Search Results (17,707)

This study introduces an energy-aware hybrid security framework that safeguards embedded systems against code theft, closing a critical gap. The approach integrates bitstream encryption, dynamic key generation, and Dynamic Function eXchange (DFX)-based memory obfuscation, yielding a layered hardware–software countermeasure to Read-Only Memory (ROM) scraping, side-channel attacks, and Man-in-the-Middle (MITM) intrusions by eavesdropping on communications on pins, cables, or Printed Circuit Board (PCB) routes. Prototyped on a Xilinx Zynq-7020 System-on-Chip (SoC) and applicable to MicroBlaze-based designs, it derives a fresh Authenticated Encryption with Associated Data (AEAD) key for each record via an Ascon-eXtendable-Output Function (XOF)–based Key Derivation Function (KDF) bound to a device identifier and a rotating slice from a secret pool, while relocating both the pool and selected Block RAM (BRAM)-resident code pages via Dynamic Function eXchange (DFX). This moving-target strategy frustrates ROM scraping, probing, and communication-line eavesdropping, while cryptographic confidentiality and integrity are provided by a lightweight AEAD (Ascon). Hardware evaluation reports cycles/byte, end-to-end latency, and per-packet energy under identical conditions across lightweight AEAD baselines; the framework’s key-derivation and DFX layers are orthogonal to the chosen AEAD. The threat model, field layouts (Nonce/AAD), receiver-side acceptance checks, and quantitative bounds are specified to enable reproducibility. By avoiding online key exchange and keeping long-lived secrets off Programmable Logic (PL)-based external memories while continuously relocating their physical locus, the framework provides a deployable, energy-aware defense in depth against code-theft vectors in FPGA-based systems. Overall, the work provides an original and deployable solution for strengthening the security of commercial products against code theft in embedded environments. Full article

Railway hazardous chemical transportation, a high-risk activity that endangers personnel, infrastructure, and ecosystems, directly undermines the sustainability of the transportation system and regional development. Traditional risk management algorithms, which rely on empirical rules, result in sluggish emergency responses (with an average response time of 4.8 h), further exacerbating the environmental and economic losses caused by accidents. The standalone DBSCAN algorithm only supports static spatial clustering (with unoptimized hyperparameters); it lacks probabilistic reasoning capabilities for dynamic scenarios and thus fails to support sustainable resource allocation. To address this gap, this study develops a DBSCAN–Bayesian network fusion model that identifies risk hotspots via static spatial clustering—with ε optimized by the K-distance method and MinPts determined through cross-validation—for targeted prevention; meanwhile, the Bayesian network quantifies the dynamic relationships among “hazardous chemical properties-accident scenarios-material requirements” and integrates real-time transportation and environmental data to form a “risk positioning-demand prediction-intelligent allocation” closed loop. Experimental results show that the fusion algorithm outperforms comparative methods in sustainability-linked dimensions: ① Emergency response time is shortened to 2.3 h (a 52.1% improvement), with a 92% compliance rate in high-risk areas (e.g., water sources), thereby reducing ecological damage. ② The material satisfaction rate reaches 92.3% (a 17.6% improvement), and the neutralizer matching accuracy for corrosive leaks is increased by 26 percentage points, which cuts down resource waste and lowers carbon footprints. ③ The coverage rate of high-risk areas reaches 95.6% (a 16.4% improvement over the standalone DBSCAN algorithm), with a 27.5% reduction in dispatch costs and a drop in resource waste from 38% to 11%. This model achieves a leap from static to dynamic decision-making, providing a data-driven paradigm for the sustainable emergency management of railway hazardous chemicals. Its “spatial clustering + probabilistic reasoning” path holds universal value for risk control in complex systems, further boosting the sustainability of infrastructure. Full article

