Miracle-dz/UniFAR-FTUs huggingface dataset:
MRC-5 Human Lung Fibroblasts Alleviate the Genotoxic Effect of Fe-N Co-Doped Titanium Dioxide Nanoparticles through an OGG1/2-Dependent Reparatory Mechanism

The current study was focused on the potential of pure P25 TiO2 nanoparticles (NPs) and Fe(1%)-N co-doped P25 TiO2 NPs to induce cyto- and genotoxic effects in MRC-5 human pulmonary fibroblasts. The oxidative lesions of P25 NPs were reflected in the amount of 8-hydroxydeoxyguanosine accumulated in DNA and the lysosomal damage produced, but iron-doping partially suppressed these effects. However, neither P25 nor Fe(1%)-N co-doped P25 NPs had such a serious effect of inducing DNA fragmentation or activating apoptosis signaling. Moreover, oxo-guanine glycosylase 1/2, a key enzyme of the base excision repair mechanism, was overexpressed in response to the oxidative DNA deterioration induced by P25 and P25-Fe(1%)-N NPs.
Acute Ozone-Induced Transcriptional Changes in Markers of Oxidative Stress and Glucocorticoid Signaling in the Rat Hippocampus and Hypothalamus Are Sex-Specific

Exposure to a prototypic air pollutant ozone (O3) has been associated with the activation of neuroendocrine stress response along with neural changes in oxidative stress (OS), inflammation, and Alzheimer’s disease-like pathologies in susceptible animal models. We hypothesized that neural oxidative and transcriptional changes induced by O3 in stress responsive regions are sex-dependent. Male and female adult Long–Evans rats were exposed to filtered air or O3 for two consecutive days (0.8 ppm, 4 h/day) and brain regions were flash-frozen. Activities of cerebellar OS parameters and mitochondrial complex I, II, and IV enzymes were assessed to confirm prior findings. We assessed transcriptional changes in hypothalamus (HYP) and hippocampus (HIP) for markers of OS, microglial activity and glucocorticoid signaling using qPCR. Although there were no O3 or sex-related differences in the cerebellar activities of OS and mitochondrial enzymes, the levels of protein carbonyls and complex II activities were higher in females regardless of O3. There were no statistical differences in baseline expression of genes related to OS (Cat, Dhcr24, Foxm1, Gpx1, Gss, Nfe2l2, Sod1) except for lower HYP Sod1 expression in air-exposed females than males, and higher HIP Gss expression in O3-exposed females relative to matched males. Microglial marker Aif1 expression was higher in O3-exposed females relative to males; O3 inhibited Itgam only in males. The expression of Bdnf in HIP and HYP was inhibited by O3 in both sexes. Genes related to glucocorticoid signaling (Fkbp4, Fkbp5, Hsp90aa1, Hspa4, nr3c1, nr3c2) showed sex-specific effects due to O3 exposure. Baseline expression of HIP Fkbp4 was higher in females relative to males. O3 inhibited Nr3c1 in female HIP and male HYP, but Nr3c2 was inhibited in male HYP. Fkbp4 expression was higher in O3-exposed females when compared to matched males, whereas Fkbp5 was expressed at higher levels in both brain regions of males and females. These results indicate that sex-specific brain region responses to O3 might, in part, be caused by OS and regulation of glucocorticoid signaling.
New results in the existence of complex covariance estimates

The problem of generating a positive definite maximum likelihood (ML) estimate of a complex Toeplitz covariance matrix given one N-length data vector is considered. The data vector is assumed to be drawn from a complex Gaussian population with mean zero and covariance sigma /sup 2/I. An upper bound is derived on the measure of the set of such N-length data vectors such that, for one data vector, the ML estimation procedure yields a positive definite solution. These data vectors are denoted as those that do not satisfy the failure condition of the ML estimation procedure, and it is shown that the measure of the set of such data vectors is small and converges to zero as the length of the data vector increases. <<ETX>>
Analysis and generalisation of a multivariate exponential smoothing model

The multivariate exponential smoothing model of Enns, Machak, Spivey and Wrobleski is examined and it is found that its structure is such that it can be estimated by using techniques designed for a univariate exponential smoothing model. Similarly forecasts can be made using algorithms for the univariate model. The model can therefore be handled very easily. A more general univariate time series model, which can include polynomial trends and seasonal factors, is then set up and a multivariate generalisation, analogous to the multivariate exponential smoothing model, is introduced. It is shown that this model can also be handled using algorithms designed for the univariate case.
Floating-Point Roundoff Error Analysis in Artificial Neural Networks

