Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of Quantal Dose-Response Characteristics in Phenotypic Assays using Supervised Classification

We have designed and implemented a fully automatic, high-throughput screen against the causative parasite of the devastating illness, schistosomiasis, using computer vision and machine learning. The computer vision component segments (individually recognizes and delineates) schistosomula in brightfield micrographs, including touching and partially overlapping parasites. A learning model employing support vector machines to identify schistosomula which differ significantly from controls. Classification is performed in a high-dimensional feature space, the dimensions of which correspond to measurements of appearance, shape and texture. Because variation between different populations of schistosomula unavoidably creates different baselines for different experiments, classification is conducted in two stages: one in which putatively “normal” parasites are identified within each control image and used to derive an estimated control centroid, and one in which all parasites are classified as “normal” or “degenerate” on the basis of tuples composed of a given parasite’s feature vector and corresponding control centroid. Finally, a continuous measurement of the phenotypic response to a particular experimental condition (such as the concentration of a certain drug) is produced using the notion of quantal response, or the proportion of individuals which differ from controls in a particular subpopulation. The learning model is demonstrated to be highly effective, and for test data has an accuracy of 0.89. Dose-response curves produced for four compounds (fluvastatin, niclosamide, praziquantel and simvastatin) with the automated method are also tightly correlated to those produced by human experts, with high statistical significance. Correlation values are > 0.97 in all cases with p-values << 10 -3 . _____________________________________________________________________
Minimizing Overhead Computation Time for Grid Scheduling System Based on Partitioned Grid Information Service

Grids systems are enormous environments that allow to users to share their resource and collaborate for executing of consumer’s job. Recently, the need for interoperability among different grid systems and using online updated grid resource information centers for both market-base grids and non-economic grids has become increased. In this paper we specifically focus on online updating resource information centers to use by local schedulers based on assumed hierarchical model. Moreover, we used knowledge extraction methods to provide some helpful predictions to classifying grid nodes based on job’s features. A positive point of this research is that schedulers don’t waste extra time for getting up-to-date information of grid nodes. The experimental result show the advantages of our approach compared to other conservative methods, especially due to its ability to predict the behavior of nodes based on comprehensive data tables on each node.
Matching images with different resolutions

In this paper we address the problem of matching two images with two different resolutions: a high-resolution image and a low-resolution one. On the premise that changes in resolution act as a smoothing equivalent to changes in scale, a scale-space representation of the high-resolution image is produced. Hence the one-to-one classical image matching paradigm becomes one-to-many because the low-resolution image is compared with all the scale-space representations of the high-resolution one. Key to the success of such a process is the proper representation of the features to be matched in scale-space. We show how to extract interest points at variable scales and we devise a method allowing the comparison of two images at two different resolutions. The method comprises the use of photometric- and rotation-invariant descriptors, a geometric model mapping the high-resolution image onto a low-resolution image region, and an image matching strategy based on the robust estimation of this geometric model. Extensive experiments show that our matching method can be used for scale changes up to a factor 6.
normalizes after treatment with escitalopram Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated depressed patients

Major Depressive Disorder (MDD) involves deficits in the reward system. While neuroimaging studies have focused on affective stimulus processing, few investigations have directly addressed deficits in the anticipation of incentives. We examined neural responses during gain and loss anticipation in patients with MDD before and after treatment with a selective serotonin reuptake inhibitor (SSRI). Fifteen adults with MDD and 15 healthy participants, matched for age, verbal IQ and smoking habits, were investigated in a functional magnetic resonance imaging (fMRI) study using a monetary incentive delay task. Patients were scanned drug-free and after 6 weeks of open-label treatment with escitalopram; controls were scanned twice at corresponding time points. We compared the blood oxygenation level dependent (BOLD) response during the anticipation of gain and loss with a neutral condition. A repeated measures ANOVA was calculated to identify effects of group (MDD vs. controls), time (first vs. second scan) and group-by-time interaction. Severity of depression was measured with the Hamilton Rating Scale of Depression and the Beck Depression Inventory. MDD patients showed significantly less ventral striatal activation during anticipation of gain and loss compared with controls before, but not after, treatment. There was a significant group-by-time interaction during anticipation of loss in the left ventral striatum due to a signal increase in patients after treatment. Ventral striatal hyporesponsiveness was associated with the severity of depression and in particular anhedonic symptoms. These findings suggest that MDD patients show ventral striatal hyporesponsiveness during incentive cue processing, which normalizes after successful treatment.
DENSITY GRADIENT SEPARATION OF SARCOTUBULAR VESICLES AND OTHER PARTICULATE CONSTITUENTS OF RABBIT MUSCLE

