bluuebunny/crossref_metadata_2025 huggingface dataset:
Latticed Gold Nanoparticle Conjugation via Monomeric Streptavidin in Lateral Flow Assay for Detection of Autoantibody to Interferon-Gamma
Authors: Thongkum Weeraya , Yasamut Umpa , Chupradit Koollawat , Sakkhachornphop Supachai , Wipasa Jiraprapa , Sornsuwan Kanokporn , Juntit On-anong , Pornprasit Rawiwan , Thongkamwitoon Wanwisa , Chaichanan Jirapan , Khaoplab Jaruwan , Chanpradab Chonnikarn , Kasinrerk Watchara , Tayapiwatana Chatchai
Published: May 2021

Adult-onset immunodeficiency syndrome (AOID) patients with autoantibodies (autoAbs) against interferon-gamma (IFN-γ) generally suffer from recurrent and recalcitrant disseminated non-tuberculous mycobacterial diseases. Since the early stages of AOID do not present specific symptoms, diagnosis and treatment of the condition are not practical. A simplified diagnostic method for differentiating AOID from other immunodeficiencies, such as HIV infection, was created. Anti-IFN-γ is generally identified using enzyme-linked immunosorbent assay (ELISA), which involves an instrument and a cumbersome process. Recombinant IFN-γ indirectly conjugated to colloidal gold was used in the modified immunochromatographic (IC) strips. The biotinylated-IFN-γ was incorporated with colloidal-gold-labeled 6HIS-maltose binding protein-monomeric streptavidin (6HISMBP-mSA) and absorbed at the conjugate pad. The efficacy of the IC strip upon applying an anti-IFN-γ autoAb cut-off ELISA titer of 2500, the sensitivity and specificity were 84% and 90.24%, respectively. When a cut-off ELISA titer of 500 was applied, the sensitivity and specificity were 73.52% and 100%, respectively.
The Vital Role of Thanatochemistry in the Postmortem Diagnostic of Diabetic Ketoacidosis—Case Report
Authors: Girlescu Nona , Stoica Bogdan , Hunea Iuliana , Diac Madalina , Damian Simona Irina , David Sofia , Iov Tatiana , Tabian Daniel , Bulgaru Iliescu Diana
Published: May 2021

Diabetic ketoacidosis (DKA) is a lethal acute hyperglycemic complication of diabetes mellitus (DM) and it represents the initial manifestation of DM in about 15–20% of cases in adults and about 30–40% of cases in children. Postmortem diagnosis of DKA can only be made by applying thanatochemistry. Biochemistry applied postmortem is viewed with skepticism by many practitioners in the forensic field, completely lacking in many forensic services around the world, and especially in the national ones. This article aims to underline the importance of the postmortem application of biochemistry by reviewing the case of a person in the third decade of life who died suddenly at home due to diabetic ketoacidosis (DKA), whose autopsy was performed at an early PMI of approximately 24 h. Routine postmortem examinations (macroscopic, anatomopathological, and toxicological) could not establish a clear cause of death. When attention was turned to biochemical determinations (i.e., determination of glycated hemoglobin, glucose and ketone bodies (acetone, beta-hydroxybutyrate) in the blood, vitreous humor, and cerebrospinal fluid), the identified values clarified the thanatogenic mechanisms by establishing the diagnosis of DKA.
Cardiac Manifestations in a Group of Romanian Patients with Gaucher Disease Type 1 (a Monocentric Study)
Authors: Lazea Cecilia , Bucerzan Simona , Al-Khzouz Camelia , Zimmermann Anca , Vesa Ștefan Cristian , Nașcu Ioana , Creț Victoria , Crișan Mirela , Asăvoaie Carmen , Miclea Diana , Grigorescu-Sido Paula
Published: May 2021

Gaucher disease (GD), one of the most common lysosomal disorders, is characterised by clinical heterogeneity. Cardiac involvement is rare and refers to pulmonary hypertension (PH), valvular abnormalities and myocardial infiltrative damage. The aim of this study was to evaluate cardiac involvement in a group of Romanian GD patients. Phenotypic and genotypic characterisation was carried out in 69 patients with GD type 1. Annual echocardiography and electrocardiography were performed to assess pulmonary pressure, morphology and function of the valves and electrocardiographic changes. Nine patients (13%) exhibited baseline echocardiographic signs suggesting PH. Mitral regurgitation was present in 33 patients (48%) and aortic regurgitation in 11 patients (16%). One patient presented aortic stenosis. Significant valvular dysfunction was diagnosed in 10% of patients. PH was associated with greater age (p < 0.001), longer time since splenectomy (p = 0.045) and longer time between clinical onset and the start of enzyme replacing therapy (p < 0.001). Electrocardiographic changes were present in five patients (7%).
Results of a Prospective Trial to Compare 68Ga-DOTA-TATE with SiPM-Based PET/CT vs. Conventional PET/CT in Patients with Neuroendocrine Tumors
Authors: Baratto Lucia , Toriihara Akira , Hatami Negin , Aparici Carina M. , Davidzon Guido , Levin Craig S. , Iagaru Andrei
Published: May 2021

