bluuebunny/crossref_metadata_2025 huggingface dataset:
Importance of internal stress control in organic/metal-oxide hybrid devices
Authors: Suemori Kouji , Ibaraki Nobuki , Kamata Toshihide
Published: July 2021

Incorporation of functional metal oxides in organic devices enables the creation of electronic devices that have both the advantages of organic materials, such as flexibility and light weight, as well as those of metal oxide materials, such as optical transparency and stability against ambient air. However, developing high-performance organic/metal-oxide hybrid devices is challenging, because the deposition of a metal oxide onto an organic semiconductor layer severely damages the device for reasons that are not well understood. In this study, we clarified that the internal stress of the metal oxide is the cause of this damage. A hybrid device composed of an organic semiconductor layer sandwiched between two indium tin oxide electrodes was investigated as a typical organic/metal-oxide hybrid device. The internal stress in the metal oxide layer causes the formation of nanometer-order clearances at the weak bonding interface in the device; this damage reduces the electrical conductivity of the device by over two orders of magnitude. A method to control the internal stress of the metal oxide layer by introducing a gas that affects crystal growth during metal oxide deposition was developed, and an undamaged hybrid device was demonstrated by controlling the internal stress of the metal oxide. High-performance organic/metal-oxide hybrid devices without the damage may be key devices that open up electronics with features beyond those possible with the organic electronics and metal oxide electronics.
Enhanced screening on remote phonon scattering in InGaZnO thin-film transistor by using Ge gate electrode
Authors: Su Hui , Tang Wing Man , Lai Pui To
Published: July 2021

Room-temperature-processed amorphous InGaZnO thin-film transistors (TFTs) with three different semiconductors (Si, GaAs, and Ge) of various doping concentrations as gate electrodes are fabricated. Like the conventional Si gate devices, both their GaAs and Ge counterparts show carrier mobility increasing with increasing gate doping concentration, further supporting that the holes at/near the surface of a p-type gate electrode can have a screening effect on the remote phonon scattering caused by the surface phonons of their high-k gate dielectrics. Moreover, for the same gate doping concentration, the Ge gate device has a carrier mobility about three times that of its conventional Si gate counterpart. This implies that lower-mass charge carriers in the gate electrode could have a stronger screening effect on remote phonon scattering. As a result, even with a moderate gate doping concentration of 1.0 × 1018 cm−3, the room-temperature-processed Ge gate device shows a high carrier mobility of 60.8 cm2/V s. The enhanced screening effect of the Ge gate electrode should be due to its higher-energy plasmons, which could couple more strongly with the phonons of the gate dielectric to result in weaker gate-dielectric vibration.
Gyrokinetic investigation of the nonlinear interaction of Alfvén instabilities and energetic particle-driven geodesic acoustic modes
Authors: Vannini F. , Biancalani A. , Bottino A. , Hayward-Schneider T. , Lauber Ph. , Mishchenko A. , Poli E. , Vlad G. ,   ASDEX Upgrade Team
Published: July 2021

This paper presents a study of the interaction between Alfvén modes and zonal structures, considering a realistic ASDEX Upgrade equilibrium. The results of gyrokinetic simulations with the global, electromagnetic, particle-in-cell code ORB5 are presented, where the modes are driven unstable by energetic particles with a bump-on-tail equilibrium distribution function, with radial density gradient. Two regimes have been observed. At low energetic particle concentration, the zonal structure (identified as an energetic particle-driven geodesic acoustic mode) is more unstable than the Alfvén mode. In the regime at high energetic particle concentration, the Alfvén mode is more unstable than the zonal structure. The interplay between the modes leads to a modification of their growth rates as well as to a modification of their saturation levels. The theoretical explanation of the mode interaction is given in terms of three-wave coupling of the energetic particle-driven geodesic acoustic mode and Alfvén mode, mediated by the curvature–pressure coupling term of the energetic particles.
Mechanical properties of layered tilkerodeite (Pd2HgSe3) and jacutingaite (Pt2HgSe3) crystals: Insights on the interlayer, intralayer interactions, and phonons
Authors: Longuinhos Monteiro Lobato Raphael , Ribeiro-Soares Jenaina
Published: July 2021

Tilkerodeite and jacutingaite are layered minerals promising for low-power nano-spintronic devices due to their robust topological phases and air stability. Their intralayer and interlayer mechanical properties, of paramount importance for real applications, are here unveiled by first-principles calculations. Their stiffness coefficients, which confirm their lattice stability, and interlayer force constants show that tilkerodeite is weaker against intralayer deformations, slightly difficult to exfoliate, and less lubricant than jacutingaite. Jacutingaite aggregates are more stiff, incompressible, and resistant to shape-change deformations than tilkerodeite, while the latter is more ductile than the former. The wavenumber shifts between corresponding vibration modes in these materials show that tilkerodeite is less stiff than jacutingaite against the atomic displacement of optical silent, infrared- and Raman-active modes, while the opposite was found for their low-frequency breathing and shear rigid-layer modes. Our findings advance the knowledge on the structural properties of new quantum spin Hall materials, key for their use, and explained the unexpected wavenumber redshift of the tilkerodeite Raman spectrum relative to that of jacutingaite observed in experiments.
Self-assembly of binary solutions to complex structures
Authors: Scacchi Alberto , Sammalkorpi Maria , Ala-Nissila Tapio
Published: July 2021

