Search Results (826)

The expansion of renewables in modern power systems and the coordinated development of upstream and downstream industrial chains are promoting a shift on the utility side from traditional settlement by energy toward operation driven by data and models. Industrial electricity consumption data exhibit pronounced multi-scale temporal structures and sectoral heterogeneity, which makes unified long-term load and generation forecasting while maintaining accuracy, interpretability, and scalability a challenge. From a modern system identification perspective, this paper proposes a System Identification in Adaptive Bayesian Framework (SIABF) for medium- and long-term industrial load forecasting based on daily freeze electricity time series. By combining daily aggregation of high-frequency data, frequency domain analysis, sparse identification, and long-term extrapolation, we first construct daily freeze series from 15 min measurements, and then we apply discrete Fourier transforms and a spectral complexity index to extract dominant periodic components and build an interpretable sinusoidal basis library. A sparse regression formulation with ${\ell }_1$ regularization is employed to select a compact set of key basis functions, yielding concise representations of sector and enterprise load profiles and naturally supporting multivariate and joint multi-sector modeling. Building on this structure, we implement a state-space-implicit physics-informed Bayesian forecasting model and evaluate it on real data from three representative sectors, namely, steel, photovoltaics, and chemical, using one year of 15 min measurements. Under a one-month-ahead evaluation using one year of 15 min measurements, the proposed framework attains a Mean Absolute Percentage Error (MAPE) of 4.5% for a representative PV-related customer case and achieves low single-digit MAPE for high-inertia sectors, often outperforming classical statistical models, sparse learning baselines, and deep learning architectures. These results should be interpreted as indicative given the limited time span and sample size, and broader multi-year, population-level validation is warranted. Full article

This study introduces a framework for estimating the optical scattering properties of thin-film phantoms using a custom-built Spectral-Domain Dental Optical Coherence Tomography (DEN-OCT) system operating within the 780–900 nm spectral range. The purpose of this work was to assess the performance of this system. The system exhibited high depth-resolved imaging performance with an axial resolution of approximately 16.30 µm, a signal-to-noise ratio of about 32.4 dB, and a 6 dB sensitivity roll-off depth near 2 mm, yielding an effective imaging range of 2.5 mm. Thin-film phantoms with controlled optical characteristics were fabricated and analyzed using Beer–Lambert and diffusion approximation models to evaluate attenuation behavior. Samples representing different tissue analogs demonstrated distinct scattering responses: one sample showed strong scattering similar to hard tissues, while the others exhibited lower scattering and higher transmission, resembling soft-tissue properties. Spectrophotometric measurements at 840 nm supported these trends through characteristic transmittance and reflectance profiles. While homogeneous samples conformed to analytical models, the highly scattering sample deviated due to structural non-uniformity, requiring Monte Carlo simulation to accurately describe photon transport. OCT A-scan analyses fitted with exponential decay models produced attenuation coefficients consistent with spectrophotometric data, confirming the dominance of scattering over absorption. The integration of OCT imaging, optical modeling, and Monte Carlo simulation establishes a reliable methodology for quantitative scattering estimation and demonstrates the potential of the developed DEN-OCT system for advanced dental and biomedical imaging applications. The innovation of this work lies in the integration of phantom-based optical calibration, multi-model scattering analysis, and depth-resolved OCT signal modeling, providing a validated pathway for quantitative parameter extraction in dental OCT applications. Full article

Background: Three-dimensional (3D) printing has been established in pharmaceutical sciences for preparing customized dosage forms with intricate release profiles. However, realizing this potential requires complex design strategies and the careful use of various excipients. This study was designed to evaluate the utility of hypromellose acetate succinate (HPMC-AS) as a singular release-modifying excipient for manufacturing oral solid dosage forms via fused deposition modeling (FDM) 3D printing. Methods: The scope of work encompassed comprehensive material characterization, formulation and production of drug-loaded filaments using hot-melt extrusion (HME), subsequent FDM 3D printing of tablet geometries, and in vitro dissolution studies using mebeverine hydrochloride (MebH) as the model drug. Results: Initial HME processing indicated that the HPMC-AS-based filaments were brittle, presenting technical challenges for direct 3D printing. This issue was successfully overcome by incorporating an additional preheating stage into the FDM printing process, which enabled production of the tablets. Dissolution analysis demonstrated that the 3D-printed mebeverine hydrochloride tablets exhibited delayed and sustained-release characteristics. Conclusions: These results confirm the viability of HPMC-AS as a standalone functional excipient in FDM 3D printing to produce tailored, complex drug delivery systems. Full article

