bluuebunny/crossref_metadata_2025 huggingface dataset:
Similarity-based probabilistic remaining useful life estimation for an aeroengine under variable operational conditions
Authors: Wang Cunsong , Miao Xiaodong , Zhang Quanling , Bo Cuimei , Zhang Dengfeng , He Wenmin
Published: July 2022

System-level remaining useful life (RUL) estimation is difficult due to multiple degrading components, external disturbances, and variable operational conditions. A similarity-based approach does not rely on health assessment and is more suitable for system-level RUL estimation. However, for practical applications, how to capture effective degradation features from raw data, how to fuse multiple nonlinear sensor data, and how to handle multiple source uncertainties need to be considered. To solve the above challenges, this study focuses on RUL estimation for systems under variable operational conditions. A similarity-based probabilistic RUL estimation strategy is proposed and verified using the NASA aeroengine dataset. First, measurement uncertainty can be addressed. Proper degradation features are extracted by three defined indicators. Subsequently, multiple nonlinear sensor data fusion and unsupervised synthesized health index construction can be realized using the proposed deep autoencoder-based polynomial regression approach. Finally, this strategy can handle the modeling and prediction uncertainties, including providing probabilistic RUL estimation results by well-trained residual-based similarity models. The verification results indicate the effectiveness and feasibility of the proposed strategy.
Fabrication of high sensitivity and stable strain sensors based on composite folded structures via embedded 3D printing
Authors: Xie Xiaozhu , Wu Wenjie , Xiao Jincheng , Ren Qinglei
Published: July 2022

Flexible strain sensors provide a practical and straightforward detection technique for the human motion to convert strain changes into resistance changes. We present extremely sensitive and stable strain sensors prepared by embedded 3D printing technology in this paper. By incorporating polydimethylsiloxane (PDMS) material and printing a folded structure, the sensing performance of the sensors is explored. The combination of PDMS with high Poisson’s ratio and silicone rubber with low modulus of elasticity endow strain sensors with an ideal combination of great sensitivity and strong stretchability (gauge factor of 6 in the strain of 50%, good durability (stretch/release test of 1000 cycles). The strain sensor attached to the hand demonstrates good sensing performance.
Growth instabilities shape morphology and genetic diversity of microbial colonies
Authors: Golden Alexander , Dukovski Ilija , Segrè Daniel , Korolev Kirill S
Published: July 2022

Cellular populations assume an incredible variety of shapes ranging from circular molds to irregular tumors. While we understand many of the mechanisms responsible for these spatial patterns, little is known about how the shape of a population influences its ecology and evolution. Here, we investigate this relationship in the context of microbial colonies grown on hard agar plates. This a well-studied system that exhibits a transition from smooth circular disks to more irregular and rugged shapes as either the nutrient concentration or cellular motility is decreased. Starting from a mechanistic model of colony growth, we identify two dimensionless quantities that determine how morphology and genetic diversity of the population depend on the model parameters. Our simulations further reveal that population dynamics cannot be accurately described by the commonly-used surface growth models. Instead, one has to explicitly account for the emergent growth instabilities and demographic fluctuations. Overall, our work links together environmental conditions, colony morphology, and evolution. This link is essential for a rational design of concrete, biophysical perturbations to steer evolution in the desired direction.
Modeling the dynamics of innate immune response to Parkinson disease with therapeutic approach
Authors: Badrah Asma , Al-Tuwairqi Salma
Published: July 2022

This paper aims to mathematically model the dynamics of Parkinson’s disease with therapeutic strategies. The constructed model consists of five state variables: healthy neurons, infected neurons, extracellular α-syn, active microglia, and resting microglia. The qualitative analysis of the model produced an unstable free equilibrium point and a stable endemic equilibrium point. Moreover, these results are validated by numerical experiments with different initial values. Two therapeutic interventions, reduction of extracellular α-syn and reduction of inflammation induced by activated microglia in the central nervous system, are investigated. It is observed that the latter has no apparent effect in delaying the deterioration of neurons. However, treatment to reduce extracellular α-syn preserves neurons and delays the onset of Parkinson’s disease, whether alone or in combination with another treatment.
An improved multiple populations quantum genetic algorithm
Authors: Niu Xu-Feng , Ma Wen-Ping
Published: July 2022

With the in-depth study of quantum genetic algorithm (QGA), the defect of premature convergence limits its development more and more. In order to further improve QGA, we propose an improved QGA based on multi population (IQGA). In the process of population initialization in IQGA, we generate multiple populations to avoid a single population falling into a local optimal value. We also abandon the fixed angle used by the traditional quantum revolving gate, and design a strategy to adjust the angle adaptively according to the difference from the optimal solution. In addition, we introduce a population catastrophe strategy to deal with the premature convergence of each population. The populations are connected based on migration operation, and the optimal solution of each population obtained by each iteration is collected in the elite group. A series of simulation experiments show that our improvement strategies of IQGA are effective.
Tuning the particle size, physical properties, and photocatalytic activity of Ag3PO4 materials by changing the Ag+/

