The development of a new conjugate gradient method, derived from the modified difference gradient vector and based on an approximation of the Hessian matrix, marks a significant advancement in optimization algorithms. This study shows that the robustness of the proposed method, particularly in applications such as compressive sensing and image processing. Its global convergence properties and sufficient descent conditions ensure reliable performance even in computationally challenging scenarios. Extensive numerical experiments in signal recovery, image restoration, and unconstrained optimization clearly illustrate the superiority of the proposed method over existing approaches, including traditional conjugate gradient techniques. The proposed CG method not only boosts computational efficiency but also significantly enhances the quality of solutions for both signal recovery and image restoration. These promising results emphasize the method's potential as a versatile and powerful tool for solving a wide range of practical problems within computational mathematics, optimization, and signal processing.

Characterization and correlation of roasted and ground coffee monosaccharides for fraud detection.

Rapid detection of ibuprofen in water using wavelet-based hyperspectral imaging.

Aim of the study A green and sustainable analytical method was developed for the extraction and determination of Acid Brown 703 dye in aqueous samples using a natural deep eutectic solvent (DES)-based liquid–liquid microextraction coupled with UV–Vis spectrophotometry. The DES, composed of choline chloride and phenol, was employed as an environmentally benign extraction medium, replacing conventional toxic organic solvents. Material and methods Critical experimental parameters, including pH, DES volume, sample-to-extractant ratio, and centrifugation time were systematically optimized to maximize extraction efficiency. Results and conclusions Under optimal conditions (pH 6, 1 mL DES, 2 min centrifugation), the method exhibited good linearity in the range of 10–60 ppm, with a limit of detection (LOD) of 2.47 μg/L and a limit of quantification (LOQ) of 7.50 μg/L. The relative standard deviation (RSD) ranged from 2.35% to 3.21%, confirming method precision. Application to real water samples demonstrated satisfactory recovery and reproducibility, highlighting the method's potential for routine monitoring of synthetic dyes in environmental matrices.

ABSTRACT Hepatitis B (HB) and hepatitis B related liver cirrhosis (LC) severely threaten global public health. Early and accurate differentiation of HB, LC, and healthy controls (HE) is crucial for optimizing treatment and improving prognosis. This study demonstrated that serum Raman spectroscopy combined with support vector machine (SVM) enables rapid diagnosis of HB and HB‐induced LC. We established a Raman spectral database of 78 HB cases, 73 LC cases, and 81 HE cases, adopting a nested fivefold cross‐validation (fivefold CV) scheme: Hyperparameters were tuned via grid search (internal fivefold CV) on the training set, with final performance estimated on an independent external test set. The entire process was repeated 10 times with different random seeds, and results were macro‐averaged. The three‐group classification achieved an overall accuracy of 78% and a macro‐average area under the curve (AUC) of 91%, outperforming random forest (RF), principal component analysis–linear discriminant analysis (PCA‐LDA), and k‐nearest neighbors (KNN). This study confirms the method's great potential for noninvasive screening of HB and LC.

Expanding the Ts-VI feature space for retrieving new parameters characterising the water and carbon cycle: proof-of-concept of a new methodological framework and its validation at selected FLUXNET sites.

Ensuring food safety requires both reliable detection of chemical contaminants and evaluation of their potential health risks. Clothianidin (CLO), a widely used neonicotinoid insecticide, is of particular concern due to its environmental persistence, bioaccumulation potential, and associated toxicological risks. Here, an ultrarapid and scalable strategy for constructing highly exposed, atomically dispersed platinum single-atoms interface on porous graphene-like carbon frameworks (Pt SA/CFs) in just 2 min is proposed. The process involves the decomposition of glucose and H2PtCl6, generating a porous carbon structure with uniformly dispersed Pt atoms in a single step. The resulting Pt SA/CFs exhibit exceptional catalytic activity, enabling highly sensitive and rapid electrochemical detection of CLO with a detection limit of 1.61 μM. Additionally, recovery rates from spiked real samples ranged from 92.87% to 105.65%, further highlighting the method's potential for CLO detection in practical applications. These results not only overcome the limitations of conventional analytical methods but also provide a cost-effective solution for on-site pesticide residue analysis. Furthermore, by integrating network toxicology, the molecular mechanisms underlying CLO-induced respiratory toxicity are found, offering valuable insights into its potential health risks. This work presents a time-efficient synthesis of single-atom Pt for rapid neonicotinoid detection and integrates network toxicology to establish a framework for risk assessment in food safety regulation.

