Miracle-dz/UniFAR-FTUs huggingface dataset:
A Cluster based Sensor-Selection Scheme for Energy-Efficient Agriculture Sensor Networks

Improving the energy-efficiency of remotely deployed sensor nodes in agriculture wireless networks is very challenging due to a lack of access to energy grid. Network clustering and limiting the amount of sensor data are among the various methods to improve the lifetime of these sensor nodes. In this work, an optimal sensor-selection scheme is proposed to improve the Quality of Service in clustered agriculture networks. the proposed method selects a limited number of sensor nodes to be active in each cluster. It considers the estimator performance while selecting limited sensor nodes for environmental monitoring. the optimal sensor-selection process considers the information of remaining energy of sensor nodes in agriculture wireless networks. the proposed method selects a limited number of nodes in each cluster while maximizing the estimator performance at the receiver. Our cluster based sensor-selection scheme optimizes the energy-efficiency in a distributed manner. Network clustering also ensures a uniform sensor-selection over a network area. Extensive experiments are conducted to analyse the performance of the proposed optimal sensor-selection method over different network scenarios. Our experimental results indicate significant improvements in energy-efficiency of agriculture wireless sensor networks and motivate the proposed method in practice.
Stratification of patients with Alzheimer’s disease based on longitudinal neuropsychological tests

Alzheimer's disease represents a heterogeneous neurodegenerative disorder that affects millions of people worldwide. The heterogeneity of the disorder slows research on the physiological underpinnings of the disorder and impedes development of treatments. We modeled for 329 patients of the ADNI database the progression of their detailed cognitive abilities over a 2-year period and found three distinct sub groups. The groups could not be differentiated by demographic characteristics but only by their cognitive profiles. The two extreme groups show either only a mild impairment or a fast progression consistently across all cognitive sub domains. The third group, however, shows severe impairment in the memory domain but relatively spared loss of other cognitive function. The loss of hippocampal volume in this group underpins the severity of memory loss. Our study shows that models of longitudinal data with detailed features will help increase our understanding of the pathophysiology underlying Alzheimer's disease.
Abstract Template

The coupling efficiency between free space waves and surface waves is low, narrowband, or both. Highly efficient broadband (better than 20% fractional bandwidth) coupling from waveguide modes can be achieved through sophisticated transitions whose fabrication can be enabled through additive manufacturing (e.g. selective laser melting). Here, we present alternative metallic transitions designed to couple the fundamental mode of a D-band waveguide to the fundamental transversemagnetic surface mode supported by a periodic metal corrugated grating. Simulations of the coupling process and initial measurements have been undertaken.
Underlying Cause of Death Identification from Death Certificates via Categorical Embeddings and Convolutional Neural Networks

Information about causes of death are collected by filling death certificates according to a standard defined by WHO. Conditions are expressed by means of the International Statistical Classification of Diseases and Related Health Problems, revision 10. Starting from such information, the so-called Underlying Cause of Death is selected with statistical and epidemiological aims. This task is usually carried out with the support of a system that implements the rules defined by WHO. However. such systems leave the selection of a fraction of certificates up to 31.5% of the total to the interpretation of the human expert, causing a significant burden for the Institutes in charge of coding. Machine learning has been used to both code free text certificates to ICD-10, and recently also to identify the underlying cause of death. The present paper describes a method for selecting the underlying cause of death from death certificates, based on the use of categorical embeddings and convolutional neural network. The proposed method achieves 98.44% accuracy, which is currently state-of-the-art performance.
Research on Temperature and Braking Performance of Water-Cooled Eddy Current Retarder

