Miracle-dz/UniFAR-FTUs huggingface dataset:
Similarity search over time series and trajectory data

Time series data have been used in many applications, such as financial data analysis and weather forecasting. Similarly, trajectories of moving objects are often used to perform movement pattern analysis in surveillance video and sensor monitoring systems. All these applications are closely related to similarity-based time series or trajectory data retrieval. In this dissertation, various similarity models are proposed to capture the similarities among time series and trajectory data under various circumstances and requirements, such as the appearance of noise and local time shifting. A novel representation, called multi-scale time series histograms , is proposed to answer pattern existence queries and shape match queries. Earlier proposals generally address one or the other; multi-scale time series histograms can answer both types, which offers users more flexibility. A metric distance function, called Edit distance with Real Penalty (ERP), is proposed that can support local time shifting in time series and trajectory data. A second distance function, Edit Distance on Real sequence (EDR) is proposed to measure the similarity between time series or trajectories with local time shifting and noise. Since the proposed similarity models are computationally expensive, several indexing and pruning methods are proposed to improve the retrieval efficiency. For multi-scale time series histograms, A multi-step filtering process is introduced to improve the retrieval efficiency without introducing false dismissals. For ERP, a framework is developed to index time series or trajectory data under a metric distance function, which exploits the pruning power of lower bounding and triangle inequality. For EDR, three pruning techniques—mean value Q-grams, near triangle inequality, and trajectory histograms—are developed to improve the retrieval efficiency.
Sources and mechanisms of modality-specific distraction in visual short-term memory

ABSTRACT Visual short-term and working memory can be disrupted by irrelevant, distracting input occurring after encoding. Distractors similar to the original memory are known to be interfering, but it is unclear whether dissimilar distractors have the same disruptive effect. The presence of dissimilar distraction would be problematic for views of similarity-based interference, hence the present study investigated modality-specific distraction using a procedure that required participants to compare single target and probe objects over a delay. An irrelevant distractor could be presented during the delay separating the target and probe, but it varied in its similarity to the target. In four experiments, recognition was disrupted by the presence of a distractor, even when the distractors were highly dissimilar to the target. Furthermore, the interference effect was not reduced when the same distractors were repeatedly used throughout the experiment, and interference from dissimilar distractors was only lessened when it was extremely predictable. These findings indicate that susceptibility to dissimilar distraction is a persistent limitation in visual short-term memory.
ON THE ESTIMATION OF SURVIVAL FUNCTION UNDER RANDOM CENSORSHIP

ABSTRACT The paper deals with an improvement of the well-known Kaplan–Meier estimator of survival function when the censoring mechanism is random and independent of the failure times. Small sample size properties of the new estimator, as well as the original Kaplan–Meier estimator are inspected by means of Monte Carlo simulations. It follows from the simulations that the proposed estimator prevails with respect to some basic statistical characteristics.
Fault Detection in Rotating Machinery Based on Sound Signal Using Edge Machine Learning

Fault detection at the early stage is very important in modern industrial processes to avoid failure with life-threatening results and to reduce the cost of maintenance and machine downtime. In this paper, we present a workflow for building a fault diagnosis system based on acoustic emission (AE) using machine learning (ML) techniques. Our fault diagnosis approach is implemented on an embedded device with the internet of things (IoT) connectivity for real-time faults detection and classification in rotating machines. The achieved accuracy for our approach with a fine decision tree ML model is 96.1%.
Asymptotic theory for imaging the attenuation factor Q

