bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Heat Treatment on the Microstructure and Hardness of A356 (AlSi7Mg0.3) Manufactured by Vertical Centrifugal Casting
Authors: Kim Wonho , Jang Kyungsu , Ji Changwook , Lee Eunkyung
Published: December 2021

The A356 alloy has been widely used in automotive components, such as wheels and brake disks, because it is an excellent lightweight material with high corrosion resistance and good mechanical properties. Recently, to reduce the weight of brake disks, the Fe-A356 hybrid brake disk has been suggested. Because brake disk quality is directly related to driving safety, the T4/T6 heat treatment of centrifugally cast A356 alloys were performed to enhance the mechanical properties and reduce micro-segregation. The solid-solution heat treatment followed by annealing caused the formation of Mg-rich intermetallic compounds on the grain boundaries of the Al matrix, decreasing the average hardness of the alloys by 13 HV. In contrast, the solid solution followed by water quenching (T4) reduced the area fractions of the intermetallic compounds and increased the average hardness by 11 HV. The T6 heat-treated A356 alloys, which were influenced by the formation of the Guinier–Preston zone exhibited a relatively higher average hardness, by 18 HV, compared to T4 heat-treated A356 alloys.
Manufacture and Characterization of Alginate-CMC-Dextran Hybrid Double Layer Superabsorbent Scaffolds
Authors: Choi Jeongyeon , Jeon Heekyung
Published: December 2021

This study focused on the manufacturing of functional superabsorbent sponges using natural polymers. An alginate/CMC-embedded dextran hybrid dual-layer formulation was prepared using the freeze-drying method. The physical properties of the formulation were characterized using a field emission scanning electron microscope and a universal testing machine, and the swelling ratio was calculated. Cell viability assays were performed using keratinocytes (HaCaT cells). The results showed that this formulation can absorb a large amount of moisture and provide morphological stability through its tensile strength and uniform porosity, and this was verified by its biocompatibility. We believe that in the future, by combining this novel hybrid dual-layer superabsorbent sponge with antibacterial agents with excellent porosity, it would serve as a medical material for producing bandages that can absorb blood and body fluids, feminine hygiene products, and functional antibacterial masks.
Hybrid Power System for the Range Extension of Security Robots: Specification Development Phase
Authors: Sung Woosuk
Published: December 2021

This paper describes our best practices related to hybrid power system (HPS) development, with a focus on the specification development phase. The HPS specifications are based on the main development goals of our security robot, which place top priority on 24 h continuous operation on a single charge. Similar to human guards, security robots are expected to operate 24 h per day, seven days per week, but existing battery-powered robots cannot meet these goals. For long-duration missions, their operating times are too short, and their charging times are too long. As an effective alternative, hydrogen fuel cells are combined with batteries to hybridize the power systems of security robots. In this study, several HPS structures were comprehensively compared by selecting a one-stage series structure. Component specifications were determined based on the selected structure to achieve the main development goals of our security robot. To verify whether the determined specifications are valid, a HPS simulator was developed. The key operating conditions for the HPS were simulated, including overloading, terminal short-circuiting, and drive cycling. Under critical conditions, the behavior of the entire system and its components was confirmed. The developed specifications will eventually be carried over to the prototyping phase.
Correction: Souza et al. A Regularized Mixture of Linear Experts for Quality Prediction in Multimode and Multiphase Industrial Processes. Appl. Sci. 2021, 11, 2040
Authors: Souza Francisco , Mendes Jérôme , Araújo Rui
Published: December 2021

We, the authors, wish to make the following corrections to our paper [...]
The Metamorphosis (of RAM3S)
Authors: Bartolini Ilaria , Patella Marco
Published: December 2021

The real-time analysis of Big Data streams is a terrific resource for transforming data into value. For this, Big Data technologies for smart processing of massive data streams are available, but the facilities they offer are often too raw to be effectively exploited by analysts. RAM3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. RAM3S has been proven helpful in simplifying the deployment of non-parallel techniques to streaming platforms, such as Apache Storm or Apache Flink. In this paper, we show how RAM3S has been updated to incorporate novel stream processing platforms, such as Apache Samza, and to be able to communicate with different message brokers, such as Apache Kafka. Abstracting from the message broker also provides us with the ability to pipeline several RAM3S instances that can, therefore, perform different processing tasks. This represents a richer model for stream analysis with respect to the one already available in the original RAM3S version. The generality of this new RAM3S version is demonstrated through experiments conducted on three different multimedia applications, proving that RAM3S is a formidable asset for enabling efficient and effective Data Mining and Machine Learning on multimedia data streams.
Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis
Authors: Ulrich Luca , Nonis Francesca , Vezzetti Enrico , Moos Sandro , Caruso Giandomenico , Shi Yuan , Marcolin Federica
Published: December 2021

Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.
Orientation of Liquid Crystalline Molecules on PDMS Surfaces and within PDMS Microfluidic Systems
Authors: Baczyński Szymon , Sobotka Piotr , Marchlewicz Kasper , Słowikowski Mateusz , Juchniewicz Marcin , Dybko Artur , Rutkowska Katarzyna A.
Published: December 2021