Trucks have the problems of frequent braking and long-term braking during long-slope transportation. As the temperature of the traditional eddy current retarder is as high as 500 °C during braking, the braking torque of the retarder is seriously degraded. According to the principle of eddy current braking and current thermal effect, this paper proposes an eddy current retarder in which both the stator and the excitation coil are water-cooled. The multi-field coupling and bidirectional data transmission model of stator temperature field, coil temperature field and transient electromagnetic field are established. The relationship between the braking torque and the working time is analyzed under continuous braking conditions, considering the stator temperature and the temperature of the excitation coil. It provides theoretical support for the optimal design of the retarder. A test prototype of a water-cooled eddy current retarder was manufactured, and a bench drag test was carried out. The calculation results show that the numerical simulation method of coupling between the stator temperature field, the coil temperature field and the transient electromagnetic field is adopted, and the simulation values of the braking torque is in good agreement with the experimental values.
Experiments on Generation of Vortex Surface Plasmon Polaritons on Plane and Cylindrical Conductors in Mid-Infrared and THz Ranges

In this article, we propose methods for the generation of surface plasmon polaritons (SPPs), both carrying orbital angular momentum, and conventional ones, using vortex Bessel beams, and also investigate the propagation of SPPs along flat and cylindrical conductors. The possibility of their practical application is discussed and the first experimental results are presented.
Design of Multi-layer Ultra-thin Frequency Selective Surface with Dual Bandpass Response

A multilayered dual-band frequency selective surface (FSS) with high selectivity is proposed in this paper. The unit cell of the presented FSS is a five-layered structure surrounded by a thin metal waveguide and has a very small thickness. The electromagnetic coupling is improved by the multilayer structure and the waveguide structure, which improves the selectivity of the FSS. Simulation results show that the proposed dual-bandpass FSS exhibits sharp roll-off characteristics and high out-of-band suppression, which are due to the introduction of three transmission zeros. The designed FSS can achieve the stable frequency response to the variations of the incident angle from 0° to 60°.
A Survey on Dental Imaging for Building Classifier to Benefit the Dental Implant Practitioners

Endo-osseous implants are considered an ideal dental fixture. It is becoming the preferred choice of the edentulous patient to rehabilitate toothlessness because of their aesthetic and functional outcome. Despite the successful surgery and implant placement, complications occur, which may be related to several factors, like operative assessment, treatment planning, patient-related factors, surgical procedures, and surgeons' experience. Comprehensive radiological assessment plays a vital role in clinical analysis for better treatment planning, avoiding complications, and increasing the Implant's success rate. However, despite the variety of dental imaging, choosing the right imaging technology has become difficult for clinical experts. The investigative survey conducted in this paper aims to determine the correlation between different imaging modalities, their essential role in implant therapy. This review extensively discussed which types of computational operations applied to image modalities in the existing literature address various noises and other relevant issues. These study findings reveal significant issues with various dental imaging modalities and provide an understanding to bridge all existing research gaps towards building cost-effective classification and predictive models for accurate dental treatment planning and higher implant success rates. Keywords—Dental implant; complication; implant failure; dental imaging; pre-processing
Novel antimicrobial activities of self-nanoemulsifying drug delivery system (SNEDDS) ethyl acetate fraction from Garcinia mangostana L. peels against Staphylococcus epidermidis: Design, optimization, and in vitro studies

The purposes of this study were to determine the comparison of Tween 80, PEG 400, and Virgin Coconut Oil to produce the optimal self-nanoemulsifying drug delivery system (SNEDDS) of the ethyl acetate fraction mangosteen peels and to analyze the effectiveness of the optimal SNEDDS against Staphylococcus epidermidis. The optimal SNEDDS was obtained with the Design-Expert software and simplex lattice design method with various combinations, namely Tween 80, PEG 400, and Virgin Coconut Oil. The research method begins with the extraction process using the maceration method using ethanol solvent, and then, the ethanol extract was fractionated with ethyl acetate solvent. The optimal SNEDDS was evaluated for transmittance value, pH, emulsification time, particle size, zeta potential, and their in vitro activity against S. epidermidis. The optimal SNEDDS obtained was a combination of Tween 80:PEG 400:Virgin Coconut Oil with a composition ratio of 4.98:1.02:1. Based on the evaluation, the transmittance value was 72.74% ± 1.08%, the pH was 6.48 ± 0.03, emulsification time was 4.83 sec ± 0.95 sec, the average droplet size was 77.3 nm ± 0.232 nm, and the zeta potential value was −8.29 ± 0.04 mV. The optimal SNEDDS of ethyl acetate fraction of mangosteen peels had a higher activity against S. epidermidis than the fraction without SNEDDS.
The Biometric Vox System for the Albayzin-RTVE 2020 Speaker Diarization and Identity Assignment Challenge

