bluuebunny/crossref_metadata_2025 huggingface dataset:
Near-Term Changes to Reach Scale Habitat Features Following Headwater Stream Restoration in a Southeastern Massachusetts Former Cranberry Bog
Authors: McCanty Sean T. , Dimino Thomas F. , Christian Alan D.
Published: May 2021

Land use changes remain one of the leading global change drivers leading to biodiversity loss in terrestrial and aquatic systems. Restoration aims to counteract the development of “natural” (i.e., forested, grassland, or wetland) spaces that alter and fragment the landscape and reduce local biodiversity through direct impacts to the water column and indirect impacts which inhibit adult dispersal of aquatic insects. This case study seeks to determine if a large-scale restoration of a former cranberry bog in Plymouth, MA has resulted in near-term measurable changes to the composition, structure, and function of local-scale in-stream habitat diversity. A three-year observational field study beginning one year prior to reconstruction was conducted at the restored cranberry bog and at two control treatment sites: an active cranberry bog reference and a least impacted reference (i.e., has never been used for modern agriculture). Seasonal inventories of in-stream habitat features including depth, substrate, macrohabitat, and in-stream cover were taken from 2015 to 2017. We found that 2 years post-restoration, there was no significant evidence of compositional or functional change, while there was a significant increase in structural diversity. There is reason to suspect the system is still in flux and longer-term monitoring may detect future habitat heterogeneity alterations.
Value Attribution in the Decision to Use of Whole Body MRI for Early Cancer Diagnosis
Authors: Busacchio Derna , Mazzocco Ketti , Radice Davide , Summers Paul E. , Pricolo Paola , Pravettoni Gabriella , Petralia Giuseppe
Published: May 2021

This study aimed to identify the main factors that asymptomatic individuals considered when deciding to undergo self-referred Whole-body MRI (WB-MRI) for early cancer diagnosis and the subjective values attributed to each mentioned factor in a Decision tree analysis. Personal characteristics such as risk perception and personality were investigated as possible factors affecting value attribution. Seventy-four volunteers (mean age 56.4; male = 47) filled a simplified decision tree by expressing the expected factors and related subjective values associated with two screening options for early cancer diagnosis (standard procedures vs. WB-MRI+standard procedures) while waiting for a WB-MRI examination. Questionnaires on risk perception and personality traits were also administered. Expected factors were summarized in 5 clusters: diagnostic certainty, psychological well-being, safety, test validity and time/cost. Test validity and time/cost were evaluated as potential losses in both procedures. Diagnostic Certainty and safety were evaluated as losses in standard screening, and as an advantage when considering WB-MRI+standard screening. Forty-five percent of participants considered WB-MRI+standard screening as beneficial for their psychological well-being. Finally, personal absolute and comparative risk to get cancer was associated with a positive value attribution to WB-MRI (p < 0.05). Our results showed the addition of WB-MRI to be generally considered a good option to increase individuals’ perceptions of diagnostic certainty and the safety of the exam, and to increase psychological well-being. The positive value of such a screening option increased with the individual’s cancer risk perception.
Computer-Aided Diagnosis Improves the Detection of Clinically Significant Prostate Cancer on Multiparametric-MRI: A Multi-Observer Performance Study Involving Inexperienced Readers
Authors: Giannini Valentina , Mazzetti Simone , Cappello Giovanni , Doronzio Valeria Maria , Vassallo Lorenzo , Russo Filippo , Giacobbe Alessandro , Muto Giovanni , Regge Daniele
Published: May 2021

Recently, Computer Aided Diagnosis (CAD) systems have been proposed to help radiologists in detecting and characterizing Prostate Cancer (PCa). However, few studies evaluated the performances of these systems in a clinical setting, especially when used by non-experienced readers. The main aim of this study is to assess the diagnostic performance of non-experienced readers when reporting assisted by the likelihood map generated by a CAD system, and to compare the results with the unassisted interpretation. Three resident radiologists were asked to review multiparametric-MRI of patients with and without PCa, both unassisted and assisted by a CAD system. In both reading sessions, residents recorded all positive cases, and sensitivity, specificity, negative and positive predictive values were computed and compared. The dataset comprised 90 patients (45 with at least one clinically significant biopsy-confirmed PCa). Sensitivity significantly increased in the CAD assisted mode for patients with at least one clinically significant lesion (GS > 6) (68.7% vs. 78.1%, p = 0.018). Overall specificity was not statistically different between unassisted and assisted sessions (94.8% vs. 89.6, p = 0.072). The use of the CAD system significantly increases the per-patient sensitivity of inexperienced readers in the detection of clinically significant PCa, without negatively affecting specificity, while significantly reducing overall reporting time.
Statistical and Criticality Analysis of the Lower Ionosphere Prior to the 30 October 2020 Samos (Greece) Earthquake (M6.9), Based on VLF Electromagnetic Propagation Data as Recorded by a New VLF/LF Receiver Installed in Athens (Greece)
Authors: Politis Dimitrios Z. , Potirakis Stelios M. , Contoyiannis Yiannis F. , Biswas Sagardweep , Sasmal Sudipta , Hayakawa Masashi
Published: May 2021

