Search Results (124)

The 27-day oscillation in total electron content (TEC) is analysed by means of world maps of TEC. The TEC maps are derived from measurements of the ground receiver network of the Global Navigation Satellite System (GNSS) and are provided by the International GNSS Service (IGS). The observed 27-day oscillation in TEC is mainly due to the 27-day solar rotation period, which induces a 27-day oscillation in extreme ultraviolet radiation (EUV) of the Sun. Analysing the time interval from 2003 to 2020, cross-correlation of the 27-day oscillation of the solar MgII-index of the Solar Radiation and Climate Experiment (SORCE) and the 27-day oscillation in TEC shows an average time delay of about 1.1 days for the ionospheric response with respect to the solar EUV variation. The average correlation coefficient of the solar and the ionospheric variation is 0.85. The cross-correlation of the 27-day oscillation in solar radio flux F10.7 and the 27-day oscillation in TEC gives a time lag of about 1.3 days and an average correlation coefficient of 0.78. The world maps of the amplitude of the 27-day oscillation in TEC are discussed for the TEC data from 1998 to 2024. Finally, TEC composites are derived for F10.7 enhancement events and geomagnetic storms. Full article

Coffee is among the trendy beverages; however, roasting coffee beans generates by-products such as coffee silver skin (CS). Although CS is rich in phenolic compounds with potential health benefits, there are limited reports on applying advanced optimization approaches combined with emerging food processing technologies for sustainable valorization of CS. This study aims to optimize the ultrasound extraction process of Taiwanese CS using the L₉ (3⁴) orthogonal Taguchi method, aiming at maximizing total phenolic content (TPC) while assessing total and specific energy consumption (TEC and SEC). The antioxidant activity of the extracts was also evaluated in relation to processing variables. Besides, variations in the extracts’ CIE color values and total soluble solids were assessed. Independent parameters were extraction time, sonication amplitude, ethanol concentration, and temperature. According to the results, optimized conditions (1 min, 50% amplitude, 80% ethanol, and 25 °C) yielded a TPC value of 7.45 mg GAE/g CS, with the lowest SEC of 0.0067 kWh/mg GAE/g. Antioxidant analysis showed a range of 0.634–1.283 mg/mL for 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability, indicating Taguchi’s effectiveness in improving antioxidant activity. In addition, process optimization reduced TEC and SEC by 23.8 and 41.8%, respectively, contributing to green extraction and sustainable food production in line with sustainable development goals. It was found that selecting optimal parameters is crucial for maximizing the extraction of phenolic and enhancing antioxidant properties, while minimizing energy use. Future chemistry-focused studies can explore the interactions between individual phenolic compounds in CS extracts to further support the optimization of multi-parameter process design. Full article

Production scheduling that involves distributed factories, machine maintenance, and resource constraints plays a crucial role in manufacturing. However, these realistic constraints have rarely been considered simultaneously in the hybrid flow shop (HFS). To address this issue, a distributed resource-constrained hybrid flow shop scheduling problem with machine breakdowns (DRCHFSP-MB) is studied. There are two optimization objectives, i.e., makespan and total energy consumption (TEC). To solve the strongly NP-hard problem, a mathematical model is established and a block–neighborhood-based multi-objective evolutionary algorithm (BNMOEA) is developed. In the proposed algorithm, an efficient hybrid initialization method is adopted to obtain high-quality individuals to participate in the evolutionary process of the population. Next, to enhance the search capability of the BNMOEA, three well-designed crossover operators are used in the global search. Then, the convergence of the proposed algorithm is improved by utilizing eight critical factory-based local search operators combined with block–neighborhood. Finally, the BNMOEA is compared with several of the most advanced multi-objective algorithms; the results indicate that the BNMOEA has an outstanding performance in solving DRCHFSP-MB. Full article

