bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonlinear acoustic theory on flowing liquid containing multiple microbubbles coated by a compressible visco-elastic shell: Low and high frequency cases
Authors: Kanagawa Tetsuya , Honda Mitsuhiro , Kikuchi Yusei
Published: July 2022

Microbubbles coated by visco-elastic shells are important for ultrasound diagnosis using contrast agents, and the dynamics of single coated bubbles has been investigated in the literature. However, although a high number of contrast agents are used in practical situations, there has long been an absence of a nonlinear acoustic theory for multiple coated bubbles, except for our recent work by Kikuchi and Kanagawa [“Weakly nonlinear theory on ultrasound propagation in liquids containing many microbubbles encapsulated by visco-elastic shell,” Jpn. J. Appl. Phys. 60, SDDD14 (2021)], under several assumptions to be excluded. Aiming for generalization, in this study, we theoretically investigate weakly nonlinear propagation of ultrasound in liquid containing multiple bubbles coated by a visco-elastic shell with compressibility. Leveraging the method of multiple scales, both the Korteweg–de Vries–Burgers (KdVB) equation for a low-frequency long wave and nonlinear Schrödinger (NLS) equation for a high-frequency short wave are derived from the volumetric averaged equations for bubbly liquids based on a two-fluid model and the up-to-date model for single coated bubbles with shell compressibility. Neglected factors in our previous paper, i.e., compressibility of the shell and liquid, drag force acting on bubbles, bubble translation, and thermal conduction, are incorporated in the present KdVB and NLS equations; the proposed model will be regarded as a generic physico-mathematical model. The results show that shell compressibility attenuated ultrasound strongly and decreased nonlinearity of ultrasound. Finally, we compared the magnitudes of six dissipation factors (shell compressibility, shell viscosity, liquid compressibility, liquid viscosity, thermal effect, and drag force) for five typical ultrasound contrast agents, and a similar tendency between KdVB and NLS equations was revealed.
Geometry of deep and intermediate water breaking waves influenced by wind speed and direction
Authors: Chen Haifei , Zou Qingping
Published: July 2022

Wind effects on the evolution of a breaking wave group due to dispersive focusing are investigated using a two-phase flow Navier–Stokes solver. The Navier–Stokes equations are solved for both air and water, with the air–water interface captured by the Volume of Fluid method and the turbulence by the Smagorinsky subgrid-scale stress model. The two-phase model is first validated with the experimental measurements with and without following wind action. The following wind delays the breaking and shifts the breaking location downstream, and vice versa for the opposing wind. The wind-induced drift current is mainly responsible for these shifts of breaking time and location. The shift of breaking location and time is approximately linearly proportional to the wind speed (wind induced drift current) under weak winds, but the shift saturates under strong winds. The direct wind forcing, on the other hand, plays an increasingly larger role in the wave breaking process in the presence of stronger wind. It was found that the strong following wind forcing enhances the initiation of wave breaking, while the strong opposing wind forcing may change breaking type or suppress wave breaking of large intensity, such as plunging breaking. Accordingly, the wave shape at breaking onset is altered considerably under strong winds. The following wind increases the maximum wave height and wave skewness slightly. However, the opposing wind may also increase the maximum wave height initially because of the wind drift current induced upwave refocusing of the wave group. Eventually, stronger opposing wind decreases the wave height and wave skewness.
COVID-19 revisited – is a national pandemic plan possible?
Authors: Lewis-Hughes Peter , Brooks Peter
Published: July 2022

As we review health governance during the COVID-19 pandemic, we have an opportunity to reflect on these processes and ensure that future challenges might be managed in a more collaborative and whole of system response. This ‘Perspective’ reviews COVID-19 responses in Australia, reflects on a number of potential solutions that have been developed by organisations over the past two decades and proffers a governance framework for a Communicable Disease and Pandemic Management Authority that might assist health responses to future challenges.
Natural products isolation studies of native Australian fern species
Authors: Gyeltshen Thinley , Smith Jason A. , Bissember Alex C.
Published: July 2022

Natural products isolation studies of 16 native Australian fern species have been undertaken, facilitated by pressurised hot water extraction (PHWE). Fourteen of these fern species have not been the subject of natural products isolation research previously. In total, 14 different compounds were isolated from 12 of these 16 different fern species. This included γ- and δ-lactones; flavonoid glycosides, a dihydrobenzofuran neolignan, in addition to hydroxycinnamate/caffeic acid esters. More specifically, the lactones 5,6-dihydro-5-hydroxy-6-methyl-2H-pyran-2-one, 5-(1-hydroxyethyl)-2(5H)-furanone and osmundalin were obtained from Todea barbara, while a dihydrobenzofuran neolignan, (−)-trans-blechnic acid were found in Austroblechnum penna-marina subsp. alpina, and the shikimate ester 5-O-caffeoylshikimic acid was isolated from Parablechnum wattsii. In addition, flavonoids and their glycoside derivatives, kaempferol 3-O-glucopyranoside, 4β-carboxymethyl-(−)-epicatechin, (2R)-eriodictyol-7-O-β-d-glucopyranoside, naringin, quercitrin, quercetin 3-O-(6″-acetyl)-β-d-glucopyranoside, rutin, and tiliroside were isolated from seven other fern species.
Southern brown bandicoots,
Authors: Bruce Matthew J. , Bryant David B. , Kohout Michele , Macak Phoebe V. , Batpurev Khorloo , Sinclair Steve J.
Published: July 2022

