bluuebunny/crossref_metadata_2025 huggingface dataset:
UAV-Embedded Sensors and Deep Learning for Pathology Identification in Building Façades: A Review
Authors: Meira Gabriel de Sousa , Guedes João Victor Ferreira , Bias Edilson de Souza
Published: July 2024

The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has stimulated the search for new data processing and validation methods, considering the magnitude of the data collected during fieldwork and the absence of specific methodologies for each type of sensor. Regarding data processing, the use of deep learning techniques has become widespread, especially for the automation of processes that involve a great amount of data. However, just as with the increasing use of embedded sensors, deep learning necessitates the development of studies, particularly those focusing on neural networks that better represent the data to be analyzed. It also requires the enhancement of practices to be used in fieldwork, especially regarding data processing. In this context, the objective of this study is to review the existing literature on the use of embedded technologies in UAVs and deep learning for the identification and characterization of pathological manifestations present in building façades in order to develop a robust knowledge base that is capable of contributing to new investigations in this field of research.
Selected Socio-Economic Aspects of the Last Two Economic Crises in Slovenia Assessed through a Three-Stage Territorial Model
Authors: Kušar Simon
Published: July 2024

The aim of this paper is to provide a systematic insight into the socio-economic aspects of the last two economic crises in Slovenia: the Economic crisis between 2009 and 2013, and the COVID-19 crisis in 2020. A three-stage territorial model was developed as a theoretical tool for this study. The data for the analyses came from various statistical sources and from the available literature. The socio-economic aspects of both economic crises were analysed in 11 categories and at three territorial levels: macro (national), meso (regional) and micro (locational). Both economic crises differ fundamentally in many aspects. Compared to the Economic crisis, the COVID-19 crisis was much shorter and less severe, and had relatively little impact on the socio-economic structure of Slovenia and its regions. Both economic crises had some common features: reduction of interregional disparities and different development paths of regions during the crisis, as well as strong economic growth in the first year of recovery. The proposed model can be extended by additional territorial levels and by adding additional social and political-geographical aspects.
Research on Path Planning Method for Autonomous Patrol Robots
Authors: Zou Qiang , Wang Haipeng , Zhang Tianle , Li Zhengqi , Zhuang Yaoming
Published: July 2024

For autonomous patrol robots, how to complete multi-point path planning efficiently is a crucial challenge. To address this issue, this work proposes a practical and efficient path planning method for patrol robots. Firstly, the evaluation function of the traditional A* method is improved to ensure that the planned path maintains a safe distance from the obstacles. Secondly, a Dubins curve is used to optimize the planned path to minimize the number of turning points while adhering to kinematic constraints. Thirdly, a trajectory-preserving strategy is proposed to preserve the continuous trajectory, linking multi-points for future inspection tasks. Finally, the proposed method is validated through both simulation and real-world experiments. Experimental results demonstrate that our proposed method performs exceptionally well in terms of safety, actual trajectory distance, and total execution efficiency.
Research on Formation Rendezvous for Unmanned Surface Vehicles Considering Arbitrary Initial Positions and Headings
Authors: Zhang Yuanyuan , Peng Pengfei , Wei Junbao
Published: July 2024

The formation of unmanned surface vehicles (USVs) stands as a paramount concern in USV formation control research. In addressing this, this paper introduces a novel formation strategy for USVs, which accounts for their arbitrary initial positions and headings. Firstly, given the random distribution of the USVs’ initial positions, to enhance the efficiency of formation assembly, the point set of the USVs is matched with basic formations using the Hausdorff distance to establish the formation. Building upon this foundation and acknowledging the potential hindrance posed by the arbitrary initial headings of the USVs, which could hinder their ability to reach the designated formation target points, a cost matrix is constructed based on the designed distance–azimuth evaluation function. Subsequently, the Hungarian algorithm is utilized to efficiently assign formation target points for the USVs. Ultimately, the effectiveness of the proposed strategy is validated through simulation experiments.
Operational Amplifiers Defect Detection and Localization Using Digital Injectors and Observer Circuits
Authors: Sekyere Michael , Saikiran Marampally , Chen Degang
Published: July 2024

Operational amplifiers (op amps) are fundamental blocks that find wide application both as stand-alone devices and as crucial blocks embedded in various Systems on Chips (SoCs). Achieving high defect coverage, as well as performing defect localization in these circuits, has proven to be a difficult/expensive task, even with sophisticated testing circuitry. The ISO 26262 standard for functional safety (FuSa) includes the stringent requirement that an automotive IC must have a very high defect coverage. This reinforces the need to ensure the functionality of analog and mixed (AMS) circuits, especially in mission critical applications. This paper presents an all-digital op amp defect detection, diagnosis, and localization method that can be used both for production and in-field tests and discusses various implementation of the proposed method. We validated our results using extensive transistor-level simulations of multiple op amp architectures using TSMC 180 nm technology. Across op amp architectures and multiple implementation approaches, we achieved a worst-case and best-case defect coverage of 94.5% and 99%, respectively. Furthermore, in this work, we also propose a defect diagnosis and localization strategy using recorded bit streams from states of digital injectors and detectors.
Quantum-Dot CA-Based Fredkin Gate and Conservative D-Latch for Reliability-Based Information Transmission on Reversible Computing
Authors: Jeon Jun-Cheol
Published: July 2024