PO43−

ratio
Authors: N M Hung , L T M Oanh , D P Chung , D V Thang , V T Mai , L T Hang , N V Minh
Published: July 2022

This study demonstrates the influence of the Ag+/

PO

4

3
−

ratio in precursor solution on the crystal structural formation, morphology, physical properties, and photocatalytic performance of a Ag3PO4 photocatalyst that is fabricated, using a facile precipitation method, from AgNO3 and Na2HPO4⋅12H2O. The material characterizations were carried out using x-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDX), Brunauer–Emmett–Teller (BET) surface area, Fourier transform infrared (FTIR) absorption, Raman scattering, x-ray photoelectron spectroscopy (XPS), UV-vis absorption, and photoluminescence (PL). The results show that Ag3PO4 crystallizes better when the excess

PO

4

3
−

content increases, and the lattice parameters decrease slightly, while the crystal diameter and the particle size increase. This change is also observed in the Raman scattering and FTIR spectra with the increase in the vibration frequency of the [PO4] group. The compression of the [PO4] unit was also confirmed in the XPS spectra with the shift of P 2p peaks toward higher binding energy. The photocatalytic results showed that the samples synthesized from excess

PO

4

3
−

solution exhibited higher photocatalytic performance compared to the sample with a Ag+/

PO

4

3
−

ratio of 3:1. A sample prepared from the precursor solution with a Ag+/

PO

4

3
−

ratio of 3:1.5 was optimal for RhB decomposition under both visible light and natural sunlight, completely decomposing 10 ppm RhB after 15 minutes of xenon lamp irradiation and after 60 minutes under solar light irradiation. This is attributed to the high crystallinity, small particle size and low electron–hole recombination rate of the sample.
Emergence of mass in the gauge sector of QCD*
Authors: Papavassiliou J.
Published: July 2022

It is currently widely accepted that gluons, while massless at the level of the fundamental QCD Lagrangian, acquire an effective mass through the non-Abelian implementation of the classic Schwinger mechanism. The key dynamical ingredient that triggers the onset of this mechanism is the formation of composite massless poles inside the fundamental vertices of the theory. These poles enter the evolution equation of the gluon propagator and nontrivially affect the way the Slavnov-Taylor identities of the vertices are resolved, inducing a smoking-gun displacement in the corresponding Ward identities. In this article, we present a comprehensive review of the pivotal concepts associated with this dynamical scenario, emphasizing the synergy between functional methods and lattice simulations and highlighting recent advances that corroborate the action of the Schwinger mechanism in QCD.
Charged quark stars in f(R,T) gravity*
Authors: Pretel Juan M. Z. , Tangphati Takol , Banerjee Ayan , Pradhan Anirudh
Published: July 2022

Recent advances in nuclear theory and new astrophysical observations have led to the need for specific theoretical models applicable to dense-matter physics phenomena. Quantum chromodynamics (QCD) predicts the existence of non-nucleonic degrees of freedom at high densities in neutron-star matter, such as quark matter. Within a confining quark matter model, which consists of homogeneous, neutral 3-flavor interacting quark matter with

corrections, we examine the structure of compact stars composed of a charged perfect fluid in the context of

gravity. The system of differential equations describing the structure of charged compact stars has been derived and numerically solved for a gravity model with

. For simplicity, we assumed that the charge density is proportional to the energy density, namely,

. It is demonstrated that the matter-geometry coupling constant β and charge parameter α affect the total gravitational mass and the radius of the star.
Application of simulations and theory of sub-cyclotron frequency modes to DIII-D
Authors: Belova E.V. , Crocker N.A. , Lestz J.B. , Fredrickson E.D.
Published: July 2022

Theoretical and numerical study of Alfvén eigenmodes (AEs) in the sub-cyclotron frequency range explains the observed frequency scaling with beam parameters in experiments across different devices. Global Alfvén (GAEs) and compressional Alfvén eigenmodes (CAEs) are frequently excited during neutral beam injection (NBI) in the National Spherical Torus Experiment (NSTX/NSTX-U), as well as other beam-heated devices such as MAST and DIII-D. These modes are driven unstable through the Doppler shifted cyclotron resonance with the NBI ions and can be excited in ITER due to super-Alfvénic velocities and anisotropy of the fast ion distribution. Numerical models and theory for sub-cyclotron frequency modes, previously developed and used to study the excitation of GAEs/CAEs in the NSTX(-U), have been successfully applied to explain the DIII-D observations. Simulations for DIII-D demonstrate that the modes with ω/ω
ci ∼ 0.6, previously mis-identified as CAEs, have shear polarization and should be identified as the GAEs. Simulation results match the observed frequencies and estimated toroidal mode numbers in DIII-D experiments. Good agreement is found between scaling of the experimentally observed GAE frequencies with NBI parameters for NSTX, NSTX-U and DIII-D and scaling predicted by the theory and simulations. The DIII-D simulation results also demonstrate that GAEs can be excited for larger aspect-ratio devices and smaller (sub-Alfvénic) beam injection velocities, therefore they can be unstable in ITER.
Comparative study of stages of titanium minerals formation in nature and experiment for “smart” materials industry
Authors: Ponaryadov A , Kotova O , Sun S , Kurovics E , Ibrahim J E F M , Gömze L A
Published: July 2022

