Miracle-dz/UniFAR-FTUs huggingface dataset:
A Diagnostic Study of the Isentropic Zonally Averaged Mass Circulation during the First GARP Global Experiment

Abstract The mass circulation of the zonally averaged global circulation is investigated in isobaric and isentropic coordinates through the use of a FGGE Level IIIa data set. The isobaric mass circulation during the First GARP Global Experiment is consistent with previous results, i.e., direct Hadley cells in low latitudes and indirect Ferrel cells in midlatitudes of both hemispheres. Within the isentropic framework, the combination of a geostrophic mean mode of mass transport within the baroclinic wave structure of extratropical latitudes, and an ageostrophic mean mode in tropical latitudes, yields an isentropic mass circulation spanning the hemisphere. The asymmetric structure of midlatitude baroclinic waves provides the degree of freedom for a geostrophic mode of mass transport that is fundamental to the direct Hadley-type circulation in isentropic coordinates. This direct Hadley-type circulation is explicitly linked to heat sources and sinks on a planetary scale. The diabatic heating estimated from th.
H2,α‐norm optimal model reduction for optimal control problems subject to parabolic and hyperbolic evolution equations

This paper deals with a numerical solution method for optimal control problems subject to parabolic and hyperbolic evolution equations. Firstly, the problem is semi‐discretized in space with the boundary or distributed controls as input and those parts of the discretized state appearing in the cost functional as output variables. The corresponding transfer function is then approximated optimally with respect to the H2,α‐norm providing an optimally reduced optimal control problem, which is finally solved by a first‐discretize‐then‐optimize approach. To enable the application of this reduction method, a new constrained optimal model reduction problem subject to reduced systems with real system matrices is considered. Necessary optimality conditions and a transformation procedure for the reduced system to a canonical form of real matrices are presented. The method is illustrated with numerical examples where also complicated controls with many bang‐bang arcs are investigated. The approximation quality of the optimal control and its correlation to the decay rate of the Hankel singular values of the system are numerically studied. A comparison to the approach of using Balanced Truncation for model reduction is applied. Copyright © 2013 John Wiley & Sons, Ltd.
Digital Gamification in Unified Payment Interface (UPI) towards Sustainable Development Goals

Gamification and Digital India are changing the world’s perception of digital payments. This research study highlights the digital Gamification contribution towards the success of the Unified Payment Interface system (UPI). Where different countries are still in the surge of the globally digitally accepted platform, the India UPI system is receiving global acceptance. The author highlighted the contribution of Gamification and digital strategy’s contribution to sustainable development goals towards climate change. Gamification is evident in different areas and is not limited to the financial sector. However, keeping up with the sustainable development goals of the United Nations is a critical challenge for every country. The study discusses the world’s largest growing economy India and its contribution towards different sustainable development goals opening a new era of partnership towards common goals.
Highly Efficient 2.45 GHz Rectifier Circuit for RF Energy Harvesting Applications

The improved bridge rectifier shown in this study was built utilizing four Schottky diodes. In order to precisely forecast the rectifier performances, the Microwave rectifier has been simulated on Agilent ADS 2019 at 2.45 GHz with associated circuit techniques. Since the provided rectifier’s circuit is devoid of an HF filter and a bypass capacitor, it is both compact and effective. At 1.2 mW power at the input terminal, the circuit has a maximum efficiency of 52.248% while converting RF to DC.
Evaluating the genetic interaction effects of gut microbiome and diet on the risk of neuroticism in the UK Biobank cohort

