bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification Method of Heavy Oil Based on Chemical Composition and Bulk Properties
Authors: Zhang Weilai , Wu Jianxun , Li Shuofan , Zhang Yahe , Zhao Suoqi , Shi Quan
Published: July 2024

Heavy oil resources in the world are extremely abundant, and viscosity is currently the main reference index for heavy oil classification. However, the diversification of practical issues in heavy oil exploitation, and the refinement of processing and utilization urgently require the support of heavy oil classification with more reference indexes. In this study, the macroscopic properties of typical heavy oils in China were analyzed, and the semi-quantitative analysis of the molecular composition of different heavy oils was completed based on high-resolution mass spectrometry. The results show that heavy oils with similar viscosities can exhibit huge differences in macroscopic properties and chemical composition. According to the evaluation of the chemical composition and macroscopic properties of typical Chinese heavy oils, 12 types of compounds belonging to saturates, aromatics, resins, and asphaltenes (SARA) were identified, establishing a connection between the macroscopic fractions and molecular compositions of heavy oils. By summarizing the comparative results, a new classification criterion for heavy oils was established, focusing on the main parameters of H/C ratio and total acid number (TAN), with sulfur content as a supplementary indicator. H/C is the embodiment of the degree of molecular condensation in the macroscopic properties, reflecting the structural characteristics of the main molecules of the heavy oil. Chinese heavy oil is generally characterized by high TAN, which corresponds to the composition of petroleum acids, and it is also an important reference index for the exploitation and processing of heavy oils. Most Chinese heavy oils have a very low sulfur content, but the presence of sulfur compounds in high-sulfur heavy oils can lead to significant differences in the distribution of compound types among the SARA. This new classification method for heavy oil combines the characteristics of chemical composition of heavy oils, which is expected to provide valuable support for the extraction and processing of heavy oil.
Data-Driven Golden Jackal Optimization–Long Short-Term Memory Short-Term Energy-Consumption Prediction and Optimization System
Authors: Yang Yongjie , Li Yulong , Cai Yan , Tang Hui , Xu Peng
Published: July 2024

In order to address the issues of significant energy and resource waste, low-energy management efficiency, and high building-maintenance costs in hot-summer and cold-winter regions of China, a research project was conducted on an office building located in Nantong. In this study, a data-driven golden jackal optimization (GJO)-based Long Short-Term Memory (LSTM) short-term energy-consumption prediction and optimization system is proposed. The system creates an equivalent model of the office building and employs the genetic algorithm tool Wallacei to automatically optimize and control the building’s air conditioning system, thereby achieving the objective of reducing energy consumption. To validate the authenticity of the optimization scheme, unoptimized building energy consumption was predicted using a data-driven short-term energy consumption-prediction model. The actual comparison data confirmed that the reduction in energy consumption resulted from implementing the air conditioning-optimization scheme rather than external factors. The optimized building can achieve an hourly energy saving rate of 6% to 9%, with an average daily energy-saving rate reaching 8%. The entire system, therefore, enables decision-makers to swiftly assess and validate the efficacy of energy consumption-optimization programs, thereby furnishing a scientific foundation for energy management and optimization in real-world buildings.
The Stabilization of a Nonlinear Permanent-Magnet- Synchronous-Generator-Based Wind Energy Conversion System via Coupling-Memory-Sampled Data Control with a Membership-Function-Dependent H∞ Approach
Authors: Yesudhas Anto Anbarasu , Lee Seong Ryong , Jeong Jae Hoon , Govindasami Narayanan , Joo Young Hoon
Published: July 2024

This study presents the coupling-memory-sampled data control (CMSDC) design for the Takagi–Sugeno (T-S) fuzzy system that solves the stabilization issue of a surface-mounted permanent-magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). A fuzzy CMSDC scheme that includes the sampled data control (SDC) and memory-sampled data control (MSDC) is designed by employing a Bernoulli distribution order. Meanwhile, the membership-function-dependent (MFD) H∞ performance index is presented, mitigating the continuous-time fuzzy system’s disturbances. Then, by using the Lyapunov–Krasovskii functional with the MFD H∞ performance index, the data of the sampling pattern, and a constant signal transmission delay, sufficient conditions are derived. These sufficient conditions are linear matrix inequalities (LMIs), ensuring the global asymptotic stability of a PMSG-based WECS under the designed control technique. The proposed method is demonstrated by a numerical simulation implemented on the PMSG-based WECS. Finally, Rossler’s system demonstrates the effectiveness and superiority of the proposed method.
A Review on the Application of Artificial Intelligence in Anomaly Analysis Detection and Fault Location in Grid Indicator Calculation Data
Authors: Sun Shiming , Tang Yuanhe , Tai Tong , Wei Xueyun , Fang Wei
Published: July 2024

