Miracle-dz/UniFAR-FTUs huggingface dataset:
DATA TO TEXT FOR GENERATING INFORMATION OF WEATHER AND AIR QUALITY IN THE R PROGRAMMING LANGUAGE

Data obtained from weather monitoring stations and air quality acquired from several meteorological websites are numerical data. The research is aimed at developing a weather-generating Data to Text (D2T) that enables people to understand weather and air quality information. On developing D2T, there are four basic elements: signal analysis, data interpretation, document planning, as well as microplanning and realization. This research contributes to extending the signal analysis by adding new features: exponential smoothing for prediction time series data, a linear model with gradient descent for handling missing values and data summarization with statistical tools. In this study, several packages available in the R programming language were utilized. To validate the results, four measuring tools consisting of readability, computation time, relevance and truthfulness and comprehensibility and importance were used. After evaluating the results, it was stated that on the readability aspect the developed system can be understood by students at the age of 13-15 years; computational time is low (round 2.64 s) and sufficient scores for relevance and truthfulness and comprehensibility and importance were obtained. Therefore, the proposed system can be used to generate text for describing weather news and air quality.
Observations and Modeling of the Surface Aerosol Radiative Forcing during UAE

Aerosol radiative forcing in the Persian Gulf region is derived from data collected during the United Arab Emirates (UAE) Unified Aerosol Experiment (UAE). This campaign took place in August and September of 2004. The land–sea-breeze circulation modulates the diurnal variability of the aerosol properties and aerosol radiative forcing at the surface. Larger aerosol radiative forcing is observed during the land breeze in comparison to the sea breeze. The aerosol optical properties change as the onshore wind brings slightly cleaner air. The mean diurnal value of the surface aerosol forcing during the UAE campaign is about 20 W m , which corresponds to large aerosol optical thickness (0.45 at 500 nm). The aerosol forcing efficiency [i.e., broadband shortwave forcing per unit optical depth at 550 nm, W m 2 ( 500) ] is 53 W m 2 ( 500) 1 and the average single scattering albedo is 0.93 at 550 nm.
Solution of the Transport Equation Using Graphical Processing Units

Computational Fluid Dynamics (CFD) always have struggled for faster computing resources to solve their problems. Until a few years ago, it was possible to just wait a few months and buy a new faster machine. Unfortunately, current technology bumped into a wall: the ever decreasing die size with increasing transistor density has made heat problems unbearable. The solution for growth is now, more than ever, parallel computing. The CPU industry already has turned multicore. But depending on the problem, the speedup of parallel computing can be from negligible to linear scaling, with the number of processing units. Meanwhile, the graphic cards industry was pursuing it’s own path, using parallel, dedicated hardware from the start and drove by the rich market demand of gamers. The Graphics Processing Unit (GPU) gained more capabilities and, in the last couple of years, toolkits and dedicated frameworks allowing for the true start of the exploration of GPU power for general computing. This work focus on dissecting and exploring the GPU for solving partial differential equation problems.
DenseNets for Time Series Classification: towards automation of time series pre-processing with CNNs

It is well known that data normalization is a fundamental preprocessing step for learning using Convolutional Neural Networks (CNN). Multiple normalization techniques have been proposed and finding an appropriate one is not an easy task. Motivated by applications in the energy consumption field, we study Time Series Classification (TSC) with deep learning techniques. We adapt DenseNets to a new convolutional architecture for TSC. We conduct an experimental study the impact of different data normalization techniques on this architecture. We propose a solution to mitigate different pre-processing methods and show its applicability across various fields.
Floating Treatment Wetland Mesocosm Experiments: Impact of hydraulic regime and organic material in mats Expérience Mésocosme Marais Flottant : impact du régime hydraulique et de la présence de matière organique dans le radeau

The aim of the present study was to define to which extent the treatment performance of Floating Treatment Wetlands (FTWs) is impacted by the hydraulic regime (dynamic versus static conditions) and the presence of organic material. This was investigated in a mesocmsm experiment using synthetic stormwater. The results indicate that FTWs with (FTWorg) or without (FTWpet) organic mat provide similar additional PO4 treatment compared to a Control (additional 46 and 39% mass removal efficiencies (MRE), respectively). Similar MREs were achieved in static and dynamic regime. NO3 was significantly removed only by FTWorg whose organic mat most probably enhanced denitrification, and this mainly during the static mode. It is worth mentioning that the synthetic stormwater didn’t comprise any organic carbon which is rarely the case in the field. FTWpet would most probably enable denitrification in a real application however FTWorg would be more efficient at removing NO3 for low organic carbon effluents. No overall significant difference was observed between the Control and the FTW treatments for NH4 and TSS. Enough microorganisms might have been able to develop on the walls of the tanks to nitrify NH4, which mainly happened during the static mode. The somehow limited roots’ development of the FTWs might have limited TSS entrapment into roots’ biofilm. However it seems that the planted treatment limited re-suspension, which was observed in the Control. TSS was similarly removed during the static and dynamic stage for the planted treatments.
Cardiac Ion Channelopathies and the Sudden Infant Death Syndrome

