Miracle-dz/UniFAR-FTUs huggingface dataset:
On the robustness of a simple domain reduction scheme for simulation‐based optimization

This paper evaluates a Successive Response Surface Method (SRSM) specifically developed for simulation‐based design optimization, e.g. that of explicit nonlinear dynamics in crashworthiness design. Linear response surfaces are constructed in a subregion of the design space using a design of experiments approach with a D‐optimal experimental design. To converge to an optimum, a domain reduction scheme is utilized. The scheme requires only one user‐defined parameter, namely the size of the initial subregion. During optimization, the size of this region is adapted using a move reversal criterion to counter oscillation and a move distance criterion to gauge accuracy. To test its robustness, the results using the method are compared to SQP results of a selection of the well‐known Hock and Schittkowski problems. Although convergence to a small tolerance is slow when compared to SQP, the SRSM method does remarkably well for these sometimes pathological analytical problems. The second test concerns three engineering problems sampled from the nonlinear structural dynamics field to investigate the method's handling of numerical noise and non‐linearity. It is shown that, despite its simplicity, the SRSM method converges stably and is relatively insensitive to its only user‐required input parameter.
Dealing with Nonnormal Data: Parametric Analysis of Transformed Data vs Nonparametric Analysis

Researchers have typically employed parametric analysis of raw data to test experimental data for statistical significance. When the data are not normally distributed, data transformation or nonparametric analysis are often recommended. The present study compares parametric analysis of raw data to parametric analysis of transformed data and to nonparametric analysis when the tests are carried out under population nonnormality. The results of a Monte Carlo simulation indicate that when distributions depart markedly from normality, nonparametric analysis and parametric analysis of transformed data show superior power to parametric analysis of raw data. Furthermore, under the conditions studied, parametric analysis of transformed data appears to be somewhat more powerful than nonparametric analysis.
Minimum k-geodetically connected digraphs

A strong digraph is k-geodetically connected lk-GCr if the removal of at least k vertices is required to increase the distance between at least one pair of vertices or reduce it to a single vertex. Such digraphs can serve as models of distance invulnerable networks limmune to k – 1 or fewer vertex failuresr for a system with one-way communications. For every integer n, we determine the minimum size 2-GC digraphs of order n. Further, we find the minimum size of a k-GC digraph of order n if n ≡ 0 lmod kr and give good bounds for all n. Also, several operations on and constructions of k-GC digraphs are presented. We show that the problem of finding a minimum size k-GC spanning subdigraph of a given digraph is NP-hard. © 2004 Wiley Periodicals, Inc. NETWORKS, Vol. 44l4r, 243–253 2004
Computer-Aided Diagnosis of COVID-19 with Joint Instance Segmentation and Classification

To address the difficulty of small lesion area detection of COVID-19 patients in their lung CT images, the author has proposed an end-to-end network which using semantic segmentation to guide instance segmentation, and extending transfer learning to the classification of COVID-19 pneumonia, Common pneumonia and Normal. Firstly, in order to extract richer multi-scale features and increase the weight of low-level features, we have introduced the Atrous Spatial Pyramid Pooling(ASPP) into the Feature Pyramid Network(FPN), and proposed Multi-scale Reverse Attention Feature Pyramid Network, then having added a semantic segmentation branch to guide instance segmentation after the output of ASPP, finally, we have extracted the object category score by detector for auxiliary classification. Segmentation experiments were carried out on the dataset of CC-CCII and COVID-19 infection segmentation dataset, the mean average precision(mAP) is 39.57%, 35.36%, Compared with the COVID-CT-Mask-Net, it has improved by 5.52%, 2.33%, we also carried out classification experiments on the dataset that is from COVIDX-CT, the sensitivity and specificity of the model for detecting COVID-19 in test data are 95.88% and 98.95% respectively. Also, the sensitivity and specificity of the model for detecting Common pneumonia in test data are 98.62% and 99.25% respectively, the sensitivity and specificity of the model for detecting Normal in test data are 99.61% and 99.11% respectively, which are the best results based on this dataset and indicators, this shows that the proposed method can quickly and effectively help the clinician identify and diagnose COVID-19 patient through their lung CT images.
Genome-Wide Analysis of Long Noncoding RNAs in Porcine Intestine during Weaning Stress