Hyper speed comprehensive two-dimensional gas chromatography with reversed column set for enhanced separation of sterane biomarkers in petrochemical samples.

Heart rate variability (HRV) is a vital metric for assessing cardiovascular health, psychological stress, and sleep quality. Non-contact HRV monitoring offers advantages in safety, comfort, and hygiene, making it an increasingly attractive solution. In this study, we propose a high-precision, non-contact HRV analysis method using a 77 GHz multiple-input multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar system. The proposed method first employs an optimized Capon beamforming algorithm to accurately localize the heart and enhance intermediate frequency (IF) signals from the heart's direction. A modified differentiate and cross-multiply (MDACM) algorithm is then used to demodulate the phase sequence, yielding a raw vital sign signal that includes both respiratory and cardiac components. This signal is further processed using a six-level wavelet packet transform (WPT), from which specific wavelet coefficients (6th to 12th bands at level six) are selected to reconstruct the seismocardiogram (SCG) signal. To extract precise inter-beat interval (IBI) sequences, a robust aortic valve opening (AO) point detection algorithm is developed. Time-domain HRV indices-including the standard deviation of normal-to-normal intervals (SDNN), the root mean square of successive differences (RMSSD), and the percentage of successive normal-to-normal intervals differing by more than 50 milliseconds (ms) (pNN50)-are then computed from the IBI sequence. To validate the approach, we developed a synchronized data acquisition system combining radar and electrocardiogram (ECG) sensors and collected data from 13 participants-each person collected data for 10 min. Experimental results demonstrate the effectiveness of our method, achieving average errors of 4.11 ms in SDNN, 8.05 ms in RMSSD, and 2.15% in pNN50 compared to ECG-derived ground truth. These results outperform existing non-contact HRV monitoring techniques and highlight the method's potential for practical, continuous, and unobtrusive cardiovascular monitoring.

We present a relativistic third-order algebraic diagrammatic construction [ADC(3)] approach for calculating double ionization potentials (DIPs). Inclusion of third-order terms significantly improves the performance of the algebraic diagrammatic construction method for DIPs. By employing the exact two-component atomic mean-field (X2CAMF) Hamiltonian in combination with a Cholesky decomposition representation of two-electron integrals and the frozen natural spinor framework for virtual space truncation, we achieve a significant reduction in both memory requirements and computational cost. The DIPs obtained using the X2CAMF Hamiltonian show excellent agreement with results from fully relativistic four-component calculations. We have validated the accuracy of our implementation through comparisons with available experimental and theoretical data for inert gas atoms and diatomic species. The effect of higher-order relativistic corrections is also explored. The efficiency of our implementation is demonstrated by computing the lowest DIP of the tungsten hexacarbonyl, W(CO)6, complex using a large basis set.

