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27 pages, 11167 KiB  
Article
Integrating In Situ Non-Destructive Techniques and Colourimetric Analysis to Evaluate Pigment Ageing and Environmental Effects on Tibetan Buddhist Murals
by Xiyao Li, Erdong She, Jingqi Wen, Yan Huang and Jianrui Zha
Chemosensors 2025, 13(6), 202; https://doi.org/10.3390/chemosensors13060202 - 2 Jun 2025
Abstract
The colour degradation of murals presents a significant challenge in the conservation of architectural heritage. Previous research has often concentrated on localized pigment changes while paying insufficient attention to the interaction between colour variation and indoor environmental conditions. Although non-destructive analytical techniques are [...] Read more.
The colour degradation of murals presents a significant challenge in the conservation of architectural heritage. Previous research has often concentrated on localized pigment changes while paying insufficient attention to the interaction between colour variation and indoor environmental conditions. Although non-destructive analytical techniques are widely used in heritage studies, their integrated application in combination with colourimetry has been limited, particularly in the context of Tibetan Buddhist murals in highland continental climates. This study investigates the murals of Liuli Hall in Meidai Lamasery, Inner Mongolia, as a representative case. We employed a comprehensive methodology that combines non-destructive analytical tools, gas chromatography–mass spectrometry, and quantitative colour analysis to examine pigment composition, binding material, and surface deterioration. Through joint analysis using the CIE Lab and CIE LCh colour space systems, we quantified mural colour changes and explored their correlation with material degradation and environmental exposure. The pigments identified include cinnabar, atacamite, azurite, and chalk, with animal glue and drying oils as binding materials. Colourimetric results revealed pronounced yellowing on the east and west walls, primarily caused by the ageing of organic binders. In contrast, a notable reduction in brightness on the south wall was attributed to dust accumulation. These findings support tailored conservation measures such as regular surface cleaning for the south wall and antioxidant stabilization treatments for the east and west walls. Initial cleaning efforts proved effective. The integrated approach adopted in this study provides a replicable model for mural diagnostics and conservation under complex environmental conditions. Full article
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24 pages, 12291 KiB  
Article
Isolation and Identification of Burkholderia stagnalis YJ-2 from the Rhizosphere Soil of Woodsia ilvensis to Explore Its Potential as a Biocontrol Agent Against Plant Fungal Diseases
by Xufei Zhu, Wanqing Ning, Wei Xiao, Zhaoren Wang, Shengli Li, Jinlong Zhang, Min Ren, Chengnan Xu, Bo Liu, Yanfeng Wang, Juanli Cheng and Jinshui Lin
Microorganisms 2025, 13(6), 1289; https://doi.org/10.3390/microorganisms13061289 - 31 May 2025
Viewed by 149
Abstract
Plant fungal diseases remain a major threat to global agricultural production, necessitating eco-friendly and sustainable strategies. Conventional chemical fungicides often lead to the development of resistant pathogen strains and cause environmental contamination. Therefore, the development of biocontrol agents is particularly important. In this [...] Read more.
Plant fungal diseases remain a major threat to global agricultural production, necessitating eco-friendly and sustainable strategies. Conventional chemical fungicides often lead to the development of resistant pathogen strains and cause environmental contamination. Therefore, the development of biocontrol agents is particularly important. In this study, we identified Burkholderia stagnalis YJ-2 from the rhizosphere soil of Woodsia ilvensis as a promising biocontrol strain using 16S rRNA and whole-genome sequencing. This strain demonstrated broad-spectrum antifungal activity against plant fungal pathogens, with its bioactive extracts maintaining high stability across a temperature range of 25–100 °C and pH range of 2–12. We used in vitro assays to further show that the metabolites of B. stagnalis YJ-2 disrupted the hyphal morphology of Valsa mali, resulting in swelling, reduced branching, and increased pigmentation. Fluorescence labeling confirmed that B. stagnalis YJ-2 stably colonized