We prospectively enrolled patients with neuroendocrine tumors (NETs). They underwent a single 68Ga-DOTA-TATE injection followed by dual imaging and were randomly scanned using first either the conventional or the silicon photomultiplier (SiPM) positron emission tomography/computed tomography (PET/CT), followed by imaging using the other system. A total of 94 patients, 44 men and 50 women, between 35 and 91 years old (mean ± SD: 63 ± 11.2), were enrolled. Fifty-two out of ninety-four participants underwent SiPM PET/CT first and a total of 162 lesions were detected using both scanners. Forty-two out of ninety-four participants underwent conventional PET/CT first and a total of 108 lesions were detected using both scanners. Regardless of whether SiPM-based PET/CT was used first or second, maximum standardized uptake value (SUVmax) of lesions measured on SiPM was on average 20% higher when comparing two scanners with all enrolled patients, and the difference was statistically significant. SiPM-based PET/CT detected 19 more lesions in 13 patients compared with conventional PET/CT. No lesions were only identified by conventional PET/CT. In conclusion, we observed higher SUVmax for lesions measured from SiPM PET/CT compared with conventional PET/CT regardless of the order of the scans. SiPM PET/CT allowed for identification of more lesions than conventional PET/CT. While delayed imaging can lead to higher SUVmax in cancer lesions, in the series of lesions identified when SiPM PET/CT was used first, this was not the case; therefore, the data suggest superior performance of the SiPM PET/CT scanner in visualizing and quantifying lesions.
Evaluation of a Pseudovirus Neutralization Assay for SARS-CoV-2 and Correlation with Live Virus-Based Micro Neutralization Assay
Authors: Tolah Ahmed Majdi K. , Sohrab Sayed S. , Tolah Khaled Majdi K. , Hassan Ahmed M. , El-Kafrawy Sherif A. , Azhar Esam I.
Published: May 2021

The unusual cases of pneumonia outbreak were reported from Wuhan city in late December 2019. Serological testing provides a powerful tool for the identification of prior infection and for epidemiological studies. Pseudotype virus neutralization assays are widely used for many viruses and applications in the fields of serology. The accuracy of pseudotype neutralizing assay allows for its use in low biosafety lab and provides a safe and effective alternative to the use of wild-type viruses. In this study, we evaluated the performance of this assay compared to the standard microneutralization assay as a reference. The lentiviral pseudotype particles were generated harboring the Spike gene of SARS-CoV-2. The generated pseudotype particles assay was used to evaluate the activity of neutralizing antibodies in 300 human serum samples from a COVID-19 sero-epidemiological study. Testing of these samples resulted in 55 positive samples and 245 negative samples by pseudotype viral particles assay while microneutralization assay resulted in 64 positive and 236 negative by MN assay. Compared to the MN, the pseudotyped viral particles assay showed a sensitivity of 85.94% and a specificity of 100%. Based on the data generated from this study, the pseudotype-based neutralization assay showed a reliable performance for the detection of neutralizing antibodies against SARS-CoV-2 and can be used safely and efficiently as a diagnostic tool in a biosafety level 2 laboratory.
Clinical Application of a New SARS-CoV-2 Antigen Detection Kit (Colloidal Gold) in the Detection of COVID-19
Authors: Terpos Evangelos , Ntanasis-Stathopoulos Ioannis , Skvarč Miha
Published: May 2021

The precise diagnosis of COVID-19 is of outmost importance in order to effectively treat patients and prevent SARS-CoV-2 transmission. Herein, we evaluated the sensitivity and specificity of the COVID-19 Antigen Detection Kit (Colloidal Gold—CG) compared with PCR in nasopharyngeal and nasal samples. A total of 114 positive and 244 negative nasopharyngeal specimens confirmed by PCR were used in this comparative study. When the PCR positive Cycle Threshold (Ct) value was ≤25, CG sensitivity was 100%. When the PCR positive Ct value was ≤33, CG sensitivity was 99%. When the PCR positive Ct value was ≤40, CG sensitivity was 89.47%. Regarding nasal swabs, a total of 109 positive and 250 negative specimens confirmed by PCR were used. When the PCR positive Ct value was ≤25, CG sensitivity was 100%. When the PCR positive Ct value was ≤33, CG sensitivity was 96.12%. When the PCR positive Ct value was ≤37, CG sensitivity was 91.74%. Specificity was above 99% regardless of the Ct value of PCR positivity for both nasopharyngeal and nasal specimens. Overall, the CG showed high sensitivity and specificity when the PCR Ct value was less than 33. Therefore, CG can be used for screening early in the disease course. Confirmatory PCR is essential when a false negative result is suspected.
Robust Aggregation Operators for Intuitionistic Fuzzy Hypersoft Set with Their Application to Solve MCDM Problem
Authors: Zulqarnain Rana Muhammad , Siddique Imran , Ali Rifaqat , Pamucar Dragan , Marinkovic Dragan , Bozanic Darko
Published: May 2021

