bluuebunny/crossref_metadata_2025 huggingface dataset:
Tantalum Suboxide Films with Tunable Composition and Electrical Resistivity Deposited by Reactive Magnetron Sputtering
Authors: Baker Alexander A. , Engwall Alison M. , Bayu-Aji Leonardus Bimo , Bae John H. , Shin Swanee J. , Moody John D. , Kucheyev Sergei O.
Published: June 2022

Tantalum-based films with tailored composition, density, and electrical resistivity are of interest for next generation hohlraums for magnetized indirect-drive inertial confinement fusion. Here, we use reactive direct-current magnetron sputtering to deposit tantalum suboxide films with O content in the range of 46–71 at.%. In contrast to a common approach involving varying reactive gas contents, compositional control is achieved kinetically by changing the total chamber pressure and the deposition rate, while keeping the working gas mix of Ar-5%O2 constant. The resultant films are X-ray amorphous with electrical resistivity varying by over seven orders of magnitude. The dominant conduction mechanism changes from metallic to activated tunneling above ∼55 at.% of O, which is characterized by a sharp increase in resistivity and a decrease in the carrier density at low temperatures.
Obstructive Sleep Apnea (OSA) and COVID-19: Mortality Prediction of COVID-19-Infected Patients with OSA Using Machine Learning Approaches
Authors: Tasmi Sidratul Tanzila , Raihan Md. Mohsin Sarker , Shams Abdullah Bin
Published: June 2022

COVID-19, or coronavirus disease, has caused an ongoing global pandemic causing un-precedented damage in all scopes of life. An infected person with underlaying medical conditions is at greater risk than the rest of the population. Obstructive sleep apnea (OSA) is an illness associated with disturbances during sleep or an unconscious state with blockage of the airway passage. The comobordities of OSA with high blood pressure, diabetes, obesity, and age can place the life of an already infected COVID-19 patient into danger. In this paper, a prediction model for the mortality of a COVID-infected patient suffering from OSA is developed using machine learning algorithms. After an extensive methodical search, we designed an artificial neural network that can predict the mortality with an overall accuracy of 99% and a precision of 100% for forecasting the fatality chances of COVID-infected patients. We believe our model can accurately predict the mortality of the patients and can therefore assist medical health workers in predicting and making emergency clinical decisions, especially in a limited resource scenario, based on the medical history of the patients and their future potential risk of death. In this way, patients with a greater risk of mortality can receive timely treatment and benefit from proper ICU resources. Such artificial intelligent application can significantly reduce the overall mortality rate of vulnerable patients with existing medical disorders.
The Role of Stereotactic Frame-Based Biopsy for Brainstem Tumors in the Era of Molecular-Based Diagnosis and Treatment Decisions
Authors: Hirano Yudai , Shinya Yuki , Aono Toshiya , Hasegawa Hirotaka , Kawashima Mariko , Shin Masahiro , Takami Hirokazu , Takayanagi Shunsaku , Umekawa Motoyuki , Ikemura Masako , Ushiku Tetsuo , Taoka Kazuki , Tanaka Shota , Saito Nobuhito
Published: June 2022

Stereotactic frame-based brain tumor biopsy (SFB) is a potent diagnostic tool considering its minimal invasiveness, though its diagnostic power and safety for brainstem lesions remain to be discussed. Here, we aimed to examine the usefulness of SFB for brainstem tumors. Twenty-two patients with brainstem tumors underwent 23 SFBs at our institution during 2002–2021. We retrospectively analyzed patient characteristics, tumor pathology, surgical procedures, and outcomes, including surgery-related complications and the diagnostic value. Seven (32%) tumors were located from the midbrain to the pons, eleven (50%) in the pons only, and four (18%) from the pons to the medulla oblongata. The target lesions were in the middle cerebellar peduncles in sixteen procedures (70%), the cerebellum in four (17%), the inferior cerebellar peduncles in two (9%), and the superior cerebellar peduncles in one (4%). A definitive diagnosis was made in 21 patients (95%) at the first SFB. The diagnoses were glioma in seventeen (77%) cases, primary central nervous system lymphoma in four (18%), and a metastatic brain tumor in one (5%). The postoperative complications (cranial nerve palsy in three [13%] cases, ataxia in one [4%]) were all transient. SFB for brainstem tumors yields a high diagnostic rate with a low risk of morbidity.
Three-Dimension-Printed Custom-Made Prosthetic Reconstructions in Bone Tumors: A Single Center Experience
Authors: Vitiello Raffaele , Matrangolo Maria Rosaria , El Motassime Alessandro , Perna Andrea , Cianni Luigi , Maccauro Giulio , Ziranu Antonio
Published: June 2022

