bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Implant Macro-Design and Magnetodynamic Surgical Preparation on Primary Implant Stability: An In Vitro Investigation
Authors: Antonelli Alessandro , Barone Selene , Attanasio Ferdinando , Salviati Marianna , Cerra Maria Giulia , Calabria Elena , Bennardo Francesco , Giudice Amerigo
Published: September 2023

Background: Macro-geometry and surgical implant site preparation are two of the main factors influencing implant stability and potentially determining loading protocol. The purpose of this study was to assess the initial stability of various implant macro-designs using both magnetodynamic and traditional osteotomy techniques in low-density bone. The parameters examined included peak insertion torque (PIT), implant stability quotient (ISQ), and peak removal torque (PRT). Methods: Four groups of 34 implants each were identified in accordance with the surgery and implant shape: T5 group (Five implant and osteotomy using drills); M5 group (Five implant and magnetodynamic osteotomy using Magnetic Mallet); TT group (TiSmart implant and osteotomy with drills); and MT group (TiSmart implant and magnetodynamic osteotomy). Every implant was placed into a low-density bone animal model and scanned using CBCT. The PIT and PRT were digitally measured in Newton-centimeters (Ncm) using a torque gauge device. The ISQ was analyzed by conducting resonance frequency analysis. Results: The PIT values were 25.04 ± 4.4 Ncm for T5, 30.62 ± 3.81 Ncm for M5, 30 ± 3.74 Ncm for TT, and 32.05 ± 3.55 Ncm for MT. The average ISQ values were 68.11 ± 3.86 for T5, 71.41 ± 3.69 for M5, 70.88 ± 3.08 for TT, and 73 ± 3.5 for MT. The PRT values were 16.47 ± 4.56 Ncm for T5, 26.02 ± 4.03 Ncm for M5, 23.91 ± 3.28 Ncm for TT, and 26.93 ± 3.96 Ncm for MT. Based on our data analysis using a t-test with α = 0.05, significant differences in PIT were observed between TT and T5 (p < 0.0001), M5 and T5 (p < 0.0001), and MT and TT (p = 0.02). Significant differences in the ISQ were found between TT and T5 (p = 0.001), M5 and T5 (p < 0.001), and MT and TT (p = 0.01). The PRT also exhibited significant differences between TT and T5, M5 and T5, and MT and TT (p < 0.0001). Conclusion: Our data showed favorable primary implant stability (PS) values for both implant macro-geometries. Furthermore, the magnetodynamic preparation technique appears to be more effective in achieving higher PS values in low-density bone.
Investigation of the JPA-Bandwidth Improvement in the Performance of the QTMS Radar
Authors: Norouzi Milad , Seyed-Yazdi Jamileh , Hosseiny Seyed Mohammad , Livreri Patrizia
Published: September 2023

Josephson parametric amplifier (JPA) engineering is a significant component in the quantum two-mode squeezed radar (QTMS) to enhance, for instance, radar performance and the detection range or bandwidth. We simulated a proposal of using engineered JPA (EJPA) to enhance the performance of a QTMS radar. We defined the signal-to-noise ratio (SNR) and detection range equations of the QTMS radar. The engineered JPA led to a remarkable improvement in the quantum radar performance, i.e., a large enhancement in SNR of about 6 dB more than the conventional QTMS radar (with respect to the latest version of the QTMS radar and not to the classical radar), a substantial improvement in the probability of detection through far fewer channels. The important point in this work was that we expressed the importance of choosing suitable detectors for the QTMS radars. Finally, we simulated the transmission of the signal to the target in the QTMS radar and obtained a huge increase in the QTMS radar range, up to 482 m in the current study.
A Dual Blind Watermarking Method for 3D Models Based on Normal Features
Authors: Tang Qijian , Li Yanfei , Wang Qilei , He Wenqi , Peng Xiang
Published: September 2023

Digital watermarking technology is an important means to effectively protect three-dimensional (3D) model data. Among them, “blind detection” and “robustness” are key and difficult points in the current research of digital watermarking technology based on 3D models. In order to realize the blind detection of a watermark and improve its robustness against various common attacks at the same time, this paper proposes a dual blind watermarking method based on the normal feature of the centroid of first-ring neighboring points. The local spherical coordinate system is constructed by calculating two different normal vectors, and the first pattern watermark and the second random binary sequence watermark are embedded, respectively. The experimental results show that this method can not only realize the blind detection of dual watermarks, but also have the ability to resist common attacks such as translation, rotation, scaling, cropping, simplification, smoothing, noise, and vertex reordering to a certain extent.
The Information Bottleneck’s Ordinary Differential Equation: First-Order Root Tracking for the Information Bottleneck
Authors: Agmon Shlomi
Published: September 2023

