Miracle-dz/UniFAR-FTUs huggingface dataset:
Line Drawing Vectorization via Coarse‐to‐Fine Curve Network Optimization

Vectorizing line drawings is a fundamental component of the workflow in various applications such as graphic design and computer animation. A practical vectorization tool is desired to produce high‐quality curves that are faithful to the original inputs and close to the connectivity of human drawings. The existing line vectorization approaches either suffer from low geometry accuracy or incorrect connectivity for noisy inputs or detailed complex drawings. We propose a novel line drawing vectorization framework based on coarse‐to‐fine curve network optimization. Our technique starts with an initial curve network generated by an existing tracing method. It then performs a global optimization which fits the curve network to image centrelines. Finally, our method performs a finer optimization in local junction regions to achieve better connectivity and curve geometry around junctions. We qualitatively and quantitatively evaluate our system on line drawings with varying image quality and shape complexity, and show that our technique outperforms existing works in terms of curve quality and computational time.
A Comprehensive Overview of Baboon Phylogenetic History

Baboons (genus Papio) are an intriguing study system to investigate complex evolutionary processes and the evolution of social systems. An increasing number of studies over the last 20 years has shown that considerable incongruences exist between phylogenies based on morphology, mitochondrial, and nuclear sequence data of modern baboons, and hybridization and introgression have been suggested as the main drivers of these patterns. Baboons, therefore, present an excellent opportunity to study these phenomena and their impact on speciation. Advances both in geographic and genomic coverage provide increasing details on the complexity of the phylogeography of baboons. Here, we compile the georeferenced genetic data of baboons and review the current knowledge on baboon phylogeny, discuss the evolutionary processes that may have shaped the patterns that we observe today, and propose future avenues for research.
Powerful polymeric thermal microactuator with embedded silicon microstructure

A powerful and effective design of a polymeric thermal microactuator is presented. The design has SU-8 epoxy layers filled and bonded in a meandering silicon (Si) microstructure. The silicon microstructure reinforces the SU-8 layers by lateral restraint. It also improves the transverse thermal expansion coefficient and heat transfer for the bonded SU-8 layers. A theoretical model shows that the proposed SU-8/Si composite can deliver an actuation stress of 1.30? MPa/K, which is approximately 2.7 times higher than the unconstrained SU-8 layer, while delivering an approximately equal thermal strain.
Consumer Expectations and Attitudes About Psychotherapy: Survey Study

Background Although mental illness is common among adults in the United States, access to, and public perception of, mental health care continue to present as key barriers to care. Objective Given the importance of attitudes toward, and perceptions of, mental health treatment in the successful access to mental health care and treatment of mental health issues, the primary goal of this survey study was to further investigate consumer perspectives of psychotherapy among adults in the United States; specifically, adding to the literature by investigating perceptions of both the general public and patients receiving telehealth. More specifically, the aims were to better understand openness to, and satisfaction with, therapy; perceptions, preferences, and expectations around therapy; and perceptions of psychotropic medication. Methods An electronic survey was administered to current and former patients (those receiving psychotherapy) of Brightside, a nationwide telehealth company, as well as to the general public; both were convenience samples. Using the same survey questions, Brightside surveyed its own members (using Qualtrics; Qualtrics International Inc) and the general population (using SurveyMonkey’s Audience tool; Momentive). This survey included questions about basic participant demographics, as well as questions about current mental health treatment, perceptions about therapy, and therapists’ qualities. Results A total of 714 people completed the survey. The data were fairly evenly split between those collected from Brightside patients (368/714, 51.5%) and those collected from the general public (346/714, 48.5%). Combining both samples, overall participation was 67.1% (479/714) women; 73.1% (522/714) White, 7.3% (52/714) Asian, 6.7% (48/714) African American, and 7.4% (53/714) Hispanic or Latinx; largely aged 25 to 34 years (255/714, 35.7%) or 35 to 44 years (187/714, 26.2%); from either the Mid-Atlantic (131/714, 18.3%) or South Atlantic (129/714, 18.1%) regions of the country; and most (402/714, 56.3%) earning annual salaries of US $30,000 to US $100,000. There were generally favorable perceptions of both psychotherapy and psychiatric medication. Selecting a therapist as well as cost and insurance are the common factors in therapy that are important to patients. The most commonly held perception of psychotherapy duration was indefinite (250/714, 35%). Very few (58/714, 8.1%) thought that therapy typically lasts 1 to 3 months. Most of the participants (414/714, 58%) thought that evidence-based practice was important. Conclusions Public education is needed to increase awareness of the typical duration and cost of psychotherapy. There seem to be generally favorable perceptions of both psychotherapy and psychotropic medication. Selecting a therapist as well as cost and insurance are the common factors in therapy that are important to patients. Practitioners and those marketing their services might consider using their marketing campaigns to counter some of the more common falsely held beliefs.
Mammographic Texture Analysis : An Evaluation Of Risk For Developing Breast Cancer