Context Many threatened species persist in modified landscapes. Species in these landscapes often inhabit vegetation strips adjacent to linear structures such as roads, railways and artificial waterways. These vegetation strips may act as refugia or provide resources, but the associated structures (e.g. roads) may also act as barriers to movement. The southern brown bandicoot (eastern subspecies) is listed as Endangered in Australia and is known to inhabit modified landscapes. Aim We aim to determine the extent of occupancy of southern brown bandicoots and the relative importance of different habitat types. Our data are intended to provide a baseline for future monitoring of changes to bandicoot populations, and to further our understanding of the relative importance of different habitat types for management and conservation. Methods We conducted a remote-camera survey of southern brown bandicoots, at 98 locations across a 60 000 ha region south-east of Melbourne. Bandicoots in this area inhabit patches of remnant habitat in reserves and remnant, modified or non-native vegetation strips along roadsides and artificial waterways created in the 19th century to drain swampland. These habitat fragments sit within a matrix of agricultural, residential and commercial land. Key results Our results suggest that bandicoot occupancy is higher along artificial waterways (0.76) than along roadsides (0.35) or within reserves (0.39). Implications Habitat along waterways is often different from remnants, with a mix of weedy and native vegetation. The implication of this is a potential conflict between habitat and vegetation management for bandicoots, weed control and maintenance of drains and associated levees.
Dynamic regulation and requirement for ribosomal RNA transcription during mammalian development
Authors: Falcon Karla T. , Watt Kristin E. N. , Dash Soma , Zhao Ruonan , Sakai Daisuke , Moore Emma L. , Fitriasari Sharien , Childers Melissa , Sardiu Mihaela E. , Swanson Selene , Tsuchiya Dai , Unruh Jay , Bugarinovic George , Li Lin , Shiang Rita , Achilleos Annita , Dixon Jill , Dixon Michael J. , Trainor Paul A.
Published: July 2022

Ribosomal RNA (rRNA) transcription by RNA polymerase I (Pol I) is a critical rate-limiting step in ribosome biogenesis, which is essential for cell survival. Despite its global function, disruptions in ribosome biogenesis cause tissue-specific birth defects called ribosomopathies, which frequently affect craniofacial development. Here, we describe a cellular and molecular mechanism underlying the susceptibility of craniofacial development to disruptions in Pol I transcription. We show that Pol I subunits are highly expressed in the neuroepithelium and neural crest cells (NCCs), which generate most of the craniofacial skeleton. High expression of Pol I subunits sustains elevated rRNA transcription in NCC progenitors, which supports their high tissue-specific levels of protein translation, but also makes NCCs particularly sensitive to rRNA synthesis defects. Consistent with this model, NCC-specific deletion of Pol I subunitsPolr1a,Polr1c, and associated factorTcof1in mice cell-autonomously diminishes rRNA synthesis, which leads to p53 protein accumulation, resulting in NCC apoptosis and craniofacial anomalies. Furthermore, compound mutations in Pol I subunits and associated factors specifically exacerbate the craniofacial anomalies characteristic of the ribosomopathies Treacher Collins syndrome and Acrofacial Dysostosis–Cincinnati type. Mechanistically, we demonstrate that diminished rRNA synthesis causes an imbalance between rRNA and ribosomal proteins. This leads to increased binding of ribosomal proteins Rpl5 and Rpl11 to Mdm2 and concomitantly diminished binding between Mdm2 and p53. Altogether, our results demonstrate a dynamic spatiotemporal requirement for rRNA transcription during mammalian cranial NCC development and corresponding tissue-specific threshold sensitivities to disruptions in rRNA transcription in the pathogenesis of congenital craniofacial disorders.
The rise of biting during the Cenozoic fueled reef fish body shape diversification
Authors: Corn Katherine A. , Friedman Sarah T. , Burress Edward D. , Martinez Christopher M. , Larouche Olivier , Price Samantha A. , Wainwright Peter C.
Published: July 2022

Diversity of feeding mechanisms is a hallmark of reef fishes, but the history of this variation is not fully understood. Here, we explore the emergence and proliferation of a biting mode of feeding, which enables fishes to feed on attached benthic prey. We find that feeding modes other than suction, including biting, ram biting, and an intermediate group that uses both biting and suction, were nearly absent among the lineages of teleost fishes inhabiting reefs prior to the end-Cretaceous mass extinction, but benthic biting has rapidly increased in frequency since then, accounting for about 40% of reef species today. Further, we measured the impact of feeding mode on body shape diversification in reef fishes. We fit a model of multivariate character evolution to a dataset comprising three-dimensional body shape of 1,530 species of teleost reef fishes across 111 families. Dedicated biters have accumulated over half of the body shape variation that suction feeders have in just 18% of the evolutionary time by evolving body shape ∼1.7 times faster than suction feeders. As a possible response to the ecological and functional diversity of attached prey, biters have dynamically evolved both into shapes that resemble suction feeders as well as novel body forms characterized by lateral compression and small jaws. The ascendance of species that use biting mechanisms to feed on attached prey reshaped modern reef fish assemblages and has been a major contributor to their ecological and phenotypic diversification.
Coupled dynamics of the North Equatorial Countercurrent and Intertropical Convergence Zone with relevance to the double-ITCZ problem
Authors: Li Zhiyuan , Fedorov Alexey V.
Published: July 2022