The Information Bottleneck (IB) is a method of lossy compression of relevant information. Its rate-distortion (RD) curve describes the fundamental tradeoff between input compression and the preservation of relevant information embedded in the input. However, it conceals the underlying dynamics of optimal input encodings. We argue that these typically follow a piecewise smooth trajectory when input information is being compressed, as recently shown in RD. These smooth dynamics are interrupted when an optimal encoding changes qualitatively, at a bifurcation. By leveraging the IB’s intimate relations with RD, we provide substantial insights into its solution structure, highlighting caveats in its finite-dimensional treatments. Sub-optimal solutions are seen to collide or exchange optimality at its bifurcations. Despite the acceptance of the IB and its applications, there are surprisingly few techniques to solve it numerically, even for finite problems whose distribution is known. We derive anew the IB’s first-order Ordinary Differential Equation, which describes the dynamics underlying its optimal tradeoff curve. To exploit these dynamics, we not only detect IB bifurcations but also identify their type in order to handle them accordingly. Rather than approaching the IB’s optimal tradeoff curve from sub-optimal directions, the latter allows us to follow a solution’s trajectory along the optimal curve under mild assumptions. We thereby translate an understanding of IB bifurcations into a surprisingly accurate numerical algorithm.
An Introduction to Complex Networks in Climate Finance
Authors: Kartun-Giles Alexander P. , Ameli Nadia
Published: September 2023

In this perspective, we introduce recent research into the structure and function of complex investor networks supporting sustainability efforts. Using the case of solar, wind and hydro energy technologies, this perspective explores the complexity in low-carbon finance markets, defined as markets that direct capital flows towards low-carbon technologies, using network approaches to study their structure and dynamics. Investors are modeled as nodes which form a network or higher-order network connected by edges representing projects in which joint funding or security-related insurance was provided or other investment-related interaction occurred. We review the literature on investor networks generally, particularly in the case of complex networks, and address areas where these ideas were applied in this emerging field. The complex investor dynamics which emerge from the extant funding scenarios are not well understood. These dynamics have the potential to result in interesting non-linear behaviour, growth, and decline, which can be studied, explained and controlled using the tools of network science.
State Space Modeling of Event Count Time Series
Authors: Moontaha Sidratul , Arnrich Bert , Galka Andreas
Published: September 2023

This paper proposes a class of algorithms for analyzing event count time series, based on state space modeling and Kalman filtering. While the dynamics of the state space model is kept Gaussian and linear, a nonlinear observation function is chosen. In order to estimate the states, an iterated extended Kalman filter is employed. Positive definiteness of covariance matrices is preserved by a square-root filtering approach, based on singular value decomposition. Non-negativity of the count data is ensured, either by an exponential observation function, or by a newly introduced “affinely distorted hyperbolic” observation function. The resulting algorithm is applied to time series of the daily number of seizures of drug-resistant epilepsy patients. This number may depend on dosages of simultaneously administered anti-epileptic drugs, their superposition effects, delay effects, and unknown factors, making the objective analysis of seizure counts time series arduous. For the purpose of validation, a simulation study is performed. The results of the time series analysis by state space modeling, using the dosages of the anti-epileptic drugs as external control inputs, provide a decision on the effect of the drugs in a particular patient, with respect to reducing or increasing the number of seizures.
Entropy of Charge Inversion in DNA including One-Loop Fluctuations
Authors: Sievert Matthew D. , Bishop Marilyn F. , McMullen Tom
Published: September 2023

The entropy and charge distributions have been calculated for a simple model of polyelectrolytes attached to the surface of DNA using a field-theoretic method that includes fluctuations to the lowest one-loop order beyond mean-field theory. Experiments have revealed correlation-driven behavior of DNA in charged solutions, including charge inversion and condensation. In our model, the condensed polyelectrolytes are taken to be doubly charged dimers of length comparable to the distance between sites along the phosphate chains. Within this lattice gas model, each adsorption site is assumed to have either a vacancy or a positively charged dimer attached with the dimer oriented either parallel or perpendicular to the double-helix DNA chain. We find that the inclusion of the fluctuation terms decreases the entropy by ∼50% in the weak-binding regime. There, the bound dimer concentration is low because the dimers are repelled from the DNA molecule, which competes with the chemical potential driving them from the solution to the DNA surface. Surprisingly, this decrease in entropy due to correlations is so significant that it overcompensates for the entropy increase at the mean-field level, so that the total entropy is even lower than in the absence of interactions between lattice sites. As a bonus, we present a transparent exposition of the methods used that could be useful to students and others wishing to use this formulation to extend this calculation to more realistic models.
An Exploratory Study of Helping Undergraduate Students Solve Literature Review Problems Using Litstudy and NLP
Authors: Wong Gary K. W. , Li Simon Y. K.
Published: September 2023

(1) Many undergraduate students struggle to produce a good literature review in their dissertations, as they are not experienced, do not have sufficient time, and do not have the required skills to articulate information. (2) Subsequently, we deployed Litstudy and NLP tools and developed a recommendation system to analyze articles in an academic database to help the students produce literature reviews. (3) The recommendation system successfully performed three levels of analysis. The elementary-level analysis provided demographic statistical analysis to the students, helping them understand the background information of the selected articles they would review. The intermediate-level analysis provided visualization of citations in network graphs for the students to understand the relationships of the articles’ authors, regions, and institutes so that the flow of ideas, development, and similarity of the selected articles can be better analyzed. The advanced level of analysis provided topic modeling functions for the students to understand the high-level themes of the selected articles to improve productivity as they read through them and simultaneously boost their creativity. (4) The three levels of analysis successfully analyzed the selected articles to provide innovative results and triggered the students to handle literature reviews in a new way. Further enhancement opportunities were identified in integrating the NLP technologies with large language models to facilitate the generation of research ideas/insights. This would be an exciting opportunity to have AI/NLP integrated to help the students with their research.
Predictors of Bullying among Athletes in the Romanian Context
Authors: Nichifor Florin , Marian Andrei-Lucian , Tiţă Silviu-Mihail
Published: September 2023

