bluuebunny/crossref_metadata_2025 huggingface dataset:
Individualized and Innovation-Centered General Education in a Chinese STEM University
Authors: Li Xu , Li Yuan
Published: August 2023

The concept and practice of general education have been widely discussed and debated in the Euro-American world, but its adaptation in China needs further discussion and understanding. Over the past decade, its impact on Chinese higher education is increasingly salient, with a large number of Chinese first-tier universities claiming to initiate general education reforms to their previously narrowly focused undergraduate programs. This paper explores the development, implementation, and support of general education in a new type of research university in China from an organizational perspective. Through a case study of the Southern University of Science and Technology (SUSTech) prior to the COVID-19 pandemic, this paper examines SUSTech’s individualized and innovation-based general education system, highlighting its institution-wide approach and innovation-centered perspective. The findings underscore the importance of integrating general education principles throughout the university to foster self-directed thinkers and cultivate students’ self-awareness, interests, and passions. This study also reveals how general education is used as an organizational solution to address a variety of historical and complicated issues that challenge Chinese universities. This research serves as a catalyst for reform and innovation in Chinese higher education, inspiring transformative practices that meet the evolving needs of students and society.
Trust, Transgression and Surrender: Exploring Teacher and SEND Student Perceptions of Engagement with Creative Arts Project-Based Learning (CAPBL) Pedagogies
Authors: Tarling James
Published: August 2023

CAPBL is an example of a student-led, Creative Arts/Project-Based Learning (CAPBL/PBL) curriculum approach to working with Special Educational Needs and Disabilities (SEND) learners. This mixed-methods, quasi-experimental study seeks to explore staff and student perceptions of working in this way and establish key themes for practice in relation to equity and inclusion. Although the literature on PBL is widespread, CAPBL is novel in that it brings these ideas to a specialist SEND, post-16 context, Further Education (FE), with a particular focus on arts education currently absent from the existing literature. This small-scale research project is positioned as a participant-led action research project involving qualitative/quantitative mixed-method instruments, bassline testing, questionnaires, and semi-structured interviews. Preliminary findings indicate that students and staff experience several benefits to working this way, including positive engagement with learning, self-efficacy, and ownership. This paper attempts to provide workable conclusions for practice located within theoretical frameworks that offer professional resistance to prevailing preoccupations with prescription in curriculum design and pedagogy both nationally and internationally. Specifically, civic compassion and pedagogical partnership are considered in relation to the experiences of learners and staff attempting to work this way. By challenging dominant paradigms of knowledge-led learning at a national level, CAPBL seeks to actively include SEND learners in the global processes of curriculum design itself.
An Intelligent Detection Method for Approach Distances of Large Construction Equipment in Substations
Authors: Wang Leixiong , Wang Bo , Zhang Jiaxin , Ma Hengrui , Luo Peng , Yin Tianrui
Published: August 2023

The safe approach distance detection of large construction equipment in substations is important to ensure the safety and stability of the power system, as well as to prevent equipment damage, power outages and other accidents. The current method is unable to intelligently distinguish construction equipment from power equipment and realize real-time safety approach distance detection. Therefore, this paper constructs a safety approach distance detection system for large-scale construction equipment in substations based on stereo vision and target detection, and realizes real-time high-precision safe approach distance detection between large-scale construction equipment and electric power equipment. Firstly, the system distinguishes construction equipment from power equipment using a GhostNet-based substation construction target detection model. Secondly, the system obtains spatial information regarding the operation scene using a lightweight stereo matching model based on channel attention, then calculates the spatial surface center of the target based on the spatial information and detection results, and finally calculates the safety approach distance between construction equipment and power equipment. Compared with MobileNetv3-YOLOv4, the map and the recall rate of the proposed method are improved by 13.1% and 29.0%; compared with the AnyNet stereo matching method, the proposed method decreases the end point error and 3 pixels error by 34.2% and 25.8%. The actual data show that the detection speed of the proposed method is 19.35 frames per second, and the mean absolute error is 0.942 m and the mean relative error is 3.802%. This method can accurately measure the safe approach distance in real time in real scenarios to guarantee the safety of personnel and equipment.
A Novel Unit Classification Method for Fast and Accurate Calculation of Radiation Patterns
Authors: Zhou Hao , Li Jiren , Wei Kun
Published: August 2023

This paper proposes a novel unit classification technique to enhance the accuracy of the conventional pattern multiplication method by taking the mutual coupling effect and edge effect into consideration. The proposed technique classifies antenna elements into different groups based on their positions in arrays, specifically corner, edge, and inner groups. By simulating the radiation patterns of antenna elements with different boundary conditions, the pattern multiplication method is then used to calculate the radiation pattern of the antenna array based on the simulated results. Several numerical examples, including a square array, a hexagonal array, and a phased array, are provided to validate the effectiveness of the proposed method. The numerical results demonstrate that the proposed method not only reduces the computational time and memory usage but also significantly improves the accuracy. The proposed method provides a powerful tool for synthesizing and predicting the radiation pattern of array antennas and offers new avenues for optimizing array antennas and phased array antennas.
Context-Dependent Multimodal Sentiment Analysis Based on a Complex Attention Mechanism
Authors: Deng Lujuan , Liu Boyi , Li Zuhe , Ma Jiangtao , Li Hanbing
Published: August 2023

