Search Results (1,175)

Despite the success of antiretroviral therapy, people living with HIV remain at heightened risk of multimorbidity spanning cardiovascular, renal, hepatic, oncologic and neuropsychiatric domains. We investigate whether routinely collected electronic health record data (30 laboratory variables plus seven demographic/social descriptors) can support early, multi-label classification of recorded comorbidities in a real-world cohort of 2200 HIV-positive patients receiving continuous care at a major London hospital. We benchmark classical machine and deep learning models under two settings: a demographic-aware configuration that includes sensitive attributes (age, gender, race and continent of birth) and a demographic-unaware configuration that excludes them. XGBoost yields the best macro-$F_1$ performance, and demographic-aware variants consistently outperform their unaware counterparts. Permutation feature importance revealed physiologically coherent drivers (e.g., creatinine/eGFR for renal and cardiometabolic labels, hemoglobin for hematologic labels, albumin for respiratory labels) and suggested that the relative contribution of demographic variables varied across comorbidity categories. These findings indicate that (i) routinely collected EHR data contain informative patterns associated with the multi-label comorbidity profiles of people living with HIV and (ii) carefully governed use of demographic context can improve accuracy while motivating transparent consideration of fairness and bias. Full article

Wireless communication above $300\mathrm{GHz}$ requires highly sophisticated analog circuit design due to severe frequency dependent ohmic losses. The complexity of such electronic hardware motivates exploring wireless quantum optical communication approaches even for the 6G “terahertz (THz) range” $\left[300\mathrm{GHz},10\mathrm{THz}\right]$. In this work, the classical radio frequency (RF)-based inner physical layer (PHY) transceiver blocks of channel coded wireless communication systems are replaced by wireless quantum optical transceiver blocks. Short range concepts employing LEDs as transmitters are particularly attractive, owing to their low implementation cost and practical simplicity. In contrast to laser based wireless quantum optical transmission over multipath channels, the quantum mechanical density operator ${\underline{\rho }}_{\mathrm{RX},[{\mathfrak{s}}_i,b_i]}$ and the transition probability $\gamma ({\mathfrak{s}}_i,{\mathfrak{s}}_{i+1})$ required by the quantum data detection must be revised accordingly. Furthermore, the novel interpretation introduced here, in which the extrinsic information is treated as a diversity branch rather than as an estimate of the a priori information, facilitates turbo equalization that still can accomodate varying a priori information. However, due to the limited uncoded transmission performance achievable with such systems, the incorporation of sophisticated channel coding schemes appears imperative. The authors therefore investigate the combination of sophisticated channel coding techniques, such as polar coding, with LED based wireless quantum optical transmission technologies. All numerical results assume a cryogenically cooled receiver front-end (approximately 10 K), yielding thermal noise levels. Operation at room temperature in the 6G THz range $\left[300\mathrm{GHz},10\mathrm{THz}\right]$ would require an average number ${\overline{N}}_{\alpha }$ of thermal noise photon values of approximately 5 to 20, which is beyond the scope of this feasibility study. The results show that the proposed paradigm enables simple, robust, and practically viable wireless quantum optical communication systems with favorable transmission performance. Additional gains are achieved through iterative turbo equalization. The results also suggest that the proposed approach can pave the way toward robust and economically viable future communication solutions. Full article

Doxorubicin (DOX) is a potent chemotherapeutic drug, whose clinical application is largely restricted by dose-dependent cardiotoxicity (DIC). Dracocephalum moldavica L. is a classic medicinal and edible plant with obvious cardiovascular protective effects; however, the role of its total flavonoids (TFDM) in DIC remains unclear. This study explored the cardioprotective effect of TFDM on DOX-induced myocardial injury and its mechanism related to mitochondrial quality control. We established in vivo and in vitro DIC models and adopted echocardiography, detection of cardiac injury and oxidative stress indicators, transmission electron microscopy, mitochondrial functional assessment and Western blotting, with AMPK knockdown performed for mechanism verification. Results showed that TFDM effectively improved cardiac function, reduced myocardial oxidative stress and apoptosis, and maintained mitochondrial ultrastructure and energy metabolism. TFDM activated the AMPK/PGC1α signaling axis to facilitate mitochondrial biogenesis, and AMPK silencing eliminated the protective effect of TFDM. In conclusion, AMPK/PGC-1α pathway is a primary key pathway involved in TFDM’s protective effects, which provides an experimental basis for the development of Dracocephalum moldavica L. as a functional food and adjuvant agent against DIC. Full article

