Search Results (645)

Biopharmaceutical medicines represent one of the most dynamic sectors of the pharmaceutical industry, with therapeutic proteins forming the largest and most important group. Their structural complexity and inherent sensitivity to chemical and physical stressors, however, continue to pose major challenges for formulation development and long-term stability. Short peptides have emerged as a promising yet underutilized class of excipients for protein-based drug products. Their modular architecture allows for precise tuning of physicochemical properties such as polarity, charge distribution, and hydrogen-bonding potential, thereby offering advantages over single amino acids. Experimental studies indicate that short peptides can serve multiple functions: stabilizers, antioxidants, viscosity-lowering agents, and as lyo/cryoprotectants or bulking agents in lyophilized formulations. Notably, the relatively small and chemically defined space of short peptides—approximately 400 possible dipeptides and 8000 tripeptides—makes them particularly amenable to systematic screening and computational modeling. This enables rational identification of candidates with tailored excipient functions. This review summarizes current knowledge on the use of short peptides as excipients in parenteral protein formulations, with a focus on their functional versatility and potential for rational design in future development. Full article

The important function of polar lipids in the biochemical chains of photosynthesis, the outstanding biochemical process on our planet, has been mentioned in many publications. Over the last several years, apart from the known function of lipids in creating a matrix for photosynthetic complexes, most attention has been paid to the role of lipids in building up and functioning of the photosynthetic complexes. The lipid molecules are found inside the complexes of photosystem II (PSII), photosystem I (PSI), and cytochrome b₆f (Cyt b₆f) together with other cofactors that accompany proteins and chlorophyll molecules. Super complexes PSII-light-harvesting complex II (PSII-LHCII) and PSI-light-harvesting complex I (PSI-LHCI) also include lipid molecules; part of the lipid molecules is located at the borders between the separate monomers of the complexes. Our interest is in the exact localization of lipid molecules inside the monomers: what are the protein subunits with the lipid molecules in between and how do the lipids contact directly with the amino acids of the proteins? The photosystems include very few classes of all the polar lipids, three groups of glyceroglycolipids, and one group of glycerophospholipids make up the quartet of polar lipids. What are the reasons they have been selected for the role? There are no doubts that the polar heads and the fatty acids chains of these lipids are taking part in the processes of photosynthesis. However, what are the distinct roles for each of them? The advantages and disadvantages of the head groups of lipids from thylakoid membranes and those lipids that for various reasons could not take their place are discussed. Attention is focused on those bound fatty acids that predominate or are characteristic for each class of thylakoid lipids. Emphasis is also placed on the content of each of the four lipids in all photosynthetic complexes, as well as on contacts of head groups and acyl chains of lipids with specific proteins, transmembrane chains, and their amino acids. This article is devoted to the search for answers to the questions posed. Full article

Most clinically used antibiotics exert their effects by targeting essential intracellular components of bacterial cells. Therefore, enhancing their ability to traverse the bacterial envelope is crucial for restoring or improving therapeutic efficacy. We investigated the potential of outer membrane (OM)-disrupting agents—EDTA, NV716, colistin, and squalamine—to potentiate antibiotic activity against the multi-drug-resistant pathogen Pseudomonas aeruginosa. Our objective was to assess the therapeutic value of this strategy while also delineating its limitations by comparing responses across antibiotic classes with diverse chemical structures and pharmacological profiles. Beyond lipophilicity, we analyzed three additional physicochemical descriptors likely to influence OM permeability: molecular surface area, polarizability, and polar surface area. Our findings offer practical insights for the rational design of antibiotic–adjuvant combinations. While each descriptor provides valuable interpretive information, none alone reliably predicts OM-mediated potentiation. Instead, these factors should be viewed collectively within a multidimensional physicochemical profile, where optimal ranges of size, polarity, and lipophilicity act synergistically to enhance antibiotic uptake. By defining a shared multidimensional “responsive zone,” we propose a framework to guide the selection or design of antibiotics compatible with OM-disrupting strategies, potentially enabling the repurposing of antibiotics limited by poor OM permeability. Full article

