bluuebunny/crossref_metadata_2025 huggingface dataset:
ecoSync: An Energy-Efficient Clock Discipline Data Synchronization in Wi-Fi IoMT Systems
Authors: Puckett Steven , Jovanov Emil
Published: October 2023

The growth of the Internet of Medical Things (IoMT) and healthcare data analytics allows wearable Wireless Body Area Networks (WBANs) and ambient sensors to collect the large quantities of physiological signals necessary for better patient diagnostics and treatments. Artificial intelligence and machine learning algorithms frequently require precisely synchronized signals from multiple sensors, which in turn require time-consuming and energy-inefficient synchronization methods with constant wireless network connectivity. We propose ecoSync, a highly energy-efficient time synchronization algorithm for Wi-Fi devices in IoMT applications. We demonstrated that ecoSync can correct the time difference error to ±42 µs with an hour between resynchronizations, using only 658 millijoules of energy. This is an 87% improvement in time difference error and a 99.93% reduction in energy usage over using TSF for synchronization alone over a 1 h period. Wireless synchronization of sensors allows placement of physiological sensors on objects of everyday use (Smart Stuff), which in turn allows seamless collection of physiological status data every time we interact with smart objects in an IoMT environment.
Quantifying Coincidence in Non-Uniform Time Series with Mutual Graph Approximation: Speech and ECG Examples
Authors: Augustyniak Piotr , Ślusarczyk Grażyna
Published: October 2023

Compressive sensing and arbitrary sampling are techniques of data volume reduction challenging the Shannon sampling theorem and expected to provide efficient storage while preserving original information. Irregularity of sampling is either a result of intentional optimization of a sampling grid or stems from sporadic occurrence or intermittent observability of a phenomenon. Quantitative comparison of irregular patterns similarity is usually preceded by a projection to a regular sampling space. In this paper, we study methods for direct comparison of time series in their original non-uniform grids. We also propose a linear graph to be a representation of the non-uniform signal and apply the Mutual Graph Approximation (MGA) method as a metric to infer the degree of similarity of the considered patterns. The MGA was implemented together with four state-of-the-art methods and tested with example speech signals and electrocardiograms projected to bandwidth-related and random sampling grids. Our results show that the performance of the proposed MGA method is comparable to most accurate (correlation of 0.964 vs. Frechet: 0.962 and Kleinberg: 0.934 for speech signals) and to less computationally expensive state-of-the-art distance metrics (both MGA and Hausdorf: O(L1+L2)). Moreover, direct comparison of non-uniform signals can be equivalent to cross-correlation of resampled signals (correlation of 0.964 vs. resampled: 0.960 for speech signals, and 0.956 vs. 0.966 for electrocardiograms) in applications as signal classification in both accuracy and computational complexity. Finally, the bandwidth-based resampling model plays a substantial role; usage of random grid is the primary cause of inaccuracy (correlation of 0.960 vs. for random sampling grid: 0.900 for speech signals, and 0.966 vs. 0.878, respectively, for electrocardiograms). These figures indicate that the proposed MGA method can be used as a simple yet effective tool for scoring similarity of signals directly in non-uniform sampling grids.
Improved Collaborative Recommendation Model: Integrating Knowledge Embedding and Graph Contrastive Learning
Authors: Jiang Liwei , Yan Guanghui , Luo Hao , Chang Wenwen
Published: October 2023

A recommendation algorithm combined with a knowledge graph enables auxiliary information on items to be obtained by using the knowledge graph to achieve better recommendations. However, the recommendation performance of existing methods relies heavily on the quality of the knowledge graph. Knowledge graphs often contain noise and irrelevant connections between items and entities in the real world. This knowledge graph sparsity and noise significantly amplifies the noise effects and hinders the accurate representation of user preferences. In response to these problems, an improved collaborative recommendation model is proposed which integrates knowledge embedding and graph contrastive learning. Specifically, we propose a knowledge contrastive learning scheme to mitigate noise within the knowledge graph during information aggregation, thereby enhancing the embedding quality of items. Simultaneously, to tackle the issue of insufficient user-side information in the knowledge graph, graph convolutional neural networks are utilized to propagate knowledge graph information from the item side to the user side, thereby enhancing the personalization capability of the recommendation system. Additionally, to resolve the over-smoothing issue in graph convolutional networks, a residual structure is employed to establish the message propagation network between adjacent layers of the same node, which expands the information propagation path. Experimental results on the Amazon-book and Yelp2018 public datasets demonstrate that the proposed model outperforms the best baseline models by 11.4% and 11.6%, respectively, in terms of the Recall@20 evaluation metric. This highlights the method’s efficacy in improving the recommendation accuracy and effectiveness when incorporating knowledge graphs into the recommendation process.
Neural Network Helps Determine the Hemorrhagic Risk of Cerebral Arteriovenous Malformation
Authors: Wang Kuan-Yu , Chen Jyh-Cheng
Published: October 2023

