Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Rice Pest Population Occurrence with Satellite-Derived Crop Phenology, Ground Meteorological Observation, and Machine Learning: A Case Study for the Central Plain of Thailand

The brown planthopper Nilaparvata lugens (BPH) is one of the most harmful insect pests in rice paddy fields, which causes considerable yield loss and consequent economic problems, particularly in the central plain of Thailand. Accurate and timely forecasting of pest population incidence would support farmers in planning effective mitigation. In this study, artificial neural network (ANN), random forest (RF) and classic linear multiple regression (MLR) analyses were applied and compared to forecast the BPH population using weather and host-plant phenology factors during the crop dry season from 2006 to 2016 in the central plain of Thailand. Data from satellite earth observation was used to monitor crop phenology factors affecting BPH population density. An ANN model with integrated ground-based meteorological variables and satellite-derived host plant variables was more accurate for short-term forecasting of the peak abundance of BPH when compared with RF and MLR, according to a reasonably validating dataset (RMSE of natural log-transformed (ln) BPH light trap catches = 1.686, 1.737, and 2.015, respectively). This finding indicates that the utilization of ground meteorological observations, satellite-derived NDVI time series, and ANN have the potential to predict BPH population density in support of integrated pest management programs. We expect the results from this study can be applied in conjunction with the satellite-based rice monitoring system developed by the Geo-Informatic and Space Technology Development Agency of Thailand (GISTDA; http://rice.gistda.or.th) to support an effective pest early warning system.
A three level sensor ranking method based on active perception

It can be said that the growth of cloud computing and Internet of Things (IoT), further drive the growth of data volume. This is due to large part to the development of a set of technologies, each allowing the development or creation of the other. OoT provides an infrastructure for physical and virtual things to communicate seamlessly in an intelligent environment. In the IoT paradigm, sensors are collecting and transmitting data that must be stored and processed. Thus, many studies have been dedicated to the task of searching, indexing and ranking sensors in the IoT environment. This paper presents a method for ranking sensors using the theory of active perception. The solution was evaluated using four data sets (real and synthetic). The results show that the proposed solution can provide reliability in the use of sensor data, with a minimum processing cost. To the best of our knowledge active perception has never been used for sensor ranking as it has never been used for the treatment of anomalies.
High Fidelity Impedance Control of Series Elastic Actuator for Physical Human-machine Interaction

This paper proposes a novel control system using a Series Elastic Actuator (SEA) for human-machine interactive applications. SEA allows high torque transparency between a forward and a backward torque transmission with the geared motor and the closed-loop controller and it so enables that human-friendly interaction is achieved. Even though the torque-controlled SEA system plays important roles in human-machine interactive applications, there is performance limitation to implement pure interactive behavior due to the imperfection of torque source such as torque ripple of the electric motor. The limitation of SEA causes the uncomfortable feeling to the human in the application such as steer-by-wire system which is the target system in this paper. This paper focuses on the minimization of the influence that is caused by the torque ripple of the electric motor in the SEA system. The proposed controller based on the principle of Disturbance Observer (DOB) is designed to realize the desired human-machine interactive behavior. Experiments have been conducted to explore the characteristics of SEA system and to verify the performance of the proposed controller.
Novel Li2MnO3 nanowire anode with internal Li-enrichment for lithium-ion battery†

Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. Accepted Manuscript Nanoscale
Neural Network Assisted Active Constellation Extension for PAPR Reduction of OFDM System

One of the major drawbacks of Orthogonal Frequency Division Multiplexing (OFDM) is its high Peak-to-Average Power Ratio (PAPR) problem, which may result in nonlinear signal distortion and thus significantly reduces the efficiency of the power amplifier. In this paper, we propose a novel Neural Network assisted Active Constellation Expansion (NN-ACE) method to reduce the PAPR of OFDM symbols. The extension vector of ACE is learned by an autoencoder to reduce the PAPR while keeping the signal power increment low. Moreover, a compromise between PAPR-reduction and power-increment can be adjusted by a weight factor in the loss function according to different requirements. The proposed neural network based ACE scheme is proved to be efficient of achieving lower PAPR and thus reduce the bit error rate (BER) in a nonlinear channel model.
Refining the variational posterior through iterative optimization

