bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuropharmacological Effects of Terpenoids on Preclinical Animal Models of Psychiatric Disorders: A Review
Authors: Mony Tamanna Jahan , Elahi Fazle , Choi Ji Woong , Park Se Jin
Published: September 2022

Terpenoids are widely distributed in nature, especially in the plant kingdom, and exhibit diverse pharmacological activities. In recent years, screening has revealed a wide variety of new terpenoids that are active against different psychiatric disorders. This review synthesized the current published preclinical studies of terpenoid use in psychiatric disorders. This review was extensively investigated to provide empirical evidence regarding the neuropharmacological effects of the vast group of terpenoids in translational models of psychiatric disorders, their relevant mechanisms of action, and treatment regimens with evidence of the safety and psychotropic efficacy. Therefore, we utilized nine (9) electronic databases and performed manual searches of each. The relevant data were retrieved from the articles published until present. We used the search terms “terpenoids” or “terpenes” and “psychiatric disorders” (“psychiatric disorders” OR “psychiatric diseases” OR “neuropsychiatric disorders” OR “psychosis” OR “psychiatric symptoms”). The efficacy of terpenoids or biosynthetic compounds in the terpenoid group was demonstrated in preclinical animal studies. Ginsenosides, bacosides, oleanolic acid, asiatic acid, boswellic acid, mono- and diterpenes, and different forms of saponins and triterpenoids were found to be important bioactive compounds in several preclinical studies of psychosis. Taken together, the findings of the present review indicate that natural terpenoids and their derivatives could achieve remarkable success as an alternative therapeutic option for alleviating the core or associated behavioral features of psychiatric disorders.
A Maintenance Maturity Model for Assessing Information Management Practices for Small and Medium Enterprises (M3AIN4SME)
Authors: Tortora Alessia Maria Rosaria , Di Pasquale Valentina , Iannone Raffaele
Published: September 2022

Maintenance management is assuming an increasingly important role and garnering increased attention in Small and Medium Enterprises (SMEs). However, the difficulty of collecting data and processing information is evident in such contexts. In the current literature, few maintenance maturity models focus on the maintenance information management practices field. Moreover, though the existing models allow for assessing the maturity level, they do not indicate or assist in identifying and defining actions to reach the highest level. Furthermore, these models are not suitable for any type of organisation, as the assessment areas defined are quite generic (high level). For this reason, this paper proposes an innovative model for assessing the maturity level of maintenance management information practices in Small and Medium Enterprises (SMEs). The model provides the organisation with the strengths and weaknesses of their maintenance information management practices. The proposed model allows a clear measure of the maturity of the maintenance information management practices in smaller industrial contexts and provides a customised improvement programme. The model proposed supports small and medium companies to improve the effectiveness and efficiency of their maintenance management information infrastructure. The maturity model developed, in addition to being an assessment tool, provides and supports knowledge on the behaviours and practices for achieving world-class results.
Assessment of Antioxidant and Scavenging Activities of Various Yogurts Using Different Sample Preparation Procedures
Authors: Papadaki Eugenia , Roussis Ioannis G.
Published: September 2022

Antioxidant activities of various yogurts were assessed using different sample preparation procedures. Specifically, full-fat cow, goat and ewe yogurts as well as cow yogurts with different fat content (4%, 2% and 0%) were employed. Antioxidant activities were determined in two different water-soluble yogurt extracts and also in a total yogurt preparation using the “Clarifying Reagent” for dairy products. Full-fat ewe yogurt preparations exhibited higher antioxidant activities in FRAP and Folin assays as well as higher scavenging capacities against DPPH, hydroxyl and superoxide anion radicals than full-fat cow and goat yogurt preparations. Bradford, Lowry and Ellman’s assays confirmed that the strong antioxidant potential of the ewe yogurt was associated with its high protein content. In addition, antioxidant activities appeared to be related with the fat content of cow yogurt. Particularly, in DPPH, FRAP and Folin assays, and also in assays for scavenging of DPPH, hydroxyl and superoxide anion radicals, it was demonstrated that the fat removal led to the increase of the antioxidant/scavenging activities of the cow yogurts due to the increase of their protein/peptide water-soluble content. Moreover, for the first time, results show that the “Clarifying Reagent” for dairy products can be used for the determination of antioxidant and radical scavenging activities of whole yogurt using the FRAP assay as well as the hydroxyl and superoxide anion radicals scavenging assays.
Sensitivity Analysis of Fracture Geometry Parameters on the Mechanical Behavior of Rock Mass with an Embedded Three-Dimensional Fracture Network
Authors: Wu Na , Liang Zhengzhao , Tao Yan , Ai Ting , Li Guijie
Published: September 2022

