Search Results (3,034)

Driven by the United Nations Sustainable Development Goals (SDGs) and the global “Bamboo as a Substitute for Plastic” initiative, China has become a key bamboo industry player by leveraging abundant resources and an integrated supply chain. To enhance international competitiveness, optimizing product structure and market resilience is essential. Using descriptive statistics, visualization, trade concentration index, and K-means clustering, this study analyzed China’s bamboo trade spatiotemporal patterns and market resilience based on 2015–2024 China customs data. Results revealed major revisions in the Harmonized System (HS) codes for bamboo products in 2017, yet existing classifications remain insufficiently detailed. Imports declined overall, characterized by fragmented primary products mainly sourced from the Taiwan region of China and Vietnam. In contrast, exports grew steadily, led by Bamboo Tableware, with the United States, Japan, and Europe as key markets, and notable expansion into Southeast Asia. In 2024, bamboo products accounted for over 99% of China’s total bamboo trade value, and the export–import gap kept widening. Compared with 2015, export concentration declined: low- and medium-concentration markets increased, highly concentrated ones decreased, and overall resilience improved. Cluster analysis split core destinations into seven groups in 2015 but only five in 2024, signalling broader demand diversity and fewer single-category-dominated markets. The study recommends refining HS codes to reflect new bamboo innovations; consolidating markets in Europe and America while expanding differentiated demand in Southeast Asia; upgrading Bamboo Tableware through technology; and boosting core product competitiveness to support global bamboo trade and the “Bamboo as a Substitute for Plastic” initiative. Full article

The geochemical characteristics of reinjection fluids play a crucial role in controlling water–rock interactions and the long-term stability of geothermal reservoirs. This study aims to evaluate how different fluid chemistries affect mineral dissolution–precipitation behavior and ion migration during geothermal reinjection. Five types of reinjection water—including geothermal source water (i.e., formation water from the reservoir), primary and secondary treated waters, and their mixtures—were reacted with carbonate rocks from the Wumishan Formation of the Xiong’an New Area, North China Basin, under reservoir-like conditions (70 °C, 17 MPa). A combination of batch experiments, inverse modeling using PHREEQC, and one-dimensional reactive transport simulations was employed. Results show that fluid pH, ionic strength, and saturation state significantly influence reaction pathways. Alkaline-treated waters enhanced silicate dissolution, increasing Na⁺, K⁺, and Si concentrations, while source water and its mixtures promoted carbonate precipitation, increasing the risk of clogging. Simulations revealed that the early injection stage is the most reactive, with rapid ion front advancement and strong mineral transformations. Reaction-controlled ions such as Ca²⁺ and SO₄²⁻ formed enrichment zones, while conservative ions like Na⁺ and Cl⁻ propagated more uniformly. Moderate alkaline regulation was found to mitigate carbonate scaling and improve silicate reactivity, thereby reducing permeability loss. This integrated approach provides mechanistic understanding and practical guidance for reinjection fluid design in medium-to-deep geothermal systems. Full article

Among the Central Asian republics, Uzbekistan is unique in that approximately 80% of its territory lies within a plain, characterized by an arid geographic zone and dry climate. Agricultural production in these regions is possible only through artificial irrigation. In recent years, global climate change and challenges related to transboundary water use have led to a reduction in water availability. The average annual water allocation to Uzbekistan is estimated at 51–53 billion m³, of which 90–91% is consumed by the agricultural sector. Due to the uneven distribution of water resources and the complex topography of irrigated lands, water supply is supported by numerous pumping stations operated by the state, water users associations, farms, and clusters. Additionally, well-based pumping systems are employed to maintain groundwater levels and ensure irrigation. On average, these facilities consume around 8.0 billion kWh of electricity annually. The agricultural sector faces several critical challenges, including crop water deficits caused by water shortages, slow adoption of water-saving technologies, and limited implementation of drip irrigation on household plots, dachas, and greenhouses that play a key role in food supply. Moreover, the delivery of water to fertile lands situated far from main power lines and water sources remains problematic. This article aims to explore the integration of solar energy solutions to support drip irrigation in both large-scale agricultural lands (ω = 1.0–100.0 ha and above) and small-scale areas such as homestead plots, dachas, and greenhouses (ω = 0.01–1.0 ha), as well as their application in small- to medium-sized pumping stations. Based on the research and experimental design work carried out, three mobile photovoltaic units—MPPU-8-500-4000, MPPU-2-550-1100, and MPPU-4-500-2000—were developed and implemented to address water and energy shortages in agriculture. Full article