The unique components of PDMS-based microfluidic systems are those combined with liquid crystalline materials. Their functionality, especially when it comes to optical applications, highly depends on the LC molecular arrangement. This work summarizes experimental investigations on the orientation of molecules within LC:PDMS structures according to the manufacturing technologies. The availability of high-quality molds to pattern PDMS is a significant barrier to the creation of advanced microfluidic systems. The possibility of using inexpensive molds in the rapid and reproducible fabrication process has been particularly examined as an alternative to photolithography. Different geometries, including an innovative approach for the electrical control of the molecular arrangement within PDMS microchannels, are presented. These studies are critical for novel optofluidic systems, introducing further research on LC:PDMS waveguiding structures.
Predicting Traffic Sign Retro-Reflectivity Degradation Using Deep Neural Networks
Authors: Alkhulaifi Abdolmaged , Jamal Arshad , Ahmad Irfan
Published: December 2021

Traffic signs are essential for the safe and efficient movement of vehicles through the transportation network. Poor sign visibility can lead to accidents. One of the key properties used to measure the visibility of a traffic sign is retro-reflection, which indicates how much light a traffic sign reflects back to the driver. The retro-reflection of the traffic sign degrades over time until it reaches a point where the traffic sign has to be changed or repaired. Several studies have explored the idea of modeling the sign degradation level to help the authorities in effective scheduling of sign maintenance. However, previous studies utilized simpler models and proposed multiple models for different combinations of the sheeting type and color used for the traffic sign. In this study, we present a neural network based deep learning model for traffic sign retro-reflectivity prediction. Data utilized in this study was collected using a handheld retro-reflectometer GR3 from field surveys of traffic signs. Sign retro-reflective measurements (i.e., the RA values) were taken for different sign sheeting brands, grades, colors, orientation angles, observation angles, and aging periods. Feature-based sensitivity analysis was conducted to identify variables’ relative importance in determining retro-reflectivity. Results show that the sheeting color and observation angle were the most significant variables, whereas sign orientation was the least important. Considering all the features, RA prediction results obtained from one-hot encoding outperformed other models reported in the literature. The findings of this study demonstrate the feasibility and robustness of the proposed neural network based deep learning model in predicting the sign retro-reflectivity.
Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care
Authors: Karwal Nisha , Rodrigues Megan , Williams David D. , McDonough Ryan J. , Ferro Diana
Published: December 2021

Type 1 diabetes (T1D) is a complex autoimmune disease that currently cannot be cured, only managed. Optimal treatment the of T1D symptoms, requires a multidisciplinary care team, including endocrinologists, educators, primary care providers, health care specialists, genetic counselors, and data scientists. This review summarizes how an integrative approach to T1D drives innovation and quality improvements in health care. Specifically, we highlight how “-omics” technologies facilitate the understanding of different aspects of the disease, including prevention, pathogenesis, diagnostics, and treatment. Furthermore, we explore how biological data can be combined with personal and electronic health records to tailor medical interventions to the individual’s biology and lifestyle. We conclude that truly personalized medicine will not be limited to one data source but will emerge from the integration of multiple sources and disciplines that together will support individuals with T1D in their everyday life.
Integrative Assessment of Sediments Affected by CO2 Enrichment: A Case Study in the Bay of Santos—SP, Brazil
Authors: Passarelli Marina Cunha , Bonnail Estefanía , Cesar Augusto , DelValls T. Ángel , Riba Inmaculada
Published: December 2021

CO2 enrichment in the marine environment caused by leakages from carbon capture and storage technologies may occur over operational procedures. An integrated approach using weight-of-evidence was applied to assess the environmental risk associated with the acidification caused by CO2 enrichment in coastal sediments from Santos (Brazil). Chemical analyses (metal(loid)s and organic contaminant (e.g., hydrocarbons), toxicity tests (amphipods mortality, sea-urchin embryo-larval development) and macro-benthic community structure alteration assessment were performed with different acidified scenarios (pH 8.0–6.0) for two stations with different contamination degrees. These lines of evidence were statistically analyzed and integrated (multivariate analysis and ANOVA). Results of toxicity showed significant chronic effects starting at pH 7.0 while acute effects were observed starting at pH 6.5. The macro-benthic community integrity showed significant differences for all treatments at the Piaçaguera channel station, considered to be moderately contaminated. Results from the multivariate analysis correlated toxic effects and increase in the mobility of some elements with acidification. Also, the biological indexes were correlated with concentrations of dissolved Zn in seawater. The pH of 6.0 was extremely toxic for marine life due to its high acidification and metal bioavailability. The approach herein identified and discriminated the origin of the degradation caused by the acidification related to the enrichment of CO2.
Characteristics of Collimators Based on the Large-Mode-Area CMCF for Coupling Laser Beam
Authors: Zhang Xuran , Liang Xiao , Bai Zhenxu , Liu Shuo , Geng Zhaoxin , Yin Tianhe
Published: December 2021

