bluuebunny/crossref_metadata_2025 huggingface dataset:
The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes—The Value of Regulatory Frameworks
Authors: Medenica Sanja , Zivanovic Dusan , Batkoska Ljubica , Marinelli Susanna , Basile Giuseppe , Perino Antonio , Cucinella Gaspare , Gullo Giuseppe , Zaami Simona
Published: November 2022

Infertility is a global health issue affecting women and men of reproductive age with increasing incidence worldwide, in part due to greater awareness and better diagnosis. Assisted reproduction technologies (ART) are considered the ultimate step in the treatment of infertility. Recently, artificial intelligence (AI) has been progressively used in the many fields of medicine, integrating knowledge and computer science through machine learning algorithms. AI has the potential to improve infertility diagnosis and ART outcomes estimated as pregnancy and/or live birth rate, especially with recurrent ART failure. A broad-ranging review has been conducted, focusing on clinical AI applications up until September 2022, which could be estimated in terms of possible applications, such as ultrasound monitoring of folliculogenesis, endometrial receptivity, embryo selection based on quality and viability, and prediction of post implantation embryo development, in order to eliminate potential contributing risk factors. Oocyte morphology assessment is highly relevant in terms of successful fertilization rate, as well as during oocyte freezing for fertility preservation, and substantially valuable in oocyte donation cycles. AI has great implications in the assessment of male infertility, with computerised semen analysis systems already in use and a broad spectrum of possible AI-based applications in environmental and lifestyle evaluation to predict semen quality. In addition, considerable progress has been made in terms of harnessing AI in cases of idiopathic infertility, to improve the stratification of infertile/fertile couples based on their biological and clinical signatures. With AI as a very powerful tool of the future, our review is meant to summarise current AI applications and investigations in contemporary reproduction medicine, mainly focusing on the nonsurgical aspects of it; in addition, the authors have briefly explored the frames of reference and guiding principles for the definition and implementation of legal, regulatory, and ethical standards for AI in healthcare.
Parallel Multiobjective Multiverse Optimizer for Path Planning of Unmanned Aerial Vehicles in a Dynamic Environment with Moving Obstacles
Authors: Jarray Raja , Bouallègue Soufiene , Rezk Hegazy , Al-Dhaifallah Mujahed
Published: November 2022

Path planning with collision avoidance for unmanned aerial vehicles (UAVs) in environments with moving obstacles is a complex process of navigation, often considered a hard optimization problem. Ordinary resolution algorithms may fail to provide flyable and collision-free paths under the time-consumption constraints required by the dynamic 3D environment. In this paper, a new parallel multiobjective multiverse optimizer (PMOMVO) is proposed and successfully applied to deal with the increased computation time of the UAV path planning problem in dynamic 3D environments. Collision constraints with moving obstacles and narrow pass zones were established based on a mathematical characterization of any intersection with lines connecting two consecutive drones’ positions. For the implementation, a multicore central processing unit (CPU) architecture was proposed according to the concept of master–slave processing parallelization. Each subswarm of the entire PMOMVO population was granted to a corresponding slave, and representative solutions were selected and shared with the master core. Slaves sent their local Pareto fronts to the CPU core representing the master that merged the received set of nondominated solutions and built a global Pareto front. Demonstrative results and nonparametric ANOVA statistical analyses were carried out to show the effectiveness and superiority of the proposed PMOMVO algorithm compared to other homologous, multiobjective metaheuristics.
Explanatory Change Detection in Financial Markets by Graph-Based Entropy and Inter-Domain Linkage
Authors: Nishikawa Yosuke , Yoshino Takaaki , Sugie Toshiaki , Nakata Yoshiyuki , Itou Kakeru , Ohsawa Yukio
Published: November 2022

In this study, we analyzed structural changes in financial markets under COVID-19 to support investors’ investment decisions. Because an explanation of these changes is necessary to respond appropriately to said changes and prepare for similar major changes in the future, we visualized the financial market as a graph. The hypothesis was based on expertise in the financial market, and the graph was analyzed from a detailed perspective by dividing the graph into domains. We also designed an original change-detection indicator based on the structure of the graph. The results showed that the original indicator was more effective than the comparison method in terms of both the speed of response and accuracy. Explanatory change detection of this method using graphs and domains allowed investors to consider specific strategies.
Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations
Authors: Machmudah Affiani , Lemma Tamiru Alemu , Solihin Mahmud Iwan , Feriadi Yusron , Rajabi Armin , Afandi Mohamad Imam , Abbasi Aijaz
Published: November 2022

