bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Application of Volatile Organic Compounds as Potential Biomarkers for Detecting Digestive Neoplasia: A Systematic Review
Authors: Dima Augustin Catalin , Balaban Daniel Vasile , Dima Alina
Published: December 2021

Volatile organic compounds (VOCs) are part of the exhaled breath that were proposed as non-invasive breath biomarkers via different human discharge products like saliva, breath, urine, blood, or tissues. Particularly, due to the non-invasive approach, VOCs were considered as potential biomarkers for non-invasive early cancer detection. We herein aimed to review the data over VOCs utility in digestive neoplasia as early diagnosis or monitoring biomarkers. A systematic literature search was done using MEDLINE via PubMed, Cochrane Library, and Thomson Reuters’ Web of Science Core Collection. We identified sixteen articles that were included in the final analysis. Based on the current knowledge, we cannot identify a single VOC as a specific non-invasive biomarker for digestive neoplasia. Several combinations of up to twelve VOCs seem promising for accurately detecting some neoplasia types. A combination of different VOCs breath expression are promising tools for digestive neoplasia screening.
Non-Simultaneous Bilateral Ischemic Optic Neuropathy Related to High Altitude and Airplane Flight in a Patient with Cerebral Small Vessel Disease
Authors: Boned-Murillo Ana , Esteban-Floria Olivia , Martinez-Velez Mireya , Mateo Gabas Javier , Ascaso Puyuelo Francisco Javier
Published: December 2021

Non-arteritic anterior ischemic optic neuropathy (NA-AION) is considered the most frequent type of acute optic neuropathy. A 61-year-old woman presented with a NA-AION in her right eye within 24 h following an airplane flight. One year later, after driving for 10 days with a daily accumulated altitude of 1500 m, she developed a NA-AION in her left eye. Systemic disorders were investigated, and cerebral small vessel disease was observed via cranial computed tomography. An inadequate response to hypoxia, in a patient with individual susceptibility, could lead to reduced blood supply to the optic nerve head, which could represent an underlying cause of NA-AION.
Molecular Classification of Soft Tissue and Bone Tumors
Authors: Creytens David
Published: December 2021

Soft tissue and bone tumors constitute a large and heterogeneous group of tumors comprising >100 distinct histological types and subtypes, which are diagnosed and classified using criteria from the World Health Organization (WHO) Classification of Tumors [...]
An Analysis of Underemployment among Young Graduates: The Case of a Higher Education Institution in South Africa
Authors: Meyer Daniel Francois , Mncayi Precious
Published: December 2021

Labour markets have undergone vast transformations over the last few years. There are arguments that employment and unemployment measures have not been adequate in understanding the complexities of labour markets. Research on labour underutilisation has focused on one side of the spectrum, which is just about the scarcity of jobs. However, there is more to the labour market than just scarcity of jobs, and many researchers believe unemployment is not a complete measurement of unused labour capacity, which is why this study aimed to investigate the existence of underemployment from the perceptions of young graduates themselves. In this regard, the definition of young people entailed those younger than 35 years as officially defined in South Africa. The study employed a primary data method of data collection in which an online survey was used to collect the necessary data from the alumni database of a South African university. The study used binary logistic regression to determine factors that contributed to or influenced underemployment status. The main findings indicated that underemployment was rife according to age, where younger graduates (20–29 years) were more likely to be underemployed compared to their more mature counterparts; that is, those in the 30–34 age category, with non-White graduates most likely to encounter underemployment compared to their counterparts. This study resulted in important findings that carry significant policy implications and recommendations that may be crucial in correcting the current employment mismatches in the South African graduate labour market.
Systemic Response: Developing a Strategic Response to Support Young Men of Color during COVID-19 Pandemic
Authors: Martinez Eligio , Brooms Derrick R. , Franklin William , Smith Matthew , Bailey Andre , Quarles Markel
Published: December 2021

The aim of this work is to provide insight into the California State University Young Men of Color Consortium (CSU YMOC), which was created to explore the unique challenges young men of color face during their postsecondary experiences, as well as advance effective approaches to better support them. Specifically, we focus on CSU Male Success Initiative programs and detail how campus partners worked collaboratively to support men of color during the previous academic year amid the COVID-19 pandemic. Given the ways that the ongoing COVID-19 pandemic disrupted education across the P-16 spectrum, the MSIs were positioned uniquely to support some of the challenges that students endured. Recent reports reveal that the pandemic has exacerbated a number of difficulties, both old and new(er), that men of color experience in their college years, from accessing and transitioning to matriculating and persisting in higher education. We provide an overview of the CSU YMOC Consortium and present details about one program element (Critical Conversations) we incorporated this year as a measure to be responsive to challenges brought on by the pandemic. Finally, partners at three institutions share reflections on how their MSI shifted their efforts to meet students’ needs and provide support.
Belonging and Global Citizenship in a STEM University
Authors: Viola Julianne K.
Published: December 2021

