Search Results (211)

Sensory, proximate composition, microbiological analyses and fatty acid profiling, combined with omic analyses, were employed to examine qualitative changes in the fillet of fresh European anchovies (Engraulis encrasicolus), caught in September of years 2020, 2021, and 2022 in the North Aegean Sea (Greece), and stored for 72 h in a salt-containing ice slurry (sub-chilled conditions). Sensorially, the quality of the whole fish decreased significantly (p < 0.05) at the end of the storage period. However, total microbial viable counts remained relatively stable (≤10⁵ CFU), as did the proximate components of the fillet, as well as the fatty acid profile of the total fat, with the main differences noted only in the distribution of the DHA and EPA in the lipid classes. Histamine levels remained at trace levels during storage and, from the proteomic analysis of the 2021 sample, significant differences were observed only in actin α1a, out of 27 major muscle proteins examined. The 16S rRNA gene analysis indicated important inter-annual changes in the anchovy’s microbiota, with no obvious pattern regarding the presence or changes in relative abundance of genera with spoilage potential during the storage period. Overall, the results suggest that short-term sub-chilled storage preserves to a large extent the nutritional and biochemical integrity of the anchovy fillets. Full article

Objectively defining an effective choice is crucial for the reliability of results in insect olfactory behavior research. Relying on subjective time thresholds often leads to inconsistent findings, primarily due to the high likelihood of mistaking an accidental intrusion for an effective choice. Our analysis indicated that 29% of preference responses were not consistent among 0 s, 15 s, 30 s, and 60 s, when these thresholds were applied to evaluate the behavioral responses of Trichogramma japonicum Ashmead (Hym.: Trichogrammatidae) to 20 odorants in a four-arm olfactometer. This inconsistency arises because subjective thresholds fail to distinguish between accidental, transient entries and sustained, purposeful choices, leading to false positives or false negatives. To address this issue, we compiled a database of the initial stay duration of T. japonicum in the odor zone, and applied the 5th percentile of its empirical distribution—a widely accepted statistical standard for excluding extreme outliers (i.e., accidental brief entries) in medical and biological research—as the threshold to differentiate between accidental intrusion and effective choice. We then systematically assessed the behavioral responses of T. japonicum to 20 odorants and validated the authenticity of olfactory preferences through oviposition choice experiments. A continuous stay of ≥10 s was determined as an effective choice. Based on this criterion, T. japonicum exhibited significant preference for 0.1 μg/μL α-pinene, 0.01 μg/μL D-limonene and 0.001 μg/μL citral, whereas avoiding 10 μg/μL β-ionone. The results of the oviposition choice experiments showed high consistency with the olfactory behavioral preferences, confirming the reliability of this standard in predicting its actual host selection decisions. Collectively, this study proposes a data-driven protocol for establishing an objective and stable behavioral criterion in insect olfactory behavior research. Full article

The nationwide implementation of B35 biodiesel in Indonesia is constrained by elevated water and particulate contents, which accelerate fuel degradation and promote filter clogging. Mitigating these issues is essential to ensure fuel quality, safe distribution, and stable engine operation. This study proposes a renewable essential-oil-derived bioadditive as an alternative to petroleum-based additives, with novelty arising from a fractionation-guided multi-essential-oil formulation and its comprehensive validation, encompassing molecular characterization, fuel-quality compliance, engine performance, and exhaust emissions. The objective of this study was to develop and validate an essential-oil bioadditive capable of (i) reducing water and particulate contents in B35 biodiesel in compliance with Indonesian fuel standards and (ii) evaluating its effects on engine performance and emissions. Turpentine, clove terpene, citronella, and rhodinol oils were characterized by GC–MS and fractionated to obtain α-pinene-, caryophyllene-, and rhodinol-rich fractions. Eight formulations were prepared by varying oil ratios and blended into B35 at 0.1% v/v. Water content was monitored over 7 days of storage, followed by flash point screening. The optimal formulation was further evaluated for particulate content, physicochemical properties, engine performance using a dynotest, and exhaust emissions on a Kubota D722 diesel engine. Among all formulations, D1 (turpentine:clove terpene:citronella = 1:8:1) exhibited the most balanced performance. D1 reduced water content to 320 mg/kg, meeting the ≤400 mg/kg limit, and increased the flash point to 75 °C (minimum requirement: 52 °C). Particulate levels across 4, 6, and 14 μm fractions were substantially reduced. The B35 + D1 blend satisfied key fuel specifications, including a cetane number of 54.7, viscosity of 3.171 mm²/s, and oxidation stability exceeding 35 h. Engine testing showed more stable torque and power at high speeds with D1 at 1% v/v compared with 0.1% v/v. Smoke emissions decreased markedly, while NOx emissions increased, indicating a combustion trade-off typical of oxygenated additives. Full article

