bluuebunny/crossref_metadata_2025 huggingface dataset:
An Overview of Safety and Security Analysis Frameworks for the Internet of Things
Authors: Abdulhamid Alhassan , Kabir Sohag , Ghafir Ibrahim , Lei Ci
Published: July 2023

The rapid progress of the Internet of Things (IoT) has continued to offer humanity numerous benefits, including many security and safety-critical applications. However, unlocking the full potential of IoT applications, especially in high-consequence domains, requires the assurance that IoT devices will not constitute risk hazards to the users or the environment. To design safe, secure, and reliable IoT systems, numerous frameworks have been proposed to analyse the safety and security, among other properties. This paper reviews some of the prominent classical and model-based system engineering (MBSE) approaches for IoT systems’ safety and security analysis. The review established that most analysis frameworks are based on classical manual approaches, which independently evaluate the two properties. The manual frameworks tend to inherit the natural limitations of informal system modelling, such as human error, a cumbersome processes, time consumption, and a lack of support for reusability. Model-based approaches have been incorporated into the safety and security analysis process to simplify the analysis process and improve the system design’s efficiency and manageability. Conversely, the existing MBSE safety and security analysis approaches in the IoT environment are still in their infancy. The limited number of proposed MBSE approaches have only considered limited and simple scenarios, which are yet to adequately evaluate the complex interactions between the two properties in the IoT domain. The findings of this survey are that the existing methods have not adequately addressed the analysis of safety/security interdependencies, detailed cyber security quantification analysis, and the unified treatment of safety and security properties. The existing classical and MBSE frameworks’ limitations obviously create gaps for a meaningful assessment of IoT dependability. To address some of the gaps, we proposed a possible research direction for developing a novel MBSE approach for the IoT domain’s safety and security coanalysis framework.
WHORU: Improving Abstractive Dialogue Summarization with Personal Pronoun Resolution
Authors: Zhou Tingting
Published: July 2023

With the abundance of conversations happening everywhere, dialogue summarization plays an increasingly important role in the real world. However, dialogues inevitably involve many personal pronouns, which hinder the performance of existing dialogue summarization models. This work proposes a framework named WHORU to inject external personal pronoun resolution (PPR) information into abstractive dialogue summarization models. A simple and effective PPR method for the dialogue domain is further proposed to reduce time and space consumption. Experiments demonstrated the superiority of the proposed methods. More importantly, WHORU achieves new SOTA results on SAMSum and AMI datasets.
Minimizing Power Losses for Distributed Generation (DG) Placements by Considering Voltage Profiles on Distribution Lines for Different Loads Using Genetic Algorithm Methods
Authors: Siregar Ramdhan Halid , Away Yuwaldi , Tarmizi  , Akhyar
Published: July 2023

The need for electrical energy is increasing in line with the increase in population and increasing progress in welfare. On the other hand, the availability of fossil fuels as the main fuel in generating electricity is dwindling; so, there is a need for policies that require the use of environmentally friendly renewable energy. The utilization of renewable energy does not necessarily apply freely due to several constraints. One effort is a generator or distributed generation (DG) which is placed in the distribution line close to the load. The utilization of DG must go through planning, especially the large capacity and position on the bus and on the feeder, which will result in small network losses and a voltage profile that meets tolerance limits. Thus, the purpose of this study is to optimize to obtain the capacity and location of the DG calculated by considering the variation in the load through the genetic algorithm method. As a result, the optimal DG position for normal load is obtained on bus 18, bus 20, and bus 32 with capacities of 190 kW, 463 kW, and 370 kW, respectively. The losses obtained decreased from 54.6733 kW to 9.9447 kW, and the voltage profile was maintained within the specified limits. Optimization was carried out for decreasing and increasing loads in percent. The result is that losses can be minimized, and the voltage profile remains within the required limits. The lower the load, the more stable the voltage and the smaller the losses; meanwhile, the larger the load, the more fluctuating the voltage is, but still within the limits specified in the optimization.
Reasons for the Recent Onshore Wind Capacity Factor Increase
Authors: Jung Christopher , Schindler Dirk
Published: July 2023

Increasing wind capacity and capacity factors (CF) are essential for achieving the goals set by the Paris Climate Agreement. From 2010–2012 to 2018–2020, the 3-year mean CF of the global onshore wind turbine fleet rose from 0.22 to 0.25. Wind turbine siting, wind turbine technology, hub height, and curtailed wind energy are well-known CF drivers. However, the extent of these drivers for CF is unknown. Thus, the goal is to quantify the shares of the four drivers in CF development in Germany as a case. Newly developed national power curves from high-resolution wind speed models and hourly energy market data are the basis for the study. We created four scenarios, each with one driver kept constant at the 2010–2012 level, in order to quantify the share of a driver for CF change between 2010–2012 and 2019–2021. The results indicated that rising hub heights increased CF by 10.4%. Improved wind turbine technology caused 7.3% higher CF. However, the absolute CF increase amounted to only 11.9%. It is because less favorable wind turbine sites and curtailment in the later period moderated the CF increase by 2.1% and 3.6%, respectively. The drivers are mainly responsible for perennial CF development. In contrast, variations in wind resource availability drive the enormous CF inter-annual variability. No multi-year wind resource change was detected.
Energy Consumption and Grid Interaction Analysis of Electric Vehicles Based on Particle Swarm Optimisation Method
Authors: Deželak Klemen , Sredenšek Klemen , Seme Sebastijan
Published: July 2023