The existence of fractures has a significant influence on the mechanical properties of a rock mass. The sensitivity of the rock mass’s mechanical properties to the fracture’s geometric parameters is conducive to improving the measurement accuracy of fractured rock mass engineering. Firstly, the fracture geometric parameters in the dam site area of Lianghekou Hydropower Station were counted using the ShapeMetriX3D system. Then, the effect of the fracture’s geometric parameters on the deformation characteristics, failure mode, and mechanical parameters of the rock mass were investigated based on the RFPA3D under the uniaxial compression test. The results showed that the stress–strain curves of the fractured rock mass mainly exhibited elastic-brittle characteristics. The failure pattern of the fractured rock mass was mainly defined by a compressive-shear composite. Additionally, the influence of the fracture’s geometric parameters on the uniaxial compressive strength (UCS) was greater than that of elastic modulus. The sensitivity of the UCS to fracture trace length was more significant.
Re-Engineered Word Embeddings for Improved Document-Level Sentiment Analysis
Authors: Yang Su , Deravi Farzin
Published: September 2022

In this paper, a novel re-engineering mechanism for the generation of word embeddings is proposed for document-level sentiment analysis. Current approaches to sentiment analysis often integrate feature engineering with classification, without optimizing the feature vectors explicitly. Engineering feature vectors to match the data between the training set and query sample as proposed in this paper could be a promising way for boosting the classification performance in machine learning applications. The proposed mechanism is designed to re-engineer the feature components from a set of embedding vectors for greatly increased between-class separation, hence better leveraging the informative content of the documents. The proposed mechanism was evaluated using four public benchmarking datasets for both two-way and five-way semantic classifications. The resulting embeddings have demonstrated substantially improved performance for a range of sentiment analysis tasks. Tests using all the four datasets achieved by far the best classification results compared with the state-of-the-art.
Dental Health, Caries Perception and Sense of Discrimination among Migrants and Refugees in Europe: Results from the Mig-HealthCare Project
Authors: Karnaki Pania , Katsas Konstantinos , Diamantis Dimitrios V. , Riza Elena , Rosen Maya Simona , Antoniadou Maria , Gil-Salmerón Alejandro , Grabovac Igor , Linou Athena
Published: September 2022

Dental and oral health are considered among the main health issues for migrants and refugees, as access to dental health care services is often expensive and difficult. The study investigates dental and oral health determinants among migrants and refugees in 10 European countries (Austria, Bulgaria, Cyprus, France, Germany, Greece, Italy, Malta, Spain, and Sweden), examining how mental health, legal status, discrimination issues and dental services’ use frequency affect dental health. Methods: A cross sectional study using a purpose-made questionnaire was carried out to assess health status and access, with a dedicated section to measure self-perceived dental health, prevalence of caries, last visit to dentist and anticipated access to dental health services. Multivariable logistic regression models were performed to investigate the impact of quality of life, discrimination, immigration status, and other demographic factors on dental health. Results: About half of the sample suffered from poor dental condition and 22% had never visited a dentist. Migrants with higher educational levels had higher odds of having good dental health (OR = 1.08; 95%CI (1.03, 1.12)) and brushing their teeth daily (OR = 1.1; 95%CI (1.04, 1.17)). Higher general and mental health scores were indicative of better dental condition (general health: OR = 1.02; 95%CI (1.01, 1.03); mental health: OR = 1.01; 95%CI (1.004, 1.02)) and higher probability of daily teeth brushing (general health: OR = 1.02; 95%CI (1.01, 1.03); mental health: OR = 1.02; 95%CI (1.01, 1.03)). The possession of any kind of legal immigration permission and not having any children showed similar results. Age and discrimination were correlated with decreased likelihood for good dental conditions. Gender was correlated with daily teeth brushing, as female migrants had higher odds of brushing their teeth daily. Conclusions: Many migrants report poor dental health. Nonetheless, migrants with higher education levels, legal immigration status, better general and mental health, no children, lower sense of discrimination, younger age, and regular dental visits were positively correlated to good dental health (perceived as no dental caries).
Characterization of Sidr (Ziziphus spp.) Honey from Different Geographical Origins
Authors: Hegazi Ahmed G. , Al Guthami Fayez M. , Ramadan Mohamed F. A. , Al Gethami Ahmed F. M. , Craig A. Morrie , Serrano Salud
Published: September 2022

The current investigation was conducted to assess the melissopalynological, physicochemical, and biochemical properties, antimicrobial and antioxidant activities as well as total phenolic and total flavonoid contents of 794 Sidr honey samples collected from the Saudi market that had been imported from 12 different countries. Testing Sidr honey from different countries showed different levels of growth suppression observed against five drug resistant bacterial strains. The pathogenic strains were Staphylococcus aureus, Streptococcus mutans, Klebsiella pneumoniae, Escherichia coli and Pseudomonas aeruginosa. The antimicrobial activity showed growth suppression levels which varied according to the origin of the honey. The comparative study of Sidr honeys revealed a strong correlation between total polyphenol and flavonoid contents and significant radical scavenging activities in particular Egyptian and Saudi Arabian honeys. The melissopalynological and physicochemical properties of different Sidr honeys complied with the recommendations of the WHO Codex Alimentarius, the European Union standards for honey quality, and the Gulf Technical Regulation on honey (GSO 147:2008-Standards Store-GCC Standardization Organization). It was concluded that Sidr honey from different geographical areas has the capacity to suppress the growth of pathogenic bacteria and perform significant radical scavenging activities.
Nonlinear Thermo-Structural Analysis of Lightweight Concrete and Steel Decking Composite Slabs under Fire Conditions: Numerical and Experimental Comparison
Authors: Martínez-Martínez Juan Enrique , Álvarez-Rabanal Felipe Pedro , Alonso-Martínez Mar , del Coz-Díaz Juan José
Published: September 2022

