bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Variability in Graph Data Sets through Statistical Modeling on the Stiefel Manifold
Authors: Mantoux Clément , Couvy-Duchesne Baptiste , Cacciamani Federica , Epelbaum Stéphane , Durrleman Stanley , Allassonnière Stéphanie
Published: April 2021

Network analysis provides a rich framework to model complex phenomena, such as human brain connectivity. It has proven efficient to understand their natural properties and design predictive models. In this paper, we study the variability within groups of networks, i.e., the structure of connection similarities and differences across a set of networks. We propose a statistical framework to model these variations based on manifold-valued latent factors. Each network adjacency matrix is decomposed as a weighted sum of matrix patterns with rank one. Each pattern is described as a random perturbation of a dictionary element. As a hierarchical statistical model, it enables the analysis of heterogeneous populations of adjacency matrices using mixtures. Our framework can also be used to infer the weight of missing edges. We estimate the parameters of the model using an Expectation-Maximization-based algorithm. Experimenting on synthetic data, we show that the algorithm is able to accurately estimate the latent structure in both low and high dimensions. We apply our model on a large data set of functional brain connectivity matrices from the UK Biobank. Our results suggest that the proposed model accurately describes the complex variability in the data set with a small number of degrees of freedom.
A New Two-Stage Algorithm for Solving Optimization Problems
Authors: Doumari Sajjad Amiri , Givi Hadi , Dehghani Mohammad , Montazeri Zeinab , Leiva Victor , Guerrero Josep M.
Published: April 2021

Optimization seeks to find inputs for an objective function that result in a maximum or minimum. Optimization methods are divided into exact and approximate (algorithms). Several optimization algorithms imitate natural phenomena, laws of physics, and behavior of living organisms. Optimization based on algorithms is the challenge that underlies machine learning, from logistic regression to training neural networks for artificial intelligence. In this paper, a new algorithm called two-stage optimization (TSO) is proposed. The TSO algorithm updates population members in two steps at each iteration. For this purpose, a group of good population members is selected and then two members of this group are randomly used to update the position of each of them. This update is based on the first selected good member at the first stage, and on the second selected good member at the second stage. We describe the stages of the TSO algorithm and model them mathematically. Performance of the TSO algorithm is evaluated for twenty-three standard objective functions. In order to compare the optimization results of the TSO algorithm, eight other competing algorithms are considered, including genetic, gravitational search, grey wolf, marine predators, particle swarm, teaching-learning-based, tunicate swarm, and whale approaches. The numerical results show that the new algorithm is superior and more competitive in solving optimization problems when compared with other algorithms.
Uncertainty Due to Infectious Diseases and Stock–Bond Correlation
Authors: Gkillas Konstantinos , Konstantatos Christoforos , Siriopoulos Costas
Published: April 2021

We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock–bond correlation. To this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ a nonlinear Granger causality test with the use of artificial neural networks so as to investigate the predictability of this type of uncertainty on realized stock–bond correlation and jumps. Our findings reveal that uncertainty-due-to-infectious-diseases has significant predictive value on the changes of the stock–bond relation.
Mathematics Education Students’ Experiences during Lockdown: Managing Collaboration in eLearning
Authors: Calder Nigel , Jafri Mairaj , Guo Lina
Published: April 2021

The current world crisis of COVID-19 has enforced international lockdowns in educational institutions, necessitating that these institutions quickly transition to online learning. In mathematics education studies, where collaborative problem-solving is considered a necessary pedagogical approach, lecturers have had challenges incorporating collaborative problem-solving in an authentic manner. There are now also complex living and learning contexts in which the students have to undertake their learning processes. This paper examines students’ experiences of the rapid transition to online learning and their perceptions of the advantages and barriers that ensued. A small comparative case study was used to explore the complexity of the situation, within rich, authentic settings. Questionnaires and semi-structured interviews were used. The participants found that personal circumstances related to having children and partners at home while they studied, and aspects such as not interacting directly with other students to clarify and mediate their thinking, led to major initial frustrations with collaborating. While some of these continued throughout lockdown they did adjust and recognize that the advantages, such as a mix of formal and informal digital pedagogical media, gave them greater flexibility and led to deeper reflective thinking. We contend that some elements related to the adaptions made should become permanent features of face-to-face learning.
A Tandem Feature Extraction Approach for Arrhythmia Identification
Authors: Tejedor Javier , Marquez David G. , Garcia Constantino A. , Otero Abraham
Published: April 2021

