bluuebunny/crossref_metadata_2025 huggingface dataset:
Model, Control, and Realistic Visual 3D Simulation of VTOL Fixed-Wing Transition Flight Considering Ground Effect
Authors: Irmawan Erwhin , Harjoko Agus , Dharmawan Andi
Published: May 2023

The research topic of VTOL (vertical take-off and landing) fixed wing (VFW) is gaining significant attention, particularly in the transition phase from VTOL to fixed wing and vice versa. One of the latest and most challenging transition strategies is the bird take-off mode, where vertical and horizontal take-off is carried out simultaneously, mimicking the behavior of birds. The condition that is rarely considered when taking off is the ground effect. Under natural conditions, a ground effect is bound to occur, which can significantly impact the stability of the transition when the VFW is close to the ground. This paper addresses this issue by proposing a model and control strategy and conducting realistic visual 3D simulations of the VFW transition that incorporates ground effect using full complex aerodynamic parameters. This research represents a novel approach, using the robot operating system (ROS) and Gazebo to conduct realistic visual 3D simulations for VFW transition. The linear quadratic regulator (LQR) control method is used to manage the transitions and compensate for any disturbances. The flight tests demonstrate the effectiveness of the proposed model and controller in executing flight missions using the bird take-off mode transition. Moreover, the controller has demonstrated reliability and robustness in compensating for attitude errors induced by ground effects and external disturbances.
Safe Reinforcement Learning for Transition Control of Ducted-Fan UAVs
Authors: Fu Yanbo , Zhao Wenjie , Liu Liu
Published: May 2023

Ducted-fan tail-sitter unmanned aerial vehicles (UAVs) provide versatility and unique benefits, attracting significant attention in various applications. This study focuses on developing a safe reinforcement learning method for back-transition control between level flight mode and hover mode for ducted-fan tail-sitter UAVs. Our method enables transition control with a minimal altitude change and transition time while adhering to the velocity constraint. We employ the Trust Region Policy Optimization, Proximal Policy Optimization with Lagrangian, and Constrained Policy Optimization (CPO) algorithms for controller training, showcasing the superiority of the CPO algorithm and the necessity of the velocity constraint. The transition trajectory achieved using the CPO algorithm closely resembles the optimal trajectory obtained via the well-known GPOPS-II software with the SNOPT solver. Meanwhile, the CPO algorithm also exhibits strong robustness under unknown perturbations of UAV model parameters and wind disturbance.
MGFNet: A Progressive Multi-Granularity Learning Strategy-Based Insulator Defect Recognition Algorithm for UAV Images
Authors: Lu Zhouxian , Li Yong , Shuang Feng
Published: May 2023

Due to the low efficiency and safety of a manual insulator inspection, research on intelligent insulator inspections has gained wide attention. However, most existing defect recognition methods extract abstract features of the entire image directly by convolutional neural networks (CNNs), which lack multi-granularity feature information, rendering the network insensitive to small defects. To address this problem, we propose a multi-granularity fusion network (MGFNet) to diagnose the health status of the insulator. An MGFNet includes a traversal clipping module (TC), progressive multi-granularity learning strategy (PMGL), and region relationship attention module (RRA). A TC effectively resolves the issue of distortion in insulator images and can provide a more detailed diagnosis for the local areas of insulators. A PMGL acquires the multi-granularity features of insulators and combines them to produce more resilient features. An RRA utilizes non-local interactions to better learn the difference between normal features and defect features. To eliminate the interference of the UAV images’ background, an MGFNet can be flexibly combined with object detection algorithms to form a two-stage object detection algorithm, which can accurately identify insulator defects in UAV images. The experimental results show that an MGFNet achieves 91.27% accuracy, outperforming other advanced methods. Furthermore, the successful deployment on a drone platform has enabled the real-time diagnosis of insulators, further confirming the practical applications value of an MGFNet.
Infrared Image Caption Based on Object-Oriented Attention
Authors: Lv Junfeng , Hui Tian , Zhi Yongfeng , Xu Yuelei
Published: May 2023

With the ongoing development of image technology, the deployment of various intelligent applications on embedded devices has attracted increased attention in the industry. One such application is automatic image captioning for infrared images, which involves converting images into text. This practical task is widely used in night security, as well as for understanding night scenes and other scenarios. However, due to the differences in image features and the complexity of semantic information, generating captions for infrared images remains a challenging task. From the perspective of deployment and application, to improve the correlation between descriptions and objects, we introduced the YOLOv6 and LSTM as encoder-decoder structure and proposed infrared image caption based on object-oriented attention. Firstly, to improve the domain adaptability of the detector, we optimized the pseudo-label learning process. Secondly, we proposed the object-oriented attention method to address the alignment problem between complex semantic information and embedded words. This method helps select the most crucial features of the object region and guides the caption model in generating words that are more relevant to the object. Our methods have shown good performance on the infrared image and can produce words explicitly associated with the object regions located by the detector. The robustness and effectiveness of the proposed methods were demonstrated through evaluation on various datasets, along with other state-of-the-art methods. Our approach achieved BLUE-4 scores of 31.6 and 41.2 on KAIST and Infrared City and Town datasets, respectively. Our approach provides a feasible solution for the deployment of embedded devices in industrial applications.
Alcohol and Drug Consumption among Drivers before and during the COVID-19 Pandemic: An Observational Study
Authors: Marrone Maricla , Pititto Fortunato , Stellacci Alessandra , Nicolì Simona , Buongiorno Luigi , De Luca Benedetta Pia , Aventaggiato Lucia , Strisciullo Giuseppe , Solarino Biagio , Benevento Marcello
Published: May 2023

