MDPI - Publisher of Open Access Journals

19 pages, 2300 KiB

Open AccessArticle

Chemical Composition, Nutritional, and Biological Properties of Extracts Obtained with Different Techniques from Aronia melanocarpa Berries

by Alessandra Piras, Silvia Porcedda, Antonella Smeriglio, Domenico Trombetta, Mariella Nieddu, Franca Piras, Valeria Sogos and Antonella Rosa

Molecules 2024, 29(11), 2577; https://doi.org/10.3390/molecules29112577 (registering DOI) - 30 May 2024

Abstract

This study investigates the chemical composition, nutritional, and biological properties of extracts obtained from A. melanocarpa berries using different extraction methods and solvents. Hydrodistillation and supercritical fluid extraction with CO₂ allowed us to isolate fruit essential oil (HD_EX) and fixed [...] Read more.

This study investigates the chemical composition, nutritional, and biological properties of extracts obtained from A. melanocarpa berries using different extraction methods and solvents. Hydrodistillation and supercritical fluid extraction with CO₂ allowed us to isolate fruit essential oil (HD_EX) and fixed oil (SFE_EX), respectively. A phenol-enriched extract was obtained using a mild ultrasound-assisted maceration with methanol (UAM_M). The HD_EX most abundant component, using gas chromatography-mass spectrometry (GC/MS), was italicene epoxide (17.2%), followed by hexadecanoic acid (12.4%), khusinol (10.5%), limonene (9.7%), dodecanoic acid (9.7%), and (E)-anethole (6.1%). Linoleic (348.9 mg/g of extract, 70.5%), oleic (88.9 mg/g, 17.9%), and palmitic (40.8 mg/g, 8.2%) acids, followed by α-linolenic and stearic acids, were the main fatty acids in SFE_EX determined using high-performance liquid chromatography coupled with a photodiode array detector and an evaporative light scattering detector (HPLC-DAD/ELSD). HPLC-DAD analyses of SFE_EX identified β-carotene as the main carotenoid (1.7 mg/g), while HPLC with fluorescence detection (FLU) evidenced α-tocopherol (1.2 mg/g) as the most abundant tocopherol isoform in SFE_EX. Liquid chromatography-electrospray ionization-MS (LC-ESI-MS) analysis of UAM_M showed the presence of quercetin-sulfate (15.6%, major component), malvidin 3-O-(6-O-p-coumaroyl) glucoside-4-vinylphenol adduct (pigment B) (9.3%), di-caffeoyl coumaroyl spermidine (7.6%), methyl-epigallocatechin (5.68%), and phloretin (4.1%), while flavonoids (70.5%) and phenolic acids (23.9%) emerged as the most abundant polyphenol classes. UAM_M exerted a complete inhibition of the cholesterol oxidative degradation at 140 °C from 75 μg of extract, showing 50% protection at 30.6 μg (IA₅₀). Furthermore, UAM_M significantly reduced viability (31–48%) in A375 melanoma cells in the range of 500–2000 μg/mL after 96 h of incubation (MTT assay), with a low toxic effect in normal HaCaT keratinocytes. The results of this research extend the knowledge of the nutritional and biological properties of A. melanocarpa berries, providing useful information on specific extracts for potential food, cosmetic, and pharmaceutical applications. Full article

(This article belongs to the Special Issue Phytochemistry and Biological Activity Perspectives of Medicinal Plants)

► Show Figures

Graphical abstract

16 pages, 902 KiB

Open AccessArticle

Insights into How to Enhance Container Terminal Operations with Digital Twins

by Marvin Kastner, Nicolò Saporiti, Ann-Kathrin Lange and Tommaso Rossi

Computers 2024, 13(6), 138; https://doi.org/10.3390/computers13060138 (registering DOI) - 30 May 2024

Abstract

The years 2021 and 2022 showed that maritime logistics are prone to interruptions. Ports especially turned out to be bottlenecks with long queues of waiting vessels. This leads to the question of whether this can be (at least partly) mitigated by means of [...] Read more.

The years 2021 and 2022 showed that maritime logistics are prone to interruptions. Ports especially turned out to be bottlenecks with long queues of waiting vessels. This leads to the question of whether this can be (at least partly) mitigated by means of better and more flexible terminal operations. Digital Twins have been in use in production and logistics to increase flexibility in operations and to support operational decision-making based on real-time information. However, the true potential of Digital Twins to enhance terminal operations still needs to be further investigated. A Delphi study is conducted to explore the operational pain points, the best practices to counter them, and how these best practices can be supported by Digital Twins. A questionnaire with 16 propositions is developed, and a panel of 17 experts is asked for their degrees of confirmation for each. The results indicate that today’s terminal operations are far from ideal, and leave space for optimisation. The experts see great potential in analysing the past working shift data to identify the reasons for poor terminal performance. Moreover, they agree on the proposed best practices and support the use of emulation for detailed ad hoc simulation studies to improve operational decision-making. Full article

(This article belongs to the Special Issue IT in Production and Logistics)

► Show Figures

Figure 1

19 pages, 1496 KiB

Open AccessArticle

Explorative Characterization of GI Complaints, General Physical and Mental Wellbeing, and Gut Microbiota in Trained Recreative and Competitive Athletes with or without Self-Reported Gastrointestinal Symptoms

by Floris C. Wardenaar, Alex E. Mohr, Carmen P. Ortega-Santos, Jean Nyakayiru, Christine Kersch-Counet, Yat Chan, Anna-Marie Clear, Jonathan Kurka, Kinta D. Schott and Ryan G. N. Seltzer

Nutrients 2024, 16(11), 1712; https://doi.org/10.3390/nu16111712 (registering DOI) - 30 May 2024

Abstract

The current state of the literature lacks a clear characterization of gastrointestinal (GI) symptoms, gut microbiota composition, and general physical and mental wellbeing in well-trained athletes. Therefore, this study aimed to characterize differences in self-reported symptoms, gut microbiota composition, and wellbeing (i.e., sleep [...] Read more.