In this work we present the statistical and criticality analysis of the very low frequency (VLF) sub-ionospheric propagation data recorded by a VLF/LF radio receiver which has recently been established at the University of West Attica in Athens (Greece). We investigate a very recent, strong (M6.9), and shallow earthquake (EQ) that occurred on 30 October 2020, very close to the northern coast of the island of Samos (Greece). We focus on the reception data from two VLF transmitters, located in Turkey and Israel, on the basis that the EQ’s epicenter was located within or very close to the 5th Fresnel zone, respectively, of the corresponding sub-ionospheric propagation path. Firstly, we employed in our study the conventional analyses known as the nighttime fluctuation method (NFM) and the terminator time method (TTM), aiming to reveal any statistical anomalies prior to the EQ’s occurrence. These analyses revealed statistical anomalies in the studied sub-ionospheric propagation paths within ~2 weeks and a few days before the EQ’s occurrence. Secondly, we performed criticality analysis using two well-established complex systems’ time series analysis methods—the natural time (NT) analysis method, and the method of critical fluctuations (MCF). The NT analysis method was applied to the VLF propagation quantities of the NFM, revealing criticality indications over a period of ~2 weeks prior to the Samos EQ, whereas MCF was applied to the raw receiver amplitude data, uncovering the time excerpts of the analyzed time series that present criticality which were closest before the Samos EQ. Interestingly, power-law indications were also found shortly after the EQ’s occurrence. However, it is shown that these do not correspond to criticality related to EQ preparation processes. Finally, it is noted that no other complex space-sourced or geophysical phenomenon that could disturb the lower ionosphere did occur during the studied time period or close after, corroborating the view that our results prior to the Samos EQ are likely related to this mainshock.
Technology Acceptance of an Interactive Augmented Reality App on Resistive Circuits for Engineering Students
Authors: Álvarez-Marín Alejandro , Velázquez-Iturbide J. Ángel , Castillo-Vergara Mauricio
Published: May 2021

In this study, we aim to establish the factors that explain the technology acceptance of augmented reality (AR) in students’ engineering education. Technology acceptance of AR apps has been insufficiently investigated. We conceive a theoretical model to explain technology acceptance by relating behavioral intention to use with the variables subjective norm, technology optimism, technology innovativeness, perceived ease of use, perceived usefulness, and attitude toward using. An interactive AR app on electrical circuits was designed to assist students to overcome their difficulties in understanding how electricity works. A theoretical model was hypothesized and tested using structural equation modeling. The study was conducted using a sample of 190 engineering students. The results demonstrate the positive effect of technology optimism and technology innovativeness on perceived usefulness and attitude toward using, respectively. Furthermore, they suggest that attitude toward using is influenced by perceived usefulness but not directly by perceived ease of use. This could mean that students would be willing to use this app if they find it useful and not just easy to use. Finally, the results illustrate that attitude toward using firmly explains behavioral intention to use, which is consistent with the findings in previous studies. These results could guide how academics and higher education centers should approach the incorporation of these technologies in classrooms.
IoMT Based Facial Emotion Recognition System Using Deep Convolution Neural Networks
Authors: Rathour Navjot , Alshamrani Sultan S. , Singh Rajesh , Gehlot Anita , Rashid Mamoon , Akram Shaik Vaseem , AlGhamdi Ahmed Saeed
Published: May 2021

Facial emotion recognition (FER) is the procedure of identifying human emotions from facial expressions. It is often difficult to identify the stress and anxiety levels of an individual through the visuals captured from computer vision. However, the technology enhancements on the Internet of Medical Things (IoMT) have yielded impressive results from gathering various forms of emotional and physical health-related data. The novel deep learning (DL) algorithms are allowing to perform application in a resource-constrained edge environment, encouraging data from IoMT devices to be processed locally at the edge. This article presents an IoMT based facial emotion detection and recognition system that has been implemented in real-time by utilizing a small, powerful, and resource-constrained device known as Raspberry-Pi with the assistance of deep convolution neural networks. For this purpose, we have conducted one empirical study on the facial emotions of human beings along with the emotional state of human beings using physiological sensors. It then proposes a model for the detection of emotions in real-time on a resource-constrained device, i.e., Raspberry-Pi, along with a co-processor, i.e., Intel Movidius NCS2. The facial emotion detection test accuracy ranged from 56% to 73% using various models, and the accuracy has become 73% performed very well with the FER 2013 dataset in comparison to the state of art results mentioned as 64% maximum. A t-test is performed for extracting the significant difference in systolic, diastolic blood pressure, and the heart rate of an individual watching three different subjects (angry, happy, and neutral).
Efficient Dimensionality Reduction Methods in Reservoir History Matching
Authors: Tadjer Amine , Bratvold Reider B. , Hanea Remus G.
Published: May 2021