To describe accurately the propagation of elastic waves for characterizing and monitoring hydrocarbon reservoirs, as well as to obtain improved earth models, it is important to take into account seismic attenuation. We describe a method to estimate anelastic medium properties by a complete SH-waveform inversion. We use an optimization approach based on the iterative minimization of the mismatch between the seismic data and the computed response. To obtain a fast analytical imaging procedure, we include an asymptotic theory for attenuation in a linearized inverse scattering formulation. The forward modeling is solved by the Born approximation for a smooth and attenuative background medium. An asymptotic ray-tracing method is used to calculate traveltime, amplitude, and attenuation between source, receiver, and scattering points. The resulting method is computationally efficient and allows for a variety of data-acquisition geometries, including those with redundant or incomplete source-receiver coverage. Synthetic examples with realistic surface-to-surface geometry show an acceptable convergence in a few iterations when anomaly perturbations are less than 10% of the reference values and when associated diffracting structures are smaller than one-tenth of the predominant seismic wavelength. Through there remains the fundamental trade-off between density and shear modulus, the iterative asymptotic inversion is able to recover the elastic parameters (density and shear modulus) and the attenuation factor.
STATE‐DEPENDENT MODELS: A GENERAL APPROACH TO NON‐LINEAR TIME SERIES ANALYSIS

We construct a general class of non‐linear models, called ‘state‐dependent models’, which have a very flexible non‐linear structure and which contain, as special cases, bilinear, threshold autoregressive, and exponential autoregressive models. We describe a sequential type of recursive algorithm for identifying state‐dependent models, and show how such models may be used for forecasting and for indicating specific types of non‐linear behaviour.
Toward an Improved Surface Roughness Parameterization Model for Soil Moisture Retrieval in Road Construction

In passive microwave remote sensing, the estimation of the surface roughness parameter is a significant obstacle for soil moisture (SM) retrieval. For a given SM content, the geometric soil surface roughness has been shown to have a large impact on the surface emission at L-band frequency, which affects the SM retrieval success when using the information observed from the radiometer and is represented through the so-called the surface roughness parameter (<inline-formula> <tex-math notation="LaTeX">$H_{R}$ </tex-math></inline-formula>). Moreover, no previous study has examined the effect of this factor in the context of road construction, where the geometric soil surface roughness is affected by the compaction process, resulting in a substantial change in roughness before and after compaction. Accordingly, a series of experiments at various compaction levels and SM contents was performed for a sand subgrade material in order to identify their effects on <inline-formula> <tex-math notation="LaTeX">$H_{R}$ </tex-math></inline-formula>. The soil brightness temperature (TB) was measured using an L-band radiometer at different incidence angles and a laser profiler was used to measure the surface roughness standard deviation (<inline-formula> <tex-math notation="LaTeX">$\sigma$ </tex-math></inline-formula>) before and after compaction. The results of this article have demonstrated that the incidence angle (<inline-formula> <tex-math notation="LaTeX">$\theta$ </tex-math></inline-formula>) and SM both affect <inline-formula> <tex-math notation="LaTeX">$H_{R}$ </tex-math></inline-formula> and its relation to the geometric soil surface roughness. Importantly, these factors are not accounted for by existing models. Consequently, a modified surface roughness parameter (<inline-formula> <tex-math notation="LaTeX">$H_{R}$ </tex-math></inline-formula>) model, based on the traditional Choudhury model, was developed to include the contribution of these two factors, and its impact on the accuracy of SM retrieval results tested. Specifically, it was shown that it is possible to obtain SM retrieval results with an accuracy of 0.04 cm3/cm3 at almost all incidence angles using either dual-polarization [both horizontal (H) and vertical polarization (V)] or only vertical polarization observations. The modified surface roughness parameter (<inline-formula> <tex-math notation="LaTeX">$H_{R}$ </tex-math></inline-formula>) model has improved the performance of the SM retrieval model to achieve an accuracy of 0.04 cm3/cm3, whereas the traditional Choudhury model achieved an accuracy of only 0.05 cm3/cm3.
Spline Interpolation and Smoothing on the Sphere

