Identification of endocannabinoid system-modulating N-alkylamides from Heliopsis helianthoides var. scabra and Lepidium meyenii.

The discovery of the interaction of plant-derived N-alkylamides (NAAs) and the mammalian endocannabinoid system (ECS) and the existence of a plant endogenous N-acylethanolamine signaling system have led to the re-evaluation of this group of compounds. Herein, the isolation of seven NAAs and the assessment of their effects on major protein targets in the ECS network are reported. Four NAAs, octadeca-2E,4E,8E,10Z,14Z-pentaene-12-ynoic acid isobutylamide (1), octadeca-2E,4E,8E,10Z,14Z-pentaene-12-ynoic acid 2'-methylbutylamide (2), hexadeca-2E,4E,9Z-triene-12,14-diynoic acid isobutylamide (3), and hexadeca-2E,4E,9,12-tetraenoic acid 2'-methylbutylamide (4), were identified from Heliopsis helianthoides var. scabra. Compounds 2-4 are new natural products, while 1 was isolated for the first time from this species. The previously described macamides, N-(3-methoxybenzyl)-(9Z,12Z,15Z)-octadecatrienamide (5), N-benzyl-(9Z,12Z,15Z)-octadecatrienamide (6), and N-benzyl-(9Z,12Z)-octadecadienamide (7), were isolated from Lepidium meyenii (Maca). N-Methylbutylamide 4 and N-benzylamide 7 showed submicromolar and selective binding affinities for the cannabinoid CB1 receptor (Ki values of 0.31 and 0.48 μM, respectively). Notably, compound 7 also exhibited weak fatty acid amide hydrolase (FAAH) inhibition (IC50 = 4 μM) and a potent inhibition of anandamide cellular uptake (IC50 = 0.67 μM) that was stronger than the inhibition obtained with the controls OMDM-2 and UCM707. The pronounced ECS polypharmacology of compound 7 highlights the potential involvement of the arachidonoyl-mimicking 9Z,12Z double-bond system in the linoleoyl group for the overall cannabimimetic action of NAAs. This study provides additional strong evidence of the endocannabinoid substrate mimicking of plant-derived NAAs and uncovers a direct and indirect cannabimimetic action of the Peruvian Maca root.

Identification of maltreatment type in children with disabilities using the National Child Abuse and Neglect Data System (NCANDS)

This study was a retrospective design and used secondary data from the National Child Abuse and Neglect Data System (NCANDS), provided by the National Data Archive on Child Abuse and Neglect Family Life Development Center administered by Cornell University. The dataset contained information for the year 2005 on children from birth to 18 years of age. Child abuse and neglect for disabled children, was evaluated in-depth in the present study. Descriptive and statistical analysis was performed using the children with and without disabilities. It was found that children with disabilities have a lower rate of substantiation that likely indicates the interference of reporting due to their handicap. The results of this research demonstrate the important need to teach professionals and laypersons alike on how to recognize and substantiate abuse among disabled children.^

A Radio Frequency Identification System for accurate indoor localization

In this paper we present a novel Radio Frequency Identification (RFID) system for accurate indoor localization. The system is composed of a standard Ultra High Frequency (UHF), ISO-18006C compliant RFID reader, a large set of standard passive RFID tags whose locations are known, and a newly developed tag-like RFID component that is attached to the items that need to be localized. The new semi-passive component, referred to as sensatag (sense-a-tag), has a dual functionality wherein it can sense the communication between the reader and standard tags which are in its proximity, and also communicate with the reader like standard tags using backscatter modulation. Based on the information conveyed by the sensatags to the reader, localization algorithms based on binary sensor principles can be developed. We present results from real measurements that show the accuracy of the proposed system.

