Search Results (1,566)

Plastic recycling has been a challenge worldwide due to various reasons, including limited profit margins, the demand for high-quality plastic reprocessing techniques to make products comparable to those from virgin materials, and challenges in sorting and processing. This problem became particularly urgent in the small towns in the U.S., where plastic waste was shipped overseas for treatment, but now it is not accepted in some countries. This study aims to understand the plastic value chain and find the necessary factors for a circular economy model of both environmental and economic settings. In this study, an educational plastics reprocessing workspace was developed with manufacturing processes such as shredding, filament extruding, 3D printing, and injection molding. A series of products was developed to increase the value of the recycled polymers. In addition, quality control of recycled polymers such as polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), polyethylene terephthalate (PET), and polyethylene terephthalate glycol (PETG) was examined. By collaborating with a university manufacturing lab, this work illustrates how plastics can be collected, prepared, and reprocessed, serving as a platform for student learning and community outreach. This study contributes to the body of knowledge by presenting a case-based educational model for community-level plastic recycling and reprocessing in a college town context. Full article

The inferior visual sensory attributes, particularly colour, of plant-based burgers, remain a barrier to enhancing consumer acceptance and uptake in the global market. This study aimed to comprehensively profile the colour transition dynamics at varying internal temperatures (uncooked, 35 °C, 55 °C, 75 °C, and 85 °C) of four distinct commercial plant-based (PB) and six animal-based (AB) burgers, and to identify key “colour gaps” for improvement. Raw beef burgers appeared red with higher positive a* values (redness), whereas v2food, vEEF, and Beyond burgers showed comparatively higher b* (yellowness) and c* (chroma) values both externally and internally. The sample Impossible PB burgers had the lowest colour differences (∆a*, ∆b*, ∆c*, and ∆E*), showing a beef-like colour transition in both raw and cooked states. Chicken and pork+beef burgers exhibited lower redness in the processed visual images attributed to higher L* values owing to lower myoglobin content. In AB burgers, a* was negatively correlated with L* and h°, while PB burgers positively correlated with b* and c*. The browning intensity observed in both AB and PB burgers is influenced by their internal structural characteristics, which respond dynamically to changes in internal temperature. Mapping the colour transition during the cooking of AB and PB burgers is a critical first step toward identifying gaps in PB product development. Enhancement of visual sensory attributes can be achieved through the modelling of suitable natural colour combinations to target specific dimensions in the colour space. Full article

The increasing demand for monoclonal antibody (mAb) therapeutics has intensified the need for more efficient and consistent biomanufacturing processes. We present a data-driven, machine-learning (ML) approach to exploring and predicting upstream yield behavior. Drawing on industrial-scale batch records for a single mAb product from a contract development and manufacturing organization, we applied regression models to identify key process parameters and estimate production outcomes. Random forest regression, gradient boosting machine, and support vector regression (SVR) were evaluated to predict three yield indicators: bioreactor final weight (BFW), harvest titer (HT), and packed cell volume (PCV). SVR outperformed other models for BFW prediction (R² = 0.978), while HT and PCV were difficult to model accurately with the available data. Exploratory analysis using sequential least-squares programming suggested parameter combinations associated with improved yield estimates relative to historical data. Sensitivity analysis highlighted the most influential process parameters. While the findings demonstrate the potential of ML for predictive, data-driven yield improvement, the results should be interpreted as an exploratory proof of concept rather than a fully validated optimization framework. This study highlights the need to incorporate process constraints and control logic, along with interpretable or hybrid modeling frameworks, to enable practical deployment in regulated biomanufacturing environments. Full article

This work proposes using acoustic emission during a static tensile test to determine the stress characteristics of the initial phase of the destruction process of elements printed using the material extrusion (MEX) additive method at various printing parameters. The changed parameters were layer height, print orientation, filling ratio, and nozzle temperature. ABS material was chosen for printing. The experiment was carried out according to the Taguchi plan. The analysis of the results showed that changes in printing parameters significantly impact the mechanical properties of the tested elements. The parameter that had the greatest impact on strength was the filling ratio. Maximum tensile strength was achieved with the following printing parameters: 0.24 mm layer, 30°, 100% infill, 275 °C, concentric pattern. The results can be the basis for optimizing the additive printing process and improving the efficiency and reliability of manufactured components. The results of recorded acoustic emissions during strength tests allow the identification of stresses characteristic of the initial phase of the destruction process of the tested material. This phase is the elastic-visco-plastic transition, and the use of the AE method enables its detection 2–5 s earlier than the static tensile test. This allows us to determine the safe range of stresses when using the mentioned materials, which is particularly helpful in designing structures or spare parts. The test results showed that the critical stress for the investigated components is approximately 6 MPa, and exceeding this value is associated with the risk of unsafe operation. Full article