Understanding the degradation behavior of lithium-ion batteries under realistic application conditions is critical for the design and operation of Battery Energy Storage Systems (BESS). This research presents a modular, cell-level simulation framework that integrates electrical, thermal, and aging models to evaluate system performance in representative utility and residential scenarios. The framework is implemented using Python and allows time-series simulations to be performed under different state of charge (SOC), depth of discharge (DOD), C-rate, and ambient temperature conditions. Simulation results reveal that high-SOC windows, deep cycling, and elevated temperatures significantly accelerate capacity fade, with distinct aging behavior observed between residential and utility profiles. In particular, frequency modulation and deep-cycle self-consumption use cases impose more severe aging stress compared to microgrid or medium-cycle conditions. The study provides interpretable degradation metrics and visualizations, enabling targeted aging analysis under different load conditions. The results highlight the importance of thermal effects and cell-level stress variability, offering insights for lifetime-aware BESS control strategies. This framework serves as a practical tool to support the aging-resilient design and operation of grid-connected storage systems. Full article

In low to medium-seismicity countries, seismic design is often not mandatory. Furthermore, zoning is frequently adopted to justify simplified calculations based on force methods without capacity criteria. However, risk analysis should merge vulnerability, threat, and exposure. So even regions with low seismicity can face potentially high consequences due to earthquakes. This is the case of Brazil, where seismic provisions were lacking until 2006 when the first standard was approved, being updated in 2023. Therefore, this study selected a typical RC frame configuration and focuses on assessing the differences in seismic performance between the provisions outlined in EN1992-1-1/EN1998-1 and ABNT NBR15421. The research highlights how different requirements affect low and medium-seismicity regions. Hence, the methodology and conclusions can serve as a guide for decision-making in other countries regarding impact and effectiveness. There are considered different scenarios of design, seismicity, and ductility class. The nonlinear static Pushover analysis was conducted and also validated with nonlinear dynamic Time-history analysis. The assessment of the results is based on the design assumptions, capacity curves, collapse mechanism, IDA curves, PSDM, damage limit states and cost-benefits. Non-seismic design structures had a premature brittle collapse. The global ductility condition was the main key to changing into a ductile mechanism, and seismic detailing was the variable that addresses the ductility level. Full article

Background/Objectives: Accumulating evidence suggests that cognitive training can induce functional reorganization of intrinsic connectivity networks involved in higher-order cognitive processes. However, few interventions have specifically targeted language, an essential domain tightly interwoven with memory, attention, and executive functions. Given their foundational role in communication, reasoning, and knowledge acquisition, enhancing language-related abilities may yield widespread cognitive benefits. This study investigated the neural impact of a new structured, language-based cognitive training program on neurotypical older adults. Methods: Twenty Brazilian Portuguese-speaking women (aged 63–77 years; schooling 9–20 years; low-to-medium socioeconomic status) participated in linguistic activities designed to engage language and general cognitive processing. Behavioral testing and resting-state functional Magnetic Resonance Imaging (fMRI) were conducted before and after the intervention. Results: Functional connectivity analyses revealed significant post-intervention increases in connectivity within the frontoparietal network, critical for language processing, and the ventral attentional network, associated with attentional control. Conclusions: The observed neural enhancements indicate substantial plasticity in cognitive networks among older adults, highlighting the effectiveness of linguistic interventions in modulating critical cognitive functions. These findings provide a foundation for future research on targeted cognitive interventions to promote healthy aging and sustain cognitive vitality. Full article

Between 1900 and 1940, African American participants in transatlantic public exhibitions reclaimed a medium that often oppressed non-White bodies: the diorama. This essay traces a transatlantic conversation among African American artists about how to render Black history in diorama form, leveraging the miniature format to make political arguments. In diorama series which circulated on both sides of the Atlantic, such as those designed by Thomas W. Hunster for the Exhibit of American Negroes in the Paris Universal Exposition in 1900 and the Pan-American Exposition in 1901, Meta Vaux Warrick Fuller for the Jamestown Ter-Centennial Exposition in 1907, and Charles C. Dawson for the American Negro Exposition in Chicago in 1940, African American makers selectively used architectural models to signify histories of oppression and liberation as they told transatlantic stories about Black migration and enslavement. This essay argues that this set of dioramas is entwined, growing from 9 to 14 to 33, and that Hunster, Fuller, and Dawson all rendered archetypal buildings, such as slave cabins or plantation homes, to designate the wide and encompassing scope of oppression, while they reference singular buildings associated with public institutions from government to universities—the M Street School in Washington DC, Carnegie Library at Howard University, Mother Bethel AME Church in Philadelphia, the Old Massachusetts State House, and the White House—to signify and emplace spaces of Black liberation. Building on research on the layered functions of miniatures and drawing on burgeoning scholarship on entwinements between race and architecture, the article speculates on how architecture style signifies through the models to reinforce what James C. Scott has parsed as dominant narratives and hidden transcripts. Seeking to build Black futurity, all three series facilitated community participation and collaboration to produce an intersocial construction of transatlantic African American history built through mobile models of architecture. Full article