Emerging sustainability demands and calls for lowering materials’ environmental impact have directed authors to examine a class of polymers characterised as covalent adaptable networks and referred to as vitrimers. In this study, composite plates were made using vitrimer resin as the matrix material and continuous unidirectional flax fibre fabrics as the reinforcement. A specific early-stage composite part production method is proposed to make the multi-ply flax/vitrimer composite plate. The development of natural fibre–reinforced vitrimer composites is of clear research interest as a promising approach towards sustainable and recyclable novel material systems. Specimens prepared with all the plies oriented 0° exhibited a 129.4 MPa tensile strength and a 12.4 GPa tensile modulus, indicating a 334% increase in tensile strength when compared to the average value of 29.8 MPa obtained for neat vitrimer specimens and a 1140% improvement in the tensile modulus compared to the 1.0 GPa reached for neat vitrimer. The specimens whose plies were oriented 90° are found to deliver a tensile strength of 12.2 MPa and a 1.3 GPa tensile modulus. Applying the classical composite material micromechanics equation to calculate the 0°-direction tensile modulus demonstrated a good agreement with the experimentally obtained value—a 9.6% difference was discovered. Proper fibre/matrix interfacial adhesion was detected when the flax/vitrimer specimens’ surfaces after fracture were examined under scanning electron microscope. The research findings on tensile mechanical properties reveal that the observed flax/vitrimer composites may be potential candidates for replacing typical synthetic fibre–reinforced materials rated for automotive applications and intended for in-plane loaded parts, particularly some inner-body vehicle elements. Full article

Co-contamination of biphenyl and heavy metals is widespread in industrial environments, but systematic studies on the simultaneous treatment of both pollutants using a single microbial strategy remain limited. In this study, we characterized the biphenyl degradation performance, metabolic pathway, transcriptomic response, and Cr(VI) tolerance of Rhodococcus sp. TG-1, and developed an alkali-modified biochar immobilization system to enhance its degradation efficiency for biphenyl under Cr(VI) stress. Degradation experiments were carried out under optimal conditions (30 °C, pH 7.0), and it was found that strain TG-1 degraded 76.84% of 300 mg/L biphenyl within 3 days. Intermediate metabolites were identified by LC-MS, and five key intermediates were detected, confirming that TG-1 metabolizes biphenyl via the classical 2,3-dihydroxybiphenyl dioxygenase pathway, with subsequent entry into the tricarboxylic acid cycle. Transcriptomic analysis was performed to profile gene expression, revealing 845 differentially expressed genes under biphenyl stress, including 672 upregulated genes significantly enriched in aromatic degradation pathways. Seven complete bph gene clusters responsible for biphenyl catabolism were also identified. Strain TG-1 exhibited high tolerance to Cr(VI), with a minimum inhibitory concentration (MIC) of 500 mg/L. However, its biphenyl degradation efficiency dropped to 51.32% in the presence of 200 mg/L Cr(VI). After immobilization using alkali-modified straw biochar (JBC), heavy metal toxicity was alleviated, and the biphenyl removal rate increased to 99.30% under co-contamination conditions. Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) analyses confirmed that TG-1 was stably loaded onto the biochar surface through hydrogen bonding and electrostatic interactions. Altogether, this study provides a promising bacterial strain and a green immobilization strategy for enhancing biphenyl removal in the presence of Cr(VI), offering a practical approach for the treatment of environments co-contaminated with aromatic compounds and heavy metals. Full article

