Authors: Jayathilaka P. G. A. N. , Munasinghe M. A. D. N. , Fernandopulle S. M. , De S. Hewavisenthi S. J.
Published: February 2024

NA
Demographic Segmentation in the Travel Market: A CHAID Analysis of Traveler Profiles and Trip Attributes Among Indian Prospective Visitors
Authors: Dassanayake D. M. C.
Published: February 2024

Demographics are central to market segmentation, as underscored in consumer behavior research. This study examines the associations between demographic factors and traveler preferences of trip attributes using 919 online surveys of prospective Indian travelers sampled conveniently but purposefully using specific filtering questions at the beginning of the questionnaire. Utilizing CHAID analysis, the study evaluates the correspondence between age, gender, marital status, income, and educational attainment with trip attributes such as outbound vs. domestic travel, accommodation type, transportation mode, travel companions, and trip duration. Distinctly, choices of travel companions correlate with education, age, marital status, and gender. Trip type, duration, accommodation, and transport have ties to specific combinations of income, education, and age. The study emphasizes the potential for leveraging these insights for precise demographic- based market segmentation in the travel sector.
Current devices, outcomes, and pain management considerations in penile implant surgery: an updated review of the literature
Authors: Ancha Nirupama , Eldin Maya , Woodle Tarah , Gereta Sofia , Hariprasad Krishna , Butler Imani , Charles Osterberg E
Published: February 2024

Penile prosthesis surgery is a definitive treatment for erectile dysfunction (ED). The two categories of penile prosthesis are endorsed by professional guidelines, inflatable penile prosthesis (IPP) and malleable penile prosthesis (MPP). Each modality of penile prosthesis offers distinct advantages and incorporates specific design features, allowing for personalized device selection that aligns with individual needs and preferences. While the overall complication rate of penile implant surgery remains low, surgeons should maintain a high index of suspicion for complications in the perioperative time period. Multimodal analgesic regimens including nerve blocks and narcotic-free pathways should be administered to manage perioperative pain. Finally, the high patient satisfaction after penile prosthesis surgery underscores the success of this ED treatment option.
Ring Finger 43 Hot-spot Frameshift Mutation G659V in Colorectal Cancer Patients: Report from a Tertiary Cancer Care Hospital in North India
Authors: Vasudevan Smreti , Mehta Anurag , Karki Diksha , Kumar Dushyant
Published: February 2024

Background:

The Ring Finger 43 (RNF43) is a tumor suppressor gene that negatively regulates the Wnt/β-catenin signaling. The p.G659fs is a recurrent RNF43 C-terminal truncating variant frequent in colorectal cancer (CRC) patients. We aimed to identify this hotspot variant in CRC patients and assessed the relationship between the mutation, clinical characteristics, and tumor β-catenin localization.

Materials and Methods:

Formalin-fixed, paraffin-embedded tissue samples of upfront, surgically resected, sporadic colorectal adenocarcinoma cases were selected. The p.G659fs mutation was determined by capillary sequencing with sequence-specific primers. Tissue microarray and immunohistochemistry were employed to analyze nuclear β-catenin expression and the expression of mismatch repair (MMR) proteins, respectively. In addition, clinical details were retrieved from the hospital medical records and data were analyzed.

Results:

The RNF43 p.G659fs mutation was observed in 8% of CRC patients. In total, 25% of tumors showed a loss of immunostaining for one or more MMR proteins and 14.6% of tumors showed positive nuclear β-catenin staining. The p.G659fs variant was significantly enriched in MMR-deficient tumors (P = 0.04). Importantly, no correlation was observed between the variant and nuclear β-catenin localization (P = 0.48), indicating a Wnt-independent role of this variant in CRC tumors.