Background: DDX41 is one of the most frequent adult-onset myeloid neoplasm predisposition gene, yet its biology remains incompletely defined. This study investigated the frequency, spectrum, and clinical characteristics of DDX41 variants in Korean patients with hematologic malignancies, including the patterns of co-occurring somatic variants. Methods: We retrospectively reviewed 716 patients with hematologic malignancies who underwent targeted next-generation sequencing. In patients with germline DDX41 variants, clinicopathologic features, co-occurring variants, variant allele frequency (VAF) distributions, and survival were analyzed. Results:DDX41 variants were identified in 34/716 patients (4.7%), including 33 germline carriers (4.6%), occurring most frequently in AML (6.2%) and MDS (11.1%). Patients with germline DDX41 variants had a median age of 68 years, were predominantly male (69.7%), and commonly had normal karyotypes (72.7%), with similar features in AML and MDS except for lower platelet counts in AML (p = 0.025). The most common germline DDX41 variants were Y259C (20.6%), A500fs (14.7%), E7* (11.8%), V152G (11.8%), and D139G (8.8%), with null variants predominating in AML and missense variants in MDS (p = 0.002). Somatic DDX41 variants occurred in 63.6% of patients with germline DDX41 variants, with R525H being the most frequent (48%), while non-DDX41 somatic variants were detected in 78.8% of patients, most commonly involving ASXL1, DNMT3A, SRSF2, and TET2, which appeared at lower VAFs, suggesting late acquisition. Conclusions: This study demonstrates ethnic-specific DDX41 variant patterns in Korean myeloid neoplasm patients, with biallelic alterations potentially involved in early leukemogenesis. These findings provide further insight into the unique features of DDX41-associated myeloid neoplasms. Full article

Tyrosine kinase inhibitors (TKIs), such as sunitinib and sorafenib, are standard treatments for renal cell carcinoma (RCC). However, most patients treated with these drugs eventually develop drug resistance and relapse; therefore, new treatment options for RCC are urgently required. Recent studies have focused on combination therapies targeting distinct molecular pathways that may produce synergistic effects and help overcome drug resistance in RCC. Niclosamide, an anthelmintic agent, is effective against various cancers; however, its potential in combination with sunitinib for treating RCC has not been evaluated. In this study, we assessed the therapeutic efficacy of niclosamide in combination with sunitinib against RCC and explored the underlying molecular mechanisms. Niclosamide alone inhibited RCC cell proliferation, whereas its combination with sunitinib produced a synergistic anticancer effect, both in vitro and in vivo. RNA sequencing (RNA-seq) and bioinformatic analyses showed that niclosamide modulated critical pathways, including BRIP1- and FANCA-mediated DNA repair and E2F2-regulated cell cycle progression. These findings provide proof-of-concept that niclosamide enhances TKI efficacy through modulation of DNA repair and cell cycle pathways, supporting the rationale for DNA damage response (DDR)-targeted combination strategies in RCC. Full article

Brilliant blue, as a pigment food additive, has all the characteristics of printing and dyeing wastewater and belongs to persistent and refractory organic compounds. The photocatalysis–Fenton reaction system consists of two parts: photocatalytic reaction and Fenton reaction. Electrons promote the decomposition of H₂O₂ to produce •OH. In addition, the effective separation of e- and h⁺ by light strengthens the direct oxidation of h⁺, and h⁺ reacts directly with OH⁻ to produce •OH, which can further promote the removal of organic pollutants. In this paper, g-C₃N₄ and Fe/g-C₃N₄ photocatalysts were prepared by the thermal polycondensation method. Fe/g-C₃N₄ of 15 wt% can reach 98.59% under the best degradation environment, and the degradation rate of g-C₃N₄ is only 7.6% under the same conditions. The photocatalytic activity of the catalysts was further studied. Through active species capture experiments, it is known that •OH and •O₂⁻ are the main active species in the system, and the action intensity of •OH is greater than that of •O₂⁻. The degradation reaction mechanism is that H₂O₂ combines with Fe²⁺ in Fe/g-C₃N₄ to generate a large amount of •OH and Fe³⁺, and the combination of Fe-N bonds accelerates the cycle of Fe³⁺/Fe²⁺ and promotes the formation of •OH, thereby accelerating the degradation of target pollutants. •O₂⁻ can reduce Fe³⁺ to Fe²⁺, Fe²⁺ reacts with H₂O₂ to produce •OH, which promotes degradation, and •O₂⁻ itself also plays a role in degradation. In addition, under the optimal experimental conditions obtained by response surface experiments, the fitting degree of first-order reaction kinetics is 0.96642, and the fitting degree of second-order reaction kinetics is 0.57884. Therefore, this reaction is more in line with first-order reaction kinetics. The adsorption rate is only proportional to the concentration of Fe/g-C₃N₄. Full article

