bluuebunny/crossref_metadata_2025 huggingface dataset:
Integration of Blended Learning in the Advent of COVID-19: Online Learning Experiences of the Science Foundation Students
Authors: Zitha Innocent , Mokganya Mokgaetji Georgina , Manyage Tshidaho
Published: July 2023

Blended learning has become immensely integrated in contemporary times owing to the emergence of COVID-19. Consequently, it was seen as an effective approach to meet the accelerated demands of the diverse student population in universities and colleges. The rapid progress of the online world has made it essential to switch from face-to-face to online space. However, first-year Science Foundation students appear to encounter challenges using various learning platforms. While the demands of the online spectrum have changed due to the advent of COVID-19, this paper aimed to assess student participation and experience while teaching online on numerous platforms including Microsoft Teams, Google Teams, Moodle, and WhatsApp. The qualitative approach was employed to obtain descriptive data which was later quantified. Semi-structured questionnaires were used to conduct interviews with a total of 120 Science Foundation students at the University of Venda in the academic year 2021 to obtain the students’ online learning experiences. The findings of this study showed that due to the variety of online platforms used in the various modules, the students are unable to interact with the lecturers since the online learning platforms were quite new and tricky to navigate through. In addition, the researchers tried to fill the gap and implement strategies for effectively engaging pedagogy on online platforms. Students’ experiences were related to poor network connectivity, computer illiteracy, difficulty adapting to the Moodle platform, intermittent home learning environment, lack of interaction, and heavy workload. There is a need for a holistic understanding of how technology has transformed the teaching and training landscape to enable academics and students to stay relevant in a rapidly evolving educational landscape.
Application of the Relative Orbit in an On-Orbit Service Mission
Authors: Li Xuehua , Zhang Lei , Li Zhijun , He Xingsuo
Published: July 2023

To achieve an on-orbit service mission, the mission spacecraft must approach the target spacecraft first, which is based on the spacecraft’s relative motion. To enhance the safety and reliability of on-orbit service missions, the relative hovering orbit was proposed and needed to be studied further. A high-precision design method for hovering orbit is presented based on the relative dynamics model of spacecraft in this paper. Firstly, based on the stability analysis of the spacecraft relative dynamics model, a method to determine the initial value of periodic relative motion orbit is explored, and an example is given to verify the validity of the method. Then, through theoretical analysis, the formulae of control acceleration required during the hovering flying mission were put forward for both without considering perturbation and with considering J2 perturbation, and numerical simulations for hovering orbit were made to verify the feasibility of the approaches proposed. Simulation results show that the control acceleration curves are smooth, which indicates that the hovering flying mission is easier to achieve, and the control method based on sliding mode control theory is adopted for hovering control. The relative hovering method proposed can provide references in space on-orbit service missions for practical engineers.
Robust Optimization with Interval Uncertainties Using Hybrid State Transition Algorithm
Authors: Zhang Haochuan , Han Jie , Zhou Xiaojun , Zheng Yuxuan
Published: July 2023

Robust optimization is concerned with finding an optimal solution that is insensitive to uncertainties and has been widely used in solving real-world optimization problems. However, most robust optimization methods suffer from high computational costs and poor convergence. To alleviate the above problems, an improved robust optimization algorithm is proposed. First, to reduce the computational cost, the second-order Taylor series surrogate model is used to approximate the robustness indices. Second, to strengthen the convergence, the state transition algorithm is studied to explore the whole search space for candidate solutions, while sequential quadratic programming is adopted to exploit the local area. Third, to balance the robustness and optimality of candidate solutions, a preference-based selection mechanism is investigated which effectively determines the promising solution. The proposed robust optimization method is applied to obtain the optimal solutions of seven examples that are subject to decision variables and parameter uncertainties. Comparative studies with other robust optimization algorithms (robust genetic algorithm, Kriging metamodel-assisted robust optimization method, etc.) show that the proposed method can obtain accurate and robust solutions with less computational cost.
DEGAN: Decompose-Enhance-GAN Network for Simultaneous Low-Light Image Lightening and Denoising
Authors: Zhang Jialiang , Ji Ruiwen , Wang Jingwen , Sun Hongcheng , Ju Mingye
Published: July 2023

Images taken in low-light situations frequently have a significant quality reduction. Taking care of these degradation problems in low-light images is essential for raising their visual quality and enhancing high-level visual task performance. However, because of the inherent information loss in dark images, conventional Retinex-based approaches for low-light image enhancement frequently fail to accomplish real denoising. This research introduces DEGANet, a revolutionary deep-learning framework created particularly for improving and denoising low-light images. To overcome these restrictions, DEGANet makes use of the strength of a Generative Adversarial Network (GAN). The Decom-Net, Enhance-Net, and an Adversarial Generative Network (GAN) are three linked subnets that make up our novel Retinex-based DEGANet architecture. The Decom-Net is in charge of separating the reflectance and illumination components from the input low-light image. This decomposition enables Enhance-Net to effectively enhance the illumination component, thereby improving the overall image quality. Due to the complicated noise patterns, fluctuating intensities, and intrinsic information loss in low-light images, denoising them presents a significant challenge. By incorporating a GAN into our architecture, DEGANet is able to effectively denoise and smooth the enhanced image as well as retrieve the original data and fill in the gaps, producing an output that is aesthetically beautiful while maintaining key features. Through a comprehensive set of studies, we demonstrate that DEGANet exceeds current state-of-the-art methods in both terms of image enhancement and denoising quality.
A Curriculum Learning Approach for Multi-Domain Text Classification Using Keyword Weight Ranking
Authors: Yuan Zilin , Li Yinghui , Li Yangning , Zheng Hai-Tao , He Yaobin , Liu Wenqiang , Huang Dongxiao , Wu Bei
Published: July 2023