Objectives In this study designed to investigate the effect of diet and gut microbiome on neuropsychiatric disorders, we explored the mechanisms of the interaction between diet and gut microbiome on the risk of neuroticism. Methods First, using the individual genotype data from the UK Biobank cohort (N = 306 165), we calculated the polygenic risk score (PRS) based on 814 dietary habits single nucleotide polymorphisms (SNPs), 21 diet compositions SNPs and 1001 gut microbiome SNPs, respectively. Gut microbiome and diet-associated SNPs were collected from three genome-wide association studies (GWAS), including the gut microbiome (N = 3890), diet compositions (over 235 000 subjects) and dietary habits (N = 449 210). The neuroticism score was calculated by 12 questions from the Eysenck Personality Inventory Neuroticism scale. Then, regression analysis was performed to evaluate the interaction effects between diet and the gut microbiome on the risk of neuroticism. Results Our studies demonstrated multiple candidate interactions between diet and gut microbiome, such as protein vs. Bifidobacterium (β = 4.59 × 10−3; P = 9.45 × 10−3) and fat vs. Clostridia (β = 3.67 × 10−3; P = 3.90 × 10−2). In addition, pieces of fresh fruit per day vs. Ruminococcus (β = −5.79 × 10−3, P = 1.10 × 10−3) and pieces of dried fruit per day vs. Clostridiales (β = −5.63 × 10−3, P = 1.49 × 10−3) were found to be negatively associated with neuroticism in fruit types. We also identified several positive interactions, such as tablespoons of raw vegetables per day vs. Veillonella (β = 5.92 × 10−3, P = 9.21 × 10−4) and cooked vegetables per day vs. Acidaminococcaceae (β = 5.69 × 10−3, P = 1.24 × 10−3). Conclusions Our results provide novel clues for understanding the roles of diet and gut microbiome in the development of neuroticism.
Positive streamer between parallel plate electrodes in atmospheric pressure air

The results of a two-dimensional simulation of a cylindrically symmetric positive streamer in atmospheric pressure air between parallel plate electrodes are reported. A hydrodynamic diffusion - drift model was used. The results show that the streamer radius and velocity grow exponentially in time. We have found that the main parameter which governs streamer propagation is the width of the space charge front . It is shown that: (i) the field at the tip of the streamer is equivalent to the field of a charged ball of radius ; and (ii) the streamer velocity is proportional to , as previously predicted by Loeb [1]. The mechanism of streamer propagation is discussed. It is shown that positive streamer advancement occurs due to avalanche multiplication of primary photoelectrons in the narrow layer of the width ahead of the streamer. The energy delivered by the power supply is calculated. This energy accumulates as electrostatic energy of the space charge envelope around streamer channel. The energy increases exponentially in time and reaches when the streamer radius is about 20 cm.
Fuzzy Modeling of Diesel Engine using Modified Self-Organizing Map Network

This article deals with a problem of nonlinear identification of big power diesel engine 12V180ZJ equipped on locomotive. A new nonlinear fuzzy model is proposed. The model is identified as black-box model with input-output training data. A modified self-organizing map (MSOM) network is developed for generating parameters of fuzzy model. Based on the MSOM, fuzzy rules are determined automatically according to the distribution of training data in the input-output space and the given approximating error. Simulating result idicates that the nonlinear model depicts the statics and dynamics of diesel engine accurately. This nonlinear model can be used to design the control system of diesel engine, and understand its complex dynamics.
The Fisher information matrix for log linear models arguing conditionally on observed explanatory variable

SUMMARY For Poisson or multinomial contingency table data the conditional distribution is product multinomial when conditioning on observed values of explanatory variables. Birch (1963) showed that under the restriction formed by keeping the marginal totals of one margin fixed at their observed values the Poisson, multinomial and product multinomial likelihoods are proportional and give the same estimates for common parameters in the log linear model. Here the inverses of the Fisher information matrices are shown to be identical over common parameters so that the asymptotic covariance matrices of the estimates correspond.
Exchange-bias-like coupling in a ferrimagnetic Fe/Tb multilayer

