bluuebunny/crossref_metadata_2025 huggingface dataset:
Rare Biogeochemical Phenomenon Associated to Manganese Patinas on Mural Painting and Granite Ashlars
Authors: Campos Bruno , Marco Alexandra , Freire-Lista David M. , Durães Nuno , Silvestre-Albero Joaquin , da Silva Eduardo Ferreira , Vieira Eduarda , Pintado Manuela , Moreira Patrícia R.
Published: July 2021

This article discloses a rare and outstanding type of Mn-rich black-blue patina found on mural painting and granite ashlars located in the church of Sta. Marinha, north of Portugal, and conjectures the phenomenon associated to the appearance of such patinas in different surface materials. This Mn-patina reported on mural painting and their origin is probably assigned to manganese leaching from building materials (i.e., granite and phyllites). Stained mural painting and granite examined by XPS and SEM have showed patinas enriched with manganese (IV) oxide, potentially catalysed by a microbiota, like fungi, observed in SEM micrographs. The pigments used to depict mural painting and groundwater were also analysed by micro-Raman and ICP-MS, respectively, indicating that they are unlikely manganese sources. Unstained building materials, such as granite ashlars, historic joints, mortars and phyllite rocks, were also analysed by ICP-MS showing that historic joints and mortars present significant concentrations of manganese, possibly associated to their absorbing feature. The main materials with potential to impart manganese to Mn-rich patinas are granite ashlars and phyllites. The aim of this investigation is to reveal and ascertain the hypothetical sources and the phenomenon responsible for the Mn-rich black-blue patina appearance, both on mural painting and granite ashlars.
Improving the Physical and Mechanical Performance of Laminated Wooden Structures by Low-Temperature Plasma Treatment
Authors: Safin Ruslan Rushanovich , Khasanshin Ruslan , Galyavetdinov Nour , Salimgaraeva Regina , Mukhametzyanov Shamil , Safina Albina , Kraysman Natalia
Published: July 2021

This paper considers the effect of RF plasma on wood in improving the adhesion of binders to wood by increasing its surface wettability. Our study reveals that radiofrequency (RF) plasma treatment causes a greater than threefold decrease in the marginal wetting angle of wood. The greatest effect is achieved in RF plasma treatment in argon, which is on average 5% greater than that of RF plasma treatment in air or in propane/nitrogen mixture. In addition, the power of the RF plasma torch has the greatest influence, and the main influence comes from the voltage applied to the RF plasma torch; current does not have such a significant effect. To achieve a significant effect, the duration of exposure should be at least 5 min, with a total power of 4.05 kW. Studies have been conducted to determine the adhesive strength of wood. An increase in the strength of laminated beams made from RF-treated bars in relation to control samples was found. The greatest impact on the adhesion strength was revealed when using PVA-based glue, compared with the use of polyurethane-based adhesives and urea-formaldehyde resin.
ARLEAN: An Augmented Reality Learning Analytics Ethical Framework
Authors: Christopoulos Athanasios , Mystakidis Stylianos , Pellas Nikolaos , Laakso Mikko-Jussi
Published: July 2021

The emergence of the Learning Analytics (LA) field contextualised the connections in various disciplines and the educational sector, acted as a steppingstone toward the reformation of the educational scenery, thus promoting the importance of providing users with adaptive and personalised learning experiences. At the same time, the use of Augmented Reality (AR) applications in education have been gaining a growing interest across all the educational levels and contexts. However, the efforts to integrate LA techniques in immersive technologies, such as AR, are limited and scarce. This inadequacy is mainly attributed to the difficulties that govern the collection and interpretation of the primary data. To deal with this shortcoming, we present the “Augmented Reality Learning Analytics” (ARLEAN) ethical framework, tailored to the specific characteristics that AR applications have, and focused on various learning subjects. The core of this framework blends the technological, pedagogical, and psychological elements that influence the outcome of educational interventions, with the most widely adopted LA techniques. It provides concrete guidelines to educational technologists and instructional designers on how to integrate LA into their practices to inform their future decisions and thus, support their learners to achieve better results.
Migration and Enrichment Behaviors of Ca and Mg Elements during Cooling and Crystallization of Boron-Bearing Titanium Slag Melt
Authors: Fan Helin , Wang Ruixiang , Xu Zhifeng , Duan Huamei , Chen Dengfu
Published: July 2021