Text classification is a well-established task in NLP, but it has two major limitations. Firstly, text classification is heavily reliant on domain-specific knowledge, meaning that a classifier that is trained on a given corpus may not perform well when presented with text from another domain. Secondly, text classification models require substantial amounts of annotated data for training, and in certain domains, there may be an insufficient quantity of labeled data available. Consequently, it is essential to explore methods for efficiently utilizing text data from various domains to improve the performance of models across a range of domains. One approach for achieving this is through the use of multi-domain text classification models that leverage adversarial training to extract domain-shared features among all domains as well as the specific features of each domain. After observing the varying distinctness of domain-specific features, our paper introduces a curriculum learning approach using a ranking system based on keyword weight to enhance the effectiveness of multi-domain text classification models. The experimental data from Amazon reviews and FDU-MTL datasets show that our method significantly improves the efficacy of multi-domain text classification models adopting adversarial learning and reaching state-of-the-art outcomes on these two datasets.
Fuzzing Technology Based on Information Theory for Industrial Proprietary Protocol
Authors: Che Xin , Geng Yangyang , Zhang Ge , Wang Mufeng
Published: July 2023

With the rapid development of the Industrial Internet of Things (IIoT), programmable logic controllers (PLCs) are becoming increasingly intelligent, leading to improved productivity. However, this also brings about a growing number of security vulnerabilities. As a result, efficiently identifying potential security vulnerabilities in PLCs has become a crucial research topic for security researchers. This article proposes a method for fuzzing industrial proprietary protocols to effectively identify security vulnerabilities in PLCs’ proprietary protocols. The aim of this study is to develop a protocol fuzzing approach that can uncover security vulnerabilities in PLCs’ proprietary protocols. To achieve this, the article presents a protocol structure parsing algorithm specifically designed for PLC proprietary protocols, utilizing information theory. Additionally, a fuzzing case generation algorithm based on genetic algorithms is introduced to select test cases that adhere to the format specifications of the proprietary protocol while exhibiting a high degree of mutation. The research methodology consists of several steps. Firstly, the proposed protocol structure parsing algorithm is used to analyze two known industrial protocols, namely Modbus TCP and S7Comm. The parsing results obtained from the algorithm are then compared with the correct results to validate its effectiveness. Next, the protocol structure parsing algorithm is applied to analyze the proprietary protocol formats of two PLC models. Finally, based on the analysis results, the PLCs are subjected to fuzzing. Overall, the proposed protocol fuzzing approach, incorporating the protocol structure parsing algorithm and the fuzzing case generation algorithm, successfully identifies two denial-of-service vulnerabilities in the PLCs’ proprietary protocols. Notably, one of these vulnerabilities is a zero-day vulnerability, indicating that it was previously unknown and undisclosed.
IoT-Enabled System for Detection, Monitoring, and Tracking of Nuclear Materials
Authors: Hernández-Gutiérrez Carlos A. , Delgado-del-Carpio Marcelo , Zebadúa-Chavarría Lizette A. , Hernández-de-León Héctor R. , Escobar-Gómez Elias N. , Quevedo-López Manuel
Published: July 2023

A low-cost embedded system for high-energy radiation detection applications was developed for national security proposes, mainly to detect nuclear material and send the detection event to the cloud in real time with tracking capabilities. The proof of concept was built with state-of-the-art electronics such as an adequate Si-based photodetector, a trans-impedance amplifier, an ARM Cortex M4 microcontroller with sufficient ADC capture capabilities, an ESP8266 Internet of Things (IoT) module, an optimized Message Queuing Telemetry Transport (MQTT) protocol, a MySQL data base, and a Python handler program. The system is able to detect alfa particles and send the nuclear detection events to the CloudMQTT servers. Moreover, the detection message records the date and time of the ionization event for the tracking application, and due to a particular MQTT-optimized protocol the message is sent with low latency. Furthermore, the designed system was validated with a standard radiation instrumentation preamplifier 109A system from ORTEC company, and more than one node was demonstrated with an internet connection employing a 20,000 bits/s CloudMQTT plan. Therefore, the design can be escalated to produce a robust big data multisensor network.
Extending the OSLC Standard for ECA-Based Automation
Authors: García-Grao Guillermo , Carrera Álvaro
Published: July 2023

