bluuebunny/crossref_metadata_2025 huggingface dataset:
The Contribution of Artificial Intelligence in Achieving the Sustainable Development Goals (SDGs): What Can Eye Health Can Learn From Commercial Industry and Early Lessons From the Application of Machine Learning in Eye Health Programmes
Authors: Sawers Nicholas , Bolster Nigel , Bastawrous Andrew
Published: February 2022

Achieving The United Nations sustainable developments goals by 2030 will be a challenge. Researchers around the world are working toward this aim across the breadth of healthcare. Technology, and more especially artificial intelligence, has the ability to propel us forwards and support these goals but requires careful application. Artificial intelligence shows promise within healthcare and there has been fast development in ophthalmology, cardiology, diabetes, and oncology. Healthcare is starting to learn from commercial industry leaders who utilize fast and continuous testing algorithms to gain efficiency and find the optimum solutions. This article provides examples of how commercial industry is benefitting from utilizing AI and improving service delivery. The article then provides a specific example in eye health on how machine learning algorithms can be purposed to drive service delivery in a resource-limited setting by utilizing the novel study designs in response adaptive randomization. We then aim to provide six key considerations for researchers who wish to begin working with AI technology which include collaboration, adopting a fast-fail culture and developing a capacity in ethics and data science.
A Nomogram for Predicting Cancer-Specific Survival of Osteosarcoma and Ewing's Sarcoma in Children: A SEER Database Analysis
Authors: Wang Jinkui , Zhanghuang Chenghao , Tan Xiaojun , Mi Tao , Liu Jiayan , Jin Liming , Li Mujie , Zhang Zhaoxia , He Dawei
Published: February 2022

Background

Osteosarcoma (OSC) and Ewing's sarcoma (EWS) are children's most common primary bone tumors. The purpose of the study is to develop and validate a new nomogram to predict the cancer-specific survival (CSS) of childhood OSC and EWS.

Methods

The clinicopathological information of all children with OSC and EWS from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to screen children's independent risk factors for CSS. These risk factors were used to construct a nomogram to predict the CSS of children with OSC and EWS. A series of validation methods, including calibration plots, consistency index (C-index), and area under the receiver operating characteristic curve (AUC), were used to validate the accuracy and reliability of the prediction model. Decision curve analysis (DCA) was used to validate the clinical application efficacy of predictive models. All patients were divided into low- and high-risk groups based on the nomogram score. Kaplan-Meier curve and log-rank test were used to compare survival differences between the two groups.

Results

A total of 2059 children with OSC and EWS were included. All patients were randomly divided into training cohort 60% (N = 1215) and validation cohort 40% (N = 844). Univariate and multivariate analysis suggested that age, surgery, stage, primary site, tumor size, and histological type were independent risk factors. Nomograms were established based on these factors to predict 3-, 5-, and 8-years CSS of children with OSC and EWS. The calibration plots showed that the predicted value was highly consistent with the actual value. In the training cohort and validation cohort, the C-index was 0.729 (0.702–0.756) and 0.735 (0.702–0.768), respectively. The AUC of the training cohort and the validation cohort also showed similar results. The DCA showed that the nomogram had good clinical value.

Conclusion

We constructed a new nomogram to predict the CSS of OSC and EWS in children. This predictive model has good accuracy and reliability and can help doctors and patients develop clinical strategies.
Driving Management of Novel Foods: A Network Analysis Approach
Authors: Zarbà Carla , Chinnici Gaetano , Hamam Manal , Bracco Salvatore , Pecorino Biagio , D'Amico Mario
Published: February 2022

The food industry has confronted, in recent years, numerous issues including meeting a food demand for individual well-being in a sufficient and healthy manner, also due to the effects of the world population growth. In this scenario, alternative food sources may be a key element both for their contribution to food needs and for the promotion of sustainable and innovative production patterns. These food sources, new compared to traditional food styles, have been regulated by specific European Union regulations under the definition of novel foods. Their importance in the world has raised different topics of scientific research. The present paper aimed to seize the direction of scientific studies in the world focused on the thematic area of novel foods, from a management point of view. This study analyzed 209 papers and carried out a descriptive analysis and a network analysis of the thematic areas under examination also with the help of the software VOSviewer. The results highlighted the importance of scientific research in the world also for the contributions on the exploration of existing markets as well as for the innovative solutions it provides, which aim to expand market possibilities. Finally, the existence of several elements and factors, which may discourage the propensity to consume and therefore the development of the novel foods market, seemed to emerge, and for this reason, many surveys focused on finding solutions to overcome these potential obstacles.
Analysis of Sensitivity of Distance between Embedded Ultrasonic Sensors and Signal Processing on Damage Detectability in Concrete Structures
Authors: Chakraborty Joyraj , Wang Xin , Stolinski Marek
Published: February 2022

