Search Results (6,420)

We modelled, for the first time, the seasonal dynamics and long-term trends of Abies marocana forests (Rif Mountains, northern Morocco) using remote-sensing-derived vegetation indices. Using the MODIS Terra Vegetation Indices product MOD13Q1 (enhanced vegetation index, EVI; 16-day frequency; 250 m spatial resolution) from 2000 to 2024 (575 images over 25 years), we applied a robust seasonal trend analysis (RSTA) workflow, representing an inferential extension of classical seasonal trend analysis (STA) through the explicit control of Type I error under serial and spatial correlation. This approach combined: (i) harmonic regression to capture the annual and semi-annual cycles of A. marocana forests, estimating seasonal amplitudes and phases while filtering out low-frequency noise; (ii) an iterative trend-free prewhitening (TFPW) procedure following Wang and Swail, applied only to time series with significant serial autocorrelation according to the Durbin–Watson test; (iii) the Theil–Sen slope (TS) estimator, a robust non-parametric method, to quantify the magnitude and direction of seasonality trends; (iv) the contextual Mann–Kendall (CMK) test to assess the statistical significance of seasonality trends, while correcting for spatial autocorrelation and accounting for cross-correlation among neighbouring pixels; (v) the Benjamini–Hochberg (BH) procedure to control the false discovery rate (FDR), ensuring that only statistically robust seasonality trends were retained; and (vi) reconstruction of seasonal curves representing the beginning and end of the study period and derivation of phenological metrics from the statistically significant seasonal trends retained after inferential filtering. After applying the complete analytical workflow, statistically significant trends were detected in 79.2% of pixels within A. marocana forests, compared with 86.4% when prewhitening and false discovery rate control were not applied. All Theil–Sen slopes retained by the RSTA workflow were positive, with a mean slope of approximately 0.00175 EVI year⁻¹, corresponding to an average annual increase of roughly 0.7% and an overall increase of approximately 15% over the 2000–2024 study period relative to the initial mean EVI conditions. Browning trends identified by classical STA were not supported after inferential filtering and FDR control, indicating that all these patterns were spurious or only marginal, and confined to limited areas and edge zones. The reconstructed seasonal trend curves were consistent with a longer growing season, although this inference is based on land-surface vegetation dynamics rather than direct phenological observations. The long-term ecological consequences of these changes in seasonal vegetation activity will hinge on the interactions among warming, rising water demand, and potential disturbance regimes under future climatic conditions. Full article

Background/Objectives: The G protein-coupled estrogen receptor (GPER) is known to interact with cellular stress responses and DNA damage pathways. Therefore, exposure to ionizing radiation may modulate the biological consequences of single-nucleotide polymorphisms in the GPR30 gene. This study aims to evaluate the association between GPER polymorphisms and radiation sensitivity. Methods: The study included 50 healthcare workers exposed to ionizing radiation and 36 healthy individuals with no known occupational exposure to radiation. Genomic DNA was isolated and PCR products were purified using GeneAll kits. Genomic regions encompassing three GPER single-nucleotide polymorphisms (rs3808350, rs3808351, and rs11544331) were amplified by polymerase chain reaction (PCR), followed by DNA sequencing analysis using the BigDye Cycle Sequencing Kit. In addition, an in silico functional and clinical annotation of rs11544331 was performed using Ensembl VEP, SIFT, PolyPhen-2, AlphaMissense, CADD, UniProt, and ClinVar. Results: Genotypic, dominant, and allelic analyses revealed no significant association between radiation exposure and the rs3808350 or rs3808351 polymorphisms. In contrast, a statistically significant association was observed for rs11544331. The frequency of individuals carrying the CT and TT genotypes (CT + TT) was significantly higher in the ionizing radiation-exposed group compared with the control group (OR = 2.981; 95% CI: 1.106–7.904; p = 0.0241). In allelic analysis, the T allele was more prevalent in the exposed group and was significantly associated with radiation exposure (OR = 2.959; 95% CI: 1.282–6.606; p = 0.0110). In silico analysis confirmed that rs11544331 corresponds to the p.Pro16Leu substitution in GPER1; however, SIFT, PolyPhen-2, AlphaMissense, CADD, and ClinVar consistently indicated a tolerated, benign, likely benign, or low-deleteriousness profile. Conclusions: GPER-mediated stress responses and genetic polymorphisms may play a potential role in determining genetic susceptibility following exposure to ionizing radiation. Full article

