bluuebunny/crossref_metadata_2025 huggingface dataset:
Etlik Piliç Karma Yemlerinde Farklı Yağ Kaynağı Kullanımının Büyüme Performansı ve Serum Lipit Konsantrasyonuna Etkisi
Authors: TÜZÜN Ahmet Engin , YILDIZ Alpönder
Published: August 2020

Bu çalışma, karma yemlere farklı yağ kaynağı kullanımının etlik piliçlerin büyüme performansı parametreleri ile serum lipitleri trigliserit, total kolesterol, HDL ve LDL konsantrasyonuna etkisini belirlemek amacı ile yapılmıştır. Denemede toplam 640 adet günlük yaşta karışık cinsiyette etlik piliç civcivi (Ross 308) kullanılmıştır. Denemede; ayçiçek yağı, kanola yağı, sığır iç yağı (%50 don yağ + %50 çöz yağ) ve bu yağların eşit oranlarda karıştırılmasından (%25 ayçiçek yağı + %25 kanola yağı + %25 don yağ + %25 çöz yağ) oluşan mix yağ olarak adlandırılan 4 farklı muamele grubu oluşturulmuştur. Muameleler sekiz tekerrürlü ve her tekerrürde 20 civciv olacak şekilde rastgele dağıtılmıştır. Başlatma yemi (1-21.gün; % 23 HP, 3000 kkal ME/kg) %5 ve bitirme yemi (22-42.gün; % 20 HP, 3200 kkal ME/kg) %7.5 seviyesinde ilgili yağ kaynağından içerecek şekilde mısır-soya küspesi ağırlıklı olarak hazırlanmıştır. Altı hafta süren deneme boyunca yem ve su ad libitum olarak verilmiştir. Deneme sonucunda etlik piliç karma yemlerine farklı yağ kaynağı kullanımının canlı ağırlık artışı üzerine önemli bir etkisi olmamıştır (P>0.05). Ayçiçek yağı ilaveli yem ile beslenen piliçlerin yem tüketimi ve yemden yararlanma oranı kanola yağı ilaveli yem ile beslenen piliçlerle benzer, iç ve mix yağ ilaveli yem ile beslenen piliçlerden önemli seviyede düşük olmuştur (P<0.05). Etlik piliç karma yemlerine farklı yağ kaynağı ilavesinin serum trigliserit, total kolesterol, HDL ve LDL konsantrasyonu üzerine önemli bir etkisi olmamıştır ( P>0.05). Ancak erkek piliçlerin total kolesterol, HDL ve LDL konsantrasyonları dişi piliçlerden daha yüksek olmuştur (P<0.05). Etlik piliç rasyonlarında ayçiçeği yağı kullanımının performansı diğer yağ kaynaklarına göre iyileştirdiği ve hayvansal yağların bitkisel yağlar ile karışım olarak kullanılmasının daha iyi olduğu ve yağ kaynaklarının serum lipitlerini etkilemediği görülmüştür.
Who Votes After Their Registration is Cancelled? Evidence from North Carolina
Authors: Morris Kevin
Published: August 2020

Voter list maintenance has received increasing attention in the press and from advocacy groups in the past few years. Little scholarly work, however, has detailed who is removed - or “purged” - despite no change in their legal eligibility to vote. By leveraging voter registration and provisional ballot data from North Carolina we identify individuals who were removed from the rolls between 2010 and 2016 despite no apparent change in their eligibility to vote and cast a provisional ballot in the 2016 presidential election. Although we find that minority voters were less likely than white voters to be removed overall, they were significantly more likely to cast a provisional ballot after being removed. Minorities who voted after being removed were also substantially less likely to have their provisional ballots counted than white voters. This paper presents the first evidence that imprecise voter list maintenance might disproportionately disenfranchise voters of color.
Drivers and Limiters of Policy Change: Interest Group Competition and Path Dependence in State Charter School Policies
Authors: Holyoke Thomas
Published: August 2020

Policies change slowly and incrementally after enactment, if they change at all. Notions of path dependence hold that the influence early decisions and institutional designs hold over policy prevent serious change. Early decision lock-in ways in which benefitting interests interact with institutions regarding the policy. Policies are therefore highly resistant to efforts of interest groups, lawmakers, and even the public to change their trajectories. I test the influence of path dependent inertia versus ongoing efforts of interest groups regarding the shape of charter school policies in the American states from 1996 to 2016. I find that strict notions of path dependence do not manifest in charter policies, and that pressure from competing interest groups starts to emerge a few years after enactment, influence that can slowly start to change the arc of a policy’s development despite the influence of institutions and expectations set at the time of its enactment.
Replicable Privacy: Enabling Replication on Sensitive Internet Data
Authors: Baleato Suso , Honaker James , Crosas Merce
Published: August 2020

In this paper we present the first results of a privacy-preserving system designed to enable safe sharing and replication of statistical analysis computed from sensitive datasets. Our system is composed of three elements, all of them made available to the scientific community thanks to an effort lead by the Institute for Quantitative Social Science at Harvard University. First, we use differential privacy, a privacy-preserving technique that avoids re-identification while preserving the statistical properties of the sensitive dataset. Second, we use the Dataverse open source software to share the resulting statistics consistently with FAIR principles, including automatic citation, persistent identifiers and data provenance. Third, we apply a simplified Datatags implementation to enable access to any sensitive dataset required for replication.
Inclusion by Design: Measuring Minority Inclusion Comparatively to Assess Institutions for Divided Societies
Authors: Lublin David
Published: August 2020

