bluuebunny/crossref_metadata_2025 huggingface dataset:
Ozone Kinetic Studies Assessment for the PPCPs Abatement: Mixtures Relevance
Authors: Gomes João , Bernardo Carla , Jesus Fátima , Pereira Joana Luísa , Martins Rui C.
Published: March 2022

The increasing consumption of pharmaceutical and personal care products (PPCPs) by humankind has been causing an accumulation of contaminants (commonly referred to as contaminants of emerging concern), in effluents and water resources. Ozonation can be used to improve the removal of these contaminants during water treatment to alleviate this burden. In this work, the degradation of methyl (MP), propylparaben (PP), paracetamol (PCT), sulfamethoxazole (SMX), and carbamazepine (CBZ) by ozonation was assessed both for individual compounds and for mixtures with increasing complexity (two to five compounds). Ozonation was performed at pH3 to gain an insight on the exclusive action of molecular ozone as oxidizing agent. The degradation of contaminants was described as a function of time and transferred ozone dose, and the corresponding pseudo-first order kinetic rate constants (k’) were determined. PPCPs were degraded individually within 1.5 to 10 min. CBZ was the most quickly degraded (k’ = 1.25 min−1) and MP the most resistant to ozone (k’ = 0.25 min−1). When in the mixture, the degradation rate of the contaminants was slower. For parabens, the increase of the number of compounds in the mixture led to an exponential decrease of the k’ values. Moreover, the presence of more PPCPs within the mixture increased energy consumption associated with the treatment, thereby reflecting higher economic costs.
Pectin Microspheres: Synthesis Methods, Properties, and Their Multidisciplinary Applications
Authors: Gutierrez-Alvarado Keila , Chacón-Cerdas Randall , Starbird-Perez Ricardo
Published: March 2022

There is great contemporary interest in using cleaner technologies through green chemistry and utilizing biopolymers as raw material. Pectin is found on plant cell walls, and it is commonly extracted from fruit shells, mostly apples or citrus fruits. Pectin has applications in many areas of commercial relevance; for this reason, it is possible to find available information about novel methods to transform pectin and pursuing enhanced features, with the structuring of biopolymer microspheres being highly cited to enhance its activity. The structuring of polymers is a technique that has been growing in recent decades, due to its potential for diverse applications in various fields of science and technology. Several techniques are used for the synthesis of microspheres, such as ionotropic gelation, extrusion, aerosol drying, or emulsions, with the latter being the most commonly used method based on its reproducibility and simplicity. The most cited applications are in drug delivery, especially for the treatment of colon diseases and digestive-tract-related issues. In the industrial field, it is used for protecting encapsulated compounds; moreover, the environmental applications mainly include the bioremediation of toxic substances. However, there are still many possibilities for expanding the use of this biopolymer in the environmental field.
The Influence of Family Bonding, Support, Engagement in Healthcare, on PrEP Stigma among Young Black and Latino Men Who Have Sex with Men: A Path Analysis
Authors: Boyd Donte T. , Abubakari Gamji M’Rabiu , Turner DeAnne , Ramos S. Raquel , Hill Mandy J. , Nelson LaRon E.
Published: March 2022

This study employs the ecodevelopmental theory to examine the influence of mother and father bonding, family engagement in healthcare, and family support on PrEP stigma among BLMSM. We used a cross-sectional sample from wave five of the Healthy Young Men (HYM) study, with a survey sample of 399 participants aged 16–24 years. We conducted two-path analyses to test multiple hypotheses: (1) mother/father bonding is associated with an increase in family engagement in healthcare; (2) family engagement in healthcare is associated with family social support; and (3) family social support is associated with PrEP stigma. Family social support was negatively correlated with PrEP stigma (r = −0.15; p < 0.001). The findings show that families either led by a Black/Latino father or mother have a significant impact on the sexual health-seeking behavior of BLMSM and their perception of HIV and PrEP.
Integration and Control of Distributed Renewable Energy Resources
Authors: Nazaripouya Hamidreza
Published: March 2022

The increase in the population growth rate and the motivation to overcome issues such as environmental concerns and air pollution have made distributed renewable energy resources (DRER) the most popular option for providing the required energy [...]
Modelling of Extremely High Rainfall in Limpopo Province of South Africa
Authors: Sikhwari Thendo , Nethengwe Nthaduleni , Sigauke Caston , Chikoore Hector
Published: March 2022