Synthetic rutile was prepared from titanium slag melt with low energy consumption and a small amount of additive (B2O3) in our previous work. The modification mechanism of titanium slag was not clear enough. The migration and enrichment behaviors of Ca and Mg elements during cooling and crystallization of boron-bearing titanium slag melt were characterized by XRF, FESEM, EMPA, and XPS. Results show that when additive (B2O3) is added, Ti elements are migrated and enriched in the area to generate rutile, while Ca, Mg, and B elements are migrated and enriched in another area to generate borate. With the additive (B2O3) amount increased, Ca and Mg element migration is complete and more thorough. Additive (B2O3) promotes rutile formation and inhibits the formation of anosovite during cooling and crystallization of titanium slag melt. With the additive (B2O3) amount increasing from 0% to 6%, the proportion of Ti3+ in the modified titanium slag reduces from 9.15% to 0%, and the proportion of Ti4+ increases from 90.85% to 100% under the same cooling and crystallization condition. The result will lay the foundation for the efficient preparation of synthetic rutile by adding B2O3 to the titanium slag melt.
Effects of Grain Refinement on the Low-Cycle Fatigue Behavior of IN792 Superalloys
Authors: Du Beining , Sheng Liyuan , Cui Chuanyong , Hu Ziyang , Sun Xiaofeng
Published: July 2021

The Ni-based IN792 superalloy is widely applied as a component in industrial turbines and aircraft engines due to its good high-temperature properties and excellent corrosion resistance. Since these components have to suffer from cyclic thermal and mechanical stresses during service, the high-temperature fatigue failure becomes one of the major factors affecting their service lives. Grain refinement has been considered as an effective way to improve the mechanical performance of superalloys. However, due to the complexity of alloy composition, microstructure and service condition, there is no unified theory about the influence of grain refinement on the fatigue performance and fracture mechanism of superalloys. In the present research, the IN792 superalloy with different grain sizes was manufactured. Then, fully reversed, strain-controlled, low-cycle fatigue (LCF) tests with four different total strain amplitudes were carried out on the alloy at 700 °C and 800 °C to clarify the effects of grain refinement on its LCF behavior. The results show that grain refinement improved the fatigue life significantly, which is mainly attributed to increasing the grain boundary content and refining MC carbides, eutectic structures and dendritic structures. During fatigue test under lower strain amplitude, the alloy exhibits a pronounced initial fatigue hardening followed by a continuous well-defined stability stage, which is caused by the formation of dislocation networks and coarsening of primary γ’ phases. However, during fatigue test under higher strain amplitude, the alloy exhibits continuous hardening response because the dislocations could shear primary γ’ phases, which could give rise to resistance to dislocation movement. In addition, the fracture surface observation shows that the fatigue fracture mode is mainly affected by the total strain amplitude. Under lower total strain amplitude, the fatigue microcracks mainly initiate at the porosities near the specimen surface, while under higher total strain amplitude, the fatigue microcracks tend to form at the interior of the specimen.
Digital Droplet PCR-Based Environmental DNA Tool for Monitoring Cryptocaryon irritans in a Marine Fish Farm from Hong Kong
Authors: Tsang Hin Hung , Domingos Jose A. , Westaway Jacob A. F. , Kam Maximilian H. Y. , Huerlimann Roger , Bastos Gomes Giana
Published: July 2021

The adoption of new investigative strategies based on environmental DNA (eDNA) can be used to monitor parasites, associated bacterial microbiomes, and physical-chemical parameters in fish farms. In this study, we used the economically important and globally distributed fish ciliate parasite Cryptocaryon irritans as a model to understand the parasite abundance and potential drivers of its presence in marine fish farms. Environmental (rainfall) and physical-chemical (temperature, oxygen, salinity, pH) data collected from a marine fish farm in Hong Kong were analyzed together with the eDNA approach targeting C. irritans abundance based on digital droplet PCR and 16S metagenomics to determine associations and triggers between parasites and specific bacterial groups. Rainfall and temperature demonstrated positive associations with high abundance of C. irritans (eDNA) at the studied marine fish cage farm. However, rainfall was the only parameter tested that demonstrated a significant association with parasite eDNA, indicating that the raining season is a risky period for fish farmers in Hong Kong. Coraliomargarita was the bacterial genus with the most significant relationship with low abundance of C. irritans in water. Understanding the environmental triggers of ciliate parasites propagation and associated bacterial microbiome could elucidate new insights into environmental control, microbial management, and promote the reduction of chemical use in marine fish farms.
Comparative Study of the Genetic Diversity of Local Steppe Cattle Breeds from Russia, Kazakhstan and Kyrgyzstan by Microsatellite Analysis of Museum and Modern Samples
Authors: Abdelmanova Alexandra S. , Kharzinova Veronika R. , Volkova Valeria V. , Dotsev Arsen V. , Sermyagin Alexander A. , Boronetskaya Oksana I. , Chinarov Roman Yu. , Lutshikhina Evgeniya M. , Sölkner Johann , Brem Gottfried , Zinovieva Natalia A.
Published: July 2021

