Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of environmental noise policies and economics in 2014-2016

This review has highlighted the important developments relating to noise issues performed by international organizations and the activities in some developed and developing countries to improve environmental noise management. The World Health Organization is in the process of finalizing the WHO Environmental Noise Guidelines for the European Region as an update of the WHO Community Noise Guidelines of 1999/2000. The International Civil Aviation Organization, in Chapter 14, has lowered the current chapter 4 standards for subsonic jet aircraft and propeller driven aeroplanes. In 2014-2016 the European Parliament and the Council and the European Commission have achieved significant progress in amending laws and regulations and creating new legislation. Efforts referred to regulating the EU type-approval of all new buses and trucks with regard to their sound level and the introduction of noise-related operating restrictions at airports, in accordance with ICAO’s Balanced Approach. The EC amended the END and arranged for the evaluation of the END based on the criteria of relevance, coherence, effectiveness and impacts, efficiency, and EU added value. Two new regulations addressed the issues of technical specification for interoperability of high-speed trains related to sound emission levels and the implementation of provisions establishing noise-differentiated track access charges. The European Environment Agency published the ‘Noise in Europe’ report describing the impacts of noise exposure in terms of cases of premature death, hospital admissions, cases of hypertension and annoyance. In addition, the European Environment Agency developed a good practice guide on quiet areas, refined the methodology for a quietness suitability index, and published its report on “Quiet areas in Europe”. In the United Kingdom, the Civil Aviation Authority reported new and updated evidence on attitudes to aviation noise around airports in England, and the Airports commission published recommendations for development in the aviation sector around London. The Department of Transport formulated a draft Airports National Policy Statement on expansion options for South East England airports. Switzerland published its Environment Report 2015 and estimated the annual external costs of road traffic, railway and aircraft noise which are quite substantial. Developing countries become increasingly aware that noise levels have gone up abnormally high and can cause acute and chronic health impacts on the human population. In consequence, Costa Rica has lowered the permissible sound pressure levels, and India, Iraq and Mexico have set new daytime and night-time noise standards. Tanzania has approved permissible sound pressure limits, which were prepared by the National Environment Management Council almost a decade ago. The Egyptian Environmental Affairs Agency developed a national plan to combat noise, which is currently implemented on a collaborative effort of 11 ministries, a rare phenomenon in developing countries. Kenya is currently committed to develop a strategy for environmental noise management.
Painting Path Planning for a Painting Robot with a RealSense Depth Sensor

The utilization of stereo cameras in robotic applications is presented in this paper. The use of a stereo depth sensor is a principal step in robotics applications, since it is the first step in sequences of robotic actions where the intent is to detect and extract windows and obstacles that are not meant to be painted from the surrounding wall. A RealSense D435 stereo camera was used for surface recording via a real-time, appearance-based (RTAB) mapping procedure, as well as to navigate the painting robot. Later, wall detection and the obstacle avoidance processes were performed using statistical filtering and a random sample consensus model (RANSAC) algorithm.
Nondestructive Assessment of Citrus Fruit Quality and Ripening by Visible–Near Infrared Reflectance Spectroscopy

As non-climacteric, citrus fruit are only harvested at their optimal edible ripening stage. The usual approach followed by producers and packinghouses to establish the internal quality and ripening of citrus fruit is to collect fruit sets throughout ripening and use them to determine the quality attributes (QA) by standard and, in many cases, destructive and time-consuming methods. However, due to the large variability within and between orchards, the number of measured fruits is seldom statistically representative of the batch, resulting in a fallible assessment of their internal QA (IQA) and a weak traceability in the citrus supply chain. Visible/near-infrared reflectance spectroscopy (Vis–NIRS) is a nondestructive method that addresses this problem, and has proved to predict many IQA of a wide number of fruit including citrus. Yet, its application on a daily basis is not straightforward, and there are still several questions to address by researchers in order to implement it routinely in the crop supply chain. This chapter reviews the application of Vis–NIRS in the assessment of the quality and ripening of citrus fruit, and makes a critical evaluation on the technique’s limiting issues that need further attention by researchers.
Microbial colonisation, the missing link: from airborne dispersal to integration within the soil community.