The widespread adoption of electric vehicles poses certain challenges to the distribution grid, which refers to the network of power lines, transformers, and other infrastructure that delivers electricity from power plants to consumers. This higher demand can strain the distribution grid, particularly in areas with a high concentration of electric vehicles. Grid operators need to ensure that the grid infrastructure can handle this additional load and prevent overloading and consequences in terms of additional losses. As part of the task, a methodology was developed for the assessment of the electricity consumption of battery electric vehicles in Slovenia. The approach used for the calculation includes the number of electric cars, average consumption, distance travelled and efficiency of the system. Additionally, the results of the modelling approach for an integrated distribution grid model in terms of steady-state simulations are presented. The regular situation of the power losses within the distribution grid is managed together with an optimal result. In this sense, an application of the particle swarm optimisation-based strategy is suggested to minimise reliance on grid systems.
A Review of Gravitational Water Vortex Hydro Turbine Systems for Hydropower Generation
Authors: Maika Nosare , Lin Wenxian , Khatamifar Mehdi
Published: July 2023

Hydropower is one of the most sustainable and desirable renewable energy sources. Gravitational water vortex hydro turbine (GWVHT) systems are one of the most suitable and sustainable renewable power generation devices for remote and rural areas, particularly in developing countries, owing to their small scales and low costs. There are various GWVHT systems with different configurations and various operating conditions. The main components of a GWVHT system include the inlet and outlet channels, a basin, and a turbine on which there are a number of blades attached. This paper presents a comprehensive review regarding the progress and development of various GWVHT systems, covering broad aspects of GWVHT systems, particularly various types of basins, inlet and outlet channels, turbines with blades which have different shapes, orientations, sizes, numbers, etc. The nature of the previous studies is summarised. The fundamentals of the vortex dynamics involved and the quantitative analysis of the performance of GWVHT systems are also described. The turbulence models and multiphase models used in some leading numerical simulation studies have been reviewed. As a case study, the implementation of a GWVHT system in PNG is presented. Based on the review of previous studies regarding GWVHT systems, the major issues and challenges are summarised, and some key topics are recommended for future research work on the performance of GWVHT systems.
An In-Depth Analysis of Strength and Stiffness Variability in 3D-Printed Sandstones: Implications for Geomechanics
Authors: Sanchez-Barra Angel , Zambrano-Narvaez Gonzalo , Chalaturnyk Rick
Published: July 2023

Natural rocks are highly heterogeneous due to various geological processes that constantly alter their properties. The accumulation, deposition, and cementation of mineral and organic particles continuously modify the spatial characteristics of rock properties. Property variability or anisotropy is commonly observed in most rock types and influences strength, transport, and thermal conductivity behavior. This unpredictability presents a significant challenge for laboratory testing. Binder-jet additive manufacturing (3D printing) has emerged as a valuable technology for characterizing rock properties in geoscience and engineering. This study proposes a novel methodology to evaluate the variability and repeatability of mechanical properties of 3D-printed sandstones during binder-jet additive manufacturing. The mechanical properties were analyzed statistically for samples located in various parts of the 3D printer build volume. The results showed that the 3D-printed sandstones exhibited significant variations in their strength and stiffness properties when measured from samples produced within the same build volume during binder-jet additive manufacturing. The uniaxial compressive strength (UCS) varied from 23 to 38 MPa, with an average value of 29 MPa. Young’s modulus, on the other hand, ranged from 1.5 to 4.05 GPa, with an average value of 2.33 GPa. The variability of the mechanical properties, quantified by the standard deviation, decreased when the entire population of 3D-printed sandstones was divided into smaller samples situated at different elevations of the build platform. These findings offer valuable insights into improving the reliability and predictability of 3D-printed sandstone properties, a critical factor for various applications in fields like petroleum engineering and construction.
Review of Waveform Distortion Interactions Assessment in Railway Power Systems
Authors: Salles Rafael S. , Rönnberg Sarah K.
Published: July 2023

This work aims to cover the measurement, modeling, and analysis of waveform distortions in railway power systems. It is focused on waveform distortion as a phenomenon that includes harmonic distortion, interharmonic distortion, and supraharmonics. A comprehensive view of the interactions of waveform distortions in railway systems is needed, together with a grid perspective of power quality incorporating all aspects, sources, propagation, requirements, and effects. It is understood that the communities interested or involved in the subject of railway power systems would benefit from an integrated overview of the literature on the complex problem of waveform distortion. The literature review is divided into four categories: characterization and measurements, modeling, the application of artificial intelligence, and specific issues. For each category of work, the contributions are highlighted, and a discussion on opportunities, gaps, and critical observations is provided. The work successfully builds a framework for the subject with two main characteristics; the review is informative and propositional, providing a road map of opportunities for future works. Some aspects and recommendations can be highlighted. Suggestions for future works and research practices on waveform distortion in electrical transportation are offered.
A Computationally Efficient Approach for the State-of-Health Estimation of Lithium-Ion Batteries
Authors: Qin Haochen , Fan Xuexin , Fan Yaxiang , Wang Ruitian , Shang Qianyi , Zhang Dong
Published: July 2023

