Miracle-dz/UniFAR-FTUs huggingface dataset:
Histocompatibility antigens and genetic control of the immune response in guinea pigs. I. Specific inhibition of antigen‐induced lymphocyte stimulation by alloantisera

Alloantisera raised by cross‐immunizing with lymphoid cells in outbred and inbred strains of guinea pigs have permitted the serological identification of several alleles of a GPL‐A locus, which differs from the 2/13 locus distinguishing NIH strain 2 and 13 guinea pigs. Five guinea pig strains, homozygous for GPL‐A and 2/13 antigens, were sequentially immunized with seven structurally unrelated antigens ((T,G)‐A–L, penicilloylated bovine IgG and poly‐L‐lysine, aspirin anhydride, phenetidine, horseradish peroxidase and DNP‐dodecapeptide). Considerable differences in the immune response were observed, as measured by skin tests and antigen‐induced lymphocyte stimulation in vitro.
Verification of Population Ring Protocols in PAT

The population protocol model has emerged as an elegant paradigm for describing mobile ad hoc networks, consisting of a number of nodes that interact with each other to carry out a computation. One essential property of self-stabilizing population protocols is that all nodes must eventually converge to the correct output value, with respect to all possible initial configurations. It has been shown that fairness constraints play a crucial role in designing population protocols. The Process Analysis Toolkit (PAT) has been developed to perform verifications under different fairness constraints efficiently. In particular, it can handle global fairness, which is required for the correctness of most of population protocols. It is an ideal candidate for automatically verifying population protocols. In this paper, we summarize our latest empirical evaluation of PAT on a set of self-stabilizing population protocols for ring networks. We report one previously unknown bug in a protocol for leader election identified using PAT.
Barriers and Bounds to Rationality

PrefaceAcknowledgments1Introduction32The Metalogic of Economic Predictions, Calculations, and Propositions733Microeconomic Foundations of Cyclical Irregularities or "Chaos"1054Qualitative Effects of Monetary Policy in "Rich" Dynamic Systems1375Decentralized, Dispersed Exchange without an Auctioneer: A Simulation Study1576Approximations of Cooperative Equilibria in Multiperson Prisoners' Dilemma Played by Cellular Automata1817The Complexity of Social Groups and Social Systems Described by Graph Structures210Works Cited243Index251
Temporal patterns of seed quality development, decline, and timing of maximum quality during seed development and maturation

Abstract The long-standing hypothesis that seed quality improves during seed filling, is greatest at the end of seed filling, and declines thereafter (because seed deterioration was assumed to begin then), provided a template for research in seed quality development. It was rejected by investigations where seed quality was shown to improve throughout both seed development and maturation until harvest maturity, before seed deterioration was first observed. Several other temporal patterns of seed quality development and decline have also been reported. These are portrayed and compared. The assessment suggests that the original hypothesis was too simple, because it combined several component hypotheses: (a) the seed improvement (only) phase ends before seed deterioration (only) commences; (b) there is only a brief single point in time during seed development and maturation when, in all circumstances, seed quality is maximal; (c) the seed quality improvement phase coincides perfectly with seed filling, with deterioration only post-seed filling. It is concluded that the search for the single point of maximum seed quality was a false quest because (a) seed improvement and deterioration may cycle (sequentially if not simultaneously) during seed development and maturation; (b) the relative sensitivity of the rates of improvement and deterioration to environment may differ; (c) the period of maximum quality may be brief or extended. Hence, when maximum quality is first attained, and for how long it is maintained, during seed development and maturation varies with genotype and environment. This is pertinent to quality seed production in current and future climates as it will be affected by climate change and a likelihood of more frequent coincidence of brief periods of extreme temperatures with highly sensitive phases of seed development and maturation. This is a possible tipping point for food security and for ecological diversity.
Chirp and Dispersion Tolerance of a Single-Drive Push–Pull Silicon Modulator at 28 Gb/s

