Growth Pattern Research Articles

Subgrading of G2 Pancreatic Neuroendocrine Tumors as 2A (Ki67 3% to < 10%) Versus 2B (10% to ≤ 20%) Identifies Behaviorally Distinct Subsets in Keeping with the Evolving Management Protocols.

Grade 1/2 PanNETs are mostly managed similarly, typically without any adjunct treatment with the belief that their overall metastasis rate is low. In oncology literature, Ki67-index of 10% is increasingly being used as the cutoff in stratifying patients to different protocols, although there are no systematic pathology-based studies supporting this approach. Ki67-index was correlated with clinicopathologic parameters in 190 resected PanNETs. A validation cohort (n = 145) was separately analyzed. In initial cohort, maximally selected rank statistics method revealed 12% to be the discriminatory cutoff (close to 10% rule of thumb). G2b cases had liver/distant metastasis rate of almost threefold higher than that of G2a and showed significantly higher frequency of all histopathologic signs of aggressiveness (tumor size, perineural/vascular invasion, infiltrative growth pattern, lymph node metastasis). In validation cohort, these figures were as striking. When all cases were analyzed together, compared with G1, the G2b category had nine times higher liver/distant metastasis rate (6.1 vs. 58.5%; p < 0.001) and three times higher lymph node metastasis rate (20.5 vs. 65.1%; p < 0.001). G2b PanNETs act very similar to G3, supporting management protocols that regard them as potential therapy candidates. Concerning local management, metastatic behavior in G2b cases indicate they may not be as amenable for conservative approaches, such as watchful waiting or enucleation. This substaging should be considered into diagnostic guidelines, and clinical trials need to be devised to determine the more appropriate management protocols for G2b (10% to ≤ 20%) group, which shows liver/distant metastasis in more than half of the cases, which at minimum warrants closer follow-up.

Forest and soil fungal community dynamics are fuelled by root rot pathogen‐induced gaps

Abstract Forest dynamics are driven by micro‐disturbances leading to gap formation. Root rot pathogens can cause mortality to adult trees, which die forming gaps. However, little is known about the biotic and abiotic factors that govern gap creation and expansion such as tree infection or drought resilience, and what are the consequences for nutrient cycling and soil microbiota. We studied the dynamics of gaps created by Heterobasidion abietinum in mountain silver fir (Abies alba) forests from the Spanish Central Pyrenees. Tree‐ring width information was used to evaluate growth patterns of trees located within and at the edge of gaps and under closed canopy conditions. We analysed soil nutrient content and microbial structure at different positions with respect to the gap. Soil fungal community was also characterized by sequencing the ITS2 region. Gaps created by H. abietinum ranged 582–1072 m2 and gathered large amounts of standing and laying dead wood biomass amounting to up to 500 m3 ha−1 of coarse woody debris. This indicates that tree mortality had been occurring over decades, and it was preceded by a long‐term growth decline and impaired drought resilience. Root rot affected trees beyond the current limit of the gaps leading to growth decline, preventing canopy closure and allowing the release of suppressed trees within the gap. Gap formation did neither affect soil fertility nor fungal and bacterial biomass and diversity, but long‐distance ectomycorrhizal fungi were more abundant within gaps. Synthesis. Root rot pathogens play key ecological roles in forest dynamics at fine spatial scale. Heterobasidion abietinum infection, and its interaction with drought, creates and expands gaps by killing large trees and preventing surrounding trees from closing the gap. The survival of mycorrhizal networks to gap formation suggests little disruption of soil fungal communities.

Correlation of Zinc and Copper Levels In Mothers and Cord Blood of Neonates With Prematurity and Intrauterine Growth Pattern

Correlation of Zinc and Copper Levels In Mothers and Cord Blood of Neonates With Prematurity and Intrauterine Growth Pattern

Assessment of hard and soft tissue thickness at mandibular symphysis in skeletal Class III patients with different vertical patterns.

