Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Prediction Model for Malicious Users Detection and Spectrum Sensing Based on Stacking and Deep Learning

Cooperative network is a promising concept for achieving a high-accuracy decision of spectrum sensing in cognitive radio networks. It enables a collaborative exchange of the sensing measurements among the network users to monitor the primary spectrum occupancy. However, the presence of malicious users leads to harmful interferences in the system by transmitting incorrect local sensing observations.To overcome this security related problem and to improve the accuracy decision of spectrum sensing in cooperative cognitive radio networks, we proposed a new approach based on two machine learning solutions. For the first solution, a new stacking model-based malicious users detection is proposed, using two innovative techniques, including chaotic compressive sensing technique-based authentication for feature extraction with a minimum of measurements and an ensemble machine learning technique for users classification. For the second solution, a novel deep learning technique is proposed, using scalogram images as inputs for the primary user spectrum’s classification. The simulation results show the high efficiency of both proposed solutions, where the accuracy of the new stacking model reaches 97% in the presence of 50% of malicious users, while the new scalogram technique-based spectrum sensing is fast and achieves a high probability of detection with a lower number of epochs and a low probability of false alarm.
Habitat selection in a fluctuating ground squirrel population: Density‐dependence and fitness consequences

Abstract Investigating individual‐based habitat settlement decisions is a central theme in ecology, yet studies that quantify density‐dependent habitat selection or tie fitness to resource selection decisions remain rare. We quantified habitat selection in golden‐mantled ground squirrels (Callospermophilus lateralis) across two spatial scales (home‐range placement, and occurrence within the home range) by using 11 consecutive years of data on individual space use, and we used resource selection functions and multilevel modeling to address how habitat preferences may be influenced by density or linked to fitness outcomes. Squirrels preferred dry meadow over other habitat types (wet meadow, aspen, spruce, and willow) at both spatial scales. Squirrels were more likely to use dry meadow that contained shorter vegetation and vision‐enhancing prominences such as rocks (“perches”). The use of dry meadow at each scale was not influenced by changes in density. The use of dry meadow did not lead to increased litter size, pre‐hibernation mass, or survival. However, squirrels that experienced a greater number of perches or lower local densities had higher survival rates. Our results suggest that a lack of visual obstruction, probably facilitating detection of predators, drives habitat selection in this system. Surprisingly, squirrels maintained their preference for dry meadow as density increased, and they experienced reduced survival as a result. This work furthers our understanding about the causes and consequences of changes in habitat use, informing wildlife management and conservation.
Synthesis and Strong Solvatochromism of Push-Pull Thienylthiazole Boron Complexes

The solvatochromic behavior of two donor-π bridge-acceptor (D-π-A) compounds based on the 2-(3-boryl-2-thienyl)thiazole π-linker and indandione acceptor moiety are investigated. DFT/TD-DFT calculations were performed in combination with steady-state absorption and emission measurements, along with electrochemical studies, to elucidate the effect of two different strongly electron-donating hydrazonyl units on the solvatochromic and fluorescence behavior of these compounds. The Lippert–Mataga equation was used to estimate the change in dipole moments (Δµ) between ground and excited states based on the measured spectroscopic properties in solvents of varying polarity with the data being supported by theoretical studies. The two asymmetrical D-π-A molecules feature strong solvatochromic shifts in fluorescence of up to ~4300 cm−1 and a concomitant change of the emission color from yellow to red. These changes were accompanied by an increase in Stokes shift to reach values as large as ~5700–5800 cm−1. Quantum yields of ca. 0.75 could be observed for the N,N-dimethylhydrazonyl derivative in nonpolar solvents, which gradually decreased along with increasing solvent polarity, as opposed to the consistently reduced values obtained for the N,N-diphenylhydrazonyl derivative of up to ca. 0.20 in nonpolar solvents. These two push–pull molecules are contrasted with a structurally similar acceptor-π bridge-acceptor (A-π-A) compound.
Effect of Comprehensive Nursing on Traumatic Paraplegia Patients by Evaluation of Magnetic Resonance Imaging Features

