Miracle-dz/UniFAR-FTUs huggingface dataset:
Transformation of a nonnormal distribution of quantitative traits for breeding purposes

Some continuous quantitative traits such as yield are not always normally distributed. This article proposes an underlying normal distribution—called the equivalent normal distribution—to help analyze and interpret the distribution of such data. The mean and standard deviation of this distribution are estimated through the regression of the theoretical (assuming normality) selection intensity on the corresponding observed standardized selection differential at each selection rate that may be applied (as many selection rates as individuals in the distribution). This simple and pragmatic transformation does not require scale transformations, which sometimes obscure biological interpretation. A possible biological interpretation of the Equivalent Normal Distribution is presented; it considers the difference between the potential and the eventually observed performance. This method allows comparisons between distributions of apparently different shapes. Simulations furthermore indicated that Equivalent statistics, compared with observed statistics, allowed an improved prediction of genetic values and estimation of realised heritability.
What kind of impacts can artwork have on viewers? Establishing a taxonomy for aesthetic impacts.

What kinds of impacts can visual art have on a viewer? To identify potential art impacts, we recruited five aesthetics experts from different academic disciplines: art history, neuroscience, philosophy, psychology and theology. Together, the group curated a set of terms that corresponded to descriptive features (124 terms) and cognitive-affective impacts (69 terms) of artworks. Using these terms as prompts, participants (n = 899) were given one minute to generate words for each term related to how an artwork looked (descriptive features) or made them think or feel (cognitive-affective impacts). Using network psychometric approaches, we identified terms that were semantically similar based on participants' responses and applied hierarchical exploratory graph analysis to map the relationships between the terms. Our analyses identified 17 descriptive dimensions, which could be further reduced to 5, and 11 impact dimensions, which could be further reduced to 4. The resulting taxonomy demonstrated overlap between the descriptive and impact networks as well as consistency with empirical evidence. This taxonomy could serve as the foundation to empirically evaluate art's impacts on viewers.
Estimating the Effect of a Time-Dependent Treatment by Levels of an Internal Time-Dependent Covariate: Application to the Contrast Between Liver Wait-List and Posttransplant Mortality

Few health policy issues in the U.S. are scrutinized as intensely as the distribution of organs for transplantation, with much effort currently underway to examine the efficacy of existing organ allocation algorithms. The design of efficient organ allocation policies depends strongly upon accurate estimates of the survival benefit of transplantation. Many organ allocation policies order patients on the wait-list based on time-dependent health status measures (internal time-dependent covariates), such that priority is given to candidates at the greatest risk for wait-list mortality. It is of great interest to measure the transplant benefit by levels of such health status measures to identify the status levels that represent either futile or unnecessary transplants. In the presence of observational data, the survival benefit of transplantation has, to date, been quantified through the parameter corresponding to a binary time-dependent transplant indicator variable. Parameters from a standard time-dependent analysis using existing methods (i.e., separate transplant indicator for each status level) are difficult to interpret because they apply while the patient is at a particular level; i.e., they account for the patient's current condition, but do not account for the possibility that the patient's condition may worsen. We propose a novel method for estimating the effect of a time-dependent treatment by levels of an internal time-dependent covariate. The method yields parameter estimates which, rather than applying to the patient's current health status, average over future potential changes in health status. The proposed method is applied to end-stage liver disease data obtained from a national organ failure registry.
The global prevalence of premature ovarian insufficiency: a systematic review and meta-analysis

Abstract Objective The objective of this review was to answer the global prevalence of premature ovarian insufficiency (POI), and explore the associated factors including etiopathology and regions with POI. Methods The search was conducted on reports from a total of eight databases that comprised Chinese National Knowledge Infrastructure (CNKI), Wanfang, China BioMedical Literature Database (CBM), PubMed, the Cochrane Library, Embase, Web of Science and Ovid MEDLINE® between 1946 and 2021. To analyze the source of heterogeneity, we performed subgroup analysis based on different etiologies and regions. Meta-analysis was carried out by Stata14.0 software. Results The results showed that the global overall prevalence of POI among women was 3.5%. By subgroup analysis, the prevalence of POI among women with iatrogenic etiology was 11.2%, followed by autoimmunity (10.5%); the prevalence of POI by region was 11.3% at the highest in North America followed by South America (5.4%); and the prevalence of POI was 5.3% in a developing country, higher than 3.1% in a developed country. The trend of prevalence of POI over the past 20 years was on the rise (although p > 0.05). Conclusion We recommend that health and medical institutions strengthen public health awareness, achieve health-education goals related to POI and increase women’s awareness of and attention to POI.
The proportional bettor's return on investment