Workflow automation is taking over software development systems, helping businesses increase efficiency, accelerate production, and adapt quickly to market changes. Combined with agile principles, it has given birth to the DevOps paradigm. However, practitioners often face an important issue known as vendor lock-in caused by the cost of tool replacement or migration to different platforms. This issue could be addressed by standardising service interfaces to facilitate their integration. Linked Data is an attractive choice for implementing such a standard without sacrificing versatility. Following this approach, the Open Services for Lifecycle Collaboration (OSLC) proposal aims to build an environment where services can interoperate using standard models. Therefore, this article proposes an extension of the existing OSLC specification, based on the Event-Condition-Action (ECA) model, for event-based interoperable automation. This extension enables a new path in the field of semantic automation for OSLC services, which allows the self-interaction of services among them and with human users. The article presents the key concepts of the proposed model and exemplifies its application in an automation scenario with two real-life services. The validation of the proposal has been carried out using established ontology evaluation methods, such as coverage and similarity metrics and competency questions.
Robust Optimal Scheduling of Integrated Energy Systems Considering the Uncertainty of Power Supply and Load in the Power Market
Authors: Zhao Lang , Zeng Yuan , Wang Zhidong , Li Yizheng , Peng Dong , Wang Yao , Wang Xueying
Published: July 2023

The integrated energy system is a complex energy system that involves multi-stakeholder and multi-energy coordinated operations. The key to improving its scale and sustainable development is to construct a better-integrated energy system dispatching method which is suitable for the power market. However, the randomness of the supply side and load side of the integrated energy system brings further challenges to system planning and scheduling. Therefore, the optimal scheduling method of an integrated energy system considering the uncertainty of supply and demand in the market environment is studied in this paper. Firstly, the uncertainty models of the supply side and load side of the integrated energy system are established. Then, the optimal scheduling model based on robust chance constraint is established. The reserve capacity constraint is set as a chance constraint with a certain confidence level to maximize the system profit in the power market. Finally, simulations show that the proposed method not only guarantees the robustness of the system but also improves the economy of the system. The method provides ideas for exploring the development mechanism and strategy of integrated energy systems in the electricity market environment.
Method of Determining the Temperature Characteristics of the Thermal and Electrical Properties of Conductive Materials on a Stand for Induction Heating
Authors: Zgraja Jerzy
Published: July 2023

In induction heating processes, knowledge of the charge material parameters, i.e., thermal conductivity and volumetric heat capacity, as well as resistivity and magnetic permeability, is important both at the stage of preparatory process simulations and during their implementation. The paper presents a measurement method for estimating the thermal diffusivity, volumetric heat capacity, and resistivity of the charge material as a function of temperature on a single measuring setup, using a generator for induction heating as the source of signals. The method is based on the study (for forced temperature levels) of the temperature responses of cylindrical samples of the test materials and the voltage induced in the designed measuring coil after short- or long-term step excitation impulses. The presented approach enabled the dedicated computer-controlled system to obtain the initial values of the searched parameters with an accuracy of several percent. The procedure constitutes an introductory step in the simultaneous determination of a set of searched characteristics, and, by performing measurements, significantly narrows the range of variability in the decision variables of the optimization process.
Computational Fluid Dynamics Analysis of Spray Cooling in Australia
Authors: Larpruenrudee Puchanee , Do Doan Khai , Bennett Nick S. , Saha Suvash C. , Ghalambaz Mohammad , Islam Mohammad S.
Published: July 2023

Spray cooling technology offers high levels of uniform heat removal with very low fluid volumes and has found recent application in relatively small-scale use cases. Since it is a complex process, research can enable spray cooling to be applied more widely and at larger scales, such as in HVAC, as a means to operate more efficiently. Weather conditions are one of the main parameters that directly affect the effectiveness of spray cooling. This study investigates the spray cooling performance for temperature and humidity conditions in six Australian cities. ANSYS Fluent (2021 R1) software is applied for the numerical simulation. The numerical model is first validated with the available literature before a numerical simulation is conducted to assess each city throughout the year. These include Adelaide, Brisbane, Darwin, Melbourne, Perth, and Sydney. The spray cooling pattern, temperature, and humidity distribution, as well as the evaporation effect on different regions in Australia, is simulated and analysed based on the CFD technique. The results from this study indicate that weather conditions influence spray cooling for all cities, especially in summer. Along the wind tunnel, the temperature significantly drops at the spray cooling area, while the humidity increases. Due to the effect of spray cooling inside the wind tunnel, the temperature at the outlet is still lower than the inlet for all cases. However, the humidity at the outlet is higher than the inlet for all cases.
Numerical Investigations for Vibration and Deformation of Power Transformer Windings under Short-Circuit Condition
Authors: Wang Jiawei , Xing Yijing , Ma Xikui , Zhao Zhiwei , Yang Lihui
Published: July 2023

The analysis of the dynamic process of winding destabilization under sudden short-circuit conditions is of great importance to accurately assess the short-circuit resistance of power transformers. Based on magneto-solid coupling, an axisymmetric model of the transformer and a 3D multilayer model of the transformer considering the support components are established, respectively, and the short-circuit electromagnetic force (EF) is simulated by using the finite element method. It is concluded that the middle layer of the winding is subjected to the larger radial EF, while the axial EF has a greater effect on the layers at both ends. Moreover, the impression of the preload force, aging temperatures, and the area share of spacers on the vibration and deformation of windings are studied under short-circuit conditions. The overall distribution of plastic strain and residual stress in the winding is symmetrical, and the maximum values occur in the lower region of the middle of the winding. Finally, considering the material properties of disks and insulating components, the cumulative effect of plastic deformation under multiple successive short-circuit shocks is calculated. Compared with the traditional axisymmetric model of transformer, the three-dimensional multilayer model of the transformer established in this paper is more suitable for the actual winding structure and the obtained results are more accurate.
Fine-Resolution Forest Height Estimation by Integrating ICESat-2 and Landsat 8 OLI Data with a Spatial Downscaling Method for Aboveground Biomass Quantification
Authors: Wang Yingxuan , Peng Yuning , Hu Xudong , Zhang Penglin
Published: July 2023