We experimentally characterized the chirp and dispersion tolerance of a single-drive push-pull silicon Mach-Zehnder modulator. The measured data indicate an effective chirp parameter of -0.8 at Vπ drive, which includes contributions from power imbalance, modulation efficiency asymmetry, and inherent free-carrier absorptions. A dispersion tolerance window of 240 ps/nm is demonstrated, with a 1-dB penalty after 10-km fiber dispersion cumulation at 28 Gb/s and BER of 1E-3.
Performance analysis of Java message-passing libraries on fast Ethernet, Myrinet and SCI clusters

The use of Java for parallel programming on clusters according to the message-passing paradigm is an attractive choice. In this case, the overall application performance will largely depend on the performance of the underlying Java message-passing library. This paper evaluates, models and compares the performance of MPI-like point-to-point and collective communication primitives from selected Java message-passing implementations on clusters with different interconnection networks. We have developed our own micro-benchmark suite to characterize the message-passing communication overhead and thus derive analytical latency models.
Novel data mining based image classification with Bayes, Tree, Rule, Lazy and Function Classifiers using fractional row mean of Cosine, Sine and Walsh column transformed images

Important task in image database is to organize images into appropriate category using different features of images. Image classification is studied for many years. There are various techniques proposed to increase the accuracy of classification. In this paper a novel data mining based approach is proposed for content based image classification. Feature extraction and classification algorithms are two main steps in classification process. This paper proposes the use of orthogonal transform to generate the feature vector and to investigate effectiveness of different transforms (Cosine, Sine, and Walsh). Experimentation is carried on different sizes of feature vectors which are formed by taking fractional coefficients. Classification algorithm from different families such as Bayes (Naive Bayes and Bayes Net), Function (RBFNetwork and Simple Logistic), Lazy (IB1 and Kstar), Rule (Decision and Part) and Tree (BFTree, J48 Random Tree and Random Forest) are used for classification. Experimental results and its analysis have shown the Simple Logistic classifier with Walsh transform to be better for proposed data mining based image classification technique.
Proteinase-Polymerase Precursor as the Active Form of Feline Calicivirus RNA-Dependent RNA Polymerase

ABSTRACT The objective of this study was to identify the active form of the feline calicivirus (FCV) RNA-dependent RNA polymerase (RdRP). Multiple active forms of the FCV RdRP were identified. The most active enzyme was the full-length proteinase-polymerase (Pro-Pol) precursor protein, corresponding to amino acids 1072 to 1763 of the FCV polyprotein encoded by open reading frame 1 of the genome. Deletion of 163 amino acids from the amino terminus of Pro-Pol (the Val-1235 amino terminus) caused a threefold reduction in polymerase activity. Deletion of an additional one (the Thr-1236 amino terminus) or two (the Ala-1237 amino terminus) amino acids produced derivatives that were 7- and 175-fold, respectively, less active than Pro-Pol. FCV proteinase-dependent processing of Pro-Pol in the interdomain region preceding Val-1235 was not observed in the presence of a catalytically active proteinase; however, processing within the polymerase domain was observed. Inactivation of proteinase activity by changing the catalytic cysteine-1193 to glycine permitted the production and purification of intact Pro-Pol. Biochemical analysis of Pro-Pol showed that this enzyme has properties expected of a replicative polymerase, suggesting that Pro-Pol is an active form of the FCV RdRP.
Mechanisms for Hydrolysis of Silicon Nanomembranes as Used in Bioresorbable Electronics

The ability of silicon to dissolve in physiological environments allows its use as the basis of a high-performance inorganic integrated circuit technology for active, bioresorbable implant devices. N. R. Aluru, J. A. Rogers, and co-workers perform systematic experimental and theoretical studies of hydrolysis of silicon nanomembranes at near neutral pH, as described on page 1857. This image shows a molecular-dynamics rendering of nucleophilic attack of a silicon surface immersed in water and the resulting formation of molecules of silicic acid.
Isolation and Culture of Spinal Cord Motor Neurons