This paper proposes a personalized federated learning framework for appliance recognition in non-intrusive load monitoring (NILM) to address real-world data heterogeneity. Each client maintains a personalized model alongside shared global components. To decouple these components, a context-aware conditional policy module adaptively separates global and personalized information via learnable gating. The method enables collaborative training without raw data exchange and mitigates the impact of inter-client label distribution skew. We evaluate the proposed method under four federated settings: independent and identically distributed (IID), Dirichlet non-IID, house-partitioned, and leave-one-house-out. Experiments on three public datasets show strong and stable performance compared with existing federated approaches. Under Dirichlet skew ($\alpha =0.1$), our method achieves an accuracy of $93.8\pm 0.9\%$ on PLAID, $92.3\pm 1.4\%$ on WHITED, and $96.6\pm 1.5\%$ on COOLL. In the leave-one-house-out setting, it attains $80.3\pm 2.0\%$ on PLAID. These results demonstrate the effectiveness of the proposed method across challenging non-IID scenarios. Full article

Graphene oxide (GO)-based nanomaterials functionalized with targeting ligands are promising platforms for selective cancer drug delivery. Among relevant targets, integrin α_Vβ₃ is a highly overexpressed receptor in several solid tumors and is commonly targeted using cyclic Arg-Gly-Asp (cRGD) peptides. However, the molecular details governing the interaction between cRGD-functionalized GO dots and integrins remain poorly understood. In this work, all-atom molecular dynamics simulations are employed to investigate the interaction between integrin α_Vβ₃ and a nanocarrier composed of a GO dot coated with polyethylene glycol (PEG) and functionalized with cRGD ligands. Multiple 1 μs simulation replicas are used to characterize both specific ligand recognition and non-specific nanocarrier/receptor interactions. The simulations show that cRGD binding within the integrin-binding pocket is stable, indicating that the nanocarrier does not impair receptor recognition. Beyond cRGD-mediated binding, both PEG-cRGD chains and GO itself establish additional contacts with the protein, whose nature and distribution are modulated by the relative orientation of the GO plane. Overall, the structural dynamics of integrin α_Vβ₃ remains preserved upon nanocarrier binding. These findings provide atomistic insights into the interplay between ligand-mediated and multivalent surface-mediated interactions of GO-based nanocarriers with integrins for the rational design of selective nanocarriers for cancer therapy. Full article

