bluuebunny/crossref_metadata_2025 huggingface dataset:
Active Buildings Based on Passivhaus Standard to Reduce the Energy Deficit of Regional Electric Network: Proposal Analysis
Authors: López-Leyva Josué Aarón , Barrera-Silva Carolina , Sarmiento-Leyva Luisa Fernanda , González-Romero María Fernanda
Published: September 2021

This manuscript presents the analysis of a real distributed generation network considering the integration of Active Buildings that meet the Passivhaus standard criteria at the Premium level, as a base case model. The novelty aspect presented in this paper is the interconnection of Active Buildings based on the Passivhaus standard at the Premium level with the National Electricity System (particularly, in Mexico’s North Baja California region) to mitigate the energy deficit. The objective of the proposal grid is to reduce the energy deficit (≈600 MW) due to the high energy demand in the region and the reduced energy generation through conventional and renewable energy sources. In a particular way, the energy rehabilitation of some buildings was analyzed with the aim of reducing the energy demand of each one and then adding energy generation through renewable sources. As a result, all Passivhaus standard criteria (i.e., heating and cooling demands, heating and cooling loads, among others) were met. Regarding the Active Buildings performance in each distributed generation circuit, an overall installed power capacity of ≈2.3 MW was obtained, which corresponds to ≈19.1% of the maximum capacity, and ≈34.30% of the recommended integration capacity. In addition, adequate results were obtained related to the import and export of energy between distributed generation circuits, i.e., the energy exchange is up to ≈106.8 kW, intending to reduce the energy contribution of the utility electrical network. Finally, the analysis of the Active Buildings showed an increase in the net generation forecast, up to ≈2.25 MW.
IQ-Data-Based WiFi Signal Classification Algorithm Using the Choi-Williams and Margenau-Hill-Spectrogram Features: A Case in Human Activity Recognition
Authors: Lin Yier , Yang Fan
Published: September 2021

This paper presents a novel approach that applies WiFi-based IQ data and time–frequency images to classify human activities automatically and accurately. The proposed strategy first uses the Choi–Williams distribution transform and the Margenau–Hill spectrogram transform to obtain the time–frequency images, followed by the offset and principal component analysis (PCA) feature extraction. The offset features were extracted from the IQ data and several spectra with maximum energy values in the time domain, and the PCA features were extracted via the whole images and several image slices on them with rich unit information. Finally, a traditional supervised learning classifier was used to label various activities. With twelve-thousand experimental samples from four categories of WiFi signals, the experimental data validated our proposed method. The results showed that our method was more robust to varying image slices or PCA numbers over the measured dataset. Our method with the random forest (RF) classifier surpassed the method with alternative classifiers on classification performance and finally obtained a 91.78% average sensitivity, 91.74% average precision, 91.73% average F1-score, 97.26% average specificity, and 95.89% average accuracy.
6D Pose Estimation for Subsea Intervention in Turbid Waters
Authors: Mohammed Ahmed , Kvam Johannes , T. Thielemann Jens , Haugholt Karl H. , Risholm Petter
Published: September 2021

Manipulation tasks on subsea instalments require extremely precise detection and localization of objects of interest. This problem is referred to as “pose estimation”. In this work, we present a framework for detecting and predicting 6DoF pose for relevant objects (fish-tail, gauges, and valves) on a subsea panel under varying water turbidity. A deep learning model that takes 3D vision data as an input is developed, providing a more robust 6D pose estimate. Compared to the 2D vision deep learning model, the proposed method reduces rotation and translation prediction error by (−Δ0.39∘) and translation (−Δ6.5 mm), respectively, in high turbid waters. The proposed approach is able to provide object detection as well as 6D pose estimation with an average precision of 91%. The 6D pose estimation results show 2.59∘ and 6.49 cm total average deviation in rotation and translation as compared to the ground truth data on varying unseen turbidity levels. Furthermore, our approach runs at over 16 frames per second and does not require pose refinement steps. Finally, to facilitate the training of such model we also collected and automatically annotated a new underwater 6D pose estimation dataset spanning seven levels of turbidity.
Korean Prosody Phrase Boundary Prediction Model for Speech Synthesis Service in Smart Healthcare
Authors: Kim Minho , Jung Youngim , Kwon Hyuk-Chul
Published: September 2021

Speech processing technology has great potential in the medical field to provide beneficial solutions for both patients and doctors. Speech interfaces, represented by speech synthesis and speech recognition, can be used to transcribe medical documents, control medical devices, correct speech and hearing impairments, and assist the visually impaired. However, it is essential to predict prosody phrase boundaries for accurate natural speech synthesis. This study proposes a method to build a reliable learning corpus to train prosody boundary prediction models based on deep learning. In addition, we offer a way to generate a rule-based model that can predict the prosody boundary from the constructed corpus and use the result to train a deep learning-based model. As a result, we have built a coherent corpus, even though many workers have participated in its development. The estimated pairwise agreement of corpus annotations is between 0.7477 and 0.7916 and kappa coefficient (K) between 0.7057 and 0.7569. In addition, the deep learning-based model based on the rules obtained from the corpus showed a prediction accuracy of 78.57% for the three-level prosody phrase boundary, 87.33% for the two-level prosody phrase boundary.
Enhanced TVI for Grid Forming VSC under Unbalanced Faults
Authors: Zubiaga Markel , Cardozo Carmen , Prevost Thibault , Sanchez-Ruiz Alain , Olea Eneko , Izurza Pedro , Khan Siam Hasan , Arza Joseba
Published: September 2021

