bluuebunny/crossref_metadata_2025 huggingface dataset:
Why Do Only Males of Mawia benovici (Pelagiidae: Semaeostomeae: Scyphozoa) Seem to Inhabit the Northern Adriatic Sea?
Authors: Tirelli Valentina , Kogovšek Tjaša , Rogelja Manja , Paliaga Paolo , Avian Massimo , Malej Alenka
Published: May 2021

This manuscript presents four new observations of the jellyfish Mawia benovici in the Adriatic Sea. This new species was recently identified as Pelagia benovici by Piraino et al. (2014) and then placed in the new genus Mawia by Avian et al. 2016. This species is rare and is almost exclusively observed in the Adriatic Sea. Interestingly, the majority of observations refer to males only. Few studies have addressed the issue of sex determination in Syphozoa in particular, as sex identity can only be determined at the medusa stage. Unfortunately, the rarity of M. benovici and the lack of female specimens have so far prevented indispensable laboratory studies to clarify its life cycle. Still, we tried to propose an explanation for our field observations.
Diagnostic Insights from Plethysmographic Alveolar Pressure Assessed during Spontaneous Breathing in COPD Patients
Authors: Zilianti Camilla , Santus Pierachille , Pecchiari Matteo , D’Angelo Edgardo , Radovanovic Dejan
Published: May 2021

Since its introduction in the clinical practice, body plethysmography has assisted pneumologists in the diagnosis of respiratory diseases and patients’ follow-up, by providing easy assessment of absolute lung volumes and airway resistance. In the last decade, emerging evidence suggested that estimation of alveolar pressure by electronically-compensated plethysmographs may contain information concerning the mechanics of the respiratory system which goes beyond those provided by the simple value of airway resistance or conductance. Indeed, the systematic study of expiratory alveolar pressure-flow loops produced during spontaneous breathing at rest has shown that the marked expansion of expiratory loops in chronic obstructive pulmonary disease patients mainly reflects the presence of tidal expiratory flow-limitation. The presence of this phenomenon can be accurately predicted on the basis of loop-derived parameters. Finally, we present results suggesting that plethysmographic alveolar pressure may be used to estimate non-invasively intrinsic positive end-expiratory pressure (PEEPi) in spontaneously breathing patients, a task which previously could be only accomplished by introducing a balloon-tipped catheter in the esophagus.
Design and Testing of Augmented Reality-Based Fluorescence Imaging Goggle for Intraoperative Imaging-Guided Surgery
Authors: Lee Seung Hyun , Quan Yu Hua , Kim Min Sub , Kwon Ki Hyeok , Choi Byeong Hyeon , Kim Hyun Koo , Kim Beop-Min
Published: May 2021

The different pathways between the position of a near-infrared camera and the user’s eye limit the use of existing near-infrared fluorescence imaging systems for tumor margin assessments. By utilizing an optical system that precisely matches the near-infrared fluorescence image and the optical path of visible light, we developed an augmented reality (AR)-based fluorescence imaging system that provides users with a fluorescence image that matches the real-field, without requiring any additional algorithms. Commercial smart glasses, dichroic beam splitters, mirrors, and custom near-infrared cameras were employed to develop the proposed system, and each mount was designed and utilized. After its performance was assessed in the laboratory, preclinical experiments involving tumor detection and lung lobectomy in mice and rabbits by using indocyanine green (ICG) were conducted. The results showed that the proposed system provided a stable image of fluorescence that matched the actual site. In addition, preclinical experiments confirmed that the proposed system could be used to detect tumors using ICG and evaluate lung lobectomies. The AR-based intraoperative smart goggle system could detect fluorescence images for tumor margin assessments in animal models, without disrupting the surgical workflow in an operating room. Additionally, it was confirmed that, even when the system itself was distorted when worn, the fluorescence image consistently matched the actual site.
A Comparative Evaluation of Computed Tomography Images for the Classification of Spirometric Severity of the Chronic Obstructive Pulmonary Disease with Deep Learning
Authors: Sugimori Hiroyuki , Shimizu Kaoruko , Makita Hironi , Suzuki Masaru , Konno Satoshi
Published: May 2021