the roots and stems of tomato and wheat plants. Furthermore, various formulations of microbial agents based on B. stagnalis YJ-2 were evaluated for their efficacy against plant pathogens. The seed-coating formulation notably protected tomato seedlings from Alternaria solani infection without affecting germination (p > 0.1), while the wettable powder exhibited significant control effects on early blight in tomatoes, with the preventive treatment showing better efficacy than the therapeutic treatment. Additionally, the B. stagnalis YJ-2 bone glue agent showed a substantial inhibitory effect on apple tree canker. Whole-genome analysis of B. stagnalis YJ-2 revealed a 7,705,355 bp genome (67.68% GC content) with 6858 coding genes and 20 secondary metabolite clusters, including three clusters (YJ-2_GM002015-YJ-2_GM002048, YJ-2_GM0020090-YJ-2_GM002133, and YJ-2_GM06534-YJ-2_GM006569) that are related to the antifungal activity of YJ-2 and are homologous to the biosynthetic gene clusters of known secondary metabolites, such as icosalide, ornibactin, and sinapigladioside. We further knocked out core biosynthetic genes of two secondary metabolic gene clusters and found that only the YJ-2_GM006534-YJ-2_GM006569 gene cluster had a corresponding function in two potential antifungal gene clusters. In contrast to the wild-type strain YJ-2, only deletion of the YJ-2_GM006563 gene reduced the antifungal activity of B. stagnalis YJ-2 by 8.79%. These findings highlight the biocontrol potential of B. stagnalis YJ-2, supporting a theoretical foundation for its development as a biocontrol agent against plant fungal diseases and thereby promoting sustainable agricultural disease management. Full article
(This article belongs to the Special Issue Rhizosphere Bacteria and Fungi That Promote Plant Growth)
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21 pages, 1418 KiB  
Article
A Cascading Delphi Method-Based FMEA Risk Assessment Framework for Surgical Instrument Design: A Case Study of a Fetoscope
by Wipharat Phokee, Sunisa Chaiklieng, Pornpimon Boriwan, Thanathorn Phoka, Jeroen Vanoirbeek and Surapong Chatpun
Appl. Sci. 2025, 15(11), 6203; https://doi.org/10.3390/app15116203 - 30 May 2025
Viewed by 150
Abstract
Failure Mode and Effect Analysis (FMEA) is crucial for identifying risk reduction opportunities in design. This study aims to aid in the design of sophisticated medical devices by setting guidelines and addressing weaknesses in data collection and risk priority numbers (RPNs). This is [...] Read more.
Failure Mode and Effect Analysis (FMEA) is crucial for identifying risk reduction opportunities in design. This study aims to aid in the design of sophisticated medical devices by setting guidelines and addressing weaknesses in data collection and risk priority numbers (RPNs). This is achieved by developing an FMEA framework with potential efficiency and efficacy benefits for design engineers, surgeons and patients. The FMEA framework covered risk analysis and risk evaluation by integrating a cascading Delphi method to address data collection and Multi-Criteria Decision-Making (MCDM) technique to address RPN calculations. This study involved the design of a flexible fetoscope for minimally invasive fetal intervention, analyzing and evaluating risks. The cascading FMEA framework had two stages for data collection, namely risk identification by individual interview and risk evaluation by individual email. The cascading Delphi FMEA framework with MCDM identified the potential risks for the mother at the tip (risk score = 0.927) and subsequent risks such as debris loss (risk score = 0.896), material degradation (risk score = 0.896), and glue dislodging (risk score = 0.896) as critical issues. By identifying failure modes early, medical device designers can better mitigate risks during the initial design stages. Full article
25 pages, 1187 KiB  
Review
SARS-CoV-2 Replication Revisited: Molecular Insights and Current and Emerging Antiviral Strategies
by Bryan John J. Subong and Imelda L. Forteza
COVID 2025, 5(6), 85; https://doi.org/10.3390/covid5060085 - 30 May 2025
Viewed by 82
Abstract
The replication machinery of SARS-CoV-2 is a primary target for therapeutic intervention, and has led to significant progress in antiviral medication discovery. This review consolidates contemporary molecular insights into viral replication and rigorously assesses treatment methods at different phases of viruses’ clinical development. [...] Read more.