I propose new cross-national measures of minority inclusion based on ethnic minority support for government parties. These measures will greatly aid efforts to design political institutions intended to achieve greater minority inclusion and to ameliorate ethnic conflict by allowing for more sophisticated quantitative cross-country assessments of the effect of institutions on inclusion. I further explain how the proposed measure can be estimated to a useful degree of accuracy through multiple methods, including polls and ecological inference from ethnic and election data.
Data-driven Democracy? Automated Decision-making, Difference and Preferences
Authors: Benitez Jesus , Gomez-Reino Margarita , Suarez Alberto
Published: August 2020

The mass adoption of the Internet has produced a deluge of data, a phenomenon termed as the 'new oil' of the digital economy. When this data is combined with algorithms, it enables the creation of computer systems capable to take decisions depending on context. Initially used as 'expert' systems in controlled environments only, they are now starting to enter the public space in the form of devices such as self-driving cars or drones, but also increasingly as part of decision making systems with direct political effects. In this paper, we evaluate the destabilization potential of algorithmic decision making looking at the normative foundations of the theory of democracy, focusing on the contributions of preference formation with an emphasis on diversity and inclusion.
Why Civil Wars are Fought By Extremists: Polarization, Abstention and the Cost of Participation
Authors: Kydd Andrew
Published: August 2020

Why are civil wars fought by extremists rather than moderates? The median voter theorem holds that organizations contesting for power will shift to the center of the ideological spectrum to maximize their support. Such models assume that supporting means voting and that it is relatively costless. When it is costly for individuals to support organizations contesting for power, such as in civil war contexts, the central tendency is constrained by the cost of participation. In equilibrium, those to either extreme are more likely to participate, moderates tend to abstain. The range of moderates who abstain grows larger the more costly participation becomes. I develop a spatial model of participation that exhibits these features and discuss its implications in the case of the civil wars in Central American in the 1970s and 1980s and Syrian Civil War.
Social service provision dilemmas faced by Social workers in the management of Zimbabwean welfare organizations: a desk review.
Authors: Gudyanga Denford
Published: August 2020

The provision of Zimbabwean social services ranges from public health to education and housing. Globally, these services have been put in place by governments and stakeholders to promote citizens’ welfare. Through a desk review, this paper briefly discusses dilemmas social work managers face daily. These include matching clients’ needs to government ideology underpinning service provision, negotiating with overarching political influence and lack of adequate resources as well as ethical dilemmas stemming from a profession’s code of conduct. The paper ends by recommending that Zimbabwean social workers should aspire for high management and or legislative positions which empowers them to make meaningful policy decisions that ensure the promotion of the dignity of service users. Further, lobbying legislators and social service funders to put the needs of service users first should be an ongoing cause to champion social justice and equity within the Zimbabwean social service sector.
Gut Microbiome Composition is Associated with Age and Memory Performance in Pet Dogs
Authors: Kubinyi Eniko , Bel Rhali Soufiane , Sándor Sára , Szabó Attila , Felföldi Tamás
Published: August 2020

Gut microbiota can crucially influence behavior and neurodevelopment. Dogs show unique similarities to humans in their physiology and may naturally develop dementia-like cognitive decline. We assessed 29 pet dogs’ cognitive performance in a memory test and analyzed the bacterial 16S rRNA gene from fecal samples collected right after the behavioral tests. The major phyla identified in the dog microbiomes were Bacteroidetes, Firmicutes, and Fusobacteria, each represented by >20% of the total bacterial community. Fewer Fusobacteria were found in older dogs and better memory performance was associated with a lower proportion of Actinobacteria. Our preliminary findings support the existence of links between gut microbiota, age, and cognitive performance in pet dogs.
Effects of Intermittent Mild Cold Stimulation on mRNA Expression of Immunoglobulins, Cytokines, and Toll-Like Receptors in the Small Intestine of Broilers
Authors: Li Shuang , Li Jianhong , Liu Yanhong , Li Chun , Zhang Runxiang , Bao Jun
Published: August 2020

Appropriate cold stimulation can improve immune function and stress tolerance in broilers. In order to investigate the effect of intermittent mild cold stimulation on the intestinal immunity of broilers, 240 healthy one-day-old Ross 308 chickens were randomly divided into three groups: the control group (CC) housed in climatic chambers under usual rearing ambient temperature with a gradual 3.5 °C decrease per week; group II (C3) and group III (C6) to which cold stimulation at 3 °C below the temperature used in CC was applied every two days for 3 and 6 h, respectively, from day 15 to 35, and at the same temperature used in CC from day 35 to 43. The mRNA expression levels of immunoglobulins (IgA and IgG), cytokines (IL2, IL6, IL8, IL17, and IFNγ), and Toll-like receptors (TLR2, TLR4, TLR5, TLR7, and TLR21) were investigated in duodenum, jejunum, and ileum tissue samples on days 22, 29, 35, and 43. From day 15 to 35, mRNA expression of IL2 and IFNγ was increased in the intestine of broilers. After one week of cold stimulation on day 43, mRNA levels of immunoglobulins, cytokines, and Toll-like receptors (TLRs) stabilized. Collectively, the findings indicate that cold stimulation at 3 °C below the usual rearing temperature had a positive impact on intestinal immunity of broilers.
Microbial Composition of Oral Biofilms after Visible Light and Water-Filtered Infrared a Radiation (VIS+wIRA) in Combination with Indocyanine Green (ICG) as Photosensitizer
Authors: Burchard Thomas , Karygianni Lamprini , Hellwig Elmar , Wittmer Annette , Al-Ahmad Ali
Published: August 2020