We extend the notion of periodic polynomial splines on the circle and thin plate splines on Euclidean d-space to splines on the sphere which are invariant under arbitrary rotations of the coordinate system. We solve the following problem: Find $u \in \mathcal{H}_m (S)$, a suitably defined reproducing kernel (Sobolev) space on the sphere S to, A) minimize $J_m (u)$ subject to $u(P_i ) = z_i $, $i = 1,2, \cdots ,n$, and B) minimize \[ \frac{1} {n}\sum\limits_{j = 1}^n {\left( {u\left( {P_i } \right) - z_i } \right)^2 } + \lambda J_m (u), \] where \[ \begin{gathered} J_m (u) = \int_0^{2\pi } {\int_0^\pi {\left( {\Delta ^{{m / 2}} u(\theta ,\phi )} \right)} } ^2 \sin \theta d\theta d\phi ,\quad m{\text{ even}} \\ = \int_0^{2\pi } {\int_0^\pi {\left\{ {\frac{{\left( {\Delta ^{{{(m-1)} / 2}} u} \right)_\phi ^2 }} {{\sin ^2 \theta }} + \left( {\Delta ^{{{(m-1)} / 2}} u} \right)_\theta ^2 } \right\}} } \sin \theta d\theta d\phi ,\quad m\,{\text{odd}}. \\ \end{gathered} \] Here $\Delta $ is the Laplace–Beltrami operator on the sphere and $J_m (u)$ is the natural analogue on the sphere, of the quadratic functional $\int_0^{2\pi } {\left( {u^{(m)} (\theta )} \right)} ^2 d\theta $ on the circle, which appears in the definition of periodic polynomial splines. $J_m (u)$ may also be considered to be the analogue of \[ \sum\limits_{j = 0}^m {\left( {\begin{array}{*{20}c} m \\ j \\ \end{array} } \right)} \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {\left( {\frac{{\partial ^m u}} {{\partial x^j \partial y^{m - j} }}} \right)} } ^2 dxdy \] appearing in the definition of thin plate splines on the plane. The solution splines are obtained in the form of infinite series, which do not appear to be convenient for certain kinds of computation. We then replace $J_m $ in A) and B) by a quadratic functional $Q_m $ which is topologically equivalent to $J_m $ on $\mathcal{H}_m (S)$ and obtain closed form solutions to the modified problems which are suitable for numerical calculation, thus providing practical pseudo-spline solutions to interpolation and smoothing problems on the sphere. Convergence rates of the splines and pseudo-splines will be the same. A number of results established or conjectured for polynomial and thin plate splines can be extended to the splines and pseudo-splines constructed here.
Advances in Genetic Engineering in Improving Photosynthesis and Microalgal Productivity

Even though sunlight energy far outweighs the energy required by human activities, its utilization is a key goal in the field of renewable energies. Microalgae have emerged as a promising new and sustainable feedstock for meeting rising food and feed demand. Because traditional methods of microalgal improvement are likely to have reached their limits, genetic engineering is expected to allow for further increases in the photosynthesis and productivity of microalgae. Understanding the mechanisms that control photosynthesis will enable researchers to identify targets for genetic engineering and, in the end, increase biomass yield, offsetting the costs of cultivation systems and downstream biomass processing. This review describes the molecular events that happen during photosynthesis and microalgal productivity through genetic engineering and discusses future strategies and the limitations of genetic engineering in microalgal productivity. We highlight the major achievements in manipulating the fundamental mechanisms of microalgal photosynthesis and biomass production, as well as promising approaches for making significant contributions to upcoming microalgal-based biotechnology.
Protection from T cell-dependent colitis by the helminth-derived immunomodulatory mimic of transforming growth factor-β, Hp-TGM

