VISUALIZING BARRIER DUNE TOPOGRAPHIC STATE SPACE AND INFERENCE OF RESILIENCE PROPERTIES

The linkage between barrier island morphologies and dune topographies, vegetation, and biogeomorphic feedbacks, has been examined. The two-fold stability domain (i.e., overwash-resisting and overwash-reinforcing stability domains) model from case studies in a couple of islands along the Georgia Bight and Virginia coast has been proposed to examine the resilience properties in the barrier dune systems. Thus, there is a need to examine geographic variations in the dune topography among and within islands. Meanwhile, previous studies just analyzed and compared dune topographies based on transect-based point elevations or dune crest elevations; therefore, it is necessary to further examine dune topography in terms of multiple patterns and processes across scales. In this dissertation, I develop and deploy a cross-scale data model developed from resilience theory to represent and compare dune topographies across twelve islands over approximately 2,050 kilometers of the US southeastern Atlantic coast. Three sets of topographic variables were employed to summarize the cross-scale structure of topography (elevational statistics, patch indices, and the continuous surface properties). These metrics differed in their degree of spatial explicitness, their level of measurement, and association with patch or gradient paradigms. Topographic metrics were derived from digital elevation models (DEMs) of dune topographies constructed from airborne Light Detection and Ranging (LiDAR). These topographic metrics were used to construct dune topographic state space to investigate and visualize the cross-scale structure of dune topography. This study investigated (1) dune topography and landscape similarity among barrier islands in different barrier island morphologic contexts, (2) the differences in barrier island dune topographies and their resilience properties across large geographic extents, and (3) how geomorphic and biogeomorphic processes are related to resilience prosperities. The findings are summarized below. First, dune topography varies according to island morphologies of the Virginia coast; however, local controls (such as human modification of the shore or shoreline accretion and erosion) also play an important role in shaping dune topographies. Compared with tide-dominated islands, wave-dominated islands exhibited more convergence in dune topographies. Second, the dune landscapes of the Virginia Barrier Islands have a poorly consistent spatial structure, along with strong collinearity among elevational variables and landscape indices, which reflects the rapid retreat and erosion along the coast. The dune landscapes of the Georgia Bight have a more consistent spatial structure and a greater dimensionality in state space. Thus, the weaker multicollinearity and higher dimensionality in the dataset reflect their potential for resilience. Last, islands of different elevations may have similar dune topography characteristics due to the difference in resistance and resilience. Notwithstanding the geographic variability in geomorphic and biogeomorphic processes, convergence in dune topography exists, which is evidenced by the response curves of the topographic metrics that are correlated with both axes. This work demonstrates the usefulness of different representations of dune topography by cross-scale data modeling. Also, the two existing models of barrier island dune states were integrated to form a conceptual model that illuminates different, but complementary, resilience properties in the barrier dune system. The differences in dune topographies and resilience properties were detected in state space, and this information offers guidance for future study’s field site selections

Critical Care of Acute Heart Failure

Acute heart failure is a life-threatening medical condition. Improving acute heart failure care is important. Early diagnosis and evaluating the etiology are important in acute heart failure. Patients with suspected acute heart failure should have a diagnostic workup, and appropriate pharmacological and nonpharmacological management should be started promptly and in parallel. Diagnosis of acute heart failure should be based on history and symptoms. The physical examination typically presents with some combination of increased congestion and decreased peripheral perfusion, further confirmed by electrocardiogram, chest radiograph, biomarkers, and echocardiogram. The first step in the management of a patient is to address life-threatening issues. Patients with respiratory failure or cardiogenic shock should be treated soon. The next step is the identification of precipitants that needs urgent management. Evidence-based medication to reduce morbidity and mortality for patients with heart failure includes an angiotensin converting enzyme inhibitor, angiotensin receptor blocker, or angiotensin receptor-neprilysin inhibitor; a beta blocker; and a mineralocorticoid receptor antagonist. During an acute heart failure episode, management of these agents depends upon whether the patient has contraindications to therapy such as hemodynamic instability or acute kidney injury. Once the patient is stable, therapies are carefully initiated, reinitiated, or titrated with appropriate follow-up

