SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Botanical drugs, synergy, and network pharmacology: forth and back to intelligent mixtures

For centuries the science of pharmacognosy has dominated rational drug development until it was gradually substituted by target-based drug discovery in the last fifty years. Pharmacognosy stems from the different systems of traditional herbal medicine and its "reverse pharmacology" approach has led to the discovery of numerous pharmacologically active molecules and drug leads for humankind. But do botanical drugs also provide effective mixtures? Nature has evolved distinct strategies to modulate biological processes, either by selectively targeting biological macromolecules or by creating molecular promiscuity or polypharmacology (one molecule binds to different targets). Widely claimed to be superior over monosubstances, mixtures of bioactive compounds in botanical drugs allegedly exert synergistic therapeutic effects. Despite evolutionary clues to molecular synergism in nature, sound experimental data are still widely lacking to support this assumption. In this short review, the emerging concept of network pharmacology is highlighted, and the importance of studying ligand-target networks for botanical drugs is emphasized. Furthermore, problems associated with studying mixtures of molecules with distinctly different pharmacodynamic properties are addressed. It is concluded that a better understanding of the polypharmacology and potential network pharmacology of botanical drugs is fundamental in the ongoing rationalization of phytotherapy.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.

EVALUATION OF INTELLIGENT COMPACTION CONTROL IN THE M-189 RECONSTRUCTION PROJECT AT IRON RIVER, MICHIGAN

This research evaluated an Intelligent Compaction (IC) unit on the M-189 highway reconstruction project at Iron River, Michigan. The results from the IC unit were compared to several traditional compaction measurement devices including Nuclear Density Gauge (NDG), Geogauge, Light Weight Deflectometer (LWD), Dynamic Cone Penetrometer (DCP), and Modified Clegg Hammer (MCH). The research collected point measurements data on a test section in which 30 test locations on the final Class II sand base layer and the 22A gravel layer. These point measurements were compared with the IC measurements (ICMVs) on a point-to-point basis through a linear regression analysis. Poor correlations were obtained among different measurements points using simple regression analysis. When comparing the ICMV to the compaction measurements points. Factors attributing to the weak correlation include soil heterogeneity, variation in IC roller operation parameters, in-place moisture content, the narrow range of the compaction devices measurement ranges and support conditions of the support layers. After incorporating some of the affecting factors into a multiple regression analysis, the strength of correlation significantly improved, especially on the stiffer gravel layer. Measurements were also studied from an overall distribution perspective in terms of average, measurement range, standard deviation, and coefficient of variance. Based on data analysis, on-site project observation and literature review, conclusions were made on how IC performed in regards to compaction control on the M-189 reconstruction project.

L'évolution du système consonantique des langues cangin

The Cangin languages are classified as an own subgroup of the Atlantic languages. Evidence for their common origin can be given by the comparative method. By means of the systematic grammatical comparison of different languages this method aims at the reconstruction of a hypothetic proto-language and allows to draw hypothesises on their diachronic linguistic development. This paper concentrates on the evolution of the consonant system of the Cangin languages.

Intelligent Virtual Patients for Training Clinical Skills

The article presents the design process of intelligent virtual human patients that are used for the enhancement of clinical skills. The description covers the development from conceptualization and character creation to technical components and the application in clinical research and training. The aim is to create believable social interactions with virtual agents that help the clinician to develop skills in symptom and ability assessment, diagnosis, interview techniques and interpersonal communication. The virtual patient fulfills the requirements of a standardized patient producing consistent, reliable and valid interactions in portraying symptoms and behaviour related to a specific clinical condition.

Semantic Methods for Intelligent Distributed Design Environments

Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.

La dénervation rénale unilatérale et le système kallikréine-bradykinine rénal chez le rat

But de l’étude L’effet antihypertenseur de la dénervation rénale chez les patients hypertendus s’explique partiellement par une augmentation de la natriurèse tubulaire. Pour étudier une contribution possible du système kallikréine-kinines (SKK) à cette natriurèse dans le rat, nous avons dosé dans le plasma et dans les tissus l’activité de la kallikréine (AK) et la concentration de la bradykinine (BK). Méthodes Pour AK, nous avons adapté et validé un essai enzymatique qui libère la para-nitroaniline à partir du tripeptide H-D-Pro-Phe-Arg-pNA ; les coefficients de variation (CV) intra-essai et inter-essai étaient inférieurs à 8 % pour AK plasmatique et tissulaire (plasma n = 6 et 13, tissu n = 4). La linéarité d’une série de dilutions confirmait la spécificité de l’essai. Le dosage de BK tissulaire se basait sur une méthode établie pour le plasma : tissus étaient homogénéisés et BK extraite et isolée par éthanol et HPLC, et finalement quantifiée par radio-immunoessai. Les CV intra- et inter-essai pour BK étaient 18 % dans le plasma (n = 8 et n = 35) et inférieurs à 16 % dans différents tissus (n = 5–8). Résultats Chez le rat mâle Wistar (n = 3), la BK plasmatique était de 8,2 ± 6,6 fmol/mL (M ± SD) et la BK tissulaire (fmol/g) variait, pour les 14 organes testés, de 14 ± 3 pour le cerveau à 521 ± 315 pour la glande sous-maxillaire. Six jours après dénervation rénale gauche, la BK rénale gauche (89 ± 9) n’était pas différente comparée à la BK rénale droite (75 ± 23). De même, l’AK était identique dans les deux reins (gauche 18,0 ± 1,5, droit 15,8 ± 1,4 μkat/g). Conclusion Un effet éventuel de la dénervation rénale unilatéral sur le SKK rénal devrait donc être bilatéral.

Toward global prevention of sexually transmitted infections (STIs): The need for STI vaccines.

An estimated 499 million curable sexually transmitted infections (STIs; gonorrhea, chlamydia, syphilis, and trichomoniasis) occurred globally in 2008. In addition, well over 500 million people are estimated to have a viral STI such as herpes simplex virus type 2 (HSV-2) or human papillomavirus (HPV) at any point in time. STIs result in a large global burden of sexual, reproductive, and maternal-child health consequences, including genital symptoms, pregnancy complications, cancer, infertility, and enhanced HIV transmission, as well as important psychosocial consequences and financial costs. STI control strategies based primarily on behavioral primary prevention and STI case management have had clear successes, but gains have not been universal. Current STI control is hampered or threatened by several behavioral, biological, and implementation challenges, including a large proportion of asymptomatic infections, lack of feasible diagnostic tests globally, antimicrobial resistance, repeat infections, and barriers to intervention access, availability, and scale-up. Vaccines against HPV and hepatitis B virus offer a new paradigm for STI control. Challenges to existing STI prevention efforts provide important reasons for working toward additional STI vaccines. We summarize the global epidemiology of STIs and STI-associated complications, examine challenges to existing STI prevention efforts, and discuss the need for new STI vaccines for future prevention efforts.