bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytical Performances of the Novel i-STAT Alinity Point-of-Care Analyzer
Authors: Larcher Romaric , Lottelier Maxence , Badiou Stephanie , Dupuy Anne-Marie , Bargnoux Anne-Sophie , Cristol Jean-Paul
Published: January 2023

Many Point-of-Care devices have been released over the past decade. However, data regarding their analytical performances in real-world situations remains scarce. Herein, we aimed to assess the analytical performances of the i-STAT Alinity system. We conducted an analytical performances study with the i-STAT Alinity device using cartridges CG4+ (pH, Pco2, Po2, lactate, bicarbonate and base excess); CHEM8+ (Na, K, Cl, ionized Ca, urea, creatinine, glucose, hematocrit and hemoglobin) and PT/INR (prothrombin time and international normalized ratio). We assessed the imprecision and compared the results to those obtained on existing instruments in the central laboratory. We found that the within-lab coefficients of variation (CV) were very low (<2%) or low (2–5%), except for creatinine and PT (CV = 5.2% and CV = 6.3%, respectively). For almost all the parameters, the results were strongly (R2 = 90–95%) or very strongly (R2 > 95%) correlated with those of the existing laboratory instruments, and the biases were very low (<2%) or low (2–5%). However, correlations of the PT and INR measurements with existing instruments were lower (R2 = 86.0% and 89.7%), and biases in the Po2 (7.9%), creatinine (5.4%) and PT (−6.6%) measurements were higher. The i-STAT Alinity appeared as a convenient device for measurements of numerous parameters. However, clinicians should interpret Po2, creatinine and PT results with caution.
Styloid Jugular Nutcracker: The Possible Role of the Styloid Process Spatial Orientation—A Preliminary Morphometric Computed Study
Authors: Mantovani Giorgio , Zangrossi Pietro , Flacco Maria Elena , Di Domenico Giovanni , Nastro Siniscalchi Enrico , De Ponte Francesco Saverio , Maugeri Rosario , De Bonis Pasquale , Cavallo Michele Alessandro , Zamboni Paolo , Scerrati Alba
Published: January 2023

Styloid Jugular Nutcracker (SJN, also known as Eagle Jugular Syndrome EJS) derives from a jugular stenosis caused by an abnormal styloid process, compressing the vessel in its superior portion (J3) against the C1 anterior arch. It could be considered a venous vascular variant of Eagle Syndrome (ES). Main clinical features of this ES variant are headache, pulsatile tinnitus and dizziness, possibly related to venous hypertension and impaired cerebral parenchyma drainage. In our opinion, conceptually, it is not the absolute length of the styloid bone that defines its abnormality, but its spatial direction. An elongated bone pointing outward far away from the midline could not compress the vein; vice versa, a short styloid process tightly adherent to the cervical spine could be pathological. To prove this hypothesis, we developed a semi-automatic software that processes CT-Angio images, giving quantitative information about distance and direction of the styloid process in three-dimensional space. We compared eight patients with SJN to a sample of healthy subjects homogeneous for sex and age. Our results suggest that SJN patients have a more vertically directed styloid, and this feature is more important than the absolute distance between the two bony structures. More studies are needed to expand our sample, including patients with the classic and carotid variants of Eagle Syndrome.
Machine Learning in Colorectal Cancer Risk Prediction from Routinely Collected Data: A Review
Authors: Burnett Bruce , Zhou Shang-Ming , Brophy Sinead , Davies Phil , Ellis Paul , Kennedy Jonathan , Bandyopadhyay Amrita , Parker Michael , Lyons Ronan A.
Published: January 2023

The inclusion of machine-learning-derived models in systematic reviews of risk prediction models for colorectal cancer is rare. Whilst such reviews have highlighted methodological issues and limited performance of the models included, it is unclear why machine-learning-derived models are absent and whether such models suffer similar methodological problems. This scoping review aims to identify machine-learning models, assess their methodology, and compare their performance with that found in previous reviews. A literature search of four databases was performed for colorectal cancer prediction and prognosis model publications that included at least one machine-learning model. A total of 14 publications were identified for inclusion in the scoping review. Data was extracted using an adapted CHARM checklist against which the models were benchmarked. The review found similar methodological problems with machine-learning models to that observed in systematic reviews for non-machine-learning models, although model performance was better. The inclusion of machine-learning models in systematic reviews is required, as they offer improved performance despite similar methodological omissions; however, to achieve this the methodological issues that affect many prediction models need to be addressed.
Preliminary Concept of Urban Air Mobility Traffic Rules
Authors: Qu Wenqiu , Xu Chenchen , Tan Xiang , Tang Anqi , He Hongbo , Liao Xiaohan
Published: January 2023

