Search Results (1,152)

The brewing of Traditional Hakka Huangjiu (THHJ) is usually divided into saccharification and post-fermentation. Microbial succession during saccharification is the major factor influencing the development of the volatile and non-volatile substances in THHJ during post-fermentation. This study systematically investigated the dynamic changes in microbial community, volatile substances and microbial metabolites by using absolute quantitative sequencing and multi-omics analysis. This study also reported that the correlation between microorganisms and substance biosynthesis was analyzed using PICRUSt. Absolute quantitative sequencing results showed that Pediococcus, Saccharomycopsis, Rhizopus, Weissella, and Limosilactobacillus were the dominant microbial genera during saccharification. 737 volatile compounds (170 esters, 94 hydrocarbons, 82 organoheterocyclic compounds) and 4370 metabolites (18 organic acids, 22 amino acids, 1124 peptides and 9 categories of functional compounds) were identified throughout the post-fermentation period. Sensory profiling revealed six main flavor attributes (Balsamic, sweet, rose, green, fruity, bitter) in THHJ and phenylethyl alcohol exerted the most prominent effect on the overall flavor of THHJ. Correlation analysis revealed that the biosynthesis of phenylethyl alcohol was potentially correlated with Saccharomyces, Cyberlindnera, Pichia, Pediococcus, Pseudomonas and Lactococcus. The biosynthesis of flavonoids was potentially correlated with Pediococcus, Lactococcus, and Lactiplantibacillus. These findings contribute to monitoring product quality and optimizing the processing techniques of THHJ. Full article

Apache Spark has gained widespread adoption for large-scale data processing. However, conventional caching methods inadequately address the dual challenges of performance bottlenecks and escalating energy consumption in data-intensive workloads. This paper introduces a sustainable computing framework that integrates Directed Acyclic Graph (DAG) dependency analysis with garbage collection (GC) behavior monitoring to optimize data placement between DRAM and non-volatile memory (NVM). The proposed Intelligent Hybrid Caching Management Framework (IHCMF) dynamically predicts data access patterns and migrates cache blocks based on cost–benefit analysis, achieving a 37.5% execution time reduction over default Spark configurations in SparkBench evaluations. By improving throughput-per-watt and projecting potential benefits from NVM’s near-zero idle power and extended hardware lifespan, IHCMF provides a scalable, cost-effective caching solution for resource-constrained edge computing environments. This work demonstrates that high-performance computing can be reconciled with environmental sustainability through intelligent memory management. Full article

This study examined the evolution of volatile and non-volatile compounds of a Cypriot monovarietal cultivar Maratheftiko red wine over a span of six years (2019–2024). Several physicochemical properties of the wines were evaluated. Alcohol content and volatile acidity remained stable; acidity and malic acid are the main differentiating factors among vintages. In addition, bioactive molecules in the wines showed a distinct vintage effect, with the 2024 vintage exhibiting significantly higher concentrations. For instance, the high concentration of polyphenols (3877.86 mg gallic acid equivalents per L), tannins (688.43 mg of catechin equivalents per L), flavonoids (506.90 mg of rutin equivalents per L), and anthocyanins (413.74 mg of cyanidin equivalents per L) contributed to the high antioxidant capacity of the specific vintage, as FRAP and DPPH assays were measured at 44.60 and 29.91 mmol of ascorbic acid equivalents per L, respectively. Furthermore, the intense crimson color of this red wine could be attributed to the high concentration of the abundant anthocyanin malvidin-3-O-glucoside in this vintage (21.62 mg/L). On the other hand, it was observed that the latest vintage showed high polyphenol concentration but low volatile compound concentration. This pattern was ascertained through correlation analyses and could be attributed to an unsatisfactory level of the aging process. Correlation analysis (Pearson’s r) confirmed inverse relationships between polyphenol concentration and volatile compounds (r = −0.62, p < 0.05). Principal component analysis (PCA) further highlighted the 2024 as an outlier vintage, distinguished by elevated phenolic and antioxidant profiles. Full article

