bluuebunny/crossref_metadata_2025 huggingface dataset:
The Complexity of the Super Subdivision of Cycle-Related Graphs Using Block Matrices
Authors: Zeen El Deen Mohamed R. , Aboamer Walaa A. , El-Sherbiny Hamed M.
Published: August 2023

The complexity (number of spanning trees) in a finite graph Γ (network) is crucial. The quantity of spanning trees is a fundamental indicator for assessing the dependability of a network. The best and most dependable network is the one with the most spanning trees. In graph theory, one constantly strives to create novel structures from existing ones. The super subdivision operation produces more complicated networks, and the matrices of these networks can be divided into block matrices. Using methods from linear algebra and the characteristics of block matrices, we derive explicit formulas for determining the complexity of the super subdivision of a certain family of graphs, including the cycle Cn, where n=3,4,5,6; the dumbbell graph Dbm,n; the dragon graph Pm(Cn); the prism graph Πn, where n=3,4; the cycle Cn with a Pn2-chord, where n=4,6; and the complete graph K4. Additionally, 3D plots that were created using our results serve as illustrations.
Sleep and Stroke-Related Delirium: A Systematic Review
Authors: Brunetti Valerio , Rollo Eleonora , Scala Irene , Marotta Jessica , Callea Antonio , Imperatori Claudio , Della Marca Giacomo
Published: August 2023

Study objectives: Sleep and circadian rhythms disorders are frequent in the acute stroke. Sleep modifications are likely to contribute to the development of stroke-related delirium, a common neuropsychiatric complication of acute stroke. This systematic review aimed to clarify the association between sleep modifications and the occurrence of delirium in patients with acute stroke. Methods: The current systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The search was performed on PubMed and Scopus databases. Only studies that provided data concerning sleep, or pre-existing sleep disorders, in acute stroke and performed a formal evaluation of delirium were included. Results: The literature search enabled the identification of 15 studies, which exhibited high heterogeneity in terms of study design, settings, sleep assessments, delirium measures, and types of sleep intervention. In the study quality assessment, the majority of the studies were rated as weak or moderate. In most of the cases, sleep was subjectively assessed by the patients or rated by clinicians. None of the studies performed polysomnography for the evaluation of sleep. Only four of the studies assessed the impact of a sleep intervention on delirium, suggesting the potentially protective role of sleep promotion in reducing the prevalence and severity of stroke-related delirium. Conclusions: The evidence arising from the present systematic review supports that sleep disruption is a potential promoting factor for stroke-related delirium. We suggest that a formal sleep assessment and sleep promotion should be included in routine stroke care.
Range Contraction and Population Decline of the European Dupont’s Lark Population
Authors: Reverter Margarita , Pérez-Granados Cristian , López-Iborra Germán M. , García-Mellado Amparo , Aledo-Olivares Emilio , Alcántara Manuel , Aranda Antonio , Barrero Adrián , Bota Gerard , Bustillo-de la Rosa Daniel , Cubero David , Giralt David , Gómez-Catasús Julia , de las Heras Matías , Fernández-Palacios José M. , Garrido José R. , Paracuellos Mariano , Rubio Miguel A. , Ruiz Gema , Sáez-Gómez Pedro , Salvador Víctor , Sampietro Javier , Santos-Torres Ana , Serrano David , Zurdo Julia , Traba Juan
Published: August 2023

The Dupont’s lark (Chersophilus duponti) is an endangered passerine typical of Mediterranean shrub-steppes, whose European distribution is restricted to Spain. Here, we update the population size and distribution range of the species at a European scale and evaluate (i) the current status; (ii) the change in population size and distribution range of the species from 2004 to 2009 to the current period (2017–2022); and (iii) the effectiveness of the current network of special protection areas (SPAs) for protecting the Dupont’s lark. The European Dupont’s lark population showed a decrease of 29.9%, declining from ca. 3267 to 2289 territorial males from 2004 to 2009 to the current period. Moreover, the species has suffered a contraction in its distribution range of 35.9%, with only 39.3% of the species’ territories located within the current network of SPAs. Our findings agree with the previously described decline of the Dupont’s lark in Europe. The population decline was even larger in peripheral regions, which suggests that the species is suffering a centripetal process of contraction and extinction. These results indicate that if there is no change in present-day declining forces, several peripheral populations will reach extinction in a few decades and the overall population size of the species will continue decreasing. Our study should be considered as a last call for action and used for implementing urgent conservation measures to protect the species and its habitat. Future studies should focus on analyzing and managing the factors driving the species’ extinction and future actions for the conservation of the species should focus on increasing the percentage of the Dupont’s lark territories within protected areas, since the data are alarmingly low for a species that is facing clear risk of extinction.
Members of the Genus Beauveria Associated with Natural Populations of Locusts in Southern European Russia
Authors: Lednev Georgy , Levchenko Maxim , Kazartsev Igor
Published: August 2023