Production forecasting is the basis for decision making in the oil and gas industry, and can be quite challenging, especially in terms of complex geological modeling of the subsurface. To help solve this problem, assisted history matching built on ensemble-based analysis such as the ensemble smoother and ensemble Kalman filter is useful in estimating models that preserve geological realism and have predictive capabilities. These methods tend, however, to be computationally demanding, as they require a large ensemble size for stable convergence. In this paper, we propose a novel method of uncertainty quantification and reservoir model calibration with much-reduced computation time. This approach is based on a sequential combination of nonlinear dimensionality reduction techniques: t-distributed stochastic neighbor embedding or the Gaussian process latent variable model and clustering K-means, along with the data assimilation method ensemble smoother with multiple data assimilation. The cluster analysis with t-distributed stochastic neighbor embedding and Gaussian process latent variable model is used to reduce the number of initial geostatistical realizations and select a set of optimal reservoir models that have similar production performance to the reference model. We then apply ensemble smoother with multiple data assimilation for providing reliable assimilation results. Experimental results based on the Brugge field case data verify the efficiency of the proposed approach.
Optimal Battery Energy Storage Dispatch Strategy for Small-Scale Isolated Hybrid Renewable Energy System with Different Load Profile Patterns
Authors: Jufri Fauzan Hanif , Aryani Dwi Riana , Garniwa Iwa , Sudiarto Budi
Published: May 2021

Most inhabited islands in Indonesia are powered by expensively known diesel generators and isolated from the primary grid due to either geographical or economic reasons. Meanwhile, the diesel generator can be combined with a photovoltaic (PV) system and Battery Energy Storage (BES) system to form a hybrid power generation system to reduce the energy cost and increase renewable energy penetration. For this, proper sizing of each power generation component is required, one of which is influenced by the applied control strategy. This paper proposes an optimal BES dispatch (OBD) control strategy that optimizes the power generation components’ sizing. The method examines the shortcomings of the other popular control strategies, such as load following, cycle charging, or combination. The optimization objectives are to minimize the Levelized Cost of Energy (LCOE) and maximize the renewable energy (RE) penetration, which can be achieved by prioritizing the BES to supply the load over other available generations and charge the BES every time the generator operates. The proposed method is implemented at two different systems with different load profiles. As a result, the proposed control strategy provides lower LCOE while maintaining higher RE penetration than the other control strategies in both locations.
Investigations of Exhaust Emissions from Rail Machinery during Track Maintenance Operations
Authors: Kamińska Michalina , Rymaniak Łukasz , Lijewski Piotr , Szymlet Natalia , Daszkiewicz Paweł , Grzeszczyk Rafał
Published: May 2021

The paper presents the investigations of exhaust emissions under actual operation of two rail vehicles: a track geometry vehicle and a clearance vehicle. The environmental assessment of this type of objects is difficult due to the necessity of adapting the measurement equipment and meeting the safety requirements during the tests (particularly regarding the distance from the overhead electrical lines). The authors have proposed and developed a unique research methodology, based on which a detailed exhaust emissions analysis (CO, HC, NOx, and PM) was carried out. The complex assessment included the unit and on-track exhaust emissions. In the analyses, the authors also included the operating conditions of the powertrains of the tested machinery. The obtained environmental indexes were referred to the homologation standards, according to which the vehicles were approved for operation. Due to the nature of operation of the tested vehicles, the authors carried out a comprehensive environmental assessment in the daily and annual approach as well as in the aspect of their operation as combined vehicles, which is a novel approach to the assessment of the environmental performance of this type of objects.
The Effect of the COVID-19 Pandemic on the Electricity Consumption in Romania
Authors: Iancu Ioana Ancuta , Darab Cosmin Pompei , Cirstea Stefan Dragos
Published: May 2021

The COVID-19 pandemic obliged the Romanian government to take drastic measures to contain the virus. More than this, they imposed the heaviest restrictions in the EU. For more than a month, during the lockdown period, everything stopped: schools and universities had only online classes, national and international flights and gatherings were forbidden, and many restrictions for travel were imposed. This paper analyzes the changes that occurred in electricity consumption linked with economic growth, during the pandemic, in Romania. For a better understanding of the correlations between gross domestic product (GDP) and electricity consumption (EC) in different economic contexts, the period 2008–2020 was divided into three series: the 2008–2012 financial crisis and the post-crisis recovery period, the 2013–2019 period of economic growth, and the Q1–Q3 2020 pandemic period. Using correlation coefficients and regression analysis, the authors found that the GDP decoupled from EC in the first period. The increase in GDP led to an increase in the consumption of electricity and the electricity produced from RESs in the second period. In Q3 2020, the real GDP is different from the calculated GDP, due to the pandemic. In Romania, the electricity consumption decreased within the first nine months of the pandemic due to the economic contraction. The electricity that comes from coal and hydropower plants suffered the biggest decrease. If the electricity that comes from NRESs can be adapted to the economic demands, the quantity of electricity that comes from RESs will be influenced by the climate conditions.
A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm
Authors: Kim Kiyoung , Kim Namdoo , Jeong Jongryeol , Min Sunghwan , Yang Horim , Vijayagopal Ram , Rousseau Aymeric , Cha Suk Won
Published: May 2021

