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Contrastive unlearning via representation editing for graph neural networks
Cassipourol and β-sitosterol from Malva parviflora L.: a mechanistic study of dual anti-inflammatory action against COX/LOX and TNF-α/BCL-2
Abstract Although inflammation protects our bodies against harmful stimuli, uncontrolled inflammation drives serious chronic disorders. Malva parviflora L. (family Malvaceae) may represent a source for anti-inflammatory metabolites based on its potent anti-inflammatory activity. Its total ethanol extract demonstrated notable inhibition of cyclooxygenase-1/2 (COX-1/COX-2) and 5-lipoxygenase (5-LOX), with IC 50 values comparable to those of the reference drugs indomethacin and zileuton, respectively. The hexane fraction was the most active fraction (lowest IC₅₀) among the solvent partitions (dichloromethane, ethyl acetate, and butanol). Subsequent column chromatography of the hexane fraction produced two compounds: Cassipourol, isolated for the first time from the Malvaceae family, and β -sitosterol. Their structures were confirmed by matching their NMR and mass spectrometry data with literature. Both were validated in vitro as dual COX/LOX inhibitors, exhibiting IC₅₀ values comparable to those of the standards. To uncover additional mechanisms, a compound–target–inflammation network was constructed using network pharmacology approaches, revealing 178 shared targets. Among these, tumor necrosis factor (TNF- α ) and the antiapoptotic protein B-cell lymphoma 2 (BCL-2) emerged as central nodes linked to inflammatory pathways. Subsequent assays in human colon carcinoma (Caco-2) and lung adenocarcinoma (A549) cell lines showed that β -sitosterol suppressed TNF- α and BCL-2 by approximately 55%, whereas cassipourol displayed only modest inhibition (~20%). Molecular docking predicted moderate ( ca. –4.5) and strong (> –5) binding affinities of both compounds to key inflammatory targets. Collectively, these results suggest that β -sitosterol from M. parviflora is a promising multitarget lead for inflammatory disorders, including cancer, whereas cassipourol requires further structural optimization and mechanistic investigation to improve its unfavorable physicochemical properties.
Enhanced antimicrobial activity, mechanical and dielectric properties of styrene butadiene rubber vulcanizates designed for protection products
Abstract This study focuses on fabricating and evaluating novel, ecofriendly, green, flexible, antimicrobial Styrene Butadiene Rubber vulcanizates for producing safety products. Styrene butadiene rubber (SBR) was compounded with ginger extract, a plant rich in bioactive phenolic compounds, and the conventional drugs, berberine and chitosan, in the ordinary mixer of rubber. Ginger ( Zingiber officinale ) extract was analyzed using HPLC. The rheological properties of the SBR mixes were analyzed to determine the optimal curing time. The compounded rubber mixes were then vulcanized at 152 °C. The prepared vulcanizates were evaluated using Fourier-transform infrared spectroscopy (FTIR), specific surface area measurements, mechanical, swelling, antimicrobial properties, and cytotoxicity analysis. The results showed that the physicochemical and mechanical properties of all vulcanizates remained robust, i.e., no significant degradation, even after exposure to thermal oxidative aging at 90 °C for seven days. Therefore, the change of tensile strength percentage after aging was 25, 5.56, 13, and 10% for free SBR, SBR/30 phr chitosan, SBR/20 phr ginger, and SBR/7 phr berberine, respectively. The cytotoxicity tests confirmed the safety of the investigated vulcanizates due to the negative results against the normal human fibroblast cell line (BJ1). Furthermore, the antimicrobial activity results demonstrated that the release of the various antimicrobial agents successfully inhibited the growth of different bacteria and fungi on the SBR rubber surface. The dielectric and electric findings highlighted the ability of the presence of bioactive agents to modify dielectric relaxation and conductivity in the investigated SBR vulcanizates and confirmed the utility of SBR composites contained 30 phr chitosan, 20 phr ginger, and 7 phr berberine as a good viable choice for antistatic and flexible electronic applications.