Long noncoding RNAs (lncRNAs) play crucial roles in various biological processes, and they are considered to be closely associated with the pathogenesis of intestinal diseases. However, the role and expression of lncRNAs in intestinal damage during weaning stress remain unknown. Herein, we investigated the expression profiles of jejunal tissue from weaning piglets at 4 and 7 d after weaning (groups W4 and W7, respectively) and from suckling piglets on the same days (groups S4 and S7, respectively). Genome-wide analysis of lncRNAs was also performed using RNA sequencing technology. A total of 1809 annotated lncRNAs and 1612 novel lncRNAs were obtained from the jejunum of piglets. In W4 vs. S4, a total of 331 lncRNAs showed significant differential expression, and a total of 163 significantly differentially expressed lncRNAs (DElncRNAs) was identified in W7 vs. S7. Biological analysis indicated that DElncRNAs were involved in intestinal diseases, inflammation, and immune functions, and were mainly enriched in the Jak-STAT signaling pathway, inflammatory bowel disease, T cell receptor signaling pathway, B cell receptor signaling pathway and intestinal immune network for IgA production. Moreover, we found that lnc_000884 and target gene KLF5 were significantly upregulated in the intestine of weaning piglets. The overexpression of lnc_000884 also significantly promoted the proliferation and depressed apoptosis of IPEC-J2 cells. This result suggested that lnc_000884 may contribute to repairing intestinal damage. Our study identified the characterization and expression profile of lncRNAs in the small intestine of weaning piglets and provided new insights into the molecular regulation of intestinal damage during weaning stress.
Pro197 and Trp574 substitutions in the acetolactate synthase of corn marigold (Glebionis segetum) and their impact on competitive ability against barley

Abstract Three suspected resistant (R1, R2, and R3) corn marigold populations collected from winter cereal fields located in central Greece were studied to confirm and elucidate the mechanisms of resistance to acetolactate synthase (ALS) inhibitors and their competitive ability against barley. Whole-plant dose–response assays proved that the three suspected R populations were highly cross-resistant to the ALS inhibitors tribenuron, pyroxsulam + florasulam, and imazamox, whereas their control with synthetic auxin plus ALS inhibitors co-formulated mixtures was increased in the order of tritosulfuron + dicamba < florasulam + clopyralid < tribenuron + mecoprop-P < florasulam + aminopyralid. The ALS gene sequence revealed a point mutation in 11 plants of the R1, R2, and R3 populations, which resulted in the substitution of Pro-197-Thr or Trp-574-Leu. By contrast, all three sequenced plants of the susceptible (S) population were found with the wild-type allele encoding Pro-197 and Trp-574. This is the first report of ALS-inhibitor resistance in corn marigold. The competition study between barley and four densities of the S, R2, or R3 populations indicated similar biomass rates for all three populations, suggesting lack of association between the competitive ability of the R populations and the target-site resistance mechanism, which was also confirmed by the similar biomass reduction rates of barley grown in competition with S or R populations. Nomenclature: Aminopyralid; clopyralid; dicamba; florasulam imazamox; mecoprop-PP; pyroxsulam; tribenuron; tritosulfuron; barley; Hordeum vulgare L. ; corn marigold; Glebionis segetum L. Fourr.
Two‐dimensional simulations for the impulsive penetration of a solar wind filament into the magnetosphere