In view of increasing antibiotic resistance, antimicrobial photodynamic therapy (aPDT) is an alternative treatment method used to eradicate the microbial community of oral biofilms that can be responsible for different oral infections. In order to investigate changes in the microbial composition after application of aPDT with visible light and water-filtered infrared A (VIS+wIRA) in combination with indocyanine green (ICG), oral microorganisms of the initial and mature biofilm were evaluated by mass spectrometry (MALDI-TOF-MS). To determine surviving microorganisms using MALDI-TOF-MS, an in situ biofilm was irradiated with VIS+wIRA for five minutes in the presence of ICG (300 and 450 µg/mL, respectively). Treatment with chlorhexidine (0.2%) served as positive control. Identified microorganisms of the initial biofilm treated with ICG showed a clear reduction in diversity. The microbial composition of the mature oral biofilm also showed changes after the implementation of aPDT, which mainly resulted in a shift in the percentage of bacterial species. The resulting destruction of the microbial balance within the oral biofilm by aPDT using VIS+wIRA and ICG can be seen as an advantageous supplementary approach in the adjunctive treatment of periodontitis and peri-implantitis.
3D Reconstruction of a Single Bubble in Transparent Media Using Three Orthographic Digital Images
Authors: Zhang Yiping , Que Xinzhe , Hu Mengxian , Zhou Yongchao
Published: August 2020

This work proposed a method to reconstruct the 3D bubble shape in a transparent medium utilizing the three orthographic digital images. The bubble was divided into several ellipse slices. The azimuth angle and projection parameters were extracted from the top view image, while the formulas for dimensionless semi-axes were derived according to the geometric projection relationship. The elliptical axes of each layer were calculated by substituting the projection width into the formulas. All layers of slices were stacked to form the 3D bubble shape. Reconstruction accuracy was evaluated with spheres, ellipsoids, and inverted teardrops. The results show that the position contributes greatly to the reconstruction accuracy of the bubbles with serious horizontal deformation. The method in Bian et al. (2013) is sensitive to both horizontal and vertical deformations. The vertical deformation has little influence on the method in Fujiwara et al. (2004), whereas the horizontal deformation greatly impacts its accuracy. The method in this paper is negligibly affected by vertical deformation, but it does better in reconstructing single bubbles with large horizontal deformation. The azimuth angle affects the accuracy of the methods in Bian et al. (2013) and Fujiwara et al. (2004) more than the method in this paper.
A Novel Virtual-Structure Formation Control Design for Mobile Robots with Obstacle Avoidance
Authors: Chen Xuanlin , Huang Fanghao , Zhang Yougong , Chen Zheng , Liu Shuo , Nie Yong , Tang Jianzhong , Zhu Shiqiang
Published: August 2020

The cooperative motion of multiple mobile robots has attracted wide attention due to its advantages in military, marine and aerospace fields, and formation control has become a significant technology in the realization of these tasks. However, most of the existing formation control designs of mobile robots do not consider the practical obstacles in the environment, and the maintenance of both formation and trajectory tracking while confronting the obstacles is still a challenging issue. Therefore, in this paper, a virtual-structure-based formation control approach is designed with obstacle avoidance for a system with multiple mobile robots. The basic trajectory is generated for each robot in the group and parameterized to keep the group in formation. A trajectory generator is then established regarding the obstacles, where a potential function is designed to adjust the basic trajectory and replan the reference trajectory to achieve obstacle avoidance. Then, a novel design for the path parameter is proposed to improve the performance of the robot group when encountering obstacles. Finally, a tracking controller is designed to achieve good tracking performance for robots, and the guaranteed performance is achieved via the Lyapunov theorem. A comparative simulation with three sets is carried out, where an objective function Fobj is designed to evaluate the tracking performance in the presence of obstacles. Besides this, a real experiment is implemented to further verify the effectiveness. The simulation and experimental results verify the good formation and tracking performance of the proposed design for a system with multiple mobile robots with obstacle avoidance.
Effect of Melting–Recycling Cycles and Mechanical Fracture on the Thermoplastic Materials Composed of Thermoplastic Polyurethane and Polypropylene Waste Blends
Authors: Lin Ting An , Lin Jia-Horng , Bao Limin
Published: August 2020