Multimodal sentiment analysis aims to understand people’s attitudes and opinions from different data forms. Traditional modality fusion methods for multimodal sentiment analysis con-catenate or multiply various modalities without fully utilizing context information and the correlation between modalities. To solve this problem, this article provides a new model based on a multimodal sentiment analysis framework based on a recurrent neural network with a complex attention mechanism. First, after the raw data is preprocessed, the numerical feature representation is obtained using feature extraction. Next, the numerical features are input into the recurrent neural network, and the output results are multimodally fused using a complex attention mechanism layer. The objective of the complex attention mechanism is to leverage enhanced non-linearity to more effectively capture the inter-modal correlations, thereby improving the performance of multimodal sentiment analysis. Finally, the processed results are fed into the classification layer and the sentiment output is obtained using the classification layer. This process can effectively capture the semantic information and contextual relationship of the input sequence and fuse different pieces of modal information. Our model was tested on the CMU-MOSEI datasets, achieving an accuracy of 82.04%.
Low-Light Image Contrast Enhancement with Adaptive Noise Attenuator for Augmented Vehicle Detection
Authors: Yoon Sungan , Cho Jeongho
Published: August 2023

The rapid progress in deep learning technologies has accelerated the use of object detection models, but most models do not operate satisfactorily in low-light environments. As a result, many studies have been conducted on image enhancement techniques aiming to make objects more visible by increasing contrast, but the process of image enhancement may negatively impact detection as it further strengthens unwanted noises due to indirect factors of light reflection such as overall low brightness, streetlamps, and neon signboards. Therefore, in this study, we propose a technique for improving the performance of object detection in low-light environments. The proposed technique inverts a low-light image to make it similar to a hazy image and then uses a haze removal algorithm based on entropy and fidelity to increase image contrast, clarifying the boundary between the object and the background. In the next step, we used the adaptive 2D Wiener filter (A2WF) to attenuate the noise accidentally strengthened during the image enhancement process and reinforced the boundary between the object and the background to increase detection performance. The test evaluation results showed that the proposed image enhancement scheme significantly increased image perception performance with the perception-based image quality evaluator being 12.73% lower than existing image enhancement techniques. In a comparison of vehicle detection performance, the proposed technique for enhancing nighttime images combined with the detection model proved its effectiveness by increasing the average precision by up to 18.63% against existing detection methods.
Research on Earthquake Data Prediction Method Based on DIN–MLP Algorithm
Authors: An Zhaoliang , Si Guannan , Tian Pengxin , Li Jianxin , Liang Xinyu , Zhou Fengyu , Wang Xiaoliang
Published: August 2023

This paper proposes a recommendation algorithm that combines MLP with the DIN model and conducts simulation experiments in the field of earthquake missing data prediction. The original DIN model may face challenges and weaknesses in earthquake monitoring data prediction, such as a limited capability in handling data loss or anomalies in seismic monitoring stations. To overcome these issues, we innovatively treat seismic monitoring stations as special users and historical data patterns as recommended items. Based on the DIN model, we implement data processing and prediction for seismic monitoring stations and introduce an attention mechanism based on MLP neural networks in the model, while leveraging the prior knowledge base to enhance predictive capabilities. Compared to the original DIN model, our proposed approach not only recommends sequence combinations that meet the demands of seismic monitoring stations but also enhances the matching between station behavior attributes and historical data characteristics, thereby significantly improving prediction accuracy. To validate the effectiveness of our method, we conducted comparative experiments. The results show that the GAUC achieved by the DIN–MLP model reaches 0.69, which is an 11 percent point improvement over the original DIN model. This highlights the remarkable advantages of our algorithm in earthquake missing data prediction. Furthermore, our research reveals the potential of the DIN–MLP algorithm in practical applications, providing more accurate data processing and time series combination recommendations for the field of earthquake monitoring stations, thus contributing to the improvement of monitoring efficiency and accuracy.
Internal Detection of Ground-Penetrating Radar Images Using YOLOX-s with Modified Backbone
Authors: Zheng Xibin , Fang Sinan , Chen Haitao , Peng Liang , Ye Zhi
Published: August 2023

Geological radar is an important method used for detecting internal defects in tunnels. Automatic interpretation techniques can effectively reduce the subjectivity of manual identification, improve recognition accuracy, and increase detection efficiency. This paper proposes an automatic recognition approach for geological radar images (GPR) based on YOLOX-s, aimed at accurately detecting defects and steel arches in any direction. The method utilizes the YOLOX-s neural network and improves the backbone with Swin Transformer to enhance the recognition capability for small targets in geological radar images. To address irregular voids commonly observed in radar images, the CBAM attention mechanism is incorporated to improve the accuracy of detection annotations. We construct a dataset using field detection data that includes targets of different sizes and orientations, representing “voids” and “steel arches”. Our model tackles the challenges of traditional GPR image interpretation and enhances the automatic recognition accuracy and efficiency of radar image detection. In comparative experiments, our improved model achieves a recognition accuracy of 92% for voids and 94% for steel arches, as evaluated on the constructed dataset. Compared to YOLOX-s, the average precision is improved by 6.51%. These results indicate the superiority of our model in geological radar image interpretation.
Blockchain and Machine Learning-Based Hybrid IDS to Protect Smart Networks and Preserve Privacy
Authors: Mishra Shailendra
Published: August 2023