Recently, deep learning applications in medical imaging have been widely applied. However, whether it is sufficient to simply input the entire image or whether it is necessary to preprocess the setting of the supervised image has not been sufficiently studied. This study aimed to create a classifier trained with and without preprocessing for the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification using CT images and to evaluate the classification accuracy of the GOLD classification by confusion matrix. According to former GOLD 0, GOLD 1, GOLD 2, and GOLD 3 or 4, eighty patients were divided into four groups (n = 20). The classification models were created by the transfer learning of the ResNet50 network architecture. The created models were evaluated by confusion matrix and AUC. Moreover, the rearranged confusion matrix for former stages 0 and ≥1 was evaluated by the same procedure. The AUCs of original and threshold images for the four-class analysis were 0.61 ± 0.13 and 0.64 ± 0.10, respectively, and the AUCs for the two classifications of former GOLD 0 and GOLD ≥ 1 were 0.64 ± 0.06 and 0.68 ± 0.12, respectively. In the two-class classification by threshold image, recall and precision were over 0.8 in GOLD ≥ 1, and in the McNemar–Bowker test, there was some symmetry. The results suggest that the preprocessed threshold image can be possibly used as a screening tool for GOLD classification without pulmonary function tests, rather than inputting the normal image into the convolutional neural network (CNN) for CT image learning.
Profiling of Microbiota at the Mouth of Bottles and in Remaining Tea after Drinking Directly from Plastic Bottles of Tea
Authors: Wakui Anna , Sano Hiroto , Hirabuki Yuka , Kawachi Miho , Aida Ayaka , Washio Jumpei , Abiko Yuki , Mayanagi Gen , Yamaki Keiko , Tanaka Kaori , Takahashi Nobuhiro , Sato Takuichi
Published: May 2021

It has been speculated that oral bacteria can be transferred to tea in plastic bottles when it is drunk directly from the bottles, and that the bacteria can then multiply in the bottles. The transfer of oral bacteria to the mouth of bottles and bacterial survival in the remaining tea after drinking directly from bottles were examined immediately after drinking and after storage at 37 °C for 24 h. Twelve healthy subjects (19 to 23 years of age) were asked to drink approximately 50 mL of unsweetened tea from a plastic bottle. The mouths of the bottles were swabbed with sterile cotton, and the swabs and the remaining tea in the bottles were analyzed by anaerobic culture and 16S rRNA gene sequencing. Metagenomic analysis of the 16S rRNA gene was also performed. The mean amounts of bacteria were (1.8 ± 1.7) × 104 colony-forming units (CFU)/mL and (1.4 ± 1.5) × 104 CFU/mL at the mouth of the bottles immediately after and 24 h after drinking, respectively. In contrast, (0.8 ± 1.6) × 104 CFU/mL and (2.5 ± 2.6) × 106 CFU/mL were recovered from the remaining tea immediately after and 24 h after drinking, respectively. Streptococcus (59.9%) were predominant at the mouth of the bottles immediately after drinking, followed by Schaalia (5.5%), Gemella (5.5%), Actinomyces (4.9%), Cutibacterium (4.9%), and Veillonella (3.6%); the culture and metagenomic analyses showed similar findings for the major species of detected bacteria, including Streptococcus (59.9%, and 10.711%), Neisseria (1.6%, and 24.245%), Haemophilus (0.6%, and 15.658%), Gemella (5.5%, and 0.381%), Cutibacterium (4.9%, and 0.041%), Rothia (2.6%, and 4.170%), Veillonella (3.6%, and 1.130%), Actinomyces (4.9%, and 0.406%), Prevotella (1.6%, and 0.442%), Fusobacterium (1.0%, and 0.461%), Capnocytophaga (0.3%, and 0.028%), and Porphyromonas (1.0%, and 0.060%), respectively. Furthermore, Streptococcus were the most commonly detected bacteria 24 h after drinking. These findings demonstrated that oral bacteria were present at the mouth of the bottles and in the remaining tea after drinking.
A Product Shape Design and Evaluation Model Based on Morphology Preference and Macroscopic Shape Information
Authors: Lu Peng , Hsiao Shih-Wen , Wu Fan
Published: May 2021

A product form design and evaluation model are proposed. In this method, the forms can be evaluated by three sub-evaluation models which can help designers to grasp consumers’ preferences. In the process, the overall shape is first disassembled into several shape elements, and a morphological chart is constructed. Then, the priority of shape elements is analyzed through the fuzzy analytical hierarchy process, and several required combinations are selected from a morphological chart. Moreover, the fuzzy comprehensive evaluation (I), preference questionnaire (II), and quadratic curvature entropy (III) of the selected combinations are analyzed. Finally, the results of I, II, and III are compared. In conclusion, the three sub-evaluation systems are consistent, which confirms the applicability of the proposed model.
A Thermodynamic Approach to Measuring Entropy in a Few-Electron Nanodevice
Authors: Pyurbeeva Eugenia , Mol Jan A.
Published: May 2021

The entropy of a system gives a powerful insight into its microscopic degrees of freedom; however, standard experimental ways of measuring entropy through heat capacity are hard to apply to nanoscale systems, as they require the measurement of increasingly small amounts of heat. Two alternative entropy measurement methods have been recently proposed for nanodevices: through charge balance measurements and transport properties. We describe a self-consistent thermodynamic framework for applying thermodynamic relations to few-electron nanodevices—small systems, where fluctuations in particle number are significant, whilst highlighting several ongoing misconceptions. We derive a relation (a consequence of a Maxwell relation for small systems), which describes both existing entropy measurement methods as special cases, while also allowing the experimentalist to probe the intermediate regime between them. Finally, we independently prove the applicability of our framework in systems with complex microscopic dynamics—those with many excited states of various degeneracies—from microscopic considerations.
Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals
Authors: Liu Tongtong , Li Peng , Liu Yuanyuan , Zhang Huan , Li Yuanyang , Jiao Yu , Liu Changchun , Karmakar Chandan , Liang Xiaohong , Ren Mengli , Wang Xinpei
Published: May 2021

Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it.
AutoPPI: An Ensemble of Deep Autoencoders for Protein–Protein Interaction Prediction
Authors: Czibula Gabriela , Albu Alexandra-Ioana , Bocicor Maria Iuliana , Chira Camelia
Published: May 2021

Proteins are essential molecules, that must correctly perform their roles for the good health of living organisms. The majority of proteins operate in complexes and the way they interact has pivotal influence on the proper functioning of such organisms. In this study we address the problem of protein–protein interaction and we propose and investigate a method based on the use of an ensemble of autoencoders. Our approach, entitled AutoPPI, adopts a strategy based on two autoencoders, one for each type of interactions (positive and negative) and we advance three types of neural network architectures for the autoencoders. Experiments were performed on several data sets comprising proteins from four different species. The results indicate good performances of our proposed model, with accuracy and AUC values of over 0.97 in all cases. The best performing model relies on a Siamese architecture in both the encoder and the decoder, which advantageously captures common features in protein pairs. Comparisons with other machine learning techniques applied for the same problem prove that AutoPPI outperforms most of its contenders, for the considered data sets.
Entropy of Quantum States
Authors: Facchi Paolo , Gramegna Giovanni , Konderak Arturo
Published: May 2021

Given the algebra of observables of a quantum system subject to selection rules, a state can be represented by different density matrices. As a result, different von Neumann entropies can be associated with the same state. Motivated by a minimality property of the von Neumann entropy of a density matrix with respect to its possible decompositions into pure states, we give a purely algebraic definition of entropy for states of an algebra of observables, thus solving the above ambiguity. The entropy so-defined satisfies all the desirable thermodynamic properties and reduces to the von Neumann entropy in the quantum mechanical case. Moreover, it can be shown to be equal to the von Neumann entropy of the unique representative density matrix belonging to the operator algebra of a multiplicity-free Hilbert-space representation.
The DEA Method and Its Application Possibilities for Measuring Efficiency in the Public Sector—The Case of Local Public Employment Services
Authors: Cichowicz Ewa , Rollnik-Sadowska Ewa , Dędys Monika , Ekes Maria
Published: May 2021

Public Employment Services (PES) are identified as important institutions in the process of improving the match between supply and demand in the labor market, which, despite their importance, still do not achieve the desired efficiency. The indicated problem is partly due to the lack of appropriate evaluation methods for the applied labor market policy instruments. This paper aims to verify the possibility of using the two-stage Data Envelopment Analysis (DEA) method in measuring the efficiency of public sector entities. The authors focused on 39 PES operating in Mazovia province, Poland in 2019. In the first stage, the model of technical efficiency of local PES included six variables (four inputs and two outputs). Only seven PES obtained full efficiency. The inefficiency of analyzed PES varied from about 1% to 80%. In the second stage, the attention focuses on the relationship between true unknown efficiency and its determinants (five environmental variables, both demand and supply oriented). Then, the regression coefficients and confidence intervals showed that three out of five variables influence the efficiency results, the share of the long-term unemployed, the share of the unemployed under 30, and the share of the unemployed over 50 in the total number of unemployed.
Renewable and Non-Renewable Energy Consumption in BRICS: Assessing the Dynamic Linkage between Foreign Capital Inflows and Energy Consumption
Authors: Qin Zhexuan , Ozturk Ilhan
Published: May 2021

This study attempt to fill the research gap by figuring out the dynamic effects of foreign capital inflows effect on renewable energy and non-renewable consumption by using the time series non-linear ARDL approach for BRICS from 1991 to 2019. Non-linear ARDL estimates show that positive change in foreign capital inflows has a positive effect on renewable consumption in Brazil, India, and South Africa in long run. Also, the negative change in foreign capital inflows exhibits negatively liked with renewable energy consumption in BRICS economies, except Russia in long run. We find that positive shock in foreign capital inflows tends to increase non-renewable energy consumption in BRICS except India in the long run. Finding suggests that negative change in foreign capital inflows has negative impacts on non-renewable energy consumption in India and Brazil, while the positive effect in only China in the long run.
Analysis of Small Hydropower Generation Potential: (1) Estimation of the Potential in Ungaged Basins
Authors: Jung Sungeun , Bae Younghye , Kim Jongsung , Joo Hongjun , Kim Hung Soo , Jung Jaewon
Published: May 2021