A new collimator based on a homemade concentric multilayer-core fiber (CMCF) is proposed and experimentally demonstrated. This collimator was fabricated using a tail fiber with large mode area and single-mode operation. By exploiting the optical transmission matrix, the propagation characteristic and coupling mechanism of this CMCF-based collimator was introduced meticulously. The coupling losses of the laser beam using this collimator in the off-axis, angular, and axial deviations were analyzed separately. In order to determine the relationship between the geometric redundancy of this collimator and the effective mode field area of the tail fiber, the corresponding mathematical model was established. Through model calculation and experiment measurement, the coupling properties of the collimator were improved effectively. Compared with the common SMF-based collimator, the declination redundancy of the CMCF-based one improved by 20%, which could make the coupling of the optical fiber collimator easier. Therefore, this collimator has potential application value in the laser diode coupling unit and high-speed optical communication system.
Feasibility of Optical Flow Field Measurements of the Coolant in a Grinding Machine
Authors: Espenhahn Björn , Schumski Lukas , Vanselow Christoph , Stöbener Dirk , Meyer Daniel , Fischer Andreas
Published: December 2021

For industrial grinding processes, the workpiece cooling by metalworking fluids, which strongly influences the workpiece surface layer quality, is not yet fully understood. This leads to high efforts for the empirical determination of suitable cooling parameters, increasing the part manufacturing costs. To close the knowledge gap, a measurement method for the metalworking fluid flow field near the grinding wheel is desired. However, the varying curved surfaces of the liquid phase result in unpredictable light deflections and reflections, which impede optical flow measurements. In order to investigate the yet unknown optical measurement capabilities achievable under these conditions, shadowgraphy in combination with a pattern correlation technique and particle image velocimetry (PIV) are applied in a grinding machine. The results show that particle image velocimetry enables flow field measurements inside the laminar metalworking fluid jet, whereby the shadowgraph imaging velocimetry complements these measurements since it is in particular suitable for regions with spray-like flow regimes. As a conclusion, optical flow field measurements of the metalworking fluid flow in a running grinding machine are shown to be feasible.
Study of the Phenolic Compound Profile of Arbutus unedo L. Fruits at Different Ripening Stages by HPLC-TQ-MS/MS
Authors: Izcara Sergio , Morante-Zarcero Sonia , Casado Natalia , Sierra Isabel
Published: December 2021

Arbutus unedo L. berries have traditionally been used as edible and medicinal fruits in folk medicine for the treatment of some pathologies. Besides their good nutritional properties, these berries are rich in bioactive compounds. Accordingly, a HPLC-triple quadrupole (TQ)-MS/MS method was developed and validated for the first time to characterize the changes produced in the phenolic composition profile of A. unedo L. fruits through three ripening stages. Several hydroxycinnamic and hydroxybenzoic acids were detected, gallic acid being the highest phenolic acid quantified. Quercetin, quercetin-3-β-glucoside, rutin, and kaempferol were found in similar amounts at the different maturity stages. High amounts of (+)-catechin, procyanidin B2, epigallocatechin, and (−)-epigallocatechin gallate were observed in the unripe fruits. Naringin and vitexin were also quantified. Stilbenes, such as trans-resveratrol and trans-piceid, were identified for the first time in these fruits. Total phenolic compounds, total anthocyanin compounds, and radical scavenging activity were also determined in the fruits harvested at different years in several locations of the Iberian Peninsula at different ripening stages. The results confirmed that these fruits are an excellent source of these bioactive compounds (mainly flavanols) with high antioxidant activity, which could be used as a new source for preparation of nutraceutical or functional foods.
Accurate Measurements of Forest Soil Water Content Using FDR Sensors Require Empirical In Situ (Re)Calibration
Authors: De Vos Bruno , Cools Nathalie , Verstraeten Arne , Neirynck Johan
Published: December 2021

Monitoring volumetric soil water content (θv) is the key for assessing water availability and nutrient fluxes. This study evaluated the empirical accuracy of θv measurements using standard and in situ calibrated frequency domain reflectometers (FDR) with gravimetric water content and bulk density measurements of 1512 samples gathered from 15 profiles across 5 ICP Forests level II intensive monitoring plots. The predicted θv, calibrated with standard functions, predominantly underestimated the real water content. The measurement error exceeded the threshold of 0.03 m3 m−3 in 93% of all soil layers. Layer specific calibration removed bias and reduced the overall prediction error with a factor up to 2.8. A simple linear regression often provided the best calibration model; temperature correction was helpful in specific cases. To adequately remove bias in our study plots, a calibration dataset of up to 24 monthly observations was required for topsoils (whereas 12 observations sufficed for subsoils). Based on estimated precision errors, 3 sensors per soil layer proved to be sufficient, while up to 16 sensors are needed to meet the required accuracy in organic topsoils. Validating FDR sensor outputs using in situ gravimetric measurements is essential for quality control and assurance of long term θv monitoring and for improving site specific instrumentalization.
A Re-Evaluation of the Swiss Hail Suppression Experiment Using Permutation Techniques Shows Enhancement of Hail Energies When Seeding
Authors: Auf der Maur Armin , Germann Urs
Published: December 2021

