Dynamics Plot Research Articles

Predicting New Anti-Norovirus Inhibitor With the Help of Machine Learning Algorithms and Molecular Dynamics Simulation-Based Model.

Hepatitis C virus (HCV) inhibitors are essential in the treatment of human norovirus (HuNoV). This study aimed to map out HCV NS5B RNA-dependent RNA polymerase inhibitors that could potentially be responsible for the inhibitory activity of HuNoV RdRp. It is necessary to develop robust machine learning and in silico methods to predict HuNoV RdRp compounds. In this study, Naïve Bayesian and random forest models were built to categorize norovirus RdRp inhibitors from the non-inhibitors using their molecular descriptors and PubChem fingerprints. The best model observed had accuracy, specificity, and sensitivity values of 98.40%, 97.62%, and 97.62%, respectively. Meanwhile, an external test set was used to validate model performance before applicability to the screened HCV compounds database. As a result, 775 compounds were predicted as NoV RdRp inhibitors. The pharmacokinetics calculations were used to filter out the inhibitors that lack drug-likeness properties. Molecular docking and molecular dynamics simulation investigated the inhibitors’ binding modes and residues critical for the HuNoV RdRp receptor. The most active compound, CHEMBL167790, closely binds to the binding pocket of the RdRp enzyme and depicted stable binding with RMSD 0.8–3.2 Å, and the RMSF profile peak was between 1.0–4.0 Å, and the conformational fluctuations were at 450–460 residues. Moreover, the dynamic residue cross-correlation plot also showed the pairwise correlation between the binding residues 300–510 of the HuNoV RdRp receptor and CHEMBL167790. The principal component analysis depicted the enhanced movement of protein atoms. Moreover, additional residues such as Glu510 and Asn505 interacted with CHEMBL167790 via water bridge and established H-bond interactions after the simulation. http://zinc15.docking.org/substances/ZINC000013589565.

Investigating the Feasibility of In Vivo Perfusion Imaging Methods for Spinal Cord Using Hyperpolarized [13C]t-Butanol and [13C,15N2]Urea

This study examined the feasibility of using two novel agents, hyperpolarized [13C]t-butanol and [13C,15N2]urea, for assessing in vivo perfusion of the intact spinal cord in rodents. Due to their distinct permeabilities to blood brain barrier (BBB), we hypothesized that [13C]t-butanol and [13C,15N2]urea exhibit unique 13C signal characteristics in the spinal cord. Dynamic 13C t-butanol MRI data were acquired from healthy Long-Evans rats using a symmetric, ramp-sampled, partial-Fourier 13C echo-planar imaging sequence after the injection of hyperpolarized [13C]t-butanol solution. In subsequent scans, dynamic 13C urea MRI data were acquired after the injection of hyperpolarized [13C,15N2]urea. The SNRs of t-butanol and urea were calculated for regions corresponding to spine, supratentorial brain, and blood vessels and plotted over time. Mean peak SNR and AUC were calculated from the dynamic plots for each region and compared between t-butanol and urea. In spine and supratentorial brain, the mean peak SNR and AUC of t-butanol were significantly higher than those of urea (p < 0.05). In contrast, urea was predominantly contained within vasculature and exhibited significantly higher levels of mean peak SNR and AUC compared to t-butanol in blood vessels (p < 0.05). This study has demonstrated the feasibility of using hyperpolarized [13C]t-butanol and [13C,15N2]urea for assessing in vivo perfusion in cervical spinal cord. Due to differences in blood-brain barrier permeability, t-butanol rapidly crossed the blood-brain barrier and diffused into spine and brain tissue, while urea predominantly remained in vasculature. The results from this study suggest that this technique may provide unique non-invasive imaging tracers that are able to directly monitor hemodynamic processes in the normal and injured spinal cord.