In order to understand the penetration process of a solar wind filament into the magnetosphere in detail, a simplified two-dimensional PPMMHD code for ideal MHD is applied to the penetration. The filament is modeled as a field-aligned cylinder impinging on the dayside magnetosphere. The initial magnetopause is considered as a purely tangential discontinuity without width. The results in this paper show that a plasma filament in the magnetosheath with excess momentum density will penetrate through the magnetopause and become irregularity inside in the magnetosphere. This paper presents detailed pictures for the distribution and the evolution of the plasma mass density, thermal pressure, flow velocity, and magnetic field around the filament. The results in this paper confirm the authors expectation that the penetration in the case with antiparallel magnetic fields happens in the same way as in the case with parallel magnetic fields in the initial situations both without and with a diamagnetic current flowing on the surface of a filament under the approximation of two-dimensional ideal MHD. 13 refs., 6 figs.
Alexander-Govern test using Winsorized means

Classical tests for testing the equality of independent groups which are based on arithmetic mean can produce invalid results especially when dealing with non-normal data and heterogeneous variances (heteroscedasticity). In alleviating the problem, researchers are working on methods that are more adapt to the aforementioned conditions which include a procedure known as Alexander-Govern test. This procedure is insensitive in the presence of heteroscedasticity under normal distribution. However, the test which employs the arithmetic mean as the central tendency measure is sensitive to non-normal data. This is due to the fact that the arithmetic mean is easily influenced by the shape of distribution. In this study, the arithmetic mean is replaced by robust estimators, namely the Winsorized mean or adaptive Winsorized mean. The proposed Alexander-Govern test with Winsorized mean and with adaptive Winsorized mean are denoted as AGW and AGAW, respectively. For the purpose of comparison, different Winsorization percentages of 5%, 10%, 15% and 20% are considered. A simulation study was conducted to investigate on the performance of the tests which is based on rate of Type I error and power. Four variables; shape of distribution, sample size, level of variance heterogeneity and nature of pairings are manipulated to create the conditions which could highlight the strengths and weaknesses of each test. The performance of the proposed tests is compared with their parametric counterparts, the t-test and ANOVA. The proposed tests show improvement in terms of controlling Type I Error and increasing power under the influence of heteroscedasticity and non-normality. The AGAW test performed best with 10% Winsorization while AGW test performed best with 5% Winsorization. Under most conditions (74%), AGAW tests outperform AGW tests. Therefore, the Winsorized mean and the adaptive Winsorized mean can significantly improve the performance of the original Alexander-Govern test. These proposed procedures are beneficial to statistical practitioners in testing the equality of independent groups even under the influence of non-normality and variance heterogeneity.
The Soft Prefabricated Orthopedic Insole Decreases Plantar Pressure during Uphill Walking with Heavy Load Carriage

This study aimed to investigate the effect of varying the hardness of prefabricated orthopedic insoles on plantar pressure and muscle fatigue during uphill walking with a heavy backpack. Fifteen healthy male recreational athletes (age: 20.4 ± 1.0 years, height: 176.9 ± 5.7 cm, weight: 76.5 ± 9.0 kg) wore prefabricated orthopedic insoles with foot arch support; a heel cup with medium (MI), hard (HI), and soft (SI) relative hardnesses; and flat insoles (FI). They performed treadmill walking on uphill gradients with 25 kg backpacks. The plantar pressure and surface electromyographic activity were recorded separately, in 30 s and 6 min uphill treadmill walking trials, respectively. The HI, MI, and SI significantly decreased peak plantar pressure in the lateral heel compared to FI. The MI and SI significantly decreased the peak plantar pressure in the fifth metatarsal compared to FI. The MI significantly reduced the pressure–time integral in the lateral heel compared to FI. The HI significantly increased the peak plantar pressure and pressure–time integral in the toes compared to other insoles, and decreased the contact area in the metatarsal compared to SI. In conclusion, a prefabricated orthopedic insole made of soft material at the fore- and rearfoot, with midfoot arch support and a heel cup, may augment the advantages of plantar pressure distribution during uphill weighted walking.
Extraction of Important Factors in a High-Dimensional Data Space: An Application for High-Growth Firms