With an increasing capacity of inverter-based generation and with a 100% renewable energy power system on the horizon, grid forming converters have the potential to become the prevalent control mode in the grid. Thus, the correct performance of these devices is going to be crucial for system stability and security of supply. Most research related to the grid-forming control is focused on normal operating conditions, although significant effort has been devoted to current limitation strategies to ensure Low Voltage Ride Through (LVRT) capability. However, most contributions usually consider only balanced faults. This paper, proposes a new current limiting method based on the well-known threshold virtual impedance (TVI) that keeps the voltage source behaviour associated to the grid forming (GFM) capability, even when the current limit is reached, while reducing the voltage unbalance according to user-defined settings.
Analysis of the Influence of the Type of Belt on the Energy Consumption of Transport Processes in a Belt Conveyor
Authors: Bajda Mirosław , Hardygóra Monika
Published: September 2021

Results of tests into the energy-efficiency of belt conveyor transportation systems indicate that the energy consumption of their drive mechanisms can be limited by lowering the main resistances in the conveyor. The main component of these resistances is represented by belt indentation rolling resistance. Limiting its value will allow a reduction in the amount of energy consumed by the drive mechanisms. This article presents a test rig which enables uncomplicated evaluations of such rolling resistances. It also presents the results of comparative tests performed for five steel-cord conveyor belts. The tests involved a standard belt, a refurbished belt and three energy-saving belts. As temperature significantly influences the values of belt indentation rolling resistance, the tests were performed in both positive and negative temperatures. The results indicate that when compared with the standard belt, the refurbished and the energy-efficient belts generate higher and lower indentation rolling resistances, respectively. In order to demonstrate practical advantages resulting from the use of energy-saving belts, this article also includes calculations of the power demand of a conveyor drive mechanism during one calendar year, as measured on a belt conveyor operated in a mine. The replacement of a standard belt with a refurbished belt generates a power demand higher by 4.8%, and with an energy-efficient belt—lower by 15.3%.
Numerical Investigation on a Axial Slot Casing Treatment of a Large Circumferential Interval and Small Opening Area
Authors: Liu Zepeng , Huang Guoping , Musa Omer
Published: September 2021

Axial slot casing treatment is a common method to extend the stall margin of a compressor. Based on the mechanism of unsteady flow control, this paper redesigns axial slots with large circumferential interval and small opening area. To test the effect of this axial slot structure, unsteady numerical simulations were carried out with different slot areas and circumferential intervals. The results show that this novel axial slot casing treatment can significantly improve compressor stall margin. Meanwhile, compared with the traditional axial slot, the efficiency loss is greatly reduced. The flow field analysis shows that the new axial slot structure proposed in this paper can suppress the development of tip leakage vortex and unsteadiness in the tip region at the near stall condition through decreasing the tip loading periodically. Moreover, we find that the slot area is proportional to the improvement of stability margin. Under the same slot area, an excessive number of slots is not conducive to the improvement of the stability margin.
Toward the Renewal of the Sustainable Urban Indicators’ System after a Global Health Crisis. Practical Application in Granada, Spain
Authors: Mercader-Moyano Pilar , Estable-Reifs Ana Mª , Pellicer Homero
Published: September 2021

The aim of this study is to highlight the need for sustainable urban development by reviewing the different Indicator Systems (SI) and contrasting them with those factors that have had a correlation in the spread of the virus in order to detect its deficiencies. This research carries out an urban diagnosis and analyzes the influence of these factors in order to detect deficiencies and propose a new IS adapted to current needs. Lastly, the new SI is validated through its practical application in one of the Autonomous Communities most affected by the pandemic in Spain. It is concluded that most of the factors causing a worse incidence of the virus are hardly evaluated by the existing IS. The practical analysis shows that there are deficiencies in urban design, resulting in poor environmental quality and urban morphology.
An Explicit Finite Element Method for Thermal Simulations of Buildings with Phase Change Materials
Authors: Zhou Hongxia , Fransson Åke , Olofsson Thomas
Published: September 2021

The thermal performance of building envelopes is essential for building thermal comfort and the reduction of building energy requirements. Phase change materials (PCMs) implemented in building envelopes can improve thermal performance. An explicit finite element method (ex-FEM) has been developed based on a previous study to investigate the heat transfer performance through building walls with installed PCMs. For verification, we introduce an electrical circuit analogy (ECA) method. For model validation, at first, COMSOL is used. For comparison, data were collected from experiments using a small hotbox, part of the sides are covered by PCMs with different configurations. This work shows how the ex-FEM model can predict the wall’s temperature profile with and without incorporated PCM. With the implementation of PCMs, the work problematizes unpredictable influences for modeling. In addition, the study introduces results from simulations of sequencing of PCM layers in wall construction.
Impacts of Extreme Ambient Temperatures and Road Gradient on Energy Consumption and CO2 Emissions of a Euro 6d-Temp Gasoline Vehicle
Authors: Giechaskiel Barouch , Komnos Dimitrios , Fontaras Georgios
Published: September 2021