In this paper, we investigate the multi-criteria decision-making complications under intuitionistic fuzzy hypersoft set (IFHSS) information. The IFHSS is a proper extension of the intuitionistic fuzzy soft set (IFSS) which discusses the parametrization of multi-sub attributes of considered parameters, and accommodates more hesitation comparative to IFSS utilizing the multi sub-attributes of the considered parameters. The main objective of this research is to introduce operational laws for intuitionistic fuzzy hypersoft numbers (IFHSNs). Additionally, based on developed operational laws two aggregation operators (AOs), i.e., intuitionistic fuzzy hypersoft weighted average (IFHSWA) and intuitionistic fuzzy hypersoft weighted geometric (IFHSWG), operators have been presented with their fundamental properties. Furthermore, a decision-making approach has been established utilizing our developed aggregation operators (AOs). Through the established approach, a technique for solving decision-making (DM) complications is proposed to select sustainable suppliers in sustainable supply chain management (SSCM). Moreover, a numerical description is presented to ensure the validity and usability of the proposed technique in the DM process. The practicality, effectivity, and flexibility of the current approach are demonstrated through comparative analysis with the assistance of some prevailing studies.
Measuring Causal Invariance Formally
Authors: Bourrat Pierrick
Published: May 2021

Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables.
R&D Investment, Financial and Environmental Performance Nexuses via Bootstrap Fourier Quantiles Granger Causality Test
Authors: Lin Feng-Li
Published: May 2021

This study investigated the relationship between R&D investments and financial and environmental performance. The direction, size, and significance of various phases of these variables were generated using the bootstrap Fourier quantiles Granger causality test. In our results, a positive relationship between R&D investment and CO2 emission reductions was found at two tails of quantiles. Additionally, we observed a significantly positive relationship between financial performance and CO2 emission reductions at the 0.5 quantile and above. The correlation between R&D investment and financial performance was identified to be positive under the 0.3, 0.4, 0.5 and 0.9 quantiles and negative under the 0.5 and 0.6 quantiles. The changing linkages among R&D investment, environmental performance and financial performance found in this study provide important information for policy makers, aiding in the development of R&D strategies to upgrade financial and environmental performance simultaneously.
Can Economic Factors Improve Momentum Trading Strategies? The Case of Managed Futures during the COVID-19 Pandemic
Authors: Guobužaitė Renata , Teresienė Deimantė
Published: May 2021

Systematic momentum trading is a prevalent risk premium strategy in different portfolios. This paper focuses on the performance of the managed futures strategy based on the momentum signal across different economic regimes, focusing on the COVID-19 pandemic period. COVID-19 had a solid but short-lived impact on financial markets, and therefore gives a unique insight into momentum strategies’ performance during such critical moments of market stress. We offer a new approach to implementing momentum strategies by adding macroeconomic variables to the model. We test a managed futures strategy’s performance with a well-diversified futures portfolio across different asset classes. The research concludes that constructing a portfolio based on academically/economically sound momentum signals with its allocation timing based on broader economic factors significantly improves managed futures strategies and adds significant diversification benefits to the investors’ portfolios.
Person–Environment Fit and Retention of Racially Minoritized College Students: Recommendations for Faculty, Support Staff, and Administrators
Authors: Ajayi Alex A. , Mitchell Lauren L. , Nelson Sarah C. , Fish Jillian , Peissig Lovey H. M. , Causadias José M. , Syed Moin
Published: May 2021

Although colleges in the United States have become increasingly racially and ethnically diverse, degree attainment remains disproportionately low among students from underrepresented and minoritized racial backgrounds. In this paper, we discuss the interactive influence of both person and environment factors in shaping academic persistence and argue that college administrators, faculty, and student support staff can intervene and take specific steps to improve the academic experience of racially minoritized college students. To this end, we offer specific evidence-based recommendations for campus leaders and stakeholders on how to adapt their campus community to facilitate the requisite person–environment fit to maximize academic persistence.
Science Teachers’ Perceptions and Self-Efficacy Beliefs Related to Integrated Science Education
Authors: Haatainen Outi , Turkka Jaakko , Aksela Maija
Published: May 2021

To understand how integrated science education (ISE) can be transferred into successful classroom practices, it is important to understand teachers’ perceptions and self-efficacy. The focus of this study is twofold: (1) to understand how teachers perceive ISE and (2) to assess if science teachers’ perceptions of and experiences with integrated education correlate with their views on self-efficacy in relation to ISE. Ninety-five Finnish science teachers participated in an online survey study. A mixed method approach via exploratory factor analysis and data-driven content analysis was used. Self-efficacy emerged as a key factor explaining teachers’ perceptions of and their lack of confidence in implementing ISE as well as their need for support. In addition, teachers regarded ISE as a relevant teaching method, but challenging to implement, and teachers primarily applied integrated approaches irregularly and seldom. Furthermore, teachers’ experiences with integrated activities and collaboration correlated with their views on integrated education and self-efficacy. These findings indicate teachers need support to better understand and implement ISE.
Design of a High-Power Multilevel Sinusoidal Signal and High-Frequency Excitation Module Based on FPGA for HIFU Systems
Authors: Bui Ngoc Thang , Nguyen Thi My Tien , Ataklti Gebremedhin Yonatan , Bui Quoc Cuong , Dinh Tran Thanh Nam , Phan Duc Tri , Park Sumin , Choi Jaeyeop , Vu Thi Thu Ha , Oh Junghwan
Published: May 2021