The sudden infant death syndrome (SIDS) causes the sudden death of an apparently healthy infant, which remains unexplained despite a thorough investigation, including the performance of a complete autopsy. The triple risk model for the pathogenesis of SIDS points to the coincidence of a vulnerable infant, a critical developmental period, and an exogenous stressor. Primary electrical diseases of the heart, which may cause lethal arrhythmias as a result of dysfunctioning cardiac ion channels (“cardiac ion channelopathies”) and are not detectable during a standard postmortem examination, may create the vulnerable infant and thus contribute to SIDS. Evidence comes from clinical correlations between the long QT syndrome and SIDS as well as genetic analyses in cohorts of SIDS victims (“molecular autopsy”), which have revealed a large number of mutations in ion channelrelated genes linked to inheritable arrhythmogenic syndromes, in particular the long QT syndrome, the short QT syndrome, the Brugada syndrome, and catecholaminergic polymorphic ventricular tachycardia. Combining data from population-based cohort studies, it can be concluded that at least one out of five SIDS victims carries a mutation in a cardiac ion channel-related gene and that the majority of these mutations are of a known malignant phenotype.
Basic life support (BLS) in adults

INTRODUCTION — Cardiopulmonary resuscitation (CPR) as we recognize it today was developed in the late 1950s and 1960s. Elam and Safar described the technique and benefits of mouth-to-mouth ventilation in 1958 [1]. Kouwenhoven, Knickerbocker, and Jude subsequently described the benefits of external chest compressions [2], which in combination with mouth-to-mouth ventilation form the basis of modern CPR. External defibrillation, first described in 1957 by Kouwenhoven [3], has since been incorporated into resuscitation guidelines.
Comprehensive EST Based Analysis of Differentially Expressed Stress Genes/Factors in Comparative Mode Among Four Legumes

Background: Legume is one of the worldˈs most important crop, it is consumed worldwide and play a significant role in the economy of producing countries. Legume crop productivity is severely affected due to various stress factors both biotic and abiotic(e.g. drought, salinity, cold, ethylene temperature, kinase cascade) these stress factors both biotic and abiotic significantly impact the production of crop in response to these, plants activates a number of defense mechanism that function to increase tolerance in adverse conditions. Therefore tracking the candidate genes responsible for stress tolerance through sequence similarity and functional studies is becoming increasing important for breeding and will act as useful resource for comparative genomics and can be further used as molecular markers or for genetic transformation to develop desired. Thus, research initiatives have been launch to produce genomic and transcriptomic data about legumes species(Cajanus cajan, Cicer arietinum, Pisum sativum and Lens culinaris). Results: Assembling the ESTs of Cajanus cajan, Cicer arietinum, Pisum sativum, Lens culinaris and by applying various bioinformatics tools, the detection of GC content through GC profile, prediction of ka/ks values using MEGA 5.0, identified legume genes under purifying and positive selection and phylogenetic relationship among various stress factors(biotic and abiotic) in four legume species. On these result we emphasize gene annotations and discuss various stress factors based on the categories defined. Conclusion: Identifying and mining genes involved in stress response represent a key step to unraveling and manipulating stress tolerance in legumes. Comparative analysis among the legumes within the same species and between species will enable us to identify species specific genes underlying stress response. Despite knowing that comparisons between these legumes species data should be carefully inspected, our initiative established possible transcriptome elements that could guide the legumes specific community in unraveling the molecular mechanism that distinguish these four extremely important legumes species. In addition, the annotation of legumesspecific/stress prominent genes adds new element to genomic initiatives that our searching for traits (factors) that could differentiate legume each species from other. We believe that such data are a valuable aid to the interpretation of legume development, 114 Sabeen Fatma et al.: Comprehensive EST Based Analysis of Differentially Expressed Stress Genes/Factors in Comparative Mode Among Four Legumes providing insight that could help in legumes reading program and indicating potentialtargets for functional analysis and biotechnology products of such socially and economically important legume species.
Technical and Economic Assessment for Hybrid PV Mini-Grid Projects Optimized Layout and Sizing of Off-Grid Power Plant for SKA1-Low Radio Telescope