With the rapid development of artificial intelligence (AI), AI has been widely applied in anomaly analysis detection and fault location in power grid data and has made significant research progress. Through looking back on traditional methods and deep learning methods in anomaly analysis detection and fault location of power grid data, we aim to provide readers with a comprehensive understanding of the existing knowledge and research advancements in this field. Firstly, we introduce the importance of anomaly analysis detection and fault location in power grid data for the safety and stability of power system operations and review traditional methods for anomaly analysis detection and fault location in power grid data, analyzing their advantages and disadvantages. Next, the paper briefly introduces the concepts of commonly used deep learning models in this field and explores, in depth, the application of deep learning methods in anomaly analysis detection and fault location of power grid data, summarizes the current research progress, and highlights the advantages of deep learning over traditional methods. Finally, we summarize the current issues and challenges faced by deep learning in this field and provide an outlook on future research direction.
Influence of Perceived Sensory Dimensions on Cultural Ecosystem Benefits of National Forest Parks Based on Public Participation: The Case of Fuzhou National Forest Park
Authors: He Songjun , Yu Yanting , Lan Siren , Zheng Yongrong , Liu Chang
Published: July 2024

The decision-making process of China’s national forest park (NFP) system typically excludes the consideration of the public’s perceived benefits. In this regard, the objective of this study was to elucidate the type of cultural ecosystem benefits (CEB) that NFP can provide and to inform the evidence-based design of forest parks by establishing its linkage to the public’s perceived sensory dimensions (PSD). A CEB evaluation scale was developed for forest parks, and a 6-day public participation GIS (PPGIS) survey was conducted in Fuzhou NFP to collect evaluations of CEB and PSD at different sites from 853 respondents. The findings revealed that the CEB furnished by NFP is comprised of three dimensions. The three dimensions of cultural ecosystem benefits (CEB) are identities, experiences, and capabilities. The impact of different PSDs on CEBs varies, as do the impacts of high and low scores on CEBs for the same PSD. It can be concluded that the creation of more serene and open spaces will result in an increase in the CEB available to the public. Furthermore, designers may wish to consider enhancing single dimensions of PSDs in order to characterize different areas, which may prove to be a more effective approach than enhancing PSDs across the board. In summary, our PPGIS survey is expected to enable community-based governance of the NFP and provide a basis for a comprehensive sustainability dialogue between people and forests.
The Importance of the Scots Pine for the Diversity of Forest Avifauna: The Augustów Forest as a Case Study
Authors: Zawadzka Dorota , Zawadzki Grzegorz
Published: July 2024

The Scots Pine Pinus sylvestris is the most widespread tree species in forests of lowland parts of Central and Eastern Europe. In Polish forests, stands dominated by the Scots pine cover almost 60% of the forest area. We analysed the relationship between forest birds and pine trees in an extensive forest complex in north-eastern (NE) Poland. Based on the 20-year-long study, we considered the percentage of broods established on pine trees and the percentage of Scots pine in stands on grouse leks and territory. A total number of over 20 bird species are dependent on the Scots pine trees or stands to locate their nests. Among this group, 11 bird species strongly associated with pine trees were confirmed, and they located at least 90% of broods or nests on pines. The Black Woodpecker Dryocopus martius selects the Scots pine to excavate cavities. Its cavities were regularly used by some species of secondary cavity nesters. In turn, the Common Raven Corvus corax nests were occupied by selected birds of prey. The importance of Scots pine for birds increased with the age of the trees. Old Scots pine trees were chosen by birds that built large nests, placed nests in the tree top, and excavated large cavities. Populations of pine-specialized bird species may be in danger due to the possibility of the Scots pine range moving to the north, which results from global warming. The maintenance of the Scots pine with the modification of the methods of forest regeneration should be included in the Polish forestry’s strategies and plans as a critical factor for the care of the population of rare breeding bird species.
The Diversity of Yeasts in Beekeeping Environments and the Selection of a Culture Starter for the Development of a Mead
Authors: Viveros-Lizondo Noelia , Fernández-Pacheco Pilar , Arévalo-Villena María
Published: July 2024

The biodiversity of several beekeeping environments and honey samples was studied. The bacterial and yeast counts ranged from 0.00 to 5.19 Log CFU/g and from 0.00 to 3.33 Log CFU/g, respectively, presenting significant differences between the values. Of the honey samples, two of them exceeded the legislative limit established for total aerobic bacteria (5.19 Log CFU/g and 5.03 Log CFU/g). A total of ninety-eight yeast strains were isolated, with eight different species: Candida albicans, Dekkera anomala, Zygosaccharomyces rouxii, Z. mellis, Kazachstania unispora, Meyerozyma guillermondii, Saccharomyces cerevisiae, and S. unisporus. This implies a low microbial biodiversity and a low genetic variability index (D = 0.116 and 6–19%, respectively) due to the large number of genetically identical individuals found in each species. To select the most adequate strains for mead elaboration (with pure and mixed cultures), the fermentation capacity and organoleptic characteristics were studied. The best yeasts were chosen for the “pure culture fermentation” of honey (Saccharomyces spp. M11A2) and for mixed sequential inoculation (K. unispora M17A2). Both of the yeasts were isolated from honey and selected for their high fermentative capacity and resistance to ethanol. The results of the sensory analysis of the meads that were produced, in addition to one commercial product, were compared and indicated that the one inoculated with the pure culture had the best overall impression.
Ontology in Hybrid Intelligence: A Concise Literature Review
Authors: Pileggi Salvatore Flavio
Published: July 2024

