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38 pages, 1394 KiB  
Article
A Ladder of Urban Resilience: An Evolutionary Framework for Transformative Governance of Communities Facing Chronic Crises
by Dario Esposito
Sustainability 2025, 17(13), 6010; https://doi.org/10.3390/su17136010 - 30 Jun 2025
Viewed by 587
Abstract
This paper explores the concept of evolutionary urban resilience by framing cities as complex, open, and adaptive Social-Ecological-Technological Systems (SETS), shaped by multi-scalar dynamics, systemic uncertainty, and interdependent crises. It challenges the reductionist view of resilience as a fixed capacity or linear sequence [...] Read more.
This paper explores the concept of evolutionary urban resilience by framing cities as complex, open, and adaptive Social-Ecological-Technological Systems (SETS), shaped by multi-scalar dynamics, systemic uncertainty, and interdependent crises. It challenges the reductionist view of resilience as a fixed capacity or linear sequence of risk management phases, and instead proposes a process-based paradigm rooted in learning, creativity, and the ability to navigate disequilibrium. The framework defines urban resilience as a continuous and iterative transformation process, supported by: (i) a combination of tangible and intangible qualities activated according to problem typology; (ii) cross-domain processes involving infrastructures, flows, governance, networks, and community dynamics; and (iii) the engagement of diverse agents in shared decision-making and coordinated action. These dimensions unfold across three incremental and interdependent scenarios—baseline, critical, and chronic crisis—forming a ladder of resilience that guides communities through escalating challenges. Special emphasis is placed on the role of Information and Communication Technologies (ICTs) as relational and adaptive tools enabling distributed intelligence and inclusive governance. The framework also outlines concrete operational and policy implications for cities aiming to build anticipatory and transformative resilience capacities. Applied to the case of Taranto, the approach offers insights into how structurally fragile communities facing conflicting adaptive trajectories can unlock transformative potential. Ultimately, the paper calls for a shift from government to governance, from control to co-creation, and from reactive adaptation to chaos generativity, recasting urban resilience as an evolving project of collective agency, systemic reconfiguration, and co-production of emergent urban futures. Full article
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10 pages, 1463 KiB  
Article
Exploring Plasma Proteome Thermal Stability in Peripheral Arterial Disease: Biophysical Findings Under Cilostazol Therapy
by Dorottya Szabó, László Benkő and Dénes Lőrinczy
Pharmaceuticals 2025, 18(6), 886; https://doi.org/10.3390/ph18060886 - 13 Jun 2025
Viewed by 429
Abstract
Introduction: Intermittent claudication, an early symptom of peripheral artery disease, can be treated by cilostazol to alleviate symptoms and improve walking distance. Our previous investigation focused on cilostazol-induced alterations in the thermodynamic properties of plasma, utilizing differential scanning calorimetry (DSC) as a [...] Read more.