This paper describes the systems developed by Biometric Vox for the Albayzin Speaker Diarization Challenge organized as part of the Iberspeech 2020 conference. The two systems (primary and contrastive) we developed for the challenge are based on Deep Neural Network x–vector embeddings and a Proba-bilistic Linear Discriminant Analysis (PLDA) backend. The resulting x-vectors are grouped using Agglomerative Hierarchical Clustering (AHC) in order to obtain the diarization labels. Systems differ in the resegmentation stage. Our primary system achieves 14.96% DER on the test set of the RTVE2018 database and 21.35% on the 2020 evaluation set.
Optimal classification and regression trees with hyperplanes are as powerful as classification and regression neural networks

We investigate the modeling power of neural networks in comparison with optimal classification and regression trees with hyperplanes (OCT-Hs and ORT-Hs). We prove that a variety of neural networks (feedforward, convolutional and recurrent) can be transformed to decision trees with hyperplanes with the same accuracy in the training set, showing that OCT-Hs and ORT-Hs are at least as powerful as neural networks. Conversely, we show that a given classification OCT-H can be transformed to a classification neural network with the perceptron activation function with the same accuracy in the training set, showing that a neural network is at least as powerful as OCT-Hs, that is, OCT-Hs and neural networks are equivalent in terms of modeling power. Given that our construction of optimal trees that emulate a given neural network necessitates the construction of deep trees, we explored the practical implication of these findings. We report a comparison of optimal classification trees and neural networks on seven well known data sets and show that the two methods exhibit remarkably close accuracy.
coli and Food Safety : It ' s a Jungle Out There

Foodborne illnesses are a substantial yet largely preventable health burden worldwide. We previously reviewed food safety in the United States[1] and harked back to the classic book, The Jungle, which portrayed the unsanitary conditions and practices prevalent in industrialized American cities in the early 1900s. [2] While this had a significant impact on reformation of the meatpacking industry, how far have we come since the conditions reported by Upton Sinclair? One indicator of progress is whether we have adequately responded to the lessons learned. In this context, we will focus specifically on foodborne Escherichia coli infections.
Partial CO1 sequence of the cotton bollworm, Helicoverpa armigera

This paper reports the comparison of the partial CO1 sequence of Indian, field collected Helicoverpa armigera and a laboratory reared, insecticide susceptible, homogeneous strain of H. armigera. Using primers C1-J-2090 and C1-N2659 the near mid region of the CO1 sequence was obtained. In the resulting amino acid sequence substitutions at 16 positions were noticed in the insecticide susceptible strain compared to
ANNALS OF “DUNAREA DE JOS” UNIVERSITY OF GALATI – FASCICLE

At present, the value of channel roughness represents the most important parameter of hydraulic model calibration for flood mapping and flood forecasting. In practice, the roughness coefficient (Manning’s “n” value) cannot be determined from in situ surveying, but it can be automatically extracted from alternative sources, like pedological maps, ortophotomaps by digitizing each polygon associated with “n” value or using satellite images LANDSAT. For calibration of Manning’s “n” values, it was used the data from 2005, when a major flood occurred in this study area. To verify the performance of the calibrated HEC-RAS model, it was analyzed the flood peaks of observed and simulated values, and computation of root mean square error for the used hydrograph station on the lower Siret River. The study aims to present an efficient calibration method for flood mapping using HEC-RAS model.
Generation of Synthetic Sign Language Sentences

