Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Haplotypes of CaSR Gene Sequence Variants and Their Associations with Growth Traits in Cattle

ABSTRACT The calcium-sensing receptor (CaSR) is a Class C G-protein coupled receptor that regulates food intake and assimilation. However, studies on the relationship between CaSR gene and growth traits in cattle are deficient. The aim of this study was to examine the association of the CaSR polymorphism with growth traits in cattle breeds. Four novel single nucleotide polymorphisms (SNPs) and one previously reported SNP (NC_007299.5: g.67630865T>C, 67638409G>C, 67660395G>C, 67661546C>G, and 67661892A>C) were identified in the bovine CaSR gene using DNA sequencing and PCR-SSCP methods in 520 individuals from three representative breeds. The three SNP P4_2, P7_1, and P7_4 in LX, QC, and JX cattle populations belonged to intermediate genetic diversity (0.25 < PIC < 0.5). In addition, we evaluated the haplotype frequency and linkage disequilibrium coefficient of five sequence variants in the three cattle breeds. LD and haplotype structure of CaSR were different between breeds. LD analysis showed that the P4_2 and P7_4 loci were in complete LD in JX cattle population (r2 = 0.99 and D′ = 1). Only 11 haplotypes were listed except for those with a frequency of <0.03. Hap1 (-TGGGC-) had the highest haplotype frequencies in LX (27.30%), Hap6(-TGGCC-) had the highest haplotype frequencies in QC (21.70%) and JX (32.30%). Association analysis indicated that P2, P4_2, and P7_4 loci were all significantly associated with growth traits and combined genotype TTGCGC was highly significantly associated with Chest circumference and body weight than the other genotype in JX cattle population. The results of this study suggest that the CaSR gene possibly is a strong candidate gene that affects growth traits in the Chinese cattle breeding program.
Tracking multiple neurons on worm images

We are interested in establishing the correspondence between neuron activity and body curvature during various movements of C. Elegans worms. Given long sequences of images, specifically recorded to glow when the neuron is active, it is required to track all identifiable neurons in each frame. The characteristics of the neuron data, e.g., the uninformative nature of neuron appearance and the sequential ordering of neurons, renders standard single and multi-object tracking methods either ineffective or unnecessary for our task. In this paper, we propose a multi-target tracking algorithm that correctly assigns each neuron to one of several candidate locations in the next frame preserving shape constraint. The results demonstrate how the proposed method can robustly track more neurons than several existing methods in long sequences of images.
Phenotypic Characterization of Osteoarthritic Osteocytes from the Sclerotic Zones: A Possible Pathological Role in Subchondral Bone Sclerosis

Subchondral bone sclerosis is a well-recognised manifestation of osteoarthritis (OA). The osteocyte cell network is now considered to be central to the regulation of bone homeostasis; however, it is not known whether the integrity of the osteocyte cell network is altered in OA patients. The aim of this study was to investigate OA osteocyte phenotypic changes and its potential role in OA subchondral bone pathogenesis. The morphological and phenotypic changes of osteocytes in OA samples were investigated by micro-CT, SEM, histology, immunohistochemistry, TRAP staining, apoptosis assay and real-time PCR studies. We demonstrated that in OA subchondral bone, the osteocyte morphology was altered showing rough and rounded cell body with fewer and disorganized dendrites compared with the osteocytes in control samples. OA osteocyte also showed dysregulated expression of osteocyte markers, apoptosis, and degradative enzymes, indicating that the phenotypical changes in OA osteocytes were accompanied with OA subchondral bone remodelling (increased osteoblast and osteoclast activity) and increased bone volume with altered mineral content. Significant alteration of osteocytes identified in OA samples indicates a potential regulatory role of osteocytes in subchondral bone remodelling and mineral metabolism during OA pathogenesis.
Power-Efficient Distributed Estimation in Hybrid MAC Wireless Sensor Networks

In this paper, the distributed estimation of a deterministic scalar source by power-constrained wireless sensor networks with a fusion center is investigated over a hybrid multiple access channel. Specifically, the maximum likelihood estimation is adopted, and the corresponding optimal and suboptimal schemes are developed to allocate sensor powers under a total power constraint. Particularly, a closed-form expression for sensor powers is obtained for suboptimal power allocation and a two-step procedure is proposed to solve the optimal power allocation problem numerically. It is analytically shown that the suboptimal power allocation scheme can offer asymptotically the same mean squared error performance as the optimal power allocation scheme when the number of sensors transmitting through the same coherent channel increases to infinity.
NormalShop: Modeling surface mesostructure

