Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-mode tunable, pulsed, and continuous wave quantum-cascade distributed feedback lasers at λ≅4.6-4.7 μm

Single-mode tunable quantum-cascade distributed feedback lasers emitting at 4.6–4.7 μm wavelength are reported. The lasers employ strained heterostructure material with global strain compensation to provide the large band offset needed for high-performance short wavelength operation. Pulsed, continuously tunable single-mode emission is achieved from 90 to 300 K with a tuning range of 65 nm. Peak output power levels of 100 mW at room temperature are obtained. In continuous-wave operation, current tunable single-mode emission is demonstrated around liquid-nitrogen temperature with a tuning range of 20 nm (over a current range of 450 mA). The maximum output power in continuous wave at 80 K is 150 mW.
Ice nucleation parameterization for global models

Global modeling of ice clouds and the effects of aerosol-related ice nuclei (IN) changes on clouds and climate remains a significant challenge. Here, we describe a parameterization that accounts for the effects of homogeneous ice nucleation as well as two different modes of heterogeneous nucleation in the upper troposphere. The parameterization treats homogeneous nucleation by sulfate aerosol, deposition nucleation as described by the MEYERS et al. (1992) formulation, and immersion nucleation by soot aerosol. Besides air mass temperature and updraft velocity, number concentration of pure sulfate aerosol acting through homogeneous ice nucleation and number concentration of soot aerosol as heterogeneous ice nuclei are explicitly included in the parameterization so that the indirect effect of aerosols on the cirrus clouds (i.e. the effect of increases in aerosol number concentrations) can be described in a global model. In addition the transition from the heterogeneous to homogeneous-dominated nucleation and the competition between homogeneous and heterogeneous nucleation in the transition regime are considered in the parameterization. The parameterization is compared to the results from air parcel model simulations of uplifting and adiabatically cooling clouds and to other recently developed ice nucleation parameterizations.
Improvements in the device characteristics of amorphous indium gallium zinc oxide thin-film transistors by Ar plasma treatment

The effect of Ar plasma treatment on amorphous indium gallium zinc oxide (a-IGZO) thin films was investigated. The net electron carrier concentration (1020–1021cm−3) of the a-IGZO thin films dramatically increased upon their exposure to the Ar plasma compared to that (1014cm−3) of the as-deposited thin film. The authors attempted to reduce the contact resistance between the Pt∕Ti (source/drain electrode) and a-IGZO (channel) by using the Ar plasma treatment. Without the treatment, the a-IGZO thin film transistors (TFTs) with W∕L=50∕4μm exhibited a moderate field-effect mobility (μFE) of 3.3cm2∕Vs, subthreshold gate swing (S) of 0.25V∕decade, and Ion∕off ratio of 4×107. The device performance of the a-IGZO TFTs was significantly improved by the Ar plasma treatment. As a result, an excellent S value of 0.19V∕decade and high Ion∕off ratio of 1×108, as well as a high μFE of 9.1cm2∕Vs, were achieved for the treated a-IGZO TFTs.
Book Review: Configural Frequency Analysis: Methods, Models, and Applications