High-intensity focused ultrasound (HIFU) is a noninvasive therapy that uses focused ultrasound to treat a part of the tissue; high temperatures can damage tissues by heat. HIFU has many applications in the field of surgery and aesthetics and is used increasingly in everyday life. In this article, we discuss the mainboard design that controls the HIFU system with the ability to create a multistep sine wave compatible with many different applications. The signal used to trigger the transducer is a sinusoidal signal with a frequency adjustable from 0.1 to 3 MHz. In addition, the power supplied to the HIFU transducer is also controlled easily by the configuration parameters installed in the control circuit board. The proposed control and design method generates a voltage signal that doubles the supply voltage, thereby reducing the current on the MOSFET. The hardware design is optimized for a surface-mounted device-type MOSFET without the need for an external heat sink. In tests, we conducted a harmonious combination of two output signals to activate the same HIFU probe. The results showed that the energy transferred to the HIFU transducer increased by 1.5 times compared to a single channel. This means that the HIFU treatment time is reduced when using this method, with absolutely no changes in the system structure.
CogniViTra, a Digital Solution to Support Dual-Task Rehabilitation Training
Authors: Quintas João , Pais Joana , Martins Ana Isabel , Santos Hugo , Neves Lúcia , Sousa Sérgio , Benhsain David , Dierick Frédéric , Callén Antonio , Cunha António , Rocha Nelson Pacheco , Cruz Vítor Tedim
Published: May 2021

This article focuses on an eHealth application, CogniViTra, to support cognitive and physical training (i.e., dual-task training), which can be done at home with supervision of a health care provider. CogniViTra was designed and implemented to take advantage of an existing Platform of Services supporting a Cognitive Health Ecosystem and comprises several components, including the CogniViTra Box (i.e., the patient terminal equipment), the Virtual Coach to provide assistance, the Game Presentation for the rehabilitation exercises, and the Pose and Gesture Recognition to quantify responses during dual-task training. In terms of validation, a functional prototype was exposed in a highly specialized event related to healthy and active ageing, and key stakeholders were invited to test it and share their insights. Fifty-seven specialists in information-technology-based applications to support healthy and active ageing were involved and the results and indicated that the functional prototype presents good performance in recognizing poses and gestures such as moving the trunk to the left or to the right, and that most of the participants would use or suggest the utilization of CogniViTra. In general, participants considered that CogniViTra is a useful tool and may represent an added value for remote dual-task training.
A Review on Improved Design Techniques for High Performance Planar Waveguide Slot Arrays
Authors: Casula Giovanni Andrea , Mazzarella Giuseppe , Montisci Giorgio , Muntoni Giacomo
Published: May 2021

Planar waveguide slot arrays (WSAs) have been used since 1940 and are currently used as performing antennas for high frequencies, especially in applications such as communication and RADAR systems. We present in this work a review of the most typical waveguide slot array configurations proposed in the literature, describing their main limitations and drawbacks along with possible effective countermeasures. Our attention has been focused mainly on the improved available design techniques to obtain high performance WSAs. In particular, the addressed topics have been reported in the following. Partially filled WSAs, or WSAs covered with single or multilayer dielectric slabs, are discussed. The most prominent second-order effects in the planar array feeding network are introduced and accurately modeled. The attention is focused on the T-junction feeding the array, on the effect of interaction between each slot coupler of the feeding network and the radiating slots nearest to this coupler, and on the waveguide bends. All these effects can critically increase the first sidelobes if compared to the ideal case, causing a sensible worsening in the performance of the array.
An Analysis and Modeling of the Class-E Inverter for ZVS/ZVDS at Any Duty Ratio with High Input Ripple Current
Authors: Ashique Ratil H. , Shihavuddin A. S. M. , Khan Mohammad Monirujjaman , Islam Aminul , Ahmed Jubaer , Arif M. Saad Bin , Maruf Md Hasan , Al Mansur Ahmed , Haq Mohammad Asif ul , Siddiquee Ashraf
Published: May 2021

This paper presents an analysis and modeling of the class-E inverter for ZVS/ZVDS execution at any duty ratio. The methodology is to determine the input current to the inverter analytically under the assumption that it always remains positive. The latter is ensured by proper selection of the input inductance such that the inverter always operates either in (1) the border condition mode or in (2) the continuous conduction mode regardless of the input ripple. Using this input current and applying the boundary conditions, the required input capacitance for the ZVS/ZVDS execution is determined at a specified input/output voltage, output power and load. The analysis shows that the ZVS/ZVDS can be achieved while the input capacitance is selected appropriately. A comparison between the analytical and simulation results is also formulated involving the proposed and other existing models. The simulation results that are provided at different duty ratios demonstrate that they are in a better agreement with the proposed analytical model regardless of the input inductance and the state of input ripple current. The analytical modeling is facilitated by using MAPLE®.
Closed-Form Expressions for Numerical Evaluation of Self-Impedance Terms Involved on Wire Antenna Analysis by the Method of Moments
Authors: Paez-Rueda Carlos-Ivan , Fajardo Arturo , Pérez Manuel , Perilla Gabriel
Published: May 2021

