Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical and dielectric characteristics of polyethylene oxide/sodium alginate-modified gold nanocomposites

Films of polyethylene oxide and sodium alginate polymer blend (50/50 wt%) embedded with different quantities of Au nanoparticles with size 3–32 nm were made using the casting process. The nanocomposite films were examined by XRD analysis, FT-IR spectroscopy, TEM, UV/vis spectroscopy, and AC conductivity and dielectric parameter measurements. The XRD spectra revealed the amorphous nature of the prepared films (PEO/SA–Au NPs). From the Fourier transform infrared spectra it can be seem that the intensity of the FT-IR bands decreased which depicted the existence of the interaction between (PEO/SA) virgin polymer and gold nanoparticles. The TEM micrographs showed a cubic-structure for Au NPs with an average size of 15–20 nm. The optical properties of the polymer composite were examined by ultraviolet-visible techniques. In a direct transition the optical energy gap (Eg) of the prepared films is decreased from 4.73 to 2.92 eV and in an indirect transition decreased from 2.95 to 1.50 eV. The dielectric and electrical spectra of the obtained films were examined via dielectric broad-band spectroscopy. The electrical and dielectric measurements are appropriate for the use of the polymer nanocomposite films in the fabrication of electroactive materials.
Lexical Cohesion Analysis On Scopus Indexed-Journal Entitled “A New Control Method For Power Based On Dynamic Evolution Control “

Cohesion is a semantic concept and part of the system of a language. The language can be orally or written. One of the indicators of good discourse (written) is having good cohesion and coherence aspect. This study is entitled Lexical Cohesion Analysis on Scopus-Indexed-Journal entitled “A New Control Method for Power based on Dynamic Evolution Control“. The aim of this study is to identify and describe the lexical cohesion in the Scopus-indexed article journal. This study is a qualitative research. The data sources in this study an article Scopus indexed-journal was obtained by purposive sampling. Furthermore, analysis of the data was done by identifying and classifying the data that related to cohesion, based on the theory of Halliday and Hasan (1976) and also analyzing used Spradley (1980). Based on the analysis, it was found five things related to cohesion and coherence. First, lexical cohesion devices which are used consist of repetition, synonymy, antonymy, hyponymy, and meronymy. The most frequent lexical cohesion used is repetition. Therefore, it can be of an interest to the (future) writer or researcher who are involved in writing journal. The study concludes that lexical cohesion determines writers’ tones in writing article and this ultimately contributes significantly enough in constructing persuasion and strong desire to persuade editorial boards of the journal to accept the article. It has also been highlighted that the findings of this study could be broaden in grammatical cohesion, and also be beneficial to researchers and ESL/EFL learners especially in persuasive and academic writing. Those aspects and factors can be considered to certain paper or journal article whether rejected or accepted in Scopus-indexed journal.
Dark Future for Dark Matter

The prevailing cosmological constant and cold dark matter (ΛCDM) cosmic concordance model accounts for the radial expansion of the universe after the Big Bang. The model appears to be authoritative because it is based on the Einstein gravitational field equation. However, a thorough scrutiny of the underlying theory calls into question the suitability of the field equation, which states that the Einstein tensor Gμv is a constant multiple of the stress-energy tensor Tμv when they both are evaluated at the same 4D space-time point: Gμv = 8πkTμv, where k is the gravitational constant. Notwithstanding its venerable provenance, this equation is incorrect unless the cosmic pressure is p = 0; but then all that remains of the Einstein equation is the Poisson equation which models the Newtonian gravity field. This shortcoming is not resolved by adding the cosmological constant term to the field equation, Gμv +Λ gμv =8πkTμv, as in the ΛCDM model, because then p = Λ, so the pressure is a universal constant, not a variable. Numerous studies support the concept of a linearly expanding universe in which gravitational forces and accelerations are negligible because the baryonic mass density of the universe is far below its critical density. We show that such a coasting universe model agrees with SNe Ia luminosity vs. redshift distances just as well or even better than the ΛCDM model, and that it does so without having to invoke dark matter or dark energy. Occam’s razor favors a coasting universe over the ΛCDM model.
Audio-Based Aircraft Detection System for Safe RPAS BVLOS Operations

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective ‘Detect and Avoid’ systems that enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based ‘Detect and Avoid’ system, composed of microphones and an embedded computer, which performs real-time inferences using a sound event detection (SED) deep learning model. Two state-of-the-art SED models, YAMNet and VGGish, are fine-tuned using our dataset of aircraft sounds and their performances are compared for a wide range of configurations. YAMNet, whose MobileNet architecture is designed for embedded applications, outperformed VGGish both in terms of aircraft detection and computational performance. YAMNet’s optimal configuration, with >70% true positive rate and precision, results from combining data augmentation and undersampling with the highest available inference frequency (i.e., 10 Hz). While our proposed ‘Detect and Avoid’ system already allows the detection of small aircraft from sound in real time, additional testing using multiple aircraft types is required. Finally, a larger training dataset, sensor fusion, or remote computations on cloud-based services could further improve system performance.
Impact of natural zeolite on chemical and biochemical properties of vineyard soils