Restrictions imposed during the COVID-19 pandemic might have changed recreational habits. In this study, the results of toxicological tests for alcohol and drugs in blood were compared among drivers stopped at roadside checks in the periods before (1 January 2018 to 8 March 2020) and after the lockdown measures (9 March 2020 to 31 December 2021). A total of 123 (20.7%) subjects had a blood alcohol level above the legal limit for driving of 0.5 g/l, 21 (3.9%) subjects tested positive for cocaine, and 29 (5.4%) subjects positive for cannabis. In the COVID-19 period, the mean blood alcohol level was significantly higher than in the previous period. Cannabis use, which was more frequent among younger subjects, was statistically associated with cocaine use. There has also been a quantitative increase in alcohol levels in the population with values above the legal limits, indicative of greater use of alcohol in the population predisposed to its intake.
Investigation of the Impact of Natural Fracture Geomechanics on the Efficiency of Oil Production and CO2 Injection from/to a Petroleum Structure: A Case Study
Authors: Szott Wiesław , Ruciński Piotr , Słota-Valim Małgorzata , Sowiżdżał Krzysztof
Published: May 2023

The paper addresses the problem of geomechanical effects in the vicinity of production/injection wells and their impacts on the processes of enhanced oil recovery by CO2 injection and CO2 sequestration in a partially depleted oil reservoir. In particular, it focuses on natural fracture systems and their dynamics caused by variations in the rock geomechanical state due to reservoir pressure changes during production/injection processes. The comprehensive approach to the problem requires the combined modeling of both geomechanical and flow phenomena associated with effective coupling simulations of their evolution. The paper applies such an approach to a real, partially depleted oil reservoir in Poland. An effective method of coupled geomechanical and dynamic simulations was used together with the natural boundary and initial conditions for both simulation types. In addition, typical operating conditions were applied in analyzing the processes of enhanced oil recovery by CO2 injection and CO2 sequestration. The detailed results of relevant modeling and simulations are presented and discussed focusing on various scale consequences, including the reservoir, well, and completion ones. Both general conclusions as well as the ones specific to the analyzed geological structure are drawn; they confirm the significant dependence of well performance on geomechanical effects and point out several key factors for this dependence. The conclusions specific to the analyzed structure concern fracture reactivation in tensile/hybrid failure mode caused by pressure build-up during CO2 injection and the importance of the fracture-induced aperture changes resulting from the normal stress, while the shear stress is found to be negligible.
A Review of Non-Residential Building Renovation and Improvement of Energy Efficiency: Office Buildings in Finland, Sweden, Norway, Denmark, and Germany
Authors: Kiviste Mihkel , Musakka Sami , Ruus Aime , Vinha Juha
Published: May 2023

Existing buildings are a source of great potential for energy efficiency through renovation. In this study, the national energy requirements equivalent for the major renovation of existing non-residential buildings using the example of office buildings in five European case countries are drawn out and discussed. The non-residential building sector has been found to be complex and heterogenous with much less available data than for the residential sector, but having greater average specific energy consumption per floor area. The existing non-residential building stock in the studied countries has been divided into varying amounts of groups and sub-groups. The energy requirements have been shifting from the increasing requirements for the U-values of the building envelope (before the 2000s) towards calculated energy demand for buildings as a whole (currently). The requirements for buildings in the near future will be carbon emission based. The energy efficiency of N-RBs in all of the studied case countries have been steadily improved during different decades of construction. Relatively older office stock combined with the relatively late introduction of national energy requirements was found to have a significantly larger potential for energy savings. Different terms and contents in national requirements were used to describe the principles of “major renovation” as from EPBD.
Variable Structure-Based Control for Dynamic Temperature Setpoint Regulation in Hospital Extreme Healthcare Zones
Authors: Hamza Ali , Uneeb Muhammad , Ahmad Iftikhar , Saleem Komal , Ali Zunaib
Published: May 2023

In critical healthcare units, such as operation theaters and intensive care units, healthcare workers require specific temperature environments at different stages of an operation, which depends upon the condition of the patient and the requirements of the surgical procedures. Therefore, the need for a dynamically controlled temperature environment and the availability of the required heating/cooling electric power is relatively more necessary for the provision of a better healthcare environment as compared to other commercial and residential buildings, where only comfortable room temperature is required. In order to establish a dynamic temperature zone, a setpoint regulator is required that can control the zone temperature with a fast dynamic response, little overshoot, and a low settling time. Thus, two zone temperature regulators have been proposed in this article, including double integral sliding mode control (DISMC) and integral terminal sliding mode control (ITSMC). A realistic scenario of a hospital operation theater is considered for evaluating their responses and performance to desired temperature setpoints. The performance analysis and superiority of the proposed controllers have been established by comparison with an already installed Johnson temperature controller (JTC) for various time spans and specific environmental conditions that require setpoints based on doctors’ and patients’ desires. The proposed controllers showed minimal overshoot and a fast settling response, making them ideal controllers for operation theater (OT) zone temperature control.
Influence of Chemical Composition on Heating Value of Biomass: A Review and Bibliometric Analysis
Authors: Esteves Bruno , Sen Umut , Pereira Helena
Published: May 2023