Bone can be affected by different neoplastic conditions. Limb salvage surgery has become the preferred treatment strategy for most malignant tumors of the extremities. Advanced 3D printing technology has transformed the conventional view of oncological surgery. These types of implants are produced by electron beam melting (EBM) technology by sintering titanium powder in a scaffold shape designed following a project designed from HRCT and MRI. The aim of our study was to evaluate the outcomes and the mid-term follow-up of a population treated with 3D-printed custom-made prosthesis implantation in major oncological bone resection or after failure of primary implants. The primary outcome was the general patient satisfaction one year after surgery. The secondary outcomes were: mortality rate, treatment related complication rate, functional and clinical outcomes (KPS, ADL and IADL). Eight patients were included, five females and two males, with a mean age of 50.3 (±23.72) years at the surgery. The enrolled patients reported a mean satisfaction rate after surgery of 7.38 (±2) where 10 was the maximum value. There were no changes between pre- and postoperative mean KPS (81.43 +/−10.69). Mean preoperative ADL and IADL score was in both cases 4.86 (±1.07), while postoperative was 5 (±0.82), with a delta of 0.13 (p > 0.05). Custom-made prosthesis permits reconstructing bone defects caused by large tumor resection, especially in anatomically complex areas, restoring articular function.
Autoantibodies Associated with Autoimmune Liver Diseases in a Healthy Population: Evaluation of a Commercial Immunoblot Test
Authors: Ahmad Awais , Dahle Charlotte , Rönnelid Johan , Sjöwall Christopher , Kechagias Stergios
Published: June 2022

Autoantibodies constitute important tools for diagnosing the autoimmune liver diseases (AILD) autoimmune hepatitis and primary biliary cholangitis. The EUROLINE immunoblot assay, detecting multiple specificities, is widely used, but the clinical importance of weakly positive findings is unclear. The manufacturer’s recommended cut-off was evaluated by investigating AILD-associated autoantibodies in 825 blood donors and 60 confirmed AILD cases. Positive findings were followed up with immunofluorescence microscopy on rat tissue, anti-M2-ELISA, alternative immunoblot assay, and liver function tests. Thirty-six (4.4%) blood donors were positive with EUROLINE. The most common specificities were LC-1 (1.6%), gp210 (1.3%), and AMA-M2 (1.1%). In general, the positive results were higher in patients than in blood donors, whereas anti-LC-1 was higher in blood donors. The liver function tests were slightly elevated in 2 of the 36 immunoblot positive blood donors. The majority of the positive EUROLINE findings could not be confirmed with the follow-up tests. The EUROLINE-Autoimmune Liver Diseases-(IgG) immunoblot detected autoantibodies in 4.4% of blood donors without signs of AILD. Our findings indicate that the recommended cut-off can be raised for most specificities without loss of diagnostic sensitivity. The prevalence of anti-LC-1 among blood donors indicates a problem with the antigen source.
The Role of Forensic Investigation in an Unusual Case of Patricide by a Schizophrenic Woman Involving Dismemberment of a Decomposed Body
Authors: Aquila Isabella , Sacco Matteo Antonio , Cordasco Fabrizio , Scalise Carmen , Galassi Francesco Maria , Varotto Elena , Caruso Walter , Aquila Valerio Riccardo , Ricci Pietrantonio
Published: June 2022

Dismemberment is characterized by the fragmentation of the body into anatomical sections. It can occur because of a murder, suicide, or accident. In the literature, there are no cases of patricide perpetrated by a daughter in which the offender performed the dismemberment. However, in this paper, we reported a case of patricide by a schizophrenic daughter that was not treated with antipsychotic therapy. Post-mortem Computed Tomography (PMCT), autopsy, and histological examinations were performed. The soft tissues were removed through maceration techniques and chemical treatment. An analysis was performed to study the bone margins and clarify the weapon and manner of death. This investigation, which used radiological and histological studies, helped to assess the vitality of the injuries. The purpose of the study is to discover the weapon used, the cause, and the manner of death, with particular interest in this case due to the dismemberment. Moreover, we emphasize the correlation between patricide, dismemberment, and a lack of antipsychotic treatment in patients with schizophrenia.
Modelling Foreign Exchange Interventions under Rayleigh Process: Applications to Swiss Franc Exchange Rate Dynamics
Authors: Hui Cho-Hoi , Lo Chi-Fai , Liu Chi-Hei
Published: June 2022