Self-assembly in natural and synthetic molecular systems can create complex aggregates or materials whose properties and functionalities rise from their internal structure and molecular arrangement. The key microscopic features that control such assemblies remain poorly understood, nevertheless. Using classical density functional theory, we demonstrate how the intrinsic length scales and their interplay in terms of interspecies molecular interactions can be used to tune soft matter self-assembly. We apply our strategy to two different soft binary mixtures to create guidelines for tuning intermolecular interactions that lead to transitions from a fully miscible, liquid-like uniform state to formation of simple and core–shell aggregates and mixed aggregate structures. Furthermore, we demonstrate how the interspecies interactions and system composition can be used to control concentration gradients of component species within these assemblies. The insight generated by this work contributes toward understanding and controlling soft multi-component self-assembly systems. Additionally, our results aid in understanding complex biological assemblies and their function and provide tools to engineer molecular interactions in order to control polymeric and protein-based materials, pharmaceutical formulations, and nanoparticle assemblies.
Surface acoustic wave-assisted spin–orbit torque switching of the Pt/Co/Ta heterostructure
Authors: Cao Y. , Bian X. N. , Yan Z. , Xi L. , Lei N. , Qiao L. , Si M. S. , Cao J. W. , Yang D. Z. , Xue D. S.
Published: July 2021

Current-induced spin–orbit torque (SOT) allows for highly efficient control of magnetization for the magnetic memory and the logic application, but its high critical current density Jc limits its applications. Here, we report that the surface acoustic wave (SAW) presents a promising approach for reducing Jc in Pt/Co/Ta heterostructures with perpendicular anisotropy. By the second harmonic Hall measurements, we find that the damping-like SOT effective field is almost the same with or without SAW, implying that the reduction of Jc does not originate from the enhancement of the SOT. However, the current-induced domain wall velocity v under SAW is greatly enhanced. By fitting with the creep law under SAW, we find that lnv is linear with SAW power (P), which reveals that the effective pinning barrier is reduced linearly with increasing P. This feature can be well described by the time average of the periodically accumulated nucleation probability under SAW. The results shed light on the application of SAW-assisted SOT devices for low consumption storage.
The interference properties of single-photon vortex beams in Mach–Zehnder interferometer
Authors: Guo Xue , Meng Zhe , Li Jian , Yang Jia-Zhi , Aili Mairikena , Zhang An-Ning
Published: July 2021

Orbital angular momentum (OAM) is a unique degree of freedom for vortex beams. It is very important to study the interference of vortex beams carrying OAM in quantum information science. In this paper, we study the interference phenomenon of vortex beams based on a stable and adjustable Mach–Zehnder (MZ) interferometer using a laser and a single-photon as light sources. Furthermore, we also show the evolution of the different initial states in the MZ interferometer, and the interferograms of initial states vary with changing the interferometer phase. Our research not only helps us to understand the special phenomenon of OAM in the MZ interferometer but also provides some theoretical and experimental support for OAM as a quantum information carrier.
Binding curve of the beryllium dimer using similarity-transformed FCIQMC: Spectroscopic accuracy with triple-zeta basis sets
Authors: Guther Kai , Cohen Aron J. , Luo Hongjun , Alavi Ali
Published: July 2021

We demonstrate how similarity-transformed full configuration interaction quantum Monte Carlo (FCIQMC) based on the transcorrelated Hamiltonian can be applied to make highly accurate predictions for the binding curve of the beryllium dimer, marking the first case study of a molecular system with this method. In this context, the non-Hermitian transcorrelated Hamiltonian, resulting from a similarity transformation with a Jastrow factor, serves the purpose to effectively address dynamic correlation beyond the used basis set and thus allows for obtaining energies close to the complete basis set limit from FCIQMC already with moderate basis sets and computational effort. Building on results from other explicitly correlated methods, we discuss the role of the Jastrow factor and its functional form, as well as potential sources for size consistency errors, and arrive at Jastrow forms that allow for high accuracy calculations of the vibrational spectrum of the beryllium dimer.
Electromagnetic induction imaging with a scanning radio frequency atomic magnetometer
Authors: Deans Cameron , Cohen Yuval , Yao Han , Maddox Benjamin , Vigilante Antonio , Renzoni Ferruccio
Published: July 2021

We demonstrate electromagnetic induction imaging with an unshielded, portable radio frequency atomic magnetometer scanning over the target object. This configuration satisfies standard requirements in typical applications, from security screening to medical imaging. The ability to scan the magnetometer over the object relies on the miniaturization of the sensor head, the active compensation of the ambient magnetic field, and the implementation of a dedicated procedure to extract high-quality images from the recorded spatial dependent magnetic resonance. The procedure is shown to be effective in suppressing the detrimental effects of the spatial variation of the magnetic environment.
Conjugated nitroxides
Authors: Tretyakov E. V. , Ovcharenko V. I. , Terent'ev A. O. , Krylov I. B. , Magdesieva T. V. , Mazhukin D. G. , Gritsan N. P.
Published: July 2021