Remotely sensed assessment of increasing chronic and episodic drought effects on a Costa Rican tropical dry forest

AbstractTropical dry forests (TDFs) have experienced pronounced droughts and increased temperatures for the last century. To assess whether these climatic shifts have influenced dry forest vegetation and ecosystem functioning, we integrated ground observations from a Costa Rican long‐term forest dynamics monitoring plot with remotely sensed measures of forest productivity and canopy functioning from a diverse set of satellite data. Previously reported long‐term climate data (1921–1997) show a reduction in annual rainfall, but since 1980 there has been no directional change in mean annual precipitation. However, the 2015 El Niño Southern Oscillation (ENSO)‐induced drought was unprecedented. Temperatures have increased by 1.1°C since 1931. However, the Landsat wet season (1987–2017) Enhanced Vegetation Index (EVI) (canopy greenness) and the dry season (1985–2017) fraction of non‐photosynthetic canopy cover all indicate that TDFs have become more deciduous but also more productive during the wet season. These changes are consistent with a shift in the functional composition observed in the long‐term plot as more drought‐deciduous tree species have increased in abundance. Nonetheless, more continuous 16‐d MODIS (the Moderate Resolution Imaging Spectroradiometer) measures of the EVI over the past 17 yr (2001–2017) showed no change in the total annual forest productivity. Further, while the 2015 ENSO event temporarily reduced forest EVI, it did not cause a longer‐term impact on forest productivity. Instead, high spatial resolution Worldview‐2 satellite imagery showed that forest phenology shifted in the subsequent years even though the region returned to normal precipitation. Our results indicate that while the species composition of TDFs may be sensitive to the long‐term trend of gradually increasing temperatures and aridity, the annual forest functioning has so far been resilient to long‐term drying and a large episodic extreme drought event. This study demonstrates the feasibility of synthesizing satellite images of different characteristics to study the vegetation dynamics of a long‐term forest dynamics plot. Our synoptically sensed results show that the longer‐term changing climate has been and is currently shifting the ecological functioning, and also provide a baseline to assess the impacts of an extreme drought year on TDFs.

Biosynthesis of α-Fe2O3-CdO Nanocomposites for Electrochemical Detection of Chloridazon Herbicide

Biosynthesised α-Fe2O3-CdO electrochemical nanosensor attained from Coriandrum sativum leaves extract and fabricated on the screen-printed electrode to detect chloridazon (CLZ) herbicide in agricultural food samples. Scanning electron microscopy, energy dispersive x-ray analysis, X-ray diffraction spectroscopy, cyclic voltammetry, and differential pulse voltammetry were used to investigate the α-Fe2O3-CdO electrochemical nanosensor. The optimization factors of the effect of pH, accumulation time, accumulation potential, and foreign substances were elevated. The α-Fe2O3-CdO/SPE electrochemical nanosensor shows the significant voltammetric response for the CLZ detection. Foreign substances did not considerably influence pesticide detection. Dynamic linear CLZ plot for a standard solution of CLZ was obtained in the concentration range of 0.1 to 36.00 µg⸳mL-1 (R=0.995) with a limit of detection 0.059 µg⸳mL-1 and a quantification limit of 0.179 µg⸳mL-1. The proposed electrochemical nanosensor was used to detect CLZ in agricultural food samples and agreeable recovery results.

Large tree mortality leads to major aboveground biomass decline in a tropical forest reserve.