This paper models the foreign exchange intervention policy following the Rayleigh process derived from the standard flexible-price monetary framework. The exchange rate dynamics associated with the interventions are more sensitive to the change in the economic fundamental when a currency’s money supply is ample and its appreciation expectation cannot be offset by lower interest rates that have fallen to the zero lower bound, suggesting that more intensive interventions are required to counteract currency appreciation pressure and resulting in foreign reserve accumulation. The empirical results using market data during January 2015–February 2020 demonstrate that the model can describe the dynamics of the Swiss franc exchange rate. The accumulation of foreign reserves through interventions is negatively co-integrated with the exchange rate volatility and the value of the mean level of the Swiss franc exchange rate in the dynamics, to some extent indicating a reasonably high degree of effectiveness of the Swiss National Bank’s interventions. The transition between the target-zone and floating-rate regimes in 2015 caused changes in the level of exchange rate volatility but not its dynamical structure, suggesting that transitions between the floating-rate and target-zone regimes do not seem to have material consequence in this regard.
A Spatially Correlated Model with Generalized Autoregressive Conditionally Heteroskedastic Structure for Counts of Crimes
Authors: Escudero Isabel , Angulo José M. , Mateu Jorge
Published: June 2022

Crime is a negative phenomenon that affects the daily life of the population and its development. When modeling crime data, assumptions on either the spatial or the temporal relationship between observations are necessary if any statistical analysis is to be performed. In this paper, we structure space–time dependency for count data by considering a stochastic difference equation for the intensity of the space–time process rather than placing structure on a latent space–time process, as Cox processes would do. We introduce a class of spatially correlated self-exciting spatio-temporal models for count data that capture both dependence due to self-excitation, as well as dependence in an underlying spatial process. We follow the principles in Clark and Dixon (2021) but considering a generalized additive structure on spatio-temporal varying covariates. A Bayesian framework is proposed for inference of model parameters. We analyze three distinct crime datasets in the city of Riobamba (Ecuador). Our model fits the data well and provides better predictions than other alternatives.
Quantum Linear System Algorithm for General Matrices in System Identification
Authors: Li Kai , Zhang Ming , Liu Xiaowen , Liu Yong , Dai Hongyi , Zhang Yijun , Dong Chen
Published: June 2022

Solving linear systems of equations is one of the most common and basic problems in classical identification systems. Given a coefficient matrix A and a vector b, the ultimate task is to find the solution x such that Ax=b. Based on the technique of the singular value estimation, the paper proposes a modified quantum scheme to obtain the quantum state |x⟩ corresponding to the solution of the linear system of equations in O(κ2rpolylog(mn)/ϵ) time for a general m×n dimensional A, which is superior to existing quantum algorithms, where κ is the condition number, r is the rank of matrix A and ϵ is the precision parameter. Meanwhile, we also design a quantum circuit for the homogeneous linear equations and achieve an exponential improvement. The coefficient matrix A in our scheme is a sparsity-independent and non-square matrix, which can be applied in more general situations. Our research provides a universal quantum linear system solver and can enrich the research scope of quantum computation.
Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania
Authors: Mangewa Lazaro J. , Ndakidemi Patrick A. , Alward Richard D. , Kija Hamza K. , Bukombe John K. , Nasolwa Emmanuel R. , Munishi Linus K.
Published: June 2022

Habitat condition is a vital ecological attribute in wildlife conservation and management in protected areas, including the Burunge wildlife management areas in Tanzania. Traditional techniques, including satellite remote sensing and ground-based techniques used to assess habitat condition, have limitations in terms of costs and low resolution of satellite platforms. The Normalized Difference Vegetation Index (NDVI) and Green NDVI (GNDVI) have potential for assessing habitat condition, e.g., forage quantity and quality, vegetation cover and degradation, soil erosion and salinization, fire, and pollution of vegetation cover. We, therefore, examined how the recently emerged Unmanned Aerial Vehicle (UAV) platform and the traditional Sentinel-2 differs in indications of habitat condition using NDVI and GNDVI. We assigned 13 survey plots to random locations in the major land cover types: three survey plots in grasslands, shrublands, and woodlands, and two in riverine and mosaics cover types. We used a UAV-mounted, multi-spectral sensor and obtained Sentinel-2 imagery between February and March 2020. We categorized NDVI and GNDVI values into habitat condition classes (very good, good, poor, and very poor). We analyzed data using descriptive statistics and linear regression model in R-software. The results revealed higher sensitivity and ability of UAV to provide the necessary preliminary diagnostic indications of habitat condition. The UAV-based NDVI and GNDVI maps showed more details of all classes of habitat conditions than the Sentinel-2 maps. The linear regressions results showed strong positive correlations between the two platforms (p < 0.001). The differences were attributed primarily to spatial resolution and minor atmospheric effects. We recommend further studies to test other vegetation indices.
Primary English Language Education Policy in Vietnam’s Disadvantaged Areas: Implementation Barriers
Authors: Do Thi Thanh Tra , Sellars Maura , Le Thi Thuy
Published: June 2022