The purpose of this study was to examine the explanatory power of a predictive model of bully/perpetrator behaviour in Romanian athletes, consisting of negative pre-competitive emotions (anxiety, sadness, and anger), perception of male gender normativity, and relationships with coaches and teammates. Additionally, we aimed to explore the mediation effect of bully–victim behaviour on the relationship between athletes’ connections with their coaches and bully/perpetrator behaviour. The current research involved a nonexperimental, cross-sectional design exploring the presence of bully/perpetrator behaviour in Romanian male and female athletes. The quantitative methodology was used to collect and analyse the data obtained. Researchers translated, adapted and pretested the questionnaire set to the Romanian cultural background (SEQ, MAMS, CART-Q, In-group Ties Scale, BSQ) before distributing it to 448 participants. 58.7% were male participants, and 41.3% were female participants. The mean age was 21.15 (SDage = 2.37, range = 18–32). The research was conducted in the first half of 2023. SPSS (V. 20) and Hayes’s PROCESS tool were used to investigate the data. The findings demonstrated that in the case of Romanian male athletes, perception of male gender normativity, anger, and weaker connections with coaches are the most important psychological factors in predicting bully/perpetrator behaviour. In contrast, in the case of Romanian female athletes, only weaker connections with coaches and perception of male gender normativity play an essential role in explaining bully/perpetrator behaviour. Additionally, the study demonstrated that bully–victim behaviour mediates the relationship between athletes’ weaker connections with their coaches and bully/perpetrator behaviour. Athletes’ weaker connections with their coaches lead to experiencing a high level of bully/perpetrator behaviour by stressing bully–victim behaviour, which also contributes to achieving a high level of bully/perpetrator behaviour.
Privacy-Preserving Attestation Scheme for Revocable UAV Charging Using Hybrid State Channels
Authors: Jia Xuedan , Song Xiangmei , Yu Chuntang
Published: September 2023

Although widely applied in varied scenarios, unmanned aerial vehicles (UAVs) suffer severe flight time and flight range limitations due to constrained onboard battery capacity, causing frequent battery recharging when performing persistent missions. The wireless power transfer technology is a promising solution for UAV charging by utilizing unmanned ground vehicles (UGVs) equipped with wireless charging facilities, where charging time slots are auctioned and assigned to UAVs. However, UGVs themselves also have limited energy capacity, resulting in the need to revoke a UAV charging transaction after auction to satisfy their own demand if necessary. In addition, as UAVs and UGVs are mutually distrustful, inherent security and privacy concerns must be resolved during the revocation. In this paper, we resort to blockchain technology for secure and efficient revocable charging in vehicle-assisted wireless UAV networks. We present PAS, an efficient privacy-preserving attestation scheme for revocable UAV charging based on hybrid state channels, where UAVs and UGVs perform off-chain operations as blockchain users for privacy and efficiency, while security and fairness are guaranteed by the on-chain mechanism. PAS consists of a multi-party state channel and multiple two-party state channels responsible for charging scheduling and transaction revocation, respectively. PAS ensures fair and private revocation negotiation and compensation in a trust-free manner by developing a set of carefully designed modular protocols. We provide PAS’ constituent primitives in detail, prove its security properties following the universally composable (UC) framework, and present experimental results to demonstrate its feasibility and scalability.
High Step-Up Converter
Authors: Hwu Kuo-Ing , Tseng Pei-Ching
Published: September 2023

A new high-boost converter derived from a charge-pump capacitor-based dual-boost converter is presented herein. Compared with the existing charge-pump capacitor-based dual-boost inductor converter, this structure adds an additional voltage-doubling circuit and additional coil to the original circuit to increase the voltage conversion ratio and winds the three coils around the same magnetic element. By this way, the overall size of the circuit can be reduced, and the leakage energy of the coupled inductor can be recovered. In this paper, the proposed new high-boost converter is firstly explained and analyzed, followed by simulations to demonstrate the feasibility of the proposed circuit and finally the experimental results to verify its effectiveness.
Multi-Objective Optimization Design of the External Rotor Permanent Magnet-Assisted Synchronous Reluctance Motor Based on the Composite Algorithm
Authors: Li Guoshuai , Sun Huiqin , Hu Weiguang , Li Ying , Bai Yongqiang , Guo Yingjun
Published: September 2023