The Intertropical Convergence Zone (ITCZ) is a salient feature of tropical atmospheric circulation characterized by intense convective clouds and rainfall north of the equator. Climate models, however, commonly experience the double-ITCZ problem—the tendency to produce another strong precipitation band but south of the equator. Here, we describe coupled interaction between the ITCZ and the North Equatorial Countercurrent (NECC) that is relevant to this problem. This current is a major component of the tropical Pacific upper-ocean circulation, which flows against easterly trade winds and transports warm water from the western Pacific eastward. Its core follows the latitudinal position of the ITCZ. Trade winds converge toward the ITCZ, creating a local minimum in zonal winds and generating positive wind stress curl that maintains an eastward current despite westward winds. We show that interaction between the ITCZ and the NECC involves positive feedback: a stronger NECC advects warm water from the western Pacific to the colder east thus increasing sea surface temperature (SST) along its path, intensifying convection within the ITCZ and hence strengthening wind stress curl, further strengthening the NECC. To demonstrate this wind stress curl-advection-SST-precipitation (WASP) feedback, we conduct climate model experiments in which we progressively strengthen the surface Ekman component of the NECC and observe the intensification of the ITCZ and the entire NECC. Consequently, a weak NECC leads to a weak ITCZ, which can contribute to the double-ITCZ problem in climate models, since weak wind convergence north of the equator enables stronger convergence in the south.
Deep neural networks constrained by neural mass models improve electrophysiological source imaging of spatiotemporal brain dynamics
Authors: Sun Rui , Sohrabpour Abbas , Worrell Gregory A. , He Bin
Published: July 2022

Many efforts have been made to image the spatiotemporal electrical activity of the brain with the purpose of mapping its function and dysfunction as well as aiding the management of brain disorders. Here, we propose a non-conventional deep learning–based source imaging framework (DeepSIF) that provides robust and precise spatiotemporal estimates of underlying brain dynamics from noninvasive high-density electroencephalography (EEG) recordings. DeepSIF employs synthetic training data generated by biophysical models capable of modeling mesoscale brain dynamics. The rich characteristics of underlying brain sources are embedded in the realistic training data and implicitly learned by DeepSIF networks, avoiding complications associated with explicitly formulating and tuning priors in an optimization problem, as often is the case in conventional source imaging approaches. The performance of DeepSIF is evaluated by 1) a series of numerical experiments, 2) imaging sensory and cognitive brain responses in a total of 20 healthy subjects from three public datasets, and 3) rigorously validating DeepSIF’s capability in identifying epileptogenic regions in a cohort of 20 drug-resistant epilepsy patients by comparing DeepSIF results with invasive measurements and surgical resection outcomes. DeepSIF demonstrates robust and excellent performance, producing results that are concordant with common neuroscience knowledge about sensory and cognitive information processing as well as clinical findings about the location and extent of the epileptogenic tissue and outperforming conventional source imaging methods. The DeepSIF method, as a data-driven imaging framework, enables efficient and effective high-resolution functional imaging of spatiotemporal brain dynamics, suggesting its wide applicability and value to neuroscience research and clinical applications.
Root angle is controlled byEGT1in cereal crops employing an antigravitropic mechanism
Authors: Fusi Riccardo , Rosignoli Serena , Lou Haoyu , Sangiorgi Giuseppe , Bovina Riccardo , Pattem Jacob K. , Borkar Aditi N. , Lombardi Marco , Forestan Cristian , Milner Sara G. , Davis Jayne L. , Lale Aneesh , Kirschner Gwendolyn K. , Swarup Ranjan , Tassinari Alberto , Pandey Bipin K. , York Larry M. , Atkinson Brian S. , Sturrock Craig J. , Mooney Sacha J. , Hochholdinger Frank , Tucker Matthew R. , Himmelbach Axel , Stein Nils , Mascher Martin , Nagel Kerstin A. , De Gara Laura , Simmonds James , Uauy Cristobal , Tuberosa Roberto , Lynch Jonathan P. , Yakubov Gleb E. , Bennett Malcolm J. , Bhosale Rahul , Salvi Silvio
Published: July 2022

Root angle in crops represents a key trait for efficient capture of soil resources. Root angle is determined by competing gravitropic versus antigravitropic offset (AGO) mechanisms. Here we report a root angle regulatory gene termedENHANCED GRAVITROPISM1(EGT1) that encodes a putative AGO component, whose loss-of-function enhances root gravitropism. Mutations in barley and wheatEGT1genes confer a striking root phenotype, where every root class adopts a steeper growth angle.EGT1encodes an F-box and Tubby domain-containing protein that is highly conserved across plant species. Haplotype analysis found that natural allelic variation at the barleyEGT1locus impacts root angle. Gravitropic assays indicated thatHvegt1roots bend more rapidly than wild-type. Transcript profiling revealedHvegt1roots deregulate reactive oxygen species (ROS) homeostasis and cell wall-loosening enzymes and cofactors. ROS imaging shows thatHvegt1root basal meristem and elongation zone tissues have reduced levels. Atomic force microscopy measurements detected elongatingHvegt1root cortical cell walls are significantly less stiff than wild-type. In situ analysis identifiedHvEGT1is expressed in elongating cortical and stele tissues, which are distinct from known root gravitropic perception and response tissues in the columella and epidermis, respectively. We propose that EGT1 controls root angle by regulating cell wall stiffness in elongating root cortical tissue, counteracting the gravitropic machinery’s known ability to bend the root via its outermost tissues. We conclude that root angle is controlled byEGT1in cereal crops employing an antigravitropic mechanism.
Shelterin is a dimeric complex with extensive structural heterogeneity
Authors: Zinder John C. , Olinares Paul Dominic B. , Svetlov Vladimir , Bush Martin W. , Nudler Evgeny , Chait Brian T. , Walz Thomas , de Lange Titia
Published: July 2022