In the context of English as a global language, compulsory English language education at the primary level has become an inevitable trend in many non-English-speaking countries, including Vietnam. However, there have been concerns regarding how English language policy is realised across contextual settings, especially in rural and remote areas of Vietnam. Based on language-in-education goals, this article investigates English language policy implementation in Vietnam’s rural and remote areas from the perspective of primary English teachers from 2008 onwards. The present paper employs a desk review of existing literature, policy analysis, and semi-structured interviews. Data collected from multiple sources show the inequality of access to English language learning in the rural localities. The findings also indicate a significant gap between the current English language policy goals and implementation in the rural primary sector regarding slow execution, curriculum variations, limited teaching resources, inappropriate pedagogy, and assessment. These problems have been accelerated due to a shortage of teachers as well as inconsistency and limitations related to pre-service teacher training programs and recruitment. Identifying significant challenges of English language policy implementation in the Northwest of Vietnam helps shed light on primary English education in remote and marginalised regions. Therefore, the recommendations target policy makers, teacher educators, and stakeholders to assist primary English teachers in rural areas to improve and advance the success of primary English education in Vietnam’s remote areas and beyond the specific context to which it refers.
Migrant-Background Student Experiences of Facing and Overcoming Difficulties in Finnish Comprehensive Schools
Authors: Kaukko Mervi , Alisaari Jenni , Heikkola Leena Maria , Haswell Nick
Published: June 2022

This article considers what students with a migrant background in Finnish comprehensive schools report as difficult, and how they succeed in overcoming these difficulties. We draw on two sets of school wellbeing and learning surveys for migrant students, conducted in 2016 and 2021 in comprehensive schools (grades 1–9) in and around two major cities in Finland. We pay attention to student answers to three questions: What is difficult in school? How do you succeed in difficult tasks in school? and Who helps you in school? The datasets from the two points in time are compared to see whether changes in school demographic situation and the student length of stay in Finland had an impact on student experiences. Our findings show that theory-based school subjects that depend strongly on language, such as science subjects, maths, Finnish, Swedish and English, are considered difficult. Additionally, interaction with peers, which also relies on language, causes challenges. The students report turning to teachers, other professionals and peers for assistance and support, and also mention personal strategies they have developed to overcome school-related difficulties. Understanding what migrant students find difficult, as well as how, and with the help of whom, they overcome such difficulties is crucial for the development of effective and sensitive pedagogical practices.
A Cost-Optimized Data Parallel Task Scheduling with Deadline Constraints in Cloud
Authors: Rajalakshmi N. R. , Dumka Ankur , Kumar Manoj , Singh Rajesh , Gehlot Anita , Akram Shaik Vaseem , Anand Divya , Elkamchouchi Dalia H. , Noya Irene Delgado
Published: June 2022

Large-scale distributed systems have the advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data within a time constraint becomes tricky, due to the complexity of data parallel task scheduling in a time constrained environment. This paper proposes data parallel task scheduling in cloud to address the minimization of cost and time constraints. By running concurrent executions of tasks on multi-core cloud resources, the number of parallel executions could be increased correspondingly, thereby, finishing the task within the deadline is possible. A mathematical model is developed here to minimize the operational cost of data parallel tasks by feasibly assigning a load to each virtual machine in the cloud data center. This work experiments with a machine learning model that is replicated on the multi-core cloud heterogeneous resources to execute different input data concurrently to accomplish distributive learning. The outcome of concurrent execution of data-intensive tasks on different parts of the input dataset gives better solutions in terms of processing the task by the deadline at optimized cost.
Analytic Design of on-Chip Spiral Inductor with Variable Line Width
Authors: Chen Hao-Hui , Hsu Yao-Wen
Published: June 2022

On-chip spiral inductors with variable line width layouts are known for their high quality factor (Q-factor). In this paper, we present an analytical approach to facilitate the design of such inductors. Based on an analysis of ohmic and eddy-current losses, we first derive an analytical formula for the metal resistance calculation of a spiral inductor. By minimizing the metal resistance, a simple design equation for finding the proper line width of each coil is then presented. Several 0.18 μm CMOS spiral inductors are investigated, via electromagnetic simulations and experimental studies, to test the proposed resistance calculation, as well as the variable line width design method. It is found that the developed resistance calculation can effectively model the metal-line resistance of a spiral inductor. Moreover, the inductor with a variable line width obtained using the proposed method can significantly improve the Q-factor with little compromise to inductance, which validates the capacity of the developed variable line width design technique. Since the proposed approach can be carried out using analytical calculations, it may be a more efficient design method than those previously reported in the literature.
Interaction of Consumer Heterogeneity and Technological Progress in the US Electric Vehicle Market
Authors: Desai Ranjit R. , Hittinger Eric , Williams Eric
Published: June 2022

