Search Results (162)

As a pivotal driver of high-quality development, new quality productivity (NQP) forms an indispensable synergistic relationship with land use efficiency (LUE) for achieving regional sustainability. Based on panel data from 29 prefecture-level cities in the Central Plains Urban Agglomeration (CPUA) from 2010 to 2023, this study integrates the entropy-weighted TOPSIS method, super-efficiency Slack-Based Measure (SBM) model, Malmquist index, and fixed-effects models to systematically explore the spatiotemporal evolution of NQP and its underlying impact mechanism on LUE. Key findings reveal: (1) The comprehensive NQP index of the CPUA increased from 0.280 to 0.828, exhibiting a “stepwise rise” trend, with a spatial pattern characterized by a “core–secondary–periphery” three-tier gradient distribution. Zhengzhou, as the core growth pole, played an innovative leading role, while peripheral cities (e.g., Handan, Hebi) remained constrained by resource-dependent economic structures, with NQP indices consistently below 0.2. (2) The average LUE in the study area increased from 0.917 to 1.031. Cities within Henan Province generally performed better than those in Hebei, Shanxi, and Anhui provinces. Total factor productivity grew at an average annual rate of 16.4%, with technological progress serving as the primary driver. (3) NQP exerts a significantly positive impact on LUE, yet with notable heterogeneity: large-scale cities enhanced intensive land use substantially through technological agglomeration and industrial upgrading; cities with scarce arable land and high economic development levels effectively leveraged NQP to boost LUE; in contrast, small cities, regions rich in arable land, and areas with low economic development have not established effective synergistic mechanisms, hindered by limited technological absorption capacity, path dependence, and factor bottlenecks. This study provides empirical support and actionable insights for optimizing land resource allocation and advancing coordinated development between NQP and LUE in similar urban agglomerations. Full article

This study examines lexical and syntactic convergence between Dai Lue and Chinese in the multilingual environment of Sipsongpanna, employing an apparent-time approach across three generational cohorts (N = 90, balanced gender). Through mixed-methods analysis (structured questionnaires and semi-structured interviews), significant diachronic variation was observed. Younger speakers exhibited pronounced convergence, adopting Chinese-derived syntactic patterns (e.g., prenominal quantifiers and preverbal adjunct phrases) and borrowing Chinese lexical elements (e.g., an adverb sɛn⁵⁵ ‘first’ ← Chinese 先 xiān, and a superlative marker tsui³⁵ ‘most/best’ ← Chinese 最 zuì). Middle-aged speakers use transitional hybrid structures, while older speakers more consistently maintain native Dai Lue features. The results conform with Labov’s age-grading model in contact linguistics and refine Thomason’s borrowing hierarchy by revealing two factors: First, the prestige of the Chinese language drives convergence among youth. Second, syntactic compatibility with Chinese is mediated not merely by language structure, but by discourse-pragmatic needs, functional load redistribution, and the social indexicality of borrowed structures. This underscores the interplay between sociolinguistic motivations and structural-adaptive constraints in language change. The findings provide critical insights into language contact mechanisms among ethnic minorities of China, with implications for sociolinguistic theory, language revitalization efforts, and bilingual education policy implementation in linguistically diverse communities. Full article

Background: Syphilis can present with diverse clinical manifestations, earning the name “great imitator.” Malignant syphilis (MS) is a rare, severe form of secondary syphilis, typically reported in immunocompromised patients, particularly those living with HIV. However, MS can occasionally occur in immunocompetent individuals, posing diagnostic challenges due to its atypical presentation. Methods: A case report is presented alongside a PubMed literature search using the terms “(malignant syphilis OR lues maligna) AND (immunocompetent) AND (case report OR case series).” No language or temporal restrictions were applied, yielding 18 relevant publications. Results: A 60-year-old HIV-negative man presented with fever, weight loss, papular lesions, and a single ulcer on the sternum. Serology was positive for syphilis, and PCR confirmed T. pallidum DNA in the lesion. Treatment with a single intramuscular dose of benzathine penicillin G led to prompt clinical and serological improvement. Literature review (n = 18) showed that MS in immunocompetent patients affects both sexes (55% male; mean age 37.1 years), often presents with ulceronodular or rupioid crusted lesions, and frequently involves systemic symptoms. Molecular diagnostics were rarely reported, with most diagnoses relying on histopathology and serology. Treatment with benzathine penicillin G was effective in all cases, and full recovery was achieved. Conclusions: MS can occur in immunocompetent, HIV-negative individuals without obvious risk factors. Clinicians should maintain a high index of suspicion in cases of systemic, cutaneous, or ocular manifestations suggestive of MS. Molecular assays can facilitate diagnosis and prevent unnecessary invasive procedures. Benzathine penicillin G remains the treatment of choice, demonstrating high therapeutic effectiveness. MS should be considered in the differential diagnosis of ulcerative or nodular dermatoses, regardless of immune status. Full article