Multiple-Q magnetic states encompass a broad class of noncollinear and noncoplanar spin textures generated by the superposition of spin density waves. In this study, we theoretically explore the emergence of vortex crystals formed by multiple-Q spin density waves on a two-dimensional triangular lattice with $D_{3\mathrm{h}}$ point group symmetry. Using simulated annealing applied to an effective spin model, we demonstrate that the synergy among the easy-plane single-ion anisotropy, the biquadratic interaction, and the out-of-plane Dzyaloshinsky–Moriya interaction defined in momentum space can give rise to a variety of double-Q and triple-Q vortex crystals. We further examine the role of easy-plane single-ion anisotropy in triple-Q vortex crystals and show that weakening the anisotropy drives topological transitions into skyrmion crystals with skyrmion numbers $\pm 1$ and $\pm 2$. The influence of an external magnetic field is also analyzed, revealing a field-induced phase transition from vortex crystals to single-Q conical spirals. These findings highlight the crucial role of out-of-plane Dzyaloshinskii–Moriya interactions in stabilizing unconventional vortex crystals, which cannot be realized in systems with purely polar or chiral symmetries. Full article

We investigated the impact of incorporating quantitative reasoning for deeper sense-making in a Quantum Interactive Learning Tutorial (QuILT) on students’ conceptual performance using a framework emphasizing integration of conceptual and quantitative aspects of quantum optics. In this investigation, we compared two versions of the QuILT that were developed and validated to help students learn various aspects of quantum optics using a Mach Zehnder Interferometer with single photons and polarizers. One version of the QuILT is entirely conceptual while the other version integrates quantitative and conceptual reasoning (hybrid version). Performance on conceptual questions of upper-level undergraduate and graduate students who engaged with the hybrid QuILT was compared with that of those who utilized the conceptual QuILT emphasizing the same concepts. Both versions of the QuILT focus on the same concepts, use a scaffolded approach to learning, and take advantage of research on students’ difficulties in learning these challenging concepts as well as a cognitive task analysis from an expert perspective as a guide. The hybrid and conceptual QuILTs were used in courses for upper-level undergraduates or first-year physics graduate students in several consecutive years at the same university. The same conceptual pre-test and post-test were administered after traditional lecture-based instruction in relevant concepts and after student engaged with the QuILT, respectively. We find that the post-test performance of physics graduate students who utilized the hybrid QuILT on conceptual questions, on average, was better than those who utilized the conceptual QuILT. For undergraduates, the results showed differences for different classes. One possible interpretation of these findings that is consistent with our framework is that integrating conceptual and quantitative aspects of physics in research-based tools and pedagogies should be commensurate with students’ prior knowledge of physics and mathematics involved so that students do not experience cognitive overload while engaging with such learning tools and have appropriate opportunities for metacognition, deeper sense-making, and knowledge organization. In the undergraduate course in which many students did not derive added benefit from the integration of conceptual and quantitative aspects, their pre-test performance suggests that the traditional lecture-based instruction may not have sufficiently provided a “first coat” to help students avoid cognitive overload when engaging with the hybrid QuILT. These findings suggest that different groups of students can benefit from a research-based learning tool that integrates conceptual and quantitative aspects if cognitive overload while learning is prevented either due to students’ high mathematical facility or due to their reasonable conceptual facility before engaging with the learning tool. Full article

This study investigates the surface characteristics and corrosion behavior of a high-C martensitic stainless steel (AISI 440C) at different stages of its manufacturing process. As a class, these steels prioritize high mechanical properties and wear resistance over superior corrosion resistance. Hot working operations, such as rolling, create a surface oxide scale that must be removed via pickling to restore the material’s inherent corrosion resistance. This process also eliminates the underlying Cr-depleted layer, allowing for the re-establishment of a protective passive film. Using potentiodynamic polarization curves and micrographic analysis, the material’s behavior in different conditions, as-rolled, with a post-heat treatment oxide scale, and in a bare, oxide-free state, has been assessed. The results showed that the material lacks stable passive behavior under all conditions. The as-rolled and heat-treated conditions both exhibited active behavior and formed thick, non-adherent corrosion products. The oxide layer formed after heat treatment performed the worst, showing a significant increase in corrosion current density. These findings confirm the material’s susceptibility to corrosion in Cl⁻ ion-rich environments, highlighting the need for limited storage in such conditions and rapid pickling after thermal processing to mitigate surface damage. Full article

