Search Results (3,234)

Background/Objectives: Manual preparation of semisolid formulations (creams, ointments, gels) is prone to variability in mixing energy and time, which may compromise uniform API distribution. This study aimed to evaluate an Electronic Mortar and Pestle (EMP; Unguator™) as a standardized compounding tool, with objectives to: (i) validate stability-indicating UHPLC methods; (ii) assess content uniformity across jar strata; (iii) quantify the impact of mixing time and rotation speed via design of experiments (DOE); and (iv) verify cleaning effectiveness and cross-contamination risk. Methods: Five representative formulations were compounded: urea 40%, clobetasol 0.05%, diclofenac 2.5% in hyaluronic acid 3% gel, urea 10% + salicylic acid 1%, and hydroquinone 5%. UHPLC methods were validated per ICH Q2(R2) and stress-tested under acid, base, oxidative, thermal, and UV conditions. Homogeneity was assessed by stratified sampling (top/middle/bottom). A 3² factorial DOE (time: 2/6/10 min; speed: 600/1500/2400 rpm) modeled effects on % label claim and RSD. Cleaning validation employed hydroquinone as a tracer, with swab sampling pre-/post-use and post-sanitization analyzed by HPLC. Results: All UHPLC methods met specificity, linearity, precision, accuracy, and sensitivity criteria and were stability-indicating (Rs ≥ 1.5). Formulations achieved 90–110% label claim with strata CV ≤ 5%. DOE revealed speed as the dominant factor for clobetasol, urea, and diclofenac, while time was more influential for salicylic acid; gels exhibited curvature, indicating diminishing returns at high rpm. Model-predicted optima were implementable on the Unguator™ with minor rounding of rpm/time. Cleaning validation confirmed post-sanitization residues below LOQ and <10 ppm acceptance. Conclusions: The Unguator™ provides a practical, parameter-controlled route for compounding pharmacies to standardize semisolid preparations, achieving reproducible layer-to-layer content uniformity within predefined criteria under the evaluated conditions through programmable set-points and validated cycles. DOE-derived rpm–time relationships define an operational design space within the studied ranges and support selection of implementable device settings and set-points. Importantly, the DOE-derived “optima” in this study are optimized for assay-based content uniformity (mean % label claim and strata variability). Cleaning validation supports a closed, low-cross-contamination workflow, facilitating consistent routines for both routine and complex formulations. Overall, the work implements selected QbD elements (QTPP—Quality Target Product Profile; CQA—Critical Quality Attribute definition; CPP—Critical Process Parameter identification; operational design space; and a proposed control strategy) and should be viewed as a step toward broader lifecycle QbD implementation in compounding. Full article

This study proposes an efficient numerical scheme for simulating heat transfer governed by the diffusion equation with moving singular sources. The work addresses two-dimensional problems with line sources and three-dimensional problems with plane sources, which are prevalent in irreversible thermodynamic processes. Developed within a finite difference framework, the method employs a partitioned discretization strategy to accurately resolve the solution singularity near the heat source—a region critical for precise local entropy production analysis. In the immediate vicinity of the source, we analytically derive and incorporate the solution’s “jump” conditions to construct specialized finite difference approximations. Away from the source, standard second-order-accurate schemes are applied. This hybrid approach yields a globally second-order convergent spatial discretization. The resulting sparse system is efficient for large-scale simulation of dissipative systems. The accuracy and efficacy of the proposed method are demonstrated through numerical examples, providing a reliable tool for the detailed study of energy distribution in non-equilibrium thermal processes. Full article

This paper proposes a valorization approach for solid lavender residue, a by-product of the essential oil industry. The biomass residue was carbonized at atmospheric pressure and two temperatures (450 °C and 650 °C), followed by solvothermal modification with zinc ions (Zn²⁺, 3 and 5 mmol). The effects of temperature and Zn²⁺ incorporation on the elemental composition and morphology of the resulting biochar were examined using X-ray Fluorescence (XRF), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy/Energy-Dispersive X-ray Spectroscopy (SEM/EDS) analyses. The applied Zn²⁺ modification was effective at both concentrations for the biochar obtained at both carbonization temperatures. However, a more uniform metal ion distribution was observed at 3 mmol, while at 5 mmol, a partial particle agglomeration occurred. Progressive degradation of the O–H, C=O, and C–O groups with increasing temperature and the presence of Zn–O-related interactions was observed. The results demonstrated consistent and reproducible trends, suggesting that controlled carbonization combined with Zn²⁺ incorporation can convert lavender residues into modified carbonaceous materials. Full article