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.
Power System Transient Stability Assessment Using Stacked Autoencoder and Voting Ensemble
Authors: Sarajcev Petar , Kunac Antonijo , Petrovic Goran , Despalatovic Marin
Published: May 2021

Increased integration of renewable energy sources brings new challenges to the secure and stable power system operation. Operational challenges emanating from the reduced system inertia, in particular, will have important repercussions on the power system transient stability assessment (TSA). At the same time, a rise of the “big data” in the power system, from the development of wide area monitoring systems, introduces new paradigms for dealing with these challenges. Transient stability concerns are drawing attention of various stakeholders as they can be the leading causes of major outages. The aim of this paper is to address the power system TSA problem from the perspective of data mining and machine learning (ML). A novel 3.8 GB open dataset of time-domain phasor measurements signals is built from dynamic simulations of the IEEE New England 39-bus test case power system. A data processing pipeline is developed for features engineering and statistical post-processing. A complete ML model is proposed for the TSA analysis, built from a denoising stacked autoencoder and a voting ensemble classifier. Ensemble consist of pooling predictions from a support vector machine and a random forest. Results from the classifier application on the test case power system are reported and discussed. The ML application to the TSA problem is promising, since it is able to ingest huge amounts of data while retaining the ability to generalize and support real-time decisions.
A Data Driven RUL Estimation Framework of Electric Motor Using Deep Electrical Feature Learning from Current Harmonics and Apparent Power
Authors: Shifat Tanvir Alam , Yasmin Rubiya , Hur Jang-Wook
Published: May 2021

An effective remaining useful life (RUL) estimation method is of great concern in industrial machinery to ensure system reliability and reduce the risk of unexpected failures. Anticipation of an electric motor’s future state can improve the yield of a system and warrant the reuse of the industrial asset. In this paper, we present an effective RUL estimation framework of brushless DC (BLDC) motor using third harmonic analysis and output apparent power monitoring. In this work, the mechanical output of the BLDC motor is monitored through a coupled generator. To emphasize the total power generation, we have analyzed the trend of apparent power, which preserves the characteristics of real power and reactive power in an AC power system. A normalized modal current (NMC) is used to extract the current features from the BLDC motor. Fault characteristics of motor current and generator power are fused using a Kalman filter to estimate the RUL. Degradation patterns for the BLDC motor have been monitored for three different scenarios and for future predictions, an attention layer optimized bidirectional long short-term memory (ABLSTM) neural network model is trained. ABLSTM model’s performance is evaluated based on several metrics and compared with other state-of-the-art deep learning models.
A Low-Cost Sustainable Energy Solution for Pristine Mountain Areas of Developing Countries
Authors: Sheikh Shakil Rehman , Shah Syed Hassan Raza , Rauf Umar , Rauf Fawad , Kausar Zareena , Aziz Umair , Shah Muhammad Faizan , Yaqoob Haseeb , Niazi Muhammad Bilal Khan
Published: May 2021

The rise in energy requirements and its shortfall in developing countries have affected socioeconomic life. Communities in remote mountainous regions in Asia are among the most affected by energy deprivation. This study presents the feasibility of an alternate strategy of supplying clean energy to the areas consisting of pristine mountains and forest terrain. Southeast Asia has a much-diversified landscape and varied natural resources, including abundant water resources. The current study is motivated by this abundant supply of streams which provides an excellent environment for run-of-river micro vertical axis water turbines. However, to limit the scope of the study, the rivers and streams flowing in northern areas of Pakistan are taken as the reference. The study proposes a comprehensive answer for supplying low-cost sustainable energy solutions for such remote communities. The suggested solution consists of a preliminary hydrodynamic design using Qblade, further analysis using numerical simulations, and finally, experimental testing in a real-world environment. The results of this study show that the use of microturbines is a very feasible option considering that the power generation density of the microturbine comes out to be approximately 2100 kWh/year/m2, with minimal adverse effects on the environment.
Fault-Tolerant Control Strategy with Asymmetric Phase Currents for Single to Four-Phase Open-Circuit Faults of Six-Phase PMSM
Authors: Huang Chen , Zhou Lidan , Cao Zujia , Yao Gang
Published: May 2021

