forest fractals

The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the "Cyberforest Experiment" conducted in the open-air Paneveggio forest in Valle di Fiemme, Trento, Italy, where spruce (i.e., Picea abies ) is cultivated. Our analysis of the bioelectric potentials reveals a strong correlation between higher-order complexity measurements and thermodynamic entropy and suggests that bioelectrical signals can reflect the metabolic activity of plants...

The relationship between carbon cycle and water demand is key to understanding global climate change, vegetation productivity, and predicting the future of water resources. The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmosphere through evapotranspiration, ET, links drawdown of atmospheric carbon with the water cycle through plant transpiration. Our theoretical description based on percolation theory proposes that dominant ecosystems tend to maximize drawdown of atmospheric carbon in the process of growth and reproduction, thus providing a link between carbon and water cycles...

BACKGROUND: To solve the withering of Hippophae rhamnoides plantation in the feldspathic sandstone areas of Inner Mongolia and to promote the regeneration, rejuvenation, and sustainability of H. rhamnoides forests. METHODS: We stumped aging H. rhamnoides trees at the ground heights of 0, 10, 15, and 20 cm (S1, S2, S3, and S4, respectively) and utilized unstumped trees as the control (CK). We then analyzed the effects of the different stump heights on the roots and the root microenvironment of H...

With the increasing development of unconventional reservoirs around the world, there is an increasing need to enhance the level of geological characterization. Obviously, since the well loggings are one of the most important data to obtain a fine-scale reservoir model, obtaining well loggings with sufficiently high vertical resolution has always been an important issue and challenge. Therefore, due to its low cost and less time-consuming, employing an advanced signal processing technique to enhance the vertical resolution of loggings has always been a research hotspot in the relevant literature...

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure...

OBJECTIVES: To analyse various corneal nerve parameters using confocal microscopy along with systemic and orthoptic parameters in patients presenting with ocular surface pain using a random forest artificial intelligence (AI) model. DESIGN: Observational, cross-sectional. METHODS: Two hundred forty eyes of 120 patients with primary symptom of ocular surface pain or discomfort and control group of 60 eyes of 31 patients with no symptoms of ocular pain were analysed...

PURPOSE: To achieve an accurate diagnosis of idiopathic epiretinal membrane (iERM) through analyzing retinal blood vessel oxygen saturation (SO2) and vascular morphological features in fundus images. METHODS: Dual-modal fundus camera was used to obtain color fundus image, 570-nm, and 610-nm images. As iERM affects the macular area, a macular-centered semicircle area as region of interest (MROI) was selected and analyzed SO2 and vascular morphologies in it. Eventually, random forest (RF) and support vector machine (SVM) were as classifiers to diagnose iERM patients...

The soil water characteristic curve (SWCC) is of great significance for studying the hydrological cycle, agricultural water management, and unsaturated soil mechanics. However, it is difficult to effectively obtain a large number of SWCCs because of the cumbersome and expensive determination experiments for SWCCs. Pedo-transfer functions (PTFs) established using soil physicochemical properties have become an effective method for solving this problem. However, due to the limitations of the establishment methods and the wide spatial variability of soil properties, it is still difficult to establish PTFs in a specific region...

Evaluating flood susceptibility, identifying flood-prone areas, and planning reasonable landscape patterns are important measures in promoting sustainable urban development and flood mitigation. To this end, this study evaluated the flood susceptibility using a neural network model depending on a flood inundation map created from satellite data from 2010 to 2020, and explanatory factors for flood inundation selected by Geodetector and regularized random forest. Subsequently, the landscape pattern of the coastal city was quantified based on the land cover, and key landscape pattern metrics for flood susceptibility were selected at patch and class levels using statistical approaches...

Soil quality can be assessed by measuring its physical, chemical and biological properties. In terrestrial ecosystems, the knowledge of the status of soil quality under different land use/cover can increase our understanding of processes related to soil functioning and help to properly managing ecosystems and increase their services. Conversion of the forest to rangelands is one of the most common forms of land use change having a significant effect on soil quality indicators. Here, we addressed the following objectives: (ii) to study the current status of soil physical, chemical and biological characteristics after more than thirty years of land use change from forest (dominated by Carpinus betulus and Parrotia persica) to rangeland, and (ii) to provide an overview of the spatial distributions of soil properties in forest and rangeland covers using a geostatistical method...