This is the most comprehensive, up-to-date book available on Configural Frequency Analysis (CFA) since Introduction to Configural Frequency Analysis: The Search for Types and Antitypes in Cross-Classifications by von Eye was published in 1990. Lately, CFA has caught on among substantive researchers especially in the fields of developmental and clinical psychology, with an emerging emphasis on the individual as an active, organizing whole in the person-oriented approach (Bergman, 1998; Bergman & Magnusson, 1997; Magnusson, 2000). For those not familiar with Configural Frequency Analysis, it is a method used to recognize and discover patterns (Hand & Bolton, 2004) in objects, persons, events, and developmental patterns using categorical information. CFA can be used for exploratory pursuits (e.g., data mining) but more importantly for the substantive researcher in finding distinctive cell configurations that deviate from the theoretical expectation in terms of observed frequencies or proportions, as indicated by statistically significant Types (more than expected) and Antitypes (less than expected). The expectation is a priori expressed as a base model. Upon setting up a base model, one of the cellwise tests available for CFA is used while protecting family-wise alpha. The resulting types and antitypes are interpreted, and findings are then used to lend support for existing theoretical hypotheses, to build new models and theories, or to classify groups that are to be used in subsequent analyses. In instances where there are no a priori hypotheses, a model of independence (i.e., a main-effect only model) may be used as a base model. Although it is often used for a relatively small number of variables and a large data set, it can also be used for big but sparse tables as well. The stand-alone program, CFA 2002 for Windows (von Eye, 2001) can be obtained gratis via e-mail from von Eye (voneye@msu.edu), and it is easy to use. An article-length introduction to CFA can be seen in the latest work by von Eye and Gutiérrez Pena (2004). The timing of the book’s arrival is fitting, given increasing interest in CFA among applied researchers and statisticians. The reader will find the book very helpful in understanding and subsequently using CFA in their research. Although this book contains some mathematical formulas and matrices, they are straightforward and easily understandable. Data examples in the book are from real research studies in the fields of clinical, industrial/organizational, educational, and developmental psychology. Moreover, the observed frequencies from the existing studies are presented throughout the book, allowing the reader to confirm or modify using a different set of hypotheses, the reported results in the book. The substantive researcher should have an easy time using the method for their own research. In addition, statisticians and more quantitatively advanced applied researchers will also appreciate the complete, thorough coverage on technical details and advanced discussions on
A Novel Wet Etching Process of Pb(Zr,Ti)O3 Thin Films for Applications in Microelectromechanical System

The wet etching of Pb(Zr,Ti)O3 (PZT) thin films has gained considerable attention in microelectromechanical systems (MEMS) since it is economical and effective compared with dry-etching methods. In this paper, a novel wet-etching process is proposed for PZT thin film patterning using 1BHF:2HCl:4NH4Cl:4H2O solution as the etchant, where NH4Cl is used as an additive to decrease the undercutting of the obtained PZT pattern. According to energy dispersion spectroscopy (EDS) analysis and X-ray diffraction (XRD) patterns, PbClF particles were left as residues on the substrate after etching using 1BHF:2HCl:4NH4Cl:4H2O solution. Therefore, an additional 2HNO3:1H2O etching process was applied to convert PbClF to PbCl2, which can be dissolved completely in deionized water. This process exhibits a high etching rate (0.016 µm/s) and good selectivity over the photoresist and Pt bottom electrode. Using this technique, PZT patterns with acceptable undercutting (1.5:1) can be obtained.
The effect of animal design on jumping performance

Previous workers have shown that the jumping performance of small animals is limited by power requirements, while that of large animals is limited by energy requirements. This is confirmed here, and the theory is extended to include animals that store energy, prior to a jump. Factors affecting jump range for animals of different sizes are discussed. For animals that store energy, a power amplification factor may be calculated, if the animal's range, mass and leg length are known. Alternatively, range may be predicted for an animal of known design. Animals that show a marked increase in jump range with an increase in body size are probably energy storers. Summary The range of large jumping animals will be limited by their ability to produce energy. In order to jump further, a large animal would need to give over a greater proportion of its body mass to jumping muscle. Small animals will be limited by their ability to produce power, but this problem can be overcome by increasing the relative length of the jumping legs or by introducing an energy storage system. Animals showing increased range with increased body size probably use energy storage systems. My thanks are due to Dr H. C. Bennet-Clark and Dr J. F. lles for supervision of this work, to Professor T. R. E. Southwood for accommodation in the Dept of Zoology, Oxford, and to the SERC for financial support.
Real-Time Occupancy Detection System Using Low-Resolution Thermopile Array Sensor for Indoor Environment