The EU aims to substantially reduce its greenhouse gas emissions in the following decades and achieve climate neutrality by 2050. Better CO2 estimates, particularly in urban conditions, are necessary for assessing the effectiveness of various regional policy strategies. In this study, we measured the CO2 emissions of a Euro 6d-temp gasoline direct injection (GDI) vehicle with a three-way catalyst (TWC) and a gasoline particulate filter (GPF) at ambient temperatures from −30 °C up to 50 °C with the air-conditioning on. The tests took place both on the road and in the laboratory, over cycles simulating congested urban traffic, dynamic driving, and uphill driving towing a trailer at 85% of the maximum payloads of both the car and the trailer. The CO2 values varied over a wide range depending on the temperature and driving conditions. Vehicle simulation was used to quantify the effect of ambient temperature, vehicle weight and road grade on the CO2 emissions. The results showed that vehicle energy demand was significantly increased under the test conditions. In urban trips, compared to the baseline at 23 °C, the CO2 emissions were 9–20% higher at −10 °C, 30–44% higher at −30 °C, and 37–43% higher at 50 °C. Uphill driving with a trailer had 2–3 times higher CO2 emissions. In motorway trips at 50 °C, CO2 emissions increased by 13–19%. The results of this study can help in better quantification of CO2 and fuel consumption under extreme conditions. Additional analysis on the occurrence of such conditions in real-world operation is advisable.
The Temporal Variation of the Microclimate and Human Thermal Comfort in Urban Wetland Parks: A Case Study of Xixi National Wetland Park, China
Authors: Zhang Zhiyong , Dong Jianhua , He Qijiang , Ye Bing
Published: September 2021

As an important part of the ecological infrastructure in urban areas, urban wetland parks have the significant ecological function of relieving the discomfort of people during their outdoor activities. In recent years, the specific structures and ecosystem services of urban wetland parks have been investigated from different perspectives. However, the microclimate and human thermal comfort (HTC) of urban wetland parks have rarely been discussed. In particular, the changing trends of HTC in different seasons and times have not been effectively presented. Accordingly, in this research, a monitoring platform was established in Xixi National Wetland Park, China, to continually monitor its microclimate in the long term. Via a comparison with a control site in the downtown area of Hangzhou, China, the temporal variations of the microclimate and HTC in the urban wetland park are quantified, and suggestions for clothing are also provided. The results of this study demonstrate that urban wetland parks can mitigate the heat island effect and dry island effect in summer. In addition, urban wetland parks can provide ecological services at midday during winter to mitigate the cold island effect. More importantly, urban wetland parks are found to exhibit their best performance in improving HTC during the daytime of the hot season and the midday period of the cold season. Finally, the findings of this study suggest that citizens should take protective measures and enjoy their activities in the morning, evening, or at night, not at midday in hot weather. Moreover, extra layers are suggested to be worn before going to urban wetland parks at night in cold weather, and recreational activities involving accommodation are not recommended. These findings provide not only basic scientific data for the assessment of the management and ecological health value of Xixi National Wetland Park and other urban wetland parks with subtropical monsoon climates, but also a reference for visitor timing and clothing suggestions for recreational activities.
Fine-Scale NDVI Reconstruction Back to 1906 from Tree-Rings in the Greater Yellowstone Ecosystem
Authors: Li Hang , Thapa Ichchha , Speer James H.
Published: September 2021

Global warming and related disturbances, such as drought, water, and heat stress, are causing forest decline resulting in regime shifts. Conventional studies have combined tree-ring width (TRW) and the normalized difference vegetation index (NDVI) to reconstruct NDVI values and ignored the influences of mixed land covers. We built an integrated TRW-NDVI model and reconstructed the annual NDVI maps by using 622 Landsat satellite images and tree cores from 15 plots using point-by-point regression. Our model performed well in the study area, as demonstrated by significant reconstructions for 71.14% (p < 0.05) of the area with the exclusion of water and barren areas. The error rate between the reconstructed NDVI using the conventional approach and our approach could reach 10.36%. The 30 m resolution reconstructed NDVI images in the recent 100 years clearly displayed a decrease in vegetation density and detected decades-long regime shifts from 1906 to 2015. Our study site experienced five regime shifts, markedly the 1930s and 1950s, which were megadroughts across North America. With fine resolution maps, regime shifts could be observed annually at the centennial scale. They can also be used to understand how the Yellowstone ecosystem has gradually changed with its ecological legacies in the last century.
Rhodaneses Enzyme Addition Could Reduce Cyanide Concentration and Enhance Fiber Digestibility via In Vitro Fermentation Study
Authors: Supapong Chanadol , Cherdthong Anusorn
Published: September 2021