The cyberspace is a convenient platform for creative, intellectual, and accessible works that provide a medium for expression and communication. Malware, phishing, ransomware, and distributed denial-of-service attacks pose a threat to individuals and organisations. To detect and predict cyber threats effectively and accurately, an intelligent system must be developed. Cybercriminals can exploit Internet of Things devices and endpoints because they are not intelligent and have limited resources. A hybrid decision tree method (HIDT) is proposed in this article that integrates machine learning with blockchain concepts for anomaly detection. In all datasets, the proposed system (HIDT) predicts attacks in the shortest amount of time and has the highest attack detection accuracy (99.95% for the KD99 dataset and 99.72% for the UNBS-NB 15 dataset). To ensure validity, the binary classification test results are compared to those of earlier studies. The HIDT’s confusion matrix contrasts with previous models by having low FP/FN rates and high TP/TN rates. By detecting malicious nodes instantly, the proposed system reduces routing overhead and has a lower end-to-end delay. Malicious nodes are detected instantly in the network within a short period. Increasing the number of nodes leads to a higher throughput, with the highest throughput measured at 50 nodes. The proposed system performed well in terms of the packet delivery ratio, end-to-end delay, robustness, and scalability, demonstrating the effectiveness of the proposed system. Data can be protected from malicious threats with this system, which can be used by governments and businesses to improve security and resilience.
An Efficient Bidirectional DC Circuit Breaker Capable of Regenerative Current Breaking for DC Microgrid Application
Authors: Hasan Md Mahmudul , Hiung Lo Hai , Kannan Ramani , Lumen S. M. Sanzad
Published: August 2023

The direct current circuit breaker (DCCB) is extensively employed in DC microgrid applications to protect the network during faults. However, numerous DC converters are combined in parallel to form a DC microgrid, which creates a large network inductance. The grid stores energy during regular operation, which repels instantaneous current breaking, and this stored energy needs to be eliminated after current breaking. Conventional topologies use different energy absorption methods to dissipate the stored energy after breaking the current. In this paper, an efficient bidirectional DC circuit breaker (EBDCCB) topology is introduced to extract and reuse this energy instead of dissipating it. The proposed topology has bidirectional power flow capability to meet the requirements of DC microgrid applications as energy storage devices are frequently utilized. Furthermore, EBDCCB shows drastically improved performance in terms of current breaking time, voltage stress, regenerated average current, and energy recovery efficiency compared to the conventional DCCB topology. The mathematical modeling and sizing of the components used in the proposed EBDCCB are elaborately analyzed, and detailed performance testing is presented along with extensive PSIM software simulation. Additionally, an experimental investigation is conducted on a laboratory-scale 48 V/1 A prototype.
Measuring the Impact of ChatGPT on Fostering Concept Generation in Innovative Product Design
Authors: Filippi Stefano
Published: August 2023

The growing demand for innovative and user-centric product design has led to a growing need for effective idea generation methods. In recent years, natural language processing (NLP) tools such as ChatGPT have emerged as a promising solution for supporting idea generation in various domains. This paper investigates a framework for studying the role of ChatGPT in facilitating the ideation process in product design. This investigation measures the impact of ChatGPT on the generation of innovative concepts compared to the use of “classic” design methods. An overview of the state-of-the-art idea generation methods in product design opens the paper. Then, the paper highlights some hypotheses about the impact of ChatGPT on innovative product design, aiming for product augmentation by adding features. The paper then describes the design experience in which ChatGPT is used as a tool for concept generation. Finally, the paper analyzes the dataset, using precise metrics to characterize the participants’ performance and compare them. This analysis allows the paper to argue about the validation/rejection of the hypotheses. The paper concludes with a discussion of the implications of the findings and some suggestions for future research. Along with the paper, the Microsoft Excel workbook used to perform the data analysis is available to the readers to perform their own data collection and analysis. The workbook UX has been carefully studied and developed to make it usable by anyone. At the same time, it should be flexible enough to manage several situations characterized by different numbers of participants, product functions to implement, and generated concepts.
Heterogeneous Activation of Persulfate by Nickel Oxide/Strontium Carbonate Composite for Sulfamethoxazole Degradation in Water
Authors: Skempi Despoina Jessica , Kouvelis Konstantinos , Petala Athanasia , Bampos Georgios , Frontistis Zacharias
Published: August 2023