Composite slabs with steel decking profiles are widely used in building construction. However, the literature on the fire resistance of lightweight concrete (LWC) composite slabs with steel decking is limited. In this work, the thermo-structural performance of LWC composite slabs with trapezoidal steel decking was studied under fire conditions. A total of 12 experimental fire tests were carried out using specimens of 160 mm thickness, 1120 mm width and 2030 mm length, in which nine composite slabs were made of LWC and the remaining three slabs were made of normal concrete (NC) to serve as a benchmark for comparison. All the samples were tested in a furnace following EN 13381-5, applying the standardized time–temperature curve and constant load. During the experimental tests, phenomena such as the vaporization of the free water inside LWC, debonding between steel decking and concrete and changes in material properties affected the thermo-structural performance of composite slabs. The test results show that the load-bearing capacity of lighter slabs does not assure the minimum structural behavior of R30. However, the lighter the concrete is, the lower the thermal transmittance, improving the slabs’ thermal performance under fire conditions. Advanced nonlinear numerical models were developed to predict the thermal and structural performance of the studied LWC composite slabs in terms of temperature and time-displacement. The influences of key factors such as vaporization, thermal strains and debonding were included using material properties and a thermal contact conductance interlayer. Finally, the nonlinear models and the experimental results were compared. The difference between the experimental and numerical values was less than 15%, showing that the numerical results were in good agreement with the experimental results. The results of this study also compared the performance of LWC composite slabs with the NC composite slabs, giving rise to interesting conclusions from a practical point of view.
BoYaTCN: Research on Music Generation of Traditional Chinese Pentatonic Scale Based on Bidirectional Octave Your Attention Temporal Convolutional Network
Authors: Jiang Fanzhi , Zhang Liumei , Wang Kexin , Deng Xi , Yang Wanyan
Published: September 2022

Recent studies demonstrate that algorithmic music attracted global attention not only because of its amusement but also its considerable potential in the industry. Thus, the yield increased academic numbers spinning around on topics of algorithm music generation. The balance between mathematical logic and aesthetic value is important in music generation. To maintain this balance, we propose a research method based on a three-dimensional temporal convolutional attention neural network. This method uses a self-collected traditional Chinese pentatonic symbolic music dataset. It combines clustering algorithms and deep learning-related algorithms to construct a three-dimensional sequential convolutional generation model 3D-SCN, a three-dimensional temporal convolutional attention model BoYaTCN. We trained both of them to generate traditional Chinese pentatonic scale music that considers both overall temporal creativity and local musical semantics. Then, we conducted quantitative and qualitative evaluations of the generated music. The experiment demonstrates that BoYaTCN achieves the best results, with a prediction accuracy of 99.12%, followed by 3D-SCN with a prediction accuracy of 99.04%. We have proven that the proposed model can generate folk music with a beautiful melody, harmonious coherence, and distinctive traditional Chinese pentatonic features, and it also conforms to certain musical grammatical characteristics.
Network Slicing Resource Allocation Based on LSTM-D3QN with Dual Connectivity in Heterogeneous Cellular Networks
Authors: Chen Geng , Mu Xinzheng , Shen Fei , Zeng Qingtian
Published: September 2022

With the explosive growth of network traffic and the diversification of service demands, network slicing (NS) and dual connectivity (DC) are considered as promising technologies in wireless networks. In this paper, we propose a novel algorithm that solves the resource allocation problem of NS in heterogeneous networks with the assistance of DC, while satisfying the characteristic requirements of eMBB and URLLC services. Firstly, we model the scenario and formulate the optimization problem, which is proved as an NP-Hard problem. Secondly, due to the nonconvex and combinatorial nature, the dueling double deep Q-network with long short-term memory (LSTM-D3QN) is proposed to solve this problem, aiming to improve the overall network utility, while ensuring the quality of experience (QoE). Then, we analyze the complexity of the algorithm. Finally, the simulation results show that the proposed algorithm can maximize the total utility of the system, while guaranteeing the user QoE. Compared with LSTM-A2C and DQN, the proposed algorithm improves the long-term network utility by 2.6% and 7.2%, respectively. In addition, compared with the algorithm without DC under the conditions of no priority, eMBB priority and URLLC priority, the proposed algorithm improves the network utility by 4.2%, 2.1% and 4.1%, respectively.
Comparative Study for Patch-Level and Pixel-Level Segmentation of Deep Learning Methods on Transparent Images of Environmental Microorganisms: From Convolutional Neural Networks to Visual Transformers
Authors: Yang Hechen , Zhao Xin , Jiang Tao , Zhang Jinghua , Zhao Peng , Chen Ao , Grzegorzek Marcin , Qi Shouliang , Teng Yueyang , Li Chen
Published: September 2022

