bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management of soil fertility through application of fertilizers.
Authors: Kihara Job , Bekunda Mateete , Chimonyo Vimbayi , Kimaro Anthony , Kotu Bekele , Lyimo Stephen , Mhango Wezi 
Published: April 2022

Abstract

This chapter presents technologies for replacing the nutrients lost from cropped fields with external fertilizer sources in a manner that minimizes the consequences of too little or too much application. The technology of using industrial fertilizers, organic fertilizers, and application of farmyard manure and compost alone or in combination with industrial fertilizers are discussed in detail.
Soil and water conservation for climate-resilient agriculture.
Authors: Kizito Fred , Chikowo Regis , Kimaro Anthony , Swai Elirehema 
Published: April 2022

Abstract

This chapter describes soil and water conservation measures for climate-resilient agriculture. It presents three interventions that can be used separately or in combination, depending on the context of the region: (1) integrating strips of forage grasses and legumes; (2) rainwater harvesting through tied ridges and ripping techniques; (3) constructing banks and ditches as part of an agroforestry system. The description of each technology, its benefits and application are discussed.
Experimental study of radio frequency waves resonant transmission through a semiconductor plasma sheet with supercritical electron density
Authors: Bogatskaya A V , Klenov N V , Popov A M , Schegolev A E , Titovets P A , Tereshonok M V 
Published: April 2022

Abstract
We present an experimental study of the effect of resonant tunnelling of radio frequency signals through a silicon semiconductor plasma sheet with supercritical electron density. The resonance effect appears when a dielectric plate is placed behind the plasma sheet and is determined by the dielectric parameters. The numerical modelling of the effect under the experimental conditions was implemented and compared with the experimental data. The features of the wave resonant tunnelling effect in the case of a high-collisional semiconductor plasma were analyzed. This study confirms the proposed earlier method of overcoming the radiocommunication blackout problem.
Giant magneto-impedance effect adjusted by electrolytic polishing and thinning of Co-based amorphous ribbons
Authors: Ma Lei , Zhao Chenbo , Ji Wentao , Liu Qingfang , Wang Jianbo 
Published: April 2022

Abstract
The giant magneto-impedance (GMI) effect of Co-based ribbons treated by using electrochemical polishing method has been investigated. The initial susceptibility (χi
) and the longitudinal GMI ratio (L-GMI) as a function of the polishing time (t
poli) were measured and discussed. The L-GMI firstly increases and then decreases with the increasing of t
poli. At t
poli = 30 s, the maximum GMI of ∼270% is obtained. This L-GMI trend as a function of t
poli is mainly attributed to the variation of effective magnetic anisotropy (H
k,eff). The variation of H
k,eff comes from the optimization of surface qualities as well as the thinning of the thickness. The thinning of the Co-based ribbons results in the changing of demagnetization effect and, more importantly, the variation in the residual stress distributions. The latter effect will strongly affect the magnetization conditions for the samples with longer t
poli: stress variation here is dominant over the influence of surface qualities in the final GMI effect. Furthermore, another factor that may influence GMI is the current density variation related to thickness decrease. At the same time, reducing of stray fields, closely related to surface qualities, is the dominant factor affecting GMI for the samples with shorter t
poli.
Determination of the site preference on the structure, magnetism and mechanical anisotropy properties of Mo-containing alloy carbide M6C (M = Fe, Mo)
Authors: Zheng Peng , Hou Tingping , Zhang Dong , Liang Xuan , Lin Hengfu , Jiang Gengping , Li Yu , Wu Kaiming 
Published: April 2022