Humans are transforming the ecology of the Earth through rapid changes in land use and climate. These changes can affect tropical forest structure, dynamics and diversity. While numerous studies have focused on diversity metrics, other aspects of forest function, such as long-term biomass dynamics, are often less considered. We evaluated plant community structure change (i.e., abundance, diversity, composition, and aboveground biomass) in a 2.25ha forest dynamics plot located within a ~ 365ha reserve in southern Costa Rica. We censused, mapped and identified to species all plants ≥ 5cm diameter at breast height (DBH) in three surveys spanning 2010-2020. While there were no changes in late-successional species diversity, there were marked changes in overall species composition and biomass. Abundance of large (≥ 40cm DBH) old-growth dense-wooded trees (e.g., Lauraceae, Rosaceae) decreased dramatically (27%), leading to major biomass decline over time, possibly driven by recent and recurrent drought events. Gaps created by large trees were colonized by early-successional species, but these recruits did not make up for the biomass lost. Finally, stem abundance increased by 20%, driven by increasing dominance of Hampea appendiculata. While results suggest this reserve may effectively conserve overall plant diversity, this may mask other key shifts such as large aboveground biomass loss. If this pattern is pervasive across tropical forest reserves, it could hamper efforts to preserve forest structure and ecosystem services (e.g., carbon storage). Monitoring programs could better assess carbon trends in reserves over time simply by tracking large tree dynamics.

The forestecology R package for fitting and assessing neighborhood models of the effect of interspecific competition on the growth of trees.

Neighborhood competition models are powerful tools to measure the effect of interspecific competition. Statistical methods to ease the application of these models are currently lacking.We present the forestecology package providing methods to (a) specify neighborhood competition models, (b) evaluate the effect of competitor species identity using permutation tests, and (cs) measure model performance using spatial cross‐validation. Following Allen and Kim (PLoS One, 15, 2020, e0229930), we implement a Bayesian linear regression neighborhood competition model.We demonstrate the package's functionality using data from the Smithsonian Conservation Biology Institute's large forest dynamics plot, part of the ForestGEO global network of research sites. Given ForestGEO’s data collection protocols and data formatting standards, the package was designed with cross‐site compatibility in mind. We highlight the importance of spatial cross‐validation when interpreting model results.The package features (a) tidyverse‐like structure whereby verb‐named functions can be modularly “piped” in sequence, (b) functions with standardized inputs/outputs of simple features sf package class, and (c) an S3 object‐oriented implementation of the Bayesian linear regression model. These three facts allow for clear articulation of all the steps in the sequence of analysis and easy wrangling and visualization of the geospatial data. Furthermore, while the package only has Bayesian linear regression implemented, the package was designed with extensibility to other methods in mind.

Authoring an Interactive Narrative with Declarative Optimization-Based Drama Management

Drama managers reconfigure a game in reaction to a player's actions. In declarative optimization-based drama management (DODM), a game's story is abstracted as a sequence of plot points; possible drama manager interventions are abstracted as a set of DM actions. The author defines an func- tion evaluating story quality, and some optimization method (currently reinforcement learning) chooses DM actions so as to maximize expected story quality according to that evaluation function. While previous work has developed this ap- proach at a technical level and discussed its potential applications, no work to date has used DODM to write real games. We report on our experiences designing a game in the Neverwinter Nights engine, entitled The Guilty, in which we use DODM to create a dynamic plot that in a previous design iteration we had found difficult to create with other techniques.

Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition

Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data.

The stability of soil organic carbon across topographies in a tropical rainforest.

Mechanisms of soil organic carbon (SOC) stability are still unclear in forest ecosystems. In order to unveil the influences of topography on the SOC stability, a 60ha dynamic plot of a tropical montane rainforest was selected in Jianfengling, in Hainan Island, China and soil was sampled from 60 quadrats. The chemical fractions of the SOC were detected with 13C CPMAS/NMR and path analyses explore the mechanisms of SOC stability in different topographies. The chemical fractions of the SOC comprised alkyl carbon > O-alkyl carbon > carboxyl carbon > aromatic carbon. The decomposition index (DI) values were greater than 1 in the different topographies, with an average DI value was 1.29, which indicated that the SOC in the study area was stable. Flat and top areas (together named RF) had more favorable nutrients and silt contents compared with steep and slight steep areas (together named RS). The influencing factors of SOC stability varied across the topographies, where SOC, soil moisture (SM) and ammoniacal nitrogen (NH4+-N, AN) were the main influencing factors in the RF, while SM and AN were the main factors in the RS. Greater SOC and AN strengthened the SOC stability, while higher soil moisture lowered SOC stability. The inertia index was higher in the RS than the RF areas, indicating that local topography significantly affects SOC content and SOC stability by changing soil environmental factors. Topography cannot be neglected in considering SOC stability and future C budgets.