Multi-phase motors and generators are regarded with great fault tolerance capability, especially on open-circuit faults. Various mathematics analytical methods are applied for their fault control. In this paper, a fault-tolerant control strategy with asymmetric phase current for the open-circuit faults with arbitrary phases in the six-phase PMSM (six-phase permanent magnetic synchronous motor, 6P-PMSM) system, is proposed for better electrical and dynamical performance of the machine. An innovative mathematical model for PMSM under one to four-phase-open circuit faults are established considering the asymmetry of the machine. Combining with time-varying relations in machines’ working conditions, targeted decoupling transformation matrixes of every kind of open-circuit faults are settled by voltage equations under different faults. Modified control strategy with a connection between the neutral point and the inverter’s DC side is presented, which aims at increasing the system redundancy and reducing the amplitude of phase currents. Besides, improved control loops with two layers are put forward as well, with which the PMSM system acquires fewer harmonics in phase current and smoother electromagnetic torque. Simulation and experimental results of open-circuit faults are provided for verification of the theoretical analysis.
Increasing Energy Efficiency and Modernization of Energy Systems in Russia: A Review
Authors: Strielkowski Wadim , Sherstobitova Anna , Rovny Patrik , Evteeva Tatiana
Published: May 2021

The main purpose of this research is to assess the energy efficiency in Russia on its path towards the modernization of its energy systems. This modernization can be seen as an effective means for promoting decarbonization and energy-saving initiatives. Our methods include a comprehensive overview of the development of the energy sector in Russia, which is distinguished by the high concentration of state-owned enterprises, the absence of clear market mechanisms, as well as the domination of the fossil fuels represented by natural gas and oil. Furthermore, we present the perspectives of developing the renewable energy technologies in Russia. Our results enable us to create an in-depth analysis of the perspectives of modernization of the Russian energy sector and to draw the key connotations for its further development. Moreover, the outcomes of this paper can provide useful policy implications and guidelines for modernizing energy efficiency and energy systems for Russian stakeholders and policy makers, supporting their efforts to reduce the dependency on carbon fuels and to embark on the path towards the sustainable economic growth and development.
Hydrogen Road Transport Analysis in the Energy System: A Case Study for Germany through 2050
Authors: Reuß Markus , Dimos Paris , Léon Aline , Grube Thomas , Robinius Martin , Stolten Detlef
Published: May 2021

Carbon-free transportation is envisaged by means of fuel cell electric vehicles (FCEV) propelled by hydrogen that originates from renewably electricity. However, there is a spatial and temporal gap in the production and demand of hydrogen. Therefore, hydrogen storage and transport remain key challenges for sustainable transportation with FCEVs. In this study, we propose a method for calculating a spatially resolved highway routing model for Germany to transport hydrogen by truck from the 15 production locations (source) to the 9683 fueling stations (sink) required by 2050. We consider herein three different storage modes, namely compressed gaseous hydrogen (CGH2), liquid hydrogen (LH2) and liquid organic hydrogen carriers (LOHC). The model applies Dijkstra’s shortest path algorithm for all available source-sink connections prior to optimizing the supply. By creating a detailed routing result for each source-sink connection, a detour factor is introduced for “first and last mile” transportation. The average detour factor of 1.32 is shown to be necessary for the German highway grid. Thereafter, the related costs, transportation time and travelled distances are calculated and compared for the examined storage modes. The overall transportation cost result for compressed gaseous hydrogen is 2.69 €/kgH2, 0.73 €/kgH2 for liquid hydrogen, and 0.99 €/kgH2 for LOHCs. While liquid hydrogen appears to be the most cost-efficient mode, with the integration of the supply chain costs, compressed gaseous hydrogen is more convenient for minimal source-sink distances, while liquid hydrogen would be suitable for distances greater than 130 km.
Mechanistic Grey-Box Modeling of a Packed-Bed Regenerator for Industrial Applications
Authors: Halmschlager Verena , Müllner Stefan , Hofmann René
Published: May 2021

Thermal energy storage is essential to compensate for energy peaks and troughs of renewable energy sources. However, to implement this storage in new or existing industries, robust and accurate component models are required. This work examines the development of a mechanistic grey-box model for a sensible thermal energy storage, a packed-bed regenerator. The mechanistic grey-box model consists of physical relations/equations and uses experimental data to optimize specific parameters of these equations. Using this approach, a basic model and two models with extensions I and II, which vary in their number from Equations (3) to (5) and parameters (3 to 6) to be fitted, are proposed. The three models’ results are analyzed and compared to existing models of the regenerator, a data-driven and a purely physical model. The results show that all developed grey-box models can extrapolate and approximate the physical behavior of the regenerator well. In particular, the extended model II shows excellent performance. While the existing data-driven model lacks robustness and the purely physical model lacks accuracy, the hybrid grey-box models do not show significant disadvantages. Compared to the data-driven and physical model, the grey-box models especially stands out due to their high accuracy, low computational effort, and high robustness.
Czechoslovakian Wolfdog Genomic Divergence from Its Ancestors Canis lupus, German Shepherd Dog, and Different Sheepdogs of European Origin
Authors: Moravčíková Nina , Kasarda Radovan , Židek Radoslav , Vostrý Luboš , Vostrá-Vydrová Hana , Vašek Jakub , Čílová Daniela
Published: May 2021

