Identification and expression analysis of two Wnt4 genes in the spotted scat ( Scatophagus argus )

Background: WNT4 is a protein that plays a crucial role in ovarian differentiation and development in mammals, with a relatively well understood function in mammalian gonadal differentiation. The role of Wnt4 in teleost fish; however, remains unclear. In the present study, cDNAs of Wnt4a and Wnt4b were cloned and characterized in the spotted scat. The expression patterns of two Wnt4 genes in the gonads at different stages of development and in fish after treatment with 17α-methyltestosterone (MT) were investigated. Results: The tissue distribution showed that Wnt4a was expressed in various tissues, including the gonads, gills, spleen, brain, and fin. Interestingly, Wnt4b not only was expressed in the gills, brain, and spleen, but also was obviously expressed in the ovary. During gonad development, Wnt4a was highly expressed in the testis at stage I and Wnt4b was mainly expressed in the ovary at stages II–III. After MT treatment, the mRNA expression of Wnt4a increased significantly up to 40 d, and the transcript level of Wnt4b decreased at 20 d. Conclusions: These results suggest that Wnt4a may be involved in gonad development and plays a role in the process of spermatogonial proliferation. Our results also demonstrate that Wnt4b is not only expressed in the nervous system, but also in the ovary and it may be involved in ovary development of the spotted scat.

Design and construction of a two dimensional duct equipped with a wave generator and a variable coastal slope and an ocean wave energy conversion system (OWC)

The aims of this thesis were evaluation the type of wave channel, wave current, and effect of some parameters on them and identification and comparison between types of wave maker in laboratory situations. In this study, designing and making of two dimension channels (flume) and wave maker for experiment son the marine buoy, marine building and energy conversion systems were also investigated. In current research, the physical relation between pump and pumpage and the designing of current making in flume were evaluated. The related calculation for steel building, channels beside glasses and also equations of wave maker plate movement, power of motor and absorb wave(co astal slope) were calculated. In continue of this study, the servo motor was designed and applied for moving of wave maker’s plate. One Ball Screw Leaner was used for having better movement mechanisms of equipment and convert of the around movement to linear movement. The Programmable Logic Controller (PLC) was also used for control of wave maker system. The studies were explained type of ocean energies and energy conversion systems. In another part of this research, the systems of energy resistance in special way of Oscillating Water Column (OWC) were explained and one sample model was designed and applied in hydrolic channel at the Sheikh Bahaii building in Azad University, Science and Research Branch. The dimensions of designed flume was considered at 16 1.98 0. 57 m which had ability to provide regular waves as well as irregular waves with little changing on the control system. The ability of making waves was evaluated in our designed channel and the results were showed that all of the calculation in designed flume was correct. The mean of error between our results and theory calculation was conducted 7%, which was showed the well result in this situation. With evaluating of designed OWC model and considering of changes in the some part of system, one bigger sample of this model can be used for designing the energy conversion system model. The obtained results showed that the best form for chamber in exit position of system, were zero degree (0) in angle for moving below part, forty and five (45) degree in front wall of system and the moving forward of front wall keep in two times of height of wave.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

"Last-Mile" preparation for a potential disaster - Interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of smallscale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socioeconomic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity. © Author(s) 2009.

Identification des grands utilisateurs de soins de santé chez les patients souffrant de la douleur chronique non cancéreuse et suivis en soins de première ligne