The use of cyanide-containing feed (HCN) is restricted because it causes prussic acid poisoning in animals. The objective of this study was to see how adding rhodanese enzyme to an HCN-containing diet affected gas dynamics, in vitro ruminal fermentation, HCN concentration reduction, and nutrient digestibility. A 3 × 4 factorial arrangement in a completely randomized design was used for the experiment. Factor A was the three levels of potassium cyanide (KCN) at 300, 450, and 600 ppm. Factor B was the four doses of rhodanese enzyme at 0, 0.65, 1, and 1.35 mg/104 ppm KCN, respectively. At 96 h of incubation, gas production from an insoluble fraction (b), potential extent (omit gas) (a + b), and cumulative gas were similar between KCN additions of 300 to 450 ppm (p > 0.05), whereas increasing KCN to 600 ppm significantly decreased those kinetics of gas (p < 0.05). Supplementation of rhodanese enzymes at 1.0 to 1.35 mg/104 ppm KCN enhanced cumulative gas when compared to the control group (p < 0.05). Increasing the dose of rhodanese up to 1.0 mg/104 ppm KCN significantly increased the rate of ruminal HCN degradation efficiency (DE) by 70% (p < 0.05). However, no further between the two factors was detected on ruminal fermentation and in vitro digestibility (p > 0.05). The concentration of ammonia-nitrogen (NH3-N) increased with increasing doses of KCN (p < 0.05), but remained unchanged with varying levels of rhodanese enzymes (p > 0.05). The in vitro dry matter digestibility (IVDMD) was suppressed when increasing doses of KCH were administered at 600 ppm, whereas supplementation of rhodanese enzymes at 1.0–1.35 mg/104 ppm KCN enhanced IVDMD (p < 0.05). Increasing doses of KCN affected reduced total volatile fatty acids (TVFA) concentration, which was lowest when 600 ppm was added (p < 0.05). Nevertheless, the concentration of TVFAs increased when rhodanese enzymes were included by 1.0–1.35 mg/104 ppm KCN (p < 0.05). Based on this study, it could be concluded that supplementation of rhodaneses enzyme at 1.0–1.35 mg/104 ppm KCN could enhance cumulative gas, digestibility, and TVAF, as well as lowering ruminal HCN concentration.
Optimization of Fermentation Conditions for Production of Hungarian Sour Cherry Spirit Using Response Surface Methodology
Authors: Pham Tuan M. , Sun Weizhe , Bujna Erika , Hoschke Ágoston , Friedrich László , Nguyen Quang D.
Published: September 2021

Pálinka is a traditional fruit spirit and a kind of gastronomic heritage in Hungary. In Pálinka production, fermentation is one of the most important processes affecting the quality and yield of spirits. Based on single-factor and three-factor influence level tests by following the Plackett–Burman design, the fermentation process from sour cherry juice concentrate and Saccharomyces cerevisiae by using Response Surface Methodology (RSM) coupled with the central composite rotatable design was investigated to optimize fermentation conditions through three variables in a defined range of temperature (15–25 °C), pH (2.75–3.75), and total soluble solid (18–30 °Brix). After eight fermentation days, production yields of alcohol and volatile compounds were a maximum of 9.02% v/v and 337.37 mg/L at an optimized temperature of 24.71 °C, pH of 3.25, and total soluble solid of 22.49 °Brix. The GC-FID analysis results showed 1-propanol, 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, and ethyl acetate were considered the major aroma compound in the cherry spirits. These results provided important information in serving the basic to develop standard fruit spirits production from sour cherry.
Emotion Recognition in Horses with Convolutional Neural Networks
Authors: Corujo Luis A. , Kieson Emily , Schloesser Timo , Gloor Peter A.
Published: September 2021

Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a “proof of concept” system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to test the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through the head, neck, ear, muzzle, and eye position. The system showed an accuracy of 80% on the validation set and 65% on the test set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.
Fine-Scale Population Estimation Based on Building Classifications: A Case Study in Wuhan
Authors: Wang Shunli , Li Rui , Jiang Jie , Meng Yao
Published: September 2021

In the context of rapid urbanization, the refined management of cities is facing higher requirements. In improving urban population management levels and the scientific allocation of resources, fine-scale population data plays an increasingly important role. The current population estimation studies mainly focus on low spatial resolution, such as city-scale and county scale, without considering differences in population distributions within cities. This paper mines and defines the spatial correlations of multi-source data, including urban building data, point of interest (POI) data, census data, and administrative division data. With populations mainly distributed in residential buildings, a population estimation model at a subdistrict scale is established based on building classifications. Composed of spatial information and attribute information, POI data are spaced irregularly. Based on this characteristic, the text classification method, frequency-inverse document frequency (TF-IDF), is applied to obtain functional classifications of buildings. Then we screen out residential buildings, and quantify characteristic variables in subdistricts, including perimeter, area, and total number of floors in residential buildings. To assess the validity of the variables, the random forest method is selected for variable screening and correlation analysis, because this method has clear advantages when dealing with unbalanced data. Under the assumption of linearity, multiple regression analysis is conducted, to obtain a linear model of the number of buildings, their geometric characteristics, and the population in each administrative division. Experiments showed that the urban fine-scale population estimation model established in this study can estimate the population at a subdistrict scale with high accuracy. This method improves the precision and automation of urban population estimation. It allows the accurate estimation of the population at a subdistrict scale, thereby providing important data to support the overall planning of regional energy resource allocation, economic development, social governance, and environmental protection.
Smart Cities in Russia: Current Situation and Insights for Future Development
Authors: Yuloskov Artem , Bahrami Mohammad Reza , Mazzara Manuel , Kotorov Iouri
Published: September 2021

