Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of γ-Interferon by Peripheral Blood Mononuclear Cells: An Important Diagnostic Tool for Detection of Subclinical Paratuberculosis

Peripheral blood mononuclear cells were isolated from noninfected control cows and from cows with either subclinical or clinical paratuberculosis (Johne s disease). Cells were incubated for 6, 12, 24, and 48 hours in complete medium with the following mitogens: concanavalin A (ConA), phytohemagglutinin-P (PHAP), pokeweed mitogen (PWM), and Escherichia coli lipopolysaccharide. In addition, cells were incubated for the same time periods with a Mycobacterium paratuberculosis sonicate (MpS) and live and heat-killed M. paratuberculosis at 10:1 bacteria: cell ratio. After incubation, cell-free supernatants were analyzed for y-interferon (γ-IFN) production. Cells from subclinical cows produced significantly higher levels of γ-IFN than did cells from clinical animals after stimulation with mitogens ConA, PHAP, and PWM. Levels of γ-IFN produced by noninfected control animals generally followed the pattern of those of subclinical animals. After incubation with MpS, significantly greater quantities of γ-IFN were produced by cells isolated from subclinical animals than by cells from clinical cows and noninfected controls. Stimulation of cells with heat-killed or live M. paratuberculosis evoked a similar response. This study indicates that γ-IFN production by peripheral blood mononuclear cells in response to M. paratuberculosis antigen may be an important diagnostic tool for the detection of paratuberculosis in subclinically affected animals.
Investigating cache energy and latency break-even points in high performance processors

In this work we study how cache complexity impacts energy and performance in high performance processors. Moreover, we estimate cache energy budget for two high performance processors. We calculate energy and latency break-even points for realistic and ideal cache organizations for different applications. We show that design efforts made to reduce cache miss rate are only justifiable from the energy and performance point of view only if the associated latency and energy overhead remain below the calculated break-even points. Furthermore, we show that, for the processors and applications studied here, the instruction cache has a lower latency break-even point compared to the data cache. However, investing energy in the data cache is likely to result in better energy efficiency compared to the instruction cache. We also study alternative cache configurations for different processors and investigate if such alternatives would improve energy efficiency.
Operating System Extensions for the Teradata Parallel VLDB

This paper describes the new architecture for supporting the Teradata commercial VLDB on several new operating environments. We start with an overview of the Teradata database software architecture, specifically the Parallel Database Extensions (PDE) that serve as a layer between the NCR Unix OS and the database software. We then describe the challenges of implementing an Open PDE for several new platforms, (Microsoft Windows 2000, Linux, HP-UX, and Microsoft Windows XP). Finally we show some performance data to compare the original NCR Unix version with the new Open Version of PDE for Teradata using published one-terabyte TPC-R data.
Extremely Rare Interbreeding Events Can Explain Neanderthal DNA in Living Humans

Considering the recent experimental discovery of Green et al that present-day non-Africans have 1 to of their nuclear DNA of Neanderthal origin, we propose here a model which is able to quantify the genetic interbreeding between two subpopulations with equal fitness, living in the same geographic region. The model consists of a solvable system of deterministic ordinary differential equations containing as a stochastic ingredient a realization of the neutral Wright-Fisher process. By simulating the stochastic part of the model we are able to apply it to the interbreeding ofthe African ancestors of Eurasians and Middle Eastern Neanderthal subpopulations and estimate the only parameter of the model, which is the number of individuals per generation exchanged between subpopulations. Our results indicate that the amount of Neanderthal DNA in living non-Africans can be explained with maximum probability by the exchange of a single pair of individuals between the subpopulations at each 77 generations, but larger exchange frequencies are also allowed with sizeable probability. The results are compatible with a long coexistence time of 130,000 years, a total interbreeding population of order individuals, and with all living humans being descendants of Africans both for mitochondrial DNA and Y chromosome.
Sympathetic interfaces: using a plush toy to direct synthetic characters

We introduce the concept of a sympathetic inter$ace forcontrolling an animated synthetic character in a 3D virtualenvironment. A plush doll embedded with wireless sensors is used tomanipulate the virtual character in an iconic and intentionalmanner. The interface extends from the novel physical input devicethrough interpretation of sensor data to the behavioral brain ofthe virtual character. We discuss the design of the interface andfocus on its latest instantiation in the Swamped! exhibit atSIGGRAPH 98. We also present what we learned from hundreds ofcasual users, who ranged from young children to adults.
Associations between Resident Perceptions of the Local Residential Environment and Metabolic Syndrome

