Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach for using extended LDPC codes in cooperative diversity

Cooperative diversity or user cooperation achieves the diversity gain without adding physical antennas to the users or mobile stations. The users work in cooperative fashion using their single antennas to create a virtual transmit diversity, called relay diversity or cooperative diversity. The diversity gain achieved by cooperative diversity can be further improved using error correction codes. Low-density parity-check (LDPC) codes are linear block codes with good error correction capabilities. We present a novel approach using extended LDPC codes to increase the diversity gain in cooperative diversity. We also compare the extended LDPC codes with punctured LDPC codes in cooperative diversity and show that extended LDPC codes have lesser complexity than punctured LDPC codes in cooperative diversity.
Multi-class protein fold recognition using support vector machines and neural networks

MOTIVATION Protein fold recognition is an important approach to structure discovery without relying on sequence similarity. We study this approach with new multi-class classification methods and examined many issues important for a practical recognition system. RESULTS Most current discriminative methods for protein fold prediction use the one-against-others method, which has the well-known 'False Positives' problem. We investigated two new methods: the unique one-against-others and the all-against-all methods. Both improve prediction accuracy by 14-110% on a dataset containing 27 SCOP folds. We used the Support Vector Machine (SVM) and the Neural Network (NN) learning methods as base classifiers. SVMs converges fast and leads to high accuracy. When scores of multiple parameter datasets are combined, majority voting reduces noise and increases recognition accuracy. We examined many issues involved with large number of classes, including dependencies of prediction accuracy on the number of folds and on the number of representatives in a fold. Overall, recognition systems achieve 56% fold prediction accuracy on a protein test dataset, where most of the proteins have below 25% sequence identity with the proteins used in training.
The Membrane Guanylyl Cyclase, Retinal Guanylyl Cyclase-1, Is Activated through Its Intracellular Domain (*)

Retinal guanylyl cyclase-1 (RetGC-1) is a membrane guanylyl cyclase found in photoreceptor outer segments. It consists of an apparent extracellular domain (ECD) linked by a single transmembrane segment to an intracellular domain (ICD). Guanylyl cyclase activating protein-2 (GCAP-2) is a Ca-binding protein that activates RetGC-1 in a Ca-sensitive manner. To establish whether GCAP-2 stimulates RetGC-1 through the ECD or ICD, we made deletion mutants lacking either the ECD or both the ECD and transmembrane domains (TMD) of RetGC-1. Recombinant wild type RetGC-1 and both deletion mutants were expressed in HEK 293 cells, and their sensitivities to GCAP-2, Ca, and ATP were compared. Our data demonstrate that both deletion mutants are regulated similarly to wild type RetGC-1 with indistinguishable EC values for Ca and similar K values for activation by GCAP-2. This shows that GCAP-2 functions through the ICD of RetGC-1 and that removal of the ECD and TMD do not significantly alter regulation by these factors. Our data also show that ATP potentiates stimulation of guanylyl cyclase activity by GCAP-2 and that neither the ECD nor the TMD of RetGC-1 participate in its regulation by ATP.
An update of novel screening methods for GPCR in drug discovery

Introduction: G protein-coupled receptors (GPCRs) are the largest and most versatile group of cytomembrane receptors, comprising of approximately 300 non-sensory and druggable members. Traditional GPCR drug screening is based on radiometric competition binding assays, which are expensive and hazardous to human health. Furthermore, the paradox of high investment and low output, in terms of new drugs, highlights the need for more efficient and effective drug screening methods. Areas covered: This review summarizes non-radioactive assays assessing the ligand–receptor binding including: the fluorescence polarization assay, the TR-FRET assay and the surface plasmon resonance assay. It also looks at non-radioactive assays that assess receptor activation and signaling including: second messenger-based assays and β-arrestin recruitment-based assays. This review also looks at assays based on cellular phenotypic change. Expert opinion: GPCR signaling pathways look to be more complicated than previously thought. The existence of receptor allosteric sites and multireceptor downstream effectors restricts the traditional assay methods. The emergence of novel drug screening methods such as those for assessing β-arrestin recruitment and cellular phenotypic change may provide us with improved drug screening efficiency and effect.
Reference evapotranspiration maps for Colorado