The economic importance of titanium oxides and hydroxides results in the active development of titanium deposits. Considering world trends in the development of titanium ores and taking into account their mineralogical features, a comparative study of stages of titanium minerals formation in nature (mineralogenesis) and their transformations in technological processing or synthesis (technogenesis) under hydrothermal conditions at the macrolevel (textural), micro-level (structural) and nanoscale (heterogeneity of individuals and microaggregates, including the synthesis of nanostructures) was made. The natural mechanism of mineral formation of titanium ores in the geological system (titanium ore – hydrothermal conditions) have been successfully used to simulate the synthesis of titanium nanotubes: a trigger for the redeposition of ore matter with the formation of new mineral phases and restructuring at the macro-, micro- and nanoscale is the energy of the geological system/its model, which is sufficient to create conditions for inhomogeneiting (destabilizing) the initial structure of titanium minerals due to external influences (P, T, pH). The relationship between the stages of mineral formation processes in nature and experiment as a promising strategy for the “smart” materials industry was discussed.
Synthesis of silver nanoparticles coated with bovine serum albumin for application as vaccine carriers
Authors: Rodríguez-Calderón A G , Contreras-García M E , Nuñez-Anita R E
Published: July 2022

Nanostructured particles represent a viable option for antigen carrier design in new vaccine development. In this research stage, some of the results obtained for the synthesis of silver nanoparticles covered with bovine serum albumin (AgNP-BSA) are presented. The silver nanoparticles were obtained by chemical reduction of silver nitrate (AgNO3) as precursor and sodium citrate (C6H5Na3O7) as reducing agent. The AgNP-BSA were obtained from the wet impregnation method using bovine serum albumin suspension at five different concentrations. The nanostructures were characterized by UV-vis spectroscopy, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), dynamic light scattering (DLS), and zeta potential (ζ).
Synthesis and characterization of alkali-activated zeolite-poor rocks
Authors: M. Ibrahim Jamal Eldin F. , Kurovics Emese , Tihtih Mohammed , Gömze László A. , Kocserha István
Published: July 2022

Zeolite-geopolymer composite materials were obtained through mechanical activation using planetary ball mill followed by chemical activation using an aqueous solution of sodium hydroxide (NaOH), these materials integrate the beneficial features of both zeolites and geopolymers. In this present work, the morphological characteristics, microstructure, phase determination of raw materials and the generated ceramic samples were studied by several characterization methods such as SEM, EDS and XRD. The microstructural analysis confirms the formation of needle-like structure in sub-micron and nanostructure, while the phase identification reveals the creation of single-phase zeolite (heulandite).
Influence of secondary carbon fiber on the mechanical behaviour and microstructure of alkali-activated granulated blast furnace slag-based composites
Authors: Klimenko N N , Kiseleva K I , Kienskaya K I , Nistratov A V , Volfkovich Yu M , Sosenkin V E , Delitsyn L M , Sigaev V N.
Published: July 2022

This study aimed to investigate the mechanical behaviour and microstructure of an environmentally friendly fibre-reinforce alkali-activated composites. The composites were obtained from alkali-activated granulated blast furnace slag reinforced with chopped secondary carbon fibres (SCFs) coming from the aircraft industry carbon fiber reinforced plastics waste. Three types of surfactants and two concentrations of SCFs were investigated. The compressive and bending strengths were measured to evaluate the mechanical behaviour of specimens. Moreover, the polycondensation products, pore structure, and microscopic morphology of the composites were analyzed using X-ray diffraction (XRD), method of standard contact porosimetry (MSCP), and scanning electron microscopy (SEM). It was found that tetraethylammonium bromide and a superplasticizer agent Glenium-51® increase compressive strength for reference granulated blast furnace slag-based alkali-activated matrix approximately by 60 % and lead to lower open porosity from 16 to 5 %. The experimental results showed that the incorporation of 0.7 vol. % SCFs had an optimal influence on mechanical behaviour and microstructure of composite. Based on the test results, it can be clearly said that using of Glenium-51® is improving the compressive strength of slag based alkali-activated composites reinforced SCFs.
Magnetic properties and morphology of ultra-small iron oxide nanoparticles
Authors: Pizúrová N , Buršík J , Sojková T , Roupcová P , Schneeweiss O
Published: July 2022

Maghemite nanoparticles prepared with the modified synthesis method published by Sun et al. 2004 and followed by filtering to extract a sample of the smallest nanoparticle size were investigated. The 2-5 nm nanoparticles of monocrystalline and multi-twinned morphology without surface shells were observed. Superparamagnetic behavior was detected above the temperature of 40 K. An exchange bias loop shift of ~ 2 mT at 3 K after cooling with an external field of 3 T suggested a low influence of the surface spin disorder effect. Mössbauer spectroscopy confirmed the two phases with different blocking temperatures, the maghemite phase as well as a second one likely originating from the disordered surface component.
A colorimetric method of As3+ ion detection and quantification using hand-held Lovibond photometers.
Authors: Kumar R. , Rauwel P. , Kriipsalu M. , Rauwel E.
Published: July 2022

