Miracle-dz/UniFAR-FTUs huggingface dataset:
Lithostratigraphy and petrology of Lachman Crags and Cape Lachman lava-fed deltas, Ulu Peninsula, James Ross Island, north-eastern Antarctic Peninsula: Preliminary results

This paper presents the preliminary results regarding the lithostratigraphy, petrography and petrology of James Ross Island Volcanic Group dominating the Lachman Crags and Cape Lachman lava-fed deltas in the Ulu Peninsula, James Ross Island north-eastern Antarctic Peninsula. Studied lava-fed deltas were produced via Late Miocene to Pleistocene sub-marine and sub-glacial volcanism and made up four main lithofacies: a- bottomset pillow lavas, peperites and associated volcanoclastic/siliciclastic deposits; b- foreset- bedded hyaloclastite breccias; c- intrusions (feeder dykes, sills, and plugs) and d- topset subaerial lavas. Collectively these lithofacies record the transition from an effusive subaqueous to an effusive subaerial eruption environment. All lava samples and dykes from bottomset, foreset and topset lava-fed delta associations are olivine-phyric alkali basalts and are mineralogically and geochemically homogeneous. These eruptive products display significant enrichments in alkali contents and have ocean island basalt (OIB)-type, intra-plate geochemical signatures characterized by enrichments in all highly to moderately incompatible trace elements relative to basaltic rocks from ocean ridge settings. Volcanic products from a number of different eruptive periods display limited variations in major and trace element relative abundances, indicating derivation from a relatively homogeneous mantle source. The results of quantitative modelling of geochemical data is consistent with the view that the primary melts from which these mafic alkaline rocks were originated are the products of relatively small degrees (~3-7%) of partial melting of a volatile-bearing, metasomatized mantle source. The magmatism is likely the result of extension-driven mantle upwelling.
Assessing the role and consistency of satellite observation products in global physical–biogeochemical ocean reanalysis

Abstract. As part of the European Space Agency's Climate Change Initiative, new sets of satellite observation products have been produced for essential climate variables including ocean colour, sea surface temperature, sea level, and sea ice. These new products have been assimilated into a global physical–biogeochemical ocean model to create a set of 13-year reanalyses at 1∘ resolution and 3-year reanalyses at 1∕4∘ resolution. In a series of experiments, the variables were assimilated individually and in combination in order to assess their consistency from a data assimilation perspective. The satellite products, and the reanalyses assimilating them, were found to be consistent in their representation of spatial features such as fronts, sea ice extent, and bloom activity. Assimilating multiple variables together often resulted in larger mean increments for a variable than assimilating it individually, providing information about model biases and compensating errors which could be addressed in the future development of the model and assimilation scheme. Sea surface fugacity of carbon dioxide had lower errors against independent observations in the higher-resolution simulations and was improved by assimilating ocean colour or sea ice concentration, but it was degraded by assimilating sea surface temperature or sea level anomaly. Phytoplankton biomass correlated more strongly with net air–sea heat fluxes in the reanalyses than chlorophyll concentration did, and the correlation was weakened by assimilating ocean colour data, suggesting that studies of phytoplankton bloom initiation based solely on chlorophyll data may not provide a full understanding of the underlying processes.
The Nearshore Heat Budget: Effects of Stratification and Surfzone Dynamics

Temperature variability in the nearshore (from ≈ 6-m depth to the shoreline) is influenced by many processes including wave breaking and internal waves. A nearshore heat budget resolving these processes has not been considered. A 7-month experiment at the Scripps Institution of Oceanography Pier (shoreline to 6-m depth) measured temperature and surface and cross-shore heat fluxes to examine a nearshore heat budget with fine cross-shore spatial (≈ 20 m) and temporal (5 day to 4 hr) resolution. Winds, waves, air and water temperature, and in particular, pier end stratification varied considerably from late Fall to late Spring. The largest heat flux terms were shortwave solar radiation and baroclinic advective heat flux both varying on tidal time scales. The net heat flux is coherent and in phase with the nearshore heat content change at diurnal and semidiurnal frequencies. The binned mean heat budget has squared correlation R2 = 0.97 and best-fit slope of 0.76. Including an elevated breaking wave albedo parameterization reduced the residual heat flux and improved the best-fit slope. Baroclinic and barotropic advective heat fluxes have significant noise, and removing them from the heat budget improves the best-fit slope when stratification is weak. However, when daily mean stratification is large, baroclinic advective heat flux dominates variability and is required to capture large (≈ 3 ◦C h−1) internal wave events. At times, large heat budget residuals highlight neglected heat budget terms, pointing to surfzone alongshore advection of temperature anomalies.
Sparse modeling for the geotechnical observation data