– In this paper, roundoff errors in Artiﬁcial Neural Networks (ANNs) are analyzed on a model for Solid-State Power Ampliﬁers (SSPAs). Calculations are carried out on 32-bit Floating-Point (FP32) arithmetics, and results are veriﬁed using 64-bit ﬂoating-point representation as reference. Besides the modeling of quantization noise at every operation, error propagation is also taken into consideration when calculating the cumulative Quantization Noise Power (QNP) after each stage and at the ﬁnal output. By this means, the pre-dictability of roundoff errors in the ANN is demonstrated. Consequently, it can be determined whether the FP32 arithmetic is sufﬁcient instead of applying the computationally more demanding 64-bit calculations.
Low-Order Mechanistic Models for Volumetric and Temporal Capnography: Development, Validation, and Application

<italic>Objective</italic>: Develop low-order mechanistic models accounting <italic>quantitatively</italic> for, and <italic>identifiable</italic> from, the <italic>capnogram</italic> — the CO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula> concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). <italic>Methods</italic>: The <italic>airflow</italic> model's single “alveolar” compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The <italic>gas-mixing</italic> model tracks mixing-region CO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula> concentration, fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. <italic>Results</italic>: For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal CO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula> concentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with literature values. The models also allow, <italic>using Tcap alone</italic>, estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. <italic>Conclusion</italic>: Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. <italic>Significance</italic>: This can inform cardiorespiratory care.
Spatial location-based outdoor mobile augmented reality 3D registration technology

Human activities are closely related to geographic location. It is proposed to combine spatial location and mobile terminal pose sensor data with meeting the characteristics of real-time accuracy and flexibility in outdoor mobile augmented reality and to realize the virtual-real superposition through the transformation relationship between 3D model coordinate system, world coordinate system, camera coordinate system, image coordinate system, and pixel coordinate system. For the limitations of the vision-based registration method in outdoor scenes, this paper derives the transformation from spatial location data to screen coordinates in detail. It gives the solution and optimization of the transformation matrix and parameters.
Risk Assessment and Characterization in Tuna Species of the Canary Islands According to Their Metal Content

Bioaccumulation is the process by which living organisms accumulate substances, such as pesticides, heavy metals, and other pollutants, from their environment. These substances can accumulate in the organism’s tissues over time, leading to potential health risks. Bioaccumulation can occur in both aquatic and terrestrial ecosystems, and can have a significant impact on the health of both humans and wildlife. The objective of this study is to find out if the concentrations of metals in the tuna species of the Canary Islands are suitable for human consumption and if they pose a health risk. Fifteen samples of Acanthocybium solandri, Katsuwonus pelamis, Thunnus albacares, Thunnus obesus and Thunnus thynnus present in canaries were analyzed. Ten grams of muscle were taken from each specimen and the metals Al, Cd, Cr, Cu, Fe, Li, Ni, Pb and Zn were determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The tuna species that presented more metals with a higher concentration compared to the others was T. thynnus, reaching up to 100 times more than the other studied species in Fe content with 137.8 ± 100.9 mg/Kg, which may be due to the fact that it is the largest species that reaches ages of more than fifteen years. The species Thunnus thynnus should not be suitable for commercialization according to the current legislation on the concentrations of Cd in blue fish, since 75% of the specimens studied exceeded the concentration legislated for Cd. A total of 40% of the studied specimens of this this species exceeded the legislated values for the concentration of Pb in oily fish meat, so this species must be monitored to ensure that it does not pose a risk to human health.
STAR-RIS Assisted Wireless Powered IoT Networks

The paper proposes a novel design of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) in a wireless powered Internet of Things (IoT) network, where two sensor node groups (SNGs) harvest energy from a power station (PS) and transmit their message to an access point (AP) with the harvested energy. The STAR-RIS, which is deployed in the middle of the SNGs and adopts the time splitting (TS) working mode, can help the energy transfer in the wireless energy transfer (WET) phase and the information transfer in the wireless information transfer (WIT) phase. The paper aims to maximize the sum throughput from the two SNGs to the AP by jointly designing the phase shifts of the STAR-RIS and the working time allocated to the two SNGs in the WET and WIT phases, respectively. To solve the formulated non-convex optimization problem, we propose a low-complexity algorithm where we first derive the optimal phase shifts of the STAR-RIS in the WIT phase. Then, we adopt the Lagrange dual method to simplify the optimization problem and optimize the phase shifts of the STAR-RIS in the WET phase by the Majorization-Minimization (MM) algorithm and the complex circle manifold (CCM) algorithm. Next, a two-layer iterative algorithm is used to obtain the optimal values of time allocated to the two SNGs. Finally, we evaluate the improvement of the proposed scheme by the simulation results compared with other benchmark schemes.
On power groups and embedding theorems for relatively free profinite monoids

