Miracle-dz/UniFAR-FTUs huggingface dataset:
Rooftop extraction method for high spatial resolution remote sensing image based on sparse representation

ABSTRACT In existing rooftop extraction methods, either too few or too many features in high spatial resolution remote-sensing image (HSRRSI) are used, reducing the rooftop extraction accuracy. Accordingly, a rooftop extraction method for HSRRSI based on sparse representation (SR) is proposed in this work. The optimal segmentation parameters are first determined by the ratio of mean difference to neighbours to standard deviation index method and maximum area method. Thereafter, the optimal feature subset of HSRRSI is constructed on the basis of the L 1 regularization SR model to remove redundant features. Finally, a random forest classifier is used to extract rooftops based on the optimal feature subset. Results show that the overall accuracy of the two study areas in Zhanggong District are 0.91776 and 0.88313, respectively. This study can help in effectively extracting rooftops from HSRRSI, which is of great significance in urban planning, population statistics and economic forecasting.
Femtosecond laser-assisted cataract surgery: Update and perspectives

Cataract surgery is among the most frequently performed surgical procedures worldwide and has a tremendous impact on patients' quality of life. Phacoemulsification (PCS) is accepted as a standard of care; its technique has continuously evolved and already achieved good anatomical, visual, and refractive outcomes. Lasers in ophthalmology are widely used in clinical practice, femtosecond lasers (FSLs) for corneal surgery in particular. It was natural to assess the usefulness of FSL in cataract surgery as this technology was within reach. Indeed, precise and reproducible cuttings provided by FSL platforms could improve standardization of care and limit the risk associated with the human element in surgery and provide a step toward robot-assisted surgery. After docking and planning the procedure, femtosecond lasers are used to perform corneal incisions, capsulorhexis, lens fragmentation, and arcuate incisions in an automated manner. A well-constructed corneal incision is primordial as it offers safety during the procedure, self-seals afterward, and influences the refractive outcome. Capsulorhexis size, centration, and resistance to shearing influence the surgery, intraocular lens (IOL) centration and stability, and posterior capsular opacification formation. Lens fragmentation is where most of the energy is delivered into the eye, and its amount influences endothelial cell damage and potential damage to other ocular structures. The arcuate incisions offer an additional opportunity to influence postoperative astigmatism. Femtosecond laser-assisted cataract surgery (FLACS) has been a topic of research in many studies and clinical trials that attempted to assess its potential benefits and cost-effectiveness over PCS and is the subject of this mini-review.
Investigation of the relationship between prolonged ventilation and the Glasgow Prognostic Score after elective isolated coronary bypass surgeries in advanced-age patients

Objectives: Coronary artery bypass graft (CABG) surgeries are the most beneficial treatment method for atherosclerotic heart disease. Prolonged ventilation is a significant condition that poses risks such as infection, renal failure, prolongs hospital stays, and increases treatment costs. In this current study, we aimed to reveal the relationship between prolonged mechanical ventilation and Glasgow Prognostic Score (GPS), in patients aged 65 years and older who underwent isolated CABG. Methods: Patients aged 65 years and over who underwent elective isolated coronary bypass surgery with cardiopulmonary bypass in our clinic, between June 2017 and June 2022, were included in the study retrospectively. The patients who were extubated within eight hours of the surgeries were determined as Group 1, whereas those who were extubated after 8 hours were determined as Group 2. Results: Prolonged ventilation occurred in 101 (20.7%) patients (Group 2). The median age of the 385 patients included in Group 1 and 101 patients in Group 2 was 68 (66 to 91) and 71 (66 to 88) years, respectively (p = 0.216). The two groups were similar in regards to gender, hypertension, smoking, diabetes mellitus, body mass index, history of cerebrovascular accident and left ventricular ejection fraction rates. In the multivariate analysis, left ventricular ejection fraction <35% (OR: 1.136, 95% CI: 1.065-1.652, p = 0.029), total perfusion time (OR: 1.190, 95% CI: 1.040-1.659, p = 0.012), and GPS = 2 (OR: 1.479, 95% CI: 1.130-2.169, p = 0.004) were determined as independent predictors for prolonged ventilation. Conclusions: GPS value calculated preoperatively in elderly patients is a parameter that indicates the increased ventilation need. With the GPS score evaluation, patient groups at risk for prolonged ventilation can be identified and necessary precautions can be undertaken.
Robust assessment of shear parameters from direct shear tests