The species composition of fungal pathogens among three of the most harmful locust species (Asian migratory locust, Moroccan locust and Italian locust) in the southern Russian Federation was studied. Insects were sampled in 20 locations of seven federal subjects of the Russian Federation (Republic of Dagestan, Republic of Kalmykia; Krasnodar and Stavropol Krai; Astrakhan, Volgograd and Rostov Regions). Forty-five isolates belonging to the fungal genus Beauveria were collected, particularly isolates of B. bassiana and B. pseudobassiana. B. bassiana was the most prevalent, constituting 98% of the samples, and could be differentiated into three clades, as evidenced by the TEF gene and intergenic spacer Bloc. Clade 1, represented by the reference isolate ARSEF 2040, was most abundant (61%), and Clade 2, represented by ARSEF 1811, had lower abundance (27%). The remaining isolates either belonged to the genetically distinct Clade 3, represented by ARSEF 1564, or were found to fall outside the major lineages. The frequency of infection in locust populations was variable and tended to increase under conditions unfavorable for the insects. The vast majority of Beauveria isolates from locusts were highly virulent in this insect group.
Skin Lesion Segmentation Using an Ensemble of Different Image Processing Methods
Authors: Tamoor Maria , Naseer Asma , Khan Ayesha , Zafar Kashif
Published: August 2023

In recent times, there has been a huge increase in the average number of cases of skin cancer per year, which sometimes become life threatening for humans. Early detection of various skin diseases through automated detection techniques plays a crucial role. However, the presence of numerous artefacts makes this task challenging. Dermoscopic images exhibit various variations, including hair artefacts, markers, and ill-defined boundaries. These artefacts make automatic analysis of skin lesion quite a difficult task. To address these issues, it is essential to have an accurate and efficient automated method which will delineate a skin lesion from the rest of the image. Unfortunately, due to the presence of several types of skin artefacts, there is no such thresholding method that can provide a sufficient segmentation result for every type of skin lesion. To overcome this limitation, an ensemble-based method is proposed that selects the optimal thresholding based on an objective function. A group of state-of-the-art different thresholding methods such as Otsu, Kapur, Harris hawk, and grey level are used. The proposed method obtained superior results (dice score = 0.89 with p-value ≤ 0.05) as compared to other state-of-the-art methods (Otsu = 0.79, Kapur = 0.80, Harris hawk = 0.60, grey level = 0.69, active contour model = 0.72). The experiments conducted in this study utilize the ISIC 2016 dataset, which is publicly available and specifically designed for skin-related research. Accurate segmentation will help in the early detection of many skin diseases.
Evaluation of the Pulp Chamber Temperature during Tooth Veneer Preparation Using Burs with Different Degrees of Wear—A Preliminary In Vitro Study
Authors: Ciora Edmond , Miron Mariana , Bojoga Daliana , Lungeanu Diana , Jivanescu Anca
Published: August 2023

The heat produced during tooth preparation could be a source of damage for dental pulp, and many variables are involved in this process. The aim of this in vitro study was to evaluate whether the different degrees of wear of the diamond burs significantly influenced the temperature changes in the pulp chamber during tangential veneer preparation. The sample comprised 30 intact permanent monoradicular teeth, randomly assigned to three study groups of 10 teeth each, of which 5 had the pulp tissue preserved and 5 had thermoconductive paste in the pulp chamber. For prosthetic preparation, we used new burs in the first group, burs at their fifth use in the second group, and burs at their eighth use for the third group. The pulp chamber temperature was evaluated at the start, after one minute, and after three minutes of preparation, using a k-type thermocouple. The results of the three-way ANOVA and Tukey post hoc comparisons showed a highly significant effect of the time of measurement, while the pulp condition and the degree of wear of the burs had no effect. In conclusion, the different degrees of wear of conventional diamond burs do not produce statistically significant different changes in the pulp chamber temperature.
Adaptable 2D to 3D Stereo Vision Image Conversion Based on a Deep Convolutional Neural Network and Fast Inpaint Algorithm
Authors: Hachaj Tomasz
Published: August 2023

Algorithms for converting 2D to 3D are gaining importance following the hiatus brought about by the discontinuation of 3D TV production; this is due to the high availability and popularity of virtual reality systems that use stereo vision. In this paper, several depth image-based rendering (DIBR) approaches using state-of-the-art single-frame depth generation neural networks and inpaint algorithms are proposed and validated, including a novel very fast inpaint (FAST). FAST significantly exceeds the speed of currently used inpaint algorithms by reducing computational complexity, without degrading the quality of the resulting image. The role of the inpaint algorithm is to fill in missing pixels in the stereo pair estimated by DIBR. Missing estimated pixels appear at the boundaries of areas that differ significantly in their estimated distance from the observer. In addition, we propose parameterizing DIBR using a singular, easy-to-interpret adaptable parameter that can be adjusted online according to the preferences of the user who views the visualization. This single parameter governs both the camera parameters and the maximum binocular disparity. The proposed solutions are also compared with a fully automatic 2D to 3D mapping solution. The algorithm proposed in this work, which features intuitive disparity steering, the foundational deep neural network MiDaS, and the FAST inpaint algorithm, received considerable acclaim from evaluators. The mean absolute error of the proposed solution does not contain statistically significant differences from state-of-the-art approaches like Deep3D and other DIBR-based approaches using different inpaint functions. Since both the source codes and the generated videos are available for download, all experiments can be reproduced, and one can apply our algorithm to any selected video or single image to convert it.
A Machine Learning Approach to Simulate Gene Expression and Infer Gene Regulatory Networks
Authors: Zito Francesco , Cutello Vincenzo , Pavone Mario
Published: August 2023

