Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal Profiles of Chainsaw Hollows and Natural Hollows during Extreme Heat Events

Simple Summary Loss of large hollow-bearing trees is a major threat to the persistence of wildlife in agricultural landscapes. To combat this problem, local governments, volunteer environmental organizations, and conservation groups increasingly carve artificial hollows (“chainsaw hollows”) in dead trees, yet little is known about their thermal profiles. We measured the thermal profiles of 13 natural and 45 artificial hollows in the central west of NSW, Australia, over the course of 2 summers. Maximum temperatures and daily temperature ranges within natural hollows and artificial hollows were similar in 2017–2018. During the January 2019 heatwave, temperatures inside chainsaw hollows in dead trees exceeded 35 °C for 6.2 consecutive days. Artificial hollows in dead trees provided little buffering from thermal extremes; when air temperatures peaked at 44.6 °C, hollow temperatures were only 2.4 °C cooler on average than ambient (range: 5.5 °C cooler to 1.0 °C hotter than ambient). Artificial hollows created in dead trees may therefore not provide suitable thermal conditions for hollow-dependent wildlife during hot summers. Thus, retention of large live trees, coupled with revegetation, is crucial for conserving hollow-dependent fauna in agricultural landscapes. Abstract Loss of hollow-bearing trees threatens many hollow-dependent wildlife. To mitigate this process, artificial chainsaw-carved hollows (CHs) are often created in dead trees, yet little is known about their thermal profiles. We measured temperatures inside 13 natural hollows (8 live and 5 dead trees) and 45 CHs (5 live and 40 dead trees) in the central west of NSW, Australia, over the course of 2 summers. Maximum temperatures and daily temperature ranges within natural hollows and artificial hollows were similar in 2017–2018. Hollow temperatures were lower in thicker-walled hollows than in thinner-walled hollows. During the January 2019 heatwave, temperatures inside CHs in dead trees exceeded 4–35 °C higher than the upper limit of the thermal neutral zone of sugar gliders—for 6.2 consecutive days (range 0–9 days). CHs in dead trees provided little buffering from thermal extremes; when air temperatures peaked at 44.6 °C, CHs in dead trees were on average 2.4 °C cooler than ambient (range: 5.5 °C cooler to 1.0 °C hotter than ambient). These results show that CHs created in dead trees may not provide suitable thermal conditions for hollow-dependent marsupials during summer heatwaves. Retention of large live trees, coupled with revegetation, is crucial for conserving hollow-dependent fauna in agricultural landscapes.
Mental Health and COVID-19 in University Students: Findings from a Qualitative, Comparative Study in Italy and the UK

Introduction: COVID-19 restrictions introduced several changes in university academic and social experience. Self-isolation and online teaching have amplified students’ mental health vulnerability. Thus, we aimed to explore feelings and perspectives about the impact of the pandemic on mental health, comparing students from Italy and the UK. Methods: Data were collected from the qualitative portion of “the CAMPUS study”, longitudinally assessing mental health of students at the University of Milano-Bicocca (Italy) and the University of Surrey (UK). We conducted in-depth interviews and thematically analysed the transcripts. Results: The explanatory model was developed from four themes identified across 33 interviews: anxiety exacerbated by COVID-19; putative mechanisms leading to poor mental health; the most vulnerable subgroups; and coping strategies. Generalised and social anxiety resulted from COVID-19 restrictions by being associated with loneliness, excessive time online, unhealthy management of time and space and poor communication with the university. Freshers, international students, and people on the extremes of the introversion/extroversion spectrum, were identified as vulnerable, while effective coping strategies included taking advantage of free time, connection with family and mental health support. The impact of COVID-19 was mostly related to academic issues by students from Italy, whereas to the drastic loss of social connectedness by the UK sample. Conclusions: Mental health support for students has an essential role, and measures that encourage communication and social connectedness are likely to be beneficial.
Particle Transport in Stochastic Media With Multivariate Gamma Statistics: Analytical Results With Application to Atoms in Tokamaks