In the context of the constant evolution and proliferation of AI technology, hybrid intelligence is gaining popularity in reference to a balanced coexistence between human and artificial intelligence. The term has been extensively used over the past two decades to define models of intelligence involving more than one technology. This paper aims to provide (i) a concise and focused overview of the adoption of ontology in the broad context of hybrid intelligence regardless of its definition and (ii) a critical discussion on the possible role of ontology to reduce the gap between human and artificial intelligence within hybrid-intelligent systems, as well as (iii) the identification of possible future research directions in the field. Alongside the typical benefits provided by the effective use of ontologies at a conceptual level, the conducted analysis has highlighted a significant contribution of ontology to improving quality and accuracy, as well as a more specific role to enable extended interoperability, system engineering and explainable/transparent systems. Additionally, an application-oriented analysis has shown a significant role in present systems (70+% of cases) and, potentially, in future systems. However, despite the relatively consistent number of papers on the topic, a proper holistic discussion on the establishment of the next generation of hybrid-intelligent environments with a balanced co-existence of human and artificial intelligence is fundamentally missed in the literature. Last but not the least, there is currently a relatively low explicit focus on automatic reasoning and inference in hybrid-intelligent systems.
Enhancing Recognition of Human–Object Interaction from Visual Data Using Egocentric Wearable Camera
Authors: Hamid Danish , Haq Muhammad Ehatisham Ul , Yasin Amanullah , Murtaza Fiza , Azam Muhammad Awais
Published: July 2024

Object detection and human action recognition have great significance in many real-world applications. Understanding how a human being interacts with different objects, i.e., human–object interaction, is also crucial in this regard since it enables diverse applications related to security, surveillance, and immersive reality. Thus, this study explored the potential of using a wearable camera for object detection and human–object interaction recognition, which is a key technology for the future Internet and ubiquitous computing. We propose a system that uses an egocentric camera view to recognize objects and human–object interactions by analyzing the wearer’s hand pose. Our novel idea leverages the hand joint data of the user, which were extracted from the egocentric camera view, for recognizing different objects and related interactions. Traditional methods for human–object interaction rely on a third-person, i.e., exocentric, camera view by extracting morphological and color/texture-related features, and thus, often fall short when faced with occlusion, camera variations, and background clutter. Moreover, deep learning-based approaches in this regard necessitate substantial data for training, leading to a significant computational overhead. Our proposed approach capitalizes on hand joint data captured from an egocentric perspective, offering a robust solution to the limitations of traditional methods. We propose a machine learning-based innovative technique for feature extraction and description from 3D hand joint data by presenting two distinct approaches: object-dependent and object-independent interaction recognition. The proposed method offered advantages in computational efficiency compared with deep learning methods and was validated using the publicly available HOI4D dataset, where it achieved a best-case average F1-score of 74%. The proposed system paves the way for intuitive human–computer collaboration within the future Internet, enabling applications like seamless object manipulation and natural user interfaces for smart devices, human–robot interactions, virtual reality, and augmented reality.
A Risk Assessment Framework for Mobile Apps in Mobile Cloud Computing Environments
Authors: Ogwara Noah Oghenefego , Petrova Krassie , Yang Mee Loong , MacDonell Stephen G.
Published: July 2024

Mobile devices (MDs) are used by mobile cloud computing (MCC) customers and by other users because of their portability, robust connectivity, and ability to house and operate third-party applications (apps). However, the apps installed on an MD may pose data security risks to the MD owner and to other MCC users, especially when the requested permissions include access to sensitive data (e.g., user’s location and contacts). Calculating the risk score of an app or quantifying its potential harmfulness based on user input or on data gathered while the app is actually running may not provide reliable and sufficiently accurate results to avoid harmful consequences. This study develops and evaluates a risk assessment framework for Android-based MDs that does not depend on user input or on actual app behavior. Rather, an app risk evaluator assigns a risk category to each resident app based on the app’s classification (benign or malicious) and the app’s risk score. The app classifier (a trained machine learning model) evaluates the permissions and intents requested by the app. The app risk score is calculated by applying a probabilistic function based on the app’s use of a set of selected dangerous permissions. The results from testing of the framework on an MD with real-life resident apps indicated that the proposed security solution was effective and feasible.
Predicting Wall Pressure in Shock Wave/Boundary Layer Interactions with Convolutional Neural Networks
Authors: Wang Hongyu , Fan Xiaohua , Yang Yanguang , Wang Gang , Xie Feng
Published: July 2024

