Store Edge Networked Data (SEND): A Data and Performance Driven Edge Storage Framework

The number of devices that the edge of the Internet accommodates and the volume of the data these devices generate are expected to grow dramatically in the years to come. As a result, managing and processing such massive data amounts at the edge becomes a vital issue. This paper proposes "Store Edge Networked Data" (SEND), a novel framework for in-network storage management realized through data repositories deployed at the network edge. SEND considers different criteria (e.g., data popularity, data proximity from processing functions at the edge) to intelligently place different categories of raw and processed data at the edge based on system-wide identifiers of the data context, called labels. We implement a data repository prototype on top of the Google file system, which we evaluate based on real-world datasets of images and Internet of Things device measurements. To scale up our experiments, we perform a network simulation study based on synthetic and real-world datasets evaluating the performance and trade-offs of the SEND design as a whole. Our results demonstrate that SEND achieves data insertion times of 0.06ms-0.9ms, data lookup times of 0.5ms-5.3ms, and on-time completion of up to 92% of user requests for the retrieval of raw and processed data

UAV trajectory optimisation in smart cities using modified A* algorithm combined with Haversine and Vincenty formulas

It is anticipated that the backbone of Smart Cities concerning automation and networking will be formed by Unmanned Aerial Vehicles in the imminent future. Therefore, our research focuses on developing advanced microcontrollers embedded with Artificial Intelligence techniques for self-governing Unmanned Aerial Vehicles. The main objective of this research was to enable full automation for the execution of flight paths with non-trivial sequences that will be performed with centimetre-level accuracy. Also, by utilising dynamic flight plans and trajectories, we aim to secure autonomous aviation based on norms, with control loops and fundamental constraints. More specifically, we evolved a novel algorithmic technique for trajectory optimisation, which deploys a modification to the A* search algorithm, implemented by the Haversine formula and enhances accuracy using Vincenty’s formula. Furthermore, realistic values for trajectory optimisation and obstacle avoidance were found through the implementation of a simulative investigation. The outcomes of our methodology indicate that the safety constraints associated with the integration of Unmanned Aerial Vehicles in the urban environment can be significantly mitigated. Consequently, their effectiveness will be increased in realising their diverse operations and capabilities

A Computational Efficient Method For Hbt Intermodulation Distortions And Two-Tone Characteristics Simulation

In this paper, a new simulation method for two-tone characteristics calculations and the third-order intercept point (OIP3) of heterojunction bipolar transistor (HBT) in large-scale time domain is proposed. Base on waveform relaxation (WR) and monotone iterative (MI) methods, we solve a set of nonlinear ordinary differential equation (ODE) of equivalent circuit. With this approach, the two-tone characteristics in frequency domain for HBTs were directly computed from time domain result with fast Fourier transform (FFT). Simulation results on a realistic HBT are presented to show the accuracy and efficiency of the method.

GCN5 modulates salicylic acid homeostasis by regulating H3K14ac levels at the 5ʹ and 3ʹ ends of its target genes

The modification of histones by acetyl groups has a key role in the regulation of chromatin structure and transcription. The Arabidopsis thaliana histone acetyltransferase GCN5 regulates histone modifications as part of the Spt-Ada-Gcn5 Acetyltransferase (SAGA) transcriptional coactivator complex. GCN5 was previously shown to acetylate lysine 14 of histone 3 (H3K14ac) in the promoter regions of its target genes even though GCN5 binding did not systematically correlate with gene activation. Here, we explored the mechanism through which GCN5 controls transcription. First, we fine-mapped its GCN5 binding sites genome-wide and then used several global methodologies (ATAC-seq, ChIP-seq and RNA-seq) to assess the effect of GCN5 loss-of-function on the expression and epigenetic regulation of its target genes. These analyses provided evidence that GCN5 has a dual role in the regulation of H3K14ac levels in their 5′ and 3′ ends of its target genes. While the gcn5 mutation led to a genome-wide decrease of H3K14ac in the 5′ end of the GCN5 down-regulated targets, it also led to an increase of H3K14ac in the 3′ ends of GCN5 up-regulated targets. Furthermore, genome-wide changes in H3K14ac levels in the gcn5 mutant correlated with changes in H3K9ac at both 5′ and 3′ ends, providing evidence for a molecular link between the depositions of these two histone modifications. To understand the biological relevance of these regulations, we showed that GCN5 participates in the responses to biotic stress by repressing salicylic acid (SA) accumulation and SA-mediated immunity, highlighting the role of this protein in the regulation of the crosstalk between diverse developmental and stress-responsive physiological programs. Hence, our results demonstrate that GCN5, through the modulation of H3K14ac levels on its targets, controls the balance between biotic and abiotic stress responses and is a master regulator of plant-environmental interactions