Sign language is one of the most usual ways of communication for deaf people. Their inclusion in the society would be greatly improved if sign language can be easily used to communicate with other people that do not understand properly that language. Automatic recognition systems, based on machine learning techniques, could be very useful for this task, providing signers with tools that could be used to transcribe sign language into written language automatically. Many previous works have centered mainly in the recognition of single words, and different datasets of single words signs are available for estimating recognition models for this task. However, the recognition of whole sentences is difﬁcult, since the acquisition of datasets of sentences is in general harder than the acquisition of single words. Thus, the possibility of generating sentences in sign language from single word datasets is very attractive to obtain automatic systems for decoding sign language sentences. In this work, we present an approximation for generating sign sentences from sign single words acquired by using the Leap-Motion sensor. We study the different difﬁculties that presents this generation process. Results for real sign language sentences show that training with these synthetic sentences improves the decoding performance with respect to using only single words for training.
Solid Oxide Fuel Cell with Anodes using Proton Conductor (Barium-Cerium/Yttrium Oxide)

A new anode with a proton conductor (Barium-Cerium/Yttrium oxide (BCY): BaCe0.8Y0. 2O3-δ) was proposed for a high-power, solid-oxide fuel cell. In the new anode, the proton-conducting material was included in a conventional anode made of nickel (Ni) and Gd-doped Ceria (GDC) in the ratio of GDC:BCY=0:100, 50:50, 90:10, 100:0 vol.%. With 3% humidity hydrogen fuel, the overpotential of the BCY anode became smaller compared with that of the conventional Ni/GDC anode. The most striking feature is that the anode with the 10%-BCY has the lowest overpotential among all anodes due to the high oxide-ion conductivity by the 90%-GDC and the reaction enhancement and/or the high hydrogen-adsorption ratio by the 10%-BCY.
Gelation and drying of weakly bonded silica-PPO nanocomposites

Silica-poly(oxypropylene) (PPO) nanocomposites containing PPO with weak physical bonds between the organic (PPO) and inorganic (silica) phases were obtained by the sol-gel procedure. Three precursor sols containing silica and PPO with molecular weights of 1000, 2000 and 4000g/mol were prepared. The structure changes during the whole sol-gel process, i. e. sol formation, sol-gel transition and gel aging and drying were investigated in situ by small angle X-ray scattering (SAXS). The experimental SAXS curves corresponding to sols and wet gels containing PPO of molecular weight 1000g/mol indicate that the aggregates formed during the studied process are fractal objects. Close to the sol-gel transition and during gel aging the fractal dimension is D=2.5. A clearly different structure evolution occurs in samples prepared with PPO with molecular weights 2000 and 4000 g/mol. Our SAXS results indicate the presence of two coexisting and well-defined structure levels, one of them corresponding to small silica clusters and the other to large silica aggregates. These two levels remain along the whole transformation. The SAXS curves of all dry samples are similar to those of the corresponding wet gels suggesting that no significant changes at nanoscopic scale occur during the drying process.
Effect of Moisture Conservation Practices on the Performance of Direct Seeded Rice–greengram Cropping Sequence in Rainfed Ecosystem of Assam

Rice is the staple food of more than half of the world population and India is the second largest producer (131 million tonnes) of rice next to China (197 million tonnes). The rice productivity in India is 3.37 t ha -1 against the world average of 4.25 t ha -1 . (Sangeetha et. al., 2015) The traditional method of rice establishment is the transplanting which requires high labour cost in seedbed preparation, sowing in nursery, uprooting, transplanting in the main field etc. Moreover repeated puddling adversely affects the soil physical properties by dismantling soil aggregates, reduces permeability in sub surface layers and form hard pans at shallow depths. (Sharma et al., 2008). The direct seeding avoids some basic operations like nursery raising, uprooting of seedlings, puddling, transplanting, maintaining standing water and thereby reduces labour requirement (Pepsico International, 2011). Among the pulse crop grown in Assam, greengram is a popular crop among the farmers and it is grown mostly in kharif season (Mid AugustInternational Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas. com
Incorporation of pertechnetate and perrhenate into corroded steel surfaces studied by X-ray absorption fine structure spectroscopy