The development of efficient heterogeneous persulfate activators is one of the main research topics in the wastewater treatment area. The present work deals with the heterogeneous activation of sodium persulfate (SPS) using nickel oxide/strontium carbonate (NiO/SrCO3) for the degradation of sulfamethoxazole (SMX), a representative compound from the group of antibiotics. Results showed that NiO/SrCO3 exhibited high performance towards the activation of SPS, leading to SMX elimination in brief time spans. The impact of SPS (25–100 mg/L), NiO/SrCO3 (50–250 mg/L), and SMX (0.25–3.00 mg/L) concentration, and initial pH on the decomposition of SMX was further examined. Experiments were also conducted in real matrices such as secondary effluent and bottled water, revealing the existence of retarding phenomena compared to ultrapure water. This behavior was further investigated with the addition of bicarbonates, chlorides, or humic acid in ultrapure water. It was found that organic matter significantly hampered SMX removal. The role of the main radicals (hydroxyl and sulfate radicals) was determined using appropriate radical traps (methanol and tert-butanol). These quenching experiments combined with the conducted electrochemical measurements revealed that both a radical and a non-radical mechanism contribute to the decomposition of SMX.
Survey on Yeast Assimilable Nitrogen Status of Musts from Native and International Grape Varieties: Effect of Variety and Climate
Authors: Bouloumpasi Elisavet , Skendi Adriana , Soufleros Evangelos H.
Published: August 2023

Yeast assimilable nitrogen (YAN), besides the oenological parameters (sugar content, titratable acidity, and pH) in grape musts of sixteen native and international varieties of Vitis vinifera cultivated in six regions of Northern Greece, was assessed in the frame of the present study. Low levels of YAN are frequently thought to be the cause of problematic fermentations and originate significant changes in the organoleptic aspects of the finished product. The objective of this multi-variety study was to assess factors affecting the YAN amount and composition in technologically mature grapes and, therefore, to evaluate the necessity of YAN supplementation with ammonium salts in musts across different native and international grape varieties. Free amino nitrogen was measured colorimetrically, ammoniacal nitrogen was measured enzymatically, and their values for each must sample were summed to obtain the total amount of YAN. Statistical analysis was carried out including principal component analysis (PCA) to discover relationships among must samples and the parameters studied. PCA analysis classified samples depending on grape varieties and region of origin, bringing knowledge about native and international cultivars of great commercial interest. Moreover, these findings could help to understand how commercial varieties can behave in different climates in the climate change context.
Design and Construction of a New Reactor for Flexible Biomethanation of Hydrogen
Authors: Hoffstadt Kevin , Cheenakula Dheeraja , Nikolausz Marcell , Krafft Simone , Harms Hauke , Kuperjans Isabel
Published: August 2023

The increasing share of renewable electricity in the grid drives the need for sufficient storage capacity. Especially for seasonal storage, power-to-gas can be a promising approach. Biologically produced methane from hydrogen produced from surplus electricity can be used to substitute natural gas in the existing infrastructure. Current reactor types are not or are poorly optimized for flexible methanation. Therefore, this work proposes a new reactor type with a plug flow reactor (PFR) design. Simulations in COMSOL Multiphysics ® showed promising properties for operation in laminar flow. An experiment was conducted to support the simulation results and to determine the gas fraction of the novel reactor, which was measured to be 29%. Based on these simulations and experimental results, the reactor was constructed as a 14 m long, 50 mm diameter tube with a meandering orientation. Data processing was established, and a step experiment was performed. In addition, a kLa of 1 h−1 was determined. The results revealed that the experimental outcomes of the type of flow and gas fractions are in line with the theoretical simulation. The new design shows promising properties for flexible methanation and will be tested.
Validation of Challenges for the Development of the Marketing Plan for Startups Considering the Post-COVID-19 Reality: An Exploratory Analysis of the Brazilian Context Using Lawshe’s Method
Authors: Nascimento Ana Carla Magalhães , Oliveira Nathália de Kassia Galdino , Nagata Verônica de Menezes Nascimento , Fernandes Reimison Moreira , Martins Vitor William Batista
Published: August 2023

Background: The post-COVID-19 scenario has demonstrated the increasing importance of marketing for organizations, as retailers and entrepreneurs have had to adapt to new ways of selling their products and services. In this regard, this research aimed to identify challenges for developing the marketing plan of startups and validate them from the perspective of managers in the field, considering the market characteristics inherent to the post-COVID-19 era; Methods: To achieve this, a literature review and a survey were conducted among professionals in the field. The collected data were analyzed using the quantitative Lawshe method. Results: The results indicate that, for the development of the marketing plan of startups considering the post-COVID-19 reality, it is important to prioritize overcoming the challenges of “Consumer behavior pattern change”, “Differentiation from the competition”, “Digital expansion”, “Innovation capacity of companies”, “Creation of transformative marketing”, and “Reevaluation of marketing channels in the post-pandemic period”; Conclusions: Therefore, it can be concluded that these challenges reflect the main concerns and obstacles faced by startups in building effective marketing strategies and striving for a competitive position in the market. By recognizing and understanding these challenges, startups will be better prepared to face adversity and seize opportunities in this new market context.
PAHs, Physicochemical and Microbiological Analyses of Trout Processed by Traditional Smoking, in Different Types of Packaging
Authors: Sava Alexandru , Uiuiu Paul , Lațiu Călin , Cocan Daniel , Muntean George-Cătălin , Papuc Tudor , Ihuț Andrada , Răducu Camelia , Becze Anca , Craioveanu Cristina , Munteanu Camelia , Constantinescu Radu , Mireșan Vioara
Published: August 2023