Currently, the field of transparent image analysis has gradually become a hot topic. However, traditional analysis methods are accompanied by large amounts of carbon emissions, and consumes significant manpower and material resources. The continuous development of computer vision enables the use of computers to analyze images. However, the low contrast between the foreground and background of transparent images makes their segmentation difficult for computers. To address this problem, we first analyzed them with pixel patches, and then classified the patches as foreground and background. Finally, the segmentation of the transparent images was completed through the reconstruction of pixel patches. To understand the performance of different deep learning networks in transparent image segmentation, we conducted a series of comparative experiments using patch-level and pixel-level methods. In two sets of experiments, we compared the segmentation performance of four convolutional neural network (CNN) models and a visual transformer (ViT) model on the transparent environmental microorganism dataset fifth version. The results demonstrated that U-Net++ had the highest accuracy rate of 95.32% in the pixel-level segmentation experiment followed by ViT with an accuracy rate of 95.31%. However, ResNet50 had the highest accuracy rate of 90.00% and ViT had the lowest accuracy of 89.25% in the patch-level segmentation experiments. Hence, we concluded that ViT performed the lowest in patch-level segmentation experiments, but outperformed most CNNs in pixel-level segmentation. Further, we combined patch-level and pixel-level segmentation results to reduce the loss of segmentation details in the EM images. This conclusion was also verified by the environmental microorganism dataset sixth version dataset (EMDS-6).
Thermal Buckling and Vibration Analysis of SMA Hybrid Composite Sandwich Beams
Authors: Nejati Mohammad , Jafari Seyed Sajad , Dimitri Rossana , Tornabene Francesco
Published: September 2022

This work studies the buckling and free vibration behavior of Shape Memory Alloy Hybrid Composite (SMAHC) sandwich beams under a thermal environment. The sandwich beams consist of layers reinforced with SMAs and a FGM core, and they are simply supported at both ends. The higher order theory is combined with the Minimum Potential Energy principle or Hamilton principle to derive the governing equations of the thermal buckling and thermal vibration problems, respectively. The material properties of the beam are assumed as temperature-independent (TID) or temperature-dependent (TD). In the last case, two different types of thermal distribution are considered, namely a uniform and a linear distribution. The results based on the proposed formulation are verified against the reference literature, with a very good matching. A parametric study checks for the influence of different effective parameters such as thickness-to-length ratios, volume fraction powers, initial strain, volume fraction of SMA wires, and temperature distribution on the overall mechanical response of the selected structural member, with useful insights from a design standpoint.
Fused Deposition Modeling with Induced Vibrations: A Study on the Mechanical Characteristics of Printed Parts
Authors: Dei Rossi Joseph , Keles Ozgur , Viswanathan Vimal
Published: September 2022

The recent development of RepRap style 3D printers has made additive manufacturing technology available to the public at a low cost. While these 3D printers are being used for a variety of purposes, one of the main applications is prototyping in design projects. The quality of the 3D-printed parts has been a concern in such cases. Many variables within these printers’ operation can be varied to obtain optimum print quality. This study explores a setup that uses externally induced mechanical vibrations to the nozzle tip as a potential method to improve the quality of 3D-printed parts. Induced vibration is expected to decrease the porosity of printed parts and enhance the cohesion between print beads, ultimately improving their mechanical properties. The objective is to understand the prints’ positional accuracy, porosity, and mechanical properties with the added vibration and then to determine the optimum vibration level to achieve the best quality prints. While previous studies have explored the role of induced vibration on the mechanical properties of printed parts, the novelty of this work lies in the determination of the positional accuracy of those parts and the determination of optimum vibration levels to achieve desired properties. For positional accuracy, the extruder filament is replaced with a pointed-tip pen that can mark the exact location where the printer delivers the material. A comparison between the locations marked by the pen with and without vibrations shows that the errors induced by the added vibration are not significantly different from those caused by the uncertainties of the printer itself. Based on the tensile tests of the printed specimens, it is concluded that the parts printed with induced vibrations have improved mechanical properties. The printed parts’ porosity is reduced significantly due to the induced vibrations. Further, this study also explores the optimum motor speeds to achieve a uniform distribution of material. It determines medium motor speeds that provide a maximum vibration amplitude, which is more desirable for a consistent infill.
An Interface-Corrected Diffuse Interface Model for Incompressible Multiphase Flows with Large Density Ratios
Authors: Guo Yuhao , Wang Yan , Hao Qiqi , Wang Tongguang
Published: September 2022