Based on the complex structural characteristics of permanent magnet-assisted synchronous reluctance motors (PMA-SynRMs), this paper proposes a multi-objective optimization design method for the motor using a composite algorithm. Firstly, the power density, electromagnetic torque, cogging torque, and torque fluctuation coefficient were used as optimization targets based on parametric analysis data of 14 motor structure variables, where parametric sensitivity analysis helped select eight optimization variables. Secondly, the motor prediction model was fitted using the genetic algorithm–back propagation (GA-BP) neural network. Finally, non-dominated sorting genetic algorithm-III (NSGA-III), based on the reference points, was used to find the optimization of the prediction model and complete the multi-objective optimization design of the external rotor PMA-SynRM with eight inputs and four outputs. A comparative analysis of the electromagnetic performance of the motor before and after optimization verifies the feasibility of optimizing the motor using the composite algorithm. This paper provides an analytical tool for the multi-parameter and multi-objective PMA-SynRM optimization design.
Realization of Unity Power Factor Wireless Power Transfer System under Subnormal Operation Conditions
Authors: Zhang Liyong , Zhang Pengyu , Li Wenwu , He Zhonghao
Published: September 2023

The power factor of wireless power transfer system, determined by its compensation network part, is easily affected by parameter detuning, coil misalignment, and load variation. In this paper, a mathematical model for the compensation network part is established. Theoretical analysis shows that the inverter part can be considered as a negative resistor by deducing the inherent static-state frequency solution of the compensation network part. Therefore, the unity power factor wireless power transfer system can be maintained under any possible operation conditions by tracking the inherent static-state frequency solution. More importantly, no digital controller or parameter identification or information interactions between the primary and secondary coils are needed during the tracking process. Compared with previous unity power factor realization methods, the proposed tracking strategy has the advantages of fewer sampling variables, a faster response time, and a simpler regulation process. Finally, an experimental platform is built to test the practical performance of the proposed tracking strategy under many subnormal operation conditions. Our experimental results show that approximate unity power factor can be realized at 10–15 cm coil misalignment distance and 30–90 Ω load variation range.
New Hybrid Graph Convolution Neural Network with Applications in Game Strategy
Authors: Xu Hanyue , Seng Kah Phooi , Ang Li-Minn
Published: September 2023

Deep convolutional neural networks (DCNNs) have enjoyed much success in many applications, such as computer vision, automated medical diagnosis, autonomous systems, etc. Another application of DCNNs is for game strategies, where the deep neural network architecture can be used to directly represent and learn strategies from expert players on different sides. Many game states can be expressed not only as a matrix data structure suitable for DCNN training but also as a graph data structure. Most of the available DCNN methods ignore the territory characteristics of both sides’ positions based on the game rules. Therefore, in this paper, we propose a hybrid approach to the graph neural network to extract the features of the model of game-playing strategies and fuse it into a DCNN. As a graph learning model, graph convolutional networks (GCNs) provide a scheme by which to extract the features in a graph structure, which can better extract the features in the relationship between the game-playing strategies. We validate the work and design a hybrid network to integrate GCNs and DCNNs in the game of Go and show that on the KGS Go dataset, the performance of the hybrid model outperforms the traditional DCNN model. The hybrid model demonstrates a good performance in extracting the game strategy of Go.
Improving the Feed-in Tariff Policy for Renewable Energy Promotion in Ukraine’s Households
Authors: Kurbatova Tetiana , Sotnyk Iryna , Prokopenko Olha , Bashynska Iryna , Pysmenna Uliana
Published: September 2023

This paper deals with improving the feed-in tariff policy for green energy advancement in Ukraine’s households based on assessing the economic efficiency of investment project implementation under the current state support mechanisms. This study was conducted for solar and wind power plants with different installed capacities. The Levelized Cost of Electricity and the payback period for such power plants were calculated considering the ongoing feed-in tariffs and discount rates determined by various equity and debt capital ratios. The results showed that the state support provides attractive payback periods for solar and wind power plants with an installed capacity of ≥30 kW. In comparison, 5 kW solar power plants and wind power plants with a capacity of up to 10 kW are not paid off during the power plants’ lifecycle. It confirmed that the ongoing energy policy in Ukraine’s residential sector is still designed to obtain profits by the owners of generating facilities by selling the excess electricity. In the meantime, its main goal—providing households energy independence—has been levelled. To resolve the issues caused by such a state support model, a methodical approach to improve the feed-in tariff calculation is proposed. In addition, recommendations for reconsidering other policy measures to ensure effective renewable energy development in the residential sector have been made.
Optimal Allocation of Primary Frequency Modulation Capacity of Battery Energy Storage Based on Antlion Algorithm
Authors: Yang Hui , Huang Renshuang , Shi Ming , Yan Zutai , Yan Laiqing
Published: September 2023

Currently, the integration of new energy sources into the power system poses a significant challenge to frequency stability. To address the issue of capacity sizing when utilizing storage battery systems to assist the power grid in frequency control, a capacity optimal allocation model is proposed for the primary frequency regulation of energy storage. Due to the requirement of a large number of actual parameters for the optimal allocation model, a simulation model of energy storage capacity is constructed based on the characteristics of primary frequency control to provide the necessary parameters. Subsequently, the primary frequency modulation output model of energy storage is established by considering the basic action output, the action in the frequency modulation dead zone, and a certain capacity margin. The antlion algorithm is employed to solve the capacity optimal allocation model. Finally, three groups of experiments are designed and compared to demonstrate the effectiveness of the proposed method in setting the capacity margin, which can increase profit to a certain extent.
An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components
Authors: Zhu Hongxin , Dai Shun , Zhang Xiaoyi , Chen Jian , Luo Mingyu , Huang Weiguang
Published: September 2023