Sustained tillage and continual applications of phytopharmaceutical and fertilizers using heavy machineries frequently give rise to soil erosion, loss of soil organic matter (SOM) and contamination phenomena in Mediterranean vineyards. Because of their distinctive properties, applying natural zeolites to vineyard soils can conceivably affect the efficient use of fertilizers and reduce nutrient leaching losses. This work assesses the impact of zeolite amendment at differing rates (0, 5 and 10 t/ha) on the chemical and biochemical soil properties of three vineyard soils after 6 months from initial treatments. In particular, chemical properties usually related to soil fertility were evaluated along with more sensitive indicators of soil functionality and indicators of chemical–structural characteristics of SOM. The vineyard soils amended with zeolite showed higher nutrient availability and dehydrogenase activity if compared with the control soils. In addition, even though total organic carbon (TOC) content was unchanged, a decrease in humic substances was observed in the zeolite‐treated soils. These results suggested that the stimulation of soil microbial processes by adding zeolite triggered a microbial mineralization process of soil organic carbon stocks. In addition, the modification in the chemical–structural composition of soil organic matter in zeolite‐treated soils was shown by the pyrolysis–gas chromatography (Py‐GC) results. Py‐CG of soil organic matter clearly demonstrated an increase in the labile aliphatic compound furfural and a decline in the more stable aromatic pyrolytic fragments in zeolite‐treated soils in contrast with the control soils, thus indicating the higher extent of decomposition of the SOM more stable pool.
Reference to characters in narratives of Russian-Hebrew bilingual and Russian and Hebrew monolingual children with Developmental Language Disorder and typical language development

This research analyzed adequacy of referential expressions in the narratives of bilingual and monolingual children with Developmental Language Disorder (DLD) and typical language development (TLD), aiming to shed light on the relative contribution of morpho-syntactic, discourse-pragmatic, and semantic constraints. Narratives were collected from 51 children using a storytelling procedure (MAIN – Multilingual Assessment Instrument for Narratives). Participants were 18 bilingual Russian-Hebrew preschool children (8 with DLD), 17 monolingual Russian speakers (9 with DLD), and 16 monolingual Hebrew speakers (5 with DLD) aged 5;6–6;7. Referential expressions were coded for form (noun phrase [NP] or pronoun) and character function (Introduction or Maintenance). Analyses addressed the effects of proficiency group (TLD/DLD), language group (bilingual/monolingual), and language (Russian/Hebrew) on inadequate pronoun use and definiteness. Results demonstrated that children in all groups introduced characters using NPs. Children with DLD used more morpho-syntactically inadequate pronouns, such as incorrect gender, while both children with DLD and those with TLD used similar numbers of discourse-pragmatically inadequate pronouns. Bilinguals used more morpho-syntactically inadequate pronouns than monolinguals. In Hebrew, bilingual children with DLD omitted definite articles for character Maintenance more frequently than bilingual children with TLD and monolingual Hebrew-speaking children with DLD. Wrong gender assignment indicates that children with DLD have difficulties with morpho-syntactic constraints. Omission of definite articles for character Maintenance indicates a possibility of both morpho-syntactic and semantic difficulties that bilingual children with DLD acquiring Hebrew face. The results offer insight into the nature of the difficulty observed in bilingual children with DLD in using referential expressions.
Short-Termism, Shareholder Payouts, and Investment in the EU

Investor-driven "short-termism'" is said to harm EU public firms' ability to invest for the long term, prompting calls for the EU to better insulate managers from shareholder pressure. But the evidence offered---in the form of rising levels of repurchases and dividends---is incomplete and misleading, as it ignores large offsetting equity issuances that move capital from investors to EU firms. We show that net shareholder payouts have been moderate, that both investment levels and investment intensity have been rising, and that cash balances have increased. In sum, the data provide little basis for the view that short-termism in the EU warrants corporate governance reforms.
Chemical Composition and Antibacterial Activity of Kaempferia galanga Essential Oil