Biomass has become an increasingly important resource for energy generation. The influence of the chemical composition on the heating value of biomass has not been a thoroughly studied subject, as shown by a bibliometric analysis. It is well known that the heating value of lignin is significantly higher (23.26–25.58 MJ/kg) than that of polysaccharides (18.6 MJ/kg), while extractives often have HHVs over 30 MJ/kg, depending on their oxidation levels. Therefore, the proportions of the chemical components in biomass determine its HHV. Softwoods generally have higher HHVs than hardwoods due to their higher contents of lignin and lipophilic resin. Ashes are incombustible, and a high ash content leads to a lower HHV in biomass. Several models have been proposed to correlate the heating values and chemical compounds of biomass, but the most accurate models are based on the lignin from extracted samples, while good correlations between lignin and extractives have also been reported. No good correlations have been obtained with polysaccharide compounds.
Management of Environmental Life Cycle Impact Assessment of a Photovoltaic Power Plant on the Atmosphere, Water, and Soil Environment
Authors: Leda Patryk , Idzikowski Adam , Piasecka Izabela , Bałdowska-Witos Patrycja , Cierlicki Tomasz , Zawada Marcin
Published: May 2023

Photovoltaic power plants are considered to be environmentally friendly solutions to the production of electricity. Solar energy conversion does not release toxic compounds into the environment. However, the construction of solar power plant components (photovoltaic modules, sup-porting structure, inverter station, electrical installation) is extremely consumptive of energy and materials. Massive volumes of minerals, fossil fuels, and electricity are consumed during the manufacturing process. Efficient management of energy and environmental resources seems to be critical for national policy. It is crucial to admit that the post-consumer management of the components of a photovoltaic power plant is connected with a certain quantity of energy and matter and a negative impact on the natural environment. A life cycle assessment was carried out on a real 2 MW photovoltaic power plant located in the northern part of Poland. The analysis was carried out applying the ReCiPe 2016 model and the Life Cycle Assessment (LCA) approach. The impact of the examined renewable energy system was evaluated using 22 impact categories and 3 emission areas (air, water, soil). Life Cycle Assessment analysis was carried out for 2 post-consumer development scenarios (landfill and recycling). The examination of the collected results reveals that photovoltaic modules are the element causing the most negative environmental repercussions connected to the release of dangerous compounds into the atmosphere. Post-consumer development in the form of recycling would provide major environmental benefits and reduce detrimental environmental consequences across the whole life cycle of the photovoltaic power plant. The obtained research results enabled the formulation of pro-environmental recommendations aimed at the long-term development of the life cycle of solar power plants.
3D-Printable Concrete for Energy-Efficient Buildings
Authors: Samudrala Manideep , Mujeeb Syed , Lanjewar Bhagyashri A. , Chippagiri Ravijanya , Kamath Muralidhar , Ralegaonkar Rahul V.
Published: May 2023

Rapid construction with an energy-efficient approach is a major challenge in the present construction industry. Cement, a carbon-intensive material, is mainly used in the construction industry and hence increases the sector’s carbon footprint on the environment. The current review focuses on the study of 3D concrete printing (3DCP), in which cement is partially replaced with industrial byproducts such as ground granulated blast furnace slag (GGBS), fly ash, and silica fume. Walling material is primarily targeted in 3DCP. There is a need to include energy efficiency to achieve a thermally comfortable environment. The life cycle assessment (LCA) of concrete is studied to discover the potential conflicts affecting the environment. The sand-to-binder ratio is pivotal in determining the performance of concrete. The content of the supplements is decided based on this factor. The rheological, physical, and mechanical properties of 3DCP are studied further and analysed. GGBS demonstrates better performance in the compressive and flexure strength of concrete. The usage of fly ash and silica fume has reduced the thermal conductivity of the material, whereas GGBS has increased it. An LCA study shows that 3DCP can be made sustainable with the use of these supplementary cementitious materials.
Capacity Market and Investments in Power Generations: Risk-Averse Decision-Making of Power Producer
Authors: Makimoto Naoki , Takashima Ryuta
Published: May 2023

