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49 pages, 1972 KiB

Open AccessArticle

Electric Vehicle Traction Battery Recycling Decision-Making Considering Blockchain Technology in the Context of Capacitance Level Differential Demand

by Lijun Yang and Yi Wang

World Electr. Veh. J. 2024, 15(12), 561; https://doi.org/10.3390/wevj15120561 - 3 Dec 2024

Abstract

In recent years, the rapid growth in electric vehicle ownership has resulted in a significant number of decommissioned traction batteries that will require recycling in the future. As consumer expectations for electric vehicle range continue to rise, the turnover of traction batteries has [...] Read more.

In recent years, the rapid growth in electric vehicle ownership has resulted in a significant number of decommissioned traction batteries that will require recycling in the future. As consumer expectations for electric vehicle range continue to rise, the turnover of traction batteries has accelerated substantially. Consequently, there is an urgent need for electric vehicle manufacturers to establish an efficient, recyclable supply chain for the return of end-of-life (EOL) electric vehicle (EV) traction batteries. In this paper, we investigate the closed-loop recycling supply chain for retired power batteries in electric vehicle manufacturers, taking into account blockchain technology and the high range preferences in the electric vehicle market, which are influenced by varying demand for different levels of electric vehicle capacitance. Blockchain, as a distributed and decentralized technology, offers features such as consensus mechanisms, traceability, and security, which have been effectively applied across various fields. In this study, we construct four models involving EV battery manufacturers, EV retailers, and battery comprehensive utilization (BCU) enterprises participating in the recycling process. Through the analysis of a Stackelberg response model, we find that (1) single-channel recycling is less efficient than dual-channel recycling models, a difference driven by the diversity of recycling channels and the variability in recycling markets; (2) Recycling models incorporating blockchain technology demonstrate superior performance compared to those that do not utilize blockchain technology, particularly when the intensity of recycling competition is below 0.76; (3) Traction batteries integrated with blockchain technology exhibit higher recycling rates when the optimization index is below 0.96. Electric vehicle battery manufacturers must evaluate the benefits and costs of adopting blockchain technology; (4) With lower recycling incentive levels and EV range preferences, the single-channel recycling model yields better returns than the other three recycling models. EV manufacturers can enhance overall battery supply chain revenues by establishing varying incentive levels based on market demand for different capacitance levels. Full article

(This article belongs to the Topic Electric Vehicles Energy Management, 2nd Volume)

17 pages, 4107 KiB

Open AccessArticle

Longitudinal Monitoring of Electric Vehicle Travel Trends Using Connected Vehicle Data

by Jairaj Desai, Jijo K. Mathew, Nathaniel J. Sturdevant and Darcy M. Bullock

World Electr. Veh. J. 2024, 15(12), 560; https://doi.org/10.3390/wevj15120560 - 3 Dec 2024

Abstract

Historically, practitioners and researchers have used selected count station data and survey-based methods along with demand modeling to forecast vehicle miles traveled (VMT). While these methods may suffer from self-reporting bias or spatial and temporal constraints, the widely available connected vehicle (CV) data [...] Read more.

Historically, practitioners and researchers have used selected count station data and survey-based methods along with demand modeling to forecast vehicle miles traveled (VMT). While these methods may suffer from self-reporting bias or spatial and temporal constraints, the widely available connected vehicle (CV) data at 3 s fidelity, independent of any fixed sensor constraints, present a unique opportunity to complement traditional VMT estimation processes with real-world data in near real-time. This study developed scalable methodologies and analyzed 238 billion records representing 16 months of connected vehicle data from January 2022 through April 2023 for Indiana, classified as internal combustion engine (ICE), hybrid (HVs) or electric vehicles (EVs). Year-over-year comparisons showed a significant increase in EVMT (+156%) with minor growth in ICEVMT (+2%). A route-level analysis enables stakeholders to evaluate the impact of their charging infrastructure investments at the federal, state, and even local level, unbound by jurisdictional constraints. Mean and median EV trip lengths on the six longest interstate corridors showed a 7.1 and 11.5 mile increase, respectively, from April 2022 to April 2023. Although the current CV dataset does not randomly sample the full fleet of ICE, HVs, and EVs, the methodologies and visuals in this study present a framework for future evaluations of the return on charging infrastructure investments on a regular basis using real-world data from electric vehicles traversing U.S. roads. This study presents novel contributions in utilizing CV data to compute performance measures such as VMT and trip lengths by vehicle type—EV, HV, or ICE, unattainable using traditional data collection practices that cannot differentiate among vehicle types due to inherent limitations. We believe the analysis presented in this paper can serve as a framework to support dialogue between agencies and automotive Original Equipment Manufacturers in developing an unbiased framework for deriving anonymized performance measures for agencies to make informed data-driven infrastructure investment decisions to equitably serve ICE, HV, and EV users. Full article

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24 pages, 5241 KiB

Open AccessArticle

Late Holocene Vegetation Dynamics and Sea Level Fluctuations: A High-Resolution Record from Southeast India

by Jyoti Srivastava, Pujarini Samal and M. C. Manoj

Quaternary 2024, 7(4), 53; https://doi.org/10.3390/quat7040053 - 3 Dec 2024

Abstract

A detailed high-resolution study of climate and vegetation changes in two sedimentary profiles from the Godavari delta in India was conducted to understand extreme climate variability over the last 3000 years. These historical climate records are vital for predicting future climate changes influenced [...] Read more.