We aimed to determine whether the hemorrhage risks of cerebral arteriovenous malformation (AVM), evaluated through digital subtraction angiography (DSA) using a neural network, were superior to those assessed through angioarchitecture. We conducted a retrospective review of patients with cerebral AVM who underwent DSA from 2011 to 2017. Angioarchitecture parameters, age, and sex were analyzed using univariate and multivariate logistic regression. Additionally, a neural network was trained using a combination of convolutional neural network (CNN) and recurrent neural network (RNN) architectures. The training dataset consisted of 118 samples, while 29 samples were reserved for testing. After adjusting for age at diagnosis and sex, single venous drainage (odds ratio [OR] = 2.48, p = 0.017), exclusive deep venous drainage (OR = 3.19, p = 0.005), and venous sac (OR = 0.43, p = 0.044) were identified as independent risk factors for hemorrhage. The angioarchitecture-based hemorrhagic prediction model achieved 69% accuracy with an AUC (area under the ROC curve) of 0.757, while the CNN–RNN-based model achieved 76% accuracy with an AUC of 0.748. We present a diagnostic performance for hemorrhagic risk assessment of AVMs that is comparable to the angioarchitectural analysis. By leveraging larger datasets, there is significant potential to enhance prediction accuracy further. The CNN–RNN algorithm not only can potentially streamline workflow within the angio-suite but also serves as a complementary approach to optimize diagnostic accuracy and treatment strategies.
Optimal Camera Placement to Generate 3D Reconstruction of a Mixed-Reality Human in Real Environments
Authors: Kim Juhwan , Jo Dongsik
Published: October 2023

Virtual reality and augmented reality are increasingly used for immersive engagement by utilizing information from real environments. In particular, three-dimensional model data, which is the basis for creating virtual places, can be manually developed using commercial modeling toolkits, but with the advancement of sensing technology, computer vision technology can also be used to create virtual environments. Specifically, a 3D reconstruction approach can generate a single 3D model from image information obtained from various scenes in real environments using several cameras (multi-cameras). The goal is to generate a 3D model with excellent precision. However, the rules for choosing the optimal number of cameras and settings to capture information from in real environments (e.g., actual people) employing several cameras in unconventional positions are lacking. In this study, we propose an optimal camera placement strategy for acquiring high-quality 3D data using an irregular camera placement, essential for organizing image information while acquiring human data in a three-dimensional real space, using multiple irregular cameras in real environments. Our results show that installation costs can be lowered by arranging a minimum number of multi-camera cameras in an arbitrary space, and automated virtual human manufacturing with high accuracy can be conducted using optimal irregular camera location.
Utilizing Fractional Artificial Neural Networks for Modeling Cancer Cell Behavior
Authors: Behinfaraz Reza , Ghavifekr Amir Aminzadeh , De Fazio Roberto , Visconti Paolo
Published: October 2023

In this paper, a novel approach involving a fractional recurrent neural network (RNN) is proposed to achieve the observer-based synchronization of a cancer cell model. According to the properties of recurrent neural networks, our proposed framework serves as a predictive method for the behavior of fractional-order chaotic cancer systems with uncertain orders. Through a stability analysis of weight updating laws, we design a fractional-order Nonlinear Autoregressive with Exogenous Inputs (NARX) network, in which its learning algorithm demonstrates admissible and faster convergence. The main contribution of this paper lies in the development of a fractional neural observer for the fractional-order cancer systems, which is robust in the presence of uncertain orders. The proposed fractional-order model for cancer can capture complex and nonlinear behaviors more accurately than traditional integer-order models. This improved accuracy can provide a more realistic representation of cancer dynamics. Simulation results are presented to demonstrate the effectiveness of the proposed method, where mean square errors of synchronization by applying integer and fractional weight matrix laws are calculated. The density of tumor cell, density of healthy host cell and density of effector immune cell errors for the observer-based synchronization of fractional-order (OSFO) cancer system are less than 0.0.0048, 0.0062 and 0.0068, respectively. Comparative tables are provided to validate the improved accuracy achieved by the proposed framework.
Tube-Based Event-Triggered Path Tracking for AUV against Disturbances and Parametric Uncertainties
Authors: Chen Yuheng , Bian Yougang
Published: October 2023

In order to enhance the performance of disturbance rejection in AUV’s path tracking, this paper proposes a novel tube-based event-triggered path-tracking strategy. The proposed tracking strategy consists of a speed control law and an event-triggered tube model predictive control (tube MPC) scheme. Firstly, the speed control law using linear model predictive control (LMPC) technology is obtained to converge the nominal path-tracking deviation. Secondly, the event-triggered tube MPC scheme is used to calculate the optimal control input, which can enhance the performance of disturbance rejection. Considering the nonlinear hydrodynamic characteristics of AUV, a linear matrix inequality (LMI) is formulated to obtain tight constraints on the AUV and the feedback matrix. Moreover, to enhance real-time performance, tight constraints and the feedback matrix are all calculated offline. An event-triggering mechanism is used. When the surge speed change command does not exceed the upper bound, adaptive tight constraints are obtained. Finally, numerical simulation results show that the proposed tube-based event-triggered path-tracking strategy can enhance the performance of disturbance rejection and ensure good real-time performance.
First Chemical–Physical Measurements by Multi-Parameter Probe in the Blue Hole of Faanu Madugau (Ari Atoll, the Maldives)
Authors: Cutroneo Laura , Ahmed Hassan , Azzola Annalisa , Fontana Herbert , Geneselli Irene , Mancini Ilaria , Montefalcone Monica , Oprandi Alice , Pancrazi Irene , Vanin Stefano , Capello Marco
Published: October 2023