Variational inference is a popular approach for approximate Bayesian inference that is particulary promising for highly parameterized models such as deep neural networks. A key challenge of variational inference is to approximate the posterior over model parameters with a distribution that is simpler and tractable yet sufficiently expressive. In this work, we propose a method for training highly flexible variational distributions by starting with a coarse approximation and iteratively refining it. Each refinement step makes cheap, local adjustments and only requires optimization of simple variational families. We demonstrate theoretically that our method always improves a bound on the approximation (the Evidence Lower BOund) and observe this empirically across a variety of benchmark tasks. In experiments, our method consistently outperforms recent variational inference methods for deep learning in terms of log-likelihood and the ELBO.
Diagnosis of osteoporosis using the low frequency acoustic response of mice femoral bones irradiated by a high frequency acoustic radiation pulse

Quantitative characterization of the mechanical properties of bones is of great importance to diagnostic pathological processes. For example, osteoporotic bones have some differences in the mechanical properties if compared with the healthy ones. In this study a new technique based on acoustic radiation force has been used as an alternative to evaluate the differences in the mechanical properties of bones, that can lead to a new method to the diagnosis of bone diseases. The technique uses a single high-frequency ultrasound pulse (MHz) to excite the medium. Non-linear interactions of this acoustic wave in the tissue produces a lower frequency signal (kHz). Femoral bones where excised from 10 healthy mice and also from 10 mice where osteoporosis had been induced. Using µCT, the porosity, trabecular number, trabecular spacing, connectivity and the connectivity density of those bones where obtained. The following step was to irradiate those samples with a short focused acoustic radiation pulse (f=3.1 MHz, t=15 µs) and acquire the low frequency acoustic response using a dedicated hydrophone (ITC 6050) with acquisition band going from 1kHz to 70 kHz. A spectral analysis of the acquired signal has been done and the results compared with the µCT data in order to see if there where correlation between them. Also, a hypothesis test has been done to see if the technique can differentiate the samples coming from the healthy group and the osteoporotic. A strong correlation was obtained between the values from the spectral analysis of the low frequency acoustic response and from the trabecular number parameter µCT (spearman correlation coefficient of 0.72 and p-value of 0.02), also a moderate correlation has been found with the connectivity parameter ( spearman correlation coefficient of 0.69 and p-value of 0.03) showing that the technique is sensible to the mechanical parameters .
Genetic Markers for Species Conservation and Timber Tracking: Development of Microsatellite Primers for the Tropical African Tree Species Prioria balsamifera and Prioria oxyphylla

Research Highlights: Two novel sets of polymorphic microsatellite markers were developed for Prioria balsamifera and Prioria oxyphylla through high-throughput sequencing. Validation in two populations of each species proved the utility of the developed primers to estimate genetic diversity at population level. Background and Objectives: Prioria balsamifera and Prioria oxyphylla are tropical tree species from Central Africa. They produce a high-quality, multi-purpose timber that is of great interest to the international market. Prioria balsamifera has been included as ‘endangered’ on the IUCN Red List of Threatened Species. In order to set up adequate management plans and facilitate timber tracking, knowledge on the genetic diversity at population level is needed. Therefore, we aim to develop microsatellite markers that can be used for species conservation, forensics, plant breeding and population genetics studies. Materials and Methods: Genomic DNA of P. balsamifera and P. oxyphylla was sequenced on an Illumina NextSeq platform (Illumina Inc., San Diego, CA, USA), generating 829,421 and 772,018 paired-end reads that contained 7148 and 7004 microsatellite sequences, respectively. The QDD-pipeline was used to design primers, which were tested for amplification in two populations of each species. Cross-species amplification was tested in all seven African Prioria species. Results: For P. balsamifera, 16 polymorphic microsatellite markers were developed and combined in three multiplexes. Inbreeding appeared to be absent but genetic diversity was low in both populations. For P. oxyphylla, 15 polymorphic microsatellite markers were developed and combined in three multiplexes. Genetic diversity was low in both populations and estimated null allele frequencies were high for multiple loci. Cross-species amplification tests demonstrated the occurrence of conserved loci that amplified for most of the African Prioria species. Conclusions: The microsatellite markers prove to be useful for estimating genetic diversity at population level. These novel markers can be used to study gene flow and spatial genetic structure in Prioria species, which is needed to set up proper conservation guidelines and to prevent genetic erosion.
Multi-Port System for Braking Energy Recovery in Diesel-Electric Locomotives - Focus on the Multi-Interphase Transformer Design