In recent years, research dealing with organic paramagnetic compounds such as stable radicals and high-spin systems has been focused on applied aspects. Several key trends have formed in the application and, hence, in the function-oriented synthesis of organic radicals and polyradicals. This review addresses one of such trends in which the dominant role is played by so-called conjugated nitroxides. Their specific feature is the presence of any unsaturated moiety (C=C, C=N or C=O multiple bond; aromatic or heteroaromatic ring; fused polyaromatic system) adjacent to the nitroxide group. The achievements of the chemistry of conjugated nitroxides are presented, and their physicochemical properties, magneto-structural correlations and practical applications are discussed.
 The bibliography includes 641 references.
Micro- and mesoporous metal-organic frameworks for hydrocarbon separation
Authors: Kovalenko K. A. , Potapov A. S. , Fedin V. P.
Published: July 2021

The review presents data on the use of porous metal-organic frameworks for the separation of some industrially important hydrocarbon mixtures, such as ethane and ethylene, propane and propylene, benzene and cyclohexane, and xylene isomers. It is shown that enhancing the efficiency of materials based on porous metal-organic frameworks relies on understanding the nature of adsorption sites in their structures, the specifics of interactions between the framework and a particular substrate, and the structural response of the framework (host) as it is filled with guest molecules. The achievements of fundamental studies and unresolved problems related to the use of porous metal-organic frameworks in industrial hydrocarbon separation processes are critically analyzed.
 The bibliography includes 183 references.
Fuel burning efficiency under various fire severities of a boreal forest landscape in north-east China
Authors: Ping Xiaoying , Chang Yu , Liu Miao , Hu Yuanman , Yuan Zhelong , Shi Sixue , Jia Yuchen , Li Dikang , Yu Lili
Published: July 2021

Forest fires are important natural disturbances that influence accurate estimations of forest carbon budgets, largely owing to the uncertainty of carbon emissions from forest fires. Fuel burning efficiency is an important factor affecting accurate estimations of carbon emissions and is difficult to quantify. Here, we quantified burning efficiencies of fuel strata by fire severity and forest types and investigated influencing factors. Burning efficiencies of fuel strata increased with increasing fire severity. The tree stratum had low values of burning efficiency of 0.76, 0.83, 6.84% under low-, moderate-, high-severity fires respectively. The burning efficiency of the herb stratum was the highest, over 95%, followed by the litter stratum between 49 and 85%. Although the tree stratum accounted for the largest carbon storage of aboveground fuels, most carbon consumed during fires came from the shrub and herb strata. Among forest types, the burning efficiency of aboveground fuels in Pinus pumila–Larix gmelinii forest was much higher than the other two studied. Fire Weather Index (FWI) and temperature exerted a positive effect on the burning efficiency of understorey fuels. Precipitation mainly had a negative influence on the burning efficiency of shrub and duff.
Global climate disruption and regional climate shelters after the Toba supereruption
Authors: Black Benjamin A. , Lamarque Jean-François , Marsh Daniel R. , Schmidt Anja , Bardeen Charles G.
Published: July 2021

Significance

The Younger Toba Tuff is the largest volcanic eruption of the past 2 million years, but its climatic consequences have been strongly debated. Resolving this debate is important for understanding environmental changes during a key interval in human evolution. This work uses a large ensemble of global climate model simulations to demonstrate that the climate response to Toba was likely to be pronounced in Europe, North America, and central Asia but muted in the Southern Hemisphere. Our results reconcile the simulated distribution of climate impacts from the eruption with paleoclimate and archaeological records. This probabilistic view of climate disruption from Earth’s most recent supereruption underscores the uneven expected distribution of societal and environmental impacts from future very large explosive eruptions.
Shifting gradients of macroscale cortical organization mark the transition from childhood to adolescence
Authors: Dong Hao-Ming , Margulies Daniel S. , Zuo Xi-Nian , Holmes Avram J.
Published: July 2021

Significance

Here, we describe age-dependent shifts in the macroscale organization of cortex in childhood and adolescence. The characterization of functional connectivity patterns in children revealed an overarching organizational framework anchored within the unimodal cortex, between somatosensory/motor and visual regions. Conversely, in adolescents, we observed a transition into an adult-like gradient, situating the default network at the opposite end of a spectrum from primary somatosensory/motor regions. This spatial framework emerged gradually with age, reaching a sharp inflection point at the transition from childhood to adolescence. These data reveal a developmental change from a functional motif first dominated by the distinction between sensory and motor systems and then balanced through interactions with later-maturing aspects of association cortex that support more abstract cognitive functions.
Integrated assessment modeling reveals near-channel management as cost-effective to improve water quality in agricultural watersheds
Authors: Hansen Amy T. , Campbell Todd , Cho Se Jong , Czuba Jonathan A. , Dalzell Brent J. , Dolph Christine L. , Hawthorne Peter L. , Rabotyagov Sergey , Lang Zhengxin , Kumarasamy Karthik , Belmont Patrick , Finlay Jacques C. , Foufoula-Georgiou Efi , Gran Karen B. , Kling Catherine L. , Wilcock Peter
Published: July 2021