Unavailability of utility power at the isolated location where the Australian component of the Square Kilometre Array (SKA1-Low) is going to be built motivates the technical and economic viability study of a standalone photovoltaics-based power plant gathered in this paper. This includes a highly conceptual power system design, analysis of load profile characteristics and particular power requirements, simulation-based sizing optimization, and a detailed economic evaluation of the system initial and operating costs. While the system’s performance evaluation is not the main focus in this paper, consideration of system components’ cooling requirements is shown to be necessary, as it considerably influences the total power requirements. From the economic analysis, it is found that economies of scale and technology price-experience curves play a major role for an accurate LCOE estimation. Regarding the optimized layout, it has been found that distributed generation (DG) is only economical in this particular case for antennas clusters further than 10 km away from the Central Processing Facility, while the rest of inner antennas and Remote Processing Facilities should be powered from a central power plant and a reticulated transmission line system. KeywordsSquare Kilometer Array (SKA); PV-battery; PVbattery-diesel; Distributed Generation (DG); Off-Grid
Water recovery and air humidification by condensing the moisture in the outlet gas of a proton exchange membrane fuel cell stack

Humidification is one of the most important factors for the operation of proton exchange membrane fuel cell (PEMFC). To maintain the membrane at hydrated state, plenty of water is needed for the state-of-theart of PEMFC technology, especially in large power applications or long time operation. A condenser is introduced to separate liquid water from the air outlet for air self-sufficient in water of the stack in this study. The condensed temperature at the outlet of the condenser and water recovered amount for air self-sufficient in water are investigated theoretically and experimentally. It is shown that the condensed temperature for air self-sufficient in water is irrelevant with the working current of the stack. When the condenser outlet temperature was above the theoretical line, recovery water was not sufficient for the air humidification. On the contrary, it is sufficient while the temperature was below the theoretical line. It is also shown that when the moisture is sufficiently cooled, large amount water can be separated from the outlet gas, and it increased almost linearly with the time. With the introduction of the condenser, the recovered amount of water can easily satisfy the air self-sufficient in water by condensing the outlet gas to a proper temperature. 2012 Elsevier Ltd. All rights reserved.
DDDT_A_196319 1145..1153

Department of Respiratory Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, People’s Republic of China Background: Non-small-cell lung cancer (NSCLC) was known as the most malignant tumor. Paclitaxel (PTX) is the effective drug used for the treatment of NSCLC; however, it also exhibits severe side effects. Emodin could induce apoptosis of NSCLC cells and serve as a potential cancer therapeutic agent. However, the effects of combination of emodin with PTX on NSCLC remain unclear. Thus, this study aimed to investigate the effects of emodin in combination with PTX on A549 cells. Materials and methods: The effects of combination treatment on the proliferation, apoptosis and invasion of NSCLC cells were evaluated by CCK-8, flow cytometric and TUNEL assays, respectively. In addition, Western blotting was used to detect the expressions of Bax, Bcl-2, active caspase 3, p-Akt and ERK in cells. Results: Combination of emodin with PTX synergistically inhibited the proliferation of A549 cells in vitro. In addition, we found that emodin significantly enhanced PTX-induced apoptosis in A549 cells via increasing the expressions of Bax and active caspase 3 and decreasing the levels of Bcl-2, p-Akt and p-ERK. Moreover, emodin markedly enhanced antitumor effect of PTX on A549 xenograft without significant side effects in vivo. Conclusion: Our findings indicated that emodin could significantly enhance antitumor effect of PTX in vitro and in vivo. Therefore, the combination of emodin with PTX may serve as a potential strategy for the treatment of patients with NSCLC.
20th ICCRTS Implementing Covert Communication Networks on Gunther-Hartnell Clique Graph Topologies

A covert communications network (CCN) is a connected, overlay peer-to-peer network used to support communications within a group in which the survival of the group depends on both anonymity of communications, and concealment of network membership to both other members of the group and external eavesdroppers. These requirements are much more stringent than for typical privacy and anonymity systems. Network membership is protected through strict topology management in order to limit each participant’s knowledge of the network addresses (IP address, email, etc.) of other participants. Gunther-Hartnell ’clique’ graphs, Clk, are topologies built by sparsely connecting cliques of order k. In this paper, we examine the application of these topologies for use in covert communication networks. We propose a logical address mechanism for that, when combined with a basic anonymity protocol, provide a degree of membership concealment. We describe how these topologies can be constructed in a distributed manner on an arbitrary number of nodes and how routing can be conducted in these topologies in constant time. The opinions in this paper are those of the authors and do not necessarily reflect the opinions of the U.S. Military Academy or the U.S. Army.
Physical Activity: Measurement and Health Outcomes for People of Advanced Age in New Zealand

ii Acknowledgements . iii List of Tables . viii List of Figures . x List of Abbreviations . xi Chapter 1: Introduction . 1 Rationale for the Thesis . 1 1.1 Objective of the Thesis . 1 1.2 Structure of the Thesis . 1 1.3 Theoretical Framework of Thesis . 2 1.4 Chapter 2: Physical Activity and Health Outcomes in Older People . 3 Introduction . 3 2.1 Background . 3 2.2 2.2.1 An Ageing Population in New Zealand . 3 2.2.2 Physical Activity and Positive Ageing . 3 Aim . 6 2.3 Physical Activity and Older Adults: Depression, Health Related Quality of Life, and 2.4 Functional Status: A Systematic Review of Reviews . 7 2.4.
An Epidemioiogical Study of Obesity among Elderly in Chandigarh