Introduction: Intermittent claudication, an early symptom of peripheral artery disease, can be treated by cilostazol to alleviate symptoms and improve walking distance. Our previous investigation focused on cilostazol-induced alterations in the thermodynamic properties of plasma, utilizing differential scanning calorimetry (DSC) as a potential monitoring tool. The current proof-of-concept study aimed to enhance the interpretation of DSC data through deconvolution techniques, specifically examining protein transitions within the plasma proteome during cilostazol therapy. Results: Notable differences in thermal unfolding profiles were found between cilostazol-treated patients and healthy controls. The fibrinogen-associated transition exhibited a downward shift in denaturation temperature and decreased enthalpy by the third month. The albumin-related transition shifted to higher temperatures, accompanied by lower enthalpy. Transitions associated with globulins showed changes in thermal stability, while the transferrin-related peak demonstrated increased structural rigidity in treated patients compared to controls. Discussion: These observations suggest that cilostazol induces systemic changes in the thermodynamic behavior of plasma proteins. DSC, when combined with deconvolution methods, presents a promising approach for detecting subtle, therapy-related alterations in plasma protein stability. Materials and methods: Ten patients (median age: 58.6 years) received 100 milligrams of cilostazol twice daily. Blood samples were collected at the baseline and after 2 weeks, 1 month, 2 months, and 3 months of therapy. Walking distances were also assessed. The DSC curves were retrieved from the thermal analysis investigated by deconvolution mathematical methods. Conclusions: Although the exact functional consequences remain unclear, the observed biophysical changes may reflect broader molecular adaptations involving protein–protein interactions, post-translational modifications, or acute phase response elements. Full article
(This article belongs to the Special Issue Advances in Medicinal Chemistry: 2nd Edition)
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13 pages, 2237 KiB  
Article
Biomimetic Soft Actuator with Deformation and Motion Driven by Near-Infrared Light
by Mei Li and Yubai Ma
Polymers 2025, 17(10), 1315; https://doi.org/10.3390/polym17101315 - 12 May 2025
Viewed by 442
Abstract
Restricted by the inherent low sensitivity of materials and complex integration technology, it is difficult for existing soft actuators (s-actuators) to simultaneously possess the advantages of flexibility, fast response, and simple manufacturing, which greatly limits their practical applications. Herein, a stretchable (ε = [...] Read more.
Restricted by the inherent low sensitivity of materials and complex integration technology, it is difficult for existing soft actuators (s-actuators) to simultaneously possess the advantages of flexibility, fast response, and simple manufacturing, which greatly limits their practical applications. Herein, a stretchable (ε = 200%) nanocomposite film capable of deformation and motion driven by near infrared light (NIR) was developed using multi-walled carbon nanotubes (MWCNTs) as the light absorption–photothermal conversion nanonetwork, and liquid crystal polymer (LCP) as an elastic matrix featured reversible phase transition. Furthermore, s-actuators with various deformation and motion modes have been realized employing MWCNT/LCP nanocomposite film. Based on the mechanism that photothermal-effect-regulated liquid crystal–isotropic phase transition in LCP can induce macroscopic deformation of nanocomposites, MWCNT/LCP s-actuators have completed a series of complex deformation and motion tasks such as opening the knot, “V”-shape reversible deformation (30 s per cycle), the “spring” rotating and unfolding, imitating a “caterpillar” walking in a straight line (the average speed is 13 s/mm), etc. This work provides an effective strategy for the intelligent development of s-actuators. Full article
(This article belongs to the Section Polymer Composites and Nanocomposites)
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20 pages, 54664 KiB  
Article
Lensless Digital Holographic Reconstruction Based on the Deep Unfolding Iterative Shrinkage Thresholding Network
by Duofang Chen, Zijian Guo, Huidi Guan and Xueli Chen
Electronics 2025, 14(9), 1697; https://doi.org/10.3390/electronics14091697 - 22 Apr 2025
Viewed by 549
Abstract
Without using any optical lenses, lensless digital holography (LDH) records the hologram of a sample and numerically retrieves the amplitude and phase of the sample from the hologram. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable, [...] Read more.