Motion and dynamic analyses of a human centrifuge system with an efficient design configuration

Modern high-maneuverable fighters and airplanes can expose pilots and aircrews to high-Gravity acceleration. In order to maintain air safety and superiority during operation, pilots and aircrews should have tolerance for this intense acceleration. Countermeasures can be taken to enhance the human tolerance to high-Gravity acceleration motion fields. One of the most promising solutions is acceleration physiology training using a Human Centrifuge System (HCS). Motivated by the lack of practical guidelines on design and development of HCS's structure and control algorithms, this study introduces an analysis framework towards characterising the most feasible HCS design configuration, meeting the requirements of effective centrifuge training. The proposed framework, including Inverse Kinematic and Dynamic (IKD) operation, motion analysis and sensitivity plots, can be simply applied to different design configurations with minor modification in the kinematic and dynamic algorithm. The outcomes of the study show the dependency of kinematic and dynamic responses of the system on the design and operational parameters. It is observed that the range of Coriolis acceleration and feet-to-head acceleration ratio can be minimised by adopting a proper orientation of the gondola. This outcome can be an important step towards the design of a more efficient and affordable HCS, without imposing the over-increased HCS's arm length challenges.

Plastome-based phylogeny improves community phylogenetics of subtropical forests in China.

Phylogenetic trees have been extensively used in community ecology. However, how the phylogeny construction affects ecological inferences is poorly understood. In this study, we constructed three different types of phylogenetic trees (a synthetic-tree generated using V.PhyloMaker, a barcode-tree generated using rbcL+matK+trnH-psbA, and a plastome-tree generated from plastid genomes) that represented an increasing level of phylogenetic resolution among 580 woody plant species from six forest dynamic plots in subtropical evergreen broadleaved forests of China. We then evaluated the performance of each phylogeny in estimations of community phylogenetic structure, turnover and phylogenetic signal in functional traits. As expected, the plastome-tree was most resolved and most supported for relationships among species. For local phylogenetic structure, the three trees showed consistent results with Faith's PD and MPD; however, only the synthetic-tree produced significant clustering patterns using MNTD for some plots. For phylogenetic turnover, contrasting results between the molecular trees and the synthetic-tree occurred only with nearest neighbor distance. The barcode-tree agreed more with the plastome-tree than the synthetic-tree for both phylogenetic structure and turnover. For functional traits, both the barcode-tree and plastome-tree detected phylogenetic signal in maximum height, but only the plastome-tree detected signal in leaf width. This is the first study that uses plastid genomes in large-scale community phylogenetics. Our results highlight the improvement of plastome-trees over barcode-trees and synthetic-trees for the analyses studied here. Our results also point to the possibility of type I and II errors in estimation of phylogenetic structure and turnover and detection of phylogenetic signal when using synthetic-trees.

Political uncertainty, COVID-19 pandemic and stock market volatility transmission

News about referendums and the ongoing evolution of a global contagious increase uncertainty about the development of economic fundamentals reflected by increased volatility in the financial markets. In this paper, employing volatility impulse response functions and assessing the volatility spillovers we examine intra-market volatility transmission in the Athens stock market. We employ a large sample period of daily data that spans from December 1999 to December 2020 and captures major events of the last 20 years especially related to the announcement of the two referendums during the Greek government-debt crisis in 2010 and the economic and political turmoil that increased country instability, the following years, the BREXIT referendum and the COVID-19 pandemic of 2020. Our results demonstrate that negative shocks during the announcement of the referendum produce larger impulse responses than during the announcement of the country lockdowns. Furthermore, we shed light on the existence of the dynamic relationship of volatility spillovers. Volatility spillovers peaked during the COVID-19 pandemic. Dynamic spillover plots demonstrate that during the COVID-19 pandemic, more volatility is transmitted by mid cap firms to large cap firms. Our findings have implications to market participants, policy makers and market regulators.