Among the existing forms of arsenic, As3+ compounds are the most abundant and toxic in the environment. In the present study, we design a colorimetric method that selectively detects arsenite ions in aqueous media using fuchsine as an indicator. The novelty of this method lies in the use of Lovibond MD-610 hand-held photometer in order to determine the absorptivity at a wavelength of 560 nm. Subsequently a calibration curve for various known As3+ concentrations was plotted using Lambert-Beer’s law. The arsenite concentrations studied ranged from 0.2-10 ppm.
Advanced and emerging materials for testing a curtain wall connection element for improved seismic performance
Authors: Giglio F , Milardi M , Sansotta S
Published: July 2022

The research for emerging and disruptive new materials and advanced technologies is a driver of technological innovation in both industry and academia. In this work, the authors present some parts of the results of their research and investigation. The experimental research of advanced materials is a constantly evolving field, concerning the need to respond to increasingly advanced technical performance, even in the construction sector and specifically for Building Envelopes. In this context, the contribution concerns ongoing experimental research, which investigates the dynamic behavior of non-structural elements of the Facade subjected to the action of the earthquake. The results of the investigations conducted so far aim to increase innovation in the field of advanced materials for extreme applications, for the constraints on the implementation of the technologies (increasing element sizes, higher mechanical strengths, better performance), exploiting the superelastic effect (SE) and the shape memory effect (SME). Thus, it seems clear that the potential of the two unique properties for Facade Design applications is a valuable tool for investigating dynamic behaviors that exist in nature as well.
Multi - Purpose Photonic Crystal-Based Sensor Design by Finite Element Method
Authors: Ozer Zafer , Palaz Selami , Mamedov Amirullah M. , Ozbay Ekmel
Published: July 2022

Due to the full reflection of electromagnetic waves, certain frequencies cannot propagate in photonic crystals. Waveguides and resonators obtained by removing some rods in photonic crystals with band gap are sensitive to small changes in refractive index. Using this sensitivity, photonic crystal-based sensors can be designed for different purposes. The refractive index changes when the sample with different refractive index is placed in the detection area. Sensors sensitive to refractive index change, detect samples with different refractive indices placed in the detection area by shifting the resonant wavelength of the sensor.

In this study, photonic crystal-based multi-purpose sensor was designed and analyzed by finite element method. The sensitivity and quality factor of the sensors were examined.
A planetary boundary-based method to assess freshwater use at the global and local scales
Authors: Kulionis Viktoras , Pfister Stephan
Published: July 2022

Many studies have attempted to evaluate the transgression of the water planetary boundary at sub-global levels. Typically, this has been done by assessing water consumption in a country/city or sector against the assigned share of the global limit. Such an approach enables evaluating whether a sub-global unit operates within the safe global limits. However, it ignores spatial water availability and thus may provide an incomplete image of water-related environmental impacts and thus local boundaries. This study demonstrates how the water planetary boundary concept can be integrated within the Environmentally Extended Multi-Region Input-Output (EEMRIO) framework to assess global and local (watershed level) boundaries. Our results demonstrate that even though most countries operate within globally safe limits, for several countries, a large share of water comes from watersheds that have reached unsafe water consumption levels. This highlights the importance of combining local and global level assessments to design more accurate and tailored policy responses targeting specific watersheds that are most at risk.
An efficient linked list for molecular simulations on a spherical surface
Authors: Ramírez Esteban Vélez , Elvingson Christer
Published: July 2022

The main part of the cpu time in molecular simulations is usually spent calculating the non-bonded interactions. To improve the efficiency, a neighbour list or a cell linked list is normally used, where the linked list is usually more efficient and requires less memory for a large number of particles or dense systems. The linked list, however, still suffers from including many pairs which will not be within the interaction distance, and this overhead becomes even more significant for higher dimensions. In this work, we consider specifically simulations of particles confined to move on a spherical surface, where the overhead using a cubic grid to form a linked list becomes even larger by also including many cells which do not intersect the sphere. We address this by setting up a linked list directly on the spherical surface, thus reducing the dimensionality of the resulting neighbour search. We show that one obtains not only a substantial reduction in cpu time, but also a significant decrease in memory requirement. We further show how to extend this procedure to the 3-sphere (hypersphere), which can be used to simulate bulk systems avoiding periodic boundaries. Also in this case, using a linked list directly on the 3-sphere, the reduction in cpu time is significant, and the decrease in memory requirement, compared with a regular grid in

R

4

, is even more pronounced. We finally comment on how the efficiency of the described method can be further improved.
Relativistic quantum scarring, spin-induced phase, and quantization in a symmetric Dirac billiard system
Authors: Li Zi-Yuan , Ye Li-Li , Ni Rui-Hua , Wang Cheng-Zhen , Huang Liang , Lai Ying-Cheng , Grebogi Celso
Published: July 2022