The comparative molecular genetic study of museum and modern representatives of cattle breeds can help to elucidate the origin and maintenance of historical genetic components in modern populations. We generated the consensus genotypes for 11 microsatellite loci for 24 museum samples of Kalmyk, Kyrgyz, and Kazakh cattle, dated from the first quarter of the 20th century, and compared them with those of modern Kalmyk, Kyrgyz, and Kazakh white-headed breeds. The level of genetic diversity of the modern Kalmyk and Kyrgyz cattle (uHe = 0.771–0.778) was similar to those observed in the museum samples (uHe = 0.772–0.776), while a visible decrease in genetic variability in the modern Kazakh white-headed breed compared to museum Kazakh cattle was detected (uHe = 0.726 and 0.767, respectively). The PCA plot, FST- and Jost’s D-based networks, and STRUCTURE clustering provided strong evidence of the maintenance of the historical genetic background in modern populations of Kalmyk and Kyrgyz cattle. In spite of the allele pool of Kazakh white-headed cattle having undergone great changes compared to the museum Kazakh cattle, several animals still carry the visible aspect of the historical genetic components. Our results can be used for the selection of individuals for the creation of gene banks and may significantly improve the efficiency of conservation programs aimed at preserving genetic diversity in the national genetic resources of cattle.
Molecular Autopsy of Sudden Cardiac Death in the Genomics Era
Authors: Castiglione Vincenzo , Modena Martina , Aimo Alberto , Chiti Enrica , Botto Nicoletta , Vittorini Simona , Guidi Benedetta , Vergaro Giuseppe , Barison Andrea , Rossi Andrea , Passino Claudio , Giannoni Alberto , Di Paolo Marco , Emdin Michele
Published: July 2021

Molecular autopsy is the process of investigating sudden death through genetic analysis. It is particularly useful in cases where traditional autopsy is negative or only shows non-diagnostic features, i.e., in sudden unexplained deaths (SUDs), which are often due to an underlying inherited arrhythmogenic cardiac disease. The final goal of molecular autopsy in SUD cases is to aid medico-legal inquiries and to guide cascade genetic screening of the victim’s relatives. Early attempts of molecular autopsy relied on Sanger sequencing, which, despite being accurate and easy to use, has a low throughput and can only be employed to analyse a small panel of genes. Conversely, the recent adoption of next-generation sequencing (NGS) technologies has allowed exome/genome wide examination, providing an increase in detection of pathogenic variants and the discovery of newer genotype-phenotype associations. NGS has nonetheless brought new challenges to molecular autopsy, especially regarding the clinical interpretation of the large number of variants of unknown significance detected in each individual.
Improper Light Curing of Bulkfill Composite Drives Surface Changes and Increases S. mutans Biofilm Growth as a Pathway for Higher Risk of Recurrent Caries around Restorations
Authors: Maktabi Haifa , Ibrahim Maria Salem , Balhaddad Abdulrahman A. , Alkhubaizi Qoot , Garcia Isadora Martini , Collares Fabrício Mezzomo , Strassler Howard , Fugolin Ana Paula P. , Pfeifer Carmem S. , Melo Mary Anne S.
Published: July 2021

How dentists cure a resin-based material has deleterious effects on the material’s properties and its interaction with surrounding dental tissues. Biofilm accumulation has been implicated in the pathogenesis of carious lesions around dental restorations, with its composition manifesting expressed dysbiosis in patients suffering from dental caries. To evaluate the influence of varying radiant exposure on the degree of conversion (DC%), Streptococcus mutans biofilm growth, and surface roughness of bulk-fill composites under different light-curing conditions. Two light-curing units (LCU) at 600 and 1000 mW/cm2 were used to simulate curing conditions with different angulations (∢20° and ∢35°) or 2 mm-distance displacements of the LCU tip. The radiant exposure (RE) was assessed, and the composites were analyzed for DC%. Biofilm formation was induced over the bulk-fill composites and analyzed via colony-forming units counting and scanning electron microscopy (SEM). The surface roughness was analyzed via a profilometer and SEM after biofilm formation. Curing conditions with different angulation or displacement decreased RE compared to the “optimal condition”. The moderately (∢35°) angulated LCU tip and low (600 mW/cm2) radiant emittance significantly reduced the DC% (p < 0.05). The difference in DC% between the top and bottom of the composites ranged from 8 to 11% for 600 mW/cm2 and 10 to 20% for 1000 mW/cm2. Greater S. mutans biofilm and surface changes were found in composites with non-optimal RE delivery (e.g., tip displacement and angulation) (p < 0.05). Inadequate polymerization of bulk-fill composites was associated with more biofilm accumulation and surface topography changes. Overall, non-optimally performed curing procedures reduced the amount of delivered RE, which led to low DC%, more biofilm formation, and higher surface roughness. The improper light-curing of bulk-fill composites compromises their physicochemical and biological properties, which could lead to inferior clinical performance and reduced restorative treatments’ longevity.
Analyzing the Co-Competition Mechanism of High-Tech Park from the Perspective of Complex Socioeconomic Network
Authors: Xing Lizhi , Han Yu , Xu Jingying
Published: July 2021