Rapid and accurate estimation of forest aboveground biomass (AGB) with fine details is crucial for effective forest monitoring and management, where forest height plays a key role in AGB quantification. In this study, we propose a random forest (RF)-based down-scaling method to map forest height and biomass at a 15-m resolution by integrating Landsat 8 OLI and Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) LiDAR data. ICESat-2 photon data are used to derive canopy parameters along 15-m segments, which are considered sample plots for the extrapolation of discrete forest height. Fourteen variables associated with spectral features, textual features and vegetation index are extracted from pan-sharpened Landsat 8 images. A regression function is established between these variables and ICESat-2-derived forest height to produce a 15-m continuous forest height distribution data based on the 30-m forest height product using the RF algorithm. Finally, a wall-to-wall forest AGB at 15-m spatial resolution is achieved by using an allometric model specific to the forest type and height. The Jilin Province in northeast China is taken as the study area, and the forest AGB estimation results reveal a density of 61.15 Mg/ha with a standard deviation of 89.46 Mg/ha. The R2 between our predicted forest heights and the ICESat-2-derived heights reaches 0.93. Validation results at the county scale demonstrate reasonable correspondence between the estimated AGB and reference data, with consistently high R2 value exceeding 0.65. This downscaling method provides a promising scheme to estimate spatial forest AGB with fine details and to enhance the accuracy of AGB estimation, which may facilitate carbon stock measurement and carbon cycle studies.
Estimation of Species-Scale Canopy Chlorophyll Content in Mangroves from UAV and GF-6 Data
Authors: Deng Liangchao , Chen Bowei , Yan Min , Fu Bolin , Yang Zhenyu , Zhang Bo , Zhang Li
Published: July 2023

The growth of mangroves is inhibited due to environmental degradation, and changes in the growing health of mangrove forests cause changes in internal physicochemical parameters. The canopy chlorophyll content is an important indicator to monitor the health status of mangroves. We study the effective inversion data sources and methods of mangrove health indicator parameters to monitor the health of mangrove ecosystems in typical areas of Beibu Gulf, Guangxi. In this study, we evaluated the capability of UAV, GF-6 data, and machine learning regression algorithms in estimating mangrove species-scale canopy chlorophyll content (CCC). Effective measures for mangrove pest and disease pressure, Sporobolus alterniflorus invasion, and anthropogenic risk are also explored, which are important for mangrove conservation and restoration. (1) We obtained several feature variables by constructing a combined vegetation index, and the most sensitive band of mangrove CCC was selected by the characteristic variable evaluation, and the CCC model at the mangrove species-scale was evaluated and validated. Through variable preferences, the feature variables with the highest contribution of Avicennia marina, Aegiceras corniculatum, Kandelia candel, and a collection of three categories of species in the UAV data were indices of RI35, MDATT413, RI35, and NDI35. (2) Random Forest, Gradient Boosting Regression Tree, and Extreme Gradient Boosting were evaluated using the root-mean-square error and coefficient of determination accuracy metrics. Extreme Gradient Boosting regression algorithms were evaluated for accuracy. In both UAV data and GF-6, RF achieved optimal results in inverse mangrove Aegiceras corniculatum species CCC, with higher stability and robustness in machine learning regressors. (3) Due to the sparse distribution of Kandelia candel in the study area and the low spatial resolution of the images, there is an increased possibility that individual image elements contain environmental noise, such as soil. Therefore, the level of CCC can effectively reflect the health status of mangroves and further reflect the increased possibility of the study area being exposed to risks, such as degradation. The establishment of the current protected areas and restoration of degraded ecosystems are effective measures to cope with the risks of mangrove pest and disease stress, invasion of Sporobolus alterniflorus, and anthropogenic activities, which are important for the protection and restoration of mangroves. This study provides an important data reference and risk warning for mangrove restoration and conservation.
Comparative Analysis of In Vitro Fermentation Parameters in Total Mixed Rations of Dairy Cows with Varied Levels of Defatted Black Soldier Fly Larvae (Hermetia illucens) as a Substitute for Soybean Meal
Authors: Kahraman Oğuzhan , Gülşen Nurettin , İnal Fatma , Alataş Mustafa Selçuk , İnanç Zekeriya Safa , Ahmed İbrar , Şişman Deniz , Küçük Atalay Enes
Published: July 2023

