Search Results (1,099)

Highway accessibility plays a vital role in supporting local economic development, particularly in regions lacking access to sea or river ports. Recognizing the functional transformation of road infrastructure, the Chinese government has made substantial investments in its expansion. Nevertheless, a theoretical gap remains in justifying whether such investments yield significant economic returns. Drawing on the theory of economic externalities, this study investigates the causal relationship between highway development and regional economic growth, and assesses whether highway construction leads to an acceleration in growth rates. Utilizing panel data from 14 Chinese cities spanning 2000 to 2014, the synthetic control method (SCM) is employed to evaluate the economic externalities of highway investment. The results indicate a positive impact on surrounding industries. Furthermore, a growth rate forecasting analysis based on Back-Propagation Neural Networks (BPNNs) is conducted using industrial enterprise data from 2005 to 2014. The growth rate in the treated city is 1.144%, which is close to the real number 1.117%, higher than the number for the weighted control group, which is 1.000%. The findings suggest that the growth rate of total industrial output improved significantly, confirming the existence of positive spillover effects. This not only enriches the empirical literature on transport infrastructure but also provides targeted enlightenment for the sustainable development of urban economy in terms of policy guidance. Full article

Melastoma dodecandrum is primarily propagated through stem cuttings, which limits genetic variation and constrains breeding efforts. To overcome this limitation and facilitate molecular breeding, the establishment of a reliable and efficient regeneration system is essential. This study investigated the effects of plant growth regulators (PGRs) and culture media on the in vitro regeneration system of M. dodecandrum. The highest rate of callus induction (96.67%) was achieved when sterile leaf explants were cultured on Murashige and Skoog (MS) basal medium supplemented with 2.00 mg·L⁻¹ 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.50 mg·L⁻¹ 6-benzylaminopurine (6-BA). For callus differentiation, the optimal formulation of MS + 2.0 mg·L⁻¹ 6-BA + 0.5 mg·L⁻¹ naphthylacetic acid (NAA) resulted in a differentiation frequency of 83.33%. The optimal PGR combinations for shoot proliferation were 1.5 mg·L⁻¹ 6-BA + 0.1 mg·L⁻¹ NAA and 0.5 mg·L⁻¹ 6-BA + 0.2 mg·L⁻¹ NAA. The optimal rooting media were MS medium supplemented with 0.1, 0.2, or 0.5 mg·L⁻¹ indole-3-butyric acid (IBA) or 1/2MS medium supplemented with 0.1 mg·L⁻¹ IBA. Additionally, this study investigated the dynamic changes in endogenous hormones during the regeneration process. The levels and ratios of hormones, including gibberellin (GA₃), abscisic acid (ABA), indole-3-acetic acid (IAA), and zeatin (ZT), collectively regulated the regeneration process. Elevated levels of ABA and GA₃ may promote callus initiation as well as the growth and development of adventitious roots during the early induction stage. Reduced levels of ABA and IAA favored callus differentiation into shoots, whereas elevated GA₃ levels facilitated proliferation of adventitious shoots. Throughout the regeneration process, fluctuations in ZT levels remained relatively stable. This study successfully established an in vitro regeneration system for M. dodecandrum using leaf explants, providing theoretical guidance and technical support for further molecular breeding efforts, genetic transformation, and industrial development. Full article