High maintenance costs and safety risks due to lithium-ion battery degeneration have significantly and seriously restricted the application potential of batteries. Thus, this paper proposes an efficient calculation approach for state of health (SOH) estimation in lithium-ion batteries that can be implemented in battery management system (BMS) hardware. First, from the variables of the charge profile, only the complete voltage data is taken as the input to represent the complete aging characteristics of the batteries while limiting the computational complexity. Then, this paper combines the light gradient boosting machine (LightGBM) and weighted quantile regression (WQR) methods to learn a nonlinear mapping between the measurable characteristics and the SOH. A confidence interval is applied to quantify the uncertainty of the SOH estimate, and the model is called LightGBM-WQR. Finally, two public datasets are employed to verify the proposed approach. The proposed LightGBM-WQR model achieves high accuracy in its SOH estimation, and the average absolute error (MAE) of all cells is limited to 1.57%. In addition, the average computation time of the model is less than 0.8 ms for ten runs. This work shows that the model is effective and rapid in its SOH estimation. The SOH estimation model has also been tested on the edge computing module as a possible innovation to replace the BMS bearer computing function, which provides tentative solutions for online practical applications such as energy storage systems and electric vehicles.
Artificial Reefs around the World: A Review of the State of the Art and a Meta-Analysis of Its Effectiveness for the Restoration of Marine Ecosystems
Authors: Bracho-Villavicencio Carolina , Matthews-Cascon Helena , Rossi Sergio
Published: July 2023

Over the past decade, there has been increasing interest in marine restoration, requiring a consideration of various approaches for optimal success. Artificial reefs (ARs) have been employed for marine restoration and fisheries management, but their effectiveness in restoring ecosystems lacks well-defined ecological criteria and empirical evidence. A systematic review of the literature on ARs articles between 1990–2020, a meta-analysis of their effectiveness based on the similarity of species composition with reference natural reefs (NRs), as well as bias risk analyses were carried out. Research on ARs primarily focused production of marine communities (n = 168). There are important information gaps regarding socioeconomic aspects; design, materials, and disposal in the selected habitats; legal, management, and planning aspects considering long-term monitoring. Regarding effectiveness, few articles (n = 13) allowed comparisons between ARs and NRs, highlighting the need to apply proper reference sites in AR implementations. Meta-analysis showed that ARs are not similar to reference NRs (p = 0.03, common effect and p = 0.05 random effect models). However, a high index of heterogeneity (88%) suggests that this relation may be influenced by factors other than the reef type. Thus, further analysis can disguise variables conditioning this AR–NR similarity as a measure of restoration for degraded marine ecosystems.
A Trunk Detection Method for Camellia oleifera Fruit Harvesting Robot Based on Improved YOLOv7
Authors: Liu Yang , Wang Haorui , Liu Yinhui , Luo Yuanyin , Li Haiying , Chen Haifei , Liao Kai , Li Lijun
Published: July 2023

Trunk recognition is a critical technology for Camellia oleifera fruit harvesting robots, as it enables accurate and efficient detection and localization of vibration or picking points in unstructured natural environments. Traditional trunk detection methods heavily rely on the visual judgment of robot operators, resulting in significant errors and incorrect vibration point identification. In this paper, we propose a new method based on an improved YOLOv7 network for Camellia oleifera trunk detection. Firstly, we integrate an attention mechanism into the backbone and head layers of YOLOv7, enhancing feature extraction for trunks and enabling the network to focus on relevant target objects. Secondly, we design a weighted confidence loss function based on Facol-EIoU to replace the original loss function in the improved YOLOv7 network. This modification aims to enhance the detection performance specifically for Camellia oleifera trunks. Finally, trunk detection experiments and comparative analyses were conducted with YOLOv3, YOLOv4, YOLOv5, YOLOv7 and improved YOLOv7 models. The experimental results demonstrate that our proposed method achieves an mAP of 89.2%, Recall Rate of 0.94, F1 score of 0.87 and Average Detection Speed of 0.018s/pic that surpass those of YOLOv3, YOLOv4, YOLOv5 and YOLOv7 models. The improved YOLOv7 model exhibits excellent trunk detection accuracy, enabling Camellia oleifera fruit harvesting robots to effectively detect trunks in unstructured orchards.
Modeling Fire Boundary Formation Based on Machine Learning in Liangshan, China
Authors: Xu Yiqing , Sun Yanyan , Zhang Fuquan , Jiang Hanyuan
Published: July 2023