Without using any optical lenses, lensless digital holography (LDH) records the hologram of a sample and numerically retrieves the amplitude and phase of the sample from the hologram. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable, and cost-effective devices to potentially address various point-of-care-, global health-, and telemedicine-related challenges. However, in lensless digital holography, the reconstruction results are severely affected by zero-order noise and twin images as only the hologram intensity can be recorded. To mitigate such interference and enhance image quality, extensive efforts have been made. In recent years, deep learning (DL)-based approaches have made significant advancements in the field of LDH reconstruction. It is well known that most deep learning networks are often regarded as black-box models, which poses challenges in terms of interpretability. Here, we present a deep unfolding network, dubbed the ISTAHolo-Net, for LDH reconstruction. The ISTAHolo-Net replaces the traditional iterative update steps with a fixed number of sub-networks and the regularization weights with learnable parameters. Every sub-network consists of two modules, which are the gradient descent module (GDM) and the proximal mapping module (PMM), respectively. The ISTAHolo-Net incorporates the sparsity-constrained inverse problem model into the neural network and hence combines the interpretability of traditional iterative algorithms with the learning capabilities of neural networks. Simulation and real experiments were conducted to verify the effectiveness of the proposed reconstruction method. The performance of the proposed method was compared with the angular spectrum method (ASM), the HRNet, the Y-Net, and the DH-GAN. The results show that the DL-based reconstruction algorithms can effectively reduce the interference of twin images, thereby improving image reconstruction quality, and the proposed ISTAHolo-Net performs best on our dataset. Full article
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20 pages, 671 KiB  
Article
Unveiling the Mental Health of Postpartum Women During and After COVID-19: Analysis of Two Population-Based National Maternity Surveys in Romania (2020–2025)
by Livia Ciolac, Dumitru-Răzvan Nițu, Elena Silvia Bernad, Adrian Gluhovschi, Daian-Ionel Popa, Teodora Toc, Anca Tudor, Anca-Laura Maghiari and Marius Lucian Craina
Healthcare 2025, 13(8), 911; https://doi.org/10.3390/healthcare13080911 - 16 Apr 2025
Viewed by 733
Abstract
(1) Background: The COVID-19 pandemic caused widespread upheaval, presenting unique challenges for pregnant and postpartum women, who were already in a particularly vulnerable phase. As the COVID-19 pandemic and its public health response unfolded, it became crucial for clinicians and researchers to explore [...] Read more.
(1) Background: The COVID-19 pandemic caused widespread upheaval, presenting unique challenges for pregnant and postpartum women, who were already in a particularly vulnerable phase. As the COVID-19 pandemic and its public health response unfolded, it became crucial for clinicians and researchers to explore postpartum depression within the context of a global crisis. (2) Methods: We used data from two cross-sectional surveys of postnatal women conducted in our tertiary academic public hospital during the SARS-CoV-2 pandemic and the post-pandemic period, based on the retrospective assessments of two samples of mothers, each including 860 postpartum women. Our research has been conducted with the scope of evaluating postpartum depression disorder during and after the COVID-19 pandemic by using comparable data across time. (3) Results: The prevalence of postpartum depression was significantly higher among women who gave birth during the COVID-19 pandemic (major postpartum depressive disorder: 54.19%, minor depressive disorder: 15.58%), compared to pre-pandemic rates (10% in developed countries and 21–26% in developing countries) and post-pandemic rates (major depressive disorder 10.12%, minor depressive disorder 10.93%). The results of our research indicate that the COVID-19 pandemic had a major negative impact on perinatal mental health and, moreover, might have sped up an existing trend of the increasing prevalence of postpartum depression, despite the fact that the risk factors for postpartum depression disease remained consistent before, during, and after the pandemic. (4) Conclusions: Strengthening support systems during periods of heightened risk, such as during a pandemic, is crucial; therefore, policymakers and health planners should prioritize the mental health of this vulnerable group during global health crises or natural disasters, ensuring the implementation of effective mental health screenings, identification, enhanced support, follow-up, and reassurance measures to better address the challenges faced by susceptible postpartum women in future similar situations. Full article
(This article belongs to the Special Issue Human Health Before, During, and After COVID-19)
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25 pages, 4374 KiB  
Article
Identifying Genes Associated with the Anticancer Activity of a Fluorinated Chalcone in Triple-Negative Breast Cancer Cells Using Bioinformatics Tools
by Eduardo De la Cruz-Cano, José Ángel González-Díaz, Ivonne María Olivares-Corichi, Jorge Tonatiuh Ayala-Sumuano, José Alfredo Díaz-Gandarilla, Quirino Torres-Sauret, Violeta Larios-Serrato, Miguel Ángel Vilchis-Reyes, Carlos Javier López-Victorio, José Arnold González-Garrido and José Rubén García-Sánchez
Int. J. Mol. Sci. 2025, 26(8), 3662; https://doi.org/10.3390/ijms26083662 - 12 Apr 2025
Viewed by 1308
Abstract
Fluorinated chalcones are molecules reported to possess potent anticancer properties against triple-negative breast cancer (TNBC) cells. However, their molecular mechanisms have not yet been fully explored. Using bioinformatics tools, we analyzed the transcriptomes of MDA-MB-231 cells treated with either a novel fluorinated chalcone [...] Read more.