A detailed high-resolution study of climate and vegetation changes in two sedimentary profiles from the Godavari delta in India was conducted to understand extreme climate variability over the last 3000 years. These historical climate records are vital for predicting future climate changes influenced by increased human activity. Pollen records reveal several climatic periods: (1) an initial warm/humid phase (2260–1560 cal yr BP) with mangrove and tropical tree pollen and maximum pollen accumulation rate (PARmax), (2) a gradual shift to drier conditions with reduced mangrove and arboreal pollen, coinciding with to the Dark Ages Cold Period (1580–1070 cal yr BP), (3) a Medieval Warm Period (1090–580 cal yr BP) marked by a stronger summer monsoon, rejuvenation of mangroves and tree pollen, (4) a relatively cool and dry phase with abundant dry deciduous and non-arboreal pollen possibly linked to the Little Ice Age (580–80 cal yr BP), showing a weakened monsoon, and (5) recent warming since 80 cal yr BP. A semi-quantitative aridity, temperature, and moisture index based on pollen concentration variations have also been used to identify centennial-scale climatic cycles in the pollen record. Full article

(This article belongs to the Special Issue Vegetation Response to the Hydro-Climatic Changes during the Late Quaternary)

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14 pages, 2988 KiB

Open AccessArticle

Physiological Function Disturbances and Adaptive Responses in Nile Tilapia (Oreochromis niloticus) Under Different Salinity Stresses

by Ping Li, Tengzhou Li, Shaoying Xing, Ling Liu and Zhi-Hua Li

Fishes 2024, 9(12), 498; https://doi.org/10.3390/fishes9120498 - 3 Dec 2024

Abstract

The physiological functions of aquatic organisms are closely linked to changes in environmental salinity. High-salinity environments can disrupt energy metabolism, induce inflammation, and negatively impact normal growth and development. However, aquatic organisms possess self-regulatory mechanisms that can mitigate these impacts to some extent. [...] Read more.

The physiological functions of aquatic organisms are closely linked to changes in environmental salinity. High-salinity environments can disrupt energy metabolism, induce inflammation, and negatively impact normal growth and development. However, aquatic organisms possess self-regulatory mechanisms that can mitigate these impacts to some extent. This study aimed to investigate the adaptive regulatory processes in Nile tilapia (Oreochromis niloticus, Linnaeus, 1758) exposed to high-salinity environments by evaluating metabolic enzyme activities and levels of inflammatory markers. The increased levels of IL-1β and elevated ACP activity suggested that high-salinity conditions (15 and 30 ppt) induced intestinal inflammation. Concurrently, the elevated activities of SOD and GSH, along with decreased SDH activity, pointed to heightened oxidative stress in the brain and a reduced mitochondrial energy supply. Additionally, the adaptive features of intestinal energy metabolism under high-salinity conditions were evident, with adjustments in HK and PK activities mitigating the effects of suppressed PFK activity. Moreover, elevated lipase (LPS) activity in muscle tissue under salinity stress indicated that fat is mobilized to supply energy for muscle activity without affecting muscle protein. In conclusion, salinity stress triggered inflammatory and oxidative stress responses in Nile tilapia, yet the fish exhibited self-regulatory processes in energy metabolism. This study provides a theoretical basis for understanding the adaptive mechanisms of aquatic organisms in stressful environments. Full article

(This article belongs to the Special Issue Environmental Physiology of Aquatic Animals)

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24 pages, 419 KiB

Open AccessReview

Continuous Cultivation of Yarrowia lipolytica: Potential, Challenges, and Case Studies

by Svetlana V. Kamzolova

Fermentation 2024, 10(12), 619; https://doi.org/10.3390/fermentation10120619 - 3 Dec 2024

Abstract

Currently, the yeast Yarrowia lipolytica is regarded as one of the most promising producers of protein, lipids, polyols, organic acids, and other metabolites. The objective of enhancing the efficiency of the target product biosynthesis can be achieved through the improvement of the strains-producers [...] Read more.

Currently, the yeast Yarrowia lipolytica is regarded as one of the most promising producers of protein, lipids, polyols, organic acids, and other metabolites. The objective of enhancing the efficiency of the target product biosynthesis can be achieved through the improvement of the strains-producers and the optimization of the cultivation conditions. The present review assesses the potential of continuous cultivation methods (chemostat, turbidostat, pH-auxostat, changestats, etc.) in order to gain insight into the impact of strains and cultivation conditions on the productivity of the developed bioprocesses. The utilization of continuous cultivation methods enables the implementation of processes under controlled and reproducible conditions, thus stabilizing the parameters of the cultivation and the physiological state of the producer, and obtaining homogeneous samples. The review focuses on nitrogen-limited chemostat cultures, which represent the most commonly employed strategy for investigating the physiological and biochemical characteristics of the yeast Y. lipolytica and for developing the processes for the production of lipids, erythritol, citric acid, and recombinant proteins. To date, such an analysis of the literature has not been conducted in the context of the yeast Y. lipolytica. Full article

(This article belongs to the Special Issue Current Research in Yeast Fermentation: Physiology, Biotechnology, and Bioprocesses)

33 pages, 10865 KiB

Open AccessArticle

A Potential Diabetic-Friendly Food Material: Optimization, Nutritional Quality, Structural Characteristics, and Functional Properties of Oat and Purple Potato Fermented by Ganoderma lucidum Mycelium

by Yingxian Guan, Tong Zhao, Anrong Zhang, Di Zhang, Xiaoxiao Huang, Xiao Fang, Jiajun Geng and Jie Gang

Fermentation 2024, 10(12), 618; https://doi.org/10.3390/fermentation10120618 - 3 Dec 2024

Abstract

Dietary intervention is the basis for the treatment of diabetes mellitus. This study employed Ganoderma lucidum (GL) mycelium to ferment a compound medium of oat and purple potato (OPP), optimized fermentation conditions to increase the triterpene content in the resulting product (F-OPPF), and [...] Read more.

Dietary intervention is the basis for the treatment of diabetes mellitus. This study employed Ganoderma lucidum (GL) mycelium to ferment a compound medium of oat and purple potato (OPP), optimized fermentation conditions to increase the triterpene content in the resulting product (F-OPPF), and systematically investigated the impact of fermentation on the nutritional quality, structural characteristics, and functional properties of OPP. The results indicated that the triterpene content in F-OPPF significantly increased from 8.53 mg/g to 17.23 mg/g under optimal conditions (temperature: 28 °C, inoculum size: 10%, material quantity: 36 g/250 mL, and fermentation time: day 13). Fermentation resulted in enhanced nutritional quality, with increased contents of protein, soluble protein, crude fiber, ash, mineral elements, essential amino acids, polysaccharides, flavonoids, and total phenols. Mycelium not only enveloped the OPP surface but also penetrated its interior, forming a porous honeycomb-like structure. The types of reactive groups and crystals (C + V-type) were not changed after fermentation, while the crystallinity increased. F-OPPF exhibited positive changes in thermogravimetric properties, antioxidant and hypoglycemic activities, and adsorption capacity of insoluble dietary fiber. Additionally, incorporating F-OPPF into the diet markedly reduced fasting blood glucose levels and promoted weight gain in T2DM rats induced by a high-fat diet and streptozotocin. The fermented groups exhibited improvements in glyco- and lipo-metabolism, oxidative stress, and the function and pathological morphology of the pancreas, liver, and kidneys compared to the unfermented group. Collectively, these findings suggested that GL mycelium fermentation enhanced the nutritional and functional values of OPP, and F-OPPF holds potential as a raw material for developing diabetic-friendly foods. Full article