The failure of gas turbines’ hot components due to fatigue significantly affects their efficient and stable operation. Conducting online damage assessment of components subjected to complex cyclic loads based on the working conditions of gas turbines can provide real-time reflection of component fatigue damage and achieve the purpose of predictive maintenance. In this study, we propose an online cycle counting method that considers temperature fluctuations during the cycle process. Our method is based on the four-point online rainflow counting method by coupling the counting variable with time, introducing the concept of the duration time for full cycles and half cycles, and incorporating a characteristic temperature that better represents the temperature information during the cycle process. With reference to the characteristic temperature, our proposed method comprehensively considers the form and parameters of subsequent life assessment models. This paper provides a detailed explanation of the proposed method and applies it to the fatigue damage assessment of turbine vanes in a micro gas turbine, thereby verifying its accuracy and applicability.
Assessing Circularity in the Wood Industry—Methodology, Tool and Results
Authors: Dragomir Mihai , Tofană Silvia , Dragomir Diana , Țîțu Aurel Mihail , Popescu Daniela
Published: September 2023

The article presents a complete approach for the wood industry for assessing the state of circular economy adoption by companies. A methodology for achieving this purpose is proposed and then implemented with the help of a specific questionnaire. The study is based on a literature survey with two components, one relating to reports on the concept of circularity and one relating to the methodological aspects of determining and measuring the progress of companies. Starting from these aspects and factoring in the sectoral evolution in Romania, the assessment directions and detailed questions for each are established essentially through a mind-mapping process. For validation, the questionnaire with seven evaluation viewpoints covered in 28 items is applied within the Romanian wood industry to 60 companies. The analysis of results is carried out using descriptive and inferential statical methods, such as ANOVA, showing good progress of the industry at company level, through individual efforts as well as the need to continue the transformation of the sector from the point of view of regulatory oversight and market acceptance. A set of recommendations for companies to advance their situation is proposed to help the maturation of the current circular approaches.
Optimizing Wildlife Habitat Management in Socio-Ecological Systems: An Evolutionary Game Theory Approach
Authors: Wang Rui , Chen Wenhui , Liang Xingyue
Published: September 2023

This paper focuses on the issue of balancing interests between stakeholders and ecosystems in the process of wildlife habitat conservation. By employing evolutionary game theory, an analysis framework for the socio-ecological system of wildlife habitats is constructed, comprising four main entities: central government, farmers, local government, and ecosystems. This framework explores the influencing factors of habitat protection strategies adopted by various stakeholders and the conditions required for the socio-ecological system to evolve towards an ideal state. In this paper, we analyze how the central government can design cost–benefit-based policy mechanisms, control the evolution of the socio-ecological system by altering conditions, and achieve a balance of interests among all parties involved in the habitat protection process. In this study, we find that the central government should establish disturbance monitoring indicators for human activities and ecological restoration, based on different compensation standards. Moreover, the hierarchical management of wildlife habitat according to different management levels can enhance the probability of the socio-ecological system evolving towards an ideal state, while achieving the sum of social costs. Additionally, shifting the compensation strategies for farmers and local governments from cost compensation to benefit compensation will reduce the harmful costs that the ecosystem imposes on the social system, thereby facilitating the realization of an ideal wildlife habitat protection and management model. Therefore, the central government should intensify compensation efforts and design reasonable compensation standards, transitioning the compensation function from cost recovery to income generation. Simultaneously, guidance should be provided to farmers for the rational utilization of forest resources to increase their income. The alignment of agricultural activities with habitat protection goals should be encouraged, and local governments should establish mechanisms for realizing the value of ecological products, making relatively implicit long-term social welfare explicit.
First Report on a Cliff-Nesting Pair of Black Storks (Ciconia nigra Linnaeus, 1758) and Their Nestlings
Authors: Freschi Pierangelo , Cosentino Carlo , Napolitano Fabio , Pacelli Corrado , Manicone Danilo , Mallia Egidio , Ragni Marco , Paolino Rosanna , Braghieri Ada
Published: September 2023