The ability to simulate gene expression and infer gene regulatory networks has vast potential applications in various fields, including medicine, agriculture, and environmental science. In recent years, machine learning approaches to simulate gene expression and infer gene regulatory networks have gained significant attention as a promising area of research. By simulating gene expression, we can gain insights into the complex mechanisms that control gene expression and how they are affected by various environmental factors. This knowledge can be used to develop new treatments for genetic diseases, improve crop yields, and better understand the evolution of species. In this article, we address this issue by focusing on a novel method capable of simulating the gene expression regulation of a group of genes and their mutual interactions. Our framework enables us to simulate the regulation of gene expression in response to alterations or perturbations that can affect the expression of a gene. We use both artificial and real benchmarks to empirically evaluate the effectiveness of our methodology. Furthermore, we compare our method with existing ones to understand its advantages and disadvantages. We also present future ideas for improvement to enhance the effectiveness of our method. Overall, our approach has the potential to greatly improve the field of gene expression simulation and gene regulatory network inference, possibly leading to significant advancements in genetics.
Contributions of Investment and Employment to the Agricultural GDP Growth in Egypt: An ARDL Approach
Authors: Abdelgawwad Nouran Abdelhamid , Kamal Abdelmonem Lotfy Mohamed
Published: August 2023

This paper explores the impact of investment and employment on Egypt’s agricultural growth during the period 1991 to 2021 using annual time series data. We use the ARDL approach to examine the long-run and short-run relationships among agricultural investment, agricultural employment and agricultural GDP. The results reveal that the variables of interest are bound together in the long run. The long-run relationship and the error correction model are estimated. The accompanying equilibrium correction proves that long-run linkages exist in a meaningful way. Results show that agricultural investment and agricultural employment are major short- and long-run determinants of the agricultural GDP. In the long run, every 1% increase in agricultural employment (AEMP) results in an increase in the agricultural GDP (AGDP) of 3.73%, while every 1% increase in agricultural investment (AINV) improves the AGDP by 0.43%. In the short run, 26% of all disequilibrium-causing motions are adjusted for in a single session. Therefore, it takes 3.85 years for the Egyptian agricultural GDP to achieve the transition from a short-term disequilibrium situation to a long-term equilibrium. Thus, decision makers should increase the rates of investment in the agricultural sector, in parallel to the development of the agricultural labor force in Egypt. Moreover, the increased allocation of public investments and the injection of private investments are highly recommended. In addition, the Egyptian agricultural sector needs improvements regarding human capital development and agricultural training. Finally, the government must initiate comprehensive farmer support services, bolstered farm/non-farm links and the promotion of rural SMEs to serve as the foundation for agricultural and rural development.
Two-Branch Feature Interaction Fusion Method Based on Generative Adversarial Network
Authors: Chang Rong , Dang Junpeng , Zhang Nanchuan , Zhao Shan , Hu Shijin , Xing Lin , Bai Haicheng , Zhou Chengjiang , Yang Yang
Published: August 2023

This study proposes a fusion method of infrared and visible images based on feature interaction. Existing fusion methods can be classified into two categories based on a single-branch network and a two-branch network. Generative adversarial networks are widely used in single-branch-based fusion methods, which ignore the difference in feature extraction caused by different input images. Most two-branch-based fusion methods use convolutional neural networks, which do not take into account the inverse promotion of fusion results and lack the interaction between different input features. To remedy the shortcomings of these fusion methods and better utilize the feature from source images, this study proposes a two-branch feature interactions method based on a generative adversarial network for visible and infrared image fusion. In the generator part, a two-branch feature interaction approach was designed to extract features from different inputs and realize feature interaction through the network connection of different branches. In the discriminator part, a double-classification discriminator was used for visible images and infrared images. Extensive comparison experiments with state-of-the-art methods have demonstrated the advantages of this proposed generative adversarial network based on two-branch feature interaction, which can enhance the texture details of objects in fusion results and reduce the interference of noise information from source inputs. In addition, the above advantages were also confirmed in generalization experiments of object detection.
Quantification and Analysis of Carrier-to-Interference Ratio in High-Throughput Satellite Systems
Authors: Dong Zanyang , Yi Longteng , Qin Pengfei , Zhou Yejun , Zhang Cheng , Liu Kang
Published: August 2023