In the geotechnical determination of the cohesion c and the angle of internal friction ? of a soil from shear tests, a linear regression model is fitted to normal and shear stress data, and confidence bounds are computed. The applicability of standard linear regression is limited by the physical requirement of non-negative cohesion and the statistical requirement of normality. We propose two methods from computational statistics that are able to overcome both obstacles: a bootstrap resampling method in case the experimental data set is sufficiently large, and a Bayesian approach for small samples. The methods are demonstrated at the hand of a real data set for glacial silt.
Sex Differences between Neuronal Loss and the Early Onset of Amyloid Deposits and Behavioral Consequences in 5xFAD Transgenic Mouse as a Model for Alzheimer’s Disease

A promising direction in the research on Alzheimer’s Disease (AD) is the identification of biomarkers that better inform the disease progression of AD. However, the performance of amyloid-based biomarkers in predicting cognitive performance has been shown to be suboptimal. We hypothesise that neuronal loss could better inform cognitive impairment. We have utilised the 5xFAD transgenic mouse model that displays AD pathology at an early phase, already fully manifested after 6 months. We have evaluated the relationships between cognitive impairment, amyloid deposition, and neuronal loss in the hippocampus in both male and female mice. We observed the onset of disease characterized by the emergence of cognitive impairment in 6-month-old 5xFAD mice coinciding with the emergence of neuronal loss in the subiculum, but not amyloid pathology. We also showed that female mice exhibited significantly increased amyloid deposition in the hippocampus and entorhinal cortex, highlighting sex-related differences in the amyloid pathology of this model. Therefore, parameters based on neuronal loss might more accurately reflect disease onset and progression compared to amyloid-based biomarkers in AD patients. Moreover, sex-related differences should be considered in studies involving 5xFAD mouse models.
Mechanical and Tribological Performance of HDPE Matrix Reinforced by Hybrid Gr/TiO2 NPs for Hip Joint Replacement

Hip joint collapse is a very common health problem. Many cases need a joint replacement, so nano-polymeric composites are an ideal alternative solution. Due to its mechanical properties and wear resistance, HDPE might be considered a suitable alternative to frictional materials. The current research focuses on using hybrid nanofiller TiO2 NPs and nano-graphene with various loading compositions to evaluate the best loading amount. The compressive strength, modules of elasticity, and hardness were examined via experiments. The COF and wear resistance were evaluated via a pin-on-disk tribometer. The worn surfaces were analyzed based on 3D topography and SEM images. The HDPE samples with various compositions of 0.5%, 1.0%, 1.5%, and 2.0 wt. % filling content of TiO2 NPs and Gr (with a ratio of 1:1) were analyzed. Results revealed that hybrid nanofiller with a composition of 1.5 wt. % exhibits superior mechanical properties compared to other filling compositions. Moreover, the COF and wear rate decreased by 27.5% and 36.3%, respectively.
Assessment of Certainty of Ventilation Processes Mathematical Modeling

Numerical experiment has been successfully used during recent 10-15 years to solve a wide range of thermal and hydrogasodynamic tasks. Application of mathematical modeling used to design the ventilation systems for production premises characterized by heat emission may be considered to be an effective method to obtain reasonable solutions. Results of calculation performed with numerical solution of ventilation tasks depend on turbulence model selection. Currently a large number of different turbulence models used to calculate turbulent flows are known. Testing and definition of applicability limits for semiempirical models of turbulence should be considered to be a preliminary stage of calculation. This article presents results of test calculations pertaining to thermal air process modeling in premises characterized by presence of heat emission sources performed with employment of different models of turbulence. Besides, analysis of calculation results and comparison with field measurements data are presented.
When Just One Phosphate Is One Too Many: The Multifaceted Interplay between Myc and Kinases