Carbon nanotube (CNT)-reinforced composites are promising advanced materials due to their exceptional mechanical properties. This paper presents a comprehensive investigation of the mechanical behavior of CNT/epoxy composites through theoretical modeling and experimental validation. An equivalent cylindrical fiber model was developed to transform CNTs into effective reinforcement phases, enabling the application of classical composite mechanics. Three reinforcement configurations were analyzed: two unidirectional short fiber models (aligned and staggered) and a three-dimensional four-directional braided long-fiber model. The effects of geometric parameters, including the diameter-to-thickness ratio (D/t) and fiber aspect ratio, on the effective elastic moduli were systematically evaluated. Static and dynamic compression experiments were conducted using an MTS 810 testing system and a Split Hopkinson Pressure Bar (SHPB) to examine the influence of loading rate, vacuum treatment, and reinforcement type (CNT, SiC, and hybrid SiC/CNT) on composite strength. The results indicated that 3 wt% CNT reinforcement increases the Young’s modulus by 30% under static loading and enhanced the dynamic compressive strength under impact loading. The vacuum degassing process significantly affected composite quality, with insufficient vacuum leading to strength degradation due to void formation. Theoretical predictions using Mori–Tanaka and dilute methods showed good agreement with experimental results at low reinforcement volume fractions. Scanning electron microscopy revealed uniform CNT dispersion and provided insights into failure mechanisms, including CNT pull-out and breakage. This work contributes to the understanding of structure–property relationships in CNT-reinforced polymer composites and provides guidelines for achieving their optimal design. Full article

Black tea quality is governed by aroma chemistry: terpene alcohols (linalool, geraniol, nerolidol), methyl salicylate, and short-chain aldehydes whose abundance and release kinetics from the polyphenol-rich leaf matrix shape perceived grade. Grade information lies not only in the average headspace concentration but in the temporal shape of volatile organic compound (VOC) release under controlled heating. Conventional electronic noses obscure this signal: they rely on multi-sensor arrays, compress each response into summary statistics, and report accuracy only at the level of individual measurements. Whether a single low-cost metal–oxide–semiconductor (MOS) gas sensor can recover grade-defining aroma chemistry, and whether waveform-level modeling can exploit it, was therefore investigated. A portable electronic nose built around a Bosch BME688 sensor recorded 90 time series, each comprising four directly measured channels (temperature, humidity, pressure, gas sensor resistance) and a derived indoor-air-quality (IAQ) proxy computed from them by the on-chip BSEC library, from 16 commercial Turkish black teas across three quality grades. Two representations were compared on the same data: a feature-based pipeline reducing 25 statistical descriptors to seven principal components for six classifiers (best F1-macro = 0.624, MLP), and a raw-waveform Multi-Scale 1D-CNN with Squeeze–Excitation and temporal self-attention (MS-CNN-Attention). Under product-grouped cross-validation, the deep model reached F1-macro = 0.811 (+30%) and graded 14 of 16 products correctly by majority vote, against 11 of 16 for the MLP, with the largest gain in the medium grade (F1: 0.52 → 0.79), where summary-statistic compression destroys the release-kinetic signal. The contributions are threefold: one programmable MOS sensor operated as a thermal-desorption profiler rather than a sensor array; a direct comparison of feature-based classical learning against raw-waveform deep learning on the same small, non-normally distributed dataset; and a product-level decision-consistency metric suited to batch screening. Pairing a low-cost MOS sensor with waveform-level modeling offers a rapid, non-destructive route to aroma-chemistry-based tea quality screening. Full article