Significance

Water quality is severely degraded in landscapes cultivated for intensive corn and soybean production. Current water quality policy focuses on reducing nutrient and sediment losses from agricultural fields, yet recent studies have highlighted important roles of near-channel areas as sources of sediment and sinks for nitrogen. We developed an integrated modeling approach to assess water quality cost-effectiveness tradeoffs for watershed management scenarios that include a wide range of both field and near-channel management actions, yielding estimates of reductions in sediment and nitrate loads and associated costs for alternative management actions. Our results indicate that near-channel management, most notably fluvial wetland restoration, was most effective for achieving long-standing policy goals for sediment and nitrate reduction.
DNAse-dependent, NET-independent pathway of thrombus formation in vivo
Authors: Carminita Estelle , Crescence Lydie , Brouilly Nicolas , Altié Alexandre , Panicot-Dubois Laurence , Dubois Christophe
Published: July 2021

Significance

Thrombosis constitutes a major contributor to the global disease burden. Recently, the contribution of neutrophils and neutrophil extracellular traps in thrombosis has been intensively documented. DNAse-I by its ability to cleave DNA has been proposed as an efficient antithrombotic drug. In this paper, we showed that DNase-I inhibits the formation of a platelet thrombus and the generation of fibrin independent of its enzymatic activity on DNA. We proposed that DNase-I hydrolyzes adenosine triphosphate and adenosine diphosphate (two important platelet and neutrophil agonists) into adenosine, an antagonist of platelet and neutrophil.
A self-powered implantable and bioresorbable electrostimulation device for biofeedback bone fracture healing
Authors: Yao Guang , Kang Lei , Li Cuicui , Chen Sihong , Wang Qian , Yang Junzhe , Long Yin , Li Jun , Zhao Kangning , Xu Weina , Cai Weibo , Lin Yuan , Wang Xudong
Published: July 2021

Significance

Bone fracture represents a significant problem in public health. State-of-the-art clinical study demonstrated that by correlating the stimulation amplitude and frequency directly to dynamic locomotion, biofeedback electrostimulation therapy is particularly effective compared to conventional continuous electrostimulation for postoperative therapy and rehabilitation after musculoskeletal injury. However, implementation of biofeedback still relies on complex electronics and sensing systems, which largely limits its accessibility to patients. Here we developed a self-powered implantable and bioresorbable device that directly applies biofeedback electrostimulations to the treatment of bone fracture. The electrostimulation signals are generated solely from relevant body motions, providing a closed-loop biofeedback therapy bringing rapid healing to fractures. This device is self-responsive, battery free, and requires no surgical removal after fulfilling the biomedical intervention.
Sex-specific ornament evolution is a consistent feature of climatic adaptation across space and time in dragonflies
Authors: Moore Michael P. , Hersch Kaitlyn , Sricharoen Chanont , Lee Sarah , Reice Caitlin , Rice Paul , Kronick Sophie , Medley Kim A. , Fowler-Finn Kasey D.
Published: July 2021

Significance

One of biology’s most pressing goals is to understand how organisms adapt to their climates. Researchers have greatly clarified the ways that organisms evolve to improve their survival in warmer climates, yet a major gap in our knowledge remains. Despite >95% of eukaryotic organisms engaging in sexual reproduction, little is known about whether or not climatic adaptation entails optimizing the traits that organisms use to coordinate mating and reproduction. Here, we show that mating-related traits in male but not female dragonflies evolve in a highly predictable way as they adapt to climatic conditions. Failing to account for adaptive evolution of mating-related traits may therefore limit our ability to forecast how organisms will respond to climate change.
Bidirectional flow of the funny current (I
f
) during the pacemaking cycle in murine sinoatrial node myocytes
Authors: Peters Colin H. , Liu Pin W. , Morotti Stefano , Gantz Stephanie C. , Grandi Eleonora , Bean Bruce P. , Proenza Catherine
Published: July 2021

Significance

The funny current (I
f
) is critical for spontaneous activity in cardiac pacemaker cells; however, its precise role remains enigmatic because it activates mostly outside the physiological voltage range and its kinetics are slow relative to the cardiac cycle. I
f
is typically considered as an inward current; however, we show that I
f
is persistently active in pacemaker cells. Once opened, the small fraction of ion channels that conduct I
f
do not reclose. Consequently, I
f
flows both inward and outward and, paradoxically, conducts a large fraction of the net charge movement. These results establish a new conceptual framework for pacemaking in which voltage-dependent gating of I
f
is minimal and I
f
contributes to spontaneous pacemaker activity by providing driving force in both directions.
Entropic barrier of topologically immobilized DNA in hydrogels
Authors: Chen Kuo , Muthukumar Murugappan
Published: July 2021

