Miracle-dz/UniFAR-FTUs huggingface dataset:
Compact filters with adjustable multi-band rejections based on spoof surface plasmon polaritons

Owing to the gorgeous features of planar design, strong field confinement, and compatibility with traditional microwave devices, spoof surface plasmon polaritons (SSPPs) have been developing at a rapid pace in modern microwave technologies. Band-rejection filters, especially multi-band rejection filters, are a significant ecosystem of SSPPs to be designed. Here, we firstly propose compact multi-band rejection filters, including dual-band and triple-band, through the addition of interdigital capacitance loaded loop resonators (IDCLLRs) into the grooves of the corrugated SSPP transmission line (TL). Compared to traditional metamaterial particles like split ring resonators (SRRs) and complementary SRRs (CSRRs) with the same size, IDCLLRs possess excellent merits of lower resonant frequency, larger dynamic range, and more tunable parameters, which enable the proposed device to be more compact and have more freedom for adjusting bandwidths. Both the simulated and experimental results demonstrate the high performance of two multi-band rejection filters, which can provide wide stop-bandwidth (a maximum relative bandwidth of up to 9.5% for the dual-band filter and 8.8% for the triple-band filter) and high isolation (the isolation of both filters can be less than −30 dB and the maximum isolation of up to −60 dB for the dual-band filter and −58 dB for the triple-band filter). The compact SSPP filters with adjustable multi-band rejections may greatly advance progress towards SSPP-based devices and integrated systems.
Bayesian Approach Dealing with Mixture Model Problems

In this dissertation, we focus on two research topics related to mixture models. The first topic is “Adaptive Rejection Metropolis Simulated Annealing for Detecting Global Maximum Regions”, and the second topic is “Bayesian Model Selection for Nonlinear Mixed Effects Model”. In the first topic, we consider a finite mixture model, which is used to fit the data from heterogeneous populations for many applications. An Expectation Maximization (EM) algorithm and Markov Chain Monte Carlo (MCMC) are two popular methods to estimate parameters in a finite mixture model. However, both of the methods may converge to local maximum regions rather than the global maximum when multiple local maxima exist. In this dissertation, we propose a new approach, Adaptive Rejection Metropolis Simulated Annealing (ARMS annealing), to improve the EM algorithm and MCMC methods. Combining simulated annealing (SA) and adaptive rejection metropolis sampling (ARMS), ARMS annealing generate a set of proper starting points which help to reach all possible modes. ARMS uses a piecewise linear envelope function for a proposal distribution. Under the SA framework, we start with a set of proposal distributions, which are constructed by ARMS. This method finds a set of proper starting points, which help to detect separate modes. We refer to this approach as ARMS annealing. By combining together ARMS annealing with the EM algorithm and with the Bayesian approach, respectively, we have proposed two approaches: an EM ARMS annealing algorithm and a Bayesian ARMS annealing approach. EM ARMS annealing implement the EM algorithm by using a set of starting points proposed by ARMS annealing. ARMS annealing also helps MCMC approaches determine starting points. Both approaches capture the global maximum region and estimate the parameters accurately. An illustrative example uses a survey data on the number of charitable donations. The second topic is related to the nonlinear mixed effects model (NLME). Typically a parametric NLME model requires strong assumptions which make the model less flexible and often are not satisfied in real applications. To allow the NLME model to have more flexible assumptions, we present three semiparametric Bayesian NLME models, constructed with Dirichlet process (DP) priors. Dirichlet process models often refer to an infinite mixture model. We propose a unified approach, the penalized posterior Bayes factor, for the purpose of model comparison. Using simulation studies, we compare the performance of two of the three semiparametric hierarchical Bayesian approaches with that of the parametric Bayesian approach. Simulation results suggest that our penalized posterior Bayes factor is a robust method for comparing hierarchical parametric and semiparametric models. An application to gastric emptying studies is used to demonstrate the advantage of our estimation and evaluation approaches.
The photodetector array camera and spectrometer (PACS) for the Herschel Space Observatory

The Photodetector Array Camera and Spectrometer (PACS) is one of the three science instruments for ESA's far infrared and submillimeter observatory Herschel. It employs two Ge:Ga photoconductor arrays (stressed and unstressed) with 16 × 25 pixels, each, and two filled silicon bolometer arrays with 16 × 32 and 32 × 64 pixels, respectively, to perform imaging line spectroscopy and imaging photometry in the 60-210μm wavelength band. In photometry mode, it will simultaneously image two bands, 60-85μm or 85-130μm and 130-210μm, over a field of view of ~ 1.75' × 3.5', with full beam sampling in each band. In spectroscopy mode, it will image a field of ~50"×50", resolved into 5×5 pixels, with an instantaneous spectral coverage of ~1500 km/s and a spectral resolution of ~ 175 km/s. In both modes the performance is expected to be not far from background-noise limited, with sensitivities (5σ in 1h) of ~ 4 mJy or 3 - 20 ×10-18W/m2, respectively. We summarize the design of the instrument and its subunits, describe the observing modes in combination with the telescope pointing modes, report results from instrument level performance tests of the Qualification Model, and present our current prediction of the in-orbit performance of the instrument based on tests done at subunit level.
HFPNet: Super Feature Aggregation Pyramid Network for Maritime Remote Sensing Small-Object Detection