Smoking represents one of the oldest thermic processing methods of fish, and it was originally used to preserve fish for later meals, delaying spoiling. The objective of this study was to analyze the physicochemical and microbiological safety and quality of two traditionally smoked trout species (Oncorhynchus mykiss and Salvelinus fontinalis). We analyzed the effect of trout processed by traditional smoking, characterizing the samples according to the relationships existing between classical microbial analysis, physicochemical parameters, and the content of polycyclic aromatic hydrocarbons (PAHs). The microbial activity of the smoked fish was very low. Although traditional smoking implies high temperatures and direct exposure to the smoke, Benzo[a]pyrene, Benzo[b]fluoranthene, Benzo[k]fluoranthene, Dibenzo[a,h]anthracene, Benzo[g,h,i]perylene, and Indeno [1,2,3-cd]pyrene compounds had undetectable levels in the samples. The products obtained in this study did not exceed the maximum values imposed by EU legislation regarding the TVB-N values during the 30 days of the experiment. We conclude that traditionally smoked trout has many advantages in terms of quality and safety of the products. Thus, the obtained products are safe for consumption for at least 30 days after processing.
Molecular Characterization and Response of Silver Carp (Hypophthalmichthys molitrix) GLUT1 under Hypoxia Stress
Authors: Zhang Zewen , Li Xiaohui , Zou Guiwei , Liang Hongwei
Published: August 2023

As an important freshwater species with economic and ecological benefits, silver carp (Hypophthalmichthys molitrix) exhibits poor tolerance to hypoxia. Glucose transporters (GLUTs) are core membrane proteins that transport glucose to tissues and regulate essential life activities. Its expression is regulated by HIF-1α and cells in hypoxic conditions to maintain energy demand through GLUTs inducing enhanced glucose transport. We cloned H. molitrix glut1 (SLC2A1) and analyzed its sequence using bioinformatics tools. The glut1 cDNA was 2104 base pairs long and encoded a 490 amino acid protein. Phylogenetic analysis revealed that sliver carp glut1 is evolutionarily conserved and exhibited the highest sequence similarity with Ctenopharyngodon idella glut1. Glut1 expression was the highest and lowest in the gills and liver, respectively. Hypoxic stress significantly increased glut1 expression in the brain (p < 0.05); in the gills, it was the highest and lowest in the semi-asphyxia and asphyxia groups, respectively; in the liver, it was significantly higher under hypoxia than that of the normoxia group; and in the heart, it was significantly higher in the floating head, semi-asphyxia, and asphyxia groups than in the normoxia group (p < 0.05). The proposed mechanism may thus provide the basis for elucidating the molecular basis of silver carp’s hypoxia stress response mediated by glut1.
Sill Role Effect on the Flow Characteristics (Experimental and Regression Model Analytical)
Authors: Abbaszadeh Hamidreza , Norouzi Reza , Sume Veli , Kuriqi Alban , Daneshfaraz Rasoul , Abraham John
Published: August 2023

This study investigates the effects of gate openings and different sill widths on the sluice gate’s energy dissipation and discharge coefficient (Cd). The physical model of the sills includes rectangular sills of different dimensions. The results show that the gate opening size is inversely related to the Cd for a gate without a sill. In addition, increasing the gate opening size for a given discharge decreases the relative energy dissipation, and increasing the Froude number increases the relative energy dissipation. The results also show that the Cd and relative energy dissipation decrease when the width of the sill is decreased, thus increasing the total area of the flux flowing through the sluice gate and vice versa. According to the experimental results, the relative energy dissipation and the Cd of the sluice gate are larger for all sill widths than without the sill. Finally, non-linear polynomial relationships are presented based on dimensionless parameters for predicting the relative energy dissipation and outflow coefficient.
Hybrid Computation of the Aerodynamic Noise Radiated by the Wake of a Subsonic Cylinder
Authors: Eiximeno Benet , Tur-Mongé Carlos , Lehmkuhl Oriol , Rodríguez Ivette
Published: August 2023

The noise radiated by the flow around a cylinder in the subcritical regime at ReD=1×104 and at a subsonic Mach number of M=0.5 is here studied. The aerodynamic sound radiated by a cylinder has been studied with a wide range of Reynolds numbers, but there are no studies about how the Mach number affects the acoustic field in the subsonic regime. The flow field is resolved by means of large-eddy simulations of the compressible Navier–Stokes equations. For the study of the noise propagation, formulation 1C of the Ffowcs Williams–Hawkings analogy is used. The fluid flow results show good agreement when comparing the surface pressure coefficient, the recirculation length, the vortex shedding frequency and the force coefficients against other studies performed under similar conditions. The dynamic mode decomposition of the pressure fluctuations is used to relate them with the far-field noise. It is shown that, in contrast to what happens for low Mach numbers, quadrupoles have a significant impact mainly in the observers located in the streamwise direction. This effect leads to a global monopole directivity pattern as the shear fluctuations compensate for the lower value of the aeolian tone away from the cross-stream direction.
Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features
Authors: Sentellas Sonia , Saurina Javier
Published: August 2023