The current state of the literature lacks a clear characterization of gastrointestinal (GI) symptoms, gut microbiota composition, and general physical and mental wellbeing in well-trained athletes. Therefore, this study aimed to characterize differences in self-reported symptoms, gut microbiota composition, and wellbeing (i.e., sleep quality, mood, and physical (PHQ) and mental wellbeing) between athletes with and without GI symptoms. In addition, we assessed the potential impact of a 3-week multi-ingredient fermented whey supplement in the GI complaints group, without a control group, on the gut microbiota and self-reported GI symptoms and wellbeing. A total of 50 athletes (24.7 ± 4.5 years) with GI issues (GI group at baseline, GI-B) and 21 athletes (25.4 ± 5.3 years) without GI issues (non-GI group, NGI) were included. At baseline, there was a significant difference in the total gastrointestinal symptom rating scale (GSRS) score (24.1 ± 8.48 vs. 30.3 ± 8.82, p = 0.008) and a trend difference in PHQ (33.9 ± 10.7 vs. 30.3 ± 8.82, p = 0.081), but no differences (p > 0.05) were seen for other outcomes, including gut microbiota metrics, between groups. After 3-week supplementation, the GI group (GI-S) showed increased Bifidobacterium relative abundance (p < 0.05), reported a lower number of severe GI complaints (from 72% to 54%, p < 0.001), and PHQ declined (p = 0.010). In conclusion, well-trained athletes with GI complaints reported more severe GI symptoms than an athletic reference group, without showing clear differences in wellbeing or microbiota composition. Future controlled research should further investigate the impact of such multi-ingredient supplements on GI complaints and the associated changes in gut health-related markers. Full article

(This article belongs to the Section Nutritional Immunology)

15 pages, 559 KiB

Open AccessReview

Hepatocellular Carcinoma: The Evolving Role of Systemic Therapies as a Bridging Treatment to Liver Transplantation

by Yacob Saleh, Taher Abu Hejleh, Maen Abdelrahim, Ali Shamseddine, Laudy Chehade, Tala Alawabdeh, Issa Mohamad, Mohammad Sammour and Rim Turfa

Cancers 2024, 16(11), 2081; https://doi.org/10.3390/cancers16112081 (registering DOI) - 30 May 2024

Abstract

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curative for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists and/or to downstage patients who are beyond [...] Read more.

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curative for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists and/or to downstage patients who are beyond the Milan criteria are widely utilized. We conducted a literature-based review to evaluate the role of systemic therapies as a bridging treatment to liver transplantation (LT) in HCC patients. Tyrosine kinase inhibitors (TKIs) can be used as a systemic bridging therapy to LT in patients with contraindications for locoregional liver-directed therapies. Immune checkpoint inhibitor (ICI) treatment can be utilized either as a monotherapy or as a combination therapy with bevacizumab or TKIs prior to LT. Acute rejection after liver transplantation is a concern in the context of ICI treatment. Thus, a safe ICI washout period before LT and cautious post-LT immunosuppression strategies are required to reduce post-LT rejections and to optimize clinical outcomes. Nevertheless, prospective clinical trials are needed to establish definitive conclusions about the utility of systemic therapy as a bridging modality prior to LT in HCC patients. Full article

(This article belongs to the Section Transplant Oncology)

14 pages, 1549 KiB

Open AccessArticle

Remediation of Pb-, Zn-, Cu-, and Cd-Contaminated Soil in a Lead–Zinc Mining Area by Co-Cropping Ilex cornuta and Epipremnum aureum with Illite Application

by Qi Li, Yanxin Tang, Dubin Dong, Xili Wang, Xuqiao Wu, Saima Gul, Yaqian Li, Xiaocui Xie, Dan Liu and Weijie Xu

Agriculture 2024, 14(6), 867; https://doi.org/10.3390/agriculture14060867 (registering DOI) - 30 May 2024

Abstract

Phytoremediation is considered an effective strategy for remediation of heavy-metal-contaminated soil in mining areas. However, single-species plants cannot reach the highest potential for uptake of heavy metals due to inhibition of their growth by high concentrations of heavy metals in the soil. Therefore, [...] Read more.

Phytoremediation is considered an effective strategy for remediation of heavy-metal-contaminated soil in mining areas. However, single-species plants cannot reach the highest potential for uptake of heavy metals due to inhibition of their growth by high concentrations of heavy metals in the soil. Therefore, this study has explored the effects of illite application and two plant species’ co-cropping on soil quality, plant growth, and heavy metal transformation in a soil–plant system. The results reveal that the addition of 1% (mass fraction) of illite significantly enhances soil pH. The co-cropping of Ilex cornuta and Epipremnum aureum is beneficial for improving the organic matter content of the soil. The contents of EDTA-extractable Pb, Zn, and Cu were significantly reduced by 29.8–32.5%, 1.85–5.72%, and 30.0–32.9%, respectively, compared to the control. The co-cropping of Ilex cornuta and Epipremnum aureum promoted enrichment effects of Epipremnum aureum on Pb and Ilex cornuta on Cd (p < 0.05). The co-cropping pattern lowered the biomass of Ilex cornuta and Epipremnum aureum; however, co-cropping of Ilex cornuta and Epipremnum aureum promoted the elimination of Pb, Zn, Cu, and Cd from the soil at 13.0–75.8%, 11.1–38.2%, 8.39–88.4%, and 27.8–72.5%, respectively. It is concluded that illite application combined with co-cropping of Ilex cornuta and Epipremnum aureum is highly effective for the elimination of Pb, Zn, Cu, and Cd from contaminated soil. This study provides a theoretical basis and pathway for the restoration of heavy-metal-contaminated soil in mining with the application of bentonite combined with phytoremediation. Full article

(This article belongs to the Section Agricultural Soils)

16 pages, 5441 KiB

Open AccessTechnical Note

Unsupervised Domain Adaptation with Contrastive Learning-Based Discriminative Feature Augmentation for RS Image Classification

by Ren Xu, Alim Samat, Enzhao Zhu, Erzhu Li and Wei Li

Remote Sens. 2024, 16(11), 1974; https://doi.org/10.3390/rs16111974 (registering DOI) - 30 May 2024

Abstract

High- and very high-resolution (HR, VHR) remote sensing (RS) images can provide comprehensive and intricate spatial information for land cover classification, which is particularly crucial when analyzing complex built-up environments. However, the application of HR and VHR images to large-scale and detailed land [...] Read more.