An interface-corrected diffuse interface method is presented in this work for the simulation of incompressible multiphase flows with large density ratios. In this method, an interface correction term together with a mass correction term is introduced into the diffuse-interface Cahn–Hilliard model to maintain both mass conservation and interface shapes between binary fluids simultaneously. The interface correction term is obtained by connecting the signed distance functions in the Hamilton–Jacobian equation with the order parameter of the Cahn–Hilliard model. In addition, an improved multiphase lattice Boltzmann flux solver is introduced, in which the fluxes are obtained by considering the contributions of the particle distribution functions before and after the streaming process through a local switch function. The proposed method is validated by simulating multiphase flows, such as the Laplace law, the evolution of a square bubble, the merging of two bubbles, Rayleigh–Taylor instability, and a droplet impacting on a film with a density ratio of 1000. Numerical results show that the presented method can not only reduce the interface diffusion but also has good control over the interface thickness and mass conservation. The improved numerical method has great potential for use in practical applications involving multiphase flows.
Chosen Plaintext Combined Attack against SM4 Algorithm
Authors: Rao Jintao , Cui Zhe
Published: September 2022

The SM4 algorithm is widely used to ensure the security of data transmission. The traditional chosen plaintext power attacks against SM4 usually need to analyze four rounds power traces in turn to recover the secret key. In this paper, we propose a new combined chosen plaintext power analysis, which combines the chosen plaintext power attack and the differential characteristics of the substitution box (S-box) in SM4. In our attack, only the second and fourth round S-box outputs of SM4 algorithm are used as attack points, and some sensitive fixed intermediate values are obtained by power analysis when inputting specific plaintext. Then the differential analysis of these sensitive intermediate values is carried out to calculate the difference between the input and output of the S-box, and the key can be recovered from the differential characteristics of S-box. Compared with the traditional chosen plaintext power analysis, which requires four rounds of analysis, our analysis reduces the number of attack rounds into two rounds, and adopts the nonlinear S-box with obvious leakage information as the attack intermediate value, which effectively improves the feasibility of attack. Finally, a practical attack experiment is carried out on a Field Programmable Gate Array (FPGA) based implementation of SM4 algorithm, and the results show that our method is feasible and effective for real experiments.
Fast Format-Aware Fuzzing for Structured Input Applications
Authors: Chen Zehan , Lu Yuliang , Zhu Kailong , Yu Lu , Zhao Jiazhen
Published: September 2022

Fuzzing is one of the most successful software testing techniques used to discover vulnerabilities in programs. Without seeds that fit the input format, existing runtime dependency recognition strategies are limited by incompleteness and high overhead. In this paper, for structured input applications, we propose a fast format-aware fuzzing approach to recognize dependencies from the specified input to the corresponding comparison instruction. We divided the dependencies into Input-to-State (I2S) and indirect dependencies. Our approach has the following advantages compared to existing works: (1) recognizing I2S dependencies more completely and swiftly using the input based on the de Bruijn sequence and its mapping structure; (2) obtaining indirect dependencies with a light dependency existence analysis on the input fragments. We implemented a fast format-aware fuzzing prototype, FFAFuzz, based on our method and evaluated FFAFuzz in real-world structured input applications. The evaluation results showed that FFAFuzz reduced the average time overhead by 76.49% while identifying more completely compared with Redqueen and by 89.10% compared with WEIZZ. FFAFuzz also achieved higher code coverage by 14.53% on average compared to WEIZZ.
An Intelligent Hybrid Scheme for Customer Churn Prediction Integrating Clustering and Classification Algorithms
Authors: Liu Rencheng , Ali Saqib , Bilal Syed Fakhar , Sakhawat Zareen , Imran Azhar , Almuhaimeed Abdullah , Alzahrani Abdulkareem , Sun Guangmin
Published: September 2022

Nowadays, customer churn has been reflected as one of the main concerns in the processes of the telecom sector, as it affects the revenue directly. Telecom companies are looking to design novel methods to identify the potential customer to churn. Hence, it requires suitable systems to overcome the growing churn challenge. Recently, integrating different clustering and classification models to develop hybrid learners (ensembles) has gained wide acceptance. Ensembles are getting better approval in the domain of big data since they have supposedly achieved excellent predictions as compared to single classifiers. Therefore, in this study, we propose a customer churn prediction (CCP) based on ensemble system fully incorporating clustering and classification learning techniques. The proposed churn prediction model uses an ensemble of clustering and classification algorithms to improve CCP model performance. Initially, few clustering algorithms such as k-means, k-medoids, and Random are employed to test churn prediction datasets. Next, to enhance the results hybridization technique is applied using different ensemble algorithms to evaluate the performance of the proposed system. Above mentioned clustering algorithms integrated with different classifiers including Gradient Boosted Tree (GBT), Decision Tree (DT), Random Forest (RF), Deep Learning (DL), and Naive Bayes (NB) are evaluated on two standard telecom datasets which were acquired from Orange and Cell2Cell. The experimental result reveals that compared to the bagging ensemble technique, the stacking-based hybrid model (k-medoids-GBT-DT-DL) achieve the top accuracies of 96%, and 93.6% on the Orange and Cell2Cell dataset, respectively. The proposed method outperforms conventional state-of-the-art churn prediction algorithms.
Global Distribution of Clouds over Six Years: A Review Using Multiple Sensors and Reanalysis Data
Authors: Shikwambana Lerato
Published: September 2022