In this study, we compared the digestibility levels and in vitro fermentation parameters of total mixed rations (TMRs) containing 20% and 40% defatted black soldier fly (Hermetia illucens) larvae (BSF) as a substitute for soybean meal (SBM) in the basal ration (60% roughage/40% concentrated feed) of dairy cows. We evaluated the volatile fatty acid (VFA), total gas production, methane emission, ammonia, pH, carbon dioxide, in vitro dry matter digestibility (IVDMD), and neutral detergent fiber digestibility (IVNDFD) of the TMR0 (basal), TMR20 (20% BSF included), and TMR40 (40% BSF included) diets at the end of 24 and 48 h of incubation. Significantly lower levels of ammonia formation were found in the TMR20 and TMR40 groups at 24 and 48 h (p < 0.001). An increase in total VFA levels was observed in the TMR0 group at 24 h (p < 0.001). The highest IVDMD was determined in TMR20 and TMR40 at 24 h. The highest IVNDFD value was observed in TMR20 at 24 h and in TMR40 at 48 h. The substitution of 20% and 40% of SBM with BSF positively affected IVDMD and IVNDFD (p < 0.001). TMR20 and TMR40 had the highest cumulative gas production at 48 h of incubation (p < 0.05). In conclusion, the use of BSF had a positive impact on digestibility and in vitro rumen fermentation. Therefore, we recommend the use of BSF in formulating dairy cow rations.
Influences of Aquaponics System on Growth Performance, Antioxidant Parameters, Stress Parameters and Gene Expression of Carassius auratus
Authors: Mao Hanping , Wang Bin , Zhao Jian , Wang Yafei , Du Xiaoxue , Shi Qiang
Published: July 2023

Aquaponics is a new type of composite farming system, which combines aquaculture and hydroponics through ecological design to achieve scientific synergism. However, the effects of aquaponics on the welfare status and stress parameters of fish are unclear. In this study, 150 crucian carp with an average initial body weight of 7.06 ± 0.32 g were selected. Nine fish were randomly selected as the control group (NC group and hypoxia group) for stress, antioxidant and gene expression parameters after acclimation and hypoxia stress, respectively. The remaining crucian carps were randomly divided into three experimental groups with 20 crucian carps in each group (T0, T1 and T2, respectively), with three replicates. The fresh weight of the lettuce root in the T2 group had no significant effect (p > 0.05). Compared with the control group (T0 and T1), there were significant differences in the specific growth rate, the weight gain rate, the fresh leaf weight, the chlorophyll content and the water quality parameters in group T2 (p < 0.05). Regarding the biochemical parameters, superoxide dismutase and catalase showed significant differences between the T2 and T1 groups (p < 0.05). At the same time, the HSP70 and Prdx3 genes were upregulated in the liver of the T2 group compared to the NC group and the hypoxia group. The research suggests that aquaponics may reduce the hypoxia stress of crucian carp without affecting the growth of crucian carp and lettuce.
Governing Distant-Water Fishing within the Blue Economy in Madagascar: Policy Frameworks, Challenges and Pathways
Authors: Andriamahefazafy Mialy
Published: July 2023

Madagascar’s vast oceanic space hosts distant-water fishing (DWF) fleets from Taiwan, Japan, South Korea, Spain, France and others since the 1960s, making DWF a substantial component of the blue economy. Considering this extensive experience of managing DWF activities for more than 60 years, this paper explores the existing policy frameworks and challenges regarding managing DWF. The results show while it is well equipped legally, the country is struggling to implement its national policies and laws while continuing to adopt new management frameworks. This is due to a limited coherence on long-term policy making and policy implementation, resulting in a mismatch between the two, and a paradoxical vision that promotes DWF without the means to monitor fishing activities and their impacts. The existing institutional settings and governance frameworks make change possible in Madagascar’s approach to DWF. To improve the management of DWF, this paper outlines four pathways. These include (i) a greater attention on the implementation, harmonisation and evaluation of existing policies and projects; (ii) continuing efforts on transparency for DWF operations and contract negotiations; (iii) realigning aspirations and policies with local needs; and (iv) taking better advantage of measures adopted at the regional Indian Ocean level to improve national management of DWF. An efficient implementation of an improved policy and legal framework could contribute to strengthening the governance of DWF activities toward sustaining national benefits while preserving coastal livelihoods.
The Effect of Nozzle Temperature on the Low-Temperature Printing Performance of Low-Viscosity Food Ink
Authors: Tong Qiang , Meng Yuxiang , Tong Yao , Wang Dequan , Dong Xiuping
Published: July 2023

Low-temperature food printing technology is used in many fields, such as personalized nutrition, cooking art, food design and medical nutrition. By precisely controlling the deposition temperature of the ink, a food with a finer and more controllable structure can be produced. This paper investigates the influence of nozzle temperature on printing performance via a numerical simulation and experimental research. The results indicate that the ink gradually changed from a granular state to a fLow-characteristic deposition structure when the nozzle temperature increased from 19 °C to 27 °C. When the nozzle temperature exceeded 21 °C, the ink demonstrated excellent extrusion behavior and tended to flow. The widths of the rectangular frame deposition showed no obvious changes and were 4.07 mm, 4.05 mm and 4.20 mm, respectively. The extrusion behavior of the ink showed a structural mutation in the temperature range of 19–21 °C. Its line width changed from 3.15 mm to 3.73 mm, and its deposition structure changed from a grainy shape to a normal shape. Under the influence of different environmental control capabilities, bulk structure deposition demonstrates an ideal printing performance at 21, 23 and 25 °C, and the latter temperature is more suitable in the case of large external interference. The ink flowed violently when the nozzle temperature reached 27 °C, at which point the deposit structure flowed and deformed seriously. On the other hand, evaporation losses had a strong effect on Low-viscosity ink. To reach the full potential of this promising technology, it is necessary to determine the effect of nozzle temperature on printing performance. This article provides a method for developing and applying Low-viscosity, Low-temperature food printing.
Bean Cuisine: The Potential of Citizen Science to Help Motivate Changes in Pulse Knowledge and Consumption
Authors: Didinger Chelsea , Bunning Marisa , Thompson Henry J.
Published: July 2023