Neutral particles (atoms, molecules) play an important role in thermonuclear fusion magnetic confinement devices. At the very edge of the plasma, close to the wall, density fluctuations with amplitude comparable to the mean density have been reported. In this work, we analyze the effect of these fluctuations on the transport of neutral particles, using a multivariate Gamma model to describe the spatial correlations of fluctuations. Analytical results are obtained in 1D for the average neutral particle density in the presence of scattering.
Three-dimensional acoustic lenses with axial symmetry

In this paper a technique to design three dimensional (3D) devices to focus acoustic waves composed of scattering elements is proposed. The devices are designed and optimized in two dimensions (2D) with the help of a genetic algorithm and the 2D multiple scattering formalism. The transition from 2D to 3D is made by applying a rotation operation to the optimized design, thus passing from a set of 2D circular scatters to their equivalent 3D concentric rings of circular section and finite dimensions, considerably improving its performance. The method has been applied to the design and theoretical characterization of a single-focus acoustic lens and a tunable lens capable of changing the focal length with frequency. A prototype lens was fabricated using aluminum rings clamped to a rigid frame, obtaining a good agreement between theory and experiment.
An Identification Method for Joint Parameters Based on Finite Element

Aiming to solve the problem of joint surface stiffiness identification,this paper presents a finite element identification method. The method based on finite element simulation and the curve fitting principles, fitting out a curve that closed to simulation results. It can identify the joint surface stifiness effectively and rapidly based on curve fitting of simulation data in sensitivity area. This method avoid the transfer function matrix difficult to test and reverse solve problem. Comparing the results of the proposed method with the substructure synthesis method, it is shown that finite element identification method is effective.
Migration and Demos in the Democratic Firm: An Extension of the State-Firm Analogy

Debates around the state-firm analogy as a route to justifying workplace democracy tend toward a static view of both state and firm and position workplace democracy as the objective. We contend, however, that states and firms are connected in ways that should alter the terms of the debate, and that the achievement of workplace democracy raises a new set of political issues about the demos in the democratic firm and “worker migration” at the boundaries of the firm. Our argument thus contains two key steps: first, drawing on an empirical case study of a worker-owned firm, we enrich the state-firm analogy by developing a more dynamic view of both, focusing on the creation of workplace democracies, worker movement in and out of them, the dynamic meanings of “citizenship” within them, and the status of the unemployed in a world of democratic workplaces. Second, we then argue that in moving to a more sociological view of the state, the things we were comparing begin to show their real-world connections to one another. By going beyond the idealized view of states that has distorted the state-firm analogy debates, we arrive at a more robust view of how widespread workplace democracy might reconfigure basic political relationships in society.
Flexible zero refractive index optical metamaterial with matched impedance

We demonstrate a flexible thin film zero refractive index optical metamaterial with matched impedance to free space and low absorption loss at 1.55 μm. The metallo-dielectric multilayer structure with fishnet geometry was optimized by a genetic algorithm. The fabrication process and characterization approach are described. The experiment results agree well with the theoretical predictions, showing an effective index of neff = 0.072 + 0.51i and an impedance of Zeff/Z0 = 1.009 – 0.021i.
Efficient PV-Based Microinverter With Enhanced ROI for Lower Economic Zone Habitants

In this article, the conceptualization, design, development, and real-field validation of a photovoltaic (PV)-based single-phase microinverter (SP<inline-formula> <tex-math notation="LaTeX">$\mu \text{I}$ </tex-math></inline-formula>) to address three major challenges of rural standalone PV-based electrical systems: 1) to perform efficiently over a wide range of input voltage variations/irradiance; 2) maintains system efficiency within a satisfactory limit even under lightly loaded conditions; and 3) robust and stable operation under harsh/outdoor operating environments has been done. The developed novel dual-stage SP<inline-formula> <tex-math notation="LaTeX">$\mu \text{I}$ </tex-math></inline-formula> adapts the benefits of the interleaved dc–dc boost converter for 180° phase-shifted harmonic cancellation and integration of voltage doubler circuit benefits in lessened transformer’s turn ratio with decreased flux leakage, thus resulting in improved energy conversion efficiency at a reduced magnetic size and Si-GaN. Furthermore, adapted high- and low-frequency switching at the first and second legs of the full-bridge converter, respectively, ensures minimized switching losses even at lightly loaded conditions. Based on a per watt comparison to a 500-W inverter, the proposed SP<inline-formula> <tex-math notation="LaTeX">$\mu \text{I}$ </tex-math></inline-formula> achieves 6.16% and 8.5% higher efficiency at 100% and 10% loading, respectively, at a reduced cost of 9.33% and an increased return on investment (ROI) of 12.23%.
Bayesian solution to the monotone likelihood in the standard mixture cure model