Recently, the demand for high data traffic transmission is experiencing unstoppable growth, and multi-beam high-throughput satellite (HTS) systems have proven to be effective solutions. However, how to manage and eliminate the co-channel interference caused by frequency reuse in multi-beam HTS systems is still a challenging issue. Motivated by this background, this paper begins with discussing the interference mechanism in the uplink and downlink of HTS systems and then uses the quantification method of carrier-to-interference ratio (CIR), whereby the influencing factors of the CIR are accordingly analyzed. In addition, the common CIR selection strategies are summarized and compared with each other in terms of their advantages and disadvantages. Based on the proposed CIR quantification and statistical selection methods, two frequency plan cases are simulated for the scenario of 19 beams with 4-color reuse. The results show that the proposed quantification and selection methods are rather practical and offer a feasible approach for frequency plan adjustment based on CIR optimization. Finally, a simulation analysis of the CIR under different power spectral density (PSD) values is conducted, and the results show that the PSD has a substantial impact on the CIR.
Speaker Recognition Based on the Joint Loss Function
Authors: Feng Tengteng , Fan Houbin , Ge Fengpei , Cao Shuxin , Liang Chunyan
Published: August 2023

The statistical pyramid dense time-delay neural network (SPD-TDNN) model makes it difficult to deal with the imbalance of training data, poses a high risk of overfitting, and has weak generalization ability. To solve these problems, we propose a method based on the joint loss function and improved statistical pyramid dense time-delay neural network (JLF-ISPD-TDNN), which improves on the SPD-TDNN model and uses the joint loss function method to combine the advantages of the cross-entropy loss function and the comparative learning of the loss function. By minimizing the distance between speech embeddings from the same speaker and maximizing the distance between speech embeddings from different speakers, the model could achieve enhanced generalization performance and more robust speaker feature representation. We evaluated the proposed method’s performance using the evaluation indexes of the equal error rate (EER) and minimum cost function (minDCF). The experimental results show that the EEE and minDCF on the Aishell-1 dataset reached 1.02% and 0.1221%, respectively. Therefore, using the joint loss function in the improved SPD-TDNN model can significantly enhance the model’s speaker recognition performance.
AHP-Based Network Security Situation Assessment for Industrial Internet of Things
Authors: Yi Junkai , Guo Lin
Published: August 2023

The Industrial Internet of Things (IIoT) is used in various industries to achieve industrial automation and intelligence. Therefore, it is important to assess the network security situation of the IIoT. The existing network situation assessment methods do not take into account the particularity of the IIoT’s network security requirements and cannot achieve accurate assessment. In addition, IIoT transmits a lot of heterogeneous data, which is subject to cyber attacks, and existing classification methods cannot effectively deal with unbalanced data. To solve the above problems, this paper first considers the special network security requirements of the IIoT, and proposes a quantitative evaluation method of network security based on the Analytic Hierarchy Process (AHP). Then, the average under-/oversampling (AUOS) method is proposed to solve the problem of unbalance of network attack data. Finally, an IIoT network security situation assessment classifier based on the eXtreme Gradient Boosting (XGBoost) is constructed. Experiments show that the situation assessment method proposed in this paper can more accurately characterize the network security state of the IIoT. The AUOS method can achieve data balance without generating too much data, and does not burden the training of the model. The classifier constructed in this paper is superior to the traditional classification algorithm.
Landfill Waste Segregation Using Transfer and Ensemble Machine Learning: A Convolutional Neural Network Approach
Authors: Ouedraogo Angelika Sita , Kumar Ajay , Wang Ning
Published: August 2023

Waste disposal remains a challenge due to land availability, and environmental and health issues related to the main disposal method, landfilling. Combining computer vision (machine learning) and robotics to sort waste is a cost-effective solution for landfilling activities limitation. The objective of this study was to combine transfer and ensemble learning to process collected waste images and classify landfill waste into nine classes. Pretrained CNN models (Inception–ResNet-v2, EfficientNetb3, and DenseNet201) were used as base models to develop the ensemble network, and three other single CNN models (Models 1, 2, and 3). The single network performances were compared to the ensemble model. The waste dataset, initially grouped in two classes, was obtained from Kaggle, and reorganized into nine classes. Classes with a low number of data were improved by downloading additional images from Google search. The Ensemble Model showed the highest prediction precision (90%) compared to the precision of Models 1, 2, and 3, 86%, 87%, and 88%, respectively. All models had difficulties predicting overlapping classes, such as glass and plastics, and wood and paper/cardboard. The environmental costs for the Ensemble network, and Models 2 and 3, approximately 15 g CO2 equivalent per training, were lower than the 19.23 g CO2 equivalent per training for Model 1.
Aerothermal Dynamic Characteristics of Array Micro Ribs in Channel Flow
Authors: Zhao Ke , Li Xueying , Ren Jing
Published: August 2023