Sandstone quarrying in Lekokoaneng contributes to both local and national economic development, yet it raises concerns about environmental degradation and community livelihoods. Using a mixed-methods design framed by the Sustainable Livelihood Framework (SLF) and the Sustainable Development Theory (SDT), 203 households were surveyed across five buffer zones (0–1000 m) around the formal quarry site in Lekokoaneng, Berea District, Lesotho. Quantitative data were analysed descriptively, while qualitative responses underwent thematic analysis and were transformed into quantifiable categories. Quarrying generated employment and small-business opportunities concentrated within 0–600 m of the site, alongside elevated reports of dust, soil degradation and water contamination that undermined agriculture and health. Households nearest the quarry reported the highest income benefits (e.g., 35% via employment) but also the greatest environmental burdens. Households furthest away reported fewer risks but also limited economic gain. Thematic analysis yielded four domains: Socio-Economic Empowerment, Livelihood Vulnerability, Health and Safety Risks, and Environmental Degradation and Control. Integrating SLF and SDT shows quarrying as a double-edged livelihood system with short-term financial gains that coincide with erosion of natural, human and social capitals. Targeted environmental safeguards, labour formalisation and community-inclusive governance are essential to realign quarrying with resilience and sustainability goals. Full article

Background: Glioblastoma (GBM) remains refractory to chemoradiotherapy. Glial populations—microglia/monocyte-derived macrophages, reactive astrocytes, and the oligodendrocyte lineage—shape both treatment resistance and radiation-related brain injury. Scope: We synthesize how myeloid ontogeny and plasticity, astrocytic hubs (IL-6/STAT3, TGF-β, connexin-43/gap junctions), and oligodendrocyte precursor cells (OPCs)–linked programs intersect with DNA-damage responses, hypoxia-driven metabolism, and extracellular vesicle signaling to support tumor fitness while predisposing normal brain to radiotoxicity. Translational implications: Convergent, targetable pathways (IL-6/JAK–STAT3, TGF-β, chemokine trafficking, DDR/senescence) enable co-design of radiosensitization and neuroprotection. Pragmatic levers include myeloid reprogramming (CSF-1R, CCR2), astrocyte-axis modulation (STAT3, TGF-β, Cx43), and brain-penetrant DDR inhibition (e.g., ATM inhibitors), paired with delivery strategies that raise intratumoral exposure while sparing healthy tissue (focused-ultrasound blood–brain barrier opening, myeloid-targeted dendrimers; Tumor Treating Fields as an approved adjunct therapy). Biomarker frameworks (TSPO-PET, macrophage-oriented MRI radiomics, extracellular vesicle liquid biopsy) can support selection and pharmacodynamic readouts alongside neurocognitive endpoints. Outlook: Timing-aware combinations around radiotherapy and hippocampal/white-matter sparing offer a near-term roadmap for “glia-informed” precision radiotherapy. Full article