Contexte: La douleur chronique non cancéreuse (DCNC) génère des retombées économiques et sociétales importantes. L’identification des patients à risque élevé d’être de grands utilisateurs de soins de santé pourrait être d’une grande utilité; en améliorant leur prise en charge, il serait éventuellement possible de réduire leurs coûts de soins de santé. Objectif: Identifier les facteurs prédictifs bio-psycho-sociaux des grands utilisateurs de soins de santé chez les patients souffrant de DCNC et suivis en soins de première ligne. Méthodologie: Des patients souffrant d’une DCNC modérée à sévère depuis au moins six mois et bénéficiant une ordonnance valide d’un analgésique par un médecin de famille ont été recrutés dans des pharmacies communautaires du territoire du Réseau universitaire intégré de santé (RUIS), de l’Université de Montréal entre Mai 2009 et Janvier 2010. Ce dernier est composé des six régions suivantes : Mauricie et centre du Québec, Laval, Montréal, Laurentides, Lanaudière et Montérégie. Les caractéristiques bio-psycho-sociales des participants ont été documentées à l’aide d’un questionnaire écrit et d’une entrevue téléphonique au moment du recrutement. Les coûts directs de santé ont été estimés à partir des soins et des services de santé reçus au cours de l’année précédant et suivant le recrutement et identifiés à partir de la base de données de la Régie d’Assurance maladie du Québec, RAMQ (assureur publique de la province du Québec). Ces coûts incluaient ceux des hospitalisations reliées à la douleur, des visites à l’urgence, des soins ambulatoires et de la médication prescrite pour le traitement de la douleur et la gestion des effets secondaires des analgésiques. Les grands utilisateurs des soins de santé ont été définis comme étant ceux faisant partie du quartile le plus élevé de coûts directs annuels en soins de santé dans l’année suivant le recrutement. Des modèles de régression logistique multivariés et le critère d’information d’Akaike ont permis d’identifier les facteurs prédictifs des coûts directs élevés en soins de santé. Résultats: Le coût direct annuel médian en soins de santé chez les grands utilisateurs de soins de santé (63 patients) était de 7 627 CAD et de 1 554 CAD pour les utilisateurs réguliers (188 patients). Le modèle prédictif final du risque d’être un grand utilisateur de soins de santé incluait la douleur localisée au niveau des membres inférieurs (OR = 3,03; 95% CI: 1,20 - 7,65), la réduction de la capacité fonctionnelle liée à la douleur (OR = 1,24; 95% CI: 1,03 - 1,48) et les coûts directs en soins de santé dans l’année précédente (OR = 17,67; 95% CI: 7,90 - 39,48). Les variables «sexe», «comorbidité», «dépression» et «attitude envers la guérison médicale» étaient également retenues dans le modèle prédictif final. Conclusion: Les patients souffrant d’une DCNC au niveau des membres inférieurs et présentant une détérioration de la capacité fonctionnelle liée à la douleur comptent parmi ceux les plus susceptibles d’être de grands utilisateurs de soins et de services. Le coût direct en soins de santé dans l’année précédente était également un facteur prédictif important. Améliorer la prise en charge chez cette catégorie de patients pourrait influencer favorablement leur état de santé et par conséquent les coûts assumés par le système de santé.

Lineup identification accuracy: the effects of alcohol, target presence, confidence ratings, and response time

Despite the intoxication of many eyewitnesses at crime scenes, only four published studies to date have investigated the effects of alcohol intoxication on eyewitness identification performance. While one found intoxication significantly increased false identification rates from target absent showups, three found no such effect using the more traditional lineup procedure. The present study sought to further explore the effects of alcohol intoxication on identification performance and examine whether accurate decisions from intoxicated witnesses could be postdicted by confidence and response times. One hundred and twenty participants engaged in a study examining the effects of intoxication (control, placebo, and mild intoxication) and target presence on identification performance. Participants viewed a simultaneous lineup one week after watching a mock crime video of a man attempting to steal cars. Ethanol intoxication (0.6 ml/kg) was found to make no significant difference to identification accuracy and such identifications from intoxicated individuals were made no less confidently or slowly than those from sober witnesses. These results are discussed with respect to the previous research examining intoxicated witness identification accuracy and the misconceptions the criminal justice system holds about the accuracy of such witnesses.