—Normals 1 have been used in geometry acquisition and rendering for years. However, modeling with normals is limited because of the lack of formally deﬁned operations. We present surface normal operations built on two key ingredients. First, a separation of models in two levels, while the base surface is represented by positions in a mesh, the details are only represented through normals in a parametric space. We edit the detail normals, while the base surface remains unchanged. In this way, we do not require a reconstruction step. Second, our editing operations are performed in an orthogonal projection. Besides being more intuitive for the user, normals in this mapping are in fact an RGBN image. This lets us deﬁne normal operations including combination, sketching features, ﬁltering, warping and texture synthesis. Since we build custom orthogonal charts for operations, processing is not restricted to the original charts.
Working memory

Working memory refers to how we keep track of what we are doing moment to moment throughout our waking lives. It allows us to remember what we have just done, focus on what we are doing now, to solve problems, be creative, think about what we will be doing in the next few seconds, and continually to update in our mind changes around us throughout the day. This book brings together in one volume, state-of-the-science chapters written by some of the most productive and well-known working memory researchers worldwide. Chapters cover leading-edge research on working memory, using behavioural experimental techniques, neuroimaging, computational modelling, development across the healthy human lifespan, and studies of neurodegenerative disease and focal brain damage. A unique feature of the book is that each chapter starts with answers to a set of common questions for all authors. This allows readers very rapidly to compare key differences in theoretical assumptions and approaches to working memory across chapters, and to understand the theoretical context before going on to read each chapter in detail. All authors also have been asked to consider evidence that is not consistent with their theoretical assumptions. It is very common for authors to ignore contradictory evidence. This approach has led to new interpretations and new hypotheses for future research to greatly enhance our understanding of this crucial human ability.
Parametric Process Model Inference

Legacy applications can be difficult and time-consuming to understand and update due to the lack of modern abstraction mechanisms in legacy languages, as well as the gradual deterioration of code due to repeated maintenance activities. We present an approach for reverse engineering process model abstractions from legacy code. Such a process model can provide a quick initial understanding of an application, and can be a useful starting point for further program exploration. Our approach takes as input a user specification of interesting events, and creates a representation (i.e., a process model) that concisely depicts the occurrences of the events and the possible control-flow among them. The key features of our approach are the use of a logical data model of the program for specifying the events, and graph-projection techniques for creating the process model.
Bit error rate analysis of cooperative beamforming for transmitting individual data streams

Cooperative beamforming (CB) has been proposed as a special case of coordinated multi-point techniques in wireless communications. In wireless sensor networks, CB can enable low power communication by allowing a collection of sensor nodes to transmit data simultaneously to a distant fusion center in one hop. Besides the traditional CB approach where all nodes need to share and transmit the same data, a more recent technique allows each node to transmit its own data while still achieving the benefits of cooperation. However, the intricacies of varying beamforming gains in the direct sequence spread spectrum with binary frequency shift keying multiple access scheme used in this context need to be taken into account when evaluating the performance of this beamforming technique. In this paper, we take the first step towards a more comprehensive understanding of this individual-data CB technique by proposing a best suited decoding scheme and analyzing its bit error rate (BER) performance over an additive white Gaussian noise channel. Through analytical expressions and simulation results BER curves are drawn and the achieved performance improvement offered by the CB gain is quantified.
Learning to Automatically Discover Meronyms

We present a system for automatically discovering meronyms (noun pairs in a part-whole relationship) from text corpora. More precisely, our system begins by parsing and extracting dependency paths similar to (but not the same as) those used by (Snow et al., 2004). For each noun pair we calculate an empirical distribution over dependency relations, which are then used as features of a Support Vector Machine classi er. Noun pairs are labeled as meronyms if there exists a path traversing only meronym and hypernym links between the nouns. Since the method of labeling training examples treats sentences as bags of words, our training examples are extremely noisy. However, we are able to nd a classi er that performs better than similar previous work.
Attacking , Repairing , and Verifying SecVisor : A Retrospective on the Security of a Hypervisor

SecVisor is a hypervisor designed to guarantee that only code approved by the user of a system executes at the privilege level of the OS kernel [17]. We employ a model checker to verify the design properties of SecVisor and identify two design-level attacks that violate SecVisor’s security requirements. Despite SecVisor’s narrow interface and tiny code size, our attacks were overlooked in both SecVisor’s design and implementation. Our attacks exploit weaknesses in SecVisor’s memory protections. We demonstrate that our attacks are realistic by crafting exploits for an implementation of SecVisor and successfully performing two attacks against a SecVisorprotected Linux kernel. To repair SecVisor, we design and implement an efficient and secure memory protection scheme. We formally verify the security of our scheme. We demonstrate that the performance impact of our proposed defense is negligible and that our exploits are no longer effective against the repaired implementation. Based on this case study, we identify facets of secure system design that aid the verification process.
Hypoxic Viable Tissue in Human Chronic Cerebral Ischemia Because of Unilateral Major Cerebral Artery Steno-Occlusive Disease