Water-in-water (W/W) Pickering emulsions based on aqueous two-phase systems (ATPS) are promising for food applications, but their stabilization is challenged by the ultra-low interfacial tension inherent to ATPSs. This study developed food-grade W/W Pickering emulsions stabilized by bacterial cellulose nanocrystals (BCNCs) and evaluated their ability to regulate starch digestibility. The effects of dextran (Dex) concentration, maltodextrin (MD) concentration, and BCNC content on the microstructure, rheological properties, and stability of the emulsions were systematically investigated. The partitioning behavior of amylopectin (AMP) between the two phases and the in vitro digestion behavior of AMP-loaded W/W Pickering emulsions in the presence of α-amylase were further examined. Fourier-transform infrared spectroscopy confirmed the successful preparation of BCNCs. The optimal formulation (24 wt% Dex, 14 wt% MD, and 0.24 wt% BCNCs) exhibited a uniform droplet distribution and enhanced storage stability. Contact angle analysis indicated preferential wettability of BCNCs toward the continuous Dex-rich phase, promoting interfacial adsorption and droplet stabilization. The emulsions remained stable at pH 3.0–7.0 but were sensitive to ionic strength above 7 mM sodium chloride. Importantly, in vitro digestion showed that BCNC-stabilized emulsions significantly inhibited α-amylase-mediated hydrolysis of AMP, with the hydrolysis extent reducing from ~54% to 14%. These results indicate that BCNCs act as effective natural stabilizers for W/W Pickering emulsions, forming a physical barrier that retards starch digestion. This work provides a sustainable strategy for designing slow-digestible, low-glycemic-index food systems with potential applications in functional foods and pharmaceuticals. Full article

Knowledge distillation transfers information from a high-capacity teacher to a smaller student, but its behavior across regression, classification, and heterogeneous tabular model families remains insufficiently understood. This paper presents a comparative simulation study of distillation in structured-data settings, where neural networks, tree ensembles, kernel methods, nearest-neighbor methods, and linear models are plausible competitors. Synthetic datasets with known ground truth and controlled noise are used to evaluate a three-model teacher ensemble distilled into multilayer perceptrons, tree ensembles, decision trees, kernel methods, instance-based methods, and linear models. Distillation weights and temperatures are selected on validation data, and test results are reported with confidence intervals, paired tests, and multiplicity-control checks. In regression, distillation acts as target smoothing and denoising: the teacher reduces label noise by 17.4%, 13 of 14 students improve numerically, and the MSE reduction is 7.1%. After multiplicity control, robust gains concentrate among MLPs. In classification, gains are smaller: 12 of 15 students improve, with an average accuracy gain of 0.5 percentage points, and soft-label distillation improves calibration for MLPs. Additional noise sweeps, teacher ablations, real-data checks, baseline comparisons, temperature analysis, and calibration results show that distillation helps most when the student has sufficient capacity, and the teacher provides a cleaner or more informative target. An extended set of confirmatory analyses—including teacher-quality controls with a shuffled negative control, ensemble-based uncertainty proxies, harder data conditions, distribution-shift robustness, a capacity ladder, computational-cost analysis, additional baselines and calibration metrics, an $\alpha$–T factorial analysis, quantitative measures of soft-probability structure, and comparisons with modern tabular models—shows that useful transfer requires teacher predictions that remain conditionally aligned with the inputs. The classification gains are small in absolute accuracy but stable across seeds and are accompanied by improvements in selected calibration measures. Full article

Aiming at the problem that sparse channel estimation in underwater acoustic communication is susceptible to complex multipath propagation, non-Gaussian impulsive noise, and channel time variations, this paper proposes a bidirectional proportionate recursive maximum correntropy criterion algorithm, referred to as Bi-PRMCC. By introducing a bidirectional filtering structure into the proportionate recursive maximum correntropy criterion (PRMCC) framework, the proposed algorithm jointly exploits the information from forward and backward data sequences, thereby improving the estimation accuracy and block-based channel variation tracking capability for sparse underwater acoustic channels. Meanwhile, the maximum correntropy criterion enhances the robustness of the algorithm against non-Gaussian impulsive noise and outlier error samples, while the proportionate update mechanism improves its identification capability for dominant taps in sparse channels. To verify the effectiveness of the proposed algorithm, short-range sparse underwater acoustic channels and long-range complex multipath underwater acoustic channels are constructed based on the Bellhop ray-tracing model. Simulation experiments are then conducted under three typical non-Gaussian noise environments, namely Cauchy noise, $\alpha$-stable distribution noise, and Middleton noise. The experimental results show that, compared with recursive least squares (RLS), bidirectional recursive least squares (Bi-RLS), proportionate recursive least squares (PRLS), recursive maximum correntropy criterion (RMCC), and PRMCC, Bi-PRMCC achieves a lower steady-state normalized mean square deviation (NMSD) under different non-Gaussian noise conditions, indicating stronger robustness against impulsive noise. Under different signal-to-noise ratio conditions, the proposed algorithm still maintains superior steady-state estimation performance. In addition, in the channel abrupt-change tracking experiment, Bi-PRMCC can rapidly reconverge after channel variations occur, demonstrating favorable reconvergence capability under abrupt channel variations. The ablation study further verifies the stable performance gain brought by the bidirectional structure to PRMCC. Overall, the proposed Bi-PRMCC algorithm exhibits high estimation accuracy, robustness, and reconvergence capability under complex non-Gaussian noise and abrupt channel variation conditions. Full article