Reversible computation is very important to minimize energy dissipation and prevent information loss not only in quantum computing but also in digital computing. Therefore, interest in designing efficient universal logic gates has recently increased. In this study, we efficiently design the Fredkin gate (FRG), a well-known conservative reversible operation gate, using quantum-dot cellular automata (QCA), and propose a D-latch using it. The proposed FRG structure can be designed efficiently using the structure of a QCA multiplexer using cell interaction, and a symmetric structure was designed. The proposed structure was simulated using QCADesigner 2.0.3 and QCADesigner-E for accurate comparison of various performance metrics, and the proposed structure clearly shows superiority in most performances and two representative design costs. Therefore, the lightweight design of an efficient reversible gate prevents data loss and increases information reliability.
Recovery of Incomplete Fingerprints Based on Ridge Texture and Orientation Field
Authors: Sun Yuting , Chen Xiaojuan , Tang Yanfeng
Published: July 2024

The recovery of mutilated fingerprints plays an important role in improving the accuracy of fingerprint recognition and the speed of identity retrieval, so it is crucial to recover mutilated fingerprints efficiently and accurately. In this paper, we propose a method for the restoration of mutilated fingerprints based on the ridge texture and orientation field. First, the part to be restored is identified via the local quality of the fingerprint, and a mask image is generated. Second, a novel dual-stream fingerprint restoration network named IFSR is designed, which contains two branches, namely an orientation prediction branch guided by the fingerprint orientation field and a detail restoration branch guided by the high-quality fingerprint texture image, through which the damaged region of the mutilated fingerprint is restored. Finally, the method proposed in this paper is validated on a real dataset and an artificially damaged fingerprint dataset. The equal error rate (EER) achieved on the DB1, DB2, and DB4 datasets of FVC2002 is 0.10%, 0.12%, and 0.20%, respectively, while on the DB1, DB2, and DB4 datasets of FVC2004, the EER reaches 1.13%, 2.00%, and 0.27%, respectively. On the artificially corrupted fingerprint dataset, the restoration method achieves a peak signal-to-noise ratio (PSNR) of 16.6735.
5G Radiation Source Location Based on Passive Virtual Aperture Technology by Single-Satellite
Authors: Zhang Tong , Zhang Xin , Wang Xiangyuan , Yang Qiang
Published: July 2024

With the development of 5th-Generation Mobile Communication (5G) technology and the deployment of low-Earth orbit satellites, using satellites to locate 5G radiation sources is of great significance in commerce and the military as an important task of integrated sensing and communication. Recently, passive virtual aperture technology has been introduced into passive location to improve accuracy, but the existing method, using matched filters to search the Doppler information to realize the location, has the disadvantages of high complexity and poor range resolution. In this paper, an improved 5G radiation source location based on a virtual aperture is proposed, which uses the improved Golden Section search-fractional Fourier algorithm (GSS-FRFT) to improve the existing passive virtual aperture location methods. First, the received signals are coherently accumulated to convert the time gain into spatial gain, and the subcarrier phase information is extracted by Fast Fourier Transform based on the 5G signal characteristics to obtain the azimuth signal. Then, an improved high-order GSS-FRFT algorithm is proposed to analyze the Doppler information, and signal focusing and satellite ephemeris data are used to estimate the effective velocity and solve the radiation source location. The simulation results show that the proposed method can improve the location accuracy compared with other single-satellite location methods and has high resolution, high accuracy and low complexity compared with the existing passive virtual aperture location method.
Encrypted Traffic Decryption Tools: Comparative Performance Analysis and Improvement Guidelines
Authors: Jo Minwoo , Jeong Hayong , Song Binwon , Jo Heeseung
Published: July 2024

With the exponential growth of encrypted communication over the internet, research into systems capable of analyzing large volumes of encrypted traffic is essential. This study focuses on evaluating the performance of two prominent tools, ssldump and tshark, in decrypting and inspecting encrypted network traffic, assuming an environment where decryption keys are available. The performance of ssldump and tshark was assessed using various metrics, including execution time, and the ability to handle different file sizes and session counts. The results showed that tshark exhibited faster processing speeds for smaller file sizes and a higher number of sessions, while ssldump demonstrated better performance for larger file sizes and fewer sessions. However, notable performance differences were not observed based solely on the type of cipher suite or encryption method used. To enhance performance, the study proposes the session-based split and conquer (SSC) technique for automating parallelization using a multi-process approach. SSC shows up to a 39× improvement in performance, depending on system capabilities and workload.
Extended Comparison and Performance Analysis for Mobile Ad-Hoc Networks Routing Protocols Based on Different Traffic Load Patterns and Performance Metrics
Authors: Razouqi Qutaiba , Boushehri Ahmed , Gaballa Mohamed , Alsaleh Lina , Abbod Maysam
Published: July 2024