Grossversuch IV is a large and well documented experiment on hail suppression by silver iodide seeding. The original 1986 evaluation remained vague, although indicating a tendency to increase hail when seeding. The strategy to deal with distributions of hail energy far from normal was not optimal. The present re-evaluation sticks to the question asked and avoids both misleading transformations and unsatisfactory meteorological predictors. The raw data show an increase by about a factor of 3 for the hail energy when seeding. This is the opposite of what seeding is supposed to do. The probability to obtain such a result by chance is below 1%, calculated by permutation and bootstrap techniques applied on the raw data. Confidence intervals were approximated by bootstrapping as well as by a new method called “correlation imposed permutation” (CIP).
Improving the Near-Surface Wind Forecast around the Turpan Basin of the Northwest China by Using the WRF_TopoWind Model
Authors: Ma Hui , Ma Xiaolei , Mei Shengwei , Wang Fei , Jing Yanwei
Published: December 2021

Wind energy is a type of renewable and clean energy which has attracted more and more attention all over the world. The Northwest China is a region with the most abundant wind energy not only in China, but also in the whole world. To achieve the goal of carbon neutralization, there is an urgent need to make full use of wind energy in Northwest China and to improve the efficiency of wind power generation systems in this region. As forecast accuracy of the near-surface wind is crucial to wind-generated electricity efficiency, improving the near-surface wind forecast is of great importance. This study conducted the first test to incorporate the subgrid surface drag into the near-surface wind forecast under the complex terrain conditions over Northwest China by using two TopoWind models added by newer versions of the Weather Research and Forecasting (WRF) model. Based on three groups (each group had 28 runs) of forecasts (i.e., Control run, Test 01 and Test 02) started at 12:00 UTC of each day (ran for 48 h) during the period of 1–28 October 2020, it was shown that, overall, both TopoWind models could improve the near-surface wind speed forecasts under the complex terrain conditions over Northwest China, particularly for reducing the errors associated with the forecast of the wind-speed’s magnitude. In addition to wind forecast, the forecasts of sea level pressure and 2-m temperature were also improved. Different geographical features (wind-farm stations located south of the mountain tended to have more accurate forecast) and weather systems were found to be crucial to forecast accuracy. Good forecasts tended to appear when the simulation domain was mainly controlled by the high-pressure systems with the upper-level jet far from it.
Haze Prediction Model Using Deep Recurrent Neural Network
Authors: Shang Kailin , Chen Ziyi , Liu Zhixin , Song Lihong , Zheng Wenfeng , Yang Bo , Liu Shan , Yin Lirong
Published: December 2021

In recent years, haze pollution is frequent, which seriously affects daily life and production process. The main factors to measure the degree of smoke pollution are the concentrations of PM2.5 and PM10. Therefore, it is of great significance to study the prediction of PM2.5/PM10 concentration. Since PM2.5 and PM10 concentration data are time series, their time characteristics should be considered in their prediction. However, the traditional neural network is limited by its own structure and has some weakness in processing time related data. Recurrent neural network is a kind of network specially used for sequence data modeling, that is, the current output of the sequence is correlated with the historical output. In this paper, a haze prediction model is established based on a deep recurrent neural network. We obtained air pollution data in Chengdu from the China Air Quality Online Monitoring and Analysis Platform, and conducted experiments based on these data. The results show that the new method can predict smog more effectively and accurately, and can be used for social and economic purposes.
The Influence of Ozone on Net Ecosystem Production of a Ryegrass–Clover Mixture under Field Conditions
Authors: Agyei Thomas , Juráň Stanislav , Edwards-Jonášová Magda , Fischer Milan , Švik Marian , Komínková Kateřina , Ofori-Amanfo Kojo Kwakye , Marek Michal V. , Grace John , Urban Otmar
Published: December 2021

In order to understand the effect of phytotoxic tropospheric ozone (O3) on terrestrial vegetation, we quantified the impact of current O3 concentration ([O3]) on net ecosystem production (NEP) when compared to the conditions of the pre-industrial era. We compared and tested linear mixed-effects models based on [O3] and stomatal O3 flux (Fsto). The managed ryegrass–clover (Lolium perenne and Trifolium pratense) mixture was grown on arable land in the Czech Republic, Central Europe. Values of [O3] and Fsto were measured and calculated based on resistance analogy, respectively, while NEP was calculated from eddy covariance CO2 fluxes. We found the Fsto-based model more precise when compared to measured NEP. High Fsto was found even at low [O3], while broad summer maximum of [O3] was not necessarily followed by significant NEP decline, due to low soil water content leading to a low stomatal conductivity and Fsto. Comparing to low pre-industrial O3 conditions, current levels of O3 resulted in the reduction of cumulative NEP over the entire growing season, up to 29.7 and 13.5% when the [O3]-based and Fsto-based model was applied, respectively. During the growing season, an O3-induced reduction of NEP ranged between 13.1% in May and 26.2% in July when compared to pre-industrial Fsto levels. Looking to the future, high [O3] and Fsto may lead to the reduction of current NEP by approximately 13.3% on average during the growing season, but may increase by up to 61–86.6% in autumn, indicating further O3-induced acceleration of the senescence. These findings indicate the importance of Fsto and its inclusion into the models estimating O3 effects on terrestrial vegetation. The interaction between environmental factors and stomatal conductance is therefore discussed in detail.
Simulation of the Scalar Transport above and within the Amazon Forest Canopy
Authors: Serra-Neto Edivaldo M. , Martins Hardiney S. , Dias-Júnior Cléo Q. , Santana Raoni A. , Brondani Daiane V. , Manzi Antônio O. , de Araújo Alessandro C. , Teixeira Paulo R. , Sörgel Matthias , Mortarini Luca
Published: December 2021