Fluorinated carboxylate ester solvents are promising electrolyte components for lithium metal batteries because they can improve oxidative stability and promote LiF-rich solid electrolyte interphase (SEI) formation. However, how fluorination position and degree regulate their intrinsic decomposition behavior on lithium metal remains unclear. Herein, density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations were employed to systematically investigate six pure fluorinated ethyl acetate solvents on the Li(001) surface, including α-fluorinated ethyl fluoroacetate (EFA), ethyl difluoroacetate (EDFA), and ethyl trifluoroacetate (ETFA), as well as β-fluorinated 2-fluoroethyl acetate (FEA), 2,2-difluoroethyl acetate (DFEA), and 2,2,2-trifluoroethyl acetate (TFEA). Electronic-structure analysis shows that although the lowest unoccupied molecular orbitals (LUMOs) of all six solvents are mainly distributed around the carbonyl and adjacent regions, the dominant electron-accepting center strongly depends on the fluorination position. In α-fluorinated solvents, the LUMO is highly localized on the α-C atom directly bonded to fluorine, whereas in β-fluorinated solvents, it remains concentrated around the carbonyl C atom. Real-time Bader charge and bond-evolution analyses reveal that fluorination position is the primary factor governing the initial decomposition pathway. The α-fluorinated series preferentially undergoes C-F bond cleavage, and increasing fluorination degree induces deeper cascade decomposition; fully fluorinated ETFA even exhibits C=O double bond cleavage. In contrast, β-fluorinated solvents preferentially undergo carbonyl-side C-O bond cleavage, while C-F bond cleavage occurs only in subsequent steps or is completely suppressed. Notably, β-fluorinated solvents retain high chemical stability even with α-H atoms because the LUMO electron density on α-H is negligible. Meanwhile, limited deep decomposition can still provide F⁻ species for SEI formation. These findings establish an atomic-level structure–reactivity relationship for fluorinated carboxylate ester solvents and provide theoretical guidance for designing stable electrolyte solvents for lithium metal batteries. Full article

Background: Obesity is a chronic, relapsing disease that often proves resistant to lifestyle measures alone. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), are reshaping treatment, yet prospective real-world data remain limited. Objective: To prospectively assess the effects of once-weekly Semaglutide on weight, body composition, and metabolic health in obesity. Methods: An exploratory observational study of 37 patients initiating Semaglutide (mean age 31 years; 11 children and adolescents; 22 females) was conducted. All met obesity criteria (baseline BMI 34.7 kg/m²). Anthropometry, bioimpedance body composition, and fasting biochemistry were obtained at baseline and 3 months. Variables were reported as mean ± SD or median (IQR) according to normal/non-normal distribution, whether a parametric test or a Wilcoxon one was used. Parametric or non-parametric paired tests (two-sided α = 0.05) were applied. We also explored tri-ponderal mass index (TMI, kg/m³) and its correlations with metabolic markers. Results: At 3 months, body weight decreased by a median 8.0 kg (p < 0.001), BMI by 1.6 kg/m² (p < 0.001). Body fat percentage declined: 43.4% to 42.8% (p = 0.009), with a small reduction in skeletal muscle mass (−0.6 kg; p = 0.035). Fasting glucose improved (p = 0.030) and HOMA-IR fell significantly. HbA1c changes were minimal, consistent with near-normal baseline values. Triglycerides decreased, while total cholesterol, LDL-C, HDL-C, liver enzymes, creatinine, uric acid, and 25-OH vitamin D remained stable. Baseline TMI (median 20.13 kg/m³; IQR 3.80) correlated strongly with HOMA-IR (r = 0.766, p < 0.001) and moderately-to-strongly with body fat percentage (r = 0.621, p < 0.001). Conclusions: In this real-world cohort, Semaglutide produced rapid, clinically meaningful improvements in weight, adiposity, and insulin resistance within 3 months. Findings suggest that Semaglutide may represent a promising adjunct to lifestyle therapy in obesity management. Full article