Cocoa and its derivative products, especially chocolate, are highly appreciated by consumers for their exceptional organoleptic qualities, thus being often considered delicacies. They are also regarded as superfoods due to their nutritional and health properties. Cocoa is susceptible to adulteration to obtain illicit economic benefits, so strategies capable of authenticating its attributes are needed. Features such as cocoa variety, origin, fair trade, and organic production are increasingly important in our society, so they need to be guaranteed. Most of the methods dealing with food authentication rely on profiling and fingerprinting approaches. The compositional profiles of natural components –such as polyphenols, biogenic amines, amino acids, volatile organic compounds, and fatty acids– are the source of information to address these issues. As for fingerprinting, analytical techniques, such as chromatography, infrared, Raman, and mass spectrometry, generate rich fingerprints containing dozens of features to be used for discrimination purposes. In the two cases, the data generated are complex, so chemometric methods are usually applied to extract the underlying information. In this review, we present the state of the art of cocoa and chocolate authentication, highlighting the pros and cons of the different approaches. Besides, the relevance of the proposed methods in quality control and the novel trends for sample analysis are also discussed.
Recent Advances in Lycopene for Food Preservation and Shelf-Life Extension
Authors: Li Zhixi , Yu Fanqianhui
Published: August 2023

In recent years, there has been increasing concern about the safety of additives used to extend the shelf-life of food products. As a result, lycopene, a natural phytochemical compound, has attracted attention, as it has been demonstrated to be a potential alternative to traditional artificial antioxidants, with significant health benefits when applied to food preservation. Based on this, this review introduces the specific forms of lycopene currently used as an antioxidant in foods, both in its naturally occurring forms in fruits and vegetables and in artificially added forms involving technologies such as composite coating, active film packaging, emulsion, and microcapsules. In addition, it also provides a comprehensive summary of the effects and progress of lycopene in the preservation of different types of food products, such as meat, seafood, oil, dairy products, fruits, and vegetables, in the last decade. At last, it also points out the limitations of lycopene, including its insolubility in water, dark color, and high sensitivity to heat or light, as well as the potential solutions to load lycopene on suitable carriers, such as combining lycopene with antimicrobial substances or other actives, in order to broaden its applications as an antioxidant in future foods.
Potential Impact of Combined Inhibition by Bacteriocins and Chemical Substances of Foodborne Pathogenic and Spoilage Bacteria: A Review
Authors: Yu Wei , Guo Jinqi , Liu Yuanyuan , Xue Xiaoge , Wang Xiangru , Wei Lili , Ma Jiage
Published: August 2023

In recent years, food safety caused by foodborne pathogens and spoilage bacteria has become a major public health problem worldwide. Bacteriocins are a kind of antibacterial peptide synthesized by microbial ribosomes, and are widely used as food preservatives. However, when used individually bacteriocins may have limitations such as high cost of isolation and purification, narrow inhibitory spectrum, easy degradation by enzymes, and vulnerability to complex food environments. Numerous studies have demonstrated that co-treatment with bacteriocins and a variety of chemical substances can have synergistic antibacterial effects on spoilage microorganisms and foodborne pathogens, effectively prolonging the shelf life of food and ensuring food safety. Therefore, this paper systematically summarizes the synergistic bacteriostatic strategies of bacteriocins in combination with chemical substances such as essential oils, plant extracts, and organic acids. The impacts of bacteriocins when used individually and in combination with other chemical substances on different food substrates are clarified, and bacteriocin–chemical substance compositions that enhance antibacterial effectiveness and reduce the potential negative effects of chemical preservatives are highlighted and discussed. Combined treatments involving bacteriocins and different kinds of chemical substances are expected to be a promising new antibacterial method and to become widely used in both the food industry and biological medicine.
Preliminary Study of Pepper Types Based on Multielement Content Combined with Chemometrics
Authors: Zeiner Michaela , Fiedler Heidelore , Juranović Cindrić Iva , Nemet Ivan , Toma Doris , Habinovec Iva
Published: August 2023

Different types of pepper (Piper nigrum L.) and cayenne pepper (Capsicum annuum L.) are widely used spices that exhibit therapeutic properties in addition to nutritional properties. In order to characterize these foods in further detail, the content of macro- (Ca, K, Mg, Na) and microelements (Ag, Al, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Ga, Li, Mn, Mo, Ni, Pb, Rb, Se, Sr, Te, Tl, V and Zn) of four pepper types was determined via inductively coupled plasma mass spectrometry (ICP-MS) after microwave-assisted digestion using nitric acid and hydrogen peroxide. The obtained results were then evaluated using chemometric methods. The content of macroelements and microelements lies in the expected ranges for such spices but differs significantly between different types. The content of macro- and microelements is characteristic for pepper types originating from different plant species, but also based on further processing. Whilst green and black pepper are similar to each other, clearly diverse patterns are obtained for white pepper (different processing method) and cayenne pepper (different plant species).
Effects of Key Components on the Antioxidant Activity of Black Tea
Authors: Wang Weiwei , Le Ting , Wang Wei , Yu Luting , Yang Lijuan , Jiang Heyuan
Published: August 2023

