Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of objective bandwidth and frequency sampling density on search landscape structure and search performance in design optimization of optical structures

The typical aim of systematic design optimization in optics is to achieve specified performance over a prescribed set of frequencies—single or multiple, narrowly or broadly distributed. While search algorithms capable of efficiently sifting large design spaces have become crucial in such design optimization, the impact of the prescribed set of frequencies on search behavior remains not well understood. This article explores the impact of objective bandwidth and frequency sampling density on design optimization problem structure and search behavior. Particularly, this article explores some intuition—that broadband and/or finely frequency-sampled objectives yield more structured problems than narrowband and/or coarsely frequency-sampled counterparts—and both evidences this intuition and illustrates its practical value in search algorithm design. Specifically, a case study—combinatorial design optimization of a multi-spatial-mode photonic crystal waveguide bend that preserves modal content—evidences the above intuition via search landscape analysis, and illustrates how this intuition informs search algorithm design via comparative performance analysis of a collection of model search algorithms.
J C A P 1 0 ( 2 0 1 7 ) 0 0 9 ournal of C osmology and A stroparticle P hysics

We present a model for the redshift-space power spectrum of galaxies and demonstrate its accuracy in describing the monopole, quadrupole, and hexadecapole of the galaxy density field down to scales of k = 0.4hMpc−1. The model describes the clustering of galaxies in the context of a halo model and the clustering of the underlying halos in redshift space using a combination of Eulerian perturbation theory and N -body simulations. The modeling of redshift-space distortions is done using the so-called distribution function approach. The final model has 13 free parameters, and each parameter is physically motivated rather than a nuisance parameter, which allows the use of well-motivated priors. We account for the Finger-of-God effect from centrals and both isolated and non-isolated satellites rather than using a single velocity dispersion to describe the combined effect. We test and validate the accuracy of the model on several sets of high-fidelity N -body simulations, as well as realistic mock catalogs designed to simulate the BOSS DR12 CMASS data set. The suite of simulations covers a range of cosmologies and galaxy bias models, providing a rigorous test of the level of theoretical systematics present in the model. The level of bias in the recovered values of fσ8 is found to be small. When including scales to k = 0.4hMpc −1, we find 15-30% gains in the statistical precision of fσ8 relative to k = 0.2hMpc −1 and a roughly 10–15% improvement for the perpendicular Alcock-Paczynski parameter α⊥. Using the BOSS DR12 CMASS mocks as a benchmark for comparison, we estimate an uncertainty on fσ8 that is ∼10–20% larger than other similar Fourier-space RSD models in the literature that use k ≤ 0.2hMpc−1, suggesting that these models likely have a too-limited parametrization.
Characterization of post MI electrocardiogram using power ratio features and K-nearest neighbor classifier

Myocardial infarction (MI) is the irreversible necrosis of heart muscles caused by prolonged ischemic condition. Subsequently, the presence of damaged tissues in post-MI patients is expected to have an effect on their electrocardiogram (ECG). Hence, this paper proposes characterization of post-MI ECG from bipolar and augmented limb leads. Data from patients of inferior and anterior MI, as well as healthy controls are acquired from PTB Diagnostic ECG Database. Noise removal is performed using band-pass filter. Power ratio is then extracted from energy spectral density of bipolar and augmented limb leads. Classification via k-nearest neighbor method revealed that features from the augmented limb leads outperform bipolar limb leads in terms of training and testing accuracies. Hence, power ratio features from the augmented limb leads exhibit higher degree of separation between the ECG classes.
The fidelity of genetic information transfer with aging segregates according to biological processes

Maintenance of cellular function requires highly coordinated communication between trillions of biomolecules. However, over time, communication deteriorates, thereby disrupting effective information flow and compromising cellular health. To quantify the age-related loss of molecular communication, we applied information theory to quantify communication efficiency between transcription factors (TF) and corresponding target genes (TGs). Using single cell RNA-seq data from the limb muscle of young, middle-aged, and aged mice, we found that the precision with which TFs regulate TGs diminished with age, but that information transfer was preferentially preserved in a subset of gene pairs associated with homeostasis—a phenomenon we termed “age-based canalization”. Collectively, these data suggest that aging may be accompanied by a reallocation of resources that favor messages crucial to maintenance of stability and survival. One sentence summary As communication efficiency in the regulatory network diminishes, aged cells prioritize homeostatic over adaptive functions.
Genomewide basis for nitrogen use efficiency in contrasting genotypes of rice