Fluorinated chalcones are molecules reported to possess potent anticancer properties against triple-negative breast cancer (TNBC) cells. However, their molecular mechanisms have not yet been fully explored. Using bioinformatics tools, we analyzed the transcriptomes of MDA-MB-231 cells treated with either a novel fluorinated chalcone (compound 3) or a control in order to identify differentially expressed (DE) genes associated with its anticancer activity and determine the biological processes in which these genes are involved. A fluorinated chalcone was synthesized using the Claisen–Schmidt method. The transcriptome of MDA-MB-231 cells was then analyzed on an Illumina NextSeq500, and DE genes with significant changes in expression were identified using the DESeq2 v1.38.0 bioinformatics tool under the strict detection criteria of |log2FC| ≥  2 and adjusted p < 0.05. We identified 504 DE genes, which were enriched in terms related to “regulation of cell death”, “cation transport”, “response to topologically incorrect proteins”, and “response to unfolded proteins”. Surprisingly, these genes were involved in “the HSF1-dependent transactivation pathway” and “the attenuation phase pathway”. This bioinformatics-based study suggests that the tested fluorinated chalcone could influence HSF-1 silencing in addition to promoting the up-regulation of several genes involved in stress-induced apoptosis. Therefore, the tested compound could have enormous potential as a novel approach for TNBC treatment. Full article
(This article belongs to the Special Issue Molecular Research in Triple-Negative Breast Cancer)
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25 pages, 11034 KiB  
Article
A Novel Deep Unfolding Network for Multi-Band SAR Sparse Imaging and Autofocusing
by Xiaopeng Li, Mengyang Zhan, Yiheng Liang, Yinwei Li, Gang Xu and Bingnan Wang
Remote Sens. 2025, 17(7), 1279; https://doi.org/10.3390/rs17071279 - 3 Apr 2025
Viewed by 386
Abstract
The sparse imaging network of synthetic aperture radar (SAR) is usually designed end to end and has a limited adaptability to radar systems of different bands. Meanwhile, the implementation of the sparse imaging algorithm depends on the sparsity of the target scene and [...] Read more.
The sparse imaging network of synthetic aperture radar (SAR) is usually designed end to end and has a limited adaptability to radar systems of different bands. Meanwhile, the implementation of the sparse imaging algorithm depends on the sparsity of the target scene and usually adopts a fixed L1 regularization solution, which has a mediocre reconstruction effect on complex scenes. In this paper, a novel SAR imaging deep unfolding network based on approximate observation is proposed for multi-band SAR systems. Firstly, the approximate observation module is separated from the optimal solution network model and selected according to the multi-band radar echo. Secondly, to realize the SAR imaging of non-sparse scenes, Lp regularization is used to constrain the uncertain transform domain of the target scene. The adaptive optimization of Lp parameters is realized by using a data-driven approach. Furthermore, considering that phase errors may be introduced in the real SAR system during echo acquisition, an error estimation module is added to the network to estimate and compensate for the phase errors. Finally, the results from both simulated and real data experiments demonstrate that the proposed method exhibits outstanding performance under 0.22 THz and 9.6 GHz echo data: high-resolution SAR focused images are achieved under four different sparsity conditions of 20%, 40%, 60%, and 80%. These results fully validate the strong adaptability and robustness of the proposed method to diverse SAR system configurations and complex target scenarios. Full article
(This article belongs to the Special Issue Microwave Remote Sensing for Object Detection (2nd Edition))
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14 pages, 5121 KiB  
Article
A Single-Phase AC-AC Power Electronic Transformer Without Bulky Energy Storage Elements
by Hui Wang, Shuyang Xie and Liang Yuan
Energies 2025, 18(7), 1769; https://doi.org/10.3390/en18071769 - 1 Apr 2025
Viewed by 424
Abstract
Compared with the line-frequency transformer (LFT), the emerging power electronic transformers (PETs) have gained wide concerns due to the significant merits of higher power density, higher reliability, more flexibility, and multiple functions. However, the need for bulky energy storage elements, multi-stage power conversion [...] Read more.