BackgroundGlobal dispersal of microorganisms primarily occurs through airborne transport. Airborne microorganisms can travel thousands of kilometres and be deposited in the most remote places on Earth, from the Arctic to Antarctica, with the potential of invasion and colonisation. The first stage of microbial colonisation is deposition into a new ecosystem. However, how and under what circumstances such deposited microorganisms might successfully colonise a new environment is yet to be determined. Using the Arctic snowpack as a model system, we investigated the colonisation potential of snow derived bacteria deposited onto Arctic soils during and after snowmelt using laboratory-based microcosm experiments set-up to mimic realistic environmental conditions. We tested different melting rate scenarios to evaluate the influence of increased precipitation (via the increase of bacterial inputs and ecosystem disturbance) as well as the influence of soil pH (as the key driver of soil diversity) on bacterial communities and on the colonisation potential.Results We observed several candidate colonisations in all experiments; however, the number of potentially successful colonisation was higher in acidoneutral soils, at the average snowmelt rate measured in the Arctic. While the higher melt rate increased the total number of potentially invading bacteria, it did not promote colonisation. Instead, persistence decreased with time and most potential colonists were not identified by the end of the experiments. On the other hand, soil pH appeared as a determinant factor impacting invasion and subsequent colonisation. In acidic and alkaline soils, bacterial persistence with time was lower than in acidoneutral soils, as was the number of potentially successful colonisations. ConclusionsThis is the first study to investigate bacterial colonisation using the snowpack as a model system, and to demonstrate the low rate of potentially successful colonisations of soil by invading bacteria. It suggests that local soil properties might have a greater influence on the colonisation outcome than increased precipitation or ecosystem disturbance.
Thermo-Chemical Engines: Unexploited High-Potential Energy Converters

Abstract Thermal engines, particularly closed power cycles, are currently a focus of many studies mainly because they represent the only way to exploit renewable thermal energy. To increase the exploitation of available thermal sources, this work investigates the higher potential offered by a complementary technology based on the use of reactive working fluids instead of inert fluids: the here-called “thermo-chemical” engine. Such a power cycle enables the simultaneous conversion of thermal and chemical energy into work. Based on a theoretical approach, this paper explores engine performance considering different stoichiometries and thermodynamic characteristics of reactive fluids and different operating conditions. It is shown that the use of specific equilibrated reactions occurring in the gaseous phase might lead to extremely powerful and highly efficient energy conversion systems in the whole current domain of the application of power cycles. Moreover, it is demonstrated that, unlike classical thermal machines, a thermo-chemical engine allows efficient and powerful exploitation of low-temperature heat sources and high-temperature cold sinks, which in general, characterize renewable thermal energy.
APPLICATION OF FOOD GRADE COATINGS TO TURKEY BUTTOCKS

Battering and breading control the level of moisture removal and fat absorption and also improve the physical and sensorial properties of deep-fried products. The effects of zein, soy protein isolate (SPI), guar and xanthan gums and corn and soy flours on the quality of turkey nuggets were studied using Response Surface Methodology. Turkey buttock chunks were predusted with combinations of zein and SPI (25:75, 50:50, 75:25%), then sprayed with combinations of guar and xanthan gum (0.1:0.3, 0.2:0.2, 0.3:0.1%) after which they were breaded with corn and soy flour (25:75, 50:50, 75:25%). The samples were evaluated for the degree of adhesion, fat absorption, cooking yield and color attributes. The pre-dusting adhesion rate (PD-AR) was higher than 5% with increased zein in the blend. Film-forming properties of zein also reduced fat uptake during frying. Wetting stage altered the last coating adhesion rate (LC-AR). Analytical optimization of nuggets having a good coating, higher cooked yield and desired color were obtained with zein and SPI at the ratio of 73:27% as pre-dusting, guar and xanthan at the ratio of 0.3:0.1%, and corn and soy flour at the ratio of 35:75. Adhesion rate of the last coating and cooking yield were correlated with each other (r=0.73, P<0.001).
Light management in plastic–paper hybrid substrate towards high-performance optoelectronics

Optoelectronic devices are ubiquitously built on substrates. To increase the efficiencies of light coupling into and out of optoelectronic devices, such as thin film solar cells and flexible lighting, a substrate with high transmittance and high haze is desired. Unfortunately, optical transmittance and optical haze are usually contrasting to each other in common substrates: plastic is highly transparent but with a low optical haze, whereas paper has a high optical haze but a low total transmittance. Herein, we combine these two materials through a simple templated infiltration approach to achieve a new type of substrate, plastic–paper, which has a high optical transmittance (>85%) and high transmittance haze (>90%) in a broadband wavelength. The plastic–paper has an ultra-flat surface, is mechanically flexible, durable in different solvents and compatible with standard processing in semiconductors, which are shown by organic light emitting diodes (OLED) fabricated directly onto the plastic–paper substrate. Plastic–paper leads to improved light coupling into and out of optoelectronic devices and demonstrates an improvement in efficiency for both OLED and typical GaAs solar cells. The fabrication method is also fully scalable with roll-to-roll production. The newly developed low-cost, high-performance transparent and hazy substrate is attractive for a range of optoelectronic devices.
Modified Firefly Algorithm for Optimizing Biomedical Breast Cancer Queries