Significance

Movement of charged macromolecules in crowded aqueous environments is ubiquitous in nature. The omnipresent capacity of macromolecules to adopt differing numbers of conformations in response to local spatiotemporal environments results in their trajectories consisting of conformational entropic barriers. The conformational fluctuations can be so large that even Einstein’s law of diffusion can apparently break down. By directly observing single DNA molecules under such conditions, we show the emergence of a nondiffusive topologically frustrated dynamical state, and measure single-molecule entropic barriers responsible for the resultant extreme metastability. The presented theory–experiment combination offers a general method to measure free energy landscapes required to deliberately navigate single macromolecules through congested aqueous media.
Thousands of induced germline mutations affecting immune cells identified by automated meiotic mapping coupled with machine learning
Authors: Xu Darui , Lyon Stephen , Bu Chun Hui , Hildebrand Sara , Choi Jin Huk , Zhong Xue , Liu Aijie , Turer Emre E. , Zhang Zhao , Russell Jamie , Ludwig Sara , Mahrt Elena , Nair-Gill Evan , Shi Hexin , Wang Ying , Zhang Duanwu , Yue Tao , Wang Kuan-wen , SoRelle Jeffrey A. , Su Lijing , Misawa Takuma , McAlpine William , Sun Lei , Wang Jianhui , Zhan Xiaoming , Choi Mihwa , Farokhnia Roxana , Sakla Andrew , Schneider Sara , Coco Hannah , Coolbaugh Gabrielle , Hayse Braden , Mazal Sara , Medler Dawson , Nguyen Brandon , Rodriguez Edward , Wadley Andrew , Tang Miao , Li Xiaohong , Anderton Priscilla , Keller Katie , Press Amanda , Scott Lindsay , Quan Jiexia , Cooper Sydney , Collie Tiffany , Qin Baifang , Cardin Jennifer , Simpson Rochelle , Tadesse Meron , Sun Qihua , Wise Carol A. , Rios Jonathan J. , Moresco Eva Marie Y. , Beutler Bruce
Published: July 2021

Significance

We developed software called Candidate Explorer (CE) that uses a machine-learning algorithm to identify chemically induced mutations that are causative of screened phenotypes. CE determines the probability that a mutation will be verified as causative for a phenotype if the gene is independently targeted for knockout or recreation of the mutation. CE uses 67 parameters from the mapping data—including gene, mutation, genotype, allelism, and phenotype information—to determine the CE Score and verification probability. We used CE to evaluate ∼87,000 mutation/phenotype associations identified by flow cytometry screening of circulating immune cells from mutagenized mice: 1,279 genes representing 2,336 mutations were rated good or excellent candidates for causation of phenotypes. Many of these genes were not previously implicated in immunity.
Tangential cone condition and Lipschitz stability for the full waveform forward operator in the acoustic regime
Authors: Eller Matthias , Rieder Andreas
Published: July 2021

Time-domain full waveform inversion (FWI) in the acoustic regime comprises a parameter identification problem for the acoustic wave equation: pressure waves are initiated by sources, get scattered by the earth’s inner structure, and their reflected parts are picked up by receivers located on the surface. From these reflected wave fields the two parameters, density and sound speed, have to be reconstructed. Mathematically, FWI reduces to the solution of a nonlinear and ill-posed operator equation involving the parameter-to-solution map of the wave equation. Newton-like iterative regularization schemes are well suited and well analyzed to tackle this inverse problem. Their convergence results are often based on an assumption about the nonlinear map known as tangential cone condition. In this paper we verify this assumption for a semi-discrete version of FWI where the searched-for parameters are restricted to a finite dimensional space. As a byproduct we establish that the semi-discrete seismic inverse problem is locally Lipschitz stable, in particular, it is conditionally well-posed.
The Berry phase rectification tensor and the solar rectification vector
Authors: Matsyshyn Oles , Dey Urmimala , Sodemann Inti , Sun Yan
Published: July 2021

We introduce an operational definition of the Berry Phase Rectification Tensor as the second order change of polarization of a material in response to an ideal short pulse of electric field. Under time reversal symmetry this tensor depends exclusively on the Berry phases of the Bloch bands and not on their energy dispersions, making it an intrinsic property to each material which contains contributions from both the inter-band shift currents and the intra-band Berry Curvature Dipole. We also introduce the Solar Rectification Vector as a technologically relevant figure of merit for bulk photo-current generation which counts the number of electrons contributing to the rectified current per incoming photon under ideal black-body radiation in analogy with the classic solar cell model of Shockley and Queisser. We perform first principle calculations of the Berry Phase Rectification Tensor and the Solar Rectification Vector for the Weyl semi-metal TaAs and the insulator LiAsSe2 which features large shift currents close to the peak of solar radiation intensity. We also generalize the formula for the Glass coefficient to include the spectral distribution of the incoming radiation, the directionality dependence of the conductivity of the material and the reflectivity at its surface.
Fatigue life prediction of the additively manufactured specimen
Authors: Paul Surajit Kumar , Tarlochan Faris , Hilditch Timothy
Published: July 2021

Additively manufactured specimens generally exhibit comparable or improved tensile properties, such as yield stress, ultimate tensile strength, and uniform elongation, compared to conventionally manufactured specimens. However, the defects that are typically present in additively manufactured microstructures result in inferior fatigue performance. A representative volume element-based modeling technique incorporating these defects has been used to predict the reduction in endurance limit of an additively manufactured stainless steel compared to the conventionally manufactured material. This physics-based model can clearly demonstrate the poor fatigue performance of additively manufactured specimens based on the micro-plasticity generated by the defects in the microstructure under cyclic loading. A Neuber analytical model has also been applied to predict the fatigue life of additively manufactured materials for a given stress amplitude. Both the prediction from the finite element model and the analytical Neuber model are very close to the experimental endurance limit.
Structural superlubricity in 2D van der Waals heterojunctions
Authors: Yuan Jiahao , Yang Rong , Zhang Guangyu
Published: July 2021