The fusion of “innovation theory” and “ecology” gave birth to a large number of studies on “innovation ecology”, which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park of a business environment. In this way, we clarify the socioeconomic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.
Graphical Models in Reconstructability Analysis and Bayesian Networks
Authors: Harris Marcus , Zwick Martin
Published: July 2021

Reconstructability Analysis (RA) and Bayesian Networks (BN) are both probabilistic graphical modeling methodologies used in machine learning and artificial intelligence. There are RA models that are statistically equivalent to BN models and there are also models unique to RA and models unique to BN. The primary goal of this paper is to unify these two methodologies via a lattice of structures that offers an expanded set of models to represent complex systems more accurately or more simply. The conceptualization of this lattice also offers a framework for additional innovations beyond what is presented here. Specifically, this paper integrates RA and BN by developing and visualizing: (1) a BN neutral system lattice of general and specific graphs, (2) a joint RA-BN neutral system lattice of general and specific graphs, (3) an augmented RA directed system lattice of prediction graphs, and (4) a BN directed system lattice of prediction graphs. Additionally, it (5) extends RA notation to encompass BN graphs and (6) offers an algorithm to search the joint RA-BN neutral system lattice to find the best representation of system structure from underlying system variables. All lattices shown in this paper are for four variables, but the theory and methodology presented in this paper are general and apply to any number of variables. These methodological innovations are contributions to machine learning and artificial intelligence and more generally to complex systems analysis. The paper also reviews some relevant prior work of others so that the innovations offered here can be understood in a self-contained way within the context of this paper.
Towards Acquiring Teachers’ Professional Qualification Based on Professional Standards: Perceptions, Expectations and Needs on the Application Process
Authors: Leibur Tiiu , Saks Katrin , Chounta Irene-Angelica
Published: July 2021

This paper presents the findings of a study into the application process of the professional standards (PS) qualification in Estonia, which is a standard used to identify the level of professionalism of a teacher. The study collected the views of active teachers who have applied for the PS and those of the assessors to understand the shortcomings in the application and the expectations for the application process. The main challenges identified are that teachers lack respective skills to adequately comprehend qualification requirements (unambiguous interpretation of PS) and the lack of evidence-based performance indicators (difficult to prove) and weak self-analysis skills; hence, the teacher needs assistance. The research found that teachers need collaborative support, motivation and constructive feedback on their professional development (PD), both from colleagues and at school and national levels. Based on this research, it can be said that teachers who have gone through the application process have gained greater self-confidence, value themselves as teachers and continue their in-service training.
A Wideband Radio Channel Sounder for Non-Stationary Channels: Design, Implementation and Testing
Authors: López-Valcárcel Luis A. , García Sánchez Manuel
Published: July 2021

The increasing bandwidths and frequencies proposed for new mobile communications give rise to new challenges for system designers. Channel sounding and channel characterization are important tasks to provide useful information for the design of systems, protocols, and techniques to fight the propagation impairments. In this paper, we present a novel radio channel sounder capable of dealing with non-stationary channels. It can be operated in real-time and has a compact size to ease transport. For versatility and cost purposes, the core of the system is implemented in Field Programmable Gate Arrays (FPGAs). Three measurement campaigns have been conducted to illustrate the performance of the sounder in both static and non-static channels. In its current configuration, the sounder reaches an RF null-to-null bandwidth of 1 GHz, providing a delay resolution of 2 ns, a maximum measurable Doppler shift of 7.63 kHz, and 4.29 s of continuous acquisition time. A comparison with other channel sounders in the literature reveals that our proposal achieves a good combination of performance, cost, and size.
Modeling and Simulation of Monolithic Single-Supply Power Operational Amplifiers
Authors: Pandiev Ivailo Milanov
Published: July 2021