Abstract In animal models of inflammatory colitis, pathology can be ameliorated by several intestinal helminth parasites, including the mouse nematode Heligmosomoides polygyrus. To identify parasite products that may exert anti-inflammatory effects in vivo, we tested H. polygyrus excretory–secretory (HES) products, as well as a recombinantly expressed parasite protein, transforming growth factor mimic (TGM), that functionally mimics the mammalian immunomodulatory cytokine TGF-β. HES and TGM showed a degree of protection in dextran sodium sulphate-induced colitis, with a reduction in inflammatory cytokines, but did not fully block the development of pathology. HES also showed little benefit in a similar acute trinitrobenzene sulphonic acid-induced model. However, in a T cell transfer-mediated model with recombination activation gene (RAG)-deficient mice, HES-reduced disease scores if administered throughout the first 2 or 4 weeks following transfer but was less effective if treatment was delayed until 14 days after T cell transfer. Recombinant TGM similarly dampened colitis in RAG-deficient recipients of effector T cells, and was effective even if introduced only once symptoms had begun to be manifest. These results are a promising indication that TGM may replicate, and even surpass, the modulatory properties of native parasite HES.
Impacts of Proanthocyanidin Binding on Conformational and Functional Properties of Decolorized Highland Barley Protein

The impacts of interaction between proanthocyanidin (PC) and decolorized highland barley protein (DHBP) at pH 7 and 9 on the functional and conformational changes in DHBP were investigated. It was shown that PC strongly quenched the intrinsic fluorescence of DHBP primarily through static quenching. PC and DHBP were mainly bound by hydrophobic interactions. Additionally, free sulfhydryl groups and surface hydrophobicity obviously decreased in DHBP after combining with PC. The zeta potential of DHBP–PC complexes at pH 7 increased significantly. A change in the structure of DHBP was caused by interactions with PC, resulting in an increase in the number of β-sheets, a decrease in the number of α-helixes, and a spectral shift in the amide Ⅱ band. Furthermore, the presence of PC enhanced the foaming properties and antioxidant activity of DHBP. Overall, this study suggests that DHBP–PC complexes at pH 7 could be designed as a stable additive, and illustrates the potential applications of DHBP–PC complexes in the food industry.
What Does “Going on the Record” Mean for Critical Media Literacy? Examining Informed Consent in Serial to Trouble Podcasts as Pedagogy

Background/Context: Considering that the rise in popularity of podcasts as ubiquitous forms of entertainment mirrors a rise in the use of podcasts as curricular texts, this research explores the need for critical listening practices within and beyond the classroom. Specifically, we draw from our overlapping identities as podcast listeners, teacher-educators, and literacy researchers to trouble how descriptions of the informed consent process in podcast journalism contrast with those of qualitative ethnographic research, which is significant because of how well-produced narrative podcasts resemble ethnographic products, particularly in classroom contexts. We center Serial podcast because of its popularity and significance to the podcast genre, and how clearly the show describes instances for gathering journalistic consent. Purpose/Objective/Research Question/Focus of Study: Thinking with and through critical media literacy, we address three research questions: (1) How can a discourse analysis of Serial inform critical listening practices in literacy education? (2) What can a discourse analysis of Serial teach us about informed consent? (3) What might an analysis of a podcast reveal about values and tensions in the fields of journalism and social science research? We hope that engaging with these questions might contribute to how we take up critical listening practices that critical media literacy calls for and, in turn, be informative for teacher-educators seeking to enact and encourage critical media pedagogy. Research Design: In this study, we utilize discourse analysis. We identified and transcribed six scenes from Serial, Season 3, and related media. We selected and organized this data, which Brinkmann referred to as “stumble data,” via an abductive method we dub “fortuitous listening and viewing. ” We then analyzed the data via Gee’s discourse organization. Conclusions/Recommendations: Our findings indicate a tension between podcast journalism and ethnographic research, further delineated as a tension between fidelity to the story versus fidelity to the protection of participants. In some ways, podcast journalism well demonstrates the kind of positive difference-making that critical qualitative researchers aspire to. In other ways, podcast journalism could benefit from better protecting sources from harm in the way that university institutional review boards are designed to help protect participants. Furthermore, considering these tensions is a valuable site for critical analysis, particularly by student and teacher listeners in classroom contexts in which podcasts are being used as curricular texts. We invite fellow educators to join us in designing pedagogy that not only encourages and supports the inclusion of podcasts in the classroom, but also helps to foster a critical framework for engaging in the how and why of podcast journalism.
The uniqueness and approximation of a positive solution of the Bardeen–Cooper–Schrieffer gap equation