Isolated spinal motoneurons are a powerful tool for studying basic mechanisms of neurite growth and survival. Since motoneurons are a minor population of developing spinal cord cells, they need to be purified and enriched to separate them from non‐neuronal cells. Therefore, the particular feature of embryonic motoneurons to express the low affinity neurotrophin receptor p75NTR is used to separate the motoneurons from other contaminating cells. Two ways are described to isolate embryonic motoneurons: the basic protocol taking advantage of the ability of p75NTR to bind lectin, and an alternative method using an antibody against p75NTR for a panning procedure. These protocols comprise suggestions for the cultivation of the isolated motoneurons for experiments regarding neural outgrowth and survival as well as instruction for the preparation of proteins of the cells. © 2015 by John Wiley & Sons, Inc.
Relationship between Dynamic Instability of Individual Microtubules and Flux of Subunits into and out of Polymer

Behaviors of dynamic polymers such as microtubules and actin are frequently assessed at one or both of two scales: (i) net assembly or disassembly of bulk polymer, (ii) growth and shortening of individual filaments. Previous work has derived various forms of an equation to relate the rate of change in bulk polymer mass (i.e., flux of subunits into and out of polymer, often abbreviated as “J”) to individual filament behaviors. However, these versions of this “J equation” differ in the variables used to quantify individual filament behavior, which correspond to different experimental approaches. For example, some variants of the J equation use dynamic instability parameters, obtained by following particular individuals for long periods of time. Another form of the equation uses measurements from many individuals followed over short time steps. We use a combination of derivations and computer simulations that mimic experiments to (i) relate the various forms of the J equation to each other; (ii) determine conditions under which these J equation forms are and are not equivalent; and (iii) identify aspects of the measurements that can affect the accuracy of each form of the J equation. Improved understanding of the J equation and its connections to experimentally measurable quantities will contribute to efforts to build a multi-scale understanding of steady-state polymer behavior.
Relay Placement in Sensor Networks

In this thesis, I study relay placement in energy-constrained wireless sensor networks. The goal is to optimise balanced data gathering, where the utility function is a weighted sum of the minimum and average amounts of data collected from each sensor node. I define a number of classes of simplified relay placement problems, including a planar problem with a simple cost model for radio communication. The computational complexity of these classes is studied, and all classes are proved NP-hard; in some cases even finding approximate solutions is NP-hard. I also present algorithms for finding k-optimal solutions to the relay placement problem. These algorithms have been implemented, and their performance has been studied empirically ; the implementation is freely available. Työn nimi — Arbetets titel — Title Oppiaine — Läroämne — Subject Työn laji — Arbetets art — Level Aika — Datum — Month and year Sivumäärä — Sidoantal — Number of pages Tiivistelmä — Referat — Abstract Avainsanat — Nyckelord — Keywords Säilytyspaikka — Förvaringsställe — Where deposited Muita tietoja — ¨ ovriga uppgifter — Additional information
Antifungal efficacy of Punica granatum, Acacia nilotica, Cuminum cyminum and Foeniculum vulgare on Candida albicans: an in vitro study.

BACKGROUND The establishment and maintenance of oral microbiota is related not only to interbacterial coaggregations but also to interactions of these bacteria with yeasts. Hence, it is important for agents used in the treatment of oral diseases to have antifungal properties for effective therapy. OBJECTIVE The main purpose of this study was to evaluate the in vitro antifungal efficacy of Punica granatum, Acacia nilotica, Cuminum cyminum and Foeniculum vulgare on Candida albicans. MATERIALS AND METHODS The pomegranate peel is separated, dried and powdered. Fennel, cumin and acacia bark obtained from the tree are powdered. Candida is inoculated at 37˚C and seeded on Sabourauds agar medium. Sterilized filter papers saturated with 30 μl of the extracts are placed on the seeded plates and inoculated at 24 and 48 h. Zones of inhibition on all four sides are measured around the filter paper with a vernier caliper. The experiments were repeated on four plates, with four samples of each extract on one plate for all of the extracts. RESULTS All the above-mentioned ingredients showed antifungal property, with Punica granatum showing the highest inhibition of Candida albicans with a mean zone of inhibition of 22 mm. P-values <0.05 were obtained for Punica granatum when compared with the other extracts. CONCLUSION The results showed the potential use of these products as cheap and convenient adjuvants to pharmaceutical antifungal products.
On Utilizing Association and Interaction Concepts for Enhancing Microaggregation in Secure Statistical Databases