Forest fires create burned and unburned areas on a spatial scale, with the boundary between these areas known as the fire boundary. Following an analysis of forest fire boundaries in the northern region of Yangyuan County, located in the Liangshan Yi Autonomous Prefecture of Sichuan Province, China, several key factors influencing the formation of fire boundaries were identified. These factors include the topography, vegetation, climate, and human activity. To explore the impact of these factors in different spaces on potential results, we varied the distances between matched sample points and built six fire environment models with different sampling distances. We constructed a matched case-control conditional light gradient boosting machine (MCC CLightGBM) to model these environment models and analyzed the factors influencing fire boundary formation and the spatial locations of the predicted boundaries. Our results show that the MCC CLightGBM model performs better when points on the selected boundaries are paired with points within the burned areas, specifically between 120 m and 480 m away from the boundaries. By using the MCC CLightGBM model to predict the probability of boundary formation under six environmental models at different distances, we found that fire boundaries are most likely to form near roads and populated areas. Boundary formation is also influenced by areas with significant topographic relief. It should be noted explicitly that this conclusion is only applicable to this study region and has not been validated for other different regions. Finally, the matched case-control conditional random forest (MCC CRF) model was constructed for comparison experiments. The MCC CLightGBM model demonstrates potential in predicting fire boundaries and fills a gap in research on fire boundary predictions in this area which can be useful in future forest fire management, allowing for a quick and intuitive assessment of where a fire has stopped.
Durability of Wood Exposed above Ground—Experience with the Bundle Test Method
Authors: Brischke Christian , Alfredsen Gry , Emmerich Lukas , Humar Miha , Meyer-Veltrup Linda
Published: July 2023

The durability against decay organisms is an essential material property for wood in outdoor use. A jack of all trades method for above-ground wood durability testing has been sought for decades, but until now no method has found its way into European standardization. The method of choice shall be applicable for untreated and treated wood—ideally also for wood composites. It shall further be reproducible, objective, fast, easy, and inexpensive. Finally, it shall provide high predictive power. This study was aimed at a review of results and practical experience with the Bundle test method which could serve as a standard procedure for above-ground field tests of wood-based materials. The method allows for water-trapping, creates a moderate moisture-induced decay risk typical for UC 3 situations, and was found applicable for a wide range of wood materials. The method allows for rapid infestation and failure of non-durable reference species within five years in Central Europe. Based on results from Bundle tests with different modifications and performed at different locations, a guideline has been developed. The method is recommended as a suitable tool for determining the durability of various wood-based materials including modified and preservative-treated wood and can provide data for durability classification.
Optimization of the Decision Criterion for Increasing the Bandwidth Utilization by Means of the Novel Effective DBA Algorithm in NG-PON2 Networks
Authors: Róka Rastislav
Published: July 2023

In this paper, the reasons for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented, and the possibilities for realization and utilization of extended dynamic wavelength and bandwidth algorithms for the second next-generation passive optical networks (NG-PON2) are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in detail, focused on the importance of the decision criterion optimization. To achieve a better bandwidth utilization of dedicated wavelengths in NG-PON2 networks, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to optical network units as well as the optimization of the decision criterion. The algorithm and the proposed method are tested and evaluated through simulation with actual traffic data. For analyzing novel extended dynamic wavelength and bandwidth algorithms used for various cases of wavelength allocation in NG-PON2 networks, the effective dynamic bandwidth allocation algorithm analysis is realized in the enhancement of simulation program. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid time and wavelength division multiplexing technique.
Machine Learning for Network Intrusion Detection—A Comparative Study
Authors: Al Lail Mustafa , Garcia Alejandro , Olivo Saul
Published: July 2023

Modern society has quickly evolved to utilize communication and data-sharing media with the advent of the internet and electronic technologies. However, these technologies have created new opportunities for attackers to gain access to confidential electronic resources. As a result, data breaches have significantly impacted our society in multiple ways. To mitigate this situation, researchers have developed multiple security countermeasure techniques known as Network Intrusion Detection Systems (NIDS). Despite these techniques, attackers have developed new strategies to gain unauthorized access to resources. In this work, we propose using machine learning (ML) to develop a NIDS system capable of detecting modern attack types with a very high detection rate. To this end, we implement and evaluate several ML algorithms and compare their effectiveness using a state-of-the-art dataset containing modern attack types. The results show that the random forest model outperforms other models, with a detection rate of modern network attacks of 97 percent. This study shows that not only is accurate prediction possible but also a high detection rate of attacks can be achieved. These results indicate that ML has the potential to create very effective NIDS systems.
Comparison of Flavor Profile Relationship of Soy Sauce under Different Storage Conditions
Authors: Wang Rui , Liang Miao , Zhang Zhimin , Wu Yajian , Liu Yuping
Published: July 2023