With advancements in solar-induced fluorescence (SIF) observation technology and the evolution of vegetation radiative transfer models, SIF signals can now be more effectively interpreted and leveraged from a mechanistic perspective. This, in turn, facilitates a deeper understanding of the mechanistic link between SIF and photosynthesis. Considering the impact of water stress on terrestrial ecosystems, this paper simulated SIF and gross primary productivity (GPP) values using the STEMMUS-SCOPE model at half-hour scales from 2017 to 2023 at the Daman site. The simulation results were compared and validated against flux tower observations and SCOPE model outputs. Taking advantage of irrigation events in the semi-arid irrigated farmland, we assessed the accuracy of STEMMUS-SCOPE in simulating SIF and GPP under drought stress, as well as its capability to quantitatively analyze the impacts of water stress on SIF and GPP. The results show that the accuracy of the SIF and GPP values simulated by the STEMMUS-SCOPE model is higher than that of the SCOPE model. The averaged R² and RMSE between the SIF simulated by STEMMUS-SCOPE model and the observed SIF values are 0.66 and 0.29 mW m⁻² nm⁻¹, and the averaged R² and RMSE between the GPP simulated by the STEMMUS-SCOPE model and the observed GPP values from 2017 to 2023 are 0.88 and 4.93 µmol CO₂ m⁻² s⁻¹, respectively. Especially under relatively drought conditions, the R² between the SIF simulated values and observed values is 0.84, and the R² between the GPP simulated values and observed values is 0.96. By further combining soil moisture content (SMC) and canopy conductance (Gs) analyses, we found that the response of the STEMMUS-SCOPE simulations under water stress was consistent with previous findings on the impacts of water deficits, thereby confirming the model’s reliability for drought conditions. Under drought stress, the decline in fluorescence emission efficiency (ΦF) with decreasing Gs and SMC was smaller than that of the light use efficiency (LUE). Therefore, the STEMMUS-SCOPE model is promising for investigating the SIF–GPP relationship under drought stress. Full article

Background/Objectives: Baihe Dihuang Tang (BDT), a classical herbal formula from Zhang Zhongjing’s Han Dynasty work Jin Gui Yao Lue, is widely used to treat depressive disorder by nourishing Yin, clearing heat, and tonifying the heart and lungs. However, its pharmacological mechanisms remain unclear. This study aims to explore BDT’s antidepressant effects via MAOA-regulated serotonin (5-HT) metabolism and synaptic plasticity, supported by experimental validation, while using network pharmacology to predict MAOA-targeting active components. Methods: Active components and targets of BDT were screened using TCMSP, TCMID, and other databases, and then a component-target-pathway network was constructed. A chronic restraint stress (CRS)-induced depressive mouse model was established. Behavioral tests, including open field test (OFT), elevated plus maze (EPM), forced swimming test (FST) and tail suspension test (TST), were conducted to evaluate antidepressant effects. ELISA, qRT-PCR, and Western blot were employed to assess hippocampal 5-HT metabolism (MAOA, 5-HT/5-HIAA ratio) neurotrophic signaling (BDNF, TrkB) and synaptic plasticity-related proteins (PSD-95, SYN1). Results: BDT significantly reduced FST/TST immobility time and improved anxiety-like behaviors in OFT/EPM. BDT treatment downregulated MAOA expression, elevated hippocampal 5-HT/5-HIAA ratio, activated BDNF/TrkB pathway, and upregulated PSD-95/SYN1. Network pharmacology confirmed MAOA’s central role, identifying MAOA/serotonergic synapse modulation as BDT’s main mechanism and pinpointing Ferulic acid, Caffeate, Stigmasterol, (−)-nopinene, Eugenol, and cis-Anethol as MAOA-targeting bioactive components. Conclusions: BDT ameliorates depressive-like behaviors. This effect is mechanistically linked to suppression of MAOA-mediated 5-HT catabolism—a key validated target. This suppression elevates hippocampal 5-HT bioavailability, thereby activating BDNF/TrkB signaling and promoting synaptic plasticity. Network pharmacology confirmed MAOA as a primary target and identified specific modulatory bioactive components. Full article