This study focused on the genomic differences between the Czechoslovakian wolfdog (CWD) and its ancestors, the Grey wolf (GW) and German Shepherd dog. The Saarloos wolfdog and Belgian Shepherd dog were also included to study the level of GW genetics retained in the genome of domesticated breeds. The dataset consisted of 131 animals and 143,593 single nucleotide polymorphisms (SNPs). The effects of demographic history on the overall genome structure were determined by screening the distribution of the homozygous segments. The genetic variance distributed within and between groups was quantified by genetic distances, the FST index, and discriminant analysis of principal components. Fine-scale population stratification due to specific morphological and behavioural traits was assessed by principal component and factorial analyses. In the CWD, a demographic history effect was manifested mainly in a high genome-wide proportion of short homozygous segments corresponding to a historical load of inbreeding derived from founders. The observed proportion of long homozygous segments indicated that the inbreeding events shaped the CWD genome relatively recently compared to other groups. Even if there was a significant increase in genetic similarity among wolf-like breeds, they were genetically separated from each other. Moreover, this study showed that the CWD genome carries private alleles that are not found in either wolves or other dog breeds analysed in this study.
Evaluation of Community Resilience in Rural China—Taking Licheng Subdistrict, Guangzhou as an Example
Authors: Fan Jianhong , Mo You , Cai Yunnan , Zhao Yabo , Su Dongchen
Published: May 2021

Resilience of rural communities is becoming increasingly important to contemporary society. In this study we used a quantitative method to measure the resilience regulating ability of rural communities close to urban areas—in Licheng Subdistrict, Guangzhou City, China. The main results are as follows: (1) Rural systems close to urban areas display superior adapting and learning abilities and have a stronger overall resilience strength, the spatial distribution of which is characterized by dispersion in whole and aggregation in part; (2) the resilience of most rural economic subsystems can reach moderate or higher levels with apparent spatial agglomeration, whilst the ecological subsystem resilience and social resilience are generally weaker; the spatial distribution of the former shows a greater regional difference while the latter is in a layered layout; (3) some strategies such as rebuilding a stable ecological pattern, making use of urban resources and cultivating rural subjectivity are proposed on this basis, in order to promote the sustainable development of rural areas and realize rural revitalization. This work also gives suggestion for the creation of appropriate and effective resilience standards specifically targeted for rural community-aiming to achieve the delivery of local sustainability goals.
Reinforcement Learning Page Prediction for Hierarchically Ordered Municipal Websites
Authors: Puustinen Petri , Stefanidis Kostas , Kekäläinen Jaana , Junkkari Marko
Published: May 2021

Public websites offer information on a variety of topics and services and are accessed by users with varying skills to browse the kind of electronic document repositories. However, the complex website structure and diversity of web browsing behavior create a challenging task for click prediction. This paper presents the results of a novel reinforcement learning approach to model user browsing patterns in a hierarchically ordered municipal website. We study how accurate predictor the browsing history is, when the target pages are not immediate next pages pointed by hyperlinks, but appear a number of levels down the hierarchy. We compare traditional type of baseline classifiers’ performance against our reinforcement learning-based training algorithm.
Management of Intrahepatic Cholangiocarcinoma
Authors: Kodali Sudha , Shetty Akshay , Shekhar Soumya , Victor David W. , Ghobrial Rafik M.
Published: May 2021

Cholangiocarcinoma is a tumor that arises as a result of differentiation of the cholangiocytes and can develop from anywhere in the biliary tree. Subtypes of cholangiocarcinoma are differentiated based on their location in the biliary tree. If diagnosed early these can be resected, but most cases of intrahepatic cholangiocarcinoma present late in the disease course where surgical resection is not an option. In these patients who are poor candidates for resection, a combination of chemotherapy, locoregional therapies like ablation, transarterial chemo and radioembolization, and in very advanced and metastatic disease, external radiation are the available options. These modalities can improve overall disease-free and progression-free survival chances. In this review, we will discuss the risk factors and clinical presentation of intrahepatic cholangiocarcinoma, diagnosis, available therapeutic options, and future directions for management options.
Scoring Systems for Clinical Colon Capsule Endoscopy—All You Need to Know
Authors: Tabone Trevor , Koulaouzidis Anastasios , Ellul Pierre
Published: May 2021