The development of smart cities is a clear growing trend all around the world. The convergence of different technological, social, political, economical, and ecological trends has allowed the concepts to rise up quickly in governmental agendas. In this paper, we analyze the situation of Russia regarding smart cities. Moscow, Saint Petersburg, and Kazan are considered at the “Smart City 3.0” stage of development, meaning that the citizens are participating in their advancement. Our reasons to focus on Russia are two-fold: (1) we know the situation well, as we live and work in a new city, Innopolis, founded in 2015 and meant to be a blueprint for smart cities; (2) large Russian cities are actively developing projects in this sphere and are highly regarded worldwide in these endeavors. It is therefore worth analyzing the context and the trends. By studying the scientific literature and categorizing the features of smart cities the world over, we found that large Russian cities are developing most of the components necessary in order to be called smart. Herein we also discuss areas of possible growth for Russian cities, such as green technologies and a smart environment.
The Snakeskin Gourami (Trichopodus pectoralis) Tends to Exhibit XX/XY Sex Determination
Authors: Panthum Thitipong , Laopichienpong Nararat , Kraichak Ekaphan , Singchat Worapong , Ho My Nguyen Dung , Ariyaraphong Nattakan , Ahmad Syed Farhan , Muangmai Narongrit , Duengkae Prateep , Peyachoknagul Surin , Ezaz Tariq , Srikulnath Kornsorn
Published: September 2021

The snakeskin gourami (Trichopodus pectoralis) has a high meat yield and is one of the top five aquaculture freshwater fishes in Thailand. The species is not externally sexually dimorphic, and its sex determination system is unknown. Understanding the sex determination system of this species will contribute to its full-scale commercialization. In this study, a cytogenetic analysis did not reveal any between-sex differences in chromosomal patterns. However, we used genotyping-by-sequencing to identify 4 male-linked loci and 1 female-linked locus, indicating that the snakeskin gourami tends to exhibit an XX/XY sex determination system. However, we did not find any male-specific loci after filtering the loci for a ratio of 100:0 ratio of males:females. This suggests that the putative Y chromosome is young and that the sex determination region is cryptic. This approach provides solid information that can help identify the sex determination mechanism and potential sex determination regions in the snakeskin gourami, allowing further investigation of genetic improvements in the species.
Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review
Authors: Gao Yaxin , Hou Lizhen , Gao Jie , Li Danfeng , Tian Zhiliang , Fan Bei , Wang Fengzhong , Li Shuying
Published: September 2021

Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods.
Antihypertensive and Antioxidant Activity of Chia Protein Techno-Functional Extensive Hydrolysates
Authors: Villanueva-Lazo Alvaro , Paz Sergio Montserrat-de la , Rodriguez-Martin Noelia Maria , Millan Francisco , Carrera Cecilio , Pedroche Justo Javier , Millan-Linares Maria del Carmen
Published: September 2021

Twelve high-quality chia protein hydrolysates (CPHs) were produced from chia protein isolate (CPI) in a pilot plant of vegetable proteins. To obtain functional hydrolysate, four CPHs were hydrolyzed by the action of Alcalase, an endoprotease, and the other eight CPHs were hydrolyzed by the action of Flavourzyme, an exoprotease. Alcalase-obtained CPHs showed significant antihypertensive properties particularly, the CPH obtained after 15 min of hydrolysis with Alcalase (CPH15A), which showed a 36.2% hydrolysis degree. In addition, CPH15A increased the antioxidant capacity compared to CPI. The CPH15A physicochemical composition was characterized and compared to chia defatted flour (CDF) and CPI, and its techno-functional properties were determined by in vitro experiments through the analysis of its oil absorption capacity, as well as the capacity and stability of foaming and emulsifying, resulting in an emulsifier and stabilizer better than the intact protein. Therefore, the present study revealed that CPH15A has potent antihypertensive and antioxidant properties and can constitute an effective alternative to other plant protein ingredients sources that are being used in the food industry.
Impact of Processing Approach and Storage Time on Bioactive and Biological Properties of Rocket, Spinach and Watercress Byproducts
Authors: Araújo-Rodrigues Helena , Santos Diva , Campos Débora A. , Guerreiro Suse , Ratinho Modesta , Rodrigues Ivo M. , Pintado Manuela E.
Published: September 2021