For the past two decades, there has been a resurgence in the actualization of civic missions in universities; these universities have continued to demonstrate commitment to educate for the purpose of global citizenship. Global citizenship is both a skillset and a mindset. As universities engage in efforts to increase students’ capabilities for living and working in a diverse society, research in this area has often focused on students of social science disciplines in the United States, presenting an opportunity for an investigation into students’ sense of belonging and global citizenship in the STEM university context in the United Kingdom. Building on prior civic scholarship, which defines citizenship in part as a sense of belonging, this paper presents interview data from a longitudinal, mixed-methods study at a STEM university in the United Kingdom to explore the meanings and experiences of students’ belonging in a multicultural institution, and their attitudes about current political issues before and during the COVID-19 pandemic. The study presents theoretical and practical implications for citizenship education research and practice.
Gender Digital Divide and Education in Latin America: A Literature Review
Authors: Ancheta-Arrabal Ana , Pulido-Montes Cristina , Carvajal-Mardones Víctor
Published: December 2021

Gender equity in education is one of the main targets for social justice and sustainable development. This literature review, from a gender approach, was conducted to understand how the gender digital divide (GDD) in information and communication technologies (ICT) and education are related in Latin American countries. A total of 28 articles have been analyzed as a satisfactory sample of the scientific literature to examine how this relation is explored and its influence, to acknowledge political stakeholders, as well as provide information and proposals to address the digital gender divide in education research in this region. The results show the need to develop research from the pedagogical and gender perspectives in Latin America, since they are not represented within an obvious problem.
Becoming a STEM-Focused School District: Administrators’ Roles and Experiences
Authors: Wieselmann Jeanna R. , Roehrig Gillian H. , Ring-Whalen Elizabeth A. , Meagher Thomas
Published: December 2021

Science, technology, engineering, and mathematics (STEM) schools and districts continue to emerge, and while some research highlights critical components to be included in STEM schools, there is a need to learn more about the process of becoming a STEM school or district. In this study, we investigated a rural United States school district’s development and expansion of its STEM education focus, which started in the years leading up to the district’s first STEM school opening in 2012. We addressed the research question: How is a district-wide STEM education vision developed, enacted, and sustained by various administrative stakeholders? We interviewed 11 participants, all of whom had some level of administrative responsibility related to the district’s STEM mission, coded interviews based on the critical components of STEM schools, and used narrative inquiry methods to describe the district’s STEM transition from these administrators’ perspectives. Our analysis revealed that several key critical components were central to this district’s STEM mission. These components included elements related to leadership, reform-based instructional strategies, and teachers’ professional learning. By focusing on different elements at different times and prioritizing several key components throughout, this district was able to achieve its goal of providing STEM instruction to all of the elementary and middle school students.
Self-Absorption Analysis of Perovskite-Based Luminescent Solar Concentrators
Authors: Sun Yujian , Zhang Yongcao , Li Yuxin , Li Yilin
Published: December 2021

Luminescent solar concentrators (LSCs) are considered promising in their application as building-integrated photovoltaics (BIPVs). However, they suffer from low performance, especially in large-area devices. One of the key issues is the self-absorption of the luminophores. In this report, we focus on the study of self-absorption in perovskite-based LSCs. Perovskite nanocrystals (NCs) are emerging luminophores for LSCs. Studying the self-absorption of perovskite NCs is beneficial to understanding fundamental photon transport properties in perovskite-based LSCs. We analyzed and quantified self-absorption properties of perovskite NCs in an LSC with the dimensions of 6 in × 6 in × 1/4 in (152.4 mm × 152.4 mm × 6.35 mm) using three approaches (i.e., limited illumination, laser excitation, and regional measurements). The results showed that a significant number of self-absorption events occurred within a distance of 2 in (50.8 mm), and the photo surface escape due to the repeated self-absorption was the dominant energy loss mechanism.
Resource Allocation in NOMA-Assisted Ambient Backscatter Communication System
Authors: Liu Qiang , Sun Songlin , Hou Jijiang , Jia Hongbiao , Kadoch Michel
Published: December 2021

This paper considers a non-orthogonal multiple access (NOMA)-assisted ambient backscatter communication (AmBC) system. To maximize the achievable sum rate (ASR) of the AmBC system, a joint optimization problem over a backscatter device (BD) grouping strategy, reflection coefficients, and decoding order is formulated, where the BD grouping strategy contains the number of BD groups and the BD allocation strategy. The BD grouping strategy, the reflection coefficients, and the decoding order are all intertwined, and the global search is extremely complex. As a result, we propose a four-step optimization algorithm. First, we give the closed-form optimal solution of the BD decoding order and reflection coefficient for a given grouping strategy. Then, for a given number of BD groups, we propose a low-complexity BD allocation strategy based on the complexity–performance trade-off. Finally, the number of BD groups with the largest ASR is selected as the global optimal number of BD groups. The simulation results show that the proposed four-step optimization algorithm is better than the benchmark solution.
Statistical Beamforming Techniques for Power Domain NOMA System
Authors: Aljohani Abdulah Jeza , Moinuddin Muhammad
Published: December 2021