Methods : The study was conducted in Union Territory of Chandigarh, a modern city in Northern India having a population of over 0.8 million 362 subjects over the age of 65 years were interviewed after having being selected through stratified random technique covering 7937 family members in 1882 houses. Objectives : This community based study assessed the prevalence of obestity and associated factors among elderly population. Results : Overweight (BMI>25kg/m2) was observed among 120 subjects (33.14%), obestity (BMI>30) in 28 (7.54%) of the elderly. 14.36% elderly subjects were undernourished (BMI<18.5)) Over weight/obesity was higher among females (42.1%) than males (20.9%). Prevalence of hypertension was 82.5% among overweight elderly in comparison to 45.87% among non-overweight/obese. Similarly probable diabetes was 15.0% and 9.92% in overweight and non-overweight elderly, respectively. Conclusion : Overweight among one-third elderly reveals existence of a high prevalence. Higher prevalence of hypertension and diabetes among overweight elderly was observed. There is an urgent need to adopt multidisciplinary approach to weight control by awareness compaign and adopting strategies to increase physical activity and changing eating behaviour.
Evaluation of Lexicon Optimization based on Discriminative Learning

In agglutinative languages, selection of lexical unit is not obvious. Morpheme unit is usually adopted to ensure a sufficient coverage, but many morphemes are short, resulting in weak constraints and possible confusions. In this paper, we propose a discriminative approach to select lexical entries which will directly contribute to ASR error reduction. We define an evaluation function for each word by a set of features and their weights, and the measure for optimization by the difference of WERs by the morpheme-based model and by the word-based model. Then, the weights of the features are learned by a perceptron algorithm. Finally, word (or sub-word) entries with higher evaluation scores are selected to be added to the lexicon. This method is successfully applied to an Uyghur large-vocabulary continuous speech recognition system, resulting in a significant reduction of WER and the lexicon size. Further improvement is achieved by combining with a statistical method based on mutual information criterion.
Classifying humans using deep time-series transfer learning : accelerometric gait-cycles to gyroscopic squats

In this paper, we’d like to disseminate a positive, serendipitous result entailing deep time-series transfer learning in the domain of human kinematics. We begin with a convolutional neural network model pre-trained to classify human subjects based on bipedal gait data emanating from tri-axial accelerometric sensors on commercial smartphones. We then use this model to transfer-learn into the problem domain of classifying subjects using tri-axial gyroscopic data emanating from a commercial motion-sensor device mapping to the activity of body-weight squats (of vividly different temporal spans). We achieve 87% top-1 accuracy on a 20-class problem even with a 60-40 train-test split. We hope that this cross-sensor, crossdevice and cross-activity transfer learning success will pave the way for widespread deployment of deep transfer learning techniques in the domain of human kinematics analysis.
An improved LIDAR SLAM algorithm based on FastSLAM for autonomous vehicle

In order to realize autonomous navigation of autonomous vehicles that don't rely on GPS, an improved LIDAR SLAM method based on FastSLAM algorithm is proposed in this paper. First, a large number of data obtained by LIDAR are prepossessed, including sparse points removal, Voxel Grid, point cloud separation. Then, the processed data are used to make the point cloud match of the adjacent frame by using the method of PLICP algorithm to obtain the coarse positioning of the autonomous vehicle. After that, the particle scatter points are carried out near the rough locations, and the Niche Technique Particle Swarm Optimization method is introduced to locate the autonomous vehicle accurately. The map of LIDAR point cloud is represented by the raster map. After getting the precise positioning of the autonomous vehicle, a local map which carried by the particle is added to the global map to update the map. Finally, the system outputs the map of the environment and the trajectory of the autonomous vehicle. The validity of the proposed method is proved by the experiment on autonomous vehicle platform. The experimental results show that the proposed technique could reduce the position error and successfully build the map of the environment.
Chapter 15: 3D Geological Modelling at the Geological Survey of Italy (Servizio Geologico d’Italia): an Overview

D’Ambrogi, C. 2019. 3D geological modelling at the Geological Survey of Italy (Servizio Geologico d ’Italia): an overview; Chapter 15 in 2019 Synopsis of Current Three-Dimensional Geological Mapping and Modelling in Geological Survey Organizations, K.E. MacCormack, R.C. Berg, H. Kessler, H.A. J. Russell, and L.H. Thorleifson (ed.), Alberta Energy Regulator / Alberta Geological Survey, AER/AGS Special Report 112, p. 159–170.