Thisstudy investigates the reliability of power-terminal solder joints in intelligent power modules (IPMs) subjected to thermal cycling, random vibration, and packaging/assembly-induced deformation. Fifty IPMs were tested under temperature cycling from −55 °C to 125 °C and random vibration from 20 to 2000 Hz, and the experimental observations were combined with finite element simulations of thermal, vibration, and deformation loads. The modules survived 200 temperature cycles in the free state, whereas functional abnormalities occurred after board-level assembly and subsequent environmental loading. Simulation results showed that random vibration produced limited solder-layer stress because the first structural mode was above the excitation range, while packaging and PCB deformation markedly increased the initial stress of the power-terminal solder joints. When local deformation reached approximately 0.5 mm, the calculated solder-pad stress reached or exceeded the shear-strength risk range, consistent with the failure tendency observed in highly deformed modules. Weibull analysis further indicated a fatigue-dominated failure process with an increasing failure rate. These findings suggest that deformation control, package stiffness improvement, and assembly flatness management are critical for improving the reliability of IPM power-terminal solder joints. Full article

Background/Objectives: DNA-targeting small molecules that induce replication stress represent a promising strategy in anticancer drug development. 1,8-Naphthalimide (NI) derivatives are well-established DNA-intercalating agents, and heterocyclic annulation offers a rational approach to enhancing their potency and tumor selectivity. Here, we report the synthesis and biological evaluation of a novel series of benzofuran-containing naphthalimide derivatives, with particular focus on the lead dinitro-substituted compound 5d. Methods: Cytotoxic activity was assessed using the MTT assay in A549 (p53 wild-type), H1299 (p53-null), and MRC-5 cells. Long-term antiproliferative effects were evaluated by clonogenic survival assay. Cell cycle distribution was analyzed by propidium iodide staining and flow cytometry. Replication stress and DNA damage were quantified by EdU incorporation and γH2AX immunofluorescence, respectively. Apoptosis was assessed by Annexin V/PI staining and caspase-3/7 activation assay. p53 nuclear accumulation and autophagy induction were evaluated by immunofluorescence and Western blot, using LC3 as an autophagic marker. Results: All compounds exhibited cytotoxic activity in the nanomolar range, with 5d emerging as the most potent and selective. Clonogenic survival was significantly reduced, indicating durable suppression of proliferative capacity. Treatment with 5d induced G₁ arrest in A549 cells and the accumulation of H1299 cells in G₂/M, consistent with p53-dependent and p53-independent checkpoint activation, respectively. EdU incorporation was markedly reduced, while γH2AX intensity increased, collectively supporting a replication stress-driven mechanism of DNA damage. Apoptosis was confirmed by increased Annexin V-positive populations and caspase-3/7 activation. LC3 puncta formation and LC3-I/LC3-II conversion were increased, indicating LC3 processing and autophagosome accumulation consistent with the activation of autophagy-related processes. Conclusions: 5d induces a cellular phenotype consistent with replication stress, including reduced EdU incorporation, γH2AX accumulation, cell cycle arrest, and apoptotic cell death in a p53 status-dependent manner. These findings establish benzofuran-annulated naphthalimides as a promising scaffold for the development of anticancer agents that exploit replication stress vulnerabilities in tumor cells. Full article