This paper proposes new closed expressions of self-impedance using the Method of Moments with the Point Matching Procedure and piecewise constant and linear basis functions in different configurations, which allow saving computing time for the solution of wire antennas with complex geometries. The new expressions have complexity O(1) with well-defined theoretical bound errors. They were compared with an adaptive numerical integration. We obtain an accuracy between 7 and 16 digits depending on the chosen basis function and segmentation used. Besides, the computing time involved in the calculation of the self-impedance terms was evaluated and compared with the time required by the adaptative quadrature integration solution of the same problem. Expressions have a run-time bounded between 50 and 200 times faster than an adaptive numerical integration assuming full computation of all constant of the expressions.
Probing the Energy-Environmental Kuznets Curve Hypothesis in Oil and Natural Gas Consumption Models Considering Urbanization and Financial Development in Middle East Countries
Authors: Mahmood Haider , Maalel Nabil , Hassan Muhammad Shahid
Published: May 2021

Economic growth, urbanization, and financial market development (FMD) may increase energy demand in any economy. Non-renewable sources of energy consumption, i.e., oil consumption and natural gas consumption (NGC), could have environmental consequences. We examine the effects of economic growth, urbanization, and FMD on the oil consumption and NGC in Middle East countries using the period 1975–2019. In the panel results, we found a positive effect of income and a negative effect of income-squared on oil and natural gas consumption. Hence, we corroborate the existence of the environmental Kuznets curve (EKC) hypothesis in oil and natural gas consumption models of the Middle East region. Urbanization has a positive effect on oil and natural gas consumption. FMD has a positive effect on oil consumption and has a negative effect on NGC. From the long-run, country-specific results, we validate the existence of the EKC hypothesis in the oil consumption models of Iran and Iraq. The EKC is also found in the natural gas consumption models of Iran, Kuwait, and the UAE. From the short-run results, the EKC hypothesis is validated in the oil consumption models of Iran, Iraq, and Israel. The EKC is also corroborated in the NGC models of Iran, Kuwait, and the UAE. In the long run, urbanization has a positive effect on oil consumption in Iraq, Kuwait, Saudi Arabia, and Qatar. Further, urbanization has a positive effect on the NGC in Iraq, Israel, and Saudi Arabia. Conversely, urbanization has a negative effect on oil consumption in Israel. In the short run, urbanization has a positive effect on oil consumption in Iraq, Israel, Kuwait, and Qatar. Moreover, urbanization has a positive effect on the NGC in Iraq. On the other hand, urbanization has a negative effect on oil consumption in Saudi Arabia and Iran. In the long run, FMD has a positive effect on oil consumption in Saudi Arabia and Israel. In the short run, FMD has a positive effect on oil consumption in Israel, Kuwait, and Saudi Arabia. In contrast, FMD has a negative effect on oil consumption in the UAE. Moreover, a positive effect of FMD on NGC is found in the UAE. However, FMD has a negative effect on the NGC in Israel.
Prospective Life Cycle Assessment: Effect of Electricity Decarbonization in Building Sector
Authors: Ayagapin Leslie , Praene Jean Philippe , Jaggeshar Doorgeshwaree , Surroop Dinesh
Published: May 2021

The building sector is responsible for 43% of France’s final energy consumption and is strongly associated with a high environmental impact due to its high consumption of energy and natural resources. These impacts are significant in isolated islands. Due to its geographical isolation and an area of 2512 km2, Reunion Island has a heavily carbon-based economy with a high import rate of raw materials for the building sector. This study aimed to investigate the effect of electricity mix decarbonization on residential house environmental impact. The methodology consists of three parts: (i) evaluating environmental impacts of Single-Family Houses (SFH) using life cyce assessment(LCA), (ii) defining SFH typologies using the K-means clustering algorithm, and (iii) implementing energy scenario in LCA of SFH to assess decarbonization effect. The environmental results were particularly sensitive in the operational phase, with a decrease of 83% between 2020 to 2040 of the global warming potential (GWP). The structural phase highlights the weight of imports in the building sector, as a decrease of only 1% is observed. This study clearly shows the necessary energy transition for Reunion Island. In the structural phase, the study recommends that stakeholders reduce imports and increase the share of recovered materials to achieve a substantial reduction in impacts.
Increasing the Energy-Efficiency in Vacuum-Based Package Handling Using Deep Q-Learning
Authors: Gabriel Felix , Bergers Johannes , Aschersleben Franziska , Dröder Klaus
Published: May 2021