Cerium-doped titania nanoflowers are obtained by hydrothermal synthesis, with different amounts of cerium (0.3, 0.5, and 1.0 at%). Both undoped nanoflowers (TNF) and Ce-doped TNF (Cex) are tested as photocatalysts in the degradation of the target pollutant (metronidazole) under simulated solar light. The samples are rutile polymorphs with high crystallinity and present a nanoflower-like morphology of about 1 µm in diameter and are made up of nanoscale petals (in the range of 100–300 nm). EDX spectroscopy was coupled with SEM and performed on the Ce-doped samples to determine the elemental composition of the catalysts and the Ce distribution in each sample. Optical and electronic spectroscopies reveal that Ce loading narrows the band gap from 3.0 to 2.8 eV, extending light absorption into the visible range of the spectrum and thus enhancing the photocatalytic activity. The best sample, Ce1, achieved 67% degradation of metronidazole after 360 min under solar irradiation at pH 4, compared to bare TNF, which reached 35%. Reusability tests confirm the chemical stability and photocatalytic efficiency of Ce1 over three cycles, and free-radical trapping experiments confirmed ·O₂⁻ and ·OH as major active species in metronidazole degradation. This study highlights the synergistic impact of morphology and doping on solar-driven organic pollutant degradation. Full article

Against the backdrop of urban stock development worldwide, resident-led urban regeneration and in-situ demolition-and-reconstruction models are crucial for advancing sustainable urban regeneration. However, these initiatives often stall due to collective action dilemmas arising from complex interactions among governments, residents, and contractors. To address this, we develop a tripartite evolutionary game model that incorporates a novel multi-dimensional policy lever system. This system integrates the following: (1) resource-allocation levers (area-expansion coefficient, w; expansion benefit-sharing coefficient, v), (2) cost-sharing levers (expansion-purchase coefficient, p; original-area reconstruction payment coefficient, q), and (3) behavioral-intervention levers (cost-burden perception coefficient, e; accident-risk perception coefficient, d), the latter quantifying behavioral economics principles like loss aversion and probability weighting. Through numerical simulations, we identify the nonlinear effects, critical thresholds, and interaction mechanisms of these levers. The results demonstrate that resource-allocation and cost-sharing levers exhibit critical ranges, whereas behavioral-intervention levers are characterized by perception thresholds and saturation effects. Crucially, coordinated optimization of all parameters—rather than one-sided incentives—is essential to steer the system towards the ideal cooperative equilibrium (government guidance, contractor participation, and resident engagement). This study provides a systematic theoretical framework and practical pathway for crafting targeted urban regeneration policies, emphasizing that aligning economic incentives with behavioral interventions can simultaneously enhance compactness, feasibility, and equity, thereby contributing to the achievement of Sustainable Development Goal 11. Full article

By alternately depositing hydrogen-free amorphous carbon (a-C) and hydrogenated amorphous carbon (a-C:H) nanolayers on HSLA-100 steel through arc-ion plating, multilayer diamond-like carbon (DLC) architectures were engineered, with the modulation period adjusted from 1 to 10 cycles. SEM and Raman spectroscopy served as the analytical tools for characterizing the microstructure. For assessing key functional behaviors, nanoindentation was used to test mechanical properties, dry-sliding tribometry and in-situ tribocorrosion tests targeted tribological and tribocorrosion performance, and polarization tests focused on corrosion resistance. Introducing C₂H₂ increased the sp³ fraction and hardness relative to pure a-C. The ten-period film (S5) yielded the highest H/E (0.0767) and H³/E² (0.171), reflecting the best hardness–toughness synergy. All coatings lowered the dry friction coefficient to 0.08–0.10 and cut wear by more than 1 order of magnitude versus the substrate; the ten-period film (S5) showed the minimum dry wear rate (1.39 × 10⁻⁷ mm³·N⁻¹·m⁻¹) and tribocorrosion wear rate (4.53 × 10⁻⁷ mm³·N⁻¹·m⁻¹) in 3.5 wt% NaCl. The superior performance is due to interlayer interfaces that dissipate stresses, arrest crack propagation, and block electrolyte ingress through defects. These findings indicate that the rational stacking of a-C/a-C:H significantly improves the tribological and tribocorrosion resistance of HSLA-100, providing a reliable protective approach for components used in marine services. Full article