Electric Technology Vehicles (ETVs: hybrid, electric, and plug-in hybrid) may reach price parity with incumbent internal combustion vehicles (ICEVs) in the near future. Climate policy for transportation will depend on the degree to which consumers prefer ETVs, and price parity is a key factor. In this study, we explore the interaction between future cost reductions and the economically motivated adoption of ETVs. We construct a model of the U.S. personal vehicle market accounting for heterogenous use and vehicle preferences, in which adoption induces cost reductions that increase future market share. Model results indicate that price parity is reached for most consumers in a number of cost scenarios, but not with constant ICEV costs and modest ETV cost declines. A price parity future suggests that government support could be temporary and phased out after a successful market transition. However, if ETVs continue to be more expensive than ICEVs, then lasting government support is needed. Heterogeneity is essential to understanding the market transition: treating consumers as heterogeneous results in an ETV market share 23% higher than assuming average consumers. Future work can clarify ETV support policy by resolving uncertainty in cost trajectories and modeling dynamic and heterogenous consumer markets.
Back-Calculation Method for Estimation of Geomechanical Parameters in Numerical Modeling Based on In-Situ Measurements and Statistical Methods
Authors: Adach-Pawelus Karolina
Published: June 2022

An important element of numerical modeling for specific mining issues is the selection of model parameters. The incorrect determination of geomechanical parameters can result in significant calculation errors carried throughout the entire problem. This paper presents a method for determining effective geomechanical parameters for technological and residual pillars through the use of numerical modeling, specifically, back-calculation. This is based on the results of numerical simulations, measurement data (e.g., excavation convergence measurements), and statistical methods (a non-linear regression model with “dummy” variables). The result is that appropriate parameters of pillars are set out iteratively so that the displacements of selected points in the numerical model correspond (with some approximation) to the results of mine measurements. The procedure of determining pillar parameters is presented using a case study of one mining field in an underground copper mine, where the deposit is mined using the room and pillar system. Numerical calculations were performed using a Phase2 v. 8.0 program (Rocscience, Toronto, Canada), while statistical calculations used a Statistica computer program. The results of excavation convergence measurements performed in the analyzed mine have been applied. This paper shows that for the presented method, the resulting matching of theoretical values of convergence determined numerically for specified pillar parameters to in-situ results of convergence measurements, is very good (R2 = 0.9896). This work exemplifies a set of the parameters of pillars for an elastic model of rock mass, but this method can also be applied to other models.
Energy and Mineral Resources Exploitation in the Delignitization Era: The Case of Greek Peripheries
Authors: Zafeiriou Eleni , Spinthiropoulos Konstantinos , Tsanaktsidis Constantinos , Garefalakis Stavros , Panitsidis Konstantinos , Garefalakis Alexandros , Arabatzis Garyfallos
Published: June 2022

The efficient and sustainable exploitation of energy resources may secure a sustainable economic growth for different regions. However, the peripheries are subject to social, economic, and political constraints, with limited power over energy management. The present work examines regional convergence in exploitation efficiency as synopsized in the GDP generated by energy and minerals in an era of the country’s efforts to shut down the lignite-run power production. With the assistance of panel unit root tests, we confirm non convergence of the variables employed, an expected result given the fact that different energy sources are being used for energy production by each different periphery, generating different economic results. In the second stage the methodology employed is a Bayesian vector auto-regressive model (BVAR) with an informative prior on the steady state. The particular methodology outperforms the conventional VAR methodology due to limited degrees of freedom. The Impulse response analysis and the Variance Decomposition analysis confirmed interlinkages among the regions studied. This result implies that the growth generated by different energy and mineral resources are interconnected. Furthermore, the energy transition taking place in Megalopoli and West Macedonia, where the two greatest lignite industries were located until recently, affects the growth generated by energy and resource exploitation for all the other peripheries, according to our findings. The novelty of the present work stands on the concept to detect interlinkages of energy and resources-based growth for the peripheries in Greece with the assistance of the Bayesian Var. The results of the present work are significant, since our findings suggest to policy makers tools to promote economic growth generated by energy based on alternative energy sources, including the environmentally friendly ones, by taking into consideration the interlinkages established by the existing infrastructure and the conventional energy sources used.
Two Generations of Hydrogen Powertrain—An Analysis of the Operational Indicators in Real Driving Conditions (RDC)
Authors: Pielecha Ireneusz , Szałek Andrzej , Tchorek Grzegorz
Published: June 2022