Background: Epidemiological data link hard and chlorinated water to atopic dermatitis (AD), but experimental evidence on their effect and on dermocosmetic benefit remains limited. Objectives: We aimed to compare the effects of soft, hard, and chlorinated water on atopic skin and assess whether a dermocosmetic routine mitigates these effects. Methods: In a 3-day, open-label, intra-individual study, 66 adults with atopic skin underwent repeated forearm immersions (five cycles/day) in soft, hard, or chlorinated water. One forearm received a cleansing-oil and moisturising-balm routine after each cycle; the contralateral forearm served as untreated control. TEWL, hydration, and global discomfort were assessed. In a 21-day real-life study, adults with AD regularly exposed to hard domestic or swimming-pool water used the routine daily. Discomfort and quality of life were recorded. Results: Water immersion induced modest, inconsistent TEWL changes, increased hydration and slightly reduced discomfort, without differences between water types. The routine reduced TEWL, increased hydration, and decreased discomfort for all water types. In real life, it produced immediate and sustained improvements in discomfort and quality of life. Conclusions: Under controlled exposure, soft, hard, and chlorinated water exert comparable, limited effects on atopic skin. The dermocosmetic routine consistently improves barrier-related parameters and comfort, independently of water type. Full article

Background/Objectives: Glucocorticoids, including dexamethasone (DEX), are known to demonstrate anti-inflammatory activity, suppress steroidogenesis, and mitigate the adverse effects of chemotherapy. They are therefore widely employed for managing solid malignancies. Emerging evidence indicates that DEX modulates both systemic and local renin–angiotensin system (RAS) activity, including genomic signaling via the glucocorticoid receptor (GR). Methods: DEX-dependent transcriptional responses for the angiotensin receptor genes (AGTR1, AGTR2, MAS1, and LNPEP) were evaluated in ovarian (SKOV3, KURAMOCHI) and prostate (DU-145, PC3) cancer cell lines. The cells were cultured under different serum conditions to determine the influence of nutrient availability on tumor progression. Results: DEX demonstrated distinct mechanisms of action between the ovarian and prostate cancer models. It was found to promote cancer cell survival through tissue-specific modulation of metabolic activity, clonogenic capacity, cell cycle distribution, and apoptotic responses. These effects were accompanied by condition-dependent alterations in angiotensin receptor gene expression. Hence, DEX may mediate the remodeling of local RAS signaling, which may be significant in overall survival and disease-free survival. The findings also indicate a previously-unreported NR3C1–LNPEP correlation, which was consistently observed across in vitro systems and patient datasets, in both ovarian- and prostate-derived cancer models. Conclusions: DEX appears to exert context-dependent regulation of RAS-associated gene networks in ovarian and prostate cancer, suggesting a role in tumor adaptive responses and potentially in therapeutic contexts. Full article

Background: Immune checkpoint inhibitors have significantly improved survival in metastatic melanoma. Combination nivolumab plus ipilimumab demonstrated superior efficacy in randomized trials, including CheckMate 067, but data beyond the first-line setting remain limited. This study evaluated real-world outcomes and predictors of response across different lines of therapy, with an exploratory comparison between first- and second-line use. Methods: This retrospective single-center study included patients with metastatic melanoma treated with nivolumab plus ipilimumab as first- or second-line therapy at Moscow City Oncology Hospital No. 62 between September 2015 and October 2023. Eligible patients had histologically confirmed melanoma and received at least one cycle of dual immune checkpoint blockade. Clinical and demographic data were extracted from electronic medical records. The primary endpoints were progression-free survival (PFS) and overall survival (OS); secondary endpoints included objective response rate (ORR) and safety. Survival outcomes were estimated using the Kaplan–Meier method and compared using the log-rank test. Multivariable Cox proportional hazards models adjusted for clinically relevant covariates were applied to evaluate the association between treatment line and survival outcomes. Additional prognostic analyses were performed using backward stepwise multivariable Cox regression. Results: Median follow-up was 18.2 months (IQR, 6.7–30.4). Median PFS in the overall cohort was 7.9 months (95% CI, 4.2–11.5), and median OS was not reached (NR); 5-year OS: 50%. The ORR was 45.8%, including 15.1% complete responses. Median PFS was 9.0 months (95% CI, 5.0–12.9) in first-line and 6.1 months (95% CI, 3.4–8.8) in second-line patients. Median OS was NR in the first-line cohort and was 30.5 months (95% CI: NR) in the second-line cohort. In exploratory analyses, OS did not differ significantly between patients treated in the first-line (n = 141) versus second-line setting (n = 63) (p = 0.848). After adjustment for clinical and demographic characteristics, line of therapy was not associated with OS (HR 0.93; 95% CI, 0.58–1.50; p = 0.762). Immune-related adverse events were associated with longer PFS (HR 0.66; 95% CI, 0.46–0.93), although this may reflect time-dependent bias. Conclusions: Nivolumab plus ipilimumab demonstrated clinically meaningful activity in both first- and second-line settings. Outcomes were numerically lower than in clinical trials, consistent with broader real-world populations. In exploratory analyses, OS did not differ significantly between treatment lines after adjustment for clinical and demographic characteristics. These findings should be interpreted with caution given the retrospective design and potential sources of bias. Full article