Power-domain non-orthogonal multiple access (NOMA) assigns different power levels for near and far users in order to discriminate their signals by employing successive interference cancellation (SIC) at the near user. In this context, multiple-input-single-output NOMA (MISO-NOMA), where the base station (BS) is equipped with multiple antennas while each mobile user has a single antenna receiver, is shown to have a better overall performance by using the knowledge of instantaneous channel state information (CSI). However, this requires prior estimation of CSI using pilot transmission, which increases the transmission overhead. Moreover, its performance is severely degraded in the presence of CSI estimation errors. In this work, we provide statistical beamforming solutions for downlink power-domain NOMA that utilize only knowledge of statistical CSI, thus reducing the transmission overhead significantly. First, we derive the outage probabilities for both near and far users in the multi-user NOMA system without imposing strong assumptions, such as Gaussian or Chi-square distribution. This is done by employing the exact characterization of the ratio of indefinite quadratic form (IQF). Second, this work proposes two techniques to obtain the optimal solution for beam vectors which rely on the derived outage probabilities. Specifically, these two methods are based on (1) minimization of total beam power while constraining the outage probabilities to the QoS threshold, and (2) minimization of outage probabilities while constraining the total beam power. These proposed methods are non-convex function of beam vectors and, hence, are solved using numerical optimization via sequential quadratic programming (SQP). Since the proposed methods do not require pilot transmission for channel estimation, they inherit better spectral efficiency. Our results validate the theoretical findings and prove the supremacy of the proposed method.
GAN-Based ROI Image Translation Method for Predicting Image after Hair Transplant Surgery
Authors: Hwang Do-Yeon , Choi Seok-Hwan , Shin Jinmyeong , Kim Moonkyu , Choi Yoon-Ho
Published: December 2021

In this paper, we propose a new deep learning-based image translation method to predict and generate images after hair transplant surgery from images before hair transplant surgery. Since existing image translation models use a naive strategy that trains the whole distribution of translation, the image translation models using the original image as the input data result in converting not only the hair transplant surgery region, which is the region of interest (ROI) for image translation, but also the other image regions, which are not the ROI. To solve this problem, we proposed a novel generative adversarial network (GAN)-based ROI image translation method, which converts only the ROI and retains the image for the non-ROI. Specifically, by performing image translation and image segmentation independently, the proposed method generates predictive images from the distribution of images after hair transplant surgery and specifies the ROI to be used for generated images. In addition, by applying the ensemble method to image segmentation, we propose a more robust method through complementing the shortages of various image segmentation models. From the experimental results using a real medical image dataset, e.g., 1394 images before hair transplantation and 896 images after hair transplantation, to train the GAN model, we show that the proposed GAN-based ROI image translation method performed better than the other GAN-based image translation methods, e.g., by 23% in SSIM (Structural Similarity Index Measure), 452% in IoU (Intersection over Union), and 42% in FID (Frechet Inception Distance), on average. Furthermore, the ensemble method that we propose not only improves ROI detection performance but also shows consistent performances in generating better predictive images from preoperative images taken from diverse angles.
A Low Power 1024-Channels Spike Detector Using Latch-Based RAM for Real-Time Brain Silicon Interfaces
Authors: Saggese Gerardo , Strollo Antonio Giuseppe Maria
Published: December 2021

High-density microelectrode arrays allow the neuroscientist to study a wider neurons population, however, this causes an increase of communication bandwidth. Given the limited resources available for an implantable silicon interface, an on-fly data reduction is mandatory to stay within the power/area constraints. This can be accomplished by implementing a spike detector aiming at sending only the useful information about spikes. We show that the novel non-linear energy operator called ASO in combination with a simple but robust noise estimate, achieves a good trade-off between performance and consumption. The features of the investigated technique make it a good candidate for implantable BMIs. Our proposal is tested both on synthetic and real datasets providing a good sensibility at low SNR. We also provide a 1024-channels VLSI implementation using a Random-Access Memory composed by latches to reduce as much as possible the power consumptions. The final architecture occupies an area of 2.3 mm2, dissipating 3.6 µW per channels. The comparison with the state of art shows that our proposal finds a place among other methods presented in literature, certifying its suitability for BMIs.
Crystal Structure Algorithm (CryStAl) Based Selective Harmonic Elimination Modulation in a Cascaded H-Bridge Multilevel Inverter
Authors: Farooqui Shoeb Azam , Shees Mohammad Munawar , Alsharekh Mohammed F. , Alyahya Saleh , Khan Rashid Ahmed , Sarwar Adil , Islam Muhammad , Khan Sheroz
Published: December 2021