Voices of nigerian women survivors of trafficking held in italian centres for identification and expulsion

Department of Equal Opportunities; Presidency of the Council of Ministries; Province of Rome (metropolitan area)

A Performance Measurement System to Manage CEN Operations, Evolution and Innovation

Part 16: Performance Measurement Systems

The identification and differentiation of the Candida parapsilosis complex species by polymerase chain reaction-restriction fragment length polymorphism of the internal transcribed spacer region of the rDNA

Currently, it is accepted that there are three species that were formerly grouped under Candida parapsilosis : C. parapsilosis sensu stricto, Candida orthopsilosis , and Candida metapsilosis . In fact, the antifungal susceptibility profiles and distinct virulence attributes demonstrate the differences in these nosocomial pathogens. An accurate, fast, and economical identification of fungal species has been the main goal in mycology. In the present study, we searched sequences that were available in the GenBank database in order to identify the complete sequence for the internal transcribed spacer (ITS)1-5.8S-ITS2 region, which is comprised of the forward and reverse primers ITS1 and ITS4. Subsequently, an in silico polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was performed to differentiate the C. parapsilosis complex species. Ninety-eight clinical isolates from patients with fungaemia were submitted for analysis, where 59 isolates were identified as C. parapsilosis sensu stricto, 37 were identified as C. orthopsilosis, and two were identified as C. metapsilosis. PCR-RFLP quickly and accurately identified C. parapsilosis complex species, making this method an alternative and routine identification system for use in clinical mycology laboratories.

Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb^-1.

In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.

The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.

We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10^-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.

Automatic identification of whole-part relations in Portuguese

Dissertação de Mestrado, Ciências da Linguagem, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2014

Application of dental morphological characteristics for medical-legal identification: sexual diagnosis in a portuguese population

Licenced under a Creative Commons Attribution 3.0.

Prevalence of Listeria species in some foods and their rapid identification

Purpose: To investigate the occurrence of Listeria spp., (particularly L. monocytogenes ), in different foods and to compare diagnostic tools for their identification at species level. Methods: Samples of high protein foods such as raw meats and meat products and including beef products, chicken, fish and camel milk were analysed for the presence of Listeria spp. The isolates were characterised by morphological and cultural analyses, and confirmed isolates were identified by protein profiling and verified using API Listeria system. Protein profiling by SDS-PAGE was also used to identify Listeria spp. Results: Out of 40 meat samples, 14 (35 %) samples were contaminated with Listeria spp., with the highest incidence (50 %) occurring in raw beef products and raw chicken. Protein profiling by SDSPAGE was used to identify Listeria spp. The results were verified with API Listeria system. Approximately 25 % of the identified isolates were Listeria seeligeri , Listeria welshimeri , and Listeria grayi (three positive samples), while 16.66 % of the isolates were Listeria monocytogenes (two positive samples); 16.6 % of the isolates were Listeria innocua (two positive samples), while 8.3 % of the isolates were Listeria ivanovii (one positive sample). Conclusion: High protein foods contain different types of Listeria species; whole-cell protein profiles and API Listeria system can help in the identification of Listeria at the species level.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Assessment of MALDI-TOF MS as Alternative Tool for Streptococcus suis Identification

The accuracy of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identifying Streptococcus suis isolates obtained from pigs, wild animals, and humans was evaluated using a PCR-based identification assay as the gold standard. In addition, MALDI-TOF MS was compared with the commercial multi-tests Rapid ID 32 STREP system. From the 129 S. suis isolates included in the study and identified by the molecular method, only 31 isolates (24.03%) had score values ≥2.300 and 79 isolates (61.24%) gave score values between 2.299 and 2.000. After updating the currently available S. suis MALDI Biotyper database with the spectra of three additional clinical isolates of serotypes 2, 7, and 9, most isolates had statistically significant higher score values (mean score: 2.65) than those obtained using the original database (mean score: 2.182). Considering the results of the present study, we suggest using a less restrictive threshold score of ≥2.000 for reliable species identification of S. suis. According to this cut-off value, a total of 125 S. suis isolates (96.9%) were correctly identified using the updated database. These data indicate an excellent performance of MALDI-TOF MS for the identification of S. suis.