We introduce a new non-black-box method of extracting multiple areas in a high-dimensional big data space where data points that satisfy specific conditions are highly concentrated. First, we extract one-dimensional areas where the data that satisfy specific conditions are mostly gathered by using the Bayesian method. Second, we construct higher-dimensional areas where the densities of focused data points are higher than the simple combination of the results for one dimension, and then we verify the results through data validation. Third, we apply this method to estimate the set of significant factors shared in successful firms with growth rates in sales at the top 1% level using 156-dimensional data of corporate financial reports for 12 years containing about 320,000 firms. We also categorize high-growth firms into 15 groups of different sets of factors.
Characterizing Some of the Influences of the General Circulation on Subtropical Marine Boundary Layer Clouds

Abstract The seasonal and intraseasonal variability of boundary layer cloud in the subtropical eastern oceans is studied using combined data from the International Satellite Cloud Climatology Project and the European Centre for Medium-Range Weather Forecasts reanalysis. Spectral analysis reveals that most of the time variability of cloud properties occurs on seasonal to annual timescales. The variance decreases by one to two orders of magnitude for each decade of timescale decrease, indicating that daily to monthly timescales and their spatial extent have smaller, although nonnegligible, variability. The length of these dominant timescales suggests that the majority of the variability is influenced by the general circulation and its interaction with boundary layer turbulence, rather than being a product of local boundary layer turbulence alone. Although the dominance of seasonal to annual periods in the temporal power spectra of low-cloud fraction—TAU and CTP—justifies the previous focus of effort on seas.
UNESCO Global Geoparks 22 Years after Their Creation: Analysis of Scientific Production

Geoparks are unique geographical areas whose geological significance is worthy of UNESCO designation as a Global Geopark. As of 2022, 177 geoparks located in 46 countries have this designation. The aim of this paper is to identify and analyse the worldwide scientific production published in the Web of Sciences database in the context of Geoparks. The methodology used was bibliometric analysis, which allows for the rigorous exploration and analysis of large volumes of data. To this end, descriptive and relational indicators were obtained for the field of study; performance analysis, scientific mapping, and network analysis. A total of 324 articles were identified, the first of which was from 1999 by Wolfgang Eder, in which he presented the UNESCO initiative on the creation of geoparks as a tool to promote a better understanding of the geological heritage and the rational use of the Earth’s crust; the rest of the articles were written after the programme was launched (2001). Few authors work on the subject continuously, the author with the highest number of publications has six, and most of the authors with a single authorship are transient. The countries with the highest number of publications are China, followed by Spain, Portugal, Brazil and Italy, where scientific production is concentrated; the high rate of transience indicates that many countries have only one publication. Most publications are concentrated in two journals: geoheritage and geosciences. In the early years (1999–2003), publications were associated with two research areas, geology and palaeontology, and it is in the last five years (2019–2002) that the areas of knowledge showing interest in the subject have diversified.
Percolation of fully penetrable disks using the three-leg cluster method

The three-leg cluster method is a relatively new approach to computing the percolation thresholds. To date, it has only been applied to lattice models. It is characterized by high versatility in choosing the shape of the system and by the universal probability 1/2 that, at the phase transition, a three-leg cluster exists that spans three segments of the system border. We applied it to the problem of continuous percolation of discs, for which we estimated the critical filling factor to be 1.128 086 7(5) . This confirms that the three-leg cluster method is applicable to continuous percolation models.
Intrinsic, Observed, and Retrieved Properties of Interstellar Turbulence

We generate synthetic observations of three-dimensional, self-gravitating MHD simulations of the interstellar medium (ISM) to evaluate the ability of principal component analysis (PCA) to measure the scale dependence of turbulent velocity fluctuations in molecular clouds. Scaling exponents, α, observationally obtained from the coupled characteristic scales for line profile variability in velocity, δv, and in space, L, where δv ∝ Lα, are compared with the intrinsic scaling exponents of the MHD velocity fields. We determine the approximate structure function order at which PCA operates in order to then verify a previously established calibration of the PCA method. We also analyze the statistical properties of projected velocity line centroid fields, including effects of intermittent velocity fluctuations, density inhomogeneity, and opacity, and examine the relationship of the projected two-dimensional statistics to the intrinsic three-dimensional statistics. Using PCA, we infer steep three-dimensional energy spectra in the molecular ISM, generally steeper than can be accounted for by Kolmogorov turbulence or possibly even shock-dominated turbulence.
The Characterization and Beta-Lactam Resistance of Staphylococcal Community Recovered from Raw Bovine Milk