Querying and retrieving Semantic Web data is a challenging task due to the increment in its volume. Many query languages were designed to retrieve Semantic Web data. A popular querying method of communication in Semantic Web is SPARQL. The query languages were designed with some optimization strategies, and it was found in literature that these query languages were not able to handle large volume of data efficiently. In this research, a Modified Firefly Algorithm (MFA) is applied to optimize the SPARQL queries so that it can retrieve data from a large Semantic Web repository efficiently by reducing query execution time. Every query will have multiple query plans generated with different cost values. The challenge is to choose the best query plan which reduces the query cost and query execution time. The proposed algorithm uses the best query plan in the previous iteration to calculate the distance between two query plans using the radius parameter. The proposed algorithm generates a query plan which is a global optimal solution. MFA is evaluated using the BioPortal dataset with triples containing breast cancer. Experimental analysis is conducted to identify the significant improvement in performance of the proposed work with the existing nature inspired query optimization algorithms. The efficiency of MFA is compared with other algorithms in terms of query execution time and the performance is evaluated.
Dual Adaptive Neural Network Controller for Underactuated Systems

SUMMARY A new stable adaptive controller based on a neural network for underactuated systems is proposed in this paper. The control scheme has been developed for two underactuated systems as examples. The Furuta pendulum and the Inertia Wheel Pendulum (IWP) have been examined in this paper. The presented approach aims to address the control problem of the given system in swing up, stabilization, and disturbance rejection. To avoid oscillations, two adaptive neural networks (ANNs) are implemented. The first one is used to approximate the equivalent control online and the second one to minimize the oscillations.
Application of Bifidobacterium spp in beverages and dairy food products: an overview of survival during refrigerated storage

Probiotic is a preparation of viable microorganisms that are added to the diet of humans to control the growth of undesirable or less desirable microorganisms in the gastrointestinal tract that rich in the flora of more than 500 different bacterial species some of which have important health functions (Shori, 2016; Zendeboodi et al., 2020). A probiotic strain must maintain viability and functionality during manufacturing food products and subsequent storage without loss of the sensory properties of these foods (Shori et al., 2016; Muniandy et al., 2017; Champagne et al., 2018).
Multitrack Compressed Sensing for Faster Hyperspectral Imaging

Hyperspectral imaging (HSI) provides additional information compared to regular color imaging, making it valuable in areas such as biomedicine, materials inspection and food safety. However, HSI is challenging because of the large amount of data and long measurement times involved. Compressed sensing (CS) approaches to HSI address this, albeit subject to tradeoffs between image reconstruction accuracy, time and generalizability to different types of scenes. Here, we develop improved CS approaches for HSI, based on parallelized multitrack acquisition of multiple spectra per shot. The multitrack architecture can be paired up with either of the two compatible CS algorithms developed here: (1) a sparse recovery algorithm based on block compressed sensing and (2) an adaptive CS algorithm based on sampling in the wavelet domain. As a result, the measurement speed can be drastically increased while maintaining reconstruction speed and accuracy. The methods were validated computationally both in noiseless as well as noisy simulated measurements. Multitrack adaptive CS has a ∼10 times shorter measurement plus reconstruction time as compared to full sampling HSI without compromising reconstruction accuracy across the sample images tested. Multitrack non-adaptive CS (sparse recovery) is most robust against Poisson noise at the expense of longer reconstruction times.
Hyperspectral Remote Sensing Image Classification Based On Deep Learning

In recent years, with the development of science and technology, in order to further explore the world, we have explored and studied remote sensing technology. As a new discipline, teleology has been widely studied and applied in the fields of spectroscopy, informatics, geography, environmental science and urban construction, and has become one of the most active fields of science and technology. However, both classifier and feature extraction are in the shallow level. How to extract deep features and make them more abstract and easy to classify is a hot issue in machine learning field. Therefore, through the study of different classifiers and various special cases, we find that the post-processing method proposed in this paper can alleviate this situation to a certain extent. When the number of hidden layers is 2, the overall classification accuracy of DBN model is higher. Experiments show that this method is better than the traditional deep learning method.
Different Perspectives on BDA Usage by Management Levels

ABSTRACT Adopting theoretical foundations of the Technology-Organization-Environment (TOE) framework and technology task fit theory, this study investigates how business managers in different management levels determine BDA use. The major findings suggest that low-level and middle-level managers decide the use of the BDA system from different perspectives. Low-level managers consider individual performance more important in their decision while the middle-level managers believe in organizational readiness and relational knowledge. Also, the relationship between data integrity and data compatibility is greater for the lower-level, while that between data timeliness and data compatibility is more substantial for the middle-level. Concerning the effect of data quality on individual performance, the middle-level perceive data compatibility and data accuracy as more important than the lower-level managers.
FPGA Design for On‐Board Measurement of Intermittency From In‐Situ Satellite Data