Damage detection of reinforced concrete (RC) structures is becoming a more attractive domain due to the safety issues arising in the last few decades. The damage in concrete can be caused by excessive exploitation of the structure or environmental effects. The cracks in concrete can be detected by different nondestructive testing methods. However, the available methods used for this purpose have numerous limitations. The technologies available in the market nowadays have difficulties detecting slowly progressive, locally limited damage. In addition, some of these methods cannot be applied, especially in hard-to-reach areas in the superstructures. In order to avoid these deficiencies, an embedded ultrasonic methodology can be used to detect cracks in RC structures. In this study, the methodology of crack detection supported with the advanced signal processing algorithm was proposed and verified on RC structures of various types, and cracks occurring between embedded sensors can be detected. Moreover, different pairs of ultrasonic sensors located in the considered structures are used for the analysis of the sensitivity of distance between them. It is shown that the ultrasonic sensors placed in the range of 1.5–2 m can detect cracks, even when the other methods failed to detect changes in the structure. The obtained results confirmed that diffuse ultrasonic sensor methodology is able to monitor real structures more effectively than traditional techniques.
An Adaptive Framework for Optimization and Prediction of Air Traffic Management (Sub-)Systems with Machine Learning
Authors: Reitmann Stefan , Schultz Michael
Published: February 2022

Evaluating the performance of complex systems, such as air traffic management (ATM), is a challenging task. When regarding aviation as a time-continuous system measured in value-discrete time series via performance indicators and certain metrics, it is important to use sufficiently targeted mathematical models within the analysis. A consistent identification of system dynamics at the evaluation level, without dealing with the actual physical events of the system, transforms the analysis of time series into a system identification process, which ensures control of an unknown (or only partially known) system. In this paper, the requirements for mathematical modeling are presented in the form of a step-by-step framework, which can be derived from the formal process model of ATM. The framework is applied to representative datasets based on former experiments and publications, for whose prediction of boarding times and classification of flight delays with machine learning (ML) the framework presented here was used. While the training process of neural networks was described in detail there, the paper shown here focuses on the control options and optimization possibilities based on the trained models. Overall, the discussed framework represents a strict guideline for addressing data and machine learning (ML)-based analysis and metaheuristic optimization in ATM.
Enhancement Opportunities for Conceptual Design in Aerospace Based on the Advanced Morphological Approach
Authors: Todorov Vladislav T. , Rakov Dmitry , Bardenhagen Andreas
Published: February 2022

The current challenges facing the aerospace domain require unconventional solutions, which could be sought in new configurations of future aircraft and spacecraft. The choice of optimal concepts requires the consideration of a significant amount of competing engineering solutions and takes place under conditions of uncertainty. Such a problem can be addressed by enhancing existing methods for analysis and synthesis solutions, such as the Advanced Morphological Approach (AMA). It uses morphological analysis to provide a more exhaustive overview of possible problem solutions, relies on expert evaluations of alternative technological options and applies clustering to the solution space. Although an intuitive method for structured concept generation, the AMA exposes the need for more robust problem structuring, improved objectivity of options evaluation and accounting for uncertainties. The current article suggests ways to overcome these challenges and their possible integration in the process. In particular, the integration of fuzzy sets is proposed to model uncertainties during the evaluation of technological options by the experts. The Fuzzy Analytical Hierarchy Process is adapted for integration into the AMA and for the conceptual design of aerospace vehicles.
Non-Destructive Detection of pH Value of Kiwifruit Based on Hyperspectral Fluorescence Imaging Technology
Authors: Wang Xiaohui , Xu Lijia , Chen Heng , Zou Zhiyong , Huang Peng , Xin Bo
Published: February 2022

Non-destructive detection of the pH value of kiwifruit has important practical significance for its quality classification. In this study, hyperspectral fluorescence imaging technology was proposed to quantitatively predict the pH value of kiwifruit non-destructively. Firstly, the SPXY algorithm was used to divide samples into training and prediction sets and three different algorithms were used to preprocess the raw spectral data. Secondly, algorithms such as the iteratively retaining information variables (IRIV), the variable iterative space shrinkage approach (VISSA), the model adaptive space shrinkage (MASS), the random frog (RF), and their combination (i.e., IRIV + VISSA + MASS + RF, IVMR) were used to extract effective variables from the preprocessed spectral data. Moreover, the second extractions, such as IRIV-VISSA and IRIV-MASS, and the third extraction (i.e., IVMR-VISSA-IRIV) were used to further reduce the redundant variables. Based on the effective variables, four regression models—random forest (RF), partial least square (PLSR), extreme learning machines (ELM), and multiple-kernel support vector regression (MK-SVR)—were built and compared for predicting. The results show that IVMR-VISSA-IRIV-MK-SVR had the best prediction results, with RP2, RC2 and RPD of 0.8512, 0.8580, and 2.66, respectively, which verifies that hyperspectral fluorescence imaging technology is reliable for predicting the pH value of kiwifruit non-destructively.
Cattle Manure Fermented with Biochar and Humic Substances Improve the Crop Biomass, Microbiological Properties and Nutrient Status of Soil
Authors: Holatko Jiri , Bielska Lucie , Hammerschmiedt Tereza , Kucerik Jiri , Mustafa Adnan , Radziemska Maja , Kintl Antonin , Baltazar Tivadar , Latal Oldrich , Brtnicky Martin
Published: February 2022