Facing the significant challenges posed by global population growth and urbanization, plant factories, as an efficient closed cultivation system capable of precise environmental control, have become a key direction in the development of modern agriculture. However, high energy consumption, particularly lighting (which accounts for over 50%), remains a major bottleneck limiting their large-scale application. This study systematically explored the effects of dynamic light regulation strategies on lettuce (Lactuca sativa L.) growth, physiological and biochemical indicators (such as chlorophyll, photosynthetic, and fluorescence parameters), nutritional quality, energy utilization efficiency, and post-harvest shelf life. Four different light treatments were designed: a stepwise increasing photosynthetic photon flux density (PPFD) from 160 to 340 μmol·m⁻²·s⁻¹ (T1), a constant light intensity of 250 μmol·m⁻²·s⁻¹ (T2), a three-stage strategy with high light intensity in the middle phase (T3), and a three-stage strategy with sequentially increasing light (T4). The results showed that the T4 treatment exhibited the best overall performance. Compared with the T2 treatment, the T4 treatment increased biomass by 23.4%, significantly improved the net photosynthetic rate by 50.32% at the final measurement, and increased ascorbic acid (AsA) and protein content by 33.36% and 33.19%, respectively. Additionally, this treatment showed the highest energy use efficiency. On the 30th day of treatment, the light energy use efficiency (LUE) and electrical energy use efficiency (EUE) of the T4 treatment were significantly increased, by 23.41% and 23.9%, respectively, compared with the T2 treatment. In summary, dynamic light regulation can synergistically improve crop yield, chlorophyll content, photosynthetic efficiency, nutritional quality, and energy utilization efficiency, providing a theoretical basis and solution for precise light regulation and energy consumption reduction in plant factories. Full article

Rapid and uncoordinated urban expansion in arid oasis city clusters intensifies land use conflicts and ecological pressure, threatening regional sustainability. This study investigates the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains (UANSTM) in Xinjiang, northwestern China—an arid region urban cluster. A multi-source spatial data framework was established to delineate urban built-up areas and to construct land use efficiency (LUE) indicators, thereby facilitating an integrated analysis of the spatial coupling between urban expansion intensity (UEI) and LUE from 2000 to 2020. The results indicate that: (1) The urban built-up area expanded from 322 km² to 1096 km², shifting northward and northwestward, producing fragmented and decentralized patterns; (2) LUE improved but exhibited clear spatial disparities. Core cities like Urumqi showed strong synergy between rapid expansion and rising efficiency, whereas peripheral cities such as Wusu expanded quickly without corresponding efficiency gains, reflecting evident trade-offs; (3) The relationship between UEI and LUE exhibited a nonlinear evolution—trade-offs dominated during 2000–2005, synergy strengthened from 2005 to 2015, and trade-offs resurged again after 2015.These findings reveal the cyclical vulnerability of arid region urbanization and highlight the effectiveness of the proposed framework for diagnosing spatial mismatches and guiding compact, efficiency-oriented urban development toward long-term sustainability. Full article