Analysis of the ERG25 gene family based on the whole-genome sequence in Trametes versicolor and its response to light stress
Convolutional low-rank adaptation for efficient semantic segmentation in vision transformers
Abstract Vision Transformers (ViTs) have shown remarkable performance across various computer vision tasks, but their fine-tuning for dense prediction tasks such as semantic segmentation remains computationally intensive. This work proposes a novel dual-task architectural application of the LyCORIS Low-Rank Adaptation for Convolutions (LyCORIS LoCon) framework, which introduces learnable low-rank convolutional modules into pre-trained ViTs. This method is applied to Depth Anything V2 (DAV2), augmenting its decoder to support dual-task outputs; monocular depth estimation and binary human semantic segmentation, without disrupting its original capabilities. By injecting only 150K trainable parameters, this approach significantly reduces the adaptation cost while achieving segmentation performance comparable to state-of-the-art models like SAM, MaskFormer, and SegFormer. Extensive experiments on filtered COCO 1 and ImageNet subsets show that Conv-LoRA enhances task-specific learning with minimal computational overhead. The method achieves an mAP of 89.69% and an mIoU of 79.17% for human segmentation, performing competitively alongside state-of-the-art models like Mask2Former, while preserving the depth prediction accuracy of the base model.
Enhanced multi-attribute decision-making method to analyze renewable energy sources for sustainable transportation by synergizing the cubic set with picture fuzzy hypersoft sets
Taxonomic reevaluation of Eryx jaculus in Anatolia with a monotypic perspective
A reliable starfish optimization algorithm for establishing equivalent circuit of proton exchange membrane fuel cell
Abstract The proton exchange membrane fuel cell (PEMFC) can be effectively simulated, managed, and controlled via accurate identification of its model’s unknown parameters. The nonlinear properties of fuel cells (FCs) and the absence of complete data in the datasheet cause certain obstacles in this procedure. This study suggests a novel approach employing the starfish optimization algorithm (SFOA) for designing the equivalent circuit of PEMFC by evaluating its parameters utilizing experimental data. This algorithm is highly efficient as well as avoiding local optima due to exploitation and exploration balance. Five distinct FCs are analyzed: Horizon_H12, Horizon H-1000XP PEMFC stack, Temasek_1kw, SR-12PEM 500-W, and BCS-500W PEMFC stacks. The suggested SFOA is evaluated in comparison with previously published techniques of seagull optimization algorithm (SOA), escape optimizer (ESC), gold rush optimizer (GRO), tunicate swarm algorithm (TSA), beluga whale optimization (BWO), success history intelligent optimizer (SHIO), enhanced transient search optimizer (ESTO) and Newton–Raphson-based optimizer (NRBO). Decreasing the sum square error (SSE) between the calculated and measured output voltages is the targeted goal. The minimum values of SSE obtained through the suggested SFOA are 4.662696E−04, 3.948527E−01, 5.4322160E−01, 1.056370, and 1.169778E−02 for Horizon_H12, Horizon H-1000XP PEMFC stack, Temasek_1kw, SR-12PEM 500-W, and BCS-500W PEMFC stacks, respectively. Additionally, the PEMFC dynamic simulation model is constructed in Matlab/Simulink, while step load disruption is employed for analyzing the model’s performance. The acquired results indicate the success of the suggested SFOA in constructing dependable models of different PEMFCs.
Grating based interferometric devices on a silicon photonic platform
Abstract This work presents a class of integrated photonic interferometers based on the Michelson architecture, implemented on a silicon-on-insulator platform operating at 1.5–1.6 $$\mu$$ m. The devices combine directional couplers, subwavelength gratings (SWG), and Bragg grating reflectors. Furthermore, by cascading and branching multiple Michelson units, we demonstrate more complex interferometric structures for specialized applications. The integration of SWG sections enables fine-tuning of the effective refractive index and enhances sensitivity for sensing applications through increased evanescent field interaction with the surrounding medium. Selected designs are fabricated and experimentally characterized. Fabricated Fabry-Pérot devices achieve quality factors exceeding 6,500, while Michelson-based structures exhibit extinction ratios up to 43 dB, demonstrating good qualitative agreement with simulations. Finally, we explore potential applications optical filtering, sensing, and electro-optic modulation.