Rice is an ideal crop with huge germplasm diversity and post-genomic resources for improvement of nitrogen (N) use efficiency (NUE). There is a paucity of comparative studies on rice genotypes contrasting for NUE, especially with urea, the predominant fertilizer in rice growing countries. In this study, low urea-responsive transcriptomes of contrasting rice genotypes namely Nidhi (low NUE) and Panvel1 (high NUE) were compared. They were based on whole plants grown for 21 days in pots containing nutrient-depleted soil fertilized with normal (15 mM) and low urea (1.5 mM) media. There were 1497 and 2819 differentially expressed genes (DEGs) in Nidhi and Panvel1, respectively, of which 271 were common. Though 1226 DEGs were genotype-specific in Nidhi and 2548 in Panvel1, there was far higher commonality in underlying processes. High NUE is associated with the urea-responsive regulation of other nutrient transporters, miRNAs, transcription factors and better photosynthesis, water use efficiency and post translational modifications. Many of their genes co-localized to NUE QTLs on chromosomes 1, 3 and 9. Field evaluation of the contrasting genotypes under different doses of urea revealed better performance of Panvel1 in different agronomic parameters including grain yield, transport/uptake efficiencies and NUE. Comparison of our urea-based transcriptomes with our previous nitrate-based transcriptomes from the same contrasting rice genotypes revealed many common processes despite large differences in their expression profiles. Our model proposes that differential involvement of transporters and transcription factors among others contributes to better urea uptake, translocation, utilization, flower development and yield for high NUE. Summary Rice genotypes with contrasting urea use efficiency differ in the role of transporters, transcription factors, miRNAs, post-translational modifications, photosynthesis and water use efficiency
Predicting the Reprogrammability of Human Cells Based on Transcriptome Data and SGD Classifier with Elastic-Net Regularization

Cell reprogramming has shown considerable importance in recent years; however, the programmability of cells and efficiency of reprogramming varies across different cell types. Considering several weeks of cell programming process and costly programming agents used through the process, every failure in reprogramming comes with a significant burden. Better planning for reprogramming experiments could be possible if there is a way of predicting the outcome of reprogramming before the experiments using transcriptome data. In this study, we have accessed the transcriptome data of successful or unsuccessful programming studies published in literature and constructed a Stochastic Gradient Descent (SGD) classifier with Elastic-Net regularization for predicting whether the cell lines are reprogrammable. We tested our classifier using 10-fold cross validation over cell lines and on each cell separately. Our results showed that it is possible to predict the outcome of cell reprogramming with accuracies up to 98% and Area Under the Curve (AUC) scores up to 0.98%. Considering the success of our experimental outcomes we conclude that an outcome of a cell reprogramming experiment can be predicted with high accuracy using machine learning on transcriptome data.
Turnover Intention and Job Satisfaction among Quantity Surveyors

Within the framework of human resource management, this study focuses on the issues of turnover intention and job satisfaction in the context of quantity surveying firms. Turnover intention leads to actual turnover. Several factors have been identified to cause turnover intention. Quantity surveyors are among the key players in construction projects. A quantity surveyor is involved in financial and contractual matters from the initiation stage to the completion of construction. In relation to the technical employees of quantity surveying firms, the objectives of this research are 1) to determine whether these employees have turnover intention and 2) to determine their level of job satisfaction. The data for this study were collected through a questionnaire survey. The scope of the study is limited to technical staff in quantity surveying firms in Malaysia. A total of 600 questionnaires were distributed to quantity surveyors in these firms, and 183 responses were received within the given period of time. Thus, the response rate for this study is 30.5%. This study found that 38.8% of respondents intend to quit their current organizations. This percentage is considered high and impacts the staff stability of the firms. Turnover intention might be related to job dissatisfaction; the majority of respondents were not satisfied with most of the items in the constructs of opportunities and rewards, specifically, the salaries, bonuses, benefits, and promotion opportunities provided by the firms. In addition, the majority of the respondents expressed their dissatisfaction with the opportunities provided by their firms to participate in work-related decisions and suggestions.
To Compare the Mean Percentage Improvement in Coordination, Strength and Disability in Overhead Throw Athletes with Partial Thickness tear of the Rotator Cuff Following Plyometric Training in Different Phases of Rehabilitation