Thirty-five years ago, Sir Michael Berry and his collaborator Mondragon studied the behaviors of neutrino, a massless relativistic quantum particle, in a classically chaotic billiard—the neutrino billiard problem. To celebrate Sir Michael Berry’s eightieth birthday, here we report results on the role of geometric symmetries of the billiard system in relativistic quantum scarring. In particular, we investigate a Dirac billiard system with a four-fold rotational symmetry whose classical dynamics are fully chaotic. The system is described by the massless Dirac equation in the fundamental domain that consists of one fourth of the full billiard, with proper boundary conditions on the symmetry lines to preserve the physical properties under the symmetry operations. We show that the relativistic quantum characteristics of spin induced phase play a fundamental role in the quantum behaviors of the Dirac particle in the billiard. We find that the peaks in the length spectra are due to the interference of states circling the fundamental domain orbits (FDOs) in opposite propagating directions, which can be constructive or destructive depending on the accumulated phases. In addition, we derive the quantization conditions of the scarring states about the unstable periodic orbits within the fundamental domain from the phase along the FDOs. Our work is a vivid demonstration that relativistic quantum scarring, or more generally quantum manifestations of classical chaos, can be fully understood by analyzing the behaviors of the geometric phase—a powerful approach in modern physics pioneered by Sir Michael Berry.
On the physical limitations of structured paraxial beams with orbital angular momentum
Authors: Jaimes-Nájera A , Gómez-Correa J E , Ugalde-Ontiveros J A , Méndez-Dzul H , Iturbe-Castillo M D , Chávez-Cerda S
Published: July 2022

In the description of physical systems it is common to discard singular solutions to second order differential equations due to their apparent lack of physical meaning. Nevertheless, it has been demonstrated, using a mathematical-physics approach, that singular solutions can be used in the description of optical beams. In this paper, we construct and study paraxial traveling-waves using the full set of solutions to the paraxial wave equation, and prove that they diverge at infinity. We ascribe that non-physical effect to the paraxial approximation of the Helmholtz equation. Despite this, we show that these traveling waves provide a mathematical-physics framework that unveils orbital angular momentum carrying Laguerre–Gauss beam as the superposition of these traveling waves, and permits a physical description of the self-healing process.
Insight into mechanisms of creatinine optical sensing using fluorescein-gold complex
Authors: Anselmo Sara , De Luca Giuseppe , Ferrara Vittorio , Pignataro Bruno , Sancataldo Giuseppe , Vetri Valeria
Published: July 2022

Creatinine level in biological fluids is a clinically relevant parameter to monitor vital functions and it is well assessed that measuring creatinine levels in the human body can be of great utility to evaluate renal, muscular, or thyroid dysfunctions. The accurate detection of creatinine levels may have a critical role in providing information on health status and represents a tool for the early diagnosis of severe pathologies. Among different methods for creatinine detection that have been introduced and that are evolving with increasing speed, fluorescence-based and colorimetric sensors represent one of the best alternatives, thanks to their affordability, sensitivity and easy readability. In this work, we demonstrate that the fluorescein-Au3+ complex provides a rapid, selective, and sensitive tool for the quantification of creatinine concentrations in ranges typical of sweat and urine. UV-visible absorption, diffuse reflectance spectroscopy, steady state and time resolved fluorescence spectroscopy were used to shed light on the molecular mechanisms involved in the changes of optical properties, which underlie the multiplexed sensor analytical reply. Interestingly, sensing can be performed in solution or on solid nylon support accessing different physiological concentrations from micromolar to millimolar range. As a proof-of-concept, the nylon-based platform was used to demonstrate its effectiveness in creatinine detection on a solid and flexible substrate, showing its analytical colorimetric properties as an easy and disposable creatinine point-of-care test.
Alkaline N-GQDs fluorescent probe for the ultrasensitive detection of creatinine
Authors: Ravi Pavithra Verthikere , Subramaniyam Vinodhini , Saravanakumar Neha , Pichumani Moorthi
Published: July 2022

Creatinine (Crn) is an important excretory product of the human body. Medical laboratory technology has improved over years and brought many advancements in clinical diagnostics equipment, and testing techniques and made the tests more efficient. Yet, the quantitative analysis of Crn is still carried out by the classical Jaffe’s reaction (using Picric acid (PA) with NaOH) method. Since PA is hazardous to human health, alternative solutions such as; nanoparticles and surface-modified nanoparticles can be used. Exploring the optoelectronic properties of carbon-based quantum dots for biomolecule sensing is of current interest among researchers. Nitrogen functionalized graphene quantum dots (Alk-NGQDs) measured featured Crn easier and reduced the time taken for the test carried out in laboratories. The synthesized Alk-NGQDs optical, structural, morphological properties, surface and compositions are studied through XPS, HRTEM, XRD, FTIR, and spectroscopic techniques. Alk-NGQDs at alkaline conditions (pH 9.5) form a stable complex with Crn through intermolecular charge transfer (ICT). The fluorescence titration method is used to sense Crn in commercial Crn samples and human blood serum. To understand the efficacy of sensing creatinine using Alk-NGQDs, working concentration, fluorescence quantum yield, the limit of detection, and quenching constant are calculated using the Stern-Volmer plot. The emission property of Alk-NGQDs is aimed to bring an alternative to the traditional colorimetric Jaffe’s reaction.
Surface state change influence’s theoretical approach of pressed iron on hollow cathode discharge characteristics: first results of plasma heating reproducibility for sintering purposes
Authors: Brunatto Silvio Francisco
Published: July 2022