Extreme value theory is a powerful method that is known to provide statistical models for events rarely observed. This paper presents a modelling framework for the maximum rainfall data recorded in Limpopo province, South Africa, from 1960 to 2020. Daily and monthly rainfall data were obtained from the South Africa Weather Service. In this work, the r-largest order statistics modelling approach is used. Yearly blocks were used in fitting a 61 years’ data set. The parameters of the developed models were estimated using the maximum likelihood method. After the suitable model for data was chosen, i.e., GEVDr=8, the 50-year return level was estimated as 368 mm, which means a probability of 0.02 exceeding 368 mm in fifty years in the Thabazimbi area. This study helps decision-makers in government and non-profit organisations improve preparation strategies and build resilience in reducing disasters resulting from extreme weather events such as excessive rainfall.
What Should Be the Topics of a Prospective Study on Ovarian Masses in Children?—Results of a Multicenter Retrospective Study and a Scoping Literature Review
Authors: Łuczak Justyna , Bagłaj Maciej , Dryjański Piotr , Kalcowska Alicja , Banaszyk-Pucała Nastazja , Boczar Maria , Dymek Krzysztof , Fryczek Małgorzata , Giżewska-Kacprzak Kaja , Górecki Wojciech , Grabowski Andrzej , Gregor Anna , Jabłońska Maria , Kowalewski Grzegorz , Lewandowska Magdalena , Małowiecka Maria , Ogorzałek Anna , Pękalska Magdalena , Piotrowska-Gall Aneta , Porębski Mateusz , Siewiński Marek , Patkowski Dariusz
Published: March 2022

Purpose: to determine management problems of ovarian masses in girls in order to form a baseline for prospective randomized studies of the established topics and quality improvement of our management. Materials and Methods: We performed a national analysis of clinical aspects of ovarian masses in girls operated on in Poland, analyzed retrospectively medical files of all consecutive patients aged 0–18 who underwent surgeries for ovarian lesions between 2012 and 2017 at 17 pediatric surgical departments and complemented the analysis with a scoping review of a recent primary research related to ovarian masses in children. Results: The study group comprised 595 patients. Forty-four (7.39%) girls were diagnosed with malignant tumors. The overall preservation rate was 64.54%. The analysis revealed that positive tumor markers (OR = 10.3), lesions larger than 6 cm (OR = 4.17) and solid mass on ultrasound examination (OR = 5.34) are interdependent variables differentiating malignant tumors from non-malignant lesions (X42 = 79.1; p = 0.00000). Our scoping review revealed 10 major branches of research within the topic of ovarian masses in pediatric population. Conclusions: We have developed an overview of the field with the emphasis on the local environment. Our next step is a multi-institutional prospective study of a quality improvement project implementation based on the obtained knowledge.
Design of Promising aza-BODIPYs for Bioimaging and Sensing
Authors: Merkushev Dmitry , Vodyanova Olga , Telegin Felix , Melnikov Pavel , Yashtulov Nikolay , Marfin Yuriy
Published: March 2022

The obtainment of new luminophores for molecular sensorics of biosystems is becoming one of the urgent tasks in the field of chemical synthesis. The solution to each practical problem imposes its own limitations in the design of new structures with practically useful properties. The relationship between the structure and spectral properties is still to be unveiled. Three aza-BODIPY complexes with substituents of different natures were studied using time-resolved and steady-state fluorescence and absorption spectroscopy. The solvatochromic properties of aza-BODIPYs were studied with the use of a combined polyparametric approach and analysis by chemoinformatics methods for the first time. It was found that red shift of aza-BODIPY dyes was due to the increase of their structural lability. Predictive and experimental methods showed that the investigated aza-BODIPYs exhibited a positive solvatochromic effect, in contrast to classic BODIPYs (bearing C in the meso-position of the dipyrromethene core), which represents the negative solvatochromic properties. Spectral maxima in the area of the therapeutic window, low and predictable solvatochromism, and the ability to fine-tune the spectral characteristics make the investigated aza-BODIPYs promising scaffolds for the construction of bioengineering devices. Generalizations on the aza-BODIPYs’ design patterns were made in accordance with further bioimaging applications.
A Banking Platform to Leverage Data Driven Marketing with Machine Learning
Authors: Torrens Marc , Tabakovic Amir
Published: March 2022

Payment data is one of the most valuable assets that retail banks can leverage as the major competitive advantage with respect to new entrants such as Fintech companies or giant internet companies. In marketing, the value behind data relates to the power of encoding customer preferences: the better you know your customer, the better your marketing strategy. In this paper, we present a B2B2C lead generation application based on payment transaction data within the online banking system. In this approach, the bank is an intermediary between its private customers and merchants. The bank uses its competence in Machine Learning driven marketing to build a lead generation application that helps merchants run data driven campaigns through the banking channels to reach retail customers. The bank’s retail customers trade the utility hidden in its payment transaction data for special offers and discounts offered by merchants. During the entire process banks protects the privacy of the retail customer.
Neural Network Structure Optimization by Simulated Annealing
Authors: Kuo Chun Lin , Kuruoglu Ercan Engin , Chan Wai Kin Victor
Published: March 2022