Separation of particulate matter in rabbit muscle extracts by differential centrifugation leads, in first approximation, to the isolation of fraction I (15,000 to 41,000 g) and fraction II (41,000 to 150,000 g). The former consists mainly of sarcotubular material, actively transporting calcium ions, and displaying relaxation factor activity. The latter is heterogeneous, shows little calcium accumulation, and contains factors both inhibiting and activating myofibrillar ATPase. Fraction I is resolved by density gradient centrifugation into 2 main subfractions. The lighter one represents sarcotubular material in the best state of preservation, with biochemical activities stable for weeks in the cold. The heavier one may consist of the same material in a less well preserved form. Upon aging, it develops an activating activity toward myofibrillar ATPase, when the relaxing effect has declined. Fraction II is resolved by density gradient centrifugation into 3 or more fractions, with some variability. Relaxing activity in terms of inhibition of myofibrillar ATPase predominates among the lighter subfractions, increase of ATPase among the heavier. The intrinsic ATPase of fraction II is activated by calcium ions, but there is little or no bulk accumulation of calcium oxalate. Nevertheless, its limited calcium uptake seems to suffice to explain its relaxing activity. The particulate material contains mucopolysaccharide and lipid. Most of the lipid in fraction I is phospholipid; in fraction II this is less than half, if calculated as lecithin. The unfractionated material contains an adenylcyclase. There is no acetylcholine esterase.
Noise-resistant quantum key distribution protocol

We present the scheme of compatible quantum information analysis of the quantum key distribution (QKD) protocols, which give answers to the following questions: is it possible to improve the quantum bit error rate (QBER) of the 6-state protocol by employing more states, up to infinity, and can we essentially improve the QBER if the multidimensional Hilbert space with dimensionality more than 3 is used? Also, a novel quantum key distribution (QKD) protocol, based on all unselected states of a quantum system, which set the alphabet with continuous set of letters, is proposed. Employing all states of the Hilbert space leads to the maximal quantum uncertainty of transmitted states and therefore an eavesdropper receives the minimal amount of information. For the case of two-dimensional Hilbert space, our protocol allows secure transmission at the error rate higher than that one for the BB84-protocol and comparable with the characteristics of the best known QKD-protocols. However, with increasing the dimensionality of the Hilbert space the critical error rate for our protocol increases and in the limit of infinite-dimensional space the protocol becomes non-threshold.
Efficient whole-genome association mapping using local phylogenies for unphased genotype data

MOTIVATION Recent advances in genotyping technology has made data acquisition for whole-genome association study cost effective, and a current active area of research is developing efficient methods to analyze such large-scale datasets. Most sophisticated association mapping methods that are currently available take phased haplotype data as input. However, phase information is not readily available from sequencing methods and inferring the phase via computational approaches is time-consuming, taking days to phase a single chromosome. RESULTS In this article, we devise an efficient method for scanning unphased whole-genome data for association. Our approach combines a recently found linear-time algorithm for phasing genotypes on trees with a recently proposed tree-based method for association mapping. From unphased genotype data, our algorithm builds local phylogenies along the genome, and scores each tree according to the clustering of cases and controls. We assess the performance of our new method on both simulated and real biological datasets. AVAILABILITY The software described in this article is available at http://www.daimi. au.dk/~mailund/Blossoc and distributed under the GNU General Public License.
Interactive Source Coding for Function Computation in Collocated Networks

A problem of interactive function computation in a collocated network is studied in a distributed block source coding framework. With the goal of computing samples of a desired function of sources at the sink, the source nodes exchange messages through a sequence of error-free broadcasts. For any function of independent sources, a computable characterization of the set of all feasible message coding rates-the rate region-is derived in terms of single-letter information measures. In the limit as the number of messages tends to infinity, the infinite-message minimum sum rate, viewed as a functional of the joint source probability mass function, is characterized as the least element of a partially ordered family of functionals having certain convex-geometric properties. This characterization leads to a family of lower bounds for the infinite-message minimum sum rate and a simple criterion to test the optimality of any achievable infinite-message sum rate. An iterative algorithm for evaluating the infinite-message minimum sum-rate functional is proposed and is demonstrated through an example of computing the minimum function of three Bernoulli sources. Based on the characterizations of the rate regions, it is shown that when computing symmetric functions of binary sources, the sink will inevitably learn certain additional information that is not demanded in computing the function. This conceptual understanding leads to new improved bounds for the minimum sum rate. The new bounds are shown to be orderwise better than those based on cut-sets as the network scales. The scaling law of the minimum sum rate is explored for different classes of symmetric functions and source parameters.
Black And White Self Esteem The Urban School Child

black and white self esteem the urban school child is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the black and white self esteem the urban school child is universally compatible with any devices to read.
A Fresh Look at Entropy and the Second Law of Thermodynamics