The parallelized large-eddy simulation model (PALM) was used to understand better the turbulent exchanges of a passive scalar above and within a forested region located in the central Amazon. Weak (2 ms−1) and strong (6 ms−1) wind conditions were simulated. A passive scalar source was introduced to the forest floor for both simulations. The simulations reproduced the main characteristics of the turbulent flow and of the passive scalar transport between the forest and the atmosphere. Noteworthily, strong and weak wind conditions presented different turbulence structures that drove different patterns of scalar exchange both within and above the forest. These results show how passive scalar concentration is influenced by the wind speed at the canopy top. Additionally, higher wind speeds are related to stronger sweep and ejection regimes, generating more intense plumes that are able to reduce the passive scalar concentration inside the forest canopy. This work was the first that used PALM to investigate scalar transport between the Amazon rainforest and the atmosphere.
Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation
Authors: Yarce Botero Andrés , Lopez-Restrepo Santiago , Pinel Peláez Nicolás , Quintero Olga L. , Segers Arjo , Heemink Arnold W.
Published: December 2021

In this work, we present the development of a 4D-Ensemble-Variational (4DEnVar) data assimilation technique to estimate NOx top-down emissions using the regional chemical transport model LOTOS-EUROS with the NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI). The assimilation was performed for a domain in the northwest of South America centered over Colombia, and includes regions in Panama, Venezuela and Ecuador. In the 4DEnVar approach, the implementation of the linearized and adjoint model are avoided by generating an ensemble of model simulations and by using this ensemble to approximate the nonlinear model and observation operator. Emission correction parameters’ locations were defined for positions where the model simulations showed significant discrepancies with the satellite observations. Using the 4DEnVar data assimilation method, optimal emission parameters for the LOTOS-EUROS model were estimated, allowing for corrections in areas where ground observations are unavailable and the region’s emission inventories do not correctly reflect the current emissions activities. The analyzed 4DEnVar concentrations were compared with the ground measurements of one local air quality monitoring network and the data retrieved by the satellite instrument Ozone Monitoring Instrument (OMI). The assimilation had a low impact on NO2 surface concentrations reducing the Mean Fractional Bias from 0.45 to 0.32, primordially enhancing the spatial and temporal variations in the simulated NO2 fields.
Absorption and Transport Characteristics and Mechanisms of Carnosic Acid
Authors: Chen Xuexiang , Huang Meigui , Liu Dongmei , Li Yongze , Luo Qiu , Pham Katherine , Wang Minghong , Zhang Jing , Zhang Runbin , Peng Zhixi , Wu Xian
Published: December 2021

Carnosic acid (CA) is a phenolic diterpenoid mainly found in rosemary and sage. CA has been reported to possess health-beneficial effects in various experimental settings. Herein, a mouse experiment and Caco-2 single-cell model were used to understand the absorption and transport characteristics of CA. First, we determined the tissue distribution of CA in mice, following an oral gavage at a physiologically relevant dose. We found that CA was bioavailable systemically and present locally in the digestive tract, especially in the cecum and colon. Next, we thought to characterize the absorption and transport of CA in the Caco-2 cell monolayer model of the intestinal epithelial barrier. In the Caco-2 cell model, CA exhibited a moderate permeability and was subjected to a mild efflux. Moreover, the apparent permeability coefficient (Papp) of CA transported across Caco-2 cell monolayers was significantly changed when the inhibitors of specific active transporter and passive diffusion were added to cells, suggesting that the absorption and transport of CA involved both passive and active transportation. The present study is an important first step towards understanding the absorption, transport, and metabolic mechanisms of CA. This could provide the scientific basis for developing CA-containing functional foods or dietary supplements with improved bioavailability.
Size-Fractionated Filtration Combined with Molecular Methods Reveals the Size and Diversity of Picophytoplankton
Authors: Shuwang Xinze , Sun Jun , Wei Yuqiu , Guo Congcong
Published: December 2021

