Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of long-term mortality in patients with stable angina pectoris whose SYNTAX score was found to be zero in coronary angiography

Aim: The number of diagnostic coronary angiography is increasing. Although previously thought that non-obstructive coronary artery disease (CAD) does not cause an increase in mortality risk, there is recently evidence that it increases mortality. In this study, we aimed to determine the mortality rates and possible predictors of all-cause death in long-term follow-up of patients who underwent coronary angiography (CAG) due to stable angina and whose SYNTAX score was zero including normal coronary arteries, minimal CAD or non-obstructive CAD, coronary slow flow, coronary artery aneurysms and ectasia. Materials and Methods: This study included 1489 patients who underwent CAG due to stable angina pectoris. In-hospital and post-discharge follow-up data were obtained. Patients' CAG images were evaluated and SYNTAX scores were calculated using the website calculator. Results: Among the 1489 patients, 64 (4.3%) all-cause deaths were observed during the 19 ± 1.1 months of follow up period. Although, no significant difference was observed between the 2 groups in terms of the presence of plaque in coronary arteries with a vessel diameter of ≤ 1.5 mm, the rate of patients with plaque in coronary arteries with a diameter of > 1.5 mm was significantly higher in the group of patients who died compared to the patients living (48 (75%) vs 842 (% 59.1), p = 0.011). The cumulative survival curve of the patients was obtained and in patients with coronary plaque in any of the coronary arteries with a vessel diameter of > 1.5 mm was significantly associated with worse survival. Conclusion: There was increase in all-cause mortality in patients who underwent CAG due to stable angina and who have at least one non-obstructive lesion in the coronary arteries > 1.5 mm. Therefore, appropriate risk classification, life style changes and appropriate medical follow-up may be important in these patients.
3D CT Soft Tissue Craniofacial Analysis and Lip Morphology

Objective: To assess the soft tissue characteristics of Bangladeshi adults to formulate soft tissue 3D CT standards using Holdaway’s (HA) and lip morphology (LM) analyses. Another aim of this study was to assess the gender dimorphism of Bangladeshi population. Material and Methods: One hundred and seventeen (Eighty-five men and Thirty-two women) Bangladeshi adults have obtained their computed tomography (CT) scan at the Radiology Department for normal diagnosis. Craniofacial deformities were undetected in all cases. The CT images were prepared by a 3D imaging programming software (Mimics 11.02 Materialise). Parameters from the identified landmark points were measured in 3D through this software. Results: Upper lip thickness (ULT) (vermillion UL-A point) measurement was significant in HA and in LM analyses, upper lip protrusion (ULP) (Ls to Sn-SPog) measurement has demonstrated significant difference among both genders, where p-value was less than 0.05. Mean measurements of Bangladeshi adults were relatively comparable except the face convexity (FC) when compared with the HA cephalometric soft tissue values. Conclusion: By using HA and LM analyses, 3D CT soft tissue standards were established for Bangladeshi adults. Measurements for all parameters have remained equivalent with the HA standard data apart from the FC measurement. This consequently may demonstrate that the Bangladeshi population retains a convex shape with a slight protrusive lip or retruded chin.
Sounding and modeling of the indoor aerial acoustic transmission channel

The authors verify that the indoor aerial acoustic transmission channel regarding small‐scale application environments, for example, a car cabin, is a quasi‐wide sense stationary uncorrelated scattering (QWSSUS) channel like radio channels. To the best knowledge of the authors, the QWSSUS feature of the indoor aerial acoustic transmission channel has never been evaluated before. Setting out from the QWSSUS concept, the channel modeling by means of correlation functions is proposed. Also, parameter sets that can be used in channel simulations are suggested.
Opportunities To Improve Diabetes Care in the Hemodialysis Unit: A Cohort Study in Ontario, Canada.