Sarcomyxa edulis is a characteristic edible and medicinal mushroom found in Northeast China that is highly valued by consumers for its tender texture, pleasant flavor, and high nutritional value. To gain a deeper understanding of the molecular mechanisms underlying the development of S. edulis fruiting bodies, this study utilized the Illumina NovaSeq platform to perform transcriptome sequencing at three growth and development stages of S. edulis strain SE8, namely primordia (SE8–P), fruiting body differentiation (SE8–F), and mature fruiting body (SE8–M). A total of 54.67 Gb of clean data was obtained, with a GC content of around 51%. After assembly, 36,423 Unigenes were obtained. Functional annotation was performed on the Unigenes, resulting in 21,206 Unigene annotation results. Differential expression gene analysis showed that 79,606 and 523 DEGs were annotated in at least one database during the SE8–P vs. SE8–F, SE8–F vs. SE8–M, and SE8–P vs. SE8–M processes, respectively. Among these, the genes encoding aldehyde dehydrogenase and fungal hydrophobins were consistently downregulated, playing a negative regulatory role in the growth and development of S. edulis. The genes encoding glycoside hydrolase and AB hydrolase superfamily proteins were consistently upregulated, playing a positive regulatory role in growth and development. Among these, the genes encoding aldehyde dehydrogenase were annotated to the Tryptophan metabolism (ko00380) pathway through KEGG, suggesting that aldehyde dehydrogenase regulates indoacetate formation in the fruiting body of S. edulis. The accuracy of RNA–Seq and DEG analysis was validated using quantitative PCR. This study enriches our knowledge of the genetic information and provides a theoretical basis for the molecular mechanisms of fruiting body development of S. edulis. Full article

Interest in research on FDM systems using inexpensive materials like PLA and ABS is constantly increasing. In this regard, the scope of this study is narrowed to exclusively focus on PLA. To improve the surface finish of PLA printed products, it is important to have optimal values of the most important process parameters, notably layer height, temperature, and printing speed. The surface roughness is a critical aspect of additive manufacturing that directly impacts the functionality, aesthetics, and overall performance of printed parts. To accomplish the improvement of surface quality, the statistical method ANOVA (Analysis of Variance) is used to analyze data and identify the most relevant process parameters that impact roughness and dimensional precision. The response variables are identified during this study in order to define the optimal printing parameters for improving part quality and ensuring the best surface finishes. Additionally, the dimensional accuracy of the parts is analyzed in order to check the reliability and effectiveness of the optimum parameters. The results are validated through this additional assessment, which also provides insight into the capabilities and limitations of inexpensive FDM machines when the optimized parameters are used. In conclusion, this study emphasizes the significance of enhancing parameters to improve the performance of 3D printed components, providing insightful information about the potential of PLA as an inexpensive material for applications that need both high surface quality and precise dimensional control. According to the analysis, the thickness of the layers and printing speed have a significant role in the roughness for a better desired surface quality. Full article

The design and development of a robust and consistent manufacturing process for monoclonal antibodies (mAbs), augmented by advanced process analytics capabilities, is a key current focus area in the pharmaceutical industry. In this work, we describe the development and operationalization of multivariate statistical process monitoring (MSPM), a data-driven modelling approach, to monitor biopharmaceutical manufacturing processes. This approach helps in understanding the correlations between the various variables and is used for the detection of the deviations and anomalies that may indicate abnormalities or changes in the process compared to the historical dataspace. Therefore, MSPM enables early fault detection with a scope for preventative intervention and corrective actions. In this work, we will additionally cover the value of in silico data in the development of MSPM models, principal component analysis (PCA), and batch modelling methods, as well as refining and validating the models in real time. Full article

Background/Objectives: Achyranthes bidentata (AB), recognized as a food and traditional Chinese medicine, exhibits notable biological activity. Our previous study showed the hypoglycemic effect of Achyrantha bidentata polysaccharide (ABP). The properties and digestion process of polysaccharides affect their pharmacological activities. The digestion characteristics of ABP are unclear. In this study, we aimed to explore the characteristics of ABP’s simulated digestion and its prebiotic properties and hypoglycemic effects. Methods: We used simulated digestion methods to investigate the alterations in ABP levels in the process of digestion and fermentation. Animal experiments were used to compare the effects of the prebiotic properties of ABP on normal control (NC) and type 2 diabetes mellitus (T2DM) mice. Then, in order to further verify the hypoglycemic effect of ABP after fermentation (ABPF), α-glucosidase activity and glucose uptake in Caco-2 cells were examined. Results: The results showed that ABP was anti-digestive and mainly degraded by the intestinal flora. Moreover, ABP showed a stronger promoting advantage against beneficial bacteria and inhibited harmful bacteria in the T2DM mice. Compared with NC mice, after ABP treatment, T2DM mice showed a higher increase in levels of short-chain fatty acids (SCFAs). Additionally, the glucose uptake and α-glucosidase activity of Caco-2 cells were significantly decreased after treatment with ABPF. Conclusions: These results underscore the potential of ABP as a prebiotic candidate for gut health promotion and T2DM alleviation. Full article