Objectives: The aim of this study was to compare the stiffness-related mechanical response and peak von Mises stress distribution of low-profile 2.4 mm mandibular reconstruction systems (a conventional reconstruction plate, a 3D grid-type plate, and a customized plate) in a virtual atrophic mandible model with a 5 cm segmental defect. Materials and Methods: A CT-based three-dimensional mandible model was created and instrumented with three plate configurations (G1–G3). Linear static finite element analyses were performed under a 300-N masticatory load combined with literature-based muscle force vectors. Peak von Mises stresses were recorded for plates and screws, and the locations of maximum stress concentration were identified. Results: Peak plate stress was highest in the conventional reconstruction plate (G1: 695.5 MPa), followed by the 3D grid-type plate (G2: 595.6 MPa), and lowest in the customized plate (G3: 185.2 MPa). The peak screw stress was 692.9 MPa (G1), 898.0 MPa (G2), and 595.6 MPa (G3). The 3D grid-type plate increased construct stiffness but shifted stress concentration toward the mandibular angle and adjacent screws, whereas the customized plate reduced the peak plate stress and limited the extent of the high-stress region across the defect. Conclusions: Within the limitations of a linear static FEA (stiffness/stress distribution rather than failure load or fatigue resistance), the customized plate (G3) demonstrated the most favorable biomechanical performance (lowest peak plate stress). The 3D grid-type plate (G2) reduced peak plate stress compared with the conventional design (G1) but produced the highest peak screw stress. Practical considerations such as manufacturing lead time and resource requirements may favor off-the-shelf plates; however, a formal cost or operative-time analysis was not performed. Full article

The use of lecithin as an emulsifier in food supplements has increased in recent years. However, successful formation of liposomes or micelles requires an appropriate mixture of phospholipids in lecithin. To evaluate the emulsification properties of lecithin for food supplements, a reliable analytical procedure for characterizing phospholipids is necessary. A liquid chromatography–mass spectrometry method was developed to identify phospholipids in lecithin without standard reference materials. For efficient separation of phospholipids before mass spectrometric analysis, a reverse-phase high-performance liquid chromatography method was optimized using a Waters XBridge Protein BEH C4 column. The optimized chromatographic method demonstrated good linearity and precision. Molecular ions were detected in full scan mode to determine accurate mass-to-charge ratios for individual peaks in the chromatogram. A custom Python program was then used to generate a list of possible phospholipid species for each peak based on the measured mass-to-charge ratios. Tandem mass spectrometry was performed to confirm the identity of specific phospholipids by comparing experimental fragmentation patterns with theoretical predictions. Identification of the phospholipids was also confirmed with four commercially available standard reference compounds, demonstrating the reliability of the proposed approach. The developed method offers a practical and cost-effective strategy for identifying phospholipids in complex matrices, especially when standard reference compounds are unavailable. Additionally, it enables targeted selection of standard compounds for future quantitative analyses, making it a valuable tool for comprehensive lipid profiling. Full article

CRISPR-Cas9 systems have enabled unprecedented advances in genome engineering, particularly in developing treatments for human diseases, like cancer. Despite potential applications, limitations of Cas9 include its relatively large size and strict targeting requirements. Cas12j2, a variant ofCasΦ-2, shows promise for overcoming these limitations. However, its effectiveness in mammalian cells remains relatively unexplored. This study sought to develop an optimized CRISPR-Cas12j2 system for targeted knockout of the E6 oncogene in HPV-associated cancers. A combination of computational tools (ColabFold, CCTop, Cas-OFFinder, HADDOCK2.4, and Amber for Molecular Dynamics) was utilized to investigate the impact of engineered modifications on structural integrity and gRNA binding of Cas12j2 fusion constructs, in potential intracellular conditions. Cas12j2_F2, a Cas12j2 variant designed and evaluated in this study, behaves similarly to the wild-type Cas12j2 structure in terms of RMSD/RMSF profiles, compact Rg values, and minimal electrostatic perturbation. The computationally validated Cas12j2 variant was incorporated into a custom expression vector, co-expressing the engineered construct along with a dual gRNA for packaging into a viral vector for targeted knockout of HPV-associated cancers. This study provides a structural and computational foundation for the rational design of Cas12j2 fusion constructs with enhanced stability and functionality, supporting their potential application for precise genome editing in mammalian cells. Full article