Heart disease is currently the leading cause of death in the world. The electrocardiogram (ECG) is the recording of the electrical activity generated by the heart. Its low cost and simplicity have made it an essential test for monitoring heart disease, especially for the identification of arrhythmias. With the advances in electronic technology, there are nowadays sensors that enable the recording of the ECG during the daily life of the patient and its wireless transmission to healthcare facilities. This type of information has a great potential to detect cardiac diseases in their early stages and to permit early interventions before the patient’s health deteriorates. However, to usefully exploit the large volume of information obtained from ambulatory ECG, pattern recognition techniques that are capable of automatically analyzing it are required. Tandem feature extraction techniques have proven to be useful for the processing of physiological parameters such as the electroencephalogram (EEG) and speech. However, to the best of our knowledge, they have never been applied to the ECG. In this paper, the utility of tandem feature extraction for the identification of arrhythmias is studied. The coefficients of a regression using Hermite functions are used to create a feature vector that represents the heartbeat. A multiple-layer perceptron (MLP) is trained using these features and its posterior probability outputs are used to extend the original feature vector. Finally, a Gaussian mixture model (GMM) is trained on the extended feature vectors, which is then used in a GMM-based arrhythmia identification system. This approach has been validated using the MIT-BIH Arrhythmia database. The accuracy of the Gaussian mixture model increased by 15.8% when applied over the extended feature vectors, compared to its application over the original feature vectors, showing the potential of tandem feature extraction for ECG analysis and arrhythmia identification.
Neutral Point Clamped Transformer-Less Multilevel Converter for Grid-Connected Photovoltaic System
Authors: Madasamy P. , Verma Rajesh , Rameshbabu A. , Murugesan A. , Umamageswari R. , Munda Josiah Lange , Bharatiraja C. , Mihet-Popa Lucian
Published: April 2021

Transformer-less (TL) inverter topologies have elicited further special treatment in photo-voltaic (PV) power system as they provide high efficiency and low cost. Neutral point clamped (NPC) multilevel-inverter (MLI) topologies-based transformer-less are being immensely used in grid-connected medium-voltage high-power claims. Unfortunately, these topologies such as NPC-MLI, full-bridge inverter with DC bypass (FB-DCBP) suffer from the shoot-through problem on the bridge legs, which affect the reliability of the implementation. Based on the previous above credits, a T type neutral point clamped (TNP)—MLI (TNP-MLI) with transformer-less topology called TL-TNP-MLI is presented to be an alternate which can be suitable in the grid-connected PV power generation systems. The suggested TL-TNP-MLI topologies free from inverter bridge legs shoot-through burden, switching frequency common-mode current (CMC), and leakage current. The control system of the grid interface with hysteresis current control (HCC) strategy is proposed. The effectiveness of the proposed PV connected transformer-less TNP-MLI topology with different grid and PV scenario has been verified through the MATLAB/Simulink simulation model and field-programmable gate area (FPGA)-based experimental results for a 1.5 kW system.
Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach
Authors: Azzaoui Nadjet , Korichi Ahmed , Brik Bouziane , Fekair Med el Amine
Published: April 2021

In this paper, we target dissemination issues of emergency messages in a highly dynamic Internet of Vehicles (IoV) network. IoV is emerging as a new class of vehicular networks to optimize road safety as well as users’ comfort. In such a context, forwarding emergency messages through vehicle-to-vehicle communications (V2V) plays a vital role in enabling road safety-related applications. For instance, when an accident occurs, forwarding such information in real time will help to avoid other accidents in addition to avoiding congestion of network traffic. Thus, dissemination of emergency information is a major concern. However, on the one hand, vehicle density has increased in the last decade which may lead to several issues including message collisions, broadcast storm, and the problem of hidden nodes. On the other hand, high mobility of vehicles and hence dynamic changes of network topology result in failure of dissemination of emergency packets. To overcome these problems, we propose a new dissemination scheme of emergency packets by vehicles equipped with both DSRC and cellular LTE wireless communication capabilities. Our scheme is based on a dynamic clustering strategy, which includes a new cluster head selection algorithm to deal with the broadcast storm problem. Furthermore, our selection algorithm enables not only the election of the most stable vehicles as cluster heads, and hence their exploitation in forwarding the emergency information, but also the avoidance of packet collisions. We simulated our scheme in an urban environment and compared it with other data dissemination schemes. Obtained results show the efficiency of our scheme in minimizing collision and broadcast storm problems, while improving latency, packet delivery ratio and data throughput, as compared to other schemes.
Design and Analysis of a Symmetric Log Star Graph with a Smaller Network Cost Than Star Graphs
Authors: Seo Jung-Hyun , Lee Hyeong-Ok
Published: April 2021

Graphs are used as models to solve problems in fields such as mathematics, computer science, physics, and chemistry. In particular, torus, hypercube, and star graphs are popular when modeling the connection structure of processors in parallel computing because they are symmetric and have a low network cost. Whereas a hypercube has a substantially smaller diameter than a torus, star graphs have been presented as an alternative to hypercubes because of their lower network cost. We propose a novel log star (LS) that is symmetric and has a lower network cost than a star graph. The LS is an undirected, recursive, and regular graph. In LSn, the number of nodes is n! while the degree is 2log2n − 1 and the diameter is 0.5n(log2n)2 + 0.75nlog2n. In this study, we analyze the basic topological properties of LS. We prove that LSn is a symmetrical connected graph and analyzed its subgraph characteristics. Then, we propose a routing algorithm and derive the diameter and network cost. Finally, the network costs of the LS and star graph-like networks are compared.
Smart Balancing of Electrical Power in Germany: Fuzzy Logic Model to Simulate Market Response
Authors: Röben Felix , Schäfers Hans , Meißner Anna , de Haan Jerom
Published: April 2021