The Integrated Decision Support Group (IDS) at Colorado State University has developed a set of monthly reference evapotranspiration (Err) maps for the western slope of Colorado. The reference evapotranspiration maps were developed using geographic information systems (GIS) to manipulate spatial data. After the monthly alfalfa-based ETr maps were complete, a Graphical User Interface (GUI) was developed to allow the user to interactively view and query the maps. In accordance with current developments in the irrigation science community the Penman-Monteith was used to calculate ETr and alfalfa was selected as the reference crop for this study; Data parameters required as input for the Penman-Monteith equation are maximum and minimum temperature, relative humidity (or dew point temperature), solar radiation, and wind-speed. During the course of this project, several data sources have been identified. Where possible, data have been subjected to a quality check. UC-S«/4/'/, t() Yf{' ! io ,/lJJ. ·,<' Index tl/{tHtfJ&
Paramagnetism of cobalt-doped ZnO nanoparticles obtained by microwave solvothermal synthesis

Zinc oxide nanopowders doped with 1–15 mol % cobalt were produced by the microwave solvothermal synthesis (MSS) technique. The obtained nanoparticles were annealed at 800 °C in nitrogen (99.999%) and in synthetic air. The material nanostructure was investigated by means of the following techniques: X-ray diffraction (XRD), helium pycnometry density, specific surface area (SSA), inductively coupled plasma optical emission spectrometry (ICP-OES), extended X-ray absorption fine structure (EXAFS) spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and with magnetometry using superconducting quantum interference device (SQUID). Irrespective of the Co content, nanoparticles in their initial state present a similar morphology. They are composed of loosely agglomerated spherical particles with wurtzite-type crystal structure with crystallites of a mean size of 30 nm. Annealing to temperatures of up to 800 °C induced the growth of crystallites up to a maximum of 2 μm in diameter. For samples annealed in high purity nitrogen, the precipitation of metallic α-Co was detected for a Co content of 5 mol % or more. For samples annealed in synthetic air, no change of phase structure was detected, except for precipitation of Co3O4 for a Co content of 15 mol %. The results of the magentometry investigation indicated that all as-synthesized samples displayed paramagnetic properties with a contribution of anti-ferromagnetic coupling of Co–Co pairs. After annealing in synthetic air, the samples remained paramagnetic and samples annealed under nitrogen flow showed a magnetic response under the influences of a magnetic field, likely related to the precipitation of metallic Co in nanoparticles.
Integrating compound terms in Bayesian text classification

Text classification usually assumed a word-based document representation. In this paper, we propose a new approach to integrate compound terms in Bayesian text classification. Compound terms are used as complementary features to single words. An acute problem is to consider their dependence with the component words. In this paper, we propose to use smoothing techniques to combine both compound term and word representations. Experiments have been conducted on two corpora. Our results show that this approach can slightly but steadily improve the classification performance on both test corpora.
TempoMP: Integrated prediction and management of temperature in heterogeneous MPSoCs

Heterogeneous Multi-Processor Systems on a Chip (MPSoCs) are more complex from a thermal perspective compared to the homogeneous MPSoCs because of their inherent imbalance in power density. In this work we develop TempoMP, a new technique for thermal management of heterogeneous MPSoCs which leverages multi-parametric optimization along with our novel thermal predictor, Tempo. TempoMP is able to deliver locally optimal dynamic thermal management decisions to meet thermal constraints while minimizing power and maximizing performance. It leverages our Tempo predictor which, unlike the previous techniques, can estimate the impact of future power state changes at negligible overhead. Our experiments show that compared to the state of the art, Tempo can reduce the maximum prediction error by up to an order of magnitude. Our experiments with heterogeneous MPSoCs also show that TempoMP meets thermal constraints while reducing the average task lateness by 2.5X and energy-lateness product by 5X compared to the state of the art techniques.
An Efficient and Novel Key Establishment Scheme for Internet Enabled Wireless Sensor Network in the Context of IOT