Background/Objectives: The resistance mutations EGFR^{L858R/T790M/C797S} in epidermal growth factor receptor (EGFR) are key factors in the reduced efficacy of Osimertinib. Predicting the inhibitory effects of Osimertinib derivatives against these mutations is crucial for the development of more effective inhibitors. This study aims to predict the inhibitory effects of Osimertinib derivatives against EGFR^{L858R/T790M/C797S} mutations. Methods: Six models were established using heuristic method (HM), random forest (RF), gene expression programming (GEP), gradient boosting decision tree (GBDT), polynomial kernel function support vector machine (SVM), and mixed kernel function SVM (MIX-SVM). The descriptors for these models were selected by the heuristic method or XGBoost. Comprehensive learning particle swarm optimizer was adopted to optimize hyperparameters. Additionally, the internal and external validation were performed by leave-one-out cross-validation ($Q_{LOO}^2$), 5-fold cross validation ($Q_{5-fold}^2$) and concordance correlation coefficient (CCC), $Q_{F1}^2$, and $Q_{F2}^2$. The properties of novel EGFR inhibitors were explored through molecular docking analysis. Results: The model established by MIX-SVM whose kernel function is a convex combination of three regular kernel functions is best: $R^2$ and RMSE for training set and test set are 0.9445, 0.1659 and 0.9490, 0.1814, respectively; $Q_{LOO}^2$, $Q_{5-fold}^2$, CCC, $Q_{F1}^2$, and $Q_{F2}^2$ are 0.9107, 0.8621, 0.9835, 0.9689, and 0.9680. Based on these results, the IC₅₀ values of 162 newly designed compounds were predicted using the HM model, and the top four candidates with the most favorable physicochemical properties were subsequently validated through PEA. Conclusions: The MIX-SVM method will provide useful guidance for the design and screening of novel EGFR^{L858R/T790M/C797S} inhibitors. Full article

When non-functioning pituitary adenomas (NFPAs) behave aggressively or recur after first-line surgical treatment, it can be challenging to decide whether and how to escalate therapy. Up to 47% of patients with residual tumor after transsphenoidal surgery will show disease recurrence or progression and may require an intervention. Repeat surgical resection can be attempted in select cases if the tumor is accessible; for the remainder of patients, non-surgical treatment options may need to be considered. Radiotherapy can control tumor growth in 75% of NFPAs, but confers increased risk of hypopituitarism and other disorders. Currently, there are no medical therapies approved for patients with recurrent or aggressive NFPA. However, several have been investigated, including temozolomide, somatostatin receptor ligands, dopamine agonists, immune checkpoint inhibitors, vascular endothelial growth factor inhibitors, and peptide receptor radionuclide therapy. We present a review of the available evidence to provide guidance for pituitary endocrinologists and neuro-oncologists when treating patients with recurrent or aggressive NFPA. Full article

The enhancement of flavonoid content and antioxidant capacity in plants remains a significant area of focus in the investigation of plant-derived functional foods. This study systematically investigated the impact of exogenous zinc sulfate (5 mM ZnSO₄) stress on flavonoid content and antioxidant capacity in finger millet (Eleusine coracana L.) sprouts, along with its underlying molecular mechanisms. The results demonstrated that treatment with 5 mM ZnSO₄ significantly increased the flavonoid content in sprouts, reaching a maximum value of 5.59 μg/sprout on the 6th day of germination. ZnSO₄ stress significantly enhanced the activities of PAL, 4CL, and C4H, while also considerably upregulating the expression levels of flavonoid-biosynthesis-related genes. Physiological indicators revealed that ZnSO₄ stress increased the contents of malondialdehyde, hydrogen peroxide, and superoxide anion in the sprouts, while inhibiting sprout growth. As a stress response, ZnSO₄ stress enhances the antioxidant system by increasing antioxidant capacity (ABTS, DPPH, and FRAP), antioxidant enzyme activity (POD and SOD), and related gene expression (POD, CAT, and APX) in sprouts. This study provides experimental evidence for ZnSO₄ stress to improve flavonoid accumulation and antioxidant capacity in finger millet sprouts and provides important theoretical and practical guidance for the development of high-quality functional foods. Full article