The growing demand for sustainable food packaging has driven the development of active packaging systems using biopolymers like poly(lactic acid) (PLA) and natural antimicrobials. This study focuses on creating novel nanohybrids by loading carvacrol (CV) and trans-cinnamaldehyde (tCN) onto ZnO nanorods for incorporation into PLA/triethyl citrate (TEC) films. The CV@ZnO and tCN@ZnO nanohybrids were synthesized and characterized using XRD, FTIR, desorption kinetics, and by assessing their antioxidant and antibacterial properties. These nanohybrids were then integrated into PLA/TEC films via extrusion. The resulting active films were evaluated for their physicochemical, mechanical, barrier, antioxidant, and antibacterial properties. The tCN@ZnO nanohybrid exhibited a stronger interaction with the ZnO surface and a slower release rate compared to CV@ZnO. While this strong interaction limited its direct antioxidant activity, it proved highly beneficial for the final film’s performance. Films containing 10% tCN@ZnO demonstrated the strongest antibacterial efficacy in vitro against Listeria monocytogenes and Escherichia coli and functioned as potent mechanical reinforcement fillers. Crucially, in a practical application, the PLA/TEC/10tCN@ZnO film significantly extended the shelf-life of fresh minced pork during 6 days of refrigerated storage. It effectively suppressed microbial growth (TVC), delayed lipid oxidation (lower TBARS values), and preserved the meat’s colour and nutritional quality (higher heme iron content) compared to control packaging. The developed tCN@ZnO nanohybrid is confirmed to be a highly effective active agent for creating PLA/TEC-based packaging that can enhance the preservation of perishable foods. Full article

Interlocking Compressed Earth Blocks (ICEBs) offer a sustainable alternative to conventional fired-clay bricks but remain hindered by inconsistent geometric designs and limited standardization. This study develops a stakeholder-weighted Analytic Hierarchy Process (AHP) framework to evaluate and select the most suitable ICEB geometry for sustainable and seismic-ready construction in developing regions. Five evaluation criteria—size, weight, interlocking effectiveness, reinforcement/grout provision, and handling ergonomics—were prioritized based on expert input from masons, engineers, architects, and researchers. The synthesized results ranked the HiLo-Tec-type geometry highest, followed by Thai-Rhino, Auram, and Hydraform designs. Unit weight (0.289) and reinforcement capacity (0.261) emerged as dominant decision factors. Sensitivity analysis confirmed the robustness of rankings under varying weight perturbations. The AHP framework identifies the top-ranked geometry, whose structural performance was examined experimentally through a full-scale cyclic test on a grouted double-wythe ICEB wall, revealing enhanced ductility and residual strength compared with traditional brick masonry. The proposed framework demonstrates that selected ICEB geometry can balance ergonomic and structural performance while meeting seismic resilience demands. Beyond geometry selection, the model provides a replicable decision-support tool adaptable for regional material innovations in sustainable construction. Full article

We present a high-speed, miniaturized, Peltier-driven thermocycler for Polymerase Chain Reaction (PCR) with heating rates of 22.25 °C/s and cooling rates of 5.30 °C/s, using a standard aluminum block (a four-well section of a 96-well plate) and laterally arranged micro-thermoelectric coolers (TECs) to induce predominantly horizontal heat flow. Simulations without copper preheating predict a cooling rate of 5.70 °C/s. Finite-element thermoelectric modeling (COMSOL 6.2) closely matches measurements. The selection of materials is guided by the introduction of the merit number G_β that balances thermal diffusivity and volumetric heat capacity, enabling consistent comparison across candidate block materials. The performance of this system is evaluated against data reported in scientific literature, encompassing both recent academic developments and selected commercial systems that employ silver components to enhance thermal conductivity. Despite aluminum’s lower thermal conductivity, our device achieves superior thermal cycling rates, demonstrating that with innovative design, less expensive materials can compete with higher-performing ones. This work includes detailed numerical simulations, comparative analyses of block materials, design considerations, fabrication methods, and experimental validation. By integrating insights from current scientific research, this study contributes to the advancement of accessible and high-performance diagnostic technologies. Full article