Wireless sensor networks (WSN) behave as a digital skin, providing a virtual layer where the information about the physical world can be accessed by any computational system. As a result, they are an invaluable resource for realizing the vision of the Internet of Things (IoT). Many applications of sensor networks require secure communication. Thus establishing a secure channel between any two sensor-nodes in WSNs/IESNs is important for many applications, such as secure data exchange, secure data aggregation, and secure routing. In this paper, first we show why existing three party key establishment schemes cannot be easily applied to IESN. Second we propose an extension of traditional three-party key establishment schemes (such as SNEP, BBF and OR). The method provides DoS and Sybil attack resistance and benefits from low communication cost, independence of prior sensor deployment knowledge and support for node mobility. In comparison to the previous well-known three-party schemes, our extension not only fixes DoS vulnerability, but also provides some other advantages such as significant efficiency. The proposed key establishment scheme can be used not only for establishing shared key between any two sensors, but it is applicable for establishing shared secret between any two entities/ things in the context of IoT.
Enhancing accessibility of microblogging messages using semantic knowledge

The volume of microblogging messages is increasing exponentially with the popularity of microblogging services. With a large number of messages appearing in user interfaces, it hinders user accessibility to useful information buried in disorganized, incomplete, and unstructured text messages. In order to enhance user accessibility, we propose to aggregate related microblogging messages into clusters and automatically assign them semantically meaningful labels. However, a distinctive feature of microblogging messages is that they are much shorter than conventional text documents. These messages provide inadequate term co occurrence information for capturing semantic associations. To address this problem, we propose a novel framework for organizing unstructured microblogging messages by transforming them to a semantically structured representation. The proposed framework first captures informative tree fragments by analyzing a parse tree of the message, and then exploits external knowledge bases (Wikipedia and WordNet) to enhance their semantic information. Empirical evaluation on a Twitter dataset shows that our framework significantly outperforms existing state-of-the-art methods.
Activity screening and structure–activity relationship of the hit compounds targeting APN/CD13

Aminopeptidase N (APN) plays an important role in tumor progression, which participates in the progress such as proliferation, attachment, angiogenesis, and tumor invasion. All of this makes APN as a good chemical therapeutic anti‐tumor target. In this study, a series of chemically synthesized APN inhibitors were tested for the anti‐tumor activities, and three most effective compounds were chosen according to the MTT assay. Then, the enzyme inhibitory, anti‐tumor, specificity, angiogenesis, and invasion were determined to evaluate the activity of these three compounds. All compounds can markedly inhibit the enzyme activity of APN, angiogenesis of endothelial cells, and the invasion of ES‐2 cells. And it had little effect on the viability of K562 which express low level of APN. This data indicated that the tested compounds were APN hit compounds. We also did kinetic assay to determine the inhibition constant and constructed a three‐dimensional quantitative structure–activity relationship model to analyze the structure–activity relationship to direct the further design of novel APN inhibitors as anti‐tumor agents. These data demonstrate that the tested compounds can be developed as novel candidates of anticancer agent.
The Influence of Erythropoietin on the Vascular Responses of Rat Resistance Arteries

This study examined the effect of erythropoietin (EPO) on resting tension and on the responses of rat mesenteric and renal arcuate arteries in vitro to a number of agonists as a possible cause of its blood pressure elevating properties when used therapeutically. Noradrenaline and potassium chloride induced concentration‐dependent vasoconstrictions in both vessel types but the basal tension, maximum tension, and the ‐log concentration producing half‐maximal response (pEC50) were altered in the presence of 0·1 or 20 U ml−1 EPO. The thromboxane A2 receptor agonist U46619 induced a constriction of the renal arcuate arteries which was enhanced by EPO at 20 U ml−1, from 1·68 ± 0·34 to 2·64 ± 0·39 mN mm−1 (P < 0·01), but which was unchanged by NG‐nitro‐L‐arginine methyl ester (10−4 m). Serotonin (10−9‐10−5 M) caused a concentration‐related vasoconstriction in renal arcuate arteries which was shifted to the right in the time control study (P < 0·001) but this was abolished by both 0·1 and 20 U ml−1 of EPO. Acetylcholine induced a relaxation of precontracted mesenteric arteries, by 95·4 ± 1·64% with an EC50 of 7·08 ± 0·08 M which was reduced (P < 0·001) by 20 U ml−1 EPO to 81·7 ± 3·56% and 6·10 ± 0·11 M, respectively. The sodium nitroprusside‐induced relaxations were unaffected by EPO. The acetylcholine‐mediated relaxations in renal arcuate arteries were unchanged by EPO. Bradykinin‐induced relaxations in mesenteric and renal arcuate arteries were unaffected by both EPO concentrations. Together these data showed that EPO over a large concentration range had only minor effects on basal tension and the vascular responsiveness of both mesenteric and renal arcuate arteries. The mechanism whereby EPO causes a chronic elevation in blood pressure is unlikely to be due to acute interactions with agonist‐mediated responses.
Geoscientific Model Development Description and evaluation of GMXe : a new aerosol submodel for global simulations ( v 1 )