Human shelterin is a six-subunit complex—composed of TRF1, TRF2, Rap1, TIN2, TPP1, and POT1—that binds telomeres, protects them from the DNA-damage response, and regulates the maintenance of telomeric DNA. Although high-resolution structures have been generated of the individual structured domains within shelterin, the architecture and stoichiometry of the full complex are currently unknown. Here, we report the purification of shelterin subcomplexes and reconstitution of the entire complex using full-length, recombinant subunits. By combining negative-stain electron microscopy (EM), cross-linking mass spectrometry (XLMS), AlphaFold modeling, mass photometry, and native mass spectrometry (MS), we obtain stoichiometries as well as domain-scale architectures of shelterin subcomplexes and determine that they feature extensive conformational heterogeneity. For POT1/TPP1 and POT1/TPP1/TIN2, we observe high variability in the positioning of the POT1 DNA-binding domain, the TPP1 oligonucleotide/oligosaccharide–binding (OB) fold, and the TIN2 TRFH domain with respect to the C-terminal domains of POT1. Truncation of unstructured linker regions in TIN2, TPP1, and POT1 did not reduce the conformational variability of the heterotrimer. Shelterin and TRF1-containing subcomplexes form fully dimeric stoichiometries, even in the absence of DNA substrates. Shelterin and its subcomplexes showed extensive conformational variability, regardless of the presence of DNA substrates. We conclude that shelterin adopts a multitude of conformations and argue that its unusual architectural variability is beneficial for its many functions at telomeres.
On the reliability of individual economic rationality measurements
Authors: Nitsch Felix J. , Lüpken Luca M. , Lüschow Nils , Kalenscher Tobias
Published: July 2022

A contemporary research agenda in behavioral economics and neuroeconomics aims to identify individual differences and (neuro)psychological correlates of rationality. This research has been widely received in important interdisciplinary and field outlets. However, the psychometric reliability of such measurements of rationality has been presumed without enough methodological scrutiny. Drawing from multiple original and published datasets (in total over 1,600 participants), we unequivocally show that contemporary measurements of rationality have moderate to poor reliability according to common standards. Further analyses of the variance components, as well as a allowing participants to revise previous choices, suggest that this is driven by low between-subject variance rather than high measurement error. As has been argued previously for other behavioral measurements, this poses a challenge to the predominant correlational research designs and the search for sociodemographic or neural predictors. While our results draw a sobering picture of the prospects of contemporary measurements of rationality, they are not necessarily surprising from a theoretical perspective, which we outline in our discussion.
Monitoring glycolytic dynamics in single cells using a fluorescent biosensor for fructose 1,6-bisphosphate
Authors: Koberstein John N. , Stewart Melissa L. , Smith Chadwick B. , Tarasov Andrei I. , Ashcroft Frances M. , Stork Philip J. S. , Goodman Richard H.
Published: July 2022

Cellular metabolism is regulated over space and time to ensure that energy production is efficiently matched with consumption. Fluorescent biosensors are useful tools for studying metabolism as they enable real-time detection of metabolite abundance with single-cell resolution. For monitoring glycolysis, the intermediate fructose 1,6-bisphosphate (FBP) is a particularly informative signal as its concentration is strongly correlated with flux through the whole pathway. Using GFP insertion into the ligand-binding domain of theBacillus subtilistranscriptional regulator CggR, we developed a fluorescent biosensor for FBP termed HYlight. We demonstrate that HYlight can reliably report the real-time dynamics of glycolysis in living cells and tissues, driven by various metabolic or pharmacological perturbations, alone or in combination with other physiologically relevant signals. Using this sensor, we uncovered previously unknown aspects of β-cell glycolytic heterogeneity and dynamics.
A missense mutation in
Kcnc3
causes hippocampal learning deficits in mice
Authors: Xu Pin , Shimomura Kazuhiro , Lee Changhoon , Gao Xiaofei , Simpson Eleanor H. , Huang Guocun , Joseph Chryshanthi M. , Kumar Vivek , Ge Woo-Ping , Pawlowski Karen S. , Frye Mitchell D. , Kourrich Saïd , Kandel Eric R. , Takahashi Joseph S.
Published: July 2022