Integrated pharmacokinetic (PK) and pharmacodynamic (PD) models are essential for the understanding of quantitative relationship between drug exposure and response towards the identification of optimal dosing regimens in drug development and clinical therapy. This article summarizes the common PK–PD models being established in oncology, with a focus on combination therapies. Among them, the PK models include those used for practical non-compartmental and compartmental analyses, as well as those for physiologically based modeling that describe and predict exposure to various chemotherapy, targeted therapy, and immunotherapy drugs. Built on proper natural disease progression models, such as the empirical logistic growth curve, the Gompertzian growth model, and their modifications, the integrated PK–PD models recapitulate and predict antitumor drug efficacy, in which the PD models include practical indirect response model and various tumor growth inhibition models, as driven by the mechanistic actions of the drugs administered. Since anticancer drugs are usually co-administered, PK–PD modeling has been extended from monotherapy to combination therapy. However, relying on a single interaction factor or parameter to capitulate complex drug interactions, predict outcomes of different combinations, and determine possible synergism is problematic. Considering the apparent contributions from individual drugs following mutual interactions, a new PK–PD model has been developed for combination therapy, which may be integrated with proper algorism (e.g., the Combination Index method) to critically define combination effects, synergism, additivity, or antagonism. As drug combinations become more complex and individual drug actions are variable, these models should be optimized further to advance the understanding of PK–PD relationships and facilitate the development of improved therapies. Full article

This article formalizes AI-assisted assessment as a discrete-time policy-level design for iterative feedback and evaluates it in a digitally transformed higher-education setting. We integrate an agentic retrieval-augmented generation (RAG) feedback engine—operationalized through planning (rubric-aligned task decomposition), tool use beyond retrieval (tests, static/dynamic analyzers, rubric checker), and self-critique (checklist-based verification)—into a six-iteration dynamic evaluation cycle. Learning trajectories are modeled with three complementary formulations: (i) an interpretable update rule with explicit parameters $\eta$ and $\lambda$ that links next-step gains to feedback quality and the gap-to-target and yields iteration-complexity and stability conditions; (ii) a logistic-convergence model capturing diminishing returns near ceiling; and (iii) a relative-gain regression quantifying the marginal effect of feedback quality on the fraction of the gap closed per iteration. In a Concurrent Programming course ($n=35$), the cohort mean increased from 58.4 to 91.2 (0–100), while dispersion decreased from 9.7 to 5.8 across six iterations; a Greenhouse–Geisser corrected repeated-measures ANOVA indicated significant within-student change. Parameter estimates show that higher-quality, evidence-grounded feedback is associated with larger next-step gains and faster convergence. Beyond performance, we engage the broader pedagogical question of what to value and how to assess in AI-rich settings: we elevate process and provenance—planning artifacts, tool-usage traces, test outcomes, and evidence citations—to first-class assessment signals, and outline defensible formats (trace-based walkthroughs and oral/code defenses) that our controller can instrument. We position this as a design model for feedback policy, complementary to state-estimation approaches such as knowledge tracing. We discuss implications for instrumentation, equity-aware metrics, reproducibility, and epistemically aligned rubrics. Limitations include the observational, single-course design; future work should test causal variants (e.g., stepped-wedge trials) and cross-domain generalization. Full article