Background & Objectives: To compare the mean percentage improvement in coordination, strength and disability in overhead throw athletes with partial thickness tear of the rotator cuff following plyometric training in different phases of rehabilitation. Methods: a total of 30 male overhead throwers suffering from partial thickness tear of the rotator cuff injury, on the basis of inclusion criteria were taken in the study. A full description of the study, including the selection process was explained to each patient. Documented consent was obtained from each patient. Group 1 consisted of athletes with history of rotator cuff injury one and half year back and group 2 included athletes with rotator cuff injury three months back. Coordination , strength and disability were assessed pre and post plyometric training for a period of three weeks and the mean percentage of improvement were compared in both the group following plyometric training. Results: intragroup analysis showed a significant improvement in coordination, strength with the level of significance (p<0.05). Discussion & Conclusion: group 1 showed an improvement in the mean percentage in coordination, the strength of supraspinatus muscle, and bench press when compared to the group 2. While the group 2 showed an improvement in mean percentage in the strength of the subscapularis, teres minor muscle and infraspinatus muscle when compared with the group1.
Modeling Soil Electrical Conductivity Under Impulse Discharge for Electrical Ground System

Soil electrical conductivity play an essential role in proper grounding system design for dissipation of static and dynamic electric charge. However, soil properties such as pH, moisture and nutrients causes’ non-linear variation in the soil electrical conductivity. This non-linear soil impedance phenomena directly affect electrical modeling of soil characteristics for efficient grounding system design. In this paper, the electrical dependency of soil properties on overall impedance have been investigated and used to formulate a soil impedance electrical circuit equation model through simulation and empirical methods. Electrical conductivity for samples of 30kg of soil with varying properties within at a moisture range of 14%-26% where injected with impulse discharge and the corresponding plot where fitted with electrical circuit simulation until a proper fit was achieved. The result shows that soil electrical impedance can be modeled with a complex circuit having both capacitive, resistive and inductive elements. Keywords— Equivalent circuit model, Grounding system, Impulse discharge, Soil conductivity, Soil Ionization.
Prediction of the crack condition of highway pavements using machine learning models

Abstract Departments of Transportation regularly evaluate the condition of pavements through visual inspections, nondestructive evaluations, image recognition models and learning algorithms. The above methodologies, though efficient, have drawn attention due to their subjective errors, uncertainties, noise effects and overfitting. To improve on the outcomes of the shallow learning models already used in pavement crack prediction, this paper reports on an investigation of the use of recursive partitioning and artificial neural networks (ANN; deep learning frameworks) in predicting the crack rating of pavements. Explanatory variables such as the average daily traffic and truck factor, roadway functional class, asphalt thickness, and pavement condition time series data are employed in the model formulation. Overall, it is observed that the recursive partitioning (regression tree – R2 > 0.8 and classification tree – R2 > 0.6) and ANN (continuous response – R2 > 0.8 and categorical response – R2 > 0.6) are compelling machine learning models for the prediction of the crack ratings based on their goodness-of-fit statistics, mean absolute deviation (MAD < 0.4) and the root mean square errors (RMSE between 0.30 and 0.65).
Reliability assessment of offshore dynamic scour protections using copulas

This article presents a methodology to assess the reliability of dynamic scour protections used to protect offshore wind turbine foundations. The computed probabilities of failure are based on a dataset of 124 months of hindcast data from the Horns Rev 3 offshore wind farm. Copula-based models are used to obtain the joint distribution function of the significant wave height and spectral peak period and to obtain the probability of failure of scour protections. The sensitivity of the probability of failure to each model is addressed. The influence of the duration of the waves’ time series is also studied. A sensitivity analysis of the probability of failure to physical constraints, such as the water depth, current’s velocity or the mean diameter of the armour units, is performed. The results show that probability of failure is dependent on the copula used to model the spectral parameters and the associated value of Kendall’s τ. It is shown that the copula presenting the best values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) did not lead to the probabilities of failure that are closer to the non-parametric estimation, obtained by means of the bivariate version of the Kernel density estimation method. The application to the case study led to annual probabilities of failure, which are comparable with the values applied for other offshore components, according to the current offshore wind industry standards.
Atmospheric fragmentation of meteoroids

The single body theory of meteoroid interaction with the atmosphere in the form of l = l(t), where l is the relative distance along the meteoroid trajectory and t the relative time, is generalized by allowing for points of sudden gross-fragmentation. This theory can be directly applied to photographic observations of meteors, comparing the measured distance, l obs , with the model computed distance, l, by means of the least-squares method. The no-fragmentation case has 4 free parameters to be determined from observations (l 0 , v 0 , v∞, σ), distance and velocity at time t = 0, velocity at t = −∞ and ablation coefficient, respectively
Spacing requirements of 0.7 in. (18 mm) diameter prestressing strands

The authors thank Insteel Industries Inc. for providing the strands and RJ Peterman and Associates Inc. for conducting the ASTM A1081 test method for strand bond for this research. The authors thank Don Logan for providing the financial support to conduct the ASTM A1081 test method for strand bond. The authors are also thankful to Richard Deschenes Jr., Cameron Murray, Joseph Daniels III, William Phillips, Doddridge Davis, Alberto Ramirez, and Ryan Hagedorn for helping fabricate the beams at the Engineering Research Center at the University of Arkansas.
Improvement of the inspection-repair process with building information modelling and image classification