Probing highly collimated photon-jets with deep learning

Many extensions of the standard model (SM) predict the existence of axion-like particles and/or dark Higgs in the sub-GeV scale. Two new sub-GeV particles, a scalar and a pseudoscalar, produced through the Higgs boson exotic decays, are investigated. The decay signatures of these two new particles with highly collimated photons in the final states are discriminated from the ones of SM backgrounds using the Convolutional Neural Networks and Boosted Decision Trees techniques. The sensitivities of searching for such new physics signatures at the Large Hadron Collider are obtained

Using Script Command to Conquer the Narrowband Constraint in Synchronous Long-distance Teaching System

Abstract: The applications of synchronous long-distance teaching (SLDT) are more and more valuable with the internet prevalence. One of the SLDT restrictions is the bandwidth consumption of the connection between teacher's side and students' sides. Even though most users use broadband network at present, there are still users using narrowband networks, such as dial-up and 3.5G network. It is very difficult to conduct SLDT in the narrowband network unless reducing the demands of network bandwidth consumption, especially while the teaching materials including video, audio, and so on. This paper proposes a novel scheme to reduce the network bandwidth requirement of SLDT efficiently. Original SLDT system transmits all teaching materials in full screen frames, so that it needs a great amount of network bandwidth. The proposed innovative technique encodes some of the teaching materials, including typing texts, messages on the electronic whiteboard, drawing pictures and timestamps into script commands. In this way, the encoded script commands are transmitted through the text channel of the multimedia streaming, while the audio and video channels carry the teacher's voice and images. When the students' sides receive the multimedia streaming, it is decoded back to the full screen frames. In this paper, the design of the encoder and decoder will be addressed in detail. The experimental results proved that our proposed scheme could reduce the demand of network bandwidth consumption efficaciously. Even at the dial-up and 3.5G network environment, students' sides could play the teaching frames very smoothly. That is, our implemented system could conquer the narrowband constraint and provide users to carry out SLDT in the narrowband network

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment

The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms. As a result, today’s markets experience intense activity in the highly dynamic environment where trading systems respond to others at a much faster pace than before. This new breed of technology involves the implementation of high-speed trading strategies which generate significant portion of activity in the financial markets and present researchers with a wealth of information not available in traditional low-speed trading environments. In this study, we aim at developing feasible computational intelligence methodologies, particularly genetic algorithms (GA), to shed light on high-speed trading research using price data of stocks on the microscopic level. Our empirical results show that the proposed GA-based system is able to improve the accuracy of the prediction significantly for price movement, and we expect this GA-based methodology to advance the current state of research for high-speed trading and other relevant financial applications

Honokiol Protected against Heatstroke-Induced Oxidative Stress and Inflammation in Diabetic Rats

We aimed at investigating the effect of honokiol on heatstroke in an experimental rat model. Sprogue-Dawley rats were divided into 3 groups: normothermic diabetic rats treated with vehicle solution (NTDR+V), heatstroke-diabetic rats treated with vehicle (HSDR+V), and heatstroke rats treated with konokiol (0.5–5 mg/ml/kg) (HSDR+H). Sixty minutes before the start of heat stress, honokiol or vehicle solution was administered. (HSDR+H) significantly (a) attenuated hyperthermia, hypotension and hypothalamic ischemia, hypoxia, and neuronal apoptosis; (b) reduced the plasma index of the toxic oxidizing radicals; (c) diminished the indices of hepatic and renal dysfunction; (d) attenuated the plasma systemic inflammatory response molecules; (e) promoted plasma levels of an anti-inflammatory cytokine; (f) reduced the index of infiltration of polymorphonuclear neutrophils in the serum; and (g) promoted the survival time fourfold compared with the (HSDR+V) group. In conclusion, honokiol protected against the outcome of heatstroke by reducing inflammation and oxidative stress-mediated multiple organ dysfunction in diabetic rats