Hydrogen fuel cells are systems that can be successfully used to partially replace internal combustion propulsion systems. For this reason, the article presents an operational analysis of energy flow along with an analysis of individual energy transmission systems. Two generations of the Toyota Mirai vehicle were used for the tests. The operational analyses were carried out on the same route (compliant with RDE test requirements), assessing the system’s operation in three driving sections (urban, rural and motorway). Both generations of the drive system with fuel cells are quite different, which affects the obtained individual systems operation results as well as the overall energy flow. Research was carried out on the energy flow in the fuel cells, FC converter, battery and electric motor using a dedicated data acquisition system. The analyses were carried out in relation to the energy of fuel cells, battery energy and recovered braking energy. It was found that in the urban drive section of the second-generation system (due to its much larger mass), a slightly higher energy consumption value was obtained (by about 2%). However, in the remaining phases of the test, consumption was lower (the maximum difference was 18% in the rural phase). Total energy consumption in the research test was 19.64 kWh/100 km for the first-generation system compared to 18.53 kWh/100 km for the second-generation system. Taking into account the increased mass of the second-generation vehicle resulted in significantly greater benefits in the second-generation drive (up to 37% in individual drive sections and about 28% in the entire drive test).
Convolutional Neural Network and Support Vector Machine for Prediction of Damage Intensity to Multi-Storey Prefabricated RC Buildings
Authors: Jędrzejczyk Adrian , Firek Karol , Rusek Janusz
Published: June 2022

This paper presents the results of a comparative analysis of Convolutional Neural Network (CNN) and Support Vector Machine (SVM) models created for the prediction of the extent and intensity of damage caused to multi-storey reinforced concrete (RC) buildings. The research was conducted on a group of residential buildings, which were subjected to mining impacts in the form of surface deformations and rock mass tremors during their technical life cycle. Damage to buildings poses a significant threat to the safety of the structure and the serviceability of the buildings. They are often the cause of breaks in thermal insulation, which leads to excessive consumption of thermal energy used for space heating, which in turn contributes to over-emissions of CO2 into the atmosphere. Therefore, this problem is important, not only from a technical dimension, but also includes social, economic, and environmental aspects, which allows it to be classified as an issue of sustainable development in the building industry. As a result of the conducted analysis, among the CNN models, the highest level of classification accuracy was the model obtained using the ADAM (derived from adaptive moment estimation) algorithm, which was also characterized by a very high level of generalization, obtaining 80.35% correctly classified patterns for the training set and 80.52% for the test set. However, its accuracy level was slightly lower than that of the SVM model (85.15% for the training set and 84.42% for the test set), in which Bayesian optimization was used to determine the parameters. The analysis confirmed the effectiveness of the adopted methodology for predicting the extent and intensity of damage. The developed tool can support the optimization of building maintenance management, resulting in reduced economic and environmental expenditures for renovations.
Analysis of the All-Year Operation of the Solar Chimney in Polish Climatic Conditions
Authors: Berdowska Sylwia
Published: June 2022

This work presents an analysis of the all-year operation of the solar chimney. The analyzed system consists of a rectangular solar collector located on the southern side of the solar chimney. The surface of the solar collector is 30 m2, while the chimney is 50 m in height. Hourly changes in solar radiation were taken into account in the calculations. The simulation was made for the climatic conditions in Katowice, Poland. This study takes into account the most important parameters of the power plant, such as air temperature, air velocity and power of the installation throughout the year of the power plant’s operation. The cumulative amount of electricity that is generated in each month of the year is shown. The analyzed solar power plant produces the largest amount of electricity in the second quarter of the year and the lowest in the fourth quarter, with the maximum amount of energy produced in May and the minimum in December.
Future of Hydrogen as an Alternative Fuel for Next-Generation Industrial Applications; Challenges and Expected Opportunities
Authors: Qazi Umair Yaqub
Published: June 2022

A general rise in environmental and anthropogenically induced greenhouse gas emissions has resulted from worldwide population growth and a growing appetite for clean energy, industrial outputs, and consumer utilization. Furthermore, well-established, advanced, and emerging countries are seeking fossil fuel and petroleum resources to support their aviation, electric utilities, industrial sectors, and consumer processing essentials. There is an increasing tendency to overcome these challenging concerns and achieve the Paris Agreement’s priorities as emerging technological advances in clean energy technologies progress. Hydrogen is expected to be implemented in various production applications as a fundamental fuel in future energy carrier materials development and manufacturing processes. This paper summarizes recent developments and hydrogen technologies in fuel refining, hydrocarbon processing, materials manufacturing, pharmaceuticals, aircraft construction, electronics, and other hydrogen applications. It also highlights the existing industrialization scenario and describes prospective innovations, including theoretical scientific advancements, green raw materials production, potential exploration, and renewable resource integration. Moreover, this article further discusses some socioeconomic implications of hydrogen as a green resource.
Optimal Sizing of Grid-Scaled Battery with Consideration of Battery Installation and System Power-Generation Costs
Authors: Klansupar Chalermjit , Chaitusaney Surachai
Published: June 2022