Within the dynamic realm of variable-geometry shock wave/boundary layer interactions, the wall parameters of the flow field undergo real-time fluctuations. The conventional approach to sensing these changes in wall pressure through sensor measurements is encumbered by a cumbersome process, leading to diminished efficiency and an inability to provide swift predictions of wall parameters. This paper introduces a data-driven methodology that leverages non-contact schlieren imaging to predict wall pressure within the flow field, a technique that holds promise for informing the optimized design of variable-geometry systems. A sophisticated deep learning framework, predicated on Convolutional Neural Networks (CNN), has been engineered to anticipate alterations in wall pressure stemming from high-speed shock wave/boundary layer interactions. Utilizing an impulsive wind tunnel with a Mach number of 6, we have procured a sequence of schlieren images and corresponding wall pressure measurements, capturing the continuous variations induced by an attack angle from a shock wave generator. These data have been instrumental in compiling a comprehensive dataset for the training and evaluation of the CNN. The CNN model, once trained, has adeptly deduced the distribution of wall pressure from the schlieren imagery. Notwithstanding, it was observed that the CNN’s predictive prowess is marginally diminished in regions where pressure variations are most pronounced. To assess the model’s generalization capabilities, we have segmented the dataset according to different temporal intervals for network training. Our findings indicate that while the generalization of all models crafted was less than optimal, Model 4 demonstrated superior generalization. It is thus suggested that augmenting the training set with additional samples and refining the network architecture will be a worthwhile endeavor in subsequent research initiatives.
Field Cricket (Gryllus bimaculatus) and Spirulina (Arthrospira platensis) Powders as Environmentally Friendly Protein Enrichment Ingredients in Corn Snacks
Authors: Ruszkowska Millena , Tańska Małgorzata , Miedzianka Joanna , Kowalczewski Przemysław Łukasz
Published: July 2024

Unconventional protein sources are currently extensively studied as food ingredients. This study aimed to evaluate the effect of 1.5% and 3% field cricket powder (GB) and 2–8% of its mixture (1:1) with spirulina powder (S) on the nutritional value, physicochemical properties, and sensory characteristics of corn extrudates. Additionally, 2% baking powder (BP) was added to assess its impact on the properties of the enriched extrudates. The results showed that both GB and GB + S improved nutritional value, with protein content increasing by up to 46% and higher levels of essential amino acids, particularly leucine and valine. However, these ingredients decreased the expansion ratio (by up to 15%), colour lightness (by up to 30%), and yellowness (by up to 47%) and increased the hardness (by up to 25%) of the corn extrudates. The S addition positively influenced product storage stability but decreased its sensory acceptance, especially aroma and taste. The BP addition mitigated the negative effects of higher GB and GB + S concentrations, particularly on sensory characteristics. In conclusion, incorporating up to 6% of the GB + S mixture provides a higher protein content with only minor changes to the product’s characteristics compared to GB. Ratings exceeding 4.2 points indicate the good acceptability of these snacks.
Extraction, Purification, Sulfated Modification, and Biological Activities of Dandelion Root Polysaccharides
Authors: Wu Xiao , Li Na , Dong Zeng , Yin Qin , Zhou Tong , Zhu Lixiang , Yan Hanxi , Chen Ziping , Zhai Kefeng
Published: July 2024

In this study, polysaccharides were extracted at a rate of 87.5% ± 1.5% from native dandelion roots, and the dandelion root polysaccharides (DRPs) were then chemically modified to obtain sulfated polysaccharides (SDRPs) with a degree of substitution of 1.49 ± 0.07. The effects of modification conditions, physicochemical characterizations, structural characteristics, antioxidant properties, hypoglycemic activity, and proliferative effects on probiotics of DRP derivatives were further investigated. Results showed that the optimum conditions for sulfation of DRPs included esterification reagents (concentrated sulfuric acid: n-butanol) ratio of 3:1, a reaction temperature of 0 °C, a reaction time of 1.5 h, and the involvement of 0.154 g of ammonium sulfate. The DRPs and SDRPs were composed of six monosaccharides, including mannose, glucosamine, rhamnose, glucose, galactose, and arabinose. Based on infrared spectra, the peaks of the characteristic absorption bands of S=O and C-O-S appeared at 1263 cm−1 and 836 cm−1. Compared with DRPs, SDRPs had a significantly lower relative molecular mass and a three-stranded helical structure. NMR analysis showed that sulfated modification mainly occurred on the hydroxyl group at C6. SDRPs underwent a chemical shift to higher field strength, with their characteristic signal peaking in the region of 1.00–1.62 ppm. Scanning electron microscopy (SEM) analysis indicated that the surface morphology of SDRPs was significantly changed. The structure of SDRPs was finer and more fragmented than DRPs. Compared with DRPs, SDRPs showed better free radical scavenging ability, higher Fe2+chelating ability, and stronger inhibition of α-glucosidase and α-amylase. In addition, SDRPs had an excellent promotional effect on the growth of Lactobacillus plantarum 10665 and Lactobacillus acidophilus. Therefore, this study could provide a theoretical basis for the development and utilization of DRPs.
Anti-Platelet Activity of Sea Buckthorn Seeds and Its Relationship with Thermal Processing
Authors: Sławińska Natalia , Żuchowski Jerzy , Stochmal Anna , Olas Beata
Published: July 2024

