Miracle-dz/UniFAR-FTUs huggingface dataset:
Accounting for the effects of a ruminal nitrogen deficiency within the structure of the Cornell Net Carbohydrate and Protein System.

The Cornell Net Carbohydrate and Protein System (CNCPS) prediction of fiber digestion and microbial mass production from ruminally degraded carbohydrate has been adjusted to accommodate a ruminal N deficiency. The steps for the adjustment are as follows: 1) the ruminal available peptide and ammonia pools are used to determine the N allowable microbial growth; 2) this value is subtracted from the energy allowable microbial growth to obtain the reduction in microbial mass; 3) this mass reduction is allocated between pools of bacteria digesting fiber (FC) and nonfiber (NFC) carbohydrate according to their original proportions in the energy allowable microbial growth; 4) the reduction in fermented FC is computed as the FC bacterial mass reduction divided by its yield (g bacteria/g FC digested); and 5) this reduction is added to the FC fraction escaping the rumen. Five published studies included information that allowed us to evaluate the response of animals to added dietary N. These evaluations compared observed and CNCPS-predicted ADG with and without this adjustment. The adjustment decreased the CNCPS overprediction of ADG from 19.2 to 4.7%, mean bias declined from . 16 to . 04 kg/d, and the r2 of the regression between observed and metabolizable energy (ME) or metabolizable protein allowable ADG was increased from . 83 to . 88 with the adjustment. When the observed dry matter intake was regressed against CNCPS-predicted DMI with an adjustment for reduction in cell wall digestibility, the r2 was increased from . 77 to . 88. These results indicated the adjustment for ruminal nitrogen deficiency increased the accuracy of the CNCPS model in evaluating diets of growing animals when ruminally degraded N is deficient.
Application of Adaptive Digital Beamforming to Osaka University Phased Array Weather Radar

The X-band phased array weather radar (PAWR) at Osaka University has a rapid scanning rate and is capable of high-density observations in elevation; it produces approximately 100 plan position indicator radar images with a 60-km range, at different elevation angles, in less than 30 s. The PAWR uses a fan-shaped beam with a narrow beamwidth (1.2°) in azimuth and a wider beamwidth (from 5° to 10°) in elevation. With digital beamforming (DBF), the elevation beamwidth can be reduced to 1.2°, using 128 antenna elements arranged in tandem. Although the fan-shaped beam is useful for rapid scanning, the received signals tend to be affected by ground clutter. In this paper, we investigate the clutter suppression capability of common DBF methods: Fourier, Capon, and minimum mean-square error (MMSE) beamforming. Furthermore, to improve performance when the PAWR data contain errors—such as lacking data caused by mechanical problems—a correction method is proposed. The effect of clutter suppression using MMSE is shown to be greatly improved if used together with the proposed correction method. The resulting method is shown to sufficiently suppress clutter in all elevation angles above a few degrees, even in the presence of strong clutter; its clutter reduction performance is compared and found to be superior to the ones of the analyzed conventional DBF methods.
Mendelian and Non-Mendelian Regulation of Gene Expression in Maize

Transcriptome variation plays an important role in affecting the phenotype of an organism. However, an understanding of the underlying mechanisms regulating transcriptome variation in segregating populations is still largely unknown. We sought to assess and map variation in transcript abundance in maize shoot apices in the intermated B73×Mo17 recombinant inbred line population. RNA–based sequencing (RNA–seq) allowed for the detection and quantification of the transcript abundance derived from 28,603 genes. For a majority of these genes, the population mean, coefficient of variation, and segregation patterns could be predicted by the parental expression levels. Expression quantitative trait loci (eQTL) mapping identified 30,774 eQTL including 96 trans-eQTL “hotspots,” each of which regulates the expression of a large number of genes. Interestingly, genes regulated by a trans-eQTL hotspot tend to be enriched for a specific function or act in the same genetic pathway. Also, genomic structural variation appeared to contribute to cis-regulation of gene expression. Besides genes showing Mendelian inheritance in the RIL population, we also found genes whose expression level and variation in the progeny could not be predicted based on parental difference, indicating that non-Mendelian factors also contribute to expression variation. Specifically, we found 145 genes that show patterns of expression reminiscent of paramutation such that all the progeny had expression levels similar to one of the two parents. Furthermore, we identified another 210 genes that exhibited unexpected patterns of transcript presence/absence. Many of these genes are likely to be gene fragments resulting from transposition, and the presence/absence of their transcripts could influence expression levels of their ancestral syntenic genes. Overall, our results contribute to the identification of novel expression patterns and broaden the understanding of transcriptional variation in plants.
De-anonymizing social networks

