Miracle-dz/UniFAR-FTUs huggingface dataset:
Orbital Complications and Cost Analysis of Enucleation by Myoconjunctival versus Conventional Techniques for Retinoblastoma

Introduction: The aim of the study was to compare complication rates and hospital costs of myoconjunctival versus conventional enucleation techniques in retinoblastoma. Methods: This retrospective cohort and cost analysis reviewed patients with retinoblastoma treated by primary or secondary enucleation between 2003 and 2021 and a minimum 6-month follow-up. Cases were reviewed for three postsurgical complications: chronic conjunctivitis, implant exposure/extrusion, and cellulitis. Cases were excluded if surgery was performed elsewhere or documentation was incomplete. Treatment costs were estimated based on two sample cases billed in 2021 that manifested the studied complications and represented each of the two surgical techniques. Univariate and multivariate analyses were applied to compare complication rates and treatment costs. Results: Included were 180 eyes (179 patients); 239 eyes (227 patients) were excluded. Patients had median age of 18.9 (0–104.4) months at diagnosis, the majority were male (94, 52%), with unilateral (115, 64%) group D or E (163, 91%) eyes. Enucleation was performed by conventional techniques in 107 eyes (59%) and by myoconjunctival approach in 73 (41%). Orbital complications occurred in 61 eyes (34%) during a median follow-up of 7.9 (0.5–33.7) years, more frequently in the conventional technique group (p = 0.014). The myoconjunctival technique had significantly lower costs for implant price (p < 0.001) and estimated treatment cost, including complication management (p < 0.001). Conclusion: Enucleation by myoconjunctival technique showed significantly less complication burden and treatment cost, indicating advantages over conventional approaches. Study limitations include the retrospective nature, confounders’ complexity, and follow-up time variations.
Constellations of practice in copper ingots from Zambia and northern Zimbabwe, cal. AD 500–1700

ABSTRACT Rectangular, fishtail and croisette copper ingots have been found in many locations in Central and southern Africa where excavated samples date to between the fifth and eighteenth centuries cal. AD. For more than fifty years, scholars have debated whether these ingots were all made in the Central African Copperbelt, where there are many finds of matching moulds, or if moulds found in Zimbabwe show that copies were produced locally. Lead isotopic and chemical analyses have recently confirmed that the Copperbelt supplied copper ingots to both southern Congo-Kinshasa and the Zimbabwe Plateau between the ninth and eighteenth centuries, but that one HXR ingot can tentatively be sourced to the Magondi Belt copper deposits in northern Zimbabwe. We expand this discussion here by linking ingot chemistry and isotopic provenance with distribution patterns and ingot morphologies. The combined evidence suggests that groups making Luangwa Tradition pottery were responsible for transporting HIH and HXR ingots, and the technological styles for making them, far to the south of the Copperbelt. These croisette ingots link constellations of practice in the Copperbelt and Zimbabwe, possibly through the movement of specialised traders and metalworkers. We identify some of the individuals buried at Ingombe Ilede and Chumnungwa as possible examples of these specialists.
Histomorphological and Histomorphometrical Postnatal Development of the Retina in White Rabbits (Oryctolagus Cuniculus)

The present study aims to elucidate retinal development by analyzing the histomorphological and histomorphometrical parameters in white rabbits (Oryctolagus cuniculus retina). Samples were collected from 25 rabbits divided into five different age groups: 1, 10, 15, 30, and 40 postnatal days (PND). The samples were then sectioned, processed, and stained with Hematoxylin and Eosin stain, as well as Masson's trichrome stain. Some sections were additionally stained with toluidine blue (TB) stain to detect cell density in the outer and inner nuclear layers. Measurements of retinal layers were performed for morphometric comparison among the age groups. The findings revealed that the total thickness of the retina gradually decreased with age. The thickness of the inner and outer nuclear layers, as well as cellular density, also decreased with the development of the photoreceptor layer (rods and cones). This decrement was accompanied by an elevation of the outer plexiform layer thickness and swelling of the ganglion cell layer, particularly after the opening of the eyelids and the differentiation of the different layers of the retina. The histomorphometry results in the retina showed significant differences in the thickness of its different layers among the five age groups. In conclusion, Retina showed highly active histological development and growth with cellular differentiation and significant measurements differences before and after eyelid opening between 10 -15 PNDs.
Responses of Soil Enzyme Activity to Long-Term Nitrogen Enrichment and Water Addition in a Typical Steppe