Suppose you repeatedly play a game of chance in which you have the advantage. Your return on investment is your net gain divided by the total amount that you have bet. It is shown that the ratio of your return on investment under optimal proportional betting to your return on investment under constant betting converges to an exponential distribution with mean as your advantage tends to 0. The case of non-optimal proportional betting is also treated.
Post Harvest Treatments and Shelf Life of Some Tropical Fruit

Fruits are perishable horticultural crops grown in tropical and sub-tropical areas of the world. It is a richest source of micro nutrients and phyto chemicals that contributed a significant role in human health. Mango, avocado, papaya, guava and pine apple are popular and economically important tropical fruits due to their essential nutritional properties and appreciated eating quality. However, in developing countries, upto 50% of those fruits are lost after harvest due to improper post-harvest handling practices. Edible coating, dip in calcium chloride solution, hot water treatment and drying are easily applicable post harvest treatments used in the preservation of such tropical fruits. Shelf life of mangoes coated using edible coating material can be extended up to 18 days without rotting and developing unpleasant-flavour relative to coated guava, papaya, avocado and pine apple fruits. Dipping harvested fruits in various concentration of calcium chloride solution exhibited different storage life. Consequently, mango fruits treated with 10% of calcium chloride solution preserved for 30 days at 12°C and 85-90% relative humidity. Guava fruits treated by hot water at 45oC for 3 minute lasts upto 31 days under room temperature. In this review maximum shelf life up to 9 months was found for Avocado fruit dried using freeze drying method.
Exploring the resilience and epistemic access of first-year female students in higher education

The transition from secondary to tertiary education often presents many first-year female students with anxiety and emotional stress. Subsequently, poorly managing this shift may increase academic risk and compromise their academic success. While a plethora of studies contribute towards the phenomenon of resilience as a positive predictor of the learning experience of female students in higher education, other scholarly findings suggest the key role resilience plays in supporting students to overcome challenges, manage their wellbeing and ultimately acquire epistemic access. Moreover, there is a significantly burgeoning focus on the positive outcomes of the resilience of women in education, However, while many of the studies highlight gender as a noteworthy core construct, to date, little is known about the first-year learning experience (FYE) of female students and how they may negotiate epistemic access through academic resilience. Hence the main aim of this article is to explore what factors enable academic resilience and to what extent such factors influence epistemic access among first-year female students. An exploratory qualitative research approach was used to capture the learning experiences of 20 hospitality accounting first-year female students. Data were collected by conducting both focus group sessions and individual semi-structured interviews. The findings of the study identified four main themes. The findings of this article have implications for promoting gender equality and academic outcomes of first-year female students in understanding the risk factors, as well as encouraging the protective factors that enable their epistemic access.Contribution: The article sheds light on how an intangible construct such as resilience serves as a vehicle for epistemic access, more especially for first-year female students.
Blending approaches to enhance structural order in block-copolymer's self-assemblies

Various blends approaches based on PS-b-PMMA block-copolymers (BCP) systems are studied. The impacts of the different components in the blends on various basic characteristics of interest for lithographic applications are highlighted. More specifically, we show how such approaches can be managed to get a tight control over the different dimensions of the self-assembly, and reach lower defects levels than a single pure BCP. These methods could greatly help the BCP self-assembly technology to be introduced as an actual lithographic technic to further reduce achievable dimensions.
Bayesian Semiparametric Joint Models for Functional Predictors

Motivated by the need to understand and predict early pregnancy loss using hormonal indicators of pregnancy health, this article proposes a semiparametric Bayesian approach for assessing the relationship between functional predictors and a response. A multivariate adaptive spline model is used to describe the functional predictors, and a generalized linear model with a random intercept describes the response. Through specifying the random intercept to follow a Dirichlet process jointly with the random spline coefficients, we obtain a procedure that clusters trajectories according to shape and according to the parameters of the response model for each cluster. This very flexible method allows for the incorporation of covariates in the models for both the response and the trajectory. We apply the method to postovulatory progesterone data from the Early Pregnancy Study and find that the model successfully predicts early pregnancy loss.
Rotational and Vibrational Relaxation in Diatomic Gases

Calculations of rotational and vibrational relaxation times for gases composed of homonuclear diatomic molecules have been carried out. The model used for the molecular interaction potential consists of an attractive component, which acts between geometrical centers of the molecules, and a repulsive component which is assumed to originate from two centers of force in each of the molecules. For large intermolecular separations, the attractive forces prevail while at close distances the repulsive forces control. Using this model, the number of collisions to establish rotational equilibrium ZR and also the number for vibraton ZV are calculated. Both ZR and ZV contain some of the same molecular parameters and are therefore dependent on each other. From the analysis it turns out that ZR is a gradually increasing function of increasing temperature and ZV is a rapidly decreasing function of increasing temperature. Comparison with experiment for the gases chlorine, nitrogen, and oxygen indicates that the calculat.
Influences of Annealing Temperature on Characteristics of Ge p-Channel Metal Oxide Semiconductor Field Effect Transistors with ZrO2 Gate Dielectrics