The problem of de-anonymizing social networks is to identify the same users between two anonymized social networks [7] (Figure 1). Network de-anonymization task is of multifold significance, with user profile enrichment as one of its most promising applications. After the deanonymization and alignment, we can aggregate and enrich user profile information from different online networking services and make the bundled profiles available for end-users as well as thirdparty applications. In our project, we aim to develop effective algorithms for de-anonymizing real-world social networks. Specifically, we focus on two tasks: one is to align the networks of Flickr1 and Instagram2 and the other is to align Flickr and Twitter 3. Our work is motivated by the two parts of information that network data is composed of: network structure and node attributes. Preliminary tests have shown that de-anonymizing algorithm based merely on node attributes, e.g. user names, is computationally efficient but not satisfactorily accurate. On the other hand, algorithms that rely on network structures, which bring in more relationship information, may contribute to the precision of de-anonymization. However, not only may the structure of the real-world social networks be quite different, but also the computation costs will be intractably high since the maximum common
Wire-length Prediction using Statistical and Probabilistic Techniques

We address the classic wire-length estimation problem and propose a new statistical wire-length estimation approach that captures the probability distribution function of net lengths after placement and before routing. These types of models are highly instrumental in formalizing a complete and consistent probabilistic approach to design automation and design closure where along with optimizing the pertinent cost function, the associated prediction error is also considered. The wire-length prediction model was developed using a combination of parametric and non-parametric statistical techniques. The model predicts not only the length of the net using input parameters extracted from the floorplan of a design, but also probability distributions that a net with given characteristics obtained after placement will have a particular length. The model is validated using both learn-and-test and resubstitution techniques. The model can be used for a variety of purposes, including the generation of a large number of statistically sound and therefore realistic instances of designs. We applied the net models to the probabilistic buffer insertion problem and obtained substantial improvement in net delay after routing (∼40%) when compared to a traditional bounding box-based buffer insertion strategy.
Separable cosparse Analysis Operator learning

The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse representations, the cosparse analysis model has recently gained increasing interest. Many signals exhibit a multidimensional structure, e.g. images or three-dimensional MRI scans. Most data analysis and learning algorithms use vectorized signals and thereby do not account for this underlying structure. The drawback of not taking the inherent structure into account is a dramatic increase in computational cost. We propose an algorithm for learning a cosparse Analysis Operator that adheres to the preexisting structure of the data, and thus allows for a very efficient implementation. This is achieved by enforcing a separable structure on the learned operator. Our learning algorithm is able to deal with multidimensional data of arbitrary order. We evaluate our method on volumetric data at the example of three-dimensional MRI scans.
Oxygen isotopic fractionation of O₂ during adsorption and desorption processes using molecular sieve at low temperatures.

RATIONALE Cryogenic trapping using molecular sieves is commonly used to collect O2 extracted from silicates for (17)O/(16)O and (18)O/(16)O analyses. However, gases which interfere with (17)O/(16)O analysis, notably NF3, are also trapped and their removal is essential for accurate direct measurement of the (17)O/(16)O ratio. It is also necessary to identify and quantify any isotopic fractionation associated with the use of cryogenic trapping using molecular sieves. METHODS The oxygen isotopic compositions of O2 before and after desorption from, and adsorption onto, 13X and 5A molecular sieves (MS13X and MS5A) at 0°C, -78°C, -114°C, and -130°C were measured in order to determine the oxygen isotopic fractionation at these temperatures. We also investigated whether isotopic fractionation occurred when O2 gas was transferred sequentially into a second cold finger, also containing molecular sieve. RESULTS It was confirmed that significant oxygen isotopic fractionation occurs between the gaseous O2 and that adsorbed onto molecular sieve, if desorption and adsorption are incomplete. As the fraction of released or untrapped O2 becomes smaller with decreasing trapping temperature (from 0 to -130°C), the isotopic fractionation becomes larger. Approximately half of the total adsorbed O2 is released from the molecular sieve during desorption at -114°C, which is the temperature recommended for separation from NF3 (retained on the molecular sieve), and this will interfere with (17)O/(16)O measurements. CONCLUSIONS The use of a single cold finger should be avoided, because partial desorption is accompanied by oxygen isotopic fractionation, thereby resulting in inaccurate isotopic data. The use of a dual cold finger arrangement is recommended because, as we have confirmed, the transfer of O2 from the first trap to the second is almost 100%. However, even under these conditions, a small isotopic fractionation (0.18 ± 0.05‰ in δ(17)O values and 0.26 ± 0.06‰ in δ(18)O values) occurred, with O2 in the second trap being isotopically enriched in the heavier isotopes.
Radiative corrections to the inflaton potential as an explanation of suppressed large scale power in density perturbations and the cosmic microwave background

