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Open AccessArticle

Prevalence and Mortality Risk of Persistent Smoking After Myocardial Infarction in a Very-High-Risk Region of Southeastern Europe

by Aleksandra Milovančev, Aleksandra Ilić, Tatjana Miljković, Snežana Čemerlić Maksimović, Isidora Milosavljević, Aleksandra Matić and Milovan Petrović

Medicina 2026, 62(7), 1357; https://doi.org/10.3390/medicina62071357 (registering DOI) - 14 Jul 2026

Abstract

Background and Objectives: Long-term real-world data regarding smoking cessation after myocardial infarction (MI) remain scarce in Southeastern Europe. Our objective was to estimate the prevalence of smoking status categories and to assess their association with long-term all-cause mortality in percutaneous coronary intervention [...] Read more.

Background and Objectives: Long-term real-world data regarding smoking cessation after myocardial infarction (MI) remain scarce in Southeastern Europe. Our objective was to estimate the prevalence of smoking status categories and to assess their association with long-term all-cause mortality in percutaneous coronary intervention (PCI) treated MI patients. Materials and Methods: We retrospectively collected data from electronic medical records of hospitalized MI patients who underwent PCI from 1 January 2016 to 1 January 2019. Smoking status and primary outcome (all-cause mortality) were assessed at baseline, during follow-up visits, and during teleconsultation until January 2024, and patients were categorized accordingly. Results: Never-smokers were older than persistent smokers (67.6 ± 11.4 vs. 57.3 ± 9.6 years; p < 0.01) and had a higher burden of hypertension and diabetes (both p < 0.01). At baseline, 47.9% were active smokers, 32.3% of them quit after an MI (with 77.7% being men). Over a median follow-up of 6.7 years, 220 deaths (17.3%) occurred. In a Cox regression model adjusted for age, persistent post-MI smoking significantly increased mortality risk (aHR 2.18; 95% CI 1.52–3.12; p < 0.001), former smokers had an aHR was 1.07 (p = 0.694), while quitters had 30% reduction in death risk (aHR 0.69; p = 0.217). Additionally, in the fully adjusted model, besides persistent smoking (aHR 2.18; p = 0.001), diabetes (aHR 1.69; p = 0.001) and age (aHR 1.09; p < 0.001) were independent predictors of all-cause mortality. Conclusions: Post-MI smoking more than doubles mortality risk, while sustained cessation reduces risk to near never-smoker levels, underscoring the need for aggressive, tailored cessation strategies in low-quit-rate regions such as Southeastern Europe. Full article

(This article belongs to the Section Cardiology)

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Open AccessShort Note

10-(3,5-Di-tert-butylphenyl)-9-methylacridinium Tetrafluoroborate

by Yuki Itabashi and Kei Ohkubo

Molbank 2026, 2026(4), M2203; https://doi.org/10.3390/M2203 (registering DOI) - 14 Jul 2026

Abstract

A 9-methylacridinium salt, 10-(3,5-di-tert-butylphenyl)-9-methylacridin-10-ium tetrafluoroborate (2), was synthesized from the corresponding acridone by treatment with methylmagnesium bromide followed by tetrafluoroboric acid. Compound 2 was obtained as a yellow solid in 95% yield and characterized by NMR spectroscopy and high-resolution [...] Read more.

A 9-methylacridinium salt, 10-(3,5-di-tert-butylphenyl)-9-methylacridin-10-ium tetrafluoroborate (2), was synthesized from the corresponding acridone by treatment with methylmagnesium bromide followed by tetrafluoroboric acid. Compound 2 was obtained as a yellow solid in 95% yield and characterized by NMR spectroscopy and high-resolution mass spectrometry. Electrochemical measurements revealed irreversible reduction behavior, with a reduction potential of −0.52 V vs. SCE determined by second-harmonic alternating-current voltammetry. Compound 2 exhibited absorption extending into the visible region and fluorescence at 492 nm with a lifetime of 4.6 ns. Unlike the previously reported 9-mesityl analogue, compound 2 was fluorescent, a difference that may reflect the absence of the high-lying donor orbital associated with the 9-mesityl group. Its singlet excited-state reduction potential was estimated to be +2.21 V vs. SCE, indicating substantial photooxidizing ability. DFT and TD-DFT calculations provided complementary insight into its frontier molecular orbital distributions and principal electronic transitions. These findings highlight the influence of the 9-substituent on the electronic and emissive properties of acridinium-based photoactive molecules. Full article

(This article belongs to the Collection Molecules from Catalytic Processes)

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Open AccessArticle

Admission Liver Enzyme Elevation Grade for Risk Stratification in Critically Ill Patients: Development and Internal Validation of an Exploratory Prognostic Model

by Giovanni Giordano, Veronica Zullino, Antonella Tosi, Giacomo Monaco, Beatrice Frasacco, Paola Celli, Franco Ruberto, Pierfrancesco Tozzi, Francesco Alessandri and Francesco Pugliese

J. Clin. Med. 2026, 15(14), 5513; https://doi.org/10.3390/jcm15145513 (registering DOI) - 14 Jul 2026

Abstract

Background: Liver enzyme abnormalities are common in critically ill patients, but the prognostic relevance of graded aminotransferase elevation and its timing remains uncertain. We evaluated whether Liver Enzyme Elevation (LEE) grade at ICU admission provides prognostic information beyond SAPS II in a [...] Read more.

Background: Liver enzyme abnormalities are common in critically ill patients, but the prognostic relevance of graded aminotransferase elevation and its timing remains uncertain. We evaluated whether Liver Enzyme Elevation (LEE) grade at ICU admission provides prognostic information beyond SAPS II in a heterogeneous ICU cohort. Methods: In this single-centre retrospective study, adult patients admitted to a mixed ICU between January 2023 and December 2024 and with ICU length of stay ≥72 h were analysed. LEE grade was assigned from AST and ALT according to predefined multiples of the local upper limit of normal, using the higher grade reached by either enzyme. The primary outcome was ICU mortality. Secondary outcomes included renal replacement therapy, ICU length of stay, and duration of invasive mechanical ventilation. A fixed logistic model including SAPS II and admission LEE grade was internally validated by bootstrap resampling. Results: Among 274 patients, ICU mortality was 27.7%. Admission LEE grade showed an adjusted association with ICU mortality (OR 1.26 per grade increase, 95% CI 1.00–1.58; p = 0.048), while SAPS II remained the dominant predictor (OR 1.04 per point, 95% CI 1.02–1.06; p < 0.001). Adding admission LEE grade to SAPS II yielded a small absolute increase in discrimination (AUC 0.737 vs. 0.703; DeLong p = 0.039). Bootstrap-corrected AUC was 0.730, with acceptable overall calibration. Admission LEE grade was also associated with RRT and longer ICU stay in exploratory secondary analyses. Conclusions: Admission LEE grade may provide modest complementary prognostic information beyond SAPS II. These findings are exploratory and require external validation before clinical implementation. Full article