This study aimed to assess the bony and soft tissue parameters at mandibular symphysis among skeletal Class III patients with different vertical growth patterns, using cone-beam computed tomography (CBCT). CBCT images of 60 skeletal Class III non-growing patients were evaluated (mean age 24.9 ± 8.4 years). Study samples were classified into three facial types based on the mandibular plane angle (SN-MP angle): low, normal, and high angle. The bony and soft tissue parameters at the mandibular symphysis were evaluated. Among hard tissue variables, symphysis and pogonion width were significantly narrower in the high-angle group (P < .05). The thickness of the buccal cortex at pogonion was also significantly thinner in subjects with high angles (P < .01). Symphysis height showed an increasing tendency from the low-angle to the high-angle group. However, no significant differences were found in chin width and height according to vertical patterns. Across all soft tissue measurements, the low-angle group exhibited the highest thickness, which gradually decreased in the high-angle group. Statistically significant differences in soft tissue thickness were observed at Menton (Me) and Gnathion (Gn) (P < .05). A significant negative correlation was observed between the SN-MP angle and the thickness of both hard and soft tissues. In skeletal Class III subjects, significant differences existed in both hard and soft tissues at the mandibular symphysis, depending on the vertical patterns. These results provide a comprehensive evaluation of symphyseal area, which can aid clinicians in identifying appropriate treatment approaches, especially for combined orthognathic and orthodontic treatment.

Small AAAs: Recommendations for Rodent Model Research for the Identification of Novel Therapeutics.

Most abdominal aortic aneurysms (AAAs) are small with low rupture risk (<1%/y) when diagnosed but slowly expand to ≥55 mm and undergo surgical repair. Patients and clinicians require medications to limit AAA growth and rupture, but drugs effective in animal models have not translated to patients. Use models that simulate human AAA tissue pathology, growth patterns, and rupture; focus on the clinically relevant outcomes of growth and rupture; design studies with the rigor required of human clinical trials; monitor AAA growth using reproducible ultrasound; and perform studies in both males and females. The aortic adventitial elastase oral β-aminopropionitrile model has many strengths including simulating human AAA pathology and modeling prolonged aneurysm growth. The Ang II (angiotensin II) model performed less well as it better simulates acute aortic syndrome than AAA. The elastase plus TGFβ (transforming growth factor-β) blocking antibody model displays a high rupture rate, making prolonged monitoring of AAA growth not feasible. The elastase perfusion and calcium chloride models both display limited AAA growth.

Pathologic features of head and neck adult rhabdomyosarcoma: Case series

IntroductionAdult Head and neck Rhabdomyosarcomas (HNRMS) are exceedingly rare and remain challenging for pathologists. Cases presentationFive cases of adult HNRMS (≥19 years) were retrieved from the archives of the Department of Pathology of Hospital of Specialities in Rabat (HSR) in Morocco, over 5 years. Clinical and pathologic findings from hematoxylin and eosin slides and immunohistochemistry for Desmin and Myogenin were reviewed. Clinical discussionThe median age was 33, with a men's predominance (3 M/2F). Histological analysis revealed three cases of Alveolar Rhabdomyosarcoma (RMS), one Pleomorphic RMS, and one spindle cell/sclerosing RMS. In addition to the typical histology observed in each RMS, we found tricky growth patterns that could be a source of misdiagnosis. All five cases demonstrated variable positivity for Desmin and Myogenin. ConclusionHNRMS cases have different pathological features than pediatric RMS cases. We identified rare subtypes such as pleomorphic and spindle cell/sclerotic RMS, which exhibit unusual morphological patterns.

Evaluating the economic and climate adaptation benefits of land conservation strategies in urban coastal regions of the U.S. and China

Land conservation has been recognized as a multifunctional adaptive strategy to tackle climate change as it includes the ability to mitigate risk and enhance biodiversity. However, limited empirical studies focus on the climatic adaptive functions of land conservation. Employing various geospatial and statistical techniques, including remote sensing, logistic regression, and landscape metrics, we investigate the effects of land conservation’s spatial characteristics. These characteristics affect the functional efficacy of climate adaptation in urban coastal regions, influencing regional economic vitality in the United States and China. Empirical results indicate that regional economic vitality is positively affected by parks and grassland, patch growth patterns, higher urban density, and closer proximities to coastlines and major roads. In contrast, the core growth form of land conservation has a negative economic effect. Among the estimated variables, we find that the patch growth form of land conservation and closer proximity to higher urban density have the largest positive effects on economic vitality across the study sites. Our findings contribute to both land conservation policy and the climate change literature by uncovering the spatially explicit effects of land conservation related to climate change adaptation.

Introgression affects Salmo trutta juvenile life-history traits generations after stocking with non-native strains.