A substantial body of research has arisen concerning the relationships between objective residential area features, particularly area-level socioeconomic status and cardiometabolic outcomes. Little research has explored residents' perceptions of such features and how these might relate to cardiometabolic outcomes. Perceptions of environments are influenced by individual and societal factors, and may not correspond to objective reality. Understanding relations between environmental perceptions and health is important for the development of environment interventions. This study evaluated associations between perceptions of local built and social environmental attributes and metabolic syndrome, and tested whether walking behaviour mediated these associations. Individual-level data were drawn from a population-based biomedical cohort study of adults in Adelaide, South Australia (North West Adelaide Health Study). Participants' local-area perceptions were analysed in cross-sectional associations with metabolic syndrome using multilevel regression models (n = 1, 324). A nonparametric bootstrapping procedure evaluated whether walking mediated these associations. Metabolic syndrome was negatively associated with greater local land-use mix, positive aesthetics, and greater infrastructure for walking, and was positively associated with greater perceived crime and barriers to walking. Walking partially mediated associations between metabolic syndrome and perceived environmental features. Initiatives targeting residents' perceptions of local areas may enhance the utility of environmental interventions to improve population health.
Island invasives : eradication and management : proceedings of the International Conference on Island Invasives

The papers and abstracts in this volume are the outcome of the conference on Island Invasives: Eradication and Management, held at Tamaki Campus, University of Auckland, New Zealand. This conference had "islands" and "eradication of invasive species" as the focus, with emphasis on the work done and results or learning achieved. The conference endeavoured to cover the full breadth of this work by breaking the subject down to: gaining political, community, financial and physical support; eradication techniques tested and used; the immediate results of eradication operations; the longer-term outcomes as seen in the biota of the island and among communities involved; and biosecurity measures for such islands from planning to implementation.
UAVs for Hydrologic Scopes: Application of a Low-Cost UAV to Estimate Surface Water Velocity by Using Three Different Image-Based Methods

Stream velocity and flow are very important parameters that must be measured accurately to develop effective water resource management plans. There are various methods and tools to measure the velocity but, nowadays, image-based methods are a promising alternative that does not require physical contact with the water body. The current study describes the application of a low cost unmanned aerial vehicle that was selected in order to capture a video over a specific reach of Aggitis River in Greece. The captured frames were analyzed by three different software (PIVlab, PTVlab, and KU-STIV) in order to estimate accurately the surface water velocity. These three software also represent three different image-based methodologies. Although there are differences among these three methods, the analysis produced similar trends for all. The velocity ranged between 0.02 and 3.98 m/s for PIVlab, 0.12 and 3.44 m/s for PTVlab, and 0.04 and 3.99 m/s for KU-STIV software. There were parts, especially in the existing vegetation, where differences were observed. Further applications will be examined in the same or different reaches, to study the parameters affecting the analysis. Finally, the image-based methods will be coupled with verification measurements by a current meter to produce more rigorous results.
Content-based social image retrieval with context regularization

The retrieval and recommendation of social media have provided an immense opportunity to exploit the collective behavior of community users through linked multi-modal data, such as images and tags, where tags provide context information, and images represent visual content. The stability of content information is more reliable than user contributed context information, which was ignored by many existing methods. In this paper, through discovering the latent feature space between visual features and context, we propose a novel approach for social image retrieval by imposing context regularization terms to constraint visual features. The method can effectively reflect the interior visual structure for social image representation. Experimental results on the NUS-WIDEOBJECT dataset demonstrate that the proposed approach obtains competitive performance compared with state-of-the-art methods.
Exploitation of Multifarious Abiotic Stresses, Antagonistic Activity and Plant Growth Promoting Attributes of Bacillus amyloliquefaciens AH53 for Sustainable Agriculture Production