The nucleation and growth mechanisms of copper electrodeposition from Cu(I)-containing-reline, a deep eutectic solvent, were investigated through a combination of electrochemical techniques and surface characterization. Cyclic voltammetry revealed the characteristic nucleation loop associated with an overpotential-driven electrocrystallization process, from which the equilibrium potential of the Cu(I)/Cu(0) redox couple was determined to be −0.35 V vs. a Ag quasi-reference electrode. Experimental potentiostatic current density transients were analyzed using nucleation models capable of accounting for both adsorption and three-dimensional (3D) diffusion-controlled growth, thereby allowing deconvolution of the individual contributions to the overall current response. The kinetic parameters, including the nucleation frequency and the number density of active sites, exhibited an exponential dependence on the applied overpotential, thus indicating enhanced nucleation kinetics at greater driving forces, while determining a Cu(I) diffusion coefficient of (3.39 + 0.09) × 10⁻⁷ cm² s⁻¹. Thermodynamic analysis showed that the Gibbs free energy of the formation of the critical nucleus decreases with increasing overpotential and follows the expected dependence on the inverse square of the overpotential, in agreement with classical nucleation theory. The estimated critical nucleus size was found to be smaller than one atom, suggesting that nucleation occurs at highly active surface sites. Furthermore, an exchange current density of (3 ± 1) μA cm⁻² was estimated for the Cu(I) electrochemical reduction. Scanning electron microscopy revealed a high density of copper nanoparticles (~20 nm) distributed across the electrode surface, along with larger aggregates (~100 nm) formed by coalescence and growth, consistent with a progressive nucleation mechanism. X-ray photoelectron spectroscopy confirmed that the deposits consist exclusively of metallic copper, with no evidence of oxidized species. These results demonstrate that copper electrodeposition in reline is governed by a complex interplay between the thermodynamic driving force, the interfacial kinetics, and mass transport, comprehensively providing fundamental insight into the electrocrystallization processes in deep eutectic solvents. Full article

Poor consolidations and the strength–conductivity trade-off limit the performance of copper alloys fabricated by laser powder bed fusion (LPBF). To address this, this study developed a strategy combining the response surface methodology (RSM) with direct ageing treatment (DAT) to achieve a favorable strength–conductivity synergy. The results showed that under the optimal process parameters, a high relative density of 99.25% (8.95 g/cm³ for theoretical density) was obtained. After direct ageing treatment at 490 °C for 60 min, the CuCrZr exhibited an ultimate tensile strength of 399.31 MPa and a thermal conductivity of 326.53 W/(m·K). To reveal the underlying mechanisms, this study employed a combination of systematic characterization via high-resolution transmission electron microscopy (HRTEM) and quantitative modeling. HRTEM characterized the uniformly dispersed nanoscale body-centered cubic (BCC) Cr precipitates that form semi-coherent interfaces with the face-centered cubic (FCC) Cu matrix, showing a crystallographic misorientation of approximately 10.5° intermediate between the classic Nishiyama–Wassermann and Kurdjumov–Sachs orientation relationships. Quantitative modeling indicates that the high strength arises from a synergistic effect: coherent strain fields exerted by the precipitates effectively pin retained dislocations, coupling Orowan and dislocation strengthening. Meanwhile, solute precipitation reduces lattice distortion, restoring notable thermal conductivity. Full article

This paper proposes a mathematical co-design framework for synchronous Boost DC-DC converters and their PI voltage controllers. In contrast to the conventional sequential design approach, where the power stage is sized first and the controller is tuned afterward, the proposed method treats the converter and the controller as a single coupled design problem. A nonlinear averaged model of the synchronous boost converter operating in continuous conduction mode is considered, explicitly incorporating the inductor series resistance, the capacitor equivalent series resistance, and the on-state resistances of the active switches. In addition, a simplified but physically interpretable loss model is included in order to capture inductor copper loss, capacitor ESR loss, semiconductor conduction loss, and switching loss. Based on this formulation, the joint design of the power stage and the PI controller is cast as a constrained multi-objective optimization problem whose decision variables include the inductance, capacitance, switching frequency, and controller gains. The optimization criteria account for output-voltage ripple, settling time, total losses, and current stress, while practical constraints related to duty cycle, current limits, ripple bounds, and closed-loop feasibility are enforced. The proposed framework makes it possible to compute Pareto-efficient designs and to reveal trade-offs that remain hidden under classical decoupled design procedures. Numerical case studies are structured to compare the proposed co-design strategy with a conventional sequential-design baseline. An optional technology-aware extension is also considered, allowing the influence of different semiconductor classes, such as Si, SiC, and GaN, to be assessed through technology-dependent loss and switching-frequency assumptions. The results indicate that the proposed framework provides a mathematically grounded and practically useful basis for integrated converter–controller synthesis in nonideal power electronic systems. Full article