(This article belongs to the Special Issue New Perspectives and Innovations in Critical Illness)

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Open AccessArticle

Nucleus Accumbens Hyperactivity and mPFC–NAc Circuit Dysfunction Promote Self-Injurious Behavior in Rats

by Yanmei Chen, Zhonghui Zuo, Di Luo, Yiling Ni, Liqiang Yang, Shicong Zhu and Jichuan Zhang

Int. J. Mol. Sci. 2026, 27(14), 6256; https://doi.org/10.3390/ijms27146256 (registering DOI) - 14 Jul 2026

Abstract

Self-injurious behavior (SIB) is a devastating and potentially life-threatening action with high prevalence in adolescents and patients with neuropsychiatric disorders. Accumulating evidence indicates that disruptions in multiple cellular and circuit mechanisms underlie vulnerability to SIB. We used an inducible SIB rat model to [...] Read more.

Self-injurious behavior (SIB) is a devastating and potentially life-threatening action with high prevalence in adolescents and patients with neuropsychiatric disorders. Accumulating evidence indicates that disruptions in multiple cellular and circuit mechanisms underlie vulnerability to SIB. We used an inducible SIB rat model to study synaptic modification during SIB. At 0.5 and 1 h after bilateral injection of muscimol (1.0 μg/side) into the rat endopeduncular nucleus (EP, a rodent homolog of the internal globus pallidus (GPi)), which induced SIB in rats, expression of the α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) subunit 1 (GluA1) and the phosphorylation of GluA1 at Ser831 and Ser845 were tested in the lateral habenula (LHb), ventral tegmental area (VTA), nucleus accumbens (NAc), amygdala, and medial prefrontal cortex (mPFC) of the rat brain. We also tested if modulation of NAc activity with a GABA_A receptor agonist or antagonist or dopamine receptor agonist or antagonist or inhibiting the mPFC–NAc pathway affected SIB in rats. At 1 h after EP inhibition, total GluA1 expression and phosphorylated GluA1 were decreased in the mPFC, VTA, and NAc, but were increased in the amygdala compared with control rats. When the EP was inhibited by 0.2 μg/side muscimol, hyperactivation of the NAc increased SIB in rats. However, if the EP was inhibited by 1.0 μg/side muscimol, hyperactivation of the NAc had no effects on SIB. Inhibiting the mPFC–NAc pathway increased wound areas in rats with SIB. At the onset of SIB, excitatory synaptic transmission is simultaneously dampened in the reward and control circuitry (VTA, NAc, mPFC) and potentiated in the aversion circuitry (amygdala), indicating that SIB is associated with molecular signatures suggestive of a shift from reward to threat processing. Hyperactivation of the NAc increased SIB incidence in rats, but administration of dopamine receptor agonists and antagonists into the NAc did not significantly affect the incidence of SIB in this study. These findings provide a novel mechanistic perspective on SIB, offering a basis for the treatment of SIB. Full article

(This article belongs to the Section Molecular Neurobiology)

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Open AccessArticle

Characterization of Community-Scale Smokeless Biochar Production from Corncobs for Potential Soil Amendment and Climate-Smart Agriculture

by Wiphada Thepjunthra, Jutithep Vongphet, Songsak Puttrawutichai, Punyavee Dechkrong and Sasiwimol Khawkomol

Sustainability 2026, 18(14), 7177; https://doi.org/10.3390/su18147177 (registering DOI) - 14 Jul 2026

Abstract

Open burning of agricultural residues remains a significant source of air pollution and greenhouse gas emissions in Southeast Asia. This study evaluated a community-scale smokeless vertical charcoal kiln for biochar production from corncob residues under practical operating conditions. Carbonization at 415–435 °C for [...] Read more.

Open burning of agricultural residues remains a significant source of air pollution and greenhouse gas emissions in Southeast Asia. This study evaluated a community-scale smokeless vertical charcoal kiln for biochar production from corncob residues under practical operating conditions. Carbonization at 415–435 °C for 150–180 min produced biochar yields of 23.3–28.3%, with the 150 min treatment giving the highest yield. The biochar exhibited high carbon content (71–71.5%), low volatile matter (15.7–16.7%), fixed carbon content of 51–54%, and moderately alkaline pH (8.97–9.08). Atomic H/C and O/C ratios (approximately 0.55 and 0.27) indicated moderate aromaticity and stability consistent with IBI Class 1 criteria, while SEM revealed a macropore-dominated porous structure. Theoretical carbon sequestration potential was estimated at 0.69–0.74 tCO₂-eq per tonne of dry feedstock. These findings demonstrate the technical feasibility of community-scale smokeless biochar production and provide physicochemical characterization of the resulting biochar, suggesting potential relevance for carbon storage and soil amendment; however, agronomic performance and emissions require direct evaluation, and results are specific to corncob feedstock. Overall, this work contributes to sustainable agricultural waste management by demonstrating a low-cost, community-accessible pathway that simultaneously supports climate change mitigation, air quality improvement, and socio-economic accessibility for smallholder farming systems in Southeast Asia. Full article

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Open AccessArticle

Skin Anti-Aging Potential of Sulfated Polysaccharides from Cladophora vagabunda Green Seaweed

by Alexandra Gaspar-Pintiliescu, Ana-Maria Seciu-Grama, Ana-Maria Prelipcean, Andreia Alecu, Florentina Gatea, Otilia Zarnescu, Ticuta Negreanu-Pirjol and Oana Craciunescu

Polysaccharides 2026, 7(3), 87; https://doi.org/10.3390/polysaccharides7030087 (registering DOI) - 14 Jul 2026

Abstract

Sulfated polysaccharides (SPs) from green seaweed species have been scarcely studied for the development of novel pharmaceutical, cosmetic or nutraceutical products. The present study aimed to investigate the physico-chemical characteristics of the sulfated polysaccharidic fractions isolated from Cladophora vagabunda green seaweed and to [...] Read more.