Afforestation plays a vital role in reshaping land systems and enhancing carbon sequestration, particularly in ecologically fragile regions. However, the carbon implications and spatial dynamics of large-scale planted-forest (PF) expansion in the Yellow River Basin (YRB) remain insufficiently understood. Focusing on the YRB, this study integrates multi-source land-use, forest type, and carbon datasets to evaluate land-use transitions (2000–2020) and quantify changes in total ecosystem carbon (TEC), aboveground carbon (AGC), and PF-derived AGC (PF-AGC) from 2005 to 2020 under the IPCC-based accounting framework. The results show cumulative land-use conversion of 118,481 km², with forest land expanded to 11.89% of the basin, mainly due to afforestation efforts in the middle reaches. TEC followed a rise–decline–rebound trajectory, yielding a net gain of 1.96 × 10⁸ t, while AGC increased by 4.37 × 10⁸ t. With the expansion of PF, PF-AGC contributed 1.60 × 10⁸ t (36.61% of AGC gains), primarily sourced from grassland (40.51%), natural forests (35.15%), and cropland (23.56%). PFs were dominated by young stands (≤40 years), spatially clustered in the middle–lower reaches, and exhibited higher carbon sink potential than natural forests. Spatially, AGC and PF distributions underwent staged reconfiguration. Standard deviational ellipse and centroid analyses revealed eastward shifts and axis changes in AGC, and southwestward migration of PFs, indicating PF expansion as a major driver of carbon redistribution. These findings clarify the forest age–land-use–carbon nexus and highlight the spatial impact of afforestation, offering critical insights for region-specific low-carbon strategies and sustainable land governance in the YRB. Full article

This paper proposes a convolutional Long Short-Term Memory (ConvLSTM) network integrated with multi-channel features dedicated to ionospheric total electron content (TEC) forecasting. To improve generalization, solar, and geomagnetic activity indices are added as auxiliary channel inputs. The model is built upon an Encoder–Decoder (ED) architecture enhanced with residual connections and convolutional channel projection, which collectively improve the synergy among its core components. Based on this framework, we developed ED-ConvLSTM-Res, a multi-channel feature-based global ionospheric TEC prediction model. Comprehensive accuracy evaluation and comparative tests were carried out using datasets from the solar minimum year of 2019 and the current solar maximum year of 2024. The results indicate that the proposed model consistently achieves strong predictive performance compared with other models, along with a significantly enhanced feature representation capability. Specifically, the Root Mean Square Errors (RMSE) of the ED-ConvLSTM-Res model’s predictions in 2019 and 2024 are 1.28 TECU and 5.28 TECU, respectively, while the corresponding Mean Absolute Errors (MAE) are 0.87 and 3.87, and the coefficients of determination (R²) are 0.95 and 0.94. In the current high solar activity year 2024, the proposed model achieves error reductions of 13.6% in MAE and 11.6% in RMSE compared with the Center for Orbit Determination in Europe (CODE)’s one-day-ahead forecast product, c1pg. These results confirm that the proposed model not only outperforms the ConvLSTM model without additional indices and c1pg but also exhibits strong generalization capability, maintaining stable performance with low errors under both high and low solar activity conditions. Full article

Geomagnetic storms can severely disturb the ionosphere, degrading Global Navigation Satellite System (GNSS) performance, particularly at low latitudes. The 10 May 2024 superstorm produced a strong ionospheric response across Mexico, with well-defined positive and negative phases observed at all analyzed stations. The proximity in time of %dTEC peaks to the second and third steps of the storm’s main phase, together with their local time dependence, indicates that Prompt Penetration Electric Fields (PPEFs) dominated the initial positive phase on the dayside. These eastward electric fields uplifted the F-region plasma, enhancing TEC values—especially at northern stations, where increases reached ±180%. In contrast, the subsequent nighttime depletion and extended recovery were mainly driven by composition-related plasma loss and enhanced recombination. A suppression of TEC followed the positive phase, with depletions between −58% and −77%, showing a persistent latitudinal gradient. Low-cost GNSS receivers successfully captured these ionospheric signatures but exhibited higher positioning degradation—up to 50% greater than geodetic-grade receivers. Multi-constellation Precise Point Positioning (PPP) mitigated these effects, reducing 3D errors by up to 23% and 53% in geodetic and low-cost receivers, respectively. These findings reveal the day–night dependence of ionospheric storm phases and underscore the importance of regional multi-GNSS monitoring during extreme space weather. Full article