Myc transcription factors are key regulators of many cellular processes, with Myc target genes crucially implicated in the management of cell proliferation and stem pluripotency, energy metabolism, protein synthesis, angiogenesis, DNA damage response, and apoptosis. Given the wide involvement of Myc in cellular dynamics, it is not surprising that its overexpression is frequently associated with cancer. Noteworthy, in cancer cells where high Myc levels are maintained, the overexpression of Myc-associated kinases is often observed and required to foster tumour cells’ proliferation. A mutual interplay exists between Myc and kinases: the latter, which are Myc transcriptional targets, phosphorylate Myc, allowing its transcriptional activity, highlighting a clear regulatory loop. At the protein level, Myc activity and turnover is also tightly regulated by kinases, with a finely tuned balance between translation and rapid protein degradation. In this perspective, we focus on the cross-regulation of Myc and its associated protein kinases underlying similar and redundant mechanisms of regulation at different levels, from transcriptional to post-translational events. Furthermore, a review of the indirect effects of known kinase inhibitors on Myc provides an opportunity to identify alternative and combined therapeutic approaches for cancer treatment.
A Model for Zebrafish Ventricular Action Potential

From the '90s, the interest in the use of zebrafish has exponentially grown thanks to the numerous characteristics, very close to the human ones, that make this little fish very attractive in different fields. Thus, zebrafish has been increasingly proposed as a pharmacological and genetic screening model. The growing interest and the relevance of this animal model motivate the development of a mathematical model of the action potential of the zebrafish to facilitate the understanding of the mechanisms associated with its electrophysiological behavior and how they correlated with those observed in humans. This work presents the first attempt to develop a mathematical model of the adult zebrafish action potential. The model is based on the Ten Tusscher formulation of the action potential of human cardiomyocyte in which the main currents have been reparametrized to be adapted to those of the zebrafish, while extending the model to account for the T-type calcium current present in the zebrafish. Preliminary results of the proposed model show an action potential morphology in good agreement with experimental data.
Spexin2 Is a Novel Food Regulator in Gallus gallus

Spexin2 (SPX2), a paralog of SPX1, is a newly identified gene in non-mammalian vertebrates. Limited studies in fish have evidenced its important role in food intake and energy balance modulation. However, little is known about its biological functions in birds. Using the chicken (c-) as a model, we cloned the full-length cDNA of SPX2 by using RACE-PCR. It is 1189 base pair (bp) in length and predicted to generate a protein of 75 amino acids that contains a 14 amino acids mature peptide. Tissue distribution analysis showed that cSPX2 transcripts were detected in a wide array of tissues, with abundant expression in the pituitary, testis, and adrenal gland. cSPX2 was also observed to be ubiquitously expressed in chicken brain regions, with the highest expression in the hypothalamus. Its expression was significantly upregulated in the hypothalamus after 24 or 36 h of food deprivation, and the feeding behavior of chicks was obviously suppressed after peripheral injection with cSPX2. Mechanistically, further studies evidenced that cSPX2 acts as a satiety factor via upregulating cocaine and amphetamine regulated transcript (CART) and downregulating agouti-related neuropeptide (AGRP) in hypothalamus. Using a pGL4-SRE-luciferase reporter system, cSPX2 was demonstrated to effectively activate a chicken galanin II type receptor (cGALR2), a cGALR2-like receptor (cGALR2L), and a galanin III type receptor (cGALR3), with the highest binding affinity for cGALR2L. Collectively, we firstly identified that cSPX2 serves as a novel appetite monitor in chicken. Our findings will help clarify the physiological functions of SPX2 in birds as well as its functional evolution in vertebrates.
Soft Robots for Cluttered Environments Based on Origami Anisotropic Stiffness Structure (OASS) Inspired by Desert Iguana