Sea buckthorn (Hippophae rhamnoides L.) is a tree or shrub with small, orange berries. Sea buckthorn seeds have shown many properties beneficial to human health, including antioxidant, anti-hypertensive, anti-hyperlipidemic, and retinoprotective activities. Seeds, as a component of food, are often exposed to high temperatures, which can increase or decrease their biological activity. In our previous study, we showed that both raw and roasted sea buckthorn seeds had significant antioxidant activity, which was measured in human plasma in vitro. In this paper, we evaluated the effect of extracts from raw and roasted sea buckthorn seeds on several parameters of hemostasis in vitro, including thrombus formation in full blood (measured by the Total Thrombus formation Analysis System—T-TAS), blood platelet activation (based on the exposition of P-selectin, the active form of GPIIb/IIIa on their surface and platelet-derived microparticles formation), aggregation (measured with impedance aggregometry), adhesion to fibrinogen and collagen, arachidonic acid metabolism in washed platelets stimulated by thrombin, and COX-1 activity. We also measured the levels of free 8-isoprostane in plasma and the total non-enzymatic antioxidant status of plasma. The extract from roasted seeds (50 µg/mL) significantly prolonged the time of occlusion measured by T-TAS—the AUC10 (area under the curve) value was decreased by approximately 18%. Both extracts decreased the exposition of the active form of GPIIb/IIIa on the surface of platelets activated with 10 μM ADP (by 38.4–62.2%) and 20 μM ADP (by 39.7–51.3%). Moreover, the extract from raw seeds decreased the exposition of P-selectin on the surface of platelets stimulated with 20 μM ADP (by 31.2–34.9%). The adhesion of thrombin-stimulated platelets to fibrinogen and collagen was inhibited only by the extract from roasted sea buckthorn seeds (by 20–30%). Moreover, the extract from raw seeds inhibited the level of TBARS (thiobarbituric acid-reactive substances, an indicator of enzymatic peroxidation of arachidonic acid) in washed platelets stimulated with thrombin; the activity of COX-1 was inhibited by both extracts, although the effect of the extract from raw seeds was stronger. These results indicate that sea buckthorn seeds have anti-platelet activity that is not decreased by thermal processing, but more research is needed to determine which exact chemical compounds and mechanisms are responsible for this phenomenon.
Influence of Cooking Technique on Bioaccessibility of Bioactive Compounds in Vegetable Lentil Soup
Authors: Vargha Sofía , Igual Marta , Miraballes Marcelo , Gámbaro Adriana , García-Segovia Purificación , Martínez-Monzó Javier
Published: July 2024

Vegetables and legume soups contain various essential and bioactive constituents such as vitamin C, carotenoids, and phenolics. Antioxidant activity characteristics related to those compounds are well known to contribute profusely to human health. The cooking technique affects the bioavailability of nutrients and bioactive compounds, making it crucial to explore optimal alternatives to maximize them. The objective of this study was to explore the influence of different cooking techniques (boiling, pressure cooking, sous-vide, and cook-vide) on the physicochemical properties and bioactive characteristics of a ready-to-eat vegetable lentil soup. For this, the bioaccessibility of those compounds was assessed through an in vitro simulated gastrointestinal methodology. The firmness of vegetables was established to define treatments’ cooking times, allowing subsequent comparison of the nutritional and functional properties of the soups. The color of vegetables was also evaluated as a quality parameter, which contributed to providing a global vision of the process impact. The results revealed that in vitro digestion (IVD) caused a decrease in all bioactive compound determinations for all cooking treatments of up to 72% for total phenols, 92% for lycopene, 98% for carotenoids, and 100% for vitamin C. Additionally, the antioxidant activity of the soups after thermal treatment improved up to 46% measured by the DPPH method. This study emphasizes the importance of considering the digestion process in the selection of the most adequate cooking technique. After IVD, traditional cooking (boiling) reached the maximum total carotenoid and lycopene contents; cook-vide and pressure-cooking techniques provided the highest total phenol content, showing these three techniques to have the maximum antioxidant capacity.
Hyaluronic Acid-Coated Nanoliposomes as Delivery Systems for Fisetin: Stability, Membrane Fluidity, and Bioavailability
Authors: Sun Yan , Shen Xinghui , Yang Jiaqi , Tan Chen
Published: July 2024