Structural superlubricity is a fundamentally important research topic in the area of tribology. Van der Waals heterojunctions of 2D materials are an ideal system for achieving structural superlubricity and possessing potentially a wide range of applications in the future due to their ultra-flat and incommensurate crystal interfaces. Here we briefly introduce the origin and mechanism of structural superlubricity and summarize the representative experimental results, in which the coefficient of friction has achieved the order of 10−5. Furthermore, we analyze the factors affecting structural superlubricity of 2D materials, including dynamic reconstruction of interfaces, edge effects, interfacial adsorption, etc, and give a perspective on how to realize the macroscopic expansion and where it can be applied in practice.
Use of Gamification in Indonesian for Non-Native Speakers (BIPA)
Authors: Arie Sandy Teguh , Ulfa Saida , Wedi Agus
Published: July 2021

The purpose of this study was to discuss the use of gamification to students of the BIPA program at State University of Malang. The platform used a mobile application that contains elements of gamification which includes challenges, missions, badges, leaderboard and multiplayer. The results showed that the learning motivation and interest of BIPA program students were very high when they were using gamification in the classroom. This study uses a quantitative approach because information will be presented in numerical form and analyzed using statistics. To find a mobile platform that is suitable for use in gamification, a literature study is conducted to choose a mobile platform that has gamification mechanics including challenges, missions, badges, leaderboard and multiplayer. The population in the study were all BIPA program students at State University of Malang. The sampling technique used purposive sampling method with a sample of 18 people. The gamification in the BIPA program uses BIPAJAR application that has adopted gamification mechanics namely challenges, missions, badges, leaderboard and multiplayer. BIPA students were given 3 days to try BIPAJAR application. The Minimum Standards for Completion Criteria (KKM) is 70. The results of the questionnaires distributed to the students concluded that students’ interest and motivation in using gamification were quite high with a score of 78.67% and student learning progress grew by 82.35%.
Augmented Reality (AR) Press Machine as the application of the latest learning media technology in the XXI Century
Authors: Bagus Nur Rahma Putra Andika , Mukhadis Amat , Ulfatin Nurul , Anwar Syafrudie Haris , Mursyidun Nidhom Ahmad , Ahmad Smaragdina Azhar , Asari Andi , Dzakiya Nurul , Hasbi Ramadani Ali , Bin Md Yunos Jailani , Irfano Sembiring Andrew
Published: July 2021

The objectives of this study are: (1) creating an augmented reality (AR) application in the form of a press machine; (2) testing the attractiveness of the technology developed; and (3) testing the effectiveness of AR technology in the form of press machines. The method used is research and development (R&D). The final stage of product development is to carry out quasi-experiments. The phase is focused on all vocational students at Malang State University. The findings in this study include: (1) AR-shaped press machine that was developed proved to have a high level of design attractiveness and material; (2) AR shaped press machine that was developed proved effective in increasing student’s basic understanding of the competence in understanding the function of press machine components; and (3) all results in this study are expected to be the main reference in the development of AR technology for learning.
Depression Detection Using Comparative Analysis of QRS Detection Algorithms and HRV Of ECG Signal Implemented on MATLAB and Verilog
Authors: Mariya L Prasanna , Kumareshan N
Published: July 2021

Nowadays depression is a major health issue with critical psychological wellness, that influencing the world lives. It impacts emotionally as well as physical and physiological individuals Condition. It can also lead to suicide. Ongoing studies say 43% Indians experience depression. Depression can detect using HRV ECG signal, before getting into Severe depression because, HRV has been associated with depression. The QRS detection algorithm is utilized for calculating heart rate. In this project, comparative analysis of QRS detection algorithms is executed in MATLAB and performance compared for analyzing HRV of various MIT-BIH ECG information base acquired from physio.net The QRS detection algorithm technique has been decided for R peak detection and heart rate calculation, proposes a simple method and it doesn’t include complex numerical model. The detection design plans in Verilog to figure heart pulse. Thus, the designed code for analyzing QRS detection algorithms and HRV ECG signal simulated in MATLAB as well as on XILINXS ISE 14.7.
79GHz Substrate Integrated Waveguide antenna for short-range radar applications
Authors: Santhakumar G , Vadivelu R , Revathy Lakshmi M , Saranya G J , Subasini R
Published: July 2021