To elucidate the relation of flavor in soy sauce (SS) kept at room temperature (SSAT) and SS kept under accelerated aging condition (SSAA), four analytical instruments, including electronic nose (E-nose), electronic tongue (E-tongue), gas chromatography–mass spectrometry-olfactory combined with solvent assisted flavor evaporation, and amino acid analyzer, were applied for analyzing the overall flavor profiles and flavor constituents in SSAT and SSAA. The results of E-nose and E-tongue showed overall flavor profile in SSAT for 3 weeks was similar to that of SSAA for 1 week, and 6 weeks (SSAT) was similar to 2 weeks (SSAA). In SS, a total of 35 odor-active compounds were identified and quantitated, and 22 compounds with odor activity value ≥1 were determined as key odorants. The compounds with the highest concentration were 4-hydroxy-2,5-dimethyl-3(2H)-furanone (28,756 μg/mL), followed by acetic acid (8838 μg/mL) and maltol (7984 μg/mL). The heatmap and hierarchical cluster analysis indicated that the concentrations of key odorants and amino acids in SSAT for 3 weeks was close to those of SSAA for 1 week, and 6 weeks (SSAT) was similar to 2 weeks (SSAA). Based on the results obtained above, it was concluded that the flavor changes in SSAA for 1 week were equivalent to those in SSAT for 3 weeks.
Effect of Supplementation with Coffee and Cocoa By-Products to Ameliorate Metabolic Syndrome Alterations Induced by High-Fat Diet in Female Mice
Authors: Braojos Cheyenne , Gila-Díaz Andrea , Rodríguez-Rodríguez Pilar , Monedero-Cobeta Ignacio , Morales María Dolores , Ruvira Santiago , Ramiro-Cortijo David , Benítez Vanesa , Martín-Cabrejas María A. , Arribas Silvia M.
Published: July 2023

Coffee and cocoa manufacturing produces large amounts of waste. Generated by-products contain bioactive compounds with antioxidant and anti-inflammatory properties, suitable for treating metabolic syndrome (MetS). We aimed to compare the efficacy of aqueous extracts and flours from coffee pulp (CfPulp-E, CfPulp-F) and cocoa shell (CcShell-E, CcShell-F) to ameliorate MetS alterations induced by a high-fat diet (HFD). Bioactive component content was assessed by HPLC/MS. C57BL/6 female mice were fed for 6 weeks with HFD followed by 6 weeks with HFD plus supplementation with one of the ingredients (500 mg/kg/day, 5 days/week), and compared to non-supplemented HFD and Control group fed with regular chow. Body weight, adipocyte size and browning (Mitotracker, confocal microscopy), plasma glycemia (basal, glucose tolerance test–area under the curve, GTT-AUC), lipid profile, and leptin were compared between groups. Cocoa shell ingredients had mainly caffeine, theobromine, protocatechuic acid, and flavan-3-ols. Coffee pulp showed a high content in caffeine, protocatechuic, and chlorogenic acids. Compared to Control mice, HFD group showed alterations in all parameters. Compared to HFD, CcShell-F significantly reduced adipocyte size, increased browning and high-density lipoprotein cholesterol (HDL), and normalized basal glycemia, while CcShell-E only increased HDL. Both coffee pulp ingredients normalized adipocyte size, basal glycemia, and GTT-AUC. Additionally, CfPulp-E improved hyperleptinemia, reduced triglycerides, and slowed weight gain, and CfPulp-F increased HDL. In conclusion, coffee pulp ingredients showed a better efficacy against MetS, likely due to the synergic effect of caffeine, protocatechuic, and chlorogenic acids. Since coffee pulp is already approved as a food ingredient, this by-product could be used in humans to treat obesity-related MetS alterations.
Effect of Different Packaging Strategies on the Secondary Shelf Life of Young and Structured Red Wine
Authors: Bianchi Alessandro , Taglieri Isabella , Macaluso Monica , Sanmartin Chiara , Zinnai Angela , Venturi Francesca
Published: July 2023

When bottled wine is opened, a completely different scenario occurs that can accelerate the oxidation of the product. This is called the secondary shelf life (SSL), which is generally shorter and less predictable than the primary shelf life (PSL). In this context, the research aim was to evaluate the changes that occur in two types of red wine during two tests to evaluate the secondary shelf life as a function of the packaging systems. The variation of Total SO2 and Free SO2 and the other chemical parameters (polyphenols, anthocyanins, proanthocyanidins, color, and volatile acidity) were used to assess the oxidation rate of the packaging samples after opening during the SSL. In both tests and for the two types of stored red wine, the polymeric cap showed the best results. The other types of closure (screw cap, natural cork, crow cap, and Tetra Brik) showed a negative trend and a reduced SSL for both red wines. Finally, the sensory results confirmed that with the polymeric cap, the SSL increases considerably compared to other capping systems. These results may be due to the technical characteristics of polymeric materials, which tend to vary slightly in shape after repeated usage.
Characterization and Correlation of Microbiota and Higher Alcohols Based on Metagenomic and Metabolite Profiling during Rice-Flavor Baijiu Fermentation
Authors: Wang Hong , Zhang Minqian , Qu Chunyun , Fei Yongtao , Liang Jinglong , Bai Weidong , Zhao Wenhong , Xiao Gengsheng , Liu Gongliang
Published: July 2023