Driven by recent technological breakthroughs, the electric vertical take-off and landing (eVTOL) aircraft has gained considerable attention. The widespread demand for eVTOL aircraft can be attributed to their potential use in the commercialisation of urban air mobility (UAM) in low-altitude urban airspaces. However, the urban low-altitude airspace environment is complex. UAM has a high traffic density and the eVTOL aircraft specifications are not uniform. Particularly in commercial scenarios, controlling eVTOL aircraft and ensuring safety in UAMs are the two major problems that should be addressed in future studies. The design of reasonable traffic rules is a potential solution; hence, we organised a UAM traffic rule system and proposed several alternative UAM traffic rules from three perspectives: a single eVTOL aircraft, a certain route, and key control areas. In addition, we validated these traffic rules using multi-rotor and fixed-wing eVTOL aircraft. The results show that designing reasonable traffic rules can facilitate attaining the primary objectives of commercialisation of UAM.
Locality, Realism, Ergodicity and Randomness in Bell’s Experiment
Authors: Hnilo Alejandro Andrés
Published: January 2023

Assuming that there is no way of sending signals propagating faster than light and that free will exists, the loophole-free observed violation of Bell’s inequalities demonstrates that at least one of three fundamental hypotheses involved in the derivation and observation of the inequalities is false: Locality, Realism, or Ergodicity. An experiment is proposed to obtain some evidence about which one is the false one. It is based on recording the time evolution of the rate of non-random series of outcomes that are generated in a specially designed Bell’s setup. The results of such experiment would be important not only to the foundations of Quantum Mechanics, but they would also have immediate practical impact on the efficient use of quantum-based random number generators and the security of Quantum Key Distribution using entangled states.
Ray-Stretching Statistics and Hot-Spot Formation in Weak Random Disorder
Authors: Chen Sicong , Kaplan Lev
Published: January 2023

Weak scattering in a random disordered medium and the associated extreme-event statistics are of great interest in various physical contexts. Here, in the context of non-relativistic particle motion through a weakly correlated random potential, we show how extreme events in particle densities are strongly related to the stretching exponents, where the ’hot spots’ in the intensity profile correspond to minima in the stretching exponents. This strong connection is expected to be valid for different random potential distributions, as long as the disorder is correlated and weak, and is also expected to apply to other physical contexts, such as deep ocean waves.
Acknowledgment to the Reviewers of Eur. Burn J. in 2022
Authors:   Eur. Burn J. Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Incorporating Augmented Reality Tools into an Educational Pilot Plant of Chemical Engineering
Authors: Díaz Manuel J. , Álvarez-Gallego Carlos J. , Caro Ildefonso , Portela Juan R.
Published: January 2023

Chemical Engineering courses are often designed to be divided into two types of lessons: lecture and experimental. In the second one, students develop the knowledge in a hands-on way by attending a pilot plant equipped with different instruments. Hence, a thorough understanding of the different unit operations is needed and, therefore, the implications of changing the operational variables in a process. In this context, the use of new digital technologies is emerging as support tools with the aim of both improving the learning and the motivation of students. Specifically, Augmented Reality (AR) provides a modified physical environment overlaid with multimedia content in the form of text, graphics, video and/or audio. Thus, the incorporation of AR systems in the learning of science has proven to be useful, because it can present multiple benefits for students and teachers related to the improvement of spatial abilities, the increase of memory retention, the decrease of cognitive overload, and a boost in student motivation. This study has carried out a search for resources, projects, software, and applications to implement AR-based tools in the experimental sessions of a Chemical Engineering educational pilot plant. Based on all the information found, several AR projects were proposed by the teachers. Later, some of them were selected according to previously defined criteria and implemented as educational tools for students in the course called Experimentation in Chemical Engineering I. Finally, this tool was evaluated through subsequent post-surveys, being very positively rated by both students and teachers, mainly in the items related to helping to understand concepts or the operating procedures of the equipment.
Arts-Based Approaches to Languages Education with Refugee-Background Learners in the Early Years: Co-Creating Spaces of Hope
Authors: Burke Rachel , Field Rebecca Soraya
Published: January 2023

Young learners with refugee experiences face a constellation of challenges particular to forced migration and resettlement. Experiences of trauma, violence, poverty, and disrupted or limited access to formal education and healthcare can have complex and long-term impacts on learning. Further, the sociocultural and linguistic challenges of undertaking education in unfamiliar schooling systems in transit and resettlement countries can also impede learner engagement and obscure individual strengths. However, like all student cohorts, children with refugee and asylum seeker backgrounds are also unique, with individual personal, sociocultural, and linguistic attributes on which to draw. While these assets may be overlooked or obscured in traditional educational contexts, arts-based approaches to instruction can offer generative and affirming learning spaces that illuminate individual strengths and provide powerful rejoinders to deficit constructions. This article provides an overview of recent research that explores vibrant and innovative arts-based approaches to languages instruction for refugee and asylum-seeker background learners in the early years. The article takes the form of a scoping study of literature using Arksey and O’Malley’s framework to map the field of research, document novel instructional approaches, and identify key themes. Our discussion is oriented toward educators who seek to innovate their own instructional practice. In addition to exploring the creative avenues for language instruction described in the literature, we consider key themes that emerged inductively from our analysis including the agentic value of arts-based instructional practices, the role of narrative in articulating experiences of place and identities, and the significance of arts-based connections between home and school linguistic repertoires.
Measuring Academic Representative Papers Based on Graph Autoencoder Framework
Authors: Zhang Xiaolu , Ma Mingyuan
Published: January 2023