Abstract
First-principles calculations are used to study the structure, magnetism and mechanical anisotropy properties of M6C (M = Fe, Mo) carbides. The stability of alloy carbide M6C can be improved when Mo atoms occupy the 48f Wyckoff position. Fe3Mo3C with Mo atoms occupying 48f position and Fe atoms occupying 16d and 32e positions has the best structural stability. The magnetic moment is triggered when the Fe content is approximately 0.5, suggesting that there exists a critical value between the paramagnetic nature and ferromagnetism. Carbides with Fe content above 0.5 have stronger magnetism. Higher Fe content corresponds to the stronger chemical bonding of carbides, resulting in improved elastic properties when Mo atoms are held in 48f position. The special carbides Fe4Mo2C and Fe3Mo3C (Fe at 48f site, Mo at 16d and 32e sites) correspond to the excellent mechanical properties. These results are helpful in providing a theoretical foundation of the possible direction for the advances of the excellent physical properties in Mo-containing steel.
Structural modification enhances the optoelectronic properties of defect blue phosphorene thin films
Authors: Dang M T , Duy N V A , Zaccone A , Schall P , Dinh V A 
Published: April 2022

Abstract
Active enhancement of the optical absorption coefficient to improve the light converting efficiency of thin-film solar cell materials is crucial to develop the next-generation solar cell devices. Here we report first-principles calculations with generalized gradient approximation to study the optoelectronic properties of pristine and divacancy (DV) blue phosphorene (BlueP) thin films under structural deformation. We show that instead of forming sp-like covalent bonds as in the pristine BlueP layer, a DV introduces two particular dangling bonds between the voids. Using a microscopic (non-) affine deformation model, we reveal that the orbital hybridization of these dangling bonds is strongly modified in both the velocity and vorticity directions depending on the type of deformation, creating an effective light trap to enhance the material absorption efficiency. Furthermore, this successful light trap is complemented by a clear signature of σ + π plasmon when a DV BlueP layer is slightly compressive. These results demonstrate a practical approach to tailor the optoelectronic properties of low-dimensional materials and to pave a novel strategy to design functionalized solar cell devices from the bottom-up with selective defects.
An experimental protocol for measuring aerosol deposition in industrial-sized ventilation ducts
Authors: Costa Delphine , Malet Jeanne , Géhin Evelyne 
Published: April 2022

AbstractIn the literature, studies on aerosol deposition in ventilation ducts mainly focus on ventilation ducts with a hydraulic diameter (Dh) of around 15–25 cm and with circular or square cross-sections. However, to the best of our knowledge, common industrial-sized ventilation ducts (Dh∼50 cm) with rectangular cross-sections have not been studied. As a result, experimental aerosol deposition measurement protocols relative to smaller ventilation ducts are not suitable for measurements in industrial-sized ducts. Therefore, a new experimental protocol is proposed here, which can be used without destruction of the surface or addition of a substrate onto the duct surface and which could be applied in industrial ventilation networks if certain conditions are met. In this paper, we present an experimental protocol developed to measure aerosol deposition in large-scale ventilation ducts. First, the collection and measurement technique, the type of aerosol and the injection method are chosen. Second, an experimental protocol relative to the collection of aerosols deposited on duct surfaces is developed, based on a so-called ‘wiping’ technique. Many verifications are presented to ensure repeatable and reproducible measurements. Third, a repeatability study is conducted as well as a validation process. In the last section of this paper, we present some results on aerosol deposition obtained at a test facility compared to two other studies.
Remote neural regulation mediated by nanomaterials
Authors: Zou Liang , Xu Ke , Tian Huihui , Fang Ying 
Published: April 2022

Abstract
Neural regulation techniques play an essential role in the functional dissection of neural circuits and also the treatment of neurological diseases. Recently, a series of nanomaterials, including upconversion nanoparticles (UCNPs), magnetic nanoparticles (MNPs), and silicon nanomaterials (SNMs) that are responsive to remote optical or magnetic stimulation, have been applied as transducers to facilitate localized control of neural activities. In this review, we summarize the latest advances in nanomaterial-mediated neural regulation, especially in a remote and minimally invasive manner. We first give an overview of existing neural stimulation techniques, including electrical stimulation, transcranial magnetic stimulation, chemogenetics, and optogenetics, with an emphasis on their current limitations. Then we focus on recent developments in nanomaterial-mediated neural regulation, including UCNP-mediated fiberless optogenetics, MNP-mediated magnetic neural regulation, and SNM-mediated non-genetic neural regulation. Finally, we discuss the possibilities and challenges for nanomaterial-mediated neural regulation.
Preparation of CeO2@C nanomaterials by adsorption of metal ions on microbial waste
Authors: Fan Wei , Feng Ningning , Xu Gangting , Zhang Xin , Zhao Xiang , Xu Gang , Wu Haiyan , Qiu Guanzhou , Xie Jianping 
Published: April 2022