The aim of this research is to avoid as much as possible the development of the woman breast cancer by the mean of a preventive systematic analysis of mammographic textures and the automatic determination of a "risk coefficient" for each given texture. In a first step, a standard procedure for obtaining X-ray mammograms is set-up and a specialist classifies the resulting radiographic images in four groups of risk. In a second step, specific and selected textures algorithms using both global and local statistical properties of the images are implemented. A number of X-ray mammograms, given by the hospital, has been studied. One of the resulting important observation is that it seems unapropriate to define a set of distinct classes of risk and that an increasing gravity degree correlated to a continuous evolution of the mammographic textures from the lowest to the highest degree of risk is to be preferred. Finally, a systematic comparison between the human classification and the numerical coefficients provided by the texture analysis is performed : a critical examination of these preliminary results leads us to a constructive discussion concerning the future developments of the proposed method.
Research on lane detection algorithm for large curvature curve

Existing lane line detection algorithm for identification of a straight line in good condition, to solve the problem of curve, however, failed to find a good strategy, especially in large curvature of curve, the visual field to extract the lane line produces by the two become one, resulting in a wrong calculation, in the case of real vehicle test, bend by camera height, visual field, etc. The indoor robot car is used as the carrier for the test, and a turning strategy is proposed to recognize the lane line at the corner, and the lane line detection algorithm based on sliding window is improved to make it less affected by the environment. The algorithm is simple and efficient, which is suitable for the indoor robot car visual line inspection. The experimental results show that the lane detection algorithm proposed in this paper improves the passing rate and stability of the robot car under large area rate curves.
Three-Dimensional Numerical Modeling of Solitary Wave Breaking and Force on a Cylinder Pile in a Coastal Surf Zone

AbstractIn this paper, a three-dimensional numerical wave model is applied to simulate solitary wave run-up and breaking on a plane beach, as well as the resulting breaking-wave force exerted on a single pile located at different elevations on the beach. The model employed is based on Reynolds–averaged Navier-Stokes (RANS) equations with a k-e model for turbulence closure. The model is validated using experimental data on breaking solitary wave run-up on a plane beach, time history of the wave force on a cylinder, and wave-pile interaction on a sloping bottom. After model validation, the wave model is applied to simulate wave-pile interaction with the pile located at seven different elevations on the plane beach. Snapshots of wave-pile interaction, as well as the time history of breaking-wave force on the pile, are obtained and analyzed. The variations in breaking-wave force with elevation of the pile are also discussed.
A novel non-isolated high gain multiport DC-DC converter for integrating fuel cell/solar PV and battery energy storage system

ABSTRACT This paper presents a novel non-isolated capacitor-assisted quasi-Z-source (CA-QZS) multiport DC-DC boost converter, which operates as a dual-input single-output high gain boost converter. It consists of a bidirectional port for the smooth operation of the energy storage system, and a unidirectional port for the solar/fuel cell to deliver power to the battery and the load. The availability of common ground between input and output ports, high voltage conversion ratio, and continuous current of the unidirectional port are the main features of this novel design, making it suitable for a wider range of applications. A typical switching strategy is followed to regulate the output voltage as well as control input power from the sources. As a battery-incorporated system, the converter’s performance is determined by its selection between three operating modes. Therefore, the CA-QZS converter offers a viable interface for the management of battery energy storage systems. A comparative study is performed with other multi-port converters to highlight the advantages. It is observed that the voltage conversion ratio of 10, can be achieved at a low duty ratio of 0.3. To evaluate the effectiveness of the proposed topology, a prototype is developed with a nominal output power rating of 200W and an output voltage of 200 V.
Quantum and medium effects in (resonant) leptogenesis