Purpose Automated technologies have been applied to facility management (FM) practices to address labour demands of, and time consumed by, inputting and processing manual data. Less attention has been focussed on automation of visual information, such as images, when improving timely maintenance decisions. This study aims to develop image classification algorithms to improve information flow in the inspection-repair process through building information modelling (BIM). Design/methodology/approach To improve and automate the inspection-repair process, image classification algorithms were used to connect images with a corresponding image database in a BIM knowledge repository. Quick response (QR) code decoding and Bag of Words were chosen to classify images in the system. Graphical user interfaces (GUIs) were developed to facilitate activity collaboration and communication. A pilot case study in an inspection-repair process was applied to demonstrate the applications of this system. Findings The system developed in this study associates the inspection-repair process with a digital three-dimensional (3D) model, GUIs, a BIM knowledge repository and image classification algorithms. By implementing the proposed application in a case study, the authors found that improvement of the inspection-repair process and automated image classification with a BIM knowledge repository (such as the one developed in this study) can enhance FM practices by increasing productivity and reducing time and costs associated with ecision-making. Originality/value This study introduces an innovative approach that applies image classification and leverages a BIM knowledge repository to enhance the inspection-repair process in FM practice. The system designed provides automated image-classifying data from a smart phone, eliminates time required to input image data manually and improves communication and collaboration between FM personnel for maintenance in the decision-making process.
Pedagogical training of medicine professors

This study examines the pedagogical training process of medical professors at a Brazilian university, the meanings attributed to it, and the positive and negative aspects identified in it. This is a descriptive-exploratory study, using a qualitative approach with a questionnaire utilizing open-ended and closed questions and a semi-structured interview. The majority of queried individuals had no formal teacher training and learned to be teachers through a process of socialization that was in part intuitive or by modeling those considered to be good teachers; they received pedagogical training mainly in post-graduate courses. Positives aspects of this training were the possibility of refresher courses in pedagogical methods and increased knowledge in their educational area. Negative factors were a lack of practical activities and a dichotomy between theoretical content and practical teaching. The skills acquired through professional experience formed the basis for teaching competence and pointed to the need for continuing education projects at the institutional level, including these skills themselves as a source of professional knowledge.
Prediction of the Black-Hole Mass in 3C 273 by Multiband Observations

With the determined black-hole (BH) spin of 3C 273 by data-fitting to the detected iron Ko line emission in the soft X-ray band, the BH mass of the galaxy is predicted by formulations of both the observed disk-luminosity in the optical-UV band and the observed jetprecession in the radio band. The multiband synthesis suggests that the BH is supermassive, 2.4 x 109 Mev. Simultaneously, other physical parameters are self-consistently obtained at the precessing radius of 230.2rg : the accretion rate of the disk is 74.9Mev yr1, the Shakura-Sunyaev viscosity a is 0.134, and the radial & orbital velocities of fluid elements are 4.3 x 10-8 and 6.6 x 10-2 , respectively.
ANALISIS KECENDERUNGAN KELUHAN KESEHATAN PADA PAJANAN MEDAN ELEKTROMAGNETIK

The impact of electromagnetic field exposure on health is still controversial. Scientific evidence are very few. This study has the objective to add information about that issue. This study has been done at kecamatan Tulangan and Wonoayu Sidoarjo district in a community who live under 500 KV (Extra High Tension) transmission lines. The number of sample were 229 persons and taken by simple random sampling from a group of population between 15 - 49 years old. Electric and magnetic fields are measured using ELF (Extremely Low Frequency) survey meter, and health disorders were asked using questionnaries. The result of this study showed that for electric field exposure there are trends of increasing headache among the group of age 25-34 years and > 35 years old (p = 0,002 74; p = 0,00122) and also among male and female (p = 0,01962; p = 0,00160). Whereas magnetic field exposure gave the same impact for headache among groups age (p = 0,00305; p = 0,00381) and female (p = 0,00015). The increase of vertigo disorder happened among age group between 25 - 34 year old (p = 0,01251) and only among females (p = 0,04297) for electrical field exposure, whereas for magnetic field exposure p = 0,01173 and p = 0,0164. The increase in heart beat disorder only happened among the age group between 15 - 24 years oldfor magnetic field exposure. The conclusion of this study is that the increase of electromagnetic field exposure, so increases the prevalence of health disorders e. q headache, vertigo and heart beat.