In the geotechnical engineering, it is a significant issue to construct the numerical models for simulation analysis based on the observation data. In this study, sparse modeling used as an effective modeling method in the field of machine learning and image processing was applied to the geotechnical engineering and its effectiveness was examined. Aa a case study based on the field observation data, the fused lasso which is a typical method of the sparse modeling was applied to model the velocity structure of the subsurface ground using the PS logging data. As a result of examination, it was found that simplified models can be obtained by increasing the value of the regularization parameter.
Ecosystem engineers: Biofilms and the ontogeny of glacier floodplain ecosystems

The term “ecosystem engineering” emerged in the 1990s and is commonly used to refer to the activities of larger organisms like beavers and trees in rivers and streams. The focus on larger organisms may be motivated by their more visible effects on the environment. However, while it may be intuitive to suggest that the bigger the organism the bigger its potential engineering effects, there may be microscale organisms who through their number rather than their size can act simultaneously to result in significant impacts. This paper considers biofilms as a candidate ecosystem engineer. It is well known that biofilms play an important role in enriching the sediment matrix of nutrients and in stabilizing sediments. Biofilms may be critical in increasing the habitability of the benthic substratum. In this paper, we consider their potential role in the ontogeny of ecosystems in recently deglaciated terrain. We show how by changing sediment stoichiometry, decreasing sediment erodibility, and reducing surface sediment permeability they may promote primary succession on lateral, incised terraces, which are less perturbed compared with the main active floodplain.
Research advances in modelling plant species distribution in China

Species distribution models (SDMs) have been extensively used in simulations of geographical distribution of distribution of plant species and the impact from climate change, and the applied science on the prediction of suitable distribution area of plant species in order to popularize their plantation. More applications of SDMs in multiple disciplines and in multiple industries such as ecology, forestry, crop science and Chinese traditional medicine should be further developed. Joint simulations and inter-comparisons using multiple plant species, more SDMs and multiple data sources of environmental data, as well as the development of new and mechanism SDMs are encouraged. The extension of model applications in new research fields is also needed.
Asian Winter Monsoon Imprint on Holocene SST Changes at the Northern Coast of the South China Sea

Independent inference of the Asian winter monsoon (AWM), albeit achieved at several sparse sites, has reached no consensus for its variability through the Holocene. A sediment core from the northern coast of the South China Sea (SCS) was utilized to analyze organic biomarkers at (bi‐)decadal resolution, unveiling how SCS oceanic conditions fingerprint the AWM signal. Generally, alkenone sea surface temperature (SST) record, resembling the temporal structures of integrated tropical SST over the past 7,500 years, shows abnormal cool temperatures (up to ~4 °C) during the Little Ice Age and between ~1,200 and 2,500 years BP, when windborne terrigenous hopane compounds experienced considerable increases superimposed on a general increasing trend. Our results, together with augmented SST gradient between the SCS coast and open ocean, consistently suggest AWM strengthening toward the late Holocene. An intensified AWM during cold intervals like the Little Ice Age would have provided strong positive feedback to enhance coastal cooling.
Neuropathological Study of Acute Myelopathy and Encephalopathy Associated to HTLV-I

Background a chronic and progressive parapares is without remission silent on MRI is the ordinary neurological presentation of HTLV-I, expression of a central axonopathy product of axoplasmic transport alterations. Infrequently acute forms like “T2 hyperintense acute myelopathy on MRI” have been reported. The Purpose of this presentation will be to describe the histopathological expression of this acute form and look for their pathogenesis. Patient and method: A 60 years old woman carrier of refractory anaemia and subjected to multiple transfusions, positive for HTLV-I. She developed a severe cognitive impairment and paraplegia set up in four weeks. MRI showed T2 hyper intense lesions in white matter of brain hemispheres and in cervico-thoraxic segments of the spinal cord. She died suddenly by myocardial infarction. The neuropathological studies showed white matter necrosis insymmetricfrontal areas, conservation of cortical structures and U fibbers; necrosis in bothlateral tracts of the spinal cord (T2T4) without gray substance damage; the microvascular walls of these areas immuno-stained with anti-Tax, expressed Taxprotein suggesting HTLV-I infection. Conclusions: This necrotizing leukopathy in absence of a primary inflammation would be the expression of HTLV-I endothelial cells infection in specific white matter areas, changing of the blood-brain barrier permeability.
Association between Common Space Occupancy and Spatial Configuration in Japanese Nursing Home

This paper explores the association between common facility space occupancy and spatial configuration and aims to have higher space occupancy by spatial design. The spatial configuration includes geometric metrics and topologic metrics from Space syntax theory.The association between space occupancy and spatial configuration in twelve nursing homes is evaluated using the multiple linear regression model. The results show that spatial integration, connectivity, and area size are significant factors to space occupancy correlation. Therefore, allocating space with higher spatial integration, more connectivity, and the large area size are three effective ways to increase space occupancy in Japanese nursing homes. Keywords: Space syntax; Space occupancy; Spatial configuration; Nursing home. eISSN 2514-751X © 2019. The Authors. Published for AMER, ABRA & cE-Bs by E-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/aje-bs.v4i14. 352
CapsFall: Fall Detection Using Ultra-Wideband Radar and Capsule Network