Spatial distribution and stability mechanisms of soil organic carbon in a tropical montane rainforest

Estimation of soil organic carbon (SOC) storage and its dynamics in tropical montane forests is crucial for climate change prediction, which calls for further investigation into the spatial variation in SOC and its stability mechanisms. In this study, 60 subplots (20 m × 20 m) were randomly selected within a 60 ha tropical montane rainforest dynamic monitoring plot located in southern China. The physical (HFC and LFC) and chemical fractions of SOC (alkyl C, O-alkyl C, aromatic C and carbonyl C), microbial biomass carbon and other soil properties at depths of 0–10 cm, plant species and root biomass (0–10 cm and 10–20 cm) were investigated. Geostatistical methods, multiple regression trees and redundant analysis were used to reveal that the spatial variations in SOC and its stability mechanisms with the terrain. The results show that the spatial variations in HFC and the ratios of alkyl carbon/O-alkyl carbon had a moderate spatial dependence due to the complex terrain. High SOC and its physical stability fractions (HFC) were distributed along ridgelines, while the chemical stability index of SOC (alkyl C/O-alkyl C) was the highest on hillsides and in valleys. Terrain convexity best explained the spatial variations in SOC and HFC, while total nitrogen and convexity together best explained the spatial variation in the chemical fractions of SOC. Abiotic factors explained more of the variation in SOC and its fractions than biotic factors, while abiotic and biotic factors were covariant. The specific factors controlling the distribution of SOC and its fractions differed with the types of micro-terrain. These results highlight the influence of terrain on the distribution and accumulation of SOC in tropical forest ecosystems. Hence, terrain should be considered a key factor in biogeochemical models.

Tropical forest understorey riparian and upland composition, structure, and function in areas with different past land use

AbstractQuestionsAlthough past land‐use effects on composition and structure are described for many forest types, forested riparian areas have been overlooked. Riparian areas may contain unique species and high species richness, as well as contribute basal leaf‐litter resources for aquatic fauna. We asked: (a) does past land use alter composition in riparian vs upland areas in wet tropical forest; (b) which vegetation life forms characterize riparian zones; and (c) what is the composition and quantity of leaf litter in riparian zones compared to uplands?LocationRiparian and upland locations in tropical wet forest, Luquillo Forest Dynamics Plot (LFDP), Luquillo Experimental Forest, Puerto Rico.MethodsStratified random sampling was conducted in riparian and upland areas of LFDP with high and low past land use. Understorey vegetation life form composition and cover were sampled in plots. Leaf‐litter species composition and components were estimated with collecting baskets placed throughout riparian zones and uplands.ResultsFerns and lianas were more abundant in riparian areas than uplands. Ordination of species composition groups was distinct for riparian and upland areas with different past land use when based on leaf litter, but this ordination pattern was not as clear in plot vegetation.ConclusionCharacterized by greater presence of ferns and lianas, riparian zones had higher species richness values and greater leaf litter biomass. Distinct leaf‐litter species composition within riparian and upland areas may result from a combination of different land‐use histories, various plant types, and environmental conditions. Although riparian areas are proportionally a small component of the forested landscape, they are significant contributors to ecosystem process, terrestrial and aquatic linkages, and plant community composition.