ABSTRACT Saprolegniosis, typically induced by oomycete Saprolegnia parasitica , is one of the most difficult pathogens in fish and other aquatic animals in freshwater systems. It is especially harmful for the endangered species landlocked salmon ( Salmo salar m. sebago ). Currently, there are only few alternatives to prevent and treat saprolegniosis occurrences, which can lead to major fish deaths and financial losses at fish farms. In this study, surface‐modified cellulose materials were used at an experimental flow‐through fish farm rearing landlocked salmon, which often suffers from saprolegniosis occurrences. The results showed that the material's cationic surfaces were able to capture the spores of S. parasitica (experimental part I and part II). The cellulose material was chemically modified with a high density of cationic quaternary ammonium groups, which performed better than a material with a weak cationic charge by amino groups obtained via physisorption of chitosan on the surface, resulting in fewer S. parasitica spores in the rearing tank water (experimental part I). The results are promising and offer a novel method for controlling saprolegniosis occurrences without harmful chemicals. However, certain environmental conditions (in experimental part II) inhibited the detection method (real‐time quantitative polymerase chain reaction) used for the detection of S. parasitica . This highlights the need for further method development for the detection of S. parasitica . Overall, the results are promising in terms of reducing S. parasitica spores in rearing water and further controlling saprolegniosis occurrences. More process optimization is required to achieve the method's full potential in industrial scale processes.

A sustainable room temperature synthesis of ultra-high surface area mesoporous silica material (1653 m2 g−1), designated as QSM-2, has been developed using tetraethyl orthosilicate, cetyltrimethylammonium bromide (CTAB), and β-cyclodextrin (β-CD) as the silicon source, structure directing agent, and additive, respectively. The process was optimised by varying key reaction parameters, including the amount of additive, reaction temperature and sonication, while maintaining a constant silica-to-surfactant ratio. Scale-up studies confirmed reproducibility at a 20-gram scale, highlighting the method's potential for large scale applications. The material with an ultra-high surface area was evaluated for the N-formylation of amines using formic acid as a benign C1 source, thereby enabling the indirect utilisation of CO2. This work presents a sustainable and selective protocol for converting a wide range of amines to the corresponding formamides under mild, solvent-free conditions, achieving excellent yields (up to 99%), and high selectivity (100%).

Despite the high demands for azetidines as privileged motifs in medicinal chemistry, efficient synthesis platforms that enable the rapid preparation of diversely decorated azetidines remain limited. Although the bis-functionalization of highly strained 1-azabicyclobutane (ABB) has been one of the most viable, modular, and versatile methods for the synthesis of structurally diverse azetidines, the catalytic installation of aliphatic pendants to ABB remains underexplored. In this work, we report the multicomponent synthesis of the elusive all-carbon quaternary azetidines from ABBs through the radical addition of azetidines to various α,β-unsaturated esters, amides, ketones, a 1,3-enyne, and a vinylphosphonate ester. The reaction is facilitated by a bromide/nickel dual-catalyzed polar-radical relay strategy, enabling the radical difunctionalization of α,β-unsaturated carbonyl compounds via sequential ring-strain-release azetidinylation and Suzuki-type arylation or alkenylation. Variation in the individual components enabled the synthesis of >60 azetidine derivatives, including modifications of selected biorelevant molecules. The functional group interconversion of representative azetidine derivatives illustrates the method's potential to produce unprecedented spirocyclic azetidine hybrids, which may be useful for exploring uncharted areas of chemical space in drug design. Additionally, a diastereoselective synthesis using Evans' oxazolidinone enabled the preparation of an enantiopure azetidine, potentially useful as a platform for library preparation of stereochemically diverse azetidines.

Abstract Despite the high demands for azetidines as privileged motifs in medicinal chemistry, efficient synthesis platforms that enable the rapid preparation of diversely decorated azetidines remain limited. Although the bis ‐functionalization of highly strained 1‐azabicyclobutane (ABB) has been one of the most viable, modular, and versatile methods for the synthesis of structurally diverse azetidines, the catalytic installation of aliphatic pendants to ABB remains underexplored. In this work, we report the multicomponent synthesis of the elusive all‐carbon quaternary azetidines from ABBs through the radical addition of azetidines to various α,β ‐unsaturated esters, amides, ketones, a 1,3‐enyne, and a vinylphosphonate ester. The reaction is facilitated by a bromide/nickel dual‐catalyzed polar‐radical relay strategy, enabling the radical difunctionalization of α,β ‐unsaturated carbonyl compounds via sequential ring‐strain‐release azetidinylation and Suzuki‐type arylation or alkenylation. Variation in the individual components enabled the synthesis of >60 azetidine derivatives, including modifications of selected biorelevant molecules. The functional group interconversion of representative azetidine derivatives illustrates the method's potential to produce unprecedented spirocyclic azetidine hybrids, which may be useful for exploring uncharted areas of chemical space in drug design. Additionally, a diastereoselective synthesis using Evans’ oxazolidinone enabled the preparation of an enantiopure azetidine, potentially useful as a platform for library preparation of stereochemically diverse azetidines.