Recent EU legislation enforces the integration of European balancing markets, with harmonized products and international platforms for the procurement and activation of reserves; nonetheless, different power balancing strategies remain. The Netherlands and Belgium encourage market participants to support balancing the control block by publishing real-time information. This article refers to such concepts as smart balancing, and a market simulation tool was developed to assess the relevant market parameters for effective smart balancing. This shall contribute to the true integration of real-time balancing energy markets. The scope of the assessment of relevant market parameters was Germany, and the results showed that a pricing scheme had less impact on the results, as currently is understood by European TSOs and regulators. Moreover, the accuracy and frequency of real-time publication indicate the effectiveness of smart balancing and the associated reduction of the activation of balancing energy and associated costs. Consequently, this article proposed a road map for Germany to introduce an adapted smart balancing approach, starting with a simple traffic light.
Support Vector Machine Based Fault Location Identification in Microgrids Using Interharmonic Injection
Authors: Forouzesh Alireza , Golsorkhi Mohammad S. , Savaghebi Mehdi , Baharizadeh Mehdi
Published: April 2021

This paper proposes an algorithm for detection and identification of the location of short circuit faults in islanded AC microgrids (MGs) with meshed topology. Considering the low level of fault current and dependency of the current angle on the control strategies, the legacy overcurrent protection schemes are not effective in in islanded MGs. To overcome this issue, the proposed algorithm detects faults based on the rms voltages of the distributed energy resources (DERs) by means of support vector machine classifiers. Upon detection of a fault, the DER which is electrically closest to the fault injects three interharmonic currents. The faulty zone is identified by comparing the magnitude of the interharmonic currents flowing through each zone. Then, the second DER connected to the faulty zone injects distinctive interharmonic currents and the resulting interharmonic voltages are measured at the terminal of each of these DERs. Using the interharmonic voltages as its features, a multi-class support vector machine identifies the fault location within the faulty zone. Simulations are conducted on a test MG to obtain a dataset comprising scenarios with different fault locations, varying fault impedances, and changing loads. The test results show that the proposed algorithm reliably detects the faults and the precision of fault location identification is above 90%.
Assessing the Sustainable Development and Renewable Energy Sources Relationship in EU Countries
Authors: Włodarczyk Bogdan , Firoiu Daniela , Ionescu George H. , Ghiocel Florin , Szturo Marek , Markowski Lesław
Published: April 2021

In the context of the 2030 Agenda for Sustainable Development, by adopting the EU Renewable Energy Directive and the European Green Deal, the European Union aims at an extremely ambitious goal to become climate neutral by 2050. This goal involves a massive investment plan to support this initiative, but also to reduce disparities between Member States, in order to transform the Union into a modern, resource-efficient, and competitive economy. The main objective of this paper is to investigate the sustainable development and renewable energy sources relationship in EU countries from a new perspective. Based on Eurostat available data and with the help of hierarchical clustering analysis, the Member States were divided in 2019 into five clusters, highlighting the key characteristics of the selected variables. The results of this research revealed high-performing groups of countries, as well as countries that need increased attention and additional support to become more efficient in achieving their sustainable development goals and renewable energy source targets.
Simulating the Impacts of Uncontrolled Electric Vehicle Charging in Low Voltage Grids
Authors: Haider Sajjad , Schegner Peter
Published: April 2021

Across the world, the impact of increasing electric vehicle (EV) adoption requires a better understanding. The authors hypothesize that the introduction of EV’s will cause significant overloading within low voltage distribution grids. To study this, several low voltage networks were reconstructed based on the literature and modelled using DigSilent Powerfactory, taking into account the stochastic variability of household electricity consumption, EV usage, and solar irradiance. The study incorporates two distinct usage scenarios—residential loads with varying EV penetrations without and with distributed grid tied generation of electricity. The Monte-Carlo simulation took into account population demographics and showed that in urban networks, EV introduction could lead to higher cable loading percentages than allowed, and in rural networks, this could lead to voltage drops beyond the allowed limits. Distributed generation (DG) in the form of solar power could significantly offset both these overloading characteristics, as well as the active and reactive power demands of the network, by between 10–50%, depending on the topology of the network.
Performance Evaluation Concept for Ocean Thermal Energy Conversion toward Standardization and Intelligent Design
Authors: Yasunaga Takeshi , Fontaine Kevin , Ikegami Yasuyuki
Published: April 2021

Ocean thermal energy conversion (OTEC) uses a very simple process to convert the thermal energy stored mainly in tropical oceans into electricity. In designs, operations, and evaluations, we need to consider the unique characteristics of OTEC to achieve the best performance or lower the electricity cost of projects. The concept and design constraints of OTEC power generation differ from those of conventional thermal power plants due to the utilization of a low temperature difference. This research theoretically recognizes the unique characteristics of the energy conversion system and summarizes the appropriate performance evaluation methods for OTEC based on finite-time thermodynamics and the equilibrium condition of the heat source. In addition, it presents the concept of normalization of thermal efficiency for OTEC and exergy efficiency based on the available thermal energy in the ocean defined as the transferable thermal energy from the ocean and the equilibrium condition as the dead state for exergy. The differences between conventional thermal efficiency and the effectiveness of the evaluation methods are visualized using the various reference design data, and it is ascertained that there is no clear relation between the conventional thermal efficiency and exergy efficiency, whereas the normalized thermal efficiency is definitely proportional to the exergy efficiency. Moreover, the exergy efficiency shows the effectiveness of the staging Rankine, Kalina, and Uehara cycles. Therefore, the normalized thermal efficiency and the exergy efficiency are important to analyze the heat and mass balance as well as improvement of the system.
Virtual Digital Substation Test System and Interoperability Assessments
Authors: Chen Linwei , Li Haiyu , Charton Thomas , Zhang Ray
Published: April 2021