With appropriate conditions, thermoplastic materials possess a good reversible ability. They are prone to exceed the reversibility range when being repeatedly processed as they cannot bear high temperatures. Therefore, this study aims to explore the impacts of the melting–recycling cycles and the presence of a compatibilizer on the omnipresent thermoplastic materials. Additionally, the tensile properties, morphology, and thermal properties are studied. The feasibility of multiple utilizations and differentiation effects are examined afterward. In this study, recycled or mechanically damaged thermoplastic polyurethane (T)/polypropylene (P) waste blends are used as the raw materials for the hot-pressing cycle, while maleic anhydride grafted polypropylene (MA) is used as the compatibilizer, thereby simulating the waste compounds. Next, the T/P/MA blends that undergo post-2nd and post-3rd recycling are evaluated for comprehensive change. The test results indicate that without MA, T/P blends exhibit significant differentiation effects due to an increase in the polypropylene content and multiple melting–recycling cycles. By contrast, the presence of MA mitigates the overall differentiation effect of T/P blends. The ultimate purpose of this study is to treat waste compounds via a simple hot-pressing approach to produce useful materials that can be used again. As a result, this study attenuates the negative influences of plastic waste on the environment while achieving sustainable development.
A Systematic Review of Defensive and Offensive Cybersecurity with Machine Learning
Authors: Aiyanyo Imatitikua D. , Samuel Hamman , Lim Heuiseok
Published: August 2020

This is a systematic review of over one hundred research papers about machine learning methods applied to defensive and offensive cybersecurity. In contrast to previous reviews, which focused on several fragments of research topics in this area, this paper systematically and comprehensively combines domain knowledge into a single review. Ultimately, this paper seeks to provide a base for researchers that wish to delve into the field of machine learning for cybersecurity. Our findings identify the frequently used machine learning methods within supervised, unsupervised, and semi-supervised machine learning, the most useful data sets for evaluating intrusion detection methods within supervised learning, and methods from machine learning that have shown promise in tackling various threats in defensive and offensive cybersecurity.
Bayesian Calibration of Hysteretic Parameters with Consideration of the Model Discrepancy for Use in Seismic Structural Health Monitoring
Authors: Ceravolo Rosario , Faraci Alessio , Miraglia Gaetano
Published: August 2020

Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model discrepancy term to account for the differences between model-based predictions and real observations. Indeed, the goal of this work is to investigate model-driven seismic structural health monitoring procedures based on a Bayesian uncertainty quantification framework, and thus make relevant considerations for its use in the seismic structural health monitoring, focusing on masonry structures. Specifically, the Bayesian inference has been applied to the calibration of nonlinear hysteretic systems to both provide: (i) most probable values (MPV) of the parameters following the calibration; and (ii) estimates of the model discrepancy posterior distribution. The effect of the model discrepancy in the calibration is first illustrated recurring to a single degree of freedom using a Bouc–Wen type oscillator as a numerical benchmark. The model discrepancy is then introduced for calibrating a reference nonlinear Bouc–Wen model derived from real data acquired on a monitored masonry building. The main novelty of this study is the application of the framework of uncertainty quantification on models representing data measured directly on masonry structures during seismic events.
Experimental Testing and Strut-and-Tie Modeling of Full-Scale Precast Concrete Girders with FRP Repaired End Regions
Authors: Zhao Hang , Andrawes Bassem
Published: August 2020

Bridges located in cold regions are susceptible to extreme deterioration due to harsh climate conditions. Distressing of girder’s end regions is among the most common damage types in these bridges. This work focuses on addressing this type of damage through the use of a fiber reinforced polymer (FRP) repair scheme. Three-point-bending tests are conducted on the control, damaged, mortar repair and carbon fiber reinforced polymer (CFRP) repair cases of bridge girders that are taken out of service. Test results are analyzed to investigate the effectiveness of FRP to repair precast concrete (PC) girders with damaged end regions. Furthermore, since the damage is mainly localized at girder’s end region where beam theory is invalid, the behavior of FRP repaired end region (D-region) is studied using the strut-and-tie method. Based on the test results, a strut-and-tie model (STM) is proposed to estimate the shear capacity of the girder with the FRP repaired end region. The outcome of the experimental work shows that the FRP laminate repair system is effective in recovering and improving the shear behavior of the girder including both peak force and ductility. The proposed STM can be used to predict the shear capacity of the PC girder with a similar damage pattern to the one considered in this study.
Pharmacological and Cosmeceutical Potential of Seaweed Beach-Casts of Macaronesia
Authors: Zárate Rafael , Portillo Eduardo , Teixidó Sílvia , Carvalho Miguel A. A. Pinheiro de , Nunes Nuno , Ferraz Sónia , Seca Ana M. L. , Rosa Gonçalo P. , Barreto Maria Carmo
Published: August 2020

Seaweed beach-casts are a seasonal phenomenon that regularly deposits tons of algae biomass on beaches, which are usually disposed of in landfills. The present work aimed to contribute to the valorization of this biomass by studying bioactivities that reveal its potential in the pharmaceutical and/or cosmeceutical industries. Methanol and ethanol extracts and fractions from 15 beach-casts biomass were tested for a range of bioactivities. Eight of the most active samples exhibit IC50 values between 11.38 µg/mL and 19.28 µg/mL and selectivity indexes higher than 3.8, against NCI-H1299 (lung cancer) and T47D (breast cancer). Concerning antiaging potential, all the extracts tested presented UV protection, with SPF values above 30, like the standard sunscreen. Regarding aging-related enzymes, 24 samples were tyrosinase inhibitors exhibiting IC50 values from 9.01 µg/mL to 200.09 µg/mL. Eight extracts inhibited collagenase (IC50 < 248.76 µg/mL), two of them more actively than positive control EDTA (IC50 = 59.26 µg/mL). In addition to UV protection, the cumulative effect of antityrosinase and anticollagenase activities shown by the samples suggest that they may play a significant role in preventing skin photoaging. The results obtained demonstrate the high potential of beach-cast seaweed biomass as sources of cosmetic bioproducts with antiaging effects, and of selective cytotoxic metabolites.
Using Machine Learning Models and Actual Transaction Data for Predicting Real Estate Prices
Authors: Pai Ping-Feng , Wang Wen-Chang
Published: August 2020