In this paper we study the Bardeen–Cooper–Schrieffer energy gap equation at finite temperatures. When the kernel is positive representing a phonon-dominant phase in a superconductor, the existence and uniqueness of a gap solution is established in a class which contains solutions obtainable from bounded domain approximations. The critical temperatures that characterize superconducting–normal phase transitions realized by bounded domain approximations and full space solutions are also investigated. It is shown under some sufficient conditions that these temperatures are identical. In this case the uniqueness of a full space solution follows directly. We will also present some examples for the nonuniqueness of solutions. The case of a kernel function with varying signs is also considered. It is shown that, at low temperatures, there exist nonzero gap solutions indicating a superconducting phase, while at high temperatures, the only solution is the zero solution, representing the dominance of the normal phas.
Thermal management and packaging of wide and ultra-wide bandgap power devices: a review and perspective

Power semiconductor devices are fundamental drivers for advances in power electronics, the technology for electric energy conversion. Power devices based on wide-bandgap (WBG) and ultra-wide bandgap (UWBG) semiconductors allow for a smaller chip size, lower loss and higher frequency compared with their silicon (Si) counterparts, thus enabling a higher system efficiency and smaller form factor. Amongst the challenges for the development and deployment of WBG and UWBG devices is the efficient dissipation of heat, an unavoidable by-product of the higher power density. To mitigate the performance limitations and reliability issues caused by self-heating, thermal management is required at both device and package levels. Packaging in particular is a crucial milestone for the development of any power device technology; WBG and UWBG devices have both reached this milestone recently. This paper provides a timely review of the thermal management of WBG and UWBG power devices with an emphasis on packaged devices. Additionally, emerging UWBG devices hold good promise for high-temperature applications due to their low intrinsic carrier density and increased dopant ionization at elevated temperatures. The fulfillment of this promise in system applications, in conjunction with overcoming the thermal limitations of some UWBG materials, requires new thermal management and packaging technologies. To this end, we provide perspectives on the relevant challenges, potential solutions and research opportunities, highlighting the pressing needs for device–package electrothermal co-design and high-temperature packages that can withstand the high electric fields expected in UWBG devices.
Increase in Near-Surface Atmospheric Moisture Content due to Land Use Changes: Evidence from the Observed Dewpoint Temperature Data

Abstract Land use change can significantly affect root zone soil moisture, surface energy balance, and near-surface atmospheric temperature and moisture content. During the second half of the twentieth century, portions of the North American Great Plains have experienced extensive introduction of irrigated agriculture. It is expected that land use change from natural grass to irrigated land use would significantly increase near-surface atmospheric moisture content. Modeling studies have already shown an enhanced rate of evapotranspiration from the irrigated areas. The present study analyzes observed dewpoint temperature (Td) to assess the affect of irrigated land use on near-surface atmospheric moisture content. This investigation provides a unique opportunity to use long-term (1982–2003) mesoscale Td data from the Automated Weather Data Network of the high plains. Long-term daily Td data from 6 nonirrigated and 11 irrigated locations have been analyzed. Daily time series were developed from the hourly da.
Collinear and quasi-collinear diffraction of bounded beams in crystals: acousto-optic interaction for the example of paratellurite

The equations in general form which permit us to solve the problem of collinear and quasi-collinear diffraction of three-dimensional optic and acoustic beams in an anisotropic medium are derived. These equations in the case of Gaussian optic and acoustic beams and under the conditions of the weak acousto-optic (AO) approximation are solved analytically. The optical beam spectra are described by the polynomial-Gaussian distribution and such an approach makes it possible to describe different prolonged AO interaction geometries. The possibility of collinear diffraction of bounded beams along the direction forbidden for plane waves is theoretically shown. The example calculation provided for the paratellurite crystal shows that the diffraction efficiency can reach a noticeable level at the usual magnitudes of input acoustic power.