Interoperability testing and analysis tools provide a means for achieving and assuring the integrity of multivendor intelligent electronic devices (IEDs) data exchanges. However, the testing and analysis are very time consuming and error prone, and these problems worsen when a substation becomes large and complex during the engineering process, commission, replacement, maintenance, and extension. To address this challenge, this paper presents a virtual digital substation test system (VDSTS) with interoperability analysis tools for assessing and identifying the engineering challenges for the multiple-vendors digital substation. This VDSTS consists of three parts: (i) A virtual digital substation modelling for generating real-time digital substation primary plant operation and fault conditions, (ii) a standard IEC 61850-based substation protection, automation, and control (PAC) system architecture with multivendor IEDs and bay solutions, and (iii) multivendor Substation Configuration description Language (SCL) tools and in-house built data visualisation tool. The study focuses on the interoperability testing of sampled values (SV), generic object-oriented substation events (GOOSE), and manufacturing message specification (MMS) communication services, as defined in IEC 61850. The main issues identified are compatibility issues of SCL tools, protocol implementation issues, different information models, and application limitations. The outcomes will help utilities to reduce the risks associated with the general rollout of digital substations.
Structural Design Optimization of Micro-Thermoelectric Generator for Wearable Biomedical Devices
Authors: Tanwar Amit , Lal Swatchith , Razeeb Kafil
Published: April 2021

Wearable sensors to monitor vital health are becoming increasingly popular both in our daily lives and in medical diagnostics. The human body being a huge source of thermal energy makes it interesting to harvest this energy to power such wearables. Thermoelectric devices are capable of converting the abundantly available body heat into useful electrical energy using the Seebeck effect. However, high thermal resistance between the skin and the device leads to low-temperature gradients (2–10 K), making it difficult to generate useful power by this device. This study focuses on the design optimization of the micro-thermoelectric generator for such low-temperature applications and investigates the role of structural geometries in enhancing the overall power output. Electroplated p-type bismuth antimony telluride (BiSbTe) and n-type copper telluride (CuTe) materials’ properties are used in this study. All the simulations and design optimizations were completed following microfabrication constraints along with realistic temperature gradient scenarios. A series of structural optimizations were performed including the thermoelectric pillar geometries, interconnect contact material layers and fill factor of the overall device. The optimized structural design of the micro-thermoelectric device footprint of 4.5 × 3.5 mm2, with 240 thermoelectric leg pairs, showcased a maximum power output of 0.796 mW and 3.18 mW when subjected to the low-temperature gradient of 5 K and 10 K, respectively. These output power values have high potential to pave the way of realizing future wearable devices.
Radial Variation of Wood Anatomical Properties Determines the Demarcation of Juvenile-Mature Wood in Schima superba
Authors: Wang Yunpeng , Zhang Rui , Zhou Zhichun
Published: April 2021

Schima superba is a precious broadleaf tree species that produces excellent timber. Analyzing the radial variation of wood anatomical properties within stems and determining the boundary between the juvenile and mature wood can provide a theoretical basis for the breeding and cultivation of S. superba. Herein, 30 54-year-old trees were used to analyze the radial variation of wood anatomical properties qualitatively. The correlation among wood properties was analyzed. On this basis, four types of model were used to predict the wood properties quantitatively, and the optimal segmentation model was used to determine the boundary between juvenile and mature wood. The results showed that the variation of the early stage (before the 20th year) was larger than that of the later stage (after the 20th year); moreover, the variation of the vessel features (9.56%) was greater than that of the fiber features (7.42%), the vessel lumen diameter (11.94%) and the fiber length (8.00%) had the most variation. There were three radial variation patterns in the wood properties. In the early stage, there was a significant positive correlation between the ring width and wood air-dry density (0.78) and wood basic density (0.89), and a significant negative correlation between the ring width and the fiber characters (−0.79~−0.93) and vessel characters (−0.64~−0.90). The growth models of Logistic and Richards were more suitable (R2 = 84.2%~95.2%) for the radial variation of wood anatomical properties than the nonlinear least square model (R2 = 67.7%~90.9%). The transition wood between juvenile and mature wood of S. superba was from the 11th to the 16th year based on aggregative indicators from the pith to bark at breast height. Finally, when taken together, the wood anatomical properties of S. superba had regular radial variation. Breeding programs need to consider both growth and wood anatomical properties in the early stage, but they can be neglected in the mature stage. The formation of mature wood of S. superba occurred after the 16th year.
Wound-Induced Changes in Antioxidant Enzyme Activities in Skin Mucus and in Gene Expression in the Skin of Gilthead Seabream (Sparus aurata L.)
Authors: Espinosa-Ruíz Cristóbal , Esteban María Ángeles
Published: April 2021