With the rising complexity of internal cooling structures in gas turbine blades, the limited cooling air volume and pressure head provided by the compressor have become significant constraints to further enhancements in the overall efficiency of gas turbines. To address this, micro-turbulators have been proposed as a viable solution in recent research. The rib turbulators, as a typical internal cooling structure, have inherent limitations in heat transfer measurements. In this study, a segmented lumped parameter method was employed to experimentally analyze the aerothermal dynamic characteristics of micro ribs under varying rib heights and Reynolds numbers in channel flow. It was found that heat transfer performance closely correlates with both rib height and the height of the incoming boundary layer. Under certain conditions of dimensionless height and dimensionless number, optimal heat transfer enhancement near the micro-rib was observed, leading to an approximately 30% increase in the overall thermal performance (OTP) compared to the results from research into traditional 90° ribs. Numerical results based on the Reynolds stress model (RSM) suggest that this improvement is primarily due to the increased turbulence intensity in the near-wall region (y+ = 20–55) of the boundary layer caused by the micro ribs. This study presents a new characteristic parameter e+/Re that offers improved representation of the heat transfer performance of micro ribs, and reveals that when this parameter is around 40, micro ribs can provide high heat transfer with low pressure loss, thereby improving the overall efficiency. These results underscore the potential applicability of micro ribs in advancing the efficiency of gas turbines and other related fields.
Impact Financing for Clean Cooking Energy Transitions: Reviews and Prospects
Authors: Stritzke Susann , Bricknell Malcolm , Leach Matthew , Thapa Samir , Khalifa Yesmeen , Brown Ed
Published: August 2023

Achieving universal access to clean cooking requires a significant mobilization of capital to close the current funding gap of around US$7 bn per year. The clean cooking landscape has changed considerably with substantial innovation in terms of technology, business models, and services. The transition towards higher-tier, modern energy cooking (MEC) solutions provides key opportunities for innovative financing models to scale MEC globally. Transitions from cooking with polluting fuels to MEC have significant positive impacts on the environment, gender equality, and health. Impact Finance to monetize these co-benefits for MEC solutions is widely seen as an outstanding opportunity to channel funding into MEC transitions. However, except for climate funding, opportunities to channel finance for wider impact SDG benefits arising from MEC have proved challenging to realize in practice. This article explores in detail two new approaches which are taking advantage of features of digital technology to overcome some of these obstacles. It adds to the recent debate around climate finance for clean cooking and presents key learning lessons from developing and piloting the ‘Metered Methodology for Clean Cooking Devices’ as the current most accurate approach to estimate carbon savings for MEC and the ‘Clean Impact Bond (CIB)’ which aims at monetizing health and gender-co-benefits. The paper demonstrates how robust methodologies can help to accelerate funding for MEC and calls for joint approaches to standardize and streamline climate and outcome finance approaches to enhance their impact by making them more accessible for a wider range of MEC technologies, geographies, and projects.
Epidemiology of Turbot (Scophthalmus maeoticus) Bacterial Contamination, a Fishery Limiting Factor on the Romanian Black Sea
Authors: Țoțoiu Aurelia , Patriche Neculai , Niță Victor , Sîrbu Elena , Dima Floricel Maricel , Nenciu Magda Ioana , Nistor Veta
Published: August 2023

The aim of this research was to evaluate the health status of the Scophthalmus maeoticus (Pallas, 1814) population from the Romanian marine area in 2016–2019, by identifying and investigating information about bacterial and constitutional diseases, establishing the influence of these bacterioses on the researched populations, and highlighting the main biological disorders (reproduction, growth, and feeding) that manifested in the analyzed fish. The bacterial diseases reported in S. maeoticus (Pallas, 1814) populations were caused by pathogens from the genera Vibrio, Aeromonas, and Pseudomonas. Numerous skin diseases, especially various types of “wounds”, lesions of bony tubercles, and tissue lesions may be the subsequent cause of neoplasms, as a result of fishing gear manipulations. The appearance of significant changes in the prevalence of neoplasia on the Romanian Black Sea coast can be considered an indicator of chronic stress (anthropogenic impact), rather than acute (environmental impact), and we suggest that the species could be used as a biological indicator of changes that may occur in the habitat in which it lives. In terms of future research directions, a combined analysis of the population structure, morphology and diseases determined in S. maeoticus populations, with a structural analysis of the habitat and bacteria contamination degree would be useful; this monitoring should be carried out regularly, to reveal changes in the Black Sea ecosystem, and to propose possible recommendations and protective measures.
Microwave Hydrodiffusion and Gravity Extraction of Vitamin C and Antioxidant Compounds from Rosehips (Rosa canina L.)
Authors: Mazzara Eugenia , Caprioli Giovanni , Simonelli Gianmarco , Mustafa Ahmed M. , Maggi Filippo , Cespi Marco
Published: August 2023