Rigidity and softness are essential for robot motion and manipulation in various complex scenarios. To integrate these two contrary features, several variable‐stiffness structures are investigated while requiring a longer processing time and more energy for switching from a stiffer to softer status, with only one status at a specific point in time. Inspired by the combined softness–rigidity hybrid property of desert iguanas’ skin, the concept of an anisotropic stiffness structure is developed, which simultaneously possesses rigidity and softness properties in different directions, leading to the development of novel soft robots. This anisotropic stiffness structure comprises a silicone–paper composite with multiple superimposed origami patterns and has high stiffness and softness properties. The anisotropic stiffness structure is then constructed by developing three novel soft robots: a crawling robot capable of extending and contracting with a payload of 117 times its own weight, a multifunctional prosthetic hand capable of grasping fragile items with its soft side and lifting and crushing items with its hard side, and a snake robot capable of traveling with the soft side and extruding out with over 75% of its body length with the stiffer side.
Robust and efficient estimation of the mode of continuous data: the mode as a viable measure of central tendency

Although a natural measure of the central tendency of a sample of continuous data is its mode the mean and median are the most popular measures of location due to their simplicity and ease of estimation. The median is often used instead of the mean for asymmetric data because it is closer to the mode and is insensitive to extreme values in the sample. However, the mode itself can be reliably estimated by first transforming the data into approximately normal data by raising the values to a real power, and then estimating the mean and standard deviation of the transformed data. With this method, two estimators of the mode of the original data are proposed: a simple estimator based on estimating the mean by the sample mean and the standard deviation by the sample standard deviation, and a more robust estimator based on estimating the mean by the median and the standard deviation by the standardized median absolute deviation. Both of these mode estimators were tested using simulated data drawn from normal (symmetric), lognormal (asymmetric), and Pareto (very asymmetric) distributions. The latter two distributions were chosen to test the generality of the method since they are not power transforms of the normal distribution. Each of the proposed estimators of the mode has a much lower variance than the mean and median for the two asymmetric distributions. When outliers were added to the simulations, the more robust of the two proposed mode estimators had a lower bias and variance than the median for the asymmetric distributions, especially when the level of contamination approached the 50% breakdown point. It is concluded that the mode is often a more reliable measure of location than the mean or median for asymmetric data. The proposed estimators also performed well relative to previous estimators of the mode. While different estimators are better under different conditions, the proposed robust estimator is reliable for a wide variety of distributions and contamination levels.
Critical distance for grating lobe series

Estimating a transition or critical distance above a planar periodic array of point sources radiating into an unbounded medium is considered. It is shown that as an observation point approaches a periodic planar phased array of point sources, the corresponding spectral-domain Green's function, or grating lobe series, converges much more slowly than an equivalent mixed-domain representation exhibiting Gaussian convergence. For a given argument of the Green's function, the critical transition distance above the array for which both representations take the same time to compute can be estimated numerically. Since phased array antenna structures with cavity- or waveguide-type backings often have dimensions that fall well below the critical distance, investigations of such structures would seem to benefit significantly from formulations incorporating such hybrid Green's functions. >
Computable exponential convergence rates for stochastically ordered Markov processes

for every initial state F ' x. 0 The goal of this paper is to identify the largest exponential convergence rate a , or at least to find computationally reasonable bounds for such a ‘‘best’’ a . Coupling techniques are used to derive such results in terms of Ž . 4 i the moment-generating function of the first passage time into state 0 Ž . and ii solutions to drift inequalities involving the generator of the process. The results give explicit bounds for total variation convergence of w Ž . x Ž . Ž . the process; convergence rates for E f F to H f y p dy for an unx t bounded function f are also found. We prove that frequently the bounds obtained are the best possible. Applications are given to dam models and queues where first passage time distributions are tractable, and to one-dimensional reflected diffusions where the generator is the more appropriate tool. An extension of the results to a multivariate setting and an analysis of a tandem queue are also included.
Activation of Mast Cells by Neuropeptides: The Role of Pro-Inflammatory and Anti-Inflammatory Cytokines