(This article belongs to the Topic Fermented Food: Health and Benefit)

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15 pages, 3238 KiB

Open AccessArticle

Effects of Trace Elements and Vitamins on the Synthesis of Steroid Hormones in Follicular Granulosa Cells of Yak

by Yanbing Lou, Tingting Yang, Yanqiu Zhu, Chenglong Xia, Hengmin Cui, Huidan Deng, Yixin Huang, Jing Fang, Zhicai Zuo and Hongrui Guo

Vet. Sci. 2024, 11(12), 619; https://doi.org/10.3390/vetsci11120619 - 3 Dec 2024

Abstract

Yak (Bos grunniens), a special breed of cattle on the Qinghai–Tibet Plateau, has low fertility due to nutritional deficiency, especially the trace elements. The steroid hormones estradiol (E2) and progesterone (P4) synthesized by yak follicular granulosa cells (BGCs) are involved in [...] Read more.

Yak (Bos grunniens), a special breed of cattle on the Qinghai–Tibet Plateau, has low fertility due to nutritional deficiency, especially the trace elements. The steroid hormones estradiol (E2) and progesterone (P4) synthesized by yak follicular granulosa cells (BGCs) are involved in the entire reproductive process. In the present study, we investigated the effects of trace elements and vitamins on yak follicular GCs, including the cellular activity, the synthesis of E2 and P4, and the expression of genes related to steroid hormone synthesis. The results showed that moderate supplementation of vitamin D3 (VD3), strontium (Sr), manganese (Mn), and selenium (Se) enhanced granulosa cell activity. Within the safe dose range, the addition of vitamin A (VA), VD3, cobalt (Co), Sr, copper (Cu), Mn, Se, and chromium (Cr) significantly increased the synthesis of E2 by GCs, while the addition of VA, vitamin C (VC), VE, zinc (Zn), Sr, Cu, and Cr enhanced the production of P4 in GCs. The changes in steroid synthesizing genes were consistent with the changes in hormone synthesis. This study provides an experimental basis for the addition of trace elements to improve the production performance of yaks. Full article

(This article belongs to the Section Nutritional and Metabolic Diseases in Veterinary Medicine)

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15 pages, 2401 KiB

Open AccessArticle

Linking Land Use Change and Hydrological Responses: The Role of Agriculture in the Decline of Urmia Lake

by Amirhossein Mirdarsoltany, Alireza B. Dariane, Mahboobeh Ghasemi, Sepehr Farhoodi, Roza Asadi and Akbar Moghaddam

Hydrology 2024, 11(12), 209; https://doi.org/10.3390/hydrology11120209 - 3 Dec 2024

Abstract

The water level and surface area of Urmia Lake, located in the northwest of Iran, has decreased dramatically, presenting significant challenges for hydrological modeling due to complex interactions between surface and groundwater. In this study, the impact of agricultural activities on streamflow within [...] Read more.

The water level and surface area of Urmia Lake, located in the northwest of Iran, has decreased dramatically, presenting significant challenges for hydrological modeling due to complex interactions between surface and groundwater. In this study, the impact of agricultural activities on streamflow within one of the largest sub-basins of Urmia Lake is assessed using the Soil and Water Assessment Tool (SWAT) for hydrological assessments. To have accurate assessments, land use change detections were considered by a novel method, which merges the Normalized Difference Vegetation Index (NDVI) with the Digital Elevation Model (DEM) to create a two-band NDVI-DEM image, effectively differentiating between agricultural and rangeland fields. Our findings reveal that agricultural development and irrigation, escalating between 1977 and 2015, resulted in increased annual evapotranspiration (ET) (ranging from 295 mm to 308 mm) and a decrease in yearly streamflow, from 317 million cubic meters to 300 million cubic meters. Overall, our study highlights the significant role that agricultural development and irrigation may play in contributing to the shrinking of Lake Urmia, underscoring the need for improved regional water management strategies to address these challenges, though further analysis across additional basins would be necessary for broader conclusions. Full article

(This article belongs to the Section Surface Waters and Groundwaters)

11 pages, 1384 KiB

Open AccessReview

A Simple Narrative Review of Progress on the Processing and Utilization of Functional Rice

by Ziying Yi, Dagang Chen, Xinqiao Zhou, Jie Guo, Ke Chen, Chanjuan Ye, Chuanguang Liu and Juan Liu

Foods 2024, 13(23), 3911; https://doi.org/10.3390/foods13233911 - 3 Dec 2024

Abstract

This paper aims to review the research progress on the processing and utilization of functional rice and explore its potential to enhance human health. The research progress in the processing and utilization of colored rice, low-protein rice, high-resistant starch rice, micronutrient-enriched rice, and [...] Read more.

