Mahmooddavenport7178

Gradient-based algorithms have been widely used in optimizing parameters of deep neural networks' (DNNs) architectures. However, the vanishing gradient remains as one of the common issues in the parameter optimization of such networks. To cope with the vanishing gradient problem, in this article, we propose a novel algorithm, evolved gradient direction optimizer (EVGO), updating the weights of DNNs based on the first-order gradient and a novel hyperplane we introduce. We compare the EVGO algorithm with other gradient-based algorithms, such as gradient descent, RMSProp, Adagrad, momentum, and Adam on the well-known Modified National Institute of Standards and Technology (MNIST) data set for handwritten digit recognition by implementing deep convolutional neural networks. Furthermore, we present empirical evaluations of EVGO on the CIFAR-10 and CIFAR-100 data sets by using the well-known AlexNet and ResNet architectures. Finally, we implement an empirical analysis for EVGO and other algorithms to investigate the behavior of the loss functions. The results show that EVGO outperforms all the algorithms in comparison for all experiments. We conclude that EVGO can be used effectively in the optimization of DNNs, and also, the proposed hyperplane may provide a basis for future optimization algorithms.The finite-time consensus fault-tolerant control (FTC) tracking problem is studied for the nonlinear multi-agent systems (MASs) in the nonstrict feedback form. The MASs are subject to unknown symmetric output dead zones, actuator bias and gain faults, and unknown control coefficients. According to the properties of the neural network (NN), the unstructured uncertainties problem is solved. The Nussbaum function is used to address the output dead zones and unknown control directions problems. By introducing an arbitrarily small positive number, the ``singularity problem caused by combining the finite-time control and backstepping design is solved. According to the backstepping design and Lyapunov stability theory, a finite-time adaptive NN FTC controller is obtained, which guarantees that the tracking error converges to a small neighborhood of zero in a finite time, and all signals in the closed-loop system are bounded. Finally, the effectiveness of the proposed method is illustrated via a physical example.Subtropical lakes are increasingly subject to cyanobacterial blooms resulting from climate change and anthropogenic activities, but the lack of long-term historical data limits understanding of how climate changes have affected cyanobacterial growth in deep subtropical lakes. Using high-resolution DNA data derived from a sediment core from a deep lake in southwestern China, together with analysis of other sedimentary hydroclimatic proxies, we investigated cyanobacterial biomass and microbial biodiversity in relation to climate changes during the last millennium. Our results show that both cyanobacterial abundance and microbial biodiversity were higher during warmer periods, including the Medieval Warm Period (930-1350 CE) and the Current Warm Period (1900 CE-present), but lower during cold periods, including the Little Ice Age (1400-1850 CE). The significant increases in cyanobacterial abundance and microbial biodiversity during warmer intervals are probably because warm climate not only favors cyanobacterial growth but also concentrates lake water nutrients through water budgets between evaporation and precipitation. Furthermore, because rising temperatures result in greater vertical stratification in deep lakes, cyanobacteria may have exploited these stratified conditions and accumulated in dense surface blooms. We anticipate that under anthropogenic warming conditions, cyanobacterial biomass may continue to increase in subtropical deep lakes.Both climate change and agricultural intensification are drivers of global nutrient cycles and biodiversity loss. A potentially great environmental threat can arise when these two drivers interact, for example, when farmers try to compensate reduced soil nutrient availability due to drought by the application of liquid organic fertiliser. As dry soils don't hold back nutrients very well, this approach can lead to nitrate leaching and potentially also to the pollution of drinking water. However, little is known about leaching from dry but fertilised grassland soil, and how this is affected by land use intensity and plant diversity. In this mesocosm study, we transferred 60 grassland sods differing in past land use intensity to a greenhouse and treated them with severe drought, fertilisation and both together. Drought was induced by almost entirely stopping irrigation for seven weeks. Fertilisation was done by three applications of slurry summing up to 168 kg total nitrogen per hectare (111 kg NH4-N). We assess leaching risk.Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices.Although the ubiquitous presence of microplastics in various environments is increasingly well studied, knowledge of the effects of microplastics on ambient microbial communities is still insufficient. To estimate the response of soil bacterial community succession and temporal turnover to microplastic amendment, a soil microcosm experiment was carried out with polyethylene microplastics. The soil samples under control and microplastic amendment conditions were collected for sequencing analysis using Illumina MiSeq technology. see more Microplastic amendment was found to significantly alter soil bacterial community structure, and the community differences were increased linearly with the incubation time. Compared with the turnover rate of bacterial community in the control samples (0.0103, p less then .05, based on Bray-Curtis similarity), the succession rate was significantly (p less then .001) higher in the soil with microplastic amendment (0.0309, p less then .001). In addition, the effects of microplastic amendment on the time-decay relationships (TDRs) on taxonomic divisions revealed considerable variations of TDRs values, indicating the effects were lineage dependent. Our results propose that the presence of microbial in soil ecosystem may lead to a faster succession rate of soil bacterial community, which provides new insights into the evolutionary consequences of microplastics in terrestrial environment.Several studies have examined the impact of economic growth on carbon emission; however, the symmetric and asymmetric impact of oil price along with FDI on carbon emission has not studied in the case of Pakistan. For this purpose, the long and short-run impact of per capita income, FDI, and oil price on carbon emissions investigated by employing the ARDL and non-linear ARDL cointegration methodology, along with Granger causality in the context of Pakistan for 1971-2014. This study confirms the EKC hypothesis for Pakistan under both methodologies, whereas symmetric results show that economic growth and FDI intensify carbon emission in both the long and short-run, while oil price increase emission in the short-run and reduces emission in the long-run. Whereas asymmetric results in the long-run show that an increase in oil price reduces emissions and decrease in oil price intensify emissions. The causality analysis also supports the above findings and suggests a feedback effect between economic growth and carbon emission in Pakistan. This study provides implications for policymakers, where the descending flow of FDI allows limited space to Pakistan in FDI selection; however, the presence of emission convergence and adoption of carbon pricing may facilitate Pakistan in achieving its environmental targets. While diversifying the overall energy mix towards more renewable/clean energy along with formulating favorable policies for the adoption of renewable energy like solar by the industrial and residential consumers can further reduce the overall emission levels.Per- and polyfluoroalkyl substances (PFASs) have been detected in many agricultural products in contaminated fields and in supply chains. Roots are the main organ in plants to uptake and bio-accumulate PFASs, but the changes of metabolic regulation in roots by PFASs are largely unexplored. Here, lettuce exposed to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) at different concentrations (500, 1000, 2000 and 5000 ng/L) was investigated via metabolomics. Many key metabolites, such as antioxidants, lipids, amino acids, fatty acids, carbohydrates, linolenic acid derivatives, purine and nucleosides, were significantly altered. Tyrosine metabolism, purine metabolism, isoquinoline alkaloid biosynthesis and terpenoid backbone biosynthesis were altered in roots by PFOA and PFOS. Tricarboxylic acid cycle was perturbed by 5000 ng/L exposure. Activation of antioxidant defense pathways, reallocation of carbon and nitrogen metabolism, regulation of energy metabolism and purine metabolism were reprogrammed in roots. Lettuce employed multiple strategies to increase tolerance to PFOA and PFOS, which includes the adjustment of membrane composition, elevation of inorganic nitrogen fixation and respiration, accumulation of sucrose and regulation of signaling molecules. The results of this study offer insights into the molecular reprogramming of plant roots in response to PFAS exposure and provide important information for the risk assessment of PFASs in environment.Natural vegetation is important for ecosystem services (ESs) provision, but is decreasing rapidly due to human-driven land use change, especially rapid expansion of commercial plantations. This is leading to a decrease in ESs provision, so measures are urgently needed to protect natural vegetation. Human activities, especially commercial plantations, can also lead to differences in vegetation types and associated ESs provision. This feature varies with altitude, an issue which has received insufficient attention. In this study, four ESs relevant to stakeholders (carbon storage, nitrogen export, sediment retention and water yield) were assessed. InVEST models and statistical methods (ANOVA; exploratory hierarchical clustering) were used to analyse 1) similarities/differences in ESs provision between different vegetation types and 2) spatial differences in ESs in different altitude zones in the Xishuangbanna region of China. The results showed that vegetation types in Xishuangbanna and their ESs supply capacity differed markedly, with the overall ESs supply capacity of natural forests exceeding that of commercial plantations.