Objectively evaluating representative papers in a specific scientific research field is of great significance to the development of academia and scientific research institutions. Representative papers on achievements in scientific research can reflect the academic level and research characteristics of researchers and research institutions. The existing research methods are mainly based on external feature indicators and citation analysis methods, and the method of combining artificial intelligence is in its infancy. From the perspective of scientific research institutions, this paper proposes a graph autoencoder framework based on heterogeneous networks for the measurement of paper impact, named GAEPIM. Specifically, we propose two versions of GAEPIM based on a graph convolutional network and graph transformer network. The models rank papers in a specific research field and find the most representative papers and their scientific institutions. The proposed framework constructs a heterogeneous network of papers, institutions, and venues and simultaneously analyzes the semantic information of papers and the heterogeneous network structural information. Finally, based on the complex network information diffusion model, the proposed method performs better than several widely used baseline methods.
Space-Time Image Velocimetry Based on Improved MobileNetV2
Authors: Hu Qiming , Wang Jianping , Zhang Guo , Jin Jianhui
Published: January 2023

Space-time image velocimetry (STIV) technology has achieved good performance in river surface-flow velocity measurement, but the application in a field environment is affected by bad weather or lighting conditions, which causes large measurement errors. To improve the measurement accuracy and robustness of STIV, we combined STIV with deep learning. Additionally, considering the light weight of the neural network model, we adopted MobileNetV2 and improved its classification accuracy. We name this method MobileNet-STIV. We also constructed a sample-enhanced mixed dataset for the first time, with 180 classes of images and 100 images per class to train our model, which resulted in a good performance. Compared to the current meter measurement results, the absolute error of the mean velocity was 0.02, the absolute error of the flow discharge was 1.71, the relative error of the mean velocity was 1.27%, and the relative error of the flow discharge was 1.15% in the comparative experiment. In the generalization performance experiment, the absolute error of the mean velocity was 0.03, the absolute error of the flow discharge was 0.27, the relative error of the mean velocity was 6.38%, and the relative error of the flow discharge was 5.92%. The results of both experiments demonstrate that our method is more accurate than the conventional STIV and large-scale particle image velocimetry (LSPIV).
ASIPAMPIUM: An Efficient ASIP Generator for Low Power Applications
Authors: Engroff Alian , Romanssini Marcelo , Compassi-Severo Lucas , de Aguirre Paulo C. C. , Girardi Alessandro
Published: January 2023

The adoption of customized ASIPs (Application Specific Instruction Set Processors) in embedded circuits is an important alternative for optimizing power consumption, silicon area, or processing performance according to the design requirements. The processor is implemented specifically for the target application, which allows the hardware customization in terms of instruction set architecture, data word length, memory size, and parallelism. This work describes an EDA tool for the semi-automatic development of ASIPs named ASIPAMPIUM. The strategy is to provide a set of integrated tools to interpret and generate a customized hardware for a given target application, including compilation, simulation, and hardware synthesis. From the C code description of the application, the tool returns a synthesizable hardware description of the processor. The proposed methodology is based on the adaptation of a new customizable microprocessor called PAMPIUM, which can be optimized in terms of silicon area, power consumption, or processing performance according to the target application. The ASIPAMPIUM tool provides a series of simulated data to the designer in order to identify optimization strategies in both software and hardware domains. We show the results for the implementation of an FFT algorithm using the proposed methodology, which achieved best results in terms of silicon area and energy consumption compared to other works described in the literature for both FPGA and silicon implementation. Moreover, measurement results of the implementation in silicon of a dedicated ASIP for interfacing with six sensors in real-time, including three I2C, an SPI, and an RS-232 interfaces, demonstrate the complete design flow, from the C code program to physical implementation and characterization. Aside from providing a short design time, the ASIPAMPIUM tool also affords a simple and intuitive design flow, allowing the designer to deal with different design trade-offs and objectives.
A Single-Coil Multi-Tapped PDM-Based Induction Heating System for Domestic Applications
Authors: Ramalingam Senthil Rajan , Boopathi C. S. , Ramasamy Sridhar , Ahsan Mominul , Haider Julfikar , Shahjalal Mohammad
Published: January 2023