Background and Purpose— Positron emission tomography (PET) with radiolabeled 2-nitroimidazoles directly detects hypoxic but viable tissue present in an acute ischemic area in the human brain. This study using PET with 1-(2-18F-fluoro-1-[hydroxymethyl]ethoxy) methyl-2-nitroimidazole (18F-FRP170) aimed to determine whether tissue with an abnormally elevated uptake of 18F-FRP170 exists in human chronic cerebral ischemia because of unilateral atherosclerotic major cerebral artery steno-occlusive disease. Methods— 18F-FRP170 PET was performed, and cerebral blood flow and metabolism were assessed using 15O-gas PET in 20 healthy subjects and 52 patients. A region of interest (ROI) was automatically placed in 3 segments of the middle cerebral artery territory in both cerebral hemispheres with a 3-dimensional stereotaxic ROI template using SPM2, and each PET value was determined in each ROI. The ratio of values in the affected versus contralateral hemispheres was calculated for the 18F-FRP170 PET image. Results— A significant correlation was observed between oxygen extraction fraction and 18F-FRP170 ratios (&rgr;=0.509; P<0.0001) in a total of 156 ROIs in 52 patients. The specificity and positive-predictive value for a combination of an elevated oxygen extraction fraction and a moderately reduced cerebral oxygen metabolism for detection of an abnormally elevated 18F-FRP170 ratio (19 ROIs: 12%) were significantly greater than those for the individual categories (elevated oxygen extraction fraction, moderately reduced cerebral oxygen metabolism, or reduced cerebral blood flow). Conclusions— Tissues with abnormally elevated uptake of 18F-FRP170 exist in human chronic cerebral ischemia characterized by a combination of misery perfusion and moderately reduced oxygen metabolism because of unilateral atherosclerotic major cerebral artery steno-occlusive disease.
Incremental covering array failure characterization in large configuration spaces

The increasing complexity of configurable software systems has created a need for more intelligent sampling mechanisms to detect and characterize failure-inducing dependencies between configurations. Prior work - in idealized environments - has shown that test schedules based on a mathematical object, called a covering array, in combination with classification techniques, can meet this need. Applying this approach in practice, however, is tricky because testing time and resource availability are unpredictable, and because failure characteristics can change from release to release. With current approaches developers must set a key covering array parameter (its strength) based on estimated release times and failure characterizations. This will influence the outcome of their results. In this paper we propose a new approach that incrementally builds covering array schedules. This approach begins at a low strength, and then iteratively increases strength as resources allow. At each stage previously tested configurations are reused, thus avoiding duplication of work. With the incremental approach developers need never commit to a specific covering array strength. Instead, by using progressively stronger covering array schedules, failures due to few configuration dependencies can be found and classified as soon and as cheaply as possibly. Additionally, it eliminates the risks of committing to overly strong test schedules. We evaluate this new approach through a case study on three consecutive releases of MySQL, an open source database. Our results suggest that our approach is as good or better than previous approaches, costing less in most cases, and allowing greater flexibility in environments with unpredictable development constraints.
Edge-on semiconductor x-ray detectors - towards high-rate counting computed tomography

The main obstacle today for photon-counting x-ray computed tomography (CT) in the clinical domain is the large x-ray flux rate employed in commercial CT systems enabling ultra-low scanning times. State-of-the-art direct-conversion semiconductor detectors with dedicated readout ASICs are able to reach rates of up to 5–10 million recorded events per second and channel. The requirement coming from clinical CT would be around one billion primary events per second and square millimeter active detector surface. Decreasing the (transverse) pixel size of typically 1 mm2 for medical CT down-to about 200 μm×200 μm is effective to reduce the count rates per channel. However, for pixel sizes around and below that level, a number of physical effects like K-escape or charge sharing set in with degrading effects on image quality and spectral information content of the transmission data. A possible way to bridge the gap of about one more order of magnitude in count rate is to apply the sub-structuring of the active sensor volume not only in the directions transverse to the x-ray beam but also along the beam. In this paper we present simulations for a so-called “edge-on” detection concept in which the different sensor layers (in different depths) are read out using independent channels. The main observation reported in this paper is that already a very simple concept of data acquisition or data usage suffices to reconstruct high-quality images with a noise increase restricted to the outermost parts of the object under consideration. The count-rate problem is severe only in the primary beam and in “the first few millimeters of object”, as the event rate is exponentially damped inside the patient, drastically reducing the remaining effective count rate per channel.
Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW) model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm's projective function. We test our work on the several datasets and obtain very promising results.
Individual Motile CD4+ T Cells Can Participate in Efficient Multikilling through Conjugation to Multiple Tumor Cells