In this paper a simple PSpice (Personal Simulation Program with Integrated Circuit Emphasis) macro-model was developed, and verified for monolithic power operational amplifiers operated with a single-supply voltage. The proposed macro-model is developed using simplification and build-up techniques for macro-modeling of operational amplifiers and simulates the basic static and dynamic characteristics, including input impedance, small-signal frequency responses at various voltage gains, output power versus supply voltage, slew-rate-limiting, voltage limiting, output offset voltage versus supply voltage ripples, and output resistance. Furthermore, the macro-model also takes into account the ground reference voltage in the amplifier at a single power supply voltage. The model is implemented as a hierarchical structure suitable for the PSpice circuit simulation platform. The sub-circuit is built using standard PSpice components and analog behavioral modeling blocks. The accuracy of the model is verified by extracting the model parameters for single-supply power operational amplifier TDA2005 from ST Microelectronics as example. The effectiveness of the model is validated by comparing the simulation results of the electrical parameters with the corresponding measured values obtained by experimental testing of sample circuits. The comparative analysis shows that the relative error of the modeled large-signal parameters is less than 15%. Moreover, an error of 15% is quite acceptable, considering the technological tolerances of the electrical parameters for this type of analog ICs.
A Multimodal Smart Quantum Particle Swarm Optimization for Electromagnetic Design Optimization Problems
Authors: Fahad Shah , Yang Shiyou , Khan Rehan Ali , Khan Shafiullah , Khan Shoaib Ahmed
Published: July 2021

Electromagnetic design problems are generally formulated as nonlinear programming problems with multimodal objective functions and continuous variables. These can be solved by either a deterministic or a stochastic optimization algorithm. Recently, many intelligent optimization algorithms, such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC), have been proposed and applied to electromagnetic design problems with promising results. However, there is no universal algorithm which can be used to solve engineering design problems. In this paper, a stochastic smart quantum particle swarm optimization (SQPSO) algorithm is introduced. In the proposed SQPSO, to tackle the premature convergence problem in order to improve the global search ability, a smart particle and a memory archive are adopted instead of mutation operations. Moreover, to enhance the exploration searching ability, a new set of random numbers and control parameters are introduced. Experimental results validate that the adopted control policy in this work can achieve a good balance between exploration and exploitation. Finally, the SQPSO has been tested on well-known optimization benchmark functions and implemented on the electromagnetic TEAM workshop problem 22. The simulation result shows an outstanding capability of the proposed algorithm in speeding convergence compared to other algorithms.
Application of Graphene in Fiber-Reinforced Cementitious Composites: A Review
Authors: Wu Songmei , Qureshi Tanvir , Wang Guorui
Published: July 2021

Graphene with fascinating properties has been deemed as an excellent reinforcement for cementitious composites, enabling construction materials to be smarter, stronger, and more durable. However, some challenges such as dispersion issues and high costs, hinder the direct incorporation of graphene-based reinforcement fillers into cementitious composites for industrial production. The combination of graphene with conventional fibers to reinforce cement hence appears as a more promising pathway especially towards the commercialization of graphene for cementitious materials. In this review paper, a critical and synthetical overview on recent research findings of the implementation of graphene in fiber-reinforced cementitious composites was conducted. The preparation and characterization methods of hybrid graphene-fiber fillers are first introduced. Mechanical reinforcing mechanisms are subsequently summarized, highlighting the main contribution of nucleation effect, filling effect, interfacial bonding effect, and toughening effect. The review further presents in detail the enhancements of multifunctional properties of graphene-fiber reinforced cementitious composites, involving the interfacial properties, mechanical properties, durability, electrical conductivity, and electromagnetic interference shielding. The main challenges and future prospects are finally discussed to provide constructive ideas and guidance to assist with relevant studies in future.
The Influence of Hydrodearomatisation Reaction Kinetics on the Modelling of Sulphur and Aromatics Removal from Diesel Fuel in an Industrial Hydrotreating Process
Authors: Glišić Sandra B. , Orlović Aleksandar M.
Published: July 2021

Over the years, the hydrotreating process has been considerably improved in order to facilitate the production of environmentally friendly diesel fuels by reducing sulphur and aromatics concentrations, as mandated by contemporary emissions regulations. In this study, different kinetic models for the hydrodearomatisation reaction and the influence of reaction rate on performance of the industrial trickle bed reactor for hydrotreating of gas oil and light cycle oil fractions were analysed. The impact on reactor temperature, catalyst wetting efficiency, and conversion of sulphur and aromatics were determined. The results of simulations were compared with experimental data from an industrial test run and the best model for the observed process is proposed. Reactor performance and overall efficiency of the process is strongly dependent on the kinetics of hydrodearomatisaton with respect to aromatics conversion but even more so with respect to the temperature increase in the reactor, which affects all key catalytic reaction parameters, catalyst wetting efficiency, and thus the sulphur conversion. Based on the obtained simulation results, it could be concluded that reactor performance is strongly dependent on the hydrodearomatisation reaction. The best predictions of outlet temperature as well as sulphur and aromatic conversion (deviation from the experimental value 0.87 K, 0.01% and 2.57%, respectively) are achieved with the Langmuir–Hinshelwood kinetic model proposed by Owusu-Boakye.
Optimization of Low Head Axial-Flow Turbines for an Overtopping BReakwater for Energy Conversion: A Case Study
Authors: Mariani Antonio , Crispino Gaetano , Contestabile Pasquale , Cascetta Furio , Gisonni Corrado , Vicinanza Diego , Unich Andrea
Published: July 2021