Blue holes are submarine karst cavities with chemical and physical characteristics of the water column completely different from those in the surrounding environment. In this study a multi-parameter probe was used, for the first time, to characterise the water column of the Blue Hole of Faanu Madugau (Ari Atoll, Maldives, 3°55.799′ E 72°56.469′ N), the only blue hole described in the Indian Ocean up to date. Measurements of the temperature, salinity, dissolved oxygen, turbidity, chlorophyll-α, photosynthetically active radiation, potential density, pH, and H2S were obtained with a high detail. Three distinct physical–chemical layers were identified from the surface up to 70 m depth. An intermediate and turbid layer, located between 40 m and 46 m depth, sharply separates the upper layer displaying water characteristics equal to those of the outside environment from the deep and more characteristic layer of the blue hole, where a unique environment can be observed. Waters are oxygenated, warm, and rich in chlorophyll-α in the upper layer, whilst waters are anoxic, colder, denser, and completely dark, with low pH values and high H2S content in the deep layer. The Blue Hole of the Maldives represents an extreme environment from a geological, oceanographic, biological, and ecological point of view. Further investigations will be thus required to understand the origin of the Blue Hole waters, the mechanisms that keep it isolated from the external environment, the influence of weather and marine forcing on it, and how climate change may impact it.
Current Status and Potential Invasiveness Evaluation of an Exotic Mangrove Species, Laguncularia racemosa (L.) C.F. Gaertn, on Hainan Island, China
Authors: Cheng Cheng , Ke Xinran , Lang Tao , Zhong Cairong , Lv Xiaobo , Zhang Mengwen , Chen Yu , Fang Zanshan , Zhou Haichao , Chen Yiqing
Published: October 2023

Laguncularia racemosa is widely planted in coastal mudflats as a pioneer species of mangrove afforestation in China; however, whether it exhibits invasiveness as an exotic species has been a topic of debate. In this study, we investigated the distribution, community structure, and population characteristics of L. racemosa on Hainan Island, China, to discuss its potential invasiveness. The results showed that Hainan Island has become an important distribution area for L. racemosa in China, covering a total area of 64.90 ha. In this investigation, a total of 11 true mangrove species, belonging to six families and 11 genera, were discovered in the L. racemosa community throughout Hainan Island. Furthermore, L. racemosa exhibited a strong adaptive range to seawater salinity and demonstrated a high capacity for natural dispersion. L. racemosa exhibited high importance values in the tree, shrub, and seedling layers of this artificial community, indicating its dominance and potential exclusion of other mangrove species. Over time, the importance values of L. racemosa in the tree and shrub layers initially decreased and then increased, while the opposite trend was observed in the seedling layer. Overall, the diversity indexes, including the Simpson index, Shannon–Wiener index, and Pielou community evenness index, were low in the planted L. racemosa forest on Hainan Island, suggesting a relatively simple species composition within the L. racemosa community. Additionally, based on the height levels of the L. racemosa population, we found that it mainly belonged to the first level, characterized by a large number of seedlings on Hainan Island. The number of L. racemosa seedlings gradually decreased in subsequent levels, and higher height levels of L. racemosa appeared with longer planting times, indicating a growing trend of potential invasiveness of L. racemosa on Hainan Island over an extended period. We suggest that the government should be able to list L. racemosa as an invasive species that can be harvested in the future. Based on this, this study provides fundamental data and theoretical references for the sustainable prevention, control, and management of the exotic species L. racemosa on Hainan Island, and also in other mangrove wetlands in China.
A Framework for Analyzing Individual-Tree and Whole-Stand Growth by Fusing Multilevel Data: Stochastic Differential Equation and Copula Network
Authors: Rupšys Petras , Mozgeris Gintautas , Petrauskas Edmundas , Krikštolaitis Ričardas
Published: October 2023

In forestry, growth functions form the basis of research and are widely used for the mathematical modeling of stand variables, e.g., tree or stand basal area, stand height, stand volume, site index, and many more. In this study, to estimate five-dimensional dependencies between tree diameter at breast height, potentially available area, height, crown area and crown base height, we used a normal copula approach whereby the growths of individual variables are described using a stochastic differential equation with mixed-effect parameters. The normal copula combines the marginal distributions of tree diameter at breast height, potentially available area, height, crown area, and crown base height into a joint multivariate probability distribution. Copula models have the advantage of being able to use collected longitudinal, multivariate, and discrete data for which the number of measurements of individual variables does not match. This study introduced a normalized multivariate interaction information measure based on differential entropy to assess the causality between tree size variables. In order to accurately and quantitatively assess the stochastic processes of the tree size variables’ growth and to provide a scientific basis for the formalization of models, an analysis method of the synergetic theory of information entropy has been proposed. Theoretical findings are illustrated using an uneven-aged, mixed-species empirical dataset of permanent experimental plots in Lithuania.
A Transition-Matrix Growth Model and Equilibrium Curve for Natural Forests in Jiangxi Province
Authors: Gao Yuan , Li Lian , Du Xue , Meng Jinghui
Published: October 2023