Techno-economic analysis and resilience enhancement of a hospital microgrid under grid outage scenarios
Abstract Hospitals are critical infrastructures where power continuity is paramount. This study presents a techno-economic and resilience analysis of a grid-connected hybrid microgrid for a medium-sized hospital, comprising solar photovoltaics (PV), a battery energy storage system (BESS), and a diesel generator. Using a mixed-integer linear programming (MILP) model via NREL’s REopt ® platform, we optimized the system design to minimize the Net Present Cost (NPC) while ensuring an uninterrupted power supply to critical loads during grid outages. The analysis evaluated a wide range of outage scenarios, varying in duration (7–24 h), timing, season, and critical load level (50–100%). This study shows that a design of a microgrid for enhanced resilience is both technically and economically beneficial. The microgrid design with optimization achieves a net present cost savings of 14% for the financial optimization scenario and 9% to 14.2% for all the resilience-constrained scenarios compared to the business-as-usual case of 100% grid dependence. Most importantly, compared to the financial optimum rather than the business-as-usual case, the cost of including resilience constraints is a mere 0.4% to 2.4% of net present cost, showing that increased energy resilience can be delivered at a minimal cost. A key finding is that systems designed for summer outages yield higher savings due to greater solar availability, and a strategic deep-discharge protocol for the battery during emergencies is crucial for cost-effectiveness. This work provides an actionable framework for hospital administrators to enhance energy resilience without incurring a financial penalty, and in many cases, while realizing significant long-term cost savings.
Lipid ligand binding and membrane interactions of a novel food-derived lipid transfer protein enhance basophil allergic responses
Abstract Non-specific (ns) lipid transfer proteins (LTPs) are lipid-binding allergens whose natural ligands are not fully known. To elucidate the function and allergenic relevance of nsLTP-lipid complexes, purified natural Lupinus luteus ( L. luteus ) nLTP and recombinant peach LTP, rPru p 3, were tested for membrane interaction and lipid transport activity using liposome assays and Förster-resonance-energy-transfer (FRET) in a case-level proof-of-principle investigation. Allergenic relevance of the LTP-lipid interaction was evaluated in the presence of oleic acid (OA), phosphatidylcholine (PC), phosphatidylglycerol (PG), and phosphatidylserine (PS) in a basophil activation test (BAT) with effector cells from an LTP-allergic patient. Both LTPs interacted with neutral PC and negatively charged PS liposomal membranes. A novel transport activity for anionic PG species was identified for both proteins, indicating a shared functional preference for the glycerol headgroup. LTP-dependent lipid exchange/mixing were consistent with transfer. However, fusion/mixing mechanisms cannot be excluded with the current readout. In BAT, both LTPs showed enhanced activation in combination with OA, PC, PG, and PS. As PG is a key component of bacterial membranes, the PG specificity of the lipid interaction of L. luteus nLTP and rPru p 3 is likely of relevance in allergen interaction with the gut microbiome and for enhancement of allergic symptoms. These findings highlight lipid-specific functional properties and lipid-dependent modulation of allergenic activity in plant nsLTPs.