Rosehips, Rosa canina L. (Rosaceae family), have been used for a long time for their beneficial effects on health, and they are largely exploited in the food and nutraceutical supplement sectors. The aim of this work was to apply and optimize for the first time the microwave hydrodiffusion and gravity (MHG) extraction of rosehips, as a novel application of solvent-free microwave extraction, previously conducted in a similar way only on mulberry, strawberry, and onion. The optimization was performed through a central composite design (CCD) by evaluating the effect of the experimental parameters on the yield; total polyphenol, flavonoid, and anthocyanin contents; radical scavenging activity; and content of vitamin C in the obtained extracts. As a result, the water moistening pretreatment was clearly revealed to possess a pivotal role in the quality of the rosehip extracts. Among the evaluated responses, the yield, the anthocyanin content, and the antioxidant activity were well described by the statistical model. Notably, the optimized MHG extract was compared with the ones obtained by conventional solvent extraction showing higher amounts of vitamin C, polyphenols, flavonoids, and anthocyanins, while the traditional extracts performed better in terms of yield. In conclusion, MHG represents a promising alternative to standard extraction methods for obtaining rosehip extracts rich in vitamin C and antioxidant compounds. In this respect, the results of our research support the employment of MHG on an industrial level for the production of rosehip-based food supplements enriched in vitamin C.
Evaluation of Roasting and Grilling Effects on Chemical Composition, Volatile Profiles, and Toxicity of Stink Bugs (Tessaratoma papillosa): Implications for Utilization as Functional Food Ingredients
Authors: Li Hua , Chumroenphat Theeraphan , Boonarsa Parinya , Yahuafai Jantana , Wrigley Colin , Siriamornpun Sirithon
Published: August 2023

The stink bug (Tessaratoma papillosa) is a highly popular edible insect in Thai traditional cuisine, but little research has investigated the effects of heat treatment on the quality of stink bugs. Therefore, we aimed to evaluate the effects of roasting and grilling on the chemical changes and volatile compounds of late nymph and adult stink bugs. In general, all treated samples showed increases in phenolic acid, tocopherols, and amino acid contents and a decrease in the content of fiber compared with raw stink bugs (p < 0.05). Cinnamic acid significantly increased by over 200% in late nymph insects and 30% in adult insects after roasting, whereas syringic acid decreased after cooking (p < 0.05). The most predominant volatile compound found in all samples was 5-methyl-octadecane and it decreased after cooking, while volatile alkane compounds increased after cooking. The processed sample extracts showed higher toxicity on oral cancer KB and cervical cancer Hela cells than on Vero cells. We have demonstrated that different cooking methods affected the chemical components which may result in quality attributes if stink bug is to be used as a functional ingredient/food. It may be helpful to improve the nutritional and functional values of stink bugs during deep processing.
Challenges in the Application of Circular Economy Models to Agricultural By-Products: Pesticides in Spain as a Case Study
Authors: Otero Paz , Echave Javier , Chamorro Franklin , Soria-Lopez Anton , Cassani Lucia , Simal-Gandara Jesus , Prieto Miguel A. , Fraga-Corral Maria
Published: August 2023

The income and residue production from agriculture has a strong impact in Spain. A circular economy and a bioeconomy are two alternative sustainable models that include the revalorization of agri-food by-products to recover healthy biomolecules. However, most crops are conventional, implying the use of pesticides. Hence, the reutilization of agri-food by-products may involve the accumulation of pesticides. Even though the waste-to-bioproducts trend has been widely studied, the potential accumulation of pesticides during by-product revalorization has been scarcely assessed. Therefore, in this study, the most common pesticides found in eight highly productive crops in Spain are evaluated according to the available published data, mainly from EFSA reports. Among these, oranges, berries and peppers showed an increasing tendency regarding pesticide exceedances. In addition, the adverse effects of pesticides on human and animal health and the environment were considered. Finally, a safety assessment was developed to understand if the reutilization of citrus peels to recover ascorbic acid (AA) would represent a risk to human health. The results obtained seem to indicate the safety of this by-product to recover AA concentrations to avoid scurvy (45 mg/day) and improve health (200 mg/day). Therefore, this work evaluates the potential risk of pesticide exposure through the revalorization of agri-food by-products using peels from citruses, one of the major agricultural crops in Spain, as a case study.
Buckwheat Flour (Fagopyrum esculentum Moench)—A Contemporary View on the Problems of Its Production for Human Nutrition
Authors: Skřivan Pavel , Chrpová Diana , Klitschová Blanka , Švec Ivan , Sluková Marcela
Published: August 2023

Buckwheat is returning to the countries of Central Europe; there are several reasons for this: firstly, due to its interesting chemical composition (proteins, fibre, and phenolic compounds), which is reflected in its nutritional value and potential health benefits. Secondly, because buckwheat, and buckwheat flour especially, are suitable raw materials for the production of gluten-free foods. Buckwheat flours are classified similarly to wheat flours, but the different anatomy of wheat grains and buckwheat seeds makes this classification partly misleading. While wheat flours are largely produced by one standard process, the production process for buckwheat flours is more varied. For wheat and wheat flours, the basic quality parameters and their required ranges for different types of primary and secondary processing are clearly defined. This is not the case for buckwheat and buckwheat flours, and the definition of the parameters and their ranges that characterize its technological quality remain unclear. The standardization of quality parameters and production processes is likely to be necessary for the potential expansion of the use of buckwheat for food production and, in particular, for bakery products.
Trends in the Use of Lipases: A Systematic Review and Bibliometric Analysis
Authors: dos Santos Lucely Nogueira , Perna Rafael Firmani , Vieira Ana Carolina , de Almeida Alex Fernando , Ferreira Nelson Rosa
Published: August 2023