SDG Indicator 11.3.1 assesses urban land use efficiency (LUE) through the ratio of the land consumption rate (LCR) to the population growth rate (PGR), or LCRPGR. However, its methodology is restricted to two-dimensional built-up area expansion, excluding vertical development and limiting insight into the structural mechanisms underlying efficiency outcomes. This study aims to integrate vertical urban growth into SDG 11.3.1 monitoring to improve the interpretation of efficiency outcomes. We introduce the Built-up Area–Built-up Volume (BUA–BUV) trajectory framework, which embeds vertical growth into LUE monitoring. The framework represents urban growth as trajectories in normalized BUA–BUV space and classifies them by prevailing built form (horizontal, balanced, vertical) and growth modality (expansion or intensification). This classification is then coupled with LCRPGR to link efficiency outcomes with spatial structure. We apply the framework to 10,856 urban centres worldwide using Global Human Settlement Urban Centre Database (GHS-UCDB 2025) data from 1980 to 2020. Results show that inefficient growth (LCRPGR > 1) dominated, affecting 69% of centres during 1980–2000 and 52% during 2000–2020, while inefficiency linked to demographic decline (LCRPGR ≤ 0) rose from 9% to 20%. Efficient centres (0 < LCRPGR ≤ 1) increased from 22% to 29%. Across all efficiency classes, BUA–BUV trajectories revealed a prevailing pattern of horizontal expansion, with similar LCRPGR values associated with structurally divergent growth paths. Vertically intensifying development was rare, even among efficient centres. The BUA–BUV framework embeds structural context into efficiency assessments, thereby strengthening SDG 11.3.1 monitoring and informing policies for compact and sustainable urbanization. Full article

Meta-cresol (m-cresol) is highly corrosive and toxic, and is widely present in industrial wastewater. As a pollutant, it adversely affects various aspects of human production and daily life. To evaluate the feasibility of using sunflowers to remediate m-cresol-contaminated wastewater, this study used Helianthus annuus L. as the test subject to analyze its tolerance and the wastewater purification efficiency under different m-cresol concentrations. The results showed that the net photosynthetic rate (P_n), transpiration rate (T_r), stomatal conductance (G_s), and light energy utilization efficiency (LUE) of Helianthus annuus L. exhibited an overall decreasing trend, while the intercellular CO₂ concentration (Cᵢ) initially increased and subsequently decreased with increasing m-cresol concentration. When m-cresol concentration reached or exceeded 60 mg·L⁻¹, the net photosynthetic rate and intercellular CO₂ concentration in the leaves showed opposite trends with further increases in m-cresol stress. The inhibition of net photosynthesis in sunflowers by m-cresol was mainly attributed to non-stomatal factors. The maximum photochemical efficiency (F_v/F_m), actual photochemical efficiency (ΦPSII), photochemical quenching coefficient (q^P), PSII excitation energy partition coefficient (α), and the fraction of absorbed light energy used for photochemistry (P) all decreased with increasing m-cresol concentration. In contrast, non-photochemical quenching (NPQ), the quantum yield of regulated energy dissipation [Y(NPQ)], and the fraction of energy dissipated as heat through the antenna (D) first increased and then decreased. Under low-concentration m-cresol stress, sunflowers protected their photosynthetic system by dissipating excess light energy as heat as a stress response. However, high concentrations of m-cresol caused irreversible damage to Photosystem II (PSII) in sunflowers. Under m-cresol stress, chlorophyll a exhibited strong stability with minimal degradation. As the m-cresol concentration increased from 30 to 180 mg·L⁻¹, the removal rate decreased from 84.91% to 11.84%. In conclusion, sunflowers show good remediation potential for wastewater contaminated with low concentrations of m-cresol and can be used for treating m-cresol wastewater with concentrations ≤ 51.9 mg·L⁻¹. Full article

Tobacco smoking remains a critical public health concern in Indonesia, particularly in Aceh Province, where male smoking prevalence reaches 56.12%. Cultural permissiveness and weak enforcement of tobacco control regulations have contributed to this high prevalence. Women, especially wives, are central figures in family health and may play an essential role in influencing household smoking behavior. However, their roles and strategies remain underexplored, especially in conservative cultural settings. This qualitative study employed a Participatory Action Research (PAR) approach to examine the roles of women in controlling the smoking behavior of family members in Aceh. A total of 75 research subjects were selected from three districts (Aceh Singkil, Gayo Lues, and Pidie Jaya) using a combination of purposive sampling and snowball sampling methods. Data were collected through semi-structured in-depth interviews and were analyzed thematically using NVivo 15 software. The analysis framework was based on Lawrence Green’s PRECEDE model, which includes predisposing, enabling, and reinforcing factors. This study found that women demonstrated progressive attitudes toward smoking, evolving from passive acceptance to active responsibility. They employed both persuasive strategies (health education, emotional appeals, and motivation) and coercive actions (household smoking bans, threats, and withdrawal of privileges). Women also positioned themselves as health monitors and guardians within the household. Despite cultural limitations and gender hierarchy, many participants reported partial or complete success in encouraging their husbands to quit smoking, particularly when supported by religious norms and health awareness. Women play a pivotal role in shaping smoking-related behavior in the family. Empowering women through participatory frameworks and culturally tailored interventions can enhance their effectiveness as health advocates. This study underscores the need to integrate gender-sensitive strategies into national tobacco control policies, especially in culturally conservative regions. Full article