Real estate price prediction is crucial for the establishment of real estate policies and can help real estate owners and agents make informative decisions. The aim of this study is to employ actual transaction data and machine learning models to predict prices of real estate. The actual transaction data contain attributes and transaction prices of real estate that respectively serve as independent variables and dependent variables for machine learning models. The study employed four machine learning models-namely, least squares support vector regression (LSSVR), classification and regression tree (CART), general regression neural networks (GRNN), and backpropagation neural networks (BPNN), to forecast real estate prices. In addition, genetic algorithms were used to select parameters of machine learning models. Numerical results indicated that the least squares support vector regression outperforms the other three machine learning models in terms of forecasting accuracy. Furthermore, forecasting results generated by the least squares support vector regression are superior to previous related studies of real estate price prediction in terms of the average absolute percentage error. Thus, the machine learning-based model is a substantial and feasible way to forecast real estate prices, and the least squares support vector regression can provide relatively competitive and satisfactory results.
Stationary Target Identification in a Traffic Monitoring Radar System
Authors: Lim Hae-Seung , Lee Jae-Eun , Park Hyung-Min , Lee Seongwook
Published: August 2020

Recently, as one of the intelligent transportation systems, radar systems that monitor traffic on the road have received attention. To ensure the reliable detection performance of the traffic monitoring radar, it is necessary to distinguish stationary road structures from moving vehicles. Therefore, in this paper, we propose a method for discriminating stationary targets in traffic monitoring radar systems. First, we install a frequency-modulated continuous wave radar system using a center frequency of 24.15 GHz on an overpass to monitor multiple lanes on the road. Then, we process the raw data obtained by the radar sensor to extract target information such as the distance, angle, velocity, and radar cross-section. Finally, we analyze the target characteristics in the angle-velocity domain to classify stationary targets and moving vehicles. In this domain, stationary targets appear as points lying around a straight line, and if we estimate that line, we can extract the stationary targets among all targets. To find the trend line, we use a random sample consensus-based estimation method, which can extract a dominant line component from a set of sample points. Through the proposed method, we can effectively remove the stationary targets in the field of view of the radar system.
Bi-LSTM Model to Increase Accuracy in Text Classification: Combining Word2vec CNN and Attention Mechanism
Authors: Jang Beakcheol , Kim Myeonghwi , Harerimana Gaspard , Kang Sang-ug , Kim Jong Wook
Published: August 2020

There is a need to extract meaningful information from big data, classify it into different categories, and predict end-user behavior or emotions. Large amounts of data are generated from various sources such as social media and websites. Text classification is a representative research topic in the field of natural-language processing that categorizes unstructured text data into meaningful categorical classes. The long short-term memory (LSTM) model and the convolutional neural network for sentence classification produce accurate results and have been recently used in various natural-language processing (NLP) tasks. Convolutional neural network (CNN) models use convolutional layers and maximum pooling or max-overtime pooling layers to extract higher-level features, while LSTM models can capture long-term dependencies between word sequences hence are better used for text classification. However, even with the hybrid approach that leverages the powers of these two deep-learning models, the number of features to remember for classification remains huge, hence hindering the training process. In this study, we propose an attention-based Bi-LSTM+CNN hybrid model that capitalize on the advantages of LSTM and CNN with an additional attention mechanism. We trained the model using the Internet Movie Database (IMDB) movie review data to evaluate the performance of the proposed model, and the test results showed that the proposed hybrid attention Bi-LSTM+CNN model produces more accurate classification results, as well as higher recall and F1 scores, than individual multi-layer perceptron (MLP), CNN or LSTM models as well as the hybrid models.
Phonocardiography Signals Compression with Deep Convolutional Autoencoder for Telecare Applications
Authors: Chien Ying-Ren , Hsu Kai-Chieh , Tsao Hen-Wai
Published: August 2020

Phonocardiography (PCG) signals that can be recorded using the electronic stethoscopes play an essential role in detecting the heart valve abnormalities and assisting in the diagnosis of heart disease. However, it consumes more bandwidth when transmitting these PCG signals to remote sites for telecare applications. This paper presents a deep convolutional autoencoder to compress the PCG signals. At the encoder side, seven convolutional layers were used to compress the PCG signals, which are collected on the patients in the rural areas, into the feature maps. At the decoder side, the doctors at the remote hospital use the other seven convolutional layers to decompress the feature maps and reconstruct the original PCG signals. To confirm the effectiveness of our method, we used an open accessed dataset on PHYSIONET. The achievable compress ratio (CR) is 32 when the percent root-mean-square difference (PRD) is less than 5%.
A New Generation of Bio-Composite Thermoplastic Filaments for a More Sustainable Design of Parts Manufactured by FDM
Authors: Calì Michele , Pascoletti Giulia , Gaeta Massimiliano , Milazzo Giovanni , Ambu Rita
Published: August 2020

