Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Architecture of Maize Kernel Composition in the Nested Association Mapping and Inbred Association Panels1[W]

The maize (Zea mays) kernel plays a critical role in feeding humans and livestock around the world and in a wide array of industrial applications. An understanding of the regulation of kernel starch, protein, and oil is needed in order to manipulate composition to meet future needs. We conducted joint-linkage quantitative trait locus mapping and genome-wide association studies (GWAS) for kernel starch, protein, and oil in the maize nested association mapping population, composed of 25 recombinant inbred line families derived from diverse inbred lines. Joint-linkage mapping revealed that the genetic architecture of kernel composition traits is controlled by 21–26 quantitative trait loci. Numerous GWAS associations were detected, including several oil and starch associations in acyl-CoA:diacylglycerol acyltransferase1-2, a gene that regulates oil composition and quantity. Results from nested association mapping were verified in a 282 inbred association panel using both GWAS and candidate gene association approaches. We identified many beneficial alleles that will be useful for improving kernel starch, protein, and oil content.
Physical changes during Z-track movement in Sco X-1 on the flaring branch

We present results of a detailed study of X-ray flaring in the Z-track source Sco X-1 in a highly super-Eddington state made using high quality Rossi-XTE data from the PCA and HEXTE instruments. The emission model successfully used to explain the dipping LMXB, and other classes of LMXB in recent years, was applied to study the physical evolution along the Z-track which remains a major problem. This model consists of blackbody emission from the neutron star plus Comptonized emission from an extended accretion disk corona. As found in earlier work, major changes take place in the neutron star blackbody emission with kT increasing in flaring, and the blackbody radius RBB increasing substantially to a maximum value of 9.4 ± 0.6 km, consistent with the radius of the neutron star, after which RBB decreases. Thus this result is a measurement of neutron star radius. The behaviour of Sco X-1 in flaring is compared with our previous results for the strong flaring that takes place in the bright dipping, flaring LMXB X 1624-490. Remarkably, during movement along the Normal Branch towards the apex with the Flaring Branch, the luminosities of both spectral components decrease, suggesting the possibility that u M may decrease on the Normal Branch, contrary to the widely-held view that u M increases monotonically along the Z-track. During flaring, we detect for the first time an increase of the Comptonization cut-off energy which may suggest heating of the ADC plasma by the neutron star flare. The energy of a broad Gaussian line at ∼6.4 keV does not change, but the intensity of the line increases in flaring suggesting either an increase in ADC size in flaring or the effects of irradiation by the neutron star.
Fault Tolerance in a Multi-Layered DRE System: A Case Study

Dynamic resource management is a crucial part of the infrastructure for emerging distributed real-time embedded systems, responsible for keeping mission-critical applications operating and allocating the resources necessary for them to meet their requirements. Because of this, the resource manager must be fault-tolerant, with nearly continuous operation. This paper describes our efforts to develop a fault-tolerant multi-layer dynamic resource management capability and the challenges we encountered, some due to the fault tolerance requirements we needed to meet and others due to characteristics of the resource management software. The challenges include the need for extremely rapid recovery; supporting the characteristics of component middleware, including peer-to-peer communication and multi-tiered calling semantics; supporting multiple languages; and the co-existence of replicated and non-replicated elements. Making our multi-layer dynamic resource manager fault-tolerant required simultaneously overcoming all of these challenges, presenting a significant fault tolerance research challenge.
Investigating the Interplay between Nucleoid-Associated Proteins, DNA Curvature, and CRISPR Elements Using Comparative Genomics

Many prokaryotic and eukaryotic genomes feature a characteristic periodic signal in distribution of short runs of A or T (A-tracts) phased with the DNA helical period of ∼10–11 bp. Such periodic spacing of A-tracts has been associated with intrinsic DNA curvature. In eukaryotes, this periodicity is a major component of the nucleosome positioning signal but its physiological role in prokaryotes is not clear. One hypothesis centers on possible role of intrinsic DNA bends in nucleoid compaction. We use comparative genomics to investigate possible relationship between the A-tract periodicity and nucleoid-associated proteins in prokaryotes. We found that genomes with DNA-bridging proteins tend to exhibit stronger A-tract periodicity, presumably indicative of more prevalent intrinsic DNA curvature. A weaker relationship was detected for nucleoid-associated proteins that do not form DNA bridges. We consider these results an indication that intrinsic DNA curvature acts collaboratively with DNA-bridging proteins in maintaining the compact structure of the nucleoid, and that previously observed differences among prokaryotic genomes in terms DNA curvature-related sequence periodicity may reflect differences in nucleoid organization. We subsequently investigated the relationship between A-tract periodicity and presence of CRISPR elements and we found that genomes with CRISPR tend to have stronger A-tract periodicity. This result is consistent with our earlier hypothesis that extensive A-tract periodicity could help protect the chromosome against integration of prophages, possibly due to its role in compaction of the nucleoid.
Primordial lithium abundance in catalyzed big bang nucleosynthesis