In this work first results of the plasma heating process reproducibility for sintering purposes of pressed iron powder sample was investigated analyzing changes on the current-voltage characteristics of pulsed direct current (dc) Ar + H2 hollow cathode discharges sequentially carried out. For this purpose, the temperature of a sample acting as central cathode was varied by changing the switched-on time (duty cycle) of the pulse, via plasma species bombardment (ions and fast neutrals), which typically occurs in both cathode cylindrical surfaces that constitute the annular (hollow cathode) glow discharge, and measured by a thermocouple inserted in the central cathode sample holder. After two sequential plasma heating experiments, the third one practically reproduced the measured plasma parameters evidenced in the second heating, and the respective heating curves as a function of the time have led to similar current-voltage characteristics suggesting the iron sample sintering in non-isothermal way. Principles comprising plasma-surface interface and metallurgical-physical-chemical reactions, powder surface aspects, thermodynamic properties, metallurgical transformation of the pressed sample, and hollow cathode discharge properties are presented and discussed. The main points considered in the present approach are related to plasma (oxygen-affected plasma ionization, high ionization and excitation rate, and the intense light radiation of the annular glow discharge), thermodynamics (oxidation-reduction reactions, electron work function, sintering driving force, and surface energy), and powder (particle size distribution, morphology, specific surface, and iron recrystallization). To the best of the author’s knowledge, it is the first time that it is brought to the light the changes on hollow cathode discharge characteristics while an iron sample acting as the central cathode of an annular glow discharge is subjected to distinct heating steps on the temperature range of 20 to ∼1250 °C, leading it to have its sintering initiated.
Developing natural film for seasoning packaging of instant noodles
Authors: Ratchawet Anodar , Taokhum Pronpimol , Chaijalern Yuttana
Published: July 2022

This research aims to develop films from natural materials to be used as seasoning packaging for instant noodles. Natural materials such as bananas and konjac are used as raw materials for film-forming. There were 27 formulations of film-forming, including 9 formulas from the banana starch film, 9 formulas from banana starch blended with konjac powder 0.5% w/w, and 9 formulas from banana starch blended with konjac powder 1.0% w/w. The mechanical and physical properties of various formulation films were tested. When selecting a formulation film that meets the packaging requirements for 2 formulations by selecting one banana starch film and one banana starch film blended with konjac powder, it was found that the film formula B4Gly20 (banana 4% W/V and glycerol 20% V/V) and formula K05/4Gly20 (konjac 0.5% W/V blended with banana 4% W/V and Glycerol 20% V/V) have the best fit. They had properties close to specifications such as thickness and water permeability, not significantly different at 0.05%, and high tensile strength of 4.015 and 5.172 N.mm−2. The flexibility was 27.67 and 22.22 percent, and the water vapor permeability was 0.0063 and 0.0021 g. hr−1.cm -2, respectively., resistance to acidic solutions, and can be formed into strong packaging film, etc. When applying these two film formulas to the seasoning packaging of instant noodles, it was found that both film formulations did not prevent moisture in the air. The film formula B4Gly20 effectively prevented oil leakage. And also, B4Gly20 was more resistant to oxygen penetration into the cooking oil than K05/4Gly20 formulation film, but film formulation B4Gly20 was dissolved in hot water 100 ± 10 °C slower than K05/4Gly20. The results showed that the film formulation B4Gly20 was suitable for application in the seasoning packaging of instant noodles.
Effect of polymer amount on the mechanical behavior of polymer-infiltrated zirconia-ceramic composite at different pre-sintering temperatures
Authors: Alao Abdur-Rasheed , Rafiuddin Eliza Md Nur Adi Syafi , Rahman Ahmad Shamil Abd
Published: July 2022