The conventional heating system is inefficient as the major part of the heating coil lies out-side the vessel it is placed on. This research article proposes a new single-coil multi-tapped induction heating system. This novel induction heating system is facilitated by a half-bridge resonant converter controlled by zero-voltage switching (ZVS). The multi-tapping winding system ensures an effective heat transfer between the coil and the working vessel with the windings of the induction coil segmented to an equivalent size of the vessel. The pulse density modulation (PDM) scheme employed here as the control proves to be the most versatile one. The whole system is duly simulated for an 850 W IH setup in MATLAB Simulink and implemented as a hardware prototype using a half-bridge resonant converter. The control pulses are developed through the PDM in a PIC16F877A controller. The simulation and experimental results prove the credibility of the proposed induction heating (IH) scheme, and during heavy loading conditions, it outperforms the single-coil IH system by gaining an efficiency of 89.29%
Robot Manipulation Skills Transfer for Sim-to-Real in Unstructured Environments
Authors: Yin Zikang , Ye Chao , An Hao , Lin Weiyang , Wang Zhifeng
Published: January 2023

Robot force control that needs to be customized for the robot structure in unstructured environments with difficult-to-tune parameters guarantees robots’ compliance and safe human–robot interaction in an increasingly expanding work environment. Although reinforcement learning provides a new idea for the adaptive adjustment of these parameters, the policy often needs to be trained from scratch when used in new robotics, even in the same task. This paper proposes the episodic Natural Actor-Critic algorithm with action limits to improve robot admittance control and transfer motor skills between robots. The motion skills learned by simple simulated robots can be applied to complex real robots, reducing the difficulty of training and time consumption. The admittance control ensures the realizability and mobility of the robot’s compliance in all directions. At the same time, the reinforcement learning algorithm builds up the environment model and realizes the adaptive adjustment of the impedance parameters during the robot’s movement. In typical robot contact tasks, motor skills are trained in a robot with a simple structure in simulation and used for a robot with a complex structure in reality to perform the same task. The real robot’s performance in each task is similar to the simulated robot’s in the same environment, which verifies the method’s effectiveness.
Cuckoo Matrix: A High Efficient and Accurate Graph Stream Summarization on Limited Memory
Authors: Li Zhuo , Li Zhuoran , Fan Zhiyuan , Zhao Jianli , Zeng Siming , Luo Peng , Liu Kaihua
Published: January 2023

The graph stream is defined as rapid edge streams on a huge domain of nodes. Nowadays, graph streams play important roles in network traffic, social networks, and cloud troubleshooting. Therefore, various summary structures for graph streams are proposed to obtain approximate evaluation results. However, these structures either sacrifice accuracy for guaranteed throughput or compromise memory consumption for high precision. In view of the limitations, we propose Cuckoo Matrix. It only uses one adjacency matrix to complete high accuracy queries while assuring large throughput. Meanwhile, Cuckoo Matrix is capable of preserving the connectivity of edges for the purpose of supporting both structural queries and weight-based estimations. The experimental results show that Cuckoo Matrix improves insertion throughput by 25% and reduces memory consumption by 25% compared to the state-of-the-art, which meets the current requirements of graph stream summarization.
Phase Diffusion in Low-EJ Josephson Junctions at Milli-Kelvin Temperatures
Authors: Lu Wen-Sen , Kalashnikov Konstantin , Kamenov Plamen , DiNapoli Thomas J. , Gershenson Michael E.
Published: January 2023

Josephson junctions (JJs) with Josephson energy EJ≲1 K are widely employed as non-linear elements in superconducting circuits for quantum computing operating at milli-Kelvin temperatures. In the qubits with small charging energy EC ( EJ/EC≫1 ), such as the transmon, the incoherent phase slips (IPS) might become the dominant source of dissipation with decreasing EJ. In this work, a systematic study of the IPS in low-EJ JJs at milli-Kelvin temperatures is reported. Strong suppression of the critical (switching) current and a very rapid growth of the zero-bias resistance due to the IPS are observed with decreasing EJ below 1 K. With further improvement of coherence of superconducting qubits, the observed IPS-induced dissipation might limit the performance of qubits based on low-EJ junctions. These results point the way to future improvements of such qubits.
Precise Identification of Food Smells to Enable Human–Computer Interface for Digital Smells
Authors: Li Yaonian , Ye Zhenyi , Li Qiliang
Published: January 2023

Food safety technologies are important in maintaining physical health for everyone. It is important to digitize the scents of foods to enable an effective human–computer interface for smells. In this work, an intelligent gas-sensing system is designed and integrated to capture the smells of food and convert them into digital scents. Fruit samples are used for testing as they release volatile organic components (VOCs) which can be detected by the gas sensors in the system. Decision tree, principal component analysis (PCA), linear discriminant analysis (LDA), and one-dimensional convolutional neural network (1D-CNN) algorithms were adopted and optimized to analyze and precisely classify the sensor responses. Furthermore, the proposed system and data processing algorithms can be used to precisely identify the digital scents and monitor the decomposition dynamics of different foods. Such a promising technology is important for mutual understanding between humans and computers to enable an interface for digital scents, which is very attractive for food identification and safety monitoring.
Incorporating Derivative-Free Convexity with Trigonometric Simplex Designs for Learning-Rate Estimation of Stochastic Gradient-Descent Method
Authors: Tokgoz Emre , Musafer Hassan , Faezipour Miad , Mahmood Ausif
Published: January 2023