Cutaneous squamous cell carcinoma (cSCC) is one of the most common non-melanoma skin cancers worldwide. Although surgery and adjuvant therapies are often effective, the treatment of high-risk or advanced lesions remains challenging due to recurrence, resistance, toxicity, and limited long-term control. Natural compounds have, therefore, gained interest as multi-target agents for cancer prevention and treatment. This systematic review aimed to evaluate the antitumoral activity of natural compounds against cSCC. A systematic literature search was conducted following PRISMA 2020 guidelines. Sixty studies met the inclusion criteria and were analyzed using a conservative, mechanism-based classification framework. The included studies evaluated purified compounds, crude extracts, essential oils, formulations, photodynamic agents, and combination treatments. Despite chemical diversity, antitumoral activity converged on defined biological processes, including apoptosis, non-apoptotic regulated cell death, redox modulation, oncogenic signaling inhibition, cell-cycle arrest, epigenetic regulation, photodynamic ROS generation, and chemopreventive or immune-mediated mechanisms. Mechanistic specificity was higher among purified compounds, while complex extracts showed broader, context-dependent effects. Several agents demonstrated consistent in vitro and in vivo activity, which supports their translational relevance. Natural compounds target shared biological vulnerabilities in cSCC through mechanistically convergent pathways. The framework presented here supports mechanism-guided prioritization and may facilitate the translation of promising compounds into clinically relevant strategies. Full article

Base excision repair (BER) and nucleotide excision repair (NER) are traditionally regarded as independent pathways; however, accumulating evidence indicates that ultraviolet (UV)-damaged DNA-binding protein (UV-DDB), a core NER factor, stimulates BER DNA glycosylases, including alkyladenine DNA glycosylase (AAG). Despite this functional link, the molecular basis of the UV-DDB/AAG interaction and its regulation by DNA remain unclear. This study investigated the direct interaction between AAG and UV-DDB using electrophoretic mobility shift assays (EMSA), surface plasmon resonance (SPR), biolayer interferometry (BLI) and AlphaFold3-based structural modeling under DNA-free and DNA-bound conditions. SPR analysis revealed that AAG and UV-DDB form a high-affinity complex in the absence of DNA (K_D ≈ 17.5 nM), which is maintained but reduced approximately 2.6-fold upon binding to apurinic/apyrimidinic site (AP site)-containing dsDNA (K_D  ≈ 46.2 nM). BLI analysis independently confirmed this interaction under both DNA-free and DNA-bound conditions, with inter-platform differences consistent with previously reported BLI/SPR variability. EMSA showed UV-DDB-mediated ternary complex formation accompanied by redistribution of binary AAG/DNA species. AlphaFold3 modeling predicted that AAG associates with DDB1 in the DNA-free state, whereas under DNA-bound conditions, DDB2 recognizes the AP site while AAG repositions toward the lesion with multiple active site residues placed in close proximity. These findings support a model in which DNA binding acts as a molecular switch that reconfigures the UV-DDB/AAG interaction, potentially enabling UV-DDB to function as a recruitment platform that facilitates directional progression of AAG through the BER cycle, and providing a structural basis for coordinated integration of BER and NER. Full article