Polymer-infiltrated zirconia-ceramic composite (PIZC) comprises a pre-sintered zirconia-ceramic matrix and a polymer. In this work, pre-sintered zirconia-ceramic was infiltrated with varied amounts of methacrylate-based polymer. Therefore, this paper reports the effect of polymer amount on the mechanical behavior of PIZC at 1100 °C–1300 °C pre-sintering temperatures. Conventional mechanical tests were performed to obtain the elastic modulus and fracture toughness while Vickers micro-indentations were employed to extract the Vickers hardness. Advanced mechanical behaviour analysis was characterized by plastic deformation resistance, elastic and plastic deformation components and brittleness index. Increasing the amount of polymer from 0 to 42% led to the corresponding decrease in elastic modulus, hardness and fracture toughness by at least 78, 85 and 75%, respectively. As the temperature was increased, both elastic modulus and hardness increased while the fracture toughness initially increased but decreased at higher temperature. Mechanical properties and polymer amount were well modelled by connected-grain models which usefully explained the densification process occurring at higher temperatures. Plastic deformation resistance and component and brittleness index confirmed better plastic properties for PIZC at higher polymer amounts and lower temperature. Therefore, in order to utilize the plastic properties of PIZC during the CAD/CAM process, these findings recommended the processing of PIZC at not-lower-than 26% polymer amount and 1100 °C, which could greatly facilitate its precision ductile machining mode realization. Finally, the results provide a technical guidance for the selection of appropriate polymer amount when fabricating dental restorations from this novel ceramic-composite.
Quantum solvability of a nonlinear δ-type mass profile system: coupling constant quantization
Authors: Chithiika Ruby V , Chandrasekar V K , Lakshmanan M
Published: July 2022

In this paper, we discuss the quantum dynamics of a nonlinear system that admits temporally localized solutions at the classical level. We consider a general ordered position-dependent mass Hamiltonian in which the ordering parameters of the mass term are treated as arbitrary. The mass function here is singular at the origin. We observe that the quantum system admits bounded solutions but importantly the coupling parameter of the system gets quantized which has also been confirmed by the semiclassical study as well.
Use of Debye–Hückel–Henry charge measurements in early antibody development elucidates effects of non-specific association
Authors: Laber Joshua R , Laue Thomas M , Filoti Dana I
Published: July 2022

The diffusion interaction parameter (kD) has been demonstrated to be a high-throughput technique for characterizing interactions between proteins in solution. kD reflects both attractive and repulsive interactions, including long-ranged electrostatic repulsions. Here, we plot the mutual diffusion coefficient (Dm) as a function of the experimentally determined Debye–Hückel–Henry surface charge (ZDHH) for seven human monoclonal antibodies (mAbs) in 15 mM histidine at pH 6. We find that graphs of Dm versus ZDHH intersect at ZDHH, ~ 2.6, independent of protein concentration. The same data plotted as kD versus ZDHH show a transition from net attractive to net repulsive interactions in the same region of the ZDHH intersection point. These data suggest that there is a minimum surface charge necessary on these mAbs needed to overcome attractive interactions.
Increasing Representation of Epidemiologists From Around the World in the Society for Epidemiologic Research: The Case of Mexico
Authors: Jimenez Marcia P , Gutierrez Tonatiuh Barrientos , Soria-Contreras Diana C , Abdel Magid Hoda S , Kaufman Jay S , Committee of the Society for Epidemiologic Research on behalf of the Diversity and Inclusion
Published: July 2022

Mexico has a population of 129 million and is considered one of the most unequal countries in the world, suffering from widespread health disparities. There is a pressing need to strengthen epidemiologic capacity in Mexico, to help solve the complex health problems the country faces and to reduce health inequities. However, the representation of Mexican epidemiologists in the largest epidemiologic society in North America is low, despite the short distance to the United States. In this commentary, we discuss the barriers to higher representation of Mexican epidemiologists within the Society for Epidemiologic Research (SER), including language barriers, costs, and regional necessities. We also discuss opportunities to expand Mexican SER representation and collaboration. Overall, we hope that this is a call towards expanding SER global participation and starting a conversation on a common agenda for epidemiologic research.
Elevated COVID-19 Case Rates of Government Employees, District of Columbia, 2020–2022
Authors: Hua Xinyi , Yin Jingjing , Fung Isaac C H
Published: July 2022

Objectives

To estimate the rate ratio (RR) of reported Coronavirus Disease 2019 (COVID-19) cases among governmental employees from seven District of Columbia (D.C.) departments from March 2020 to February 2022.

Methods

Poisson regression models were used to estimate the RR by department, using D.C. residents as the reference and the person-day as the offset. The COVID-19 surveillance data and the full-time equivalent hours for each department were obtained from the D.C. governmental websites.

Results

Five of the seven departments had statistically significant higher COVID-19 case rates than D.C. residents. Stratified by four pandemic stages, RR of Fire and Emergency Medical Services (FEMS), Office of Unified Communication (OUC), and Metropolitan Police Department (MPD) were consistently >1: FEMS: 3.34 (95% confidence interval, CI [2.94, 3.77]), 2.39 (95% CI [2.06, 2.75]), 2.48 (95% CI [2.06, 2.95]), and 3.90 (95% CI [3.56, 4.26]), respectively; OUC: 1.47 (95% CI [0.92, 2.18]), 2.72 (95% CI [1.93, 3.69]), 1.85 (95% CI [1.09, 2.92]), and 2.18 (95% CI [1.62, 2.85]), respectively; and MPD: 2.33 (95% CI [2.11, 2.58]), 1.96 (95% CI [1.75, 2.18]), 1.52 (95% CI [1.29, 1.77]), and 1.76 (95% CI [1.60, 1.92]), respectively.