The therapeutic use of non-steroidal anti-inflammatory drugs (NSAIDs) is limited by gastrointestinal and renal adverse effects caused by non-selective COX-1 and COX-2 inhibition. To address this issue, a new series of naproxen–azetidinone hybrids was rationally designed and synthesized to enhance COX-2 selectivity and reduce off-target toxicity. The synthesis involved esterification, hydrazide formation, Schiff base condensation, and intramolecular cyclization with chloroacetyl chloride. Structural characterization was achieved through FT-IR, ¹H NMR, and ¹³C NMR analyses. In silico ADMET profiling confirmed compliance with Lipinski’s rule and predicted favorable gastrointestinal absorption. Molecular docking revealed high COX-2 binding affinities (−11.93 to −9.72 kcal/mol), while MM/GBSA analysis identified compound N4_c (ΔG = −62.27 kcal/mol) as the most stable complex, surpassing meloxicam and naproxen. DFT (B3LYP/6-31G(d,p)) frontier molecular orbital analysis indicated a narrow HOMO–LUMO gap (ΔE = 2.97 eV) for N4_c, suggesting high electronic reactivity and strong enzyme interaction. Molecular dynamics simulations confirmed complex stability. In vivo anti-inflammatory testing using an egg-white-induced rat paw edema model showed that N4_d, N4_e, and N4_f achieved higher inhibition (19.22%, 16.98%, and 16.98%) than naproxen (4.3%). These results highlight 2-azetidinone–naproxen hybrids as promising selective COX-2 inhibitors with enhanced pharmacokinetic and electronic properties. Full article

Targeting juvenile hormone esterase (JHE) is an emerging strategy to combat the broadly resistant pest, Plutella xylostella; this study employed transcriptomics to investigate the sublethal effects of the JHE inhibitor OTFP, revealing a non-monotonic dose response characterized by stronger transcriptional changes at lower concentrations, resulting in low mortality, prolonged pupation time, and increased pupal weight. The results from the Differentially Expressed Genes (DEGs) analysis revealed that the core effect of OTFP is the persistent perturbation of the “insect hormone biosynthesis” pathway and altered expression of components of the JH/20E axis; to cope with this stress, the larvae exhibited a dual defense associated with compensatory upregulation of JH-degrading enzyme genes to attempt to restore hormone homeostasis, and the activation of a broad-spectrum detoxification network to clear the compound. More critically, the developmental delay resulting from endocrine disruption KEGG-enriched growth-related pathways (amino-acid and central-carbon metabolism; ribosome biogenesis; aminoacyl-tRNA biosynthesis), consistent with a growth-permissive milieu during prolonged feeding. This study therefore elucidates a novel integrative regulatory network that links endocrine disruption, detoxification, and compensatory growth, revealing a complex physiological trade-off strategy in this pest that sacrifices developmental tempo for survival. Full article

Here, we show that the aureolic acid-class antibiotic, olivomycin A, exerts potent anticancer activity in renal cell carcinoma (RCC) by disrupting both cell survival and metastatic programs. In A-498 (wild-type p53) and 786-O (loss-of-function in p53 and PTEN) cells, olivomycin A markedly inhibited migratory capacity and reversed epithelial–mesenchymal transition (EMT), as shown by downregulation of nuclear Snail and the mesenchymal marker N-cadherin and restoration of the epithelial markers, E-cadherin and ZO-1. In parallel, olivomycin A induced apoptosis through distinct p53-dependent mechanisms: In A-498 cells, apoptosis was primarily mediated through the intrinsic pathway, characterized by the upregulation of Puma, Bak, and activation of caspase-9. In 786-O cells, caspase-8 activation and Bid truncation were observed alongside mitochondrial involvement, suggesting possible cross-talk apoptotic cascades. Notably, in p53-mutant 786-O cells, treatment with olivomycin A elicited severe genotoxic stress accompanied by robust DNA damage signaling, excessive reactive oxygen species (ROS) accumulation, and lysosomal activation, culminating in extensive mitochondrial removal. Such changes were weaker in p53-wild-type A-498 cells, suggesting that the altered p53 context sensitizes RCC cells to olivomycin A-mediated mitochondrial quality control mechanisms. Collectively, our findings delineate a multifaceted mechanism whereby olivomycin A coordinates EMT suppression, apoptotic induction, and mitochondrial clearance. Thus, olivomycin A has potential as a therapeutic candidate that can target both survival and metastatic pathways in heterogeneous genetic backgrounds. Full article