Generally, in diesel-electric locomotives, the energy generated during braking is dissipated in resistors through a dynamic braking mechanism. To exploit this energy, a multi-port system might be employed, using static converters to control the power flow between sources and loads. Due to a lack of space on the traction locomotives, high-power-density DC-DC converters based on multi-state switching cell (MSSC) were chosen to connect sources and loads to a common DC-link. One of the main challenges of this type of converter is the physical design of the multi-interphase transformer (MIPT). Since there is a shortage in literature regarding the MIPT project with more than two windings, this paper aims to present the detailed design of a 1 kW multi-interphase transformer and its validation through theoretical/numerical simulations and experimental results.
Exploring Identity through Appraisal Theory: a Corpus Annotation Methodology

This paper is concerned with how Appraisal Theory (Martin and White 2005) can be used to shed light on the identity that writers/speakers assume when they produce text, and on the identity these text producers assign to the other voices that participate in the text. Further, we present a methodology of corpus annotation which best supports this approach to identity. The term ‘identity’ has many meanings, not only between the many fields that make up human practice, but also as we focus in on the field of linguistics. I do not want to enter too deeply into the discussion of what ‘identity’ is, except to the extent that I will focus on two aspects of ‘identity’ that can be brought to light through the analysis of text in terms of Appraisal Theory. Firstly, people identify themselves through association: we declare our identity by affiliating ourselves with socially defined groupings of people. Teenagers declare their identity when they espouse one rock band over all others, and make this declaration multi-semiotically, through the adoption of a look (clothing, hair-style, etc.), and perhaps through a way of speaking (e.g., ‘Hey dude’), and even through the way they walk or gesture. This is not only restricted to teenagers, nearly all of us declare our identity as belonging to a particular sub-grouping of society, whether it is as a businessman in a suit, a hippy in a sarong, or as a sportswoman in running shorts. A second way to explore the identity of individuals is in terms of the set of values they identify with: do they value conservatism over radicalism, ecology over economy, justice over legality, etc. If we can identify the set of social characteristics that an individual values, we have taken a step towards specifying the identity construct of the individual. The first goal of this paper is to describe how Appraisal Theory can be used to explore identity in terms of both group affiliation (in at least a limited sense), and the value structure of writers. The second goal of the paper is to show how corpus annotation software can be used to achieve these ends. The ideas here can be applied within most corpus annotation environments, although UAM CorpusTool (O’Donnell 2008a, 2008b) will be used for illustration.
A Variable Symbol Duration Based FTN Signaling Scheme for PLS

Physical layer security (PLS) has become an urgent issue as the growing importance of the information security. In this paper, a variable symbol duration based faster-than-Nyquist (FTN) signaling scheme for PLS is proposed. The information rates of the cooperative link and the uncooperative link are derived. The positivity of the secrecy rate of the cooperative link is proved. Numerical results show that the cooperative link has higher information rate than the uncooperative link, the optimal secrecy rate corresponds to a certain $E_{b}/N_{0}$ and the bigger the difference of the symbol duration is, the higher the secrecy rate will be for the cooperative link.
A characterization of Australian shortfin mako shark anglers

Understanding the human dimensions of recreational fisheries is critical to the development of effective fisheries management regulations. This study aimed to characterize Australian shortfin mako shark (Isurus oxyrinchus) anglers in terms of their gear use, perceptions on circle hooks, perceptions on sharks and shark conservation, and attitudes towards fisheries management. A targeted web survey was completed by 272 shortfin mako anglers distributed across southeastern Australia. Responses were compared across angler subgroups in relation to their state of residence, membership to an angling club, and tendency to release or keep captured sharks. Overall, anglers' perceptions about how their fishing behaviours and gear choices may affect the survival of released shortfin mako sharks were quite in line with existing scientific knowledge though anglers believed their behaviours have less of an impact on shark stocks than other threats such as commercial fisheries. Gear selection was determined largely by fishing preference (harvest or catch-and-release) of the angler, with those practicing catch-and-release more frequently using circle hooks. State of residence also influenced the perceptions of anglers towards sharks and shark survival as well as their attitudes towards fisheries management. Angler support for precautionary management suggests that a better understanding of the potential impacts of recreational fishing on shark stocks may assist in promoting greater accountability and responsible fishing practices amongst these resource users; however, improved communication between recreational fishers, management authorities, and fisheries scientists is a necessary precursor to this step.
Walking Pad and Gyroscope-Based Object Manipulation for Virtual Reality CAVE

Thanks to the recent advancement in computer hardware and software, the virtual reality is becoming a hot topic, again. It can be utilized in various settings - from entertainment through education and workforce training to a training and assessment of visuospatial cognitive functions. A fully immersive virtual reality experience requires not only high quality stereoscopic graphical output but also input devices that feel natural to use. In this paper we present two cost-effective solutions that try to fulfil this requirement: a low-cost modular walking pad and an application for an Android device, which utilizes the gyroscope of the device to manipulate with objects in a virtual environment. While both solutions have been primarily developed to be used with cave automatic virtual environments, they are also suitable for installations utilizing see-through head-mounted displays or ordinary computer screens.
Comparative Analysis of the Utilization of Supercapacitor Versus Grid-Tie Inverter Regenerative Braking Methods for Elevator Systems