The dependence of gate leakage current and p+/n-junction characteristics on annealing temperature is investigated comprehensively in order to obtain good electrical characteristics of Ge p-channel metal oxide semiconductor field effect transistors (p-MOSFETs) with ZrO2 gate dielectrics. The upper limit of annealing temperature is restricted to 500 °C to preserve low gate leakage. Gate leakage current remains low even after Ge incorporation into ZrO2, because ZrO2/Ge gate stacks retain their band alignment to as high as 500 °C. The degradation of gate leakage at the high temperature of 700 °C is due to the emergence of void regions near the interface in the Ge substrate. On the other hand, the lower limit of the annealing temperature is restricted to 400 °C in order to activate dopant boron sufficiently. Good rectifying diode characteristics lead to promising p-MOSFET performance, such as an S-factor of 80 mV/decade. The effective hole mobility of the ZrO2/Ge gate stack without an intentional interfacial layer after annealing at the optimized temperature is as high as 100 cm2/(V·s).
Maximum Kurtosis Phase Correction

Summary Seismic reflectivity sequences have amplitude distributions that are leptokurtic, that is, they are more heavy-tailed than a Gaussian distribution. This property forms the basis of a method of phase adjustment for seismic reflection data, called maximum kurtosis phase correction (MKPC), that maximizes the ‘stand-out’ of events on seismic sections. the method is normally applied after standard deconvolution and stacking and, unlike methods of minimum entropy deconvolution (MED) which attempt to employ the same property of seismic reflectivities, it is a thoroughly predictable and testable process. the requirements for estimating stable phase corrections can be stated explicitly and, moreover, these show exactly why MED has never been a practical success. The method simply determines, in an efficient way, the frequency-independent phase shift that maximizes the kurtosis of the seismic data. In so doing it realizes the true potential advantage of MED-type methods, the ability to tune the phase, without attempting to control signal whitening and noise amplification, where MED methods offer no advantage over the near-optimum balance already achievable from the usual well-tried deconvolution tests. A constant phase shift is sufficient correction for most post-stack processing and, although stable estimates sometimes demand surprisingly large amounts of data, the selection of the phase correction that maximizes kurtosis is very straightforward and easily tested. the paper gives the theory of the method and describes its data requirements by means of expressions that relate the accuracy of the phase estimates to the amount, bandwidth, and kurtosis of the seismic data. Equations are also given to show how noise and filtering affect the kurtosis of a seismic trace. By analysing the operation of a band-limited phase-shifter, it is shown that the bandwidth of the data must exceed the centre frequency for a successful determination of a phase shift from maximum kurtosis, and the magnitudes of the variations in kurtosis with phase angle for bandwidths above this threshold are derived. the phase correction itself can be determined without applying a whole series of phase shifts to the data. the performance of the method on seismic data is fully consistent with the theory presented here and has been reported in separate studies (Levy & Oldenburg 1987; Longbottom, Walden & White 1988; Hosken et al. 1987).
Speedometer for withdrawal time monitoring during colonoscopy: a clinical implementation trial

Abstract Objectives Meticulous inspection of the mucosa during colonoscopy, represents a lengthier withdrawal time, but has been shown to increase adenoma detection rate (ADR). We investigated if artificial intelligence-aided speed monitoring can improve suboptimal withdrawal time. Methods We evaluated the implementation of a computer-aided speed monitoring device during colonoscopy at a large academic endoscopy center. After informed consent, patients ≥18 years undergoing colonoscopy between 5 March and 29 April 2021 were examined without the use of the speedometer, and with the speedometer between 29 April and 30 June 2021. All colonoscopies were recorded, and withdrawal time was assessed based on the recordings in a blinded fashion. We compared mean withdrawal time, percentage of withdrawal time ≥6 min, and ADR with and without the speedometer. Results One hundred sixty-six patients in each group were eligible for analyses. Mean withdrawal time was 9 min and 6.6 s (95% CI: 8 min and 34.8 s to 9 min and 39 s) without the use of the speedometer, and 9 min and 9 s (95% CI: 8 min and 45 s to 9 min and 33.6 s) with the speedometer; difference 2.3 s (95% CI: −42.3–37.7, p = 0.91). The ADRs were 45.2% (95% CI: 37.6–52.8) without the speedometer as compared to 45.8% (95% CI: 38.2–53.4) with the speedometer (p = 0.91). The proportion of colonoscopies with withdrawal time ≥6 min without the speedometer was 85.5% (95% CI: 80.2–90.9) versus 86.7% (95% CI: 81.6–91.9) with the speedometer (p = 0.75). Conclusions Use of speed monitoring during withdrawal did not increase withdrawal time or ADR in colonoscopy. ClinicalTrials.gov Identifier NCT04710251
The robustness of lognormal-based estimators of abundance