Kucha, a unique tea germplasm rich in theacrine, imparts its fresh leaves with a particularly bitter taste and multiple bioactivities. However, systematic studies on processed Kucha—especially white tea—remain limited. In this study, white teas were produced from two Yunnan Kucha accessions (YLKC1, YLKC2) and two conventional cultivars. Their quality characteristics and non-volatile metabolic profiles were systematically compared using sensory evaluation, targeted quantification and widely targeted metabolomics. Results indicated that Kucha white teas displayed pronounced bitterness, with YLKC1 presenting a richer, well-layered flavor, indicating promising quality potential. Targeted quantification demonstrated a remarkably high theacrine content (~30 mg/g) in Kucha white teas, whereas caffeine and several catechin monomers were significantly lower than those in conventional cultivars. Widely targeted metabolomic analysis identified 3376 non-volatile metabolites. PCA and OPLS-DA demonstrated a clear separation in metabolic profiles between Kucha and control groups. In total, 601 significantly differential metabolites were identified. Taste-driven annotation against ChemTastesDB revealed 17 known bitter compounds, 10 of which were significantly accumulated in Kucha white tea—including theacrine, theophylline, theobromine, L-arginine, neohesperidin, pinocembrin, kaempferol-3-O-(6”-malonyl)glucoside, fraxin, adenosine, and xanthine. Among these compounds, theacrine showed the highest upregulation (9.30-fold). In addition, several galloylated flavonoid glycosides also exhibited significant accumulation. KEGG enrichment analysis further indicated that flavonoid biosynthesis and caffeine metabolism were crucial pathways contributing to these metabolic differences. Collectively, these findings demonstrate that the characteristic bitterness of Kucha white tea arises from the coordinated accumulation of a specific set of bitter phytochemicals rather than a single compound and provide a prioritized panel of candidate compounds for flavor-oriented breeding and processing. Full article

As a uniquely Chinese post-fermented tea, Pu-erh tea undergoes profound changes in quality and flavor during aging, a process primarily driven by microbially mediated metabolic transformations. However, the patterns of microbe–metabolite co-evolution spanning a century-long timescale remain unclear. This study employed three samples—S (1920 raw Pu-erh tea), Y (1999 raw Pu-erh tea), and Q (2024 ripe Pu-erh tea)—integrating non-targeted metabolomics and microbiomics technologies to systematically analyze the characteristics of metabolites and microbial communities in century-old Pu-erh tea. The study elucidated the metabolic characteristics at the endpoint of long-term natural aging: the specific enrichment of hydrolyzable tannins, sucrose, and bipyrrole aromatic derivatives, providing a chemical basis for its unique “century-old charm”. Microbial community analysis indicated that long-term aging leads to simplified bacterial communities but increased fungal evenness, with the century-old sample specifically enriching for Thermodesulfobacterium and a large number of unclassified fungi. Multivariate statistics further constructed a microbe–metabolite interaction network, confirming significant correlations between key bacterial genera such as Paenibacillus and Bacillus and flavor precursors like sugars and phenolic acids. Full article

This paper presents a novel, minimalist floating memristor emulator circuit designed for low-power biomedical analog front ends. The proposed topology requires only two dynamic threshold MOS (DTMOS) transistors and one capacitor, constituting one of the most compact memristor emulators reported. The circuit operates without static power consumption and exploits the body-effect coupling in DTMOS devices to generate a state-dependent resistance. Comprehensive simulation in a 0.18 μm CMOS process verifies core memristive characteristics: a frequency-dependent pinched hysteresis loop tunable via capacitance, non-volatile memory, and robustness across temperature and process variations. Experimental validation using a discrete CD4007-based prototype confirms the pinched hysteresis loop from 100 Hz to 800 kHz, with a maximum simulated operating frequency of 500 MHz. A comparative analysis demonstrates that the design achieves a favorable trade-off, simultaneously minimizing transistor count and power while providing floating operation and high-speed performance. These attributes make the emulator a compelling candidate for integration into adaptive, area and power constrained biomedical signal conditioning systems. Full article

Background: Red/blue- light-emitting diode (LED)-assisted withering provides a controllable spectral input to steer tea quality, yet metabolite-level evidence linking spectrum composition to quantitative taste phenotypes in white tea remains insufficient. Methods: Fresh leaves were withered under supplemental red/blue LEDs—S0, S1, S2, S3, S4, and S5—and the resulting white teas were evaluated by quantitative descriptive analysis (QDA), untargeted metabolomics, weighted gene co-expression network analysis (WGCNA), and high-performance liquid chromatography (HPLC) quantification of caffeine, gallic acid, and eight catechin monomers. Results: Red/blue-mixed spectrum enhanced the overall sensory quality relative to the incandescent lamp; S3 maximized sweetness and freshness, whereas S4 minimized bitterness and astringency and achieved the highest overall score. Untargeted metabolomics showed the largest deviation for S0 vs. S4. A total of 18 common metabolites were identified between the S0 and light-supplemented withering treatments, dominated by saccharides and related derivatives. WGCNA linked a saccharide-centered module to higher sweetness/freshness/smoothness and a lipid-oxylipin-centered module to stronger bitterness/astringency. HPLC independently confirmed that S4 contained the lowest catechins and caffeine, supporting its reduced bitter/astringent attributes. Conclusions: Overall, the application of mixed red-blue spectra offered a promising approach to enhancing the palatability of white tea by coordinately intensifying saccharide metabolism while simultaneously suppressing key bitter and astringent components. Our study provided a scientific basis for standardizing white tea processing to enhance sensory quality. Full article