Kaempferia galanga L. is a traditional herbal medicine with high essential oil content. Gas chromatography-mass spectrometry (GC-MS) detected 25 different compounds in K. galanga essential oil, representing 95.98% of the total oil. The antibacterial activity of the essential oil was measured by the microtiter broth dilution method, and minimum inhibitory concentrations (MICs) against the three pathogenic bacterial strains Escherichia coli, Salmonella typhimurium and Staphylococcus aureus were 5, 1, and 2 mg/mL, respectively. The antibacterial mechanisms of K. galanga essential oil were further explored, and massive nucleotide and protein leakage demonstrated that it caused membrane disruption in the pathogens. SDS-PAGE confirmed the disruptive action of the essential oil on the cytoplasmic membrane. Moreover, the essential oil-induced cell wall and membrane damage was observed by scanning electron microscopy. These findings indicated K. galanga essential oil might constitute a candidate for developing new food preservatives and pharmaceuticals. © 2018 Friends Science Publishers
Sensitivity and Directivity Analysis of Piezoelectric Ultrasonic Cantilever-Based MEMS Hydrophone for Underwater Applications

In this paper, we report on the characterization of the sensitivity and the directionality of a novel ultrasonic hydrophone fabricated by micro-electro-mechanical systems (MEMS) process, using aluminum nitride (AlN) thin film as piezoelectric functional layer and exploiting a stress-driven design. Hydrophone structure and fabrication consist of four piezoelectric cantilevers in cross configuration, whose first resonant frequency mode in water is designed between 20 kHz and 200 kHz. The MEMS fabricated structures exploit 1 µm and 2 µm thick piezoelectric AlN thin film embedded between two molybdenum electrodes grown by DC magnetron sputtering on silicon (Si) wafer. The 200 nm thick molybdenum electrodes thin layers add a stress-gradient through cantilever thickness, leading to an out-of-plane cantilever bending. A water resistant parylene conformal coating of 1 µm was deposited on each cantilever for waterproof operation. AlN upward bent cantilevers show maximum sensitivity up to −163 dB. The cross configuration of four stress-driven piezoelectric cantilevers, combined with an opportune algorithm for processing all data sensors, permits a finer directionality response of this hydrophone.
Methodology for Indoor Positioning and Landing of an Unmanned Aerial Vehicle in a Smart Manufacturing Plant for Light Part Delivery

Unmanned aerial vehicles (UAV) are spreading their usage in many areas, including last-mile distribution. In this research, a UAV is used for performing light parts delivery to workstation operators within a manufacturing plant, where GPS is no valid solution for indoor positioning. A generic localization solution is designed to provide navigation using RFID received signal strength measures and sonar values. A system on chip computer is onboarded with two missions: first, compute positioning and provide communication with backend software; second, provide an artificial vision system that cooperates with UAV’s navigation to perform landing procedures. An Industrial Internet of Things solution is defined for workstations to allow wireless mesh communication between the logistics vehicle and the backend software. Design is corroborated through experiments that validate planned solutions.
Environmental Risk Assessment of Pesticides: Improving Simulation Model Credibility

Registrant use of computer simulation modeling is generally accepted by regulators in lieu of some experimental data for risk assessment, provided worst-case assumptions and extremely conservative criteria for negligible risk are used. These requirements taken together mean that only extreme cases escape the requirement for actual environmental data. This conservatism reflects the uncertainty in both exposure estimates by the models and in the hazard estimates from toxicologists. Until the credibility of estimated environmental concentrations given by models is improved by more experimental data and experience on the part of both registrants and regulators, the models will continue to be considered not-validated by many. There are four current developments that provide a compromise between the two impossible extremes of total model validation and total field measurement: (1) as models develop more process detail the parameters become more fundamental in nature and these are generally more amenable to independent estimation or measurement; (2) the reporting of probabilistic analyses and probable errors of results by modelers will enhance credibility; (3) the development of data sets for specific crop/site/pesticide/weather scenarios will allow users to modify those parts of the input they are concerned with while retaining confidence that parameters with which they are unfamiliar will have reasonable values; and (4) meso-scale and micro-scale physical simulation experiments can fill the gap between laboratory and field results. The most important need for enhancing model credibility is full access by the pesticide science community to all the information available, so that we may increase our understanding. Legal mechanisms should be considered for longer ownership of exclusive marketing rights of active ingredients, in exchange for complete public disclosure of the environmental fate and toxicology data submitted to regulatory agencies.
Substrate – Inositol Transporter Interactions: Molecular Docking Study

Inositol is a cyclic polyol naturally occurring as seven optically inactive stereoisomers and one enantiomeric pair. Within the human body, brain is the most saturated organ of inositol, mainly with myoand scyllo-inositol. One of the molecular mechanisms for the maintenance of inositol brain levels is active transport via stereospecific carrier molecules – one hydrogen myo-inositol transporter (HMIT) and two sodium myo-inositol transporters (SMIT1 and SMIT2). In this study, we modeled by homology the myo-inositol transporter SMIT1 using the X-ray structure of Vibrio parahaemolyticus sodium/galactose symporter (vSGLT) as a template. A set of inositol derivatives – strong and weak competitors of inositol transport – was docked in the SMIT1 binding site. The docking protocol was optimized in terms of scoring function, radius of the binding site and flexible residues inside to distinguish between strong and weak competitors. The analysis of ligand – transporter interactions revealed that tiny structural differences exist between strong and weak competitors. Both groups have almost equal number of hydroxyl groups but the strong competitors are able to form more hydrogen bonds with the transporter (5.07 vs. 4.53 per molecule) and take part in less hydrophobic interactions (0.6 vs. 0.73) than the weak competitors.
Intelligent Recognition of Insulator Contamination Grade Based on the Deep Learning of Ultraviolet Discharge Image Information