The replication machinery of SARS-CoV-2 is a primary target for therapeutic intervention, and has led to significant progress in antiviral medication discovery. This review consolidates contemporary molecular insights into viral replication and rigorously assesses treatment methods at different phases of viruses’ clinical development. Direct-acting antivirals, such as nucleoside analogs (e.g., remdesivir, molnupiravir) and protease inhibitors (e.g., nirmatrelvir), have shown clinical effectiveness in diminishing morbidity and hospitalization rates. Simultaneously, host-targeted medicines like baricitinib, camostat, and brequinar leverage critical host–virus interactions, providing additional pathways to reduce viral replication while possibly minimizing the development of resistance. Notwithstanding these advancements, constraints in distribution methods, antiviral longevity, and the risk of mutational evasion demand novel strategies. Promising investigational approaches encompass CRISPR-mediated RNA degradation systems, inhalable siRNA-nanoparticle conjugates, and molecular glue degraders that target host and viral proteins. Furthermore, next-generation treatments aimed at underutilized enzyme domains (e.g., NiRAN, ExoN) and host chaperone systems (e.g., TRiC complex) signify a transformative approach in antiviral targeting. The integration of high-throughput phenotypic screening, AI-driven medication repurposing, and systems virology is transforming the antiviral discovery field. An ongoing interdisciplinary endeavor is necessary to convert these findings into versatile, resistance-resistant antiviral strategies that are applicable beyond the present pandemic and in future coronavirus epidemics. Full article
(This article belongs to the Special Issue New Antivirals against Coronaviruses)
11 pages, 2541 KiB  
Article
Predicting Early Outcomes of Prostatic Artery Embolization Using n-Butyl Cyanoacrylate Liquid Embolic Agent: A Machine Learning Study
by Burak Berksu Ozkara, David Bamshad, Ramita Gowda, Mert Karabacak, Vivian Bishay, Kirema Garcia-Reyes, Ardeshir R. Rastinehad, Dan Shilo and Aaron Fischman
Diagnostics 2025, 15(11), 1351; https://doi.org/10.3390/diagnostics15111351 - 28 May 2025
Viewed by 47
Abstract
Background/Objectives: Prostatic artery embolization (PAE) has been increasingly recognized, especially with recent progress in embolization techniques for the management of lower urinary tract symptoms due to benign prostatic hyperplasia. Nevertheless, a proportion of patients undergoing PAE fail to demonstrate clinical improvement. Machine [...] Read more.
Background/Objectives: Prostatic artery embolization (PAE) has been increasingly recognized, especially with recent progress in embolization techniques for the management of lower urinary tract symptoms due to benign prostatic hyperplasia. Nevertheless, a proportion of patients undergoing PAE fail to demonstrate clinical improvement. Machine learning models have the potential to provide valuable prognostic insights for patients undergoing PAE. Methods: A retrospective cohort study was performed utilizing a modified prior-data fitted network architecture to predict short-term (7 weeks) favorable outcomes, defined as a reduction greater than 9 points in the International Prostate Symptom Score (IPSS), in patients who underwent PAE with nBCA glue. Patients were stratified into two groups based on the median IPSS reduction value, and a binary classification model was developed to predict the outcome of interest. The model was developed using clinical tabular data, including both pre-procedural and intra-procedural variables. SHapley Additive ExPlanations (SHAP) were used to uncover the relative importance of features. Results: The final cohort included 109 patients. The model achieved an accuracy of 0.676, an MCC of 0.363, a precision of 0.666, a recall of 0.856, an F1-score of 0.731, and a Brier score of 0.203, with an AUPRC of 0.851 and an AUROC of 0.821. SHAP analysis identified pre-PAE IPSS, prior therapy, right embolization volume, preoperative quality of life, and age as the top five most influential features. Conclusions: Our model showed promising discrimination and calibration in predicting early outcomes of PAE with nBCA glue, highlighting the potential of precision medicine to deliver interpretable, individualized risk assessments. Full article
(This article belongs to the Special Issue Artificial Intelligence for Health and Medicine)
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15 pages, 2498 KiB  
Article
Research on Image Stitching Based on an Improved LightGlue Algorithm
by Yuening Feng, Fei Zhang, Xiaozhan Li, Xiong Xiao, Lijun Wang and Xiaofei Xiang
Processes 2025, 13(6), 1687; https://doi.org/10.3390/pr13061687 - 28 May 2025
Viewed by 78
Abstract
In traditional centralized steel plant production monitoring systems, there are two major problems. On the one hand, the limited shooting angles of cameras make it impossible to capture comprehensive information. On the other hand, using multiple cameras to display monitoring screens separately on [...] Read more.