We test the robustness of a method for estimating abundance that assumes that the underlying distribution of the nonzero observations is lognormal (Pennington, 1983, Biometrics 39, 281-286). Violations in model assumptions that cannot reliably be detected with moderate sample sizes (-40) lead to biases and large reductions in efficiency. Unless it can be clearly demonstrated from repeated sampling that nonzero values follow a lognormal distribution, the sample mean and variance are more robust than lognormal-based estimators of mean and variance of population abundance.
Physiological Status Prediction Based on a Novel Hybrid Intelligent Scheme

Physiological status plays an important role in clinical diagnosis. However, the temporal physiological data change dynamically with time, and the amount of data is large; furthermore, obtaining a complete history of data has become difficult. We propose a hybrid intelligent scheme for physiological status prediction, which can be effectively utilized to predict the physiological status of patients and provide a reference for clinical diagnosis. Our proposed scheme initially extracted the attribute information of nonlinear dynamic changes in physiological signals. The maximum discriminant feature subset was selected by employing conditional relevance mutual information feature selection. An optimal subset of features was fed into the particle swarm optimization–support vector machine classifier to perform classification. For the prediction task, the proposed hybrid intelligent scheme was tested on the Sleep Heart Health Study dataset for sleep status prediction. Experimental results demonstrate that our proposed intelligent scheme outperforms the conventional machine learning classification methods.
Epipolar image generation on vehicle-based sequence images based on fundamental matrix

In the process of 3D information extraction using sequence images collected by vehicle-based mobile measurement system, epipolar image eliminates the vertical disparity of image pairs. Furthermore, it converts the search area of the correspondences from two-dimensional plane to one-dimensional line in dense matching, thus improving the matching accuracy and efficiency. However, unlike the nearly horizontal epipolar lines of aerial images, the epipolar lines of the vehicle-based sequence image pairs are distributed radially on the images, which makes it difficult for the vehicle-based sequence images to generate epipolar images. To solve the above problems, the fundamental matrix is used to determine the geometrical relation of the image pair to epipolar line. Then the epipolar image is generated by the fan-shaped circular epipolar model. First, high-precision correspondences are obtained by sparse matching for fundamental matrix estimation. Then we use the fundamental matrix to map the nuclear line quickly and determine the region of the epipolar line. At last, the image of the epipolar line area is resampled by bilinear interpolation in the direction of the epipolar line. Experiments were conducted using multiple sets of vehicle-based sequence images, and the average vertical disparity of the correspondences of the generated epipolar image is 0.63 pixels. The results show that the vertical disparity of the epipolar image generated by the proposed method is smaller, which verifies the correctness of the process.
Comparison of the Compression and Tensile Modulus of Two Chosen Resins Used in Dentistry for 3D Printing

(1) The CAD/CAM technique exploiting 3D printing is becoming more and more popular in dentistry. The resins are used in all the dental specialties, including conservative dentistry, prosthodontics, surgery, and orthodontics. The interest in investigating the different properties of dental materials has been an aim of researchers. The purpose of the presented study was to compare the properties of two 3D-printable dental resins (both rigid, used for medical purposes). (2) Methods: Ten blocks of two-type shapes were printed on a printer designed for medical use. The tensile modulus and compression were investigated and compared. The axial compression test was performed according to the PN-EN ISO 604:2003 norm, while the tensile test was performed according to the PN-En ISO 527-1-2019 (E) norm. In the first test, the sample size of the perpendicular shape was 10 ± 0.2 mm × 10 ± 0.2 mm × 4 ± 0.2 mm and in the second it was 75 mm, the end width 10 mm, and the thickness 2 mm. (3) Results: The statistical analysis based on ANOVA tests showed that all the obtained results were statistically significant. Both of the examined materials had similar properties and were resistant and stable in shape. The tensile modulus and compression tests performed on them gave similar results. They also showed high durability to compression and tensility. (4) Conclusions: Both of the examined materials were durable and rigid materials. BioMed Amber was more resistant to compression, while Dental LT clear was more resistant in the tensility test. Although both resins had similar physical properties, it is still disputable whether the chosen materials could be used interchangeably.