Enzyme activity plays an important role in soil biochemical processes and is a key factor driving nutrient cycling. Although a great number of studies examined the effects of nitrogen (N) enrichment and water (W) addition on soil enzyme activity, most of them focused on the effect of only one resource and are based on short-term investigations. The separate and interactive effects of long-term changes in nitrogen and water on soil enzyme activity remain largely unexplored. In this study, we demonstrated the responses of two types of soil enzyme, β-1,4-glucosidase (BG) and acid phosphatase (APA), to increased nitrogen and water based on a 16-year experiment conducted in a typical grassland in northern China. The results show that: (1) nitrogen addition inhibited BG and APA in 2019 and 2020; (2) water addition had no significant effect on BG activity, but significantly reduced APA activity in 2020; and (3) redundancy analysis (RDA) showed that nitrogen and water addition affected soil enzyme activity mainly by affecting soil microbial biomass carbon (MBC). The present research offers a comprehensive explanation of how atmospheric nitrogen deposition and precipitation patterns affect the characteristics of microorganisms and the cycling of nutrients in grassland ecosystems.
Commentary: Pilot study of the adaptation of an alcohol, tobacco, and illicit drug use intervention for vulnerable urban young adults

COPYRIGHT © 2023 Sussman, Galimov and Meza. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Commentary: Pilot study of the adaptation of an alcohol, tobacco, and illicit drug use intervention for vulnerable urban young adults
Study of Archaeal Diversity in the Arctic Meltwater Lake Region

Simple Summary The Arctic is experiencing a significant temperature increase under the global warming trend. As a result, the Arctic permafrost is thawing, glacial meltwater is gathering, and the depressions are gradually forming lakes, affecting the composition and material cycles of the terrestrial ecosystems. Two meltwater lakes with different landscapes in the Ny-Ålesund region of the Arctic were taken as study objects. The structure of the archaeal community and the influence of soil physiochemical factors on the archaeal community were investigated. The differences in the archaeal community structure between the intertidal and subtidal zones of the two lakes were compared, and the reasons for the differences were analyzed and discussed. A redundancy analysis identified NH4+, SiO32−, MC, NO3−, and NO2− as key soil physicochemical factors that have significantly influenced the structure of the archaeal community. The hub archaea in the archaeal community were identified by weighted gene co-expression network analysis (WGCNA). The use of WGCNA in this study provides new ideas for future research on the microbial community structure. In the context of global warming, this study contributes to research on archaeal communities in Arctic meltwater lakes in response to climate change. Abstract Two typical lakes formed from meltwater in the Ny-Ålesund area were taken as the study subjects in 2018. To investigate the archaeal community compositions of the two lakes, 16S rRNA genes from soil samples from the intertidal and subtidal zones of the two lakes were sequenced with high throughput. At the phylum level, the intertidal zone was dominated by Crenarchaeota and the subtidal zone was dominated by Halobacter; at the genus level, the intertidal zone was dominated by Nitrososphaeraceae_unclassified and Candidatus_Nitrocosmicus, while the subtidal zone was dominated by Methanoregula. The soil physicochemical factors pH, moisture content (MC), total organic carbon (TOC), total organic nitrogen (TON), nitrite nitrogen (NO2−-N), and nitrate nitrogen (NO3−-N) were significantly different in the intertidal and subtidal zones of the lake. By redundancy analysis, the results indicated that NH4+-N, SiO32−-Si, MC, NO3−-N, and NO2−-N have had highly significant effects on the archaeal diversity and distribution. A weighted gene co-expression network analysis (WGCNA) was used to search for hub archaea associated with physicochemical factors. The results suggested that these physicochemical factors play important roles in the diversity and structure of the archaeal community at different sites by altering the abundance of certain hub archaea. In addition, Woesearchaeales was found to be the hub archaea genus at every site.
Domain decomposition methods for nonlinear problems in structural mechanics

We propose substructured formulations of nonlinear structure problems which can be interpreted as the nonlinear versions of classical FETI, BDD and FETI2LM solvers. Applying a Newton method leads to independent nonlinear systems per subdomains and linear interface system (as encountered in classical FETI or BDD). Thus part of the treatment of the nonlinearity is brought to the scale of the subdomains which can improve the scalability of the method. Contrary to the linear case, the nonlinear versions of FETI, BDD and FETI2LM are strongly different.
Determination of Minimum Sample Size Requirement for Multiple Linear Regression and Analysis of Covariance Based on Experimental and Non-experimental Studies