Introgression of non-native conspecifics changes the genetic composition of wild populations, potentially leading to loss of local adaptations and fitness declines. However, long-term data from wild populations are still relatively few. Here, we studied the effects of introgression in a Danish brown trout (Salmo trutta, L.) population, subjected to intensive stocking with domesticated hatchery fish of non-native origin. We used wild-caught genetically wild and admixed trout as well as fish from the partly domesticated hatchery strain used for stocking the river up until ~15 years prior to this study, to produce 22 families varying in hatchery/wild admixture. Following a replicated common-garden experiment conducted in fish tanks from first feeding through 23 weeks at 7, 12, and 16°C, we observed a significant positive relationship between family admixture and fish size upon termination, an effect observed through all levels of admixture. Furthermore, the admixture effect was most distinct at the higher rearing temperatures. Although the hatchery strain used for stocking had been in culture for ~7 generations, it had not been deliberately selected for increased growth. These data thus demonstrate: (i) that growth had increased in the hatchery strain even in the absence of deliberate directional selection for this trait, (ii) that the increasing effect of admixture by temperature could represent inadvertent selection for performance in the hatchery strain at higher temperatures, and most significantly, (iii) that despite undergoing up to five generations of natural selection in the admixed wild population, the genetically increased growth potential was still detectable and thus persistent. Our findings suggest that altered growth patterns and potentially their cascading effects are of importance to the severity of hatchery/wild introgression, especially under changing-climate scenarios and are of general significance to conservation practitioners seeking to evaluate long-term effects of intra-specific hybridization including under recovery.

Comments by Nam Seok Kim, on How Does Trade Liberalization in Imports Affect China's Export Growth Pattern?

Comments by Nam Seok Kim, on How Does Trade Liberalization in Imports Affect China's Export Growth Pattern?

How Does Trade Liberalization in Imports Affect China's Export Growth Pattern?

Abstract Optimizing export growth patterns and improving the quality of export trade have become prominent issues that need to be addressed urgently in the context of increasing global economic uncertainty. This study utilizes matched data from the CEPII database (1995–2020) and WTO tariff database, adopts a product-level perspective based on the triple margins of exports, and uses an individual-time two-way fixed-effects model to investigate the impact of import trade liberalization on China's export growth pattern. The research findings are as follows: (1) Increasing levels of import trade liberalization are beneficial for enhancing the extensive margin, intensive margin, and quantity margin of products, while exerting a restraining effect on the price margin. This strengthens the price advantage of Chinese products, indicating that import trade liberalization helps optimize China's export growth pattern. (2) Compared with the intensive margin, import trade liberalization has a more significant promoting effect on the extensive margin. (3) The conclusions drawn from heterogeneity analysis suggest that trade liberalization has a more pronounced effect on the extensive margin, intensive margin, and quantity margin of products in medium-high technology industries, differentiated products, and intermediate goods. This study holds important theoretical and practical significance for evaluating the economic benefits of expanding imports, optimizing China's export growth pattern, and improving the quality of export trade.

Pertumbuhan dan Mortalitas Ikan Kuro (Eleutheronema tetradactylum) yang Didaratkan di Pelabuhan Perikanan Nusantara Kabupaten Merauke

This research aimed to determine the size structure, length-weight relationship, growth, and mortality of kuro fish (Eleutheronema tetradactylum) that landed on Nusantara Fishery Harbour, Merauke District. The samples were taken off in August-October 2022 at Nusantara Fishery Harbour, Merauke District. The metusedsing was a purposive sampling method. The measured data was the total length and weight body of kuro fish. The size structure and length-weight relationship of kuro fish were analyzed using Microsoft Excel. Meanwhile, the growth and mortality were analyzed using the FISAT II application. The result analysis shows that the range of E. tetradactylum total length landed on Nusantara Fishery Harbour is 430 – 1030 mm with a weight range of 92 – 3613 grams. The length-weight relationship of E. tetradactylum has the allometric negative growth pattern with equation W = 0,0016L2,1167 in August, W = 0,0017L2,1134 in September, and W = 0,0017L2,1077 in October. The analysis of E. tetradactylum’s growth parameter shows the value L∞ = 1053 mm, K = 0,51/year, and t₀ = -0,1201 year. The result mortality analysis of E. tetradactylum shows the total mortality (Z) was 0,78/ year, natural mortality was 0,43/year, fishing mortality (F) was 0,35/year, and exploitation rate was 0,45/year.