This paper aims to review the research progress on the processing and utilization of functional rice and explore its potential to enhance human health. The research progress in the processing and utilization of colored rice, low-protein rice, high-resistant starch rice, micronutrient-enriched rice, and bioreactor rice was systematically analyzed through a comprehensive literature review. The impact of various processing techniques on the retention of nutritional components in functional rice was also discussed. This study found that functional rice exhibits great potential in terms of nutritional value, health effects, and market demand. However, issues such as the loss of bioactive components during processing, the maintenance of specific agronomic traits, and market acceptance still need to be addressed. The research and development of functional rice are significant for enriching people’s dietary choices and addressing global malnutrition and chronic disease problems. Future efforts should focus on further optimizing processing techniques and utilizing genetic engineering and molecular breeding technologies to enhance the nutritional value and agronomic traits of functional rice, thus meeting market demands and health objectives. Full article

(This article belongs to the Special Issue Formulation and Nutritional Aspects of Cereal-Based Functional Foods)

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15 pages, 2607 KiB

Open AccessArticle

Choroidal Response to Intravitreal Bevacizumab Injections in Treatment-Naïve Macular Neovascularization Secondary to Chronic Central Serous Chorioretinopathy

by David Rabinovitch, Shiri Shulman, Dafna Goldenberg, Liang Wang, Prashanth Iyer, Anat Loewenstein, Noah Igra, Olivia Levine, Gissel Herrera and Omer Trivizki

Biomedicines 2024, 12(12), 2760; https://doi.org/10.3390/biomedicines12122760 - 3 Dec 2024

Abstract

Background/Objectives: To evaluate the impact of intravitreal bevacizumab (IVB) therapy on anatomical and visual outcomes in patients with macular neovascularization (MNV) secondary to chronic central serous chorioretinopathy (cCSC). Methods: This retrospective observational study reviewed the medical records of treatment-naïve patients diagnosed with cCSC [...] Read more.

Background/Objectives: To evaluate the impact of intravitreal bevacizumab (IVB) therapy on anatomical and visual outcomes in patients with macular neovascularization (MNV) secondary to chronic central serous chorioretinopathy (cCSC). Methods: This retrospective observational study reviewed the medical records of treatment-naïve patients diagnosed with cCSC complicated by MNV and treated with IVB injections over a 5-year period. The presence of MNV was confirmed using optical coherence tomography angiography (OCTA). Best-corrected visual acuity (BCVA), subfoveal choroidal thickness (SFCT), and subretinal fluid (SRF) were recorded pre- and post-IVB treatment. Results: Twenty-two eyes of 22 patients (mean age, 68 ± 11 years) were included. After a mean follow-up of 21.0 ± 14.6 months, SRF significantly decreased from baseline (176.86 ± 115.62 µm) to the final follow-up (80.95 ± 87.32 µm, p = 0.003). A greater SRF reduction was associated with more injections (>7) (p = 0.047). However, no significant changes were observed in BCVA (p > 0.05) or SFCT (p > 0.05), irrespective of follow-up duration or injection frequency. Complete resolution of SRF was achieved in nine patients (40.9%), and a significantly greater reduction in SFCT was observed in complete responders compared to non-responders (p = 0.03). Conclusions: IVB therapy significantly reduced SRF in cCSC patients with secondary MNV, though it did not lead to visual improvement or significant changes in SFCT. However, greater choroidal thinning in patients with complete fluid resorption may suggest distinct underlying mechanisms or alternative sources of subretinal fluid beyond the MNV itself. Full article

(This article belongs to the Special Issue Recent Advances in Diagnosis and Therapeutic Strategies in Intraocular Inflammation)

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18 pages, 521 KiB

Open AccessArticle

Addition of Carrot Pomace to Enhance the Physical, Sensory, and Functional Properties of Beef Patties

by Jordan Richards, Amy Lammert, Jack Madden, Anna Cahn, Iksoon Kang and Samir Amin

Foods 2024, 13(23), 3910; https://doi.org/10.3390/foods13233910 - 3 Dec 2024

Abstract

The global challenge of food waste necessitates innovative solutions, such as incorporating carrot pomace, a nutrient-rich by-product of carrot juice production, into beef patties to enhance their nutritional and functional properties. This study evaluated beef patties with carrot pomace added at 0%, 1.0%, [...] Read more.

The global challenge of food waste necessitates innovative solutions, such as incorporating carrot pomace, a nutrient-rich by-product of carrot juice production, into beef patties to enhance their nutritional and functional properties. This study evaluated beef patties with carrot pomace added at 0%, 1.0%, 3.0%, and 4.2%, analyzing the proximate composition, pH, color, cooking yield, water-holding capacity (WHC), texture, and sensory attributes. Adding 3.0% and 4.2% pomace significantly reduced the moisture content by 5.5% and 3.3%, respectively, and decreased redness by 40% in the 4.2% patties. The cooking yield increased by 13.9% and 22.8%, and WHC improved by 8.5% and 15.7%, respectively, with these additions. The textural properties showed substantial reductions in hardness, cohesiveness, gumminess, and chewiness, particularly at 4.2%. The sensory evaluation indicated no significant differences in appearance, aroma, taste, or overall liking for patties with up to 3% pomace. In comparison, patties with 4.2% pomace received lower scores for overall liking and firmness. These findings suggest that incorporating up to 3% carrot pomace in beef patties enhances their functional properties and dietary fiber content without compromising the sensory quality. This offers a sustainable and practical approach to food waste valorization. Full article

(This article belongs to the Special Issue Revalorization of Plant-Based By-Products for Novel Ingredients and Functional Foods)

22 pages, 1645 KiB

Open AccessArticle

Unified Assessment of Open and Ducted Propulsors

by Rainer Schnell and Maximilian Mennicken

Aerospace 2024, 11(12), 1002; https://doi.org/10.3390/aerospace11121002 - 3 Dec 2024

Abstract

This paper reconciles the assessment of fan and propeller performance by deriving common metrics that describe their design and operational characteristics and applies them to real-world design examples. Historically, various applications with large differences in flight Mach number and thrust requirements have led [...] Read more.

This paper reconciles the assessment of fan and propeller performance by deriving common metrics that describe their design and operational characteristics and applies them to real-world design examples. Historically, various applications with large differences in flight Mach number and thrust requirements have led to different design methodologies and performance descriptors for ducted and unducted propulsors, making direct comparisons between these propulsion concepts challenging until today. One of the limitations of conventional propeller design methods is the difficulty in isolating the aerodynamic performance of blade sections from the overall design concept. The overall efficiency is largely impacted by top-level design parameters, while the aerodynamic quality is determined by the shaping and spanwise stacking of blade profiles. In contrast, turbomachinery design focuses primarily on the efficiency of the compression process and their respective efficiency metrics. This paper addresses these issues by systematically breaking down propeller efficiency into contributions commonly used in turbomachinery design. By applying consistent methodologies, we thereby enable a fair and quantitative comparison of the potential performance benefit of each concept. Furthermore, using common performance metrics simplifies the design process, making it more accessible to less experienced designers and facilitating the exploration of alternative design approaches for unducted propulsors. Full article

(This article belongs to the Section Aeronautics)

22 pages, 2415 KiB

Open AccessArticle

A Fuzzy-Bayesian Network Approach Based Assessment of CoP System in Forging Higher Education Social Responsibility

by Binglei Xie, Pengchang Li, Yuhong Wang, Feiyi Luo and Linhua Wu

Systems 2024, 12(12), 540; https://doi.org/10.3390/systems12120540 - 3 Dec 2024

Abstract

Community of practice (CoP) has been seen as a pivotal support for higher education institutions to implement their social responsibilities. Even though this model is widely admired, assessing its effectiveness and sustainability still faces many challenges: (1) the absence of an appropriate index [...] Read more.