The black stork is an endangered species in many countries, due to its low adaptability to environmental changes and its sensitivity to anthropogenic disturbances. In Italy, the most recent report on the species’ nesting sites lists only 36 pairs, of which 16 are in Basilicata, 7 are in Calabria, 4 are in Piedmont and Molise and 1 is in Campania. This study focuses for the first time on the behavior of a Ciconia nigra pair in the Basilicata region, where the species nests exclusively on cliffs rather than in trees, as is more frequent elsewhere. The video recordings were used to observe the species during the pre- and post-hatching periods and to refer to the 2012 nesting season, as in that year, the video recordings covered the entire reproductive period. In the pre-hatching phase, the activity for which most time is spent is brooding, which lasts on average 43′ in the morning and in evening and more than 49′ at midday. In the post-hatching phase, a large part of the recording period is spent on activities related to parental care. There were no moments of inactivity during this phase, the parents were frequently observed setting up the nest and preening themselves, while they were rarely seen in a huddled position. The alert activity was also very frequent, especially at midday. Our study has shown that the black stork, a shy and cautious species, may return to nest in increasing numbers given the development of the promising Lucanian nucleus, if attention is paid to the habitat quality and feeding areas, where human activities should be avoided unless absolutely necessary.
Detection of the Microbial Composition of Some Commercial Fermented Liquid Products via Metagenomic Analysis
Authors: Çelik Doğan Cansu , Yüksel Dolgun Hafize Tuğba , İkiz Serkan , Kırkan Şükrü , Parın Uğur
Published: September 2023

The fermented liquid sector is developing all over the world due to its contribution to health. Our study has contributed to the debate about whether industrially manufactured fermented liquids live up to their claims by analyzing pathogens and beneficial bacteria using a 16S rRNA sequencing technique called metagenomic analysis. Paenibacillus, Lentibacillus, Bacillus, Enterococcus, Levilactobacillus, and Oenococcus were the most abundant bacterial genera observed as potential probiotics. Pseudomonas stutzeri, Acinetobacter, and Collimonas, which have plant-growth-promoting traits, were also detected. The fact that we encounter biocontroller bacteria that promote plant growth demonstrates that these organisms are widely used in foods and emphasizes the necessity of evaluating them in terms of public health. Their potential applications in agriculture may pose a danger to food hygiene and human health in the long term, so our data suggest that this should be evaluated.
Investigation of 60Co Irradiation on the Volatile Organic Compounds from Finger Citron (Citri Sarcodactylis Fructus) Using GC–IMS
Authors: Xiang Yun , Lei Chang , Hu Ge , Zhou Wei , Li Ya , Huang Dan
Published: September 2023

In recent years, as the desire for a healthy lifestyle has become more widespread, consumers are gaining an increasing appreciation for safe, high-quality food. Researchers are constantly seeking new ways to protect foods from insect pests and fungi. This study used GC-IMS to analyze the volatile organic compounds and flavor characteristics of Finger Citron in response to different doses of 60Co irradiation. The principal component analysis method was used to explore the overall differences in flavor spectra, and a total of 60 compounds were identified. The fingerprints of volatile organic compounds in the samples showed that the volatile organic compounds with doses of 60Co irradiation in about 0 kGy and 5 kGy are similar, while the 10 kGy samples are quite different. The PCA results showed that the similarity between 0 kGy and 5 kGy was slightly higher, and the difference between 10 kGy and other samples was greater. Therefore, it was determined that 60Co irradiation with a 10 kGy intensity has a significant influence on the content of volatile oils components, while 60Co irradiation with a 5 kGy intensity has little effect. Irradiation technology is demonstrated as a promising method of food sterilization, but the irradiation dose and chemical composition must be taken into consideration.
Quantitative Profiling of Carotenoids, Tocopherols, Phytosterols, and Fatty Acids in the Flower Petals of Ten Marigold (Tagetes spp. L.) Cultivars
Authors: Saini Ramesh Kumar , Ahn Hui-Yeon , Park Geon-Woo , Shin Ji-Won , Lee Jung-Hoon , Yu Ji-Woo , Song Min-Ho , Keum Young-Soo , Lee Ji-Ho
Published: September 2023

Marigold (Tagetes spp.) flower petals are the most vital sources of carotenoids, especially lutein esters, for the production of natural lutein to use for food, feed, and pharmaceutical industries. Several marigold cultivars are cultivated globally; however, their lutein ester composition and contents have not been widely investigated. Considering this, this study aimed to identify and quantify prominent carotenoid esters from the flower petals of ten marigold cultivars by liquid chromatography (LC)–diode-array detection (DAD)–mass spectrometry (MS). In addition, tocopherols, phytosterols, and fatty acids were analyzed by gas chromatography (GC)–flame ionization detection (FID) and GC–MS. Furthermore, the 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS•+) and 2,2-diphenyl-1-picrylhydrazyl (DPPH•) radical scavenging abilities of lipophilic extracts were determined. The total carotenoid contents varied significantly (p < 0. 05, Tukey HSD) among cultivars, ranging from 25.62 (cv. Alaska)–2723.11 µg/g fresh weight (cv. Superboy Orange). Among the five major lutein-diesters, (all-E)-lutein-3-O-myristate-3′-O-palmitate and lutein dipalmitate were predominant. Among the studied cultivars, α-tocopherol was recorded, ranging from 167.91 (cv. Superboy Yellow) to 338.50 µg/g FW (cv. Taishan Orange). Among phytosterols, β-sitosterol was the most prevalent phytosterol, ranging between 127.08 (cv. Superboy Yellow) and 191.99 µg/g FW (cv. Taishan Yellow). Palmitic acid (C16:0; 33.36–47.43%) was the most dominant among the fatty acids. In this study, the highest contents of lutein were recorded from cv. Superboy Orange; however, due to the substantially higher flower petal yield, the cv. Durango Red can produce the highest lutein yield of 94.45 kg/ha. These observations suggest that cv. Durango Red and cv. Superboy Orange are the ideal candidates for lutein fortification in foods and also for commercial lutein extraction.
Enhancing Bread’s Benefits: Investigating the Influence of Boosted Native Sourdough on FODMAP Modulation and Antioxidant Potential in Wheat Bread
Authors: Pejcz Ewa , Lachowicz-Wiśniewska Sabina , Nowicka Paulina , Wojciechowicz-Budzisz Agata , Harasym Joanna
Published: September 2023

