Miracle-dz/UniFAR-FTUs huggingface dataset:
Dispersion of elastic waves in random particulate composites

Elastic wave propagation in a discrete random medium is studied to predict dynamic effective properties of composite materials containing spherical inclusions. A self‐consistent method is proposed which is analogous to the well‐known coherent potential approximation in alloy physics. Three conditions are derived that should be satisfied by two effective elastic moduli and effective density. The derived self‐consistency conditions have the physical meaning that the scattering of a coherent wave by the constituents in the effective medium vanishes, on the average. The frequency‐dependent effective wave speed and coherent attenuation can be obtained by solving the self‐consistency conditions numerically. At the lowest resonance frequency, the phase speed increases rapidly and the attenuation reaches the maximum in the composites having a large density mismatch. The lowest resonance is caused mainly by the density mismatch between matrix and particles and higher resonances by the stiffness mismatch. The dispe.
Children with language disorder as friends: Interviews with classroom peers to gather their perspectives

Language disorder (LD) is a common childhood condition affecting language development, which can in turn impact children's peer relationships. Although most children with LD are included in mainstream classrooms, there is limited knowledge about the way friendships support or hinder the learning experiences of children with LD in inclusive settings. Typically developing (TD) peers’ views tend to get overlooked when considering inclusion but they need to be heard as they too adapt to inclusive classrooms. In this small-scale study, we explored the perspectives of peers on their friendship quality with children with LD. We conducted friendship interviews with classroom friends (n = 9) of 6–8-year-old children with LD (n = 9), who attended the enhanced provision and mainstream classrooms in the United Kingdom and the Republic of Ireland. We used sociometric nomination methods to identify the reciprocal friends of children with LD. We then interviewed these friends using art-based methods and analysed our interview data using thematic framework. Friends of children with LD attending the enhanced provision showed an inclusive mindset and revealed their own strategies for overcoming potential communication barriers. In contrast, friends in full-time mainstream classrooms did not report experiencing communication difficulties when interacting with a peer with LD. We conclude that educational practice should build on those inclusion strategies that children find natural and consider the importance of teaching all children about adjustments that can support inclusion of those with communication difficulties.
A Time-Varying Copula Approach to Investigate the Dependence Structures of BRICS Stock Markets Before and After COVID-19

ABSTRACT In this study, changes in the dependence structures of BRICS countries’ stock markets before and after the World Health Organization’s Covid-19 emergency declaration were examined using the time-varying (TV) copula method. The return series of the stock markets were divided into two periods, namely before COVID-19 (BC) and after COVID-19 (AC). The novel time-varying flexy copula (TVFC) proposed in the study provides a more flexible structure and produces better results than the TV single copula and the TV optimal copula in comparative analyses. In addition, risk spillovers between market indices were explored using the CoVaR-Copula method. According to the results, the interdependence coefficients of all countries were higher in the AC period than in the BC period with the exception of the China – South Africa pair. Moreover, the dependence coefficient of India with other BRICS countries was quite high compared to the other pairs. Based on the risk spillover results, it was concluded that the Chinese stock market index was the index least affected by the other BRICS countries in the AC period compared to the BC period.
Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN

Hypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related HR lesions and then classifying them using traditional machine learning algorithms. Consequently, those CADx systems required complicated image processing methods and domain-expert knowledge. To address these issues, a new CAD-HR system is proposed to advance depth-wise separable CNN (DSC) with residual connection and a linear support vector machine (LSVM). Initially, the data augmentation approach is used on retina graphics to enhance the size of the datasets. Afterward, this DSC approach is applied to retinal images to extract robust features. The retinal samples are then classified as either HR or non-HR using an LSVM classifier as the final step. The statistical investigation of 9500 retinograph images from two publicly available and one private source is undertaken to assess the accuracy. Several experimental results demonstrate that the CAD-HR model requires less computational time and fewer parameters to categorize HR. On average, the CAD-HR achieved a sensitivity (SE) of 94%, specificity (SP) of 96%, accuracy (ACC) of 95% and area under the receiver operating curve (AUC) of 0.96. This confirms that the CAD-HR system can be used to correctly diagnose HR.
Parameterization of the Autoconversion Process: Kessler-Type, Sundqvist-Type, and Unification