The penetration of power generations from renewable energy sources into the power market has a significant impact on the capacity factor of existing power generations. This is because power producers cannot recover a capital cost of power generations with high operating cost possibly due to underinvestment. One solution to address this problem includes a capacity mechanism; that is, the capacities of the power generations can be sold through a market or a bilateral contract. Many schemes of the capacity mechanism have been used worldwide. In this study, we examine an investment in a power plant in both the electricity and capacity markets. The effect of investment opportunity on uncertainty and risk aversion is analyzed by a real options approach that is one of analytical methods for investment decisions under uncertainty. The investment timing for the standard energy-only market is compared with that for the capacity market. When the risk averse for the power producer is relatively small, the income in the energy-only market is obtained whereas, when the risk averse is relatively high, the income is gained in both the electricity and capacity markets for the sake of enough profit.
Uncertainties of Climate Change on Suitable Habitat of Calligonum mongolicum Turcz. (Polygonaceae) in Desert Areas of Central Asia
Authors: Liu Guan , Zhang Yanru , Lu Qi , An Keli , Li Yurong , Xiong Dongyang , Li Guoqing , Du Sheng
Published: May 2023

Understanding the climatically suitable habitat of species plays a vital role in the sustainable use and management of target species. Calligonum mongolicum Turcz., a native shrub species found in desert areas of Central Asia, is generally considered as one of the top four tree species for desertification control. However, previous works on suitable habitat simulation had focused mainly on either the national or specific geographical scales rather than entire biota scales, which have underestimated the climatic tolerance of the species. Furthermore, the uncertainty outcomes of climate change were largely ignored. With these questions, the arid regions of Central Asia were selected as our research background area. Occurrence data of C. mongolicum were obtained from various sources, such as the Global Biodiversity Information Facility, the Chinese Virtual Herbarium, and the iPlant website. The maximum entropy model (MaxEnt) was used to simulate the suitable habitat change dynamics under various climate change scenarios [5 general circulation models (GCMs) × 3 shared socioeconomic pathways (SSPs)]. The uncertainty of climate change induced by GCMs and SSPs were decomposed by the two-way ANOVA method. Our results show that hydrological-related variables are more important for the species’ habitat suitability than thermal-related variables. The climatic threshold for the core suitable habitat was 1–30 mm for precipitation of the coldest quarter, 14–401 mm for annual precipitation, −16.01–12.42 °C for mean temperature of the driest quarter, 9.48–32.63 °C for mean temperature of the wettest quarter, and −25.01–−9.77 °C for the minimum temperature of the coldest month. The size of suitable habitat was about 287.4 × 104 km2 under the current climate condition, located in China and Mongolia. Climate change has less impact on the total area size, but it has bigger impacts on the gain area and loss area sizes. The loss area is mainly located in the southeast boundaries, whereas the gain area is mainly located in Mongolia and the Qinghai-Tibet Plateau. The decomposition uncertainty of climate change indicates that GCMs could explain 14.5%, 66.4%, and 97.0% of total variation, respectively, and SSPs could explain 85.5%, 33.6%, and 3.0% of the total variation for gain, loss, and total habitat sizes, respectively. Our work clearly demonstrates that while C. mongolicum has great planting potential in Central Asia under various climate change scenarios, the sensitive areas possess large uncertainties requiring long-term climate monitoring for afforestation projects.
MISF: A Method for Measurement of Standing Tree Size via Multi-Vision Image Segmentation and Coordinate Fusion
Authors: Mo Lufeng , Shi Lijuan , Wang Guoying , Yi Xiaomei , Wu Peng , Wu Xiaoping
Published: May 2023

With the development of computer vision technology, its applications in forestry are steadily becoming wider. To address the problems of inconvenience in transporting unmanned aerial vehicles (UAVs), as well as the complex operation of large instruments for measurement, a new method based on multi-vision image segmentation and coordinate fusion (MISF) is proposed in this paper for measuring the size of standing trees. In MISF, after images of a standing tree are captured using a camera from multiple angles, a semantic segmentation method based on deep learning is used to segment the main body of the standing tree and automatically detect the edge feature points. Next, the effects of visual field splicing and fusion are analyzed collaboratively using the correlations among images, so as to restore the three-dimensional spatial information of the feature points of the tree to be measured. Lastly, the size attributes of the standing tree, such as height, diameter at breast height (DBH), and crown width, are automatically measured. The urban environment measurement experiment showed that the relative errors of tree height, DBH, and crown width measured using the proposed method, i.e., MISF, were 1.89%, 2.42%, and 3.15%, respectively, representing a significant enhancement compared with binocular measurement. On the one hand, the experimental results exhibited a high degree of measurement accuracy; therefore, MISF can be used for the management inventory of typical forests. On the other hand, MISF cannot be used if a tree’s images cannot be acquired due to environmental or other reasons.
Natural Factors Play a Dominant Role in the Short-Distance Transmission of Pine Wilt Disease
Authors: Liu Yanqing , Huang Jixia , Yang Tong
Published: May 2023