This paper proposes a novel mathematical theory of adaptation to convexity of loss functions based on the definition of the condense-discrete convexity (CDC) method. The developed theory is considered to be of immense value to stochastic settings and is used for developing the well-known stochastic gradient-descent (SGD) method. The successful contribution of change of the convexity definition impacts the exploration of the learning-rate scheduler used in the SGD method and therefore impacts the convergence rate of the solution that is used for measuring the effectiveness of deep networks. In our development of methodology, the convexity method CDC and learning rate are directly related to each other through the difference operator. In addition, we have incorporated the developed theory of adaptation with trigonometric simplex (TS) designs to explore different learning rate schedules for the weight and bias parameters within the network. Experiments confirm that by using the new definition of convexity to explore learning rate schedules, the optimization is more effective in practice and has a strong effect on the training of the deep neural network.
Microalgal Consortia for Waste Treatment and Valuable Bioproducts
Authors: Zhu Shousong , Higa Lauren , Barela Antonia , Lee Caitlyn , Chen Yinhua , Du Zhi-Yan
Published: January 2023

Microalgae have been considered a promising and sustainable candidate for wastewater treatment and valuable bioproducts, such as feedstocks for food, nutrients, and energy. However, many challenging bottlenecks, such as low biomass productivity, expensive biomass harvesting techniques, and inefficient extraction of biofuels restrict its large-scale commercial production. Symbiotic relationships between microalgae and bacteria, also known as microalgal consortia, have proven to be effective solutions for mitigating technical and economic limitations. The natural and artificial symbiotic microalgal consortia combine microorganisms with various metabolic activities, which leads to valuable biomass production and the removal of nutrients, pharmaceuticals, and personal care products (PPCP) from wastewater. Many microalgal consortia have been applied for various wastewater treatments with reduced energy costs and higher efficiency in recovering valuable resources. In this study we review the present research status and prospects of microalgal consortia, emphasizing the associated mechanism of microalgae consortia cooperative symbiosis and its studies on diverse environmental and biotechnological applications.
Multi-Parameter Optimization Analysis of Hydrodynamic Performance for Rim-Driven Thruster
Authors: Nie Yuanzhe , Ouyang Wu , Zhang Zhuo , Li Gaoqiang , Zheng Ruicong
Published: January 2023

The efficiency of rim-driven thrusters (RDT) has always been the focus of attention in the context of energy conservation and environmental protection. A multi-parameter collaborative optimization framework is proposed to improve the efficiency of RDT based on the response surface method (RSM). The common structural parameters of RDT, including pitch ratio, disk ratio and rake angle, are selected as design variables to carry out the Box–Behnken experimental design combined with the simulation data obtained through CFD calculations. The response surface second-order model is employed to evaluate the extent to which different parameters can affect the target variable and obtain the optimal hydraulic efficiency. The results show that the established model has high precision, good reproducibility and strong anti-interference ability. The influence of the pitch ratio, rake angle and disk ratio on open water efficiency decreases in sequence. Compared with the prototype RDT, the maximum efficiency of the optimized RDT is increased by 13.8%, and the surface pressure distribution and flow field characteristics are also significantly modified.
Perspective of Voltage-Fed Single-Phase Multilevel DC-AC Inverters
Authors: Shieh Jenn-Jong , Hwu Kuo-Ing , Chen Sheng-Ju
Published: January 2023

Standing out for their remarkable benefits, such as lower voltage stress on integrated semiconductor devices, reduction in total harmonic distortion, as well as lower electromagnetic effects, multilevel inverters (MLIs) increase their share in the field of energy supply. The multilevel inverter is an interesting research topic that realizes the generation of desired output voltage waveforms composed of small voltage steps. However, many studies have put a premium on the structure, efficiency, and output of the multilevel inverter, but there are relatively few studies on the THD and practical product applications. Consequently, in this brief perspective, some puzzles for MLIs are pointed out to explore new ideas as well as to present new questions.
Multi-Criteria Decision Analysis for Energy Retrofit of Residential Buildings: Methodology and Feedback from Real Application
Authors: Daniel Souleymane , Ghiaus Christian
Published: January 2023