A key process that must be parameterized in atmospheric models of various scales (from large eddy simulation models to cloud-resolving models to global climate models) is the autoconversion process whereby large cloud droplets collect small ones and become embryonic raindrops. Accurate parameterization and physical understanding of this process is especially important for studies of the second indirect aerosol effect. (Rotstayn 2000; Rotstayn and Liu 2005). All the autoconversion parameterizations that have been developed so far can be generically written as
Helical vortex filament motion under the non-local Biot-Savart model

The thin helical vortex filament is one of the fundamental exact solutions possible under the local induction approximation (LIA). The LIA is itself an approximation to the non-local Biot–Savart dynamics governing the self-induced motion of a vortex filament, and helical filaments have also been considered for the Biot–Savart dynamics, under a variety of configurations and assumptions. We study the motion of such a helical filament in the Cartesian reference frame by determining the curve defining this filament mathematically from the Biot–Savart model. In order to do so, we consider a matched approximation to the Biot–Savart dynamics, with local effects approximated by the LIA in order to avoid the logarithmic singularity inherent in the Biot–Savart formulation. This, in turn, allows us to determine the rotational and translational velocity of the filament in terms of a local contribution (which is exactly that which is found under the LIA) and a non-local contribution, each of which depends on the wavenumber, $k$ , and the helix diameter, $A$ . Performing our calculations in such a way, we can easily compare our results to those of the LIA. For small $k$ , the transverse velocity scales as $k^{2}$ , while for large $k$ , the transverse velocity scales as $k$ . On the other hand, the rotational velocity attains a maximum value at some finite $k$ , which corresponds to the wavenumber giving the maximal torsion.
Binary pulsars as probes of relativistic gravity

Until now, most experiments have succeeded in testing relativistic gravity only in its extreme weak-field limit. Because of the strong self-gravity of neutron stars, observations of pulsars in binary systems provide a unique opportunity for probing the strong-field régime of relativistic gravity. The two basic approaches to using binary pulsar measurements as probes of relativistic gravity are reviewed: the phenomenological (‘parametrized post-keplerian’ formalism) and the alternative-theory approach (multidimensional space of possible theories). The experimental constraints recently derived from the actual timing observations of three binary pulsars are summarized. General relativity passes these new, strong-field tests with complete success.
Optical pump-and-probe measurement of the thermal conductivity of nitride thin films

We report on measurements of the thermal conductivity of epitaxially grown nitride thin films. These semiconductor materials are of considerable technological importance for applications such as blue-light emitters and high-power, high frequency electronic devices. Measurements were made in the temperature range of 150–400 K using an optical technique in which the sample is heated with an ultrashort (∼150 fs) light pulse, and a time-delayed probe light pulse is used to measure the temperature of the sample as a function of time. The conductivity of the polycrystalline sample and the alloys are found to be significantly reduced compared to published values for bulk GaN.
Exploring Speed Maximization of Frequency-to-Digital Conversion for Ultra-Low-Voltage VCO-Based ADCs