This paper addresses a design optimization of a gas turbine (GT) for marine applications. A gain-scheduling method incorporating a meta-heuristic optimization is proposed to optimize a thermodynamics-based model of a small GT engine. A comprehensive control system consisting of a proportional integral (PI) controller with additional proportional gains, gain scheduling, and a min-max controller is developed. The modeling of gains as a function of plant variables is presented. Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. The results show that the WOA has better performance than that of the GA, where the WOA exhibits the minimum fitness value. Compared to the unoptimized gain, the time to reach the target of the power lever angle is significantly reduced. Optimal gain scheduling shows a stable response compared with a fixed gain, which can have oscillation effects as a controller responds. An effect of using bioethanol as a fuel has been observed. It shows that for the same input parameters of the GT dynamics model, the fuel flow increases significantly, as compared with diesel fuel, because of its low bioethanol heating value. Thus, a significant increase occurs only at the gain that depends on the fuel flow.
Extended Divergence on a Foliation by Deformed Probability Simplexes
Authors: Uohashi Keiko
Published: November 2022

This study considers a new decomposition of an extended divergence on a foliation by deformed probability simplexes from the information geometry perspective. In particular, we treat the case where each deformed probability simplex corresponds to a set of q-escort distributions. For the foliation, different q-parameters and the corresponding α-parameters of dualistic structures are defined on each of the various leaves. We propose the divergence decomposition theorem that guides the proximity of q-escort distributions with different q-parameters and compare the new theorem to the previous theorem of the standard divergence on a Hessian manifold with a fixed α-parameter.
Water Regulating in Kenozero Taiga: Excess or Lack of Water and Where Does It Go?
Authors: Petrov Leonid , Bukvareva Elena , Aleinikov Alexey
Published: November 2022

Water-regulating ecosystem services (ESs) are a key factor in water supply for the population and the economy. In recent years, these ESs have been intensively included in regional and global assessments. However, the degree of knowledge of various water-regulating ESs and the availability of models for their estimation and mapping vary greatly. For example, most regional assessments currently do not take into account the ESs of moisture and precipitation recycling by forests which can lead to erroneous decisions on land use and forest management. To what extent is it possible to make adequate decisions on the basis of a partial assessment of the ESs? In this article, we discuss this problem using the example of boreal forests in the catchment of the Lake Kenozero in the north of the European part of Russia. Using the InVEST model, two ESs were quantified and mapped: water yield regulation due to evapotranspiration and water quality assurance due to prevention of soil erosion. The reduction in water yield due to evapotranspiration was estimated at 125 mm/year, and the prevention of soil erosion was estimated at 9.56 t/ha/year. Forest felling in the study area from 2007 to 2021 led to an increase in runoff and soil erosion by 6 mm/year and 0.03 t/ha/year, respectively. The hypothetical total instantaneous forest loss could lead to an increase in runoff and soil erosion by 71 mm/year and 2.44 t/ha/year, respectively. A tradeoff between these ESs was predictably identified as deforestation led to an increase in water yield and a deterioration in water quality due to soil erosion. The significance of a number of other water-regulating ESs for making regional decisions was expertly assessed. In particular, the importance of the ESs of precipitation recycling of sludge under climate change was discussed. Expanding the range of ESs under consideration increases the likelihood of choosing a protection strategy instead of a harvesting one in forest management.
Incorporating Microbial Species Interaction in Management of Freshwater Toxic Cyanobacteria: A Systems Science Challenge
Authors: Banerji Aabir , Benesh Kasey
Published: November 2022

Water resources are critically important, but also pose risks of exposure to toxic and pathogenic microbes. Increasingly, a concern is toxic cyanobacteria, which have been linked to the death and disease of humans, domesticated animals, and wildlife in freshwater systems worldwide. Management approaches successful at reducing cyanobacterial abundance and toxin production have tended to be short-term solutions applied on small scales (e.g., algaecide application) or solutions that entail difficult multifaceted investments (e.g., modification of landscape and land use to reduce nutrient inputs). However, implementation of these approaches can be undermined by microbial species interactions that (a) provide toxic cyanobacteria with protection against the method of control or (b) permit toxic cyanobacteria to be replaced by other significant microbial threats. Understanding these interactions is necessary to avoid such scenarios and can provide a framework for novel strategies to enhance freshwater resource management via systems science (e.g., pairing existing physical and chemical approaches against cyanobacteria with ecological strategies such as manipulation of natural enemies, targeting of facilitators, and reduction of benthic occupancy and recruitment). Here, we review pertinent examples of the interactions and highlight potential applications of what is known.
Actor Fluidity and Knowledge Persistence in Regional Inventor Networks
Authors: Fritsch Michael , Zoellner Moritz
Published: November 2022

The development of inventor networks is characterized by the addition of a significant number of new inventors, while a considerable number of incumbent inventors discontinue. We estimated the persistence of knowledge in the inventor networks of nine German regions using alternative assumptions about knowledge transfer. Based on these estimates, we analyzed how the size and structure of a network may influence knowledge persistence over time. In a final step, we assessed how persistent knowledge as well as the knowledge of new inventors affect the performance of regional innovation systems (RIS). The results suggest that the knowledge of new inventors is much more important for RIS performance than old knowledge that persists.
The Impacts of Geopolitical Risks on the Energy Sector: Micro-Level Operative Analysis in the European Union
Authors: Figueiredo Ronnie , Soliman Mohammad , Al-Alawi Alamir N. , Sousa Maria José
Published: November 2022