Reliable temperature monitoring is essential for the thermal management and safe operation of modern telecommunication equipment. However, conventional temperature sensors are often relatively large and rigid, which limits their applicability for localized temperature measurement on compact electronic components. In this study, a flexible thin-film thermocouple based on NiCr–NiSi thermoelectric materials was developed for temperature monitoring of telecommunication equipment. The sensor adopts a multilayer structure consisting of a polyimide (PI) flexible substrate, an Al₂O₃ insulating layer, NiCr and NiSi thermoelectric films, and a SiO protective layer and was fabricated using magnetron sputtering. Static calibration experiments show that the fabricated sensor exhibits a thermoelectric sensitivity of approximately 40.45 µV/°C, which is close to the reference value of conventional K-type thermocouples, with a relative error of about 1.34%. Repeated heating–cooling cycles demonstrate good repeatability and stable thermoelectric characteristics. Dynamic tests under representative transient thermal conditions showed that the sensor could continuously capture temperature variations without signal interruption or abnormal fluctuations. To further quantify its dynamic behavior, a numerical step-response simulation was performed for the PI/Al₂O₃/NiCr–NiSi/SiO multilayer structure. The simulated thermal time constant and curve-extracted 90% response time were 0.0343 s and 0.0803 s, respectively, under the specified boundary conditions. Owing to its small thickness, low thermal mass, and good mechanical flexibility, the proposed thin-film thermocouple can be conformally attached to compact and curved electronic surfaces, indicating promising potential for real-time localized temperature monitoring of telecommunication equipment and other compact electronic systems. Full article

Additive–subtractive hybrid manufacturing (ASHM) allows for the rapid manufacturing of metal components with complex and precise geometries for ready-to-use or near-ready-to-use applications. Laser wire-directed energy deposition (LW-DED) can be used to quickly manufacture metal components, while CNC machining can achieve precise geometric tolerances. In this study, Ti-6Al-4V alloy specimens were fabricated using an LW-DED process combined with CNC machining and tested to evaluate the effects of ASHM on mechanical performance. Post fabrication, the Ti-6Al-4V material was evaluated through hardness mapping, monotonic tensile testing, and fully reversed axial fatigue testing. Vicker’s micro-hardness mapping showed a range of hardness results from 300 to 350 HV in the ASHM Ti-6Al-4V that remained consistent throughout the build. Tensile results showed a similar response to cast and wrought Ti-6Al-4V, with an average yield stress of 819.4 MPa, ultimate tensile strength of 935.5 MPa, and modulus of 119 GPa. When tested in fatigue, the material had a reduced life compared to wrought Ti-6Al-4V, which is attributed to defects originating from the additive process. While no run-outs were observed from the testing, the fatigue results remain aligned with trends reported for other methods of additively manufactured Ti-6Al-4V. Fully reversed high-cycle fatigue loading revealed that the ASHM-fabricated Ti-6Al-4V fell into a Basquin power-law fit with a fatigue strength coefficient of 1942 MPa with a fatigue strength exponent of −0.115. The fatigue life of the ASHM material is found to be dependent on the resulting porosity of the material that stems from the LW-DED process used in the ASHM process described. Full article

Soil organic carbon (SOC) is closely linked to soil fertility, agricultural carbon cycling, and the functioning of cotton field ecosystems, and it provides essential information for sustainable soil management. Rapid and accurate SOC estimation is therefore important for assessing carbon sequestration potential and supporting low-carbon agricultural management. This study focused on cotton fields in northern Shawan City and used optical imagery, Synthetic Aperture Radar (SAR) imagery, and 140 ground-collected SOC samples to estimate SOC content with three machine learning models: Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Extreme Gradient Boosting (XGBoost). The Kennard–Stone algorithm was applied to partition the 140 SOC samples into training and validation subsets at a 7:3 ratio, ensuring a more representative distribution of samples. Model performance was evaluated using the coefficient of determination (R²) and root mean square error (RMSE), and SHapley Additive exPlanations (SHAP) was used to interpret feature contributions and SOC spatial variability. The results showed that: (1) optical features performed better than SAR features, while fused optical-SAR features achieved the highest accuracy; (2) XGBoost consistently outperformed RF and LightGBM, with the optimal model achieving R² = 0.726 and RMSE = 1.252% on the validation set; (3) SHAP analysis confirmed the dominant contribution of optical features to SOC estimation; and (4) the predicted SOC distribution showed higher values in the central study area, lower values in the northern and southern parts, and high-value zones mainly along both sides of the Manas River. By comparing optical, SAR, and fused features for SOC estimation in arid-zone cotton fields, this study provides methodological support for rapid SOC monitoring and sustainable soil management, and offers practical guidance for variable-rate fertilization and soil carbon sequestration planning along the Manas River corridor. Full article