Parametric Stability Analysis of a Spring Attached, Pre-Twisted, Rotating Sandwich Beam with Tip Mass and Viscoelastic Support

This paper inspects the influence of a spring attachment provided on the top elastic layer on the stability of a pre-twisted, rotating sandwich beam having viscoelastic supports at the root under the impact of a periodically varying axial load. The spring is deployed on the beam to achieve more strength to weight ratio without compromising the stability. The beam is exponentially tapered, and a tip mass is at the free end to represent the rotating members in various types of machinery as closely as possible. The ruling equations and inter-related boundary conditions are attained by applying Hamilton’s principle. To obtain the solution, a matrix equation was developed through the assumed-mode variational method. The resulting matrix equation was converted to a coupled Hill’s equation of parametric vibration through the modal matrix corresponding to the free vibration problem. Finally, static and dynamic stability graphs were obtained for several system parameters such as position and length of the attached spring on the top elastic layer, the mass of the spring attachment, stiffness of the spring attachment, angle of pre-twist, tip mass, taper parameter, temperature gradient parameter, setting angle, viscoelastic spring stiffness, etc. to analyze their impact on the system’s stability. Saito and Otomi conditions were used to obtain dynamic stability plots. Greater stability is achieved due to the spring attachment on the top of the top elastic layer.

Validated tensile characterization of the strain rate dependence in soft materials

A major obstacle in the accurate measurement of the dynamic tensile response of soft materials is the issue of obtaining material response under simultaneous stress equilibrium, stress uniaxiality and constant strain rate. To resolve this issue, a split-Hopkinson pressure bar (SHPB)-based dynamic tension experiment is developed in this study, which has sufficient fidelity to ensure temporal and spatial accuracy of the stress state, to investigate soft materials under large deformations and intermediate dynamic strain rates (100-102 s−1). Cross-linked polydimethylsiloxane (PDMS) elastomer is chosen as a model material. By examining the evolution of full-field strain and strain rate measured using digital image correlation (DIC) and employing analytical criteria for quantifying stress equilibrium and deformation uniaxiality, it is demonstrated that the proposed test method yields a true steady-state and inertia-free stress-strain material response when all three conditions of equilibrium, uniaxiality and strain rate constancy are satisfied. Quasi-static experiments at 10−3-10−1 s−1 strain rate are also conducted for comparison. By analyzing the quasi-static and dynamic stress-strain plots and the variation of uniaxial moduli in the investigated range of strain rates, it is shown that the tensile response of PDMS points to limiting chain extensibility and exhibits a weak nonlinear strain rate sensitivity. Finally, a visco-hyperelastic model based on the Gent strain energy density function and a recently proposed viscous dissipation potential is employed to capture the experimentally obtained response. It is shown that all the features of the rate-dependent stress-strain response are modeled with good fitting accuracy.

Inference on Reported Vehicular Fatal Accidents in Nigeria Using a Bayesian Model

The study introduced a special case of the Poisson-Generalized Gamma empirical Bayes model to survey states in Nigeria with a higher risk of fatal accidents. Monte Carlo error and stationary dynamic trace plots were used to validate model convergence and accuracy of the posterior estimates. The main results included the disease mappings that revealed Ebonyi had the highest risk of road vehicular fatal accidents in Nigeria with a relative risk estimate of 1.4120 while Abuja had the lowest risk with a relative risk estimate 0.5711. In terms of geopolitical region, the risk of road vehicular fatal accident is highest in South-South region with a relative risk estimate of 1.1850 while North-Central had the lowest risk with a relative risk estimate of 0.7846. The study is to aid planned government programs to ameliorate vehicular road carnage in Nigeria.

Humus microhabitat affects distributions of soil fungi and bacteria in a temperate mountain forest

AbstractHumus layer has an important effect on the diversity and spatial distribution of microbes. However, the role of partitioning of humus layer microhabitats for soil microbial diversity has been poorly documented. In this study, 120 soil samples were collected from a 5‐ha forest dynamic monitoring sample plot in a deciduous broad‐leaved forest. Clustering analysis was used to delineate microhabitats by humus layer. We explored diversity and community composition of soil fungi and bacteria using Illumina sequencing of the ITS rRNA gene and 16S rRNA gene region on the MiSeq platform. We investigated the diversity, species composition, and the microhabitat preferences of fungi and bacteria and then analyzed the effects of environmental factors on soil fungi and bacteria. Our results showed that the diversity, species composition, and the indicator species of the fungal and bacterial community varied among different humus layer microhabitats. In network analysis, the specialization indexes showed that 16.20%/22.30% of the fungal/bacterial operational taxonomic units (OTUs) had the characteristics of distribution specialization for humus layer microhabitats. Mantel test showed that the main environmental drivers of fungi and bacteria were not consistent among the four microhabitats. Our findings indicated that the distribution of soil microbes among humus layer microhabitats is not random, but specialized. We furthermore found that there were differences in the relationship between soil microbes and environment among microhabitats defined by humus layer. Together, these findings suggest the importance of partitioning of humus layer microhabitats in maintaining local diversity in a soil microbial community.