Abstract Batch reaction experiments and solid-phase characterization analyses were completed to examine the uptake of dissolved perrhenate [Re(VII)] or pertechnetate [Tc(VII)] by A-516 steel coupons that corroded in simulated groundwater solutions or dilute water. The goal was to identify the mechanism(s) that control the uptake of 99Tc by corrosion products on carbon steel in the presence of dilute solutions. X-ray absorption fine structure spectroscopy (XAFS) was used to study the oxidation states of Re and Tc incorporated into the corroded steel coupon surfaces. X-ray fluorescence maps showed that the corroded coupons contain localized regions enriched in Re or Tc. The Re L3 near edge XAFS results for the coupons reacted with Re-spiked waters were consistent with nearly all of the sorbed Re being present as perrhenate and not significantly reduced to Re(IV). Linear combination fits of the extended XAFS signals for the perrhenate and ReIVO2 standards indicate that Re sorbed to the steel coupons corroded in simulated J-13 (a relatively dilute Na-HCO3-CO3 groundwater) and even more dilute waters consists of a maximum of 5 and 10% Re(IV), respectively. The fluorescence results also showed that the Re concentrations increased with increasing time of exposure to the X-ray beam, which suggests that the perrhenate ions are only weakly bonded to the matrix of the corrosion product. In contrast to the Re results, the Tc K edge XAFS results for the coupons reacted in 99Tc-spiked waters indicate that most of the sorbed Tc had been reduced to Tc(IV). The shape of the near edge and extended fine structure is similar to the Tc(IV)-hydrous ferric oxide (HFO) and not the TcO2·nH2O standard. Differences were noted in the XAFS results for steel coupons reacted with waters spiked with 0.001 vs. 0.1 mmol/L 99Tc in that much more of the sorbed Tc from 0.001 mmol/L 99Tc experiments was in the form of pertechnetate. Comparison of the XAFS results for coupons reacted with 0.001 mmol/L 99Tc-spiked dilute simulated Na-HCO3-CO3 groundwater vs. 0.001 mmol/L 99Tc-spiked dilute water also suggest that there are likely differences in the sorption mechanism for the pertechnetate fraction in the corrosion product which formed in these two test solutions. The cause for these differences is not known, but is likely due to differences in the compositions of the dilute simulated Na-HCO3-CO3 groundwater and more dilute waters, such as the dissolved carbonate concentrations.
Constituents of the essential oil of Pulicaria gnaphalodes (Vent.) Boiss. from Iran

The essential oil of Pulicaria gnaphalodes (Vent.) Boiss. from Iran was investigated by GC, GC–MS and NMR spectroscopy. Typical for this oil are pinane [chrysanthenone (23), cis-chrysanthenol (34)], cadinane [cadina-1(10),4-dien-8α-ol (114)] and bisabolane derivatives [nuciferol (118), γ-curcumen-12-ol (119)]. New, naturally occurring compounds are (Z)-3-methylnon-3-en-2-one (43), the so-called helifolen-12-als 94, 95, 98, 99, tricyclic sesquiterpene aldehydes with a helifolane (syn. allo-cedrane or khusiane) skeleton, and the italicen-12-ols 108 and 110. These aldehydes and alcohols are presumably formed by [4+2] resp. [2+2] cycloaddition of the corresponding γ-curcumene derivatives. Copyright © 1999 John Wiley & Sons, Ltd.
Benzimidazole grafted polybenzimidazoles for proton exchange membrane fuel cells

High molecular weight polybenzimidazole (PBI) was synthesized and grafted with benzimidazole pendant groups. The high molecular weight of PBI resulted in good film-forming properties and superior tensile strength. With a phosphoric acid doping level (ADL) of 13.1, a tensile strength of 16 MPa was achieved at room temperature. Grafting of benzimidazole moieties onto the PBI macromolecular chain introduced additional basic sites which allowed the membrane to achieve higher phosphoric acid uptakes. A molar acid conductivity, defined as the specific conductivity of each mole of doping acid, was proposed to evaluate the effective conductivity contributed from the doping acids. With a grafting degree of 5.3% and an ADL of 13.1, the PBI membranes exhibited a total conductivity of 0.15 S cm−1. A H2–air fuel cell based on this membrane showed a peak power density of 378 mW cm−2 at 180 °C without humidification.