Many components (such as tea polyphenols, catechins, theaflavins, theasinensins, thearubigins, flavonoids, gallic acid, etc.) in black tea have antioxidant activities. However, it is not clear which components have a greater influence on the antioxidant activity of black tea. In this study, the antioxidant activity and contents of tea polyphenols, catechins, theaflavins, thearubigins, theabrownins, TSA, total flavonoids, amino acids, caffeine, and total soluble sugar were analyzed in 51 black teas. Principal component analysis (PCA), orthogonal partial least-squares discrimination analysis (OPLS-DA), and the correlation analysis method were used for data analysis. The results showed that catechins in tea polyphenols were the most important components that determine the antioxidant activity of black tea. Among them, epicatechin gallate (ECG), epi-gallocatechin gallate (EGCG), epicatechin (EC), and epi-gallocatechin (EGC) were significantly positively correlated with the antioxidant activity of black tea, and theabrownin was negatively correlated with the antioxidant activity of black tea. Furthermore, this study analyzed the correlation between the changes in catechin and its oxidized polymers with antioxidant activity during black tea fermentation; it verified that catechins were significantly positively correlated with the antioxidant activity of black tea, and theabrownin showed a negative correlation. And the antioxidant activity of catechins and their oxidation products in vitro and their correlation in black tea processing were used as validation. This study provides a comparison method for comparing the antioxidant activity of black tea.
A Monotone Discretization for the Fractional Obstacle Problem and Its Improved Policy Iteration
Authors: Han Rubing , Wu Shuonan , Zhou Hao
Published: August 2023

In recent years, the fractional Laplacian has attracted the attention of many researchers, the corresponding fractional obstacle problems have been widely applied in mathematical finance, particle systems, and elastic theory. Furthermore, the monotonicity of the numerical scheme is beneficial for numerical stability. The purpose of this work is to introduce a monotone discretization method for addressing obstacle problems involving the integral fractional Laplacian with homogeneous Dirichlet boundary conditions over bounded Lipschitz domains. Through successful monotone discretization of the fractional Laplacian, the monotonicity is preserved for the fractional obstacle problem and the uniform boundedness, existence, and uniqueness of the numerical solutions of the fractional obstacle problems are proved. A policy iteration is adopted to solve the discrete nonlinear problems, and the convergence after finite iterations can be proved through the monotonicity of the scheme. Our improved policy iteration, adapted to solution regularity, demonstrates superior performance by modifying discretization across different regions. Numerical examples underscore the efficacy of the proposed method.
A Fast θ Scheme Combined with the Legendre Spectral Method for Solving a Fractional Klein–Gordon Equation
Authors: Li Yanan , Xu Yibin , Liu Yanqin , Shen Yanfeng
Published: August 2023

In the current work, a fast θ scheme combined with the Legendre spectral method was developed for solving a fractional Klein–Gordon equation (FKGE). The numerical scheme was provided by the Legendre spectral method in the spatial direction, and for the temporal direction, a θ scheme of order O(τ2) with a fast algorithm was taken into account. The fast algorithm could decrease the computational cost from O(M2) to O(MlogM), where M denotes the number of time levels. In addition, correction terms could be employed to improve the convergence rate when the solutions have weak regularity. We proved theoretically that the scheme is unconditionally stable and obtained an error estimate. The numerical experiments demonstrated that our numerical scheme is accurate and efficient.
Two Integral Representations for the Relaxation Modulus of the Generalized Fractional Zener Model
Authors: Bazhlekova Emilia , Pshenichnov Sergey
Published: August 2023

A class of generalized fractional Zener-type viscoelastic models with general fractional derivatives is considered. Two integral representations are derived for the corresponding relaxation modulus. The first representation is established by applying the Laplace transform to the constitutive equation and using the Bernstein functions technique to justify the change of integration contour in the complex Laplace inversion formula. The second integral representation for the relaxation modulus is obtained by applying the subordination principle for the relaxation equation with generalized fractional derivatives. Two particular examples of the considered class of models are discussed in more detail: a model with fractional derivatives of uniformly distributed order and a model with general fractional derivatives, the kernel of which is a multinomial Mittag-Leffler-type function. To illustrate the analytical results, some numerical examples are presented.
Fractional Order Sequential Minimal Optimization Classification Method
Authors: Zhao Chunna , Dai Licai , Huang Yaqun
Published: August 2023