Billions of packages are automatically handled in warehouses every year. The gripping systems are, however, most often oversized in order to cover a large range of different carton types, package masses, and robot motions. In addition, a targeted optimization of the process parameters with the aim of reducing the oversizing requires prior knowledge, personnel resources, and experience. This paper investigates whether the energy-efficiency in vacuum-based package handling can be increased without the need for prior knowledge of optimal process parameters. The core method comprises the variation of the input pressure for the vacuum ejector, compliant to the robot trajectory and the resulting inertial forces at the gripper-object-interface. The control mechanism is trained by applying reinforcement learning with a deep Q-agent. In the proposed use case, the energy-efficiency can be increased by up to 70% within a few hours of learning. It is also demonstrated that the generalization capability with regard to multiple different robot trajectories is achievable. In the future, the industrial applicability can be enhanced by deployment of the deep Q-agent in a decentral system, to collect data from different pick and place processes and enable a generalizable and scalable solution for energy-efficient vacuum-based handling in warehouse automation.
Determination of the Backfilling Time for the Zinc and Lead Ore Deposits with Application of the BackfillCAD Model
Authors: Skrzypkowski Krzysztof
Published: May 2021

This article introduces a BackfillCAD model that relates to the determination of the backfilling time. The relationship of the individual model modules using a flow chart are characterized and presented. The main aim of the research was to determine the time of backfilling for the prospective deposits of zinc and lead ores in the Olkusz region in Poland. In the first stage of the research, laboratory tests were carried out on the backfilling mixture consisting of sand and water in a 1:1 volume ratio. In the laboratory tests, the content of grains below 0.1 mm, the washability, water permeability, and compressibility of the backfilling mixture were determined. After the standard requirements were met by the backfilling mixture, the arrangement of one-way and bidirectional strip excavations was designed. In the next stages, by means of computer aided-design MineScape software, maximum thicknesses of the ore-bearing dolomite layer (T21_VI) for four geological cross-sections were determined. The height of the first backfilled layer with a thickness of 5 m was analyzed. Taking into account the geometrical parameters of the strip—the maximum length and its width and height, as well as the capacity of the backfilling installation—this study calculated the backfilling times for the future strip excavations.
A Comparative Study of Machine Learning-Based Methods for Global Horizontal Irradiance Forecasting
Authors: Gbémou Shab , Eynard Julien , Thil Stéphane , Guillot Emmanuel , Grieu Stéphane
Published: May 2021

The proliferation of photovoltaic (PV) power generation in power distribution grids induces increasing safety and service quality concerns for grid operators. The inherent variability, essentially due to meteorological conditions, of PV power generation affects the power grid reliability. In order to develop efficient monitoring and control schemes for distribution grids, reliable forecasting of the solar resource at several time horizons that are related to regulation, scheduling, dispatching, and unit commitment, is necessary. PV power generation forecasting can result from forecasting global horizontal irradiance (GHI), which is the total amount of shortwave radiation received from above by a surface horizontal to the ground. A comparative study of machine learning methods is given in this paper, with a focus on the most widely used: Gaussian process regression (GPR), support vector regression (SVR), and artificial neural networks (ANN). Two years of GHI data with a time step of 10 min are used to train the models and forecast GHI at varying time horizons, ranging from 10 min to 4 h. Persistence on the clear-sky index, also known as scaled persistence model, is included in this paper as a reference model. Three criteria are used for in-depth performance estimation: normalized root mean square error (nRMSE), dynamic mean absolute error (DMAE) and coverage width-based criterion (CWC). Results confirm that machine learning-based methods outperform the scaled persistence model. The best-performing machine learning-based methods included in this comparative study are the long short-term memory (LSTM) neural network and the GPR model using a rational quadratic kernel with automatic relevance determination.
Physiological, Biochemical and Energetic Characteristics of Torulaspora globosa, a Potential Producer of Biofuel
Authors: Kamzolova Svetlana V. , Morgunov Igor G.
Published: May 2021

It was obtained that the yeast Torulaspora globosa VKPM Y-953 is suitable for the production of biodiesel fuel. Zinc plays an important regulatory role in the metabolism of the studied strain. The study of the growth parameters and the fatty acid profile of the yeast T. globosa showed that the limitation of its growth by ethanol, at different concentrations of zinc in the medium, considerably influences the chemical composition and the energy content of yeast cells, but not their yield by weight (Yx/s). The increased concentrations of zinc in the medium, in combination with the yeast growth limitation by ethanol, elevated the content of lipids in the cells by 28% and diminished the content of proteins by 14%. At the same time, the limitation of yeast growth by zinc decreased Yx/s and energy (ηX/S) by 2.6 and 3.1 times, respectively. In this case, the content of lipids in cells fell by 72%, while that of proteins rose by 65%. The fatty acid profile of the T. globosa cells was used to estimate the main characteristics of biodiesel (iodine value, cetane number, density, and kinematic viscosity). The biomass of T. globosa can also be used in agriculture as a feed additive rich in essential amino acids.
Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm
Authors: Mohamed Mohamed Abd-El-Hakeem , Ali Ziad M. , Ahmed Mahrous , Al-Gahtani Saad F.
Published: May 2021