In recent years, with the development of the maritime industry, computer vision tasks based on optical remote sensing images have gained increasing attention in the field of marine remote sensing. However, in complex marine meteorological environments, traditional detection methods often suffer from high rates of missed detections and false alarms for small targets. To address this issue, this article proposes a super feature pyramid network (HFPNet) for detecting marine remote sensing objects, which includes a feature enhancement module (FEM) and a multiscale feature aggregation module (MFM). The FEM can highlight features of small targets and weaken complex background features in detection, the MFM can share high-level and low-level features to better fuse multiscale feature information. Additionally, due to the lack of marine remote sensing object datasets, this article constructs a marine target detection dataset (MTDS) containing six types of marine objects. To address the issue of imbalanced positive and negative samples in the dataset, this article designs a network loss function to accelerate network convergence and improve the accuracy of small-target detection. Compared with other models, HFPNet achieved the highest $\text{mAP}_{0.5}$ of 97.48% and 95.46% on the self-built dataset MTDS and the public dataset NWPU-VHR-10, respectively, after environmental enhancement. At the same time, it also achieved the fastest frames per second (FPS) on the test set. Finally, this article discusses the influence of attention mechanisms and postprocessing methods on HFPNet and obtains the best small-target detection model.
Measuring the motility and drag forces acting on biological particles using optical tweezers

Using absolutely calibrated optical tweezers, we make quantitative measurements of the motility force of Escherichia coli (E. coli) by measuring the change in momentum of the deflected beam. By tracking the position of the particle, in addition to the optical force measurements, it should be possible to simultaneously calculate the motility force and drag. In a simple Gaussian beam optical trap away from the sample chamber E. coli tends to align and swim along the beam axis, which can make tracking the particle position and measuring the force difficult. We use a 3-D optical force detection system to measure the absolute force on the particle, allowing us to measure the motility force of E. coli in a simple Gaussian beam. By using a line-shaped trap, it is possible to align E. coli transverse to the beam axis, facilitating easy particle position measurement. The investigated methods are not specific to E. coli and could be applied to other motile organisms, the study of wall effects and bio-films.
COMBINING FUZZY PROBABILITY AND FUZZY CLUSTERING FOR MULTISPECTRAL SATELLITE IMAGERY CLASSIFICATION

In practice, the classification algorithms and the initialization of the clusters and the initial centroid of clusters have great influence on the stability of the algorithms, dealing time and classification results. Some algorithms are used commonly in data classification, but their disadvantages are low accuracy and unstability such as k-Means algorithm, c-Means algorithm, Iso-data algorithm. This paper proposes a method of combining fuzzy probability and fuzzy clustering algorithm to overcome these disadvantages. The method consists of two steps, first to calculate the number of clusters and the centroid of clusters based fuzzy probability, then to use fuzzy clustering algorithm to land-cover classification. The results showed that, the accuracy of the land cover classification using multispectral satellite images according to the developed method significantly increases compared with various algorithms such as k-Means, Iso-data.
Examining Elementary Teachers’ Engineering Self-Efficacy and Engineering Teacher Efficacy

Research indicates that teacher efficacy influences student achievement and is situation specific. With the Next Generation Science Standards calling for the incorporation of engineering practices into K–12 classrooms, it is important to identify teachers’ engineering teaching efficacy. A study of K–5 teachers’ engineering self-efficacy and engineering teaching efficacy revealed that that they have low engineering self-efficacy and low teacher efficacy related to engineering pedagogical content knowledge. Additionally, significant differences existed in self-efficacy levels based on gender, ethnicity, Title I school status, and grade level taught.
Resonant Light Scattering from Semiconductor Quantum Dots