Background Patients with diabetes receiving chronic, in-center hemodialysis face healthcare challenges. We examined the prevalence of gaps in their diabetes care, explored regional differences, and determined predictors of care gaps. Methods We conducted a population-based, retrospective study between January 1, 2016 and January 1, 2018 in Ontario, Canada. We included adults with prevalent diabetes mellitus receiving in-center hemodialysis as of January 1, 2018 and examined the proportion with (1) insufficient or excessive glycemic monitoring, (2) suboptimal screening for diabetes-related complications (retinopathy and cardiovascular screening), (3) hospital encounters for hypo- or hyperglycemia, and (4) hospital encounters for hypertension in the 2 years prior (January 1, 2016 to January 1, 2018). We then identified patient, provider, and health-system factors associated with more than one care gap and used multivariable logistic regression to determine predictors. Further, we used geographic information systems to explore spatial variation in gaps. Results There were 4173 patients with diabetes receiving in-center hemodialysis; the mean age was 67 years, 39% were women, and the majority were of lower socioeconomic status. Approximately 42% of patients had more than one diabetes care gap, the most common being suboptimal retinopathy screening (53%). Significant predictors of more than one gap included younger age, female sex, shorter duration of diabetes, dementia, fewer specialist visits, and not seeing a physician for diabetes. There was evidence of spatial variation in care gaps across our region. Conclusions There are opportunities to improve diabetes care in patients receiving in-center hemodialysis, particularly screening for retinopathy. Focused efforts to bring diabetes support to high-risk individuals might improve their care and outcomes.
Data-Driven Dynamic Models of Active Distribution Networks Using Unsupervised Learning Techniques on Field Measurements

The development of realistic dynamic models for active distribution networks (ADNs) is a challenging problem faced by both the transmission system operators and academia due to the random and complex nature of loads and distributed generation. Real field measurements are often not available and when they are, they usually contain various dynamics, irrelevant data, and outliers. This article proposes a three-stage methodology to effectively build a set of dynamic models for an ADN based on field measurements. In the first stage, an unsupervised learning method identifies and then discards all the irrelevant data for the model parameter estimation. In the next stage, the remaining data are clustered into groups with similar dynamics while in the third stage, a nonlinear dynamic model is developed for each of the derived groups. This papers concludes that, in spite of the large number of measurements representing a wide range of grid configurations, the general dynamic characteristics of an ADN can be accurately captured and modeled using a limited number of clusters. The proposed method is validated using real data from six substations in Southern Germany.
Electron Momentum Density of Nanoparticles ZrO2: A Compton Profile Study

This work investigates the electronic momentum density (EMD) distribution in nanosize zirconia (ZrO2) using the technique of Compton scattering. The ZrO2 nanoparticles (11.2[Formula: see text]nm) are synthesized of mechanical milling and characterized by SEM, XRD and TEM probes. The Compton profile [Formula: see text] of nanoZrO2 is measured by Compton spectrometer 59.54[Formula: see text]KeV Gamma rays (Americium-241) source. The study finds out that EMD in nanoZrO2 is narrower comparing in case bulk ZrO2. This study adopts the ionic-model-based free atom [Formula: see text] calculation for many configurations (Zr)[Formula: see text](O[Formula: see text])2 ([Formula: see text]) to measure the charge transfer (CT) on the compound formation. According to this study’s findings, CT values in these materials are ranged from 1.5 to 1.0 electrons from Zr to O atom.
Do small farms prefer agricultural mechanization services? Evidence from wheat production in China

ABSTRACT Developing agricultural mechanization services has been an important approach to pushing smallholder farmers engaging modern agricultural production in China. However, whether smallholder farmers prefer adopting agricultural mechanization services is still under-analysed. In this paper, we use data covering 3,440 wheat farmers collected from Henan province in China to investigate the links between farm size and the adoption of agricultural mechanization services. The results indicate that an inverted U-shaped relationship between farm size and the adoption of agricultural mechanization services exists. We also find that small farms can input more family labour, and large farms tend to invest in self-owned machinery assets. Our analysis implies that the development of agricultural mechanization services is not inevitable to attract farmers with alternative elements, and smallholder farmers may not be the major groups involved in the market of social services in agriculture in the future.
Targeted Gene Sequencing, Bone Health, and Body Composition in Cornelia de Lange Syndrome