In traditional centralized steel plant production monitoring systems, there are two major problems. On the one hand, the limited shooting angles of cameras make it impossible to capture comprehensive information. On the other hand, using multiple cameras to display monitoring screens separately on a large screen leads to clutter and easy omission of key information. To address the above-mentioned issues, this paper proposes an image stitching technique based on an improved LightGlue algorithm. First of all, this paper employs the SuperPoint (Self-Supervised Interest Point Detection and Description) algorithm as the feature extraction algorithm. The experimental results show that this algorithm outperforms traditional algorithms both in terms of feature extraction speed and extraction accuracy. Then, the LightGlue (Local Feature Matching at Light Speed) algorithm is selected as the feature matching algorithm, and it is optimized and improved by combining it with the Agglomerative Clustering (AGG) algorithm. The experimental results indicate that this improvement effectively increases the speed of feature matching. Compared with the original LightGlue algorithm, the matching efficiency is improved by 26.2%. Finally, aiming at the problems of parallax and ghosting existing in the image fusion process, this paper proposes a pixel dynamic adaptive fusion strategy. A local homography matrix strategy is proposed in the geometric alignment stage, and a pixel difference fusion strategy is proposed in the pixel fusion stage. The experimental results show that this improvement successfully solves the problems of parallax and ghosting and achieves a good image stitching effect. Full article
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29 pages, 2702 KiB  
Article
IFMIR-VR: Visual Relocalization for Autonomous Vehicles Using Integrated Feature Matching and Image Retrieval
by Gang Li, Xiaoman Xu, Jian Yu and Hao Luo
Appl. Sci. 2025, 15(10), 5767; https://doi.org/10.3390/app15105767 - 21 May 2025
Viewed by 118
Abstract
Relocalization technology is an important part of autonomous vehicle navigation. It allows the vehicle to find its position on the map after a reboot. This paper presents a relocalization algorithm framework that uses image retrieval techniques. An integrated matching algorithm is applied during [...] Read more.
Relocalization technology is an important part of autonomous vehicle navigation. It allows the vehicle to find its position on the map after a reboot. This paper presents a relocalization algorithm framework that uses image retrieval techniques. An integrated matching algorithm is applied during the feature matching process. This improves the accuracy of the vehicle’s relocalization. We use image retrieval to select the most relevant image from the map database. The integrated matching algorithm then finds precise feature correspondences. Using these correspondences and depth information, we calculate the vehicle’s global pose with the Perspective-n-Point (PnP) and Levenberg–Marquardt (L-M) algorithms. This process helps the vehicle determine its position on the map. Experimental results on public datasets show that the proposed framework outperforms existing methods like LightGlue and LoFTR in terms of matching accuracy. Full article
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18 pages, 789 KiB  
Review
Perspective on Perinatal Birth Canal Injuries: An Analysis of Risk Factors, Injury Mechanisms, Treatment Methods, and Patients’ Quality of Life: A Literature Review
by Patrycja Głoćko, Sylwia Janczak, Agnieszka Nowosielska-Ogórek, Wiktoria Patora, Olga Wielgoszewska, Mateusz Kozłowski and Aneta Cymbaluk-Płoska
J. Clin. Med. 2025, 14(10), 3583; https://doi.org/10.3390/jcm14103583 - 20 May 2025
Viewed by 164
Abstract
Perineal injuries are a common complication of vaginal delivery, affecting 75–85% of women. This review examines current knowledge on risk factors, classification, treatment, and quality of life impacts. Risk factors are divided into maternal, foetal, and labour-related categories. Treatment depends on injury severity. [...] Read more.
Perineal injuries are a common complication of vaginal delivery, affecting 75–85% of women. This review examines current knowledge on risk factors, classification, treatment, and quality of life impacts. Risk factors are divided into maternal, foetal, and labour-related categories. Treatment depends on injury severity. First-degree tears can be managed conservatively, with skin glue or suturing—preferably with synthetic absorbable sutures to reduce pain and infection risk. Second-degree tears and episiotomies respond best to continuous non-locking sutures, improving healing, and minimizing postpartum pain. Severe third- and fourth-degree tears require specialised surgical techniques, such as the overlay method for anal sphincter repair, which improves faecal continence. Proper preoperative care, including antibiotics and anaesthesia, enhances outcomes. Episiotomy is controversial; selective use based on clinical indications is recommended over routine practice. Research shows no significant long-term benefits compared to spontaneous tears, and links episiotomy to psychological distress and negative body image. Preventative strategies, like perineal massage and warm compresses during labour, may reduce the risk of severe trauma, particularly in first-time mothers. Perineal trauma can have lasting physical and psychological effects, impacting sexual function, continence, and mental health. Proper diagnosis, treatment, and postpartum care are essential. Future studies should aim to standardise care protocols and explore long-term outcomes to enhance patient quality of life. Full article
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13 pages, 2101 KiB  
Article
Design and Synthesis of E7820/Tasisulam Hybrids as Potential DCAF15 Binders
by Sofiane Hocine, Victor Cosson, Remi Calandrino, Timea Baló, Jayson Alves Bordelo, Sébastien Triboulet, Laure Caruana, Laurence Klipfel, Sandrine Calis, András Herner and Stephen Hanessian
Reactions 2025, 6(2), 34; https://doi.org/10.3390/reactions6020034 - 20 May 2025
Viewed by 175
Abstract
We describe the design and synthesis of a series of N-[arylsulfonyl]-1H-pyrrole-2-carboxamides as hybrid analogs of the DCAF15 binders E7820 and tasisulam, two representative SPLAMs (sulfonamide-containing molecular glues). These hybrid molecules were designed to combine the key interactions of both parent ligands within the [...] Read more.