Radar technology for at home health-care has many advantages such as safety, reliability, privacy-preserving, and contact-less sensing nature. Detecting falls using radar has recently gained attention in smart health care. In this paper, CapsFall, a new method for fall detection using an ultra-wideband radar that leverages the recent deep learning advances is proposed. To this end, a radar time series is derived from the radar back-scattered matrix and its time-frequency representation is obtained and used as input to the capsule network for automatic feature learning. In contrast to other existing methods, the proposed CapsFall method relies on multi-level feature learning from radar time-frequency representations. In particular, the proposed method utilizes a capsule network for automating feature learning and enhancing model discriminability. The experiments are conducted using a set of radar signals collected from ten subjects when performing various activities in a room environment. The performance of the proposed CapsFall method is evaluated in terms of classification metrics and compared with those of the other existing methods based on convolutional neural network, multi-layer perceptron, decision tree, and support vector machine. The results show that the proposed CapsFall method outperforms the other methods in terms of accuracy, precision, sensitivity, and specificity values.
Pervasive-Based Access Control Model for IoT Environments

The Internet of Things (IoT) has become a global sensory network that links physical and virtual objects by communicating and exploiting data and initiating physical actions. The evolution of this paradigm is already threatened by security issues, which constitute major risk factors that demand efficient solutions adapted to the IoT context. In this paper, we put forward a logical approach and systemic analysis that enables us to present the key aspects of new access control (AC) model for the IoT environments, called a pervasive-based access control model (PerBAC). Our approach is based on the study of important, reputable AC models that we use as a background for our proposed model. PerBAC is defined here based on a representation of the decision-making algorithm, a description of the abstract entities using the attributes as a fundamental concept and the collaboration aspects necessary to handle the case of multiple organizations. These attributes are the perfect recipient of the information collected by IoT environments from the physical world and allow optimal access control decisions to be taken according to dynamic rules and entities based on the algorithm. Our interpretation of the attributes, the dynamic entities and their exploitation by our proposed algorithm produce a new AC model adapted to the IoT paradigm.
Falls in people with chronic obstructive pulmonary disease : risk factors, incidence and impact on health related quality of life

ii TABLE OF CONTENTS . iv LIST OF TABLES . ix LIST OF FIGURES. x LIST OF ABBREVIATIONS . xi ACKNOWLEDGEMENTS. xiii DEDICATION . xiv CO-AUTHORSHIP STATEMENT.xv CHAPTER ONE: STATEMENT OF THE PROBLEM . 1 1.
Harmonic Minimization in Modified PUC-5 Inverter Using Genetic Algorithm

In this paper, new harmonic reduction scheme by using the genetic algorithm (GA) is proposed for single phase modified Packed U-Cell (MPUC-5) five-level inverter. Packed U-Cell multilevel inverter was first introduced in 2011 and since then many switching sequences have been proposed for obtaining different levels of output voltage, with overall reduction in harmonic content from output voltage waveform. In this paper, the authors have tried to obtain the optimum switching angles to reduce the output harmonics by applying genetic algorithm. Genetic algorithm is nature inspiring optimization technique, which works on the principle of heredity, evolution and Darwin’s theory of survival of the fittest. Genetic algorithm evolves iteration by iteration and gives better and better results and finally converges to optimum result as per our requirements. This concept is verified in MATLAB®/Simulink environment and is also validated experimentally using the TI-28335 DSP.
Finite element analysis of cyclic behaviour of laterally loaded pile influenced by vertical and biaxial loading

ABSTRACT This study is concerned with evaluating the response of single pile subjected to cyclic horizontal uniaxial loading. Combination of lateral cyclic loading and constant vertical or lateral load in two-orthogonal directions is also studied. Moreover, the influence of one- and two-way loading, number of cycles and the intensity of constant load in conjunction with the cyclic lateral load is presented. The study is further continued by comparing the performance of long and short single pile embedded in clayey soil. A series of three-dimensional finite element models using ANSYS code are conducted to model three-dimensional transient analysis as well as the complicated soil pile interaction. In order to verify the validity numerical model, the numerical response is compared with reported results obtained by experimental cyclic load test performed on single pile penetrated in soft clay. Results show strong coupling between the two-orthogonal direction of lateral loading that decreases the lateral pile capacity. The interaction relation of biaxial loading with the factor b = 1.2 and 1.15 for one- and two-way loading respectively may well approximate the analysis results. The results of study are presented in terms of lateral cyclic capacities, pile head deflection, displacement profile and bending moment over the pile length.
Joint Routing and Scheduling for Vehicle-Assisted Multidrone Surveillance