Fisetin has shown numerous health benefits, whereas its food application is constrained by water insolubility, poor stability, and low bioaccessibility. This work investigated the potential of hyaluronic acid (HA)-coated nanoliposomes for the encapsulation and delivery of fisetin. It was observed that HA can adsorb onto the liposomal membrane through hydrogen bonding and maintain the spherical shape of nanoliposomes. Fluorescence analysis suggested that the HA coating restricted the motion and freedom of phospholipid molecules in the headgroup region and reduced the interior micropolarity of the nanoliposomes but did not affect the fluidity of the hydrophobic core. These effects were more pronounced for the HA with a low molecular weight (35 kDa) and moderate concentration (0.4%). The HA coating improved the storage and thermal stability of the nanoliposomes, as well as the digestive stability and bioaccessibility of the encapsulated fisetin. These findings could guide the development of HA-coated nanoliposomes for the controlled delivery of hydrophobic bioactives such as fisetin in functional foods.
Preparation and Characterization of Chitosan-Modified Bentonite Hydrogels and Application for Tetracycline Adsorption from Aqueous Solution
Authors: Guo Xuebai , Wu Zhenjun , Lu Zheng , Wang Zelong , Li Shunyi , Madhau Freeman , Guo Ting , Huo Rongqican
Published: July 2024

The “sol–gel method” was used to prepare spherical chitosan-modified bentonite (SCB) hydrogels in this study. The SCB hydrogels were characterized and used as sorbents to remove tetracycline (TC) from aqueous solutions. The adsorbents were characterized by SEM, XRD, FTIR, TG, and BET techniques. Various characterization results showed that the SCB adsorbent had fewer surface pores and a specific surface area that was 96.6% lower than the powder, but the layered mesoporous structure of bentonite remained unchanged. The adsorption process fit to both the Freundlich model and the pseudo-second-order kinetic model showed that it was a non-monolayer chemical adsorption process affected by intra-particle diffusion. The maximum monolayer adsorption capacity determined by the Langmuir model was 39.49 mg/g. Thermodynamic parameters indicated that adsorption was a spontaneous, endothermic, and entropy-increasing process. In addition, solid–liquid separation was easy with the SCB adsorbent, providing important reference information for the synthesis of SCB as a novel and promising adsorbent for the removal of antibiotics from wastewater at the industrial level.
Evaluating the Impact of DEM Spatial Resolution on 3D Rockfall Simulation in GIS Environment
Authors: Kakavas Maria P. , Frattini Paolo , Previati Alberto , Nikolakopoulos Konstantinos G.
Published: July 2024

Rockfalls are natural geological phenomena characterized by the abrupt detachment and freefall descent of rock fragments from steep slopes. These events exhibit considerable variability in scale, velocity, and trajectory, influenced by the geological composition of the slope, the topography, and other environmental conditions. By employing advanced modeling techniques and terrain analysis, researchers aim to predict and control rockfall hazards to prevent casualties and protect properties in areas at risk. In this study, two rockfall events in the villages of Myloi and Platiana of Ilia prefecture were examined. The research was conducted by means of HY-STONE software, which performs 3D numerical modeling of the motion of non-interacting blocks. To perform this modeling, input files require the processing of base maps and datasets in a GIS environment. Stochastic modeling and 3D descriptions of slope topography, based on Digital Elevation Models (DEMs) without spatial resolution limitations, ensure multiscale analysis capabilities. Considering this capability, seven freely available DEMs, derived from various sources, were applied in HY-STONE with the scope of performing a large number of multiparametric analyses and selecting the most appropriate and efficient DEM for the software requirements. All the necessary data for the multiparametric analyses were generated within a GIS environment, utilizing either the same restitution coefficients and rolling friction coefficient or varying ones. The results indicate that finer-resolution DEMs capture detailed terrain features, enabling the precise identification of rockfall source areas and an accurate depiction of the kinetic energy distribution. Further, the results show that a correct application of the model to different DEMs requires a specific parametrization to account for the different roughness of the models.
Management of Stress Urinary Incontinence by Obstetricians and Gynecologists in Jordan: A Nationwide Survey Study
Authors: Qatawneh Ayman , Lari Fatemah N. , Sawas Wedad A. , Alsabree Fatemah A. , Alowaisheer Mariam Kh. , Aldarawsheh Marah A. , Alshareef Renad A.
Published: July 2024

Background: Stress urinary incontinence (SUI) is a common condition that can significantly impact a patient’s quality of life. Although multiple diagnostic and treatment options exist, significant variability in SUI management exists between countries. Since women’s SUI prevalence in Jordan is high, and Jordan is a lower-middle-income country, this study aimed to investigate how obstetricians and gynecologists (OBGYNs) across Jordan manage and treat women with SUI. Method: A Google Forms survey was prepared and sent out to Jordanian OBGYNs via WhatsApp. The results were collected and arranged in Microsoft Excel and then transferred to SPSS for statistical analysis. Results: Out of the 804 Jordanian registered OBGYNs, 497 could be reached, 240 conduct gynecological surgeries, and 94 completed the survey, providing a response rate of 39.2%. Most of the respondents were females between 41 and 55 years old. More than 70% of the OBGYNs worked in the private sector, and 88.3% operated in the capital of Jordan. Most of the respondents favored lifestyle and behavior therapy (43.6%) or pelvic floor physiotherapy (40.4%) as the first-line management for SUI. The transobturator mid-urethral sling (MUS) was the most common initial surgical treatment option. The physicians preferred two-staged procedures for the repair of pelvic organ prolapse alongside concomitant SUI. In the case of recurrent SUI following surgery, 77% of the respondents chose to refer to a urologist or urogynecologist. Conclusions: The Jordanian OBGYNs preferred using lifestyle/behavioral therapy and pelvic floor muscle physiotherapy as the first-line treatment to manage SUI. Secondly, the MUS would be the most frequently preferred surgical choice. To effectively manage SUI, adequate training in urogynecology and referral resources are essential in lower-middle-income countries.
Motivational Barriers and Facilitators for Older Adults’ Engagement in Exercise during Depressive Episodes: A Network Meta-Analysis of Randomized Controlled Trials
Authors: Dai Mei-Ling , Ting Berne , Malau Ikbal Andrian , Wu Suet-Kei , Lin Chia-Ching , Lin Pan-Yen , Chen Min-Hsiung
Published: July 2024