Energy prices play a crucial role in combating geopolitical risks, especially for the major suppliers of energy resources. However, energy prices display a bilateral relationship with geopolitical risks in any economy. Any hike in the price of energy stimulates geopolitical risk factors and visa-versa. The consequences adversely impact economies and bring forth international tensions. This paper bridges a gap between the influence of geopolitical risks relating to energy and international tensions by analyzing micro-level operational measures. We deploy an empirical model to predict the energy sector and possible risk factors incorporating Eurostat data on twenty-seven states, from 2011 to 2020. This study collected a different energy variable to support the multiple regression model constructed by the “blocks” (hierarchical linear regression) method. The results suggest that geopolitical risks cause adverse effects on both the energy and other corporate sectors. The future direction of this research is to estimate how statistical model relationships may assist the corporate sector, and investors, in adopting mitigating measures to control upcoming geopolitical risks due to energy risks caused by geopolitical unrest.
Teaching Is a Story Whose First Page Matters—Teacher Counselling as Part of Teacher Growth
Authors: Piispanen Maarika , Meriläinen Merja
Published: November 2022

The starting point of the study is the work counselling process taking place in the induction phase of the students’ teaching career. The work counselling process consists of activities that support and strengthen the students’ teacher hood and their primary function as teachers by helping them to analyse their work and to attach to working life as newly graduated teachers. In this study, we use contextualisation and storytelling in the frameworks of positive pedagogy and systems theory to reflect on the students’ growth process as teachers. We also acknowledge the importance of Vygotsky’s zone of proximal development and, related to that, timely learning support (scaffolding) and a solution-focused approach as part of the supervision process utilising the methods of work counselling. In this study, autoethnography was used as a tool to help us reflect on our actions and work. Methods were chosen based on the thought that in the induction period, the students’ experiences function as mirrors for us supervisors, helping us to reflect on our actions and the supervision process and to form ideas and meanings based on the documented discourse data.
Effect of Peer Influence and Self-Reflection on Scaffolded Out-of-Class Activity Administered Using a Mobile Application
Authors: Fuad Muztaba , Akbar Monika
Published: November 2022

Student engagement with out-of-class activities is becoming more difficult as students spend fewer hours outside the classroom studying the content. This research developed a mobile educational platform, Dysgu, to provide students with an optimal learning experience outside of the classroom. Dysgu includes social networking and gamification features to increase student engagement. The platform offers interactive auto-graded assessments to help students practice concepts and take tests. Students can see their scores and a summary of the performance of the rest of the class. We used Dysgu for multiple out-of-class activities at two universities with different student demographics for two semesters. The data shows that students obtain better grades when using Dysgu. We also saw more on-time or ahead-of-time submissions with Dysgu. Survey responses indicated several Dysgu features which students found helpful. We conclude that digital educational platforms should consider features to support scaffolding to master the concept, peer influence to keep students engaged, self-reflection to foster critical thinking, and easy adaption of the platform to reduce faculty workload and improve students’ acceptance of the system.
Inquiry in a Science Museum: Science Museum Educators’ Views and Practices
Authors: Karnezou Maria , Kariotoglou Petros
Published: November 2022

Our study looks into science museum educators’ views and their practices about inquiry in non-formal venues, such as NOESIS, Greece. On this ground, we developed an interview protocol to use as a basis in the semi-structured interviews conducted with four science museum educators to cast light on their views about inquiry. In addition, an observation protocol was modified in order to observe their practices when implementing educational programs for school groups. Data analysis showed that in regard to the museum educators’ views, they all expressed a slightly different view about inquiry, which was either empirically or intuitively based. They all agreed that inquiry is easier adopted in non-formal settings and argued that students’ main gain when they get engaged in inquiry-based activities is the actual involvement they experience. As regards the museum educators’ practices, a repertoire of teaching approaches was observed, ranging from a traditional teacher-centered approach to open inquiry. Building on our data, we suggest the development and implementation of a professional development course that will enrich science museum educators’ inquiry views and practices and empower them to integrate inquiry-based practices into their own.
The Influence of Problem Construction on Undergraduates’ Success with Stoichiometry Problems
Authors: Gulacar Ozcan , Mann Harjeet Kaur , Mann Sukhdev Singh , Vernoy Brandon James
Published: November 2022