An advantage of the standard mixture cure model over an usual survival model is how it accounts for the population heterogeneity. It allows a joint estimation for the distribution related to the susceptible and non‐susceptible subjects. The estimation algorithm may provide ±∞$$ \pm \infty $$ coefficients when the likelihood cannot be maximized. This phenomenon is known as Monotone Likelihood (ML), common in survival and logistic regressions. The ML tends to appear in situations with small sample size, many censored times, many binary or unbalanced covariates. Particularly, it occurs when all uncensored cases correspond to one level of a binary covariate. The existing frequentist solution is an adaptation of the Firth correction, originally proposed to reduce bias of maximum likelihood estimates. It prevents ±∞$$ \pm \infty $$ estimates by penalizing the likelihood, with the penalty interpreted as the Bayesian Jeffreys prior. In this paper, the penalized likelihood of the standard mixture cure model is considered with different penalties (Bayesian priors). A Monte Carlo simulation study indicates good inference results, especially for balanced data sets. Finally, a real application involving a melanoma data illustrates the approach.
Optimization of Execution for Machine Learning Applications in the Computing Continuum

Today, adoption of Machine Learning (ML) techniques is widespread and is encountered in almost every aspect of our everyday lives. The plethora of IoT devices and the enormous amounts of data that are being generated has led to the evolution of existing and the development of new learning algorithms that aim in leveraging data for driving accurate inference and automated decision-making. In parallel, with the computing continuum paradigm, where heterogeneous and distributed resources are stretching all the way from Cloud to Edge and IoT devices, it is imperative that ML applications reap the performance and efficiency benefits of heterogeneity. However, ML application developers and data scientists are faced with the burden of manually deploying their applications in a manner that is frequently sub-optimal.In this paper, we design and implement an integrated MLOps framework that, initially, enables developers to decompose an ML workflow into its functional steps, which correspond to distinct stages of the development and execution of an ML model. Our developed scheduler is therefore able to efficiently schedule these individual components by considering their specific requirements for computing capacity during the training stage, and for low network latency during data ingestion and model serving. The proposed MLOps framework is evaluated with a proof-of-concept experimentation conducted in a realistic testbed environment. Results show significant benefits in performance, when compared with scheduling the whole ML workflow.
Thermal impedance of SiGe HBTs: Characterization and modeling

Electro-thermal characterization of SiGe HBTs was performed for different operating points. Small-signal simulations with a single-pole and various multi-pole thermal networks are compared with measured data over a wide frequency range. The results show that nodal and recursive thermal networks are unable to match the measured phase of the thermal impedance Zth, while Foster, Cauer and Cauer-type recursive thermal networks are more accurate and flexible for modeling Zth. Furthermore, a guide for the usage of different networks upon the phase of Zth is provided.
Recognizing boundaries of online professional learning communities in an automated discourse analysis approach

Recognizing boundaries of online professional learning communities can help to provide teachers with a meaningful online learning environment that improves their training performance. This study proposed an automated discourse analysis approach for recognizing boundaries of the online learning communities, that combines both Topic Modelling approach (Latent Dirichlet Allocation) and Social Network Analysis. The study examined online discourse data of 1843 teachers participating in an online training program. The findings revealed that teachers mainly responded to others’ posts and the pattern of teachers’ response could be mainly divided into four types. The semantic network formed by discourse unit was high-density with low average network distance and high degree centrality, and the cohesion parameter of the semantic network was relatively stable during the whole process of online discourse. The findings of the study also can provide insights into creating online learning communities and teacher education.
Hemispheric water balance for the IGY