In this work, resonant laser spectroscopy has been utilized in two major projects – resonance fluorescence measurements in solid-state quantum-confined nanostructures and laser-induced fluorescence measurements in gases. The first project focuses on studying resonant light-matter interactions in semiconductor quantum dots “artificial atoms” with potential applications in quantum information science. Of primary interest is the understanding of fundamental processes and how they are affected by the solid-state matrix. Unlike atoms, quantum dots are susceptible to a variety of environmental influences such as phonon scattering and spectral diffusion. These interactions alter the desired properties of the scattered light and hinder uses in certain single photon source applications. One application of current interest is the use of quantum dots in quantum repeaters for which two-photon interference is key. Motivated by such an application we have explored the limits imposed by environmental effects on two quantum dots in the same sample, the scattered light from which is being interfered. We find that both one-photon and twophoton interference, although substantial, are affected in a variety of ways, in particular by spectral diffusion. These observations are discussed and compared with a theoretical model. We further investigated correlations in pulsed resonance fluorescence, and found significant unexpected spectral and temporal deviations from those studied under continuous wave excitation. Under these conditions, the scattered light exhibits Rabi oscillations and photon anti-bunching, while maintaining a rich spectrum containing many spectral features. These observations are discussed and compared with a theoretical model. In the second project, the focus is on the investigation of the possibility of detecting N2 ions in air using laser induced fluorescence, with potential applications in detection of fissile materials at a distance. A photon-counting analysis reveals that the fluorescence decay
Structural Equation Modeling: Foundations and Extensions (Advanced Quantitative Techniques in the Social Sciences Series, Vol. 10.) by David Kaplan

In his encompassing, time-perspective review of some books on structural equation modeling (SEM), Steiger (2001) distinguished two categories in which almost all such books fall: (a) low-level introductory textbooks that are refrained from any technicalities like matrix algebra and (b) edited volumes written around a unified theme. Kaplan’s book does not fall in these categories: With its intermediate level, its broad coverage in contents, and the refreshing topics it brings over the footlights, it reaches out beyond the far too many introductory books in the field. Steiger (2001) also enumerated seven topics that anyone should know about and that should be addressed in any introductory textbook: (a) equivalent models and path reversibility [not covered by Kaplan], (b) nonconvergence and local minima [not covered], (c) power and sample size analysis, (d) proper reporting techniques [not covered], (e) violation of statistical assumptions, (f) standardized model problems and paradoxes [latter issue not covered], and (g) the analysis of correlations [not explicitly covered]. Although Kaplan has not written a prefatorial textbook, the annotated enumeration shows that it is not a reference book either. In that respect, Bollen (1989) is still the best source, but desperately awaits an update to cover recent developments. Kaplan’s work, however, can be viewed partly as an “updated” volume in the sense that it handles the progress and unfolding of SEM developments since the 1990s (e.g., advancements in the treatment of missing values, multilevel analysis, latent variable mixed modeling, and growth curve modeling). After a compact treatment of the underlying theory, Kaplan illustrates many such issues with a disSTRUCTURAL EQUATION MODELING, 10(2), 323–331 Copyright © 2003, Lawrence Erlbaum Associates, Inc.
The Alignment of Circular Economy Business Models (CEBM) with the Strategies of Small and Micro Enterprises Operating in Malta

This paper sets out preliminary findings for research investigating, from a dynamic viewpoint, how small and micro enterprises operating in the small island state of Malta align their business strategies with Circular Economy Business Models (CEBM). The aim is to establish an analytical framework evaluating their process of alignment. These businesses are a major economic driver for the island. In 2021, out of the 55,950 registered businesses in Malta, 52,674 were micro-firms and 2,686 were small businesses (NSO 2021). The study applies grounded theory methodology, using Corbin and Strausss conditional matrix (2015) and Charmazs constructivist approach (2006). To understand their implementation of circular practices, interpretative, in-depth interviews were carried out with five owners-managers in the service, logistics, manufacturing, retail, and wholesale sectors. The research postulates an early conceptual model showing how a set of contextual conditions influences the alignment of CEBM with the strategies of businesses in Malta. Factors influencing CEBM adoption include owner-managers personal traits, organisational factors, and external factors. The findings presented are part of a larger study mapping common alignment paths pursued by firms in the circular economic shift. It offers recommendations to owners-managers, policymakers, and academic researchers. Few studies have yet focused on the alignment between CEBM and the business strategy of firms in small island states. Generally, studies concentrate on larger businesses in bigger countries. This research study adds significantly to existing knowledge and academic literature.
Classification of Extreme Cold Incursions over South America

Cold-air incursions across South America present a variety of problems, sometimes by advancing to the Amazon basin and causing agricultural losses related to extreme low-temperature events. The synoptic conditions that produce cold-air incursions are relatively well understood; however, the most affected region depends on the route by which cold air spreads across the continent. Therefore, the classification of extreme cold-air incursions allows a better understanding of the particularities directly related to the aforementioned losses. In this work, similarities and differences among extreme cold surges were found through time series correlation of anomaly temperatures in four selected areas and compositing techniques from ERA-Interim reanalysis datasets, resulting in three distinct patterns: meridional penetration (MP), meridional restriction (MR), and east penetration (EP). The patterns identified here enable a more detailed understanding of the synoptic patterns and forcing mechanisms associated with extreme cold-air incursions and therefore can be used for operational weather forecasting.
Electromagnetic Marchenko imaging in 1D for dissipative media