We describe the design and synthesis of a series of N-[arylsulfonyl]-1H-pyrrole-2-carboxamides as hybrid analogs of the DCAF15 binders E7820 and tasisulam, two representative SPLAMs (sulfonamide-containing molecular glues). These hybrid molecules were designed to combine the key interactions of both parent ligands within the DCAF15 binding site, as supported by docking studies. Binding affinity was evaluated using fluorescence polarization assays, and structure–activity relationships were established, highlighting the importance of dichlorinated pyrrole moieties. Selected compounds were also tested in HCT116 cells to assess in vitro activity. Full article
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23 pages, 12437 KiB  
Article
Vision-Based Structural Adhesive Detection for Electronic Components on PCBs
by Ruzhou Zhang, Tengfei Yan and Jian Zhang
Electronics 2025, 14(10), 2045; https://doi.org/10.3390/electronics14102045 - 17 May 2025
Viewed by 251
Abstract
Structural adhesives or fixing glues are typically applied to larger components on printed circuit boards (PCBs) to increase mechanical stability and minimize damage from vibration. Existing work tends to focus on component placement verification and solder joint analysis, etc. However, the detection of [...] Read more.
Structural adhesives or fixing glues are typically applied to larger components on printed circuit boards (PCBs) to increase mechanical stability and minimize damage from vibration. Existing work tends to focus on component placement verification and solder joint analysis, etc. However, the detection of structural adhesives remains largely unexplored. This paper proposes a vision-based method for detecting structural adhesive defects on PCBs. The method uses HSV color segmentation to extract PCB regions, followed by Hough-transform-based morphological analysis to identify board features. The perspective transformation then extracts and rectifies the adhesive regions, and constructs an adhesive region template by detecting the standard adhesive area ratio in its corresponding adhesive region. Finally, template matching is used to detect the structural adhesives. The experimental results show that this approach can accurately detect the adhesive state of PCBs and identify the qualified/unqualified locations, providing an effective vision-based detection scheme for PCB manufacturing. The main contributions of this paper are as follows: (1) A vision-based structural adhesive detection method is proposed, and its detailed algorithm is presented. (2) The developed system includes a user-friendly visualization interface, streamlining the inspection workflow. (3) Actual experiments are performed to evaluate this study, and the results validate its effectiveness. Full article
(This article belongs to the Section Computer Science & Engineering)
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22 pages, 2169 KiB  
Article
How Do Innovation-Driven Policies Affect Urban Green Land Use Efficiency? Evidence from China’s Innovative City Pilot Policy
by Xinfeng Zuo and Xiekui Zhang
Land 2025, 14(5), 1034; https://doi.org/10.3390/land14051034 - 9 May 2025
Viewed by 324
Abstract
China has already joined the ranks of innovative nations. Accelerating technological innovation to lead a green transformation in land use is an urgent requirement for promoting ecological civilization and, in turn, driving high-quality economic development. This study examines urban data spanning from 2006 [...] Read more.