Organic-rich shale, as a significant alternative energy source, possesses abundant resources. Classified by maturity, it comprises three categories: medium-high maturity shale oil, medium-low maturity shale oil, and oil shale. Medium-high maturity shale oil faces challenges such as tight reservoirs and poor fluidity; medium-low maturity shale oil is characterized by a high proportion of retained hydrocarbons and poor mobility; and oil shale requires high-temperature conversion. Addressing the inherent characteristics of these three resource types, this paper systematically reviews the theoretical foundations and key technologies from two dimensions: “CO₂ injection for medium-high maturity shale oil extraction” and “in situ conversion of medium-low maturity shale/oil shale”. The results indicate that CO₂ injection technology for medium-high maturity shale oil utilizes its supercritical diffusion properties to reduce miscibility pressure by 40–60% compared to conventional reservoirs, efficiently displacing crude oil in nanopores while establishing a geological storage system for greenhouse gases, thereby pioneering an integrated “displacement–drive–storage” model for carbon-reduced oil production. The autothermic pyrolysis in situ conversion process for medium-low maturity shale/oil shale significantly reduces costs by leveraging the oxidation latent heat of kerogen. Under temperature and pressure conditions of 350–450 °C, the shale pore network expansion rate reaches 200–300%, with permeability increasing by two orders of magnitude. Assisted natural gas injection further optimizes the thermal field distribution within the reservoir. Future research should focus on two key directions: synergistic cost reduction and carbon sequestration through CO₂ injection, and the matching of in situ conversion with complex fracture networks. This study delineates key technological pathways for the low-carbon and efficient development of different types of organic-rich shale, contributing to energy security. Full article

Dynamic Habitat Indices (DHIs) are crucial for understanding species richness patterns and provide a powerful tool for large-scale biodiversity conservation research. DHIs summarize three key aspects of vegetation productivity: (a) cumulative annual productivity, (b) minimum productivity, and (c) intra-annual variability. While DHIs have demonstrated potential for predicting richness patterns globally and in tropical regions, their predictive ability across climate zones and using multiple sources of species richness data remains untested. We assess the feasibility of using DHIs to predict the richness of resident birds in China and explore approaches to improve model performance. We used (a) IUCN range maps of terrestrial resident birds in China, and (b) species distribution models (SDMs) to delineate bird richness patterns, classifying species into six habitat guilds: forest, shrubland, grassland, cropland, wetland, and all resident birds. We linked DHIs to richness in each guild and quantified their predictive power using three modeling approaches: linear (GLM) and non-linear models (GAM, Random Forest). We also recorded the relative importance of each DHI component in the models. Our results show that DHIs best predicted cropland bird richness (SDM-based richness, adjusted R² = 0.73), while for IUCN-based guilds, adjusted R² ranged from 0.68 to 0.71. The Random Forest model achieved the highest performance and interpretability. Among DHI components, cumulative DHI consistently played the most dominant role in predicting richness from both SDM and IUCN sources. DHIs effectively capture the link between energy availability and resident bird richness in China, demonstrating considerable potential for biodiversity assessment and conservation planning. Full article