Co-composting of raw manure with other organic sources has recently gained the attention of the scientific community. In the present study, raw manure and manures enriched with humic substances (Humac) or biochar were co-composted to improve their physico-chemical properties. We conducted an experiment including variants consisting of soil amended with manure (M), manure + Humac (M + H), manure + biochar (M + B), and unamended (control). Soil physico-chemical, biological, and plant properties were assessed altogether. All matured manures differed from each other physico-chemically (nutrient content) and in microbial composition, and hence their effects on the observed parameters. Compared to control, the soil respiration and enzyme activities related to N and P mineralization were enhanced due to the amendment of either manure or enriched manures. The M + H treatment resulted in higher pH of the manures as compared to other treatments, whereas the M + B and M treatments revealed the highest Corg contents of the final product, which was negatively correlated with HA:FA. In the same manner, M + H and M + B were the most prominent treatments, causing higher variations in basal soil respiration. The same treatments resulted in the highest percent increase values of soil enzymes related to C, N, and P, which further show the potential of manure modification as a viable option to boost soil fertility and health.
Will Climate Warming Alter Biotic Stresses in Wild Lowbush Blueberries?
Authors: Chen Yu-Ying , Pahadi Pratima , Calderwood Lily , Annis Seanna , Drummond Francis , Zhang Yong-Jiang
Published: February 2022

As global temperatures rise, a growing need exists for understanding the impacts of warming on crop production. Warming not only changes crop physiology and growth but also the weeds, insect pests, and diseases of crops including wild lowbush blueberries, which have not been studied till now. Changes in pest pressures can cause instability in production and will require changes in management practices and the development of mitigation strategies. The objective of this study was to determine the impacts of warming on the prevalence of major weeds, insect pests, and diseases of the wild blueberry production system. We selected six genotypes of wild lowbush blueberries in a commercially managed wild blueberry field in Maine Northeast USA and used open-top-chambers (OTCs) to study the effects of warming for two years (2019 and 2020). Both active-heating OTCs (elevated monthly mean temperatures by 3.3 °C) and passive-heating OTCs (elevated by 1.2 °C) were employed and compared with ambient controls. Our results showed that warming did not change the prevalence of red leaf disease, blueberry gall midge, red-striped fireworm, or any weed species. In contrast, the incidence of Sphaerulina leaf spot, powdery mildew, and other leaf spot disease were significantly lower under warming treatments compared to the ambient control at the end of the growing season in 2020. Overall, different pests responded to warming differently, inviting further research to reveal the mechanisms. The lower overall pressure of leaf spot disease under warming was probably due to decreased air humidity.
Polyarenes Distribution in the Soil-Plant System of Reindeer Pastures in the Polar Urals
Authors: Shamrikova Elena , Yakovleva Evgeniia , Gabov Dmitry , Zhangurov Egor , Korolev Michail , Zazovskaya Elya
Published: February 2022

Humic substances of soils consist of various organic compounds, including polycyclic aromatic hydrocarbons (PAHs). Soil as a fairly stable medium allows the correct use of polyarenes as markers of the humus formation process. Monitoring of the accumulation of PAHs as resistant organic toxicants is also necessary due to their carcinogenic and mutagenic properties. Natural plant resources serve as the feed base of northern reindeer husbandry. In this study, high-performance liquid chromatography in a gradient mode and gas chromatography-mass spectrometry methods were used to estimate the content of PAHs in mountain tundra and meadows of the Polar Urals (Russia). The accumulation of polyarenes in soils on carbonate rocks of the Bolshoi Paipudynsky ridge occurs mainly in the process of soil formation and largely depends on factors such as productivity of plant communities, the composition of standing biomass, the site’s position in relief, the granulometric composition of soils, cryogenesis process and pyrogenesis. According to the set of polyarenes, their number, and ratio, the studied objects were classified into separate groups by discriminant analysis. The most typical representatives of pedogenic origin are naphthalene and phenanthrene. The accumulation features of dibenz[a,h]anthracene and benz[b]-, benz[k]fluoranthene, benz[ghi]perylene, and benz[a]perylene are shown. In mountain tundra landscapes, the characteristics of PAHs can be used to diagnose the intensity and direction of soil formation processes in general and humification in particular.
Animal Welfare and Parasite Infections in Organic and Conventional Dairy Farms: A Comparative Pilot Study in Central Italy
Authors: Chincarini Matteo , Lanzoni Lydia , Di Pasquale Jorgelina , Morelli Simone , Vignola Giorgio , Paoletti Barbara , Di Cesare Angela
Published: February 2022