Sulfated polysaccharides (SPs) from green seaweed species have been scarcely studied for the development of novel pharmaceutical, cosmetic or nutraceutical products. The present study aimed to investigate the physico-chemical characteristics of the sulfated polysaccharidic fractions isolated from Cladophora vagabunda green seaweed and to evaluate their anti-aging properties in vitro. SPF1 and SPF2 fractions were separated from the purified polysaccharidic extract by size exclusion chromatography. The content of neutral carbohydrates, uronic acids and sulfate was assessed, while Fourier transform infrared spectroscopy (FT-IR) analysis confirmed the presence of a functional group characteristic for sulfated polysaccharides. Capillary zone electrophoresis indicated the monosaccharides profile and the presence of bioactive fucose and uronic acids. The two fractions differed in sulfate content (22.59% and 29.44%). SF2 showed stronger collagenase inhibition (95.69%), whereas SF1 exhibited greater elastase inhibition (84.2%) in comparison with EGCG. Both fractions exhibited antioxidant, anti-collagenase and anti-elastase activities and also a good biocompatibility and capacity to modulate the cell cycle progression in human dermal fibroblast culture. They showed anti-inflammatory potential by inhibition of interleukin-1 beta (IL-1β), tumor necrosis factor-α (TNF-α) and nitric oxide (NO) production in lipopolysaccharide (LPS)-inflamed THP-1-derived macrophages. Also, the level of matrix metalloproteinase-1 (MMP-1) and MMP-9 secretion was reduced after treatment with C. vagabunda fractions with MMP-1 reduced by ~95% in both fractions and MMP-9 reduced by ~79% in SF2 compared with the control. Both fractions stimulated the growth of probiotic cultures Lactobacillus acidophilus and L. rhamnosus. All these results demonstrated, for the first time, the anti-aging potential of sulfated polysaccharides isolated from C. vagabunda green seaweed. Full article

(This article belongs to the Special Issue Translational Advances in Polysaccharide-Based Materials: Bridging Pharmacy, Biomedicine, and Engineering)

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Open AccessArticle

Post-Disaster Power Outage Risk Perception of Medium- and Low-Voltage Distribution Networks Under Typhoons Based on Graded Building Damage: Integrating Dempster–Shafer Theory, Parallel Deep Learning and Multi-Source Data Fusion

by Yu Zou, Juan Bai, Xiaonan Shen, Yang Luo, Yiran Mo, Xingtong Xie, Honghui Zhang, Mingzhi Bin, Yongtu Li, Pingping Gong and Linfei Yin

Energies 2026, 19(14), 3313; https://doi.org/10.3390/en19143313 (registering DOI) - 14 Jul 2026

Abstract

The medium- and low-voltage distribution network is a critical hub connecting the transmission grid and end-users, and its power supply reliability directly determines livelihood security and socio-economic operational efficiency. Typhoon-induced strong winds and rainfall often trigger large-scale power outage risks, severely threatening power [...] Read more.

The medium- and low-voltage distribution network is a critical hub connecting the transmission grid and end-users, and its power supply reliability directly determines livelihood security and socio-economic operational efficiency. Typhoon-induced strong winds and rainfall often trigger large-scale power outage risks, severely threatening power grid security and resilience. To achieve the rapid and accurate perception of outage risk areas based on building damage after typhoons, this study proposes the ResiDS-Net method, which infers distribution network outage risk levels by identifying building damage levels. An improved Dempster–Shafer evidence theory is here adopted to fuse the outputs of CM-ResNet50, Inception-V3 and DenseNet121, enhancing perception accuracy. A two-stage “coarse screening–fine judgment” framework using dual datasets is established to quickly identify large-scale suspected power outage areas from building group damage data. To address the issue that equating building damage with power outages reduces judgment accuracy, this study further develops a hierarchical building damage dataset, classifying individual buildings by damage level to achieve precise outage risk identification. Our experiments show that ResiDS-Net achieves 96.66% and 93.00% accuracy on the two datasets, 2.13% and 2.50% higher than nine comparative networks including Inception-V3. The proposed method effectively improves outage risk perception precision and provides a scientific basis for power emergency repair. It should be noted that the proposed method provides building-damage-based outage risk inference for emergency decision support, rather than the direct detection of verified actual outage status. Full article

(This article belongs to the Special Issue Artificial Intelligence for Smart Grids and Sustainable Energy Systems)

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Open AccessArticle

Nutriphysiological Effects of Hermetia illucens Meal Low Inclusion in Common Carp as an Omnivorous Fish Model Species

by Jan Mazurkiewicz, Zaynab Mashood, Mateusz Rawski, Paula Skrzypczak, Agata Dankowiakowska, Patrycja Reszka and Magdalena Stanek

Fishes 2026, 11(7), 413; https://doi.org/10.3390/fishes11070413 (registering DOI) - 14 Jul 2026

Abstract

Common carp (Cyprinus carpio) fry were fed diets containing defatted Hermetia illucens (HI) larvae meal at three inclusion levels to investigate its effects on the nutriphysiological status, focusing on protein and fat digestibility (in vitro and in vivo), growth performance parameters, [...] Read more.

Common carp (Cyprinus carpio) fry were fed diets containing defatted Hermetia illucens (HI) larvae meal at three inclusion levels to investigate its effects on the nutriphysiological status, focusing on protein and fat digestibility (in vitro and in vivo), growth performance parameters, diet utilization, somatic indices, and GIT histomorphology. The HI meal was included at 0%, 2%, 4%, and 6%. A total of 240 carp fry were randomly divided into four groups, six replicates each (10 fish/tank), and the growth trials lasted 60 days. The dietary inclusion of HI meal up to 6% in carp feed did not significantly affect growth performance, feed utilization, or homeostasis. In vitro protein digestibility exceeded 97% across all treatments with pepsin, indicating efficient hydrolysis. However, the highest crude protein digestibility coefficients were recorded in all treatment groups, which differed significantly from the control group (90.5%). Also, villus width and crypt depth did not differ significantly; however, other parameters, such as villus height and area, showed some significant variations across the treatment groups. No adverse effects were observed on liver condition, structure, or function, reinforcing the safety of HI up to 6% in carp diets. In conclusion, this study demonstrates that HI can be incorporated as a functional, health-promoting ingredient in the diets of common carp fry. Full article

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

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Open AccessReview

Fungal Bioactives in Modern Cosmetic Formulations—A Review

by Michał Kolisz, Katarzyna Sułkowska-Ziaja, Monika Trepa, Małgorzata Cicha-Jeleń, Katarzyna Kała and Bożena Muszyńska

Appl. Sci. 2026, 16(14), 7059; https://doi.org/10.3390/app16147059 (registering DOI) - 14 Jul 2026

Abstract

Fungal-derived compounds are attracting increasing interest in cosmetic science because of their chemical diversity, multifunctional biological activity, and suitability for controlled biotechnological production. Macrofungi produce a wide range of bioactive metabolites, including polysaccharides, phenolic compounds, terpenoids, sterols, and pigments, many of which exhibit [...] Read more.