This study investigated the antioxidant enzyme activities in the skin mucus of gilthead seabream (Sparus aurata L.) at 3 and 7 days post-wounding (dpw). The expression levels of the genes that encode stress proteins (grp170, grp94, grp75, sod and hsp70) and skin regeneration-related proteins (tf, igf1, tgfb1, der1, apo1 and erdj3) in the skin also were determined. Mucus and skin samples were obtained from the left and right flanks of non-wounded and wounded fish. In both flanks of the wounded fish, catalase and glutathione reductase activities in the skin mucus increased (p < 0.05) at 3 and 7 dpw (100 ± 31% and 111 ± 25%, respectively), whereas superoxide dismutase activity increased (p < 0.05) only at 7 dpw (135 ± 15%). The expression levels of stress proteins in the skin of the wounded flank of the wounded fish mainly increased at 7 dpw (grp170 increased to 288 ± 85%, grp94 to 502 ± 143%, grp75 to 274 ± 69%, sod to 569 ± 99%, and hsp70 increased to 537 ± 14%) (p < 0.05). However, the expression levels of the tissue regeneration-related genes varied depending on the flank investigated, on the experimental time, and on the gene studied. To the best of our knowledge, this is the first work to determine the effect of a wound in different skin parts of the same fish.
Frequency Power Spectra of Global Quantities in Unsteady Magnetoconvection
Authors: Das Sandip , Kumar Krishna
Published: April 2021

We present the results of direct numerical simulations of power spectral densities for kinetic energy, convective entropy, and heat flux for unsteady Rayleigh–Bénard magnetoconvection in the frequency space. For larger values of frequency, the power spectral densities for all the global quantities vary with frequency (f) as f−2. The scaling exponent is independent of Rayleigh number, Chandrasekhar’s number, and thermal Prandtl number.
Protein Profile and Simulated Digestive Behavior of Breast Milk from Overweight and Normal Weight Mothers
Authors: Sánchez-Hernández Silvia , Théron Laëtitia , Jiménez-Barrios Pablo , Olalla-Herrera Manuel , Recio Isidra , Miralles Beatriz
Published: April 2021

Human milk proteins have shown to vary in concentration and distribution through lactation. However, while some regulatory components, such as hormones, have shown associations with regard to the mothers’ body mass index, there is limited information on the possible influence of this condition on the whole protein distribution. The objective of this study was to evaluate the protein profile of human milk from normal weight and overweight or obese mothers to identify differences in protein expression in colostrum, transitional and mature milk. The mass spectrometry analysis showed the ability to class with a high degree of confidence the lactation state and the milk profile according to the mother’s condition. Individual milk samples were subjected to a digestion in vitro model that takes into account the specificities of the gastrointestinal conditions of full-term newborn infants. The digestion products were compared with available data from the digestive contents in newborns. The behavior of the most abundant proteins and the overall peptide generation and survival, showed good correspondence with in vivo data.
Evaluation of Immersion and Spray Applications of Antimicrobial Treatments for Reduction of Campylobacter jejuni on Chicken Wings
Authors: Gonzalez Sara V. , Geornaras Ifigenia , Nair Mahesh N. , Belk Keith E.
Published: April 2021

The decontamination efficacy of antimicrobial treatments against Campylobacter jejuni on chicken wings was evaluated. Chicken wings surface-inoculated with C. jejuni (3.9 log colony-forming units [CFU]/mL) were left untreated (control) or were treated by immersion (5 s) or in a spray cabinet (4 s) with water, a sulfuric acid and sodium sulfate blend (SSS; pH 1.2), formic acid (1.5%), peroxyacetic acid (PAA; 550 ppm), or PAA (550 ppm) that was pH-adjusted (acidified) with SSS (pH 1.2) or formic acid (1.5%). All evaluated immersion and spray chemical treatments effectively (p < 0.05) lowered C. jejuni populations on chicken wings. Spray application of chemical treatments resulted in immediate pathogen reductions ranging from 0.5 to 1.2 log CFU/mL, whereas their application by immersion lowered initial pathogen levels by 1.7 to 2.2 log CFU/mL. The PAA and acidified PAA treatments were equally (p ≥ 0.05) effective at reducing initial C. jejuni populations, however, following a 24 h refrigerated (4 °C) storage period, wings treated with acidified PAA had lower (p < 0.05) pathogen levels than samples that had been treated with PAA that was not acidified. Findings of this study should be useful to the poultry industry in its efforts to control Campylobacter contamination on chicken parts.
Shale Poroelastic Effects on Well Performance Analysis of Shale Gas Reservoirs
Authors: Fathi Ebrahim , Belyadi Fatemeh , Jabbar Bahiya
Published: April 2021