Small hydropower (SHP) plants are advantageous as they have a short construction period and can be easily maintained. They also have a higher energy density than other alternative energy sources as environmentally-friendly energy sources. In general, hydropower potential is estimated based on the discharge in the river basin, and the discharge can be obtained from the stage station in the gaged basin. However, if there is no station (i.e., ungaged basin) or no sufficient discharge data, the discharge should be estimated based on rainfall data. The flow duration characteristic model is the most widely used method for the estimation of mean annual discharge because of its simplicity and it consists of rainfall, basin area, and runoff coefficient. Due to the characteristics of hydroelectric power depending on the discharge, there is a limit to guaranteeing the accuracy of estimating the generated power with only one method of the flow duration characteristic model. Therefore, this study assumes the gaged basins of the three hydropower plants of Deoksong, Hanseok, and Socheon in Korea exist as ungaged basins and the river discharges were simulated using the Kajiyama formula, modified-TPM(Two-Parameter Monthly) model, and Tank model for a comparison with the flow duration characteristics model. Furthermore, to minimize the uncertainty of the simulated discharge, four blending techniques of simple average method, MMSE(Multi-Model Super Ensemble), SMA(Simple Model Average), and MSE(Mean Square Error) were applied. As for the results, the obtained discharges from the four models were compared with the observed discharge and we noted that the discharges by the Kajiyama formula and modified-TPM model were better fitted with the observations than the discharge by the flow duration characteristics model. However, the result by the Tank model was not well fitted with the observation. Additionally, when we investigated the four blending techniques, we concluded that the MSE technique was the most appropriate for the discharge simulation of the ungaged basin. This study proposed a methodology to estimate power generation potential more accurately by applying discharge simulation models that have not been previously applied to the estimation of SHP potential and blending techniques were also used to minimize the uncertainty of the simulated discharge. The methodology proposed in this study is expected to be applicable for the estimation of SHP potential in ungaged basins.
Prediction of Air Pressure Change Inside the Chamber of an Oscillating Water Column–Wave Energy Converter Using Machine-Learning in Big Data Platform
Authors: Seo Dongwoo , Huh Taesang , Kim Myungil , Hwang Jaesoon , Jung Daeyong
Published: May 2021

Wave power is an eco-friendly power generation method. Owing to the highly volatile nature of wave energy, the application of prediction techniques for power generation, failure diagnosis, and operational efficiency plays a key role in the successful operation of wave power plants (WPPs). To this end, we propose the following approaches: (i) deriving the correlation between highly volatile data such as wave height data and sensor data in an oscillating water column (OWC) chamber; (ii) development of an optimal training model capable of accurate prediction of the state of the wave energy converter (WEC) based on the collected sensor data. In this study, we developed a big data analysis system that can utilize the machine learning framework in KNIME (an open analysis platform), and to enable smart operation, we designed a training model using a digital twin of an OWC–WEC that is currently in operation. Using various machine learning models, the pressure of the OWC chamber was predicted, and the results obtained were tested and evaluated to confirm its validity. Furthermore, the prediction performance was comparatively analyzed, demonstrating the excellent performance of the proposed CNN-LSTM-based prediction model.
High Precision LSTM Model for Short-Time Load Forecasting in Power Systems
Authors: Ciechulski Tomasz , Osowski Stanisław
Published: May 2021

The paper presents the application of recurrent LSTM neural networks for short-time load forecasting in the Polish Power System (PPS) and a small region of a power system in Central Poland. The objective of the present work was to develop an efficient and accurate method of forecasting the 24-h pattern of power load with a 1-h and 24-h horizon. LSTM showed effectiveness in predicting the irregular trends in time series. The final forecast is estimated using an ensemble consisted of five independent predictions. Numerical experiments proved the superiority of the ensemble above single predictor resulting in a reduction of the MAPE the RMSE error by more than 6% in both forecasting tasks.
Technical and Economic Analysis of the Supercritical Combined Gas-Steam Cycle
Authors: Jamróz Marcin , Piwowarski Marian , Ziemiański Paweł , Pawlak Gabriel
Published: May 2021

Combined cycle power plants are characterized by high efficiency, now exceeding 60%. The record-breaking power plant listed in the Guinness Book of World Records is the Nishi-Nagoya power plant commissioned in March 2018, located in Japan, and reaching the gross efficiency of 63.08%. Research and development centers, energy companies, and scientific institutions are taking various actions to increase this efficiency. Both the gas turbine and the steam turbine of the combined cycle are modified. The main objective of this paper is to improve the gas-steam cycle efficiency and to reach the efficiency that is higher than in the record-breaking Nishi-Nagoya power plant. To do so, a number of numerical calculations were performed for the cycle design similar to the one used in the Nishi-Nagoya power plant. The paper assumes the use of the same gas turbines as in the reference power plant. The process of recovering heat from exhaust gases had to be organized so that the highest capacity and efficiency were achieved. The analyses focused on the selection of parameters and the modification of the cycle design in the steam part area in order to increase overall efficiency. As part of the calculations, the appropriate selection of the most favorable thermodynamic parameters of the steam at the inlet to the high-pressure (HP) part of the turbine (supercritical pressure) allowed the authors to obtain the efficiency and the capacity of 64.45% and about 1.214 GW respectively compared to the reference values of 63.08% and 1.19 GW. The authors believe that efficiency can be improved further. One of the methods to do so is to continue increasing the high-pressure steam temperature because it is the first part of the generator into which exhaust gases enter. The economic analysis revealed that the difference between the annual revenue from the sale of electricity and the annual fuel cost is considerably higher for power plants set to supercritical parameters, reaching approx. USD 14 million per annum. It is proposed that investments in adapting components of the steam part to supercritical parameters may be balanced out by a higher profit.
Modelling Aspects in the Simulation of the Diffusive Flame in A Bluff-Body Geometry
Authors: Di Mauro Alessandro , Ravetto Marco , Goel Prashant , Baratta Mirko , Misul Daniela Anna , Salvadori Simone , Rothbauer Rainer , Gretter Riccardo
Published: May 2021