Although there are numerous studies that aim to reveal the source of student failure in problem solving in STEM fields, there is a lack of attention on testing different methods to identify what works best in improving students’ problem-solving performance. In this study, the authors examined the influence of the type of problem construction intervention and compared it to the effect of traditional practice on 38 general chemistry students’ comprehension of problem-solving process as well as overall success with given stoichiometric problems. To determine students’ success with each subtopic involved in stoichiometric problems and to better understand the source of difficulty at a finer level rather than focusing on the end product as practiced in most studies, students’ solutions were examined using the COSINE (Coding System for Investigating Sub-problems and Network) method. The findings revealed that students who practiced the problem-construction method outperformed their counterparts in the control group who followed a traditional approach during their study session. An in-depth analysis also showed that the experimental group improved their success with seven out of nine subtopics while three topics observed an increase in the control group. The practical implication of the problem-construction method was discussed for a wider adoption by textbook publishers and educators across different disciplines.
A Novel MQTT 5.0-Based Over-the-Air Updating Architecture Facilitating Stronger Security
Authors: Chien Hung-Yu , Wang Nian-Zu
Published: November 2022

Over-the-air (OTA) updating is a critical mechanism for secure internet of things (IoT) systems for remotely updating the firmware (or keys) of IoT devices. Message queue telemetry transport (MQTT) is a very popular internet of things (IoT) communication protocol globally. Therefore, MQTT also becomes popular in facilitating the OTA mechanism in many IoT platforms, such as the Amazon IoT platform. In these IoT platforms, the MQTT broker acts as the message broker and as an OTA server simultaneously; in these broker-based OTA architectures, it is quite common that an IoT application manager not only uploads the new firmware/software to the broker but also delegates his signing authority on the firmware/software to the same broker. If the broker is secure and trusted, this OTA model works well; however, it incurs lots of security concerns if the broker is not fully trusted or if it is curious. Many MQTT deployments do not own their own brokers, but rely on a third-party broker, which sometimes is a freeware program or is maintained by a curious third party. Therefore, a secure OTA process should protect privacy against these brokers. This paper designs a novel MQTT-based OTA model in which an IoT application manager can fully control the OTA process through an end-to-end (E2E) channel. We design the model using MQTT 5.0’s new features and functions. The analysis shows that the new model greatly enhances security and privacy properties while maintaining high efficiency.
Emergency Mechanical Ventilator Design: Low-Cost and Accessible Components
Authors: Flor Omar , Fuentes Mauricio , Carvajal Henry , Quiroga Josué , Luzuriaga Verónica , Tapia Jeysson , Acosta-Vargas Patricia
Published: November 2022

This paper presents the fundamentals; criteria; and mechanical, electrical, and electronic aspects required to properly operate and control emerging mechanical ventilators. We present the basis for their design and manufacture as a contribution to implementing this type of equipment at low cost for intensive care units. In particular, we describe the materials and the mechanical, electrical, and electronic aspects used to implement the SURKAN mechanical ventilator, which was developed in Ecuador during the COVID-19 pandemic for some health centers in the country. The proposed mechanical ventilator provides a functional and reliable design that can be considered a reference for future developments and new implementations.
k-Level Extended Sparse Array Design for Direction-of-Arrival Estimation
Authors: Zhao Pinjiao , Wu Qisong , Wu Na , Hu Guobing , Wang Liwei
Published: November 2022

Sparse arrays based on the concept of a sum-difference coarray (SDCA) have increased degrees of freedom and enlarged effective array aperture compared to those only considering a difference coarray. Nevertheless, there still exist a number of overlapping virtual sensors between the difference coarray and the sum coarray, yielding high coarray redundancy. In this paper, we propose a k-level extended sparse array configuration consisting of one sparse subarray with k-level expansion and one uniform linear subarray. By systematically analyzing the inherent structure of the k-level extended sparse array, the closed-form expressions for sensor locations, uniform DOF and coarray redundancy ratio (CARR) are derived. Moreover, with the utilization of a k-level extended strategy, the proposed array remains a hole-free property and achieves low coarray redundancy. According to the proposed sparse array, the spatial and temporal information of the incident sources are jointly exploited for underdetermined direction-of-arrival estimation. The theoretical propositions are proven and numerical simulations are performed to demonstrate the superior performance of the proposed array.
Control Synchronization Design of a Multiple Electrohydraulic Actuator System with Linearization Dynamics and an External Disturbance Observer
Authors: Qi Jun , Guo Qing , Ren Hualong , Chen Zhenlei , Yan Yao , Jiang Dan
Published: November 2022

The control synchronization of multiple electrohydraulic actuators (MEHAs) is initially discussed to ensure the consensus of every electrohydraulic actuator (EHA) with three-order isomorphic dynamics. First, the EHA model is linearized using the Lie derivative method to obtain the state-space model of MEHAs. Then, the disturbance observer is used to estimate and compensate for the unknown external load caused by the driving force of a motion plant. Via the Lyapunov technique, this protocol asymptotically achieves consensus to a zero neighborhood with the ultimate boundaries of the MEHAs’ state errors. The effectiveness of the synchronous control protocol is verified by both simulation and experimental benches with two-node EHAs.
A Real-Time Maximum Efficiency Tracker for Wireless Power Transfer Systems with Cross-Coupling
Authors: Laha Arpan , Kalathy Abirami , Pahlevani Majid , Jain Praveen
Published: November 2022