A six-year global study of cloud distribution and cloud properties obtained from observations of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), the Atmospheric Infrared Sounder (AIRS), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data is presented in this study. From the CALIPSO observations, the highest clouds for both daytime and night-time were found in the Inter Tropical Convergence Zone (ITCZ) region. The lowest cloud heights were found towards the poles due to the decrease in the tropopause height. Seasonal studies also revealed a high dominance of clouds in the 70 °S–80 °S (Antarctic) region in the June–July–August (JJA) season and a high dominance of Arctic clouds in the December–January–February (DJF) and September–October–November (SON) seasons. The coldest cloud top temperatures (CTT) were mostly observed over land in the ITCZ and the polar regions, while the warmest CTTs were mostly observed in the mid-latitudes and over the oceans. Regions with CTTs greater than 0 °C experienced less precipitation than regions with CTTs less than 0 °C.
Modeling Actual Evapotranspiration with MSI-Sentinel Images and Machine Learning Algorithms
Authors: dos Santos Robson Argolo , Mantovani Everardo Chartuni , Fernandes-Filho Elpídio Inácio , Filgueiras Roberto , Lourenço Rodrigo Dal Sasso , Bufon Vinícius Bof , Neale Christopher M. U.
Published: September 2022

The modernization of computational resources and application of artificial intelligence algorithms have led to advancements in studies regarding the evapotranspiration of crops by remote sensing. Therefore, this research proposed the application of machine learning algorithms to estimate the ETrF (Evapotranspiration Fraction) of sugar can crop using the METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) model with data from the Sentinel-2 satellites constellation. In order to achieve this goal, images from the MSI sensor (MultiSpectral Instrument) from the Sentinel-2 and the OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors from the Landsat-8 were acquired nearly at the same time between the years 2018 and 2020 for sugar cane crops. Images from OLI and TIR sensors were intended to calculate ETrF through METRIC (target variable), while for the MSI sensor images, the explanatory variables were extracted in two approaches, using 10 m (approach 1) and 20 m (approach 2) spatial resolution. The results showed that the algorithms were able to identify patterns in the MSI sensor data to predict the ETrF of the METRIC model. For approach 1, the best predictions were XgbLinear (R2 = 0.80; RMSE = 0.15) and XgbTree (R2 = 0.80; RMSE = 0.15). For approach 2, the algorithm that demonstrated superiority was the XgbLinear (R2 = 0.91; RMSE = 0.10), respectively. Thus, it became evident that machine learning algorithms, when applied to the MSI sensor, were able to estimate the ETrF in a simpler way than the one that involves energy balance with the thermal band used in the METRIC model.
Highly Efficient Removal of CO2 Using Water-Lean KHCO3/Isopropanol Solutions
Authors: Wang Lei , Saeed Mohammad , Luo Jianmin , Lee Anna , Simonet Rowan , Sun Zhao , Walker Nigel , Aro Matthew , Davis Richard , Zahra Mohammad Abu , Alkasrawi Malek , Toan Sam
Published: September 2022

The use of aqueous carbonate as an inorganic absorbent is not only inexpensive but also stable and environmentally friendly. However, the regeneration processes for aqueous carbonate sorbents require high regeneration heat duty; this energy intensity makes their wide utilization unaffordable. In this work, a low-temperature, energy-saving, and environmentally friendly carbon dioxide desorption method has been investigated in potassium bicarbonate-water-alcohol solutions. The addition of alcohol, particularly isopropanol, to the potassium bicarbonate-water solution can significantly increase carbon dioxide desorption capacity. The potassium bicarbonate-water-isopropanol solution used in this study (36 wt % isopropanol) resulted in 15.2 mmol of carbon dioxide desorption within 2400 s at 80 °C, which was 2000-fold higher than the potassium bicarbonate-water-solution. This research demonstrates a water-lean solvent-based carbon dioxide removal route with the potential to be economical, environmentally safe, and energy-efficient. CO2 sequestration, capture, and utilization technologies will play a key role in reducing CO2 emissions. The excellent desorption kinetics and relatively moderate desorption temperatures (80 °C) of water-lean solvent could help in reducing the cost of CO2 capture, particularly in terms of the heat demand at the regenerator.
Impact of Radar and Surface Data Assimilation on the Forecast of a Nocturnal Squall Line in the Yangtze–Huaihe River
Authors: Pan Zongmei , Zhang Shuwen , Zhang Weidong
Published: September 2022

The impact of radar and surface data assimilation on the forecast of a nocturnal squall line initiated above the stable boundary layer in the Yangtze–Huaihe River is investigated by the Weather Research and Forecasting (WRF) model and its three-dimensional variational assimilation system (WRFDA 3DVar). Results show that the assimilation of radar and surface data can improve the prediction of the convection initiation time, height and vertical ascending motion during the early stage of the squall line formation by adjusting the thermodynamic structure, circulation patterns, water vapor conditions and hydrometeor mixing ratios. Although the radar and surface data assimilation can improve the forecast of the location of the squall line to a certain extent, the squall line is stronger in the radar data assimilation than that in the surface data assimilation, leading to stronger radar reflectivity and heavier precipitation. The assimilation of both radar and surface data has a more positive impact on the forecast skill than the assimilation of either type of data. Moreover, during the mature stage of the squall line, radar and surface data assimilation can enhance the intensity of the surface cold pool. Specifically, radar data assimilation or assimilating the two data simultaneously can produce a stronger cold pool than only assimilating surface data, which is more conducive to the maintenance and development of the squall line.
Increasing Wind Speeds Fuel the Wider Spreading of Pollution Caused by Fires over the IGP Region during the Indian Post-Monsoon Season
Authors: Kumar Vinay , Patil Rupesh , Bhawar Rohini L. , Rahul P.R.C. , Yelisetti Subbarao
Published: September 2022