Fungal-derived compounds are attracting increasing interest in cosmetic science because of their chemical diversity, multifunctional biological activity, and suitability for controlled biotechnological production. Macrofungi produce a wide range of bioactive metabolites, including polysaccharides, phenolic compounds, terpenoids, sterols, and pigments, many of which exhibit antioxidant, anti-inflammatory, moisturizing, photoprotective, and barrier-supporting properties relevant to skin health. However, current research is largely limited to isolated metabolites and simplified in vitro models, whereas comparatively little attention has been paid to the performance of fungal-derived compounds in finished cosmetic formulations. In practice, cosmetic efficacy depends not only on biological activity but also on extraction methods, physicochemical stability, formulation compatibility, and delivery efficiency. This review examines fungal-derived bioactive compounds from the perspective of cosmetic formulation and industrial applicability. It discusses how cultivation conditions, extraction procedures, and formulation design influence stability, bioavailability, and cosmetic performance, and critically evaluates extraction technologies, fermentation systems, encapsulation strategies, lipid carriers, hydrogels, and nanoscale delivery platforms. The review also addresses major limitations, including oxidative instability, variability in metabolite composition, limited penetration of high-molecular-weight compounds, and insufficient standardization and clinical validation. Although fungal-derived compounds show considerable promise for multifunctional cosmetic formulations, their broader industrial application will require improved standardization, optimized formulation strategies, and robust clinical evaluation of efficacy and safety. Full article

(This article belongs to the Section Biomedical Engineering)

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Open AccessArticle

MBP-RTDETR: A Lightweight and Efficient Weed Detection Model for Field Crop Environments

by Yudi Wang, Tao Chen, Qinghua Liu, Yilong Shang, Ke Wang and Zhiyu Jia

Appl. Sci. 2026, 16(14), 7060; https://doi.org/10.3390/app16147060 (registering DOI) - 14 Jul 2026

Abstract

Weed management is an important part of agricultural production and a key factor affecting crop yields. However, weeds in the field have characteristics such as mixed categories, high similarity in morphology with crops, and small detection targets, making detection quite difficult. To address [...] Read more.

Weed management is an important part of agricultural production and a key factor affecting crop yields. However, weeds in the field have characteristics such as mixed categories, high similarity in morphology with crops, and small detection targets, making detection quite difficult. To address these issues, this paper proposes an improved lightweight model, MBP-RTDETR, based on the RTDETR model. This is a real-time detection algorithm that reduces computational load while effectively enhancing the detection accuracy of small-sized weeds in complex farmland backgrounds. The key improvements include: (1) MSNet, a lightweight backbone network, integrates the MSInit module into the CSPNet architecture, effectively incorporating contextual information to provide enhanced multi-scale feature extraction at low computational cost. (2) The AIFI-SSA module simplifies multiplication into efficient binary masking and accumulation operations by leveraging the binary characteristics of peaks, reducing the number of model parameters while maintaining detection accuracy. (3) The PST-DET architecture replaces the conventional convolutional layers in the Feature Pyramid Network (FPN) with the PST module, thereby reducing computational complexity while preserving critical spatial information. Experimental results demonstrate that the proposed model achieves mAP@50 and mAP@50:95 scores of 93.7% and 75.2%, respectively, outperforming the baseline model across both evaluation metrics. Importantly, this performance gain is accompanied by significant efficiency improvements: the model reduces parameter count, computational complexity (GFLOPs), and model weight by 41.2%, 33.3%, and 41.0%, respectively. These enhancements collectively enable robust and computationally efficient detection of field weeds under complex real-world conditions. Full article

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Open AccessArticle

Seasonal Dynamics of Antibiotic Resistance Genes in Irrigation Canals and a Protected Wetland Receiving Treated Wastewater (Central Chile)

by Oscar López-Sandoval, Daniela López-Leyton and Claudia Vélez

Water 2026, 18(14), 1702; https://doi.org/10.3390/w18141702 (registering DOI) - 14 Jul 2026

Abstract

The presence of antibiotic resistance genes (ARGs) in wastewater and their dissemination into aquatic ecosystems represents a significant threat to ecological integrity and public health. This study focuses on the Batuco Lagoon Natural Sanctuary (receiving effluents from a WWTP) and on irrigation canals [...] Read more.

The presence of antibiotic resistance genes (ARGs) in wastewater and their dissemination into aquatic ecosystems represents a significant threat to ecological integrity and public health. This study focuses on the Batuco Lagoon Natural Sanctuary (receiving effluents from a WWTP) and on irrigation canals used for agriculture (without WWTP influence). The aim was to analyze seasonal ARG dynamics and relate their occurrence to water physicochemical characteristics. Five sampling campaigns were conducted, during which physicochemical analyses and molecular detection were performed to identify the blaTEM, sul1, tetW, and ermB genes. Dissolved oxygen ranged from 2.8 to 5.0 mg/L, COD in untreated wastewater reached 287.84 mg/L, and the lagoon exhibited hypereutrophic conditions with total nitrogen averaging 4.56 mg/L (BL1) and 4.39 mg/L (BL2). blaTEM was the most prevalent gene, detected in 71% of samples, followed by sul1 (63%) and tetW (50%). ermB was the least prevalent, present in only 25% of samples. Significant seasonal variations were observed: 33% of samples were ARG-positive in winter, 38% in spring, 50% in fall, and 88% in summer, with all four genes detected during the latter. Seasonal factors, especially summer temperatures and human activity, may increase ARG dissemination, highlighting the need for better WWTP effluent management. Full article

(This article belongs to the Special Issue Emerging Contaminants in Water Environments: Occurrence, Analysis and Ecotoxicity)

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Open AccessReview

Can Disruption of Circadian Rhythms Be Linked to Radiation-Induced Acute Myeloid Leukaemia?

by Aleksandra Czyzak, Gráinne O’Brien, Milagrosa Lopez-Riego, Lourdes Cruz-Garcia and Christophe Badie

Cancers 2026, 18(14), 2255; https://doi.org/10.3390/cancers18142255 (registering DOI) - 14 Jul 2026

Abstract

Acute myeloid leukaemia (AML) remains a highly lethal malignancy with poor prognosis in adults above 60 years old and often occurs after radiation exposure. Emerging evidence suggests that circadian rhythm disruption, prevalent in shift workers, may contribute to cancer development. Clock genes (CGs) [...] Read more.