Abstract
The use of microbial adsorption for metal ions to prepare novel carbon-supported metal nanomaterials has attracted growing research attention. However, the relationship between the adsorbed metal content and catalytic performance of the resulting nanomaterials is unclear. In this work, Pichia pastoris residues was utilized to adsorb Ce(Ⅲ) at different metal ion concentrations, and then CeO2@C nanomaterials were prepared by pyrolysis. The effects of solution pH and adsorption behavior were investigated. The prepared nanostructures were characterized using electron microscopy and different spectroscopy methods, and their catalytic performances in the removal of salicylic acid from solution by catalytic ozonation were invested. The microbial residue had a metal uptake of 172.00 ± 2.82 mg· g−1 at pH 6. In addition, the efficiency of total organic carbon (TOC) removal increased from 21.54% to 34.10% with an increase in metal content in the catalysts from 0 mg· g−1 to 170.05 mg· g−1. After pyrolysis, the absorbed Ce(Ⅲ) metal transformed to CeO2 metal nanoparticles embedded in a carbon matrix and had a core–shell CeO2@C structure. Therefore, this work not only reveals a relationship between metal content and catalytic performance, but also provides an approach for studying performance of materials with different metal contents loaded on various carriers.
Magnetic implosion of thin aluminum foil liners
Authors: Sorokin S A 
Published: April 2022

Abstract
Metal liner implosions driven by a pulsed current generator are used in research on inertial confinement fusion, generation of soft x-ray pulses and megagauss magnetic fields. The energy density in the plasma column formed during the liner stagnation is largely determined by the initial radius and the radial convergence of the liner. When the liner implosion time is close to the current rise time, the liner initial radius is proportional to the current rise time. The paper presents the results of experiments on the fast implosion of cylindrical liners on the MIG generator (2 MA, 80 ns) at the Institute of High Current Electronics, Tomsk, Russia. Liners 0.7–1.0 mm in diameter were made from a 1.8 to 2.5 μm thick aluminum foil. A low-density plasma was pre-injected into the liner area. As the Lorentz force sweeps away the pre-injected plasma, the current switches to the liner in 1–3 ns. Then the liner is imploded in 3–7 ns by a current close to the peak generator current. The stagnation radius measured via time-integrated pinhole camera images was found to be not more than 25 µm. Such a radius of the stagnated plasma assumes that the plasma mass density is several times higher than the solid aluminum density.
Relevance of E × B drifts for particle and heat transport in divertors
Authors: Tsui C K , Boedo J A , Février O , Reimerdes H , Colandrea C , Gorno S 
Published: April 2022

Abstract
Radial electric fields up to ∼4 kV m−1 are observed in the boundary between the private flux region (PFR) and the scrape-off layer (SOL) driving E × B drifts between the inner and outer targets at speeds up to 2.8 km s−1 in the Tokamak à configuration variable divertor. The resulting E × B fluxes, located in a narrow region (

Δ

ρ
Ψ

<
0.012

in normalized radius or

Δ

R − R
sep <4 mm mapped to the outer midplane) are equivalent to around 20% of the total heat and particle flux to the divertor targets (inner + outer). At the peak E
r, the E × B poloidal transport is equivalent to parallel flows with M
∥ ∼ 3. In the snowflake divertor with a second X-point in the outer SOL, the drifts in the PFR-SOL boundary were equivalent to around 30% of the total heat and particle flux to the divertor targets and cover a region ∼50% wider than in the single null (