The most recent developments of Fused Deposition Modelling (FDM) techniques are moving the application of Additive Manufacturing (AM) technologies toward new areas of investigation such as the biomedical, aerospace, and marine engineering in addition to the more consolidated industrial and civil fields. Some specific characteristics are required for the components designed for peculiar applications, such as complex geometries, lightweight, and high strength as well as breathability and aesthetic appearance specifically in the biomedical field. All these design specifications could be potentially satisfied by manufacturing with 3D printing techniques. Moreover, the development of purpose-dedicated filaments can be considered a key factor to successfully meet all the requirements. In this paper, fabrication and applications of five new thermoplastic materials with fillers are described and analyzed. They are organic bio-plastic compounds made of polylactic acid (PLA) and organic by-products. The growing interest in these new composite materials reinforced with organic by-products is due to the reduction of production management costs and their low environmental impact. In this study, the production workflow has been set up and described in detail. The main properties of these new thermoplastic materials have been analyzed with a major emphasis on strength, lightweight, and surface finish. The analysis showed that these materials can be particularly suitable for biomedical applications. Therefore, two different biomedical devices were selected and relative prototypes were manufactured with one of the analyzed thermoplastic materials. The feasibility, benefits, and performance of the thermoplastic material considered for these applications were successfully assessed.
Empirical Analysis and Geomechanical Modelling of an Underground Water Reservoir for Hydroelectric Power Plants
Authors: Menéndez Javier , Schmidt Falko , Konietzky Heinz , Bernardo Sánchez Antonio , Loredo Jorge
Published: August 2020

The European Union policy of encouraging renewable energy sources and a sustainable and safe low-carbon economy requires flexible energy storage systems (FESSs), such as pumped-storage hydropower (PSH) systems. Energy storage systems are the key to facilitate a high penetration of the renewable energy sources in the electrical grids. Disused mining structures in closed underground coal mines in NW Spain have been selected as a case study to analyze the construction of underground pumped-storage hydropower (UPSH) plants. Mine water, depth and subsurface space in closured coal mines may be used for the construction of FESSs with reduced environmental impacts. This paper analyzes the stability of a network of tunnels used as a lower water reservoir at 450 m depth in sandstone and shale formations. Empirical methods based on rock mass classification systems are employed to preliminarily design the support systems and to determinate the rock mass properties. In addition, 3D numerical modelling has been conducted in order to verify the stability of the underground excavations. The deformations and thickness of the excavation damage zones (EDZs) around the excavations have been evaluated in the simulations without considering a support system and considering systematic grouted rock bolts and a layer of reinforced shotcrete as support system. The results obtained show that the excavation of the network of tunnels is technically feasible with the support system that has been designed.
Characterizing Black Carbon Emissions from Gasoline, LPG, and Diesel Vehicles via Transient Chassis-Dynamometer Tests
Authors: Park Gyutae , Kim Kyunghoon , Park Taehyun , Kang Seokwon , Ban Jihee , Choi Siyoung , Yu Dong-Gil , Lee Sanguk , Lim Yunsung , Kim Sunmoon , Lee Jongtae , Woo Jung-Hun , Lee Taehyoung
Published: August 2020

With global anthropogenic black carbon (BC) emissions increasing, automobiles are significantly contributing as the major source of emissions. However, the appropriate regulations of BC emissions from vehicles are not in place. This study examined BC emissions following fuel types (gasoline, liquefied petroleum gas (LPG), and diesel) and engine combustion (gasoline direct injection (GDI) and multi-port injection (MPI) for gasoline vehicles) with emission regulations. To this end, chassis dynamometer and aethalometer (AE33) were used. Driving modes created by the National Institute of Environmental Research (NIER) and emission certification modes (CVS-75 and NEDC) for vehicles in Korea were used to determine BC emissions for various vehicle speeds. In addition, the contributions of biomass and coal combustion to the data of AE33 were analyzed to determine the possibility of tracking the BC sources. MPI, LPG, and EURO 6 with diesel particulate filter (DPF) vehicles emitted the lowest BC emissions in NIER modes. Among gasoline vehicles, MPI vehicles showed the lower BC content in PM emissions. Also, older vehicles in MPI vehicles emitted the high PM and BC emissions. The BC emissions of EURO 3 vehicles without DPF were the highest as the results of previous studies, and it was found that as emissions regulations were tightened, the level of BC results of diesel vehicles became similar with MPI vehicles. The average absorption Ångström exponent (AAE) from difference emissions sources were biomass combustion (oak wood) > coal combustion (the power plant stack) > automobile emissions (gasoline, LPG, diesel).
Applications of Cytokinins in Horticultural Fruit Crops: Trends and Future Prospects
Authors: Aremu Adeyemi O. , Fawole Olaniyi A. , Makunga Nokwanda P. , Masondo Nqobile A. , Moyo Mack , Buthelezi Nana M. D. , Amoo Stephen O. , Spíchal Lukáš , Doležal Karel
Published: August 2020