In this study, flow cytometry (FCM) and size-fractionated filtration, together with high-throughput molecular sequencing methods (SM), were used to investigate picophytoplankton. A particle separation filter and a higher-throughput sequencing method were used to evaluate the composition of a euphotic zone of picophytoplankton—especially picoeukaryotic phytoplankton—in the Western Pacific, and the results of flow cytometry, which is a classic way to detect picophytoplankton, were used as a standard to evaluate the reliability of the results of the SMs. Within a water column of 200 m, six water depths (5, 25, 50, 113 (DCM), 150, and 200 m) were established. In order to further study the particle size spectra of the picophytoplankton, size-fractionated filtration was used to separate water samples from each water depth into three particle size ranges: 0.2–0.6, 0.6–1.2, and 1.2–2 μm. A total of 36 (6 × 3 × 2) samples were obtained through PCR amplification of the 18S rRNA V4 hypervariable region and 16S rRNA, which were biased toward phytoplankton plastids, and then high-throughput sequencing was performed. The estimation of the picophytoplankton diameter relied on forward scattering (FSC) through FCM. The estimation of the vertical distribution and diameter of the picophytoplankton using the SM was consistent with the results with FCM; thus, we believe that the estimation of picophytoplankton composition with the SM has value as a reference, although the size-fractionated filtration seemed to cause some deviations. In addition to Prochlorococcus and Synechococcus, the SM was used to evaluate the composition of picoeukaryotic phytoplankton, which mainly included Prymnesiophycea (Haptophyta) (38.15%), Cryptophyceae (Cryptophyta) (22.36%), Dictyochophyceae (Chrysophyta) (12.22%), and Mamiellophyceae (Chlorophyta) (3.31%). In addition, the SM also detected Dinophyceae (Dinoflagellata) (11.69%) sequences and a small number of Bacillariophyceae (Diatom) (1.64%) sequences, which are generally considered to have large particle sizes. The results of the SM also showed that the picoeukaryotic phytoplankton were not evenly distributed in the euphotic layer, and the vertical distributions of the different picoeukaryotic phytoplankton were different. An analysis of correlations with environmental factors showed that temperature was the main environmental factor controlling the vertical distribution of picophytoplankton.
Steam Explosion (STEX) of Citrus × Poncirus Hybrids with Exceptional Tolerance to Candidatus Liberibacter Asiaticus (CLas) as Useful Sources of Volatiles and Other Commercial Products
Authors: Dorado Christina , Bowman Kim D. , Cameron Randall G. , Manthey John A. , Bai Jinhe , Ferguson Kyle L.
Published: December 2021

Florida citrus production has declined 75% due to Huanglongbing (HLB), a disease caused by the pathogenic bacterium Candidatus Liberibacter asiaticus (CLas). Methods to combat CLas are costly and only partially effective. The cross-compatible species Poncirus trifoliata and some of its hybrids are known to be highly tolerant to CLas, and thus can potentially serve as an alternative feedstock for many citrus products. To further investigate the commercial potential of citrus hybrids, three citrus hybrids, US-802, US-897, and US-942, were studied for their potential as feedstocks for citrus co-products using steam explosion (STEX) followed by water extraction. Up to 93% of sugars were recovered. US-897 and US-942 have similar volatile profiles to that of the commercial citrus fruit types and as much as 85% of these volatiles could be recovered. Approximately 80% of the pectic hydrocolloids present in all three hybrids could be obtained in water washes of STEX material. Of the phenolics identified, the flavanone glycosides, i.e., naringin, neohesperidin, and poncirin were the most abundant quantitatively in these hybrids. The ability to extract a large percentage of these compounds, along with their inherent values, make US-802, US-897, and US-942 potentially viable feedstock sources for citrus co-products in the current HLB-blighted environment.
Cutaneous Melanocytic Tumor with CRTC1::TRIM11 Fusion: Review of the Literature of a Potentially Novel Entity
Authors: Parra Ourania , Linos Konstantinos
Published: December 2021

“Cutaneous melanocytic tumor with CRTC1::TRIM11 fusion” (CMTCT) is a recently described entity belonging to the family of superficial tumors displaying melanocytic differentiation. Thirteen cases have been reported so far, on the head and neck, extremities, and trunk of adults of all ages (12 cases) and one in an 11-year-old child. Histopathologically, it is a nodular or multilobulated tumor composed of spindle and epithelioid cells arranged in nests, fascicles, or bundles that are surrounded by thin collagenous septa. By immunohistochemistry, the tumor shows variable immunoreactivity for S100-protein, SOX10, and MITF, as well as specific melanocytic markers such as MelanA and HMB-45. The neoplasm’s biologic behavior remains uncertain since the reported cases are limited and the follow-up is short (median 12 months). However, local recurrence and synchronous distant metastasis after 13 years of initial resection has been described in one case. Herein, we present a comprehensive literature review of CMTCT hoping to raise awareness among the dermatopathologists of this potentially novel entity.
Matching Biomedical Ontologies through Adaptive Multi-Modal Multi-Objective Evolutionary Algorithm
Authors: Xue Xingsi , Tsai Pei-Wei , Zhuang Yucheng
Published: December 2021