Pine wilt disease (PWD) is regarded as one of the most serious conifer diseases affecting pines worldwide. To date, an in-depth study of the driving mechanisms behind short-distance PWD spread is lacking. In this study, we collected PWD forest subcompartment data in Fushun, China, and analysed the effects of factors on the short-distance transmission of PWD; the analysed factors included the number of neighbouring PWD-infected forest subcompartments, the canopy density, the slope direction, and different traffic corridor types. The results suggested that the spatial spill-over effect of nearby PWD-infected subcompartments contributed the most to short-distance PWD transmission, with an impact of up to 78% on its propagation. The impact of the traffic corridor was 20%. With the help of a beetle vector, PWD can spread to nearby forest subcompartments, and this spatial PWD spill-over effect showed a linearly decaying trend as the distance to neighbouring subcompartments increased. Different traffic corridor types exhibited significant PWD transmission impact differences. County roadways and highways had great impacts, while others had relatively small impacts. For each additional 100 m of distance from a county roadway, highway, national, or provincial roadway, the PWD infection risks in forest subcompartments were reduced by 18%, 11%, 5%, and 3%, respectively. In this study, we quantified the influence of driving factors on the short-distance spread of PWD and provided a theoretical basis for the control of PWD transmission; the results obtained herein are critical for maintaining the ecological security of forests, promoting ecological forest management and stabilising forest carbon sinks.
Emission of Volatile Organic Compounds from the Heat Treatment of Afrormosia and Newtonia Wood: Effects of Air and Palm Oil Heat Media
Authors: Bessala Lionnel Frederique Bidzanga , Gao Jingjing , He Zhengbin , Wang Zhenyu , Yi Songlin
Published: May 2023

The objective of this work was to study the influence of palm oil on the VOCs emitted during the heat treatment of Afromosia (Pericopsis Elata Van Meeuwen) and Newtonia (Newtonia paucijuga Harms) wood by comparing to the VOCs emitted during the heat treatment under air. Two batches of Afrormosia and Newtonia wood samples were heated under air and palm oil at temperatures of 160 °C, 180 °C, and 200 °C for 2 h. Then, the VOCs were collected by Solid Phase Micro Extraction (SPME) and measured using a Gas Chromatograph and Mass Spectrometer (GC-MS). The results showed that the temperature, the wood species, and the treatment medium have a great influence on the categories and percentages of VOCs emitted. In the air heat treatment, ethers were the most emitted VOCs from Afrormosia and Newtonia when these woods were thermally treated at 160 °C. Newtonia treated under air at 180 °C emitted more esters, while Afrormosia continued to emit more ethers under the same conditions. Moreover, Afrormosia and Newtonia treated at 200 °C emitted more ketones and aldehydes, respectively. Regarding the heat treatment of Afrormosia and Newtonia wood under palm oil, a similarity of the VOCs emitted from Newtonia with those emitted from Afrormosia under the same conditions was observed. Furthermore, palm oil was the main factor conditioning the nature of the VOCs emitted during the heat treatment. In general, for the treatment of Afrormoshia wood with palm oil, the VOCs emitted, such as alcohols, alkanes, and ethers, decreased with the treatment temperature. Ethers and ketones increased with the processing temperature. At 160 °C and 180 °C, the percentage of aldehydes was highest, while, at 200 °C, the percentage of esters was highest. Similarly, for Newtonia treated under palm oil, adehydes, ethers, and alcohols were the most abundant VOCs emitted at 160 °C. However, their percentages decreased with the increase in the treatment temperature; on the contrary, esters and ketones were weakly emitted at 160 °C and became abundant with the increase in temperature. Additionally, the ethers formed during the heat treatment of Afrormosia and Newtonia wood treated under air carry acetyl groups, while those formed during the treatment of the said wood under palm oil carry hydroxyl groups.
Brewing with Unmalted and Malted Sorghum: Influence on Beer Quality
Authors: Ciocan Marius Eduard , Salamon Rozália Veronika , Ambrus Ágota , Codină Georgiana Gabriela , Chetrariu Ancuța , Dabija Adriana
Published: May 2023

One of the earliest biotechnological processes is brewing, which uses conventional raw materials like barley malt and, to a lesser extent, wheat malt. Today, adjuncts are used in the brewing of 85–90% of the world’s beer, with significant regional differences. The results of this study’s brewing were compared to those of beer made only from malted barley. Malted and unmalted sorghum were suggested for use in this study’s brewing. In order to improve the technical mashing operation and raise output yield, commercial enzymes were introduced. The following physicochemical analyses of the finished beer were carried out in accordance with regulatory requirements: original extract (% m/m), apparent extract (% m/m), alcohol content (% v/v, % m/m), density (g/cm3), turbidity (EBC), pH, color (EBC), bitterness value (IBU), oxygen content (mg/L), carbon dioxide content (g/L). A nine-point hedonic scale was used to conduct the sensory evaluation of the beer samples. Sorghum was easily included into the technological process to create a finished product that, in many ways, resembled traditional beer, making sorghum appropriate for typical beer drinkers. The laboratory brewing formula that produced the highest-quality results of all the tested variants included 60% sorghum malt and 40% unmalted sorghum: original extract 11.26% m/m, apparent extract 4.59% m/m, alcohol content 4.12% v/v, turbidity 0.74 EBC, CO2 content 5.10 g/L. The resulting sorghum beer typically has low alcohol content, a complex, aromatic, slightly sour flavor, a mild bitter or astringent sensation, and less stable foam.
Improvement of the Nutritional Quality of Rapeseed Meal through Solid-State Fermentation with B. subtilis, S. cerevisiae, and B. amyloliquefaciens
Authors: Zhu Xiaoyan , Chen Yiling , Hao Shanxin , Jin Shiyu , Li Xiangqian
Published: May 2023