Intermittency is a fundamental property of space plasma dynamics, characterizing turbulent dynamical variables as well as passive scalars. Its qualitative and quantitative description from in‐situ data requires an accurate estimation of the probability density functions (PDFs) of fluctuations and their moments, particularly the flatness, a normalized fourth order moment of the PDF. Such a statistical description needs a sufficiently large number of samples for the computation to be meaningful. Due to inherent technological limitations (e.g., limited telemetry bandwidth) not all samples collected on‐board can be sent to the ground for further analysis. Therefore, a technology designed to process on‐board the data and to compute the flatness is useful to fully exploit the capabilities of scientific instruments installed on robotic platforms, including nanosatellites. We designed, built, and tested in laboratory such a technology based on Field Programable Gate Arrays (FPGA). The building principle is the classical estimation of PDFs and their moments, based on normalized histograms of a measure. The technical design uses the FloPoCo (Floating‐Point Cores) framework with customized arithmetic operators; the computation block is a pipelined architecture, which computes a new value of the flatness in each clock cycle. The design and implementation achieve optimization directives of the FPGA resources relevant for operation in space, like area, energy efficiency, and precision. The technology was tested in laboratory using Xilinx SRL16 or SRLC32 macros and provides correct results validated with test time series provided by magnetic field data collected in the solar wind by ULYSSES spacecraft. The characteristics and performance of the laboratory prototype pave the way for a space qualified version of the laboratory design.
Acoustic scattering in nonhomogeneous media and the problem of discontinuous gradients: Analysis and inf‐sup stability in the method of finite spheres

In this paper we focus on a meshfree formulation for the solution of time‐harmonic acoustic scattering problems and verify the stability of the procedure. The sound waves propagate in nonhomogeneous media, giving rise to discontinuities in the gradients of the pressure field across the interfaces between regions of different material properties. Meshfree methods usually do not reproduce accurately the discontinuities in a numerical solution. We overcome this issue by introducing Lagrange multiplier fields defined at the interfaces in order to treat the discontinuities in the gradients of the pressure field. The method does not depend on any kind of adjustable parameter. We show by a numerical study of the applicable inf‐sup conditions that the resulting mixed formulation leads to well‐posed problems. The use of the proposed method is illustrated in the solution of a number of problems of wave propagation through nonhomogeneous media.
About the possibility of using speech recognition technologies in problems of assessing the protection of acoustic information from the leakage throught technical channels

This article discusses the possibility of improving the existing instrumental calculation method for assessing the security of meeting rooms by moving from the Pokrovsky formant method to using speech recognition algorithms based on deep neural networks. In our case, it is proposed to use recurrent neural networks that have shown themselves best in terms of information processing with low SNR ratios. Also, using the long-term short-term memory of a recurrent neural network, it is proposed to improve the test signal. In addition, it substantiates the need to take into account the individual characteristics of the room and the possibility of using interference, such as a “speech choir”.
Long range daily ocean forecasts in the Indo-Pacific oceans with ACCESS-S1

Abstract Currently most ocean forecast systems provide daily eddy resolving predictions 7 days or so in advance. We first investigate the potential for longer range daily ocean forecast up to 28 days using the coupled system ACCESS-S1 in which the ocean component is eddy permitting. The daily ocean forecasts over the hindcast period 1990–2012 in the Indo-Pacific oceans have been evaluated, using persistence skill as a reference. Our results show that the sea surface temperature (SST) biases are in the range of ±0.3 °C in most regions within the first 28 days of the forecast. The model’s predicted correlation skill of SST anomaly (SSTA) is higher than persistence skill in most areas beyond the first few days up until the 28-day lead time. The skill of SSTA indices averaged in different domains suggest that the model produces more skilful predictions in the North Indian Ocean, South Indian Ocean, western tropical Pacific and Leeuwin Current regions than the corresponding persistence forecasts. The model’s SSTA prediction skill in the eastern tropical Pacific is comparable to the persistence skill which is very high. The model’s correlation skill for sea surface height anomaly (SSHA) can beat persistence skill beyond the first week and the model’s skill has a great advantage with a longer lead time. The daily prediction of the larger mesoscale eddies that shed off the East Australia Current is also investigated here. The spatial correlation between the model predicted and observed SSHA is applied to measure the model prediction skill for these eddies. Our results suggest that the averaged correlation for all forecasting cases at the same lead time is above 0.5 up to 14-day lead. It indicates that ACCESS-S1 has some skill in predicting these eddies, since the strength and track of the eddies in the Tasman Sea are highly complicated.