Comparative analysis of pediatric rheumatic patient growth patterns against norms: A cross-sectional study conducted in an Eastern Indian hospital

Background. Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease. Rheumatic diseases are a major cause of chronic illness in children around the world. SLE is a further prevalent inflammatory illness. Aims and objectives. To study different growth parameters of pediatric patients attending pediatric rheumatology clinic, to compare the growth parameters with age and sex matched controls and to compare growth among different types of pediatric rheumatic patients. Method. Different growth parameters and SMI (for children above 9 years) were recorded for patients attending pediatric rheumatology OPD having disease duration more than one year. Results. Among 121 patients, JIA was most common followed by SLE. Among JIA subtypes, SOJIA is most common. Mean age of presentation was earlier in SOJIA, late in JoAS. SLE patients had larger duration of illness prior to diagnosis than JIA patients. In JIA patients, mean height was significantly less than controls. SOJIA and polyarticular variety had significantly less weight and height compared to controls. SLE patients had significantly less weight and height compared to control. Anthropometric parameters were significantly more in SLE patients compared to JIA cohort. There was significantly more delayed puberty both in JIA and SLE patients compared to controls. Conclusion. JIA was most common, followed by SLE. Among JIA patients SOJIA variety was most common, JIA patients had significantly lower height than controls. SLE patients had significantly lower weight and height than controls. Delayed puberty was significantly more in both JIA and SLE patients compared to controls.

Probiotic Growth Pattern and Physicochemical Evaluation of Water Kefir Fermentation

Probiotics are live-friendly microorganisms that can confer a health benefit on the host if it is consumed in sufficient amounts. Water kefir is a probiotic-rich fermented beverage that contains multi-species of live cultures. Brown sugar and palm sugar were used for water kefir fermentation due to their high sucrose and mineral contents. The objective of this study was to determine the probiotic growth pattern of water kefir and to evaluate the physicochemical parameters, including the pH changes, lactic acid content, reducing sugar content, and total soluble solids. The fermented water kefir was collected at every 6-hour interval, until the end of 72 hours of fermentation. The growth curve was determined by enumerated probiotics on De Man, Rogosa, and Sharpe (MRS) agar, Yeast Extract-Peptone-Dextrose (YPD) agar, and Gluconobacter (GM) agar plates, respectively. MRS, YPD, and GM agar plates were used to enumerate lactic acid bacteria, yeast, and acetic acid bacteria, respectively. The result showed increased probiotic growth as fermentation time increased with different phases observed from the growth curve. The stationary phase of probiotics was recorded at 30-42 h and was recommended as the optimal harvesting point. Besides, longer fermentation time produced lower pH values and lower total soluble solids while higher lactic acid and higher reducing sugars. At the end of fermentation, the concentration of lactic acid and reducing sugars were 2.16 ± 0.09 g/L and 13.66 ± 0.14 mg/mL, respectively. In conclusion, probiotics from water kefir fermentation are suggested to be best harvested between 30-42 hours and can be used for self-consume or downstream processing.

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud

Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in the miniaturization of sensors and platforms, contemporary remote sensing offers data at resolutions finer enough to respond to within-farm variations. LiDAR point cloud, offers features amenable to modelling structural parameters of crops. Early prediction of crop growth parameters helps farmers and other stakeholders dynamically manage farming activities. The objective of this work is the development and application of a deep learning framework to predict plant-level crop height and crown area at different growth stages for vegetable crops. LiDAR point clouds were acquired using a terrestrial laser scanner on five dates during the growth cycles of tomato, eggplant and cabbage on the experimental research farms of the University of Agricultural Sciences, Bengaluru, India. We implemented a hybrid deep learning framework combining distinct features of long-term short memory (LSTM) and Gated Recurrent Unit (GRU) for the predictions of plant height and crown area. The predictions are validated with reference ground truth measurements. These predictions were validated against ground truth measurements. The findings demonstrate that plant-level structural parameters can be predicted well ahead of crop growth stages with around 80% accuracy. Notably, the LSTM and the GRU models exhibited limitations in capturing variations in structural parameters. Conversely, the hybrid model offered significantly improved predictions, particularly for crown area, with error rates for height prediction ranging from 5 to 12%, with deviations exhibiting a more balanced distribution between overestimation and underestimation This approach effectively captured the inherent temporal growth pattern of the crops, highlighting the potential of deep learning for precision agriculture applications. However, the prediction quality is relatively low at the advanced growth stage, closer to the harvest. In contrast, the prediction quality is stable across the three different crops. The results indicate the presence of a robust relationship between the features of the LiDAR point cloud and the auto-feature map of the deep learning methods adapted for plant-level crop structural characterization. This approach effectively captured the inherent temporal growth pattern of the crops, highlighting the potential of deep learning for precision agriculture applications.