We present a new aerosol microphysics and gas aerosol partitioning submodel (Global Modal-aerosol eXtension, GMXe) implemented within the ECHAM/MESSy Atmospheric Chemistry model (EMAC, version 1.8). The submodel is computationally efficient and is suitable for medium to long term simulations with global and regional models. The aerosol size distribution is treated using 7 log-normal modes and has the same microphysical core as the M7 submodel (Vignati et al., 2004). The main developments in this work are: (i) the extension of the aerosol emission routines and the M7 microphysics, so that an increased (and variable) number of aerosol species can be treated (new species include sodium and chloride, and potentially magnesium, calcium, and potassium), (ii) the coupling of the aerosol microphysics to a choice of treatments of gas/aerosol partitioning to allow the treatment of semi-volatile aerosol, and, (iii) the implementation and evaluation of the developed submodel within the EMAC model of atmospheric chemistry. Simulated concentrations of black carbon, particulate organic matter, dust, sea spray, sulfate and ammonium aerosol are shown to be in good agreement with observations (for all species at least 40% of modeled values are within a factor of 2 of the observations). The distribution of nitrate aerosol is compared to observations in both clean and polluted regions. Correspondence to: K. J. Pringle (kirsty.pringle@mpic.de) Concentrations in polluted continental regions are simulated quite well, but there is a general tendency to overestimate nitrate, particularly in coastal regions (geometric mean of modelled values/geometric mean of observed data ≈2). In all regions considered more than 40% of nitrate concentrations are within a factor of two of the observations. Marine nitrate concentrations are well captured with 96% of modeled values within a factor of 2 of the observations.
Distinctive microbial ecology and biokinetics of autotrophic ammonia and nitrite oxidation in a partial nitrification bioreactor

Biological nitrogen removal (BNR) based on partial nitrification and denitrification via nitrite is a cost‐effective alternate to conventional nitrification and denitrification (via nitrate). The goal of this study was to investigate the microbial ecology, biokinetics, and stability of partial nitrification. Stable long‐term partial nitrification resulting in 82.1 ± 17.2% ammonia oxidation, primarily to nitrite (77.3 ± 19.5% of the ammonia oxidized) was achieved in a lab‐scale bioreactor by operation at a pH, dissolved oxygen and solids retention time of 7.5 ± 0.1, 1.54 ± 0.87 mg O2/L, and 3.0 days, respectively. Bioreactor ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) populations were most closely related to Nitrosomonas europaea and Nitrobacter spp. , respectively. The AOB population fraction varied in the range 61 ± 45% and was much higher than the NOB fraction, 0.71 ± 1.1%. Using direct measures of bacterial concentrations in conjunction with independent activity measures and mass balances, the maximum specific growth rate (µmax), specific decay (b) and observed biomass yield coefficients (Yobs) for AOB were 1.08 ± 1.03 day−1, 0.32 ± 0.34 day−1, and 0.15 ± 0.06 mg biomass COD/mg N oxidized, respectively. Corresponding µmax, b, and Yobs values for NOB were 2.6 ± 2.05 day−1, 1.7 ± 1.9 day−1, and 0.04 ± 0.02 mg biomass COD/mg N oxidized, respectively. The results of this study demonstrate that the highly selective partial nitrification operating conditions enriched for a narrow diversity of rapidly growing AOB and NOB populations unlike conventional BNR reactors, which host a broader diversity of nitrifying bacteria. Further, direct measures of microbial abundance enabled not only elucidation of mixed community microbial ecology but also estimation of key engineering parameters describing bioreactor systems supporting these communities. Biotechnol. Bioeng. 2008;100: 1078–1087. © 2008 Wiley Periodicals, Inc.
Revised International Staging System for Multiple Myeloma: A Report From International Myeloma Working Group.