Overtopping-type wave power conversion devices represent one of the most promising technology to combine reliability and competitively priced electricity supplies from waves. While satisfactory hydraulic and structural performance have been achieved, the selection of the hydraulic turbines and their regulation is a complex process due to the very low head and a variable flow rate in the overtopping breakwater set-ups. Based on the experience acquired on the first Overtopping BReakwater for Energy Conversion (OBREC) prototype, operating since 2016, an activity has been carried out to select the most appropriate turbine dimension and control strategy for such applications. An example of this multivariable approach is provided and illustrated through a case study in the San Antonio Port, along the central coast of Chile. In this site the deployment of a breakwater equipped with OBREC modules is specifically investigated. Axial-flow turbines of different runner diameter are compared, proposing the optimal ramp height and turbine control strategy for maximizing system energy production. The energy production ranges from 20.5 MWh/y for the smallest runner diameter to a maximum of 34.8 MWh/y for the largest runner diameter.
Effect of Injection Timing and Injection Duration of Manifold Injected Fuels in Reactivity Controlled Compression Ignition Engine Operated with Renewable Fuels
Authors: Harari P. A. , Banapurmath N. R. , Yaliwal V. S. , Khan T. M. Yunus , Badruddin Irfan Anjum , Kamangar Sarfaraz , Mahlia Teuku Meurah Indra
Published: July 2021

In the current work, an effort is made to study the influence of injection timing (IT) and injection duration (ID) of manifold injected fuels (MIF) in the reactivity controlled compression ignition (RCCI) engine. Compressed natural gas (CNG) and compressed biogas (CBG) are used as the MIF along with diesel and blends of Thevetia Peruviana methyl ester (TPME) are used as the direct injected fuels (DIF). The ITs of the MIF that were studied includes 45° ATDC, 50° ATDC, and 55° ATDC. Also, present study includes impact of various IDs of the MIF such as 3, 6, and 9 ms on RCCI mode of combustion. The complete experimental work is conducted at 75% of rated power. The results show that among the different ITs studied, the D+CNG mixture exhibits higher brake thermal efficiency (BTE), about 29.32% is observed at 50° ATDC IT, which is about 1.77, 3.58, 5.56, 7.51, and 8.54% higher than D+CBG, B20+CNG, B20+CBG, B100+CNG, and B100+CBG fuel combinations. The highest BTE, about 30.25%, is found for the D+CNG fuel combination at 6 ms ID, which is about 1.69, 3.48, 5.32%, 7.24, and 9.16% higher as compared with the D+CBG, B20+CNG, B20+CBG, B100+CNG, and B100+CBG fuel combinations. At all ITs and IDs, higher emissions of nitric oxide (NOx) along with lower emissions of smoke, carbon monoxide (CO), and hydrocarbon (HC) are found for D+CNG mixture as related to other fuel mixtures. At all ITs and IDs, D+CNG gives higher In-cylinder pressure (ICP) and heat release rate (HRR) as compared with other fuel combinations.
Characterization of Potential-Induced Degradation and Recovery in CIGS Solar Cells
Authors: Lee Solhee , Bae Soohyun , Park Se Jin , Gwak Jihye , Yun JaeHo , Kang Yoonmook , Kim Donghwan , Eo Young-Joo , Lee Hae-Seok
Published: July 2021

The potential-induced degradation (PID) mechanism in Cu(In,Ga)(Se,S)2 (CIGS) thin-film solar cells, which are alternative energy sources with a high efficiency (>23%) and upscaling possibilities, remains unclear. Therefore, the cause of PID in CIGS solar cells was investigated in this study at the cell level. First, an appropriate PID experiment structure at the cell level was determined. Subsequently, PID and recovery tests were conducted to confirm the PID phenomenon. Light current–voltage (I–V), dark I–V, and external quantum efficiency (EQE) analyses were conducted to determine changes in the cell characteristics. In addition, capacitance–voltage (C–V) measurements were carried out to determine the doping concentration and width of the space charge region (SCR). Based on the results, the causes of PID and recovery of CIGS solar cells were explored, and it was found that PID occurs due to changes in the bulk doping concentration and built-in potential at the junction. Furthermore, by distinguishing the effects of temperature and voltage, it was found that PID phenomena occurred when potential difference was involved.
Cooking Fuel Usage in Sub-Saharan Urban Households
Authors: Meng Ting , Florkowski Wojciech J. , Sarpong Daniel B. , Chinnan Manjeet , Resurreccion Anna V. A.
Published: July 2021