Diverging growth trends and climate sensitivities of individual pine trees after the 1976 extreme drought

Summer droughts are affecting the productivity and functioning of central European forests, with potentially lasting consequences for species composition and carbon sequestration. Long-term recovery rates and individual growth responses that may diverge from species-specific and population-wide behaviour are, however, poorly understood. Here, we present 2052 pine (Pinus sylvestris) ring width series from 19 forest sites in south-west Germany to investigate growth responses of individual trees to the exceptionally hot and dry summer of 1976. This outstanding drought event presents a distinctive test case to examine long-term post-drought recovery dynamics. We have proposed a new classification approach to identify a distinct sub-population of trees, referred to as “temporarily affected trees”, with a prevalence ranging from 9 to 33 % across the forest stands. These trees exhibited an exceptionally prolonged growth suppression, lasting over a decade, indicating significantly lower resilience to the 1976 drought and a 50 % reduced capacity to recover to pre-drought states. Furthermore, shifts in resilience and recovery dynamics are accompanied by changing climate sensitivities, notably an increased response to maximum temperatures and summer droughts in post-1976 affected pines. Our findings underscore the likely interplay between individual factors and micro-site conditions that contribute to divergent tree responses to droughts. Assessing these factors at the individual tree level is recommended to advancing our understanding of forest responses to extreme drought events. By analyzing sub-population growth patterns, our study provides valuable insights into the impacts of summer droughts on central European forests in context of increasing drought events.

Core regions in immunoglobulin heavy chain enhancers essential for survival of non-Hodgkin lymphoma cells are identified by a CRISPR interference screen.

Chromosomal translocations in non-Hodgkin lymphoma (NHL) result in activation of oncogenes by placing them under the regulation of immunoglobulin heavy chain (IGH) super-enhancers. Aberrant expression of translocated oncogenes induced by enhancer activity can contribute to lymphomagenesis. The role of the IGH enhancers in normal B-cell development is well established, but knowledge regarding the precise mechanisms of their involvement in control of the translocated oncogenes is limited. The goal of this project was to define the critical regions in the IGH regulatory elements and identify enhancer RNAs (eRNA). We designed a sgRNA library densely covering the IGH enhancers and performed tiling CRISPR interference screens in three NHL cell lines. This revealed three regions crucial for NHL cell growth. With chromatin-enriched RNA-Seq we showed transcription from the core enhancer regions and subsequently validated expression of the eRNAs in a panel of NHL cell lines and tissue samples. Inhibition of the essential IGH enhancer regions decreased expression of eRNAs and translocated oncogenes in several NHL cell lines. The observed expression and growth patterns were consistent with the breakpoints in the IGH locus. Moreover, targeting the Eμ enhancer resulted in loss of B-cell receptor expression. In a Burkitt lymphoma cell line, MYC overexpression partially rescued the phenotype induced by IGH enhancer inhibition. Our results indicated the most critical regions in the IGH enhancers and provided new insights into the current understanding of the role of IGH enhancers in B-cell NHL. As such, this study forms a basis for development of potential therapeutic approaches.

An adaptive phase field approach to 3D internal crack growth in rocks

Modeling the 3D internal crack under compression entails complex fracture mechanics (mode I-II-III fracture), resulting in substantial computational costs and challenges in characterizing fracture morphology characterization for Phase Field Method (PFM) simulations. In the present paper, we developed a 3D adaptive crack propagation model integrated into the PFM to study the internal cracks in rocks. The proposed locally refined solution was implemented within the isogeometric analysis (IGA) framework, utilizing PHT-splines and employing the phase field variable as an error indicator to accurately capture non-smooth crack surfaces. The simulation begins with a coarser mesh, and the spatial discretization is adaptively refined in real-time as the computation progresses and the phase variable threshold is reached. By comparing our results with previous numerical tests, we validated the effectiveness of our model in simulating crack growth. Notably, a smaller length scale parameter led to a higher peak force in notched square plates under tension, and our adaptive PFM successfully reduced errors caused by length scale parameters. We further validated our model by comparing it with uniaxial compression experiments on 3D-printed resin samples with internal penny-shaped cracks, achieving good agreement with the experimental data. Using the 3D adaptive PFM, we predicted changes in crack morphology and fracturing mechanisms by varying the inclination angles of internal penny-shaped cracks. Our numerical results showed that as the inclination angle increased, wing cracks initiated closer to the end tips of the original crack, and their length decreased due to the wings wrapping effect. The corresponding fracturing mechanisms transition from mode I-III fracture (0°) to mode I-II-III fracture (30°, 45°, 60°), and eventually to mode I fracture (90°) as inclination angles increase. Comparing 2D and 3D models, we found that the growth of wing cracks in 3D was significantly influenced by the intermediate principal stress. We conclude that the extended 3D adaptive PFM-based model accurately predicted complex mechanical behavior and crack growth patterns in rock.