Non-invasive blood glucose estimation from exhaled breath has been proposed as a painless alternative to repeated capillary measurements; however, performance evaluation remains challenging in small-sample settings. This study investigates the estimation of blood glucose from human breath using volatile organic compound (VOC) signals acquired with an electronic nose. Responses from three metal-oxide sensor channels sensitive to CO, alcohol, and acetone were collected from 58 individuals, with one measurement per subject, and analyzed using strictly patient-level five-fold cross-validation, in which test folds comprised only real subjects. Two experimental factors were examined. First, model performance was evaluated with and without an additional interpretable alcohol–acetone log-ratio capturing relative variation between compounds. Second, model training was performed using either real data only or fold-wise tabular synthetic augmentation generated via a Gaussian copula fitted exclusively on training subjects, while evaluation remained strictly real-only. Under real-only training, classical machine learning models achieved the lowest prediction errors (approximately 6–7 mg/dL), whereas under synthetic augmentation FTTransformer was the best-performing deep learning model. This findings should be understood as a constrained proof-of-concept analysis rather than as evidence of diagnostic capability or clinical readiness. Full article

Automated analysis of peripheral nerve ultrastructure is bottlenecked by heterogeneous electron microscopy (EM) datasets, where varying staining protocols and resolutions create domain shifts that confound deep learning. To address this, we developed a generalized segmentation pipeline. Using a custom pre-processing workflow (CLAHE and noise suppression) integrated into ZEISS Arivis Pro, we standardized inputs across three disparate domains: traditional osmium-based Palade, lanthanide-based “green” Uranyl-free method, and low-resolution Ellisman preparations. A U-Net trained on a highly constrained 15-image composite dataset achieved peak internal Intersection over Union (IoU) scores >0.95 for myelin and Schwann cells. Crucially, during open-world, zero-shot inference on an expanded independent testing cohort (N = 40), the model sustained robust Dice Similarity Coefficients of 0.854 for myelin and 0.597 for mitochondria. This demonstrates that integrating classical image standardization with deep learning effectively mitigates EM domain gaps, enabling comprehensive 3D multi-organelle reconstructions from challenging data. To ensure transparency and community utility, the pre-trained models and standardization scripts are provided in a public, open-access repository. Ultimately, this pipeline supports the transition to sustainable, non-toxic EM protocols and provides a robust pathway for unlocking historical clinical archives for automated organellomics. Full article

This study aims to investigate the performance and mechanism of N′-[(E)-phenylmethylidene] furan-2-carbohydrazide (FNH), a hydrazone Schiff base, as a corrosion inhibitor for carbon steel in 1.0 M HCl. The research was conducted by coupling electrochemical testing (Tafel analysis and Impedance spectroscopy) with surface characterization (SEM and AFM) and advanced computational tools, including quantum-chemical modeling and classical molecular dynamics (MD) simulations. Tafel analysis revealed that FNH acts as a mixed-type inhibitor, concurrently slowing iron oxidation and hydrogen reduction. Impedance data showed that the Faradaic resistance grew monotonically with FNH dosage, reaching 95% protection at 1 × 10⁻⁴ M. Fitting the results to the Langmuir model indicated a joint physical–chemical anchoring pathway, further confirmed by SEM/AFM inspection which disclosed a uniform organic deposit. Quantum-chemical modeling revealed that protonated species broaden the molecule’s capacity for bidirectional electron exchange, while MD simulations on the Fe (110) slab confirmed a flat-lying geometry that maximizes heteroatom–metal contact. The consistency between laboratory observables and atomic-scale predictions provides a detailed, mechanism-oriented picture of how this organic protective layer curtails acid corrosion. Full article