The effect of poroelastic properties of the shale matrix on gas storage and transport mechanisms has gained significant attention, especially during history-matching and hydrocarbon production forecasting in unconventional reservoirs. The common oil and gas industry practice in unconventional reservoir simulation is the extension of conventional reservoir simulation that ignores the dynamic behavior of matrix porosity and permeability as a function of reservoir effective net stress. This approach ignores the significant impact of the poroelastic characteristics of the shale matrix on hydrocarbon production. The poroelastic characteristics of the shale matrix highly relate to the shale matrix geomechanical properties, such as the Young’s Modulus, Poisson’s ratio, bulk modulus, sorption behavior, total organic content (TOC), mineralogy and presence of natural fractures in the multi-scale shale structure. In this study, in order to quantify the effect of the poroelasticity of the shale matrix on gas production, a multi-continuum approach was employed in which the shale matrix was divided into organic materials, inorganic materials and natural fractures. The governing equations for gas transport and storage in shale were developed from the basic fundamentals of mass and momentum conservation equations. In this case, gas transport in organics was assumed to be diffusive, while gas transport in inorganics was governed by convection. Finally, a fracture system was added to the multi-scale shale gas matrix, and the poroelastic effect of the shale matrix on transport and storage was investigated. A modified Palmer and Mansoori model (1998) was used to include the pore compression, matrix swelling/shrinkage and desorption-induced deformation of shale organic matter on the overall pore compressibility of the shale matrix. For the inorganic part of the matrix, relations between rock mechanical properties and the pore compressibility were obtained. A dual Langmuir–Henry isotherm was also used to describe the sorption behavior of shale organic materials. The coupled governing equations of gas storage and transport in the shale matrix were then solved using the implicit finite difference approach using MATLAB. For this purpose, rock and fluid properties were obtained using actual well logging and core analysis of the Marcellus gas well. The results showed the importance of the poroelastic effect on the pressure response and rate of gas recovery from the shale matrix. The effect was found to be mainly due to desorption-induced matrix deformation at an early stage. Coupling the shale matrix gas production including the poroelastic effect in history-matching the gas production from unconventional reservoirs will significantly improve engineering completion design optimization of the unconventional reservoirs by providing more accurate and robust production forecasts for each hydraulic fracture stage.
Properties of Faint X-ray Activity of XTE J1908+094 in 2019
Authors: Chatterjee Debjit , Jana Arghajit , Chatterjee Kaushik , Bhowmick Riya , Nath Sujoy Kumar , Chakrabarti Sandip K. , Mangalam A. , Debnath Dipak
Published: April 2021

We study the properties of the faint X-ray activity of Galactic transient black hole candidate XTE J1908+094 during its 2019 outburst. Here, we report the results of detailed spectral and temporal analysis during this outburst using observations from Nuclear Spectroscopic Telescope Array (NuSTAR). We have not observed any quasi-periodic-oscillations (QPOs) in the power density spectrum (PDS). The spectral study suggests that the source remained in the softer (more precisely, in the soft–intermediate) spectral state during this short period of X-ray activity. We notice a faint but broad Fe Kα emission line at around 6.5 keV. We also estimate the probable mass of the black hole to be 6.5−0.7+0.5M⊙, with 90% confidence.
MTHFR C677T and A1298C Polymorphisms in Breast Cancer, Gliomas and Gastric Cancer: A Review
Authors: Petrone Igor , Bernardo Paula Sabbo , dos Santos Everton Cruz , Abdelhay Eliana
Published: April 2021

Folate (vitamin B9) is found in some water-soluble foods or as a synthetic form of folic acid and is involved in many essential biochemical processes. Dietary folate is converted into tetrahydrofolate, a vital methyl donor for most methylation reactions, including DNA methylation. 5,10-methylene tetrahydrofolate reductase (MTHFR) is a critical enzyme in the folate metabolism pathway that converts 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate, which produces a methyl donor for the remethylation of homocysteine to methionine. MTHFR polymorphisms result in reduced enzyme activity and altered levels of DNA methylation and synthesis. MTHFR polymorphisms have been linked to increased risks of several pathologies, including cancer. Breast cancer, gliomas and gastric cancer are highly heterogeneous and aggressive diseases associated with high mortality rates. The impact of MTHFR polymorphisms on these tumors remains controversial in the literature. This review discusses the relationship between the MTHFR C677T and A1298C polymorphisms and the increased risk of breast cancer, gliomas, and gastric cancer. Additionally, we highlight the relevance of ethnic and dietary aspects of population-based studies and histological stratification of highly heterogeneous tumors. Finally, this review discusses these aspects as potential factors responsible for the controversial literature concerning MTHFR polymorphisms.
Maternal Uniparental Disomy of Chromosome 20 (UPD(20)mat) as Differential Diagnosis of Silver Russell Syndrome: Identification of Three New Cases
Authors: Tannorella Pierpaola , Minervino Daniele , Guzzetti Sara , Vimercati Alessandro , Calzari Luciano , Patti Giuseppa , Maghnie Mohamad , Allegri Anna Elsa Maria , Milani Donatella , Scuvera Giulietta , Mariani Milena , Modena Piergiorgio , Selicorni Angelo , Larizza Lidia , Russo Silvia
Published: April 2021