In days long gone, the second law of thermodynamics (which predated the first law) was regarded as perhaps the most perfect and unassailable law in physics. It was even supposed to have philosophical import: It has been hailed for providing a proof of the existence of God (who started the universe off in a state of low entropy, from which it is constantly degenerating); conversely, it has been rejected as being incompatible with dialectical materialism and the perfectibility of the human condition.
Our Eyes do Not Always Go Where we Want Them to Go: Capture of the Eyes by New Objects

Observers make rapid eye movements to examine the world around them. Before an eye movement is made, attention is covertly shifted to the location of the object of interest. The eyes typically will land at the position at which attention is directed. Here we report that a goal-directed eye movement toward a uniquely colored object is disrupted by the appearance of a new but task-irrelevant object, unless subjects have a sufficient amount of time to focus their attention on the location of the target prior to the appearance of the new object. In many instances, the eyes started moving toward the new object before gaze started to shift to the color-singleton target. The eyes often landed for a very short period of time (25–150 ms) near the new object. The results suggest parallel programming of two saccades: one voluntary, goal-directed eye movement toward the color-singleton target and one stimulus-driven eye movement reflexively elicited by the appearance of the new object. Neuroanatomical structures responsible for parallel programming of saccades are discussed.
Relationship Between Cognitive Appraisals for Left-home Hassles,Depression and Loneliness in Rural Left-home-children

Objective: To evaluate rural left-home-children's cognitive appraisals for left-home hassles,and their effects on children's depression and loneliness.Methods: Participants included 207 rural left-home children selected from a town in Henan province.They were asked to complete scales of children's depression,loneliness,and cognitive appraisals for left-home hassles.Results: ①Parents-left-home children endorsed greater negative cognitive appraisals for hypothetical left-home hassles than father-left-home children. ②The higher levels of children's depression and loneliness,the greater negative cognitive appraisals for hypothetical left-home hassles,and this was the same for both parents-left-home children and father-left-home children. ③The lower levels of children's depression and loneliness,the greater positive cognitive appraisals for hypothetical left-home hassles.But for parents-left-home children,positive cognitive appraisals didn't reduce children's depression.Conclusion: The prediction power of cognitive appraisals for left-home hassles to left-home-children's loneliness is stronger than to children's depression,but varies with different children's groups.
Faktor-Faktor Brand Loyalty Smartphone Pada Generasi Y

Brand loyalty terhadap smartphone merupakan bentuk perilaku pembelian berulang yang dilakukan konsumen terhadap suatu merek smartphone yang sama. Brand loyalty merupakan suatu fenomena penting bagi industri. Generasi Y merupakan sasaran penelitian ini karena berkarakteristik sebagai techno-generation yang akan menjadi pimpinan pasar pada masa depan. Tujuan penelitian ini adalah mengidentifikasi faktor-faktor yang mempengaruhi brand loyalty terhadap smartphone, pada generasi Y. Teknik sampling adalah purposive dan snowball. Penelitian ini dilakukan dengan perspektif kualitatif, dengan metode fenomenologi. Data dikumpulkan dengan wawancara, dan dianalisis mengunakan analisis tematik induktif. Hasil menunjukkan dua faktor yang memengaruhi brand loyalty terhadap smartphone pada generasi Y, yakni faktor internal dan eksternal. Faktor interla mencakup faktor-faktor psikologis yang melibatkan motivasi, persepsi, proses belajar, dan faktor-faktor pribadi yang melibatkan kepribadian dan nilai. Faktor-faktor eksternal mencakup faktor-faktor sosial yang melibatkan gaya hidup komunitas, lingkaran kerja atau kuliah, teman, lingkaran keluarga, dan media. Kepribadian yang dipengaruhi oleh lingkaran keluarga merupakan hal terpenting yang memengaruhi brand loyalty generasi Y terhadap smartphone.
Exploiting PUF Models for Error Free Response Generation