In this study, we explore the potential of applying machine learning (ML) to enhance high-pressure luminescence sensing. We investigate the luminescence behavior of Y₂MoO₆:Eu³⁺, synthesized via a self-initiated, self-sustained reaction. Emission spectra were collected under varying pressures using a 405 nm laser diode and an AVANTES AvaSpec 2048TEC USB2 spectrometer. An analysis of the pressure-dependent curve, based on the intensities of two key peaks, indicates a possible crystal phase transition or another underlying physical phenomenon. Moreover, the non-unique relationship between pressure and peak intensity limits its effectiveness for precise sensing. To overcome this challenge, we employ an ML-based approach, combining Uniform Manifold Approximation and Projection (UMAP) for data visualization with a deep neural network to estimate pressure directly from the full luminescence spectrum. This strategy significantly extends the usable pressure range of Y₂MoO₆:Eu³⁺ up to 12 GPa, representing a marked improvement over conventional methods. Full article

Big L days are days when the lunar semidiurnal variation M₂ in the ionosphere is strongly enhanced by a factor of 2 or more. The worldwide network of ground-based receivers for the Global Navigation Satellite System (GNSS) has monitored the ionospheric total electron content (TEC) since 1998. The derived world maps of TEC are provided by the International GNSS Service (IGS) and allow the study of the characteristics of big L days in TEC. In the data analysis, the signal of the lunar semidiurnal variation M₂ in TEC is separated from the solar semidiurnal variation S₂ by means of windowing in the spectral domain. The time series of the M₂ amplitude often shows enhancements of M₂ (big L days) a few days after sudden stratospheric warmings (SSWs). The M₂ amplitude can reach values of 8 TECU. The M₂ composite of all SSWs from 1998 to 2024 shows that the M₂ amplitude is enhanced after the central date of the SSW. Regions in Southern China and South America show stronger effects of big L days. Generally, the effects of big L days on TEC show latitudinal and longitudinal dependencies. Full article

The Denoising Wavelet Transform Convolutional Long Short-Term Memory Network (DWTConvLSTM) is a novel ionospheric total electron content (TEC) spatiotemporal prediction model proposed in 2025 that can simultaneously consider high-frequency and low-frequency features while suppressing noise. However, it also has flaws as it only considers unidirectional temporal features in spatiotemporal prediction. To address this issue, this paper adopts a bidirectional structure and designs a bidirectional DWTConvLSTM model that can simultaneously extract bidirectional spatiotemporal features from TEC maps. Furthermore, we integrate a lightweight attention mechanism called Convolutional Additive Self-Attention (CASA) to enhance important features and attenuate unimportant ones. The final model was named CASA-BiDWTConvLSTM. We validated the effectiveness of each improvement through ablation experiments. Then, a comprehensive comparison was performed on the 11-year Global Ionospheric Maps (GIMs) dataset, involving the proposed CASA-BiDWTConvLSTM model and several other state-of-the-art models such as C1PG, ConvGRU, ConvLSTM, and PredRNN. In this experiment, the dataset was partitioned into 7 years for training, 2 years for validation, and the final 2 years for testing. The experimental results indicate that the RMSE of CASA-BiDWTConvLSTM is lower than those of C1PG, ConvGRU, ConvLSTM, and PredRNN. Specifically, the decreases in RMSE during high solar activity years are 24.84%, 16.57%, 13.50%, and 10.29%, respectively, while the decreases during low solar activity years are 26.11%, 16.83%, 11.68%, and 7.04%, respectively. In addition, this article also verified the effectiveness of CASA-BiDWTConvLSTM from spatial and temporal perspectives, as well as on four geomagnetic storms. Full article

Accurate temperature regulation is essential in microfluidic apparatus, particularly for procedures such as polymerase chain reaction (PCR), cellular analysis, and chemical reactions that rely on stable thermal conditions. However, achieving temperature uniformity at the microscale remains challenging due to rapid heat dissipation, small thermal mass, and intricate flow–heat interactions. This work reviews contemporary methodologies to enhance thermal control in microfluidic systems, including proportional–integral–derivative (PID) and fuzzy PID controllers, liquid metal-based sensing, thermoelectric cooling (TECs), and evaporation or integrated heating elements for precise thermal output management. Emerging fabrication technologies, such as additive manufacturing, enable the direct integration of heating elements and sensors within microchips, improving thermal efficiency and device compactness. Advanced materials, including carbon nanotubes infused with gallium and temperature-sensitive quantum dots, offer innovative, non-contact thermal monitoring capabilities. Furthermore, artificial intelligence-driven feedback systems present opportunities for adaptive, real-time thermal optimization. By consolidating these strategies, this review highlights pathways to develop more dependable, efficient, and application-ready microfluidic devices, with implications for diagnostics, research, and other practical uses. Full article