Compared with the line-frequency transformer (LFT), the emerging power electronic transformers (PETs) have gained wide concerns due to the significant merits of higher power density, higher reliability, more flexibility, and multiple functions. However, the need for bulky energy storage elements, multi-stage power conversion and reduced conversion efficiency, and the intrinsic twice-frequency pulsating power issue are the main disadvantages of the conventional single-phase PETs. To overcome the above shortcomings of conventional single-phase PETs, this paper develops a matrix-type single-phase AC-AC PET without bulky energy storage elements. The proposed PET consists of a line-frequency commutated rectifier, a half-bridge LLC resonant converter with a fixed switching frequency, a boost converter, and a line-frequency commutated inverter. The LLC operates efficiently with unity voltage gain and acts as a high-frequency isolated DC transformer (DCX). The boost converter provides AC output voltage regulation function and the line-frequency commutated inverter unfolds the output voltage of the boost converter to generate the sinusoidal AC output voltage. As a result, high power density, reduced power conversion stages, direct AC-AC power conversion without twice-frequency pulsating power, high conversion efficiency, and high reliability are achieved. The experimental results on a 1kW PET prototype show that sinusoidal input current and output voltage, ZVS of the LLC stage, and output voltage regulation capability are realized. The experimental results verify the correctness and feasibility of the presented methods. Full article
(This article belongs to the Section F3: Power Electronics)
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16 pages, 5156 KiB  
Article
The Heat-Induced Gel–Sol Transition in Coated Tofu: A Study on Protein Conformation and Microstructural Changes
by Xin Xie, Meng Li, Xinrui Diao, Saihua Sun, Ming Wen, Xiaohu Zhou, Liangzhong Zhao, Yang Li, Ping Lv, Bin Li, Xiaolong Shen, Zhanrui Huang, Hao Chen and Kuilin Zhang
Gels 2025, 11(4), 237; https://doi.org/10.3390/gels11040237 - 24 Mar 2025
Cited by 1 | Viewed by 902
Abstract
To enhance and stabilise the edible quality of coated tofu, this study explored the changes in the microstructure and intermolecular forces of coated tofu gel and sol under different heat treatments. It elucidated the phase transformation mechanism of coated tofu gel and sol [...] Read more.
To enhance and stabilise the edible quality of coated tofu, this study explored the changes in the microstructure and intermolecular forces of coated tofu gel and sol under different heat treatments. It elucidated the phase transformation mechanism of coated tofu gel and sol under heat treatment. The results showed that the protein structure unfolded, the fluorescence intensity decreased, and the protein solubility, surface hydrophobicity, and free sulfhydryl group content increased as the coated tofu gel transformed to sol. Disulfide bonding and hydrophobic interactions were the primary intermolecular forces in the heat-induced gel–sol transition. FTIR showed that the content of β-sheets decreased significantly during gel–sol transformation, while the content of β-turns, α-helices and random coils increased significantly. Most remained relatively stable during the gel–sol transformation process, with only the A and B subunits of the 11S protein decreasing slightly. Their reduction became significant when the temperature reached 200 °C. Additionally, the high-temperature heat treatment promoted the gel–sol transition of the coated tofu, with its cross-section gradually transforming from a porous network structure to a more uniform and smooth texture during heat treatment process. The findings of this study provide a theoretical basis for improving the quality of coated tofu by optimising heat treatment parameters, laying the groundwork for future advancements in the development of pre-heat-treated coated tofu. Full article
(This article belongs to the Special Issue Advances in Protein Gels and Their Applications)
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17 pages, 1097 KiB  
Opinion
Delayed-Onset Muscle Soreness Begins with a Transient Neural Switch
by Balázs Sonkodi
Int. J. Mol. Sci. 2025, 26(5), 2319; https://doi.org/10.3390/ijms26052319 - 5 Mar 2025
Cited by 4 | Viewed by 3347
Abstract
Unaccustomed and/or strenuous eccentric contractions are known to cause delayed-onset muscle soreness. In spite of this fact, their exact cause and mechanism have been unknown for more than 120 years. The exploration of the diverse functionality of the Piezo2 ion channel, as the [...] Read more.