High- and very high-resolution (HR, VHR) remote sensing (RS) images can provide comprehensive and intricate spatial information for land cover classification, which is particularly crucial when analyzing complex built-up environments. However, the application of HR and VHR images to large-scale and detailed land cover mapping is always constrained by the intricacy of land cover classification models, the exorbitant cost of collecting training samples, and geographical changes or acquisition conditions. To overcome this limitation, we propose an unsupervised domain adaptation (UDA) with contrastive learning-based discriminative feature augmentation (CLDFA) for RS image classification. In detail, our method first utilizes contrastive learning (CL) through a memory bank in order to memorize sample features and improve model performance, where the approach employs an end-to-end Siamese network and incorporates dynamic pseudo-label assignment and class-balancing strategies for adaptive domain joint learning. By transferring classification models trained on a source domain (SD) to an unlabeled target domain (TD), our proposed UDA method enables large-scale land cover mapping. We conducted experiments using a massive five billion-pixels dataset as the SD and tested the HR and VHR RS images of five typical Chinese cities as the TD and applied the method on the completely unlabeled world view 3 (WV3) image of Urumqi city. The experimental results demonstrate that our method excels in large-scale HR and VHR RS image classification tasks, highlighting the advantages of semantic segmentation based on end-to-end deep convolutional neural networks (DCNNs). Full article

(This article belongs to the Special Issue Advances in Deep Fusion of Multi-Source Remote Sensing Images)

15 pages, 477 KiB

Open AccessArticle

Green Human Resource Management and Employee Retention in the Hotel Industry of UAE: The Mediating Effect of Green Innovation

by Fida Hassanein, Amira Daouk, Diala Yassine, Najib Bou Zakhem, Ranim Elsayed and Ahmad Saleh

Sustainability 2024, 16(11), 4668; https://doi.org/10.3390/su16114668 (registering DOI) - 30 May 2024

Abstract

The concept of Green Human Resource Management (GHRM) is regarded as a major turning point in managing human capital among firms. Sustainable practices, ecofriendly initiatives, and adequate management of employees (i.e., recruitment, training, performance, rewards, and involvement) are fundamental aspects of GHRM, which [...] Read more.

The concept of Green Human Resource Management (GHRM) is regarded as a major turning point in managing human capital among firms. Sustainable practices, ecofriendly initiatives, and adequate management of employees (i.e., recruitment, training, performance, rewards, and involvement) are fundamental aspects of GHRM, which enable improvements in the performance of firms and enhanced competitiveness among their rivals. In this regard, the current study takes a quantitative approach towards analyzing GHRM practices and their effects on employee retention among hotels in the UAE. Furthermore, the indirect effect of green innovation is analyzed as a potential mediating variable that can better explain the GHRM–employee retention relationship. A total of 207 employees from five 5-star hotels were selected as participants to provide information regarding the factors under examination in this research. The collected data were analyzed using Smart-PLS v.3 and a partial least squares–structural equation modeling technique, which is a fitting technique for causal models. The perspective of employees on the outcome of GHRM initiatives and their willingness to remain in their firms can greatly contribute to the current understanding of GHRM and its effectiveness on employee retention in the context of the hotel industry of the UAE, and thus, aid practitioners and scholars alike. Full article

(This article belongs to the Special Issue Sustaining Work and Careers for Human Well-Being in the New Normal)

17 pages, 1231 KiB

Open AccessArticle

Study on Obstacle Detection Method Based on Point Cloud Registration

by Hongliang Wang, Jianing Wang, Yixin Wang, Dawei Pi, Yijie Chen and Jingjing Fan

World Electr. Veh. J. 2024, 15(6), 241; https://doi.org/10.3390/wevj15060241 (registering DOI) - 30 May 2024

Abstract

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high [...] Read more.

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection. Full article

55 pages, 6195 KiB

Open AccessArticle

Improved Snake Optimizer Using Sobol Sequential Nonlinear Factors and Different Learning Strategies and Its Applications

by Wenda Zheng, Yibo Ai and Weidong Zhang

Mathematics 2024, 12(11), 1708; https://doi.org/10.3390/math12111708 (registering DOI) - 30 May 2024

Abstract

The Snake Optimizer (SO) is an advanced metaheuristic algorithm for solving complicated real-world optimization problems. However, despite its advantages, the SO faces certain challenges, such as susceptibility to local optima and suboptimal convergence performance in cases involving discretized, high-dimensional, and multi-constraint problems. To [...] Read more.