Researchers build growth models to predict the growth of forest stands and propose management measures to improve the overall quality of these stands. In this study, data collected from 91 sample plots from the eighth (2010) and ninth (2015) Chinese National Forest Inventories in Jiangxi Province were used to establish a transition-matrix growth model. Then, 12 potential equilibrium curves were set to guide forest management, and a transition-matrix growth model was used to predict stand growth in Jiangxi Province. In each 10-year management period, trees with diameters that exceeded the equilibrium curve were cut down. The results show that species diversity (H1), size diversity (H2), and basal area (B) have statistically significant influences on growth, mortality, and recruitment. Moreover, the high accuracy of the transition-matrix growth model is demonstrated. According to the simulation results, B = 35 m2/ha, the maximum diameter of retained trees Dmax = 45 cm and the adjacent diameter ratio q = 1.7 constitute the optimal equilibrium curve to guide forest management. The diameter distribution guided by the equilibrium curve is reverse J-shaped and is associated with significant increases in the hardwood stock volume and current annual growth. Under the guidance of the equilibrium curve, the forests in Jiangxi Province can be reasonably managed, produce more high-economic-value timber, and achieve a more stable species composition. This study will help maximize the ecological and economic benefits of forests and provide a reference for the realization of the sustainable development of forestry. Furthermore, the results can be used to improve the facility and accuracy of natural forest harvesting.
Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021
Authors: Wang Xiaoxian , Zhang Xiuxia , Li Wangping , Cheng Xiaoqiang , Zhou Zhaoye , Liu Yadong , Wu Xiaodong , Hao Junming , Ling Qing , Deng Lingzhi , Zhang Xilai , Ling Xiao
Published: October 2023

Rapid climate variability and intense human activities generate obvious impacts on the Qilian Mountains ecosystem. The time series of fractional vegetation coverage (FVC) from 1986 to 2021 were used to quantify the impact of climate variability and human activities on vegetation variations in the Qilian Mountain National Nature Reserve (QMNNR), using 3147 land satellite images based on the Google Earth Engine cloud platform. The contributions of climate variability and human activities to FVC were quantified using multiple regression residual analysis. Partial correlation and correlation methods were used to quantify the impact of temperature, precipitation, and human activity footprints on FVC. The results showed that from 1986 to 2021, the increase rate of FVC was 1.7 × 10−3 y−1, and the high vegetation coverage of the FVC was mainly distributed in the southeastern part of the reserve. In contrast, the low vegetation coverage was mainly distributed in the northwest part of the reserve. The Mann–Kendall mutation test found that the year of 2009 was the year of the mutation. The growth rate of FVC from 2010 to 2021 was greater than that from 1986 to 2009. In addition, climate variability and human activities exhibited a remarkable spatial heterogeneity in FVC changes. Climate variability and human activities contributed 49% and 51% to the increase in FVC in the reserve, respectively, and the contribution of human activities was greater than that of climate variability. The warming and humidification phenomena in the reserve were obvious. However, precipitation was the dominant factor affecting the dynamic changes in FVC. This study improves our understanding of the response of vegetation dynamics to the climate and human activities in the QMNNR.
Practical LAI Estimation with DHP Images in Complex Forest Structure with Rugged Terrain
Authors: Lee Junghee , Cha Sungeun , Lim Joongbin , Chun Junghwa , Jang Keunchang
Published: October 2023

Leaf area index is a key structural parameter for biological and physical processes. Korea is planning to launch CAS500-4 in 2025, so in situ data is needed to validate the leaf area index. Unlike other networks (e.g., NEON and TERN), establishing an elementary sampling unit is difficult in Korea due to the complex forest structure and rugged terrain. Therefore, pixel-level correspondence between the satellite product and fisheye footprints is the best way to verify in complex terrain. In this study, we analyzed the spatial footprint of fisheye lenses in different forest types using terrestrial LiDAR data for the first time. The three-dimensional forest structure was analyzed at various viewing zenith angles, and the footprint radius was approximately 3 m at view zenith angle (VZA) 20° and approximately 10 m at VZA 90°. We also analyzed the Z-values from terrestrial laser data and the plant area index on leafless seasons to assess the impact of obstacles, such as tree trunks, under various viewing zenith angles. The analysis showed that the influence of woody components increases dramatically as the VZA exceeds 40°. Such factors influenced the increase in LAI and the decrease in the clumping index as the VZA increased. Overall, we concluded that narrowing VZA between 20° and 40° is appropriate for Korean forests with complex structures.
Optimization of Polyvinyl Alcohol-Based Electrospun Fibers with Bioactive or Electroconductive Phases for Tissue-Engineered Scaffolds
Authors: Renkler Zeynep , Cruz Maya Iriczalli , Guarino Vincenzo
Published: October 2023