To integrate massive amounts of heterogeneous biomedical data in biomedical ontologies and to provide more options for clinical diagnosis, this work proposes an adaptive Multi-modal Multi-Objective Evolutionary Algorithm (aMMOEA) to match two heterogeneous biomedical ontologies by finding the semantically identical concepts. In particular, we first propose two evaluation metrics on the alignment’s quality, which calculate the alignment’s statistical and its logical features, i.e., its f-measure and its conservativity. On this basis, we build a novel multi-objective optimization model for the biomedical ontology matching problem. By analyzing the essence of this problem, we point out that it is a large-scale Multi-modal Multi-objective Optimization Problem (MMOP) with sparse Pareto optimal solutions. Then, we propose a problem-specific aMMOEA to solve this problem, which uses the Guiding Matrix (GM) to adaptively guide the algorithm’s convergence and diversity in both objective and decision spaces. The experiment uses Ontology Alignment Evaluation Initiative (OAEI)’s biomedical tracks to test aMMOEA’s performance, and comparisons with two state-of-the-art MOEA-based matching techniques and OAEI’s participants show that aMMOEA is able to effectively determine diverse solutions for decision makers.
Metabolic Response of Aphid Cinara tujafilina to Cold Stress
Authors: Durak Roma , Durak Tomasz
Published: December 2021

Climate changes enable thermophilic insect species to expand their ranges, but also force them to adapt to unfavourable environmental conditions in new habitats. Focusing on Cinara tujafilina, we investigated the metabolic changes in the body of the aphid that enabled it to survive the low temperatures of winter. Using GC–MS analysis, differences in the chemical composition of the aphids in summer and winter were found. The metabolic changes were mainly related to the increased activity of the pathways of carbohydrate metabolism, such as glycolysis and the pentose phosphate pathway; a decrease in tricarboxylic acid cycle (TCA); accumulation of polyols; and increased levels of proline, tyrosine, and fatty acids.
Species and Fatty Acid Diversity of Desmodesmus (Chlorophyta) in a Local Japanese Area and Identification of New Docosahexaenoic Acid-Producing Species
Authors: Demura Mikihide , Noma Seiji , Hayashi Nobuyuki
Published: December 2021

Desmodesmus is a green microalgal genus that is frequently found in aquatic environments. Its high biomass productivity and potential as a source of lipids have attracted considerable attention. Although Desmodesmus is ubiquitous, it is difficult to identify; even within a small area, the diversity of the species and the fatty acids they produce are unknown. In this study, we performed scanning electron microscopy (SEM) and analyzed the genetic diversity of the internal transcribed spacer (ITS) region to accurately identify Desmodesmus in a local area of Japan (Saga City, Saga Pref.) and to assess its existence as a biological resource. In addition, we analyzed the fatty acid composition and content of the newly established strains. In total, 10 new strains were established, and 9 previously described species were identified. The presence of a cosmopolitan species indicated the global distribution of Desmodesmus. However, only regional species were found. One strain, dSgDes-b, did not form a clear clade with any described species in the phylogenetic analysis and had a characteristic ITS2 secondary structure. The cell wall of this strain exhibited a distinctive microstructure, and it produced docosahexaenoic acid (DHA); hence, the strain was described as a new species, Desmodesmus dohacommunis Demura sp. nov. Thus, useful information regarding the use of Desmodesmus as a bioresource was provided.
High Flow in the Storm. Early Administration of High-Flow Nasal Cannula in Patients with Severe Acute Hypoxic Respiratory Failure Due to Clinically Suspected COVID-19
Authors: Jimeno Sara , Gómez Máximo , Ventura Paula Sol , Calle Ángeles , Núñez Elena , Castellano José María , López-Escobar Alejandro
Published: December 2021

Background: The worldwide COVID-19 pandemic has created a shortage of ICU beds and ventilators. The objective was to assess whether administration of high-flow nasal cannula (HFNC) in patients with acute hypoxic respiratory failure due to COVID-19 averted mechanical ventilation (MV). Methods: Prospective observational study performed at Hospital Universitario HM Puerta del Sur (Madrid). The protocol included early administration of HFNC in clinically suspected COVID-19 patients with progressive desaturation. Results: Twenty patients were started on respiratory support with HFNC. Hospital admission took place after a median of 7 days since symptom onset and clinical deterioration was apparent at 9 days after symptom onset. Anti-inflammatory treatment with methylprednisolone and tocilizumab was initiated at 9 days (6.5–12), followed by HFNC at 9.5 days (7–12). HFNC was maintained for an average of 4.5 days (2.8–6.3), was successful in eighteen patients (90%), as defined by not needing invasive MV, and failed in two cases (10%) resulting in death. Since HFNC was implemented, there has been a decrease in the number of patients admitted to the ICU and treated with MV for acute hypoxic respiratory failure. Conclusions: HFNC administration may represent a viable therapeutic option for patients in the early stages of severe respiratory failure due to clinically suspected COVID-19.
Current Overview on Therapeutic Potential of Vitamin D in Inflammatory Lung Diseases
Authors: Afzal Muhammad , Kazmi Imran , Al-Abbasi Fahad A. , Alshehri Sultan , Ghoneim Mohammed M. , Imam Syed Sarim , Nadeem Muhammad Shahid , Al-Zahrani Maryam Hassan , Alzarea Sami I. , Alquraini Ali
Published: December 2021