This contribution presents a simulation-based approach for optimizing injection molding processes using digital twins. It combines surrogate modeling via response surface methodology (RSM) with the evolutionary algorithm NSGA-II to efficiently capture complex relationships between process parameters and objectives. A key element is the adaptive enhancement of the training dataset within the decision-relevant region of interest (ADEROI) by a modified greedy max–min algorithm. This strategy closes data gaps, improves model accuracy in the potentially optimal region, and directs additional simulations to informative areas. Leave-one-out (LOO) and hold-out (HO) cross-validations show strong root mean square error (RMSE) and $R^2$ values for deformation, shrinkage, cycle time, and mass. NSGA-II converges after 403 generations and results in 191 Pareto-optimal solutions, which are consolidated into preference-consistent operating points. These points make trade-offs between analyzed objectives’ deformation, shrinkage, and cycle time explicit for process pre-design. Preferred solutions are identified through weighted sums of normalized objectives and inversely mapped process parameters. Their agreement with the physics-based digital twin at the hundredths level supports the plausibility of the selected operating points within the investigated simulation-based workflow. A retrospective benchmark against a scaled single-stage LHS baseline shows that ADEROI achieves ROI-equivalent point density with fewer simulation runs for the investigated case, reducing the estimated runtime by $39.1\%$ and resulting in a $1.64\times$ speed-up. The quantitative validation is limited to one thin-walled PP keyholder component; further geometries, mold layouts, and polymer materials are required to empirically assess generalizability. Full article

Rising complexity in cyber-physical systems development exposes challenges in the consistent and reusable specification of graphical domain-specific languages (DSLs). Despite the benefits of model-based systems engineering (MBSE), the absence of a standardized, life-cycle-wide specification process results in semantic inconsistencies, tool dependence, and limited interoperability. While our previous work has addressed individual stages of DSL definition, a comprehensive, standards-based process integrating these stages remains missing. Building on these foundations, this paper introduces a unified language specification process for graphical DSLs grounded in established standards—the Meta-Object Facility (MOF), Unified Modeling Language (UML), Web Ontology Language (OWL), and Resource Description Framework (RDF). The process integrates three core artifacts: a tool-independent ontology capturing domain semantics, a MOF-conforming metamodel unifying abstract syntax, semantics, and concrete syntax, and a UML-profile-based implementation. To support and exemplify this process, a prototypical toolchain is introduced that enables automated transformations between these artifacts, thereby facilitating the consistent propagation of semantics from ontology to implementation. The applicability of the proposed process is demonstrated through both a top-down automotive case and a bottom-up cybersecurity DSL, illustrating its cross-domain generalizability. By explicitly structuring and connecting ontology, metamodel, and implementation, this work contributes a semantically consistent, machine-interpretable, and tool-independent specification process for graphical DSLs in MBSE. Full article

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on operating conditions, enabling the model to generalize across different load levels and motor power ratings without retraining. A lightweight BiLSTM architecture is employed, reducing computational complexity while maintaining high diagnostic performance. The proposed method is validated under various operating conditions, including different speeds, load variations, motor power ratings, and noisy conditions. The results demonstrate an overall classification accuracy of 99.65%, with reliable fault detection achieved within less than half of a fundamental cycle. The proposed approach provides an efficient, robust, and scalable solution for inverter fault detection and diagnosis, offering strong potential for practical deployment in modern motor drive systems. Full article