A mobile ad-hoc network (MANET) is a network of mobile nodes that dynamically form a transitory network lacking any existence of infrastructure and any form of centralized management. Nodes in ad hoc networks are powered by batteries with a limited lifespan and communicate in a restricted bandwidth. The unpredictable environment of a MANET may run into a major concern in the routing mechanism, therefore the need for a routing protocol with robust performance is still one of the key challenges in MANET deployment. In this work, a comparative comparison and extensive simulation analysis have been carried out for three major routing protocols: destination sequenced distance vector (DSDV), dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV). Protocol evaluation has been extended by considering several simulation arrangements, different classes of traffic load patterns and diverse performance metrics. Based on packet rate change, node quantity and node speed, simulation scenarios were generated. Protocols were investigated against energy consumption, throughput, lost packets, routing load and packet delivery fraction for three types of traffic load patterns regular, irregular and joint traffic. DSR and AODV protocols proved to be more reliable when joint traffic was implemented when node speed and packets variations are considered. DSDV protocol verifies outstanding response over other protocols in terms of energy consumption when either regular or irregular traffic is applied. The simulation results for DSR protocol have verified the superiority over other protocols in 9 simulation scenarios when diverse metrics are considered. DSDV showed optimal performance in 7 cases, especially at low packet rates and in networks with minimum number of nodes. Similarly, AODV protocol showed outstanding performance in 6 scenarios, when higher packet rates and node mobility are considered.
Distributed Model Predictive Control Based on Bus Voltage Derivative and SoC Dynamic Model for Shipboard DC Microgrids
Authors: Ban Changyu , Huang Sunhua , Xiong Linyun , Zhou Yang , Wang Qingde , Song Ruikai , Wang Luwei , Li Fei
Published: July 2024

State-of-charge (SoC) consistency and bus voltage regulation are two major control objectives of shipboard DC microgrids. To achieve these objectives, this paper presents a novel distributed model predictive control (DMPC) strategy with multiple cost functions. Firstly, based on the bus voltage derivative and SoC dynamic model, the voltage and SoC control equations in discrete form are established. Subsequently, considering the safe operation of battery energy storage systems (BESSs), a DMPC taking the energy storage current as the control set is designed. Finally, the average voltage compensation is taken to achieve precise control of the average voltage. The proposed method can avoid the complex process of adjusting weight coefficients, thereby simplifying controller design. Furthermore, the robustness and practicality of the proposed DMPC method are verified through MATLAB/Simulink 2021a simulations and hardware-in-the-loop (HiL) experiments.
A Novel Geothermal Wellbore Model Based on the Drift-Flux Approach
Authors: Yuan Yin , Li Weiqing , Zhang Jiawen , Lei Junkai , Xu Xianghong , Bian Lihan
Published: July 2024

Geothermal energy, being a clean energy source, has immense potential, and accurate wellbore modeling is crucial for optimizing the drilling process and ensuring safety. This paper presents a novel geothermal wellbore model based on the drift-flux approach, tested under three different temperature and pressure well conditions. The proposed model integrates the conservation equations of mass, momentum, and energy, incorporating the gas–liquid two-phase flow drift-flux model and heat transfer model. The key features include handling the heat transfer between the formation and the wellbore, addressing the slip relationship between the gas and liquid phases, and accounting for wellbore friction. The nonlinear equations are discretized using the finite difference method, and the highly nonlinear system is solved using the Newton–Raphson method. The numerical simulation, validation, and comparison with existing models demonstrate the enhanced accuracy of this model. In our tests, the model achieved a high accuracy in calculating the bottom-hole pressure and temperature, with mean relative errors (MREs) significantly lower than those of other models. For example, the MREs for the bottom-hole pressure and temperature of the Rongxi area well in Xiongan, calculated by this model, are 1.491% and 1.323%, respectively. These results offer valuable insights for optimizing drilling parameters and ensuring drilling safety. Comparisons indicate that this approach significantly outperforms others in capturing the complex dynamics of geothermal wellbores, making it a superior tool for geothermal energy development.
A Deep Reinforcement Learning Approach to DC-DC Power Electronic Converter Control with Practical Considerations
Authors: Mazaheri Nafiseh , Santamargarita Daniel , Bueno Emilio , Pizarro Daniel , Cobreces Santiago
Published: July 2024