Mast cells (MCs) are tissue cells that are derived from bone marrow stem cells that contribute to allergic reactions, inflammatory diseases, innate and adaptive immunity, autoimmunity, and mental disorders. MCs located near the meninges communicate with microglia through the production of mediators such as histamine and tryptase, but also through the secretion of IL-1, IL-6 and TNF, which can create pathological effects in the brain. Preformed chemical mediators of inflammation and tumor necrosis factor (TNF) are rapidly released from the granules of MCs, the only immune cells capable of storing the cytokine TNF, although it can also be produced later through mRNA. The role of MCs in nervous system diseases has been extensively studied and reported in the scientific literature; it is of great clinical interest. However, many of the published articles concern studies on animals (mainly rats or mice) and not on humans. MCs are known to interact with neuropeptides that mediate endothelial cell activation, resulting in central nervous system (CNS) inflammatory disorders. In the brain, MCs interact with neurons causing neuronal excitation with the production of neuropeptides and the release of inflammatory mediators such as cytokines and chemokines. This article explores the current understanding of MC activation by neuropeptide substance P (SP), corticotropin-releasing hormone (CRH), and neurotensin, and the role of pro-inflammatory cytokines, suggesting a therapeutic effect of the anti-inflammatory cytokines IL-37 and IL-38.
Representation and approximation of ambit fields in Hilbert space

We lift ambit fields to a class of Hilbert space-valued volatility modulated Volterra processes. We name this class Hambit fields, and show that they can be expressed as a countable sum of weighted real-valued volatility modulated Volterra processes. Moreover, Hambit fields can be interpreted as the boundary of the mild solution of a certain first order stochastic partial differential equation. This stochastic partial differential equation is formulated on a suitable Hilbert space of functions on the positive real line with values in the state space of the Hambit field. We provide an explicit construction of such a space. Finally, we apply this interpretation of Hambit fields to develop a finite difference scheme, for which we prove convergence under some Lipschitz conditions.
Linearization of The Timing Analysis and Optimization of Level-Sensitive Circuits

This thesis describes a linear programming (LP) formulation applicable to the static timing analysis of large scale synchronous circuits with level-sensitive latches. The automatic timing analysis procedure presented here is composed of deriving the connectivity information, constructing the LP model and solving the clock period minimization problem of synchronous digital VLSI circuits. In synchronous circuits with level-sensitive latches, operation at a reduced clock period (higher clock frequency) is possible by takingadvantage of both non-zero clock skew scheduling and time borrowing. Clock skew schedulingis performed in order to exploit the benefits of nonidentical clock signal delays on circuit timing. The time borrowing property of level-sensitive circuits permits higher operating frequencies compared to edge-sensitivecircuits. Considering time borrowing in the timing analysis, however, introduces non-linearity in this timing analysis. The modified big M (MBM) method is defined in order to transform the non-linear constraints arising in the problem formulation into solvable linear constraints. Equivalent LP model problemsfor single-phase clock synchronization of the ISCAS'89 benchmark circuits are generated and these problems are solved by the industrial LP solver CPLEX. Through the simultaneous application of time borrowing and clock skew scheduling, up to 63% improvements are demonstrated in minimum clock period with respect to zero-skew edge-sensitive synchronous circuits. The timing constraints governing thelevel-sensitive synchronous circuit operation not only solve the clock period minimization problem but also provide a common framework for the general timing analysis of such circuits. The inclusion of additional constraints into the problem formulation in order to meet the timing requirements imposed by specific applicationenvironments is discussed.