Δ

ρ
Ψ

∼ 0.018,

Δ

R − R
sep ∼ 6 mm). The location of the PFR-SOL boundary drift shifts radially in the E
∥ × B direction when reversing the toroidal field direction. Peaks in density and electron pressure have been identified near the primary X-point along with large gradients in density, temperature, and potential, the latter resulting in a local electric field ∼2.7 kV m−1 which drives a drift (1.9 km s−1) upwards towards the closed flux surfaces. Floating potential (V
f) magnitudes up to 75 V (∼2 kTe) were measured, indicating that V
f and parallel currents should not be neglected when estimating plasma potential.
Design of microwave β-(Al
x
Ga

1−

x
)2O3/Ga2O3 lateral Schottky barrier diodes
Authors: Shaikshavali Dudekula , Kannadassan D 
Published: April 2022

Abstract
High power microwave Schottky barrier diodes (SBDs) are required to develop detectors and mixers in advance the millimeter-wave (mm-wave) wireless technologies such as fifth generation long-term evolution. To achieve high efficiency and sensitivity in SBDs, materials/structures with high mobility and low series resistance are needed. In this regard, we have proposed the two dimensional electron gas of β-(Al
x
Ga

1
−
x

)2O3/Ga2O3 heterostructure channel lateral SBDs (LSBDs) for the first time. To design high performance LSBDs, detailed physical models of both β-(Al
x
Ga

1
−
x

)2O3 and Ga2O3 were studied and characterized with experimental results. These physical models were used to perform realistic numerical simulations of DC, small signal and large signal conditions. It was observed that the structural and compositional aspects of heterostructure are largely influencing the small signal sensitivity and cut-off frequencies. Also the large signal analysis reveals that the LSBD can operate in linear detection of microwave signals, up to 38 dBm. By scaling down the device to a sub-micron channel length, a cut-off frequency of

>

1.5 THz was achieved in the proposed LSBD. Comparison with state-of-the-art SBDs, the observations from DC, small signal and large signal analysis recommend the proposed β-(Al
x
Ga

1
−
x

)2O3/Ga2O3 LSBDs for high power and mm-wave/sub-THz detector/mixer application.
Structural and ultrasound studies of Pr2O3 settlement in AlNaBi–phosphate spectacles
Authors: El-Denglawey A , Saddeek Yasser B , Aly K A , Showahy A A , Alharbi T 
Published: April 2022

Abstract
Pr2O3 doped bismuth-phosphate glasses have been produced via an ordinary melt quenching tool. Glasses have a chemical content (5–x) Al2O3–15Na2O–20Bi2O3–60 P2O5 –xPr2O3 with x values between 0 and 2 mol%. The structural and mechanical features of the prepared phosphate-based glasses were investigated. The XRD spectra confined the amorphous type of these glasses. Furthermore, the influence of Pr2O3 on the mechanical features has been explored and related to the structure. The relationship between structural variations and the contents of Pr2O3 has been investigated in terms of FTIR and by the determination of the density and the ultrasonic velocity. The density and the ultrasonic velocities were utilized to calculate the elastic moduli of the glasses. The acquired results indicate that the ultrasonic velocity and the elastic moduli increase as a function of Pr2O3 in the whole explored studied glasses. The analysis of FTIR spectra refers that Pr2O3 is interstitial settled in the phosphate network with [PrO7] associated with covalent Pr–O–P bonds, whereas Bi2O3 and Al2O3 settle on the network with [BiO6], and [AlO6] units. These experimental features coincide with a compact structure and act in a manner that Pr2O3 incorporates the glassy network with plenty of bridging oxygen atoms. These arguments encourage the use of these glasses in radiation shielding materials.
The effect of dark matter discreteness on light propagation
Authors: Koksbang Sofie Marie , Räsänen Syksy 
Published: April 2022

Abstract
Light propagation in cosmology is usually studied in the
geometrical optics approximation which requires the spacetime
curvature to be much smaller than the light wavenumber. However, for
non-fuzzy particle dark matter the curvature is concentrated in
widely separated spikes at particle location. If the particle mass
is localised within a Compton wavelength, then for masses
≳104 GeV the curvature is larger than the energy of CMB
photons.