China has already joined the ranks of innovative nations. Accelerating technological innovation to lead a green transformation in land use is an urgent requirement for promoting ecological civilization and, in turn, driving high-quality economic development. This study examines urban data spanning from 2006 to 2021, focusing on cities classified at the prefecture level or above. Employing the Chinese Innovative City Pilot Policy (ICPP) as a quasi-natural experiment, this study utilizes a super-efficiency Slack-Based Measure (SBM) model that incorporates undesirable outputs to assess Green Land Use Efficiency (GLUE). Additionally, a multi-period Difference-in-Differences (DID) model, combined with a mediation effect model, is employed to evaluate the influence of innovation-driven policies on GLUE. The findings are as follows: (1) Although GLUE showed variability throughout the study period, it generally trended upwards, with significant improvements noted in the eastern regions and coastal city clusters. (2) Innovation-driven policies have effectively enhanced urban GLUE, a conclusion supported by extensive robustness tests. (3) The heterogeneity investigation indicates that the ICPP’s impact on GLUE is more significant in cities with advantageous geographic locations, increased environmental awareness, and strong market potential. (4) A mechanism analysis demonstrates that the ICPP positively influences GLUE by reducing urban sprawl and promoting the concentration of digital service industries. Based on these results, this study proposes policy recommendations aimed at refining innovation-driven approaches to improve urban GLUE. These recommendations are pivotal in promoting a green, low-carbon transformation in China’s economic and social development. Full article
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136 pages, 24434 KiB  
Perspective
Alzheimer’s Is a Multiform Disease of Sustained Neuronal Integrated Stress Response Driven by the C99 Fragment Generated Independently of AβPP; Proteolytic Production of Aβ Is Suppressed in AD-Affected Neurons: Evolution of a Theory
by Vladimir Volloch and Sophia Rits-Volloch
Int. J. Mol. Sci. 2025, 26(9), 4252; https://doi.org/10.3390/ijms26094252 - 29 Apr 2025
Viewed by 718
Abstract
The present Perspective analyzes the remarkable evolution of the Amyloid Cascade Hypothesis 2.0 (ACH2.0) theory of Alzheimer’s disease (AD) since its inception a few years ago, as reflected in the diminishing role of amyloid-beta (Aβ) in the disease. In the initial iteration of [...] Read more.
The present Perspective analyzes the remarkable evolution of the Amyloid Cascade Hypothesis 2.0 (ACH2.0) theory of Alzheimer’s disease (AD) since its inception a few years ago, as reflected in the diminishing role of amyloid-beta (Aβ) in the disease. In the initial iteration of the ACH2.0, Aβ-protein-precursor (AβPP)-derived intraneuronal Aβ (iAβ), accumulated to neuronal integrated stress response (ISR)-eliciting levels, triggers AD. The neuronal ISR, in turn, activates the AβPP-independent production of its C99 fragment that is processed into iAβ, which drives the disease. The second iteration of the ACH2.0 stemmed from the realization that AD is, in fact, a disease of the sustained neuronal ISR. It introduced two categories of AD—conventional and unconventional—differing mainly in the manner of their causation. The former is caused by the neuronal ISR triggered by AβPP-derived iAβ, whereas in the latter, the neuronal ISR is elicited by stressors distinct from AβPP-derived iAβ and arising from brain trauma, viral and bacterial infections, and various types of inflammation. Moreover, conventional AD always contains an unconventional component, and in both forms, the disease is driven by iAβ generated independently of AβPP. In its third, the current, iteration, the ACH2.0 posits that proteolytic production of Aβ is suppressed in AD-affected neurons and that the disease is driven by C99 generated independently of AβPP. Suppression of Aβ production in AD seems an oxymoron: Aβ is equated with AD, and the later is inconceivable without the former in an ingrained Amyloid Cascade Hypothesis (ACH)-based notion. But suppression of Aβ production in AD-affected neurons is where the logic leads, and to follow it we only need to overcome the inertia of the preexisting assumptions. Moreover, not only is the generation of Aβ suppressed, so is the production of all components of the AβPP proteolytic pathway. This assertion is not a quantum leap (unless overcoming the inertia counts as such): the global cellular protein synthesis is severely suppressed under the neuronal ISR conditions, and there is no reason for constituents of the AβPP proteolytic pathway to be exempted, and they, apparently, are not, as indicated by the empirical data. In contrast, tau protein translation persists in AD-affected neurons under ISR conditions because the human tau mRNA contains an internal ribosomal entry site in its 5′UTR. In current mouse models, iAβ derived from AβPP expressed exogenously from human transgenes elicits the neuronal ISR and thus suppresses its own production. Its levels cannot principally reach AD pathology-causing levels regardless of the number of transgenes or the types of FAD mutations that they (or additional transgenes) carry. Since the AβPP-independent C99 production pathway is inoperative in mice, the current transgenic models have no potential for developing the full spectrum of AD pathology. What they display are only effects of the AβPP-derived iAβ-elicited neuronal ISR. The paper describes strategies to construct adequate transgenic AD models. It also details the utilization of human neuronal cells as the only adequate model system currently available for conventional and unconventional AD. The final alteration of the ACH2.0, introduced in the present Perspective, is that AβPP, which supports neuronal functionality and viability, is, after all, potentially produced in AD-affected neurons, albeit not conventionally but in an ISR-driven and -compatible process. Thus, the present narrative begins with the “omnipotent” Aβ capable of both triggering and driving the disease and ends up with this peptide largely dislodged from its pedestal and retaining its central role in triggering the disease in only one, although prevalent (conventional), category of AD (and driving it in none). Among interesting inferences