The study investigated and compared welfare conditions and gastrointestinal (GI) parasites distribution among organic (ORG) and conventional (CONV) farms in central Italy. Five ORG and five CONV farms were assessed for animal welfare with an adapted version of the AssureWel protocol. Faecal samples collected from the rectum of the animals both in ORG (n = 150) and CONV (n = 150) were analysed using conventional copromiscroscopy. The presence of skin damages in the rear legs was significantly predominant (p < 0.001) in CONV (26.7%) compared with ORG farms (10.0%). No differences were found for lameness, cleanliness, Body Condition Score, hair loss, body lesions and swelling prevalence. Data concerning the productive performances, e.g., total milk, fat and protein yields standardised in mature equivalent (ME) were collected. ME milk yield (ORG: 9656.9 ± 1620.7 kg; CONV: 12,047.2 ± 2635.3) and ME fat yield (ORG: 396.6 ± 66.8; CONV: 450.3 ± 102.8) were significantly lower in ORG farms (p < 0.001). Anthelmintics were used regularly in 4/5 CONV and 0/5 ORG farms. In 2 CONV farms (40%) and 4 ORGs (80%) at least one animal tested positive for GI parasites. No significant differences in parasites prevalence emerged (ORG = 10.7%; CONV = 8%). These data indicate that ORG farming does not influence parasite prevalence and animal welfare status.
Herbst Appliance Reinforced with an Hybrid Hyrax Expander and Two Miniscrews in the Lower Arch: Case Report
Authors: Migliorati Marco , Calzolari Chiara
Published: February 2022

Introduction: Class II growing patients can be successfully treated with the Herbst appliance, nevertheless this therapy generally produces side effects, such as upper incisors retroclination and lower incisors proclination, which eventually could reduce mandibular forward advancement. Treatment objectives: The purpose of this article is to show a treatment of class II malocclusion with crowding in both arches by a skeletally reinforced Herbst appliance. Treatment description: Two miniscrews were applied in the lower arch to control lower incisors proclination and in the upper arch an Hybrid palatal expander was used. Results: the correction of the severe class II malocclusion was obtained with mandibular advancement, avoiding lower incisors proclination with control also of the upper incisors. Upper crowding with lack of space for upper canine alignment was corrected. Conclusions: Upper and lower miniscrews worked successfully as anchorage for the entire treatment.
Quantitative Proteome Analysis in Response to Glucose Concentration in C2C12 Myotubes
Authors: Kato Ayano , Sakakibara Iori , Fukushima Taku , Sugiura Kosuke , Fukawa Tomoya , Nikawa Takeshi , Uchida Takayuki
Published: February 2022

Glucose is important for the maintenance of muscle function; however, it is still unclear how changes in glucose concentration affect muscle. Here, we analyzed the effect of glucose concentration on protein expression under different glucose concentration media in C2C12 myotubes. First, we performed proteome analysis in C2C12 myotubes cultured in Low (1.0 g/L), Medium (2.0 g/L), and High (4.5 g/L) glucose media. Proteome analysis revealed 113 proteins were significantly changed in group cultured in Low or Medium glucose media compared to group cultured in High glucose media. Furthermore, glycolysis, oxidative phosphorylation, and fatty acid metabolism were increased in the Medium and Low groups. Among these pathways, HK2, PFKP, NDUFA11, and FABP3 were especially upregulated proteins in Low and Medium groups. In this context, ATP production in C2C12 myotubes cultured in Low and Medium glucose media was increased. There was no significant change in myotubes morphology and myogenic differentiation factors in all groups. Finally, we examined the effect on glucose concentration in culture media on myosin isoforms expression by qRT-PCR. As a result, Myh2 and Myh4 were significantly increased in Low and Medium conditions. Altogether, Low and Medium glucose conditions induced Myh expression probably via enhancement glucose utilization.
Geo-Electrical Detection of Impermeable Membranes in the Subsurface
Authors: Karaoulis Marios , Kruiver Pauline P. , Hopman Victor , Beuving Bob
Published: February 2022

In this paper, we have investigate looking ahead capabilities of electrical resistivity tomography (ERT) for a soil penetrating tool with electrodes. In our case study, the desired detection resolution (10 to 20 cm at a depth of at least 6 m) was much higher than what can be achieved from classical surface ERT measurements. Therefore, we designed a logging-type tool, that can be pushed into the ground. Our target was a buried PVC membrane which acts as an electrical insulator. In this phase, we performed numerical simulations and laboratory measurements. The methodology is based on a two-step approach. First, we calculate the background resistivity of the tool’s path is determined by inversion of near-looking electrode configurations. Next, the theoretical response (kernel) of the far-looking configurations is calculated for different membrane positions. The root mean square (RMS) error between the kernel and the measurements is minimized to detect the membrane. If the membrane is within sensing reach, the RMS has a minimum for the kernel corresponding to the true membrane position. If no minimum in RMS is found, the membrane is not within sensing reach and the tool can be pushed closer to the membrane. The laboratory tests comprised measurements in a tank filled with either water or saturated sand or saturated sand with clay slabs and chunks. The laboratory results were successful in pinpointing the position of the membrane with an accuracy of 10 to 20 cm, depending on the dimension of the tool and the distance from the membrane.
Password Guessability as a Service (PGaaS)
Authors: Bojato Juan , Donado Daniel , Jimeno Miguel , Moreno Giovanni , Villanueva-Polanco Ricardo
Published: February 2022