A critical problem in large neural networks is over parameterization with a large number of weight parameters, which limits their use on edge devices due to prohibitive computational power and memory/storage requirements. To make neural networks more practical on edge devices and real-time industrial applications, they need to be compressed in advance. Since edge devices cannot train or access trained networks when internet resources are scarce, the preloading of smaller networks is essential. Various works in the literature have shown that the redundant branches can be pruned strategically in a fully connected network without sacrificing the performance significantly. However, majority of these methodologies need high computational resources to integrate weight training via the back-propagation algorithm during the process of network compression. In this work, we draw attention to the optimization of the network structure for preserving performance despite compression by pruning aggressively. The structure optimization is performed using the simulated annealing algorithm only, without utilizing back-propagation for branch weight training. Being a heuristic-based, non-convex optimization method, simulated annealing provides a globally near-optimal solution to this NP-hard problem for a given percentage of branch pruning. Our simulation results have shown that simulated annealing can significantly reduce the complexity of a fully connected network while maintaining the performance without the help of back-propagation.
Device-Independent Certification of Maximal Randomness from Pure Entangled Two-Qutrit States Using Non-Projective Measurements
Authors: Borkała Jakub J. , Jebarathinam Chellasamy , Sarkar Shubhayan , Augusiak Remigiusz
Published: March 2022

While it has recently been demonstrated how to certify the maximal amount of randomness from any pure two-qubit entangled state in a device-independent way, the problem of optimal randomness certification from entangled states of higher local dimension remains open. Here we introduce a method for device-independent certification of the maximal possible amount of 2log23 random bits using pure bipartite entangled two-qutrit states and extremal nine-outcome general non-projective measurements. To this aim, we exploit a device-independent method for certification of the full Weyl–Heisenberg basis in three-dimensional Hilbert spaces together with a one-sided device-independent method for certification of two-qutrit partially entangled states.
Nonparametric Causal Structure Learning in High Dimensions
Authors: Chakraborty Shubhadeep , Shojaie Ali
Published: March 2022

The PC and FCI algorithms are popular constraint-based methods for learning the structure of directed acyclic graphs (DAGs) in the absence and presence of latent and selection variables, respectively. These algorithms (and their order-independent variants, PC-stable and FCI-stable) have been shown to be consistent for learning sparse high-dimensional DAGs based on partial correlations. However, inferring conditional independences from partial correlations is valid if the data are jointly Gaussian or generated from a linear structural equation model—an assumption that may be violated in many applications. To broaden the scope of high-dimensional causal structure learning, we propose nonparametric variants of the PC-stable and FCI-stable algorithms that employ the conditional distance covariance (CdCov) to test for conditional independence relationships. As the key theoretical contribution, we prove that the high-dimensional consistency of the PC-stable and FCI-stable algorithms carry over to general distributions over DAGs when we implement CdCov-based nonparametric tests for conditional independence. Numerical studies demonstrate that our proposed algorithms perform nearly as good as the PC-stable and FCI-stable for Gaussian distributions, and offer advantages in non-Gaussian graphical models.
Non-Markovian Quantum Dynamics in a Squeezed Reservoir
Authors: Link Valentin , Strunz Walter T. , Luoma Kimmo
Published: March 2022

We study non-Markovian dynamics of an open quantum system system interacting with a nonstationary squeezed bosonic reservoir. We derive exact and approximate descriptions for the open system dynamics. Focusing on the spin boson model, we compare exact dynamics with Redfield theory and a quantum optical master equation for both short and long time dynamics and in non-Markovian and Markov regimes. The squeezing of the bath results in asymptotic oscillations in the stationary state, which are captured faithfully by the Redfield master equation in the case of weak coupling. Furthermore, we find that the bath squeezing direction modifies the effective system–environment coupling strength and, thus, the strength of the dissipation.
When Is a Genuine Multipartite Entanglement Measure Monogamous?
Authors: Guo Yu
Published: March 2022

A crucial issue in quantum communication tasks is characterizing how quantum resources can be quantified and distributed over many parties. Consequently, entanglement has been explored extensively. However, there are few genuine multipartite entanglement measures and whether it is monogamous is so far unknown. In this work, we explore the complete monogamy of genuine multipartite entanglement measure (GMEM) for which, at first, we investigate a framework for unified/complete GMEM according to the unified/complete multipartite entanglement measure we proposed in 2020. We find a way of inducing unified/complete GMEM from any given unified/complete multipartite entanglement measure. It is shown that any unified GMEM is completely monogamous, and any complete GMEM that is induced by given complete multipartite entanglement measure is completely monogamous. In addition, the previous GMEMs are checked under this framework. It turns out that the genuinely multipartite concurrence is not as good of a candidate as GMEM.
A Systematic Review of Integrated Learning Definitions, Frameworks, and Practices in Recent Health Professions Education Literature
Authors: Matinho Davina , Pietrandrea Marisa , Echeverria Carlos , Helderman Ron , Masters Madison , Regan Daniel , Shu Samuel , Moreno Rafael , McHugh Douglas
Published: March 2022