There exists a well-known problem with the {sup 7}Li+{sup 7}Be abundance predicted by standard big bang nucleosynthesis being larger than the value observed in population II stars. The catalysis of big bang nucleosynthesis by metastable, {tau}{sub X} > or approx. 10{sup 3} sec, charged particles X{sup -} is capable of suppressing the primordial {sup 7}Li+{sup 7}Be abundance and making it consistent with the observations. We show that to produce the correct abundance, this mechanism of suppression places a requirement on the initial abundance of X{sup -} at temperatures of 4x10{sup 8} K to be on the order of or larger than 0.02 per baryon, which is within the natural range of abundances in models with metastable electroweak-scale particles. The suppression of {sup 7}Li+{sup 7}Be is triggered by the formation of ({sup 7}BeX{sup -}) compound nuclei, with fast depletion of their abundances by catalyzed proton reactions, and in some models by direct capture of X{sup -} on {sup 7}Be. The combination of {sup 7}Li+{sup 7}Be and {sup 6}Li constraints favors the window of lifetimes, 1000 s < or approx. {tau}{sub X}{<=}2000 s.
On the choice of the correlation term for multi-baseline stereo-vision

We address DSM reconstruction from calibrated limited-angle aerial side-looking image sequences. We use a regularised approach which combines a multi-view pixel-wise similarity criterion and a L1-norm regularisation term. Although it gives quite good results, it has two main drawbacks: occlusions are not dealt with and the reconstruction improvement brought by addition of a new view becomes negligible beyond a certain number of views. We argue that these problems result from lacks of goodness-of-t term. We propose to modify this term in order to obtain high resolution DSMs with occlusions handling. First developed on synthetic sequence, these modications are evaluated here on a real sequence with good results.
Modeling three‐dimensional protein structures for CASP5 using the 3D‐SHOTGUN meta‐predictors

Full‐atom models were generated for all CASP5 targets by using the fully automated 3D‐SHOTGUN fold recognition meta‐predictors (Fischer D, Proteins 2003;51:434–441). The 3D‐SHOTGUN meta‐predictors assemble hybrid 3D models by combining structural information of a number of independently generated, fold recognition models. At the time CASP5 took place, the 3D‐SHOTGUN servers generated unrefined Cα‐only models. Fischer's participation in CASP had three main goals. The first was to test the value of using 3D‐SHOTGUN models as input to a refinement procedure. The second goal was to test whether human intervention could result in a better performance than that of the automated servers. The third goal was to evaluate which human procedures, not yet implemented within the 3D‐SHOTGUN servers, can be implemented in the future. For CASP5, our group's predictions applied a very simple approach using the multiple parent option of the Modeller program (Sali and Blundell, J Mol Biol 1993;234:779–815). The input to Modeller was different combinations of the unrefined 3D‐SHOTGUN models and the sequence‐template alignments used by 3D‐SHOTGUN's assembly step. Our evaluation of the accuracies of the refined versus the SHOTGUN models shows that the refined models were consistently slightly more accurate than SHOTGUN's. For a few targets, the manual use of the information from the CAFASP servers resulted in better human models. This manual intervention was particularly valuable in the identification of domains, still a difficult feature for automated servers. The CASP5 results indicate that 3D‐SHOTGUN's hybrid models can be a valuable starting point for full‐atom refinement and that the resulting refined models are, on average, more accurate than those produced by the servers. Thus, we conclude that our three goals were achieved. A preliminary automated version of the refinement procedure, named SHGUM, is now available. Proteins 2003;53:389–394. © 2003 Wiley‐Liss, Inc.
Particle swarm optimization based modeling and compensation of hysteresis of PZT micro-actuator used in high precision dual-stage servo system

Piezoelectric micro-actuator made from PZT (Lead-Zirconium-Titanium) has been a popular choice as the secondary actuator of a dual-stage actuator system. However, the advantage gained by the precision of secondary actuator is somewhat lost by the inherent hysteresis nonlinearity of PZT actuator, if not compensated. This paper proposes a new rigorous technique for modeling and compensation of the hysteresis of PZT actuator used in dual-stage actuator system, which is established by artificial intelligence based heuristic optimization technique based on particle swarm optimization. In this paper, first the model parameters of Generalized Prandtl-Ishlinskii (GPI) model are identified off-line by PSO technique and corresponding inverse GPI is obtained as the hysteresis compensator. Then in case of parameter uncertainty, PSO based online tuning method is employed to adaptively adjust the parameters of inverse GPI model. For the linear controller of dual-stage, a simple design approach is followed. Simulation results show that the proposed technique can be efficiently used for the identification of hysteresis of PZT micro-actuator and the adaptive tuning the parameters of the effectiveness of the design.
The Mindlessness and Mindfulness of Secondary Eating