This paper presents an adaptable password guessability service suited for different password generators according to what a user might need when using such a service. In particular, we introduce a flexible cloud-based software architecture engineered to provide an efficient and robust password guessability service that benefits from all the features and goals expected from cloud applications. This architecture comprises several components, featuring the combination of a synthetic dataset generator realized via a generative adversarial network (GAN), which may learn the distribution of passwords from a given dictionary and generate high-quality password guesses, along with a password guessability estimator realized via a password strength estimation algorithm. In addition to detailing the architecture’s components, we run a performance evaluation on the architecture’s key components, obtaining promising results. Finally, the complete application is delivered and may be used by a user to estimate the strength of a password and the time taken by an average computer to enumerate it.
Analysis of Viscoelastic Damping Effect on the Underwater Acoustic Radiation of a Ring-Stiffened Conical Shell
Authors: Chen Zhanyang , Gong Qingtao , Zhao Weidong , Gui Hongbin
Published: February 2022

Hydroacoustic radiation from submarine power compartments has been the focus of research for many years. In this work, a ring-stiffened conical shell with bases is employed as the target model. The self-factors of viscoelastic damping, such as the damping thickness and damping location, are selected to study their effect on the underwater acoustic radiation, which will give a better understanding of the optimal scheme for applying damping. Firstly, based on a combination of finite element method (FEM) and boundary element method (BEM), the underwater vibration and acoustic radiation of the whole structure are analyzed. Secondly, taking a clamped-free sandwich beam as an example, through comparison with the published numerical data, the present damping application method and mesh density are verified. Finally, the influence of viscoelastic damping parameters on acoustic radiation is studied. The results show that the viscoelastic damping thickness has a significant influence on the amplitude of radiated noise but does not change the distribution of the acoustic field. Furthermore, the damping on the web may achieve the best vibration damping effect in this work.
Classification of Ground-Based Cloud Images by Improved Combined Convolutional Network
Authors: Zhu Wen , Chen Tianliang , Hou Beiping , Bian Chen , Yu Aihua , Chen Lingchao , Tang Ming , Zhu Yuzhen
Published: February 2022

Changes in clouds can affect the outpower of photovoltaics (PVs). Ground-based cloud images classification is an important prerequisite for PV power prediction. Due to the intra-class difference and inter-class similarity of cloud images, the classical convolutional network is obviously insufficient in distinguishing ability. In this paper, a classification method of ground-based cloud images by improved combined convolutional network is proposed. To solve the problem of sub-network overfitting caused by redundancy of pixel information, overlap pooling kernel is used to enhance the elimination effect of information redundancy in the pooling layer. A new channel attention module, ECA-WS (Efficient Channel Attention–Weight Sharing), is introduced to improve the network’s ability to express channel information. The decision fusion algorithm is employed to fuse the outputs of sub-networks with multi-scales. According to the number of cloud images in each category, different weights are applied to the fusion results, which solves the problem of network scale limitation and dataset imbalance. Experiments are carried out on the open MGCD dataset and the self-built NRELCD dataset. The results show that the proposed model has significantly improved the classification accuracy compared with the classical network and the latest algorithms.
In-Orbit Reliability Evaluation of Space TWTA Based on Copula Function and Bivariate Hybrid Stochastic Processes
Authors: Wang Xiao-Ning , Su Xiao-Bao , Ma Dong-Dong , Zhang Rui , Miao Guo-Xing , Wang Wei-Long
Published: February 2022

Currently, it is still a challenge to study the degradation mechanisms of the space traveling wave tube amplifier (TWTA) with no failure and small sample tests. Given that the Copula functions are used to describe the correlation of multiple performance characteristics, this paper develops a bivariate hybrid stochastic degradation model to evaluate the in-orbit reliability of TWTA. Firstly, based on the impact analysis of the life of TWTA, helix current and anode voltage are selected as the performance degradation parameters. Secondly, stochastic processes with random effects based on the one-dimensional Wiener process and Gamma process are applied to describe the degradation of TWTA’s helix current and anode voltage, respectively, and the corresponding marginal distribution function is obtained. Then, the Copula function is utilized to describe the correlation between two different performance parameters of TWTA. Meanwhile, this paper also proposed a two-step method to estimate the reliability level of TWTA based on its in-orbit telemetry data through a two-step method, which contains a Markov Chain Monte Carlo (MCMC) algorithm and a maximum likelihood estimation (MLE) algorithm. Besides, the Bayes-Bootstrap sampling method is also used to improve the evaluation accuracy to overcome the defect of an in-orbit small sample of TWTA. Finally, a TWTA degradation case with a set of telemetry data is carried out, and the results show that the method proposed in this paper is more applicable and more accurate than other methods.
PIV Measurements of Turbulent Airflow in a Channel with Trapezoidal Ribs on One Wall
Authors: Wodziak Waldemar , Sobczyk Jacek
Published: February 2022