After numerous false starts, the global microalgae industry is re-emerging, driven by its potential to address critical challenges in food and nutrition, sustainable energy, nutraceuticals, cosmetics and pharmaceuticals, and climate change mitigation. Although technical advances in microalgae production show value adding potential, progressing from innovation to product launch and competitiveness is complex. It requires an integrated understanding of technology readiness, regulatory compliance, financial necessities, and market competition. This study presents a novel analytical framework underpinning a data-enabled, evidence-based approach to navigating the innovation pathways to market and beyond. The framework integrates value-add opportunities, identifying key stages faced in pre-competitive (including Technology Readiness Level (TRL), R&D spend, and patent trends), and competitive market stages (including product launches, product claims, market size, market share, growth/maturity, international markets, distribution channels, sectoral profile, and competitive landscape), aligned with regulatory requirements. Although not without limitations, such as incomplete data for emerging products, as well as reliance on secondary sources for product stage determination and market size estimates which can influence the accuracy of TRL classification and market potential estimates. This integration of multiple analyses can help in identifying market opportunities and business competitiveness via product, business, and industry level analyses in the pre-competitive (pre-market launch) and competitive (on market) landscapes. Building on the team’s interdisciplinary experience of developing interactive dashboards for food and beverage industries, and microalga processes, this paper provides an overview of the framework, which was designed to guide businesses and researchers in an emerging microalgae industry through the complex landscape of product development along regulatory and commercial pathways. Full article

Riverbed topography in natural rivers commonly features sand dunes, whose morphological variations can alter the turbulent flow structure near the bed and thereby affect processes of channel scour, deposition, and sediment transport. In this study, a series of flume experiments was conducted using an acoustic Doppler velocimeter (ADV) to simulate fixed bedforms of different dune scales (ratio of wavelength to flow depth, λ/h) in a laboratory flume. Velocity measurements were taken along the water depth at the dune crest and trough for each test case. The near-bed distributions of mean flow velocity, Reynolds stress, turbulent kinetic energy (TKE), and turbulence intensity were obtained at the crest and trough under three flow conditions, allowing analysis of the vertical decay of turbulence intensity at different locations on the dune. The results show that the dune steepness (Ψ, defined as dune height over wavelength) is a key parameter controlling the near-bed flow structure. As Ψ increases, the near-bed velocity gradient, Reynolds stress, TKE, and peak turbulence intensity all increase significantly, with the peak positions shifting closer to the bed. The trough region, due to flow separation and vortex shedding, exhibits substantially higher values of all turbulence-related parameters than the crest, making it the primary zone of energy dissipation and turbulence production. This study provides experimental evidence and theoretical reference for understanding the mechanism by which sand dune morphology influences flow structure, and it offers insight for predicting riverbed evolution. Full article

This study examines the determinants of U.S. CO₂ emissions and provides evidence to inform more effective carbon-reduction policies. Using Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models, the analysis covers January 1997 to February 2022 across four end-use sectors: Residential, Commercial, Industrial, and Transportation. The models capture both long-run equilibria and short-run adjustments between emissions and key drivers, including industrial production, interest rates, climate policy uncertainty (CPU), and energy prices. Results indicate a long-run asymmetric relationship in which economic growth and interest rates differentially affect total emissions, while CPU exerts a significant negative influence only in the transportation sector. Methodologically, the combined ARDL–NARDL approach offers robust evidence of nonlinear and asymmetric effects of macroeconomic and policy variables on emissions. These findings underscore the need to integrate economic and financial conditions into climate policy design and suggest that sector-specific measures—particularly targeting transportation—may substantially improve the effectiveness of carbon-mitigation strategies. Full article

This study presents the design, fabrication, and performance evaluation of a solar dryer capsule cabinet equipped with a parabola reflector, developed to enhance drying efficiency through the reflection of sunlight onto both the upper and lower surfaces of the product. Conventional solar drying exposes only the upper surface, resulting in uneven heating and the need for manual turning. The proposed system integrates a parabolic reflector and IoT-based monitoring sensors (BH1750 light sensor and DHT22 temperature-humidity sensor) to optimize heat distribution and record real-time environmental parameters. Dry experiments were conducted using Citrus hystrix DC. (Makrut lime) peels under natural sunlight from 9:00 a.m. to 5:00 p.m. The moisture loss achieved with the proposed dryer (P-DSD) was 45.66%, compared with 6.79% for direct solar drying (DSD). The drying rate increased from 3.05 g h⁻¹ (DSD) to 20.50 g h⁻¹ (P-DSD), while the specific energy consumption (SEC) decreased from 3519.75 kWh kg⁻¹ to 523.67 kWh kg⁻¹, representing an 85.13% energy reduction. Economic analysis showed a system cost of $1384 and a return on investment of 30.0%. These results demonstrate that the proposed solar dryer capsule cabinet with a parabola reflector offers a low-cost, eco-friendly, and high-efficiency solution for drying agricultural and herbal products, significantly shortening the drying time and improving product quality. Full article