Field cooling of a transition metal-rare earth (TM-RE) Fe/Tb-multilayer system is shown to form a double hysteresis loop with exchange-bias-like shifts along and opposite to the field cooling axis below the ordering temperature of the RE. The measurement of the polarized neutron reflectivity at various applied fields confirms an antiferromagnetic alignment between the individual layers of Fe and Tb associated with a significant value of the magnetic moment for the Tb layers, even at room temperature. We attribute the shifts of the hysteresis loops to the formation of 2$\ensuremath{\pi}$-domain walls by the interface moments that are pinned by the magnetically hard Tb layers forming bidomainlike states in this layered artificial ferrimagnetic system. We conclude that the exchange bias in Fe/Tb-multilayers, the RE layers being on either sides of the TM layers, is caused by the formation of 2$\ensuremath{\pi}$-domain walls in the Fe layers thus excluding an explanation in terms of $\ensuremath{\pi}$-domain walls, which are believed to be responsible for the exchange bias in other RE-TM bilayer systems.
Development and Validation of a Novel Tool to Predict Model for End-Stage Liver Disease (MELD) Scores in Cirrhosis, Using Administrative Datasets

Background The Model for End-Stage Liver Disease (MELD) score predicts disease severity and mortality in cirrhosis. To improve cirrhosis phenotyping in administrative databases lacking laboratory data, we aimed to develop and externally validate claims-based MELD prediction models, using claims data linked to electronic health records (EHR). Methods We included adults with established cirrhosis in two Medicare-linked EHR networks (training and internal validation; 2007–2017), and a Medicaid-linked EHR network (external validation; 2000–2014). Using least absolute shrinkage and selection operator (LASSO) with 5-fold cross-validation, we selected among 146 investigator-specified variables to develop models for predicting continuous MELD and relevant MELD categories (MELD<10, MELD≥15 and MELD≥20), with observed MELD calculated from laboratory data. Regression coefficients for each model were applied to the validation sets to predict patient-level MELD and assess model performance. Results We identified 4501 patients in the Medicare training set (mean age 75.1 years, 18.5% female, mean MELD=13.0), and 2435 patients in the Medicare validation set (mean age: 74.3 years, 31.7% female, mean MELD=12.3). Our final model for predicting continuous MELD included 112 variables, explaining 58% of observed MELD variability; in the Medicare validation set, the area-under-the-receiver operating characteristic curves (AUC) for MELD<10 and MELD≥15 were 0.84 and 0.90, respectively; the AUC for the model predicting MELD≥20 (using 27 variables) was 0.93. Overall, these models correctly classified 77% of patients with MELD<10 (95% CI=0.75–0.78), 85% of patients with MELD≥15 (95% CI=0.84–0.87), and 87% of patients with MELD≥20 (95% CI=0.86–0.88). Results were consistent in the external validation set (n=2240). Conclusion Our MELD prediction tools can be used to improve cirrhosis phenotyping in administrative datasets lacking laboratory data.
Formalized of Model of Linear Kind for Differentiate Distributed Network Attacks on the Basis of a Weight Coefficients

: This study discusses the problem distributed network attacks, formalized of model of linear kind for differentiate distributed network attacks on the basis of a weight coefficients Structured the formalized mathematical models allow to consider structure of the On network to a basis big percent, a measure of influence of each type of attack that gives the fine chance effectively to design to protect information system taking into account information on threats. Based on classification of information threats, characteristic for distributed network attacks it is offered the formalized models of a linear look for differentiation of attacks on the basis of a method of weight coefficients. By these indicators and coefficients it is possible to define the main types of threats in computer systems allowing to design effectively systems of information security taking into account information threats.
Safety Helmet Wearing Detection Model Based on Improved YOLO-M