Mutational analysis of multidrug efflux pump (AcrAB-TolC) in Enterobacter cloacae isolates from clinical samples
Thickness dependent properties of NiO thin films on ITO/PET flexible substrates for solar cell applications
System for study of diverse cellular composition in alveolar rhabdomyosarcoma
Bioprospecting of bacteria from textile effluents for enhanced dye biodegradation
Single-shot detection limits of quantum illumination with multi-qudit states
Path analysis of cardiovascular disease preventive health behavior in postmenopausal Korean women based on the I-Change model
Abstract Postmenopausal women are at increased risk of cardiovascular disease (CVD) owing to hormonal changes; however, many remain unaware of this increased risk and do not engage in CVD-preventive health behavior. This study aimed to examine factors associated with CVD-preventive health behavior among postmenopausal women living in residential area across South Korea. Data were collected through an online survey of 227 community-dwelling postmenopausal women. Associations among CVD knowledge, risk perception, attitudes, social support, intention, and CVD-preventive health behavior were examined using the Integrated Change (I-Change) model and analyzed through path analysis. The path analysis showed that CVD knowledge had a direct effect on attitudes (β = .21, p < .001), self-efficacy (β = .15, p = .021), and social support (β = .15, p = .023). Self-efficacy (β = .37, p < .001) and intention (β = .38, p < .001) had direct effects on CVD-preventive health behavior. The final model explained 48.7% of the variance in CVD-preventive health behavior. These findings suggest that self-efficacy and intention play important mediating roles in the association between CVD knowledge and CVD-preventive health behavior among postmenopausal women. Therefore, interventions aimed at reducing CVD risk should consider strategies to enhance self-efficacy and strengthen behavioral intention.
Experimental and analytical geodetic accuracy assessment of terrestrial laser scanning for deformation monitoring under static and dynamic conditions
Abstract Recent advances in three-dimensional (3D) measurement technologies have significantly improved the capability of monitoring the structural deformation. Among these technologies, terrestrial laser scanning (TLS) has emerged as a powerful geodetic tool capable of rapidly acquiring dense 3D point clouds with millimeter-level accuracy. However, the reliability of TLS for high-precision deformation monitoring requires comprehensive experimental and analytical validation and assessment under both static and dynamic measurement conditions. This study presents a detailed experimental and analytical evaluation of the geometric accuracy of TLS observations for structural deformation monitoring. A series of controlled experiments were conducted to assess the accuracy of coordinates, distances and angular measurements derived from TLS by comparing them with reference observations obtained using a high-precision total station. The capability of TLS to detect small structural displacements was also investigated through controlled horizontal, vertical and inclined movements measured using a digital accurate vernier device. Furthermore, the influence of tripod-induced vibrations on TLS measurement accuracy was examined under different vibration frequencies and amplitudes in order to simulate dynamic field conditions. The practical applicability of TLS in structural health monitoring was also demonstrated through a real industrial case study involving the geometric assessment and inclination analysis of a vertical cylindrical oil storage tank located in Ras – Gharib city, Egypt. The experimental results indicate that TLS can detect structural displacements with discrepancies ranging between 0.78 and 2.16 mm compared with reference measurements, while vibration effects can introduce distance variations of up to 4.1 mm and horizontal angular deviations reaching approximately 100 arc-seconds under several vibration conditions. These results provide practical insights into the capabilities and operational limitations of TLS technology and support its effective application in structural deformation monitoring and precision engineering surveying.
Individual threat-relevance accelerates belief-updating in conditioned hallucinations
Abstract Threat-related learning is implicated in psychopathological hallucinations; however, its role in experimentally-induced hallucinations remains unclear. Here, we investigated how threat-relevant stimuli (spiders vs. flowers) influence conditioned hallucinations (i.e., illusory auditory tones triggered by learned associations with images). We found that, for conditioning with spiders (but not flowers), higher spider-phobia was related to time-dependent variations in conditioned hallucinations: increasing in early phases (where spiders reliably predicted tones) and decreasing in later phases (as this predictive relationship weakened). These tendencies were related to accelerated belief-updating in a hierarchical Gaussian filter model and shifts in participants’ internal criterion within a signal detection framework. Additionally, trait anxiety and hallucination-proneness were inversely related to conditioned hallucinations and reliance on prior beliefs, but did not significantly vary according to image condition. Unlike the theorized role of threat in developing rigid priors and clinical hallucinations, our findings indicate that individual threat-relevance sensitises hallucination-related beliefs to shifting stimulus contingencies.