Fall Detection with Unobtrusive Infrared Array Sensors

As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risks to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data with various degrees of success. In this paper, we present a fall detection system using infrared array sensors with several deep learning methods, including long-short-term-memory and gated recurrent unit models. Evaluated with fall data collected in two different sets of configurations, we show that our approach gives significant improvement over existing works using the same infrared array sensor

Perturbation of lipids and glucose metabolism associated with previous 2,4-D exposure: a cross-sectional study of NHANES III data, 1988-1994

<p>Abstract</p> <p>Background</p> <p>Results from previous population studies showed that mortality rates from acute myocardial infarction and type-2 diabetes during the 1980s and 1990s in rural, agricultural counties of Minnesota, Montana, North and South Dakota, were higher in counties with a higher level of spring wheat farming than in counties with lower levels of this crop. Spring wheat, one of the major field crops in these four states, was treated for 85% or more of its acreage with chlorophenoxy herbicides. In the current study NHANES III data were reviewed for associations of 2,4-dichlorophenoxy acetic acid (2,4-D) exposure, one of the most frequently used chlorophenoxy herbicides, with risk factors that are linked to the pathogenesis of acute myocardial infarction and type-2 diabetes, such as dyslipidemia and impaired glucose metabolism.</p> <p>Methods</p> <p>To investigate the toxicity pattern of chlorophenoxy herbicides, effects of a previous 2,4-D exposure were assessed by comparing levels of lipids, glucose metabolism, and thyroid stimulating hormone in healthy adult NHANES III subjects with urinary 2,4-D above and below the level of detection, using linear regression analysis. The analyses were conducted for all available subjects and for two susceptible subpopulations characterized by high glycosylated hemoglobin (upper 50^thpercentile) and low thyroxine (lower 50^thpercentile).</p> <p>Results</p> <p>Presence of urinary 2,4-D was associated with a decrease of HDL levels: 8.6% in the unadjusted data (p-value = 0.006), 4.8% in the adjusted data (p-value = 0.08), and 9% in the adjusted data for the susceptible subpopulation with low thyroxine (p-value = 0.02). An effect modification of the inverse triglycerides-HDL relation was observed in association with 2,4-D. Among subjects with low HDL, urinary 2,4-D was associated with increased levels of triglycerides, insulin, C-peptide, and thyroid stimulating hormone, especially in the susceptible subpopulations. In contrast, subjects with high HDL did not experience adverse 2,4-D associated effects.</p> <p>Conclusions</p> <p>The results indicate that exposure to 2,4-D was associated with changes in biomarkers that, based on the published literature, have been linked to risk factors for acute myocardial infarction and type-2 diabetes.</p

Financial Characteristics of Companies Audited by Large Audit Firms

Purpose “ The purpose of this paper is to examine how financial characteristics associated with the choice of a big audit firm with further investigation on the agency costs of free cash flows.Design/methodology/approach “ The sample used for this work includes industrial listed companies from Germany and France. To test our hypothesis, we used a number of logit models, extending the standard model selection audit firm, to include the variables of interest. Following previous work, our dependent dummy variable is Big4 or non-Big4.Findings “ We observed that most independent variables in the German companies show similar results to previous work, but we did not have the same results for the French industry. Moreover, our findings suggest that the total debt and dividends can be an important reason for determining the choice of a large audit firm, reducing agency costs of free cash flows.Research limitations/implications “ This study has some limitations on the measurements of the cost of the audit fees and also generates opportunities for additional searching.Originality/value “ The paper provides only one aspect to explain the relationship between the problems of agency costs of free cash flow and influence in choosing a large auditing firm, which stems from investors\u27 demand for higher quality audits