PURPOSE The clinical outcome of multiple myeloma (MM) is heterogeneous. A simple and reliable tool is needed to stratify patients with MM. We combined the International Staging System (ISS) with chromosomal abnormalities (CA) detected by interphase fluorescent in situ hybridization after CD138 plasma cell purification and serum lactate dehydrogenase (LDH) to evaluate their prognostic value in newly diagnosed MM (NDMM). PATIENTS AND METHODS Clinical and laboratory data from 4,445 patients with NDMM enrolled onto 11 international trials were pooled together. The K-adaptive partitioning algorithm was used to define the most appropriate subgroups with homogeneous survival. RESULTS ISS, CA, and LDH data were simultaneously available in 3,060 of 4,445 patients. We defined the following three groups: revised ISS (R-ISS) I (n = 871), including ISS stage I (serum β2-microglobulin level < 3.5 mg/L and serum albumin level ≥ 3.5 g/dL), no high-risk CA [del(17p) and/or t(4;14) and/or t(14;16)], and normal LDH level (less than the upper limit of normal range); R-ISS III (n = 295), including ISS stage III (serum β2-microglobulin level > 5.5 mg/L) and high-risk CA or high LDH level; and R-ISS II (n = 1,894), including all the other possible combinations. At a median follow-up of 46 months, the 5-year OS rate was 82% in the R-ISS I, 62% in the R-ISS II, and 40% in the R-ISS III groups; the 5-year PFS rates were 55%, 36%, and 24%, respectively. CONCLUSION The R-ISS is a simple and powerful prognostic staging system, and we recommend its use in future clinical studies to stratify patients with NDMM effectively with respect to the relative risk to their survival.
Oral activity of a nature-derived cyclic peptide for the treatment of multiple sclerosis

Significance Multiple sclerosis (MS) imposes substantial economic burdens on patients, their families, and society. Until now, there are few therapies available, but often unattractive parenteral application or severe side effects are serious issues. This study highlights the use of circular peptides as orally active T-cell-specific immunosuppressive therapeutics against the MS model experimental autoimmune encephalomyelitis, without inducing major adverse effects. Our work provides a proof of principle that nature-derived cyclic peptides serve as oral active therapeutics, utilizing their intrinsic bioactivity and stable three-dimensional structure. Cyclotides are considered a combinatorial peptide library and they can be anticipated to complement the existing collections of natural products that are used in drug discovery. Multiple sclerosis (MS) is the most common autoimmune disease affecting the central nervous system. It is characterized by auto-reactive T cells that induce demyelination and neuronal degradation. Treatment options are still limited and several MS medications need to be administered by parenteral application but are modestly effective. Oral active drugs such as fingolimod have been weighed down by safety concerns. Consequently, there is a demand for novel, especially orally active therapeutics. Nature offers an abundance of compounds for drug discovery. Recently, the circular plant peptide kalata B1 was shown to silence T-cell proliferation in vitro in an IL-2–dependent mechanism. Owing to this promising effect, we aimed to determine in vivo activity of the cyclotide [T20K]kalata B1 using the MS mouse model experimental autoimmune encephalomyelitis (EAE). Treatment of mice with the cyclotide resulted in a significant delay and diminished symptoms of EAE by oral administration. Cyclotide application substantially impeded disease progression and did not exhibit adverse effects. Inhibition of lymphocyte proliferation and the reduction of proinflammatory cytokines, in particular IL-2, distinguish the cyclotide from other marketed drugs. Considering their stable structural topology and oral activity, cyclotides are candidates as peptide therapeutics for pharmaceutical drug development for treatment of T-cell-mediated disorders.