Acute myeloid leukaemia (AML) remains a highly lethal malignancy with poor prognosis in adults above 60 years old and often occurs after radiation exposure. Emerging evidence suggests that circadian rhythm disruption, prevalent in shift workers, may contribute to cancer development. Clock genes (CGs) regulate fundamental cellular processes, including the DNA damage response (DDR), cell cycle progression, and haematopoiesis. In the absence of substantial experimental data, this review examines the potential pathways linking circadian clock dysregulation to radiation-induced AML (rAML) and evaluates how temporal disruption may modulate leukaemogenesis and radiation-induced effects. The evidence was synthesised on core clock components (BMAL1, CLOCK, PER, CRY, REV-ERB, ROR), their dysregulation in AML, and their roles in radiation response. Epigenetic and post-transcriptional regulatory mechanisms, including m⁶A RNA modification and sirtuin-mediated chromatin remodelling, were evaluated for their contribution to circadian-regulated DNA repair capacity. Multiple CGs demonstrated aberrant expression in AML, with BMAL1 showing tissue-specific dysregulation, and PER1/2/3 was consistently downregulated in peripheral blood. Clock proteins directly regulate DNA damage checkpoints through interactions with ATM/CHK2 and p53 pathways. Circadian disruption enhances inflammatory signalling, promotes accumulation of myeloid-derived suppressor cells, and accelerates immune senescence. Moreover, radiation exposure modulates CG expression, which may alter repair fidelity and increase leukaemogenic risk. Understanding these connections in the context of disrupted circadian rhythms could help identify at-risk populations and improve shift workplace health policies. Full article

(This article belongs to the Special Issue Circadian Rhythms, Cancers and Chronotherapy (2nd Edition))

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Open AccessArticle

Sustainability and Ecotourism Opportunities: Evaluating the Indicators in a Complex Adaptive System

by Riyan Mohammad Sahahiri, Abdullah Alattas, Ahmad Fallatah and Ammar Mandourah

World 2026, 7(7), 121; https://doi.org/10.3390/world7070121 (registering DOI) - 14 Jul 2026

Abstract

Assessing sustainability in complex adaptive systems (CAS) is still considerable challenge, due to the prevalence of dynamic non-linear interdependent socio-ecological processes. Traditional assessment approaches often target a single outcome and have a limited ability to model the interactions and feedback loops that influence [...] Read more.

Assessing sustainability in complex adaptive systems (CAS) is still considerable challenge, due to the prevalence of dynamic non-linear interdependent socio-ecological processes. Traditional assessment approaches often target a single outcome and have a limited ability to model the interactions and feedback loops that influence system behavior. To overcome this limitation, this research proposes a hybrid methodological framework that integrates the Ecotourism Opportunity Spectrum (ECOS), the Delphi method, and key components of CAS theory. The framework allows for the systematic identification, organization, and validation of sustainability indicators in a structured way. It uses a layered approach where indicators are first conceptualized within an integrated framework, then adapted through expert agreement, and subsequently interpreted through the theoretical perspective of CAS to better understand interdependencies and adaptive dynamics. The findings demonstrate strong expert agreement across the identified sustainability indicators and highlight the importance of understanding sustainability dimensions as interdependent rather than isolated assessment components. The CAS-based interpretation further revealed that sustainability indicators operate through adaptive and interconnected relationships, where changes in external environmental, institutional, or socio-economic conditions may influence multiple sustainability dimensions simultaneously. This study contributes to the improvement of sustainability assessment tools and supports decision-making in a more informed, flexible, and context-specific manner by providing a structured but still flexible decision-support approach. Full article

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Open AccessArticle

Dual-Domain Adaptive Input Perturbation Sensitivity for Adversarial Example Detection

by Li Yue, He Gao, Hao Wang, Ming Yang and Dawei Xu

Sensors 2026, 26(14), 4467; https://doi.org/10.3390/s26144467 (registering DOI) - 14 Jul 2026

Abstract

Vision-sensor-based intelligent perception systems are increasingly used in safety-critical scenarios such as autonomous driving, edge surveillance, and Internet-of-Things (IoT) platforms. The vulnerability of deep neural networks to adversarial examples raises security concerns for sensor-acquired visual data in such systems, motivating the study of [...] Read more.

Vision-sensor-based intelligent perception systems are increasingly used in safety-critical scenarios such as autonomous driving, edge surveillance, and Internet-of-Things (IoT) platforms. The vulnerability of deep neural networks to adversarial examples raises security concerns for sensor-acquired visual data in such systems, motivating the study of output-probability-based adversarial example detection methods under controlled benchmark settings. Existing input-level sensitivity detection methods generally rely on static perturbation scales or single-state metrics. When confronted with heterogeneous attacks, such as one-step attacks and iterative attacks, as well as complex tasks with high class density, these methods often suffer from unstable metric directions and insufficient boundary probing capability. To address these issues, this paper proposes a dual-domain adaptive adversarial example detection method based on Multi-scale Input Sensitivity (MSIS). The proposed method introduces a Manifold-Motivated Micro-scale Probing (MMP) mechanism and a Dual-State Sensitivity Fusion (DSF) mechanism. MMP adopts a task-level perturbation scaling strategy motivated by the compressed inter-class manifold structures observed in high-density classification tasks, thereby alleviating perturbation overflow and improving boundary probing effectiveness. DSF employs temperature scaling to extract sensitivity features under both the native state and the smoothed state, and alleviates the directional conflict of heterogeneous attacks under a single metric through dual-state joint modeling. Experimental results demonstrate that, without modifying the parameters of the target model, the proposed method achieves favorable detection performance against representative attacks, including FGSM, PGD, and C&W, on the CIFAR-10 and CIFAR-100 datasets. Taking the CIFAR-10 + ResNet-18 configuration as an example, the detection AUC of the proposed method against the PGD attack reaches 97.75%, an improvement of 24.32 percentage points over the best-performing non-intrusive baseline method, Energy Score (73.43%), with the lowest FPR@95TPR dropping to 7.75%. Under the CIFAR-10 + ResNet-50 configuration, the detection AUC against the PGD attack further reaches 99.14%. Meanwhile, even when compared with PASA (2024), the latest intrusive method requiring access to model gradients, the average AUC of the proposed method on CIFAR-10 + ResNet-18 (97.49%) is still 18.81 percentage points higher, and its inference latency is only 1/11th that of PASA. These results suggest that introducing task-level spatial-domain scaling and temperature-state adaptation can improve output-probability-based adversarial example detection under non-intrusive benchmark settings, providing algorithmic evidence for output-probability-based detection of adversarial perturbations in visual classification tasks. Full article

(This article belongs to the Section Sensing and Imaging)

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Open AccessEditorial

Special Issue: Toxicity of Metals, Metal-Based Drugs, and Microplastics

by Agnieszka Ścibior, Manuel Aureliano and Juan Llopis

Int. J. Mol. Sci. 2026, 27(14), 6257; https://doi.org/10.3390/ijms27146257 (registering DOI) - 14 Jul 2026

Abstract

In the present Special Issue (SI), titled “Toxicity of Metals, Metal-Based Drugs, and Microplastics”, an attempt has been made to include reports updating our knowledge about micro- and nanoplastics, certain airborne metals, some metals/metal complexes, chemotherapeutic drugs, and antioxidants [...] Full article

(This article belongs to the Special Issue Toxicity of Metals, Metal-Based Drugs, and Microplastics)

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Open AccessArticle

A Multi-Criteria Decision Framework for Sustainable Mountain Tourism Development Under Climate Change: Case Study Central Serbia

by Danijela Vukoičić, Dušan Kićović, Dragan Petrović, Ljiljana Mihajlović and Dušan Ristić

Geographies 2026, 6(3), 65; https://doi.org/10.3390/geographies6030065 (registering DOI) - 14 Jul 2026

Abstract

Mountain tourism destinations are increasingly challenged by climate change, environmental degradation, and the need to balance economic development with the long-term conservation of natural resources. This study evaluates alternative pathways for the sustainable development of mountain tourism in Central Serbia by applying an [...] Read more.