Electrochemical Impedance Spectroscopy (EIS) measurements are highly sensitive to the fixturing, temperature, and state of charge (SoC) of batteries. For 10 kWh automotive battery modules, we show that variations in SoC and temperature introduce significant errors at low-to-medium frequencies (<100 Hz), while improper fixture wiring affects mainly higher-frequency accuracy, with errors up to 100% in the imaginary part at 1 kHz. In addition, we study repeatability across various tester-module configurations. EIS results remain highly consistent (±100 µΩ) across three different modules. Comparing the same module across two different testers, deviations are even lower (±30 µΩ up to 1 kHz). The EIS evolution is studied with respect to the cycle numbers, where a strong correlation of low-frequency impedance features is demonstrated. A new combined quotient feature is introduced and suggested as a reliable and efficient state of health (SoH) indicator, solely based on a model-free and phenomenological approach. The study demonstrates the potential of EIS as a powerful tool for battery module characterization, provided that its requirements and limitations are carefully addressed through well-defined experimental setups. Accurate and repeatable EIS measurements are particularly important for obtaining accurate electrochemical insights, especially in the low-to-mid frequency domain, where impedance variations are most sensitive to battery states and ageing effects. Full article

For the fault issues in the workshop environmental control system sensor network, a fault diagnosis and recovery method based on medium-to-long-term predictions is proposed. Firstly, a temperature observer based on the Informer model is established. Then, the predicted data temporarily replaces the missing real data, and the model predicts the state of the sensor system within the step size. Secondly, the predicted data is combined with the measured temperature series, and residuals are utilized for real-time detection of sensor faults. Finally, the predicted data at the time of the fault replaces the real data, enabling the recovery of fault data; experiments are conducted to verify the effectiveness of the proposed method. The results indicate that when the prediction horizon is 1, 5, 10, 20, and 50, the average fault diagnosis rates under four fault levels are 94.40%, 95.28%, 94.79%, 92.52%, and 93.35%, respectively. The average coefficients of determination for data recovery are 0.999, 0.997, 0.995, 0.985, and 0.915, respectively. This achieves medium-to-long-term predictions in the field of sensor fault diagnosis. Full article

Small and medium-sized enterprises (SMEs) drive economic growth but face barriers in adopting AI for creative digital marketing, particularly in underserved U.S. markets. This study investigates an AI-driven unified advisory platform to enable strategic digital marketing in these communities. Integrating modules such as MarketRadar (customer insights, benchmarking) with StrategicCoaching and ComplianceTools, it supports data-driven campaign design, pricing, and engagement. Using mixed methods, we interviewed 13 SME owners/managers in Houston’s underserved neighborhoods and surveyed 172 platform users across three U.S. states. Results show that SMEs using multiple modules achieved higher customer acquisition and revenue than standalone users, with qualitative insights revealing creative repositioning and refinement despite limited budgets. Trust elements like PeerBenchmarks and ComplianceAlerts boosted uptake. Our study advances digital marketing literature by evidencing how AI platforms and cross-module collaboration catalyze innovation, decision-making, and sustainable growth in U.S. contexts, with caution for broader extrapolation. It offers recommendations for policymakers and SaaS providers on inclusive transformation in resource-constrained settings. Full article

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response of the medium through which it passes and determine its state. However, our knowledge of the atmospheric phenomena generated by the terminator is far from complete. One clear indication of the terminator’s influence is geomagnetic disturbances manifested in the vertical and eastward components of the magnetic field measured at magnetic observatories. To determine the sources of geomagnetic disturbances from the solar terminator, which can be identified by the strict phase correlation of these disturbances with the moments of terminator passage, ionospheric irregularities arising during terminator passage were studied. Ionospheric irregularities extending along the boundary of the morning solar terminator were detected in total electron content data, based on measurements by GNSS receivers. Assumptions are made about the possible parameters of the ionospheric current structure that creates variations in the magnetic field associated with the passage of the solar terminator. Full article

Cottonseed meal (CSM), an important protein-rich feed ingredient, faces limited utilization in livestock diets due to the presence of free gossypol (FG)—a potent antinutritional toxin. This study aimed to isolate FG-degrading bacteria from the cotton bollworm, Helicoverpa armigera, and to evaluate their potential as probiotics in vitro. Eleven gossypol-tolerant strains were isolated from the gut of Helicoverpa armigera larvae using a screening medium containing gossypol as the sole carbon source. Among these, four lactic acid bacteria strains—Pediococcus acidilactici GM-NP, Pediococcus acidilactici GM-P, Enterococcus faecalis GM-6, and Weissella confusa GM-2—were selected for further investigation of their gossypol degradation capacity and probiotic potential. Probiotic characterization revealed that all strains exhibited tolerance to gastrointestinal fluids and bile salts, safe γ-hemolysis, and strong auto-aggregation, cell surface hydrophobicity, and antimicrobial activity. Solid-state fermentation of CSM with these strains reduced FG content by more than 50%, increased crude protein by over 6%, and elevated acid-soluble protein content by more than 70%, thereby effectively enhancing the nutritional quality of CSM. This study is the first to demonstrate that bacterial isolates from the gut of Helicoverpa armigera possess concurrent high-efficiency gossypol degradation and probiotic properties, providing a theoretical foundation for developing novel probiotic resources and promoting the safe utilization of CSM. Full article