We consider a post-geometrical optics approximation that includes
curvature. Photons gain a gravity-induced mass when travelling through
dark matter, and light paths are not null nor geodesic. We find that
the correction to the redshift is negligible. For the angular diameter
distance, we show how the small average density emerges from the large
local spikes when integrating along the light ray. We find that there
can be a large correction to the angular diameter distance even for
photon energies much larger than the curvature. This may allow to set
a strong upper limit on the mass of dark matter particles. We discuss
open issues related to the validity of our approximations.
The influence of approximation in generalized uncertainty principle on black hole evaporation
Authors: Du Xin-Dong , Long Chao-Yun 
Published: April 2022

Abstract
The generalized uncertainty principle is often used to modify various thermodynamics systems by regarding the greater-than-equal relation as an approximate relation. We give a method to improve this approximation and compare the differences between the original and improved methods during the evaporation of black hole from two aspects of positive and negative parameters. Finally, we prove the rationality of the improved method and give some guiding opinions.
Temperature-based Collision Detection in Extreme Low Light Condition with Bio-inspired LGMD Neural Network
Authors: Zhang Yicheng , Hu Cheng , Liu Mei , Luan Hao , Lei Fang , Cuayahuitl Heriberto , Yue Shigang 
Published: April 2022

Abstract
It is an enormous challenge for intelligent vehicles to avoid collision accidents at night because of the extremely poor light conditions. Thermal cameras can capture temperature map at night, even with no light sources and are ideal for collision detection in darkness. However, how to extract collision cues efficiently and effectively from the captured temperature map with limited computing resources is still a key issue to be solved. Recently, a bio-inspired neural network LGMD has been proposed for collision detection successfully, but for daytime and visible light. Whether it can be used for temperature-based collision detection or not remains unknown. In this study, we proposed an improved LGMD-based visual neural network for temperature-based collision detection at extreme light conditions. We show in this study that the insect inspired visual neural network can pick up the expanding temperature differences of approaching objects as long as the temperature difference against its background can be captured by a thermal sensor. Our results demonstrated that the proposed LGMD neural network can detect collisions swiftly based on the thermal modality in darkness; therefore, it can be a critical collision detection algorithm for autonomous vehicles driving at night to avoid fatal collisions with humans, animals, or other vehicles.
Using deep learning to detect the presence/absence of defects on leather: on the way to build an industry-driven approach
Authors: Adão Telmo , Gonzalez Dibet , Castilla Yusbel Chavez , Pérez José , Shahrabadi Somayeh , Sousa Nuno , Guevara Miguel , Magalhães Luis G. 
Published: April 2022

Abstract
In textile/leather manufacturing environments, as in many other industrial contexts, quality inspection is an essential activity that is commonly performed by human operators. Error, fatigue, ergonomic issues, and related costs associated to this fashion of carrying out fabric validation are aspects concerning companies’ strategists, whose mission includes to watch over the physical integrity of their employees, while aiming at enhanced quality control methods implementation towards profit maximization. Considering these challenges from a technical/scientific perspective, machine/deep learning approaches have been showing great skills in adapting a wide range of contexts and, in particular, industrial environments, complementing traditional computer vision methods with characteristics such as increased accuracy while dealing with image classification and segmentation problems, capacity for continuous learning from experts input and feedback, flexibility to easily scale training for new contextualization classes – unknown types of occurrences relevant to characterize a given problem –, among other advantages. The goal of crossing deep learning strategies with fabric inspection processes is pursued in this paper. After providing a brief but representative characterization of the targeted industrial context, in which, typically, fabric rolls of raw-material mats must be processed at a relatively low latency, an Automatic Optical Inspection (AOI) system architecture designed for such environments is revisited [1], for contextualization purposes. Afterwards, a set of deep learning-oriented training methods/processes is proposed in combination with neural networks built based on Xception architecture, towards the implementation of one of the components that integrate the aforementioned system, from which is expected the identification of presence/absence of defective textile/leather raw material at a low-latency. Several models powered by Xception were trained with different tunning parameters, resorting to datasets variations that were set up from raw images of leather, following different annotation strategies (meticulous and rough). The model that performed better reached 96% of accuracy.