Polymer blends are an essential category of materials formed by physically combining two or more polymers. The plasticizing process is advantageous for brittle or rigid polymer systems that need improved flexibility or ductility. The increasing demand for environmentally friendly and high-performance polymeric materials has spurred research into alternative plasticization methods. The use of ionic liquids as non-volatile plasticizers in polymer blends is owing to their outstanding properties. In this short review, several ionic liquids employed in polymer blends and some polymers used in blends with ionic liquids are listed. Additionally, the plasticizing effects of ionic liquids on the properties of polymer blends are concisely elucidated. This review also provides a brief overview of the potential applications of polymer blends plasticized with ionic liquids. In summary, many studies reveal that ionic liquid-based plasticization impacts the structural, thermal, conductive, and mechanical properties of polymer blends. The potential applications of polymer blends plasticized with ionic liquids cover various fields, including energy systems, packaging, electronics, and soft robotics. Full article

Parastrephia quadrangularis (tola) is a native plant of the Chilean Andean Altiplano that is traditionally used for its anti-inflammatory properties. In this study, the aerial parts of the plant were analysed to determine their fatty acid (FA) profile and to identify bioactive compounds using gas chromatography–mass spectrometry (GC–MS). Both conventional extraction methods and Supercritical Fluid Extraction (SFE) were employed, using a 2³ factorial design with centre-point replicates. The variables included temperature (30–60 °C), pressure (15–45 MPa), and ethanol as a cosolvent (0–30% v/v). Extraction kinetics were evaluated using a linear spline model under central conditions (45 °C, 30 MPa, 15% ethanol). Response variables included extraction yield, Total Phenolic Content (TPC), antioxidant activity measured by Trolox Equivalent Antioxidant Capacity (TEAC), and FA composition. A factorial design identified pressure and ethanol concentration as key drivers of phenolic content and antioxidant activity, as supported by confocal autofluorescence microscopy. Multi-response optimisation based on the desirability function was applied to simultaneously maximise all response variables, yielding predicted optimal extraction conditions at 60 °C, 45 MPa, and 30% v/v ethanol for P. quadrangularis. The FA profile highlighted polyunsaturated FAs such as oleic, linoleic, and linolenic acids, as well as saturated FAs including palmitic and lignoceric acids, and short-chain non-volatile FAs. GC–MS analysis revealed metabolites potentially responsible for the plant’s traditionally reported therapeutic effects. Overall, these results highlight ethanol-based SFE as a sustainable strategy for recovering phenolic compounds and antioxidant-related fractions from ancestral medicinal plants. Full article

Cinnamomum cassia essential oil production generates substantial waste, and the therapeutic potential of non-volatile constituents from cinnamomum cassia leaves in ulcerative colitis (UC) has not been fully explored. This research focused on identifying the principal components of cinnamomum cassia leaf extract (CCLE) through ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS), and its anti-inflammatory potential was verified in vitro. A lipopolysaccharide (LPS)-stimulated RAW264.7 macrophage model was employed, with assessments performed through cell viability assays, Griess assay, fluorescent probe detection, wound healing, and Transwell migration assays. Network pharmacology analysis combined with molecular docking revealed that CCLE exerts therapeutic effects against UC by targeting key molecules including TNF, TLR4, STAT3, SRC, PTGS2, NFKB1, MMP9, EGFR, BCL2, and AKT1, with high binding affinity between these targets and CCLE components (especially Quercetin, Catechin, Naringenin, 3′,4′-dimethoxyflavonol, Procyanidin Bl, and Caffeic acid). Enrichment analysis indicated that the therapeutic effect of CCLE on UC was significantly associated with the PI3K-Akt signaling pathway, B cell receptor signaling pathway, NF-κB signaling pathway, TNF signaling pathway, and JAK-STAT signaling pathway. The experimental results demonstrated that CCLE markedly reduced the production of nitric oxide (NO) and reactive oxygen species (ROS) (* p < 0.05) and inhibited macrophage migration (* p < 0.05). In conclusion, CCLE appears to ameliorate UC via a multi-target regulatory mechanism involving inflammatory signaling pathways. These outcomes offer a scientific foundation for the further development of CCLE. Full article