The high nutritional value of vegetables is well recognized, but their short shelf life and seasonal nature result in massive losses and wastes. Vegetable’s byproducts are an opportunity to develop value-added ingredients, increasing food system efficiency and environmental sustainability. In the present work, pulps and powders of byproducts from rocket and spinach leaves and watercress were developed and stored for six months under freezing and vacuum conditions, respectively. After processing and storage, microbiological quality, bioactive compounds (polyphenols, carotenoids and tocopherols profiles), antioxidant capacity, and pulps viscosity were analyzed. Generally, the developed vegetable’s pulps and powders were considered microbiologically safe. Although some variations after processing and storage were verified, the antioxidant activity was preserved or improved. A rich phenolic composition was also registered and maintained. During freezing, the quantitative carotenoid profile was significantly improved (mainly in rocket and spinach), while after drying, there was a significant decrease. A positive effect was verified in the vitamin E level. Both processing and storage conditions resulted in products with relevant phenolics, carotenoids and tocopherol levels, contributing to the antioxidant activity registered. Thus, this study demonstrates the potential of vegetable byproducts valorization through developing these functional ingredients bringing economic and environmental value into the food chain.
The Effect of Cold Press Chia Seed Oil By-Products on the Rheological, Microstructural, Thermal, and Sensory Properties of Low-Fat Ice Cream
Authors: Atik Ilker , Tekin Cakmak Zeynep Hazal , Avcı Esra , Karasu Salih
Published: September 2021

This study aimed to investigate the utilization of cold-pressed chia-seed oil by-products (CSOB) in a low-fat ice cream formulation as a fat replacer and stabilizer. In the study, ice cream emulsion mixtures were formulated by using 0.2–0.4% xanthan gum (XG), 2.5–12.5% fat, and 1–3% CSOB. Optimization was performed using the response surface methodology (RSM) and full factorial central composite design (CCD) based on the flow behavior rheological properties of the emulsions obtained from 17 different experimental points. All of the emulsion samples showed non-Newtonian shear-thinning flow behavior. The consistency coefficient (Κ) values of the emulsion samples were found to be 4.01–26.05 Pasn and were significantly affected by optimization parameters (p < 0.05). The optimum formulation was determined as 0.29% XG, 2.5% CSOB, 2.5% fat. The low-fat (LF-IC) and full-fat control samples (FF-IC) were compared to samples produced with an optimum formulation (CBLF-IC) based on the steady shear, frequency sweep, and 3-ITT (three interval thixotropy test) rheological properties, thermal properties, emulsion stability, light microscope images, and sensory quality. CBLF-IC showed similar rheological behavior to FF-IC. The mix of CBLF-IC showed higher emulsion stability and lower poly-dispersity index (PDI) value and fat globule diameters than those of FF-IC and LF-IC. The thermal properties of the samples were significantly affected by the addition of CSOB in an ice cream mix. CBLF-IC exhibited a lower temperature range (ΔT), enthalpy of fusion (ΔHf), and freezing point temperature (Tf) than those of FF-IC and LF-IC. While CBLF-IC exhibited a higher overrun value than other samples, it showed similar sensory properties to the FF-IC sample. The results of this study suggested that CSOB could be used successfully in low-fat ice cream production. This study also has the potential to gain new perspectives for the evaluation of CSOB as a fat substitute in a low-fat ice cream.
Microalgae Derived Astaxanthin: Research and Consumer Trends and Industrial Use as Food
Authors: Villaró Silvia , Ciardi Martina , Morillas-España Ainoa , Sánchez-Zurano Ana , Acién-Fernández Gabriel , Lafarga Tomas
Published: September 2021

Astaxanthin is a high-value carotenoid currently being produced by chemical synthesis and by extraction from the biomass of the microalga Haematococcus pluvialis. Other microalgae, such as Chlorella zofingiensis, have the potential for being used as sources of astaxanthin. The differences between the synthetic and the microalgae derived astaxanthin are notorious: not only their production and price but also their uses and bioactivity. Microalgae derived astaxanthin is being used as a pigment in food and feed or aquafeed production and also in cosmetic and pharmaceutical products. Several health-promoting properties have been attributed to astaxanthin, and these were summarized in the current review paper. Most of these properties are attributed to the high antioxidant capacity of this molecule, much higher than that of other known natural compounds. The aim of this review is to consider the main challenges and opportunities of microalgae derived products, such as astaxanthin as food. Moreover, the current study includes a bibliometric analysis that summarizes the current research trends related to astaxanthin. Moreover, the potential utilization of microalgae other than H. pluvialis as sources of astaxanthin as well as the health-promoting properties of this valuable compound will be discussed.
Applicable Plant Proteins and Dietary Fibers for Simulate Plant-Based Yogurts
Authors: Shin Jae-Sung , Kim Beom-Hee , Baik Moo-Yeol
Published: September 2021