Similar climate–growth relationships but divergent drought resilience strategies in coexisting Mediterranean shrubs

Abstract Anticipating future impacts of climate warming and aridification on drylands requires understanding how coexisting woody plant species respond to climate variability. However, we lack knowledge of the growth resilience capacity of Mediterranean shrubs. Do coexisting trees and shrubs differ in their response to climate? Do coexisting shrub species have comparable post‐drought growth resilience? This study was conducted in two Mediterranean shrublands with sparse trees in semi‐arid north‐eastern Spain. We selected sites situated in formerly agricultural or grassland areas in two regions subjected to semi‐arid Mediterranean climate conditions. We sampled six shrubs' species (Juniperus phoenicea, Juniperus oxycedrus, Pistacia lentiscus, Pistacia terebinthus, Rhamnus lycioides and Rhamnus alaternus) and one tree species (Pinus halepensis) to measure their radial growth and to reconstruct their past growth patterns using dendrochronology. We quantified climate–growth relationships of trees and shrubs, as well as the growth resilience capacity after drought events of the six shrubs. Growth patterns differed between species but a prevalent trade‐off between growth and longevity was found. Growth responses to climate were comparable between species but differed between sites. Most species responded positively to precipitation and negatively to temperature. The most negative correlations of growth with drought severity were found at the driest Valcuerna site. Shrubs differed in their resilience capacity. Across sites, species were more resistant and resilient in Alcubierre, the wettest site. The shrubs P. terebinthus and R. lycioides were more resistant and resilient than the rest of species, which required longer growth recovery times and accumulated stronger growth reductions, particularly J. phoenicea. Synthesis. These results highlight the importance of drought as a driver of growth in Mediterranean scrublands. Growth resilience strategies differed between species with junipers being less resilient to drought than other coexisting shrubs. Further research should investigate how this difference in post‐drought resilience is related to functional traits, particularly those related with plant water‐use strategies.

Tracing the Evolution of E-Government: A Visual Bibliometric Analysis from 2000 to 2023

In the continuously evolving field of E-government, understanding the breadth and depth of academic research is crucial for advancing governmental digital transformation and policy development. This study employs visual bibliometric analysis, using the Web of Science database to map the evolution trajectory of E-government research from 2000 to 2023. By utilizing CiteSpace for a comprehensive examination of 4536 academic articles, this paper outlines the growth patterns and thematic evolution within the field. The development of the E-government field is delineated into four distinct phases: the budding period (2000–2003), the bottleneck period (2004–2014), the development period (2015–2018), and the growth period (2019–2023), which are each marked by unique thematic shifts and technological advancements. The research results reveal the transformation of research focus in different periods, from the initial focus on the technological means and the electronic transformation of government services, moving on to more complex issues such as E-government acceptance and government transparency and corruption, and ultimately to the current focus on innovation and smart cities. In addition, the paper also clarifies that the research boom that began in 2019 is driven by technological innovation opportunities, the improvement in infrastructure, and multidisciplinary research. By depicting these developmental stages and emerging trends, this study not only unveils past academic efforts but also forecasts future research directions, thereby providing valuable insights for researchers and policymakers aiming to understand and implement effective E-government strategies.

Energy inputs imprint seasonality and fractal structure on river metabolic regimes

AbstractThe temporal structures of gross primary production (GPP) and ecosystem respiration (ER) vary across time scales in response to complex interactions among dynamic drivers (e.g., flow, light, temperature, organic matter supply). To explore emergent patterns of river metabolic variation, we applied frequency‐domain analysis to multiyear records of metabolism across 87 US rivers. We observed a dominant annual periodicity in metabolic variation and universal fractal scaling (i.e., power spectral density inversely correlated with frequency) at subannual frequencies, suggesting these are foundational temporal structures of river metabolic regimes. Frequency‐domain patterns of river metabolism aligned best with drivers related to energy inputs: benthic light for GPP and GPP for ER. Simple river metabolism models captured frequency‐domain patterns when parameterized with appropriate energy inputs but neglecting temperature controls. These results imply that temporal variation of energy supply imprints directly on metabolic signals and that frequency‐domain patterns provide benchmark properties to predict river metabolic regimes.