This paper presents a possibly pioneering endeavor to tackle the microaggregation techniques (MATs) in secure statistical databases by resorting to the principles of associative neural networks (NNs). The prior art has improved the available solutions to the MAT by incorporating proximity information, and this approach is done by recursively reducing the size of the data set by excluding points that are farthest from the centroid and points that are closest to these farthest points. Thus, although the method is extremely effective, arguably, it uses only the proximity information while ignoring the mutual interaction between the records. In this paper, we argue that interrecord relationships can be quantified in terms of the following two entities: 1) their ldquoassociationrdquo and 2) their ldquointeraction.rdquo This case means that records that are not necessarily close to each other may still be ldquogrouped,rdquo because their mutual interaction, which is quantified by invoking transitive-closure-like operations on the latter entity, could be significant, as suggested by the theoretically sound principles of NNs. By repeatedly invoking the interrecord associations and interactions, the records are grouped into sizes of cardinality ldquok,rdquo where k is the security parameter in the algorithm. Our experimental results, which are done on artificial data and benchmark real-life data sets, demonstrate that the newly proposed method is superior to the state of the art not only based on the information loss (IL) perspective but also when it concerns a criterion that involves a combination of the IL and the disclosure risk (DR).
A Novel Technique to Classify Intra Cardiac Tumor and Thrombus in Echocardiography

This paper describes an automatic method for classification and segmentation of different intra cardiac masses in tumor echocardiograms. Correct diagnosis of the character of intra cardiac mass in a living patient is a true challenge for a cardiologist. To improve diagnosis accuracy, a novel fully automatic classification method based on Kernel Collaborative Representation is proposed to distinguish intra cardiac tumor and thrombi in echocardiography. First, a region of interest is cropped to define the mass area. Then, a unique globally denoising method is employed which yields better noise attenuation and edge enhancement, without destroying the important cardiac structures. For segmentation, SLIC method, based on a local version of K-means is used. Finally, the motion, the boundary as well as the texture features are processed by a Kernel Collaborative Representation Classifier to distinguish two masses. The proposed detected contours closely approximate the manually traced ones. The better accuracy and simple implementation make the proposed method beneficial to help the cardiologists make a diagnosis before the surgery. Keywords— Automatic classification, echocardiography, Intra cardiac tumor and thrombi ,Simple Linear Iterative Clustering, Collaborative Representation
Effects of 17β-Estradiol and Xenoestrogens on the Neuronal Survival in an Organotypic Hippocampal Culture