The Shizhuyuan polymetallic deposit in Hunan Province, China, is a world-class ore field rich in tungsten (W), tin (Sn), molybdenum (Mo), and bismuth (Bi), now facing resource depletion due to prolonged exploitation. This study addresses the limitations of traditional geological prediction methods in complex terrain by integrating multi-source datasets—including γ-ray spectrometry, high-precision magnetometry, induced polarization (IP), and soil radon measurements—across 5049 samples. Unsupervised factor analysis was employed to extract five key ore-indicating factors, explaining 82.78% of data variance. Based on these geological features, predictive models including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were constructed and compared. SHAP values were employed to quantify the contribution of each geological feature to the prediction outcomes, thereby transforming the machine learning “black-box models” into an interpretable geological decision-making basis. The results demonstrate that machine learning, particularly when integrated with multi-source data, provides a powerful and interpretable approach for deep mineral prospectivity mapping in concealed terrains. Full article

Spiking neural networks (SNNs) have emerged as a promising model for energy-efficient, event-driven processing of asynchronous event streams from Dynamic Vision Sensors (DVSs), a class of neuromorphic image sensors with microsecond-level latency and high dynamic range. Nevertheless, challenges persist in optimising training and effectively handling spatio-temporal complexity, which limits their potential for real-time applications on embedded sensing systems such as object tracking and recognition. Targeting this neuromorphic sensing pipeline, this paper proposes the Dynamic Tracking with Event Attention Spiking Network (DTEASN), a novel framework designed to address these challenges by employing a pure SNN architecture, bypassing conventional convolutional neural network (CNN) operations, and reducing GPU resource dependency, while tailoring the processing to DVS signal characteristics (asynchrony, sparsity, and polarity). The model incorporates two innovative, self-developed components: an event-driven multi-scale attention mechanism and a spatio-temporal event convolver, both of which significantly enhance spatio-temporal feature extraction from raw DVS events. An Event-Weighted Spiking Loss (EW-SLoss) is introduced to optimise the learning process by prioritising informative events and improving robustness to sensor noise. Additionally, a lightweight event tracking mechanism and a custom synaptic connection rule are proposed to further improve model efficiency for low-power, edge deployment. The efficacy of DTEASN is demonstrated through empirical results on event-based (DVS) object recognition and tracking benchmarks, where it outperforms conventional methods in accuracy, latency, event throughput (events/s) and spike rate (spikes/s), memory footprint, spike-efficiency (energy proxy), and overall computational efficiency under typical DVS settings. By virtue of its event-aligned, sparse computation, the framework is amenable to highly parallel neuromorphic hardware, supporting on- or near-sensor inference for embedded applications. Full article

In this article, the mechanism of relaxation polarization currents occurring at a constant temperature (isothermal process) in crystals with ionic-molecular chemical bonds (CIMBs) in an alternating electric field was investigated. Methods of the quasi-classical kinetic theory of dielectric relaxation, based on solutions of the nonlinear system of Fokker–Planck and Poisson equations (for the blocking electrode model) and perturbation theory (by expanding into an infinite series in powers of a dimensionless small parameter) were used. Generalized nonlinear mathematical expressions for calculating the complex amplitudes of relaxation modes of the volume-charge distribution of the main charge carriers (ions, protons, water molecules, etc.) were obtained. On this basis, formulas for the current density of relaxation polarization (for transient processes in a dielectric) in the k-th approximation of perturbation theory were constructed. The isothermal polarization currents are investigated in detail in the first four approximations (k = 1, 2, 3, 4) of perturbation theory. These expressions will be applied in the future to compare the results of theory and experiment, in analytical studies of the kinetics of isothermal ion-relaxation (in crystals with hydrogen bonds (HBC), proton-relaxation) polarization and in calculating the parameters of relaxers (molecular characteristics of charge carriers and crystal lattice parameters) in a wide range of field parameters (0.1–1000 MV/m) and temperatures (1–1550 K). Asymptotic (far from transient processes) recurrent formulas are constructed for complex amplitudes of relaxation modes and for the polarization current density in an arbitrary approximation k of perturbation theory with a multiplicity r by the polarizing field (a multiple of the fundamental frequency of the field). The high degree of reliability of the theoretical results obtained is justified by the complete agreement of the equations of the mathematical model for transient and stationary processes in the system with a harmonic external disturbance. This work is of a theoretical nature and is focused on the construction and analysis of nonlinear properties of a physical and mathematical model of isothermal ion-relaxation polarization in CIMB crystals under various parameters of electrical and temperature effects. The theoretical foundations for research (construction of equations and working formulas, algorithms, and computer programs for numerical calculations) of nonlinear kinetic phenomena during thermally stimulated relaxation polarization have been laid. This allows, with a higher degree of resolution of measuring instruments, to reveal the physical mechanisms of dielectric relaxation and conductivity and to calculate the parameters of a wide class of relaxators in dielectrics in a wide experimental temperature range (25–550 K). Full article