The accurate mimicking of the fibrillary structure of the extracellular matrix represents one of the critical aspects of tissue engineering, playing a significant role in cell behavior and functions during the regenerative process. This work proposed the design of PVA-based multi-component membranes as a valuable and highly versatile strategy to support in vitro regeneration of different tissues. PVA can be successfully processed through electrospinning processes, allowing for the integration of other organic/inorganic materials suitable to confer additive bio-functional properties to the fibers to improve their biological response. It was demonstrated that adding polyethylene oxide (PEO) improves fiber processability; moreover, SEM analyses confirmed that blending PVA with PEO or gelatin enables the reduction of fiber size from 1.527 ± 0.66 μm to 0.880 ± 0.30 μm and 0.938 ± 0.245 μm, respectively, also minimizing defect formation. Furthermore, in vitro tests confirmed that gelatin integration allows the formation of bioactive nanofibers with improved biological response in terms of L929 adhesion and proliferation. Lastly, the processability of PVA fibers with conductive phases such as polyvinylpyrrolidone (PVP) or poly(3,4-ethylene dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) has also been verified. From this perspective, they could be promisingly used to design electroactive composite fibers able to support the regeneration process of electrically stimulated tissues such as nerves or muscles.
Synergistic Integration of Hydrogen Energy Economy with UK’s Sustainable Development Goals: A Holistic Approach to Enhancing Safety and Risk Mitigation
Authors: Li He , Yazdi Mohammad , Moradi Rosita , Pirbalouti Reza Ghasemi , Nedjati Arman
Published: October 2023

Hydrogen is gaining prominence as a sustainable energy source in the UK, aligning with the country’s commitment to advancing sustainable development across diverse sectors. However, a rigorous examination of the interplay between the hydrogen economy and the Sustainable Development Goals (SDGs) is imperative. This study addresses this imperative by comprehensively assessing the risks associated with hydrogen production, storage, transportation, and utilization. The overarching aim is to establish a robust framework that ensures the secure deployment and operation of hydrogen-based technologies within the UK’s sustainable development trajectory. Considering the unique characteristics of the UK’s energy landscape, infrastructure, and policy framework, this paper presents practical and viable recommendations to facilitate the safe and effective integration of hydrogen energy into the UK’s SDGs. To facilitate sophisticated decision making, it proposes using an advanced Decision-Making Trial and Evaluation Laboratory (DEMATEL) tool, incorporating regret theory and a 2-tuple spherical linguistic environment. This tool enables a nuanced decision-making process, yielding actionable insights. The analysis reveals that Incident Reporting and Learning, Robust Regulatory Framework, Safety Standards, and Codes are pivotal safety factors. At the same time, Clean Energy Access, Climate Action, and Industry, Innovation, and Infrastructure are identified as the most influential SDGs. This information provides valuable guidance for policymakers, industry stakeholders, and regulators. It empowers them to make well-informed strategic decisions and prioritize actions that bolster safety and sustainable development as the UK transitions towards a hydrogen-based energy system. Moreover, the findings underscore the varying degrees of prominence among different SDGs. Notably, SDG 13 (Climate Action) exhibits relatively lower overall distinction at 0.0066 and a Relation value of 0.0512, albeit with a substantial impact. In contrast, SDG 7 (Clean Energy Access) and SDG 9 (Industry, Innovation, and Infrastructure) demonstrate moderate prominence levels (0.0559 and 0.0498, respectively), each with its unique influence, emphasizing their critical roles in the UK’s pursuit of a sustainable hydrogen-based energy future.
High-Pressure Pasteurization of Soy Okara
Authors: Helstad Amanda , Marefati Ali , Ahlström Cecilia , Rayner Marilyn , Purhagen Jeanette , Östbring Karolina
Published: October 2023

Okara is a by-product from the production of soy beverages, which has a high content of protein and fiber. Even though it has a high nutritional value, it is generally discarded or used as animal feed or compost. The problem is its short shelf life due to its high water content and high water activity. The aim of this study was to investigate the effect of high-pressure pasteurization at 200 MPa, 400 MPa, and 600 MPa on the shelf life of soy okara. Microbiological growth, as well as thermal properties, viscosity, water holding capacity, and oil holding capacity, was evaluated after the pressure treatments. Treatment at 600 MPa significantly reduced (p < 0.05) the growth of total aerobic count, yeast and mold, and lactic acid bacteria for up to four weeks of storage at 4 °C. The pasting properties were increased while the water and oil holding capacities of the soy okara did not significantly change (p > 0.05) after high-pressure pasteurization at 400 MPa and 600 MPa. High-pressure pasteurization is therefore a potential application technique for soy okara to produce a microbiologically safe product with maintained functional properties. However, more research is needed to optimize the process and to further investigate the microbiological species present in untreated soy okara to exclude any potential food safety risks.
Tart Cherry (Prunus cerasus L.) Pit Extracts Protect Human Skin Cells against Oxidative Stress: Unlocking Sustainable Uses for Food Industry Byproducts
Authors: Decot Hannah , Sudhakaran Meenakshi , Boismier Emma , Schilmiller Anthony , Claucherty Ethan , Doseff Andrea I. , Aliakbarian Bahar
Published: October 2023