This research aimed to discuss the comprehensive nursing under the Omaha system in the treatment of patients with traumatic paraplegia (TP) and the changes in magnetic resonance imaging (MRI) features of patients. In total, 60 patients with TP were included as the research objects, and they were randomly divided into the experimental group (Omaha system-based comprehensive nursing) and the control group (routine nursing). All the objects underwent parallel MRI multisequence scanning. The scores of the quality of life, role change, mental health, care, oral hygiene, skin, neuromusculoskeletal (NMS) system, defecation function, urination function, contagion/infection, nutrition, healthcare supervision, and rest/sleep pattern in the experimental group were all significantly higher than those in the control group 3 months and 6 months after discharge (P < 0.05). The caregiving burden scores in the experimental group 3 months and 6 months after discharge from the hospital were 48.67 ± 6.97 and 43.40 ± 4.97, respectively, statistically lower than those in the control group (52.83 ± 6.37; 50.07 ± 7.14) (P < 0.05). On admission, MRI showed that the white lines disappeared from the compression of the dural sac, the spinal cord was compressed, and the intramedullary signal was abnormal. Then, six months after discharge, MRI showed that the compression of the dural sac was relieved, and the double white lines recovered. The apparent diffusion coefficient (ADC) of patients in the experimental group 6 months after discharge (1.063 ± 0.148) was highly lower than that in the control group (1.325 ± 0.245), with a difference of statistical significance (P < 0.05). In conclusion, comprehensive nursing under the Omaha system could improve the clinical treatment effect of patients with spinal cord injury (SCI) effectively, reduce the incidence of complications, and improve the quality of life and nursing outcomes of patients.
Antibacterial Activity from Momordica charantia L. Leaves and Flavones Enriched Phase

Momordica charantia L. (Cucurbitaceae) is a plant known in Brazil as “melão de São Caetano”, which has been related to many therapeutic applications in folk medicine. Herein, we describe antibacterial activities and related metabolites for an extract and fractions obtained from the leaves of that species. An ethanolic extract and its three fractions were used to perform in vitro antibacterial assays. In addition, liquid chromatography coupled to mass spectrometry and the molecular networking approach were used for the metabolite annotation process. Overall, 25 compounds were annotated in the ethanolic extract from M. charantia leaves, including flavones, terpenes, organic acids, and inositol pyrophosphate derivatives. The ethanolic extract exhibited low activity against Proteus mirabilis (MIC 312.5 µg·mL−1) and Klebsiella pneumoniae (MIC 625 µg·mL−1). The ethyl acetate phase showed interesting antibacterial activity (MIC 156.2 µg·mL−1) against Klebsiella pneumoniae, and it was well justified by the high content of glycosylated flavones. Therefore, based on the ethyl acetate phase antibacterial result, we suggest that M. charantia leaves could be considered as an alternative antibacterial source against K. pneumoniae and can serve as a pillar for future studies as well as pharmacological application against the bacteria.
Monitoring Physical Behavior in Rehabilitation Using a Machine Learning–Based Algorithm for Thigh-Mounted Accelerometers: Development and Validation Study