Every year, forest fires and harvest harnessing produce atmospheric pollution in October and November over the Indo-Gangetic Plain (IGP). The fire count data (MODIS) shows a decreasing/increasing trend of fire counts in all confidence ranges in October/November over Northern India. There is a widespread increase in fires with a confidence level above 60 to 80% over the whole Northern Indian region. The Aerosol Optical Index (AOD) also shows an increase with values > 0.7 over the northwestern and IGP regions. There have been some startling results over the lower IGP belt, where there has been increasing trend in AOD during October ~56% and during November, the increase was by a whopping ~116%. However, in November, a slight turning of the winds towards central India might be transporting the AOD towards the central Indian region. Hence, during November, it is inferred that due to the low wind speed over the lower IGP belt and increased fires, the AODs in the polluted air tend to hover for a long time. During recent years from 2010, the winds have become stronger, indicating more transport of AOD is occurring over the lower IGP belt as compared to previous years till 2009, especially in October.
Corn Disease Recognition Based on Attention Mechanism Network
Authors: Wang Yingying , Tao Jin , Gao Haitao
Published: September 2022

To extract more accurate and abundant features of corn disease and solve the problems of rough classification and low recognition accuracy, the attention mechanism is introduced into the field of corn disease recognition. The corn disease recognition model (AT-AlexNet) is proposed based on an attention mechanism. The network was based on AlexNet, and the new down-sampling attention module was constructed to enhance the foreground response of the disease; the Mish activation function was introduced to improve the nonlinear expression of the network; the new module of the full connection layer was designed to reduce the network parameters. In the experiment of the enhanced corn disease datasets, the average recognition accuracy of the attention-based network model AT-AlexNet is 99.35%. The recognition accuracy of using the Mish activation function is 0.65% higher than that of the ReLu activation function. The experiments show that compared with other identification methods, the proposed method has better classification performance for corn diseases.
Univariate and Multivariate Ostrowski-Type Inequalities Using Atangana–Baleanu Caputo Fractional Derivative
Authors: Desta Henok Desalegn , Pachpatte Deepak B. , Mijena Jebessa B. , Abdi Tadesse
Published: September 2022

In this paper, we obtain some univariate and multivariate Ostrowski-type inequalities using the Atangana–Baleanu fractional derivative in the sense of Liouville–Caputo (ABC). The results obtained for both left and right ABC fractional derivatives can be applied to study further fractional inequalities and estimate various non-local function problems since the operator consists of a non-singular kernel. The obtained results are more generalized in nature.
The Multistage 20-m Shuttle Run Test for Predicting VO2Peak in 6–9-Year-Old Children: A Comparison with VO2Peak Predictive Equations
Authors: Brito João Paulo , Domingos Christophe , Pereira Ana Fátima , Moutão João , Oliveira Rafael
Published: September 2022

This study aimed (i) to verify if using and carrying a portable gas analyzer (PGA) constrained the performance of school children on the multistage 20-m shuttle run test (20mSRT), (ii) to verify which peak oxygen consumption (VO2peak) predictive equations have greater agreement with VO2peak values measured by direct oximetry using the 20mSRT. The study participants were 130 children ((67 boys (age 7.76 ± 0.97 years) and 63 girls (age 7.59 ± 0.91 years)), who performed two randomized trials of the 20mSRT with and without a PGA. Twenty-two predictive equations predicted the VO2peak values through the performance of the test with and without a PGA. Without a PGA, lower values of maximal speed (MS), total laps (TL), and total time (TT) were found for girls than for boys with a PGA. Only six equations were considered to correctly predict VO2peak. In general, higher MS, TL, and TT values were found with the use of a PGA. The predicted VO2peak values from the 20mSRT varied significantly among the published predictive equations. Therefore, we suggest that the six equations that presented satisfactory accuracy could be practically used to examine cardiorespiratory fitness in schools and in research with large populations when direct measurement of VO2peak is not feasible.
GPX3 Overexpression in Cumulus Cells Entails a Poor Prognosis for Uterine Implantation of Morphotype A Embryos
Authors: Bejarano Ignacio , Dorado-Silva Mónica , Sarmiento-Soto Helia , Álvarez-Sánchez Nuria , Lardone Patricia Judith , Guerrero Juan Miguel , Sánchez-Martín Pascual , Carrillo-Vico Antonio
Published: September 2022