The Snake Optimizer (SO) is an advanced metaheuristic algorithm for solving complicated real-world optimization problems. However, despite its advantages, the SO faces certain challenges, such as susceptibility to local optima and suboptimal convergence performance in cases involving discretized, high-dimensional, and multi-constraint problems. To address these problems, this paper presents an improved version of the SO, known as the Snake Optimizer using Sobol sequential nonlinear factors and different learning strategies (SNDSO). Firstly, using Sobol sequences to generate better distributed initial populations helps to locate the global optimum solution faster. Secondly, the use of nonlinear factors based on the inverse tangent function to control the exploration and exploitation phases effectively improves the exploitation capability of the algorithm. Finally, introducing learning strategies improves the population diversity and reduces the probability of the algorithm falling into the local optimum trap. The effectiveness of the proposed SNDSO in solving discretized, high-dimensional, and multi-constraint problems is validated through a series of experiments. The performance of the SNDSO in tackling high-dimensional numerical optimization problems is first confirmed by using the Congress on Evolutionary Computation (CEC) 2015 and CEC2017 test sets. Then, twelve feature selection problems are used to evaluate the effectiveness of the SNDSO in discretized scenarios. Finally, five real-world technical multi-constraint optimization problems are employed to evaluate the performance of the SNDSO in high-dimensional and multi-constraint domains. The experiments show that the SNDSO effectively overcomes the challenges of discretization, high dimensionality, and multi-constraint problems and outperforms superior algorithms. Full article

(This article belongs to the Special Issue Intelligence Optimization Algorithms and Applications)

► Show Figures

Graphical abstract

25 pages, 26353 KiB

Open AccessArticle

Identifying Heterogeneity in SAR Data with New Test Statistics

by Alejandro C. Frery, Janeth Alpala and Abraão D. C. Nascimento

Remote Sens. 2024, 16(11), 1973; https://doi.org/10.3390/rs16111973 (registering DOI) - 30 May 2024

Abstract

This paper presents a statistical approach to identify the underlying roughness characteristics in synthetic aperture radar (SAR) intensity data. The physical modeling of this kind of data allows the use of the Gamma distribution in the presence of fully developed speckle, i.e., when [...] Read more.

This paper presents a statistical approach to identify the underlying roughness characteristics in synthetic aperture radar (SAR) intensity data. The physical modeling of this kind of data allows the use of the Gamma distribution in the presence of fully developed speckle, i.e., when there are infinitely many independent backscatterers per resolution cell, and none dominates the return. Such areas are often called “homogeneous” or “textureless” regions. The

G_{I}^{0}

distribution is also a widely accepted law for heterogeneous and extremely heterogeneous regions, i.e., areas where the fully developed speckle hypotheses do not hold. We propose three test statistics to distinguish between homogeneous and inhomogeneous regions, i.e., between gamma and

G_{I}^{0}

distributed data, both with a known number of looks. The first test statistic uses a bootstrapped non-parametric estimator of Shannon entropy, providing a robust assessment in uncertain distributional assumptions. The second test uses the classical coefficient of variation (CV). The third test uses an alternative form of estimating the CV based on the ratio of the mean absolute deviation from the median to the median. We apply our test statistic to create maps of p-values for the homogeneity hypothesis. Finally, we show that our proposal, the entropy-based test, outperforms existing methods, such as the classical CV and its alternative variant, in identifying heterogeneity when applied to both simulated and actual data. Full article

(This article belongs to the Special Issue SAR Processing in Urban Planning)

18 pages, 4290 KiB

Open AccessArticle

A Transient Analysis of Latent Thermal Energy Storage Using Phase Change Materials in a Refrigerated Truck

by Luca Cirillo, Adriana Greco and Claudia Masselli

Energies 2024, 17(11), 2665; https://doi.org/10.3390/en17112665 (registering DOI) - 30 May 2024

Abstract

The preservation of perishable food items within the cold chain is a critical aspect of modern food logistics. Traditional refrigeration systems consume large amounts of energy, without an optimal temperature distribution, leading to potential food spoilage and economic losses. In recent years, the [...] Read more.

The preservation of perishable food items within the cold chain is a critical aspect of modern food logistics. Traditional refrigeration systems consume large amounts of energy, without an optimal temperature distribution, leading to potential food spoilage and economic losses. In recent years, the integration of Phase Change Materials (PCMs) into cold chain systems has emerged as a promising solution to address these challenges. This article presents a comprehensive analysis of the utilization of PCMs for food preservation in a refrigerated truck, focusing on the impact on temperature control, phase change fraction, costs, and energy savings. The effectiveness of PCM-based refrigeration system to maintain the refrigerated truck at a temperature of −18 °C under various scenarios and environmental conditions using a transient model was evaluated. The TRNSYS model includes a representation of a conventional refrigerated van’s system, with simulations conducted in a Mediterranean climate (Naples). The model’s core components consist of Type 56 for cooling load estimation and Type 1270a for the new PCM component. Results indicate that for guaranteeing −18 °C for 10 h, 96.4 kg and 102.2 kg of E-26 and E-29 PCM are needed, respectively, for scenarios with 10 door openings during transportation and for two different velocities of the truck: 30 and 80 km h⁻¹. Results indicate that the incorporation of PCMs in the refrigerated van leads to significant improvements in temperature stability and uniformity, thereby extending the shelf life of perishable food products and reducing the risk of spoilage. Furthermore, the analysis shows that, using the PCMs, a significant reduction of the energy costs can be obtained (up to a maximum of around 79%). Full article

(This article belongs to the Special Issue Research on Refrigeration and Energy Storage for Carbon Emission Reduction)

15 pages, 1453 KiB

Open AccessArticle

Rapid and Efficient Molecular Detection of Phytophthora nicotianae Based on RPA-CRISPR/Cas12a

by Jiahui Zang, Tingting Dai, Tingli Liu, Xiaoqiao Xu and Jing Zhou

Forests 2024, 15(6), 952; https://doi.org/10.3390/f15060952 (registering DOI) - 30 May 2024

Abstract

Phytophthora nicotianae is a global and polyphagous pathogen with a wide host range. P. nicotianae can infect Areca catechu, Durio zibethinus L., Psidium guajava L., Hevea brasiliensis, and other tree species. The pathogen is capable of inducing butt rot and affecting [...] Read more.