Effects of plant proteins and dietary fibers on the physical properties of stirred soy yogurt were investigated. Buffering capacity against lactic acid was not affected by the protein concentration for any of the four proteins that were examined: isolate soy protein (ISP), pea protein (PP), rice protein (RP), and almond protein (AP). Three proteins other than AP exhibited an increase in buffering capacity (dB/dPH) following a physical treatment, whereas AP saw a decrease in buffering capacity. Furthermore, physically treated PP revealed a significant increase in viscosity, reaching up to 497 cp in the pH 6.0~6.2 range during the titration process. Following fermentation, PP produced the highest viscosity and coagulum strength with no syneresis. In the case of dietary fiber, Acacia Fiber (AF) was completely dissolved in the solvent and did not affect the physical properties of the fermented coagulum. Soy fiber (SF) was also not suitable for fermented milk processes because precipitation occurred after the physical treatment. In the case of citrus fiber (CF), however, syneresis did not occur during storage after the physical treatment, and the viscosity also increased up to 2873 cP. Consequently, PP and CF were deemed to be a suitable plant protein and dietary fiber for stirred soy yogurt, respectively.
Weak Solutions for Time-Fractional Evolution Equations in Hilbert Spaces
Authors: Loreti Paola , Sforza Daniela
Published: September 2021

Our purpose is to introduce a notion of weak solution for a class of abstract fractional differential equations. We point out that the time fractional derivative occurring in the equations is in the sense of the Caputo derivative. We prove existence results for weak and strong solutions. To justify the abstract theory we develop, we apply two examples of concrete equations: time-fractional wave equations and time-fractional Petrovsky systems. Both these concrete examples are of great interest in the theory of fractional partial differential equations.
Evolutionary Game Theory: Darwinian Dynamics and the G Function Approach
Authors: Bukkuri Anuraag , Brown Joel S.
Published: September 2021

Classical evolutionary game theory allows one to analyze the population dynamics of interacting individuals playing different strategies (broadly defined) in a population. To expand the scope of this framework to allow us to examine the evolution of these individuals’ strategies over time, we present the idea of a fitness-generating (G) function. Under this model, we can simultaneously consider population (ecological) and strategy (evolutionary) dynamics. In this paper, we briefly outline the differences between game theory and classical evolutionary game theory. We then introduce the G function framework, deriving the model from fundamental biological principles. We introduce the concept of a G-function species, explain the process of modeling with G functions, and define the conditions for evolutionary stable strategies (ESS). We conclude by presenting expository examples of G function model construction and simulations in the context of predator–prey dynamics and the evolution of drug resistance in cancer.
Anemia in Newly Diagnosed Pediatric Patients with Inflammatory Bowel Disease
Authors: Shentova-Eneva Rayna , Kofinova Denitza , Hadzhiyski Petyo , Yaneva Penka , Lazarova Elena , Baycheva Mila
Published: September 2021

Anemia is the most common extraintestinal manifestation and complication of inflammatory bowel disease (IBD). The aim of our study was to assess the prevalence of anemia in newly diagnosed pediatric patients with IBD and to analyze its association with disease type, extent, and severity. We retrospectively reviewed the medical records of all patients with IBD treated in our department in the period of November 2011 to November 2020. The final analysis included the records of 80 children with newly diagnosed IBD: 45 with ulcerative colitis (UC) and 35 with Crohn’s disease (CD). The prevalence of anemia was 60.0% in the UC patients and 77.1% in the CD patients. Of the UC patients with anemia, 37.1% had pancolitis, 18.5% extensive disease, 33.3% left-sided colitis and 11.1% ulcerative proctitis. Of the CD patients with anemia, 81.5% had ileocolonic disease, 11.1% colonic disease and 7.4% ileal disease. Anemia was less common in patients with mild disease than in patients with moderate–severe disease (22.2 vs. 77.8%, p < 0.001 in UC and 25.9% vs. 74.1%, p < 0.001 in CD). Our study confirmed anemia as a frequent problem in pediatric patients with IBD. Children with more extensive and more severe disease are at higher risk to develop anemia.
Graphene Oxide-Chitosan Aerogels: Synthesis, Characterization, and Use as Adsorbent Material for Water Contaminants
Authors: Pinelli Filippo , Nespoli Tommaso , Rossi Filippo
Published: September 2021

Porous aerogels, formed by subjecting precursor hydrogels using a freeze-drying process, are certainly one of the most studied and synthetized soft materials, thanks to their important features such as elasticity, swelling behavior, softness, and micro and nanosized pores, which guarantee their applicability in various fields. Typically, these systems are synthetized working with natural or synthetic polymers, but in the last years great interest has been given to proper formulated aerogels able to combine polymeric structures with other moieties such as graphene or graphene oxide. This working strategy can be pivotal in many cases to tune important properties of the final system such as toughness, porosity, elasticity, electrical conductivity, or responsive behavior. In this work we propose the synthesis of chitosan graphene oxide aerogels obtained through self-assembly of graphene oxide sheets and chitosan chains. These three-dimensional systems were chemically characterized with IR and XRD technique and their inner structure was investigated through the scanning electron microscopy (SEM). Moreover, we mechanically characterized the material through dynamic mechanical analysis, showing the stability of these systems. Finally, the adsorption ability of these soft materials has been demonstrated using model molecules to simulate water contaminants showing the efficacy of those graphene-based systems even for the removal of anionic dyes. Complete removal of contaminants was obtained at low concentration of dyes in solution (100 mg/L), while with a higher amount of pollutant in the solution (350 mg/L) high sorption capacity (q > 200 mg/g) was observed.
Repair of Peripheral Nerve Injury Using Hydrogels Based on Self-Assembled Peptides
Authors: Zhang Meng , Li Lei , An Heng , Zhang Peixun , Liu Peilai
Published: September 2021