Unaccustomed and/or strenuous eccentric contractions are known to cause delayed-onset muscle soreness. In spite of this fact, their exact cause and mechanism have been unknown for more than 120 years. The exploration of the diverse functionality of the Piezo2 ion channel, as the principal proprioceptive component, and its autonomously acquired channelopathy may bring light to this apparently simple but mysterious pain condition. Correspondingly, the neurocentric non-contact acute compression axonopathy theory of delayed-onset muscle soreness suggests two damage phases affecting two muscle compartments, including the intrafusal (within the muscle spindle) and the extrafusal (outside the muscle spindle) ones. The secondary damage phase in the extrafusal muscle space is relatively well explored. However, the suggested primary damage phase within the muscle spindle is far from being entirely known. The current manuscript describes how the proposed autonomously acquired Piezo2 channelopathy-induced primary damage could be the initiating transient neural switch in the unfolding of delayed-onset muscle soreness. This primary damage results in a transient proprioceptive neural switch and in a switch from quantum mechanical free energy-stimulated ultrafast proton-coupled signaling to rapid glutamate-based signaling along the muscle–brain axis. In addition, it induces a transient metabolic switch or, even more importantly, an energy generation switch in Type Ia proprioceptive terminals that eventually leads to a transient glutaminolysis deficit and mitochondrial deficiency, not to mention a force generation switch. In summary, the primary damage or switch is likely an inward unidirectional proton pathway reversal between Piezo2 and its auxiliary ligands, leading to acquired Piezo2 channelopathy. Full article
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23 pages, 587 KiB  
Review
Factors That Strengthen Community Resilience to Externally Initiated and Controlled Tourism in Post-Conflict Destinations: The Role of Amenity Migrants and Management Policies
by Seweryn Zielinski, Luz Helena Díaz Rocca and Young-joo Ahn
Land 2025, 14(3), 546; https://doi.org/10.3390/land14030546 - 5 Mar 2025
Viewed by 1197
Abstract
This study examines community resilience in post-conflict tourism destinations of the Global South, where externally initiated and controlled tourism development often prevails. Using a conceptual research approach grounded in a comprehensive literature review, the paper identifies critical conditions for resilience-building in these fragile [...] Read more.
This study examines community resilience in post-conflict tourism destinations of the Global South, where externally initiated and controlled tourism development often prevails. Using a conceptual research approach grounded in a comprehensive literature review, the paper identifies critical conditions for resilience-building in these fragile contexts. It demonstrates that post-conflict tourism development typically unfolds in three stages: an initial phase of rapid growth driven by external stakeholders, followed by community awakening to tourism’s impacts, and culminating in community-led efforts to regain control. The study argues that even when initial tourism development exceeds local adaptive capacities, it can initiate a gradual process of resilience-building through proactive community action and supportive policies. The transformative potential of amenity migrants is emphasized, as they can shift from being stressors to becoming agents of change, fostering resilience, provided they are successfully integrated into local communities. The paper also advocates for longitudinal research to better understand the dynamics of amenity migrants’ assimilation and their role in resilience-building, particularly in the Global South, where empirical evidence remains limited. The findings provide valuable insights for designing strategies to achieve sustainable and inclusive tourism development in post-conflict and other vulnerable destinations, offering a pathway to empower local communities and foster long-term resilience. Full article
(This article belongs to the Special Issue The Role of Land Policy in Shaping Tourism Development)
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19 pages, 1583 KiB  
Article
How Does China Explore the Synergetic Development of Automotive Industry and Semiconductor Industry with the Opportunity for Industrial Transformation?
by Wang Zhang, Fuquan Zhao and Zongwei Liu
Sustainability 2025, 17(4), 1753; https://doi.org/10.3390/su17041753 - 19 Feb 2025
Viewed by 1608
Abstract
Amidst the unfolding technological revolution and industrial transformation, the synergistic development between China’s automotive and semiconductor industries has emerged as a salient trend. To explore the potential difficulties and pathways of the synergistic development of the two industries, this study conducted cross-sectional surveys [...] Read more.
