Miracle-dz/UniFAR-FTUs huggingface dataset:
Conventional versus Reduced-Frequency Follow-Up in Early-Stage Melanoma Survivors: A Systematic Review with Meta-Analysis

To date, there have been multiple studies and clinical guidelines or recommendations for complex management of melanoma patients. The most controversial subjects included the frequency of follow-up. This study provides a coherent and comprehensive comparison of conventional vs. reduced-frequency follow-up strategies for early-stage melanoma patients. The value of our study consists in the precise analysis of a large collection of articles and the selection of the most valuable works in relation to the topic according to rigorous criteria, which allowed for a thorough study of the topic. The search strategy was implemented using multiple databases. The inclusion criteria were randomized clinical trial or cohort studies that compared the outcomes of a conventional follow-up schedule versus a reduced-frequency follow-up schedule for patients diagnosed with melanoma. In this study, authors analyzed recurrence and 3-year survival. Meta-analysis of outcomes presented by Deckers et al. and Moncrieff et. al. did not reveal a significant difference favoring one of the groups (OR 1.14; 95%CI: 0.65–2.00; p = 0.64). The meta-analysis of 3-year overall survival included two studies. The statistical analysis showed no significant difference in favor of the conventional follow-up group. (OR 1.10; 95%CI: 0.57–2.11; p = 0.79). Our meta-analysis shows that there is no advantage in a conventional follow-up regimen over a reduced-frequency regimen in early-stage melanoma patients.
An automated breast ultrasound scanner with integrated photoacoustic tomography

We have integrated photo-acoustic imaging into an automated breast ultrasound scanner (ABUS) with the goal of simultaneously performing ultrasound (US) and multi-spectral photo-acoustic tomography (PAT). This was accomplished with minimal change to the existing automated scanner by coupling laser light into an optical fiber for flexible and robust light delivery. We present preliminary tomography data acquired with this setup, including a simple resolution-testing geometry and a tissue phantom. Integrating PAT into the ABUS such that breast imaging is possible will require illumination from below the transducer dome. To that end, we are moving towards a fiber-based, localized illumination geometry which is fixed relative to the transducer. By illuminating locally (only near the current acquisition slice), this approach reduces overall light exposure at the tissue surface, allowing higher light intensity per acquisition (which translates to higher absorber contrast), while remaining below safe exposure thresholds. We present time-domain simulations of photo-acoustic imaging under non-uniform illumination conditions, and test one potential weighting scheme which can be used to extract absorber locations.
Systematic Literature Review Analysing Smart Tourism Destinations in Context of Sustainable Development: Current Applications and Future Directions

The growing popularity of smart tourism destinations (STDs) has increased the need to investigate their potential impact on sustainable development. This systematic literature review (SLR) aims to analyse the past achievements and future directions of smart tourism destinations in the context of sustainable development. The review was conducted through a systematic literature review that examined 20 papers using a rigorous framework of the research problem, the primary delimitation of the research, and the definition of the data collection and extraction tools. The review focuses on identifying and analysing the current state of the research on SLRs in smart tourism destinations and their implications for sustainable development. This includes the research questions, methods, journals, dates of publications, and key themes. The review also examines the implications and limitations of SLRs in this field, and it identifies gaps in the literature and areas for future directions. The review found that SLRs have been used to examine the impacts of smart tourism destinations on various aspects of sustainable development, such as economic, social, and environmental aspects. Additionally, the review found that there is a growing interest in smart cities, with a focus on reducing the environmental footprint of tourism and promoting sustainable tourism development. The review also identified the emerging research areas in the literature, such as the achievement of the sustainable development goals, the adoption of green IT, smart energy, and waste management.
The radiation resistance of a microstrip element