This paper introduces an effective Selective Harmonic Elimination (SHE) modulation technique in a five, seven, and nine-level cascaded H-bridge (CHB) multilevel inverter (MLI). Minimization of the harmonics and device counts is the basis for the ongoing research in the area of MLI. Reduced harmonics and hence the lower Total Harmonic Distortion (THD), improve the output power quality. SHE is a low-frequency modulation scheme to achieve this goal. SHE techniques are used to eliminate the distinct lower-order harmonics by determining the optimum switching angles. These angles are evaluated by solving the non-linear transcendental equations using any optimization technique. For this purpose, the Crystal Structure Algorithm (CryStAl) has been used in this paper. It is a metaheuristic, nature-inspired, and highly efficient optimization technique. CryStAl is a simple and parameter-free algorithm that doesn’t require the determination of any internal parameter during the optimization process. It is based on the concept of crystal structure formation by joining the basis and lattice point. This natural occurrence can be realized in crystalline minerals in their symmetrically organized components: ions, atoms, and molecules. The concept has been utilized to solve non-linear transcendental equations. SIMULINK/MATLAB environment has been used for the simulation. The simulation result shows that the crystal structure algorithm is very effective and excels the other metaheuristic algorithm. Hardware results validate the performance.
Distributed Remote E-Voting System Based on Shamir’s Secret Sharing Scheme
Authors: Tejedor-Romero Marino , Orden David , Marsa-Maestre Ivan , Junquera-Sanchez Javier , Gimenez-Guzman Jose Manuel
Published: December 2021

A number of e-voting systems have been proposed in the last decades, attracting the interest of the research community. The challenge is far from being fully addressed, especially for remote systems. In this work, we propose DiverSEC, a distributed, remote e-voting system based on Shamir secret sharing, operations in Galois field and mixnets, which enables end-to-end vote verification. Parties participate as nodes in the network, protecting their interests and ensuring process integrity due to the conflicting interests. The threat model is very conservative, not letting even the most privileged actors to compromise votes privacy or integrity. Security in depth is implemented, overlapping different mechanisms to offer guarantees even in the most adverse operating conditions. The main contributions of the resulting system are our proposal for secret-sharing among the political parties, which guarantees that no party can compromise the integrity of the ballot without being detected and identified in real time, and the computational and architectural scalability of the proposal, which make it easy to implement.
Optimization for a Photovoltaic Pumping System Using Indirect Field Oriented Control of Induction Motor
Authors: Saady Ikram , Karim Mohammed , Bossoufi Badre , Motahhir Saad , Adouairi Mohamed said , Majout Btissam , Lamnadi Mouna , Masud Mehedi , Al-Amri Jehad F.
Published: December 2021

Due to the increase in electricity and diesel costs, solar photovoltaic pumping systems have become a good solution, especially in rural areas. This work presents a standalone photovoltaic (PV) water pumping system (PVWPS) driven by an induction motor without energy storage to improve the pumping system’s performance. First, a comparison is made between two types: perturb and observe (P&O) method and incremental conductance (INC) MPPT method with a variable step size that is automatically adjusted. Studying these two techniques helps to understand which one can result in a system with less oscillation and greater efficiency when tracking the maximum power point from the PV panel under sudden irradiation conditions. This MPPT works on the operating duty cycle of the boost converter. Then, that converter combines with a voltage source inverter (VSI) to convert DC power to AC power. Second, we use indirect field-oriented control (IRFOC), which drives the three-phase of an induction motor in turn to run the centrifugal pump. The simulation results of this work were obtained using the MATLAB Simulink platform.
Machine Learning Applied to Music/Audio Signal Processing
Authors: Lerch Alexander , Knees Peter
Published: December 2021

Over the past two decades, the utilization of machine learning in audio and music signal processing has dramatically increased [...]
Real-Time Automatic Investigation of Indian Roadway Animals by 3D Reconstruction Detection Using Deep Learning for R-3D-YOLOv3 Image Classification and Filtering
Authors: Sengan Sudhakar , Kotecha Ketan , Vairavasundaram Indragandhi , Velayutham Priya , Varadarajan Vijayakumar , Ravi Logesh , Vairavasundaram Subramaniyaswamy
Published: December 2021

Statistical reports say that, from 2011 to 2021, more than 11,915 stray animals, such as cats, dogs, goats, cows, etc., and wild animals were wounded in road accidents. Most of the accidents occurred due to negligence and doziness of drivers. These issues can be handled brilliantly using stray and wild animals-vehicle interaction and the pedestrians’ awareness. This paper briefs a detailed forum on GPU-based embedded systems and ODT real-time applications. ML trains machines to recognize images more accurately than humans. This provides a unique and real-time solution using deep-learning real 3D motion-based YOLOv3 (DL-R-3D-YOLOv3) ODT of images on mobility. Besides, it discovers methods for multiple views of flexible objects using 3D reconstruction, especially for stray and wild animals. Computer vision-based IoT devices are also besieged by this DL-R-3D-YOLOv3 model. It seeks solutions by forecasting image filters to find object properties and semantics for object recognition methods leading to closed-loop ODT.
Open-Source Tool for Transforming CityGML Levels of Detail
Authors: Malhotra Avichal , Raming Simon , Frisch Jérôme , van Treeck Christoph
Published: December 2021