Mountain tourism destinations are increasingly challenged by climate change, environmental degradation, and the need to balance economic development with the long-term conservation of natural resources. This study evaluates alternative pathways for the sustainable development of mountain tourism in Central Serbia by applying an integrated multi-criteria decision-making framework that combines conventional and fuzzy approaches to account for uncertainty in expert judgments. A set of economic, environmental, social, developmental, and governance-related criteria was used to assess different tourism development models and identify those with the greatest potential to support long-term sustainability. The findings indicate that development strategies emphasizing climate adaptation, environmental protection, tourism diversification, and active participation of local communities provide the most promising basis for sustainable mountain tourism development. The study also highlights the importance of diversifying tourism products beyond winter-based activities through nature-based forms of tourism, including geotourism, which builds upon the region’s rich geoheritage, geomorphological diversity, and cultural landscapes while strengthening destination resilience to climate change. The proposed evaluation framework provides a practical decision-support tool that can be adapted to other mountain regions facing similar environmental and developmental challenges. Full article

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Open AccessArticle

An Edge-Preserving Guided Filtering Algorithm Based on Edge Tangent Flow and Side Window

by Tingting Liu and Peng Cui

Appl. Sci. 2026, 16(14), 7058; https://doi.org/10.3390/app16147058 (registering DOI) - 14 Jul 2026

Abstract

To address the limited edge-preserving capability of traditional guided filtering caused by fixing the filtering window center at the target pixel, an edge-preserving guided filtering algorithm based on edge tangent flow and side window (EWGF) is proposed. Rather than relying on local intensity [...] Read more.

To address the limited edge-preserving capability of traditional guided filtering caused by fixing the filtering window center at the target pixel, an edge-preserving guided filtering algorithm based on edge tangent flow and side window (EWGF) is proposed. Rather than relying on local intensity statistics, the proposed method exploits local geometric structures through the integration of edge-aware weighting, tangent direction estimation, and adaptive side window filtering. Firstly, an edge-aware weighting strategy is introduced to construct a weighted gradient representation, enabling characterization of edge intensity and local structural features. Secondly, based on the weighted gradient field, a structure tensor constrained by local geometric information is established, and edge tangent flow is estimated through eigenvalue decomposition to capture local edge orientations. Furthermore, a tangent-guided one-dimensional side window guided filtering mechanism is developed, in which the filtering direction is adaptively aligned with local edge structures to suppress noise and textures while preserving edge sharpness and structural continuity. Finally, comparative experiments are conducted on the BSD500, Set5, and Set14 datasets, with PSNR and SSIM employed as evaluation metrics. Experimental results demonstrate that, compared with the traditional guided filtering algorithm, the proposed method improves PSNR by an average of 5.69 dB and SSIM by an average of 0.11, validating its performance in structure preservation and noise suppression. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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Open AccessArticle

Epidemiology, Risk Factors, and Mortality in Unprovoked and Provoked Pulmonary Embolism—A Single-Center Retrospective Study in the Israeli Population: Gender and Ethnic Differences

by Raymond Farah, Nicola Luigi Bragazzi, Halil İbrahim Ceylan, Łukasz Szarpak, Agnese Maria Fioretti, Wisam Mahajna, Noor Ashqar and Rola Khamisy-Farah

Epidemiologia 2026, 7(4), 101; https://doi.org/10.3390/epidemiologia7040101 (registering DOI) - 14 Jul 2026

Abstract

Background: Pulmonary embolism (PE) is a leading cause of morbidity and mortality worldwide, ranking third among cardiovascular-related deaths after myocardial infarction and stroke. Despite extensive research, data on PE incidence and characteristics within the Israeli population remain limited. This study aimed to investigate [...] Read more.

Background: Pulmonary embolism (PE) is a leading cause of morbidity and mortality worldwide, ranking third among cardiovascular-related deaths after myocardial infarction and stroke. Despite extensive research, data on PE incidence and characteristics within the Israeli population remain limited. This study aimed to investigate the demographic, clinical, and prognostic factors associated with provoked (PPE) and unprovoked PE (UPE) cases in Israel. Methods: We conducted a retrospective observational study analyzing medical records of patients diagnosed with PE at Ziv Medical Center, Safed, Israel, from 2017 to 2022. Patients were classified into PPE or UPE groups based on identifiable risk factors. Demographic data, clinical characteristics, and mortality outcomes were compared using descriptive and inferential statistical methods, including the Mann–Whitney U test, chi-square test, logistic regression, Kaplan–Meier survival analysis, and Cox proportional hazards modeling. Results: A total of 348 patients (mean age: 68.6 ± 17.6 years; 54.3% female) were included, with 189 (54.3%) classified as PPE and 159 (45.7%) as UPE. Female patients were significantly older than males (p < 0.001), and Jewish patients were slightly older than Arab patients (p = 0.060). The average hospital stay was 10.7 ± 16.2 days. Although no group differences emerged in unadjusted analyses, male sex was associated with longer hospitalization and UPE with shorter hospitalization than PPE in the adjusted model. Ethnicity emerged as a significant predictor of PE type, with Jewish patients less likely to have UPE (OR = 0.457, 95% CI 0.256–0.817, p = 0.008). Among PPE cases, 67.2% were of Jewish origin and 32.8% were Arab, compared to 56.0% and 44.0%, respectively, in the UPE group. In-hospital mortality was 16.1% (n = 56). Age was a significant predictor of mortality (HR = 1.03, 95% CI 1.00–1.06, p = 0.020), while ethnicity, gender, and PE type showed no significant associations in multivariable models. Conclusions: Our findings highlight key demographic and clinical factors influencing PE outcomes in Israel. The significant association between ethnicity and PE type warrants further investigation to refine diagnostic and therapeutic strategies for high-risk populations. Full article

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Open AccessArticle

Prioritising the Adaptive Reuse of Closed Schools in Depopulating Regions: Reconciling Urgency and Potential Through a Multi-Criteria Framework

by Jinju Jung, Inkwan Paik, Junhyuk Lim and Seunguk Na

Buildings 2026, 16(14), 2789; https://doi.org/10.3390/buildings16142789 (registering DOI) - 14 Jul 2026

Abstract

The accelerating closure of schools in depopulating regions is leaving a growing surplus of public assets whose reuse must be prioritised, yet systematic and transferable tools for supporting such decisions in advance remain scarce. This study proposes an artificial-intelligence-augmented multi-criteria framework that prioritises [...] Read more.