Gross primary productivity (GPP) is a key indicator for assessing carbon uptake capacity and photosynthetic productivity in agricultural ecosystems, playing a crucial role in regional carbon cycle evaluation and sustainable agriculture development. However, traditional mechanistic light use efficiency (LUE) models exhibit variable accuracy under different climatic conditions and crop types. Machine learning models, while demonstrating strong fitting capabilities, heavily depend on the selection of input features and data availability. This study focuses on winter wheat in the Guanzhong region, utilizing continuous field observation data from the 2020–2022 growing seasons to develop five machine learning models: Ridge Regression (Ridge), Random Forest (RF), Support Vector Regression (SVR), Gradient Boosting Regression (GB), and a stacking-based ensemble learning model (LSM). These models were compared with the LUE model under two scenarios, excluding and including solar-induced chlorophyll fluorescence (SIF), to evaluate the contribution of SIF to GPP estimation accuracy. The results indicate significant differences in GPP estimation performance among the machine learning models, with LSM outperforming others in both scenarios. Without SIF, LSM achieved an average R² of 0.87, surpassing individual models (0.72–0.83), demonstrating strong stability and generalization ability. With SIF inclusion, all machine learning models showed marked accuracy improvements, with LSM’s average R² rising to 0.91, highlighting SIF’s critical role in capturing photosynthetic dynamics. Although the LUE model approached machine learning model accuracy in some growth stages, its overall performance was limited by structural constraints. This study demonstrates that ensemble learning methods integrating multi-source observations offer significant advantages for high-precision winter wheat GPP estimation, and that incorporating SIF as a physiological indicator further enhances model robustness and predictive capacity. The findings validate the potential of combining ensemble learning and photosynthetic physiological parameters to improve GPP retrieval accuracy, providing a reliable technical pathway for agricultural ecosystem carbon flux estimation and informing strategies for climate change adaptation. Full article

Land use efficiency (LUE) serves as a crucial nexus between economic development and sustainable resource management, directly influencing urban production–consumption systems. While economic development stages (EDSs) reflect a region’s environmental carrying capacity and profoundly affect LUE, the specific mechanisms governing this relationship remain unclear. In this study, we combined multi-source data to portray the spatiotemporal patterns of EDSs and LUE in 276 Chinese cities from 1995 to 2020, and we identified the nonlinear effects of EDSs on LUE. Based on the fine-scale LUE, it is confirmed that the older the age of urban land generation, the higher the LUE, laying a theoretical foundation for subsequent research. Simultaneously, the EDS continues to be upgraded, with approximately 70% of cities reaching the post-industrialization stage or higher by 2020. The results of partial dependency plots (PDPs) revealed that the EDS has a positive impact on LUE. From the perspective of different urban scales, the higher the EDSs of supercities, type I large cities, type II large cities, and type II small cities, the greater the positive impact on LUE, whereas the impact patterns at other urban scales follow an inverted U-shape. These findings carry important implications for sustainable spatial development, particularly in optimizing land resource allocation to assist the shift to more efficient production systems and responsible consumption patterns. Full article