The Wilkinson microwave anisotropy probe microwave background data suggest that the primordial spectrum of scalar curvature fluctuations is suppressed at small wavenumbers. We propose a UV/IR mixing effect in small field inflationary models that can explain the observable deviation in WMAP data from the concordance model. Specifically, in inflationary models where the inflaton couples to an asymptotically free gauge theory, the radiative corrections to the effective inflaton potential can be anomalously large. This occurs for small values of the inflaton field which are of the order of the gauge theory strong coupling scale. Radiative corrections cause the inflaton potential to blow up at small values of the inflaton field. As a result, these corrections can violate the slow roll condition at the initial stage of the inflation and suppress the production of scalar density perturbations.
Sharing of Bacterial Strains Between Breast Milk and Infant Feces

In previous years, it has been shown that human milk is a potential source of bacteria for the infant gut. The results of this work confirm the presence of the same specific bacterial strains of Bifidobacterium, Lactobacillus, and Staphylococcus in breast milk and infant fecal samples. The identity of bacteria isolated from breast milk and infant feces from 20 mother-infant pairs was investigated at the strain level. DNA from Staphylococcus, Lactobacillus, and Bifidobacterium was detected by qRTi-PCR in nearly all samples analyzed. These samples were cultured on different agar media. One colony representative of each morphology was selected and identified at the species level combining classical tests and molecular techniques (PCR, RAPD, PFGE, and/or MLST genotyping). Breast milk and infant feces from 19 mother-infant pairs shared different Staphylococcus, Lactobacillus, and/or Bifidobacterium species and strains. Significantly, 2 mother-infant pairs shared 4 bacterial strains although most pairs shared 2. These results confirm that breast milk and infant feces from mother-infant pairs share the same strain(s), indicating that breastfeeding could contribute to the bacterial transfer from the mother to the infant and, therefore, to the infant gut colonization.
A Bayesian Semiparametric Model for Volatility with a Leverage Effect

A Bayesian semiparametric stochastic volatility model for financial data is developed. This nonparametrically estimates the return distribution from the data allowing for stylized facts such as heavy tails of the distribution of returns whilst also allowing for correlation between the returns and changes in volatility, which is usually termed the leverage effect. An efficient MCMC algorithm is described for inference. The model is applied to simulated data and two real data sets. The results of fitting the model to these data show that choosing a parametric return distribution can have a substantial effect on inference about the leverage effect.
Diurnal Variation in Tennis Service

With informed consent, 6 competitive tennis players performed alternate 15 “first” (emphasis-speed) serves and 15 “second” (emphasis-accuracy) serves at 09:00, 14:00 and 18:00 hours. Serve velocity was measured by the digitisation of video footage of each serve. The Hewitt Tennis Achievement Test was employed to measure the accuracy of serve. The amount of spin imparted on the ball was not measured. First serves were at all times of day faster than second serves. First serves were faster but least accurate at 18:00 hours, the time of day that body temperature and grip strength were highest. At 09:00 hours, first serves were just as accurate as second serves, even though velocity of first serves was higher. No effects for time of day were found for the speed and accuracy of second serves. These results indicate that time of day does affect the performance of tennis serves in a way that suggests a nonlinear relationship between velocity and accuracy.
Effectiveness of rifampin in eradicating the meningococcal carrier state in a relatively closed population: emergence of resistant strains.

A four-day course of therapy with rifampin (900 mg/day in a single dose) was given to a relatively closed population consisting of three companies of U.S. Army recruits. This regimen resulted in the eradication of the meningococcal carrier state in 83 of 90 individuals. The carrier rate for the treated companies fell from an average of 21% to 2% following treatment. Thereafter, the carrier rate rose gradually to reach an average of 11% at eight weeks after initiation of the study. The carrier rates of the two control companies rose from an average of 22% in the first week to 84% at eight weeks. The emergence of strains of Neisseria meningitidis resistant to 500 [tg/ml of rifampin was observed in four individuals following treatment. All strains isolated before treatment were sensitive to 0.25 Rg/ ml of rifampin or less. While rifampin appears to be an effective prophylactic agent for meningococcal disease, its usefulness is severely limited by the high rate of emergence of resistant organisms.
Functional polymorphism in the MicroRNA-367 binding site as a prognostic factor for colonic cancer.