This study aimed to assess the impact of bacterial species and fermentation time on wheat bread quality, FODMAP (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) content, and antioxidant activity of wheat bread, utilizing boosted native sourdough as a novel approach to enhance bread production. The incorporation of lactic acid bacteria strains, i.e., Lacticaseibacillus casei and Lactiplantibacillus plantarum, during 72 h fermentation significantly reduced FODMAP content to less than 0.1 g/100 g of wheat bread. Extending the fermentation time to 72 h notably increased the polyphenol content to 145.35 mg gallic acid (GA) per 100 g in the case of spontaneous fermentation and to 151.11 and 198.73 mg GA/100 g in the case of sourdoughs inoculated with L. casei and L. plantarum, respectively. While the treatment yielded positive effects on FODMAP modulation and antioxidant activity, it is crucial to acknowledge its impact on some organoleptic properties, such as aroma and flavor, which, despite good overall bread quality, have changed as a result of prolonged fermentation time. The study results indicate that choosing specific bacterial species and controlling fermentation time can effectively reduce FODMAPs and boost antioxidants. These findings contribute to the understanding of sourdough-based interventions in bread production, offering insights for the development of healthier and nutritionally improved wheat bread products.
Effect of Thermal Inactivation on Antioxidant, Anti-Inflammatory Activities and Chemical Profile of Postbiotics
Authors: Sun Zhe , Zhao Zhi , Fang Bing , Hung Weilian , Gao Haina , Zhao Wen , Lan Hanglian , Liu Mingkun , Zhao Liang , Zhang Ming
Published: September 2023

Inactivation is a crucial step in the production of postbiotics, with thermal inactivation being the prevailing method employed. Nevertheless, the impact of thermal treatment on bioactivity and chemical composition remains unexplored. The objective of this study was to assess the influence of heating temperature on the antioxidant, anti-inflammatory properties and the chemical composition of ET-22 and BL-99 postbiotics. The findings revealed that subjecting ET-22 and BL-99 to thermal treatment ranging from 70 °C to 121 °C for a duration of 10 min effectively deactivated them, leading to the disruption of cellular structure and release of intracellular contents. The antioxidant and anti-inflammatory activity of ET-22 and BL-99 postbiotics remained unaffected by mild heating temperatures (below 100 °C). However, excessive heating at 121 °C diminished the antioxidant activity of the postbiotic. To further investigate the impact of thermal treatments on chemical composition, non-targeted metabolomics was conducted to analyze the cell-free supernatants derived from ET-22 and BL-99. The results revealed that compared to mild inactivation at temperatures below 100 °C, the excessive temperature of 121 °C significantly altered the chemical profile of the postbiotic. Several bioactive components with antioxidant and anti-inflammatory properties, including zomepirac, flumethasone, 6-hydroxyhexanoic acid, and phenyllactic acid, exhibited a significant reduction in their levels following exposure to a temperature of 121 °C. This decline in their abundance may be associated with a corresponding decrease in their antioxidant and anti-inflammatory activities. The cumulative evidence gathered strongly indicates that heating temperatures exert a discernible influence on the properties of postbiotics, whereby excessive heating leads to the degradation of heat-sensitive active constituents and subsequent diminishment of their biological efficacy.
The Influence of Enzymatic Hydrolysis on Bee Pollen Antioxidant and Antibacterial Activities
Authors: Damulienė Vaida , Kaškonienė Vilma , Kaškonas Paulius , Maruška Audrius
Published: September 2023

Bee pollen is one of the most valuable apitherapeutic products with high nutritional value. To obtain a higher diversity of compounds, higher bioactivity, and improve the release of nutrients from bee pollen, additional processing of the raw material may be applied: fermentation using microorganisms or hydrolysis using selective enzymes. This research aimed to determine the impact of enzymatic hydrolysis on the antioxidant and antibacterial activities of bee pollen. Bee pollen samples from Sweden, Spain, Netherlands, Italy, Poland, Denmark, Slovakia, Malta, and Lithuania were hydrolyzed using pure enzymes, including lipase, cellulase, protease, and amyloglucosidase, as well as enzyme mixtures such as Viscozyme® L and Clara-diastase. Total phenolic content, total flavonoid content, and antioxidant activity were analyzed spectrophotometrically. Antibacterial activity against Staphylococcus aureus, Listeria monocytogenes, Staphylococcus enteritidis, and Salmonella typhimurium was evaluated using the agar well diffusion assay. Obtained results revealed a positive effect of enzymatic hydrolysis on biologically active compound content and activity: total phenolic content increased by 1.1 to 2.5 times, total flavonoid content by 1.1 to 3.0 times, radical scavenging activity by 1.1–3.5 times, and antibacterial activity by 1.1 to 3.3 times. K-means clustering analysis grouped samples into 5–9 clusters and was dependent on the measured characteristic used as an input—total phenolic compounds content, total flavonoid content, antioxidant activity, and antibacterial activity against four different bacteria. Chemometrics showed, that the enzyme used for the hydrolysis had a higher impact on clustering results than the geographical origin of the samples.
Assessment of Functional Properties of Wheat–Cassava Composite Flour
Authors: Li Mingjuan , Zhang Yayuan , You Xiangrong , Wang Ying , Zhou Kui , Wei Ping , Wei Linyan
Published: September 2023