Although a wide variety of genetic tools has been developed to study learning and memory, the molecular basis of memory encoding remains incompletely understood. Here, we undertook an unbiased approach to identify novel genes critical for memory encoding. From a large-scale, in vivo mutagenesis screen using contextual fear conditioning, we isolated in mice a mutant, named
Clueless
, with spatial learning deficits. A causative missense mutation (G434V) was found in the voltage-gated potassium channel, subfamily C member 3 (
Kcnc3)
gene in a region that encodes a transmembrane voltage sensor. Generation of a Kcnc3
G434V
CRISPR mutant mouse confirmed this mutation as the cause of the learning defects. While G434V had no effect on transcription, translation, or trafficking of the channel, electrophysiological analysis of the G434V mutant channel revealed a complete loss of voltage-gated conductance, a broadening of the action potential, and decreased neuronal firing. Together, our findings have revealed a role for
Kcnc3
in learning and memory.
Applying systemic functional linguistics in translation studies
Authors: Chen Shukun , Xuan Winfred Wenhui , Yu Hailing
Published: July 2022

This paper takes a meta-analysis and synthesis approach to emphasize systemic functional linguistics’ contribution to translation studies. A coding book was designed to analyze 123 studies collected through email inquiry, database search, and manual examination. The paper reports on the substantive features and methodological features of the studies. Content analysis was presented on four major research themes: general translation, genre translation, interpreting, and translation training. After discussing the synthesis results, the paper is concluded with implications for future research.
Reliable InAs quantum dot lasers grown on patterned Si (001) substrate with embedded hollow structures assisted thermal stress relaxation
Authors: Wei Wenqi , Huang Jingzhi , Ji Zitao , Han Dong , Yang Bo , Chen Jiajian , Qin Jiale , Cui Yiou , Wang Zihao , Wang Ting , Zhang Jianjun
Published: July 2022

Direct epitaxial growth of III–V quantum dot (QD) lasers on Si (001) substrates is recognized as a promising and low-cost method for realizing high-performance on-chip light sources in silicon photonic integrated circuits (PICs). Recently, the CMOS-compatible patterned Si (001) substrates with sawtooth structures have been widely implemented to suppress the lattice mismatch induced defects and antiphase boundaries for heteroepitaxial growth of high-quality III–V materials on Si. Considerable progresses have been made on high-performance 1300 nm InAs/GaAs QD lasers on Si (001). Here, we report a thermal stress-relaxed (111)-faceted silicon hollow structures by homoepitaxial method for reliable InAs/GaAs QD lasers growing on Si (001) substrates. Both simulation analysis and experimental results indicate that the voids buried below the sawtooth structures can release about 9% of the accumulative thermal stress of the III–V/Si system during the cooling process. Furthermore, electrically pumped InAs/GaAs QD narrow ridge lasers are grown and fabricated on the specially designed Si (001) platforms with a maximum operation temperature up to 90 °C under continuous-wave operation mode. Additionally, an extrapolated lifetime of over 5300 h is calculated from the reliability test at 65 °C. These results lead toward high-yield, scalable, and reliable III–V lasers on Si (001) substrates for PICs.
Enhanced performance of p-type SnO
x
thin film transistors through defect compensation
Authors: Zhang Wei , Hong Ruohao , Qin Wenjing , Lv Yawei , Ma Jianmin , Liao Lei , Li Kenli , Jiang Changzhong
Published: July 2022

Due to the unique outermost orbitals of Sn, hole carriers in tin monoxide (SnO) possess small effective mass and high mobility among oxide semiconductors, making it a promising p-channel material for thin film field-effect transistors (TFTs). However, the Sn vacancy induced field-effect mobility deterioration and threshold voltage (V
th) shift in experiments greatly limit its application in complementary metal-oxide-semiconductor (CMOS) transistors. In this study, the internal mechanism of vacancy defect compensation by aluminum (Al) doping in SnO
x
film is studied combining experiments with the density functional theory (DFT). The doping is achieved by an argon (Ar) plasma treatment of Al2O3 deposited onto the SnO
x
film, in which the Al2O3 provides both the surface passivation and Al doping source. Experimental results show a wide V
th modulation range (6.08 to −19.77 V) and notable mobility enhancement (11.56 cm2V−1s−1) in the SnO
x
TFTs after the Al doping by Ar plasma. DFT results reveal that the most possible positions of Al in SnO and SnO2 segments are the compensation to Sn vacancy and interstitial. The compensation will create an n-type doping effect and improve the hole carrier transport by reducing the hole effective mass (m
h*), which is responsible for the device performance variation, while the interstitial in the SnO2 segment can hardly affect the valence transport of the film. The defect compensation is suitable for the electronic property modulation of SnO towards the high-performance CMOS application.
Non-intrusive ultrasonic measurement of tie-bar stress for molding equipment
Authors: Zhuo Chaojie , Ji Kaipeng , Xie Jun , Cheng Xuewen , Jiao Xiaolong , Ye Sheng , Fu Jianzhong , Zhao Peng
Published: July 2022