Inflammatory lung disorders (ILDs) are one of the world’s major reasons for fatalities and sickness, impacting millions of individuals of all ages and constituting a severe and pervasive health hazard. Asthma, lung cancer, bronchiectasis, pulmonary fibrosis acute respiratory distress syndrome, and COPD all include inflammation as a significant component. Microbe invasions, as well as the damage and even death of host cells, can cause and sustain inflammation. To counteract the negative consequences of irritants, the airways are equipped with cellular and host defense immunological systems that block the cellular entrance of these irritants or eliminate them from airway regions by triggering the immune system. Failure to activate the host defense system will trigger chronic inflammatory cataracts, leading to permanent lung damage. This damage makes the lungs more susceptible to various respiratory diseases. There are certain restrictions of the available therapy for lung illnesses. Vitamins are nutritional molecules that are required for optimal health but are not produced by the human body. Cholecalciferol (Vitamin D) is classified as a vitamin, although it is a hormone. Vitamin D is thought to perform a function in bone and calcium homeostasis. Recent research has found that vitamin D can perform a variety of cellular processes, including cellular proliferation; differentiation; wound repair; healing; and regulatory systems, such as the immune response, immunological, and inflammation. The actions of vitamin D on inflammatory cells are dissected in this review, as well as their clinical significance in respiratory illnesses.
Alternative Splicing in Myeloid Malignancies
Authors: Gurnari Carmelo , Pagliuca Simona , Visconte Valeria
Published: December 2021

Alternative RNA splicing (AS) is an essential physiologic function that diversifies the human proteome. AS also has a crucial role during cellular development. In fact, perturbations in RNA-splicing have been implicated in the development of several cancers, including myeloid malignancies. Splicing dysfunction can be independent of genetic lesions or appear as a direct consequence of mutations in components of the RNA-splicing machinery, such as in the case of mutations occurring in splicing factor genes (i.e., SF3B1, SRSF2, U2AF1) and their regulators. In addition, cancer cells exhibit marked gene expression alterations, including different usage of AS isoforms, possibly causing tissue-specific effects and perturbations of downstream pathways. This review summarizes several modalities leading to splicing diversity in myeloid malignancies.
Activation of PPARα by Fenofibrate Attenuates the Effect of Local Heart High Dose Irradiation on the Mouse Cardiac Proteome
Authors: Azimzadeh Omid , Subramanian Vikram , Sievert Wolfgang , Merl-Pham Juliane , Oleksenko Kateryna , Rosemann Michael , Multhoff Gabriele , Atkinson Michael J. , Tapio Soile
Published: December 2021

Radiation-induced cardiovascular disease is associated with metabolic remodeling in the heart, mainly due to the inactivation of the transcription factor peroxisome proliferator-activated receptor alpha (PPARα), thereby inhibiting lipid metabolic enzymes. The objective of the present study was to investigate the potential protective effect of fenofibrate, a known agonist of PPARα on radiation-induced cardiac toxicity. To this end, we compared, for the first time, the cardiac proteome of fenofibrate- and placebo-treated mice 20 weeks after local heart irradiation (16 Gy) using label-free proteomics. The observations were further validated using immunoblotting, enzyme activity assays, and ELISA. The analysis showed that fenofibrate restored signalling pathways that were negatively affected by irradiation, including lipid metabolism, mitochondrial respiratory chain, redox response, tissue homeostasis, endothelial NO signalling and the inflammatory status. The results presented here indicate that PPARα activation by fenofibrate attenuates the cardiac proteome alterations induced by irradiation. These findings suggest a potential benefit of fenofibrate administration in the prevention of cardiovascular diseases, following radiation exposure.
Profiling of Plasma Extracellular Vesicle Transcriptome Reveals That circRNAs Are Prevalent and Differ between Multiple Sclerosis Patients and Healthy Controls
Authors: Iparraguirre Leire , Alberro Ainhoa , Hansen Thomas B. , Castillo-Triviño Tamara , Muñoz-Culla Maider , Otaegui David
Published: December 2021

(1) Background: Extracellular vesicles (EVs) are released by most cell types and are implicated in several biological and pathological processes, including multiple sclerosis (MS). Differences in the number and cargo of plasma-derived EVs have been described in MS. In this work, we have characterised the EV RNA cargo of MS patients, with particular attention to circular RNAs (circRNAs), which have attracted increasing attention for their roles in physiology and disease and their biomarker potential. (2) Methods: Plasma-derived EVs were isolated by differential centrifugation (20 patients, 8 controls), and RNA-Sequencing was used to identify differentially expressed linear and circRNAs. (3) Results: We found differences in the RNA type distribution, circRNAs being enriched in EVs vs. leucocytes. We found a number of (corrected p-value < 0.05) circRNA significantly DE between the groups. Nevertheless, highly structured circRNAs are preferentially retained in leukocytes. Differential expression analysis reports significant differences in circRNA and linear RNA expression between MS patients and controls, as well as between different MS types. (4) Conclusions: Plasma derived EV RNA cargo is not a representation of leukocytes’ cytoplasm but a message worth studying. Moreover, our results reveal the interest of circRNAs as part of this message, highlighting the importance of further understanding RNA regulation in MS.