During long-range imaging, the turbid medium in the atmosphere absorbs and scatters light, resulting in reduced contrast, a narrowed dynamic range, and obscure detail information in remote sensing images. The prior-based method has the advantages of good real-time performance and a wide application range. However, few of the existing prior-based methods are applicable to the dehazing of panchromatic images. In this paper, we innovatively propose a prior-based dehazing method for panchromatic remote sensing images through statistical histogram features. First, the hazy image is divided into plain image patches and mixed image patches according to the histogram features. Then, the features of the average occurrence differences between adjacent gray levels (AODAGs) of plain image patches and the features of the average distance to the gray-level gravity center (ADGG) of mixed image patches are, respectively, calculated. Then, the transmission map is obtained according to the statistical relation equation. Then, the atmospheric light of each image patch is calculated separately based on the maximum gray level of the image patch using the threshold segmentation method. Finally, the dehazed image is obtained based on the physical model. Extensive experiments in synthetic and real-world panchromatic hazy remote sensing images show that the proposed algorithm outperforms state-of-the-art dehazing methods in both efficiency and dehazing effect. Full article

Vanillin is the compound widely used in the food industry as a flavoring agent. Currently, chemically synthesized vanillin provides the majority of the world’s supply. Due to the increase in consumer awareness, there is a change in preferences towards natural food additives. The main goal of this research was to obtain vanillin through Solid-State Fermentation on agri-food by-products such as brewer’s spent grain, wheat bran, and linseed oil cake. A specially designed SSF culture single-use bag bioreactor made of a poliamide-6 foil sleeve was used to conduct the process on a bench-scale (600 g of dry medium). After extraction and purification, obtained vanillin samples were subjected to sensory analysis to determine whether the origin of microbiologically obtained vanillin affects its aromatic properties. The panelists assessed that the extracts obtained from the cultures of P. chrysosporium CBS246.84 and F. culmorum MUT5855 proved to be attractive flavors as they showed more attractive sensory properties than synthetic vanillin and were comparable to commercially available vanilla bean extract. This is the first study to include sensory analysis of vanillin obtained biotechnologically by the SSF method. Full article

Background: Accurately detecting the onset of saturated boiling in herbal medicine extraction processes is critical for improving production efficiency and reducing energy consumption. However, the traditional monitoring methods based on temperature suffer from time delays. To address the challenge, acoustic emission (AE) signals were used in this study owing to its sensitivity to bubble behavior. Methods: An AE signal acquisition system was constructed for herbal extraction monitoring. Characteristics of AE signals at different boiling stages were analyzed in pure water systems with and without herbs. The performance of AE-based and temperature-based recognition of boiling stages was compared. To enhance applicability in different herb extraction systems, multivariate statistical analysis was adopted to compress spectral–frequency information into Hotelling’s T² and SPE statistics. For real-time monitoring, a self-adaptive decision-making boiling judgment method (BoilStart) was proposed. To evaluate the robustness, the performance of BoilStart under different conditions was investigated, including extraction system mass and heating medium temperature. Furthermore, BoilStart was applied to a lab-scale extraction process of Dabuyin Wan, which is a practical formulation, to assess its performance in energy conservation and efficiency improvement. Results: AE signal in the 75–100 kHz frequency band could reflect the boiling states of herbal medicine extraction. It was more sensitive to the onset of saturated boiling than the temperature signal. Compared with SPE, Hotelling’s T² was identified as the optimal indicator with higher accuracy. BoilStart could adaptively monitor saturated boiling across diverse herbal systems. The absolute error of BoilStart’s boiling determination ranged from 1.5 min to 2.0 min. The increasing-temperature time was reduced by about 22–36%. For the extraction process of Dabuyin Wan, after adopting BoilStart, the increasing-temperature time was reduced by about 29%, and the corresponding energy consumption was lowered by about 26%. Conclusions: The first AE-based method for precise boiling state detection in herbal extraction was established. BoilStart’s model-free adaptability met industrial demands for multi-herb compatibility. This offered a practical solution to shorten ineffective heating phases and reduce energy consumption. Full article