The production of quantum dots (QDs) has increased due to their wide variety of commercial products and applications. QDs can be dangerous in the environment because their small size can encourage their incorporation into living systems. In this project, ZnS and ZnSSe were synthesized under microwave irradiation, generating a water-stable nanomaterial. The bandgap energies calculated using the UV-Vis spectra were 3.81 and 3.86 eV for ZnS and ZnSSe QDs, respectively, indicating that the selenium worked as a dopant agent. The photoluminescence analysis shows narrow emission peaks, confirming a low size distribution, and the selenium doping generated a blue shift. The crystal size of both nanomaterials was around 7 nm. The cellular toxicity of these nanomaterials was evaluated using Chinese Hamster Ovary (CHO) Cells (a standard mammalian cell model). The results suggest that ZnS and ZnSSe QDs slightly affect the viability of CHO Cells, but Zn²⁺ decreases the viability at concentrations higher than 20 mg/L. The content of zinc inside cells (by ICP-OES) suggested that QDs can enter cells more easily than Zn²⁺. Therefore, the decrease in cell viability caused by Zn²⁺ outside the cells is likely due to its effect on cell membrane integrity, suggesting that these nanomaterials are less toxic than bulk materials. Full article

The circular economy offers effective strategies to support the transition from fossil fuels to renewable energy. However, research at the nexus of the circular economy and energy transition remains fragmented across disciplines and lacks a systematic and integrative overview of its intellectual structure and thematic evolution. To address this gap, this study conducts a large-scale bibliometric analysis of 2977 journal articles published between 2008 and 2025 to examine the development, knowledge structure, and global distribution of this field. Performance analysis and scientific mapping are employed to evaluate research output, subject areas, thematic structures, intellectual foundations, journal dissemination, and international collaborations. The results indicate that the circular economy–energy transition nexus is a rapidly growing and multidisciplinary field. It is anchored by conceptual and policy-oriented works and complemented by applied studies on waste management, bioenergy, and decarbonization technologies that directly relate to energy production, conversion, and system efficiency. The geographical distribution shows a multi-pillar but uneven research landscape, with Europe and China emerging as leading contributors, while other regions remain comparatively underrepresented, shaped by regional priorities and collaborative networks. The study highlights emerging research gaps and future directions, offering insights into how circular economy strategies such as resource circularity and waste-to-energy applications can contribute to sustainable and equitable energy transitions and inform future energy-focused research agendas in the context of low-carbon transformation. Full article

With the growing emphasis on holistic management throughout the entire product lifecycle, multi-stage production models that integrate distributed manufacturing, transportation, and assembly processes have gradually attracted research attention. However, studies in this area remain relatively scarce. This paper addresses the fuzzy distributed assembly hybrid flow shop scheduling problem (FDAHFSP), comprehensively considering the entire production flow from manufacturing and transportation to final assembly. A mathematical model is first established with the objectives of minimizing the fuzzy total weighted earliness/tardiness and the fuzzy total energy consumption. To effectively solve this problem, a Q-learning-based adaptive NSGA-II (Q-ANSGA) is proposed. The algorithm incorporates a hybrid strategy combining multiple rules to enhance the quality of the initial population. Additionally, a Q-learning-based adaptive parameter adjustment mechanism is designed to dynamically optimize genetic algorithm parameters, thereby improving the algorithm’s search efficiency and convergence performance. Furthermore, eight neighborhood search operators are developed, and an iterative greedy strategy is integrated to guide the local search process. Finally, comprehensive experiments on 45 test instances are conducted to evaluate the effectiveness of each improvement component and the overall performance of Q-ANSGA. Experimental results demonstrate that the proposed algorithm achieves superior performance in solving the FDAHFSP due to its systematic enhancements. Full article