Blazars are a class of active galactic nuclei characterized by having one of their relativistic jets oriented close to our line of sight. Their broad emission spectrum makes them exceptional laboratories for probing fundamental physics. In this review, we explore the potential impact on blazar observations of three scenarios beyond the standard paradigm: (i) the hadron beam model, (ii) the interaction of photons with axion-like particles (ALPs), and (iii) Lorentz invariance violation. We focus on the very-high-energy spectral features these scenarios induce in the blazars Markarian 501 and 1ES 0229+200, making them ideal targets for testing such effects. Additionally, we examine ALP-induced effects on the polarization of UV-X-ray and high-energy photons from the blazar OJ 287. The unique signatures produced by these models are accessible to current and upcoming instruments—such as the ASTRI Mini Array, CTAO, LHAASO, IXPE, COSI, and AMEGO—offering new opportunities to probe and constrain fundamental physics through blazar observations. Full article

Antarctic research stations require reliable low-carbon power under extreme conditions. This study compiles a synchronized PV-meteorological time-series data set on Horseshoe Island (Antarctica) at 30 s, 1 min, and 5 min resolutions and compares four PV module types (monocrystalline, polycrystalline, flexible mono, and semitransparent) under controlled field operation. Model development adopts an interpretable, multi-objective framework: a modified SPEA-2 searches rule sets on the Pareto front that jointly optimize precision and recall, yielding transparent, physically plausible decision rules for operational use. For context, benchmark machine-learning models (e.g., kNN, SVM) are evaluated on the same splits. Performance is reported with precision, recall, and complementary metrics (F1, balanced accuracy, and MCC), emphasizing class-wise behavior and robustness. Results show that the proposed rule-based approach attains competitive predictive performance while retaining interpretability and stability across panel types and sampling intervals. Contributions are threefold: (i) a high-resolution field data set coupling PV output with solar radiation, temperature, wind, and humidity in polar conditions; (ii) a Pareto-front, explainable rule-extraction methodology tailored to small-power PV; and (iii) a comparative assessment against standard ML baselines using multiple, class-aware metrics. The resulting XAI models achieved 92.3% precision and 89.7% recall. The findings inform the design and operation of PV systems for harsh, high-latitude environments. Full article

Rhodopsin, the prototypical Class A G protein-coupled receptor (GPCR) and visual pigment of rod photoreceptors, has long served as a structural and mechanistic model for GPCR biology. Mutations in rhodopsin are the leading cause of autosomal dominant retinitis pigmentosa (adRP), making this receptor a critical therapeutic target. In this review, we summarize the chemical, structural, and biophysical features of small-molecule modulators of this receptor, spanning both classical retinoid analogs and emerging non-retinoid scaffolds. These ligands reveal recurrent binding modes within the orthosteric chromophore pocket as well as peripheral allosteric and bitopic sites, where they mediate folding, rescue trafficking, photocycle modulation, and mutant stabilization. We organize ligand performance into a three-tier framework linking binding affinity, cellular rescue potency, and stability gains. Chemotypes in tier 2, which show sub-micromolar to low-micromolar activity with broad mutant coverage, emerge as promising candidates for optimization into next-generation scaffolds. Across scaffolds, a recurring minimal pharmacophore is evident by a contiguous hydrophobic π-surface anchored in the β-ionone region, coupled with a strategically oriented polar handle that modulates the Lys296/Glu113 microenvironment, offering tractable design vectors for non-retinoid chemotypes. Beyond the chromophore binding pocket, we highlight opportunities to exploit extracellular loop epitopes, cytoplasmic microswitch clefts, dimer/membrane interfaces, and ion co-binding sites to engineer safer, state-biased control with fewer photochemical liabilities. By integrating rhodopsin photobiophysics with environment-aware, multi-state medicinal chemistry, and by addressing current translational challenges in drug delivery, this review outlines a rational framework for advancing rhodopsin-targeted therapeutics toward clinically credible interventions for RP and related retinal degenerations. Full article