In recent years, there has been a growing interest in using model-free deep reinforcement learning (DRL)-based controllers as an alternative approach to improve the dynamic behavior, efficiency, and other aspects of DC–DC power electronic converters, which are traditionally controlled based on small signal models. These conventional controllers often fail to self-adapt to various uncertainties and disturbances. This paper presents a design methodology using proximal policy optimization (PPO), a widely recognized and efficient DRL algorithm, to make near-optimal decisions for real buck converters operating in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) while handling resistive and inductive loads. Challenges associated with delays in real-time systems are identified. Key innovations include a chattering-reduction reward function, engineering of input features, and optimization of neural network architecture, which improve voltage regulation, ensure smoother operation, and optimize the computational cost of the neural network. The experimental and simulation results demonstrate the robustness and efficiency of the controller in real scenarios. The findings are believed to make significant contributions to the application of DRL controllers in real-time scenarios, providing guidelines and a starting point for designing controllers using the same method in this or other power electronic converter topologies.
Numerical Simulation Method of Hydraulic Power Take-Off of Point-Absorbing Wave Energy Device Based on Simulink
Authors: Jing Fengmei , Wang Song , Sant Tonio , Micallef Christopher , Mollicone Jean Paul
Published: July 2024

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources.
Crystal Structure Prediction and Performance Assessment of Hydrogen Storage Materials: Insights from Computational Materials Science
Authors: Yang Xi , Li Yuting , Liu Yitao , Li Qian , Yang Tingna , Jia Hongxing
Published: July 2024

Hydrogen storage materials play a pivotal role in the development of a sustainable hydrogen economy. However, the discovery and optimization of high-performance storage materials remain a significant challenge due to the complex interplay of structural, thermodynamic and kinetic factors. Computational materials science has emerged as a powerful tool to accelerate the design and development of novel hydrogen storage materials by providing atomic-level insights into the storage mechanisms and guiding experimental efforts. In this comprehensive review, we discuss the recent advances in crystal structure prediction and performance assessment of hydrogen storage materials from a computational perspective. We highlight the applications of state-of-the-art computational methods, including density functional theory (DFT), molecular dynamics (MD) simulations, and machine learning (ML) techniques, in screening, evaluating, and optimizing storage materials. Special emphasis is placed on the prediction of stable crystal structures, assessment of thermodynamic and kinetic properties, and high-throughput screening of material space. Furthermore, we discuss the importance of multiscale modeling approaches that bridge different length and time scales, providing a holistic understanding of the storage processes. The synergistic integration of computational and experimental studies is also highlighted, with a focus on experimental validation and collaborative material discovery. Finally, we present an outlook on the future directions of computationally driven materials design for hydrogen storage applications, discussing the challenges, opportunities, and strategies for accelerating the development of high-performance storage materials. This review aims to provide a comprehensive and up-to-date account of the field, stimulating further research efforts to leverage computational methods to unlock the full potential of hydrogen storage materials.
Permeability Evolution of Shale during High-Ionic-Strength Water Sequential Imbibition
Authors: Bai Tianhao , Hashemi Sam , Melkoumian Noune , Badalyan Alexander , Zeinijahromi Abbas
Published: July 2024

It is widely accepted in the oil and gas industry that high-ionic-strength water (HISW) can improve oil and gas recovery in unconventional shale reservoirs by limiting shale hydration. Despite numerous supporting studies, there is a lack of a systematic analysis exploring the effect of HISW on shale permeability evolution, particularly considering varying chemical compositions. In this work, we investigated the impact of different concentrations of NaCl and CaCl2 on shale permeability through sequential HISW imbibition experiments, beginning with the highest NaCl and lowest CaCl2 concentrations. After maintaining the highest effective stress for an extended period, significant permeability reduction and potential fracture generation were observed, as indicated by periodic fluctuations in differential pressure. These effects were further intensified by displacements with HISW solutions. Advanced post-experimental analyses using micro-CT scans and SEM-EDS analysis revealed microstructural changes within the sample. Our findings offer initial insight into how HISW-shale interactions influence shale permeability, using innovative approaches to simulate reservoir conditions. The findings indicate that discrepancies in the chemical composition between injected solutions and shale may lead to shale disintegration during hydraulic fracturing processes.
Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction
Authors: Uddin Mohammad Nasim , Gao Yang , Akangah Paul M.
Published: July 2024

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output.
Seasonal Effects of Wildfires on the Physical and Chemical Properties of Soil in Andean Grassland Ecosystems in Cusco, Peru: Pending Challenges
Authors: Roman Melida , Zubieta Ricardo , Ccanchi Yerson , Martínez Alejandra , Paucar Ysai , Alvarez Sigrid , Loayza Julio , Ayala Filomeno
Published: July 2024