Low-Resolution Thermopile Array Sensors are widely used in several indoor applications such as security, intelligent surveillance, robotics, military, and health monitoring systems. It is compact, cost-effective, and offers a low-resolution thermal image of the environment, attracting its use in privacy-focused applications. Many industries migrating towards Industry 4.0 are facing challenges in using sensors and automating the systems. One of the areas in which automation could be implemented is by using sensors to operate the systems smartly based on occupancy. The major challenge in such applications is maintaining privacy; conventional imaging mechanisms using optical camera systems fail to achieve it. The same could be achieved by using thermopile sensors which provide thermal data of the desired region. This generates the possibility to identify the number of people in a specified area without revealing their identity. This paper proposes various approaches to detect human occupancy using a low-resolution infrared thermopile array sensor to keep their identity safe and avoid privacy issues. The proposed system detects IR-emitting objects using a low-resolution thermopile array Grid-EYE sensor (AMG8833). The sensor acquires $8\times 8$ pixels of thermal distribution. These thermal distribution data are subjected to interpolation, filtering, adaptive thresholding, and background suppression to attain the set goal of human detection.
Resource-Restricted Environments Based Memory-Efficient Compressed Convolutional Neural Network Model for Image-Level Object Classification

In the past decade, Convolutional Neural Networks (CNNs) have achieved tremendous success in solving complex classification problems. CNN architectures require an excessive number of computations to achieve high accuracy. However, these models are deficient due to the heavy cost of storage and energy, which prohibits the application of CNNs to resource-constrained edge-devices. Hence, developing aggressive optimization schemes for efficient deployment of CNNs on edge devices has become the most important requirement. To find the optimal approach, we present a resource-limited environment based memory-efficient network compression model for image-level object classification. The main aim is to compress CNN architecture by achieving low computational cost and memory requirements without dropping system’s accuracy. To achieve the said goal, we propose a network compression strategy, that works in a collaborative manner, where Soft Filter Pruning is first applied to reduce the computational cost of the model. In the next step, the model is divided into No-Pruning Layers (NP-Layers) and Pruning Layers (P-Layers). Incremental Quantization is applied to P-Layers due to irregular weights distribution, while for NP-Layers, we propose a novel Optimized Quantization algorithm for the quantization of weights up to optimal levels obtained from the Optimizer. This scheme is designed to achieve the best trade-off between compression ratio and accuracy of the model. Our proposed system is validated for image-level object classification on LeNet-5, CIFAR-quick, and VGG-16 networks using MNIST, CIFAR-10, and ImageNet ILSVRC2012 datasets respectively. We have achieved high compression ratio with negligible accuracy drop, outperforming the state-of-the-art methods.
Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance

The relative abilities of 2, dimensioned statistics — the root-mean-square error (RMSE) and the mean absolute error (MAE) — to describe average model-performance error are examined. The RMSE is of special interest because it is widely reported in the climatic and environmental liter- ature; nevertheless, it is an inappropriate and misinterpreted measure of average error. RMSE is inappropriate because it is a function of 3 characteristics of a set of errors, rather than of one (the average error). RMSE varies with the variability within the distribution of error magnitudes and with the square root of the number of errors (n 1/2 ), as well as with the average-error magnitude (MAE). Our findings indicate that MAE is a more natural measure of average error, and (unlike RMSE) is unambiguous. Dimensioned evaluations and inter-comparisons of average model-performance error, therefore, should be based on MAE.
Chaos in Dynamical Systems: Contents

Preface 1. Introduction and overview 2. One-dimensional maps 3. Strange attractors and fractal dimensions 4. Dynamical properties of chaotic systems 5. Nonattracting chaotic sets 6. Quasiperiodicity 7. Chaos in Hamiltonian systems 8. Chaotic transitions 9. Multifractals 10. Control and synchronization of chaos 11. Quantum chaos.
THE PERIOD-LUMINOSITY RELATION: A HISTORICAL REVIEW