Silver Russell Syndrome (SRS, MIM #180860) is a rare growth retardation disorder in which clinical diagnosis is based on six features: pre- and postnatal growth failure, relative macrocephaly, prominent forehead, body asymmetry, and feeding difficulties (Netchine–Harbison clinical scoring system (NH-CSS)). The molecular mechanisms consist in (epi)genetic deregulations at multiple loci: the loss of methylation (LOM) at the paternal H19/IGF2:IG-DMR (chr11p15.5) (50%) and the maternal uniparental disomy of chromosome 7 (UPD(7)mat) (10%) are the most frequent causes. Thus far, about 40% of SRS remains undiagnosed, pointing to the need to define the rare mechanisms in such a consistent fraction of unsolved patients. Within a cohort of 176 SRS with an NH-CSS ≥ 3, a molecular diagnosis was disclosed in about 45%. Among the remaining patients, we identified in 3 probands (1.7%) with UPD(20)mat (Mulchandani–Bhoj–Conlin syndrome, OMIM #617352), a molecular mechanism deregulating the GNAS locus and described in 21 cases, characterized by severe feeding difficulties associated with failure to thrive, preterm birth, and intrauterine/postnatal growth retardation. Our patients share prominent forehead, feeding difficulties, postnatal growth delay, and advanced maternal age. Their clinical assessment and molecular diagnostic flowchart contribute to better define the characteristics of this rare imprinting disorder and to rank UPD(20)mat as the fourth most common pathogenic molecular defect causative of SRS.
Identification of a Candidate Gene for the Novel Cytoplasmic Male Sterility Derived from Inter-Subspecific Crosses in Rice (Oryza sativa L.)
Authors: Jin Zhuo , Seo Jeonghwan , Kim Backki , Lee Seung Young , Koh Hee-Jong
Published: April 2021

Tetep-cytoplasmic male sterility (CMS) was developed through successive backcrosses between subspecies indica and japonica in rice (Oryza sativa L.), which showed abnormal anther dehiscence phenotypes. Whole genome sequencing and de novo assembly of the mitochondrial genome identified the chimeric gene orf312, which possesses a transmembrane domain and overlaps with two mitotype-specific sequences (MSSs) that are unique to the Tetep-CMS line. The encoded peptide of orf312 was toxic to Escherichia coli and inhibited cell growth compared to the control under isopropyl-β-D-1-thiogalactopyranoside (IPTG) induction. The peptide of orf312 contains COX11-interaction domains, which are thought to be a main functional domain for WA352c in the wild abortive (WA-CMS) line of rice. A QTL for Rf-Tetep (restorer-of-fertility gene(s) originating from Tetep) was identified on chromosome 10. In this region, several restorer genes, Rf1a, Rf1b, and Rf4, have previously been reported. Collectively, the interactions of orf312, a candidate gene for Tetep-CMS, and Rf-Tetep, a restorer QTL, confer male sterility and fertility restoration, respectively, which enables a hybrid rice breeding system. Further studies on orf312 and isolation of Rf-Tetep will help to identify the underlying molecular mechanism of mitochondrial ORFs with the COX11-interaction domains.
Protective Role of a TMPRSS2 Variant on Severe COVID-19 Outcome in Young Males and Elderly Women
Authors: Monticelli Maria , Hay Mele Bruno , Benetti Elisa , Fallerini Chiara , Baldassarri Margherita , Furini Simone , Frullanti Elisa , Mari Francesca ,   GEN-COVID Multicenter Study, Andreotti Giuseppina , Cubellis Maria , Renieri Alessandra
Published: April 2021

The protease encoded by the TMPRSS2 gene facilitates viral infections and has been implicated in the pathogenesis of SARS-CoV-2. We analyzed the TMPRSS2 sequence and correlated the protein variants with the clinical features of a cohort of 1177 patients affected by COVID-19 in Italy. Nine relatively common variants (allele frequency > 0.01) and six missense variants which may affect the protease activity according to PolyPhen-2 in HumVar-trained mode were identified. Among them, p.V197M (p.Val197Met) (rs12329760) emerges as a common variant that has a deleterious effect on the protease and a protective effect on the patients. Its role appears particularly relevant in two subgroups of patients—young males and elderly women—and among those affected by co-morbidities, where the variant frequency is higher among individuals who were mildly affected by the disease and did not need hospitalization or oxygen therapy than among those more severely affected, who required oxygen therapy, ventilation or intubation. This study provides useful information for the identification of patients at risk of developing a severe form of COVID-19, and encourages the usage of drugs affecting the expression of TMPRSS2 or inhibiting protein activity.
Application of Genome Sequencing from Blood to Diagnose Mitochondrial Diseases
Authors: Rius Rocio , Compton Alison G. , Baker Naomi L. , Welch AnneMarie E. , Coman David , Kava Maina P. , Minoche Andre E. , Cowley Mark J. , Thorburn David R. , Christodoulou John
Published: April 2021