Soils are a valuable renewable resource on human timescales, and they interact with distinctive grassland ecosystems characterized by unique biodiversity and essential provision of ecosystem services, such as water supply and carbon sequestration. However, knowledge of the effects of wildfires on soil properties and nutrient availability in the Andes remains limited. Andean grasslands are currently one of the ecosystems of the Peruvian Andes most affected by wildfires. Our objective is to analyze the effect of fire activity on the physicochemical properties of soil and analyze its social context in Cusco, in the southern Andes of Peru. Soil samples were collected during five periods, spanning both the dry and rainy seasons, to characterize changes in soil properties and monitor vegetation recovery post-fire in two local communities dedicated to livestock activities. The vegetation restored after the wildfire was measured by the “step transect” method. Post-fire changes in soil properties indicate slight increases in pH, electrical conductivity, organic matter, nitrogen, phosphorus, and potassium during the onset of the rainy season; thereafter, a gradual reduction in these values was observed. This reduction can be attributed to leaching associated with the seasonal rainfall and runoff regime. Our findings indicate that one-year post-fire, the biomass in burned areas is reduced to 30–46% of the biomass in unburned areas. A complete regeneration is likely to occur in up to 4 years; this assertion is supported by the perceptions of the affected population, as expressed in interviews conducted in the two farming communities. These results are significant for decision-makers formulation of policies and regulations regarding grasslands and their seasonal restoration.
Analytical and Computational Modeling of Relaxation Times for Non-Newtonian Fluids
Authors: Wang Sheldon , Gao Dalong , Wester Alexandria , Beaver Kalyb , Wyke Kuwin
Published: July 2024

With the availability of efficient and sophisticated finite element analysis (FEA) and computational fluid dynamics (CFD) tools, engineering designs are becoming more software-driven and simulation-based. However, the insights relevant to engineering designs tend to be hidden within massive temporal and spatial data produced with full-fledged three-dimensional simulations. In this paper, we present a preliminary study of the controlled intermittent dispensing of a typical non-Newtonian glue employed in the manufacturing of electric vehicles (EVs). The focus of the study is on the scaling issues derived from different computational and analytical models of interest and importance to the precision control of this non-Newtonian fluid, the lowest dynamic viscosity of which at extremely high shear rates is nearly four million times that of water. More specifically, the abrupt change of the inlet pressure with a constant outlet or ambient pressure and various modeling strategies for transient viscous internal flow with both Newtonian and non-Newtonian fluids are modeled and compared. The analytical and computational results of the developing Newtonian fluid, i.e., water, are derived and computed for validation and verification purposes before the actual applications to the developing non-Newtonian fluid. The concept of a well-established relaxation time before the onset of the steady solution for Newtonian fluids has been validated with both analytical and computational approaches before its expansion and adoption to non-Newtonian fluids with complex rheological behaviors. Other issues attributed to transient operations and precision controls of non-Newtonian fluid delivery involve the pressure pulse and pressure wave propagation within the flexible pipe with compressible or almost incompressible non-Newtonian fluids with a constant pressure at the outlet and a constant mass flow rate or average axial velocity at the inlet, which will be addressed in a separate paper.
Investigation of Convective Heat Transfer and Stability on a Rotating Disk: A Novel Experimental Method and Thermal Modeling
Authors: Cati Yusuf , Wiesche Stefan aus der , Düzgün Mesut
Published: July 2024

Experimental and numerical investigations are conducted on a rotating disk from the perspective of convective heat transfer to understand the effect of heating on the stability of flow. A non-invasive approach with a thermal camera is employed to determine local Nusselt numbers for different rotational rates and perturbation parameters, i.e., the strength of the heat transfer. A novel transient temperature data extraction over the disk radius and an evaluation method are developed and applied for the first time for the air on a rotating disk. The evaluation method utilizes the lumped capacitance approach with a constant heat flux input. Nusselt number distributions from this experimental study show that there is a good agreement with the previous experimental correlations and linear stability analysis on the subject. A significant result of this approach is that by using the experimental setup and developed approach, it is possible to qualitatively show that instability in the flow starts earlier, i.e., an earlier departure from laminar behavior is observed at lower rotational Reynolds numbers with an increasing perturbation parameter, which is due to the strength of heating. Two experimental setups are modeled and simulated using a validated in-house Python code, featuring a three-dimensional thermal model of the disk. The thermal code was developed for the rotating disks and brake disks with a simplified geometry. Experimentally evaluated heat transfer coefficients are implemented and used as convective boundary conditions in the thermal code. Radial temperature distributions are compared with the experimental data, and there is good agreement between the experiment and the model. The model was used to evaluate the effect of radial conduction, which is neglected when using the lumped capacitance approach to determine heat transfer coefficients. It was observed that the radial conduction has a slight effect. The methodology and approach used in this experimental study, combined with the numerical model, can be used for further investigations on the subject.
Rim Driven Thruster as Innovative Propulsion Element for Dual Phase Flows in Plug Flow Reactors
Authors: Lackner Maximilian , Löhr Alexander , Schill Felix , Van Essche Martin
Published: July 2024