BACKGROUND As microRNAs play important roles in cancer development and progression by regulating the expressions of oncogenes and tumor suppressor genes though interacting with the 3' untranslated region (UTR) of target genes, we aimed to evaluate the association between genetic variants of miRNAs and their binding sites and prognosis in patients with colorectal cancer (CRC). MATERIALS AND METHODS Three miRNA variants and four variants in the miRNA binding sites were selected based on allelic frequencies, while their potential impact has been described in previous studies. DNA was extracted from fresh-frozen tissues of 344 patients with CRC who underwent curative surgery and genotyping analyses were performed using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. RESULTS Among seven target variants, rs1044129 at the miR-367 binding site of calcium channel ryanodine receptor gene 3 (RYR3) was associated with relapse-free survival (RFS) for colon cancer patients as a recessive model in a univariate analysis. Moreover, a multivariate analysis revealed that patients carrying the GG genotype had poor RFS, compared to those with the AA or AG genotype (hazard ratio, HR=2.864; p=0.005), yet there was only a marginal trend for disease-specific survival (HR=2.226; p=0.087) regardless of patient and tumor characteristics. CONCLUSION The current study suggests that the functional variant (rs1044129) in the miR-367 binding site of RYR3 may be a potential marker for prognosis in patients following curative surgery for CRC.
Distance-Based Representative Skyline

Given an integer $k$, a {\em representative skyline} contains the $k$ skyline points that best describe the tradeoffs among different dimensions offered by the full skyline. Although this topic has been previously studied, the existing solution may sometimes produce $k$ points that appear in an arbitrarily tiny cluster, and therefore, fail to be representative. Motivated by this, we propose a new definition of representative skyline that minimizes the distance between a non-representative skyline point and its nearest representative. We also study algorithms for computing distance-based representative skylines. In 2D space, there is a dynamic programming algorithm that guarantees the optimal solution. For dimensionality at least 3, we prove that the problem is NP-hard, and give a 2-approximate polynomial time algorithm. Using a multidimensional access method, our algorithm can directly report the representative skyline, without retrieving the full skyline. We show that our representative skyline not only better captures the contour of the entire skyline than the previous method, but also can be computed much faster.
A Comparative Study of Sampling Analysis in the Scene Classification of Optical High-Spatial Resolution Remote Sensing Imagery

Scene classification, which consists of assigning images with semantic labels by exploiting the local spatial arrangements and structural patterns inside tiled regions, is a key problem in the automatic interpretation of optical high-spatial resolution remote sensing imagery. Many state-of-the-art methods, e.g., the bag-of-visual-words model and its variants, the topic models and unsupervised feature learning-based approaches, share similar procedures: patch sampling, feature learning and classification. Patch sampling is the first and a key procedure, and it has a considerable influence on the results. In the literature, many different sampling strategies have been used, e.g., random sampling and saliency-based sampling. However, the sampling strategy that is most suitable for the scene classification of optical high-spatial resolution remote sensing images remains unclear. In this paper, we comparatively study the effects of different sampling strategies under the scenario of scene classification of optical high-spatial resolution remote sensing images. We divide the existing sampling methods into two types: random sampling and saliency-based sampling. Here, we consider the commonly-used grid sampling to be a specific type of random sampling method, and the saliency-based sampling consists of keypoint-based sampling and salient region-based sampling. To compare their performances, we rely on a standard bag-of-visual-words model to learn the global features for testing because of its simplicity, robustness and efficiency. In addition, we conduct experiments using a Fisher kernel framework to validate our conclusions. The experimental results obtained on two commonly-used datasets using different feature learning methods show that random sampling can provide comparable and even better performance than all of the saliency-based strategies.
The role of appearance investment in the adjustment of women with breast cancer

Objective: Appearance investment can be considered an important factor in the explanation of individual differences in adjustment to breast cancer. This study aims to analyze the role of this variable on a set of adjustment outcomes, namely, quality of life (QOL), emotional adjustment (depression and anxiety) and fear of negative evaluations. The differential role of motivational salience facet of appearance investment (MS; the individual's efforts to be or feel attractive), conceptualized as a protective factor, and of self‐evaluative salience facet (SES; the importance an individual places on physical appearance for their definition of self‐worth), conceptualized as a vulnerability factor, is explored.
The Effect of 4/3/2 Technique on the Students’ Oral Fluency at SMAN 2 Malang

This study aims to find out the difference in the oral fluency of students who are taught using 4/3/2 technique and those who are taught without using it. This study adopted true-experimental r e s e a r ch design. The experiment took place at SMAN 2 Malang. This study yields two findings related to students’ oral fluency. Firstly, 4/3/2 technique does not give significant effects on students’ oral fluency in terms of their speaking speed. Secondly, 4/3/2 technique does not give significant effects on the students’ oral fluency in terms of the students’ hesitations, repetitions, and false starts.