Scientific mapping using bibliometric data network analysis was applied to analyze research works related to lipases and their industrial applications, evaluating the current state of research, challenges, and opportunities in the use of these biocatalysts, based on the evaluation of a large number of publications on the topic, allowing a comprehensive systematic data analysis, which had not yet been conducted in relation to studies specifically covering lipases and their industrial applications. Thus, studies involving lipase enzymes published from 2018 to 2022 were accessed from the Web of Science database. The extracted records result in the analysis of terms of bibliographic compatibility among the articles, co-occurrence of keywords, and co-citation of journals using the VOSviewer algorithm in the construction of bibliometric maps. This systematic review analysis of 357 documents, including original and review articles, revealed studies inspired by lipase enzymes in the research period, showing that the development of research, together with different areas of knowledge, presents good results related to the applications of lipases, due to information synchronization. Furthermore, this review showed the main challenges in lipase applications regarding increased production and operational stability; establishing well-defined evaluation criteria, such as cultivation conditions, activity, biocatalyst stability, type of support and reactor; thermodynamic studies; reuse cycles; and it can assist in defining goals for the development of successful large-scale applications, showing several points for improvement of future studies on lipase enzymes.
Assessing the Prevalence and Potential Risks of Salmonella Infection Associated with Fresh Salad Vegetable Consumption in the United Arab Emirates
Authors: Habib Ihab , Khan Mushtaq , Mohamed Mohamed-Yousif Ibrahim , Ghazawi Akela , Abdalla Afra , Lakshmi Glindya , Elbediwi Mohammed , Al Marzooqi Hassan Mohamed , Afifi Hanan Sobhy , Shehata Mohamed Gamal , Al-Rifai Rami
Published: August 2023

This study aimed to investigate the occurrence and characteristics of Salmonella isolates in salad vegetables in the United Arab Emirates (UAE). Out of 400 samples tested from retail, only 1.25% (95% confidence interval, 0.41–2.89) were found to be positive for Salmonella, all of which were from conventional local produce, presented at ambient temperature, and featured as loose items. The five Salmonella-positive samples were arugula (n = 3), dill (n = 1), and spinach (n = 1). The Salmonella isolates from the five samples were found to be pan-susceptible to a panel of 12 antimicrobials tested using a disc diffusion assay. Based on whole-genome sequencing (WGS) analysis, only two antimicrobial resistance genes were detected—one conferring resistance to aminoglycosides (aac(6′)-Iaa) and the other to fosfomycin (fosA7). WGS enabled the analysis of virulence determinants of the recovered Salmonella isolates from salad vegetables, revealing a range from 152 to 165 genes, collectively grouped under five categories, including secretion system, fimbrial adherence determinants, macrophage-inducible genes, magnesium uptake, and non-fimbrial adherence determinants. All isolates were found to possess genes associated with the type III secretion system (TTSS), encoded by Salmonella pathogenicity island-1 (SPI-1), but various genes associated with the second type III secretion system (TTSS-2), encoded by SPI-2, were absent in all isolates. Combining the mean prevalence of Salmonella with information regarding consumption in the UAE, an exposure of 0.0131 salmonellae consumed per person per day through transmission via salad vegetables was calculated. This exposure was used as an input in a beta-Poisson dose–response model, which estimated that there would be 10,584 cases of the Salmonella infection annually for the entire UAE population. In conclusion, salad vegetables sold in the UAE are generally safe for consumption regarding Salmonella occurrence, but occasional contamination is possible. The results of this study may be used for the future development of risk-based food safety surveillance systems in the UAE and to elaborate on the importance for producers, retailers, and consumers to follow good hygiene practices, particularly for raw food items such as leafy salad greens.
Chemical Analysis of Various Tea Samples Concerning Volatile Compounds, Fatty Acids, Minerals and Assessment of Their Thermal Behavior
Authors: Dippong Thomas , Cadar Oana , Kovacs Melinda Haydee , Dan Monica , Senila Lacrimioara
Published: August 2023