In the constantly developing era of minimal diagnostic invasiveness, the role of colon capsule endoscopy in colonic examination is being increasingly recognised, especially in the context of curtailed endoscopy services due to the COVID-19 pandemic. It is a safe diagnostic tool with low adverse event rates. As with other endoscopic modalities, various colon capsule endoscopy scores allow the standardisation of reporting and reproducibility. As bowel cleanliness affects CCE’s diagnostic yield, a few operator-dependent scores (Leighton–Rex and CC-CLEAR scores) and a computer-dependent score (CAC score) have been developed to grade bowel cleanliness objectively. CCE can be used to monitor IBD mucosal disease activity through the UCEIS and the panenteric CECDAIic score for UC and CD, respectively. CCE may also have a role in CRC screening, given similar sensitivity and specificity rates to conventional colonoscopy to detect colonic polyps ≥ 10 mm and CRC. Given CCE’s diagnostic yield and reproducible clinical scores with high inter-observer agreements, CCE is fast becoming a suitable alternative to conventional colonoscopy in specific patient populations.
Vessel Density Loss of the Deep Peripapillary Area in Glaucoma Suspects and Its Association with Features of the Lamina Cribrosa
Authors: Jeon Soo-Ji , Park Hae-Young Lopilly , Park Chan-Kee
Published: May 2021

Purpose: To investigate the association of decreased vessel density (VD) in the deep peripapillary region and structural features of the lamina cribrosa (LC). Materials and Methods: 70 eyes of glaucoma suspects with enlarged cup-to-disc ratio were scanned and 51 eyes with adequate image quality were included in this study. All subjects had localized VD defects in the deep layer but intact VD in the superficial layer around the peripapillary region using optical coherence tomography angiography (OCTA). Only single-hemizone OCTA results from one eye of each subject had to fulfill the distinctive feature mentioned above to perform inter-eye and inter-hemizone comparisons. The thickness and depth of the LC, and prelaminar thickness were measured using enhanced depth imaging OCT (EDI-OCT). Paired t-tests were performed to evaluate differences in measurements of the LC and prelaminar thickness within each individual. p-values lower than 0.05 was considered to be statistically significant. Results: Eyes with deep VD defects in the peripapillary region in OCTA had thinner LC than the fellow eyes. The hemizone with the deep VD defects in the peripapillary region had a thinner LC and a deeper depth of LC than the other hemizone in the same eye. According to logistic regression analysis, a thin LC was a significant factor associated with deep VD defect in the peripapillary region. Conclusions: Glaucoma suspect eyes with deep VD defects in the peripapillary area exhibited structural differences in the LC. The structural changes of the LC was associated with the vessel density in the deep peripapillary layer at the stage of suspected glaucoma.
Implementation of CT Coronary Angiography as an Alternative to Invasive Coronary Angiography in the Diagnostic Work-Up of Non-Coronary Cardiac Surgery, Cardiomyopathy, Heart Failure and Ventricular Arrhythmias
Authors: van den Boogert Thomas P. W. , Claessen Bimmer E. P. M. , van Randen Adrienne , van Schuppen Joost , Boekholdt S. Matthijs , Beijk Marcel A. M. , Vrijmoeth M. Karlijn , Baan Jan , Vis M. Marije , Winkelman Jacobus A. , Driessen Antoine H. G. , Stoker Jaap , Planken R. Nils , Henriques Jose P.
Published: May 2021

To assess the need for additional invasive coronary angiography (CAG) after initial computed tomography coronary angiography (CTCA) in patients awaiting non-coronary cardiac surgery and in patients with cardiomyopathy, heart failure or ventricular arrhythmias, and to determine differences between patients that were referred to initial CTCA or direct CAG, consecutive patients were included between August 2017 and January 2020 and categorized as those referred to initial CTCA (conform protocol), and to direct CAG (non-conform protocol). Out of a total of 415 patients, 78.8% (327 patients, mean age: 57.9 years, 67.3% male) were referred to initial CTCA, of whom 260 patients (79.5%) had no obstructive lesions (<50% DS). A total of 55 patients (16.8%) underwent additional CAG after initial CTCA, which showed coronary lesions of >50% DS in 21 patients (6.3% of 327). Eighty-eight patients (mean age: 66.0 years, 59.1% male) were directly referred to CAG (non-conform protocol). These patients were older and had more cardiovascular risk factors compared to patients that underwent initial CTCA (conform protocol), and coronary lesions of >50% DS were detected in 16 patients (17.2%). Revascularization procedures were infrequently performed in both groups: initial CTCA (3.0%), direct CAG (3.4%). The use of CTCA as a gatekeeper CAG in the diagnostic work-up of non-coronary cardiac surgery, cardiomyopathy, heart failure and ventricular arrhythmias is feasible, and only 17% of these patients required additional CAG after initial CTCA. Therefore, CTCA should be considered as the initial imaging modality to rule out CAD in these patients.
Vitamin D Levels in COVID-19 Outpatients from Western Mexico: Clinical Correlation and Effect of Its Supplementation
Authors: Sánchez-Zuno Gabriela Athziri , González-Estevez Guillermo , Matuz-Flores Mónica Guadalupe , Macedo-Ojeda Gabriela , Hernández-Bello Jorge , Mora-Mora Jesús Carlos , Pérez-Guerrero Edsaúl Emilio , García-Chagollán Mariel , Vega-Magaña Natali , Turrubiates-Hernández Francisco Javier , Machado-Sulbaran Andrea Carolina , Muñoz-Valle José Francisco
Published: May 2021