Since the mid-1970s, obesity has rapidly increased among people in the U.S. Secondary eating is one factor blamed for obesity. Secondary eating is defined as eating while doing something else such as reading or watching TV. We hypothesize that lifestyle is an important moderator of the effect of secondary eating on obesity. Using data from the 2006-8 American Time Use Survey (ATUS), the results indicate that a sedentary lifestyle increases the odds of mindless secondary eating, leading to overeating and obesity.
Improved Image Fusion Algorithm for Detecting Obstacles in Forests

The harvester has been widely used in forestry operations. However the existence of obstacles in forests, such as stones, animals, human and clustered trees, may leads to safety accident and decreases the operating efficiency of the harvester. Therefore it becomes vital to show the obstacles accurately to provide guidance for the harvester. In this paper, an improved image fusion algorithm based on Contourlet transform and pulse coupled neural network (PCNN) is proposed to enhance the fused images' clarity and capture more abundant information of the reality. As for comparison, algorithms, such as wavelet transform, Principal Component Analysis (PCA) and PCNN are simulated to evaluate the proposed algorithm. Visible and infrared thermal image are captured in forest in this experiment. The experimental results demonstrate that the proposed algorithm outperform the mentioned methods by the objective criteria of Entropy, Average gradient and Standard deviation.
The Three-Dimensional Morphological Effects of Captivity

Many captive animals are fed diets that are drastically different in mechanical properties than their wild diet. Most captive pantherines are fed a nutritionally supplemented diet consisting almost entirely of ground meat. While many zoos supplement this diet with bones, the fact remains that large captive felids are fed diets that require substantially less masticatory effort than those of their wild counterparts. The osteological effects of this dietary difference have not been fully evaluated. To this end, we compared linear measurements and 3D geometric morphometric landmarks of captive and wild lions and tigers. Using Principal Component (PC) analysis of the linear measurements, not only were the sexes and species statistically distinct, but so too was the population clearly divisible in terms of captivity status. The 3D analysis supported these findings: although the most influential variable in the sample (PC1, 21.5% of the variation) separates the two species, the second most influential contributor (PC2) to the overall skull shape is driven not by the sex differences in these highly dimorphic species, but rather by their captivity status. In fact, captivity status drives nearly twice as much of the 3D variation as sexual dimorphism (14.8% vs. 8.0% for PC2 vs. PC3). Thus the shape is influenced nearly twice as much by whether the animal was captive or wild than by whether it was male or female. If a causal relationship can be demonstrated between dietary mechanical properties and morphology, people who oversee the diets of captive carnivores should consider modifying these diets to account for not only nutritional but also the mechanical properties of a carcass-based diet as well. In addition to the husbandry implications, our analyses show the ways in which captive specimens are different than their wild counterparts – findings that have implications for morphologists when considering anatomical samples.
MPOE based adaptive space-time multiuser detector for multipath CDMA channels

DS-CDMA is a popular multiple access technology for wireless communication. The performance of DS-CDMA is limited by multiple access interference and multipath distortion. Multiuser detection and space-time processing techniques are employed to improve the performance of DS-CDMA. An adaptive space-time multiuser detector based on the minimum probability of error (MPOE) criterion is proposed here for an asynchronous multipath DS-CDMA channel, with the receiver employing multiple antennas. The receiver structure is derived for gradient descent based adaptation. A blind version of the receiver is also proposed. It is seen that the MPOE receiver offers BER performance comparable to the optimal non-adaptive MMSE detector in steady state, however with much lower computational complexity and a faster convergence rate compared to other adaptive implementations of the MMSE detector (LMS, RLS).
Changing Perspective in Stereoscopic Images

Traditional image editing techniques cannot be directly used to edit stereoscopic ("3D”) media, as extra constraints are needed to ensure consistent changes are made to both left and right images. Here, we consider manipulating perspective in stereoscopic pairs. A straightforward approach based on depth recovery is unsatisfactory: Instead, we use feature correspondences between stereoscopic image pairs. Given a new, user-specified perspective, we determine correspondence constraints under this perspective and optimize a 2D warp for each image that preserves straight lines and guarantees proper stereopsis relative to the new camera. Experiments verify that our method generates new stereoscopic views that correspond well to expected projections, for a wide range of specified perspective. Various advanced camera effects, such as dolly zoom and wide angle effects, can also be readily generated for stereoscopic image pairs using our method.
sEMG Techniques to Detect and Predict Localised Muscle Fatigue