In recent years, construction accidents have occurred frequently. The safety guarantee measures for construction personnel are thrown into sharp focus. Wearing helmets is one of the most important requirements to protect the safety of construction personnel, and the detection of wearing safety helmets has become necessary. For the problems of the existing helmet wearing detection algorithm such as too many parameters, substantial detection interferences, and low detection accuracy, in this paper a helmet wearing detection model YOLO-M is proposed. Firstly, MobileNetv3 is adopted as the backbone network of YOLOv5s for the feature extraction, which can reduce the number of model parameters and model size. Secondly, a residual edge is introduced in the feature fusion. The original feature map information is fused during feature fusion, and the detection ability of small targets is enhanced. At last, by changing the connection between CAM and SAM, a new attention module BiCAM is designed. The comparison experiments show that the detection accuracy of YOLO-M is 2.22% higher than YOLOv5s, and the model parameter quantity is reduced to 3/4 of YOLOv5s. Under the same detection conditions, the detection speed of YOLO-M is better than the other models, which meets the accuracy requirements of helmet detection in the construction scene.
Comparative radiosensitization efficiency assessment of graphene oxide and Ti3C2 MXene as 2D carbon-based nanoparticles against breast cancer cells: characterization, toxicity and mechanisms

The efficacy of two carbon-based nanomaterials, graphene oxide (GO) and Ti3C2 MXene (MX), on the radiosensitivity of the breast cancer cells (BCCs) was investigated using clinical x-ray irradiation. The prepared GO and MX nanoparticles (NPs) were firstly characterized utilizing Fourier transform infrared, ultraviolet–visible, atomic force microscopy and transmission electron microscopy techniques and subsequently assessed in terms of their radiobiological properties. The results of the cell toxicity assay indicated that neither NPs exhibited significant cytotoxicity after 48 h incubation with BCC up to 50 µg ml−1 concentration without irradiation. The cell internalization results showed an approximately equivalent cellular uptake for both NPs after 6 h incubation with BCC. Our comparative studies with radiotherapy demonstrated that both NPs substantially increased cell proliferation inhibition and cell apoptosis of BCC under x-ray irradiation when compared to BCC treated with irradiation alone. Additionally, the 2ʹ,7ʹ-dichlorofluorescin diacetate flow cytometry results and fluorescent microscopy images revealed that both NPs remarkably increased the level of intracellular reactive oxygen species (ROS) generation in BCC under x-ray irradiation. The MX nanosheets exhibited superior radiosensitization efficiency than GO under x-ray irradiation due to its higher level of intracellular ROS generation (MX = 75.2% and GO = 65.2%). Clonogenic cell survival assay and extracted radiobiological parameters revealed that both NPs in combination with x-ray irradiation induced more lethal damage and less sublethal damage to BCC. Generally, the obtained results demonstrate that the MX NPs, as a stronger radiosensitizer than GO, could be a promising candidate for enhancing the effectiveness of radiotherapy in breast cancer treatment.
Global linear independence and finitely supported dual basis

Relating the global linear independence of an arbitrary locally finite family of functions to the basic fact that a linear map is onto if and only if its adjoint is 1-1, it is shown that any locally finite and globally linearly independent family of functions has a dual basis consisting of finitely supported linear functionals.
Characteristic temperature analysis for PbSe/PbSrSe multiple quantum well structure

The characteristic temperature calculations and dependency on cavity length was analyzed for Pb0.934Sr0. 066 Se multiple Quantum well Structure at three temperature ranges 77<T<150 K, 150<T<300 K, and 77<T<300 K. In this work, we show the behavior of the characteristic temperature as a function of cavity length and were able to best fit the data to a second degree polynomial. Inclusion of theoretical values for the quantum efficiency due to Auger recombination reduces the characteristic temperature T0 in these ranges. It was found that inclusion of the quantum efficiency decreases the characteristic temperature by a factor of 0.6 for a wide range of cavity lengths. When results were compared to experimental data, it was concluded that there is a leakage current above the barrier due to thermionic emission. The leakage current density was estimated to be around 5423 A/cm2 at room temperature. With this high value more work is needed to understand the thermionic emission process to improve on the performance of this material system and similar ones.
Special Issue on Symbolic Numeric Algebra for Polynomials