Decision-making in energy retrofit of existing buildings needs to consider the economic and technical criteria, as well as social and environmental ones. The main problems are to define and to aggregate these contradicting issues to support a measurable and verifiable decision process. The working hypothesis of this paper is that the ELECTRE Tri method would respond to the problem. The paper proposes and tests in a real professional environment the ELECTRE Tri method to help choose a retrofit program for collective residential buildings. The evaluation criteria used as performance indicators are defined in consultation with the decision maker and weighted by using the revised Simos’ cards method. The paper proposes to construct the renovation scenarios by combining individual actions that are mutually compatible. The methodology, the proposed criteria and the scenarios were successfully applied on a renovation project of a residential assembly composed of three buildings (67 apartments). A new solution to the problem of defining reference scenarios specific to the ELECTRE Tri method is also proposed. The main advantages of the proposed methodology are the formalization of the decision-making process within the framework of energy renovation strategies and the application of a robust multi-criteria analysis method, considering the complexity of the problem. The main drawbacks are the cost (in time and resources) for obtaining the information needed to construct the decision matrix and the precision of the weights of the criteria. The methodology implemented in Python is available in open source.
Development of a Model-Based Coordinated Air-Fuel Controller for a 3.0 dm3 Diesel Engine and Its Assessment through Model-in-the-Loop
Authors: Ventura Loris , Finesso Roberto , Malan Stefano A.
Published: January 2023

The tightening of diesel pollutant emission regulations has made Internal Combustion Engine (ICE) management through steady-state maps obsolete. To overcome the map’s scarce performance and efficiently manage the engine, control systems must cope with ICE transient operations, the coupling between its subsystem dynamics, and the tradeoff between different requirements. The work demonstrates the effectiveness of a reference generator that coordinates the air path and combustion control systems of a turbocharged heavy-duty diesel engine. The control system coordinator is based on neural networks and allows for following different engine-out Nitrogen Oxide (NOx) targets while satisfying the load request. The air path control system provides the global conditions for the correct functioning of the engine, targeting O2 concentration and pressure in the intake manifold. Through cooperation, the combustion control targets Brake Mean Effective Pressure (BMEP) and NOx to react to rapid changes in the engine operating state and compensates for the remaining deviations with respect to load and NOx targets. The reference generator and the two controller algorithms are suitable for real-time implementation on rapid-prototyping hardware. The performance overall was good, allowing the engine to follow different NOx targets with 150 ppm of deviation and to achieve an average BMEP error of 0.3 bar.
Atomic {Pdn+-X} States at Nanointerfaces: Implications in Energy-Related Catalysis
Authors: Stathi Panagiota , Solakidou Maria , Zindrou Areti , Belles Loukas , Deligiannakis Yiannis
Published: January 2023

Palladium is among the most versatile noble-metal atoms that, when dispersed on solid supports, can be stabilized in 0, +1, +2, +3 redox states. Moreover, despite its noble-metal character, Pd shows a considerable degree of chemical reactivity. In Pd Nanoparticles (NPs), atomic {Pdn+-X} states, where n = 0, 1, 2, 3, and X = atom or hydride, can play key roles in catalytic processes. Pd-oxygen moieties can be stabilized at nanointerfaces of Pd in contact with metal-oxides. These {Pdn+-X}s can be either isolated Pd atoms dispersed on the support, or, more interestingly, atomic states of Pd occurring on the Pd NPs. The present review focuses on the role of such {Pdn+-X} states in catalytic processes related to energy storage or energy conversion, with specific focus on photocatalysis, H2 production reaction (HRR), oxygen reduction reaction (ORR), and water-splitting. Synthesis of atomic {Pdn+-X} states and their detection methodology is among the current challenges. Herein, the chemistry of {Pdn+-X} states on Pd- [metal oxide] interfaces, methods of detection, and identification are discussed. The implication of {Pdn+-X} in transient catalytic intermediates is reviewed. Finally, the role of {Pdn+-X} in photo electrocatalytic processes is critically discussed.
Power Hardware-in-the-Loop (PHIL): A Review to Advance Smart Inverter-Based Grid-Edge Solutions
Authors: von Jouanne Annette , Agamloh Emmanuel , Yokochi Alex
Published: January 2023

Over the past decade, the world’s electrical grid infrastructure has experienced rapid growth in the integration of grid-edge inverter-based distributed energy resources (DERs). This has led to operating concerns associated with reduced system inertia, stability and intermittent renewable power generation. However, advanced or “smart” inverters can provide grid services such as volt-VAR, frequency-Watt, and constant power factor capabilities to help sustain reliable grid and microgrid operations. To address the challenges and accelerate the benefits of smart inverter integration, new approaches are needed to test both the impacts of inverter-based resources (IBRs) on the grid as well as the impacts of changing grid conditions on the operation of IBRs. Power hardware-in-the-loop (PHIL) stands out as a strong testing solution, enabling a real-time simulated power system to be interfaced to hardware devices such as inverters which can be implemented to determine interactions between multiple inverters at multiple points of common coupling on the grid and microgrids. This paper presents a review of PHIL for grid and microgrid applications including recent advancements and requirements such as real-time simulators, hardware interfaces and communication and stability considerations. An illuminating case study is summarized followed by exemplary PHIL testbed developments around the world, concluding with a proposed research paradigm to advance the integration of smart grid-following and grid-forming inverters.
Bamboo Scrimber’s Physical and Mechanical Properties in Comparison to Four Structural Timber Species
Authors: Sylvayanti Sarah Putri , Nugroho Naresworo , Bahtiar Effendi Tri
Published: January 2023