Recent advances in physiological studies have demonstrated the importance of muscle fatigue detection and prediction in various aspects of our lives, including sports, rehabilitation and ergonomics. Automating muscle fatigue detection/prediction in wearable technology has the potential to aid in many applications. However, current research has made little progress towards automating muscle fatigue detection/prediction in computational models. The work presented in this chapter supports the idea that an automated muscle fatigue detection/prediction system can be used to aid sporting performance and to avoid injury. In support of this view, a wearable system that operates based on the detection and classification of three different stages of muscle fatigue (Non-Fatigue, Transition-to-Fatigue and Fatigue) has been developed. Current research focuses on only two muscle fatigue stages (Non-Fatigue and Fatigue); with this limitation in mind, data was analysed with the aim to develop features that best extract muscle fatigue content, using both statistical models and evolutionary computations tools to help find the number of muscle fatigue stages. This enabled the development of an automatedmuscle fatigue detection system, which provides true prediction capabilities. In doing so, a third stage of fatigue was identified, the so-called Transition-to-Fatigue stage, which occurs before the onset of fatigue. By identifying this transitional fatigue stage, it is possible to predict when fatigue will occur, which provides the foundation of the automated system. To demonstrate the applicability of the Transition-to-Fatigue class, the classification performance of the two class (Non-Fatigue and Fatigue) and three class approaches (Non-Fatigue, Transition-to-Fatigue and Fatigue) were compared. This chapter will include various studies that identify the most suitable methods to apply in the real-time autonomous system. The first section of studies developed various statistical features that best distinguished between the different classes of fatigue, resulting in new combined feature extraction methods called 1D spectro and 1D spectro_std. The second section used evolutionary computation, evolving features and creating pseudo-wavelets improving current state of the art. The various features evolved in this work all produced high classification accuracy from surface electromyography (sEMG) signals emanating from the biceps brachii during both isometric and non-isometric contractions. In the third section, a method to predict the time to fatigue was established using artificial neural network classification based on the three classes of fatigue. This technique was also implemented in 9
Is Fiscal Stimulus a Good Idea?

The results in this paper, using a structural multicountry macroeconometric model, suggest that there is at most a small gain from fiscal stimulus in the form of increased transfer payments or increased tax deductions if the increased debt generated must eventually be paid back. The gain in output and employment on the way up is roughly offset by the loss in output and employment on the way down as the debt from the initial stimulus is paid off. This conclusion is robust to different assumptions about monetary policy. To the extent that there is a gain, the longer one waits to begin paying the debt back the better. Possible caveats regarding the model used are that (1) monetary policy is not powerful enough to keep the economy at full employment, (2) potential output is taken to be exogenous, (3) possible permanent effects on asset prices and animal spirits from a stimulus are not taken into account, and (4) the model does not have the feature that in really bad times the economy might collapse without a stimulus.
Polygenic Modeling with Bayesian Sparse Linear Mixed Models

Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches make very different assumptions, so are expected to perform well in different situations. However, in practice, for a given dataset one typically does not know which assumptions will be more accurate. Motivated by this, we consider a hybrid of the two, which we refer to as a “Bayesian sparse linear mixed model” (BSLMM) that includes both these models as special cases. We address several key computational and statistical issues that arise when applying BSLMM, including appropriate prior specification for the hyper-parameters and a novel Markov chain Monte Carlo algorithm for posterior inference. We apply BSLMM and compare it with other methods for two polygenic modeling applications: estimating the proportion of variance in phenotypes explained (PVE) by available genotypes, and phenotype (or breeding value) prediction. For PVE estimation, we demonstrate that BSLMM combines the advantages of both standard LMMs and sparse regression modeling. For phenotype prediction it considerably outperforms either of the other two methods, as well as several other large-scale regression methods previously suggested for this problem. Software implementing our method is freely available from http://stephenslab.uchicago. edu/software.html.
Multilevel codes: Theoretical concepts and practical design rules

This paper deals with 2/sup l/-ary transmission using multilevel coding (MLC) and multistage decoding (MSD). The known result that MLC and MSD suffice to approach capacity if the rates at each level are appropriately chosen is reviewed. Using multiuser information theory, it is shown that there is a large space of rate combinations such that MLC and full maximum-likelihood decoding (MLD) can approach capacity. It is noted that multilevel codes designed according to the traditional balanced distance rule tend to fall in the latter category and, therefore, require the huge complexity of MLD. The capacity rule, the balanced distances rules, and two other rules based on the random coding exponent and cutoff rate are compared and contrasted for practical design. Simulation results using multilevel binary turbo codes show that capacity can in fact be closely approached at high bandwidth efficiencies. Moreover, topics relevant in practical applications such as signal set labeling, dimensionality of the constituent constellation, and hard-decision decoding are emphasized. Bit interleaved coded modulation, proposed by Caire et al. (see ibid., vol.44, p.927-46, 1998), is reviewed in the context of MLC. Finally, the combination of signal shaping and coding is discussed. Significant shaping gains are achievable in practice only if these design rules are taken into account.