Higher alcohol, as an inevitable product of fermentation, plays an important role in the flavor and quality of Baijiu. However, the relationship between the complex microbial metabolism and the formation of higher alcohols in rice-flavor Baijiu was not clear. To investigate the relationship between microorganisms and higher alcohol production, two fermentation mashes inoculated with starters from Heyuan Jinhuangtian Liquor Co., Ltd. (Heyuan, China) as JM and Guangdong Changleshao Co., Ltd. (Meizhou, China) as CM, respectively, with significant differences in higher alcohol profiles during rice-flavor Baijiu fermentation were selected. In general, higher alcohols presented a rapid accumulation during the early fermentation stages, especially in JM, with higher and faster increases than those in CM. As for their precursors including amino acids, pyruvic acid and ketoacids, complex variations were observed during the fermentation. Metagenomic results indicated that Saccharomyces cerevisiae and Rhizopus microsporus were the microorganisms present throughout the brewing process in JM and CM, and the relative abundance of R. microsporus in JM was significantly higher than that in CM. The results of higher alcohol metabolism in JM may contribute to the regulation of higher alcohols in rice-flavor Baijiu.
Determination of Integrity Index Kv in CHN-BQ Method by BP Neural Network Based on Fractal Dimension D
Authors: Zhang Qi , Shen Yixin , Pei Yuechao , Wang Xiaojun , Wang Maohui , Lai Jingqi
Published: July 2023

The integrity index Kv is the quantitative index in the CHN-BQ method, which can be determined by the acoustic wave test, volume joint number Jv, or empirical judgment. However, these methods are not convenient and require the practitioner to have extensive experience. In this study, a new quantitative evaluation of Kv is proposed to determine Kv accurately and conveniently. A method for determining the fractal dimension D based on the structural plane network simulation is proposed. A quantitative relationship between fractal dimension D and integrity index Kv is established based on the geological information from 80 sampling windows in Mingtang Tunnel. To further consider the effect of structural plane conditions on Kv, a BP neural network is constructed with the fractal dimension D and structural plane condition index R3 as input and Kv as output. The BP neural network is trained by 260 groups of tunnel data and validated by 39 groups of test data. The results show that the correlation coefficient R2 between the predicted Kvp and measured Kvm is 0.93, and the average relative error is 7.51%. In addition, the predicted Kvp from the 39 groups of data is compared with the Kvd determined directly by fractal dimension D. It can be found that the Kvd has a larger error compared with the Kvp, especially in the case of a Kv less than 0.5. Finally, the BP neural network for predicting Kv is applied to the Jiulaopo Tunnel. The maximum relative error between the measured Kvm and the predicted Kvp is 5.13%, and the average relative error is 2.71%. The BP neural network is well trained and can accurately predict Kv based on the fractal dimension D and the structural plane condition index R3.
A Novel Method of Blockchain Cryptocurrency Price Prediction Using Fractional Grey Model
Authors: Yang Yunfei , Xiong Jiamei , Zhao Lei , Wang Xiaomei , Hua Lianlian , Wu Lifeng
Published: July 2023

Cryptocurrency prices have the characteristic of high volatility, which has a specific resistance to cryptocurrency price prediction. Therefore, the appropriate cryptocurrency price predictive method can help reduce the investment risk of investors. In this study, we proposed a novel prediction method using a fractional grey model (FGM (1,1)) to predict the price of blockchain cryptocurrency. Specifically, this study established the FGM (1,1) through the closing price of three representative blockchain cryptocurrencies (Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC)). It adopted the PSO algorithm to optimize and obtain the optimal order of the model, thereby conducting prediction research on the price of blockchain cryptocurrency. To verify the predictive precision of the FGM (1,1), we mainly took MAPE, MAE, and RMSE as the judging criteria and compared the model’s predictive precision with the GM (1,1) through experiments. The research results indicate that within the data range studied, the predictive accuracy of the FGM (1,1) in the closing price of BTC, ETH, and LTC has reached a “highly accurate” level. Moreover, in contrast to the GM (1,1), the FGM (1,1) outperforms predictive capability in the experiments. This study provides a feasible new method for the price prediction of blockchain cryptocurrency. It has specific references and enlightenment for government departments, investors, and researchers in theory and practice.
Racial and Ethnic Disparities in Genomic Healthcare Utilization, Patient Activation, and Intrafamilial Communication of Risk among Females Tested for BRCA Variants: A Mixed Methods Study
Authors: Hesse-Biber Sharlene , Seven Memnun , Shea Hannah , Heaney Madeline , Dwyer Andrew A.
Published: July 2023