Bamboo scrimber is a sustainable engineered material that overcomes natural round bamboo’s various weaknesses. This study compared the bamboo scrimber’s mechanical (strength, stiffness, and ductility) to timber. The results showed that scrimber’s physical and mechanical properties are comparable, even superior, to wood, especially in compression. Scrimber has a higher density than timber. Its drier equilibrium moisture content indicates that scrimber is more hydrophobic than timbers. The maximum crushing strength (σc//), compressive stress perpendicular-to-fiber at the proportional limit (σcp⊥) and that at the 0.04” deformation (σc0.04⊥), shear strength (τ//), longitudinal compressive modulus of elasticity (Ec//), lateral compressive modulus of elasticity (Ec⊥), and modulus of rigidity (G) of scrimber are higher than those of timbers. Both scrimber’s and timber’s flexural properties (modulus of rupture (σb) and flexural modulus of elasticity (Eb)) are comparable. On the contrary, the tensile strength parallel-to-fiber (σt//) of scrimber is weaker than that of timber. Scrimber is high ductility (μ > 6) when subjected to compression perpendicular-to-fiber, medium ductility (4 < μ ≤ 6) when subjected to compression parallel-to-fiber, and low ductility (brittle) when subjected to bending, shear, or tensile parallel-to-fiber. The higher ductility of scrimber may give an alarm and more time before failure than timbers. Timbers have brittle to lower ductility when receiving each kind of loading scheme. The ratio of shear modulus to strength (G/τ) and compression modulus to strength parallel-to-fiber (EC∥/σC∥) strongly correlates with the ductility ratio. However, the ratio of the flexural modulus of elasticity to the modulus of rupture (Eb/σb) and the ratio of the modulus Young to compression stress perpendicular-to-fiber (Ec⊥/σcp⊥) do not strongly correlate to the ductility value.
Estimation of Extreme Daily Rainfall Probabilities: A Case Study in Kyushu Region, Japan
Authors: Sato Tadamichi , Shuin Yasuhiro
Published: January 2023

Extreme rainfall causes floods and landslides, and so damages humans and socioeconomics; for instance, floods and landslides have been triggered by repeated torrential precipitation and have caused severe damage in the Kyushu region, Japan. Therefore, evaluating extreme rainfall in Kyushu is necessary to provide basic information for measures of rainfall-induced disasters. In this study, we estimated the probability of daily rainfall in Kyushu. The annual maximum values for daily rainfall at 23 long-record stations were normalized using return values at each station, corresponding to 2 and 10 years, and were combined by the station-year method. Additionally, the return period (RP) was calculated by fitting them to the generalized extreme value distribution. Based on the relationship between the normalized values of annual maximum daily rainfall and the RP, we obtained a regression equation to accurately estimate the RP up to 300 years by using data at given stations, considering outliers. In addition, we verified this equation using data from short-record stations where extreme rainfall events triggering floods and landslides were observed, and thereby elucidated that our method was consistent with previous techniques. Thus, this study develops strategies of measures for floods and landslides.
Economic and Environmental Analysis of Woody Biomass Power Generation Using Forest Residues and Demolition Debris in Japan without Assuming Carbon Neutrality
Authors: Fujino Masaya , Hashimoto Masaya
Published: January 2023

Despite the increasing importance of renewable energy worldwide, the argument that forest biomass power generation is not carbon neutral has been rising. This research used Gifu Biomass Power Co., Ltd. (GBP) in Japan as a case study to investigate this matter. An evaluation was conducted through an input–output analysis on the economic and environmental benefits (i.e., CO2 reduction) of forest biomass power generation without assuming carbon neutrality. GBP’s economic benefits were estimated to be 3452.18 million JPY during the construction period and 114.38 million JPY per year from operations. It was also estimated to generate 21.77 jobs per year in the forestry sector. CO2 emissions were estimated to increase by 423.02 tons during the construction period and 137,747 tons per year from operations. Although forests may offset CO2 by absorbing it, woody biomass power generation does not necessarily reduce CO2 emissions in Gifu Prefecture. The results indicate that woody biomass power generation is effective for the local economy but not necessarily for the global environment. The analysis should include more industrial sectors to clarify the environmental significance of wood biomass power generation without assuming carbon neutrality.
Self-Propelled Swimming of a Flexible Propulsor Actuated by a Distributed Active Moment
Authors: Han Changhong , Zhang Zhiyu , Zhang Xing
Published: January 2023