We determine those pseudovarieties of groups ${\bf H}$ for which the power monoids $P(G)$, ranging over all groups $G$ in ${\bf H}$, satisfy the same profinite identities (i.e. pseudoidentities) as all semidirect products of ${\cal J}$-trivial monoids by groups in ${\bf H}$. That is, in the language of finite monoid theory, we characterize all solutions to the pseudovariety equation ${\bf PH}\,{=}\,{\bf J}\ast {\bf H}$. The characterization is in terms of the geometry of the Cayley graphs of the free pro-${\bf H}$ groups as well as in terms of the pro-${\bf H}$ topology of a finitely generated free group.
Exponential multiplicity of inherent structures

The mechanically stable spatial arrangements of interacting molecules ~potential energy minima, ‘‘inherent structures’’! provide a discrete fiducial basis for understanding condensed phase properties. Simple plausibility arguments have been advanced previously suggesting that at fixed positive density the number of distinguishable inherent structures rises exponentially with system size. A more systematic analysis is presented here, using lower and upper bounds, that leads to the same conclusion. Further examination reveals that the characteristic exponential rise rate for inherent structure enumeration diverges as the density approaches zero, when attractive interparticle forces are present. @S1063-651X~99! 07001-4#
Introduction to mathematical modeling using discrete dynamical systems

This book is an introductory treatise on discrete models and their dynamics. It provides an introduction to the dynamics of discrete models and their applications. The book has five chapters and an Appendix. The presentation is devoted to oneand two-dimensional discrete models except at the end of Chapter 4, where examples of a three-state Markov process and an exercise touching n-dimensional systems are provided. Chapter 2 is dedicated to the basic techniques of solving one-dimensional linear models of both autonomous and non-autonomous equations. Other concepts addressed in this book include stability analysis of fixed points and mcycles of one-dimensional nonlinear models in Chapter 3. The dynamics of twodimensional linear systems is presented in Chapter 4. Based on this linear theory, local stability of two-dimensional nonlinear systems and a brief discussion of bifurcation and chaotic dynamics are presented in Chapter 5. The chapter also provides introductory examples to show the complex nature of chaotic dynamics exhibited by simple discrete models. It is followed by some examples of fractals on a line and on the plane. However, theories of discrete dynamical systems involving more complicated mathematical tools are not mentioned. In addition, only local stability of fixed points for nonlinear equations is discussed and there is no remark about any global dynamics for the interested readers. Applications of basic discrete dynamics to problems arising from ecology, economics, finance and epidemics are presented throughout the five chapters. Figures are also included to illustrate dynamics of the baseline equations and of solutions to related models emerging from applications. These efforts of connecting theory with applications and of numerical illustrations shed light on the concepts introduced and help to motivate the reader. Computer projects are assigned at the end of each chapter and computation techniques using Microsoft Excel and Mathematica are provided in the Appendix. Exercises are included at the end of each section and answers to some of the odd numbered problems are given right after the Appendix. The book is self-contained with a summary of relevant background material, including sequence and series, vector, matrix algebra and complex numbers. Overall, this book is a good introduction for readers who are interested in learning about discrete dynamics and their applications to mathematical models.
Eating Patterns of Young Women (18–25 y) with Overweight and Obesity: A Preliminary Investigation

Overweight and obesity impact up to 40% of young women in Australia; however, young women are challenging to recruit to research and are rarely the focus of weight loss interventions. This study aimed to examine dietary patterns in young women (18–25 years; BMI > 25 kg/m2). An analysis of participants’ (mean age: 22.6 year; BMI: 32.2 kg/m2) 3-day food records found young women with overweight/obesity consumed a diet characterised by total energy intake of 9174 (2526) kJ/day, with the first meal at 9:12 am (range: 4:30 am–12:40 pm), the last at 10:43 pm (range: 2:40 pm–2:00 am), and an average eating window of 11.5 h. Young women had poor quality diets, which did not meet dietary recommendations for most core food groups, and high intake of refined carbohydrates. They also reported consuming at least one takeaway meal per day and >30% of total energy intake was from discretionary items. The findings showed that young women with overweight or obesity consume most of their energy intake in the afternoons and late into the evenings and have poor-quality diets with high-discretionary intake, each of which have been shown in previous work to be associated with increased weight and risk of metabolic comorbidities. While these findings require further examination in larger groups with both qualitative and longitudinal data collection to verify the impact of these eating patterns on weight maintenance, the eating behaviours identified here may present a suitable target for novel weight loss interventions in young women, who are an understudied population group in need of tailored weight management solutions.
An experiment on boundary mixing. Part 2 The slope dependence at small angles