This study models the frequency use of wood, charcoal, liquid gas, electricity, and kerosene in urban households in Ghana and supplements the literature on cooking fuel choices. The modeling is based on survey data collected in several major Ghanaian cities. Survey results indicate that charcoal and liquid gas are frequently used in meal preparation, while the frequency use of firewood, kerosene, and electricity is limited. Frequency use is estimated using the ordered probit technique. Five cooking fuel use equations identify income, socio-demographic characteristics, and location of urban residents as influencing the frequency use. Statistically significant effects measure probability changes in each of the four fuel categories. Income and education increase the probability of often or very often of using liquid gas or electricity to cook. The effect of being employed by the government is similar but less consistent. Age, household size, and marital status are linked to frequency use, but differently affect specific fuels. As the number of children or adults increases in a household, so does the probability of using firewood or charcoal, but this also increases the probability that such households never use liquid gas or electricity for cooking. Regional differences indicate Tamale residents heavily rely on wood and charcoal, and infrequently use liquid gas or electricity. Multiple cooking fuel use behavior may reflect risk aversion to fuel shortages. Increasing incomes and improving education will drive the probability of an increased use of cleaner cooking fuels and decreased use of fuel mixes, benefiting meal preparers’ health and the environment.
The Preferences of Active Final Purchasers Regarding the Environment of Cooperation with Offerors and Benefits Achieved Thanks to Such Cooperation
Authors: Baruk Agnieszka Izabela
Published: July 2021

The aim of this study was to identify the preferences of final purchasers regarding the environment of cooperation with offerors and the benefits of cooperation, as well as to identify dependencies between two groups of preferences, taking into account the age of purchasers. The results of an analysis of the global literature on the subject indicate that so far these issues have not been studied, either in relation to the energy market or other areas of the consumer market. Therefore, we can talk about a cognitive and research gap in this area. In order to reduce the gap, seven research hypotheses were formulated and primary research was carried out on 1196 adult representatives of final purchasers in Poland to verify the hypotheses. The collected data were subjected to quantitative analysis, the results of which made it possible to state that most respondents preferred the parallel use of the online and offline environments as a place of interaction with offerors. More than half of the respondents stated that a combination of material and non-material benefits achieved through cooperation with offerors effectively encourages purchasers to undertake this cooperation. Non-material benefits such as the possibility of gaining new knowledge, the possibility of gaining new skills, and the possibility of establishing relationships with new people turned out to be particularly important. Statistically significant dependencies were identified between the preferences regarding the environment of cooperation and preferences regarding the benefits of cooperation. Moreover, dependencies were identified between age and the general specificity of benefits of cooperation with offerors, and between age and twelve specific benefits of cooperation. Conclusions drawn from the results obtained have great cognitive and application value, enriching knowledge of the behavior of final purchasers and making it easier for offerors, including companies operating on the consumer energy market, to make effective decisions about encouraging recipients to cooperate in the process of creating a marketing offer.
Integrated Optimal Design of Permanent Magnet Synchronous Generator for Smart Wind Turbine Using Genetic Algorithm
Authors: Agrebi Henda Zorgani , Benhadj Naourez , Chaieb Mohamed , Sher Farooq , Amami Roua , Neji Rafik , Mansfield Neil
Published: July 2021

In recent years, the investment in the wind energy sector has increased in the context of producing green electricity and saving the environment. The installation of small wind turbines (SWTs) represents an actual strategy for meeting energy needs for off-grid systems and certain specialized applications. SWTs are more expensive per kilowatt installed as compared to large-scale wind turbines. Therefore, the main objective of this study is to produce an economical technology for the wind power market offering low-cost SWTs. The idea consists of considering a simple structure of the wind turbine using direct-drive permanent magnet synchronous generator (DDPMSG). DDPMSGs are the most useful machines in the wind energy field thanks to several advantages, such as elimination of noise and maintenance cost due to suppression of the gearbox and absence of the rotor circuit excitation barriers by the presence of the permanent magnets (PMs). Their major downside is the high cost of active materials, especially the PMs. Thus, the improvement of the generator design is treated as being the main component of the considered chain to assure active materials’ mass and cost reduction. The methodology studied aims to explain the approach of the design integrated by optimization of the considered system. It is based on the elaboration of analytical models to find a feasible structure for the system, taking into account the multi-disciplinary analysis. The relevance of these models is validated by the finite element method using 2D MATLAB-FEMM simulation. The models are integrated to elaborate the optimization problem based on a genetic algorithm to improve the cost of the proposed generator by minimizing the mass of its active constructive materials. As an outcome, an optimal solution is offered for the wind generators market, providing a 16% cost reduction.
A Multi-Model Probability Based Two-Layer Fusion Modeling Approach of Supercapacitor for Electric Vehicles
Authors: Huang Bo , Ma Yuting , Wang Chun , Chen Yongzhi , Yu Quanqing
Published: July 2021