This study identifies the technological signature of ancient and alternative “Chu” and “Kriab” gold glass mosaic mirrors from Thailand. Although these mirrors play an important role in Thai decorative heritage, their production routes and interfacial chemistry at the lead-to-glass interface have remained unclear. A survey of 154 sites across Thailand shows mosaic glass was widely distributed and likely produced during the Ayutthaya period (~300 years ago). Portable X-Ray Fluorescence (pXRF), Wavelength-Dispersive XRF (WD-XRF), scanning electron microscopy (SEM), and X-ray Photoelectron Spectroscopy (XPS) were used to examine the material properties of observed Chu mirrors. Most samples can be classified as a mixed lead–alkaline glass type, with a PbO content ranging from 4.28 to 48.17 wt%. Their yellow tone is controlled by iron and manganese redox states. Chemical and physical analyses distinguish between Chu from the northern part of Thailand and Kriab from the central part of Thailand, which share a silica source but rely on different fluxes, pointing to different glass workshops. Crucially, XPS depth profiling reveals a well-defined interfacial reaction zone extending to approximately 6 nm in the ancient mirrors, predominantly characterized by disordered, chain-like Pb–O–Pb linkages. These polymeric structures enable a “chemical bridging” mechanism that effectively accommodates interfacial strain arising from thermal expansion mismatch, thereby ensuring exceptional long-term adhesion. Furthermore, the depth-dependent distribution of hydrated lead species and the emergence of photoelectron energy-loss features beyond ~6 nm distinguish the superior metallic integrity of the ancient coatings from the alternative reproductions. This distinct stratification confirms that ancient artisans achieved a sophisticated balance between a chemically bonded interface and a coherent metallic bulk. These findings offer significant insights into the ingenuity of ancient Thai artisans, providing a scientific foundation for the conservation, restoration, and replication of these culturally significant artifacts. Full article

The rapid expansion of new energy vehicles (NEVs) has intensified concerns over power battery safety, making consumer safety preferences an important driver of firms’ innovation and supply chain decisions. From the perspective of structural symmetry and structural asymmetry in supply chains, this study examines how consumer safety preferences shape innovation incentives and supply mode selection in the power battery supply chain. A game-theoretic framework is developed to analyze four representative supply modes characterized by different degrees of decision power and structural asymmetry, including in-house production, sourcing from a dominant supplier, sourcing from a non-dominant supplier, and equity-based cooperation. Stackelberg and Nash game models are employed to derive equilibrium pricing, innovation effort, recycling decisions, and profit allocation outcomes. Numerical simulations further explore the interaction effects between consumer safety preferences and key cost factors. The results show that stronger consumer safety preferences consistently promote battery innovation and enhance overall supply chain profitability, while the distribution of innovation gains depends critically on the underlying supply structure. Supply mode selection exhibits threshold effects as safety preferences increase, and innovation and recycling decisions respond asymmetrically. Moreover, innovation costs significantly moderate the impact of safety preferences on innovation effort, with the strength of this interaction varying across symmetric and asymmetric supply modes. These findings highlight the role of structural asymmetry in shaping innovation incentives and provide insights for firms and policymakers seeking to design effective supply chain governance mechanisms under rising safety concerns. Full article

Ecolabelling has emerged as a key instrument to communicate environmental performance to consumers, particularly in the agri-food sector where resource use and ecological pressures are highly interlinked. Conventional Life Cycle Assessment (LCA)-based ecolabels often suffer from methodological discretion, lack of territorial specificity, and limited consumer trust. This study investigates how the Water–Energy–Food–Ecosystem (WEFE) Nexus could be integrated into LCA-based ecolabelling, with a specific focus on pasta production as a representative case in the food industry. Indicators were collected from recent literature on LCA and Nexus applications, selected for simplicity and clear attribution to one WEFE dimension, and then evaluated by experts from COST Action CA20138 (NexusNet) through a two round Delphi protocol. The process yielded 23 indicators distributed across the four dimensions, which were subsequently compared with six Environmental Product Declarations to assess data availability and compatibility. The results suggest that many indicators can be computed with standard LCA inventories, while the Nexus perspective adds value by capturing multidimensional impacts and regional resource pressures. Further refinement and empirical testing are expected to enhance the framework’s applicability, but the findings already indicate that incorporating WEFE-based indicators into pasta ecolabelling could represent a promising pathway to improve analytical depth and consumer relevance, aligning circular economy principles with corporate assessment practices. Full article