Epileptic seizures arise from abnormally synchronized neural activity and remain a major global health challenge, affecting more than 50 million people worldwide. Despite advances in pharmacological interventions, a significant proportion of patients continue to experience uncontrolled seizures, underscoring the need for alternative neuromodulation strategies. Rhythmic neural entrainment has recently emerged as a promising mechanism for disrupting pathological synchrony, but most existing systems rely on complex analog electronics or high-power stimulation hardware. This study investigates a proof-of-concept digital custom-designed chip that generates a stable 6 Hz oscillation capable of imposing a stable rhythmic pattern onto digitized seizure-like EEG dynamics. Using a publicly available EEG seizure dataset, we extracted and averaged analog seizure waveforms, digitized them to emulate neural front-ends, and directly interfaced the digitized signals with digital output recordings acquired from the chip using a Saleae Logic analyser. The chip’s pulse train was resampled and low-pass-reconstructed to produce an analog 6 Hz waveform, allowing direct comparison between seizure morphology, its digitized representation, and the entrained output. Frequency-domain and time-domain analyses demonstrate that the chip imposes a narrow-band 6 Hz rhythm that overrides the broadband spectral profile of seizure activity. These results provide a proof-of-concept for low-power digital custom-designed entrainment as a potential pathway toward simplified, wearable neuromodulation device for future healthcare diagnostics. Full article

This study evaluated the effect of clockwise reciprocation motion used in the original Optimum Torque Reverse kinematics, compared with clockwise continuous rotation, on the cyclic fatigue strength of nickel–titanium rotary instruments (NiTi) with different metallurgical characteristics. A total of 120 instruments, ProFile and EndoSequence in sizes 25/.04, 30/.04, and 35/.04, were tested under continuous rotation or reciprocation motions (n = 10 per subgroup). Instruments were examined by optical and scanning electron microscopy to exclude manufacturing defects. Phase transformation temperatures were determined by differential scanning calorimetry, and cyclic fatigue testing was conducted using a custom device simulating a curved canal with a 6 mm radius and an 86° curvature. The time to fracture was recorded, and the number of cycles to fracture was calculated. Statistical comparisons were performed using the Mann–Whitney U test with a significance level of p < 0.05. Differential scanning calorimetry showed that ProFile instruments were fully austenitic at the test temperature, while EndoSequence instruments exhibited a mixed R-phase and austenitic structure. Clockwise reciprocation motion significantly increased cyclic fatigue resistance in all groups compared with clockwise continuous rotation. Time to fracture increased by 241.3% to 337.5%, and EndoSequence instruments consistently demonstrated higher fatigue resistance. The greatest relative improvement was observed in ProFile 35/.04, with a 422.4% increase in the number of cycles to fracture. Overall, the reciprocation motion markedly enhanced cyclic fatigue strength irrespective of metallurgical phase composition, indicating a practical mechanical benefit that may reduce the risk of instrument separation during endodontic procedures. Full article

Diffractive optical elements (DOEs) offer significant advantages over conventional refractive optics, particularly in non-visible spectral regions such as ultraviolet, gamma rays, and X-rays, where material limitations restrict traditional optical components. Owing to their design flexibility, DOEs enable the generation of complex beam profiles—including circular, vortex, and Airy beams—across a wide range of wavelengths. Despite their structural simplicity and compatibility with micro- and nanoscale fabrication, conventional DOEs often suffer from limited focusing efficiency, frequently requiring additional refractive lenses that introduce optical aberrations, increased system complexity, and higher cost. In this work, we present an integrated design and fabrication approach for micro-scale diffractive optical elements capable of achieving high focusing performance without reliance on supplementary optical components. A machine learning-based decision tree method is employed to generate optimized writing paths, which are subsequently fabricated using direct laser lithography. The proposed integrated DOE structures enable efficient focusing of multiple customized beam profiles within a compact and standalone optical element. This approach improves optical efficiency while maintaining low fabrication cost and system simplicity. The demonstrated integrated micro-DOEs provide a scalable and versatile platform for advanced beam shaping and focusing applications in photonics, particularly where compactness and performance are critical. Full article