Conclusions:

To the best of our knowledge, this is the first study from North India to show the involvement of RNF43 p.G659fs variant in CRC patients. The mutation correlated with MMR protein deficiency and seems to be conferring tumorigenicity independent of the Wnt pathway.
Analysis of immediate effect of nadishodhana pranayama in the ratio of 1:3:2 on autonomic and respiratory variables in healthy individuals
Authors: Saisupriya K. , Chandrappa Shashikiran H. , Shetty Shivaprasad K. , Shetty Prashanth , Honnegowda Thittamaranahalli Muguregowda , Hiremath Leena
Published: February 2024

Background:

Nadishodhana pranayama (NS) has been used extensively for relaxation as well as therapeutics by many practitioners; the physiological effects of NS in this specific ratio have not been studied yet. Hence, the present study aims to evaluate the immediate effect of NS pranayama in the ratio of 1:3:2 with a time line of 6:18:12 s and its role in clinical application.

Materials and Methods:

Sixty healthy volunteers were recruited for the study. Individuals were randomly allocated into two groups, NS pranayama with antarkumbhaka (Group 1) and breathe awareness (Group 2). For case group, intervention was given for 12 rounds and for the control group, breath awareness was given for 12 rounds and assessed immediately after the practice.

Results:

In the study group, a significant decrease in mean heart rate (HR) (p < 0.0001) and a significant increase in mean respiratory rate (RR), NN50 (p < 0.0001), RMSSD, and pNN50 (p < 0.0001) after the intervention compared to their prevalues and with that of the control group were noted. Frequency domain analysis of HR variability showed a significant decrease in the pre- and post-values of low-frequency (LF) power (p < 0.0001), very LF, and LF/high-frequency (HF) power (p < 0.0075) and a significant increase in the pre- and post-values of HF power (p < 0.001) after the intervention in the study group.

Conclusions:

The result concludes that the immediate effect of NS pranayama in the ratio of 1:3:2 brings parasympathetic activity in the study group by decreasing RR and HR. Hence, the NS pranayama with kumbhaka is a better method to increase parasympathetic activity.
Anxiety and depression related to yog nidra among professional students
Authors: Joshi Rupali
Published: February 2024

Background:

Anxiety is one's response to stress. Its symptoms can be psychological, physical, or environmental challenges. Depression is a common mental disorder that presents with depressed mood, loss of interest or pleasure, feeling of guilt or low self-worth, disturbed sleep or appetite, low energy, and poor concentration. Yog nidra is probably the best known technique to induce complete physical and emotional relaxation.

Aim:

The aim of this study was to explore the effectiveness of yog nidra for reducing anxiety and depression among first-year professional students.

Materials and Methods:

The level of anxiety was measured by using State, Trait, and Free-Floating Anxiety Scale developed by Tripathi and Rastogi (1986). The Hindi version of Beck Depression Inventory by Arora and Prashant (1988) was used to assess the depression level of participants. The study was conducted in three phases. In Phase-1 (preintervention), data were obtained from 201 students. In the Phase-2 (intervention phase), the participants were selected on the basis of high scores on the measures of anxiety and depression and divided into intervention (28 students) and non-intervention groups (30 students). The intervention group was given yog nidra training regularly for 5 weeks. Posttest was conducted after 5 weeks of the intervention.

Results:

The results showed a reduction in mean scores on the measures of anxiety and depression within the intervention group but not in the nonintervention group, which indicated the effectiveness of practicing yog nidra for reducing anxiety and depression and its positive effects among professional students.

Conclusion:

A dramatic effect of practicing yog nidra was observed among students for reducing anxiety and depression.
Yoga and naturopathy -based lifestyle during quarantine for the prevention of COVID-19
Authors: Mooventhan A. , Kahlilsubramanian K. , Manavalan N.
Published: February 2024

Introduction:

Coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (CoV) known as severe acute respiratory syndrome CoV-2. It is transmitted through infected patients' droplet and contact. Individuals with chronic cardiorespiratory diseases are mostly affected. Yoga and naturopathy are commonly employed in the prevention and management of cardiorespiratory diseases. This is the first-ever study conducted to find the impact of yoga and naturopathy-based lifestyle (YNBLS) on frequency of conversion of positive cases during COVID-19 quarantine period.