Experiments of the type described by Phillips et al. (1986) were performed using different slopes with the aim of examining the slope dependence of the buoyancy and volume transports, particularly at small slopes. The new observations confirmed the general flow patterns described for experiments conducted at a fixed slope, but a reconsideration of the local balances suggest that the buoyancy flux at small slopes θ is proportional to $(\kappa N)^{\frac{3}{2}}\sin\theta $, where κ is the turbulent diffusivity. and the volume flux associated with the overall convergence flow is linear with depth and proportional to (κ3/2/N½h) sin θ, where h is the thickness of the pycnocline. These differ in their dependence on the slope suggested (but not tested) in Phillips et al., and are generally consistent with measurements over a range of slopes from 7.1° to 23.5°.
Why, how, and when, MHD turbulence becomes two-dimensional

A description of MHD turbulence at low magnetic Reynolds number and large interaction parameter is proposed, in which attention is focussed on the role of insulating walls perpendicular to a uniform applied magnetic field. The flow is divided in two regions: the thin Hartmann layers near the walls, and the bulk of the flow. In the latter region, a kind of electromagnetic diffusion along the magnetic field lines (a degenerate form of Alfvén waves) is displayed, which elongates the turbulent eddies in the field direction, but is not sufficient to generate a two-dimensional dynamics. However the normal derivative of velocity must be zero (to leading order) at the boundaries of the bulk region (as at a free surface), so that when the length scale l⊥ perpendicular to the magnetic field is large enough, the corresponding eddies are necessarily two-dimensional. Furthermore, if l⊥ is not larger than a second limit, the Hartmann braking effect is negligible and the dynamics of these eddies is described by the ordinary Navier-Stokes equations without electromagnetic forces. MHD then appears to offer a means of achieving experiments on two-dimensional turbulence, and of deducing velocity and vorticity from measurements of electric field.
Remote sensing image segmentation network based on attention mechanism feature fusion

For remote sensing image segmentation projects, it is usually necessary to segment the boundary of ground objects finely, but the fitting of the boundary is a difficult problem in deep learning image segmentation. At the same time, for remote sensing images taken from high altitude, usually many large-scale targets in natural scenes will become small target objects in remote sensing images. To solve this problem, in order to improve the recognition effect of remote sensing image scene targets with huge scale differences, this paper combines UNet and FPN. This paper uses the framework of pytorch1.7. 1 to establish the UNet + FPN model. Through the experimental results and visual analysis of building data sets and road data sets, the model in this paper has obvious advantages.
EASIX Is an Accurate and Easily Available Prognostic Score in Critically Ill Patients with Advanced Liver Disease

Acute-on-chronic liver failure (ACLF) is associated with high mortality. Objective prognostic scores are important for treatment decisions. EASIX (Endothelial Activation and Stress Index) is a simple biomarker consisting of LDH, platelets, and creatinine, reflecting endothelial dysfunction after allogeneic stem cell transplantation. Considering endothelial dysfunction in the pathogenesis of ACLF, this study aimed to test the discriminative ability of EASIX in advanced liver disease. We retrospectively analysed the prognostic potential of EASIX to predict 28-day and 3-month mortality in a total of 188 liver cirrhotic patients requiring treatment at the intensive care unit. We evaluated the ability of EASIX to rule out early infections and predict the need for hemodialysis. EASIX performed moderately better than established scores in predicting 28-day mortality (AUC = 0.771) and was nearly equivalent (AUC = 0.791) to SOFA and APACHE-II in the prediction of 3-month mortality. Importantly, EASIX showed better diagnostic potential in ruling out clinically apparent infections than common proinflammatory markers (AUC = 0.861, p < 0.001) and showed suitable accuracy in predicting the need for hemodialysis (AUC = 0.833). EASIX is an accurate, objective and easily assessable biomarker for predicting mortality and complications in patients with advanced liver disease.
Review on Z-Source Solid State Circuit Breakers for DC Distribution Networks

—DC technologies will be essential building blocks for future DC distribution networks. As in any DC system, these networks will face crucial threats imposed by short-circuit DC faults. Protection is thus of great interest, and it will likely rely on DC circuit breakers (DCCBs). Among available configurations, Z -source solid-state circuit breakers (Z-SSCBs) are promising candidates for protecting low and medium-voltage distribution networks, as well as DC equipment due to their structural and control simplicity and low cost. In this paper, start-of-the-art of Z-SSCBs topologies is reviewed. To set the context, the use of DC technologies for grid integration of renewables, DC power transmission, and the main types of DCCBs to protect DC transmission and distribution corridors are discussed. The Z-SSCB topologies are then classified into unidirectional and bidirectional. Advantages and disadvantages of different configurations are compared and analyzed based on existing research. Finally, a perspective on the future development of Z-SSCBs is discussed and potential challenges are elucidated.