Amidst the unfolding technological revolution and industrial transformation, the synergistic development between China’s automotive and semiconductor industries has emerged as a salient trend. To explore the potential difficulties and pathways of the synergistic development of the two industries, this study conducted cross-sectional surveys across three phases, specifically in March 2021, March 2022, and March 2024. The first phase of the survey identified that the two industries could mutually promote each other in both technical and market aspects and pinpointed three major challenges: computational capacity bottlenecks, supply chain risks, and unclear industrial cooperation models. The second phase of the survey discussed three opportunities to address the three challenges, respectively: intelligent vehicle infrastructure cooperative system, supply chain localization, and the reconstruction of the technology stack. The third phase of the survey summarized the development experience over the past three years, validated the aforementioned opportunities, and suggested the government promote the digitalization of vehicles and mobility, automotive companies use more domestic chips, and two industries build the ecological cooperation model. Full article
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19 pages, 1802 KiB  
Article
Variability and Relationship Between Phenological and Morphological Traits in Early and Late Pedunculate Oak
by Andrijana Bauer Živković, Mirjana Šijačić Nikolić, Dejan B. Stojanović, Saša Orlović and Branislav Kovačević
Forests 2025, 16(2), 198; https://doi.org/10.3390/f16020198 - 22 Jan 2025
Viewed by 860
Abstract
Variability and relationship between phenological traits and leaf, acorn, and tree size morphometric traits were examined in early and late bud-flushing groups of the pedunculate oak population in the vicinity of Sremska Mitrovica, Serbia. According to the obtained three-year results, there were no [...] Read more.
Variability and relationship between phenological traits and leaf, acorn, and tree size morphometric traits were examined in early and late bud-flushing groups of the pedunculate oak population in the vicinity of Sremska Mitrovica, Serbia. According to the obtained three-year results, there were no significant differences in tree size and leaf morphometric characteristics between the early and late group. The effect of trees within phenological groups was statistically significant and considerable, especially in leaf blade width (lbw) and leaf area (la). Acorn length (acl) and acorn index (acinx) were significantly influenced by phenological group, achieving moderate contribution of phenological group to the total variation. There was a clear effect of phenological group on variation of examined phenological traits. The effect of year of monitoring on the same traits was not significant, but there was a clear effect of interaction between phenological group and year, especially in case of traits describing the period from bud swelling until the emergence of wrinkled leaves (f12a), unfolded leaves (f12b), and fully developed leaves (f12g) and their ratio with the period from 8 March until the emergence of wrinkled leaves: f12b/f02a and f12g/f02a ratio. Earlier phenology in warmer years is clearer in the early bud-flushing group than in the late one. Periods between different bud swelling and f12a, f12b, and f12g phenological phases were significantly shorter in 2017 (with a warm April) than in 2015 (with moderate temperatures in March and April) in the early group, but significantly longer in the late group. Examined traits were classified in six groups based on their factorial loadings with the first six principal components rotated by Varimax method, revealing strict distinction between traits by their original nature. In that sense, all examined groups of traits could be considered as informative in variability studies of pedunculate oak. The tree size traits (tree height and diameter at breast height) formed the separate, fifth group, suggesting no close relationship of these traits with any other examined characteristic. Both cluster analysis and PCA suggest distinct classification by trees’ phenology, but also considerable differences by the second principal component which is closely related to leaf size characteristics. The research should be continued on variability between populations and progenies, especially with respect to phenological and acorn morphometric traits. Understanding the phenological variations between early and late oaks could be essential for designing robust forest adaptation management strategies. Full article
(This article belongs to the Section Forest Ecology and Management)
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35 pages, 20583 KiB  
Article
A Comprehensive Approach to CO2 Emissions Analysis in High-Human-Development-Index Countries Using Statistical and Time Series Approaches
by Hamed Khosravi, Ahmed Shoyeb Raihan, Farzana Islam, Ashish Nimbarte and Imtiaz Ahmed
Sustainability 2025, 17(2), 603; https://doi.org/10.3390/su17020603 - 14 Jan 2025
Viewed by 1512
Abstract
Reducing carbon dioxide (CO2) emissions is vital at both global and national levels, given their significant role in exacerbating climate change. CO2 emissions, stemming from a variety of industrial and economic activities, are major contributors to the greenhouse effect and [...] Read more.