This article proposes a real-time dynamic maximum efficiency tracking algorithm for wireless power transfer (WPT) systems with multiple receivers. The algorithm sequentially varies the net reactance of each of the receivers using switched capacitor circuits (SCCs) to reach the maximum efficiency point (MEP). The MEP in multiple-receiver systems varies in the presence of cross-coupling. This article provides an in-depth analysis of the effects of cross-coupling and proves that cross-coupling could be beneficial or detrimental to efficiency, depending on circuit conditions such as the load resistances and coupling factors among the coils. Hence, unlike previous research, this article emphasizes the improvement of the link efficiency in the presence of cross-coupling rather than the complete elimination of its effects. Experimental results have been included for a single-transmitter and two-receiver system to validate the feasibility of the proposed algorithm.
Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
Authors: Gupta Neha , Gupta Kamali , Qahtani Abdulrahman M. , Gupta Deepali , Alharithi Fahd S. , Singh Aman , Goyal Nitin
Published: November 2022

The demand for digitization has inspired organizations to move towards cloud computing, which has increased the challenge for cloud service providers to provide quality service. One of the challenges is energy consumption, which can shoot up the cost of using computing resources and has raised the carbon footprint in the atmosphere; therefore, it is an issue that it is imperative to address. Virtualization, bin-packing, and live VM migration techniques are the key resolvers that have been found to be efficacious in presenting sound solutions. Thus, in this paper, a new live VM migration algorithm, live migration with efficient ballooning (LMEB), is proposed; LMEB focuses on decreasing the size of the data that need to be shifted from the source to the destination server so that the total energy consumption of migration can be reduced. A simulation was performed with a specific configuration of virtual machines and servers, and the results proved that the proposed algorithm could trim down energy usage by 18%, migration time by 20%, and downtime by 20% in comparison with the existing approach of live migration with ballooning (LMB).
Speech Emotion Recognition Based on Parallel CNN-Attention Networks with Multi-Fold Data Augmentation
Authors: Bautista John Lorenzo , Lee Yun Kyung , Shin Hyun Soon
Published: November 2022

In this paper, an automatic speech emotion recognition (SER) task of classifying eight different emotions was experimented using parallel based networks trained using the Ryeson Audio-Visual Dataset of Speech and Song (RAVDESS) dataset. A combination of a CNN-based network and attention-based networks, running in parallel, was used to model both spatial features and temporal feature representations. Multiple Augmentation techniques using Additive White Gaussian Noise (AWGN), SpecAugment, Room Impulse Response (RIR), and Tanh Distortion techniques were used to augment the training data to further generalize the model representation. Raw audio data were transformed into Mel-Spectrograms as the model’s input. Using CNN’s proven capability in image classification and spatial feature representations, the spectrograms were treated as an image with the height and width represented by the spectrogram’s time and frequency scales. Temporal feature representations were represented by attention-based models Transformer, and BLSTM-Attention modules. Proposed architectures of the parallel CNN-based networks running along with Transformer and BLSTM-Attention modules were compared with standalone CNN architectures and attention-based networks, as well as with hybrid architectures with CNN layers wrapped in time-distributed wrappers stacked on attention-based networks. In these experiments, the highest accuracy of 89.33% for a Parallel CNN-Transformer network and 85.67% for a Parallel CNN-BLSTM-Attention Network were achieved on a 10% hold-out test set from the dataset. These networks showed promising results based on their accuracies, while keeping significantly less training parameters compared with non-parallel hybrid models.
Improved Thermal Performance of a Serpentine Cooling Channel by Topology Optimization Infilled with Triply Periodic Minimal Surfaces
Authors: Yeranee Kirttayoth , Rao Yu , Yang Li , Li Hao
Published: November 2022

The present study utilizes a density-based topology optimization method to design a serpentine channel under turbulent flow, solving a high pressure loss issue and enhancing heat transfer capability. In the topology optimization, the k–ε turbulence model is modified by adding penalization terms to reveal turbulence effects. Heat transfer modeling is included by setting the modified energy equation with additional terms related to topology optimization. The main objective is to minimize pressure loss while restricting heat transfer. The 2D simplified model is topologically optimized. Then, the optimal solution with intermediate results is extruded in the 3D system and interpreted with triply periodic minimal surfaces (TPMS) to further enhance heat transfer performance. Compared to the baseline serpentine channel, the optimized model infilled with the diamond-TPMS structure lowers pressure loss by 30.8% and significantly enhances total heat transfer by up to 45.8%, yielding thermal performance of 64.8% superior to the baseline. The temperature uniformity is also improved. The simulation results show that the curvatures in the optimized model with diamond-TPMS structure eliminate the large recirculation flow and low heat transfer regions. This model diminishes the effect of Dean’s vortices but promotes high turbulent kinetic energy, leading to better uniform flow and heat transfer distributions.
Optimization of Energy Production from Two-Stage Mesophilic–Thermophilic Anaerobic Digestion of Cheese Whey Using a Response Surface Methodology Approach
Authors: Kovalev Andrey A. , Mikheeva Elza R. , Panchenko Vladimir , Katraeva Inna V. , Kovalev Dmitriy A. , Zhuravleva Elena A. , Litti Yuriy V.
Published: November 2022