For molding equipment, the accurate measurement of tie-bar stress helps improve product quality and prolong the lifespan of the machine. In our previous work, the mathematical model between the ultrasonic time difference (UTD) and the tie-bar stress was established, and this model was shown to have high accuracy with the maximum of difference square being only 1.5678 (MPa)2. Nevertheless, when calculating the UTD using the cross-correlation function (CCF) method, it is necessary to manually divide the position of the echoes. This makes it impossible to automate the stress measurement and it is ineffective when dealing with massive data. In this paper, a non-intrusive ultrasonic measurement method for tie-bar stress based on the minimum entropy blind deconvolution is firstly proposed. The results of simulation and verification experiments show that the proposed method has high precision, and the maximum relative error is only 2.44%. Hence this method has been successfully applied in the tie-bar stress measurement in molding equipment. Compared with the CCF method, accuracy is improved and the maximum relative error is reduced from 3.67% to 1.68% when the clamping force is small. In summary, the proposed method is comparable to the CCF method in terms of accuracy, and has a higher resolution during echos disturbance. Moreover, this approach does not require human intervention and is helpful to realize the automation of the tie-bar stress measurement for the molding equipment.
Simulations of energetic particle driven instabilities in CFQS
Authors: Wang Hao , Todo Yasushi , Huang Jie , Suzuki Yasuhiro , Shimizu Akihiro , Ogawa Kunihiro , Wang Xianqu , Adulsiriswad Panith
Published: July 2022

A nonlinear simulation of the energetic particle driven instabilities in the Chinese First Quasi-axisymmetric Stellarator (CFQS) has been conducted for the first time. MEGA, a hybrid simulation code for energetic particles interacting with a magneto-hydrodynamic fluid, was used in the present work. Both the m/n = 3/1 energetic-particle-mode (EPM) like mode and the m/n = 5/2 toroidal Alfvén eigenmode (TAE) were found, where m is the poloidal mode number and n is the toroidal mode number. Four important results were obtained as follows. First, the instability in the CFQS in three-dimensional form was shown for the first time. Second, strong toroidal mode coupling was found for the spatial profiles, and it is consistent with the theoretical prediction. Third, the resonant condition caused by the absence of axial symmetry in CFQS was demonstrated for the first time. The general resonant condition is f
mode = Nf

ϕ
− Lf

θ
, where f
mode, f

ϕ
, and f

θ
are mode frequency, particle toroidal transit frequency, and particle poloidal transit frequency, respectively; N and L are arbitrary integers, represent toroidal and poloidal resonance numbers. For EPM-like mode, the dominant and subdominant resonant conditions are f
mode = 3f

ϕ
− 7f

θ
and f
mode = f

ϕ
− f

θ
, respectively. For TAE, the dominant and subdominant resonant conditions are f
mode = 4f

ϕ
− 9f

θ
and f
mode = 2f

ϕ
− 3f

θ
, respectively. On the one hand, the toroidal resonance numbers are different from the toroidal mode numbers by 2. This indicates that the two-fold rotational symmetry affects the resonance condition. On the other hand, the subdominant resonances satisfy N = n, which is expected for the axisymmetric plasmas and most of the toroidal plasmas including stellarators. Fourth, the nonlinear frequency chirpings in CFQS were demonstrated for the first time. Hole and clump structures were formed in the pitch angle and energy phase space, and the particles comprising the hole and clump were kept resonant with the modes during the mode frequencies chirping.
Cognitive mechatronic smart system with obstacle detection using sensor-based system to avoid car accidents
Authors: Chatterjee Sumanta , Chanda Aindrila , Bhunia Pabitra Kumar , Dey Amit , Raza Md Aslam , Kundu Mainak
Published: July 2022

Nowadays the maximum number of cars have a high level of automatic safety system which help driver to maintain control of car and their safety system warn the driver of any potential danger. Car safety is increased by these types of distinctive attributes, but they are expensive and can be found only in expensive cars. Our research paper focuses on making a forward collision mitigation system that can work in all Kinds of vehicles without making any kind of differences between them because of Age, make, model or type and can be affordable at minimum price. If two vehicles are Moving on the same road and in the same direction, the system will analyse the distance Between two vehicles, then warn the driver about any potential danger in which she or He can be in by using ultrasonic sensors and a microcontroller. To alert the driver and Passengers effectively, the distance between two vehicles is calculated by an audio-Visual alarm and an ultrasonic.
Application of Fourier Transform to Study Hyers-Ulam Stability of Linear Differential Equations
Authors: Nallathambi Kandhasami , Santra Shyam Sundar , Alagesan K. , Routh Rajib , Maji Sayan , Khedher Khaled Mohamed
Published: July 2022

In this paper, we investigate the generalized Hyers-Ulam stabilities of the fourth-order homogeneous differential equation and the non-homogeneous linear differential equation by applying Fourier transform method.
Student’s performance evaluation according to the cognitive domain: fuzzy logic approach
Authors: Dam Mrinmoy , Majumder Debasish , Bhattacharjee Rupak , Santra Shyam Sundar
Published: July 2022

Teaching learning process is one of the important aspects in academic performance evaluation of students. This gives an idea of how much a student has gained the knowledge and skill in a particular subject during the entire season. In this paper, a multi criteria-based decision support system based on six levels of revised Bloom’s cognitive domain has been presented to measure the cognitive knowledge and skill acquired by a student. The fuzzy set theoretic approach has been adopted to overcome the vagueness/fuzziness present in the evaluation process and the inexact causal relationship between input and output parameters has been addressed using the Mamdani fuzzy IF-THEN rules. Finally, a comparative study has been depicted between the marks obtain by a group of students in the exam with their cognitive knowledge score.
Oscillatory Properties of Third-order Neutral Delay Difference Equations
Authors: Chitra L. , Alagesan K. , Das S. , Bhattacharjee A. , Govindan V.
Published: July 2022