Urban Building Energy Modelling (UBEM) requires adequate geometrical information to represent buildings in a 3D digital form. However, open data models usually lack essential information, such as building geometries, due to a lower granularity in available data. For heating demand simulations, this scarcity impacts the energy predictions and, thereby, questioning existing simulation workflows. In this paper, the authors present an open-source CityGML LoD Transformation (CityLDT) tool for upscaling or downscaling geometries of 3D spatial CityGML building models. With the current support of LoD0–2, this paper presents the adapted methodology and developed algorithms for transformations. Using the presented tool, the authors transform open CityGML datasets and conduct heating demand simulations in Modelica to validate the geometric processing of transformed building models.
Assessment of GHG Interactions in the Vicinity of the Municipal Waste Landfill Site—Case Study
Authors: Górka Maciej , Bezyk Yaroslav , Sówka Izabela
Published: December 2021

Landfills have been identified as one of the major sources of greenhouse gas (GHG) emissions and as a contributor to climate change. Landfill facilities exhibit considerable spatial and temporal variability of both methane (CH4) and carbon dioxide (CO2) rates. The present work aimed to evaluate the spatial distribution of CH4 and CO2 and their δ13C isotopic composition originating from a municipal landfill site, to identify its contribution to the local GHG budget and the potential impact on the air quality of the immediate surroundings in a short-term response to environmental conditions. The objective was met by performing direct measurements of atmospheric CO2 and CH4 at the selected monitoring points on the surface and applying a binary mixing model for the determination of carbon isotopic ratios in the vicinity of the municipal waste landfill site. Air samples were collected and analysed for isotopic composition using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. Kriging and Inverse distance weighting (IDW) methods were used to evaluate the values at unsampled locations and to map the excess of GHGs emitted from the landfill surface. The large off-site dispersion of methane from the landfill site at a 500 m distance was identified during field measurements using isotopic data. The mean δ13C of the landfill biogas emitted to the surrounded atmosphere was −53.9 ± 2.2‰, which corresponded well to the microbial degradation processes during acetate fermentation in the waste deposits. The calculated isotopic compositions of CO2 (δ13C = −18.64 ± 1.75‰) indicate the domination of biogenic carbon reduction by vegetation surrounding the landfill. Finally, amounts of methane escaping into the air can be limited by the appropriate landfill management practices (faster covers active quarter through separation layer), and CH4 reduction can be achieved by sealing the cover on the leachate tank.
Advancing the Industrial Sectors Participation in Demand Response within National Electricity Grids
Authors: Brem Alexander , O’Sullivan Dominic T. J. , Bruton Ken
Published: December 2021

Increasing the level and diversifying the sources of flexible capacity available to transmission system operators will be a pivotal factor for maintaining reliable control of national electricity grids. These response capacities are widely available; however, one area with large capacities that could benefit from advancements is the industrial sector. This sector’s highly regulated nature ensures that structured procedures and thorough investigations are required to implement significant change. This study presents a systematic methodology to effectively categorise assets and evaluate their perceived risk of participation in demand response, allowing industries to present a sustainable portfolio of flexible capacity to the grid. Following implementation on an internationally relevant industrial site, this methodology identified several assets for participation, determining that it is realistic to expect 35 to 75 kW of flexible capacity from only air handling units on a single site. A selected unit was further evaluated using an internal air-temperature modelling tool. This demonstrated its ability to respond safely to the actual 2019 and 2020 grid frequency events and even remain off, at no risk to the indoor thermal environment for at least 20 min in each case. The potential impact of advancing industrial participation is presented, with the highest scenario providing almost 15 MW of flexible capacity to the Irish national grid. The financial benefit achievable on a site from the most conservative assets was found to be between EUR 993 and EUR 2129 annually for a single response category and up to EUR 6563 based on payment multipliers. Overall, this research demonstrates the significant flexible capacities available within the industrial sector and illustrates the low-risk capabilities and considerable benefits achievable on a single site and for the wider national electricity grids with this concept.
Production of Ultra-High-Performance Concrete with Low Energy Consumption and Carbon Footprint Using Supplementary Cementitious Materials Instead of Silica Fume: A Review
Authors: Hamad Mays A. , Nasr Mohammed , Shubbar Ali , Al-Khafaji Zainab , Al Masoodi Zainab , Al-Hashimi Osamah , Kot Patryk , Alkhaddar Rafid , Hashim Khalid
Published: December 2021

The increase in cement production as a result of growing demand in the construction sector means an increase in energy consumption and CO2 emissions. These emissions are estimated at 7% of the global production of CO2. Ultra-high-performance concrete (UHPC) has excellent mechanical and durability characteristics. Nevertheless, it is costly and affects the environment due to its high amount of cement, which may reach 800–1000 kg/m3. In order to reduce the cement content, silica fume (SF) was utilized as a partial alternative to cement in the production of UHPC. Nevertheless, SF is very expensive. Therefore, the researchers investigated the use of supplementary cementitious materials cheaper than SF. Very limited review investigates addressed the impact of such materials on different properties of UHPC in comparison to that of SF. Thus, this study aims to summarize the effectiveness of using some common supplementary cementitious materials, including fly ashes (FA), ground granulated blast furnace slag (GGBS), metakaolin (MK) and rice husk ashes (RHA) in the manufacturing of UHPC, and comparing the performance of each material with that of SF. The comparison among these substances was also discussed. It has been found that RHA is considered a successful alternative to SF to produce UHPC with similar or even higher properties than SF. Moreover, FA, GGBS and MK can be utilized in combination with SF (as a partial substitute of SF) as a result of having less pozzolanic activity than SF.
Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform
Authors: Kania Konrad , Rymarczyk Tomasz , Mazurek Mariusz , Skrzypek-Ahmed Sylwia , Guzik Mirosław , Oleszczuk Piotr
Published: December 2021