Spatial separation into acidogenic and methanogenic stages is considered a viable option to ensure process stability, energy efficiency and the better control of key anaerobic digestion (AD) parameters. The elucidation of the optimal modes of two-stage AD for the maximization of the recovery of biofuels (H2 and CH4) is still an urgent task, the main optimization criteria being the highest energy yield (EY) and energy production rate (EPR). In this work, a response surface methodology was used for an optimization of energy production from the two-stage mesophilic–thermophilic AD of cheese whey (CW). Three dilution rates of CW, providing values of 10.9, 14.53 and 21.8 g for the chemical oxygen demand (COD)/L in the influent and three hydraulic retention times (HRTs) (1, 2 and 3 days) in methanogenic biofilters at a constant HRT in an acidogenic biofilter of 0.42 days, were tested to optimize the EY and EPR. The desirability approach produced combined optimum conditions as follows: the dilution rate of the CW provided 17.58 g COD/L (corresponding to OLR of 6.5 g COD/(L·day)) in the influent and a HRT in the methanogenic biofilter of 2.28 days, both of which provided a maximum EPR of 80.263 kJ/(L·day) and EY of 9.56 kJ/g COD, with an overall desirability value of 0.883.
Performance Comparison of CSTR and CSFBR in Anaerobic Co-Digestion of Food Waste with Grease Trap Waste
Authors: Hu Yong , Ma Haiyuan , Wu Jiang , Kobayashi Takuro , Xu Kai-Qin
Published: November 2022

In this study, a newly established bench-scale thermophilic continuously stirred fluidized bed reactor (CSFBR) was applied for anaerobic co-digestion of food waste (FW) with grease trap waste (GTW). The performance of CSFBR regarding stability and treatment efficiency was inspected through a laboratory contrast experiment with two traditional continuous stirred tank reactors (CSTRs). In the OLR range of 3.19–7.41 g COD/L/d, the methane production rate of the thermophilic CSFBR was about as high as that of the thermophilic CSTR. Nevertheless, the thermophilic CSFBR had much lower VFAs (<1000 mg/L) and LCFA concentrations (<100 mg/L) as compared with the thermophilic CSTR. Unlike the mesophilic CSTR, there was no foaming that occurred in the CSFBR during the whole experimental period. The results all suggested that CSFBR simultaneously provided high treatment capacity and process stability in anaerobic digestion with high-lipid loading.
Computational Design Analysis of a Hydrokinetic Horizontal Parallel Stream Direct Drive Counter-Rotating Darrieus Turbine System: A Phase One Design Analysis Study
Authors: Crooks John M. , Hewlin Rodward L. , Williams Wesley B.
Published: November 2022

This paper introduces a phase one computational design analysis study of a hydrokinetic horizontal parallel stream direct-drive (no gear box) counter-rotating Darrieus turbine system. This system consists of two Darrieus rotors that are arranged in parallel and horizontal to the water stream and operate in counter-rotation due to the incoming flow. One of the rotors directly drives an armature coil rotor and the other one a permanent magnet generator. A two-dimensional (2-D) and three-dimensional (3-D) computational fluid dynamic (CFD) simulation study was conducted to assess the hydrokinetic performance of the design. From a high computational cost and time perspective, the simulation setup was reduced from a 3-D to a 2-D analysis. Although useful information was obtained from the 3-D simulations, the output performance could be assessed with the 2-D simulations without compromising the integrity of the turbine output results. A scaled experimental design prototype was developed for static (non-movement of the rotors with dynamic fluid flow) particle image velocimetry (PIV) studies. The PIV studies were used as a benchmark for validating and verifying the CFD simulations. This paper outlines the prototype development, PIV experimental setup and results, computational simulation setup and results, as well as recommendations for future work that could potentially improve overall performance of the proposed design.
Research on the Dust Diffusion and Pollution Behaviour of Dynamic Tunneling in Header Excavators Based on Dynamic Mesh Technology and Field Measurement
Authors: Chen Xi , Zhang Hao , Ge Shaocheng , Deng Cunbao , Fan Chaonan , Ma Guoliang , Li Weichao
Published: November 2022