In this paper, we are connected with oscillation of third-order linear neutral delay difference equation of the form

Δ
(

c
2

(
σ
)
Δ
(

c
1

(
σ
)
Δ
h
(
σ
)
)
)
+
p
(
σ
)
x
(
σ
−
ς
)
=
0
,

σ
≥

σ
0

>
0
,

where

h
(
σ
)
=
x
(
σ
)
+
q
(
σ
)
x
(
σ
−
η
)

. Here c
1(σ) and c
2(σ) are the sequence of positive integers, p(σ) and q(σ) are positive and real sequences such that q(σ) ≥ q
0 > 1 and p(σ) ≠ 0, ς, η are positive integers, such that ς > η.
An Ensemble Heart Disease Prediction Model Bagged with Logistic Regression, Naïve Bayes and K Nearest Neighbour.
Authors: Majumder Annwesha Banerjee , Gupta Somsubhra , Singh Dharmpal
Published: July 2022

Cardiovascular disease is an immense threat in today’s world. Every year lots of people died by this disease. Though medical science evolved and evaluated much extends still in many areas of the world there are lack of medical support. Early detection of cardiovascular can save lives where machine learning can help us. Advancement of artificial intelligence and machine learning are now playing an effective role in disease prediction and different health care applications. In this paper a heart disease prediction model has been proposed using ensemble learning. Single learning mechanism may not give a proper result so by combing multiple learners better performance from the model can be achieved. In this paper bagging with Logistic Regression, Gaussian Naïve Bayes and K Nearest Neighbour have applied.
Impact of diksha app as an electronic resource in english language teaching learning process in different kendriya vidyalayas’ of india
Authors: Ghosh Koushik
Published: July 2022

This paper seeks to present the impact of Diksha App as an electronic resource in English Language Teaching Learning process in different Kendriya Vidyalayas’ of India. NEP-2020 Para 23.6 emphasizes on the integration of technology-based education platforms, such as Diksha across school and higher educational institutions for using e-contents in teaching learning processes and to use this platform for the professional development of the teachers. NEP-2020 also emphasizes on tech-savvy teachers. Diksha is such a platform through which training can be imparted both to the teachers and to students, not only that it can be used as a great resource of English language teaching learning process. How far Diksha app as a teaching learning tool is fruitful to put some light on that the researcher made a case study, a questionnaire was implemented through Google form and both the qualitative and quantitative analysis of the data has been done of the collected data received from different KVS English teachers from all over the India. This practical study also diagnoses the different demerits and limitations of Diksha App as an English Language Teaching Learning tool. The result and discussion shows some positive implications for different stakeholders on the usages of Diksha App in English Language teaching learning process.
Suitable model prediction based on COVID 19 Phase I data
Authors: Dutta Palash , Dutta Trina , Barman Ananya , Pal Moumita , Ray Ranjana
Published: July 2022

This paper integrates multiple standard regression models for prediction of COVID-19 infected data. We have taken Linear Regression, Polynomial Regression and Logistic Regression for our modelling and prediction purposes. These models are created, trialled and tested in MATLAB software with available data for Covid 19 infected cases. These models evolves as we get more and more data to show better predictions. Explanations of these models are valuable. The models’ forecasts are credible to epidemiologists and provide confidence in end-users such as policy makers and healthcare institutions as an output of this study. These models can be applied at different geographic resolutions, and in this paper, it is demonstrated for states in India. The model supplies more exact forecasts, in metrics averaged across the entire India. Lastly, we analyse the performance of our models for various datapoints and regression parameters to recommend optimized regression model.
Work Group 2 Position Paper: Experiments and Laboratory Work in Teacher Education
Authors: Bearden Ian , Dvořák Leoš , Planinšič Gorazd
Published: July 2022

The paper summarizes the results of discussion of the work group that focused on different aspects of experiments and laboratory work in teacher education. The discussion evolved around the following four guiding questions: What is the role of experiments in learning physics in general?; What are the labs supposed to help students learn?; How to achieve these goals in practice?; and How do we help future teachers develop skills/knowledge/competences so they will be successful in achieving these goals? About 30 participants shared their experience, views and ideas. The resulting views are summarized into general findings and recommendations.
Indicators of critical thinking and physics experiments
Authors: Trúsiková Anna , Velmovská Klára
Published: July 2022

Critical thinking is an important skill which people use every day, together with other abilities, to evaluate and interpret information, choose criteria, make decisions or solve problems. It is considered to be essential for the life in the 21st century. Various experts agree that critical thinking is not inherent and students should have an opportunity to learn how to think critically and to develop this skill in various classes. In order to do so, teachers need to be prepared to support students’ thinking. The article summarizes indicators of critical thinking which can be used in Physics classes. The proposal of an activity where students can explore how the conductor heats up when the electric current passes through it in relation to different parameters of conductor is presented. Activity exemplifies the connection between the indicators of critical thinking and the experiments in Physics classes.
Video making as a powerful tool in physics teacher education and in teaching and learning
Authors: Lucz I T , Milner-Bolotin M
Published: July 2022