Sequential minimal optimization (SMO) method is an algorithm for solving optimization problems arising from the training process of support vector machines (SVM). The SMO algorithm is mainly used to solve the optimization problem of the objective function of SVM, and it can have high accuracy. However, its optimization accuracy can be improved. Fractional order calculus is an extension of integer order calculus, which can more accurately describe the actual system and get more accurate results. In this paper, the fractional order sequential minimal optimization (FOSMO) method is proposed based on the SMO method and fractional order calculus for classification. Firstly, an objective function is expressed by a fractional order function using the FOSMO method. The representation and meaning of fractional order terms in the objective function are studied. Then the fractional derivative of Lagrange multipliers is obtained according to fractional order calculus. Lastly, the objective function is optimized based on fractional order Lagrange multipliers, and then some experiments are carried out on the linear and nonlinear classification cases. Some experiments are carried out on two-classification and multi-classification situations, and experimental results show that the FOSMO method can obtain better accuracy than the normal SMO method.
Maxillary Impacted Canine and Upper Lateral Incisor Agenesis Treatment with “Canine First Technique” and Clear Aligners: A Case Report
Authors: Bocchino Tecla , Martina Stefano , Sangiuolo Carolina , Galdi Marzio , Valletta Alessandra , D’Antò Vincenzo
Published: August 2023

The aim of this study was to show a case of an impacted canine in an adult patient with agenesis of the maxillary lateral incisor treated with clear aligners (CA). A 19-year-old male with a persistence of 5.3 and absence of 1.2 came to our department of the School of Orthodontics at the University of Federico II in Naples and asked for an aesthetic treatment. The Canine First approach was used to surgically expose the canine and pull it into the dental arch. In order to ensure long-term aesthetic, periodontal, and occlusal results, a treatment with CAs to close the space through the mesial placement of the canine and the enameloplasty of the tooth crown was performed. At the end of the treatment, the occlusal objectives were achieved.
Prevention, Intervention and Care of Neurodegenerative Diseases
Authors: Bakirtzis Christos , Boziki Marina-Kleopatra , Grigoriadis Nikolaos
Published: August 2023

Chronic neurodegenerative diseases encompass a wide spectrum of disorders and affect millions of people worldwide [...]
Workshop for Basic Gynaecological Examinations: Improving Medical Student Learning through Clinical Simulation
Authors: Cuñarro-López Yolanda , Sánchez Llanos Lucia , Cueto Hernández Ignacio , González-Garzón De Zumárraga Blanca , Del Pilar Pintado Recarte María , Ruiz Labarta Francisco Javier , Cano-Valderrama Óscar , Aedo Ocaña Olga , Pérez Lucas Raquel , Viñuela Benéitez María Del Carmen , Reyes Angullo Zurine Raquel , Fernández Muñoz María , Pina Moreno Juan Manuel , Sanchez Rodriguez Maria Mercedes , Aracil Rodríguez Rocío , Pérez Burrel Laura , Sáez Prat Ainoa , Fraile López Andrea , Gutiérrez Del Río Beatriz , Quintana Coronado María de Guadalupe , Cisternas Tamara , Feltrer Hidalgo Marta , González Navarro Pablo , Ortega Miguel A. , López Ramón y Cajal Carlos , De León-Luis Juan Antonio
Published: August 2023

Introduction: This study was designed to evaluate whether the Workshop on Basic Principles for Clinical Gynaecological Exploration, offered to medical students, improves theoretical–practical knowledge, safety, confidence, global satisfaction and the achievement of the proposed objectives in the area of gynaecological clinical examinations. Materials and Methods: This was a quasi-experimental pre–post-learning study carried out at the Gynaecology and Obstetrics department of Gregorio Marañón Hospital in Madrid (Spain). The volunteer participants were 4th-year students earning a degree in Medicine during the 2020–2021 and 2021–2022 academic years. The study period was divided into the following stages: pre-workshop, intra-workshop and 2 weeks post-workshop. In the pre-workshop stage, students completed a brief online course to prepare for the workshop. The effectiveness of the workshop was evaluated through multiple-choice tests and self-administered questionnaires to assess self-assurance, self-confidence, self-satisfaction and the achievement of the objectives. Results: Of the 277 students invited in both academic years, 256 attended the workshop (92.4%), with a total participation in the different stages of the study greater than 70%. A total of 82.5% of the students in the 2020–2021 academic year and 80.6% of students in the 2021–2022 academic year did not have any type of experience performing gynaecological clinical examinations. Between the pre-workshop and 2 weeks post-workshop stages, there was significant improvement in theoretical–practical knowledge (improvement mean = 1.38 and 1.21 in 2020–2021 and 2021–2022 academic years, respectively). The security and confidence of the students prior to the workshop were low (average scores less than 5 points) in both academic years. However, post-workshop scores for satisfaction and the achievement of objectives were high in the two academic years; all the values approached or exceeded 8 points. Conclusions: Our students, after outstanding participation, evaluated the BPCGE, and improved their theoretical and practical knowledge, as well as their skills in a gynaecological clinical examination. Moreover, in their view, after the workshop, they felt very satisfied, far outreaching the proposed aims. In addition, excellent results were maintained over time, year after year.