It is evident that radar sensing is robust technology compared to camera or LiDAR in the case of autonomous vehicles. Since, they are capable of working even under harsh weather conditions like thick fog, glaring sun, etc. The 77-81GHz frequency band for short range radar provides a global framework for automotive radar by preventing collisions, reducing traffic accidents and thus improvingvehicular safety. The proposed antenna resonates at 79GHz. Below-10dB, return loss characteristic greater than -35dB is obtained in the band of 77.5GHz to 80.4GHz (i.e., impedance bandwidth of 2.86GHz) and gain of above 8dB is achieved. Rectangular vias and complementary concentric square loops of the metamaterial structure are introduced to suppress the surface waves and to achieve the desired frequency of resonance. The feed line and the metamaterial structure are positionedaccordinglyto provide a better impedance matching. VSWR obtained is 1.04 and the antenna is linearly polarized and has a low profile. The total dimension of the antenna is 1.96×2.26×0.127mm3. The antenna structure can be used in an array for automotive radar applications.
Sustainable Intelligent Prediction and Price Recommendation System
Authors: Poorani G , Rishwan S Mohammed , Kumar R Pavan , Ragul M
Published: July 2021

Online brief time frame period condominium stages, comprising of Airbnb, had been transforming into mainstream, and a higher evaluating technique is indispensable for hosts of most recent postings. In this paper, the association is broken down among the portrayal of each rundown and its charge, and proposed a content essentially based absolutely charge counsel gadget alluded to as TAPE to suggest a moderate charge for recently brought postings. The deep knowledge utilized makes them more familiar with strategies (for example, feed-forward networks, longer short-term memory, and recommended moves) to design and put in an influential TAPE. By using a data set of 4 indistinguishable urban areas that were deleted sequentially, it was found that basic elements (such as small indoor objects and high-thickness areas) would undoubtedly have an adverse effect on the charges of each property, and evaluated that it is basic and more attractive style of. Our style is completed with 33.73 in Boston, 20.50 in London, 34.68 in Los Angeles and 26.31 in New York. This is related to the use of other current forms of highlighting.
An efficient machine learning approach for activity recognition
Authors: Jashwant K , Jasvant R , Devi S Siamala
Published: July 2021

The population of older people in western nations are growing drastically. Independent lifestyle is their preference and this leads to fall instances often. Falls of this kind results in severe health issues or sometimes causes deadly damages to the elderly people. Considering this problem, it is highly important to come up with fall discovery systems. A machine learning framework has been proposed in this regard which covers both fall discovery and day to day movement recognition. Utilizing acceleration and speed inputs from dual unrestricted repositories are highly helpful in diagnosing to the maximum of seven movements. Acceleration and angular velocity parameters can be used to extract the attributes that are relevant to time and frequency domain. These attributes are then offered to a classification algorithm. An attempt has been made to check the outcomes of four different procedures for categorizing manual movements. The above-mentioned procedures are the Artificial Neural Network (ANN), K-Nearest Neighbours (KNN), Quadratic Support Vector Machine (QSVM), and FP growth. Power spectral density of the acceleration is used to maximize the outcomes of the classifier. Acceleration data alone is considered for activity discovery in the initial step. Experimental results show that the KNN, ANN, QSVM, and FP growth procedures can attain correctness of 81.2%, 87.8%, 93.2%, and 94.1%. The accuracy of fall detection touches 97.2% and 99.1% with no false positive values for the QSVM and FP growth procedures. As a next phase, the attributes can be taken autocorrelation function and the power spectral density of the acceleration and the angular velocity data that obviously maximizes the classification correctness. Projected attributes are adopted to achieve notable improvement in accuracy of 85.8%, 91.8%, 96.1%, and 97.7% for the KNN, ANN, QSVM, and FP growth algorithm. The accurateness of fall discovery touches 100% for both the QSVM and FP growth procedures in the absence of any incorrect alarm, which is the finest attainable performance.
Analysis of air quality using IoT with machine learning prediction
Authors: Shanmugaraja T , Sakthivel M , Shaila Shree R , Sooraj P , Vishnu K
Published: July 2021

The Think speak technology is a dynamic field that seeks to engage ‘matters,’ human beings, and machines as whole and, making them a necessary part of the world wide web. The complete society is shifting toward industrialization and computerization, which may result in substantial environmental pollution. Deciding the air best is a top need of great importance. This paper offers the improvement of contamination global positioning frameworks with the organization of astute sensors. Checking the gas spillage stage from any piece of the globe can be finished by methods for a combination of enormous records to the Google Cloud through the networkers. Examination of the realities is improved accordingly permitting simplicity of following. Alarms might be caused if there should arise an occurrence of uncommon decay of air decent. The proposed approach discovers application in industry and also in the checking of brought about by like a fan, engines. This strategy utilizing the proposed framework is data set transferred to at long last pc and AI.
Brain Tumor Classification Using Convolution Neural Network
Authors: Saranya N , Karthika Renuka D , kanthan J Nikkesh
Published: July 2021

Brain tumour is a very serious brain cancer. It is present or become due to the separation of the brain cells. In the recent field of this study, tells us that deep learning will help in health industry of medical diseases imaging in the Medical Diagnostic of all the diseases. CNN is mostly used in this Machine learning algorithm. Likewise, in this paper also, we bring out the Convolution Neural Network algorithm, image processing and data augmentation to say the brain images are cancerous and which are not cancerous. This project will require less computational power due to the transfer learning compared to the old CNN model. This has good accuracy results than the old pre-trained models.
Prediction of potential intrusion areas of Ambrosia L. plant in Jilin Province
Authors: Lan Xuehan , Fu Cong , Li Chenghong , Wang Meifang , Cheng Chenguang , Sun Hua , Du Fengguo
Published: July 2021