The improvement of the supercapacitor model redundancy is a significant method to guarantee the reliability of the power system in electric vehicle application. In order to enhance the accuracy of the supercapacitor model, eight conventional supercapacitor models were selected for parameter identification by genetic algorithm, and the model accuracies based on standard diving cycle are further discussed. Then, three fusion modeling approaches including Bayesian fusion, residual normalization fusion, and state of charge (SOC) fragment fusion are presented and compared. In order to further improve the accuracy of these models, a two-layer fusion model based on SOC fragments is proposed in this paper. Compared with other fusion models, the root mean square error (RMSE), maximum error, and mean error of the two-layer fusion model can be reduced by at least 23.04%, 8.70%, and 30.13%, respectively. Moreover, the two-layer fusion model is further verified at 10, 25, and 40 °C, and the RMSE can be correspondingly reduced by 60.41%, 47.26%, 23.04%. The results indicate that the two-layer fusion model proposed in this paper achieves better robustness and accuracy.
Numerical Simulation on Charge Transport and DC Breakdown in Polyethylene-Based Micro-h-BN/Nano-SiO2 with Filler Orientation Dependent Trap Energy
Authors: Xu Xuri , Gao Yu , Li Jing , Song Zheng , Zhao Huicun , Han Tao
Published: July 2021

In order to improve the thermal conductivity and the insulation properties of polyethylene (PE) used as cable insulation under DC stress, hexagonal boron nitride (h-BN) and inorganic particles have been considered as micro-filler and nano-filler, respectively. As a 2D material, the orientation of h-BN possibly affects the insulation properties of the polymer. It is important to understand the influence of the filler orientation on the insulation performance of the polymer. In this work, a numerical simulation has been performed to investigate the effect of orientation of micro-h-BN on charge transport and DC breakdown of PE-based micro/nano-composites and a comparison between the simulation result and previous literature data has been conducted. The h-BN was designated to be parallel, perpendicular to the normal sample surface vector (the direction of electric field in this work) or randomly distributed in the matrix, and the charge transport behavior and DC breakdown strength in the samples were discussed by using the bipolar charge transport (BCT) model. The results indicated that when the h-BN was perpendicular to the normal vector, the density of trapped charge was the largest and the DC breakdown strength was the highest among the three cases studied. It is suggested that the charge trapping/de-trapping processes and the electric field in the sample vary with the orientation of h-BN through tailoring the trap characteristics of the material.
LED Luminaires: Many Chips—Many Photometric and Lighting Simulation Issues to Solve
Authors: Skarżyński Krzysztof , Żagan Wojciech , Krajewski Kamil
Published: July 2021

Currently, built LED luminaires are usually multi-source. This causes a large number of photometric and simulation problems connected with computer lighting visualization. This paper highlights three key issues with these luminaires: a change in the traditional understanding of the coordinate system for these luminaires, the photometric test distance of these luminaires and the need for the photometric separation of a single LED in the computer lighting simulation process. An optical model of a linear LED luminaire used in floodlighting was formulated on this basis. The presented conclusions refer to practical applications. Thus, it is necessary to address the crucial points that specify the coordinate system for the multi-source LED luminaire by its designer and present the information in a datasheet. The other important points concern determining the appropriate photometric test distance for the multi-source LED luminaires of a given type and creating photometric files for the different distances in the operation of the luminaire. Taking the above ideas into account will lead to an improvement in the quality and accuracy of lighting measurements and simulations.
Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid
Authors: Çavdar İsmail Hakkı , Feryad Vahit
Published: July 2021

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.
Nutrition, Exercise, and Stress Management for Treatment and Prevention of Psychiatric Disorders. A Narrative Review Psychoneuroendocrineimmunology-Based
Authors: Bottaccioli Francesco , Bottaccioli Anna Giulia , Marzola Enrica , Longo Paola , Minelli Andrea , Abbate-Daga Giovanni
Published: July 2021

Psychoneuroendocrineimmunology (PNEI) brings together knowledge acquired since the 1930s from endocrinology, immunology, neuroscience, and psychology. With PNEI, a model of research and interpretation of health and disease is emerging, which sees the human body as a structured and interconnected unit, where the psychological and biological systems are mutually coordinated. In the PNEI view, many factors could influence mental health, with the endocrine system involved in mediating the effects of environmental stress on mental health and inflammation in the onset and course of psychiatric disorders as a result of individual and collective conditions and behaviors. Among these, nutrition is one way by which the environment impacts physiology: indeed, many pieces of research showed that several elements (e.g., probiotics, fish oil, zinc) have a positive effect on mental disorders thus being potentially augmentation agents in treatment. Still, physical activity can moderate depressive symptoms, while prolonged stress increases the risk of psychopathology. Taken together, the PNEI-based approach may inform prevention and treatment strategies, also in the field of mental health care.