This paper presents the results of PIV measurements of turbulent airflow in a channel with a single ribbed wall. The rough elements had the form of evenly spaced trapezoids. The ratio of the height of a single rib to the height of the measurement channel was 0.1. The ratio of the distance between adjacent ribs to the height of a single rib (i.e., the w/k ratio) was 5, which suggests a transitional region within the airflow structure between the d- and k- types. The measurements were carried out for the inlet velocity, at which the Reynolds number (Re) was equal to 32,500. The distance to the first rib, at which the turbulent velocity profile is fully developed, was determined. The distribution of the average velocity components, the velocity fluctuation components, turbulent shear stress, as well as the turbulence kinetic energy between two adjacent ribs was presented. The analysis of average streamlines indicated the existence of two vortex structures between the ribs.
Variability of the Aerosol Content in the Tropical Lower Stratosphere from 2013 to 2019: Evidence of Volcanic Eruption Impacts
Authors: Tidiga Mariam , Berthet Gwenaël , Jégou Fabrice , Kloss Corinna , Bègue Nelson , Vernier Jean-Paul , Renard Jean-Baptiste , Bossolasco Adriana , Clarisse Lieven , Taha Ghassan , Portafaix Thierry , Deshler Terry , Wienhold Frank G. , Godin-Beekmann Sophie , Payen Guillaume , Metzger Jean-Marc , Duflot Valentin , Marquestaut Nicolas
Published: February 2022

This paper quantifies the tropical stratospheric aerosol content as impacted by volcanic events over the 2013–2019 period. We use global model simulations by the Whole Atmosphere Community Climate Model (WACCM) which is part of the Community Earth System Model version 1.0 (CESM1). WACCM is associated with the Community Aerosol and Radiation Model for Atmospheres (CARMA) sectional aerosol microphysics model which includes full sulphur chemical and microphysical cycles with no a priori assumption on particle size. Five main volcanic events (Kelud, Calbuco, Ambae, Raikoke and Ulawun) have been reported and are shown to have significantly influenced the stratospheric aerosol layer in the tropics, either through direct injection in this region or through transport from extra-tropical latitudes. Space-borne data as well as ground-based lidar and balloon-borne in situ observations are used to evaluate the model calculations in terms of aerosol content, vertical distribution, optical and microphysical properties, transport and residence time of the various volcanic plumes. Overall, zonal mean model results reproduce the occurrence and vertical extents of the plumes derived from satellite observations but shows some discrepancies for absolute values of extinction and of stratospheric aerosol optical depth (SAOD). Features of meridional transport of the plumes emitted from extra-tropical latitudes are captured by the model but simulated absolute values of SAOD differ from 6 to 200% among the various eruptions. Simulations tend to agree well with observed in situ vertical profiles for the Kelud and Calbuco plumes but this is likely to depend on the period for which comparison is done. Some explanations for the model–measurement discrepancies are discussed such as the inaccurate knowledge of the injection parameters and the presence of ash not accounted in the simulations.
Spatiotemporal Variations and Influent Factors of Tropospheric Ozone Concentration over China Based on OMI Data
Authors: Zhu Lei , Liu Minxia , Song Jiaying
Published: February 2022

Spatiotemporal distribution of atmospheric pollutants has been a hot topic in the field of environmental science in recent years. Rapid economic development, urbanization, and industrialization have resulted in a significant increase in ozone emissions, and China is facing the issue of air pollution with high ozone concentrations in the ambient air. The Aura ozone monitoring instrument (OMI), can provide long-term and large-scale dynamic monitoring of tropospheric column ozone (TCO). The TCO concentrations over China were extracted and analyzed from 2005 to 2019. The results showed that the spatiotemporal distribution of ozone concentration decreased from northeast to southeast in China. The seasonal variations of ozone concentration were spring’s concentration is greater than winter’s concentration, winter’s concentration is greater than summer’s concentration, summer’s concentration is greater than autumn’s concentration. The monthly variation showed a cyclical trend, with low values observed from June to November and high values from December to May. In addition, the spatiotemporal distribution of ozone concentration was affected by natural factors and anthropogenic factors. Regarding natural factors, TCO concentration was positively correlated with temperature, wind field, and vegetation coverage, but negatively with precipitation in southwest China. Regarding anthropogenic factors, TCO concentration showed a significant positive correlation with regional GDP, oxides of nitrogen (NOx), and volatile organic compounds (VOCs) in most areas of China. Clustering of backward air trajectories revealed that northwest and southeast airflows led to a higher TCO concentration in northeast China. These further indicate that the variation of TCO concentration was affected by many factors, but temperature, wind field, and the emissions of NOx and VOCs were the key factors.
Strontium Isotope Systematics of Tenerife Wines (Canary Islands): Tracing Provenance in Ocean Island Terroir
Authors: Coldwell Beverley C. , Pérez Nemesio M. , Vaca Maria Cordero , Pankhurst Matthew J. , Hernández Pedro A. , Rodriguez Gladys V. Melián , Padrón Eleazar , Asensio-Ramos María , Ribeiro Sara , Santos José Francisco
Published: February 2022