International curricular redevelopment and quality improvement efforts include integration within and across disciplines as a focal point. Definitions and applications of the term ‘integration’ vary routinely in health professions education literature, weakening opportunities to enhance our educational practice through collaborative, interprofessional knowledge-sharing. This systematic review examined recent health professions education literature for reported definitions, theories or frameworks, and educational activities around integrated learning, education, curricula, or teaching. A total of 35 articles representing learners from 12 different health professions, between 2017 and 2021, were analyzed through a literature search of seven databases: PubMed, Scopus, CINAHL, JSTOR, the Cochrane Library, LGBTQ + Life, and ERIC. Full-text retrieval and data extraction of the included studies were conducted. Of the 35 articles reviewed, 13 included explicit definitions of integration (an additional six alluded to a definition), 19 referred to an educational theory or framework used to guide integration design efforts, and 27 mentioned teaching methods by which integration was implemented. Misunderstanding what is meant by integrated, how others have planned for it, or how others have sought to bring it about practically, all threaten attempts to improve the cultivation of health professionals as integrated thinkers and holistic care providers.
A Dual-Armed Robotic Puncture System: Design, Implementation and Preliminary Tests
Authors: Gao Yongzhuo , Liu Xiaomin , Zhang Xu , Zhou Zhanfeng , Jiang Wenhe , Chen Lei , Liu Zheng , Wu Dongmei , Dong Wei
Published: March 2022

Traditional renal puncture surgery requires manual operation, which has a poor puncture effect, low surgical success rate, and high incidence of postoperative complications. Robot-assisted puncture surgery can effectively improve the accuracy of punctures, improve the success rate of surgery, and reduce the occurrence of postoperative complications. This paper provides a dual-armed robotic puncture scheme to assist surgeons. The system is divided into an ultrasound scanning arm and a puncture arm. Both robotic arms with a compliant positioning function and master–slave control function are designed, respectively, and the control system is achieved. The puncture arm’s position and posture are decoupled by the wrist RCM mechanism and the arm decoupling mechanism. According to the independent joint control principle, the compliant positioning function is realized based on the single-joint human–computer interactive admittance control. The simulation and tests verify its functions and performance. The differential motion incremental master–slave mapping strategy is used to realize the master–slave control function. The error feedback link is introduced to solve the cumulative error problem in the master–slave control. The dual-armed robotic puncture system prototype is established and animal tests verify the effectiveness.
Ensemble of Deep Convolutional Learning Classifier System Based on Genetic Algorithm for Database Intrusion Detection
Authors: Bu Seok-Jun , Kang Han-Bit , Cho Sung-Bae
Published: March 2022

Methods of applying deep learning to database protection have increased over the years. To secure role-based access control (RBAC) by learning the mapping function between query features and roles, it is known that the convolutional neural networks combined with learning classifier systems (LCS) can reach formidable accuracy. However, current methods are focused on using a singular model architecture and fail to fully exploit features that other models are capable of utilizing. Different deep architectures, such as ResNet and Inception, can exploit different spatial correlations within the feature space. In this paper, we propose an ensemble of multiple models with different deep convolutional architectures to improve the overall coverage of features used in role classification. By combining models with heterogeneous topologies, the ensemble-LCS model shows significantly increased performance compared to previous single architecture LCS models and achieves better robustness in the case of training data imbalance.
Interactive System for Package Delivery in Pedestrian Areas Using a Self-Developed Fleet of Autonomous Vehicles
Authors: Kocsis Mihai , Zöllner Raoul , Mogan Gheorghe
Published: March 2022

In the context of automation and digitalization technologies and due to the existing trends of re-urbanization, autonomous vehicles for execution of services such as package delivery, transportation, vegetation care and street cleaning are considered innovative solutions. This paper presents a concept and implementation of a system developed to plan and deliver packages within pedestrian areas, using autonomous vehicles. The novelty of the system lies in the systematic view of this use case, which considers all stakeholder views from the CEP (courier, express, and parcel services) provider, traffic participants, and customers and where the technical and technological innovation is guided by interactivity with the users. This work outlines the design and integration of user interaction, the developed vehicles within the fleet designed for operating within pedestrian environments, and localization and navigation strategies. After the vehicles were approved and certified from a technical point of view to operate in pedestrian areas, the entire system was tested and evaluated in a new city district of Heilbronn with approximately 800 inhabitants. In the last six weeks of experiments, 572 packages were delivered in an autonomous way. The interactive way of planning and executing services on demand led, according to a market study in Heilbronn, to an increased acceptance of the users for autonomous package delivery services from 76% to 91%.
Inductance Calculation of Single-Layer Planar Spiral Coil
Authors: Hussain Iftikhar , Woo Dong-Kyun
Published: March 2022

In this paper, an analytical calculation of the inductance of an air-core planar spiral coil is presented. The inner and outer radius of the planar spiral coil is determined from the general equation of the filament of the wire. Using the Neumann integral formula, the expression of inductance is obtained. The double integral of Neumann’s formula is computed numerically to evaluate the inductance. The accuracy of the calculation results is verified by comparing it with the conventional and the simulation results. Different geometry of spiral coils is fabricated to validate it experimentally. Finally, the comparison is performed with the experiment results, which show good agreement. Thus, the accuracy of the calculation result paves the way for designing and optimizing the spiral coil for electromagnetic applications.
Virtual Sensor Using a Super Twisting Algorithm Based Uniform Robust Exact Differentiator for Electric Vehicles
Authors: Muazzam Hassam , Ishak Mohamad Khairi , Hanif Athar , Uppal Ali Arshad , Bhatti AI , Isa Nor Ashidi Mat
Published: March 2022