Cytokinins (CKs) are a chemically diverse class of plant growth regulators, exhibiting wide-ranging actions on plant growth and development, hence their exploitation in agriculture for crop improvement and management. Their coordinated regulatory effects and cross-talk interactions with other phytohormones and signaling networks are highly sophisticated, eliciting and controlling varied biological processes at the cellular to organismal levels. In this review, we briefly introduce the mode of action and general molecular biological effects of naturally occurring CKs before highlighting the great variability in the response of fruit crops to CK-based innovations. We present a comprehensive compilation of research linked to the application of CKs in non-model crop species in different phases of fruit production and management. By doing so, it is clear that the effects of CKs on fruit set, development, maturation, and ripening are not necessarily generic, even for cultivars within the same species, illustrating the magnitude of yet unknown intricate biochemical and genetic mechanisms regulating these processes in different fruit crops. Current approaches using genomic-to-metabolomic analysis are providing new insights into the in planta mechanisms of CKs, pinpointing the underlying CK-derived actions that may serve as potential targets for improving crop-specific traits and the development of new solutions for the preharvest and postharvest management of fruit crops. Where information is available, CK molecular biology is discussed in the context of its present and future implications in the applications of CKs to fruits of horticultural significance.
Multiple Screening of Pesticides Toxicity in Zebrafish and Daphnia Based on Locomotor Activity Alterations
Authors: Hussain Akhlaq , Audira Gilbert , Malhotra Nemi , Uapipatanakul Boontida , Chen Jung-Ren , Lai Yu-Heng , Huang Jong-Chin , Chen Kelvin H.-C. , Lai Hong-Thih , Hsiao Chung-Der
Published: August 2020

Pesticides are widely used to eradicate insects, weed species, and fungi in agriculture. The half-lives of some pesticides are relatively long and may have the dire potential to induce adverse effects when released into the soil, terrestrial and aquatic systems. To assess the potential adverse effects of pesticide pollution in the aquatic environment, zebrafish (Danio rerio) and Daphnia magna are two excellent animal models because of their transparent bodies, relatively short development processes, and well-established genetic information. Moreover, they are also suitable for performing high-throughput toxicity assays. In this study, we used both zebrafish larvae and water flea daphnia neonates as a model system to explore and compare the potential toxicity by monitoring locomotor activity. Tested animals were exposed to 12 various types of pesticides (three fungicides and 9 insecticides) for 24 h and their corresponding locomotor activities, in terms of distance traveled, burst movement, and rotation were quantified. By adapting principal component analysis (PCA) and hierarchical clustering analysis, we were able to minimize data complexity and compare pesticide toxicity based on locomotor activity for zebrafish and daphnia. Results showed distinct locomotor activity alteration patterns between zebrafish and daphnia towards pesticide exposure. The majority of pesticides tested in this study induced locomotor hypo-activity in daphnia neonates but triggered locomotor hyper-activity in zebrafish larvae. According to our PCA and clustering results, the toxicity for 12 pesticides was grouped into two major groups based on all locomotor activity endpoints collected from both zebrafish and daphnia. In conclusion, all pesticides resulted in swimming alterations in both animal models by either producing hypo-activity, hyperactivity, or other changes in swimming patterns. In addition, zebrafish and daphnia displayed distinct sensitivity and response against different pesticides, and the combinational analysis approach by using a phenomic approach to combine data collected from zebrafish and daphnia provided better resolution for toxicological assessment.
Canonical and Non-Canonical Roles of Connexin43 in Cardioprotection
Authors: Rusiecka Olga M. , Montgomery Jade , Morel Sandrine , Batista-Almeida Daniela , Van Campenhout Raf , Vinken Mathieu , Girao Henrique , Kwak Brenda R.
Published: August 2020

Since the mid-20th century, ischemic heart disease has been the world’s leading cause of death. Developing effective clinical cardioprotection strategies would make a significant impact in improving both quality of life and longevity in the worldwide population. Both ex vivo and in vivo animal models of cardiac ischemia/reperfusion (I/R) injury are robustly used in research. Connexin43 (Cx43), the predominant gap junction channel-forming protein in cardiomyocytes, has emerged as a cardioprotective target. Cx43 posttranslational modifications as well as cellular distribution are altered during cardiac reperfusion injury, inducing phosphorylation states and localization detrimental to maintaining intercellular communication and cardiac conduction. Pre- (before ischemia) and post- (after ischemia but before reperfusion) conditioning can abrogate this injury process, preserving Cx43 and reducing cell death. Pre-/post-conditioning has been shown to largely rely on the presence of Cx43, including mitochondrial Cx43, which is implicated to play a major role in pre-conditioning. Posttranslational modifications of Cx43 after injury alter the protein interactome, inducing negative protein cascades and altering protein trafficking, which then causes further damage post-I/R injury. Recently, several peptides based on the Cx43 sequence have been found to successfully diminish cardiac injury in pre-clinical studies.
Comparative Characterization of Gluten and Hydrolyzed Wheat Proteins
Authors: Gabler Angelika , Scherf Katharina
Published: August 2020