Community of practice (CoP) has been seen as a pivotal support for higher education institutions to implement their social responsibilities. Even though this model is widely admired, assessing its effectiveness and sustainability still faces many challenges: (1) the absence of an appropriate index reveals the significance of CoP; (2) the difficulty of realizing quantitative assessment; and (3) the strategies to improve contribution sustainably by considering CoP development. To address these challenges, a comprehensive Higher Education Social Responsibility Contribution Index (HESRCI) is constructed by taking into account the CoP key influence factors. An FBN model is further developed for the purpose of assessing the various corresponding contributions quantitatively and investigating the potential interdependencies between influence factors. The effectiveness of the proposed approach is evidenced by the quantitative indication of CoP’s contributions to priorities. Research findings also highlight the significance of CoP governance, the mechanism of resource allocation, and team development, in particular, in facilitating the synergy between university development and sustainable socio-economic growth. In addition, it provides data support and a theoretical basis for higher education institutions to make more informed decisions when implementing industry-education integration strategies. Full article

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16 pages, 541 KiB

Open AccessArticle

Echinacea purpurea and Onopordum acanthium Combined Extracts Cause Immunomodulatory Effects in Lipopolysaccharide-Challenged Rats

by Maria Vlasheva, Mariana Katsarova, Ilin Kandilarov, Hristina Zlatanova-Tenisheva, Petya Gardjeva, Petko Denev, Nora Sadakova, Viktor Filipov, Ilia Kostadinov and Stela Dimitrova

Plants 2024, 13(23), 3397; https://doi.org/10.3390/plants13233397 - 3 Dec 2024

Abstract

Echinacea purpurea and Onopordum acanthium, which belong to the Asteraceae family, are widely used plants in traditional medicine. Their antioxidant, anti-inflammatory, antiviral, antibacterial, and antitumor effects are well known. However, there are no data on the effects of their combination. The aim of [...] Read more.

Echinacea purpurea and Onopordum acanthium, which belong to the Asteraceae family, are widely used plants in traditional medicine. Their antioxidant, anti-inflammatory, antiviral, antibacterial, and antitumor effects are well known. However, there are no data on the effects of their combination. The aim of the present study was to combine E. purpurea with O. acanthium to study the in vivo immunomodulatory effect of two combinations and to compare it with that of single plants. Their total polyphenolic and flavonoid content and the amounts of individual compounds characteristic of both species were determined. The influence of the obtained extracts on the serum concentrations of cytokines IFN-γ, TNF-α, and IL-10 in experimental animals with lipopolysaccharide-induced systemic inflammatory response was investigated. This research found that a combination of E. purpurea/O. acanthium in the ratio 1:1 reduced the proinflammatory cytokines TNF-α (244.82 pg/mL) and IFN-γ (1327.92 pg/mL) compared to the LPS-control, respectively, (574.17 pg/mL) and (3354.00 pg/mL), and the combination E. purpurea/O. acanthium in the ratio of 3:1 significantly increased the levels of the anti-inflammatory cytokine IL-10 (1313.95 pg/mL) compared to the LPS-control (760.09 pg/mL). In conclusion, our results could be a basis for future biomedical research on creating phytopreparations with an immunomodulatory effect. Full article

(This article belongs to the Special Issue Exploring the Immunomodulatory Potential of Plant Extracts)

24 pages, 3275 KiB

Open AccessArticle

Adjacency List Algorithm for Traffic Light Control Systems in Urban Networks

by Sergio Rojas-Blanco, Alberto Cerezo-Narváez, Manuel Otero-Mateo and Sol Sáez-Martínez

Systems 2024, 12(12), 539; https://doi.org/10.3390/systems12120539 - 3 Dec 2024

Abstract

The increasing complexity of urban road networks has driven the development of Intelligent Transportation Systems (ITS) to optimize vehicle flow. To address this challenge, this paper presents an algorithm and MATLAB function that generates an adjacency list of traffic signals to provide detailed [...] Read more.

The increasing complexity of urban road networks has driven the development of Intelligent Transportation Systems (ITS) to optimize vehicle flow. To address this challenge, this paper presents an algorithm and MATLAB function that generates an adjacency list of traffic signals to provide detailed information about the relationships between all signals within a network. This list is based on stable structural road and traffic lights data and offers a crucial global perspective for signal coordination, especially in managing multiple intersections. An adjacency list is more efficient than matrices in terms of space and computational cost, allowing for the identification of critical signals before applying advanced optimization techniques such as neural networks or hypergraphs. We successfully tested the proposed method on three networks of varying complexity extracted from VISSIM and VISUM, demonstrating its effectiveness even in networks with up to 8372 links and 547 traffic lights. This tool provides a solid foundation for improving urban traffic management and coordinating signals across intersections. Full article

(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)

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31 pages, 5958 KiB

Open AccessArticle

The Impact Mechanism of Non-Economic Policies on Social and Investor Disagreement in China: A Dual Analysis Based on Empirical Evidence and DSGE Models

by Jianing Liu, Junjun Ma and Yafei Tai

Systems 2024, 12(12), 538; https://doi.org/10.3390/systems12120538 - 3 Dec 2024

Abstract

This study investigates the integration of non-economic policies into the framework for assessing macroeconomic coherence as applied by the Chinese government, with a particular focus on green policies. We examine the impact of non-economic factors on social disagreement and investor disagreement (expectations), and [...] Read more.