Atherosclerosis is a progressive disease characterized by lipid accumulation and fibrous elements in large and medium-sized arteries, and remains a leading cause of death worldwide. A deeper understanding of its molecular nature is critical for developing novel strategies for the prevention, diagnosis, and treatment. This study evaluates attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with multivariate analysis techniques to differentiate and classify atherosclerosis by identifying disease-specific spectral variations. Spectral analyses indicated statistically significant differences in lipid (p < 0.0001), protein (p < 0.01), nucleic acid (p < 0.0001), and glucose (p < 0.0001) content of serum samples in the atherosclerosis group compared to controls. Patients with atherosclerosis exhibit altered lipid metabolism, marked by a decrease in saturated lipids and an increase in unsaturated lipids compared to healthy individuals. Additionally, elevated levels of protein, RNA, glucose, and conformational changes in DNA were key spectral features, distinguishing atherosclerosis from controls. Principal component analysis (PCA) successfully differentiated patients from controls, while classification models based on linear discriminant analysis (LDA) and support vector machine (SVM) achieved accuracies of 96.61% and 93.22%, respectively. The ability of FTIR spectroscopy to detect subtle biochemical alterations suggests its potential for early diagnosis. These molecular markers may appear prior to clinical symptoms, highlighting the method's potential for future screening, pending validation in at-risk or preclinical cohorts.

We report a metal-free strategy for the efficient synthesis of polysubstituted quinolines via Brønsted acid-promoted cyclization of readily accessible ene-ynamides. Promoted by stoichiometric TfOH under mild conditions (30 °C), this method transforms simple, modular substrates into a wide range of quinoline derivatives in a single step, eliminating the need for precious-metal catalysts or prefunctionalized reagents. Its broad functional group tolerance and successful gram-scale operation underscore the method's practical utility and potential for broader application.

Accurate acoustic simulations of enclosed spaces require precise boundary conditions, typically expressed through surface impedances for wave-based methods. Conventional measurement techniques rely on simplifying assumptions about the sound field and mounting conditions, limiting their validity for real-world scenarios. To overcome these limitations, this study introduces a Bayesian framework for the in situ estimation of frequency-dependent surface impedances from sparse interior sound pressure measurements. The approach employs simulation-based inference, which leverages the expressiveness of neural network architectures to directly map simulated data to posterior distributions of model parameters, bypassing conventional sampling-based Bayesian approaches and offering advantages for high-dimensional inference problems. Impedance behavior is modeled using a damped oscillator model extended with a fractional calculus term. The framework is verified on a finite element model of a cuboid room with a volume of 1.95 m3 and further tested with impedance tube measurements used as reference, achieving robust and accurate estimation of all six individual impedances from 63 to 500 Hz. Application to a numerical car cabin model further demonstrates reliable uncertainty quantification and high predictive accuracy for complex-shaped geometries. Posterior predictive checks and coverage diagnostics confirm well-calibrated inference, highlighting the method's potential for generalizable and physically consistent characterization of acoustic boundary conditions in real-world interior environments.

Ultrasound-based personalized hemodynamic modeling of large regions of the peripheral artery using a novel optical tracking approach.

Neural networks for faster laser ultrasound tomography in tissue phantoms.

Simultaneous quantification of fourteen urinary tobacco biomarkers via UHPLC-Q-Orbitrap HRMS and isotope dilution.