Peripheral nerve injury often occurs in young adults and is characterized by complex regeneration mechanisms, poor prognosis, and slow recovery, which not only creates psychological obstacles for the patients but also causes a significant burden on society, making it a fundamental problem in clinical medicine. Various steps are needed to promote regeneration of the peripheral nerve. As a bioremediation material, self-assembled peptide (SAP) hydrogels have attracted international attention. They can not only be designed with different characteristics but also be applied in the repair of peripheral nerve injury by promoting cell proliferation or drug-loaded sustained release. SAP hydrogels are widely used in tissue engineering and have become the focus of research. They have extensive application prospects and are of great potential biological value. In this paper, the application of SAP hydrogel in peripheral nerve injury repair is reviewed, and the latest progress in peptide composites and fabrication techniques are discussed.
The Role of Human Satellite III (1q12) Copy Number Variation in the Adaptive Response during Aging, Stress, and Pathology: A Pendulum Model
Authors: Porokhovnik Lev N. , Veiko Natalia N. , Ershova Elizaveta S. , Kostyuk Svetlana V.
Published: September 2021

The pericentric satellite III (SatIII or Sat3) and II tandem repeats recently appeared to be transcribed under stress conditions, and the transcripts were shown to play an essential role in the universal stress response. In this paper, we review the role of human-specific SatIII copy number variation (CNV) in normal stress response, aging and pathology, with a focus on 1q12 loci. We postulate a close link between transcription of SatII/III repeats and their CNV. The accrued body of data suggests a hypothetical universal mechanism, which provides for SatIII copy gain during the stress response, alongside with another, more hypothetical reverse mechanism that might reduce the mean SatIII copy number, likely via the selection of cells with excessively large 1q12 loci. Both mechanisms, working alternatively like swings of the pendulum, may ensure the balance of SatIII copy numbers and optimum stress resistance. This model is verified on the most recent data on SatIII CNV in pathology and therapy, aging, senescence and response to genotoxic stress in vitro.
Evaluation of Genotype-Based Gene Expression Model Performance: A Cross-Framework and Cross-Dataset Study
Authors: Tavares Vânia , Monteiro Joana , Vassos Evangelos , Coleman Jonathan , Prata Diana
Published: September 2021

Predicting gene expression from genotyped data is valuable for studying inaccessible tissues such as the brain. Herein we present eGenScore, a polygenic/poly-variation method, and compare it with PrediXcan, a method based on regularized linear regression using elastic nets. While both methods have the same purpose of predicting gene expression based on genotype, they carry important methodological differences. We compared the performance of expression quantitative trait loci (eQTL) models to predict gene expression in the frontal cortex, comparing across these frameworks (eGenScore vs. PrediXcan) and training datasets (BrainEAC, which is brain-specific, vs. GTEx, which has data across multiple tissues). In addition to internal five-fold cross-validation, we externally validated the gene expression models using the CommonMind Consortium database. Our results showed that (1) PrediXcan outperforms eGenScore regardless of the training database used; and (2) when using PrediXcan, the performance of the eQTL models in frontal cortex is higher when trained with GTEx than with BrainEAC.
Immune Profiling of Medullary Thyroid Cancer—An Opportunity for Immunotherapy
Authors: Hińcza-Nowak Kinga , Kowalik Artur , Walczyk Agnieszka , Pałyga Iwona , Gąsior-Perczak Danuta , Płusa Agnieszka , Kopczyński Janusz , Chrapek Magdalena , Góźdź Stanisław , Kowalska Aldona
Published: September 2021

Medullary thyroid cancer (MTC) is a rare malignancy that arises from calcitonin-producing C-cells. Curative treatment for patients with metastatic MTC is challenging. Identifying the mechanisms by which cancer cells inhibit the activity of immune cells provides an opportunity to develop new therapies that restore anticancer activity. Little is known about the immunological phenomena underlying MTC. Here, we examined the expression profile of 395 genes associated with MTC. The study included 51 patients diagnosed with MTC at a single center. Bioinformatical analysis revealed that CD276 expression in MTC cells was at least three-fold higher than that in normal tissue. The expression of CD276 showed a weak but statistically significant positive correlation with tumor diameter, but we did not find a significant association between CD276 expression and other histopathological clinical factors, or the response to initial therapy. A search of published data identified the monoclonal antibody (inhibitor) enoblituzumab as a potential drug for patients diagnosed with MTC overexpressing CD276.