The main aim of this work was the maximization of the energy saving of balanced and unbalanced distribution power systems via system reconfiguration and the optimum capacitor’s bank choice, which were estimated by using a new algorithm: modified Tabu search and Harper sphere search (MTS-HSSA). The results demonstrated that the proposed method is appropriate for energy saving and improving performance compared with other methods reported in the literature for IEEE 33-bus adopted systems, including large scale systems such as IEEE 119 and the IEEE 123 unbalanced distribution system. Moreover, it can be used for unbalanced distribution systems distributed generators (DGs). The results demonstrated that the proposed method (the optimal choice of shunt capacitor (SC) banks and the optimal reconfiguration via the proposed algorithm) is appropriate for energy saving compared with different strategies for energy saving, which included distributed generation (DG) at different cost levels.
Level Crossing Barrier Machine Faults and Anomaly Detection with the Use of Motor Current Waveform Analysis
Authors: Grzechca Damian , Rybka Paweł , Pawełczyk Roman
Published: May 2021

Barrier machines are a key component of automatic level crossing systems ensuring safety on railroad crossings. Their failure results not only in delayed railway transportation, but also puts human life at risk. To prevent faults in this critical safety element of automatic level crossing systems, it is recommended that fault and anomaly detection algorithms be implemented. Both algorithms are important in terms of safety (information on whether a barrier boom has been lifted/lowered as required) and predictive maintenance (information about the condition of the mechanical components). Here, the authors propose fault models for barrier machine fault and anomaly detection procedures based on current waveform observation. Several algorithms were applied and then assessed such as self-organising maps (SOM), autoencoder artificial neural network, local outlier factor (LOF) and isolation forest. The advantage of the proposed solution is there is no change of hardware, which is already homologated, and the use of the existing sensors (in a current measurement module). The methods under evaluation demonstrated acceptable rates of detection accuracy of the simulated faults, thereby enabling a practical application at the test stage.
Comprehensive Model for Real Battery Simulation Responsive to Variable Load
Authors: Fenner Gustavo Piske , Stringini Leonardo Weber , Rangel Camilo Alberto Sepulveda , Canha Luciane Neves
Published: May 2021

This paper proposes a battery voltage model that is suitable for variable operation. The model combines the features of the Kinetic Battery Model (KiBaM) and voltage model (VM), and it improves the accuracy and quality of the solution, addressing four characteristics of operation: charging, discharging, rest after charge, and rest after discharge. This model will be known as 4-KiVM and shows low impact on computational burden. The proposed model can keep track of the voltage even when the load is inverted or turned off. To calibrate and validate the model, a NASA-provided dataset was used composed of a battery with variable charges and discharges, simulating real applications. A metaheuristic method based on tabu search is used to extract constants from this dataset and validate this hybrid model. In addition, a comparison of performance of the 4-KiVM against KiBaM, VM, and the electric circuit model (ECM) was made, showing its advantages. The results of the simulations showed a good prediction of the battery voltage response and SOC prediction in random (variable) use.
Techno-Economic Assessment of Calcium Looping for Thermochemical Energy Storage with CO2 Capture
Authors: Martinez Castilla Guillermo , Guío-Pérez Diana Carolina , Papadokonstantakis Stavros , Pallarès David , Johnsson Filip
Published: May 2021

The cyclic carbonation-calcination of CaCO3 in fluidized bed reactors not only offers a possibility for CO2 capture but can at the same time be implemented for thermochemical energy storage (TCES), a feature which will play an important role in a future that has an increasing share of non-dispatchable variable electricity generation (e.g., from wind and solar power). This paper provides a techno-economic assessment of an industrial-scale calcium looping (CaL) process with simultaneous TCES and CO2 capture. The process is assumed to make profit by selling dispatchable electricity and by providing CO2 capture services to a certain nearby emitter (i.e., transport and storage of CO2 are not accounted). Thus, the process is connected to two other facilities located nearby: a renewable non-dispatchable energy source that charges the storage and a plant from which the CO2 in its flue gas flow is captured while discharging the storage and producing dispatchable electricity. The process, which offers the possibility of long-term storage at ambient temperature without any significant energy loss, is herein sized for a given daily energy input under certain boundary conditions, which mandate that the charging section runs steadily for one 12-h period per day and that the discharging section can provide a steady output during 24 h per day. Intercoupled mass and energy balances of the process are computed for the different process elements, followed by the sizing of the main process equipment, after which the economics of the process are computed through cost functions widely used and validated in literature. The economic viability of the process is assessed through the breakeven electricity price (BESP), payback period (PBP), and as cost per ton of CO2 captured. The cost of the renewable energy is excluded from the study, although its potential impact on the process costs if included in the system is assessed. The sensitivities of the computed costs to the main process and economic parameters are also assessed. The results show that for the most realistic economic projections, the BESP ranges from 141 to −20 $/MWh for different plant sizes and a lifetime of 20 years. When the same process is assessed as a carbon capture facility, it yields a cost that ranges from 45 to −27 $/tCO2-captured. The cost of investment in the fluidized bed reactors accounts for most of the computed capital expenses, while an increase in the degree of conversion in the carbonator is identified as a technical goal of major importance for reducing the global cost.
Use of Environmental Management Systems and Renewable Energy Sources in Selected Food Processing Enterprises in Poland
Authors: Bielski Stanisław , Zielińska-Chmielewska Anna , Marks-Bielska Renata
Published: May 2021