Xenoestrogens are man-made compounds that mimic the actions of estrogens through interactions with estrogen receptors (ERs). Although xenoestrogens have received a great deal of attention as possible causes of brain disfunctions, little information concerning the effects of xenoestrogens on the central nervous system is available. In this study, we investigated the effects of 17β-estradiol (E2) and four xenoestrogens (17α-ethynylestradiol, diethylstilbestrol, p-nonylphenol and bisphenol A (BPA)) on the neuronal survival using organotypic hippocampal slice cultures. When the cultured hippocampal slices were exposed to glutamate (1 mM, 15 min), the CA1-selective neuronal damage was induced. Pretreatment with E2 and the xenoestrogens (24 h) selectively exacerbated the CA3 neuronal damage caused by glutamate. In spite of the marked difference of binding affinities to ERs, all compounds revealed maximal effects at 1 nM. ER antagonists, tamoxifen and ICI 182,780, did not affect responses to E2 and the xenoestrogens, indicating that these effects are mediated through mechanisms other than ERs. In spite of the fact that BPA has little interaction with ERs at 1 nM, E2 and BPA equally increased the expression of N-methyl-D-aspartate receptor in CA3 and upregulated the spine density of the apical portion of CA3 dendrites at 1 nM. These compounds also enhanced the sprouting of mossy fibers to CA3 neurons. These results suggest that exposure to E2 and xenoestrogens during the developmental stage results in a marked influence on synaptogenesis and neuronal vulnerability through mechanisms other than ERs.
FLUID FLOW STRESS AFFECTS PERITONEAL CELL KINETICS: POSSIBLE PATHOGENESIS OF PERITONEAL FIBROSIS

♦ Background: Peritoneal fibrosis is an essential precursor condition to the development of encapsulating peritoneal sclerosis (EPS). This serious complication leads to a high mortality rate in peritoneal dialysis (PD) patients. Although several factors, including highly concentrated glucose in the dialysis solution, are believed to be potent agents for peritoneal fibrosis, the underlying mechanism remains unclear. During PD, the dialysis solution continuously generates fluid flow stress to the peritoneum under peristalsis and body motion. Fluid flow stress has been implicated as playing a critical role in the physiologic responses of many cell types. We therefore hypothesized that fluid flow stress may be involved in the pathogenesis of peritoneal fibrosis leading to EPS. ♦ Methods: To generate fluid flow stress, culture containers were placed on a rotatory shaker in a thermostatic chamber. In this system, the shaker rotated at a speed of 25 rpm with a radius of 1.5 cm. Mesothelial cells were cultured in low-glucose (1000 mg/L) or high-glucose (4500 mg/L) complete medium with and without flow stress. ♦ Results: Fluid flow stress promoted hyperplasia and epithelial-mesenchymal transition (EMT) of mesothelial cells independent of glucose concentration. Fluid flow stress inhibited expression of ERK (extracellular signal-regulated kinase) and p38 MAPK (mitogen-activated protein kinase) in mesothelial cells. Administration of ERK and p38 MAPK inhibitors replicated the stress-induced morphology of mesothelial cells. ♦ Conclusions: The present data indicate that fluid flow stress promotes hyperplasia and EMT of mesothelial cells via the MAPK axis, suggesting that fluid flow stress may be involved in the pathogenesis of peritoneal fibrosis.
Cysteine Dioxygenase 1 Is a Tumor Suppressor Gene Silenced by Promoter Methylation in Multiple Human Cancers

The human cysteine dioxygenase 1 (CDO1) gene is a non-heme structured, iron-containing metalloenzyme involved in the conversion of cysteine to cysteine sulfinate, and plays a key role in taurine biosynthesis. In our search for novel methylated gene promoters, we have analyzed differential RNA expression profiles of colorectal cancer (CRC) cell lines with or without treatment of 5-aza-2′-deoxycytidine. Among the genes identified, the CDO1 promoter was found to be differentially methylated in primary CRC tissues with high frequency compared to normal colon tissues. In addition, a statistically significant difference in the frequency of CDO1 promoter methylation was observed between primary normal and tumor tissues derived from breast, esophagus, lung, bladder and stomach. Downregulation of CDO1 mRNA and protein levels were observed in cancer cell lines and tumors derived from these tissue types. Expression of CDO1 was tightly controlled by promoter methylation, suggesting that promoter methylation and silencing of CDO1 may be a common event in human carcinogenesis. Moreover, forced expression of full-length CDO1 in human cancer cells markedly decreased the tumor cell growth in an in vitro cell culture and/or an in vivo mouse model, whereas knockdown of CDO1 increased cell growth in culture. Our data implicate CDO1 as a novel tumor suppressor gene and a potentially valuable molecular marker for human cancer.