Marine aerosol particles influence the climate, and interactions between ocean waves and coral reefs may impact aerosol size distributions in remote locations, such as the Great Barrier Reef. However, quantifying these processes has proven to be challenging. We tested whether marine aerosol size distributions and concentrations differ across four zones: background air outside the lagoon, above the reef crest, within the lagoon, and near the beach of Heron Island, approximately 85 km offshore. Using a modified DJI Matrice 600 hexacopter equipped with a miniaturised optical particle counter and custom inline gas dryer, we measured aerosols from 165 to 3000 nm across 64 drone flights during 16 sampling events in November 2024. Aerosol concentrations showed substantial day-to-day temporal variability, while spatial differences among reef zones were generally minor; on certain days, the maximum difference between background and near-island measurements reached approximately 25%. K-means clustering identified four dominant air mass transport patterns, and Hybrid Single-Particle Lagrangian Integrated Trajectory model analysis indicated that upwind conditions had a strong influence on aerosol loading. Vertical profiles revealed limited variability within the lowest 100 m. Mixing layer height, air parcel travel speed, and water depth along the final 12 h of trajectories were key drivers of aerosol variability. These results demonstrate the potential of drone-based measurements for characterising marine aerosols and provide a foundation for improving climate model representations of natural aerosol processes. Full article

Microneedle (MN) technologies have emerged as a groundbreaking platform for transdermal and intradermal drug delivery, offering a minimally invasive alternative to oral and parenteral routes. Unlike passive transdermal systems, MNs allow the permeation of hydrophilic macromolecules, such as peptides, proteins, and vaccines, by penetrating the stratum corneum barrier without causing pain or tissue damage, unlike hypodermic needles. Recent advances in materials science, microfabrication, and biomedical engineering have enabled the development of various MN types, including solid, coated, dissolving, hollow, hydrogel-forming, and hybrid designs. Each type has unique mechanisms, fabrication techniques, and pharmacokinetic profiles, providing customized solutions for a range of therapeutic applications. The integration of 3D printing technologies and stimulus-responsive polymers into MN systems has enabled patches that combine drug delivery with real-time physiological sensing. Over the years, MN applications have grown beyond vaccines to include the delivery of insulin, anticancer agents, contraceptives, and various cosmeceutical ingredients, highlighting the versatility of this platform. Despite this progress, broader clinical and commercial adoption is still limited by issues such as scalable and reliable manufacturing, patient acceptance, and meeting regulatory expectations. Overcoming these barriers will require coordinated efforts across engineering, clinical research, and regulatory science. This review thoroughly summarizes MN technologies, beginning with their classification and drug-delivery mechanisms, and then explores innovations, therapeutic uses, and translational challenges. It concludes with a critical analysis of clinical case studies and a future outlook for global healthcare. By comparing technological progress with regulatory and commercial hurdles, this article highlights the opportunities and limitations of MN systems as a next-generation drug-delivery platform. Full article

Background: Unhealthy diets characterized by high salt, fat, and fructose content are established risk factors for metabolic and cardiovascular disorders and may have indirect effects on cognitive function. However, the combined impact of a high-salt, high-fat, and high-fructose diet (HSHFHFD) on systemic physiology and brain health remains to be fully elucidated. Methods: Sprague-Dawley (SD) rats received a customized high-salt, high-fat diet supplemented with 30% fructose water for 18 weeks. Physiological and brain parameters were assessed, in combination with multi-omics analyses including brain proteomics and metabolomics, serum metabolomics, and gut microbiota profiling. Results: HSHFHFD significantly elevated blood glucose, blood pressure, and serum levels of TG, TC, and LDL in rats. Serum metabolomic profiling identified over 100 differentially abundant metabolites in the Model group. Proteomics, metabolomics, and gut microbiome integration revealed pronounced alterations in both brain proteomic and metabolomic profiles, with 155 differentially expressed proteins associated with glial cell proliferation and 65 differential metabolites linked to fatty acid and amino acid metabolism, among others. Experimental validation confirmed marked upregulation of GFAP and Bax protein, concomitant with downregulation of ZO-1 and occludin. Furthermore, HSHFHFD perturbed the CREB signaling pathway, leading to diminished BDNF expression. The levels of inflammatory factors, including IL-6, IL-10, IL-1β and TNFα, were significantly elevated in the brain. Oxidative stress was evident, as indicated by elevated malondialdehyde (MDA) levels, increased superoxide dismutase (SOD) activity, and altered NAD⁺/NADH ratio. Additionally, HSHFHFD significantly reduced the abundance of beneficial gut bacteria, including Lactobacillus, Romboutsia, and Monoglobus. Conclusions: HSHFHFD-induced depletion of gut Lactobacillus spp. may disrupt the linoleic acid metabolic pathway and gut–brain axis homeostasis, leading to the impairment of neuroprotective function, blood–brain barrier dysfunction, and exacerbated neuroinflammation and oxidative stress in the brain. These effects potentially increase the susceptibility of rats to neurodegenerative disorders. Full article