of the present Perspective is the determination that “sporadic AD” is not sporadic at all (“non-familial” would be a much better designation). The term has fatalistic connotations, implying that the disease can strike at random. This is patently not the case: The conventional disease affects a distinct subpopulation, and the basis for unconventional AD is well understood. Another conclusion is that, unless prevented, the occurrence of conventional AD is inevitable given a sufficiently long lifespan. This Perspective also defines therapeutic directions not to be taken as well as auspicious ways forward. The former category includes ACH-based drugs (those interfering with the proteolytic production of Aβ and/or depleting extracellular Aβ). They are legitimate (albeit inefficient) preventive agents for conventional AD. There is, however, a proverbial snowball’s chance in hell of them being effective in symptomatic AD, lecanemab, donanemab, and any other “…mab” or “…stat” notwithstanding. They comprise Aβ-specific antibodies, inhibitors of beta- and gamma-secretase, and modulators of the latter. In the latter category, among ways to go are the following: (1) Depletion of iAβ, which, if sufficiently “deep”, opens up a tantalizing possibility of once-in-a-lifetime preventive transient treatment for conventional AD and aging-associated cognitive decline, AACD. (2) Composite therapy comprising the degradation of C99/iAβ and concurrent inhibition of the neuronal ISR. A single transient treatment could be sufficient to arrest the progression of conventional AD and prevent its recurrence for life. Multiple recurrent treatments would achieve the same outcome in unconventional AD. Alternatively, the sustained reduction/removal of unconventional neuronal ISR-eliciting stressors through the elimination of their source would convert unconventional AD into conventional one, preventable/treatable by a single transient administration of the composite C99/iAβ depletion/ISR suppression therapy. Efficient and suitable ISR inhibitors are available, and it is explicitly clear where to look for C99/iAβ-specific targeted degradation agents—activators of BACE1 and, especially, BACE2. Directly acting C99/iAβ-specific degradation agents such as proteolysis-targeting chimeras (PROTACs) and molecular-glue degraders (MGDs) are also viable options. (3) A circumscribed shift (either upstream or downstream) of the position of transcription start site (TSS) of the human AβPP gene, or, alternatively, a gene editing-mediated excision or replacement of a small, defined segment of its portion encoding 5′-untranslated region of AβPP mRNA; targeting AβPP RNA with anti-antisense oligonucleotides is another possibility. If properly executed, these RNA-based strategies would not interfere with the protein-coding potential of AβPP mRNA, and each would be capable of both preventing and stopping the AβPP-independent generation of C99 and thus of either preventing AD or arresting the progression of the disease in its conventional and unconventional forms. The paper is interspersed with “validation” sections: every conceptually significant notion is either validated by the existing data or an experimental procedure validating it is proposed. Full article
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17 pages, 39370 KiB  
Article
Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization
by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi and Ying Liu
Sensors 2025, 25(8), 2541; https://doi.org/10.3390/s25082541 - 17 Apr 2025
Viewed by 334
Abstract
Particleboard is an important forest product that can be reprocessed using wood processing by-products. This approach has the potential to achieve significant conservation of forest resources and contribute to the protection of forest ecology. Most current detection models require a significant number of [...] Read more.
Particleboard is an important forest product that can be reprocessed using wood processing by-products. This approach has the potential to achieve significant conservation of forest resources and contribute to the protection of forest ecology. Most current detection models require a significant number of tagged samples for training. However, with the advancement of industrial technology, the prevalence of surface defects in particleboard is decreasing, making the acquisition of sample data difficult and significantly limiting the effectiveness of model training. Deep reinforcement learning-based detection methods have been shown to exhibit strong generalization ability and sample utilization efficiency when the number of samples is limited. This paper focuses on the potential application of deep reinforcement learning in particleboard defect detection and proposes a novel detection method, PPOBoardNet, for the identification of five typical defects: dust spot, glue spot, scratch, sand leak and indentation. The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. In addition, this paper proposes a state characterization strategy of multi-scale feature fusion, which integrates global features, local features and historical action sequences of the defect image and provides reliable guidance for action selection. On the particleboard defect dataset with limited images, PPOBoardNet achieves a mean average precision (mAP) of 79.0%, representing a 5.3% performance improvement over the YOLO series of optimal detection models. This result provides a novel technical approach to the challenge of defect detection with limited samples in the particleboard domain, with significant practical application value. Full article
(This article belongs to the Special Issue Sensing and Imaging for Defect Detection: 2nd Edition)
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21 pages, 15502 KiB  
Article
Multi-Scale Spatiotemporal Feature Enhancement and Recursive Motion Compensation for Satellite Video Geographic Registration
by Yu Geng, Jingguo Lv, Shuwei Huang and Boyu Wang
J. Imaging 2025, 11(4), 112; https://doi.org/10.3390/jimaging11040112 - 8 Apr 2025
Viewed by 369
Abstract
Satellite video geographic alignment can be applied to target detection and tracking, true 3D scene construction, image geometry measurement, etc., which is a necessary preprocessing step for satellite video applications. In this paper, a multi-scale spatiotemporal feature enhancement and recursive motion compensation method [...] Read more.