This study investigates the integration of non-economic policies into the framework for assessing macroeconomic coherence as applied by the Chinese government, with a particular focus on green policies. We examine the impact of non-economic factors on social disagreement and investor disagreement (expectations), and how these influences interact with macroeconomic regulation, employing both empirical evidence and dynamic stochastic general equilibrium (DSGE) theoretical models. In the basic analysis section, we merge statistical data on social divergence with policy implementation, utilizing multiple regression and deep neural network models. Our findings provide direct evidence that non-economic policies significantly regulate social sentiment. Additionally, theoretical analyses using contagion models, grounded in real textual data on social and investor divergence, demonstrate that expectations of social sentiment can ultimately affect economic variables. In the extended analysis, we enhance the classic DSGE model to delineate the pathways through which non-economic policies impact the macroeconomy. Drawing from our analyses, we propose specific optimization measures for non-economic policies. The results indicate that targeted policy optimization can effectively manage social disagreement, thereby shaping expectations and harmonizing non-economic with economic policy initiatives. This alignment enhances the coherence of macroeconomic policy interventions. The innovative contribution of this study lies in its provision of both theoretical and empirical evidence supporting the formulation of non-economic policies for the first time, alongside specific recommendations for improving the consistency of macroeconomic policies. Full article

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17 pages, 2635 KiB

Open AccessArticle

Applied Research on Face Image Beautification Based on a Generative Adversarial Network

by Junying Gan and Jianqiang Liu

Electronics 2024, 13(23), 4780; https://doi.org/10.3390/electronics13234780 - 3 Dec 2024

Abstract

Generative adversarial networks (GANs) are widely used in image conversion tasks and have shown unique advantages in the context of face image beautification, as they can generate high-resolution face images. When used alongside potential spatial adjustments, it becomes possible to control the diversity [...] Read more.

Generative adversarial networks (GANs) are widely used in image conversion tasks and have shown unique advantages in the context of face image beautification, as they can generate high-resolution face images. When used alongside potential spatial adjustments, it becomes possible to control the diversity of the generated images and learn from small amounts of labeled data or unsupervised data, thus reducing the costs associated with data acquisition and labeling. At present, there are some problems in terms of face image beautification processes, such as poor learning of the details of a beautification style, the use of only one beautification effect, and distortions being present in the generated face image. Therefore, this study proposes the facial image beautification generative adversarial network (FIBGAN) method, in which images with different beautification style intensities are generated with respect to an input face image. First, a feature pyramid network is used to construct a pre-encoder to generate multi-layer feature vectors containing the details of the face image, such that it can learn the beautification details of the face images during the beautification style transmission. Second, the pre-encoder combines the separate style vectors generated with respect to the original image and the style image to transfer the beautification style, such that the generated images have different beautification style intensities. Finally, the weight demodulation method is used as the beautification style transmission module in the generator, and the normalization operation on the feature map is replaced with the convolution weight to eliminate any artifacts from the feature map and reduce distortions in the generated images. The experimental results show that the FIBGAN model not only transmits the beautification style to face images in a detailed manner but also generates face images with different beautification intensities while reducing the distortion of the generated face images. Therefore, it can be widely used in the beauty and fashion industry, advertising, and media production. Full article

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28 pages, 12760 KiB

Open AccessArticle

Hydro–Wind–PV–Integrated Operation Optimization and Ultra-Short-Term HESS Configuration

by Jinhua Zhang, Haizheng Wang, Chuanxi Fan, Jiahao Hu and Xinyue Zhang

Electronics 2024, 13(23), 4778; https://doi.org/10.3390/electronics13234778 - 3 Dec 2024

Abstract

In order to address the challenges associated with optimizing multi-timescale operations and allocating ultra-short-term energy storage for HWP integration, this study takes into account both the economic and reliability aspects of the HWP integration base. It proposes a model for optimizing operations and [...] Read more.

In order to address the challenges associated with optimizing multi-timescale operations and allocating ultra-short-term energy storage for HWP integration, this study takes into account both the economic and reliability aspects of the HWP integration base. It proposes a model for optimizing operations and allocating energy storage capacity, achieving optimization across long-term, short-term, and ultra-short-term operations for an MECB. Initially, operation optimization is implemented for an entire group of terraced hydropower plants by regulating them with annual regulating capabilities on a long-term timescale. The objectives are to maximize the daily average minimum output and annual power generation. Subsequently, short-term operation optimization focuses on maximizing HWP power feed-in, minimizing new energy power curtailment, and reducing residual load standard deviation while ensuring the guaranteed output optimization results for the long term. Finally, to mitigate ultra-short-term fluctuations in new energy, a HESS with specified capacity and power is configured with the goal of minimizing comprehensive costs. Additionally, to address the challenge of smoothing negative fluctuations, which is hindered by charging and discharging efficiency limitations, a variable baseline is introduced, deviating from the conventional 0 MW baseline. A simulation study based on data from the hydro–wind–PV hybrid project in the Beipanjiang River Basin, China, demonstrates the following: (1) after long-term system optimization, the total power generation capacity of the system increases by 9.68%, while the peak-to-valley difference in output is significantly reduced; (2) short-term system optimization significantly reduces both the average variance in residual loads and the amount of power curtailed over five representative days; (3) the system incorporates 398.62 MWh of lithium-ion battery storage with a power of 412.47 MW and 51.09 MWh of supercapacitor storage with a power of 223.32 MW, which, together, completely smooth out the ultra-short-term fluctuations in new energy output. Full article

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14 pages, 4676 KiB

Open AccessArticle

Wearable System for Continuous Estimation of Transepidermal Water Loss

by Natsumi Matsui, Ayumi Ohnishi, Ayaka Uyama, Tetsuzo Sugino, Tsutomu Terada and Masahiko Tsukamoto

Electronics 2024, 13(23), 4779; https://doi.org/10.3390/electronics13234779 - 3 Dec 2024

Abstract

To maintain skin moisture, we need to maintain good stratum corneum barrier function, which prevents moisture evaporation from the inside of the skin. Transepidermal water loss (TEWL), the amount of water that evaporates from the skin, indicates the state of barrier function. The [...] Read more.