Background: MLR and ANCOVA are common statistical techniques and are used for both experimental and non-experimental studies. However, both types of study designs may require different basis of sample size requirement. Therefore, this study aims to proposed sample size guidelines for MLR and ANCOVA for both experimental and non-experimental studies. Methods: We estimated the minimum sample sizes required for MLR and ANCOVA by using Power and Sample Size software (PASS) based on the pre-specified values of alpha, power and effect size (R2). In addition, we also performed validation of the estimates using a real clinical data to evaluate how close the approximations of selected statistics which were derived from the samples were to the actual parameters in the targeted populations. All the coefficients, effect sizes and r-squared obtained from the sample were then compared with their respective parameters in the population. Results: Small minimum sample sizes required for performing both MLR and ANCOVA when r-squared is used as the effect size. However, the validation results based on an evaluation from a real-life dataset suggest that a minimum sample size of 300 or more is necessary to generate a close approximation of estimates with the parameters in the population. Conclusions: We proposed sample size calculation when r-squared is used as an effect size is more suitable for experimental studies. However, taking a larger sample size such as 300 or more is necessary for clinical survey that is conducted in a non-experimental manner.
Spectral Properties of Photonic Crystals: Bloch Waves and Band Gaps

The author of this dissertation studies the spectral properties of high-contrast photonic crystals, i.e. periodic electromagnetic waveguides made of two materials (a connected phase and included phase) whose electromagnetic material properties are in large contrast. A spectral analysis of 2nd-order divergence-form partial differential operators (with a coupling constant k) is provided. A result of this analysis is a uniformly convergent power series representation of Bloch-wave eigenvalues in terms of the coupling constant k in the high-contrast limit k → ∞. An explicit radius of convergence for this power series is obtained, and can be written explicitly in terms of the Bloch-wave vector α, the Dirichlet eigenvalues of the inclusion geometry, and a lower bound on another spectrum known as the ”generalized electrostatic resonances”. This lower bound is derived from geometric properties of the inclusion geometry for the photonic crystal.
Comprehensive genomic analysis of primary bone sarcomas reveals different genetic patterns compared with soft tissue sarcomas

Introduction Sarcomas are classified into two types, bone sarcoma and soft tissue sarcoma (STS), which account for approximately 1% of adult solid malignancies and 20% of pediatric solid malignancies. There exist more than 50 subtypes within the two types of sarcoma. Each subtype is highly diverse and characterized by significant variations in morphology and phenotypes. Understanding tumor molecular genetics is helpful in improving the diagnostic accuracy of tumors that have been difficult to classify based on morphology alone or that have overlapping morphological features. The different molecular characteristics of bone sarcoma and STS in China remain poorly understood. Therefore, this study aimed to analyze genomic landscapes and actionable genomic alterations (GAs) as well as tumor mutational burden (TMB), microsatellite instability (MSI), and programmed death ligand-1 (PD-L1) expression among Chinese individuals diagnosed with primary bone sarcomas and STS. Methods This retrospective study included 145 patients with primary bone sarcomas (n = 75) and STS (n = 70), who were categorized based on the 2020 World Health Organization classification system. Results Patients diagnosed with bone sarcomas were significantly younger than those diagnosed with STS (p < 0.01). The top 10 frequently altered genes in bone sarcoma and STS were TP53, CDKN2A, CDKN2B, MAP3K1, LRP1B, MDM2, RB1, PTEN, MYC, and CDK4.The EWSR1 fusions exhibited statistically significant differences (p < 0.01) between primary bone sarcoma and STS in terms of their altered genes. Based on the actionable genes defined by OncoKB, actionable GAs was found in 30.7% (23/75) of the patients with bone sarcomas and 35.7% (25/70) of those with STS. There were 4.0% (3/75) patients with bone sarcoma and 4.3% (3/70) patients with STS exhibited high tumor mutational burden (TMB-H) (TMB ≥ 10). There was only one patient with STS exhibited MSI-L, while the remaining cases were microsatellite stable. The positive rate of PD-L1 expression was slightly higher in STS (35.2%) than in bone sarcoma (33.3%), however, this difference did not reach statistical significance. The expression of PD-L1 in STS patients was associated with a poorer prognosis (p = 0.007). Patients with STS had a better prognosis than those with bone sarcoma, but the observed difference did not attain statistical significance (p = 0.21). Amplification of MET and MYC genes were negatively correlated with clinical prognosis in bone tumors (p<0.01). Discussion In conclusion, bone sarcoma and STS have significantly different clinical and molecular characteristics, suggesting that it is vital to diagnose accurately for clinical treatment. Additionally, comprehensive genetic landscape can provide novel treatment perspectives for primary bone sarcoma and STS. Taking TMB, MSI, PD-L1 expression, and OncoKB definition together into consideration, there are still many patients who have the potential to respond to targeted therapy or immunotherapy.
Role of dimensionality in preferential attachment growth model with random fitness