In order to accurately characterize and evaluate dust particle diffusion in the dynamic tunneling process of a boring machine, this study considers the 31,116 main transport chute heaving face of the Lijiahao coal mine as a case study. A dynamic tunneling model is developed considering the real dynamic tunneling state of the header, to carry out an in-depth analysis of the spatial and temporal evolution of wind flow and dust dispersion in the tunnel under dynamic excavation. In addition, the results were compared against the calculations of a static standard excavation model of a conventional header. Employing CFD analysis accompanied by field measurements, it was highlighted that the dynamic tunneling of the header leads to an increase in the pressure difference and the turbulent kinetic energy at the working face. Moreover, an increase in the number of vortices was reported, and a higher concentration of dust spreads more quickly along the return wind side wall to the return flow area. On the other hand, the high concentration of dust under the standard tunneling model was found to accumulate a lot on the return wind side. Simultaneously, as the distance between the pressurized air outlet and the working face increases, the average wind speed in the vortex-type wind flow area at the front of the tunnel decreases. When t = 60 s, the return flow area expands to a space of 8 m~24 m from the head, and the dust accumulated above the header spreads to the back of the header to form a high concentration dust region of more than 500 mg/m³. It was shown that the range of high-concentration dust clouds in the breathing zone decreases compared to the results of the standard tunneling model. Moreover, the dust concentration in the breathing zone of the driver is significantly lower than that reported by the standard tunneling model. Based on the results of the field test, the average error between the simulated and measured data of the dynamic tunneling model was calculated to be around 6.46%, thus demonstrating the model’s capability in describing the real working conditions of the heave tunnel.
Numerical Study for Enhancement of Heat Transfer Using Discrete Metal Foam with Varying Thickness and Porosity in Solar Air Heater by LTNE Method
Authors: Diganjit Rawal , Gnanasekaran N. , Mobedi Moghtada
Published: November 2022

A two-dimensional rectangular domain is considered with a discrete arrangement at equal distances from copper metal foam in a solar air heater (SAH). The local thermal non-equilibrium model is used for the analysis of heat transfer in a single-pass rectangular channel of SAH for different mass flow rates ranging from 0.03 to 0.05 kg/s at 850 W/m2 heat flux. Three different pores per inch (PPI) and porosities of copper metal foam with three different discrete thicknesses at equal distances are studied numerically. This paper evaluates the performance of SAH with 10 PPI 0.8769 porosity, 20 PPI 0.8567 porosity, and 30 PPI 0.92 porosity at 22 mm, 44 mm, and 88 mm thicknesses. The Nusselt number for 22 mm, 44 mm, and 88 mm thicknesses is 157.64%, 183.31%, and 218.60%, respectively, higher than the empty channel. The performance factor for 22 mm thick metal foam is 5.02% and 16.61% higher than for 44 mm and 88 mm thick metal foam, respectively. Hence, it is found that metal foam can be an excellent option for heat transfer enhancement in SAH, if it is designed properly.
Study on the Mechanical Properties of Natural Gas Hydrate Reservoirs with Multicomponent under Different Engineering Conditions
Authors: Wang Lei , Yang Jin , Li Lilin , Sun Ting , Xu Dongsheng
Published: November 2022

For wellbore stability issues induced by drilling operations in natural gas hydrate-containing reservoirs, wellbore stability research will focus on the mechanical properties of hydrate reservoirs. According to the content of the research, the response relationship between the hydrate core and the base physical property changes under different engineering parameters is established, and the law of hydrate mechanical property changes with temperature and pressure is studied for various physical properties. According to theoretical research and experimental data, it has been determined that: hydrate core-resolved gas and transverse and longitudinal wave velocity have a positive correlation with saturation and pressure and a negative correlation with temperature; a negative correlation exists between resistivity and saturation. The hydrate core stiffness strength correlates positively with saturation and adversely with temperature. Under the identical strain conditions, when saturation, pore pressure, and temperature increase, the stress of the hydrate grows rapidly; there is a distinct inflection point, and the hydrate does not form above a particular temperature. To prevent the decomposition of hydrates and minimize disasters such as well wall instability and reservoir collapse, it is possible to reduce reservoir in situ temperature and pressure fluctuations in accordance with operational requirements.
Vanadium Oxide–Conducting Polymers Composite Cathodes for Aqueous Zinc-Ion Batteries: Interfacial Design and Enhancement of Electrochemical Performance
Authors: Tolstopyatova Elena G. , Kamenskii Mikhail A. , Kondratiev Veniamin V.
Published: November 2022

Aqueous zinc-ion batteries (AZIBs) are being intensively developed as potential alternative electrochemical power sources, due to their advantages such as low cost, high safety, abundance of natural zinc resources and appropriate energy density. Among currently investigated prospective cathode materials for AZIBs, vanadium oxide-based composites with intrinsically conducting polymers have shown many advantages, such as high capacity, high power density and long battery life. This review gives a focused view of the design for the boosting of zinc ion storage performance using intrinsically conducting polymers in vanadium oxide-based composites and the mechanism of intercalation processes. The main challenges in interfacial engineering of vanadium oxide-conducting polymers composite structures and the prospects for further development of such cathode materials are summarized and discussed. The review would give rise to a broad interest focusing on the advantageous strategy of the development of vanadium oxide composite cathodes with intrinsically conducting polymers (polyaniline, polypyrrole, poly(3,4-ethylenedioxythiophene)) for AZIBs with improved energy density, high-rate capability and stability.
Hydrogen Technology Development and Policy Status by Value Chain in South Korea
Authors: Shin Jae-Eun
Published: November 2022