Total hip arthroplasty (THA) is a transformative procedure for managing severe hip disorders, yet implant longevity remains a critical challenge, particularly for younger, active patients. Wear-related complications are a leading cause of revision surgery, emphasizing the need for optimized design and material performance. This systematic review aims to synthesize evidence on the wear behavior, material properties, and design parameters of hip implants with a focus on finite element analysis (FEA)-based predictive approaches. A comprehensive literature search was conducted across Scopus, PubMed, ScienceDirect, MDPI, and Cochrane databases following PRISMA guidelines. Studies published between 2010 and 2025 were included if they addressed THA biomechanics, wear analysis, or material optimization using FEA, hip simulators, or radiostereometric techniques. Key findings reveal that larger femoral heads, while reducing contact pressure, increase wear due to greater sliding distance. Gravimetric wear rates ranged from 3.15 ± 0.27 mg/Mc to 2.18 ± 0.31 mg/Mc, while linear and volumetric wear reached 0.0375 mm/Mc and 33.6 mm³/Mc, respectively. Stress analysis showed custom stems exhibited markedly lower von Mises stress (194.9 MPa) compared to standard designs (664.3 MPa), and fatigue assessments confirmed a factor of safety > 1 across profiles. Patient-specific factors, such as body weight, significantly influenced wear with a 26% increase in metal wear observed between 100 kg and 140 kg. This systematic review synthesizes current research on total hip arthroplasty, emphasizing biomechanical and material factors critical for implant longevity and patient care. It uniquely integrates FEA-based wear prediction with clinical implications, bridging computational modeling, geometry optimization, and material performance to provide actionable insights for next-generation, patient-specific hip implant design. Full article

The optimization of bioactive compound extraction from medicinal herbs is critical for developing functional food ingredients with substantiated health benefits. This study employed response surface methodology (RSM) and partial least squares (PLS) regression to maximize polyphenol recovery and antioxidant capacity from five medicinal herbs (Helichrysum stoechas, Chelidonium majus, Mentha pulegium, Artemisia absinthium, and Adiantum capillus-veneris). A custom experimental design assessed the effects of herb identity, extraction technique, and solvent-to-solid ratio on total polyphenolic content (TPC), total flavonoid content (TFC), ferric reducing antioxidant power (FRAP), and DPPH radical scavenging activity. The PLS compromise optimum was identified for M. pulegium using 60% ethanol at 55 mL/g, yielding 37.54 ± 2.10 mg GAE/g dw TPC, 21.62 ± 1.15 mg RtE/g dw TFC, 334.38 ± 12.37 µmol AAE/g dw FRAP, and 262.67 ± 9.46 µmol AAE/g dw DPPH. HPLC-DAD profiling revealed 18 polyphenolic compounds (10.22 ± 0.34 mg/g dw), dominated by kaempferol-3-O-β-rutinoside, protocatechuic acid, and luteolin-7-O-glucoside. These compounds contribute complementary mechanisms: protocatechuic acid modulates oxidative and antioxidant pathways, kaempferol-3-O-β-rutinoside exerts cardioprotective and anti-inflammatory effects via VEGF-C binding, and luteolin-7-O-glucoside suppresses NF-κB-mediated inflammatory signaling. Principal component analysis (PCA) explained 84.8% of variance, clearly separating optimized from non-optimized extracts, while PLS confirmed strong correlations between specific phenolics and antioxidant indices. Overall, this integrated chemometric approach demonstrates that data-driven optimization can deliver phenolic-rich herbal extracts with robust and balanced antioxidant potential for functional food applications. Full article

The practical deployment of Orthogonal Frequency Division Multiplexing Passive Optical Networks (OFDM-PONs) is hindered by the lack of a Medium Access Network (MAC) protocol capable of managing their flexible, distance-dependent data rates, despite their high spectral efficiency. This paper proposes and validates a novel rate-adaptive, Time Division Multiplexing (TDM)-based MAC protocol for OFDM-PON systems. A key contribution is the design of a three-layer header frame structure that supports multi-ONU data scheduling with heterogeneous rate profiles. Furthermore, the protocol incorporates a unique channel probing mechanism to dynamically determine the optimal transmission rate for each Optical Network Unit (ONU) during activation. The proposed Optical Line Terminal (OLT) side MAC protocol has been fully implemented in hardware on a Xilinx VCU118 FPGA platform, featuring a custom-designed ring buffer pool for efficient multi-ONU data management. Experimental results demonstrate robust upstream and downstream data transmission and confirm the system’s ability to achieve flexible net data rate switching on the downlink from 8.1 Gbit/s to 32.8 Gbit/s, contingent on the assigned rate stage. Full article