Material and Methods:

In this pilot cohort study, 43 participants those who had exposure with COVID-19-positive case (self-quarantined individuals) and adopted YNBLS after exposure were observed till the COVID-19 swab test results had come.

Results:

Of 43-participants' swab-test for COVID-19, none of the participant test has turned into positive for COVID-19.

Conclusion:

Results suggest that adopting YNBLS during the quarantine period might be considered as an effective strategy for the prevention of COVID-19.
Kapalabhati
Authors: Vaid Mansi , Verma Sanjay
Published: February 2024

The purpose of this article is to aware people about the yogic technique of Kapalabhati and its benefits. It clearly explains how Kapalabhati helps in prevention and cure of various health issues in different physiological systems in the human body. This review focuses on the role of kapalabhati in maintaining the normal functioning of organs and its contribution to curing different ailments in the human body. All the information that is given in this article is consulted from different websites, journal articles, and books and is written in a way suitable for reading even to the common public. The review discloses that Kapalabhati is that high-frequency breathing exercise, which promotes overall well-being and cures diseases. This study mainly focuses on cure of number of illnesses caused due to unhealthy living habits, impurities and different types of pollutants present in the environment, and inhalation of harmful nanoparticles and other factors responsible for creating severe to major problems in the human body. Kapalabhati works in a curative and revolutionary way to cope with the health issues and improves the overall function of the body.
Effective preprocessing and feature analysis on Twitter data for Fake news detection using RWS algorithm
Authors: Santhoshkumar M , Divya V
Published: February 2024

The tremendous headway of web empowered gadgets develops the clients dependably strong in virtual redirection affiliations. Individuals from social affairs getting moment notices with respect to news, amusement, training, business, and different themes.  The development of artificial intelligence-based classification models plays an optimum role in making deeper analysis of text data. The massive growth of text-based communication impacts the social decisions also. People rely on news and updates coming over in social media and networking groups. Micro blogs such as tweeter, facebooks manipulate the news as faster as possible.The quality of classification of fake news and real news depends on the processing steps. The proposed articles focused on deriving a significant method for pre-processing the dataset and feature extraction of the unique data. Dataset is considered as the input data for analyzing the presence of fake news. The extraction of unique features from the data is implemented using Bags of relevant tags (BORT) extraction and Bags of relevant meta words (BORMW).
Photovoltaic power generation prediction and optimization configuration model based on GPR and improved PSO algorithm
Authors: Zhang Zhennan , Duan Zhenliang , Zhang Lingwei
Published: February 2024

As the growing demand for energy as well as the strengthening of environmental awareness, photovoltaic power generation, as a clean and renewable energy source, has gradually attracted people's attention and attention. To facilitate the dispatching and planning of power system, this study uses historical data and meteorological data to build a photovoltaic power generation prediction and configuration optimization model on the ground of Gaussian process regression and improved particle swarm optimization algorithm. The simulation results show that the regression prediction curve of the Gaussian process regression prediction model is the closest to the real curve, and the prediction curve is stable and not easily disturbed by noise data. The Root-mean-square deviation and the average absolute proportional error of the model are small, and the disparity in the predicted value and the true value of the model is small; The integration of multi factor data has improved the accuracy of prediction data, and the regression prediction effect is good. The improved Particle swarm optimization algorithm could continuously enhance in the search for the optimal solution, and the Rate of convergence is fast. The Pareto solution can provide different solutions suitable for photovoltaic power generation optimization. Reasonable optimization configuration can effectively reduce active power line loss and voltage deviation, with the maximum reduction values reaching 132kW and 0.028, respectively. The research and design of predictive models and optimized configuration models can promote the formation of smart grids.