Satellite video geographic alignment can be applied to target detection and tracking, true 3D scene construction, image geometry measurement, etc., which is a necessary preprocessing step for satellite video applications. In this paper, a multi-scale spatiotemporal feature enhancement and recursive motion compensation method for satellite video geographic alignment is proposed. Based on the SuperGlue matching algorithm, the method achieves automatic matching of inter-frame image points by introducing the multi-scale dilated attention (MSDA) to enhance the feature extraction and adopting a joint multi-frame optimization strategy (MFMO), designing a recursive motion compensation model (RMCM) to eliminate the cumulative effect of the orbit error and improve the accuracy of the inter-frame image point matching, and using a rational function model to establish the geometrical mapping between the video and the ground points to realize the georeferencing of satellite video. The geometric mapping between video and ground points is established by using the rational function model to realize the geographic alignment of satellite video. The experimental results show that the method achieves the inter-frame matching accuracy of 0.8 pixel level, and the georeferencing accuracy error is 3 m, which is a significant improvement compared with the traditional single-frame method, and the method in this paper can provide a certain reference for the subsequent related research. Full article
(This article belongs to the Topic Computer Vision and Image Processing, 2nd Edition)
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16 pages, 3441 KiB  
Article
Utilization of Waste Rubber Materials After the End of Their Life Cycle in the Production of Three-Layer Particleboards—Physical and Mechanical Properties
by Vladimír Mancel, Iveta Čabalová, Jozef Krilek, Çağrı Olgun, Mustafa Öncel, Önder Tor, Tomasz Szul, Grzegorz Woroniak and Joanna Piotrowska-Woroniak
Polymers 2025, 17(7), 998; https://doi.org/10.3390/polym17070998 - 7 Apr 2025
Viewed by 566
Abstract
The aim of the article was to test new types of rubber-containing particleboards created from waste materials, which positively contributes to environmental protection, saving primary resources and reducing production costs. This article focuses on the study of three-layer particleboards made from wood particles [...] Read more.
The aim of the article was to test new types of rubber-containing particleboards created from waste materials, which positively contributes to environmental protection, saving primary resources and reducing production costs. This article focuses on the study of three-layer particleboards made from wood particles (spruce non-treated beams) and waste rubber granulates (tires, mixture of seals and carpets, internal flammable cables, external non-flammable cables). Urea–formaldehyde glue, melamine–formaldehyde glue, paraffin emulsion, and ammonium nitrate were used as a binders and excipients in the manufacturing of particleboards. In the core layer of each particleboard, 10% of the weight was made up of rubber granulate. Physical properties (density, water absorption, thickness swelling) and mechanical properties (internal bonding strength, modulus of rupture, modulus of elasticity, screw driving torque) were assessed from this perspective using current EN technical standards. According to the findings, the average densities of all particleboards were comparable to each other in a range from 0.692 to 0.704 g·cm−3. The lowest average water absorption and thickness swelling reached particleboards containing 10% of waste internal flammable cables, namely 32.79% for water absorption and 13.21% for thickness swelling. The highest average internal bonding strength reached particleboards without rubber filler and particleboards containing 10% of waste external non-flammable cables, namely 0.52 MPa for both types. The highest average modulus of rupture reached particleboards without rubber filler, namely 12.44 MPa. The highest average modulus of elasticity reached particleboards containing 10% of waste internal flammable cables, namely 2206.29 MPa, and the highest screw driving torque reached particleboards without rubber filler, namely 0.46 N·m for seating torque and 1.44 N·m for stripping torque. The results show that particleboards containing waste external non-flammable cables and particleboards containing waste internal flammable cables achieved comparable results to particleboards without rubber filler, which provides a good basis for a new way of utilizing this type of waste in the form of producing new wood–rubber composites. Full article
(This article belongs to the Special Issue Life Cycle and Utilization of Lignocellulosic Materials)
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