Variable renewable energy (VRE) generation changes the shape of residual demand curves, contributing to the high operating costs of conventional generators. Moreover, the variable characteristics of VRE cause a mismatch between electricity demand and power generation, resulting in a greater expected energy not supplied (EENS) value. EENS involves an expected outage cost, which is one of the important components of power-generation costs. A utility-scale battery energy storage system (BESS) is popularly used to provide ancillary services to mitigate the VRE impact. The general BESS ancillary-service applications are as a spinning reserve, for regulation, and for ramping. A method to determine optimal sizing and the optimal daily-operation schedule of a grid-scale BESS (to compensate for the negative impacts of VRE in terms of operating costs, power-generation-reliability constraints, avoided expected-outage costs, and the installation cost of the BESS) is proposed in this paper. Moreover, the optimal BESS application at a specific time during the day can be selected. The method is based on a multiple-BESS-applications unit-commitment problem (MB-UC), which is solved by mixed-integer programming (MIP). The results show a different period for a BESS to operate at its best value in each application, and more benefits are found when operating the BESS in multiple applications.
Circular Economy in the European Construction Sector: A Review of Strategies for Implementation in Building Renovation
Authors: Sáez-de-Guinoa Aitana , Zambrana-Vasquez David , Fernández Víctor , Bartolomé Carmen
Published: June 2022

Building renovation was declared a key point for sustainable development, however, the renovation rate of residential buildings in the European Union is insufficient to meet the climate and energy targets set. This paper analyses the main circular economy models used in the construction sector, as well as the situation of the building renovation market, to set a framework for circular economy models in building renovation. Of all the existing strategies in this sector, design, material recovery, building renovation and end-of-life actions would be the best, respectively. It also includes a market analysis consisting of a literature review covering PEST perspectives (political, economic, social and technical) and a SWOT analysis (strengths, weaknesses, opportunities and threats), concluding with a market gap analysis. The results of these analyses allow the development of a series of suggestions and strategies to be followed in order to solve the main barriers that hinder the implementation of the circular economy in the building´s renovation sector.
An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices
Authors: Powroźnik Piotr , Szcześniak Paweł , Turchan Krzysztof , Krysik Miłosz , Koropiecki Igor , Piotrowski Krzysztof
Published: June 2022

In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs. In experimental studies, simplified results for three SA types and 100 devices for each type were presented. The obtained results confirm that, thanks to the use of SAs and the appropriate algorithm for their control, it is possible to change the load profile of the power grid. The efficacious operation of SAs will be possible thanks to the change of habits of electricity users, which is briefly described in the article.
Piece-Wise Linear (PWL) Probabilistic Analysis of Power Grid with High Penetration PV Integration
Authors: Gruosso Giambattista , Daniel Luca , Maffezzoni Paolo
Published: June 2022

This paper aims at presenting a novel effective approach to probabilistic analysis of distribution power grid with high penetration of PV sources. The novel method adopts a Gaussian Mixture Model for reproducing the uncertainty of correlated PV sources along with a piece-wise-linear approximation of the voltage-power relationship established by load flow problem. The method allows the handling of scenarios with a large number of uncertain PV sources in an efficient yet accurate way. A distinctive feature of the proposed probabilistic analysis is that of directly providing, in closed-form, the joint probability distribution of the set of observable variables of interest. From such a comprehensive statistical representation, remarkable information about grid uncertainty can be deduced. This includes the probability of violating the safe operation conditions as a function of PV penetration.
Method for Planning, Optimizing, and Regulating EV Charging Infrastructure
Authors: Chowdhury Amor , Klampfer Saša , Sredenšek Klemen , Seme Sebastijan , Hadžiselimović Miralem , Štumberger Bojan
Published: June 2022

The paper presents and solves the problems of modeling and designing the required EV charging service capacity for systems with a slow dynamic component. This includes possible bursts within a peak hour interval. A simulation tool with a newly implemented capacity planning method has been developed and implemented for these needs. The method can be used for different system simulations and simultaneously for systems with high, medium, and low service dynamics. The proposed method is based on a normal distribution, a primary mechanism that describes events within a daily interval (24 h) or a peak hour interval (rush hour). The goal of the presented approach, including the proposed method, is to increase the level and quality of the EV charging service system. The near-optimal solution with the presented method can be found manually by changing the service capacity parameter concerning the criterion function. Manual settings limit the number of rejected events, the time spent in the queue, and other service system performance parameters. In addition to manual search for near-optimal solutions, the method also provides automatic search by using the automation procedure of simulation runs and increasing/decreasing the service capacity parameter by a specifically calculated amount.
Design and Research on Electro-Hydraulic Drive and Energy Recovery System of the Electric Excavator Boom
Authors: Li Lin , Zhang Tiezhu , Wu Kaiwei , Lu Liqun , Lin Lianhua , Xu Haigang
Published: June 2022