Ammonia borane (AB) is recognized as a highly promising material for hydrogen storage owing to its exceptional safety and high hydrogen density, enabling controllable hydrogen release at room temperature through catalytic hydrolysis. The development of efficient catalysts to accelerate this process remains a critical research challenge. In this work, carbon nanotube (CNT)-supported Co-MoO₃ nanoparticles were synthesized through reduction with sodium borohydride. The catalyst with a Co/MoO₃ molar ratio of 1.0:0.1 (denoted as Co₁Mo_0.1/CNTs) showed optimal performance in AB hydrolysis, with a turnover frequency (TOF) of 19.15 mol_H2 mol_cat⁻¹ min⁻¹ and an activation energy (E_a) of 26.41 kJ mol⁻¹. The superior performance of the Co₁Mo_0.1/CNTs catalyst can be ascribed to the efficient proton-transfer promotion by carboxylated carbon nanotubes and the synergistic catalytic effect between Co and Mo in the system. This study offers a viable pathway for constructing high-efficiency noble metal-free catalysts for hydrogen production from AB hydrolysis. Full article

Leaf senescence is a precisely regulated developmental process that is critical for grapevine growth and yield, which is easily influenced by environmental factors. High temperature is a major factor that accelerates senescence rapidly, adversely affects photosynthetic performance, severely hindering fruit nutrient metabolism and growth. This study investigated chlorophyll fluorescence and physiological traits in grape (Vitis vinifera L.) leaves at different senescence stages under natural high-temperature conditions in Turpan. Measurements included chlorophyll content, MDA levels, antioxidant enzyme activities, and chlorophyll fluorescence parameters. The results showed that (1) young leaves exhibited higher and more sustained chlorophyll content but were prone to wilting, whereas older leaves showed accelerated chlorosis and functional decline; (2) high temperature severely impaired PSII function, inhibiting electron transport and photochemical efficiency, reflected in increased ABS/RC, TR_o/RCC, and DI_o/RC, and decreased F_v/F_m, F_v/F_o, and PI_abs; (3) POD, SOD, CAT and MDA levels initially increased then decreased, correlating with photosynthetic changes and leaf age; and (4) young leaves maintained stronger photosynthetic capability and physiological resilience than older ones. Although partial recovery occurred after temperature reduction, photosynthetic and antioxidant activities did not fully revert. This suggests persistent heat-induced functional decline and accelerated senescence, providing insights for understanding heat-induced leaf senescence and developing strategies for cultivating grapevines. Full article

Herein, we propose an ultrasensitive electrochemical immunosensor based on glucose oxidase labeling and enzyme-catalyzed Au staining. In brief, the primary antibody (Ab₁), bovine serum albumin, an antigen and then a bionanocomposite that contains a second antibody (Ab₂), poly(3-anilineboronic acid) (PABA), Au nanoparticles (AuNPs) and glucose oxidase (GOx) are modified on a glassy carbon electrode coated with multiwalled carbon nanotubes, yielding a corresponding sandwich-type immunoelectrode. In the presence of glucose, a chemical reduction of NaAuCl₄ by enzymatically generated H₂O₂ can precipitate a lot of gold on the Ab₂-PABA-AuNPs-GOx immobilized immunoelectrode. In situ anodic stripping voltammetry (ASV) detection of gold in 8 μL 1.0 M aqueous HBr-Br₂ is conducted for the antigen assay, and the ASV detection process takes approximately 6 min. This method is employed for the assay of human immunoglobulin G (IgG) and human carbohydrate antigen 125 (CA125), which demonstrates exceptional sensitivity, high selectivity and fewer required reagents/samples. The achieved limits of detection (S/N = 3) by the method are 0.25 fg mL⁻¹ for IgG (approximately equivalent to containing 1 IgG molecule in the 1 microlitre of the analytical solution) and 0.1 nU mL⁻¹ for CA125, which outperforms many previously reported results. Full article