Phytophthora nicotianae is a global and polyphagous pathogen with a wide host range. P. nicotianae can infect Areca catechu, Durio zibethinus L., Psidium guajava L., Hevea brasiliensis, and other tree species. The pathogen is capable of inducing butt rot and affecting aerial parts, including stems, leaves, and fruits. Compared to other Phytophthora species, P. nicotianae is more adaptable to abiotic stress. In this study, recombinase polymerase amplification (RPA) in combination with the CRISPR/Cas12a system was used for the detection of P. nicotianae, and achieved rapid and efficient detection of P. nicotianae. The assay was highly specific to P. nicotianae. All 4 tested isolates of P. nicotianae yielded positive results, whereas 30 isolates belonging to 17 other Phytophthora species, 8 fungal species, and 4 Bursaphelenchus xylophilus vermicules lacked detection. Under the conditions of 37 °C, after 20 min of RPA reaction and 25 min of Cas12a cleavage, a DNA concentration as low as 10 pg·μL⁻¹ could be detected. In addition, it detected P. nicotianae from artificially inoculated leaves of Fatsia japonica. In this study, a novel method was established for the efficient and accurate detection of P. nicotianae based on the combination of RPA and the CRISPR/Cas12a system. Full article

(This article belongs to the Special Issue Advances in Detection and Identification of Insect Pests and Pathogens)

14 pages, 338 KiB

Open AccessArticle

The Effect of Motivation on Physical Activity among Middle and High School Students

by Hélio Antunes, Ana Rodrigues, Bebiana Sabino, Ricardo Alves, Ana Luísa Correia and Helder Lopes

Sports 2024, 12(6), 154; https://doi.org/10.3390/sports12060154 (registering DOI) - 30 May 2024

Abstract

The study addressed two main objectives: (i) to investigate disparities in motivation dimensions regarding extracurricular physical activity and (ii) to identify the influence of motivation on time spent in formal and informal physical activity. A sample of 704 adolescents (56% girls) from middle [...] Read more.

The study addressed two main objectives: (i) to investigate disparities in motivation dimensions regarding extracurricular physical activity and (ii) to identify the influence of motivation on time spent in formal and informal physical activity. A sample of 704 adolescents (56% girls) from middle (46%) and high school (54%), with an average age of 14.88 ± 2.52, was assessed for different motivation dimensions using the Questionnaire of Motivation for Sports Activities (QMSA). Additionally, participants were categorized based on extracurricular physical activity practice. Multivariate analyses and multiple linear regressions were conducted to examine the effect of physical activity type on motivation dimensions and identify predictors of time spent in formal and informal physical activities, respectively. Results indicated that motivation varied significantly with extracurricular physical activity practice (p < 0.05), with students involved in extracurricular activities being more motivated. Sex and age differences were observed, with boys showing higher motivation in certain dimensions (achievement status (p < 0.001); group activity (p = 0.027); contextual (p = 0.004); technical improvement (p = 0.012) and older participants having lower scores in all dimensions. The influence of family and friends was a significant predictor only for boys in formal physical activity (p = 0.039). In terms of time spent in physical activity, group activity was a predictor for informal activities (p < 0.001), while technical improvement was a predictor for formal activities (p < 0.001), with notable sex differences. These findings underscore the importance of considering sex- and age-specific motivations when promoting physical activity among adolescents. Full article

(This article belongs to the Special Issue Advances in Sport Psychology)

12 pages, 1748 KiB

Open AccessArticle

Automatic Modulation Recognition Method Based on Phase Transformation and Deep Residual Shrinkage Network

by Hao Chen, Wenpu Guo, Kai Kang and Guojie Hu

Electronics 2024, 13(11), 2141; https://doi.org/10.3390/electronics13112141 (registering DOI) - 30 May 2024

Abstract

Automatic Modulation Recognition (AMR) is currently a research hotspot, and research under low Signal-to-Noise Ratio (SNR) conditions still poses certain challenges. This paper proposes an AMR method based on phase transformation and deep residual shrinkage network to improve recognition accuracy. Firstly, the raw [...] Read more.

Automatic Modulation Recognition (AMR) is currently a research hotspot, and research under low Signal-to-Noise Ratio (SNR) conditions still poses certain challenges. This paper proposes an AMR method based on phase transformation and deep residual shrinkage network to improve recognition accuracy. Firstly, the raw I/Q data from the benchmark dataset RML2016.10a are used as the input. Then, an end-to-end modulation recognition is performed using the model. Phase transformation is used to correct the raw I/Q data and reduce the interference of phase shift on modulation recognition. Convolutional neural network (CNN) and Gate Recurrent Unit (GRU) extract the spatial and temporal features of the modulation signal, respectively. The improved deep residual shrinkage network is added after CNN to eliminate unimportant features through soft thresholding. Finally, the proposed model is trained and tested. The experimental results show that the proposed model notably reduces the number of parameters compared to other models, effectively improving the recognition accuracy under low SNR conditions. The average recognition accuracy reaches 62.46%, and the highest recognition accuracy reaches 92.41%. Full article

24 pages, 6408 KiB

Open AccessArticle

Towards Fully Autonomous Drone Tracking by a Reinforcement Learning Agent Controlling a Pan–Tilt–Zoom Camera

by Mariusz Wisniewski, Zeeshan A. Rana, Ivan Petrunin, Alan Holt and Stephen Harman

Drones 2024, 8(6), 235; https://doi.org/10.3390/drones8060235 (registering DOI) - 30 May 2024

Abstract

Pan–tilt–zoom cameras are commonly used for surveillance applications. Their automation could reduce the workload of human operators and increase the safety of airports by tracking anomalous objects such as drones. Reinforcement learning is an artificial intelligence method that outperforms humans on certain specific [...] Read more.