Industrial processing of tart cherries (Prunus cerasus L.) produces bioproducts like cherry pits (CP), which contribute to adverse environmental effects. To identify sustainable strategies to minimize the environmental impact of cherry processing, we investigated their potential value as antioxidants for prospective utilization within cosmeceutical applications. Untargeted metabolomic analyses of water and water: ethanol CP extracts using an eco-friendly technique revealed significant enrichment in coumaroyl derivatives and flavonoids with congruent metabolite representation regardless of the extraction solvent. The antioxidant activity of tart CP extracts was evaluated on human skin cells exposed to H2O2 or LPS, modeling environmentally induced oxidants. Notably, both CP extracts provide antioxidant activity by reducing H2O2 or LPS-induced ROS in human skin keratinocytes without affecting cell viability. The CP extracts increased the expression of CAT and SOD1 genes encoding antioxidant regulatory enzymes while decreasing the expression of NOS2, a pro-oxidant regulator. These findings reveal the antioxidant properties of tart CP, offering new opportunities to produce natural-based skin care products and adding economic value while providing sustainable options to reduce the environmental impact of food byproducts.
Effect of a Chitosan Coating Enriched with an Olive Leaf Extract on the Characteristics of Pork Burgers
Authors: Carrapiso Ana Isabel , Pimienta Manuel , Martín Lourdes , Cardenia Vladimiro , Andrés Ana Isabel
Published: October 2023

Chitosan coatings have been investigated for improving food shelf-life. The addition of an olive leaf extract could enhance its beneficial effect. The aim of this study was to evaluate the effectiveness of an olive leaf extract added to a chitosan coating in delaying deterioration in refrigerated pork burgers without additives packaged under a 40% oxygen and 60% carbon dioxide modified atmosphere. Some general parameters (microbial counts, instrumental color and texture, and lipid and protein oxidation) were measured over the storage of pork burgers without coating (Control), with a chitosan-based coating (Chitosan) and with a chitosan-based coating enriched with an olive leaf extract (Chitoex). The coating impacted the effect of the storage time on most parameters. Both coatings were especially effective at limiting the changes that occur over time in the headspace gases, some texture parameters (hardness, gumminess, and chewiness) and lipid oxidation, although the effect on the microbial counts was weak. Chitoex was more effective than Chitosan at preventing changes in the headspace gases on day 11 and in lipid oxidation on all the sampling days. In conclusion, the Chitoex coating could be useful for prolonging the storage of pork burgers by preventing changes in texture and reducing lipid oxidation.
Effects of Roasting on the Quality of Moringa oleifera Leaf Powder and Loaf Volume of Moringa oleifera-Supplemented Bread
Authors: Koriyama Takako , Saikawa Mika , Kurosu Yuria , Kumagai Michiyo , Hosoya Takahiro
Published: October 2023

Although a decrease in bread volume on adding nutrient-rich Moringa oleifera leaf powder (MLP) is known, to our knowledge, improving the swelling of MLP-added bread has not been attempted. This study aimed to investigate the effects of MLP and roasted MLP (RMLP) on bread quality. Bread was supplemented with MLP and RMLP treated at varying temperatures and times; the baked bread was then biochemically evaluated relative to the control. The specific volume of MLP-supplemented bread was 2.4 cm3/g, which increased to >4.0 cm3/g on using MLP roasted at 130 °C for ≥20 min, demonstrating remarkable swelling. The specific volume of bread supplemented with MLP roasted at 170 °C for 20 min was 4.6 cm3/g, similar to that of the control. Additionally, MLP interfered with carbon dioxide production in bread, thus decreasing the abundance of yeast cells; however, RMLP had no such effect and allowed normal fermentation. Scanning electron microscopy revealed gluten formation independent of MLP roasting. Thus, MLP-containing breads generally exhibit suppressed fermentation and expansion due to the bactericidal properties of raw MLP, but these effects are alleviated by heat treatment. These findings highlight the importance of heat treatment in mitigating the effects of MLP on bread fermentation and swelling.
Characterization of Fruit Vinegars via Bioactive and Organic Acid Profile Using Chemometrics
Authors: Yildiz Elif
Published: October 2023