Conclusions

The results suggested higher case rates for emergency responders and frontline personnel than for general population in D.C.
Changes in physiological responses of OsCaM1-1 overexpression in the transgenic rice under dehydration stress
Authors: Sangchai Pun , Buaboocha Teerapong , Sirikantaramas Supaart , Wutipraditkul Nuchanat
Published: July 2022

Calmodulin, a primary calcium sensor in eukaryotes, binds calcium and regulates the activity of effector proteins in response to calcium signals that evoked in response to abiotic and biotic stress. To identify physiological responses associated with improved tolerance under dehydration stress that may be regulated by calmodulin in rice, the transgenic rice overexpressing OsCaM1-1, the control, and the wild-type KDML105 differing in their dehydration tolerance were compared 24 h after exposure to dehydration stress. The results demonstrated a greater increase in relative water content, relative growth rate, abscisic acid, photosynthetic pigment and proline contents, and antioxidant activities in the transgenic rice plants, whereas Na/K and Na/Ca ratio, lipid peroxidation, and electrolytic leakage decreased. The OsCaM1-1 gene overexpression in the transgenic rice showed greater tolerance to dehydration stress than non-transgenic rice, suggesting that OsCaM1-1 might play an important role in mitigating dehydration stress.
A systematic review of analytical methods used in genetic association analysis of the X-chromosome
Authors: Keur Nick , Ricaño-Ponce Isis , Kumar Vinod , Matzaraki Vasiliki
Published: July 2022

Genetic association studies have been very successful at elucidating the genetic background of many complex diseases/traits. However, the X-chromosome is often neglected in these studies because of technical difficulties and the fact that most tools only utilize genetic data from autosomes. In this review, we aim to provide an overview of different practical approaches that are followed to incorporate the X-chromosome in association analysis, such as Genome-Wide Association Studies and Expression Quantitative Trait Loci Analysis. In general, the choice of which test statistics is most appropriate will depend on three main criteria: (1) the underlying X-inactivation model, (2) if Hardy–Weinberg equilibrium holds and sex-specific allele frequencies are expected and (3) whether adjustment for confounding variables is required. All in all, it is recommended that a combination of different association tests should be used for the analysis of X-chromosome.
Prediction of biomarker–disease associations based on graph attention network and text representation
Authors: Yang Minghao , Huang Zhi-An , Gu Wenhao , Han Kun , Pan Wenying , Yang Xiao , Zhu Zexuan
Published: July 2022

Motivation

The associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers.

Results

Here, we present a novel computational model named GTGenie for predicting the biomarker–disease associations based on graph and text features. In GTGenie, a graph attention network is utilized to characterize diverse similarities of biomarkers and diseases from heterogeneous information resources. Meanwhile, a pretrained BERT-based model is applied to learn the text-based representation of biomarker–disease relation from biomedical literature. The captured graph and text features are then integrated in a bimodal fusion network to model the hybrid entity representation. Finally, inductive matrix completion is adopted to infer the missing entries for reconstructing relation matrix, with which the unknown biomarker–disease associations are predicted. Experimental results on HMDD, HMDAD and LncRNADisease data sets showed that GTGenie can obtain competitive prediction performance with other state-of-the-art methods.

Availability

The source code of GTGenie and the test data are available at: https://github.com/Wolverinerine/GTGenie.
CoGO: a contrastive learning framework to predict disease similarity based on gene network and ontology structure
Authors: Chen Yuhao , Hu Yanshi , Hu Xiaotian , Feng Cong , Chen Ming
Published: July 2022

Motivation

Quantifying the similarity of human diseases provides guiding insights to the discovery of micro-scope mechanisms from a macro scale. Previous work demonstrated that better performance can be gained by integrating multiview data sources or applying machine learning techniques. However, designing an efficient framework to extract and incorporate information from different biological data using deep learning models remains unexplored.

Results

We present CoGO, a Contrastive learning framework to predict disease similarity based on Gene network and Ontology structure, which incorporates the gene interaction network and gene ontology (GO) domain knowledge using graph deep learning models. First, graph deep learning models are applied to encode the features of genes and GO terms from separate graph structure data. Next, gene and GO features are projected to a common embedding space via a nonlinear projection. Then cross-view contrastive loss is applied to maximize the agreement of corresponding gene-GO associations and lead to meaningful gene representation. Finally, CoGO infers the similarity between diseases by the cosine similarity of disease representation vectors derived from related gene embedding. In our experiments, CoGO outperforms the most competitive baseline method on both AUROC and AUPRC, especially improves 19.57% in AUPRC (0.7733). The prediction results are significantly comparable with other disease similarity studies and thus highly credible. Furthermore, we conduct a detailed case study of top similar disease pairs which is demonstrated by other studies. Empirical results show that CoGO achieves powerful performance in disease similarity problem.

Availability and implementation

https://github.com/yhchen1123/CoGO.