Ambrosia L. plant refers to one of the critical alien invasive species in Jilin Province, which can significantly jeopardize the environment. In this study, the MaxEnt model and the ArcGIS were combined to predict the potential intrusion areas of Ambrosia plant in Jilin Province. Subsequently, the dominant environmental factors affecting the geographical distribution of Ambrosia plant we’re determined. Next, the geographical distributions and ecological niche overlap degrees of two species of Ambrosia plant were analyzed. As revealed from the results, the total areas of Ambrosia artemisiifolia L. and Ambrosia trifida L. in potential high and middle suitable distribution areas of Jilin Province reached 11988.71km2 and 48039.68 km2, respectively. According to results, the environmental factors primarily affecting the distributions of Ambrosia artemisiifolia L. and Ambrosia trifida L. consisted of solar radiation (sard9) and annual mean temperature range (bio7) in September, as well as solar radiation (sard9) and isothermality in September (bio). Ambrosia plant was suggested to exhibit a high degree of ecological niche overlap and a large geographical distribution overlap. For the mentioned reason, this study laid a scientific basis for monitoring and controlling the spread of alien invasive species of Ambrosia plant in Jilin Province.
The Electromagnetic Signal Track Correlation Algorithm based on Attribute Clustering and Space-time Constraints
Authors: Wu Bo , Wang Jianan , Wang Zhaojun , Yu Jiecheng , Gao Yue , Li Peiyun
Published: July 2021

In view of the problem that start-end correlation of ship electromagnetic signal, the electromagnetic signal track correlation algorithm, based on attribute clustering and space-time constraints, is proposed. The algorithm consists of K-means dynamic clustering stage, space-time constraints of the track association stage. By extracting the relevant properties of electromagnetic signals, through the clustering stage, obtaining an indefinite number of clusters, and through the space-time correlation stage, obtaining a number of tracks per cluster. The main contributions of this paper are: 1. the K-means dynamic clustering method is proposed; 2. the track correlation method of space-time constraints is proposed. In this paper, the results of the comparison experiment show that the accuracy of this algorithm is better than that of the comparison algorithm, and the practical feasibility is verified.
Research on Personalized Recommendation System Based on Association Rules
Authors: Song HaiYan , Zhang Huan , Xing ZhiHao
Published: July 2021

With the rapid development of network technology, the amount of information is rapidly expanding, and the amount of various data has become huge and scattered. Using traditional keywords to retrieve search data has become quite time-consuming and difficult to focus on. Traditional search engines have been unable to help people effectively solve this problem, so personalized recommendation systems have emerged. In view of the user’s behavior and preferences, this article makes a detailed comparison of different recommendation technologies. It focuses on analyzing the applicability of the current popular content-based, association rules, and collaborative filtering recommendation technologies to the current needs. The technical scheme and system structure of recommendation system based on association rules are proposed, and aiming at the shortcomings of traditional recommendation system algorithms (the algorithm’s sparsity problem) and the current cold start problem of the recommendation system. Based on the MovieLens data set, a series of evaluation indicators are set up, comparative experiments are carried out, and the effectiveness of the proposed improved algorithm is analyzed.
Comparison of multi-beam bathymetric system and 3D sonar system in underwater detection of beach obstacles
Authors: Wang Shirui , Rong Yingjiao , Jiang Hejun , Li Menglei , Sun Ping
Published: July 2021

The instrument detection methods of underwater part of beach obstacle mainly include multi-beam bathymetric system and three-dimensional panoramic imaging sonar system. SeaBat T50-P multi beam bathymetry and BV5000-1350 sonar system are widely used in the area of underwater detection. The underwater part of beach obstacles is measured and analyzed, and the application scope of both equipment is discussed. The results show that the BV5000-1350 sonar system can be used to detect underwater incomplete obstacles with wider application scope, high accuracy, convenient installation of instruments, and no auxiliary equipment such as navigation, positioning and attitude sensor is needed; SeaBat T50-P multi-beam bathymetric system has high requirements for the structure of the measured object, moderate accuracy, and is more suitable for large-scale underwater obstacle survey.
Trajectory time series classification algorithm based on conv-olutional self-attention mechanism
Authors: Yang Hang , Li Xiaohui , Liu Zhonglin , Wang Licai , Luo Qibin
Published: July 2021

As a kind of time series data in the field of transportation, trajectory has complex multi-dimensional information. How to fully excavate the multi-dimensional information of the trajectory and analyse its complex dynamic pattern is an important problem to be solved in the classification of trajectory time series. In response to the above problems, this paper improves the existing self-attention mechanism, and proposes a trajectory time series classification algorithm based on convolutional self-attention mechanism. According to the characteristics of the trajectory data, the convolutional self-attention mechanism first extracts the characteristics of the trajectory fragments in the trajectory to obtain the flight status characteristics, and then performs the self-attention operation on these characteristics, so as to achieve a better feature extraction effect. The experimental results show that the trajectory time series classification algorithm based on the convolutional self-attention mechanism has better feature extraction ability and classification accuracy than other existing algorithms.