The accelerating closure of schools in depopulating regions is leaving a growing surplus of public assets whose reuse must be prioritised, yet systematic and transferable tools for supporting such decisions in advance remain scarce. This study proposes an artificial-intelligence-augmented multi-criteria framework that prioritises the adaptive reuse of closed schools using only openly available demographic and spatial data. Four criteria—regional ageing, building floor area, and proximity to administrative and transport infrastructure—were evaluated for 121 closed schools in Chungbuk Province, South Korea, under two weighting schemes, the subjective analytic hierarchy process and the objective entropy method, with a large-language-model agent added as an explanatory layer to interpret context and recommend reuse types. The data-driven weights proved liable to a structural distortion, elevating the single largest building to first place in urgency on the strength of its size alone, a misjudgement the agent corrected through contextual reasoning over the same data. Examining the schools from the opposed standpoints of intervention urgency and reuse potential further revealed a near-perfect inversion between them (Spearman ρ = −0.998), indicating that the most urgent schools are systematically those least able to sustain a market-led conversion. The framework addresses this dilemma not through a single optimal ranking but through spatially differentiated, agent-generated recommendations and is formulated for transfer to other middle-income economies approaching the same demographic transition. Full article

(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

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Open AccessArticle

Synergistic Hydrogels Enabled by Dual-Regulatory Mussel Foot Protein for Advancing Wound Healing

by Jiren Xu, Na Li, Chen Wang, Jeevithan Elango, Wenhui Wu, Peng Fu and Bailei Li

Gels 2026, 12(7), 627; https://doi.org/10.3390/gels12070627 (registering DOI) - 14 Jul 2026

Abstract

Impaired wound healing is often caused by persistent inflammation, bacterial infection, and insufficient extracellular matrix remodeling. Natural polymer-based hydrogels represent ideal wound dressings but often struggle to balance structural stability and biological activity. Herein, we report a dual-functional network regulation strategy enabled by [...] Read more.

Impaired wound healing is often caused by persistent inflammation, bacterial infection, and insufficient extracellular matrix remodeling. Natural polymer-based hydrogels represent ideal wound dressings but often struggle to balance structural stability and biological activity. Herein, we report a dual-functional network regulation strategy enabled by highly soluble mussel foot protein (HMFP) that acts simultaneously as a structural crosslinking regulator and bioactive effector to fabricate synergistic hydrogels (CS-SH-H) from β-chitosan (CS) and sodium hyaluronate (SH). HMFP homogenizes the porous microstructure, strengthens intermolecular interactions, and significantly improves thermal and structural stability via multivalent non-covalent bonding. In vitro, CS-SH-H shows excellent cytocompatibility, significantly promotes fibroblast proliferation and migration, and exerts potent antibacterial activity against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). In a mouse full-thickness skin defect model, the hydrogel dramatically accelerates wound closure, reducing the residual wound area to 25% on day 7, outperforming the control groups. Immunohistochemistry confirms that HMFP suppresses TNF-α-mediated inflammation and enhances Ki-67-positive cell proliferation, leading to accelerated re-epithelialization and collagen deposition. This study establishes HMFP as a promising marine-derived dual-functional network regulator for designing high-performance hydrogel dressings. This strategy is scalable and translatable for treating infected and inflammatory wounds. Full article

(This article belongs to the Section Gel Applications)

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Formaldehyde Emissions from Wood Materials and Their Impact on Indoor Air Quality

by Karen Negrete-Carrillo, Jorge Salvador-Carlos, Benjamín Valdez-Salas, Ernesto Beltrán-Partida, Jhonathan Castillo-Saenz and Roberto Gamboa-Becerra

Sustainability 2026, 18(14), 7176; https://doi.org/10.3390/su18147176 (registering DOI) - 14 Jul 2026

Abstract

Wood-based materials are a significant source of formaldehyde (HCHO), which is a volatile organic compound (VOC) classified as a human carcinogen that has adverse effects on the indoor air quality (IAQ) and health. This study evaluates HCHO emissions from six materials commonly used [...] Read more.

Wood-based materials are a significant source of formaldehyde (HCHO), which is a volatile organic compound (VOC) classified as a human carcinogen that has adverse effects on the indoor air quality (IAQ) and health. This study evaluates HCHO emissions from six materials commonly used indoors, including medium-density fiberboard, melamine, pine boards, birch boards, oak boards, and alder boards, using the desiccator method in accordance with ASTM D5582. The experimental results were integrated with an indoor air model to estimate exposure under representative residential conditions. The measured emissions ranged from 0.235 ± 0.01 to 1.023 ± 0.10 mg m⁻³, with composite materials exhibiting the highest values. The risk analysis showed that all samples exceeded international reference values, with the greatest concern arising in scenarios of chronic exposure. The modeling indicated that indoor air concentrations depend heavily on material load and ventilation, reaching values as high as 0.155 mg m⁻³ under conditions of low air exchange. Overall, the results show that material composition, installed quantity, and ventilation conditions are key factors influencing indoor HCHO concentrations. This study offers an integrated approach that combines experimental measurement and exposure estimation, contributing to informed material selection and the assessment of their impact on IAQ. Full article

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Enhanced Estimation of PV Power Production and Consumption with Multi-Step Prediction in Smart Energy Grids

by Phil Aupke, Seema Seema, Andreas Theocharis and Andreas Kassler

Energies 2026, 19(14), 3312; https://doi.org/10.3390/en19143312 (registering DOI) - 14 Jul 2026

Abstract

Accurate forecasting of power production and consumption is essential for the efficient operation of smart energy grids, enabling stable energy exchange and grid reliability. However, the growing integration of photovoltaics (PVs) and electric vehicles introduces significant uncertainty. This paper evaluates multiple Machine Learning [...] Read more.