This paper presents an open architecture for a sensor platform for the processing, collection, and image reconstruction from measurement data. This paper focuses on ultrasound tomography in block-wise-transform-reduction image reconstruction. The advantage of the presented solution, which is part of the project “Next-generation industrial tomography platform for process diagnostics and control”, is the ability to analyze spatial data and process it quickly. The developed solution includes industrial tomography, big data, smart sensors, computational intelligence algorithms, and cloud computing. Along with the measurement platform, we validate the methods that incorporate image compression into the reconstruction process, speeding up computation and simplifying the regularisation of solving the inverse tomography problem. The algorithm is based on discrete transformation. This method uses compression on each block of the image separately. According to the experiments, this solution is much more efficient than deterministic methods. A feature of this method is that it can be directly incorporated into the compression process of the reconstructed image. Thus, the proposed solution allows tomographic sensor-based process control, multidimensional industrial process control, and big data analysis.
Energy Resources Exploitation in the Russian Arctic: Challenges and Prospects for the Sustainable Development of the Ecosystem
Authors: Romasheva Natalia , Dmitrieva Diana
Published: December 2021

According to the forecasts made by IEA, BP, and Total in early 2021, the demand for hydrocarbons will continue for decades, and their share in the global energy balance will remain significant. Russia, as a key player in the energy market, is interested in maintaining and increasing hydrocarbon production, so further exploitation of the Arctic energy resources is an urgent issue. A large number of onshore oil and gas projects have been successfully implemented in the Arctic since the 1930s, while recently, special attention has been paid to the offshore energy resources and implementation of natural gas liquefaction projects. However, the implementation of oil and gas projects in the Arctic is characterized by a negative impact on the environment, which leads to a violation of the ecological balance in the Arctic, and affects the stability of its ecosystem, which is one of the most vulnerable ecosystems on the planet. The main goal of the present study is to understand how the implementation of oil and gas projects in the Arctic affects the ecosystem, to assess the significance of this process, and to find out what the state and business could do to minimize it. In the article, the authors analyze energy trends, provide brief information about important oil and gas projects being implemented in the Arctic region of Russia, and investigate the challenges of the oil and gas projects’ development and its negative impacts on the Arctic environment. The main contributions of this paper are the identification of all possible environmental risks and processes accompanying oil and gas production, and its qualitative analysis and recommendations for the state and business to reduce the negative impact of oil and gas projects on the Arctic ecosystem. The research methodology includes desk studies, risk management tools (such as risk analysis, registers, and maps), brainstorming, the expert method, systematization, comparative analysis, generalization, and grouping.
Proposal of a Novel Mooring System Using Three-Bifurcated Mooring Lines for Spar-Type Off-Shore Wind Turbines
Authors: Liu Shi , Yang Yi , Wang Chengyuan , Tu Yuangang , Liu Zhenqing
Published: December 2021

Floating wind turbine vibration controlling becomes more and more important with the increase in wind turbine size. Thus, a novel three-bifurcated mooring system is proposed for Spar-type floating wind turbines. Compared with the original mooring system using three mooring lines, three-bifurcated sub-mooring-lines are added into the novel mooring system. Specifically, each three-bifurcated sub-mooring-line is first connected to a Spar-type platform using three fairleads, then it is connected to the anchor using the main mooring line. Six fairleads are involved in the proposed mooring system, theoretically resulting in larger overturning and torsional stiffness. For further improvement, a clump mass is attached onto the main mooring lines of the proposed mooring system. The wind turbine surge, pitch, and yaw movements under regular and irregular waves are calculated to quantitatively examine the mooring system performances. A recommended configuration for the proposed mooring system is presented: the three-bifurcated sub-mooring-line and main mooring line lengths should be (0.0166, 0.0111, 0.0166) and 0.9723 times the total mooring line length in the traditional mooring system. The proposed mooring system can at most reduce the wind turbine surge movement 37.15% and 54.5% when under regular and irregular waves, respectively, and can at most reduce the yaw movement 30.1% and 40% when under regular and irregular waves, respectively.
Real-Time Fault Detection to Ensure the Safe Operation of the Single-Phase Five-Level VIENNA Rectifier
Authors: Linh Pham Thi Thuy , Bach Nguyen Ngoc , Phap Vu Minh , Van Binh Doan
Published: December 2021