A frequency-to-digital converter (FDC) performs the role of precise frequency digitization within a voltage-controlled oscillator (VCO)-based ADC. To be compatible with energy-harvesting (EH) Internet-of-Things (IoT) devices, the development of ultra-low-voltage (ULV) FDCs is crucial, where the primary focus must be directed towards the maximization of data throughput under dramatic constraints of reliability and timing variability associated with deep-subthreshold operation. This article investigates the speed maximization of a 0.2V full-custom ULV FDC design, consisting of an array of several parallel XOR-based FDC units, and the multi-rate decimation-filtering digital back-end. At the core of this broad exploration is a high-speed sense-amplify phase sampler (PS) featuring hardware redundancy, capable of sampling the phase of low-voltage-swing inputs. Particular focus is placed on the yield-based reliability-driven design methodology for the sense-amplify phase-sampling circuits running up to 40MS/s and practical variability-mitigation strategies. To overcome the speed bottleneck in the digital back-end, a fully parallel bitstream-processing architectural composition of the computations for summation and decimation are proposed. Experimental verification through measurements of the FDC integrated within a 10-bit 160kHz bandwidth (BW) open-loop VCO-based ADC across clock frequency with supply variations demonstrate robust operation of the first 0.2V multi-phase FDC in the advanced 28nm CMOS process.
Plant eIF4E isoforms as factors of susceptibility and resistance to potyviruses

Potyviruses are the largest group of plant-infecting RNA viruses that affect a wide range of crop plants. Plant resistance genes against potyviruses are often recessive and encode translation initiation factors eIF4E. The inability of potyviruses to use plant eIF4E factors leads to the development of resistance through a loss-of-susceptibility mechanism. Plants have a small family of eIF4E genes that encode several isoforms with distinct but overlapping functions in cell metabolism. Potyviruses use distinct eIF4E isoforms as susceptibility factors in different plants. The role of different members of the plant eIF4E family in the interaction with a given potyvirus could differ drastically. An interplay exists between different members of the eIF4E family in the context of plant–potyvirus interactions, allowing different eIF4E isoforms to modulate each other’s availability as susceptibility factors for the virus. In this review, possible molecular mechanisms underlying this interaction are discussed, and approaches to identify the eIF4E isoform that plays a major role in the plant–potyvirus interaction are suggested. The final section of the review discusses how knowledge about the interaction between different eIF4E isoforms can be used to develop plants with durable resistance to potyviruses.
Higher incubation temperatures produce long-lasting upward shifts in cold tolerance, but not heat tolerance, of hatchling geckos

ABSTRACT Heatwaves are a regular occurrence in Australia, and are predicted to increase in intensity and duration in the future. These changes may elevate temperatures inside lizard nests, shortening the incubation period, so that hatchlings are more likely to emerge during heatwaves. Potentially, developmental plasticity or heat hardening could buffer hatchings from future warming. For example, higher incubation temperatures could shift critical thermal maxima upwards, enabling lizards to withstand higher temperatures. To investigate whether developmental plasticity affects hatchling thermal tolerance, we incubated eggs of the velvet gecko Amalosia lesueurii under two fluctuating incubation treatments to mimic current (mean=24.3°C, range 18.4–31.1°C) and future ‘hot’ (mean=28.9°C, range 19.1–38.1°C) nest temperatures. We maintained the hatchlings under identical conditions, and measured their thermal tolerance (CTmax) aged 14 days and 42 days. We then released hatchlings at field sites, and recaptured individually marked lizards aged 6 months, to determine whether incubation induced shifts in thermal tolerance were transitory or long-lasting. We found that at age 14 days, hatchlings from hot-temperature incubation had higher CTmax [mean=39.96±0.25°C (s.d.)] than hatchlings from current-temperature incubation [mean=39.70±0.36°C (s.d.)]. Hatchlings from the current-incubation treatment also had significantly higher heat hardening capacity [mean=0.79±0.37°C (s.d.)] than hatchlings from hot-temperature incubation treatment [mean=0.47±0.17°C (s.d. )]. However, both of these incubation-induced effects did not persist into later life. By contrast, incubation treatment had significant and long-lasting effects on the cold tolerance of hatchlings. At age 14 days, current-incubated hatchlings tolerated colder temperatures [CTmin=11.24±0.41°C (s.d.)] better than hot-incubated hatchlings [CTmin=14.11±0.25°C (s.d.)]. This significant difference in cold tolerance persisted into the juvenile life stage, and was present in 6-month-old lizards that we recaptured from field sites. This finding indicates that upward shifts in cold tolerance caused by higher incubation temperatures might affect overwinter survival of lizards, but field studies linking fitness to thermal tolerance are necessary to test this idea. Overall, our results suggest that developmental plasticity for heat tolerance is unlikely to buffer lizard populations from higher temperatures. This article has an associated First Person interview with the first author of the paper. Summary: Hatchling geckos from current temperature incubation tolerated cold better than hatchlings from future temperature incubation. The developmental shift in cold tolerance persisted for 6 months, and could therefore influence hatchling survival.
Sugarcane Disease Detection Using CNN-Deep Learning Method