In this paper, supercapacitors and grid-tie inverters are compared as means of integrating regenerative braking functionality into elevator systems. In dynamic braking, a conventional motor drive is unable to utilize energy during braking periods because it is powered by a rectifier in which energy flows in only one direction. Typically, braking resistors are used to dissipate any excess energy generated that can result in a breakdown of the device if left uncontrolled. Alternatively, supercapacitors or grid-tie inverters can be installed to the DC-link and the energy either stored for future use or fed to the power grid, thus preventing energy waste. Models for these two regenerative braking methods are constructed and simulated in the Simulink environment in order to compare their energy efficiencies under several unique elevator usage patterns. In usage patterns that allow the motor to generate energy within a long duration, the simulation results show the supercapacitor option is less of an improvement in energy efficiency than the grid-tie method due to energy flowing through two energy conversion devices. On the contrary, in usage patterns that limit regeneration within short bursts, the grid-tie inverter option is less efficient than the supercapacitor method due to output current limitations.
Uniform Sampling Methodology to Construct Projection Matrices for Angle-of-Arrival Estimation Applications

This manuscript firstly proposes a reduced size, low-complexity Angle of Arrival (AoA) approach, called Reduced Uniform Projection Matrix (RUPM). The RUPM method applies a Uniform Sampling Matrix (USM) criterion to sample certain columns from the obtained covariance matrix in order to efficiently find the directions of the incident signals on an antenna array. The USM methodology is applied to reduce the dependency between the adjacent sampled columns within a covariance matrix; then, the sampled matrix is used to construct the projection matrix. The size of the obtained projection matrix is reduced to minimise the computational complexity in the searching grid stage. A theoretical analysis is presented to demonstrate that the USM methodology can increase the Degrees of Freedom (DOFs) with the same aperture size and number of sampled columns compared to the classical sampling criterion. Then, a polynomial root is constructed as an alternative efficient computational solution of the UPM method in a one-dimensional (1D) array spectrum peak searching problem. It is found that this distribution increases the number of produced nulls and enhances noise immunity. The advantage of the RUPM method is that it is appropriate to apply for any array configuration while the Root-UPM offers better estimation accuracy with less execution time under a uniform linear array condition. A computer simulation based on various scenarios is performed to demonstrate the theoretical claims. The proposed direction-finding methods are compared with several AoA methods in terms of the required execution time, Signal-to-Noise Ratio (SNR) and different numbers of data measurements. The results verify that the new methods can achieve significantly better performance with reduced computational demands.
Transport of Microplastic Particles in Saturated Porous Media

This study used polystyrene latex colloids as model microplastic particles (MPs) and systematically investigated their retention and transport in glass bead-packed columns. Different pore volumes (PVs) of MP influent suspension were first injected into the columns at different ionic strengths (ISs). The breakthrough curves (BTCs) were obtained by measuring the MP concentrations of the effluents. Column dissection was then implemented to obtain retention profiles (RPs) of the MPs by measuring the concentration of attached MPs at different column depths. The results showed that the variation in the concentrations of retained MPs with depth changed from monotonic to non-monotonic with the increase in the PV of the injected influent suspension and solution IS. The non-monotonic retention was attributed to blocking of MPs and transfer of these colloids among collectors in the down-gradient direction. The BTCs were well simulated by the convection-diffusion equation including two types of first-order kinetic deposition (i.e., reversible and irreversible attachment). However, this model could not well simulate the non-monotonic retention profiles due to the fact that the transfer of colloids among collectors was not considered. The results in this study are critical to developing models to simulate the fate and transport of MPs in porous media such as soil.
3D high frame rate flow measurement using a prototype matrix transducer for carotid imaging

To accurately investigate the state of the carotid artery by the local haemodynamics and motion of the plaque using ultrasound, high-frame rate volumetric imaging is necessary. We have specifically designed a matrix array for this purpose. In this proceeding we will focus on imaging a volumetric flow profile using this matrix. For this purpose, we extend a fast frequency domain vector flow imaging method to 3D and perform measurements on a flow phantom. The results indicate that it is feasible to estimate 3D velocity vectors on a 3D grid using our matrix transducer and the proposed algorithm.