Soils are dynamic and complex systems in their natural state, which are subjected to profound changes due to management. Additionally, agricultural soils are continuously exposed to wetting and drying (W-D) cycles, which can cause modifications in the complexity of their pores. Thus, we explore how successive W-D cycles can affect the pore network of an Oxisol under contrasting managements (conventional tillage-CT, minimum tillage-MT, no tillage-NT, and secondary forest-F). The complexity of the soil pore architecture was evaluated using a 3D multifractal approach combined with lacunarity, Shannon's entropy, and pore geometric parameters...

Changes in land use and landscapes have a direct impact on the regional eco-environment. It is of great importance to understand the change pattern of land use, landscapes, and their mechanism on the ecological quality, especially ecologically fragile areas. The northern sand-prevention belt (NSPB) is an important ecologically fragile area in China, which has a large influence on the ecological security of the entire country. Based on the land use data of the NSPB in 2000, 2010, and 2018, we studied the spatio-temporal characteristics of land-use change and change in landscape patterns...

Fast and accurate diagnosis is critical for the triage and management of pneumonia, particularly in the current scenario of a COVID-19 pandemic, where this pathology is a major symptom of the infection. With the objective of providing tools for that purpose, this study assesses the potential of three textural image characterisation methods: radiomics, fractal dimension and the recently developed superpixel-based histon, as biomarkers to be used for training Artificial Intelligence (AI) models in order to detect pneumonia in chest X-ray images...

AIMS: Investigate the growth adaptation law of the Tamarix chinensis root system in response to the groundwater level in a muddy coastal zone. METHODS: The high groundwater level (0.7-0.9 m), medium groundwater level (1.1-1.3 m) and low groundwater level (1.5-1.7 m) T. chinensis forests on the beaches of the Yellow River Delta were used as the research objects. Full excavation methods were used to excavate root systems with different groundwater levels; then, the aboveground biomass, root biomass, root spatial distribution, root topological structure and fractal characteristics of T...

The stability of aggregates is of great significance to evaluate water and soil environment in regions plan-ting economic fruit forest. We explored the effects of economic fruit forest types on the structure and stability of soil aggregates in the 0-50 cm soil layer from 5-year-old Amygdalus persica , Pyrus sorotina , Citrus reticulata , Camellia oleifera and Actinidia chinensis forests in the hilly area in northern Hunan. The content, distribution characteristics and stability indices of soil aggregates from each economic fruit forest were quantitatively analyzed by the Shavinov method...

Background: The search for a method that utilizes biomarkers to identify patients with schizophrenia from healthy individuals has occupied researchers for decades. However, no single indicator can be employed to achieve the good in clinical practice. We aim to develop a comprehensive machine learning pipeline based on neurocognitive and electrophysiological combined features for distinguishing schizophrenia patients from healthy people. Methods: In the present study, 69 patients with schizophrenia and 50 healthy controls participated...

During the COVID-19 pandemic, predicting case spikes at the local level is important for a precise, targeted public health response and is generally done with compartmental models. The performance of compartmental models is highly dependent on the accuracy of their assumptions about disease dynamics within a population; thus, such models are susceptible to human error, unexpected events, or unknown characteristics of a novel infectious agent like COVID-19. We present a relatively non-parametric random forest model that forecasts the number of COVID-19 cases at the U...

Landscape fragmentation and habitat loss at multiple scales directly affect species abundance, diversity, and productivity. There is a paucity of information about the effect of the landscape structure and diversity on honey bee colony strength in Africa. Here, we present new insights into the relationship between landscape metrics such as patch size, shape, connectivity, composition, and configuration and honey bee (Apis mellifera) colony strength characteristics. Remote-sensing-based landscape variables were linked to honey bee colony strength variables in a typical highly fragmented smallholder agroecological region in Kenya...

Electroencephalogram (EEG) signals portray hidden neuronal interactions in the brain and indicate brain dynamics. These signals are dynamic, complex, chaotic and nonlinear, the nature of which is represented with features - fractal dimensions, entropies and chaotic features. This study aims at examining the discriminative power of individual features and their combination in the diagnosis of a neuro-pathological condition called encephalopathy. Feature combination is accomplished with the help of feature selection using Gini impurity score that improves discriminative power and keeps redundancy minimal...

Highly prevalent in nature, fractal patterns possess self-similar components that repeat at varying size scales. The perceptual experience of human-made environments can be impacted with inclusion of these natural patterns. Previous work has demonstrated consistent trends in preference for and complexity estimates of fractal patterns. However, limited information has been gathered on the impact of other visual judgments. Here we examine the aesthetic and perceptual experience of fractal 'global-forest' designs already installed in humanmade spaces and demonstrate how fractal pattern components are associated with positive psychological experiences that can be utilized to promote occupant wellbeing...