This paper describes the results of an ongoing international research collaboration on educational science video making between the researchers at The University of British Columbia in Vancouver, Canada and Eötvös Loránd University in Budapest, Hungary. In this study, future physics teachers designed short YouTube-style educational videos showcasing their own physics demonstrations and experiments. We used Deliberate Pedagogical Thinking with Technology theoretical framework to examine how these future physics teachers acquire their pedagogical physics demonstration skills while also becoming amateur video producers. We also investigated how these videos can be used to deepen secondary students’ physics knowledge, stimulate their curiosity to increase their science engagement, interest, and motivation. Secondary school students’ feedback and the results of their pre- and post-tests also provide evidence that educational science videos that utilize the results of education research can be effective in supporting self-directed student learning.
A teaching-learning sequence to present the relativity principle and the principle of equivalence in classical Mechanics to pre-service physics teachers
Authors: Marzari A , Malgieri M , Rosi T , Onorato P
Published: July 2022

We designed a teaching-learning sequence on the relativity principle and the principle of equivalence in classical Mechanics, rooted in previous research about students and teachers’ conceptions. A series of experiments based on video analysis is used to highlight selected key concepts and to motivate students in their exploration of the topic and interactive simulations, which can be modified on the fly by student teachers, are used to stimulate autonomous investigation. The sequence was designed for teacher education at University level and was tested with a group of 20 pre-service physics teachers.
Answering to physics teachers’ needs in professional development
Authors: Buongiorno D , Michelini M , Santi L , Stefanel A
Published: July 2022

The IDIFO project conducted at the University of Udine, in collaboration with 18 Italian universities, is an example of integration and collaboration between schools and universities proposals on innovation in physics education. The aspects of the project relating to the professional development of teachers are discussed, presenting the various implementation methods designed and activated, also answering to the formative needs of schools relating to laboratory-based scientific teaching/learning.
Teaching quantum physics in the footsteps of Einstein
Authors: Di Mauro M , Esposito S , Naddeo A
Published: July 2022

A teaching-learning sequence designed to introduce some fundamental concepts of quantum physics to high school teachers is proposed. Some parts of the proposal can be adapted to be taught to advanced high school students themselves. The inspiration came from the recognition of the fact that the roots of many pivotal concepts of quantum physics, namely light quanta, wave-particle duality, and probability, were introduced for the first time in some paper by Albert Einstein. Moreover, this was done in a characteristically deep and illuminating way. A critical study of Einstein’s papers should therefore be useful for teachers and students as well, in view of the fact that such concepts are often misconceived. The teaching-learning sequence can supplement usual historically oriented treatments of elementary quantum physics and can in turn be complemented by a discussion of some elementary tools of statistical physics, which may be not part of the learners’ background. Preliminary results obtained with both teachers and pupils in high schools in southern Italy, which are very promising, are presented.
Mobile application devices for MATAG coconut variety detection based on spectral signature analysis: A review
Authors: Che’Ya Nik Norasma , Mohidem Nur Adibah , Tarmidi Zakri , Sarifudin Muhd Syafie Asyraf , Shah Jasmin Arif
Published: July 2022

A smartphone is a high-speed technology with many new features available. Users can install games, education, health, financial, safety, and even agriculture apps. Some smartphones can detect plant species based on the processed images from RGB and its algorithm. MATAG hybrid process including fermentation is being described. This review also shows the current trend of MATAG variety identification based on spectral signature differences between MATAG hybrid. It can be linked via mobile applications to detect the species. This review then elaborates the image segmentation in the smartphone for the segregation of digital images into several segments and locates the objects and the bounding lines of the pictures. Applications of computer vision techniques such as machine learning and support vector machine to identify MATAG variety based on spectral analysis is being reviewed. As a user-friendly approach, the mobile application is essential for farmers to capture the MATAG information from smartphones’ cameras with all the processing links to the server and finally will help farmers identify the species using the mobile apps.
Probing the role of CNTs in Pt nanoparticle/CNT/graphene nanohybrids H2 sensors
Authors: Alamri Mohammed , Liu Bo , Berrie Cindy L , Walsh Michael , Wu Judy Z
Published: July 2022

In the carbon nanotubes film/graphene heterostructure decorated with catalytic Pt nanoparticles using atomic layer deposition (Pt-NPs/CNTs/Gr) H2 sensors, the CNT film determines the effective sensing area and the signal transport to Gr channel. The former requires a large CNT aspect ratio for a higher sensing area while the latter demands high electric conductivity for efficient charge transport. Considering the CNT’s aspect ratio decreases, while its conductivity increases (i.e., bandgap decreases), with the CNT diameter, it is important to understand how quantitatively these effects impact the performance of the Pt-NPs/CNTs/Gr nanohybrids sensors. Motivated by this, this work presents a systematic study of the Pt-NPs/CNTs/Gr H2 sensor performance with the CNT films made from different constituent CNTs of diameters ranging from 1 nm for single-wall CNTs, to 2 nm for double-wall CNTs, and to 10–30 nm for multi-wall CNTs (MWCNTs). By measuring the morphology and electric conductivity of SWCNT, DWCNT and MWCNT films, this work aims to reveal the quantitative correlation between the sensor performance and relevant CNT properties. Interestingly, the best performance is obtained on Pt-NPs/MWCNTs/Gr H2 sensors, which can be attributed to the compromise of the effective sensing area and electric conductivity on MWCNT films and illustrates the importance of optimizing sensor design.