Dynamic theta/beta ratio of clinical EEG in Alzheimer's disease

BackgroundEEG of a resting state in Alzheimer disease (AD) patients and healthy controls (HC) are analyzed to identify the characteristics of EEG in AD. New methodA dynamic box plot approach to the theta/beta ratio with various window durations is proposed to analyze EEG. ResultsSpectral results during a resting state in AD patients demonstrate the effect of relatively greater power in the low-frequency bands (i.e. ‘slowing down’ of the EEG). A significant difference is observed in the dynamic distribution of the theta/beta ratio in the AD and HC groups, which is related to the effect of ‘slowing down’. There is a more obvious visual separation between the theta/beta ratio results for the AD and HC groups with increasing window durations. Variability of the theta/beta ratio can be observed with shorter window durations with a dynamic functional box plot. This provides a better classification accuracy by using the dynamic theta/beta ratio as a sensor to discriminate AD EEG from HC EEG by using the receiver operating characteristics (ROC) curve and the area under curve (AUC) with various window durations. Comparison with existing method(s)EEG spectral analysis and theta/beta ratio used to evaluate EEG typically rely on long time averaging. ConclusionsThe dynamic box plot approach to the theta/beta ratio with various window durations provides the possibility of observing features of the EEG. The dynamic theta/beta ratio is a better sensor to discriminate AD EEG from HC EEG. Moreover, the reliability and accuracy of results can be increased by combining spectral analysis and the dynamic box plot approach to theta/beta ratio with various window durations.

Effects of logging on the ecological strategy spectrum of a tropical montane rain forest

Ecological strategy is the various adaptation tactics of species to different living conditions, which can reflect their contrasting approaches to survival in varying habitats. The number and relative abundance of species in different types of ecological strategies actually forms an ecological strategy spectrum in a community. Logging is a widespread driver of forest degradation, severely influencing the composition of communities and the ecological strategy spectra in forest ecosystems. Understanding effects of logging on the ecological strategy composition of communities is vital to biodiversity conservation and efficient restoration of degraded forest ecosystems. Yet, the knowledge of how ecological strategies of different communities respond to varying types and intensities of disturbances in tropical forests are largely unknown. Here, by establishing forest dynamics plots (FDPs) in communities experienced increasing logging intensities (no logging (old-growth (OG)), selective logging (SL), and clear-cutting (CL) and measuring plant functional traits in a tropical montane rain forest, we compared the changes in ecological strategies of these stands by using Grime’s competitor, stress-tolerator, ruderal (CSR) scheme and by “StrateFy” ordination method based on measurements of three plant functional traits (Leaf area (LA), leaf dry matter content (LDMC), and specific leaf area (SLA)). Results showed that strategy number increased and ecological strategy spectra of communities changed significantly with increasing logging intensity: the proportion of S-selected strategies decreased while those of C- and R-selected strategies increased with increasing logging intensity. Community-weighted mean CSR (CWM-CSR) strategies of stands shifted from S to the C & R direction, i.e. CWM-C and CWM-R values increased and CWM-S values decreased with increasing logging intensity. Our findings suggest that logging intensity should be carefully controlled in harvesting planning, so that the recovery of species assemblages with multiple ecological strategies can be assured and the ecosystem services from these biodiverse forests can be provided sustainably.