This study aims to assess the motivational factors influencing the participation of older adults in various exercise interventions during depressive episodes and to identify which types of exercise are most effective in alleviating depressive symptoms in this population. Therefore, randomized controlled trials (RCTs) focusing on exercise interventions and their impact on depression in older adult patients, identified by the terms “exercise” AND “depression” AND “elderly” OR “geriatric”, were selected from primary electronic databases to conduct this network meta-analysis (NMA). The primary outcome was the effect on depressive symptoms, while the secondary outcome was the comparison of dropout rates between the intervention groups and the usual care control groups, as a measure of sustained motivation and engagement. Standardized mean difference (SMD) values and the corresponding 95% confidence intervals (CIs) were computed for effect evaluation. This study protocol has been registered in IPLASY (INPLASY 202460035). The results of 31 RCTs with 3238 participants indicated that qigong (SMD −1.17, −2.28 to −0.06), Otago Exercise (SMD −1.15, −2.29 to −0.01), and yoga (SMD −0.88, −1.55 to −0.21) significantly alleviate depressive symptoms in older adults. Walking (SMD −0.82, −1.34 to −0.31) and strength training (SMD −0.67, −1.05 to −0.30) also showed significant effects. Aerobic, physical training, and tai chi had moderate effects, while multisport showed a weaker impact with no significant improvement. In summary, our research findings demonstrate that exercise can effectively alleviate depressive symptoms in older adults, with low dropout rates likely due to interconnected physiological, psychological, and social mechanisms. This is crucial for enhancing treatment strategies for older adults’ depression.
Impact of Southbound Expansion on Clustered OpenFlow Software-Defined Network Controller Synchronisation Using ODL and ONOS
Authors: Hettiarachchi Egodahettiarachchige Don Sarada Indumini , Sarkar Nurul I. , Gutierrez Jairo
Published: July 2024

The clustering methods of Software-Defined Networking (SDN) have gained popularity due to their ability to offer improved scalability, consistency, dependability, and load balancing within overlay networks and SDN partitions. This paper delved into the effects of increasing the number of OpenFlow-enabled southbound devices on the establishment and coordination of SDN-controller clusters. Specifically, we examined the volume of east–west cluster packet communications concerning the number of southbound devices within the topology. Many research studies have focused on bandwidth and the number of bytes in east–west communication. While bandwidth refers to the maximum rate at which data can be transferred, and the number of bytes reflects the volume of data being transmitted, the number of packet communications directly influences the efficiency and responsiveness of network operations. Our investigation encompassed the impact of SDN controller-to-controller communication within the cluster concerning the rising number of OpenFlow switches connected to various topologies, including tree (star-bus network), linear, and torus configurations. This study provided data on communication patterns within Open Network Operating Systems (ONOS) and OpenDaylight (ODL) clusters, revealing differing levels of controller communication with southbound network expansions. We evaluated the scalability of ODL and ONOS controllers by scrutinising the effect of increasing the number of southbound devices on the control communication volume. Our analysis revealed varied communication patterns within ONOS and ODL clusters, resulting in different volumes of control communication with southbound expansions. The findings indicated that in small-to-medium-sized SDNs, ODL outperformed ONOS, notably with faster cluster discovery. Conversely, ONOS demonstrated greater efficiency in larger networks owing to its centralised communication architecture. Finally, we provide recommendations for selecting the most suitable controllers based on the size of southbound networks, aiming to provide practical guidelines for optimal network performance.
Optimizing Task Offloading for Power Line Inspection in Smart Grid Networks with Edge Computing: A Game Theory Approach
Authors: Lu Xu , Yuan Sihan , Nian Zhongyuan , Mu Chunfang , Li Xi
Published: July 2024