The radiation resistance of a rectangular microstrip element printed on a grounded dielectric is evaluated through the use of a bidimensional Fourier transform. The antenna is assumed to be half a guided wavelength long and to have a given width. The Q-factor of the antenna is assumed to be high so that the current in the feed at resonance is negligible. The longitudinal current distribution along the patch is assumed to resemble that of a resonant end-fed half-wavelength segment of a microstrip transmission line. The transversal current is taken to be constant. The resulting integrals are estimated in an asymptotic form using finite series and product expansions. An empirical formula replaces the former one for higher values of dielectric constants. The simple expressions thus derived lend insight into the nature of dependence of the radiation resistance on the various parameters such as width, thickness, and relative dielectric constant. In spite of their simplicity, the formulas provide quite accurate results. >
Dynamical instabilities in two-phase media and the minimum masses of stellar systems

Two-phase media, with cool dense clouds in pressure equilibrium with a hot, tenuous background from which they have cooled, have a prominent place in astrophysics, possibly being involved in the evolution of cooling flows, active galactic nuclei, and the formation of galaxies, star clusters and individual stars. Following their formation, the cool clouds are subject to Kelvin-Helmholtz instability, which grows as they move through the background gas. The instability is suppressed if the clouds are bound by a sufficiently strong gravitational potential. Analytical estimates of the growth and stability requirements of clouds are presented and are compared with the results of two-dimensional hydrodynamical simulations
A Pseudorange-Based GPS Spoofing Detection Using Hyperbola Equations

Spoofing attacks are one of the most critical threats against secure global navigation satellite system (GNSS) positioning. Since correct positioning is a must in many vehicle-to-everything (V2X) communication systems, the detection of these attacks is vital. In the literature on the detection strategies of spoofing attacks, the majority of the solutions are based on the assumption that all available signals are spoofed. In this paper, we focus on detecting spoofing attacks in which authentic and spoofing positioning signals coexist in a V2X system. The observable pseudorange values are utilized with the help of derived hyperbola equations during the design of the spoofing detection algorithms. We propose an algorithm, which is named as the sub-optimal search-based spoofing detection algorithm (Algorithm 1), and it considers all possible numbers of spoofing attacking signals, but not all spoofing scenarios with the same amount of spoofing signals. To address the complexity problems based on the increased number of search scenarios of this approach, we propose another algorithm, which is called subset selection-based spoofing detection algorithm (Algorithm 2), with a smart selection of the search subsets. Both of these algorithms are first compared with fixed detection thresholds, which are determined with the Pareto front approach. Then, the performance of the algorithms is investigated when vehicle mobility and spoofing imperfection are considered. Finally, a supervised learning-based decision tree machine learning (ML) algorithm is run without specifying any detection threshold. The results indicate that Algorithm 1 provides higher detection rates than the subset selection-based algorithm; however, the false alarm ratios of Algorithm 2 are much lower than its original performance.
The differential geometry of landmark shape manifolds: metrics, geodesics, and curvature

The study of shapes and their similarities is central in computer vision, in that it allows to recognize and classify objects from their representation. One has the interest of defining a distance function between shapes, which both embodies the meaning of similarity between shapes for the application and task that one has in mind, and is at the same time mathematically sound and treatable. In recent years the use of differential-geometric techniques for the study of shape deformation has become popular in the field of pattern analysis: the central idea is to endow "shape spaces" with the structure of a Riemannian manifold, so that one can talk about length of a path, geodesic distance, Euler-Lagrange equations, et cetera; however, the geometry and in particular the curvature of shape manifolds have remained, until very recently, largely unexplored. This thesis first introduces a class of Riemannian metrics on the shape space of landmark points that arise from fluid flow ideas, illustrating the structure of the geodesic equations that derive from such metrics. The central part of this work consists in the computation of the Riemannian curvature tensor and sectional for the landmarks manifold, which first necessitates solving the highly non-trivial problem of expressing sectional curvature in terms of the partial derivatives of the cometric tensor. The effects of curvature on the qualitative dynamics of landmarks and are then explored, for example verifying the existence of conjugate points in regions of positive curvature and the divergence of geodesics on regions of negative curvature. Finally, the potential application of the results to the statistical analysis of medical images is briefly discussed.
Sparse KNN - a method for object recognition over x-ray images using KNN based in sparse reconstruction