In this study, the effect of solid-state fermentation with Bacillus subtilis GYB6, Saccharomyces cerevisiae NJ1, and Bacillus amyloliquefaciens Y8 on the anti-nutritional factors, nutritional components, bioactive compounds, antioxidant activity, functional properties, and structure of rapeseed meal (RSM) were investigated. Results showed that the action of three strains in the fermentation of RSM caused a significant decline in glucosinolates, phytic acid, crude fiber, and tannins by 99.18%, 42.41%, 27.21%, and 34.17%, respectively. The amount of crude protein, amino acids, and peptides of RSM increased significantly after fermentation. The SDS-PAGE results showed that 12S globulin and 2S albumin protein were almost entirely degraded. Fermentation considerably increased the concentration of total phenolics and flavonoids, and activated antioxidant activity and functional properties. Furthermore, the structural variation was observed by scanning electron microscopy and FTIR spectroscopy. Thus, these results indicated that the solid-state fermentation process in this study was a promising approach to enhance both the nutritional value and bioactivity of RSM, which could be used as value-added functional animal food ingredients.
Acoustic Based Fire Event Detection System in Underground Utility Tunnels
Authors: Lee Byung-Jin , Lee Mi-Suk , Jung Woo-Sug
Published: May 2023

Underground utility tunnels (UUTs) are convenient for the integrated management of various infrastructure facilities. They ensure effective control of underground facilities and reduce occupied space. However, aging UUTs require effective management and preventive measures for fire safety. The fundamental problems in operating UUTs are the frequent occurrence of mold, corrosion, and damage caused to finishing materials owing to inadequate waterproofing, dehumidification, and ventilation facilities, which result in corrosion-related electrical leakage in wiring and cables. To prevent this, an abnormal sound detection technology is developed in this study based on acoustic sensing. An acoustic sensor is used to detect electric sparks in the moldy environments of UUTs using a system to collect and analyze the sound generated in the UUTs. We targeted the sound that had the highest impact on detecting electric sparks and performed U-Net-based noise reduction and two-dimensional convolutional neural network-based abnormal sound detection. A mock experiment was conducted to verify the performance of the proposed model. The results indicated that local and spatial features could capture the internal characteristics of both abnormal and normal sounds. The superior performance of the proposed model verified that the local and spatial features of electric sparks are crucial for detecting abnormal sounds.
A Critical Review of Fire Tests and Safety Systems in Road Tunnels: Limitations and Open Points
Authors: Lombardi Mara , Berardi Davide , Galuppi Marta
Published: May 2023

Fire tests are used to determine whether fire protection products meet the minimum performance criteria set out in codes and legislation, as well as to certify these products. Experimental large-scale fires are used to test the performance of safety systems in tunnels, which are confined environments with a high probability of accidents and significant consequences due to the evolution of the event and whether there is the capability of counteracting it by safety measures. In this study, we conducted a systematic literature review following PRISMA guidelines. We searched the Scopus and Web of Science databases for publications from 2013 to 2022, resulting in a selection of 72 articles. An analysis was conducted on the following main topics: tunnel fires, fire characteristics (measured variables, spread, and smoke), model-scale tests, automatic shutdown systems, and ventilation solutions. One of the most important contributions of this study is the suggestion that fire tests represent an effective method not only to prevent fire events in tunnels but also to ensure the resilience of the infrastructure. Based on this state-of-the-art literature review, future tunnels could be designed by linking new smart technology and artificial intelligence to create interactive and high-performing safety systems.
Sodium Replacement with KCl and MSG: Attitudes, Perception and Acceptance in Reduced Salt Soups
Authors: Walker Jordan C. , Dando Robin
Published: May 2023

Sodium intake is linked to multiple negative health outcomes, particularly hypertension, the leading cause of premature death globally. Sodium intake levels in human populations are high, due in part to our desire for palatable salty-tasting foods. Two leading salt replacement strategies are the use of potassium chloride (KCl) and monosodium glutamate (MSG), the latter of which still contains some sodium, but both of which can replace some salty taste in foods while reducing net sodium levels. In this report, we employed a trained descriptive sensory panel to optimize saltiness in sodium-reduced aqueous samples using various concentrations of KCl and MSG. Following this, we assessed consumer attitudes to sodium-reduction strategies in a model food, canned soup, known to typically be high in sodium. Finally, in a large consumer test, we verified that these optimized levels of KCl and MSG did not lead to a drop in liking for the reduced-sodium soups with saltiness subsidized in this manner. Our results showed that sodium can be readily reduced in soups by 18% while actually scoring higher in liking, and in some cases being perceived as even more salty tasting, but that consumers are more open to sodium reduction in this manner when sodium replacements are not specifically highlighted, and when percentage sodium reduction is stated over absolute levels.
Health-Aware Food Recommendation Based on Knowledge Graph and Multi-Task Learning
Authors: Chen Yi , Guo Yandi , Fan Qiuxu , Zhang Qinghui , Dong Yu
Published: May 2023