The highly efficient Interior Permanent Magnet Synchronous Motor (IPMSM) is ubiquitous choice in Electric Vehicles (EVs) for today’s automotive industry. IPMSM control requires accurate knowledge of an immeasurable critical Permanent Magnet (PM) flux linkage parameter. The PM flux linkage is highly influenced by operating temperature which results in torque derating and hence power loss, unable to meet road loads and reduced life span of electrified powertrain in EVs. In this paper, novel virtual sensing scheme for estimating PM flux linkage through measured stator currents is designed for an IPMSM centric electrified powertrain. The proposed design is based on a Uniform Robust Exact Differentiator (URED) centric Super Twisting Algorithm (STA), which ensures robustness and finite-time convergence of the time derivative of the quadrature axis stator current of IPMSM. Moreover, URED is able to eliminate chattering without sacrificing robustness and precision. The proposed design detects variation in PM flux linkage due to change in operating temperature and hence is also able to establish characteristics of fault detection. The effectiveness and accuracy in different operating environments of the proposed scheme for nonlinear mathematical IPMSM model with complex EV dynamics are verified thorough extensive simulation experiments using MATLAB/Simulink.
Feasibility Study for Off-Grid Hybrid Power Systems Considering an Energy Efficiency Initiative for an Island in Ecuador
Authors: Hidalgo-Leon Ruben , Amoroso Fernando , Urquizo Javier , Villavicencio Viviana , Torres Miguel , Singh Pritpal , Soriano Guillermo
Published: March 2022

This paper shows the technical–economic, operational and environmental feasibility of four off-grid hybrid power systems to supply energy to the Cerrito de los Morreños community in Ecuador. These configurations consist of combinations of diesel generators, solar photovoltaic systems, and battery energy storage systems. Each configuration was simulated and the results were analyzed for two different load conditions: (1) the existing load profile and (2) a reduced load profile by incorporating an energy efficiency initiative. Homer Pro software was used to perform the simulations. The planning horizon for the simulations was selected to be 15 years. The results showed the diesel/photovoltaic/battery configuration with energy efficiency showed the best performance, which was achieved with a photovoltaic system of 160 kWp, the existing generator of 165 kW and a storage system of 283 kWh. The stand-alone diesel generator and photovoltaic/diesel configurations showed higher Net Present Costs, instability problems and higher CO2 emissions. Additionally, the configurations without energy efficiency had increases of between 15% and 40% higher costs compared to their respective energy-efficient scenarios. The information in this work could be useful for some organizations in Ecuador who are interested in investing in rural electrification projects with renewable energy to reduce and/or compensate their CO2 emissions.
Development and Characterization of Composite Desiccant Impregnated with LiCl for Thermoelectric Dehumidifier (TED)
Authors: Channoy Chanchira , Maneewan Somchai , Chirarattananon Surapong , Punlek Chantana
Published: March 2022

Aqueous salt solutions (LiCl) were impregnated into a porous host matrix to create composite desiccant materials (silica gel). The authors of this paper fabricated and analyzed composite desiccant-coated aluminum sheets (DCAS) with varying LiCl mass concentrations. Nitrogen sorption results revealed that the Brunauer–Emmett–Teller (BET) surface area and pore volume of the composite desiccant-coated aluminum sheets decreased. Furthermore, composite DCAS had lower nitrogen sorption than silica-gel-coated aluminum sheets (SGCAS). According to the results, the composite DCAS had the highest thermal conductivity, measuring 6.1 Wm−1 K−1, doubling that of the SGCAS. For evaluating sorption kinetics, the linear driving force model (LDF) was used, and composite DCAS showed greater dynamic sorption quantities and sorption rate coefficients than SGCAS. Furthermore, three different moisture sorption isotherm models were used to fit the experimental results: the Brunauer–Emmett–Teller (BET) model, the Guggenheim–Anderson–Boer (GAB) model, and the double log polynomial (DLP) model. The DLP model was shown to be the best model for predicting the moisture sorption isotherms of DCAS. Additionally, the composite desiccant-coated heat sink (DCHS) of the thermoelectric dehumidifier (TED) was evaluated and compared to silica gel in terms of dehumidification capacity. According to the findings, the outlet air humidity ratio of the composite DCHS reached a minimum of 10.23 g kg−1, and the dehumidification capacity was 0.117 kg h−1 when the input electrical voltage was kept at 9 V.
Heat Exchanging Grid Structures Based on Laser-Based Powder Bed Fusion: Formation Process and Boiling Heat Transfer Performance
Authors: Qian Bo , Fan Hongri , Zhang Jianrui , Liu Gang , Li Pei
Published: March 2022