Background: Physical activity is emerging as an outcome measure. Accelerometers have become an important tool in monitoring physical behavior, and newer analytical approaches of recognition methods increase the degree of details. Many studies have achieved high performance in the classification of physical behaviors through the use of multiple wearable sensors; however, multiple wearables can be impractical and lower compliance. Objective: The aim of this study was to develop and validate an algorithm for classifying several daily physical behaviors using a single thigh-mounted accelerometer and a supervised machine-learning scheme. Methods: We collected training data by adding the behavior classes—running, cycling, stair climbing, wheelchair ambulation, and vehicle driving—to an existing algorithm with the classes of sitting, lying, standing, walking, and transitioning. After combining the training data, we used a random forest learning scheme for model development. We validated the algorithm through a simulated free-living procedure using chest-mounted cameras for establishing the ground truth. Furthermore, we adjusted our algorithm and compared the performance with an existing algorithm based on vector thresholds. Results: We developed an algorithm to classify 11 physical behaviors relevant for rehabilitation. In the simulated free-living validation, the performance of the algorithm decreased to 57% as an average for the 11 classes (F-measure). After merging classes into sedentary behavior, standing, walking, running, and cycling, the result revealed high performance in comparison to both the ground truth and the existing algorithm. Conclusions: Using a single thigh-mounted accelerometer, we obtained high classification levels within specific behaviors. The behaviors classified with high levels of performance mostly occur in populations with higher levels of functioning. Further development should aim at describing behaviors within populations with lower levels of functioning. outcomes do not increase their objectively measured sport and physical activity hip the HAFAI cohort.
Monte‐Carlo simulations of electronic excitations in swift heavy ion tracks in SiO2

Monte‐Carlo simulations were applied for investigation of the initial electronic kinetics (⩽10−14 s) in tracks of Ca+19 (11.4 MeV/u) in SiO2. The spatial and temporal distributions of the volume and excess energy densities of free electrons, electronic vacancies in different atomic shells and the lattice were obtained. It was demonstrated that at 10−14 s an essential part (∼55%) of the energy deposited by the ion is trapped in electronic vacancies. The energy transferred to the lattice at times shorter than the characteristic time of electron‐phonon coupling was determined. It was found that only ∼6% of the excess energy of delocalized electrons near the projectile trajectory (∼6 nm) may be thermalized on the time 10−14 s from the projectile passage. Ballistic spatial propagation of excess energy cannot be described by thermal diffusion.
Atomistic Simulation of Structural Evolution at Long Time Scales: Diffusion of Aluminum in Nickel at a Low Concentration Limit

The diffusivity of aluminum in a Ni-Al system at a low concentration limit was studied using the compounded computational methods of (1) the Autonomous Basin Climbing method, (2) the nudged elastic band method, and (3) the on-the-fly Kinetic Monte Carlo method. The probable diffusion pathways were determined using the Autonomous Basin Climbing method, while the corresponding activation barriers were obtained from the nudged elastic band method. The on-the-fly Kinetic Monte Carlo method was then utilized to account for all hopping events and calculate associated escaped time. The tracer diffusion coefficient was calculated from tracking atomic species locations while accumulating associated escaped time intervals. The diffusion prefactor and effective activation energy of aluminum diffusion in a nickel matrix were determined from curve fitting to an Arrhenius equation. Our numerical results are in same order of magnitudes with a set of available published data, indicating the predictability of the compounded computational methods and transferability to other kinetics problems.
Subterm-Based Proof Techniques for Improving the Automation and Scope of Security Protocol Analysis

During the last decades, many advances in the field of automated security protocol analysis have seen the field mature and grow from being applicable to toy examples, to modeling intricate protocol standards and finding real-world vulnerabilities that extensive manual analysis had missed. However, modern security protocols often contain elements for which such tools were not originally designed, such as protocols that construct, by design, terms of unbounded size, such as counters, trees, and blockchains. Protocol analysis tools such as Tamarin and ProVerif have some very restricted support, but typically lack the ability to effectively reason about dynamically growing unbounded-depth terms. In this work, we introduce subterm-based proof techniques that are tailored for automated protocol analysis in the Tamarin prover. In several case studies, we show that these techniques improve automation (allow for analyzing more protocols, or remove the need for manually specified invariants), efficiency (reduce proof size for existing analyses), and expressive power (enable new kinds of properties). In particular, we provide the first automated proofs for TreeKEM, S/Key, and Tesla Scheme 2; and we show substantial benefits, most notably in WPA2 and 5G-AKA, two of the largest automated protocol proofs.
A Survey on Liquid Content Aware Image Resizing Technique