Background: The immunomodulatory effects of vitamin D are known to be beneficial in viral infections; it is also known that its deficiency is associated with a prognosis more critical of Coronavirus Disease 2019. This study aimed to determine baseline vitamin D serum concentrations and the effects of its supplementation in asymptomatic or mildly symptomatic Coronavirus Disease 2019 outpatients. Methods: 42 outpatients were included, 22 of which received a supplement of 10,000 IU of vitamin D3 for 14 days; the remaining 20 outpatients were designated as a control group. Serum levels of transferrin, ferritin, vitamin D, and D-dimer were measured at baseline in both groups. After 14 days, serum levels of total vitamin D were determined in the supplemented group. Results: At baseline, only 19% of infected outpatients had vitamin D levels corresponding to sufficiency. All outpatients with vitamin D insufficiency had at least one symptom associated with the disease, while only 75% of patients with symptoms presented sufficiency. On the seventh and fourteenth day of follow-up, the supplemented group presented fewer symptoms with respect to those non-supplemented. A vitamin D3 dose of 10,000 IU/daily for 14 days was sufficient to raise vitamin D serum concentrations. Conclusions: Immunomodulatory effects of vitamin D appear to be linked to the development of symptoms in positive outpatients. Vitamin D supplementation could have significant benefits in the Western Mexican population.
Effects of Whole-Body Vibration and Balance Training on Female Athletes with Chronic Ankle Instability
Authors: Chang Wen-Dien , Chen Shuya , Tsou Yung-An
Published: May 2021

We explored the effects of 6-week whole-body vibration (WBV) and balance training programs on female athletes with chronic ankle instability (CAI). This randomized controlled study involved female athletes with dominant-leg CAI. The participants were randomly divided into three groups: WBV training (Group A), balance training (Group B), and nontraining (control group; Group C). Groups A and B performed three exercise movements (double-leg stance, one-legged stance, and tandem stance) in 6-week training programs by using a vibration platform and balance ball, respectively. The Star Excursion Balance Test (SEBT), a joint position sense test, and an isokinetic strength test were conducted. In total, 63 female athletes with dominant-leg CAI were divided into three study groups (all n = 21). All of them completed the study. We observed time-by-group interactions in the SEBT (p = 0.001) and isokinetic strength test at 30°/s of concentric contraction (CON) of ankle inversion (p = 0.04). Compared with the control group, participants of the two exercise training programs improved in dynamic balance, active repositioning, and 30°/s of CON and eccentric contraction of the ankle invertor in the SEBT, joint position sense test, and isokinetic strength test, respectively. Furthermore, the effect sizes for the assessed outcomes in Groups A and B ranged from very small to small. Female athletes who participated in 6-week training programs incorporating a vibration platform or balance ball exhibited very small or small effect sizes for CAI in the SEBT, joint position sense test, and isokinetic strength test. No differences were observed in the variables between the two exercise training programs.
Effect of Posterior Pelvic Tilt Taping on Pelvic Inclination, Muscle Strength, and Gait Ability in Stroke Patients: A Randomized Controlled Study
Authors: In Tae-sung , Jung Jin-hwa , Kim May , Jung Kyoung-sim , Cho Hwi-young
Published: May 2021

Objective: Pelvic alignment asymmetry in stroke patients negatively affects postural control ability. This study aimed to investigate the effect of posterior pelvic tilt taping on pelvic inclination, muscle strength, and gait ability in stroke patients. Methods: Forty stroke patients were recruited and randomly divided into the following two groups: the posterior pelvic tilt taping (PPTT) group (n = 20) and the control group (n = 20). All participants underwent sitting-to-standing, indoor walking, and stair walking training (30 min per day, 5 days per week, for 6 weeks). The PPTT group applied posterior pelvic tilt taping during the training period, while the control group did not receive a tape intervention. Pelvic inclination was measured using a palpation meter (PALM). A hand-held dynamometer and the 10-meter walk test were used to measure muscle strength and gait ability. Results: Significantly greater improvements in the pelvic anterior tilt were observed in the PPTT group than in the control group (p < 0.05). Muscle strength in the PPTT group was significantly increased compared to the control group (p < 0.05). Significantly greater improvements in gait speed were observed in the PPTT group than the control group. Conclusions: According to our results, posterior pelvic tilt taping may be used to improve the anterior pelvic inclination, muscle strength, and gait ability in stroke patients.