Physical unclonable functions (PUF) extract secrets from randomness inherent in manufacturing processes. PUFs are utilized for basic cryptographic tasks such as authentication and key generation, and more recently, to realize key exchange and bit commitment requiring a large number of error free responses from a strong PUF. We propose an approach to eliminate the need to implement expensive on-chip error correction logic implementation and the associated helper data storage to reconcile naturally noisy PUF responses. In particular, we exploit a statistical model of an Arbiter PUF (APUF) constructed under the nominal operating condition during the challenge response enrollment phase by a trusted party to judiciously select challenges that yield error-free responses even across a wide operating conditions, specifically, a $ \pm 20\% $ supply voltage variation and a $ 40^{\crc} $ temperature variation. We validate our approach using measurements from two APUF datasets. Experimental results indicate that large number of error-free responses can be generated on demand under worst-case when PUF response error rate is up to 16.68\%.
Robust High-Dimensional Precision Matrix Estimation

The dependency structure of multivariate data can be analyzed using the covariance matrix \(\boldsymbol{\varSigma }\). In many fields the precision matrix \(\boldsymbol{\varSigma }^{-1}\) is even more informative. As the sample covariance estimator is singular in high dimensions, it cannot be used to obtain a precision matrix estimator. A popular high-dimensional estimator is the graphical lasso, but it lacks robustness. We consider the high-dimensional independent contamination model. Here, even a small percentage of contaminated cells in the data matrix may lead to a high percentage of contaminated rows. Downweighting entire observations, which is done by traditional robust procedures, would then result in a loss of information. In this paper, we formally prove that replacing the sample covariance matrix in the graphical lasso with an elementwise robust covariance matrix leads to an elementwise robust, sparse precision matrix estimator computable in high dimensions. Examples of such elementwise robust covariance estimators are given. The final precision matrix estimator is positive definite, has a high breakdown point under elementwise contamination, and can be computed fast.
Uniform Continuity of the Value of Zero-Sum Games with Differential Information

We establish uniform continuity of the value for zero-sum games with differential information, when the distance between changing information fields of each player is measured by the Boylan (1971) pseudo-metric. We also show that the optimal strategy correspondence is upper semicontinuous when the information fields of players change, even with the weak topology on players' strategy sets.
Quality Measure Functions for Calibration of Speaker Recognition Systems in Various Duration Conditions

This paper investigates the effect of utterance duration to the calibration of a modern i-vector speaker recognition system with probabilistic linear discriminant analysis (PLDA) modeling. A calibration approach to deal with these effects using quality measure functions (QMFs) is proposed to include duration in the calibration transformation. Extensive experiments are performed in order to evaluate the robustness of the proposed calibration approach for unseen conditions in the training of calibration parameters. Using the latest NIST corpora for evaluation, results highlight the importance of considering the quality metrics like duration in calibrating the scores for automatic speaker recognition systems.
Convex Optimization Algorithms for Active Balancing of Humanoid Robots

We show that a large class of active balancing problems for legged robots can be framed as a second-order cone programming (SOCP) problem, a convex optimization problem for which efficient and numerically robust algorithms exist. We describe this general SOCP balancing framework, show that several existing optimization-based balancing strategies reduce to special cases of this more general formulation, and investigate the computational performance of our SOCP algorithms through simulation studies involving a humanoid model.
Mesenchymal Stem Cell-Based Therapy for Kidney Disease: A Review of Clinical Evidence

Mesenchymal stem cells form a population of self-renewing, multipotent cells that can be isolated from several tissues. Multiple preclinical studies have demonstrated that the administration of exogenous MSC could prevent renal injury and could promote renal recovery through a series of complex mechanisms, in particular via immunomodulation of the immune system and release of paracrine factors and microvesicles. Due to their therapeutic potentials, MSC are being evaluated as a possible player in treatment of human kidney disease, and an increasing number of clinical trials to assess the safety, feasibility, and efficacy of MSC-based therapy in various kidney diseases have been proposed. In the present review, we will summarize the current knowledge on MSC infusion to treat acute kidney injury, chronic kidney disease, diabetic nephropathy, focal segmental glomerulosclerosis, systemic lupus erythematosus, and kidney transplantation. The data obtained from these clinical trials will provide further insight into safety, feasibility, and efficacy of MSC-based therapy in renal pathologies and allow the design of consensus protocol for clinical purpose.
Using eye tracking to compare web page designs: a case study

A proposed design for the American Society of Clinical Oncology (ASCO) Web site was evaluated against the original design in terms of the ease with which the right starting points for key tasks were located and processed. This report focuses on the eye tracking methodology that accompanied other conventional usability practices used in the evaluation. Twelve ASCO members were asked to complete several search tasks using each design. Performance measures such as click accuracy and time on task were supplemented with eye movements which allowed for an assessment of the processes that led to both the failures and the successes. The report details three task examples in which eye tracking helped diagnose errors and identify the better of the two designs (and the reasons for its superiority) when both were equally highly successful. Advantages and limitations of the application of eye tracking to design comparison are also discussed.