The aim of this study was to evaluate bone health and body composition by dual-energy X-ray absorptiometry (DXA) in individuals with Cornelia de Lange Syndrome (CdLS). Overall, nine individuals with CdLS (five females, all Caucasian, aged 5–38 years) were assessed. Total body less head (TBLH) and lumbar spine (LS) scans were performed, and bone serum biomarkers were determined. Molecular analyses were carried out and clinical scores and skeletal features were assessed. Based on deep sequencing of a custom target gene panel, it was discovered that eight of the nine CdLS patients had potentially causative genetic variants in NIPBL. Fat and lean mass indices (FMI and LMI) were 3.4–11.1 and 8.4–17.0 kg/m2, respectively. For TBLH areal bone mineral density (aBMD), after adjusting for height for age Z-score of children and adolescents, two individuals (an adolescent and an adult) had low BMD (aBMD Z-scores less than –2.0 SD). Calcium, phosphorus, 25-OH-vitamin D, parathyroid hormone, and alkaline phosphatase levels were 2.08–2.49 nmol/L, 2.10–3.75 nmol/L, 39.94–78.37 nmol/L, 23.4–80.3 pg/mL, and 43–203 IU/L, respectively. Individuals with CdLS might have normal adiposity and low levels of lean mass measured with DXA. Bone health in this population seems to be less of a concern during childhood and adolescence. However, they might be at risk for impaired bone health due to low aBMD in adulthood.
Lattice-Point Mutually Guided Ground-to-Aerial Feature Matching for Urban Scene Images

Ground-to-aerial feature matching bridges information from cross-view images, which enables optimized urban applications, e.g., pixel-level geolocating and complete urban 3-D reconstruction. However, urban ground and aerial images typically suffer from drastic changes in viewpoint, scale, and illumination, together with repetitive patterns. Thus, direct matching of local features between ground and aerial images is particularly difficult because of the low similarity of local descriptors and high ambiguity in true–false match discrimination. For this challenging task, we propose a novel lattice-point mutually guided matching (LPMG) method in this article. We specifically address two key issues: 1) reducing descriptor variance and 2) enhancing true–false match discriminability. The former is solved by recovering the geometry and appearance of the underlying image region in 3-D through automatic view rectification on ground and aerial images. The latter is circumvented by replacing the conventional mismatch removal with an LPMG strategy. In this strategy, the topology structure of repeated façade elements (i.e., lattice), and the high reliable point matching seeds, are first extracted from the rectified ground and aerial images. Then, the point matching seeds guide the self-similar lattice tiles from two views to be precisely aligned, thereby estimating an accurate transformation model from lattice tile correspondences. Finally, the estimated model powerfully supervises the differentiation of true and false matches from the entire putative match set. Extensive experiments conducted on several datasets show that our method can obtain a considerable number of nearly pure correct matches from urban ground and aerial images, significantly outperforming those existing methods.
The effect of weed control timing on the growth and yield of upland rice (Oryza sativa L.)

Weed interference is a major threat to rice production, leading to high yield reduction and reduced profitability. Therefore, field experiments were conducted to evaluate the effect of the different timings of weed control on the growth and yield of upland rice in the 2015 and 2016 cropping seasons. The treatments consisted of periods when the crop was allowed to be weed-infested for the first 3, 6 and 9 weeks after sowing (WAS) and periods when the weeds were controlled for the first 3, 6 and 9 WAS. Two treatments of weed infestation and weed control until harvest were also included as the checks in a randomized complete block design with three replications. In both years, rice grain yields ranged from 0.6 to 0.8 t ha-1 in plots kept weed-infested until harvest, and from 3.5 to 3.9 t ha-1 in plots kept weed-free until harvest, indicating a 79-83% yield loss with uncontrolled weed growth. Weed infestation for the first 3 WAS did not cause a significant reduction in the growth and yield of rice provided the weeds were removed thereafter. However, the delay in weed control until 9 WAS reduced rice growth and resulted in irrevocable yield reduction. It was only necessary to remove the weeds between 3 and 9 WAS for optimum grain yield, as no significant yield increase was observed in weed control after 9 WAS in both years. This study showed that weed control between 3 and 9 WAS would give the optimum growth and yield of upland rice.
The Predictive Value of Serum Progesterone and Estrogen Recepters as Diagnostic Tool for Premature Ovarian Failure