Microchannel structures possess high efficiency and high boiling heat transfer coefficient of two-phase flow. In particular, the grid structure has the advantages of a simple pattern, large load capacity, and good surface adaptability. Employing the laser-based powder bed fusion (L-PBF) manufacturing technology, a new method of forming heat transfer grids with a controllable structure is proposed in this study. The formation principle, process, and the reasons for improvements in the boiling heat transfer performance were investigated with stainless steel materials. Laser scanning with varying scan spacings was used to prepare multiple structures with different grid widths and wall heights. On this basis, the porosity and pore morphology of the grid structures were analyzed, followed by pool boiling heat transfer experiments. The results revealed that the grid structure significantly affected the nucleate boiling behavior and increased the critical heat flux (CHF). It was found that the 0.5 mm sample exhibited optimum critical heat transfer performance, with an improvement of 10–27% compared to those of the other four samples (minimum of 63.3 W·cm−2 and maximum of 93.9 W·cm−2). In addition, for samples with a grid width greater than 0.5 mm, the boiling slightly decreased by <5%. When the grid width was further increased, the flow resistance effect and the bubble synapse generation effect tended to converge. In these cases, boiling heat transfer only occurred in a single phase along the direction of the medium wall thickness, thus failing to achieve two-phase heat transfer through bubble growth and collapse.
Comparison of Indoor Environment and Energy Consumption before and after Spread of COVID-19 in Schools in Japanese Cold-Climate Region
Authors: Mori Taro , Akamatsu Taisei , Kuwabara Kouhei , Hayashi Motoya
Published: March 2022

A report released by the WHO indicates that aerosols from infected people are one of the major sources of the spread of COVID-19. Therefore, as the COVID-19 infection caused by the SARS-CoV-2 virus spreads, it has become necessary to reconsider the design and operation of buildings. Inside school buildings in cold regions, not only is it not easy to increase ventilation during the winter, but it may also be difficult for students to attend classes while wearing masks during the summer because such buildings are not equipped with air-conditioning systems. In short, school buildings in cold climates have more problems than those in warm climates. We report on the results of indoor environmental measurement using our developed CO2-concentration meters, a questionnaire survey on students’ feeling of being hot or cold (i.e., ‘thermal sensation’), and a comparison of energy consumption before and after the spread of COVID-19 infection in schools in Sapporo, Japan, a cold-climate area. The results indicate that (1) more than 70% of the students participated in window ventilation by the CO2 meter, and (2) a relatively good indoor environment was maintained through the efforts of teachers and students. However, we also found that (1) 90% of the students felt hot in summer and (2) 40% felt cold in winter, (3) energy efficiency worsened by 7% due to increased ventilation, and (4) air quality was not as clean as desired during the coldest months of the year. Therefore, investment in insulation and air conditioning systems for school buildings is needed.
Numerical Investigation of the Application of Miller Cycle and Low-Carbon Fuels to Increase Diesel Engine Efficiency and Reduce Emissions
Authors: Roper Edward , Wang Yaodong , Zhang Zhichao
Published: March 2022

In this paper, validated simulations using Ricardo WAVE have been performed to investigate the effect of the Miller cycle and low-carbon fuels on the performance (power, torque, BTE and BSFC) and emissions of a diesel engine. The results show that the increased Miller cycle effect (larger deviation of the advanced or retarded intake valve closing from the standard intake valve closing time) will decrease NOx, CO and HC emissions, and slightly improve brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) with slight loss in engine performance and increase in soot emissions. An engine running B0 (diesel with 0% Biodiesel in the blend) with a −18% Miller cycle effect has a reduction in NOx of 9% and CO of 4.3% with a decrease of 1.6% in power at the rated engine speed. Using low carbon fuels drastically reduces emissions with reduced BTE and increased BSFC. When used in conjunction, the Miller cycle and low-carbon fuels have an improved effect on both performance and emissions. The optimal results demonstrate that using B60 (60% Biodiesel in the blend) and a −8% Miller effect contributes to a 1.5% improvement in power, 1.2% in BTE, 13.3% in NOx, 38.5% in CO, 8.9% in HC, and 33.0% in soot at a cost of 6.0% increase in BSFC. The results show that it is an easy way to reduce NOx, CO, HC and soot emissions and increase the BTE of the engine by combining Miller cycle and low-carbon fuels.
A Study on Frequency Stability and Primary Frequency Response of the Korean Electric Power System Considering the High Penetration of Wind Power
Authors: Lim SungHoon , Kim Taewan , Yoon Kipo , Choi DongHee , Park Jung-Wook
Published: March 2022

The high penetration of wind power decreases the system inertia and primary frequency reserve while replacing the conventional synchronous generators (SGs). Therefore, if the system operator does not take appropriate action on the remaining generation units (GUs) operation, high penetration of wind power will aggravate the frequency stability. To solve this problem, wind power plants (WPPs) may provide the inertial response and primary frequency response (PFR) to support the frequency stability. However, due to the variability of renewable energy, WPPs may not provide adequate frequency response whenever it is required. This paper proposes an algorithm to determine the operation of GUs to provide appropriate PFR for a power system with high penetration of wind power. Through the proposed algorithm, it calculates the required PFR to restore the decreased frequency stability caused by the high penetration of wind power. Then, while considering the available PFR from WPPs, it redetermines the droop coefficient of SGs governor to provide the sufficient PFR to recover the frequency stability. Finally, the effectiveness of the proposed algorithm is verified on the practical Korean electric power system.
Piloted Simulation of the Rotorcraft Wind Turbine Wake Interaction during Hover and Transit Flights
Authors: Štrbac Alexander , Greiwe Daniel Heinrich , Hoffmann Frauke , Cormier Marion , Lutz Thorsten
Published: March 2022