Current food recommender systems tend to prioritize either the user’s dietary preferences or the healthiness of the food, without considering the importance of personalized health requirements. To address this issue, we propose a novel approach to healthy food recommendations that takes into account the user’s personalized health requirements, in addition to their dietary preferences. Our work comprises three perspectives. Firstly, we propose a collaborative recipe knowledge graph (CRKG) with millions of triplets, containing user–recipe interactions, recipe–ingredient associations, and other food-related information. Secondly, we define a score-based method for evaluating the healthiness match between recipes and user preferences. Based on these two prior perspectives, we develop a novel health-aware food recommendation model (FKGM) using knowledge graph embedding and multi-task learning. FKGM employs a knowledge-aware attention graph convolutional neural network to capture the semantic associations between users and recipes on the collaborative knowledge graph and learns the user’s requirements in both preference and health by fusing the losses of these two learning tasks. We conducted experiments to demonstrate that FKGM outperformed four competing baseline models in integrating users’ dietary preferences and personalized health requirements in food recommendations and performed best on the health task.
Editorial for the Special Issue “Operators of Fractional Calculus and Their Multidisciplinary Applications”
Authors: Srivastava Hari Mohan
Published: May 2023

This Special Issue of the MDPI journal, Fractal and Fractional, on the subject area of “Operators of Fractional Calculus and Their Multidisciplinary Applications” consists of 19 peer-reviewed papers, including some invited feature articles, originating from all over the world [...]
Computational Fluid Dynamics Analysis of a Hollow Fiber Membrane Module for Binary Gas Mixture
Authors: Qadir Salman , Ahsan Muhammad , Hussain Arshad
Published: May 2023

The membrane gas separation process has gained significant attention using the computational fluid dynamics (CFD) technique. This study considered the CFD method to find gas concentration profiles in a hollow fiber membrane (HFM) module to separate the binary gas mixture. The membrane was considered with a fiber thickness where each component’s mass fluxes could be obtained based on the local partial pressures, solubility, diffusion, and the membrane’s selectivity. COMSOL Multiphysics was used to solve the numerical solution at corresponding operating conditions and results were compared to experimental data. The two different mixtures, CO2/CH4 and N2/O2, were investigated to obtain concentration gradient and mass flux profiles of CO2 and O2 species in an axial direction. This study allows assessing the feed pressure’s impact on the HFM system’s overall performance. These results demonstrate that the increment in feed pressures decreased the membrane system’s separation performance. The impact of hollow fiber length indicates that increasing the active fiber length has a higher effective mass transfer region but dilutes the permeate-side purities of O2 (46% to 28%) and CO2 (93% to 73%). The results show that increasing inlet pressure and a higher concentration gradient resulted in higher flux through the membrane.
Polyurethane Shape Memory Polymer/pH-Responsive Hydrogel Hybrid for Bi-Function Synergistic Actuations
Authors: Peng Shuyi , Cao Xingyu , Sun Ye , Chen Lin , Ma Chao , Yang Lang , Zhao Hongliang , Liu Qijie , Liu Zhenzhong , Ma Chunxin
Published: May 2023

Stimuli-responsive actuating hydrogels response to the external stimulus with complex deformation behaviors based on the programmable anisotropic structure design are one of the most important smart soft materials, which have great potential applications in artificial muscles, smart values, and mini-robots. However, the anisotropic structure of one actuating hydrogel can only be programmed one time, which can only provide single actuating performance, and subsequently, has severely limited their further applications. Herein, we have explored a novel SMP/hydrogel hybrid actuator through combining polyurethane shape memory polymer (PU SMP) layer and pH-responsive polyacrylic-acid (PAA) hydrogel layer by a napkin with UV-adhesive. Owing to both the super-hydrophilicity and super-lipophilicity of the cellulose-fiber based napkin, the SMP and the hydrogel can be bonded firmly by the UV-adhesive in the napkin. More importantly, this bilayer hybrid 2D sheet can be programmed by designing a different temporary shape in heat water which can be fixed easily in cool water to achieve various fixed shapes. This hybrid with a fixed temporary shape can achieve complex actuating performance based on the bi-functional synergy of temperature-triggered SMP and pH-responsive hydrogel. The relatively high modulus PU SMP achieved high to 87.19% and 88.92% shape-fixing ratio, respectively, correspond to bending and folding shapes. The hybrid actuator can actuate with the 25.71 °/min actuating speed. Most importantly, one SMP/hydrogel bi-layer hybrid sheet was repeatedly programmed at least nine times in our research to fix various temporary 1D, 2D and 3D shapes, including bending, folding and spiraling shapes. As a result, only one SMP/hydrogel hybrid can provide various complex stimuli-responsive actuations, including the reversable bending-straightening, spiraling-unspiraling. A few of the intelligent devices have been designed to simulate the movement of the natural organisms, such as bio-mimetic “paw”, “pangolin” and “octopus”. This work has developed a new SMP/hydrogel hybrid with excellent multi-repeatable (≥9 times) programmability for high-level complex actuations, including the 1D to 2D bending and the 2D to 3D spiraling actuations, which also provides a new strategy to design other new soft intelligent materials and systems.
Mechanical and Physical Properties of an Experimental Chemically and Green-Nano Improved Dental Alginate after Proven Antimicrobial Potentials
Authors: Singer Lamia , Bourauel Christoph
Published: May 2023