Pulses, or the dry, edible seeds of non-oilseed legumes (e.g., chickpeas, cowpeas, dry beans, dry peas, and lentils), are uniquely positioned to simultaneously benefit human and environmental well-being, all while being affordable and important to diverse cultural food traditions around the world. Despite the benefits they can provide, pulses are dramatically under-consumed. One key barrier preventing higher intake among consumers is a lack of familiarity with how to prepare and regularly incorporate pulses into meals. To address this barrier and actualize findings from our laboratory, we created the Bean Cuisine, a 2-week cuisine (i.e., meal plan) with 56 pulse-centric recipes corresponding to 14 unique breakfast, lunch, snack, and dinner ideas. Each meal category was largely interchangeable, i.e., the order of the breakfast recipes is not important, and one could be swapped for another if a different order were preferrable to a consumer. Fifty-six citizen scientists were recruited to provide feedback on the Bean Cuisine. Free response feedback related to project participation was very positive, and common themes included changes in pulse consumption and cooking behaviors, increased awareness of pulse variety and versatility, and positive perceptions of citizen science. Overall, participation in the Bean Cuisine citizen science project helped create pulse advocates, empowering participants to advance the well-being of their communities through pulses.
A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging
Authors: Liu Yisen , Zhou Songbin , Wan Zhiyong , Qiu Zefan , Zhao Lulu , Pang Kunkun , Li Chang , Yin Zexuan
Published: July 2023

Hyperspectral imaging combined with chemometric approaches is proven to be a powerful tool for the quality evaluation and control of fruits. In fruit defect-detection scenarios, developing an unsupervised anomaly detection framework is vital, as defect sample preparation is labor-intensive and time-consuming, especially for exploring potential defects. In this paper, a spectral–spatial, information-based, self-supervised anomaly detection (SSAD) approach is proposed. During training, an auxiliary classifier is proposed to identify the projection axes of principal component (PC) images that were transformed from the hyperspectral data cubes. In test time, the fully connected layer of the learned classifier was used as a ‘spectral–spatial’ feature extractor, and the feature similarity metric was adopted as the score function for the downstream anomaly evaluation task. The proposed network was evaluated with two fruit data sets: a strawberry data set with bruised, infected, chilling-injured, and contaminated test samples and a blueberry data set with bruised, infected, chilling-injured, and wrinkled samples as anomalies. The results show that the SSAD yielded the best anomaly detection performance (AUC = 0.923 on average) over the baseline methods, and the visualization results further confirmed its advantage in extracting effective ‘spectral–spatial’ latent representation. Moreover, the robustness of SSAD is verified with the data pollution experiment; it performed significantly better than the baselines when a portion of anomalous samples was involved in the training process.
Development of a Sensitive SERS Method for Label-Free Detection of Hexavalent Chromium in Tea Using Carbimazole Redox Reaction
Authors: Yin Limei , Jayan Heera , Cai Jianrong , El-Seedi Hesham R. , Guo Zhiming , Zou Xiaobo
Published: July 2023

Tea plants absorb chromium-contaminated soil and water and accumulate in tea leaves. Hexavalent chromium (Cr6+) is a very toxic heavy metal; excessive intake of tea containing Cr6+ can cause serious harm to human health. A reliable and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed using Au@Ag nanoparticles as an enhanced substrate for the determination of Cr6+ in tea. The Au@AgNPs coated with carbimazole showed a highly selective reaction to Cr6+ in tea samples through a redox reaction between Cr6+ and carbimazole. The Cr6+ in the contaminated tea sample reacted with methimazole—the hydrolysate of carbimazole—to form disulfide, which led to the decrease in the Raman intensity of the peak at 595 cm−1. The logarithm of the concentration of Cr6+ has a linear relationship with the Raman intensity at the characteristic peak and showed a limit of detection of 0.945 mg/kg for the tea sample. The carbimazole functionalized Au@AgNPs showed high selectivity in analyzing Cr6+ in tea samples, even in the presence of other metal ions. The SERS detection technique established in this study also showed comparable results with the standard ICP-MS method, indicating the applicability of the established technique in practical applications.
Molecular and Genetic Characterization of Colicinogenic Escherichia coli Strains Active against Shiga Toxin-Producing Escherichia coli O157:H7
Authors: García Mauro D. , Ruiz María J. , Medina Luis M. , Vidal Roberto , Padola Nora L. , Etcheverria Analía I.
Published: July 2023