This study aimed to gain a deeper understanding of genomic healthcare utilization, patient activation, and intrafamilial risk communication among racially and ethnically diverse individuals tested for BRCA variants. We employed an explanatory, sequential, mixed-methods study guided by the Theory of Planned Behavior. Participants completed an online survey, including sociodemographic, medical history, and several validated instruments. A subset of participants participated in in-depth, semi-structured interviews. A total of 242 women were included in the quantitative analyses. The majority of survey participants identified as non-Hispanic white (NHW) (n = 197, 81.4%) while 45/242 (18.5%) identified as black, Indigenous, and people of color (BIPOC). The NHW participants were more likely to communicate genetic test results with healthcare providers, family, and friends than BIPOC participants (p < 0.05). BIPOC participants had lower satisfaction with testing decisions and significantly higher ratings of personal discrimination, fatalism, resilience, uncertainty, and lower patient activation scores (p < 0.05). Participants with higher education, greater satisfaction with testing decisions, and lower resilience are more likely to communicate BRCA test results with family members through the mediating effect of patient activation. Bridging disparities to ensure that genomic healthcare benefits all people may demand theory-driven, multi-level interventions targeting the individual, interpersonal, and healthcare system levels.
Nutrient-Sensing Ghrelin Receptor in Macrophages Modulates Bisphenol A-Induced Intestinal Inflammation in Mice
Authors: Ye Xiangcang , Liu Zeyu , Han Hye Won , Noh Ji Yeon , Shen Zheng , Kim Da Mi , Wang Hongying , Guo Huiping , Ballard Johnathan , Golovko Andrei , Morpurgo Benjamin , Sun Yuxiang
Published: July 2023

Bisphenols are environmental toxins with endocrine disruptor activity, yet bisphenol A (BPA) and its analogs are still widely used in manufacturing plastic products. There is evidence showing that BPA elicits inflammation in humans and animals, but the target cell types of BPA are not well understood. In this study, we sought to determine BPA’s direct effect on macrophages and BPA immunotoxicity in mouse intestine. Ghrelin is an important nutrient-sensing hormone, acting through its receptor growth hormone secretagogue receptor (GHSR) to regulate metabolism and inflammation. We found that BPA promotes intestinal inflammation, showing increased infiltrating immune cells in colons and enhanced expression of Ghsr and pro-inflammatory cytokines and chemokines, such as Il6 and Ccl2, in colonic mucosa. Moreover, we found that both long- and short-term BPA exposure elevated pro-inflammatory monocytes and macrophages in mouse peripheral blood mononuclear cells (PBMC) and peritoneal macrophages (PM), respectively. To determine the role of GHSR in BPA-mediated inflammation, we generated Ghsr deletion mutation in murine macrophage RAW264.7 using CRISPR gene editing. In wild-type RAW264.7 cells, the BPA exposure promotes macrophage pro-inflammatory polarization and increases Ghsr and cytokine/chemokine Il6 and Ccl2 expression. Interestingly, Ghsr deletion mutants showed a marked reduction in pro-inflammatory cytokine/chemokine expression in response to BPA, suggesting that GHSR is required for the BPA-induced pro-inflammatory response. Further understanding how nutrient-sensing GHSR signaling regulates BPA intestinal immunotoxicity will help design new strategies to mitigate BPA immunotoxicity and provide policy guidance for BPA biosafety.
Anger and Aggression in Relation to Psychological Resilience and Alcohol Abuse among Health Professionals during the First Pandemic Wave
Authors: Pachi Argyro , Kavourgia Evgenia , Bratis Dionisios , Fytsilis Konstantinos , Papageorgiou Styliani Maria , Lekka Dimitra , Sikaras Christos , Tselebis Athanasios
Published: July 2023

Mental health problems, behavior changes, and addictive issues have been consistently documented among healthcare workers during the pandemic. The objective of this study was to investigate the levels of anger and aggression in relation to psychological resilience and alcohol abuse among healthcare workers during the first wave of the COVID-19 pandemic. A total of 120 physicians and 123 nurses completed an online survey of the Dimensions of Anger Reactions-5 (DAR-5), the Brief Aggression Questionnaire (BAQ), the Brief Resilience Scale (BRS), and the Alcohol Screening questionnaire CAGE which is an acronym for the focus of the questions (Cutting down, Annoyance by criticism, Guilty feeling, and Eye-openers). Demographic and professional data were also recorded. A total of 53 men and 190 women participated in the study. Almost one-third of the participants had a positive score on the DAR-5 scale and one out of ten respondents presented with current problematic alcohol use. Male participants demonstrated lower scores on the DAR-5 scale compared to females. Individuals with current problematic alcohol use displayed higher scores on the BAQ compared to those without alcohol use disorders. Regression analysis revealed that 16.4% of the variance in the BAQ scores can be attributed to scores on the DAR-5, 5.9% to the BRS scores, 2.1% to the CAGE scores, 1.7% to gender, and 1.2% to years of work experience. Mediation analysis highlighted the role of psychological resilience as a negative mediator in the DAR-5 and BAQ relationship. Professional experience and alcohol abuse emerged as positive and negative risk factors contributing to aggression and psychological resilience. The findings hold practical implications for implementing interventions to strengthen resilience in order to compensate for aggressive tendencies and discourage addictive issues.
A Molecule from Madness: An Exploration into Patients’ Illnesses through West Texas Polio
Authors: Kopel Jonathan
Published: July 2023