The worlds of symbolic and numeric computation have had surprisingly little overlap since the invention of the digital computer. The problems addressed, the techniques, the literature — in short, the cultures — have had largely separate developments. This has been a reflection of the backgrounds of the scientists who were active in the two areas in the 1970s: the fundamental algorithms of symbolic computation, or computer algebra, were to a great extent developed by individuals with a background in modern algebra. Numerical computation or numerical analysis attracted instead applied mathematicians, with hard core analysis at their fingertips. Since that time, computer algebra has largely viewed the world as consisting of discrete objects whereas numerical analysis sees a continuous world virtually everywhere. This has been particularly striking in polynomial algebra, the problem area of this special issue, where a good number of natural problems have been addressed by both communities, with practically no intersection of results until fairly recently. The methods used in one setting are usually not directly transferable to the other: algorithms designed for exact computation may be numerically unstable or break down in a numerical setting because tests like “a 6= 0 ? ” become meaningless. Most numerical algorithms, on the other hand, cannot reasonably be applied to discrete problems or suffer problems of intermediate expression swell. Thus, to conquer the largely unexplored area between computer algebra and numerical analysis, the two cultures must move towards each other and acknowledge each other’s existence and particular traits, and they must learn each other’s language. Appropriate approaches must use ideas and algorithmic techniques from numeric computation together with standard and possibly extended procedures from classical computer algebra. Fundamental in this collaboration will be two factors: the computer algebra community’s realization that computational algebraic problems must be immersed in an analytic context if their numerical solution is to make sense; and the realization by the numerical analysis community that algebraic methods can reveal information about computational algebraic problems which facilitates their numerical solution decisively. The challenges posed by the immersion of linear algebra into a setting of potentially inexact data and inexact computation have spawned the well-known area of “numerical linear algebra” which has become not only one of the fastest growing areas in mathematics but also the indispensable foundation for almost all of scientific computing. Thus, the emerging area of mathematics dealing with inexact computation in algebraic problems of an intrinsically nonlinear nature might appropriately be called “numerical nonlinear algebra”. Within that area, the consideration of computational problems with polynomials will certainly be a core subject: specific polynomials over a field of characteristic zero
The effect of nutritional and lifestyle education intervention program on nutrition knowledge, diet quality, lifestyle, and nutritional status of Croatian school children

Introduction Nutrition education during adolescence has proven effective in increasing knowledge, attitudes, and practices in the diet. The Mediterranean diet has proven health benefits and is proposed as a model of a sustainable diet that is beneficial for health and the environment. Its promotion with the educational program can have a significant effect on improvements in nutrition knowledge, diet quality, and nutritive status of adolescents for their healthy adulthood. Objective This study aimed to investigate the effect of the educational program on the nutrition knowledge, diet quality, lifestyle, and nutritional status of school children from the littoral part of Croatia. Methods An education-based intervention study was carried out on 2,709 schoolchildren aged 10–12 years (educated/control group: 2617/92). The questionnaire about sociodemographic, anthropometric, dietary, physical activity, screen time, sleep habits, and nutrition knowledge was assessed at the baseline and after a 6- to 9-month follow-up for the medium-term effect of education. Nutrition knowledge was provided after 3 weeks for the short-term education effect assessment. Results Educated schoolchildren achieved a significant increase in nutrition knowledge (+75.5%), expressed as a short-term effect of the education and maintained at the 6- to 9-month follow-up (+66.8%, p < 0.001). Follow-up of children significantly improved their nutritional status (underweight −56.6%, normal weight 24.8%, overweight −22.1%, and obesity −57.5%) and physical activity engagement (+13.2%). The proportion of children with a diet highly adhering to the Mediterranean diet significantly doubled (+105.0). Those children with the highest nutrition knowledge at the follow-up significantly improved their nutritional status (+218.9%), participated in organized sports (+204.7%), and had a diet that highly adhered to the MD (+291.8%). Conclusion A significantly good medium-term effect of education-based nutrition and lifestyle intervention program on nutrition knowledge, diet quality, lifestyle, and nutritional status of schoolchildren aged 10–12 years was shown. The educational program promoted a Mediterranean diet and lifestyle as a healthy and sustainable way of living, important for children's future health and wellbeing. New research-based approaches are needed for making children more aware and capable of handling the complexity of sustainable living.