The hydraulic accumulator has the advantages of high power density, fast response, stable operation and high cost performance. However, compared with the electric energy storage method, the hydraulic accumulator has low energy density and large pressure fluctuation while absorbing and discharging energy, which severely limits its application in hydraulic excavators. To improve the potential energy loss of the boom during the lowering process, an electro-hydraulic drive and energy recovery system for excavator booms (EHDR-EEB) based on a battery and accumulator is proposed. As a result, a simulation model of the electro-hydraulic drive and energy management strategy of a 1.6 t pure electric hydraulic excavator is built to investigate the energy regeneration and utilization. The simulation outcomes show that the potential energy recovery rate is as high as 92%. This research on EHDR-EEB makes a significant contribution to the economic improvement of electric hydraulic excavators.
An Accurate Evaluation of Switching Impulse Voltages for High-Voltage Tests
Authors: Yutthagowith Peerawut
Published: June 2022

For assessment of the insulation performance of high-voltage (HV) equipment installed in extra-high-voltage (EHV) systems, switching impulse voltage tests are performed in an HV testing laboratory. The waveform parameters of the switching impulse voltages are defined by peak voltage (Up), time to crest (Tp), and time to half (T2) according to IEC 60060-1. In this paper, a new, simplified, and accurate approach used for determination of the waveform parameters of the switching impulse voltages is presented. The formula used in the evaluation of Tp was derived from analytically simulated two-exponential waveforms, where Tp and T2 are in the ranges of 20 μs to 300 μs and 1000 μs to 4000 μs, respectively. The accuracy of the proposed approach was validated by the waveforms collected from the test waveform data generator (TDG) provided by IEC 61083-2, simulations, and experiments. It is found that the accuracy of the proposed approach is relatively higher than the expressions provided by IEC 60060-1 and previously developed. The proposed method is an alternative and useful approach for evaluating the waveform parameters of the standard switching impulse voltage.
Effect of Six Lactic Acid Bacteria Strains on Physicochemical Characteristics, Antioxidant Activities and Sensory Properties of Fermented Orange Juices
Authors: Quan Qi , Liu Wei , Guo Jiajing , Ye Meiling , Zhang Juhua
Published: June 2022

Six lactic acid bacteria strains were used to study the effects on physicochemical characteristics, antioxidant activities and sensory properties of fermented orange juices. All strains exhibited good growth in orange juice. Of these fermentations, some bioactive compositions (e.g., vitamin C, shikimic acid) and aroma-active compounds (e.g., linalool, 3-carene, ethyl 3-hydroxyhexanoate, etc.) significantly increased in Lactiplantibacillus plantarum and Lactobacillus acidophilus samples. DPPH free radical scavenging rates in L. plantarum and Lacticaseibacillus paracasei samples increased to 80.25% and 77.83%, respectively. Forty-three volatile profiles were identified, including 28 aroma-active compounds. 7 key factors significantly influencing sensory flavors of the juices were revealed, including D-limonene, linalool, ethyl butyrate, ethanol, β-caryophyllene, organic acids and SSC/TA ratio. The orange juice fermented by L. paracasei, with more optimization aroma-active compounds such as D-limonene, β-caryophyllene, terpinolene and β-myrcene, exhibited more desirable aroma flavors such as orange-like, green, woody and lilac incense, and gained the highest sensory score. Generally, L. paracasei fermentation presented better aroma flavors and overall acceptability, meanwhile enhancing antioxidant activities.
Genes and Diseases: Insights from Transcriptomics Studies
Authors: Kolobkov Dmitry S. , Sviridova Darya A. , Abilev Serikbai K. , Kuzovlev Artem N. , Salnikova Lyubov E.
Published: June 2022

Results of expression studies can be useful to clarify the genotype-phenotype relationship. However, according to data from recent literature, there is a large group of genes that are revealed as differentially expressed (DE) in many studies, regardless of the biological context. Additional analyses could shed more light on the relationships between genes, their differential expression, and diseases. We generated a set of 9972 disease genes from five gene-phenotype databases (OMIM, ORPHANET, DDG2P, DisGeNet and MalaCards) and a report of the International Union of Immunological Societies. To study transcriptomics of disease and non-disease genes in healthy tissues, we obtained data from the Human Protein Atlas (HPA) website. We analyzed the dependency between expression in healthy tissues and gene occurrence in Gene Expression Omnibus series using tools within the Enrichr libraries. The results of expression studies were annotated with Gene Ontology (GO) and Human Phenotype Ontology (HPO) terms. Using transcriptomics analysis of healthy tissues, we validated the previous findings of higher expression levels of disease genes in pathologically linked tissues compared to other tissues. Preferentially DE genes were generally highly expressed in one or multiple tissues and were enriched for disease genes. According to the results of GO enrichment analyses, both down- and up-regulated DE genes most often took part in immune response, translation and tissue-specific processes. A connection between DE-related pathology and the diversity of HPO terms was found. Investigating a link between expression and phenotype contributes to understanding the mode of development and progression of human diseases.