Vegetation photosynthesis is a key Earth system process that can fix carbon dioxide in the atmosphere. Mountainous areas usually have high productivity and extensive vegetation cover, but their study requires a higher spatiotemporal resolution due to the complex climate and vegetation variations with altitude. In this study, we analyzed the variations and climatic responses of vegetation gross primary productivity (GPP) in northwestern Hubei, China, at a 30 m spatial resolution from 2001 to 2020, based on the fusion of multi-source remote sensing data. A GPP estimation framework based on the CASA model was applied, and spatiotemporal fusion of Landsat and MODIS data was achieved using the STNLFFM algorithm. The results indicate that GPP exhibits higher values in the mountainous regions of west Shennongjia, compared to the eastern plain regions, with a generally increasing trend with increasing elevation. GPP has shown an overall increasing trend over the past 20 years, with almost 90% of the high-elevation regions showing an increasing trend, and the low-elevation regions showing an opposite trend. The relationship between GPP and climate factors is greatly impacted by the temporal scale, with the most pronounced correlation at a seasonal scale. The impact of temperature has been generally stable over the past 20 years across different altitudes, while the relationship with precipitation has exhibited an overall decreasing trend with the increase of altitude. Precipitation and temperature correlations show opposing variations in different months and elevations, which can be mainly attributed to the varied climatic conditions in the different elevations. Full article

Phosphorus (P) and silicon (Si) could profoundly affect the net primary productivity (ANPP) of grassland ecosystems. However, how ecosystem biomass will respond to different Si addition, especially under a concurrent increase in P fertilization, remains limited. With persistent demand for grassland utilization, there is a need to enhance and sustain the productivity of grasslands on the Qinghai–Tibet Plateau. Three P addition rates (0, 400, 800, and 1200 kg Ca(H₂PO₄)₂ ha⁻¹ yr⁻¹) without Si and with Si (14.36 kg H₄SiO₄ ha⁻¹ yr⁻¹) were applied to alpine grassland on the Qinghai–Tibet Plateau to evaluate the responses of aboveground biomass and the underlying mechanisms linking to structural carbon composition and physiological traits of grasses and forbs. Our results show that the application of Si significantly reduced the lignin, cellulose, hemicellulose, and total phenol contents of both grasses and forbs. Additionally, the addition of P, Si, and phosphorus and silicon (PSi) co-application significantly increased the net photosynthetic rate (Pn) and light use efficiency (LUE) of grasses and forbs. Moreover, Si promoted the absorption of N and P by plants, resulting in significant changes in the Si:C, Si:P, and Si:N ratios and increasing the aboveground biomass. Our findings suggest that Si can replace structural carbohydrates and regulate the absorption and utilization of N and P to optimize the photosynthetic process of leaves, thereby achieving greater biomass. In summary, Si supplementation improves ecosystem stability in alpine meadows by optimizing plant functions and increasing biomass accumulation. Full article

Indoor farming presents a sustainable response to urbanization and climate change, yet optimizing light use efficiency (LUE) remains vital for maximizing crop yield and minimizing energy use. This study introduces an IoT-based framework for adaptive light management in controlled environments, using lettuce (Lactuca sativa L.) as a model crop due to its rapid growth and sensitivity to light spectra. The system integrates advanced LED lighting, real-time sensors, and cloud-based analytics to enhance light distribution and automate adjustments based on growth stages. The key findings indicate a 20% increase in energy efficiency and a 15% improvement in lettuce growth compared to traditional static models. Novel metrics—Light Use Efficiency at Growth stage Canopy Level (LUEP) and Lamp Level (LUEL)—were developed to assess system performance comprehensively. Simulations identified optimal growth conditions, including a light intensity of 350–400 µmol/m²/s and photoperiods of 16–17 h/day. Spectral optimization showed that a balanced blue-red light mix benefits vegetative growth, while higher red content supports flowering. The framework’s feedback control ensures rapid (<2 s) and accurate (>97%) adjustments to environmental deviations, maintaining ideal conditions throughout growth stages. Comparative analysis confirms the adaptive system’s superiority over static models in responding to dynamic environmental conditions and improving performance metrics like LUEP and LUEL. Practical recommendations include stage-specific guidelines for light spectrum, intensity, and duration to enhance both energy efficiency and crop productivity. While tailored to lettuce, the modular system design allows for adaptation to a variety of leafy greens and other crops with species-specific calibration. This research demonstrates the potential of IoT-driven adaptive lighting systems to advance precision agriculture in indoor environments, offering scalable, energy-efficient solutions for sustainable food production. Full article