Leptogenesis offers a very attractive explanation for the origin of the baryon asymmetry of the universe. Such scenarios based on leptonic CP–violation can be realized already within minimalistic seesaw extensions of the standard model. Apart from model building issues the answer to the question of whether a given particle theory can explain the observed baryon number density depends also on the detailed statistical evolution of the asymmetry. The CP–violation within a given model leads to an asymmetry only if it is accompanied by an out–of–equilibrium evolution in the early universe. Most existing analyses employ Boltzmann–like equations (BEs) to describe it. In this context fundamental issues arise which can be addressed in the framework of non–equilibrium quantum field theory (NEQFT). Here, the relevance of quantum and medium effects for thermal leptogenesis is investigated. Within the 2PI–formalism of NEQFT, questions such as that for the justification of the particle picture arise naturally in subsequent approximations when BEs are to be derived. This specific problem is particularly important in the case of resonant leptogenesis where the relevant particle states are almost degenerate in mass. It is found that Boltzmann like equations can (only) be obtained in certain cases. But it is then possible to account for corrections due to quantum and medium effects.
Skin cancer image classification optimization through transfer learning with Tensorflow and InceptionV3

Skin cancer is a common illness that claims thousands of lives annually in the United States alone. Accurately identifying malignant tumors is crucial to survival but can be challenging as the visual distinctions between benign and life-threatening tumors are minimal. The purpose of this project is to explore deep learning algorithms that can be trained to systematically classify skin cancer images, create a program to execute the algorithm, and exemplify an optimization process for the program that can serve as a reference for future works. The project will adopt a transfer learning algorithm based on previous studies on the subject and select a pre-trained model given practical restraints. Then a program will be coded in Python to retrieve datasets, process images, train the model, and evaluate accuracy. Finally, the algorithm will be optimized by tuning model parameters and training restraints. The experiments revealed that the algorithm was able to perform the task with an accuracy of around 70%. Model parameters such as optimizer choice and learning rate and training restraints such as batch size and epoch count have significant impacts on the training results and require precise values for maxima accuracy and minimal overfitting.
400 W broadband power amplifier using transmission-line transformers with 1:8 impedance transformation ratio

Abstract This paper presents a broadband high-power amplifier using transmission-line transformers with a high impedance transformation ratio. Two series-connected transformers with 1:8 and 1:1 impedance transformation ratios are used at the load network of a single-balanced high-power amplifier to match the low load impedance in broadband. The same transformer configuration is also used at the input network. A negative feedback is applied to improve the gain flatness and to increase the stability over the broadband. In order to validate the proposed circuit structure, a broadband high-power amplifier is designed and implemented to achieve an output power of more than 400 W in the frequency band of 30 to 500 MHz. The implemented power amplifier exhibits a flat gain response within 1.80 dB at an average of 19.1 dB and high power-added efficiencies of 28.0 to 56.9 at an output power of 400 W over the entire frequency band.
BarkDroid: Android Malware Detection Using Bark Frequency Cepstral Coefficients

Since their inaugural releases in 2007, Google’s Android and Apple’s iOS have grown to dominate the mobile OS market share. Currently, they jointly possess over 99% of the global market share with Android being the leading mobile Operating System of choice worldwide, controlling close to 70% of the market share. Mobile devices have enabled the exponential growth of a plethora of mobile applications that play key roles in enabling many use cases that are pivotal in our daily lives. On the other hand, access to a large pool of potential end users is available to both legitimate and nefarious applications, thus making mobile devices a burgeoning target of malicious applications. Current malware detection solutions rely on tedious, time-consuming, knowledge-based, and manual processes to identify malware. This paper presents BarkDroid, a novel Android malware detection technique that uses the low-level Bark Frequency Cepstral Coefficients audio features to detect malware. The results obtained outperform results obtained using other features on the same datasets. BarkDroid achieved 97.9% accuracy, 98.5% precision, an F1 score of 98.6%, and shorter execution times.
Experiment protocols for brain-body imaging of locomotion: A systematic review

Introduction Human locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings. Methods This paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols. Results The findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments. Discussion Finally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.
Influence of Extremely High Pressure and Oxygen on Hydrocarbon-Enriched Microbial Communities in Sediments from the Challenger Deep, Mariana Trench