Tea is the most consumed drink worldwide due to its pleasant taste and various beneficial effects on human health. This paper assesses the physicochemical analysis of different varieties of tea (leaves, flowers, and instant) after prior drying and fine grinding. The thermal decomposition behavior of the tea components shows that the tea has three stages of decomposition, depending on temperature. The first stage was attributed to the volatilization of water, while the second stage involved the degradation of volatiles, polyphenols, and fatty acids. The degradation of cellulose, hemicellulose, and lignin content occurs at the highest temperature of 400 °C in the third stage. A total of 66 volatile compounds, divided into eight classes, were identified in the tea samples. The volatile compounds were classified into nine odor classes: floral, fruity, green, sweet, chemical, woody, citrus, roasted, and alcohol. In all flower and leaf tea samples, monounsaturated (MUFAs), polyunsaturated (PUFAs), and saturated fatty acids (SFAs) were identified. A high content of omega-6 was quantified in acacia, Saint John’s Wort, rose, and yarrow, while omega-3 was found in mint, Saint John’s Wort, green, blueberry, and lavender samples. The flower and leaf tea samples studied could be a good dietary source of polyphenolic compounds, essential elements. In instant tea samples, a low quantity of polyphenols and major elements were identified. The physicochemical analysis demonstrated that both flower and leaf teas have high-quality properties when compared to instant tea.
Research Advances of Modification and Nutraceutical Properties of Polysaccharide
Authors: Song Shuang , Ai Chunqing
Published: August 2023

As a group of important biopolymers, polysaccharides exist widely in living organisms and play many known and unknown biological roles in life activities via different pathways [...]
Economic Growth, Income Inequality and Food Safety Risk
Authors: Chen Yong-Qi , Chen You-Hua
Published: August 2023

Food safety risk, as an implicit cost of social and economic development, endangers the health of global residents, including China. To systematically understand the impact of socioeconomic development on food safety risk and to establish a sound modern governance system of food safety in China, this paper uses provincial panel data from 2011 to 2020 to explore the relationship between food safety risk and socio-economic development factors such as economic growth and income inequality by employing a two-way fixed effect model and moderating effect model. The results show that the food safety risk is a Kuznets curve, and the turning point is about RMB 58,104.59 per capita GDP (based on prices in 2011). However, under the moderating effect of income inequality, the turning point of the Kuznets curve of food safety risk will shift to the right, and the curve will be flattened. In other words, income inequality has a negative moderating effect on the “inverted U-shaped” relationship between economic growth and food safety risk. When dealing with food safety problems, the goal of stable and sustained economic growth and common prosperity should be incorporated into policy formulation to enhance the governance effectiveness of food safety risk.
A Result Regarding Finite-Time Stability for Hilfer Fractional Stochastic Differential Equations with Delay
Authors: Li Man , Niu Yujun , Zou Jing
Published: August 2023

Hilfer fractional stochastic differential equations with delay are discussed in this paper. Firstly, the solutions to the corresponding equations are given using the Laplace transformation and its inverse. Afterwards, the Picard iteration technique and the contradiction method are brought up to demonstrate the existence and uniqueness of understanding, respectively. Further, finite-time stability is obtained using the generalized Grönwall–Bellman inequality. As verification, an example is provided to support the theoretical results.
Experimental Study and Thermodynamic Analysis of Carbon Dioxide Adsorption onto Activated Carbons Prepared from Biowaste Raw Materials
Authors: Solovtsova Olga V. , Men’shchikov Ilya E. , Shkolin Andrey V. , Grinchenko Alexander E. , Khozina Elena V. , Fomkin Anatoly A.
Published: August 2023

Nutshells are regarded as cost-effective and abundant raw materials for producing activated carbons (ACs) for CO2 capture, storage, and utilization. The effects of carbonization temperature and thermochemical KOH activation conditions on the porous structure as a BET surface, micropore volume, micropore width, and pore size distribution of ACs prepared from walnut (WNS) and hazelnut (HNS) shells were investigated. As a result, one-step carbonization at 900/800 °C and thermochemical KOH activation with a char/KOH mass ratio of 1:2/1:3 were found to be optimal for preparing ACs from WNS/HNS: WNS-AC-3 and HNS-AC-2, respectively. The textural properties of the WNS/HNS chars and ACs were characterized by low-temperature nitrogen vapor adsorption, XRD, and SEM methods. Dubinin’s theory of volume filling of micropores was used to evaluate the microporosity parameters and to calculate the CO2 adsorption equilibrium over the sub- and supercritical temperatures from 216.4 to 393 K at a pressure up to 10 MPa. The CO2 capture capacities of WNS- and HNS-derived adsorbents reached 5.9/4.1 and 5.4/3.9 mmol/g at 273/293 K under 0.1 MPa pressure, respectively. A discrepancy between the total and delivery volumetric adsorption capacities of the adsorbents was attributed to the strong binding of CO2 molecules with the adsorption sites, which were mainly narrow micropores with a high adsorption potential. The high initial differential heats of CO2 adsorption onto ACs of ~32 kJ/mol confirmed this proposal. The behaviors of thermodynamic functions (enthalpy and entropy) of the adsorption systems were attributed to changes in the state of adsorbed CO2 molecules determined by a balance between attractive and repulsive CO2–CO2 and CO2–AC interactions during the adsorption process. Thus, the chosen route for preparing ACs from the nutshells made it possible to prepare efficient carbon adsorbents with a relatively high CO2 adsorption performance due to a substantial volume of micropores with a size in the range of 0.6–0.7 nm.