Morphological embryo quality is an accurate prognostic tool for the success of assisted reproduction implantation, although complete certainty cannot be guaranteed. The transcriptome of the cumulus cells could be monitored as a faithful reflex of the physiological state of the oocytes, given the molecular crosstalk between both types of cells. Here, we compare the expression of specific genes related to oocyte competence, such as hyaluronic acid synthase 2 (HAS2), cell division control protein 42 (CDC42), connexin 43 (CX43), and glutathione peroxidase 3 (GPX3), in cumulus cells from implanted versus non-implanted embryos in 25 women, using RT-qPCR. After embryo transfer, two cohorts were differentiated: the pregnant group (women with the implantation of 100% of embryos transferred) versus the non-pregnant group (with an absence of embryo implantation), aiming to compare the possible differential expression of the selected genes in the cumulus cells of embryos from each group. HAS2, CDC42 and CX43 did not reveal differential expression between the two cohorts. However, GPX3 showed significantly reduced expression in the cumulus belonging to the pregnant group. Interestingly, even cumulus cells belonging only to morphotype A embryos showed a significantly lower expression of GPX3 in the pregnancy group. GPX3 overexpression in cumulus cells could be a poor prognostic indicator of implantation, discriminating beyond the capacity of the morphokinetic score. Unveiling the cumulus transcriptome could improve successful implantation in assisted reproduction treatments.
Incident Chlamydia trachomatis Infection in a High School Population
Authors: Nsuami M. Jacques , Nsa Wato , Cammarata Catherine L. , Martin David H. , Taylor Stephanie N.
Published: September 2022

Prospective cohort studies of sexually transmitted infections (STIs) are logistically impractical owing to time and expenses. In schools, students are readily available for school-related follow-ups and monitoring. Capitalizing on the logistics that society already commits to ensure regular attendance of adolescents in school, a school-based STI screening in New Orleans made it possible to naturally observe the occurrence of chlamydia and to determine its incidence among 14–19-year-old adolescents. Among participants screened repeatedly, we calculated incidence rates, cumulative incidence, and incidence times. Male (n = 3820) and female (n = 3501) students were observed for 6251 and 5143 person-years, respectively, during which 415 boys and 610 girls acquired chlamydia. Incidence rates per 100 person-years were 6.6 cases for boys and 11.9 cases for girls. In multivariable analysis, the adjusted hazard ratio was 5.34 for boys and 3.68 for girls if the student tested positive for gonorrhea during follow-up, and 2.76 for boys and 1.59 for girls if at first participation the student tested positive for chlamydia, and it increased with age among boys but not among girls. In joinpoint trend analysis, the annual percentage change in the incidence rate was 6.6% for boys (95% CI: −1.2%, 15.1%) and 0.1% for girls (95% CI: −5.3%, 5.7%). Annual cumulative incidence was 5.5% among boys and 8.6% among girls. Median incidence time was 9.7 months for boys and 6.9 months for girls. Our findings can be used to refine assumptions in mathematical modeling and in cost analysis studies of C. trachomatis infection, and provide strong evidence in support of annual chlamydia screening for adolescent boys.
A Mouse Model of Neurodegeneration Induced by Blade Penetrating Stab Wound to the Hippocampus
Authors: He Bao-Dong , Liu Chang-Mei , Teng Zhao-Qian
Published: September 2022

Traumatic brain injury (TBI) is closely associated with the later development of neurodegenerative and psychiatric diseases which are still incurable. Although various animal TBI models have been generated, they usually have weaknesses in standardization, survivability and/or reproducibility. In the present study, we investigated whether applying a blade penetrating stab wound to the hippocampus would create an animal model of cognitive deficits. Open-field, Morris water maze and Barnes maze tests were used to evaluate the animal behaviors. The immunofluorescence staining of NeuN, GFAP, IBA1, and TUNEL was conducted to analyze the changes in neurons, astrocytes, and microglia, as well as cell death. Mice with a hippocampal blade stab injury (HBSI) displayed the activation of microglia and astrocytes, inflammation, neuronal apoptosis, and deficits in spatial learning and memory. These findings suggest that HBSI is an easy approach to generate a reliable in vivo model of TBI to capture hemorrhage, neuroinflammation, reactive gliosis, and neural death, as well as cognitive deficits observed in human patients.
Status and Analysis of Artificial Breeding and Management of Aquatic Turtles in China
Authors: Hong Xiaoyou , Zhang Xiaoyan , Liu Xiaoli , Wang Yakun , Yu Lingyun , Li Wei , Chen Fangcan , Zhu Xinping
Published: September 2022

China is a major country in turtle cultivation and has a long history of artificial breeding of turtles. In this study, a census and statistical analysis of artificially domesticated aquatic turtles in 15 provinces of China were conducted. The results showed that 29 species were aquatic turtles native to China, accounting for approximately 9% of the world’s total, and a large number of exotic aquatic turtles are also domesticated in China. The present situation of artificial breeding and protection of aquatic turtles in major provinces of China is shown, and existing problems are also put forward, with suggestions for the protection and management of aquatic turtles.