The Qinghai–Tibetan Plateau (QTP), often referred to as the “Third Pole” of the world, harbors alpine grassland ecosystems that play an essential role as global carbon sinks, helping to mitigate the pace of climate change. Nonetheless, alterations in natural environmental conditions coupled with escalating human activities have disrupted the seasonal growth cycles of grasslands, thereby intensifying degradation processes. To date, the key drivers and lifecycle dynamics of Grassland Depletion across the QTP remain contentious, limiting our comprehension of its ecological repercussions and regulatory mechanisms. This study comprehensively investigates grassland degradation on the Qinghai–Tibetan Plateau, analyzing its drivers and changes in ecological suitability during the growing season. By integrating natural factors (e.g., precipitation and temperature) and anthropogenic influences (e.g., population density and grazing intensity), it examines observational data from over 160 monitoring stations collected between the 1980s and 2020. The findings reveal three distinct phases of grassland degradation: an acute degradation phase in 1990 (GDI, Grassland Degradation Index = 2.53), a partial recovery phase from 1996 to 2005 (GDI < 2.0) during which the proportion of degraded grassland decreased from 71.85% in 1990 to 51.22% in 2005, and a renewed intensification of degradation after 2006 (GDI > 2.0), with degraded grassland areas reaching 56.39% by 2020. Among the influencing variables, precipitation emerged as the most significant driver, interacting closely with anthropogenic factors such as grazing practices and population distribution. Specifically, the combined impacts of precipitation with population density, grazing pressure, and elevation were particularly notable, yielding interaction q-values of 0.796, 0.767, and 0.752, respectively. Our findings reveal that while grasslands exhibit superior carbon sink potential relative to forests, their productivity and ecological functionality are undergoing considerable declines due to the compounded effects of multiple interacting factors. Consequently, the spatial distribution of ecologically suitable zones has contracted significantly, with the remaining high-suitability regions concentrating in the “twin-star” zones of Baingoin and Zanda grasslands, areas recognized as focal points for future ecosystem preservation. Furthermore, the effects of climate change and intensifying anthropogenic activity have driven the reduction in highly suitable grassland areas, shrinking from 41,232 km² in 1990 to 24,485 km² by 2020, with projections indicating a further decrease to only 2844 km² by 2060. This study sheds light on the intricate mechanisms behind Grassland Depletion, providing essential guidance for conservation efforts and ecological restoration on the QTP. Moreover, it offers theoretical underpinnings to support China’s carbon neutrality and peak carbon emission goals. Full article

A primary expectation of college is that students in all majors and disciplines will learn content, skills, and knowledge that support individual growth, job placement, or continued academic endeavors. In short, being a student implies an expectation to learn. Effective learning directly impacts student academic success, and this success has downstream effects on student retention and graduation rates. However, the process of learning is often taken for granted, and, too often, student learning is not successful because students have not received any guidance on the methods of effective learning. Across higher education, students are often left on their own to learn about learning, and their improvised methods frequently involve ineffective techniques such as cramming for exams or rereading assigned materials without deeper engagement. To counter such observations, the University of Iowa implemented a campus-wide learning framework, Learning at Iowa. The initiative is grounded in empirically validated practices from the cognitive and learning sciences, which have been organized around the Three Ms: mindset, metacognition, and memory. This article briefly reviews the relevant literature supporting each of the Three Ms and then discusses the implementation of the framework with students, student-facing staff, and instructors and how the framework supports effective educational practices. Full article

In this study, we propose a method for systematic nanowire length control through the precise control of the polyvinylpyrrolidone (PVP) concentration during the synthesis of tellurium nanowires. Furthermore, we report the changes in the electrical properties of thin-film transistor (TFT) devices with different lengths of synthesized tellurium nanowires used as channels. Through the use of scanning electron microscopy (SEM) and atomic force microscopy (AFM), it was determined that the length of the wires increased in relation to the amount of PVP incorporated, while the diameter remained consistent. The synthesized long wires formed a well-connected percolation network with a junction density of 4.6 junctions/µm², which enabled the fabrication of devices with excellent electrical properties, the highest on/off ratio of 10³, and charge mobility of 1.1 cm²/V·s. In contrast, wires with comparatively reduced PVP content demonstrated a junction density of 2.1 junctions/µm², exhibiting a lower on/off ratio and reduced charge mobility. These results provide guidance on how the amount of PVP added during wire growth affects the length of the synthesized wires and how it affects the connectivity between the wires when they form a network, which may help optimize the performance of high-performance nanoelectronic devices. Full article