Background: Premature ovarian insufficiency (POI) is a delicate medical problem in young women. Thiscondition is not unchangeable and permanent but is associated with intermittent and unpredictable ovarianactivity, resulting in low conception rate. Over the period of 8 years, the evaluation of secondary amenorrheawas conducted in 90 patients below the age of 40 who wished to restore fertility and is characterized byirregular or absent periods and reduced fertility. Symptoms include those associated with the naturalmenopause (night sweats and vaginal dryness), and with the long-term adverse effects of estrogen deficiency(osteoporosis and cardiovascular disease): The latter is believed to explain the shorter life expectancyassociated with POI.Aim: To illustrate the predictive value of progesterone receptors (PRs), estrogen receptors (ERs), progesterone(PRG), estradiol (E2), Lulilizing hormones (LH), Follicle stimulating hormones (FSH) and Anti mullerianhormones (AMH) serum levels as diagnostic approach for POI.Method: Sixty (60) women with idiopathic POF with thirty (30) women as control groups were includedin the study. Baseline investigation in all subjects included serum progesterone receptors(PRs), estrogenreceptors(ERs), progesterone (PRG), estradiol (E2), Lulilizing hormones (LH), Follicle stimulatinghormones (FSH) and Anti mullerian hormones (AMH) levels were estimated using appropriate assays inbiochemistry laboratory.Results: There was statistically significant differences in the serum progesterone receptors, estrogenreceptors, progesterone, estradiol, LH, FSH and AMH in POI cases when compared with healthy control(P=<0.05). Conclusion: These results indicate that serum progesterone and estrogen receptors levels, is high in POI casesas a result of lack progesterone and estradiol hormones as a result of loss negative feedback inhibition,thisresult may be used to primary diagnosis of premature ovarian failure.
Converting croplands to orchards changes soil microbial community composition and co‐occurrence patterns

Soil microorganisms are key to uncovering the mechanisms driving variation in soil biogeochemical processes associated with land‐use change. A large number of croplands have been converted to orchards on the Chinese Loess Plateau due to the increased economic benefits which result. However, the microbial community and their functional composition remain poorly understood. In this study, soil samples were collected from croplands and orchards. Soil physicochemical properties and the community (represented by 16S rRNA for bacteria and ITS for fungi) were measured, and interactions among species and the soil organic matter (SOM) degradation via microbial metabolism and its associated genes were analyzed. Croplands converted to orchards affected bacterial and fungal community structure by increasing the relative abundance of Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, and Ascomycota, whereas it decreased the α‐diversity of bacteria and fungi. The co‐occurrence network was larger and more complex within croplands than within orchards, indicating more extensive interactions and higher community stability potential. The abundance of potential genes related to cellulose and hemicellulose metabolism in orchards was higher than that in croplands, whereas the abundance of genes related to lignin decomposition was lower than that in croplands. In addition, the abundance of saprotrophic and symbiotrophic fungi in orchards was significantly lower than that in croplands (27 and 88%, respectively), whereas the abundance of pathotrophic fungi in orchards was almost six‐times that in croplands. The soil organic carbon (SOC) and soil C:N in orchards were significantly lower than that in croplands. Converting croplands to orchards significantly altered the microbial community composition and their functionality, as well as decreased the complexity of interaction between microorganisms. The decreased SOC and increased soil C:N ratio could be attributed to these variations. Improved management practices should be implemented for the maintenance of soil biodiversity and SOC in orchards to avoid soil degradation and ensure sustainable development.
Schoolnonattendance and childlabor in Mexico: North-South, Gender, and Rural Divides