In recent decades, unmanned aerial vehicles (UAVs, also known as drones) equipped with multiple sensors have been widely utilized in various applications. Nevertheless, constrained by limited battery capacities, the hovering time of UAVs is quite limited, prohibiting them from serving a wide area. To cater with remote sensing applications, people often employ vehicles to transport, launch, and recycle them. The so-called vehicle-drone cooperation (VDC) benefits from both the far driving distance of vehicles and the high mobility of UAVs. Efficient routing and scheduling can greatly reduce time consumption and financial expenses incurred in VDC. However, previous works in vehicle-drone cooperative sensing considered only one drone, thus unable to simultaneously cover multiple targets distributed in an area. Using multiple drones to sense different targets in parallel can significantly promote efficiency and expand service areas. Therefore, we propose a novel problem, referred to as vehicle-assisted multidrone routing and scheduling problem. To tackle the problem, we contribute an efficient algorithm, referred to as vehicle-assisted multi-UAV routing and scheduling algorithm (VURA). In VURA, we maintain and iteratively update a memory containing candidate UAV routes. VURA works by iteratively deriving solutions based on UAV routes picked from the memory. In every iteration, VURA jointly optimizes anchor point selection, path planning, and tour assignment via nested optimization operations. To the best of our knowledge, we are the first to tackle this novel yet challenging problem. Finally, performance evaluation is presented to demonstrate the effectiveness and efficiency of our algorithm when compared with existing solutions.
Simulation of Stator Winding Faults with an Analytical Model of a PMSM

Stator winding faults are one of the major limitations of the lifetime and reliability of electrical machines. Interturn faults are for that matter often the origin of more severe faults, which can lead to complete system failures. This paper presents an analytical machine model, to investigate the behavior of PMSMs with dynamic stator winding faults on turn level. In order to keep the model compact, the levels of abstraction can be adapted within the machine model. The acausal implementation of the electric domain allows the simulation of one model with different operating modes. This paper compares the simulation results of the analytical model with FEA simulation results. The average torque differs in case of two inter-turn faults at nominal load operation by 2% and the amplitude of the fault currents differs by 5%. There is no difference in the frequencies and phase angles of the fault currents and the torque. In our future work, we will use the presented model to develop a fault management system, allowing fault tolerant operation of safety critical applications.
Single Carrier-Based Pulse Width Modulator for Modular Multilevel Converters

Carrier-based pulse width modulation (PWM) schemes are the preferred choice for modular multilevel converters (MMCs) due to their simplicity and ease of implementation. However, the required number of carriers for gating signal generation drastically increases with the number of submodules (SMs) in an MMC. These carriers should be accurately synchronized with each other to generate the high-quality output voltage and current waveforms. However, it is difficult to achieve the synchronization due to the memory constraints, sampling issues, computational delays, and control complexity. To overcome these issues, a simple single carrier-based PWM modulator is proposed in this paper. In addition, a simple SM capacitor voltage-balancing approach with less computational burden is presented. The proposed scheme can be easily applied to the n-level MMC without any modifications and applicable to any SM type. The effectiveness of the proposed modulation scheme and SM capacitor voltage balancing algorithm is demonstrated through the simulations in the PLECS® software platform.
An Optimized Selective Harmonic Minimization-PWM Scheme for Cascaded H-Bridge Inverter Fulfilling NRS 048-2:2003 Grid code

This paper presents, an optimized pulse width modulation (PWM) scheme for a five-level cascaded H-bridge (CHB) inverter that minimizes some selective harmonics to fulfill the grid code NRS 048-2:2003 for medium-voltage level three-phase applications. Moreover, this scheme has also been compared with the standard SHE-PWM scheme through simulation based on harmonics and %THD value up to 40th order. Here, particle swarm optimization (PSO) technique has been used to find the solution of four variable switching instances and the equally variable DC voltage sources. Finally, simulation and experimental results have been obtained from a three-phase five-level CHB inverter to confirm the aforesaid claims.
A Study of Aero-Engine Control Method Based on Deep Reinforcement Learning

A novel aero-engine control method based on deep reinforcement learning (DRL) is proposed to improve the engine response ability. The Q-learning that is model free and can be performed online is adopted. For improving the learning capacity of DRL, the online sliding window deep neural network (OL-SW-DNN) is proposed and adopted to estimate the action value function. The OL-SW-DNN selects the nearest point data with certain length as training data and is insensitivity to the noise. Finally, the comparison simulations of the proposed method with the proportion–integration–differentiation (PID) that is the most commonly used as an engine controller algorithm in industry are conducted to verify the validity of the proposed method. The results show that, compared with the PID, the acceleration time of the proposed method decreased by 1.525 s under the premise of satisfying all engine limits.