Hydrolyzed wheat proteins (HWPs) are widely used as functional ingredients in foods and cosmetics, because of their emulsifying and foaming properties. However, in individuals suffering from celiac disease or wheat allergy, HWPs may have a modified immunoreactivity compared to native gluten due to changes in molecular structures. Although a variety of HWPs are commercially available, there are no in-depth comparative studies that characterize the relative molecular mass (Mr) distribution, solubility, and hydrophilicity/hydrophobicity of HWPs compared to native gluten. Therefore, we aimed to fill this gap by studying the above characteristics of different commercial HWP and gluten samples. Up to 100% of the peptides/proteins in the HWP were soluble in aqueous solution, compared to about 3% in native gluten. Analysis of the Mr distribution indicated that HWPs contained high percentages of low-molecular-weight peptides/proteins and also deamidated glutamine residues. We also found considerable differences between the seven HWPs studied, so that each HWP needs to be studied in detail to help explain its potential immunoreactivity.
Gene Expression Analysis of Astrocyte and Microglia Endocannabinoid Signaling during Autoimmune Demyelination
Authors: Moreno-García Álvaro , Bernal-Chico Ana , Colomer Teresa , Rodríguez-Antigüedad Alfredo , Matute Carlos , Mato Susana
Published: August 2020

The endocannabinoid system is associated with protective effects in multiple sclerosis (MS) that involve attenuated innate immune cell responses. Astrocytes and microglia are modulated by endocannabinoids and participate in the biosynthesis and metabolism of these compounds. However, the role of neuroglial cells as targets and mediators of endocannabinoid signaling in MS is poorly understood. Here we used a microfluidic RT-qPCR screen to assess changes in the expression of the main endocannabinoid signaling genes in astrocytes and microglia purified from female mice during the time-course of experimental autoimmune encephalomyelitis (EAE). We show that astrocytes and microglia upregulate the expression of genes encoding neurotoxic A1 and pro-inflammatory molecules at the acute disease with many of these transcripts remaining elevated during the recovery phase. Both cell populations exhibited an early onset decrease in the gene expression levels of 2-arachidonoylglycerol (2-AG) hydrolytic enzymes that persisted during EAE progression as well as cell-type-specific changes in the transcript levels for genes encoding cannabinoid receptors and molecules involved in anandamide (AEA) signaling. Our results demonstrate that astrocytes and microglia responses to autoimmune demyelination involve alterations in the expression of multiple endocannabinoid signaling-associated genes and suggest that this system may regulate the induction of neurotoxic and pro-inflammatory transcriptional programs in both cell types during MS.
Poly(9H-carbazole) as a Organic Semiconductor for Enzymatic and Non-Enzymatic Glucose Sensors
Authors: Bagdžiūnas Gintautas , Palinauskas Delianas
Published: August 2020

Organic semiconductors and conducting polymers are the most promising next-generation conducting materials for electrochemical biosensors as the greener and cheaper alternative for electrodes based on transition metals or their oxides. Therefore, polycarbazole as the organic semiconducting polymer was electrochemically synthesized and deposited on working electrode. Structure and semiconducting properties of polycarbazole have theoretically and experimentally been analyzed and proved. For these electrochemical systems, a maximal sensitivity of 14 μA·cm−2·mM−1, a wide linear range of detection up to 5 mM, and a minimal limit of detection of around 0.2 mM were achieved. Moreover, Michaelis’s constant of these sensors depends not only on the enzyme but on the material of electrode and applied potential. The electrocatalytic mechanism and performance of the non- and enzymatic sensors based on this material as a conducting layer have been discussed by estimating pseudocapacitive and faradaic currents and by adding glucose as an analyte at the different applied potentials. In this work, the attention was focused on the electrochemical origin and mechanism involved in the non- and enzymatic oxidation and reduction of glucose.
Angiogenesis Inhibition in Prostate Cancer: An Update
Authors: Sarkar Chandrani , Goswami Sandeep , Basu Sujit , Chakroborty Debanjan
Published: August 2020

Prostate cancer (PCa), like all other solid tumors, relies on angiogenesis for growth, progression, and the dissemination of tumor cells to other parts of the body. Despite data from in vitro and in vivo preclinical studies, as well as human specimen studies indicating the crucial role played by angiogenesis in PCa, angiogenesis inhibition in clinical settings has not shown significant benefits to patients, thus challenging the inclusion and usefulness of antiangiogenic agents for the treatment of PCa. However, one of the apparent reasons why these antiangiogenic agents failed to meet expectations in PCa can be due to the choice of the antiangiogenic agents, because the majority of these drugs target vascular endothelial growth factor-A (VEGFA) and its receptors. The other relevant causes might be inappropriate drug combinations, the duration of treatment, and the method of endpoint determination. In this review, we will first discuss the role of angiogenesis in PCa growth and progression. We will then summarize the different angiogenic growth factors that influence PCa growth dynamics and review the outcomes of clinical trials conducted with antiangiogenic agents in PCa patients and, finally, critically assess the current status and fate of antiangiogenic therapy in this disease.
Editorial Catalysts: Special Issue on Photocatalytic Membrane Reactors
Authors: Molinari Raffaele , Mozia Sylwia
Published: August 2020

The themed collection of articles in the Special Issue on Photocatalytic Membrane Reactors in the journal Catalysts constitutes some significant and highly representative publications referring to this topic [...]