We present a one-dimensional lossless scheme to compute an image of a dissipative medium from two single-sided reflection responses. One reflection response is measured at or above the top reflector of a dissipative medium and the other reflection response is computed as if measured at or above the top reflector of a medium with negative dissipation which we call the effectual medium. These two reflection responses together can be used to construct the approximate reflection data of the corresponding lossless medium by multiplying and taking the square root in time domain. The corresponding lossless medium has the same reflectors as the dissipative medium. Then the constructed reflection data can be used to compute the focusing wavefield which focuses at the chosen location in subsurface of the dissipative medium. From the focusing function and constructed reflection response the Green’s function for a virtual receiver can be obtained. Because the up- and downgoing parts of the Green’s function are retrieved separately, these are used to compute the image. We show with an example that the method works well for a sample in a synthesized waveguide that could be used for measurements in a laboratory.
Feed Utilization and Growth Performance of Tanzania Shorthorn Zebu Fed Untreated or Urea Treated Rice Straws as Hay Replacement in Traditional Feedlot System

: This study evaluated the effects of complete or partial replacement of Cenchrus ciliaris hay with untreated or urea treated rice straws on feed intake, growth performance, feed conversion ratio (FCR) and gross margin of Tanzania Shorthorn Zebu (TSHZ) cattle under feedlot condition. A total of 50 bulls with age of 2.5 - 3.0 years and mean initial weight of 132.4 ± 26.7 kg were assigned randomly to five treatments i.e. 100% Cenchrus ciliaris hay (CCH), 100% untreated rice straws (URS), 100% urea treated rice straws (TRS), 50% untreated rice straw + 50% C. ciliaris hay (URH) and 50% treated rice straw + 50% C. ciliaris (TRH). All animals were supplemented with a diet comprised of 53% maize bran, 25% molasses, 20% sunflower seed cake, 1.5% mineral premix and 0.5% table salt. The results show that average daily gain and weight gain did not differ (p > 0.05) among the treatments. However, animals on TRH showed the highest growth rate (770.0 ± 0.1 g/day) and weight gain (64.7 ± 4.4 kg), followed by those on TRS (growth rate = 725.0 ± 0.1 g/day, weight gain = 60.9 ± 4.4 kg) while those on URS had the lowest growth rate (599.0 ± 0.1 g/day) and weight gain (50.3 ± 4.4 kg). Animals fed TRS (9.8 ± 0.1) and TRH (8.9 ± 0.1) had lower (p ≤ 0.001) FCR than those fed CCH (10.3 ± 0.1), URS (11.9 ± 0.1) and URH (10.4 ± 0.1). The highest gross margin was obtained on animals under TRS (TZS 154,293.00) while the lowest was found on animals under CCH (TZS 120,450.00). Partial or complete replacement of hay with treated or untreated rice straws resulted into higher growth performance than feeding hay alone. Feeding animals with urea treated rice straws resulted into higher growth performance and better feed utilization compared to feeding hay or untreated rice straws. It is concluded that complete replacement of hay with urea treated rice straws resulted into high growth rate, lower FCR and high gross margin, hence, it is recommended as the best basal diet for fattening of TSHZ under traditional feedlot system.
OPERATOR METHOD FOR A DUAL RISK MODEL WITH BARRIER STRATEGY

In this paper, we investigate the dual of a Sparre Andersen model perturbed by diffusion under a barrier strategy, in which innovation inter-arrival times have a generalized Erlang ( ) distribution. Integro-differential equations with certain boundary conditions for the expected total discounted dividends are derived. Using an algebraic operator method, we derive a defective renewal equation for the expected total discounted dividends until ruin. The special case where the innovation times are Erlang (2) distribution and the profit is exponential distribution is considered in some details.
Complex bend: Strong-focusing magnet for low-emittance synchrotrons

Modern synchrotron light sources are competing intensively to increase x-ray brightness and, eventually, approach the diffraction limit, which sets the final goal of lattice emittance. All recent synchrotron facility upgrades follow the multibend achromat approach by arranging small horizontal beta function and dispersion inside discrete bending dipoles. In this paper we propose a concept of a lattice element that we call “complex bend,” which has the potential of becoming a main building block for low emittance lattices. The complex bend is a sequence of dipole poles interleaved with strong alternate focusing so as to maintain the beta function and dispersion oscillating at low values. Comprising the ring lattice with complex bends, instead of regular dipoles, will minimize the H-function and reduce horizontal emittance while localizing bending to a small fraction of the storage ring circumference, which should provide more space for insertion devices. In this paper we present the details of the complex bend, considerations regarding the choice of optimal parameters, and thoughts for its practical realization. We focus here on complex bend physics and engineering design, rather than integration of this complex bend into a specific ring lattice.