— Advances in imaging technology have made the capture and display of digital images ubiquitous. A variety of displays are used to view them, ranging from high-resolution computer monitors to low-resolution mobile devices, and images often have to undergo changes in size and aspect ratio to adapt to di ﬀ erent screens. Also, displaying and printing documents with embedded images frequently entail resizing of the images to comply with the overall layout. Straightforward image resizing operators, such as scaling, often do not produce satisfactory results, since they are oblivious to image content. In this work, we review and categorize algorithms for content-aware image retargeting, i.e., resizing an image while taking its content into consideration to preserve important regions and minimize distortions. This is a challenging problem, as it requires preserving the relevant information while maintaining an aesthetically pleasing image for the user. The techniques typically start by computing an importance map which represents the relevance of every pixel, and then apply an operator that resizes the image while taking into account the importance map and additional constraints. We intend this review to be useful to researchers and practitioners interested in image retargeting.
A Modular Type Inference and Specializer for Array Bound Checks Elimination

We propose a modular inference mechanism, based on a dependent type system with Presburger arithmetic, to ﬁnd array checks that can be safely eliminated. Our proposal works for a core imperative language with assignments, and can discover symbolic program states (or postconditions) to support the elimination of redundant checks. Our inference is precise as it is both path and context sensitive. It is also eﬃcient , as we analyse each method once through a summary-based approach. Moreover, through suitable techniques that either weaken postconditions or strengthen pre-conditions, we can selectively reduce the sizes of our formulae. We also subject each inferred program to a ﬂexivariant specialization process that can achieve a tradeoﬀ between maximal elimination of array checks whilst being mindful on code explosion concerns. We have proven the soundness of our approach and have also implemented a prototype inference and specialization system. Initial experiments suggest that such a system can be both eﬃcient and accurate.
Comparison of ice dynamics using full-Stokes and Blatter-Pattyn approximation: application to the central North East Northeast Greenland Ice Stream

Full-Stokes (FS) ice sheet models provide the most sophisticated formulation of ice sheet ﬂow. However, their applicability is often limited due to its (cid:58)(cid:58) the (cid:58) high computational demand and its owing numerical challenges. To balance computational demand and accuracy, the so-called Blatter-Pattyn (BP) stress regime is frequently used. Here, we explore the dynamic consequences caused by solving FS and the BP stress regime applied to the central part of the North East (cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58) Northeast Greenland Ice Stream(NEGIS). To ensure a consistent comparison, we use one single ice sheet model to run the simulations under 5 identical numerical conditions. A sensitivity study to grid resolution (cid:58)(cid:58) the (cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58) horizontal (cid:58)(cid:58)(cid:58)(cid:58) grid (cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58) Regarding the desired consistency between the simulations simulation results, we must clarify the different usage of the linear solvers: the coarser models show a poor performance with the ASM solver (cid:58)(cid:58)(cid:58) and (cid:58)(cid:58)(cid:58)(cid:58)(cid:58) Vanka (cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58)(cid:58) preconditioner. At the same time, the higher resolutions run out of memory with the MUMPS solver. But the limiting case with a horizontal grid resolution of l =0 . 4 km reveals differences between
CONTROLS OF DEVELOPMENT IN COCKROACHES