The purpose of this work was to test a new setup to pump water with entrained air for application in gas fermentation. A mixed flow, where gas is contained in a liquid to be pumped, rapidly reduces the efficiency of a conventional pump, due to the compressibility of the gas. It is not always possible to degas the fluid, for instance in gas fermentation, which is preferably carried out in tubular reactors (loop fermenters) to achieve a high conversion rate of the gaseous feedstocks. Method: In this work, a rim-driven thruster (RDT) was tested in a lab-scale, cold flow model of a loop reactor with 5–30% (by volume) of gas fraction (air) in the liquid (water) as alternative propulsion element (6 m total pipe length, ambient temperature and pressure). As a result, it was found that the RDT, in connection with a guiding vane providing swirling motion to the two-phase fluid, could pump a mixed flow with up to 25.7% of gas content (by volume) at atmospheric pressure and 25 °C and 0.5 to 2 m/s flow speed. In conclusion, an RDT is advantageous over a classic propulsion element like a centrifugal pump or axial flow pump for transporting liquids with entrained gases. This article describes the potential of rim-driven thrusters, as known from marine propulsion, in biotechnology, the chemical industry, and beyond, to handle multiphase flows.
Essential Oils of Laurus nobilis L.: From Chemical Analysis to In Silico Investigation of Anti-Inflammatory Activity by Soluble Epoxide Hydrolase (sEH) Inhibition
Authors: Fantasma Francesca , Samukha Vadym , Aliberti Michela , Colarusso Ester , Chini Maria Giovanna , Saviano Gabriella , De Felice Vincenzo , Lauro Gianluigi , Casapullo Agostino , Bifulco Giuseppe , Iorizzi Maria
Published: July 2024

Laurus nobilis L. is commonly used in folk medicine in the form of infusion or decoction to treat gastrointestinal diseases and flatulence as a carminative, antiseptic, and anti-inflammatory agent. In this study, the essential oil (EO) composition of wild-grown L. nobilis L. leaves collected from seven different altitudinal locations in the Molise region and adjacent regions (Abruzzo and Campania) was investigated. EOs from the leaves were obtained by hydrodistillation and analyzed by GC-FID and GC/MS, and 78 compounds were identified. The major oil components were 1,8-cineol (43.52–31.31%), methyl-eugenol (14.96–4.07%), α-terpinyl acetate (13.00–8.51%), linalool (11.72–1.08%), sabinene (10.57–4.85%), α-pinene (7.41–3.61%), eugenol (4.12–1.97%), and terpinen-4-ol (2.33–1.25%). Chemometric techniques have been applied to compare the chemical composition. To shed light on the nutraceutical properties of the main hydrophobic secondary metabolites (≥1.0%) of laurel EOs, we assessed the in vitro antioxidant activities based on 2,2-diphenyl-1-picrylhydrazyl (DPPH•) radical scavenging activity and the reducing antioxidant power by using a ferric reducing power (FRAP) assay. Furthermore, we highlighted the anti-inflammatory effects of seven EOs able to interfere with the enzyme soluble epoxide hydrolase (sEH), a key enzyme in the arachidonic acid cascade, in concentrations ranging from 16.5 ± 4.3 to 8062.3 ± 580.9 mg/mL. Thanks to in silico studies, we investigated and rationalized the observed anti-inflammatory properties, ascribing the inhibitory activity toward the disclosed target to the most abundant volatile phytochemicals (≥1.0%) of seven EOs.
Comparative Analysis of Grape Seed Oil, Linseed Oil, and a Blend: In Vivo Effects of Supplementation
Authors: Fernandes Carolina Di Pietro , Pott Arnildo , Hiane Priscila Aiko , Nascimento Valter Aragão do , Filiú Wander Fernando de Oliveira , Oliveira Lincoln Carlos Silva de , Sanjinez-Argandoña Eliana Janet , Cavalheiro Leandro Fontoura , Nazário Carlos Eduardo Domingues , Caires Anderson Rodrigues Lima , Michels Flavio Santana , Freitas Karine de Cássia , Asato Marcel Arakaki , Donadon Juliana Rodrigues , Bogo Danielle , Guimarães Rita de Cássia Avellaneda
Published: July 2024