This work aims to explore and evaluate the nonreversible AC/DC five-level structure from the point of view of its operational safety: high electrical security on internal destruction and continuity in operation. It only has low-voltage monotransistor cells (Si and SiC 600 V max) and is intrinsically tolerant to imperfection control and parasites, therefore naturally secure. The design and lab-test of fault monitoring and fault diagnosis with just one voltage sensor of a single-phase five-level VIENNA rectifier were proposed. This real-time diagnostic method allows for a safe stop or corrective control strategy based on the reconfiguration of the modulation. The reconstruction strategy allows for optimization of the current and voltage signals as well as power factor. A continuous post-fault operation can be achieved for critical applications. An experimental prototype 3 kW/230 VAC/800 VDC/32 kHz was created to validate the proposed fault diagnosis method and reconfiguration control method.
Empirical Studies on Biomass Briquette Production: A Literature Review
Authors: Marreiro Hívila M. P. , Peruchi Rogério S. , Lopes Riuzuani M. B. P. , Andersen Silvia L. F. , Eliziário Sayonara A. , Rotella Junior Paulo
Published: December 2021

The densification of raw material into fuel briquettes is one of the routes to convert biomass into energy. This method provides uniformity to the solid fuel, better physical and energy properties, facilitating its storage and transport, in addition to more homogeneous combustion. Given the importance of these characteristics, this work presents a literature review, emphasizing the experimental levels of the variables of the briquetting process, as well as on the most relevant quality parameters for obtaining briquettes. We also carry out a survey of the main technologies used in the production of briquettes, as well as the experimental methodologies and statistical analysis used in the planning and validation of processes. It was observed among the studies that the raw material granulometry, followed by pressure, initial moisture, compaction time and binder are the most used process variables for the production of briquettes. Other factors, such as the proportion of biomass, process temperature and thermal pre-treatments are used to obtain greater energetic and physical responses. Among the works, divergences were observed regarding the relevance and interaction of some process variables on the quality variables of the briquettes, indicating the need for the experiments to be mathematically modeled.
Cost–Benefit Analysis of Pumped Hydroelectricity Storage Investment in China
Authors: Sospiro Paolo , Nibbi Leonardo , Liscio Marco Ciro , De Lucia Maurizio
Published: December 2021

In this study, the energy scenario in China was analyzed by retracing the trend of exponential population growth, gross domestic product (GDP), and electricity production and consumption. A forecast up to 2050 was made based on the history and forecasts of other field studies. It was possible to deduce data on pollutants in terms of CO2 equivalent (CO2-eq) emitted over time if there were no changes in the way energy was produced. Moreover, different scenarios were hypothesized for the use of pumped hydroelectricity storage plants, namely 4.5%, 6%, 8%, 11%, and 14% (percentage of electricity compared to requirements in 2050), to balance variable renewable energy sources and avoid curtailment, thereby reducing the use of energy produced by coal-fired plants. For this implementation, direct and indirect costs and benefits were considered, with interesting results obtained from an economic standpoint and very positive results from environmental, social, and territorial perspectives.
Legal Regulation of Hydrogen in Germany and Ukraine as a Precondition for Energy Partnership and Energy Transition
Authors: Hritsyshyna Maryna , Hutarevych Nataliia
Published: December 2021

In August 2020, Germany and Ukraine launched an energy partnership that includes the development of a hydrogen economy. Ukraine has vast renewable energy resources for “green” hydrogen production and a gas transmission system for transportation instead of Russian natural gas. Based on estimates by Hydrogen Europe, Ukraine can install 8000 MW of total electrolyser capacity by 2030. For these reasons, Ukraine is among the EU’s priority partners concerning clean hydrogen, according to the EU Hydrogen strategy. Germany plans to reach climate neutrality by 2045, and “green” hydrogen plays an important role in achieving this target. However, according to the National Hydrogen Strategy of Germany, local production of “green” hydrogen will not cover all internal demand in Germany. For this reason, Germany considers importing hydrogen from Ukraine. To govern the production and import of “green” hydrogen, Germany and Ukraine shall introduce legal regulations, the initial analysis of which is covered in this study. Based on observation and comparison, this paper presents and compares approaches while exploring the current stage and further perspectives for legal regulation of hydrogen in Germany and Ukraine. This research identifies opportunities in hydrogen production to improve the flexibility of the Ukrainian power system. This is an important issue for Ukrainian energy security. In the meantime, hydrogen can be a driver for decarbonisation according to the initial plans of Germany, and it may also have positive impact on the operation of Germany’s energy system with a high share of renewables.
A Review about Microalgae Wastewater Treatment for Bioremediation and Biomass Production—A New Challenge for Europe
Authors: Geremia Eugenio , Ripa Maddalena , Catone Claudio Marcello , Ulgiati Sergio
Published: December 2021