x RESUMEN . xi 1. INTRODUCCION . 1 1.1. The problem . 1 1.2. State of the Art . 2 1.3. Motivation . 4 1.4. Known Methods . 5 1.4. 1. k-Nearest Neighbors (knn) . 5 1.4. 2. Sequential Fordward Selection (SFS) . 6 1.4. 3. SIFT . 7 1.4. 4. K-means . 8 1.4. 5. Sparse Reconstruction . 9 2. PROPOSED METHOD . 11 2.1. Training . 12 2.1.1. Feature Extraction . 12 2.1.2. Delta Feature . 13 2.1.3. SFS . 14 2.1.4. Kmeans . 16 2.1. 5. Dictionary Construction . 17 2.2. Testing . 17 2.2.1. Feature Extraction . 18
The Role of Positive and Negative Aspects of Life Events in Depressive and Anxiety Symptoms

Negative or stressful life events are robust risk factors for depression and anxiety. Less attention has been paid to the positive aspects of events and whether positivity buffers the impact of the negative aspects of events. In this study, we examined the positivity and negativity of interpersonal and noninterpersonal episodic life events in predicting anxiety and depressive symptoms in a sample of 373 young adults. Regressions tested the main and interactive effects of positivity and negativity ratings of events in predicting symptom factors (fears, anhedonia-apprehension, general distress) relevant to anxiety and depression. A significant interaction demonstrated that positivity protected against high levels of negativity of noninterpersonal events in predicting general distress. A main effect of interpersonal negativity predicting higher anhedonia-apprehension was observed. Results for fears were nonsignificant. Findings suggest that the positivity of life events may buffer against negativity in predicting symptoms shared between anxiety and depression.
Spermidine Synthase and Saccharopine Reductase Have Co-Expression Patterns Both in Basidiomycetes with Fusion Form and Ascomycetes with Separate Form

Gene fusion is a process through which two or more distinct genes are fused into a single chimeric gene. Unlike most harmful fusion genes in cancer cells, in this study, we first found that spermidine synthetase- (SPDS, catalyst of spermidine biosynthesis) and saccharopine reductase- (SR, catalyst of the penultimate step of lysine biosynthesis) encoding genes form a natural chimeric gene, FfSpdsSr, in Flammulina filiformis. Through the cloning of full-length ORFs in different strains and the analysis of alternative splicing in developmental stages, FfSpdsSr has only one copy and unique transcript encoding chimeric SPDS-SR in F. filiformis. By an orthologous gene search of SpdsSr in more than 80 fungi, we found that the chimeric SpdsSr exists in basidiomycetes, while the two separate Spds and Sr independently exist in ascomycetes, chytridiomycetes, and oomycetes. Further, the transcript level of FfSpdsSr was investigated in different developmental stages and under some common environmental factors and stresses by RT-qPCR. The results showed that FfSpdsSr mainly up-regulated in the elongation stage and pileus development of F. filiformis, as well as under blue light, high temperature, H2O2, and MeJA treatments. Moreover, a total of 15 sets of RNA-Seq data, including 218 samples of Neurospora crassa, were downloaded from the GEO database and used to analyze the expression correlation of NcSpds and NcSr. The results showed that the separate NcSpds and NcSr shared highly similar co-expression patterns in the samples with different strains and different nutritional and environmental condition treatments. The chimeric SpdsSr in basidiomycetes and the co-expression pattern of the Spds and Sr in N. crassa indicate the special link of spermidine and lysine in fungi, which may play an important role in the growth and development of fruiting body and in response to the multiple environmental factors and abiotic stresses.
Two Spectral Algorithms for Ensembling Document Clusters