The Hunga-Tonga volcanic eruption on 15 January 2022, produced significant atmospheric and ionospheric disturbances that may degrade global navigation satellite system (GNSS) and precise point positioning (PPP) accuracy. Using data from the GEONET GNSS network and Soratena barometric pressure sensors across Japan, we analyzed the eruption’s effects through the gradient ionospheric index (GIX) and the rate of TEC index (ROTI) to characterize the propagation and effects of these disturbances on ionospheric total electron content (TEC) gradients. Our analysis identified two separate ionospheric disturbance events. The first event, coinciding with the arrival of atmospheric Lamb waves, was characterized by wave-like pressure anomalies, differential TEC (dTEC) fluctuations, and modest horizontal gradients of vertical TEC (VTEC). In contrast, the second, more pronounced disturbance was driven by equatorial plasma bubbles (EPBs), which generated severe ionospheric irregularities and large TEC gradients. Further analysis revealed that these two disturbances had markedly different impacts on GNSS positioning accuracy. The Lamb wave–induced disturbance mainly caused moderate TEC fluctuations with limited effects on positioning accuracy, and mid-latitude stations maintained both average and 95th percentile positioning ($\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$) errors below 0.1 m throughout the event. In contrast, the EPB-driven disturbance had a substantial impact on low-latitude regions, where the average horizontal PPP error peaked at 0.5 m and the horizontal and vertical $\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$ errors exceeded 1 m. Our findings reveal two episodes of spatial-gradient enhancement and successfully estimate the propagation speed and direction of the Lamb waves, supporting the potential application of ionospheric gradient monitoring in forecasting GNSS performance degradation. Full article

The efficacy of indoor residual spray (IRS) products is affected by various factors, such as the substrate on which they are sprayed and the surface concentration and bioavailability of the insecticide. This study investigated the potential of bespoke silica particles (hereafter referred to as ‘X-tec silica’) as a unique carrier for insecticides to reduce the insecticide content in an IRS formulation by improving pickup by mosquitoes and optimising the physical state of the insecticide while maintaining its residual biological activity on a surface. Molecular computer modelling was used to define the critical crystallisation size of clothianidin, and silica particles were manufactured with pore diameters smaller than this length to maintain the insecticide in an amorphous state. Silica carriers were then formulated to incorporate clothianidin inside their pores, and a full material characterisation was conducted to assess the clothianidin coating position on/in the silica particles, their concentration, and their physical form. The clothianidin-formulated silica (10%) was sprayed at three different application rates (30, 60, and 90 mg active ingredient (a.i.)/m²) onto two surfaces: glazed and unglazed tiles. The tiles were tested for bioefficacy against the insecticide-susceptible Anopheles gambiae s.s. Kisumu mosquito strain at 1 week and 8 months post-spray application. At 1 week post-spray application, at 60 and 90 mg a.i./m² application rates, 100% mortality was observed on both surfaces within 48 h. For the lowest concentration (30 mg a.i./m²), 100% mortality was reached within 72 h on glazed tiles; however, for unglazed tiles, due to the surface irregularity and porosity, it remained below 60%. At 8 months post-spray application, on glazed tiles, 100% mortality was reached within 24 h at 60 and 90 mg a.i./m² application rates and within 48 h at 30 mg a.i./m². On unglazed tiles, 96 h mortality was not measured; however, 100% mortality was reached within 72 h (90 mg a.i./m²) and 120 h (60 mg a.i./m²) at higher concentrations. At the lowest concentration (30 mg a.i./m²) at 120 h, mortality only reached 25%. The lowest application rate tested (30 mg a.i./m²) is ten times lower than that of current products on the market and demonstrates the potential of this approach. Preliminary findings from this study suggest that X-tec silica particles may enhance the effectiveness of IRS using clothianidin. However, further extensive research is needed to confirm this. Full article