Cassava flour (CF) was used as a raw material to replace wheat flour (WF) at levels of 0% (control), 10%, 20%, 30%, 40%, and 50% to prepare wheat–cassava composite flour (W-CF) and dough. The effects of different CF substituting levels on the functional properties of the W-CF and dough were investigated. The results show that an increase in CF led to a decrease in the moisture, protein, fat, and b* values of W-CF. The crude fiber, ash, starch, L*, a* values, iodine blue value (IBV), and swelling power (SP) of the composite flour increased gradually. It was found that the water absorption, hardness, and chewiness of the W-CF dough increased with an increase in the CF substitution level. A different trend could be observed with the springiness and cohesiveness of the W-CF dough. The resistance to extension, extensibility, and the extended area of the W-CF dough at all substitution levels was significantly lower than that of the WF dough. The elasticity and cohesiveness of the dough tended to increase for CF content from 10% to 30%, followed by a decrease at a higher replacement. Pearson correlation analysis indicated that the substitution levels of CF had a significant influence on the proximate analysis and functional properties of the W-CF and dough. This study will provide important information on choosing CF substitution levels for different products.
The Averaging Principle for Hilfer Fractional Stochastic Evolution Equations with Lévy Noise
Authors: Yang Min , Lv Ting , Wang Qiru
Published: September 2023

This article focuses on deriving the averaging principle for Hilfer fractional stochastic evolution equations (HFSEEs) driven by Lévy noise. We show that the solutions of the averaged equations converge to the corresponding solutions of the original equations, both in the sense of mean square and of probability. Our results enable us to focus on the averaged system rather than the original, more complex one. Given that the existing literature on the averaging principle for Hilfer fractional stochastic differential equations has been established in finite-dimensional spaces, the novelty here is the derivation of the averaging principle for a class of HFSEEs in Hilbert space. Furthermore, an example is allotted to illustrate the feasibility and utility of our results.
Multifractal Characteristics of Uranium Grade Distribution and Spatial Regularities in a Sandstone-Type Uranium Deposit in Xinjiang, China
Authors: Cai Qiue , Tan Kaixuan , Zhu Junjie , Zeng Sheng
Published: September 2023

Based on an analysis of the spatial distribution of uranium grade in 338 boreholes of a uranium deposit in Xinjiang, the enrichment and spatial variation of uranium ore in two stopes of the deposit are discussed using multifractal theory. The distribution characteristics of the uranium ore of the two stopes are studied by multifractal parameters: the scaling exponent of mass τ(q), the scaling exponent α(q) of each sub-set and its corresponding fractal dimension f(α), the fractal dimension D0 and information dimension D1. The differences of uranium distribution in the two stopes can be quantified well by using multifractal spectrum and multifractal parameters such as Δα, Δf and R. After a comprehensive multifractal distribution analysis, 10 m × 10 m is defined as a fence unit, and the window sizes ε=3,6,9⋯,45 are set; the singularity exponents α of the two stopes are calculated by using this element concentration–area method. The results show that the multifractal theory and model can organically combine spatial structure information, scale change information and anisotropy information to obtain low-grade and weak mineral resources information and can effectively distinguish complex and superimposed anomalies. This will provide a basis for the local concentration and spatial variation rules of uranium distribution and the design of the parameters of the leaching uranium mining well site.
Immobilization of Lipases on Chitosan Hydrogels Improves Their Stability in the Presence of the Products of Triglyceride Oxidation
Authors: Pirozzi Domenico , Latte Alessandro , Sannino Filomena
Published: September 2023

A significant bottleneck for the industrial application of lipases stems from their poor stability in the presence of commercial triglycerides. This is mainly due to the inactivating effect of the products of triglyceride oxidation (PTO), which are usually produced when oils and fats, being imported from far countries, are stored for long periods. In this study, the immobilization of a lipase from Candida rugosa on chitosan hydrogels has been carried out following two alternative approaches based on the enzyme adsorption and entrapment to increase the lipase stability under the operating conditions that are typical of oleochemical transformations. The effect of model compounds representing different classes of PTO on a lipase has been studied to optimize the enzyme immobilization method. Particular attention has been devoted to the characterization of the inactivating effect of PTO in nonaqueous media, which are adopted for most industrial applications of lipases.