Ti–6Al–4V is the primary titanium alloy for aerospace, biomedical, and additive manufacturing applications; however, the high cost of powders produced by atomization limits their widespread adoption. This study aims to develop a cost-effective method for producing chemically homogeneous pre-alloyed Ti–6Al–4V powders from titanium sponge. A combined process is proposed, involving the hydrogenation of titanium sponge, mechanical alloying of the hydride phase with Al and V powders, and subsequent vacuum dehydrogenation. The formation of the brittle δ-TiH₂ phase facilitated intensive material comminution and effective distribution of the alloying elements. According to laser diffraction data, the median particle size decreased from 450 to 30–35 µm. X-ray diffraction (XRD) analysis confirmed the sequential α-Ti → δ-TiH₂ transition and the formation of a stable α + β two-phase structure characteristic of Ti–6Al–4V following dehydrogenation. SEM observations demonstrated that the final powders predominantly consist of individual fractured particles with limited hard agglomeration, favorable for powder flowability and compaction behavior. EDS analysis indicated a relatively homogeneous microscale distribution of Al and V without observable large-scale segregation. The synthesized powders exhibited low impurity levels, with O < 0.07 wt.% and H < 0.02 wt.%. The developed approach represents a promising and economical alternative to expensive atomization techniques for powder metallurgy and additive manufacturing. Full article

This study investigates the correlation between sintering temperature, microstructure, and mechanical properties in AlSi10Mg alloy produced by supersolidus liquid phase sintering and subsequent artificial aging. Sintering was performed at 571, 575, and 579 °C using different heating rates for a total duration of approximately 5 h, followed by a 2 h dwell at the sintering temperature. At low sintering temperature, the alloy exhibits relatively fine α-Al grains with uniformly distributed Si precipitates, whereas intermediate temperature promotes Si coarsening. At higher temperature, excessive liquid formation leads to coarse α-Al grains and the development of partially interconnected Si networks. β-Al₅FeSi progressively coarsen with increasing sintering temperature. In the as-sintered state, the modest mechanical properties result from coarse α-Al grain size and subgrain structure, as well as from the size, morphology, and distribution of the Si phase. After aging (at 160 °C for 6 h following solution treatment at 530 °C for 30 min), the hardness and UTS were almost double (going from 44 ± 1 to 103 ± 2 HV and from 121 ± 1 to 273 ± 40 MPa). Meanwhile, α-Al grain size and Si morphology remained unchanged and Fe-rich intermetallics partially transformed into the more stable γ-Al₃FeSi₂ phase. Full article

To address the limited constraints of ground-based lidar with few channels in retrieving aerosol microphysical parameters in urban atmospheres, this study developed a method to retrieve aerosol volume size distribution and effective radius from a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar system. The method uses 3β + 2α optical quantities as input constraints, applies Mie scattering theory as the forward model, parameterizes the volume size distribution with B-spline functions, and achieves stable solutions through Tikhonov regularization and cross-validation. To reduce uncertainties in prior parameters, including the complex refractive index, particle size range, and lidar ratio, an optimization strategy based on parameter search, retrieval reconstruction, and error minimization was introduced. Numerical simulations showed that the method reproduced the main features of a bimodal lognormal aerosol volume size distribution with good feasibility and stability. Two case studies further showed fine-mode dominance and decreasing extinction coefficient, depolarization ratio, and effective radius with height under good air quality conditions, but enhanced coarse-mode contribution and effective radius in the upper cloud-influenced layer under lightly polluted conditions, as inferred from the combined variations in RSCS, extinction coefficient, depolarization ratio, and effective radius. Full article