Grape seeds are rich in bioactive substances, including polyphenols, terpenoids, and phytosterols. Linseed (Linum usitatissimum L.) boasts a high concentration of polyunsaturated fatty acids (PUFAs), lignans, phytoestrogens, and soluble fibers, all contributing to its therapeutic potential. In this study, we pioneered the formulation of an oil blend (GL) combining grape seed oil (G) and golden linseed oil (GL) in equal volumes (1:1 (v/v)) and we evaluated in terms of the nutritional, physical, and chemical properties and their influence in an in vivo experimental model. We analyzed the oils by performing physical–chemical analyses, examining the oxidative stability using Rancimat; conducting thermal analyses via thermogravimetry/derivative thermogravimetry (TG/DTG) and differential scanning calorimetry (DSC), performing optical UV–vis absorption analyses; examining the fluorescence emission–excitation matrix, total carotenoids, and color, and conducting metabolic assessments in an in vivo experimental trial. The fatty acid profile presented a higher fraction of linoleic acid (C18:2) in G and GL and alpha-linolenic acid (C18:3) in L. The acidity and peroxide indices were within the recommended ranges. The TG/DTG, DSC, and Rancimat analyses revealed similar behaviors, and the optical analyses revealed color variations caused by carotenoid contents in L and GL. In the in vivo trial, G (G2: 2000 mg/kg/day) promoted lower total consumption, and the blend (GL: 2000 mg/kg/day) group exhibited less weight gain per gram of consumed food. The group with G supplementation (G2: 2000 mg/kg/day) and GL had the highest levels of HDL-c. The group with L supplementation (L2: 2000 mg/kg/day) had the lowest total cholesterol level. The L2, G1 (1000 mg/kg/day), and G2 groups exhibited the lowest MCP-1 and TNF-α values. Additionally, the lowest adipocyte areas occurred in G and GL. Our results suggest that this combination is of high quality for consumption and can influence lipid profiles, markers of inflammation, and antioxidant status.
Mangosteen Pericarp Processing Technology to Create Economic Value and Reduce Biowaste
Authors: Soontornwat Alisa , Pongsuttiyakorn Thadchapong , Rakmae Samak , Sritham Eakasit , Sirisomboon Panmanas , Pun Umed Kumar , Krusong Warawut , Pornchaloempong Pimpen
Published: July 2024

This research comparatively investigates different mangosteen pericarp processing schemes. The experimental pericarp processing schemes were hot air drying (HAD; control), quick freezing/HAD (QF + HAD), slow freezing/HAD (SF + HAD), and slow freezing/freeze-drying (SF + FD). For freezing, the QF temperature was −38 °C for 2 h and that of SF was −25 °C for 2 weeks. For drying, the HAD temperature was 60 °C for 7 h. In the FD process, the primary and secondary temperatures were −20 °C and 50 °C for 48 h. The experimental results showed that the freezing method (i.e., QF and SF) affected the physical properties (moisture content, water activity, and color) of dried mangosteen pericarp. The antioxidant activities (DPPH and ABTS) of the SF + HAD scheme (28.20 and 26.86 mg Trolox/g DW of mangosteen pericarp) were lower than the SF + FD scheme (40.68 and 41.20 mg Trolox/g DW of mangosteen pericarp). The α-mangostin contents were 82.3 and 78.9 mg/g DW of mangosteen pericarp for FD and HAD, respectively; and the corresponding TPC were 1065.57 and 783.24 mg GAE/g DW of mangosteen pericarp. The results of this study suggest that the drying process had a negligible effect on bioactive compounds. Essentially, the SF + HAD technology is the most operationally and economically viable scheme to process mangosteen pericarp.
Process Optimization and Quality Components Analysis of γ-Aminobutyric Acid Pickled Tea
Authors: Luo Qiuyu , Li Qinmei , Li Jiayu , Xu Wei , Lin Ling
Published: July 2024

Pickled tea is an anaerobically fermented tea common in Thailand, Myanmar and Yunnan minority areas. γ-aminobutyric acid (GABA) is non-protein amino acid with multiple bioactives, which can be easily produced under anaerobic conditions. During the processing of pickled tea, controlling the process parameters is effective for the production of GABA-rich products; however, the precise parameters remain to be clarified. In the present study, the fresh leaves of Camellia sinensis (L.) Kuntze (C. sinensis) ‘FudingDabai’, C. sinensis ‘MabianLv No. 1’, C. sinensis ‘Wuniuzao’ and C. sinensis ‘Fuxuan No. 9’ were used as raw materials to process GABA-rich pickled tea. Single-factor and orthogonal experiments were conducted to determine the best tea cultivars and optimize the best processing parameters via comparing the content of GABA, tea polyphenols (TPs) and other biochemical components of GABA-rich pickled tea. The results of the signal-factor experiment showed that the fresh leaves of C. sinensis ‘MabianLv No. 1’ had the highest GABA content of 2.61 mg·g−1 after treatment with vacuum for 6 h; therefore, C. sinensis ‘MabianLv No. 1’ was selected as the raw material for the subsequent experiments. Orthogonal experiments showed that the highest GABA content of 2.53 mg·g−1 was found in the pickled tea with 8 h of vacuum treatment, 20 min of rolling after microwave fixing, 20 min of spreading and 20 d of anaerobic fermentation at room temperature. Further, the sensory evaluation showed that it possesses a strong sour taste with a slight sweetness and a light yellow color and better comprehensive quality. This indicates that these parameters are optimal for the processing of GABA-rich pickled tea. This study will provide scientific basis for the subsequent production of high GABA tea.
Mechanisms of Litchi Response to Postharvest Energy Deficiency via Energy and Sugar Metabolisms
Authors: Zhao Kunkun , Gao Zhaoyin , Nizamani Mir Muhammad , Hu Meijiao , Li Min , Li Xiaohui , Wang Jiabao
Published: July 2024