The production of fraudulent goods remains widespread and economically damaging. The high value of the wine industry makes it particularly vulnerable, and a number of geochemical methods have been developed to ensure traceability and identification of origin. Here, strontium (Sr) isotope data on wines from five defined regions in Tenerife (Canary Islands, Spain) show that the young volcanic geology imparts a clearly identifiable low 87Sr/86Sr signature (<0.7072). These values discriminate Tenerife wines from mainland Spanish and continental European produce, as these are much more radiogenic in general. However, unlike continental wine regions, wines from Tenerife show small but ubiquitous enrichments in 87Sr/86Sr above what is expected in the soils. Bentonite addition has not affected the 87Sr/86Sr signatures, with white wines at lower Sr concentrations than red wines in all regions. A number of natural contributions to the terroir are evaluated in relation to Tenerife’s unique combination of geology and geography. Atmospheric precipitation (rainfall) is likely a dominant influence on Sr isotope systematics in northern Denominación de Origen regions, and evaporation may play a role in buffering signatures in southern regions. Other natural additions of 87Sr are not precluded at a local scale, given the large range in climatic conditions of island terroir and known input of mineral dust from Africa. Despite natural explanations affecting the overall small shift observed, there are clear outliers with considerably higher 87Sr/86Sr and Sr concentration. This confirms the utility of Sr isotope systematics for oceanic-island viticulture and demonstrates the use of young volcanic soils for tracing natural inputs that may be masked in other regions.
Molybdenum Disulfide-Based Nanoprobes: Preparation and Sensing Application
Authors: Gong Lingbo , Feng Lin , Zheng Youwei , Luo Yi , Zhu Dan , Chao Jie , Su Shao , Wang Lianhui
Published: February 2022

The use of nanoprobes in sensors is a popular way to amplify their analytical performance. Coupled with two-dimensional nanomaterials, nanoprobes have been widely used to construct fluorescence, electrochemical, electrochemiluminescence (ECL), colorimetric, surface enhanced Raman scattering (SERS) and surface plasmon resonance (SPR) sensors for target molecules’ detection due to their extraordinary signal amplification effect. The MoS2 nanosheet is an emerging layered nanomaterial with excellent chemical and physical properties, which has been considered as an ideal supporting substrate to design nanoprobes for the construction of sensors. Herein, the development and application of molybdenum disulfide (MoS2)-based nanoprobes is reviewed. First, the preparation principle of MoS2-based nanoprobes was introduced. Second, the sensing application of MoS2-based nanoprobes was summarized. Finally, the prospect and challenge of MoS2-based nanoprobes in future were discussed.
Prodromal Cognitive Deficits and the Risk of Subsequent Parkinson’s Disease
Authors: Speelberg Daniël H. B. , Janssen Daalen Jules M. , Bloem Bastiaan R. , Gagnon Jean-François , Post Bart , Darweesh Sirwan K. L.
Published: February 2022

Background: There is growing interest in identifying individuals who are in the prodromal phase of Parkinson’s disease (PD), as these individuals are potentially suitable for inclusion in intervention trials to prevent clinically manifest PD. However, it is less clear whether—and to what extent—cognitive deficits are present in prodromal PD. Methods: A systematic query was conducted through PubMed and Embase for prospective observational cohort studies that (a) assessed cognitive performance in individuals free of manifest PD at baseline and (b) subsequently followed up participants for incident PD. We grouped the results by cognitive domain, and for domains that had been reported in at least three separate studies, we performed random-effects, inverse variance meta-analyses based on summary statistics. Results: We identified nine articles suitable for inclusion, with a total of 215 patients with phenoconversion and 13,524 individuals remaining disease-free at follow-up. The studies were highly heterogeneous in study design, study population, and cognitive test batteries. Studies that included only cognitive screening measures such as MMSE or MoCA reported no association between worse cognitive performance and onset of manifest PD (combined odds ratio 1.08; 95% confidence interval 0.66–1.77). By contrast, studies that used extensive cognitive testing batteries found that global cognitive deficits were associated with an increased risk of manifest PD. In domain-specific analyses, there was evidence for an association between worse executive functioning (OR 1.45; 95% CI 1.10–1.92), but not memory (OR 1.20; 95% CI 0.85–1.70) or attention (OR 0.98; 95% CI 0.23–4.26), and clinically manifest PD. Conclusion: Although some caution due to high heterogeneity among published studies is warranted, the available evidence suggests that global and executive cognitive deficits are prodromal features of PD. Collaborative prospective studies with extensive cognitive test batteries are required to shed light on domain-specific deficits, temporal relations, and subgroup differences in prodromal cognitive deficits in PD.
Decision Making and Risk Propensity in Individuals with Tendencies towards Specific Internet-Use Disorders
Authors: Müller Silke M. , Wegmann Elisa , Garcia Arías María , Bernabéu Brotóns Elena , Marchena Giráldez Carlos , Brand Matthias
Published: February 2022

The uncontrolled use of specific Internet applications is increasingly recognized as a mental health issue. Gaming disorder, which is one subtype of specific Internet-use disorders (sIUDs), has been included in the ICD-11 as disorder due to addictive behaviors. Addictive disorders are assumed to be accompanied by cognitive deficits as indicated by weaker performance in executive function and risky decision-making tasks. This study investigates risky decision-making in individuals with tendencies towards sIUDs including gaming, online buying-shopping, and social-networks-use disorders. A total of 293 individuals participated in the study. Based on specific screening instruments, the participants were assigned to a group with tendencies towards sIUD or a control group. Participants completed a risky decision-making task and questionnaires assessing risk-taking propensity, impulsivity, psychopathology, and perceived stress. The group with sIUD tendencies showed higher attentional impulsivity and higher levels of depression and anxiety compared to the control group. The groups did not differ in decision making and risk propensity. Decision making did not have significant effects on sIUD symptoms. Risk for developing sIUDs does not appear to be accompanied by altered general decision-making tendencies. Rather, psychological (pre-)load and attentional deficits appear to be relevant features in uncontrolled use of the Internet.
Magnetic Resonance Parkinsonism Index Is Associated with REM Sleep Behavior Disorder in Parkinson’s Disease
Authors: Urso Daniele , Nigro Salvatore , Tafuri Benedetta , Gnoni Valentina , Filardi Marco , De Blasi Roberto , Ray Chaudhuri K. , Logroscino Giancarlo
Published: February 2022