Vinegar has been known as a traditional remedy since ancient times. In addition to being used as a flavoring and aroma enhancer in world cuisines, it has attracted more and more attention due to its bioactive potential and health properties. Although the most common use is apple cider vinegar together with grape vinegar, vinegar produced from red fruits has come to the fore due to their health purposes. Rosehip, pomegranate, fig, guelder-rose, blackberry, raspberry, and blueberry vinegars were evaluated regarding the organic acid content, phenolic compound content, and bioactive potential to assess their health potential and associated contents. Acetic acid, citric acid, succinic acid, and malic acid were determined as prominent organic acids in the vinegar samples. In contrast, gallic acid, vanillic acid, protocatechuic acid, and ferulic acid were dominant regarding phenolic compounds. Raspberry, guelder-rose, and pomegranate vinegars came forth regarding their bioactive content and potential. The discriminative parameters of the vinegar samples were pH, total acidity, dL-isocitric acid, gallic acid, and hydroxybenzoic acid. Fruit vinegars were determined to have a notable bioactive content compared to apple and grape vinegars. The use of these vulnerable bioactive materials in vinegar fermentation could provide an effective way for nutrition and raw material resourcing.
Domains of Quasi Attraction: Why Stable Processes Are Observed in Reality?
Authors: Kolokoltsov Vassili N.
Published: October 2023

From the very start of modelling with power-tail distributions, concerns were expressed about the actual applicability of distributions with infinite expectations to real-world distributions, which usually have bounded ranges. Here, we suggest resolving this issue by shifting the analysis from the true convergence in various CLTs to some kind of quasi convergence, where a stable approximation to, say, normalised sums of n i.i.d. random variables (or more generally, in a functional setting, to the processes of random walks), holds for large n, but not “too large” n. If the range of “large n” includes all imaginable applications, the approximation is practically indistinguishable from the true limit. This approach allows us to justify a stable approximation to random walks with bounded jumps and, moreover, it leads to some kind of cascading (quasi) asymptotics, where for different ranges of a small parameter, one can have different stable or light-tail approximations. The author believes that this development might be relevant to all applications of stable laws (and thus of fractional equations), say, in Earth systems, astrophysics, biological transport and finances.
Unraveling the Dynamics of Singular Stochastic Solitons in Stochastic Fractional Kuramoto–Sivashinsky Equation
Authors: Al-Sawalha M. Mossa , Yasmin Humaira , Shah Rasool , Ganie Abdul Hamid , Moaddy Khaled
Published: October 2023

This work investigates the complex dynamics of the stochastic fractional Kuramoto–Sivashinsky equation (SFKSE) with conformable fractional derivatives. The research begins with the creation of singular stochastic soliton solutions utilizing the modified extended direct algebraic method (mEDAM). Comprehensive contour, 3D, and 2D visual representations clearly depict the categorization of these stochastic soliton solutions as kink waves or shock waves, offering a clear description of these soliton behaviors within the context of the SFKSE framework. The paper also illustrates the flexibility of the transformation-based approach mEDAM for investigating soliton occurrence not only in SFKSE but also in a wide range of nonlinear fractional partial differential equations (FPDEs). Furthermore, the analysis considers the effect of noise, specifically Brownian motion, on soliton solutions and wave dynamics, revealing the significant influence of randomness on the propagation, generation, and stability of soliton in complex stochastic systems and advancing our understanding of extreme behaviors in scientific and engineering domains.
Increased Microbially Induced Calcium Carbonate Precipitation (MICP) Efficiency in Multiple Treatment Sand Biocementation Processes by Augmentation of Cementation Medium with Ammonium Chloride
Authors: Spencer Christine Ann , Sass Henrik , van Paassen Leon
Published: October 2023

The cementation medium for ureolytic microbially induced calcium carbonate precipitation (MICP) typically consists of urea and a calcium source. While some studies have augmented this basic medium, the effects of adding substrates such as ammonium chloride are unclear. The studies detailed in this paper sought to quantify the effect of the ammonium chloride augmentation of cementation medium (CM) on the process of MICP. An aqueous MICP study was initially carried out to study the effects of adding ammonium chloride to the urea–calcium cementation medium. This batch test also explored the effect of varying the concentration of calcium chloride dihydrate (calcium source) in the CM. A subsequent sand column study was undertaken, whereby multiple treatments of CM were injected over several days to produce a biocement. Six columns were prepared using F65 sand bioaugmented with Sporosarcina pasteurii, half of which were injected with the basic medium only and half with the augmented medium for treatment two onwards. Effluent displaced from columns was tested using ion chromatography and Nesslerisation to determine the calcium and ammonium ion concentrations, respectively, and hence the treatment efficiency. Conductivity and pH testing of effluent gave insights into the bacterial urease activity. The addition of 0.187 M ammonium chloride to the CM resulted in approximately 100% chemical conversion efficiency within columns, based on calcium ion measurements, compared to only 57% and 33% efficiency for treatments three and four, respectively, when using the urea–calcium medium. Columns treated with the CM containing ammonium chloride had unconfined compressive strengths which were 1.8 times higher on average than columns treated with the urea–calcium medium only.
A Re-Evaluation of the Grievance Studies Affair
Authors: Cole Geoff G.
Published: October 2023