The issue of environmental management systems in food processing companies is gaining importance due to the need to reduce water withdrawal, wastewater, air emissions, and waste generation. New technological solutions and innovations can reduce the negative effects of the enterprises’ production facilities on the environment. In Poland, the phenomenon of increasing use of the amount of renewable energy sources is influenced by, e.g., adopted national and EU legislation, development of new technologies in the field of energy, and increasing awareness of producers and consumers in the field of ecology and environmental protection. It is also important that the state creates favorable conditions for the use of renewable energy in micro-installations. The application goal of the study is to develop a procedure for improvement of the environmental management systems for food processing companies and increase the awareness of potential use and implementation of renewable energy sources by food processing entities. In the theoretical part of the study, methods of comparative, deductive, and synthetic analysis are used. In the practical part of the study survey method, case studies, a simple flashback, and transfer of ideas are presented. The results of the research can be used by state institutions to put emphasis on the implementation of sustainable development of state policy on the food market.
Multiple-Criteria-Based Electric Vehicle Charging Infrastructure Design Problem
Authors: Schmidt Mikołaj , Zmuda-Trzebiatowski Paweł , Kiciński Marcin , Sawicki Piotr , Lasak Konrad
Published: May 2021

The article presents the issue of designing a network of electric vehicle charging stations (EVCSs) for servicing passenger and commercial vehicles and taking into account the already existing locations. The authors propose a five-stage multicriteria- and GIS-based EVCS location methodology (5MAGISEV) for designing the EVCS network that includes defining potential EVCS locations (stage 1), constructing a family of evaluation criteria (stage 2), generating alternatives (stage 3), selecting an appropriate multiple criteria decision aid method (stage 4) and conducting a multicriteria evaluation of alternatives (stage 5). The methodology was verified by its experimental application for solving the problem of EVCS location in Poznan, Poland. As a result of its application, a set of over 155,000 alternatives was generated in view of different EVCS location determination policies. A family of eight criteria with subcriteria was proposed to assess the solutions, including the evaluation of the degree of integration of the considered EVCSs with such issues as public transport (C1); urbanized areas (C2); main road network (C3); industrial areas (C4); and the location with respect to transport areas (C5), shops of various types (C6), address points (C7) and DYI stores (C8). Based on the selected method of multiple criteria decision aid (LBS), a solution was selected that constitutes a compromise design of the EVCS network.
An Investigation of Takagi-Sugeno Fuzzy Modeling for Spatial Prediction with Sparsely Distributed Geospatial Data
Authors: Thomas Robert , Khan Usman , Valeo Caterina , Talebzadeh Mahta
Published: May 2021

Fuzzy set theory has shown potential for reducing uncertainty as a result of data sparsity and also provides advantages for quantifying gradational changes like those of pollutant concentrations through fuzzy clustering based approaches. The ability to lower the sampling frequency and perform laboratory analyses on fewer samples, yet still produce an adequate pollutant distribution map, would reduce the initial cost of new remediation projects. To assess the ability of fuzzy modeling to make spatial predictions using fewer sample points, its predictive ability was compared with the ordinary kriging (OK) and inverse distance weighting (IDW) methods under increasingly sparse data conditions. This research used a Takagi–Sugeno (TS) fuzzy modelling approach with fuzzy c-means (FCM) clustering to make spatial predictions of the lead concentrations in soil. The performance of the TS model was very dependent on the number of outliers in the respective validation set. For modeling under sparse data conditions, the TS fuzzy modeling approach using FCM clustering and constant width Gaussian shaped membership functions did not show any advantages over IDW and OK for the type of data tested. Therefore, it was not possible to speculate on a possible reduction in sampling frequency for delineating the extent of contamination for new remediation projects.
Developing the Assessment and Indicators for Local Institutions in Dealing with Forest Fire Dilemmas
Authors: Purnomo Eko Priyo , Agustiyara Agustiyara , Ramdani Rijal , Trisnawati Dina Wahyu , Anand P.B. , Fathani Aqil Teguh
Published: May 2021

This study is an analysis of the main criteria and indicators utilised in strengthening local institutions in charge of forest management towards dealing with forest fire incidents in Riau Province, Indonesia. Data were collected using in-depth interviews and observation. Out of the 120 questionnaires distributed to stakeholders, 81 responses were received and analysed using Microsoft Excel and with structural equation modelling (SEM) techniques using SPSS and SmartPLS. Four dimensions, including organization, capacity, authority, and governance, were respectively measured using ten indicators. The results showed a significant correlation between local institutions and these dimension variables in highlighting forest management issues. The results suggest a need to strengthen local institutions’ institutional arrangements and their capacities in order to ensure the effective management of natural resources, which may be achievable through the support and co-operation of government institutions and communities.