Liadi, Singh, and colleagues used Timelapse Imaging Microscopy In Nanowell Grids (TIMING) to show that CD4+ CD19-chimeric antigen receptor (CAR+) T cells participate in multikilling of tumor cells with slower kinetics of killing than CD8+CAR+ T cells, but high motility subgroups of both T-cell subsets have similar kinetics. T cells genetically modified to express a CD19-specific chimeric antigen receptor (CAR) for the investigational treatment of B-cell malignancies comprise a heterogeneous population, and their ability to persist and participate in serial killing of tumor cells is a predictor of therapeutic success. We implemented Timelapse Imaging Microscopy in Nanowell Grids (TIMING) to provide direct evidence that CD4+CAR+ T cells (CAR4 cells) can engage in multikilling via simultaneous conjugation to multiple tumor cells. Comparisons of the CAR4 cells and CD8+CAR+ T cells (CAR8 cells) demonstrate that, although CAR4 cells can participate in killing and multikilling, they do so at slower rates, likely due to the lower granzyme B content. Significantly, in both sets of T cells, a minor subpopulation of individual T cells identified by their high motility demonstrated efficient killing of single tumor cells. A comparison of the multikiller and single-killer CAR+ T cells revealed that the propensity and kinetics of T-cell apoptosis were modulated by the number of functional conjugations. T cells underwent rapid apoptosis, and at higher frequencies, when conjugated to single tumor cells in isolation, and this effect was more pronounced on CAR8 cells. Our results suggest that the ability of CAR+ T cells to participate in multikilling should be evaluated in the context of their ability to resist activation-induced cell death. We anticipate that TIMING may be used to rapidly determine the potency of T-cell populations and may facilitate the design and manufacture of next-generation CAR+ T cells with improved efficacy. Cancer Immunol Res; 3(5); 473–82. ©2015 AACR. See related commentary by June, p. 470
Tailoring the Properties of Artificially Layered Ferroelectric Superlattices

The polarization of PbTiO3/SrTiO3 superlattices is experimentally tuned from 0-60 mu C/cm(-2) and the transition temperature from room temperature to 1000 K while maintaining a perfect crystal structure and low leakage currents (see figure). A simple model based on Landau theory is developed as a guide for the straightforward production of samples with ferroelectric properties designed for particular applications.
Estimating soil seed bank characteristics in ponderosa pine forests using vegetation and forest-floor data

Soil seed banks are important for vegetation management because they contain propagules of species that may be considered desirable or undesirable for site colonization after management and disturbance events. Knowledge of seed bank size and composition before planning management activities facilitates proactive management by providing early alerts of exotic species presence and of abilities of seed banks to promote colonization by desirable species. We developed models in ponderosa pine (Pinus ponderosa) forests in northern Arizona to estimate the size and richness of mineral soil seed banks using readily observable vegetation and fores-floor characteristics. Regression models using three or fewer predictors explained 41 to 59 percent of the variance in 0- to 2-inch (0- to 5-cm) seed densities of total and native perennial seed banks. Key predictors included aboveground plant species richness/10.8 ft2 (1 m2), litter weight and thickness, and tree canopy type (open or closed). Both total and native perennial seed banks were larger and richer in plots containing: (1) species-rich understories, (2) sparse litter, and (3) tree canopy openings. A regression tree model estimated that seed bank density of native perennials is 14-fold greater if aboveground plant richness exceeds eight species/10.8 ft2, forest-floor leaf litter is < 1 inch (2.5 cm) thick, and tree canopies are open.
An optical measurement using the DNA hybridization method for specific species of bacteria detection

This paper reports a developed DNA hybridization detection method using gold-streptavidin conjugates as a reporter, the silver enhancement reaction to magnify the detection signal, and a flatbed scanner to detect the hybridization signal. There was a significant difference in grayscale between the experimental samples and the negative control after 18 min. The detection limit for a DNA sample is 8.25 ng/mL with 5 µM of probe and 10−3 µM of AuNPsstreptavidin. The probe specific tests for different DNA samples were discussed: (1) the probe specific tests for various species of bacteria, and (2) the probe specific tests between the various strains of a single species and various species of a single genus. The developed DNA hybridization method is easy, convenient, and rapid.
Ultraviolet and EELS spectra of CeO2 nanoparticles produced by laser ablation

The nanoparticles of cerium dioxide have been produced by laser ablation. The ultraviolet (UV) absorption spectra of the synthesized nanoparticles are studied. The band gap of the particles and the effect exerted on it by laser radiation intensity during the synthesis of nanoparticles are determined from the analysis of the spectra. Electron energy loss spectra (EELS) of the nanoparticles are investigated on a transmission electron microscope. Comparative analysis of the UV and EELS spectra has been carried out.