We investigated the association between the Magnetic Resonance Parkinsonism Index (MRPI) and REM sleep behavior disorder (RBD). We included 226 de novo PD patients (82 PD-RBD and 144 PD-noRBD) and 19 idiopathic RBD patients. Furthermore, 3T T1-weighted MR images were used for automated brainstem calculations. MRPI values were higher in the PD-RBD (p = 0.004) compared to PD-noRBD patients. Moreover, MRPI proved to be a significant predictor of REM Behavior Disorder Screening Questionnaire scores in PD (β = 0.195, p = 0.007) and iRBD patients (β = 0.582, p = 0.003). MRPI can be used as an imaging marker of RBD in patients with de novo PD and iRBD.
Using Inhibitory DREADDs to Silence LC Neurons in Monkeys
Authors: Perez Pauline , Chavret-Reculon Estelle , Ravassard Philippe , Bouret Sebastien
Published: February 2022

Understanding the role of the noradrenergic nucleus locus coeruleus (LC) in cognition and behavior is critical: It is involved in several key behavioral functions such as stress and vigilance, as well as in cognitive processes such as attention and decision making. In recent years, the development of viral tools has provided a clear insight into numerous aspects of brain functions in rodents. However, given the specificity of primate brains and the key benefit of monkey research for translational applications, developing viral tools to study the LC in monkeys is essential for understanding its function and exploring potential clinical strategies. Here, we describe a pharmacogenetics approach that allows to selectively and reversibly inactivate LC neurons using Designer Receptors Exclusively Activated by Designer Drugs (DREADD). We show that the expression of the hM4Di DREADD can be restricted to noradrenergic LC neurons and that the amount of LC inhibition can be adjusted by adapting the dose of the specific DREADD activator deschloroclozapine (DCZ). Indeed, even if high doses (>0.3 mg/kg) induce a massive inhibition of LC neurons and a clear decrease in vigilance, smaller doses (<0.3 mg/kg) induce a more moderate decrease in LC activity, but it does not affect vigilance, which is more compatible with an assessment of subtle cognitive functions such as decision making and attention.
The Role of Thymine DNA Glycosylase in Transcription, Active DNA Demethylation, and Cancer
Authors: Onabote Oladapo , Hassan Haider M. , Isovic Majdina , Torchia Joseph
Published: February 2022

DNA methylation is an essential covalent modification that is required for growth and development. Once considered to be a relatively stable epigenetic mark, many studies have established that DNA methylation is dynamic. The 5-methylcytosine (5-mC) mark can be removed through active DNA demethylation in which 5-mC is converted to an unmodified cytosine through an oxidative pathway coupled to base excision repair (BER). The BER enzyme Thymine DNA Glycosylase (TDG) plays a key role in active DNA demethylation by excising intermediates of 5-mC generated by this process. TDG acts as a key player in transcriptional regulation through its interactions with various nuclear receptors and transcription factors, in addition to its involvement in classical BER and active DNA demethylation, which serve to protect the stability of the genome and epigenome, respectively. Recent animal studies have identified a connection between the loss of Tdg and the onset of tumorigenesis. In this review, we summarize the recent findings on TDG’s function as a transcriptional regulator as well as the physiological relevance of TDG and active DNA demethylation in cancer.
Pregnant Women and Endocrine Disruptors: Role of P2X7 Receptor and Mitochondrial Alterations in Placental Cell Disorders
Authors: Fouyet Sophie , Olivier Elodie , Leproux Pascale , Dutot Mélody , Rat Patrice
Published: February 2022

In pregnant women, the lungs, skin and placenta are exposed daily to endocrine-disrupting chemicals (EDCs). EDCs induce multiple adverse effects, not only on endocrine organs, but also on non-endocrine organs, with the P2X7 cell death receptor being potentially the common key element. Our objective was first to investigate mechanisms of EDCs toxicity in both endocrine and non-endocrine cells through P2X7 receptor activation, and second, to compare the level of activation in lung, skin and placental cells. In addition, apoptosis in placental cells was studied because the placenta is the most exposed organ to EDCs and has essential endocrine functions. A total of nine EDCs were evaluated on three human cell models. We observed that the P2X7 receptor was not activated by EDCs in lung non-endocrine cells but was activated in skin and placenta cells, with the highest activation in placenta cells. P2X7 receptor activation and apoptosis are pathways shared by all tested EDCs in endocrine placental cells. P2X7 receptor activation along with apoptosis induction could be key elements in understanding endocrine placental and skin disorders induced by EDCs.