Background/Objectives: Diabetes mellitus (DM) is a critical metabolic condition with escalated blood glucose levels caused by insulin resistance, restricted insulin production, and the activity of alpha-amylase and alpha-glucosidase enzymes. Methods: This current work focuses on the synthesis and evaluation of novel Pyrimidine-derived pyrazole-based thiadiazole derivatives to target DM by inhibiting α-amylase and α-glucosidase. Results: The findings exhibited that, except for three compounds, all other synthesized derivatives inhibited α-amylase and α-glucosidase enzymes with IC₅₀ values ranging from 5.17 μM to 29.84 μM on α-amylase and 7.60 μM to 31.62 μM on α-glucosidase, in comparison to the standard drug Acarbose (α-amylase IC₅₀ = 8.25 ± 0.80 μM; α-glucosidase IC₅₀ = 10.75 ± 1.10 μM). Analogs 8g, 8k, and 8b displayed superior or comparable inhibitory activity compared to the reference drug Acarbose. The inhibition potential of the derivatives can be attributed to their stable contacts with crucial amino acid residues of targeted enzymes, as shown through molecular docking analysis. Moreover, DFT-calculated HOMO–LUMO parameters and electrostatic potential (ESP) maps were used to gain complementary insight into the electronic characteristics, charge distribution, and potential interaction behavior of the synthesized derivatives, which supported the molecular docking observations. Conclusions: Experimental outcomes and in silico support display that these derivatives serve as potential leads for anti-diabetic drug development. These potent pyrimidine-derived pyrazole-based thiadiazole derivatives were comparable to an existing diabetic mellitus inhibitor, specifying potential for further therapeutic development and optimization against diabetic mellitus. Full article

Background/Objectives: Natural macromolecule-based drug delivery carriers have gained extensive attention for biomedical applications. This study aimed to construct an efficient oral delivery system for the widely used antitumor drug docetaxel (DTX) by utilizing natural nanoparticles derived from Ganoderma (LZ-Nnps). Methods: LZ-Nnps loaded with DTX (LZ-Nnps-DTX) were fabricated via an optimized heat-induced self-assembly approach and characterized for morphology, particle size, zeta potential, stability, drug loading, encapsulation efficiency, and molecular interactions with DTX. Intestinal absorption, pharmacokinetics, and tissue distribution were respectively assessed, while antitumor efficacy, macrophage internalization mechanisms, and immunomodulatory activation were further investigated. Results: The optimized formulation showed a particle size of 361.3 ± 5.3 nm, zeta potential of −39.55 ± 1.31 mV, drug loading of 1.51 ± 0.08%, and near-complete encapsulation efficiency (99.97 ± 0.02%), with favorable stability in gastrointestinal fluids. Hydrogen bonding and hydrophobic interactions effectively kept DTX in a stable amorphous state. LZ-Nnps-DTX markedly improved DTX aqueous solubility, dissolution, and intestinal absorption. In vivo assays showed oral LZ-Nnps-DTX achieved 34-fold higher C_max and 7.8-fold larger plasma AUC_0-t than free DTX, and mainly accumulated in the liver and lung. The nanoparticles entered Caco-2 cells via macropinocytosis and mainly accumulated in the liver. LZ-Nnps-DTX exerted strong cytotoxicity against HepG2, A549, and HCT116 cells, was internalized by RAW264.7 macrophages through caveolae-mediated endocytosis and phagocytosis, and stimulated TNF-α and NO production to suppress tumor growth. Conclusions: These findings demonstrate that LZ-Nnps-DTX effectively enhances oral bioavailability, exerts potent antitumor effects, and activates macrophage-mediated immunity, supporting its promise as an oral DTX delivery system. Full article