Carnitine plays an essential role in fatty acid metabolism, and its biosynthesis is tightly regulated by γ-butyrobetaine hydroxylase (BBOX), an Fe(II)/α-ketoglutarate-dependent dioxygenase. BBOX is the target of mildronate (THP), a clinically used drug for treating ischemic heart diseases. However, the detailed mechanisms of BBOX-catalyzed hydroxylation and the atypical oxidative rearrangement underlying THP inhibition remain elusive. In this study, we employed combined quantum mechanics/molecular mechanics (QM/MM) methods to systematically elucidate these mechanisms at the atomic level. Our calculations reveal that the hydroxylation of γBB proceeds via a classical three-step mechanism in the quintet state, with hydrogen atom abstraction as the rate-determining step. Remarkably, substitution of the C4 methylene group in γBB with an amino group in THP redirects the reaction pathway, as the lone pair electrons on the adjacent nitrogen atom render N-N bond cleavage kinetically favored over hydroxyl rebound, thereby blocking carnitine synthesis. Through systematic evaluation of possible rearrangement pathways, we rule out the previously proposed direct 1,2-H migration and suggest a revised mechanism featuring imine-mediated hydrogen transfer, hydroxyl rebound preceding C-C bond formation, and final radical coupling. This work provides a detailed atomic-level understanding of both the catalytic and inhibitory mechanisms of BBOX, revealing how substrate electronic effects dictate reaction outcomes. The elucidated mechanistic insights offer a theoretical foundation for understanding the catalytic versatility of the αKG-dependent dioxygenase family and provide valuable guidance for the rational design of novel BBOX inhibitors. Full article

Light intensity and spectral composition regulate plant physiological processes and productivity, particularly under low-light greenhouse conditions. This study was designed to address two main objectives in aeroponically grown potato (Solanum tuberosum L. cv. Agria). First, we evaluated the effects of supplemental light quality, focusing on different red (R), blue (B), and white (W) combinations at a constant intensity of 100 μmol m⁻² s⁻¹. Second, we assessed the specific effects of far-red (FR) light on plant performance and biomass allocation patterns. Potato plants were grown under greenhouse conditions in a completely randomized design consisting of eight supplemental LED spectral treatments and a natural-light control. Supplemental lighting increased net photosynthesis, stomatal conductance, chlorophyll content, and biomass compared to the control, demonstrating that moderate increases in light intensity improved plant performance under low-light conditions. Among the spectral treatments, W light and balanced R–B combinations increased net photosynthetic rate by 93.7–198.7% and total biomass by 23.8–132.1% relative to the control, suggesting improved coordination of stomatal activity, electron transport, and chlorophyll biosynthesis under the experimental light environment. In contrast, FR inclusion reduced the net photosynthetic rate and mini-tuber biomass by 15.0–38.6% relative to the corresponding FR-free treatments, particularly under treatments with lower red proportions, suggesting that FR effects are more likely associated with phytochrome-mediated regulation of photosynthetic efficiency and assimilate partitioning under modified red to far-red spectral balance rather than classical shade-avoidance responses. Mini-tuber yield was strongly affected by light treatments. White light and balanced R:B spectra produced the highest tuber number and biomass, increasing mini-tuber number and biomass by 26.6–62.5% and 15.4–87.7%, respectively, compared with the control, whereas FR reduced yield. Although FR appeared to increase the relative allocation of biomass to tubers, overall photosynthetic performance and biomass accumulation remained lower, resulting in lower productivity. Overall, mini-tuber production appeared to be associated with source–sink relationships, where light intensity enhanced photosynthetic performance and biomass production, light quality optimized photosynthetic performance, and FR light appeared to modify biomass allocation patterns. These findings highlight the importance of optimizing spectral composition and FR management in aeroponic seed potato production under low-light greenhouse conditions. Full article