In the post-harvest phase, fruit is inexorably subjected to extrinsic stressors that expedite energy expenditure and truncate the storage lifespan. The present study endeavors to elucidate the response strategies of litchi to the alterations of energy state caused by 2,4-Dinitrophenol (DNP) treatment through energy metabolism and sugar metabolism. It was observed that the DNP treatment reduced the energy state of the fruit, exacerbated membrane damage and triggered rapid browning in the pericarp after 24 h of storage. Furthermore, the expression of genes germane to energy metabolism (LcAtpB, LcAOX1, LcUCP1, LcAAC1, and, LcSnRK2) reached their peak within the initial 24 h of storage, accompanied by an elevation in the respiratory rate, which effectively suppressed the rise in browning index of litchi pericarp. The study also posits that, to cope with the decrease of energy levels and membrane damage, litchi may augment the concentrations of fructose, glucose, inositol, galactose, and sorbose, thus safeguarding the canonical metabolic functions of the fruit. Collectively, these findings suggest that litchi can modulate energy and sugar metabolism to cope with fruit senescence under conditions of energy deficiency. This study significantly advances the understanding of the physiological responses exhibited by litchi fruit to post-harvest external stressors.
Secondary Bioactive Metabolites from Foods of Plant Origin as Theravention Agents against Neurodegenerative Disorders
Authors: Gomes Telma Marisa , Sousa Patrícia , Campos Catarina , Perestrelo Rosa , Câmara José S.
Published: July 2024

Neurodegenerative disorders (NDDs) such as Alzheimer’s (AD) and Parkinson’s (PD) are on the rise, robbing people of their memories and independence. While risk factors such as age and genetics play an important role, exciting studies suggest that a diet rich in foods from plant origin may offer a line of defense. These kinds of foods, namely fruits and vegetables, are packed with a plethora of powerful bioactive secondary metabolites (SBMs), including terpenoids, polyphenols, glucosinolates, phytosterols and capsaicinoids, which exhibit a wide range of biological activities including antioxidant, antidiabetic, antihypertensive, anti-Alzheimer’s, antiproliferative, and antimicrobial properties, associated with preventive effects in the development of chronic diseases mediated by oxidative stress such as type 2 diabetes mellitus, respiratory diseases, cancer, cardiovascular diseases, and NDDs. This review explores the potential of SBMs as theravention agents (metabolites with therapeutic and preventive action) against NDDs. By understanding the science behind plant-based prevention, we may be able to develop new strategies to promote brain health and prevent the rise in NDDs. The proposed review stands out by emphasizing the integration of multiple SBMs in plant-based foods and their potential in preventing NDDs. Previous research has often focused on individual compounds or specific foods, but this review aims to present a comprehensive fingerprint of how a diet rich in various SBMs can synergistically contribute to brain health. The risk factors related to NDD development and the diagnostic process, in addition to some examples of food-related products and medicinal plants that significantly reduce the inhibition of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and β-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1), are highlighted.
A Lexicon of Descriptive Sensory Terms for Peas (Pisum sativum L.): A Systematic Review
Authors: Lara Szymon Wojciech , Tsiami Amalia
Published: July 2024

Background: The popularity of peas (Pisum sativum L.) and pea-derived products is constantly growing globally and is estimated to continue to do so at an average annual rate of 12%. This is partially stimulated by the increase in the consumption of meat analogues and the popularisation of animal-protein-free diets. Peas are considered a great source of protein and dietary fibre and are not depicted as allergenic, making them a good replacement ingredient for other legumes such as soy. Peas are also considered good for the environment, mainly due to their nitrogen fixation capabilities. Despite the above benefits, sensory quality is still a limiting factor in increasing consumer acceptance of peas and pea-derived products. Results: This review has been conducted in accordance with the Joanna Brings Institute’s guidance for systematic literature reviews. The search has been conducted on the descriptive sensory terms for Pisum sativum L., where the objectives of the study were to select, present, and analyse the identified descriptive sensory terms for peas found throughout the academic literature. The reviewers have screened 827 articles, of which 12 were eligible for data extraction. Out of the 12 articles, 205 descriptive sensory terms were identified. Those were divided into five categories: smell/odour (27%), flavour (51%), taste (10%), texture (8%), and visual (4%). These included results from sensory analyses by trained/untrained panels and instrumental analyses of texture and of volatile compounds. Conclusion: The identified descriptive sensory terms for Pisum sativum L. could be used for future descriptive sensory evaluation of peas and other legumes, making the process less time consuming. The full list could be used for the initial sensory panel training and then adapted based on the frequency of the depicted terms that meet the criteria for the developed lexicon.