In Indian economy, agriculture is the main backbone, which either directly or indirectly provides livelihood to approximately 70% of the country population. Therefore growth in the agricultural sector is essential for the growth and development of the country (Nerker et al., 2013). However, due to global climatic changes, environment typically meets a large number of single and combination of abiotic and biotic stresses, which severely Due to climate change, abiotic and biotic stresses like soil salinity, drought, pH, high temperature and plant fungal diseases are major threat for agriculture production and which reduces the growing demand of food of the population. To cope the adverse effect of such stresses, use of wide variety of synthetic chemical fertilizers cause serious hazardous effects on environment, soil, water and human health. Use of microorganisms as a bioinoculants is a new green eco-friendly technology for sustainable agriculture production and can lessen the effect of these stresses. With this respect in the present study a dominant bacterial strain AH53 was isolated from barren agriculture soil of Uttar Pradesh, India for exploiting its unique plant growth promotion properties, tolerance to abiotic stresses, as well as antifungal activities against the fungal pathogens. The results of different level of abiotic stresses tolerance showed that strain AH53 was able to grow up to 14% NaCl, 30% PEG, between 20 to 50°C temperature and 5–9 pH. Further dual culture assay revealed that strain AH53 significantly inhibited mycelial growth of Sclerotium rolfsii and Fusarium avenaceum with the inhibition rate of 86.59 and 85.15% respectively. The different mode of action for abiotic stresses tolerance and biocontrol activity of the strain AH53 was confirmed by production of multiple plant growth promoting and biocontrol determinants like production of indole acetic acid (125.24 ug/ml), siderophore, HCN, ACC deaminase, solubilization of phosphate – zinc, production of hydrolytic enzymes and PCR amplification of antimicrobial peptides genes. The 16S rRNA gene sequencing and phylogenetic analysis identified the strain as Bacillus amyloliquefaciens. The results provide evidence that strain AH53 may contribute to its potential activity as mitigation of abiotic stresses and biological control of plants disease to enhancement of sustainable agriculture production under different stressful condition. K e y w o r d s
Palm oil plantation area clusterization for monitoring

This paper discusses the use of the clusterization to group palm trees in plantation areas using three categories, i.e. healthy, unhealthy, and non-plantation. Here, overhead images taken by an Unmanned Aerial Vehicle (UAV) were used to view a wider area. Images were divided into several smaller images using sliding windows and extracted using three color feature extraction techniques, i.e. 2D Wavelet Decomposition Color Energy, Principal Component Analysis, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Texture feature extraction techniques used were Local Binary Pattern, Gray Level Co-occurrence Matrix and Segmentation-based Fractal Texture Analysis. Cluster results using the different techniques were compared to determine the optimal feature. Sliding windows were first implemented, and then cropped into small images with the same size as the windows. During clusterization, the K-Means clustering method was used to divide all smaller images into groups with high degrees of similarity. Feature extraction techniques were used individually to divide areas into three categories. The ground truth of the dataset was determined in advance, and results were compared to determine recognition rate. The study shows that dimensionality reduction using t-SNE in RGB color obtained the best clusterization results with 1135 correct patches.
Common feature extraction in multi-source domains for transfer learning

In transfer learning scenarios, finding a common feature representation is crucial to tackle the problem of domain shift where the training (source domain) and test (target domain) sets have difference in their distribution. However, classical dimensionality reduction approaches such as Fisher Discriminant Analysis (FDA), are not in good yields whenever dealing with shift problem. In this paper we introduce CoMuT, a Common feature extraction in Multi-source domains for Transfer learning, that finds a common feature representation between different source and target domains. CoMuT projects the data into a latent space to reduce the drift in distributions across domains and concurrently preserves the separability between classes. CoMuT constructs the latent space in semi-supervised manner to bridge across domains and relate the different domains to each other. The projected domains have distribution similarity and classical machine learning methods can be applied on them to classify target data. Empirical results indicate that CoMuT outperforms other dimensionality reduction methods on different artificial and real datasets.
Exact Interior Reconstruction with Cone-Beam CT

Using the backprojection filtration (BPF) and filtered backprojection (FBP) approaches, respectively, we prove that with cone-beam CT the interior problem can be exactly solved by analytic continuation. The prior knowledge we assume is that a volume of interest (VOI) in an object to be reconstructed is known in a subregion of the VOI. Our derivations are based on the so-called generalized PI-segment (chord). The available projection onto convex set (POCS) algorithm and singular value decomposition (SVD) method can be applied to perform the exact interior reconstruction. These results have many implications in the CT field and can be extended to other tomographic modalities, such as SPECT/PET, MRI.
Multiscale Entropy Study of Medical Laser Speckle Contrast Images