A study of the hemispheric water balance over the northern hemisphere during the IGY covering the mean conditions for the calendar year 1958 is presented. The study includes analyses of the amount of precipitable water, of the vertically integrated water vapor transport vector field and of the divergence of water vapor transport for the hemisphere. Some implications of the water vapor divergence field are deduced which are important for hydrology and oceanography. Finally, the water vapor balance is discussed in the light of various meteorological considerations. DOI: 10.1111/j.2153-3490.1965. tb00209.x
Numerical study on the incompressible Euler equations as a Hamiltonian system: Sectional curvature and Jacobi field

We study some of the key quantities arising in the theory of [Arnold “Sur la geometrie differentielle des groupes de Lie de dimension infinie et ses applications a l’hydrodynamique des fluides parfaits,” Annales de l’institut Fourier 16, 319 (1966)] of the incompressible Euler equations both in two and three dimensions. The sectional curvatures for the Taylor–Green vortex and the ABC flow initial conditions are calculated exactly in three dimensions. We trace the time evolution of the Jacobi fields by direct numerical simulations and, in particular, see how the sectional curvatures get more and more negative in time. The spatial structure of the Jacobi fields is compared to the vorticity fields by visualizations. The Jacobi fields are found to grow exponentially in time for the flows with negative sectional curvatures. In two dimensions, a family of initial data proposed by Arnold (1966) is considered. The sectional curvature is observed to change its sign quickly even if it starts from a positive value.
HLA-I and HLA-II Peptidomes of SARS-CoV-2: A Review

The adaptive (T-cell-mediated) immune response is a key player in determining the clinical outcome, in addition to neutralizing antibodies, after SARS-CoV-2 infection, as well as supporting the efficacy of vaccines. T cells recognize viral-derived peptides bound to major histocompatibility complexes (MHCs) so that they initiate cell-mediated immunity against SARS-CoV-2 infection or can support developing a high-affinity antibody response. SARS-CoV-2-derived peptides bound to MHCs are characterized via bioinformatics or mass spectrometry on the whole proteome scale, named immunopeptidomics. They can identify potential vaccine targets or therapeutic approaches for SARS-CoV-2 or else may reveal the heterogeneity of clinical outcomes. SARS-CoV-2 epitopes that are naturally processed and presented on the human leukocyte antigen class I (HLA-I) and class II (HLA-II) were identified for immunopeptidomics. Most of the identified SARS-CoV-2 epitopes were canonical and out-of-frame peptides derived from spike and nucleocapsid proteins, followed by membrane proteins, whereby many of which are not caught by existing vaccines and could elicit effective responses of T cells in vivo. This review addresses the detection of SARS-CoV-2 viral epitopes on HLA-I and HLA-II using bioinformatics prediction and mass spectrometry (HLA peptidomics). Profiling the HLA-I and HLA-II peptidomes of SARS-CoV-2 is also detailed.
Lonely Today, Lonely Tomorrow: Temporal Dynamics of Loneliness in Everyday Life and its Associations With Psychopathological Symptoms

Although theory emphasizes that loneliness fluctuates in everyday life, most previous studies focused on the general and stable tendency of feeling lonely. In the present study, we used daily diary data collected over two 4-week periods (N1 = 3,309; N2 = 907) to examine different indicators of temporal dynamics of loneliness in everyday life and compare them with temporal dynamics of positive and negative affect. Moreover, we examined associations between temporal dynamics of loneliness and psychopathological symptoms (i.e., stress, anxiety, depression). We found large similarities in the variability, instability, and inertia of loneliness and affect. Moreover, all indicators of temporal dynamics of loneliness were related to psychopathological symptoms. However, these indicators had little added value above the average state and trait level of loneliness in predicting psychopathology. We discuss the potential of assessing the short-term dynamics of loneliness for the early detection of mental health issues.
Model simulation of gravity waves triggered by a density current