Phase-change materials of the Ge–Sb–Te (GST) system are promising for non-volatile memory and programmable photonics owing to their reversible amorphous–crystalline transitions. Among these materials, GeSb₄Te₇ stands out for its optimal balance of thermal stability, switching speed, and energy efficiency. The properties of GST materials are critically dependent on structural defects, particularly germanium vacancies that occur during synthesis and operation. Using density functional theory, we demonstrate that Ge vacancies and Ge–Sb intermixing significantly influence the electronic and optical properties of GeSb₄Te₇. Positive binding energies reveal vacancy clustering tendencies, which systematically reduce p-type degeneracy and widen the band gap (from 0.47 to 0.67 eV at a 2.7% vacancy concentration). Consequently, the metallic optical response in the visible range diminishes, as reflected in the less negative real dielectric function. Furthermore, we extend our investigation to the fundamental building block of this material system, the GeSb₂Te₄ monolayer. By studying controlled interlayer displacements of Ge and Te atoms in an otherwise stoichiometric slab, we elucidate the switching mechanism in the two-dimensional limit. The pristine monolayer exhibits semiconducting behavior with an indirect band gap of 0.74 eV, while layer sliding induces a semiconductor-to-metal transition accompanied by pronounced changes in the optical absorption spectrum. The asymmetric energy barrier (1.69 eV forward, 0.60 eV reverse) suggests favorable reversible switching via structural distortions alone, without requiring chemical modifications. The obtained results, spanning from defective bulk crystals to structurally distorted monolayers, are important for the targeted optimization of GST material properties in memory devices, optical elements, and emerging nanoscale phase-change applications. Full article

Asymmetric error characteristics in spin-transfer torque magnetic random-access memory (STT-MRAM), particularly the imbalance between logical ‘0’ and ‘1’ error probabilities, can significantly degrade system reliability under conventional modulation and error-correcting schemes. This issue is especially critical in sensor network applications, where STT-MRAM is widely adopted for its non-volatility, low standby power, and robustness under energy-constrained and intermittently active operation. Existing approaches typically optimize the detection threshold under the assumption of a fixed or equiprobable bit distribution, while sparse coding techniques impose a predefined imbalance without explicitly accounting for its interaction with threshold detection. In this paper, we formulate the bit error rate (BER) minimization problem as a joint optimization of the codeword bit distribution and the detection threshold over an asymmetric cascaded STT-MRAM channel. Analytical results reveal that the minimum BER is achieved when the error probabilities associated with transmitted ‘0’ and ‘1’ bits are balanced, which induces an intrinsic coupling between the optimal detection threshold and the codeword composition. Motivated by this insight, we propose a new family of threshold-matched probability codes (TMPCs), in which the proportion of logical ‘1’s in each codeword is explicitly designed to match the optimal detection threshold of the underlying channel. The proposed coding framework generalizes conventional sparse modulation by enabling adjustable bit distributions while preserving low-complexity linear encoding and syndrome-based decoding. Numerical evaluations demonstrate that the TMPC achieves consistently lower BERs than existing sparse and fixed-distribution coding schemes across a wide range of STT-MRAM operating conditions, particularly under severe write asymmetry and resistance variation. These results indicate that the proposed joint design offers a principled and flexible approach for improving reliability in STT-MRAM-based sensor networks and non-volatile memory systems. Full article