Gas turbines are expected to play a key role in the energy production scenario in the future, and the introduction of carbon-free fuels is fundamental for the development of a sustainable energy mix. The development of a reliable numerical model is thus fundamental in order to support the design changes required for the burners. This paper presents the results of a numerical investigation on a turbulent, diffusive, combustion test case, with the purpose of identifying the best compromise between accuracy and computational cost, in the perspective of the model application in real, more complex, geometries. Referring to a test case has two main advantages. First, a rather simple geometry can be considered, still retaining a few peculiar flow features, such as recirculation vortices and shear layers, which are typical of real applications. Second, the experimental setup is much more detailed than in the case of real turbines, allowing a thorough model validation to be performed. In this paper, the Standard 2-equations k-ε model and the Speziale-Sarkar-Gatski Reynolds Stress Model are considered. Moreover, both the FGM combustion model and the detailed chemistry model are used, coupled with two chemical reaction mechanisms, and their results are compared. Finally, a standard and an enhanced near-wall approach are employed to solve the transport equations close to the walls. The results show a good agreement in the temperature distribution at the axial positions corresponding to the experimental measurements. Overall, the standard wall function approach for describing the near-wall flow proved to be more effective at increasingly higher distances from the jet centre. Such differences are related to the formulations employed by the two near-wall approaches, which led to changes in the predicted flow field around the fuel jet. Finally, the adoption of a reaction mechanism describing in detail the species concentration is mandatory whenever the reliable prediction of the NOx formation is of primary importance. The conclusion reached in this paper can be helpful for the development of reliable and cost-effective CFD models of turbine combustors.
Production of Volatile Fatty Acids in a Semi-Continuous Dark Fermentation of Kitchen Waste: Impact of Organic Loading Rate and Hydraulic Retention Time
Authors: Swiatkiewicz Justyna , Slezak Radoslaw , Krzystek Liliana , Ledakowicz Stanislaw
Published: May 2021

The aim of the study was to evaluate the possibility of using the process of dark fermentation to convert kitchen waste into valuable volatile fatty acids in a semi-continuous process at different values of the organic loading rate (2.5 and 5.0 gVS/(L × d)) and hydraulic retention time (5 and 10 d) using anaerobic mixed microbial consortia. The experiments were performed in a bioreactor of working volume 8L with pH control. The maximum volatile fatty acids yield in a steady state (22.3 g/L) was achieved at the organic loading rate of 5.0 gVS/(L × d) and HRT of 10 days. The main products of dark fermentation were acetic and butyric acids, constituting, respectively, 35.2–47.7% and 24.1–30.0% of all identified volatile fatty acids. Additionally, at the beginning of the fermentation and in a steady-state condition, the microbial population analysis (16S rDNA) of the fermentation mixture with the most effective volatile fatty acids generation has been performed to monitor the DF microflora development. The dominant microorganisms at a phylum level in a steady state were Firmicutes (44.9%) and Bacteroidetes (30.1%), which indicate the main role of those phyla in the volatile fatty acids synthesis.
Effects of Impurities on Pre-Doped and Post-Doped Membranes for High Temperature PEM Fuel Cell Stacks
Authors: Simon Araya Samuel , Thomas Sobi , Lotrič Andrej , Lennart Sahlin Simon , Liso Vincenzo , Andreasen Søren Juhl
Published: May 2021

In this paper, we experimentally investigated two high temperature polymer electrolyte membrane fuel cell (HT-PEMFC) stacks for their response to the presence of reformate impurities in an anode gas stream. The investigation was aimed at characterizing the effects of reformate impurities at the stack level, including in humidified conditions and identifying fault features for diagnosis purposes. Two HT-PEMFC stacks of 37 cells each with active areas of 165 cm2 were used with one stack containing a pre-doped membrane with a woven gas diffusion layer (GDL) and the other containing a post-doped membrane with non-woven GDL. Polarization curves and galvanostatic electrochemical impedance spectroscopy (EIS) were used for characterization. We found that both N2 dilution and impurities in the anode feed affected mainly the charge transfer losses, especially on the anode side. We also found that humidification alleviated the poisoning effects of the impurities in the stack with pre-doped membrane electrode assemblies (MEA) and woven GDL but had detrimental effects on the stack with post-doped MEAs and non-woven GDL. We demonstrated that pure and dry hydrogen operation at the end of the tests resulted in significant recovery of the performance losses due to impurities for both stacks even after the humidified reformate operation. This implies that there was only limited acid loss during the test period of around 150 h for each stack.
Analysis of Small Hydropower Generation Potential: (2) Future Prospect of the Potential under Climate Change
Authors: Jung Jaewon , Jung Sungeun , Lee Junhyeong , Lee Myungjin , Kim Hung Soo
Published: May 2021