Mitochondrial diseases can be caused by pathogenic variants in nuclear or mitochondrial DNA-encoded genes that often lead to multisystemic symptoms and can have any mode of inheritance. Using a single test, Genome Sequencing (GS) can effectively identify variants in both genomes, but it has not yet been universally used as a first-line approach to diagnosing mitochondrial diseases due to related costs and challenges in data analysis. In this article, we report three patients with mitochondrial disease molecularly diagnosed through GS performed on DNA extracted from blood to demonstrate different diagnostic advantages of this technology, including the detection of a low-level heteroplasmic pathogenic variant, an intragenic nuclear DNA deletion, and a large mtDNA deletion. Current technical improvements and cost reductions are likely to lead to an expanded routine diagnostic usage of GS and of the complementary “Omic” technologies in mitochondrial diseases.
Molecular Phylogeny and Evolution of Amazon Parrots in the Greater Antilles
Authors: Kolchanova Sofiia , Komissarov Alexey , Kliver Sergei , Mazo-Vargas Anyi , Afanador Yashira , Velez-Valentín Jafet , de la Rosa Ricardo Valentín , Castro-Marquez Stephanie , Rivera-Colon Israel , Majeske Audrey J. , Wolfsberger Walter W. , Hains Taylor , Corvelo André , Martinez-Cruzado Juan-Carlos , Glenn Travis C. , Robinson Orlando , Koepfli Klaus-Peter , Oleksyk Taras K.
Published: April 2021

Amazon parrots (Amazona spp.) colonized the islands of the Greater Antilles from the Central American mainland, but there has not been a consensus as to how and when this happened. Today, most of the five remaining island species are listed as endangered, threatened, or vulnerable as a consequence of human activity. We sequenced and annotated full mitochondrial genomes of all the extant Amazon parrot species from the Greater Antillean (A. leucocephala (Cuba), A. agilis, A. collaria (both from Jamaica), A. ventralis (Hispaniola), and A. vittata (Puerto Rico)), A. albifrons from mainland Central America, and A. rhodocorytha from the Atlantic Forest in Brazil. The assembled and annotated mitogenome maps provide information on sequence organization, variation, population diversity, and evolutionary history for the Caribbean species including the critically endangered A. vittata. Despite the larger number of available samples from the Puerto Rican Parrot Recovery Program, the sequence diversity of the A. vittata population in Puerto Rico was the lowest among all parrot species analyzed. Our data support the stepping-stone dispersal and speciation hypothesis that has started approximately 3.47 MYA when the ancestral population arrived from mainland Central America and led to diversification across the Greater Antilles, ultimately reaching the island of Puerto Rico 0.67 MYA. The results are presented and discussed in light of the geological history of the Caribbean and in the context of recent parrot evolution, island biogeography, and conservation. This analysis contributes to understating evolutionary history and empowers subsequent assessments of sequence variation and helps design future conservation efforts in the Caribbean.
Effects of Different Assistive Seats on Ability of Elderly in Sit-To-Stand and Back-To-Sit Movements
Authors: Lou Shu-Zon , You Jia-Yuan , Tsai Yi-Chuan , Chen Yu-Chi
Published: April 2021

The ability to perform sit-to-stand (STS) and back-to-sit (BTS) movements is important for the elderly to live independently and maintain a reasonable quality of life. Accordingly, this study investigated the STS and BTS motions of 28 healthy older adults (16 male and 12 female) under three different seat conditions, namely nonassisted, self-designed lifting seat, and UpLift seat. The biomechanical data were acquired using a three-dimensional (3D) motion analysis system and force plates, and were examined by one-way repeated-measures ANOVA to investigate the effects of the different seat conditions on the joint angle, joint moments, and movement duration time (α = 0.05). No significant difference was observed in the STS duration among the three test conditions. However, the BTS duration was significantly increased in the UpLift seat condition. Moreover, the peak flexion angle of the hip during STS motion was also significantly higher in the UpLift condition. For both motions (STS and BTS), the lifting seats significantly decreased the knee and hip joint moments, but significantly increased the ankle joint moment. Moreover, compared to the nonassistive seat, both assistive lifting seats required a greater ankle joint strength to complete the STS and BTS motions.
Brucella Shunt Infection Complicated by Peritonitis: Case Report and Review of the Literature
Authors: Al-Qarhi Rawan , Al-Dabbagh Mona
Published: April 2021

Brucellosis is an endemic zoonotic disease in the Mediterranean basin and Middle East. The disease remains a diagnostic challenge due to an increasing trend of ambiguous and non-specific manifestations. We report a rare case of a 9-year-old boy who had a left frontotemporal arachnoid cyst with cystoperitoneal shunt who presented with fever for 2 weeks with gastrointestinal symptoms. He had no neurological manifestations. Diagnosis of Brucella shunt infection complicated with a peritoneal collection was established by isolation of the organism from cerebrospinal fluid (CSF) culture. Successful treatment was accomplished by shunt replacement and intravenous antibiotics followed by step-down oral therapy for an 18-month duration based on serological and radiological responses with no sequelae. We also reviewed the reported cases of CSF shunt infection in the literature for further guidance. Brucella shunt infection may be difficult to diagnose due to the diversity of signs and symptoms and the low yield on culture. Brucellosis should be always kept in mind in the differential diagnosis of patients living in endemic area with fever and non-specific symptoms. Diagnosis depends on a high index of suspicion. In addition to drug therapy, device replacement is advised to prevent treatment failure.