Background: Intravenous fluids modify acid–base balance by changing plasma strong ion difference (SID_PL) and total non-volatile weak acids. Experimental data suggest that pre-infusion plasma bicarbonate (HCO₃⁻) may further modulate these effects. We tested this hypothesis in a large cohort of postoperative ICU patients receiving intravenous fluids. Methods: We retrospectively analyzed all-consecutive post-operative ICU admissions over a 21-month period who received fluid therapy. Fluid inputs/outputs, plasma electrolytes, and arterial blood gases were collected from admission to 9:00 A.M. of postoperative day one. Average SID of infused fluids (SID_INF) was calculated, and SID_PL and standard base excess variations (ΔSBE) were assessed. Patients were stratified by SID_INF tertiles (low, <41.0 mEq/L; medium, 41.2–54.6 mEq/L; high, ≥55.0 mEq/L), median pre-infusion HCO₃⁻ (24.3 [22.4–26.3] mmol/L), and tertiles of SID_INF-HCO₃⁻ difference. Results: Among 650 admissions, 641 were included (83% elective surgery). Pre-infusion acid–base was, as average, within normal ranges. Total infused volume averaged 2327 ± 1111 mL. Across SID_INF tertiles, ΔSBE increased from 1.2 ± 3.4 to 3.0 ± 3.0 and 3.4 ± 3.0 mmol/L (p < 0.001), paralleled by ΔSID_PL rise (0.6 ± 2.3, 1.3 ± 2.4 and 1.4 ± 2.3 mEq/L, respectively; p = 0.004). For any given SID_INF, patients with lower pre-infusion HCO₃⁻ showed greater ΔSBE and ΔSID_PL (p < 0.001). When analyzed by tertiles of SID_INF-HCO₃⁻ difference, ΔSBE rose from 1.0 ± 3.2 to 2.7 ± 2.9 and 4.0 ± 3.0 mmol/L (p < 0.001), with amplified effects at higher infused volume (>2500 mL). Conclusions: In postoperative ICU patients, fluid-induced acid–base changes are largely driven by SID_INF-HCO₃⁻ difference, supporting individualized fluid selection based on baseline HCO₃⁻. Full article

Background: Geraniaceae species are widely used in traditional medicine. Pelargonium radula and Geranium macrorrhizum are aromatic medicinal plants traditionally used in Bulgaria for their antimicrobial, anti-inflammatory, and wound-healing properties. Comparative phytochemical data on Pelargonium radula and Geranium macrorrhizum cultivated in Bulgaria, however, remain limited. The present work aimed to characterize and compare the chemical composition of essential oils and main phenols, in support of future pharmacological evaluation. Methods: Essential oils from aerial parts of both species were obtained by hydrodistillation and analyzed by GC-MS. Through HPLC-UV, ethanol extracts were evaluated to quantify the major phenolic acids and flavonoids. Results: The yield of essential oils was 0.10% for P. radula and 0.03% for G. macrorrhizum, dominated by oxidized monoterpenes, mainly citronellol and geraniol-type compounds. HPLC analysis revealed marked differences in their phenolic profiles. P. radula showed a composition with six phenolic acids—primary protocatechuic and ferulic acids, and very low levels of flavonoids, with rutin being the only quantifiable glycoside. In contrast, G. macrorrhizum contained nine phenolic acids and four flavonoids, with remarkably high levels of salicylic, rosmarinic, and p-coumaric acids, as well as catechins, absent in P. radula. Conclusions: The two species showed different phytochemical characteristics in both their volatile and non-volatile fractions. P. radula is characterized by a citronellol/geraniol-rich essential oil and a moderate phenolic profile, while G. macrorrhizum exhibits significantly higher phenolic diversity and abundance. These findings expand the current phytochemical knowledge of both taxa and provide a solid basis for future chemotaxonomic and pharmacological studies. The obtained results suggest that Geranium macrorrhizum may be more promising for antioxidant and anti-inflammatory applications, while Pelargonium radula may be preferentially explored for ant-microbial purposes. Full article

To support multimedia and deep learning applications running on containers within a server, both processor cores and main memory space are critical resources for performance tuning. With the growing memory demands of applications to maintain intermediate data, installing additional dynamic random-access memory (DRAM) modules increases not only hardware costs but also the static and dynamic energy consumption of a server. In this study, both DRAM and non-volatile memory (NVM) are leveraged to provide short access latency and large main memory capacity for a server running multiple containers with diverse applications. Contention for memory space and processor cores among containers is jointly modeled as part of the performance optimization problem for the hybrid memory system of the server. Our memory and computing resource scheduling algorithms are thus developed to judiciously balance the usage of cores and DRAM space among tasks, while NVM is utilized to increase the degree of parallelism to reduce the Makespan of task batches. Benchmark programs were used to generate the input task set, and experimental results show that our solution outperforms others by achieving at least an 18.34% reduction in Makespan when 100 distinct containerized tasks are executed on a system with 512 gigabytes (GB) of NVM, 32 GB of DRAM, and eight cores. Full article