This study addresses individual, household and contextual characteristics of children 12 to 17 years of age that determine nonattendance at school (naesc) and their integration to the labor market (pea) nationwide, the border states in the North and the South, including the Yucatan peninsula. The Infant Labor Module 2017 data was used to build probit models to estimate naesc and pea probabilities to assess marginal effects of observable characteristics while nonlinear decomposition was used to evaluate geographical, gender, and rural gaps. The differences in the probability of naesc and pea are not larger than . 9 percent between the North and South. Although the differences between females and males are not larger than . 2 percent for naesc, they are as large as 12 percent for pea. Moreover, the differences between nonrural vs rural were consistently large: 9-14 percent for naesc, and 8-10 percent for pea. Government support in encouraging school attendance and reduction of children in the labor market showed significant marginal effects throughout.
Generalized Nesterov's Acceleration-Incorporated, Non-Negative and Adaptive Latent Factor Analysis

A non-negative latent factor (NLF) model with a single latent factor-dependent, non-negative and multiplicative update (SLF-NMU) algorithm is frequently adopted to extract useful knowledge from non-negative data represented by high-dimensional and sparse (HiDS) matrices arising from various service-oriented applications. However, its convergence rate is slow. To address this issue, this study proposes a <underline>G</underline>eneralized Nesterov's acceleration-incorporated, <underline>N</underline>on-negative and <underline>A</underline>daptive <underline>L</underline>atent <underline>F</underline>actor (GNALF) model. It results from a) incorporating a generalized Nesterov's accelerated gradient (NAG) method into an SLF-NMU algorithm, thereby achieving an <underline>N</underline>AG-incorporated and <underline>e</underline>lement-oriented <underline>n</underline>on-negative (NEN) algorithm to perform efficient parameter update; and b) making its regularization and acceleration parameters self-adaptive via incorporating the principle of a particle swarm optimization algorithm into the training process, thereby implementing a highly adaptive and practical model. Empirical studies on six large sparse matrices from different recommendation service applications show that a GNALF model achieves very high convergence rate without the need of hyper-parameter tuning, making its computational efficiency significantly higher than state-of-the-art models. Meanwhile, such efficiency gain does not result in accuracy loss, since its prediction accuracy is comparable with its peers. Hence, it can better serve practical service applications with real-time demands.
A unique hybodontiform skeleton provides novel insights into Mesozoic chondrichthyan life

Asteracanthus was one of the most common Mesozoic hybodontiform chondrichthyans, given that remains traditionally referred to this genus have been reported almost worldwide from Middle Triassic to Late Cretaceous strata so far. Asteracanthus was erected by Louis Agassiz for Late Jurassic fin spines with stellate tubercles. Later, Arthur Smith Woodward synonymized Strophodus, originally introduced by Agassiz for distinctive crushing teeth of Triassic–Cretaceous age, with Asteracanthus based on associated teeth and spines from the English Middle Jurassic. This taxonomic scheme has been accepted for more than 130 years until now, although articulated material has never been found. Here, we present a unique hybodontiform skeleton from the German Late Jurassic, displaying a striking combination of characters: tuberculate dorsal fin spines reminiscent of Asteracanthus, and multicuspid teeth that markedly differ from the crushing teeth previously referred to this genus. Using qualitative and quantitative approaches, we compared its fin spines with those that were found in association with Agassiz's Strophodus teeth, providing evidence that Asteracanthus and Strophodus in fact represent two valid genera distinct from all other hybodontiforms. Morphological features that distinguish fin spines of Strophodus from those of all other hybodontiforms include a straight anterior border and distally distributed posterior denticles. These observations led us to present an emended diagnosis for Asteracanthus. Dentally, Asteracanthus shows strong resemblance to Hybodus, but it otherwise lacks a palatobasal process on the palatoquadrate. Therefore, and in the absence of any reliable phylogenetic framework, we recommend treating Asteracanthus as incertae familiae until hybodontiform interrelationships are resolved.