In this study, starting from an observational case of internal gravity waves (IGWs) generated at the top of a drainage flow during the SABLES2006 field campaign, we aim to reproduce the IGWs and their origin through mesoscale meteorological modelling. We used the Weather Research and Forecast (WRF) model with fine horizontal resolution (1 km), testing the model capabilities to simulate the IGWs through a WRF fixed physics package option but two different planetary boundary layer schemes, the Mellor‐Yamada‐Janjić (MYJ) and the Yonsei University (YSU). The comparison between model simulations and measurements from a 100 m meteorological tower reveals that the MYJ scheme simulation gives much better results, as it better represents the main features of the density current measured by the tower instruments, although the event is predicted to occur sooner than it is observed to occur. The study has also shown the capacity of this scheme to detect the oscillations in temperature and specific humidity generated by the arrival of the density current. In contrast, the YSU scheme captures the arrival of the current on time but it fails to correctly track its properties and therefore it does not reproduce the gravity waves with the current arrival. In addition, wave parameters calculated from model outputs (MYJ) using the wavelet method reveal waves with longer periods and longer wavelengths (T = 20–22 min and λ = 8–10 km) than those calculated from measurements (T = 9.2 min and λ = 3.5 km) using the same technique. Copyright © 2012 Royal Meteorological Society
A New Estimator for Panel Data Sample Selection Models

In this paper we are concerned with the estimation of a panel data sample selection model where both the selection and the regression equation contain individual effects allowed to be correlated with the observable variables. In this direction, some estimation techniques have been recently developed. We propose a new method for correcting for sample selection bias. Our estimation procedure is an extension of the familiar two-step sample selection technique to the case where one correlated selection rule in two different time periods generates the sample. Some non-parametric components are allowed. The finite sample properties of the estimator are investigated by Monte Carlo simulation experiments.
Supporting EdD Scholar-Practitioners through the COVID-19 Pandemic Using an Ethic of Care

Given the significant challenges PK-12 educational leaders currently face, the purpose of this essay is to orient EdD faculty with Noddings’ (1984/2003) care ethics as a framework for conceptualizing their work and employing care acts to support EdD scholar-practitioners through the COVID-19 pandemic. Practical strategies for this work are suggested. The author argues that Noddings’ (1984/2003) ethic of care provides a timely lens through which EdD faculty’s actions can be guided. Due to the COVID-19 pandemic, faculty have become tasked with supporting their students’ socioemotional well-being in addition to their academic progress. EdD faculty must be responsive to these needs if they are to retain students and effectively train scholar-practitioners to identify and address problems of practice. Stemming from this argument, future research could empirically investigate how employing care ethics affects scholar-practitioners’ well-being, program satisfaction, retention, and completion rates.
Acoustic implications of a thin viscous boundary layer over a compliant surface or permeable liner

This paper considers the implications of a high-Reynolds-number thin parallel boundary layer on fluid–solid interaction. Two types of boundaries are considered: a compliant boundary which is flexible but impermeable, such as an elastic sheet or elastic solid, and a permeable boundary which is rigidly fixed, such as a perforated rigid sheet. The fluid flow consists of a steady flow along the boundary and a small time-dependent perturbation, with the boundary reacting to the perturbation. The fluid displacement due to the perturbation is assumed to be much smaller than the boundary-layer thickness. The analysis is equally valid for compressible and incompressible fluids. Numerical examples are given for compressible flow along a cylindrical duct, for both permeable and compliant cylinder walls. The difference between compliant and permeable walls is shown to be dramatic in some cases. High- and low-frequency asymptotics are derived, and shown to compare well to the numerics. When used with a mass–spring–damper boundary, this model is shown to lead to similar, but not identical, temporal instability with unbounded growth rate to that seen for slipping flow using the Myers boundary condition. It is therefore suggested that a regularization of the Myers boundary condition removing the unbounded growth rate may lead to, or at least inform, a regularization of the model presented here.