Scale-free networks are quite popular nowadays since many systems are well represented by such structures. In order to study these systems, several models were proposed. However, most of them do not take into account the node-to-node Euclidean distance, i.e., the geographical distance. In real networks, the distance between sites can be very relevant, e.g., those cases where it is intended to minimize costs. Within this scenario we studied the role of dimensionality $d$ in the Fitness Model with a preferential attachment growth involving Euclidean distances. The preferential attachment in this model follows the rule $\Pi_{i} \propto \eta_i k_i/r_{ij}^{\alpha_A}$ $(1 \leq i < j; \alpha_A \geq 0)$, where $\eta_i$ characterizes the fitness of the $i$-th site and is randomly chosen within the $(0,1]$ interval. We verified that the degree distribution $P(k)$ for dimensions $d=1,2,3,4$ are well fitted by $P(k) \propto e_q^{-k/\kappa}$, where $e_q^{-k/\kappa}$ is the $q$-exponential function naturally emerging within nonextensive statistical mechanics. We determine the index $q$ and $\kappa$ as functions of the quantities $\alpha_A$ and $d$, and numerically verify that both present a universal behavior with respect to the scaled variable $\alpha_A/d$. The same behavior also has been displayed by the dynamical $\beta$ exponent which characterizes the steadily growing number of links of a given site.
Detection of Block-Exchangeable Structure in High-Dimensional Correlation Matrices

Correlation matrices are omnipresent in multivariate data analysis. When the number of variables is large, however, their sample estimates are typically noisy and may muddle up underlying dependence patterns. In this article, we assume that the $d$ variables under study can be grouped into $K$ clusters with exchangeable dependence. Under this partial exchangeability condition, the corresponding correlation matrix has a block structure and the number of unknown parameters is reduced from $d(d-1)/2$ to at most $K(K+1)/2$. We propose an efficient algorithm to identify the clusters without assuming the knowledge of $K$ a priori. As a by-product, we obtain an improved estimator of the correlation matrix and its inverse, along with its asymptotic variance. Our procedure is based on Kendall's rank correlation, which makes it robust, margin-free, and valid whenever the marginal distributions are continuous; no assumption of multivariate Normality is required. When the data are Normal or more generally elliptical, our results are easily extended to classical linear correlation matrices and their inverses, as we show. The procedure is illustrated on financial stock returns; the clusters identified nicely correspond to different business sectors. Technical proofs and the R-code of the algorithm are provided in the Online Supplement.
ON THE ORDER OF GRID CONVERGENCE OF THE HYBRID CONVECTION SCHEME FOR RANS CODES

This paper presents a study of the order of grid convergence of the Hybrid convection discretization scheme that blends first-order upwind with the second-order central-difference scheme. Although this approach was proposed forty years ago, it is still available in many CFD commercial solvers. One could naively assume that the order of grid convergence of this scheme would change linearly with the blending parameter. Therefore, the aim of this study is to demonstrate that the relation between the order of grid convergence and the blending parameter is not linear. Three manufactured solutions that mimic statistically steady, two-dimensional, incompressible, turbulent, near-wall viscous flows were selected to enable the evaluation of discretization errors. To avoid any possible disturbances of the solution of turbulence quantities transport equations on the asymptotic order of grid convergence of mean flow quantities, we use a manufactured eddy-viscosity field in the RANS equations. Grid refinement studies were performed with the RANS solver ReFRESCO in geometrically similar stretched Cartesian grids, which ensure that the discretization schemes of all remaining terms of the RANS equations are second-order accurate. For flows dominated by convection, the Hybrid scheme remains first-order accurate up to values of the blending parameter very close to 1. On the other hand, the decrease of the error level with the blending parameter is close to linear.
Simulations of a Flexible Cylinder in a Confined Region using a Chimera technique

Fluid-structure interaction (FSI) simulations involving the motion of flexible structures within confined regions are often hindered by mesh degradation when an arbitrary Lagrangian-Eulerian (ALE) approach is used. In this paper the feasibility of using an overset or Chimera methodology for this kind of simulations is investigated. The overset mesh, surrounding the flexible structure, is superimposed on a fixed background mesh, which covers the entire flow domain. The overset mesh is not confined to the physical fluid domain allowing for larger structural deformations without severe grid degradation. To assess the limitations and errors associated to the use of an overset grid, simulations in which the structural motion is imposed are performed and, when possible, compared to an arbitrary Lagrangian-Eulerian formulation. The increase in computational cost and memory requirements are also considered. Subsequently, fluid-structure interaction simulations are performed with varying degrees of freedom for the structure. The flow is calculated based on the compressible Reynolds-averaged Navier-Stokes equations as both high and low Mach number flows are considered. For high Mach number flows, the nozzle geometry used in the fluid-structure interaction simulations is subjected to shocks. The presence of these shocks should be taken into account when constructing the overset grid.