We theoretically investigate the supercurrent and superconducting diode effect (SDE) in an Aharonov–Bohm (AB) interferometer sandwiched between two aluminium-based superconducting leads. The interferometer features a quantum dot (QD), which is created in an indium arsenide (InAs) semiconductor nanowire by local electrostatic gating, inserted in one of its arms and a magnetic flux threading through the ring structure. The magnetic flux breaks the system time-reversal symmetry by modulating the quantum phase difference between electronic transport through the QD path and the direct arm, which enhances constructive interference in one direction and destructive interference in the other. This leads to a discrepancy between the magnitudes of the forward and reverse critical supercurrents and is the core mechanism that induces the SDE. We demonstrate that the critical supercurrents exhibit Fano line shapes arising from the interference between discrete Andreev bound states in the QD and continuous states in the direct arm. It is found that when electron transport is dominated by the QD-containing path as compared to the direct arm path of the interferometer, the diode efficiency reaches a maximum, with values as high as 80%. In contrast, when the direct arm path dominates transport, the diode efficiency becomes weak. This attenuation is attributed to the participation of higher-order quantum interference processes, which disrupt the nonreciprocal supercurrent balance. Importantly, the proposed AB interferometer system has a relatively simple structure, and the realization of the SDE within it is feasible using current nano-fabrication technologies. Full article

Michelia ‘Xin’ is an evergreen rare ornamental tree species that undergoes FBD only once but blooms twice a year. However, the molecular mechanisms controlling its FBD process remain largely unknown. This study characterized the FBD process and delved into the key molecular regulatory mechanisms through transcriptomic and metabolomic analyses of developing flower buds. FBD in Michelia ‘Xin’ was characterized into five stages, including vegetative (T1), floral meristem transition (T2), tepal primordia differentiation (T3), stamen primordia differentiation (T4), and pistil primordia differentiation (T5). Analyses revealed a stage-specific metabolic and transcriptional regulation of FBD, with increasing numbers of differential metabolites and a decreasing number of DEGs from T1 to T5. Most phytohormone and transcription factor-related DEGs were highly induced from T2. The down-regulation of dormancy-associated protein homologs and CONSTANS-LIKE proteins associated with significant induction of flowering-promoting factor, CLAVATA3, trichome birefringence-like, and GRAVITROPIC IN THE LIGHT proteins was essential for the induction and reproductive organs’ development. Porphyrin biosynthesis, chlorophyll a-b binding proteins, DNA replication, flavonoid biosynthesis, and starch and sucrose metabolism were also significantly induced from T2. Key pivotal candidate genes were screened out. Our results provide fundamental resources for dissecting the molecular network regulating FBD and molecular-assisted flowering control in Michelia ‘Xin’. Full article

Background/Objectives: Biofilms are key in spreading antibiotic resistance in various ecosystems. This study employed comparative genomics to examine the resistance and adaptability mechanisms of the Vibrio parahaemolyticus strain Vaw-5, isolated from a seafood market biofilm. Methods: A comparative examination of Vaw-5 and 32 publicly available V. parahaemolyticus genomes identified a distinct set of genetic resistance characteristics. Results: Unlike clinical strains, Vaw-5 lacks acquired antimicrobial resistance genes like the blaCARB and qnr variations. Instead, its resistance potential is based on chromosomal alterations, efflux pump systems (vmeAB, vcmD), and a unique repertoire of 16 strain-specific transposons, including Tn5501 and Tn5393, which are well-known vectors for antibiotic resistance gene (ARG) mobilization. Although not multidrug-resistant, Vaw-5 possesses unique genomic islands that share negligible homology with those of clinical strains, enriched with gene clusters for environmental adaptation, such as exopolysaccharide production and a fully functional Type VI Secretion System. Vaw-5 carries a distinctive plasmid with the resistance gene aac(2${}^{\prime }$)-Ia. Conclusions: Biofilm adaptation promotes structural integrity, inherent processes, and resistance above standard ARG acquisition. This study focuses on how biofilm communities in the food chain can operate as covert incubators for mobilizable resistance determinants, emphasizing the significance of ecological monitoring within a One Health paradigm to reduce possible public health hazards. Full article

This study evaluates the environmental impacts of shipbuilding materials through life cycle assessment (LCA) and assesses potential exposure under the EU Carbon Border Adjustment Mechanism (CBAM). Three representative vessel types, a pure car and truck carrier (PCTC), a bulk carrier, and a container ship, were analyzed across scenarios reflecting different steelmaking routes, recycling rates, and regional energy mixes. Results show that structural steel (AH36, EH36, DH36, A/B grades) overwhelmingly dominates embedded emissions, while aluminium and copper contribute secondarily but with high sensitivity to recycling and energy pathways. Coatings, polymers, and yard processes add smaller but non-negligible effects. Scenario-based CBAM cost estimates for 2026–2030 indicate rising liabilities, with container vessels facing the highest exposure, followed by bulk carriers and PCTCs. The findings highlight the strategic importance of steel sourcing, recycling strategies, and verifiable supply chain data for reducing embedded emissions and mitigating financial risks. While operational emissions still dominate the life cycle, the relative importance of construction-phase emissions will grow as shipping decarbonizes. Current EU-level discussions on extending CBAM to maritime services, together with recognition of domestic carbon pricing as a potential pathway to reduce liabilities, underscore regulatory uncertainty and emphasize the need for harmonized methods, transparent datasets, and digital integration to support decarbonization. Full article