Computational Methods for Identification of Vibrating Structures

System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system" [1]. In the context of civil engineering, the system refers to a large scale structure such as a building, bridge, or an offshore structure, and identification mostly involves the determination of modal parameters (the natural frequencies, damping ratios, and mode shapes). This paper presents some modal identification results obtained using a state-of-the-art time domain system identification method (data-driven stochastic subspace algorithms [2]) applied to the output-only data measured in a steel arch bridge. First, a three dimensional finite element model was developed for the numerical analysis of the structure using ANSYS. Modal analysis was carried out and modal parameters were extracted in the frequency range of interest, 0-10 Hz. The results obtained from the finite element modal analysis were used to determine the location of the sensors. After that, ambient vibration tests were conducted during April 23-24, 2009. The response of the structure was measured using eight accelerometers. Two stations of three sensors were formed (triaxial stations). These sensors were held stationary for reference during the test. The two remaining sensors were placed at the different measurement points along the bridge deck, in which only vertical and transversal measurements were conducted (biaxial stations). Point estimate and interval estimate have been carried out in the state space model using these ambient vibration measurements. In the case of parametric models (like state space), the dynamic behaviour of a system is described using mathematical models. Then, mathematical relationships can be established between modal parameters and estimated point parameters (thus, it is common to use experimental modal analysis as a synonym for system identification). Stable modal parameters are found using a stabilization diagram. Furthermore, this paper proposes a method for assessing the precision of estimates of the parameters of state-space models (confidence interval). This approach employs the nonparametric bootstrap procedure [3] and is applied to subspace parameter estimation algorithm. Using bootstrap results, a plot similar to a stabilization diagram is developed. These graphics differentiate system modes from spurious noise modes for a given order system. Additionally, using the modal assurance criterion, the experimental modes obtained have been compared with those evaluated from a finite element analysis. A quite good agreement between numerical and experimental results is observed.

Patrol team language identification system for DARPA RATS P1 evaluation

This paper describes the language identification (LID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We show that techniques originally developed for LID on telephone speech (e.g., for the NIST language recognition evaluations) remain effective on the noisy RATS data, provided that careful consideration is applied when designing the training and development sets. In addition, we show significant improvements from the use of Wiener filtering, neural network based and language dependent i-vector modeling, and fusion.

Characteristic study, its identification and self-tuned approach to control hydro-power plants

The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

Identification and analysis of a nickel-inducible cation diffusion facilitator-NiCoT combined system in Rhizobium leguminosarum bv. viciae

Nickel, like other transition metals, can be toxic to cells even at moderate concentration (low microM range) by displacing essential metals from their native binding sites or by generating reactive oxygen species that cause oxidative DNA damage. For this reason, cells have evolved mechanisms to deal with excess nickel. Efflux systems include members of the Resistance-Nodulation-cell Division (RND) protein family, P-type ATPases, cation diffusion facilitators (CDF) and other resistance factors. Nickel-specific exporters have been characterized in Cupravidus metallidurans, Helicobacter pylori, Achromobacter xylosoxidans, Serratia marcenses and Escherichia coli.

Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.

Low-Cost Radar-Based Target Identification Prototype using an Expert System

Smart and green cities are hot topics in current research because people are becoming more conscious about their impact on the environment and the sustainability of their cities as the population increases. Many researchers are searching for mechanisms that can reduce power consumption and pollution in the city environment. This paper addresses the issue of public lighting and how it can be improved in order to achieve a more energy efficient city. This work is focused on making the process of turning the streetlights on and off more intelligent so that they consume less power and cause less light pollution. The proposed solution is comprised of a radar device and an expert system implemented on a low-cost platform based on a DSP. By analyzing the radar echo in both the frequency and time domains, the system is able to detect and identify objects moving in front of it. This information is used to decide whether or not the streetlight should be turned on. Experimental results show that the proposed system can provide hit rates over 80%, promising a good performance. In addition, the proposed solution could be useful in kind of other applications such as intelligent security and surveillance systems and home automation.

Identification of voting systems for the identification of preferences in public participation. Case Study: application of the Borda Count system for collective decision making at the Salonga National Park in the Democratic Republic of Congo.

Abstract:The aim of this paper is to review the literature on voting systems based on Condorcet and Borda. We compared and classified them. Also we referred to some strengths and weaknesses of voting systems and finally in a case study, we made use of the Borda voting system for collective decision making in the Salonga National Park in the Democratic Republic of Congo. Resumen: el objetivo de este trabajo es hacer una revisión bibliográfica de los sistemas de votación basados en Condorcet y Borda. Se ha comparado y clasificado los mismos. Así mismo se ha hecho referencia a algunas debilidades y fortalezas de los sistemas de votación y por último en un caso de estudio, se ha hecho uso del sistema de votación de Borda para la toma de decisión colectiva en el Parque Nacional de Salonga en la República Democrática del Congo.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Identification of GIT1/Cat-1 as a substrate molecule of protein tyrosine phosphatase ζ/β by the yeast substrate-trapping system