A Machine Learning (ML) technique called deep learning focuses on learning numerous representation layers simultaneously. Deep neural network includes Convolutional Neural Network (CNN). Sugarcane diseases can be prevented and managed more successfully if they are identified properly and quickly. Using a modified deep learning CNN approach this research proposes a method for identifying sugarcane diseases. Sugarcane infections are an issue in the sugar business because they can entirely kill diseased crops, causing financial loss to the farmers if not treated and diagnosed quickly. The study was prompted by the rapid evolution of disease classes and farmer's lack of disease diagnostic and recognition skills. To solve this challenge, machine learning techniques such as computer vision and deep learning can be applied. By separating and categorizing sugarcane images into two groups: healthy and unhealthy/diseased, the trained model is able to fulfill its goal. With a simple CNN with four discrete classes, the analysis shows an accuracy of 98.69% for sugarcane disease detection.
Sampled-data flux estimation in induction machines

This paper proposes a discrete-time flux observer for the induction machine. The observer is based on a discretization of the continuous-time space-phasor flux description facilitated by a Jordan factorization of the system matrix. The proposed observer requires no assumption of stepwise constancy of the input voltage and can be modified to be especially well suited for the case of sinusoidal inputs. This makes the observer an effective tool in, for example, monitoring applications where the proposed observer is shown to yield accurate flux estimates at considerably lower sampling rates than has been possible with conventional methods. Numerical examples, as well as experimental runs, show comparisons of the proposed observer and a well-known discrete-time observer.
Antimicrobial activity of Mimosa caesalpiniifolia Benth and its interaction with antibiotics against Staphylococcus aureus strains overexpressing efflux pump genes

This study aimed to evaluate the antimicrobial activity of the dichloromethane fraction (DCMF) from the stem bark of Mimosa caesalpiniifolia and its effect on the activity of conventional antibiotics against Staphylococcus aureus strains overexpressing specific efflux pump genes. DCMF showed activity against S. aureus, Staphylococcus epidermidis and Candida albicans. Addition of DCMF at subinhibitory concentrations to the growth media enhanced the activity of norfloxacin, ciprofloxacin and ethidium bromide against S. aureus strains overexpressing norA suggesting the presence of efflux pump inhibitors in its composition. Similar results were verified for tetracycline against S. aureus overexpressing tetK, as well as, for ethidium bromide against S. aureus overexpressing qacC. These results indicate that M. caesalpiniifolia is a source of molecules able to modulate the fluoroquinolone‐ and tetracycline‐resistance in S. aureus probably by inhibition of NorA, TetK and QacC respectively.
Complex multiplication of abelian surfaces