To maintain skin moisture, we need to maintain good stratum corneum barrier function, which prevents moisture evaporation from the inside of the skin. Transepidermal water loss (TEWL), the amount of water that evaporates from the skin, indicates the state of barrier function. The barrier function of facial skin is easily damaged in daily life, and the condition of the skin becomes worse without us noticing. We should constantly monitor TEWL to prevent worsening skin conditions. In this paper, we propose a wearable device that continuously measures TEWL. We estimate TEWL using machine learning from temperature and humidity values of water evaporation from the skin and parameters that affect TEWL, such as skin surface temperature and galvanic skin response. We experimented with the prototype device in a controlled environment. We confirmed that the prototype device could estimate TEWL accurately enough to judge the skin’s condition in stationary and conversational situations. Then, we experimented to verify the environmental conditions for estimating TEWL using the prototype device. The prototype device could estimate TEWL with sufficient precision in an office without airflow. However, we could not estimate TEWL in the office with airflow and outdoor. Full article

(This article belongs to the Special Issue Machine Learning for Biomedical Applications)

20 pages, 2859 KiB

Open AccessArticle

A Mobility Handover Decision Method Based on Multi-Topology

by Chi Zhang, Haojiang Deng and Rui Han

Electronics 2024, 13(23), 4777; https://doi.org/10.3390/electronics13234777 - 3 Dec 2024

Abstract

With the emergence of new applications in mobile networks, users demand higher network stability and lower data transmission delays. When the network address of a mobile user changes, the data transmission path in the wired network may need to be switched to maintain [...] Read more.

With the emergence of new applications in mobile networks, users demand higher network stability and lower data transmission delays. When the network address of a mobile user changes, the data transmission path in the wired network may need to be switched to maintain service continuity. Traditional mobility support methods typically rely on a single switching path for all mobile data flows. However, if this path cannot meet the requirements of all the flows, it may lead to network congestion or a decline in user experience. To overcome this limitation, this paper proposes a mobility handover decision method based on multi-topology. It enables the dynamic allocation of mobile data flows across different switching paths within multiple logical topologies. The method models a multi-topology selection problem aimed at minimizing average packet transmission delay and packet loss rate, while considering network conditions and the Quality of Service (QoS) requirements for each flow. By solving the dual problem of the original optimization, a near-optimal solution is achieved. The proposed scheme and algorithm were implemented and tested using the Mininet network simulator. Results show that the proposed approach achieves low average packet transmission delay, low average packet loss rate, and high throughput, compared to traditional single-path switching methods and existing multipath routing methods. Full article

(This article belongs to the Special Issue Advances in Mobile Networked Systems)

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15 pages, 23802 KiB

Open AccessArticle

Vision-Based Prediction of Flashover Using Transformers and Convolutional Long Short-Term Memory Model

by M. Hamed Mozaffari, Yuchuan Li, Niloofar Hooshyaripour and Yoon Ko

Electronics 2024, 13(23), 4776; https://doi.org/10.3390/electronics13234776 - 3 Dec 2024

Abstract

The prediction of fire growth is crucial for effective firefighting and rescue operations. Recent advancements in vision-based techniques using RGB vision and infrared (IR) thermal imaging data, coupled with artificial intelligence and deep learning techniques, have shown promising solutions to be applied in [...] Read more.

The prediction of fire growth is crucial for effective firefighting and rescue operations. Recent advancements in vision-based techniques using RGB vision and infrared (IR) thermal imaging data, coupled with artificial intelligence and deep learning techniques, have shown promising solutions to be applied in the detection of fire and the prediction of its behavior. This study introduces the use of Convolutional Long Short-term Memory (ConvLSTM) network models for predicting room fire growth by analyzing spatiotemporal IR thermal imaging data acquired from full-scale room fire tests. Our findings revealed that SwinLSTM, an enhanced version of ConvLSTM combined with transformers (a deep learning architecture based on a new mechanism called multi-head attention) for computer vision purposes, can be used for the prediction of room fire flashover occurrence. Notably, transformer-based ConvLSTM deep learning models, such as SwinLSTM, demonstrate superior prediction capability, which suggests a new vision-based smart solution for future fire growth prediction tasks. The main focus of this work is to perform a feasibility study on the use of a pure vision-based deep learning model for analysis of future video data to anticipate behavior of fire growth in room fire incidents. Full article

(This article belongs to the Special Issue Deep Learning for Computer Vision Application)

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20 pages, 2076 KiB

Open AccessArticle

The Use of Machine Learning Models with Optuna in Disease Prediction

by Li-Hsing Lai, Ying-Lei Lin, Yu-Hui Liu, Jung-Pin Lai, Wen-Chieh Yang, Hung-Pin Hou and Ping-Feng Pai

Electronics 2024, 13(23), 4775; https://doi.org/10.3390/electronics13234775 - 3 Dec 2024

Abstract

Effectively and equitably allocating medical resources, particularly for minority groups, is a critical issue that warrants further investigation in rural hospitals. Machine learning techniques have gained significant traction and demonstrated strong performance across various fields in recent years. The determination of hyperparameters significantly [...] Read more.

Effectively and equitably allocating medical resources, particularly for minority groups, is a critical issue that warrants further investigation in rural hospitals. Machine learning techniques have gained significant traction and demonstrated strong performance across various fields in recent years. The determination of hyperparameters significantly influences the performance of machine learning models. Thus, this study employs Optuna, a framework specifically designed for optimizing the hyperparameters of machine learning models. Building on prior research, machine learning models with Optuna (MLOPTA) are introduced to forecast diseases of indigenous patients. The numerical results reveal that the designed MLOPTA system can accurately capture the occurrences of specified diseases. Therefore, the MLOPTA system offers a promising approach for disease forecasting. The disease forecasting results can serve as crucial references for allocating hospital resources. Full article

(This article belongs to the Special Issue Machine Learning in Electronic and Biomedical Engineering, 3rd Edition)

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16 pages, 1489 KiB

Open AccessArticle

Theoretical Study of the Dissociative Recombination and Vibrational (De-)Excitation of HCNH and Its Isomers by Electron Impact⁺

by Mehdi Adrien Ayouz and Arnaud Buch

Atoms 2024, 12(12), 64; https://doi.org/10.3390/atoms12120064 - 3 Dec 2024

Abstract

Protonated hydrogen cyanide, HCNH⁺, is one of the most important molecules of interest in the astrophysical and astrochemical fields. This molecule not only plays the role of a reaction intermediary in various types of interstellar reactions but was also identified in [...] Read more.