Accurate forecasting of power production and consumption is essential for the efficient operation of smart energy grids, enabling stable energy exchange and grid reliability. However, the growing integration of photovoltaics (PVs) and electric vehicles introduces significant uncertainty. This paper evaluates multiple Machine Learning (ML) models for single- and multi-step forecasts of PV generation and household consumption, incorporating uncertainty bounds to inform operator decisions. We use data from two Swedish sites and the CityLearn benchmark dataset to compare direct, recursive, and hybrid multi-step strategies. LightGBM with gradient-boosted quantile regression achieves the best single-step performance, with Mean Absolute Error (MAE) as low as 10.19 W in Halmstad and 16.12 W in Uppsala. For multi-step forecasts, the direct method outperforms others, reaching a 48 h consumption MAE of 71.08 W in Uppsala and 52.05 W in Halmstad, and achieving prediction interval coverage probabilities above 0.95. Moreover, personalized models trained on individual households outperform generalized ones, even with smaller datasets, highlighting the value of tailored approaches for improving forecast accuracy under uncertainty. Full article

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Open AccessArticle

How Entrepreneurship Education Shapes Startup Motivation Among University Female Students: The Conditional Indirect Role of Entrepreneurial Identity and Social Support

by Tamer Hamdy Ayad, Abdullah Hamoud Ali Seraj and Nadia A. Abdelmegeed Abdelwahed

Societies 2026, 16(7), 220; https://doi.org/10.3390/soc16070220 (registering DOI) - 14 Jul 2026

Abstract

Entrepreneurship education is a key driver of entrepreneurial activity. This study empirically examines the mixed evidence regarding how entrepreneurship education experiences motivate start-up intentions among female university students through the lenses of identity theory and the social support perspective. Specifically, it investigates whether [...] Read more.

Entrepreneurship education is a key driver of entrepreneurial activity. This study empirically examines the mixed evidence regarding how entrepreneurship education experiences motivate start-up intentions among female university students through the lenses of identity theory and the social support perspective. Specifically, it investigates whether entrepreneurial identity mediates the relationship between perceived entrepreneurship education experience and start-up motivation. Survey data were collected from 412 female students enrolled at public universities in Saudi Arabia. The findings revealed that a large proportion of participants had received some form of entrepreneurship-related instruction. The results further demonstrate that entrepreneurship education positively influences start-up motivation both directly and indirectly by fostering entrepreneurial identity (EI). Moreover, social support strengthens the relationship between entrepreneurship education and entrepreneurial identity, resulting in a significant conditional indirect effect on start-up motivation. These findings suggest that entrepreneurship education is most effective when it cultivates entrepreneurial identity within supportive social environments, thereby enhancing female students’ motivation to pursue entrepreneurial ventures. Understanding these relationships is particularly important for female university students, who often encounter greater social, institutional, and resource-related barriers to entrepreneurial participation and venture creation. Full article

(This article belongs to the Special Issue The Employability and Entrepreneurship in Higher Education)

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Comparative Analysis of Second- and Fourth-Order Runge–Kutta Methods for Solving Chaotic Dynamical Systems

by Ndivhuwo Ndou

AppliedMath 2026, 6(7), 112; https://doi.org/10.3390/appliedmath6070112 (registering DOI) - 14 Jul 2026

Abstract

This study presents a comparative numerical investigation of second-order and fourth-order Runge–Kutta methods for solving chaotic dynamical systems. The Lorenz, Genesio–Tesi, and Rössler systems are considered because of their nonlinear behavior and high sensitivity to initial conditions. The numerical schemes investigated include the [...] Read more.

This study presents a comparative numerical investigation of second-order and fourth-order Runge–Kutta methods for solving chaotic dynamical systems. The Lorenz, Genesio–Tesi, and Rössler systems are considered because of their nonlinear behavior and high sensitivity to initial conditions. The numerical schemes investigated include the Midpoint, Improved Euler, Ralston, and fourth-order Runge–Kutta (RK4) methods. The performance of the methods is evaluated in terms of convergence behavior, numerical accuracy, stability characteristics, and computational cost. A stability analysis of each chaotic system is carried out through equilibrium point determination and Jacobian eigenvalue analysis. Numerical simulations are implemented in MATLAB 2023 version, and comparisons are performed using different step sizes. The results indicate that all numerical methods converge as the step size decreases; however, the RK4 method consistently provides significantly smaller errors and improved stability properties compared with the second-order schemes. The findings further demonstrate that higher-order numerical integration methods provide superior performance for highly sensitive chaotic systems where accuracy and reliability are essential. Full article

(This article belongs to the Special Issue Advances in Iterative Methods and Stability Analysis for Solving Nonlinear Problems)

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Online Trajectory Planning for Stewart Parallel Mechanisms Based on Improved Trajectory Scaling and Condition-Number-Aware Velocity Bound Regulation

by Xue Jiang, Chao Wang, Hai Zeng, Binghao Zhang and Lijie Zhang

Machines 2026, 14(7), 794; https://doi.org/10.3390/machines14070794 (registering DOI) - 14 Jul 2026

Abstract

Stewart parallel mechanisms are widely used in motion simulation, posture adjustment, and active compensation owing to their high stiffness, high load capacity, and high positioning accuracy. However, under unknown paths or time-varying target trajectories, their strong multi-chain coupling, limited workspace, and configuration-dependent motion [...] Read more.

Stewart parallel mechanisms are widely used in motion simulation, posture adjustment, and active compensation owing to their high stiffness, high load capacity, and high positioning accuracy. However, under unknown paths or time-varying target trajectories, their strong multi-chain coupling, limited workspace, and configuration-dependent motion capability may cause actuator velocity and acceleration violations, especially near workspace boundaries or low-mobility regions. Moreover, conventional online trajectory scaling methods are usually designed for acceleration bounds with regular positive and negative limits. After nonlinear kinematic constraint mapping, the acceleration bounds of a Stewart mechanism in the path-parameter space may become same-signed, shifted, or abruptly varying, which can lead to planning failure or motion discontinuity. To address these problems, this paper proposes a condition-number-aware velocity bound regulation scaling method for online trajectory planning under unknown paths. Path–velocity decomposition is first used to transform the six-degree-of-freedom trajectory planning problem into a path-time-law planning problem, and actuator constraints are mapped into the path-parameter space. Then, a workspace classification model and the dimensionless Jacobian condition number are introduced to evaluate local motion capability. Based on the workspace level and condition number, a hierarchical scaling factor is designed to adaptively adjust the path velocity boundary. In addition, the conventional trajectory scaling method is improved by introducing a special acceleration-bound handling mechanism. Single-axis and platform experimental results show that the proposed method can effectively handle special acceleration bounds, reduce actuator constraint violations, and improve the safety and continuity of online trajectory planning. Full article

(This article belongs to the Section Machine Design and Theory)

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Open AccessEditorial

Non-Coding and Coding RNAs in Targeted Cancer Therapy

by Macrina B. Silva-Cázares and César López-Camarillo

Cells 2026, 15(14), 1264; https://doi.org/10.3390/cells15141264 (registering DOI) - 14 Jul 2026

Abstract

Cancer remains one of the leading causes of morbidity and mortality worldwide despite remarkable advances in molecular biology, precision medicine, and targeted therapeutics [...] Full article

(This article belongs to the Special Issue Non-Coding and Coding RNAs in Targeted Cancer Therapy)

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