The increasing complexity of urban structures has significantly elevated the risk and severity of façade fires in high-rise buildings. Unlike traditional models assuming continuous fuel beds, real-world fire scenarios often involve discrete combustible materials arranged in discrete fuel matrices. This study presents a systematic investigation into the influence of lateral spacing on vertical flame propagation behavior. Laboratory-scale experiments were conducted using vertically oriented polymethyl methacrylate (PMMA) fuel arrays under nine different spacing configurations. Results reveal that lateral spacing plays a critical role in determining flame spread paths and intensities. Specifically, with a vertical spacing fixed at 8 cm, a lateral spacing of 10 mm resulted in rapid flame growth, reaching a peak flame height of approximately 96.5 cm within 450 s after ignition. In contrast, increasing the lateral spacing to 15 mm significantly slowed flame development, achieving a peak flame height of just under 90 cm at approximately 600 s. This notable transition in flame dynamics is closely associated with the critical thermal boundary layer thickness (~11.5 mm). Additionally, at 10 mm spacing, a chimney-like effect was observed, enhancing upward air entrainment and resulting in intensified combustion. These findings reveal the coupled influence of geometric configuration and heat transfer mechanisms on façade flame propagation. The insights gained provide guidance for cladding system design, suggesting that increasing lateral separation between combustible elements may be an effective strategy to limit flame spread and enhance fire safety performance in buildings. Full article

As a pivotal model organism in Lepidoptera research, the silkworm (Bombyx mori) holds significant importance in life science due to its economic value and biotechnological applications. Advancements in proteomics and bioinformatics have enabled substantial progress in characterizing the B. mori proteome. Systematic screening and identification of protein–protein interactions (PPIs) have progressively elucidated the molecular mechanisms governing key biological processes, including viral infection, immune regulation, and growth development. This review comprehensively summarizes traditional PPI detection techniques, such as yeast two-hybrid (Y2H) and immunoprecipitation (IP), alongside emerging methodologies such as mass spectrometry-based interactomics and artificial intelligence (AI)-driven PPI prediction. We critically analyze the strengths, limitations, and technological integration strategies for each approach, highlighting current field challenges. Furthermore, we elaborate on the molecular regulatory networks of Bombyx mori nucleopolyhedrovirus (BmNPV) from multiple perspectives: apoptosis and cell cycle regulation; viral protein invasion and trafficking; non-coding RNA-mediated modulation; metabolic reprogramming; and host immune evasion. These insights reveal the dynamic interplay between viral replication and host defense mechanisms. Collectively, this synthesis aims to provide a robust theoretical foundation and technical guidance for silkworm genetic improvement, infectious disease management, and the advancement of related biotechnological applications. Full article

The Adaptive Cross Ivy (ACIVY) algorithm is a novel bio-inspired metaheuristic that emulates ivy plant growth behaviors for complex optimization problems. While the original Ivy Optimization Algorithm (IVYA) demonstrates a competitive performance, it suffers from limited inter-individual information exchange, inadequate directional guidance for local optima escape, and abrupt exploration–exploitation transitions. To address these limitations, ACIVY integrates three strategic enhancements: the crisscross strategy, enabling horizontal and vertical crossover operations for improved population diversity; the LightTrack strategy, incorporating positional memory and repulsion mechanisms for effective local optima escape; and the Top-Guided Adaptive Mutation strategy, implementing ranking-based mutation with dynamic selection pools for smooth exploration–exploitation balance. Comprehensive evaluations on the CEC2017 and CEC2022 benchmark suites demonstrate ACIVY’s superior performance against state-of-the-art algorithms across unimodal, multimodal, hybrid, and composite functions. ACIVY achieved outstanding average rankings of 1.25 (CEC2022) and 1.41 (CEC2017 50D), with statistical significance confirmed through Wilcoxon tests. Practical applications in engineering design optimization and UAV path planning further validate ACIVY’s robust performance, consistently delivering optimal solutions across diverse real-world scenarios. The algorithm’s exceptional convergence precision, solution reliability, and computational efficiency establish it as a powerful tool for challenging optimization problems requiring both accuracy and consistency. Full article

In the context of the explosive growth of the digital economy, how inter-organizational connectivity affects corporate ambidextrous innovation has emerged as a pressing issue in the current digital economy. Based on the perspectives of the innovation ecosystem and digital coupling, this paper explores the inner mechanism of this issue through structural modeling by using the data of China’s high-tech enterprise alliance cooperation from 2015 to 2022. It is found in the empirical study that the local efficiency and reach rate of the digital innovation ecosystem have an inverted U-shaped relationship with exploratory innovation, and the local efficiency and reach rate of the digital innovation ecosystem have a negative effect on firm exploitative innovation. In addition, the level of firms’ digital transformation mediates the relationship between the local efficiency, reach rate, and ambidextrous innovation. The level of market development plays a moderating role in the relationship between the local efficiency, reach rate, and ambidextrous innovation. The findings provide a theoretical basis for the digital innovation ecosystem to realize the role of a “resource pool” through structural connections, which in turn provides important guidance for the digital transformation and innovation development of high-tech enterprises. Full article