A critical problem in cluster ensemble is how to combine multiple clusters to yield a superior result.In this paper,the idea of spectral clustering algorithm is brought into the document cluster ensemble problem.Since spectral clustering algorithm needs to solve eigenvalue decomposition problem of a large scale matrix to get the low dimensional embedding of documents for later clustering,a fast spectral algorithm is first proposed,in which the large scale matrix eigenvalue decomposition problem is transformed to an equivalent singular value decomposition problem and then to a much smaller matrix eigenvalue decomposition problem.The characteristic of spectral clustering algorithm is further investigated and another spectral algorithm is proposed,in which the low dimensional embedding of documents are obtained indirectly by those of hyperedges.Experiments on TREC and Reuters document sets show that both proposed spectral algorithms outperform other cluster ensemble techniques based on graph partitioning,and can effectively solve document cluster ensemble problem.
Design of lens for 3 mega-pixel mobile phone camera

A mobile phone lens assembly composed of 3 plastic aspheric lenses and an IR filter was designed.This lens assembly has an excellent imaging performance.Considering production and cost,the plastic lens 480R was chosen.The 1/4 in 3 mega-pixel CMOS made by Samsung was taken as the image sensor of the lens assembly,whose pixel size was 1. 75μm,limiting resolution was 285lp/mm,F-number was 2.85 and FOV was 62°. Its MTF in the most of FOV at half of Nyquist frequency is higher than 0.5,RMS wavefront error is less than 0. 14λ and maximum distortion is-0.2%.
Semi‐analytical time‐domain low‐frequency scattering formulation for biological applications

In this paper, an efficient time domain formulation is proposed for a low‐frequency scattering by a complicated inhomogeneous dielectric scatterer. The formulation is based on the Born approximation and a sampling theorem. To extend the valid region of the proposed solution, the Rayleigh scattering formulation for a small dielectric object is used to modify the Born current inside the scatterer. In order to verify the obtained formulation, scatterings by several canonical objects such as a cubic box and a sphere are compared, which are calculated by the proposed formulation and the known exact or approximate solutions of a Mie series and the Rayleigh scattering. In addition, scattering by a human head is investigated at a very low‐frequency band (< 100 Hz). For the simulation, two excitations are considered: plane wave incidence from outside the head and an artificial point source located inside the head. The head model is discretized by a 3 × 3 × 3 mm3 cubic box, which is comprised of eight types of tissue. These are blood, bone, fat, grey matter, white matter, muscle, skin and vitreous humor. Copyright © 2006 John Wiley & Sons, Ltd.
A Simple Yet Effective Metric for Assessing Doppler Tolerance

The Doppler tolerance of a waveform refers to its behavior when subjected to fast-time Doppler shift imposed by scattering that involves nonnegligible radial velocity. The delay/Doppler ambiguity function characterizes this behavior, with notable attributes of Doppler-dependent mismatch loss (relative to zero Doppler) and possible offset in delay estimation. Previous effort has gone into establishing decision-based criteria where a binary judgement of being Doppler tolerant or not is made. Here, we consider the utility of a simple, yet effective measure of the degree of Doppler tolerance arising from a fundamental attribute of the ambiguity function that is also convenient to extract. This metric is examined in the context of a variety of different waveform classes including traditional linear/nonlinear chirps, noise-like signals, and phase codes. Extension to wideband operation is likewise considered. The purpose in doing so is to establish a consistent standard that can be readily applied, thereby permitting easy assessment across different parameterizations, as well as introducing a Doppler “quasi-tolerant” trade-space that can ultimately inform automated/cognitive waveform design in increasingly complex and dynamic radio frequency (RF) environments.
Finite-Horizon Minimax Estimation for Linear Discrete-Time Systems