Pan–tilt–zoom cameras are commonly used for surveillance applications. Their automation could reduce the workload of human operators and increase the safety of airports by tracking anomalous objects such as drones. Reinforcement learning is an artificial intelligence method that outperforms humans on certain specific tasks. However, there exists a lack of data and benchmarks for pan–tilt–zoom control mechanisms in tracking airborne objects. Here, we show a simulated environment that contains a pan–tilt–zoom camera being used to train and evaluate a reinforcement learning agent. We found that the agent can learn to track the drone in our basic tracking scenario, outperforming a solved scenario benchmark value. The agent is also tested on more complex scenarios, where the drone is occluded behind obstacles. While the agent does not quantitatively outperform the optimal human model, it shows qualitative signs of learning to solve the complex, occluded non-linear trajectory scenario. Given further training, investigation, and different algorithms, we believe a reinforcement learning agent could be used to solve such scenarios consistently. Our results demonstrate how complex drone surveillance tracking scenarios may be solved and fully autonomized by reinforcement learning agents. We hope our environment becomes a starting point for more sophisticated autonomy in control of pan–tilt–zoom cameras tracking of drones and surveilling airspace for anomalous objects. For example, distributed, multi-agent systems of pan–tilt–zoom cameras combined with other sensors could lead towards fully autonomous surveillance, challenging experienced human operators. Full article

(This article belongs to the Special Issue UAV Detection, Classification, and Tracking)

10 pages, 603 KiB

Open AccessArticle

SiOx/C Composite Anode for Lithium-Ion Battery with Improved Performance Using Graphene Quantum Dots and Carbon Nanoparticles

by Sung Won Hwang

Molecules 2024, 29(11), 2578; https://doi.org/10.3390/molecules29112578 (registering DOI) - 30 May 2024

Abstract

In this study, a composite was manufactured by mixing graphene quantum dots, silicon oxide, and carbon nanoparticles, and the characteristics of the anode materials for secondary batteries were examined. To improve the capacity of the graphene quantum dot (GQD) anode material, the added [...] Read more.

In this study, a composite was manufactured by mixing graphene quantum dots, silicon oxide, and carbon nanoparticles, and the characteristics of the anode materials for secondary batteries were examined. To improve the capacity of the graphene quantum dot (GQD) anode material, the added silicon oxide content was varied among 0, 5, 10, 15, and 30 wt%, and carbon nanoparticles were added as a structural stabilizer to alleviate silicon oxide volume expansion. The physical properties of the prepared GQD/SiOx/C composite were investigated through XRD, SEM, EDS, and powder resistance analysis. Additionally, the electrochemical properties of the manufactured composite were observed through an analysis of the charge–discharge cycle, rate, and impedance of a lithium secondary battery. In the GQD/SiOx/C composite, by adding carbon nanoparticles, an internal cavity was formed that can alleviate the volume expansion of silicon oxide, and the carbon nanoparticles and silicon oxide particles were uniformly distributed. The formed internal cavity had a silicon oxide content of 5 wt%. Low initial efficiency was observed, and above 30 wt%, low cycle stability was observed. The GQD/SiOx/C composite with 15 wt% of silicon oxide added showed an initial discharge capacity of 595 mAh/g, a capacity retention rate of 92%, and a rate characteristic of 81 at 2 C/0.1 C. Silicon oxide was added to improve the capacity of the anode material, and carbon nanoparticles were added as a structural stabilizer to buffer the volume change of the silicon oxide. To use GQD/SiOx/C composite as a highly efficient anode material, the optimal silicon oxide content and carbon nanoparticle mechanism as a structural stabilizer were discussed. Full article

(This article belongs to the Section Applied Chemistry)

24 pages, 1086 KiB

Open AccessArticle

Improving Supply Chain Management Processes Using Smart Contracts in the Ethereum Network Written in Solidity

by Eren Yigit and Tamer Dag

Appl. Sci. 2024, 14(11), 4738; https://doi.org/10.3390/app14114738 (registering DOI) - 30 May 2024

Abstract

This paper investigates the potential of integrating supply chain management with blockchain technology, specifically by implementing smart contracts on the Ethereum network using Solidity. The paper explores supply chain management concepts, blockchain, distributed ledger technology, and smart contracts in the context of their [...] Read more.

This paper investigates the potential of integrating supply chain management with blockchain technology, specifically by implementing smart contracts on the Ethereum network using Solidity. The paper explores supply chain management concepts, blockchain, distributed ledger technology, and smart contracts in the context of their integration into supply chains to increase traceability, transparency, and accountability with faster processing times. After investigating these technologies’ applications and potential use cases, a framework for smart contract implementation for supply chain management is constructed. Potential data models and functions of a smart contract implementation improving supply chain management processes are discussed. After constructing a framework, the effects of the proposed system on supply chain processes are explained. The proposed framework increases the reliability of the supply chain history due to the usage of DLT (distributed ledger technology). It utilizes smart contracts to increase the manageability and traceability of the supply chain. The proposed framework also eliminates the SPoF (Single Point of Failure) vulnerabilities and external alteration of the transactional data. However, due to the ever-changing and variable nature of the supply chains, the proposed architecture might not be a one-size-fits-all solution, and tailor-made solutions might be necessary for different supply chain management implementations. Full article

(This article belongs to the Special Issue Blockchain and Intelligent Networking for Smart Applications)

20 pages, 1799 KiB

Open AccessArticle

Comparative Analysis of Spillover Effects in the Global Stock Market under Normal and Extreme Market Conditions

by Qiang Liu, Chen Xu and Jane Xie

Int. J. Financial Stud. 2024, 12(2), 53; https://doi.org/10.3390/ijfs12020053 (registering DOI) - 30 May 2024

Abstract

Using the volatility spillover index method based on the quantile vector autoregression (QVAR) model, this paper systematically examines structural changes and corresponding spillover effects within 20 major stock markets under both extreme and normal market conditions, using data spanning from January 2005 to [...] Read more.