The theory of complex multiplication makes it possible to construct certain class fields and abelian varieties. The main theme of this thesis is making these constructions explicit for the case where the abelian varieties have dimension 2. Chapter I is an introduction to complex multiplication, and shows that a general result of Shimura can be improved for degree-4 CM-fields. Chapter II gives an algorithm for computing class polynomials for quartic CM-fields, based on an algorithm of Spallek. We make the algorithm more explicit, and use Goren and Lauterâs recent bounds on the denominators of the coefficients, which yields the first running time bound and proof of correctness of an algorithm computing these polynomials. Chapter III studies and computes the irreducible components of the modular variety of abelian surfaces with CM by a given primitive quartic CM-field. We adapt the algorithm of Chapter II to compute these components. Chapters IV and V construct certain `Weil numbers'. They have properties that are number theoretic in nature and are motivated by cryptography. Chapter IV is joint work with David Freeman and Peter Stevenhagen. Chapter V is joint work with Laura Hitt O'Connor, Gary McGuire, and Michael Naehrig.
Why a standard IAT effect cannot provide evidence for association formation: the role of similarity construction

ABSTRACT Moran and Bar-Anan (Moran, T., & Bar-Anan, Y. (2013). The effect of object-valence relations on automatic evaluation. Cognition and Emotion, 27(4), 743–752) demonstrated that evaluations on a direct measure reflected information on both US valence and CS-US relations, whereas evaluations on an indirect measure (IAT) reflected only information on US valence. This dissociation between measures supposedly tapping into propositional and associative processes apparently supports dual process models of EC. In the present study, we present an alternative explanation of this pattern, based on an interpretation of IAT effects in terms of flexible similarity construction processes. According to this account, processing draws on those features that discriminate between target categories, and help to align targets with attributes in the compatible block. Across two experiments, we consistently found that IAT effects did not reflect rigid associations, but instead depended on whichever information could be used for similarity constructions between targets and attributes in different variants of the IAT. The findings are discussed with regard to theoretical models of EC as well as in reference to prominent accounts of IAT performance.
High-Fat Breakfast Meal Replacement in Overweight and Obesity: Implications on Body Composition, Metabolic Markers, and Satiety

The purpose of this paper was to determine the effect of replacing breakfast with a high-fat drink on fat mass (FM), lean mass (LM), percent body fat (%BF), visceral fat (VAT), resting metabolic rate (RMR), fuel utilization (RER), blood lipids and satiety in overweight and obese adults. Healthy adults (n = 42; 21 Females; body mass index (BMI): 32.8 ± 4.6 kg·m−2) were randomized to control (CON; n = 21) or meal replacement (MRP; n = 22) groups. Body composition was measured using a four-compartment model; RMR and RER were assessed from indirect calorimetry. The MRP (70% fat) was consumed once daily for eight weeks. For males, there was no change (p > 0.05) in FM (mean difference (MD) = 0.41 ± 1.19 kg], %BF MD = 0.50 ± 1.09%, LM MD = −0.64 ± 1.79 kg, or VAT MD = −0.31 ± 1.36 cm for MRP versus CON. Similarly, no differences for females for FM MD = −0.73 ± 1.37 kg, %BF MD = −0.57 ± 1.26%, LM MD = 0.31 ± 1.37 kg, or VAT MD: −0.83 ± 1.2 cm. HDL was significantly reduced in the MRP group for females (adjusted mean change: −6.41 ± 4.44 units, p = 0.018). There was no effect on RMR or RER. Satiety increased in the afternoon for MRP (p = 0.021). Despite high fat, no negative impact on lipids resulted; increased satiety may be beneficial for controlling afternoon cravings, but does not affect body composition.
Chlamydomonas reinhardtii, a Reference Organism to Study Algal–Microbial Interactions: Why Can’t They Be Friends?

The stability and harmony of ecological niches rely on intricate interactions between their members. During evolution, organisms have developed the ability to thrive in different environments, taking advantage of each other. Among these organisms, microalgae are a highly diverse and widely distributed group of major primary producers whose interactions with other organisms play essential roles in their habitats. Understanding the basis of these interactions is crucial to control and exploit these communities for ecological and biotechnological applications. The green microalga Chlamydomonas reinhardtii, a well-established model, is emerging as a model organism for studying a wide variety of microbial interactions with ecological and economic significance. In this review, we unite and discuss current knowledge that points to C. reinhardtii as a model organism for studying microbial interactions.