Laser speckle contrast imaging (LSCI) is a noninvasive full-field optical imaging technique that gives a 2-D microcirculatory blood flow map of tissue. Due to novelty of commercial laser speckle contrast imagers, image processing of LSCI data is new. By opposition, the numerous signal processing works of laser Doppler flowmetry (LDF) data-that give a 1-D view of microvascular blood flow-have led to interesting physiological information. Recently, analysis of multiscale entropy (MSE) of LDF signals has been proposed. A nonmonotonic evolution of MSE with two distinctive scales-probably dominated by the cardiac activity-has been reported. We herein analyze MSE of LSCI data. We compare LSCI results with the ones of LDF signals obtained during the same experiment. We show that when time evolution of LSCI single pixels is studied, MSE presents a monotonic decreasing pattern, similar to the one of Gaussian white noises. By opposition, when the mean of LSCI pixel values is computed in a region of interest (ROI) and followed with time, MSE pattern becomes close to the one of LDF data, for ROI large enough. LSCI is gaining increased interest for blood flow monitoring. The physiological implications of our results require future study.
Equations for the soil-water characteristic curve

The soil-water characteristic curve can be used to estimate various parameters used to describe unsaturated soil behaviour. A general equation for the soil-water characteristic curve is proposed. A nonlinear, least-squares computer program is used to determine the best-fit parameters for experimental data presented in the literature. The equation is based on the assumption that the shape of the soil-water characteristic curve is dependent upon the pore-size distribution of the soil (i.e., the desaturation is a function of the pore-size distribution). The equation has the form of an integrated frequency distribution curve. The equation provides a good fit for sand, silt, and clay soils over the entire suction range from 0 to 106 kPa. Key words : soil-water characteristic curve, pore-size distribution, nonlinear curve fitting, soil suction, water content.
Learning DNF over the uniform distribution using a quantum example oracle

We generalize the notion of probably approximately correct (PAC) learning from an example oracle to a notion of efficient learning on a quantum computer using a quantum example oracle. This quantum example oracle is a natural extension of the traditional PAC example oracle, and it immediately follows that all PAC-learnable function classes are learnable in the quantum model. Furthermore, we obtain positive quantum learning results for classes that are not known to be PAC learnable. Specifically, we show that disjunctive normal form (DNF) is efficiently learnable with respect to the uniform distribution by a quantum algorithm using a quantum example oracle. While it was already known that DNF is uniform-learnable using a membership oracle, we prove that a quantum example oracle with respect to uniform is less powerful than a membership oracle.
Robust DFT with high breakdown point for complex-valued impulse noise environment

Modification of the robust discrete Fourier transform (DFT) is proposed in order to achieve a high breakdown point for signals corrupted by complex-valued impulse noise with independent real and imaginary parts. Obtained results are compared with existing robust DFT forms. In addition, an adaptive procedure for selection of the modified robust DFT form is developed.
Computed tomography interobserver agreement in the assessment of aneurysmal subarachnoid hemorrhage and predictors for clinical outcome

Background The severity of aneurysmal subarachnoid hemorrhage (SAH) is often assessed by the clinical state of the patient on presentation, but radiological evaluation of the extent of hemorrhage has rarely been examined in the literature. Several CT scan based grading systems exist yet only a few studies have investigated interobserver agreement. We evaluated five radiological grading systems and assessed their clinical value for early prognostication. Methodology This was a retrospective study of patients diagnosed with aneurysmal SAH with a CT scan performed within 72 hours of symptom onset. Four independent observers, blinded to patient outcome, evaluated each scan using the five grading systems. A separate assessor determined 6 month outcome from clinical records. The primary outcome was interobserver agreement for each grading system using the Fleiss κ statistic. The secondary endpoint was the 6 month modified Rankin Scale score, with poor outcome defined as a score of 4–6. Results 165 patients with a mean age of 59 years were assessed. Interobserver agreement for the Fisher, modified Fisher, Claassen, Barrow Neurological Institute, and Hijdra grading systems were as follows: k=0.53 (moderate), k=0.42 (moderate), k=0.38 (mild), k=0.20 (poor), and k=0.66 (good), respectively. The only independent clinical risk factor for poor outcome was a World Federation of Neurological Surgeons (WFNS) grade of 4 or 5 (adjusted OR 6.55; p<0.05). After adjusting for confounders, Fisher grade 4 (adjusted OR 17.84), modified Fisher grade 4 (adjusted OR 5.65), and Hijdra grade 3 (adjusted OR 3.34) were associated with poor outcome. Receiver operator characteristic analysis revealed that the Hijdra grading system (area under the curve=0.76) was more predictive of outcome compared with the Fisher and modified Fisher systems. A Hijdra cut-off score of 22 was associated with poor outcome (adjusted OR 5.92). Conclusions The Hijdra grading system had the best interobserver agreement and was a better independent early predictor for 6 month clinical outcome than the other systems. A Hijdra score ≥22 was associated with poor outcome.