The self-propelled swimming of a flexible propulsor is numerically investigated by using fluid-structure interaction simulations. A distributed active moment mimicking the muscle actuation in fish is used to drive the self-propulsion. The active moment imposed on the body of the swimmer takes the form of a traveling wave. The influences of some key parameters, such as the wavenumber, the amplitude of moment density and the Reynolds number, on the performance of straight-line swimming are explored. The influence of the ground effect on speed and efficiency is investigated through the simulation of near-wall swimming. The turning maneuver is also successfully performed by adopting a simple evolution law for the leading-edge deflection angle. The results of the present study are expected to be helpful to the design of bio-inspired autonomous underwater vehicles.
A Mixture of Full-Fat and Defatted Hermetia illucens Larvae and Poultry By-Products as Sustainable Protein Sources Improved Fillet Quality Traits in Farmed Barramundi, Lates calcarifer
Authors: Chaklader Md Reaz , Chung Wing H. , Howieson Janet , Fotedar Ravi
Published: January 2023

The physicochemical quality and shelf-life of fillets from barramundi, which were fed for 56 days on a mixture of poultry by-product meal (PBM), full-fat Hermetia illucens (FHI), and defatted HI (DHI), were investigated and compared to a fishmeal (FM) control diet. The proximate and total amino acids compositions of the fillets were unaffected by the test diets, while the mixture of PBM and HI larvae improved the sensory quality. An eight-day shelf-life study showed that PBM-HI-based diets improved the texture profile based upon the chewiness, cohesiveness, gumminess, and hardness, regardless of the storage time. The improved texture was aligned with comparatively less degradation of the microstructure of the muscle tissue in the same diets. An improvement in the quality index (QI) value, an increase in pH, and a decrease in lipid oxidation were also found in the fillets of barramundi fed test diets compared with the control diet during the storage time. The test diets positively influenced flesh lightness and redness, while the color profiles were negatively influenced by the storage time. Overall, the maintenance of compositional attributes; the enhancement of fillet sensory attributes, texture, and brightness; and the improved raw fillet shelf-life support the inclusion of PBM-HI-based diets in aquafeed.
Effect of Juglone and Other Allelochemicals in Walnut Leaves on Yield, Quality and Metabolites of Snack Cucumber (Cucumis sativus L.)
Authors: Medic Aljaz , Zamljen Tilen , Slatnar Ana , Hudina Metka , Grohar Mariana Cecilia , Veberic Robert
Published: January 2023

The consumption of fresh vegetables has been consistently associated with numerous health benefits. However, several factors (such as allelochemicals) influence yield, quality, and metabolites, which inevitably affect the fruit quality and health benefits. The present study was conducted to investigate the yield, quality, metabolic responses, and potential toxicity of Cucumis sativus grown in juglone-containing soils. For the treatments, pure juglone (100 µM, 1 mM) and walnut leaf extracts (100 µM) in soil concentrations found in walnut orchards were used. A total of 36 phenolic compounds were identified and quantified in fruits, leaves, and roots using a mass spectrometer coupled with high-performance liquid chromatography. We concluded that juglone at a concentration of 100 µM or walnut leaf extract at the same juglone concentration does not affect the yield of C. sativus, while juglone at a concentration of 1 mM strongly affects it. In the case of juglone, juglone itself was found only in the roots of C. sativus, but not in the leaves or fruits, so C. sativus fruits are considered safe for cultivation in juglone-containing soils. However, this could prove problematic if the plants grown are tubers or root vegetables. The data suggest that juglone itself inhibits secondary metabolism in the plant, making it more susceptible to stress and pathogen attacks.
Relationship between Volatile Organic Compounds and Microorganisms Isolated from Raw Sheep Milk Cheeses Determined by Sanger Sequencing and GC–IMS
Authors: Ruiz María J. , Salatti-Dorado José A. , Cardador María J. , Frizzo Laureano , Jordano Rafael , Arce Lourdes , Medina Luis M.
Published: January 2023

Recently, the interest of consumers regarding artisan cheeses worldwide has increased. The ability of different autochthonous and characterized lactic acid bacteria (LAB) to produce aromas and the identification of the volatile organic compounds (VOCs) responsible for flavor in cheeses are important aspects to consider when selecting strains with optimal aromatic properties, resulting in the diversification of cheese products. The objective of this work is to determine the relationship between VOCs and microorganisms isolated (Lacticaseibacillus paracasei, Lactiplantibacillus plantarum, Leuconostoc mesenteroides and Lactococcus lactis subsp. hordniae) from raw sheep milk cheeses (matured and creamy natural) using accuracy and alternative methods. On combining Sanger sequencing for LAB identification with Gas Chromatography coupled to Ion Mobility Spectrometry (GC–IMS) to determinate VOCs, we describe cheeses and differentiate the potential role of each microorganism in their volatilome. The contribution of each LAB can be described according to their different VOC profile. Differences between LAB behavior in each cheese are shown, especially between LAB involved in creamy cheeses. Only L. lactis subsp. hordniae and L. mesenteroides show the same VOC profile in de Man Rogosa and Sharpe (MRS) cultures, but for different cheeses, and show two differences in VOC production in skim milk cultures. The occurrence of Lactococcus lactis subsp. hordniae from cheese is reported for first time.