In some ways astronomers are like small children. The high adventure, the furor and excitement they create among themselves is not greatly cared about or understood outside, at least in any immediate way. Of all the discoveries of ground-based astronomy in this century, only the smallest handful can claim to have made the front-page headlines of the world’s newspapers. One such instance came in 1952, when the headlines cried the news that the universe was at least twice as big as hitherto believed. To astronomers, the event signaled a turning point in the histoiy of the cepheid periodluminosity relation. It was the revelation of a major error which had gone undetected in forty years’ work on this subject. The story is an interesting one, in that it illuminates many facets of the scientist at work, persistently groping his way through research via misapprehensions and downright mistakes.
VideoCAD: An Uncertainty-Driven Neural Network for Coronary Artery Disease Screening From Facial Videos

Coronary artery disease (CAD) is highly prevalent worldwide but is challenging to identify due to its hidden symptoms. Facial videos provide a possible means for CAD screening as facial features and skin color changes are associated with CAD risk. However, opposite test results of CAD may be drawn from facial features and skin color changes. A neural network, VideoCAD, is proposed in this work to address this problem. It consists of two modules, PulseCAD and ImageCAD. PulseCAD predicts whether CAD was present based on the facial features in a video frame, and ImageCAD performs CAD prediction based on the pulse-related features in skin color changes. VideoCAD quantifies the uncertainties of the two modules’ predictions before selecting the prediction with lower uncertainty as the final result. VideoCAD is evaluated on 1200 video samples of 200 subjects (50% CAD). Its predictions are in substantial agreement with the ground truths, with both the sensitivity (SE) and specificity (SP) of $>0.88$ . It also outperforms the state-of-the-art methods that only consider the face or pulse features, achieving a >20% increase in Cohen’s Kappa coefficient. This technique may hold promise to achieve opportunistic screening for occult CAD in the community.
Determinants, Pfaffians and Quasi-Free Representations of the CAR Algebra

In this paper we apply the theory of quasi-free states of CAR algebras and Bogolubov automorphisms to give an alternative C*-algebraic construction of the Determinant and Pfaffian line bundles discussed by Pressley and Segal and by Borthwick. The basic property of the Pfaffian of being the holomorphic square root of the Determinant line bundle (after restriction from the Hilbert space Grassmannian to the Siegel manifold, or isotropic Grassmannian, consisting of all complex structures on an associated Hilbert space) is derived from a Fock–anti-Fock correspondence and an application of the Powers–Stormer purification procedure. A Borel–Weil type description of the infinite dimensional Spinc-representation is obtained, via a Shale–Stinespring implementation of Bogolubov transformations.
Assessing Physiological and Psychological Factors Contributing to Stress among Medical Students: Implications for Health

Abstract Background: Physiological responses to stress disturb internal homeostasis, leading to serious health consequences. Medical students experience high stress levels that should be managed promptly to prevent stress-related impacts on students’ health and education. Aim: This study aims to identify the relationship between stress factors, general health, and academic performance. Methods: This study recruited 421 medical students of all academic years. Participants completed an online survey assessing stress levels using a validated 10-item Perceived Stress Scale. Stress was also compared with students’ health and academic performance. Results: We found that 93.6% of our sample experienced moderate to severe stress, and 31% reported increased stress due to the coronavirus disease (COVID-19) pandemic. Except for internship students, stress significantly decreases as students progress each academic year (p < 0.05). Students with higher GPAs and with comorbidities are more stressed. Comorbidities were primarily reported in students in their final years of education with a 4% lower GPA than healthy students. Although we had three stress-related themes (general, academic, and pandemic), students’ perceptions of stress factors were primarily academically related. Conclusions: Students experience high stress levels in their final educational years, which might increase the risk of health issues and low academic performance. It is essential to innovate stress-coping strategies specially designed for medical students and mandatorily provided by all medical colleges and to educate students on the effects of stress on their health.
Asteroids dimensions and the truncated Pareto distribution