Helicopters are used for offshore wind farms for maintenance and support flights. The number of helicopter operations is increasing with the expansion of offshore wind energy, which stresses the point that the current German regulations have not yet been validated through scientific analysis. A collaborative research project between DLR, the Technical University of Munich, the University of Stuttgart and the University of Tübingen has been conducted to examine the sizes of the flight corridors on offshore wind farms and the lateral safety clearance for helicopter hoist operations at offshore wind turbines. This paper details the results of piloted helicopter simulations in a realistic offshore wind farm scenario. The far-wake of rotating wind turbines and the near-wake of non-rotating wind turbines have been simulated with high-fidelity computational fluid dynamics under realistic turbulent inflow conditions. The resulting flow fields have been processed by superposition during piloted simulations in the research flight simulator AVES to examine the flight corridors in transit flights and the lateral safety clearance in hovering flights. The results suggest a sufficient size for the flight corridor and sufficient lateral safety clearance at the offshore wind turbines in the considered scenarios.
Key Areas of Gas Hydrates Study: Review
Authors: Gaidukova Olga , Misyura Sergei , Strizhak Pavel
Published: March 2022

Gas hydrates are widespread all over the world. They feature high energy density and are a clean energy source of great potential. The paper considers experimental and theoretical studies on gas hydrates in the following key areas: formation and dissociation, extraction and transportation technologies of natural methane hydrates, and ignition, and combustion. We identified a lack of research in more areas and defined prospects of further development of gas hydrates as a promising strategic resource. One of the immediate problems is that there are no research findings for the effect of sediments and their matrices on hydrate saturation, as well as on gas hydrate formation and dissociation rates. No mathematical models describe the dissociation of gas hydrates under various conditions. There is a lack of research into the renewal and improvement of existing technologies for the easier and cheaper production of gas hydrates and the extraction of natural gas from them. There are no models of gas hydrate ignition taking into account dissociation processes and the self-preservation effect.
Numerical Analysis of Wick-Type Two-Phase Mechanically Pumped Fluid Loop for Thermal Control of Electric Aircraft Motors
Authors: Chang Xinyu , Fujita Koji , Nagai Hiroki
Published: March 2022

The development of thermal control systems has become an important issue in next-generation electric aircraft design due to the increase in heat exhausted with electrification. In this paper, a wick-type two-phase mechanically pumped fluid loop system for future electric aircraft was proposed through the investigation of current two-phase flow cooling technology. Taking the experimental electric aircraft X-57 as an example, a wick-type two-phase mechanically pumped fluid loop with four evaporators for transporting 12 kW of waste heat within an 80 °C temperature limit was proposed and its feasibility was confirmed. A numerical model was constructed and validated to predict the operating characteristics of a two-phase mechanically pumped fluid loop. The optimal pump outputs under-even and uneven heat load conditions and was investigated for the first time by considering the vapor-liquid separation conditions in each flow path and the power consumption of the pump. Under the optimal pump output condition, the operating characteristics of the wick-type two-phase mechanically pumped fluid loop system were calculated. The calculation results indicate that the proposed wick-type two-phase mechanically pumped fluid loop is suitable as the thermal control system for an X-57 electric aircraft motor, as the calculation results satisfied the operational requirements of the motor.
Building Integrated Photovoltaics—The Journey So Far and Future
Authors: Awuku Samuel Amo , Muhammad-Sukki Firdaus , Sellami Nazmi
Published: March 2022

The road to decarbonization has led to the exploration of sustainable energy sources for domestic and industrial use [...]
PF2RM: A Power Fault Retrieval and Recommendation Model Based on Knowledge Graph
Authors: Liang Kun , Zhou Baoxian , Zhang Yiying , Li Yiping , Zhang Bo , Zhang Xiankun
Published: March 2022