The interest in renewable energy to replace fossil fuel is increasing as the problem caused by climate change has become more severe. In this study, small hydropower (SHP) was evaluated as a resource with high development value because of its high energy density compared to other renewable energy sources. SHP may be an attractive and sustainable power generation environmental perspective because of its potential to be found in small rivers and streams. The power generation potential could be estimated based on the discharge in the river basin. Since the river discharge depends on the climate conditions, the hydropower generation potential changes sensitively according to climate variability. Therefore, it is necessary to analyze the SHP potential in consideration of future climate change. In this study, the future prospect of SHP potential is simulated for the period of 2021 to 2100 considering the climate change in three hydropower plants of Deoksong, Hanseok, and Socheon stations, Korea. The results show that SHP potential for the near future (2021 to 2040) shows a tendency to be increased, and the highest increase is 23.4% at the Deoksong SPH plant. Through the result of future prospect, we have shown that hydroelectric power generation capacity or SHP potential will be increased in the future. Therefore, we believe that it is necessary to revitalize the development of SHP to expand the use of renewable energy. In addition, a methodology presented in this study could be used for the future prospect of the SHP potential.
Ultrasonic Signal Transmission Performance in Bolted Connections of Wood Structures under Different Preloads
Authors: Zhuang Zilong , Yu Yabin , Liu Ying , Chen Jiawei , Wang Zhengguang
Published: May 2021

In industrial applications, bolt connections are simple and economical, contributing to their popularity for use in wood packing boxes. However, they can easily fail when subjected to a continuous vibrational load under usual working conditions such as transportation and hoisting. Based on an ultrasonic technique, nondestructive evaluation can be used to quickly detect large-scale structures, but the complex propagation properties in wood limit its application. To solve this problem, a time-reversal method was adopted to predict the residual preload on bolted connections by focusing on the signals collected by wood structures, which helps to assess the structures’ reliability. In this study, the residual preload of bolted connections in wood structures was predicted using the deep-learning method, LSTM, one-dimensional Resnet and Densenet, and tree classification models. It was confirmed that the use of the time-reversal method for ultrasonic detection focused on the signals transmitted in bolted connections of wood structures and deep-learning methods are a feasible way to predict an ultrasonic transmission model.
Harvest Retention Survivorship of Endangered Whitebark Pine Trees
Authors: Murray Michael P. , Berg Jenny , Huggard David J.
Published: May 2021

Whitebark pine (Pinus albicaulis Engelm.) is a widely distributed high-elevation species in western North America that is threatened primarily by an introduced disease and other disturbances. In British Columbia, this tree is a component of harvested forests, yet knowledge of post-harvest survivorship and factors that promote successful retention is lacking. Our objectives are to describe the temporal attrition of retained mature whitebark pine trees and to identify factors that likely influence survivorship during the critical initial post-harvest period. We assessed five separate harvest units in southeastern British Columbia. Dendrochronological investigation revealed that retained trees experienced high annual mortality rates (3–16%) across harvest sites during the initial five-year post-harvest period. By eight years post-harvest, retention survivorship ranged from 17–80%. After eight years post-harvest, mortality rates drastically declined. The preponderance of fallen stems oriented towards the northeast suggests that storm system events arriving from the Pacific Ocean are the most significant drivers of blowdown. We estimate that survivorship is positively associated with shorter tree heights and longer crown lengths, a lack of disease cankers, a greater presence of rodent wounding, and higher numbers of surrounding retained trees. We found little effect based on slope and aspect. As these trees are an endangered species, harvest operations should be practiced cautiously in associated forests. We recommend carefully selecting retention trees, ensuring an adequate number of neighbor trees, and orienting retention patches to avoid predominant storm wind directions.
Genetic Variability of Alnus cordata (Loisel.) Duby Populations and Introgressive Hybridization with A. glutinosa (L.) Gaertn. in Southern Italy: Implication for Conservation and Management of Genetic Resources
Authors: Villani Fiorella , Castellana Simone , Beritognolo Isacco , Cherubini Marcello , Chiocchini Francesca , Battistelli Alberto , Mattioni Claudia
Published: May 2021