Recent studies reported that highly abundant alkane content exists in the ~11,000 m sediment of the Mariana Trench, and a few key alkane-degrading bacteria were identified in the Mariana Trench. At present, most of the studies on microbes for degrading hydrocarbons were performed mainly at atmospheric pressure (0.1 MPa) and room temperature; little is known about which microbes could be enriched with the addition of n-alkanes under in-situ environmental pressure and temperature conditions in the hadal zone. In this study, we conducted microbial enrichments of sediment from the Mariana Trench with short-chain (SCAs, C7–C17) or long-chain (LCAs, C18–C36) n-alkanes and incubated them at 0.1 MPa/100 MPa and 4 °C under aerobic or anaerobic conditions for 150 days. Microbial diversity analysis showed that a higher microbial diversity was observed at 100 MPa than at 0.1 MPa, irrespective of whether SCAs or LCAs were added. Non-metric multidimensional scaling (nMDS) and hierarchical cluster analysis revealed that different microbial clusters were formed according to hydrostatic pressure and oxygen. Significantly different microbial communities were formed according to pressure or oxygen (p < 0.05). For example, Gammaproteobacteria (Thalassolituus) were the most abundant anaerobic n-alkanes-enriched microbes at 0.1 MPa, whereas the microbial communities shifted to dominance by Gammaproteobacteria (Idiomarina, Halomonas, and Methylophaga) and Bacteroidetes (Arenibacter) at 100 MPa. Compared to the anaerobic treatments, Actinobacteria (Microbacterium) and Alphaproteobacteria (Sulfitobacter and Phenylobacterium) were the most abundant groups with the addition of hydrocarbon under aerobic conditions at 100 MPa. Our results revealed that unique n-alkane-enriched microorganisms were present in the deepest sediment of the Mariana Trench, which may imply that extremely high hydrostatic pressure (100 MPa) and oxygen dramatically affected the processes of microbial-mediated alkane utilization.
Hyperbolic state space decomposition for a linear stochastic delay equation

We consider the equation $dX(t) = (\int_{ - r}^0 {X(s + t)d\mu (s))dt} + GdW(t)$ where $r > 0$, $\mu $ is a matrix-valued signed measure on $[ - r,0]$, W is an n-dimensional Wiener process and G is a fixed $n \times n$ matrix. Using the known decomposition $C = S \oplus U$ of $C = C[ - r,0]$ into a stable closed subspace S and a finite dimensional unstable subspace U for the analogous deterministic equation, we prove that the projection of the solution X onto S converges exponentially fast to a stationary Gaussian process. Also the speed of explosion of the projection onto U is exhibited.
Stability balloon for the double-lid-driven cavity flow

The linear stability of the two-dimensional, steady, incompressible flow in a rectangular cavity is investigated numerically. The flow is driven by the parallel or antiparallel motion of two facing walls. When the cavity is infinitely extended in the spanwise direction a variety of different, three-dimensional flow instabilities can arise. We provide an overview on the global structure of the critical hypersurface in the three-dimensional parameter space spanned by the cross-sectional aspect ratio and the two side-wall Reynolds numbers. It turns out that the critical hypersurface is made up of six major segments belonging to different modes of instability. The interrelation and connectivity of these critical modes is elucidated.
Case report: Acinetobacter baumannii septic arthritis in an immunocompetent infant

Acinetobacter baumannii is a gram-negative coccobacilli, mainly causing nosocomial infections with poor prognosis, especially in patients with prolonged hospitalization or antibiotics administration. A. baumannii pneumonia is the most common clinical form and usually occurs in critically ill patients in the intensive care unit. However, septic arthritis caused by A. baumannii is rarely reported. In this report, we describe a case of A. baumannii septic arthritis combined with incomplete Kawasaki disease in an infant. The child's chief complaint was a 2-week intermittent fever with poor response to antibiotics. Initial physical examination revealed swollen lymph nodes in the neck, pharynx congestion, and the appearance of rashes. Combined with laboratory tests, the diagnosis of incomplete Kawasaki disease was considered. After administration of high-dose intravenous immunoglobulin and corticosteroids, the child's fever improved and periungual desquamation appeared simultaneously. Swelling of the right knee occurred 5 days after the fever improved and imaging tests of MRI and ultrasound suggested the existence of infection. A diagnosis of septic arthritis was established subsequently, and arthroscopy was carried out. A. baumannii was finally identified by metagenomics next-generation sequencing of joint draining fluid for pathogenic microorganisms. Treatment with meropenem was then started. The patient eventually recovered and was discharged from the hospital after 23 days of treatment with meropenem. Although A. baumannii is not a common bacterium of septic arthritis, this rare infection can still occur in infants. Early diagnosis, pathogenic identification, and target antibiotic treatment are important to reduce the occurrence of joint sequelae.