Global transitions from carbon- to hydrogen-based economies are an essential component of curbing greenhouse gas emissions and climate change. This study provides an investigative review of the technological development trends within the overall hydrogen value chain in terms of production, storage, transportation, and application, with the aim of identifying patterns in the announcement and execution of hydrogen-based policies, both domestically within Korea, as well as internationally. The current status of technological trends was analyzed across the three areas of natural hydrogen, carbon dioxide capture, utilization, and storage technology linked to blue hydrogen, and green hydrogen production linked to renewable energy (e.g., water electrolysis). In Korea, the establishment of underground hydrogen storage facilities is potentially highly advantageous for the storage of domestically produced and imported hydrogen, providing the foundations for large-scale application, as economic feasibility is the most important national factor for the provision of fuel cells. To realize a hydrogen economy, pacing policy and technological development is essential, in addition to establishing a roadmap for efficient policy support. In terms of technological development, it is important to prioritize that which can connect the value chain, all of which will ultimately play a major role in the transformation of human energy consumption.
Review on Model Based Design of Advanced Control Algorithms for Cogging Torque Reduction in Power Drive Systems
Authors: Dini Pierpaolo , Saponara Sergio
Published: November 2022

This review of the state of the art aims to collect the description and main research results in the field of development and validation of control algorithms with the main purpose to solve the problem of cogging torque and main sources of electromagnetic torque ripple. In particular, we focus on electric drives for advanced and modern mechatronic applications such as industrial automation, robotics, and automotive applications, with special emphasis on work that exploits model-based design. A great added value of this paper is to explicitly show the operational steps required for the model-based design design of optimized control algorithms for electric drives where it is necessary to make up for electromagnetic torque oscillations due to the main sources of ripple, particularly cogging torque. The ultimate goal of this paper is to provide researchers approaching this particular problem with a comprehensive collection of the most effective solutions reported in the state of the art and also a summary for effectively applying the model-based design methodology.
Control Strategy for Resonant Inverter in High Frequency AC Power Distribution System with Harmonic Suppression and Transient Performance Improvement
Authors: Zhou Hao , Liu Junfeng , Fang Zijie , Zhang Pengyu , Zhang Bolun , Ma Mingze , Zeng Jun
Published: November 2022

In high frequency AC (HFAC) distribution system, the resonant inverter is used to improve power quality and keep the stability of the output AC voltage. Aiming at the problems of poor output power quality and slow transient performance caused by unreasonable filter parameter design and load change during inverter operation, a single-phase H-bridge LCLC resonant inverter based on analog circuit controller implement is introduced in this paper for HFAC power distribution system (PDS). In this study, to design harmonic compensator and analyze the responsiveness of the inverter, it is necessary to analyze the output voltage total harmonic distortion (THD) of LCLC resonant inverter and the performance of the open loop system in detail. On the one hand, a proportional-integral-resonant (PIR) controller is designed to maintain the zero static error of the voltage output and suppress the output voltage THD of LCLC resonant inverter. On the other hand, an integral controller combines with phase-shift modulation (PSM) method is presented to effectively improve the transient performance of resonant inverter and provide the fixed frequency of the output voltage. On the basis of the above, the experimental prototype is implemented with the output AC voltage root mean square of 28 V, and the output voltage frequency for resonant inverter is equal to switching frequency. A rated output power of 130 W experimental platform is built to verify the effectiveness of the theoretical analysis, control strategy, and modulation method.
A Review of Recent Investigations on Flow and Heat Transfer Enhancement in Cooling Channels Embedded with Triply Periodic Minimal Surfaces (TPMS)
Authors: Yeranee Kirttayoth , Rao Yu
Published: November 2022

Triply periodic minimal surfaces (TPMS) have shown better mechanical performance, mass transfer, and thermal conductivity than conventional and strut-based structures, which have been employed in different disciplines. Most of the literature investigates different TPMS topologies in cooling channels to enhance thermal performance due to the smooth curvature and large surface area. However, a deeper investigation of the effects of TPMS design variables and the thermal performance advantages of cooling channels is required. This review details the effects of TPMS design variables, i.e., porosity, wall thickness, and unit cell size, on flow and heat transfer enhancement. It is found that varying the design variables significantly changes the flow and heat transfer characteristics. Also, by comparing TPMS and conventional cooling structures, it is found that most TPMS structures show better thermal performance than other strategies. Moreover, different fabrication methods for TPMS-based cooling channels in recent investigations are collected and discussed. In light of the reviewed literature, recommendations for future research suggest that more experimental and numerical studies on the flow and heat transfer for different cooling applications are needed. Therefore, this review serves as a reference tool to guide future studies on the flow and heat transfer of TPMS-based cooling channels.