Using the volatility spillover index method based on the quantile vector autoregression (QVAR) model, this paper systematically examines structural changes and corresponding spillover effects within 20 major stock markets under both extreme and normal market conditions, using data spanning from January 2005 to January 2023. The results show that, compared to the traditional volatility spillover index method, which focuses mainly on average spillover effects, the QVAR model-based spillover index better captures spillover effects under extreme and various market conditions among global stock markets. The connections between stock markets are closer in extreme market conditions. The total spillover index of major global stock markets significantly increases in extreme conditions compared to normal conditions. In extreme market conditions, inflow indices show varying degrees of increase, with emerging economy stock markets displaying more significant increases. The outflow indices exhibit heterogeneity; emerging economies show consistent increases, while developed economies show mixed changes. Full article

14 pages, 848 KiB

Open AccessArticle

Effect of Technological Factors on the Extraction of Polymeric Condensed Tannins from Acacia Species

by Zeinab Osman, Antonio Pizzi, Mohammed Elamin Elbadawi, Jérémy Mehats, Wadah Mohammed and Bertrand Charrier

Polymers 2024, 16(11), 1550; https://doi.org/10.3390/polym16111550 (registering DOI) - 30 May 2024

Abstract

The aim of this research work was to investigate the influence of parameters such as particle size, mass/solvent ratio, temperature and spray drying on the tannin extraction process in order to develop cost-effective methods with better environmental and structural performance. The pods of [...] Read more.

The aim of this research work was to investigate the influence of parameters such as particle size, mass/solvent ratio, temperature and spray drying on the tannin extraction process in order to develop cost-effective methods with better environmental and structural performance. The pods of Acacia nilotica ssp. tomentosa (ANT) were fractionated into three fractions, coarse fraction (C) (>2 mm), medium fraction (M) (1–2 mm), and fine fraction (F) < 1 mµ), and extracted with different water-to-pod ratios (2:1, 4:1 and 6:1) at different temperatures (30, 50 and 70 °C). The best results were scaled up using the three fractions of ANT, its bark and the bark of Acacia seyal var. seyal (ASS). Part of their extract was spray dried. The tannin content and total polyphenolic materials were evaluated using standard methods. Their adhesives were tested for their tensile strength. Tannins of ASS were characterized by ¹³C NMR and MALDI-TOF. The results revealed that the fine fraction (F) gave the highest percentage of tannins in both small and scaled-up experiments. The results of the tensile strength conformed to the European standard. The ¹³C NMR spectra of ANT and ASS showed that the bark contained condensed tannins mainly consisting of procyanidins/prodelphinidin of 70%/30% and 60%/40%, respectively. MALDI–TOF spectra confirmed the results obtained by ¹³C NMR and detailed the presence of flavonoid monomers and oligomers, some of which were linked to short carbohydrate monomers or dimers. Full article

(This article belongs to the Special Issue Green Polymers from Renewable Resources)

17 pages, 5923 KiB

Open AccessArticle

Enhancing Heat Removal and H₂O Retention in Passive Air-Cooled Polymer Electrolyte Membrane Fuel Cells by Altering Flow Field Geometry

by Ali M. Mohsen and Ali Basem

Sustainability 2024, 16(11), 4666; https://doi.org/10.3390/su16114666 (registering DOI) - 30 May 2024

Abstract

This numerical study presents six three-dimensional (3D) cathode flow field designs for a passive air-cooled polymer electrolyte membrane (PEM) fuel cell to enhance heat removal and H₂O retention. The data collected are evaluated in terms of water content, average temperature, and [...] Read more.

This numerical study presents six three-dimensional (3D) cathode flow field designs for a passive air-cooled polymer electrolyte membrane (PEM) fuel cell to enhance heat removal and H₂O retention. The data collected are evaluated in terms of water content, average temperature, and current flux density. The proposed cathode flow field designs are a straight baseline channel (Design 1), converging channel (Design 2), diverging channel (Design 3), straight channel with cylindrical pin fins (Design 4), trapezium cross-section channel (Design 5), and semi-circle cross-section channel (Design 6). The lowest cell temperature value of 56.67 °C was obtained for Design 2, while a noticeable water retention improvement of 6.5% was achieved in a semi-circle cathode flow field (Design 5) compared to the baseline channel. However, the current flux density shows a reduction of 0.1% to 1.2%. Nevertheless, those values are relatively small compared to the improvement in the durability of the fuel cell due to heat reduction. Although the modifications to the cathode flow field resulted in only minor improvements, ongoing advancements in fuel cell technology have the potential to make our energy landscape more sustainable. These advancements can help reduce emissions, increase efficiency, integrate renewable energy sources, enhance energy security, and support the transition to a hydrogen-based economy. Full article

(This article belongs to the Section Energy Sustainability)

► Show Figures

Figure 1

15 pages, 532 KiB

Open AccessArticle

Dynamic Changes in Gut Microbiota-Derived Metabolite Trimethylamine-N-Oxide and Risk of Type 2 Diabetes Mellitus: Potential for Dietary Changes in Diabetes Prevention

by Yuliang Huang, Yani Wu, Yao Zhang, He Bai, Ruiheng Peng, Wenli Ruan, Qianlong Zhang, Enmao Cai, Mingfeng Ma, Yueyang Zhao, Ying Lu and Liqiang Zheng

Nutrients 2024, 16(11), 1711; https://doi.org/10.3390/nu16111711 (registering DOI) - 30 May 2024

Abstract

Background: A gut-microbial metabolite, trimethylamine N-oxide (TMAO), has been associated with type 2 diabetes mellitus (T2DM). Few previous prospective studies have addressed associations between the changes in TMAO and T2DM incidence. Methods: Data were derived from a longitudinal cohort conducted from 2019 [...] Read more.