During 2018, three academics employed what they referred to as “reflective ethnography” to examine the hypothesis that many disciplines (e.g., sociology, educational philosophy, and critical race theory) are motivated by extreme ideologies, as opposed to generating knowledge. The authors published, or had accepted, seven “hoax” articles in a number of peer-reviewed journals. When the story broke in the Wall Street Journal, the authors stated that the articles advocated a number of ludicrous, inhumane, and appalling ideas. For example, one argued that men should be trained like dogs with shock collars. Their acceptance for publication was therefore taken as evidence for the kind of ideas that many academic disciplines will advocate. In the present article, I will show that the central aspects of the hoax articles do not match with how they were later described by the hoax authors and many other commentators (e.g., journalists). Despite the vast amount of media coverage, this has (virtually) gone unnoticed. I will suggest that the widely accepted narrative of the so-called Grievance Studies affair is incorrect.
Awareness, Attitudes and Willingness to Donate Biological Samples to a Biobank: A Survey of a Representative Sample of Polish Citizens
Authors: Pronicki Łukasz , Czech Marcin , Gujski Mariusz , Boguszewska Natalia D.
Published: October 2023

Biotechnology is developing at an ever-increasing pace, and the progressive computerization of health care and research is making it increasingly easy to share data. One of the fastest growing areas is biobanking. However, even with the best equipment and the best trained staff, a biobank will be useless without donors. For this reason, we have decided to gauge Polish citizens’ awareness and attitudes towards biobanking and their willingness to donate biological samples. For this purpose the survey was conducted among a nationwide group of 1052 Poles aged 18 and over where the totals for gender, age and place of residence were selected according to their representation in the total population of adult Poles. The survey was conducted using the Computer Assisted Web Interview (CAWI) technique. Approximately two thirds of respondents N = 701 (66.6%) indicated that they had heard of scientific studies in which samples of biological material such as blood, saliva or urine are collected. More than half of respondents (N = 613, 58.3%) had a positive opinion regarding scientific research in which samples of biological material are taken. Only N = 220 (20.9%) of respondents had previously encountered the term biobanking. More than a half N = 687 (65.3%) of respondents would participate in a scientific study that biobanked biological material and health information. Almost half of the respondents (48.0%) would like specific consent to be used in biobanking. In our study we observed a negligible correlation between socio-demographic factors and a willingness to donate biological material to a biobank. Considering the results presented above, the level of knowledge and awareness of biobanks, and their role in scientific research and the health care system, among Polish citizens is low and requires education and information activities.
Latent Profile Analysis of Mental Health among Chinese University Students: Evidence for the Dual-Factor Model
Authors: Jiang Yumei , Ding Chen , Shen Bo
Published: October 2023

The dual-factor model of mental health has garnered substantial support, positing the necessity of encompassing both negative (e.g., psychological problems) and positive (e.g., well-being) indicators in comprehensive evaluations of people’s mental health. Nonetheless, the nature of the profiles and predictors (such as academic emotions) during four years of university life lack clarity, hampering a profound understanding of mental well-being among university students. This research included 135 items designed to assess an array of depression symptoms, negative emotional experiences, life satisfaction, positive emotional experiences, and academic emotions. First, this research affirmed the applicability of the dual-factor model in the context of Chinese university students (N = 2277) with the utilization of confirmatory factor analysis (CFA). Furthermore, latent profile analysis (LPA) was employed to delineate prevalent constellations of psychological symptoms and subjective well-being within participants. The outcomes unveiled the existence of three distinct clusters: (1) Complete Mental Health, (2) Vulnerable, and (3) Troubled. Third, by employing R3stept on academic emotions and mental health classifications, this study revealed that there were associations between this variable and specific amalgams of psychological symptoms and well-being levels. These findings bear influence on the practice of mental health screening and the identification of individuals necessitating targeted interventions.
Predictors of Psychological Distress among Post-Operative Cardiac Patients: A Narrative Review
Authors: McCann William D. , Hou Xiang-Yu , Stolic Snezana , Ireland Michael J.
Published: October 2023

Following surgery, over 50% of cardiac surgery patients report anxiety, stress and/or depression, with at least 10% meeting clinical diagnoses, which can persist for more than a year. Psychological distress predicts post-surgery health outcomes for cardiac patients. Therefore, post-operative distress represents a critical recovery challenge affecting both physical and psychological health. Despite some research identifying key personal, social, and health service correlates of patient distress, a review or synthesis of this evidence remains unavailable. Understanding these factors can facilitate the identification of high-risk patients, develop tailored support resources and interventions to support optimum recovery. This narrative review synthesises evidence from 39 studies that investigate personal, social, and health service predictors of post-surgery psychological distress among cardiac patients. The following factors predicted lower post-operative distress: participation in pre-operative education, cardiac rehabilitation, having a partner, happier marriages, increased physical activity, and greater social interaction. Conversely, increased pain and functional impairment predicted greater distress. The role of age, and sex in predicting distress is inconclusive. Understanding several factors is limited by the inability to carry out experimental manipulations for ethical reasons (e.g., pain). Future research would profit from addressing key methodological limitations and exploring the role of self-efficacy, pre-operative distress, and pre-operative physical activity. It is recommended that cardiac patients be educated pre-surgery and attend cardiac rehabilitation to decrease distress.