In the power grid, inspection robots enhance operational efficiency and safety by inspecting power lines for information sharing and interaction. Edge computing improves computational efficiency by positioning resources close to the data source, supporting real-time fault detection and line monitoring. However, large data volumes and high latency pose challenges. Existing offloading strategies often neglect task divisibility and priority, resulting in low efficiency and poor system performance. This paper constructs a power grid inspection offloading scenario using Python 3.11.2 to study and improve various offloading strategies. Implementing a game-theory-based distributed computation offloading strategy, simulation analysis reveals issues with high latency and low resource utilization. To address these, an improved game-theory-based strategy is proposed, optimizing task allocation and priority settings. By integrating local and edge computing resources, resource utilization is enhanced, and latency is significantly reduced. Simulations show that the improved strategy lowers communication latency, enhances system performance, and increases resource utilization in the power grid inspection context, offering valuable insights for related research.
Multi-Antenna Array-Based Massive MIMO for B5G/6G: State of the Art, Challenges, and Future Research Directions
Authors: Qamar Faizan , Kazmi Syed Hussain Ali , Ariffin Khairul Akram Zainol , Tayyab Muhammad , Nguyen Quang Ngoc
Published: July 2024

This comprehensive article explores the massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, cell-free MIMO, and security considerations, this article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights the challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of federated learning in M-MIMO systems. By examining these cutting-edge developments, this article aims to advance knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.
Index of Attention for a Simplified Condition Assessment and Classification of Bridges
Authors: Ormando Chiara , Lucaferri Valentina , Giocoli Alessandro , Clemente Paolo , Buffarini Giacomo , Tofani Alberto
Published: July 2024

A procedure for a simplified evaluation of bridges is proposed based on census and visual inspections. The structural–foundational, seismic, landslide, and hydraulic risks are considered, the hazard, vulnerability, and exposure factors of which are quantified with an index that can assume integer values from 1 to 5. Polynomial functions are then defined combining these indices, calculating an index for each risk and finally a multi-risk index of attention. The procedure follows a mathematical approach, less influenced by subjective choices, leading to a more gradual and efficient classification that managers can directly utilize. Specific needs and requirements result in specific configuration and calibration of the mathematical model coefficients. In this study, the authors calibrated coefficients to obtain results that were compliant with the Italian guidelines for existing bridges. The procedure, tested on a set of 86 bridges, does not replace an accurate evaluation, which is necessary in some cases and represents a higher level of knowledge, nor does it claim to provide a definitive result. It provides a more efficient classification, useful for establishing a rational decision-making process to prioritize any subsequent retrofit interventions.
Genome-Wide Identification and Analysis of Family Members with Juvenile Hormone Binding Protein Domains in Spodoptera frugiperda
Authors: Liu Yang , Zou Kunliang , Wang Tonghan , Guan Minghui , Duan Haiming , Yu Haibing , Wu Degong , Du Junli
Published: July 2024

Juvenile hormone binding proteins (JHBPs) are carrier proteins that bind to juvenile hormone (JH) to form a complex, which then transports the JH to target organs to regulate insect growth and development. Through bioinformatics analysis, 76 genes encoding JHBP in S. frugiperda were identified from whole genome data (SfJHBP1-SfJHBP76). These genes are unevenly distributed across 8 chromosomes, with gene differentiation primarily driven by tandem duplication. Most SfJHBP proteins are acidic, and their secondary structures are mainly composed of α-helices and random coils. Gene structure and conserved motif analyses reveal significant variations in the number of coding sequences (CDS) and a high diversity in amino acid sequences. Phylogenetic analysis classified the genes into four subfamilies, with a notable presence of directly homologous genes between S. frugiperda and S. litura, suggesting a close relationship between the two species. RNA-seq data from public databases and qPCR of selected SfJHBP genes show that SfJHBP20, SfJHBP50, and SfJHBP69 are highly expressed at most developmental stages, while SfJHBP8 and SfJHBP14 exhibit specific expression during the pupal stage and in the midgut. These findings provide a theoretical basis for future studies on the biological functions of this gene family.
Sensillar Ultrastructure of the Antennae and Maxillary Palps of the Warble Fly Oestromyia leporina (Pallas, 1778) (Diptera: Oestridae)
Authors: An Zhuowei , Li Xinyu , Wang Qike , Xu Wentian , Zhang Dong
Published: July 2024

Despite the development of molecular techniques, morphological phylogeny still remains integral in underpinning the relationship between some clades of Calyptratae, especially the ones with fast radiation, such as those in Oestridae (Diptera: Brachycera), yet few synapomorphy has been proposed for adults in this family. Using scanning electron microscopy, we investigated the morphological structure and ultrastructure of the antennae and maxillary palps of adult Oestromyia leporina (Hypodermatinae, Oestridae). One type of trichoid sensillum (Tr), three types of basiconic sensilla (Ba I, Ba II, and Ba III), one type of coeloconic sensillum (Co I), and one type of clavate sensillum (Cl) were found on the antennal postpedicel. Surprisingly, this species has the most complex types of sensilla on the maxillary palps that have been reported in Calyptratae so far, with two types of coeloconic sensilla (Co II and Co III) and two types of mechanoreceptors. We then identified three common characteristics on the arista of Oestridae (Hypodermatinae, Oestrinae, Gasterophilinae and Cuterebrinae) that are potential synapomorphies. These characteristics indicate the value of the morphology of maxillary palps and aristae in taxonomy studies of Calyptratae.