Alnus cordata (Loisel.) Duby (Neapolitan alder) is an endemic tree species with a restricted distribution range, limited to Corsica and southern Italy. The economic value of its wood, its rapid growth, the tolerance to drought stress and the nitrogen fixation capacity make A. cordata an excellent candidate for breeding, as well as for conservation and management of genetic resources. In this context, we evaluated the genetic variability of southern Italy populations and verified the hybridization capacity with the simpatric species A. glutinosa (L.) Gaertn. Eight pure A. cordata populations, two pure A. glutinosa populations and six mixed A. cordata/A. glutinosa populations located in southern Italy were analyzed using seven microsatellite markers. A low genetic diversity within and among populations was observed, but no inbreeding effects were evident. A variable frequency of F2 interspecific hybrids was observed in most of the mixed populations and few backcross individuals were scored. These results suggest a limited capacity of hybrid individuals to cross back with the parent species, reducing the risk of genetic pollution of A. cordata. This work provides meaningful knowledge for the conservation and management of the endemic species A. cordata, which represents a valuable source of biodiversity to be conserved.
Critical Factors of Industry 4.0 Implementation in an Emerging Country: Empirical Study
Authors: Dikhanbayeva Dinara , Tokbergenova Akmaral , Lukhmanov Yevgeniy , Shehab Essam , Pastuszak Zbigniew , Turkyilmaz Ali
Published: May 2021

The concept of Industry 4.0 is becoming more and more popular all over the world. The implementation of its assumptions in business practice changes the way companies operate. The enormous innovative potential of the Industry 4.0 concept and the intensive use of processes based on the implementation of advanced technologies in its assumptions have an impact on various industries in each country. The article attempts to analyze the critical factors for the implementation of Industry 4.0 in Kazakhstan. Primary and secondary data sources were used for this purpose. The majority of existing government initiatives and reports do not reflect the actual situation. Additionally, these materials do not always represent the experiences or positions of all the parties involved. Opinions of companies and organizations implementing Industry 4.0 solutions remain unexplored. The primary goal of the paper is to fill the cognitive gap by analyzing stakeholder responses and identifying the actual level of their awareness of the development of Industry 4.0. An additional intention of the authors was to empirically establish barriers that companies face while implementing the most desirable technologies, as well as to establish other critical factors, taking into account the specificity of the country under study. The results of the research can be used by policymakers, scientists and other stakeholders to develop forecasts and strategic plans, as well as to develop and conduct further research on the implementation processes of Industry 4.0 in Kazakhstan.
Stinging Nettles as Potential Food Additive: Effect of Drying Processes on Quality Characteristics of Leaf Powders
Authors: Nallan Chakravartula Swathi Sirisha , Moscetti Roberto , Farinon Barbara , Vinciguerra Vittorio , Merendino Nicolò , Bedini Giacomo , Neri Lilia , Pittia Paola , Massantini Riccardo
Published: May 2021

Stinging nettle (Urtica dioica L.) is a ubiquitous, multi-utility, and under-utilized crop with potential health benefits owing to its nutritional and bioactive components. The objective of the work is to produce powders by drying wild stinging nettle leaves as a storable, low-cost functional additive to be used in bakery and ready-to-cook products. Convective drying (CD) and freeze-drying (FD) were applied on unblanched (U) or blanched (B) leaves, which were then milled to nettle powders (NPs). The obtained NPs were evaluated for selected physicochemical (moisture, color), techno-functional (flow indices, hygroscopicity), and phytochemical (pigments, phenols) characteristics as well as mineral contents. Blanching improved mass transfer and reduced the oxidative degradation of pigments during drying, but it caused a loss of total phenols content, antioxidant activity, and potassium content. As for the drying method, CD resulted in better flow properties (i.e., Carr Index and Hausner Ratio), while FD retained better the color, pigments, magnesium content, phenolic, and antioxidant parameters. Overall, the evaluated processing methods resulted in different technological properties that can allow for better evaluation of NPs as a food additive or ingredient. Among the NPs, blanched and freeze-dried powders despite showing inferior technological properties can be recommended as more suitable ingredients targeted f or food enrichment owing to better retention of bio-active components.
Interaction of the Exopolysaccharide from Lactobacillus plantarum YW11 with Casein and Bioactivities of the Polymer Complex
Authors: Zhang Min , Lai Tiantian , Yao Mengke , Zhang Man , Yang Zhennai
Published: May 2021

There has been an increased application of exopolysaccharide (EPS)-producing lactic acid bacteria (LAB) in fermented dairy products, but interactions between EPS and casein (CAS), and bioactivities of their complex are poorly studied. In this study, EPS produced by Lactobacillus plantarum YW11 (EPS-YW11) was studied for interactions with CAS in a simulated fermentation system acidified by D-(+)-gluconic acid δ-lactone. The results showed that there was interaction between EPS-YW11 and CAS when EPS (up to 1%, w/v) was added to the casein solution (3%, w/v) as observed with increased viscoelasticity, water holding capacity, ζ-potential and particle size of EPS-YW11/CAS complex compared with CAS alone. Microstructural analysis showed that a higher concentration of EPS facilitated more even distribution of CAS particles that were connected through the polysaccharide chains. Infrared spectroscopy further confirmed interactions between EPS and CAS by intermolecular hydrogen bonding, electrostatic and hydrophobic contacts. Further evaluation of the bioactivities of EPS-YW11/CAS complex revealed significantly increased antibiofilm, antioxidation, and bile acids binding capacity. The present study provides further understanding on the mechanism of interactions between EPS produced by LAB and CAS, which would benefit potential applications of EPS in fermented dairy products with enhanced functionality.
Effect of Two Combined Functional Additives on Yoghurt Properties
Authors: Szołtysik Marek , Kucharska Alicja Z. , Dąbrowska Anna , Zięba Tomasz , Bobak Łukasz , Chrzanowska Józefa
Published: May 2021