Microalgae have received much attention in the last few years. Their use is being extended to different fields of application and technologies, such as food, animal feed, and production of valuable polymers. Additionally, there is interest in using microalgae for removal of nutrients from wastewater. Wastewater treatment with microalgae allows for a reduction in the main chemicals responsible for eutrophication (nitrogen and phosphate), the reduction of organic substrates (by decreasing parameters such as BOD and COD) and the removal of other substances such as heavy metals and pharmaceuticals. By selecting and reviewing 202 articles published in Scopus between 1992 and 2020, some aspects such as the feasibility of microalgae cultivation on wastewater and potential bioremediation have been investigated and evaluated. In this review, particular emphasis was placed on the different types of wastewaters on which the growth of microalgae is possible, the achievable bioremediation and the factors that make large-scale microalgae treatment feasible. The results indicated that the microalgae are able to grow on wastewater and carry out effective bioremediation. Furthermore, single-step treatment with mixotrophic microalgae could represent a valid alternative to conventional processes. The main bottlenecks are the large-scale feasibility and costs associated with biomass harvesting.
Tree Species Classification Based on Sentinel-2 Imagery and Random Forest Classifier in the Eastern Regions of the Qilian Mountains
Authors: Ma Minfei , Liu Jianhong , Liu Mingxing , Zeng Jingchao , Li Yuanhui
Published: December 2021

Obtaining accurate forest coverage of tree species is an important basis for the rational use and protection of existing forest resources. However, most current studies have mainly focused on broad tree classification, such as coniferous vs. broadleaf tree species, and a refined tree classification with tree species information is urgently needed. Although airborne LiDAR data or unmanned aerial vehicle (UAV) images can be used to acquire tree information even at the single tree level, this method will encounter great difficulties when applied to a large area. Therefore, this study takes the eastern regions of the Qilian Mountains as an example to explore the possibility of tree species classification with satellite-derived images. We used Sentinel-2 images to classify the study area’s major vegetation types, particularly four tree species, i.e., Sabina przewalskii (S.P.), Picea crassifolia (P.C.), Betula spp. (Betula), and Populus spp. (Populus). In addition to the spectral features, we also considered terrain and texture features in this classification. The results show that adding texture features can significantly increase the separation between tree species. The final classification result of all categories achieved an accuracy of 86.49% and a Kappa coefficient of 0.83. For trees, the classification accuracy was 90.31%, and their producer’s accuracy (PA) and user’s (UA) were all higher than 84.97%. We found that altitude, slope, and aspect all affected the spatial distribution of these four tree species in our study area. This study confirms the potential of Sentinel-2 images for the fine classification of tree species. Moreover, this can help monitor ecosystem biological diversity and provide references for inventory estimation.
Submerged Fermentation of Animal Fat By-Products by Oleaginous Filamentous Fungi for the Production of Unsaturated Single Cell Oil
Authors: Gaykawad Sushil S. , Ramanand Sreerekha S. , Blomqvist Johanna , Zimmermann Boris , Shapaval Volha , Kohler Achim , Oostindjer Marije , Boccadoro Catherine
Published: December 2021

Animal waste fats were explored as a fermentation substrate for the production of high-value unsaturated single cell oil (SCO) using oleaginous fungi, Mucor circinelloides and Mortierella alpina. Both strains showed good growth and lipid accumulation when using animal fat as a single carbon source. The biomass concentration of 16.7 ± 2.2 gDCW/L and lipid content of 54.1%wt (of dry cell weight) were obtained for Mucor circinelloides in shake flask experiments, surpassing the biomass yield achieved in batch and fed-batch fermentation. In contrast, Mortierella alpina gave the highest biomass concentration (8.3 ± 0.3 gDCW/L) and lipid content (55.8%wt) in fed-batch fermentation. Fat grown Mortierella alpina was able to produce arachidonic acid (ARA), and the highest ARA content of 23.8%wt (of total lipid weight) was in fed-batch fermentation. Gamma-linolenic acid (GLA) was produced by both fungal strains. At the end of fed-batch fermentation, the GLA yields obtained for Mucor circinelloides and Mortierella alpina were 4.51%wt and 2.77%wt (of total lipid weight), respectively. This study demonstrates the production of unsaturated SCO-rich fungal biomass from animal fat by fermentation.
A Method for WWTP Sludge Valorization through Hygienization by Electron Beam Treatment
Authors: Sudlitz Marcin , Chmielewski Andrzej G.
Published: December 2021

This work reports on municipal sludge hygienization using electron beams. Three types of sewage sludge from two municipal wastewater treatment plants were tested: preliminary sludge with 4% TS, postflotation sludge with 2.5% TS and thickened preliminary sludge with 10% TS. The analysis of reference samples demonstrated the presence of bacteria and helminths ova in all examined samples. For the study of hygienization, electron beams from two types of accelerators, linear (Elektronika 10/10) and single cavity (ILU-6), were applied. For each type of accelerator, different irradiation methods were used: irradiation in sealed polyethylene bags using conveyor and flow irradiation installation. Experiments showed that the doses necessary for the elimination of mentioned pathogens were 4 kGy for preliminary sludge, 4 kGy for postflotation sludge and 5.5 kGy for preliminary sludge. The differences between the amounts of initial pathogens in preliminary and thickened preliminary sludge were marginal. It is possible that the higher irradiation dose required to hygienize thickened sludge resulted from higher TS concentration.