In order to achieve the noncontact detection of the contamination grade of insulators and to provide guidance for preventing the contamination flashover of insulators based on the pollution state, we propose a contamination grade recognition method based on the deep learning of ultraviolet discharge images using a sparse autoencoder (SAE) and a deep belief network (DBN). Under different humidity conditions, we filmed and preprocessed the ultraviolet discharge images of insulators at different contamination grades and we obtained the ultraviolet spot area sequence as original data for contamination grade recognition. A double-layer sparse autoencoder was used to extract sparse features that could characterize different contamination grades from the ultraviolet spot area sequence. Using the extracted features, a DBN composed of three layers of restricted Boltzmann machine was trained to provide contamination grade recognition. To verify the effectiveness of the method proposed in this paper, high-voltage experiments were performed on contaminated insulators at relative humidity levels of 80%, 85%, and 90%, and ultraviolet images were recorded. The proposed SAE–DBN method was used to identify the ultraviolet images of the insulators with different contamination grades. The recognition accuracy rates at the three humidity levels were 91.25%, 93.125%, and 92.5%. The experimental results showed that this method could accurately recognize the contamination grade of the insulator and provide guidance for the prevention of contamination flashover based on the pollution severity.
CoGe LoadExp+: A web‐based suite that integrates next‐generation sequencing data analysis workflows and visualization

Summary To make genomic and epigenomic analyses more widely available to the biological research community, we have created LoadExp+, a suite of bioinformatics workflows integrated with the web‐based comparative genomics platform, CoGe. LoadExp+ allows users to perform transcriptomic (RNA‐seq), epigenomic (bisulfite‐seq), chromatin‐binding (ChIP‐seq), variant identification (SNPs), and population genetics analyses against any genome in CoGe, including genomes integrated by users themselves. Through LoadExp+'s integration with CoGe's existing features, all analyses are available for visualization and additional downstream processing, and are available for export to CyVerse's data management and analysis platforms. LoadExp+ provides easy‐to‐use functionality to manage genomics and epigenomics data throughout its entire lifecycle using a publicly available web‐based platform and facilitates greater accessibility of genomics analyses to researchers of all skill levels. LoadExp+ can be accessed at https://genomevolution.org.
In search of traces of ‘The Tourist Gaze’ on locals: an ethnographic study in Garmeh village, Iran

ABSTRACT This study aims to explore the meaning reconstruction of consequences of the tourism boom with a social interpretive approach. This approach presupposes that social actors play a key role in constructing and reconstructing their lives. This study seeks to answer the question of how the people of Garmeh village interpret the changes caused by the tourism boom? Data were collected over a period of four months using ethnographic methods and were analyzed using grounded theory. In this respect, the tourism boom consequences were classified into six themes consisting of economy, social interactions, beliefs, education, consumption patterns, and leisure time. Through the process of data analysis, the following six core categories were emerged from selective coding process; improving livelihoods, sustainable social relationships, belief foreshocks, deprivation, consumerism, and tourism as a leisure ground. Results suggest that locals consider the consequences of tourism constructive and subversive. They perceived the tourism consequences as bestowing the modern ways of life and growth of the village, while simultaneously threatening cultural beliefs and the traditional lifestyle. The results are presented in a model consisting of conditions, interactions, and consequences.
The Impact of Memrise Application on Iranian EFL Learnersâ€™ Collocation Learning and Retention

This study aimed at investigating the effect of Memrise application on Iranian EFL learners’ collocation learning and retention. To this end, a quasi-experimental design was used. 75 Iranian intermediate EFL learners studying English at a private language institute, namely Farahan, Iran were selected to participate in the study based on convenience sampling in the form of two intact classes. The scores obtained were entered into SPSS software for the purpose of data analysis. The results of data analysis showed that Memrise application had a statistically differential effect on collocation learning of Iranian EFL learners. Moreover, it was demonstrated that Memrise application had a statistically differential effect on collocation retention of Iranian EFL learners. In addition, it was proved that there was a significant difference between the immediate post-test scores Iranian EFL learners who received Memrise application and those who received traditional teaching. Finally, it was indicated that there was a statistically significant difference between the delayed post-test scores of Iranian EFL learners who received Memrise application and those who received traditional teaching. Key Words: Collocation Learning; Collocation Retention; Memrise application; Mobile Assisted Language Learning (MALL); Computer Assisted Language Learning (CALL).