Staphylococci is an opportunistic bacterial population that is permanent in the normal flora of milk and poses a serious threat to animal and human health with some virulence factors and antibiotic-resistance genes. This study was aimed at identifying staphylococcal species isolated from raw milk and to determine hemolysis, biofilm, coagulase activities, and beta-lactam resistance. The raw milk samples were collected from the Düzce (Türkiye) region, and the study data represent a first for this region. The characterization of the bacteria was performed with MALDI-TOF MS and 16S rRNA sequence analysis. The presence of coa, icaB, blaZ, and mecA was investigated with PCR. A nitrocefin chromogenic assay was used for beta-lactamase screening. In this context, 84 staphylococci were isolated from 10 different species, and the dominant species was determined as S. aureus (32.14%). Although 32.14% of all staphylococci were positive for beta hemolysis, the icaB gene was found in 57.14%, coa in 46.42%, mecA in 15.47%, and blaZ in 8.33%. As a result, Staphylococcus spp. strains that were isolated from raw milk in this study contained some virulence factors at a high level, but also contained a relatively low level of beta-lactam resistance genes. However, considering the animal–environment–human interaction, it is considered that the current situation must be monitored constantly in terms of resistance concerns. It must not be forgotten that the development of resistance is in constant change among bacteria.
Neurodegeneration, Mitochondria, and Antibiotics

Neurodegenerative diseases are characterized by the progressive loss of neurons, synapses, dendrites, and myelin in the central and/or peripheral nervous system. Actual therapeutic options for patients are scarce and merely palliative. Although they affect millions of patients worldwide, the molecular mechanisms underlying these conditions remain unclear. Mitochondrial dysfunction is generally found in neurodegenerative diseases and is believed to be involved in the pathomechanisms of these disorders. Therefore, therapies aiming to improve mitochondrial function are promising approaches for neurodegeneration. Although mitochondrial-targeted treatments are limited, new research findings have unraveled the therapeutic potential of several groups of antibiotics. These drugs possess pleiotropic effects beyond their anti-microbial activity, such as anti-inflammatory or mitochondrial enhancer function. In this review, we will discuss the controversial use of antibiotics as potential therapies in neurodegenerative diseases.
Impact of Big Data Analytics and Managerial Support on CRM: Exploring Mediating Role of Marketing Analytics

IT sector has faced immense competition, and the importance of CRM cannot be neglected in the IT sector. Therefore, the purpose of this study was to examine the relationship between big data analytics, competitor pressure, managerial support, marketing analytics, and CRM. This study also examined the mediating effect of marketing analytics as well. To identify the effect of these factors on CRM, this study adopted the PLS-SEM model. The data were collected from the respondents using simple random sampling. The response rate of the study was 60.70%. The findings of the study showed that big data analytical capability, managerial support, competitive pressure, and marketing analytics have a significant relationship with CRM capability. The mediating marketing analytics is confirmed as well. The findings of the study support that big data analytics and managerial support have an important role in the satisfaction of customers. These results can be used by the government sector and IT decision-makers to develop their strategies for customers.
Optical absorption of thin film on a Lambertian reflector substrate

A formula is derived for calculating the optical absorption of thin films deposited on a Lambertian reflector substrate. It is shown that compared with the case of flat reflecting substrate, the incoherent absorption is enhanced by a factor of m\epsilon_{1} in the weak absorption limit, where e 1 is the real part of the film dielectric constant and m \simeq 2 is a slightly varying function of e 1 . For a 0.5-µm a-SiH x (bandgap 1.7 eV) solar cell with a Lambertian reflector substrate, the total absorption in terms of the short-circuit current is calculated to be 18.63 mA/cm2.