Energy saving and emission reduction have become common concerns in countries around the world. In China, with the implementation of the new strategy of “carbon peak and neutrality” and the rapid development of the new smart grid infrastructure, the amount of data of actual power grid dispatching and fault analysis show exponential growth, which has led to phenomena such as poor supervision effectiveness and difficulty in handling faults in the process of grid operation and maintenance. Existing research on retrieval recommendation methods has had a lower accuracy rate at cold-start due to a small sample of user interactions. In addition, the cumulative learning of user personalization during general retrieval results in a poor perception of potential interest. By constructing a power knowledge graph, this paper presents a power fault retrieval and recommendation model (PF2RM) based on user-polymorphic perception. This model includes two methods: the power fault retrieval method (PFR) and the user-polymorphic retrieval recommendation method (UPRR). First, we take the power grid fault dispatching business as the core and reconstruct the ontology layer of the power knowledge graph. The PFR method is used to design the graph-neighbor fault entity cluster to enhance the polymerization degree of a fault implementation scenario. This method can solve the search cold-start recommendation problem. At the same time, the UPRR method aims to form user retrieval subgraphs of the past-state and current-state and make a feature matching for the graph-neighbor fault entity cluster, and then realize the accurate prediction of the user’s general search intention. The model is compared with other current classical models through the evaluation of multiple recommendation evaluation metrics, and the experimental results show that the model has a 3–8% improvement in the cold-start recommendation effect and 2–10% improvement in regular retrieval. The model has the best average recommendation performance in multiple metrics and has good results in fault analysis and retrieval recommendation. It plays a helpful role in intelligent operation and maintenance of the power grid and auxiliary decision-making, and effectively improves the reliability of the power grid.
Using Deep Learning in Real-Time for Clothing Classification with Connected Thermostats
Authors: Medina Adán , Méndez Juana Isabel , Ponce Pedro , Peffer Therese , Meier Alan , Molina Arturo
Published: March 2022

Thermal comfort is associated with clothing insulation, conveying a level of satisfaction with the thermal surroundings. Besides, clothing insulation is commonly associated with indoor thermal comfort. However, clothing classification in smart homes might save energy when the end-user wears appropriate clothes to save energy and obtain thermal comfort. Furthermore, object detection and classification through Convolutional Neural Networks has increased over the last decade. There are real-time clothing garment classifiers, but these are oriented towards single garment recognition for texture, fabric, shape, or style. Consequently, this paper proposes a CNN model classification for the implementation of these classifiers on cameras. First, the Fashion MNIST was analyzed and compared with the VGG16, Inceptionvv4, TinyYOLOv3, and ResNet18 classification algorithms to determine the best clo classifier. Then, for real-time analysis, a new dataset with 12,000 images was created and analyzed with the YOLOv3 and TinyYOLO. Finally, an Azure Kinect DT was employed to analyze the clo value in real-time. Moreover, real-time analysis can be employed with any other webcam. The model recognizes at least three garments of a clothing ensemble, proving that it identifies more than a single clothing garment. Besides, the model has at least 90% accuracy in the test dataset, ensuring that it can be generalized and is not overfitting.
Facile Route for Fabrication of Ferrimagnetic Mn3O4 Spinel Material for Supercapacitors with Enhanced Capacitance
Authors: Yang Wenjuan , Nawwar Mohamed , Zhitomirsky Igor
Published: March 2022

The purpose of this investigation was the development of a new colloidal route for the fabrication of Mn3O4 electrodes for supercapacitors with enhanced charge storage performance. Mn3O4-carbon nanotube electrodes were fabricated with record-high capacitances of 6.67 F cm−2 obtained from cyclic voltammetry tests at a scan rate of 2 mV s−1 and 7.55 F cm−2 obtained from the galvanostatic charge–discharge tests at a current density of 3 mA cm−2 in 0.5 M Na2SO4 electrolyte in a potential window of 0.9 V. The approach involves the use of murexide as a capping agent for the synthesis of Mn3O4 and a co-dispersant for Mn3O4 and carbon nanotubes. Good electrochemical performance of the electrode material was achieved at a high active mass loading of 40 mg cm−2 and was linked to a reduced agglomeration of Mn3O4 nanoparticles and efficient co-dispersion of Mn3O4 with carbon nanotubes. The mechanisms of murexide adsorption on Mn3O4 and carbon nanotube are discussed. With the proposed method, the time-consuming electrode activation procedure for Mn3O4 electrodes can be avoided. The approach developed in this investigation paves the way for the fabrication of advanced cathodes for asymmetric supercapacitors and multifunctional devices, combining capacitive, magnetic, and other functional properties.
Overview of the M-Cycle Technology for Air Conditioning and Cooling Applications
Authors: Taler Jan , Jagieła Bartosz , Jaremkiewicz Magdalena
Published: March 2022

The indirect evaporative cooler (IEC) has excellent potential to replace or improve conventional vapor compression equipment in HVAC and refrigeration applications. This could be achieved by using the M-cycle (dew-point evaporative cooling technology). This thermodynamic concept makes it possible to derive a large amount of energy from the air stream (as latent heat released during water evaporation into the working air stream) and use it for another air stream (product). Its application has also spread to other sectors, such as water desalination and distillation, power plants, or NOx reduction. This paper provides an overview of the M-cycle mainly in air conditioning (MAC, D-MAC, H-MAC) and refrigeration (MCT, M-condenser). Various integrated solutions are described, showing improved effectiveness in terms of the wet-bulb temperature and the dew point. The design features of consolidated solutions are better In terms of the flow distribution, geometry, or volume. Most of the improvements confirm the great potential of the M-cycle to increase the unit or the system efficiency due to lower energy and water consumption.