We used a genetic method, the yeast substrate-trapping system, to identify substrates for protein tyrosine phosphatases ζ (PTPζ/RPTPβ). This method is based on the yeast two-hybrid system, with two essential modifications: conditional expression of protein tyrosine kinase v-src (active src) to tyrosine-phosphorylate the prey proteins and screening by using a substrate-trap mutant of PTPζ (PTPζ-D1902A) as bait. By using this system, several substrate candidates for PTPζ were isolated. Among them, GIT1/Cat-1 (G protein-coupled receptor kinase-interactor 1/Cool-associated, tyrosine-phosphorylated 1) was examined further. GIT1/Cat-1 bound to PTPζ-D1902A dependent on the substrate tyrosine phosphorylation. Tyrosine-phosphorylated GIT1/Cat-1 was dephosphorylated by PTPζ in vitro. Immunoprecipitation experiments indicated that PTPζ-D1902A and GIT1/Cat-1 form a stable complex also in mammalian cells. Immunohistochemical analyses revealed that PTPζ and GIT1/Cat-1 were colocalized in the processes of pyramidal cells in the hippocampus and neocortex in rat brain. Subcellular colocalization was further verified in the growth cones of mossy fibers from pontine explants and in the ruffling membranes and processes of B103 neuroblastoma cells. Moreover, pleiotrophin, a ligand for PTPζ, increased tyrosine phosphorylation of GIT1/Cat-1 in B103 cells. All these results indicate that GIT1/Cat-1 is a substrate molecule of PTPζ.

Identification of a virulence locus encoding a second type III secretion system in Salmonella typhimurium.

Mapping the insertion points of 16 signature-tagged transposon mutants on the Salmonella typhimurium chromosome led to the identification of a 40-kb virulence gene cluster at minute 30.7. This locus is conserved among all other Salmonella species examined but is not present in a variety of other pathogenic bacteria or in Escherichia coli K-12. Nucleotide sequencing of a portion of this locus revealed 11 open reading frames whose predicted proteins encode components of a type III secretion system. To distinguish between this and the type III secretion system encoded by the inv/spa invasion locus known to reside on a pathogenicity island, we refer to the inv/spa locus as Salmonella pathogenicity island (SPI) 1 and the new locus as SPI2. SPI2 has a lower G+C content than that of the remainder of the Salmonella genome and is flanked by genes whose products share greater than 90% identity with those of the E. coli ydhE and pykF genes. Thus SPI2 was probably acquired horizontally by insertion into a region corresponding to that between the ydhE and pykF genes of E. coli. Virulence studies of SPI2 mutants have shown them to be attenuated by at least five orders of magnitude compared with the wild-type strain after oral or intraperitoneal inoculation of mice.

Identification of a second homolog of N-ethylmaleimide-sensitive fusion protein that is expressed in the nervous system and secretory tissues of Drosophila.

N-Ethylmaleimide-sensitive fusion protein (NSF) is an ATPase known to have an essential role in intracellular membrane transport events. Recently, cDNA clones encoding a Drosophila melanogaster homolog of this protein, named dNSF, were characterized and found to be expressed in the nervous system. We now report the identification of a second homolog of NSF, called dNSF-2 within this species and report evidence that this ubiquitous and widely utilized fusion protein belongs to a multigene family. The predicted amino acid sequence of dNSF-2 is 84.5% identical to dNSF (hereafter named dNSF-1), 59% identical to NSF from Chinese hamster, and 38.5% identical to the yeast homolog SEC18. The highest similarity was found in a region of dNSF-2 containing one of two ATP-binding sites; this region is most similar to members of a superfamily of ATPases. dNSF-2 is localized to a region between bands 87F12 and 88A3 on chromosome 3, and in situ hybridization techniques revealed expression in the nervous system during embryogenesis and in several imaginal discs and secretory structures in the larvae. Developmental modulation of dNSF-2 expression suggests that quantitative changes in the secretory apparatus are important in histogenesis.

Hybrid convex combinations for IIR system identification.

The low complexity of IIR adaptive filters (AFs) is specially appealing to realtime applications but some drawbacks have been preventing their widespread use so far. For gradient based IIR AFs, adverse operational conditions cause convergence problems in system identification scenarios: underdamped and clustered poles, undermodelling or non-white input signals lead to error surfaces where the adaptation nearly stops on large plateaus or get stuck at sub-optimal local minima that can not be identified as such a priori. Furthermore, the non-stationarity in the input regressor brought by the filter recursivity and the approximations made by the update rules of the stochastic gradient algorithms constrain the learning step size to small values, causing slow convergence. In this work, we propose IIR performance enhancement strategies based on hybrid combinations of AFs that achieve higher convergence rates than ordinary IIR AFs while keeping the stability.