Objectives: Impression materials could be a source of cross-contamination due to the presence of microorganisms from blood and saliva inside the oral cavity. Nevertheless, routinely performed post-setting disinfection could compromise the dimensional accuracy and other mechanical properties of alginates. Thus, this study aimed to evaluate detail reproduction, dimensional accuracy, tear strength, and elastic recovery of new experimentally prepared self-disinfecting dental alginates. Methods: Two antimicrobial-modified dental alginate groups were prepared by mixing alginate powder with 0.2% silver nitrate (AgNO3 group) and a 0.2% chlorohexidine solution (CHX group) instead of pure water. Moreover, a third modified group was examined by the extraction of Boswellia sacra (BS) oleoresin using water. The extract was used to reduce silver nitrate to form silver nanoparticles (AgNPs), and the mixture was used as well in dental alginate preparation (BS + AgNP group). Dimensional accuracy and detail reproduction were examined as per the ISO 1563 standard guidelines. Specimens were prepared using a metallic mold engraved with three parallel vertical lines 20, 50, and 75 µm wide. Detail reproduction was evaluated by checking the reproducibility of the 50 µm line using a light microscope. Dimensional accuracy was assessed by measuring the change in length between defined reference points. Elastic recovery was measured according to ISO 1563:1990, in which specimens were gradually loaded and then the load was released to allow for recovery from the deformation. Tear strength was evaluated using a material testing machine until failure at a crosshead speed of 500 mm/min. Results: The recorded dimensional changes between all tested groups were insignificantly different and within the reported acceptable values (between 0.037–0.067 mm). For tear strength, there were statistically significant differences between all tested groups. Groups modified with CHX (1.17 ± 0.26 N/mm) and BS + AgNPs (1.11 ± 0.24 N/mm) showed higher tear strength values compared to the control (0.86 ± 0.23 N/mm) but were insignificant from AgNO3 (0.94 ± 0.17 N/mm). All tested groups showed elastic recovery values that met both the ISO standard and ADA specifications for elastic impression materials and tear strength values within the acceptable documented ranges. Discussion: The CHX, silver nitrate, and green-synthesized silver nanoparticles could be promising, inexpensive alternatives for the preparation of a self-disinfecting alginate impression material without affecting its performance. Green synthesis of metal nanoparticles could be a very safe, efficient, and nontoxic method, with the advantage of having a synergistic effect between metal ions and active chemical constituents of plant extracts.
A Critical Review on Classified Excipient Sodium-Alginate-Based Hydrogels: Modification, Characterization, and Application in Soft Tissue Engineering
Authors: Sharma Rishav , Malviya Rishabha , Singh Sudarshan , Prajapati Bhupendra
Published: May 2023

Alginates are polysaccharides that are produced naturally and can be isolated from brown sea algae and bacteria. Sodium alginate (SA) is utilized extensively in the field of biological soft tissue repair and regeneration owing to its low cost, high biological compatibility, and quick and moderate crosslinking. In addition to their high printability, SA hydrogels have found growing popularity in tissue engineering, particularly due to the advent of 3D bioprinting. There is a developing curiosity in tissue engineering with SA-based composite hydrogels and their potential for further improvement in terms of material modification, the molding process, and their application. This has resulted in numerous productive outcomes. The use of 3D scaffolds for growing cells and tissues in tissue engineering and 3D cell culture is an innovative technique for developing in vitro culture models that mimic the in vivo environment. Especially compared to in vivo models, in vitro models were more ethical and cost-effective, and they stimulate tissue growth. This article discusses the use of sodium alginate (SA) in tissue engineering, focusing on SA modification techniques and providing a comparative examination of the properties of several SA-based hydrogels. This review also covers hydrogel preparation techniques, and a catalogue of patents covering different hydrogel formulations is also discussed. Finally, SA-based hydrogel applications and future research areas concerning SA-based hydrogels in tissue engineering were examined.
Application of Silk-Fibroin-Based Hydrogels in Tissue Engineering
Authors: Lyu Yihan , Liu Yusheng , He Houzhe , Wang Hongmei
Published: May 2023

Silk fibroin (SF) is an excellent protein-based biomaterial produced by the degumming and purification of silk from cocoons of the Bombyx mori through alkali or enzymatic treatments. SF exhibits excellent biological properties, such as mechanical properties, biocompatibility, biodegradability, bioabsorbability, low immunogenicity, and tunability, making it a versatile material widely applied in biological fields, particularly in tissue engineering. In tissue engineering, SF is often fabricated into hydrogel form, with the advantages of added materials. SF hydrogels have mostly been studied for their use in tissue regeneration by enhancing cell activity at the tissue defect site or counteracting tissue-damage-related factors. This review focuses on SF hydrogels, firstly summarizing the fabrication and properties of SF and SF hydrogels and then detailing the regenerative effects of SF hydrogels as scaffolds in cartilage, bone, skin, cornea, teeth, and eardrum in recent years.