Protonated hydrogen cyanide, HCNH⁺, is one of the most important molecules of interest in the astrophysical and astrochemical fields. This molecule not only plays the role of a reaction intermediary in various types of interstellar reactions but was also identified in Titan’s upper atmosphere. The cross sections for the dissociative recombination (DR) and vibrational (de-)excitation (VE and VDE) of HCNH⁺ and its

{CNH}_{2}^{+}

isomer are computed using a theoretical approach based on a combination of the normal mode approximation for the vibrational states of the target ions and the UK R-matrix code to evaluate electron-ion scattering matrices for fixed geometries of ions. The theoretical convoluted DR cross section for HCNH⁺ agrees well with the experimental data and a previous study. It was also found that the DR of the

{CNH}_{2}^{+}

isomer is important, which suggests that this ion might be present in DR experiments of HCNH⁺. Moreover, the ab initio calculations performed on the H₂CN⁺ isomer predict that this ion is a transition state. This result was confirmed by the study of the reaction path of the HCNH⁺ isomerization that was carried out by evaluating the intrinsic reaction coordinate (IRC). Finally, thermally averaged rate coefficients derived from the cross sections are provided for temperatures in the 10–10,000 K range. A comprehensive set of calculations is performed to assess the uncertainty of the obtained data. These results should help in modeling non-LTE spectra of HCNH⁺, taking into account the role of its most stable isomer, in various astrophysical environments. Full article

(This article belongs to the Special Issue Interaction of Electrons with Atoms and Molecules in Ionized Environments)

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12 pages, 1176 KiB

Open AccessArticle

Clinical Utility of Broad-Range PCR Testing and Impact on Outcomes in Adults with Suspected Infection

by Kaitlyn Weinert-Stein, Mackenzie Cater, Sree Sarah Cherian, Reem Azem, Ana E. Khazan, Ankita P. Desai, LeAnne Tripp, Peter Paul Lim, Lisa M. Stempak and Leila S. Hojat

Antibiotics 2024, 13(12), 1166; https://doi.org/10.3390/antibiotics13121166 - 3 Dec 2024

Abstract

Background: The development of broad-range polymerase chain reaction (BR-PCR) and next-generation sequencing techniques has significant implications for antimicrobial stewardship by increasing clinicians’ ability to provide a tailored antimicrobial regimen. We sought to explore the clinical utility of BR-PCR testing and its impact [...] Read more.

Background: The development of broad-range polymerase chain reaction (BR-PCR) and next-generation sequencing techniques has significant implications for antimicrobial stewardship by increasing clinicians’ ability to provide a tailored antimicrobial regimen. We sought to explore the clinical utility of BR-PCR testing and its impact on antimicrobial treatment among an adult cohort in a large hospital system. Methods: We retrospectively evaluated samples that underwent BR-PCR testing between 2017 and 2021 and summarized their clinical characteristics and impact on antimicrobial therapy. We identified BR-PCR testing as having clinical utility if the results led to adjustment of antimicrobial choice or duration or to confirmation of the initial empiric regimen, while no clinical utility was assigned to results that were negative or clinically insignificant, unavailable due to loss to follow-up, or lacking clinical indication (treatment completed before the test results returned or conventional cultures revealed the causative pathogen). Results: Among 359 specimens, BR-PCR was positive for 107 (30%). Clinical utility was identified for 106 (29.5%) specimens, including 45 with negative BR-PCR results. The rates of clinical utility varied based on the type of sample tested, with the highest clinical utility associated with cranial samples (60%), followed by body fluid (56%) and endovascular (54%) samples, and the lowest with CSF (15%) and bone and joint (19%) samples. We also identified many BR-PCR tests that were not clinically indicated (23.4%). Conclusions: This study highlights the utility of BR-PCR testing to support antimicrobial stewardship initiatives. Further studies are needed to identify clinical scenarios in which it is appropriate to order BR-PCR testing and for a careful interpretation of negative BR-PCR results. Full article

(This article belongs to the Section Antibiotics Use and Antimicrobial Stewardship)

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13 pages, 2989 KiB

Open AccessArticle

Self-Assembled Lubricin (PRG-4)-Based Biomimetic Surface-Enhanced Raman Scattering Sensor for Direct Droplet Detection of Melamine in Undiluted Milk

by Mingyu Han, Mya Myintzu. Hlaing, Paul R. Stoddart and George W. Greene

Biosensors 2024, 14(12), 591; https://doi.org/10.3390/bios14120591 - 3 Dec 2024

Abstract

Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding [...] Read more.

Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding of noise molecules in clinical samples, which complicates its use in complex samples such as bodily fluids, environmental water, or food matrices. To address this, we developed a novel non-fouling biomimetic SERS sensor by self-assembling an anti-adhesive, anti-fouling, and size-selective Lubricin (LUB) coating on gold nanoparticle (AuNP) functionalized glass slide surfaces via a simple drop-casting method. Compared to a conventional AuNPs-SERS substrate, the biomimetic SERS meets the requirements of simple preparation and enables direct droplet detection without any sample pre-treatment. Atomic force microscopy was used to confirm the self-assembled Lubricin coating on the AuNP surface, acting as an anti-fouling and size-selective protection layer. A series of Raman spectra were collected using melamine as the target analyte, which was spiked into 150 mM NaCl solution or undiluted milk. It was demonstrated that the LUB coating effectively prevents the detrimental fouling generated by the proteins and fats in milk, ensuring the clear detection of melamine. Our sensor showed high selectivity and could detect melamine in milk at concentrations as low as 1 ppm. Given that the EU/US legal limit for melamine in food is 2.5 ppm, this sensor offers a promising, cost-effective solution for routine screening and has potential applications for detecting food adulteration in the food safety, environmental monitoring, aquaculture, and biomedical fields. Full article

(This article belongs to the Special Issue SERS-Based Biosensors: Design and Biomedical Applications)

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