Availability of food extrinsicly controls both the molting and reproductive cycles of the roaches, Blattella germanica and Periplaneta americana. The progressive increase in asynchrony of larval development when food is continuously available is prevented by removing food before each ecdysis and replacing it after all animals have finished ecdysis. This method was used to provide experimental animals. Differences in molting cycle length and synchrony were found in three strains of Blattella, Orlando, Chlordane Resistant (Ross and Cochran, 1966, J. Heredity 57,221-ZZ6) and New York. The strain Orlando molts 125 hours after feeding with the highest synchrony (S.D.= 8hrs.at 29C). A genetic marker enables raising two treatment groups in the same bowl, a simplification of experimental design. Probit analysis was used to provide a map of the mean times, variability and sequence of events in synchronized colonies of cockroaches. The time when the brain is no longer needed to support a molting cycle is closely associated with the time after which regeneration is post-poned until the next molting cycle. This suggests that regeneration delays molting by delaying the last brain event necessary to initiate molting. The time when the prothoracic gland, source of molting hormone, is no longer needed to support molting is close to the end of epidermal cell proliferation and the first events related to production of a new cuticle. Using colchicine to collect dividing cells, I studied the pattern of mitosis in the epidermis. The differentiative divisions of specialized epidermal structures, dermal glands and sensory organules, occur before general epidermal proliferation. Epidermal proliferation starts simultaneously at the posterior of each abdominal tergite and proceeds anteriorly ending at the anterior edge of the inter-tergite. Epidermal proliferation stops locally before the first structural events in production of a new cuticle begin. Regeneration delays epidermal proliferation and subsequent events of the molting cycle to the same extent. The existing theory (O'Farrell et al. 1960, Acta Soc. Ent. Csl. 317-324) that the amount of tissue regenerating dictates the amount of delay could not be supported. Animals with strikingly different sized left and right metathoracic legs were produced by prior regeneration. There was no difference in delay associated with autotomy of a small versus a large tarsus even though the amount of delay is a third degree polynomial in length of the regenerate. Also, autotomy of a second tarsus has the same additive effect as autotomy of a second femur, which is not reasonable if delay is caused by the size of the regenerate. I conclude that the amount of delay is correlated with but not caused by the amount of regeneration. Amputation at non-autotomy points does not allow the proper delay of the molting cycle for regeneration to occur. Nerve section between a leg ganglion and the brain prevents the delay of molting needed to regenerate a leg. Nervous feedback from the ganglion of the autotomized leg is suggested as the mechanism by which leg autotomy delays the molting cycle.
Quantitative Fourier Domain Optical Coherence Tomography Imaging of the Ocular Anterior Segment

Quantitative Fourier Domain Optical Coherence Tomography Imaging of the Ocular Anterior Segment by Ryan Palmer McNabb Department of Biomedical Engineering Duke University Date:_______________________ Approved: ___________________________ Joseph A. Izatt, Supervisor ___________________________ Sina Farsiu ___________________________ Anthony N. Kuo ___________________________ Tuan Vo-Dinh ___________________________ Adam P. Wax An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biomedical Engineering in the Graduate School of Duke University 2013 Copyright by Ryan Palmer McNabb 2013 iv Abstract Clinical imaging within ophthalmology has had transformative effects on ocular health over the last century. Imaging has guided clinicians in their pharmaceutical and surgical treatments of macular degeneration, glaucoma, cataracts and numerous other pathologies. Many of the imaging techniques currently used are photography based and are limited to imaging the surface of ocular structures. This limitation forces clinicians to make assumptions about the underlying tissue which may reduce the efficacy of their diagnoses. Optical coherence tomography (OCT) is a non-invasive, non-ionizing imaging modality that has been widely adopted within the field of ophthalmology in the last 15 years. As an optical imaging technique, OCT utilizes low-coherence interferometry to produce micron-scale three-dimensional datasets of a tissue’s structure. Much of the human body consists of tissues that significantly scatter and attenuate optical signals limiting the imaging depth of OCT in those tissues to only 1-2mm. However, the ocular anterior segment is unique among human tissue in that it is primarily transparent or translucent. This allows for relatively deep imaging of tissue structure with OCT and is no longer limited by the optical scattering properties of the tissue. This goal of this work is to develop methods utilizing OCT that offer the potential to reduce the assumptions made by clinicians in their evaluations of their
Geometric Invariant Theory and Birational Geometry

In this paper we will survey some recent developments in the last decade or so on variation of Geometric Invariant Theory and its applications to Birational Geometry such as the weak Factorization Theorems of nonsingular projective varieties and more generally projective varieties with finite quotient singularities. Along the way, we will also mention some progresses on birational geometry of hyperK\"ahler manifolds as well as certain open problems and conjectures.