The aim of the research was the analysis of yoghurts enriched with blue honeysuckle berries dry polyphenolic extract and new preparation of resistant starch. The additives were introduced individually at concentration 0.1% (w/v) and in mixture at final concentration of 0.1 and 0.2% of both components. Yogurt microflora, pH, and its physicochemical and antioxidant properties were examined over 14 days of storage under refrigerated conditions. Studies showed that both substances can be successfully used in yoghurt production. Yoghurt microflora es. S. thermophilus and Lb. delbrueckii subsp. bulgaricus counts appeared to be higher in samples supplemented with these additives comparing to control yoghurt by 3–8%. More stimulating effect on their growth, especially on S. thermophilus, revealed resistant starch. Addition of this polysaccharide improved also the rheological properties of yogurts, which showed higher viscosity than samples produced without it. Addition of honeysuckle berries preparation significantly influenced the yogurts’ color, giving them deep purple color, and their antioxidant potential. During storage, contents of anthocyanin and iridoid compounds were decreasing, but antioxidant activity in the products remained stable.
Astronomical Seeing at Maidanak Observatory during the Year 2018
Authors: Tillayev Yusufjon , Azimov Azimjon , Hafizov Aktam
Published: May 2021

Results of a four-month campaign of astronomical seeing measurements at Maidanak astronomical observatory (MAO) are presented. A differential image motion monitor (DIMM) was used for seeing estimations during the period from August to November 2018. The observation was organized within the framework of a site testing for a new telescope which is going to be installed at the observatory. The median value of seeing for the entire period was determined as 0.70 arcseconds, which agrees well with the results of the period 1996–2003. The comparison of monthly values showed that some monthly median values differ from the seasonal trend of the previous period.
Network Protein Interaction in the Link between Stroke and Periodontitis Interplay: A Pilot Bioinformatic Analysis
Authors: Leira Yago , Mascarenhas Paulo , Blanco Juan , Sobrino Tomás , Mendes José João , Machado Vanessa , Botelho João
Published: May 2021

The clinical interaction between stroke and periodontitis has been consistently studied and confirmed. Hence, exploring potentially new protein interactions in this association using bioinformatic strategies presents potential interest. In this exploratory study, we conducted a protein–protein network interaction (PPI) search with documented encoded proteins for both stroke and periodontitis. Genes of interest were collected via GWAS database. The STRING database was used to predict the PPI networks, first in a sensitivity purpose (confidence cut-off of 0.7), and then with a highest confidence cut-off (0.9). Genes over-representation was inspected in the final network. As a result, we foresee a prospective protein network of interaction between stroke and periodontitis. Inflammation, pro-coagulant/pro-thrombotic state and, ultimately, atheroma plaque rupture is the main biological mechanism derived from the network. These pilot results may pave the way to future molecular and therapeutic studies to further comprehend the mechanisms between these two conditions.
Methylation of Estrogen Receptor 1 Gene in the Paraspinal Muscles of Girls with Idiopathic Scoliosis and Its Association with Disease Severity
Authors: Janusz Piotr , Chmielewska Małgorzata , Andrusiewicz Mirosław , Kotwicka Małgorzata , Kotwicki Tomasz
Published: May 2021

Idiopathic scoliosis (IS) is a multifactorial disease with epigenetic modifications. Tissue dependent and differentially methylated regions (T-DMRs) may regulate tissue-specific expression of the estrogen receptor 1 gene (ESR1). This study aimed to analyze methylation levels within T-DMR1 and T-DMR2 and its concatenation with ESR1 expression of IS patients. The study involved 87 tissue samples (deep paravertebral muscles, both on the convex and the concave side of the curve, and from back superficial muscles) from 29 girls who underwent an operation due to IS. Patient subgroups were analyzed according to Cobb angle ≤70° vs. >70°. Methylation was significantly higher in the superficial muscles than in deep paravertebral muscles in half of the T-DMR1 CpGs and all T-DMR2 CpGs. The methylation level correlated with ESR1 expression level on the concave, but not convex, side of the curvature in a majority of the T-DMR2 CpGs. The T-DMR2 methylation level in the deep paravertebral muscles on the curvature’s concave side was significantly lower in patients with a Cobb angle ≤70° in four CpGs. DNA methylation of the T-DMRs is specific to muscle tissue location and may be related to ESR1 expression regulation. Additionally, the difference in T-DMR2 methylation may be associated with IS severity.