Neurology holds a unique perspective that embodies the art of capturing a patient’s story. Despite medical advancements, many neurological conditions leave patients permanently impaired. This sudden loss of independence can be demoralizing and, in most cases, directly changes a person’s identity. It is therefore a necessary part of a neurologist’s trade to know their patient’s history—their story. Their tales reveal intimate details of their personality changes, memory loss, sensory deprivation, and movement disorders. A true neurologist is a person that remains vulnerable through their willingness to take a history—the story of their patient—and remain curious, vulnerable, and compassionate through their journey to heal and comfort the patient. To understand the patient’s illness experience in neurology, the underlying themes of patient recovery (compassion, determination, and patience) are explored with regard to the neurological patient’s experience. These themes are then expanded to include the neurology patient’s mental perceptions of themselves, and their illness’ influences over their identity, recovery, and daily life. In addition to the patient’s experience, the neurologist’s awareness and emotional response to the patient’s illness experience can provide an opportunity to develop a strong therapeutic bond with their patient and improve patient outcomes. Given that their neurological impairment causes a loss of independence and control over their identity and self-worth, neurologists can incorporate the patient’s experience into their management and treatment, to better address their emotional and spiritual needs as they come to terms with their identity.
Use of Intersectionality Theory in Interventional Health Research in High-Income Countries: A Scoping Review
Authors: Tinner Laura , Holman Daniel , Ejegi-Memeh Stephanie , Laverty Anthony A.
Published: July 2023

Background: Intersectionality theory posits that considering a single axis of inequality is limited and that considering (dis)advantage on multiple axes simultaneously is needed. The extent to which intersectionality has been used within interventional health research has not been systematically examined. This scoping review aimed to map out the use of intersectionality. It explores the use of intersectionality when designing and implementing public health interventions, or when analysing the impact of these interventions. Methods: We undertook systematic searches of Medline and Scopus from inception through June 2021, with key search terms including “intersectionality”, “interventions” and “public health”. References were screened and those using intersectionality and primary data from high-income countries were included and relevant data synthesised. Results: After screening 2108 studies, we included 12 studies. Six studies were qualitative and focused on alcohol and substance abuse (two studies), mental health (two studies), general health promotion (one study) and housing interventions (one study). The three quantitative studies examined mental health (two studies) and smoking cessation (one study), while the three mixed-method studies examined mental health (two studies) and sexual exploitation (one study). Intersectionality was used primarily to analyse intervention effects (eight studies), but also for intervention design (three studies), and one study used it for both design and analysis. Ethnicity and gender were the most commonly included axes of inequality (11 studies), followed by socio-economic position (10 studies). Four studies included consideration of LGBTQ+ and only one considered physical disability. Intersectional frameworks were used by studies to formulate specific questions and assess differences in outcomes by intersectional markers of identity. Analytical studies also recommended intersectionality approaches to improve future treatments and to structure interventions to focus on power and structural dynamics. Conclusions: Intersectionality theory is not yet commonly used in interventional health research, in either design or analysis. Conditions such as mental health have more studies using intersectionality, while studies considering LGBTQ+ and physical disability as axes of inequality are particularly sparse. The lack of studies in our review suggests that theoretical and methodological advancements need to be made in order to increase engagement with intersectionality in interventional health.
Evaluation of Multidimensional Functional Impairment in Adult Sexual Assault Survivors, with a Focus on Its Psychological, Physical, and Social Dimensions, Based on Validated Measurements: A PRISMA Systematic Review
Authors: Schalk Thibault , Oliero Juliette , Fedele Emma , Trousset Victor , Lefèvre Thomas
Published: July 2023

Sexual violence (SV) is widely prevalent around the world: according to studies, 18 to 51% of women and 1 to 9% of men experience it at some point in their lives. Yet, experiences of SV are rarely disclosed outside the private sphere. Pathologies, acute or chronic, can be associated with SV. The study of the links between SV and health is often fragmented, viewed through the lens of a specific pathology, yet SV certainly has an impact on the different dimensions of the functioning of survivors (physical, psychological, social, and so on), whether or not there is an identified pathology at the origin of this impact. No synthesis of the knowledge on functional impairment in adult sexual assault survivors has been identified to date. Therefore, we conducted a systematic review according to the PRISMA recommendations, focusing on the assessment via validated scales or standardized measurements of the different dimensions of functional impairment in sexual assault survivors aged 15 and over, excluding abuse in childhood and polyvictimization. We searched the Medline database from its inception to October 2022, identifying 1130 articles. Two evaluators carried out their analysis, and fifty-one articles were retained. In the end, only 13 articles were included. Their quality was assessed by referring to their compliance with STROBE recommendations. Of these 13 articles, only 4 have a quality level deemed to be satisfactory, and they relate to 4 dimensions of functioning: psychological, sexual, physical (pain), and social. The main results were that survivors reported increased restrictions of activities, sexual dysfunctions such as vulvodynia or dyspareunia, decreased social satisfaction and functioning, and decreased self-esteem and quality of life compared to the general population. To date, evidence for functional impairment is very limited, preventing researchers and clinicians from gaining clear and well-established knowledge about the functioning of sexual assault survivors. Research in this area needs to evolve urgently.