Reducing carbon dioxide (CO2) emissions is vital at both global and national levels, given their significant role in exacerbating climate change. CO2 emissions, stemming from a variety of industrial and economic activities, are major contributors to the greenhouse effect and global warming, posing substantial obstacles in addressing climate issues. It is imperative to forecast CO2 emissions trends and classify countries based on their emission patterns to effectively mitigate worldwide carbon emissions. This paper presents an in-depth comparative study on the determinants of CO2 emissions in twenty countries with high Human Development Index (HDI), exploring factors related to economy, environment, energy use, and renewable resources over a span of 25 years. The study unfolds in two distinct phases: initially, statistical techniques such as Ordinary Least Squares (OLS), fixed effects, and random effects models are applied to pinpoint significant determinants of CO2 emissions. Following this, the study leverages supervised and unsupervised time series approaches to further scrutinize and understand the factors influencing CO2 emissions. Seasonal AutoRegressive Integrated Moving Average with eXogenous variables (SARIMAX), a statistical time series forecasting model, is first used to predict emission trends from historical data, offering practical insights for policy formulation. Subsequently, Dynamic Time Warping (DTW), an unsupervised time series clustering approach, is used to group countries by similar emission patterns. The dual-phase approach utilized in this study significantly improves the accuracy of CO2 emissions predictions while also providing a deeper insight into global emission trends. By adopting this thorough analytical framework, nations can develop more focused and effective carbon reduction policies, playing a vital role in the global initiative to combat climate change. Full article
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22 pages, 638 KiB  
Article
Unfolded Algorithms for Deep Phase Retrieval
by Naveed Naimipour, Shahin Khobahi, Mojtaba Soltanalian, Haleh Safavi and Harry C. Shaw
Algorithms 2024, 17(12), 587; https://doi.org/10.3390/a17120587 - 20 Dec 2024
Viewed by 1177
Abstract
Exploring the idea of phase retrieval has been intriguing researchers for decades due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typically to recover a signal from linear phase-less measurements. In this paper, we [...] Read more.
Exploring the idea of phase retrieval has been intriguing researchers for decades due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typically to recover a signal from linear phase-less measurements. In this paper, we approach the problem by proposing a hybrid model-based, data-driven deep architecture referred to as Unfolded Phase Retrieval (UPR), which exhibits significant potential in improving the performance of state-of-the-art data-driven and model-based phase retrieval algorithms. The proposed method benefits from the versatility and interpretability of well-established model-based algorithms while simultaneously benefiting from the expressive power of deep neural networks. In particular, our proposed model-based deep architecture is applied to the conventional phase retrieval problem (via the incremental reshaped Wirtinger flow algorithm) and the sparse phase retrieval problem (via the sparse truncated amplitude flow algorithm), showing immense promise in both cases. Furthermore, we consider a joint design of the sensing matrix and the signal processing algorithm and utilize the deep unfolding technique in the process. Our numerical results illustrate the effectiveness of such hybrid model-based and data-driven frameworks and showcase the untapped potential of data-aided methodologies to enhance existing phase retrieval algorithms. Full article
(This article belongs to the Special Issue Machine Learning for Edge Computing)
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