Nitrogen (N) is one of the most important nutrients determining crop growth performance. With the increasing demand for sustainability in global agriculture, improving nitrogen use efficiency in rice has become a critical issue. Nitrogen use efficiency (NUE) in rice is a complex trait influenced by multiple factors, among which phytohormones play a key role. NUE is primarily regulated through the influence of phytohormones on absorption, transport, assimilation, and utilization processes. In this review, we focus on these interactions and summarize the relationships between major hormones and nitrogen use efficiency in rice. Finally, we outline the current challenges and future research prospects in this field. Although studies have shown promising results for their role in improving crop NUE, the specific mechanisms remain unclear. Additionally, the interactions among phytohormones and the influence of environmental factors on their effectiveness require further investigation. This review provides theoretical support and technical guidance for understanding the role of phytohormones in rice NUE and offers insights into improving NUE in rice. Full article

With the increasing application of hyperspectral technology, rapid and accurate monitoring of cotton leaf nitrogen concentrations (LNCs) has become an effective tool for large-scale areas. This study used Tahe No. 2 cotton seeds with four nitrogen levels (0, 200, 350, 500 kg ha⁻¹) and four phosphorus levels (0, 100, 200, 300 kg ha⁻¹). Spectral data were acquired using an ASD FieldSpec HandHeld2 portable spectrometer, which measures spectral reflectance covering a band of 325–1075 nm with a spectral resolution of 1 nm. LNCs determination and spectral estimation were conducted at six growth stages: squaring, initial bloom, peak bloom, initial boll, peak boll, and boll opening. Thirty-seven spectral indices (SIs) were selected. First derivative (FD), standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky–Golay (SG) were applied to preprocess the spectra. Feature bands were screened using partial least squares discriminant analysis (PLS–DA), and support vector machine (SVM) and random forest (RF) models were used for accuracy validation. The results revealed that (1) LNCs initially increased and then decreased with growth, peaking at the full-flowering stage before gradually declining. (2) The best LNC recognition models were SVM–MSC in the squaring stage, SVM–FD in the initial bloom stage, SVM–FD in the peak bloom stage, SVM–FD in the initial boll stage, RF–SNV in the peak boll Mstage, and SVM–FD in the boll opening stage. FD showed the best performance compared with the other three treatments, with SVM outperforming RF in terms of higher R² and lower RMSE values. The SVM–FD model effectively improved the accuracy and robustness of LNCs prediction using hyperspectral leaf spectra, providing valuable guidance for large-scale information production in high-standard cotton fields. Full article

Hydrogen has gradually become one of the indispensable sources of energy for mankind. Since the discovery of hydrogen embrittlement (hydrogen-induced degradation of material properties) more than 100 years ago, fatigue properties in hydrogen environments have been studied. Fatigue crack growth of materials in a hydrogen environment is a complex process involving the interaction of multiple factors. Hydrogen binds to atoms within the material, leading to diffusion and aggregation of hydrogen atoms, which causes an increase in internal stresses. These stresses may concentrate at the crack tip, accelerating the rate of crack expansion and leading to fatigue fracture of the material. The work of current researchers has summarised a number of fatigue models to help understand this phenomenon. This paper firstly summarises the existing hydrogen embrittlement mechanisms as well as hydrogen embrittlement experiments. It then focuses on the mechanism of fatigue crack propagation in hydrogen environments and related literature. It also analyses and summarises a cluster diagram of the literature generated using CiteSpace. The fatigue life prediction methods for materials in hydrogen environment are then summarised in this paper. It aims to provide some guidance for the selection and design of materials in developing fields such as fatigue materials in hydrogen environment. Finally, challenges in the current research on the fatigue properties of materials under hydrogen embrittlement conditions are pointed out and discussed to guide future research efforts. Full article