The objective of this work was to molecularly and genotypically characterize and test the inhibitory activity of six colicinogenic Escherichia coli strains (ColEc) and their partially purified colicins against STEC O157:H7 isolated from clinical human cases. Inhibition tests demonstrated the activity of these strains and their colicins against STEC O157:H7. By PCR it was possible to detect colicins Ia, E7, and B and microcins M, H47, C7, and J25. By genome sequencing of two selected ColEc strains, it was possible to identify additional colicins such as E1 and Ib. No genes coding for stx1 and stx2 were detected after analyzing the genome sequence. The inhibitory activity of ColEc against STEC O157:H7 used as an indicator showed that colicins are potent growth inhibitors of E. coli O157:H7, being a potential alternative to reduce the presence of pathogens of public health relevance.
Microbiota Composition during Fermentation of Broomcorn Millet Huangjiu and Their Effects on Flavor Quality
Authors: Wang Ke , Wu Huijun , Wang Jiaxuan , Ren Qing
Published: July 2023

Broomcorn millet Huangjiu brewing is usually divided into primary fermentation and post-fermentation. Microbial succession is the major factor influencing the development of the typical Huangjiu flavor. Here, we report the changes in flavor substances and microbial community during the primary fermentation of broomcorn millet Huangjiu. Results indicated that a total of 161 volatile flavor compounds were measured during primary fermentation, and estragole was detected for the first time in broomcorn millet Huangjiu. A total of 82 bacteria genera were identified. Pediococcus, Pantoea, and Weissella were the dominant genera. Saccharomyces and Rhizopus were dominant among the 30 fungal genera. Correlation analysis showed that 102 microorganisms were involved in major flavor substance production during primary fermentation, Lactobacillus, Photobacterium, Hyphodontia, Aquicella, Erysipelothrix, Idiomarina, Paraphaeosphaeria, and Sulfuritalea were most associated with flavoring substances. Four bacteria, Lactobacillus (R1), Photobacterium (R2), Idiomarina (R3), and Pediococcus (R4), were isolated and identified from wheat Qu, which were added to wine Qu to prepare four kinds of fortified Qu (QR1, QR2, QR3, QR4). QR1 and QR2 fermentation can enhance the quality of Huangjiu. This work reveals the correlation between microorganisms and volatile flavor compounds and is beneficial for regulating the micro-ecosystem and flavor of the broomcorn millet Huangjiu.
Novel Hydrophilic Oligomer-Crosslinked Gelatin-Based Hydrogels for Biomedical Applications
Authors: Tariq Mamoona , Khokhar Rabia , Javed Arslan , Usman Muhammad , Anjum Syed Muhammad Muneeb , Rasheed Huma , Bukhari Nadeem Irfan , Yan Chao , Nawaz Hafiz Awais
Published: July 2023

Gelatin-based hydrogels have shown good injectability and biocompatibility and have been broadly used for drug delivery and tissue regeneration. However, their low mechanical strengths and fast degradation rates must be modified for long-term implantation applications. With an aim to develop mechanically stable hydrogels, reactive anhydride-based oligomers were developed and used to fabricate gelatin-based crosslinked hydrogels in this study. A cascade of hydrophilic oligomers containing reactive anhydride groups was synthesized by free radical polymerization. These oligomers varied in degree of reactivity, comonomer composition, and showed low molecular weights (Mn < 5 kDa). The reactive oligomers were utilized to fabricate hydrogels that differed in their mechanical strengths and degradation profiles. These formulations exhibited good cytocompatibility with human adipose tissue-derived stem cells (hADCs). In conclusion, the reactive MA-containing oligomers were successfully synthesized and utilized for the development of oligomer-crosslinked hydrogels. Such oligomer-crosslinked gelatin-based hydrogels hold promise as drug or cell carriers in various biomedical applications.
Cilia and Cancer: From Molecular Genetics to Therapeutic Strategies
Authors: Carotenuto Pietro , Gradilone Sergio A. , Franco Brunella
Published: July 2023

Cilia are microtubule-based organelles that project from the cell surface with motility or sensory functions. Primary cilia work as antennae to sense and transduce extracellular signals. Cilia critically control proliferation by mediating cell-extrinsic signals and by regulating cell cycle entry. Recent studies have shown that primary cilia and their associated proteins also function in autophagy and genome stability, which are important players in oncogenesis. Abnormal functions of primary cilia may contribute to oncogenesis. Indeed, defective cilia can either promote or suppress cancers, depending on the cancer-initiating mutation, and the presence or absence of primary cilia is associated with specific cancer types. Together, these findings suggest that primary cilia play important, but distinct roles in different cancer types, opening up a completely new avenue of research to understand the biology and treatment of cancers. In this review, we discuss the roles of primary cilia in promoting or inhibiting oncogenesis based on the known or predicted functions of cilia and cilia-associated proteins in several key processes and related clinical implications.
Ghost Mines for Geoheritage Enhancement in the Umbria Region (Central Italy)
Authors: Melelli Laura , Palombo Massimo , Nazzareni Sabrina
Published: July 2023