This paper considers the finite-horizon discrete-time minimax estimation problems related to the H∞ estimation cost. Based on the Lagrange multiplier technique, we show that the minimax estimators are identical to H∞ estimators in both filtering and onestep prediction cases. Moreover, necessary and sufficient conditions for the existence of the minimax estimators are given in terms of an H∞ type Riccati difference equation (RDE) satisfying the positive definiteness of certain matrices. Using the RDE, we compare the minimax estimators with Kalman filter, and investigate the some properties of the minimax estimators. A numerical example is also included to show the applicability of the present minimax estimators.
Diffuse solar coronal features and their spicular footpoints

In addition to a component of the emission that originates from clearly distinguishable coronal loops, the solar corona also exhibits extreme-ultraviolet (EUV) and X-ray ambient emission that is rather diffuse and is often considered undesirable background. Importantly, unlike the generally more structured transition region and chromosphere, the diffuse corona appears to be rather featureless. The magnetic nature of the diffuse corona, and in particular, its footpoints in the lower atmosphere, are not well understood. We study the origin of the diffuse corona above the quiet-Sun network on supergranular scales. We identified regions of diffuse EUV emission in the coronal images from the SDO/AIA. To investigate their connection to the lower atmosphere, we combined these SDO/AIA data with the transition region spectroscopic data from the IRIS and with the underlying surface magnetic field information from the SDO/HMI. The region of the diffuse emission is of supergranular size and persists for more than five hours, during which it shows no obvious substructure. It is associated with plasma at about 1 MK that is located within and above a magnetic canopy. The canopy is formed by unipolar magnetic footpoints that show highly structured spicule-like emission in the overlying transition region. Our results suggest that the diffuse EUV emission patch forms at the base of long-ranging loops, and it overlies spicular structures in the transition region. Heated material might be supplied to it by means of spicular upflows, conduction-driven upflows from coronal heating events, or perhaps by flows originating from the farther footpoint. Therefore, the question remains open how the diffuse EUV patch might be sustained. Nevertheless, our study indicates that heated plasma trapped by long-ranging magnetic loops might substantially contribute to the featureless ambient coronal emission.
Channel Temperature Analysis and Nonlinear Thermal Model of AlGaN/GaN HEMTs Including Steady-State and Transient

The thermal analysis of GaN-based high electron-mobility transistors (HEMTs) is carried out from steady-state and transient aspects, respectively. An improved closed-form nonlinear thermal model based on device structure is proposed. In the steady-state case, the plane layer is added on the basis of the original partition, and the effect of thermal boundary resistance on channel temperature is also considered. In addition, the operating temperature of each gate finger is predicted based on the thermal coupling, and the nonlinear thermal model is extended to the transient by combining the thermal time constant. The validity of our presented model is verified by comparing the simulation results with the experimental data. Furthermore, this model is also embedded in the surface-potential-based current model to verify the self-heating effect in the circuits.
RELATIVE SUPERIOR MANDELBROT SETS AND RELATIVE SUPERIOR JULIA SETS FOR INTEGER AND NON-INTEGER VALUES

“Fractal” is a word invented by Mandelbrot to bring together under the one heading, a large class of objects that have played an historical role in the development of pure mathematics. A great revolution of ideas separates the classical mathematics of the 19th century from the modern mathematics of the 20th. Classical mathematics had its roots in the regular geometric structures of Euclid and the continuously evolving dynamics of Newton. Modern mathematics began with Cantor‟s set theory and Piano‟s space-filling curve. Historically, the revolution was forced by the discovery of mathematical structures that did not fit the patterns of Euclid and Newton. These new structures were regarded as „pathological,‟. as a „gallery of monsters,‟ kin to the cubist painting and atonal music that were upsetting established standards of taste in the arts at about the same time. The mathematicians who created the monsters regarded them as important in showing that the world of pure mathematics contains a richness of possibilities going far beyond the simple structures that they saw in Nature. Twentieth-century mathematics flowered in the belief that it had transcended completely the limitations imposed by its natural origins.