Accurate monitoring of the coverage and distribution of photosynthetic (PV) and non-photosynthetic vegetation (NPV) in the grasslands of semi-arid regions is crucial for understanding the environment and addressing climate change. However, the extraction of PV and NPV information from Unmanned Aerial Vehicle (UAV) remote sensing imagery is often hindered by challenges such as low extraction accuracy and blurred boundaries. To overcome these limitations, this study proposed an improved semantic segmentation model, designated SegFormer-CPED. The model was developed based on the SegFormer architecture, incorporating several synergistic optimizations. Specifically, a Convolutional Block Attention Module (CBAM) was integrated into the encoder to enhance early-stage feature perception, while a Polarized Self-Attention (PSA) module was embedded to strengthen contextual understanding and mitigate semantic loss. An Edge Contour Extraction Module (ECEM) was introduced to refine boundary details. Concurrently, the Dice Loss function was employed to replace the Cross-Entropy Loss, thereby more effectively addressing the class imbalance issue and significantly improving both the segmentation accuracy and boundary clarity of PV and NPV. To support model development, a high-quality PV and NPV segmentation dataset for Hengshan grassland was also constructed. Comprehensive experimental results demonstrated that the proposed SegFormer-CPED model achieved state-of-the-art performance, with a mIoU of 93.26% and an F1-score of 96.44%. It significantly outperformed classic architectures and surpassed all leading frameworks benchmarked here. Its high-fidelity maps can bridge field surveys and satellite remote sensing. Ablation studies verified the effectiveness of each improved module and its synergistic interplay. Moreover, this study successfully utilized SegFormer-CPED to perform fine-grained monitoring of the spatiotemporal dynamics of PV and NPV in the Hengshan grassland, confirming that the model-estimated f_PV and f_NPV were highly correlated with ground survey data. The proposed SegFormer-CPED model provides a robust and effective solution for the precise, semi-automated extraction of PV and NPV from high-resolution UAV imagery. Full article

Deep eutectic solvents (DESs) represent a versatile and sustainable class of solvents, characterized by their low volatility, favorable biodegradability, and the ability to tailor their viscosity, polarity, and hydrogen-bonding capacity through the choice of their individual components. These characteristics have established them as powerful media in various analytical extraction and separation processes. This review presents a critical evaluation of the expanding role of DESs within the field of capillary electromigration techniques, summarizing key advancements from 2019 to mid-2025. We synthesize the current literature to delineate the benefits, persistent challenges, and future prospects of integrating DESs into capillary electrophoresis (CE)-based analytical workflows. Specifically, it systematically documents the following: (i) the diverse types of DESs employed in electrophoretic separations, (ii) proposed mechanisms underlying their influence on chiral compound resolution, and (iii) their utilization as separation media and pseudostationary phases (PSP) in capillary electromigration systems. By critically assessing their advantages and drawbacks, this review aims to provide a comprehensive perspective on the application of DESs in modern capillary electromigration techniques. Full article

Maritime transportation, fishing, scientific research, and other activities rely on various types of ships and platforms, making precise monitoring of ships at sea essential. Synthetic Aperture Radar (SAR) is minimally affected by weather conditions and darkness and is used for ship detection in maritime environments. This study analyzes the differences in backscatter characteristics among various ship types in SAR images and proposes SISS-YOLO, an enhanced model based on YOLOv8. The proposed method addresses the challenge of ship instance segmentation in SAR images involving multiple polarizations, scenarios, and classes. First, the backbone structure was optimized by incorporating additional pooling layers and refining the activation functions. Second, the Coordinate Attention (CA) module was integrated into the C2F template, embedding spatial position information into the channel attention mechanism. Third, a slide loss function was adopted to address the class imbalance across ship categories. The experiments were conducted on the OpenSARShip2.0 dataset, which includes cargo, tanker, passenger and engineering ships. The results show that the SISS-YOLO achieves a mask precision of 88.3%, a mask recall of 86.4% and a mask mAP50 of 93.4% for engineering ships. Compared with YOLOv8m, SISS-YOLO achieved improvements of 15.7% in mask precision and 8.8% in mask recall. The model trained on the OpenSARShip2.0 dataset was directly applied to the FUSAR-Ship1.0 dataset, demonstrating a degree of robustness. When applied to SAR data, the SISS-YOLO model achieves high detection accuracy, demonstrating generalization. Full article