In this chapter first the statistics of the standard and truncated Pareto distributions are derived and used to fit empirical values of asteroids diameters from different families, namely, Koronis, Eos and Themis, and from the Astorb database. A theoretical analysis is then carried out and two possible physical mechanisms are suggested that account for Pareto tails in distributions of asteroids diameter.
Discrete Interpolating and Smoothing Spline Functions

This paper uses the results of Anselone and Laurent to carry out discrete interpolation and smoothing, which give rise to discrete natural polynomial spline functions. The discrete interpolation is a generalization of work done by Vaughan and Greville. The discrete smoothing generalizes work done by Whittaker. Both discrete spline interpolation and smoothing are shown to be smoothing processes in a sense defined by Greville. The algorithms developed for the discrete natural cubic spline case are shown to be good computational procedures.
Fundamental Neurochemistry Review: Incorporating a greater diversity of cell types, including microglia, in brain organoid cultures improves clinical translation

Brain organoids have the potential to improve clinical translation, with the added benefit of reducing any extraneous use of experimental animals. As brain organoids are three‐dimensional in vitro constructs that emulate the human brain, they bridge in vitro and in vivo studies more appropriately than monocultures. Although many factors contribute to the failure of extrapolating monoculture‐based information to animal‐based experiments and clinical trials, for the purpose of this review, we will focus on glia (non‐neuronal brain cells), whose functions and transcriptome are particularly abnormal in monocultures. As discussed herein, glia require signals from—and contact with—other cell types to exist in their homeostatic state, which likely contributes to some of the differences between data derived from monocultures and data derived from brain organoids and even two‐dimensional co‐cultures. Furthermore, we highlight transcriptomic differences between humans and mice in regard to aging and Alzheimer's disease, emphasizing need for a model using the human genome—again, a benefit of brain organoids—to complement data derived from animals. We also identify an urgency for guidelines to improve the reporting and transparency of research using organoids. The lack of reporting standards creates challenges for the comparison and discussion of data from different articles. Importantly, brain organoids mark the first human model enabling the study of brain cytoarchitecture and development.
Effects of air cavity on fly-ear inspired directional microphones: a numerical study

The superacute ear of the parasitoid fly Ormia ochracea has inspired the development of a variety of novel miniature directional microphones for sound source localization, in which the effects of air cavity backing the eardrums are often neglected without validation. In the original testing on the fly ear, the integrity of the air space is shown not to be the key to the intertympnal coupling. However, it does not necessarily mean that the tympanum can be treated as in vacuo, and the effects of the air cavity backing the eardrums have yet to be fully understood. In this article, a normalized version of our previous model of air-backed circular membranes is derived to study the conditions under which the air cavity can be indeed neglected. This model is then used to study a fly-ear inspired directional microphone design with two clamped circular membranes mechanically coupled by a bridge. The performance of the directional microphone with air cavity is evaluated in comparison to its counterpart in vacuo. This article not only provides more insights into the fly ear phenomena, but builds a theoretical foundation on whether and how to take the air cavity into account in the design of pressure sensors and directional microphones in general.
A Review: Research Progress of Neural Probes for Brain Research and Brain–Computer Interface

Neural probes, as an invasive physiological tool at the mesoscopic scale, can decipher the code of brain connections and communications from the cellular or even molecular level, and realize information fusion between the human body and external machines. In addition to traditional electrodes, two new types of neural probes have been developed in recent years: optoprobes based on optogenetics and magnetrodes that record neural magnetic signals. In this review, we give a comprehensive overview of these three kinds of neural probes. We firstly discuss the development of microelectrodes and strategies for their flexibility, which is mainly represented by the selection of flexible substrates and new electrode materials. Subsequently, the concept of optogenetics is introduced, followed by the review of several novel structures of optoprobes, which are divided into multifunctional optoprobes integrated with microfluidic channels, artifact-free optoprobes, three-dimensional drivable optoprobes, and flexible optoprobes. At last, we introduce the fundamental perspectives of magnetoresistive (MR) sensors and then review the research progress of magnetrodes based on it.