The paper proposes a method to valorize abandoned mines whose traces were lost in the territory and in the collective memory. We selected two case studies in the Umbria region (central Italy) that were used as examples. The evidence of the presence of lignite mines on the Upper Tiber River Valley (northern Umbria) has been completely erased, and since they were located in rural areas, they represent an interesting challenge regarding recovering the memory of the places and proposing a no-longer-existent site as a geosite. The recovery and valorization of historical documents of the two lignite mines (Caiperino–Terranera and Carsuga) and their conversion into a digital format was carried out before constructing a geolocalized database in a GIS environment. This framework is the starting point for a promising dissemination process via a digital media app, using multimedia contents as video, 3D models and the principles of augmented reality (AR) to enhance the touristic or didactic experience and promote the cultural heritage of the territory by keeping the memory of ’ghost places’.
Association between Sexual Activity during Pregnancy, Pre- and Early-Term Birth, and Vaginal Cytokine Inflammation: A Prospective Study of Black Women
Authors: Dougherty Kylie , Zhao Yihong , Dunlop Anne L. , Corwin Elizabeth
Published: July 2023

This study aimed to investigate the association between sexual activity during pregnancy and adverse birth outcomes among Black women, and to explore whether vaginal cytokine inflammation mediates this association. Data from 397 Black pregnant women through questionnaires on sexual activity and vaginal biosamples during early (8–14 weeks) and late (24–30 weeks) pregnancy, and birth outcomes were analyzed. Using a data-driven approach, the study found that vaginal sex during late pregnancy was associated with spontaneous early-term birth (sETB, 38–39 completed weeks’ gestation) (OR = 0.39, 95% CI: [0.21, 0.72], p-value = 0.003) but not with spontaneous preterm birth (sPTB) (OR = 1.08, p-value = 0.86) compared to full-term birth. Overall, despite vaginal sex in late pregnancy showing an overall positive effect on sETB (total effect = −0.1580, p-value = 0.015), we observed a negative effect of vaginal sex on sETB (indirect effect = 0.0313, p-value = 0.026) due to the fact that having vaginal sex could lead to elevated IL6 levels, which in turn increased the odds of sETB. In conclusion, the study found an overall positive association between sexual activity on ETB and a negative partial mediation effect via increased vaginal cytokine inflammation induced by vaginal sexual activity. This inconsistent mediation model suggested that vaginal sexual activity is a complex behavior that could have both positive and negative effects on the birth outcome.
Application of SHAP for Explainable Machine Learning on Age-Based Subgrouping Mammography Questionnaire Data for Positive Mammography Prediction and Risk Factor Identification
Authors: Sun Jeffrey , Sun Cheuk-Kay , Tang Yun-Xuan , Liu Tzu-Chi , Lu Chi-Jie
Published: July 2023

Mammography is considered the gold standard for breast cancer screening. Multiple risk factors that affect breast cancer development have been identified; however, there is an ongoing debate regarding the significance of these factors. Machine learning (ML) models and Shapley Additive Explanation (SHAP) methodology can rank risk factors and provide explanatory model results. This study used ML algorithms with SHAP to analyze the risk factors between two different age groups and evaluate the impact of each factor in predicting positive mammography. The ML model was built using data from the risk factor questionnaires of women participating in a breast cancer screening program from 2017 to 2021. Three ML models, least absolute shrinkage and selection operator (lasso) logistic regression, extreme gradient boosting (XGBoost), and random forest (RF), were applied. RF generated the best performance. The SHAP values were then applied to the RF model for further analysis. The model identified age at menarche, education level, parity, breast self-examination, and BMI as the top five significant risk factors affecting mammography outcomes. The differences between age groups ranked by reproductive lifespan and BMI were higher in the younger and older age groups, respectively. The use of SHAP frameworks allows us to understand the relationships between risk factors and generate individualized risk factor rankings. This study provides avenues for further research and individualized medicine.
Immediate Effects of Foam Roller and Stretching to the Lead Hip on Golfers Swing: A Randomized Crossover Trial
Authors: Hamada Yuji , Akasaka Kiyokazu , Otsudo Takahiro , Sawada Yutaka , Hattori Hiroshi , Hasebe Yuki , Kikuchi Yuto , Hall Toby
Published: July 2023

Golfers with decreased range of motion (ROM) of their leading hip internal rotation (IR) have increased lumbar rotation ROM and load. This study investigated the effects of foam roller (FR) applied to their leading hip muscles combined with stretching to the leading hip together with lumbar rotation ROM during the golf swing. The study design was a crossover design. Subjects were allocated to one of two groups comprising FR and dynamic stretching (FR + DS) or practice swing. Motion analysis was used to evaluate hip and lumbar angles during the golf swing. Data were compared using analysis of variance with Bonferroni correction using paired t-test’s post hoc. The association between lead hip IR angle and lumbar spine left rotation (Lrot) angle was investigated using correlation analysis. Lead hip IR ROM during the golf swing was significantly greater in the FR + DS group (p = 0.034). The FR + DS group showed a moderate negative correlation between lead hip IR ROM and lower lumbar spine Lrot ROM during the golf swing (r = −0.522). The application of FR + DS might be useful to increase lead hip IR angle during the golf swing. Moreover, the application of FR + DS improves lead hip IR angle and may decrease lumbar spine rotation.