Background: A gut-microbial metabolite, trimethylamine N-oxide (TMAO), has been associated with type 2 diabetes mellitus (T2DM). Few previous prospective studies have addressed associations between the changes in TMAO and T2DM incidence. Methods: Data were derived from a longitudinal cohort conducted from 2019 to 2021 in rural areas of Fuxin County, Liaoning Province, China, and 1515 diabetes-free participants aged above 35 years were included. The concentrations of serum TMAO and its precursors were measured at two time points, namely in 2019 and 2021. TMAO and TMAO changes (ΔTMAO) were separately tested in a logistic regression model. For further examination, the odds ratios (ORs) for T2DM were calculated according to a combination of TMAO levels and ΔTMAO levels. Results: During a median follow-up of 1.85 years, 81 incident cases of T2DM (5.35%) were identified. Baseline TMAO levels exhibited a nonlinear relationship, first decreasing and then increasing, and only at the highest quartile was it associated with the risk of T2DM. The OR for T2DM in the highest quartile of serum TMAO was 3.35 (95%CI: 1.55–7.26, p = 0.002), compared with the lowest quartile. As for its precursors, only choline level was associated with T2DM risk and the OR for T2DM in the Q3 and Q4 of serum choline was 3.37 (95%CI: 1.41–8.05, p = 0.006) and 4.72 (95%CI: 1.47–15.13, p = 0.009), respectively. When considering both baseline TMAO levels and ΔTMAO over time, participants with sustained high TMAO levels demonstrated a significantly increased risk of T2DM, with a multivariable-adjusted OR of 8.68 (95%CI: 1.97, 38.34). Conclusion: Both initial serum TMAO levels and long-term serum TMAO changes were collectively and significantly associated with the occurrence of subsequent T2DM events. Interventions aimed at normalizing TMAO levels, such as adopting a healthy dietary pattern, may be particularly beneficial in T2DM prevention. Full article

(This article belongs to the Special Issue Update on Diet, Nutrition and Type 2 Diabetes: Separating the Science from the Hype)

12 pages, 1337 KiB

Open AccessReview

Sentinel Lymph Node Biopsy in Atypical Spitz Tumor: A Systematic Review

by Marcodomenico Mazza, Francesco Cavallin, Elisa Galasso, Paolo Del Fiore, Rocco Cappellesso, Fortunato Cassalia, Saveria Tropea, Irene Russo, Mauro Alaibac and Simone Mocellin

J. Clin. Med. 2024, 13(11), 3232; https://doi.org/10.3390/jcm13113232 (registering DOI) - 30 May 2024

Abstract

Background: Atypical Spitz tumor (AST) is an intermediate category among Spitz melanocytic neoplasms. Sentinel node biopsy (SNB) has been proposed in the clinical management of AST patients, but this approach remains the subject of debate. This systematic review aims to summarize the available [...] Read more.

Background: Atypical Spitz tumor (AST) is an intermediate category among Spitz melanocytic neoplasms. Sentinel node biopsy (SNB) has been proposed in the clinical management of AST patients, but this approach remains the subject of debate. This systematic review aims to summarize the available evidence on SNB procedures in AST patients. Methods: A comprehensive search was conducted, including MEDLINE/Pubmed, EMBASE, and SCOPUS, through April 2023. Case series, cohort studies, and case–control studies of AST patients were eligible for inclusion. PRISMA guidelines were followed. Results: Twenty-two studies with a total of 756 AST patients were included. The pooled SNB prevalence was 54% (95% CI 32 to 75%), with substantial heterogeneity (I2 90%). The pooled SNB+ prevalence was 35% (95% CI 25 to 46%) with moderate heterogeneity (I2 39%). Lymphadenectomy was performed in 0–100% of SNB+ patients. Overall survival rates ranged from 93% to 100%, and disease-free survival ranged from 87% to 100% in AST patients. Overall and disease-free survival rates were 100% in SNB patients. Pooled survival estimates were not calculated due to the heterogeneous timing of the survival assessment and/or the small size of the subgroups. All studies clearly reported inclusion criteria and measured the condition in a standard way for all participants, but only 50% indicated valid methods for the identification of the condition. Conclusions: The oncologic behavior of AST is related to an almost always favorable outcome. SNB does not seem to be relevant as a staging or prognostic procedure, and its indication remains debatable and controversial. Full article

(This article belongs to the Special Issue Skin Cancer: Prevention, Diagnosis and Treatment)

► Show Figures

Figure 1

13 pages, 1462 KiB

Open AccessArticle

Mycelium-Based Composites: Surveying Their Acceptance by Professional Architects

by Anna Lewandowska, Agata Bonenberg and Maciej Sydor

Biomimetics 2024, 9(6), 333; https://doi.org/10.3390/biomimetics9060333 (registering DOI) - 30 May 2024

Abstract

Mycelium-based composites (MBCs) are biomaterials with scientifically proven potential to improve sustainability in construction. Although mycelium-based products are not entirely new, their use in engineering presents challenges due to the inherent properties of this fungal material. This study investigated professional architects’ and interior [...] Read more.

Mycelium-based composites (MBCs) are biomaterials with scientifically proven potential to improve sustainability in construction. Although mycelium-based products are not entirely new, their use in engineering presents challenges due to the inherent properties of this fungal material. This study investigated professional architects’ and interior designers’ perceptions of MBCs, focusing on familiarity, aesthetic appeal, and willingness to use. The first phase of the survey explored respondents’ views on material-related ecological design principles. In the second phase, respondents evaluated ten small architectural objects crafted from MBCs, focusing on form, detail, and visual appeal. The last phase of the survey measured their interest in using mycelium in their design work. The results revealed that MBCs were relatively unknown among the surveyed professionals; only every second respondent knew this material. Despite this, 90% found MBCs visually appealing after seeing the examples. Interestingly, the natural, unprocessed appearance of the material was assessed as less aesthetically pleasing, with thermal treatment improving its perceived value. Architects were more receptive to using MBCs in their professional projects for customers than for personal use. This observation points to a ‘double standard’: professional architects are more open to using MBCs in projects not intended for their own use. Full article

(This article belongs to the Special Issue Biological and Bioinspired Materials and Structures)

Recent Articles

Open Access Journals

Highly Accessed Articles

Latest Books

News

Blog Posts

Topics

Selected Special Issues

Selected Collections

Journals by Subject

Further Information

Guidelines

MDPI Initiatives

Follow MDPI